WorldWideScience

Sample records for extreme load predictions

  1. Stochastic Extreme Load Predictions for Marine Structures

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher

    1999-01-01

    Development of rational design criteria for marine structures requires reliable estimates for the maximum wave-induced loads the structure may encounter during its operational lifetime. The paper discusses various methods for extreme value predictions taking into account the non-linearity of the ......Development of rational design criteria for marine structures requires reliable estimates for the maximum wave-induced loads the structure may encounter during its operational lifetime. The paper discusses various methods for extreme value predictions taking into account the non......-linearity of the waves and the response. As example the wave-induced bending moment in the ship hull girder is considered....

  2. Predicting the Extreme Loads on a Wind Turbine Considering Uncertainty in Airfoil Data

    DEFF Research Database (Denmark)

    Abdallah, Imad; Natarajan, Anand; Sørensen, John Dalsgaard

    2014-01-01

    The sources contributing to uncertainty in a wind turbine blade static airfoil data include wind tunnel testing, CFD calculations, 3D rotational corrections based on CFD or emprircal models, surface roughness corrections, Reynolds number corrections, expansion to the full 360-degree angle of attack...... range, validation by full scale measurements, and geometric distortions of the blade during manufacturing and under loading. In this paper a stochastic model of the static airfoil data is proposed to supplement the prediction of extreme loads effects for large wind turbines. It is shown...... that the uncertainty in airfoil data can have e significant impact on the prediction of extreme loads effects depending on the component, and the correlation along the span of the blade....

  3. Numerical tools to predict the environmental loads for offshore structures under extreme weather conditions

    Science.gov (United States)

    Wu, Yanling

    2018-05-01

    In this paper, the extreme waves were generated using the open source computational fluid dynamic (CFD) tools — OpenFOAM and Waves2FOAM — using linear and nonlinear NewWave input. They were used to conduct the numerical simulation of the wave impact process. Numerical tools based on first-order (with and without stretching) and second-order NewWave are investigated. The simulation to predict force loading for the offshore platform under the extreme weather condition is implemented and compared.

  4. Stochastic Procedures for Extreme Wave Load Predictions- Wave Bending Moment in Ships

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher

    2009-01-01

    A discussion of useful stochastic procedures for stochastic wave load problems is given, covering the range from slightly linear to strongly non-linear (bifurcation) problems. The methods are: Hermite transformation, Critical wave episodes and the First Order Reliability Method (FORM). The proced......). The procedures will be illustrated by results for the extreme vertical wave bending moment in ships....

  5. Extreme Value Predictions using Monte Carlo Simulations with Artificially Increased Load Spectrum

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher

    2011-01-01

    In the analysis of structures subjected to stationary stochastic load processes the mean out-crossing rate plays an important role as it can be used to determine the extreme value distribution of any response, usually assuming that the sequence of mean out-crossings can be modelled as a Poisson...... be scaled down to its actual value. In the present paper the usefulness of this approach is investigated, considering problems related to wave loads on marine structures. Here the load scale parameter is conveniently taken as the square of the significant wave height....... be found using the First Order Reliability Method (FORM). The FORM analysis also shows that the reliability index is strictly inversely proportional to the square root of the magnitude of the load spectrum, irrespectively of the non-linearity in the system. However, the FORM analysis only gives...

  6. Extreme Value Predictions for Wave- and Wind-induced Loads on Floating Offshore Wind Turbines using FORM

    DEFF Research Database (Denmark)

    Joensen, Sunvard; Jensen, Jørgen Juncher; Mansour, Alaa E.

    2007-01-01

    duration of the time domain simulations needed (typically 60-300s to cover the hy-drodynamic memory effects in the response) the calcu-lation of the mean out-crossing rates of a given response are very fast. Thus complicated non-linear effects can be included. The FORM analysis also identifies the most...... probable wave episodes leading to given re-sponses. As an example the motions of floating foundations for offshore wind turbines are analysed taking into consid-eration both the wave and wind induced loads and con-sidering different mooring systems. The possible large horizontal motions make it important...

  7. Global predictability of temperature extremes

    Science.gov (United States)

    Coughlan de Perez, Erin; van Aalst, Maarten; Bischiniotis, Konstantinos; Mason, Simon; Nissan, Hannah; Pappenberger, Florian; Stephens, Elisabeth; Zsoter, Ervin; van den Hurk, Bart

    2018-05-01

    Extreme temperatures are one of the leading causes of death and disease in both developed and developing countries, and heat extremes are projected to rise in many regions. To reduce risk, heatwave plans and cold weather plans have been effectively implemented around the world. However, much of the world’s population is not yet protected by such systems, including many data-scarce but also highly vulnerable regions. In this study, we assess at a global level where such systems have the potential to be effective at reducing risk from temperature extremes, characterizing (1) long-term average occurrence of heatwaves and coldwaves, (2) seasonality of these extremes, and (3) short-term predictability of these extreme events three to ten days in advance. Using both the NOAA and ECMWF weather forecast models, we develop global maps indicating a first approximation of the locations that are likely to benefit from the development of seasonal preparedness plans and/or short-term early warning systems for extreme temperature. The extratropics generally show both short-term skill as well as strong seasonality; in the tropics, most locations do also demonstrate one or both. In fact, almost 5 billion people live in regions that have seasonality and predictability of heatwaves and/or coldwaves. Climate adaptation investments in these regions can take advantage of seasonality and predictability to reduce risks to vulnerable populations.

  8. Committee VI.1. Extreme Hull Girder Loading

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher

    2000-01-01

    Committee Mandate. Evaluate and develop direct calculation procedures for extreme wawe loads on ship hull girders. Due consideration shall be given to stochastic and non-linear effects. The procedures shall be assessed by comparison with in-service experiences, model tests and more refined...

  9. Wind simulation for extreme and fatigue loads

    Energy Technology Data Exchange (ETDEWEB)

    Nielsen, M.; Larsen, G.C.; Mann, J.; Ott, S.; Hansen, K.S.; Pedersen, B.J.

    2004-01-01

    Measurements of atmospheric turbulence have been studied and found to deviate from a Gaussian process, in particular regarding the velocity increments over small time steps, where the tails of the pdf are exponential rather than Gaussian. Principles for extreme event counting and the occurrence of cascading events are presented. Empirical extreme statistics agree with Rices exceedence theory, when it is assumed that the velocity and its time derivative are independent. Prediction based on the assumption that the velocity is a Gaussian process underpredicts the rate of occurrence of extreme events by many orders of magnitude, mainly because the measured pdf is non-Gaussian. Methods for simulation of turbulent signals have been developed and their computational efficiency are considered. The methods are applicable for multiple processes with individual spectra and probability distributions. Non-Gaussian processes are simulated by the correlation-distortion method. Non-stationary processes are obtained by Bezier interpolation between a set of stationary simulations with identical random seeds. Simulation of systems with some signals available is enabled by conditional statistics. A versatile method for simulation of extreme events has been developed. This will generate gusts, velocity jumps, extreme velocity shears, and sudden changes of wind direction. Gusts may be prescribed with a specified ensemble average shape, and it is possible to detect the critical gust shape for a given construction. The problem is formulated as the variational problem of finding the most probable adjustment of a standard simulation of a stationary Gaussian process subject to relevant event conditions, which are formulated as linear combination of points in the realization. The method is generalized for multiple correlated series, multiple simultaneous conditions, and 3D fields of all velocity components. Generalization are presented for a single non-Gaussian process subject to relatively

  10. Wave induced extreme hull girder loads on containerships

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher; Pedersen, Preben Terndrup; Shi, Bill

    2009-01-01

    This paper provides simple but rational procedures for prediction of extreme wave – induced sectional hull girder forces with reasonable engineering accuracy. The procedures take into account main ship hull characteristics such as: length, breadth, draught, block coefficient, bow flare coefficient......, forward speed and hull flexibility. The vertical hull girder loads are evaluated for specific operational profiles. Firstly a quadratic strip theory is presented which can give separate predictions for the hogging and sagging bending moments and shear forces and for hull girder loads. Then this procedure...... is based on rational methods it can be applied for novel single hull ship types not presently covered by the rules of the classification societies or to account for specific operational profiles....

  11. Containment bellows testing under extreme loads

    International Nuclear Information System (INIS)

    Splezter, B.L.; Lambert, L.D.; Parks, M.B.

    1993-01-01

    Sandia National Laboratories (SNL) is conducting several research programs to help develop validated methods for the prediction of the ultimate pressure capacity, at elevated temperatures, of light water reactor (LWR) containment structures. To help understand the ultimate pressure of the entire containment pressure boundary, each component must be evaluated. The containment pressure boundary consists of the containment shell and many access, piping, and electrical penetrations. The focus of the current research program is to study the ultimate behavior of flexible metal bellows that are used at piping penetrations. Bellows are commonly used at piping penetrations in steel containments; however, they have very few applications in concrete (reinforced or prestressed) containments. The purpose of piping bellows is to provide a soft connection between the containment shell and the pipe are attached while maintaining the containment pressure boundary. In this way, piping loads caused by differential movement between the piping and the containment shell are minimized. SNL is conducting a test program to determine the leaktight capacity of containment bellows when subjected to postulated severe accident conditions. If the test results indicate that containment bellows could be a possible failure mode of the containment pressure boundary, then methods will be developed to predict the deformation, pressure, and temperature conditions that would likely cause a bellows failure. Results from the test program would be used to validate the prediction methods. This paper provides a description of the use and design of bellows in containment piping penetrations, the types of possible bellows loadings during a severe accident, and an overview of the test program, including available test results at the time of writing

  12. Numerical prediction of slamming loads

    DEFF Research Database (Denmark)

    Seng, Sopheak; Jensen, Jørgen J; Pedersen, Preben T

    2012-01-01

    It is important to include the contribution of the slamming-induced response in the structural design of large vessels with a significant bow flare. At the same time it is a challenge to develop rational tools to determine the slamming-induced loads and the prediction of their occurrence. Today i...

  13. Mitigating the Long term Operating Extreme Load through Active Control

    DEFF Research Database (Denmark)

    Koukoura, Christina; Natarajan, Anand

    2014-01-01

    blade azimuth location are shown to affect the extreme blade load magnitude during operation in normal turbulence wind input. The simultaneously controlled operation of generator torque variation and pitch variation at low blade pitch angles is detected to be responsible for very high loads acting...... on the blades. Through gain scheduling of the controller (modifications of the proportional Kp and the integral Ki gains) the extreme loads are mitigated, ensuring minimum instantaneous variations in the power production for operation above rated wind speed. The response of the blade load is examined...

  14. Mitigating the Long term Operating Extreme Load through Active Control

    International Nuclear Information System (INIS)

    Koukoura, Christina; Natarajan, Anand

    2014-01-01

    The parameters influencing the long term extreme operating design loads are identified through the implementation of a Design of Experiment (DOE) method. A function between the identified critical factors and the ultimate out-of-plane loads on the blade is determined. Variations in the initial blade azimuth location are shown to affect the extreme blade load magnitude during operation in normal turbulence wind input. The simultaneously controlled operation of generator torque variation and pitch variation at low blade pitch angles is detected to be responsible for very high loads acting on the blades. Through gain scheduling of the controller (modifications of the proportional Kp and the integral K gains) the extreme loads are mitigated, ensuring minimum instantaneous variations in the power production for operation above rated wind speed. The response of the blade load is examined for different values of the integral gain as resulting in rotor speed error and the rate of change of rotor speed. Based on the results a new load case for the simulation of extreme loads during normal operation is also presented

  15. Extreme loads seismic testing of conduit systems

    International Nuclear Information System (INIS)

    Howard, G.E.; Ibanez, P.; Harrison, S.; Shi, Z.T.

    1991-01-01

    Rigid steel conduit (thin-wall tubes with threaded connections) containing electrical cabling are a common feature in nuclear power plants. Conduit systems are in many cases classified in U.S.A. practice as Seismic Category I structures. this paper summarizes results and others aspects of a dynamic test program conducted to investigate conduit systems seismic performance under three-axis excitation for designs representative at a nuclear power plant sited near Ft. Worth, Texas (a moderate seismic zone), with a Safe Shutdown Earthquake (SSE) of 0.12 g. Test specimens where subjected to postulated seismic events, including excitation well in excess of Safe Shutdown Earthquake events typical for U.S.A. nuclear power stations. A total of 18 conduit systems of 9-meter nominal lengths were shake table mounted and subjected to a variety of tests. None of the specimens suffered loss of load capacity when subjected to a site-enveloping Safe Shutdown Earthquake (SSE). Clamp/attachment hardware failures only began to occur when earthquake input motion was scaled upward to minimum values of 2.3-4.6 times site enveloping SSE response spectra. Tensile and/or shear failure of clamp attachment bolts or studs was the failure mode in all case in which failure was induced. (author)

  16. Extreme and First-Passage Time of Ship Collision Loads

    DEFF Research Database (Denmark)

    Nielsen, Søren R. K.; Thoft-Christensen, Palle

    1983-01-01

    The paper outlines a general theory from which the distribution function of the extreme peak collision load encountered during a certain intended lifetime can be cal culated assuming the arrival of ship collisions to be specified by a Poisson counting proces s.......The paper outlines a general theory from which the distribution function of the extreme peak collision load encountered during a certain intended lifetime can be cal culated assuming the arrival of ship collisions to be specified by a Poisson counting proces s....

  17. Predicting Ultimate Loads for Wind Turbine Design

    International Nuclear Information System (INIS)

    Madsen, P. H.; Pierce, K.; Buhl, M.

    1998-01-01

    This paper addresses the statistical uncertainty of loads prediction using structural dynamics simulation codes and the requirements for the number and duration of simulations for obtaining robust load estimates

  18. Influence of the control system on wind turbine loads during power production in extreme turbulence: Structural reliability

    DEFF Research Database (Denmark)

    Abdallah, Imad; Natarajan, Anand; Sørensen, John Dalsgaard

    2016-01-01

    structural reliability are assessed when the extreme turbulence model is uncertain. The structural reliability is assessed for the wind turbine when three configurations of an industrial grade load alleviation control system of increasing complexity and performance are used. The load alleviation features......The wind energy industry is continuously researching better computational models of wind inflow and turbulence to predict extreme loading (the nature of randomness) and their corresponding probability of occurrence. Sophisticated load alleviation control systems are increasingly being designed...... and deployed to specifically reduce the adverse effects of extreme load events resulting in lighter structures. The main objective herein is to show that despite large uncertainty in the extreme turbulence models, advanced load alleviation control systems yield both a reduction in magnitude and scatter...

  19. Load prediction of stall regulated wind turbines

    Energy Technology Data Exchange (ETDEWEB)

    Bjoerck, A.; Dahlberg, J.Aa. [Aeronautical Research Inst. of Sweden, Bromma (Sweden); Carlen, I. [Chalmers Univ. of Technology, Goeteborg (Sweden). Div. of Marine Structural Engineering; Ganander, H. [Teknikgruppen AB, Sollentua (Sweden)

    1996-12-01

    Measurements of blade loads on a turbine situated in a small wind farm shows that the highest blade loads occur during operation close to the peak power i.e. when the turbine operates in the stall region. In this study the extensive experimental data base has been utilised to compare loads in selected campaigns with corresponding load predictions. The predictions are based on time domain simulations of the wind turbine structure, performed by the aeroelastic code VIDYN. In the calculations a model were adopted in order to include the effects of dynamic stall. This paper describes the work carried out so far within the project and key results. 5 refs, 10 figs

  20. Specific gas turbines for extreme peak-load

    International Nuclear Information System (INIS)

    Bellot, C.

    1992-12-01

    As with other European countries, in France peak consumption of electricity occurs during winter. Due to the increasing use of electricity for domestic heating, outside temperature greatly influences consumption (1 200 MW for a drop of 1 deg C). To meet requirements during cold spells, EDF has sought to determine which special facilities are best suited for extreme peak load conditions (i.e. offering short lifespan and minimum capital cost) and has studied the possibility of installing generation means in transformer substations (20 kV). This solution does not require extension of networks since these means are scattered near consumption areas. An experiment conducted on 3 Diesel generators of 800 kWe each at Senlis revealed some of the disadvantages of Diesel (maintenance requirements, polluting emissions and noise). EDF then examined, for this same application, the use of gas turbines, for which these drawbacks are significantly less. A study carried out under an EDF contract by the French manufacturer TURBOMECA showed that it is possible to design a small capacity gas turbine that can compete with Diesel generators, and that capital costs could be minimized by simplifying the machine, adapting its lifespan to extreme peak load needs, and taking advantage of lower cost provided by mass production. TURBOMECA defined the machine's characteristics (2 MW, 6 000 hours lifespan) and aerodynamic flow. It also estimated the cost of packaging. In terms of overall cost (including initial investment, maintenance and fuel) the gas turbine appears cheaper than Diesel generators for annual operation times of less than one hundred hours, which corresponds closely with extreme peak load use. The lower maintenance costs and the better availability counterbalance the higher capital cost (+6%) and the greater consumption (+50%). (author). 7 figs

  1. Hydrogen ion induced ultralow wear of PEEK under extreme load

    Science.gov (United States)

    Yan, Shuai; Wang, Anying; Fei, Jixiong; Wang, Zhenyang; Zhang, Xiaofeng; Lin, Bin

    2018-03-01

    As a high-performance engineering polymer, poly(ether ether ketone) (PEEK) is a perfect candidate material for applications under extreme working conditions. However, its high wear rate greatly shortens its service life. In this study, ultralow friction and wear between PEEK and silicon nitride (Si3N4) under extreme-load conditions (with a mean contact pressure above 100 MPa) are found in acid lubricating solutions. Both friction and wear decrease sharply with decreasing pH. At pH = 1, the friction coefficient decreases by an order of magnitude and the wear rate of the PEEK decreases by two orders of magnitude compared to the results with water lubrication. These reductions in friction and wear occur for different speed, load, and surface roughness conditions. The underlying mechanism can be attributed to the formation of hydrogen-ion-induced electrical double layers on the surfaces of PEEK and Si3N4. The combined effect of the resulting repulsive force, electro-viscosity, and low shear strength of the water layer dramatically reduces both friction and wear.

  2. Variability of extreme flap loads during turbine operation

    Energy Technology Data Exchange (ETDEWEB)

    Ronold, K O [Det Norske Veritas, Hoevik (Norway); Larsen, G C [Risoe National Lab., Wind Energy and Atmospheric Physics Dept., Roskilde (Denmark)

    1999-03-01

    The variability of extreme flap loads is of utmost importance for design of wind-turbine rotor blades. The flap loads of interest consist of the flap-wise bendin moment response at the blade root whose variability in the short-term, for a given wind climate, can be represented by a stationary process. A model for the short-term bending moment process is presented, and the distribution of its associated maxima is derived. A model for the wind climate is given in terms of the probability distributions for the 10-minute mean wind speed and the standard deviation of the arbitrary wind speed. This is used to establish the distribution of the largest flap-wise bending moment in a specific reference period, and it is outlined how a characteristic bending moment for use in design can be extracted from this distribution. The application of the presented distribution models is demonstrated by a numerical example for a site-specific wind turbine. (au)

  3. Extreme load alleviation using industrial implementation of active trailing edge flaps in a full design load basis

    OpenAIRE

    Barlas, Athanasios; Pettas, Vasilis; Gertz, Drew Patrick; Aagaard Madsen , Helge

    2016-01-01

    The application of active trailing edge flaps in an industrial oriented implementation is evaluated in terms of capability of alleviating design extreme loads. A flap system with basic control functionality is implemented and tested in a realistic full Design Load Basis (DLB) for the DTU 10MW Reference Wind Turbine (RWT) model and for an upscaled rotor version in DTU's aeroelastic code HAWC2. The flap system implementation shows considerable potential in reducing extreme loads in components o...

  4. Political extremism predicts belief in conspiracy theories

    NARCIS (Netherlands)

    van Prooijen, J.W.; Krouwel, A.P.M.; Pollet, T. V.

    2015-01-01

    Historical records suggest that the political extremes—at both the “left” and the “right”—substantially endorsed conspiracy beliefs about other-minded groups. The present contribution empirically tests whether extreme political ideologies, at either side of the political spectrum, are positively

  5. PREDICTION OF THE EXTREMAL SHAPE FACTOR OF SPHEROIDAL PARTICLES

    Directory of Open Access Journals (Sweden)

    Daniel Hlubinka

    2011-05-01

    Full Text Available In the stereological unfolding problem for spheroidal particles the extremal shape factor is predicted. The theory of extreme values has been used to show that extremes of the planar shape factor of particle sections tend to the same limit distribution as extremes of the original shape factor for both the conditional and marginal distribution. Attention is then paid to the extreme shape factor conditioned by the particle size. Normalizing constants are evaluated for a parametric model and the numerical procedure is tested on real data from metallography.

  6. Prediction of Lower Extremity Movement by Cyclograms

    Directory of Open Access Journals (Sweden)

    P. Kutilek

    2012-01-01

    Full Text Available Human gait is nowadays undergoing extensive analysis. Predictions of leg movements can be used for orthosis and prosthesis programming, and also for rehabilitation. Our work focuses on predicting human gait with the use of angle-angle diagrams, also called cyclograms. In conjunction with artificial intelligence, cyclograms offer a wide area of medical applications. We have identified cyclogram characteristics such as the slope and the area of the cyclogram for a neural network learning algorithm. Neural networks learned by cyclograms offer wide applications in prosthesis control systems.

  7. The Effects of Load Carriage and Muscle Fatigue on Lower-Extremity Joint Mechanics

    Science.gov (United States)

    Wang, He; Frame, Jeff; Ozimek, Elicia; Leib, Daniel; Dugan, Eric L.

    2013-01-01

    Military personnel are commonly afflicted by lower-extremity overuse injuries. Load carriage and muscular fatigue are major stressors during military basic training. Purpose: To examine effects of load carriage and muscular fatigue on lower-extremity joint mechanics during walking. Method: Eighteen men performed the following tasks: unloaded…

  8. Outlier robustness for wind turbine extrapolated extreme loads

    DEFF Research Database (Denmark)

    Natarajan, Anand; Verelst, David Robert

    2012-01-01

    . Stochastic identification of numerical artifacts in simulated loads is demonstrated using the method of principal component analysis. The extrapolation methodology is made robust to outliers through a weighted loads approach, whereby the eigenvalues of the correlation matrix obtained using the loads with its...

  9. Extreme load alleviation using industrial implementation of active trailing edge flaps in a full design load basis

    DEFF Research Database (Denmark)

    Barlas, Athanasios; Pettas, Vasilis; Gertz, Drew Patrick

    2016-01-01

    The application of active trailing edge flaps in an industrial oriented implementation is evaluated in terms of capability of alleviating design extreme loads. A flap system with basic control functionality is implemented and tested in a realistic full Design Load Basis (DLB) for the DTU 10MW...

  10. Predicting extreme rainfall over eastern Asia by using complex networks

    International Nuclear Information System (INIS)

    He Su-Hong; Gong Yan-Chun; Huang Yan-Hua; Wu Cheng-Guo; Feng Tai-Chen; Gong Zhi-Qiang

    2014-01-01

    A climate network of extreme rainfall over eastern Asia is constructed for the period of 1971–2000, employing the tools of complex networks and a measure of nonlinear correlation called event synchronization (ES). Using this network, we predict the extreme rainfall for several cases without delay and with n-day delay (1 ≤ n ≤ 10). The prediction accuracy can reach 58% without delay, 21% with 1-day delay, and 12% with n-day delay (2 ≤ n ≤ 10). The results reveal that the prediction accuracy is low in years of a weak east Asia summer monsoon (EASM) or 1 year later and high in years of a strong EASM or 1 year later. Furthermore, the prediction accuracy is higher due to the many more links that represent correlations between different grid points and a higher extreme rainfall rate during strong EASM years. (geophysics, astronomy, and astrophysics)

  11. Multivariate Modelling of Extreme Load Combinations for Wind Turbines

    DEFF Research Database (Denmark)

    Dimitrov, Nikolay Krasimirov

    2015-01-01

    into a periodic part and a perturbation term, where each part has a known probability distribution. The proposed model shows good agreement with simulated data under stationary conditions, and a design load envelope based on this model is comparable to the load envelope estimated using the standard procedure...

  12. Predicting Malaysian palm oil price using Extreme Value Theory

    OpenAIRE

    Chuangchid, K; Sriboonchitta, S; Rahman, S; Wiboonpongse, A

    2013-01-01

    This paper uses the extreme value theory (EVT) to predict extreme price events of Malaysian palm oil in the future, based on monthly futures price data for a 25 year period (mid-1986 to mid-2011). Model diagnostic has confirmed non-normal distribution of palm oil price data, thereby justifying the use of EVT. Two principal approaches to model extreme values – the Block Maxima (BM) and Peak-Over- Threshold (POT) models – were used. Both models revealed that the palm oil price will peak at ...

  13. Effect of linear and non-linear blade modelling techniques on simulated fatigue and extreme loads using Bladed

    Science.gov (United States)

    Beardsell, Alec; Collier, William; Han, Tao

    2016-09-01

    There is a trend in the wind industry towards ever larger and more flexible turbine blades. Blade tip deflections in modern blades now commonly exceed 10% of blade length. Historically, the dynamic response of wind turbine blades has been analysed using linear models of blade deflection which include the assumption of small deflections. For modern flexible blades, this assumption is becoming less valid. In order to continue to simulate dynamic turbine performance accurately, routine use of non-linear models of blade deflection may be required. This can be achieved by representing the blade as a connected series of individual flexible linear bodies - referred to in this paper as the multi-part approach. In this paper, Bladed is used to compare load predictions using single-part and multi-part blade models for several turbines. The study examines the impact on fatigue and extreme loads and blade deflection through reduced sets of load calculations based on IEC 61400-1 ed. 3. Damage equivalent load changes of up to 16% and extreme load changes of up to 29% are observed at some turbine load locations. It is found that there is no general pattern in the loading differences observed between single-part and multi-part blade models. Rather, changes in fatigue and extreme loads with a multi-part blade model depend on the characteristics of the individual turbine and blade. Key underlying causes of damage equivalent load change are identified as differences in edgewise- torsional coupling between the multi-part and single-part models, and increased edgewise rotor mode damping in the multi-part model. Similarly, a causal link is identified between torsional blade dynamics and changes in ultimate load results.

  14. Predictability and possible earlier awareness of extreme precipitation across Europe

    Science.gov (United States)

    Lavers, David; Pappenberger, Florian; Richardson, David; Zsoter, Ervin

    2017-04-01

    Extreme hydrological events can cause large socioeconomic damages in Europe. In winter, a large proportion of these flood episodes are associated with atmospheric rivers, a region of intense water vapour transport within the warm sector of extratropical cyclones. When preparing for such extreme events, forecasts of precipitation from numerical weather prediction models or river discharge forecasts from hydrological models are generally used. Given the strong link between water vapour transport (integrated vapour transport IVT) and heavy precipitation, it is possible that IVT could be used to warn of extreme events. Furthermore, as IVT is located in extratropical cyclones, it is hypothesized to be a more predictable variable due to its link with synoptic-scale atmospheric dynamics. In this research, we firstly provide an overview of the predictability of IVT and precipitation forecasts, and secondly introduce and evaluate the ECMWF Extreme Forecast Index (EFI) for IVT. The EFI is a tool that has been developed to evaluate how ensemble forecasts differ from the model climate, thus revealing the extremeness of the forecast. The ability of the IVT EFI to capture extreme precipitation across Europe during winter 2013/14, 2014/15, and 2015/16 is presented. The results show that the IVT EFI is more capable than the precipitation EFI of identifying extreme precipitation in forecast week 2 during forecasts initialized in a positive North Atlantic Oscillation (NAO) phase. However, the precipitation EFI is superior during the negative NAO phase and at shorter lead times. An IVT EFI example is shown for storm Desmond in December 2015 highlighting its potential to identify upcoming hydrometeorological extremes.

  15. Power Load Prediction Based on Fractal Theory

    OpenAIRE

    Jian-Kai, Liang; Cattani, Carlo; Wan-Qing, Song

    2015-01-01

    The basic theories of load forecasting on the power system are summarized. Fractal theory, which is a new algorithm applied to load forecasting, is introduced. Based on the fractal dimension and fractal interpolation function theories, the correlation algorithms are applied to the model of short-term load forecasting. According to the process of load forecasting, the steps of every process are designed, including load data preprocessing, similar day selecting, short-term load forecasting, and...

  16. Summary of international extreme load design requirements for nuclear power plant facilities

    International Nuclear Information System (INIS)

    Stevenson, J.D.

    1978-01-01

    An attempt is made to trace the development of extreme load criteria as it applies to earthquakes, extreme wind, high energy system rupture (LOCA), floods and other manmade and natural external hazards, from 1965 until the present, in the leading nuclear power nations throughout the world. (Author)

  17. Climate control loads prediction of electric vehicles

    International Nuclear Information System (INIS)

    Zhang, Ziqi; Li, Wanyong; Zhang, Chengquan; Chen, Jiangping

    2017-01-01

    Highlights: • A model of vehicle climate control loads is proposed based on experiments. • Main climate control loads of the modeled vehicle are quantitatively analyzed. • Range reductions of the modeled vehicle under different conditions are simulated. - Abstract: A new model of electric vehicle climate control loads is provided in this paper. The mathematical formulations of the major climate control loads are developed, and the coefficients of the formulations are experimentally determined. Then, the detailed climate control loads are analyzed, and the New European Driving Cycle (NEDC) range reductions due to these loads are calculated under different conditions. It is found that in an electric vehicle, the total climate control loads vary with the vehicle speed, HVAC mode and blower level. The ventilation load is the largest climate control load, followed by the solar radiation load. These two add up to more than 80% of total climate control load in summer. The ventilation load accounts for 70.7–83.9% of total heating load under the winter condition. The climate control loads will cause a 17.2–37.1% reduction of NEDC range in summer, and a 17.1–54.1% reduction in winter, compared to the AC off condition. The heat pump system has an advantage in range extension. A heat pump system with an average heating COP of 1.7 will extend the range by 7.6–21.1% based on the simulation conditions.

  18. Power load prediction based on GM (1,1)

    Science.gov (United States)

    Wu, Di

    2017-05-01

    Currently, Chinese power load prediction is highly focused; the paper deeply studies grey prediction and applies it to Chinese electricity consumption during the recent 14 years; through after-test test, it obtains grey prediction which has good adaptability to medium and long-term power load.

  19. Working Memory Load Strengthens Reward Prediction Errors.

    Science.gov (United States)

    Collins, Anne G E; Ciullo, Brittany; Frank, Michael J; Badre, David

    2017-04-19

    Reinforcement learning (RL) in simple instrumental tasks is usually modeled as a monolithic process in which reward prediction errors (RPEs) are used to update expected values of choice options. This modeling ignores the different contributions of different memory and decision-making systems thought to contribute even to simple learning. In an fMRI experiment, we investigated how working memory (WM) and incremental RL processes interact to guide human learning. WM load was manipulated by varying the number of stimuli to be learned across blocks. Behavioral results and computational modeling confirmed that learning was best explained as a mixture of two mechanisms: a fast, capacity-limited, and delay-sensitive WM process together with slower RL. Model-based analysis of fMRI data showed that striatum and lateral prefrontal cortex were sensitive to RPE, as shown previously, but, critically, these signals were reduced when the learning problem was within capacity of WM. The degree of this neural interaction related to individual differences in the use of WM to guide behavioral learning. These results indicate that the two systems do not process information independently, but rather interact during learning. SIGNIFICANCE STATEMENT Reinforcement learning (RL) theory has been remarkably productive at improving our understanding of instrumental learning as well as dopaminergic and striatal network function across many mammalian species. However, this neural network is only one contributor to human learning and other mechanisms such as prefrontal cortex working memory also play a key role. Our results also show that these other players interact with the dopaminergic RL system, interfering with its key computation of reward prediction errors. Copyright © 2017 the authors 0270-6474/17/374332-11$15.00/0.

  20. Characterization and prediction of extreme events in turbulence

    Science.gov (United States)

    Fonda, Enrico; Iyer, Kartik P.; Sreenivasan, Katepalli R.

    2017-11-01

    Extreme events in Nature such as tornadoes, large floods and strong earthquakes are rare but can have devastating consequences. The predictability of these events is very limited at present. Extreme events in turbulence are the very large events in small scales that are intermittent in character. We examine events in energy dissipation rate and enstrophy which are several tens to hundreds to thousands of times the mean value. To this end we use our DNS database of homogeneous and isotropic turbulence with Taylor Reynolds numbers spanning a decade, computed with different small scale resolutions and different box sizes, and study the predictability of these events using machine learning. We start with an aggressive data augmentation to virtually increase the number of these rare events by two orders of magnitude and train a deep convolutional neural network to predict their occurrence in an independent data set. The goal of the work is to explore whether extreme events can be predicted with greater assurance than can be done by conventional methods (e.g., D.A. Donzis & K.R. Sreenivasan, J. Fluid Mech. 647, 13-26, 2010).

  1. Climatic extremes improve predictions of spatial patterns of tree species

    Science.gov (United States)

    Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, Antoine; Schmatz, D.R.; Pearman, P.B.

    2009-01-01

    Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D2, +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

  2. Effects of normal and extreme turbulence spectral parameters on wind turbine loads

    DEFF Research Database (Denmark)

    Dimitrov, Nikolay Krasimirov; Natarajan, Anand; Mann, Jakob

    2017-01-01

    the recommended values in the IEC 61400-1 Ed.3 that is used for wind turbine design. The present paper investigates the impact of Mann turbulence model parameter variations on the design loads envelope for 5 MW and 10 MW reference wind turbines. Specific focus is made on the blade root loads, tower top moments...... of design loads is investigated with a focus on the commonly used Mann turbulence model. Quantification of the Mann model parameters is made through wind measurements acquired from the Høvsøre site. The parameters of the Mann model fitted to site specific observations can differ significantly from...... and tower base loads under normal turbulence and extreme turbulence, whereby the change in operating extreme and fatigue design loads obtained through turbulence model parameter variations is compared with corresponding variations obtained from random seeds of turbulence. The investigations quantify...

  3. Impact of extreme load requirements and quality assurance on nuclear power plant costs

    International Nuclear Information System (INIS)

    Stevenson, J.D.

    1993-01-01

    Definitive costs, applicable to nuclear power plant concrete structures, as a function of National Regulatory Requirements, standardization, the effect of extreme load design associated with both design basis accidents and extreme external events and quality assurance are difficult to develop since such effects are interrelated and not only differ widely from country to country, project to project but also vary in time. Table 1 shows an estimate of the of the overall plant cost effects of external event extreme load design on nuclear power plant design for the U.S -and selected foreign countries for which experience with LWRs exist- Germany is the most expensive primarily due to a military aircraft crash resistance. However, the German requirement for 4 safeguards trains rather than 2 and the containment design requirement to consider one Steam Generator blowdown concurrent with a RCS blowdown. This presentation will concentrate on the direct current impact extreme load design and quality assurance have on concrete structures, systems and components for nuclear plants. This presentation is considered timely due to the increased interest in the c potential backfit of Eastern European nuclear power stations of the WWER 440 and WWER 1000 types which typically did not consider the extreme loads identified in Table 1 and accident loads in Table 3 and quality assurance in Table 5 in their original design. Concrete structures in particular are highlighted because they typically form the last barrier to radioactive release from the containment and other Safety Related Structures

  4. Extremely Randomized Machine Learning Methods for Compound Activity Prediction

    Directory of Open Access Journals (Sweden)

    Wojciech M. Czarnecki

    2015-11-01

    Full Text Available Speed, a relatively low requirement for computational resources and high effectiveness of the evaluation of the bioactivity of compounds have caused a rapid growth of interest in the application of machine learning methods to virtual screening tasks. However, due to the growth of the amount of data also in cheminformatics and related fields, the aim of research has shifted not only towards the development of algorithms of high predictive power but also towards the simplification of previously existing methods to obtain results more quickly. In the study, we tested two approaches belonging to the group of so-called ‘extremely randomized methods’—Extreme Entropy Machine and Extremely Randomized Trees—for their ability to properly identify compounds that have activity towards particular protein targets. These methods were compared with their ‘non-extreme’ competitors, i.e., Support Vector Machine and Random Forest. The extreme approaches were not only found out to improve the efficiency of the classification of bioactive compounds, but they were also proved to be less computationally complex, requiring fewer steps to perform an optimization procedure.

  5. Prediction of length-of-day using extreme learning machine

    Directory of Open Access Journals (Sweden)

    Yu Lei

    2015-03-01

    Full Text Available Traditional artificial neural networks (ANN such as back-propagation neural networks (BPNN provide good predictions of length-of-day (LOD. However, the determination of network topology is difficult and time consuming. Therefore, we propose a new type of neural network, extreme learning machine (ELM, to improve the efficiency of LOD predictions. Earth orientation parameters (EOP C04 time-series provides daily values from International Earth Rotation and Reference Systems Service (IERS, which serves as our database. First, the known predictable effects that can be described by functional models—such as the effects of solid earth, ocean tides, or seasonal atmospheric variations—are removed a priori from the C04 time-series. Only the residuals after the subtraction of a priori model from the observed LOD data (i.e., the irregular and quasi-periodic variations are employed for training and predictions. The predicted LOD is the sum of a prior extrapolation model and the ELM predictions of the residuals. Different input patterns are discussed and compared to optimize the network solution. The prediction results are analyzed and compared with those obtained by other machine learning-based prediction methods, including BPNN, generalization regression neural networks (GRNN, and adaptive network-based fuzzy inference systems (ANFIS. It is shown that while achieving similar prediction accuracy, the developed method uses much less training time than other methods. Furthermore, to conduct a direct comparison with the existing prediction techniques, the mean-absolute-error (MAE from the proposed method is compared with that from the EOP prediction comparison campaign (EOP PCC. The results indicate that the accuracy of the proposed method is comparable with that of the former techniques. The implementation of the proposed method is simple.

  6. Predictability of summer extreme precipitation days over eastern China

    Science.gov (United States)

    Li, Juan; Wang, Bin

    2017-08-01

    Extreme precipitation events have severe impacts on human activity and natural environment, but prediction of extreme precipitation events remains a considerable challenge. The present study aims to explore the sources of predictability and to estimate the predictability of the summer extreme precipitation days (EPDs) over eastern China. Based on the region- and season-dependent variability of EPDs, all stations over eastern China are divided into two domains: South China (SC) and northern China (NC). Two domain-averaged EPDs indices during their local high EPDs seasons (May-June for SC and July-August for NC) are therefore defined. The simultaneous lower boundary anomalies associated with each EPDs index are examined, and we find: (a) the increased EPDs over SC are related to a rapid decaying El Nino and controlled by Philippine Sea anticyclone anomalies in May-June; (b) the increased EPDs over NC are accompanied by a developing La Nina and anomalous zonal sea level pressure contrast between the western North Pacific subtropical high and East Asian low in July-August. Tracking back the origins of these boundary anomalies, one or two physically meaningful predictors are detected for each regional EPDs index. The causative relationships between the predictors and the corresponding EPDs over each region are discussed using lead-lag correlation analyses. Using these selected predictors, a set of Physics-based Empirical models is derived. The 13-year (2001-2013) independent forecast shows significant temporal correlation skills of 0.60 and 0.74 for the EPDs index of SC and NC, respectively, providing an estimation of the predictability for summer EPDs over eastern China.

  7. Current summary of international extreme load design requirements for nuclear power plant facilities

    International Nuclear Information System (INIS)

    Stevenson, J.D.

    1980-01-01

    The development of extreme load design criteria both as to rate and depth within any national jurisdiction as applied to nuclear power plant design is a function of several factors. The prime factor is the number of nuclear power plant facilities which are operating, under construction or planned in a given country. The second most important factor seems to be the degree of development of a domestic independent nuclear steam system supplier, NSSS vendor. Finally, countries whose domestic NSSS firms are active in the export market appear to have more active criteria development programs or at least they appear more visible to the foreign observer. For the purposes of this paper, extreme loads are defined as those loads having probability of occurence less than 10 -1 /yr and whose occurence could result in radiological consequences in excess of those permitted by national health standards. The specific loads considered include earthquake, extreme wind (tornado), airplane crash, detonation, and high energy system rupture. The paper identifies five national centers for extreme load criteria development; Canada, Great Britian, USA, USSR, and West Germany with both France and Japan also about to appear as independent centers of criteria development. Criteria under development by each national center are discussed in detail. (orig.)

  8. Ultimate design load analysis of planetary gearbox bearings under extreme events

    DEFF Research Database (Denmark)

    Gallego Calderon, Juan Felipe; Natarajan, Anand; Cutululis, Nicolaos Antonio

    2017-01-01

    This paper investigates the impact of extreme events on the planet bearings of a 5 MW gearbox. The system is simulated using an aeroelastic tool, where the turbine structure is modeled, and MATLAB/Simulink, where the drivetrain (gearbox and generator) are modeled using a lumped-parameter approach....... Three extreme events are assessed: low-voltage ride through, emergency stop and normal stop. The analysis is focused on finding which event has the most negative impact on the bearing extreme radial loads. The two latter events are carried out following the guidelines of the International...

  9. Computational data sciences for assessment and prediction of climate extremes

    Science.gov (United States)

    Ganguly, A. R.

    2011-12-01

    Climate extremes may be defined inclusively as severe weather events or large shifts in global or regional weather patterns which may be caused or exacerbated by natural climate variability or climate change. This area of research arguably represents one of the largest knowledge-gaps in climate science which is relevant for informing resource managers and policy makers. While physics-based climate models are essential in view of non-stationary and nonlinear dynamical processes, their current pace of uncertainty reduction may not be adequate for urgent stakeholder needs. The structure of the models may in some cases preclude reduction of uncertainty for critical processes at scales or for the extremes of interest. On the other hand, methods based on complex networks, extreme value statistics, machine learning, and space-time data mining, have demonstrated significant promise to improve scientific understanding and generate enhanced predictions. When combined with conceptual process understanding at multiple spatiotemporal scales and designed to handle massive data, interdisciplinary data science methods and algorithms may complement or supplement physics-based models. Specific examples from the prior literature and our ongoing work suggests how data-guided improvements may be possible, for example, in the context of ocean meteorology, climate oscillators, teleconnections, and atmospheric process understanding, which in turn can improve projections of regional climate, precipitation extremes and tropical cyclones in an useful and interpretable fashion. A community-wide effort is motivated to develop and adapt computational data science tools for translating climate model simulations to information relevant for adaptation and policy, as well as for improving our scientific understanding of climate extremes from both observed and model-simulated data.

  10. Extreme Design Loads Calibration of Offshore Wind Turbine Blades through Real Time Measurements

    DEFF Research Database (Denmark)

    Natarajan, Anand; Vesth, Allan; Lamata, Rebeca Rivera

    2014-01-01

    Blade Root flap and Edge moments are measured on the blades of a 3.6MW offshore wind turbine in normal operation. Ten minute maxima of the measurements are sampled to determine the extreme blade root flap moment, edge moment and resultant moment over six month duration. A random subset of the mea......Blade Root flap and Edge moments are measured on the blades of a 3.6MW offshore wind turbine in normal operation. Ten minute maxima of the measurements are sampled to determine the extreme blade root flap moment, edge moment and resultant moment over six month duration. A random subset...... of the measurements over a week is taken as input to stochastic load extrapolation whereby the one year extrapolated design extreme is obtained, which are then compared with the maximum extremes obtained from direct measurements over a six month period to validate the magnification in the load levels for the blade...... root flap moment, edge moment obtained by extrapolation. The validation yields valuable information on prescribing the slope of the local extrapolation curve at each mean wind speed. As an alternative to determining the contemporaneous loads for each primary extrapolated load, the blade root resultant...

  11. Using bench press load to predict upper body exercise loads in physically active individuals.

    Science.gov (United States)

    Wong, Del P; Ngo, Kwan-Lung; Tse, Michael A; Smith, Andrew W

    2013-01-01

    This study investigated whether loads for assistance exercises of the upper body can be predicted from the loads of the bench press exercise. Twenty-nine physically active collegiate students (age: 22.6 ± 2.5; weight training experience: 2.9 ± 2.1 years; estimated 1RM bench press: 54.31 ± 14.60 kg; 1RM: body weight ratio: 0.80 ± 0.22; BMI: 22.7 ± 2.1 kg·m(-2)) were recruited. The 6RM loads for bench press, barbell bicep curl, overhead dumbbell triceps extension, hammer curl and dumbbell shoulder press were measured. Test-retest reliability for the 5 exercises as determined by Pearson product moment correlation coefficient was very high to nearly perfect (0.82-0.98, p bench press load was significantly correlated with the loads of the 4 assistance exercises (r ranged from 0.80 to 0.93, p bench press load was a significant (R(2) range from 0.64 to 0.86, p Bench press load (0.28) + 6.30 kg, (b) Barbell biceps curl = Bench press load (0.33) + 6.20 kg, (c) Overhead triceps extension = Bench press load (0.33) - 0.60 kg, and (d) Dumbbell shoulder press = Bench press load (0.42) + 5.84 kg. The difference between the actual load and the predicted load using the four equations ranged between 6.52% and 8.54%, such difference was not significant. Fitness professionals can use the 6RM bench press load as a time effective and accurate method to predict training loads for upper body assistance exercises. Key pointsThe bench press load was significantly correlated with the loads of the 4 assistance exercises.No significant differences were found between the actual load and the predicted load in the four equations.6RM bench press load can be a time effective and accurate method to predict training loads for upper body assistance exercises.

  12. Extreme value predictions and critical wave episodes for marine structures by FORM

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher

    2007-01-01

    The aim of the present paper is to advocate for a very effective stochastic procedure, based on the First Order Reliability Method (FORM), for extreme value predictions related to wave induced loads. Three different applications will be illustrated. The first deals with a jack-up rig where second...... order stochastic waves are included in the analysis. The second application is parametric roll motions of ships. Finally, the motion of a TLP floating foundation for an offshore wind turbine is analysed taking into account large motions....

  13. Extreme value predictions and critical wave episodes for marine structures by FORM

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher

    2008-01-01

    The aim of the present paper is to advocate for a very effective stochastic procedure, based on the First Order Reliability Method (FORM), for extreme value predictions related to wave induced loads. Three different applications will be illustrated. The first deals with a jack-up rig where second...... order stochastic waves are included in the analysis. The second application is parametric roll motions of ships. Finally, the motion of a TLP floating foundation for an offshore wind turbine is analysed taking into account large motions....

  14. Investigation of potential extreme load reduction for a two-bladed upwind turbine with partial pitch

    DEFF Research Database (Denmark)

    Kim, Taeseong; Larsen, Torben J.; Yde, Anders

    2015-01-01

    This paper presents a wind turbine concept with an innovative design combining partial pitch with a two-bladed (PP-2B) turbine configuration. Special emphasis is on extreme load reduction during storm situations at standstill, but operational loads are also investigated. In order to compare...... loads are reduced by approximately 20% for the PP-2B and 18% for the PP-3B compared with the 3B turbine for the parked condition in a storm situation. Moreover, a huge potential of 60% is observed for the reduction of the extreme tower bottom bending moment for the PP-2B turbine, when the wind direction...... is from ±90° to the turbine, but this also requires that the turbine is parked in a T-configuration. © 2014 The Authors. Wind Energy published by John Wiley & Sons, Ltd....

  15. Advances in the Assessment of Wind Turbine Operating Extreme Loads via More Efficient Calculation Approaches

    Energy Technology Data Exchange (ETDEWEB)

    Graf, Peter; Damiani, Rick R.; Dykes, Katherine; Jonkman, Jason M.

    2017-01-09

    A new adaptive stratified importance sampling (ASIS) method is proposed as an alternative approach for the calculation of the 50 year extreme load under operational conditions, as in design load case 1.1 of the the International Electrotechnical Commission design standard. ASIS combines elements of the binning and extrapolation technique, currently described by the standard, and of the importance sampling (IS) method to estimate load probability of exceedances (POEs). Whereas a Monte Carlo (MC) approach would lead to the sought level of POE with a daunting number of simulations, IS-based techniques are promising as they target the sampling of the input parameters on the parts of the distributions that are most responsible for the extreme loads, thus reducing the number of runs required. We compared the various methods on select load channels as output from FAST, an aero-hydro-servo-elastic tool for the design and analysis of wind turbines developed by the National Renewable Energy Laboratory (NREL). Our newly devised method, although still in its infancy in terms of tuning of the subparameters, is comparable to the others in terms of load estimation and its variance versus computational cost, and offers great promise going forward due to the incorporation of adaptivity into the already powerful importance sampling concept.

  16. Predicting Footbridge Response using Stochastic Load Models

    DEFF Research Database (Denmark)

    Pedersen, Lars; Frier, Christian

    2013-01-01

    Walking parameters such as step frequency, pedestrian mass, dynamic load factor, etc. are basically stochastic, although it is quite common to adapt deterministic models for these parameters. The present paper considers a stochastic approach to modeling the action of pedestrians, but when doing so...... decisions need to be made in terms of statistical distributions of walking parameters and in terms of the parameters describing the statistical distributions. The paper explores how sensitive computations of bridge response are to some of the decisions to be made in this respect. This is useful...

  17. Biomechanical loading on the upper extremity increases from single key tapping to directional tapping.

    Science.gov (United States)

    Qin, Jin; Trudeau, Matthieu; Katz, Jeffrey N; Buchholz, Bryan; Dennerlein, Jack T

    2011-08-01

    Musculoskeletal disorders associated with computer use span the joints of the upper extremity. Computing typically involves tapping in multiple directions. Thus, we sought to describe the loading on the finger, wrist, elbow and shoulder joints in terms of kinematic and kinetic difference across single key switch tapping to directional tapping on multiple keys. An experiment with repeated measures design was conducted. Six subjects tapped with their right index finger on a stand-alone number keypad placed horizontally in three conditions: (1) on single key switch (the number key 5); (2) left and right on number key 4 and 6; (3) top and bottom on number key 8 and 2. A force-torque transducer underneath the keypad measured the fingertip force. An active-marker infrared motion analysis system measured the kinematics of the fingertip, hand, forearm, upper arm and torso. Joint moments for the metacarpophalangeal, wrist, elbow, and shoulder joints were estimated using inverse dynamics. Tapping in the top-bottom orientation introduced the largest biomechanical loading on the upper extremity especially for the proximal joint, followed by tapping in the left-right orientation, and the lowest loading was observed during single key switch tapping. Directional tapping on average increased the fingertip force, joint excursion, and peak-to-peak joint torque by 45%, 190% and 55%, respectively. Identifying the biomechanical loading patterns associated with these fundamental movements of keying improves the understanding of the risks of upper extremity musculoskeletal disorders for computer keyboard users. Copyright © 2010 Elsevier Ltd. All rights reserved.

  18. Extremes of shock index predicts death in trauma patients

    Directory of Open Access Journals (Sweden)

    Stephen R Odom

    2016-01-01

    Full Text Available Context: We noted a bimodal relationship between mortality and shock index (SI, the ratio of heart rate to systolic blood pressure. Aims: To determine if extremes of SI can predict mortality in trauma patients. Settings and Designs: Retrospective evaluation of adult trauma patients at a tertiary care center from 2000 to 2012 in the United States. Materials and Methods: We examined the SI in trauma patients and determined the adjusted mortality for patients with and without head injuries. Statistical Analysis Used: Descriptive statistics and multivariable logistic regression. Results: SI values demonstrated a U-shaped relationship with mortality. Compared with patients with a SI between 0.5 and 0.7, patients with a SI of 1.3 had an odds ratio of death of 3.1. (95% CI 1.6–5.9. Elevated SI is associated with increased mortality in patients with isolated torso injuries, and is associated with death at both low and high values in patients with head injury. Conclusion: Our data indicate a bimodal relationship between SI and mortality in head injured patients that persists after correction for various co-factors. The distribution of mortality is different between head injured patients and patients without head injuries. Elevated SI predicts death in all trauma patients, but low SI values only predict death in head injured patients.

  19. Using the load-velocity relationship for 1RM prediction.

    OpenAIRE

    Jidovtseff, Boris; Harris, N. K.; Crielaard, Jean-Michel; Cronin, J. B.

    2011-01-01

    Jidovtseff, B, Harris, NK, Crielaard, J-M, and Cronin, JB. Using the load-velocity relationship for 1RM prediction. J Strength Cond Res 24(x): 000-000, 2009-The purpose of this study was to investigate the ability of the load-velocity relationship to accurately predict a bench press 1 repetition maximum (1RM). Data from 3 different bench press studies (n = 112) that incorporated both 1RM assessment and submaximal load-velocity profiling were analyzed. Individual regression analysis was perfor...

  20. A Novel Hybrid Model Based on Extreme Learning Machine, k-Nearest Neighbor Regression and Wavelet Denoising Applied to Short-Term Electric Load Forecasting

    Directory of Open Access Journals (Sweden)

    Weide Li

    2017-05-01

    Full Text Available Electric load forecasting plays an important role in electricity markets and power systems. Because electric load time series are complicated and nonlinear, it is very difficult to achieve a satisfactory forecasting accuracy. In this paper, a hybrid model, Wavelet Denoising-Extreme Learning Machine optimized by k-Nearest Neighbor Regression (EWKM, which combines k-Nearest Neighbor (KNN and Extreme Learning Machine (ELM based on a wavelet denoising technique is proposed for short-term load forecasting. The proposed hybrid model decomposes the time series into a low frequency-associated main signal and some detailed signals associated with high frequencies at first, then uses KNN to determine the independent and dependent variables from the low-frequency signal. Finally, the ELM is used to get the non-linear relationship between these variables to get the final prediction result for the electric load. Compared with three other models, Extreme Learning Machine optimized by k-Nearest Neighbor Regression (EKM, Wavelet Denoising-Extreme Learning Machine (WKM and Wavelet Denoising-Back Propagation Neural Network optimized by k-Nearest Neighbor Regression (WNNM, the model proposed in this paper can improve the accuracy efficiently. New South Wales is the economic powerhouse of Australia, so we use the proposed model to predict electric demand for that region. The accurate prediction has a significant meaning.

  1. Ventilator flow data predict bronchopulmonary dysplasia in extremely premature neonates

    Directory of Open Access Journals (Sweden)

    Mariann H. Bentsen

    2018-03-01

    Full Text Available Early prediction of bronchopulmonary dysplasia (BPD may facilitate tailored management for neonates at risk. We investigated whether easily accessible flow data from a mechanical ventilator can predict BPD in neonates born extremely premature (EP. In a prospective population-based study of EP-born neonates, flow data were obtained from the ventilator during the first 48 h of life. Data were logged for >10 min and then converted to flow–volume loops using custom-made software. Tidal breathing parameters were calculated and averaged from ≥200 breath cycles, and data were compared between those who later developed moderate/severe and no/mild BPD. Of 33 neonates, 18 developed moderate/severe and 15 no/mild BPD. The groups did not differ in gestational age, surfactant treatment or ventilator settings. The infants who developed moderate/severe BPD had evidence of less airflow obstruction, significantly so for tidal expiratory flow at 50% of tidal expiratory volume (TEF50 expressed as a ratio of peak tidal expiratory flow (PTEF (p=0.007. A compound model estimated by multiple logistic regression incorporating TEF50/PTEF, birthweight z-score and sex predicted moderate/severe BPD with good accuracy (area under the curve 0.893, 95% CI 0.735–0.973. This study suggests that flow data obtained from ventilators during the first hours of life may predict later BPD in premature neonates. Future and larger studies are needed to validate these findings and to determine their clinical usefulness.

  2. Prediction of future nitrogen loading to Lake Rotorua

    International Nuclear Information System (INIS)

    Morgenstern, U.; Gordon, D.

    2006-01-01

    Groundwater that feeds streams and springs in the Lake Rotorua catchment has 15-130 years mean residence times in the aquifer. These long residence times of the water in the ground result in large time-delays of nitrogen loading from historical agricultural and urban development in the catchment. Currently observed increases in nitrogen loading in surface and groundwater are mostly due to the delayed impact of catchment development that occurred around 55 years ago. Further increases in nitrogen are expected. The time-dependence of the arrival of water to the lake that was recharged since landuse development in the 1950's was calculated using the age distribution of the water derived from tritium, CFC and SF 6 data. The arrival of post-landuse water over time was then used to estimate the nitrogen load to the lake for the time prior to landuse development, for the time since then, and for the future. Excellent matches between measured N loads over the last decades and predicted loads demonstrate the robustness of the approach, and that the model assumptions used for future predictions are reasonable. Future groundwater-derived nutrient loads are listed below. No changes are expected in phosphorus loads via groundwater as long as landuse-derived P continues to be absorbed by the volcanic soils in the catchment. The nitrogen loading to Lake Rotorua prior to major landuse development in the catchment in the 1950's was calculated to be 60 t/year. This has slowly increased to a present nitrogen load of 420 t/y, delayed by long travel times of the groundwater. The nitrogen loading is expected to further increase to 532 t/y in 50 years (25% increase from current), 572 t/y in 100 years (35% increase from current), and to 619 t/y at steady-state (47% increase from current). About 75% of the groundwater-derived nitrogen loading at steady-state enters Lake Rotorua via the nine major streams, and about 20% enters the lake from direct groundwater inflow to the lake bed. The

  3. Deterministic and Probabilistic Analysis of NPP Communication Bridge Resistance Due to Extreme Loads

    Directory of Open Access Journals (Sweden)

    Králik Juraj

    2014-12-01

    Full Text Available This paper presents the experiences from the deterministic and probability analysis of the reliability of communication bridge structure resistance due to extreme loads - wind and earthquake. On the example of the steel bridge between two NPP buildings is considered the efficiency of the bracing systems. The advantages and disadvantages of the deterministic and probabilistic analysis of the structure resistance are discussed. The advantages of the utilization the LHS method to analyze the safety and reliability of the structures is presented

  4. Intracranial hypertension prediction using extremely randomized decision trees.

    Science.gov (United States)

    Scalzo, Fabien; Hamilton, Robert; Asgari, Shadnaz; Kim, Sunghan; Hu, Xiao

    2012-10-01

    Intracranial pressure (ICP) elevation (intracranial hypertension, IH) in neurocritical care is typically treated in a reactive fashion; it is only delivered after bedside clinicians notice prolonged ICP elevation. A proactive solution is desirable to improve the treatment of intracranial hypertension. Several studies have shown that the waveform morphology of the intracranial pressure pulse holds predictors about future intracranial hypertension and could therefore be used to alert the bedside clinician of a likely occurrence of the elevation in the immediate future. In this paper, a computational framework is proposed to predict prolonged intracranial hypertension based on morphological waveform features computed from the ICP. A key contribution of this work is to exploit an ensemble classifier method based on extremely randomized decision trees (Extra-Trees). Experiments on a representative set of 30 patients admitted for various intracranial pressure related conditions demonstrate the effectiveness of the predicting framework on ICP pulses acquired under clinical conditions and the superior results of the proposed approach in comparison to linear and AdaBoost classifiers. Copyright © 2011 IPEM. Published by Elsevier Ltd. All rights reserved.

  5. Verifying a computational method for predicting extreme ground motion

    Science.gov (United States)

    Harris, R.A.; Barall, M.; Andrews, D.J.; Duan, B.; Ma, S.; Dunham, E.M.; Gabriel, A.-A.; Kaneko, Y.; Kase, Y.; Aagaard, Brad T.; Oglesby, D.D.; Ampuero, J.-P.; Hanks, T.C.; Abrahamson, N.

    2011-01-01

    In situations where seismological data is rare or nonexistent, computer simulations may be used to predict ground motions caused by future earthquakes. This is particularly practical in the case of extreme ground motions, where engineers of special buildings may need to design for an event that has not been historically observed but which may occur in the far-distant future. Once the simulations have been performed, however, they still need to be tested. The SCEC-USGS dynamic rupture code verification exercise provides a testing mechanism for simulations that involve spontaneous earthquake rupture. We have performed this examination for the specific computer code that was used to predict maximum possible ground motion near Yucca Mountain. Our SCEC-USGS group exercises have demonstrated that the specific computer code that was used for the Yucca Mountain simulations produces similar results to those produced by other computer codes when tackling the same science problem. We also found that the 3D ground motion simulations produced smaller ground motions than the 2D simulations.

  6. Survey of extreme load design regulatory agency licensing requirements for nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Stevenson, J D

    1976-04-01

    Since 1965, when extreme load requirements began to be considered explicitly in nuclear power plant design, there has been a gradual divergence in requirements imposed by national regulatory agencies. However, nuclear plant safety is an international problem because of the potential international effects of any postulated plant failure. For this reason this paper has been prepared in an attempt to highlight the differences in national criteria currently used in the extreme load design of nuclear plant facilities. No attempt has been made to evaluate the relative merit of the criteria established by the various national regulatory agencies. This paper presents the results of a recent survey made of national atomic energy regulatory agencies and major nuclear steam supply design agencies, which requested a summary of current licensing criteria associated with earthquake, extreme wind (tornado), flood, airplane crash and accident (pipe break) loads applicable within the various national jurisdictions. Also presented are a number of comparisons which are meant to illustrate the differences in national regulatory criteria.

  7. Survey of extreme load design regulatory agency licensing requirements for nuclear power plants

    International Nuclear Information System (INIS)

    Stevenson, J.D.

    1976-01-01

    Since 1965, when extreme load requirements began to be considered explicitly in nuclear power plant design, there has been a gradual divergence in requirements imposed by national regulatory agencies. However, nuclear plant safety is an international problem because of the potential international effects of any postulated plant failure. For this reason this paper has been prepared in an attempt to highlight the differences in national criteria currently used in the extreme load design of nuclear plant facilities. No attempt has been made to evaluate the relative merit of the criteria established by the various national regulatory agencies. This paper presents the results of a recent survey made of national atomic energy regulatory agencies and major nuclear steam supply design agencies, which requested a summary of current licensing criteria associated with earthquake, extreme wind (tornado), flood, airplane crash and accident (pipe break) loads applicable within the various national jurisdictions. Also presented are a number of comparisons which are meant to illustrate the differences in national regulatory criteria. (Auth.)

  8. Investigating extreme event loading on coastal bridges using wireless sensor technology

    Science.gov (United States)

    Gelineau, Douglas A.; Davis, Justin R.; Rice, Jennifer A.

    2017-04-01

    Coastal infrastructure, such as bridges, are susceptible to many forms of coastal hazards: particularly hurricane surge and wave loading. These two forms of loading can cause catastrophic damage to aging highway infrastructure. It is estimated that storm damage costs the United States about $50 Billion per year. In light of this, it is crucial that we understand the damaging forces placed on infrastructure during storm events so that we can develop safer and more resilient coastal structures. This paper presents the ongoing research to enable the efficient collection of extreme event loads acting on both the substructure and superstructure of low clearance, simple span, reinforced concrete bridges. Bridges of this type were commonly constructed during the 1950's and 60's and are particularly susceptible to deck unseating caused by hurricane surge and wave loading. The sensing technology used to capture this data must be ruggedized to survive in an extremely challenging environment, be designed to allow for redundancy in the event of sensors or other network components being lost in the storm, and be relatively low cost to allow for more bridges to be instrumented per storm event. The prototype system described in this paper includes wireless technology, rapid data transmission, and, for the sensors, self-contained power. While this specific application focuses on hurricane hazards, the framework can be extended to include other natural hazards.

  9. Using the load-velocity relationship for 1RM prediction.

    Science.gov (United States)

    Jidovtseff, Boris; Harris, Nigel K; Crielaard, Jean-Michel; Cronin, John B

    2011-01-01

    The purpose of this study was to investigate the ability of the load-velocity relationship to accurately predict a bench press 1 repetition maximum (1RM). Data from 3 different bench press studies (n = 112) that incorporated both 1RM assessment and submaximal load-velocity profiling were analyzed. Individual regression analysis was performed to determine the theoretical load at zero velocity (LD0). Data from each of the 3 studies were analyzed separately and also presented as overall group mean. Thereafter, correlation analysis provided quantification of the relationships between 1RM and LD0. Practically perfect correlations (r = ∼0.95) were observed in our samples, confirming the ability of the load-velocity profile to accurately predict bench press 1RM.

  10. Locomotion With Loads: Practical Techniques for Predicting Performance Outcomes

    Science.gov (United States)

    2015-05-01

    Metabolic energy consumption as a function of speed and body size in birds and mammals. J Exp Biol. 97, 1-21. Weyand, P., Smith, B., Puyau, M. and...height, weight (including load), speed, and grade algorithms proposed will allow walking metabolic rates to be predicted to within 6.0 and 12.0% in...gait, metabolism , performance, load carriage 16. SECURITY CLASSIFICATION OF: Unclassified 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME

  11. Corrosion pit depth extreme value prediction from limited inspection data

    International Nuclear Information System (INIS)

    Najjar, D.; Bigerelle, M.; Iost, A.; Bourdeau, L.; Guillou, D.

    2004-01-01

    Passive alloys like stainless steels are prone to localized corrosion in chlorides containing environments. The greater the depth of the localized corrosion phenomenon, the more dramatic the related damage that can lead to a structure weakening by fast perforation. In practical situations, because measurements are time consuming and expensive, the challenge is usually to predict the maximum pit depth that could be found in a large scale installation from the processing of a limited inspection data. As far as the parent distribution of pit depths is assumed to be of exponential type, the most successful method was found in the application of the statistical extreme-value analysis developed by Gumbel. This study aims to present a new and alternative methodology to the Gumbel approach with a view towards accurately estimating the maximum pit depth observed on a ferritic stainless steel AISI 409 subjected to an accelerated corrosion test (ECC1) used in automotive industry. This methodology consists in characterising and modelling both the morphology of pits and the statistical distribution of their depths from a limited inspection dataset. The heart of the data processing is based on the combination of two recent statistical methods that avoid making any choice about the type of the theoretical underlying parent distribution of pit depths: the Generalized Lambda Distribution (GLD) is used to model the distribution of pit depths and the Bootstrap technique to determine a confidence interval on the maximum pit depth. (authors)

  12. Study on Predicting Axial Load Capacity of CFST Columns

    Science.gov (United States)

    Ravi Kumar, H.; Muthu, K. U.; Kumar, N. S.

    2017-11-01

    This work presents an analytical study and experimental study on the behaviour and ultimate load carrying capacity of axially compressed self-compacting concrete-filled steel tubular columns. Results of tests conducted by various researchers on 213 samples concrete-filled steel tubular columns are reported and present authors experimental data are reported. Two theoretical equations were derived for the prediction of the ultimate axial load strength of concrete-filled steel tubular columns. The results from prediction were compared with the experimental data. Validation to the experimental results was made.

  13. Lower extremity kinematics that correlate with success in lateral load transfers over a low friction surface.

    Science.gov (United States)

    Catena, Robert D; Xu, Xu

    2015-01-01

    We previously studied balance during lateral load transfers, but were left without explanation of why some individuals were successful in novel low friction conditions and others were not. Here, we retrospectively examined lower extremity kinematics between successful (SL) and unsuccessful (UL) groups to determine what characteristics may improve low friction performance. Success versus failure over a novel slippery surface was used to dichotomise 35 healthy working-age individuals into the two groups (SL and UL). Participants performed lateral load transfers over three sequential surface conditions: high friction, novel low friction, and practiced low friction. The UL group used a wide stance with rotation mostly at the hips during the high and novel low friction conditions. To successfully complete the practiced low friction task, they narrowed their stance and pivoted both feet and torso towards the direction of the load, similar to the SL group in all conditions. This successful kinematic method potentially results in reduced muscle demand throughout the task. Practitioner Summary: The reason for this paper is to retrospectively examine the different load transfer strategies that are used in a low friction lateral load transfer. We found stance width to be the major source of success, while sagittal plane motion was altered to potentially maintain balance.

  14. Cognitive load predicts point-of-care ultrasound simulator performance.

    Science.gov (United States)

    Aldekhyl, Sara; Cavalcanti, Rodrigo B; Naismith, Laura M

    2018-02-01

    The ability to maintain good performance with low cognitive load is an important marker of expertise. Incorporating cognitive load measurements in the context of simulation training may help to inform judgements of competence. This exploratory study investigated relationships between demographic markers of expertise, cognitive load measures, and simulator performance in the context of point-of-care ultrasonography. Twenty-nine medical trainees and clinicians at the University of Toronto with a range of clinical ultrasound experience were recruited. Participants answered a demographic questionnaire then used an ultrasound simulator to perform targeted scanning tasks based on clinical vignettes. Participants were scored on their ability to both acquire and interpret ultrasound images. Cognitive load measures included participant self-report, eye-based physiological indices, and behavioural measures. Data were analyzed using a multilevel linear modelling approach, wherein observations were clustered by participants. Experienced participants outperformed novice participants on ultrasound image acquisition. Ultrasound image interpretation was comparable between the two groups. Ultrasound image acquisition performance was predicted by level of training, prior ultrasound training, and cognitive load. There was significant convergence between cognitive load measurement techniques. A marginal model of ultrasound image acquisition performance including prior ultrasound training and cognitive load as fixed effects provided the best overall fit for the observed data. In this proof-of-principle study, the combination of demographic and cognitive load measures provided more sensitive metrics to predict ultrasound simulator performance. Performance assessments which include cognitive load can help differentiate between levels of expertise in simulation environments, and may serve as better predictors of skill transfer to clinical practice.

  15. Failure mitigation in software defined networking employing load type prediction

    KAUST Repository

    Bouacida, Nader

    2017-07-31

    The controller is a critical piece of the SDN architecture, where it is considered as the mastermind of SDN networks. Thus, its failure will cause a significant portion of the network to fail. Overload is one of the common causes of failure since the controller is frequently invoked by new flows. Even through SDN controllers are often replicated, the significant recovery time can be an overkill for the availability of the entire network. In order to overcome the problem of the overloaded controller failure in SDN, this paper proposes a novel controller offload solution for failure mitigation based on a prediction module that anticipates the presence of a harmful long-term load. In fact, the long-standing load would eventually overwhelm the controller leading to a possible failure. To predict whether the load in the controller is short-term or long-term load, we used three different classification algorithms: Support Vector Machine, k-Nearest Neighbors, and Naive Bayes. Our evaluation results demonstrate that Support Vector Machine algorithm is applicable for detecting the type of load with an accuracy of 97.93% in a real-time scenario. Besides, our scheme succeeded to offload the controller by switching between the reactive and proactive mode in response to the prediction module output.

  16. Seasonal Climate Extremes : Mechanism, Predictability and Responses to Global Warming

    NARCIS (Netherlands)

    Shongwe, M.E.

    2010-01-01

    Climate extremes are rarely occurring natural phenomena in the climate system. They often pose one of the greatest environmental threats to human and natural systems. Statistical methods are commonly used to investigate characteristics of climate extremes. The fitted statistical properties are often

  17. Assessment of extreme design loads for modern wind turbines using the probabilistic approach

    DEFF Research Database (Denmark)

    Abdallah, Imad

    There is a large drive to reduce the cost of energy of wind energy generators. Various tracks are being considered such as enhanced O&M strategies through condition monitoring, increased manufacturing efficiency through higher production volumes and increased automation, improved resource...... and drag coefficients showed (a) a tangible reduction in the load partial safety factor for a blade and (b) generally a larger impact on extreme loads during power production compared to stand-still. Therefore, the way forward is for wind turbine manufactures to further update the stochastic model...... assessment through turbine-mounted real-time site assessment technologies, improved components reliability by increased laboratory testing, increased number of prototype test turbines before serial production, larger rotor and tower concepts for both onshore and offshore installations, advanced drive train...

  18. MESSENGER Observations of Extreme Loading and Unloading of Mercury's Magnetic Tail

    Science.gov (United States)

    Slavin, James A.; Anderson, Brian J.; Baker, Daniel N.; Benna, Mehdi; Boardsen, Scott A.; Gloeckler, George; Gold, Robert E.; Ho, George C.; Korth, Haje; Krimigis, Stamatios M.; hide

    2010-01-01

    During MESSENGER's third flyby of Mercury, the magnetic field in the planet's magnetotail increased by factors of 2 to 3.5 over intervals of 2 to 3 min. Magnetospheric substorms at Earth are powered by similar tail loading, but the amplitude is approx.10 times less and typical durations are approx.1 hour. The extreme tail loading observed at Mercury implies that the relative intensity of sub storms must be much larger than at Earth. The correspondence between the duration of tail field enhancements and the characteristic time for the Dungey cycle, which describes plasma circulation through Mercury's magnetosphere. suggests that such circulation determines substorm timescale. A key aspect of tail unloading during terrestrial substorms is the acceleration of energetic charged particles, but no acceleration signatures were seen during the MESSENGER flyby.

  19. Short-Term Electricity-Load Forecasting Using a TSK-Based Extreme Learning Machine with Knowledge Representation

    Directory of Open Access Journals (Sweden)

    Chan-Uk Yeom

    2017-10-01

    Full Text Available This paper discusses short-term electricity-load forecasting using an extreme learning machine (ELM with automatic knowledge representation from a given input-output data set. For this purpose, we use a Takagi-Sugeno-Kang (TSK-based ELM to develop a systematic approach to generating if-then rules, while the conventional ELM operates without knowledge information. The TSK-ELM design includes a two-phase development. First, we generate an initial random-partition matrix and estimate cluster centers for random clustering. The obtained cluster centers are used to determine the premise parameters of fuzzy if-then rules. Next, the linear weights of the TSK fuzzy type are estimated using the least squares estimate (LSE method. These linear weights are used as the consequent parameters in the TSK-ELM design. The experiments were performed on short-term electricity-load data for forecasting. The electricity-load data were used to forecast hourly day-ahead loads given temperature forecasts; holiday information; and historical loads from the New England ISO. In order to quantify the performance of the forecaster, we use metrics and statistical characteristics such as root mean squared error (RMSE as well as mean absolute error (MAE, mean absolute percent error (MAPE, and R-squared, respectively. The experimental results revealed that the proposed method showed good performance when compared with a conventional ELM with four activation functions such sigmoid, sine, radial basis function, and rectified linear unit (ReLU. It possessed superior prediction performance and knowledge information and a small number of rules.

  20. Prediction-based dynamic load-sharing heuristics

    Science.gov (United States)

    Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.

    1993-01-01

    The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.

  1. Integrity of reinforced concrete cooling towers under extreme loads: Wind and earthquake

    International Nuclear Information System (INIS)

    Louhi, Amine

    2015-01-01

    The authorities have planned to increase the lifetime of currently operating nuclear power plants. The ageing of reinforced concrete structures such as cooling towers should be evaluated and its impact on the bearing capacity calculated. In the case of significant damage, the strengthening must be considered to ensure the sustainability of these towers facing the risk of storms and earthquakes becoming more and more frequent. This work aims to quantify the adverse effects that can generate concrete cracks and rebar section loss induced by corrosion, especially on the bearing capacity of nuclear power plant cooling towers under monotonic or cyclic extreme load conditions (wind and earthquake). These loads are certainly the most severe, since they take the structure into the nonlinear domain and can induce or amplify cracking damage. Numerical simulations are proposed to determine the quasi-static or dynamic response of the structure, taking into account appearance of concrete cracks and their evolution via an appropriate material concrete law and rebar's yielding. In the case of a seismic load, the responses are evaluated by three different methods; the nonlinear response history analysis (NLRHA), the response spectrum analysis and the modal response history analysis (MRHA) in order to compare the earthquake modeling approaches and to evaluate the robustness of the results. Parametric studies on damping, load combinations and structural configurations, are also performed. In the case of a wind load, the strengthening technique using composite materials, such as carbon fiber reinforced plastic (CFRP) is modeled. The behavior of the damaged structure with an advanced corrosion rate is estimated in the pre- and post-cracking regime, compared to the undamaged structure. The drop of bearing capacity is quantified, a reinforcement designed is proposed to restore the integrity and thus increase the lifetime of the structure. (author)

  2. The measured contribution of whipping and springing on the fatigue and extreme loading of container vessels

    Science.gov (United States)

    Storhaug, Gaute

    2014-12-01

    Whipping/springing research started in the 50'ies. In the 60'ies inland water vessels design rules became stricter due to whipping/springing. The research during the 70-90'ies may be regarded as academic. In 2000 a large ore carrier was strengthened due to severe cracking from North Atlantic operation, and whipping/springing contributed to half of the fatigue damage. Measurement campaigns on blunt and slender vessels were initiated. A few blunt ships were designed to account for whipping/springing. Based on the measurements, the focus shifted from fatigue to extreme loading. In 2005 model tests of a 4,400 TEU container vessel included extreme whipping scenarios. In 2007 the 4400 TEU vessel MSC Napoli broke in two under similar conditions. In 2009 model tests of an 8,600 TEU container vessel container vessel included extreme whipping scenarios. In 2013 the 8,100 TEU vessel MOL COMFORT broke in two under similar conditions. Several classification societies have published voluntary guidelines, which have been used to include whipping/springing in the design of several container vessels. This paper covers results from model tests and full scale measurements used as background for the DNV Legacy guideline. Uncertainties are discussed and recommendations are given in order to obtain useful data. Whipping/springing is no longer academic.

  3. Predictability of Extreme Precipitations Over the Conterminous us, 1949-2010

    Science.gov (United States)

    Jiang, M.; Felzer, B. S.

    2015-12-01

    Extreme precipitation plays an important role in regulating ecosystem services. Precipitation extremes vary in magnitude and duration both spatially and temporally, making it one of the most challenging climate variables to comprehend and predict. Using information theory, we provide an attempt to improve understanding of the predictability of extreme precipitation in the conterminous U.S. over the period of 1949-2010. We define predictability as the recurrent likelihood of patterns described by the measures of constancy and contingency, with the former describing the inter-annual variability and the latter describing the seasonality. This study shows that there are clear west-east contrasts of predictability over the U.S. landscape, with a generally decreasing gradient from the Northeast to the Southwest for intensity-based extremes and a generally increasing gradient from the West to the East for duration-based extremes. We further identify spatially heterogeneous patterns of temporal changes in predictability over the investigated timeframe. Finally, it is evident that constancy plays a heavier role in regulating predictability increases for both intensity and duration-based extremes and for predictability decreases for duration-based extremes, while contingency contributes equally with constancy to determining the decreases in predictability for intensity-based extremes.

  4. Analysis of extreme wind events at Høvsøre and the effect on wind turbine loads

    DEFF Research Database (Denmark)

    Hannesdóttir, Ásta; Kelly, Mark C.; Mann, Jakob

    used to simulate wind turbine response in time domain. The simulations are made for the DTU 10 MW reference wind turbine. Load analysis shows that the maximum tilt moment on the tower yaw bearing correlates well with the wind shear of the measurements. When these loads are compared with the extreme...... wind shear load case of the IEC standards, it is seen that they are of similar magnitude and in one case even higher....

  5. Cognitive task load in a naval ship control centre: from identification to prediction.

    Science.gov (United States)

    Grootjen, M; Neerincx, M A; Veltman, J A

    Deployment of information and communication technology will lead to further automation of control centre tasks and an increasing amount of information to be processed. A method for establishing adequate levels of cognitive task load for the operators in such complex environments has been developed. It is based on a model distinguishing three load factors: time occupied, task-set switching, and level of information processing. Application of the method resulted in eight scenarios for eight extremes of task load (i.e. low and high values for each load factor). These scenarios were performed by 13 teams in a high-fidelity control centre simulator of the Royal Netherlands Navy. The results show that the method provides good prediction of the task load that will actually appear in the simulator. The model allowed identification of under- and overload situations showing negative effects on operator performance corresponding to controlled experiments in a less realistic task environment. Tools proposed to keep the operator at an optimum task load are (adaptive) task allocation and interface support.

  6. CAN UPPER EXTREMITY FUNCTIONAL TESTS PREDICT THE SOFTBALL THROW FOR DISTANCE: A PREDICTIVE VALIDITY INVESTIGATION

    Science.gov (United States)

    Hanney, William J.; Kolber, Morey J.; Davies, George J.; Riemann, Bryan

    2011-01-01

    Introduction: Understanding the relationships between performance tests and sport activity is important to the rehabilitation specialist. The purpose of this study was two- fold: 1) To identify if relationships exist between tests of upper body strength and power (Single Arm Seated Shot Put, Timed Push-Up, Timed Modified Pull-Up, and The Davies Closed Kinetic Chain Upper Extremity Stability Test, and the softball throw for distance), 2) To determine which variable or group of variables best predicts the performance of a sport specific task (the softball throw for distance). Methods: One hundred eighty subjects (111 females and 69 males, aged 18-45 years) performed the 5 upper extremity tests. The Pearson product moment correlation and a stepwise regression were used to determine whether relationships existed between performance on the tests and which upper extremity test result best explained the performance on the softball throw for distance. Results: There were significant correlations (r=.33 to r=.70, p=0.001) between performance on all of the tests. The modified pull-up test was the best predictor of the performance on the softball throw for distance (r2= 48.7), explaining 48.7% of variation in performance. When weight, height, and age were added to the regression equation the r2 values increased to 64.5, 66.2, and 67.5 respectively. Conclusion: The results of this study indicate that several upper extremity tests demonstrate significant relationships with one another and with the softball throw for distance. The modified pull up test was the best predictor of performance on the softball throw for distance. PMID:21712942

  7. Forecasting Strategies for Predicting Peak Electric Load Days

    Science.gov (United States)

    Saxena, Harshit

    Academic institutions spend thousands of dollars every month on their electric power consumption. Some of these institutions follow a demand charges pricing structure; here the amount a customer pays to the utility is decided based on the total energy consumed during the month, with an additional charge based on the highest average power load required by the customer over a moving window of time as decided by the utility. Therefore, it is crucial for these institutions to minimize the time periods where a high amount of electric load is demanded over a short duration of time. In order to reduce the peak loads and have more uniform energy consumption, it is imperative to predict when these peaks occur, so that appropriate mitigation strategies can be developed. The research work presented in this thesis has been conducted for Rochester Institute of Technology (RIT), where the demand charges are decided based on a 15 minute sliding window panned over the entire month. This case study makes use of different statistical and machine learning algorithms to develop a forecasting strategy for predicting the peak electric load days of the month. The proposed strategy was tested for a whole year starting May 2015 to April 2016 during which a total of 57 peak days were observed. The model predicted a total of 74 peak days during this period, 40 of these cases were true positives, hence achieving an accuracy level of 70 percent. The results obtained with the proposed forecasting strategy are promising and demonstrate an annual savings potential worth about $80,000 for a single submeter of RIT.

  8. Analysis of Global Sensitivity of Landing Variables on Landing Loads and Extreme Values of the Loads in Carrier-Based Aircrafts

    Directory of Open Access Journals (Sweden)

    Jin Zhou

    2018-01-01

    Full Text Available When a carrier-based aircraft is in arrested landing on deck, the impact loads on landing gears and airframe are closely related to landing states. The distribution and extreme values of the landing loads obtained during life-cycle analysis provide an important basis for buffering parameter design and fatigue design. In this paper, the effect of the multivariate distribution was studied based on military standards and guides. By establishment of a virtual prototype, the extended Fourier amplitude sensitivity test (EFAST method is applied on sensitivity analysis of landing variables. The results show that sinking speed and rolling angle are the main influencing factors on the landing gear’s course load and vertical load; sinking speed, rolling angle, and yawing angle are the main influencing factors on the landing gear’s lateral load; and sinking speed is the main influencing factor on the barycenter overload. The extreme values of loads show that the typical condition design in the structural strength analysis is safe. The maximum difference value of the vertical load of the main landing gear is 12.0%. This research may provide some reference for structure design of landing gears and compilation of load spectrum for carrier-based aircrafts.

  9. Model of analysis of maximum loads in wind generators produced by extreme winds

    International Nuclear Information System (INIS)

    Herrera – Sánchez, Omar; Schellong, Wolfgang; González – Fernández, Vladimir

    2010-01-01

    The use of the wind energy by means of the wind turbines in areas of high risk of occurrence of Hurricanes comes being an important challenge for the designers of wind farm at world for some years. The wind generator is not usually designed to support this type of phenomena, for this reason the areas of high incidence of tropical hurricanes of the planning are excluded, that which, in occasions disables the use of this renewable source of energy totally, either because the country is very small, or because it coincides the area of more potential fully with that of high risk. To counteract this situation, a model of analysis of maxims loads has been elaborated taken place the extreme winds in wind turbines of great behavior. This model has the advantage of determining, in a chosen place, for the installation of a wind farm, the micro-areas with higher risk of wind loads above the acceptable for the standard classes of wind turbines. (author)

  10. Extreme value prediction of the wave-induced vertical bending moment in large container ships

    DEFF Research Database (Denmark)

    Andersen, Ingrid Marie Vincent; Jensen, Jørgen Juncher

    2015-01-01

    increase the extreme hull girder response significantly. Focus in the present paper is on the influence of the hull girder flexibility on the extreme response amidships, namely the wave-induced vertical bending moment (VBM) in hogging, and the prediction of the extreme value of the same. The analysis...... in the present paper is based on time series of full scale measurements from three large container ships of 8600, 9400 and 14000 TEU. When carrying out the extreme value estimation the peak-over-threshold (POT) method combined with an appropriate extreme value distribution is applied. The choice of a proper...... threshold level as well as the statistical correlation between clustered peaks influence the extreme value prediction and are taken into consideration in the present paper....

  11. Data-Driven Predictive Direct Load Control of Refrigeration Systems

    DEFF Research Database (Denmark)

    Shafiei, Seyed Ehsan; Knudsen, Torben; Wisniewski, Rafal

    2015-01-01

    A predictive control using subspace identification is applied for the smart grid integration of refrigeration systems under a direct load control scheme. A realistic demand response scenario based on regulation of the electrical power consumption is considered. A receding horizon optimal control...... is proposed to fulfil two important objectives: to secure high coefficient of performance and to participate in power consumption management. Moreover, a new method for design of input signals for system identification is put forward. The control method is fully data driven without an explicit use of model...... against real data. The performance improvement results in a 22% reduction in the energy consumption. A comparative simulation is accomplished showing the superiority of the method over the existing approaches in terms of the load following performance....

  12. Predictive Solar-Integrated Commercial Building Load Control

    Energy Technology Data Exchange (ETDEWEB)

    Glasgow, Nathan [EdgePower Inc., Aspen, CO (United States)

    2017-01-31

    This report is the final technical report for the Department of Energy SunShot award number EE0007180 to EdgePower Inc., for the project entitled “Predictive Solar-Integrated Commercial Building Load Control.” The goal of this project was to successfully prove that the integration of solar forecasting and building load control can reduce demand charge costs for commercial building owners with solar PV. This proof of concept Tier 0 project demonstrated its value through a pilot project at a commercial building. This final report contains a summary of the work completed through he duration of the project. Clean Power Research was a sub-recipient on the award.

  13. Model Predictive Control for Load Frequency Control with Wind Turbines

    Directory of Open Access Journals (Sweden)

    Yi Zhang

    2015-01-01

    Full Text Available Reliable load frequency (LFC control is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control (DMPC based on coordination scheme. The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The scheme incorporates the two critical nonlinear constraints, for example, the generation rate constraint (GRC and the valve limit, into convex optimization problems. Furthermore, the algorithm reduces the impact on the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and that without the participation of the wind turbines is carried out. Good performance is obtained in the presence of power system nonlinearities due to the governors and turbines constraints and load change disturbances.

  14. Mechanistic Modeling Framework for Predicting Extreme Battery Response

    Energy Technology Data Exchange (ETDEWEB)

    Moffat, Harry K.; Geller, Anthony S.; R. Kee (CSM); S. Allu (ORNL)

    2017-03-01

    The objective of this project was to Address root cause and implications of thermal runaway of Li-ion batteries by delivering a software architecture solution that can lead to the development of predictive mechanisms that are based on identification of species.

  15. Mechanistic Modeling Framework for Predicting Extreme Battery Response

    Energy Technology Data Exchange (ETDEWEB)

    Geller, Anthony S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2014-11-01

    The objectives of this project are to address the root cause implications of thermal runaway of Li-ion batteries by delivering a software architecture solution that can lead to the development of predictive mechanisms that are based on identification of species.

  16. Predicting the extreme 2015/16 El Nino event

    CSIR Research Space (South Africa)

    Mpheshea, LE

    2015-09-01

    Full Text Available A strong El Niño phenomenon is expected to develop during the austral summer. This study seeks to address the two main questions. 1) How strong will the 2016 event be? 2) With how much skill and confidence can a really strong event be predicted? A...

  17. Predicting Tail Buffet Loads of a Fighter Airplane

    Science.gov (United States)

    Moses, Robert W.; Pototzky, Anthony S.

    2006-01-01

    Buffet loads on aft aerodynamic surfaces pose a recurring problem on most twin-tailed fighter airplanes: During maneuvers at high angles of attack, vortices emanating from various surfaces on the forward parts of such an airplane (engine inlets, wings, or other fuselage appendages) often burst, immersing the tails in their wakes. Although these vortices increase lift, the frequency contents of the burst vortices become so low as to cause the aft surfaces to vibrate destructively. Now, there exists a new analysis capability for predicting buffet loads during the earliest design phase of a fighter-aircraft program. In effect, buffet pressures are applied to mathematical models in the framework of a finite-element code, complete with aeroelastic properties and working knowledge of the spatiality of the buffet pressures for all flight conditions. The results of analysis performed by use of this capability illustrate those vibratory modes of a tail fin that are most likely to be affected by buffet loads. Hence, the results help in identifying the flight conditions during which to expect problems. Using this capability, an aircraft designer can make adjustments to the airframe and possibly the aerodynamics, leading to a more robust design.

  18. Lower extremity injuries in runners. Advances in prediction.

    Science.gov (United States)

    Macera, C A

    1992-01-01

    Recreational and competitive running is practised by many individuals to improve cardiorespiratory function and general well-being. The major negative aspect of running is the high rate of injuries to the lower extremities. Several well-designed population-based studies have found no major differences in injury rates between men and women; no increasing effect of age on injuries; a declining injury rate with more years of running experience; no substantial effect of weight or height; an uncertain effect of psychological factors; and a strong effect of previous injury on future injuries. Among the modifiable risk factors studied, weekly distance is the strongest predictor of future injuries. Other training characteristics (speed, frequency, surface, timing) have little or no effect on future injuries after accounting for distance run. More studies are needed to address the effects of appropriate stretching practices and abrupt change in training patterns. For recreational runners who have sustained injuries, especially within the past year, a reduction in running to below 32 km per week is recommended. For those about to begin a running programme, moderation is the best advice. For competitive runners, great care should be taken to ensure that prior injuries are sufficiently healed before attempting any racing event, particularly a marathon.

  19. Fatigue life prediction of oil ducts under service loads

    Energy Technology Data Exchange (ETDEWEB)

    Meggiolaro, Marco A.; Castro, Jaime T.P. [Pontificia Univ. Catolica do Rio de Janeiro, RJ (Brazil)

    2003-07-01

    A methodology to calculate the residual initiation and propagation lives of fatigue cracks in oil pipelines with corrosion-like defects is proposed and applied to predict the residual life of an old duct made of API 5L Gr. B steel, in service for more than 40 years. Since its inauguration, this pipeline has carried several heated products under variable temperatures and pressures. The calculated (nominal) service stresses are very high, due to thermal loads that induce significant bending in curved parts of the duct, with peaks close to the yield strength of the steel. The elastic- plastic fatigue damage at a notch or a corrosion pit root is calculated using the {epsilon}N method, and the effects of surface semi-elliptical cracks in its internal (or external) wall is studied considering appropriate stress intensity factor expressions and the actual service loads. In the presence of surface flaws associated to stress concentration factors of the order of three, a fatigue crack likely will initiate in the pipeline. However, if these surface cracks are small compared to the duct wall thickness, their predicted propagation rates are very low. (author)

  20. Lifetime prediction of structures submitted to thermal fatigue loadings

    International Nuclear Information System (INIS)

    Amiable, S.

    2006-01-01

    The aim of this work is to predict the lifetime of structures submitted to thermal fatigue loadings. This work lies within the studies undertaken by the CEA on the thermal fatigue problems from the french reactor of Civaux. In particular we study the SPLASH test: a specimen is heated continuously and cyclically cooled down by a water spray. This loading generates important temperature gradients in space and time and leads to the initiation and the propagation of a crack network. We propose a new thermo-mechanical model to simulate the SPLASH experiment and we propose a new fatigue criterion to predict the lifetime of the SPLASH specimen. We propose and compare several numerical models with various complexity to estimate the mechanical response of the SPLASH specimen. The practical implications of this work are the reevaluation of the hypothesis used in the French code RCC, which are used to simulate thermal shock and to interpret the results in terms of fatigue. This work leads to new perspectives on the mechanical interpretation of the fatigue criterion. (author)

  1. Spatial extreme learning machines: An application on prediction of disease counts.

    Science.gov (United States)

    Prates, Marcos O

    2018-01-01

    Extreme learning machines have gained a lot of attention by the machine learning community because of its interesting properties and computational advantages. With the increase in collection of information nowadays, many sources of data have missing information making statistical analysis harder or unfeasible. In this paper, we present a new model, coined spatial extreme learning machine, that combine spatial modeling with extreme learning machines keeping the nice properties of both methodologies and making it very flexible and robust. As explained throughout the text, the spatial extreme learning machines have many advantages in comparison with the traditional extreme learning machines. By a simulation study and a real data analysis we present how the spatial extreme learning machine can be used to improve imputation of missing data and uncertainty prediction estimation.

  2. Ultramarathon is an outstanding model for the study of adaptive responses to extreme load and stress

    Directory of Open Access Journals (Sweden)

    Millet Grégoire P

    2012-07-01

    Full Text Available Abstract Ultramarathons comprise any sporting event involving running longer than the traditional marathon length of 42.195 km (26.2 miles. Studies on ultramarathon participants can investigate the acute consequences of ultra-endurance exercise on inflammation and cardiovascular or renal consequences, as well as endocrine/energetic aspects, and examine the tissue recovery process over several days of extreme physical load. In a study published in BMC Medicine, Schütz et al. followed 44 ultramarathon runners over 4,487 km from South Italy to North Cape, Norway (the Trans Europe Foot Race 2009 and recorded daily sets of data from magnetic resonance imaging, psychometric, body composition and biological measurements. The findings will allow us to better understand the timecourse of degeneration/regeneration of some lower leg tissues such as knee joint cartilage, to differentiate running-induced from age-induced pathologies (for example, retropatelar arthritis and finally to assess the interindividual susceptibility to injuries. Moreover, it will also provide new information about the complex interplay between cerebral adaptations/alterations and hormonal influences resulting from endurance exercise and provide data on the dose-response relationship between exercise and brain structure/function. Overall, this study represents a unique attempt to investigate the limits of the adaptive response of human bodies. Please see related article: http://www.biomedcentral.com/1741-7015/10/78

  3. Reliability prediction for structures under cyclic loads and recurring inspections

    Directory of Open Access Journals (Sweden)

    Alberto W. S. Mello Jr

    2009-06-01

    Full Text Available This work presents a methodology for determining the reliability of fracture control plans for structures subjected to cyclic loads. It considers the variability of the parameters involved in the problem, such as initial flaw and crack growth curve. The probability of detection (POD curve of the field non-destructive inspection method and the condition/environment are used as important factors for structural confidence. According to classical damage tolerance analysis (DTA, inspection intervals are based on detectable crack size and crack growth rate. However, all variables have uncertainties, which makes the final result totally stochastic. The material properties, flight loads, engineering tools and even the reliability of inspection methods are subject to uncertainties which can affect significantly the final maintenance schedule. The present methodology incorporates all the uncertainties in a simulation process, such as Monte Carlo, and establishes a relationship between the reliability of the overall maintenance program and the proposed inspection interval, forming a “cascade” chart. Due to the scatter, it also defines the confidence level of the “acceptable” risk. As an example, the damage tolerance analysis (DTA results are presented for the upper cockpit longeron splice bolt of the BAF upgraded F-5EM. In this case, two possibilities of inspection intervals were found: one that can be characterized as remote risk, with a probability of failure (integrity nonsuccess of 1 in 10 million, per flight hour; and other as extremely improbable, with a probability of nonsuccess of 1 in 1 billion, per flight hour, according to aviation standards. These two results are compared with the classical military airplane damage tolerance requirements.

  4. Potential Hydrodynamic Loads on Coastal Bridges in the Greater New York Area due to Extreme Storm Surge and Wave

    Science.gov (United States)

    2018-04-18

    This project makes a computer modeling study on vulnerability of coastal bridges in New York City (NYC) metropolitan region to storm surges and waves. Prediction is made for potential surges and waves in the region and consequent hydrodynamic load an...

  5. Footbridge Response Predictions and Their Sensitivity to Stochastic Load Assumptions

    DEFF Research Database (Denmark)

    Pedersen, Lars; Frier, Christian

    2011-01-01

    Knowledge about footbridges response to actions of walking is important in assessments of vibration serviceability. In a number of design codes for footbridges, the vibration serviceability limit state is assessed using a walking load model in which the walking parameters (step frequency, pedestr......Knowledge about footbridges response to actions of walking is important in assessments of vibration serviceability. In a number of design codes for footbridges, the vibration serviceability limit state is assessed using a walking load model in which the walking parameters (step frequency...... of pedestrians for predicting footbridge response, which is meaningful, and a step forward. Modelling walking parameters stochastically, however, requires decisions to be made in terms of their statistical distribution and the parameters describing the statistical distribution. The paper investigates...... the sensitivity of results of computations of bridge response to some of the decisions to be made in this respect. This is a useful approach placing focus on which decisions (and which information) are important for sound estimation of bridge response. The studies involve estimating footbridge responses using...

  6. Prediction of dynamic blade loading of the Francis-99 turbine

    International Nuclear Information System (INIS)

    Nicolle, J; Cupillard, S

    2015-01-01

    CFD simulations focusing on capturing dynamic fluctuations of the flow for three operating points were performed for a scale model of a high head Francis turbine. A mesh sensitivity study showed an influence of the near wall resolution, consequently a low Reynolds mesh with a SST turbulence model was used. Rotor/stator fluctuations are well reproduced with the full turbine simulation at all operating points. Velocity contours and average velocity profiles from LDV measurements in the draft tube confirm that the flow physics is generally well reproduced. Simplified approaches such as profile transform and Fourier transform underestimated the measured fluctuations. As full turbine simulations were time-consuming, a simulation with only the draft tube was performed at part load to predict the fluctuations in the draft tube cone. The SAS-SST turbulence model was able to capture the vortex rope behavior

  7. Fast core prediction simulator for load follow control

    International Nuclear Information System (INIS)

    Yim, Man Sung; Lee, Sang Hoon; Lee, Un Chul

    1990-01-01

    An operator-assisting system for the reactor core control under power changing operating condition was developed. The system is consisted of core simulator routine and Xenon and Iodine initial condition generation routine. The initial condition generation routine, without exactly knowing the core status, is capable of providing accurate number densities and axial offset conditions of Xenon and Iodine after several hours of predictor- corrector calculations using the plant instrumentation signals of power level and power axial offset. The core simulator routine, even with the two node core model, gives equivalently accurate results as the one-dimensional model for the core behaviour simulation under power changing condition and can provide proper control strategies for load follow operation. The core simulator can also be used by the operator to develop remedial actions to restore the distorted power distribution by using its prediction capability

  8. A Deep Learning Prediction Model Based on Extreme-Point Symmetric Mode Decomposition and Cluster Analysis

    OpenAIRE

    Li, Guohui; Zhang, Songling; Yang, Hong

    2017-01-01

    Aiming at the irregularity of nonlinear signal and its predicting difficulty, a deep learning prediction model based on extreme-point symmetric mode decomposition (ESMD) and clustering analysis is proposed. Firstly, the original data is decomposed by ESMD to obtain the finite number of intrinsic mode functions (IMFs) and residuals. Secondly, the fuzzy c-means is used to cluster the decomposed components, and then the deep belief network (DBN) is used to predict it. Finally, the reconstructed ...

  9. Framing Failures in Wood-Frame Hip Roofs under Extreme Wind Loads

    Directory of Open Access Journals (Sweden)

    Sarah A. Stevenson

    2018-02-01

    Full Text Available Wood-frame residential roof failures are among the most common and expensive types of wind damage. Hip roofs are commonly understood to be more resilient during extreme wind in relation to gable roofs. However, inspection of damage survey data from recent tornadoes has revealed a previously unstudied failure mode in which hip roofs suffer partial failure of the framing structure. In the current study, evidence of partial framing failures and statistics of their occurrence are explored and discussed, while the common roof design and construction practice are reviewed. Two-dimensional finite element models are developed to estimate the element-level load effects on hip roof trusses and stick-frame components. The likelihood of failure in each member is defined based on relative demand-to-capacity ratios. Trussed and stick-frame structures are compared to assess the relative performance of the two types of construction. The present analyses verify the common understanding that toenailed roof-to-wall connections are likely to be the most vulnerable elements in the structure of a wood-frame hip roof. However, the results also indicate that certain framing members and connections display significant vulnerability under the same wind uplift, and the possibility of framing failure is not to be discounted. Furthermore, in the case where the roof-to-wall connection uses hurricane straps, certain framing members and joints become the likely points of failure initiation. The analysis results and damage survey observations are used to expand the understanding of wood-frame residential roof failures, as they relate to the Enhanced Fujita Scale and provide assessment of potential gaps in residential design codes.

  10. Prognostic factors for specific lower extremity and spinal musculoskeletal injuries identified through medical screening and training load monitoring in professional football (soccer): a systematic review

    Science.gov (United States)

    Sergeant, Jamie C; Parkes, Matthew J; Callaghan, Michael J

    2017-01-01

    Background Medical screening and load monitoring procedures are commonly used in professional football to assess factors perceived to be associated with injury. Objectives To identify prognostic factors (PFs) and models for lower extremity and spinal musculoskeletal injuries in professional/elite football players from medical screening and training load monitoring processes. Methods The MEDLINE, AMED, EMBASE, CINAHL Plus, SPORTDiscus and PubMed electronic bibliographic databases were searched (from inception to January 2017). Prospective and retrospective cohort studies of lower extremity and spinal musculoskeletal injury incidence in professional/elite football players aged between 16 and 40 years were included. The Quality in Prognostic Studies appraisal tool and the modified Grading of Recommendations Assessment, Development and Evaluation synthesis approach was used to assess the quality of the evidence. Results Fourteen studies were included. 16 specific lower extremity injury outcomes were identified. No spinal injury outcomes were identified. Meta-analysis was not possible due to heterogeneity and study quality. All evidence related to PFs and specific lower extremity injury outcomes was of very low to low quality. On the few occasions where multiple studies could be used to compare PFs and outcomes, only two factors demonstrated consensus. A history of previous hamstring injuries (HSI) and increasing age may be prognostic for future HSI in male players. Conclusions The assumed ability of medical screening tests to predict specific musculoskeletal injuries is not supported by the current evidence. Screening procedures should currently be considered as benchmarks of function or performance only. The prognostic value of load monitoring modalities is unknown. PMID:29177074

  11. Influential Factors for Accurate Load Prediction in a Demand Response Context

    DEFF Research Database (Denmark)

    Wollsen, Morten Gill; Kjærgaard, Mikkel Baun; Jørgensen, Bo Nørregaard

    2016-01-01

    Accurate prediction of a buildings electricity load is crucial to respond to Demand Response events with an assessable load change. However, previous work on load prediction lacks to consider a wider set of possible data sources. In this paper we study different data scenarios to map the influence....... Next, the time of day that is being predicted greatly influence the prediction which is related to the weather pattern. By presenting these results we hope to improve the modeling of building loads and algorithms for Demand Response planning.......Accurate prediction of a buildings electricity load is crucial to respond to Demand Response events with an assessable load change. However, previous work on load prediction lacks to consider a wider set of possible data sources. In this paper we study different data scenarios to map the influence...

  12. Extreme value modeling for the analysis and prediction of time series of extreme tropospheric ozone levels: a case study.

    Science.gov (United States)

    Escarela, Gabriel

    2012-06-01

    The occurrence of high concentrations of tropospheric ozone is considered as one of the most important issues of air management programs. The prediction of dangerous ozone levels for the public health and the environment, along with the assessment of air quality control programs aimed at reducing their severity, is of considerable interest to the scientific community and to policy makers. The chemical mechanisms of tropospheric ozone formation are complex, and highly variable meteorological conditions contribute additionally to difficulties in accurate study and prediction of high levels of ozone. Statistical methods offer an effective approach to understand the problem and eventually improve the ability to predict maximum levels of ozone. In this paper an extreme value model is developed to study data sets that consist of periodically collected maxima of tropospheric ozone concentrations and meteorological variables. The methods are applied to daily tropospheric ozone maxima in Guadalajara City, Mexico, for the period January 1997 to December 2006. The model adjusts the daily rate of change in ozone for concurrent impacts of seasonality and present and past meteorological conditions, which include surface temperature, wind speed, wind direction, relative humidity, and ozone. The results indicate that trend, annual effects, and key meteorological variables along with some interactions explain the variation in daily ozone maxima. Prediction performance assessments yield reasonably good results.

  13. Full Scale Test SSP 34m blade, edgewise loading LTT. Extreme load and PoC_InvE Data report

    DEFF Research Database (Denmark)

    Nielsen, Magda; Roczek-Sieradzan, Agnieszka; Jensen, Find Mølholt

    This report is the second report covering the research and demonstration project “Eksperimentel vingeforskning: Strukturelle mekanismer i nutidens og fremtidens store vinger under kombineret last”, supported by the EUDP program. A 34m wind turbine blade from SSP-Technology A/S has been tested...... in edgewise direction (LTT). The blade has been submitted to thorough examination by means of strain gauges, displacement transducers and a 3D optical measuring system. This data report presents results obtained during full scale testing of the blade up to 80% Risø load, where 80% Risø load corresponds to 100...... stresses in the adhesive joints. Test results from measurements with the reinforcement have been compared to results without the coupling. The report presents only the relevant results for the 80% Risø load and the results applicable for the investigation of the influence of the invention on the profile...

  14. Reliability and validity of a low load endurance strength test for upper and lower extremities in patients with fibromyalgia.

    Science.gov (United States)

    Munguía-Izquierdo, Diego; Legaz-Arrese, Alejandro

    2012-11-01

    To evaluate the reliability, standard error of the mean (SEM), clinical significant change, and known group validity of 2 assessments of endurance strength to low loads in patients with fibromyalgia syndrome (FS). Cross-sectional reliability and comparative study. University Pablo de Olavide, Seville, Spain. Middle-aged women with FS (n=95) and healthy women (n=64) matched for age, weight, and body mass index (BMI) were recruited for the study. Not applicable. The endurance strength to low loads tests of the upper and lower extremities and anthropometric measures (BMI) were used for the evaluations. The differences between the readings (tests 1 and 2) and the SDs of the differences, intraclass correlation coefficient (ICC) model (2,1), 95% confidence interval for the ICC, coefficient of repeatability, intrapatient SD, SEM, Wilcoxon signed-rank test, and Bland-Altman plots were used to examine reliability. A Mann-Whitney U test was used to analyze the differences in test values between the patient group and the control group. We hypothesized that patients with FS would have an endurance strength to low loads performance in lower and upper extremities at least twice as low as that of the healthy controls. Satisfactory test-retest reliability and SEMs were found for the lower extremity, dominant arm, and nondominant arm tests (ICC=.973-.979; P.05 for all). The Bland-Altman plots showed 95% limits of agreement for the lower extremity (4.7 to -4.5), dominant arm (3.8 to -4.4), and nondominant arm (3.9 to -4.1) tests. The endurance strength to low loads test scores for the patients with FS were 4-fold lower than for the controls in all performed tests (P<.001 for all). The endurance strength to low loads tests showed good reliability and known group validity and can be recommended for evaluating endurance strength to low loads in patients with FS. For individual evaluation, however, an improved score of at least 4 and 5 repetitions for the upper and lower extremities

  15. Mean annual precipitation predicts primary production resistance and resilience to extreme drought.

    Science.gov (United States)

    Stuart-Haëntjens, Ellen; De Boeck, Hans J; Lemoine, Nathan P; Mänd, Pille; Kröel-Dulay, György; Schmidt, Inger K; Jentsch, Anke; Stampfli, Andreas; Anderegg, William R L; Bahn, Michael; Kreyling, Juergen; Wohlgemuth, Thomas; Lloret, Francisco; Classen, Aimée T; Gough, Christopher M; Smith, Melinda D

    2018-04-27

    Extreme drought is increasing in frequency and intensity in many regions globally, with uncertain consequences for the resistance and resilience of ecosystem functions, including primary production. Primary production resistance, the capacity to withstand change during extreme drought, and resilience, the degree to which production recovers, vary among and within ecosystem types, obscuring generalized patterns of ecological stability. Theory and many observations suggest forest production is more resistant but less resilient than grassland production to extreme drought; however, studies of production sensitivity to precipitation variability indicate that the processes controlling resistance and resilience may be influenced more by mean annual precipitation (MAP) than ecosystem type. Here, we conducted a global meta-analysis to investigate primary production resistance and resilience to extreme drought in 64 forests and grasslands across a broad MAP gradient. We found resistance to extreme drought was predicted by MAP; however, grasslands (positive) and forests (negative) exhibited opposing resilience relationships with MAP. Our findings indicate that common plant physiological mechanisms may determine grassland and forest resistance to extreme drought, whereas differences among plant residents in turnover time, plant architecture, and drought adaptive strategies likely underlie divergent resilience patterns. The low resistance and resilience of dry grasslands suggests that these ecosystems are the most vulnerable to extreme drought - a vulnerability that is expected to compound as extreme drought frequency increases in the future. Copyright © 2018. Published by Elsevier B.V.

  16. Effect of fuel assembly mechanical design changes on dynamic response of reactor pressure vessel system under extreme loadings

    International Nuclear Information System (INIS)

    Bhandari, D.R.; Hankinson, M.F.

    1993-01-01

    This paper presents the results of a study to assess the effect of fuel assembly mechanical design changes on the dynamic response of a pressurized water reactor vessel and reactor internals under Loss-Of-Coolant Accident (LOCA) conditions. The results of this study show that the dynamic response of the reactor vessel internals and the core under extreme loadings, such as LOCA, is very sensitive to fuel assembly mechanical design changes. (author)

  17. Global resistance and resilience of primary production following extreme drought are predicted by mean annual precipitation

    Science.gov (United States)

    Stuart-Haëntjens, E. J.; De Boeck, H. J.; Lemoine, N. P.; Gough, C. M.; Kröel-Dulay, G.; Mänd, P.; Jentsch, A.; Schmidt, I. K.; Bahn, M.; Lloret, F.; Kreyling, J.; Wohlgemuth, T.; Stampfli, A.; Anderegg, W.; Classen, A. T.; Smith, M. D.

    2017-12-01

    Extreme drought is increasing globally in frequency and intensity, with uncertain consequences for the resistance and resilience of key ecosystem functions, including primary production. Primary production resistance, the capacity of an ecosystem to withstand change in primary production following extreme climate, and resilience, the degree to which primary production recovers, vary among and within ecosystem types, obscuring global patterns of resistance and resilience to extreme drought. Past syntheses on resistance have focused climatic gradients or individual ecosystem types, without assessing interactions between the two. Theory and many empirical studies suggest that forest production is more resistant but less resilient than grassland production to extreme drought, though some empirical studies reveal that these trends are not universal. Here, we conducted a global meta-analysis of sixty-four grassland and forest sites, finding that primary production resistance to extreme drought is predicted by a common continuum of mean annual precipitation (MAP). However, grasslands and forests exhibit divergent production resilience relationships with MAP. We discuss the likely mechanisms underlying the mixed production resistance and resilience patterns of forests and grasslands, including different plant species turnover times and drought adaptive strategies. These findings demonstrate the primary production responses of forests and grasslands to extreme drought are mixed, with far-reaching implications for Earth System Models, ecosystem management, and future studies of extreme drought resistance and resilience.

  18. Advances in the analysis and design of concrete structures, metal containments and liner plate for extreme loads

    International Nuclear Information System (INIS)

    Stevenson, J.D.; Eibl, J.; Curbach, M.; Johnson, T.E.; Daye, M.A.; Riera, J.D.; Nemet, J.; Iyengar, K.T.S.

    1992-01-01

    The material presented in this paper summarizes the progress that has been made in the analysis, design, and testing of concrete structures. The material is summarized in the following documents: Part I: Containment Design Criteria and Loading Combinations; Part II: Reinforced and Prestressed Concrete Behavior; Part III: Concrete Containment Analysis, Design and Related Testing; Part IV: Impact and Impulse Loading and Response Prediction; Part V: Metal Containments and Liner Plate Systems; Part VI: Prestressed Reactor Vessel Design, Testing and Analysis. (orig.)

  19. Fear among the extremes: how political ideology predicts negative emotions and outgroup derogation.

    Science.gov (United States)

    van Prooijen, Jan-Willem; Krouwel, André P M; Boiten, Max; Eendebak, Lennart

    2015-04-01

    The "rigidity of the right" hypothesis predicts that particularly the political right experiences fear and derogates outgroups. We propose that above and beyond that, the political extremes (at both sides of the spectrum) are more likely to display these responses than political moderates. Results of a large-scale sample reveal the predicted quadratic term on socio-economic fear. Moreover, although the political right is more likely to derogate the specific category of immigrants, we find a quadratic effect on derogation of a broad range of societal categories. Both extremes also experience stronger negative emotions about politics than politically moderate respondents. Finally, the quadratic effects on derogation of societal groups and negative political emotions were mediated by socio-economic fear, particularly among left- and right-wing extremists. It is concluded that negative emotions and outgroup derogation flourish among the extremes. © 2015 by the Society for Personality and Social Psychology, Inc.

  20. Extreme Motion Predictions for Deepwater TLP Floaters for Offshore Wind Turbines

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher; Mansour, A. E.

    2006-01-01

    illustrates that a very effective, stochastic response analysis can be performed using the First-order reliability method (FORM), well-known within structural reliability. The results presented are the mean outcrossing rates of the horizontal motions, from where extreme value predictions are readily obtained...

  1. Prediction and discovery of extremely strong hydrodynamic instabilities due to a velocity jump: theory and experiments

    International Nuclear Information System (INIS)

    Fridman, A M

    2008-01-01

    The theory and the experimental discovery of extremely strong hydrodynamic instabilities are described, viz. the Kelvin-Helmholtz, centrifugal, and superreflection instabilities. The discovery of the last two instabilities was predicted and the Kelvin-Helmholtz instability in real systems was revised by us. (reviews of topical problems)

  2. A new crack growth model for life prediction under random loading

    International Nuclear Information System (INIS)

    Lee, Ouk Sub; Chen, Zhi Wei

    1999-01-01

    The load interaction effect in variable amplitude fatigue test is a very important issue for correctly predicting fatigue life. Some prediction methods for retardation are reviewed and the problems discussed. The so-called 'under-load' effect is also of importance for a prediction model to work properly under random load spectrum. A new model that is simple in form but combines overload plastic zone and residual stress considerations together with Elber's closure concept is proposed to fully take account of the load-interaction effects including both over-load and under-load effects. Applying this new model to complex load sequence is explored here. Simulations of tests show the improvement of the new model over other models. The best prediction (mostly closely resembling test curve) is given by the newly proposed Chen-Lee model

  3. Prediction of contact mechanics in metal-on-metal Total Hip Replacement for parametrically comprehensive designs and loads.

    Science.gov (United States)

    Donaldson, Finn E; Nyman, Edward; Coburn, James C

    2015-07-16

    Manufacturers and investigators of Total Hip Replacement (THR) bearings require tools to predict the contact mechanics resulting from diverse design and loading parameters. This study provides contact mechanics solutions for metal-on-metal (MoM) bearings that encompass the current design space and could aid pre-clinical design optimization and evaluation. Stochastic finite element (FE) simulation was used to calculate the head-on-cup contact mechanics for five thousand combinations of design and loading parameters. FE results were used to train a Random Forest (RF) surrogate model to rapidly predict the contact patch dimensions, contact area, pressures and plastic deformations for arbitrary designs and loading. In addition to widely observed polar and edge contact, FE results included ring-polar, asymmetric-polar, and transitional categories which have previously received limited attention. Combinations of design and load parameters associated with each contact category were identified. Polar contact pressures were predicted in the range of 0-200 MPa with no permanent deformation. Edge loading (with subluxation) was associated with pressures greater than 500 MPa and induced permanent deformation in 83% of cases. Transitional-edge contact (with little subluxation) was associated with intermediate pressures and permanent deformation in most cases, indicating that, even with ideal anatomical alignment, bearings may face extreme wear challenges. Surrogate models were able to accurately predict contact mechanics 18,000 times faster than FE analyses. The developed surrogate models enable rapid prediction of MoM bearing contact mechanics across the most comprehensive range of loading and designs to date, and may be useful to those performing bearing design optimization or evaluation. Published by Elsevier Ltd.

  4. Prediction of extreme floods in the Central Andes by means of Complex Networks

    Science.gov (United States)

    Boers, Niklas; Bookhagen, Bodo; Barbosa, Henrique; Marwan, Norbert; Kurths, Jürgen; Marengo, Jose

    2014-05-01

    Based on a non-linear synchronisation measure and complex network theory, we present a novel framework for the prediction of extreme events of spatially embedded, interrelated time series. This method is general in the sense that it can be applied to any type of spatially sampled time series with significant interrelations, ranging from climate observables to biological or stock market data. In this presentation, we apply our method to extreme rainfall in South America and show how this leads to the prediction of more than 60% (90% during El Niño conditions) of extreme rainfall events in the eastern Central Andes of Bolivia and northern Argentina, with only 1% false alarms. From paleoclimatic to decadal time scales, the Central Andes continue to be subject to pronounced changes in climatic conditions. In particular, our and past work shows that frequency as well as magnitudes of extreme rainfall events have increased significantly during past decades, calling for a better understanding of the involved climatic mechanisms. Due to their large spatial extend and occurrence at high elevations, these extreme events often lead to severe floods and landslides with disastrous socioeconomic impacts. They regularly affect tens of thousands of people and produce estimated costs of the order of several hundred million USD. Alongside with the societal value of predicting natural hazards, our study provides insights into the responsible climatic features and suggests interactions between Rossby waves in polar regions and large scale (sub-)tropical moisture transport as a driver of subseasonal variability of the South American monsoon system. Predictable extreme events result from the propagation of extreme rainfall from the region of Buenos Aires towards the Central Andes given characteristic atmospheric conditions. Our results indicate that the role of frontal systems originating from Rossby waves in polar latitudes is much more dominant for controlling extreme rainfall in

  5. Assessment of Wind Parameter Sensitivity on Extreme and Fatigue Wind Turbine Loads

    Energy Technology Data Exchange (ETDEWEB)

    Robertson, Amy N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sethuraman, Latha [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jonkman, Jason [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2018-01-12

    Wind turbines are designed using a set of simulations to ascertain the structural loads that the turbine could encounter. While mean hub-height wind speed is considered to vary, other wind parameters such as turbulence spectra, sheer, veer, spatial coherence, and component correlation are fixed or conditional values that, in reality, could have different characteristics at different sites and have a significant effect on the resulting loads. This paper therefore seeks to assess the sensitivity of different wind parameters on the resulting ultimate and fatigue loads on the turbine during normal operational conditions. Eighteen different wind parameters are screened using an Elementary Effects approach with radial points. As expected, the results show a high sensitivity of the loads to the turbulence standard deviation in the primary wind direction, but the sensitivity to wind shear is often much greater. To a lesser extent, other wind parameters that drive loads include the coherence in the primary wind direction and veer.

  6. Predictive equations for lumbar spine loads in load-dependent asymmetric one- and two-handed lifting activities.

    Science.gov (United States)

    Arjmand, N; Plamondon, A; Shirazi-Adl, A; Parnianpour, M; Larivière, C

    2012-07-01

    Asymmetric lifting activities are associated with low back pain. A finite element biomechanical model is used to estimate spinal loads during one- and two-handed asymmetric static lifting activities. Model input variables are thorax flexion angle, load magnitude as well as load sagittal and lateral positions while response variables are L4-L5 and L5-S1 disc compression and shear forces. A number of levels are considered for each input variable and all their possible combinations are introduced into the model. Robust yet user-friendly predictive equations that relate model responses to its inputs are established. Predictive equations with adequate goodness-of-fit (R(2) ranged from ~94% to 99%, P≤0.001) that relate spinal loads to task (input) variables are established. Contour plots are used to identify combinations of task variable levels that yield spine loads beyond the recommended limits. The effect of uncertainties in the measurements of asymmetry-related inputs on spinal loads is studied. A number of issues regarding the NIOSH asymmetry multiplier are discussed and it is concluded that this multiplier should depend on the trunk posture and be defined in terms of the load vertical and horizontal positions. Due to an imprecise adjustment of the handled load magnitude this multiplier inadequately controls the biomechanical loading of the spine. Ergonomists and bioengineers, faced with the dilemma of using either complex but more accurate models on one hand or less accurate but simple models on the other hand, have hereby easy-to-use predictive equations that quantify spinal loads under various occupational tasks. Copyright © 2011 Elsevier Ltd. All rights reserved.

  7. Assessing the ability of operational snow models to predict snowmelt runoff extremes (Invited)

    Science.gov (United States)

    Wood, A. W.; Restrepo, P. J.; Clark, M. P.

    2013-12-01

    In the western US, the snow accumulation and melt cycle of winter and spring plays a critical role in the region's water management strategies. Consequently, the ability to predict snowmelt runoff at time scales from days to seasons is a key input for decisions in reservoir management, whether for avoiding flood hazards or supporting environmental flows through the scheduling of releases in spring, or for allocating releases for multi-state water distribution in dry seasons of year (using reservoir systems to provide an invaluable buffer for many sectors against drought). Runoff forecasts thus have important benefits at both wet and dry extremes of the climatological spectrum. The importance of the prediction of the snow cycle motivates an assessment of the strengths and weaknesses of the US's central operational snow model, SNOW17, in contrast to process-modeling alternatives, as they relate to simulating observed snowmelt variability and extremes. To this end, we use a flexible modeling approach that enables an investigation of different choices in model structure, including model physics, parameterization and degree of spatiotemporal discretization. We draw from examples of recent extreme events in western US watersheds and an overall assessment of retrospective model performance to identify fruitful avenues for advancing the modeling basis for the operational prediction of snow-related runoff extremes.

  8. TBCs for Gas Turbines under Thermomechanical Loadings: Failure Behaviour and Life Prediction

    Directory of Open Access Journals (Sweden)

    Herzog R.

    2012-10-01

    Full Text Available The present contribution gives an overview about recent research on a thermal barrier coating (TBC system consisted of (i an intermetallic MCrAlY-alloy Bondcoat (BC applied by vacuum plasma spraying (VPS and (ii an Yttria Stabilised Zirconia (YSZ top coat air plasma sprayed (APS at Forschungszentrum Juelich, Institute of Energy and Climate Research (IEK-1. The influence of high temperature dwell time, maximum and minimum temperature on crack growth kinetics during thermal cycling of such plasma sprayed TBCs is investigated using infrared pulse thermography (IT, acoustic emission (AE analysis and scanning electron microscopy. Thermocyclic life in terms of accumulated time at maximum temperature decreases with increasing high temperature dwell time and increases with increasing minimum temperature. AE analysis proves that crack growth mainly occurs during cooling at temperatures below the ductile-to-brittle transition temperature of the BC. Superimposed mechanical load cycles accelerate delamination crack growth and, in case of sufficiently high mechanical loadings, result in premature fatigue failure of the substrate. A life prediction model based on TGO growth kinetics and a fracture mechanics approach has been developed which accounts for the influence of maximum and minimum temperature as well as of high temperature dwell time with good accuracy in an extremely wide parameter range.

  9. Predicting the Response of Electricity Load to Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Sullivan, Patrick [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Colman, Jesse [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Kalendra, Eric [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2015-07-28

    Our purpose is to develop a methodology to quantify the impact of climate change on electric loads in the United States. We perform simple linear regression, assisted by geospatial smoothing, on paired temperature and load time-series to estimate the heating- and coolinginduced sensitivity to temperature across 300 transmission zones and 16 seasonal and diurnal time periods. The estimated load sensitivities can be coupled with climate scenarios to quantify the potential impact of climate change on load, with a primary application being long-term electricity scenarios. The method allows regional and seasonal differences in climate and load response to be reflected in the electricity scenarios. While the immediate product of this analysis was designed to mesh with the spatial and temporal resolution of a specific electricity model to enable climate change scenarios and analysis with that model, we also propose that the process could be applied for other models and purposes.

  10. The prediction of rotor rotational noise using measured fluctuating blade loads

    Science.gov (United States)

    Hosier, R. N.; Pegg, R. J.; Ramakrishnan, R.

    1974-01-01

    In tests conducted at the NASA Langley Research Center Helicopter Rotor Test Facility, simultaneous measurements of the high-frequency fluctuating aerodynamic blade loads and far-field radiated noise were made on a full-scale, nontranslating rotor system. After their characteristics were determined, the measured blade loads were used in an existing theory to predict the far-field rotational noise. A comparison of the calculated and measured rotational noise is presented with specific attention given to the effect of blade loading coefficients, chordwise loading distributions, blade loading phases, and observer azimuthal position on the predictions.

  11. Prediction method for cavitation erosion based on measurement of bubble collapse impact loads

    International Nuclear Information System (INIS)

    Hattori, S; Hirose, T; Sugiyama, K

    2009-01-01

    The prediction of cavitation erosion rates is important in order to evaluate the exact life of components. The measurement of impact loads in bubble collapses helps to predict the life under cavitation erosion. In this study, we carried out erosion tests and the measurements of impact loads in bubble collapses with a vibratory apparatus. We evaluated the incubation period based on a cumulative damage rule by measuring the impact loads of cavitation acting on the specimen surface and by using the 'constant impact load - number of impact loads curve' similar to the modified Miner's rule which is employed for fatigue life prediction. We found that the parameter Σ(F i α xn i ) (F i : impact load, n i : number of impacts and α: constant) is suitable for the evaluation of the erosion life. Moreover, we propose a new method that can predict the incubation period under various cavitation conditions.

  12. Prediction of Air Pollutants Concentration Based on an Extreme Learning Machine: The Case of Hong Kong

    Directory of Open Access Journals (Sweden)

    Jiangshe Zhang

    2017-01-01

    Full Text Available With the development of the economy and society all over the world, most metropolitan cities are experiencing elevated concentrations of ground-level air pollutants. It is urgent to predict and evaluate the concentration of air pollutants for some local environmental or health agencies. Feed-forward artificial neural networks have been widely used in the prediction of air pollutants concentration. However, there are some drawbacks, such as the low convergence rate and the local minimum. The extreme learning machine for single hidden layer feed-forward neural networks tends to provide good generalization performance at an extremely fast learning speed. The major sources of air pollutants in Hong Kong are mobile, stationary, and from trans-boundary sources. We propose predicting the concentration of air pollutants by the use of trained extreme learning machines based on the data obtained from eight air quality parameters in two monitoring stations, including Sham Shui Po and Tap Mun in Hong Kong for six years. The experimental results show that our proposed algorithm performs better on the Hong Kong data both quantitatively and qualitatively. Particularly, our algorithm shows better predictive ability, with R 2 increased and root mean square error values decreased respectively.

  13. Prediction of Air Pollutants Concentration Based on an Extreme Learning Machine: The Case of Hong Kong.

    Science.gov (United States)

    Zhang, Jiangshe; Ding, Weifu

    2017-01-24

    With the development of the economy and society all over the world, most metropolitan cities are experiencing elevated concentrations of ground-level air pollutants. It is urgent to predict and evaluate the concentration of air pollutants for some local environmental or health agencies. Feed-forward artificial neural networks have been widely used in the prediction of air pollutants concentration. However, there are some drawbacks, such as the low convergence rate and the local minimum. The extreme learning machine for single hidden layer feed-forward neural networks tends to provide good generalization performance at an extremely fast learning speed. The major sources of air pollutants in Hong Kong are mobile, stationary, and from trans-boundary sources. We propose predicting the concentration of air pollutants by the use of trained extreme learning machines based on the data obtained from eight air quality parameters in two monitoring stations, including Sham Shui Po and Tap Mun in Hong Kong for six years. The experimental results show that our proposed algorithm performs better on the Hong Kong data both quantitatively and qualitatively. Particularly, our algorithm shows better predictive ability, with R 2 increased and root mean square error values decreased respectively.

  14. Model for predicting non-linear crack growth considering load sequence effects (LOSEQ)

    International Nuclear Information System (INIS)

    Fuehring, H.

    1982-01-01

    A new analytical model for predicting non-linear crack growth is presented which takes into account the retardation as well as the acceleration effects due to irregular loading. It considers not only the maximum peak of a load sequence to effect crack growth but also all other loads of the history according to a generalised memory criterion. Comparisons between crack growth predicted by using the LOSEQ-programme and experimentally observed data are presented. (orig.) [de

  15. Methodologies for predicting the part-load performance of aero-derivative gas turbines

    DEFF Research Database (Denmark)

    Haglind, Fredrik; Elmegaard, Brian

    2009-01-01

    Prediction of the part-load performance of gas turbines is advantageous in various applications. Sometimes reasonable part-load performance is sufficient, while in other cases complete agreement with the performance of an existing machine is desirable. This paper is aimed at providing some guidance...... on methodologies for predicting part-load performance of aero-derivative gas turbines. Two different design models – one simple and one more complex – are created. Subsequently, for each of these models, the part-load performance is predicted using component maps and turbine constants, respectively. Comparisons...... with manufacturer data are made. With respect to the design models, the simple model, featuring a compressor, combustor and turbines, results in equally good performance prediction in terms of thermal efficiency and exhaust temperature as does a more complex model. As for part-load predictions, the results suggest...

  16. SU-E-J-191: Motion Prediction Using Extreme Learning Machine in Image Guided Radiotherapy

    International Nuclear Information System (INIS)

    Jia, J; Cao, R; Pei, X; Wang, H; Hu, L

    2015-01-01

    Purpose: Real-time motion tracking is a critical issue in image guided radiotherapy due to the time latency caused by image processing and system response. It is of great necessity to fast and accurately predict the future position of the respiratory motion and the tumor location. Methods: The prediction of respiratory position was done based on the positioning and tracking module in ARTS-IGRT system which was developed by FDS Team (www.fds.org.cn). An approach involving with the extreme learning machine (ELM) was adopted to predict the future respiratory position as well as the tumor’s location by training the past trajectories. For the training process, a feed-forward neural network with one single hidden layer was used for the learning. First, the number of hidden nodes was figured out for the single layered feed forward network (SLFN). Then the input weights and hidden layer biases of the SLFN were randomly assigned to calculate the hidden neuron output matrix. Finally, the predicted movement were obtained by applying the output weights and compared with the actual movement. Breathing movement acquired from the external infrared markers was used to test the prediction accuracy. And the implanted marker movement for the prostate cancer was used to test the implementation of the tumor motion prediction. Results: The accuracy of the predicted motion and the actual motion was tested. Five volunteers with different breathing patterns were tested. The average prediction time was 0.281s. And the standard deviation of prediction accuracy was 0.002 for the respiratory motion and 0.001 for the tumor motion. Conclusion: The extreme learning machine method can provide an accurate and fast prediction of the respiratory motion and the tumor location and therefore can meet the requirements of real-time tumor-tracking in image guided radiotherapy

  17. SU-E-J-191: Motion Prediction Using Extreme Learning Machine in Image Guided Radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Jia, J; Cao, R; Pei, X; Wang, H; Hu, L [Key Laboratory of Neutronics and Radiation Safety, Institute of Nuclear Energy Safety Technology, Chinese Academy of Sciences, Hefei, Anhui, 230031 (China); Engineering Technology Research Center of Accurate Radiotherapy of Anhui Province, Hefei 230031 (China); Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, SuZhou (China)

    2015-06-15

    Purpose: Real-time motion tracking is a critical issue in image guided radiotherapy due to the time latency caused by image processing and system response. It is of great necessity to fast and accurately predict the future position of the respiratory motion and the tumor location. Methods: The prediction of respiratory position was done based on the positioning and tracking module in ARTS-IGRT system which was developed by FDS Team (www.fds.org.cn). An approach involving with the extreme learning machine (ELM) was adopted to predict the future respiratory position as well as the tumor’s location by training the past trajectories. For the training process, a feed-forward neural network with one single hidden layer was used for the learning. First, the number of hidden nodes was figured out for the single layered feed forward network (SLFN). Then the input weights and hidden layer biases of the SLFN were randomly assigned to calculate the hidden neuron output matrix. Finally, the predicted movement were obtained by applying the output weights and compared with the actual movement. Breathing movement acquired from the external infrared markers was used to test the prediction accuracy. And the implanted marker movement for the prostate cancer was used to test the implementation of the tumor motion prediction. Results: The accuracy of the predicted motion and the actual motion was tested. Five volunteers with different breathing patterns were tested. The average prediction time was 0.281s. And the standard deviation of prediction accuracy was 0.002 for the respiratory motion and 0.001 for the tumor motion. Conclusion: The extreme learning machine method can provide an accurate and fast prediction of the respiratory motion and the tumor location and therefore can meet the requirements of real-time tumor-tracking in image guided radiotherapy.

  18. Extreme Loads on the Mooring Lines and Survivability Mode for the Wave Dragon Wave Energy Converter

    DEFF Research Database (Denmark)

    Parmeggiani, Stefano; Kofoed, Jens Peter; Friis-Madsen, E.

    2011-01-01

    Dragon aims at optimizing the power production by adapting the floating level to the incoming waves and by activating the hydro-turbines and regulating their working speed. In extreme conditions though, the control strategy could be changed in order to reduce the forces in the mooring system, lowering...

  19. Static reliability of concrete structures under extreme temperature, radiation, moisture and force loading

    International Nuclear Information System (INIS)

    Stepanek, P.; Stastnik, S.; Salajka, V.; Hradil, P.; Skolar, J.; Chlanda, V.

    2003-01-01

    The contribution presents some aspects of the static reliability of concrete structures under temperature effects and under mechanical loading. The mathematical model of a load-bearing concrete structure was performed using the FEM method. The temperature field and static stress that generated states of stress were taken into account. A brief description of some aspects of evaluation of the reliability within the primary circuit concrete structures is stated. The knowledge of actual physical and mechanical characteristics and chemical composition of concrete were necessary for obtaining correct results of numerical analysis. (author)

  20. An Adaptive Model Predictive Load Frequency Control Method for Multi-Area Interconnected Power Systems with Photovoltaic Generations

    Directory of Open Access Journals (Sweden)

    Guo-Qiang Zeng

    2017-11-01

    Full Text Available As the penetration level of renewable distributed generations such as wind turbine generator and photovoltaic stations increases, the load frequency control issue of a multi-area interconnected power system becomes more challenging. This paper presents an adaptive model predictive load frequency control method for a multi-area interconnected power system with photovoltaic generation by considering some nonlinear features such as a dead band for governor and generation rate constraint for steam turbine. The dynamic characteristic of this system is formulated as a discrete-time state space model firstly. Then, the predictive dynamic model is obtained by introducing an expanded state vector, and rolling optimization of control signal is implemented based on a cost function by minimizing the weighted sum of square predicted errors and square future control values. The simulation results on a typical two-area power system consisting of photovoltaic and thermal generator have demonstrated the superiority of the proposed model predictive control method to these state-of-the-art control techniques such as firefly algorithm, genetic algorithm, and population extremal optimization-based proportional-integral control methods in cases of normal conditions, load disturbance and parameters uncertainty.

  1. Fusing Simulation Results From Multifidelity Aero-servo-elastic Simulators - Application To Extreme Loads On Wind Turbine

    DEFF Research Database (Denmark)

    Abdallah, Imad; Sudret, Bruno; Lataniotis, Christos

    2015-01-01

    Fusing predictions from multiple simulators in the early stages of the conceptual design of a wind turbine results in reduction in model uncertainty and risk mitigation. Aero-servo-elastic is a term that refers to the coupling of wind inflow, aerodynamics, structural dynamics and controls. Fusing...... the response data from multiple aero-servo-elastic simulators could provide better predictive ability than using any single simulator. The co-Kriging approach to fuse information from multifidelity aero-servo-elastic simulators is presented. We illustrate the co-Kriging approach to fuse the extreme flapwise...... bending moment at the blade root of a large wind turbine as a function of wind speed, turbulence and shear exponent in the presence of model uncertainty and non-stationary noise in the output. The extreme responses are obtained by two widely accepted numerical aero-servo-elastic simulators, FAST...

  2. Which screening tools can predict injury to the lower extremities in team sports?: a systematic review.

    Science.gov (United States)

    Dallinga, Joan M; Benjaminse, Anne; Lemmink, Koen A P M

    2012-09-01

    Injuries to lower extremities are common in team sports such as soccer, basketball, volleyball, football and field hockey. Considering personal grief, disabling consequences and high costs caused by injuries to lower extremities, the importance for the prevention of these injuries is evident. From this point of view it is important to know which screening tools can identify athletes who are at risk of injury to their lower extremities. The aim of this article is to determine the predictive values of anthropometric and/or physical screening tests for injuries to the leg, anterior cruciate ligament (ACL), knee, hamstring, groin and ankle in team sports. A systematic review was conducted in MEDLINE (1966 to September 2011), EMBASE (1989 to September 2011) and CINAHL (1982 to September 2011). Based on inclusion criteria defined a priori, titles, abstracts and full texts were analysed to find relevant studies. The analysis showed that different screening tools can be predictive for injuries to the knee, ACL, hamstring, groin and ankle. For injuries in general there is some support in the literature to suggest that general joint laxity is a predictive measure for leg injuries. The anterior right/left reach distance >4 cm and the composite reach distance injuries. Furthermore, an increasing age, a lower hamstring/quadriceps (H : Q) ratio and a decreased range of motion (ROM) of hip abduction may predict the occurrence of leg injuries. Hyperextension of the knee, side-to-side differences in anterior-posterior knee laxity and differences in knee abduction moment between both legs are suggested to be predictive tests for sustaining an ACL injury and height was a predictive screening tool for knee ligament injuries. There is some evidence that when age increases, the probability of sustaining a hamstring injury increases. Debate exists in the analysed literature regarding measurement of the flexibility of the hamstring as a predictive screening tool, as well as using the H

  3. Radiation load of the extremities and eye lenses of the staff during selected interventional radiology procedures

    International Nuclear Information System (INIS)

    Nikodemova, Denisa; Trosanova, Dominika

    2010-01-01

    The Slovak Medical University in Bratislava is involved in the ORAMED (Optimization of Radiation Protection for Medical Staff) research project, aimed at developing a unified methodology for a more accurate assessment of professional exposure of interventional radiology staff, with focus on extremity and eye lens dosimetry in selected procedures. Three cardiac procedures and 5 angiography examinations were selected: all technical parameters were monitored and the dose equivalent levels were measured by TL dosimetry at 9 anatomic sites of the body. Preliminary results were obtained for the radiation burden of the eyes and extremities during digital subtraction angiography of the lower limbs, collected from 7 hospital departments in partner EU states. Correlations between the evaluated data and the influence of some parameters are shown

  4. DeRisk - Accurate prediction of ULS wave loads. Outlook and first results

    DEFF Research Database (Denmark)

    Bredmose, Henrik; Dixen, Martin; Ghadirian, Amin

    2016-01-01

    Loads from extreme waves can be dimensioning for the substructures of offshore wind turbines. The DeRisk project (2015-2019) aims at an improved load evaluation procedure for extreme waves through application of advanced wave models, laboratory tests of load effects, development of hydrodynamic...... load models, aero-elastic response calculations and statistical analysis. This first paper from the project outlines the content and philosophy behind DeRisk. Next, the first results from laboratory tests with irregular waves are presented, including results for 2D and 3D focused wave groups....... The results of focused wave group tests and a 6-hour (full scale duration) test are reproduced numerically by re-application of the wave paddle signal in a fully nonlinear potential flow wave model. A good match for the free surface elevation and associated exceedance probability curve is obtained. Finally...

  5. Rod behaviour under base load, load follow and frequency control operation: CYRANO 2 code predictions versus experimental results

    International Nuclear Information System (INIS)

    Gautier, B.; Raybaud, A.

    1984-01-01

    The French PWR reactors are now currently operating under load follow and frequency control. In order to demonstrate that these operating conditions were not able to increase the fuel failure rate, fuel rod behaviour calculations have been performed by E.D.F. with CYRANO 2 code. In parallel with these theoretical calculations, code predictions have been compared to experimental results. The paper presents some of the comparisons performed on 17x17 fuel irradiated in FESSENHEIM 2 up to 30 GWd/tU under base load operation and in the CAP reactor under load follow and frequency control conditions. It is shown that experimental results can be predicted with a reasonable accuracy by CYRANO 2 code. The experimental work was carried out under joint R and D programs by EDF, FRAGEMA, CEA, and WESTINGHOUSE (CAP program by French partners only). (author)

  6. Pressure Prediction of Coal Slurry Transportation Pipeline Based on Particle Swarm Optimization Kernel Function Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Xue-cun Yang

    2015-01-01

    Full Text Available For coal slurry pipeline blockage prediction problem, through the analysis of actual scene, it is determined that the pressure prediction from each measuring point is the premise of pipeline blockage prediction. Kernel function of support vector machine is introduced into extreme learning machine, the parameters are optimized by particle swarm algorithm, and blockage prediction method based on particle swarm optimization kernel function extreme learning machine (PSOKELM is put forward. The actual test data from HuangLing coal gangue power plant are used for simulation experiments and compared with support vector machine prediction model optimized by particle swarm algorithm (PSOSVM and kernel function extreme learning machine prediction model (KELM. The results prove that mean square error (MSE for the prediction model based on PSOKELM is 0.0038 and the correlation coefficient is 0.9955, which is superior to prediction model based on PSOSVM in speed and accuracy and superior to KELM prediction model in accuracy.

  7. Using squat testing to predict training loads for lower-body exercises in elite karate athletes.

    Science.gov (United States)

    Wong, Del P; Tan, Erik C H; Chaouachi, Anis; Carling, Christopher; Castagna, Carlo; Bloomfield, Jonathan; Behm, David G

    2010-11-01

    The purpose of this study was to determine the relationship between squat loads and 2 bilateral and 2 unilateral stepping lower-body exercises in predominantly unilateral movement elite athletes (Karate). Equations to predict loads for lower-body exercises based on the squat load were also determined. Fourteen male elite Karate athletes (age = 22.6 ± 1.2 years) performed 6 repetition maximum (RM) of the following free-weight bilateral exercises: back half squat, deadlift, leg press and unilateral stepping exercises, lunge; and step-up. Results showed that 6RM squat load was significantly (p squat load was a significant predictor for deadlift, leg press, lunge, and step-up (R2 range from 0.57 to 0.85, p squat load (1.12)-16.60 kg, (b) Leg press = squat load (1.66) + 16.10 kg, (c) Lunge = squat load (0.61) + 9.39 kg, and (d) step-up = squat load (0.85)-10.36 kg. Coaches and fitness professionals can use the 6RM squat load as a time effective and accurate method to predict training loads for both bilateral and unilateral lower-body exercises with quadriceps as the prime mover. Load prescriptions for unilateral exercises should take into account the type of athletic population.

  8. MESSENGER Observations of Extreme Magnetic Tail Loading and Unloading During its Third Flyby of Mercury: Substorms?

    Science.gov (United States)

    Slavin, James A.; Anderson, Brian J.; Baker, Daniel N.; Benna, Mehdi; Gloeckler, George; Krimigis, Stamatios M.; McNutt, Ralph L., Jr.; Schriver, David; Solomon, Sean C.; Zurbuchen, Thomas H.

    2010-01-01

    During MESSENGER's third flyby of Mercury on September 29, 2009, a variable interplanetary magnetic field produced a series of several minute enhancements of the tail magnetic field hy factors of approx. 2 to 3.5. The magnetic field flaring during these intervals indicates that they result from loading of the tail with magnetic flux transferred from the dayside magnetosphere. The unloading intervals were associated with plasmoids and traveling compression regions, signatures of tail reconnection. The peak tail magnetic flux during the smallest loading events equaled 30% of the magnetic flux emanating from Mercury, and may have reached 100% for the largest event. In this case the dayside magnetic shielding is reduced and solar wind flux impacting the surface may be greatly enhanced. Despite the intensity of these events and their similarity to terrestrial substorm magnetic flux dynamics, no energetic charged particles with energies greater than 36 keV were observed.

  9. Physical and JIT Model Based Hybrid Modeling Approach for Building Thermal Load Prediction

    Science.gov (United States)

    Iino, Yutaka; Murai, Masahiko; Murayama, Dai; Motoyama, Ichiro

    Energy conservation in building fields is one of the key issues in environmental point of view as well as that of industrial, transportation and residential fields. The half of the total energy consumption in a building is occupied by HVAC (Heating, Ventilating and Air Conditioning) systems. In order to realize energy conservation of HVAC system, a thermal load prediction model for building is required. This paper propose a hybrid modeling approach with physical and Just-in-Time (JIT) model for building thermal load prediction. The proposed method has features and benefits such as, (1) it is applicable to the case in which past operation data for load prediction model learning is poor, (2) it has a self checking function, which always supervises if the data driven load prediction and the physical based one are consistent or not, so it can find if something is wrong in load prediction procedure, (3) it has ability to adjust load prediction in real-time against sudden change of model parameters and environmental conditions. The proposed method is evaluated with real operation data of an existing building, and the improvement of load prediction performance is illustrated.

  10. On the prediction of residential loads in India

    NARCIS (Netherlands)

    Fuchs, P.S.; Lele, A.; Venkatesha-Prasad, R.R.

    2015-01-01

    The Indian Energy grid is growing rapidly and there is a large simulation to improve not only the grid reliability, but also provide power for all by 2027. To this aim the Government of India has launched the Restructured Accelerated Power Development Program (RAPDRP). In India, residential loads

  11. Conditional Stochastic Processes Applied to Wave Load Predictions

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher

    2015-01-01

    The concept of conditional stochastic processes provides a powerful tool for evaluation and estimation of wave loads on ships and offshore structures. This article first considers conditional waves with a focus on critical wave episodes. Then the inherent uncertainty in the results is illustrated...

  12. Effects of extreme-duration heavy load carriage on neuromuscular function and locomotion: a military-based study.

    Directory of Open Access Journals (Sweden)

    Jordane G Grenier

    Full Text Available Trekking and military missions generally consist of carrying heavy loads for extreme durations. These factors have been separately shown to be sources of neuromuscular (NM fatigue and locomotor alterations. However, the question of their combined effects remains unresolved, and addressing this issue required a representative context.The aim was to investigate the effects of extreme-duration heavy load carriage on NM function and walking characteristics.Ten experienced infantrymen performed a 21-h simulated military mission (SMM in a middle-mountain environment with equipment weighing ∼27 kg during battles and ∼43 kg during marches. NM function was evaluated for knee extensors (KE and plantar flexors (PF pre- and immediately post-SMM using isometric maximal voluntary contraction (MVC measurement, neural electrical stimulation and surface EMG. The twitch-interpolation method was used to assess central fatigue. Peripheral changes were examined by stimulating the muscle in the relaxed state. The energy cost, mechanical work and spatio-temporal pattern of walking were also evaluated pre-/post-SMM on an instrumented treadmill in three equipment conditions: Sportswear, Battle and March.After the SMM, MVC declined by -10.2±3.6% for KE (P<0.01 and -10.7±16.1% for PF (P = 0.06. The origin of fatigue was essentially peripheral for both muscle groups. A trend toward low-frequency fatigue was detected for KE (5.5%, P = 0.08. These moderate NM alterations were concomitant with a large increase in perceived fatigue from pre- (rating of 8.3±2.2 to post-SMM (15.9±2.1, P<0.01. The SMM-related fatigue did not alter walking energetics or mechanics, and the different equipment carried on the treadmill did not interact with this fatigue either.this study reports the first data on physiological and biomechanical consequences of extreme-duration heavy load carriage. Unexpectedly, NM function alterations due to the 21-h SMM were moderate and did not

  13. Effects of extreme-duration heavy load carriage on neuromuscular function and locomotion: a military-based study.

    Science.gov (United States)

    Grenier, Jordane G; Millet, Guillaume Y; Peyrot, Nicolas; Samozino, Pierre; Oullion, Roger; Messonnier, Laurent; Morin, Jean-Benoît

    2012-01-01

    Trekking and military missions generally consist of carrying heavy loads for extreme durations. These factors have been separately shown to be sources of neuromuscular (NM) fatigue and locomotor alterations. However, the question of their combined effects remains unresolved, and addressing this issue required a representative context. The aim was to investigate the effects of extreme-duration heavy load carriage on NM function and walking characteristics. Ten experienced infantrymen performed a 21-h simulated military mission (SMM) in a middle-mountain environment with equipment weighing ∼27 kg during battles and ∼43 kg during marches. NM function was evaluated for knee extensors (KE) and plantar flexors (PF) pre- and immediately post-SMM using isometric maximal voluntary contraction (MVC) measurement, neural electrical stimulation and surface EMG. The twitch-interpolation method was used to assess central fatigue. Peripheral changes were examined by stimulating the muscle in the relaxed state. The energy cost, mechanical work and spatio-temporal pattern of walking were also evaluated pre-/post-SMM on an instrumented treadmill in three equipment conditions: Sportswear, Battle and March. After the SMM, MVC declined by -10.2±3.6% for KE (P<0.01) and -10.7±16.1% for PF (P = 0.06). The origin of fatigue was essentially peripheral for both muscle groups. A trend toward low-frequency fatigue was detected for KE (5.5%, P = 0.08). These moderate NM alterations were concomitant with a large increase in perceived fatigue from pre- (rating of 8.3±2.2) to post-SMM (15.9±2.1, P<0.01). The SMM-related fatigue did not alter walking energetics or mechanics, and the different equipment carried on the treadmill did not interact with this fatigue either. this study reports the first data on physiological and biomechanical consequences of extreme-duration heavy load carriage. Unexpectedly, NM function alterations due to the 21-h SMM were moderate and did not alter

  14. Lower extremity joint loads in habitual rearfoot and mid/forefoot strike runners with normal and shortened stride lengths.

    Science.gov (United States)

    Boyer, Elizabeth R; Derrick, Timothy R

    2018-03-01

    Our purpose was to compare joint loads between habitual rearfoot (hRF) and habitual mid/forefoot strikers (hFF), rearfoot (RFS) and mid/forefoot strike (FFS) patterns, and shorter stride lengths (SLs). Thirty-eight hRF and hFF ran at their normal SL, 5% and 10% shorter, as well as with the opposite foot strike. Three-dimensional ankle, knee, patellofemoral (PF) and hip contact forces were calculated. Nearly all contact forces decreased with a shorter SL (1.2-14.9% relative to preferred SL). In general, hRF had higher PF (hRF-RFS: 10.8 ± 1.4, hFF-FFS: 9.9 ± 2.0 BWs) and hip loads (axial hRF-RFS: -9.9 ± 0.9, hFF-FFS: -9.6 ± 1.0 BWs) than hFF. Many loads were similar between foot strike styles for the two groups, including axial and lateral hip, PF, posterior knee and shear ankle contact forces. Lateral knee and posterior hip contact forces were greater for RFS, and axial ankle and knee contact forces were greater for FFS. The tibia may be under greater loading with a FFS because of these greater axial forces. Summarising, a particular foot strike style does not universally decrease joint contact forces. However, shortening one's SL 10% decreased nearly all lower extremity contact forces, so it may hold potential to decrease overuse injuries associated with excessive joint loads.

  15. Angiographic assessment of atherosclerotic load at the lower extremity in patients with diabetic foot and charcot neuro-arthropathy.

    Science.gov (United States)

    Çildağ, Mehmet B; Ertuğrul, Bülent M; Köseoğlu, Ömer Fk; Çildağ, Songül; Armstrong, David G

    2018-06-01

    The aim of this study was to investigate atherosclerotic load at the lower extremity in patients with diabetic foot and charcot neuro-arthropathy and compare them with patients with diabetic foot without charcot neuro-arthropathy. This retrospective study consists of 78 patients with diabetic foot who had lower extremity angiography with antegrade approach. All patients were classified into two groups; neuro ischemic wounds with charcot neuro-arthropathy (30/78) and without charcot neuro-arthropathy (48/78).Atherosclerotic load at the side of diabetic foot was determined by using the Bollinger angiogram scoring method. Comparison of atherosclerotic load between the two groups was performed. The mean of total and infrapopliteal level angiogram scoring of all patients was 33.3 (standard deviation, sd:±17.2) and 29.3 (sd:±15.6), respectively. The mean of total and infrapopliteal level angiogram scoring of neuroischemic wounds with charcot neuro-arthropathy group was 18.1 (sd:±11.6) and 15.7 (sd:±10.4), respectively. The mean of total and infrapopliteal level angiogram scoring of neuroischemic wounds without charcot neuro-arthropathy group was 42.8 (sd:±12.7) and 37.7 (sd:±12.0), respectively. There was a statistically significant difference between the two groups of mean total and infrapopliteal angiogram scoring (p diabetic foot and chronic charcot neuro-arthropathy is significantly less than in patients with neuroischemic diabetic foot wounds without chronic charcot neuro-arthropathy. Copyright © 2017. Published by Elsevier Taiwan LLC.

  16. Prediction of Running Injuries from Training Load: a Machine Learning Approach.

    NARCIS (Netherlands)

    Dijkhuis, Talko; Otter, Ruby; Velthuijsen, H.; Lemmink, Koen A.P.M.

    2017-01-01

    The prediction of the running injuries based on selfreported training data on load is difficult. At present, coaches and researchers have no validated system to predict if a runner has an increased risk of injuries. We aim to develop an algorithm to predict the increase of the risk of a runner to

  17. Theoretical prediction on corrugated sandwich panels under bending loads

    Science.gov (United States)

    Shu, Chengfu; Hou, Shujuan

    2018-05-01

    In this paper, an aluminum corrugated sandwich panel with triangular core under bending loads was investigated. Firstly, the equivalent material parameters of the triangular corrugated core layer, which could be considered as an orthotropic panel, were obtained by using Castigliano's theorem and equivalent homogeneous model. Secondly, contributions of the corrugated core layer and two face panels were both considered to compute the equivalent material parameters of the whole structure through the classical lamination theory, and these equivalent material parameters were compared with finite element analysis solutions. Then, based on the Mindlin orthotropic plate theory, this study obtain the closed-form solutions of the displacement for a corrugated sandwich panel under bending loads in specified boundary conditions, and parameters study and comparison by the finite element method were executed simultaneously.

  18. Reversible Watermarking Using Prediction-Error Expansion and Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Guangyong Gao

    2015-01-01

    Full Text Available Currently, the research for reversible watermarking focuses on the decreasing of image distortion. Aiming at this issue, this paper presents an improvement method to lower the embedding distortion based on the prediction-error expansion (PE technique. Firstly, the extreme learning machine (ELM with good generalization ability is utilized to enhance the prediction accuracy for image pixel value during the watermarking embedding, and the lower prediction error results in the reduction of image distortion. Moreover, an optimization operation for strengthening the performance of ELM is taken to further lessen the embedding distortion. With two popular predictors, that is, median edge detector (MED predictor and gradient-adjusted predictor (GAP, the experimental results for the classical images and Kodak image set indicate that the proposed scheme achieves improvement for the lowering of image distortion compared with the classical PE scheme proposed by Thodi et al. and outperforms the improvement method presented by Coltuc and other existing approaches.

  19. Challenges of extreme load hexapod design and modularization for large ground-based telescopes

    Science.gov (United States)

    Gloess, Rainer; Lula, Brian

    2010-07-01

    The hexapod is a parallel kinematic manipulator that is the minimum arrangement for independent control of six degrees of freedom. Advancing needs for hexapod performance, capacity and configurations have driven development of highly capable new actuator designs. This paper describes new compact hexapod design proposals for high load capacity, and corresponding hexapod actuator only mechanisms suitable for integration as structural motion elements in next-generation telescope designs. These actuators provide up to 90 000N load capability while preserving sub-micrometer positional capability and in-position stability. The design is optimized for low power dissipation and incorporates novel encoders direct manufactured with the nut flange to achieve more than 100000 increments per revolution. In the hexapod design we choose cardan joints for the actuator that have axis offsets to provide optimized stiffness. The additional computational requirements for offset axes are readily solved by advanced kinematic algorithms and modern hardware. The paper also describes the hexapod controller concept with individual actuator designs, which allows the integration of hexapod actuators into the main telescope structure to reduce mass and provide the telescope designer more design freedom in the incorporation of these types of motion systems. An adaptive software package was developed including collision control feature for real-time safety during hexapod movements.

  20. Extremely efficient crystallization of HKUST-1 and Keggin-loaded related phases through the epoxide route.

    Science.gov (United States)

    Oestreicher, Víctor; Jobbágy, Matías

    2017-03-25

    Highly crystalline HKUST-1 and COK-16-like phases were obtained based on a mild in situ alkalinization one-pot epoxide driven method. A slurry composed of finely ground trimesic acid, H 3 BTC, dispersed in a CuCl 2 aqueous solution quantitatively developed well crystallized HKUST-1 after the addition of propylene oxide. The use of solid H 3 BTC ensures a low concentration of free linker, favoring crystalline growth over the precipitation of amorphous or metastable impurities. An extreme space-time yield of 2.1 × 10 5 kg m -3 day -1 was reached, with no linker excess and minimum use of solvent. The method was equally efficient in the achievement of pure NENU/COK-16 phases, containing [PW 12 O 40 ] 3- , [PMo 12 O 40 ] 3- and [SiMo 12 O 40 ] 4- polyoxometalates.

  1. Environmental prediction, risk assessment and extreme events: adaptation strategies for the developing world

    Science.gov (United States)

    Webster, Peter J.; Jian, Jun

    2011-01-01

    The uncertainty associated with predicting extreme weather events has serious implications for the developing world, owing to the greater societal vulnerability to such events. Continual exposure to unanticipated extreme events is a contributing factor for the descent into perpetual and structural rural poverty. We provide two examples of how probabilistic environmental prediction of extreme weather events can support dynamic adaptation. In the current climate era, we describe how short-term flood forecasts have been developed and implemented in Bangladesh. Forecasts of impending floods with horizons of 10 days are used to change agricultural practices and planning, store food and household items and evacuate those in peril. For the first time in Bangladesh, floods were anticipated in 2007 and 2008, with broad actions taking place in advance of the floods, grossing agricultural and household savings measured in units of annual income. We argue that probabilistic environmental forecasts disseminated to an informed user community can reduce poverty caused by exposure to unanticipated extreme events. Second, it is also realized that not all decisions in the future can be made at the village level and that grand plans for water resource management require extensive planning and funding. Based on imperfect models and scenarios of economic and population growth, we further suggest that flood frequency and intensity will increase in the Ganges, Brahmaputra and Yangtze catchments as greenhouse-gas concentrations increase. However, irrespective of the climate-change scenario chosen, the availability of fresh water in the latter half of the twenty-first century seems to be dominated by population increases that far outweigh climate-change effects. Paradoxically, fresh water availability may become more critical if there is no climate change. PMID:22042897

  2. Predictability of extreme weather events for NE U.S.: improvement of the numerical prediction using a Bayesian regression approach

    Science.gov (United States)

    Yang, J.; Astitha, M.; Anagnostou, E. N.; Hartman, B.; Kallos, G. B.

    2015-12-01

    Weather prediction accuracy has become very important for the Northeast U.S. given the devastating effects of extreme weather events in the recent years. Weather forecasting systems are used towards building strategies to prevent catastrophic losses for human lives and the environment. Concurrently, weather forecast tools and techniques have evolved with improved forecast skill as numerical prediction techniques are strengthened by increased super-computing resources. In this study, we examine the combination of two state-of-the-science atmospheric models (WRF and RAMS/ICLAMS) by utilizing a Bayesian regression approach to improve the prediction of extreme weather events for NE U.S. The basic concept behind the Bayesian regression approach is to take advantage of the strengths of two atmospheric modeling systems and, similar to the multi-model ensemble approach, limit their weaknesses which are related to systematic and random errors in the numerical prediction of physical processes. The first part of this study is focused on retrospective simulations of seventeen storms that affected the region in the period 2004-2013. Optimal variances are estimated by minimizing the root mean square error and are applied to out-of-sample weather events. The applicability and usefulness of this approach are demonstrated by conducting an error analysis based on in-situ observations from meteorological stations of the National Weather Service (NWS) for wind speed and wind direction, and NCEP Stage IV radar data, mosaicked from the regional multi-sensor for precipitation. The preliminary results indicate a significant improvement in the statistical metrics of the modeled-observed pairs for meteorological variables using various combinations of the sixteen events as predictors of the seventeenth. This presentation will illustrate the implemented methodology and the obtained results for wind speed, wind direction and precipitation, as well as set the research steps that will be

  3. Fat or lean: adjustment of endogenous energy stores to predictable and unpredictable changes in allostatic load

    Science.gov (United States)

    Schultner, Jannik; Kitaysky, Alexander S.; Welcker, Jorg; Hatch, Scott

    2013-01-01

    1. The ability to store energy endogenously is an important ecological mechanism that allows animals to buffer predictable and unpredictable variation in allostatic load. The secretion of glucocorticoids, which reflects changes in allostatic load, is suggested to play a major role in the adjustment of endogenous stores to these varying conditions.

  4. Development of an aerodyanmic theory capable of predicting surface loads on slender wings with vortex flow

    Science.gov (United States)

    Gloss, B. B.; Johnson, F. T.

    1976-01-01

    The Boeing Commercial Airplane Company developed an inviscid three-dimensional lifting surface method that shows promise in being able to accurately predict loads, subsonic and supersonic, on wings with leading-edge separation and reattachment.

  5. Extrinsic Cognitive Load Impairs Spoken Word Recognition in High- and Low-Predictability Sentences.

    Science.gov (United States)

    Hunter, Cynthia R; Pisoni, David B

    Listening effort (LE) induced by speech degradation reduces performance on concurrent cognitive tasks. However, a converse effect of extrinsic cognitive load on recognition of spoken words in sentences has not been shown. The aims of the present study were to (a) examine the impact of extrinsic cognitive load on spoken word recognition in a sentence recognition task and (b) determine whether cognitive load and/or LE needed to understand spectrally degraded speech would differentially affect word recognition in high- and low-predictability sentences. Downstream effects of speech degradation and sentence predictability on the cognitive load task were also examined. One hundred twenty young adults identified sentence-final spoken words in high- and low-predictability Speech Perception in Noise sentences. Cognitive load consisted of a preload of short (low-load) or long (high-load) sequences of digits, presented visually before each spoken sentence and reported either before or after identification of the sentence-final word. LE was varied by spectrally degrading sentences with four-, six-, or eight-channel noise vocoding. Level of spectral degradation and order of report (digits first or words first) were between-participants variables. Effects of cognitive load, sentence predictability, and speech degradation on accuracy of sentence-final word identification as well as recall of preload digit sequences were examined. In addition to anticipated main effects of sentence predictability and spectral degradation on word recognition, we found an effect of cognitive load, such that words were identified more accurately under low load than high load. However, load differentially affected word identification in high- and low-predictability sentences depending on the level of sentence degradation. Under severe spectral degradation (four-channel vocoding), the effect of cognitive load on word identification was present for high-predictability sentences but not for low-predictability

  6. Effect of Enhanced Air Temperature (extreme heat, and Load of Non-Linear Against the Use of Electric Power

    Directory of Open Access Journals (Sweden)

    I Ketut Wijaya

    2015-12-01

    Full Text Available Usage Electric power is very easy to do, because the infrastructure for connecting  already available and widely sold. Consumption electric power is not accompanied by the ability to recognize electric power. The average increase of electricity power in Bali in extreme weather reaches 10% in years 2014, so that Bali suffered power shortages and PLN as the manager of electric power to perform scheduling on of electric power usage. Scheduling is done because many people use electric power as the load  of fan and Air Conditioner exceeding the previous time. Load of fan, air conditioning, and computers including non-linear loads which can add heat on the conductor of electricity. Non-linear load and hot weather can lead to heat on conductor so  insulation damaged  and cause electrical short circuit. Data of electric power obtained through questionnaires, surveys, measurement and retrieve data from various parties. Fires that occurred in 2014, namely 109 events, 44 is  event caused by an electric short circuit (approximately 40%. Decrease power factors can cause losses of electricity and hot. Heat can cause and adds heat on the  conductor electric. The analysis showed  understanding electric power of the average  is 27,700 with value between 20 to 40. So an understanding of the electrical power away from the understand so that many errors because of the act own. Installation tool ELCB very necessary but very necessary provide counseling   of electricity to the community.

  7. Extreme events and predictability of catastrophic failure in composite materials and in the Earth

    Science.gov (United States)

    Main, I.; Naylor, M.

    2012-05-01

    Despite all attempts to isolate and predict extreme earthquakes, these nearly always occur without obvious warning in real time: fully deterministic earthquake prediction is very much a `black swan'. On the other hand engineering-scale samples of rocks and other composite materials often show clear precursors to dynamic failure under controlled conditions in the laboratory, and successful evacuations have occurred before several volcanic eruptions. This may be because extreme earthquakes are not statistically special, being an emergent property of the process of dynamic rupture. Nevertheless, probabilistic forecasting of event rate above a given size, based on the tendency of earthquakes to cluster in space and time, can have significant skill compared to say random failure, even in real-time mode. We address several questions in this debate, using examples from the Earth (earthquakes, volcanoes) and the laboratory, including the following. How can we identify `characteristic' events, i.e. beyond the power law, in model selection (do dragon-kings exist)? How do we discriminate quantitatively between stationary and non-stationary hazard models (is a dragon likely to come soon)? Does the system size (the size of the dragon's domain) matter? Are there localising signals of imminent catastrophic failure we may not be able to access (is the dragon effectively invisible on approach)? We focus on the effect of sampling effects and statistical uncertainty in the identification of extreme events and their predictability, and highlight the strong influence of scaling in space and time as an outstanding issue to be addressed by quantitative studies, experimentation and models.

  8. SWAT Model Prediction of Phosphorus Loading in a South Carolina Karst Watershed with a Downstream Embayment

    Science.gov (United States)

    Devendra M. Amatya; Manoj K. Jha; Thomas M. Williams; Amy E. Edwards; Daniel R.. Hitchcock

    2013-01-01

    The SWAT model was used to predict total phosphorus (TP) loadings for a 1555-ha karst watershed—Chapel Branch Creek (CBC)—which drains to a lake via a reservoir-like embayment (R-E). The model was first tested for monthly streamflow predictions from tributaries draining three potential source areas as well as the downstream R-E, followed by TP loadings using data...

  9. Comparative analysis of methods for modelling the short-term probability distribution of extreme wind turbine loads

    DEFF Research Database (Denmark)

    Dimitrov, Nikolay Krasimirov

    2016-01-01

    We have tested the performance of statistical extrapolation methods in predicting the extreme response of a multi-megawatt wind turbine generator. We have applied the peaks-over-threshold, block maxima and average conditional exceedance rates (ACER) methods for peaks extraction, combined with four...... levels, based on the assumption that the response tail is asymptotically Gumbel distributed. Example analyses were carried out, aimed at comparing the different methods, analysing the statistical uncertainties and identifying the factors, which are critical to the accuracy and reliability...

  10. Fatigue life prediction of fiber reinforced concrete under flexural load

    DEFF Research Database (Denmark)

    Zhang, Jun; Stang, Henrik; Li, Victor

    1999-01-01

    This paper presents a semi-analytical method to predict fatigue behavior in flexure of fiber reinforced concrete (FRC) based on the equilibrium of force in the critical cracked section. The model relies on the cyclic bridging law, the so-called stress-crack width relationship under cyclic tensile...

  11. Early Conventional MRI for Prediction of Neurodevelopmental Impairment in Extremely-Low-Birth-Weight Infants.

    Science.gov (United States)

    Slaughter, Laurel A; Bonfante-Mejia, Eliana; Hintz, Susan R; Dvorchik, Igor; Parikh, Nehal A

    2016-01-01

    Extremely-low-birth-weight (ELBW; ≤1,000 g) infants are at high risk for neurodevelopmental impairments. Conventional brain MRI at term-equivalent age is increasingly used for prediction of outcomes. However, optimal prediction models remain to be determined, especially for cognitive outcomes. The aim was to evaluate the accuracy of a data-driven MRI scoring system to predict neurodevelopmental impairments. 122 ELBW infants had a brain MRI performed at term-equivalent age. Conventional MRI findings were scored with a standardized algorithm and tested using a multivariable regression model to predict neurodevelopmental impairment, defined as one or more of the following at 18-24 months' corrected age: cerebral palsy, bilateral blindness, bilateral deafness requiring amplification, and/or cognitive/language delay. Results were compared with a commonly cited scoring system. In multivariable analyses, only moderate-to-severe gyral maturational delay was a significant predictor of overall neurodevelopmental impairment (OR: 12.6, 95% CI: 2.6, 62.0; p neurodevelopmental impairment/death. Diffuse cystic abnormality was a significant predictor of cerebral palsy (OR: 33.6, 95% CI: 4.9, 229.7; p neurodevelopmental impairment. In our cohort, conventional MRI at term-equivalent age exhibited high specificity in predicting neurodevelopmental outcomes. However, sensitivity was suboptimal, suggesting additional clinical factors and biomarkers are needed to enable accurate prognostication. © 2016 S. Karger AG, Basel.

  12. The Prediction of Yarn Elongation of Kenyan Ring-Spun Yarn using Extreme Learning Machines (ELM

    Directory of Open Access Journals (Sweden)

    Josphat Igadwa Mwasiagi

    2017-03-01

    Full Text Available The optimization of the manufacture of cotton yarns involves several processes, while the prediction of yarn quality parameters forms an important area of investigation. This research work concentrated on the prediction of cotton yarn elongation. Cotton lint and yarn samples were collected in textile factories in Kenya.The collected samples were tested under standard testing conditions. Cotton lint parameters, machine parameters and yarn elongation were used to design yarn elongation prediction models. The elongation prediction models used three network training algorithms, including backpropagation (BP, an extreme learning machine (ELM, and a hybrid of differential evolution (DE and an ELM referred to as DE-ELM. The prediction models recorded a mean squared error (mse value of 0.001 using 11, 43 and 2 neurons in the hidden layer for the BP, ELM and DE-ELM models respectively. The ELM models exhibited faster training speeds than the BP algorithms, but required more neurons in the hidden layer than other models. The DEELM hybrid algorithm was faster than the BP algorithm, but slower than the ELM algorithm.

  13. Dosimetric properties of carbon loaded LiF detectors for beta photon extremity dosimetry

    International Nuclear Information System (INIS)

    Burgkhardt, B.; Klipfel, A.

    1990-01-01

    The dosimetric properties of carbon loaded LiF detectors manufactured by Alnor and Vinten are presented in comparison with various LiF detectors. In particular, the beta and photon response, the residual reading after repeated annealing in the oven or reader as well as light sensitivity and fading are discussed. In comparison with LiF detectors of 240 mg.cm -2 , LiF + C detectors indicate a photon response of only 2% and in finger rings irradiated on a finger phantom an unexpected high photon energy response. Regarding repeated use, oven annealing in air or N 2 affects mainly Vinten LiF + 1% C by discoloration and reduces the 147 Pm response of LiF + C detectors by between 1% and 6% per N 2 annealing, whereas reader annealing in the Toledo and Alnor reader does not affect the relative beta response. The residual dose H 0 of LiF + C remains sufficiently low after oven annealing, but increases for Alnor LiF + 4% C after reader annealing, which is therefore more suitable for Vinten LiF + 1% C. Spurious detector reading exceeds H 0 and its standard deviation by a factor of 2 to 3. (author)

  14. Nonhydrostatic and surfbeat model predictions of extreme wave run-up in fringing reef environments

    Science.gov (United States)

    Lashley, Christopher H.; Roelvink, Dano; van Dongeren, Ap R.; Buckley, Mark L.; Lowe, Ryan J.

    2018-01-01

    The accurate prediction of extreme wave run-up is important for effective coastal engineering design and coastal hazard management. While run-up processes on open sandy coasts have been reasonably well-studied, very few studies have focused on understanding and predicting wave run-up at coral reef-fronted coastlines. This paper applies the short-wave resolving, Nonhydrostatic (XB-NH) and short-wave averaged, Surfbeat (XB-SB) modes of the XBeach numerical model to validate run-up using data from two 1D (alongshore uniform) fringing-reef profiles without roughness elements, with two objectives: i) to provide insight into the physical processes governing run-up in such environments; and ii) to evaluate the performance of both modes in accurately predicting run-up over a wide range of conditions. XBeach was calibrated by optimizing the maximum wave steepness parameter (maxbrsteep) in XB-NH and the dissipation coefficient (alpha) in XB-SB) using the first dataset; and then applied to the second dataset for validation. XB-NH and XB-SB predictions of extreme wave run-up (Rmax and R2%) and its components, infragravity- and sea-swell band swash (SIG and SSS) and shoreline setup (), were compared to observations. XB-NH more accurately simulated wave transformation but under-predicted shoreline setup due to its exclusion of parameterized wave-roller dynamics. XB-SB under-predicted sea-swell band swash but overestimated shoreline setup due to an over-prediction of wave heights on the reef flat. Run-up (swash) spectra were dominated by infragravity motions, allowing the short-wave (but not wave group) averaged model (XB-SB) to perform comparably well to its more complete, short-wave resolving (XB-NH) counterpart. Despite their respective limitations, both modes were able to accurately predict Rmax and R2%.

  15. A study of the importance of occupancy to building cooling load in prediction by intelligent approach

    International Nuclear Information System (INIS)

    Kwok, Simon S.K.; Lee, Eric W.M.

    2011-01-01

    Research highlights: → The building occupancy affecting the cooling load prediction is studied. → PENN model is adopted in this study for predicting the building cooling load. → Statistical approach is adopted to result a less prejudice prediction performance. → Results show that occupancy data can significantly improve the prediction. -- Abstract: Building cooling load prediction is one of the key factors in the success of energy-saving measures. Many computational models available in the industry today have been developed from either forward or inverse modeling approaches. However, most of these models require extensive computer resources and involve lengthy computation. This paper discusses the use of data-driven intelligent approaches, a probabilistic entropy-based neural (PENN) model to predict the cooling load of a building. Although it is common knowledge that the presence and activity of building occupants have a significant impact on the required cooling load of buildings, practices currently adopted in modeling the presence and activity of people in buildings do not reflect the complexity of the impact occupants have on building cooling load. In contrast to previous artificial neural network (ANN) models, most of which employ a fixed schedule or historic load data to represent building occupancy in simulating building cooling load, this paper introduces two input parameters, dynamic occupancy area and rate and uses it to mimic building cooling load. The training samples used include weather data obtained from the Hong Kong Observatory and building-related data acquired from an existing grade A mega office buildings in Hong Kong with tenants including many multi-national financial companies that require 24-h air conditioning seven days a week. The dynamic changes that occur in the occupancy of these buildings therefore make it very difficult to forecast building cooling load by means of a fixed time schedule. The performance of simulation results

  16. A study of the importance of occupancy to building cooling load in prediction by intelligent approach

    Energy Technology Data Exchange (ETDEWEB)

    Kwok, Simon S.K. [Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong (Hong Kong); Lee, Eric W.M., E-mail: ericlee@cityu.edu.h [Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong (Hong Kong)

    2011-07-15

    Research highlights: {yields} The building occupancy affecting the cooling load prediction is studied. {yields} PENN model is adopted in this study for predicting the building cooling load. {yields} Statistical approach is adopted to result a less prejudice prediction performance. {yields} Results show that occupancy data can significantly improve the prediction. -- Abstract: Building cooling load prediction is one of the key factors in the success of energy-saving measures. Many computational models available in the industry today have been developed from either forward or inverse modeling approaches. However, most of these models require extensive computer resources and involve lengthy computation. This paper discusses the use of data-driven intelligent approaches, a probabilistic entropy-based neural (PENN) model to predict the cooling load of a building. Although it is common knowledge that the presence and activity of building occupants have a significant impact on the required cooling load of buildings, practices currently adopted in modeling the presence and activity of people in buildings do not reflect the complexity of the impact occupants have on building cooling load. In contrast to previous artificial neural network (ANN) models, most of which employ a fixed schedule or historic load data to represent building occupancy in simulating building cooling load, this paper introduces two input parameters, dynamic occupancy area and rate and uses it to mimic building cooling load. The training samples used include weather data obtained from the Hong Kong Observatory and building-related data acquired from an existing grade A mega office buildings in Hong Kong with tenants including many multi-national financial companies that require 24-h air conditioning seven days a week. The dynamic changes that occur in the occupancy of these buildings therefore make it very difficult to forecast building cooling load by means of a fixed time schedule. The performance of

  17. Optimized Extreme Learning Machine for Power System Transient Stability Prediction Using Synchrophasors

    Directory of Open Access Journals (Sweden)

    Yanjun Zhang

    2015-01-01

    Full Text Available A new optimized extreme learning machine- (ELM- based method for power system transient stability prediction (TSP using synchrophasors is presented in this paper. First, the input features symbolizing the transient stability of power systems are extracted from synchronized measurements. Then, an ELM classifier is employed to build the TSP model. And finally, the optimal parameters of the model are optimized by using the improved particle swarm optimization (IPSO algorithm. The novelty of the proposal is in the fact that it improves the prediction performance of the ELM-based TSP model by using IPSO to optimize the parameters of the model with synchrophasors. And finally, based on the test results on both IEEE 39-bus system and a large-scale real power system, the correctness and validity of the presented approach are verified.

  18. Prediction of laser cutting heat affected zone by extreme learning machine

    Science.gov (United States)

    Anicic, Obrad; Jović, Srđan; Skrijelj, Hivzo; Nedić, Bogdan

    2017-01-01

    Heat affected zone (HAZ) of the laser cutting process may be developed based on combination of different factors. In this investigation the HAZ forecasting, based on the different laser cutting parameters, was analyzed. The main goal was to predict the HAZ according to three inputs. The purpose of this research was to develop and apply the Extreme Learning Machine (ELM) to predict the HAZ. The ELM results were compared with genetic programming (GP) and artificial neural network (ANN). The reliability of the computational models were accessed based on simulation results and by using several statistical indicators. Based upon simulation results, it was demonstrated that ELM can be utilized effectively in applications of HAZ forecasting.

  19. Mixed price and load forecasting of electricity markets by a new iterative prediction method

    International Nuclear Information System (INIS)

    Amjady, Nima; Daraeepour, Ali

    2009-01-01

    Load and price forecasting are the two key issues for the participants of current electricity markets. However, load and price of electricity markets have complex characteristics such as nonlinearity, non-stationarity and multiple seasonality, to name a few (usually, more volatility is seen in the behavior of electricity price signal). For these reasons, much research has been devoted to load and price forecast, especially in the recent years. However, previous research works in the area separately predict load and price signals. In this paper, a mixed model for load and price forecasting is presented, which can consider interactions of these two forecast processes. The mixed model is based on an iterative neural network based prediction technique. It is shown that the proposed model can present lower forecast errors for both load and price compared with the previous separate frameworks. Another advantage of the mixed model is that all required forecast features (from load or price) are predicted within the model without assuming known values for these features. So, the proposed model can better be adapted to real conditions of an electricity market. The forecast accuracy of the proposed mixed method is evaluated by means of real data from the New York and Spanish electricity markets. The method is also compared with some of the most recent load and price forecast techniques. (author)

  20. Predictive Scheduling for Electric Vehicles Considering Uncertainty of Load and User Behaviors

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Bin; Huang, Rui; Wang, Yubo; Nazaripouya, Hamidreza; Qiu, Charlie; Chu, Chi-Cheng; Gadh, Rajit

    2016-05-02

    Un-coordinated Electric Vehicle (EV) charging can create unexpected load in local distribution grid, which may degrade the power quality and system reliability. The uncertainty of EV load, user behaviors and other baseload in distribution grid, is one of challenges that impedes optimal control for EV charging problem. Previous researches did not fully solve this problem due to lack of real-world EV charging data and proper stochastic model to describe these behaviors. In this paper, we propose a new predictive EV scheduling algorithm (PESA) inspired by Model Predictive Control (MPC), which includes a dynamic load estimation module and a predictive optimization module. The user-related EV load and base load are dynamically estimated based on the historical data. At each time interval, the predictive optimization program will be computed for optimal schedules given the estimated parameters. Only the first element from the algorithm outputs will be implemented according to MPC paradigm. Current-multiplexing function in each Electric Vehicle Supply Equipment (EVSE) is considered and accordingly a virtual load is modeled to handle the uncertainties of future EV energy demands. This system is validated by the real-world EV charging data collected on UCLA campus and the experimental results indicate that our proposed model not only reduces load variation up to 40% but also maintains a high level of robustness. Finally, IEC 61850 standard is utilized to standardize the data models involved, which brings significance to more reliable and large-scale implementation.

  1. Predicting mass loading as a function of pressure difference across prefilter/HEPA filter systems

    International Nuclear Information System (INIS)

    Novick, V.J.; Klassen, J.F.; Monson, P.R.

    1992-01-01

    The purpose of this work is to develop a methodology for predicting the mass loading and pressure drop effects on a prefilter/ HEPA filter system. The methodology relies on the use of empirical equations for the specific resistance of the aerosol loaded filter as a function of the particle diameter. These correlations relate the pressure difference across a filter to the mass loading on the filter and accounts for aerosol particle density effects. These predictions are necessary for the efficient design of new filtration systems and for risk assessment studies of existing filter systems. This work specifically addresses the prefilter/HEPA filter Airborne Activity Confinement Systems (AACS) at the Savannah River Plant. In order to determine the mass loading on the system, it is necessary to establish the efficiency characteristics for the prefilter, the mass loading characteristics of the prefilter measured as a function of pressure difference across the prefilter, and the mass loading characteristics of the HEPA filter as a function of pressure difference across the filter. Furthermore, the efficiency and mass loading characteristics need to be determined as a function of the aerosol particle diameter. A review of the literature revealed that no previous work had been performed to characterize the prefilter material of interest. In order to complete the foundation of information necessary to predict total mass loadings on prefilter/HEPA filter systems, it was necessary to determine the prefilter efficiency and mass loading characteristics. The measured prefilter characteristics combined with the previously determined HEPA filter characteristics allowed the resulting pressure difference across both filters to be predicted as a function of total particle mass for a given particle distribution. These predictions compare favorably to experimental measurements (±25%)

  2. The effect of prosthetic foot push-off on mechanical loading associated with knee osteoarthritis in lower extremity amputees.

    Science.gov (United States)

    Morgenroth, David C; Segal, Ava D; Zelik, Karl E; Czerniecki, Joseph M; Klute, Glenn K; Adamczyk, Peter G; Orendurff, Michael S; Hahn, Michael E; Collins, Steven H; Kuo, Art D

    2011-10-01

    Lower extremity amputation not only limits mobility, but also increases the risk of knee osteoarthritis of the intact limb. Dynamic walking models of non-amputees suggest that pushing-off from the trailing limb can reduce collision forces on the leading limb. These collision forces may determine the peak knee external adduction moment (EAM), which has been linked to the development of knee OA in the general population. We therefore hypothesized that greater prosthetic push-off would lead to reduced loading and knee EAM of the intact limb in unilateral transtibial amputees. Seven unilateral transtibial amputees were studied during gait under three prosthetic foot conditions that were intended to vary push-off. Prosthetic foot-ankle push-off work, intact limb knee EAM and ground reaction impulses for both limbs during step-to-step transition were measured. Overall, trailing limb prosthetic push-off work was negatively correlated with leading intact limb 1st peak knee EAM (slope=-.72±.22; p=.011). Prosthetic push-off work and 1st peak intact knee EAM varied significantly with foot type. The prosthetic foot condition with the least push-off demonstrated the largest knee EAM, which was reduced by 26% with the prosthetic foot producing the most push-off. Trailing prosthetic limb push-off impulse was negatively correlated with leading intact limb loading impulse (slope=-.34±.14; p=.001), which may help explain how prosthetic limb push-off can affect intact limb loading. Prosthetic feet that perform more prosthetic push-off appear to be associated with a reduction in 1st peak intact knee EAM, and their use could potentially reduce the risk and burden of knee osteoarthritis in this population. Published by Elsevier B.V.

  3. A Novel Online Sequential Extreme Learning Machine for Gas Utilization Ratio Prediction in Blast Furnaces

    Directory of Open Access Journals (Sweden)

    Yanjiao Li

    2017-08-01

    Full Text Available Gas utilization ratio (GUR is an important indicator used to measure the operating status and energy consumption of blast furnaces (BFs. In this paper, we present a soft-sensor approach, i.e., a novel online sequential extreme learning machine (OS-ELM named DU-OS-ELM, to establish a data-driven model for GUR prediction. In DU-OS-ELM, firstly, the old collected data are discarded gradually and the newly acquired data are given more attention through a novel dynamic forgetting factor (DFF, depending on the estimation errors to enhance the dynamic tracking ability. Furthermore, we develop an updated selection strategy (USS to judge whether the model needs to be updated with the newly coming data, so that the proposed approach is more in line with the actual production situation. Then, the convergence analysis of the proposed DU-OS-ELM is presented to ensure the estimation of output weight converge to the true value with the new data arriving. Meanwhile, the proposed DU-OS-ELM is applied to build a soft-sensor model to predict GUR. Experimental results demonstrate that the proposed DU-OS-ELM obtains better generalization performance and higher prediction accuracy compared with a number of existing related approaches using the real production data from a BF and the created GUR prediction model can provide an effective guidance for further optimization operation.

  4. A Novel Online Sequential Extreme Learning Machine for Gas Utilization Ratio Prediction in Blast Furnaces.

    Science.gov (United States)

    Li, Yanjiao; Zhang, Sen; Yin, Yixin; Xiao, Wendong; Zhang, Jie

    2017-08-10

    Gas utilization ratio (GUR) is an important indicator used to measure the operating status and energy consumption of blast furnaces (BFs). In this paper, we present a soft-sensor approach, i.e., a novel online sequential extreme learning machine (OS-ELM) named DU-OS-ELM, to establish a data-driven model for GUR prediction. In DU-OS-ELM, firstly, the old collected data are discarded gradually and the newly acquired data are given more attention through a novel dynamic forgetting factor (DFF), depending on the estimation errors to enhance the dynamic tracking ability. Furthermore, we develop an updated selection strategy (USS) to judge whether the model needs to be updated with the newly coming data, so that the proposed approach is more in line with the actual production situation. Then, the convergence analysis of the proposed DU-OS-ELM is presented to ensure the estimation of output weight converge to the true value with the new data arriving. Meanwhile, the proposed DU-OS-ELM is applied to build a soft-sensor model to predict GUR. Experimental results demonstrate that the proposed DU-OS-ELM obtains better generalization performance and higher prediction accuracy compared with a number of existing related approaches using the real production data from a BF and the created GUR prediction model can provide an effective guidance for further optimization operation.

  5. Daily sea level prediction at Chiayi coast, Taiwan using extreme learning machine and relevance vector machine

    Science.gov (United States)

    Imani, Moslem; Kao, Huan-Chin; Lan, Wen-Hau; Kuo, Chung-Yen

    2018-02-01

    The analysis and the prediction of sea level fluctuations are core requirements of marine meteorology and operational oceanography. Estimates of sea level with hours-to-days warning times are especially important for low-lying regions and coastal zone management. The primary purpose of this study is to examine the applicability and capability of extreme learning machine (ELM) and relevance vector machine (RVM) models for predicting sea level variations and compare their performances with powerful machine learning methods, namely, support vector machine (SVM) and radial basis function (RBF) models. The input dataset from the period of January 2004 to May 2011 used in the study was obtained from the Dongshi tide gauge station in Chiayi, Taiwan. Results showed that the ELM and RVM models outperformed the other methods. The performance of the RVM approach was superior in predicting the daily sea level time series given the minimum root mean square error of 34.73 mm and the maximum determination coefficient of 0.93 (R2) during the testing periods. Furthermore, the obtained results were in close agreement with the original tide-gauge data, which indicates that RVM approach is a promising alternative method for time series prediction and could be successfully used for daily sea level forecasts.

  6. The Hybrid of Classification Tree and Extreme Learning Machine for Permeability Prediction in Oil Reservoir

    KAUST Repository

    Prasetyo Utomo, Chandra

    2011-06-01

    Permeability is an important parameter connected with oil reservoir. Predicting the permeability could save millions of dollars. Unfortunately, petroleum engineers have faced numerous challenges arriving at cost-efficient predictions. Much work has been carried out to solve this problem. The main challenge is to handle the high range of permeability in each reservoir. For about a hundred year, mathematicians and engineers have tried to deliver best prediction models. However, none of them have produced satisfying results. In the last two decades, artificial intelligence models have been used. The current best prediction model in permeability prediction is extreme learning machine (ELM). It produces fairly good results but a clear explanation of the model is hard to come by because it is so complex. The aim of this research is to propose a way out of this complexity through the design of a hybrid intelligent model. In this proposal, the system combines classification and regression models to predict the permeability value. These are based on the well logs data. In order to handle the high range of the permeability value, a classification tree is utilized. A benefit of this innovation is that the tree represents knowledge in a clear and succinct fashion and thereby avoids the complexity of all previous models. Finally, it is important to note that the ELM is used as a final predictor. Results demonstrate that this proposed hybrid model performs better when compared with support vector machines (SVM) and ELM in term of correlation coefficient. Moreover, the classification tree model potentially leads to better communication among petroleum engineers concerning this important process and has wider implications for oil reservoir management efficiency.

  7. Statistical Model of Extreme Shear

    DEFF Research Database (Denmark)

    Larsen, Gunner Chr.; Hansen, Kurt Schaldemose

    2004-01-01

    In order to continue cost-optimisation of modern large wind turbines, it is important to continously increase the knowledge on wind field parameters relevant to design loads. This paper presents a general statistical model that offers site-specific prediction of the probability density function...... by a model that, on a statistically consistent basis, describe the most likely spatial shape of an extreme wind shear event. Predictions from the model have been compared with results from an extreme value data analysis, based on a large number of high-sampled full-scale time series measurements...... are consistent, given the inevitabel uncertainties associated with model as well as with the extreme value data analysis. Keywords: Statistical model, extreme wind conditions, statistical analysis, turbulence, wind loading, statistical analysis, turbulence, wind loading, wind shear, wind turbines....

  8. Towards building a neural network model for predicting pile static load test curves

    Directory of Open Access Journals (Sweden)

    Alzo’ubi A. K.

    2018-01-01

    Full Text Available In the United Arab Emirates, Continuous Flight Auger piles are the most widely used type of deep foundation. To test the pile behaviour, the Static Load Test is routinely conducted in the field by increasing the dead load while monitoring the displacement. Although the test is reliable, it is expensive to conduct. This test is usually conducted in the UAE to verify the pile capacity and displacement as the load increase and decreases in two cycles. In this paper we will utilize the Artificial Neural Network approach to build a model that can predict a complete Static Load Pile test. We will show that by integrating the pile configuration, soil properties, and ground water table in one artificial neural network model, the Static Load Test can be predicted with confidence. We believe that based on this approach, the model is able to predict the entire pile load test from start to end. The suggested approach is an excellent tool to reduce the cost associated with such expensive tests or to predict pile’s performance ahead of the actual test.

  9. Large-strain time-temperature equivalence in high density polyethylene for prediction of extreme deformation and damage

    Directory of Open Access Journals (Sweden)

    Gray G.T.

    2012-08-01

    Full Text Available Time-temperature equivalence is a widely recognized property of many time-dependent material systems, where there is a clear predictive link relating the deformation response at a nominal temperature and a high strain-rate to an equivalent response at a depressed temperature and nominal strain-rate. It has been found that high-density polyethylene (HDPE obeys a linear empirical formulation relating test temperature and strain-rate. This observation was extended to continuous stress-strain curves, such that material response measured in a load frame at large strains and low strain-rates (at depressed temperatures could be translated into a temperature-dependent response at high strain-rates and validated against Taylor impact results. Time-temperature equivalence was used in conjuction with jump-rate compression tests to investigate isothermal response at high strain-rate while exluding adiabatic heating. The validated constitutive response was then applied to the analysis of Dynamic-Tensile-Extrusion of HDPE, a tensile analog to Taylor impact developed at LANL. The Dyn-Ten-Ext test results and FEA found that HDPE deformed smoothly after exiting the die, and after substantial drawing appeared to undergo a pressure-dependent shear damage mechanism at intermediate velocities, while it fragmented at high velocities. Dynamic-Tensile-Extrusion, properly coupled with a validated constitutive model, can successfully probe extreme tensile deformation and damage of polymers.

  10. Short-Term Power Load Point Prediction Based on the Sharp Degree and Chaotic RBF Neural Network

    Directory of Open Access Journals (Sweden)

    Dongxiao Niu

    2015-01-01

    Full Text Available In order to realize the predicting and positioning of short-term load inflection point, this paper made reference to related research in the field of computer image recognition. It got a load sharp degree sequence by the transformation of the original load sequence based on the algorithm of sharp degree. Then this paper designed a forecasting model based on the chaos theory and RBF neural network. It predicted the load sharp degree sequence based on the forecasting model to realize the positioning of short-term load inflection point. Finally, in the empirical example analysis, this paper predicted the daily load point of a region using the actual load data of the certain region to verify the effectiveness and applicability of this method. Prediction results showed that most of the test sample load points could be accurately predicted.

  11. The use of geoinformatic data and spatial analysis to predict faecal pollution during extreme precipitation events

    Science.gov (United States)

    Ward, Ray; Purnell, Sarah; Ebdon, James; Nnane, Daniel; Taylor, Huw

    2013-04-01

    The Water Framework Directive (WFD) regulates surface water quality standards in the European Union (EU). The Directive call for the identification and management of point and diffuse sources of pollution and requires the establishment of a 'programme of measures' for identified river basin districts, in order to achieve a "good status" by 2015. The hygienic quality of water is normally monitored using faecal indicator organisms (FIO), such as Escherichia coli, which indicate a potential risk to public health from human waterborne pathogens. Environmental factors influence the transmission of these pathogens and indicator organisms, and statistically significant relationships have been found between rainfall and outbreaks of waterborne disease. Climate change has been predicted to lead to an increase in severe weather events in many parts of Europe, including an increase in the frequency of extreme rainfall events. This in turn is likely to lead to an increase in incidents of human waterborne disease in Europe, unless measures are taken to predict and mitigate for such events. This study investigates a variety of environmental factors that influence the concentration of FIO in surface waters receiving faecal contamination from a variety of sources. Levels of FIO, including Escherichia coli, intestinal enterococci, somatic coliphage and GB124 (a human-specific microbial source tracking marker), were monitored in the Sussex Ouse catchment in Southeast England over a period of 26 months. These data were combined with geoinformatic environmental data within a GIS to map faecal contamination within the river. Previously, precipitation and soil erosion have been identified as major factors that can influence the concentration of these faecal markers, and studies have shown that slope, soil type and vegetation influence both the mechanisms and the rate by which erosion occurs in river catchments. Of the environmental variables studied, extreme precipitation was found to

  12. Predicting lower body power from vertical jump prediction equations for loaded jump squats at different intensities in men and women.

    Science.gov (United States)

    Wright, Glenn A; Pustina, Andrew A; Mikat, Richard P; Kernozek, Thomas W

    2012-03-01

    The purpose of this study was to determine the efficacy of estimating peak lower body power from a maximal jump squat using 3 different vertical jump prediction equations. Sixty physically active college students (30 men, 30 women) performed jump squats with a weighted bar's applied load of 20, 40, and 60% of body mass across the shoulders. Each jump squat was simultaneously monitored using a force plate and a contact mat. Peak power (PP) was calculated using vertical ground reaction force from the force plate data. Commonly used equations requiring body mass and vertical jump height to estimate PP were applied such that the system mass (mass of body + applied load) was substituted for body mass. Jump height was determined from flight time as measured with a contact mat during a maximal jump squat. Estimations of PP (PP(est)) for each load and for each prediction equation were compared with criterion PP values from a force plate (PP(FP)). The PP(est) values had high test-retest reliability and were strongly correlated to PP(FP) in both men and women at all relative loads. However, only the Harman equation accurately predicted PP(FP) at all relative loads. It can therefore be concluded that the Harman equation may be used to estimate PP of a loaded jump squat knowing the system mass and peak jump height when more precise (and expensive) measurement equipment is unavailable. Further, high reliability and correlation with criterion values suggest that serial assessment of power production across training periods could be used for relative assessment of change by either of the prediction equations used in this study.

  13. Drivers and seasonal predictability of extreme wind speeds in the ECMWF System 4 and a statistical model

    Science.gov (United States)

    Walz, M. A.; Donat, M.; Leckebusch, G. C.

    2017-12-01

    As extreme wind speeds are responsible for large socio-economic losses in Europe, a skillful prediction would be of great benefit for disaster prevention as well as for the actuarial community. Here we evaluate patterns of large-scale atmospheric variability and the seasonal predictability of extreme wind speeds (e.g. >95th percentile) in the European domain in the dynamical seasonal forecast system ECMWF System 4, and compare to the predictability based on a statistical prediction model. The dominant patterns of atmospheric variability show distinct differences between reanalysis and ECMWF System 4, with most patterns in System 4 extended downstream in comparison to ERA-Interim. The dissimilar manifestations of the patterns within the two models lead to substantially different drivers associated with the occurrence of extreme winds in the respective model. While the ECMWF System 4 is shown to provide some predictive power over Scandinavia and the eastern Atlantic, only very few grid cells in the European domain have significant correlations for extreme wind speeds in System 4 compared to ERA-Interim. In contrast, a statistical model predicts extreme wind speeds during boreal winter in better agreement with the observations. Our results suggest that System 4 does not seem to capture the potential predictability of extreme winds that exists in the real world, and therefore fails to provide reliable seasonal predictions for lead months 2-4. This is likely related to the unrealistic representation of large-scale patterns of atmospheric variability. Hence our study points to potential improvements of dynamical prediction skill by improving the simulation of large-scale atmospheric dynamics.

  14. Changes in Predictive Task Switching with Age and with Cognitive Load.

    Science.gov (United States)

    Levy-Tzedek, Shelly

    2017-01-01

    Predictive control of movement is more efficient than feedback-based control, and is an important skill in everyday life. We tested whether the ability to predictively control movements of the upper arm is affected by age and by cognitive load. A total of 63 participants were tested in two experiments. In both experiments participants were seated, and controlled a cursor on a computer screen by flexing and extending their dominant arm. In Experiment 1, 20 young adults and 20 older adults were asked to continuously change the frequency of their horizontal arm movements, with the goal of inducing an abrupt switch between discrete movements (at low frequencies) and rhythmic movements (at high frequencies). We tested whether that change was performed based on a feed-forward (predictive) or on a feedback (reactive) control. In Experiment 2, 23 young adults performed the same task, while being exposed to a cognitive load half of the time via a serial subtraction task. We found that both aging and cognitive load diminished, on average, the ability of participants to predictively control their movements. Five older adults and one young adult under a cognitive load were not able to perform the switch between rhythmic and discrete movement (or vice versa). In Experiment 1, 40% of the older participants were able to predictively control their movements, compared with 70% in the young group. In Experiment 2, 48% of the participants were able to predictively control their movements with a cognitively loading task, compared with 70% in the no-load condition. The ability to predictively change a motor plan in anticipation of upcoming changes may be an important component in performing everyday functions, such as safe driving and avoiding falls.

  15. Prediction of a thermodynamic wave train from the monsoon to the Arctic following extreme rainfall events

    Science.gov (United States)

    Krishnamurti, T. N.; Kumar, Vinay

    2017-04-01

    This study addresses numerical prediction of atmospheric wave trains that provide a monsoonal link to the Arctic ice melt. The monsoonal link is one of several ways that heat is conveyed to the Arctic region. This study follows a detailed observational study on thermodynamic wave trains that are initiated by extreme rain events of the northern summer south Asian monsoon. These wave trains carry large values of heat content anomalies, heat transports and convergence of flux of heat. These features seem to be important candidates for the rapid melt scenario. This present study addresses numerical simulation of the extreme rains, over India and Pakistan, and the generation of thermodynamic wave trains, simulations of large heat content anomalies, heat transports along pathways and heat flux convergences, potential vorticity and the diabatic generation of potential vorticity. We compare model based simulation of many features such as precipitation, divergence and the divergent wind with those evaluated from the reanalysis fields. We have also examined the snow and ice cover data sets during and after these events. This modeling study supports our recent observational findings on the monsoonal link to the rapid Arctic ice melt of the Canadian Arctic. This numerical modeling suggests ways to interpret some recent episodes of rapid ice melts that may require a well-coordinated field experiment among atmosphere, ocean, ice and snow cover scientists. Such a well-coordinated study would sharpen our understanding of this one component of the ice melt, i.e. the monsoonal link, which appears to be fairly robust.

  16. Development of Building Thermal Load and Discomfort Degree Hour Prediction Models Using Data Mining Approaches

    Directory of Open Access Journals (Sweden)

    Yaolin Lin

    2018-06-01

    Full Text Available Thermal load and indoor comfort level are two important building performance indicators, rapid predictions of which can help significantly reduce the computation time during design optimization. In this paper, a three-step approach is used to develop and evaluate prediction models. Firstly, the Latin Hypercube Sampling Method (LHSM is used to generate a representative 19-dimensional design database and DesignBuilder is then used to obtain the thermal load and discomfort degree hours through simulation. Secondly, samples from the database are used to develop and validate seven prediction models, using data mining approaches including multilinear regression (MLR, chi-square automatic interaction detector (CHAID, exhaustive CHAID (ECHAID, back-propagation neural network (BPNN, radial basis function network (RBFN, classification and regression trees (CART, and support vector machines (SVM. It is found that the MLR and BPNN models outperform the others in the prediction of thermal load with average absolute error of less than 1.19%, and the BPNN model is the best at predicting discomfort degree hour with 0.62% average absolute error. Finally, two hybrid models—MLR (MLR + BPNN and MLR-BPNN—are developed. The MLR-BPNN models are found to be the best prediction models, with average absolute error of 0.82% in thermal load and 0.59% in discomfort degree hour.

  17. Manual for the prediction of blast and fragment loadings on structures

    Energy Technology Data Exchange (ETDEWEB)

    1980-11-01

    The purpose of this manual is to provide Architect-Engineer (AE) firms guidance for the prediction of air blast, ground shock and fragment loadings on structures as a result of accidental explosions in or near these structures. Information in this manual is the result of an extensive literature survey and data gathering effort, supplemented by some original analytical studies on various aspects of blast phenomena. Many prediction equations and graphs are presented, accompanied by numerous example problems illustrating their use. The manual is complementary to existing structural design manuals and is intended to reflect the current state-of-the-art in prediction of blast and fragment loads for accidental explosions of high explosives at the Pantex Plant. In some instances, particularly for explosions within blast-resistant structures of complex geometry, rational estimation of these loads is beyond the current state-of-the-art.

  18. Prediction of the metabolic cost of walking with and without loads.

    Science.gov (United States)

    Duggan, A; Haisman, M F

    1992-04-01

    Measurement of the metabolic cost of walking inconveniences subjects, and requires skilled technical support and expensive equipment. These factors have stimulated interest in predictive equations. The present study assessed existing equations. Under each of 17 combinations of gradient (0-6%) and carried load (4.1-37.4 kg), 7-12 men undertook treadmill walking at 1.67 m/s. Measured oxygen consumption and respiratory exchange ratio were used to calculate metabolic rate (MRobserved). Metabolic rate was also predicted from the equation of Pandolf et al. (1977) (MRpandolf) and, where appropriate, from another five equations relating to walking without loads. MRobserved and MRpandolf did not differ significantly (p greater than 0.05) under any combination of gradient and load. The overall mean MRobserved and MRpandolf of 609 W and 602 W, respectively, also did not differ significantly (p greater than 0.05). These variables were highly correlated (r = 0.94) with a standard deviation about the prediction error of 47 W. For level walking without loads, the mean predictions from the equations of Pandolf et al. (1977) and Cotes and Meade (1960) did not differ significantly (p greater than 0.05) from the mean MRobserved of 428 Watts, but four other equations overestimated by 17-74 W. In conclusion, the Pandolf et al. (1977) equation has given good results across the range of combinations of load and gradient tested, and the errors are considered acceptable for most practical purposes.

  19. Structural and functional responses of extremity veins to long-term gravitational loading or unloading—lessons from animal systems

    Science.gov (United States)

    Monos, Emil; Raffai, Gábor; Dörnyei, Gabriella; Nádasy, György L.; Fehér, Erzsébet

    2007-02-01

    Long, transparent tubular tilt-cages were developed to maintain experimental rats either in 45∘ head-up (orthostasis model), or in 45∘ head-down body position (antiorthostasis model) for several weeks. In order to study the functional and structural changes in extremity blood vessels, also novel pressure angiograph systems, as well as special quantitative electron microscopic methods were applied. It was found that several adaptive mechanisms are activated in the lower limb superficial veins and microvessels of muscles when an organism is exposed to long-term (1-2 weeks) orthostatic-type gravitational load including a reversible amplification of the pressure-dependent myogenic response, tuning of the myogenic tone by Ca++- and voltage-sensitive K+ channels in humans, augmentation of the intramural sympathetic innervation involving an increased nerve terminal density and synaptic vesicle count with functional remodeling, reorganization of vascular network properties (microvascular rarefaction in muscles, decreased branching angles in superficial veins), and responses of an endothelin and platelet-derived growth factor (PDGF) containing vesicle system in the endothelium. On the other hand, when applying long-term head-down tilting, the effects are dichotomous, e.g. it suppresses significantly the pressure-induced myogenic response, however does not diminish the adventitial sympathetic innervation density.

  20. Climate extremes and predicted warming threaten Mediterranean Holocene firs forests refugia.

    Science.gov (United States)

    Sánchez-Salguero, Raúl; Camarero, J Julio; Carrer, Marco; Gutiérrez, Emilia; Alla, Arben Q; Andreu-Hayles, Laia; Hevia, Andrea; Koutavas, Athanasios; Martínez-Sancho, Elisabet; Nola, Paola; Papadopoulos, Andreas; Pasho, Edmond; Toromani, Ervin; Carreira, José A; Linares, Juan C

    2017-11-21

    Warmer and drier climatic conditions are projected for the 21st century; however, the role played by extreme climatic events on forest vulnerability is still little understood. For example, more severe droughts and heat waves could threaten quaternary relict tree refugia such as Circum-Mediterranean fir forests (CMFF). Using tree-ring data and a process-based model, we characterized the major climate constraints of recent (1950-2010) CMFF growth to project their vulnerability to 21st-century climate. Simulations predict a 30% growth reduction in some fir species with the 2050s business-as-usual emission scenario, whereas growth would increase in moist refugia due to a longer and warmer growing season. Fir populations currently subjected to warm and dry conditions will be the most vulnerable in the late 21st century when climatic conditions will be analogous to the most severe dry/heat spells causing dieback in the late 20th century. Quantification of growth trends based on climate scenarios could allow defining vulnerability thresholds in tree populations. The presented predictions call for conservation strategies to safeguard relict tree populations and anticipate how many refugia could be threatened by 21st-century dry spells.

  1. A critical pressure based panel method for prediction of unsteady loading of marine propellers under cavitation

    International Nuclear Information System (INIS)

    Liu, P.; Bose, N.; Colbourne, B.

    2002-01-01

    A simple numerical procedure is established and implemented into a time domain panel method to predict hydrodynamic performance of marine propellers with sheet cavitation. This paper describes the numerical formulations and procedures to construct this integration. Predicted hydrodynamic loads were compared with both a previous numerical model and experimental measurements for a propeller in steady flow. The current method gives a substantial improvement in thrust and torque coefficient prediction over a previous numerical method at low cavitation numbers of less than 2.0, where severe cavitation occurs. Predicted pressure coefficient distributions are also presented. (author)

  2. Prediction of Summer Extreme Precipitation over the Middle and Lower Reaches of the Yangtze River Basin

    Science.gov (United States)

    Liu, L.; Ning, L.; Liu, J.; Yan, M.; Sun, W.

    2017-12-01

    Abstract: Summer extreme precipitation (SEP) often causes severe landslide, debris flow and floods over the middle and lower reaches of the Yangtze River Basin(MLYRB), so skillful prediction of the SEP is critical to the future climate adaptions and mitigations. In this work, the characteristic region over the MLYRB (27°N-32°N,108°1-118°E) is defined by the spatial mode of the rotated empirical orthogonal functions (REOF) of SEP over the China from 1961 to 2014. A physics-based empirical model (PEM) of SEP predictions is built with two preceding predictors with significant physical influences on the SEP over the MLYRB. The first predictor is the spring sea surface temperature (SST) over the Northern Indian Ocean (20°S-20°N,50°E-95°E), and the second predictor is the spring sea surface pressure (SLP) over the Aleutian Island (50°N-70°N,160°E-160°W). Analyses of physical mechanism show that when the spring SST over the Northern Indian Ocean is higher, the South Asian High (SAH) extends to the east and the western Pacific sub-tropical high (WPSH) extends to the west, therefore, the generated secondary circulation induces anomalous upward motions and more water vapor transportation to the MLYRB, resulting more SEP. Meanwhile, when the spring SLP over the Aleutian Island is lower, the also WPSH extends to the west, which leads to a negative omega anomaly centered the MLYRB and more water vapor transportation to the MLYRB, resulting in more SEP. The regression model is built using the data from a training period from 1961 to 1999 with correlation coefficient skill of 0.57 (p<0.01) for prediction of SEP in 1961-1999. The independent forecast of the PEM shows that it is skillful in SEP prediction with the correlation coefficient between observed SEP and model-simulated SEP over the validation period 2000-2014 is 0.51 (p<0.05). This finding shows that the preceding spring SST and SLP can provide useful information for prediction of SEP, and the methodology

  3. Developing a Framework for Seamless Prediction of Sub-Seasonal to Seasonal Extreme Precipitation Events in the United States.

    Science.gov (United States)

    Rosendahl, D. H.; Ćwik, P.; Martin, E. R.; Basara, J. B.; Brooks, H. E.; Furtado, J. C.; Homeyer, C. R.; Lazrus, H.; Mcpherson, R. A.; Mullens, E.; Richman, M. B.; Robinson-Cook, A.

    2017-12-01

    Extreme precipitation events cause significant damage to homes, businesses, infrastructure, and agriculture, as well as many injures and fatalities as a result of fast-moving water or waterborne diseases. In the USA, these natural hazard events claimed the lives of more than 300 people during 2015 - 2016 alone, with total damage reaching $24.4 billion. Prior studies of extreme precipitation events have focused on the sub-daily to sub-weekly timeframes. However, many decisions for planning, preparing and resilience-building require sub-seasonal to seasonal timeframes (S2S; 14 to 90 days), but adequate forecasting tools for prediction do not exist. Therefore, the goal of this newly funded project is an enhancement in understanding of the large-scale forcing and dynamics of S2S extreme precipitation events in the United States, and improved capability for modeling and predicting such events. Here, we describe the project goals, objectives, and research activities that will take place over the next 5 years. In this project, a unique team of scientists and stakeholders will identify and understand weather and climate processes connected with the prediction of S2S extreme precipitation events by answering these research questions: 1) What are the synoptic patterns associated with, and characteristic of, S2S extreme precipitation evens in the contiguous U.S.? 2) What role, if any, do large-scale modes of climate variability play in modulating these events? 3) How predictable are S2S extreme precipitation events across temporal scales? 4) How do we create an informative prediction of S2S extreme precipitation events for policymaking and planing? This project will use observational data, high-resolution radar composites, dynamical climate models and workshops that engage stakeholders (water resource managers, emergency managers and tribal environmental professionals) in co-production of knowledge. The overarching result of this project will be predictive models to reduce of

  4. Condition Assessment and End-of-Life Prediction System for Electric Machines and Their Loads

    Science.gov (United States)

    Parlos, Alexander G.; Toliyat, Hamid A.

    2005-01-01

    An end-of-life prediction system developed for electric machines and their loads could be used in integrated vehicle health monitoring at NASA and in other government agencies. This system will provide on-line, real-time condition assessment and end-of-life prediction of electric machines (e.g., motors, generators) and/or their loads of mechanically coupled machinery (e.g., pumps, fans, compressors, turbines, conveyor belts, magnetic levitation trains, and others). In long-duration space flight, the ability to predict the lifetime of machinery could spell the difference between mission success or failure. Therefore, the system described here may be of inestimable value to the U.S. space program. The system will provide continuous monitoring for on-line condition assessment and end-of-life prediction as opposed to the current off-line diagnoses.

  5. XBeach-G: a tool for predicting gravel barrier response to extreme storm conditions

    Science.gov (United States)

    Masselink, Gerd; Poate, Tim; McCall, Robert; Roelvink, Dano; Russell, Paul; Davidson, Mark

    2014-05-01

    Gravel beaches protect low-lying back-barrier regions from flooding during storm events and their importance to society is widely acknowledged. Unfortunately, breaching and extensive storm damage has occurred at many gravel sites and this is likely to increase as a result of sea-level rise and enhanced storminess due to climate change. Limited scientific guidance is currently available to provide beach managers with operational management tools to predict the response of gravel beaches to storms. The New Understanding and Prediction of Storm Impacts on Gravel beaches (NUPSIG) project aims to improve our understanding of storm impacts on gravel coastal environments and to develop a predictive capability by modelling these impacts. The NUPSIG project uses a 5-pronged approach to address its aim: (1) analyse hydrodynamic data collected during a proto-type laboratory experiment on a gravel beach; (2) collect hydrodynamic field data on a gravel beach under a range of conditions, including storm waves with wave heights up to 3 m; (3) measure swash dynamics and beach response on 10 gravel beaches during extreme wave conditions with wave heights in excess of 3 m; (4) use the data collected under 1-3 to develop and validate a numerical model to model hydrodynamics and morphological response of gravel beaches under storm conditions; and (5) develop a tool for end-users, based on the model formulated under (4), for predicting storm response of gravel beaches and barriers. The aim of this presentation is to present the key results of the NUPSIG project and introduce the end-user tool for predicting storm response on gravel beaches. The model is based on the numerical model XBeach, and different forcing scenarios (wave and tides), barrier configurations (dimensions) and sediment characteristics are easily uploaded for model simulations using a Graphics User Interface (GUI). The model can be used to determine the vulnerability of gravel barriers to storm events, but can also be

  6. Deflection Prediction of No-Fines Lightweight Concrete Wall Using Neural Network Caused Dynamic Loads

    Directory of Open Access Journals (Sweden)

    Ridho Bayuaji

    2018-04-01

    Full Text Available No-fines lightweight concrete wall with horizontal reinforcement refers to an alternative material for wall construction with an aim of improving the wall quality towards horizontal loads. This study is focused on artificial neural network (ANN application to predicting the deflection deformation caused by dynamic loads. The ANN method is able to capture the complex interactions among input/output variables in a system without any knowledge of interaction nature and without any explicit assumption to model form. This paper explains the existing data research, data selection and process of ANN modelling training process and validation. The results of this research show that the deformation can be predicted more accurately, simply and quickly due to the alternating horizontal loads.

  7. Crack under biaxial loading: Two-parameter description and prediction of crack growth direction

    Czech Academy of Sciences Publication Activity Database

    Seitl, Stanislav

    2014-01-01

    Roč. 31, APR (2014), s. 44-49 ISSN 0213-3725 R&D Projects: GA MŠk(CZ) 7AMB14AT012 Institutional support: RVO:68081723 Keywords : Concrete * T-stress * cracks growth prediction * numerical calculation * biaxial loading Subject RIV: JL - Materials Fatigue, Friction Mechanics

  8. Amyloid Load in Fat Tissue Reflects Disease Severity and Predicts Survival in Amyloidosis

    NARCIS (Netherlands)

    Van Gameren, Ingrid I.; Hazenberg, Bouke P. C.; Bijzet, Johan; Haagsma, Elizabeth B.; Vellenga, Edo; Posthumus, Marcel D.; Jager, Pieter L.; Van Rijswijk, Martin H.

    Objective. The severity of systemic amyloidosis is thought to be related to the extent of amyloid deposition. We studied whether amyloid load in fat tissue reflects disease severity and predicts survival. Methods. We studied all consecutive patients with systemic amyloidosis seen between January

  9. An EMD-ANN based prediction methodology for DR driven smart household load demand

    NARCIS (Netherlands)

    Tascikaraoglu, A.; Paterakis, N.G.; Catalaõ, J.P.S.; Erdinç, O.; Bakirtzis, A.G.

    2015-01-01

    This study proposes a model for the prediction of smart household load demand influenced by a dynamic pricing demand response (DR) program. Price-based DR programs have a considerable impact on household demand pattern due to the expected choice of customers or their home energy management systems

  10. Fatigue life prediction in composites using progressive damage modelling under block and spectrum loading

    DEFF Research Database (Denmark)

    Passipoularidis, Vaggelis; Philippidis, T.P.; Brøndsted, Povl

    2010-01-01

    series can be simulated. The predictions are validated against fatigue life data both from repeated block tests at a single stress ratio as well as against spectral fatigue using the WISPER, WISPERX and NEW WISPER load sequences on a Glass/Epoxy multidirectional laminate typical of a Wind Turbine Rotor...

  11. Reliability and Validity of the Load-Velocity Relationship to Predict the 1RM Back Squat.

    Science.gov (United States)

    Banyard, Harry G; Nosaka, Kazunori; Haff, G Gregory

    2017-07-01

    Banyard, HG, Nosaka, K, and Haff, GG. Reliability and validity of the load-velocity relationship to predict the 1RM back squat. J Strength Cond Res 31(7): 1897-1904, 2017-This study investigated the reliability and validity of the load-velocity relationship to predict the free-weight back squat one repetition maximum (1RM). Seventeen strength-trained males performed three 1RM assessments on 3 separate days. All repetitions were performed to full depth with maximal concentric effort. Predicted 1RMs were calculated by entering the mean concentric velocity of the 1RM (V1RM) into an individualized linear regression equation, which was derived from the load-velocity relationship of 3 (20, 40, 60% of 1RM), 4 (20, 40, 60, 80% of 1RM), or 5 (20, 40, 60, 80, 90% of 1RM) incremental warm-up sets. The actual 1RM (140.3 ± 27.2 kg) was very stable between 3 trials (ICC = 0.99; SEM = 2.9 kg; CV = 2.1%; ES = 0.11). Predicted 1RM from 5 warm-up sets up to and including 90% of 1RM was the most reliable (ICC = 0.92; SEM = 8.6 kg; CV = 5.7%; ES = -0.02) and valid (r = 0.93; SEE = 10.6 kg; CV = 7.4%; ES = 0.71) of the predicted 1RM methods. However, all predicted 1RMs were significantly different (p ≤ 0.05; ES = 0.71-1.04) from the actual 1RM. Individual variation for the actual 1RM was small between trials ranging from -5.6 to 4.8% compared with the most accurate predictive method up to 90% of 1RM, which was more variable (-5.5 to 27.8%). Importantly, the V1RM (0.24 ± 0.06 m·s) was unreliable between trials (ICC = 0.42; SEM = 0.05 m·s; CV = 22.5%; ES = 0.14). The load-velocity relationship for the full depth free-weight back squat showed moderate reliability and validity but could not accurately predict 1RM, which was stable between trials. Thus, the load-velocity relationship 1RM prediction method used in this study cannot accurately modify sessional training loads because of large V1RM variability.

  12. Nested-scale discharge and groundwater level monitoring to improve predictions of flow route discharges and nitrate loads

    Science.gov (United States)

    van der Velde, Y.; Rozemeijer, J. C.; de Rooij, G. H.; van Geer, F. C.; Torfs, P. J. J. F.; de Louw, P. G. B.

    2010-10-01

    Identifying effective measures to reduce nutrient loads of headwaters in lowland catchments requires a thorough understanding of flow routes of water and nutrients. In this paper we assess the value of nested-scale discharge and groundwater level measurements for predictions of catchment-scale discharge and nitrate loads. In order to relate field-site measurements to the catchment-scale an upscaling approach is introduced that assumes that scale differences in flow route fluxes originate from differences in the relationship between groundwater storage and the spatial structure of the groundwater table. This relationship is characterized by the Groundwater Depth Distribution (GDD) curve that relates spatial variation in groundwater depths to the average groundwater depth. The GDD-curve was measured for a single field site (0.009 km2) and simple process descriptions were applied to relate the groundwater levels to flow route discharges. This parsimonious model could accurately describe observed storage, tube drain discharge, overland flow and groundwater flow simultaneously with Nash-Sutcliff coefficients exceeding 0.8. A probabilistic Monte Carlo approach was applied to upscale field-site measurements to catchment scales by inferring scale-specific GDD-curves from hydrographs of two nested catchments (0.4 and 6.5 km2). The estimated contribution of tube drain effluent (a dominant source for nitrates) decreased with increasing scale from 76-79% at the field-site to 34-61% and 25-50% for both catchment scales. These results were validated by demonstrating that a model conditioned on nested-scale measurements simulates better nitrate loads and better predictions of extreme discharges during validation periods compared to a model that was conditioned on catchment discharge only.

  13. Fatigue crack growth and life prediction under mixed-mode loading

    Science.gov (United States)

    Sajith, S.; Murthy, K. S. R. K.; Robi, P. S.

    2018-04-01

    Fatigue crack growth life as a function of crack length is essential for the prevention of catastrophic failures from damage tolerance perspective. In damage tolerance design approach, principles of fracture mechanics are usually applied to predict the fatigue life of structural components. Numerical prediction of crack growth versus number of cycles is essential in damage tolerance design. For cracks under mixed mode I/II loading, modified Paris law (d/a d N =C (ΔKe q ) m ) along with different equivalent stress intensity factor (ΔKeq) model is used for fatigue crack growth rate prediction. There are a large number of ΔKeq models available for the mixed mode I/II loading, the selection of proper ΔKeq model has significant impact on fatigue life prediction. In the present investigation, the performance of ΔKeq models in fatigue life prediction is compared with respect to the experimental findings as there are no guidelines/suggestions available on the selection of these models for accurate and/or conservative predictions of fatigue life. Within the limitations of availability of experimental data and currently available numerical simulation techniques, the results of present study attempt to outline models that would provide accurate and conservative life predictions. Such a study aid the numerical analysts or engineers in the proper selection of the model for numerical simulation of the fatigue life. Moreover, the present investigation also suggests a procedure to enhance the accuracy of life prediction using Paris law.

  14. Thoracolumbar spine model with articulated ribcage for the prediction of dynamic spinal loading.

    Science.gov (United States)

    Ignasiak, Dominika; Dendorfer, Sebastian; Ferguson, Stephen J

    2016-04-11

    Musculoskeletal modeling offers an invaluable insight into the spine biomechanics. A better understanding of thoracic spine kinetics is essential for understanding disease processes and developing new prevention and treatment methods. Current models of the thoracic region are not designed for segmental load estimation, or do not include the complex construct of the ribcage, despite its potentially important role in load transmission. In this paper, we describe a numerical musculoskeletal model of the thoracolumbar spine with articulated ribcage, modeled as a system of individual vertebral segments, elastic elements and thoracic muscles, based on a previously established lumbar spine model and data from the literature. The inverse dynamics simulations of the model allow the prediction of spinal loading as well as costal joints kinetics and kinematics. The intradiscal pressure predicted by the model correlated well (R(2)=0.89) with reported intradiscal pressure measurements, providing a first validation of the model. The inclusion of the ribcage did not affect segmental force predictions when the thoracic spine did not perform motion. During thoracic motion tasks, the ribcage had an important influence on the predicted compressive forces and muscle activation patterns. The compressive forces were reduced by up to 32%, or distributed more evenly between thoracic vertebrae, when compared to the predictions of the model without ribcage, for mild thoracic flexion and hyperextension tasks, respectively. The presented musculoskeletal model provides a tool for investigating thoracic spine loading and load sharing between vertebral column and ribcage during dynamic activities. Further validation for specific applications is still necessary. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Feature selection in wind speed prediction systems based on a hybrid coral reefs optimization – Extreme learning machine approach

    International Nuclear Information System (INIS)

    Salcedo-Sanz, S.; Pastor-Sánchez, A.; Prieto, L.; Blanco-Aguilera, A.; García-Herrera, R.

    2014-01-01

    Highlights: • A novel approach for short-term wind speed prediction is presented. • The system is formed by a coral reefs optimization algorithm and an extreme learning machine. • Feature selection is carried out with the CRO to improve the ELM performance. • The method is tested in real wind farm data in USA, for the period 2007–2008. - Abstract: This paper presents a novel approach for short-term wind speed prediction based on a Coral Reefs Optimization algorithm (CRO) and an Extreme Learning Machine (ELM), using meteorological predictive variables from a physical model (the Weather Research and Forecast model, WRF). The approach is based on a Feature Selection Problem (FSP) carried out with the CRO, that must obtain a reduced number of predictive variables out of the total available from the WRF. This set of features will be the input of an ELM, that finally provides the wind speed prediction. The CRO is a novel bio-inspired approach, based on the simulation of reef formation and coral reproduction, able to obtain excellent results in optimization problems. On the other hand, the ELM is a new paradigm in neural networks’ training, that provides a robust and extremely fast training of the network. Together, these algorithms are able to successfully solve this problem of feature selection in short-term wind speed prediction. Experiments in a real wind farm in the USA show the excellent performance of the CRO–ELM approach in this FSP wind speed prediction problem

  16. Weaker lower extremity muscle strength predicts traumatic knee injury in youth female but not male athletes.

    Science.gov (United States)

    Ryman Augustsson, Sofia; Ageberg, Eva

    2017-01-01

    The role of lower extremity (LE) muscle strength for predicting traumatic knee injury in youth athletes is largely unknown. The aim was to investigate the influence of LE muscle strength on traumatic knee injury in youth female and male athletes. 225 athletes (40% females) from sport senior high schools in Sweden were included in this case-control study. The athletes recorded any traumatic knee injury that had occurred during their high-school period in a web-based injury form. A one repetition maximum (1RM) barbell squat test was used to measure LE muscle strength. The 1RM was dichotomised to analyse 'weak' versus 'strong' athletes according to the median (weak median vs strong median ). 63 traumatic knee injuries, including 18 ACL injuries, were registered. The majority of injured female athletes were in the weak group compared with the strong group (p=0.0001). The odds of sustaining a traumatic knee injury and an ACL injury was 9.5 times higher and 7 times higher, respectively, in the weak median group compared with the strong median group in females (p ≤0.011). A relative 1RM squat ≤1.05 kg (105% of bodyweight) was established as the best cut-off value to distinguish high versus low risk of injury in female athletes. No strength-injury relationships were observed for the male athletes (p ≥0.348). Weaker LE muscle strength predicted traumatic knee injury in youth female athletes, but not in males. This suggests that LE muscle strength should be included in injury screening in youth female athletes.

  17. Automated system for load flow prediction in power substations using artificial neural networks

    Directory of Open Access Journals (Sweden)

    Arlys Michel Lastre Aleaga

    2015-09-01

    Full Text Available The load flow is of great importance in assisting the process of decision making and planning of generation, distribution and transmission of electricity. Ignorance of the values in this indicator, as well as their inappropriate prediction, difficult decision making and efficiency of the electricity service, and can cause undesirable situations such as; the on demand, overheating of the components that make up a substation, and incorrect planning processes electricity generation and distribution. Given the need for prediction of flow of electric charge of the substations in Ecuador this research proposes the concept for the development of an automated prediction system employing the use of Artificial Neural Networks.

  18. Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction

    Directory of Open Access Journals (Sweden)

    Jianzhou Wang

    2014-01-01

    Full Text Available Swarm intelligence (SI is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities. In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS as well as the singular spectrum analysis (SSA, time series, and machine learning methods are proposed to conduct short-term power load prediction. The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon. The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA and support vector regression (SVR in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance. Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.

  19. Predicting the solubility of gases in Nitrile Butadiene Rubber in extreme conditions using molecular simulation

    Science.gov (United States)

    Khawaja, Musab; Molinari, Nicola; Sutton, Adrian; Mostofi, Arash

    In the oil and gas industry, elastomer seals play an important role in protecting sensitive monitoring equipment from contamination by gases - a problem that is exacerbated by the high pressures and temperatures found down-hole. The ability to predict and prevent such permeative failure has proved elusive to-date. Nitrile butadiene rubber (NBR) is a common choice of elastomer for seals due to its resistance to heat and fuels. In the conditions found in the well it readily absorbs small molecular weight gases. How this behaviour changes quantitatively for different gases as a function of temperature and pressure is not well-understood. In this work a series of fully atomistic simulations are performed to understand the effect of extreme conditions on gas solubility in NBR. Widom particle insertion is used to compute solubilities. The importance of sampling and allowing structural relaxation upon compression are highlighted, and qualitatively reasonable trends reproduced. Finally, while at STP it has previously been shown that the solubility of CO2 is higher than that of He in NBR, we observe that under the right circumstances it is possible to reverse this trend.

  20. Variable complexity online sequential extreme learning machine, with applications to streamflow prediction

    Science.gov (United States)

    Lima, Aranildo R.; Hsieh, William W.; Cannon, Alex J.

    2017-12-01

    In situations where new data arrive continually, online learning algorithms are computationally much less costly than batch learning ones in maintaining the model up-to-date. The extreme learning machine (ELM), a single hidden layer artificial neural network with random weights in the hidden layer, is solved by linear least squares, and has an online learning version, the online sequential ELM (OSELM). As more data become available during online learning, information on the longer time scale becomes available, so ideally the model complexity should be allowed to change, but the number of hidden nodes (HN) remains fixed in OSELM. A variable complexity VC-OSELM algorithm is proposed to dynamically add or remove HN in the OSELM, allowing the model complexity to vary automatically as online learning proceeds. The performance of VC-OSELM was compared with OSELM in daily streamflow predictions at two hydrological stations in British Columbia, Canada, with VC-OSELM significantly outperforming OSELM in mean absolute error, root mean squared error and Nash-Sutcliffe efficiency at both stations.

  1. Prediction of core and lower extremity strains and sprains in collegiate football players: a preliminary study.

    Science.gov (United States)

    Wilkerson, Gary B; Giles, Jessica L; Seibel, Dustin K

    2012-01-01

    Poor core stability is believed to increase vulnerability to uncontrolled joint displacements throughout the kinetic chain between the foot and the lumbar spine. To assess the value of preparticipation measurements as predictors of core or lower extremity strains or sprains in collegiate football players. Cohort study. National Collegiate Athletic Association Division I Football Championship Subdivision football program. All team members who were present for a mandatory physical examination on the day before preseason practice sessions began (n = 83). Preparticipation administration of surveys to assess low back, knee, and ankle function; documentation of knee and ankle injury history; determination of body mass index; 4 different assessments of core muscle endurance; and measurement of step-test recovery heart rate. All injuries were documented throughout the preseason practice period and 11-game season. Receiver operating characteristic analysis and logistic regression analysis were used to identify dichotomized predictive factors that best discriminated injured from uninjured status. The 75th and 50th percentiles were evaluated as alternative cutpoints for dichotomization of injury predictors. Players with ≥2 of 3 potentially modifiable risk factors related to core function had 2 times greater risk for injury than those with football injury risk factors that can be identified on preparticipation screening. These predictors need to be assessed in a prospective manner with a larger sample of collegiate football players.

  2. Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation

    Energy Technology Data Exchange (ETDEWEB)

    Abbas, Nikhar [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Tom, Nathan M [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-06-03

    Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalman filter and autoregressive model to evaluate model predictive control performance.

  3. Rigid-Plastic Approximations for Predicting Plastic Deformation of Cylindrical Shells Subject to Dynamic Loading

    Directory of Open Access Journals (Sweden)

    Michelle S. Hoo Fatt

    1996-01-01

    Full Text Available A theoretical approach was developed for predicting the plastic deformation of a cylindrical shell subject to asymmetric dynamic loads. The plastic deformation of the leading generator of the shell is found by solving for the transverse deflections of a rigid-plastic beam/string-on-foundation. The axial bending moment and tensile force in the beam/string are equivalent to the longitudinal bending moments and membrane forces of the shell, while the plastic foundation force is equivalent to the shell circumferential bending moment and membrane resistances. Closed-form solutions for the transient and final deformation profile of an impulsive loaded shell when it is in a “string” state were derived using the eigenfunction expansion method. These results were compared to DYNA 3D predictions. The analytical predictions of the transient shell and final centerline deflections were within 25% of the DYNA 3D results.

  4. Prediction of elastic-plastic response of structural elements subjected to cyclic loading

    International Nuclear Information System (INIS)

    El Haddad, M.H.; Samaan, S.

    1985-01-01

    A simplified elastic-plastic analysis is developed to predict stress strain and force deformation response of structural metallic elements subjected to irregular cyclic loadings. In this analysis a simple elastic-plastic method for predicting the skeleton force deformation curve is developed. In this method, elastic and fully plastic solutions are first obtained for unknown quantities, such as deflection or local strains. Elastic and fully plastic contributions are then combined to obtain an elastic-plastic solution. The skeleton curve is doubled to establish the shape of the hysteresis loop. The complete force deformation response can therefore be simulated through reversal by reversal in accordance with hysteresis looping and material memory. Several examples of structural elements with various cross sections made from various materials and subjected to irregular cyclic loadings, are analysed. A close agreement is obtained between experimental results found in the literature and present predictions. (orig.)

  5. Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Abbas, Nikhar; Tom, Nathan

    2017-09-01

    Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalman filter and autoregressive model to evaluate model predictive control performance.

  6. Dynamical prediction and pattern mapping in short-term load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Aguirre, Luis Antonio; Rodrigues, Daniela D.; Lima, Silvio T. [Departamento de Engenharia Eletronica, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, 31270-901 Belo Horizonte, MG (Brazil); Martinez, Carlos Barreira [Departamento de Engenharia Hidraulica e Recursos Hidricos, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, 31270-901 Belo Horizonte, MG (Brazil)

    2008-01-15

    This work will not put forward yet another scheme for short-term load forecasting but rather will provide evidences that may improve our understanding about fundamental issues which underlay load forecasting problems. In particular, load forecasting will be decomposed into two main problems, namely dynamical prediction and pattern mapping. It is argued that whereas the latter is essentially static and becomes nonlinear when weekly features in the data are taken into account, the former might not be deterministic at all. In such cases there is no determinism (serial correlations) in the data apart from the average cycle and the best a model can do is to perform pattern mapping. Moreover, when there is determinism in addition to the average cycle, the underlying dynamics are sometimes linear, in which case there is no need to resort to nonlinear models to perform dynamical prediction. Such conclusions were confirmed using real load data and surrogate data analysis. In a sense, the paper details and organizes some general beliefs found in the literature on load forecasting. This sheds some light on real model-building and forecasting problems and helps understand some apparently conflicting results reported in the literature. (author)

  7. Prediction of crack density and electrical resistance changes in indium tin oxide/polymer thin films under tensile loading

    KAUST Repository

    Mora Cordova, Angel; Khan, Kamran; El Sayed, Tamer

    2014-01-01

    We present unified predictions for the crack onset strain, evolution of crack density, and changes in electrical resistance in indium tin oxide/polymer thin films under tensile loading. We propose a damage mechanics model to quantify and predict

  8. Improving prediction accuracy of cooling load using EMD, PSR and RBFNN

    Science.gov (United States)

    Shen, Limin; Wen, Yuanmei; Li, Xiaohong

    2017-08-01

    To increase the accuracy for the prediction of cooling load demand, this work presents an EMD (empirical mode decomposition)-PSR (phase space reconstruction) based RBFNN (radial basis function neural networks) method. Firstly, analyzed the chaotic nature of the real cooling load demand, transformed the non-stationary cooling load historical data into several stationary intrinsic mode functions (IMFs) by using EMD. Secondly, compared the RBFNN prediction accuracies of each IMFs and proposed an IMF combining scheme that is combine the lower-frequency components (called IMF4-IMF6 combined) while keep the higher frequency component (IMF1, IMF2, IMF3) and the residual unchanged. Thirdly, reconstruct phase space for each combined components separately, process the highest frequency component (IMF1) by differential method and predict with RBFNN in the reconstructed phase spaces. Real cooling load data of a centralized ice storage cooling systems in Guangzhou are used for simulation. The results show that the proposed hybrid method outperforms the traditional methods.

  9. Recent developments on SMA actuators: predicting the actuation fatigue life for variable loading schemes

    Science.gov (United States)

    Wheeler, Robert W.; Lagoudas, Dimitris C.

    2017-04-01

    Shape memory alloys (SMAs), due to their ability to repeatably recover substantial deformations under applied mechanical loading, have the potential to impact the aerospace, automotive, biomedical, and energy industries as weight and volume saving replacements for conventional actuators. While numerous applications of SMA actuators have been flight tested and can be found in industrial applications, these actuators are generally limited to non-critical components, are not widely implemented and frequently one-off designs, and are generally overdesigned due to a lack of understanding of the effect of the loading path on the fatigue life and the lack of an accurate method for predicting actuator lifetimes. In recent years, multiple research efforts have increased our understanding of the actuation fatigue process of SMAs. These advances can be utilized to predict the fatigue lives and failure loads in SMA actuators. Additionally, these prediction methods can be implemented in order to intelligently design actuators in accordance with their fatigue and failure limits. In the following paper, both simple and complex thermomechanical loading paths have been considered. Experimental data was utilized from two material systems: equiatomic Nickel-Titanium and Nickelrich Nickel-Titanium.

  10. Load Torque Compensator for Model Predictive Direct Current Control in High Power PMSM Drive Systems

    DEFF Research Database (Denmark)

    Preindl, Matthias; Schaltz, Erik

    2011-01-01

    The widely used cascade speed and torque controllers have a limited control performance in most high power applications due to the low switching frequency of power electronic converters and the convenience to avoid speed overshoots and oscillations for lifetime considerations. Model Predictive...... Direct Current Control (MPDCC) leads to an increase of torque control performance taking into account the discrete nature of inverters but temporary offsets and poor responses to load torque variations are still issues in speed control. A load torque estimator is proposed in this paper in order...

  11. Active load management in an intelligent building using model predictive control strategy

    DEFF Research Database (Denmark)

    Zong, Yi; Kullmann, Daniel; Thavlov, Anders

    2011-01-01

    This paper introduces PowerFlexHouse, a research facility for exploring the technical potential of active load management in a distributed power system (SYSLAB) with a high penetration of renewable energy and presents in detail on how to implement a thermal model predictive controller for load...... shifting in PowerFlexHouse heaters' power consumption scheme. With this demand side control study, it is expected that this method of demand response can dramatically raise energy efficiencies and improve grid reliability, when there is a high penetration of intermittent energy resources in the power...

  12. Instability predictions for circumferentially cracked Type-304 stainless-steel pipes under dynamic loading. Final report

    International Nuclear Information System (INIS)

    Zahoor, A.; Wilkowski, G.; Abou-Sayed, I.; Marschall, C.; Broek, D.; Sampath, S.; Rhee, H.; Ahmad, J.

    1982-04-01

    This report provides methods to predict margins of safety for circumferentially cracked Type 304 stainless steel pipes subjected to applied bending loads. An integrated combination of experimentation and analysis research was pursued. Two types of experiments were performed: (1) laboratory-scale tests on center-cracked panels and bend specimens to establish the basic mechanical and fracture properties of Type 304 stainless steel, and (2) full-scale pipe fracture tests under quasi-static and dynamic loadings to assess the analysis procedures. Analyses were based upon the simple plastic collapse criterion, a J-estimation procedure, and elastic-plastic large-deformation finite element models

  13. Thermal deformation prediction in reticles for extreme ultraviolet lithography based on a measurement-dependent low-order model

    NARCIS (Netherlands)

    Bikcora, C.; Weiland, S.; Coene, W.M.J.

    2014-01-01

    In extreme ultraviolet lithography, imaging errors due to thermal deformation of reticles are becoming progressively intolerable as the source power increases. Despite this trend, such errors can be mitigated by adjusting the wafer and reticle stages based on a set of predicted deformation-induced

  14. Which Screening Tools Can Predict Injury to the Lower Extremities in Team Sports? A Systematic Review

    NARCIS (Netherlands)

    Dallinga, Joan M.; Benjaminse, Anne; Lemmink, Koen A. P. M.

    2012-01-01

    Background: Injuries to lower extremities are common in team sports such as soccer, basketball, volleyball, football and field hockey. Considering personal grief, disabling consequences and high costs caused by injuries to lower extremities, the importance for the prevention of these injuries is

  15. The Consequences of Collective Discontent : A New Measure of Zeitgeist Predicts Voting for Extreme Parties

    NARCIS (Netherlands)

    van der Bles, Anne Marthe; Postmes, Tom; LeKander-Kanis, Babet; Otjes, Simon

    2018-01-01

    In recent years, extreme right-wing and left-wing political parties and actors have gained popularity in many Western countries. What motivates people to vote for extreme right- or left-wing parties? In previous research, we showed that a collectively shared sense of doom and gloom about society can

  16. Prediction of fatigue life under service loading using the relative method

    International Nuclear Information System (INIS)

    Buch, A.

    1982-01-01

    Fatigue life estimates obtained with the local strain approach (LSA) and with the conventional nominal stress approach (NSA) were compared with experimental results obtained on notched AlCuMg2 aircraft material specimens with flight simulation random tensile loading. The effect of change of the reference stress, of the loading program and of some changes in the loading frequency distribution, on the ratio Nsub(exp)/Nsub(pred) was investigated. A material strain-life curve, a cyclic stress-strain curve. The Neuber-Topper rule Ksub(sigma) x Ksub(epsilon) = K 2 = const. and a K value estimated with an exact two-parameter notch factor formula for the case R = 0, N = 10 7 were used for life predictions. (orig./RW) [de

  17. Loading intensity prediction by velocity and the OMNI-RES 0–10 scale in bench press

    OpenAIRE

    Naclerio, Fernando; Larumbe-Zabala, Eneko

    2017-01-01

    This study examined the possibility of using movement velocity and the perceived exertion as indicators of relative load in the bench press exercise. Three hundred eight young, healthy, resistance trained athletes (242 male and 66 female) performed a progressive strength test up to the one-repetition maximum for the individual determination of the full load-velocity and load-exertion relationships. Longitudinal regression models were used to predict the relative load from the average velocity...

  18. Predicting Sport and Occupational Lower Extremity Injury Risk through Movement Quality Screening: A Systematic Review

    Science.gov (United States)

    Whittaker, Jackie L; Booysen, Nadine; de la Motte, Sarah; Dennett, Liz; Lewis, Cara L.; Wilson, Dave; McKay, Carly; Warner, Martin; Padua, Darin; Emery, Carolyn A; Stokes, Maria

    2017-01-01

    Background Identification of risk factors for lower extremity (LE) injury in sport and military/first-responder occupations is required to inform injury prevention strategies. Objective To determine if poor movement quality is associated with LE injury in sport and military/first-responder occupations. Material and methods Five electronic databases were systematically searched. Studies selected included: original data; analytic design; movement quality outcome (qualitative rating of functional compensation, asymmetry, impairment or efficiency of movement control); LE injury sustained with sport or military/first-responder occupation. The PRISMA guidelines were followed. Two independent authors assessed the quality [Downs and Black (DB) criteria] and level of evidence (Oxford Centre of Evidence-Based Medicine model). Results Of 4361 potential studies, 17 were included. The majority were low quality cohort studies (level 4 evidence). Median DB score was 11/33 (range 3–15). Heterogeneity in methodology and injury definition precluded meta-analyses. The Functional Movement Screen was the most common outcome investigated (15/17 studies). Four studies considered interrelationships between risk factors, seven reported diagnostic accuracy and none tested an intervention program targeting individuals identified as high-risk. There is inconsistent evidence that poor movement quality is associated with increased risk of LE injury in sport and military/first-responder occupations. Conclusions Future research should focus on high quality cohort studies to identify the most relevant movement quality outcomes for predicting injury risk followed by developing and evaluating pre-participation screening and LE injury prevention programs through high quality randomized controlled trials targeting individuals at greater risk of injury based upon screening tests with validated test properties. PMID:27935483

  19. Predicting sport and occupational lower extremity injury risk through movement quality screening: a systematic review.

    Science.gov (United States)

    Whittaker, Jackie L; Booysen, Nadine; de la Motte, Sarah; Dennett, Liz; Lewis, Cara L; Wilson, Dave; McKay, Carly; Warner, Martin; Padua, Darin; Emery, Carolyn A; Stokes, Maria

    2017-04-01

    Identification of risk factors for lower extremity (LE) injury in sport and military/first-responder occupations is required to inform injury prevention strategies. To determine if poor movement quality is associated with LE injury in sport and military/first-responder occupations. 5 electronic databases were systematically searched. Studies selected included original data; analytic design; movement quality outcome (qualitative rating of functional compensation, asymmetry, impairment or efficiency of movement control); LE injury sustained with sport or military/first-responder occupation. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines were followed. 2 independent authors assessed the quality (Downs and Black (DB) criteria) and level of evidence (Oxford Centre of Evidence-Based Medicine model). Of 4361 potential studies, 17 were included. The majority were low-quality cohort studies (level 4 evidence). Median DB score was 11/33 (range 3-15). Heterogeneity in methodology and injury definition precluded meta-analyses. The Functional Movement Screen was the most common outcome investigated (15/17 studies). 4 studies considered inter-relationships between risk factors, 7 reported diagnostic accuracy and none tested an intervention programme targeting individuals identified as high risk. There is inconsistent evidence that poor movement quality is associated with increased risk of LE injury in sport and military/first-responder occupations. Future research should focus on high-quality cohort studies to identify the most relevant movement quality outcomes for predicting injury risk followed by developing and evaluating preparticipation screening and LE injury prevention programmes through high-quality randomised controlled trials targeting individuals at greater risk of injury based on screening tests with validated test properties. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted

  20. Recent Successes and Remaining Challenges in Predicting Phosphorus Loading to Surface Waters at Large Scales

    Science.gov (United States)

    Harrison, J.; Metson, G.; Beusen, A.

    2017-12-01

    Over the past century humans have greatly accelerated phosphorus (P) flows from land to aquatic ecosystems, causing eutrophication and associated effects such as harmful algal blooms and hypoxia. Effectively addressing this challenge requires understanding geographic and temporal distribution of aquatic P loading, knowledge of major controls on P loading, and the relative importance of various potential P sources. The Global (N)utrient (E)xport from (W)ater(S)heds) NEWS model and recent improvements and extensions of this modeling system can be used to generate this understanding. This presentation will focus on insights global NEWS models grant into past, present, and potential future P sources and sinks, with a focus on the world's large rivers. Early results suggest: 1) that while aquatic P loading is globally dominated by particulate forms, dissolved P can be locally dominant; 2) that P loading has increased substantially at the global scale, but unevenly between world regions, with hotspots in South and East Asia; 3) that P loading is likely to continue to increase globally, but decrease in certain regions that are actively pursuing proactive P management; and 4) that point sources, especially in urban centers, play an important (even dominant) role in determining loads of dissolved inorganic P. Despite these insights, substantial unexplained variance remains when model predictions and measurements are compared at global and regional scales, for example within the U.S. Disagreements between model predictions and measurements suggest opportunities for model improvement. In particular, explicit inclusion of soil characteristics and the concept of temporal P legacies in future iterations of NEWS (and other) models may help improve correspondence between models and measurements.

  1. Loading Intensity Prediction by Velocity and the OMNI-RES 0-10 Scale in Bench Press.

    Science.gov (United States)

    Naclerio, Fernando; Larumbe-Zabala, Eneko

    2017-02-01

    Naclerio, F and Larumbe-Zabala, E. Loading intensity prediction by velocity and the OMNI-RES 0-10 scale in bench press. J Strength Cond Res 32(1): 323-329, 2017-This study examined the possibility of using movement velocity and the perceived exertion as indicators of relative load in the bench press (BP) exercise. A total of 308 young, healthy, resistance trained athletes (242 men and 66 women) performed a progressive strength test up to the one repetition maximum for the individual determination of the full load-velocity and load-exertion relationships. Longitudinal regression models were used to predict the relative load from the average velocity (AV) and the OMNI-Resistance Exercise Scales (OMNI-RES 0-10 scale), considering sets as the time-related variable. Load associated with the AV and the OMNI-RES 0-10 scale value expressed after performing a set of 1-3 repetitions were used to construct 2 adjusted predictive equations: Relative load = 107.75 - 62.97 × average velocity; and Relative load = 29.03 + 7.26 × OMNI-RES 0-10 scale value. The 2 models were capable of estimating the relative load with an accuracy of 84 and 93%, respectively. These findings confirm the ability of the 2 calculated regression models, using load-velocity and load-exertion from the OMNI-RES 0-10 scale, to accurately predict strength performance in BP.

  2. Evaluation of a numerical model's ability to predict bed load transport observed in braided river experiments

    Science.gov (United States)

    Javernick, Luke; Redolfi, Marco; Bertoldi, Walter

    2018-05-01

    New data collection techniques offer numerical modelers the ability to gather and utilize high quality data sets with high spatial and temporal resolution. Such data sets are currently needed for calibration, verification, and to fuel future model development, particularly morphological simulations. This study explores the use of high quality spatial and temporal data sets of observed bed load transport in braided river flume experiments to evaluate the ability of a two-dimensional model, Delft3D, to predict bed load transport. This study uses a fixed bed model configuration and examines the model's shear stress calculations, which are the foundation to predict the sediment fluxes necessary for morphological simulations. The evaluation is conducted for three flow rates, and model setup used highly accurate Structure-from-Motion (SfM) topography and discharge boundary conditions. The model was hydraulically calibrated using bed roughness, and performance was evaluated based on depth and inundation agreement. Model bed load performance was evaluated in terms of critical shear stress exceedance area compared to maps of observed bed mobility in a flume. Following the standard hydraulic calibration, bed load performance was tested for sensitivity to horizontal eddy viscosity parameterization and bed morphology updating. Simulations produced depth errors equal to the SfM inherent errors, inundation agreement of 77-85%, and critical shear stress exceedance in agreement with 49-68% of the observed active area. This study provides insight into the ability of physically based, two-dimensional simulations to accurately predict bed load as well as the effects of horizontal eddy viscosity and bed updating. Further, this study highlights how using high spatial and temporal data to capture the physical processes at work during flume experiments can help to improve morphological modeling.

  3. Impact of Madden–Julian Oscillation upon Winter Extreme Rainfall in Southern China: Observations and Predictability in CFSv2

    Directory of Open Access Journals (Sweden)

    Hong-Li Ren

    2017-09-01

    Full Text Available The impact of Madden–Julian oscillation (MJO upon extreme rainfall in southern China was studied using the Real-time Multivariate MJO (RMM index and daily precipitation data from high-resolution stations in China. The probability-distribution function (PDF of November–March rainfall in southern China was found to be skewed toward larger (smaller values in phases 2–3 (6–7 of MJO, during which the probability of extreme rainfall events increased (reduced by 30–50% (20–40% relative to all days in the same season. Physical analysis indicated that the favorable conditions for generating extreme rainfall are associated with southwesterly moisture convergence and vertical moisture advection over southern China, while the direct contributions from horizontal moisture advection are insignificant. Based on the above results, the model-based predictability for extreme rainfall in winter was examined using hindcasts from the Climate Forecast System version 2 (CFSv2 of NOAA. It is shown that the modulations of MJO on extreme rainfall are captured and forecasted well by CFSv2, despite the existence of a relatively small bias. This study suggests the feasibility of deriving probabilistic forecasts of extreme rainfall in southern China based on RMM indices.

  4. Enhancing Accuracy of Sediment Total Load Prediction Using Evolutionary Algorithms (Case Study: Gotoorchay River

    Directory of Open Access Journals (Sweden)

    K. Roshangar

    2016-09-01

    Full Text Available Introduction: Exact prediction of transported sediment rate by rivers in water resources projects is of utmost importance. Basically erosion and sediment transport process is one of the most complexes hydrodynamic. Although different studies have been developed on the application of intelligent models based on neural, they are not widely used because of lacking explicitness and complexity governing on choosing and architecting of proper network. In this study, a Genetic expression programming model (as an important branches of evolutionary algorithems for predicting of sediment load is selected and investigated as an intelligent approach along with other known classical and imperical methods such as Larsen´s equation, Engelund-Hansen´s equation and Bagnold´s equation. Materials and Methods: In this study, in order to improve explicit prediction of sediment load of Gotoorchay, located in Aras catchment, Northwestern Iran latitude: 38°24´33.3˝ and longitude: 44°46´13.2˝, genetic programming (GP and Genetic Algorithm (GA were applied. Moreover, the semi-empirical models for predicting of total sediment load and rating curve have been used. Finally all the methods were compared and the best ones were introduced. Two statistical measures were used to compare the performance of the different models, namely root mean square error (RMSE and determination coefficient (DC. RMSE and DC indicate the discrepancy between the observed and computed values. Results and Discussions: The statistical characteristics results obtained from the analysis of genetic programming method for both selected model groups indicated that the model 4 including the only discharge of the river, relative to other studied models had the highest DC and the least RMSE in the testing stage (DC= 0.907, RMSE= 0.067. Although there were several parameters applied in other models, these models were complicated and had weak results of prediction. Our results showed that the model 9

  5. Prediction of wax buildup in 24 inch cold, deep sea oil loading line

    Energy Technology Data Exchange (ETDEWEB)

    Asperger, R.G.; Sattler, R.E.; Tolonen, W.J.; Pitchford, A.C.

    1981-10-01

    When designing pipelines for cold environments, it is important to know how to predict potential problems due to wax deposition on the pipeline's inner surface. The goal of this work was to determine the rate of wax buildup and the maximum, equlibrium wax thickness for a North Sea field loading line. The experimental techniques and results used to evaluate the waxing potential of the crude oil (B) are described. Also, the theoretic model which was used for predicting the maximum wax deposit thickness in the crude oil (B) loading pipeline at controlled temperatures of 40 F (4.4 C) and 100 F (38 C), is illustrated. Included is a recommendation of a procedure for using hot oil at the end of a tanker loading period in order to dewax the crude oil (B) line. This technique would give maximum heating of the pipeline and should be followed by shutting the hot oil into the pipeline at the end of the loading cycle which will provide a hot oil soaking to help soften existing wax. 14 references.

  6. Failure Predictions of Out-of-Autoclave Sandwich Joints with Delaminations Under Flexure Loads

    Science.gov (United States)

    Nordendale, Nikolas A.; Goyal, Vinay K.; Lundgren, Eric C.; Patel, Dhruv N.; Farrokh, Babak; Jones, Justin; Fischetti, Grace; Segal, Kenneth N.

    2015-01-01

    An analysis and a test program was conducted to investigate the damage tolerance of composite sandwich joints. The joints contained a single circular delamination between the face-sheet and the doubler. The coupons were fabricated through out-of-autoclave (OOA) processes, a technology NASA is investigating for joining large composite sections. The four-point bend flexure test was used to induce compression loading into the side of the joint where the delamination was placed. The compression side was chosen since it tends to be one of the most critical loads in launch vehicles. Autoclave cure was used to manufacture the composite sandwich sections, while the doubler was co-bonded onto the sandwich face-sheet using an OOA process after sandwich panels were cured. A building block approach was adopted to characterize the mechanical properties of the joint material, including the fracture toughness between the doubler and face-sheet. Twelve four-point-bend samples were tested, six in the sandwich core ribbon orientation and six in sandwich core cross-ribbon direction. Analysis predicted failure initiation and propagation at the pre-delaminated location, consistent with experimental observations. A building block approach using fracture analyses methods predicted failure loads in close agreement with tests. This investigation demonstrated a small strength reduction due to a flaw of significant size compared to the width of the sample. Therefore, concerns of bonding an OOA material to an in-autoclave material was mitigated for the geometries, materials, and load configurations considered.

  7. Helicopter Rotor Load Prediction Using a Geometrically Exact Beam with Multicomponent Model

    DEFF Research Database (Denmark)

    Lee, Hyun-Ku; Viswamurthy, S.R.; Park, Sang Chul

    2010-01-01

    In this paper, an accurate structural dynamic analysis was developed for a helicopter rotor system including rotor control components, which was coupled to various aerodynamic and wake models in order to predict an aeroelastic response and the loads acting on the rotor. Its blade analysis was based...... rotor-blade/control-system model was loosely coupled with various inflow and wake models in order to simulate both hover and forward-flight conditions. The resulting rotor blade response and pitch link loads are in good agreement with those predicted byCAMRADII. The present analysis features both model...... on an intrinsic formulation of moving beams implemented in the time domain. The rotor control system was modeled as a combination of rigid and elastic components. A multicomponent analysis was then developed by coupling the beam finite element model with the rotor control system model to obtain a complete rotor-blade/control...

  8. Narrowing the scope of failure prediction using targeted fault load injection

    Science.gov (United States)

    Jordan, Paul L.; Peterson, Gilbert L.; Lin, Alan C.; Mendenhall, Michael J.; Sellers, Andrew J.

    2018-05-01

    As society becomes more dependent upon computer systems to perform increasingly critical tasks, ensuring that those systems do not fail becomes increasingly important. Many organizations depend heavily on desktop computers for day-to-day operations. Unfortunately, the software that runs on these computers is written by humans and, as such, is still subject to human error and consequent failure. A natural solution is to use statistical machine learning to predict failure. However, since failure is still a relatively rare event, obtaining labelled training data to train these models is not a trivial task. This work presents new simulated fault-inducing loads that extend the focus of traditional fault injection techniques to predict failure in the Microsoft enterprise authentication service and Apache web server. These new fault loads were successful in creating failure conditions that were identifiable using statistical learning methods, with fewer irrelevant faults being created.

  9. Full scale test SSP 34m blade, edgewise loading LTT. Extreme load and PoC{sub I}nvE Data report

    Energy Technology Data Exchange (ETDEWEB)

    Nielsen, Magda; Roczek-Sieradzan, A.; Jensen, Find M. (and others)

    2010-09-15

    This report is the second report covering the research and demonstration project 'Experimental blade research: Structural mechanisms in current and future large blades under combined loading', supported by the EUDP program. A 34m wind turbine blade from SSP-Technology A/S has been tested in edgewise direction (LTT). The blade has been submitted to thorough examination by means of strain gauges, displacement transducers and a 3D optical measuring system. This data report presents results obtained during full scale testing of the blade up to 80% Risoe load, where 80% Risoe load corresponds to 100% certification load. These pulls at 80% Risoe load were repeated and the results from these pulls were compared. The blade was reinforced according to a Risoe DTU invention, where the trailing edge panels are coupled. The coupling is implemented to prevent the out of plane deformations and to reduce peeling stresses in the adhesive joints. Test results from measurements with the reinforcement have been compared to results without the coupling. The report presents only the relevant results for the 80% Risoe load and the results applicable for the investigation of the influence of the invention on the profile deformation. (Author)

  10. Prediction of bead area contact load at the tire-wheel interface using NASTRAN

    Science.gov (United States)

    Chen, C. H. S.

    1982-01-01

    The theoretical prediction of the bead area contact load at the tire wheel interface using NASTRAN is reported. The application of the linear code to a basically nonlinear problem results in excessive deformation of the structure and the tire-wheel contact conditions become impossible to achieve. A psuedo-nonlinear approach was adopted in which the moduli of the cord reinforced composite are increased so that the computed key deformations matched that of the experiment. Numerical results presented are discussed.

  11. Mid-term load forecasting of power systems by a new prediction method

    International Nuclear Information System (INIS)

    Amjady, Nima; Keynia, Farshid

    2008-01-01

    Mid-term load forecasting (MTLF) becomes an essential tool for today power systems, mainly in those countries whose power systems operate in a deregulated environment. Among different kinds of MTLF, this paper focuses on the prediction of daily peak load for one month ahead. This kind of load forecast has many applications like maintenance scheduling, mid-term hydro thermal coordination, adequacy assessment, management of limited energy units, negotiation of forward contracts, and development of cost efficient fuel purchasing strategies. However, daily peak load is a nonlinear, volatile, and nonstationary signal. Besides, lack of sufficient data usually further complicates this problem. The paper proposes a new methodology to solve it, composed of an efficient data model, preforecast mechanism and combination of neural network and evolutionary algorithm as the hybrid forecast technique. The proposed methodology is examined on the EUropean Network on Intelligent TEchnologies (EUNITE) test data and Iran's power system. We will also compare our strategy with the other MTLF methods revealing its capability to solve this load forecast problem

  12. Prediction of the Tensile Load of Drilled CFRP by Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Burak Yenigun

    2018-04-01

    Full Text Available The application areas of carbon fiber reinforced plastics (CFRP have been increasing day by day. The machining of CFRP with incorrect machining parameters leads in huge loss cost and time. Therefore, it is very important that the composite materials are machined with correct machining parameters. The aim of this paper is to examine the influence of drilling parameters on tensile load after drilling of CFRP. The drilling operations were carried out on Computer Numerical Control (CNC by Tungsten Carbide (WC, High Speed Steel (HSS and Brad Spur type drill bits with spindle speeds of 1000, 3000 and 5000 rpm and feed rates of 0.05, 0.10 and 0.15 mm/rev. The results indicate that the surface roughness, delamination and thrust force, were affected by drilling parameters therefore tensile load was also affected by the same parameters. It was observed that increase in surface roughness, delamination and thrust force all lead to the decrease of tensile load of CFRP. If the correct drilling parameters are selected; the decrease in tensile load of CFRP can be saved up to 25%. Furthermore, an artificial neural network (ANN model has been used to predict of tensile load. The results of the ANN model are in close agreement with the experimental results.

  13. Loading Analysis of Composite Wind Turbine Blade for Fatigue Life Prediction of Adhesively Bonded Root Joint

    Science.gov (United States)

    Salimi-Majd, Davood; Azimzadeh, Vahid; Mohammadi, Bijan

    2015-06-01

    Nowadays wind energy is widely used as a non-polluting cost-effective renewable energy resource. During the lifetime of a composite wind turbine which is about 20 years, the rotor blades are subjected to different cyclic loads such as aerodynamics, centrifugal and gravitational forces. These loading conditions, cause to fatigue failure of the blade at the adhesively bonded root joint, where the highest bending moments will occur and consequently, is the most critical zone of the blade. So it is important to estimate the fatigue life of the root joint. The cohesive zone model is one of the best methods for prediction of initiation and propagation of debonding at the root joint. The advantage of this method is the possibility of modeling the debonding without any requirement to the remeshing. However in order to use this approach, it is necessary to analyze the cyclic loading condition at the root joint. For this purpose after implementing a cohesive interface element in the Ansys finite element software, one blade of a horizontal axis wind turbine with 46 m rotor diameter was modelled in full scale. Then after applying loads on the blade under different condition of the blade in a full rotation, the critical condition of the blade is obtained based on the delamination index and also the load ratio on the root joint in fatigue cycles is calculated. These data are the inputs for fatigue damage growth analysis of the root joint by using CZM approach that will be investigated in future work.

  14. Walking economy is predictably determined by speed, grade, and gravitational load.

    Science.gov (United States)

    Ludlow, Lindsay W; Weyand, Peter G

    2017-11-01

    The metabolic energy that human walking requires can vary by more than 10-fold, depending on the speed, surface gradient, and load carried. Although the mechanical factors determining economy are generally considered to be numerous and complex, we tested a minimum mechanics hypothesis that only three variables are needed for broad, accurate prediction: speed, surface grade, and total gravitational load. We first measured steady-state rates of oxygen uptake in 20 healthy adult subjects during unloaded treadmill trials from 0.4 to 1.6 m/s on six gradients: -6, -3, 0, 3, 6, and 9°. Next, we tested a second set of 20 subjects under three torso-loading conditions (no-load, +18, and +31% body weight) at speeds from 0.6 to 1.4 m/s on the same six gradients. Metabolic rates spanned a 14-fold range from supine rest to the greatest single-trial walking mean (3.1 ± 0.1 to 43.3 ± 0.5 ml O 2 ·kg -body -1 ·min -1 , respectively). As theorized, the walking portion (V̇o 2-walk  =  V̇o 2-gross - V̇o 2-supine-rest ) of the body's gross metabolic rate increased in direct proportion to load and largely in accordance with support force requirements across both speed and grade. Consequently, a single minimum-mechanics equation was derived from the data of 10 unloaded-condition subjects to predict the pooled mass-specific economy (V̇o 2-gross , ml O 2 ·kg -body + load -1 ·min -1 ) of all the remaining loaded and unloaded trials combined ( n = 1,412 trials from 90 speed/grade/load conditions). The accuracy of prediction achieved ( r 2  = 0.99, SEE = 1.06 ml O 2 ·kg -1 ·min -1 ) leads us to conclude that human walking economy is predictably determined by the minimum mechanical requirements present across a broad range of conditions. NEW & NOTEWORTHY Introduced is a "minimum mechanics" model that predicts human walking economy across a broad range of conditions from only three variables: speed, surface grade, and body-plus-load mass. The derivation

  15. Deep Recurrent Model for Server Load and Performance Prediction in Data Center

    Directory of Open Access Journals (Sweden)

    Zheng Huang

    2017-01-01

    Full Text Available Recurrent neural network (RNN has been widely applied to many sequential tagging tasks such as natural language process (NLP and time series analysis, and it has been proved that RNN works well in those areas. In this paper, we propose using RNN with long short-term memory (LSTM units for server load and performance prediction. Classical methods for performance prediction focus on building relation between performance and time domain, which makes a lot of unrealistic hypotheses. Our model is built based on events (user requests, which is the root cause of server performance. We predict the performance of the servers using RNN-LSTM by analyzing the log of servers in data center which contains user’s access sequence. Previous work for workload prediction could not generate detailed simulated workload, which is useful in testing the working condition of servers. Our method provides a new way to reproduce user request sequence to solve this problem by using RNN-LSTM. Experiment result shows that our models get a good performance in generating load and predicting performance on the data set which has been logged in online service. We did experiments with nginx web server and mysql database server, and our methods can been easily applied to other servers in data center.

  16. Comparison of Methods to Predict Lower Bound Buckling Loads of Cylinders Under Axial Compression

    Science.gov (United States)

    Haynie, Waddy T.; Hilburger, Mark W.

    2010-01-01

    Results from a numerical study of the buckling response of two different orthogrid stiffened circular cylindrical shells with initial imperfections and subjected to axial compression are used to compare three different lower bound buckling load prediction techniques. These lower bound prediction techniques assume different imperfection types and include an imperfection based on a mode shape from an eigenvalue analysis, an imperfection caused by a lateral perturbation load, and an imperfection in the shape of a single stress-free dimple. The STAGS finite element code is used for the analyses. Responses of the cylinders for ranges of imperfection amplitudes are considered, and the effect of each imperfection is compared to the response of a geometrically perfect cylinder. Similar behavior was observed for shells that include a lateral perturbation load and a single dimple imperfection, and the results indicate that the predicted lower bounds are much less conservative than the corresponding results for the cylinders with the mode shape imperfection considered herein. In addition, the lateral perturbation technique and the single dimple imperfection produce response characteristics that are physically meaningful and can be validated via testing.

  17. Predicting lake responses to phosphorus loading with measurement-based characterization of P recycling in sediments

    Science.gov (United States)

    Katsev, S.; Li, J.

    2017-12-01

    Predicting the time scales on which lake ecosystems respond to changes in anthropogenic phosphorus loadings is critical for devising efficient management strategies and setting regulatory limits on loading. Internal loading of phosphorus from sediments, however, can significantly contribute to the lake P budget and may delay recovery from eutrophication. The efficiency of mineralization and recycling of settled P in bottom sediments, which is ultimately responsible for this loading, is often poorly known and is surprisingly poorly characterized in the societally important systems such as the Great Lakes. We show that a simple mass-balance model that uses only a minimum number of parameters, all of which are measurable, can successfully predict the time scales over which the total phosphorus (TP) content of lakes responds to changes in external loadings, in a range of situations. The model also predicts the eventual TP levels attained under stable loading conditions. We characterize the efficiency of P recycling in Lake Superior based on a detailed characterization of sediments at 13 locations that includes chemical extractions for P and Fe fractions and characterization of sediment-water exchange fluxes of P. Despite the low efficiency of P remobilization in these deeply oxygenated sediments (only 12% of deposited P is recycled), effluxes of dissolved phosphorus (2.5-7.0 μmol m-2 d-1) still contribute 37% to total P inputs into the water column. In this oligotrophic large lake, phosphate effluxes are regulated by organic sedimentation rather than sediment redox conditions. By adjusting the recycling efficiency to conditions in other Laurentian Great Lakes, we show that the model reproduces the historical data for total phosphorus levels. Analysis further suggests that, in the Lower Lakes, the rate of P sequestration from water column into sediments has undergone a significant change in recent decades, possibly in response to their invasion by quagga mussels

  18. Prior contralateral amputation predicts worse outcomes for lower extremity bypasses performed in the intact limb.

    Science.gov (United States)

    Baril, Donald T; Goodney, Philip P; Robinson, William P; Nolan, Brian W; Stone, David H; Li, YouFu; Cronenwett, Jack L; Schanzer, Andres

    2012-08-01

    To date, history of a contralateral amputation as a potential predictor of outcomes after lower extremity bypass (LEB) for critical limb ischemia (CLI) has not been studied. We sought to determine if a prior contralateral lower extremity amputation predicts worse outcomes in patients undergoing LEB in the remaining intact limb. A retrospective analysis of all patients undergoing infrainguinal LEB for CLI between 2003 and 2010 within hospitals comprising the Vascular Study Group of New England was performed. Patients were stratified according to whether or not they had previously undergone a contralateral major or minor amputation before LEB. Primary end points included major amputation and graft occlusion at 1 year postoperatively. Secondary end points included in-hospital major adverse events, discharge status, and mortality at 1 year. Of 2636 LEB procedures, 228 (8.6%) were performed in the setting of a prior contralateral amputation. Patients with a prior amputation compared to those without were younger (66.5 vs 68.7; P = .034), more like to have congestive heart failure (CHF; 25% vs 16%; P = .002), hypertension (94% vs 85%; P = .015), renal insufficiency (26% vs 14%; P = .0002), and hemodialysis-dependent renal failure (14% vs 6%; P = .0002). They were also more likely to be nursing home residents (8.0% vs 3.6%; P = .036), less likely to ambulate without assistance (41% vs 80%; P < .0002), and more likely to have had a prior ipsilateral bypass (20% vs 12%; P = .0005). These patients experience increased in-hospital major adverse events, including myocardial infarction (MI; 8.9% vs 4.2%; P = .002), CHF (6.1% vs 3.4%; P = .044), deterioration in renal function (9.0% vs 4.7%; P = .006), and respiratory complications (4.2% vs 2.3%; P = .034). They were less likely to be discharged home (52% vs 72%; P < .0001) and less likely to be ambulatory on discharge (25% vs 55%; P < .0001). Although patients with a prior contralateral amputation experienced increased rates of

  19. Predicting dynamic knee joint load with clinical measures in people with medial knee osteoarthritis.

    Science.gov (United States)

    Hunt, Michael A; Bennell, Kim L

    2011-08-01

    Knee joint loading, as measured by the knee adduction moment (KAM), has been implicated in the pathogenesis of knee osteoarthritis (OA). Given that the KAM can only currently be accurately measured in the laboratory setting with sophisticated and expensive equipment, its utility in the clinical setting is limited. This study aimed to determine the ability of a combination of four clinical measures to predict KAM values. Three-dimensional motion analysis was used to calculate the peak KAM at a self-selected walking speed in 47 consecutive individuals with medial compartment knee OA and varus malalignment. Clinical predictors included: body mass; tibial angle measured using an inclinometer; walking speed; and visually observed trunk lean toward the affected limb during the stance phase of walking. Multiple linear regression was performed to predict KAM magnitudes using the four clinical measures. A regression model including body mass (41% explained variance), tibial angle (17% explained variance), and walking speed (9% explained variance) explained a total of 67% of variance in the peak KAM. Our study demonstrates that a set of measures easily obtained in the clinical setting (body mass, tibial alignment, and walking speed) can help predict the KAM in people with medial knee OA. Identifying those patients who are more likely to experience high medial knee loads could assist clinicians in deciding whether load-modifying interventions may be appropriate for patients, whilst repeated assessment of joint load could provide a mechanism to monitor disease progression or success of treatment. Copyright © 2010 Elsevier B.V. All rights reserved.

  20. Energy Coordinative Optimization of Wind-Storage-Load Microgrids Based on Short-Term Prediction

    Directory of Open Access Journals (Sweden)

    Changbin Hu

    2015-02-01

    Full Text Available According to the topological structure of wind-storage-load complementation microgrids, this paper proposes a method for energy coordinative optimization which focuses on improvement of the economic benefits of microgrids in the prediction framework. First of all, the external characteristic mathematical model of distributed generation (DG units including wind turbines and storage batteries are established according to the requirements of the actual constraints. Meanwhile, using the minimum consumption costs from the external grid as the objective function, a grey prediction model with residual modification is introduced to output the predictive wind turbine power and load at specific periods. Second, based on the basic framework of receding horizon optimization, an intelligent genetic algorithm (GA is applied to figure out the optimum solution in the predictive horizon for the complex non-linear coordination control model of microgrids. The optimum results of the GA are compared with the receding solution of mixed integer linear programming (MILP. The obtained results show that the method is a viable approach for energy coordinative optimization of microgrid systems for energy flow and reasonable schedule. The effectiveness and feasibility of the proposed method is verified by examples.

  1. Using subseasonal-to-seasonal (S2S) extreme rainfall forecasts for extended-range flood prediction in Australia

    Science.gov (United States)

    White, C. J.; Franks, S. W.; McEvoy, D.

    2015-06-01

    Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal). Making improvements to extended-range rainfall and flood forecast models, assessing forecast skill and uncertainty, and exploring how to apply flood forecasts and communicate their benefits to decision-makers are significant challenges facing the forecasting and water resources management communities. This paper presents some of the latest science and initiatives from Australia on the development, application and communication of extreme rainfall and flood forecasts on the extended-range "subseasonal-to-seasonal" (S2S) forecasting timescale, with a focus on risk-based decision-making, increasing flood risk awareness and preparedness, capturing uncertainty, understanding human responses to flood forecasts and warnings, and the growing adoption of "climate services". The paper also demonstrates how forecasts of flood events across a range of prediction timescales could be beneficial to a range of sectors and society, most notably for disaster risk reduction (DRR) activities, emergency management and response, and strengthening community resilience. Extended-range S2S extreme flood forecasts, if presented as easily accessible, timely and relevant information are a valuable resource to help society better prepare for, and subsequently cope with, extreme flood events.

  2. Using subseasonal-to-seasonal (S2S extreme rainfall forecasts for extended-range flood prediction in Australia

    Directory of Open Access Journals (Sweden)

    C. J. White

    2015-06-01

    Full Text Available Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal. Making improvements to extended-range rainfall and flood forecast models, assessing forecast skill and uncertainty, and exploring how to apply flood forecasts and communicate their benefits to decision-makers are significant challenges facing the forecasting and water resources management communities. This paper presents some of the latest science and initiatives from Australia on the development, application and communication of extreme rainfall and flood forecasts on the extended-range "subseasonal-to-seasonal" (S2S forecasting timescale, with a focus on risk-based decision-making, increasing flood risk awareness and preparedness, capturing uncertainty, understanding human responses to flood forecasts and warnings, and the growing adoption of "climate services". The paper also demonstrates how forecasts of flood events across a range of prediction timescales could be beneficial to a range of sectors and society, most notably for disaster risk reduction (DRR activities, emergency management and response, and strengthening community resilience. Extended-range S2S extreme flood forecasts, if presented as easily accessible, timely and relevant information are a valuable resource to help society better prepare for, and subsequently cope with, extreme flood events.

  3. Predictive value of the DASH tool for predicting return to work of injured workers with musculoskeletal disorders of the upper extremity.

    Science.gov (United States)

    Armijo-Olivo, Susan; Woodhouse, Linda J; Steenstra, Ivan A; Gross, Douglas P

    2016-12-01

    To determine whether the Disabilities of the Arm, Shoulder, and Hand (DASH) tool added to the predictive ability of established prognostic factors, including patient demographic and clinical outcomes, to predict return to work (RTW) in injured workers with musculoskeletal (MSK) disorders of the upper extremity. A retrospective cohort study using a population-based database from the Workers' Compensation Board of Alberta (WCB-Alberta) that focused on claimants with upper extremity injuries was used. Besides the DASH, potential predictors included demographic, occupational, clinical and health usage variables. Outcome was receipt of compensation benefits after 3 months. To identify RTW predictors, a purposeful logistic modelling strategy was used. A series of receiver operating curve analyses were performed to determine which model provided the best discriminative ability. The sample included 3036 claimants with upper extremity injuries. The final model for predicting RTW included the total DASH score in addition to other established predictors. The area under the curve for this model was 0.77, which is interpreted as fair discrimination. This model was statistically significantly different than the model of established predictors alone (pmodels (p=0.34). The DASH tool together with other established predictors significantly helped predict RTW after 3 months in participants with upper extremity MSK disorders. An appealing result for clinicians and busy researchers is that DASH item 23 has equal predictive ability to the total DASH score. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  4. Modified Inverse First Order Reliability Method (I-FORM) for Predicting Extreme Sea States.

    Energy Technology Data Exchange (ETDEWEB)

    Eckert-Gallup, Aubrey Celia; Sallaberry, Cedric Jean-Marie; Dallman, Ann Renee; Neary, Vincent Sinclair

    2014-09-01

    Environmental contours describing extreme sea states are generated as the input for numerical or physical model simulation s as a part of the stand ard current practice for designing marine structure s to survive extreme sea states. Such environmental contours are characterized by combinations of significant wave height ( ) and energy period ( ) values calculated for a given recurrence interval using a set of data based on hindcast simulations or buoy observations over a sufficient period of record. The use of the inverse first - order reliability method (IFORM) i s standard design practice for generating environmental contours. In this paper, the traditional appli cation of the IFORM to generating environmental contours representing extreme sea states is described in detail and its merits and drawbacks are assessed. The application of additional methods for analyzing sea state data including the use of principal component analysis (PCA) to create an uncorrelated representation of the data under consideration is proposed. A reexamination of the components of the IFORM application to the problem at hand including the use of new distribution fitting techniques are shown to contribute to the development of more accurate a nd reasonable representations of extreme sea states for use in survivability analysis for marine struc tures. Keywords: In verse FORM, Principal Component Analysis , Environmental Contours, Extreme Sea State Characteri zation, Wave Energy Converters

  5. STRUCTURAL SCALE LIFE PREDICTION OF AERO STRUCTURES EXPERIENCING COMBINED EXTREME ENVIRONMENTS

    Science.gov (United States)

    2017-07-01

    complex loading environments. Today’s state of the art methods cannot address structural reliability under combined environment conditions due to...probabilistically assess the structural life under complex loading environments. Today’s state of the art methods cannot address structural reliability...Institute of Aeronautics and Astronautics, San Diego, CA, January 4th‐8th, 2016. Clark, L. D., Bae, H., Gobal, K., and Penmetsa, R., “ Engineering

  6. Predictive Simulations of Neuromuscular Coordination and Joint-Contact Loading in Human Gait.

    Science.gov (United States)

    Lin, Yi-Chung; Walter, Jonathan P; Pandy, Marcus G

    2018-04-18

    We implemented direct collocation on a full-body neuromusculoskeletal model to calculate muscle forces, ground reaction forces and knee contact loading simultaneously for one cycle of human gait. A data-tracking collocation problem was solved for walking at the normal speed to establish the practicality of incorporating a 3D model of articular contact and a model of foot-ground interaction explicitly in a dynamic optimization simulation. The data-tracking solution then was used as an initial guess to solve predictive collocation problems, where novel patterns of movement were generated for walking at slow and fast speeds, independent of experimental data. The data-tracking solutions accurately reproduced joint motion, ground forces and knee contact loads measured for two total knee arthroplasty patients walking at their preferred speeds. RMS errors in joint kinematics were joint kinematics, ground forces, knee contact loads and muscle activation patterns measured for slow and fast walking. The results demonstrate the feasibility of performing computationally-efficient, predictive, dynamic optimization simulations of movement using full-body, muscle-actuated models with realistic representations of joint function.

  7. Automatic Power Control for Daily Load-following Operation using Model Predictive Control Method

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Keuk Jong; Kim, Han Gon [KH, Daejeon (Korea, Republic of)

    2009-10-15

    Under the circumstances that nuclear power occupies more than 50%, nuclear power plants are required to be operated on load-following operation in order to make the effective management of electric grid system and enhanced responsiveness to rapid changes in power demand. Conventional reactors such as the OPR1000 and APR1400 have a regulating system that controls the average temperature of the reactor core relation to the reference temperature. This conventional method has the advantages of proven technology and ease of implementation. However, this method is unsuitable for controlling the axial power shape, particularly the load following operation. Accordingly, this paper reports on the development of a model predictive control method which is able to control the reactor power and the axial shape index. The purpose of this study is to analyze the behavior of nuclear reactor power and the axial power shape by using a model predictive control method when the power is increased and decreased for a daily load following operation. The study confirms that deviations in the axial shape index (ASI) are within the operating limit.

  8. Dynamic Loads and Wake Prediction for Large Wind Turbines Based on Free Wake Method

    Institute of Scientific and Technical Information of China (English)

    Cao Jiufa; Wang Tongguang; Long Hui; Ke Shitang; Xu Bofeng

    2015-01-01

    With large scale wind turbines ,the issue of aerodynamic elastic response is even more significant on dy-namic behaviour of the system .Unsteady free vortex wake method is proposed to calculate the shape of wake and aerodynamic load .Considering the effect of aerodynamic load ,inertial load and gravity load ,the decoupling dy-namic equations are established by using finite element method in conjunction of the modal method and equations are solved numerically by Newmark approach .Finally ,the numerical simulation of a large scale wind turbine is performed through coupling the free vortex wake modelling with structural modelling .The results show that this coupling model can predict the flexible wind turbine dynamic characteristics effectively and efficiently .Under the influence of the gravitational force ,the dynamic response of flapwise direction contributes to the dynamic behavior of edgewise direction under the operational condition of steady wind speed .The difference in dynamic response be-tween the flexible and rigid wind turbines manifests when the aerodynamics/structure coupling effect is of signifi-cance in both wind turbine design and performance calculation .

  9. Using PROGUMBEL to predict extreme external hazards during nuclear power plant construction

    International Nuclear Information System (INIS)

    Diburg, S.; Hoelscher, N.; Niemann, H.J.; Meiswinkel, R.

    2010-01-01

    Safety considerations concerning the construction of power plants, supporting structure planning, safety concept and structural design require reliable data on external events, their incidence probability and characteristic parameters. The basis for supporting structure calculations based on probabilistic reliability considerations is the knowledge on the statistical distribution or the incidence frequency of specific phenomena and their characteristic basic variables. The extreme value statistics software PRO GUMBEL is the extended version of the original GUMBEL software used for seismic assessments. The authors describe the features of the software, that covers seismic events, flooding and extreme storms.

  10. Application of Model Predictive Control for Active Load Management in a Distributed Power System with High Wind Penetration

    DEFF Research Database (Denmark)

    Zong, Yi; Kullmann, Daniel; Thavlov, Anders

    2012-01-01

    management. It also presents in detail how to implement a thermal model predictive controller (MPC) for the heaters' power consumption prediction in the PowerFlexHouse. It demonstrates that this MPC strategy can realize load shifting, and using good predictions in MPC-based control, a better matching...

  11. Distributed Model Predictive Load Frequency Control of Multi-area Power System with DFIGs

    Institute of Scientific and Technical Information of China (English)

    Yi Zhang; Xiangjie Liu; Bin Qu

    2017-01-01

    Reliable load frequency control(LFC) is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control(DMPC) based on coordination scheme.The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints(GRCs), load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed–loop performance, and computational burden with the physical constraints.

  12. A simplified model predicting the weight of the load carrying beam in a wind turbine blade

    DEFF Research Database (Denmark)

    Mikkelsen, Lars Pilgaard

    2016-01-01

    from 20 to 90 m. In addition, it can be seen that for a blade using glass fibre reinforced polymers, the design is controlled by the deflection and thereby the material stiffness in order to avoid the blade to hit the tower. On the other hand if using aluminium, the design will be controlled...... to predict the weight of the load carrying beam when using glassfibre reinforced polymers, carbon fibre reinforced polymers or an aluminium alloy as the construction material. Thereby, it is found that the weight of a glass fibre wind turbine blade is increased from 0.5 to 33 tons when the blade length grows...... by the fatigue resistance in orderto making the material survive the 100 to 500 million load cycles experience of the windturbine blade throughout the lifetime. The aluminium blade is also found to be considerably heavier compared with the composite blades....

  13. Literature review for Texas Department of Transportation Research Project 0-4695: Guidance for design in areas of extreme bed-load mobility, Edwards Plateau, Texas

    Science.gov (United States)

    Heitmuller, Franklin T.; Asquith, William H.; Fang, Xing; Thompson, David B.; Wang, Keh-Han

    2005-01-01

    A review of the literature addressing sediment transport in gravel-bed river systems and structures designed to control bed-load mobility is provided as part of Texas Department of Transportation research project 0–4695: Guidance for Design in Areas of Extreme Bed-Load Mobility. The study area comprises the western half of the Edwards Plateau in central Texas. Three primary foci of the literature review are journal articles, edited volumes, and government publications. Major themes within the body of literature include deterministic sediment transport theory and equations, development of methods to measure and analyze fluvial sediment, applications and development of theory in natural channels and flume experiments, and recommendations for river management and structural design. The literature review provides an outline and foundation for the research project to characterize extreme bed-load mobility in rivers and streams across the study area. The literature review also provides a basis upon which potential modifications to low-water stream-crossing design in the study area can be made.

  14. Reliability analysis and prediction of mixed mode load using Markov Chain Model

    International Nuclear Information System (INIS)

    Nikabdullah, N.; Singh, S. S. K.; Alebrahim, R.; Azizi, M. A.; K, Elwaleed A.; Noorani, M. S. M.

    2014-01-01

    The aim of this paper is to present the reliability analysis and prediction of mixed mode loading by using a simple two state Markov Chain Model for an automotive crankshaft. The reliability analysis and prediction for any automotive component or structure is important for analyzing and measuring the failure to increase the design life, eliminate or reduce the likelihood of failures and safety risk. The mechanical failures of the crankshaft are due of high bending and torsion stress concentration from high cycle and low rotating bending and torsional stress. The Markov Chain was used to model the two states based on the probability of failure due to bending and torsion stress. In most investigations it revealed that bending stress is much serve than torsional stress, therefore the probability criteria for the bending state would be higher compared to the torsion state. A statistical comparison between the developed Markov Chain Model and field data was done to observe the percentage of error. The reliability analysis and prediction was derived and illustrated from the Markov Chain Model were shown in the Weibull probability and cumulative distribution function, hazard rate and reliability curve and the bathtub curve. It can be concluded that Markov Chain Model has the ability to generate near similar data with minimal percentage of error and for a practical application; the proposed model provides a good accuracy in determining the reliability for the crankshaft under mixed mode loading

  15. Artificial neural network (ANN)-based prediction of depth filter loading capacity for filter sizing.

    Science.gov (United States)

    Agarwal, Harshit; Rathore, Anurag S; Hadpe, Sandeep Ramesh; Alva, Solomon J

    2016-11-01

    This article presents an application of artificial neural network (ANN) modelling towards prediction of depth filter loading capacity for clarification of a monoclonal antibody (mAb) product during commercial manufacturing. The effect of operating parameters on filter loading capacity was evaluated based on the analysis of change in the differential pressure (DP) as a function of time. The proposed ANN model uses inlet stream properties (feed turbidity, feed cell count, feed cell viability), flux, and time to predict the corresponding DP. The ANN contained a single output layer with ten neurons in hidden layer and employed a sigmoidal activation function. This network was trained with 174 training points, 37 validation points, and 37 test points. Further, a pressure cut-off of 1.1 bar was used for sizing the filter area required under each operating condition. The modelling results showed that there was excellent agreement between the predicted and experimental data with a regression coefficient (R 2 ) of 0.98. The developed ANN model was used for performing variable depth filter sizing for different clarification lots. Monte-Carlo simulation was performed to estimate the cost savings by using different filter areas for different clarification lots rather than using the same filter area. A 10% saving in cost of goods was obtained for this operation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1436-1443, 2016. © 2016 American Institute of Chemical Engineers.

  16. Constrained model predictive control for load-following operation of APR reactors

    International Nuclear Information System (INIS)

    Kim, Jae Hwan; Lee, Sim Won; Kim, Ju Hyun; Na, Man Gyun; Yu, Keuk Jong; Kim, Han Gon

    2012-01-01

    The load-following operation of APR+ reactor is needed to control the power effectively using the control rods and to restrain the reactivity control from using the boric acid for flexibility of plant operation. Usually, the reason why the disproportion of axial flux distribution occurs during load-following operation is xenon-induced oscillation. The xenon has a very high absorption cross-section and makes the impact on the reactor delayed by the iodine precursor. The power maneuvering using automatically load-following operation has advantage in terms of safety and economic operation of the reactor, so the controller has to be designed efficiently. Therefore, an advanced control method that meets the conditions such as automatic control, flexibility, safety, and convenience is necessary to load-following operation of APR+ reactor. In this paper, the constrained model predictive control (MPC) method is applied to design APR reactor's automatic load-following controller for the integrated thermal power level and axial shape index (ASI) control. Some controllers use only the current tracking command, but MPC considers future commands in addition to the current tracking command. So, MPC can achieve better tracking performance than others. Furthermore, an MPC is to used in many industrial process control systems. The basic concept of the MPC is to solve an optimization problem for a finite future time interval at present time and to implement the first optimal control input as the current control input. The KISPAC-1D code, which models the APR+ nuclear power plants, is interfaced to the proposed controller to verify the tracking performance of the reactor power level and ASI. It is known that the proposed controller exhibits very fast tracking responses

  17. Prediction of a Francis turbine prototype full load instability from investigations on the reduced scale model

    Science.gov (United States)

    Alligné, S.; Maruzewski, P.; Dinh, T.; Wang, B.; Fedorov, A.; Iosfin, J.; Avellan, F.

    2010-08-01

    The growing development of renewable energies combined with the process of privatization, lead to a change of economical energy market strategies. Instantaneous pricings of electricity as a function of demand or predictions, induces profitable peak productions which are mainly covered by hydroelectric power plants. Therefore, operators harness more hydroelectric facilities at full load operating conditions. However, the Francis Turbine features an axi-symmetric rope leaving the runner which may act under certain conditions as an internal energy source leading to instability. Undesired power and pressure fluctuations are induced which may limit the maximum available power output. BC Hydro experiences such constraints in a hydroelectric power plant consisting of four 435 MW Francis Turbine generating units, which is located in Canada's province of British Columbia. Under specific full load operating conditions, one unit experiences power and pressure fluctuations at 0.46 Hz. The aim of the paper is to present a methodology allowing prediction of this prototype's instability frequency from investigations on the reduced scale model. A new hydro acoustic vortex rope model has been developed in SIMSEN software, taking into account the energy dissipation due to the thermodynamic exchange between the gas and the surrounding liquid. A combination of measurements, CFD simulations and computation of eigenmodes of the reduced scale model installed on test rig, allows the accurate calibration of the vortex rope model parameters at the model scale. Then, transposition of parameters to the prototype according to similitude laws is applied and stability analysis of the power plant is performed. The eigenfrequency of 0.39 Hz related to the first eigenmode of the power plant is determined to be unstable. Predicted frequency of the full load power and pressure fluctuations at the unit unstable operating point is found to be in general agreement with the prototype measurements.

  18. Prediction of a Francis turbine prototype full load instability from investigations on the reduced scale model

    International Nuclear Information System (INIS)

    Alligne, S; Maruzewski, P; Avellan, F; Dinh, T; Wang, B; Fedorov, A; Iosfin, J

    2010-01-01

    The growing development of renewable energies combined with the process of privatization, lead to a change of economical energy market strategies. Instantaneous pricings of electricity as a function of demand or predictions, induces profitable peak productions which are mainly covered by hydroelectric power plants. Therefore, operators harness more hydroelectric facilities at full load operating conditions. However, the Francis Turbine features an axi-symmetric rope leaving the runner which may act under certain conditions as an internal energy source leading to instability. Undesired power and pressure fluctuations are induced which may limit the maximum available power output. BC Hydro experiences such constraints in a hydroelectric power plant consisting of four 435 MW Francis Turbine generating units, which is located in Canada's province of British Columbia. Under specific full load operating conditions, one unit experiences power and pressure fluctuations at 0.46 Hz. The aim of the paper is to present a methodology allowing prediction of this prototype's instability frequency from investigations on the reduced scale model. A new hydro acoustic vortex rope model has been developed in SIMSEN software, taking into account the energy dissipation due to the thermodynamic exchange between the gas and the surrounding liquid. A combination of measurements, CFD simulations and computation of eigenmodes of the reduced scale model installed on test rig, allows the accurate calibration of the vortex rope model parameters at the model scale. Then, transposition of parameters to the prototype according to similitude laws is applied and stability analysis of the power plant is performed. The eigenfrequency of 0.39 Hz related to the first eigenmode of the power plant is determined to be unstable. Predicted frequency of the full load power and pressure fluctuations at the unit unstable operating point is found to be in general agreement with the prototype measurements.

  19. Analytical approach for predicting three-dimensional tire-pavement contact load

    CSIR Research Space (South Africa)

    Hernandez, JA

    2014-12-01

    Full Text Available stream_source_info De Beer1_2014.pdf.txt stream_content_type text/plain stream_size 38657 Content-Encoding UTF-8 stream_name De Beer1_2014.pdf.txt Content-Type text/plain; charset=UTF-8 75 Transportation Research Record... by measuring the applied forces in each perpendicular direction (15). Analytical Approach for Predicting Three-Dimensional Tire–Pavement Contact Load Jaime A. Hernandez, Angeli Gamez, Imad L. Al-Qadi, and Morris De Beer J. A. Hernandez, A. Gamez, and I. L...

  20. Adaptive algorithm for predicting increases in central loads of electrical energy systems

    Energy Technology Data Exchange (ETDEWEB)

    Arbachyauskene, N A; Pushinaytis, K V

    1982-01-01

    An adaptive algorithm for predicting increases in central loads of the electrical energy system is suggested for the task of evaluating the condition. The algorithm is based on the Kalman filter. In order to calculate the coefficient of intensification, the a priori assigned noise characteristics with low accuracy are used only in the beginning of the calculation. Further, the coefficient of intensification is calculated from the innovation sequence. This approach makes it possible to correct errors in the assignment of the statistical noise characteristics and to follow their changes. The algorithm is experimentally verified.

  1. Dorsolateral Prefrontal Cortex GABA Concentration in Humans Predicts Working Memory Load Processing Capacity.

    Science.gov (United States)

    Yoon, Jong H; Grandelis, Anthony; Maddock, Richard J

    2016-11-16

    The discovery of neural mechanisms of working memory (WM) would significantly enhance our understanding of complex human behaviors and guide treatment development for WM-related impairments found in neuropsychiatric conditions and aging. Although the dorsolateral prefrontal cortex (DLPFC) has long been considered critical for WM, we still know little about the neural elements and pathways within the DLPFC that support WM in humans. In this study, we tested whether an individual's DLPFC gamma-aminobutryic acid (GABA) content predicts individual differences in WM task performance using a novel behavioral approach. Twenty-three healthy adults completed a task that measured the unique contribution of major WM components (memory load, maintenance, and distraction resistance) to performance. This was done to address the possibility that components have differing GABA dependencies and the failure to parse WM into components would lead to missing true associations with GABA. The subjects then had their DLPFC GABA content measured by single-voxel proton magnetic spectroscopy. We found that individuals with lower DLPFC GABA showed greater performance degradation with higher load, accounting for 31% of variance, p (corrected) = 0.015. This relationship was component, neurochemical, and brain region specific. DLPFC GABA content did not predict performance sensitivity to other components tested; DLPFC glutamate + glutamine and visual cortical GABA content did not predict load sensitivity. These results confirm the involvement of DLPFC GABA in WM load processing in humans and implicate factors controlling DLPFC GABA content in the neural mechanisms of WM and its impairments. This study demonstrated for the first time that the amount of gamma-aminobutryic acid (GABA), the major inhibitory neurotransmitter of the brain, in an individual's prefrontal cortex predicts working memory (WM) task performance. Given that WM is required for many of the most characteristic cognitive and

  2. Empirical Model Development for Predicting Shock Response on Composite Materials Subjected to Pyroshock Loading

    Science.gov (United States)

    Gentz, Steven J.; Ordway, David O; Parsons, David S.; Garrison, Craig M.; Rodgers, C. Steven; Collins, Brian W.

    2015-01-01

    The NASA Engineering and Safety Center (NESC) received a request to develop an analysis model based on both frequency response and wave propagation analyses for predicting shock response spectrum (SRS) on composite materials subjected to pyroshock loading. The model would account for near-field environment (approx. 9 inches from the source) dominated by direct wave propagation, mid-field environment (approx. 2 feet from the source) characterized by wave propagation and structural resonances, and far-field environment dominated by lower frequency bending waves in the structure. This report documents the outcome of the assessment.

  3. Robust Distributed Model Predictive Load Frequency Control of Interconnected Power System

    Directory of Open Access Journals (Sweden)

    Xiangjie Liu

    2013-01-01

    Full Text Available Considering the load frequency control (LFC of large-scale power system, a robust distributed model predictive control (RDMPC is presented. The system uncertainty according to power system parameter variation alone with the generation rate constraints (GRC is included in the synthesis procedure. The entire power system is composed of several control areas, and the problem is formulated as convex optimization problem with linear matrix inequalities (LMI that can be solved efficiently. It minimizes an upper bound on a robust performance objective for each subsystem. Simulation results show good dynamic response and robustness in the presence of power system dynamic uncertainties.

  4. Validated Loads Prediction Models for Offshore Wind Turbines for Enhanced Component Reliability

    DEFF Research Database (Denmark)

    Koukoura, Christina

    To improve the reliability of offshore wind turbines, accurate prediction of their response is required. Therefore, validation of models with site measurements is imperative. In the present thesis a 3.6MW pitch regulated-variable speed offshore wind turbine on a monopole foundation is built...... are used for the modification of the sub-structure/foundation design for possible material savings. First, the background of offshore wind engineering, including wind-wave conditions, support structure, blade loading and wind turbine dynamics are presented. Second, a detailed description of the site...

  5. Statistical Model of Extreme Shear

    DEFF Research Database (Denmark)

    Hansen, Kurt Schaldemose; Larsen, Gunner Chr.

    2005-01-01

    In order to continue cost-optimisation of modern large wind turbines, it is important to continuously increase the knowledge of wind field parameters relevant to design loads. This paper presents a general statistical model that offers site-specific prediction of the probability density function...... by a model that, on a statistically consistent basis, describes the most likely spatial shape of an extreme wind shear event. Predictions from the model have been compared with results from an extreme value data analysis, based on a large number of full-scale measurements recorded with a high sampling rate...

  6. The role of atmospheric diagnosis and Big Data science in improving hydroclimatic extreme prediction and the merits of climate informed prediction for future water resources management

    Science.gov (United States)

    Lu, Mengqian; Lall, Upmanu

    2017-04-01

    The threats that hydroclimatic extremes pose to sustainable development, safety and operation of infrastructure are both severe and growing. Recent heavy precipitation triggered flood events in many regions and increasing frequency and intensity of extreme precipitation suggested by various climate projections highlight the importance of understanding the associated hydrometeorological patterns and space-time variability of such extreme events, and developing a new approach to improve predictability with a better estimation of uncertainty. This clear objective requires the optimal utility of Big Data analytics on multi-source datasets to extract informative predictors from the complex ocean-atmosphere coupled system and develop a statistical and physical based framework. The proposed presentation includes the essence of our selected works in the past two years, as part of our Global Floods Initiatives. Our approach for an improved extreme prediction begins with a better understanding of the associated atmospheric circulation patterns, under the influence and regulation of slowly changing oceanic boundary conditions [Lu et al., 2013, 2016a; Lu and Lall, 2016]. The study of the associated atmospheric circulation pattern and the regulation of teleconnected climate signals adopted data science techniques and statistical modeling recognizing the nonstationarity and nonlinearity of the system, as the underlying statistical assumptions of the classical extreme value frequency analysis are challenged in hydroclimatic studies. There are two main factors that are considered important for understanding how future flood risk will change. One is the consideration of moisture holding capacity as a function of temperature, as suggested by Clausius-Clapeyron equation. The other is the strength of the convergence or convection associated with extreme precipitation. As convergence or convection gets stronger, rain rates can be expected to increase if the moisture is available. For

  7. Thermal oxidation of cesium loaded Prussian blue as a precaution for exothermic phase change in extreme conditions

    International Nuclear Information System (INIS)

    Parajuli, Durga; Tanaka, Hisashi; Takahashi, Akira; Kawamoto, Tohru

    2013-01-01

    Cesium adsorbed Prussian blue is studied for the thermal oxidation. The TG-DTA shows exothermic phase change of micro aggregates of nano-PB at above 270°C. For this reason, Cs loaded PB was heated between 180 to 260°C. Heating at 180 removed only the water. Neither the oxidation of Iron nor the removal of cyanide is observed at this temperature. Oxidation of cyanide is observed upon heating above 200°C while loaded Cs is released after heating at >250°C followed by washing with water. Thermal oxidation between 200 to 220°C for more than 2 h showed control on exothermic phase change and loaded Cs is also not solubilized. (author)

  8. Prediction calculation of HTR-10 fuel loading for the first criticality

    International Nuclear Information System (INIS)

    Jing Xingqing; Yang Yongwei; Gu Yuxiang; Shan Wenzhi

    2001-01-01

    The 10 MW high temperature gas cooled reactor (HTR-10) was built at Institute of Nuclear Energy Technology, Tsinghua University, and the first criticality was attained in Dec. 2000. The high temperature gas cooled reactor physics simulation code VSOP was used for the prediction of the fuel loading for HTR-10 first criticality. The number of fuel element and graphite element was predicted to provide reference for the first criticality experiment. The prediction calculations toke into account the factors including the double heterogeneity of the fuel element, buckling feedback for the spectrum calculation, the effect of the mixture of the graphite and the fuel element, and the correction of the diffusion coefficients near the upper cavity based on the transport theory. The effects of impurities in the fuel and the graphite element in the core and those in the reflector graphite on the reactivity of the reactor were considered in detail. The first criticality experiment showed that the predicted values and the experiment results were in good agreement with little relative error less than 1%, which means the prediction was successful

  9. A Hybrid Short-Term Traffic Flow Prediction Model Based on Singular Spectrum Analysis and Kernel Extreme Learning Machine.

    Directory of Open Access Journals (Sweden)

    Qiang Shang

    Full Text Available Short-term traffic flow prediction is one of the most important issues in the field of intelligent transport system (ITS. Because of the uncertainty and nonlinearity, short-term traffic flow prediction is a challenging task. In order to improve the accuracy of short-time traffic flow prediction, a hybrid model (SSA-KELM is proposed based on singular spectrum analysis (SSA and kernel extreme learning machine (KELM. SSA is used to filter out the noise of traffic flow time series. Then, the filtered traffic flow data is used to train KELM model, the optimal input form of the proposed model is determined by phase space reconstruction, and parameters of the model are optimized by gravitational search algorithm (GSA. Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. And the SSA-KELM model is compared with several well-known prediction models, including support vector machine, extreme learning machine, and single KLEM model. The experimental results demonstrate that performance of the proposed model is superior to that of the comparison models. Apart from accuracy improvement, the proposed model is more robust.

  10. On the predictability of extreme events in records with linear and nonlinear long-range memory: Efficiency and noise robustness

    Science.gov (United States)

    Bogachev, Mikhail I.; Bunde, Armin

    2011-06-01

    We study the predictability of extreme events in records with linear and nonlinear long-range memory in the presence of additive white noise using two different approaches: (i) the precursory pattern recognition technique (PRT) that exploits solely the information about short-term precursors, and (ii) the return interval approach (RIA) that exploits long-range memory incorporated in the elapsed time after the last extreme event. We find that the PRT always performs better when only linear memory is present. In the presence of nonlinear memory, both methods demonstrate comparable efficiency in the absence of white noise. When additional white noise is present in the record (which is the case in most observational records), the efficiency of the PRT decreases monotonously with increasing noise level. In contrast, the RIA shows an abrupt transition between a phase of low level noise where the prediction is as good as in the absence of noise, and a phase of high level noise where the prediction becomes poor. In the phase of low and intermediate noise the RIA predicts considerably better than the PRT, which explains our recent findings in physiological and financial records.

  11. Fault Tolerance Automotive Air-Ratio Control Using Extreme Learning Machine Model Predictive Controller

    OpenAIRE

    Pak Kin Wong; Hang Cheong Wong; Chi Man Vong; Tong Meng Iong; Ka In Wong; Xianghui Gao

    2015-01-01

    Effective air-ratio control is desirable to maintain the best engine performance. However, traditional air-ratio control assumes the lambda sensor located at the tail pipe works properly and relies strongly on the air-ratio feedback signal measured by the lambda sensor. When the sensor is warming up during cold start or under failure, the traditional air-ratio control no longer works. To address this issue, this paper utilizes an advanced modelling technique, kernel extreme learning machine (...

  12. Validation of nonlinear FEA models of a thin-walled elbow under extreme loading conditions for Sodium-cooled Fast Reactors

    International Nuclear Information System (INIS)

    Watakabe, Tomoyoshi; Wakai, Takashi; Jin, Chuanrong; Usui, Yoshiya; Sakai, Shinkichi; Ooshika, Junji; Tsukimori, Kazuyuki

    2015-01-01

    For the purpose of confirming failure modes and safety margin, some studies on the ultimate strength of thin-walled piping components for Sodium-cooled Fast Reactors (SFRs) under extreme loading conditions such as large earthquakes have been reported these several years. Nonlinear finite element analysis has been applied in these studies to simulate buckling and yielding with large deformation, whose accuracy is dependent on the element type, the mesh size, the elasto-plastic model and so on. It is important to check the validation of a finite element model for nonlinear analysis especially under extreme loading conditions. This paper presents static and dynamic analyses of a thin-walled elbow with large deformation under large seismic loading, and discusses the validation of the FEA models comparing with experimental results. The finite element analysis models in this study are generated by shell elements for a stainless steel pipe elbow of diameter-to-thickness ratio 59:1 similar to the main pipe of SFRs, which is used for shaking table tests. At first, a static analysis is carried out for an in-plane monotonic bending test, in order to confirm that the shell element is appropriate to the large deformation analysis and the material parameters are proper for the strain level in the experiments. And then, a dynamic in-plane bending test with the maximum acceleration of 11.7G is simulated by the nonlinear FEA with stiffness-proportional damping. The influence of mesh sizes on results is investigated, to determine proper mesh sizes and reduce the computational cost. Finally, comparing the results of the FEM analyses with those of experiments, it is concluded that the appropriately generated FEA models are effective and give accurate results for nonlinear analyses of the thin-walled elbow under large seismic loading. (author)

  13. Adipose tissue and muscle attenuation as novel biomarkers predicting mortality in patients with extremity sarcomas

    International Nuclear Information System (INIS)

    Veld, Joyce; Vossen, Josephina A.; Torriani, Martin; Bredella, Miriam A.; De Amorim Bernstein, Karen; Halpern, Elkan F.

    2016-01-01

    To assess CT-attenuation of abdominal adipose tissue and psoas muscle as predictors of mortality in patients with sarcomas of the extremities. Our study was IRB approved and HIPAA compliant. The study group comprised 135 patients with history of extremity sarcoma (mean age: 53 ± 17 years) who underwent whole body PET/CT. Abdominal subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and psoas muscle attenuation (HU) was assessed on non-contrast, attenuation-correction CT. Clinical information including survival, tumour stage, sarcoma type, therapy and pre-existing comorbidities were recorded. Cox proportional hazard models were used to determine longitudinal associations between adipose tissue and muscle attenuation and mortality. There were 47 deaths over a mean follow-up period of 20 ± 17 months. Higher SAT and lower psoas attenuation were associated with increased mortality (p = 0.03 and p = 0.005, respectively), which remained significant after adjustment for age, BMI, sex, tumor stage, therapy, and comorbidities (p = 0.002 and p = 0.02, respectively). VAT attenuation was not associated with mortality. Attenuation of SAT and psoas muscle, assessed on non-contrast CT, are predictors of mortality in patients with extremity sarcomas, independent of other established prognostic factors, suggesting that adipose tissue and muscle attenuation could serve as novel biomarkers for mortality in patients with sarcomas. (orig.)

  14. Adipose tissue and muscle attenuation as novel biomarkers predicting mortality in patients with extremity sarcomas

    Energy Technology Data Exchange (ETDEWEB)

    Veld, Joyce; Vossen, Josephina A.; Torriani, Martin; Bredella, Miriam A. [Massachusetts General Hospital and Harvard Medical School, Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Boston, MA (United States); De Amorim Bernstein, Karen [Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, Francis H Burr Proton Therapy Center, Boston, MA (United States); Halpern, Elkan F. [Massachusetts General Hospital and Harvard Medical School, Institute of Technology Assessment, Boston, MA (United States)

    2016-12-15

    To assess CT-attenuation of abdominal adipose tissue and psoas muscle as predictors of mortality in patients with sarcomas of the extremities. Our study was IRB approved and HIPAA compliant. The study group comprised 135 patients with history of extremity sarcoma (mean age: 53 ± 17 years) who underwent whole body PET/CT. Abdominal subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and psoas muscle attenuation (HU) was assessed on non-contrast, attenuation-correction CT. Clinical information including survival, tumour stage, sarcoma type, therapy and pre-existing comorbidities were recorded. Cox proportional hazard models were used to determine longitudinal associations between adipose tissue and muscle attenuation and mortality. There were 47 deaths over a mean follow-up period of 20 ± 17 months. Higher SAT and lower psoas attenuation were associated with increased mortality (p = 0.03 and p = 0.005, respectively), which remained significant after adjustment for age, BMI, sex, tumor stage, therapy, and comorbidities (p = 0.002 and p = 0.02, respectively). VAT attenuation was not associated with mortality. Attenuation of SAT and psoas muscle, assessed on non-contrast CT, are predictors of mortality in patients with extremity sarcomas, independent of other established prognostic factors, suggesting that adipose tissue and muscle attenuation could serve as novel biomarkers for mortality in patients with sarcomas. (orig.)

  15. Decentralized model predictive based load frequency control in an interconnected power system

    Energy Technology Data Exchange (ETDEWEB)

    Mohamed, T.H., E-mail: tarekhie@yahoo.co [High Institute of Energy, South Valley University (Egypt); Bevrani, H., E-mail: bevrani@ieee.or [Dept. of Electrical Engineering and Computer Science, University of Kurdistan (Iran, Islamic Republic of); Hassan, A.A., E-mail: aahsn@yahoo.co [Faculty of Engineering, Dept. of Electrical Engineering, Minia University, Minia (Egypt); Hiyama, T., E-mail: hiyama@cs.kumamoto-u.ac.j [Dept. of Electrical Engineering and Computer Science, Kumamoto University, Kumamoto (Japan)

    2011-02-15

    This paper presents a new load frequency control (LFC) design using the model predictive control (MPC) technique in a multi-area power system. The MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. Each local area controller is designed independently such that stability of the overall closed-loop system is guaranteed. A frequency response model of multi-area power system is introduced, and physical constraints of the governors and turbines are considered. The model was employed in the MPC structures. Digital simulations for both two and three-area power systems are provided to validate the effectiveness of the proposed scheme. The results show that, with the proposed MPC technique, the overall closed-loop system performance demonstrated robustness in the face of uncertainties due to governors and turbines parameters variation and loads disturbances. A performance comparison between the proposed controller and a classical integral control scheme is carried out confirming the superiority of the proposed MPC technique.

  16. Short-term load and wind power forecasting using neural network-based prediction intervals.

    Science.gov (United States)

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2014-02-01

    Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

  17. Decentralized model predictive based load frequency control in an interconnected power system

    International Nuclear Information System (INIS)

    Mohamed, T.H.; Bevrani, H.; Hassan, A.A.; Hiyama, T.

    2011-01-01

    This paper presents a new load frequency control (LFC) design using the model predictive control (MPC) technique in a multi-area power system. The MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. Each local area controller is designed independently such that stability of the overall closed-loop system is guaranteed. A frequency response model of multi-area power system is introduced, and physical constraints of the governors and turbines are considered. The model was employed in the MPC structures. Digital simulations for both two and three-area power systems are provided to validate the effectiveness of the proposed scheme. The results show that, with the proposed MPC technique, the overall closed-loop system performance demonstrated robustness in the face of uncertainties due to governors and turbines parameters variation and loads disturbances. A performance comparison between the proposed controller and a classical integral control scheme is carried out confirming the superiority of the proposed MPC technique.

  18. Tool-life prediction under multi-cycle loading during metal forming: a feasibility study

    Directory of Open Access Journals (Sweden)

    Hu Yiran

    2015-01-01

    Full Text Available In the present research, the friction and wear behaviour of a hard coating were studied by using ball-on-disc tests to simulate the wear process of the coated tools for sheet metal forming process. The evolution of the friction coefficient followed a typical dual-plateau pattern, i.e. at the initial stage of sliding, the friction coefficient was relatively low, followed by a sharp increase due to the breakdown of the coatings after a certain number of cyclic dynamic loadings. This phenomenon was caused by the interactive response between the friction and wear from a coating tribo-system, which is often neglected by metal forming researchers, and constant friction coefficient values are normally used in the finite element (FE simulations to represent the complex tribological nature at the contact interfaces. Meanwhile, most of the current FE simulations consider single-cycle loading processes, whereas many metal-forming operations are conducted in a form of multi-cycle loading. Therefore, a novel friction/wear interactive friction model was developed to, simultaneously, characterise the evolutions of friction coefficient and the remaining thickness of the coating layer, to enable the wear life of coated tooling to be predicted. The friction model was then implemented into the FE simulation of a sheet metal forming process for feasibility study.

  19. Predicting Dynamic Response of Structures under Earthquake Loads Using Logical Analysis of Data

    Directory of Open Access Journals (Sweden)

    Ayman Abd-Elhamed

    2018-04-01

    Full Text Available In this paper, logical analysis of data (LAD is used to predict the seismic response of building structures employing the captured dynamic responses. In order to prepare the data, computational simulations using a single degree of freedom (SDOF building model under different ground motion records are carried out. The selected excitation records are real and of different peak ground accelerations (PGA. The sensitivity of the seismic response in terms of displacements of floors to the variation in earthquake characteristics, such as soil class, characteristic period, and time step of records, peak ground displacement, and peak ground velocity, have also been considered. The dynamic equation of motion describing the building model and the applied earthquake load are presented and solved incrementally using the Runge-Kutta method. LAD then finds the characteristic patterns which lead to forecast the seismic response of building structures. The accuracy of LAD is compared to that of an artificial neural network (ANN, since the latter is the most known machine learning technique. Based on the conducted study, the proposed LAD model has been proven to be an efficient technique to learn, simulate, and blindly predict the dynamic response behaviour of building structures subjected to earthquake loads.

  20. Robust nonlinear model predictive control for nuclear power plants in load following operations with bounded xenon oscillations

    International Nuclear Information System (INIS)

    Eliasi, H.; Menhaj, M.B.; Davilu, H.

    2011-01-01

    Research highlights: → In this work, a robust nonlinear model predictive control algorithm is developed. → This algorithm is applied to control the power level for load following. → The state constraints are imposed on the predicted trajectory during optimization. → The xenon oscillations are the main constraint for the load following problem. → In this algorithm, xenon oscillations are bounded within acceptable limits. - Abstract: One of the important operations in nuclear power plants is load-following in which imbalance of axial power distribution induces xenon oscillations. These oscillations must be maintained within acceptable limits otherwise the nuclear power plant could become unstable. Therefore, bounded xenon oscillation considered to be a constraint for the load-following operation. In this paper, a robust nonlinear model predictive control for the load-following operation problem is proposed that ensures xenon oscillations are kept bounded within acceptable limits. The proposed controller uses constant axial offset (AO) strategy to maintain xenon oscillations to be bounded. The constant AO is a robust state constraint for load-following problem. The controller imposes restricted state constraints on the predicted trajectory during optimization which guarantees robust satisfaction of state constraints without restoring to a min-max optimization problem. Simulation results show that the proposed controller for the load-following operation is so effective so that the xenon oscillations kept bounded in the given region.

  1. Spatial reliability analysis of a wind turbine blade cross section subjected to multi-axial extreme loading

    DEFF Research Database (Denmark)

    Dimitrov, Nikolay Krasimirov; Bitsche, Robert; Blasques, José Pedro Albergaria Amaral

    2017-01-01

    This paper presents a methodology for structural reliability analysis of wind turbine blades. The study introduces several novel elements by taking into account loading direction using a multiaxial probabilistic load model, considering random material strength, spatial correlation between material...... properties, progressive material failure, and system reliability effects. An example analysis of reliability against material failure is demonstrated for a blade cross section. Based on the study we discuss the implications of using a system reliability approach, the effect of spatial correlation length......, type of material degradation algorithm, and reliability methods on the system failure probability, as well as the main factors that have an influence on the reliability. (C) 2017 Elsevier Ltd. All rights reserved....

  2. Position of the pelvis, lower extremities load and the arch of the feet in young adults who are physically active

    Directory of Open Access Journals (Sweden)

    Agnieszka Jankowicz-Szymańska

    2013-10-01

    Full Text Available Introduction: Body posture is an individual motion habit. It is variable and depends on the gender, age, structure of the body but also on mental and physical state. Although it is difficult to formulate a universal definition of correct body posture, the opinion that its elementary feature is symmetry is beyond any doubt. Such symmetry is related to the position of particular anatomical points and effects of static and dynamic forces. Aim of the research: To assess the relations between the pelvis position in the frontal plane, the static load on the lower limbs and architecture of the feet. The following features were analysed in a group of young, healthy and particularly physically active women and men: the frequency of asymmetry related to pelvis position, the load on the lower limbs related to body weight and foot architecture. Material and methods: The study group consisted of 100 students of physical education. To assess the position of the pelvis a palpable-visual method was used. Clarke’s method was applied to characterize the foot architecture determined by the position of standing with one leg on the CQ Elektronik podoscope. The static load on the lower limbs was assessed using the stabilographic platform EMILDUE from Technomex. Results : Collected data and observations show frequent asymmetric changes of pelvis position in the frontal plane and incorrect balance of the body in the standing position. The change of static load on the lower limbs influences the longitudinal architecture of the feet and this influence is statistically significant. Increased asymmetry of the pelvis in the frontal plane is related to profound disorder of body balance. Conclusions : Asymmetric position of the pelvis is associated with asymmetric arching of the feet and asymmetric body weight distribution. Full symmetric position of the pelvis is rare even among young people who are physically active.

  3. Extreme Environment Damage Index and Accumulation Model for CMC Laminate Fatigue Life Prediction, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Materials Research & Design (MR&D) is proposing in the SBIR Phase II an effort to develop a tool for predicting the fatigue life of C/SiC composite...

  4. Prediction of Air Pollutants Concentration Based on an Extreme Learning Machine: The Case of Hong Kong

    OpenAIRE

    Zhang, Jiangshe; Ding, Weifu

    2017-01-01

    With the development of the economy and society all over the world, most metropolitan cities are experiencing elevated concentrations of ground-level air pollutants. It is urgent to predict and evaluate the concentration of air pollutants for some local environmental or health agencies. Feed-forward artificial neural networks have been widely used in the prediction of air pollutants concentration. However, there are some drawbacks, such as the low convergence rate and the local minimum. The e...

  5. Scaling approach in predicting the seatbelt loading and kinematics of vulnerable occupants: How far can we go?

    Science.gov (United States)

    Nie, Bingbing; Forman, Jason L; Joodaki, Hamed; Wu, Taotao; Kent, Richard W

    2016-09-01

    Occupants with extreme body size and shape, such as the small female or the obese, were reported to sustain high risk of injury in motor vehicle crashes (MVCs). Dimensional scaling approaches are widely used in injury biomechanics research based on the assumption of geometrical similarity. However, its application scope has not been quantified ever since. The objective of this study is to demonstrate the valid range of scaling approaches in predicting the impact response of the occupants with focus on the vulnerable populations. The present analysis was based on a data set consisting of 60 previously reported frontal crash tests in the same sled buck representing a typical mid-size passenger car. The tests included two categories of human surrogates: 9 postmortem human surrogates (PMHS) of different anthropometries (stature range: 147-189 cm; weight range: 27-151 kg) and 5 anthropomorphic test devices (ATDs). The impact response was considered including the restraint loads and the kinematics of multiple body segments. For each category of the human surrogates, a mid-size occupant was selected as a baseline and the impact response was scaled specifically to another subject based on either the body mass (body shape) or stature (the overall body size). To identify the valid range of the scaling approach, the scaled response was compared to the experimental results using assessment scores on the peak value, peak timing (the time when the peak value occurred), and the overall curve shape ranging from 0 (extremely poor) to 1 (perfect match). Scores of 0.7 to 0.8 and 0.8 to 1.0 indicate fair and acceptable prediction. For both ATDs and PMHS, the scaling factor derived from body mass proved an overall good predictor of the peak timing for the shoulder belt (0.868, 0.829) and the lap belt (0.858, 0.774) and for the peak value of the lap belt force (0.796, 0.869). Scaled kinematics based on body stature provided fair or acceptable prediction on the overall head

  6. Real-time prediction of extreme ambient carbon monoxide concentrations due to vehicular exhaust emissions using univariate linear stochastic models

    International Nuclear Information System (INIS)

    Sharma, P.; Khare, M.

    2000-01-01

    Historical data of the time-series of carbon monoxide (CO) concentration was analysed using Box-Jenkins modelling approach. Univariate Linear Stochastic Models (ULSMs) were developed to examine the degree of prediction possible for situations where only a limited data set, restricted only to the past record of pollutant data are available. The developed models can be used to provide short-term, real-time forecast of extreme CO concentrations for an Air Quality Control Region (AQCR), comprising a major traffic intersection in a Central Business District of Delhi City, India. (author)

  7. Effect of sound stimulion reciprocal interaction of antagonist muscles of lowe extremities in humans under vestibular loadе

    Directory of Open Access Journals (Sweden)

    I. V. Dregval

    2015-05-01

    Full Text Available Results of the research are evidence of changing muscles reflex activity of human lower extremity under the influence of sound stimulus of various frequency range together with the vestibular burden. The most change of the H-reflex was observed under the sound stimulus of 800 hertz. Not only the proprioceptive but auditory sensory system takes part in the regulation of the brain reflex activity. Existence of different labyrinths actions, according to the situation, on the interneuronic inhibitory ways of the postsynaptic inhibition of the salens muscle’s motoneurons is supposed.

  8. Investigation of Load Prediction on the Mexico Rotor Using the Technique of Determination of the Angle of Attack

    DEFF Research Database (Denmark)

    Yang, Hua; Shen, Wen Zhong; Sørensen, Jens Nørkær

    2012-01-01

    Blade element moment (BEM) is a widely used technique for prediction of wind turbine aerodynamics performance, the reliability of airfoil data is an important factor to improve the prediction accuracy of aerodynamic loads and power using a BEM code. The method of determination of angle of attack ...

  9. Prediction of phosphorus loads in an artificially drained lowland catchment using a modified SWAT model

    Science.gov (United States)

    Bauwe, Andreas; Eckhardt, Kai-Uwe; Lennartz, Bernd

    2017-04-01

    Eutrophication is still one of the main environmental problems in the Baltic Sea. Currently, agricultural diffuse sources constitute the major portion of phosphorus (P) fluxes to the Baltic Sea and have to be reduced to achieve the HELCOM targets and improve the ecological status. Eco-hydrological models are suitable tools to identify sources of nutrients and possible measures aiming at reducing nutrient loads into surface waters. In this study, the Soil and Water Assessment Tool (SWAT) was applied to the Warnow river basin (3300 km2), the second largest watershed in Germany discharging into the Baltic Sea. The Warnow river basin is located in northeastern Germany and characterized by lowlands with a high proportion of artificially drained areas. The aim of this study were (i) to estimate P loadings for individual flow fractions (point sources, surface runoff, tile flow, groundwater flow), spatially distributed on sub-basin scale. Since the official version of SWAT does not allow for the modeling of P in tile drains, we tested (ii) two different approaches of simulating P in tile drains by changing the SWAT source code. The SWAT source code was modified so that (i) the soluble P concentration of the groundwater was transferred to the tile water and (ii) the soluble P in the soil was transferred to the tiles. The SWAT model was first calibrated (2002-2011) and validated (1992-2001) for stream flow at 7 headwater catchments at a daily time scale. Based on this, the stream flow at the outlet of the Warnow river basin was simulated. Performance statistics indicated at least satisfactory model results for each sub-basin. Breaking down the discharge into flow constituents, it becomes visible that stream flow is mainly governed by groundwater and tile flow. Due to the topographic situation with gentle slopes, surface runoff played only a minor role. Results further indicate that the prediction of soluble P loads was improved by the modified SWAT versions. Major sources of

  10. Difficult to predict early failure after major lower-extremity amputations

    DEFF Research Database (Denmark)

    Kristensen, Morten Tange; Holm, Gitte; Gebuhr, Peter

    2015-01-01

    INTRODUCTION: The successful outcome of a major amputation depends on several factors, including stump wound healing. The purpose of this study was to examine the criteria upon which the index amputation was based and to identify factors associated with early amputation failure after major non......-traumatic lower-extremity amputation. METHODS: We studied a consecutive one-year series of 36 men and 34 women with a median (25-75% quartiles) age of 72 (63-83) years who were treated in an acute orthopaedic ward; 44 below-knee and 26 above-knee amputees of whom 47 had an American Society of Anesthesiologists...... rating above two. Patient characteristics and other factors potentially influencing early amputation failure within 30 days were evaluated. RESULTS: Eleven patients died (16%) and 11 (16%) had a re-amputation at a higher level, whereas four (6%) had a major revision at the same level within 30 days...

  11. Quality prediction modeling for sintered ores based on mechanism models of sintering and extreme learning machine based error compensation

    Science.gov (United States)

    Tiebin, Wu; Yunlian, Liu; Xinjun, Li; Yi, Yu; Bin, Zhang

    2018-06-01

    Aiming at the difficulty in quality prediction of sintered ores, a hybrid prediction model is established based on mechanism models of sintering and time-weighted error compensation on the basis of the extreme learning machine (ELM). At first, mechanism models of drum index, total iron, and alkalinity are constructed according to the chemical reaction mechanism and conservation of matter in the sintering process. As the process is simplified in the mechanism models, these models are not able to describe high nonlinearity. Therefore, errors are inevitable. For this reason, the time-weighted ELM based error compensation model is established. Simulation results verify that the hybrid model has a high accuracy and can meet the requirement for industrial applications.

  12. Statistical Analysis of Wave Climate Data Using Mixed Distributions and Extreme Wave Prediction

    Directory of Open Access Journals (Sweden)

    Wei Li

    2016-05-01

    Full Text Available The investigation of various aspects of the wave climate at a wave energy test site is essential for the development of reliable and efficient wave energy conversion technology. This paper presents studies of the wave climate based on nine years of wave observations from the 2005–2013 period measured with a wave measurement buoy at the Lysekil wave energy test site located off the west coast of Sweden. A detailed analysis of the wave statistics is investigated to reveal the characteristics of the wave climate at this specific test site. The long-term extreme waves are estimated from applying the Peak over Threshold (POT method on the measured wave data. The significant wave height and the maximum wave height at the test site for different return periods are also compared. In this study, a new approach using a mixed-distribution model is proposed to describe the long-term behavior of the significant wave height and it shows an impressive goodness of fit to wave data from the test site. The mixed-distribution model is also applied to measured wave data from four other sites and it provides an illustration of the general applicability of the proposed model. The methodologies used in this paper can be applied to general wave climate analysis of wave energy test sites to estimate extreme waves for the survivability assessment of wave energy converters and characterize the long wave climate to forecast the wave energy resource of the test sites and the energy production of the wave energy converters.

  13. Generation and development of damage in double forged tungsten in different combined regimes of irradiation with extreme heat loads

    Science.gov (United States)

    Paju, Jana; Väli, Berit; Laas, Tõnu; Shirokova, Veroonika; Laas, Katrin; Paduch, Marian; Gribkov, Vladimir A.; Demina, Elena V.; Prusakova, Marina D.; Pimenov, Valeri N.; Makhlaj, Vadym A.; Antonov, Maksim

    2017-11-01

    Armour materials in fusion devices, especially in the region of divertor, are exposed to a continuous heat and particle load. In addition, several off-normal events can reach the material during a work session. Calculations show that the effects of plasma and heat during such events can lead to cracking, erosion and detachment of the armour material. On the other hand, mutual and combined influences of different kinds of heat and particle loads can lead to the amplification of defects or vice versa, to the mitigation of damages. Therefore, the purpose of the study is to investigate the plasma induced damages on samples of double forged tungsten, which is considered a potential candidate for armour material of future tokamak's divertor. The combined effect of different kinds of plasma induced damages was investigated and analysed in this research. The study was conducted by irradiating the samples in various irradiation regimes twice, to observe the accumulation of the damages. Afterwards the analysis of micro-topography, scanning electron microscopy images and electrical conductivity measurements was used. Results indicate that double-forging improved the tungsten's durability to irradiation. Nevertheless, powerful pulses lead to significant damage of the sample, which will lead to further deterioration in the bulk. Although the average micro-roughness on the sample's surface does not change, the overall height/depth ratios can change.

  14. Ultimate compression after impact load prediction in graphite/epoxy coupons using neural network and multivariate statistical analyses

    Science.gov (United States)

    Gregoire, Alexandre David

    2011-07-01

    The goal of this research was to accurately predict the ultimate compressive load of impact damaged graphite/epoxy coupons using a Kohonen self-organizing map (SOM) neural network and multivariate statistical regression analysis (MSRA). An optimized use of these data treatment tools allowed the generation of a simple, physically understandable equation that predicts the ultimate failure load of an impacted damaged coupon based uniquely on the acoustic emissions it emits at low proof loads. Acoustic emission (AE) data were collected using two 150 kHz resonant transducers which detected and recorded the AE activity given off during compression to failure of thirty-four impacted 24-ply bidirectional woven cloth laminate graphite/epoxy coupons. The AE quantification parameters duration, energy and amplitude for each AE hit were input to the Kohonen self-organizing map (SOM) neural network to accurately classify the material failure mechanisms present in the low proof load data. The number of failure mechanisms from the first 30% of the loading for twenty-four coupons were used to generate a linear prediction equation which yielded a worst case ultimate load prediction error of 16.17%, just outside of the +/-15% B-basis allowables, which was the goal for this research. Particular emphasis was placed upon the noise removal process which was largely responsible for the accuracy of the results.

  15. Predicting fractional bed load transport rates: Application of the Wilcock‐Crowe equations to a regulated gravel bed river

    Science.gov (United States)

    Gaeuman, David; Andrews, E.D.; Krause, Andreas; Smith, Wes

    2009-01-01

    Bed load samples from four locations in the Trinity River of northern California are analyzed to evaluate the performance of the Wilcock‐Crowe bed load transport equations for predicting fractional bed load transport rates. Bed surface particles become smaller and the fraction of sand on the bed increases with distance downstream from Lewiston Dam. The dimensionless reference shear stress for the mean bed particle size (τ*rm) is largest near the dam, but varies relatively little between the more downstream locations. The relation between τ*rm and the reference shear stresses for other size fractions is constant across all locations. Total bed load transport rates predicted with the Wilcock‐Crowe equations are within a factor of 2 of sampled transport rates for 68% of all samples. The Wilcock‐Crowe equations nonetheless consistently under‐predict the transport of particles larger than 128 mm, frequently by more than an order of magnitude. Accurate prediction of the transport rates of the largest particles is important for models in which the evolution of the surface grain size distribution determines subsequent bed load transport rates. Values of τ*rm estimated from bed load samples are up to 50% larger than those predicted with the Wilcock‐Crowe equations, and sampled bed load transport approximates equal mobility across a wider range of grain sizes than is implied by the equations. Modifications to the Wilcock‐Crowe equation for determining τ*rm and the hiding function used to scale τ*rm to other grain size fractions are proposed to achieve the best fit to observed bed load transport in the Trinity River.

  16. Application of Galerkin meshfree methods to nonlinear thermo-mechanical simulation of solids under extremely high pulsed loading

    International Nuclear Information System (INIS)

    Ibáñez, Daniel Iglesias; García Orden, Juan C.; Brañas, B.; Carmona, J.M.; Molla, J.

    2013-01-01

    Highlights: • The paper presents a novel application of meshfree methods, valid for its implementation on a multibody framework. • Coupled nonlinear thermo-mechanical formulation is detailed and described in the reference configuration, as this allows to compute the shape functions only once. • We show the conditions in which future information induces inefficiency. • Beam parameters are the only information needed to apply the thermal load. • The solution procedure takes charge of updating the volumetric heat rate as the body moves and deforms. -- Abstract: Beam facing elements of the International Fusion Materials Irradiation Facility (IFMIF) Linear Particle Accelerator prototype (LIPAc) must stop 5–40 MeV D + ions with a peak current of 125 mA. The duty cycle of the beam loading varies from 0.1% to 100% (CW), depending on the device, with the ions being stopped in the first hundreds microns of the beam facing material. For intermediate duty cycles up to CW, the thermal load can be considered a heat flux load on the boundary, but this approximation gets too conservative as the duty cycle is reduced because the thermal diffusion becomes more important. Instant heat flux produced by the beam can reach up to 3 GW/m 2 in elements such as the beam dump and slits during short times of hundredths of microseconds. In these cases, the accuracy of the volumetric heat generation is critical for obtaining realistic results. Meshfree Galerkin methods discretize a continuum using scattered nodes. As opposed to FEM, no predefined connectivity is needed between the nodes, so C ∞ (infinitely differentiable) locally supported shape functions can be used to approximate both the trial and the test functions. This feature makes these type of methods well suited for those problems where the domain experiences very large deformations or has high gradients of the state variables. Radial basis (RBF) and moving least squares (MLS) functions have been applied to the

  17. Jump landing characteristics predicts lower extremity injuries in indoor team sports

    NARCIS (Netherlands)

    van der Does, Hendrike; Brink, Michel; Benjaminse, Anne; Visscher, Chris; Lemmink, Koen

    2015-01-01

    The aim of this study is to investigate the predictive value of landing stability and technique to gain insight into risk factors for ankle and knee injuries in indoor team sport players. Seventyfive male and female basketball, volleyball or korfball players were screened by measuring landing

  18. Jump Landing Characteristics Predicts Lower Extremity Injuries in Indoor Team Sports

    NARCIS (Netherlands)

    van der Does, H. T. D.; Brink, M. S.; Benjaminse, A.; Visscher, C.; Lemmink, K. A. P. M.

    The aim of this study is to investigate the predictive value of landing stability and technique to gain insight into risk factors for ankle and knee injuries in indoor team sport players. Seventy-five male and female basketball, volleyball or korfball players were screened by measuring landing

  19. Comparison of genetic algorithm and imperialist competitive algorithms in predicting bed load transport in clean pipe.

    Science.gov (United States)

    Ebtehaj, Isa; Bonakdari, Hossein

    2014-01-01

    The existence of sediments in wastewater greatly affects the performance of the sewer and wastewater transmission systems. Increased sedimentation in wastewater collection systems causes problems such as reduced transmission capacity and early combined sewer overflow. The article reviews the performance of the genetic algorithm (GA) and imperialist competitive algorithm (ICA) in minimizing the target function (mean square error of observed and predicted Froude number). To study the impact of bed load transport parameters, using four non-dimensional groups, six different models have been presented. Moreover, the roulette wheel selection method is used to select the parents. The ICA with root mean square error (RMSE) = 0.007, mean absolute percentage error (MAPE) = 3.5% show better results than GA (RMSE = 0.007, MAPE = 5.6%) for the selected model. All six models return better results than the GA. Also, the results of these two algorithms were compared with multi-layer perceptron and existing equations.

  20. Regression models for predicting peak and continuous three-dimensional spinal loads during symmetric and asymmetric lifting tasks.

    Science.gov (United States)

    Fathallah, F A; Marras, W S; Parnianpour, M

    1999-09-01

    Most biomechanical assessments of spinal loading during industrial work have focused on estimating peak spinal compressive forces under static and sagittally symmetric conditions. The main objective of this study was to explore the potential of feasibly predicting three-dimensional (3D) spinal loading in industry from various combinations of trunk kinematics, kinetics, and subject-load characteristics. The study used spinal loading, predicted by a validated electromyography-assisted model, from 11 male participants who performed a series of symmetric and asymmetric lifts. Three classes of models were developed: (a) models using workplace, subject, and trunk motion parameters as independent variables (kinematic models); (b) models using workplace, subject, and measured moments variables (kinetic models); and (c) models incorporating workplace, subject, trunk motion, and measured moments variables (combined models). The results showed that peak 3D spinal loading during symmetric and asymmetric lifting were predicted equally well using all three types of regression models. Continuous 3D loading was predicted best using the combined models. When the use of such models is infeasible, the kinematic models can provide adequate predictions. Finally, lateral shear forces (peak and continuous) were consistently underestimated using all three types of models. The study demonstrated the feasibility of predicting 3D loads on the spine under specific symmetric and asymmetric lifting tasks without the need for collecting EMG information. However, further validation and development of the models should be conducted to assess and extend their applicability to lifting conditions other than those presented in this study. Actual or potential applications of this research include exposure assessment in epidemiological studies, ergonomic intervention, and laboratory task assessment.

  1. Predicting Clinical Outcomes and Lost Work in Patients with Work-Related Upper Extremity Disorders

    Science.gov (United States)

    1998-02-13

    a double-sided message which can promote 24 somatization and exaggerated "pain behavior" which is then often interpreted as evidence ofrnalingering...specific psychiatric populations this may have some value (e.g... hypochondriasis , somati7ation disorder), it may not be an appropriate indicator for...subscale specificaDy measuring somatic complaintc;.was not significantly predictive ofsubjective report ofback injury. In addition, studies ofworkers with

  2. Toward Improving Predictability of Extreme Hydrometeorological Events: the Use of Multi-scale Climate Modeling in the Northern High Plains

    Science.gov (United States)

    Munoz-Arriola, F.; Torres-Alavez, J.; Mohamad Abadi, A.; Walko, R. L.

    2014-12-01

    Our goal is to investigate possible sources of predictability of hydrometeorological extreme events in the Northern High Plains. Hydrometeorological extreme events are considered the most costly natural phenomena. Water deficits and surpluses highlight how the water-climate interdependence becomes crucial in areas where single activities drive economies such as Agriculture in the NHP. Nonetheless we recognize the Water-Climate interdependence and the regulatory role that human activities play, we still grapple to identify what sources of predictability could be added to flood and drought forecasts. To identify the benefit of multi-scale climate modeling and the role of initial conditions on flood and drought predictability on the NHP, we use the Ocean Land Atmospheric Model (OLAM). OLAM is characterized by a dynamic core with a global geodesic grid with hexagonal (and variably refined) mesh cells and a finite volume discretization of the full compressible Navier Stokes equations, a cut-grid cell method for topography (that reduces error in computational gradient computation and anomalous vertical dispersion). Our hypothesis is that wet conditions will drive OLAM's simulations of precipitation to wetter conditions affecting both flood forecast and drought forecast. To test this hypothesis we simulate precipitation during identified historical flood events followed by drought events in the NHP (i.e. 2011-2012 years). We initialized OLAM with CFS-data 1-10 days previous to a flooding event (as initial conditions) to explore (1) short-term and high-resolution and (2) long-term and coarse-resolution simulations of flood and drought events, respectively. While floods are assessed during a maximum of 15-days refined-mesh simulations, drought is evaluated during the following 15 months. Simulated precipitation will be compared with the Sub-continental Observation Dataset, a gridded 1/16th degree resolution data obtained from climatological stations in Canada, US, and

  3. Prediction of pavement remaining service life based on repetition of load and permanent deformation

    Science.gov (United States)

    Usman, R. S.; Setyawan, A.; Suprapto, M.

    2018-03-01

    One of the methods which was applied in the assessment of flexible pavement performance was mechanistic method assuming structures of road pavement to become multi-layer structure for flexible pavement, that the vehicle load working on the pavement layer under repetition with power failure worth 1 (one) unit which was assumed as evenly distributed static load, and therefore the pavement material would provide response in the form of stress, strain, and deflection. This is closely related in order to assess the structure of flexible pavement and to predict the remaining service life on the roads of Pulau Indah sta 0 + 000 to sta. 0 + 845 in Kota Kupang, Nusa Tenggara Timur. The performance appraisal indicator which was used was fatigue cracking happening bottom of the asphalt layer and permanent deformation (rutting) on the surface of subgrade. The strain estimate on the flexible pavement layer structure needs carefulness and high accuracy and therefore a software like KENPAVE which produces horizontal tensile strain of 8,802E-05 and vertical compressive strain of 2,642E-04 was used. By applying equation of The Asphalt Instituteit was obtained repetition of permit load when reaching fatigue cracking (Nf) was 16.071.516 ESAL and permanent deformation (rutting) was 14.703.867 ESAL and also it was predicted the remaining service life of pavement applied the equation of AASTHO 1993 by considering Traffic Multiplier factor (TM 1.8, TM 1.9 and TM 2.0) obtained the remaining life service due to fatigue of 5.51% in the year of 13th (TM 1.8), 7.95% in the year of12th (TM 1.9) and 3.11% (TM 2.0) in the year of 12th, also the remaining service life due to rutting of 4.69% in the year of 12th(TM 1.8), 7.79% in the year of 11th (TM 1.9), and 2.94 in the year of 11th (TM 2.0).

  4. Using Blood Indexes to Predict Overweight Statuses: An Extreme Learning Machine-Based Approach.

    Directory of Open Access Journals (Sweden)

    Huiling Chen

    Full Text Available The number of the overweight people continues to rise across the world. Studies have shown that being overweight can increase health risks, such as high blood pressure, diabetes mellitus, coronary heart disease, and certain forms of cancer. Therefore, identifying the overweight status in people is critical to prevent and decrease health risks. This study explores a new technique that uses blood and biochemical measurements to recognize the overweight condition. A new machine learning technique, an extreme learning machine, was developed to accurately detect the overweight status from a pool of 225 overweight and 251 healthy subjects. The group included 179 males and 297 females. The detection method was rigorously evaluated against the real-life dataset for accuracy, sensitivity, specificity, and AUC (area under the receiver operating characteristic (ROC curve criterion. Additionally, the feature selection was investigated to identify correlating factors for the overweight status. The results demonstrate that there are significant differences in blood and biochemical indexes between healthy and overweight people (p-value < 0.01. According to the feature selection, the most important correlated indexes are creatinine, hemoglobin, hematokrit, uric Acid, red blood cells, high density lipoprotein, alanine transaminase, triglyceride, and γ-glutamyl transpeptidase. These are consistent with the results of Spearman test analysis. The proposed method holds promise as a new, accurate method for identifying the overweight status in subjects.

  5. Assessing the suitability of extreme learning machines (ELM for groundwater level prediction

    Directory of Open Access Journals (Sweden)

    Yadav Basant

    2017-03-01

    Full Text Available Fluctuation of groundwater levels around the world is an important theme in hydrological research. Rising water demand, faulty irrigation practices, mismanagement of soil and uncontrolled exploitation of aquifers are some of the reasons why groundwater levels are fluctuating. In order to effectively manage groundwater resources, it is important to have accurate readings and forecasts of groundwater levels. Due to the uncertain and complex nature of groundwater systems, the development of soft computing techniques (data-driven models in the field of hydrology has significant potential. This study employs two soft computing techniques, namely, extreme learning machine (ELM and support vector machine (SVM to forecast groundwater levels at two observation wells located in Canada. A monthly data set of eight years from 2006 to 2014 consisting of both hydrological and meteorological parameters (rainfall, temperature, evapotranspiration and groundwater level was used for the comparative study of the models. These variables were used in various combinations for univariate and multivariate analysis of the models. The study demonstrates that the proposed ELM model has better forecasting ability compared to the SVM model for monthly groundwater level forecasting.

  6. Predictive characterization of aging and degradation of reactor materials in extreme environments. Final report, December 20, 2013 - September 20, 2017

    Energy Technology Data Exchange (ETDEWEB)

    Qu, Jianmin [Northwestern Univ., Evanston, IL (United States)

    2017-09-20

    Understanding of reactor material behavior in extreme environments is vital not only to the development of new materials for the next generation nuclear reactors, but also to the extension of the operating lifetimes of the current fleet of nuclear reactors. To this end, this project conducted a suite of unique experimental techniques, augmented by a mesoscale computational framework, to understand and predict the long-term effects of irradiation, temperature, and stress on material microstructures and their macroscopic behavior. The experimental techniques and computational tools were demonstrated on two distinctive types of reactor materials, namely, Zr alloys and high-Cr martensitic steels. These materials are chosen as the test beds because they are the archetypes of high-performance reactor materials (cladding, wrappers, ducts, pressure vessel, piping, etc.). To fill the knowledge gaps, and to meet the technology needs, a suite of innovative in situ transmission electron microscopy (TEM) characterization techniques (heating, heavy ion irradiation, He implantation, quantitative small-scale mechanical testing, and various combinations thereof) were developed and used to elucidate and map the fundamental mechanisms of microstructure evolution in both Zr and Cr alloys for a wide range environmental boundary conditions in the thermal-mechanical-irradiation input space. Knowledge gained from the experimental observations of the active mechanisms and the role of local microstructural defects on the response of the material has been incorporated into a mathematically rigorous and comprehensive three-dimensional mesoscale framework capable of accounting for the compositional variation, microstructural evolution and localized deformation (radiation damage) to predict aging and degradation of key reactor materials operating in extreme environments. Predictions from this mesoscale framework were compared with the in situ TEM observations to validate the model.

  7. Predictive characterization of aging and degradation of reactor materials in extreme environments. Final report, December 20, 2013 - September 20, 2017

    International Nuclear Information System (INIS)

    Qu, Jianmin

    2017-01-01

    Understanding of reactor material behavior in extreme environments is vital not only to the development of new materials for the next generation nuclear reactors, but also to the extension of the operating lifetimes of the current fleet of nuclear reactors. To this end, this project conducted a suite of unique experimental techniques, augmented by a mesoscale computational framework, to understand and predict the long-term effects of irradiation, temperature, and stress on material microstructures and their macroscopic behavior. The experimental techniques and computational tools were demonstrated on two distinctive types of reactor materials, namely, Zr alloys and high-Cr martensitic steels. These materials are chosen as the test beds because they are the archetypes of high-performance reactor materials (cladding, wrappers, ducts, pressure vessel, piping, etc.). To fill the knowledge gaps, and to meet the technology needs, a suite of innovative in situ transmission electron microscopy (TEM) characterization techniques (heating, heavy ion irradiation, He implantation, quantitative small-scale mechanical testing, and various combinations thereof) were developed and used to elucidate and map the fundamental mechanisms of microstructure evolution in both Zr and Cr alloys for a wide range environmental boundary conditions in the thermal-mechanical-irradiation input space. Knowledge gained from the experimental observations of the active mechanisms and the role of local microstructural defects on the response of the material has been incorporated into a mathematically rigorous and comprehensive three-dimensional mesoscale framework capable of accounting for the compositional variation, microstructural evolution and localized deformation (radiation damage) to predict aging and degradation of key reactor materials operating in extreme environments. Predictions from this mesoscale framework were compared with the in situ TEM observations to validate the model.

  8. Prediction of delayed neurological deficit after subarachnoid haemorrhage: a CT blood load and Doppler velocity approach

    International Nuclear Information System (INIS)

    Grosset, D.G.; McDonald, I.; Cockburn, M.; Straiton, J.; Bullock, R.R.

    1994-01-01

    The predictive value of cranial computed tomography (CT) blood load and serial transcranial Doppler sonography for the development of delayed ischaemic neurological deficit was assessed in 121 patients following subarachnoid haemorrhage. Of the 121 patients, 81 (67 %) had thick layers of blood or haematoma, including intraventricular bleeding. The proportion of patients who developed delayed deficit was higher with increasing amounts of subarachnoid blood on the admission CT (51 % of 53 cases in Fisher grade 3; 35 % of 33 cases in grade 2; 28 % of 7 cases in grade 1, P < 0.01). Doppler velocities obtained from readings at least every 2 days following admission were higher in patients with delayed neurological deficit (peak velocity for grade 3 patients 176 ± 6 cm/s (mean ± SE), versus grade 2: 164 ± 7 cm/s; grade 4 149 ± 9, both P = 0.04, Mann-Whitney). Peak velocity and maximal 24-h rise tended to be higher within different CT grades in patients with a deficit than in those without; this difference was significant for grade 3 patients (P < 0.01). We conclude that a combined approach with CT and Doppler sonography provides greater predictive value for the development of delayed ischaemic neurological deficit than either test considered independently. The value of Doppler sonography may be greatest for patients with Fisher grade 3 blood, in whom the risk of delayed ischaemia is greatest. (orig.)

  9. Performance of synchrotron x-ray monochromators under heat load: How reliable are the predictions?

    International Nuclear Information System (INIS)

    Freund, A.K.; Hoszowska, J.; Migliore, J.-S.; Mocella, V.; Zhang, L.; Ferrero, C.

    2000-01-01

    With the ongoing development of insertion devices with smaller gaps the heat load generated by modern synchrotron sources increases continuously. To predict the overall performance of experiments on beam lines it is of crucial importance to be able to predict the efficiency of x-ray optics and in particular that of crystal monochromators. We report on a detailed comparison between theory and experiment for a water-cooled silicon crystal exposed to bending magnet radiation of up to 237 W total power and 1.3 W/mm2 power density. The thermal deformation has been calculated by the code ANSYS and its output has been injected into a finite difference code based on the Takagi-Taupin diffraction theory for distorted crystals. Several slit settings, filters and reflection orders were used to vary the geometrical conditions and the x-ray penetration depth in the crystal. In general, good agreement has been observed between the calculated and the observed values for the rocking curve width

  10. Research on dynamic creep strain and settlement prediction under the subway vibration loading.

    Science.gov (United States)

    Luo, Junhui; Miao, Linchang

    2016-01-01

    This research aims to explore the dynamic characteristics and settlement prediction of soft soil. Accordingly, the dynamic shear modulus formula considering the vibration frequency was utilized and the dynamic triaxial test conducted to verify the validity of the formula. Subsequently, the formula was applied to the dynamic creep strain function, with the factors influencing the improved dynamic creep strain curve of soft soil being analyzed. Meanwhile, the variation law of dynamic stress with sampling depth was obtained through the finite element simulation of subway foundation. Furthermore, the improved dynamic creep strain curve of soil layer was determined based on the dynamic stress. Thereafter, it could to estimate the long-term settlement under subway vibration loading by norms. The results revealed that the dynamic shear modulus formula is straightforward and practical in terms of its application to the vibration frequency. The values predicted using the improved dynamic creep strain formula closed to the experimental values, whilst the estimating settlement closed to the measured values obtained in the field test.

  11. Early-Onset Invasive Candidiasis in Extremely Low Birth Weight Infants: Perinatal Acquisition Predicts Poor Outcome.

    Science.gov (United States)

    Barton, Michelle; Shen, Alex; O'Brien, Karel; Robinson, Joan L; Davies, H Dele; Simpson, Kim; Asztalos, Elizabeth; Langley, Joanne; Le Saux, Nicole; Sauve, Reginald; Synnes, Anne; Tan, Ben; de Repentigny, Louis; Rubin, Earl; Hui, Chuck; Kovacs, Lajos; Yau, Yvonne C W; Richardson, Susan E

    2017-04-01

    Neonatal invasive candidiasis (IC) presenting in the first week of life is less common and less well described than later-onset IC. Risk factors, clinical features, and disease outcomes have not been studied in early-onset disease (EOD, ≤7 days) or compared to late-onset disease (LOD, >7 days). All extremely low birth weight (ELBW, candidiasis enrolled from 2001 to 2003 were included in this study. Factors associated with occurrence and outcome of EOD in ELBW infants were determined. Forty-five ELBW infants and their 84 matched controls were included. Fourteen (31%) ELBW infants had EOD. Birth weight <750 g, gestation <25 weeks, chorioamnionitis, and vaginal delivery were all strongly associated with EOD. Infection with Candida albicans, disseminated disease, pneumonia, and cardiovascular disease were significantly more common in EOD than in LOD. The EOD case fatality rate (71%) was higher than in LOD (32%) or controls (15%) (P = .0001). The rate of neurodevelopmental impairment and mortality combined was similar in EOD (86%) and LOD (72%), but higher than in controls (32%; P = .007). ELBW infants with EOD have a very poor prognosis compared to those with LOD. The role of perinatal transmission in EOD is supported by its association with chorioamnionitis, vaginal delivery, and pneumonia. Dissemination and cardiovascular involvement are common, and affected infants often die. Empiric treatment should be considered for ELBW infants delivered vaginally who have pneumonia and whose mothers have chorioamnionitis or an intrauterine foreign body. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

  12. Removal of volatile organic compounds at extreme shock-loading using a scaled-up pilot rotating drum biofilter.

    Science.gov (United States)

    Sawvel, Russell A; Kim, Byung; Alvarez, Pedro J J

    2008-11-01

    A pilot-scale rotating drum biofilter (RDB), which is a novel biofilter design that offers flexible flow-through configurations, was used to treat complex and variable volatile organic compound (VOC) emissions, including shock loadings, emanating from paint drying operations at an Army ammunition plant. The RDB was seeded with municipal wastewater activated sludge. Removal efficiencies up to 86% and an elimination capacity of 5.3 g chemical oxygen demand (COD) m(-3) hr(-1) were achieved at a filter-medium contact time of 60 sec. Efficiency increased at higher temperatures that promote higher biological activity, and decreased at lower pH, which dropped down to pH 5.5 possibly as a result of carbon dioxide and volatile fatty acid production and ammonia consumption during VOC degradation. In comparison, other studies have shown that a bench-scale RDB could achieve a removal efficiency of 95% and elimination capacity of 331 g COD m(-3) hr(-1). Sustainable performance of the pilot-scale RDB was challenged by the intermittent nature of painting operations, which typically resulted in 3-day long shutdown periods when bacteria were not fed. This challenge was overcome by adding sucrose (2 g/L weekly) as an auxiliary substrate to sustain metabolic activity during shutdown periods.

  13. A novel prediction approach for antimalarial activities of Trimethoprim, Pyrimethamine, and Cycloguanil analogues using extremely randomized trees.

    Science.gov (United States)

    Nattee, Cholwich; Khamsemanan, Nirattaya; Lawtrakul, Luckhana; Toochinda, Pisanu; Hannongbua, Supa

    2017-01-01

    Malaria is still one of the most serious diseases in tropical regions. This is due in part to the high resistance against available drugs for the inhibition of parasites, Plasmodium, the cause of the disease. New potent compounds with high clinical utility are urgently needed. In this work, we created a novel model using a regression tree to study structure-activity relationships and predict the inhibition constant, K i of three different antimalarial analogues (Trimethoprim, Pyrimethamine, and Cycloguanil) based on their molecular descriptors. To the best of our knowledge, this work is the first attempt to study the structure-activity relationships of all three analogues combined. The most relevant descriptors and appropriate parameters of the regression tree are harvested using extremely randomized trees. These descriptors are water accessible surface area, Log of the aqueous solubility, total hydrophobic van der Waals surface area, and molecular refractivity. Out of all possible combinations of these selected parameters and descriptors, the tree with the strongest coefficient of determination is selected to be our prediction model. Predicted K i values from the proposed model show a strong coefficient of determination, R 2 =0.996, to experimental K i values. From the structure of the regression tree, compounds with high accessible surface area of all hydrophobic atoms (ASA_H) and low aqueous solubility of inhibitors (Log S) generally possess low K i values. Our prediction model can also be utilized as a screening test for new antimalarial drug compounds which may reduce the time and expenses for new drug development. New compounds with high predicted K i should be excluded from further drug development. It is also our inference that a threshold of ASA_H greater than 575.80 and Log S less than or equal to -4.36 is a sufficient condition for a new compound to possess a low K i . Copyright © 2016 Elsevier Inc. All rights reserved.

  14. A prediction model for treatment decisions in high-grade extremity soft-tissue sarcomas: Personalised sarcoma care (PERSARC).

    Science.gov (United States)

    van Praag, Veroniek M; Rueten-Budde, Anja J; Jeys, Lee M; Laitinen, Minna K; Pollock, Rob; Aston, Will; van der Hage, Jos A; Dijkstra, P D Sander; Ferguson, Peter C; Griffin, Anthony M; Willeumier, Julie J; Wunder, Jay S; van de Sande, Michiel A J; Fiocco, Marta

    2017-09-01

    To support shared decision-making, we developed the first prediction model for patients with primary soft-tissue sarcomas of the extremities (ESTS) which takes into account treatment modalities, including applied radiotherapy (RT) and achieved surgical margins. The PERsonalised SARcoma Care (PERSARC) model, predicts overall survival (OS) and the probability of local recurrence (LR) at 3, 5 and 10 years. Development and validation, by internal validation, of the PERSARC prediction model. The cohort used to develop the model consists of 766 ESTS patients who underwent surgery, between 2000 and 2014, at five specialised international sarcoma centres. To assess the effect of prognostic factors on OS and on the cumulative incidence of LR (CILR), a multivariate Cox proportional hazard regression and the Fine and Gray model were estimated. Predictive performance was investigated by using internal cross validation (CV) and calibration. The discriminative ability of the model was determined with the C-index. Multivariate Cox regression revealed that age and tumour size had a significant effect on OS. More importantly, patients who received RT showed better outcomes, in terms of OS and CILR, than those treated with surgery alone. Internal validation of the model showed good calibration and discrimination, with a C-index of 0.677 and 0.696 for OS and CILR, respectively. The PERSARC model is the first to incorporate known clinical risk factors with the use of different treatments and surgical outcome measures. The developed model is internally validated to provide a reliable prediction of post-operative OS and CILR for patients with primary high-grade ESTS. LEVEL OF SIGNIFICANCE: level III. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Data-Driven Machine-Learning Model in District Heating System for Heat Load Prediction: A Comparison Study

    Directory of Open Access Journals (Sweden)

    Fisnik Dalipi

    2016-01-01

    Full Text Available We present our data-driven supervised machine-learning (ML model to predict heat load for buildings in a district heating system (DHS. Even though ML has been used as an approach to heat load prediction in literature, it is hard to select an approach that will qualify as a solution for our case as existing solutions are quite problem specific. For that reason, we compared and evaluated three ML algorithms within a framework on operational data from a DH system in order to generate the required prediction model. The algorithms examined are Support Vector Regression (SVR, Partial Least Square (PLS, and random forest (RF. We use the data collected from buildings at several locations for a period of 29 weeks. Concerning the accuracy of predicting the heat load, we evaluate the performance of the proposed algorithms using mean absolute error (MAE, mean absolute percentage error (MAPE, and correlation coefficient. In order to determine which algorithm had the best accuracy, we conducted performance comparison among these ML algorithms. The comparison of the algorithms indicates that, for DH heat load prediction, SVR method presented in this paper is the most efficient one out of the three also compared to other methods found in the literature.

  16. Jump Landing Characteristics Predict Lower Extremity Injuries in Indoor Team Sports.

    Science.gov (United States)

    van der Does, H T D; Brink, M S; Benjaminse, A; Visscher, C; Lemmink, K A P M

    2016-03-01

    The aim of this study is to investigate the predictive value of landing stability and technique to gain insight into risk factors for ankle and knee injuries in indoor team sport players. Seventy-five male and female basketball, volleyball or korfball players were screened by measuring landing stability after a single-leg jump landing and landing technique during a repeated counter movement jump by detailed 3-dimensional kinematics and kinetics. During the season 11 acute ankle injuries were reported along with 6 acute and 7 overuse knee injuries by the teams' physical therapist. Logistic regression analysis showed less landing stability in the forward and diagonal jump direction (OR 1.01-1.10, p≤0.05) in players who sustained an acute ankle injury. Furthermore landing technique with a greater ankle dorsiflexion moment increased the risk for acute ankle injury (OR 2.16, p≤0.05). A smaller knee flexion moment and greater vertical ground reaction force increased the risk of an overuse knee injury (OR 0.29 and 1.13 respectively, p≤0.05). Less one-legged landing stability and suboptimal landing technique were shown in players sustaining an acute ankle and overuse knee injury compared to healthy players. Determining both landing stability and technique may further guide injury prevention programs. © Georg Thieme Verlag KG Stuttgart · New York.

  17. Prediction of crack density and electrical resistance changes in indium tin oxide/polymer thin films under tensile loading

    KAUST Repository

    Mora Cordova, Angel

    2014-06-11

    We present unified predictions for the crack onset strain, evolution of crack density, and changes in electrical resistance in indium tin oxide/polymer thin films under tensile loading. We propose a damage mechanics model to quantify and predict such changes as an alternative to fracture mechanics formulations. Our predictions are obtained by assuming that there are no flaws at the onset of loading as opposed to the assumptions of fracture mechanics approaches. We calibrate the crack onset strain and the damage model based on experimental data reported in the literature. We predict crack density and changes in electrical resistance as a function of the damage induced in the films. We implement our model in the commercial finite element software ABAQUS using a user subroutine UMAT. We obtain fair to good agreement with experiments. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  18. Predicting hourly cooling load in the building: A comparison of support vector machine and different artificial neural networks

    International Nuclear Information System (INIS)

    Li Qiong; Meng Qinglin; Cai Jiejin; Yoshino, Hiroshi; Mochida, Akashi

    2009-01-01

    This study presents four modeling techniques for the prediction of hourly cooling load in the building. In addition to the traditional back propagation neural network (BPNN), the radial basis function neural network (RBFNN), general regression neural network (GRNN) and support vector machine (SVM) are considered. All the prediction models have been applied to an office building in Guangzhou, China. Evaluation of the prediction accuracy of the four models is based on the root mean square error (RMSE) and mean relative error (MRE). The simulation results demonstrate that the four discussed models can be effective for building cooling load prediction. The SVM and GRNN methods can achieve better accuracy and generalization than the BPNN and RBFNN methods

  19. Predicting Statistical Response and Extreme Events in Uncertainty Quantification through Reduced-Order Models

    Science.gov (United States)

    Qi, D.; Majda, A.

    2017-12-01

    A low-dimensional reduced-order statistical closure model is developed for quantifying the uncertainty in statistical sensitivity and intermittency in principal model directions with largest variability in high-dimensional turbulent system and turbulent transport models. Imperfect model sensitivity is improved through a recent mathematical strategy for calibrating model errors in a training phase, where information theory and linear statistical response theory are combined in a systematic fashion to achieve the optimal model performance. The idea in the reduced-order method is from a self-consistent mathematical framework for general systems with quadratic nonlinearity, where crucial high-order statistics are approximated by a systematic model calibration procedure. Model efficiency is improved through additional damping and noise corrections to replace the expensive energy-conserving nonlinear interactions. Model errors due to the imperfect nonlinear approximation are corrected by tuning the model parameters using linear response theory with an information metric in a training phase before prediction. A statistical energy principle is adopted to introduce a global scaling factor in characterizing the higher-order moments in a consistent way to improve model sensitivity. Stringent models of barotropic and baroclinic turbulence are used to display the feasibility of the reduced-order methods. Principal statistical responses in mean and variance can be captured by the reduced-order models with accuracy and efficiency. Besides, the reduced-order models are also used to capture crucial passive tracer field that is advected by the baroclinic turbulent flow. It is demonstrated that crucial principal statistical quantities like the tracer spectrum and fat-tails in the tracer probability density functions in the most important large scales can be captured efficiently with accuracy using the reduced-order tracer model in various dynamical regimes of the flow field with

  20. A new simulation method for turbines in wake - Applied to extreme response during operation

    DEFF Research Database (Denmark)

    Thomsen, K.; Aagaard Madsen, H.

    2005-01-01

    The work focuses on prediction of load response for wind turbines operating in wind forms using a newly developed aeroelostic simulation method The traditionally used concept is to adjust the free flow turbulence intensity to account for increased loads in wind farms-a methodology that might......, the resulting extremes might be erroneous. For blade loads the traditionally used simplified approach works better than for integrated rotor loads-where the instantaneous load gradient across the rotor disc is causing the extreme loads. In the article the new wake simulation approach is illustrated...

  1. Using Haines Index coupled with fire weather model predicted from high resolution LAM forecasts to asses wildfire extreme behaviour in Southern Europe.

    Science.gov (United States)

    Gaetani, Francesco; Baptiste Filippi, Jean; Simeoni, Albert; D'Andrea, Mirko

    2010-05-01

    Haines Index (HI) was developed by USDA Forest Service to measure the atmosphere's contribution to the growth potential of a wildfire. The Haines Index combines two atmospheric factors that are known to have an effect on wildfires: Stability and Dryness. As operational tools, HI proved its ability to predict plume dominated high intensity wildfires. However, since HI does not take into account the fuel continuity, composition and moisture conditions and the effects of wind and topography on fire behaviour, its use as forecasting tool should be carefully considered. In this work we propose the use of HI, predicted from HR Limited Area Model forecasts, coupled with a Fire Weather model (i.e., RISICO system) fully operational in Italy since 2003. RISICO is based on dynamic models able to represent in space and in time the effects that environment and vegetal physiology have on fuels and, in turn, on the potential behaviour of wildfires. The system automatically acquires from remote databases a thorough data-set of input information both of in situ and spatial nature. Meteorological observations, radar data, Limited Area Model weather forecasts, EO data, and fuel data are managed by a Unified Interface able to process a wide set of different data. Specific semi-physical models are used in the system to simulate the dynamics of the fuels (load and moisture contents of dead and live fuel) and the potential fire behaviour (rate of spread and linear intensity). A preliminary validation of this approach will be provided with reference to Sardinia and Corsica Islands, two major islands of the Mediterranean See frequently affected by extreme plume dominated wildfires. A time series of about 3000 wildfires burnt in Sardinia and Corsica in 2007 and 2008 will be used to evaluate the capability of HI coupled with the outputs of the Fire Weather model to forecast the actual risk in time and in space.

  2. Computational methods using weighed-extreme learning machine to predict protein self-interactions with protein evolutionary information.

    Science.gov (United States)

    An, Ji-Yong; Zhang, Lei; Zhou, Yong; Zhao, Yu-Jun; Wang, Da-Fu

    2017-08-18

    Self-interactions Proteins (SIPs) is important for their biological activity owing to the inherent interaction amongst their secondary structures or domains. However, due to the limitations of experimental Self-interactions detection, one major challenge in the study of prediction SIPs is how to exploit computational approaches for SIPs detection based on evolutionary information contained protein sequence. In the work, we presented a novel computational approach named WELM-LAG, which combined the Weighed-Extreme Learning Machine (WELM) classifier with Local Average Group (LAG) to predict SIPs based on protein sequence. The major improvement of our method lies in presenting an effective feature extraction method used to represent candidate Self-interactions proteins by exploring the evolutionary information embedded in PSI-BLAST-constructed position specific scoring matrix (PSSM); and then employing a reliable and robust WELM classifier to carry out classification. In addition, the Principal Component Analysis (PCA) approach is used to reduce the impact of noise. The WELM-LAG method gave very high average accuracies of 92.94 and 96.74% on yeast and human datasets, respectively. Meanwhile, we compared it with the state-of-the-art support vector machine (SVM) classifier and other existing methods on human and yeast datasets, respectively. Comparative results indicated that our approach is very promising and may provide a cost-effective alternative for predicting SIPs. In addition, we developed a freely available web server called WELM-LAG-SIPs to predict SIPs. The web server is available at http://219.219.62.123:8888/WELMLAG/ .

  3. Lesion load may predict long-term cognitive dysfunction in multiple sclerosis patients.

    Directory of Open Access Journals (Sweden)

    Francesco Patti

    Full Text Available Magnetic Resonance Imaging (MRI techniques provided evidences into the understanding of cognitive impairment (CIm in Multiple Sclerosis (MS.To investigate the role of white matter (WM and gray matter (GM in predicting long-term CIm in a cohort of MS patients.303 out of 597 patients participating in a previous multicenter clinical-MRI study were enrolled (49.4% were lost at follow-up. The following MRI parameters, expressed as fraction (f of intracranial volume, were evaluated: cerebrospinal fluid (CSF-f, WM-f, GM-f and abnormal WM (AWM-f, a measure of lesion load. Nine years later, cognitive status was assessed in 241 patients using the Symbol Digit Modalities Test (SDMT, the Semantically Related Word List Test (SRWL, the Modified Card Sorting Test (MCST, and the Paced Auditory Serial Addition Test (PASAT. In particular, being SRWL a memory test, both immediate recall and delayed recall were evaluated. MCST scoring was calculated based on the number of categories, number of perseverative and non-perseverative errors.AWM-f was predictive of an impaired performance 9 years ahead in SDMT (OR 1.49, CI 1.12-1.97 p = 0.006, PASAT (OR 1.43, CI 1.14-1.80 p = 0.002, SRWL-immediate recall (OR 1.72 CI 1.35-2.20 p<0.001, SRWL-delayed recall (OR 1.61 CI 1.28-2.03 p<0.001, MCST-category (OR 1.52, CI 1.2-1.9 p<0.001, MCST-perseverative error(OR 1.51 CI 1.2-1.9 p = 0.001, MCST-non perseverative error (OR 1.26 CI 1.02-1.55 p = 0.032.In our large MS cohort, focal WM damage appeared to be the most relevant predictor of the long-term cognitive outcome.

  4. Model-Based Load Estimation for Predictive Condition Monitoring of Wind Turbines

    DEFF Research Database (Denmark)

    Perisic, Nevena; Pederen, Bo Juul; Grunnet, Jacob Deleuran

    signal is performed online, and a Load Indicator Signal (LIS) is formulated as a ratio between current estimated accumulated fatigue loads and its expected value based only on a priori knowledge (WTG dynamics and wind climate). LOT initialisation is based on a priori knowledge and can be obtained using...... programme for pre-maintenance actions. The performance of LOT is demonstrated by applying it to one of the most critical WTG components, the gearbox. Model-based load CMS for gearbox requires only standard WTG SCADA data. Direct measuring of gearbox fatigue loads requires high cost and low reliability...... measurement equipment. Thus, LOT can significantly reduce the price of load monitoring....

  5. Analytical capability for predicting structural response of NPP concrete containments to severe loads

    International Nuclear Information System (INIS)

    Planas, J.; Guinea, G.; Trbojevic, V.M.; Marti, J.; Martinez, F.; Cortes, P.

    1989-12-01

    A survey has been conducted on the state-of-the-art of analytical techniques for predicting the structural response of concrete containment buildings under severe accident conditions. The validity of inelastic analysis is often limited by the inadequacy of the material models adopted. This is specially true in the case of materials which undergo localization phenomena in the course of the deformation process. Because of this, the Joint Research Centre at Ispra has given a high priority to the review of existing constitutive models for concrete. Such models must be able to describe concrete behaviour with and without steel reinforcement across the complete stress range, from initial elastic behaviour to and beyond the point of failure. For reinforced and prestressed concrete, segregated models (where concrete and steel are independently simulated) are preferred. A review of existing constitutive models for mass concrete has been conducted. The review focused on necessary features for describing the near-peak and post-peak stages of deformation. Special attention was dedicated to the localization of strains in tension and the post-peak softening behaviour. Existing models for representing the concrete steel bond were also reviewed. These models are still relatively simplistic and incorporate seldom a number of effects of considerable importance: sustained, dynamic and cyclic loading, environmental effects, etc. Finally, the computational procedures currently available for modelling problems involving the ultimate capacity of concrete containments have also been reviewed. This includes methodologies for modelling amongst other mass concrete, cracking procedures, bond behaviour, in existing computer codes

  6. Recombination in diverse maize is stable, predictable, and associated with genetic load.

    Science.gov (United States)

    Rodgers-Melnick, Eli; Bradbury, Peter J; Elshire, Robert J; Glaubitz, Jeffrey C; Acharya, Charlotte B; Mitchell, Sharon E; Li, Chunhui; Li, Yongxiang; Buckler, Edward S

    2015-03-24

    Among the fundamental evolutionary forces, recombination arguably has the largest impact on the practical work of plant breeders. Varying over 1,000-fold across the maize genome, the local meiotic recombination rate limits the resolving power of quantitative trait mapping and the precision of favorable allele introgression. The consequences of low recombination also theoretically extend to the species-wide scale by decreasing the power of selection relative to genetic drift, and thereby hindering the purging of deleterious mutations. In this study, we used genotyping-by-sequencing (GBS) to identify 136,000 recombination breakpoints at high resolution within US and Chinese maize nested association mapping populations. We find that the pattern of cross-overs is highly predictable on the broad scale, following the distribution of gene density and CpG methylation. Several large inversions also suppress recombination in distinct regions of several families. We also identify recombination hotspots ranging in size from 1 kb to 30 kb. We find these hotspots to be historically stable and, compared with similar regions with low recombination, to have strongly differentiated patterns of DNA methylation and GC content. We also provide evidence for the historical action of GC-biased gene conversion in recombination hotspots. Finally, using genomic evolutionary rate profiling (GERP) to identify putative deleterious polymorphisms, we find evidence for reduced genetic load in hotspot regions, a phenomenon that may have considerable practical importance for breeding programs worldwide.

  7. Tool life prediction under multi-cycle loading conditions: A feasibility study

    Directory of Open Access Journals (Sweden)

    Yuan Xi

    2015-01-01

    Full Text Available In the present research, the friction and wear behaviour of a hard coating were studied by using ball-on-disc tests to simulate the wear process of the coated tools for sheet metal forming process. The evolution of the friction coefficient followed a typical dual-plateau pattern, i.e. at the initial stage of sliding, the friction coefficient was relatively low, followed by a sharp increase due to the breakdown of the coatings after a certain number of cyclic dynamic loadings. This phenomenon was caused by the interactive response between the friction and wear from a coating tribo-system, which has not been addressed so far by metal forming researchers, and constant friction coefficient values are normally used in the FE simulations to represent the complex tribological nature at the contact interfaces. Meanwhile, most of the current FE simulations are single cycle, whereas most sheet metal forming operations are conducted as multi-cycle. Therefore, a novel friction/wear interactive friction model was developed to, simultaneously, characterise the evolutions of friction coefficient and the remaining thickness of the coating layer, to enable the wear life of coated tooling to be predicted. The friction model was then implemented into the FE simulation of a sheet metal forming process for feasibility study.

  8. On the prediction of the reactor vessel integrity under severe accident loadings (RPVSA)

    Energy Technology Data Exchange (ETDEWEB)

    Krieg, R. E-mail: maeule@irs.fzk.de; Devos, J.; Caroli, C.; Solomos, G.; Ennis, P.J.; Kalkhof, D

    2001-11-01

    In order to allow more reliable predictions on the lower head response under core melt-down conditions, the temperature distribution has been analysed including the natural convection in the corium pool. Furthermore, the mechanical models and the failure criteria have been improved based on the RUPTHER and FASTHER experiments where typical temperature gradients are simulated. Lower head local melting as well as corium crust development has been addressed in the CORVIS experiments studying the contact between an alumina/iron thermite and a thick steel plate. The upper head loading by corium impact due to a postulated in-vessel steam explosion has been investigated by the BERDA experiments. Similarity rules were considered such that the results can be directly converted to reactor conditions. Based on these investigations admissible steam explosion energy releases are determined which the upper head can carry. If these limits are not exceeded the reactor containment cannot be endangered by broken head fragments. To provide the necessary basic data, mechanical material tests have been performed.

  9. Microstructure-based constitutive modeling of TRIP steel: Prediction of ductility and failure modes under different loading conditions

    International Nuclear Information System (INIS)

    Choi, K.S.; Liu, W.N.; Sun, X.; Khaleel, M.A.

    2009-01-01

    We study the ultimate ductility and failure modes of a commercial transformation-induced plasticity (TRIP) 800 steel under different loading conditions with an advanced microstructure-based finite-element analysis. The representative volume element (RVE) for the TRIP 800 under examination is developed based on an actual microstructure obtained from scanning electron microscopy. The ductile failure of the TRIP 800 under different loading conditions is predicted in the form of plastic strain localization without any prescribed failure criteria for the individual phases. This indicates that the microstructure-level inhomogeneity of the various constituent phases can be the key factor influencing the final ductility of the TRIP 800 steel under different loading conditions. Comparisons of the computational results with experimental measurements suggest that the microstructure-based modeling approach accurately captures the overall macroscopic behavior of the TRIP 800 steel under different loading and boundary conditions.

  10. Nested-scale discharge and groundwater level monitoring to improve predictions of flow route discharges and nitrate loads

    NARCIS (Netherlands)

    Velde, Y. van der; Rozemeijer, J.C.; Rooij, G.H.de; Geer, F.C. van; Torfs, P.J.J.F.; Louw, P.G.B. de

    2010-01-01

    Identifying effective measures to reduce nutrient loads of headwaters in lowland catchments requires a thorough understanding of flow routes of water and nutrients. In this paper we assess the value of nested-scale discharge and groundwater level measurements for predictions of catchment-scale

  11. High and increasing Oxa-51 DNA load predict mortality in Acinetobacter baumannii bacteremia: implication for pathogenesis and evaluation of therapy.

    Directory of Open Access Journals (Sweden)

    Yu-Chung Chuang

    Full Text Available BACKGROUND: While quantification of viral loads has been successfully employed in clinical medicine and has provided valuable insights and useful markers for several viral diseases, the potential of measuring bacterial DNA load to predict outcome or monitor therapeutic responses remains largely unexplored. We tested this possibility by investigating bacterial loads in Acinetobacter baumannii bacteremia, a rapidly increasing nosocomial infection characterized by high mortality, drug resistance, multiple and complicated risk factors, all of which urged the need of good markers to evaluate therapeutics. METHODS AND FINDINGS: We established a quantitative real-time PCR assay based on an A. baumannii-specific gene, Oxa-51, and conducted a prospective study to examine A. baumannii loads in 318 sequential blood samples from 51 adults patients (17 survivors, 34 nonsurvivors with culture-proven A. baumannii bacteremia in the intensive care units. Oxa-51 DNA loads were significantly higher in the nonsurvivors than survivors on day 1, 2 and 3 (P=0.03, 0.001 and 0.006, respectively. Compared with survivors, nonsurvivors had higher maximum Oxa-51 DNA load and a trend of increase from day 0 to day 3 (P<0.001, which together with Pitt bacteremia score were independent predictors for mortality by multivariate analysis (P=0.014 and 0.016, for maximum Oxa-51 DNA and change of Oxa-51 DNA, respectively. Kaplan-Meier analysis revealed significantly different survival curves in patients with different maximum Oxa-51 DNA and change of Oxa-51 DNA from day 0 to day 3. CONCLUSIONS: High Oxa-51 DNA load and its initial increase could predict mortality. Moreover, monitoring Oxa-51 DNA load in blood may provide direct parameters for evaluating new regimens against A. baumannii in future clinical studies.

  12. Acoustic Log Prediction on the Basis of Kernel Extreme Learning Machine for Wells in GJH Survey, Erdos Basin

    Directory of Open Access Journals (Sweden)

    Jianhua Cao

    2017-01-01

    Full Text Available In petroleum exploration, the acoustic log (DT is popularly used as an estimator to calculate formation porosity, to carry out petrophysical studies, or to participate in geological analysis and research (e.g., to map abnormal pore-fluid pressure. But sometime it does not exist in those old wells drilled 20 years ago, either because of data loss or because of just being not recorded at that time. Thus synthesizing the DT log becomes the necessary task for the researchers. In this paper we propose using kernel extreme learning machine (KELM to predict missing sonic (DT logs when only common logs (e.g., natural gamma ray: GR, deep resistivity: REID, and bulk density: DEN are available. The common logs are set as predictors and the DT log is the target. By using KELM, a prediction model is firstly created based on the experimental data and then confirmed and validated by blind-testing the results in wells containing both the predictors and the target (DT values used in the supervised training. Finally the optimal model is set up as a predictor. A case study for wells in GJH survey from the Erdos Basin, about velocity inversion using the KELM-estimated DT values, is presented. The results are promising and encouraging.

  13. Predictable variation of range-sizes across an extreme environmental gradient in a lizard adaptive radiation: evolutionary and ecological inferences.

    Directory of Open Access Journals (Sweden)

    Daniel Pincheira-Donoso

    Full Text Available Large-scale patterns of current species geographic range-size variation reflect historical dynamics of dispersal and provide insights into future consequences under changing environments. Evidence suggests that climate warming exerts major damage on high latitude and elevation organisms, where changes are more severe and available space to disperse tracking historical niches is more limited. Species with longer generations (slower adaptive responses, such as vertebrates, and with restricted distributions (lower genetic diversity, higher inbreeding in these environments are expected to be particularly threatened by warming crises. However, a well-known macroecological generalization (Rapoport's rule predicts that species range-sizes increase with increasing latitude-elevation, thus counterbalancing the impact of climate change. Here, I investigate geographic range-size variation across an extreme environmental gradient and as a function of body size, in the prominent Liolaemus lizard adaptive radiation. Conventional and phylogenetic analyses revealed that latitudinal (but not elevational ranges significantly decrease with increasing latitude-elevation, while body size was unrelated to range-size. Evolutionarily, these results are insightful as they suggest a link between spatial environmental gradients and range-size evolution. However, ecologically, these results suggest that Liolaemus might be increasingly threatened if, as predicted by theory, ranges retract and contract continuously under persisting climate warming, potentially increasing extinction risks at high latitudes and elevations.

  14. Lower extremity computed tomography angiography can help predict technical success of endovascular revascularization in the superficial femoral and popliteal artery.

    Science.gov (United States)

    Itoga, Nathan K; Kim, Tanner; Sailer, Anna M; Fleischmann, Dominik; Mell, Matthew W

    2017-09-01

    Preprocedural computed tomography angiography (CTA) assists in evaluating vascular morphology and disease distribution and in treatment planning for patients with lower extremity peripheral artery disease (PAD). The aim of the study was to determine the predictive value of radiographic findings on CTA and technical success of endovascular revascularization of occlusions in the superficial femoral artery-popliteal (SFA-pop) region. Medical records and available imaging studies were reviewed for patients undergoing endovascular intervention for PAD between January 2013 and December 2015 at a single academic institution. Radiologists reviewed preoperative CTA scans of patients with occlusions in the SFA-pop region. Radiographic criteria previously used to evaluate chronic occlusions in the coronary arteries were used. Technical success, defined as restoration of inline flow through the SFA-pop region with technical failure (P = .014). Longer lengths of occlusion were also associated with technical failure (P = .042). Multiple occlusions (P = .55), negative remodeling (P = .69), vessel runoff (P = .56), and percentage of vessel calcification (P = .059) were not associated with failure. On multivariable analysis, 100% calcification remained the only significant predictor of technical failure (odds ratio, 9.0; 95% confidence interval, 1.8-45.8; P = .008). Analysis of preoperative CTA shows 100% calcification as the best predictor of technical failure of endovascular revascularization of occlusions in the SFA-pop region. Further studies are needed to determine the cost-effectiveness of obtaining preoperative CTA for lower extremity PAD. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

  15. Prediction of equibiaxial loading stress in collagen-based extracellular matrix using a three-dimensional unit cell model.

    Science.gov (United States)

    Susilo, Monica E; Bell, Brett J; Roeder, Blayne A; Voytik-Harbin, Sherry L; Kokini, Klod; Nauman, Eric A

    2013-03-01

    Mechanical signals are important factors in determining cell fate. Therefore, insights as to how mechanical signals are transferred between the cell and its surrounding three-dimensional collagen fibril network will provide a basis for designing the optimum extracellular matrix (ECM) microenvironment for tissue regeneration. Previously we described a cellular solid model to predict fibril microstructure-mechanical relationships of reconstituted collagen matrices due to unidirectional loads (Acta Biomater 2010;6:1471-86). The model consisted of representative volume elements made up of an interconnected network of flexible struts. The present study extends this work by adapting the model to account for microstructural anisotropy of the collagen fibrils and a biaxial loading environment. The model was calibrated based on uniaxial tensile data and used to predict the equibiaxial tensile stress-stretch relationship. Modifications to the model significantly improved its predictive capacity for equibiaxial loading data. With a comparable fibril length (model 5.9-8μm, measured 7.5μm) and appropriate fibril anisotropy the anisotropic model provides a better representation of the collagen fibril microstructure. Such models are important tools for tissue engineering because they facilitate prediction of microstructure-mechanical relationships for collagen matrices over a wide range of microstructures and provide a framework for predicting cell-ECM interactions. Copyright © 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  16. Proposal of a Global Training Load Measure Predicting Match Performance in an Elite Team Sport

    Directory of Open Access Journals (Sweden)

    Brendan H. Lazarus

    2017-11-01

    Full Text Available Aim: The use of external and internal load is an important aspect of monitoring systems in team sport. The aim of this study was to validate a novel measure of training load by quantifying the training-performance relationship of elite Australian footballers.Methods: The primary training measure of each of 36 players was weekly load derived from a weighted combination of Global Positioning System (GPS data and perceived wellness over a 24-week season. Smoothed loads representing an exponentially weighted rolling average were derived with decay time constants of 1.5, 2, 3, and 4 weeks. Differential loads representing rate of change in load were generated in similar fashion. Other derived measures of training included monotony, strain and acute:chronic ratio. Performance was a proprietary score derived from match performance indicators. Effects of a 1 SD within-player change below and above the mean of each training measure were quantified with a quadratic mixed model for each position (defenders, forwards, midfielders, and rucks. Effects were interpreted using standardization and magnitude-based inferences.Results: Performance was generally highest near the mean or ~1 SD below the mean of each training measure, and 1 SD increases in the following measures produced small impairments: weekly load (defenders, forwards, and midfielders; 1.5-week smoothed load (midfielders; 4-week differential load (defenders, forwards, and midfielders; and acute:chronic ratio (defenders and forwards. Effects of other measures in other positions were either trivial or unclear.Conclusion: The innovative combination of load was sensitive to performance in this elite Australian football cohort. Periods of high acute load and sustained increases in load impaired match performance. Positional differences should be taken into account for individual training prescription.

  17. Study of connected system of automatic control of load and operation efficiency of a steam boiler with extremal controller on a simulation model

    Science.gov (United States)

    Sabanin, V. R.; Starostin, A. A.; Repin, A. I.; Popov, A. I.

    2017-02-01

    The problems of operation effectiveness increase of steam boilers are considered. To maintain the optimum fuel combustion modes, it is proposed to use an extremal controller (EC) determining the value of airflow rate, at which the boiler generating the desired amount of heat will consume a minimum amount of fuel. EC sets the determined value of airflow rate to airflow rate controller (ARC). The test results of numerical simulation dynamic nonlinear model of steam boiler with the connected system of automatic control of load and combustion efficiency using EC are presented. The model is created in the Simulink modeling package of MATLAB software and can be used to optimize the combustion modes. Based on the modeling results, the conclusion was drawn about the possibility in principle of simultaneously boiler load control and optimizing by EC the combustion modes when changing the fuel combustion heat and the boiler characteristics and its operating mode. It is shown that it is possible to automatically control the operation efficiency of steam boilers when using EC without applying the standard flue gas analyzers. The article considers the numerical simulation dynamic model of steam boiler with the schemes of control of fuel consumption and airflow rate, the steam pressure and EC; the purpose of using EC in the scheme with linear controllers and the requirements to the quality of its operation; the results of operation of boiler control schemes without EC with estimation of influence of roughness of thermal mode maps on the nature of static and dynamic connection of the control units of fuel consumption and airflow rate; the phase trajectories and the diagrams of transient processes occurring in the control scheme with EC with stepped changing the fuel quality and boiler characteristics; analysis of modeling results and prospects for using EC in the control schemes of boilers.

  18. Instability predictions for circumferentially cracked Type-304 stainless steel pipes under dynamic loading. Volume 2. Appendixes. Final report. [BWR

    Energy Technology Data Exchange (ETDEWEB)

    Zahoor, A.; Wilkowski, G.; Abou-Sayed, I.; Marschall, C.; Broek, D.; Sampath, S.; Rhee, H.; Ahmad, J.

    1982-04-01

    This report provides methods to predict margins of safety for circumferentially cracked Type 304 stainless steel pipes subjected to applied bending loads. An integrated combination of experimentation and analysis research was pursued. Two types of experiments were performed: (1) laboratory-scale tests on center-cracked panels and bend specimens to establish the basic mechanical and fracture properties of Type 304 stainless steel, and (2) full-scale pipe fracture tests under quasi-static and dynamic loadings to assess the analysis procedures. Analyses were based upon the simple plastic collapse criterion, a J-estimation procedure, and elastic-plastic large-deformation finite element models.

  19. Instability predictions for circumferentially cracked Type-304 stainless steel pipes under dynamic loading. Volume 2. Appendixes. Final report

    International Nuclear Information System (INIS)

    Zahoor, A.; Wilkowski, G.; Abou-Sayed, I.; Marschall, C.; Broek, D.; Sampath, S.; Rhee, H.; Ahmad, J.

    1982-04-01

    This report provides methods to predict margins of safety for circumferentially cracked Type 304 stainless steel pipes subjected to applied bending loads. An integrated combination of experimentation and analysis research was pursued. Two types of experiments were performed: (1) laboratory-scale tests on center-cracked panels and bend specimens to establish the basic mechanical and fracture properties of Type 304 stainless steel, and (2) full-scale pipe fracture tests under quasi-static and dynamic loadings to assess the analysis procedures. Analyses were based upon the simple plastic collapse criterion, a J-estimation procedure, and elastic-plastic large-deformation finite element models

  20. Instability predictions for circumferentially cracked Type-304 stainless-steel pipes under dynamic loading. Final report. [BWR

    Energy Technology Data Exchange (ETDEWEB)

    Zahoor, A.; Wilkowski, G.; Abou-Sayed, I.; Marschall, C.; Broek, D.; Sampath, S.; Rhee, H.; Ahmad, J.

    1982-04-01

    This report provides methods to predict margins of safety for circumferentially cracked Type 304 stainless steel pipes subjected to applied bending loads. An integrated combination of experimentation and analysis research was pursued. Two types of experiments were performed: (1) laboratory-scale tests on center-cracked panels and bend specimens to establish the basic mechanical and fracture properties of Type 304 stainless steel, and (2) full-scale pipe fracture tests under quasi-static and dynamic loadings to assess the analysis procedures. Analyses were based upon the simple plastic collapse criterion, a J-estimation procedure, and elastic-plastic large-deformation finite element models.

  1. Hourly cooling load prediction of a vehicle in the southern region of Turkey by Artificial Neural Network

    International Nuclear Information System (INIS)

    Solmaz, Ozgur; Ozgoren, Muammer; Aksoy, Muharrem Hilmi

    2014-01-01

    Highlights: • An ANN model was developed to predict hourly cooling load of a vehicle. • Hourly meteorological data of 5 different provinces was used. • The agreement of the cooling load values between the calculations and predictions was fairly promising. • The ANN model could be successfully used to design automotive air conditioning systems. - Abstract: In this study, Artificial Neural Networks (ANNs) method for prediction hourly cooling load of a vehicle was implemented. The cooling load of the vehicle was calculated along the cooling season (1 May–30 September) for Antalya, Konya, Mersin, Mugla and Sanliurfa provinces in Turkey. For ANN model, seven neurons determinated as input signals of latitude, longitude, altitude, day of the year, hour of the day, hourly mean ambient air temperature and hourly solar radiation were used for the input layer of the network. One neuron producing an output signal of the hourly cooling load was utilized in the output layer. All data were divided into two categories for training and testing of the ANN. The 80% of the data was reserved to training and the remaining was used for testing of the model. Neuron numbers in the hidden layer from 7 to 40 were tested step by step to find the best matching ANN structure. The obtained results for different numbers of neurons were compared in terms of root mean squared error (RMSE), coefficient of determination (R 2 ) and mean absolute error (MAE). The best matching results for the training and testing were obtained as 8 neurons for the minimum testing RMSE value for the prediction of cooling load by the ANN model on the 23rd day of each month along the cooling season. For the model with 8 neurons RMSE, R 2 and MAE (Training/Testing) were found to be 0.0128/0.0259, 0.9959/0.9818 and 78.81/174.71 W/m 2 , respectively. It is shown that the cooling load of a vehicle can be successfully predicted by means of the ANNs from geographical characteristics and meteorological data

  2. A finite element lower extremity and pelvis model for predicting bone injuries due to knee bolster loading

    NARCIS (Netherlands)

    Rooij, L. van; Hoof, J. van; Barbir, A.; Made, R. van der; Slaats, P.M.A.; McCann, M.J.; Ridella, S.A.; Rupp, J.D.

    2004-01-01

    Injuries to the knee-thigh-hip (KTH) complex in frontal motor vehicle crashes are of substantial concern because of their frequency and potential to result in long-term disability. Current frontal impact Anthropometric Test Dummies (ATDs) have been shown to respond differently than human cadavers

  3. Testing a distributed hydrological model to predict scenarios of extreme events on a marginal olive orchard microcatchment

    Science.gov (United States)

    Guzmán, Enrique; Aguilar, Cristina; Taguas, Encarnación V.

    2014-05-01

    Olive groves constitute a traditional Mediterranean crop and thus, an important source of income to these regions and a crucial landscape component. Despite its importance, most of the olive groves in the region of Andalusia, Southern Spain, are located in sloping areas, which implies a significant risk of erosion. The combination of data and models allow enhancing the knowledge about processes taking place in these areas as well as the prediction of future scenarios. This aspect might be essential to plan soil protection strategies within a context of climate change where the IPCC estimates a significant increase of soil aridity and torrential events by the end of the century. The objective of this study is to estimate the rainfall-runoff-sediment dynamics in a microcatchment olive grove with the aid of a physically-based distributed hydrological model in order to evaluate the effect of extreme events on runoff and erosion. This study will allow to improve land-use and management planning activities in similar areas. In addition, the scale of the study (microcatchment) will allow to contrast the results in larger areas such as catchment regional spatial scales.

  4. Coupled prediction of flash flood response and debris flow occurrence: Application on an alpine extreme flood event

    Science.gov (United States)

    Destro, Elisa; Amponsah, William; Nikolopoulos, Efthymios I.; Marchi, Lorenzo; Marra, Francesco; Zoccatelli, Davide; Borga, Marco

    2018-03-01

    The concurrence of flash floods and debris flows is of particular concern, because it may amplify the hazard corresponding to the individual generative processes. This paper presents a coupled modelling framework for the predictions of flash flood response and of the occurrence of debris flows initiated by channel bed mobilization. The framework combines a spatially distributed flash flood response model and a debris flow initiation model to define a threshold value for the peak flow which permits identification of channelized debris flow initiation. The threshold is defined over the channel network as a function of the upslope area and of the local channel bed slope, and it is based on assumptions concerning the properties of the channel bed material and of the morphology of the channel network. The model is validated using data from an extreme rainstorm that impacted the 140 km2 Vizze basin in the Eastern Italian Alps on August 4-5, 2012. The results show that the proposed methodology has improved skill in identifying the catchments where debris-flows are triggered, compared to the use of simpler thresholds based on rainfall properties.

  5. Allostatic load but not medical burden predicts memory performance in late-life bipolar disorder.

    Science.gov (United States)

    Vaccarino, Sophie R; Rajji, Tarek K; Gildengers, Ariel G; Waters, Sarah E S; Butters, Meryl A; Menon, Mahesh; Blumberger, Daniel M; Voineskos, Aristotle N; Miranda, Dielle; Mulsant, Benoit H

    2018-03-01

    Older patients with bipolar disorder (BD) present with variable degrees of cognitive impairment. Over time, stress, mood episodes, and comorbidities increase the body's allostatic load. We assessed the extent to which allostatic load vs more traditional measures of medical burden account for the heterogeneity in cognition in this population. Thirty-five older euthymic patients with BD and 30 age-equated, gender-equated, and education-equated comparison participants were administered a comprehensive assessment including a neuropsychological battery, and 9 physiological measures to determine allostatic load. The relationship among allostatic load, medical burden, and cognition was assessed. Compared with the mentally healthy comparators, patients were impaired globally, and in 4 cognitive domains-information-processing speed / executive functioning, delayed memory, language, and visuomotor ability, and presented with greater medical burden but not a different allostatic load. Allostatic load, but not medical burden, was associated with delayed memory performance both in a correlational analysis and in a multivariate regression analysis. Euthymic older patients with BD are impaired on several cognitive domains and have high medical burden. Their memory performance is more strongly associated with allostatic load than with traditional measures of medical burden. These findings need to be replicated and extended longitudinally. Copyright © 2017 John Wiley & Sons, Ltd.

  6. Working memory load predicts visual search efficiency: Evidence from a novel pupillary response paradigm.

    Science.gov (United States)

    Attar, Nada; Schneps, Matthew H; Pomplun, Marc

    2016-10-01

    An observer's pupil dilates and constricts in response to variables such as ambient and focal luminance, cognitive effort, the emotional stimulus content, and working memory load. The pupil's memory load response is of particular interest, as it might be used for estimating observers' memory load while they are performing a complex task, without adding an interruptive and confounding memory test to the protocol. One important task in which working memory's involvement is still being debated is visual search, and indeed a previous experiment by Porter, Troscianko, and Gilchrist (Quarterly Journal of Experimental Psychology, 60, 211-229, 2007) analyzed observers' pupil sizes during search to study this issue. These authors found that pupil size increased over the course of the search, and they attributed this finding to accumulating working memory load. However, since the pupil response is slow and does not depend on memory load alone, this conclusion is rather speculative. In the present study, we estimated working memory load in visual search during the presentation of intermittent fixation screens, thought to induce a low, stable level of arousal and cognitive effort. Using standard visual search and control tasks, we showed that this paradigm reduces the influence of non-memory-related factors on pupil size. Furthermore, we found an early increase in working memory load to be associated with more efficient search, indicating a significant role of working memory in the search process.

  7. A damage cumulation method for crack initiation prediction under non proportional loading and overloading

    International Nuclear Information System (INIS)

    Taheri, S.

    1992-04-01

    For a sequence of constant amplitude cyclic loading containing overloads, we propose a method for damage cumulation in non proportional loading. This method uses as data cyclic stabilized states at non proportional loading and initiation or fatigue curve in uniaxial case. For that, we take into account the dependence of Cyclic Strain Stress Curves (C.S.S.C.) and mean cell size on prehardening and we define a stabilized uniaxial state cyclically equivalent to a non proportional stabilized state through a family of C.S.S.C. Although simple assumptions like linear damage function and linear cumulation is used we obtain a sequence effect for difficult cross slip materials as 316 stainless steel, but the Miner rule for easy cross-slip materials. We show then differences between a load-controlled test and a strain controlled test: for a 316 stainless steel in a load controlled test, the non proportional loading at each cycle is less damaging than the uniaxial one for the same equivalent stress, while the result is opposite in a strain controlled test. We show also that an overloading retards initiation in a load controlled test while it accelerates initiation in a strain controlled test. (author). 26 refs., 8 figs

  8. Predictive ability of the Society for Vascular Surgery Wound, Ischemia, and foot Infection (WIfI) classification system after first-time lower extremity revascularizations

    OpenAIRE

    Darling, Jeremy; McCallum, John C.; Soden, Peter A.; Guzman, R.J. (Raul J.); Wyers, M.C. (Mark C.); Hamdan, A.D. (Allen D.); Verhagen, Hence; Schermerhorn, Marc

    2017-01-01

    markdownabstract__Objective:__ The Society for Vascular Surgery (SVS) Wound, Ischemia and foot Infection (WIfI) classification system was proposed to predict 1-year amputation risk and potential benefit from revascularization. Our goal was to evaluate the predictive ability of this scale in a real-world selection of patients undergoing a first-time lower extremity revascularization for chronic limb-threatening ischemia (CLTI). __Methods:__ From 2005 to 2014, 1336 limbs underwent a first-time ...

  9. Proposed Model of Predicting the Reduced Yield Axial Load of Reinforced Concrete Columns Due to Casting Deficiency Effect

    Directory of Open Access Journals (Sweden)

    Achillopoulou Dimitra

    2014-12-01

    Full Text Available The study deals with the investigation of the effect of casting deficiencies- both experimentally and analytically on axial yield load or reinforced concrete columns. It includes 6 specimens of square section (150x150x500 mm of 24.37 MPa nominal concrete strength with 4 longitudinal steel bars of 8 mm (500 MPa nominal strength with confinement ratio ωc=0.15. Through casting procedure the necessary provisions defined by International Standards were not applied strictly in order to create construction deficiencies. These deficiencies are quantified geometrically without the use of expensive and expertise non-destructive methods and their effect on the axial load capacity of the concrete columns is calibrated trough a novel and simplified prediction model extracted by an experimental and analytical investigation that included 6 specimens. It is concluded that: a even with suitable repair, load reduction up to 22% is the outcome of the initial construction damage presence, b the lower dispersion is noted for the section damage index proposed, c extended damage alters the failure mode to brittle accompanied with longitudinal bars buckling, d the proposed model presents more than satisfying results to the load capacity prediction of repaired columns.

  10. Development of a computer model to predict aortic rupture due to impact loading.

    Science.gov (United States)

    Shah, C S; Yang, K H; Hardy, W; Wang, H K; King, A I

    2001-11-01

    Aortic injuries during blunt thoracic impacts can lead to life threatening hemorrhagic shock and potential exsanguination. Experimental approaches designed to study the mechanism of aortic rupture such as the testing of cadavers is not only expensive and time consuming, but has also been relatively unsuccessful. The objective of this study was to develop a computer model and to use it to predict modes of loading that are most likely to produce aortic ruptures. Previously, a 3D finite element model of the human thorax was developed and validated against data obtained from lateral pendulum tests. The model included a detailed description of the heart, lungs, rib cage, sternum, spine, diaphragm, major blood vessels and intercostal muscles. However, the aorta was modeled as a hollow tube using shell elements with no fluid within, and its material properties were assumed to be linear and isotropic. In this study fluid elements representing blood have been incorporated into the model in order to simulate pressure changes inside the aorta due to impact. The current model was globally validated against experimental data published in the literature for both frontal and lateral pendulum impact tests. Simulations of the validated model for thoracic impacts from a number of directions indicate that the ligamentum arteriosum, subclavian artery, parietal pleura and pressure changes within the aorta are factors that could influence aortic rupture. The model suggests that a right-sided impact to the chest is potentially more hazardous with respect to aortic rupture than any other impact direction simulated in this study. The aortic isthmus was the most likely site of aortic rupture regardless of impact direction. The reader is cautioned that this model could only be validated on a global scale. Validation of the kinematics and dynamics of the aorta at the local level could not be done due to a lack of experimental data. It is hoped that this model will be used to design

  11. Life prediction of different commercial dental implants as influence by uncertainties in their fatigue material properties and loading conditions.

    Science.gov (United States)

    Pérez, M A

    2012-12-01

    Probabilistic analyses allow the effect of uncertainty in system parameters to be determined. In the literature, many researchers have investigated static loading effects on dental implants. However, the intrinsic variability and uncertainty of most of the main problem parameters are not accounted for. The objective of this research was to apply a probabilistic computational approach to predict the fatigue life of three different commercial dental implants considering the variability and uncertainty in their fatigue material properties and loading conditions. For one of the commercial dental implants, the influence of its diameter in the fatigue life performance was also studied. This stochastic technique was based on the combination of a probabilistic finite element method (PFEM) and a cumulative damage approach known as B-model. After 6 million of loading cycles, local failure probabilities of 0.3, 0.4 and 0.91 were predicted for the Lifecore, Avinent and GMI implants, respectively (diameter of 3.75mm). The influence of the diameter for the GMI implant was studied and the results predicted a local failure probability of 0.91 and 0.1 for the 3.75mm and 5mm, respectively. In all cases the highest failure probability was located at the upper screw-threads. Therefore, the probabilistic methodology proposed herein may be a useful tool for performing a qualitative comparison between different commercial dental implants. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  12. Prediction of composite fatigue life under variable amplitude loading using artificial neural network trained by genetic algorithm

    Science.gov (United States)

    Rohman, Muhamad Nur; Hidayat, Mas Irfan P.; Purniawan, Agung

    2018-04-01

    Neural networks (NN) have been widely used in application of fatigue life prediction. In the use of fatigue life prediction for polymeric-base composite, development of NN model is necessary with respect to the limited fatigue data and applicable to be used to predict the fatigue life under varying stress amplitudes in the different stress ratios. In the present paper, Multilayer-Perceptrons (MLP) model of neural network is developed, and Genetic Algorithm was employed to optimize the respective weights of NN for prediction of polymeric-base composite materials under variable amplitude loading. From the simulation result obtained with two different composite systems, named E-glass fabrics/epoxy (layups [(±45)/(0)2]S), and E-glass/polyester (layups [90/0/±45/0]S), NN model were trained with fatigue data from two different stress ratios, which represent limited fatigue data, can be used to predict another four and seven stress ratios respectively, with high accuracy of fatigue life prediction. The accuracy of NN prediction were quantified with the small value of mean square error (MSE). When using 33% from the total fatigue data for training, the NN model able to produce high accuracy for all stress ratios. When using less fatigue data during training (22% from the total fatigue data), the NN model still able to produce high coefficient of determination between the prediction result compared with obtained by experiment.

  13. Brain atrophy and lesion load predict long term disability in multiple sclerosis

    DEFF Research Database (Denmark)

    Popescu, Veronica; Agosta, Federica; Hulst, Hanneke E

    2013-01-01

    To determine whether brain atrophy and lesion volumes predict subsequent 10 year clinical evolution in multiple sclerosis (MS).......To determine whether brain atrophy and lesion volumes predict subsequent 10 year clinical evolution in multiple sclerosis (MS)....

  14. The prediction of the impact of climatic factors on short-term electric power load based on the big data of smart city

    Science.gov (United States)

    Qiu, Yunfei; Li, Xizhong; Zheng, Wei; Hu, Qinghe; Wei, Zhanmeng; Yue, Yaqin

    2017-08-01

    The climate changes have great impact on the residents’ electricity consumption, so the study on the impact of climatic factors on electric power load is of significance. In this paper, the effects of the data of temperature, rainfall and wind of smart city on short-term power load is studied to predict power load. The authors studied the relation between power load and daily temperature, rainfall and wind in the 31 days of January of one year. In the research, the authors used the Matlab neural network toolbox to establish the combinational forecasting model. The authors trained the original input data continuously to get the internal rules inside the data and used the rules to predict the daily power load in the next January. The prediction method relies on the accuracy of weather forecasting. If the weather forecasting is different from the actual weather, we need to correct the climatic factors to ensure accurate prediction.

  15. A method for predicting the fatigue life of pre-corroded 2024-T3 aluminum from breaking load tests

    Science.gov (United States)

    Gruenberg, Karl Martin

    Characterization of material properties is necessary for design purposes and has been a topic of research for many years. Over the last several decades, much progress has been made in identifying metrics to describe fracture mechanics properties and developing procedures to measure the appropriate values. However, in the context of design, there has not been as much success in quantifying the susceptibility of a material to corrosion damage and its subsequent impact on material behavior in the framework of fracture mechanics. A natural next step in understanding the effects of corrosion damage was to develop a link between standard material test procedures and fatigue life in the presence of corrosion. Simply stated, the goal of this investigation was to formulate a cheaper and quicker method for assessing the consequences of corrosion on remaining fatigue life. For this study, breaking load specimens and fatigue specimens of a single nominal gage (0.063″) of aluminum alloy 2024-T3 were exposed to three levels of corrosion. The breaking load specimens were taken from three different material lots, and the fatigue tests were carried out at three stress levels. All failed specimens, both breaking load and fatigue specimens, were examined to characterize the damage state(s) and failure mechanism(s). Correlations between breaking load results and fatigue life results in the presence of corrosion damage were developed using a fracture mechanics foundation and the observed mechanisms of failure. Where breaking load tests showed a decrease in strength due to increased corrosion exposure, the corresponding set of fatigue tests showed a decrease in life. And where breaking load tests from different specimen orientations exhibited similar levels of strength, the corresponding set of fatigue specimens showed similar lives. The spread from shortest to longest fatigue lives among the different corrosion conditions decreased at the higher stress levels. Life predictions based

  16. Cognitive task load in a naval ship control centre : from identification to prediction

    NARCIS (Netherlands)

    Grootjen, M.; Neerincx, M.A.; Grootjen, M.; Veltman, J.

    2006-01-01

    Deployment of information and communication technology will lead to further automation of control centre tasks and an increasing amount of information to be processed. A method for establishing adequate levels of cognitive task load for the operators in such complex environments has been developed.

  17. Application of Watershed Scale Models to Predict Nitrogen Loading From Coastal Plain Watersheds

    Science.gov (United States)

    George M. Chescheir; Glenn P Fernandez; R. Wayne Skaggs; Devendra M. Amatya

    2004-01-01

    DRAINMOD-based watershed models have been developed and tested using data collected from an intensively instrumented research site on Kendricks Creek watershed near Plymouth. NC. These models were applied to simulate the hydrology and nitrate nitrogen (NO3-N) loading from two other watersheds in the Coastal Plain of North Carolina, the 11600 ha Chicod Creek watershed...

  18. Multi-scale mechanics of traumatic brain injury : predicting axonal strains from head loads

    NARCIS (Netherlands)

    Cloots, R.J.H.; Dommelen, van J.A.W.; Kleiven, S.; Geers, M.G.D.

    2013-01-01

    The length scales involved in the development of diffuse axonal injury typically range from the head level (i.e., mechanical loading) to the cellular level. The parts of the brain that are vulnerable to this type of injury are mainly the brainstem and the corpus callosum, which are regions with

  19. Pressure fluctuation prediction of a model pump turbine at no load opening by a nonlinear k-ε turbulence model

    International Nuclear Information System (INIS)

    Liu, J T; Zuo, Z G; Liu, S H; Wu, Y L

    2014-01-01

    In this paper, a new nonlinear k-ε turbulence model based on RNG k-ε turbulence model and Wilcox's k-ω turbulence model was proposed to simulate the unsteady flow and to predict the pressure fluctuation through a model pump turbine for engineering application. Calculations on a curved rectangular duct proved that the nonlinear k-ε turbulence model is applicable for high pressure gradient flows and large curvature flows. The numerically predicted relative pressure amplitude (peak to peak) in time domain to the pump turbine head at no load condition is very close to the experimental data. It is indicated that the prediction of the pressure fluctuation is valid by the present nonlinear k-ε method. The high pressure fluctuation in this area is the main issue for pump turbine design, especially at high head condition

  20. Load balancing prediction method of cloud storage based on analytic hierarchy process and hybrid hierarchical genetic algorithm.

    Science.gov (United States)

    Zhou, Xiuze; Lin, Fan; Yang, Lvqing; Nie, Jing; Tan, Qian; Zeng, Wenhua; Zhang, Nian

    2016-01-01

    With the continuous expansion of the cloud computing platform scale and rapid growth of users and applications, how to efficiently use system resources to improve the overall performance of cloud computing has become a crucial issue. To address this issue, this paper proposes a method that uses an analytic hierarchy process group decision (AHPGD) to evaluate the load state of server nodes. Training was carried out by using a hybrid hierarchical genetic algorithm (HHGA) for optimizing a radial basis function neural network (RBFNN). The AHPGD makes the aggregative indicator of virtual machines in cloud, and become input parameters of predicted RBFNN. Also, this paper proposes a new dynamic load balancing scheduling algorithm combined with a weighted round-robin algorithm, which uses the predictive periodical load value of nodes based on AHPPGD and RBFNN optimized by HHGA, then calculates the corresponding weight values of nodes and makes constant updates. Meanwhile, it keeps the advantages and avoids the shortcomings of static weighted round-robin algorithm.

  1. Load-Unload Response Ratio and Accelerating Moment/Energy Release Critical Region Scaling and Earthquake Prediction

    Science.gov (United States)

    Yin, X. C.; Mora, P.; Peng, K.; Wang, Y. C.; Weatherley, D.

    The main idea of the Load-Unload Response Ratio (LURR) is that when a system is stable, its response to loading corresponds to its response to unloading, whereas when the system is approaching an unstable state, the response to loading and unloading becomes quite different. High LURR values and observations of Accelerating Moment/Energy Release (AMR/AER) prior to large earthquakes have led different research groups to suggest intermediate-term earthquake prediction is possible and imply that the LURR and AMR/AER observations may have a similar physical origin. To study this possibility, we conducted a retrospective examination of several Australian and Chinese earthquakes with magnitudes ranging from 5.0 to 7.9, including Australia's deadly Newcastle earthquake and the devastating Tangshan earthquake. Both LURR values and best-fit power-law time-to-failure functions were computed using data within a range of distances from the epicenter. Like the best-fit power-law fits in AMR/AER, the LURR value was optimal using data within a certain epicentral distance implying a critical region for LURR. Furthermore, LURR critical region size scales with mainshock magnitude and is similar to the AMR/AER critical region size. These results suggest a common physical origin for both the AMR/AER and LURR observations. Further research may provide clues that yield an understanding of this mechanism and help lead to a solid foundation for intermediate-term earthquake prediction.

  2. Load Frequency Control in Isolated Micro-Grids with Electrical Vehicles Based on Multivariable Generalized Predictive Theory

    Directory of Open Access Journals (Sweden)

    Jun Yang

    2015-03-01

    Full Text Available In power systems, although the inertia energy in power sources can partly cover power unbalances caused by load disturbance or renewable energy fluctuation, it is still hard to maintain the frequency deviation within acceptable ranges. However, with the vehicle-to-grid (V2G technique, electric vehicles (EVs can act as mobile energy storage units, which could be a solution for load frequency control (LFC in an isolated grid. In this paper, a LFC model of an isolated micro-grid with EVs, distributed generations and their constraints is developed. In addition, a controller based on multivariable generalized predictive control (MGPC theory is proposed for LFC in the isolated micro-grid, where EVs and diesel generator (DG are coordinated to achieve a satisfied performance on load frequency. A benchmark isolated micro-grid with EVs, DG, and wind farm is modeled in the Matlab/Simulink environment to demonstrate the effectiveness of the proposed method. Simulation results demonstrate that with MGPC, the energy stored in EVs can be managed intelligently according to LFC requirement. This improves the system frequency stability with complex operation situations including the random renewable energy resource and the continuous load disturbances.

  3. Transient Vibration Prediction for Rotors on Ball Bearings Using Load-dependent Non-linear Bearing Stiffness

    Science.gov (United States)

    Fleming, David P.; Poplawski, J. V.

    2002-01-01

    Rolling-element bearing forces vary nonlinearly with bearing deflection. Thus an accurate rotordynamic transient analysis requires bearing forces to be determined at each step of the transient solution. Analyses have been carried out to show the effect of accurate bearing transient forces (accounting for non-linear speed and load dependent bearing stiffness) as compared to conventional use of average rolling-element bearing stiffness. Bearing forces were calculated by COBRA-AHS (Computer Optimized Ball and Roller Bearing Analysis - Advanced High Speed) and supplied to the rotordynamics code ARDS (Analysis of Rotor Dynamic Systems) for accurate simulation of rotor transient behavior. COBRA-AHS is a fast-running 5 degree-of-freedom computer code able to calculate high speed rolling-element bearing load-displacement data for radial and angular contact ball bearings and also for cylindrical and tapered roller beatings. Results show that use of nonlinear bearing characteristics is essential for accurate prediction of rotordynamic behavior.

  4. Comparison of Damage Models for Predicting the Non-Linear Response of Laminates Under Matrix Dominated Loading Conditions

    Science.gov (United States)

    Schuecker, Clara; Davila, Carlos G.; Rose, Cheryl A.

    2010-01-01

    Five models for matrix damage in fiber reinforced laminates are evaluated for matrix-dominated loading conditions under plane stress and are compared both qualitatively and quantitatively. The emphasis of this study is on a comparison of the response of embedded plies subjected to a homogeneous stress state. Three of the models are specifically designed for modeling the non-linear response due to distributed matrix cracking under homogeneous loading, and also account for non-linear (shear) behavior prior to the onset of cracking. The remaining two models are localized damage models intended for predicting local failure at stress concentrations. The modeling approaches of distributed vs. localized cracking as well as the different formulations of damage initiation and damage progression are compared and discussed.

  5. Prior failed ipsilateral percutaneous endovascular intervention in patients with critical limb ischemia predicts poor outcome after lower extremity bypass

    Science.gov (United States)

    Nolan, Brian W.; De Martino, Randall R.; Stone, David H.; Schanzer, Andres; Goodney, Philip P.; Walsh, Daniel W.; Cronenwett, Jack L.

    2017-01-01

    Background Although open surgical bypass remains the standard revascularization strategy for patients with critical limb ischemia (CLI), many centers now perform peripheral endovascular intervention (PVI) as the first-line treatment for these patients. We sought to determine the effect of a prior ipsilateral PVI (iPVI) on the outcome of subsequent lower extremity bypass (LEB) in patients with CLI. Methods A retrospective cohort analysis of all patients undergoing infrainguinal LEB between 2003 and 2009 within hospitals comprising the Vascular Study Group of New England (VSGNE) was performed. Primary study endpoints were major amputation and graft occlusion at 1 year postoperatively. Secondary outcomes included in-hospital major adverse events (MAE), 1-year mortality, and composite 1-year major adverse limb events (MALE). Event rates were determined using life table analyses and comparisons were performed using the log-rank test. Multivariate predictors were determined using a Cox proportional hazards model with multilevel hierarchical adjustment. Results Of 1880 LEBs performed, 32% (n = 603) had a prior infrainguinal revascularization procedure (iPVI, 7%; ipsilateral bypass, 15%; contralateral PVI, 3%; contralateral bypass, 17%). Patients with prior iPVI, compared with those without a prior iPVI, were more likely to be women (32 vs 41%; P = .04), less likely to have tissue loss (52% vs 63%; P = .02), more likely to require arm vein conduit (16% vs 5%; P = .001), and more likely to be on statin (71% vs 54%; P = .01) and beta blocker therapy (92% vs 81%; P = .01) at the time of their bypass procedure. Other demographic factors were similar between these groups. Prior PVI or bypass did not alter 30-day MAE and 1-year mortality after the index bypass. In contrast, 1-year major amputation and 1-year graft occlusion rates were significantly higher in patients who had prior iPVI than those without (31% vs 20%; P = .046 and 28% vs 18%; P = .009), similar to patients who

  6. Evaluation of MOSTAS computer code for predicting dynamic loads in two bladed wind turbines

    Science.gov (United States)

    Kaza, K. R. V.; Janetzke, D. C.; Sullivan, T. L.

    1979-01-01

    Calculated dynamic blade loads were compared with measured loads over a range of yaw stiffnesses of the DOE/NASA Mod-O wind turbine to evaluate the performance of two versions of the MOSTAS computer code. The first version uses a time-averaged coefficient approximation in conjunction with a multi-blade coordinate transformation for two bladed rotors to solve the equations of motion by standard eigenanalysis. The second version accounts for periodic coefficients while solving the equations by a time history integration. A hypothetical three-degree of freedom dynamic model was investigated. The exact equations of motion of this model were solved using the Floquet-Lipunov method. The equations with time-averaged coefficients were solved by standard eigenanalysis.

  7. How uncertain is model-based prediction of copper loads in stormwater runoff?

    DEFF Research Database (Denmark)

    Lindblom, Erik Ulfson; Ahlman, S.; Mikkelsen, Peter Steen

    2007-01-01

    (runoff volumes and pollutant masses). We use the generalized likelihood uncertainty estimation (GLUE) methodology and generate posterior parameter distributions that result in model outputs encompassing a significant number of the highly variable measurements. Given the applied pollution accumulation......In this paper, we conduct a systematic analysis of the uncertainty related with estimating the total load of pollution (copper) from a separate stormwater drainage system, conditioned on a specific combination of input data, a dynamic conceptual pollutant accumulation-washout model and measurements...

  8. Perceptual load vs. dilution: the roles of attentional focus, stimulus category, and target predictability

    OpenAIRE

    Chen, Zhe; Cave, Kyle R.

    2013-01-01

    Many studies have shown that increasing the number of neutral stimuli in a display decreases distractor interference. This result has been interpreted within two different frameworks; a perceptual load account, based on a reduction in spare resources, and a dilution account, based on a degradation in distractor representation and/or an increase in crosstalk between the distractor and the neutral stimuli that contain visually similar features. In four experiments, we systematically manipulated...

  9. User-Preference-Driven Model Predictive Control of Residential Building Loads and Battery Storage for Demand Response: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Xin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Baker, Kyri A. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Christensen, Dane T. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Isley, Steven C. [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-08-21

    This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility and reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.

  10. The SbSOS1 gene from the extreme halophyte Salicornia brachiata enhances Na+ loading in xylem and confers salt tolerance in transgenic tobacco

    Directory of Open Access Journals (Sweden)

    Yadav Narendra

    2012-10-01

    Full Text Available Abstract Background Soil salinity adversely affects plant growth and development and disturbs intracellular ion homeostasis resulting cellular toxicity. The Salt Overly Sensitive 1 (SOS1 gene encodes a plasma membrane Na+/H+ antiporter that plays an important role in imparting salt stress tolerance to plants. Here, we report the cloning and characterisation of the SbSOS1 gene from Salicornia brachiata, an extreme halophyte. Results The SbSOS1 gene is 3774 bp long and encodes a protein of 1159 amino acids. SbSOS1 exhibited a greater level of constitutive expression in roots than in shoots and was further increased by salt stress. Overexpressing the S. brachiata SbSOS1 gene in tobacco conferred high salt tolerance, promoted seed germination and increased root length, shoot length, leaf area, fresh weight, dry weight, relative water content (RWC, chlorophyll, K+/Na+ ratio, membrane stability index, soluble sugar, proline and amino acid content relative to wild type (WT plants. Transgenic plants exhibited reductions in electrolyte leakage, reactive oxygen species (ROS and MDA content in response to salt stress, which probably occurred because of reduced cytosolic Na+ content and oxidative damage. At higher salt stress, transgenic tobacco plants exhibited reduced Na+ content in root and leaf and higher concentrations in stem and xylem sap relative to WT, which suggests a role of SbSOS1 in Na+ loading to xylem from root and leaf tissues. Transgenic lines also showed increased K+ and Ca2+ content in root tissue compared to WT, which reflect that SbSOS1 indirectly affects the other transporters activity. Conclusions Overexpression of SbSOS1 in tobacco conferred a high degree of salt tolerance, enhanced plant growth and altered physiological and biochemical parameters in response to salt stress. In addition to Na+ efflux outside the plasma membrane, SbSOS1 also helps to maintain variable Na+ content in different organs and also affect the other

  11. The SbSOS1 gene from the extreme halophyte Salicornia brachiata enhances Na(+) loading in xylem and confers salt tolerance in transgenic tobacco.

    Science.gov (United States)

    Yadav, Narendra Singh; Shukla, Pushp Sheel; Jha, Anupama; Agarwal, Pradeep K; Jha, Bhavanath

    2012-10-11

    Soil salinity adversely affects plant growth and development and disturbs intracellular ion homeostasis resulting cellular toxicity. The Salt Overly Sensitive 1 (SOS1) gene encodes a plasma membrane Na(+)/H(+) antiporter that plays an important role in imparting salt stress tolerance to plants. Here, we report the cloning and characterisation of the SbSOS1 gene from Salicornia brachiata, an extreme halophyte. The SbSOS1 gene is 3774 bp long and encodes a protein of 1159 amino acids. SbSOS1 exhibited a greater level of constitutive expression in roots than in shoots and was further increased by salt stress. Overexpressing the S. brachiata SbSOS1 gene in tobacco conferred high salt tolerance, promoted seed germination and increased root length, shoot length, leaf area, fresh weight, dry weight, relative water content (RWC), chlorophyll, K(+)/Na(+) ratio, membrane stability index, soluble sugar, proline and amino acid content relative to wild type (WT) plants. Transgenic plants exhibited reductions in electrolyte leakage, reactive oxygen species (ROS) and MDA content in response to salt stress, which probably occurred because of reduced cytosolic Na(+) content and oxidative damage. At higher salt stress, transgenic tobacco plants exhibited reduced Na(+) content in root and leaf and higher concentrations in stem and xylem sap relative to WT, which suggests a role of SbSOS1 in Na(+) loading to xylem from root and leaf tissues. Transgenic lines also showed increased K(+) and Ca(2+) content in root tissue compared to WT, which reflect that SbSOS1 indirectly affects the other transporters activity. Overexpression of SbSOS1 in tobacco conferred a high degree of salt tolerance, enhanced plant growth and altered physiological and biochemical parameters in response to salt stress. In addition to Na(+) efflux outside the plasma membrane, SbSOS1 also helps to maintain variable Na(+) content in different organs and also affect the other transporters activity indirectly. These

  12. The SbSOS1 gene from the extreme halophyte Salicornia brachiata enhances Na+ loading in xylem and confers salt tolerance in transgenic tobacco

    Science.gov (United States)

    2012-01-01

    Background Soil salinity adversely affects plant growth and development and disturbs intracellular ion homeostasis resulting cellular toxicity. The Salt Overly Sensitive 1 (SOS1) gene encodes a plasma membrane Na+/H+ antiporter that plays an important role in imparting salt stress tolerance to plants. Here, we report the cloning and characterisation of the SbSOS1 gene from Salicornia brachiata, an extreme halophyte. Results The SbSOS1 gene is 3774 bp long and encodes a protein of 1159 amino acids. SbSOS1 exhibited a greater level of constitutive expression in roots than in shoots and was further increased by salt stress. Overexpressing the S. brachiata SbSOS1 gene in tobacco conferred high salt tolerance, promoted seed germination and increased root length, shoot length, leaf area, fresh weight, dry weight, relative water content (RWC), chlorophyll, K+/Na+ ratio, membrane stability index, soluble sugar, proline and amino acid content relative to wild type (WT) plants. Transgenic plants exhibited reductions in electrolyte leakage, reactive oxygen species (ROS) and MDA content in response to salt stress, which probably occurred because of reduced cytosolic Na+ content and oxidative damage. At higher salt stress, transgenic tobacco plants exhibited reduced Na+ content in root and leaf and higher concentrations in stem and xylem sap relative to WT, which suggests a role of SbSOS1 in Na+ loading to xylem from root and leaf tissues. Transgenic lines also showed increased K+ and Ca2+ content in root tissue compared to WT, which reflect that SbSOS1 indirectly affects the other transporters activity. Conclusions Overexpression of SbSOS1 in tobacco conferred a high degree of salt tolerance, enhanced plant growth and altered physiological and biochemical parameters in response to salt stress. In addition to Na+ efflux outside the plasma membrane, SbSOS1 also helps to maintain variable Na+ content in different organs and also affect the other transporters activity indirectly

  13. Effect of loading on unintentional lifting velocity declines during single sets of repetitions to failure during upper and lower extremity muscle actions.

    Science.gov (United States)

    Izquierdo, M; González-Badillo, J J; Häkkinen, K; Ibáñez, J; Kraemer, W J; Altadill, A; Eslava, J; Gorostiaga, E M

    2006-09-01

    The purpose of this study was to examine the effect of different loads on repetition speed during single sets of repetitions to failure in bench press and parallel squat. Thirty-six physical active men performed 1-repetition maximum in a bench press (1 RM (BP)) and half squat position (1 RM (HS)), and performed maximal power-output continuous repetition sets randomly every 10 days until failure with a submaximal load (60 %, 65 %, 70 %, and 75 % of 1RM, respectively) during bench press and parallel squat. Average velocity of each repetition was recorded by linking a rotary encoder to the end part of the bar. The values of 1 RM (BP) and 1 RM (HS) were 91 +/- 17 and 200 +/- 20 kg, respectively. The number of repetitions performed for a given percentage of 1RM was significantly higher (p bench press performance. Average repetition velocity decreased at a greater rate in bench press than in parallel squat. The significant reductions observed in the average repetition velocity (expressed as a percentage of the average velocity achieved during the initial repetition) were observed at higher percentage of the total number of repetitions performed in parallel squat (48 - 69 %) than in bench press (34 - 40 %) actions. The major finding in this study was that, for a given muscle action (bench press or parallel squat), the pattern of reduction in the relative average velocity achieved during each repetition and the relative number of repetitions performed was the same for all percentages of 1RM tested. However, relative average velocity decreased at a greater rate in bench press than in parallel squat performance. This would indicate that in bench press the significant reductions observed in the average repetition velocity occurred when the number of repetitions was over one third (34 %) of the total number of repetitions performed, whereas in parallel squat it was nearly one half (48 %). Conceptually, this would indicate that for a given exercise (bench press or squat) and

  14. Shock loading predictions from application of indicial theory to shock-turbulence interactions

    Science.gov (United States)

    Keefe, Laurence R.; Nixon, David

    1991-01-01

    A sequence of steps that permits prediction of some of the characteristics of the pressure field beneath a fluctuating shock wave from knowledge of the oncoming turbulent boundary layer is presented. The theory first predicts the power spectrum and pdf of the position and velocity of the shock wave, which are then used to obtain the shock frequency distribution, and the pdf of the pressure field, as a function of position within the interaction region. To test the validity of the crucial assumption of linearity, the indicial response of a normal shock is calculated from numerical simulation. This indicial response, after being fit by a simple relaxation model, is used to predict the shock position and velocity spectra, along with the shock passage frequency distribution. The low frequency portion of the shock spectra, where most of the energy is concentrated, is satisfactorily predicted by this method.

  15. Empirical Model Development for Predicting Shock Response on Composite Materials Subjected to Pyroshock Loading. Volume 2, Part 1; Appendices

    Science.gov (United States)

    Gentz, Steven J.; Ordway, David O.; Parsons, David S.; Garrison, Craig M.; Rodgers, C. Steven; Collins, Brian W.

    2015-01-01

    The NASA Engineering and Safety Center (NESC) received a request to develop an analysis model based on both frequency response and wave propagation analyses for predicting shock response spectrum (SRS) on composite materials subjected to pyroshock loading. The model would account for near-field environment (approximately 9 inches from the source) dominated by direct wave propagation, mid-field environment (approximately 2 feet from the source) characterized by wave propagation and structural resonances, and far-field environment dominated by lower frequency bending waves in the structure. This document contains appendices to the Volume I report.

  16. Application of dimensionless sediment rating curves to predict suspended-sediment concentrations, bedload, and annual sediment loads for rivers in Minnesota

    Science.gov (United States)

    Ellison, Christopher A.; Groten, Joel T.; Lorenz, David L.; Koller, Karl S.

    2016-10-27

    variety of basin sizes and flow regimes than DSRC models developed using data collected for Pagosa Springs, Colorado. Minnesota DSRC models retained a substantial portion of the unique sediment signatures for most rivers, although deviations were observed for streams with limited sediment supply and for rivers in southeastern Minnesota, which had markedly larger regression exponents. Compared to Pagosa Springs DSRC models, Minnesota DSRC models had regression slopes that more closely matched the slopes of site-specific regression models, had greater Nash-Sutcliffe Efficiency values, had lower model biases, and approximated measured annual sediment loads more closely. The results presented in this report indicate that regionally based DSRCs can be used to estimate reasonably accurate values of SSC and bedload.Practitioners are cautioned that DSRC reliability is dependent on representative measures of bankfull streamflow, SSC, and bedload. It is, therefore, important that samples of SSC and bedload, which will be used for estimating SSC and bedload at the bankfull streamflow, are collected over a range of conditions that includes the ascending and descending limbs of the event hydrograph. The use of DSRC models may have substantial limitations for certain conditions. For example, DSRC models should not be used to predict SSC and sediment loads for extreme streamflows, such as those that exceed twice the bankfull streamflow value because this constitutes conditions beyond the realm of current (2016) empirical modeling capability. Also, if relations between SSC and streamflow and between bedload and streamflow are not statistically significant, DSRC models should not be used to predict SSC or bedload, as this could result in large errors. For streams that do not violate these conditions, DSRC estimates of SSC and bedload can be used for stream restoration planning and design, and for estimating annual sediment loads for streams where little or no sediment data are available.

  17. Impact of Madden–Julian Oscillation upon Winter Extreme Rainfall in Southern China: Observations and Predictability in CFSv2

    OpenAIRE

    Hong-Li Ren; Pengfei Ren

    2017-01-01

    The impact of Madden–Julian oscillation (MJO) upon extreme rainfall in southern China was studied using the Real-time Multivariate MJO (RMM) index and daily precipitation data from high-resolution stations in China. The probability-distribution function (PDF) of November–March rainfall in southern China was found to be skewed toward larger (smaller) values in phases 2–3 (6–7) of MJO, during which the probability of extreme rainfall events increased (reduced) by 30–50% (20–40%) relative to all...

  18. Lifetime prediction of structures submitted to thermal fatigue loadings; Prediction de duree de vie de structures sous chargement de fatigue thermique

    Energy Technology Data Exchange (ETDEWEB)

    Amiable, S

    2006-01-15

    The aim of this work is to predict the lifetime of structures submitted to thermal fatigue loadings. This work lies within the studies undertaken by the CEA on the thermal fatigue problems from the french reactor of Civaux. In particular we study the SPLASH test: a specimen is heated continuously and cyclically cooled down by a water spray. This loading generates important temperature gradients in space and time and leads to the initiation and the propagation of a crack network. We propose a new thermo-mechanical model to simulate the SPLASH experiment and we propose a new fatigue criterion to predict the lifetime of the SPLASH specimen. We propose and compare several numerical models with various complexity to estimate the mechanical response of the SPLASH specimen. The practical implications of this work are the reevaluation of the hypothesis used in the French code RCC, which are used to simulate thermal shock and to interpret the results in terms of fatigue. This work leads to new perspectives on the mechanical interpretation of the fatigue criterion. (author)

  19. Different Predictive Control Strategies for Active Load Management in Distributed Power Systems with High Penetration of Renewable Energy Sources

    DEFF Research Database (Denmark)

    Zong, Yi; Bindner, Henrik W.; Gehrke, Oliver

    2013-01-01

    In order to achieve a Danish energy supply based on 100% renewable energy from combinations of wind, biomass, wave and solar power in 2050 and to cover 50% of the Danish electricity consumption by wind power in 2020, it requires more renewable energy in buildings and industries (e.g. cold stores......, greenhouses, etc.), and to coordinate the management of large numbers of distributed energy resources with the smart grid solution. This paper presents different predictive control (Genetic Algorithm-based and Model Predictive Control-based) strategies that schedule controlled loads in the industrial...... and residential sectors, based on dynamic power price and weather forecast, considering users’ comfort settings to meet an optimization objective, such as maximum profit or minimum energy consumption. Some field tests were carried out on a facility for intelligent, active and distributed power systems, which...

  20. Multivariable predictive control considering time delay for load-frequency control in multi-area power systems

    Directory of Open Access Journals (Sweden)

    Daniar Sabah

    2016-12-01

    Full Text Available In this paper, a multivariable model based predictive control (MPC is proposed for the solution of load frequency control (LFC in a multi-area interconnected power system. The proposed controller is designed to consider time delay, generation rate constraint and multivariable nature of the LFC system, simultaneously. A new formulation of the MPC is presented to compensate time delay. The generation rate constraint is considered by employing a constrained MPC and economic allocation of the generation is further guaranteed by an innovative modification in the predictive control objective function. The effectiveness of proposed scheme is verified through time-based simulations on the standard 39-bus test system and the responses are then compared with the proportional-integral controller. The evaluation of the results reveals that the proposed control scheme offers satisfactory performance with fast responses.

  1. Prediction of regular wave loads on a fixed offshore oscillating water column-wave energy converter using CFD

    Directory of Open Access Journals (Sweden)

    Ahmed Elhanafi

    2016-12-01

    Full Text Available In this paper, hydrodynamic wave loads on an offshore stationary–floating oscillating water column (OWC are investigated via a 2D and 3D computational fluid dynamics (CFD modeling based on the RANS equations and the VOF surface capturing scheme. The CFD model is validated against previous experiments for nonlinear regular wave interactions with a surface-piercing stationary barge. Following the validation stage, the numerical model is modified to consider the pneumatic damping effect, and an extensive campaign of numerical tests is carried out to study the wave–OWC interactions for different wave periods, wave heights and pneumatic damping factors. It is found that the horizontal wave force is usually larger than the vertical one. Also, there a direct relationship between the pneumatic and hydrodynamic vertical forces with a maximum vertical force almost at the device natural frequency, whereas the pneumatic damping has a little effect on the horizontal force. Additionally, simulating the turbine damping with an orifice plate induces higher vertical loads than utilizing a slot opening. Furthermore, 3D modeling significantly escalates and declines the predicted hydrodynamic vertical and horizontal wave loads, respectively.

  2. A Sensorless Predictive Current Controlled Boost Converter by Using an EKF with Load Variation Effect Elimination Function.

    Science.gov (United States)

    Tong, Qiaoling; Chen, Chen; Zhang, Qiao; Zou, Xuecheng

    2015-04-28

    To realize accurate current control for a boost converter, a precise measurement of the inductor current is required to achieve high resolution current regulating. Current sensors are widely used to measure the inductor current. However, the current sensors and their processing circuits significantly contribute extra hardware cost, delay and noise to the system. They can also harm the system reliability. Therefore, current sensorless control techniques can bring cost effective and reliable solutions for various boost converter applications. According to the derived accurate model, which contains a number of parasitics, the boost converter is a nonlinear system. An Extended Kalman Filter (EKF) is proposed for inductor current estimation and output voltage filtering. With this approach, the system can have the same advantages as sensored current control mode. To implement EKF, the load value is necessary. However, the load may vary from time to time. This can lead to errors of current estimation and filtered output voltage. To solve this issue, a load variation elimination effect elimination (LVEE) module is added. In addition, a predictive average current controller is used to regulate the current. Compared with conventional voltage controlled system, the transient response is greatly improved since it only takes two switching cycles for the current to reach its reference. Finally, experimental results are presented to verify the stable operation and output tracking capability for large-signal transients of the proposed algorithm.

  3. Predicting runoff induced mass loads in urban watersheds: Linking land use and pyrethroid contamination.

    Science.gov (United States)

    Chinen, Kazue; Lau, Sim-Lin; Nonezyan, Michael; McElroy, Elizabeth; Wolfe, Becky; Suffet, Irwin H; Stenstrom, Michael K

    2016-10-01

    Pyrethroid pesticide mass loadings in the Ballona Creek Watershed were calculated using the volume-concentration method with a Geographic Information Systems (GIS) to explore potential relationships between urban land use, impervious surfaces, and pyrethroid runoff flowing into an urban stream. A calibration of the GIS volume-concentration model was performed using 2013 and 2014 wet-weather sampling data. Permethrin and lambda-cyhalothrin were detected as the highest concentrations; deltamethrin, lambda-cyhalothrin, permethrin and cyfluthrin were the most frequently detected synthetic pyrethroids. Eight neighborhoods within the watershed were highlighted as target areas based on a Weighted Overlay Analysis (WOA) in GIS. Water phase concentration of synthetic pyrethroids (SPs) were calculated from the reported usage. The need for stricter BMP and consumer product controls was identified as a possible way of reducing the detections of pyrethroids in Ballona Creek. This model has significant implications for determining mass loadings due to land use influence, and offers a flexible method to extrapolate data for a limited amount of samplings for a larger watershed, particularly for chemicals that are not subject to environmental monitoring. Offered as a simple approach to watershed management, the GIS-volume concentration model has the potential to be applied to other target pesticides and is useful for simulating different watershed scenarios. Further research is needed to compare results against other similar urban watersheds situated in mediterranean climates. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Flight Loads Prediction of High Aspect Ratio Wing Aircraft Using Multibody Dynamics

    Directory of Open Access Journals (Sweden)

    Michele Castellani

    2016-01-01

    Full Text Available A framework based on multibody dynamics has been developed for the static and dynamic aeroelastic analyses of flexible high aspect ratio wing aircraft subject to structural geometric nonlinearities. Multibody dynamics allows kinematic nonlinearities and nonlinear relationships in the forces definition and is an efficient and promising methodology to model high aspect ratio wings, which are known to be prone to structural nonlinear effects because of the high deflections in flight. The multibody dynamics framework developed employs quasi-steady aerodynamics strip theory and discretizes the wing as a series of rigid bodies interconnected by beam elements, representative of the stiffness distribution, which can undergo arbitrarily large displacements and rotations. The method is applied to a flexible high aspect ratio wing commercial aircraft and both trim and gust response analyses are performed in order to calculate flight loads. These results are then compared to those obtained with the standard linear aeroelastic approach provided by the Finite Element Solver Nastran. Nonlinear effects come into play mainly because of the need of taking into account the large deflections of the wing for flight loads computation and of considering the aerodynamic forces as follower forces.

  5. Unsteady flow damping force prediction of MR dampers subjected to sinusoidal loading

    Science.gov (United States)

    Yu, M.; Wang, S. Q.; Fu, J.; Peng, Y. X.

    2013-02-01

    So far quasi-steady models are usually used to design magnetorheological (MR) dampers, but these models are not sufficient to describe the MR damper behavior under unsteady dynamic loading, for fluid inertia is neglected in quasi-steady models, which will bring more error between computer simulation and experimental results. Under unsteady flow model, the fluid inertia terms will bring error calculated upto 10%, so it is necessary to be considered in the governing equation. In this paper, force-stroke behavior of MR damper with flow mode due to sinusoidal loading excitation is mainly investigated, to simplify the analysis, the one-dimensional axisymmetric annular duct geometry of MR dampers is approximated as a rectangular duct. The rectangular duct can be divided into 3 regions for the velocity profile of the incompressible MR fluid flow, in each region, a partial differential equation is composed of by Navier-Stokes equations, boundary conditions and initial conditions to determine the velocity solution. In addition, in this work, not only Bingham plastic model but the Herschel—Bulkley model is adopted to analyze the MR damper performance. The damping force resulting from the pressure drop of unsteady MR dampers can be obtained and used to design or size MR dampers. Compared with the quasi-steady flow damping force, the damping force of unsteady MR dampers is more close to practice, particularly for the high-speed unsteady movement of MR dampers.

  6. Unsteady flow damping force prediction of MR dampers subjected to sinusoidal loading

    International Nuclear Information System (INIS)

    Yu, M; Fu, J; Wang, S Q; Peng, Y X

    2013-01-01

    So far quasi-steady models are usually used to design magnetorheological (MR) dampers, but these models are not sufficient to describe the MR damper behavior under unsteady dynamic loading, for fluid inertia is neglected in quasi-steady models, which will bring more error between computer simulation and experimental results. Under unsteady flow model, the fluid inertia terms will bring error calculated upto 10%, so it is necessary to be considered in the governing equation. In this paper, force-stroke behavior of MR damper with flow mode due to sinusoidal loading excitation is mainly investigated, to simplify the analysis, the one-dimensional axisymmetric annular duct geometry of MR dampers is approximated as a rectangular duct. The rectangular duct can be divided into 3 regions for the velocity profile of the incompressible MR fluid flow, in each region, a partial differential equation is composed of by Navier-Stokes equations, boundary conditions and initial conditions to determine the velocity solution. In addition, in this work, not only Bingham plastic model but the Herschel—Bulkley model is adopted to analyze the MR damper performance. The damping force resulting from the pressure drop of unsteady MR dampers can be obtained and used to design or size MR dampers. Compared with the quasi-steady flow damping force, the damping force of unsteady MR dampers is more close to practice, particularly for the high-speed unsteady movement of MR dampers.

  7. Using Data Mining Approaches for Force Prediction of a Dynamically Loaded Flexible Structure

    DEFF Research Database (Denmark)

    Schlechtingen, Meik; Achiche, Sofiane; Lourenco Costa, Tiago

    2014-01-01

    -deterministic excitation forces with different excitation frequencies and amplitudes. Additionally, the influence of the sampling frequency and sensor location on the model performance is investigated. The results obtained in this paper show that most data mining approaches can be used, when a certain degree of inaccuracy...... of freedom and a force transducer for validation and training. The models are trained using data obtained from applying a random excitation force on the flexible structure. The performance of the developed models is evaluated by analyzing the prediction capabilities based on a normalized prediction error...

  8. Fatigue and extreme wave loads on bottom fixed offshore wind turbines. Effects from fully nonlinear wave forcing on the structural dynamics

    DEFF Research Database (Denmark)

    Schløer, Signe

    2013-01-01

    wind farms. As wind farms are being moved further offshore the wave loads become larger compared to the wind loads and therefore more important in the design of offshore wind turbines. Yet, the water depth is still only shallow or intermediate where the waves should be described by nonlinear irregular...

  9. Prediction of storm transfers and annual loads with data-based mechanistic models using high-frequency data

    Science.gov (United States)

    Ockenden, Mary C.; Tych, Wlodek; Beven, Keith J.; Collins, Adrian L.; Evans, Robert; Falloon, Peter D.; Forber, Kirsty J.; Hiscock, Kevin M.; Hollaway, Michael J.; Kahana, Ron; Macleod, Christopher J. A.; Villamizar, Martha L.; Wearing, Catherine; Withers, Paul J. A.; Zhou, Jian G.; Benskin, Clare McW. H.; Burke, Sean; Cooper, Richard J.; Freer, Jim E.; Haygarth, Philip M.

    2017-12-01

    Excess nutrients in surface waters, such as phosphorus (P) from agriculture, result in poor water quality, with adverse effects on ecological health and costs for remediation. However, understanding and prediction of P transfers in catchments have been limited by inadequate data and over-parameterised models with high uncertainty. We show that, with high temporal resolution data, we are able to identify simple dynamic models that capture the P load dynamics in three contrasting agricultural catchments in the UK. For a flashy catchment, a linear, second-order (two pathways) model for discharge gave high simulation efficiencies for short-term storm sequences and was useful in highlighting uncertainties in out-of-bank flows. A model with non-linear rainfall input was appropriate for predicting seasonal or annual cumulative P loads where antecedent conditions affected the catchment response. For second-order models, the time constant for the fast pathway varied between 2 and 15 h for all three catchments and for both discharge and P, confirming that high temporal resolution data are necessary to capture the dynamic responses in small catchments (10-50 km2). The models led to a better understanding of the dominant nutrient transfer modes, which will be helpful in determining phosphorus transfers following changes in precipitation patterns in the future.

  10. Prediction of a Densely Loaded Particle-Laden Jet using a Euler-Lagrange Dense Spray Model

    Science.gov (United States)

    Pakseresht, Pedram; Apte, Sourabh V.

    2017-11-01

    Modeling of a dense spray regime using an Euler-Lagrange discrete-element approach is challenging because of local high volume loading. A subgrid cluster of droplets can lead to locally high void fractions for the disperse phase. Under these conditions, spatio-temporal changes in the carrier phase volume fractions, which are commonly neglected in spray simulations in an Euler-Lagrange two-way coupling model, could become important. Accounting for the carrier phase volume fraction variations, leads to zero-Mach number, variable density governing equations. Using pressure-based solvers, this gives rise to a source term in the pressure Poisson equation and a non-divergence free velocity field. To test the validity and predictive capability of such an approach, a round jet laden with solid particles is investigated using Direct Numerical Simulation and compared with available experimental data for different loadings. Various volume fractions spanning from dilute to dense regimes are investigated with and without taking into account the volume displacement effects. The predictions of the two approaches are compared and analyzed to investigate the effectiveness of the dense spray model. Financial support was provided by National Aeronautics and Space Administration (NASA).

  11. Prediction of Vertical-Plane Wave Loading and Ship Responses in High Seas

    DEFF Research Database (Denmark)

    Wang, Z.; Xia, J.; Jensen, Jørgen Juncher

    2000-01-01

    The non-linearities in wave- and slamming-induced rigid-body motions and structural responses of ships such as heave, pitch and vertical bending moments are consistently investigated based on a rational time-domain strip method. A hydrodynamic model for predicting sectional green water force is a...

  12. Mutational and putative neoantigen load predict clinical benefit of adoptive T cell therapy in melanoma

    DEFF Research Database (Denmark)

    Lauss, Martin; Donia, Marco; Harbst, Katja

    2017-01-01

    Adoptive T-cell therapy (ACT) is a highly intensive immunotherapy regime that has yielded remarkable response rates and many durable responses in clinical trials in melanoma; however, 50-60% of the patients have no clinical benefit. Here, we searched for predictive biomarkers to ACT in melanoma. ...

  13. Design of a model predictive load-following controller by discrete optimization of control rod speed for PWRs

    International Nuclear Information System (INIS)

    Kim, Jae Hwan; Park, Soon Ho; Na, Man Gyun

    2014-01-01

    Highlights: • A model predictive controller for load-following operation was developed. • Genetic algorithm optimizes the five nonlinear discrete control rod speeds. • The boron concentration is adjusted with automatic adjustment logic. • The proposed controller reflects the realistic control rod drive mechanism movement. • The performance was confirmed to be satisfactory by simulation from BOC to EOC. - Abstract: Currently, most existing nuclear power plants alter the reactor power by adjusting the boron concentration in the coolant because it has a smaller effect on the reactor power distribution. Frequent control rod movements for load-following operation induce xenon-oscillation. Therefore, a controller that can subdue this phenomenon effectively is needed. At an APR1400 nuclear power plant which is a pressurized water reactor (PWR), the reactor power is controlled automatically using a Reactor Regulating System (RRS) but the power distribution is controlled manually by operators. Therefore, for APR+ nuclear power plants which is an improved version of APR1400 nuclear reactor, a new concept of a reactor controller is needed to control both the reactor power and power distribution automatically. The model predictive control (MPC) method is applicable to multiple-input multiple-output control, and can be applied for complex and nonlinear systems, such as the nuclear power plants. In this study, an MPC controller was developed by applying a genetic algorithm to optimize the discrete control rod speeds and by reflecting the realistic movement of the control rod drive mechanism that moves at only five discrete speeds. The performance of the proposed controller was confirmed to be satisfactory by simulating the load-following operation of an APR+ nuclear power plant through interface with KISPAC-1D code

  14. Prediction of Spring Rate and Initial Failure Load due to Material Properties of Composite Leaf Spring

    International Nuclear Information System (INIS)

    Oh, Sung Ha; Choi, Bok Lok

    2014-01-01

    This paper presented analysis methods for adapting E-glass fiber/epoxy composite (GFRP) materials to an automotive leaf spring. It focused on the static behaviors of the leaf spring due to the material composition and its fiber orientation. The material properties of the GFRP composite were directly measured based on the ASTM standard test. A reverse implementation was performed to obtain the complete set of in-situ fiber and matrix properties from the ply test results. Next, the spring rates of the composite leaf spring were examined according to the variation of material parameters such as the fiber angles and resin contents of the composite material. Finally, progressive failure analysis was conducted to identify the initial failure load by means of an elastic stress analysis and specific damage criteria. As a result, it was found that damage first occurred along the edge of the leaf spring owing to the shear stresses

  15. Power and loads for wind turbines in yawed conditions. Analysis of field measurements and aerodynamic predictions

    Energy Technology Data Exchange (ETDEWEB)

    Boorsma, K. [ECN Wind Energy, Petten (Netherlands)

    2012-11-15

    A description is given of the work carried out within the framework of the FLOW (Far and Large Offshore Wind) project on single turbine performance in yawed flow conditions. Hereto both field measurements as well as calculations with an aerodynamic code are analyzed. The rotors of horizontal axis wind turbines follow the changes in the wind direction for optimal performance. The reason is that the power is expected to decrease for badly oriented rotors. So, insight in the effects of the yaw angle on performance is important for optimization of the yaw control of each individual turbine. The effect of misalignment on performance and loads of a single 2.5 MW wind turbine during normal operation is investigated. Hereto measurements at the ECN Wind Turbine Test Site Wieringermeer (EWTW) are analyzed from December 2004 until April 2009. Also, the influence of yaw is studied using a design code and results from this design code are compared with wind tunnel measurements.

  16. Evaluation of the constant pressure panel method (CPM) for unsteady air loads prediction

    Science.gov (United States)

    Appa, Kari; Smith, Michael J. C.

    1988-01-01

    This paper evaluates the capability of the constant pressure panel method (CPM) code to predict unsteady aerodynamic pressures, lift and moment distributions, and generalized forces for general wing-body configurations in supersonic flow. Stability derivatives are computed and correlated for the X-29 and an Oblique Wing Research Aircraft, and a flutter analysis is carried out for a wing wind tunnel test example. Most results are shown to correlate well with test or published data. Although the emphasis of this paper is on evaluation, an improvement in the CPM code's handling of intersecting lifting surfaces is briefly discussed. An attractive feature of the CPM code is that it shares the basic data requirements and computational arrangements of the doublet lattice method. A unified code to predict unsteady subsonic or supersonic airloads is therefore possible.

  17. Inelastic spectra to predict period elongation of structures under earthquake loading

    DEFF Research Database (Denmark)

    Katsanos, Evangelos; Sextos, A.G.

    2015-01-01

    Period lengthening, exhibited by structures when subjected to strong ground motions, constitutes an implicit proxy of structural inelasticity and associated damage. However, the reliable prediction of the inelastic period is tedious and a multi-parametric task, which is related to both epistemic ...... for period lengthening as a function of Ry and Tel. These equations may be used in the framework of the earthquake record selection and scaling....

  18. Predicting the Failure of Aluminum Exposed to Simulated Fire and Mechanical Loading Using Finite Element Modeling

    OpenAIRE

    Arthur, Katherine Marie

    2011-01-01

    The interest in the use of aluminum as a structural material in marine applications has increased greatly in recent years. This increase is primarily due to the low weight of aluminum compared to other structural materials as well as its ability to resist corrosion. However, a critical issue in the use of any structural material for naval applications is its response to fire. Past experience has shown that finite element programs can produce accurate predictions of failure of structural c...

  19. Development of Predictive Models of Injury for the Lower Extremity, Lumbar, and Thoracic Spine after discharge from Physical Rehabilitation

    Science.gov (United States)

    2017-10-01

    prediction models will vary by age and sex . Hypothesis 3: A multi-factorial prediction model that accurately predicts risk of new and recurring injuries, as...cleared to return to duty from an injury is of great importance. The purpose of this project is to determine if performance on a battery of...balance screens, measures of power, demographic data and biopsychosocial measures. • Injury data will be collected through self -report, profile data, and

  20. On the use of non-Gaussian models for prediction of extreme pollution levels in environmental studies

    Science.gov (United States)

    Berg, D. B.; Medvedev, A. N.; Sergeev, A. P.; Taubayev, A. A.

    2015-11-01

    The aim of this work is to study the distribution of contamination at the territory on the data of snow samples analysis, in order to find an approach to forecasting of the extreme pollution levels. The hypothesis of normal distribution of the values of pollution index (the intensity of dust fallout on the territory, mg /m2/day) is not confirmed on the results of statistical analysis of the data for six different experimental sites (from 81 to 256 values of the index for each site). For the set of 243 values of the pollution index at the territory of a city, there is made an attempt of forecast of its possible extreme values not detected on the results of the snow sampling. For this, the linear dependence "pollution index - the number of points with the given pollution index" built in double logarithmic coordinates, is extrapolated into the area of high values of the pollution index.

  1. Observations and predictions of wave runup, extreme water levels, and medium-term dune erosion during storm conditions

    OpenAIRE

    Suanez , Serge ,; Cancouët , Romain; Floc'h , France; Blaise , Emmanuel; Ardhuin , Fabrice; Filipot , Jean-François; Cariolet , Jean-Marie; Delacourt , Christophe

    2015-01-01

    Monitoring of dune erosion and accretion on the high-energy macrotidal Vougot beach in North Brittany (France) over the past decade (2004–2014) has revealed significant morphological changes. Dune toe erosion/accretion records have been compared with extreme water level measurements, defined as the sum of (i) astronomic tide; (ii) storm surge; and (iii) vertical wave runup. Runup parameterization was conducted using swash limits, beach profiles, and hydrodynamic (Hm0, Tm0,–1, and high tide wa...

  2. Observations and Predictions of Wave Runup, Extreme Water Levels, and Medium-Term Dune Erosion during Storm Conditions

    Directory of Open Access Journals (Sweden)

    Serge Suanez

    2015-07-01

    Full Text Available Monitoring of dune erosion and accretion on the high-energy macrotidal Vougot beach in North Brittany (France over the past decade (2004–2014 has revealed significant morphological changes. Dune toe erosion/accretion records have been compared with extreme water level measurements, defined as the sum of (i astronomic tide; (ii storm surge; and (iii vertical wave runup. Runup parameterization was conducted using swash limits, beach profiles, and hydrodynamic (Hm0, Tm0,–1, and high tide water level—HTWL data sets obtained from high frequency field surveys. The aim was to quantify in-situ environmental conditions and dimensional swash parameters for the best calibration of Battjes [1] runup formula. In addition, an empirical equation based on observed tidal water level and offshore wave height was produced to estimate extreme water levels over the whole period of dune morphological change monitoring. A good correlation between this empirical equation (1.01Hmoξo and field runup measurements (Rmax was obtained (R2 85%. The goodness of fit given by the RMSE was about 0.29 m. A good relationship was noticed between dune erosion and high water levels when the water levels exceeded the dune foot elevation. In contrast, when extreme water levels were below the height of the toe of the dune sediment budget increased, inducing foredune recovery. These erosion and accretion phases may be related to the North Atlantic Oscillation Index.

  3. A novel modeling to predict the critical current behavior of Nb$_{3}$Sn PIT strand under transverse load based on a scaling law and Finite Element Analysis

    CERN Document Server

    Wang, Tiening; Takayasu, Makoto; Bordini, Bernardo

    2014-01-01

    Superconducting Nb$_{3}$Sn Powder-In-Tube (PIT) strands could be used for the superconducting magnets of the next generation Large Hadron Collider. The strands are cabled into the typical flat Rutherford cable configuration. During the assembly of a magnet and its operation the strands experience not only longitudinal but also transverse load due to the pre-compression applied during the assembly and the Lorentz load felt when the magnets are energized. To properly design the magnets and guarantee their safe operation, mechanical load effects on the strand superconducting properties are studied extensively; particularly, many scaling laws based on tensile load experiments have been established to predict the critical current dependence on strain. However, the dependence of the superconducting properties on transverse load has not been extensively studied so far. One of the reasons is that transverse loading experiments are difficult to conduct due to the small diameter of the strand (about 1 mm) and the data ...

  4. Literature Review for Texas Department of Transportation Research Project 0-4695: Guidance for Design in Areas of Extreme Bed-Load Mobility, Edwards Plateau, Texas

    National Research Council Canada - National Science Library

    Heitmuller, Franklin T; Asquith, William H; Fang, Xing; Thompson, David B; Wang, Keh-Han

    2005-01-01

    A review of the literature addressing sediment transport in gravel-bed river systems and structures designed to control bed-load mobility is provided as part of Texas Department of Transportation research project 0-4695...

  5. Prediction Models for Plutonium, Strontium, Uranium and Neptunium Loading onto Monosodium Titanate (MST)

    International Nuclear Information System (INIS)

    Fondeur, F. F.; Hobbs, D. T.; Barnes, M. J.; Peters, T. B.; Fink, S. D.

    2005-01-01

    The DA isotherm parameters for U, Pu, Sr and Np have been updated to include additional data obtained since the original derivation. The DA isotherms were modified to include a kinetic function derived by Rahn to describe sorbate loading from the beginning of sorption up to equilibrium. The final functions describe both kinetic and thermodynamic sorption. We selected the Rahn function to describe radionuclide sorption because it originates from diffusion and absorption controlled sorption. An investigation of the thermal behavior of radionuclide sorption on MST as shown by this data revealed the sorption process is diffusion (or transport) controlled (in solution). Transport in solution can in theory be accelerated by vigorous mixing but the range of available mixing speed in the facility design will probably not be sufficient to markedly increase radionuclide sorption rate on MST from diffusion-controlled sorption. The laboratory studies included mixing energies hydraulically-scaled to match those of the Actinide Removal Process and these likely approximate the range of energies available in the Salt Waste Processing Facility

  6. Unbalance Response Prediction for Rotors on Ball Bearings Using Speed and Load Dependent Nonlinear Bearing Stiffness

    Science.gov (United States)

    Fleming, David P.; Poplawski, J. V.

    2003-01-01

    Rolling-element bearing forces vary nonlinearly with bearing deflection. Thus an accurate rotordynamic analysis requires that bearing forces corresponding to the actual bearing deflection be utilized. For this work bearing forces were calculated by COBRA-AHS, a recently developed rolling-element bearing analysis code. Bearing stiffness was found to be a strong function of bearing deflection, with higher deflection producing markedly higher stiffness. Curves fitted to the bearing data for a range of speeds and loads were supplied to a flexible rotor unbalance response analysis. The rotordynamic analysis showed that vibration response varied nonlinearly with the amount of rotor imbalance. Moreover, the increase in stiffness as critical speeds were approached caused a large increase in rotor and bearing vibration amplitude over part of the speed range compared to the case of constant bearing stiffness. Regions of bistable operation were possible, in which the amplitude at a given speed was much larger during rotor acceleration than during deceleration. A moderate amount of damping will eliminate the bistable region, but this damping is not inherent in ball bearings.

  7. Multilevel microvibration test for performance predictions of a space optical load platform

    Science.gov (United States)

    Li, Shiqi; Zhang, Heng; Liu, Shiping; Wang, Yue

    2018-05-01

    This paper presents a framework for the multilevel microvibration analysis and test of a space optical load platform. The test framework is conducted on three levels, including instrument, subsystem, and system level. Disturbance source experimental investigations are performed to evaluate the vibration amplitude and study vibration mechanism. Transfer characteristics of space camera are validated by a subsystem test, which allows the calculation of transfer functions from various disturbance sources to optical performance outputs. In order to identify the influence of the source on the spacecraft performance, a system level microvibration measurement test has been performed on the ground. From the time domain analysis and spectrum analysis of multilevel microvibration tests, we concluded that the disturbance source has a significant effect on its installation position. After transmitted through mechanical links, the residual vibration reduces to a background noise level. In addition, the angular microvibration of the platform jitter is mainly concentrated in the rotation of y-axes. This work is applied to a real practical application involving the high resolution satellite camera system.

  8. Perceptual load vs. dilution: the roles of attentional focus, stimulus category, and target predictability

    Directory of Open Access Journals (Sweden)

    Zhe eChen

    2013-06-01

    Full Text Available Many studies have shown that increasing the number of neutral stimuli in a display decreases distractor interference. This result has been interpreted within two different frameworks; a perceptual load account, based on a reduction in spare resources, and a dilution account, based on a degradation in distractor representation and/or an increase in crosstalk between the distractor and the neutral stimuli that contain visually similar features. In four experiments, we systematically manipulated the extent of attentional focus, stimulus category, and preknowledge of the target to examine how these factors would interact with the display set size to influence the degree of distractor processing. Display set size did not affect the degree of distractor processing in all situations. Increasing the number of neutral items decreased distractor processing only when a task induced a broad attentional focus that included the neutral stimuli, when the neutral stimuli were in the same category as the target and distractor, and when the preknowledge of the target was insufficient to guide attention to the target efficiently. These results suggest that the effect of neutral stimuli on the degree of distractor processing is more complex than previously assumed. They provide new insight into the competitive interactions between bottom-up and top-down processes that govern the efficiency of visual selective attention.

  9. Perceptual load vs. dilution: the roles of attentional focus, stimulus category, and target predictability.

    Science.gov (United States)

    Chen, Zhe; Cave, Kyle R

    2013-01-01

    Many studies have shown that increasing the number of neutral stimuli in a display decreases distractor interference. This result has been interpreted within two different frameworks; a perceptual load account, based on a reduction in spare resources, and a dilution account, based on a degradation in distractor representation and/or an increase in crosstalk between the distractor and the neutral stimuli that contain visually similar features. In four experiments, we systematically manipulated the extent of attentional focus, stimulus category, and preknowledge of the target to examine how these factors would interact with the display set size to influence the degree of distractor processing. Display set size did not affect the degree of distractor processing in all situations. Increasing the number of neutral items decreased distractor processing only when a task induced a broad attentional focus that included the neutral stimuli, when the neutral stimuli were in the same category as the target and distractor, and when the preknowledge of the target was insufficient to guide attention to the target efficiently. These results suggest that the effect of neutral stimuli on the degree of distractor processing is more complex than previously assumed. They provide new insight into the competitive interactions between bottom-up and top-down processes that govern the efficiency of visual selective attention.

  10. Load Torque Compensator for Model Predictive Direct Current Control in High Power PMSM Drive Systems

    DEFF Research Database (Denmark)

    Preindl, Matthias; Schaltz, Erik

    2010-01-01

    In drive systems the most used control structure is the cascade control with an inner torque, i.e. current and an outer speed control loop. The fairly small converter switching frequency in high power applications, e.g. wind turbines lead to modest speed control performance. An improvement bring...... the use of a current controller which takes into account the discrete states of the inverter, e.g. DTC or a more modern approach: Model Predictive Direct Current Control (MPDCC). Moreover overshoots and oscillations in the speed are not desired in many applications, since they lead to mechanical stress...

  11. A Distributed Model Predictive Control approach for the integration of flexible loads, storage and renewables

    DEFF Research Database (Denmark)

    Ferrarini, Luca; Mantovani, Giancarlo; Costanzo, Giuseppe Tommaso

    2014-01-01

    This paper presents an innovative solution based on distributed model predictive controllers to integrate the control and management of energy consumption, energy storage, PV and wind generation at customer side. The overall goal is to enable an advanced prosumer to autoproduce part of the energy...... he needs with renewable sources and, at the same time, to optimally exploit the thermal and electrical storages, to trade off its comfort requirements with different pricing schemes (including real-time pricing), and apply optimal control techniques rather than sub-optimal heuristics....

  12. Contribution to life-time predictions of gas turbine components under cyclic load

    Energy Technology Data Exchange (ETDEWEB)

    Hoelscher, R.

    1982-02-15

    The low cycle fatique life of gas turbine components is analysed using the turbine blade of the ATAR 101 F jet engine turbine as example. The results show that, among other things thermal stresses during start-up and shut-off cause considerable damage to the material. Tests using a model rig showed that damage caused by material creep and LCF-mechanisms stongly depended on cyclic parameters such as temperature, temperature development, and power etc. Two long-term tests confirm that the Manson model can be used to give a reasonable prediction of turbine blade life.

  13. Muscle Strength Is a Poor Screening Test for Predicting Lower Extremity Injuries in Professional Male Soccer Players: A 2-Year Prospective Cohort Study.

    Science.gov (United States)

    Bakken, Arnhild; Targett, Stephen; Bere, Tone; Eirale, Cristiano; Farooq, Abdulaziz; Mosler, Andrea B; Tol, Johannes L; Whiteley, Rod; Khan, Karim M; Bahr, Roald

    2018-03-01

    Lower extremity muscle strength tests are commonly used to screen for injury risk in professional soccer. However, there is limited evidence on the ability of such tests in predicting future injuries. To examine the association between hip and thigh muscle strength and the risk of lower extremity injuries in professional male soccer players. Case-control study; Level of evidence, 3. Professional male soccer players from 14 teams in Qatar underwent a comprehensive strength assessment at the beginning of the 2013/2014 and 2014/2015 seasons. Testing consisted of concentric and eccentric quadriceps and hamstring isokinetic peak torques, eccentric hip adduction and abduction forces, and bilateral isometric adductor force (squeeze test at 45°). Time-loss injuries and exposure in training and matches were registered prospectively by club medical staff throughout each season. Univariate and multivariate Cox regression analyses were used to calculate hazard ratios (HRs) with 95% CIs. In total, 369 players completed all strength tests and had registered injury and exposure data. Of these, 206 players (55.8%) suffered 538 lower extremity injuries during the 2 seasons; acute muscle injuries were the most frequent. Of the 20 strength measures examined, greater quadriceps concentric peak torque at 300 deg/s (HR, 1.005 [95% CI, 1.00-1.01]; P = .037) was the only strength measure identified as significantly associated with a risk of lower extremity injuries in multivariate analysis. Greater quadriceps concentric peak torque at 60 deg/s (HR, 1.004 [95% CI, 1.00-1.01]; P = .026) was associated with the risk of overuse injuries, and greater bilateral adductor strength adjusted for body weight (HR, 0.75 [95% CI, 0.57-0.97; P = .032) was associated with a lower risk for any knee injury. Receiver operating characteristic curve analyses indicated poor predictive ability of the significant strength variables (area under the curve, 0.45-0.56). There was a weak association with the risk of

  14. Predicted tyre-soil interface area and vertical stress distribution based on loading characteristics

    DEFF Research Database (Denmark)

    Schjønning, Per; Stettler, M.; Keller, Thomas

    2015-01-01

    The upper boundary condition for all models simulating stress patterns throughout the soil profile is the stress distribution at the tyre–soil interface. The so-called FRIDA model (Schjønning et al., 2008. Biosyst. Eng. 99, 119–133) treats the contact area as a superellipse and has been shown...... of the actual to recommended inflation pressure ratio. We found that VT and Kr accounted for nearly all variation in the data with respect to the contact area. The contact area width was accurately described by a combination of tyre width and Kr, while the superellipse squareness parameter, n, diminished...... slightly with increasing Kr. Estimated values of the contact area length related to observed data with a standard deviation of about 0.06 m. A difference between traction and implement tyres called for separate prediction equations, especially for the contact area. The FRIDA parameters α and β, reflecting...

  15. Fatigue Life Analysis and Prediction of 316L Stainless Steel Under Low Cycle Fatigue Loading

    Energy Technology Data Exchange (ETDEWEB)

    Oh, Hyeong; Myung, NohJun; Choi, Nak-Sam [Hanyang Univ., Seoul (Korea, Republic of)

    2016-12-15

    In this study, a strain-controlled fatigue test of widely-used 316L stainless steel with excellent corrosion resistance and mechanical properties was conducted, in order to assess its fatigue life. Low cycle fatigue behaviors were analyzed at room temperature, as a function of the strain amplitude and strain ratio. The material was hardened during the initial few cycles, and then was softened during the long post period, until failure occurred. The fatigue life decreased with increasing strain amplitude. Masing behavior in the hysteresis loop was shown under the low strain amplitude, whereas the high strain amplitude caused non-Masing behavior and reduced the mean stress. Low cycle fatigue life prediction based on the cyclic plastic energy dissipation theory, considering Masing and non-Masing effects, showed a good correlation with the experimental results.

  16. Rational molecular dynamics scheme for predicting optimum concentration loading of nano-additive in phase change materials

    Directory of Open Access Journals (Sweden)

    Monisha Rastogi

    2015-10-01

    Full Text Available The present study deals with the diffusion and phase transition behaviour of paraffin reinforced with carbon nano-additives namely graphene oxide (GO and surface functionalized single walled carbon nanotubes (SWCNT. Bulk disordered systems of paraffin hydrocarbons impregnated with carbon nano-additives have been generated in realistic equilibrium conformations for potential application as latent heat storage systems. Ab initio molecular dynamics(MD in conjugation with COMPASS forcefield has been implemented using periodic boundary conditions. The proposed scheme allows determination of optimum nano-additive loading for improving thermo-physical properties through analysis of mass, thermal and transport properties; and assists in determination of composite behaviour and related performance from microscopic point of view. It was observed that nanocomposites containing 7.8 % surface functionalised SWCNT and 55% GO loading corresponds to best latent heat storage system. The propounded methodology could serve as a by-pass route for economically taxing and iterative experimental procedures required to attain the optimum composition for best performance. The results also hint at the large unexplored potential of ab-initio classical MD techniques for predicting performance of new nanocomposites for potential phase change material applications.

  17. Human Error Prediction and Countermeasures based on CREAM in Loading and Storage Phase of Spent Nuclear Fuel (SNF)

    International Nuclear Information System (INIS)

    Kim, Jae San; Kim, Min Su; Jo, Seong Youn

    2007-01-01

    With the steady demands for nuclear power energy in Korea, the amount of accumulated SNF has inevitably increased year by year. Thus far, SNF has been on-site transported from one unit to a nearby unit or an on-site dry storage facility. In the near future, as the amount of SNF generated approaches the capacity of these facilities, a percentage of it will be transported to another SNF storage facility. In the process of transporting SNF, human interactions involve inspecting and preparing the cask and spent fuel, loading the cask, transferring the cask and storage or monitoring the cask, etc. So, human actions play a significant role in SNF transportation. In analyzing incidents that have occurred during transport operations, several recent studies have indicated that 'human error' is a primary cause. Therefore, the objectives of this study are to predict and identify possible human errors during the loading and storage of SNF. Furthermore, after evaluating human error for each process, countermeasures to minimize human error are deduced

  18. Improved Short-Term Load Forecasting Based on Two-Stage Predictions with Artificial Neural Networks in a Microgrid Environment

    Directory of Open Access Journals (Sweden)

    Jaime Lloret

    2013-08-01

    Full Text Available Short-Term Load Forecasting plays a significant role in energy generation planning, and is specially gaining momentum in the emerging Smart Grids environment, which usually presents highly disaggregated scenarios where detailed real-time information is available thanks to Communications and Information Technologies, as it happens for example in the case of microgrids. This paper presents a two stage prediction model based on an Artificial Neural Network in order to allow Short-Term Load Forecasting of the following day in microgrid environment, which first estimates peak and valley values of the demand curve of the day to be forecasted. Those, together with other variables, will make the second stage, forecast of the entire demand curve, more precise than a direct, single-stage forecast. The whole architecture of the model will be presented and the results compared with recent work on the same set of data, and on the same location, obtaining a Mean Absolute Percentage Error of 1.62% against the original 2.47% of the single stage model.

  19. Rational molecular dynamics scheme for predicting optimum concentration loading of nano-additive in phase change materials

    Science.gov (United States)

    Rastogi, Monisha; Vaish, Rahul; Madhar, Niyaz Ahamad; Shaikh, Hamid; Al-Zahrani, S. M.

    2015-10-01

    The present study deals with the diffusion and phase transition behaviour of paraffin reinforced with carbon nano-additives namely graphene oxide (GO) and surface functionalized single walled carbon nanotubes (SWCNT). Bulk disordered systems of paraffin hydrocarbons impregnated with carbon nano-additives have been generated in realistic equilibrium conformations for potential application as latent heat storage systems. Ab initio molecular dynamics(MD) in conjugation with COMPASS forcefield has been implemented using periodic boundary conditions. The proposed scheme allows determination of optimum nano-additive loading for improving thermo-physical properties through analysis of mass, thermal and transport properties; and assists in determination of composite behaviour and related performance from microscopic point of view. It was observed that nanocomposites containing 7.8 % surface functionalised SWCNT and 55% GO loading corresponds to best latent heat storage system. The propounded methodology could serve as a by-pass route for economically taxing and iterative experimental procedures required to attain the optimum composition for best performance. The results also hint at the large unexplored potential of ab-initio classical MD techniques for predicting performance of new nanocomposites for potential phase change material applications.

  20. Modelling changes to electricity demand load duration curves as a consequence of predicted climate change for Australia

    International Nuclear Information System (INIS)

    Thatcher, Marcus J.

    2007-01-01

    In this paper, we describe a method for constructing regional electricity demand data sets at 30 min intervals, which are consistent with climate change scenarios. Specifically, we modify a commonly used linear regression model between regional electricity demand and climate to also describe intraday variability in demand so that regional load duration curves (LDCs) can be predicted. The model is evaluated for four different Australian states that are participants in the Australian National Electricity Market (NEM) and the resultant data sets are found to reproduce each state's LDCs with reasonable accuracy. We also apply the demand model to CSIRO's Mk 3 global climate model data sets that have been downscaled to 60 km resolution using CSIRO's conformal-cubic atmospheric model to estimate how LDCs change as a consequence of a 1 C increase in the average temperature of Australian state capital cities. These regional electricity demand data sets are then useful for economic modelling of electricity markets such as the NEM. (author)

  1. Predicting extreme rainfall events over Jeddah, Saudi Arabia: Impact of data assimilation with conventional and satellite observations

    KAUST Repository

    Viswanadhapalli, Yesubabu; Srinivas, C.V.; Langodan, Sabique; Hoteit, Ibrahim

    2015-01-01

    The impact of variational data assimilation for predicting two heavy rainfall events that caused devastating floods in Jeddah, Saudi Arabia is studied using the Weather Research and Forecasting (WRF) model. On 25 November 2009 and 26 January 2011

  2. Diagnostic value of microRNA-143 in predicting in-stent restenosis for patients with lower extremity arterial occlusive disease

    OpenAIRE

    Yu, Zhi-Hai; Wang, Hai-Tao; Tu, Can

    2017-01-01

    Purpose This study was conducted to explore the diagnostic value of microRNA-143 (miRNA-143) in predicting in-stent restenosis (ISR) of lower extremity arterial occlusive disease (LEAOD). Methods From February 2012 to March 2015, 165 patients (112 males and 53 females) with LEAOD undergoing interventional treatment were enrolled in this study. Serum miRNA-143 expression was detected using quantitative real-time polymerase chain reaction (qRT-PCR). Patients were assigned into the restenosis an...

  3. Prediction of Francis Turbine Prototype Part Load Pressure and Output Power Fluctuations with Hydroelectric Model

    Science.gov (United States)

    Alligné, S.; Nicolet, C.; Béguin, A.; Landry, C.; Gomes, J.; Avellan, F.

    2017-04-01

    The prediction of pressure and output power fluctuations amplitudes on Francis turbine prototype is a challenge for hydro-equipment industry since it is subjected to guarantees to ensure smooth and reliable operation of the hydro units. The European FP7 research project Hyperbole aims to setup a methodology to transpose the pressure fluctuations induced by the cavitation vortex rope from the reduced scale model to the prototype generating units. A Francis turbine unit of 444MW with a specific speed value of ν = 0.29, is considered as case study. A SIMSEN model of the power station including electrical system, controllers, rotating train and hydraulic system with transposed draft tube excitation sources is setup. Based on this model, a frequency analysis of the hydroelectric system is performed for all technologies to analyse potential interactions between hydraulic excitation sources and electrical components. Three technologies have been compared: the classical fixed speed configuration with Synchronous Machine (SM) and the two variable speed technologies which are Doubly Fed Induction Machine (DFIM) and Full Size Frequency Converter (FSFC).

  4. Medical students’ logbook case loads do not predict final exam scores in surgery clerkship

    Directory of Open Access Journals (Sweden)

    Alabbad J

    2018-04-01

    Full Text Available Jasim Alabbad,1,2 Fawaz Abdul Raheem,2 Ahmad Almusaileem,1 Sulaiman Almusaileem,1 Saba Alsaddah,2 Abdulaziz Almubarak2 1Department of Surgery, Faculty of Medicine, Kuwait University, Kuwait City, Kuwait; 2Department of Surgery, Mubarak Al-Kabeer Hospital, Jabriya, Kuwait Purpose: To investigate the reliability of medical student logbook data in assessing student performance and predicting outcomes in an objective standardized clinical exam and a multiple-choice exam during surgery rotation. In addition, we examined the relationship between exam performance and the number of clinical tutors per student.Materials and methods: A retrospective review of the logbooks of first and third clinical year medical students at the Faculty of Medicine, Kuwait University, was undertaken during their surgery rotation during the academic year 2012–2013.Results: Logbooks of 184 students were reviewed and analyzed. There were 92 and 93 students in the first and third clinical years, respectively. We did not identify any correlation between the number of clinical encounters and clinical exam or multiple-choice exam scores; however, there was an inverse relationship between the number of clinical tutors encountered during a rotation and clinical exam scores.Conclusion: Overall, there was no correlation between the volume of self-reported clinical encounters and exam scores. Furthermore, an inverse correlation between the number of clinical tutors encountered and clinical exam scores was detected. These findings indicate a need for reevaluation of the way logbook data are entered and used as an assessment tool. Keywords: OSCE, assessment, Kuwait, universities, rotation

  5. PCCE-A Predictive Code for Calorimetric Estimates in actively cooled components affected by pulsed power loads

    International Nuclear Information System (INIS)

    Agostinetti, P.; Palma, M. Dalla; Fantini, F.; Fellin, F.; Pasqualotto, R.

    2011-01-01

    The analytical interpretative models for calorimetric measurements currently available in the literature can consider close systems in steady-state and transient conditions, or open systems but only in steady-state conditions. The PCCE code (Predictive Code for Calorimetric Estimations), here presented, introduces some novelties. In fact, it can simulate with an analytical approach both the heated component and the cooling circuit, evaluating the heat fluxes due to conductive and convective processes both in steady-state and transient conditions. The main goal of this code is to model heating and cooling processes in actively cooled components of fusion experiments affected by high pulsed power loads, that are not easily analyzed with purely numerical approaches (like Finite Element Method or Computational Fluid Dynamics). A dedicated mathematical formulation, based on concentrated parameters, has been developed and is here described in detail. After a comparison and benchmark with the ANSYS commercial code, the PCCE code is applied to predict the calorimetric parameters in simple scenarios of the SPIDER experiment.

  6. Statistical analysis and ANN modeling for predicting hydrological extremes under climate change scenarios: the example of a small Mediterranean agro-watershed.

    Science.gov (United States)

    Kourgialas, Nektarios N; Dokou, Zoi; Karatzas, George P

    2015-05-01

    The purpose of this study was to create a modeling management tool for the simulation of extreme flow events under current and future climatic conditions. This tool is a combination of different components and can be applied in complex hydrogeological river basins, where frequent flood and drought phenomena occur. The first component is the statistical analysis of the available hydro-meteorological data. Specifically, principal components analysis was performed in order to quantify the importance of the hydro-meteorological parameters that affect the generation of extreme events. The second component is a prediction-forecasting artificial neural network (ANN) model that simulates, accurately and efficiently, river flow on an hourly basis. This model is based on a methodology that attempts to resolve a very difficult problem related to the accurate estimation of extreme flows. For this purpose, the available measurements (5 years of hourly data) were divided in two subsets: one for the dry and one for the wet periods of the hydrological year. This way, two ANNs were created, trained, tested and validated for a complex Mediterranean river basin in Crete, Greece. As part of the second management component a statistical downscaling tool was used for the creation of meteorological data according to the higher and lower emission climate change scenarios A2 and B1. These data are used as input in the ANN for the forecasting of river flow for the next two decades. The final component is the application of a meteorological index on the measured and forecasted precipitation and flow data, in order to assess the severity and duration of extreme events. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Development of Predictive Models of Injury for the Lower Extremity, Lumbar, and Thoracic Spine after Discharge from Physical Rehabilitation

    Science.gov (United States)

    2015-10-01

    prevention titled “Prediction, Prevention, and Preemption: Screening for sports and training injuries. What are the possibilities?” The talk was...the resources and training. The decision was made after MAJ Rhon’s PCS to BAMC, and because the site PI at Madigan there had some pregnancy

  8. A load predictive energy management system for supercapacitor-battery hybrid energy storage system in solar application using the Support Vector Machine

    International Nuclear Information System (INIS)

    Chia, Yen Yee; Lee, Lam Hong; Shafiabady, Niusha; Isa, Dino

    2015-01-01

    Highlights: • A novel energy management system (EMS) for supercapacitor-battery hybrid energy storage system is implemented. • It is a load predictive EMS which is implemented using Support Vector Machine (SVM). • An optimum SVM load prediction model is obtained, which yields 100% accuracy in 0.004866 s of training time. • The implemented load predictive EMS is compared with the conventional sequential programming control. • This methodology reduces the number of power electronics used and prolong battery lifespan. - Abstract: This paper presents the use of a Support Vector Machine load predictive energy management system to control the energy flow between a solar energy source, a supercapacitor-battery hybrid energy storage combination and the load. The supercapacitor-battery hybrid energy storage system is deployed in a solar energy system to improve the reliability of delivered power. The combination of batteries and supercapacitors makes use of complementary characteristic that allow the overlapping of a battery’s high energy density with a supercapacitors’ high power density. This hybrid system produces a straightforward benefit over either individual system, by taking advantage of each characteristic. When the supercapacitor caters for the instantaneous peak power which prolongs the battery lifespan, it also minimizes the system cost and ensures a greener system by reducing the number of batteries. The resulting performance is highly dependent on the energy controls implemented in the system to exploit the strengths of the energy storage devices and minimize its weaknesses. It is crucial to use energy from the supercapacitor and therefore minimize jeopardizing the power system reliability especially when there is a sudden peak power demand. This study has been divided into two stages. The first stage is to obtain the optimum SVM load prediction model, and the second stage carries out the performance comparison of the proposed SVM-load predictive

  9. Cooling-load prediction by the combination of rough set theory and an artificial neural-network based on data-fusion technique

    International Nuclear Information System (INIS)

    Hou Zhijian; Lian Zhiwei; Yao Ye; Yuan Xinjian

    2006-01-01

    A novel method integrating rough sets (RS) theory and an artificial neural network (ANN) based on data-fusion technique is presented to forecast an air-conditioning load. Data-fusion technique is the process of combining multiple sensors data or related information to estimate or predict entity states. In this paper, RS theory is applied to find relevant factors to the load, which are used as inputs of an artificial neural-network to predict the cooling load. To improve the accuracy and enhance the robustness of load forecasting results, a general load-prediction model, by synthesizing multi-RSAN (MRAN), is presented so as to make full use of redundant information. The optimum principle is employed to deduce the weights of each RSAN model. Actual prediction results from a real air-conditioning system show that, the MRAN forecasting model is better than the individual RSAN and moving average (AMIMA) ones, whose relative error is within 4%. In addition, individual RSAN forecasting results are better than that of ARIMA

  10. Ductile Tearing of Thin Aluminum Plates Under Blast Loading. Predictions with Fully Coupled Models and Biaxial Material Response Characterization

    Energy Technology Data Exchange (ETDEWEB)

    Corona, Edmundo [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gullerud, Arne S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Haulenbeek, Kimberly K. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Reu, Phillip L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-06-01

    The work presented in this report concerns the response and failure of thin 2024- T3 aluminum alloy circular plates to a blast load produced by the detonation of a nearby spherical charge. The plates were fully clamped around the circumference and the explosive charge was located centrally with respect to the plate. The principal objective was to conduct a numerical model validation study by comparing the results of predictions to experimental measurements of plate deformation and failure for charges with masses in the vicinity of the threshold between no tearing and tearing of the plates. Stereo digital image correlation data was acquired for all tests to measure the deflection and strains in the plates. The size of the virtual strain gage in the measurements, however, was relatively large, so the strain measurements have to be interpreted accordingly as lower bounds of the actual strains in the plate and of the severity of the strain gradients. A fully coupled interaction model between the blast and the deflection of the structure was considered. The results of the validation exercise indicated that the model predicted the deflection of the plates reasonably accurately as well as the distribution of strain on the plate. The estimation of the threshold charge based on a critical value of equivalent plastic strain measured in a bulge test, however, was not accurate. This in spite of efforts to determine the failure strain of the aluminum sheet under biaxial stress conditions. Further work is needed to be able to predict plate tearing with some degree of confidence. Given the current technology, at least one test under the actual blast conditions where the plate tears is needed to calibrate the value of equivalent plastic strain when failure occurs in the numerical model. Once that has been determined, the question of the explosive mass value at the threshold could be addressed with more confidence.

  11. Analysis of extreme events

    CSIR Research Space (South Africa)

    Khuluse, S

    2009-04-01

    Full Text Available ) determination of the distribution of the damage and (iii) preparation of products that enable prediction of future risk events. The methodology provided by extreme value theory can also be a powerful tool in risk analysis...

  12. Predicting extreme rainfall events over Jeddah, Saudi Arabia: Impact of data assimilation with conventional and satellite observations

    KAUST Repository

    Viswanadhapalli, Yesubabu

    2015-08-20

    The impact of variational data assimilation for predicting two heavy rainfall events that caused devastating floods in Jeddah, Saudi Arabia is studied using the Weather Research and Forecasting (WRF) model. On 25 November 2009 and 26 January 2011, the city was deluged with more than double the annual rainfall amount caused by convective storms. We used a high resolution, two-way nested domain WRF model to simulate the two rainfall episodes. Simulations include control runs initialized with National Center for Environmental Prediction (NCEP) Global Forecasting System (GFS) data and 3-Dimensional Variational (3DVAR) data assimilation experiments conducted by assimilating NCEP prepbufr and radiance observations. Observations from Automated Weather Stations (AWS), synoptic charts, radar reflectivity and satellite pictures from the Presidency of Meteorology and Environment (PME), Jeddah, Saudi Arabia are used to assess the forecasting results. To evaluate the impact of the different assimilated observational datasets on the simulation of the major flooding event of 2009, we conducted 3DVAR experiments assimilating individual sources and a combination of all data sets. Results suggest that while the control run had a tendency to predict the storm earlier than observed, the assimilation of profile observations greatly improved the model\\'s thermodynamic structure and lead to better representation of simulated rainfall both in timing and amount. The experiment with assimilation of all available observations compared best with observed rainfall in terms of timing of the storm and rainfall distribution, demonstrating the importance of assimilating different types of observations. Retrospective experiments with and without data assimilation, for three different model lead times (48, 72 and 96-h), were performed to examine the skill of WRF model to predict the heavy rainfall events. Quantitative rainfall analysis of these simulations suggests that 48-h lead time runs with

  13. Somatic mutation load of estrogen receptor-positive breast tumors predicts overall survival: an analysis of genome sequence data.

    Science.gov (United States)

    Haricharan, Svasti; Bainbridge, Matthew N; Scheet, Paul; Brown, Powel H

    2014-07-01

    Breast cancer is one of the most commonly diagnosed cancers in women. While there are several effective therapies for breast cancer and important single gene prognostic/predictive markers, more than 40,000 women die from this disease every year. The increasing availability of large-scale genomic datasets provides opportunities for identifying factors that influence breast cancer survival in smaller, well-defined subsets. The purpose of this study was to investigate the genomic landscape of various breast cancer subtypes and its potential associations with clinical outcomes. We used statistical analysis of sequence data generated by the Cancer Genome Atlas initiative including somatic mutation load (SML) analysis, Kaplan-Meier survival curves, gene mutational frequency, and mutational enrichment evaluation to study the genomic landscape of breast cancer. We show that ER(+), but not ER(-), tumors with high SML associate with poor overall survival (HR = 2.02). Further, these high mutation load tumors are enriched for coincident mutations in both DNA damage repair and ER signature genes. While it is known that somatic mutations in specific genes affect breast cancer survival, this study is the first to identify that SML may constitute an important global signature for a subset of ER(+) tumors prone to high mortality. Moreover, although somatic mutations in individual DNA damage genes affect clinical outcome, our results indicate that coincident mutations in DNA damage response and signature ER genes may prove more informative for ER(+) breast cancer survival. Next generation sequencing may prove an essential tool for identifying pathways underlying poor outcomes and for tailoring therapeutic strategies.

  14. Pre-impact lower extremity posture and brake pedal force predict foot and ankle forces during an automobile collision.

    Science.gov (United States)

    Hardin, E C; Su, A; van den Bogert, A J

    2004-12-01

    The purpose of this study was to determine how a driver's foot and ankle forces during a frontal vehicle collision depend on initial lower extremity posture and brake pedal force. A 2D musculoskeletal model with seven segments and six right-side muscle groups was used. A simulation of a three-second braking task found 3647 sets of muscle activation levels that resulted in stable braking postures with realistic pedal force. These activation patterns were then used in impact simulations where vehicle deceleration was applied and driver movements and foot and ankle forces were simulated. Peak rearfoot ground reaction force (F(RF)), peak Achilles tendon force (FAT), peak calcaneal force (F(CF)) and peak ankle joint force (F(AJ)) were calculated. Peak forces during the impact simulation were 476 +/- 687 N (F(RF)), 2934 +/- 944 N (F(CF)) and 2449 +/- 918 N (F(AJ)). Many simulations resulted in force levels that could cause fractures. Multivariate quadratic regression determined that the pre-impact brake pedal force (PF), knee angle (KA) and heel distance (HD) explained 72% of the variance in peak FRF, 62% in peak F(CF) and 73% in peak F(AJ). Foot and ankle forces during a collision depend on initial posture and pedal force. Braking postures with increased knee flexion, while keeping the seat position fixed, are associated with higher foot and ankle forces during a collision.

  15. Reliability of the Load-Velocity Relationship Obtained Through Linear and Polynomial Regression Models to Predict the One-Repetition Maximum Load.

    Science.gov (United States)

    Pestaña-Melero, Francisco Luis; Haff, G Gregory; Rojas, Francisco Javier; Pérez-Castilla, Alejandro; García-Ramos, Amador

    2017-12-18

    This study aimed to compare the between-session reliability of the load-velocity relationship between (1) linear vs. polynomial regression models, (2) concentric-only vs. eccentric-concentric bench press variants, as well as (3) the within-participants vs. the between-participants variability of the velocity attained at each percentage of the one-repetition maximum (%1RM). The load-velocity relationship of 30 men (age: 21.2±3.8 y; height: 1.78±0.07 m, body mass: 72.3±7.3 kg; bench press 1RM: 78.8±13.2 kg) were evaluated by means of linear and polynomial regression models in the concentric-only and eccentric-concentric bench press variants in a Smith Machine. Two sessions were performed with each bench press variant. The main findings were: (1) first-order-polynomials (CV: 4.39%-4.70%) provided the load-velocity relationship with higher reliability than second-order-polynomials (CV: 4.68%-5.04%); (2) the reliability of the load-velocity relationship did not differ between the concentric-only and eccentric-concentric bench press variants; (3) the within-participants variability of the velocity attained at each %1RM was markedly lower than the between-participants variability. Taken together, these results highlight that, regardless of the bench press variant considered, the individual determination of the load-velocity relationship by a linear regression model could be recommended to monitor and prescribe the relative load in the Smith machine bench press exercise.

  16. The near-term prediction of drought and flooding conditions in the northeastern United States based on extreme phases of AMO and NAO

    Science.gov (United States)

    Berton, Rouzbeh; Driscoll, Charles T.; Adamowski, Jan F.

    2017-10-01

    A series of hydroclimatic teleconnection patterns were identified between variations in either Atlantic or Pacific oceanic indices with precipitation and discharge anomalies in the northeastern United States. We hypothesized that temporal annual or seasonal changes in discharge could be explained by variations in extreme phases of the Atlantic Multi-decadal Oscillation (AMO index, SST: Sea Surface Temperature anomalies) and the North Atlantic Oscillation (NAO index, SLP: Sea-Level Pressure anomalies) up to three seasons in advance. The Merrimack River watershed, the fourth largest basin in New England, with a drainage area of 13,000 km2, is a compelling study site because it not only provides an opportunity to investigate the teleconnection between hydrologic variables and large-scale climate circulation patterns, but also how those patterns may become obscured by anthropogenic disturbances such as river regulation or urban development. We considered precipitation and discharge data of 21 gauging stations within the Merrimack River watershed, including the Hubbard Brook Experimental Forest (HBEF), NH, with a median record length of 55 years beginning as early as 1904. The discharge anomalies were statistically significant (p-value ≤ 0.2) between extreme positive and negative phases of AMO (1857-2011) and NAO (1900-2011) and revealed the potential teleconnectivity of climate circulation patterns with discharge. Annual and seasonal correlations of discharge were examined with the extreme phases of AMO and NAO at zero-, one-, or two- year/season lags (total of 30 scenarios). When AMO was greater than 0.2, the strongest correlations of AMO and NAO with discharge were observed at headwater catchments. This correlation weakened downstream towards larger regulated and/or developed sub-basins. We introduced a simple approach for near-term prediction of drought and flooding events. An exponential decay function was regressed through the historic occurrence of the relative

  17. Muscle quality, aerobic fitness and fat mass predict lower-extremity physical function in community-dwelling older adults.

    Science.gov (United States)

    Misic, Mark M; Rosengren, Karl S; Woods, Jeffrey A; Evans, Ellen M

    2007-01-01

    Muscle mass, strength and fitness play a role in lower-extremity physical function (LEPF) in older adults; however, the relationships remain inadequately characterized. This study aimed to examine the relationships between leg mineral free lean mass (MFLM(LEG)), leg muscle quality (leg strength normalized for MFLM(LEG)), adiposity, aerobic fitness and LEPF in community-dwelling healthy elderly subjects. Fifty-five older adults (69.3 +/- 5.5 years, 36 females, 19 males) were assessed for leg strength using an isokinetic dynamometer, body composition by dual energy X-ray absorptiometry and aerobic fitness via a treadmill maximal oxygen consumption test. LEPF was assessed using computerized dynamic posturography and stair ascent/descent, a timed up-and-go task and a 7-meter walk with and without an obstacle. Muscle strength, muscle quality and aerobic fitness were similarly correlated with static LEPF tests (r range 0.27-0.40, p < 0.05); however, the strength of the independent predictors was not robust with explained variance ranging from 9 to 16%. Muscle quality was the strongest correlate of all dynamic LEPF tests (r range 0.54-0.65, p < 0.001). Using stepwise linear regression analysis, muscle quality was the strongest independent predictor of dynamic physical function explaining 29-42% of the variance (p < 0.001), whereas aerobic fitness or body fat mass explained 5-6% of the variance (p < 0.05) depending on performance measure. Muscle quality is the most important predictor, and aerobic fitness and fat mass are secondary predictors of LEPF in community-dwelling older adults. These findings support the importance of exercise, especially strength training, for optimal body composition, and maintenance of strength and physical function in older adults.

  18. Impact of GHG warming on the mean and extreme loading of particulate matter pollution in a chemistry-climate model ensemble simulation

    Science.gov (United States)

    Xu, Y.; Lamarque, J. F.; Wu, X.

    2017-12-01

    Particulate matter with the diameter smaller than 2.5 micrometers (PM2.5) poses health threats to human populations. Regardless of efforts to regulate the pollution sources, it is unclear how climate change caused by greenhouse gases (GHGs) would affect PM2.5 levels. Using century-long ensemble simulations with Community Earth System Model 1 (CESM1), we show that, if the anthropogenic emissions would remain at the level in the year 2005, the global surface concentration and atmospheric column burden of sulfate, black carbon, and primary organic carbon would still increase by 5-10% at the end of 21st century (2090-2100) due to global warming alone. The decrease in the wet removal flux of PM2.5, despite an increase in global precipitation, is the primary cause for the increase in the PM2.5 column burden. Regionally over North America and East Asia, a shift of future precipitation toward more frequent heavy events contributes to weakened wet removal fluxes. Based on the daily model output, the frequency and intensity of extreme pollution events are also studied. We found that both stagnation frequency and rainfall changes serve to worsen extreme pollution in the future.

  19. Extremely fast increase in the organic loading rate during the co-digestion of rapeseed oil and sewage sludge in a CSTR--characterization of granules formed due to CaO addition to maintain process stability.

    Science.gov (United States)

    Kasina, M; Kleyböcker, A; Michalik, M; Würdemann, H

    2015-01-01

    In a co-digestion system running with rapeseed oil and sewage sludge, an extremely fast increase in the organic loading rate was studied to develop a procedure to allow for flexible and demand-driven energy production. The over-acidification of the digestate was successfully prevented by calcium oxide dosage, which resulted in granule formation. Mineralogical analyses revealed that the granules were composed of insoluble salts of long chain fatty acids and calcium and had a porous structure. Long chain fatty acids and calcium formed the outer cover of granules and offered interfaces on the inside thereby enhancing the growth of biofilms. With granule size and age, the pore size increased and indicated degradation of granular interfaces. A stable biogas production up to the organic loading rate of 10.4 kg volatile solids m(-3) d(-1) was achieved although the hydrogen concentration was not favorable for propionic acid degradation. However, at higher organic loading rates, unbalanced granule formation and degradation were observed. Obviously, the adaption time for biofilm growth was too short to maintain the balance, thereby resulting in a low methane yield.

  20. Glycaemic index and glycaemic load of breakfast predict cognitive function and mood in school children: a randomised controlled trial.

    Science.gov (United States)

    Micha, Renata; Rogers, Peter J; Nelson, Michael

    2011-11-01

    The macronutrient composition of a breakfast that could facilitate performance after an overnight fast remains unclear. As glucose is the brain's major energy source, the interest is in investigating meals differing in their blood glucose-raising potential. Findings vary due to unaccounted differences in glucoregulation, arousal and cortisol secretion. We investigated the effects of meals differing in glycaemic index (GI) and glycaemic load (GL) on cognition and mood in school children. A total of seventy-four school children were matched and randomly allocated either to the high-GL or low-GL group. Within each GL group, children received high-GI and low-GI breakfasts. Cognitive function (CF) and mood were measured 95-140 min after breakfast. Blood glucose and salivary cortisol were measured at baseline, before and after the CF tests. Repeated-measures ANOVA was used to identify differences in CF, mood, glucose and cortisol levels between the breakfasts. Low-GI meals predicted feeling more alert and happy, and less nervous and thirsty (P breakfast, and high-GI meals increased cortisol levels (P breakfast may help to improve learning, and of potential value in informing government education policies relating to dietary recommendations and implementation concerning breakfast.

  1. Damage prediction of carbon fibre composite armoured actively cooled plasma-facing components under cycling heat loads

    International Nuclear Information System (INIS)

    Chevet, G; Schlosser, J; Courtois, X; Escourbiac, F; Missirlian, M; Herb, V; Martin, E; Camus, G; Braccini, M

    2009-01-01

    In order to predict the lifetime of carbon fibre composite (CFC) armoured plasma-facing components in magnetic fusion devices, it is necessary to analyse the damage mechanisms and to model the damage propagation under cycling heat loads. At Tore Supra studies have been launched to better understand the damage process of the armoured flat tile elements of the actively cooled toroidal pump limiter, leading to the characterization of the damageable mechanical behaviour of the used N11 CFC material and of the CFC/Cu bond. Up until now the calculations have shown damage developing in the CFC (within the zone submitted to high shear stress) and in the bond (from the free edge of the CFC/Cu interface). Damage is due to manufacturing shear stresses and does not evolve under heat due to stress relaxation. For the ITER divertor, NB31 material has been characterized and the characterization of NB41 is in progress. Finite element calculations show again the development of CFC damage in the high shear stress zones after manufacturing. Stresses also decrease under heat flux so the damage does not evolve. The characterization of the CFC/Cu bond is more complex due to the monoblock geometry, which leads to more scattered stresses. These calculations allow the fabrication difficulties to be better understood and will help to analyse future high heat flux tests on various mock-ups.

  2. Mandelbrot's Extremism

    NARCIS (Netherlands)

    Beirlant, J.; Schoutens, W.; Segers, J.J.J.

    2004-01-01

    In the sixties Mandelbrot already showed that extreme price swings are more likely than some of us think or incorporate in our models.A modern toolbox for analyzing such rare events can be found in the field of extreme value theory.At the core of extreme value theory lies the modelling of maxima

  3. Which adherence measure - self-report, clinician recorded or pharmacy refill - is best able to predict detectable viral load in a public ART programme without routine plasma viral load monitoring?

    Science.gov (United States)

    Mekuria, Legese A; Prins, Jan M; Yalew, Alemayehu W; Sprangers, Mirjam A G; Nieuwkerk, Pythia T

    2016-07-01

    Combination antiretroviral therapy (cART) suppresses viral replication to an undetectable level if a sufficiently high level of adherence is achieved. We investigated which adherence measurement best distinguishes between patients with and without detectable viral load in a public ART programme without routine plasma viral load monitoring. We randomly selected 870 patients who started cART between May 2009 and April 2012 in 10 healthcare facilities in Addis Ababa, Ethiopia. Six hundred and sixty-four (76.3%) patients who were retained in HIV care and were receiving cART for at least 6 months were included and 642 had their plasma HIV-1 RNA concentration measured. Patients' adherence to cART was assessed according to self-report, clinician recorded and pharmacy refill measures. Multivariate logistic regression model was fitted to identify the predictors of detectable viremia. Model accuracy was evaluated by computing the area under the receiver operating characteristic (ROC) curve. A total of 9.2% and 5.5% of the 642 patients had a detectable viral load of ≥40 and ≥400 RNA copies/ml, respectively. In the multivariate analyses, younger age, lower CD4 cell count at cART initiation, being illiterate and widowed, and each of the adherence measures were significantly and independently predictive of having ≥400 RNA copies/ml. The ROC curve showed that these variables altogether had a likelihood of more than 80% to distinguish patients with a plasma viral load of ≥400 RNA copies/ml from those without. Adherence to cART was remarkably high. Self-report, clinician recorded and pharmacy refill non-adherence were all significantly predictive of detectable viremia. The choice for one of these methods to detect non-adherence and predict a detectable viral load can therefore be based on what is most practical in a particular setting. © 2016 John Wiley & Sons Ltd.

  4. Reduced brachial flow-mediated vasodilation in young adult ex extremely low birth weight preterm: a condition predictive of increased cardiovascular risk?

    Science.gov (United States)

    Bassareo, P P; Fanos, V; Puddu, M; Demuru, P; Cadeddu, F; Balzarini, M; Mercuro, G

    2010-10-01

    Sporadic data present in literature report how preterm birth and low birth weight constitute the risk factors for the development of cardiovascular diseases in later life. To assess the presence of potential alterations to endothelial function in young adults born preterm at extremely low birth weight (Cesarea, Israel). Endothelial function was significantly reduced in ex-ELBW subjects compared to C (1.94 +/- 0.37 vs. 2.68 +/- 0.41, p < 0.0001). Moreover, this function correlated significantly with gestational age (r = 0.56, p < 0.0009) and birth weight (r = 0.63, p < 0.0001). The results obtained reveal a significant decrease in endothelial function of ex-ELBW subjects compared to controls, underlining a probable correlation with preterm birth and low birth weight. Taken together, these results suggest that an ELBW may underlie the onset of early circulatory dysfunction predictive of increased cardiovascular risk.

  5. The more, the less: age and chemotherapy load are predictive of poor stem cell mobilization in patients with hematologic malignancies

    Institute of Scientific and Technical Information of China (English)

    YANG Shen-miao; CHEN Huan; CHEN Yu-hong; ZHU Hong-hu; ZHAO Ting; LIU Kai-yan

    2012-01-01

    Background Intensive treatment such as autologous peripheral blood stem cell (PBSC) transplantation is an important therapeutic strategy in many hematologic malignancies.A number of factors have been reported to impact PBSC mobilization,but the predictive factors varied from one study to another.This retrospective study assessed our current mobilization and collection protocols,and explored the factors predictive of PBSC mobilization in patients with hematologic malignancies.Methods Data of 64 consecutive patients with hematologic malignancies (multiple myeloma,n=22; acute leukemia,n=27; lymphoma,n=15) who underwent PBSC mobilization for over 1 year were analyzed.Four patients with response to treatment of near complete remission or better were administered granulocyte colony-stimulating factor (G-CSF) to mobilize PBSCs.Sixty patients received G-CSF followed by chemotherapy mobilizing regimens.Poor mobilization (PM) was defined as when ≤2.0×106 CD34+ cells/kg body weight were collected within three leukapheresis procedures.Results The incidence of PM at the first mobilization attempt was 19% (12/64).The PM group was older than the non-PM group (median age,51 vs.40 years; P=0.013).In univariate analysis,there were no significant differences in gender,diagnosis,and body weight between the PM and non-PM groups.A combination of chemotherapy and G-CSF was more effective than G-CSF alone as a mobilizing regimen (P=0.019).Grade Ⅲ or Ⅳ hematopoietic toxicity of chemotherapy had no significant effect on the mobilization efficacy.Supportive care and the incidence of febrile neutropenia were not significantly different between the two groups.In multivariate analysis,age (odds ratio (OR),9.536;P=-0.002) and number of previous chemotherapy courses (OR 3.132; P=0.024) were two independent negative predictive factors for CD34+ cell yield.PM patients could be managed well by remobilization.Conclusion Older age and a heavy load of previous chemotherapy are the negative

  6. 近海风电机结构动力响应极值预报%Prediction of Structural Dynamic Response Extreme Values of Offshore Wind Turbine

    Institute of Scientific and Technical Information of China (English)

    王立夫

    2017-01-01

    鉴于国内外在预报风浪共同作用下近海风电机的极限结构动力响应方面仍然面临挑战的现状,提出用最小二乘法高效精确地求解广义柏拉图分布中的待定参数,预报某5 MW漂浮式风电机塔筒平台接合处的前后向弯矩极值,并用蒙特卡罗仿真和诊断图证明了最小二乘法与传统的矩方法相比的优越性.可为浮式海上风电机的结构设计提供参考.%Due to the fact that it is still a challenge at both home and abroad on how to predict the extreme structural dynamic responses of an offshore wind turbine under the con current action of wind and waves,the method of least squares is used to more efficiently and accurately estimate the unknown parameters in the Generalized Pareto distribution so that the extreme values of the fore-aft bending moments at the tower-Spar interface of a 5 MW floating wind turbine are predicted.Monte Carlo simulation and diagnostic plots are used to test the advantages of the method of least squares over the traditional method of moments.The new method proposed will become a powerful tool for the people in their structural design of a floating offshore wind turbine.

  7. Investigation of Unsteady Pressure-Sensitive Paint (uPSP) and a Dynamic Loads Balance to Predict Launch Vehicle Buffet Environments

    Science.gov (United States)

    Schuster, David M.; Panda, Jayanta; Ross, James C.; Roozeboom, Nettie H.; Burnside, Nathan J.; Ngo, Christina L.; Kumagai, Hiro; Sellers, Marvin; Powell, Jessica M.; Sekula, Martin K.; hide

    2016-01-01

    This NESC assessment examined the accuracy of estimating buffet loads on in-line launch vehicles without booster attachments using sparse unsteady pressure measurements. The buffet loads computed using sparse sensor data were compared with estimates derived using measurements with much higher spatial resolution. The current method for estimating launch vehicle buffet loads is through wind tunnel testing of models with approximately 400 unsteady pressure transducers. Even with this relatively large number of sensors, the coverage can be insufficient to provide reliable integrated unsteady loads on vehicles. In general, sparse sensor spacing requires the use of coherence-length-based corrections in the azimuthal and axial directions to integrate the unsteady pressures and obtain reasonable estimates of the buffet loads. Coherence corrections have been used to estimate buffet loads for a variety of launch vehicles with the assumption methodology results in reasonably conservative loads. For the Space Launch System (SLS), the first estimates of buffet loads exceeded the limits of the vehicle structure, so additional tests with higher sensor density were conducted to better define the buffet loads and possibly avoid expensive modifications to the vehicle design. Without the additional tests and improvements to the coherence-length analysis methods, there would have been significant impacts to the vehicle weight, cost, and schedule. If the load estimates turn out to be too low, there is significant risk of structural failure of the vehicle. This assessment used a combination of unsteady pressure-sensitive paint (uPSP), unsteady pressure transducers, and a dynamic force and moment balance to investigate the integration schemes used with limited unsteady pressure data by comparing them with direct integration of extremely dense fluctuating pressure measurements. An outfall of the assessment was to evaluate the potential of using the emerging uPSP technique in a production

  8. A fast-running core prediction model based on neural networks for load-following operations in a soluble boron-free reactor

    Energy Technology Data Exchange (ETDEWEB)

    Jang, Jin-wook [Korea Atomic Energy Research Institute, P.O. Box 105, Yusong, Daejon 305-600 (Korea, Republic of)], E-mail: Jinwook@kaeri.re.kr; Seong, Seung-Hwan [Korea Atomic Energy Research Institute, P.O. Box 105, Yusong, Daejon 305-600 (Korea, Republic of)], E-mail: shseong@kaeri.re.kr; Lee, Un-Chul [Department of Nuclear Engineering, Seoul National University, Shinlim-Dong, Gwanak-Gu, Seoul 151-742 (Korea, Republic of)

    2007-09-15

    A fast prediction model for load-following operations in a soluble boron-free reactor has been proposed, which can predict the core status when three or more control rod groups are moved at a time. This prediction model consists of two multilayer feedforward neural network models to retrieve the axial offset and the reactivity, and compensation models to compensate for the reactivity and axial offset arising from the xenon transient. The neural network training data were generated by taking various overlaps among the control rod groups into consideration for training the neural network models, and the accuracy of the constructed neural network models was verified. Validation results of predicting load following operations for a soluble boron-free reactor show that this model has a good capability to predict the positions of the control rods for sustaining the criticality of a core during load-following operations to ensure that the tolerable axial offset band is not exceeded and it can provide enough corresponding time for the operators to take the necessary actions to prevent a deviation from the tolerable operating band.

  9. A fast-running core prediction model based on neural networks for load-following operations in a soluble boron-free reactor

    International Nuclear Information System (INIS)

    Jang, Jin-wook; Seong, Seung-Hwan; Lee, Un-Chul

    2007-01-01

    A fast prediction model for load-following operations in a soluble boron-free reactor has been proposed, which can predict the core status when three or more control rod groups are moved at a time. This prediction model consists of two multilayer feedforward neural network models to retrieve the axial offset and the reactivity, and compensation models to compensate for the reactivity and axial offset arising from the xenon transient. The neural network training data were generated by taking various overlaps among the control rod groups into consideration for training the neural network models, and the accuracy of the constructed neural network models was verified. Validation results of predicting load following operations for a soluble boron-free reactor show that this model has a good capability to predict the positions of the control rods for sustaining the criticality of a core during load-following operations to ensure that the tolerable axial offset band is not exceeded and it can provide enough corresponding time for the operators to take the necessary actions to prevent a deviation from the tolerable operating band

  10. A distributed model predictive control based load frequency control scheme for multi-area interconnected power system using discrete-time Laguerre functions.

    Science.gov (United States)

    Zheng, Yang; Zhou, Jianzhong; Xu, Yanhe; Zhang, Yuncheng; Qian, Zhongdong

    2017-05-01

    This paper proposes a distributed model predictive control based load frequency control (MPC-LFC) scheme to improve control performances in the frequency regulation of power system. In order to reduce the computational burden in the rolling optimization with a sufficiently large prediction horizon, the orthonormal Laguerre functions are utilized to approximate the predicted control trajectory. The closed-loop stability of the proposed MPC scheme is achieved by adding a terminal equality constraint to the online quadratic optimization and taking the cost function as the Lyapunov function. Furthermore, the treatments of some typical constraints in load frequency control have been studied based on the specific Laguerre-based formulations. Simulations have been conducted in two different interconnected power systems to validate the effectiveness of the proposed distributed MPC-LFC as well as its superiority over the comparative methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  11. Load-related brain activation predicts spatial working memory performance in youth aged 9-12 and is associated with executive function at earlier ages.

    Science.gov (United States)

    Huang, Anna S; Klein, Daniel N; Leung, Hoi-Chung

    2016-02-01

    Spatial working memory is a central cognitive process that matures through adolescence in conjunction with major changes in brain function and anatomy. Here we focused on late childhood and early adolescence to more closely examine the neural correlates of performance variability during this important transition period. Using a modified spatial 1-back task with two memory load conditions in an fMRI study, we examined the relationship between load-dependent neural responses and task performance in a sample of 39 youth aged 9-12 years. Our data revealed that between-subject differences in task performance was predicted by load-dependent deactivation in default network regions, including the ventral anterior cingulate cortex (vACC) and posterior cingulate cortex (PCC). Although load-dependent increases in activation in prefrontal and posterior parietal regions were only weakly correlated with performance, increased prefrontal-parietal coupling was associated with better performance. Furthermore, behavioral measures of executive function from as early as age 3 predicted current load-dependent deactivation in vACC and PCC. These findings suggest that both task positive and task negative brain activation during spatial working memory contributed to successful task performance in late childhood/early adolescence. This may serve as a good model for studying executive control deficits in developmental disorders. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  12. Load-related brain activation predicts spatial working memory performance in youth aged 9–12 and is associated with executive function at earlier ages

    Science.gov (United States)

    Huang, Anna S.; Klein, Daniel N.; Leung, Hoi-Chung

    2015-01-01

    Spatial working memory is a central cognitive process that matures through adolescence in conjunction with major changes in brain function and anatomy. Here we focused on late childhood and early adolescence to more closely examine the neural correlates of performance variability during this important transition period. Using a modified spatial 1-back task with two memory load conditions in an fMRI study, we examined the relationship between load-dependent neural responses and task performance in a sample of 39 youth aged 9–12 years. Our data revealed that between-subject differences in task performance was predicted by load-dependent deactivation in default network regions, including the ventral anterior cingulate cortex (vACC) and posterior cingulate cortex (PCC). Although load-dependent increases in activation in prefrontal and posterior parietal regions were only weakly correlated with performance, increased prefrontal-parietal coupling was associated with better performance. Furthermore, behavioral measures of executive function from as early as age 3 predicted current load-dependent deactivation in vACC and PCC. These findings suggest that both task positive and task negative brain activation during spatial working memory contributed to successful task performance in late childhood/early adolescence. This may serve as a good model for studying executive control deficits in developmental disorders. PMID:26562059

  13. The Baby Moves prospective cohort study protocol: using a smartphone application with the General Movements Assessment to predict neurodevelopmental outcomes at age 2 years for extremely preterm or extremely low birthweight infants.

    Science.gov (United States)

    Spittle, A J; Olsen, J; Kwong, A; Doyle, L W; Marschik, P B; Einspieler, C; Cheong, Jly

    2016-10-03

    Infants born extremely preterm (EP; smartphone application (app) developed for caregivers to video and upload their infant's general movements to be scored remotely by a certified GMA assessor. The aim of this study is to determine the predictive ability of using the GMA via the Baby Moves app for neurodevelopmental impairment in infants born EP/ELBW. This prospective cohort study will recruit infants born EP/ELBW across the state of Victoria, Australia in 2016 and 2017. A control group of normal birth weight (>2500 g birth weight), term-born (≥37 weeks' gestation) infants will also be recruited as a local reference group. Parents will video their infant's general movements at two time points between 3 and 4 months' corrected age using the Baby Moves app. Videos will be scored by certified GMA assessors and classified as normal or abnormal. Parental satisfaction using the Baby Moves app will be assessed via survey. Neurodevelopmental outcome at 2 years' corrected age includes developmental delay according to the Bayley Scales of Infant and Toddler Development-III and cerebral palsy diagnosis. This study was approved by the Human Research and Ethics Committees at the Royal Children's Hospital, The Royal Women's Hospital, Monash Health and Mercy Health in Melbourne, Australia. Study findings will be disseminated via peer-reviewed publications and conference presentations. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  14. Ochratoxin A and citrinin loads in stored wheat grains: impact of grain dust and possible prediction using ergosterol measurement.

    Science.gov (United States)

    Tangni, E K; Pussemier, L

    2006-02-01

    Crop storage should be carried out under hygienic conditions to ensure safe products, but sometimes grain dust which has settled from previous storage may be left over and incorporated to the following stored grains. This paper describes the results obtained using a lab model developed in order to assess the impact of grain dust incorporation for its direct contribution as a contaminant but also as an inoculum in stored wheat. Settled grain dust (4 samples) released from Belgian grain storages were collected and analysed by HPLC for ergosterol, ochratoxin A (OTA) and citrinin (CIT) content. For OTA and for ergosterol, there was a high degree of variability in concentrations found in the dust samples (from 17.3-318 ng g(-1) and from 39-823 microg g(-1), respectively) whilst for CIT, the range was less significant (from 137-344 ng g(-1)). Incorporation of grain dust into wheat storage contributed to an increase in the concentrations of mycotoxins in the stored grain. Dust acts as a contaminant and as an inoculum. According to these two ways, patterns of mycotoxin generation vary with the nature of the mycotoxin, the mycotoxigenic potential of dust and the water activity of the wheat. OTA and CIT showed a very versatile image when considering the amounts of toxins produced under the selected experimental conditions. The development of a robust tool to forecast the mycotoxigenicity of dust was based on the determination of ergosterol content as a general marker of fungal biomass. Present results suggest that this predictive tool would only be valid for predicting the contamination level of CIT and OTA at reasonable moisture content (14-20%). The potential risk of having highly contaminated batches from stock to stock may thus occur and this paper discusses possible pathways leading to OTA and CIT contamination either under wet or dry storage conditions. We therefore, recommend taking precautionary measures not only by controlling and maintaining moisture at a

  15. On the applicability of extreme value statistics in the prediction of maximum pit depth in heavily corroded non-piggable buried pipelines

    Energy Technology Data Exchange (ETDEWEB)

    Alfonso, L. [Universidad Autonoma de la Ciudad de Mexico, Mexico D.F. 09790 (Mexico); Caleyo, F.; Hallen, J. M.; Araujo, J. [ESIQIE, Instituto Politecnico Nacional, Mexico D.F. (Mexico)

    2010-07-01

    Pitting corrosion entails serious risks in industrial plants, since a perforation resulting from a single pit can cause the failure of in-service components like water pipes, heat exchangers or oil tanks. A number of statistical methods have been suggested to estimate the maximum pit depth. Over the years, a successful application of extreme value analysis has been found in the application of the Gumbel distribution to predict the maximum pit depth from a smaller number of samples with small area. There is a lack of studies devoted to the applicability of the Gumbel method to the prediction of maximum pitting-corrosion depth. The aim of the work presented in this paper is to introduce a new strategy for the application of the Gumbel method in real pipelines. The methodology proposed is based on the fact that the clustered pattern of the pit depth distribution is less pronounced when the analysis is restricted to sections of the pipeline that exhibits similar characteristics.

  16. Predicting Extreme Droughts in Savannah Africa: A Comparison of Proxy and Direct Measures in Detecting Biomass Fluctuations, Trends and Their Causes.

    Science.gov (United States)

    Western, David; Mose, Victor N; Worden, Jeffrey; Maitumo, David

    2015-01-01

    We monitored pasture biomass on 20 permanent plots over 35 years to gauge the reliability of rainfall and NDVI as proxy measures of forage shortfalls in a savannah ecosystem. Both proxies are reliable indicators of pasture biomass at the onset of dry periods but fail to predict shortfalls in prolonged dry spells. In contrast, grazing pressure predicts pasture deficits with a high degree of accuracy. Large herbivores play a primary role in determining the severity of pasture deficits and variation across habitats. Grazing pressure also explains oscillations in plant biomass unrelated to rainfall. Plant biomass has declined steadily and biomass per unit of rainfall has fallen by a third, corresponding to a doubling in grazing intensity over the study period. The rising probability of forage deficits fits local pastoral perceptions of an increasing frequency of extreme shortfalls. The decline in forage is linked to sedentarization, range loss and herbivore compression into drought refuges, rather than climate change. The results show that the decline in rangeland productivity and increasing frequency of pasture shortfalls can be ameliorated by better husbandry practices and reinforces the need for ground monitoring to complement remote sensing in forecasting pasture shortfalls.

  17. Experimental investigation of ultimate loads

    Energy Technology Data Exchange (ETDEWEB)

    Petersen, S M; Larsen, G C; Antoniou, I; Lind, S O; Courtney, M [Risoe National Lab., Wind Energy and Atmospheric Physics, Roskilde (Denmark)

    1999-03-01

    Verification of the structural integrity of a wind turbine involves analysis of fatigue loading as well as ultimate loading. With the trend of persistently growing turbines, the ultimate loading seems to become relatively more important. For wind turbines designed according to the wind conditions prescribed in the IEC-61400 code, the ultimate load is often identified as the leading load parameter. Exemplified by the use of an extensive measurement campaign a procedure for evaluation of the extreme flap-wise bending moments, occurring during normal operating of a wind turbine, is presented. The structural measurements are made on a NEG Micon 650 kW wind turbine erected at a complex high wind site in Oak Creek, California. The turbine is located on the top of a ridge. The prevailing wind direction is perpendicular to the ridge, and the annual mean wind speed is 9.5 m/s. The associated wind field measurement, are taken from two instrumented masts erected less than one rotor diameter in front of the turbine in direction of the prevailing wind direction. Both masts are instrumented at different heights in order to gain insight of the 3D-wind speed structure over the entire rotor plane. Extreme distributions, associated with a recurrence period of 10 minutes, conditioned on the mean wind speed and the turbulence intensity are derived. Combined with the wind climate model proposed in the IEC standard, these distributions are used to predict extreme distributions with recurrence periods equal to one and fifty years, respectively. The synthesis of the conditioned PDF`s and the wind climate model is performed by means of Monte Carlo simulation. (au)

  18. Energy and carbon emissions analysis and prediction of complex petrochemical systems based on an improved extreme learning machine integrated interpretative structural model

    International Nuclear Information System (INIS)

    Han, Yongming; Zhu, Qunxiong; Geng, Zhiqiang; Xu, Yuan

    2017-01-01

    Highlights: • The ELM integrated ISM (ISM-ELM) method is proposed. • The proposed method is more efficient and accurate than the ELM through the UCI data set. • Energy and carbon emissions analysis and prediction of petrochemical industries based ISM-ELM is obtained. • The proposed method is valid in improving energy efficiency and reducing carbon emissions of ethylene plants. - Abstract: Energy saving and carbon emissions reduction of the petrochemical industry are affected by many factors. Thus, it is difficult to analyze and optimize the energy of complex petrochemical systems accurately. This paper proposes an energy and carbon emissions analysis and prediction approach based on an improved extreme learning machine (ELM) integrated interpretative structural model (ISM) (ISM-ELM). ISM based the partial correlation coefficient is utilized to analyze key parameters that affect the energy and carbon emissions of the complex petrochemical system, and can denoise and reduce dimensions of data to decrease the training time and errors of the ELM prediction model. Meanwhile, in terms of the model accuracy and the training time, the robustness and effectiveness of the ISM-ELM model are better than the ELM through standard data sets from the University of California Irvine (UCI) repository. Moreover, a multi-inputs and single-output (MISO) model of energy and carbon emissions of complex ethylene systems is established based on the ISM-ELM. Finally, detailed analyses and simulations using the real ethylene plant data demonstrate the effectiveness of the ISM-ELM and can guide the improvement direction of energy saving and carbon emissions reduction in complex petrochemical systems.

  19. A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities

    International Nuclear Information System (INIS)

    Vallières, M; El Naqa, I; Freeman, C R; Skamene, S R

    2015-01-01

    This study aims at developing a joint FDG-PET and MRI texture-based model for the early evaluation of lung metastasis risk in soft-tissue sarcomas (STSs). We investigate if the creation of new composite textures from the combination of FDG-PET and MR imaging information could better identify aggressive tumours. Towards this goal, a cohort of 51 patients with histologically proven STSs of the extremities was retrospectively evaluated. All patients had pre-treatment FDG-PET and MRI scans comprised of T1-weighted and T2-weighted fat-suppression sequences (T2FS). Nine non-texture features (SUV metrics and shape features) and forty-one texture features were extracted from the tumour region of separate (FDG-PET, T1 and T2FS) and fused (FDG-PET/T1 and FDG-PET/T2FS) scans. Volume fusion of the FDG-PET and MRI scans was implemented using the wavelet transform. The influence of six different extraction parameters on the predictive value of textures was investigated. The incorporation of features into multivariable models was performed using logistic regression. The multivariable modeling strategy involved imbalance-adjusted bootstrap resampling in the following four steps leading to final prediction model construction: (1) feature set reduction; (2) feature selection; (3) prediction performance estimation; and (4) computation of model coefficients. Univariate analysis showed that the isotropic voxel size at which texture features were extracted had the most impact on predictive value. In multivariable analysis, texture features extracted from fused scans significantly outperformed those from separate scans in terms of lung metastases prediction estimates. The best performance was obtained using a combination of four texture features extracted from FDG-PET/T1 and FDG-PET/T2FS scans. This model reached an area under the receiver-operating characteristic curve of 0.984 ± 0.002, a sensitivity of 0.955 ± 0.006, and a specificity of 0.926 ± 0.004 in bootstrapping

  20. System performance modeling of extreme ultraviolet lithographic thermal issues

    International Nuclear Information System (INIS)

    Spence, P. A.; Gianoulakis, S. E.; Moen, C. D.; Kanouff, M. P.; Fisher, A.; Ray-Chaudhuri, A. K.

    1999-01-01

    Numerical simulation is used in the development of an extreme ultraviolet lithography Engineering Test Stand. Extensive modeling was applied to predict the impact of thermal loads on key lithographic parameters such as image placement error, focal shift, and loss of CD control. We show that thermal issues can be effectively managed to ensure that their impact on lithographic performance is maintained within design error budgets. (c) 1999 American Vacuum Society

  1. HBeAg and not genotypes predicts viral load in patients with hepatitis B in Denmark: A nationwide cohort study

    DEFF Research Database (Denmark)

    Krarup, Henrik; Andersen, Stig; Madsen, Poul Henning

    2011-01-01

    To explore the influence of HBV genotype on viral load in patients with HBV infection, and to investigate the relation to gender, age and country of origin or antibodies against hepatitis Be antigen (anti-HBe).......To explore the influence of HBV genotype on viral load in patients with HBV infection, and to investigate the relation to gender, age and country of origin or antibodies against hepatitis Be antigen (anti-HBe)....

  2. HBeAg and not genotypes predicts viral load in patients with hepatitis B in Denmark: a nationwide cohort study

    DEFF Research Database (Denmark)

    Krarup, Henrik Bygum; Andersen, Stig; Madsen, Poul Henning

    2011-01-01

    To explore the influence of HBV genotype on viral load in patients with HBV infection, and to investigate the relation to gender, age and country of origin or antibodies against hepatitis Be antigen (anti-HBe).......To explore the influence of HBV genotype on viral load in patients with HBV infection, and to investigate the relation to gender, age and country of origin or antibodies against hepatitis Be antigen (anti-HBe)....

  3. Load and Global Response of Ships

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher

    The present monograph covers wave load and global structural response for ships. It is primary written as a textbook for students with an introductionary background in naval architecture and a basic knowledge of statistics and strength of materials. The subjects are treated in details starting from...... first principles. The aim has been to derive and present the necessary theoretical framework for predicting the extreme loads and the corresponding hull girder stresses the ship may be subjected to during its operational lifetime.Although some account is given to reliabiity analysis, the present...

  4. Regarding "A new method for predicting nonlinear structural vibrations induced by ground impact loading" [Journal of Sound and Vibration, 331/9 (2012) 2129-2140

    Science.gov (United States)

    Cartmell, Matthew P.

    2016-09-01

    The Editor wishes to make the reader aware that the paper "A new method for predicting nonlinear structural vibrations induced by ground impact loading" by Jun Liu, Yu Zhang, Bin Yun, Journal of Sound and Vibration, 331 (2012) 2129-2140, did not contain a direct citation of the fundamental and original work in this field by Dr. Mark Svinkin. The Editor regrets that this omission was not noted at the time that the above paper was accepted and published.

  5. A coupled diffusion-fluid pressure model to predict cell density distribution for cells encapsulated in a porous hydrogel scaffold under mechanical loading.

    Science.gov (United States)

    Zhao, Feihu; Vaughan, Ted J; Mc Garrigle, Myles J; McNamara, Laoise M

    2017-10-01

    Tissue formation within tissue engineering (TE) scaffolds is preceded by growth of the cells throughout the scaffold volume and attachment of cells to the scaffold substrate. It is known that mechanical stimulation, in the form of fluid perfusion or mechanical strain, enhances cell differentiation and overall tissue formation. However, due to the complex multi-physics environment of cells within TE scaffolds, cell transport under mechanical stimulation is not fully understood. Therefore, in this study, we have developed a coupled multiphysics model to predict cell density distribution in a TE scaffold. In this model, cell transport is modelled as a thermal conduction process, which is driven by the pore fluid pressure under applied loading. As a case study, the model is investigated to predict the cell density patterns of pre-osteoblasts MC3T3-e1 cells under a range of different loading regimes, to obtain an understanding of desirable mechanical stimulation that will enhance cell density distribution within TE scaffolds. The results of this study have demonstrated that fluid perfusion can result in a higher cell density in the scaffold region closed to the outlet, while cell density distribution under mechanical compression was similar with static condition. More importantly, the study provides a novel computational approach to predict cell distribution in TE scaffolds under mechanical loading. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Extreme cosmos

    CERN Document Server

    Gaensler, Bryan

    2011-01-01

    The universe is all about extremes. Space has a temperature 270°C below freezing. Stars die in catastrophic supernova explosions a billion times brighter than the Sun. A black hole can generate 10 million trillion volts of electricity. And hypergiants are stars 2 billion kilometres across, larger than the orbit of Jupiter. Extreme Cosmos provides a stunning new view of the way the Universe works, seen through the lens of extremes: the fastest, hottest, heaviest, brightest, oldest, densest and even the loudest. This is an astronomy book that not only offers amazing facts and figures but also re

  7. Life prediction of simple structures subject to cyclic primary and secondary loading resulting in creep and platicity

    International Nuclear Information System (INIS)

    Otter, N.R.; Jones, R.T.

    1979-01-01

    High temperature reactors are subject to cyclic mechanical and thermal loadings resulting from start up and shut down operations. The design must therefore guard against structural failure resulting from excessive deformation and creep-fatigue damage. Before any simplified inelastic analysis techniques can be applied, their validity needs to be examined under situations representative of the reactor. For this to be carried out it is necessary to determine the behaviour of components, initially geometrically simple, subject to loadings, cyclic primary and secondary in nature, which result in creep and plasticity. Beam-like structures have been investigated on a finite element basis with the aim of determining how cyclic plasticity, creep enhancement and plastic ratchetting vary in relationship with modified shakedown criteria, magnitude of loading and hold time. (orig.)

  8. Next Day Building Load Predictions based on Limited Input Features Using an On-Line Laterally Primed Adaptive Resonance Theory Artificial Neural Network.

    Energy Technology Data Exchange (ETDEWEB)

    Jones, Christian Birk [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Photovoltaic and Grid Integration Group; Robinson, Matt [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Mechanical Engineering; Yasaei, Yasser [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Electrical and Computer Engineering; Caudell, Thomas [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Electrical and Computer Engineering; Martinez-Ramon, Manel [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Electrical and Computer Engineering; Mammoli, Andrea [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Mechanical Engineering

    2016-07-01

    Optimal integration of thermal energy storage within commercial building applications requires accurate load predictions. Several methods exist that provide an estimate of a buildings future needs. Methods include component-based models and data-driven algorithms. This work implemented a previously untested algorithm for this application that is called a Laterally Primed Adaptive Resonance Theory (LAPART) artificial neural network (ANN). The LAPART algorithm provided accurate results over a two month period where minimal historical data and a small amount of input types were available. These results are significant, because common practice has often overlooked the implementation of an ANN. ANN have often been perceived to be too complex and require large amounts of data to provide accurate results. The LAPART neural network was implemented in an on-line learning manner. On-line learning refers to the continuous updating of training data as time occurs. For this experiment, training began with a singe day and grew to two months of data. This approach provides a platform for immediate implementation that requires minimal time and effort. The results from the LAPART algorithm were compared with statistical regression and a component-based model. The comparison was based on the predictions linear relationship with the measured data, mean squared error, mean bias error, and cost savings achieved by the respective prediction techniques. The results show that the LAPART algorithm provided a reliable and cost effective means to predict the building load for the next day.

  9. Undetectable plasma viral load predicts normal survival in HIV-2-infected people in a West African village

    Directory of Open Access Journals (Sweden)

    Ricard Dominique

    2010-05-01

    Full Text Available Abstract Background There have been no previous studies of the long-term survival and temporal changes in plasma viral load among HIV-2 infected subjects. Methods 133 HIV-2 infected and 158 HIV-uninfected subjects from a rural area in North-west Guinea-Bissau, West Africa were enrolled into a prospective cohort study in 1991 and followed-up to mid-2009. Data were collected on four occasions during that period on HIV antibodies, CD4% and HIV-2 plasma viral load. Results Median age (interquartile range [IQR] of HIV-2 infected subjects at time of enrollment was 47 (36, 60 years, similar to that of HIV-uninfected control subjects, 49 (38, 62 (p = 0.4. Median (IQR plasma viral load and CD4 percentage were 347 (50, 4,300 copies/ml and 29 (22, 35 respectively. Overall loss to follow-up to assess vital status was small, at 6.7% and 6.3% for HIV-2 infected and uninfected subjects respectively. An additional 17 (12.8% and 16 (10.1% of HIV-2 infected and uninfected subjects respectively were censored during follow-up due to infection with HIV-1. The mortality rate per 100 person-years (95% CI was 4.5 (3.6, 5.8 among HIV-2 infected subjects compared to 2.1 (1.6, 2.9 among HIV-uninfected (age-sex adjusted rate ratio 1.9 (1.3, 2.8, p Viral load measurements were available for 98%, 78%, 77% and 61% HIV-2 infected subjects who were alive and had not become super-infected with HIV-1, in 1991, 1996, 2003 and 2006 respectively. Median plasma viral load (RNA copies per ml (IQR did not change significantly over time, being 150 (50, 1,554; n = 77 in 1996, 203 (50, 2,837; n = 47 in 2003 and 171 (50, 497; n = 31 in 2006. Thirty seven percent of HIV-2 subjects had undetectable viraemia ( Conclusions A substantial proportion of HIV-2 infected subjects in this cohort have stable plasma viral load, and those with an undetectable viral load (37% at study entry had a normal survival rate. However, the sequential laboratory findings need to be interpreted with caution given

  10. Wind Simulation for Extreme and Fatigue Loads

    DEFF Research Database (Denmark)

    Nielsen, Morten; Larsen, Gunner Chr.; Mann, Jakob

    2003-01-01

    by many orders of magnitude, mainly because the measured pdf is non-Gaussian. Methods for simulation of turbulent signals have been developed and theircomputational efficiency are considered. The methods are applicable for multiple processes with individual spectra and probability distributions. Non...... is formulated as the variational problem of finding the most probable adjustment of a standard simulation of a stationary Gaussian process subject to relevant event conditions, which are formulated as linear combination of pointsin the realization. The method is generalized for multiple correlated series......Measurements of atmospheric turbulence have been studied and found to deviate from a Gaussian process, in particular regarding the velocity increments over small time steps, where the tails of the pdf are exponential rather than Gaussian. Principles forextreme event counting and the occurrence...

  11. Predicting Likelihood of Surgery Prior to First Visit in Patients with Back and Lower Extremity Symptoms: A simple mathematical model based on over 8000 patients.

    Science.gov (United States)

    Boden, Lauren M; Boden, Stephanie A; Premkumar, Ajay; Gottschalk, Michael B; Boden, Scott D

    2018-02-09

    Retrospective analysis of prospectively collected data. To create a data-driven triage system stratifying patients by likelihood of undergoing spinal surgery within one year of presentation. Low back pain (LBP) and radicular lower extremity (LE) symptoms are common musculoskeletal problems. There is currently no standard data-derived triage process based on information that can be obtained prior to the initial physician-patient encounter to direct patients to the optimal physician type. We analyzed patient-reported data from 8006 patients with a chief complaint of LBP and/or LE radicular symptoms who presented to surgeons at a large multidisciplinary spine center between September 1, 2005 and June 30, 2016. Univariate and multivariate analysis identified independent risk factors for undergoing spinal surgery within one year of initial visit. A model incorporating these risk factors was created using a random sample of 80% of the total patients in our cohort, and validated on the remaining 20%. The baseline one-year surgery rate within our cohort was 39% for all patients and 42% for patients with LE symptoms. Those identified as high likelihood by the center's existing triage process had a surgery rate of 45%. The new triage scoring system proposed in this study was able to identify a high likelihood group in which 58% underwent surgery, which is a 46% higher surgery rate than in non-triaged patients and a 29% improvement from our institution's existing triage system. The data-driven triage model and scoring system derived and validated in this study (Spine Surgery Likelihood model [SSL-11]), significantly improved existing processes in predicting the likelihood of undergoing spinal surgery within one year of initial presentation. This triage system will allow centers to more selectively screen for surgical candidates and more effectively direct patients to surgeons or non-operative spine specialists. 4.

  12. Hybrid model predictive control applied to switching control of burner load for a compact marine boiler design

    DEFF Research Database (Denmark)

    Solberg, Brian; Andersen, Palle; Maciejowski, Jan

    2008-01-01

    This paper discusses the application of hybrid model predictive control to control switching between different burner modes in a novel compact marine boiler design. A further purpose of the present work is to point out problems with finite horizon model predictive control applied to systems for w...

  13. Using AnnAGNPS to Predict the Effects of Tile Drainage Control on Nutrient and Sediment Loads for a River Basin.

    Science.gov (United States)

    Que, Z; Seidou, O; Droste, R L; Wilkes, G; Sunohara, M; Topp, E; Lapen, D R

    2015-03-01

    Controlled tile drainage (CTD) can reduce pollutant loading. The Annualized Agricultural Nonpoint Source model (AnnAGNPS version 5.2) was used to examine changes in growing season discharge, sediment, nitrogen, and phosphorus loads due to CTD for a ∼3900-km agriculturally dominated river basin in Ontario, Canada. Two tile drain depth scenarios were examined in detail to mimic tile drainage control for flat cropland: 600 mm depth (CTD) and 200 mm (CTD) depth below surface. Summed for five growing seasons (CTD), direct runoff, total N, and dissolved N were reduced by 6.6, 3.5, and 13.7%, respectively. However, five seasons of summed total P, dissolved P, and total suspended solid loads increased as a result of CTD by 0.96, 1.6, and 0.23%. The AnnAGNPS results were compared with mass fluxes observed from paired experimental watersheds (250, 470 ha) in the river basin. The "test" experimental watershed was dominated by CTD and the "reference" watershed by free drainage. Notwithstanding environmental/land use differences between the watersheds and basin, comparisons of seasonal observed and predicted discharge reductions were comparable in 100% of respective cases. Nutrient load comparisons were more consistent for dissolved, relative to particulate water quality endpoints. For one season under corn crop production, AnnAGNPS predicted a 55% decrease (CTD) in dissolved N from the basin. AnnAGNPS v. 5.2 treats P transport from a surface pool perspective, which is appropriate for many systems. However, for assessment of tile drainage management practices for relatively flat tile-dominated systems, AnnAGNPS may benefit from consideration of P and particulate transport in the subsurface. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

  14. The Efficacy of Intraoperative Neurophysiological Monitoring Using Transcranial Electrically Stimulated Muscle-evoked Potentials (TcE-MsEPs) for Predicting Postoperative Segmental Upper Extremity Motor Paresis After Cervical Laminoplasty.

    Science.gov (United States)

    Fujiwara, Yasushi; Manabe, Hideki; Izumi, Bunichiro; Tanaka, Hiroyuki; Kawai, Kazumi; Tanaka, Nobuhiro

    2016-05-01

    Prospective study. To investigate the efficacy of transcranial electrically stimulated muscle-evoked potentials (TcE-MsEPs) for predicting postoperative segmental upper extremity palsy following cervical laminoplasty. Postoperative segmental upper extremity palsy, especially in the deltoid and biceps (so-called C5 palsy), is the most common complication following cervical laminoplasty. Some papers have reported that postoperative C5 palsy cannot be predicted by TcE-MsEPs, although others have reported that it can be predicted. This study included 160 consecutive cases that underwent open-door laminoplasty, and TcE-MsEP monitoring was performed in the biceps brachii, triceps brachii, abductor digiti minimi, tibialis anterior, and abductor hallucis. A >50% decrease in the wave amplitude was defined as an alarm point. According to the monitoring alarm, interventions were performed, which include steroid administration, foraminotomies, etc. Postoperative deltoid and biceps palsy occurred in 5 cases. Among the 155 cases without segmental upper extremity palsy, there were no monitoring alarms. Among the 5 deltoid and biceps palsy cases, 3 had significant wave amplitude decreases in the biceps during surgery, and palsy occurred when the patients awoke from anesthesia (acute type). In the other 2 cases in which the palsy occurred 2 days after the operation (delayed type), there were no significant wave decreases. In all of the cases, the palsy was completely resolved within 6 months. The majority of C5 palsies have been reported to occur several days after surgery, but some of them have been reported to occur immediately after surgery. Our results demonstrated that TcE-MsEPs can predict the acute type, whereas the delayed type cannot be predicted. A >50% wave amplitude decrease in the biceps is useful to predict acute-type segmental upper extremity palsy. Further examination about the interventions for monitoring alarm will be essential for preventing palsy.

  15. How extreme is extreme hourly precipitation?

    Science.gov (United States)

    Papalexiou, Simon Michael; Dialynas, Yannis G.; Pappas, Christoforos

    2016-04-01

    The importance of accurate representation of precipitation at fine time scales (e.g., hourly), directly associated with flash flood events, is crucial in hydrological design and prediction. The upper part of a probability distribution, known as the distribution tail, determines the behavior of extreme events. In general, and loosely speaking, tails can be categorized in two families: the subexponential and the hyperexponential family, with the first generating more intense and more frequent extremes compared to the latter. In past studies, the focus has been mainly on daily precipitation, with the Gamma distribution being the most popular model. Here, we investigate the behaviour of tails of hourly precipitation by comparing the upper part of empirical distributions of thousands of records with three general types of tails corresponding to the Pareto, Lognormal, and Weibull distributions. Specifically, we use thousands of hourly rainfall records from all over the USA. The analysis indicates that heavier-tailed distributions describe better the observed hourly rainfall extremes in comparison to lighter tails. Traditional representations of the marginal distribution of hourly rainfall may significantly deviate from observed behaviours of extremes, with direct implications on hydroclimatic variables modelling and engineering design.

  16. Chondrocyte deformations as a function of tibiofemoral joint loading predicted by a generalized high-throughput pipeline of multi-scale simulations.

    Directory of Open Access Journals (Sweden)

    Scott C Sibole

    Full Text Available Cells of the musculoskeletal system are known to respond to mechanical loading and chondrocytes within the cartilage are not an exception. However, understanding how joint level loads relate to cell level deformations, e.g. in the cartilage, is not a straightforward task. In this study, a multi-scale analysis pipeline was implemented to post-process the results of a macro-scale finite element (FE tibiofemoral joint model to provide joint mechanics based displacement boundary conditions to micro-scale cellular FE models of the cartilage, for the purpose of characterizing chondrocyte deformations in relation to tibiofemoral joint loading. It was possible to identify the load distribution within the knee among its tissue structures and ultimately within the cartilage among its extracellular matrix, pericellular environment