Modeling and Parameter Estimation of a Small Wind Generation System
Directory of Open Access Journals (Sweden)
Carlos A. Ramírez Gómez
2013-11-01
Full Text Available The modeling and parameter estimation of a small wind generation system is presented in this paper. The system consists of a wind turbine, a permanent magnet synchronous generator, a three phase rectifier, and a direct current load. In order to estimate the parameters wind speed data are registered in a weather station located in the Fraternidad Campus at ITM. Wind speed data were applied to a reference model programed with PSIM software. From that simulation, variables were registered to estimate the parameters. The wind generation system model together with the estimated parameters is an excellent representation of the detailed model, but the estimated model offers a higher flexibility than the programed model in PSIM software.
Tokunaga, Yoshitaka; Kubota, Kunihiro
This paper presents estimation techniques of machine parameters for two windings power transformer using design procedure of winding structure. Especially, it is very difficult to obtain machine parameters for transformers in customers' facilities. Using estimation techniques, machine parameters could be calculated from the only nameplate data of these transformers. Subsequently, EMTP-ATP simulation of the inrush current was carried out using machine parameters estimated by design procedure of winding structure and simulation results were reproduced measured waveforms.
Estimation of Aircraft Nonlinear Unsteady Parameters From Wind Tunnel Data
Klein, Vladislav; Murphy, Patrick C.
1998-01-01
Aerodynamic equations were formulated for an aircraft in one-degree-of-freedom large amplitude motion about each of its body axes. The model formulation based on indicial functions separated the resulting aerodynamic forces and moments into static terms, purely rotary terms and unsteady terms. Model identification from experimental data combined stepwise regression and maximum likelihood estimation in a two-stage optimization algorithm that can identify the unsteady term and rotary term if necessary. The identification scheme was applied to oscillatory data in two examples. The model identified from experimental data fit the data well, however, some parameters were estimated with limited accuracy. The resulting model was a good predictor for oscillatory and ramp input data.
Hierarchical parameter estimation of DFIG and drive train system in a wind turbine generator
Pan, Xueping; Ju, Ping; Wu, Feng; Jin, Yuqing
2017-09-01
A new hierarchical parameter estimation method for doubly fed induction generator (DFIG) and drive train system in a wind turbine generator (WTG) is proposed in this paper. Firstly, the parameters of the DFIG and the drive train are estimated locally under different types of disturbances. Secondly, a coordination estimation method is further applied to identify the parameters of the DFIG and the drive train simultaneously with the purpose of attaining the global optimal estimation results. The main benefit of the proposed scheme is the improved estimation accuracy. Estimation results confirm the applicability of the proposed estimation technique.
Reliability Estimation of Parameters of Helical Wind Turbine with Vertical Axis
Dumitrascu, Adela-Eliza; Lepadatescu, Badea; Dumitrascu, Dorin-Ion; Nedelcu, Anisor; Ciobanu, Doina Valentina
2015-01-01
Due to the prolonged use of wind turbines they must be characterized by high reliability. This can be achieved through a rigorous design, appropriate simulation and testing, and proper construction. The reliability prediction and analysis of these systems will lead to identifying the critical components, increasing the operating time, minimizing failure rate, and minimizing maintenance costs. To estimate the produced energy by the wind turbine, an evaluation approach based on the Monte Carlo simulation model is developed which enables us to estimate the probability of minimum and maximum parameters. In our simulation process we used triangular distributions. The analysis of simulation results has been focused on the interpretation of the relative frequency histograms and cumulative distribution curve (ogive diagram), which indicates the probability of obtaining the daily or annual energy output depending on wind speed. The experimental researches consist in estimation of the reliability and unreliability functions and hazard rate of the helical vertical axis wind turbine designed and patented to climatic conditions for Romanian regions. Also, the variation of power produced for different wind speeds, the Weibull distribution of wind probability, and the power generated were determined. The analysis of experimental results indicates that this type of wind turbine is efficient at low wind speed. PMID:26167524
Reliability Estimation of Parameters of Helical Wind Turbine with Vertical Axis
Directory of Open Access Journals (Sweden)
Adela-Eliza Dumitrascu
2015-01-01
Full Text Available Due to the prolonged use of wind turbines they must be characterized by high reliability. This can be achieved through a rigorous design, appropriate simulation and testing, and proper construction. The reliability prediction and analysis of these systems will lead to identifying the critical components, increasing the operating time, minimizing failure rate, and minimizing maintenance costs. To estimate the produced energy by the wind turbine, an evaluation approach based on the Monte Carlo simulation model is developed which enables us to estimate the probability of minimum and maximum parameters. In our simulation process we used triangular distributions. The analysis of simulation results has been focused on the interpretation of the relative frequency histograms and cumulative distribution curve (ogive diagram, which indicates the probability of obtaining the daily or annual energy output depending on wind speed. The experimental researches consist in estimation of the reliability and unreliability functions and hazard rate of the helical vertical axis wind turbine designed and patented to climatic conditions for Romanian regions. Also, the variation of power produced for different wind speeds, the Weibull distribution of wind probability, and the power generated were determined. The analysis of experimental results indicates that this type of wind turbine is efficient at low wind speed.
Reliability Estimation of Parameters of Helical Wind Turbine with Vertical Axis.
Dumitrascu, Adela-Eliza; Lepadatescu, Badea; Dumitrascu, Dorin-Ion; Nedelcu, Anisor; Ciobanu, Doina Valentina
2015-01-01
Due to the prolonged use of wind turbines they must be characterized by high reliability. This can be achieved through a rigorous design, appropriate simulation and testing, and proper construction. The reliability prediction and analysis of these systems will lead to identifying the critical components, increasing the operating time, minimizing failure rate, and minimizing maintenance costs. To estimate the produced energy by the wind turbine, an evaluation approach based on the Monte Carlo simulation model is developed which enables us to estimate the probability of minimum and maximum parameters. In our simulation process we used triangular distributions. The analysis of simulation results has been focused on the interpretation of the relative frequency histograms and cumulative distribution curve (ogive diagram), which indicates the probability of obtaining the daily or annual energy output depending on wind speed. The experimental researches consist in estimation of the reliability and unreliability functions and hazard rate of the helical vertical axis wind turbine designed and patented to climatic conditions for Romanian regions. Also, the variation of power produced for different wind speeds, the Weibull distribution of wind probability, and the power generated were determined. The analysis of experimental results indicates that this type of wind turbine is efficient at low wind speed.
International Nuclear Information System (INIS)
Khahro, Shahnawaz Farhan; Tabbassum, Kavita; Soomro, Amir Mahmood; Dong, Lei; Liao, Xiaozhong
2014-01-01
Highlights: • Weibull scale and shape parameters are calculated using 5 numerical methods. • Yearly mean wind speed is 6.712 m/s at 80 m height with highest in May 9.595 m/s. • Yearly mean WPD is 310 W/m 2 and available energy density is 2716 kWh/m 2 at 80 m height. • Probability of higher wind speeds is more in spring and summer than in autumn and winter. • Estimated cost of per kWh of electricity from wind is calculated as 0.0263 US$/kWh. - Abstract: Pakistan is currently experiencing an acute shortage of energy and urgently needs new sources of affordable energy that could alleviate the misery of the energy starved masses. At present the government is increasing not only the conventional energy sources like hydel and thermal but also focusing on the immense potential of renewable energy sources like; solar, wind, biogas, waste-to-energy etc. The recent economic crisis worldwide, global warming and climate change have also emphasized the need for utilizing economic feasible energy sources having lowest carbon emissions. Wind energy, with its sustainability and low environmental impact, is highly prominent. The aim of this paper is to explore the wind power production prospective of one of the sites in south region of Pakistan. It is worth mentioning here that this type of detailed analysis is hardly done for any location in Pakistan. Wind power densities and frequency distributions of wind speed at four different altitudes along with estimated wind power expected to be generated through commercial wind turbines is calculated. Analysis and comparison of 5 numerical methods is presented in this paper to determine the Weibull scale and shape parameters for the available wind data. The yearly mean wind speed of the considered site is 6.712 m/s and has power density of 310 W/m 2 at 80 m height with high power density during April to August (highest in May with wind speed 9.595 m/s and power density 732 W/m 2 ). Economic evaluation, to exemplify feasibility
DEFF Research Database (Denmark)
Sales-Cruz, Mauricio; Heitzig, Martina; Cameron, Ian
2011-01-01
In this chapter the importance of parameter estimation in model development is illustrated through various applications related to reaction systems. In particular, rate constants in a reaction system are obtained through parameter estimation methods. These approaches often require the application...... of algebraic equations as the basis for parameter estimation.These approaches are illustrated using estimations of kinetic constants from reaction system models....
Aerodynamic Parameters of High Performance Aircraft Estimated from Wind Tunnel and Flight Test Data
Klein, Vladislav; Murphy, Patrick C.
1998-01-01
A concept of system identification applied to high performance aircraft is introduced followed by a discussion on the identification methodology. Special emphasis is given to model postulation using time invariant and time dependent aerodynamic parameters, model structure determination and parameter estimation using ordinary least squares an mixed estimation methods, At the same time problems of data collinearity detection and its assessment are discussed. These parts of methodology are demonstrated in examples using flight data of the X-29A and X-31A aircraft. In the third example wind tunnel oscillatory data of the F-16XL model are used. A strong dependence of these data on frequency led to the development of models with unsteady aerodynamic terms in the form of indicial functions. The paper is completed by concluding remarks.
National Aeronautics and Space Administration — ZONA Technology, Inc. (ZONA) proposes to develop an on-line flutter prediction tool for wind tunnel model using the parameter varying estimation (PVE) technique to...
National Aeronautics and Space Administration — ZONA Technology, Inc. (ZONA) proposes to develop an on-line flutter prediction tool for wind tunnel model using the parameter varying estimation (PVE) technique to...
Mathematical Model to estimate the wind power using four-parameter Burr distribution
Liu, Sanming; Wang, Zhijie; Pan, Zhaoxu
2018-03-01
When the real probability of wind speed in the same position needs to be described, the four-parameter Burr distribution is more suitable than other distributions. This paper introduces its important properties and characteristics. Also, the application of the four-parameter Burr distribution in wind speed prediction is discussed, and the expression of probability distribution of output power of wind turbine is deduced.
Directory of Open Access Journals (Sweden)
P Bhattacharya
2016-09-01
Full Text Available The wind resource varies with of the day and the season of the year and even some extent from year to year. Wind energy has inherent variances and hence it has been expressed by distribution functions. In this paper, we present some methods for estimating Weibull parameters in case of a low wind speed characterization, namely, shape parameter (k, scale parameter (c and characterize the discrete wind data sample by the discrete Hilbert transform. We know that the Weibull distribution is an important distribution especially for reliability and maintainability analysis. The suitable values for both shape parameter and scale parameters of Weibull distribution are important for selecting locations of installing wind turbine generators. The scale parameter of Weibull distribution also important to determine whether a wind farm is good or not. Thereafter the use of discrete Hilbert transform (DHT for wind speed characterization provides a new era of using DHT besides its application in digital signal processing. Basically in this paper, discrete Hilbert transform has been applied to characterize the wind sample data measured on College of Engineering and Management, Kolaghat, East Midnapore, India in January 2011.
Extreme wind estimate for Hornsea wind farm
DEFF Research Database (Denmark)
Larsén, Xiaoli Guo
The purpose of this study is to provide estimation of the 50-year winds of 10 min and 1-s gust value at hub height of 100 m, as well as the design parameter shear exponent for the Hornsea offshore wind farm. The turbulence intensity required for estimating the gust value is estimated using two ap....... The greatest sector-wise extreme winds are from west to northwest. Different data, different periods and different methods have provided a range of values of the 50-year wind and accordingly the gust values, as summarized in Table 15.......The purpose of this study is to provide estimation of the 50-year winds of 10 min and 1-s gust value at hub height of 100 m, as well as the design parameter shear exponent for the Hornsea offshore wind farm. The turbulence intensity required for estimating the gust value is estimated using two...... approaches. One is through the measurements from the wind Doppler lidar, WindCube, which implies serious uncertainty, and the other one is through similarity theory for the atmospheric surface layer where the hub height is likely to belong to during strong storms. The turbulence intensity for storm wind...
Martinović, M.
2017-12-01
Quasi-thermal noise (QTN) spectroscopy is an accurate technique for in situ measurements of electron density and temperature in space plasmas. The QTN spectrum has a characteristic noise peak just above the plasma frequency produced by electron quasi-thermal fluctuations, which allows a very accurate measurement of the electron density. The size and shape of the peak are determined by suprathermal electrons. Since this nonthermal electron population is well described by a generalized Lorentzian - Kappa velocity distribution, it is possible to determinate the distribution properties in the solar wind from a measured spectrum. In this work, we discuss some basic properties of the QTN spectrum dependence of the Kappa distribution parameters - total electron density, temperature and the Kappa index, giving an overview on how instrument characteristics and environment conditions affect quality of the measurements. Further on, we aim to apply the method to Wind Thermal Noise Receiver (TNR) measurements. However, the spectra observed by this instrument usually contain contributions from nonthermal phenomena, like ion acoustic waves below, or galactic noise above the plasma frequency. This is why, besides comparison of the theory with observations, work with Wind data requires development of a sophisticated algorithm that distinguish parts of the spectra that are dominated by the QTN, and therefore can be used in our study. Postulates of this algorithm, as well as major results of its implementation, are also presented.
Energy Technology Data Exchange (ETDEWEB)
Lee, Jared A.; Hacker, Joshua P.; Delle Monache, Luca; Kosović, Branko; Clifton, Andrew; Vandenberghe, Francois; Rodrigo, Javier Sanz
2016-12-14
A current barrier to greater deployment of offshore wind turbines is the poor quality of numerical weather prediction model wind and turbulence forecasts over open ocean. The bulk of development for atmospheric boundary layer (ABL) parameterization schemes has focused on land, partly due to a scarcity of observations over ocean. The 100-m FINO1 tower in the North Sea is one of the few sources worldwide of atmospheric profile observations from the sea surface to turbine hub height. These observations are crucial to developing a better understanding and modeling of physical processes in the marine ABL. In this study, we use the WRF single column model (SCM), coupled with an ensemble Kalman filter from the Data Assimilation Research Testbed (DART), to create 100-member ensembles at the FINO1 location. The goal of this study is to determine the extent to which model parameter estimation can improve offshore wind forecasts.
Wind Climate Parameters for Wind Turbine Fatigue Load Assessment
DEFF Research Database (Denmark)
Toft, Henrik Stensgaard; Svenningsen, Lasse; Moser, Wolfgang
2016-01-01
established from the on-site distribution functions of the horizontal mean wind speeds, the 90% quantile of turbulence along with average values of vertical wind shear and air density and the maximum flow inclination. This paper investigates the accuracy of fatigue loads estimated using this equivalent wind...... climate required by the current design standard by comparing damage equivalent fatigue loads estimated based on wind climate parameters for each 10 min time-series with fatigue loads estimated based on the equivalent wind climate parameters. Wind measurements from Boulder, CO, in the United States...... and Høvsøre in Denmark have been used to estimate the natural variation in the wind conditions between 10 min time periods. The structural wind turbine loads have been simulated using the aero-elastic model FAST. The results show that using a 90% quantile for the turbulence leads to an accurate assessment...
Directory of Open Access Journals (Sweden)
D. Kidmo Kaoga
2014-12-01
Full Text Available In this study, five numerical Weibull distribution methods, namely, the maximum likelihood method, the modified maximum likelihood method (MLM, the energy pattern factor method (EPF, the graphical method (GM, and the empirical method (EM were explored using hourly synoptic data collected from 1985 to 2013 in the district of Maroua in Cameroon. The performance analysis revealed that the MLM was the most accurate model followed by the EPF and the GM. Furthermore, the comparison between the wind speed standard deviation predicted by the proposed models and the measured data showed that the MLM has a smaller relative error of -3.33% on average compared to -11.67% on average for the EPF and -8.86% on average for the GM. As a result, the MLM was precisely recommended to estimate the scale and shape parameters for an accurate and efficient wind energy potential evaluation.
DEFF Research Database (Denmark)
Knudsen, Torben
2014-01-01
the results using full-scale wind turbine data. The previously developed methods were based on extended Kalman filtering. This method has several drawback compared to unscented Kalman filtering which has therefore been developed. The unscented Kalman filter was first tested on linear and non-linear test cases......Dynamic inflow is an effect which is normally not included in the models used for wind turbine control design. Therefore, potential improvement from including this effect exists. The objective in this project is to improve the methods previously developed for this and especially to verify...... which was successful. Then the estimation of a wind turbine state including dynamic inflow was tested on a simulated NREL 5MW turbine was performed. This worked perfectly with wind speeds from low to nominal wind speed as the output prediction errors where white. In high wind where the pitch actuator...
Tokunaga, Yoshitaka
This paper presents estimation techniques of machine parameters for power transformer using design procedure of transformer and genetic algorithm with real coding. Especially, it is very difficult to obtain machine parameters for transformers in customers' facilities. Using estimation techniques, machine parameters could be calculated from the only nameplate data of these transformers. Subsequently, EMTP-ATP simulation of the inrush current was carried out using machine parameters estimated by techniques developed in this study and simulation results were reproduced measured waveforms.
Directory of Open Access Journals (Sweden)
Ruben M. Mouangue
2014-05-01
Full Text Available The modeling of the wind speed distribution is of great importance for the assessment of wind energy potential and the performance of wind energy conversion system. In this paper, the choice of two determination methods of Weibull parameters shows theirs influences on the Weibull distribution performances. Because of important calm winds on the site of Ngaoundere airport, we characterize the wind potential using the approach of Weibull distribution with parameters which are determined by the modified maximum likelihood method. This approach is compared to the Weibull distribution with parameters which are determined by the maximum likelihood method and the hybrid distribution which is recommended for wind potential assessment of sites having nonzero probability of calm. Using data provided by the ASECNA Weather Service (Agency for the Safety of Air Navigation in Africa and Madagascar, we evaluate the goodness of fit of the various fitted distributions to the wind speed data using the Q – Q plots, the Pearson’s coefficient of correlation, the mean wind speed, the mean square error, the energy density and its relative error. It appears from the results that the accuracy of the Weibull distribution with parameters which are determined by the modified maximum likelihood method is higher than others. Then, this approach is used to estimate the monthly and annual energy productions of the site of the Ngaoundere airport. The most energy contribution is made in March with 255.7 MWh. It also appears from the results that a wind turbine generator installed on this particular site could not work for at least a half of the time because of higher frequency of calm. For this kind of sites, the modified maximum likelihood method proposed by Seguro and Lambert in 2000 is one of the best methods which can be used to determinate the Weibull parameters.
Fetisova, Yu. A.; Ermolenko, B. V.; Ermolenko, G. V.; Kiseleva, S. V.
2017-04-01
We studied the information basis for the assessment of wind power potential on the territory of Russia. We described the methodology to determine the parameters of the Weibull function, which reflects the density of distribution of probabilities of wind flow speeds at a defined basic height above the surface of the earth using the available data on the average speed at this height and its repetition by gradations. The application of the least square method for determining these parameters, unlike the use of graphical methods, allows performing a statistical assessment of the results of approximation of empirical histograms by the Weibull formula. On the basis of the computer-aided analysis of the statistical data, it was shown that, at a fixed point where the wind speed changes at different heights, the range of parameter variation of the Weibull distribution curve is relatively small, the sensitivity of the function to parameter changes is quite low, and the influence of changes on the shape of speed distribution curves is negligible. Taking this into consideration, we proposed and mathematically verified the methodology of determining the speed parameters of the Weibull function at other heights using the parameter computations for this function at a basic height, which is known or defined by the average speed of wind flow, or the roughness coefficient of the geological substrate. We gave examples of practical application of the suggested methodology in the development of the Atlas of Renewable Energy Resources in Russia in conditions of deficiency of source meteorological data. The proposed methodology, to some extent, may solve the problem related to the lack of information on the vertical profile of repeatability of the wind flow speeds in the presence of a wide assortment of wind turbines with different ranges of wind-wheel axis heights and various performance characteristics in the global market; as a result, this methodology can become a powerful tool for
Waszak, Martin R.; Fung, Jimmy
1998-01-01
This report describes the development of transfer function models for the trailing-edge and upper and lower spoiler actuators of the Benchmark Active Control Technology (BACT) wind tunnel model for application to control system analysis and design. A simple nonlinear least-squares parameter estimation approach is applied to determine transfer function parameters from frequency response data. Unconstrained quasi-Newton minimization of weighted frequency response error was employed to estimate the transfer function parameters. An analysis of the behavior of the actuators over time to assess the effects of wear and aerodynamic load by using the transfer function models is also presented. The frequency responses indicate consistent actuator behavior throughout the wind tunnel test and only slight degradation in effectiveness due to aerodynamic hinge loading. The resulting actuator models have been used in design, analysis, and simulation of controllers for the BACT to successfully suppress flutter over a wide range of conditions.
National Aeronautics and Space Administration — ZONA Technology, Inc. (ZONA) proposes to develop an on-line flutter prediction tool using the parameter varying estimation (PVE) methodology, called the PVE Toolbox,...
Offshore wind resource estimation for wind energy
DEFF Research Database (Denmark)
Hasager, Charlotte Bay; Badger, Merete; Mouche, A.
2010-01-01
Satellite remote sensing from active and passive microwave instruments is used to estimate the offshore wind resource in the Northern European Seas in the EU-Norsewind project. The satellite data include 8 years of Envisat ASAR, 10 years of QuikSCAT, and 23 years of SSM/I. The satellite observati......Satellite remote sensing from active and passive microwave instruments is used to estimate the offshore wind resource in the Northern European Seas in the EU-Norsewind project. The satellite data include 8 years of Envisat ASAR, 10 years of QuikSCAT, and 23 years of SSM/I. The satellite...... observations are compared to selected offshore meteorological masts in the Baltic Sea and North Sea. The overall aim of the Norsewind project is a state-of-the-art wind atlas at 100 m height. The satellite winds are all valid at 10 m above sea level. Extrapolation to higher heights is a challenge. Mesoscale...... modeling of the winds at hub height will be compared to data from wind lidars observing at 100 m above sea level. Plans are also to compare mesoscale model results and satellite-based estimates of the offshore wind resource....
Wind farm production estimates
DEFF Research Database (Denmark)
Larsen, Torben J.; Larsen, Gunner Chr.; Aagaard Madsen, Helge
2012-01-01
inves- tigated for a full polar (i.e. as function of mean inflow wind direction). This investigation relates to a mean wind speed bin defined as 8m=s±1m=s. The impact of ambient turbu- lence intensity and turbine inter spacing on the production of a wind turbine operating under full wake conditions...... is investi- gated. Four different turbine inter spacings, ranging between 3.8 and 10.4 rotor diameters, are analyzed for ambient turbu- lence intensities varying between 2% and 20%. This analysis is based on full scale production data from three other wind farms Wieringermeer [3], Horns Rev [4] and Nysted [5......]. A very satisfactory agreement between experimental data and predictions is observed. This paper finally includes additionally an analysis of the production impact caused by atmospheric stability effects. For this study, atmospheric stability conditions are defined in terms of the Monin-Obukhov length...
Knudsen, Torben
2014-01-01
Dynamic inflow is an effect which is normally not included in the models used for wind turbine control design. Therefore, potential improvement from including this effect exists. The objective in this project is to improve the methods previously developed for this and especially to verify the results using full-scale wind turbine data. The previously developed methods were based on extended Kalman filtering. This method has several drawback compared to unscented Kalman filtering which has the...
PESTO: Parameter EStimation TOolbox.
Stapor, Paul; Weindl, Daniel; Ballnus, Benjamin; Hug, Sabine; Loos, Carolin; Fiedler, Anna; Krause, Sabrina; Hroß, Sabrina; Fröhlich, Fabian; Hasenauer, Jan; Wren, Jonathan
2018-02-15
PESTO is a widely applicable and highly customizable toolbox for parameter estimation in MathWorks MATLAB. It offers scalable algorithms for optimization, uncertainty and identifiability analysis, which work in a very generic manner, treating the objective function as a black box. Hence, PESTO can be used for any parameter estimation problem, for which the user can provide a deterministic objective function in MATLAB. PESTO is a MATLAB toolbox, freely available under the BSD license. The source code, along with extensive documentation and example code, can be downloaded from https://github.com/ICB-DCM/PESTO/. jan.hasenauer@helmholtz-muenchen.de. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.
Are local wind power resources well estimated?
Lundtang Petersen, Erik; Troen, Ib; Jørgensen, Hans E.; Mann, Jakob
2013-03-01
Planning and financing of wind power installations require very importantly accurate resource estimation in addition to a number of other considerations relating to environment and economy. Furthermore, individual wind energy installations cannot in general be seen in isolation. It is well known that the spacing of turbines in wind farms is critical for maximum power production. It is also well established that the collective effect of wind turbines in large wind farms or of several wind farms can limit the wind power extraction downwind. This has been documented by many years of production statistics. For the very large, regional sized wind farms, a number of numerical studies have pointed to additional adverse changes to the regional wind climate, most recently by the detailed studies of Adams and Keith [1]. They show that the geophysical limit to wind power production is likely to be lower than previously estimated. Although this problem is of far future concern, it has to be considered seriously. In their paper they estimate that a wind farm larger than 100 km2 is limited to about 1 W m-2. However, a 20 km2 off shore farm, Horns Rev 1, has in the last five years produced 3.98 W m-2 [5]. In that light it is highly unlikely that the effects pointed out by [1] will pose any immediate threat to wind energy in coming decades. Today a number of well-established mesoscale and microscale models exist for estimating wind resources and design parameters and in many cases they work well. This is especially true if good local data are available for calibrating the models or for their validation. The wind energy industry is still troubled by many projects showing considerable negative discrepancies between calculated and actually experienced production numbers and operating conditions. Therefore it has been decided on a European Union level to launch a project, 'The New European Wind Atlas', aiming at reducing overall uncertainties in determining wind conditions. The
Wind resource estimation and siting of wind turbines
DEFF Research Database (Denmark)
Lundtang Petersen, Erik; Mortensen, N.G.; Landberg, L.
1994-01-01
Detailed knowledge of the characteristics of the natural wind is necessary for the design, planning and operational aspect of wind energy systems. Here, we shall only be concerned with those meteorological aspects of wind energy planning that are termed wind resource estimation. The estimation...... of the wind resource ranges from the overall estimation of the mean energy content of the wind over a large area - called regional assessment - to the prediction of the average yearly energy production of a specific wind turbine at a specific location - called siting. A regional assessment will most often...
Directory of Open Access Journals (Sweden)
Chen Wang
2016-01-01
Full Text Available Power systems could be at risk when the power-grid collapse accident occurs. As a clean and renewable resource, wind energy plays an increasingly vital role in reducing air pollution and wind power generation becomes an important way to produce electrical power. Therefore, accurate wind power and wind speed forecasting are in need. In this research, a novel short-term wind speed forecasting portfolio has been proposed using the following three procedures: (I data preprocessing: apart from the regular normalization preprocessing, the data are preprocessed through empirical model decomposition (EMD, which reduces the effect of noise on the wind speed data; (II artificially intelligent parameter optimization introduction: the unknown parameters in the support vector machine (SVM model are optimized by the cuckoo search (CS algorithm; (III parameter optimization approach modification: an improved parameter optimization approach, called the SDCS model, based on the CS algorithm and the steepest descent (SD method is proposed. The comparison results show that the simple and effective portfolio EMD-SDCS-SVM produces promising predictions and has better performance than the individual forecasting components, with very small root mean squared errors and mean absolute percentage errors.
Fault Detection of Wind Turbines with Uncertain Parameters
DEFF Research Database (Denmark)
Tabatabaeipour, Seyed Mojtaba; Odgaard, Peter Fogh; Bak, Thomas
2012-01-01
on the torque coefficient. High noise on the wind speed measurement, nonlinearities in the aerodynamic torque and uncertainties on the parameters make fault detection a challenging problem. We use an effective wind speed estimator to reduce the noise on the wind speed measurements. A set-membership approach...... is detected. For representation of these sets we use zonotopes and for modeling of uncertainties we use matrix zonotopes, which yields a computationally efficient algorithm. The method is applied to the wind turbine benchmark problem without and with uncertainties. The result demonstrates the effectiveness...
Improved diagnostic model for estimating wind energy
Energy Technology Data Exchange (ETDEWEB)
Endlich, R.M.; Lee, J.D.
1983-03-01
Because wind data are available only at scattered locations, a quantitative method is needed to estimate the wind resource at specific sites where wind energy generation may be economically feasible. This report describes a computer model that makes such estimates. The model uses standard weather reports and terrain heights in deriving wind estimates; the method of computation has been changed from what has been used previously. The performance of the current model is compared with that of the earlier version at three sites; estimates of wind energy at four new sites are also presented.
Optimum Operational Parameters for Yawed Wind Turbines
Directory of Open Access Journals (Sweden)
David A. Peters
2011-01-01
Full Text Available A set of systematical optimum operational parameters for wind turbines under various wind directions is derived by using combined momentum-energy and blade-element-energy concepts. The derivations are solved numerically by fixing some parameters at practical values. Then, the interactions between the produced power and the influential factors of it are generated in the figures. It is shown that the maximum power produced is strongly affected by the wind direction, the tip speed, the pitch angle of the rotor, and the drag coefficient, which are specifically indicated by figures. It also turns out that the maximum power can take place at two different optimum tip speeds in some cases. The equations derived herein can also be used in the modeling of tethered wind turbines which can keep aloft and deliver energy.
Aswath Damodaran
1999-01-01
Over the last three decades, the capital asset pricing model has occupied a central and often controversial place in most corporate finance analysts’ tool chests. The model requires three inputs to compute expected returns – a riskfree rate, a beta for an asset and an expected risk premium for the market portfolio (over and above the riskfree rate). Betas are estimated, by most practitioners, by regressing returns on an asset against a stock index, with the slope of the regression being the b...
Parameter estimation in food science.
Dolan, Kirk D; Mishra, Dharmendra K
2013-01-01
Modeling includes two distinct parts, the forward problem and the inverse problem. The forward problem-computing y(t) given known parameters-has received much attention, especially with the explosion of commercial simulation software. What is rarely made clear is that the forward results can be no better than the accuracy of the parameters. Therefore, the inverse problem-estimation of parameters given measured y(t)-is at least as important as the forward problem. However, in the food science literature there has been little attention paid to the accuracy of parameters. The purpose of this article is to summarize the state of the art of parameter estimation in food science, to review some of the common food science models used for parameter estimation (for microbial inactivation and growth, thermal properties, and kinetics), and to suggest a generic method to standardize parameter estimation, thereby making research results more useful. Scaled sensitivity coefficients are introduced and shown to be important in parameter identifiability. Sequential estimation and optimal experimental design are also reviewed as powerful parameter estimation methods that are beginning to be used in the food science literature.
WIND TURBINE OPERATION PARAMETER CHARACTERISTICS AT A GIVEN WIND SPEED
Directory of Open Access Journals (Sweden)
Zdzisław Kamiński
2014-06-01
Full Text Available This paper discusses the results of the CFD simulation of the flow around Vertical Axis Wind Turbine rotor. The examined rotor was designed following patent application no. 402214. The turbine operation is characterised by parameters, such as opening angle of blades, power, torque, rotational velocity at a given wind velocity. Those parameters have an impact on the performance of entire assembly. The distribution of forces acting on the working surfaces in the turbine can change, depending on the angle of rotor rotation. Moreover, the resultant force derived from the force acting on the oncoming and leaving blades should be as high as possible. Accordingly, those parameters were individually simulated over time for each blade in three complete rotations. The attempts to improve the performance of the entire system resulted in a new research trend to improve the performance of working turbine rotor blades.
Wind Resource Estimation using QuikSCAT Ocean Surface Winds
DEFF Research Database (Denmark)
Xu, Qing; Zhang, Guosheng; Cheng, Yongcun
2011-01-01
In this study, the offshore wind resources in the East China Sea and South China Sea were estimated from over ten years of QuikSCAT scatterometer wind products. Since the errors of these products are larger close to the coast due to the land contamination of radar backscatter signal and the compl...
Wind Resource Estimation using QuikSCAT Ocean Surface Winds
DEFF Research Database (Denmark)
Xu, Qing; Zhang, Guosheng; Cheng, Yongcun
2011-01-01
In this study, the offshore wind resources in the East China Sea and South China Sea were estimated from over ten years of QuikSCAT scatterometer wind products. Since the errors of these products are larger close to the coast due to the land contamination of radar backscatter signal...
Wind power error estimation in resource assessments.
Rodríguez, Osvaldo; Del Río, Jesús A; Jaramillo, Oscar A; Martínez, Manuel
2015-01-01
Estimating the power output is one of the elements that determine the techno-economic feasibility of a renewable project. At present, there is a need to develop reliable methods that achieve this goal, thereby contributing to wind power penetration. In this study, we propose a method for wind power error estimation based on the wind speed measurement error, probability density function, and wind turbine power curves. This method uses the actual wind speed data without prior statistical treatment based on 28 wind turbine power curves, which were fitted by Lagrange's method, to calculate the estimate wind power output and the corresponding error propagation. We found that wind speed percentage errors of 10% were propagated into the power output estimates, thereby yielding an error of 5%. The proposed error propagation complements the traditional power resource assessments. The wind power estimation error also allows us to estimate intervals for the power production leveled cost or the investment time return. The implementation of this method increases the reliability of techno-economic resource assessment studies.
Estimation of wind characteristics at potential wind energy conversion sites
Energy Technology Data Exchange (ETDEWEB)
1979-10-01
A practical method has been developed and applied to the problem of determining wind characteristics at candidate wind energy conversion sites where there are no available historical data. The method uses a mass consistent wind flow model (called COMPLEX) to interpolate between stations where wind data are available. The COMPLEX model incorporates the effects of terrain features and airflow. The key to the practical application of COMPLEX to the derivation of wind statistics is the model's linearity. This allows the input data sets to be resolved into orthogonal components along the set of eigenvectors of the covariance matrix. The solution for each eigenvector is determined with COMPLEX; the hourly interpolated winds are then formed from linear combinations of these solutions. The procedure requires: acquisition and merger of wind data from three to five stations, application of COMPLEX to each of the seven to 11 (depending on the number of stations for which wind data are available) eigenvectors, reconstruction of the hourly interpolated winds at the site from the eigenvector solutions, and finally, estimating the wind characteristics from the simulated hourly values. The report describes the methodology and the underlying theory. Possible improvements to the procedure are also discussed.
Stellar and wind parameters of massive stars from spectral analysis
Araya, Ignacio; Curé, Michel
2017-11-01
The only way to deduce information from stars is to decode the radiation it emits in an appropriate way. Spectroscopy can solve this and derive many properties of stars. In this work we seek to derive simultaneously the stellar and wind characteristics of a wide range of massive stars. Our stellar properties encompass the effective temperature, the surface gravity, the stellar radius, the micro-turbulence velocity, the rotational velocity and the Si abundance. For wind properties we consider the mass-loss rate, the terminal velocity and the line-force parameters α, k and δ (from the line-driven wind theory). To model the data we use the radiative transport code Fastwind considering the newest hydrodynamical solutions derived with Hydwind code, which needs stellar and line-force parameters to obtain a wind solution. A grid of spectral models of massive stars is created and together with the observed spectra their physical properties are determined through spectral line fittings. These fittings provide an estimation about the line-force parameters, whose theoretical calculations are extremely complex. Furthermore, we expect to confirm that the hydrodynamical solutions obtained with a value of δ slightly larger than ~ 0.25, called δ-slow solutions, describe quite reliable the radiation line-driven winds of A and late B supergiant stars and at the same time explain disagreements between observational data and theoretical models for the Wind-Momentum Luminosity Relationship (WLR).
Parameter estimation in plasmonic QED
Jahromi, H. Rangani
2018-03-01
We address the problem of parameter estimation in the presence of plasmonic modes manipulating emitted light via the localized surface plasmons in a plasmonic waveguide at the nanoscale. The emitter that we discuss is the nitrogen vacancy centre (NVC) in diamond modelled as a qubit. Our goal is to estimate the β factor measuring the fraction of emitted energy captured by waveguide surface plasmons. The best strategy to obtain the most accurate estimation of the parameter, in terms of the initial state of the probes and different control parameters, is investigated. In particular, for two-qubit estimation, it is found although we may achieve the best estimation at initial instants by using the maximally entangled initial states, at long times, the optimal estimation occurs when the initial state of the probes is a product one. We also find that decreasing the interqubit distance or increasing the propagation length of the plasmons improve the precision of the estimation. Moreover, decrease of spontaneous emission rate of the NVCs retards the quantum Fisher information (QFI) reduction and therefore the vanishing of the QFI, measuring the precision of the estimation, is delayed. In addition, if the phase parameter of the initial state of the two NVCs is equal to πrad, the best estimation with the two-qubit system is achieved when initially the NVCs are maximally entangled. Besides, the one-qubit estimation has been also analysed in detail. Especially, we show that, using a two-qubit probe, at any arbitrary time, enhances considerably the precision of estimation in comparison with one-qubit estimation.
Improved Estimates of Moments and Winds from Radar Wind Profiler
Energy Technology Data Exchange (ETDEWEB)
Helmus, Jonathan [Argonne National Lab. (ANL), Argonne, IL (United States); Ghate, Virendra P. [Argonne National Lab. (ANL), Argonne, IL (United States)
2017-01-02
The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) operates nine radar wind profilers (RWP) across its sites. These RWPs operate at 915 MHz or 1290 MHz frequency and report the first three moments of the Doppler spectrum. The operational settings of the RWP were modified in summer, 2015 to have single pulse length setting for the wind mode and two pulse length settings for the precipitation mode. The moments data collected during the wind mode are used to retrieve horizontal winds. The vendor-reported winds are available at variable time resolution (10 mins, 60 mins, etc.) and contain a significant amount of contamination due to noise and clutter. In this data product we have recalculated the moments and the winds from the raw radar Doppler spectrum and have made efforts to mitigate the contamination due to instrument noise in the wind estimates. Additionally, the moments and wind data has been reported in a harmonized layout identical for all locations and sites.
Extreme gust wind estimation using mesoscale modeling
DEFF Research Database (Denmark)
Larsén, Xiaoli Guo; Kruger, Andries
2014-01-01
Currently, the existing estimation of the extreme gust wind, e.g. the 50-year winds of 3 s values, in the IEC standard, is based on a statistical model to convert the 1:50-year wind values from the 10 min resolution. This statistical model assumes a Gaussian process that satisfies the classical...... through turbulent eddies. This process is modeled using the mesoscale Weather Forecasting and Research (WRF) model. The gust at the surface is calculated as the largest winds over a layer where the averaged turbulence kinetic energy is greater than the averaged buoyancy force. The experiments have been...
Parameter estimation and inverse problems
Aster, Richard C; Thurber, Clifford H
2005-01-01
Parameter Estimation and Inverse Problems primarily serves as a textbook for advanced undergraduate and introductory graduate courses. Class notes have been developed and reside on the World Wide Web for faciliting use and feedback by teaching colleagues. The authors'' treatment promotes an understanding of fundamental and practical issus associated with parameter fitting and inverse problems including basic theory of inverse problems, statistical issues, computational issues, and an understanding of how to analyze the success and limitations of solutions to these probles. The text is also a practical resource for general students and professional researchers, where techniques and concepts can be readily picked up on a chapter-by-chapter basis.Parameter Estimation and Inverse Problems is structured around a course at New Mexico Tech and is designed to be accessible to typical graduate students in the physical sciences who may not have an extensive mathematical background. It is accompanied by a Web site that...
Parameter Estimation Using VLA Data
Venter, Willem C.
The main objective of this dissertation is to extract parameters from multiple wavelength images, on a pixel-to-pixel basis, when the images are corrupted with noise and a point spread function. The data used are from the field of radio astronomy. The very large array (VLA) at Socorro in New Mexico was used to observe planetary nebula NGC 7027 at three different wavelengths, 2 cm, 6 cm and 20 cm. A temperature model, describing the temperature variation in the nebula as a function of optical depth, is postulated. Mathematical expressions for the brightness distribution (flux density) of the nebula, at the three observed wavelengths, are obtained. Using these three equations and the three data values available, one from the observed flux density map at each wavelength, it is possible to solve for two temperature parameters and one optical depth parameter at each pixel location. Due to the fact that the number of unknowns equal the number of equations available, estimation theory cannot be used to smooth any noise present in the data values. It was found that a direct solution of the three highly nonlinear flux density equations is very sensitive to noise in the data. Results obtained from solving for the three unknown parameters directly, as discussed above, were not physical realizable. This was partly due to the effect of incomplete sampling at the time when the data were gathered and to noise in the system. The application of rigorous digital parameter estimation techniques result in estimated parameters that are also not physically realizable. The estimated values for the temperature parameters are for example either too high or negative, which is not physically possible. Simulation studies have shown that a "double smoothing" technique improves the results by a large margin. This technique consists of two parts: in the first part the original observed data are smoothed using a running window and in the second part a similar smoothing of the estimated parameters
Inflation and cosmological parameter estimation
Energy Technology Data Exchange (ETDEWEB)
Hamann, J.
2007-05-15
In this work, we focus on two aspects of cosmological data analysis: inference of parameter values and the search for new effects in the inflationary sector. Constraints on cosmological parameters are commonly derived under the assumption of a minimal model. We point out that this procedure systematically underestimates errors and possibly biases estimates, due to overly restrictive assumptions. In a more conservative approach, we analyse cosmological data using a more general eleven-parameter model. We find that regions of the parameter space that were previously thought ruled out are still compatible with the data; the bounds on individual parameters are relaxed by up to a factor of two, compared to the results for the minimal six-parameter model. Moreover, we analyse a class of inflation models, in which the slow roll conditions are briefly violated, due to a step in the potential. We show that the presence of a step generically leads to an oscillating spectrum and perform a fit to CMB and galaxy clustering data. We do not find conclusive evidence for a step in the potential and derive strong bounds on quantities that parameterise the step. (orig.)
Wind Speed Preview Measurement and Estimation for Feedforward Control of Wind Turbines
Simley, Eric J.
Wind turbines typically rely on feedback controllers to maximize power capture in below-rated conditions and regulate rotor speed during above-rated operation. However, measurements of the approaching wind provided by Light Detection and Ranging (lidar) can be used as part of a preview-based, or feedforward, control system in order to improve rotor speed regulation and reduce structural loads. But the effectiveness of preview-based control depends on how accurately lidar can measure the wind that will interact with the turbine. In this thesis, lidar measurement error is determined using a statistical frequency-domain wind field model including wind evolution, or the change in turbulent wind speeds between the time they are measured and when they reach the turbine. Parameters of the National Renewable Energy Laboratory (NREL) 5-MW reference turbine model are used to determine measurement error for a hub-mounted circularly-scanning lidar scenario, based on commercially-available technology, designed to estimate rotor effective uniform and shear wind speed components. By combining the wind field model, lidar model, and turbine parameters, the optimal lidar scan radius and preview distance that yield the minimum mean square measurement error, as well as the resulting minimum achievable error, are found for a variety of wind conditions. With optimized scan scenarios, it is found that relatively low measurement error can be achieved, but the attainable measurement error largely depends on the wind conditions. In addition, the impact of the induction zone, the region upstream of the turbine where the approaching wind speeds are reduced, as well as turbine yaw error on measurement quality is analyzed. In order to minimize the mean square measurement error, an optimal measurement prefilter is employed, which depends on statistics of the correlation between the preview measurements and the wind that interacts with the turbine. However, because the wind speeds encountered by
Experimental Wind Field Estimation and Aircraft Identification
Condomines, Jean-Philippe; Bronz, Murat; Hattenberger, Gautier; Erdelyi, Jean-François
2015-01-01
International audience; The presented work is focusing on the wind estimation and airframe identification based on real flight experiments as part of the SkyScanner project. The overall objective of this project is to estimate the local wind field in order to study the formation of cumulus-type clouds with a fleet of autonomous mini-UAVs involving many aspects including flight control and energy harvesting. For this purpose, a small UAV has been equipped with airspeed and angle of attack sens...
Assessment of Wind Parameter Sensitivity on Ultimate and Fatigue Wind Turbine Loads: Preprint
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)
2018-02-13
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.
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.
Applied parameter estimation for chemical engineers
Englezos, Peter
2000-01-01
Formulation of the parameter estimation problem; computation of parameters in linear models-linear regression; Gauss-Newton method for algebraic models; other nonlinear regression methods for algebraic models; Gauss-Newton method for ordinary differential equation (ODE) models; shortcut estimation methods for ODE models; practical guidelines for algorithm implementation; constrained parameter estimation; Gauss-Newton method for partial differential equation (PDE) models; statistical inferences; design of experiments; recursive parameter estimation; parameter estimation in nonlinear thermodynam
Data Handling and Parameter Estimation
DEFF Research Database (Denmark)
Sin, Gürkan; Gernaey, Krist
2016-01-01
literature that are mostly based on the ActivatedSludge Model (ASM) framework and their appropriate extensions (Henze et al., 2000).The chapter presents an overview of the most commonly used methods in the estimation of parameters from experimental batch data, namely: (i) data handling and validation, (ii...... and spatial scales. At full-scale wastewater treatment plants (WWTPs),mechanistic modelling using the ASM framework and concept (e.g. Henze et al., 2000) has become an important part of the engineering toolbox for process engineers. It supports plant design, operation, optimization and control applications......). Models have also been used as an integral part of the comprehensive analysis and interpretation of data obtained from a range of experimental methods from the laboratory, as well as pilot-scale studies to characterise and study wastewater treatment plants. In this regard, models help to properly explain...
Dst Prediction Based on Solar Wind Parameters
Directory of Open Access Journals (Sweden)
Yoon-Kyung Park
2009-12-01
Full Text Available We reevaluate the Burton equation (Burton et al. 1975 of predicting Dst index using high quality hourly solar wind data supplied by the ACE satellite for the period from 1998 to 2006. Sixty magnetic storms with monotonously decreasing main phase are selected. In order to determine the injection term (Q and the decay time (tau of the equation, we examine the relationships between Dst* and VB_s, Delta Dst* and VB_s, and Delta Dst* and Dst* during the magnetic storms. For this analysis, we take into account one hour of the propagation time from the ACE satellite to the magnetopause, and a half hour of the response time of the magnetosphere/ring current to the solar wind forcing. The injection term is found to be Q({nT}/h=-3.56VB_s for VB_s>0.5mV/m and Q({nT}/h=0 for VB_s leq0.5mV/m. The tau (hour is estimated as 0.060 Dst* + 16.65 for Dst*>-175nT and 6.15 hours for Dst* leq -175nT. Based on these empirical relationships, we predict the 60 magnetic storms and find that the correlation coefficient between the observed and predicted Dst* is 0.88. To evaluate the performance of our prediction scheme, the 60 magnetic storms are predicted again using the models by Burton et al. (1975 and O'Brien & McPherron (2000a. The correlation coefficients thus obtained are 0.85, the same value for both of the two models. In this respect, our model is slightly improved over the other two models as far as the correlation coefficients is concerned. Particularly our model does a better job than the other two models in predicting intense magnetic storms (Dst* lesssim -200nT.
Structured Linear Parameter Varying Control of Wind Turbines
DEFF Research Database (Denmark)
Adegas, Fabiano Daher; Sloth, Christoffer; Stoustrup, Jakob
2012-01-01
High performance and reliability are required for wind turbines to be competitive within the energy market. To capture their nonlinear behavior, wind turbines are often modeled using parameter-varying models. In this chapter, a framework for modelling and controller design of wind turbines is pre...
Estimating near-shore wind resources
DEFF Research Database (Denmark)
Floors, Rogier Ralph; Hahmann, Andrea N.; Peña, Alfredo
An evaluation and sensitivity study using the WRF mesoscale model to estimate the wind in a coastal area is performed using a unique data set consisting of scanning, profiling and floating lidars. The ability of the WRF model to represent the wind speed was evaluated by running the model for a four...... RMSE and correlation coefficient. Using a finer grid spacing of 1 and 0.5 km did not give better results and sensitivity to the input of different SST and land cover data in the RUNE area was small. The difference in mean wind speed between all simulations over a region 80 km around the RUNE area were...... month period in twelve different set-ups. The atmospheric boundary layer was parametrized using the first-order YSU scheme and the 1.5-order MYJ scheme. Simulations with two sources of land use data, two sources of reanalysis data, two sources of sea-surface temperatures and three different horizontal...
Mooring line damping estimation for a floating wind turbine.
Qiao, Dongsheng; Ou, Jinping
2014-01-01
The dynamic responses of mooring line serve important functions in the station keeping of a floating wind turbine (FWT). Mooring line damping significantly influences the global motions of a FWT. This study investigates the estimation of mooring line damping on the basis of the National Renewable Energy Laboratory 5 MW offshore wind turbine model that is mounted on the ITI Energy barge. A numerical estimation method is derived from the energy absorption of a mooring line resulting from FWT motion. The method is validated by performing a 1/80 scale model test. Different parameter changes are analyzed for mooring line damping induced by horizontal and vertical motions. These parameters include excitation amplitude, excitation period, and drag coefficient. Results suggest that mooring line damping must be carefully considered in the FWT design.
Mooring Line Damping Estimation for a Floating Wind Turbine
Directory of Open Access Journals (Sweden)
Dongsheng Qiao
2014-01-01
Full Text Available The dynamic responses of mooring line serve important functions in the station keeping of a floating wind turbine (FWT. Mooring line damping significantly influences the global motions of a FWT. This study investigates the estimation of mooring line damping on the basis of the National Renewable Energy Laboratory 5 MW offshore wind turbine model that is mounted on the ITI Energy barge. A numerical estimation method is derived from the energy absorption of a mooring line resulting from FWT motion. The method is validated by performing a 1/80 scale model test. Different parameter changes are analyzed for mooring line damping induced by horizontal and vertical motions. These parameters include excitation amplitude, excitation period, and drag coefficient. Results suggest that mooring line damping must be carefully considered in the FWT design.
Study on Parameters Modeling of Wind Turbines Using SCADA Data
Directory of Open Access Journals (Sweden)
Yonglong YAN
2014-08-01
Full Text Available Taking the advantage of the current massive monitoring data from Supervisory Control and Data Acquisition (SCADA system of wind farm, it is of important significance for anomaly detection, early warning and fault diagnosis to build the data model of state parameters of wind turbines (WTs. The operational conditions and the relationships between the state parameters of wind turbines are complex. It is difficult to establish the model of state parameter accurately, and the modeling method of state parameters of wind turbines considering parameter selection is proposed. Firstly, by analyzing the characteristic of SCADA data, a reasonable range of data and monitoring parameters are chosen. Secondly, neural network algorithm is adapted, and the selection method of input parameters in the model is presented. Generator bearing temperature and cooling air temperature are regarded as target parameters, and the two models are built and input parameters of the models are selected, respectively. Finally, the parameter selection method in this paper and the method using genetic algorithm-partial least square (GA-PLS are analyzed comparatively, and the results show that the proposed methods are correct and effective. Furthermore, the modeling of two parameters illustrate that the method in this paper can applied to other state parameters of wind turbines.
Parameter Estimation in Continuous Time Domain
Directory of Open Access Journals (Sweden)
Gabriela M. ATANASIU
2016-12-01
Full Text Available This paper will aim to presents the applications of a continuous-time parameter estimation method for estimating structural parameters of a real bridge structure. For the purpose of illustrating this method two case studies of a bridge pile located in a highly seismic risk area are considered, for which the structural parameters for the mass, damping and stiffness are estimated. The estimation process is followed by the validation of the analytical results and comparison with them to the measurement data. Further benefits and applications for the continuous-time parameter estimation method in civil engineering are presented in the final part of this paper.
Improving Lidar Turbulence Estimates for Wind Energy
Energy Technology Data Exchange (ETDEWEB)
Newman, Jennifer F.; Clifton, Andrew; Churchfield, Matthew J.; Klein, Petra
2016-10-06
Remote sensing devices (e.g., lidars) are quickly becoming a cost-effective and reliable alternative to meteorological towers for wind energy applications. Although lidars can measure mean wind speeds accurately, these devices measure different values of turbulence intensity (TI) than an instrument on a tower. In response to these issues, a lidar TI error reduction model was recently developed for commercially available lidars. The TI error model first applies physics-based corrections to the lidar measurements, then uses machine-learning techniques to further reduce errors in lidar TI estimates. The model was tested at two sites in the Southern Plains where vertically profiling lidars were collocated with meteorological towers. This presentation primarily focuses on the physics-based corrections, which include corrections for instrument noise, volume averaging, and variance contamination. As different factors affect TI under different stability conditions, the combination of physical corrections applied in L-TERRA changes depending on the atmospheric stability during each 10-minute time period. This stability-dependent version of L-TERRA performed well at both sites, reducing TI error and bringing lidar TI estimates closer to estimates from instruments on towers. However, there is still scatter evident in the lidar TI estimates, indicating that there are physics that are not being captured in the current version of L-TERRA. Two options are discussed for modeling the remainder of the TI error physics in L-TERRA: machine learning and lidar simulations. Lidar simulations appear to be a better approach, as they can help improve understanding of atmospheric effects on TI error and do not require a large training data set.
Estimating wind frequency limits for natural ventilation at remote sites
International Nuclear Information System (INIS)
Su, B.; Aynsley, R.
2006-01-01
Detailed wind data are collected at a limited number of sites, usually at airports. When a building is sited remote from the nearest wind data collection site, estimating wind frequency is more complex. The techniques involved come from the discipline of wind engineering. Where there is a relatively flat terrain between the wind data-recording site and the building site, simple computations can be made to account for the wind velocities over intervening terrain roughness. Where significant topographic features such as hills or mountains are present between the wind data-recording site and the building site, then boundary layer wind tunnel studies will be necessary to determine the influence of such features on wind speed and direction. Rough estimates can be calculated using factors used in some wind loading codes. When buildings are to be designed to take advantage of the energy efficiency offered by natural ventilation, it is important to estimate the actual potential for such ventilation. The natural ventilation potential can be estimated in terms of the percentage of time when wind exceeds some minimum value. For buildings near airports this is a relatively simple procedure. Such estimates are important as they also indicate the likely percentage of time when fans or other energy consuming devices will be needed to maintain indoor thermal comfort. This paper identifies the wind engineering techniques that can be used for such estimates and gives examples of such calculations
Parameter estimation applied to physiological systems
Rideout, V.C.; Beneken, J.E.W.
Parameter estimation techniques are of ever-increasing interest in the fields of medicine and biology, as greater efforts are currently being made to describe physiological systems in explicit quantitative form. Although some of the techniques of parameter estimation as developed for use in other
Estimation of physical parameters in induction motors
DEFF Research Database (Denmark)
Børsting, H.; Knudsen, Morten; Rasmussen, Henrik
1994-01-01
Parameter estimation in induction motors is a field of great interest, because accurate models are needed for robust dynamic control of induction motors......Parameter estimation in induction motors is a field of great interest, because accurate models are needed for robust dynamic control of induction motors...
On parameter estimation in deformable models
DEFF Research Database (Denmark)
Fisker, Rune; Carstensen, Jens Michael
1998-01-01
Deformable templates have been intensively studied in image analysis through the last decade, but despite its significance the estimation of model parameters has received little attention. We present a method for supervised and unsupervised model parameter estimation using a general Bayesian form...
ESTIMATION ACCURACY OF EXPONENTIAL DISTRIBUTION PARAMETERS
Directory of Open Access Journals (Sweden)
muhammad zahid rashid
2011-04-01
Full Text Available The exponential distribution is commonly used to model the behavior of units that have a constant failure rate. The two-parameter exponential distribution provides a simple but nevertheless useful model for the analysis of lifetimes, especially when investigating reliability of technical equipment.This paper is concerned with estimation of parameters of the two parameter (location and scale exponential distribution. We used the least squares method (LSM, relative least squares method (RELS, ridge regression method (RR, moment estimators (ME, modified moment estimators (MME, maximum likelihood estimators (MLE and modified maximum likelihood estimators (MMLE. We used the mean square error MSE, and total deviation TD, as measurement for the comparison between these methods. We determined the best method for estimation using different values for the parameters and different sample sizes
Representivity of wind measurements for design wind speed estimations
CSIR Research Space (South Africa)
Goliger, Adam M
2013-07-01
Full Text Available Engineer in South Africa, January 1987. Wever, N., and G. Groen. 2009. Improving potential wind for extreme wind statistics. KNMI scientific report - wetenschappelijk rapport : WR 2009-02. KNMI. De Bilt. The Netherlands. 114 pp. Wieringa, J. 1986...
Cosmological parameter estimation using Particle Swarm Optimization
International Nuclear Information System (INIS)
Prasad, J; Souradeep, T
2014-01-01
Constraining parameters of a theoretical model from observational data is an important exercise in cosmology. There are many theoretically motivated models, which demand greater number of cosmological parameters than the standard model of cosmology uses, and make the problem of parameter estimation challenging. It is a common practice to employ Bayesian formalism for parameter estimation for which, in general, likelihood surface is probed. For the standard cosmological model with six parameters, likelihood surface is quite smooth and does not have local maxima, and sampling based methods like Markov Chain Monte Carlo (MCMC) method are quite successful. However, when there are a large number of parameters or the likelihood surface is not smooth, other methods may be more effective. In this paper, we have demonstrated application of another method inspired from artificial intelligence, called Particle Swarm Optimization (PSO) for estimating cosmological parameters from Cosmic Microwave Background (CMB) data taken from the WMAP satellite
Cosmological parameter estimation using Particle Swarm Optimization
Prasad, J.; Souradeep, T.
2014-03-01
Constraining parameters of a theoretical model from observational data is an important exercise in cosmology. There are many theoretically motivated models, which demand greater number of cosmological parameters than the standard model of cosmology uses, and make the problem of parameter estimation challenging. It is a common practice to employ Bayesian formalism for parameter estimation for which, in general, likelihood surface is probed. For the standard cosmological model with six parameters, likelihood surface is quite smooth and does not have local maxima, and sampling based methods like Markov Chain Monte Carlo (MCMC) method are quite successful. However, when there are a large number of parameters or the likelihood surface is not smooth, other methods may be more effective. In this paper, we have demonstrated application of another method inspired from artificial intelligence, called Particle Swarm Optimization (PSO) for estimating cosmological parameters from Cosmic Microwave Background (CMB) data taken from the WMAP satellite.
Wind shear estimation and wake detection by rotor loads — First wind tunnel verification
Schreiber, J.; Cacciola, S.; Campagnolo, F.; Petrović, V.; Mourembles, D.; Bottasso, C. L.
2016-09-01
The paper describes a simple method for detecting presence and location of a wake affecting a downstream wind turbine operating in a wind power plant. First, the local wind speed and shear experienced by the wind turbine are estimated by the use of rotor loads and other standard wind turbine response data. Then, a simple wake deficit model is used to determine the lateral position of the wake with respect to the affected rotor. The method is verified in a boundary layer wind tunnel using two instrumented scaled wind turbine models, demonstrating its effectiveness.
Energy Technology Data Exchange (ETDEWEB)
Lundquist, J. K. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Pukayastha, A. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Martin, C. [Univ. of Colorado, Boulder, CO (United States); Newsom, R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2014-03-01
Previous estimates of the wind resources in Uttarakhand, India, suggest minimal wind resources in this region. To explore whether or not the complex terrain in fact provides localized regions of wind resource, the authors of this study employed a dynamic down scaling method with the Weather Research and Forecasting model, providing detailed estimates of winds at approximately 1 km resolution in the finest nested simulation.
The behavior of solar wind parameters and geomagnetic activity ...
African Journals Online (AJOL)
The main objective of the current work is to investigate the behavior of space weather parameter as well as geomagnetic activity indices to observe the Geomagnetically Induced Current (GIC). Subsequently, solar wind parameter and geomagnetic activity indices provided an evidence that GIC formed during quiet days.
Estimating the wind energy potential over the coastal stations of ...
African Journals Online (AJOL)
The suitability of two coastal stations in Nigeria for wind energy generation is presented in this study. To estimate the wind speeds at the desired height 70 m for standard wind turbine, two methods; namely power law relationship and diabatic evaluation have been considered. It was found that the diabatic evaluation method ...
Application of spreadsheet to estimate infiltration parameters
Directory of Open Access Journals (Sweden)
Mohammad Zakwan
2016-09-01
Full Text Available Infiltration is the process of flow of water into the ground through the soil surface. Soil water although contributes a negligible fraction of total water present on earth surface, but is of utmost importance for plant life. Estimation of infiltration rates is of paramount importance for estimation of effective rainfall, groundwater recharge, and designing of irrigation systems. Numerous infiltration models are in use for estimation of infiltration rates. The conventional graphical approach for estimation of infiltration parameters often fails to estimate the infiltration parameters precisely. The generalised reduced gradient (GRG solver is reported to be a powerful tool for estimating parameters of nonlinear equations and it has, therefore, been implemented to estimate the infiltration parameters in the present paper. Field data of infiltration rate available in literature for sandy loam soils of Umuahia, Nigeria were used to evaluate the performance of GRG solver. A comparative study of graphical method and GRG solver shows that the performance of GRG solver is better than that of conventional graphical method for estimation of infiltration rates. Further, the performance of Kostiakov model has been found to be better than the Horton and Philip's model in most of the cases based on both the approaches of parameter estimation.
Hurricane Wind Vector Estimates from WindSat Polarimetric Radiometer
National Research Council Canada - National Science Library
Adams, Ian S; Hennon, Christopther C; Jones, W. L; Ahmad, Khalil
2005-01-01
.... In late 2004, the first preliminary oceanic wind vector results were released, and this paper presents the first evaluation of this product for several Atlantic hurricanes during the 2003 season...
Estimating the true energy value of a wind farm
International Nuclear Information System (INIS)
Bass, J.
1995-01-01
To assess the true energy yield of a wind farm taking into account real-world effects such as control losses in individual turbines, losses in the distribution network and wake and topographic effects, this report from the Energy Technology Support Unit, has developed a more appropriate methodology for making economic assessments of wind farm projects. Simulations of wind turbines are used to enable control losses to be quantified, and long term performance data from wind turbines in operational United Kingdom wind farms adds to the accuracy of assessment. A model has also been used to estimate performance of a power distribution system for a wind farm, to enable losses associated with wind turbine, wind speed and various distribution layouts to be predicted. Data on wake effects are drawn from a separate study. All these are drawn into an economic simulation model which predicts a wind farm's likely achievement of its target energy yield, thus demonstrating the risk factors involved. (UK)
State and parameter estimation in bio processes
Energy Technology Data Exchange (ETDEWEB)
Maher, M.; Roux, G.; Dahhou, B. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France)]|[Institut National des Sciences Appliquees (INSA), 31 - Toulouse (France)
1994-12-31
A major difficulty in monitoring and control of bio-processes is the lack of reliable and simple sensors for following the evolution of the main state variables and parameters such as biomass, substrate, product, growth rate, etc... In this article, an adaptive estimation algorithm is proposed to recover the state and parameters in bio-processes. This estimator utilizes the physical process model and the reference model approach. Experimentations concerning estimation of biomass and product concentrations and specific growth rate, during batch, fed-batch and continuous fermentation processes are presented. The results show the performance of this adaptive estimation approach. (authors) 12 refs.
On Carleman estimates with two large parameters
Energy Technology Data Exchange (ETDEWEB)
Le Rousseau, Jerome, E-mail: jlr@univ-orleans.fr [Jerome Le Rousseau. Universite d' Orleans, Laboratoire Mathematiques et Applications, Physique Mathematique d' Orleans, CNRS UMR 6628, Federation Denis-Poisson, FR CNRS 2964, B.P. 6759, 45067 Orleans cedex 2 (France)
2011-04-01
We provide a general framework for the analysis and the derivation of Carleman estimates with two large parameters. For an appropriate form of weight functions strong pseudo-convexity conditions are shown to be necessary and sufficient.
International Nuclear Information System (INIS)
Tu, Yi-Long; Chang, Tsang-Jung; Chen, Cheng-Lung; Chang, Yu-Jung
2012-01-01
Highlights: ► ANN with short record training data is used to estimate power outputs in an existing station. ► The suitable numbers/parameters of input neurons for ANN are presented. ► Current wind speeds and previous power outputs are the most important input neurons. ► Choosing suitable input parameters is more important than choosing multiple parameters. - Abstract: For the brand new wind power industry, online recordings of wind power data are always in a relatively limited period. The aim of the study is to investigate the suitable numbers/parameters of input neurons for artificial neural networks under a short record of measured data. Measured wind speeds, wind directions (yaw angles) and power outputs with 10-min resolution at an existing wind power station, located at Jhongtun, Taiwan, are integrated to form three types of input neuron numbers and sixteen cases of input neurons. The first-10 days of each month in 2006 are used for data training to simulate the following 20-day power generation of the same month. The performance of various input neuron cases is evaluated. The simulated results show that using the first 10-day training data with adequate input neurons can estimate energy outputs well except the weak wind regime (May, June, and July). Among the input neuron parameters used, current wind speeds V(t) and previous power outputs P(t − 1) are the most important. Individually using one of them into input neurons can only provide satisfactory estimation. However, simultaneously using these two parameters into input neurons can give the best estimation. Thus, choosing suitable input parameters is more important than choosing multiple parameters.
Results of large scale wind climatologically estimations
Directory of Open Access Journals (Sweden)
Andrea Kircsi
2008-05-01
Full Text Available The aim of this article is to describe theparticular field of climatology which analyzes airmovement characteristics regarding utilization of windfor energy generation. The article describes features ofwind energy potential available in Hungary compared towind conditions in other areas of the northern quartersphere in order to assist the wind energy use developmentin Hungary. Information on wind climate gives a solidbasis for financial and economic decisions ofstakeholders in the field of wind energy utilization.
Association measures and estimation of copula parameters ...
African Journals Online (AJOL)
We apply the inversion method of estimation, with several combinations of two among the four most popular association measures, to estimate the parameters of copulas in the case of bivariate distributions. We carry out a simulation study with two examples, namely Farlie-Gumbel-Morgenstern and Marshall-Olkin ...
Parameter Estimation of Partial Differential Equation Models
Xun, Xiaolei
2013-09-01
Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from long-range infrared light detection and ranging data. Supplementary materials for this article are available online. © 2013 American Statistical Association.
Estimation of the Possible Power of a Wind Farm
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Göçmen Bozkurt, Tuhfe; Giebel, Gregor
2014-01-01
It seems possible to increase competitiveness of wind power plants by offering grid services (also called ancillary services) and enter the wind power plants into the ancillary market. One of the ancillary services is called reserve power, the differential capacity between the generated power...... and the available power in the farm. The total amount of energy that a wind farm can potentially generate is called possible power. It is very important for a wind farm owner to have a relatively accurate estimate of the possible power of the wind farm in order to be able to trade the reserve power. In this paper...... the possible power calculated based on the estimated effective wind speed of a down regulated wind farm (the industry standard) is compared against the calculated possible power based on the algorithm presented in the paper. The latter takes into account the eect of the wakes of down regulated turbines...
Estimation of Modal Parameters and their Uncertainties
DEFF Research Database (Denmark)
Andersen, P.; Brincker, Rune
1999-01-01
In this paper it is shown how to estimate the modal parameters as well as their uncertainties using the prediction error method of a dynamic system on the basis of uotput measurements only. The estimation scheme is assessed by means of a simulation study. As a part of the introduction, an example...... is given showing how the uncertainty estimates can be used in applications such as damage detection....
Reionization history and CMB parameter estimation
Energy Technology Data Exchange (ETDEWEB)
Dizgah, Azadeh Moradinezhad; Gnedin, Nickolay Y.; Kinney, William H.
2013-05-01
We study how uncertainty in the reionization history of the universe affects estimates of other cosmological parameters from the Cosmic Microwave Background. We analyze WMAP7 data and synthetic Planck-quality data generated using a realistic scenario for the reionization history of the universe obtained from high-resolution numerical simulation. We perform parameter estimation using a simple sudden reionization approximation, and using the Principal Component Analysis (PCA) technique proposed by Mortonson and Hu. We reach two main conclusions: (1) Adopting a simple sudden reionization model does not introduce measurable bias into values for other parameters, indicating that detailed modeling of reionization is not necessary for the purpose of parameter estimation from future CMB data sets such as Planck. (2) PCA analysis does not allow accurate reconstruction of the actual reionization history of the universe in a realistic case.
Estimation of Rotor Effective Wind Speed: A Comparison
DEFF Research Database (Denmark)
Soltani, Mohsen; Knudsen, Torben; Svenstrup, Mikael
2013-01-01
Modern wind turbine controllers use wind speed information to improve power production and reduce loads on the turbine components. The turbine top wind speed measurement is unfortunately imprecise and not a good representative of the rotor effective wind speed. Consequently, many different model......-based algorithms have been proposed that are able to estimate the wind speed using common turbine measurements. In this paper, we present a concise yet comprehensive analysis and comparison of these techniques, reviewing their advantages and drawbacks. We implement these techniques and compare the results on both...
Statistics of Parameter Estimates: A Concrete Example
Aguilar, Oscar
2015-01-01
© 2015 Society for Industrial and Applied Mathematics. Most mathematical models include parameters that need to be determined from measurements. The estimated values of these parameters and their uncertainties depend on assumptions made about noise levels, models, or prior knowledge. But what can we say about the validity of such estimates, and the influence of these assumptions? This paper is concerned with methods to address these questions, and for didactic purposes it is written in the context of a concrete nonlinear parameter estimation problem. We will use the results of a physical experiment conducted by Allmaras et al. at Texas A&M University [M. Allmaras et al., SIAM Rev., 55 (2013), pp. 149-167] to illustrate the importance of validation procedures for statistical parameter estimation. We describe statistical methods and data analysis tools to check the choices of likelihood and prior distributions, and provide examples of how to compare Bayesian results with those obtained by non-Bayesian methods based on different types of assumptions. We explain how different statistical methods can be used in complementary ways to improve the understanding of parameter estimates and their uncertainties.
Practical method for estimating wind characteristics at potential wind-energy-conversion sites
Energy Technology Data Exchange (ETDEWEB)
Endlich, R. M.; Ludwig, F. L.; Bhumralkar, C. M.; Estoque, M. A.
1980-08-01
Terrain features and variations in the depth of the atmospheric boundary layer produce local variations in wind, and these variations are not depicted well by standard weather reports. A method is developed to compute local winds for use in estimating the wind energy available at any potential site for a wind turbine. The method uses the terrain heights for an area surrounding the site and a series of wind and pressure reports from the nearest four or five national Weather Service stations. An initial estimate of the winds in the atmospheric boundary layer is made, then these winds are adjusted to satisfy the continuity equation. In this manner the flow is made to reflect the influences of the terrain and the shape of the boundary-layer top. This report describes in detail the methodology and results, and provides descriptions of the computer programs, instructions for using them, and complete program listings.
Multi-Parameter Estimation for Orthorhombic Media
Masmoudi, Nabil
2015-08-19
Building reliable anisotropy models is crucial in seismic modeling, imaging and full waveform inversion. However, estimating anisotropy parameters is often hampered by the trade off between inhomogeneity and anisotropy. For instance, one way to estimate the anisotropy parameters is to relate them analytically to traveltimes, which is challenging in inhomogeneous media. Using perturbation theory, we develop travel-time approximations for orthorhombic media as explicit functions of the anellipticity parameters η1, η2 and a parameter Δγ in inhomogeneous background media. Specifically, our expansion assumes inhomogeneous ellipsoidal anisotropic background model, which can be obtained from well information and stacking velocity analysis. This approach has two main advantages: in one hand, it provides a computationally efficient tool to solve the orthorhombic eikonal equation, on the other hand, it provides a mechanism to scan for the best fitting anisotropy parameters without the need for repetitive modeling of traveltimes, because the coefficients of the traveltime expansion are independent of the perturbed parameters. Furthermore, the coefficients of the traveltime expansion provide insights on the sensitivity of the traveltime with respect to the perturbed parameters. We show the accuracy of the traveltime approximations as well as an approach for multi-parameter scanning in orthorhombic media.
Parameter Estimation for Thurstone Choice Models
Energy Technology Data Exchange (ETDEWEB)
Vojnovic, Milan [London School of Economics (United Kingdom); Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-04-24
We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one or more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.
Bayesian estimation of Weibull distribution parameters
International Nuclear Information System (INIS)
Bacha, M.; Celeux, G.; Idee, E.; Lannoy, A.; Vasseur, D.
1994-11-01
In this paper, we expose SEM (Stochastic Expectation Maximization) and WLB-SIR (Weighted Likelihood Bootstrap - Sampling Importance Re-sampling) methods which are used to estimate Weibull distribution parameters when data are very censored. The second method is based on Bayesian inference and allow to take into account available prior informations on parameters. An application of this method, with real data provided by nuclear power plants operation feedback analysis has been realized. (authors). 8 refs., 2 figs., 2 tabs
Fatigue-Damage Estimation and Control for Wind Turbines
DEFF Research Database (Denmark)
Barradas Berglind, Jose de Jesus
How can fatigue-damage for control of wind turbines be represented? Fatigue-damage is indeed a crucial factor in structures such as wind turbines that are exposed to turbulent and rapidly changing wind flow conditions. This is relevant both in their design stage and during the control......, the inclusion of fatigue-damage within feedback control loops is of special interest. Four strategies in total are proposed in this work: three for the wind turbine level and one for the wind farm level. On one hand, the three strategies in the turbine level are based on hysteresis operators and strive......-damage estimation in wind turbine components, to the mixed objective operation of wind energy conversion systems, and to the synthesis of control strategies that include hysteresis operators....
Modelling and parameter estimation of dynamic systems
Raol, JR; Singh, J
2004-01-01
Parameter estimation is the process of using observations from a system to develop mathematical models that adequately represent the system dynamics. The assumed model consists of a finite set of parameters, the values of which are calculated using estimation techniques. Most of the techniques that exist are based on least-square minimization of error between the model response and actual system response. However, with the proliferation of high speed digital computers, elegant and innovative techniques like filter error method, H-infinity and Artificial Neural Networks are finding more and mor
Robust estimation of hydrological model parameters
Directory of Open Access Journals (Sweden)
A. Bárdossy
2008-11-01
Full Text Available The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.
MCMC for parameters estimation by bayesian approach
International Nuclear Information System (INIS)
Ait Saadi, H.; Ykhlef, F.; Guessoum, A.
2011-01-01
This article discusses the parameter estimation for dynamic system by a Bayesian approach associated with Markov Chain Monte Carlo methods (MCMC). The MCMC methods are powerful for approximating complex integrals, simulating joint distributions, and the estimation of marginal posterior distributions, or posterior means. The MetropolisHastings algorithm has been widely used in Bayesian inference to approximate posterior densities. Calibrating the proposal distribution is one of the main issues of MCMC simulation in order to accelerate the convergence.
Wind Loads on Ships and Offshore Structures Estimated by CFD
DEFF Research Database (Denmark)
Aage, Christian; Hvid, S.L.; Hughes, P.H.
1997-01-01
Wind loads on ships and offshore structures could until recently be determined only by model tests, or by statistical methods based on model tests. By the development of Computational Fluid Dynamics or CFD there is now a realistic computational alternative available. In this paper, wind loads...... on a seagoing ferry and on a semisubmersible offshore platform have been estimated by CFD. The results have been compared with wind tunnel model tests and, for the ferry, a few full-scale measurements, and good agreement is obtained. The CFD method offers the possibility of a computational estimate of scale...... effects related to wind tunnel model testing. An example of such an estimate on the ferry is discussed. Due to the time involved in generating the computational mesh and in computing the solution, the CFD method is not at the moment economically competitive to routine wind tunnel model testing....
Parameter estimation methods for chaotic intercellular networks.
Directory of Open Access Journals (Sweden)
Inés P Mariño
Full Text Available We have investigated simulation-based techniques for parameter estimation in chaotic intercellular networks. The proposed methodology combines a synchronization-based framework for parameter estimation in coupled chaotic systems with some state-of-the-art computational inference methods borrowed from the field of computational statistics. The first method is a stochastic optimization algorithm, known as accelerated random search method, and the other two techniques are based on approximate Bayesian computation. The latter is a general methodology for non-parametric inference that can be applied to practically any system of interest. The first method based on approximate Bayesian computation is a Markov Chain Monte Carlo scheme that generates a series of random parameter realizations for which a low synchronization error is guaranteed. We show that accurate parameter estimates can be obtained by averaging over these realizations. The second ABC-based technique is a Sequential Monte Carlo scheme. The algorithm generates a sequence of "populations", i.e., sets of randomly generated parameter values, where the members of a certain population attain a synchronization error that is lesser than the error attained by members of the previous population. Again, we show that accurate estimates can be obtained by averaging over the parameter values in the last population of the sequence. We have analysed how effective these methods are from a computational perspective. For the numerical simulations we have considered a network that consists of two modified repressilators with identical parameters, coupled by the fast diffusion of the autoinducer across the cell membranes.
Parameter Estimation in Active Plate Structures
DEFF Research Database (Denmark)
Araujo, A. L.; Lopes, H. M. R.; Vaz, M. A. P.
2006-01-01
In this paper two non-destructive methods for elastic and piezoelectric parameter estimation in active plate structures with surface bonded piezoelectric patches are presented. These methods rely on experimental undamped natural frequencies of free vibration. The first solves the inverse problem...
Using Digital Filtration for Hurst Parameter Estimation
Directory of Open Access Journals (Sweden)
J. Prochaska
2009-06-01
Full Text Available We present a new method to estimate the Hurst parameter. The method exploits the form of the autocorrelation function for second-order self-similar processes and is based on one-pass digital filtration. We compare the performance and properties of the new method with that of the most common methods.
Simultaneous estimation of earthquake source parameters and ...
Indian Academy of Sciences (India)
This paper presents the simultaneous estimation of source parameters and crustal Q values for small to moderate-size aftershocks ( 2.1–5.1) of the 7.7 2001 Bhuj earthquake. The horizontal-component S-waves of 144 well located earthquakes (2001–2010) recorded at 3–10 broadband seismograph sites in the ...
Simultaneous estimation of earthquake source parameters and ...
Indian Academy of Sciences (India)
This paper presents the simultaneous estimation of source parameters and crustal Q values for small to moderate-size aftershocks (Mw 2.1–5.1) of the Mw 7.7 2001 Bhuj earthquake. The horizontal-component. S-waves of 144 well located earthquakes (2001–2010) recorded at 3–10 broadband seismograph sites in.
An Error-Reduction Algorithm to Improve Lidar Turbulence Estimates for Wind Energy
Energy Technology Data Exchange (ETDEWEB)
Newman, Jennifer F.; Clifton, Andrew
2016-08-01
Currently, cup anemometers on meteorological (met) towers are used to measure wind speeds and turbulence intensity to make decisions about wind turbine class and site suitability. However, as modern turbine hub heights increase and wind energy expands to complex and remote sites, it becomes more difficult and costly to install met towers at potential sites. As a result, remote sensing devices (e.g., lidars) are now commonly used by wind farm managers and researchers to estimate the flow field at heights spanned by a turbine. While lidars can accurately estimate mean wind speeds and wind directions, there is still a large amount of uncertainty surrounding the measurement of turbulence with lidars. This uncertainty in lidar turbulence measurements is one of the key roadblocks that must be overcome in order to replace met towers with lidars for wind energy applications. In this talk, a model for reducing errors in lidar turbulence estimates is presented. Techniques for reducing errors from instrument noise, volume averaging, and variance contamination are combined in the model to produce a corrected value of the turbulence intensity (TI), a commonly used parameter in wind energy. In the next step of the model, machine learning techniques are used to further decrease the error in lidar TI estimates.
Parameter estimation in stochastic differential equations
Bishwal, Jaya P N
2008-01-01
Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modelling complex phenomena and making beautiful decisions. The subject has attracted researchers from several areas of mathematics and other related fields like economics and finance. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods. Useful because of the current availability of high frequency data is the study of refined asymptotic properties of several estimators when the observation time length is large and the observation time interval is small. Also space time white noise driven models, useful for spatial data, and more sophisticated non-Markovian and non-semimartingale models like fractional diffusions that model the long memory phenomena are examined in this volume.
Estimation of wind velocity over a complex terrain using the Generalized Mapping Regressor
Energy Technology Data Exchange (ETDEWEB)
Beccali, M.; Marvuglia, A. [Dipartimento di Ricerche Energetiche ed Ambientali (DREAM), Universita degli Studi di Palermo, Viale delle Scienze - edificio 9, 90128 Palermo (Italy); Cirrincione, G. [Department de Genie Electrique, Universite de Picardie Jules Verne, 33, Rue Saint Leu, 80039 Amiens (France); Serporta, C. [ISSIA-CNR (Institute on Intelligent Systems for the Automation), Section of Palermo, Via Dante12, Palermo (Italy)
2010-03-15
Wind energy evaluation is an important goal in the conversion of energy systems to more environmentally friendly solutions. In this paper, we present a novel approach to wind speed spatial estimation on the isle of Sicily (Italy): an incremental self-organizing neural network (Generalized Mapping Regressor - GMR) is coupled with exploratory data analysis techniques in order to obtain a map of the spatial distribution of the average wind speed over the entire region. First, the topographic surface of the island was modelled using two different neural techniques and by exploiting the information extracted from a digital elevation model of the region. Then, GMR was used for automatic modelling of the terrain roughness. Afterwards, a statistical analysis of the wind data allowed for the estimation of the parameters of the Weibull wind probability distribution function. In the last sections of the paper, the expected values of the Weibull distributions were regionalized using the GMR neural network. (author)
Estimation of wind speed and wave height during cyclones
Digital Repository Service at National Institute of Oceanography (India)
SanilKumar, V.; Mandal, S.; AshokKumar, K.
based on standard Hydromet pressure profile, were used for the hindcast of storm wind fields. For all the cyclones the maximum significant wave height within the storm and its associated spectral peak period was estimated using the Young's model...
Sensor Placement for Modal Parameter Subset Estimation
DEFF Research Database (Denmark)
Ulriksen, Martin Dalgaard; Bernal, Dionisio; Damkilde, Lars
2016-01-01
). It is shown that the widely used Effective Independence (EI) method, which uses the modal amplitudes as surrogates for the parameters of interest, provides sensor configurations yielding theoretical lower bound variances whose maxima are up to 30 % larger than those obtained by use of the max-min approach.......The present paper proposes an approach for deciding on sensor placements in the context of modal parameter estimation from vibration measurements. The approach is based on placing sensors, of which the amount is determined a priori, such that the minimum Fisher information that the frequency...... responses carry on the selected modal parameter subset is, in some sense, maximized. The approach is validated in the context of a simple 10-DOF mass-spring-damper system by computing the variance of a set of identified modal parameters in a Monte Carlo setting for a set of sensor configurations, whose...
Estimated Drag Coefficients and Wind Structure of Hurricane Frances
Zedler, S. E.; Niiler, P. P.; Stammer, D.; Terrill, E.
2006-12-01
As part of the Coupled Boundary Layers Air Sea Transfer (CBLAST) experiment, an array of drifters and floats was deployed from an aircraft just ahead of Hurricane Frances during it's passage to the northwest side of the Caribbean Island chain in August, 2004. The ocean and surface air conditions prior to, during, and after Hurricane Frances were documented by multiple sensors. Two independent estimates of the surface wind field suggest different storm structures. NOAA H*WINDS, an objectively analyzed product using a combination of data collected at the reconnaissance flight level, GPS profilers (dropwindsondes), satellites, and other data, suggest a 40km radius of maximum wind. A product based on the radial momentum equation balance using \\ital{in-situ} surface pressure data and wind direction measurements from the CBLAST drifter array suggests that the radius of maximum winds was 15km. We used a regional version of the MITGCM model with closed boundaries and realistic temperature and salinity fields which was forced with these wind field products to determine which wind field leads to circulation and SST structures that are most consistent with observed sea surface temperature fields and float profile data. Best estimates of the surface wind structure are then used to estimate the appropriate drag coefficient corresponding to the maximum velocity. Our results are compared with those obtained previously.
High-speed solar wind flow parameters at 1 AU
International Nuclear Information System (INIS)
Feldman, W.C.; Asbridge, J.R.; Bame, S.J.; Gosling, J.T.
1976-01-01
To develop a set of constraints for theories of solar wind high-speed streams, a detailed study was made of the fastest streams observed at 1 AU during the time period spanning March 1971 through July 1974. Streams were accepted for study only if (1) the maximum speed exceeded 650 km s -1 ; (2) effects of stream-stream dynamical interaction on the flow parameters could be safely separated from the intrinsic characteristics of the high-speed regions; (3) the full width at half maximum (FWHM) of the stream when mapped back to 20 solar radii by using a constant speed approximation was greater than 45degree in Carrington longitude; and (4) there were no obvious solar-activity-induced contaminating effects. Nineteen streams during this time interval satisfied these criteria. Average parameters at 1 AU for those portions of these streams above V=650 km s -1 are given.Not only is it not presently known why electrons are significantly cooler than the protons within high-speed regions, but also observed particle fluxes and convected energy fluxes for speed greater than 650 km s -1 are substantially larger than those values predicted by any of the existing theories of solar wind high-speed streams. More work is therefore needed in refining present solar wind models to see whether suitable modifications and/or combinations of existing theories based on reasonable coronal conditions can accommodate the above high-speed flow parameters
Nonparametric estimation of location and scale parameters
Potgieter, C.J.
2012-12-01
Two random variables X and Y belong to the same location-scale family if there are constants μ and σ such that Y and μ+σX have the same distribution. In this paper we consider non-parametric estimation of the parameters μ and σ under minimal assumptions regarding the form of the distribution functions of X and Y. We discuss an approach to the estimation problem that is based on asymptotic likelihood considerations. Our results enable us to provide a methodology that can be implemented easily and which yields estimators that are often near optimal when compared to fully parametric methods. We evaluate the performance of the estimators in a series of Monte Carlo simulations. © 2012 Elsevier B.V. All rights reserved.
Zastrau, David
2017-01-01
Wind drives in combination with weather routing can lower the fuel consumption of cargo ships significantly. For this reason, the author describes a mathematical method based on quantile regression for a probabilistic estimate of the wind propulsion force on a ship route.
Estimating RASATI scores using acoustical parameters
International Nuclear Information System (INIS)
Agüero, P D; Tulli, J C; Moscardi, G; Gonzalez, E L; Uriz, A J
2011-01-01
Acoustical analysis of speech using computers has reached an important development in the latest years. The subjective evaluation of a clinician is complemented with an objective measure of relevant parameters of voice. Praat, MDVP (Multi Dimensional Voice Program) and SAV (Software for Voice Analysis) are some examples of software for speech analysis. This paper describes an approach to estimate the subjective characteristics of RASATI scale given objective acoustical parameters. Two approaches were used: linear regression with non-negativity constraints, and neural networks. The experiments show that such approach gives correct evaluations with ±1 error in 80% of the cases.
Fatigue Damage Estimation and Data-based Control for Wind Turbines
DEFF Research Database (Denmark)
Barradas Berglind, Jose de Jesus; Wisniewski, Rafal; Soltani, Mohsen
2015-01-01
The focus of this work is on fatigue estimation and data-based controller design for wind turbines. The main purpose is to include a model of the fatigue damage of the wind turbine components in the controller design and synthesis process. This study addresses an online fatigue estimation method...... based on hysteresis operators, which can be used in control loops. The authors propose a data-based model predictive control (MPC) strategy that incorporates an online fatigue estimation method through the objective function, where the ultimate goal in mind is to reduce the fatigue damage of the wind...... turbine components. The outcome is an adaptive or self-tuning MPC strategy for wind turbine fatigue damage reduction, which relies on parameter identification on previous measurement data. The results of the proposed strategy are compared with a baseline model predictive controller....
Cosmological parameter estimation using particle swarm optimization
Prasad, Jayanti; Souradeep, Tarun
2012-06-01
Constraining theoretical models, which are represented by a set of parameters, using observational data is an important exercise in cosmology. In Bayesian framework this is done by finding the probability distribution of parameters which best fits to the observational data using sampling based methods like Markov chain Monte Carlo (MCMC). It has been argued that MCMC may not be the best option in certain problems in which the target function (likelihood) poses local maxima or have very high dimensionality. Apart from this, there may be examples in which we are mainly interested to find the point in the parameter space at which the probability distribution has the largest value. In this situation the problem of parameter estimation becomes an optimization problem. In the present work we show that particle swarm optimization (PSO), which is an artificial intelligence inspired population based search procedure, can also be used for cosmological parameter estimation. Using PSO we were able to recover the best-fit Λ cold dark matter (LCDM) model parameters from the WMAP seven year data without using any prior guess value or any other property of the probability distribution of parameters like standard deviation, as is common in MCMC. We also report the results of an exercise in which we consider a binned primordial power spectrum (to increase the dimensionality of problem) and find that a power spectrum with features gives lower chi square than the standard power law. Since PSO does not sample the likelihood surface in a fair way, we follow a fitting procedure to find the spread of likelihood function around the best-fit point.
Algorithm for wind speed estimate with polarimetric radar
Directory of Open Access Journals (Sweden)
Ю. А. Авер’янова
2013-07-01
Full Text Available The connection of wind speed and drops behavior is substantiated as well as the drop behavior influence onto the polarization characteristics of electromagnetic waves. The expression to calculate the wind speed taking into account the Weber number for the critical regime of drop deformation is obtained. The critical regime of drop deformation is the regime when drop is divided into two parts. The dependency of critical wind speed on the drop diameter is calculated and shown. The concept o polarization spectrum that is introduced in the previous papers is used to estimate the dynamic processes in the atmosphere. At the moment when the drop is under the influence of the wind that is equal to the critical wind speed the drop will be divided into two parts. This process will be reflected as the appearance of the two equal components of polarization spectra of reflected electromagnetic waves at the orthogonal antennas of Doppler Polarimetric Radar. Owing the information about the correspondence of the polarization component energy level to the drop diameter it is possible to estimate the wind speed with the obtained dependency. The process of the wind speed estimate with polarimetric radar is presented with the developed common algorithm
Kosovic, B.; Bryan, G. H.; Haupt, S. E.
2012-12-01
Schwartz et al. (2010) recently reported that the total gross energy-generating offshore wind resource in the United States in waters less than 30m deep is approximately 1000 GW. Estimated offshore generating capacity is thus equivalent to the current generating capacity in the United States. Offshore wind power can therefore play important role in electricity production in the United States. However, most of this resource is located along the East Coast of the United States and in the Gulf of Mexico, areas frequently affected by tropical cyclones including hurricanes. Hurricane strength winds, associated shear and turbulence can affect performance and structural integrity of wind turbines. In a recent study Rose et al. (2012) attempted to estimate the risk to offshore wind turbines from hurricane strength winds over a lifetime of a wind farm (i.e. 20 years). According to Rose et al. turbine tower buckling has been observed in typhoons. They concluded that there is "substantial risk that Category 3 and higher hurricanes can destroy half or more of the turbines at some locations." More robust designs including appropriate controls can mitigate the risk of wind turbine damage. To develop such designs good estimates of turbine loads under hurricane strength winds are essential. We use output from a large-eddy simulation of a hurricane to estimate shear and turbulence intensity over first couple of hundred meters above sea surface. We compute power spectra of three velocity components at several distances from the eye of the hurricane. Based on these spectra analytical spectral forms are developed and included in TurbSim, a stochastic inflow turbulence code developed by the National Renewable Energy Laboratory (NREL, http://wind.nrel.gov/designcodes/preprocessors/turbsim/). TurbSim provides a numerical simulation including bursts of coherent turbulence associated with organized turbulent structures. It can generate realistic flow conditions that an operating turbine
MATHEMATICAL MODELING OF FLOW PARAMETERS FOR SINGLE WIND TURBINE
Directory of Open Access Journals (Sweden)
2016-01-01
to adequatelycalculate the flow parameters for a single wind turbine.
DEFF Research Database (Denmark)
Østergaard, Kasper Zinck; Stoustrup, Jakob; Brath, Per
2009-01-01
This paper considers the design of linear parameter varying (LPV) controllers for wind turbines in order to obtain a multivariable control law that covers the entire nominal operating trajectory.The paper first presents a controller structure for selecting a proper operating trajectory as a funct......This paper considers the design of linear parameter varying (LPV) controllers for wind turbines in order to obtain a multivariable control law that covers the entire nominal operating trajectory.The paper first presents a controller structure for selecting a proper operating trajectory...... as a function of estimated wind speed. The dynamic control law is based on LPV controller synthesis with general parameter dependency by gridding the parameter space.The controller construction can, for medium- to large-scale systems, be difficult from a numerical point of view, because the involved matrix...... operations tend to be ill-conditioned. The paper proposes a controller construction algorithm together with various remedies for improving the numerical conditioning the algorithm.The proposed algorithm is applied to the design of a LPV controller for wind turbines, and a comparison is made with a controller...
Ultrasonic data compression via parameter estimation.
Cardoso, Guilherme; Saniie, Jafar
2005-02-01
Ultrasonic imaging in medical and industrial applications often requires a large amount of data collection. Consequently, it is desirable to use data compression techniques to reduce data and to facilitate the analysis and remote access of ultrasonic information. The precise data representation is paramount to the accurate analysis of the shape, size, and orientation of ultrasonic reflectors, as well as to the determination of the properties of the propagation path. In this study, a successive parameter estimation algorithm based on a modified version of the continuous wavelet transform (CWT) to compress and denoise ultrasonic signals is presented. It has been shown analytically that the CWT (i.e., time x frequency representation) yields an exact solution for the time-of-arrival and a biased solution for the center frequency. Consequently, a modified CWT (MCWT) based on the Gabor-Helstrom transform is introduced as a means to exactly estimate both time-of-arrival and center frequency of ultrasonic echoes. Furthermore, the MCWT also has been used to generate a phase x bandwidth representation of the ultrasonic echo. This representation allows the exact estimation of the phase and the bandwidth. The performance of this algorithm for data compression and signal analysis is studied using simulated and experimental ultrasonic signals. The successive parameter estimation algorithm achieves a data compression ratio of (1-5N/J), where J is the number of samples and N is the number of echoes in the signal. For a signal with 10 echoes and 2048 samples, a compression ratio of 96% is achieved with a signal-to-noise ratio (SNR) improvement above 20 dB. Furthermore, this algorithm performs robustly, yields accurate echo estimation, and results in SNR enhancements ranging from 10 to 60 dB for composite signals having SNR as low as -10 dB.
Toward unbiased estimations of the statefinder parameters
Aviles, Alejandro; Klapp, Jaime; Luongo, Orlando
2017-09-01
With the use of simulated supernova catalogs, we show that the statefinder parameters turn out to be poorly and biased estimated by standard cosmography. To this end, we compute their standard deviations and several bias statistics on cosmologies near the concordance model, demonstrating that these are very large, making standard cosmography unsuitable for future and wider compilations of data. To overcome this issue, we propose a new method that consists in introducing the series of the Hubble function into the luminosity distance, instead of considering the usual direct Taylor expansions of the luminosity distance. Moreover, in order to speed up the numerical computations, we estimate the coefficients of our expansions in a hierarchical manner, in which the order of the expansion depends on the redshift of every single piece of data. In addition, we propose two hybrids methods that incorporates standard cosmography at low redshifts. The methods presented here perform better than the standard approach of cosmography both in the errors and bias of the estimated statefinders. We further propose a one-parameter diagnostic to reject non-viable methods in cosmography.
Wind Plant Preconstruction Energy Estimates. Current Practice and Opportunities
Energy Technology Data Exchange (ETDEWEB)
Clifton, Andrew [National Renewable Energy Lab. (NREL), Golden, CO (United States); Smith, Aaron [National Renewable Energy Lab. (NREL), Golden, CO (United States); Fields, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States)
2016-04-19
Understanding the amount of energy that will be harvested by a wind power plant each year and the variability of that energy is essential to assessing and potentially improving the financial viability of that power plant. The preconstruction energy estimate process predicts the amount of energy--with uncertainty estimates--that a wind power plant will deliver to the point of revenue. This report describes the preconstruction energy estimate process from a technical perspective and seeks to provide insight into the financial implications associated with each step.
Composite likelihood estimation of demographic parameters
Directory of Open Access Journals (Sweden)
Garrigan Daniel
2009-11-01
Full Text Available Abstract Background Most existing likelihood-based methods for fitting historical demographic models to DNA sequence polymorphism data to do not scale feasibly up to the level of whole-genome data sets. Computational economies can be achieved by incorporating two forms of pseudo-likelihood: composite and approximate likelihood methods. Composite likelihood enables scaling up to large data sets because it takes the product of marginal likelihoods as an estimator of the likelihood of the complete data set. This approach is especially useful when a large number of genomic regions constitutes the data set. Additionally, approximate likelihood methods can reduce the dimensionality of the data by summarizing the information in the original data by either a sufficient statistic, or a set of statistics. Both composite and approximate likelihood methods hold promise for analyzing large data sets or for use in situations where the underlying demographic model is complex and has many parameters. This paper considers a simple demographic model of allopatric divergence between two populations, in which one of the population is hypothesized to have experienced a founder event, or population bottleneck. A large resequencing data set from human populations is summarized by the joint frequency spectrum, which is a matrix of the genomic frequency spectrum of derived base frequencies in two populations. A Bayesian Metropolis-coupled Markov chain Monte Carlo (MCMCMC method for parameter estimation is developed that uses both composite and likelihood methods and is applied to the three different pairwise combinations of the human population resequence data. The accuracy of the method is also tested on data sets sampled from a simulated population model with known parameters. Results The Bayesian MCMCMC method also estimates the ratio of effective population size for the X chromosome versus that of the autosomes. The method is shown to estimate, with reasonable
Sequential parameter estimation for stochastic systems
Directory of Open Access Journals (Sweden)
G. A. Kivman
2003-01-01
Full Text Available The quality of the prediction of dynamical system evolution is determined by the accuracy to which initial conditions and forcing are known. Availability of future observations permits reducing the effects of errors in assessment the external model parameters by means of a filtering algorithm. Usually, uncertainties in specifying internal model parameters describing the inner system dynamics are neglected. Since they are characterized by strongly non-Gaussian distributions (parameters are positive, as a rule, traditional Kalman filtering schemes are badly suited to reducing the contribution of this type of uncertainties to the forecast errors. An extension of the Sequential Importance Resampling filter (SIR is proposed to this aim. The filter is verified against the Ensemble Kalman filter (EnKF in application to the stochastic Lorenz system. It is shown that the SIR is capable of estimating the system parameters and to predict the evolution of the system with a remarkably better accuracy than the EnKF. This highlights a severe drawback of any Kalman filtering scheme: due to utilizing only first two statistical moments in the analysis step it is unable to deal with probability density functions badly approximated by the normal distribution.
Estimation of the future advances of wind power technology
International Nuclear Information System (INIS)
Andersen, P.D.; Fuglsang, P.
1996-03-01
The report estimates the future advances of wind power technology. Two trajectories are considered and described: a normal (business as usual) trajectory and a technology trajectory. Two types of plants are considered: 1500 kW turbines on land (roughness class 1.5) in small groups and 2500 kW turbines in large off-shore wind farms. In both cases cost of energy (in DKK/kWh) is estimated to be approximately halved during the next 25 years. For wind turbines in flat terrain cost is estimated to decrease from an average in 1995 of 0.43 DKK/kWh to an average in 2020 of 0.26 DKK/kWh on a normal trajectory and 0.21 DKK/kWh on a technology trajectory. For large off-shore (near coast) wind farms cost is estimated to decrease from an average in 1995 of 0.51 DKK/kWh to an average in 2020 of 0.27 DKK/kWh on a normal trajectory and 0.23 DKK/kWh on a technology trajectory. Increase in the total market volume for wind turbines is estimated as the most important factor for cost reductions. The market is anticipated to follow the most conservative scenario of World Energy Council (180,000 MW by 2020). (au) 17 tabs., 7 ills. 25 refs
A Parameter Selection Method for Wind Turbine Health Management through SCADA Data
Directory of Open Access Journals (Sweden)
Mian Du
2017-02-01
Full Text Available Wind turbine anomaly or failure detection using machine learning techniques through supervisory control and data acquisition (SCADA system is drawing wide attention from academic and industry While parameter selection is important for modelling a wind turbine’s condition, only a few papers have been published focusing on this issue and in those papers interconnections among sub-components in a wind turbine are used to address this problem. However, merely the interconnections for decision making sometimes is too general to provide a parameter list considering the differences of each SCADA dataset. In this paper, a method is proposed to provide more detailed suggestions on parameter selection based on mutual information. First, the copula is proven to be capable of simplifying the estimation of mutual information. Then an empirical copulabased mutual information estimation method (ECMI is introduced for application. After that, a real SCADA dataset is adopted to test the method, and the results show the effectiveness of the ECMI in providing parameter selection suggestions when physical knowledge is not accurate enough.
Gait parameter and event estimation using smartphones.
Pepa, Lucia; Verdini, Federica; Spalazzi, Luca
2017-09-01
The use of smartphones can greatly help for gait parameters estimation during daily living, but its accuracy needs a deeper evaluation against a gold standard. The objective of the paper is a step-by-step assessment of smartphone performance in heel strike, step count, step period, and step length estimation. The influence of smartphone placement and orientation on estimation performance is evaluated as well. This work relies on a smartphone app developed to acquire, process, and store inertial sensor data and rotation matrices about device position. Smartphone alignment was evaluated by expressing the acceleration vector in three reference frames. Two smartphone placements were tested. Three methods for heel strike detection were considered. On the basis of estimated heel strikes, step count is performed, step period is obtained, and the inverted pendulum model is applied for step length estimation. Pearson correlation coefficient, absolute and relative errors, ANOVA, and Bland-Altman limits of agreement were used to compare smartphone estimation with stereophotogrammetry on eleven healthy subjects. High correlations were found between smartphone and stereophotogrammetric measures: up to 0.93 for step count, to 0.99 for heel strike, 0.96 for step period, and 0.92 for step length. Error ranges are comparable to those in the literature. Smartphone placement did not affect the performance. The major influence of acceleration reference frames and heel strike detection method was found in step count. This study provides detailed information about expected accuracy when smartphone is used as a gait monitoring tool. The obtained results encourage real life applications. Copyright © 2017 Elsevier B.V. All rights reserved.
Hurricane Wind Speed Estimation Using WindSat 6 and 10 GHz Brightness Temperatures
Directory of Open Access Journals (Sweden)
Lei Zhang
2016-08-01
Full Text Available The realistic and accurate estimation of hurricane intensity is highly desired in many scientific and operational applications. With the advance of passive microwave polarimetry, an alternative opportunity for retrieving wind speed in hurricanes has become available. A wind speed retrieval algorithm for wind speeds above 20 m/s in hurricanes has been developed by using the 6.8 and 10.7 GHz vertically and horizontally polarized brightness temperatures of WindSat. The WindSat measurements for 15 category 4 and category 5 hurricanes from 2003 to 2010 and the corresponding H*wind analysis data are used to develop and validate the retrieval model. In addition, the retrieved wind speeds are also compared to the Remote Sensing Systems (RSS global all-weather product and stepped-frequency microwave radiometer (SFMR measurements. The statistical results show that the mean bias and the overall root-mean-square (RMS difference of the retrieved wind speeds with respect to the H*wind analysis data are 0.04 and 2.75 m/s, respectively, which provides an encouraging result for retrieving hurricane wind speeds over the ocean surface. The retrieved wind speeds show good agreement with the SFMR measurements. Two case studies demonstrate that the mean bias and RMS difference are 0.79 m/s and 1.79 m/s for hurricane Rita-1 and 0.63 m/s and 2.38 m/s for hurricane Rita-2, respectively. In general, the wind speed retrieval accuracy of the new model in hurricanes ranges from 2.0 m/s in light rain to 3.9 m/s in heavy rain.
Statistical estimation of nuclear reactor dynamic parameters
International Nuclear Information System (INIS)
Cummins, J.D.
1962-02-01
This report discusses the study of the noise in nuclear reactors and associated power plant. The report is divided into three distinct parts. In the first part parameters which influence the dynamic behaviour of some reactors will be specified and their effect on dynamic performance described. Methods of estimating dynamic parameters using statistical signals will be described in detail together with descriptions of the usefulness of the results, the accuracy and related topics. Some experiments which have been and which might be performed on nuclear reactors will be described. In the second part of the report a digital computer programme will be described. The computer programme derives the correlation functions and the spectra of signals. The programme will compute the frequency response both gain and phase for physical items of plant for which simultaneous recordings of input and output signal variations have been made. Estimations of the accuracy of the correlation functions and the spectra may be computed using the programme and the amplitude distribution of signals may also b computed. The programme is written in autocode for the Ferranti Mercury computer. In the third part of the report a practical example of the use of the method and the digital programme is presented. In order to eliminate difficulties of interpretation a very simple plant model was chosen i.e. a simple first order lag. Several interesting properties of statistical signals were measured and will be discussed. (author)
Statistical distributions applications and parameter estimates
Thomopoulos, Nick T
2017-01-01
This book gives a description of the group of statistical distributions that have ample application to studies in statistics and probability. Understanding statistical distributions is fundamental for researchers in almost all disciplines. The informed researcher will select the statistical distribution that best fits the data in the study at hand. Some of the distributions are well known to the general researcher and are in use in a wide variety of ways. Other useful distributions are less understood and are not in common use. The book describes when and how to apply each of the distributions in research studies, with a goal to identify the distribution that best applies to the study. The distributions are for continuous, discrete, and bivariate random variables. In most studies, the parameter values are not known a priori, and sample data is needed to estimate parameter values. In other scenarios, no sample data is available, and the researcher seeks some insight that allows the estimate of ...
Estimation of the uncertainty in wind power forecasting
International Nuclear Information System (INIS)
Pinson, P.
2006-03-01
WIND POWER experiences a tremendous development of its installed capacities in Europe. Though, the intermittence of wind generation causes difficulties in the management of power systems. Also, in the context of the deregulation of electricity markets, wind energy is penalized by its intermittent nature. It is recognized today that the forecasting of wind power for horizons up to 2/3-day ahead eases the integration of wind generation. Wind power forecasts are traditionally provided in the form of point predictions, which correspond to the most-likely power production for a given horizon. That sole information is not sufficient for developing optimal management or trading strategies. Therefore, we investigate on possible ways for estimating the uncertainty of wind power forecasts. The characteristics of the prediction uncertainty are described by a thorough study of the performance of some of the state-of-the-art approaches, and by underlining the influence of some variables e.g. level of predicted power on distributions of prediction errors. Then, a generic method for the estimation of prediction intervals is introduced. This statistical method is non-parametric and utilizes fuzzy logic concepts for integrating expertise on the prediction uncertainty characteristics. By estimating several prediction intervals at once, one obtains predictive distributions of wind power output. The proposed method is evaluated in terms of its reliability, sharpness and resolution. In parallel, we explore the potential use of ensemble predictions for skill forecasting. Wind power ensemble forecasts are obtained either by converting meteorological ensembles (from ECMWF and NCEP) to power or by applying a poor man's temporal approach. A proposal for the definition of prediction risk indices is given, reflecting the disagreement between ensemble members over a set of successive look-ahead times. Such prediction risk indices may comprise a more comprehensive signal on the expected level
Reassessing Wind Potential Estimates for India: Economic and Policy Implications
Energy Technology Data Exchange (ETDEWEB)
Phadke, Amol; Bharvirkar, Ranjit; Khangura, Jagmeet
2011-09-15
We assess developable on-shore wind potential in India at three different hub-heights and under two sensitivity scenarios – one with no farmland included, the other with all farmland included. Under the “no farmland included” case, the total wind potential in India ranges from 748 GW at 80m hub-height to 976 GW at 120m hub-height. Under the “all farmland included” case, the potential with a minimum capacity factor of 20 percent ranges from 984 GW to 1,549 GW. High quality wind energy sites, at 80m hub-height with a minimum capacity factor of 25 percent, have a potential between 253 GW (no farmland included) and 306 GW (all farmland included). Our estimates are more than 15 times the current official estimate of wind energy potential in India (estimated at 50m hub height) and are about one tenth of the official estimate of the wind energy potential in the US.
Ziter, Brett
Current industry standards for evaluating wind turbine power performance require erecting a meteorological mast on site to obtain reference measurements of hub-height wind speed. New considerations for small wind turbines (SWTs) offer the alternative of using an anemometer extending from a lower elevation on the turbine tower. In either case, SWT owners face questions and impracticalities when applying this standard in-situ. Alternative methods of predicting hub-height wind speed for SWT performance evaluation have been assessed experimentally using a Bergey XL.1 SWT collocated with a meteorological mast. Findings indicate that vertical extrapolation can increase the accuracy of tower-mounted anemometry for predicting hub-height wind speed. It is recommended to use concurrent wind speed measurements from anemometers at two elevations to develop site-specific wind shear parameters. Three-dimensional wind speed data from a sonic anemometer were used alongside a theoretical model to determine the optimal location for the topmost anemometer but results were inconclusive.
Statistical Properties of Geomagnetic Activity Indices and Solar Wind Parameters
Directory of Open Access Journals (Sweden)
Jung-Hee Kim
2014-06-01
Full Text Available As the prediction of geomagnetic storms is becoming an important and practical problem, conditions in the Earth’s magnetosphere have been studied rigorously in terms of those in the interplanetary space. Another approach to space weather forecast is to deal with it as a probabilistic geomagnetic storm forecasting problem. In this study, we carry out detailed statistical analysis of solar wind parameters and geomagnetic indices examining the dependence of the distribution on the solar cycle and annual variations. Our main findings are as follows: (1 The distribution of parameters obtained via the superimposed epoch method follows the Gaussian distribution. (2 When solar activity is at its maximum the mean value of the distribution is shifted to the direction indicating the intense environment. Furthermore, the width of the distribution becomes wider at its maximum than at its minimum so that more extreme case can be expected. (3 The distribution of some certain heliospheric parameters is less sensitive to the phase of the solar cycle and annual variations. (4 The distribution of the eastward component of the interplanetary electric field BV and the solar wind driving function BV2, however, appears to be all dependent on the solar maximum/minimum, the descending/ascending phases of the solar cycle and the equinoxes/solstices. (5 The distribution of the AE index and the Dst index shares statistical features closely with BV and BV2 compared with other heliospheric parameters. In this sense, BV and BV2 are more robust proxies of the geomagnetic storm. We conclude by pointing out that our results allow us to step forward in providing the occurrence probability of geomagnetic storms for space weather and physical modeling.
Estimation of wind and solar resources in Mali
Energy Technology Data Exchange (ETDEWEB)
Badger, J.; Kamissoko, F.; Olander Rasmussen, M.; Larsen, Soeren; Guidon, N.; Boye Hansen, L.; Dewilde, L.; Alhousseini, M.; Noergaard, P.; Nygaard, I.
2012-11-15
The wind resource has been estimated for all of Mali at 7.5 km resolution using the KAMM/WAsP numerical wind atlas methodology. Three domains were used to cover entire country and three sets of wind classes used to capture change in large scale forcing over country. The final output includes generalized climate statistics for any location in Mali, giving wind direction and wind speed distribution. The modelled generalized climate statistics can be used directly in the WAsP software. The preliminary results show a wind resource, which is relatively low, but which under certain conditions may be economically feasible, i.e. at favourably exposed sites, giving enhanced winds, and where practical utilization is possible, given consideration to grid connection or replacement or augmentation of diesel-based electricity systems. The solar energy resource for Mali was assessed for the period between July 2008 and June 2011 using a remote sensing based estimate of the down-welling surface shortwave flux. The remote sensing estimates were adjusted on a month-by-month basis to account for seasonal differences between the remote sensing estimates and in situ data. Calibration was found to improve the coefficient of determination as well as decreasing the mean error both for the calibration and validation data. Compared to the results presented in the ''Renewable energy resources in Mali - preliminary mapping''-report that showed a tendency for underestimation compared to data from the NASA PPOWER/SSE database, the presented results show a very good agreement with the in situ data (after calibration) with no significant bias. Unfortunately, the NASA-database only contains data up until 2005, so a similar comparison could not be done for the time period analyzed in this study, although the agreement with the historic NASA data is still useful as reference. (LN)
Transformer winding temperature estimation based on tank surface temperature
Guo, Wenyu; Wijaya, Jaury; Martin, Daniel; Lelekakis, Nick
2011-04-01
Power transformers are among the most valuable assets of the electrical grid. Since the largest units cost in the order of millions of dollars, it is desirable to operate them in such a manner that extends their remaining lives. Operating these units at high temperature will cause excessive insulation ageing in the windings. Consequently, it is necessary to study the thermal performance of these expensive items. Measuring or estimating the winding temperature of power transformers is beneficial to a utility because this provides them with the data necessary to make informed decisions on how best to use their assets. Fiber optic sensors have recently become viable for the direct measurement of winding temperatures while a transformer is energized. However, it is only practical to install a fiber optic temperature sensor during the manufacture of a transformer. For transformers operating without fiber optic sensors, the winding temperature can be estimated with calculations using the temperature of the oil at the top of the transformer tank. When the oil temperature measurement is not easily available, the temperature of the tank surface may be used as an alternative. This paper shows how surface temperature may be utilized to estimate the winding temperature within a transformer designed for research purposes.
Spectral Analysis of Geomagnetic Activity Indices and Solar Wind Parameters
Directory of Open Access Journals (Sweden)
Jung-Hee Kim
2014-06-01
Full Text Available Solar variability is widely known to affect the interplanetary space and in turn the Earth’s electromagnetical environment on the basis of common periodicities in the solar and geomagnetic activity indices. The goal of this study is twofold. Firstly, we attempt to associate modes by comparing a temporal behavior of the power of geomagnetic activity parameters since it is barely sufficient searching for common peaks with a similar periodicity in order to causally correlate geomagnetic activity parameters. As a result of the wavelet transform analysis we are able to obtain information on the temporal behavior of the power in the velocity of the solar wind, the number density of protons in the solar wind, the AE index, the Dst index, the interplanetary magnetic field, B and its three components of the GSM coordinate system, BX, BY, BZ. Secondly, we also attempt to search for any signatures of influence on the space environment near the Earth by inner planets orbiting around the Sun. Our main findings are as follows: (1 Parameters we have investigated show periodicities of ~ 27 days, ~ 13.5 days, ~ 9 days. (2 The peaks in the power spectrum of BZ appear to be split due to an unknown agent. (3 For some modes powers are not present all the time and intervals showing high powers do not always coincide. (4 Noticeable peaks do not emerge at those frequencies corresponding to the synodic and/or sidereal periods of Mercury and Venus, which leads us to conclude that the Earth’s space environment is not subject to the shadow of the inner planets as suggested earlier.
Direct Statistical Thermal Wind Estimation Procedure
1989-03-10
1 . Althloti1 tourI other- mini mit1lation criteria were ev aluated inI that reference. there w as not a SLtICIent i11vIrOVe:illent uing1 the mlore...position x,. i = 1,...,N , where x = (x1 , x2) define a two- dimensional regular grid Find a plane : f(x = a + bx1 + cx 2 = d T X, (D.1-1) D-I wliere: x...Equation D. I-I defines a plane w% hose gradient, (b c). is an estimate of the radiance gra- dient at the center of the data grid expressed in the data
Failure Probability Estimation of Wind Turbines by Enhanced Monte Carlo
DEFF Research Database (Denmark)
Sichani, Mahdi Teimouri; Nielsen, Søren R.K.; Naess, Arvid
2012-01-01
is controlled by the pitch controller. This provides a fair framework for comparison of the behavior and failure event of the wind turbine with emphasis on the effect of the pitch controller. The Enhanced Monte Carlo method is then applied to the model and the failure probabilities of the model are estimated......, estimation of very low failure probabilities with SMC simulations leads to unacceptably high computational costs. In this study, an Enhanced Monte Carlo (EMC) method is proposed that overcomes this obstacle. The method has advantages over both POT and SMC in terms of its low computational cost and accuracy....... The method is applied to a low-order numerical model of a 5 MW wind turbine with a pitch controller exposed to a turbulent inflow. Two cases of the wind turbine model are investigated. In the first case, the rotor is running with a constant rotational speed. In the second case, the variable rotational speed...
Impact of Solar wind plasma parameters on geomagnetic condition
Rathore, Balveer Singh; Gupta, Dinesh Chandra
Today’s challenge for space weather research is to quantitatively predict the dynamics of the magnetosphere from measured solar wind and interplanetary magnetic field conditions. A correlative studies between the Geomagnetic Storms (GMSs) and the various interplanetary field/plasma parameters have been performed to search the causes of geomagnetic activity and developing models for prediction of the occurrence of GMSs which are important for space weather predictions. In the present paper we found possible co-relation of geomagnetic storms with solar wind and IMF parameters in three different situations and also drive the linear relation equation for all parameters in three situations. On basis of present statistical study we developed an empirical model. With the help of this model we can predict all categories of geomagnetic storms. This model based on following fact. The total interplanetary magnetic field Btotal can use as alarm of geomagnetic storms, when sudden changes in total magnetic field B total, it is a first alarm on condition for storms arrival. It is observed in the present study that southward Bz-component of IMF is an important factor for geomagnetic storms. And it is the result of the paper that the magnitude of Bz is maximum neither during initial phase (at the instant of IP shock) nor during main phase (at the instant of Dst minimum). So it is seen in this study that there is a time delay between maximum value of southward Bz and Dst minimum and this time delay can be used in the prediction of the intensity of magnetic storm two -three hours before of main phase of geomagnetic storm. A linear relation have been derived between maximum value of southward component of Bz and Dst for prediction is Dst = (-0.06) + (7.65)Bz + t. Some auxiliary condition should be fulfils with this, speed of solar wind should be on average 350 km/s to 750 km/s, plasma beta should be low and most important plasma temperature should be low for intense storms if plasma
Effect of solar wind plasma parameters on space weather
Rathore, Balveer S.; Gupta, Dinesh C.; Kaushik, Subhash C.
2015-01-01
Today's challenge for space weather research is to quantitatively predict the dynamics of the magnetosphere from measured solar wind and interplanetary magnetic field (IMF) conditions. Correlative studies between geomagnetic storms (GMSs) and the various interplanetary (IP) field/plasma parameters have been performed to search for the causes of geomagnetic activity and develop models for predicting the occurrence of GMSs, which are important for space weather predictions. We find a possible relation between GMSs and solar wind and IMF parameters in three different situations and also derived the linear relation for all parameters in three situations. On the basis of the present statistical study, we develop an empirical model. With the help of this model, we can predict all categories of GMSs. This model is based on the following fact: the total IMF Btotal can be used to trigger an alarm for GMSs, when sudden changes in total magnetic field Btotal occur. This is the first alarm condition for a storm's arrival. It is observed in the present study that the southward Bz component of the IMF is an important factor for describing GMSs. A result of the paper is that the magnitude of Bz is maximum neither during the initial phase (at the instant of the IP shock) nor during the main phase (at the instant of Disturbance storm time (Dst) minimum). It is seen in this study that there is a time delay between the maximum value of southward Bz and the Dst minimum, and this time delay can be used in the prediction of the intensity of a magnetic storm two-three hours before the main phase of a GMS. A linear relation has been derived between the maximum value of the southward component of Bz and the Dst, which is Dst = (-0.06) + (7.65) Bz +t. Some auxiliary conditions should be fulfilled with this, for example the speed of the solar wind should, on average, be 350 km s-1 to 750 km s-1, plasma β should be low and, most importantly, plasma temperature should be low for intense
International Nuclear Information System (INIS)
Liu, Heping; Shi, Jing; Qu, Xiuli
2013-01-01
Highlights: ► Ten-minute wind speed and power generation data of an offshore wind turbine are used. ► An ARMA–GARCH-M model is built to simultaneously forecast wind speed mean and volatility. ► The operation probability and expected power output of the wind turbine are predicted. ► The integrated approach produces more accurate wind power forecasting than other conventional methods. - Abstract: In this paper, we introduce a quantitative methodology that performs the interval estimation of wind speed, calculates the operation probability of wind turbine, and forecasts the wind power output. The technological advantage of this methodology stems from the empowered capability of mean and volatility forecasting of wind speed. Based on the real wind speed and corresponding wind power output data from an offshore wind turbine, this methodology is applied to build an ARMA–GARCH-M model for wind speed forecasting, and then to compute the operation probability and the expected power output of the wind turbine. The results show that the developed methodology is effective, the obtained interval estimation of wind speed is reliable, and the forecasted operation probability and expected wind power output of the wind turbine are accurate
Error estimates for CCMP ocean surface wind data sets
Atlas, R. M.; Hoffman, R. N.; Ardizzone, J.; Leidner, S.; Jusem, J.; Smith, D. K.; Gombos, D.
2011-12-01
The cross-calibrated, multi-platform (CCMP) ocean surface wind data sets are now available at the Physical Oceanography Distributed Active Archive Center from July 1987 through December 2010. These data support wide-ranging air-sea research and applications. The main Level 3.0 data set has global ocean coverage (within 78S-78N) with 25-kilometer resolution every 6 hours. An enhanced variational analysis method (VAM) quality controls and optimally combines multiple input data sources to create the Level 3.0 data set. Data included are all available RSS DISCOVER wind observations, in situ buoys and ships, and ECMWF analyses. The VAM is set up to use the ECMWF analyses to fill in areas of no data and to provide an initial estimate of wind direction. As described in an article in the Feb. 2011 BAMS, when compared to conventional analyses and reanalyses, the CCMP winds are significantly different in some synoptic cases, result in different storm statistics, and provide enhanced high-spatial resolution time averages of ocean surface wind. We plan enhancements to produce estimated uncertainties for the CCMP data. We will apply the method of Desroziers et al. for the diagnosis of error statistics in observation space to the VAM O-B, O-A, and B-A increments. To isolate particular error statistics we will stratify the results by which individual instruments were used to create the increments. Then we will use cross-validation studies to estimate other error statistics. For example, comparisons in regions of overlap for VAM analyses based on SSMI and QuikSCAT separately and together will enable estimating the VAM directional error when using SSMI alone. Level 3.0 error estimates will enable construction of error estimates for the time averaged data sets.
An Improved Global Wind Resource Estimate for Integrated Assessment Models: Preprint
Energy Technology Data Exchange (ETDEWEB)
Eurek, Kelly [National Renewable Energy Lab. (NREL), Golden, CO (United States); Sullivan, Patrick [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gleason, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Hettinger, Dylan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Heimiller, Donna [National Renewable Energy Lab. (NREL), Golden, CO (United States); Lopez, Anthony [National Renewable Energy Lab. (NREL), Golden, CO (United States)
2017-02-01
This paper summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquely detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5 MW composite wind turbines with 90 m hub heights, 0.95 availability, 90% array efficiency, and 5 MW/km2 deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.
Online Estimation of wind turbine blade deflection with UWB signals
DEFF Research Database (Denmark)
Jensen, Tobias Lindstrøm; Jakobsen, Morten Lomholt; Østergaard, Jan
2015-01-01
In this paper we use ultra-wideband (UWB) signals for the localization of blade tips on wind turbines. Our approach is to acquire two separate distances to each tip via time-delay estimation, and each tip is then localized by triangulation. We derive an approximate maximum a posteriori (MAP) delay...
Anthropogenic radioisotopes to estimate rates of soil redistribution by wind
Erosion of soil by wind and water is a degrading process that affects millions of hectares worldwide. Atmospheric testing of nuclear weapons and the resulting fallout of anthropogenic radioisotopes, particularly Cesium 137, has made possible the estimation of mean soil redistribution rates. The pe...
Fault Detection of Wind Turbines with Uncertain Parameters: A Set-Membership Approach
Directory of Open Access Journals (Sweden)
Thomas Bak
2012-07-01
Full Text Available In this paper a set-membership approach for fault detection of a benchmark wind turbine is proposed. The benchmark represents relevant fault scenarios in the control system, including sensor, actuator and system faults. In addition we also consider parameter uncertainties and uncertainties on the torque coefficient. High noise on the wind speed measurement, nonlinearities in the aerodynamic torque and uncertainties on the parameters make fault detection a challenging problem. We use an effective wind speed estimator to reduce the noise on the wind speed measurements. A set-membership approach is used generate a set that contains all states consistent with the past measurements and the given model of the wind turbine including uncertainties and noise. This set represents all possible states the system can be in if not faulty. If the current measurement is not consistent with this set, a fault is detected. For representation of these sets we use zonotopes and for modeling of uncertainties we use matrix zonotopes, which yields a computationally efficient algorithm. The method is applied to the wind turbine benchmark problem without and with uncertainties. The result demonstrates the effectiveness of the proposed method compared to other proposed methods applied to the same problem. An advantage of the proposed method is that there is no need for threshold design, and it does not produce positive false alarms. In the case where uncertainty on the torque lookup table is introduced, some faults are not detectable. Previous research has not addressed this uncertainty. The method proposed here requires equal or less detection time than previous results.
Dynamic State Estimation and Parameter Calibration of DFIG based on Ensemble Kalman Filter
Energy Technology Data Exchange (ETDEWEB)
Fan, Rui; Huang, Zhenyu; Wang, Shaobu; Diao, Ruisheng; Meng, Da
2015-07-30
With the growing interest in the application of wind energy, doubly fed induction generator (DFIG) plays an essential role in the industry nowadays. To deal with the increasing stochastic variations introduced by intermittent wind resource and responsive loads, dynamic state estimation (DSE) are introduced in any power system associated with DFIGs. However, sometimes this dynamic analysis canould not work because the parameters of DFIGs are not accurate enough. To solve the problem, an ensemble Kalman filter (EnKF) method is proposed for the state estimation and parameter calibration tasks. In this paper, a DFIG is modeled and implemented with the EnKF method. Sensitivity analysis is demonstrated regarding the measurement noise, initial state errors and parameter errors. The results indicate this EnKF method has a robust performance on the state estimation and parameter calibration of DFIGs.
Estimating the Probability of Wind Ramping Events: A Data-driven Approach
Wang, Cheng; Wei, Wei; Wang, Jianhui; Qiu, Feng
2016-01-01
This letter proposes a data-driven method for estimating the probability of wind ramping events without exploiting the exact probability distribution function (PDF) of wind power. Actual wind data validates the proposed method.
Yu, Tao; Kang, Chao; Zhao, Pan
2018-01-01
The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing. PMID:29385048
Parameter estimation in fractional diffusion models
Kubilius, Kęstutis; Ralchenko, Kostiantyn
2017-01-01
This book is devoted to parameter estimation in diffusion models involving fractional Brownian motion and related processes. For many years now, standard Brownian motion has been (and still remains) a popular model of randomness used to investigate processes in the natural sciences, financial markets, and the economy. The substantial limitation in the use of stochastic diffusion models with Brownian motion is due to the fact that the motion has independent increments, and, therefore, the random noise it generates is “white,” i.e., uncorrelated. However, many processes in the natural sciences, computer networks and financial markets have long-term or short-term dependences, i.e., the correlations of random noise in these processes are non-zero, and slowly or rapidly decrease with time. In particular, models of financial markets demonstrate various kinds of memory and usually this memory is modeled by fractional Brownian diffusion. Therefore, the book constructs diffusion models with memory and provides s...
Ocean wave parameters estimation using backpropagation neural networks
Digital Repository Service at National Institute of Oceanography (India)
Mandal, S.; SubbaRao; Raju, D.H.
is trained the ocean wave parameters can be estimated for unknown measured spectra, whereas significant wave height and spectral peak period are required to first generate the Scott spectra and then estimate other ocean wave parameters....
Determination of Parameter Estimation Errors Due to Noise and Undermodelling
DEFF Research Database (Denmark)
Knudsen, Morten
1996-01-01
A simple method for determination of the estimation error of physical parameters due to noise and undermodelling is developed.......A simple method for determination of the estimation error of physical parameters due to noise and undermodelling is developed....
Model-Based Load Estimation for Predictive Condition Monitoring of Wind Turbines
DEFF Research Database (Denmark)
Perisic, Nevena; Pederen, Bo Juul; Grunnet, Jacob Deleuran
The main objective of this paper is to present a Load Observer Tool (LOT) for condition monitoring of structural extreme and fatigue loads on the main wind turbine (WTG) components. LOT uses well-known methods from system identification, state estimation and fatigue analysis in a novel approach...... for application in condition monitoring. Fatigue loads are estimated online using a load observer and grey box models which include relevant WTG dynamics. Identification of model parameters and calibration of observer are performed offline using measurements from WTG prototype. Signal processing of estimated load...... 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...
Estimation of Two-Parameter Logistic Item Response Curves.
Tsutakawa, Robert K.
1984-01-01
The EM algorithm is used to derive maximum likelihood estimates for item parameters of the two-parameter logistic item response curves. The observed information matrix is then used to approximate the covariance matrix of these estimates. Simulated data are used to compare the estimated and actual item parameters. (Author/BW)
State of the art on wind resource estimation
Energy Technology Data Exchange (ETDEWEB)
Maribo Pedersen, B.
1998-12-31
With the increasing number of wind resource estimation studies carried out for regions, countries and even larger areas all over the world, the IEA finds that the time has come to stop and take stock of the various methods used in these studies. The IEA would therefore like to propose an Experts Meeting on wind resource estimation. The Experts Meeting should describe the models and databases used in the various studies. It should shed light on the strengths and shortcomings of the models and answer questions like: where and under what circumstances should a specific model be used? what is the expected accuracy of the estimate of the model? and what is the applicability? When addressing databases the main goal will be to identify the content and scope of these. Further, the quality, availability and reliability of the databases must also be recognised. In the various studies of wind resources the models and databases have been combined in different ways. A final goal of the Experts Meeting is to see whether it is possible to develop systems of methods which would depend on the available input. These systems of methods should be able to address the simple case (level 0) of a region with barely no data, to the complex case of a region with all available measurements: surface observations, radio soundings, satellite observations and so on. The outcome of the meeting should be an inventory of available models as well as databases and a map of already studied regions. (au)
Directory of Open Access Journals (Sweden)
Pé Alexandra St.
2016-01-01
Compared to lidar measurements, power law extrapolation estimates and operational National Weather Service models underestimated hub-height wind speeds in the WEA. In addition, lidar observations suggest the frequent development of a low-level wind maximum (LLWM, with high turbinelayer wind shear and low turbulence intensity within a turbine’s rotor layer (40m-160m. Results elucidate the advantages of using Doppler wind lidar technology to improve offshore wind resource estimates and its ability to monitor under-sampled offshore meteorological controls impact on a potential turbine’s ability to produce power.
VizieR Online Data Catalog: Stellar parameters and assumed wind parameters (Cazorla+, 2017)
Cazorla, C.; Morel, T.; Naze, Y.; Rauw, G.; Semaan, T.; Daflon, S.; Oey, S.
2017-03-01
Stellar parameters derived for the stars in our sample and assumed wind parameters for our hotter stars. Because macroturbulent velocities cannot be determined reliably for fast rotators (Sect. 4.2), all values in column 6 are upper limits. Column 7 provides the multiplicity status (see Sect. 4.1 for the classification criterion and Appendix C for the RV studies of each individual object). The runaway status is based on literature studies (references are given on a star-to-star basis in Appendix C). Columns 15, 16, and 17 of the table presenting the results for the hotter stars list the assumed wind parameters. For stars with the lowest temperatures (typically B0.5 stars), the carbon abundance cannot be firmly determined due to the weakness of the CIII lines at these temperatures. Besides, NII lines may also be very weak for the hottest stars studied with DETAIL/SURFACE. In these cases, we provide upper limits for both carbon and nitrogen abundances. They correspond to predicted lines becoming detectable, i.e., having a depth significantly exceeding the local noise. Similarly, CMFGEN fits may converge towards very high or very low CNO abundances. In both cases, the upper or lower limits were determined from the chi2 curves and correspond to the limit of their flat minimum. Since the CNO abundances are measured relative to the hydrogen content (assumed to be constant in our study), a correction should in principle be applied to the CNO abundances of stars that exhibit a very high helium abundance (and therefore have a reduced hydrogen abundance). However, we found this correction to be negligible (<~0.1dex) even for the most He-rich stars. The 1σ errors on the parameters are given in dedicated columns. (2 data files).
Application of spreadsheet to estimate infiltration parameters
Zakwan, Mohammad; Muzzammil, Mohammad; Alam, Javed
2016-01-01
Infiltration is the process of flow of water into the ground through the soil surface. Soil water although contributes a negligible fraction of total water present on earth surface, but is of utmost importance for plant life. Estimation of infiltration rates is of paramount importance for estimation of effective rainfall, groundwater recharge, and designing of irrigation systems. Numerous infiltration models are in use for estimation of infiltration rates. The conventional graphical approach ...
[Statistical estimation of parameters in allometric equations].
Zotin, A A
2000-01-01
An algorithm for estimating allometric coefficients widely used in biological studies is presented. The coefficients can be estimated only when the relationship between logarithms of the approximated data meets the linearity criterion. The proposed algorithm was applied for the brain-body weight relationship in mammals and oxygen consumption rate-body weight relationship in amphibians.
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
Loads simulations as performed to obtain design loads on wind turbines, requires wind turbulence as an input, characterized by parameters associated with the turbulence length scale, dissipation and anisotropy. The effect of variation in these turbulence spectral parameters on the magnitude...... 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...
determination of weibull parameters and analysis of wind power
African Journals Online (AJOL)
HOD
for sustainable energy sources. The 2016 International. Energy Agency (IEA) world energy outlook report assess the growth in the renewable energy sector as quite impressive [1]. With respect to wind turbine installations, about 63,135 MW of wind power capacity was added globally in 2015 indicating a 23.2% increase.
Empirically modelled Pc3 activity based on solar wind parameters
Directory of Open Access Journals (Sweden)
B. Heilig
2010-09-01
Full Text Available It is known that under certain solar wind (SW/interplanetary magnetic field (IMF conditions (e.g. high SW speed, low cone angle the occurrence of ground-level Pc3–4 pulsations is more likely. In this paper we demonstrate that in the event of anomalously low SW particle density, Pc3 activity is extremely low regardless of otherwise favourable SW speed and cone angle. We re-investigate the SW control of Pc3 pulsation activity through a statistical analysis and two empirical models with emphasis on the influence of SW density on Pc3 activity. We utilise SW and IMF measurements from the OMNI project and ground-based magnetometer measurements from the MM100 array to relate SW and IMF measurements to the occurrence of Pc3 activity. Multiple linear regression and artificial neural network models are used in iterative processes in order to identify sets of SW-based input parameters, which optimally reproduce a set of Pc3 activity data. The inclusion of SW density in the parameter set significantly improves the models. Not only the density itself, but other density related parameters, such as the dynamic pressure of the SW, or the standoff distance of the magnetopause work equally well in the model. The disappearance of Pc3s during low-density events can have at least four reasons according to the existing upstream wave theory: 1. Pausing the ion-cyclotron resonance that generates the upstream ultra low frequency waves in the absence of protons, 2. Weakening of the bow shock that implies less efficient reflection, 3. The SW becomes sub-Alfvénic and hence it is not able to sweep back the waves propagating upstream with the Alfvén-speed, and 4. The increase of the standoff distance of the magnetopause (and of the bow shock. Although the models cannot account for the lack of Pc3s during intervals when the SW density is extremely low, the resulting sets of optimal model inputs support the generation of mid latitude Pc3 activity predominantly through
Robust and Fault-Tolerant Linear Parameter-Varying Control of Wind Turbines
DEFF Research Database (Denmark)
Sloth, Christoffer; Esbensen, Thomas; Stoustrup, Jakob
2011-01-01
High performance and reliability are required for wind turbines to be competitive within the energy market. To capture their nonlinear behavior, wind turbines are often modeled using parameter-varying models. In this paper we design and compare multiple linear parameter-varying (LPV) controllers,...
Multi-objective optimization in quantum parameter estimation
Gong, BeiLi; Cui, Wei
2018-04-01
We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved, it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives: (1) maximizing the Fisher information, improving the parameter estimation precision, and (2) minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ɛ-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.
Improving Lidar Turbulence Estimates for Wind Energy: Preprint
Energy Technology Data Exchange (ETDEWEB)
Newman, Jennifer; Clifton, Andrew; Churchfield, Matthew; Klein, Petra
2016-10-01
Remote sensing devices (e.g., lidars) are quickly becoming a cost-effective and reliable alternative to meteorological towers for wind energy applications. Although lidars can measure mean wind speeds accurately, these devices measure different values of turbulence intensity (TI) than an instrument on a tower. In response to these issues, a lidar TI error reduction model was recently developed for commercially available lidars. The TI error model first applies physics-based corrections to the lidar measurements, then uses machine-learning techniques to further reduce errors in lidar TI estimates. The model was tested at two sites in the Southern Plains where vertically profiling lidars were collocated with meteorological towers. Results indicate that the model works well under stable conditions but cannot fully mitigate the effects of variance contamination under unstable conditions. To understand how variance contamination affects lidar TI estimates, a new set of equations was derived in previous work to characterize the actual variance measured by a lidar. Terms in these equations were quantified using a lidar simulator and modeled wind field, and the new equations were then implemented into the TI error model.
Estimation of Kinetic Parameters in an Automotive SCR Catalyst Model
DEFF Research Database (Denmark)
Åberg, Andreas; Widd, Anders; Abildskov, Jens
2016-01-01
A challenge during the development of models for simulation of the automotive Selective Catalytic Reduction catalyst is the parameter estimation of the kinetic parameters, which can be time consuming and problematic. The parameter estimation is often carried out on small-scale reactor tests...
Genetic parameter estimates for growth traits at different ages in ...
African Journals Online (AJOL)
Precise and accurate genetic parameter estimates are crucial for making sound decisions in many stages of animal improvement programme. Genetic parameter estimates for eight growth traits were determined in 308 turkeys generated from mating pure indigenous parents. PROC MIXED of SAS was used to estimate ...
Wind gust estimation by combining numerical weather prediction model and statistical post-processing
Patlakas, Platon; Drakaki, Eleni; Galanis, George; Spyrou, Christos; Kallos, George
2017-04-01
The continuous rise of off-shore and near-shore activities as well as the development of structures, such as wind farms and various offshore platforms, requires the employment of state-of-the-art risk assessment techniques. Such analysis is used to set the safety standards and can be characterized as a climatologically oriented approach. Nevertheless, a reliable operational support is also needed in order to minimize cost drawbacks and human danger during the construction and the functioning stage as well as during maintenance activities. One of the most important parameters for this kind of analysis is the wind speed intensity and variability. A critical measure associated with this variability is the presence and magnitude of wind gusts as estimated in the reference level of 10m. The latter can be attributed to different processes that vary among boundary-layer turbulence, convection activities, mountain waves and wake phenomena. The purpose of this work is the development of a wind gust forecasting methodology combining a Numerical Weather Prediction model and a dynamical statistical tool based on Kalman filtering. To this end, the parameterization of Wind Gust Estimate method was implemented to function within the framework of the atmospheric model SKIRON/Dust. The new modeling tool combines the atmospheric model with a statistical local adaptation methodology based on Kalman filters. This has been tested over the offshore west coastline of the United States. The main purpose is to provide a useful tool for wind analysis and prediction and applications related to offshore wind energy (power prediction, operation and maintenance). The results have been evaluated by using observational data from the NOAA's buoy network. As it was found, the predicted output shows a good behavior that is further improved after the local adjustment post-process.
The Parameters Affect on Power Coefficient Vertical Axis Wind Turbine
Directory of Open Access Journals (Sweden)
Ahmed Y. Qasim
2012-04-01
Full Text Available ABSTRACT: This study describes the design of a special type of vertical axis rotor wind turbine with moveable vertically positioned vanes. The novel design increases the torque in the left side of the wind turbine by increasing the drag coefficient. It also reduces the negative torque of the frame which rotates contrary to the wind in the other side. Two different types of models, having different vane shapes (flat vane and cavity shaped vane, were fabricated. Each type consisted of two models with varying number of frames (three and four frames. The models were tested in a wind tunnel with variable wind speed in order to understand the effect of shape, weight, and number of frames on the power coefficient of the wind turbine. ABSTRAK: Di dalam kajian ini, rotor turbin angin berpaksi vertikel sebagai rangka khusus telah direkabentuk dengan lokasi vertikel mudahalih oleh bilah kipas. Rekabentuk ini meningkatkan tork di bahagian kiri turbin angin dengan meningkatkan pekali seretan dan mengurangkan tork negatif rangka yang berputar berlawanan dengan angin pada bahagian lain. Dua jenis model berbentuk berlainan telah difabrikasi (bilah kipas rata dan bilah kipas berbentuk kaviti, dengan setiap jenis mempunyai dua model dengan bilangan rangka yang berlainan (berangka tiga dan berangka empat. Model-model telah diuji di dalam terowong angin dengan kelajuan angin yang berbeza bagi mendapatkan kesan rekabentuk, berat dan bilangan rangka ke atas pekali kuasa.KEYWORDS: design; wind turbine; drag coefficient; vane
Model-Based Estimation of Collision Risks of Predatory Birds with Wind Turbines
Directory of Open Access Journals (Sweden)
Marcus Eichhorn
2012-06-01
Full Text Available The expansion of renewable energies, such as wind power, is a promising way of mitigating climate change. Because of the risk of collision with rotor blades, wind turbines have negative effects on local bird populations, particularly on raptors such as the Red Kite (Milvus milvus. Appropriate assessment tools for these effects have been lacking. To close this gap, we have developed an agent-based, spatially explicit model that simulates the foraging behavior of the Red Kite around its aerie in a landscape consisting of different land-use types. We determined the collision risk of the Red Kite with the turbine as a function of the distance between the wind turbine and the aerie and other parameters. The impact function comprises the synergistic effects of species-specific foraging behavior and landscape structure. The collision risk declines exponentially with increasing distance. The strength of this decline depends on the raptor's foraging behavior, its ability to avoid wind turbines, and the mean wind speed in the region. The collision risks, which are estimated by the simulation model, are in the range of values observed in the field. The derived impact function shows that the collision risk can be described as an aggregated function of distance between the wind turbine and the raptor's aerie. This allows an easy and rapid assessment of the ecological impacts of (existing or planned wind turbines in relation to their spatial location. Furthermore, it implies that minimum buffer zones for different landscapes can be determined in a defensible way. This modeling approach can be extended to other bird species with central-place foraging behavior. It provides a helpful tool for landscape planning aimed at minimizing the impacts of wind power on biodiversity.
Simultaneous estimation of earthquake source parameters and ...
Indian Academy of Sciences (India)
stress drop values are quite large compared to the other similar size Indian intraplate earthquakes, which can be attributed ... Earthquake source parameters; crustal Q-value; simultaneous inversion; S-wave spectra; aftershocks. J. Earth Syst. Sci. ...... 28 1339–1342. Lee W H K and Valdes C M 1985 HYP071PC: A personal.
ESTIMATION OF SHEAR STRENGTH PARAMETERS OF ...
African Journals Online (AJOL)
This research work seeks to develop models for predicting the shear strength parameters (cohesion and angle of friction) of lateritic soils in central and southern areas of Delta State using artificial neural network modeling technique. The application of these models will help reduce cost and time in acquiring geotechnical ...
Simultaneous estimation of experimental and material parameters
CSIR Research Space (South Africa)
Jansen van Rensburg, GJ
2012-07-01
Full Text Available This conference contribution focusses on the invertibility of non-ideal material tests to accurately determine material parameters. This is done by attempting to model non-ideal test cases and comparing strains as well as force history...
Wilches-Bernal, Felipe
of the WTG while the second controller manipulates the reactive power control of the WTG using the current magnitude as the feedback signal. Finally, the dissertation proposes a parameter identification method for identifying and verifying the reactive power control parameters of WTGs. Using voltage and current measurements of a wind unit as an input, the proposed method estimates an optimal set of parameters such that the output current of a standalone WTG model better approximates the measured signal. Because WTG are nonlinear systems, the identification method is solved by a Gauss-Newton iteration used to calculate the solution of a nonlinear least-squares problem. The effectiveness of the proposed method is illustrated using a set of simulated data and actual PMU recordings.
A Comparative Study of Distribution System Parameter Estimation Methods
Energy Technology Data Exchange (ETDEWEB)
Sun, Yannan; Williams, Tess L.; Gourisetti, Sri Nikhil Gup
2016-07-17
In this paper, we compare two parameter estimation methods for distribution systems: residual sensitivity analysis and state-vector augmentation with a Kalman filter. These two methods were originally proposed for transmission systems, and are still the most commonly used methods for parameter estimation. Distribution systems have much lower measurement redundancy than transmission systems. Therefore, estimating parameters is much more difficult. To increase the robustness of parameter estimation, the two methods are applied with combined measurement snapshots (measurement sets taken at different points in time), so that the redundancy for computing the parameter values is increased. The advantages and disadvantages of both methods are discussed. The results of this paper show that state-vector augmentation is a better approach for parameter estimation in distribution systems. Simulation studies are done on a modified version of IEEE 13-Node Test Feeder with varying levels of measurement noise and non-zero error in the other system model parameters.
Parameter estimation and testing of hypotheses
International Nuclear Information System (INIS)
Fruhwirth, R.
1996-01-01
This lecture presents the basic mathematical ideas underlying the concept of random variable and the construction and analysis of estimators and test statistics. The material presented is based mainly on four books given in the references: the general exposition of estimators and test statistics follows Kendall and Stuart which is a comprehensive review of the field; the book by Eadie et al. contains selecting topics of particular interest to experimental physicist and a host of illuminating examples from experimental high-energy physics; for the presentation of numerical procedures, the Press et al. and the Thisted books have been used. The last section deals with estimation in dynamic systems. In most books the Kalman filter is presented in a Bayesian framework, often obscured by cumbrous notation. In this lecture, the link to classical least-squares estimators and regression models is stressed with the aim of facilitating the access to this less familiar topic. References are given for specific applications to track and vertex fitting and for extended exposition of these topics. In the appendix, the link between Bayesian decision rules and feed-forward neural networks is presented. (J.S.). 10 refs., 5 figs., 1 appendix
Estimation of extreme wind gusts from inadequate data. Technical paper
Energy Technology Data Exchange (ETDEWEB)
Louw, W.J.; Katsiambirtas, E.
1974-01-01
The economic value of meteorological information to many weather-sensitive sectors of the economy has been established indisputably. However, to derive the maximum benefit from the use of weather data it is essential that such information be made available in the most useful form. Diversification of interest and enterprise therefore implies that meteorological parameters be presented in a variety of processed forms to suit the specialized needs of individual users. In the design and construction of high buildings, stack and power lines there is specific interest not only in the established values of maximum winds but also in the peak gusts which can be expected in future.
Wang, C.; Dai, L.; Sun, T.; Han, J.
2015-12-01
The Solar wind Magnetosphere Ionosphere Link Explorer (SMILE) is a novel self-standing mission to observe solar wind - magnetosphere coupling via simultaneous in situ solar wind /magnetosheath plasma and magnetic field measurements, X-ray images of the magnetosphere, and UV images of global auroral distribution defining system - level consequences. The SMILE mission is jointly supported by ESA and CSA, and the launch date is expected to be in 2021. SMILE will address several key outstanding questions concerning how the solar wind interacts with the magnetospheres on a global level. Quantitatively estimating the energy input from the solar wind into the magnetosphere on a global scale is still an observational challenge. Using global MHD simulations, we derive a new solar wind - magnetosphere energy coupling function. The X-ray images of the magnetosphere from the SMILE mission will help estimate the energy transfer from the solar wind into the magnetosphere. A second aspect SMILE can address is the open magnetic flux, which is closely related to magnetic reconnections in the dayside magnetopause and magnetotail. In a similar way, we find that the open magnetic flux can be estimated through a combined parameter f, which is a function of the solar wind velocity, number density, the southern interplanetary magnetic field strength, and the ionospheric Pederson conductance. The UV auroral images from SMILE will be used to determine the open magnetic flux, which may serve as a key space weather forecast element in the future.
Model-based Estimation of Gas Leakage for Fluid Power Accumulators in Wind Turbines
DEFF Research Database (Denmark)
Liniger, Jesper; Pedersen, Henrik Clemmensen; N. Soltani, Mohsen
2017-01-01
for accumulators, namely gas leakage. The method utilizes an Extended Kalman Filter for joint state and parameter estimation with special attention to limiting the use of sensors to those commonly used in wind turbines. The precision of the method is investigated on an experimental setup which allows for operation...... of the accumulator similar to the conditions in a turbine. The results show that gas leakage is indeed detectable during start-up of the turbine and robust behavior is achieved in a multi-fault environment where both gas and external fluid leakage occur simultaneously. The estimation precision is shown...... to be sensitive to initial conditions for the gas temperature and volume....
The use of wind tunnel facilities to estimate hydrodynamic data
Directory of Open Access Journals (Sweden)
Hoffmann Kristoffer
2016-01-01
In a series of measurements, wind tunnel testing has been used to investigate the static response characteristics of a circular and a rectangular section model. Motivated by the wish to estimate the vortex-induced in-line vibration characteristics of a neutrally buoyant submerged marine structure, additional measurements on extremely lightweight, helium-filled circular section models were conducted in a dynamic setup. During the experiment campaign, the mass of the model was varied in order to investigate how the mass ratio influences the vibration amplitude. The results show good agreement with both aerodynamic and hydrodynamic experimental results documented in the literature.
Estimation of a collision impact parameter
International Nuclear Information System (INIS)
Shmatov, S.V.; Zarubin, P.I.
2001-01-01
We demonstrate that the nuclear collision geometry (i.e. impact parameter) can be determined in an event-by-event analysis by measuring the transverse energy flow in the pseudorapidity region 3≤|η|≤5 with a minimal dependence on collision dynamics details at the LHC energy scale. Using the HIJING model we have illustrated our calculation by a simulation of events of nucleus-nucleus interactions at the c.m.s. energy from 1 up to 5.5 TeV per nucleon and various types of nuclei
Parameter Estimation for Improving Association Indicators in Binary Logistic Regression
Directory of Open Access Journals (Sweden)
Mahdi Bashiri
2012-02-01
Full Text Available The aim of this paper is estimation of Binary logistic regression parameters for maximizing the log-likelihood function with improved association indicators. In this paper the parameter estimation steps have been explained and then measures of association have been introduced and their calculations have been analyzed. Moreover a new related indicators based on membership degree level have been expressed. Indeed association measures demonstrate the number of success responses occurred in front of failure in certain number of Bernoulli independent experiments. In parameter estimation, existing indicators values is not sensitive to the parameter values, whereas the proposed indicators are sensitive to the estimated parameters during the iterative procedure. Therefore, proposing a new association indicator of binary logistic regression with more sensitivity to the estimated parameters in maximizing the log- likelihood in iterative procedure is innovation of this study.
DEFF Research Database (Denmark)
Gögmen, Tuhfe; Giebel, Gregor
2016-01-01
varies over the extent of the wind farm. This paper describes a method to estimate the TI at individual turbine locations by using the rotor effective wind speed calculated via high frequency turbine data. The method is applied to Lillgrund and Horns Rev-I offshore wind farms and the results are compared...... with TI derived from the meteorological mast, nacelle mounted anemometer on the turbines and estimation based on the standard deviation of power. The results show that the proposed TI estimation method is in the best agreement with the meteorological mast. Therefore, the rotor effective wind speed...... is shown to be applicable for the TI assessment in real-time wind farm calculations under different operational conditions. Furthermore, the TI in the wake is seen to follow the same trend with the estimated wake deficit which enables to quantify the turbulence in terms of the wake loss locally inside...
Kaoga, Dieudonné Kidmo; Bogno, Bachirou; Aillerie, Michel; Raidandi, Danwe; Yamigno, Serge Doka; Hamandjoda, Oumarou; Tibi, Beda
2016-07-01
In this work, 28 years of wind data, measured at 10m above ground level (AGL), from Maroua meteorological station is utilized to assess the potential of wind energy at exposed ridges tops of mountains surrounding the city of Maroua. The aim of this study is to estimate the cost of wind-generated electricity using six types of wind turbines (50 to 2000 kW). The Weibull distribution function is employed to estimate Weibull shape and scale parameters using the energy pattern factor method. The considered wind shear model to extrapolate Weibull parameters and wind profiles is the empirical power law correlation. The results show that hilltops in the range of 150-350m AGL in increments of 50, fall under Class 3 or greater of the international system of wind classification and are deemed suitable to outstanding for wind turbine applications. A performance of the selected wind turbines is examined as well as the costs of wind-generated electricity at the considered hilltops. The results establish that the lowest costs per kWh are obtained using YDF-1500-87 (1500 kW) turbine while the highest costs are delivered by P-25-100 (90 kW). The lowest costs (US) per kWh of electricity generated are found to vary between a minimum of 0.0294 at hilltops 350m AGL and a maximum of 0.0366 at hilltops 150m AGL, with corresponding energy outputs that are 6,125 and 4,932 MWh, respectively. Additionally, the matching capacity factors values are 38.05% at hilltops 150m AGL and 47.26% at hilltops 350m AGL. Furthermore, YDF-1500-87 followed by Enercon E82-2000 (2000 kW) wind turbines provide the lowest cost of wind generated electricity and are recommended for use for large communities. Medium wind turbine P-15-50 (50 kW), despite showing the best coefficients factors (39.29% and 48.85% at hilltops 150 and 350m AGL, in that order), generates electricity at an average higher cost/kWh of US0.0547 and 0.0440 at hilltops 150 and 350m AGL, respectively. P-15-50 is deemed a more advantageous option
Incremental parameter estimation of kinetic metabolic network models
Directory of Open Access Journals (Sweden)
Jia Gengjie
2012-11-01
Full Text Available Abstract Background An efficient and reliable parameter estimation method is essential for the creation of biological models using ordinary differential equation (ODE. Most of the existing estimation methods involve finding the global minimum of data fitting residuals over the entire parameter space simultaneously. Unfortunately, the associated computational requirement often becomes prohibitively high due to the large number of parameters and the lack of complete parameter identifiability (i.e. not all parameters can be uniquely identified. Results In this work, an incremental approach was applied to the parameter estimation of ODE models from concentration time profiles. Particularly, the method was developed to address a commonly encountered circumstance in the modeling of metabolic networks, where the number of metabolic fluxes (reaction rates exceeds that of metabolites (chemical species. Here, the minimization of model residuals was performed over a subset of the parameter space that is associated with the degrees of freedom in the dynamic flux estimation from the concentration time-slopes. The efficacy of this method was demonstrated using two generalized mass action (GMA models, where the method significantly outperformed single-step estimations. In addition, an extension of the estimation method to handle missing data is also presented. Conclusions The proposed incremental estimation method is able to tackle the issue on the lack of complete parameter identifiability and to significantly reduce the computational efforts in estimating model parameters, which will facilitate kinetic modeling of genome-scale cellular metabolism in the future.
Sample Size and Item Parameter Estimation Precision When Utilizing the One-Parameter "Rasch" Model
Custer, Michael
2015-01-01
This study examines the relationship between sample size and item parameter estimation precision when utilizing the one-parameter model. Item parameter estimates are examined relative to "true" values by evaluating the decline in root mean squared deviation (RMSD) and the number of outliers as sample size increases. This occurs across…
Potential of neuro-fuzzy methodology to estimate noise level of wind turbines
Nikolić, Vlastimir; Petković, Dalibor; Por, Lip Yee; Shamshirband, Shahaboddin; Zamani, Mazdak; Ćojbašić, Žarko; Motamedi, Shervin
2016-01-01
Wind turbines noise effect became large problem because of increasing of wind farms numbers since renewable energy becomes the most influential energy sources. However, wind turbine noise generation and propagation is not understandable in all aspects. Mechanical noise of wind turbines can be ignored since aerodynamic noise of wind turbine blades is the main source of the noise generation. Numerical simulations of the noise effects of the wind turbine can be very challenging task. Therefore in this article soft computing method is used to evaluate noise level of wind turbines. The main goal of the study is to estimate wind turbine noise in regard of wind speed at different heights and for different sound frequency. Adaptive neuro-fuzzy inference system (ANFIS) is used to estimate the wind turbine noise levels.
DC Link Current Estimation in Wind-Double Feed Induction Generator Power Conditioning System
Directory of Open Access Journals (Sweden)
MARIAN GAICEANU
2010-12-01
Full Text Available In this paper the implementation of the DC link current estimator in power conditioning system of the variable speed wind turbine is shown. The wind turbine is connected to double feed induction generator (DFIG. The variable electrical energy parameters delivered by DFIG are fitted with the electrical grid parameters through back-to-back power converter. The bidirectional AC-AC power converter covers a wide speed range from subsynchronous to supersynchronous speeds. The modern control of back-to-back power converter involves power balance concept, therefore its load power should be known in any instant. By using the power balance control, the DC link voltage variation at the load changes can be reduced. In this paper the load power is estimated from the dc link, indirectly, through a second order DC link current estimator. The load current estimator is based on the DC link voltage and on the dc link input current of the rotor side converter. This method presents certain advantages instead of using measured method, which requires a low pass filter: no time delay, the feedforward current component has no ripple, no additional hardware, and more fast control response. Through the numerical simulation the performances of the proposed DC link output current estimator scheme are demonstrated.
Control and Estimation of Distributed Parameter Systems
Kappel, F; Kunisch, K
1998-01-01
Consisting of 23 refereed contributions, this volume offers a broad and diverse view of current research in control and estimation of partial differential equations. Topics addressed include, but are not limited to - control and stability of hyperbolic systems related to elasticity, linear and nonlinear; - control and identification of nonlinear parabolic systems; - exact and approximate controllability, and observability; - Pontryagin's maximum principle and dynamic programming in PDE; and - numerics pertinent to optimal and suboptimal control problems. This volume is primarily geared toward control theorists seeking information on the latest developments in their area of expertise. It may also serve as a stimulating reader to any researcher who wants to gain an impression of activities at the forefront of a vigorously expanding area in applied mathematics.
Parameter and Uncertainty Estimation in Groundwater Modelling
DEFF Research Database (Denmark)
Jensen, Jacob Birk
The data basis on which groundwater models are constructed is in general very incomplete, and this leads to uncertainty in model outcome. Groundwater models form the basis for many, often costly decisions and if these are to be made on solid grounds, the uncertainty attached to model results must...... be quantified. This study was motivated by the need to estimate the uncertainty involved in groundwater models.Chapter 2 presents an integrated surface/subsurface unstructured finite difference model that was developed and applied to a synthetic case study.The following two chapters concern calibration...... was applied.Capture zone modelling was conducted on a synthetic stationary 3-dimensional flow problem involving river, surface and groundwater flow. Simulated capture zones were illustrated as likelihood maps and compared with a deterministic capture zones derived from a reference model. The results showed...
FUZZY SUPERNOVA TEMPLATES. II. PARAMETER ESTIMATION
International Nuclear Information System (INIS)
Rodney, Steven A.; Tonry, John L.
2010-01-01
Wide-field surveys will soon be discovering Type Ia supernovae (SNe) at rates of several thousand per year. Spectroscopic follow-up can only scratch the surface for such enormous samples, so these extensive data sets will only be useful to the extent that they can be characterized by the survey photometry alone. In a companion paper we introduced the Supernova Ontology with Fuzzy Templates (SOFT) method for analyzing SNe using direct comparison to template light curves, and demonstrated its application for photometric SN classification. In this work we extend the SOFT method to derive estimates of redshift and luminosity distance for Type Ia SNe, using light curves from the Sloan Digital Sky Survey (SDSS) and Supernova Legacy Survey (SNLS) as a validation set. Redshifts determined by SOFT using light curves alone are consistent with spectroscopic redshifts, showing an rms scatter in the residuals of rms z = 0.051. SOFT can also derive simultaneous redshift and distance estimates, yielding results that are consistent with the currently favored ΛCDM cosmological model. When SOFT is given spectroscopic information for SN classification and redshift priors, the rms scatter in Hubble diagram residuals is 0.18 mag for the SDSS data and 0.28 mag for the SNLS objects. Without access to any spectroscopic information, and even without any redshift priors from host galaxy photometry, SOFT can still measure reliable redshifts and distances, with an increase in the Hubble residuals to 0.37 mag for the combined SDSS and SNLS data set. Using Monte Carlo simulations, we predict that SOFT will be able to improve constraints on time-variable dark energy models by a factor of 2-3 with each new generation of large-scale SN surveys.
Gravity Field Parameter Estimation Using QR Factorization
Klokocnik, J.; Wagner, C. A.; McAdoo, D.; Kostelecky, J.; Bezdek, A.; Novak, P.; Gruber, C.; Marty, J.; Bruinsma, S. L.; Gratton, S.; Balmino, G.; Baboulin, M.
2007-12-01
This study compares the accuracy of the estimated geopotential coefficients when QR factorization is used instead of the classical method applied at our institute, namely the generation of normal equations that are solved by means of Cholesky decomposition. The objective is to evaluate the gain in numerical precision, which is obtained at considerable extra cost in terms of computer resources. Therefore, a significant increase in precision must be realized in order to justify the additional cost. Numerical simulations were done in order to examine the performance of both solution methods. Reference gravity gradients were simulated, using the EIGEN-GL04C gravity field model to degree and order 300, every 3 seconds along a near-circular, polar orbit at 250 km altitude. The simulation spanned a total of 60 days. A polar orbit was selected in this simulation in order to avoid the 'polar gap' problem, which causes inaccurate estimation of the low-order spherical harmonic coefficients. Regularization is required in that case (e.g., the GOCE mission), which is not the subject of the present study. The simulated gravity gradients, to which white noise was added, were then processed with the GINS software package, applying EIGEN-CG03 as the background gravity field model, followed either by the usual normal equation computation or using the QR approach for incremental linear least squares. The accuracy assessment of the gravity field recovery consists in computing the median error degree-variance spectra, accumulated geoid errors, geoid errors due to individual coefficients, and geoid errors calculated on a global grid. The performance, in terms of memory usage, required disk space, and CPU time, of the QR versus the normal equation approach is also evaluated.
Blade Bearing Friction Estimation of Operating Wind Turbines
DEFF Research Database (Denmark)
Perisic, Nevena; Pedersen, Bo Juul; Kirkegaard, Poul Henning
2012-01-01
Blade root bearing on a wind turbine (WTG) enables pitching of blades for power control and rotor braking and is a WTG critical component. As the size of modern WTGs is constantly increasing, this leads to relatively less rigid bearings, more sensitive to deformations, thus WTG operational...... reliability can be increased by continuous monitoring of blade bearing. High blade bearing friction is undesirable, as it may be associated with excessive heating of the surfaces, damage and/or inefficient operation. Thus, continuous observation of bearing friction level is crucial for blade bearing health...... monitoring systems. A novel algorithm for online monitoring of bearing friction level is developed combining physical knowledge about pitch system dynamics with state estimator, i.e. observer theory and signal processing assuming realistic sensor availability. Results show estimation of bearing friction...
Directory of Open Access Journals (Sweden)
Yun-Su Kim
2015-02-01
Full Text Available This paper presents a method to seek the PI controller parameters of a PMSG wind turbine to improve control performance. Since operating conditions vary with the wind speed, therefore the PI controller parameters should be determined as a function of the wind speed. Small-signal modeling of a PMSG WT is implemented to analyze the stability under various operating conditions and with eigenvalues obtained from the small-signal model of the PMSG WT, which are coordinated by adjusting the PI controller parameters. The parameters to be tuned are chosen by investigating participation factors of state variables, which simplifies the problem by reducing the number of parameters to be tuned. The process of adjusting these PI controller parameters is carried out using particle swarm optimization (PSO. To characterize the improvements in the control method due to the PSO method of tuning the PI controller parameters, the PMSG WT is modeled using the MATLAB/SimPowerSystems libraries with the obtained PI controller parameters.
Parameter estimation of an aeroelastic aircraft using neural networks
Indian Academy of Sciences (India)
https://www.ias.ac.in/article/fulltext/sadh/025/02/0181-0191. Keywords. Parameter estimation; modelling; aeroelastic aircraft; neural networks; system identification. Abstract. Application of neural networks to the problem of aerodynamic modelling and parameter estimation for aeroelastic aircraft is addressed. A neural model ...
Genetic parameter estimation of 16-month live weight and ...
African Journals Online (AJOL)
The genetic, phenotypic and environmental parameters for live weight and objectively measured wool traits were estimated for a South African Merino flock. Records of the Tygerhoek Merino resource flock were used to estimate these parameters. The database consisted of records of 4 495 animals, the progeny of 449 sires ...
Genetic parameter estimates for tick resistance in Bonsmara cattle ...
African Journals Online (AJOL)
The objectives of the study were to estimate genetic parameters for tick resistance and to evaluate the effect of the level of tick infestation on the estimates of genetic parameters for South African Bonsmara cattle. Field data of repeated tick count records (n = 11 280) on 1 176 animals were collected between 1993 and 2005 ...
Estimation of the soil strength parameters in Tertiary volcanic regolith
Indian Academy of Sciences (India)
Costly and time consuming testing techniques and the difficulties in providing undisturbed samples for these tests have led researchers to estimate strength parameters of soils with simple index tests. However, the paper focuses on estimation of strength parameters of soils as a function of the index properties. Analytical ...
Across flock genetic parameter estimation for yearling body weight ...
African Journals Online (AJOL)
Accurate genetic parameter estimates are needed upon which to perform multiple-trait across flock breed analyses. Genetic parameters for yearling body weight (BW), clean fleece weight (CFW) and mean fibre diameter (MFD) were estimated using records of 107 389 individuals (the progeny of 1 530 sires and 45 178 ...
Bayesian Parameter Estimation for Heavy-Duty Vehicles
Energy Technology Data Exchange (ETDEWEB)
Miller, Eric; Konan, Arnaud; Duran, Adam
2017-03-28
Accurate vehicle parameters are valuable for design, modeling, and reporting. Estimating vehicle parameters can be a very time-consuming process requiring tightly-controlled experimentation. This work describes a method to estimate vehicle parameters such as mass, coefficient of drag/frontal area, and rolling resistance using data logged during standard vehicle operation. The method uses Monte Carlo to generate parameter sets which is fed to a variant of the road load equation. Modeled road load is then compared to measured load to evaluate the probability of the parameter set. Acceptance of a proposed parameter set is determined using the probability ratio to the current state, so that the chain history will give a distribution of parameter sets. Compared to a single value, a distribution of possible values provides information on the quality of estimates and the range of possible parameter values. The method is demonstrated by estimating dynamometer parameters. Results confirm the method's ability to estimate reasonable parameter sets, and indicates an opportunity to increase the certainty of estimates through careful selection or generation of the test drive cycle.
HF Radar Observations of Current, Wave and Wind Parameters in the South Australian Gulf
Middleditch, A.; Cosoli, S.
2016-12-01
The Australian Coastal Ocean Radar Network (ACORN) has been measuring metocean parameters from an array of HF radar systems since 2007. Current, wave and wind measurements from a WERA phased-array radar system in the South Australian Gulf are evaluated using current meter, wave buoy and weather station data over a 12-month period. The spatial and temporal scales of the radar deployment have been configured for the measurement of surface currents from the first order backscatter spectra. Quality control procedures are applied to the radar currents that relate to the geometric configurations, statistical properties, and diagnostic variables provided by the analysis software. Wave measurements are obtained through an iterative inversion algorithm that provides an estimate of the directional frequency spectrum. The standard static configurations and data sampling strategies are not optimised for waves and so additional signal processing steps need to be implemented in order to provide reliable estimates. These techniques are currently only applied in offline mode but a real-time approach is in development. Improvements in the quality of extracted wave data are found through increased averaging of the raw radar data but the impact of temporal non-stationarity and spatial inhomogeneities in the WERA measurement region needs to be taken into account. Validations of wind direction data from a weather station on Neptune Island show the potential of using HF radar to combat the spread of bushfires in South Australia.
Parameter and State Estimator for State Space Models
Directory of Open Access Journals (Sweden)
Ruifeng Ding
2014-01-01
Full Text Available This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.
Parameter and state estimator for state space models.
Ding, Ruifeng; Zhuang, Linfan
2014-01-01
This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.
Wind-Ramp-Forecast Sensitivity to Closure Parameters in a Boundary-Layer Parametrization Scheme
Jahn, David E.; Takle, Eugene S.; Gallus, William A.
2017-09-01
Wind ramps are relatively large changes in wind speed over a period of a few hours and present a challenge for electric utilities to balance power generation and load. Failures of boundary-layer parametrization schemes to represent physical processes limit the ability of numerical models to forecast wind ramps, especially in a stable boundary layer. Herein, the eight "closure parameters" of a widely used boundary-layer parameterization scheme are subject to sensitivity tests for a set of wind-ramp cases. A marked sensitivity of forecast wind speed to closure-parameter values is observed primarily for three parameters that influence in the closure equations the depth of turbulent mixing, dissipation, and the transfer of kinetic energy from the mean to the turbulent flow. Reducing the value of these parameters independently by 25% or by 50% reduces the overall average in forecast wind-speed errors by at least 24% for the first two parameters and increases average forecast error by at least 63% for the third parameter. Doubling any of these three parameters increases average forecast error by at least 67%. Such forecast sensitivity to closure parameter values provides motivation to explore alternative values in the context of a stable boundary layer.
METHODS FOR ESTIMATING THE PARAMETERS OF THE POWER FUNCTION DISTRIBUTION.
Directory of Open Access Journals (Sweden)
azam zaka
2013-10-01
Full Text Available Normal 0 false false false EN-US X-NONE X-NONE In this paper, we present some methods for estimating the parameters of the two parameter Power function distribution. We used the least squares method (LSM, relative least squares method (RELS and ridge regression method (RR. Sampling behavior of the estimates is indicated by a Monte Carlo simulation. The objective of identifying the best estimator amongst them we use the Total Deviation (T.D and Mean Square Error (M.S.E as performance index. We determined the best method for estimation using different values for the parameters and different sample sizes.
Kozu, Toshiaki; Nakamura, Kenji; Meneghini, Robert
1991-01-01
A method to estimate raindrop size distribution (DSD) parameters from a combined Zm profile and path-integrated attenuation is shown, and a test result of the method using the data from an aircraft experiment is presented. The 'semi' dual-parameter (SDP) measurement is employed to estimate DSD parameters using the data obtained from an aircraft experiment conducted by Communications Research Laboratory, Tokyo, in conjunction with NASA. The validity of estimated DSD parameters is examined using measured Ka-band radar reflectivities. The estimated path-averaged N(0) is consistent with the Ka/X Ze ratio, and the use of estimated DSD shows excellent agreement between the rain rates estimated from the X-band and K-band Zes. The feasibility of estimating DSD parameters from space is confirmed.
Ma, Ke; Liserre, Marco; Blaabjerg, Frede
2013-01-01
As a key component in the wind turbine system, power electronic converter and its power semiconductors suffer from adverse power loadings related to environment, and are proven to have certain failure rates. Therefore, correct lifetime estimation of wind power converter is crucial for the reliability improvement and also for cost reduction of wind power technology. Unfortunately, the existing lifetime estimation methods for the power electronic converter are not yet suitable in the wind power...
Parameter estimation and prediction of nonlinear biological systems: some examples
Doeswijk, T.G.; Keesman, K.J.
2006-01-01
Rearranging and reparameterizing a discrete-time nonlinear model with polynomial quotient structure in input, output and parameters (xk = f(Z, p)) leads to a model linear in its (new) parameters. As a result, the parameter estimation problem becomes a so-called errors-in-variables problem for which
Revisiting Boltzmann learning: parameter estimation in Markov random fields
DEFF Research Database (Denmark)
Hansen, Lars Kai; Andersen, Lars Nonboe; Kjems, Ulrik
1996-01-01
and generalization in the context of Boltzmann machines. We provide an illustrative example concerning parameter estimation in an inhomogeneous Markov field. The regularized adaptation produces a parameter set that closely resembles the “teacher” parameters, hence, will produce segmentations that closely reproduce...
A Novel Nonlinear Parameter Estimation Method of Soft Tissues
Directory of Open Access Journals (Sweden)
Qianqian Tong
2017-12-01
Full Text Available The elastic parameters of soft tissues are important for medical diagnosis and virtual surgery simulation. In this study, we propose a novel nonlinear parameter estimation method for soft tissues. Firstly, an in-house data acquisition platform was used to obtain external forces and their corresponding deformation values. To provide highly precise data for estimating nonlinear parameters, the measured forces were corrected using the constructed weighted combination forecasting model based on a support vector machine (WCFM_SVM. Secondly, a tetrahedral finite element parameter estimation model was established to describe the physical characteristics of soft tissues, using the substitution parameters of Young’s modulus and Poisson’s ratio to avoid solving complicated nonlinear problems. To improve the robustness of our model and avoid poor local minima, the initial parameters solved by a linear finite element model were introduced into the parameter estimation model. Finally, a self-adapting Levenberg–Marquardt (LM algorithm was presented, which is capable of adaptively adjusting iterative parameters to solve the established parameter estimation model. The maximum absolute error of our WCFM_SVM model was less than 0.03 Newton, resulting in more accurate forces in comparison with other correction models tested. The maximum absolute error between the calculated and measured nodal displacements was less than 1.5 mm, demonstrating that our nonlinear parameters are precise.
Robust Parameter and Signal Estimation in Induction Motors
DEFF Research Database (Denmark)
Børsting, H.
This thesis deals with theories and methods for robust parameter and signal estimation in induction motors. The project originates in industrial interests concerning sensor-less control of electrical drives. During the work, some general problems concerning estimation of signals and parameters...... in nonlinear systems, have been exposed. The main objectives of this project are: - analysis and application of theories and methods for robust estimation of parameters in a model structure, obtained from knowledge of the physics of the induction motor. - analysis and application of theories and methods...... for robust estimation of the rotor speed and driving torque of the induction motor based only on measurements of stator voltages and currents. Only contimuous-time models have been used, which means that physical related signals and parameters are estimated directly and not indirectly by some discrete...
Dependence of Weibull distribution parameters on the CNR threshold i wind lidar data
DEFF Research Database (Denmark)
Gryning, Sven-Erik; Batchvarova, Ekaterina; Floors, Rogier Ralph
2015-01-01
The increase in height and area swept by the blades of wind turbines that harvest energy from the air flow in the lower atmosphere have raised a need for better understanding of the structure of the profiles of the wind, its gusts and the monthly to annual long-term, statistical distribution...... in the boundary layer. Observations from tall towers in combination with observations from a lidar of wind speed up to 600 m are used to study the long-term variability of the wind profile over sub-urban, rural, coastal and marine areas. The variability is expressed in terms of the shape parameter in the Weibull...... distribution. When the lidar Carrier to Noise Ratio (CNR) is lower than a threshold value the observations are often not used as the uncertainty on the wind speed of the lidar measurements increases. This analysis shows that the mean wind speed is a function of the applied CNR threshold, which indicates...
Modal Parameter Identification of New Design of Vertical Axis Wind Turbine
DEFF Research Database (Denmark)
Chougule, Prasad; Nielsen, Søren R.K.
2013-01-01
Vertical axis wind turbines have lower power efficiency than the horizontal axis wind turbines. However vertical axis wind turbines are proven to be economical and noise free on smaller scale. A new design of three bladed vertical axis wind turbine by using two airfoils in construction of each...... blade has been proposed to improve power efficiency. The purpose of two airfoils in blade design of vertical axis wind turbine is to create high lift which in turns gives higher power output. In such case the structural parameter identification is important to understand the system behavior due to its...... Abaqus cae software. The study is limited to evaluate lowest fundamental modal frequencies and mode shapes of proposed wind turbine....
Parameter estimation for chaotic systems using improved bird swarm algorithm
Xu, Chuangbiao; Yang, Renhuan
2017-12-01
Parameter estimation of chaotic systems is an important problem in nonlinear science and has aroused increasing interest of many research fields, which can be basically reduced to a multidimensional optimization problem. In this paper, an improved boundary bird swarm algorithm is used to estimate the parameters of chaotic systems. This algorithm can combine the good global convergence and robustness of the bird swarm algorithm and the exploitation capability of improved boundary learning strategy. Experiments are conducted on the Lorenz system and the coupling motor system. Numerical simulation results reveal the effectiveness and with desirable performance of IBBSA for parameter estimation of chaotic systems.
A simulation of water pollution model parameter estimation
Kibler, J. F.
1976-01-01
A parameter estimation procedure for a water pollution transport model is elaborated. A two-dimensional instantaneous-release shear-diffusion model serves as representative of a simple transport process. Pollution concentration levels are arrived at via modeling of a remote-sensing system. The remote-sensed data are simulated by adding Gaussian noise to the concentration level values generated via the transport model. Model parameters are estimated from the simulated data using a least-squares batch processor. Resolution, sensor array size, and number and location of sensor readings can be found from the accuracies of the parameter estimates.
DEFF Research Database (Denmark)
Pedersen, Leif Toudal; Tonboe, Rasmus T.; Høyer, Jacob
.e. horizontal and vertical polarization at channels between 6 and 89 GHz as a function of a limited set of physical parameters, i.e. atmospheric water vapor, cloud liquid water, wind speed, surface and air temperature. This type of model is ideal for optimal estimation applications because of its limited set...... channels as well as the combination of data from multiple sources such as microwave radiometry, scatterometry and numerical weather prediction. Optimal estimation is data assimilation without a numerical model for retrieving physical parameters from remote sensing using a multitude of available information....... The methodology is observation driven and model innovation is limited to the translation between observation space and physical parameter space Over open water we use a semi-empirical radiative transfer model developed by Meissner & Wentz that estimates the multispectral AMSR brightness temperatures, i...
Energy Technology Data Exchange (ETDEWEB)
Nagai, H. [Nihon University, Tokyo (Japan); Kojima, T. [Yamagata Wind Energy Institute, Yamagata (Japan)
1996-10-27
For two 400kW wind turbines erected in Jan. 1996 of Yamagata Wind Energy Institute, their estimated power output was compared with actual output for 7 months. AMeDAS data in 1985-94 were totaled every month to use as basic data. The altitude and surface roughness model necessary for WAsP analysis recommended by NEDO`s wind condition close inspection manual were prepared using 1/25,000 maps and aerial photographs. The obstacle model for estimating wind conditions at height of the wind turbine was prepared using the data obtained by field survey. Mean wind velocity and latent energy were determined by statistical analysis of wind velocity occurrence relative frequencies and Weibull distribution parameters. The power output of 717,700kWh was obtained for 7 months, which is equivalent to 88.5% of the estimated output of 810,730kWh for the same period. It was clarified from obtained characteristic wind conditions at the site that the wind power generation is promising at the site not only in winter but also in summer. Although the test period was too short, this method was effective as analytical method of output estimation in the planning stage of wind turbines. 3 refs., 8 figs., 4 tabs.
A high resolution global wind atlas - improving estimation of world wind resources
DEFF Research Database (Denmark)
Badger, Jake; Ejsing Jørgensen, Hans
2011-01-01
data and the tools necessary are present, so the time is right to link the parts together to create a much needed dataset. Geospatial information systems (GIS) will be one of the significant applications of the Global Wind Atlas datasets. As location of wind resource, and its relationships...... resources. These aspects will also be addressed by the Global Wind Atlas. The Global Wind Atlas, through a transparent methodology, will provide a unified, high resolution, and public domain dataset of wind energy resources for the whole world. The wind atlas data will be the most appropriate wind resource...
Estimation of Parameters in Latent Class Models with Constraints on the Parameters.
Paulson, James A.
This paper reviews the application of the EM Algorithm to marginal maximum likelihood estimation of parameters in the latent class model and extends the algorithm to the case where there are monotone homogeneity constraints on the item parameters. It is shown that the EM algorithm can be used to obtain marginal maximum likelihood estimates of the…
Aryan, Homayon; Yearby, Keith; Balikhin, Michael; Agapitov, Oleksiy; Krasnoselskikh, Vladimir; Boynton, Richard
2014-08-01
Energetic electrons within the Earth's radiation belts represent a serious hazard to geostationary satellites. The interactions of electrons with chorus waves play an important role in both the acceleration and loss of radiation belt electrons. The common approach is to present model wave distributions in the inner magnetosphere under different values of geomagnetic activity as expressed by the geomagnetic indices. However, it has been shown that only around 50% of geomagnetic storms increase flux of relativistic electrons at geostationary orbit while 20% causes a decrease and the remaining 30% has relatively no effect. This emphasizes the importance of including solar wind parameters such as bulk velocity (V), density (n), flow pressure (P), and the vertical interplanetary magnetic field component (Bz) that are known to be predominately effective in the control of high energy fluxes at the geostationary orbit. Therefore, in the present study the set of parameters of the wave distributions is expanded to include the solar wind parameters in addition to the geomagnetic activity. The present study examines almost 4 years (1 January 2004 to 29 September 2007) of Spatio-Temporal Analysis of Field Fluctuation data from Double Star TC1 combined with geomagnetic indices and solar wind parameters from OMNI database in order to present a comprehensive model of wave magnetic field intensities for the chorus waves as a function of magnetic local time, L shell (L), magnetic latitude (λm), geomagnetic activity, and solar wind parameters. Generally, the results indicate that the intensity of chorus emission is not only dependent upon geomagnetic activity but also dependent on solar wind parameters with velocity and southward interplanetary magnetic field Bs (Bz < 0), evidently the most influential solar wind parameters. The largest peak chorus intensities in the order of 50 pT are observed during active conditions, high solar wind velocities, low solar wind densities, high
Full load estimation of an offshore wind turbine based on SCADA and accelerometer data
Noppe, N.; Iliopoulos, A.; Weijtjens, W.; Devriendt, C.
2016-09-01
As offshore wind farms (OWFs) grow older, the optimal use of the actual fatigue lifetime of an offshore wind turbine (OWT) and predominantly its foundation will get more important. In case of OWTs, both quasi-static wind/thrust loads and dynamic loads, as induced by turbulence, waves and the turbine's dynamics, contribute to its fatigue life progression. To estimate the remaining useful life of an OWT, the stresses acting on the fatigue critical locations within the structure should be monitored continuously. Unfortunately, in case of the most common monopile foundations these locations are often situated below sea-level and near the mud line and thus difficult or even impossible to access for existing OWTs. Actual strain measurements taken at accessible locations above the sea level show a correlation between thrust load and several SCADA parameters. Therefore a model is created to estimate the thrust load using SCADA data and strain measurements. Afterwards the thrust load acting on the OWT is estimated using the created model and SCADA data only. From this model the quasi static loads on the foundation can be estimated over the lifetime of the OWT. To estimate the contribution of the dynamic loads a modal decomposition and expansion based virtual sensing technique is applied. This method only uses acceleration measurements recorded at accessible locations on the tower. Superimposing both contributions leads to a so-called multi-band virtual sensing. The result is a method that allows to estimate the strain history at any location on the foundation and thus the full load, being a combination of both quasi-static and dynamic loads, acting on the entire structure. This approach is validated using data from an operating Belgian OWF. An initial good match between measured and predicted strains for a short period of time proofs the concept.
Response-Based Estimation of Sea State Parameters
DEFF Research Database (Denmark)
Nielsen, Ulrik Dam
2007-01-01
Reliable estimation of the on-site sea state parameters is essential to decision support systems for safe navigation of ships. The sea state parameters can be estimated by Bayesian Modelling which uses complex-valued frequency response functions (FRF) to estimate the wave spectrum on the basis...... of measured ship responses. It is therefore interesting to investigate how the filtering aspect, introduced by FRF, affects the final outcome of the estimation procedures. The paper contains a study based on numerical generated time series, and the study shows that filtering has an influence...
Kinetic parameter estimation from attenuated SPECT projection measurements
International Nuclear Information System (INIS)
Reutter, B.W.; Gullberg, G.T.
1998-01-01
Conventional analysis of dynamically acquired nuclear medicine data involves fitting kinetic models to time-activity curves generated from regions of interest defined on a temporal sequence of reconstructed images. However, images reconstructed from the inconsistent projections of a time-varying distribution of radiopharmaceutical acquired by a rotating SPECT system can contain artifacts that lead to biases in the estimated kinetic parameters. To overcome this problem the authors investigated the estimation of kinetic parameters directly from projection data by modeling the data acquisition process. To accomplish this it was necessary to parametrize the spatial and temporal distribution of the radiopharmaceutical within the SPECT field of view. In a simulated transverse slice, kinetic parameters were estimated for simple one compartment models for three myocardial regions of interest, as well as for the liver. Myocardial uptake and washout parameters estimated by conventional analysis of noiseless simulated data had biases ranging between 1--63%. Parameters estimated directly from the noiseless projection data were unbiased as expected, since the model used for fitting was faithful to the simulation. Predicted uncertainties (standard deviations) of the parameters obtained for 500,000 detected events ranged between 2--31% for the myocardial uptake parameters and 2--23% for the myocardial washout parameters
Models for estimating photosynthesis parameters from in situ production profiles
Kovač, Žarko; Platt, Trevor; Sathyendranath, Shubha; Antunović, Suzana
2017-12-01
The rate of carbon assimilation in phytoplankton primary production models is mathematically prescribed with photosynthesis irradiance functions, which convert a light flux (energy) into a material flux (carbon). Information on this rate is contained in photosynthesis parameters: the initial slope and the assimilation number. The exactness of parameter values is crucial for precise calculation of primary production. Here we use a model of the daily production profile based on a suite of photosynthesis irradiance functions and extract photosynthesis parameters from in situ measured daily production profiles at the Hawaii Ocean Time-series station Aloha. For each function we recover parameter values, establish parameter distributions and quantify model skill. We observe that the choice of the photosynthesis irradiance function to estimate the photosynthesis parameters affects the magnitudes of parameter values as recovered from in situ profiles. We also tackle the problem of parameter exchange amongst the models and the effect it has on model performance. All models displayed little or no bias prior to parameter exchange, but significant bias following parameter exchange. The best model performance resulted from using optimal parameter values. Model formulation was extended further by accounting for spectral effects and deriving a spectral analytical solution for the daily production profile. The daily production profile was also formulated with time dependent growing biomass governed by a growth equation. The work on parameter recovery was further extended by exploring how to extract photosynthesis parameters from information on watercolumn production. It was demonstrated how to estimate parameter values based on a linearization of the full analytical solution for normalized watercolumn production and from the solution itself, without linearization. The paper complements previous works on photosynthesis irradiance models by analysing the skill and consistency of
A rotor-aerodynamics-based wind estimation method using a quadrotor
Song, Yao; Luo, Bing; Meng, Qing-Hao
2018-02-01
Attempts to estimate horizontal wind by the quadrotor are reviewed. Wind estimations are realized by utilizing the quadrotor’s thrust change, which is caused by the wind’s effect on the rotors. The basis of the wind estimation method is the aerodynamic formula for the rotor’s thrust, which is verified and calibrated by experiments. A hardware-in-the-loop simulation (HILS) system was built as a testbed; its dynamic model and control structure are demonstrated. Verification experiments on the HILS system proved that the wind estimation method was effective.
Optimum Parameters of a Tuned Liquid Column Damper in a Wind Turbine Subject to Stochastic Load
Alkmim, M. H.; de Morais, M. V. G.; Fabro, A. T.
2017-12-01
Parameter optimization for tuned liquid column dampers (TLCD), a class of passive structural control, have been previously proposed in the literature for reducing vibration in wind turbines, and several other applications. However, most of the available work consider the wind excitation as either a deterministic harmonic load or random load with white noise spectra. In this paper, a global direct search optimization algorithm to reduce vibration of a tuned liquid column damper (TLCD), a class of passive structural control device, is presented. The objective is to find optimized parameters for the TLCD under stochastic load from different wind power spectral density. A verification is made considering the analytical solution of undamped primary system under white noise excitation by comparing with result from the literature. Finally, it is shown that different wind profiles can significantly affect the optimum TLCD parameters.
The use of energy pattern factor (EPF) in estimating wind power ...
African Journals Online (AJOL)
The Energy Pattern Factor (EPF) method is a less computational method of estimating the available wind power density of an area and wind speed variation account for the energy power density throughout a given period. Using the Average daily wind speed data for an 11 year period (2004-2014) obtained from the ...
the use of energy pattern factor (epf) in estimating wind power density
African Journals Online (AJOL)
Dogara M. D et. al
Factor of Kaduna was estimated to be 1.03 and from the energy pattern factor, the average annual available wind power density was calculated to be 222.13 W/m2. This calculated wind power density falls within the stipulated values under wind power class 4 of the National Renewable Energy Laboratory (NREL) of the US.
Parameter Estimation for the Thurstone Case III Model.
Mackay, David B.; Chaiy, Seoil
1982-01-01
The ability of three estimation criteria to recover parameters of the Thurstone Case V and Case III models from comparative judgment data was investigated via Monte Carlo techniques. Significant differences in recovery are shown to exist. (Author/JKS)
Dynamic Mode Decomposition based on Kalman Filter for Parameter Estimation
Shibata, Hisaichi; Nonomura, Taku; Takaki, Ryoji
2017-11-01
With the development of computational fluid dynamics, large-scale data can now be obtained. In order to model physical phenomena from such data, it is required to extract features of flow field. Dynamic mode decomposition (DMD) is a method which meets the request. DMD can compute dominant eigenmodes of flow field by approximating system matrix. From this point of view, DMD can be considered as parameter estimation of system matrix. To estimate such parameters, we propose a novel method based on Kalman filter. Our numerical experiments indicated that the proposed method can estimate the parameters more accurately if it is compared with standard DMD methods. With this method, it is also possible to improve the parameter estimation accuracy if characteristics of noise acting on the system is given.
On-Line Estimation of Allan Variance Parameters
National Research Council Canada - National Science Library
Ford, J
1999-01-01
... (Inertial Measurement Unit) gyros and accelerometers. The on-line method proposes a state space model and proposes parameter estimators for quantities previously measured from off-line data techniques such as the Allan variance graph...
Neural networks for estimation of ocean wave parameters
Digital Repository Service at National Institute of Oceanography (India)
Mandal, S.; Rao, S.; Raju, D.H.
as measured ocean wave spectra off Mormugao, west coast of India. The correlations of neural network and Scott spectra are also compared. Once the network is trained, the ocean wave parameters can be estimated for unknown measured spectra, whereas significant...
A distributed approach for parameters estimation in System Biology models
International Nuclear Information System (INIS)
Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.
2009-01-01
Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.
Estimation of the porosity of wind breaks by using GIS-based ortho-image analysis
Mohammadian Behbahani, Ali; Hikel, Harald; Fister, Wolfgang; Heckrath, Goswin; Kuhn, Nikolaus J.
2013-04-01
The optimal design of windbreaks is very important to reduce wind erosion on farmlands and to combat soil degradation. Main parameters that must be considered when designing windbreaks are: height, width, orientation, porosity (density), distance between barrier rows, and length. There are two types of windbreaks, living (natural) and non-living (artificial). For tree shelterbelts (living windbreak) some of these parameters are related to inherent characteristics of the plants. For example, the height of a windbreak depends on the type of the plant, its growing conditions and the age of the plant. Porosity of windbreaks is considered to be one of the most important factors that controls wind erosion. It is expressed as the ratio between pore space and the space occupied by tree stems, branches, twigs and leaves. For the assessment of porosity it is necessary to convert the three-dimensional plant structure to a two-dimensional model of its shape or plant silhouette, because a direct measurement in the field is very inefficient, time consuming, and therefore impractical. To solve this issue, different approaches have been introduced to estimate the porosity of wind breaks, e.g. optical or aerodynamic porosity. In this study, the porosity of wind break networks was assessed for agricultural land in north Jutland, Denmark. The objective of this study was to develop a GIS-based Ortho-Image Analysis (OIA) method to estimate the porosity of windbreaks. The images of the windbreaks have three visible (RGB) bands and were taken in autumn 2012. The pixel size of 0.5 m is sufficient to visually distinguish the tree rows from their surrounding background. The identification of trees was done using grayscale images, where the dark trees strongly contrast to the bright sky in the background. The preliminary results indicate that the GIS based Ortho-Image analysis can be used as a quick, accurate, and reliable method to estimate the porosity of wind break networks. It can
Kalman filter data assimilation: targeting observations and parameter estimation.
Bellsky, Thomas; Kostelich, Eric J; Mahalov, Alex
2014-06-01
This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly located observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.
Kalman filter estimation of RLC parameters for UMP transmission line
Directory of Open Access Journals (Sweden)
Mohd Amin Siti Nur Aishah
2018-01-01
Full Text Available This paper present the development of Kalman filter that allows evaluation in the estimation of resistance (R, inductance (L, and capacitance (C values for Universiti Malaysia Pahang (UMP short transmission line. To overcome the weaknesses of existing system such as power losses in the transmission line, Kalman Filter can be a better solution to estimate the parameters. The aim of this paper is to estimate RLC values by using Kalman filter that in the end can increase the system efficiency in UMP. In this research, matlab simulink model is developed to analyse the UMP short transmission line by considering different noise conditions to reprint certain unknown parameters which are difficult to predict. The data is then used for comparison purposes between calculated and estimated values. The results have illustrated that the Kalman Filter estimate accurately the RLC parameters with less error. The comparison of accuracy between Kalman Filter and Least Square method is also presented to evaluate their performances.
Accelerated maximum likelihood parameter estimation for stochastic biochemical systems
Directory of Open Access Journals (Sweden)
Daigle Bernie J
2012-05-01
Full Text Available Abstract Background A prerequisite for the mechanistic simulation of a biochemical system is detailed knowledge of its kinetic parameters. Despite recent experimental advances, the estimation of unknown parameter values from observed data is still a bottleneck for obtaining accurate simulation results. Many methods exist for parameter estimation in deterministic biochemical systems; methods for discrete stochastic systems are less well developed. Given the probabilistic nature of stochastic biochemical models, a natural approach is to choose parameter values that maximize the probability of the observed data with respect to the unknown parameters, a.k.a. the maximum likelihood parameter estimates (MLEs. MLE computation for all but the simplest models requires the simulation of many system trajectories that are consistent with experimental data. For models with unknown parameters, this presents a computational challenge, as the generation of consistent trajectories can be an extremely rare occurrence. Results We have developed Monte Carlo Expectation-Maximization with Modified Cross-Entropy Method (MCEM2: an accelerated method for calculating MLEs that combines advances in rare event simulation with a computationally efficient version of the Monte Carlo expectation-maximization (MCEM algorithm. Our method requires no prior knowledge regarding parameter values, and it automatically provides a multivariate parameter uncertainty estimate. We applied the method to five stochastic systems of increasing complexity, progressing from an analytically tractable pure-birth model to a computationally demanding model of yeast-polarization. Our results demonstrate that MCEM2 substantially accelerates MLE computation on all tested models when compared to a stand-alone version of MCEM. Additionally, we show how our method identifies parameter values for certain classes of models more accurately than two recently proposed computationally efficient methods
Estimation of Parameters of the Beta-Extreme Value Distribution
Directory of Open Access Journals (Sweden)
Zafar Iqbal
2008-09-01
Full Text Available In this research paper The Beta Extreme Value Type (III distribution which is developed by Zafar and Aleem (2007 is considered and parameters are estimated by using moments of the Beta-Extreme Value (Type III Distribution when the parameters ‘m’ & ‘n’ are real and moments of the Beta-Extreme Value (Type III Distribution when the parameters ‘m��� & ‘n’ are integers and then a Comparison between rth moments about origin when parameters are ‘m’ & ‘n’ are real and when parameters are ‘m’ & ‘n’ are integers. At the end second method, method of Maximum Likelihood is used to estimate the unknown parameters of the Beta Extreme Value Type (III distribution.
Pollen parameters estimates of genetic variability among newly ...
African Journals Online (AJOL)
Estimates of some pollen parameters where used to assess the genetic diversity among some newly selected Nigerian Roselle (Hibiscus sabdariffa L.). Standard procedures were used to determine the pollen parameters such as: percentage pollen fertility, percentage pollen sterility, pollen diameters as well as anther ...
Estimation of riverbank soil erodibility parameters using genetic ...
Indian Academy of Sciences (India)
Tapas Karmaker
2017-11-07
Nov 7, 2017 ... Abstract. Determination of the erodibility parameters, such as critical shear stress and erodibility coefficient, are necessary before estimating the annual bank erosion (or bank retreat) at river reaches. However, in many cases, the river site is inaccessible making it difficult to assess the soil parameters either ...
The problem of the second wind turbine – a note on a common but flawed wind power estimation method
Directory of Open Access Journals (Sweden)
A. Kleidon
2012-06-01
Full Text Available Several recent wind power estimates suggest that this renewable energy resource can meet all of the current and future global energy demand with little impact on the atmosphere. These estimates are calculated using observed wind speeds in combination with specifications of wind turbine size and density to quantify the extractable wind power. However, this approach neglects the effects of momentum extraction by the turbines on the atmospheric flow that would have effects outside the turbine wake. Here we show with a simple momentum balance model of the atmospheric boundary layer that this common methodology to derive wind power potentials requires unrealistically high increases in the generation of kinetic energy by the atmosphere. This increase by an order of magnitude is needed to ensure momentum conservation in the atmospheric boundary layer. In the context of this simple model, we then compare the effect of three different assumptions regarding the boundary conditions at the top of the boundary layer, with prescribed hub height velocity, momentum transport, or kinetic energy transfer into the boundary layer. We then use simulations with an atmospheric general circulation model that explicitly simulate generation of kinetic energy with momentum conservation. These simulations show that the assumption of prescribed momentum import into the atmospheric boundary layer yields the most realistic behavior of the simple model, while the assumption of prescribed hub height velocity can clearly be disregarded. We also show that the assumptions yield similar estimates for extracted wind power when less than 10% of the kinetic energy flux in the boundary layer is extracted by the turbines. We conclude that the common method significantly overestimates wind power potentials by an order of magnitude in the limit of high wind power extraction. Ultimately, environmental constraints set the upper limit on wind power potential at larger scales rather than
On the Nature of SEM Estimates of ARMA Parameters.
Hamaker, Ellen L.; Dolan, Conor V.; Molenaar, Peter C. M.
2002-01-01
Reexamined the nature of structural equation modeling (SEM) estimates of autoregressive moving average (ARMA) models, replicated the simulation experiments of P. Molenaar, and examined the behavior of the log-likelihood ratio test. Simulation studies indicate that estimates of ARMA parameters observed with SEM software are identical to those…
On robust parameter estimation in brain–computer interfacing
Samek, Wojciech; Nakajima, Shinichi; Kawanabe, Motoaki; Müller, Klaus-Robert
2017-12-01
Objective. The reliable estimation of parameters such as mean or covariance matrix from noisy and high-dimensional observations is a prerequisite for successful application of signal processing and machine learning algorithms in brain–computer interfacing (BCI). This challenging task becomes significantly more difficult if the data set contains outliers, e.g. due to subject movements, eye blinks or loose electrodes, as they may heavily bias the estimation and the subsequent statistical analysis. Although various robust estimators have been developed to tackle the outlier problem, they ignore important structural information in the data and thus may not be optimal. Typical structural elements in BCI data are the trials consisting of a few hundred EEG samples and indicating the start and end of a task. Approach. This work discusses the parameter estimation problem in BCI and introduces a novel hierarchical view on robustness which naturally comprises different types of outlierness occurring in structured data. Furthermore, the class of minimum divergence estimators is reviewed and a robust mean and covariance estimator for structured data is derived and evaluated with simulations and on a benchmark data set. Main results. The results show that state-of-the-art BCI algorithms benefit from robustly estimated parameters. Significance. Since parameter estimation is an integral part of various machine learning algorithms, the presented techniques are applicable to many problems beyond BCI.
Parameter Estimation for a Computable General Equilibrium Model
DEFF Research Database (Denmark)
Arndt, Channing; Robinson, Sherman; Tarp, Finn
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of nonlinear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...
Parameter Estimation for a Computable General Equilibrium Model
DEFF Research Database (Denmark)
Arndt, Channing; Robinson, Sherman; Tarp, Finn
2002-01-01
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of non-linear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...
Estimates of lactation curve parameters for Bonsmara and Nguni ...
African Journals Online (AJOL)
Despite the importance of milk production in beef cattle, little research has been done to evaluate the milk production potential of South African indigenous beef cattle. The objective of this study was to estimate average lactation curve parameters for the South African Bonsmara and Nguni cattle. Milk yield was estimated ...
Distribution Line Parameter Estimation Under Consideration of Measurement Tolerances
DEFF Research Database (Denmark)
Prostejovsky, Alexander; Gehrke, Oliver; Kosek, Anna Magdalena
2016-01-01
State estimation and control approaches in electric distribution grids rely on precise electric models that may be inaccurate. This work presents a novel method of estimating distribution line parameters using only root mean square voltage and power measurements under consideration of measurement...
Global parameter estimation methods for stochastic biochemical systems
Directory of Open Access Journals (Sweden)
Poovathingal Suresh
2010-08-01
Full Text Available Abstract Background The importance of stochasticity in cellular processes having low number of molecules has resulted in the development of stochastic models such as chemical master equation. As in other modelling frameworks, the accompanying rate constants are important for the end-applications like analyzing system properties (e.g. robustness or predicting the effects of genetic perturbations. Prior knowledge of kinetic constants is usually limited and the model identification routine typically includes parameter estimation from experimental data. Although the subject of parameter estimation is well-established for deterministic models, it is not yet routine for the chemical master equation. In addition, recent advances in measurement technology have made the quantification of genetic substrates possible to single molecular levels. Thus, the purpose of this work is to develop practical and effective methods for estimating kinetic model parameters in the chemical master equation and other stochastic models from single cell and cell population experimental data. Results Three parameter estimation methods are proposed based on the maximum likelihood and density function distance, including probability and cumulative density functions. Since stochastic models such as chemical master equations are typically solved using a Monte Carlo approach in which only a finite number of Monte Carlo realizations are computationally practical, specific considerations are given to account for the effect of finite sampling in the histogram binning of the state density functions. Applications to three practical case studies showed that while maximum likelihood method can effectively handle low replicate measurements, the density function distance methods, particularly the cumulative density function distance estimation, are more robust in estimating the parameters with consistently higher accuracy, even for systems showing multimodality. Conclusions The parameter
A Note On the Estimation of the Poisson Parameter
Directory of Open Access Journals (Sweden)
S. S. Chitgopekar
1985-01-01
distribution when there are errors in observing the zeros and ones and obtains both the maximum likelihood and moments estimates of the Poisson mean and the error probabilities. It is interesting to note that either method fails to give unique estimates of these parameters unless the error probabilities are functionally related. However, it is equally interesting to observe that the estimate of the Poisson mean does not depend on the functional relationship between the error probabilities.
Power Curve Estimation With Multivariate Environmental Factors for Inland and Offshore Wind Farms
Lee, Giwhyun
2015-04-22
In the wind industry, a power curve refers to the functional relationship between the power output generated by a wind turbine and the wind speed at the time of power generation. Power curves are used in practice for a number of important tasks including predicting wind power production and assessing a turbine’s energy production efficiency. Nevertheless, actual wind power data indicate that the power output is affected by more than just wind speed. Several other environmental factors, such as wind direction, air density, humidity, turbulence intensity, and wind shears, have potential impact. Yet, in industry practice, as well as in the literature, current power curve models primarily consider wind speed and, sometimes, wind speed and direction. We propose an additive multivariate kernel method that can include the aforementioned environmental factors as a new power curve model. Our model provides, conditional on a given environmental condition, both the point estimation and density estimation of power output. It is able to capture the nonlinear relationships between environmental factors and the wind power output, as well as the high-order interaction effects among some of the environmental factors. Using operational data associated with four turbines in an inland wind farm and two turbines in an offshore wind farm, we demonstrate the improvement achieved by our kernel method.
Parameter Estimation of Damped Compound Pendulum Using Bat Algorithm
Directory of Open Access Journals (Sweden)
Saad Mohd Sazli
2016-01-01
Full Text Available In this study, the parameter identification of the damped compound pendulum system is proposed using one of the most promising nature inspired algorithms which is Bat Algorithm (BA. The procedure used to achieve the parameter identification of the experimental system consists of input-output data collection, ARX model order selection and parameter estimation using bat algorithm (BA method. PRBS signal is used as an input signal to regulate the motor speed. Whereas, the output signal is taken from position sensor. Both, input and output data is used to estimate the parameter of the autoregressive with exogenous input (ARX model. The performance of the model is validated using mean squares error (MSE between the actual and predicted output responses of the models. Finally, comparative study is conducted between BA and the conventional estimation method (i.e. Least Square. Based on the results obtained, MSE produce from Bat Algorithm (BA is outperformed the Least Square (LS method.
Iterative methods for distributed parameter estimation in parabolic PDE
Energy Technology Data Exchange (ETDEWEB)
Vogel, C.R. [Montana State Univ., Bozeman, MT (United States); Wade, J.G. [Bowling Green State Univ., OH (United States)
1994-12-31
The goal of the work presented is the development of effective iterative techniques for large-scale inverse or parameter estimation problems. In this extended abstract, a detailed description of the mathematical framework in which the authors view these problem is presented, followed by an outline of the ideas and algorithms developed. Distributed parameter estimation problems often arise in mathematical modeling with partial differential equations. They can be viewed as inverse problems; the `forward problem` is that of using the fully specified model to predict the behavior of the system. The inverse or parameter estimation problem is: given the form of the model and some observed data from the system being modeled, determine the unknown parameters of the model. These problems are of great practical and mathematical interest, and the development of efficient computational algorithms is an active area of study.
A software for parameter estimation in dynamic models
Directory of Open Access Journals (Sweden)
M. Yuceer
2008-12-01
Full Text Available A common problem in dynamic systems is to determine parameters in an equation used to represent experimental data. The goal is to determine the values of model parameters that provide the best fit to measured data, generally based on some type of least squares or maximum likelihood criterion. In the most general case, this requires the solution of a nonlinear and frequently non-convex optimization problem. Some of the available software lack in generality, while others do not provide ease of use. A user-interactive parameter estimation software was needed for identifying kinetic parameters. In this work we developed an integration based optimization approach to provide a solution to such problems. For easy implementation of the technique, a parameter estimation software (PARES has been developed in MATLAB environment. When tested with extensive example problems from literature, the suggested approach is proven to provide good agreement between predicted and observed data within relatively less computing time and iterations.
Bank Tavakoli, M. Reza; Power, Michael; Ruttledge, Lisa; Flynn, Damian
2012-01-01
The increasing penetration of wind farms in power systems has increased concerns over the frequency behaviour and control of synchronous power systems due to a low contribution from modern wind turbines to overall system inertia. With this trend of conventional generators being displaced by variable speed wind turbines, the contribution from load inertia becomes more significant. The need for greater consideration towards load inertia estimation, or even on-line tracking of load inertia, seem...
DEFF Research Database (Denmark)
Li, H.; Zhao, B.; Yang, C.
2011-01-01
of a grid-connected wind turbine with squirrel cage induction generator (SCIG). Firstly, by using an equivalent lump mass method, a three-mass wind turbine equivalent model is proposed considering both the blades and the shaft flexibility of the wind turbine drive train system. Combined with the detailed......Increasing levels of wind energy in modern electrical power system is initiating a need for accurate analysis and estimation of transient stability of wind turbine generation systems. This paper investigates the transient behaviors and possible direct methods for transient stability evaluation...... electromagnetic transient models of a SCIG, the transient behaviors of the wind turbine generation system during a three-phase fault are simulated and compared with the traditional models. Secondly, in order to quickly estimate the transient stability limit of the wind turbine generation system, a direct method...
Improving the realism of hydrologic model through multivariate parameter estimation
Rakovec, Oldrich; Kumar, Rohini; Attinger, Sabine; Samaniego, Luis
2017-04-01
Increased availability and quality of near real-time observations should improve understanding of predictive skills of hydrological models. Recent studies have shown the limited capability of river discharge data alone to adequately constrain different components of distributed model parameterizations. In this study, the GRACE satellite-based total water storage (TWS) anomaly is used to complement the discharge data with an aim to improve the fidelity of mesoscale hydrologic model (mHM) through multivariate parameter estimation. The study is conducted in 83 European basins covering a wide range of hydro-climatic regimes. The model parameterization complemented with the TWS anomalies leads to statistically significant improvements in (1) discharge simulations during low-flow period, and (2) evapotranspiration estimates which are evaluated against independent (FLUXNET) data. Overall, there is no significant deterioration in model performance for the discharge simulations when complemented by information from the TWS anomalies. However, considerable changes in the partitioning of precipitation into runoff components are noticed by in-/exclusion of TWS during the parameter estimation. A cross-validation test carried out to assess the transferability and robustness of the calibrated parameters to other locations further confirms the benefit of complementary TWS data. In particular, the evapotranspiration estimates show more robust performance when TWS data are incorporated during the parameter estimation, in comparison with the benchmark model constrained against discharge only. This study highlights the value for incorporating multiple data sources during parameter estimation to improve the overall realism of hydrologic model and its applications over large domains. Rakovec, O., Kumar, R., Attinger, S. and Samaniego, L. (2016): Improving the realism of hydrologic model functioning through multivariate parameter estimation. Water Resour. Res., 52, http://dx.doi.org/10
Traveltime approximations and parameter estimation for orthorhombic media
Masmoudi, Nabil
2016-05-30
Building anisotropy models is necessary for seismic modeling and imaging. However, anisotropy estimation is challenging due to the trade-off between inhomogeneity and anisotropy. Luckily, we can estimate the anisotropy parameters Building anisotropy models is necessary for seismic modeling and imaging. However, anisotropy estimation is challenging due to the trade-off between inhomogeneity and anisotropy. Luckily, we can estimate the anisotropy parameters if we relate them analytically to traveltimes. Using perturbation theory, we have developed traveltime approximations for orthorhombic media as explicit functions of the anellipticity parameters η1, η2, and Δχ in inhomogeneous background media. The parameter Δχ is related to Tsvankin-Thomsen notation and ensures easier computation of traveltimes in the background model. Specifically, our expansion assumes an inhomogeneous ellipsoidal anisotropic background model, which can be obtained from well information and stacking velocity analysis. We have used the Shanks transform to enhance the accuracy of the formulas. A homogeneous medium simplification of the traveltime expansion provided a nonhyperbolic moveout description of the traveltime that was more accurate than other derived approximations. Moreover, the formulation provides a computationally efficient tool to solve the eikonal equation of an orthorhombic medium, without any constraints on the background model complexity. Although, the expansion is based on the factorized representation of the perturbation parameters, smooth variations of these parameters (represented as effective values) provides reasonable results. Thus, this formulation provides a mechanism to estimate the three effective parameters η1, η2, and Δχ. We have derived Dix-type formulas for orthorhombic medium to convert the effective parameters to their interval values.
The distribution of waves in the inner magnetosphere as a function of solar wind parameters
Aryan, Homayon; Balikhin, Michael A.; Agapitov, Oleksiy; Krasnoselskikh, Vladimir; Yearby, Keith
Energetic electrons within the Earth’s radiation belts represent a serious hazard to geostationary satellites. The interactions of electrons with chorus waves play an important role in both the acceleration and loss of radiation belt electrons. Studies of the evolution of energetic electron fluxes rely heavily on numerical codes in order to model energy and pitch angle diffusion due to electron interaction with plasma waves in the frame of quasilinear approximation. Application of these codes requires knowledge of statistical wave models to present wave distributions in the magnetosphere. A number of such models are based on CRESS, Cluster, THEMIS and other mission data. These models present wave distributions as a function of L-shell, magnetic local time, magnetic latitude and geomagnetic activity expressed by geomagnetic indices (Kp or Ae). However, it has been shown by G. Reeves and co-authors that only 50% of geomagnetic storms increase flux of relativistic electrons at GEO while 20% cause a decrease. This emphasizes the importance of including solar wind parameters in addition to geomagnetic indices. The present study examines almost four years (01, January, 2004 to 29, September, 2007) of STAFF (Spatio-Temporal Analysis of Field Fluctuation) data from Double Star TC1 combined with geomagnetic indices and solar wind parameters from OMNI database in order to present a comprehensive model of chorus wave intensities as a function of L-shell, magnetic local time, magnetic latitude, geomagnetic indices and solar wind parameters. The results show that chorus emission is not only sub-storm dependent but also dependent upon solar wind parameters with solar wind velocity evidently the most influential solar wind parameter. The largest peak intensities are observed for lower band chorus during active conditions, high solar wind velocity, low density and high pressure.
Possible Power Estimation of Down-Regulated Offshore Wind Power Plants
DEFF Research Database (Denmark)
Gögmen, Tuhfe
The penetration of offshore wind power is continuously increasing in the Northern European grids. To assure safety in the operation of the power system, wind power plants are required to provide ancillary services, including reserve power attained through down-regulating the wind farm from its...... power plant. The developed procedure, the PossPOW algorithm, can also be used in the wind farm control as it yields a real-time wind farm power curve. The modern wind turbines have a possible power signal at the turbine level and the current state of the art is to aggregate those signals to achieve...... the wind farm scale production capacity. However the summation of these individual signals is simply an over-estimation for the wind power plant, due to reduced wake losses during curtailment. The determination of the possible power with the PossPOW algorithm works as follows: firstly the second...
Small sample GEE estimation of regression parameters for longitudinal data.
Paul, Sudhir; Zhang, Xuemao
2014-09-28
Longitudinal (clustered) response data arise in many bio-statistical applications which, in general, cannot be assumed to be independent. Generalized estimating equation (GEE) is a widely used method to estimate marginal regression parameters for correlated responses. The advantage of the GEE is that the estimates of the regression parameters are asymptotically unbiased even if the correlation structure is misspecified, although their small sample properties are not known. In this paper, two bias adjusted GEE estimators of the regression parameters in longitudinal data are obtained when the number of subjects is small. One is based on a bias correction, and the other is based on a bias reduction. Simulations show that the performances of both the bias-corrected methods are similar in terms of bias, efficiency, coverage probability, average coverage length, impact of misspecification of correlation structure, and impact of cluster size on bias correction. Both these methods show superior properties over the GEE estimates for small samples. Further, analysis of data involving a small number of subjects also shows improvement in bias, MSE, standard error, and length of the confidence interval of the estimates by the two bias adjusted methods over the GEE estimates. For small to moderate sample sizes (N ≤50), either of the bias-corrected methods GEEBc and GEEBr can be used. However, the method GEEBc should be preferred over GEEBr, as the former is computationally easier. For large sample sizes, the GEE method can be used. Copyright © 2014 John Wiley & Sons, Ltd.
Parameter estimation in stochastic rainfall-runoff models
DEFF Research Database (Denmark)
Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur
2006-01-01
A parameter estimation method for stochastic rainfall-runoff models is presented. The model considered in the paper is a conceptual stochastic model, formulated in continuous-discrete state space form. The model is small and a fully automatic optimization is, therefore, possible for estimating all....... For a comparison the parameters are also estimated by an output error method, where the sum of squared simulation error is minimized. The former methodology is optimal for short-term prediction whereas the latter is optimal for simulations. Hence, depending on the purpose it is possible to select whether...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...
Adaptive distributed parameter and input estimation in linear parabolic PDEs
Mechhoud, Sarra
2016-01-01
In this paper, we discuss the on-line estimation of distributed source term, diffusion, and reaction coefficients of a linear parabolic partial differential equation using both distributed and interior-point measurements. First, new sufficient identifiability conditions of the input and the parameter simultaneous estimation are stated. Then, by means of Lyapunov-based design, an adaptive estimator is derived in the infinite-dimensional framework. It consists of a state observer and gradient-based parameter and input adaptation laws. The parameter convergence depends on the plant signal richness assumption, whereas the state convergence is established using a Lyapunov approach. The results of the paper are illustrated by simulation on tokamak plasma heat transport model using simulated data.
Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model
Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami
2017-06-01
A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.
Modeling extreme events: Sample fraction adaptive choice in parameter estimation
Neves, Manuela; Gomes, Ivette; Figueiredo, Fernanda; Gomes, Dora Prata
2012-09-01
When modeling extreme events there are a few primordial parameters, among which we refer the extreme value index and the extremal index. The extreme value index measures the right tail-weight of the underlying distribution and the extremal index characterizes the degree of local dependence in the extremes of a stationary sequence. Most of the semi-parametric estimators of these parameters show the same type of behaviour: nice asymptotic properties, but a high variance for small values of k, the number of upper order statistics to be used in the estimation, and a high bias for large values of k. This shows a real need for the choice of k. Choosing some well-known estimators of those parameters we revisit the application of a heuristic algorithm for the adaptive choice of k. The procedure is applied to some simulated samples as well as to some real data sets.
Synoptic maps of solar wind parameters from in situ spacecraft observations
Gazis, P. R.
1995-01-01
Solar wind observations from the Interplanetary Monitoring Platform-8 (IMP-8) and Pioneer Venus Orbiter (PVO) spacecraft from 1982 until 1988 are combined to construct synoptic maps of solar wind parameters near 1 AU. Each map consists of 6 months of hourly averaged solar wind data, binned by heliographic latitude and Carrington longitude and projected back to the Sun. These maps show the structure and time evolution of solar wind streams near 1 AU in the heliographic latitudes of +/- 7.25 deg and provide and explicit picture of several phenomena, such as gradients, changes in the inclination of the heliospheric current sheet, and the relative positions of various structures in the inner heliosphere, that is difficult to obtain from single-spacecraft observations. The stream structure varied significantly during the last solar cycle. Between 1982 and early 1985, solar wind parameters did not depend strongly on heliographic latitude. During the last solar minimum, the solar wind developed significant latitudinal structure, and high-speed streams were excluded from the vicinity of the solar equator. The interplanetary magnetic field was strongly correlated with the coronal field, and the current sheet tended to coincide with the coronal neutral line. The solar wind speed showed the expected correlations with temperature, interplanetary magnetic field, and distance from the current sheet. The solar wind speed was anticorrelated with density, but the regions of highest density occurred east of the heliospheric current sheet and the regions of lowest solar wind speed. This is consistent with compression at the leading edge of high-speed streams.
Offshore Wind Resource Estimation in Mediterranean Area Using SAR Images
DEFF Research Database (Denmark)
Calaudi, Rosamaria; Arena, Felice; Badger, Merete
Satellite observations of the ocean surface from Synthetic Aperture Radars (SAR) provide information about the spatial wind variability over large areas. This is of special interest in the Mediterranean, where spatial wind information is only provided by sparse buoys, often with long periods...
Wind damage to windows as estimated from explosion tests
International Nuclear Information System (INIS)
Reed, J.W.
1973-01-01
Window damage data from chemical and nuclear explosions were analyzed to provide information on the realistic behavior of installed glass. The results, in terms of blast overpressure, were transformed to wind gust loadings of comparable time scales, and can be used to predict window breakage probability for various wind speeds. (U.S.)
Estimation of the wind turbine yaw error by support vector machines
DEFF Research Database (Denmark)
Sheibat-Othman, Nida; Othman, Sami; Tayari, Raoaa
2015-01-01
Wind turbine yaw error information is of high importance in controlling wind turbine power and structural load. Normally used wind vanes are imprecise. In this work, the estimation of yaw error in wind turbines is studied using support vector machines for regression (SVR). As the methodology...... is data-based, simulated data from a high fidelity aero-elastic model is used for learning. The model simulates a variable speed horizontal-axis wind turbine composed of three blades and a full converter. Both partial load (blade angles fixed at 0 deg) and full load zones (active pitch actuators...
Parameter Estimation of Damped Compound Pendulum Differential Evolution Algorithm
Directory of Open Access Journals (Sweden)
Saad Mohd Sazli
2016-01-01
Full Text Available This paper present the parameter identification of damped compound pendulum using differential evolution algorithm. The procedure used to achieve the parameter identification of the experimental system consisted of input output data collection, ARX model order selection and parameter estimation using conventional method least square (LS and differential evolution (DE algorithm. PRBS signal is used to be input signal to regulate the motor speed. Whereas, the output signal is taken from position sensor. Both, input and output data is used to estimate the parameter of the ARX model. The residual error between the actual and predicted output responses of the models is validated using mean squares error (MSE. Analysis showed that, MSE value for LS is 0.0026 and MSE value for DE is 3.6601×10-5. Based results obtained, it was found that DE have lower MSE than the LS method.
Estimation of shape model parameters for 3D surfaces
DEFF Research Database (Denmark)
Erbou, Søren Gylling Hemmingsen; Darkner, Sune; Fripp, Jurgen
2008-01-01
is applied to a database of 3D surfaces from a section of the porcine pelvic bone extracted from 33 CT scans. A leave-one-out validation shows that the parameters of the first 3 modes of the shape model can be predicted with a mean difference within [-0.01,0.02] from the true mean, with a standard deviation......Statistical shape models are widely used as a compact way of representing shape variation. Fitting a shape model to unseen data enables characterizing the data in terms of the model parameters. In this paper a Gauss-Newton optimization scheme is proposed to estimate shape model parameters of 3D...... surfaces using distance maps, which enables the estimation of model parameters without the requirement of point correspondence. For applications with acquisition limitations such as speed and cost, this formulation enables the fitting of a statistical shape model to arbitrarily sampled data. The method...
Parameter estimation and model selection in computational biology.
Directory of Open Access Journals (Sweden)
Gabriele Lillacci
2010-03-01
Full Text Available A central challenge in computational modeling of biological systems is the determination of the model parameters. Typically, only a fraction of the parameters (such as kinetic rate constants are experimentally measured, while the rest are often fitted. The fitting process is usually based on experimental time course measurements of observables, which are used to assign parameter values that minimize some measure of the error between these measurements and the corresponding model prediction. The measurements, which can come from immunoblotting assays, fluorescent markers, etc., tend to be very noisy and taken at a limited number of time points. In this work we present a new approach to the problem of parameter selection of biological models. We show how one can use a dynamic recursive estimator, known as extended Kalman filter, to arrive at estimates of the model parameters. The proposed method follows. First, we use a variation of the Kalman filter that is particularly well suited to biological applications to obtain a first guess for the unknown parameters. Secondly, we employ an a posteriori identifiability test to check the reliability of the estimates. Finally, we solve an optimization problem to refine the first guess in case it should not be accurate enough. The final estimates are guaranteed to be statistically consistent with the measurements. Furthermore, we show how the same tools can be used to discriminate among alternate models of the same biological process. We demonstrate these ideas by applying our methods to two examples, namely a model of the heat shock response in E. coli, and a model of a synthetic gene regulation system. The methods presented are quite general and may be applied to a wide class of biological systems where noisy measurements are used for parameter estimation or model selection.
CMB Beam Systematics: Impact on Lensing Parameter Estimation
Miller, N. J.; Shimon, M.; Keating, B. G.
2008-01-01
The CMB's B-mode polarization provides a handle on several cosmological parameters most notably the tensor-to-scalar ratio, $r$, and is sensitive to parameters which govern the growth of large scale structure (LSS) and evolution of the gravitational potential. The primordial gravitational-wave- and secondary lensing-induced B-mode signals are very weak and therefore prone to various foregrounds and systematics. In this work we use Fisher-matrix-based estimations and apply, for the first time,...
An approach of parameter estimation for non-synchronous systems
International Nuclear Information System (INIS)
Xu Daolin; Lu Fangfang
2005-01-01
Synchronization-based parameter estimation is simple and effective but only available to synchronous systems. To come over this limitation, we propose a technique that the parameters of an unknown physical process (possibly a non-synchronous system) can be identified from a time series via a minimization procedure based on a synchronization control. The feasibility of this approach is illustrated in several chaotic systems
Parameter Estimation for Single Diode Models of Photovoltaic Modules
Energy Technology Data Exchange (ETDEWEB)
Hansen, Clifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Photovoltaic and Distributed Systems Integration Dept.
2015-03-01
Many popular models for photovoltaic system performance employ a single diode model to compute the I - V curve for a module or string of modules at given irradiance and temperature conditions. A single diode model requires a number of parameters to be estimated from measured I - V curves. Many available parameter estimation methods use only short circuit, o pen circuit and maximum power points for a single I - V curve at standard test conditions together with temperature coefficients determined separately for individual cells. In contrast, module testing frequently records I - V curves over a wide range of irradi ance and temperature conditions which, when available , should also be used to parameterize the performance model. We present a parameter estimation method that makes use of a fu ll range of available I - V curves. We verify the accuracy of the method by recov ering known parameter values from simulated I - V curves . We validate the method by estimating model parameters for a module using outdoor test data and predicting the outdoor performance of the module.
Visco-piezo-elastic parameter estimation in laminated plate structures
DEFF Research Database (Denmark)
Araujo, A. L.; Mota Soares, C. M.; Herskovits, J.
2009-01-01
A parameter estimation technique is presented in this article, for identification of elastic, piezoelectric and viscoelastic properties of active laminated composite plates with surface-bonded piezoelectric patches. The inverse method presented uses experimental data in the form of a set...... determining the material parameters for the best fit. The solution of the inverse problem is obtained by gradient-based optimization techniques, through constrained minimization of an error functional, which expresses the deviation of the numerical model's response with respect to the experimentally measured...... data. Results are presented for the estimation of elastic, piezoelectric and viscoelastic properties in laminated plates....
MPEG2 video parameter and no reference PSNR estimation
DEFF Research Database (Denmark)
Li, Huiying; Forchhammer, Søren
2009-01-01
to the MPEG stream. This may be used in systems and applications where the coded stream is not accessible. Detection of MPEG I-frames and DCT (discrete cosine transform) block size is presented. For the I-frames, the quantization parameters are estimated. Combining these with statistics of the reconstructed......MPEG coded video may be processed for quality assessment or postprocessed to reduce coding artifacts or transcoded. Utilizing information about the MPEG stream may be useful for these tasks. This paper deals with estimating MPEG parameter information from the decoded video stream without access...
Parameter Estimation in Stochastic Differential Equations; An Overview
DEFF Research Database (Denmark)
Nielsen, Jan Nygaard; Madsen, Henrik; Young, P. C.
2000-01-01
This paper presents an overview of the progress of research on parameter estimation methods for stochastic differential equations (mostly in the sense of Ito calculus) over the period 1981-1999. These are considered both without measurement noise and with measurement noise, where the discretely...... observed stochastic differential equations are embedded in a continuous-discrete time state space model. Every attempts has been made to include results from other scientific disciplines. Maximum likelihood estimation of parameters in nonlinear stochastic differential equations is in general not possible...
Application of genetic algorithms for parameter estimation in liquid chromatography
International Nuclear Information System (INIS)
Hernandez Torres, Reynier; Irizar Mesa, Mirtha; Tavares Camara, Leoncio Diogenes
2012-01-01
In chromatography, complex inverse problems related to the parameters estimation and process optimization are presented. Metaheuristics methods are known as general purpose approximated algorithms which seek and hopefully find good solutions at a reasonable computational cost. These methods are iterative process to perform a robust search of a solution space. Genetic algorithms are optimization techniques based on the principles of genetics and natural selection. They have demonstrated very good performance as global optimizers in many types of applications, including inverse problems. In this work, the effectiveness of genetic algorithms is investigated to estimate parameters in liquid chromatography
Adjustment of Sensor Locations During Thermal Property Parameter Estimation
Milos, Frank S.; Marschall, Jochen; Rasky, Daniel J. (Technical Monitor)
1996-01-01
The temperature dependent thermal properties of a material may be evaluated from transient temperature histories using nonlinear parameter estimation techniques. The usual approach is to minimize the sum of the squared errors between measured and calculated temperatures at specific locations in the body. Temperature measurements are usually made with thermocouples and it is customary to take thermocouple locations as known and fixed during parameter estimation computations. In fact, thermocouple locations are never known exactly. Location errors on the order of the thermocouple wire diameter are intrinsic to most common instrumentation procedures (e.g., inserting a thermocouple into a drilled hole) and additional errors can be expected for delicate materials, difficult installations, large thermocouple beads, etc.. Thermocouple location errors are especially significant when estimating thermal properties of low diffusively materials which can sustain large temperature gradients during testing. In the present work, a parameter estimation formulation is presented which allows for the direct inclusion of thermocouple positions into the primary parameter estimation procedure. It is straightforward to set bounds on thermocouple locations which exclude non-physical locations and are consistent with installation tolerances. Furthermore, bounds may be tightened to an extent consistent with any independent verification of thermocouple location, such as x-raying, and so the procedure is entirely consonant with experimental information. A mathematical outline of the procedure is given and its implementation is illustrated through numerical examples characteristic of light-weight, high-temperature ceramic insulation during transient heating. The efficacy and the errors associated with the procedure are discussed.
Bayesian estimation of parameters in a regional hydrological model
Directory of Open Access Journals (Sweden)
K. Engeland
2002-01-01
Full Text Available This study evaluates the applicability of the distributed, process-oriented Ecomag model for prediction of daily streamflow in ungauged basins. The Ecomag model is applied as a regional model to nine catchments in the NOPEX area, using Bayesian statistics to estimate the posterior distribution of the model parameters conditioned on the observed streamflow. The distribution is calculated by Markov Chain Monte Carlo (MCMC analysis. The Bayesian method requires formulation of a likelihood function for the parameters and three alternative formulations are used. The first is a subjectively chosen objective function that describes the goodness of fit between the simulated and observed streamflow, as defined in the GLUE framework. The second and third formulations are more statistically correct likelihood models that describe the simulation errors. The full statistical likelihood model describes the simulation errors as an AR(1 process, whereas the simple model excludes the auto-regressive part. The statistical parameters depend on the catchments and the hydrological processes and the statistical and the hydrological parameters are estimated simultaneously. The results show that the simple likelihood model gives the most robust parameter estimates. The simulation error may be explained to a large extent by the catchment characteristics and climatic conditions, so it is possible to transfer knowledge about them to ungauged catchments. The statistical models for the simulation errors indicate that structural errors in the model are more important than parameter uncertainties. Keywords: regional hydrological model, model uncertainty, Bayesian analysis, Markov Chain Monte Carlo analysis
Lumped-Parameter Models for Wind-Turbine Footings on Layered Ground
DEFF Research Database (Denmark)
Andersen, Lars; Liingaard, Morten
2007-01-01
The design of modern wind turbines is typically based on lifetime analyses using aeroelastic codes. In this regard, the impedance of the foundations must be described accurately without increasing the overall size of the computational model significantly. This may be obtained by the fitting...... of a lumped-parameter model to the results of a rigorous model or experimental results. In this paper, guidelines are given for the formulation of such lumped-parameter models and examples are given in which the models are utilised for the analysis of a wind turbine supported by a surface footing on a layered...
DEFF Research Database (Denmark)
Ma, Ke; Liserre, Marco; Blaabjerg, Frede
2013-01-01
As a key component in the wind turbine system, power electronic converter and its power semiconductors suffer from adverse power loadings related to environment, and are proven to have certain failure rates. Therefore, correct lifetime estimation of wind power converter is crucial for the reliabi......As a key component in the wind turbine system, power electronic converter and its power semiconductors suffer from adverse power loadings related to environment, and are proven to have certain failure rates. Therefore, correct lifetime estimation of wind power converter is crucial...
Targeted estimation of nuisance parameters to obtain valid statistical inference.
van der Laan, Mark J
2014-01-01
In order to obtain concrete results, we focus on estimation of the treatment specific mean, controlling for all measured baseline covariates, based on observing independent and identically distributed copies of a random variable consisting of baseline covariates, a subsequently assigned binary treatment, and a final outcome. The statistical model only assumes possible restrictions on the conditional distribution of treatment, given the covariates, the so-called propensity score. Estimators of the treatment specific mean involve estimation of the propensity score and/or estimation of the conditional mean of the outcome, given the treatment and covariates. In order to make these estimators asymptotically unbiased at any data distribution in the statistical model, it is essential to use data-adaptive estimators of these nuisance parameters such as ensemble learning, and specifically super-learning. Because such estimators involve optimal trade-off of bias and variance w.r.t. the infinite dimensional nuisance parameter itself, they result in a sub-optimal bias/variance trade-off for the resulting real-valued estimator of the estimand. We demonstrate that additional targeting of the estimators of these nuisance parameters guarantees that this bias for the estimand is second order and thereby allows us to prove theorems that establish asymptotic linearity of the estimator of the treatment specific mean under regularity conditions. These insights result in novel targeted minimum loss-based estimators (TMLEs) that use ensemble learning with additional targeted bias reduction to construct estimators of the nuisance parameters. In particular, we construct collaborative TMLEs (C-TMLEs) with known influence curve allowing for statistical inference, even though these C-TMLEs involve variable selection for the propensity score based on a criterion that measures how effective the resulting fit of the propensity score is in removing bias for the estimand. As a particular special
Korner-Nievergelt, Fränzi; Brinkmann, Robert; Niermann, Ivo; Behr, Oliver
2013-01-01
Environmental impacts of wind energy facilities increasingly cause concern, a central issue being bats and birds killed by rotor blades. Two approaches have been employed to assess collision rates: carcass searches and surveys of animals prone to collisions. Carcass searches can provide an estimate for the actual number of animals being killed but they offer little information on the relation between collision rates and, for example, weather parameters due to the time of death not being precisely known. In contrast, a density index of animals exposed to collision is sufficient to analyse the parameters influencing the collision rate. However, quantification of the collision rate from animal density indices (e.g. acoustic bat activity or bird migration traffic rates) remains difficult. We combine carcass search data with animal density indices in a mixture model to investigate collision rates. In a simulation study we show that the collision rates estimated by our model were at least as precise as conventional estimates based solely on carcass search data. Furthermore, if certain conditions are met, the model can be used to predict the collision rate from density indices alone, without data from carcass searches. This can reduce the time and effort required to estimate collision rates. We applied the model to bat carcass search data obtained at 30 wind turbines in 15 wind facilities in Germany. We used acoustic bat activity and wind speed as predictors for the collision rate. The model estimates correlated well with conventional estimators. Our model can be used to predict the average collision rate. It enables an analysis of the effect of parameters such as rotor diameter or turbine type on the collision rate. The model can also be used in turbine-specific curtailment algorithms that predict the collision rate and reduce this rate with a minimal loss of energy production. PMID:23844144
Korner-Nievergelt, Fränzi; Brinkmann, Robert; Niermann, Ivo; Behr, Oliver
2013-01-01
Environmental impacts of wind energy facilities increasingly cause concern, a central issue being bats and birds killed by rotor blades. Two approaches have been employed to assess collision rates: carcass searches and surveys of animals prone to collisions. Carcass searches can provide an estimate for the actual number of animals being killed but they offer little information on the relation between collision rates and, for example, weather parameters due to the time of death not being precisely known. In contrast, a density index of animals exposed to collision is sufficient to analyse the parameters influencing the collision rate. However, quantification of the collision rate from animal density indices (e.g. acoustic bat activity or bird migration traffic rates) remains difficult. We combine carcass search data with animal density indices in a mixture model to investigate collision rates. In a simulation study we show that the collision rates estimated by our model were at least as precise as conventional estimates based solely on carcass search data. Furthermore, if certain conditions are met, the model can be used to predict the collision rate from density indices alone, without data from carcass searches. This can reduce the time and effort required to estimate collision rates. We applied the model to bat carcass search data obtained at 30 wind turbines in 15 wind facilities in Germany. We used acoustic bat activity and wind speed as predictors for the collision rate. The model estimates correlated well with conventional estimators. Our model can be used to predict the average collision rate. It enables an analysis of the effect of parameters such as rotor diameter or turbine type on the collision rate. The model can also be used in turbine-specific curtailment algorithms that predict the collision rate and reduce this rate with a minimal loss of energy production.
Enhancing parameter estimation precision by non-Hermitian operator process
Guo, You-neng; Fang, Mao-fa; Wang, Guo-you; Hang, Jiang; Zeng, Ke
2017-12-01
Recently, Zhong et al. (Phys Rev A 87:022337, 2013) investigated the dynamics of quantum Fisher information (QFI) in the presence of decoherence. We here reform their results and propose two schemes to enhance and preserve the QFIs for a qubit system subjected to a decoherence noisy environment by applying {non {-}Hermitian} operator process either before or after the amplitude damping noise. Resorting to the Bloch sphere representation, we derive the exact analytical expressions of the QFIs with respect to the amplitude parameter θ and the phase parameter φ , and in detail investigate the influence of {non {-}Hermitian} operator parameters on the QFIs. Compared with pure decoherence process (without non-Hermitian operator process), we find that the {post non {-}Hermitian} operator process can potentially enhance and preserve the QFIs by choosing appropriate {non {-}Hermitian} operator parameters, while with the help of the {prior non {-}Hermitian} operator process one could completely eliminate the effect of decoherence to improve the parameters estimation. Finally, a generalized non-Hermitian operator parameters effect on the parameters estimation is also discussed.
Estimation of Compaction Parameters Based on Soil Classification
Lubis, A. S.; Muis, Z. A.; Hastuty, I. P.; Siregar, I. M.
2018-02-01
Factors that must be considered in compaction of the soil works were the type of soil material, field control, maintenance and availability of funds. Those problems then raised the idea of how to estimate the density of the soil with a proper implementation system, fast, and economical. This study aims to estimate the compaction parameter i.e. the maximum dry unit weight (γ dmax) and optimum water content (Wopt) based on soil classification. Each of 30 samples were being tested for its properties index and compaction test. All of the data’s from the laboratory test results, were used to estimate the compaction parameter values by using linear regression and Goswami Model. From the research result, the soil types were A4, A-6, and A-7 according to AASHTO and SC, SC-SM, and CL based on USCS. By linear regression, the equation for estimation of the maximum dry unit weight (γdmax *)=1,862-0,005*FINES- 0,003*LL and estimation of the optimum water content (wopt *)=- 0,607+0,362*FINES+0,161*LL. By Goswami Model (with equation Y=mLogG+k), for estimation of the maximum dry unit weight (γdmax *) with m=-0,376 and k=2,482, for estimation of the optimum water content (wopt *) with m=21,265 and k=-32,421. For both of these equations a 95% confidence interval was obtained.
Procedures for parameter estimates of computational models for localized failure
Iacono, C.
2007-01-01
In the last years, many computational models have been developed for tensile fracture in concrete. However, their reliability is related to the correct estimate of the model parameters, not all directly measurable during laboratory tests. Hence, the development of inverse procedures is needed, that
Parameter estimation of an aeroelastic aircraft using neural networks
Indian Academy of Sciences (India)
Application of neural networks to the problem of aerodynamic modelling and parameter estimation for aeroelastic aircraft is addressed. A neural model capable of predicting generalized force and moment coefficients using measured motion and control variables only, without any need for conventional normal elastic ...
The observer-based synchronization and parameter estimation of a ...
Indian Academy of Sciences (India)
Haipeng Su
2017-10-31
Oct 31, 2017 ... Chaotic system; observer-based synchronization; parameter estimation; single output. PACS No. 05.45.Gg. 1. Introduction. Chaos is a widespread phenomenon occurring in many nonlinear systems, such as communication system, meteorological system etc. Since Pecora and Carroll. [1] developed a ...
On Modal Parameter Estimates from Ambient Vibration Tests
DEFF Research Database (Denmark)
Agneni, A.; Brincker, Rune; Coppotelli, B.
2004-01-01
Modal parameter estimates from ambient vibration testing are turning into the preferred technique when one is interested in systems under actual loadings and operational conditions. Moreover, with this approach, expensive devices to excite the structure are not needed, since it can be adequately...
An iterative scheme for estimating the parameters for an ...
African Journals Online (AJOL)
... parameter estimate using the least square method. It has the advantage of handling large system of equations which is difficult to handle when using the Least squares method. Some simulated data and one real life data are used to demonstrate this approach. Global Jouranl of Mathematical Sciences Vol. 6 (1) 2007: pp.
Bayesian estimation of the parameters of the birnbaum-saunders ...
African Journals Online (AJOL)
Bayesian estimation of the parameters of the birnbaum-saunders distribution. K Robert, LO Odongo. Abstract. No Abstract > East African Journal of Statistics Vol. 1 (3) 2007: pp.248-260. Full Text: EMAIL FULL TEXT EMAIL FULL TEXT · DOWNLOAD FULL TEXT DOWNLOAD FULL TEXT.
Estimation of object motion parameters from noisy images.
Broida, T J; Chellappa, R
1986-01-01
An approach is presented for the estimation of object motion parameters based on a sequence of noisy images. The problem considered is that of a rigid body undergoing unknown rotational and translational motion. The measurement data consists of a sequence of noisy image coordinates of two or more object correspondence points. By modeling the object dynamics as a function of time, estimates of the model parameters (including motion parameters) can be extracted from the data using recursive and/or batch techniques. This permits a desired degree of smoothing to be achieved through the use of an arbitrarily large number of images. Some assumptions regarding object structure are presently made. Results are presented for a recursive estimation procedure: the case considered here is that of a sequence of one dimensional images of a two dimensional object. Thus, the object moves in one transverse dimension, and in depth, preserving the fundamental ambiguity of the central projection image model (loss of depth information). An iterated extended Kalman filter is used for the recursive solution. Noise levels of 5-10 percent of the object image size are used. Approximate Cramer-Rao lower bounds are derived for the model parameter estimates as a function of object trajectory and noise level. This approach may be of use in situations where it is difficult to resolve large numbers of object match points, but relatively long sequences of images (10 to 20 or more) are available.
Revised models and genetic parameter estimates for production and ...
African Journals Online (AJOL)
Genetic parameters for production and reproduction traits in the Elsenburg Dormer sheep stud were estimated using records of 11743 lambs born between 1943 and 2002. An animal model with direct and maternal additive, maternal permanent and temporary environmental effects was fitted for traits considered traits of the ...
Cubic spline approximation techniques for parameter estimation in distributed systems
Banks, H. T.; Crowley, J. M.; Kunisch, K.
1983-01-01
Approximation schemes employing cubic splines in the context of a linear semigroup framework are developed for both parabolic and hyperbolic second-order partial differential equation parameter estimation problems. Convergence results are established for problems with linear and nonlinear systems, and a summary of numerical experiments with the techniques proposed is given.
Measuring, calculating and estimating PEP's parasitic mode loss parameters
International Nuclear Information System (INIS)
Weaver, J.N.
1981-01-01
This note discusses various ways the parasitic mode losses from a bunched beam to a vacuum chamber can be measured, calculated or estimated. A listing of the parameter, k, for the various PEP ring components is included. A number of formulas for calculating multiple and single pass losses are discussed and evaluated for several cases. 25 refs., 1 fig., 1 tab
Parameter estimates for reproductive output and product quality ...
African Journals Online (AJOL)
Parameter estimates for reproductive output and product quality traits of ostrich females within breeding seasons. ... South African Journal of Animal Science ... Egg production of young birds increased to reach a peak of approximately 4 to 5 eggs per month relatively late in the breeding season (September to December).
Parameter estimation of linear and quadratic chirps by employing ...
Indian Academy of Sciences (India)
This paper discusses some analytical results of the GTFT. We identify the eigenfunctions and eigenvalues of the GTFT. The time shift property of the GTFT is discussed. The paper describes methods for estimation of parameters of individual chirp signals on receipt of a noisy mixture of chirps. A priori knowledge of the nature ...
Parameter extraction and estimation based on the PV panel outdoor ...
African Journals Online (AJOL)
This work presents a novel approach to predict the voltage-current (V-I) characteristics of a PV panel under varying weather conditions to estimate the PV parameters. Outdoor performance of the PV module (AP-PM-15) was carried out for several times. The experimental data obtained are validated and compared with the ...
Simultaneous estimation of QTL parameters for mapping multiple traits
Indian Academy of Sciences (India)
LIANG TONG
2018-03-13
MIM) method was ... Our simulation results present the advantages of the new method in estimating parameters over an .... random error of the ith trait value of the jth subject, with mean zero and cov(eji, ejl) = σil = ρσiσl, i, l = 1,...
Synchronous Generator Model Parameter Estimation Based on Noisy Dynamic Waveforms
Berhausen, Sebastian; Paszek, Stefan
2016-01-01
In recent years, there have occurred system failures in many power systems all over the world. They have resulted in a lack of power supply to a large number of recipients. To minimize the risk of occurrence of power failures, it is necessary to perform multivariate investigations, including simulations, of power system operating conditions. To conduct reliable simulations, the current base of parameters of the models of generating units, containing the models of synchronous generators, is necessary. In the paper, there is presented a method for parameter estimation of a synchronous generator nonlinear model based on the analysis of selected transient waveforms caused by introducing a disturbance (in the form of a pseudorandom signal) in the generator voltage regulation channel. The parameter estimation was performed by minimizing the objective function defined as a mean square error for deviations between the measurement waveforms and the waveforms calculated based on the generator mathematical model. A hybrid algorithm was used for the minimization of the objective function. In the paper, there is described a filter system used for filtering the noisy measurement waveforms. The calculation results of the model of a 44 kW synchronous generator installed on a laboratory stand of the Institute of Electrical Engineering and Computer Science of the Silesian University of Technology are also given. The presented estimation method can be successfully applied to parameter estimation of different models of high-power synchronous generators operating in a power system.
Estimate of genetic and phenotypic parameters for litter size and ...
African Journals Online (AJOL)
Data on 964 and 1150 weaning weight and litter size records respectively, collected over a 10-year period on Yankasa Sheep breeding project at the National Animal Production Research Institute (N.A.P.R.I.), Zaria, were used in this study. The analysis was for estimation of genetic and phenotypic parameters for litter size ...
Estimation of genetic parameters for growth traits in Brangus cattle
African Journals Online (AJOL)
p2492989
Abstract. A combination of multiple trait and repeatability models were used to estimate genetic parameters for birth weight (BW), weaning weight (WW), yearling weight (YW), eighteen month weight (FW) and three measurements of mature weight (MW) using 23 768 records obtained from the South African Brangus.
Estimation of genetic parameters for carcass traits in Japanese quail ...
African Journals Online (AJOL)
The aim of this study was to estimate genetic parameters of some carcass characteristics in the Japanese quail. For this aim, carcass weight (Cw), breast weight (Bw), leg weight (Lw), abdominal fat weight (AFw), carcass yield (CP), breast percentage (BP), leg percentage (LP) and abdominal fat percentage (AFP) were ...
Estimation of light transport parameters in biological media using ...
Indian Academy of Sciences (India)
The suitability of using the angular peak shape of the coherent backscattered light for estimating the light transport parameters of biological media has been investigated. Milk and methylene blue doped milk were used as tissue phantoms for the measurements carried out with a He–Ne laser (632.8 nm). Results indicate that ...
A Sparse Bayesian Learning Algorithm With Dictionary Parameter Estimation
DEFF Research Database (Denmark)
Hansen, Thomas Lundgaard; Badiu, Mihai Alin; Fleury, Bernard Henri
2014-01-01
This paper concerns sparse decomposition of a noisy signal into atoms which are specified by unknown continuous-valued parameters. An example could be estimation of the model order, frequencies and amplitudes of a superposition of complex sinusoids. The common approach is to reduce the continuous...
A novel parameter estimation method for metal oxide surge arrester ...
Indian Academy of Sciences (India)
with experimental results. Keywords. Metal oxide surge arrester models; PSO; ACO; parameter estimation;. EMTP. 1. Introduction. Metal oxide (MO) surge arresters are widely used as protective devices against switching and lightning over-voltages in power systems. The proper nonlinear voltage-current characteristics,. ∗.
Estimation of light transport parameters in biological media using ...
Indian Academy of Sciences (India)
the use of the coherent backscattered peak from tissues to estimate the transport parameters has also been suggested [5–7]. ... closely resemble those of tissues and milk has been used to model light transport in brain tissue [15], to study optical imaging [16], .... The dye-doped colloids thus. Pramana – J. Phys., Vol. 54, No.
Estimation of stature from facial parameters in adult Abakaliki people ...
African Journals Online (AJOL)
This study is carried out in order to estimate the height of adult Igbo people of Abakaliki ethnic group in South-Eastern Nigeria from their facial Morphology. The parameters studied include Facial Length, Bizygomatic Diameter, Bigonial Diameter, Nasal Length, and Nasal Breadth. A total of 1000 subjects comprising 669 ...
Estimates Of Genetic Parameters Of Body Weights Of Different ...
African Journals Online (AJOL)
four (44) farrowings were used to estimate the genetic parameters (heritability and repeatability) of body weight of pigs. Results obtained from the study showed that the heritability (h2) of birth and weaning weights were moderate (0.33±0.16 ...
parameter extraction and estimation based on the pv panel outdoor
African Journals Online (AJOL)
userpc
PV panel under varying weather conditions to estimate the PV parameters. Outdoor performance of the PV module (AP-PM-15) was carried out for several times. The .... Performance. Analysis of Different Photovoltaic. Technologies Based on MATLAB. Simulation. In Northwest University. Science, Faculty of Science Annual.
Low Complexity Parameter Estimation For Off-the-Grid Targets
Jardak, Seifallah
2015-10-05
In multiple-input multiple-output radar, to estimate the reflection coefficient, spatial location, and Doppler shift of a target, a derived cost function is usually evaluated and optimized over a grid of points. The performance of such algorithms is directly affected by the size of the grid: increasing the number of points will enhance the resolution of the algorithm but exponentially increase its complexity. In this work, to estimate the parameters of a target, a reduced complexity super resolution algorithm is proposed. For off-the-grid targets, it uses a low order two dimensional fast Fourier transform to determine a suboptimal solution and then an iterative algorithm to jointly estimate the spatial location and Doppler shift. Simulation results show that the mean square estimation error of the proposed estimators achieve the Cram\\'er-Rao lower bound. © 2015 IEEE.
Parameter Estimation for a Class of Lifetime Models
Directory of Open Access Journals (Sweden)
Xinyang Ji
2014-01-01
Full Text Available Our purpose in this paper is to present a better method of parametric estimation for a bivariate nonlinear regression model, which takes the performance indicator of rubber aging as the dependent variable and time and temperature as the independent variables. We point out that the commonly used two-step method (TSM, which splits the model and estimate parameters separately, has limitation. Instead, we apply the Marquardt’s method (MM to implement parametric estimation directly for the model and compare these two methods of parametric estimation by random simulation. Our results show that MM has better effect of data fitting, more reasonable parametric estimates, and smaller prediction error compared with TSM.
Accuracy and sensitivity analysis on seismic anisotropy parameter estimation
Yan, Fuyong; Han, De-Hua
2018-04-01
There is significant uncertainty in measuring the Thomsen’s parameter δ in laboratory even though the dimensions and orientations of the rock samples are known. It is expected that more challenges will be encountered in the estimating of the seismic anisotropy parameters from field seismic data. Based on Monte Carlo simulation of vertical transversely isotropic layer cake model using the database of laboratory anisotropy measurement from the literature, we apply the commonly used quartic non-hyperbolic reflection moveout equation to estimate the seismic anisotropy parameters and test its accuracy and sensitivities to the source-receive offset, vertical interval velocity error and time picking error. The testing results show that the methodology works perfectly for noise-free synthetic data with short spread length. However, this method is extremely sensitive to the time picking error caused by mild random noises, and it requires the spread length to be greater than the depth of the reflection event. The uncertainties increase rapidly for the deeper layers and the estimated anisotropy parameters can be very unreliable for a layer with more than five overlain layers. It is possible that an isotropic formation can be misinterpreted as a strong anisotropic formation. The sensitivity analysis should provide useful guidance on how to group the reflection events and build a suitable geological model for anisotropy parameter inversion.
Estimation of parameter sensitivities for stochastic reaction networks
Gupta, Ankit
2016-01-07
Quantification of the effects of parameter uncertainty is an important and challenging problem in Systems Biology. We consider this problem in the context of stochastic models of biochemical reaction networks where the dynamics is described as a continuous-time Markov chain whose states represent the molecular counts of various species. For such models, effects of parameter uncertainty are often quantified by estimating the infinitesimal sensitivities of some observables with respect to model parameters. The aim of this talk is to present a holistic approach towards this problem of estimating parameter sensitivities for stochastic reaction networks. Our approach is based on a generic formula which allows us to construct efficient estimators for parameter sensitivity using simulations of the underlying model. We will discuss how novel simulation techniques, such as tau-leaping approximations, multi-level methods etc. can be easily integrated with our approach and how one can deal with stiff reaction networks where reactions span multiple time-scales. We will demonstrate the efficiency and applicability of our approach using many examples from the biological literature.
Tsunami Prediction and Earthquake Parameters Estimation in the Red Sea
Sawlan, Zaid A
2012-12-01
Tsunami concerns have increased in the world after the 2004 Indian Ocean tsunami and the 2011 Tohoku tsunami. Consequently, tsunami models have been developed rapidly in the last few years. One of the advanced tsunami models is the GeoClaw tsunami model introduced by LeVeque (2011). This model is adaptive and consistent. Because of different sources of uncertainties in the model, observations are needed to improve model prediction through a data assimilation framework. Model inputs are earthquake parameters and topography. This thesis introduces a real-time tsunami forecasting method that combines tsunami model with observations using a hybrid ensemble Kalman filter and ensemble Kalman smoother. The filter is used for state prediction while the smoother operates smoothing to estimate the earthquake parameters. This method reduces the error produced by uncertain inputs. In addition, state-parameter EnKF is implemented to estimate earthquake parameters. Although number of observations is small, estimated parameters generates a better tsunami prediction than the model. Methods and results of prediction experiments in the Red Sea are presented and the prospect of developing an operational tsunami prediction system in the Red Sea is discussed.
Dual ant colony operational modal analysis parameter estimation method
Sitarz, Piotr; Powałka, Bartosz
2018-01-01
Operational Modal Analysis (OMA) is a common technique used to examine the dynamic properties of a system. Contrary to experimental modal analysis, the input signal is generated in object ambient environment. Operational modal analysis mainly aims at determining the number of pole pairs and at estimating modal parameters. Many methods are used for parameter identification. Some methods operate in time while others in frequency domain. The former use correlation functions, the latter - spectral density functions. However, while some methods require the user to select poles from a stabilisation diagram, others try to automate the selection process. Dual ant colony operational modal analysis parameter estimation method (DAC-OMA) presents a new approach to the problem, avoiding issues involved in the stabilisation diagram. The presented algorithm is fully automated. It uses deterministic methods to define the interval of estimated parameters, thus reducing the problem to optimisation task which is conducted with dedicated software based on ant colony optimisation algorithm. The combination of deterministic methods restricting parameter intervals and artificial intelligence yields very good results, also for closely spaced modes and significantly varied mode shapes within one measurement point.
Amiri-Simkooei, A. R.
2018-01-01
Three-dimensional (3D) coordinate transformations, generally consisting of origin shifts, axes rotations, scale changes, and skew parameters, are widely used in many geomatics applications. Although in some geodetic applications simplified transformation models are used based on the assumption of small transformation parameters, in other fields of applications such parameters are indeed large. The algorithms of two recent papers on the weighted total least-squares (WTLS) problem are used for the 3D coordinate transformation. The methodology can be applied to the case when the transformation parameters are generally large of which no approximate values of the parameters are required. Direct linearization of the rotation and scale parameters is thus not required. The WTLS formulation is employed to take into consideration errors in both the start and target systems on the estimation of the transformation parameters. Two of the well-known 3D transformation methods, namely affine (12, 9, and 8 parameters) and similarity (7 and 6 parameters) transformations, can be handled using the WTLS theory subject to hard constraints. Because the method can be formulated by the standard least-squares theory with constraints, the covariance matrix of the transformation parameters can directly be provided. The above characteristics of the 3D coordinate transformation are implemented in the presence of different variance components, which are estimated using the least squares variance component estimation. In particular, the estimability of the variance components is investigated. The efficacy of the proposed formulation is verified on two real data sets.
PhyloPars: estimation of missing parameter values using phylogeny.
Bruggeman, Jorn; Heringa, Jaap; Brandt, Bernd W
2009-07-01
A wealth of information on metabolic parameters of a species can be inferred from observations on species that are phylogenetically related. Phylogeny-based information can complement direct empirical evidence, and is particularly valuable if experiments on the species of interest are not feasible. The PhyloPars web server provides a statistically consistent method that combines an incomplete set of empirical observations with the species phylogeny to produce a complete set of parameter estimates for all species. It builds upon a state-of-the-art evolutionary model, extended with the ability to handle missing data. The resulting approach makes optimal use of all available information to produce estimates that can be an order of magnitude more accurate than ad-hoc alternatives. Uploading a phylogeny and incomplete feature matrix suffices to obtain estimates of all missing values, along with a measure of certainty. Real-time cross-validation provides further insight in the accuracy and bias expected for estimated values. The server allows for easy, efficient estimation of metabolic parameters, which can benefit a wide range of fields including systems biology and ecology. PhyloPars is available at: http://www.ibi.vu.nl/programs/phylopars/.
Directory of Open Access Journals (Sweden)
Y. Lehahn
2010-07-01
Full Text Available Six years (2003–2008 of satellite measurements of aerosol parameters from the Moderate Resolution Imaging Spectroradiometer (MODIS and surface wind speeds from Quick Scatterometer (QuikSCAT, the Advanced Microwave Scanning Radiometer (AMSR-E, and the Special Sensor Microwave Imager (SSM/I, are used to provide a comprehensive perspective on the link between surface wind speed and marine aerosol optical depth over tropical and subtropical oceanic regions. A systematic comparison between the satellite derived fields in these regions allows to: (i separate the relative contribution of wind-induced marine aerosol to the aerosol optical depth; (ii extract an empirical linear equation linking coarse marine aerosol optical depth and wind intensity; and (iii identify a time scale for correlating marine aerosol optical depth and surface wind speed. The contribution of wind induced marine aerosol to aerosol optical depth is found to be dominated by the coarse mode elements. When wind intensity exceeds 4 m/s, coarse marine aerosol optical depth is linearly correlated with the surface wind speed, with a remarkably consistent slope of 0.009±0.002 s/m. A detailed time scale analysis shows that the linear correlation between the fields is well kept within a 12 h time frame, while sharply decreasing when the time lag between measurements is longer. The background aerosol optical depth, associated with aerosols that are not produced in-situ through wind driven processes, can be used for estimating the contributions of terrestrial and biogenic marine aerosol to over-ocean satellite retrievals of aerosol optical depth.
Estimation of Physical Parameters in Linear and Nonlinear Dynamic Systems
DEFF Research Database (Denmark)
Knudsen, Morten
for certain input in the time or frequency domain, are emphasised. Consequently, some special techniques are required, in particular for input signal design and model validation. The model structure containing physical parameters is constructed from basic physical laws (mathematical modelling). It is possible......Estimation of physical parameters is an important subclass of system identification. The specific objective is to obtain accurate estimates of the model parameters, while the objective of other aspects of system identification might be to determine a model where other properties, such as responses...... and essential to utilise this physical insight in the input design and validation procedures. This project has two objectives: 1. To develop and apply theories and techniques that are compatible with physical insight and robust to violation of assumptions and approximations, for system identification in general...
Estimating Arrhenius parameters using temperature programmed molecular dynamics
Energy Technology Data Exchange (ETDEWEB)
Imandi, Venkataramana; Chatterjee, Abhijit, E-mail: abhijit@che.iitb.ac.in [Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai 400076 (India)
2016-07-21
Kinetic rates at different temperatures and the associated Arrhenius parameters, whenever Arrhenius law is obeyed, are efficiently estimated by applying maximum likelihood analysis to waiting times collected using the temperature programmed molecular dynamics method. When transitions involving many activated pathways are available in the dataset, their rates may be calculated using the same collection of waiting times. Arrhenius behaviour is ascertained by comparing rates at the sampled temperatures with ones from the Arrhenius expression. Three prototype systems with corrugated energy landscapes, namely, solvated alanine dipeptide, diffusion at the metal-solvent interphase, and lithium diffusion in silicon, are studied to highlight various aspects of the method. The method becomes particularly appealing when the Arrhenius parameters can be used to find rates at low temperatures where transitions are rare. Systematic coarse-graining of states can further extend the time scales accessible to the method. Good estimates for the rate parameters are obtained with 500-1000 waiting times.
Estimation of Parameters in Mean-Reverting Stochastic Systems
Directory of Open Access Journals (Sweden)
Tianhai Tian
2014-01-01
Full Text Available Stochastic differential equation (SDE is a very important mathematical tool to describe complex systems in which noise plays an important role. SDE models have been widely used to study the dynamic properties of various nonlinear systems in biology, engineering, finance, and economics, as well as physical sciences. Since a SDE can generate unlimited numbers of trajectories, it is difficult to estimate model parameters based on experimental observations which may represent only one trajectory of the stochastic model. Although substantial research efforts have been made to develop effective methods, it is still a challenge to infer unknown parameters in SDE models from observations that may have large variations. Using an interest rate model as a test problem, in this work we use the Bayesian inference and Markov Chain Monte Carlo method to estimate unknown parameters in SDE models.
Using Genetic Algorithm to Estimate Hydraulic Parameters of Unconfined Aquifers
Directory of Open Access Journals (Sweden)
Asghar Asghari Moghaddam
2009-03-01
Full Text Available Nowadays, optimization techniques such as Genetic Algorithms (GA have attracted wide attention among scientists for solving complicated engineering problems. In this article, pumping test data are used to assess the efficiency of GA in estimating unconfined aquifer parameters and a sensitivity analysis is carried out to propose an optimal arrangement of GA. For this purpose, hydraulic parameters of three sets of pumping test data are calculated by GA and they are compared with the results of graphical methods. The results indicate that the GA technique is an efficient, reliable, and powerful method for estimating the hydraulic parameters of unconfined aquifer and, further, that in cases of deficiency in pumping test data, it has a better performance than graphical methods.
Scour depth estimation using an equation based on wind tunnel experiments
Directory of Open Access Journals (Sweden)
Tsutsui Takayuki
2016-01-01
Full Text Available Scour is the result of degradation and aggradation by wind or moving fluid in the front and back of a pole standing in sand, respectively, and is often observed at the bottom of bridge piers in rivers. In this study, we propose a method of estimating the scour depth around a cylindrical structure standing in sand. The relationships among the depth of the scour, the aspect ratio of the structure (= height/diameter, the fluid velocity, and the sand properties (particle size and density were determined experimentally using a wind tunnel. The experiments were carried out under clear-water scour conditions. In the experiments, the aspect ratio of the cylindrical structure, the fluid velocity, and the sand particle size were varied systematically. The diameters of the structure were 20, 40, and 60 mm, and the aspect ratio was varied from 0.25 to 3.0. Sand particles of four sizes (200, 275, 475, and 600 μm were used in the experiment, and the velocity was varied from 4 to 11 m/s. The depth and radius of the scour were measured. As a result, we have developed an equation for estimating the scour depth that uses the aspect ratio, fluid velocity, and sand particle size as parameters.
Directory of Open Access Journals (Sweden)
Jonathan R Karr
2015-05-01
Full Text Available Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.
Estimating model parameters in nonautonomous chaotic systems using synchronization
International Nuclear Information System (INIS)
Yang, Xiaoli; Xu, Wei; Sun, Zhongkui
2007-01-01
In this Letter, a technique is addressed for estimating unknown model parameters of multivariate, in particular, nonautonomous chaotic systems from time series of state variables. This technique uses an adaptive strategy for tracking unknown parameters in addition to a linear feedback coupling for synchronizing systems, and then some general conditions, by means of the periodic version of the LaSalle invariance principle for differential equations, are analytically derived to ensure precise evaluation of unknown parameters and identical synchronization between the concerned experimental system and its corresponding receiver one. Exemplifies are presented by employing a parametrically excited 4D new oscillator and an additionally excited Ueda oscillator. The results of computer simulations reveal that the technique not only can quickly track the desired parameter values but also can rapidly respond to changes in operating parameters. In addition, the technique can be favorably robust against the effect of noise when the experimental system is corrupted by bounded disturbance and the normalized absolute error of parameter estimation grows almost linearly with the cutoff value of noise strength in simulation
Directory of Open Access Journals (Sweden)
Weimin Huang
2017-02-01
Full Text Available In this paper, a method for extracting wind parameters from rain-contaminated X-band nautical radar images is presented. The texture of the radar image is first generated based on spatial variability analysis. Through this process, the rain clutter in an image can be removed while the wave echoes are retained. The number of rain-contaminated pixels in each azimuthal direction of the texture is estimated, and this is used to determine the azimuthal directions in which the rain-contamination is negligible. Then, the original image data in these directions are selected for wind direction and speed retrieval using the modified intensity-level-selection-based wind algorithm. The proposed method is applied to shipborne radar data collected from the east Coast of Canada. The comparison of the radar results with anemometer data shows that the standard deviations of wind direction and speed using the rain mitigation technique can be reduced by about 14.5° and 1.3 m/s, respectively.
Venäläinen, Ari; Laapas, Mikko; Pirinen, Pentti; Horttanainen, Matti; Hyvönen, Reijo; Lehtonen, Ilari; Junila, Päivi; Hou, Meiting; Peltola, Heli M.
2017-07-01
The bioeconomy has an increasing role to play in climate change mitigation and the sustainable development of national economies. In Finland, a forested country, over 50 % of the current bioeconomy relies on the sustainable management and utilization of forest resources. Wind storms are a major risk that forests are exposed to and high-spatial-resolution analysis of the most vulnerable locations can produce risk assessment of forest management planning. In this paper, we examine the feasibility of the wind multiplier approach for downscaling of maximum wind speed, using 20 m spatial resolution CORINE land-use dataset and high-resolution digital elevation data. A coarse spatial resolution estimate of the 10-year return level of maximum wind speed was obtained from the ERA-Interim reanalyzed data. Using a geospatial re-mapping technique the data were downscaled to 26 meteorological station locations to represent very diverse environments. Applying a comparison, we find that the downscaled 10-year return levels represent 66 % of the observed variation among the stations examined. In addition, the spatial variation in wind-multiplier-downscaled 10-year return level wind was compared with the WAsP model-simulated wind. The heterogeneous test area was situated in northern Finland, and it was found that the major features of the spatial variation were similar, but in some locations, there were relatively large differences. The results indicate that the wind multiplier method offers a pragmatic and computationally feasible tool for identifying at a high spatial resolution those locations with the highest forest wind damage risks. It can also be used to provide the necessary wind climate information for wind damage risk model calculations, thus making it possible to estimate the probability of predicted threshold wind speeds for wind damage and consequently the probability (and amount) of wind damage for certain forest stand configurations.
Incorporating engineering intuition for parameter estimation in thermal sciences
Balaji, C.; Reddy, B. Konda; Herwig, H.
2013-12-01
This paper proposes a new method of incorporating priors based on engineering intuition for solving inverse problems. The thesis of this paper is that if an asymptote can be found to a problem in applied sciences or engineering, estimation of parameters can be first done for this asymptotic variant, which in principle should be simpler, since one or more parameters of the original problem may vanish for the asymptotic variant. Even so, by solving the inverse problem associated with the asymptotic variant, estimates of key parameters of the full problem can be obtained. This information can then be quantitatively incorporated as priors in the estimation of parameters for the full version of the problem which we call as prior generation through asymptotic variant. The goal is to see if this methodology will significantly reduce the uncertainties in the resulting estimates. To demonstrate this methodology, the classic problem of unsteady heat transfer from a one dimensional fin is chosen. The inverse problem is posed as the simultaneous estimation of the temperature dependent transfer coefficient (h θ ) and the thermal diffusivity ( α) of the fin material, given experimentally measured temperature-time histories at various locations along the fin. The asymptotic variant θ ( x, t) is the steady state problem where the influence of thermal diffusivity vanishes. Using surrogate temperature data generated from assumed values of h θ , first the asymptotic variant of the problem is solved using the Markov Chain Monte Carlo method in a Bayesian framework to generate an estimate of h θ . The estimate of h θ is then used as an informative prior for solving the inverse problem of determining h θ and α from θ ( x, t), and the effect of prior is quantitatively assessed by performing estimation with and without the prior. Finally, for purposes of validation, in-house experiments have been done where θ ( x, t) is generated using liquid crystal thermography and these data
Czech Academy of Sciences Publication Activity Database
Kraus, Michaela; Borges Fernandes, M.; Kubát, Jiří
2009-01-01
Roč. 499, č. 1 (2009), s. 291-299 ISSN 0004-6361 R&D Projects: GA AV ČR KJB300030701; GA ČR GA205/08/0003 Institutional research plan: CEZ:AV0Z10030501 Keywords : stars * fundamental parameters * winds Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 4.179, year: 2009
Spectral tensor parameters for wind turbine load modeling from forested and agricultural landscapes
DEFF Research Database (Denmark)
Chougule, Abhijit S.; Mann, Jakob; Segalini, A.
2015-01-01
A velocity spectral tensor model was evaluated from the single-point measurements of wind speed. The model contains three parameters representing the dissipation rate of specific turbulent kinetic energy, a turbulence length scale and the turbulence anisotropy. Sonic anemometer measurements taken...
Stable Parameter Estimation for Autoregressive Equations with Random Coefficients
Directory of Open Access Journals (Sweden)
V. B. Goryainov
2014-01-01
Full Text Available In recent yearsthere has been a growing interest in non-linear time series models. They are more flexible than traditional linear models and allow more adequate description of real data. Among these models a autoregressive model with random coefficients plays an important role. It is widely used in various fields of science and technology, for example, in physics, biology, economics and finance. The model parameters are the mean values of autoregressive coefficients. Their evaluation is the main task of model identification. The basic method of estimation is still the least squares method, which gives good results for Gaussian time series, but it is quite sensitive to even small disturbancesin the assumption of Gaussian observations. In this paper we propose estimates, which generalize the least squares estimate in the sense that the quadratic objective function is replaced by an arbitrary convex and even function. Reasonable choice of objective function allows you to keep the benefits of the least squares estimate and eliminate its shortcomings. In particular, you can make it so that they will be almost as effective as the least squares estimate in the Gaussian case, but almost never loose in accuracy with small deviations of the probability distribution of the observations from the Gaussian distribution.The main result is the proof of consistency and asymptotic normality of the proposed estimates in the particular case of the one-parameter model describing the stationary process with finite variance. Another important result is the finding of the asymptotic relative efficiency of the proposed estimates in relation to the least squares estimate. This allows you to compare the two estimates, depending on the probability distribution of innovation process and of autoregressive coefficients. The results can be used to identify an autoregressive process, especially with nonGaussian nature, and/or of autoregressive processes observed with gross
Directory of Open Access Journals (Sweden)
K. V. S. Namboodiri
2014-01-01
Full Text Available The study discusses the features of wind, turbulence, and surface roughness parameter over the coastal boundary layer of the Peninsular Indian Station, Thumba Equatorial Rocket Launching Station (TERLS. Every 5 min measurements from an ultrasonic anemometer at 3.3 m agl from May 2007 to December 2012 are used for this work. Symmetries in mesoscale turbulence, stress off-wind angle computations, structure of scalar wind, resultant wind direction, momentum flux (M, Obukhov length (L, frictional velocity (u*, w-component, turbulent heat flux (H, drag coefficient (CD, turbulent intensities, standard deviation of wind directions (σθ, wind steadiness factor-σθ relationship, bivariate normal distribution (BND wind model, surface roughness parameter (z0, z0 and wind direction (θ relationship, and variation of z0 with the Indian South West monsoon activity are discussed.
Directory of Open Access Journals (Sweden)
A. Elsonbaty
2014-10-01
Full Text Available In this article, the adaptive chaos synchronization technique is implemented by an electronic circuit and applied to the hyperchaotic system proposed by Chen et al. We consider the more realistic and practical case where all the parameters of the master system are unknowns. We propose and implement an electronic circuit that performs the estimation of the unknown parameters and the updating of the parameters of the slave system automatically, and hence it achieves the synchronization. To the best of our knowledge, this is the first attempt to implement a circuit that estimates the values of the unknown parameters of chaotic system and achieves synchronization. The proposed circuit has a variety of suitable real applications related to chaos encryption and cryptography. The outputs of the implemented circuits and numerical simulation results are shown to view the performance of the synchronized system and the proposed circuit.
METAHEURISTIC OPTIMIZATION METHODS FOR PARAMETERS ESTIMATION OF DYNAMIC SYSTEMS
Directory of Open Access Journals (Sweden)
V. Panteleev Andrei
2017-01-01
Full Text Available The article considers the usage of metaheuristic methods of constrained global optimization: “Big Bang - Big Crunch”, “Fireworks Algorithm”, “Grenade Explosion Method” in parameters of dynamic systems estimation, described with algebraic-differential equations. Parameters estimation is based upon the observation results from mathematical model behavior. Their values are derived after criterion minimization, which describes the total squared error of state vector coordinates from the deduced ones with precise values observation at different periods of time. Paral- lelepiped type restriction is imposed on the parameters values. Used for solving problems, metaheuristic methods of constrained global extremum don’t guarantee the result, but allow to get a solution of a rather good quality in accepta- ble amount of time. The algorithm of using metaheuristic methods is given. Alongside with the obvious methods for solving algebraic-differential equation systems, it is convenient to use implicit methods for solving ordinary differen- tial equation systems. Two ways of solving the problem of parameters evaluation are given, those parameters differ in their mathematical model. In the first example, a linear mathematical model describes the chemical action parameters change, and in the second one, a nonlinear mathematical model describes predator-prey dynamics, which characterize the changes in both kinds’ population. For each of the observed examples there are calculation results from all the three methods of optimization, there are also some recommendations for how to choose methods parameters. The obtained numerical results have demonstrated the efficiency of the proposed approach. The deduced parameters ap- proximate points slightly differ from the best known solutions, which were deduced differently. To refine the results one should apply hybrid schemes that combine classical methods of optimization of zero, first and second orders and
Consistent Parameter and Transfer Function Estimation using Context Free Grammars
Klotz, Daniel; Herrnegger, Mathew; Schulz, Karsten
2017-04-01
This contribution presents a method for the inference of transfer functions for rainfall-runoff models. Here, transfer functions are defined as parametrized (functional) relationships between a set of spatial predictors (e.g. elevation, slope or soil texture) and model parameters. They are ultimately used for estimation of consistent, spatially distributed model parameters from a limited amount of lumped global parameters. Additionally, they provide a straightforward method for parameter extrapolation from one set of basins to another and can even be used to derive parameterizations for multi-scale models [see: Samaniego et al., 2010]. Yet, currently an actual knowledge of the transfer functions is often implicitly assumed. As a matter of fact, for most cases these hypothesized transfer functions can rarely be measured and often remain unknown. Therefore, this contribution presents a general method for the concurrent estimation of the structure of transfer functions and their respective (global) parameters. Note, that by consequence an estimation of the distributed parameters of the rainfall-runoff model is also undertaken. The method combines two steps to achieve this. The first generates different possible transfer functions. The second then estimates the respective global transfer function parameters. The structural estimation of the transfer functions is based on the context free grammar concept. Chomsky first introduced context free grammars in linguistics [Chomsky, 1956]. Since then, they have been widely applied in computer science. But, to the knowledge of the authors, they have so far not been used in hydrology. Therefore, the contribution gives an introduction to context free grammars and shows how they can be constructed and used for the structural inference of transfer functions. This is enabled by new methods from evolutionary computation, such as grammatical evolution [O'Neill, 2001], which make it possible to exploit the constructed grammar as a
Parameter estimation in nonlinear models for pesticide degradation
International Nuclear Information System (INIS)
Richter, O.; Pestemer, W.; Bunte, D.; Diekkrueger, B.
1991-01-01
A wide class of environmental transfer models is formulated as ordinary or partial differential equations. With the availability of fast computers, the numerical solution of large systems became feasible. The main difficulty in performing a realistic and convincing simulation of the fate of a substance in the biosphere is not the implementation of numerical techniques but rather the incomplete data basis for parameter estimation. Parameter estimation is a synonym for statistical and numerical procedures to derive reasonable numerical values for model parameters from data. The classical method is the familiar linear regression technique which dates back to the 18th century. Because it is easy to handle, linear regression has long been established as a convenient tool for analysing relationships. However, the wide use of linear regression has led to an overemphasis of linear relationships. In nature, most relationships are nonlinear and linearization often gives a poor approximation of reality. Furthermore, pure regression models are not capable to map the dynamics of a process. Therefore, realistic models involve the evolution in time (and space). This leads in a natural way to the formulation of differential equations. To establish the link between data and dynamical models, numerical advanced parameter identification methods have been developed in recent years. This paper demonstrates the application of these techniques to estimation problems in the field of pesticide dynamics. (7 refs., 5 figs., 2 tabs.)
The Detection and Parameter Estimation of Binary Black Hole Mergers
Biwer, Christopher M.
In this dissertation we study gravitational-wave data analysis techniques for binary neutron star and black hole mergers. During its first observing run, the Advanced Laser Interferometer Gravitational-wave Observatory (Advanced LIGO) reported the first, direct observations of gravitational waves from two binary black hole mergers. We present the results from the search for binary black hole mergers which unambiguously detected the binary black hole mergers. We determine the effect of calibration errors on the detection statistic of the search. Since the search is not designed to precisely measure the astrophysical parameters of the binary neutron star and black hole mergers, we use Bayesian methods to develop a new parameter estimation analysis. We demonstrate the performance of the analysis on the binary black hole mergers detected during Advanced LIGO's first observing run. We use the parameter estimation analysis to assess the ability of gravitational-wave observatories to observe a gap in the black hole mass distribution between 52 M and 133 M due to pair-instability supernovae. Finally, we use simulated signals added to the Advanced LIGO detectors to validate the search and parameter estimation analyses used to publish the detection of the astrophysical events.
Spatial Distribution of Estimated Wind-Power Royalties in West Texas
Directory of Open Access Journals (Sweden)
Christian Brannstrom
2015-12-01
Full Text Available Wind-power development in the U.S. occurs primarily on private land, producing royalties for landowners through private contracts with wind-farm operators. Texas, the U.S. leader in wind-power production with well-documented support for wind power, has virtually all of its ~12 GW of wind capacity sited on private lands. Determining the spatial distribution of royalty payments from wind energy is a crucial first step to understanding how renewable power may alter land-based livelihoods of some landowners, and, as a result, possibly encourage land-use changes. We located ~1700 wind turbines (~2.7 GW on 241 landholdings in Nolan and Taylor counties, Texas, a major wind-development region. We estimated total royalties to be ~$11.5 million per year, with mean annual royalty received per landowner per year of $47,879 but with significant differences among quintiles and between two sub-regions. Unequal distribution of royalties results from land-tenure patterns established before wind-power development because of a “property advantage,” defined as the pre-existing land-tenure patterns that benefit the fraction of rural landowners who receive wind turbines. A “royalty paradox” describes the observation that royalties flow to a small fraction of landowners even though support for wind power exceeds 70 percent.
Energy Technology Data Exchange (ETDEWEB)
Piper, S.; Lee, L.K.
1989-06-01
Wind erosion contributes significantly to particulate air pollution in some regions of the Western United States. As a result, wind erosion imposes damages on households in the form of increased interior and exterior cleaning, reduced recreational opportunities, and impaired health. Costs are difficult to estimate because of limited data availability. However, damages appear to be much larger offsite than onsite.
Advanced Method to Estimate Fuel Slosh Simulation Parameters
Schlee, Keith; Gangadharan, Sathya; Ristow, James; Sudermann, James; Walker, Charles; Hubert, Carl
2005-01-01
The nutation (wobble) of a spinning spacecraft in the presence of energy dissipation is a well-known problem in dynamics and is of particular concern for space missions. The nutation of a spacecraft spinning about its minor axis typically grows exponentially and the rate of growth is characterized by the Nutation Time Constant (NTC). For launch vehicles using spin-stabilized upper stages, fuel slosh in the spacecraft propellant tanks is usually the primary source of energy dissipation. For analytical prediction of the NTC this fuel slosh is commonly modeled using simple mechanical analogies such as pendulums or rigid rotors coupled to the spacecraft. Identifying model parameter values which adequately represent the sloshing dynamics is the most important step in obtaining an accurate NTC estimate. Analytic determination of the slosh model parameters has met with mixed success and is made even more difficult by the introduction of propellant management devices and elastomeric diaphragms. By subjecting full-sized fuel tanks with actual flight fuel loads to motion similar to that experienced in flight and measuring the forces experienced by the tanks these parameters can be determined experimentally. Currently, the identification of the model parameters is a laborious trial-and-error process in which the equations of motion for the mechanical analog are hand-derived, evaluated, and their results are compared with the experimental results. The proposed research is an effort to automate the process of identifying the parameters of the slosh model using a MATLAB/SimMechanics-based computer simulation of the experimental setup. Different parameter estimation and optimization approaches are evaluated and compared in order to arrive at a reliable and effective parameter identification process. To evaluate each parameter identification approach, a simple one-degree-of-freedom pendulum experiment is constructed and motion is induced using an electric motor. By applying the
Parameter estimation for groundwater models under uncertain irrigation data
Demissie, Yonas; Valocchi, Albert J.; Cai, Ximing; Brozovic, Nicholas; Senay, Gabriel; Gebremichael, Mekonnen
2015-01-01
The success of modeling groundwater is strongly influenced by the accuracy of the model parameters that are used to characterize the subsurface system. However, the presence of uncertainty and possibly bias in groundwater model source/sink terms may lead to biased estimates of model parameters and model predictions when the standard regression-based inverse modeling techniques are used. This study first quantifies the levels of bias in groundwater model parameters and predictions due to the presence of errors in irrigation data. Then, a new inverse modeling technique called input uncertainty weighted least-squares (IUWLS) is presented for unbiased estimation of the parameters when pumping and other source/sink data are uncertain. The approach uses the concept of generalized least-squares method with the weight of the objective function depending on the level of pumping uncertainty and iteratively adjusted during the parameter optimization process. We have conducted both analytical and numerical experiments, using irrigation pumping data from the Republican River Basin in Nebraska, to evaluate the performance of ordinary least-squares (OLS) and IUWLS calibration methods under different levels of uncertainty of irrigation data and calibration conditions. The result from the OLS method shows the presence of statistically significant (p model predictions that persist despite calibrating the models to different calibration data and sample sizes. However, by directly accounting for the irrigation pumping uncertainties during the calibration procedures, the proposed IUWLS is able to minimize the bias effectively without adding significant computational burden to the calibration processes.
A frequency-based parameter for rapid estimation of magnitude
Atefi, Sanam; Heidari, Reza; Mirzaei, Noorbakhsh; Siahkoohi, Hamid Reza
2017-12-01
This study introduce a new frequency parameter called τ_{fcwt}, which can be used to estimate earthquake magnitude on the basis of the first few seconds of P-waves, using the waveforms of earthquakes occurring in Japan. This new parameter is introduced using continuous wavelet transform as a tool for extracting the frequency contents carried by the first few seconds of P-wave. The empirical relationship between the logarithm of τ_{fcwt} within the initial 4 s of a waveform and magnitude was obtained. To evaluate the precision of τ_{fcwt}, we also calculated parameters τp^{ max } and τc. The average absolute values of observed and estimated magnitude differences (|M_{est} - M_{obs} |) were 0.43, 0.49, and 0.66 units of magnitude, as determined using τp^{ max }, τc, and τ_{fcwt}, respectively. For earthquakes with magnitudes greater than 6, these values were 0.34, 0.56, and 0.44 units of magnitude, as derived using τp^{ max }, τc, and τ_{fcwt}, respectively. The τ_{fcwt} parameter exhibited more precision in determining the magnitude of moderate- and small-scale earthquakes than did the τc-based approach. For a general range of magnitudes, however, the τp^{ max }-based method showed more acceptable precision than did the other two parameters.
Parameter and state estimation in nonlinear dynamical systems
Creveling, Daniel R.
This thesis is concerned with the problem of state and parameter estimation in nonlinear systems. The need to evaluate unknown parameters in models of nonlinear physical, biophysical and engineering systems occurs throughout the development of phenomenological or reduced models of dynamics. When verifying and validating these models, it is important to incorporate information from observations in an efficient manner. Using the idea of synchronization of nonlinear dynamical systems, this thesis develops a framework for presenting data to a candidate model of a physical process in a way that makes efficient use of the measured data while allowing for estimation of the unknown parameters in the model. The approach presented here builds on existing work that uses synchronization as a tool for parameter estimation. Some critical issues of stability in that work are addressed and a practical framework is developed for overcoming these difficulties. The central issue is the choice of coupling strength between the model and data. If the coupling is too strong, the model will reproduce the measured data regardless of the adequacy of the model or correctness of the parameters. If the coupling is too weak, nonlinearities in the dynamics could lead to complex dynamics rendering any cost function comparing the model to the data inadequate for the determination of model parameters. Two methods are introduced which seek to balance the need for coupling with the desire to allow the model to evolve in its natural manner without coupling. One method, 'balanced' synchronization, adds to the synchronization cost function a requirement that the conditional Lyapunov exponents of the model system, conditioned on being driven by the data, remain negative but small in magnitude. Another method allows the coupling between the data and the model to vary in time according to a specific form of differential equation. The coupling dynamics is damped to allow for a tendency toward zero coupling
Bayesian Parameter Estimation via Filtering and Functional Approximations
Matthies, Hermann G.
2016-11-25
The inverse problem of determining parameters in a model by comparing some output of the model with observations is addressed. This is a description for what hat to be done to use the Gauss-Markov-Kalman filter for the Bayesian estimation and updating of parameters in a computational model. This is a filter acting on random variables, and while its Monte Carlo variant --- the Ensemble Kalman Filter (EnKF) --- is fairly straightforward, we subsequently only sketch its implementation with the help of functional representations.
Beef quality parameters estimation using ultrasound and color images.
Nunes, Jose; Piquerez, Martín; Pujadas, Leonardo; Armstrong, Eileen; Fernández, Alicia; Lecumberry, Federico
2015-01-01
Beef quality measurement is a complex task with high economic impact. There is high interest in obtaining an automatic quality parameters estimation in live cattle or post mortem. In this paper we set out to obtain beef quality estimates from the analysis of ultrasound (in vivo) and color images (post mortem), with the measurement of various parameters related to tenderness and amount of meat: rib eye area, percentage of intramuscular fat and backfat thickness or subcutaneous fat. An algorithm based on curve evolution is implemented to calculate the rib eye area. The backfat thickness is estimated from the profile of distances between two curves that limit the steak and the rib eye, previously detected. A model base in Support Vector Regression (SVR) is trained to estimate the intramuscular fat percentage. A series of features extracted on a region of interest, previously detected in both ultrasound and color images, were proposed. In all cases, a complete evaluation was performed with different databases including: color and ultrasound images acquired by a beef industry expert, intramuscular fat estimation obtained by an expert using a commercial software, and chemical analysis. The proposed algorithms show good results to calculate the rib eye area and the backfat thickness measure and profile. They are also promising in predicting the percentage of intramuscular fat.
Bayesian adaptive Markov chain Monte Carlo estimation of genetic parameters.
Mathew, B; Bauer, A M; Koistinen, P; Reetz, T C; Léon, J; Sillanpää, M J
2012-10-01
Accurate and fast estimation of genetic parameters that underlie quantitative traits using mixed linear models with additive and dominance effects is of great importance in both natural and breeding populations. Here, we propose a new fast adaptive Markov chain Monte Carlo (MCMC) sampling algorithm for the estimation of genetic parameters in the linear mixed model with several random effects. In the learning phase of our algorithm, we use the hybrid Gibbs sampler to learn the covariance structure of the variance components. In the second phase of the algorithm, we use this covariance structure to formulate an effective proposal distribution for a Metropolis-Hastings algorithm, which uses a likelihood function in which the random effects have been integrated out. Compared with the hybrid Gibbs sampler, the new algorithm had better mixing properties and was approximately twice as fast to run. Our new algorithm was able to detect different modes in the posterior distribution. In addition, the posterior mode estimates from the adaptive MCMC method were close to the REML (residual maximum likelihood) estimates. Moreover, our exponential prior for inverse variance components was vague and enabled the estimated mode of the posterior variance to be practically zero, which was in agreement with the support from the likelihood (in the case of no dominance). The method performance is illustrated using simulated data sets with replicates and field data in barley.
A large-eddy simulation based power estimation capability for wind farms over complex terrain
Senocak, I.; Sandusky, M.; Deleon, R.
2017-12-01
There has been an increasing interest in predicting wind fields over complex terrain at the micro-scale for resource assessment, turbine siting, and power forecasting. These capabilities are made possible by advancements in computational speed from a new generation of computing hardware, numerical methods and physics modelling. The micro-scale wind prediction model presented in this work is based on the large-eddy simulation paradigm with surface-stress parameterization. The complex terrain is represented using an immersed-boundary method that takes into account the parameterization of the surface stresses. Governing equations of incompressible fluid flow are solved using a projection method with second-order accurate schemes in space and time. We use actuator disk models with rotation to simulate the influence of turbines on the wind field. Data regarding power production from individual turbines are mostly restricted because of proprietary nature of the wind energy business. Most studies report percentage drop of power relative to power from the first row. There have been different approaches to predict power production. Some studies simply report available wind power in the upstream, some studies estimate power production using power curves available from turbine manufacturers, and some studies estimate power as torque multiplied by rotational speed. In the present work, we propose a black-box approach that considers a control volume around a turbine and estimate the power extracted from the turbine based on the conservation of energy principle. We applied our wind power prediction capability to wind farms over flat terrain such as the wind farm over Mower County, Minnesota and the Horns Rev offshore wind farm in Denmark. The results from these simulations are in good agreement with published data. We also estimate power production from a hypothetical wind farm in complex terrain region and identify potential zones suitable for wind power production.
Estimating parameters for probabilistic linkage of privacy-preserved datasets.
Brown, Adrian P; Randall, Sean M; Ferrante, Anna M; Semmens, James B; Boyd, James H
2017-07-10
Probabilistic record linkage is a process used to bring together person-based records from within the same dataset (de-duplication) or from disparate datasets using pairwise comparisons and matching probabilities. The linkage strategy and associated match probabilities are often estimated through investigations into data quality and manual inspection. However, as privacy-preserved datasets comprise encrypted data, such methods are not possible. In this paper, we present a method for estimating the probabilities and threshold values for probabilistic privacy-preserved record linkage using Bloom filters. Our method was tested through a simulation study using synthetic data, followed by an application using real-world administrative data. Synthetic datasets were generated with error rates from zero to 20% error. Our method was used to estimate parameters (probabilities and thresholds) for de-duplication linkages. Linkage quality was determined by F-measure. Each dataset was privacy-preserved using separate Bloom filters for each field. Match probabilities were estimated using the expectation-maximisation (EM) algorithm on the privacy-preserved data. Threshold cut-off values were determined by an extension to the EM algorithm allowing linkage quality to be estimated for each possible threshold. De-duplication linkages of each privacy-preserved dataset were performed using both estimated and calculated probabilities. Linkage quality using the F-measure at the estimated threshold values was also compared to the highest F-measure. Three large administrative datasets were used to demonstrate the applicability of the probability and threshold estimation technique on real-world data. Linkage of the synthetic datasets using the estimated probabilities produced an F-measure that was comparable to the F-measure using calculated probabilities, even with up to 20% error. Linkage of the administrative datasets using estimated probabilities produced an F-measure that was higher
Estimation of economic parameters of U.S. hydropower resources
Energy Technology Data Exchange (ETDEWEB)
Hall, Douglas G. [Idaho National Lab. (INL), Idaho Falls, ID (United States). Idaho National Engineering and Environmental Lab. (INEEL); Hunt, Richard T. [Idaho National Lab. (INL), Idaho Falls, ID (United States). Idaho National Engineering and Environmental Lab. (INEEL); Reeves, Kelly S. [Idaho National Lab. (INL), Idaho Falls, ID (United States). Idaho National Engineering and Environmental Lab. (INEEL); Carroll, Greg R. [Idaho National Lab. (INL), Idaho Falls, ID (United States). Idaho National Engineering and Environmental Lab. (INEEL)
2003-06-01
Tools for estimating the cost of developing and operating and maintaining hydropower resources in the form of regression curves were developed based on historical plant data. Development costs that were addressed included: licensing, construction, and five types of environmental mitigation. It was found that the data for each type of cost correlated well with plant capacity. A tool for estimating the annual and monthly electric generation of hydropower resources was also developed. Additional tools were developed to estimate the cost of upgrading a turbine or a generator. The development and operation and maintenance cost estimating tools, and the generation estimating tool were applied to 2,155 U.S. hydropower sites representing a total potential capacity of 43,036 MW. The sites included totally undeveloped sites, dams without a hydroelectric plant, and hydroelectric plants that could be expanded to achieve greater capacity. Site characteristics and estimated costs and generation for each site were assembled in a database in Excel format that is also included within the EERE Library under the title, “Estimation of Economic Parameters of U.S. Hydropower Resources - INL Hydropower Resource Economics Database.”
Aryan, H.; Yearby, K.; Balikhin, M. A.; Krasnoselskikh, V.; Agapitov, O. V.
2013-12-01
The interaction of gyroresonant wave particles with chorus waves largely determine the dynamics of the Earth's radiation belts that effects the acceleration and loss of radiation belt electrons. The common approach is to present model waves distribution in the inner magnetosphere under different values of geomagnetic activity as expressed by the geomagnetic indices. However it is known that solar wind parameters such as bulk velocity (V) and density (n) are more effective in the control of high energy fluxes at the geostationary orbit. Therefore in the present study the set of parameters of the wave distribution is expanded to include the solar wind parameters in addition to the geomagnetic indices. The present study examines almost four years (01, January, 2004 to 29, September, 2007) of Cluster STAFF-SA, Double Star TC1 and OMNI data in order to present a combined model of wave magnetic field intensities for the chorus waves as a function of magnetic local time (MLT), L-shell (L*), geomagnetic activity, and solar wind velocity and density. Generally, the largest wave intensities are observed during average solar wind velocities (3006cm-3. On the other hand the wave intensity is lower and limited between 06:00 to 18:00 MLT for V700kms-1.
Basic Earth's Parameters as estimated from VLBI observations
Directory of Open Access Journals (Sweden)
Ping Zhu
2017-11-01
Full Text Available The global Very Long Baseline Interferometry observation for measuring the Earth rotation's parameters was launched around 1970s. Since then the precision of the measurements is continuously improving by taking into account various instrumental and environmental effects. The MHB2000 nutation model was introduced in 2002, which is constructed based on a revised nutation series derived from 20 years VLBI observations (1980–1999. In this work, we firstly estimated the amplitudes of all nutation terms from the IERS-EOP-C04 VLBI global solutions w.r.t. IAU1980, then we further inferred the BEPs (Basic Earth's Parameters by fitting the major nutation terms. Meanwhile, the BEPs were obtained from the same nutation time series using a BI (Bayesian Inversion. The corrections to the precession rate and the estimated BEPs are in an agreement, independent of which methods have been applied.
CosmoSIS: A System for MC Parameter Estimation
Energy Technology Data Exchange (ETDEWEB)
Zuntz, Joe [Manchester U.; Paterno, Marc [Fermilab; Jennings, Elise [Chicago U., EFI; Rudd, Douglas [U. Chicago; Manzotti, Alessandro [Chicago U., Astron. Astrophys. Ctr.; Dodelson, Scott [Chicago U., Astron. Astrophys. Ctr.; Bridle, Sarah [Manchester U.; Sehrish, Saba [Fermilab; Kowalkowski, James [Fermilab
2015-01-01
Cosmological parameter estimation is entering a new era. Large collaborations need to coordinate high-stakes analyses using multiple methods; furthermore such analyses have grown in complexity due to sophisticated models of cosmology and systematic uncertainties. In this paper we argue that modularity is the key to addressing these challenges: calculations should be broken up into interchangeable modular units with inputs and outputs clearly defined. We present a new framework for cosmological parameter estimation, CosmoSIS, designed to connect together, share, and advance development of inference tools across the community. We describe the modules already available in Cosmo- SIS, including camb, Planck, cosmic shear calculations, and a suite of samplers. We illustrate it using demonstration code that you can run out-of-the-box with the installer available at http://bitbucket.org/joezuntz/cosmosis.
Probabilistic estimation of the constitutive parameters of polymers
Directory of Open Access Journals (Sweden)
Siviour C.R.
2012-08-01
Full Text Available The Mulliken-Boyce constitutive model predicts the dynamic response of crystalline polymers as a function of strain rate and temperature. This paper describes the Mulliken-Boyce model-based estimation of the constitutive parameters in a Bayesian probabilistic framework. Experimental data from dynamic mechanical analysis and dynamic compression of PVC samples over a wide range of strain rates are analyzed. Both experimental uncertainty and natural variations in the material properties are simultaneously considered as independent and joint distributions; the posterior probability distributions are shown and compared with prior estimates of the material constitutive parameters. Additionally, particular statistical distributions are shown to be effective at capturing the rate and temperature dependence of internal phase transitions in DMA data.
PARAMETER ESTIMATION OF THE HYBRID CENSORED LOMAX DISTRIBUTION
Directory of Open Access Journals (Sweden)
Samir Kamel Ashour
2010-12-01
Full Text Available Survival analysis is used in various fields for analyzing data involving the duration between two events. It is also known as event history analysis, lifetime data analysis, reliability analysis or time to event analysis. One of the difficulties which arise in this area is the presence of censored data. The lifetime of an individual is censored when it cannot be exactly measured but partial information is available. Different circumstances can produce different types of censoring. The two most common censoring schemes used in life testing experiments are Type-I and Type-II censoring schemes. Hybrid censoring scheme is mixture of Type-I and Type-II censoring scheme. In this paper we consider the estimation of parameters of Lomax distribution based on hybrid censored data. The parameters are estimated by the maximum likelihood and Bayesian methods. The Fisher information matrix has been obtained and it can be used for constructing asymptotic confidence intervals.
On Using Exponential Parameter Estimators with an Adaptive Controller
Patre, Parag; Joshi, Suresh M.
2011-01-01
Typical adaptive controllers are restricted to using a specific update law to generate parameter estimates. This paper investigates the possibility of using any exponential parameter estimator with an adaptive controller such that the system tracks a desired trajectory. The goal is to provide flexibility in choosing any update law suitable for a given application. The development relies on a previously developed concept of controller/update law modularity in the adaptive control literature, and the use of a converse Lyapunov-like theorem. Stability analysis is presented to derive gain conditions under which this is possible, and inferences are made about the tracking error performance. The development is based on a class of Euler-Lagrange systems that are used to model various engineering systems including space robots and manipulators.
Propagation channel characterization, parameter estimation, and modeling for wireless communications
Yin, Xuefeng
2016-01-01
Thoroughly covering channel characteristics and parameters, this book provides the knowledge needed to design various wireless systems, such as cellular communication systems, RFID and ad hoc wireless communication systems. It gives a detailed introduction to aspects of channels before presenting the novel estimation and modelling techniques which can be used to achieve accurate models. To systematically guide readers through the topic, the book is organised in three distinct parts. The first part covers the fundamentals of the characterization of propagation channels, including the conventional single-input single-output (SISO) propagation channel characterization as well as its extension to multiple-input multiple-output (MIMO) cases. Part two focuses on channel measurements and channel data post-processing. Wideband channel measurements are introduced, including the equipment, technology and advantages and disadvantages of different data acquisition schemes. The channel parameter estimation methods are ...
Estimation of solid earth tidal parameters and FCN with VLBI
International Nuclear Information System (INIS)
Krásná, H.
2012-01-01
Measurements of a space-geodetic technique VLBI (Very Long Baseline Interferometry) are influenced by a variety of processes which have to be modelled and put as a priori information into the analysis of the space-geodetic data. The increasing accuracy of the VLBI measurements allows access to these parameters and provides possibilities to validate them directly from the measured data. The gravitational attraction of the Moon and the Sun causes deformation of the Earth's surface which can reach several decimetres in radial direction during a day. The displacement is a function of the so-called Love and Shida numbers. Due to the present accuracy of the VLBI measurements the parameters have to be specified as complex numbers, where the imaginary parts describe the anelasticity of the Earth's mantle. Moreover, it is necessary to distinguish between the single tides within the various frequency bands. In this thesis, complex Love and Shida numbers of twelve diurnal and five long-period tides included in the solid Earth tidal displacement modelling are estimated directly from the 27 years of VLBI measurements (1984.0 - 2011.0). In this work, the period of the Free Core Nutation (FCN) is estimated which shows up in the frequency dependent solid Earth tidal displacement as well as in a nutation model describing the motion of the Earth's axis in space. The FCN period in both models is treated as a single parameter and it is estimated in a rigorous global adjustment of the VLBI data. The obtained value of -431.18 ± 0.10 sidereal days differs slightly from the conventional value -431.39 sidereal days given in IERS Conventions 2010. An empirical FCN model based on variable amplitude and phase is determined, whose parameters are estimated in yearly steps directly within VLBI global solutions. (author) [de
Estimation of parameters of interior permanent magnet synchronous motors
International Nuclear Information System (INIS)
Hwang, C.C.; Chang, S.M.; Pan, C.T.; Chang, T.Y.
2002-01-01
This paper presents a magnetic circuit model to the estimation of machine parameters of an interior permanent magnet synchronous machine. It extends the earlier work of Hwang and Cho that focused mainly on the magnetic aspects of motor design. The proposed model used to calculate EMF, d- and q-axis reactances. These calculations are compared to those from finite element analysis and measurement with good agreement
Estimation of parameters of interior permanent magnet synchronous motors
Hwang, C C; Pan, C T; Chang, T Y
2002-01-01
This paper presents a magnetic circuit model to the estimation of machine parameters of an interior permanent magnet synchronous machine. It extends the earlier work of Hwang and Cho that focused mainly on the magnetic aspects of motor design. The proposed model used to calculate EMF, d- and q-axis reactances. These calculations are compared to those from finite element analysis and measurement with good agreement.
Factorized Estimation of Partially Shared Parameters in Diffusion Networks
Czech Academy of Sciences Publication Activity Database
Dedecius, Kamil; Sečkárová, Vladimíra
2017-01-01
Roč. 65, č. 19 (2017), s. 5153-5163 ISSN 1053-587X R&D Projects: GA ČR(CZ) GP14-06678P; GA ČR GA16-09848S Institutional support: RVO:67985556 Keywords : Diffusion network * Diffusion estimation * Heterogeneous parameters * Multitask networks Subject RIV: BD - Theory of Information OBOR OECD: Applied mathematics Impact factor: 4.300, year: 2016 http://library.utia.cas.cz/separaty/2017/AS/dedecius-0477044.pdf
Directory of Open Access Journals (Sweden)
Akatsuki eKimura
2015-03-01
Full Text Available Construction of quantitative models is a primary goal of quantitative biology, which aims to understand cellular and organismal phenomena in a quantitative manner. In this article, we introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. The aim of optimization is to minimize the sum of squared errors (SSE in a prediction or to maximize likelihood. A (local maximum of likelihood or (local minimum of the SSE can efficiently be identified using gradient approaches. Addition of a stochastic process enables us to identify the global maximum/minimum without becoming trapped in local maxima/minima. Sampling approaches take advantage of increasing computational power to test numerous sets of parameters in order to determine the optimum set. By combining Bayesian inference with gradient or sampling approaches, we can estimate both the optimum parameters and the form of the likelihood function related to the parameters. Finally, we introduce four examples of research that utilize parameter optimization to obtain biological insights from quantified data: transcriptional regulation, bacterial chemotaxis, morphogenesis, and cell cycle regulation. With practical knowledge of parameter optimization, cell and developmental biologists can develop realistic models that reproduce their observations and thus, obtain mechanistic insights into phenomena of interest.
Analysis of the wind data and estimation of the resultant air concentration rates
International Nuclear Information System (INIS)
Hu, Shze Jer; Katagiri, Hiroshi; Kobayashi, Hideo
1988-09-01
Statistical analyses and comparisons of the meteorological wind data obtained by the propeller and supersonic anemometers for the year of 1987 in the Japan Atomic Energy Research Institute, Tokai, were performed. For wind speeds less than 1 m/s, the propeller readings are generally 0.5 m/s less than those of the supersonic readings. The resultant average air concentration and ground level γ exposure rates due to the radioactive releases for the normal operation of a nuclear plant are over-estimated when calculated using the propeller wind data. As supersonic anemometer can give accurate wind speed to as low as 0.01 m/s, it should be used to measure the low wind speed. The difference in the average air concentrations and γ exposure rates calculated using the two different sets of wind data, is due to the influence of low wind speeds at calm. If the number at calm is large, actual low wind speeds and wind directions should be used in the statistical analysis of atmospheric dispersion to give a more accurate and realistic estimation of the air concentrations and γ exposure rates due to the normal operation of a nuclear plant. (author). 4 refs, 3 figs, 9 tabs
Model parameters estimation and sensitivity by genetic algorithms
International Nuclear Information System (INIS)
Marseguerra, Marzio; Zio, Enrico; Podofillini, Luca
2003-01-01
In this paper we illustrate the possibility of extracting qualitative information on the importance of the parameters of a model in the course of a Genetic Algorithms (GAs) optimization procedure for the estimation of such parameters. The Genetic Algorithms' search of the optimal solution is performed according to procedures that resemble those of natural selection and genetics: an initial population of alternative solutions evolves within the search space through the four fundamental operations of parent selection, crossover, replacement, and mutation. During the search, the algorithm examines a large amount of solution points which possibly carries relevant information on the underlying model characteristics. A possible utilization of this information amounts to create and update an archive with the set of best solutions found at each generation and then to analyze the evolution of the statistics of the archive along the successive generations. From this analysis one can retrieve information regarding the speed of convergence and stabilization of the different control (decision) variables of the optimization problem. In this work we analyze the evolution strategy followed by a GA in its search for the optimal solution with the aim of extracting information on the importance of the control (decision) variables of the optimization with respect to the sensitivity of the objective function. The study refers to a GA search for optimal estimates of the effective parameters in a lumped nuclear reactor model of literature. The supporting observation is that, as most optimization procedures do, the GA search evolves towards convergence in such a way to stabilize first the most important parameters of the model and later those which influence little the model outputs. In this sense, besides estimating efficiently the parameters values, the optimization approach also allows us to provide a qualitative ranking of their importance in contributing to the model output. The
Real-time Wind Profile Estimation using Airborne Sensors
In 't Veld, A.C.; De Jong, P.M.A.; Van Paassen, M.M.; Mulder, M.
2011-01-01
Wind is one of the major contributors to uncertainty in continuous descent approach operations. Especially when aircraft that are flying low or idle thrust approaches are issued a required time of arrival over the runway threshold, as is foreseen in some of the future ATC scenarios, the on-board
Estimation of wind power potential of the Gulf of Finland
DEFF Research Database (Denmark)
Monzikova, Anna K.; Kudryavtsev, V.N.; Larsen, Søren Ejling
2013-01-01
An assessment of wind power potential of the eastern part of the Gulf of Finland and its seasonal variations are presented. Measurements taken from meteorological stations around the coastline are used as the input data. Calculations are based on the similarity theory for the atmospheric planetar...
Estimation of power system variability due to wind power
Papaefthymiou, G.; Verboomen, J.; Van der Sluis, L.
2007-01-01
The incorporation of wind power generation to the power system leads to an increase in the variability of the system power flows. The assessment of this variability is necessary for the planning of the necessary system reinforcements. For the assessment of this variability, the uncertainty in the
Hybrid fault diagnosis of nonlinear systems using neural parameter estimators.
Sobhani-Tehrani, E; Talebi, H A; Khorasani, K
2014-02-01
This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems taking advantage of both the system's mathematical model and the adaptive nonlinear approximation capability of computational intelligence techniques. Unlike most FD techniques, the proposed solution simultaneously accomplishes fault detection, isolation, and identification (FDII) within a unified diagnostic module. At the core of this solution is a bank of adaptive neural parameter estimators (NPEs) associated with a set of single-parameter fault models. The NPEs continuously estimate unknown fault parameters (FPs) that are indicators of faults in the system. Two NPE structures, series-parallel and parallel, are developed with their exclusive set of desirable attributes. The parallel scheme is extremely robust to measurement noise and possesses a simpler, yet more solid, fault isolation logic. In contrast, the series-parallel scheme displays short FD delays and is robust to closed-loop system transients due to changes in control commands. Finally, a fault tolerant observer (FTO) is designed to extend the capability of the two NPEs that originally assumes full state measurements for systems that have only partial state measurements. The proposed FTO is a neural state estimator that can estimate unmeasured states even in the presence of faults. The estimated and the measured states then comprise the inputs to the two proposed FDII schemes. Simulation results for FDII of reaction wheels of a three-axis stabilized satellite in the presence of disturbances and noise demonstrate the effectiveness of the proposed FDII solutions under partial state measurements. Copyright © 2013 Elsevier Ltd. All rights reserved.
Effects of parameter estimation on maximum-likelihood bootstrap analysis.
Ripplinger, Jennifer; Abdo, Zaid; Sullivan, Jack
2010-08-01
Bipartition support in maximum-likelihood (ML) analysis is most commonly assessed using the nonparametric bootstrap. Although bootstrap replicates should theoretically be analyzed in the same manner as the original data, model selection is almost never conducted for bootstrap replicates, substitution-model parameters are often fixed to their maximum-likelihood estimates (MLEs) for the empirical data, and bootstrap replicates may be subjected to less rigorous heuristic search strategies than the original data set. Even though this approach may increase computational tractability, it may also lead to the recovery of suboptimal tree topologies and affect bootstrap values. However, since well-supported bipartitions are often recovered regardless of method, use of a less intensive bootstrap procedure may not significantly affect the results. In this study, we investigate the impact of parameter estimation (i.e., assessment of substitution-model parameters and tree topology) on ML bootstrap analysis. We find that while forgoing model selection and/or setting substitution-model parameters to their empirical MLEs may lead to significantly different bootstrap values, it probably would not change their biological interpretation. Similarly, even though the use of reduced search methods often results in significant differences among bootstrap values, only omitting branch swapping is likely to change any biological inferences drawn from the data. Copyright 2010 Elsevier Inc. All rights reserved.
Genetic Algorithm-based Affine Parameter Estimation for Shape Recognition
Directory of Open Access Journals (Sweden)
Yuxing Mao
2014-06-01
Full Text Available Shape recognition is a classically difficult problem because of the affine transformation between two shapes. The current study proposes an affine parameter estimation method for shape recognition based on a genetic algorithm (GA. The contributions of this study are focused on the extraction of affine-invariant features, the individual encoding scheme, and the fitness function construction policy for a GA. First, the affine-invariant characteristics of the centroid distance ratios (CDRs of any two opposite contour points to the barycentre are analysed. Using different intervals along the azimuth angle, the different numbers of CDRs of two candidate shapes are computed as representations of the shapes, respectively. Then, the CDRs are selected based on predesigned affine parameters to construct the fitness function. After that, a GA is used to search for the affine parameters with optimal matching between candidate shapes, which serve as actual descriptions of the affine transformation between the shapes. Finally, the CDRs are resampled based on the estimated parameters to evaluate the similarity of the shapes for classification. The experimental results demonstrate the robust performance of the proposed method in shape recognition with translation, scaling, rotation and distortion.
Cross-hole Radio Imaging Method with Radiation Parameters Estimation
Ou, Y.; Feng, J.; Li, Y.; Jia, D.; Gao, W.
2017-12-01
To avoid distortions of the radiation pattern and source strength correction, the ray-based amplitude tomography with radiation parameters estimation for cross-hole radio-frequency electromagnetic data has been presented. It has been indicated by the numerical simulations from finite difference time domain (FDTD) method that the radiation pattern and source strength have been seriously affected by the electric material parameters along the borehole, which cannot be corrected accurately. Therefore, the radiation pattern and source strength are treated as unknown parameters with the assumption that radiation pattern changes with the ray angle and the source strength varies with the position of transmitter. The inversion algorithm applies Tikhonov regularization and imposes a variance constraint on the source strength to make the results consistent with the geological features of the boreholes revealed. The results from estimation of these radiation parameters and attenuation simultaneously have shown that an improvement in resolution of anomalies over traditional amplitude tomography can be achieved by the proposed method.
Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks
Kaltenbacher, Barbara; Hasenauer, Jan
2017-01-01
Mechanistic mathematical modeling of biochemical reaction networks using ordinary differential equation (ODE) models has improved our understanding of small- and medium-scale biological processes. While the same should in principle hold for large- and genome-scale processes, the computational methods for the analysis of ODE models which describe hundreds or thousands of biochemical species and reactions are missing so far. While individual simulations are feasible, the inference of the model parameters from experimental data is computationally too intensive. In this manuscript, we evaluate adjoint sensitivity analysis for parameter estimation in large scale biochemical reaction networks. We present the approach for time-discrete measurement and compare it to state-of-the-art methods used in systems and computational biology. Our comparison reveals a significantly improved computational efficiency and a superior scalability of adjoint sensitivity analysis. The computational complexity is effectively independent of the number of parameters, enabling the analysis of large- and genome-scale models. Our study of a comprehensive kinetic model of ErbB signaling shows that parameter estimation using adjoint sensitivity analysis requires a fraction of the computation time of established methods. The proposed method will facilitate mechanistic modeling of genome-scale cellular processes, as required in the age of omics. PMID:28114351
Impact of relativistic effects on cosmological parameter estimation
Lorenz, Christiane S.; Alonso, David; Ferreira, Pedro G.
2018-01-01
Future surveys will access large volumes of space and hence very long wavelength fluctuations of the matter density and gravitational field. It has been argued that the set of secondary effects that affect the galaxy distribution, relativistic in nature, will bring new, complementary cosmological constraints. We study this claim in detail by focusing on a subset of wide-area future surveys: Stage-4 cosmic microwave background experiments and photometric redshift surveys. In particular, we look at the magnification lensing contribution to galaxy clustering and general-relativistic corrections to all observables. We quantify the amount of information encoded in these effects in terms of the tightening of the final cosmological constraints as well as the potential bias in inferred parameters associated with neglecting them. We do so for a wide range of cosmological parameters, covering neutrino masses, standard dark-energy parametrizations and scalar-tensor gravity theories. Our results show that, while the effect of lensing magnification to number counts does not contain a significant amount of information when galaxy clustering is combined with cosmic shear measurements, this contribution does play a significant role in biasing estimates on a host of parameter families if unaccounted for. Since the amplitude of the magnification term is controlled by the slope of the source number counts with apparent magnitude, s (z ), we also estimate the accuracy to which this quantity must be known to avoid systematic parameter biases, finding that future surveys will need to determine s (z ) to the ˜5 %- 10 % level. On the contrary, large-scale general-relativistic corrections are irrelevant both in terms of information content and parameter bias for most cosmological parameters but significant for the level of primordial non-Gaussianity.
Basic MR sequence parameters systematically bias automated brain volume estimation
International Nuclear Information System (INIS)
Haller, Sven; Falkovskiy, Pavel; Roche, Alexis; Marechal, Benedicte; Meuli, Reto; Thiran, Jean-Philippe; Krueger, Gunnar; Lovblad, Karl-Olof; Kober, Tobias
2016-01-01
Automated brain MRI morphometry, including hippocampal volumetry for Alzheimer disease, is increasingly recognized as a biomarker. Consequently, a rapidly increasing number of software tools have become available. We tested whether modifications of simple MR protocol parameters typically used in clinical routine systematically bias automated brain MRI segmentation results. The study was approved by the local ethical committee and included 20 consecutive patients (13 females, mean age 75.8 ± 13.8 years) undergoing clinical brain MRI at 1.5 T for workup of cognitive decline. We compared three 3D T1 magnetization prepared rapid gradient echo (MPRAGE) sequences with the following parameter settings: ADNI-2 1.2 mm iso-voxel, no image filtering, LOCAL- 1.0 mm iso-voxel no image filtering, LOCAL+ 1.0 mm iso-voxel with image edge enhancement. Brain segmentation was performed by two different and established analysis tools, FreeSurfer and MorphoBox, using standard parameters. Spatial resolution (1.0 versus 1.2 mm iso-voxel) and modification in contrast resulted in relative estimated volume difference of up to 4.28 % (p < 0.001) in cortical gray matter and 4.16 % (p < 0.01) in hippocampus. Image data filtering resulted in estimated volume difference of up to 5.48 % (p < 0.05) in cortical gray matter. A simple change of MR parameters, notably spatial resolution, contrast, and filtering, may systematically bias results of automated brain MRI morphometry of up to 4-5 %. This is in the same range as early disease-related brain volume alterations, for example, in Alzheimer disease. Automated brain segmentation software packages should therefore require strict MR parameter selection or include compensatory algorithms to avoid MR parameter-related bias of brain morphometry results. (orig.)
Basic MR sequence parameters systematically bias automated brain volume estimation
Energy Technology Data Exchange (ETDEWEB)
Haller, Sven [University of Geneva, Faculty of Medicine, Geneva (Switzerland); Affidea Centre de Diagnostique Radiologique de Carouge CDRC, Geneva (Switzerland); Falkovskiy, Pavel; Roche, Alexis; Marechal, Benedicte [Siemens Healthcare HC CEMEA SUI DI BM PI, Advanced Clinical Imaging Technology, Lausanne (Switzerland); University Hospital (CHUV), Department of Radiology, Lausanne (Switzerland); Meuli, Reto [University Hospital (CHUV), Department of Radiology, Lausanne (Switzerland); Thiran, Jean-Philippe [LTS5, Ecole Polytechnique Federale de Lausanne, Lausanne (Switzerland); Krueger, Gunnar [Siemens Medical Solutions USA, Inc., Boston, MA (United States); Lovblad, Karl-Olof [University of Geneva, Faculty of Medicine, Geneva (Switzerland); University Hospitals of Geneva, Geneva (Switzerland); Kober, Tobias [Siemens Healthcare HC CEMEA SUI DI BM PI, Advanced Clinical Imaging Technology, Lausanne (Switzerland); LTS5, Ecole Polytechnique Federale de Lausanne, Lausanne (Switzerland)
2016-11-15
Automated brain MRI morphometry, including hippocampal volumetry for Alzheimer disease, is increasingly recognized as a biomarker. Consequently, a rapidly increasing number of software tools have become available. We tested whether modifications of simple MR protocol parameters typically used in clinical routine systematically bias automated brain MRI segmentation results. The study was approved by the local ethical committee and included 20 consecutive patients (13 females, mean age 75.8 ± 13.8 years) undergoing clinical brain MRI at 1.5 T for workup of cognitive decline. We compared three 3D T1 magnetization prepared rapid gradient echo (MPRAGE) sequences with the following parameter settings: ADNI-2 1.2 mm iso-voxel, no image filtering, LOCAL- 1.0 mm iso-voxel no image filtering, LOCAL+ 1.0 mm iso-voxel with image edge enhancement. Brain segmentation was performed by two different and established analysis tools, FreeSurfer and MorphoBox, using standard parameters. Spatial resolution (1.0 versus 1.2 mm iso-voxel) and modification in contrast resulted in relative estimated volume difference of up to 4.28 % (p < 0.001) in cortical gray matter and 4.16 % (p < 0.01) in hippocampus. Image data filtering resulted in estimated volume difference of up to 5.48 % (p < 0.05) in cortical gray matter. A simple change of MR parameters, notably spatial resolution, contrast, and filtering, may systematically bias results of automated brain MRI morphometry of up to 4-5 %. This is in the same range as early disease-related brain volume alterations, for example, in Alzheimer disease. Automated brain segmentation software packages should therefore require strict MR parameter selection or include compensatory algorithms to avoid MR parameter-related bias of brain morphometry results. (orig.)
Chloramine demand estimation using surrogate chemical and microbiological parameters.
Moradi, Sina; Liu, Sanly; Chow, Christopher W K; van Leeuwen, John; Cook, David; Drikas, Mary; Amal, Rose
2017-07-01
A model is developed to enable estimation of chloramine demand in full scale drinking water supplies based on chemical and microbiological factors that affect chloramine decay rate via nonlinear regression analysis method. The model is based on organic character (specific ultraviolet absorbance (SUVA)) of the water samples and a laboratory measure of the microbiological (F m ) decay of chloramine. The applicability of the model for estimation of chloramine residual (and hence chloramine demand) was tested on several waters from different water treatment plants in Australia through statistical test analysis between the experimental and predicted data. Results showed that the model was able to simulate and estimate chloramine demand at various times in real drinking water systems. To elucidate the loss of chloramine over the wide variation of water quality used in this study, the model incorporates both the fast and slow chloramine decay pathways. The significance of estimated fast and slow decay rate constants as the kinetic parameters of the model for three water sources in Australia was discussed. It was found that with the same water source, the kinetic parameters remain the same. This modelling approach has the potential to be used by water treatment operators as a decision support tool in order to manage chloramine disinfection. Copyright © 2017. Published by Elsevier B.V.
International Nuclear Information System (INIS)
Kaldellis, J.K.; Kapsali, M.; Tiligadas, D.
2012-01-01
Highlights: ► This study estimates the maximum wind energy contribution to an isolated micro-grid. ► An integrated computational tool is developed on the basis of stochastic analysis. ► The probability distribution of the wind energy surplus and deficit is estimated. ► The results indicate that a strict penetration limit is imposed to wind energy. -- Abstract: The electrification in remote islands whose electricity distribution network is not connected to the mainland’s grid is mostly based on Autonomous Power Stations (APSs) that are usually characterized by a considerably high electricity production cost, while at the same time the contribution of Renewable Energy Sources (RES) in these regions accounts for less than 10% of the total electricity generation. This actually results from the fact that despite the excellent wind potential of most of these islands, the wind energy contribution is significantly restricted from limits imposed to protect the remote electrical grids from possible instability problems, due to the stochastic wind speed behavior and the variable electricity consumption. On the basis of probability distribution of the load demand of a representative Greek island and the corresponding data related to the available wind potential, the present study estimates the maximum – acceptable by the local grid – wind energy contribution. For that reason, an integrated computational algorithm has been developed from first principles, based on a stochastic analysis. According to the results obtained, it becomes evident that with the current wind turbine technology, wind energy cannot play a key role in coping with the electrification problems encountered in many Greek island regions, excluding however the case of introducing bulk energy storage systems that may provide considerable recovery of the remarkable wind energy rejections expected.
Energy Technology Data Exchange (ETDEWEB)
Howard, S. M.; Chen, P. C.
1978-03-01
To achieve the DOE goal of placing the most economically viable wind energy conversion system at a site, it becomes necessary to determine the accuracy of the climatology development technique, and to determine the extent of its applicability to sites of differing geographic settings and data station locations. To achieve this goal, the Climatology Development Methodology was applied to eight candidate wind energy sites of differing site geographic settings and data station locations. The performance of the methodology was evaluated by examining the accuracy of the hub-height wind climatologies generated for each type of site and station geographic setting. The validity of the site wind climatology for a given setting helped establish the accuracy of the Climatology Development Methodology and the extent of its applicability. The Climatology Development Methodology developed in this study is presented and the techniques of the methodology discussed. Also presented are the eight candidate site hub-height wind climatologies generated, and a description of each site's geographic setting and data station proximity. The report concludes with an evaluation of the Climatology Development Methodology and a discussion of the study's conclusions and recommendations.
DEFF Research Database (Denmark)
Larsén, Xiaoli Guo; Ott, Søren; Badger, Jake
2012-01-01
Extreme winds derived from simulations using mesoscale models are underestimated due to the effective spatial and temporal resolutions. This is reflected in the spectral domain as an energy deficit in the mesoscale range. The energy deficit implies smaller spectral moments and thus underestimation...... in the extreme winds. We have developed two approaches for correcting the smoothing effect resulting from the mesoscale model resolution on the extreme wind estimation by taking into account the difference between the modeled and measured spectra in the high frequency range. Both approaches give estimates...... of the smoothing effect in good agreement with measurements from several sites in Denmark and Germany....
Reliability/Cost Evaluation on Power System connected with Wind Power for the Reserve Estimation
DEFF Research Database (Denmark)
Lee, Go-Eun; Cha, Seung-Tae; Shin, Je-Seok
2012-01-01
Wind power is ideally a renewable energy with no fuel cost, but has a risk to reduce reliability of the whole system because of uncertainty of the output. If the reserve of the system is increased, the reliability of the system may be improved. However, the cost would be increased. Therefore...... the reserve needs to be estimated considering the trade-off between reliability and economic aspects. This paper suggests a methodology to estimate the appropriate reserve, when wind power is connected to the power system. As a case study, when wind power is connected to power system of Korea, the effects...
Biases on cosmological parameter estimators from galaxy cluster number counts
International Nuclear Information System (INIS)
Penna-Lima, M.; Wuensche, C.A.; Makler, M.
2014-01-01
Sunyaev-Zel'dovich (SZ) surveys are promising probes of cosmology — in particular for Dark Energy (DE) —, given their ability to find distant clusters and provide estimates for their mass. However, current SZ catalogs contain tens to hundreds of objects and maximum likelihood estimators may present biases for such sample sizes. In this work we study estimators from cluster abundance for some cosmological parameters, in particular the DE equation of state parameter w 0 , the amplitude of density fluctuations σ 8 , and the Dark Matter density parameter Ω c . We begin by deriving an unbinned likelihood for cluster number counts, showing that it is equivalent to the one commonly used in the literature. We use the Monte Carlo approach to determine the presence of bias using this likelihood and study its behavior with both the area and depth of the survey, and the number of cosmological parameters fitted. Our fiducial models are based on the South Pole Telescope (SPT) SZ survey. Assuming perfect knowledge of mass and redshift some estimators have non-negligible biases. For example, the bias of σ 8 corresponds to about 40% of its statistical error bar when fitted together with Ω c and w 0 . Including a SZ mass-observable relation decreases the relevance of the bias, for the typical sizes of current SZ surveys. Considering a joint likelihood for cluster abundance and the so-called ''distance priors'', we obtain that the biases are negligible compared to the statistical errors. However, we show that the biases from SZ estimators do not go away with increasing sample sizes and they may become the dominant source of error for an all sky survey at the SPT sensitivity. Finally, we compute the confidence regions for the cosmological parameters using Fisher matrix and profile likelihood approaches, showing that they are compatible with the Monte Carlo ones. The results of this work validate the use of the current maximum likelihood methods for
Combined Estimation of Hydrogeologic Conceptual Model and Parameter Uncertainty
Energy Technology Data Exchange (ETDEWEB)
Meyer, Philip D.; Ye, Ming; Neuman, Shlomo P.; Cantrell, Kirk J.
2004-03-01
The objective of the research described in this report is the development and application of a methodology for comprehensively assessing the hydrogeologic uncertainties involved in dose assessment, including uncertainties associated with conceptual models, parameters, and scenarios. This report describes and applies a statistical method to quantitatively estimate the combined uncertainty in model predictions arising from conceptual model and parameter uncertainties. The method relies on model averaging to combine the predictions of a set of alternative models. Implementation is driven by the available data. When there is minimal site-specific data the method can be carried out with prior parameter estimates based on generic data and subjective prior model probabilities. For sites with observations of system behavior (and optionally data characterizing model parameters), the method uses model calibration to update the prior parameter estimates and model probabilities based on the correspondence between model predictions and site observations. The set of model alternatives can contain both simplified and complex models, with the requirement that all models be based on the same set of data. The method was applied to the geostatistical modeling of air permeability at a fractured rock site. Seven alternative variogram models of log air permeability were considered to represent data from single-hole pneumatic injection tests in six boreholes at the site. Unbiased maximum likelihood estimates of variogram and drift parameters were obtained for each model. Standard information criteria provided an ambiguous ranking of the models, which would not justify selecting one of them and discarding all others as is commonly done in practice. Instead, some of the models were eliminated based on their negligibly small updated probabilities and the rest were used to project the measured log permeabilities by kriging onto a rock volume containing the six boreholes. These four
Finite Sample Corrections for Parameters Estimation and Significance Testing
Directory of Open Access Journals (Sweden)
Boon Kin Teh
2018-01-01
Full Text Available An increasingly important problem in the era of Big Data is fitting data to distributions. However, many stop at visually inspecting the fits or use the coefficient of determination as a measure of the goodness of fit. In general, goodness-of-fit measures do not allow us to tell which of several distributions fit the data best. Also, the likelihood of drawing the data from a distribution can be low even when the fit is good. To overcome these limitations, Clauset et al. advocated a three-step procedure for fitting any distribution: (i estimate parameter(s accurately, (ii choosing and calculating an appropriate goodness of fit, (iii test its significance to determine how likely this goodness of fit will appear in samples of the distribution. When we perform this significance testing on exponential distributions, we often obtain low significance values despite the fits being visually good. This led to our realization that most fitting methods do not account for effects due to the finite number of elements and the finite largest element. The former produces sample size dependence in the goodness of fits and the latter introduces a bias in the estimated parameter and the goodness of fit. We propose modifications to account for both and show that these corrections improve the significance of the fits of both real and simulated data. In addition, we used simulations and analytical approximations to verify that convergence rate of the estimated parameters toward its true value depends on how fast the largest element converge to infinity, and provide fast inversion formulas to obtain p-values directly from the adjusted test statistics, in place of doing more Monte Carlo simulations.
Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems
Directory of Open Access Journals (Sweden)
Banga Julio R
2006-11-01
Full Text Available Abstract Background We consider the problem of parameter estimation (model calibration in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector. In order to surmount these difficulties, global optimization (GO methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness. Results We have developed a new procedure based on the scatter search methodology for nonlinear optimization of dynamic models of arbitrary (or even unknown structure (i.e. black-box models. In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned successful methods. Conclusion Robust and efficient methods for parameter estimation are of key importance in systems biology and related areas. The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values. This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously
Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems.
Rodriguez-Fernandez, Maria; Egea, Jose A; Banga, Julio R
2006-11-02
We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector). In order to surmount these difficulties, global optimization (GO) methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness. We have developed a new procedure based on the scatter search methodology for nonlinear optimization of dynamic models of arbitrary (or even unknown) structure (i.e. black-box models). In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned) successful methods. Robust and efficient methods for parameter estimation are of key importance in systems biology and related areas. The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values. This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously used for these benchmark problems.
Voicescu, Sonia A; Michaud, David S; Feder, Katya; Marro, Leonora; Than, John; Guay, Mireille; Denning, Allison; Bower, Tara; van den Berg, Frits; Broner, Norm; Lavigne, Eric
2016-03-01
The Community Noise and Health Study conducted by Health Canada included randomly selected participants aged 18-79 yrs (606 males, 632 females, response rate 78.9%), living between 0.25 and 11.22 km from operational wind turbines. Annoyance to wind turbine noise (WTN) and other features, including shadow flicker (SF) was assessed. The current analysis reports on the degree to which estimating high annoyance to wind turbine shadow flicker (HAWTSF) was improved when variables known to be related to WTN exposure were also considered. As SF exposure increased [calculated as maximum minutes per day (SFm)], HAWTSF increased from 3.8% at 0 ≤ SFm wind turbine-related features, concern for physical safety, and noise sensitivity. Reported dizziness was also retained in the final model at p = 0.0581. Study findings add to the growing science base in this area and may be helpful in identifying factors associated with community reactions to SF exposure from wind turbines.
DEFF Research Database (Denmark)
Sathe, Ameya
, as well as experimental evidence from different measurement campaigns at a test center in Denmark. Several measurement configurations from the commercial and research lidars are described along with mathematical formulations of estimated turbulence statistics and parameters for the respective......This report is prepared as a written contribution to the Remote Sensing Summer School, that is organized by the Department of Wind Energy, Technical University of Denmark. It provides an overview of the state-of-the-art with regards to estimating turbulence statistics from lidar measurements...... configuration. The so-called velocity Azimuth Display (VAD) and the Doppler Beam Swinging (DBS) methods of post processing the lidar data are investigated in greater details, partly due to their wide use in commercial lidars. It is demonstrated that the VAD or DBS techniques result in introducing significant...
Estimating Mass of Inflatable Aerodynamic Decelerators Using Dimensionless Parameters
Samareh, Jamshid A.
2011-01-01
This paper describes a technique for estimating mass for inflatable aerodynamic decelerators. The technique uses dimensional analysis to identify a set of dimensionless parameters for inflation pressure, mass of inflation gas, and mass of flexible material. The dimensionless parameters enable scaling of an inflatable concept with geometry parameters (e.g., diameter), environmental conditions (e.g., dynamic pressure), inflation gas properties (e.g., molecular mass), and mass growth allowance. This technique is applicable for attached (e.g., tension cone, hypercone, and stacked toroid) and trailing inflatable aerodynamic decelerators. The technique uses simple engineering approximations that were developed by NASA in the 1960s and 1970s, as well as some recent important developments. The NASA Mars Entry and Descent Landing System Analysis (EDL-SA) project used this technique to estimate the masses of the inflatable concepts that were used in the analysis. The EDL-SA results compared well with two independent sets of high-fidelity finite element analyses.
Statistical analysis of wind speed using two-parameter Weibull distribution in Alaçatı region
International Nuclear Information System (INIS)
Ozay, Can; Celiktas, Melih Soner
2016-01-01
Highlights: • Wind speed & direction data from September 2008 to March 2014 has been analyzed. • Mean wind speed for the whole data set has been found to be 8.11 m/s. • Highest wind speed is observed in July with a monthly mean value of 9.10 m/s. • Wind speed with the most energy has been calculated as 12.77 m/s. • Observed data has been fit to a Weibull distribution and k &c parameters have been calculated as 2.05 and 9.16. - Abstract: Weibull Statistical Distribution is a common method for analyzing wind speed measurements and determining wind energy potential. Weibull probability density function can be used to forecast wind speed, wind density and wind energy potential. In this study a two-parameter Weibull statistical distribution is used to analyze the wind characteristics of Alaçatı region, located in Çeşme, İzmir. The data used in the density function are acquired from a wind measurement station in Alaçatı. Measurements were gathered on three different heights respectively 70, 50 and 30 m between 10 min intervals for five and half years. As a result of this study; wind speed frequency distribution, wind direction trends, mean wind speed, and the shape and the scale (k&c) Weibull parameters have been calculated for the region. Mean wind speed for the entirety of the data set is found to be 8.11 m/s. k&c parameters are found as 2.05 and 9.16 in relative order. Wind direction analysis along with a wind rose graph for the region is also provided with the study. Analysis suggests that higher wind speeds which range from 6–12 m/s are prevalent between the sectors 340–360°. Lower wind speeds, from 3 to 6 m/s occur between sectors 10–29°. Results of this study contribute to the general knowledge about the regions wind energy potential and can be used as a source for investors and academics.
Estimation of Eruption Source Parameters from Plume Growth Rate
Pouget, Solene; Bursik, Marcus; Webley, Peter; Dehn, Jon; Pavalonis, Michael; Singh, Tarunraj; Singla, Puneet; Patra, Abani; Pitman, Bruce; Stefanescu, Ramona; Madankan, Reza; Morton, Donald; Jones, Matthew
2013-04-01
The eruption of Eyjafjallajokull, Iceland in April and May, 2010, brought to light the hazards of airborne volcanic ash and the importance of Volcanic Ash Transport and Dispersion models (VATD) to estimate the concentration of ash with time. These models require Eruption Source Parameters (ESP) as input, which typically include information about the plume height, the mass eruption rate, the duration of the eruption and the particle size distribution. However much of the time these ESP are unknown or poorly known a priori. We show that the mass eruption rate can be estimated from the downwind plume or umbrella cloud growth rate. A simple version of the continuity equation can be applied to the growth of either an umbrella cloud or the downwind plume. The continuity equation coupled with the momentum equation using only inertial and gravitational terms provides another model. Numerical modeling or scaling relationships can be used, as necessary, to provide values for unknown or unavailable parameters. Use of these models applied to data on plume geometry provided by satellite imagery allows for direct estimation of plume volumetric and mass growth with time. To test our methodology, we compared our results with five well-studied and well-characterized historical eruptions: Mount St. Helens, 1980; Pinatubo, 1991, Redoubt, 1990; Hekla, 2000 and Eyjafjallajokull, 2010. These tests show that the methodologies yield results comparable to or better than currently accepted methodologies of ESP estimation. We then applied the methodology to umbrella clouds produced by the eruptions of Okmok, 12 July 2008, and Sarychev Peak, 12 June 2009, and to the downwind plume produced by the eruptions of Hekla, 2000; Kliuchevsko'i, 1 October 1994; Kasatochi 7-8 August 2008 and Bezymianny, 1 September 2012. The new methods allow a fast, remote assessment of the mass eruption rate, even for remote volcanoes. They thus provide an additional path to estimation of the ESP and the forecasting
Two methods for estimating limits to large-scale wind power generation.
Miller, Lee M; Brunsell, Nathaniel A; Mechem, David B; Gans, Fabian; Monaghan, Andrew J; Vautard, Robert; Keith, David W; Kleidon, Axel
2015-09-08
Wind turbines remove kinetic energy from the atmospheric flow, which reduces wind speeds and limits generation rates of large wind farms. These interactions can be approximated using a vertical kinetic energy (VKE) flux method, which predicts that the maximum power generation potential is 26% of the instantaneous downward transport of kinetic energy using the preturbine climatology. We compare the energy flux method to the Weather Research and Forecasting (WRF) regional atmospheric model equipped with a wind turbine parameterization over a 10(5) km2 region in the central United States. The WRF simulations yield a maximum generation of 1.1 We⋅m(-2), whereas the VKE method predicts the time series while underestimating the maximum generation rate by about 50%. Because VKE derives the generation limit from the preturbine climatology, potential changes in the vertical kinetic energy flux from the free atmosphere are not considered. Such changes are important at night when WRF estimates are about twice the VKE value because wind turbines interact with the decoupled nocturnal low-level jet in this region. Daytime estimates agree better to 20% because the wind turbines induce comparatively small changes to the downward kinetic energy flux. This combination of downward transport limits and wind speed reductions explains why large-scale wind power generation in windy regions is limited to about 1 We⋅m(-2), with VKE capturing this combination in a comparatively simple way.
Zhang, Changjiang; Dai, Lijie; Ma, Leiming; Qian, Jinfang; Yang, Bo
2017-10-01
An objective technique is presented for estimating tropical cyclone (TC) innercore two-dimensional (2-D) surface wind field structure using infrared satellite imagery and machine learning. For a TC with eye, the eye contour is first segmented by a geodesic active contour model, based on which the eye circumference is obtained as the TC eye size. A mathematical model is then established between the eye size and the radius of maximum wind obtained from the past official TC report to derive the 2-D surface wind field within the TC eye. Meanwhile, the composite information about the latitude of TC center, surface maximum wind speed, TC age, and critical wind radii of 34- and 50-kt winds can be combined to build another mathematical model for deriving the innercore wind structure. After that, least squares support vector machine (LSSVM), radial basis function neural network (RBFNN), and linear regression are introduced, respectively, in the two mathematical models, which are then tested with sensitivity experiments on real TC cases. Verification shows that the innercore 2-D surface wind field structure estimated by LSSVM is better than that of RBFNN and linear regression.
PARAMETER ESTIMATION OF VALVE STICTION USING ANT COLONY OPTIMIZATION
Directory of Open Access Journals (Sweden)
S. Kalaivani
2012-07-01
Full Text Available In this paper, a procedure for quantifying valve stiction in control loops based on ant colony optimization has been proposed. Pneumatic control valves are widely used in the process industry. The control valve contains non-linearities such as stiction, backlash, and deadband that in turn cause oscillations in the process output. Stiction is one of the long-standing problems and it is the most severe problem in the control valves. Thus the measurement data from an oscillating control loop can be used as a possible diagnostic signal to provide an estimate of the stiction magnitude. Quantification of control valve stiction is still a challenging issue. Prior to doing stiction detection and quantification, it is necessary to choose a suitable model structure to describe control-valve stiction. To understand the stiction phenomenon, the Stenman model is used. Ant Colony Optimization (ACO, an intelligent swarm algorithm, proves effective in various fields. The ACO algorithm is inspired from the natural trail following behaviour of ants. The parameters of the Stenman model are estimated using ant colony optimization, from the input-output data by minimizing the error between the actual stiction model output and the simulated stiction model output. Using ant colony optimization, Stenman model with known nonlinear structure and unknown parameters can be estimated.
Temporal Parameters Estimation for Wheelchair Propulsion Using Wearable Sensors
Directory of Open Access Journals (Sweden)
Manoela Ojeda
2014-01-01
Full Text Available Due to lower limb paralysis, individuals with spinal cord injury (SCI rely on their upper limbs for mobility. The prevalence of upper extremity pain and injury is high among this population. We evaluated the performance of three triaxis accelerometers placed on the upper arm, wrist, and under the wheelchair, to estimate temporal parameters of wheelchair propulsion. Twenty-six participants with SCI were asked to push their wheelchair equipped with a SMARTWheel. The estimated stroke number was compared with the criterion from video observations and the estimated push frequency was compared with the criterion from the SMARTWheel. Mean absolute errors (MAE and mean absolute percentage of error (MAPE were calculated. Intraclass correlation coefficients and Bland-Altman plots were used to assess the agreement. Results showed reasonable accuracies especially using the accelerometer placed on the upper arm where the MAPE was 8.0% for stroke number and 12.9% for push frequency. The ICC was 0.994 for stroke number and 0.916 for push frequency. The wrist and seat accelerometer showed lower accuracy with a MAPE for the stroke number of 10.8% and 13.4% and ICC of 0.990 and 0.984, respectively. Results suggested that accelerometers could be an option for monitoring temporal parameters of wheelchair propulsion.
Estimation of extreme wind speeds in the mixed strong wind climate of South Africa
CSIR Research Space (South Africa)
Kruger, AC
2010-08-01
Full Text Available assessment was done by the CSIR in 1985 when only a limited number of climate stations over South Africa were available, which had sufficiently long time series of continuously recorded high-resolution wind data. Due to the complexity of the South African...
Campbell, D A; Chkrebtii, O
2013-12-01
Statistical inference for biochemical models often faces a variety of characteristic challenges. In this paper we examine state and parameter estimation for the JAK-STAT intracellular signalling mechanism, which exemplifies the implementation intricacies common in many biochemical inference problems. We introduce an extension to the Generalized Smoothing approach for estimating delay differential equation models, addressing selection of complexity parameters, choice of the basis system, and appropriate optimization strategies. Motivated by the JAK-STAT system, we further extend the generalized smoothing approach to consider a nonlinear observation process with additional unknown parameters, and highlight how the approach handles unobserved states and unevenly spaced observations. The methodology developed is generally applicable to problems of estimation for differential equation models with delays, unobserved states, nonlinear observation processes, and partially observed histories. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.
Statistical characterization of roughness uncertainty and impact on wind resource estimation
Directory of Open Access Journals (Sweden)
M. Kelly
2017-04-01
Full Text Available In this work we relate uncertainty in background roughness length (z0 to uncertainty in wind speeds, where the latter are predicted at a wind farm location based on wind statistics observed at a different site. Sensitivity of predicted winds to roughness is derived analytically for the industry-standard European Wind Atlas method, which is based on the geostrophic drag law. We statistically consider roughness and its corresponding uncertainty, in terms of both z0 derived from measured wind speeds as well as that chosen in practice by wind engineers. We show the combined effect of roughness uncertainty arising from differing wind-observation and turbine-prediction sites; this is done for the case of roughness bias as well as for the general case. For estimation of uncertainty in annual energy production (AEP, we also develop a generalized analytical turbine power curve, from which we derive a relation between mean wind speed and AEP. Following our developments, we provide guidance on approximate roughness uncertainty magnitudes to be expected in industry practice, and we also find that sites with larger background roughness incur relatively larger uncertainties.
Directory of Open Access Journals (Sweden)
L. Vollmer
2016-09-01
Full Text Available An intentional yaw misalignment of wind turbines is currently discussed as one possibility to increase the overall energy yield of wind farms. The idea behind this control is to decrease wake losses of downstream turbines by altering the wake trajectory of the controlled upwind turbines. For an application of such an operational control, precise knowledge about the inflow wind conditions, the magnitude of wake deflection by a yawed turbine and the propagation of the wake is crucial. The dependency of the wake deflection on the ambient wind conditions as well as the uncertainty of its trajectory are not sufficiently covered in current wind farm control models. In this study we analyze multiple sources that contribute to the uncertainty of the estimation of the wake deflection downstream of yawed wind turbines in different ambient wind conditions. We find that the wake shapes and the magnitude of deflection differ in the three evaluated atmospheric boundary layers of neutral, stable and unstable thermal stability. Uncertainty in the wake deflection estimation increases for smaller temporal averaging intervals. We also consider the choice of the method to define the wake center as a source of uncertainty as it modifies the result. The variance of the wake deflection estimation increases with decreasing atmospheric stability. Control of the wake position in a highly convective environment is therefore not recommended.
A method for model identification and parameter estimation
International Nuclear Information System (INIS)
Bambach, M; Heinkenschloss, M; Herty, M
2013-01-01
We propose and analyze a new method for the identification of a parameter-dependent model that best describes a given system. This problem arises, for example, in the mathematical modeling of material behavior where several competing constitutive equations are available to describe a given material. In this case, the models are differential equations that arise from the different constitutive equations, and the unknown parameters are coefficients in the constitutive equations. One has to determine the best-suited constitutive equations for a given material and application from experiments. We assume that the true model is one of the N possible parameter-dependent models. To identify the correct model and the corresponding parameters, we can perform experiments, where for each experiment we prescribe an input to the system and observe a part of the system state. Our approach consists of two stages. In the first stage, for each pair of models we determine the experiment, i.e. system input and observation, that best differentiates between the two models, and measure the distance between the two models. Then we conduct N(N − 1) or, depending on the approach taken, N(N − 1)/2 experiments and use the result of the experiments as well as the previously computed model distances to determine the true model. We provide sufficient conditions on the model distances and measurement errors which guarantee that our approach identifies the correct model. Given the model, we identify the corresponding model parameters in the second stage. The problem in the second stage is a standard parameter estimation problem and we use a method suitable for the given application. We illustrate our approach on three examples, including one where the models are elliptic partial differential equations with different parameterized right-hand sides and an example where we identify the constitutive equation in a problem from computational viscoplasticity. (paper)
Parameter Estimation for GRACE-FO Geometric Ranging Errors
Wegener, H.; Mueller, V.; Darbeheshti, N.; Naeimi, M.; Heinzel, G.
2017-12-01
Onboard GRACE-FO, the novel Laser Ranging Instrument (LRI) serves as a technology demonstrator, but it is a fully functional instrument to provide an additional high-precision measurement of the primary mission observable: the biased range between the two spacecraft. Its (expectedly) two largest error sources are laser frequency noise and tilt-to-length (TTL) coupling. While not much can be done about laser frequency noise, the mechanics of the TTL error are widely understood. They depend, however, on unknown parameters. In order to improve the quality of the ranging data, it is hence essential to accurately estimate these parameters and remove the resulting TTL error from the data.Means to do so will be discussed. In particular, the possibility of using calibration maneuvers, the utility of the attitude information provided by the LRI via Differential Wavefront Sensing (DWS), and the benefit from combining ranging data from LRI with ranging data from the established microwave ranging, will be mentioned.
Transport parameter estimation from lymph measurements and the Patlak equation.
Watson, P D; Wolf, M B
1992-01-01
Two methods of estimating protein transport parameters for plasma-to-lymph transport data are presented. Both use IBM-compatible computers to obtain least-squares parameters for the solvent drag reflection coefficient and the permeability-surface area product using the Patlak equation. A matrix search approach is described, and the speed and convenience of this are compared with a commercially available gradient method. The results from both of these methods were different from those of a method reported by Reed, Townsley, and Taylor [Am. J. Physiol. 257 (Heart Circ. Physiol. 26): H1037-H1041, 1989]. It is shown that the Reed et al. method contains a systematic error. It is also shown that diffusion always plays an important role for transmembrane transport at the exit end of a membrane channel under all conditions of lymph flow rate and that the statement that diffusion becomes zero at high lymph flow rate depends on a mathematical definition of diffusion.
Pedotransfer functions estimating soil hydraulic properties using different soil parameters
DEFF Research Database (Denmark)
Børgesen, Christen Duus; Iversen, Bo Vangsø; Jacobsen, Ole Hørbye
2008-01-01
Estimates of soil hydraulic properties using pedotransfer functions (PTF) are useful in many studies such as hydrochemical modelling and soil mapping. The objective of this study was to calibrate and test parametric PTFs that predict soil water retention and unsaturated hydraulic conductivity...... parameters. The PTFs are based on neural networks and the Bootstrap method using different sets of predictors and predict the van Genuchten/Mualem parameters. A Danish soil data set (152 horizons) dominated by sandy and sandy loamy soils was used in the development of PTFs to predict the Mualem hydraulic...... of the hydraulic properties of the studied soils. We found that introducing measured water content as a predictor generally gave lower errors for water retention predictions and higher errors for conductivity predictions. The best of the developed PTFs for predicting hydraulic conductivity was tested against PTFs...
Niedzielski, Tomasz; Skjøth, Carsten; Werner, Małgorzata; Spallek, Waldemar; Witek, Matylda; Sawiński, Tymoteusz; Drzeniecka-Osiadacz, Anetta; Korzystka-Muskała, Magdalena; Muskała, Piotr; Modzel, Piotr; Guzikowski, Jakub; Kryza, Maciej
2017-09-01
The objective of this paper is to empirically show that estimates of wind speed and wind direction based on measurements carried out using the Pitot tubes and GNSS receivers, mounted on consumer-grade unmanned aerial vehicles (UAVs), may accurately approximate true wind parameters. The motivation for the study is that a growing number of commercial and scientific UAV operations may soon become a new source of data on wind speed and wind direction, with unprecedented spatial and temporal resolution. The feasibility study was carried out within an isolated mountain meadow of Polana Izerska located in the Izera Mountains (SW Poland) during an experiment which aimed to compare wind characteristics measured by several instruments: three UAVs (swinglet CAM, eBee, Maja) equipped with the Pitot tubes and GNSS receivers, wind speed and direction meters mounted at 2.5 and 10 m (mast), conventional weather station and vertical sodar. The three UAVs performed seven missions along spiral-like trajectories, most reaching 130 m above take-off location. The estimates of wind speed and wind direction were found to agree between UAVs. The time series of wind speed measured at 10 m were extrapolated to flight altitudes recorded at a given time so that a comparison was made feasible. It was found that the wind speed estimates provided by the UAVs on a basis of the Pitot tube/GNSS data are in agreement with measurements carried out using dedicated meteorological instruments. The discrepancies were recorded in the first and last phases of UAV flights.
Prediction of the Dst index from solar wind parameters by a neural network method
Watanabe, S.; Sagawa, E.; Ohtaka, K.; Shimazu, H.
2002-12-01
Using the Elman-type neural network technique, operational models are constructed that predict the Dst index two hours in advance. The input data consist of real-time solar wind velocity, density, and magnetic field data obtained by the Advanced Composition Explorer (ACE) spacecraft since May 1998 (http://www2.crl.go.jp/uk/uk223/service/nnw/index.html). During the period from February to October 1998, eleven storms occurred with minimum Dst values below -80 nT. For ten of these storms the differences between the predicted minimum Dst and the minimum Dst calculated from ground-based magnetometer data were less than 23%. For the remaining one storm (beginning on 19 October 1998) the difference was 48%. The discrepancy is likely to stem from a imperfect correlation between the solar wind parameters near ACE and those near the earth. While the IMF Bz remains to be the most important parameter, other parameters do have their effects. For instance, Dst appears to be enhanced when the azimuthal direction of IMF is toward the sun. A trapezoid-shaped increase in the solar wind density enhances the main phase Dst by almost 10% compared with the case of no density increase. Velocity effects appear to be stronger than the density effects. Our operational models have, in principle, no limitations in applicability with respect to storm intensity.
Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver
Kang, Ling; Zhou, Liwei
2018-02-01
Abstract . The Muskingum model is an effective flood routing technology in hydrology and water resources Engineering. With the development of optimization technology, more and more variable-parameter Muskingum models were presented to improve effectiveness of the Muskingum model in recent decades. A variable-parameter nonlinear Muskingum model (NVPNLMM) was proposed in this paper. According to the results of two real and frequently-used case studies by various models, the NVPNLMM could obtain better values of evaluation criteria, which are used to describe the superiority of the estimated outflows and compare the accuracies of flood routing using various models, and the optimal estimated outflows by the NVPNLMM were closer to the observed outflows than the ones by other models.
Energy parameter estimation in solar powered wireless sensor networks
Mousa, Mustafa
2014-02-24
The operation of solar powered wireless sensor networks is associated with numerous challenges. One of the main challenges is the high variability of solar power input and battery capacity, due to factors such as weather, humidity, dust and temperature. In this article, we propose a set of tools that can be implemented onboard high power wireless sensor networks to estimate the battery condition and capacity as well as solar power availability. These parameters are very important to optimize sensing and communications operations and maximize the reliability of the complete system. Experimental results show that the performance of typical Lithium Ion batteries severely degrades outdoors in a matter of weeks or months, and that the availability of solar energy in an urban solar powered wireless sensor network is highly variable, which underlines the need for such power and energy estimation algorithms.
Robustness of Modal Parameter Estimation Methods Applied to Lightweight Structures
DEFF Research Database (Denmark)
Dickow, Kristoffer Ahrens; Kirkegaard, Poul Henning; Andersen, Lars Vabbersgaard
2013-01-01
of two parameter estimation methods built into the commercial modal testing software B&K Pulse Re ex Advanced Modal Analysis. The investigations are done by means of frequency response functions generated from a nite-element model and subjected to articial noise before being analyzed with Pulse Re ex....... The ability to handle closely spaced modes and broad frequency ranges is investigated for a numerical model of a lightweight junction under dierent signal-to-noise ratios. The selection of both excitation points and response points are discussed. It is found that both the Rational Fraction Polynomial-Z method...
Parameter Estimation Analysis for Hybrid Adaptive Fault Tolerant Control
Eshak, Peter B.
Research efforts have increased in recent years toward the development of intelligent fault tolerant control laws, which are capable of helping the pilot to safely maintain aircraft control at post failure conditions. Researchers at West Virginia University (WVU) have been actively involved in the development of fault tolerant adaptive control laws in all three major categories: direct, indirect, and hybrid. The first implemented design to provide adaptation was a direct adaptive controller, which used artificial neural networks to generate augmentation commands in order to reduce the modeling error. Indirect adaptive laws were implemented in another controller, which utilized online PID to estimate and update the controller parameter. Finally, a new controller design was introduced, which integrated both direct and indirect control laws. This controller is known as hybrid adaptive controller. This last control design outperformed the two earlier designs in terms of less NNs effort and better tracking quality. The performance of online PID has an important role in the quality of the hybrid controller; therefore, the quality of the estimation will be of a great importance. Unfortunately, PID is not perfect and the online estimation process has some inherited issues; the online PID estimates are primarily affected by delays and biases. In order to ensure updating reliable estimates to the controller, the estimator consumes some time to converge. Moreover, the estimator will often converge to a biased value. This thesis conducts a sensitivity analysis for the estimation issues, delay and bias, and their effect on the tracking quality. In addition, the performance of the hybrid controller as compared to direct adaptive controller is explored. In order to serve this purpose, a simulation environment in MATLAB/SIMULINK has been created. The simulation environment is customized to provide the user with the flexibility to add different combinations of biases and delays to
Modal Parameters from a Wind Turbine Wing by Operational Modal Analysis
DEFF Research Database (Denmark)
Herlufsen, H.; Møller, N.; Brincker, Rune
2002-01-01
Operational Modal Analysis also known as Ambient Modal Analysis has an increasing interest in mechanical engineering. Especially on big structures where the excitation and not less important the determination of the forces is most often a problem. In a structure like a wind turbine wing where...... the modes occur both close in frequency and bidirectional the Ambient excitation has big advantages. In this paper modal parameters are identified from the wing by operational modal analysis. For the parameter identification both parametric and non-parametric techniques are used. Advantages...
Mellinger, Philippe; Döhler, Michael; Mevel, Laurent
2016-01-01
International audience; An important step in the operational modal analysis of a structure is to infer on its dynamic behavior through its modal parameters. They can be estimated by various modal identification algorithms that fit a theoretical model to measured data. When output-only data is available, i.e. measured responses of the structure, frequencies, damping ratios and mode shapes can be identified assuming that ambient sources like wind or traffic excite the system sufficiently. When ...
Parameter estimation in multi-axial thermal diffusivity experiments
Davis, Sean Edgar
Thermomechanical analysis requires quantifying the thermophysical properties of thermal conductivity (or diffusivity) and specific heat. The extended flash method allows simultaneous measurement of multiple components of the thermal diffusivity tensor. The locations of the temperature sensors in such an experiment have an affect on the ability to accurately estimate the desired components of the diffusivity tensor. Here, D-optimization is applied to a simulated extended flash diffusivity experiment to improve the accuracy of the experiment through optimization of the inter-sensor distance. Results indicate that the optimal inter-sensor distance increases with an increasing ratio of inplane to out-of-plane diffusivity. The analytically determined optimal sensor positioning for an isotropic material is validated via experimental measurements on AISI 304 stainless steel, where it is shown that the accuracy of the estimated parameters improves for data sampled at the optimized locations. When modeling the anisotropic thermal response of materials, the material may be rotated such that the physical axes coincide with the principal axes of the thermal diffusivity tensor, resulting in thermal orthotropy. During measurements of such a tensor, however, the principal axes may be unknown, requiring a method to determine principal values and the orientation of the principal directions while simultaneously measuring the diffusivity. An analytical study was performed where the four non-zero components of the diffusivity tensor alpha were estimated for a material possessing random in-plane anisotropy on the order of certain manufactured or mechanically loaded elastomers. Results indicate that a four-sensor array allows sufficient sampling of the material response to permit estimation of alpha to within 1% of the reference values. When orthotropy is assumed for a material exhibiting random in-plane anisotropy, the estimated values of alphaii are resolved to within 0.4% of the
DEFF Research Database (Denmark)
Gaynor, J. E.; Kristensen, Leif
1986-01-01
For pt.I see ibid., vol.3, no.3, p.523-8 (1986). The authors use the theoretical results presented in part I to correct turbulence parameters derived from monostatic sodar wind measurements in an attempt to improve the statistical comparisons with the sonic anemometers on the Boulder Atmospheric...... Observatory tower. The approximate magnitude of the error due to spatial and temporal pulse volume separation is presented as a function of mean wind angle relative to the sodar configuration and for several antenna pulsing orders. Sodar-derived standard deviations of the lateral wind component, before...
Estimating Friction Parameters in Reaction Wheels for Attitude Control
Directory of Open Access Journals (Sweden)
Valdemir Carrara
2013-01-01
Full Text Available The ever-increasing use of artificial satellites in both the study of terrestrial and space phenomena demands a search for increasingly accurate and reliable pointing systems. It is common nowadays to employ reaction wheels for attitude control that provide wide range of torque magnitude, high reliability, and little power consumption. However, the bearing friction causes the response of wheel to be nonlinear, which may compromise the stability and precision of the control system as a whole. This work presents a characterization of a typical reaction wheel of 0.65 Nms maximum angular momentum storage, in order to estimate their friction parameters. It used a friction model that takes into account the Coulomb friction, viscous friction, and static friction, according to the Stribeck formulation. The parameters were estimated by means of a nonlinear batch least squares procedure, from data raised experimentally. The results have shown wide agreement with the experimental data and were also close to a deterministic model, previously obtained for this wheel. This model was then employed in a Dynamic Model Compensator (DMC control, which successfully reduced the attitude steady state error of an instrumented one-axis air-bearing table.
Parameter estimation in space systems using recurrent neural networks
Parlos, Alexander G.; Atiya, Amir F.; Sunkel, John W.
1991-01-01
The identification of time-varying parameters encountered in space systems is addressed, using artificial neural systems. A hybrid feedforward/feedback neural network, namely a recurrent multilayer perception, is used as the model structure in the nonlinear system identification. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard back-propagation-learning algorithm is modified and it is used for both the off-line and on-line supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying parameters of nonlinear dynamic systems is investigated by estimating the mass properties of a representative large spacecraft. The changes in the spacecraft inertia are predicted using a trained neural network, during two configurations corresponding to the early and late stages of the spacecraft on-orbit assembly sequence. The proposed on-line mass properties estimation capability offers encouraging results, though, further research is warranted for training and testing the predictive capabilities of these networks beyond nominal spacecraft operations.
Genetic Parameter Estimation in Seedstock Swine Population for Growth Performances
Directory of Open Access Journals (Sweden)
Jae Gwan Choi
2013-04-01
Full Text Available The objective of this study was to estimate genetic parameters that are to be used for across-herd genetic evaluations of seed stock pigs at GGP level. Performance data with pedigree information collected from swine breeder farms in Korea were provided by Korea Animal Improvement Association (AIAK. Performance data were composed of final body weights at test days and ultrasound measures of back fat thickness (BF, rib eye area (EMA and retail cut percentage (RCP. Breeds of swine tested were Landrace, Yorkshire and Duroc. Days to 90 kg body weight (DAYS90 were estimated with linear function of age and ADG calculated from body weights at test days. Ultrasound measures were taken with A-mode ultrasound scanners by trained technicians. Number of performance records after censoring outliers and keeping records pigs only born from year 2000 were of 78,068 Duroc pigs, 101,821 Landrace pigs and 281,421 Yorkshire pigs. Models included contemporary groups defined by the same herd and the same seasons of births of the same year, which was regarded as fixed along with the effect of sex for all traits and body weight at test day as a linear covariate for ultrasound measures. REML estimation was processed with REMLF90 program. Heritability estimates were 0.40, 0.32, 0.21 0.39 for DAYS90, ADG, BF, EMA, RCP, respectively for Duroc population. Respective heritability estimates for Landrace population were 0.43, 0.41, 0.22, and 0.43 and for Yorkshire population were 0.36, 0.38, 0.22, and 0.42. Genetic correlation coefficients of DAYS90 with BF, EMA, or RCP were estimated to be 0.00 to 0.09, −0.15 to −0.25, 0.22 to 0.28, respectively for three breeds populations. Genetic correlation coefficients estimated between BF and EMA was −0.33 to −0.39. Genetic correlation coefficient estimated between BF and RCP was high and negative (−0.78 to −0.85 but the environmental correlation coefficients between these two traits was medium and negative (near −0
Correlation of Magnetic Fields with Solar Wind Plasma Parameters at 1AU
Shen, F.
2017-12-01
The physical parameters of the solar wind observed in-situ near 1AU have been studied for several decades, and relationships between them, such as the positive correlation between the solar wind plasma temperature T and velocity V, and the negative correlation between density N and velocity V, are well known. However, the magnetic field intensity does not appear to be well correlated with any individual plasma parameter. In this paper, we discuss previously under-reported correlations between B and the combined plasma parameters √NV2 as well as between B and √NT. These two correlations are strong during the periods of corotating interaction regions and high speed streams, moderate during intervals of slow solar wind, and rather poor during the passage of interplanetary coronal mass ejections. The results indicate that the magnetic pressure in the solar wind is well correlated both with the plasma dynamic pressure and the thermal pressure. Then, we employ a 3D MHD model to simulate the formation of the relationships between the magnetic strength B and √NV2 as well as √NT observed at 1AU. The inner boundary condition is derived by empirical models, with the magnetic field and density are optional. Five kinds of boundary conditions at the inner boundary of heliosphere are tested. In the cases that the magnetic field is related to speed at the inner boundary, the correlation coefficients between B and √NV2 as well as between B and √NT are even higher than that in the observational results. At 1AU the simulated radial magnetic field shows little latitude dependence, which matches the observation of Ulysses. Most of the modeled characters in these cases are closer to observation than others. This inner boundary condition may more accurately characterize Sun's magnetic influence on the heliosphere. The new input may be able to improve the simulation of CME propagation in the inner heliosphere and the space weather forecasting.
Estimates of Sputter Yields of Solar-Wind Heavy Ions of Lunar Regolith Materials
Barghouty, Abdulmasser F.; Adams, James H., Jr.
2008-01-01
At energies of approximately 1 keV/amu, solar-wind protons and heavy ions interact with the lunar surface materials via a number of microscopic interactions that include sputtering. Solar-wind induced sputtering is a main mechanism by which the composition of the topmost layers of the lunar surface can change, dynamically and preferentially. This work concentrates on sputtering induced by solar-wind heavy ions. Sputtering associated with slow (speeds the electrons speed in its first Bohr orbit) and highly charged ions are known to include both kinetic and potential sputtering. Potential sputtering enjoys some unique characteristics that makes it of special interest to lunar science and exploration. Unlike the yield from kinetic sputtering where simulation and approximation schemes exist, the yield from potential sputtering is not as easy to estimate. This work will present a preliminary numerical scheme designed to estimate potential sputtering yields from reactions relevant to this aspect of solar-wind lunar-surface coupling.
Estimate of Hurricane Wind Speed from AMSR-E Low-Frequency Channel Brightness Temperature Data
Directory of Open Access Journals (Sweden)
Lei Zhang
2018-01-01
Full Text Available Two new parameters (W6H and W6V were defined that represent brightness temperature increments for different low-frequency channels due to ocean wind. We developed a new wind speed retrieval model inside hurricanes based on W6H and W6V using brightness temperature data from AMSR-E. The AMSR-E observations of 12 category 3–5 hurricanes from 2003 to 2011 and corresponding data from the H*wind analysis system were used to develop and validate the AMSR-E wind speed retrieval model. The results show that the mean bias and the overall root-mean-square (RMS difference of the AMSR-E retrieved wind speeds with respect to H*wind (HRD Real-time Hurricane Wind Analysis System analysis data were −0.01 m/s and 2.66 m/s, respectively. One case study showed that W6H and W6V were less sensitive to rain than the observed AMSR-E C-band and X-band brightness temperature data. The AMSR-E retrieval model was further validated by comparing the retrieved wind speeds against stepped-frequency microwave radiometer (SFMR measurements. The comparison showed an RMS difference of 3.41 m/s and a mean bias of 0.49 m/s.
Gearbox Fatigue Load Estimation for Condition Monitoring of Wind Turbines
DEFF Research Database (Denmark)
Perisic, Nevena; Pedersen, Bo Juul; Kirkegaard, Poul Henning
2012-01-01
control and data acquisition (SCADA) system. Estimated loads can be further used for prediction of remaining operating lifetime of turbine components, detection of high stress level or fault detection. An augmented Kalman filter is chosen as the fatigue load estimator because its characteristics well suit...
Periodic orbits of hybrid systems and parameter estimation via AD.
Energy Technology Data Exchange (ETDEWEB)
Guckenheimer, John. (Cornell University); Phipps, Eric Todd; Casey, Richard (INRIA Sophia-Antipolis)
2004-07-01
Rhythmic, periodic processes are ubiquitous in biological systems; for example, the heart beat, walking, circadian rhythms and the menstrual cycle. Modeling these processes with high fidelity as periodic orbits of dynamical systems is challenging because: (1) (most) nonlinear differential equations can only be solved numerically; (2) accurate computation requires solving boundary value problems; (3) many problems and solutions are only piecewise smooth; (4) many problems require solving differential-algebraic equations; (5) sensitivity information for parameter dependence of solutions requires solving variational equations; and (6) truncation errors in numerical integration degrade performance of optimization methods for parameter estimation. In addition, mathematical models of biological processes frequently contain many poorly-known parameters, and the problems associated with this impedes the construction of detailed, high-fidelity models. Modelers are often faced with the difficult problem of using simulations of a nonlinear model, with complex dynamics and many parameters, to match experimental data. Improved computational tools for exploring parameter space and fitting models to data are clearly needed. This paper describes techniques for computing periodic orbits in systems of hybrid differential-algebraic equations and parameter estimation methods for fitting these orbits to data. These techniques make extensive use of automatic differentiation to accurately and efficiently evaluate derivatives for time integration, parameter sensitivities, root finding and optimization. The boundary value problem representing a periodic orbit in a hybrid system of differential algebraic equations is discretized via multiple-shooting using a high-degree Taylor series integration method [GM00, Phi03]. Numerical solutions to the shooting equations are then estimated by a Newton process yielding an approximate periodic orbit. A metric is defined for computing the distance
DEFF Research Database (Denmark)
Sommer, Helle Mølgaard; Holst, Helle; Spliid, Henrik
1995-01-01
Three identical microbiological experiments were carried out and analysed in order to examine the variability of the parameter estimates. The microbiological system consisted of a substrate (toluene) and a biomass (pure culture) mixed together in an aquifer medium. The degradation of the substrat...
DEFF Research Database (Denmark)
Sommer, Helle Mølgaard; Holst, Helle; Spliid, Henrik
1995-01-01
Three identical microbiological experiments were carried out and analysed in order to examine the variability of the parameter estimates. The microbiological system consisted of a substrate (toluene) and a biomass (pure culture) mixed together in an aquifer medium. The degradation of the substrate...
Estimating Mass Parameters of Doubly Synchronous Binary Asteroids
Davis, Alex; Scheeres, Daniel J.
2017-10-01
The non-spherical mass distributions of binary asteroid systems lead to coupled mutual gravitational forces and torques. Observations of the coupled attitude and orbital dynamics can be leveraged to provide information about the mass parameters of the binary system. The full 3-dimensional motion has 9 degrees of freedom, and coupled dynamics require the use of numerical investigation only. In the current study we simplify the system to a planar ellipsoid-ellipsoid binary system in a doubly synchronous orbit. Three modes are identified for the system, which has 4 degrees of freedom, with one degree of freedom corresponding to an ignorable coordinate. The three modes correspond to the three major librational modes of the system when it is in a doubly synchronous orbit. The linearized periods of each mode are a function of the mass parameters of the two asteroids, enabling measurement of these parameters based on observations of the librational motion. Here we implement estimation techniques to evaluate the capabilities of this mass measurement method. We apply this methodology to the Trojan binary asteroid system 617 Patroclus and Menoetius (1906 VY), the final flyby target of the recently announced LUCY Discovery mission. This system is of interest because a stellar occultation campaign of the Patroclus and Menoetius system has suggested that the asteroids are similarly sized oblate ellipsoids moving in a doubly-synchronous orbit, making the system an ideal test for this investigation. A number of missed observations during the campaign also suggested the possibility of a crater on the southern limb of Menoetius, the presence of which could be evaluated by our mass estimation method. This presentation will review the methodology and potential accuracy of our approach in addition to evaluating how the dynamical coupling can be used to help understand light curve and stellar occultation observations for librating binary systems.
Estimating negative binomial parameters from occurrence data with detection times.
Hwang, Wen-Han; Huggins, Richard; Stoklosa, Jakub
2016-11-01
The negative binomial distribution is a common model for the analysis of count data in biology and ecology. In many applications, we may not observe the complete frequency count in a quadrat but only that a species occurred in the quadrat. If only occurrence data are available then the two parameters of the negative binomial distribution, the aggregation index and the mean, are not identifiable. This can be overcome by data augmentation or through modeling the dependence between quadrat occupancies. Here, we propose to record the (first) detection time while collecting occurrence data in a quadrat. We show that under what we call proportionate sampling, where the time to survey a region is proportional to the area of the region, that both negative binomial parameters are estimable. When the mean parameter is larger than two, our proposed approach is more efficient than the data augmentation method developed by Solow and Smith (, Am. Nat. 176, 96-98), and in general is cheaper to conduct. We also investigate the effect of misidentification when collecting negative binomially distributed data, and conclude that, in general, the effect can be simply adjusted for provided that the mean and variance of misidentification probabilities are known. The results are demonstrated in a simulation study and illustrated in several real examples. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Estimation of Parameters of CCF with Staggered Testing
International Nuclear Information System (INIS)
Kim, Myung-Ki; Hong, Sung-Yull
2006-01-01
Common cause failures are extremely important in reliability analysis and would be dominant to risk contributor in a high reliable system such as a nuclear power plant. Of particular concern is common cause failure (CCF) that degrades redundancy or diversity implemented to improve a reliability of systems. Most of analyses of parameters of CCF models such as beta factor model, alpha factor model, and MGL(Multiple Greek Letters) model deal a system with a nonstaggered testing strategy. Non-staggered testing is that all components are tested at the same time (or at least the same shift) and staggered testing is that if there is a failure in the first component, all the other components are tested immediately, and if it succeeds, no more is done until the next scheduled testing time. Both of them are applied in the nuclear power plants. The strategy, however, is not explicitly described in the technical specifications, but implicitly in the periodic test procedure. For example, some redundant components particularly important to safety are being tested with staggered testing strategy. Others are being performed with non-staggered testing strategy. This paper presents the parameter estimator of CCF model such as beta factor model, MGL model, and alpha factor model with staggered testing strategy. In addition, a new CCF model, rho factor model, is proposed and its parameter is presented with staggered testing strategy
Parameter and uncertainty estimation for mechanistic, spatially explicit epidemiological models
Finger, Flavio; Schaefli, Bettina; Bertuzzo, Enrico; Mari, Lorenzo; Rinaldo, Andrea
2014-05-01
Epidemiological models can be a crucially important tool for decision-making during disease outbreaks. The range of possible applications spans from real-time forecasting and allocation of health-care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. Our spatially explicit, mechanistic models for cholera epidemics have been successfully applied to several epidemics including, the one that struck Haiti in late 2010 and is still ongoing. Calibration and parameter estimation of such models represents a major challenge because of properties unusual in traditional geoscientific domains such as hydrology. Firstly, the epidemiological data available might be subject to high uncertainties due to error-prone diagnosis as well as manual (and possibly incomplete) data collection. Secondly, long-term time-series of epidemiological data are often unavailable. Finally, the spatially explicit character of the models requires the comparison of several time-series of model outputs with their real-world counterparts, which calls for an appropriate weighting scheme. It follows that the usual assumption of a homoscedastic Gaussian error distribution, used in combination with classical calibration techniques based on Markov chain Monte Carlo algorithms, is likely to be violated, whereas the construction of an appropriate formal likelihood function seems close to impossible. Alternative calibration methods, which allow for accurate estimation of total model uncertainty, particularly regarding the envisaged use of the models for decision-making, are thus needed. Here we present the most recent developments regarding methods for parameter and uncertainty estimation to be used with our mechanistic, spatially explicit models for cholera epidemics, based on informal measures of goodness of fit.
Gal-Chen, Tzvi; Xu, Mei; Eberhard, Wynn L.
1992-11-01
Techniques for extraction of boundary layer parameters from measurements of a short pulse (≈0.4 μs) CO2 Doppler lidar (λ = 10.6 μm) are described. The lidar is operated by the National Oceanic and Atmospheric Administration (NOAA) Wave Propagation Laboratory (WPL). The measurements are those collected during the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE). The recorded radial velocity measurements have a range resolution of 150 m. With a pulse repetition rate of 20 Hz it is possible to perform scannings in two perpendicular vertical planes (x-z and y-z) in approximately 72 s. By continuously operating the lidar for about an hour, one can extract stable statistics of the radial velocities. Assuming that the turbulence is horizontally homogeneous, we have estimated the mean wind, its standard deviations, and the momentum fluxes. We have estimated the first, second, and, third moments of the vertical velocity from the vertically pointing beam. Spectral analysis of the radial velocities is also performed, from which (by examining the amplitude of the power spectrum at the inertial range) we have deduced the kinetic energy dissipation. Finally, using the statistical form of the Navier-Stokes equations, the surface heat flux is derived as the residual balance between the vertical gradient of the third moment of the vertical velocity and the kinetic energy dissipation. With the exception of the vertically pointing beam an individual radial velocity estimate is accurate only to ±0.7 m s-1. Combining many measurements would normally reduce the error, provided that it is unbiased and uncorrelated. The nature of some of the algorithms, however, is such that biased and correlated errors may be generated even though the "raw" measurements are not. We have developed data processing procedures that eliminate bias and minimize error correlation. Once bias and error correlations are accounted for, the large sample size is
Automated modal parameter estimation using correlation analysis and bootstrap sampling
Yaghoubi, Vahid; Vakilzadeh, Majid K.; Abrahamsson, Thomas J. S.
2018-02-01
The estimation of modal parameters from a set of noisy measured data is a highly judgmental task, with user expertise playing a significant role in distinguishing between estimated physical and noise modes of a test-piece. Various methods have been developed to automate this procedure. The common approach is to identify models with different orders and cluster similar modes together. However, most proposed methods based on this approach suffer from high-dimensional optimization problems in either the estimation or clustering step. To overcome this problem, this study presents an algorithm for autonomous modal parameter estimation in which the only required optimization is performed in a three-dimensional space. To this end, a subspace-based identification method is employed for the estimation and a non-iterative correlation-based method is used for the clustering. This clustering is at the heart of the paper. The keys to success are correlation metrics that are able to treat the problems of spatial eigenvector aliasing and nonunique eigenvectors of coalescent modes simultaneously. The algorithm commences by the identification of an excessively high-order model from frequency response function test data. The high number of modes of this model provides bases for two subspaces: one for likely physical modes of the tested system and one for its complement dubbed the subspace of noise modes. By employing the bootstrap resampling technique, several subsets are generated from the same basic dataset and for each of them a model is identified to form a set of models. Then, by correlation analysis with the two aforementioned subspaces, highly correlated modes of these models which appear repeatedly are clustered together and the noise modes are collected in a so-called Trashbox cluster. Stray noise modes attracted to the mode clusters are trimmed away in a second step by correlation analysis. The final step of the algorithm is a fuzzy c-means clustering procedure applied to
Learn-as-you-go acceleration of cosmological parameter estimates
International Nuclear Information System (INIS)
Aslanyan, Grigor; Easther, Richard; Price, Layne C.
2015-01-01
Cosmological analyses can be accelerated by approximating slow calculations using a training set, which is either precomputed or generated dynamically. However, this approach is only safe if the approximations are well understood and controlled. This paper surveys issues associated with the use of machine-learning based emulation strategies for accelerating cosmological parameter estimation. We describe a learn-as-you-go algorithm that is implemented in the Cosmo++ code and (1) trains the emulator while simultaneously estimating posterior probabilities; (2) identifies unreliable estimates, computing the exact numerical likelihoods if necessary; and (3) progressively learns and updates the error model as the calculation progresses. We explicitly describe and model the emulation error and show how this can be propagated into the posterior probabilities. We apply these techniques to the Planck likelihood and the calculation of ΛCDM posterior probabilities. The computation is significantly accelerated without a pre-defined training set and uncertainties in the posterior probabilities are subdominant to statistical fluctuations. We have obtained a speedup factor of 6.5 for Metropolis-Hastings and 3.5 for nested sampling. Finally, we discuss the general requirements for a credible error model and show how to update them on-the-fly
Simplified rotor load models and fatigue damage estimates for offshore wind turbines.
Muskulus, M
2015-02-28
The aim of rotor load models is to characterize and generate the thrust loads acting on an offshore wind turbine. Ideally, the rotor simulation can be replaced by time series from a model with a few parameters and state variables only. Such models are used extensively in control system design and, as a potentially new application area, structural optimization of support structures. Different rotor load models are here evaluated for a jacket support structure in terms of fatigue lifetimes of relevant structural variables. All models were found to be lacking in accuracy, with differences of more than 20% in fatigue load estimates. The most accurate models were the use of an effective thrust coefficient determined from a regression analysis of dynamic thrust loads, and a novel stochastic model in state-space form. The stochastic model explicitly models the quasi-periodic components obtained from rotational sampling of turbulent fluctuations. Its state variables follow a mean-reverting Ornstein-Uhlenbeck process. Although promising, more work is needed on how to determine the parameters of the stochastic model and before accurate lifetime predictions can be obtained without comprehensive rotor simulations. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Optimal nonlinear estimation for aircraft flight control in wind shear
Mulgund, Sandeep S.
1994-01-01
The most recent results in an ongoing research effort at Princeton in the area of flight dynamics in wind shear are described. The first undertaking in this project was a trajectory optimization study. The flight path of a medium-haul twin-jet transport aircraft was optimized during microburst encounters on final approach. The assumed goal was to track a reference climb rate during an aborted landing, subject to a minimum airspeed constraint. The results demonstrated that the energy loss through the microburst significantly affected the qualitative nature of the optimal flight path. In microbursts of light to moderate strength, the aircraft was able to track the reference climb rate successfully. In severe microbursts, the minimum airspeed constraint in the optimization forced the aircraft to settle on a climb rate smaller than the target. A tradeoff was forced between the objectives of flight path tracking and stall prevention.
Toulabi, Mohammadreza; Bahrami, Shahab; Ranjbar, Ali Mohammad
2018-03-01
In most of the existing studies, the frequency response in the variable speed wind turbines (VSWTs) is simply realized by changing the torque set-point via appropriate inputs such as frequency deviations signal. However, effective dynamics and systematic process design have not been comprehensively discussed yet. Accordingly, this paper proposes a proportional-derivative frequency controller and investigates its performance in a wind farm consisting of several VSWTs. A band-pass filter is deployed before the proposed controller to avoid responding to either steady state frequency deviations or high rate of change of frequency. To design the controller, the frequency model of the wind farm is first characterized. The proposed controller is then designed based on the obtained open loop system. The stability region associated with the controller parameters is analytically determined by decomposing the closed-loop system's characteristic polynomial into the odd and even parts. The performance of the proposed controller is evaluated through extensive simulations in MATLAB/Simulink environment in a power system comprising a high penetration of VSWTs equipped with the proposed controller. Finally, based on the obtained feasible area and appropriate objective function, the optimal values associated with the controller parameters are determined using the genetic algorithm (GA). Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Parameter Analysis on Wind-Induced Vibration of UHV Cross-Rope Suspension Tower-Line
Directory of Open Access Journals (Sweden)
Xilai Li
2017-01-01
Full Text Available This paper analyzes the influences of important structural design parameters on the wind-induced response of cross-rope suspension tower-line. A finite element model of cross-rope suspension tower-line system is established, and the dynamic time-history analysis with harmonic wave superposition method is conducted. The two important structural design parameters such as initial guy pretension and sag-span ratio of suspension-rope are studied, as well as their influences on the three wind-induced vibration responses such as tensile force on guys, the reaction force on mast supports, and the along-wind displacement of the mast top; the results show that the value of sag-span ratio of suspension-rope should not be less than 1/9 and the value of guy pretension should be less than 30% of its design bearing capacity. On this occasion, the tension in guys and compression in masts would be maintained in smaller values, which can lead to a much more reasonable structure.
Artificial neural network approach to spatial estimation of wind velocity data
International Nuclear Information System (INIS)
Oztopal, Ahmet
2006-01-01
In any regional wind energy assessment, equal wind velocity or energy lines provide a common basis for meaningful interpretations that furnish essential information for proper design purposes. In order to achieve regional variation descriptions, there are methods of optimum interpolation with classical weighting functions or variogram methods in Kriging methodology. Generally, the weighting functions are logically and geometrically deduced in a deterministic manner, and hence, they are imaginary first approximations for regional variability assessments, such as wind velocity. Geometrical weighting functions are necessary for regional estimation of the regional variable at a location with no measurement, which is referred to as the pivot station from the measurements of a set of surrounding stations. In this paper, weighting factors of surrounding stations necessary for the prediction of a pivot station are presented by an artificial neural network (ANN) technique. The wind speed prediction results are compared with measured values at a pivot station. Daily wind velocity measurements in the Marmara region from 1993 to 1997 are considered for application of the ANN methodology. The model is more appropriate for winter period daily wind velocities, which are significant for energy generation in the study area. Trigonometric point cumulative semivariogram (TPCSV) approach results are compared with the ANN estimations for the same set of data by considering the correlation coefficient (R). Under and over estimation problems in objective analysis can be avoided by the ANN approach
Shoemaker, David M.
Described and listed herein with concomitant sample input and output is the Fortran IV program which estimates parameters and standard errors of estimate per parameters for parameters estimated through multiple matrix sampling. The specific program is an improved and expanded version of an earlier version. (Author/BJG)
Estimation of the Alpha Factor Parameters Using the ICDE Database
International Nuclear Information System (INIS)
Kang, Dae Il; Hwang, M. J.; Han, S. H.
2007-04-01
Detailed common cause failure (CCF) analysis generally need for the data for CCF events of other nuclear power plants because the CCF events rarely occur. KAERI has been participated at the international common cause failure data exchange (ICDE) project to get the data for the CCF events. The operation office of the ICDE project sent the CCF event data for EDG to the KAERI at December 2006. As a pilot study, we performed the detailed CCF analysis of EDGs for Yonggwang Units 3 and 4 and Ulchin Units 3 and 4 using the ICDE database. There are two onsite EDGs for each NPP. When an offsite power and the two onsite EDGs are not available, one alternate AC (AAC) diesel generator (hereafter AAC) is provided. Two onsite EDGs and the AAC are manufactured by the same company, but they are designed differently. We estimated the Alpha Factor and the CCF probability for the cases where three EDGs were assumed to be identically designed, and for those were assumed to be not identically designed. For the cases where three EDGs were assumed to be identically designed, double CCF probabilities of Yonggwang Units 3/4 and Ulchin Units 3/4 for 'fails to start' were estimated as 2.20E-4 and 2.10E-4, respectively. Triple CCF probabilities of those were estimated as 2.39E-4 and 2.42E-4, respectively. As each NPP has no experience for 'fails to run', Yonggwang Units 3/4 and Ulchin Units 3/4 have the same CCF probability. The estimated double and triple CCF probabilities for 'fails to run' are 4.21E-4 and 4.61E-4, respectively. Quantification results show that the system unavailability for the cases where the three EDGs are identical is higher than that where the three EDGs are different. The estimated system unavailability of the former case was increased by 3.4% comparing with that of the latter. As a future study, a computerization work for the estimations of the CCF parameters will be performed
Colocated MIMO Radar: Beamforming, Waveform design, and Target Parameter Estimation
Jardak, Seifallah
2014-04-01
Thanks to its improved capabilities, the Multiple Input Multiple Output (MIMO) radar is attracting the attention of researchers and practitioners alike. Because it transmits orthogonal or partially correlated waveforms, this emerging technology outperformed the phased array radar by providing better parametric identifiability, achieving higher spatial resolution, and designing complex beampatterns. To avoid jamming and enhance the signal to noise ratio, it is often interesting to maximize the transmitted power in a given region of interest and minimize it elsewhere. This problem is known as the transmit beampattern design and is usually tackled as a two-step process: a transmit covariance matrix is firstly designed by minimizing a convex optimization problem, which is then used to generate practical waveforms. In this work, we propose simple novel methods to generate correlated waveforms using finite alphabet constant and non-constant-envelope symbols. To generate finite alphabet waveforms, the proposed method maps easily generated Gaussian random variables onto the phase-shift-keying, pulse-amplitude, and quadrature-amplitude modulation schemes. For such mapping, the probability density function of Gaussian random variables is divided into M regions, where M is the number of alphabets in the corresponding modulation scheme. By exploiting the mapping function, the relationship between the cross-correlation of Gaussian and finite alphabet symbols is derived. The second part of this thesis covers the topic of target parameter estimation. To determine the reflection coefficient, spatial location, and Doppler shift of a target, maximum likelihood estimation yields the best performance. However, it requires a two dimensional search problem. Therefore, its computational complexity is prohibitively high. So, we proposed a reduced complexity and optimum performance algorithm which allows the two dimensional fast Fourier transform to jointly estimate the spatial location
Ben Mosbah, Abdallah
In order to improve the qualities of wind tunnel tests, and the tools used to perform aerodynamic tests on aircraft wings in the wind tunnel, new methodologies were developed and tested on rigid and flexible wings models. A flexible wing concept is consists in replacing a portion (lower and/or upper) of the skin with another flexible portion whose shape can be changed using an actuation system installed inside of the wing. The main purpose of this concept is to improve the aerodynamic performance of the aircraft, and especially to reduce the fuel consumption of the airplane. Numerical and experimental analyses were conducted to develop and test the methodologies proposed in this thesis. To control the flow inside the test sections of the Price-Paidoussis wind tunnel of LARCASE, numerical and experimental analyses were performed. Computational fluid dynamics calculations have been made in order to obtain a database used to develop a new hybrid methodology for wind tunnel calibration. This approach allows controlling the flow in the test section of the Price-Paidoussis wind tunnel. For the fast determination of aerodynamic parameters, new hybrid methodologies were proposed. These methodologies were used to control flight parameters by the calculation of the drag, lift and pitching moment coefficients and by the calculation of the pressure distribution around an airfoil. These aerodynamic coefficients were calculated from the known airflow conditions such as angles of attack, the mach and the Reynolds numbers. In order to modify the shape of the wing skin, electric actuators were installed inside the wing to get the desired shape. These deformations provide optimal profiles according to different flight conditions in order to reduce the fuel consumption. A controller based on neural networks was implemented to obtain desired displacement actuators. A metaheuristic algorithm was used in hybridization with neural networks, and support vector machine approaches and their
Rotor Position Estimation for Switched Reluctance Wind Generator Using Extreme Learning Machine
DEFF Research Database (Denmark)
Wang, Chao; Liu, Xiao; Chen, Zhe
2014-01-01
Switched reluctance generator (SRG) is becoming more and more attractive in wind energy applications mainly because of its high fault tolerant ability and high reliability. The position sensor is one of the vulnerable points of the SRG when exposed to harsh environments such as offshore where man...... and rotor poles . The effectiveness and accuracy of the proposed position estimation method are verified by simulation at various operating conditions.......Switched reluctance generator (SRG) is becoming more and more attractive in wind energy applications mainly because of its high fault tolerant ability and high reliability. The position sensor is one of the vulnerable points of the SRG when exposed to harsh environments such as offshore where many...... wind turbines are operating. Fast and accurate rotor position estimation is essential to promote the sensorless control as well as sensor fault tolerant operation of the SRG, which may improve the reliability of the system. This paper presents a rotor position sensorless estimation scheme for Switched...
Multiphase flow parameter estimation based on laser scattering
International Nuclear Information System (INIS)
Vendruscolo, Tiago P; Fischer, Robert; Martelli, Cicero; Da Silva, Marco J; Rodrigues, Rômulo L P; Morales, Rigoberto E M
2015-01-01
The flow of multiple constituents inside a pipe or vessel, known as multiphase flow, is commonly found in many industry branches. The measurement of the individual flow rates in such flow is still a challenge, which usually requires a combination of several sensor types. However, in many applications, especially in industrial process control, it is not necessary to know the absolute flow rate of the respective phases, but rather to continuously monitor flow conditions in order to quickly detect deviations from the desired parameters. Here we show how a simple and low-cost sensor design can achieve this, by using machine-learning techniques to distinguishing the characteristic patterns of oblique laser light scattered at the phase interfaces. The sensor is capable of estimating individual phase fluxes (as well as their changes) in multiphase flows and may be applied to safety applications due to its quick response time. (paper)
Multiphase flow parameter estimation based on laser scattering
Vendruscolo, Tiago P.; Fischer, Robert; Martelli, Cicero; Rodrigues, Rômulo L. P.; Morales, Rigoberto E. M.; da Silva, Marco J.
2015-07-01
The flow of multiple constituents inside a pipe or vessel, known as multiphase flow, is commonly found in many industry branches. The measurement of the individual flow rates in such flow is still a challenge, which usually requires a combination of several sensor types. However, in many applications, especially in industrial process control, it is not necessary to know the absolute flow rate of the respective phases, but rather to continuously monitor flow conditions in order to quickly detect deviations from the desired parameters. Here we show how a simple and low-cost sensor design can achieve this, by using machine-learning techniques to distinguishing the characteristic patterns of oblique laser light scattered at the phase interfaces. The sensor is capable of estimating individual phase fluxes (as well as their changes) in multiphase flows and may be applied to safety applications due to its quick response time.
Estimation of genetic parameters for reproductive traits in Shall sheep.
Amou Posht-e-Masari, Hesam; Shadparvar, Abdol Ahad; Ghavi Hossein-Zadeh, Navid; Hadi Tavatori, Mohammad Hossein
2013-06-01
The objective of this study was to estimate genetic parameters for reproductive traits in Shall sheep. Data included 1,316 records on reproductive performances of 395 Shall ewes from 41 sires and 136 dams which were collected from 2001 to 2007 in Shall breeding station in Qazvin province at the Northwest of Iran. Studied traits were litter size at birth (LSB), litter size at weaning (LSW), litter mean weight per lamb born (LMWLB), litter mean weight per lamb weaned (LMWLW), total litter weight at birth (TLWB), and total litter weight at weaning (TLWW). Test of significance to include fixed effects in the statistical model was performed using the general linear model procedure of SAS. The effects of lambing year and ewe age at lambing were significant (Psheep.
A possible estimation of atmospheric Cherenkov light parameters
International Nuclear Information System (INIS)
Aleksandrov, L.; Brankova, M.; Kirov, I.; Mavrodiev, S.Cht.; Mishev, A.; Stamenov, J.; Ushev, S.
1998-01-01
A method for analysis of extensive air showers initiated by primary gamma quanta of primary protons and nuclei in the atmosphere is presented. The method is based on measuring of Cherenkov light distribution in showers. A new approximation of the lateral and radial distributions is obtained on the basis of a nonlinear overdetermined inverse problem solution. The concrete mathematical model is created by analysis of recent measurements carried out by the Cherenkov wide angle timing telescope HOTOVO. The model is tested on simulated data obtained with the code CORSIKA. The method is applied to different sets of detectors of CELESTE array. A new detector array for optimal estimation of Cherenkov flux parameters is proposed
Total variation with automatic hyper-parameter estimation.
Nascimento, Jacinto; Sanches, João
2008-01-01
Medical diagnosis is often hampered by the quality of the images. This happens in a wide range of image modalities. Image noise reduction is a crucial step, however difficult to be accomplished. Bayesian algorithms have been commonly used with success, namely with additive white Gaussian noise (AWGN) model. In fact, the noise corrupting some of the most used medical imaging modalities is not additive neither Gaussian but multiplicative described by Poisson or Rayleigh distributions. This paper proposes a unified framework with automatic hyper parameters estimation. The proposed framework deals with AWGN but also with both Poisson and Rayleigh distributions. The algorithm proposed herein, is based on a maximum a posteriori (MAP) criterion with the edge preserving prior based on the total variation (TV), which avoids the distortion of relevant anatomical details. The denoising technique is performed via single parametric iterative scheme parameterized for each noise model considered. Tests with real data from several medical imaging modalities testify the performance of the algorithm.
Cosmological Parameter Estimation with Large Scale Structure Observations
Di Dio, Enea; Durrer, Ruth; Lesgourgues, Julien
2014-01-01
We estimate the sensitivity of future galaxy surveys to cosmological parameters, using the redshift dependent angular power spectra of galaxy number counts, $C_\\ell(z_1,z_2)$, calculated with all relativistic corrections at first order in perturbation theory. We pay special attention to the redshift dependence of the non-linearity scale and present Fisher matrix forecasts for Euclid-like and DES-like galaxy surveys. We compare the standard $P(k)$ analysis with the new $C_\\ell(z_1,z_2)$ method. We show that for surveys with photometric redshifts the new analysis performs significantly better than the $P(k)$ analysis. For spectroscopic redshifts, however, the large number of redshift bins which would be needed to fully profit from the redshift information, is severely limited by shot noise. We also identify surveys which can measure the lensing contribution and we study the monopole, $C_0(z_1,z_2)$.
Dynamic systems models new methods of parameter and state estimation
2016-01-01
This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics. Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated. The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamic...
Multivariate phase type distributions - Applications and parameter estimation
DEFF Research Database (Denmark)
Meisch, David
and statistical inference, is the multivariate normal distribution. Unfortunately only little is known about the general class of multivariate phase type distribution. Considering the results concerning parameter estimation and inference theory of univariate phase type distributions, the class of multivariate......The best known univariate probability distribution is the normal distribution. It is used throughout the literature in a broad field of applications. In cases where it is not sensible to use the normal distribution alternative distributions are at hand and well understood, many of these belonging...... to the class of phase type distributions. Phase type distributions have several advantages. They are versatile in the sense that they can be used to approximate any given probability distribution on the positive reals. There exist general probabilistic results for the entire class of phase type distributions...
The Small Wind Energy Estimation Tool (SWEET –a practical application for a complicated resource
Directory of Open Access Journals (Sweden)
Keith Sunderland
2013-10-01
Full Text Available Of the forms of renewable energy available, wind energy is at the forefront of the European (and Irish green initiative with wind farms supplying a significant proportion of electrical energy demand. Increasingly, this type of distributed generation (DG represents a “paradigm shift” towards increased decentralisation of energy supply. However, because of the distances of most DG from urban areas where demand is greatest, there is a loss of efficiency. One possible solution, placing smaller wind energy systems in urban areas, faces significant challenges. However, if a renewable solution to increasing energy demand is to be achieved, energy conversion systems in cities, where populations are concentrated, must be considered. That said, assessing the feasibility of small/micro wind energy systems within the built environment is still a major challenge. These systems are aerodynamically rough and heterogeneous surfaces create complex flows that disrupt the steady-state conditions ideal for the operation of small wind turbines. In particular, a considerable amount of uncertainty is attributable to the lack of understanding concerning how turbulence within urban environments affects turbine productivity. This paper addresses some of these issues by providing an improved understanding of the complexities associated with wind energy prediction. This research used detailed wind observations to model its turbulence characteristics. The data was obtained using a sonic anemometer that measures wind speed along three orthogonal axes to resolve the wind vector at a temporal resolution of 10Hz. That modelling emphasises the need for practical solutions by optimising standard meteorological observations of mean speeds, and associated standard deviations, to facilitate an improved appreciation of turbulence. The results of the modelling research are incorporated into a practical tool developed in EXCEL, namely the Small Wind Energy Estimation Tool (SWEET
Evaluation of Tropospherical Parameters Estimated In Various Routine GPS Analyses
Douza, J.
Although using always the double-differenced GPS observables and the Bernese GPS sofware processing tool, the analysis center of Geodetic observatory Pecný (AC GOP) routinely process GPS networks with different approaches for various objectives. Primarily, already 1997 GOP started to process the part of the European Reference Frame permanent network (EPN) with general delay of about 3 weeks. From the be- ginning, there was purely geodetic motivation - the precise coordinate estimation. Nevertheless, from the summer in 2001 the working group for the troposphere has started a pilot project of delivering the individual AC's ZTD products together with combining them into an unique european solution. Besides, in 1999-2000 the AC GOP was testing the near real-time (NRT) analysis for the ground-based GPS meteorology application. In 2001, the Czech Republic joined an ongoing COST-716 project focused on this topic and during the whole year, the AC GOP routinely analysed the european NRT demonstrational network. The results were delayed about 1 hour but, in addition, the GOP evaluated the same network also on post-processed basis (delayed 1-2 days) using a daily concatenated GPS data and rapid IGS orbit products. Finally, determining the subdaily precise GPS orbits, the AC GOP tested in 2000/2001 the global NRT processing on 6 hour data basis. When starting to upgrade this solution within each 3 hours (from Jan/2002), the ZTD parameters have been archived for the global NRT GPS network as well. Among these rather different analysing schemes, we can recognized important differ- ent features: e.g. the network's configurations, the use of daily or hourly GPS data, a priori products applied, reference frame realization and coordinate estimation, am- biguity resolution and general parameter handling, observation cut-off angle, data weighting and many others.In this presentation, we try to compare and evaluate all these ZTD results whenever it is possible.
Project Parameter Estimation on the Basis of an Erp Database
Directory of Open Access Journals (Sweden)
Relich Marcin
2013-12-01
Full Text Available Nowadays, more and more enterprises are using Enterprise Resource Planning (EPR systems that can also be used to plan and control the development of new products. In order to obtain a project schedule, certain parameters (e.g. duration have to be specified in an ERP system. These parameters can be defined by the employees according to their knowledge, or can be estimated on the basis of data from previously completed projects. This paper investigates using an ERP database to identify those variables that have a significant influence on the duration of a project phase. In the paper, a model of knowledge discovery from an ERP database is proposed. The presented method contains four stages of the knowledge discovery process such as data selection, data transformation, data mining and interpretation of patterns in the context of new product development. Among data mining techniques, a fuzzy neural system is chosen to seek relationships on the basis of data from completed projects stored in an ERP system.
Bayesian parameter estimation for stochastic models of biological cell migration
Dieterich, Peter; Preuss, Roland
2013-08-01
Cell migration plays an essential role under many physiological and patho-physiological conditions. It is of major importance during embryonic development and wound healing. In contrast, it also generates negative effects during inflammation processes, the transmigration of tumors or the formation of metastases. Thus, a reliable quantification and characterization of cell paths could give insight into the dynamics of these processes. Typically stochastic models are applied where parameters are extracted by fitting models to the so-called mean square displacement of the observed cell group. We show that this approach has several disadvantages and problems. Therefore, we propose a simple procedure directly relying on the positions of the cell's trajectory and the covariance matrix of the positions. It is shown that the covariance is identical with the spatial aging correlation function for the supposed linear Gaussian models of Brownian motion with drift and fractional Brownian motion. The technique is applied and illustrated with simulated data showing a reliable parameter estimation from single cell paths.
Genetic parameter estimates and identification of superior white maize populations
Directory of Open Access Journals (Sweden)
Sara Regina Silvestrin Rovaris
2017-04-01
Full Text Available In Brazil, there is a shortage of white maize cultivars and genetic studies for special maize breeding programs. This study aimed to identify populations and promising hybrid white maize for main agronomic traits and grits processing and to estimate the genetic parameters of parents and heterosis. In the 2012/13 growing season, fifteen hybrids were obtained by complete diallel crosses, and six parental and commercial check varieties were evaluated for: female flowering (FF, ear height (EH, grain yield (GY, ear length (EL, volumetric mass (VM and grits processing (GP in two locations in São Paulo State, Campinas and Mococa, using a randomized block design. Analyses of variance were carried out, and diallel crosses were performed using the Gardner and Eberhart model. The populations P3 and P6 stood out because of the estimated effects of the parents and of heterosis; the studied characters are promising for obtaining new lines and forming composites. For GP, the treatments showed no differences, implying the need to introduce new sources of germplasm.
Estimation of fracture parameters using elastic full-waveform inversion
Zhang, Zhendong
2017-08-17
Current methodologies to characterize fractures at the reservoir scale have serious limitations in spatial resolution and suffer from uncertainties in the inverted parameters. Here, we propose to estimate the spatial distribution and physical properties of fractures using full-waveform inversion (FWI) of multicomponent surface seismic data. An effective orthorhombic medium with five clusters of vertical fractures distributed in a checkboard fashion is used to test the algorithm. A shape regularization term is added to the objective function to improve the estimation of the fracture azimuth, which is otherwise poorly constrained. The cracks are assumed to be penny-shaped to reduce the nonuniqueness in the inverted fracture weaknesses and achieve a faster convergence. To better understand the inversion results, we analyze the radiation patterns induced by the perturbations in the fracture weaknesses and orientation. Due to the high-resolution potential of elastic FWI, the developed algorithm can recover the spatial fracture distribution and identify localized “sweet spots” of intense fracturing. However, the fracture azimuth can be resolved only using long-offset data.
Burkatovskaya, Yuliya Borisovna; Kabanova, T.; Khaustov, Pavel Aleksandrovich
2016-01-01
CUSUM algorithm for controlling chain state switching in the Markov modulated Poissonprocess was investigated via simulation. Recommendations concerning the parameter choice were givensubject to characteristics of the process. Procedure of the process parameter estimation was described.
Aryan, H.; Sibeck, D. G.; Balikhin, M. A.; Agapitov, O. V.; Kletzing, C.
2016-12-01
Highly energetic electrons in the Earth's Van Allen radiation belts can cause serious damage to spacecraft electronic systems, and affect the atmospheric composition if they precipitate into the upper atmosphere. Whistler mode chorus waves have attracted significant attention in recent decades for their crucial role in the acceleration and loss of energetic electrons that ultimately change the dynamics of the radiation belts. The distribution of these waves in the inner magnetosphere is commonly presented as a function of geomagnetic activity. However, geomagnetic indices are non-specific parameters that are compiled from imperfectly covered ground based measurements. The present study uses wave data from the two Van Allen Probes to present the distribution of lower band chorus waves not only as functions of single geomagnetic index and solar wind parameters, but also as functions of combined parameters. Also the current study takes advantage of the unique equatorial orbit of the Van Allen Probes to estimate the average scale size of chorus wave packets, during close separations between the two spacecraft, as a function of radial distance, magnetic latitude, and geomagnetic activity respectively. Results show that the average scale size of chorus wave packets is approximately 1300 - 2300 km. The results also show that the inclusion of combined parameters can provide better representation of the chorus wave distributions in the inner magnetosphere, and therefore can further improve our knowledge of the acceleration and loss of radiation belt electrons.
Aryan, Homayon; Sibeck, David; Balikhin, Michael; Agapitov, Oleksiy; Kletzing, Craig
2016-01-01
Highly energetic electrons in the Earths Van Allen radiation belts can cause serious damage to spacecraft electronic systems and affect the atmospheric composition if they precipitate into the upper atmosphere. Whistler mode chorus waves have attracted significant attention in recent decades for their crucial role in the acceleration and loss of energetic electrons that ultimately change the dynamics of the radiation belts. The distribution of these waves in the inner magnetosphere is commonly presented as a function of geomagnetic activity. However, geomagnetic indices are nonspecific parameters that are compiled from imperfectly covered ground based measurements. The present study uses wave data from the two Van Allen Probes to present the distribution of lower band chorus waves not only as functions of single geomagnetic index and solar wind parameters but also as functions of combined parameters. Also the current study takes advantage of the unique equatorial orbit of the Van Allen Probes to estimate the average scale size of chorus wave packets, during close separations between the two spacecraft, as a function of radial distance, magnetic latitude, and geomagnetic activity, respectively. Results show that the average scale size of chorus wave packets is approximately 13002300 km. The results also show that the inclusion of combined parameters can provide better representation of the chorus wave distributions in the inner magnetosphere and therefore can further improve our knowledge of the acceleration and loss of radiation belt electrons.
On the estimation of wind comfort in a building environment by micro-scale simulation
Directory of Open Access Journals (Sweden)
Günter Gross
2014-06-01
Full Text Available A three-dimensional micro-scale model is used to study some aspects of wind comfort in a built-up area. The equations for calculating the mean wind have been extended by a Markov approach for short-term wind fluctuations. The model components have been successfully verified against wind tunnel measurements and observations of a field experiment. The simulated time series are used to estimate wind comfort measures. It turns out that the frequency of exceedance of prescribed thresholds depends strongly on the specification of the gust duration time. It was also possible to calculate the spatial distribution of a gust factor g$g$ depending on local wind characteristics. The simulated range is much broader than a value of g=3–3.5$g=3\\text{--}3.5$ commonly used for wind comfort assessments. Again, the order of magnitude and the bandwidth of g$g$ depends strongly on the definition of a gust.
Estimation of genetic parameters for reproductive traits in alpacas.
Cruz, A; Cervantes, I; Burgos, A; Morante, R; Gutiérrez, J P
2015-12-01
One of the main deficiencies affecting animal breeding programs in Peruvian alpacas is the low reproductive performance leading to low number of animals available to select from, decreasing strongly the selection intensity. Some reproductive traits could be improved by artificial selection, but very few information about genetic parameters exists for these traits in this specie. The aim of this study was to estimate genetic parameters for six reproductive traits in alpacas both in Suri (SU) and Huacaya (HU) ecotypes, as well as their genetic relationship with fiber and morphological traits. Dataset belonging to Pacomarca experimental farm collected between 2000 and 2014 was used. Number of records for age at first service (AFS), age at first calving (AFC), copulation time (CT), pregnancy diagnosis (PD), gestation length (GL), and calving interval (CI) were, respectively, 1704, 854, 19,770, 5874, 4290 and 934. Pedigree consisted of 7742 animals. Regarding reproductive traits, model of analysis included additive and residual random effects for all traits, and also permanent environmental effect for CT, PD, GL and CI traits, with color and year of recording as fixed effects for all the reproductive traits and also age at mating and sex of calf for GL trait. Estimated heritabilities, respectively for HU and SU were 0.19 and 0.09 for AFS, 0.45 and 0.59 for AFC, 0.04 and 0.05 for CT, 0.07 and 0.05 for PD, 0.12 and 0.20 for GL, and 0.14 and 0.09 for CI. Genetic correlations between them ranged from -0.96 to 0.70. No important genetic correlations were found between reproductive traits and fiber or morphological traits in HU. However, some moderate favorable genetic correlations were found between reproductive and either fiber and morphological traits in SU. According to estimated genetic correlations, some reproductive traits might be included as additional selection criteria in HU. Copyright © 2015 Elsevier B.V. All rights reserved.
Before-after field study of effects of wind turbine noise on polysomnographic sleep parameters.
Jalali, Leila; Bigelow, Philip; Nezhad-Ahmadi, Mohammad-Reza; Gohari, Mahmood; Williams, Diane; McColl, Steve
2016-01-01
Wind is considered one of the most advantageous alternatives to fossil energy because of its low operating cost and extensive availability. However, alleged health-related effects of exposure to wind turbine (WT) noise have attracted much public attention and various symptoms, such as sleep disturbance, have been reported by residents living close to wind developments. Prospective cohort study with synchronous measurement of noise and sleep physiologic signals was conducted to explore the possibility of sleep disturbance in people hosting new industrial WTs in Ontario, Canada, using a pre and post-exposure design. Objective and subjective sleep data were collected through polysomnography (PSG), the gold standard diagnostic test, and sleep diary. Sixteen participants were studied before and after WT installation during two consecutive nights in their own bedrooms. Both audible and infrasound noises were also concurrently measured inside the bedroom of each participant. Different noise exposure parameters were calculated (LAeq, LZeq) and analyzed in relation to whole-night sleep parameters. Results obtained from PSG show that sleep parameters were not significantly changed after exposure. However, reported sleep qualities were significantly (P = 0.008) worsened after exposure. Average noise levels during the exposure period were low to moderate and the mean of inside noise levels did not significantly change after exposure. The result of this study based on advanced sleep recording methodology together with extensive noise measurements in an ecologically valid setting cautiously suggests that there are no major changes in the sleep of participants who host new industrial WTs in their community. Further studies with a larger sample size and including comprehensive single-event analyses are warranted.
Before–After Field Study of Effects of Wind Turbine Noise on Polysomnographic Sleep Parameters
Jalali, Leila; Bigelow, Philip; Nezhad-Ahmadi, Mohammad-Reza; Gohari, Mahmood; Williams, Diane; McColl, Steve
2016-01-01
Wind is considered one of the most advantageous alternatives to fossil energy because of its low operating cost and extensive availability. However, alleged health-related effects of exposure to wind turbine (WT) noise have attracted much public attention and various symptoms, such as sleep disturbance, have been reported by residents living close to wind developments. Prospective cohort study with synchronous measurement of noise and sleep physiologic signals was conducted to explore the possibility of sleep disturbance in people hosting new industrial WTs in Ontario, Canada, using a pre and post-exposure design. Objective and subjective sleep data were collected through polysomnography (PSG), the gold standard diagnostic test, and sleep diary. Sixteen participants were studied before and after WT installation during two consecutive nights in their own bedrooms. Both audible and infrasound noises were also concurrently measured inside the bedroom of each participant. Different noise exposure parameters were calculated (LAeq, LZeq) and analyzed in relation to whole-night sleep parameters. Results obtained from PSG show that sleep parameters were not significantly changed after exposure. However, reported sleep qualities were significantly (P=0.008) worsened after exposure. Average noise levels during the exposure period were low to moderate and the mean of inside noise levels did not significantly change after exposure. The result of this study based on advanced sleep recording methodology together with extensive noise measurements in an ecologically valid setting cautiously suggests that there are no major changes in the sleep of participants who host new industrial WTs in their community. Further studies with a larger sample size and including comprehensive single-event analyses are warranted. PMID:27569407
Examining the utility of satellite-based wind sheltering estimates for lake hydrodynamic modeling
Van Den Hoek, Jamon; Read, Jordan S.; Winslow, Luke A.; Montesano, Paul; Markfort, Corey D.
2015-01-01
Satellite-based measurements of vegetation canopy structure have been in common use for the last decade but have never been used to estimate canopy's impact on wind sheltering of individual lakes. Wind sheltering is caused by slower winds in the wake of topography and shoreline obstacles (e.g. forest canopy) and influences heat loss and the flux of wind-driven mixing energy into lakes, which control lake temperatures and indirectly structure lake ecosystem processes, including carbon cycling and thermal habitat partitioning. Lakeshore wind sheltering has often been parameterized by lake surface area but such empirical relationships are only based on forested lakeshores and overlook the contributions of local land cover and terrain to wind sheltering. This study is the first to examine the utility of satellite imagery-derived broad-scale estimates of wind sheltering across a diversity of land covers. Using 30 m spatial resolution ASTER GDEM2 elevation data, the mean sheltering height, hs, being the combination of local topographic rise and canopy height above the lake surface, is calculated within 100 m-wide buffers surrounding 76,000 lakes in the U.S. state of Wisconsin. Uncertainty of GDEM2-derived hs was compared to SRTM-, high-resolution G-LiHT lidar-, and ICESat-derived estimates of hs, respective influences of land cover type and buffer width on hsare examined; and the effect of including satellite-based hs on the accuracy of a statewide lake hydrodynamic model was discussed. Though GDEM2 hs uncertainty was comparable to or better than other satellite-based measures of hs, its higher spatial resolution and broader spatial coverage allowed more lakes to be included in modeling efforts. GDEM2 was shown to offer superior utility for estimating hs compared to other satellite-derived data, but was limited by its consistent underestimation of hs, inability to detect within-buffer hs variability, and differing accuracy across land cover types. Nonetheless
DEFF Research Database (Denmark)
Ma, Ke; Liserre, Marco; Blaabjerg, Frede
2015-01-01
As a key component in the wind turbine system, the power electronic converter and its power semiconductors suffer from complicated power loadings related to environment, and are proven to have high failure rates. Therefore, correct lifetime estimation of wind power converter is crucial for the re......As a key component in the wind turbine system, the power electronic converter and its power semiconductors suffer from complicated power loadings related to environment, and are proven to have high failure rates. Therefore, correct lifetime estimation of wind power converter is crucial....... Consequently, a relative more advanced approach is proposed in this paper, which is based on the loading and strength analysis of devices and takes into account different time constants of the thermal behaviors in power converter. With the established methods for loading and lifetime estimation for power...... devices, more detailed information of the lifetime-related performance in wind power converter can be obtained. Some experimental results are also included to validate the thermal behavior of power device under different mission profiles....
Electricity Generation and Energy Cost Estimation of Large-Scale Wind Turbines in Jarandagh, Iran
Directory of Open Access Journals (Sweden)
Kasra Mohammadi
2014-01-01
Full Text Available Currently, wind energy utilization is being continuously growing so that it is regarded as a large contender of conventional fossil fuels. This study aimed at evaluating the feasibility of electricity generation using wind energy in Jarandagh situated in Qazvin Province in north-west part of Iran. The potential of wind energy in Jarandagh was investigated by analyzing the measured wind speed data between 2008 and 2009 at 40 m height. The electricity production and economic evaluation of four large-scale wind turbine models for operation at 70 m height were examined. The results showed that Jarandagh enjoys excellent potential for wind energy exploitation in 8 months of the year. The monthly wind power at 70 m height was in the range of 450.28–1661.62 W/m2, and also the annual wind power was 754.40 W/m2. The highest capacity factor was obtained using Suzlon S66/1.25 MW turbine model, while, in terms of electricity generation, Repower MM82/2.05 MW model showed the best performance with total annual energy output of 5705 MWh. The energy cost estimation results convincingly demonstrated that investing on wind farm construction using all nominated turbines is economically feasible and, among all turbines, Suzlon S66/1.25 MW model with energy cost of 0.0357 $/kWh is a better option.
Consiglio, Maria C.; Hoadley, Sherwood T.; Allen, B. Danette
2009-01-01
Wind prediction errors are known to affect the performance of automated air traffic management tools that rely on aircraft trajectory predictions. In particular, automated separation assurance tools, planned as part of the NextGen concept of operations, must be designed to account and compensate for the impact of wind prediction errors and other system uncertainties. In this paper we describe a high fidelity batch simulation study designed to estimate the separation distance required to compensate for the effects of wind-prediction errors throughout increasing traffic density on an airborne separation assistance system. These experimental runs are part of the Safety Performance of Airborne Separation experiment suite that examines the safety implications of prediction errors and system uncertainties on airborne separation assurance systems. In this experiment, wind-prediction errors were varied between zero and forty knots while traffic density was increased several times current traffic levels. In order to accurately measure the full unmitigated impact of wind-prediction errors, no uncertainty buffers were added to the separation minima. The goal of the study was to measure the impact of wind-prediction errors in order to estimate the additional separation buffers necessary to preserve separation and to provide a baseline for future analyses. Buffer estimations from this study will be used and verified in upcoming safety evaluation experiments under similar simulation conditions. Results suggest that the strategic airborne separation functions exercised in this experiment can sustain wind prediction errors up to 40kts at current day air traffic density with no additional separation distance buffer and at eight times the current day with no more than a 60% increase in separation distance buffer.
Balas, Mark J.; Thapa Magar, Kaman S.; Frost, Susan A.
2013-01-01
A theory called Adaptive Disturbance Tracking Control (ADTC) is introduced and used to track the Tip Speed Ratio (TSR) of 5 MW Horizontal Axis Wind Turbine (HAWT). Since ADTC theory requires wind speed information, a wind disturbance generator model is combined with lower order plant model to estimate the wind speed as well as partial states of the wind turbine. In this paper, we present a proof of stability and convergence of ADTC theory with lower order estimator and show that the state feedback can be adaptive.
Energy Technology Data Exchange (ETDEWEB)
Badger, J.; Giebel, G.; Guo Larsen, X.; Skov Nielsen, T.; Aalborg Nielsen, H.; Madsen, Henrik; Toefting, J.
2007-06-15
In this report investigations using atmospheric stability measures to improve wind speed predictions at wind farm sites are described. Various stability measures have been calculated based on numerical weather prediction model output. Their ability to improve the wind speed predictions is assessed at three locations. One of the locations is in complex terrain. Mesoscale modelling has been carried out using KAMM at this location. The characteristics of the measured winds are captured well by the mesoscale modelling. It can be seen that the atmospheric stability plays an important role in determining how the flow is influence by the terrain. A prediction system employing a look-up table approach based on wind class simulations is presented. The mesoscale modelling results produced by KAMM were validated using an alternative mesoscale model called WRF. A good agreement in the results of KAMM and WRF was found. It is shown that including a stability parameter in physical and/or statistical modelling can improve the wind speed predictions at a wind farm site. A concept for the inclusion of a stability measure in the WPPT prediction system is presented, and the testing of the concept is outlined. (au)
Performance Analysis of Methods for Estimating Weibull Parameters ...
African Journals Online (AJOL)
Furthermore, the comparison between the wind speed standard deviation predicted by the proposed models and the measured data showed that the MLM has a smaller relative error of -3.33% on average compared to -11.67% on average for the EPF and -8.86% on average for the GM. As a result, the MLM was precisely ...
Energy Technology Data Exchange (ETDEWEB)
Carranza, O. [Escuela Superior de Computo, Instituto Politecnico Nacional, Av. Juan de Dios Batiz S/N, Col. Lindavista, Del. Gustavo A. Madero 7738, D.F. (Mexico); Figueres, E.; Garcera, G. [Grupo de Sistemas Electronicos Industriales, Departamento de Ingenieria Electronica, Universidad Politecnica de Valencia, Camino de Vera S/N, 7F, 46020 Valencia (Spain); Gonzalez, L.G. [Departamento de Ingenieria Electronica, Universidad de los Andes, Merida (Venezuela)
2011-03-15
This paper presents a comparative study of several speed estimators to implement a sensorless speed control loop in Wind Energy Generation Systems driven by power factor correction three-phase boost rectifiers. This rectifier topology reduces the low frequency harmonics contents of the generator currents and, consequently, the generator power factor approaches unity whereas undesired vibrations of the mechanical system decrease. For implementation of the speed estimators, the compared techniques start from the measurement of electrical variables like currents and voltages, which contain low frequency harmonics of the fundamental frequency of the wind generator, as well as switching frequency components due to the boost rectifier. In this noisy environment it has been analyzed the performance of the following estimation techniques: Synchronous Reference Frame Phase Locked Loop, speed reconstruction by measuring the dc current and voltage of the rectifier and speed estimation by means of both an Extended Kalman Filter and a Linear Kalman Filter. (author)
Neural Models: An Option to Estimate Seismic Parameters of Accelerograms
Alcántara, L.; García, S.; Ovando-Shelley, E.; Macías, M. A.
2014-12-01
Seismic instrumentation for recording strong earthquakes, in Mexico, goes back to the 60´s due the activities carried out by the Institute of Engineering at Universidad Nacional Autónoma de México. However, it was after the big earthquake of September 19, 1985 (M=8.1) when the project of seismic instrumentation assumes a great importance. Currently, strong ground motion networks have been installed for monitoring seismic activity mainly along the Mexican subduction zone and in Mexico City. Nevertheless, there are other major regions and cities that can be affected by strong earthquakes and have not yet begun their seismic instrumentation program or this is still in development.Because of described situation some relevant earthquakes (e.g. Huajuapan de León Oct 24, 1980 M=7.1, Tehuacán Jun 15, 1999 M=7 and Puerto Escondido Sep 30, 1999 M= 7.5) have not been registered properly in some cities, like Puebla and Oaxaca, and that were damaged during those earthquakes. Fortunately, the good maintenance work carried out in the seismic network has permitted the recording of an important number of small events in those cities. So in this research we present a methodology based on the use of neural networks to estimate significant duration and in some cases the response spectra for those seismic events. The neural model developed predicts significant duration in terms of magnitude, epicenter distance, focal depth and soil characterization. Additionally, for response spectra we used a vector of spectral accelerations. For training the model we selected a set of accelerogram records obtained from the small events recorded in the strong motion instruments installed in the cities of Puebla and Oaxaca. The final results show that neural networks as a soft computing tool that use a multi-layer feed-forward architecture provide good estimations of the target parameters and they also have a good predictive capacity to estimate strong ground motion duration and response spectra.
Directory of Open Access Journals (Sweden)
H. Wang
2005-09-01
Full Text Available Based on 1829 well-defined substorm onsets in the Northern Hemisphere, observed during a 2-year period by the FUV Imager on board the IMAGE spacecraft, a statistical study is performed. From the combination of solar wind parameter observations by ACE and magnetic field observations by the low altitude satellite CHAMP, the location of auroral breakups in response to solar illumination and solar coupling parameters are studied. Furthermore, the correspondence of the onset location with prominent large-scale field-aligned currents and electrojets are investigated. Solar illumination and the related ionospheric conductivity have significant effects on the most probable substorm onset latitude and local time. In sunlight, substorm onsets tend to occur 1h earlier in local time and 1.5° more poleward than in darkness. The solar wind input, represented by the merging electric field, integrated over 1h prior to the substorm, correlates well with the latitude of the breakup. Most poleward latitudes of the onsets are found to range around 73° magnetic latitude during very quiet times. Field-aligned and Hall currents observed concurrently with the onset are consistent with the signature of a westward travelling surge evolving out of the Harang discontinuity. The observations suggest that the ionospheric conductivity has an influence on the location of the precipitating energetic electron which causes the auroral break-up signature. Keywords. Ionosphere (Auroral ionosphere – Magnetospheric Physics (Current systems; Magnetosphereionosphere interactions
Estimation of the ability to use a mass of air from a moving vehicle in wind turbine propulsion
Adam BAWORSKI; Krzysztof GARBALA; Piotr CZECH; Kazimierz WITASZEK
2015-01-01
This work presents division and classification of wind turbines according to the location of the axis of rotation and generated power. The work introduces applications of the wind turbines in electric energy generation with their direct development. The paper discusses indicators and exploitation parameters that characterize particular types of wind rotators. Dimension and construction factors, as well as work parameters, have been analyzed in order to choose the optimal rotator in the road i...
DEFF Research Database (Denmark)
Henriksen, Matthew Lee; Jensen, Bogi Bech
2013-01-01
Several methods of estimating the annual energy losses for wind turbine generators are investigated in this paper. Utilizing a high amount of transient simulations with motion is first demonstrated. Usage of a space-time transformation for prediction of iron losses is also explored. The methods, ...
Use of Anthropogenic Radioisotopes to Estimate Rates of Soil Redistribution by Wind
Wind erosion results in soil degradation and fugitive dust emissions. The temporal and spatial variability of aeolian processes makes local estimates of long-term average erosion costly and time consuming. Atmospheric testing of nuclear weapons during the 1950s and 1960s resulted in previously non...
Estimation of wake propagation behind the rotors of wind-powered generators
DEFF Research Database (Denmark)
Naumov, I. V.; Mikkelsen, Robert Flemming; Okulov, Valery
2016-01-01
The objectives of this work are to develop the experimental model of wake behind the wind-power generator rotor to estimate its propagation distance and the impact on the average and pulsation characteristics of incident flow with the possibility of further use of these data in the calculation mo...
AUTOMATIC ESTIMATION OF SIZE PARAMETERS USING VERIFIED COMPUTERIZED STEREOANALYSIS
Directory of Open Access Journals (Sweden)
Peter R Mouton
2011-05-01
Full Text Available State-of-the-art computerized stereology systems combine high-resolution video microscopy and hardwaresoftware integration with stereological methods to assist users in quantifying multidimensional parameters of importance to biomedical research, including volume, surface area, length, number, their variation and spatial distribution. The requirement for constant interactions between a trained, non-expert user and the targeted features of interest currently limits the throughput efficiency of these systems. To address this issue we developed a novel approach for automatic stereological analysis of 2-D images, Verified Computerized Stereoanalysis (VCS. The VCS approach minimizes the need for user interactions with high contrast [high signal-to-noise ratio (S:N] biological objects of interest. Performance testing of the VCS approach confirmed dramatic increases in the efficiency of total object volume (size estimation, without a loss of accuracy or precision compared to conventional computerized stereology. The broad application of high efficiency VCS to high-contrast biological objects on tissue sections could reduce labor costs, enhance hypothesis testing, and accelerate the progress of biomedical research focused on improvements in health and the management of disease.
Model-Based Material Parameter Estimation for Terahertz Reflection Spectroscopy
Kniffin, Gabriel Paul
Many materials such as drugs and explosives have characteristic spectral signatures in the terahertz (THz) band. These unique signatures imply great promise for spectral detection and classification using THz radiation. While such spectral features are most easily observed in transmission, real-life imaging systems will need to identify materials of interest from reflection measurements, often in non-ideal geometries. One important, yet commonly overlooked source of signal corruption is the etalon effect -- interference phenomena caused by multiple reflections from dielectric layers of packaging and clothing likely to be concealing materials of interest in real-life scenarios. This thesis focuses on the development and implementation of a model-based material parameter estimation technique, primarily for use in reflection spectroscopy, that takes the influence of the etalon effect into account. The technique is adapted from techniques developed for transmission spectroscopy of thin samples and is demonstrated using measured data taken at the Northwest Electromagnetic Research Laboratory (NEAR-Lab) at Portland State University. Further tests are conducted, demonstrating the technique's robustness against measurement noise and common sources of error.
Bayesian analysis of inflation: Parameter estimation for single field models
International Nuclear Information System (INIS)
Mortonson, Michael J.; Peiris, Hiranya V.; Easther, Richard
2011-01-01
Future astrophysical data sets promise to strengthen constraints on models of inflation, and extracting these constraints requires methods and tools commensurate with the quality of the data. In this paper we describe ModeCode, a new, publicly available code that computes the primordial scalar and tensor power spectra for single-field inflationary models. ModeCode solves the inflationary mode equations numerically, avoiding the slow roll approximation. It is interfaced with CAMB and CosmoMC to compute cosmic microwave background angular power spectra and perform likelihood analysis and parameter estimation. ModeCode is easily extendable to additional models of inflation, and future updates will include Bayesian model comparison. Errors from ModeCode contribute negligibly to the error budget for analyses of data from Planck or other next generation experiments. We constrain representative single-field models (φ n with n=2/3, 1, 2, and 4, natural inflation, and 'hilltop' inflation) using current data, and provide forecasts for Planck. From current data, we obtain weak but nontrivial limits on the post-inflationary physics, which is a significant source of uncertainty in the predictions of inflationary models, while we find that Planck will dramatically improve these constraints. In particular, Planck will link the inflationary dynamics with the post-inflationary growth of the horizon, and thus begin to probe the ''primordial dark ages'' between TeV and grand unified theory scale energies.
Comparative study on parameter estimation methods for attenuation relationships
Sedaghati, Farhad; Pezeshk, Shahram
2016-12-01
In this paper, the performance and advantages and disadvantages of various regression methods to derive coefficients of an attenuation relationship have been investigated. A database containing 350 records out of 85 earthquakes with moment magnitudes of 5-7.6 and Joyner-Boore distances up to 100 km in Europe and the Middle East has been considered. The functional form proposed by Ambraseys et al (2005 Bull. Earthq. Eng. 3 1-53) is selected to compare chosen regression methods. Statistical tests reveal that although the estimated parameters are different for each method, the overall results are very similar. In essence, the weighted least squares method and one-stage maximum likelihood perform better than the other considered regression methods. Moreover, using a blind weighting matrix or a weighting matrix related to the number of records would not yield in improving the performance of the results. Further, to obtain the true standard deviation, the pure error analysis is necessary. Assuming that the correlation between different records of a specific earthquake exists, the one-stage maximum likelihood considering the true variance acquired by the pure error analysis is the most preferred method to compute the coefficients of a ground motion predication equation.
Two methods for estimating aeroelastic damping of operational wind turbine modes from experiments
DEFF Research Database (Denmark)
Hansen, Morten Hartvig; Thomsen, Kenneth; Fuglsang, Peter
2006-01-01
The theory and results of two experimental methods for estimating the modal damping of a wind turbine during operation are presented. Estimations of the aeroelastic damping of the operational turbine modes (including the effects of the aerodynamic forces) give a quantitative view of the stability...... the deterministic excitation, and the modal frequencies and damping of the first tower and first edgewise whirling modes are extracted. Copyright © 2006 John Wiley & Sons, Ltd....
DEFF Research Database (Denmark)
Bajrić, Anela; Høgsberg, Jan Becker; Rüdinger, Finn
2018-01-01
with a particular focus on damping estimation of wind turbine towers. In the design of offshore structures the estimates of damping are crucial for tuning of the numerical model. The errors of damping estimates are evaluated from simulated tower response of an aeroelastic model of an 8 MW offshorewind turbine...... techniques are discussed and illustrated with respect to signal noise, measurement time, vibration amplitudes and stationarity of the ambient response. The best bias-variance error trade-off of damping estimates is obtained by the COV-SSI. The proposed automated procedure is validated by real vibration...
Estimating of a nonlinear power curve for a Wind Turbine Generator
Calif, R.; Schmitt, F. G.
2012-04-01
The output power from a Wind Turbine Generator (WTG) is an intermittent resource, due to the high variability of the atmospheric wind at all spatial or temporal scales ranging from large scale variations to very short variations. Generally, a function transfer or a power curve of WTG is estimated with the IEC standard 61400 - 12 giving a relation of coupling between the measured wind speed and the output power for the considered WTG. However, this relation is a statistical representation and not takes into account the dynamics of the power output, more precisely on small time scales. The goal is to provide a method to estimate and to model the function transfer of a WTG, in order to synthesize the output power mimicking the statistical and the dynamical properties of the real output power. For that, we study the statistics of power curve in the multifractal framework motivated by the presence of spectral scaling for the wind speed and the output power data from a WTG. The first step consists to quantify the power curve or the transfer function of two intermittent stochastic processes such as the wind speed u(t) and the output power p(t) at all temporal scales and at all intensities. In this study, firstly, we define the time increment of the wind speed measurement u'(t) = u(t + τ) - u(t) and the time increment of the output power measurement p'(t) = p(t + τ) - p(t) characterized by mth and nth order structure functions to estimate the exponent functions ζu'(m) and ζp'(n) that characterize respectively the multifractal properties of the wind speed fluctuations u'(t) and the output power fluctuations p'(t) from the WTG. The exponent function ζ defines the types of scaling behavior of a process: if ζ is linear the statistical behavior is monoscaling corresponding to a monofractal process. If ζ is nonlinear and concave, the statistical behavior is multiscaling corresponding to a multifractal process. The concavity of this function is a characteristic of the
Underwater Acoustic Measurements to Estimate Wind and Rainfall in the Mediterranean Sea
Directory of Open Access Journals (Sweden)
Sara Pensieri
2015-01-01
Full Text Available Oceanic ambient noise measurements can be analyzed to obtain qualitative and quantitative information about wind and rainfall phenomena over the ocean filling the existing gap of reliable meteorological observations at sea. The Ligurian Sea Acoustic Experiment was designed to collect long-term synergistic observations from a passive acoustic recorder and surface sensors (i.e., buoy mounted rain gauge and anemometer and weather radar to support error analysis of rainfall rate and wind speed quantification techniques developed in past studies. The study period included combination of high and low wind and rainfall episodes and two storm events that caused two floods in the vicinity of La Spezia and in the city of Genoa in 2011. The availability of high resolution in situ meteorological data allows improving data processing technique to detect and especially to provide effective estimates of wind and rainfall at sea. Results show a very good correspondence between estimates provided by passive acoustic recorder algorithm and in situ observations for both rainfall and wind phenomena and demonstrate the potential of using measurements provided by passive acoustic instruments in open sea for early warning of approaching coastal storms, which for the Mediterranean coastal areas constitutes one of the main causes of recurrent floods.
Total cost estimates for large-scale wind scenarios in UK
International Nuclear Information System (INIS)
Dale, Lewis; Milborrow, David; Slark, Richard; Strbac, Goran
2004-01-01
The recent UK Energy White Paper suggested that the Government should aim to secure 20% of electricity from renewable sources by 2020. A number of estimates of the extra cost of such a commitment have been made, but these have not necessarily included all the relevant cost components. This analysis sets out to identify these and to calculate the extra cost to the electricity consumer, assuming all the renewable electricity is sourced from wind energy. This enables one of the more controversial issues--the implications of wind intermittency--to be addressed. The basis of the assumptions associated with generating costs, extra balancing costs and distribution and transmission system reinforcement costs are all clearly identified and the total costs of a '20% wind' scenario are compared with a scenario where a similar amount of energy is generated by gas-fired plant. This enables the extra costs of the renewables scenario to be determined. The central estimate of the extra costs to electricity consumers is just over 0.3 p/kW h in current prices (around 5% extra on average domestic unit prices). Sensitivity analyses examine the implications of differing assumptions. The extra cost would rise if the capital costs of wind generation fall slower than anticipated, but would fall if gas prices rise more rapidly than has been assumed, or if wind plant are more productive. Even if it is assumed that wind has no capacity displacement value, the added cost to the electricity consumer rises by less than 0.1 p/kW h. It is concluded that there does not appear to be any technical reason why a substantial proportion of the country's electricity requirements could not be delivered by wind
Wind climate estimation using WRF model output: method and model sensitivities over the sea
DEFF Research Database (Denmark)
Hahmann, Andrea N.; Vincent, Claire Louise; Peña, Alfredo
2015-01-01
setup parameters. The results of the year-long sensitivity simulations show that the long-term mean wind speed simulated by the WRF model offshore in the region studied is quite insensitive to the global reanalysis, the number of vertical levels, and the horizontal resolution of the sea surface...... temperature used as lower boundary conditions. Also, the strength and form (grid vs spectral) of the nudging is quite irrelevant for the mean wind speed at 100 m. Large sensitivity is found to the choice of boundary layer parametrization, and to the length of the period that is discarded as spin-up to produce...
Chen, Li; Han, Ting-Ting; Li, Tao; Ji, Ya-Qin; Bai, Zhi-Peng; Wang, Bin
2012-07-01
Due to the lack of a prediction model for current wind erosion in China and the slow development for such models, this study aims to predict the wind erosion of soil and the dust emission and develop a prediction model for wind erosion in Tianjin by investigating the structure, parameter systems and the relationships among the parameter systems of the prediction models for wind erosion in typical areas, using the U.S. wind erosion prediction system (WEPS) as reference. Based on the remote sensing technique and the test data, a parameter system was established for the prediction model of wind erosion and dust emission, and a model was developed that was suitable for the prediction of wind erosion and dust emission in Tianjin. Tianjin was divided into 11 080 blocks with a resolution of 1 x 1 km2, among which 7 778 dust emitting blocks were selected. The parameters of the blocks were localized, including longitude, latitude, elevation and direction, etc.. The database files of blocks were localized, including wind file, climate file, soil file and management file. The weps. run file was edited. Based on Microsoft Visualstudio 2008, secondary development was done using C + + language, and the dust fluxes of 7 778 blocks were estimated, including creep and saltation fluxes, suspension fluxes and PM10 fluxes. Based on the parameters of wind tunnel experiments in Inner Mongolia, the soil measurement data and climate data in suburbs of Tianjin, the wind erosion module, wind erosion fluxes, dust emission release modulus and dust release fluxes were calculated for the four seasons and the whole year in suburbs of Tianjin. In 2009, the total creep and saltation fluxes, suspension fluxes and PM10 fluxes in the suburbs of Tianjin were 2.54 x 10(6) t, 1.25 x 10(7) t and 9.04 x 10(5) t, respectively, among which, the parts pointing to the central district were 5.61 x 10(5) t, 2.89 x 10(6) t and 2.03 x 10(5) t, respectively.
Automated Modal Parameter Estimation of Civil Engineering Structures
DEFF Research Database (Denmark)
Andersen, Palle; Brincker, Rune; Goursat, Maurice
In this paper the problems of doing automatic modal parameter extraction of ambient excited civil engineering structures is considered. Two different approaches for obtaining the modal parameters automatically are presented: The Frequency Domain Decomposition (FDD) technique and a correlation...
Obukhov, S. G.; Plotnikov, I. A.; Masolov, V. G.
2018-01-01
The article presents an original technique for selecting parameters and evaluating the efficiency of wind-diesel power plants for isolated power supply systems. The initial data to perform energy calculations are simulation models of electric load and wind speed. The load is simulated using typical schedules of electric loads of a decentralized consumer, taking into account a random component for each hour of the day. To create a simulation model of the wind, a typical climatic series of wind speeds at a prospective site of the power plant has been constructed according to the data of long-term meteorological observations. The proposed technique was verified through the example of choosing a wind-diesel power plant for the village of Ust-Olenyok of the Republic of Sakha (Yakutia).
Directory of Open Access Journals (Sweden)
V. M. Khade
2013-03-01
Full Text Available The ensemble adjustment Kalman filter (EAKF is used to estimate the erodibility fraction parameter field in a coupled meteorology and dust aerosol model (Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS over the Sahara desert. Erodibility is often employed as the key parameter to map dust source. It is used along with surface winds (or surface wind stress to calculate dust emissions. Using the Saharan desert as a test bed, a perfect model Observation System Simulation Experiments (OSSEs with 40 ensemble members, and observations of aerosol optical depth (AOD, the EAKF is shown to recover correct values of erodibility at about 80% of the points in the domain. It is found that dust advected from upstream grid points acts as noise and complicates erodibility estimation. It is also found that the rate of convergence is significantly impacted by the structure of the initial distribution of erodibility estimates; isotropic initial distributions exhibit slow convergence, while initial distributions with geographically localized structure converge more quickly. Experiments using observations of Deep Blue AOD retrievals from the MODIS satellite sensor result in erodibility estimates that are considerably lower than the values used operationally. Verification shows that the use of the tuned erodibility field results in better predictions of AOD over the west Sahara and the Arabian Peninsula.
First Passage Probability Estimation of Wind Turbines by Markov Chain Monte Carlo
DEFF Research Database (Denmark)
Sichani, Mahdi Teimouri; Nielsen, Søren R.K.
2013-01-01
Markov Chain Monte Carlo simulation has received considerable attention within the past decade as reportedly one of the most powerful techniques for the first passage probability estimation of dynamic systems. A very popular method in this direction capable of estimating probability of rare events...... of the method by modifying the conditional sampler. In this paper, applicability of the original SS is compared to the recently introduced modifications of the method on a wind turbine model. The model incorporates a PID pitch controller which aims at keeping the rotational speed of the wind turbine rotor equal...... to its nominal value. Finally Monte Carlo simulations are performed which allow assessment of the accuracy of the first passage probability estimation by the SS methods....
Vibration-based angular speed estimation for multi-stage wind turbine gearboxes
Peeters, Cédric; Leclère, Quentin; Antoni, Jérôme; Guillaume, Patrick; Helsen, Jan
2017-05-01
Most processing tools based on frequency analysis of vibration signals are only applicable for stationary speed regimes. Speed variation causes the spectral content to smear, which encumbers most conventional fault detection techniques. To solve the problem of non-stationary speed conditions, the instantaneous angular speed (IAS) is estimated. Wind turbine gearboxes however are typically multi-stage gearboxes, consisting of multiple shafts, rotating at different speeds. Fitting a sensor (e.g. a tachometer) to every single stage is not always feasible. As such there is a need to estimate the IAS of every single shaft based on the vibration signals measured by the accelerometers. This paper investigates the performance of the multi-order probabilistic approach for IAS estimation on experimental case studies of wind turbines. This method takes into account the meshing orders of the gears present in the system and has the advantage that a priori it is not necessary to associate harmonics with a certain periodic mechanical event, which increases the robustness of the method. It is found that the MOPA has the potential to easily outperform standard band-pass filtering techniques for speed estimation. More knowledge of the gearbox kinematics is beneficial for the MOPA performance, but even with very little knowledge about the meshing orders, the MOPA still performs sufficiently well to compete with the standard speed estimation techniques. This observation is proven on two different data sets, both originating from vibration measurements on the gearbox housing of a wind turbine.
Bootstrap Standard Errors for Maximum Likelihood Ability Estimates When Item Parameters Are Unknown
Patton, Jeffrey M.; Cheng, Ying; Yuan, Ke-Hai; Diao, Qi
2014-01-01
When item parameter estimates are used to estimate the ability parameter in item response models, the standard error (SE) of the ability estimate must be corrected to reflect the error carried over from item calibration. For maximum likelihood (ML) ability estimates, a corrected asymptotic SE is available, but it requires a long test and the…
A diagnostic model to estimate winds and small-scale drag from Mars Observer PMIRR data
Barnes, J. R.
1993-01-01
Theoretical and modeling studies indicate that small-scale drag due to breaking gravity waves is likely to be of considerable importance for the circulation in the middle atmospheric region (approximately 40-100 km altitude) on Mars. Recent earth-based spectroscopic observations have provided evidence for the existence of circulation features, in particular, a warm winter polar region, associated with gravity wave drag. Since the Mars Observer PMIRR experiment will obtain temperature profiles extending from the surface up to about 80 km altitude, it will be extensively sampling middle atmospheric regions in which gravity wave drag may play a dominant role. Estimating the drag then becomes crucial to the estimation of the atmospheric winds from the PMIRR-observed temperatures. An interative diagnostic model based upon one previously developed and tested with earth satellite temperature data will be applied to the PMIRR measurements to produce estimates of the small-scale zonal drag and three-dimensional wind fields in the Mars middle atmosphere. This model is based on the primitive equations, and can allow for time dependence (the time tendencies used may be based upon those computed in a Fast Fourier Mapping procedure). The small-scale zonal drag is estimated as the residual in the zonal momentum equation; the horizontal winds having first been estimated from the meridional momentum equation and the continuity equation. The scheme estimates the vertical motions from the thermodynamic equation, and thus needs estimates of the diabatic heating based upon the observed temperatures. The latter will be generated using a radiative model. It is hoped that the diagnostic scheme will be able to produce good estimates of the zonal gravity wave drag in the Mars middle atmosphere, estimates that can then be used in other diagnostic or assimilation efforts, as well as more theoretical studies.
Energy Technology Data Exchange (ETDEWEB)
Morrison, M.L. [California State Univ., Sacramento, CA (United States); Pollock, K.H. [North Carolina State Univ., Raleigh, NC (United States)
1997-11-01
One of the most pressing environmental concerns related to wind project development is the potential for avian fatalities caused by the turbines. The goal of this project is to develop a useful, practical modeling framework for evaluating potential wind power plant impacts that can be generalized to most bird species. This modeling framework could be used to get a preliminary understanding of the likelihood of significant impacts to birds, in a cost-effective way. The authors accomplish this by (1) reviewing the major factors that can influence the persistence of a wild population; (2) briefly reviewing various models that can aid in estimating population status and trend, including methods of evaluating model structure and performance; (3) reviewing survivorship and population projections; and (4) developing a framework for using models to evaluate the potential impacts of wind development on birds.
International Nuclear Information System (INIS)
Morrison, M.L.; Pollock, K.H.
1997-11-01
One of the most pressing environmental concerns related to wind project development is the potential for avian fatalities caused by the turbines. The goal of this project is to develop a useful, practical modeling framework for evaluating potential wind power plant impacts that can be generalized to most bird species. This modeling framework could be used to get a preliminary understanding of the likelihood of significant impacts to birds, in a cost-effective way. The authors accomplish this by (1) reviewing the major factors that can influence the persistence of a wild population; (2) briefly reviewing various models that can aid in estimating population status and trend, including methods of evaluating model structure and performance; (3) reviewing survivorship and population projections; and (4) developing a framework for using models to evaluate the potential impacts of wind development on birds
Time variations of oxygen emission lines and solar wind dynamic parameters in low latitude region
Jamlongkul, P.; Wannawichian, S.; Mkrtichian, D.; Sawangwit, U.; A-thano, N.
2017-09-01
Aurora phenomenon is an effect of collision between precipitating particles with gyromotion along Earth’s magnetic field and Earth’s ionospheric atoms or molecules. The particles’ precipitation occurs normally around polar regions. However, some auroral particles can reach lower latitude regions when they are highly energetic. A clear emission from Earth’s aurora is mostly from atomic oxygen. Moreover, the sun’s activities can influence the occurrence of the aurora as well. This work studies time variations of oxygen emission lines and solar wind parameters, simultaneously. The emission’s spectral lines were observed by Medium Resolution Echelle Spectrograph (MRES) along with 2.4 meters diameter telescope at Thai National Observatory, Intanon Mountain, Chiang Mai, Thailand. Oxygen (OI) emission lines were calibrated by Dech-Fits spectra processing program and Dech95 2D image processing program. The correlations between oxygen emission lines and solar wind dynamics will be analyzed. This result could be an evidence of the aurora in low latitude region.
Damage estimates from long-term structural analysis of a wind turbine in a US wind farm environment
Energy Technology Data Exchange (ETDEWEB)
Kelley, N.D. [National Renewable Energy Lab., Golden, CO (United States); Sutherland, H.J. [Sandia National Lab., Albuquerque, NM (United States)
1996-10-01
Time-domain simulations of the loads on wind energy conversion systems have been hampered in the past by the relatively long computational times for nonlinear structural analysis codes. However, recent advances in both the level of sophistication and computational efficiency of available computer hardware and the codes themselves now permit long-term simulations to be conducted in reasonable times. Thus, these codes provide a unique capability to evaluate the spectral content of the fatigue loads on a turbine. To demonstrate these capabilities, a Micon 65/13 turbine is analyzed using the YawDyn and the ADAMS dynamic analysis codes. The SNLWIND-3D simulator and measured boundary conditions are used to simulate the inflow environment that can be expected during a single, 24-hour period by a turbine residing in Row 41 of a wind farm located in San Gorgonio Pass, California. Also, long-term simulations (up to 8 hours of simulated time) with constant average inflow velocities are used to better define the characteristics of the fatigue load on the turbine. Damage calculations, using the LIFE2 fatigue analysis code and the MSU/DOE fatigue data base for composite materials, are then used to determine minimum simulation times for consistent estimates of service lifetimes.
Directory of Open Access Journals (Sweden)
Yu-Cheng Chen
2017-12-01
Full Text Available Roughness length is a critical parameter for estimation of wind conditions, and it is therefore also relevant for the estimation of human thermal conditions in urban areas. The high density of buildings in urban areas causes large changes in land coverage, thereby increasing surface roughness. This influence atmospheric flow and also leads to a reduction in urban air ventilation, thus increasing the risk of human thermal stress. In this study, a digital building model of Tainan city was used to calculate roughness length using an approach based on Voronoi cells by applying the microclimate model, SkyHelios. The model was also used to estimate the wind conditions, including the wind speed and wind direction. For estimation of the thermal conditions, this study obtained meteorological data for air temperature, relative humidity, globe temperature, wind speed, and wind direction on two specific days (31 July 2015 and 21 January 2016. To quantify the thermal stress, the physiologically equivalent temperature (PET was used to represent the thermal conditions. The wind conditions results obtained from the model indicate that even microscale conditions with vortices and corner flow can be represented with high precision and resolution. The thermal conditions results demonstrate that different created environments and microclimate conditions affect the thermal environment. The difference in PET can be up to 3 °C. This study confirmed that comparison of microclimate thermal conditions based on measurements and obtained from modeling using SkyHelios are in sufficient agreement and can be used in urban planning in the future.