Examination of Effective Dielectric Constants Derived from Non-Spherical Melting Hydrometeor

Science.gov (United States)

Liao, L.; Meneghini, R.

2009-04-01

The bright band, a layer of enhanced radar echo associated with melting hydrometeors, is often observed in stratiform rain. Understanding the microphysical properties of melting hydrometeors and their scattering and propagation effects is of great importance in accurately estimating parameters of the precipitation from spaceborne radar and radiometers. However, one of the impediments in the study of the radar signature of the melting layer is the determination of effective dielectric constants of melting hydrometeors. Although a number of mixing formulas are available to compute the effective dielectric constants, their results vary to a great extent when water is a component of the mixture, such as in the case of melting snow. It is also physically unclear as to how to select among these various formulas. Furthermore, the question remains as to whether these mixing formulas can be applied to computations of radar polarimetric parameters from non-spherical melting particles. Recently, several approaches using numerical methods have been developed to derive the effective dielectric constants of melting hydrometeors, i.e., mixtures consisting of air, ice and water, based on more realistic melting models of particles, in which the composition of the melting hydrometeor is divided into a number of identical cells. Each of these cells is then assigned in a probabilistic way to be water, ice or air according to the distribution of fractional water contents for a particular particle. While the derived effective dielectric constants have been extensively tested at various wavelengths over a range of particle sizes, these numerical experiments have been restricted to the co-polarized scattering parameters from spherical particles. As polarimetric radar has been increasingly used in the study of microphysical properties of hydrometeors, an extension of the theory to polarimetric variables should provide additional information on melting processes. To account for polarimetric

Fall Velocities of Hydrometeors in the Atmosphere: Refinements to a Continuous Analytical Power Law.

Science.gov (United States)

Khvorostyanov, Vitaly I.; Curry, Judith A.

2005-12-01

This paper extends the previous research of the authors on the unified representation of fall velocities for both liquid and crystalline particles as a power law over the entire size range of hydrometeors observed in the atmosphere. The power-law coefficients are determined as continuous analytical functions of the Best or Reynolds number or of the particle size. Here, analytical expressions are formulated for the turbulent corrections to the Reynolds number and to the power-law coefficients that describe the continuous transition from the laminar to the turbulent flow around a falling particle. A simple analytical expression is found for the correction of fall velocities for temperature and pressure. These expressions and the resulting fall velocities are compared with observations and other calculations for a range of ice crystal habits and sizes. This approach provides a continuous analytical power-law description of the terminal velocities of liquid and crystalline hydrometeors with sufficiently high accuracy and can be directly used in bin-resolving models or incorporated into parameterizations for cloud- and large-scale models and remote sensing techniques.

The role of charged ice hydrometeors in lightning initiation

DEFF Research Database (Denmark)

Babich, L. P.; Bochkov, E. I.; Neubert, Torsten

2017-01-01

and conductivity, and determine the external field intensity, at which stable streamer development is possible for different hydrometeor sizes and charge magnitudes. We find that the required charge is within the range of measured precipitation charges while the required external field is higher than observed...

Kinematic, dynamic, and thermodynamic impacts of hook-echo hydrometeors, including explorations into the utilization of polarimetric radar data

Science.gov (United States)

Askelson, Mark Anthony

Recent studies have revealed that the thermodynamic properties of the rear flank downdraft (RFD) may dictate whether or not a supercell becomes tornadic. Since hydrometeors are thought to be an important driving force for the RFD, it is postulated that they may be important to its thermodynamic properties and, possibly, to tornadogenesis. The role hook-echo hydrometeors play in driving RFDs is investigated by estimating hook-echo hydrometeor types and amounts from polarimetric radar data and by using that information to drive a relatively simple downdraft model. Soundings for the individual cases are used to initialize the downdraft model in order to replicate the environments of the storms as closely as possible. Since this effort and others like it require the quantitative utilization of radar data, issues pertaining to this are explored. In addition to analyses of coordinate transformation equations and an innovative objective analysis technique for weather radar data, the difficult problem of response functions for arbitrary weight functions and data distributions was considered. A novel approach to this problem revealed that the local response function for distance dependent weighted averaging schemes is the complex conjugate of the normalized Fourier transform of the effective weight function. This facilitates new research avenues, especially regarding analyses of irregularly spaced data. Simulations of hydrometeor driven RFDs show that hydrometeor fields inferred from radar data are able to drive significant downdrafts without the influence of vertical perturbation pressure gradients. Moreover, they reveal that above the boundary layer supercell environments are relatively resistant to downdrafts whereas within the boundary layer they are generally supportive of downdrafts. It appears that in many supercell environments relatively large hail (≥1 cm in diameter) or vertical perturbation pressure gradients may be needed to drive deep midlevel downdrafts that

Initiation of Positive Streamers near Uncharged Ice Hydrometeors in the Thundercloud Field

Science.gov (United States)

Babich, L. P.; Bochkov, E. I.

2018-05-01

Since the threshold electric field required for breakdown of air is much higher than the maximum field strength measured in thunderstorm clouds, the problem of lightning initiation still remains unsolved. According to the popular hypothesis, lightning can be initiated by a streamer discharge in the field enhanced near a hydrometeor. To verify the adequacy of this hypothesis, the development of a positive streamer propagating along the thunderstorm electric field in the vicinity of an ice needle at an air pressure corresponding to an altitude of 5 km (which is typical of the lightning initiation conditions) was simulated numerically. The hydrometeor dimensions are determined at which streamers can be initiated at different strengths of the thunderstorm electric field.

Modeling C-band single scattering properties of hydrometeors using discrete-dipole approximation and T-matrix method

International Nuclear Information System (INIS)

Tyynelae, Jani; Nousiainen, Timo; Goeke, Sabine; Muinonen, Karri

2009-01-01

We study the applicability of the discrete-dipole approximation by modeling centimeter (C-band) radar echoes for hydrometeors, and compare the results to exact theories. We use ice and water particles of various shapes with varying water-content to investigate how the backscattering, extinction, and absorption cross sections change as a function of particle radius. We also compute radar parameters, such as the differential reflectivity, the linear depolarization ratio, and the copolarized correlation coefficient. We find that using discrete-dipole approximation (DDA) to model pure ice and pure water particles at the C-band, is a lot more accurate than particles containing both ice and water. For coated particles, a large grid-size is recommended so that the coating is modeled adequately. We also find that the absorption cross section is significantly less accurate than the scattering and backscattering cross sections. The accuracy of DDA can be increased by increasing the number of dipoles, but also by using the filtered coupled dipole-option for the polarizability. This halved the relative errors in cross sections.

Hydrometeor Size Distribution Measurements by Imaging the Attenuation of a Laser Spot

Science.gov (United States)

Lane, John

2013-01-01

The optical extinction of a laser due to scattering of particles is a well-known phenomenon. In a laboratory environment, this physical principle is known as the Beer-Lambert law, and is often used to measure the concentration of scattering particles in a fluid or gas. This method has been experimentally shown to be a usable means to measure the dust density from a rocket plume interaction with the lunar surface. Using the same principles and experimental arrangement, this technique can be applied to hydrometeor size distributions, and for launch-pad operations, specifically as a passive hail detection and measurement system. Calibration of a hail monitoring system is a difficult process. In the past, it has required comparison to another means of measuring hydrometeor size and density. Using a technique recently developed for estimating the density of surface dust dispersed during a rocket landing, measuring the extinction of a laser passing through hail (or dust in the rocket case) yields an estimate of the second moment of the particle cloud, and hydrometeor size distribution in the terrestrial meteorological case. With the exception of disdrometers, instruments that measure rain and hail fall make indirect measurements of the drop-size distribution. Instruments that scatter microwaves off of hydrometeors, such as the WSR-88D (Weather Surveillance Radar 88 Doppler), vertical wind profilers, and microwave disdrometers, measure the sixth moment of the drop size distribution (DSD). By projecting a laser onto a target, changes in brightness of the laser spot against the target background during rain and hail yield a measurement of the DSD's second moment by way of the Beer-Lambert law. In order to detect the laser attenuation within the 8-bit resolution of most camera image arrays, a minimum path length is required. Depending on the intensity of the hail fall rate for moderate to heavy rainfall, a laser path length of 100 m is sufficient to measure variations in

Multiscale Analysis of the Water Content Output the NWP Model COSMO Over Switzerland and Comparison With Radar Data

Science.gov (United States)

Wolfensberger, D.; Gires, A.; Berne, A.; Tchiguirinskaia, I.; Schertzer, D. J. M.

2015-12-01

The resolution of operational numerical prediction models is typically of the order of a few kilometres meaning that small-scale features of precipitation can not be resolved explicitly. This creates the need for representative parametrizations of microphysical processes whose properties should be carefully analysed. In this study we will focus on the COSMO model which is a non-hydrostatic limited-area model, initially developed as the Lokal Model and used operationally in Switzerland and Germany. In its operational version, cloud microphysical processes are simulated with a one-moment bulk scheme where five hydrometeor classes are considered: cloud droplets, rain, ice crystals, snow, and graupel. A more sophisticated two-moment scheme is also available. The study will focus on two case studies: one in Payerne in western Switzerland in a relatively flat region and one in Davos in the eastern Swiss Alps in a more complex terrain.The objective of this work is to characterize the ability of the COSMO NWP model to reproduce the microphysics of precipitation across temporal and spatial scales as well as scaling variability. The characterization of COSMO outputs will rely on the Universal Multifractals framework, which allows to analyse and simulate geophysical fields extremely variabile over a wide range of scales with the help of a reduced number of parameters. First COSMO outputs are analysed; spatial multifractal analysis of 2D maps at various altitudes for each time steps are carried out for simulated solid, liquid, vapour and total water content. In general the fields exhibit a good quality of scaling on the whole range of available scales (2 km - 250 km), but some loss of scaling quality corresponding to the emergence of a scaling break are sometimes visible. This behaviour is not found at the same time or at the same altitude according to the water state and does not necessarily spread to the total water content. It is interpreted with the help of the underlying

Impact of Precipitating Ice Hydrometeors on Longwave Radiative Effect Estimated by a Global Cloud-System Resolving Model

Science.gov (United States)

Chen, Ying-Wen; Seiki, Tatsuya; Kodama, Chihiro; Satoh, Masaki; Noda, Akira T.

2018-02-01

Satellite observation and general circulation model (GCM) studies suggest that precipitating ice makes nonnegligible contributions to the radiation balance of the Earth. However, in most GCMs, precipitating ice is diagnosed and its radiative effects are not taken into account. Here we examine the longwave radiative impact of precipitating ice using a global nonhydrostatic atmospheric model with a double-moment cloud microphysics scheme. An off-line radiation model is employed to determine cloud radiative effects according to the amount and altitude of each type of ice hydrometeor. Results show that the snow radiative effect reaches 2 W m-2 in the tropics, which is about half the value estimated by previous studies. This effect is strongly dependent on the vertical separation of ice categories and is partially generated by differences in terminal velocities, which are not represented in GCMs with diagnostic precipitating ice. Results from sensitivity experiments that artificially change the categories and altitudes of precipitating ice show that the simulated longwave heating profile and longwave radiation field are sensitive to the treatment of precipitating ice in models. This study emphasizes the importance of incorporating appropriate treatments for the radiative effects of precipitating ice in cloud and radiation schemes in GCMs in order to capture the cloud radiative effects of upper level clouds.

Microphysical variability of vigorous Amazonian deep convection observed by CloudSat, and relevance for cloud-resolving model

Science.gov (United States)

Dodson, J. B.; Taylor, P. C.

2017-12-01

The number and varieties of both satellite cloud observations and cloud simulations are increasing rapidly. This create a challenge in identifying the best methods for quantifying the physical processes associated with deep convection, and then comparing convective observations with simulations. The use of satellite simulators in conjunction with model output is an increasingly popular method of comparison studies. However, the complexity of deep convective systems renders simplistic comparison metrics hazardous, possibly resulting is misleading or even contradicting conclusions. To investigate this, CloudSat observations of Amazonian deep convective cores (DCCs) and associated anvils are compared and contrasted with output from cloud resolving models in a manner that both highlights microphysical proprties of observed convection, and displays the effects of microphysical parameterizations on allowing robust comparisons. First, contoured frequency by altitude diagrams (CFAD) are calculated from the reflectivity fields of DCCs observed by CloudSat. This reveals two distinct modes of hydrometeor variability in the high level cloud region, with one dominated by snow and aggregates, and the other by large graupel and hail. Second, output from the superparameterized Community Atmospheric Model (SP-CAM) data are processed with the Quickbeam radar simulator to produce CFADs which can be compared with the observed CFADs. Two versions of SP-CAM are used, with one (version 4) having single-moment microphysics which excludes graupel/hail, and the other (version 5) a double-moment scheme with graupel. The change from version 4 to 5 improves the reflectivity CFAD, even without corresponding changes to non-hydrometeor fields such as vertical velocity. However, it does not produce a realistic double hydrometeor mode. Finally, the influences of microphysics are further tested in the System for Atmospheric Modeling (SAM), which allows for higher control over model parameters than

WRF Model Output

Data.gov (United States)

U.S. Environmental Protection Agency — This dataset contains WRF model output. There are three months of data: July 2012, July 2013, and January 2013. For each month, several simulations were made: A...

CMAQ Model Output

Data.gov (United States)

U.S. Environmental Protection Agency — CMAQ and CMAQ-VBS model output. This dataset is not publicly accessible because: Files too large. It can be accessed through the following means: via EPA's NCC tape...

Analysis of Propagation of Electromagnetic Waves in Atmospheric Hydrometeors on Low-Elevation Paths

Directory of Open Access Journals (Sweden)

M. Grabner

2018-04-01

Full Text Available Attenuation of electromagnetic waves in millimeter wave bands is analyzed by means of experimental measurement of received signal fluctuations on terrestrial radio links operating in frequency bands 58, 94 and 122 GHz. Long-term time series of the received signal are processed to obtain annual and two-year cumulative distributions of attenuation due to hydrometeors. The measured statistics give the attenuation higher than predicted by the model of the Recommendation ITU-R P.530. Rain intensity measured simultaneously with rain attenuation is used to obtain fitted parameters of an attenuation/intensity power-law relationship. The empirical data extracted from the experiment are compared with the results of numerical simulations of attenuation due to rain and hailstones.

Model validation and calibration based on component functions of model output

International Nuclear Information System (INIS)

Wu, Danqing; Lu, Zhenzhou; Wang, Yanping; Cheng, Lei

2015-01-01

The target in this work is to validate the component functions of model output between physical observation and computational model with the area metric. Based on the theory of high dimensional model representations (HDMR) of independent input variables, conditional expectations are component functions of model output, and the conditional expectations reflect partial information of model output. Therefore, the model validation of conditional expectations tells the discrepancy between the partial information of the computational model output and that of the observations. Then a calibration of the conditional expectations is carried out to reduce the value of model validation metric. After that, a recalculation of the model validation metric of model output is taken with the calibrated model parameters, and the result shows that a reduction of the discrepancy in the conditional expectations can help decrease the difference in model output. At last, several examples are employed to demonstrate the rationality and necessity of the methodology in case of both single validation site and multiple validation sites. - Highlights: • A validation metric of conditional expectations of model output is proposed. • HDRM explains the relationship of conditional expectations and model output. • An improved approach of parameter calibration updates the computational models. • Validation and calibration process are applied at single site and multiple sites. • Validation and calibration process show a superiority than existing methods

The multi-factor energy input–output model

International Nuclear Information System (INIS)

Guevara, Zeus; Domingos, Tiago

2017-01-01

Energy input–output analysis (EIO analysis) is a noteworthy tool for the analysis of the role of energy in the economy. However, it has relied on models that provide a limited description of energy flows in the economic system and do not allow an adequate analysis of energy efficiency. This paper introduces a novel energy input–output model, the multi-factor energy input–output model (MF-EIO model), which is obtained from a partitioning of a hybrid-unit input–output system of the economy. This model improves on current models by describing the energy flows according to the processes of energy conversion and the levels of energy use in the economy. It characterizes the vector of total energy output as a function of seven factors: two energy efficiency indicators; two characteristics of end-use energy consumption; and three economic features of the rest of the economy. Moreover, it is consistent with the standard model for EIO analysis, i.e., the hybrid-unit model. This paper also introduces an approximate version of the MF-EIO model, which is equivalent to the former under equal energy prices for industries and final consumers, but requires less data processing. The latter is composed by two linked models: a model of the energy sector in physical units, and a model of the rest of the economy in monetary units. In conclusion, the proposed modelling framework improves EIO analysis and extends EIO applications to the accounting for energy efficiency of the economy. - Highlights: • A novel energy input–output model is introduced. • It allows a more adequate analysis of energy flows than current models. • It describes energy flows according to processes of energy conversion and use. • It can be used for other environmental applications (material use and emissions). • An approximate version of the model is introduced, simpler and less data intensive.

Problems in Modelling Charge Output Accelerometers

Directory of Open Access Journals (Sweden)

Tomczyk Krzysztof

2016-12-01

Full Text Available The paper presents major issues associated with the problem of modelling change output accelerometers. The presented solutions are based on the weighted least squares (WLS method using transformation of the complex frequency response of the sensors. The main assumptions of the WLS method and a mathematical model of charge output accelerometers are presented in first two sections of this paper. In the next sections applying the WLS method to estimation of the accelerometer model parameters is discussed and the associated uncertainties are determined. Finally, the results of modelling a PCB357B73 charge output accelerometer are analysed in the last section of this paper. All calculations were executed using the MathCad software program. The main stages of these calculations are presented in Appendices A−E.

Hydrometeor discrimination in melting layer using multiparameter airborne radar measurement

Science.gov (United States)

Kumagai, H.; Meneghini, R.; Kozu, T.

1992-01-01

Results from a multiparameter airborne radar/radiometer experiment (the Typhoon experiment) are presented. The experiment was conducted in the western Pacific with the NASA DC-8 aircraft, in which a dual-wavelength at X-band and Ka-band and dual-polarization at X-band radar was installed. The signatures of dBZ(X), dBZ(Ka), LDR (linear depolarization ratio) at X-band and DZ=dBZ(X)-dBZ(Ka) are discussed for the data obtained in the penetration of the typhoon Flo. With emphasis on discrimination of hydrometeor particles, some statistical features of the brightband in stratiform rain are discussed.

Multi-model MPC with output feedback

Directory of Open Access Journals (Sweden)

J. M. Perez

2014-03-01

Full Text Available In this work, a new formulation is presented for the model predictive control (MPC of a process system that is represented by a finite set of models, each one corresponding to a different operating point. The general case is considered of systems with stable and integrating outputs in closed-loop with output feedback. For this purpose, the controller is based on a non-minimal order model where the state is built with the measured outputs and the manipulated inputs of the control system. Therefore, the state can be considered as perfectly known and, consequently, there is no need to include a state observer in the control loop. This property of the proposed modeling approach is convenient to extend previous stability results of the closed loop system with robust MPC controllers based on state feedback. The controller proposed here is based on the solution of two optimization problems that are solved sequentially at the same time step. The method is illustrated with a simulated example of the process industry. The rigorous simulation of the control of an adiabatic flash of a multi-component hydrocarbon mixture illustrates the application of the robust controller. The dynamic simulation of this process is performed using EMSO - Environment Model Simulation and Optimization. Finally, a comparison with a linear MPC using a single model is presented.

A two stage data envelopment analysis model with undesirable output

Science.gov (United States)

Shariff Adli Aminuddin, Adam; Izzati Jaini, Nur; Mat Kasim, Maznah; Nawawi, Mohd Kamal Mohd

2017-09-01

The dependent relationship among the decision making units (DMU) is usually assumed to be non-existent in the development of Data Envelopment Analysis (DEA) model. The dependency can be represented by the multi-stage DEA model, where the outputs from the precedent stage will be the inputs for the latter stage. The multi-stage DEA model evaluate both the efficiency score for each stages and the overall efficiency of the whole process. The existing multi stage DEA models do not focus on the integration with the undesirable output, in which the higher input will generate lower output unlike the normal desirable output. This research attempts to address the inclusion of such undesirable output and investigate the theoretical implication and potential application towards the development of multi-stage DEA model.

New explicit equations for the accurate calculation of the growth and evaporation of hydrometeors by the diffusion of water vapor

Science.gov (United States)

Srivastava, R. C.; Coen, J. L.

1992-01-01

The traditional explicit growth equation has been widely used to calculate the growth and evaporation of hydrometeors by the diffusion of water vapor. This paper reexamines the assumptions underlying the traditional equation and shows that large errors (10-30 percent in some cases) result if it is used carelessly. More accurate explicit equations are derived by approximating the saturation vapor-density difference as a quadratic rather than a linear function of the temperature difference between the particle and ambient air. These new equations, which reduce the error to less than a few percent, merit inclusion in a broad range of atmospheric models.

Global sensitivity analysis for models with spatially dependent outputs

International Nuclear Information System (INIS)

Iooss, B.; Marrel, A.; Jullien, M.; Laurent, B.

2011-01-01

The global sensitivity analysis of a complex numerical model often calls for the estimation of variance-based importance measures, named Sobol' indices. Meta-model-based techniques have been developed in order to replace the CPU time-expensive computer code with an inexpensive mathematical function, which predicts the computer code output. The common meta-model-based sensitivity analysis methods are well suited for computer codes with scalar outputs. However, in the environmental domain, as in many areas of application, the numerical model outputs are often spatial maps, which may also vary with time. In this paper, we introduce an innovative method to obtain a spatial map of Sobol' indices with a minimal number of numerical model computations. It is based upon the functional decomposition of the spatial output onto a wavelet basis and the meta-modeling of the wavelet coefficients by the Gaussian process. An analytical example is presented to clarify the various steps of our methodology. This technique is then applied to a real hydrogeological case: for each model input variable, a spatial map of Sobol' indices is thus obtained. (authors)

Pandemic recovery analysis using the dynamic inoperability input-output model.

Science.gov (United States)

Santos, Joost R; Orsi, Mark J; Bond, Erik J

2009-12-01

Economists have long conceptualized and modeled the inherent interdependent relationships among different sectors of the economy. This concept paved the way for input-output modeling, a methodology that accounts for sector interdependencies governing the magnitude and extent of ripple effects due to changes in the economic structure of a region or nation. Recent extensions to input-output modeling have enhanced the model's capabilities to account for the impact of an economic perturbation; two such examples are the inoperability input-output model((1,2)) and the dynamic inoperability input-output model (DIIM).((3)) These models introduced sector inoperability, or the inability to satisfy as-planned production levels, into input-output modeling. While these models provide insights for understanding the impacts of inoperability, there are several aspects of the current formulation that do not account for complexities associated with certain disasters, such as a pandemic. This article proposes further enhancements to the DIIM to account for economic productivity losses resulting primarily from workforce disruptions. A pandemic is a unique disaster because the majority of its direct impacts are workforce related. The article develops a modeling framework to account for workforce inoperability and recovery factors. The proposed workforce-explicit enhancements to the DIIM are demonstrated in a case study to simulate a pandemic scenario in the Commonwealth of Virginia.

An improved robust model predictive control for linear parameter-varying input-output models

NARCIS (Netherlands)

Abbas, H.S.; Hanema, J.; Tóth, R.; Mohammadpour, J.; Meskin, N.

2018-01-01

This paper describes a new robust model predictive control (MPC) scheme to control the discrete-time linear parameter-varying input-output models subject to input and output constraints. Closed-loop asymptotic stability is guaranteed by including a quadratic terminal cost and an ellipsoidal terminal

A sensitivity study of diffusional mass transfer of gases in tropical storm hydrometeors

Science.gov (United States)

Ghosh, Satyajit; Gumber, Siddharth; Varotsos, C.

2017-11-01

This paper quantifies mass transfer and diffusional uptake rates of gases in liquid and solid hydrometeors within a cyclonic system. The non-availability of transfer rates for trace gases diffusing into storm hydrometeors, particularly over polluted urban conurbations, often constrain modellers the world over; however, this is an essential requirement to quantify the scavenging rates over the region concerned. The present paper seeks to provide modellers with such rates. Further, all of the earlier studies apply only to temperate regimes, and surprisingly identical formulations are assumed even for tropical conditions. The present analysis fills this research gap and couples cloud morphology with the associated thermodynamics through Weather Research and Forecasting (WRF) runs for cyclone Chapala (27 October 2015-04 November 2015) which battered the coasts of Yemen (Skamarock et al. 2008). It was a good example for undertaking this sensitivity study because the vertical extent spanned from around 0.75 to 16 km—enabling uptake rate calculations over both droplet and ice phases. Many of the diffusing gases were polar; the dipole moment of sulphur dioxide (SO2) and water vapour (H2O) was also included using a full Lennard-Jones model to compute the binary diffusivities of these gases as they diffused into the droplets mixed with water vapour. The first-order uptake rate constants ranged from 2.08 × 10-07 to 3.44 × 10-06 (s-1) and 1.97 × 10-07 to 7.81 × 10-07 (s-1) for H2O and SO2 respectively. The rates are of the order of 10-09 (s-1) for diffusion of water vapour into ice crystals further aloft. Closely linked with the gas uptake rates is another crucial parameter—the mass accommodation coefficient, α. The most widely used values are 1 and 0.036 (Pruppacher and Klett 1998)—the chosen values are restrictive and warrants a closer look. In storm systems, the vertical extents are in the kilometre range. Chapala with a large vertical extent warrants a full

Constraining mass-diameter relations from hydrometeor images and cloud radar reflectivities in tropical continental and oceanic convective anvils

Science.gov (United States)

Fontaine, E.; Schwarzenboeck, A.; Delanoë, J.; Wobrock, W.; Leroy, D.; Dupuy, R.; Gourbeyre, C.; Protat, A.

2014-10-01

In this study the density of ice hydrometeors in tropical clouds is derived from a combined analysis of particle images from 2-D-array probes and associated reflectivities measured with a Doppler cloud radar on the same research aircraft. Usually, the mass-diameter m(D) relationship is formulated as a power law with two unknown coefficients (pre-factor, exponent) that need to be constrained from complementary information on hydrometeors, where absolute ice density measurement methods do not apply. Here, at first an extended theoretical study of numerous hydrometeor shapes simulated in 3-D and arbitrarily projected on a 2-D plan allowed to constrain the exponent βof the m(D) relationship from the exponent σ of the surface-diameterS(D)relationship, which is likewise written as a power law. Since S(D) always can be determined for real data from 2-D optical array probes or other particle imagers, the evolution of the m(D) exponent can be calculated. After that, the pre-factor α of m(D) is constrained from theoretical simulations of the radar reflectivities matching the measured reflectivities along the aircraft trajectory. The study was performed as part of the Megha-Tropiques satellite project, where two types of mesoscale convective systems (MCS) were investigated: (i) above the African continent and (ii) above the Indian Ocean. For the two data sets, two parameterizations are derived to calculate the vertical variability of m(D) coefficients α and β as a function of the temperature. Originally calculated (with T-matrix) and also subsequently parameterized m(D) relationships from this study are compared to other methods (from literature) of calculating m(D) in tropical convection. The significant benefit of using variable m(D) relations instead of a single m(D) relationship is demonstrated from the impact of all these m(D) relations on Z-CWC (Condensed Water Content) and Z-CWC-T-fitted parameterizations.

Model output: fact or artefact?

Science.gov (United States)

Melsen, Lieke

2015-04-01

As a third-year PhD-student, I relatively recently entered the wonderful world of scientific Hydrology. A science that has many pillars that directly impact society, for example with the prediction of hydrological extremes (both floods and drought), climate change, applications in agriculture, nature conservation, drinking water supply, etcetera. Despite its demonstrable societal relevance, hydrology is often seen as a science between two stools. Like Klemeš (1986) stated: "By their academic background, hydrologists are foresters, geographers, electrical engineers, geologists, system analysts, physicists, mathematicians, botanists, and most often civil engineers." Sometimes it seems that the engineering genes are still present in current hydrological sciences, and this results in pragmatic rather than scientific approaches for some of the current problems and challenges we have in hydrology. Here, I refer to the uncertainty in hydrological modelling that is often neglected. For over thirty years, uncertainty in hydrological models has been extensively discussed and studied. But it is not difficult to find peer-reviewed articles in which it is implicitly assumed that model simulations represent the truth rather than a conceptualization of reality. For instance in trend studies, where data is extrapolated 100 years ahead. Of course one can use different forcing datasets to estimate the uncertainty of the input data, but how to prevent that the output is not a model artefact, caused by the model structure? Or how about impact studies, e.g. of a dam impacting river flow. Measurements are often available for the period after dam construction, so models are used to simulate river flow before dam construction. Both are compared in order to qualify the effect of the dam. But on what basis can we tell that the model tells us the truth? Model validation is common nowadays, but validation only (comparing observations with model output) is not sufficient to assume that a

Water and chemical input via hydrometeors in central European mountains with Szrenica as an example

Science.gov (United States)

Błaś, M.; Sobik, M.; Polkowska, Ż.; Cichała-Kamrowska, K.

2010-07-01

Atmospheric pollutants are transferred to the ground by the contribution of various types of hydrometeors. These are atmospheric precipitation and non-precipitation components belonging to the atmospheric deposits (dew and hoarfrost as well as rime and liquid fog). Due to the different techniques concerning sampling and measurements, comparative analyses between them are often neglected. Hence, the main goal is to compare chemistry of different types of hydrometeors and their role in both: water balance and pollutants deposition. Precipitation, dew, hoarfrost, liquid fog and rime samples were collected daily all through the 2009 year at the Szrenica Mt. [1330 m a.s.l.]. It is situated in the western part of the main ridge of the Karkonosze Mts. which falls steeply northward on the Polish side and forms a distinct slope about 1000 m high. During typical westerly wind conditions the Karkonosze Mts. are exposed to highly polluted air from heavy industry densely situated at the distance of tens to hundreds kilometers on the windward side of the mountains. Precipitation is the main source of water flux at the Szrenica Mt. reaching 1430 mm annually, with the highest molar concentrations of ammonia, nitrates and sulphates (33%, 21% and 14% respectively). However the average TIC (Total Inorganic Ionic Content) of precipitation (273 µMoles•l-1) was the lowest when compared with other non-precipitation hydrometeors, discussed below. This results from relatively clean air in middle and/or upper parts of troposphere where atmospheric processes responsible for precipitation formation take place. This is in contrast with much more polluted atmospheric boundary layer being continuously polluted by various emission sources. Fog deposit tends to be the second important component of water flux at the Szrenica Mt., which forms even 50% of water delivered by atmospheric precipitation. Cloud water concentration of dissolved pollutants expressed by TIC was 3 times higher than in case

Semi-Automated Processing of Trajectory Simulator Output Files for Model Evaluation

Science.gov (United States)

2018-01-01

ARL-TR-8284 ● JAN 2018 US Army Research Laboratory Semi-Automated Processing of Trajectory Simulator Output Files for Model...Semi-Automated Processing of Trajectory Simulator Output Files for Model Evaluation 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT...although some minor changes may be needed. The program processes a GTRAJ output text file that contains results from 2 or more simulations , where each

Investigation of solar photovoltaic module power output by various models

International Nuclear Information System (INIS)

Jakhrani, A.Q.; Othman, A.K.; Rigit, A.R.H.; Baini, R.

2012-01-01

This paper aims to investigate the power output of a solar photovoltaic module by various models and to formulate a suitable model for predicting the performance of solar photovoltaic modules. The model was used to correct the configurations of solar photovoltaic systems for sustainable power supply. Different types of models namely the efficiency, power, fill factor and current-voltage characteristic curve models have been reviewed. It was found that the examined models predicted a 40% yield of the rated power in cloudy weather conditions and up to 80% in clear skies. The models performed well in terms of electrical efficiency in cloudy days if the influence of low irradiance were incorporated. Both analytical and numerical methods were employed in the formulation of improved model which gave +- 2% error when compared with the rated power output of solar photovoltaic module. The proposed model is more practical in terms of number of variables used and acceptable performance in humid atmospheres. Therefore, it could be useful for the estimation of power output of the solar photovoltaic systems in Sarawak region. (author)

Input-output model for MACCS nuclear accident impacts estimation¹

Energy Technology Data Exchange (ETDEWEB)

Outkin, Alexander V. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bixler, Nathan E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vargas, Vanessa N [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-01-27

Since the original economic model for MACCS was developed, better quality economic data (as well as the tools to gather and process it) and better computational capabilities have become available. The update of the economic impacts component of the MACCS legacy model will provide improved estimates of business disruptions through the use of Input-Output based economic impact estimation. This paper presents an updated MACCS model, bases on Input-Output methodology, in which economic impacts are calculated using the Regional Economic Accounting analysis tool (REAcct) created at Sandia National Laboratories. This new GDP-based model allows quick and consistent estimation of gross domestic product (GDP) losses due to nuclear power plant accidents. This paper outlines the steps taken to combine the REAcct Input-Output-based model with the MACCS code, describes the GDP loss calculation, and discusses the parameters and modeling assumptions necessary for the estimation of long-term effects of nuclear power plant accidents.

Modeling the power output of piezoelectric energy harvesters

KAUST Repository

Al Ahmad, Mahmoud

2011-04-30

Design of experiments and multiphysics analyses were used to develop a parametric model for a d 33-based cantilever. The analysis revealed that the most significant parameters influencing the resonant frequency are the supporting layer thickness, piezoelectric layer thickness, and cantilever length. On the other hand, the most important factors affecting the charge output arethe piezoelectric thickness and the interdigitated electrode dimensions. The accuracy of the developed model was confirmed and showed less than 1% estimation error compared with a commercial simulation package. To estimate the power delivered to a load, the electric current output from the piezoelectric generator was calculated. A circuit model was built and used to estimate the power delivered to a load, which compared favorably to experimentally published power data on actual cantilevers of similar dimensions. © 2011 TMS.

Modeling the power output of piezoelectric energy harvesters

KAUST Repository

Al Ahmad, Mahmoud; Alshareef, Husam N.

2011-01-01

Design of experiments and multiphysics analyses were used to develop a parametric model for a d 33-based cantilever. The analysis revealed that the most significant parameters influencing the resonant frequency are the supporting layer thickness, piezoelectric layer thickness, and cantilever length. On the other hand, the most important factors affecting the charge output arethe piezoelectric thickness and the interdigitated electrode dimensions. The accuracy of the developed model was confirmed and showed less than 1% estimation error compared with a commercial simulation package. To estimate the power delivered to a load, the electric current output from the piezoelectric generator was calculated. A circuit model was built and used to estimate the power delivered to a load, which compared favorably to experimentally published power data on actual cantilevers of similar dimensions. © 2011 TMS.

Adjustment of regional climate model output for modeling the climatic mass balance of all glaciers on Svalbard.

NARCIS (Netherlands)

Möller, M.; Obleitner, F.; Reijmer, C.H.; Pohjola, V.A.; Glowacki, P.; Kohler, J.

2016-01-01

Large-scale modeling of glacier mass balance relies often on the output from regional climate models (RCMs). However, the limited accuracy and spatial resolution of RCM output pose limitations on mass balance simulations at subregional or local scales. Moreover, RCM output is still rarely available

Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation

Science.gov (United States)

Urata, Kengo; Inoue, Masaki; Murayama, Dai; Adachi, Shuichi

2016-09-01

We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon.

Appropriatie spatial scales to achieve model output uncertainty goals

NARCIS (Netherlands)

Booij, Martijn J.; Melching, Charles S.; Chen, Xiaohong; Chen, Yongqin; Xia, Jun; Zhang, Hailun

2008-01-01

Appropriate spatial scales of hydrological variables were determined using an existing methodology based on a balance in uncertainties from model inputs and parameters extended with a criterion based on a maximum model output uncertainty. The original methodology uses different relationships between

Mathematical model of accelerator output characteristics and their calculation on a computer

International Nuclear Information System (INIS)

Mishulina, O.A.; Ul'yanina, M.N.; Kornilova, T.V.

1975-01-01

A mathematical model is described of output characteristics of a linear accelerator. The model is a system of differential equations. Presence of phase limitations is a specific feature of setting the problem which makes it possible to ensure higher simulation accuracy and determine a capture coefficient. An algorithm is elaborated of computing output characteristics based upon the mathematical model suggested. A capture coefficient, coordinate expectation characterizing an average phase value of the beam particles, coordinate expectation characterizing an average value of the reverse relative velocity of the beam particles as well as dispersion of these coordinates are output characteristics of the accelerator. Calculation methods of the accelerator output characteristics are described in detail. The computations have been performed on the BESM-6 computer, the characteristics computing time being 2 min 20 sec. Relative error of parameter computation averages 10 -2

An Improved Mathematical Model for Computing Power Output of Solar Photovoltaic Modules

Directory of Open Access Journals (Sweden)

Abdul Qayoom Jakhrani

2014-01-01

Full Text Available It is difficult to determine the input parameters values for equivalent circuit models of photovoltaic modules through analytical methods. Thus, the previous researchers preferred to use numerical methods. Since, the numerical methods are time consuming and need long term time series data which is not available in most developing countries, an improved mathematical model was formulated by combination of analytical and numerical methods to overcome the limitations of existing methods. The values of required model input parameters were computed analytically. The expression for output current of photovoltaic module was determined explicitly by Lambert W function and voltage was determined numerically by Newton-Raphson method. Moreover, the algebraic equations were derived for the shape factor which involves the ideality factor and the series resistance of a single diode photovoltaic module power output model. The formulated model results were validated with rated power output of a photovoltaic module provided by manufacturers using local meteorological data, which gave ±2% error. It was found that the proposed model is more practical in terms of precise estimations of photovoltaic module power output for any required location and number of variables used.

Investigation on the integral output power model of a large-scale wind farm

Institute of Scientific and Technical Information of China (English)

BAO Nengsheng; MA Xiuqian; NI Weidou

2007-01-01

The integral output power model of a large-scale wind farm is needed when estimating the wind farm's output over a period of time in the future.The actual wind speed power model and calculation method of a wind farm made up of many wind turbine units are discussed.After analyzing the incoming wind flow characteristics and their energy distributions,and after considering the multi-effects among the wind turbine units and certain assumptions,the incoming wind flow model of multi-units is built.The calculation algorithms and steps of the integral output power model of a large-scale wind farm are provided.Finally,an actual power output of the wind farm is calculated and analyzed by using the practical measurement wind speed data.The characteristics of a large-scale wind farm are also discussed.

NACP Site: Terrestrial Biosphere Model Output Data in Original Format

Data.gov (United States)

National Aeronautics and Space Administration — ABSTRACT: This data set contains the original model output data submissions from the 24 terrestrial biosphere models (TBM) that participated in the North American...

NACP Site: Terrestrial Biosphere Model Output Data in Original Format

Data.gov (United States)

National Aeronautics and Space Administration — This data set contains the original model output data submissions from the 24 terrestrial biosphere models (TBM) that participated in the North American Carbon...

Specification and Aggregation Errors in Environmentally Extended Input-Output Models

NARCIS (Netherlands)

Bouwmeester, Maaike C.; Oosterhaven, Jan

This article considers the specification and aggregation errors that arise from estimating embodied emissions and embodied water use with environmentally extended national input-output (IO) models, instead of with an environmentally extended international IO model. Model specification errors result

Modelling and Prediction of Photovoltaic Power Output Using Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Aminmohammad Saberian

2014-01-01

Full Text Available This paper presents a solar power modelling method using artificial neural networks (ANNs. Two neural network structures, namely, general regression neural network (GRNN feedforward back propagation (FFBP, have been used to model a photovoltaic panel output power and approximate the generated power. Both neural networks have four inputs and one output. The inputs are maximum temperature, minimum temperature, mean temperature, and irradiance; the output is the power. The data used in this paper started from January 1, 2006, until December 31, 2010. The five years of data were split into two parts: 2006–2008 and 2009-2010; the first part was used for training and the second part was used for testing the neural networks. A mathematical equation is used to estimate the generated power. At the end, both of these networks have shown good modelling performance; however, FFBP has shown a better performance comparing with GRNN.

Model output statistics applied to wind power prediction

Energy Technology Data Exchange (ETDEWEB)

Joensen, A; Giebel, G; Landberg, L [Risoe National Lab., Roskilde (Denmark); Madsen, H; Nielsen, H A [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)

1999-03-01

Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.

Measuring power output intermittency and unsteady loading in a micro wind farm model

OpenAIRE

Bossuyt, Juliaan; Howland, Michael; Meneveau, Charles; Meyers, Johan

2016-01-01

In this study porous disc models are used as a turbine model for a wind-tunnel wind farm experiment, allowing the measurement of the power output, thrust force and spatially averaged incoming velocity for every turbine. The model's capabilities for studying the unsteady turbine loading, wind farm power output intermittency and spatio temporal correlations between wind turbines are demonstrated on an aligned wind farm, consisting of 100 wind turbine models.

About the use of rank transformation in sensitivity analysis of model output

International Nuclear Information System (INIS)

Saltelli, Andrea; Sobol', Ilya M

1995-01-01

Rank transformations are frequently employed in numerical experiments involving a computational model, especially in the context of sensitivity and uncertainty analyses. Response surface replacement and parameter screening are tasks which may benefit from a rank transformation. Ranks can cope with nonlinear (albeit monotonic) input-output distributions, allowing the use of linear regression techniques. Rank transformed statistics are more robust, and provide a useful solution in the presence of long tailed input and output distributions. As is known to practitioners, care must be employed when interpreting the results of such analyses, as any conclusion drawn using ranks does not translate easily to the original model. In the present note an heuristic approach is taken, to explore, by way of practical examples, the effect of a rank transformation on the outcome of a sensitivity analysis. An attempt is made to identify trends, and to correlate these effects to a model taxonomy. Employing sensitivity indices, whereby the total variance of the model output is decomposed into a sum of terms of increasing dimensionality, we show that the main effect of the rank transformation is to increase the relative weight of the first order terms (the 'main effects'), at the expense of the 'interactions' and 'higher order interactions'. As a result the influence of those parameters which influence the output mostly by way of interactions may be overlooked in an analysis based on the ranks. This difficulty increases with the dimensionality of the problem, and may lead to the failure of a rank based sensitivity analysis. We suggest that the models can be ranked, with respect to the complexity of their input-output relationship, by mean of an 'Association' index I y . I y may complement the usual model coefficient of determination R y 2 as a measure of model complexity for the purpose of uncertainty and sensitivity analysis

NACP Regional: Original Observation Data and Biosphere and Inverse Model Outputs

Data.gov (United States)

National Aeronautics and Space Administration — This data set contains the originally-submitted observation measurement data, terrestrial biosphere model output data, and inverse model simulations that various...

NACP Regional: Original Observation Data and Biosphere and Inverse Model Outputs

Data.gov (United States)

National Aeronautics and Space Administration — ABSTRACT: This data set contains the originally-submitted observation measurement data, terrestrial biosphere model output data, and inverse model simulations that...

Alternative to Ritt's pseudodivision for finding the input-output equations of multi-output models.

Science.gov (United States)

Meshkat, Nicolette; Anderson, Chris; DiStefano, Joseph J

2012-09-01

Differential algebra approaches to structural identifiability analysis of a dynamic system model in many instances heavily depend upon Ritt's pseudodivision at an early step in analysis. The pseudodivision algorithm is used to find the characteristic set, of which a subset, the input-output equations, is used for identifiability analysis. A simpler algorithm is proposed for this step, using Gröbner Bases, along with a proof of the method that includes a reduced upper bound on derivative requirements. Efficacy of the new algorithm is illustrated with several biosystem model examples. Copyright © 2012 Elsevier Inc. All rights reserved.

Enhanced DEA model with undesirable output and interval data for rice growing farmers performance assessment

Energy Technology Data Exchange (ETDEWEB)

Khan, Sahubar Ali Mohd. Nadhar, E-mail: sahubar@uum.edu.my; Ramli, Razamin, E-mail: razamin@uum.edu.my; Baten, M. D. Azizul, E-mail: baten-math@yahoo.com [School of Quantitative Sciences, UUM College of Arts and Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah (Malaysia)

2015-12-11

Agricultural production process typically produces two types of outputs which are economic desirable as well as environmentally undesirable outputs (such as greenhouse gas emission, nitrate leaching, effects to human and organisms and water pollution). In efficiency analysis, this undesirable outputs cannot be ignored and need to be included in order to obtain the actual estimation of firms efficiency. Additionally, climatic factors as well as data uncertainty can significantly affect the efficiency analysis. There are a number of approaches that has been proposed in DEA literature to account for undesirable outputs. Many researchers has pointed that directional distance function (DDF) approach is the best as it allows for simultaneous increase in desirable outputs and reduction of undesirable outputs. Additionally, it has been found that interval data approach is the most suitable to account for data uncertainty as it is much simpler to model and need less information regarding its distribution and membership function. In this paper, an enhanced DEA model based on DDF approach that considers undesirable outputs as well as climatic factors and interval data is proposed. This model will be used to determine the efficiency of rice farmers who produces undesirable outputs and operates under uncertainty. It is hoped that the proposed model will provide a better estimate of rice farmers’ efficiency.

Enhanced DEA model with undesirable output and interval data for rice growing farmers performance assessment

International Nuclear Information System (INIS)

Khan, Sahubar Ali Mohd. Nadhar; Ramli, Razamin; Baten, M. D. Azizul

2015-01-01

Agricultural production process typically produces two types of outputs which are economic desirable as well as environmentally undesirable outputs (such as greenhouse gas emission, nitrate leaching, effects to human and organisms and water pollution). In efficiency analysis, this undesirable outputs cannot be ignored and need to be included in order to obtain the actual estimation of firms efficiency. Additionally, climatic factors as well as data uncertainty can significantly affect the efficiency analysis. There are a number of approaches that has been proposed in DEA literature to account for undesirable outputs. Many researchers has pointed that directional distance function (DDF) approach is the best as it allows for simultaneous increase in desirable outputs and reduction of undesirable outputs. Additionally, it has been found that interval data approach is the most suitable to account for data uncertainty as it is much simpler to model and need less information regarding its distribution and membership function. In this paper, an enhanced DEA model based on DDF approach that considers undesirable outputs as well as climatic factors and interval data is proposed. This model will be used to determine the efficiency of rice farmers who produces undesirable outputs and operates under uncertainty. It is hoped that the proposed model will provide a better estimate of rice farmers’ efficiency

Enhanced DEA model with undesirable output and interval data for rice growing farmers performance assessment

Science.gov (United States)

Khan, Sahubar Ali Mohd. Nadhar; Ramli, Razamin; Baten, M. D. Azizul

2015-12-01

Agricultural production process typically produces two types of outputs which are economic desirable as well as environmentally undesirable outputs (such as greenhouse gas emission, nitrate leaching, effects to human and organisms and water pollution). In efficiency analysis, this undesirable outputs cannot be ignored and need to be included in order to obtain the actual estimation of firms efficiency. Additionally, climatic factors as well as data uncertainty can significantly affect the efficiency analysis. There are a number of approaches that has been proposed in DEA literature to account for undesirable outputs. Many researchers has pointed that directional distance function (DDF) approach is the best as it allows for simultaneous increase in desirable outputs and reduction of undesirable outputs. Additionally, it has been found that interval data approach is the most suitable to account for data uncertainty as it is much simpler to model and need less information regarding its distribution and membership function. In this paper, an enhanced DEA model based on DDF approach that considers undesirable outputs as well as climatic factors and interval data is proposed. This model will be used to determine the efficiency of rice farmers who produces undesirable outputs and operates under uncertainty. It is hoped that the proposed model will provide a better estimate of rice farmers' efficiency.

Modelling and study on the output flow characteristics of expansion energy used hydropneumatic transformer

Energy Technology Data Exchange (ETDEWEB)

Shi, Yan; Wu, Tiecheng; Cai, Maolin; Liu, Chong [Beihang University, Beijing (China)

2016-03-15

Hydropneumatic transformer (short for HP transformer) is used to pump pressurized hydraulic oil. Whereas, due to its insufficient usage of energy and low efficiency, a new kind of HP transformer: EEUHP transformer (Expansion energy used hydropneumatic transformer) was proposed. To illustrate the characteristics of the EEUHP transformer, a mathematical model was built. To verify the mathematical model, an experimental prototype was setup and studied. Through simulation and experimental study on the EEUHP transformer, the influence of five key parameters on the output flow of the EEUHP transformer were obtained, and some conclusions can be drawn. Firstly, the mathematical model was proved to be valid. Furthermore, the EEUHP transformer costs fewer of compressed air than the normal HP transformer when the output flow of the two kinds of transformers are almost same. Moreover, with an increase in the output pressure, the output flow decreases sharply. Finally, with an increase in the effective area of hydraulic output port, the output flow increases distinctly. This research can be referred to in the performance and design optimization of the EEUHP transformers.

Conditions for Model Matching of Switched Asynchronous Sequential Machines with Output Feedback

OpenAIRE

Jung–Min Yang

2016-01-01

Solvability of the model matching problem for input/output switched asynchronous sequential machines is discussed in this paper. The control objective is to determine the existence condition and design algorithm for a corrective controller that can match the stable-state behavior of the closed-loop system to that of a reference model. Switching operations and correction procedures are incorporated using output feedback so that the controlled switched machine can show the ...

Modelling innovation performance of European regions using multi-output neural networks.

Science.gov (United States)

Hajek, Petr; Henriques, Roberto

2017-01-01

Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics) regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes.

Modelling innovation performance of European regions using multi-output neural networks.

Directory of Open Access Journals (Sweden)

Petr Hajek

Full Text Available Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes.

CONSTRUCTION OF A DYNAMIC INPUT-OUTPUT MODEL WITH A HUMAN CAPITAL BLOCK

Directory of Open Access Journals (Sweden)

Baranov A. O.

2017-03-01

Full Text Available The accumulation of human capital is an important factor of economic growth. It seems to be useful to include «human capital» as a factor of a macroeconomic model, as it helps to take into account the quality differentiation of the workforce. Most of the models usually distinguish labor force by the levels of education, while some of the factors remain unaccounted. Among them are health status and culture development level, which influence productivity level as well as gross product reproduction. Inclusion of the human capital block to the interindustry model can help to make it more reliable for economic development forecasting. The article presents a mathematical description of the extended dynamic input-output model (DIOM with a human capital block. The extended DIOM is based on the Input-Output Model from The KAMIN system (the System of Integrated Analyses of Interindustrial Information developed at the Institute of Economics and Industrial Engineering of the Siberian Branch of the Academy of Sciences of the Russian Federation and at the Novosibirsk State University. The extended input-output model can be used to analyze and forecast development of Russian economy.

System convergence in transport models: algorithms efficiency and output uncertainty

DEFF Research Database (Denmark)

Rich, Jeppe; Nielsen, Otto Anker

2015-01-01

of this paper is to analyse convergence performance for the external loop and to illustrate how an improper linkage between the converging parts can lead to substantial uncertainty in the final output. Although this loop is crucial for the performance of large-scale transport models it has not been analysed...... much in the literature. The paper first investigates several variants of the Method of Successive Averages (MSA) by simulation experiments on a toy-network. It is found that the simulation experiments produce support for a weighted MSA approach. The weighted MSA approach is then analysed on large......-scale in the Danish National Transport Model (DNTM). It is revealed that system convergence requires that either demand or supply is without random noise but not both. In that case, if MSA is applied to the model output with random noise, it will converge effectively as the random effects are gradually dampened...

Modeling the short-run effect of fiscal stimuli on GDP : A new semi-closed input-output model

NARCIS (Netherlands)

Chen, Quanrun; Dietzenbacher, Erik; Los, Bart; Yang, Cuihong

In this study, we propose a new semi-closed input-output model, which reconciles input-output analysis with modern consumption theories. It can simulate changes in household consumption behavior when exogenous stimulus policies lead to higher disposable income levels. It is useful for quantifying

Modeling the short-run effect of fiscal stimuli on GDP : A new semi-closed input-output model

NARCIS (Netherlands)

Chen, Quanrun; Dietzenbacher, Erik; Los, Bart; Yang, Cuihong

2016-01-01

In this study, we propose a new semi-closed input-output model, which reconciles input-output analysis with modern consumption theories. It can simulate changes in household consumption behavior when exogenous stimulus policies lead to higher disposable income levels. It is useful for quantifying

Multi-model analysis of terrestrial carbon cycles in Japan: reducing uncertainties in model outputs among different terrestrial biosphere models using flux observations

Science.gov (United States)

Ichii, K.; Suzuki, T.; Kato, T.; Ito, A.; Hajima, T.; Ueyama, M.; Sasai, T.; Hirata, R.; Saigusa, N.; Ohtani, Y.; Takagi, K.

2009-08-01

Terrestrial biosphere models show large uncertainties when simulating carbon and water cycles, and reducing these uncertainties is a priority for developing more accurate estimates of both terrestrial ecosystem statuses and future climate changes. To reduce uncertainties and improve the understanding of these carbon budgets, we investigated the ability of flux datasets to improve model simulations and reduce variabilities among multi-model outputs of terrestrial biosphere models in Japan. Using 9 terrestrial biosphere models (Support Vector Machine-based regressions, TOPS, CASA, VISIT, Biome-BGC, DAYCENT, SEIB, LPJ, and TRIFFID), we conducted two simulations: (1) point simulations at four flux sites in Japan and (2) spatial simulations for Japan with a default model (based on original settings) and an improved model (based on calibration using flux observations). Generally, models using default model settings showed large deviations in model outputs from observation with large model-by-model variability. However, after we calibrated the model parameters using flux observations (GPP, RE and NEP), most models successfully simulated seasonal variations in the carbon cycle, with less variability among models. We also found that interannual variations in the carbon cycle are mostly consistent among models and observations. Spatial analysis also showed a large reduction in the variability among model outputs, and model calibration using flux observations significantly improved the model outputs. These results show that to reduce uncertainties among terrestrial biosphere models, we need to conduct careful validation and calibration with available flux observations. Flux observation data significantly improved terrestrial biosphere models, not only on a point scale but also on spatial scales.

Application of a Linear Input/Output Model to Tankless Water Heaters

Energy Technology Data Exchange (ETDEWEB)

Butcher T.; Schoenbauer, B.

2011-12-31

In this study, the applicability of a linear input/output model to gas-fired, tankless water heaters has been evaluated. This simple model assumes that the relationship between input and output, averaged over both active draw and idle periods, is linear. This approach is being applied to boilers in other studies and offers the potential to make a small number of simple measurements to obtain the model parameters. These parameters can then be used to predict performance under complex load patterns. Both condensing and non-condensing water heaters have been tested under a very wide range of load conditions. It is shown that this approach can be used to reproduce performance metrics, such as the energy factor, and can be used to evaluate the impacts of alternative draw patterns and conditions.

Logistics flows and enterprise input-output models: aggregate and disaggregate analysis

NARCIS (Netherlands)

Albino, V.; Yazan, Devrim; Messeni Petruzzelli, A.; Okogbaa, O.G.

2011-01-01

In the present paper, we propose the use of enterprise input-output (EIO) models to describe and analyse the logistics flows considering spatial issues and related environmental effects associated with production and transportation processes. In particular, transportation is modelled as a specific

SISTEM KONTROL OTOMATIK DENGAN MODEL SINGLE-INPUT-DUAL-OUTPUT DALAM KENDALI EFISIENSI UMUR-PEMAKAIAN INSTRUMEN

Directory of Open Access Journals (Sweden)

S.N.M.P. Simamora

2014-10-01

Full Text Available Efficiency condition occurs when the value of the used outputs compared to the resource total that has been used almost close to the value 1 (absolute environment. An instrument to achieve efficiency if the power output level has decreased significantly in the life of the instrument used, if it compared to the previous condition, when the instrument is not equipped with additional systems (or proposed model improvement. Even more effective if the inputs model that are used in unison to achieve a homogeneous output. On this research has been designed and implemented the automatic control system for models of single input-dual-output, wherein the sampling instruments used are lamp and fan. Source voltage used is AC (alternate-current and tested using quantitative research methods and instrumentation (with measuring instruments are observed. The results obtained demonstrate the efficiency of the instrument experienced a significant current model of single-input-dual-output applied separately instrument trials such as lamp and fan when it compared to the condition or state before. And the result show that the design has been built, can also run well.

Rice growing farmers efficiency measurement using a slack based interval DEA model with undesirable outputs

Science.gov (United States)

Khan, Sahubar Ali Mohd. Nadhar; Ramli, Razamin; Baten, M. D. Azizul

2017-11-01

In recent years eco-efficiency which considers the effect of production process on environment in determining the efficiency of firms have gained traction and a lot of attention. Rice farming is one of such production processes which typically produces two types of outputs which are economic desirable as well as environmentally undesirable. In efficiency analysis, these undesirable outputs cannot be ignored and need to be included in the model to obtain the actual estimation of firm's efficiency. There are numerous approaches that have been used in data envelopment analysis (DEA) literature to account for undesirable outputs of which directional distance function (DDF) approach is the most widely used as it allows for simultaneous increase in desirable outputs and reduction of undesirable outputs. Additionally, slack based DDF DEA approaches considers the output shortfalls and input excess in determining efficiency. In situations when data uncertainty is present, the deterministic DEA model is not suitable to be used as the effects of uncertain data will not be considered. In this case, it has been found that interval data approach is suitable to account for data uncertainty as it is much simpler to model and need less information regarding the underlying data distribution and membership function. The proposed model uses an enhanced DEA model which is based on DDF approach and incorporates slack based measure to determine efficiency in the presence of undesirable factors and data uncertainty. Interval data approach was used to estimate the values of inputs, undesirable outputs and desirable outputs. Two separate slack based interval DEA models were constructed for optimistic and pessimistic scenarios. The developed model was used to determine rice farmers efficiency from Kepala Batas, Kedah. The obtained results were later compared to the results obtained using a deterministic DDF DEA model. The study found that 15 out of 30 farmers are efficient in all cases. It

Usefulness of non-linear input-output models for economic impact analyses in tourism and recreation

NARCIS (Netherlands)

Klijs, J.; Peerlings, J.H.M.; Heijman, W.J.M.

2015-01-01

In tourism and recreation management it is still common practice to apply traditional input–output (IO) economic impact models, despite their well-known limitations. In this study the authors analyse the usefulness of applying a non-linear input–output (NLIO) model, in which price-induced input

Modeling of Output Characteristics of a UV Cu+ Ne-CuBr Laser

Directory of Open Access Journals (Sweden)

Snezhana Georgieva Gocheva-Ilieva

2012-01-01

Full Text Available This paper examines experiment data for a Ne-CuBr UV copper ion laser excited by longitudinal pulsed discharge emitting in multiline regime. The flexible multivariate adaptive regression splines (MARSs method has been used to develop nonparametric regression models describing the laser output power and service life of the devices. The models have been constructed as explicit functions of 9 basic input laser characteristics. The obtained models account for local nonlinearities of the relationships within the various multivariate subregions. The built best MARS models account for over 98% of data. The models are used to estimate the investigated output laser characteristics of existing UV lasers. The capabilities for using the models in predicting existing and future experiments have been demonstrated. Specific analyses have been presented comparing the models with actual experiments. The obtained results are applicable for guiding and planning the engineering experiment. The modeling methodology can be applied for a wide range of similar lasers and laser devices.

Including model uncertainty in the model predictive control with output feedback

Directory of Open Access Journals (Sweden)

Rodrigues M.A.

2002-01-01

Full Text Available This paper addresses the development of an efficient numerical output feedback robust model predictive controller for open-loop stable systems. Stability of the closed loop is guaranteed by using an infinite horizon predictive controller and a stable state observer. The performance and the computational burden of this approach are compared to a robust predictive controller from the literature. The case used for this study is based on an industrial gasoline debutanizer column.

Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling

Science.gov (United States)

Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.

2018-05-01

Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed

On the statistical comparison of climate model output and climate data

International Nuclear Information System (INIS)

Solow, A.R.

1991-01-01

Some broad issues arising in the statistical comparison of the output of climate models with the corresponding climate data are reviewed. Particular attention is paid to the question of detecting climate change. The purpose of this paper is to review some statistical approaches to the comparison of the output of climate models with climate data. There are many statistical issues arising in such a comparison. The author will focus on some of the broader issues, although some specific methodological questions will arise along the way. One important potential application of the approaches discussed in this paper is the detection of climate change. Although much of the discussion will be fairly general, he will try to point out the appropriate connections to the detection question. 9 refs

On the statistical comparison of climate model output and climate data

International Nuclear Information System (INIS)

Solow, A.R.

1990-01-01

Some broad issues arising in the statistical comparison of the output of climate models with the corresponding climate data are reviewed. Particular attention is paid to the question of detecting climate change. The purpose of this paper is to review some statistical approaches to the comparison of the output of climate models with climate data. There are many statistical issues arising in such a comparison. The author will focus on some of the broader issues, although some specific methodological questions will arise along the way. One important potential application of the approaches discussed in this paper is the detection of climate change. Although much of the discussion will be fairly general, he will try to point out the appropriate connections to the detection question

Transport coefficient computation based on input/output reduced order models

Science.gov (United States)

Hurst, Joshua L.

The guiding purpose of this thesis is to address the optimal material design problem when the material description is a molecular dynamics model. The end goal is to obtain a simplified and fast model that captures the property of interest such that it can be used in controller design and optimization. The approach is to examine model reduction analysis and methods to capture a specific property of interest, in this case viscosity, or more generally complex modulus or complex viscosity. This property and other transport coefficients are defined by a input/output relationship and this motivates model reduction techniques that are tailored to preserve input/output behavior. In particular Singular Value Decomposition (SVD) based methods are investigated. First simulation methods are identified that are amenable to systems theory analysis. For viscosity, these models are of the Gosling and Lees-Edwards type. They are high order nonlinear Ordinary Differential Equations (ODEs) that employ Periodic Boundary Conditions. Properties can be calculated from the state trajectories of these ODEs. In this research local linear approximations are rigorously derived and special attention is given to potentials that are evaluated with Periodic Boundary Conditions (PBC). For the Gosling description LTI models are developed from state trajectories but are found to have limited success in capturing the system property, even though it is shown that full order LTI models can be well approximated by reduced order LTI models. For the Lees-Edwards SLLOD type model nonlinear ODEs will be approximated by a Linear Time Varying (LTV) model about some nominal trajectory and both balanced truncation and Proper Orthogonal Decomposition (POD) will be used to assess the plausibility of reduced order models to this system description. An immediate application of the derived LTV models is Quasilinearization or Waveform Relaxation. Quasilinearization is a Newton's method applied to the ODE operator

Early-Transition Output Decline Revisited

Directory of Open Access Journals (Sweden)

Crt Kostevc

2016-05-01

Full Text Available In this paper we revisit the issue of aggregate output decline that took place in the early transition period. We propose an alternative explanation of output decline that is applicable to Central- and Eastern-European countries. In the first part of the paper we develop a simple dynamic general equilibrium model that builds on work by Gomulka and Lane (2001. In particular, we consider price liberalization, interpreted as elimination of distortionary taxation, as a trigger of the output decline. We show that price liberalization in interaction with heterogeneous adjustment costs and non-employment benefits lead to aggregate output decline and surge in wage inequality. While these patterns are consistent with actual dynamics in CEE countries, this model cannot generate output decline in all sectors. Instead sectors that were initially taxed even exhibit output growth. Thus, in the second part we consider an alternative general equilibrium model with only one production sector and two types of labor and distortion in a form of wage compression during the socialist era. The trigger for labor mobility and consequently output decline is wage liberalization. Assuming heterogeneity of workers in terms of adjustment costs and non-employment benefits can explain output decline in all industries.

texreg: Conversion of Statistical Model Output in R to LATEX and HTML Tables

Directory of Open Access Journals (Sweden)

Philip Leifeld

2013-11-01

Full Text Available A recurrent task in applied statistics is the (mostly manual preparation of model output for inclusion in LATEX, Microsoft Word, or HTML documents usually with more than one model presented in a single table along with several goodness-of-fit statistics. However, statistical models in R have diverse object structures and summary methods, which makes this process cumbersome. This article first develops a set of guidelines for converting statistical model output to LATEX and HTML tables, then assesses to what extent existing packages meet these requirements, and finally presents the texreg package as a solution that meets all of the criteria set out in the beginning. After providing various usage examples, a blueprint for writing custom model extensions is proposed.

A Hierarchical multi-input and output Bi-GRU Model for Sentiment Analysis on Customer Reviews

Science.gov (United States)

Zhang, Liujie; Zhou, Yanquan; Duan, Xiuyu; Chen, Ruiqi

2018-03-01

Multi-label sentiment classification on customer reviews is a practical challenging task in Natural Language Processing. In this paper, we propose a hierarchical multi-input and output model based bi-directional recurrent neural network, which both considers the semantic and lexical information of emotional expression. Our model applies two independent Bi-GRU layer to generate part of speech and sentence representation. Then the lexical information is considered via attention over output of softmax activation on part of speech representation. In addition, we combine probability of auxiliary labels as feature with hidden layer to capturing crucial correlation between output labels. The experimental result shows that our model is computationally efficient and achieves breakthrough improvements on customer reviews dataset.

A model to predict the power output from wind farms

Energy Technology Data Exchange (ETDEWEB)

Landberg, L. [Riso National Lab., Roskilde (Denmark)

1997-12-31

This paper will describe a model that can predict the power output from wind farms. To give examples of input the model is applied to a wind farm in Texas. The predictions are generated from forecasts from the NGM model of NCEP. These predictions are made valid at individual sites (wind farms) by applying a matrix calculated by the sub-models of WASP (Wind Atlas Application and Analysis Program). The actual wind farm production is calculated using the Riso PARK model. Because of the preliminary nature of the results, they will not be given. However, similar results from Europe will be given.

Modelling Analysis of Forestry Input-Output Elasticity in China

Directory of Open Access Journals (Sweden)

Guofeng Wang

2016-01-01

Full Text Available Based on an extended economic model and space econometrics, this essay analyzed the spatial distributions and interdependent relationships of the production of forestry in China; also the input-output elasticity of forestry production were calculated. Results figure out there exists significant spatial correlation in forestry production in China. Spatial distribution is mainly manifested as spatial agglomeration. The output elasticity of labor force is equal to 0.6649, and that of capital is equal to 0.8412. The contribution of land is significantly negative. Labor and capital are the main determinants for the province-level forestry production in China. Thus, research on the province-level forestry production should not ignore the spatial effect. The policy-making process should take into consideration the effects between provinces on the production of forestry. This study provides some scientific technical support for forestry production.

Reactive Power Pricing Model Considering the Randomness of Wind Power Output

Science.gov (United States)

Dai, Zhong; Wu, Zhou

2018-01-01

With the increase of wind power capacity integrated into grid, the influence of the randomness of wind power output on the reactive power distribution of grid is gradually highlighted. Meanwhile, the power market reform puts forward higher requirements for reasonable pricing of reactive power service. Based on it, the article combined the optimal power flow model considering wind power randomness with integrated cost allocation method to price reactive power. Meanwhile, considering the advantages and disadvantages of the present cost allocation method and marginal cost pricing, an integrated cost allocation method based on optimal power flow tracing is proposed. The model realized the optimal power flow distribution of reactive power with the minimal integrated cost and wind power integration, under the premise of guaranteeing the balance of reactive power pricing. Finally, through the analysis of multi-scenario calculation examples and the stochastic simulation of wind power outputs, the article compared the results of the model pricing and the marginal cost pricing, which proved that the model is accurate and effective.

Caliver: An R package for CALIbration and VERification of forest fire gridded model outputs.

Science.gov (United States)

Vitolo, Claudia; Di Giuseppe, Francesca; D'Andrea, Mirko

2018-01-01

The name caliver stands for CALIbration and VERification of forest fire gridded model outputs. This is a package developed for the R programming language and available under an APACHE-2 license from a public repository. In this paper we describe the functionalities of the package and give examples using publicly available datasets. Fire danger model outputs are taken from the modeling components of the European Forest Fire Information System (EFFIS) and observed burned areas from the Global Fire Emission Database (GFED). Complete documentation, including a vignette, is also available within the package.

Input-Output model for waste management plan for Nigeria | Njoku ...

African Journals Online (AJOL)

An Input-Output Model for Waste Management Plan has been developed for Nigeria based on Leontief concept and life cycle analysis. Waste was considered as source of pollution, loss of resources, and emission of green house gasses from bio-chemical treatment and decomposition, with negative impact on the ...

DIMITRI 1.0: Beschrijving en toepassing van een dynamisch input-output model

NARCIS (Netherlands)

Wilting HC; Blom WF; Thomas R; Idenburg AM; LAE

2001-01-01

DIMITRI, the Dynamic Input-Output Model to study the Impacts of Technology Related Innovations, was developed in the framework of the RIVM Environment and Economy project to answer questions about interrelationships between economy, technology and the environment. DIMITRI, a meso-economic model,

Modeling uncertainties in workforce disruptions from influenza pandemics using dynamic input-output analysis.

Science.gov (United States)

El Haimar, Amine; Santos, Joost R

2014-03-01

Influenza pandemic is a serious disaster that can pose significant disruptions to the workforce and associated economic sectors. This article examines the impact of influenza pandemic on workforce availability within an interdependent set of economic sectors. We introduce a simulation model based on the dynamic input-output model to capture the propagation of pandemic consequences through the National Capital Region (NCR). The analysis conducted in this article is based on the 2009 H1N1 pandemic data. Two metrics were used to assess the impacts of the influenza pandemic on the economic sectors: (i) inoperability, which measures the percentage gap between the as-planned output and the actual output of a sector, and (ii) economic loss, which quantifies the associated monetary value of the degraded output. The inoperability and economic loss metrics generate two different rankings of the critical economic sectors. Results show that most of the critical sectors in terms of inoperability are sectors that are related to hospitals and health-care providers. On the other hand, most of the sectors that are critically ranked in terms of economic loss are sectors with significant total production outputs in the NCR such as federal government agencies. Therefore, policy recommendations relating to potential mitigation and recovery strategies should take into account the balance between the inoperability and economic loss metrics. © 2013 Society for Risk Analysis.

Multi input single output model predictive control of non-linear bio-polymerization process

Energy Technology Data Exchange (ETDEWEB)

Arumugasamy, Senthil Kumar; Ahmad, Z. [School of Chemical Engineering, Univerisiti Sains Malaysia, Engineering Campus, Seri Ampangan,14300 Nibong Tebal, Seberang Perai Selatan, Pulau Pinang (Malaysia)

2015-05-15

This paper focuses on Multi Input Single Output (MISO) Model Predictive Control of bio-polymerization process in which mechanistic model is developed and linked with the feedforward neural network model to obtain a hybrid model (Mechanistic-FANN) of lipase-catalyzed ring-opening polymerization of ε-caprolactone (ε-CL) for Poly (ε-caprolactone) production. In this research, state space model was used, in which the input to the model were the reactor temperatures and reactor impeller speeds and the output were the molecular weight of polymer (M{sub n}) and polymer polydispersity index. State space model for MISO created using System identification tool box of Matlab™. This state space model is used in MISO MPC. Model predictive control (MPC) has been applied to predict the molecular weight of the biopolymer and consequently control the molecular weight of biopolymer. The result shows that MPC is able to track reference trajectory and give optimum movement of manipulated variable.

Robust Output Model Predictive Control of an Unstable Rijke Tube

Directory of Open Access Journals (Sweden)

Fabian Jarmolowitz

2012-01-01

Full Text Available This work investigates the active control of an unstable Rijke tube using robust output model predictive control (RMPC. As internal model a polytopic linear system with constraints is assumed to account for uncertainties. For guaranteed stability, a linear state feedback controller is designed using linear matrix inequalities and used within a feedback formulation of the model predictive controller. For state estimation a robust gain-scheduled observer is developed. It is shown that the proposed RMPC ensures robust stability under constraints over the considered operating range.

Modeling and control of the output current of a Reformed Methanol Fuel Cell system

DEFF Research Database (Denmark)

Justesen, Kristian Kjær; Andreasen, Søren Juhl; Pasupathi, Sivakumar

2015-01-01

In this work, a dynamic Matlab SIMULINK model of the relationship between the fuel cell current set point of a Reformed Methanol Fuel Cell system and the output current of the system is developed. The model contains an estimated fuel cell model, based on a polarization curve and assumed first order...... dynamics, as well as a battery model based on an equivalent circuit model and a balance of plant power consumption model. The models are tuned with experimental data and verified using a verification data set. The model is used to develop an output current controller which can control the charge current...... of the battery. The controller is a PI controller with feedforward and anti-windup. The performance of the controller is tested and verified on the physical system....

Input vs. Output Taxation—A DSGE Approach to Modelling Resource Decoupling

Directory of Open Access Journals (Sweden)

Marek Antosiewicz

2016-04-01

Full Text Available Environmental taxes constitute a crucial instrument aimed at reducing resource use through lower production losses, resource-leaner products, and more resource-efficient production processes. In this paper we focus on material use and apply a multi-sector dynamic stochastic general equilibrium (DSGE model to study two types of taxation: tax on material inputs used by industry, energy, construction, and transport sectors, and tax on output of these sectors. We allow for endogenous adoption of resource-saving technologies. We calibrate the model for the EU27 area using an IO matrix. We consider taxation introduced from 2021 and simulate its impact until 2050. We compare the taxes along their ability to induce reduction in material use and raise revenue. We also consider the effect of spending this revenue on reduction of labour taxation. We find that input and output taxation create contrasting incentives and have opposite effects on resource efficiency. The material input tax induces investment in efficiency-improving technology which, in the long term, results in GDP and employment by 15%–20% higher than in the case of a comparable output tax. We also find that using revenues to reduce taxes on labour has stronger beneficial effects for the input tax.

Using Weather Data and Climate Model Output in Economic Analyses of Climate Change

Energy Technology Data Exchange (ETDEWEB)

Auffhammer, M.; Hsiang, S. M.; Schlenker, W.; Sobel, A.

2013-06-28

Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overview of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.

Similarity Assessment of Land Surface Model Outputs in the North American Land Data Assimilation System

Science.gov (United States)

Kumar, Sujay V.; Wang, Shugong; Mocko, David M.; Peters-Lidard, Christa D.; Xia, Youlong

2017-11-01

Multimodel ensembles are often used to produce ensemble mean estimates that tend to have increased simulation skill over any individual model output. If multimodel outputs are too similar, an individual LSM would add little additional information to the multimodel ensemble, whereas if the models are too dissimilar, it may be indicative of systematic errors in their formulations or configurations. The article presents a formal similarity assessment of the North American Land Data Assimilation System (NLDAS) multimodel ensemble outputs to assess their utility to the ensemble, using a confirmatory factor analysis. Outputs from four NLDAS Phase 2 models currently running in operations at NOAA/NCEP and four new/upgraded models that are under consideration for the next phase of NLDAS are employed in this study. The results show that the runoff estimates from the LSMs were most dissimilar whereas the models showed greater similarity for root zone soil moisture, snow water equivalent, and terrestrial water storage. Generally, the NLDAS operational models showed weaker association with the common factor of the ensemble and the newer versions of the LSMs showed stronger association with the common factor, with the model similarity increasing at longer time scales. Trade-offs between the similarity metrics and accuracy measures indicated that the NLDAS operational models demonstrate a larger span in the similarity-accuracy space compared to the new LSMs. The results of the article indicate that simultaneous consideration of model similarity and accuracy at the relevant time scales is necessary in the development of multimodel ensemble.

An analytical model for an input/output-subsystem

International Nuclear Information System (INIS)

Roemgens, J.

1983-05-01

An input/output-subsystem of one or several computers if formed by the external memory units and the peripheral units of a computer system. For these subsystems mathematical models are established, taking into account the special properties of the I/O-subsystems, in order to avoid planning errors and to allow for predictions of the capacity of such systems. Here an analytical model is presented for the magnetic discs of a I/O-subsystem, using analytical methods for the individual waiting queues or waiting queue networks. Only I/O-subsystems of IBM-computer configurations are considered, which can be controlled by the MVS operating system. After a description of the hardware and software components of these I/O-systems, possible solutions from the literature are presented and discussed with respect to their applicability in IBM-I/O-subsystems. Based on these models a special scheme is developed which combines the advantages of the literature models and avoids the disadvantages in part. (orig./RW) [de

Forecasting Lightning Threat using Cloud-Resolving Model Simulations

Science.gov (United States)

McCaul, Eugene W., Jr.; Goodman, Steven J.; LaCasse, Katherine M.; Cecil, Daniel J.

2008-01-01

Two new approaches are proposed and developed for making time and space dependent, quantitative short-term forecasts of lightning threat, and a blend of these approaches is devised that capitalizes on the strengths of each. The new methods are distinctive in that they are based entirely on the ice-phase hydrometeor fields generated by regional cloud-resolving numerical simulations, such as those produced by the WRF model. These methods are justified by established observational evidence linking aspects of the precipitating ice hydrometeor fields to total flash rates. The methods are straightforward and easy to implement, and offer an effective near-term alternative to the incorporation of complex and costly cloud electrification schemes into numerical models. One method is based on upward fluxes of precipitating ice hydrometeors in the mixed phase region at the-15 C level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domain-wide statistics of the peak values of simulated flash rate proxy fields against domain-wide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. Our blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Exploratory tests for selected North Alabama cases show that, because WRF can distinguish the general character of most convective events, our methods show promise as a means of generating quantitatively realistic fields of lightning threat. However, because the models tend to have more difficulty in predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single

Regional disaster impact analysis: comparing Input-Output and Computable General Equilibrium models

NARCIS (Netherlands)

Koks, E.E.; Carrera, L.; Jonkeren, O.; Aerts, J.C.J.H.; Husby, T.G.; Thissen, M.; Standardi, G.; Mysiak, J.

2016-01-01

A variety of models have been applied to assess the economic losses of disasters, of which the most common ones are input-output (IO) and computable general equilibrium (CGE) models. In addition, an increasing number of scholars have developed hybrid approaches: one that combines both or either of

An Evaluation of Mesoscale Model Based Model Output Statistics (MOS) During the 2002 Olympic and Paralympic Winter Games

National Research Council Canada - National Science Library

Hart, Kenneth

2003-01-01

The skill of a mesoscale model based Model Output Statistics (MOS) system that provided hourly forecasts for 18 sites over northern Utah during the 2002 Winter Olympic and Paralympic Games is evaluated...

A passive and active microwave-vector radiative transfer (PAM-VRT) model

International Nuclear Information System (INIS)

Yang, Jun; Min, Qilong

2015-01-01

A passive and active microwave vector radiative transfer (PAM-VRT) package has been developed. This fast and accurate forward microwave model, with flexible and versatile input and output components, self-consistently and realistically simulates measurements/radiation of passive and active microwave sensors. The core PAM-VRT, microwave radiative transfer model, consists of five modules: gas absorption (two line-by-line databases and four fast models); hydrometeor property of water droplets and ice (spherical and nonspherical) particles; surface emissivity (from Community Radiative Transfer Model (CRTM)); vector radiative transfer of successive order of scattering (VSOS); and passive and active microwave simulation. The PAM-VRT package has been validated against other existing models, demonstrating good accuracy. The PAM-VRT not only can be used to simulate or assimilate measurements of existing microwave sensors, but also can be used to simulate observation results at some new microwave sensors. - Highlights: • A novel microwave vector radiative transfer model is developed. • It can simulate passive and active microwave radiative transfer simultaneously. • It can be applied to simulate measurements for different types of viewing geometry. • The accuracy of this model has been validated against other existing models

Use of medium-range numerical weather prediction model output to produce forecasts of streamflow

Science.gov (United States)

Clark, M.P.; Hay, L.E.

2004-01-01

This paper examines an archive containing over 40 years of 8-day atmospheric forecasts over the contiguous United States from the NCEP reanalysis project to assess the possibilities for using medium-range numerical weather prediction model output for predictions of streamflow. This analysis shows the biases in the NCEP forecasts to be quite extreme. In many regions, systematic precipitation biases exceed 100% of the mean, with temperature biases exceeding 3??C. In some locations, biases are even higher. The accuracy of NCEP precipitation and 2-m maximum temperature forecasts is computed by interpolating the NCEP model output for each forecast day to the location of each station in the NWS cooperative network and computing the correlation with station observations. Results show that the accuracy of the NCEP forecasts is rather low in many areas of the country. Most apparent is the generally low skill in precipitation forecasts (particularly in July) and low skill in temperature forecasts in the western United States, the eastern seaboard, and the southern tier of states. These results outline a clear need for additional processing of the NCEP Medium-Range Forecast Model (MRF) output before it is used for hydrologic predictions. Techniques of model output statistics (MOS) are used in this paper to downscale the NCEP forecasts to station locations. Forecasted atmospheric variables (e.g., total column precipitable water, 2-m air temperature) are used as predictors in a forward screening multiple linear regression model to improve forecasts of precipitation and temperature for stations in the National Weather Service cooperative network. This procedure effectively removes all systematic biases in the raw NCEP precipitation and temperature forecasts. MOS guidance also results in substantial improvements in the accuracy of maximum and minimum temperature forecasts throughout the country. For precipitation, forecast improvements were less impressive. MOS guidance increases

Output fields from the NOAA WAVEWATCH III® wave model monthly hindcasts

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA WAVEWATCH III® hindcast dataset comprises output fields from the monthly WAVEWATCH III® hindcast model runs conducted at the National Centers for...

Efficient Output Solution for Nonlinear Stochastic Optimal Control Problem with Model-Reality Differences

Directory of Open Access Journals (Sweden)

Sie Long Kek

2015-01-01

Full Text Available A computational approach is proposed for solving the discrete time nonlinear stochastic optimal control problem. Our aim is to obtain the optimal output solution of the original optimal control problem through solving the simplified model-based optimal control problem iteratively. In our approach, the adjusted parameters are introduced into the model used such that the differences between the real system and the model used can be computed. Particularly, system optimization and parameter estimation are integrated interactively. On the other hand, the output is measured from the real plant and is fed back into the parameter estimation problem to establish a matching scheme. During the calculation procedure, the iterative solution is updated in order to approximate the true optimal solution of the original optimal control problem despite model-reality differences. For illustration, a wastewater treatment problem is studied and the results show the efficiency of the approach proposed.

SU-F-T-143: Implementation of a Correction-Based Output Model for a Compact Passively Scattered Proton Therapy System

Energy Technology Data Exchange (ETDEWEB)

Ferguson, S; Ahmad, S; Chen, Y; Ferreira, C; Islam, M; Lau, A; Jin, H [University of Oklahoma Health Sciences Center, Oklahoma City, OK (United States); Keeling, V [Carti, Inc., Little Rock, AR (United States)

2016-06-15

Purpose: To commission and investigate the accuracy of an output (cGy/MU) prediction model for a compact passively scattered proton therapy system. Methods: A previously published output prediction model (Sahoo et al, Med Phys, 35, 5088–5097, 2008) was commissioned for our Mevion S250 proton therapy system. This model is a correction-based model that multiplies correction factors (d/MUwnc=ROFxSOBPF xRSFxSOBPOCFxOCRxFSFxISF). These factors accounted for changes in output due to options (12 large, 5 deep, and 7 small), modulation width M, range R, off-center, off-axis, field-size, and off-isocenter. In this study, the model was modified to ROFxSOBPFxRSFxOCRxFSFxISF-OCFxGACF by merging SOBPOCF and ISF for simplicity and introducing a gantry angle correction factor (GACF). To commission the model, outputs over 1,000 data points were taken at the time of the system commissioning. The output was predicted by interpolation (1D for SOBPF, FSF, and GACF; 2D for RSF and OCR) with inverse-square calculation (ISF-OCR). The outputs of 273 combinations of R and M covering total 24 options were measured to test the model. To minimize fluence perturbation, scattered dose from range compensator and patient was not considered. The percent differences between the predicted (P) and measured (M) outputs were calculated to test the prediction accuracy ([P-M]/Mx100%). Results: GACF was required because of up to 3.5% output variation dependence on the gantry angle. A 2D interpolation was required for OCR because the dose distribution was not radially symmetric especially for the deep options. The average percent differences were −0.03±0.98% (mean±SD) and the differences of all the measurements fell within ±3%. Conclusion: It is concluded that the model can be clinically used for the compact passively scattered proton therapy system. However, great care should be taken when the field-size is less than 5×5 cm{sup 2} where a direct output measurement is required due to substantial

Spatial and Temporal Extrapolation of Disdrometer Size Distributions Based on a Lagrangian Trajectory Model of Falling Rain

Science.gov (United States)

Lane, John E.; Kasparis, Takis; Jones, W. Linwood; Metzger, Philip T.

2009-01-01

Methodologies to improve disdrometer processing, loosely based on mathematical techniques common to the field of particle flow and fluid mechanics, are examined and tested. The inclusion of advection and vertical wind field estimates appear to produce significantly improved results in a Lagrangian hydrometeor trajectory model, in spite of very strict assumptions of noninteracting hydrometeors, constant vertical air velocity, and time independent advection during the scan time interval. Wind field data can be extracted from each radar elevation scan by plotting and analyzing reflectivity contours over the disdrometer site and by collecting the radar radial velocity data to obtain estimates of advection. Specific regions of disdrometer spectra (drop size versus time) often exhibit strong gravitational sorting signatures, from which estimates of vertical velocity can be extracted. These independent wind field estimates become inputs and initial conditions to the Lagrangian trajectory simulation of falling hydrometeors.

A PRODUCTIVITY EVALUATION MODEL BASED ON INPUT AND OUTPUT ORIENTATIONS

Directory of Open Access Journals (Sweden)

C.O. Anyaeche

2012-01-01

Full Text Available

ENGLISH ABSTRACT: Many productivity models evaluate either the input or the output performances using standalone techniques. This sometimes gives divergent views of the same system’s results. The work reported in this article, which simultaneously evaluated productivity from both orientations, was applied on real life data. The results showed losses in productivity (–2% and price recovery (–8% for the outputs; the inputs showed productivity gain (145% but price recovery loss (–63%. These imply losses in product performances but a productivity gain in inputs. The loss in the price recovery of inputs indicates a problem in the pricing policy. This model is applicable in product diversification.

AFRIKAANSE OPSOMMING: Die meeste produktiwiteitsmodelle evalueer of die inset- of die uitsetverrigting deur gebruik te maak van geïsoleerde tegnieke. Dit lei soms tot uiteenlopende perspektiewe van dieselfde sisteem se verrigting. Hierdie artikel evalueer verrigting uit beide perspektiewe en gebruik ware data. Die resultate toon ‘n afname in produktiwiteit (-2% en prysherwinning (-8% vir die uitsette. Die insette toon ‘n toename in produktiwiteit (145%, maar ‘n afname in prysherwinning (-63%. Dit impliseer ‘n afname in produkverrigting, maar ‘n produktiwiteitstoename in insette. Die afname in die prysherwinning van insette dui op ‘n problem in die prysvasstellingbeleid. Hierdie model is geskik vir produkdiversifikasie.

A Synergistic Approach for Evaluating Climate Model Output for Ecological Applications

Directory of Open Access Journals (Sweden)

Rachel D. Cavanagh

2017-09-01

Full Text Available Increasing concern about the impacts of climate change on ecosystems is prompting ecologists and ecosystem managers to seek reliable projections of physical drivers of change. The use of global climate models in ecology is growing, although drawing ecologically meaningful conclusions can be problematic. The expertise required to access and interpret output from climate and earth system models is hampering progress in utilizing them most effectively to determine the wider implications of climate change. To address this issue, we present a joint approach between climate scientists and ecologists that explores key challenges and opportunities for progress. As an exemplar, our focus is the Southern Ocean, notable for significant change with global implications, and on sea ice, given its crucial role in this dynamic ecosystem. We combined perspectives to evaluate the representation of sea ice in global climate models. With an emphasis on ecologically-relevant criteria (sea ice extent and seasonality we selected a subset of eight models that reliably reproduce extant sea ice distributions. While the model subset shows a similar mean change to the full ensemble in sea ice extent (approximately 50% decline in winter and 30% decline in summer, there is a marked reduction in the range. This improved the precision of projected future sea ice distributions by approximately one third, and means they are more amenable to ecological interpretation. We conclude that careful multidisciplinary evaluation of climate models, in conjunction with ongoing modeling advances, should form an integral part of utilizing model output.

Predicting Time Series Outputs and Time-to-Failure for an Aircraft Controller Using Bayesian Modeling

Science.gov (United States)

He, Yuning

2015-01-01

Safety of unmanned aerial systems (UAS) is paramount, but the large number of dynamically changing controller parameters makes it hard to determine if the system is currently stable, and the time before loss of control if not. We propose a hierarchical statistical model using Treed Gaussian Processes to predict (i) whether a flight will be stable (success) or become unstable (failure), (ii) the time-to-failure if unstable, and (iii) time series outputs for flight variables. We first classify the current flight input into success or failure types, and then use separate models for each class to predict the time-to-failure and time series outputs. As different inputs may cause failures at different times, we have to model variable length output curves. We use a basis representation for curves and learn the mappings from input to basis coefficients. We demonstrate the effectiveness of our prediction methods on a NASA neuro-adaptive flight control system.

ANALYSIS OF THE BANDUNG CHANGES EXCELLENT POTENTIAL THROUGH INPUT-OUTPUT MODEL USING INDEX LE MASNE

Directory of Open Access Journals (Sweden)

Teti Sofia Yanti

2017-03-01

Full Text Available Input-Output Table is arranged to present an overview of the interrelationships and interdependence between units of activity (sector production in the whole economy. Therefore the input-output models are complete and comprehensive analytical tool. The usefulness of input-output tables is an analysis of the economic structure of the national/regional level which covers the structure of production and value-added (GDP of each sector. For the purposes of planning and evaluation of the outcomes of development that is comprehensive both national and smaller scale (district/city, a model for regional development planning approach can use the model input-output analysis. Analysis of Bandung Economic Structure did use Le Masne index, by comparing the coefficients of the technology in 2003 and 2008, of which nearly 50% change. The trade sector has grown very conspicuous than other areas, followed by the services of road transport and air transport services, the development priorities and investment Bandung should be directed to these areas, this is due to these areas can be thrust and be power attraction for the growth of other areas. The areas that experienced the highest decrease was Industrial Chemicals and Goods from Chemistry, followed by Oil and Refinery Industry Textile Industry Except For Garment.

a mathematical model for predicting output in an oilfield in the niger

African Journals Online (AJOL)

eobe

resultant model was found to have greater utility in predicting oil field output as it produced less residual. The ... decision making by the oilfield manager is facilitated by reliable ... Scaling laws from percolation theory was used to predict oilfield ...

Modelling health and output at business cycle horizons for the USA.

Science.gov (United States)

Narayan, Paresh Kumar

2010-07-01

In this paper we employ a theoretical framework - a simple macro model augmented with health - that draws guidance from the Keynesian view of business cycles to examine the relative importance of permanent and transitory shocks in explaining variations in health expenditure and output at business cycle horizons for the USA. The variance decomposition analysis of shocks reveals that at business cycle horizons permanent shocks explain the bulk of the variations in output, while transitory shocks explain the bulk of the variations in health expenditures. We undertake a shock decomposition analysis for private health expenditures versus public health expenditures and interestingly find that while transitory shocks are more important for private sector expenditures, permanent shocks dominate public health expenditures. Copyright (c) 2009 John Wiley & Sons, Ltd.

Input-output model of regional environmental and economic impacts of nuclear power plants

International Nuclear Information System (INIS)

Johnson, M.H.; Bennett, J.T.

1979-01-01

The costs of delayed licensing of nuclear power plants calls for a more-comprehensive method of quantifying the economic and environmental impacts on a region. A traditional input-output (I-O) analysis approach is extended to assess the effects of changes in output, income, employment, pollution, water consumption, and the costs and revenues of local government disaggregated among 23 industry sectors during the construction and operating phases. Unlike earlier studies, this model uses nonlinear environmental interactions and specifies environmental feedbacks to the economic sector. 20 references

The Canadian Defence Input-Output Model DIO Version 4.41

Science.gov (United States)

2011-09-01

Request to develop DND tailored Input/Output Model. Electronic communication from AllenWeldon to Team Leader, Defence Economics Team onMarch 12, 2011...and similar contain- ers 166 1440 Handbags, wallets and similar personal articles such as eyeglass and cigar cases and coin purses 167 1450 Cotton yarn...408 3600 Radar and radio navigation equipment 409 3619 Semi-conductors 410 3621 Printed circuits 411 3622 Integrated circuits 412 3623 Other electronic

Evaluation of input output efficiency of oil field considering undesirable output —A case study of sandstone reservoir in Xinjiang oilfield

Science.gov (United States)

Zhang, Shuying; Wu, Xuquan; Li, Deshan; Xu, Yadong; Song, Shulin

2017-06-01

Based on the input and output data of sandstone reservoir in Xinjiang oilfield, the SBM-Undesirable model is used to study the technical efficiency of each block. Results show that: the model of SBM-undesirable to evaluate its efficiency and to avoid defects caused by traditional DEA model radial angle, improve the accuracy of the efficiency evaluation. by analyzing the projection of the oil blocks, we find that each block is in the negative external effects of input redundancy and output deficiency benefit and undesirable output, and there are greater differences in the production efficiency of each block; the way to improve the input-output efficiency of oilfield is to optimize the allocation of resources, reduce the undesirable output and increase the expected output.

A case study of microphysical structures and hydrometeor phase in convection using radar Doppler spectra at Darwin, Australia

Energy Technology Data Exchange (ETDEWEB)

Riihimaki, Laura D.; Comstock, Jennifer M.; Luke, Edward; Thorsen, Tyler J.; Fu, Qiang

2017-07-28

To understand the microphysical processes that impact diabatic heating and cloud lifetimes in convection, we need to characterize the spatial distribution of supercooled liquid water. To address this observational challenge, vertically pointing active sensors at the Darwin Atmospheric Radiation Measurement (ARM) site are used to classify cloud phase within a deep convective cloud in a shallow to deep convection transitional case. The cloud cannot be fully observed by a lidar due to signal attenuation. Thus we develop an objective method for identifying hydrometeor classes, including mixed-phase conditions, using k-means clustering on parameters that describe the shape of the Doppler spectra from vertically pointing Ka band cloud radar. This approach shows that multiple, overlapping mixed-phase layers exist within the cloud, rather than a single region of supercooled liquid, indicating complexity to how ice growth and diabatic heating occurs in the vertical structure of the cloud.

A case study of microphysical structures and hydrometeor phase in convection using radar Doppler spectra at Darwin, Australia

International Nuclear Information System (INIS)

Riihimaki, Laura D.; Comstock, J. M.; Luke, E.; Thorsen, T. J.; Fu, Q.

2017-01-01

To understand the microphysical processes that impact diabatic heating and cloud lifetimes in convection, we need to characterize the spatial distribution of supercooled liquid water. To address this observational challenge, ground-based vertically pointing active sensors at the Darwin Atmospheric Radiation Measurement site are used to classify cloud phase within a deep convective cloud. The cloud cannot be fully observed by a lidar due to signal attenuation. Therefore, we developed an objective method for identifying hydrometeor classes, including mixed-phase conditions, using k-means clustering on parameters that describe the shape of the Doppler spectra from vertically pointing Ka-band cloud radar. Furthermore, this approach shows that multiple, overlapping mixed-phase layers exist within the cloud, rather than a single region of supercooled liquid. Diffusional growth calculations show that the conditions for the Wegener-Bergeron-Findeisen process exist within one of these mixed-phase microstructures.

A case study of microphysical structures and hydrometeor phase in convection using radar Doppler spectra at Darwin, Australia

Science.gov (United States)

Riihimaki, L. D.; Comstock, J. M.; Luke, E.; Thorsen, T. J.; Fu, Q.

2017-07-01

To understand the microphysical processes that impact diabatic heating and cloud lifetimes in convection, we need to characterize the spatial distribution of supercooled liquid water. To address this observational challenge, ground-based vertically pointing active sensors at the Darwin Atmospheric Radiation Measurement site are used to classify cloud phase within a deep convective cloud. The cloud cannot be fully observed by a lidar due to signal attenuation. Therefore, we developed an objective method for identifying hydrometeor classes, including mixed-phase conditions, using k-means clustering on parameters that describe the shape of the Doppler spectra from vertically pointing Ka-band cloud radar. This approach shows that multiple, overlapping mixed-phase layers exist within the cloud, rather than a single region of supercooled liquid. Diffusional growth calculations show that the conditions for the Wegener-Bergeron-Findeisen process exist within one of these mixed-phase microstructures.

Development of algorithm for depreciation costs allocation in dynamic input-output industrial enterprise model

Directory of Open Access Journals (Sweden)

Keller Alevtina

2017-01-01

Full Text Available The article considers the issue of allocation of depreciation costs in the dynamic inputoutput model of an industrial enterprise. Accounting the depreciation costs in such a model improves the policy of fixed assets management. It is particularly relevant to develop the algorithm for the allocation of depreciation costs in the construction of dynamic input-output model of an industrial enterprise, since such enterprises have a significant amount of fixed assets. Implementation of terms of the adequacy of such an algorithm itself allows: evaluating the appropriateness of investments in fixed assets, studying the final financial results of an industrial enterprise, depending on management decisions in the depreciation policy. It is necessary to note that the model in question for the enterprise is always degenerate. It is caused by the presence of zero rows in the matrix of capital expenditures by lines of structural elements unable to generate fixed assets (part of the service units, households, corporate consumers. The paper presents the algorithm for the allocation of depreciation costs for the model. This algorithm was developed by the authors and served as the basis for further development of the flowchart for subsequent implementation with use of software. The construction of such algorithm and its use for dynamic input-output models of industrial enterprises is actualized by international acceptance of the effectiveness of the use of input-output models for national and regional economic systems. This is what allows us to consider that the solutions discussed in the article are of interest to economists of various industrial enterprises.

A Water-Withdrawal Input-Output Model of the Indian Economy.

Science.gov (United States)

Bogra, Shelly; Bakshi, Bhavik R; Mathur, Ritu

2016-02-02

Managing freshwater allocation for a highly populated and growing economy like India can benefit from knowledge about the effect of economic activities. This study transforms the 2003-2004 economic input-output (IO) table of India into a water withdrawal input-output model to quantify direct and indirect flows. This unique model is based on a comprehensive database compiled from diverse public sources, and estimates direct and indirect water withdrawal of all economic sectors. It distinguishes between green (rainfall), blue (surface and ground), and scarce groundwater. Results indicate that the total direct water withdrawal is nearly 3052 billion cubic meter (BCM) and 96% of this is used in agriculture sectors with the contribution of direct green water being about 1145 BCM, excluding forestry. Apart from 727 BCM direct blue water withdrawal for agricultural, other significant users include "Electricity" with 64 BCM, "Water supply" with 44 BCM and other industrial sectors with nearly 14 BCM. "Construction", "miscellaneous food products"; "Hotels and restaurants"; "Paper, paper products, and newsprint" are other significant indirect withdrawers. The net virtual water import is found to be insignificant compared to direct water used in agriculture nationally, while scarce ground water associated with crops is largely contributed by northern states.

Evacuation emergency response model coupling atmospheric release advisory capability output

International Nuclear Information System (INIS)

Rosen, L.C.; Lawver, B.S.; Buckley, D.W.; Finn, S.P.; Swenson, J.B.

1983-01-01

A Federal Emergency Management Agency (FEMA) sponsored project to develop a coupled set of models between those of the Lawrence Livermore National Laboratory (LLNL) Atmospheric Release Advisory Capability (ARAC) system and candidate evacuation models is discussed herein. This report describes the ARAC system and discusses the rapid computer code developed and the coupling with ARAC output. The computer code is adapted to the use of color graphics as a means to display and convey the dynamics of an emergency evacuation. The model is applied to a specific case of an emergency evacuation of individuals surrounding the Rancho Seco Nuclear Power Plant, located approximately 25 miles southeast of Sacramento, California. The graphics available to the model user for the Rancho Seco example are displayed and noted in detail. Suggestions for future, potential improvements to the emergency evacuation model are presented

Commissioning of output factors for uniform scanning proton beams

International Nuclear Information System (INIS)

Zheng Yuanshui; Ramirez, Eric; Mascia, Anthony; Ding Xiaoning; Okoth, Benny; Zeidan, Omar; Hsi Wen; Harris, Ben; Schreuder, Andries N.; Keole, Sameer

2011-01-01

Purpose: Current commercial treatment planning systems are not able to accurately predict output factors and calculate monitor units for proton fields. Patient-specific field output factors are thus determined by either measurements or empirical modeling based on commissioning data. The objective of this study is to commission output factors for uniform scanning beams utilized at the ProCure proton therapy centers. Methods: Using water phantoms and a plane parallel ionization chamber, the authors first measured output factors with a fixed 10 cm diameter aperture as a function of proton range and modulation width for clinically available proton beams with ranges between 4 and 31.5 cm and modulation widths between 2 and 15 cm. The authors then measured the output factor as a function of collimated field size at various calibration depths for proton beams of various ranges and modulation widths. The authors further examined the dependence of the output factor on the scanning area (i.e., uncollimated proton field), snout position, and phantom material. An empirical model was developed to calculate the output factor for patient-specific fields and the model-predicted output factors were compared to measurements. Results: The output factor increased with proton range and field size, and decreased with modulation width. The scanning area and snout position have a small but non-negligible effect on the output factors. The predicted output factors based on the empirical modeling agreed within 2% of measurements for all prostate treatment fields and within 3% for 98.5% of all treatment fields. Conclusions: Comprehensive measurements at a large subset of available beam conditions are needed to commission output factors for proton therapy beams. The empirical modeling agrees well with the measured output factor data. This investigation indicates that it is possible to accurately predict output factors and thus eliminate or reduce time-consuming patient-specific output

Analyses of gust fronts by means of limited area NWP model outputs

Czech Academy of Sciences Publication Activity Database

Kašpar, Marek

67-68, - (2003), s. 559-572 ISSN 0169-8095 R&D Projects: GA ČR GA205/00/1451 Institutional research plan: CEZ:AV0Z3042911 Keywords : gust front * limited area NWP model * output Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.012, year: 2003

The Comparison of Point Data Models for the Output of WRF Hydro Model in the IDV

Science.gov (United States)

Ho, Y.; Weber, J.

2017-12-01

WRF Hydro netCDF output files contain streamflow, flow depth, longitude, latitude, altitude and stream order values for each forecast point. However, the data are not CF compliant. The total number of forecast points for the US CONUS is approximately 2.7 million and it is a big challenge for any visualization and analysis tool. The IDV point cloud display shows point data as a set of points colored by parameter. This display is very efficient compared to a standard point type display for rendering a large number of points. The one problem we have is that the data I/O can be a bottleneck issue when dealing with a large collection of point input files. In this presentation, we will experiment with different point data models and their APIs to access the same WRF Hydro model output. The results will help us construct a CF compliant netCDF point data format for the community.

Output-Feedback Model Predictive Control of a Pasteurization Pilot Plant based on an LPV model

Science.gov (United States)

Karimi Pour, Fatemeh; Ocampo-Martinez, Carlos; Puig, Vicenç

2017-01-01

This paper presents a model predictive control (MPC) of a pasteurization pilot plant based on an LPV model. Since not all the states are measured, an observer is also designed, which allows implementing an output-feedback MPC scheme. However, the model of the plant is not completely observable when augmented with the disturbance models. In order to solve this problem, the following strategies are used: (i) the whole system is decoupled into two subsystems, (ii) an inner state-feedback controller is implemented into the MPC control scheme. A real-time example based on the pasteurization pilot plant is simulated as a case study for testing the behavior of the approaches.

Econometric model of the petroleum industry. [Determining crude supply and outputs/prices of refinery products

Energy Technology Data Exchange (ETDEWEB)

Rice, P [Oak Ridge National Lab., TN; Smith, V K

1977-11-01

This paper describes a forty-two nonlinear equation model of the U.S. petroleum industry estimated over the period 1946 to 1973. The model specifies refinery outputs and prices as being simultaneously determined by market forces while the domestic output of crude oil is determined in a block-recursive segment of the model. The simultaneous behavioral equations are estimated with nonlinear two-stage least-squares adjusted to reflect the implications of autocorrelation for those equations where it appears to be a problem. A multi-period sample simulation, together with forecasts for 1974 and 1975 are used to evaluate the model's performance. Finally, it is used to forecast to 1985 under two scenarios and compared with the Federal Energy Administration's forecast for the same period. 2 figures, 8 tables, 38 references.

Real-time prediction models for output power and efficiency of grid-connected solar photovoltaic systems

International Nuclear Information System (INIS)

Su, Yan; Chan, Lai-Cheong; Shu, Lianjie; Tsui, Kwok-Leung

2012-01-01

Highlights: ► We develop online prediction models for solar photovoltaic system performance. ► The proposed prediction models are simple but with reasonable accuracy. ► The maximum monthly average minutely efficiency varies 10.81–12.63%. ► The average efficiency tends to be slightly higher in winter months. - Abstract: This paper develops new real time prediction models for output power and energy efficiency of solar photovoltaic (PV) systems. These models were validated using measured data of a grid-connected solar PV system in Macau. Both time frames based on yearly average and monthly average are considered. It is shown that the prediction model for the yearly/monthly average of the minutely output power fits the measured data very well with high value of R 2 . The online prediction model for system efficiency is based on the ratio of the predicted output power to the predicted solar irradiance. This ratio model is shown to be able to fit the intermediate phase (9 am to 4 pm) very well but not accurate for the growth and decay phases where the system efficiency is near zero. However, it can still serve as a useful purpose for practitioners as most PV systems work in the most efficient manner over this period. It is shown that the maximum monthly average minutely efficiency varies over a small range of 10.81% to 12.63% in different months with slightly higher efficiency in winter months.

Toward a more robust variance-based global sensitivity analysis of model outputs

Energy Technology Data Exchange (ETDEWEB)

Tong, C

2007-10-15

Global sensitivity analysis (GSA) measures the variation of a model output as a function of the variations of the model inputs given their ranges. In this paper we consider variance-based GSA methods that do not rely on certain assumptions about the model structure such as linearity or monotonicity. These variance-based methods decompose the output variance into terms of increasing dimensionality called 'sensitivity indices', first introduced by Sobol' [25]. Sobol' developed a method of estimating these sensitivity indices using Monte Carlo simulations. McKay [13] proposed an efficient method using replicated Latin hypercube sampling to compute the 'correlation ratios' or 'main effects', which have been shown to be equivalent to Sobol's first-order sensitivity indices. Practical issues with using these variance estimators are how to choose adequate sample sizes and how to assess the accuracy of the results. This paper proposes a modified McKay main effect method featuring an adaptive procedure for accuracy assessment and improvement. We also extend our adaptive technique to the computation of second-order sensitivity indices. Details of the proposed adaptive procedure as wells as numerical results are included in this paper.

Governmentally amplified output volatility

Science.gov (United States)

Funashima, Yoshito

2016-11-01

Predominant government behavior is decomposed by frequency into several periodic components: updating cycles of infrastructure, Kuznets cycles, fiscal policy over business cycles, and election cycles. Little is known, however, about the theoretical impact of such cyclical behavior in public finance on output fluctuations. Based on a standard neoclassical growth model, this study intends to examine the frequency at which public investment cycles are relevant to output fluctuations. We find an inverted U-shaped relationship between output volatility and length of cycle in public investment. This implies that periodic behavior in public investment at a certain frequency range can cause aggravated output resonance. Moreover, we present an empirical analysis to test the theoretical implication, using the U.S. data in the period from 1968 to 2015. The empirical results suggest that such resonance phenomena change from low to high frequency.

Hydrologic response to multimodel climate output using a physically based model of groundwater/surface water interactions

Science.gov (United States)

Sulis, M.; Paniconi, C.; Marrocu, M.; Huard, D.; Chaumont, D.

2012-12-01

General circulation models (GCMs) are the primary instruments for obtaining projections of future global climate change. Outputs from GCMs, aided by dynamical and/or statistical downscaling techniques, have long been used to simulate changes in regional climate systems over wide spatiotemporal scales. Numerous studies have acknowledged the disagreements between the various GCMs and between the different downscaling methods designed to compensate for the mismatch between climate model output and the spatial scale at which hydrological models are applied. Very little is known, however, about the importance of these differences once they have been input or assimilated by a nonlinear hydrological model. This issue is investigated here at the catchment scale using a process-based model of integrated surface and subsurface hydrologic response driven by outputs from 12 members of a multimodel climate ensemble. The data set consists of daily values of precipitation and min/max temperatures obtained by combining four regional climate models and five GCMs. The regional scenarios were downscaled using a quantile scaling bias-correction technique. The hydrologic response was simulated for the 690 km2des Anglais catchment in southwestern Quebec, Canada. The results show that different hydrological components (river discharge, aquifer recharge, and soil moisture storage) respond differently to precipitation and temperature anomalies in the multimodel climate output, with greater variability for annual discharge compared to recharge and soil moisture storage. We also find that runoff generation and extreme event-driven peak hydrograph flows are highly sensitive to any uncertainty in climate data. Finally, the results show the significant impact of changing sequences of rainy days on groundwater recharge fluxes and the influence of longer dry spells in modifying soil moisture spatial variability.

The economic impact of multifunctional agriculture in Dutch regions: An input-output model

NARCIS (Netherlands)

Heringa, P.W.; Heide, van der C.M.; Heijman, W.J.M.

2013-01-01

Multifunctional agriculture is a broad concept lacking a precise definition. Moreover, little is known about the societal importance of multifunctional agriculture. This paper is an empirical attempt to fill this gap. To this end, an input-output model was constructed for multifunctional agriculture

Structured, Physically Inspired (Gray Box) Models Versus Black Box Modeling for Forecasting the Output Power of Photovoltaic Plants

Czech Academy of Sciences Publication Activity Database

Paulescu, M.; Brabec, Marek; Boata, R.; Badescu, V.

2017-01-01

Roč. 121, 15 February (2017), s. 792-802 ISSN 0360-5442 Grant - others:European Cooperation in Science and Technology(XE) COST ES1002 Institutional support: RVO:67985807 Keywords : photovoltaic plant * output power * forecasting * fuzzy model * generalized additive model Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability Impact factor: 4.520, year: 2016

Initiation of secondary ice production in clouds

Directory of Open Access Journals (Sweden)

S. C. Sullivan

2018-02-01

Full Text Available Disparities between the measured concentrations of ice-nucleating particles (INPs and in-cloud ice crystal number concentrations (ICNCs have led to the hypothesis that mechanisms other than primary nucleation form ice in the atmosphere. Here, we model three of these secondary production mechanisms – rime splintering, frozen droplet shattering, and ice–ice collisional breakup – with a six-hydrometeor-class parcel model. We perform three sets of simulations to understand temporal evolution of ice hydrometeor number (Nice, thermodynamic limitations, and the impact of parametric uncertainty when secondary production is active. Output is assessed in terms of the number of primarily nucleated ice crystals that must exist before secondary production initiates (NINP(lim as well as the ICNC enhancement from secondary production and the timing of a 100-fold enhancement. Nice evolution can be understood in terms of collision-based nonlinearity and the phasedness of the process, i.e., whether it involves ice hydrometeors, liquid ones, or both. Ice–ice collisional breakup is the only process for which a meaningful NINP(lim exists (0.002 up to 0.15 L−1. For droplet shattering and rime splintering, a warm enough cloud base temperature and modest updraft are the more important criteria for initiation. The low values of NINP(lim here suggest that, under appropriate thermodynamic conditions for secondary ice production, perturbations in cloud concentration nuclei concentrations are more influential in mixed-phase partitioning than those in INP concentrations.

UFO - The Universal FEYNRULES Output

Science.gov (United States)

Degrande, Céline; Duhr, Claude; Fuks, Benjamin; Grellscheid, David; Mattelaer, Olivier; Reiter, Thomas

2012-06-01

We present a new model format for automatized matrix-element generators, the so-called Universal FEYNRULES Output (UFO). The format is universal in the sense that it features compatibility with more than one single generator and is designed to be flexible, modular and agnostic of any assumption such as the number of particles or the color and Lorentz structures appearing in the interaction vertices. Unlike other model formats where text files need to be parsed, the information on the model is encoded into a PYTHON module that can easily be linked to other computer codes. We then describe an interface for the MATHEMATICA package FEYNRULES that allows for an automatic output of models in the UFO format.

Input-output interactions and optimal monetary policy

DEFF Research Database (Denmark)

Petrella, Ivan; Santoro, Emiliano

2011-01-01

This paper deals with the implications of factor demand linkages for monetary policy design in a two-sector dynamic general equilibrium model. Part of the output of each sector serves as a production input in both sectors, in accordance with a realistic input–output structure. Strategic...... complementarities induced by factor demand linkages significantly alter the transmission of shocks and amplify the loss of social welfare under optimal monetary policy, compared to what is observed in standard two-sector models. The distinction between value added and gross output that naturally arises...... in this context is of key importance to explore the welfare properties of the model economy. A flexible inflation targeting regime is close to optimal only if the central bank balances inflation and value added variability. Otherwise, targeting gross output variability entails a substantial increase in the loss...

Prediction model and treatment of high-output ileostomy in colorectal cancer surgery.

Science.gov (United States)

Fujino, Shiki; Miyoshi, Norikatsu; Ohue, Masayuki; Takahashi, Yuske; Yasui, Masayoshi; Sugimura, Keijiro; Akita, Hirohumi; Takahashi, Hidenori; Kobayashi, Shogo; Yano, Masahiko; Sakon, Masato

2017-09-01

The aim of the present study was to examine the risk factors of high-output ileostomy (HOI), which is associated with electrolyte abnormalities and/or stoma complications, and to create a prediction model. The medical records of 68 patients who underwent colorectal cancer surgery with ileostomy between 2011 and 2016 were retrospectively investigated. All the patients underwent surgical resection for colorectal cancer at the Osaka Medical Center for Cancer and Cardiovascular Diseases (Osaka, Japan). A total of 7 patients with inadequate data on ileostomy output were excluded. Using a group of 50 patients who underwent surgery between 2011 and 2013, the risk of HOI was classified by a decision tree model using a partition platform. The HOI prediction model was validated in an additional group of 11 patients who underwent surgery between 2014 and 2016. Univariate analysis of clinical factors demonstrated that young age (P=0.003) and high white blood cell (WBC) count (Pmodel, three factors (gender, age and WBC on postoperative day 1) were generated for the prediction of HOI. The patients were classified into five groups, and HOI was observed in 0-88% of patients in each group. The area under the curve (AUC) was 0.838. The model was validated by an external dataset in an independent patient group, for which the AUC was 0.792. In conclusion, HOI patients were classified and an HOI prediction model was developed that may help clinicians in postoperative care.

Grouping influences output interference in short-term memory: a mixture modeling study

Directory of Open Access Journals (Sweden)

Min-Suk eKang

2016-05-01

Full Text Available Output interference is a source of forgetting induced by recalling. We investigated how grouping influences output interference in short-term memory. In Experiment 1, the participants were asked to remember four colored items. Those items were grouped by temporal coincidence as well as spatial alignment: two items were presented in the first memory array and two were presented in the second, and the items in both arrays were either vertically or horizontally aligned as well. The participants then performed two recall tasks in sequence by selecting a color presented at a cued location from a color wheel. In the same-group condition, the participants reported both items from the same memory array; however, in the different-group condition, the participants reported one item from each memory array. We analyzed participant responses with a mixture model, which yielded two measures: guess rate and precision of recalled memories. The guess rate in the second recall was higher for the different-group condition than for the same-group condition; however, the memory precisions obtained for both conditions were similarly degraded in the second recall. In Experiment 2, we varied the probability of the same- and different-group conditions with a ratio of 3 to 7. We expected output interference to be higher in the same-group condition than in the different-group condition. This is because items of the other group are more likely to be probed in the second recall phase and, thus, protecting those items during the first recall phase leads to a better performance. Nevertheless, the same pattern of results was robustly reproduced, suggesting grouping shields the grouped items from output interference because of the secured accessibility. We discussed how grouping influences output interference.

Energy and output dynamics in Bangladesh

International Nuclear Information System (INIS)

Paul, Biru Paksha; Uddin, Gazi Salah

2011-01-01

The relationship between energy consumption and output is still ambiguous in the existing literature. The economy of Bangladesh, having spectacular output growth and rising energy demand as well as energy efficiency in recent decades, can be an ideal case for examining energy-output dynamics. We find that while fluctuations in energy consumption do not affect output fluctuations, movements in output inversely affect movements in energy use. The results of Granger causality tests in this respect are consistent with those of innovative accounting that includes variance decompositions and impulse responses. Autoregressive distributed lag models also suggest a role of output in Bangladesh's energy use. Hence, the findings of this study have policy implications for other developing nations where measures for energy conservation and efficiency can be relevant in policymaking.

Monte Carlo and Lambertian light guide models of the light output from scintillation crystals at megavoltage energies

International Nuclear Information System (INIS)

Evans, Philip M.; Mosleh-Shirazi, M. Amin; Harris, Emma J.; Seco, Joao

2006-01-01

A new model of the light output from single-crystal scintillators in megavoltage energy x-ray beams has been developed, based on the concept of a Lambertian light guide model (LLG). This was evaluated in comparison with a Monte Carlo (MC) model of optical photon transport, previously developed and reported in the literature, which was used as a gold standard. The LLG model was developed to enable optimization of scintillator detector design. In both models the dose deposition and light propagation were decoupled, the scintillators were cuboids, split into a series of cells as a function of depth, with Lambertian side and entrance faces, and a specular exit face. The signal in a sensor placed 1 and 1000 mm beyond the exit face was calculated. Cesium iodide (CSI) crystals of 1.5 and 3 mm square cross section and 1, 5, and 10 mm depth were modeled. Both models were also used to determine detector signal and optical gain factor as a function of CsI scintillator thickness, from 2 to 10 mm. Results showed a variation in light output with position of dose deposition of a factor of up to approximately 5, for long, thin scintillators (such as 10x1.5x1.5 mm 3 ). For short, fat scintillators (such as 1x3x3 mm 3 ) the light output was more uniform with depth. MC and LLG generally agreed to within 5%. Results for a sensor distance of 1 mm showed an increase in light output the closer the light originates to the exit face, while a distance of 1000 mm showed a decrease in light output the closer the light originates to the exit face. For a sensor distance of 1 mm, the ratio of signal for a 10 mm scintillator to that for a 2 mm scintillator was 1.98, whereas for the 1000 mm distance the ratio was 3.00. The ratio of quantum efficiency (QE) between 10 and 2 mm thicknesses was 4.62. We conclude that these models may be used for detector optimization, with the light guide model suitable for parametric study

Multiregional input-output model for the evaluation of Spanish water flows.

Science.gov (United States)

Cazcarro, Ignacio; Duarte, Rosa; Sánchez Chóliz, Julio

2013-01-01

We construct a multiregional input-output model for Spain, in order to evaluate the pressures on the water resources, virtual water flows, and water footprints of the regions, and the water impact of trade relationships within Spain and abroad. The study is framed with those interregional input-output models constructed to study water flows and impacts of regions in China, Australia, Mexico, or the UK. To build our database, we reconcile regional IO tables, national and regional accountancy of Spain, trade and water data. Results show an important imbalance between origin of water resources and final destination, with significant water pressures in the South, Mediterranean, and some central regions. The most populated and dynamic regions of Madrid and Barcelona are important drivers of water consumption in Spain. Main virtual water exporters are the South and Central agrarian regions: Andalusia, Castile-La Mancha, Castile-Leon, Aragon, and Extremadura, while the main virtual water importers are the industrialized regions of Madrid, Basque country, and the Mediterranean coast. The paper shows the different location of direct and indirect consumers of water in Spain and how the economic trade and consumption pattern of certain areas has significant impacts on the availability of water resources in other different and often drier regions.

Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast

Science.gov (United States)

Ahmed, Kazi Farzan; Wang, Guiling; Silander, John; Wilson, Adam M.; Allen, Jenica M.; Horton, Radley; Anyah, Richard

2013-01-01

Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1/8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.

Linear and quadratic models of point process systems: contributions of patterned input to output.

Science.gov (United States)

Lindsay, K A; Rosenberg, J R

2012-08-01

In the 1880's Volterra characterised a nonlinear system using a functional series connecting continuous input and continuous output. Norbert Wiener, in the 1940's, circumvented problems associated with the application of Volterra series to physical problems by deriving from it a new series of terms that are mutually uncorrelated with respect to Gaussian processes. Subsequently, Brillinger, in the 1970's, introduced a point-process analogue of Volterra's series connecting point-process inputs to the instantaneous rate of point-process output. We derive here a new series from this analogue in which its terms are mutually uncorrelated with respect to Poisson processes. This new series expresses how patterned input in a spike train, represented by third-order cross-cumulants, is converted into the instantaneous rate of an output point-process. Given experimental records of suitable duration, the contribution of arbitrary patterned input to an output process can, in principle, be determined. Solutions for linear and quadratic point-process models with one and two inputs and a single output are investigated. Our theoretical results are applied to isolated muscle spindle data in which the spike trains from the primary and secondary endings from the same muscle spindle are recorded in response to stimulation of one and then two static fusimotor axons in the absence and presence of a random length change imposed on the parent muscle. For a fixed mean rate of input spikes, the analysis of the experimental data makes explicit which patterns of two input spikes contribute to an output spike. Copyright © 2012 Elsevier Ltd. All rights reserved.

Light output measurements and computational models of microcolumnar CsI scintillators for x-ray imaging

Energy Technology Data Exchange (ETDEWEB)

Nillius, Peter, E-mail: nillius@mi.physics.kth.se; Klamra, Wlodek; Danielsson, Mats [Royal Institute of Technology (KTH), Stockholm SE-100 44 (Sweden); Sibczynski, Pawel [National Centre for Nuclear Research, Otwock 05-400 (Poland); Sharma, Diksha; Badano, Aldo [Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, FDA, Silver Spring, Maryland 20993 (United States)

2015-02-15

Purpose: The authors report on measurements of light output and spatial resolution of microcolumnar CsI:Tl scintillator detectors for x-ray imaging. In addition, the authors discuss the results of simulations aimed at analyzing the results of synchrotron and sealed-source exposures with respect to the contributions of light transport to the total light output. Methods: The authors measured light output from a 490-μm CsI:Tl scintillator screen using two setups. First, the authors used a photomultiplier tube (PMT) to measure the response of the scintillator to sealed-source exposures. Second, the authors performed imaging experiments with a 27-keV monoenergetic synchrotron beam and a slit to calculate the total signal generated in terms of optical photons per keV. The results of both methods are compared to simulations obtained with hybridMANTIS, a coupled x-ray, electron, and optical photon Monte Carlo transport package. The authors report line response (LR) and light output for a range of linear absorption coefficients and describe a model that fits at the same time the light output and the blur measurements. Comparing the experimental results with the simulations, the authors obtained an estimate of the absorption coefficient for the model that provides good agreement with the experimentally measured LR. Finally, the authors report light output simulation results and their dependence on scintillator thickness and reflectivity of the backing surface. Results: The slit images from the synchrotron were analyzed to obtain a total light output of 48 keV{sup −1} while measurements using the fast PMT instrument setup and sealed-sources reported a light output of 28 keV{sup −1}. The authors attribute the difference in light output estimates between the two methods to the difference in time constants between the camera and PMT measurements. Simulation structures were designed to match the light output measured with the camera while providing good agreement with the

Downscaling climate model output for water resources impacts assessment (Invited)

Science.gov (United States)

Maurer, E. P.; Pierce, D. W.; Cayan, D. R.

2013-12-01

Water agencies in the U.S. and around the globe are beginning to wrap climate change projections into their planning procedures, recognizing that ongoing human-induced changes to hydrology can affect water management in significant ways. Future hydrology changes are derived using global climate model (GCM) projections, though their output is at a spatial scale that is too coarse to meet the needs of those concerned with local and regional impacts. Those investigating local impacts have employed a range of techniques for downscaling, the process of translating GCM output to a more locally-relevant spatial scale. Recent projects have produced libraries of publicly-available downscaled climate projections, enabling managers, researchers and others to focus on impacts studies, drawing from a shared pool of fine-scale climate data. Besides the obvious advantage to data users, who no longer need to develop expertise in downscaling prior to examining impacts, the use of the downscaled data by hundreds of people has allowed a crowdsourcing approach to examining the data. The wide variety of applications employed by different users has revealed characteristics not discovered during the initial data set production. This has led to a deeper look at the downscaling methods, including the assumptions and effect of bias correction of GCM output. Here new findings are presented related to the assumption of stationarity in the relationships between large- and fine-scale climate, as well as the impact of quantile mapping bias correction on precipitation trends. The validity of these assumptions can influence the interpretations of impacts studies using data derived using these standard statistical methods and help point the way to improved methods.

Implementation of a Model Output Statistics based on meteorological variable screening for short‐term wind power forecast

DEFF Research Database (Denmark)

Ranaboldo, Matteo; Giebel, Gregor; Codina, Bernat

2013-01-01

A combination of physical and statistical treatments to post‐process numerical weather predictions (NWP) outputs is needed for successful short‐term wind power forecasts. One of the most promising and effective approaches for statistical treatment is the Model Output Statistics (MOS) technique....... The proposed MOS performed well in both wind farms, and its forecasts compare positively with an actual operative model in use at Risø DTU and other MOS types, showing minimum BIAS and improving NWP power forecast of around 15% in terms of root mean square error. Further improvements could be obtained...

Robust Model Predictive Control Using Linear Matrix Inequalities for the Treatment of Asymmetric Output Constraints

Directory of Open Access Journals (Sweden)

Mariana Santos Matos Cavalca

2012-01-01

Full Text Available One of the main advantages of predictive control approaches is the capability of dealing explicitly with constraints on the manipulated and output variables. However, if the predictive control formulation does not consider model uncertainties, then the constraint satisfaction may be compromised. A solution for this inconvenience is to use robust model predictive control (RMPC strategies based on linear matrix inequalities (LMIs. However, LMI-based RMPC formulations typically consider only symmetric constraints. This paper proposes a method based on pseudoreferences to treat asymmetric output constraints in integrating SISO systems. Such technique guarantees robust constraint satisfaction and convergence of the state to the desired equilibrium point. A case study using numerical simulation indicates that satisfactory results can be achieved.

International trade inoperability input-output model (IT-IIM): theory and application.

Science.gov (United States)

Jung, Jeesang; Santos, Joost R; Haimes, Yacov Y

2009-01-01

The inoperability input-output model (IIM) has been used for analyzing disruptions due to man-made or natural disasters that can adversely affect the operation of economic systems or critical infrastructures. Taking economic perturbation for each sector as inputs, the IIM provides the degree of economic production impacts on all industry sectors as the outputs for the model. The current version of the IIM does not provide a separate analysis for the international trade component of the inoperability. If an important port of entry (e.g., Port of Los Angeles) is disrupted, then international trade inoperability becomes a highly relevant subject for analysis. To complement the current IIM, this article develops the International Trade-IIM (IT-IIM). The IT-IIM investigates the resulting international trade inoperability for all industry sectors resulting from disruptions to a major port of entry. Similar to traditional IIM analysis, the inoperability metrics that the IT-IIM provides can be used to prioritize economic sectors based on the losses they could potentially incur. The IT-IIM is used to analyze two types of direct perturbations: (1) the reduced capacity of ports of entry, including harbors and airports (e.g., a shutdown of any port of entry); and (2) restrictions on commercial goods that foreign countries trade with the base nation (e.g., embargo).

The economic impact of multifunctional agriculture in The Netherlands: A regional input-output model

NARCIS (Netherlands)

Heringa, P.W.; Heide, van der C.M.; Heijman, W.J.M.

2012-01-01

Multifunctional agriculture is a broad concept lacking a precise and uniform definition. Moreover, little is known about the societal importance of multifunctional agriculture. This paper is an empirical attempt to fill this gap. To this end, an input-output model is constructed for multifunctional

Detection of no-model input-output pairs in closed-loop systems.

Science.gov (United States)

Potts, Alain Segundo; Alvarado, Christiam Segundo Morales; Garcia, Claudio

2017-11-01

The detection of no-model input-output (IO) pairs is important because it can speed up the multivariable system identification process, since all the pairs with null transfer functions are previously discarded and it can also improve the identified model quality, thus improving the performance of model based controllers. In the available literature, the methods focus just on the open-loop case, since in this case there is not the effect of the controller forcing the main diagonal in the transfer matrix to one and all the other terms to zero. In this paper, a modification of a previous method able to detect no-model IO pairs in open-loop systems is presented, but adapted to perform this duty in closed-loop systems. Tests are performed by using the traditional methods and the proposed one to show its effectiveness. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Total output operation chart optimization of cascade reservoirs and its application

International Nuclear Information System (INIS)

Jiang, Zhiqiang; Ji, Changming; Sun, Ping; Wang, Liping; Zhang, Yanke

2014-01-01

Highlights: • We propose a new double nested model for cascade reservoirs operation optimization. • We use two methods to extract the output distribution ratio. • The adopted two methods perform better than the widely used methods at present. • Stepwise regression method performs better than mean value method on the whole. - Abstract: With the rapid development of cascade hydropower stations in recent decades, the cascade system composed of multiple reservoirs needs unified operation and management. However, the output distribution problem has not yet been solved reasonably when the total output of cascade system obtained, which makes the full utilization of hydropower resources in cascade reservoirs very difficult. Discriminant criterion method is a traditional and common method to solve the output distribution problem at present, but some shortcomings cannot be ignored in the practical application. In response to the above concern, this paper proposes a new total output operation chart optimization model and a new optimal output distribution model, the two models constitute to a double nested model with the goal of maximizing power generation. This paper takes the cascade reservoirs of Li Xianjiang River in China as an instance to obtain the optimal total output operation chart by the proposed double nested model and the 43 years historical runoff data, progressive searching method and progressive optimality algorithm are used in solving the model. In order to take the obtained total output operation chart into practical operation, mean value method and stepwise regression method are adopted to extract the output distribution ratios on the basis of the optimal simulation intermediate data. By comparing with discriminant criterion method and conventional method, the combined utilization of total output operation chart and output distribution ratios presents better performance in terms of power generation and assurance rate, which proves it is an effective

Characterizing the effects of cell settling on bioprinter output

International Nuclear Information System (INIS)

Pepper, Matthew E; Burg, Timothy C; Burg, Karen J L; Groff, Richard E; Seshadri, Vidya

2012-01-01

The time variation in bioprinter output, i.e. the number of cells per printed drop, was studied over the length of a typical printing experiment. This variation impacts the cell population size of bioprinted samples, which should ideally be consistent. The variation in output was specifically studied in the context of cell settling. The bioprinter studied is based on the thermal inkjet HP26A cartridge; however, the results are relevant to other cell delivery systems that draw fluid from a reservoir. A simple mathematical model suggests that the cell concentration in the bottom of the reservoir should increase linearly over time, up to some maximum, and that the cell output should be proportional to this concentration. Two studies were performed in which D1 murine stem cells and similarly sized polystyrene latex beads were printed. The bead output profiles were consistent with the model. The cell output profiles initially followed the increasing trend predicted by the settling model, but after several minutes the cell output peaked and then decreased. The decrease in cell output was found to be associated with the number of use cycles the cartridge had experienced. The differing results for beads and cells suggest that a biological process, such as adhesion, causes the decrease in cell output. Further work will be required to identify the exact process. (communication)

A utility piezoelectric energy harvester with low frequency and high-output voltage: Theoretical model, experimental verification and energy storage

Directory of Open Access Journals (Sweden)

Guangyi Zhang

2016-09-01

Full Text Available In this paper, a utility piezoelectric energy harvester with low frequency and high-output voltage is presented. Firstly, the harvester’s three theoretical models are presented, namely the static model, the quasi static model and the dynamic vibration model. By analyzing the influence of the mass ratio of the mass block to the beam on output characteristics of the harvester, we compare the quasi static model and the dynamic vibration model and then define their applicable ranges. Secondly, simulation and experiments are done to verify the models, using the harvester with PZT-5H piezoelectric material, which are proved to be consistent with each other. The experimental results show that the output open-circuit voltage and the output power can reach up to 86.36V and 27.5mW respectively. The experiments are conducted when this harvester system is excited by the first modal frequency (58.90Hz with the acceleration 10m/s2. In this low frequency vibration case, it is easy to capture the energy in the daily environment. In addition, LTC 3588-1 chip (Linear Technology Corporation is used as the medium energy circuit to transfer charges from the PZT-5H electrode to the 0.22F 5V super capacitor and ML621 rechargeable button battery. For this super-capacitor, it takes about 100min for the capacitor voltage to rise from 0V to 3.6V. For this button battery, it takes about 200min to increase the battery voltage from 2.5V to 3.48V.

Choice of theoretical model for beam scattering at accelerator output foil for particle energy determination

International Nuclear Information System (INIS)

Balagyra, V.S.; Ryabka, P.M.

1999-01-01

For measuring the charged particle energy calculations of mean square angles of electron beam multiple Coulomb scattering at output combined accelerator target were undertaken according to seven theoretical models. Mollier method showed the best agreement with experiments

Accessing National Water Model Output for Research and Application: An R package

Science.gov (United States)

Johnson, M.; Coll, J.

2017-12-01

With the National Water Model becoming operational in August of 2016, the need for a open source way to translate a huge amount of data into actionable intelligence and innovative research is apparent. The first step in doing this is to provide a package for accessing, managing, and writing data in a way that is both interpretable, portable, and useful to the end user in both the R environment, and other applications. This can be as simple as subsetting the outputs and writing to a CSV, but can also include converting discharge output to more meaningful statistics and measurements, and methods to visualize data in ways that are meaningful to a wider audience. The NWM R package presented here aims to serve this need through a suite of functions fit for researchers, first responders, and average citizens. A vignette of how this package can be applied to real-time flood mapping will be demonstrated.

Earth System Model Development and Analysis using FRE-Curator and Live Access Servers: On-demand analysis of climate model output with data provenance.

Science.gov (United States)

Radhakrishnan, A.; Balaji, V.; Schweitzer, R.; Nikonov, S.; O'Brien, K.; Vahlenkamp, H.; Burger, E. F.

2016-12-01

There are distinct phases in the development cycle of an Earth system model. During the model development phase, scientists make changes to code and parameters and require rapid access to results for evaluation. During the production phase, scientists may make an ensemble of runs with different settings, and produce large quantities of output, that must be further analyzed and quality controlled for scientific papers and submission to international projects such as the Climate Model Intercomparison Project (CMIP). During this phase, provenance is a key concern:being able to track back from outputs to inputs. We will discuss one of the paths taken at GFDL in delivering tools across this lifecycle, offering on-demand analysis of data by integrating the use of GFDL's in-house FRE-Curator, Unidata's THREDDS and NOAA PMEL's Live Access Servers (LAS).Experience over this lifecycle suggests that a major difficulty in developing analysis capabilities is only partially the scientific content, but often devoted to answering the questions "where is the data?" and "how do I get to it?". "FRE-Curator" is the name of a database-centric paradigm used at NOAA GFDL to ingest information about the model runs into an RDBMS (Curator database). The components of FRE-Curator are integrated into Flexible Runtime Environment workflow and can be invoked during climate model simulation. The front end to FRE-Curator, known as the Model Development Database Interface (MDBI) provides an in-house web-based access to GFDL experiments: metadata, analysis output and more. In order to provide on-demand visualization, MDBI uses Live Access Servers which is a highly configurable web server designed to provide flexible access to geo-referenced scientific data, that makes use of OPeNDAP. Model output saved in GFDL's tape archive, the size of the database and experiments, continuous model development initiatives with more dynamic configurations add complexity and challenges in providing an on

A new chance-constrained DEA model with birandom input and output data

OpenAIRE

Tavana, M.; Shiraz, R. K.; Hatami-Marbini, A.

2013-01-01

The purpose of conventional Data Envelopment Analysis (DEA) is to evaluate the performance of a set of firms or Decision-Making Units using deterministic input and output data. However, the input and output data in the real-life performance evaluation problems are often stochastic. The stochastic input and output data in DEA can be represented with random variables. Several methods have been proposed to deal with the random input and output data in DEA. In this paper, we propose a new chance-...

Analytical approach for modeling and performance analysis of microring resonators as optical filters with multiple output bus waveguides

Science.gov (United States)

Lakra, Suchita; Mandal, Sanjoy

2017-06-01

A quadruple micro-optical ring resonator (QMORR) with multiple output bus waveguides is mathematically modeled and analyzed by making use of the delay-line signal processing approach in Z-domain and Mason's gain formula. The performances of QMORR with two output bus waveguides with vertical coupling are analyzed. This proposed structure is capable of providing wider free spectral response from both the output buses with appreciable cross talk. Thus, this configuration could provide increased capacity to insert a large number of communication channels. The simulated frequency response characteristic and its dispersion and group delay characteristics are graphically presented using the MATLAB environment.

Monetary Policy and Industrial Output in the BRICS Countries: A Markov-Switching Model

Directory of Open Access Journals (Sweden)

Kutu Adebayo Augustine

2017-12-01

Full Text Available This paper examines whether the five BRICS countries share similar business cycles and determines the probability of any of the countries moving from a contractionary regime to an expansionary regime. The study further examines the extent to which changes in monetary policy affect industrial output in expansions relative to contractions. Employing the Peersman and Smets (2001 Markov-Switching Model (MSM and monthly data from 1994.01–2013.12, the study reveals that the five BRICS countries have similar business cycles. The results further demonstrate that the BRICS countries’ business cycles are characterized by two distinct growth rate phases: a contractionary regime and an expansionary regime. It can also be observed that the area-wide monetary policy has significantly large effects on industrial output in recessions as well as in booms. It has also been established that there is a high probability of moving from state one (recession to state two (expansion and that on average, the probabilities of staying in state 2 (expansion are high for each of the five countries. It is, therefore, recommended that the BRICS countries should sustain uniform policy consistency (monetary policy, especially as they formulate and implement economic policies to stimulate industrial output.

Decision- rather than scenario-centred downscaling: Towards smarter use of climate model outputs

Science.gov (United States)

Wilby, Robert L.

2013-04-01

Climate model output has been used for hydrological impact assessments for at least 25 years. Scenario-led methods raise awareness about risks posed by climate variability and change to the security of supplies, performance of water infrastructure, and health of freshwater ecosystems. However, it is less clear how these analyses translate into actionable information for adaptation. One reason is that scenario-led methods typically yield very large uncertainty bounds in projected impacts at regional and river catchment scales. Consequently, there is growing interest in vulnerability-based frameworks and strategies for employing climate model output in decision-making contexts. This talk begins by summarising contrasting perspectives on climate models and principles for testing their utility for water sector applications. Using selected examples it is then shown how water resource systems may be adapted with varying levels of reliance on climate model information. These approaches include the conventional scenario-led risk assessment, scenario-neutral strategies, safety margins and sensitivity testing, and adaptive management of water systems. The strengths and weaknesses of each approach are outlined and linked to selected water management activities. These cases show that much progress can be made in managing water systems without dependence on climate models. Low-regret measures such as improved forecasting, better inter-agency co-operation, and contingency planning, yield benefits regardless of the climate outlook. Nonetheless, climate model scenarios are useful for evaluating adaptation portfolios, identifying system thresholds and fixing weak links, exploring the timing of investments, improving operating rules, or developing smarter licensing regimes. The most problematic application remains the climate change safety margin because of the very low confidence in extreme precipitation and river flows generated by climate models. In such cases, it is necessary to

Input-output and energy demand models for Ireland: Data collection report. Part 1: EXPLOR

Energy Technology Data Exchange (ETDEWEB)

Henry, E W; Scott, S

1981-01-01

Data are presented in support of EXPLOR, an input-output economic model for Ireland. The data follow the listing of exogenous data-sets used by Batelle in document X11/515/77. Data are given for 1974, 1980, and 1985 and consist of household consumption, final demand-production, and commodity prices. (ACR)

Finding identifiable parameter combinations in nonlinear ODE models and the rational reparameterization of their input-output equations.

Science.gov (United States)

Meshkat, Nicolette; Anderson, Chris; Distefano, Joseph J

2011-09-01

When examining the structural identifiability properties of dynamic system models, some parameters can take on an infinite number of values and yet yield identical input-output data. These parameters and the model are then said to be unidentifiable. Finding identifiable combinations of parameters with which to reparameterize the model provides a means for quantitatively analyzing the model and computing solutions in terms of the combinations. In this paper, we revisit and explore the properties of an algorithm for finding identifiable parameter combinations using Gröbner Bases and prove useful theoretical properties of these parameter combinations. We prove a set of M algebraically independent identifiable parameter combinations can be found using this algorithm and that there exists a unique rational reparameterization of the input-output equations over these parameter combinations. We also demonstrate application of the procedure to a nonlinear biomodel. Copyright © 2011 Elsevier Inc. All rights reserved.

Explaining output volatility: The case of taxation

DEFF Research Database (Denmark)

Posch, Olaf

the second moment of output growth rates without (long-run) effects on the first moment. Taking the model to the data, we exploit observed heterogeneity patterns to estimate effects of tax rates on macro volatility using panel estimation, explicitly modeling the unobserved variance process. We find a strong......This paper studies the effects of taxation on output volatility in OECD countries to shed light on the sources of observed heterogeneity over time and across countries. To this end, we derive tax effects on macro aggregates in a stochastic neoclassical model. As a result, taxes are shown to affect...... positive effects....

Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms

Directory of Open Access Journals (Sweden)

G. McFarquhar

2009-07-01

Full Text Available The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during 9–10 October, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-h simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors' concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process

Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms

Science.gov (United States)

Sednev, I.; Menon, S.; McFarquhar, G.

2009-07-01

The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM) scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE) campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP) on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during 9-10 October, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-h simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors' concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity) against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process of ice phase initiation

A hybrid input–output multi-objective model to assess economic–energy–environment trade-offs in Brazil

International Nuclear Information System (INIS)

Carvalho, Ariovaldo Lopes de; Antunes, Carlos Henggeler; Freire, Fausto; Henriques, Carla Oliveira

2015-01-01

A multi-objective linear programming (MOLP) model based on a hybrid Input–Output (IO) framework is presented. This model aims at assessing the trade-offs between economic, energy, environmental (E3) and social objectives in the Brazilian economic system. This combination of multi-objective models with Input–Output Analysis (IOA) plays a supplementary role in understanding the interactions between the economic and energy systems, and the corresponding impacts on the environment, offering a consistent framework for assessing the effects of distinct policies on these systems. Firstly, the System of National Accounts (SNA) is reorganized to include the National Energy Balance, creating a hybrid IO framework that is extended to assess Greenhouse Gas (GHG) emissions and the employment level. The objective functions considered are the maximization of GDP (gross domestic product) and employment levels, as well as the minimization of energy consumption and GHG emissions. An interactive method enabling a progressive and selective search of non-dominated solutions with distinct characteristics and underlying trade-offs is utilized. Illustrative results indicate that the maximization of GDP and the employment levels lead to an increase of both energy consumption and GHG emissions, while the minimization of either GHG emissions or energy consumption cause negative impacts on GDP and employment. - Highlights: • A hybrid Input–Output multi-objective model is applied to the Brazilian economy. • Objective functions are GDP, employment level, energy consumption and GHG emissions. • Interactive search process identifies trade-offs between the competing objectives. • Positive correlations between GDP growth and employment. • Positive correlations between energy consumption and GHG emissions

Output Information Based Fault-Tolerant Iterative Learning Control for Dual-Rate Sampling Process with Disturbances and Output Delay

Directory of Open Access Journals (Sweden)

Hongfeng Tao

2018-01-01

Full Text Available For a class of single-input single-output (SISO dual-rate sampling processes with disturbances and output delay, this paper presents a robust fault-tolerant iterative learning control algorithm based on output information. Firstly, the dual-rate sampling process with output delay is transformed into discrete system in state-space model form with slow sampling rate without time delay by using lifting technology; then output information based fault-tolerant iterative learning control scheme is designed and the control process is turned into an equivalent two-dimensional (2D repetitive process. Moreover, based on the repetitive process stability theory, the sufficient conditions for the stability of system and the design method of robust controller are given in terms of linear matrix inequalities (LMIs technique. Finally, the flow control simulations of two flow tanks in series demonstrate the feasibility and effectiveness of the proposed method.

Data Envelopment Analysis with Fixed Inputs, Undesirable Outputs and Negative Data

Directory of Open Access Journals (Sweden)

F. Seyed Esmaeili

2017-03-01

Full Text Available In Data Envelopment Analysis (DEA, different models have been measured to evaluate the performance of decision making units with multiple inputs and outputs. Revised model of Slack-based measures known as MBSM of collective models family has been introduced by Sharp et al. Slack-based measure has been introduced by Ton. In this study, a model is proposed that is able to estimate the efficiency when a number of outputs of decision making units are undesirable, inputs are fixed and some of outputs and inputs are negative. So that, level of undesirable output is reduced at the constant level of inputs in the evaluation unit and by conserving the efficiency.

Output performance analyses of solar array on stratospheric airship with thermal effect

International Nuclear Information System (INIS)

Li, Jun; Lv, Mingyun; Tan, Dongjie; Zhu, Weiyu; Sun, Kangwen; Zhang, Yuanyuan

2016-01-01

Highlights: • A model investigating the output power of solar array is proposed. • The output power in the cruise condition with thermal effect is researched. • The effect of some factors on output performance is discussed in detail. • A suitable transmissivity of external layer is crucial in preliminary design step. - Abstract: Output performance analyses of the solar array are very critical for solving the energy problem of a long endurance stratospheric airship, and the solar cell efficiency is very sensitive to temperature of the solar cell. But the research about output performance of solar array with thermal effect is rare. This paper outlines a numerical model including the thermal model of airship and solar cells, the incident solar radiation model on the solar array, and the power output model. Based on this numerical model, a MATLAB computer program is developed. In the course of the investigation, the comparisons of the simulation results with and without considering thermal effect are reported. Furthermore, effects of the transmissivity of external encapsulation layer of solar array and wind speed on the thermal performance and output power of solar array are discussed in detail. The results indicate that this method is helpful for planning energy management.

Two-dimensional modeling of x-ray output from switched foil implosions on Procyon

Science.gov (United States)

Bowers, R. L.; Nakafuji, G.; Greene, A. E.; McLenithan, K. D.; Peterson, D. L.; Roderick, N. F.

1996-09-01

A series of two-dimensional radiation magnetohydrodynamic calculations are presented of a Z-pinch implosion using a plasma flow switch. Results from a recent experiment using the high explosive driven generator Procyon, which delivered 16.5 MA to a plasma flow switch and switched about 15 MA into a static load, are used to study the implosion of a 29 mg load foil [J. H. Goforth et al., ``Review of the Procyon Explosive Pulsed Power System,'' in Ninth IEEE Pulsed Power Conference, June 1993, Albuquerque, edited by K. R. Prestwich and W. L. Baker (Institute of Electrical and Electronics Engineers, Piscataway, NJ, 1993), p. 36]. The interaction of the switch with the load plasma and the effects of background plasma on the total radiation output is examined. Models which assume ideal switching are also included. Also included are the effects of perturbations in the load plasma which may be associated with initial vaporization of the load foil. If the background plasma density in the switch region and in the load region does not affect the dynamics, the pinch is predicted to produce a total radiation output of about 4 MJ. Including perturbations of the load plasma associated with switching and assuming a background plasma density after switching in excess of 10-7 g/cm3 results in a total output from the pinch of about 0.6 MJ.

A statistical-dynamical modeling approach for the simulation of local paleo proxy records using GCM output

Energy Technology Data Exchange (ETDEWEB)

Reichert, B.K.; Bengtsson, L. [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Aakesson, O. [Sveriges Meteorologiska och Hydrologiska Inst., Norrkoeping (Sweden)

1998-08-01

Recent proxy data obtained from ice core measurements, dendrochronology and valley glaciers provide important information on the evolution of the regional or local climate. General circulation models integrated over a long period of time could help to understand the (external and internal) forcing mechanisms of natural climate variability. For a systematic interpretation of in situ paleo proxy records, a combined method of dynamical and statistical modeling is proposed. Local 'paleo records' can be simulated from GCM output by first undertaking a model-consistent statistical downscaling and then using a process-based forward modeling approach to obtain the behavior of valley glaciers and the growth of trees under specific conditions. The simulated records can be compared to actual proxy records in order to investigate whether e.g. the response of glaciers to climatic change can be reproduced by models and to what extent climate variability obtained from proxy records (with the main focus on the last millennium) can be represented. For statistical downscaling to local weather conditions, a multiple linear forward regression model is used. Daily sets of observed weather station data and various large-scale predictors at 7 pressure levels obtained from ECMWF reanalyses are used for development of the model. Daily data give the closest and most robust relationships due to the strong dependence on individual synoptic-scale patterns. For some local variables, the performance of the model can be further increased by developing seasonal specific statistical relationships. The model is validated using both independent and restricted predictor data sets. The model is applied to a long integration of a mixed layer GCM experiment simulating pre-industrial climate variability. The dynamical-statistical local GCM output within a region around Nigardsbreen glacier, Norway is compared to nearby observed station data for the period 1868-1993. Patterns of observed

Prioritizing Interdependent Production Processes using Leontief Input-Output Model

Directory of Open Access Journals (Sweden)

Masbad Jesah Grace

2016-03-01

Full Text Available This paper proposes a methodology in identifying key production processes in an interdependent production system. Previous approaches on this domain have drawbacks that may potentially affect the reliability of decision-making. The proposed approach adopts the Leontief input-output model (L-IOM which was proven successful in analyzing interdependent economic systems. The motivation behind such adoption lies in the strength of L-IOM in providing a rigorous quantitative framework in identifying key components of interdependent systems. In this proposed approach, the consumption and production flows of each process are represented respectively by the material inventory produced by the prior process and the material inventory produced by the current process, both in monetary values. A case study in a furniture production system located in central Philippines was carried out to elucidate the proposed approach. Results of the case were reported in this work

Mechanisms Regulating the Cardiac Output Response to Cyanide Infusion, a Model of Hypoxia

Science.gov (United States)

Liang, Chang-seng; Huckabee, William E.

1973-01-01

When tissue metabolic changes like those of hypoxia were induced by intra-aortic infusion of cyanide in dogs, cardiac output began to increase after 3 to 5 min, reached a peak (220% of the control value) at 15 min, and returned to control in 40 min. This pattern of cardiac output rise was not altered by vagotomy with or without atropine pretreatment. However, this cardiac output response could be differentiated into three phases by pretreating the animals with agents that block specific activities of the sympatho-adrenal system. First, ganglionic blockade produced by mecamylamine or sympathetic nerve blockade by bretylium abolished the middle phase of the cardiac output seen in the untreated animal, but early and late phases still could be discerned. Second, beta-adrenergic receptor blockade produced by propranolol shortened the total duration of the cardiac output rise by abolishing the late phase. Third, when given together, propranolol and mecamylamine (or bretylium) prevented most of the cardiac output rise that follows the early phase. When cyanide was given to splenectomized dogs, the duration of the cardiac output response was not shortened, but the response became biphasic, resembling that seen after chemical sympathectomy. A similar biphasic response of the cardiac output also resulted from splenic denervation; sham operation or nephrectomy had no effect on the monophasic pattern of the normal response. Splenic venous blood obtained from cyanide-treated dogs, when infused intraportally, caused an increase in cardiac output in recipient dogs; similar infusion of arterial blood had no effects. These results suggest that the cardiac output response to cyanide infusion consists of three components: an early phase, related neither to the autonomic nervous system nor to circulating catecholamines; a middle phase, caused by a nonadrenergic humoral substance released from the spleen by sympathetic stimulation; and a late phase, dependent upon adrenergic receptors

From LCC to LCA Using a Hybrid Input Output Model – A Maritime Case Study

DEFF Research Database (Denmark)

Kjær, Louise Laumann; Pagoropoulos, Aris; Hauschild, Michael Zwicky

2015-01-01

As companies try to embrace life cycle thinking, Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) have proven to be powerful tools. In this paper, an Environmental Input-Output model is used for analysis as it enables an LCA using the same economic input data as LCC. This approach helps...

Thin disk laser with unstable resonator and reduced output coupler

Science.gov (United States)

Gavili, Anwar; Shayganmanesh, Mahdi

2018-05-01

In this paper, feasibility of using unstable resonator with reduced output coupling in a thin disk laser is studied theoretically. Unstable resonator is modeled by wave-optics using Collins integral and iterative method. An Yb:YAG crystal with 250 micron thickness is considered as a quasi-three level active medium and modeled by solving rate equations of energy levels populations. The amplification of laser beam in the active medium is calculated based on the Beer-Lambert law and Rigrod method. Using generalized beam parameters method, laser beam parameters like, width, divergence, M2 factor, output power as well as near and far-field beam profiles are calculated for unstable resonator. It is demonstrated that for thin disk laser (with single disk) in spite of the low thickness of the disk which leads to low gain factor, it is possible to use unstable resonator (with reduced output coupling) and achieve good output power with appropriate beam quality. Also, the behavior of output power and beam quality versus equivalent Fresnel number is investigated and optimized value of output coupling for maximum output power is achieved.

Public Investment and Output Performance: Evidence from Nigeria

Directory of Open Access Journals (Sweden)

Aregbeyen Omo

2016-05-01

Full Text Available This study examined the direct/indirect long-run relationships and dynamic interactions between public investment (PI and output performance in Nigeria using annual data spanning 1970-2010. A macro-econometric model derived from Keynes’ income-expenditure framework was employed. The model was disaggregated into demand and supply sides to trace the direct and indirect effects of PI on aggregate output. The direct supply side effect was assessed using the magnitude of PI multiplier coefficient, while the indirect effect of PI on the demand side was evaluated with marginal propensity to consume, accelerator coefficient and import multiplier. The results showed relatively less strong direct effect of PI on aggregate output, while the indirect effects were stronger with the import multiplier being the most pronounced. This is attributed to declining capital expenditure, poor implementation and low quality of PI projects due to widespread corruption. By and large, we concluded that PI exerted considerable influence on aggregate output.

Sensitivity of Glacier Mass Balance Estimates to the Selection of WRF Cloud Microphysics Parameterization in the Indus River Watershed

Science.gov (United States)

Johnson, E. S.; Rupper, S.; Steenburgh, W. J.; Strong, C.; Kochanski, A.

2017-12-01

Climate model outputs are often used as inputs to glacier energy and mass balance models, which are essential glaciological tools for testing glacier sensitivity, providing mass balance estimates in regions with little glaciological data, and providing a means to model future changes. Climate model outputs, however, are sensitive to the choice of physical parameterizations, such as those for cloud microphysics, land-surface schemes, surface layer options, etc. Furthermore, glacier mass balance (MB) estimates that use these climate model outputs as inputs are likely sensitive to the specific parameterization schemes, but this sensitivity has not been carefully assessed. Here we evaluate the sensitivity of glacier MB estimates across the Indus Basin to the selection of cloud microphysics parameterizations in the Weather Research and Forecasting Model (WRF). Cloud microphysics parameterizations differ in how they specify the size distributions of hydrometeors, the rate of graupel and snow production, their fall speed assumptions, the rates at which they convert from one hydrometeor type to the other, etc. While glacier MB estimates are likely sensitive to other parameterizations in WRF, our preliminary results suggest that glacier MB is highly sensitive to the timing, frequency, and amount of snowfall, which is influenced by the cloud microphysics parameterization. To this end, the Indus Basin is an ideal study site, as it has both westerly (winter) and monsoonal (summer) precipitation influences, is a data-sparse region (so models are critical), and still has lingering questions as to glacier importance for local and regional resources. WRF is run at a 4 km grid scale using two commonly used parameterizations: the Thompson scheme and the Goddard scheme. On average, these parameterizations result in minimal differences in annual precipitation. However, localized regions exhibit differences in precipitation of up to 3 m w.e. a-1. The different schemes also impact the

Industrial output restriction and the Kyoto protocol. An input-output approach with application to Canada

International Nuclear Information System (INIS)

Lixon, Benoit; Thomassin, Paul J.; Hamaide, Bertrand

2008-01-01

The objective of this paper is to assess the economic impacts of reducing greenhouse gas emissions by decreasing industrial output in Canada to a level that will meet the target set out in the Kyoto Protocol. The study uses an ecological-economic Input-Output model combining economic components valued in monetary terms with ecologic components - GHG emissions - expressed in physical terms. Economic and greenhouse gas emissions data for Canada are computed in the same sectoral disaggregation. Three policy scenarios are considered: the first one uses the direct emission coefficients to allocate the reduction in industrial output, while the other two use the direct plus indirect emission coefficients. In the first two scenarios, the reduction in industrial sector output is allocated uniformly across sectors while it is allocated to the 12 largest emitting industries in the last one. The estimated impacts indicate that the results vary with the different allocation methods. The third policy scenario, allocation to the 12 largest emitting sectors, is the most cost effective of the three as the impacts of the Kyoto Protocol reduces Gross Domestic Product by 3.1% compared to 24% and 8.1% in the first two scenarios. Computed economic costs should be considered as upper-bounds because the model assumes immediate adjustment to the Kyoto Protocol and because flexibility mechanisms are not incorporated. The resulting upper-bound impact of the third scenario may seem to contradict those who claim that the Kyoto Protocol would place an unbearable burden on the Canadian economy. (author)

Money and Output: A Test of Reverse Causation.

OpenAIRE

Coleman, Wilbur John, II

1996-01-01

This paper attempts to explain the correlation between money and output at various leads and lags with a model in which money is largely neutral and endogenously responds to output. Money is endogenous because both monetary policy and deposit creation are endogenous. Parameters are selected according to the simulated moments estimation technique. While the estimated model succeeds along some dimensions in matching properties of postwar U.S. data, its failure to match key patterns of lead-lag ...

Does Black’s Hypothesis for Output Variability Hold for Mexico?

OpenAIRE

Macri, Joseph; Sinha, Dipendra

2007-01-01

Using two data series, namely GDP and the index of industrial production, we study the relationship between output variability and the growth rate of output. Ng-Perron unit root test shows that the growth rate of GDP is non-stationary but the growth rate of industrial output is stationary. Thus, we use the ARCH-M model for the monthly data of industrial output. A number of specifications (with and without a dummy variable) are used. In all cases, the results show that output variability has a...

Data Envelopment Analysis with Uncertain Inputs and Outputs

Directory of Open Access Journals (Sweden)

Meilin Wen

2014-01-01

Full Text Available Data envelopment analysis (DEA, as a useful management and decision tool, has been widely used since it was first invented by Charnes et al. in 1978. On the one hand, the DEA models need accurate inputs and outputs data. On the other hand, in many situations, inputs and outputs are volatile and complex so that they are difficult to measure in an accurate way. The conflict leads to the researches of uncertain DEA models. This paper will consider DEA in uncertain environment, thus producing a new model based on uncertain measure. Due to the complexity of the new uncertain DEA model, an equivalent deterministic model is presented. Finally, a numerical example is presented to illustrate the effectiveness of the uncertain DEA model.

Application of Artificial Thunderstorm Cells for the Investigation of Lightning Initiation Problems between a Thundercloud and the Ground

Science.gov (United States)

Temnikov, A. G.; Chernensky, L. L.; Orlov, A. V.; Lysov, N. Y.; Zhuravkova, D. S.; Belova, O. S.; Gerastenok, T. K.

2017-12-01

The results of the experimental application of artificial thunderstorm cells of negative and positive polarities for the investigation of the lightning initiation problems between the thundercloud and the ground using model hydrometeor arrays are presented. Possible options of the initiation and development of a discharge between the charged cloud and the ground in the presence of model hydrometeors are established. It is experimentally shown that groups of large hydrometeors of various shapes significantly increase the probability of channel discharge initiation between the artificial thunderstorm cell and the ground, especially in the case of positive polarity of the cloud. The authors assume that large hail arrays in the thundercloud can initiate the preliminary breakdown stage in the lower part of the thundercloud or initiate and stimulate the propagation of positive lightning from its upper part. A significant effect of the shape of model hydrometeors and the way they are grouped on the processes of initiation and stimulation of the channel discharge propagation in the artificial thunderstorm cell of negative or positive polarity-ground gap is experimentally established. It is found that, in the case of negative polarity of a charged cloud, the group of conductive cylindrical hydrometeors connected by a dielectric string more effectively initiates the channel discharge between the artificial thunderstorm cell and the ground. In the case of positive polarity of the artificial thunderstorm cell, the best effect of the channel discharge initiation is achieved for model hydrometeors grouped together by the dielectric tape. The obtained results can be used in the development of the method for the directed artificial lightning initiation between the thundercloud and the ground.

Output, renewable energy consumption and trade in Africa

International Nuclear Information System (INIS)

Ben Aïssa, Mohamed Safouane; Ben Jebli, Mehdi; Ben Youssef, Slim

2014-01-01

We use panel cointegration techniques to examine the relationship between renewable energy consumption, trade and output in a sample of 11 African countries covering the period 1980–2008. The results from panel error correction model reveal that there is evidence of a bidirectional causality between output and exports and between output and imports in both the short and long-run. However, in the short-run, there is no evidence of causality between output and renewable energy consumption and between trade (exports or imports) and renewable energy consumption. Also, in the long-run, there is no causality running from output or trade to renewable energy. In the long-run, our estimations show that renewable energy consumption and trade have a statistically significant and positive impact on output. Our energy policy recommendations are that national authorities should design appropriate fiscal incentives to encourage the use of renewable energies, create more regional economic integration for renewable energy technologies, and encourage trade openness because of its positive impact on technology transfer and on output. - Highlights: • We examine the relationship between renewable energy consumption, trade and output in African countries. • There is a bidirectional causality between output and trade in both the short and long-run. • In the short-run, there is no causality between renewable energy consumption and trade or output. • In the long-run, renewable energy consumption and trade have a statistically significant positive impact on output. • African authorities should encourage trade openness because of its positive impact on technology transfer and on output

Steady State Analysis of LCLC Resonant Converter with Capacitive Output Filter

Directory of Open Access Journals (Sweden)

Navid Shafiyi

2010-01-01

Full Text Available This paper presents the mathematical analysis and modeling of a 4th order LCLC resonant converter with capacitive output filter in steady-state condition. Due to the nonlinearity of the LCLC resonant circuit with capacitive output filter, the conventional modeling procedure cannot thoroughly describe the behavior of the converter. In this paper, a mathematical model is proposed that can accommodate the absence of the output inductor and predict the converter performance for a wide range of operating conditions. A 2.25KW prototype converter is provided to evaluate the accuracy of the proposed model. Experimental results show that the proposed model can precisely predict the behavior of the converter for a wide range of operating conditions.

Wavelet transform-vector quantization compression of supercomputer ocean model simulation output

Energy Technology Data Exchange (ETDEWEB)

Bradley, J N; Brislawn, C M

1992-11-12

We describe a new procedure for efficient compression of digital information for storage and transmission purposes. The algorithm involves a discrete wavelet transform subband decomposition of the data set, followed by vector quantization of the wavelet transform coefficients using application-specific vector quantizers. The new vector quantizer design procedure optimizes the assignment of both memory resources and vector dimensions to the transform subbands by minimizing an exponential rate-distortion functional subject to constraints on both overall bit-rate and encoder complexity. The wavelet-vector quantization method, which originates in digital image compression. is applicable to the compression of other multidimensional data sets possessing some degree of smoothness. In this paper we discuss the use of this technique for compressing the output of supercomputer simulations of global climate models. The data presented here comes from Semtner-Chervin global ocean models run at the National Center for Atmospheric Research and at the Los Alamos Advanced Computing Laboratory.

CM-DataONE: A Framework for collaborative analysis of climate model output

Science.gov (United States)

Xu, Hao; Bai, Yuqi; Li, Sha; Dong, Wenhao; Huang, Wenyu; Xu, Shiming; Lin, Yanluan; Wang, Bin

2015-04-01

CM-DataONE is a distributed collaborative analysis framework for climate model data which aims to break through the data access barriers of increasing file size and to accelerate research process. As data size involved in project such as the fifth Coupled Model Intercomparison Project (CMIP5) has reached petabytes, conventional methods for analysis and diagnosis of model outputs have been rather time-consuming and redundant. CM-DataONE is developed for data publishers and researchers from relevant areas. It can enable easy access to distributed data and provide extensible analysis functions based on tools such as NCAR Command Language, NetCDF Operators (NCO) and Climate Data Operators (CDO). CM-DataONE can be easily installed, configured, and maintained. The main web application has two separate parts which communicate with each other through APIs based on HTTP protocol. The analytic server is designed to be installed in each data node while a data portal can be configured anywhere and connect to a nearest node. Functions such as data query, analytic task submission, status monitoring, visualization and product downloading are provided to end users by data portal. Data conform to CMIP5 Model Output Format in each peer node can be scanned by the server and mapped to a global information database. A scheduler included in the server is responsible for task decomposition, distribution and consolidation. Analysis functions are always executed where data locate. Analysis function package included in the server has provided commonly used functions such as EOF analysis, trend analysis and time series. Functions are coupled with data by XML descriptions and can be easily extended. Various types of results can be obtained by users for further studies. This framework has significantly decreased the amount of data to be transmitted and improved efficiency in model intercomparison jobs by supporting online analysis and multi-node collaboration. To end users, data query is

Fuzzy portfolio model with fuzzy-input return rates and fuzzy-output proportions

Science.gov (United States)

Tsaur, Ruey-Chyn

2015-02-01

In the finance market, a short-term investment strategy is usually applied in portfolio selection in order to reduce investment risk; however, the economy is uncertain and the investment period is short. Further, an investor has incomplete information for selecting a portfolio with crisp proportions for each chosen security. In this paper we present a new method of constructing fuzzy portfolio model for the parameters of fuzzy-input return rates and fuzzy-output proportions, based on possibilistic mean-standard deviation models. Furthermore, we consider both excess or shortage of investment in different economic periods by using fuzzy constraint for the sum of the fuzzy proportions, and we also refer to risks of securities investment and vagueness of incomplete information during the period of depression economics for the portfolio selection. Finally, we present a numerical example of a portfolio selection problem to illustrate the proposed model and a sensitivity analysis is realised based on the results.

Downscaling Global Weather Forecast Outputs Using ANN for Flood Prediction

Directory of Open Access Journals (Sweden)

Nam Do Hoai

2011-01-01

Full Text Available Downscaling global weather prediction model outputs to individual locations or local scales is a common practice for operational weather forecast in order to correct the model outputs at subgrid scales. This paper presents an empirical-statistical downscaling method for precipitation prediction which uses a feed-forward multilayer perceptron (MLP neural network. The MLP architecture was optimized by considering physical bases that determine the circulation of atmospheric variables. Downscaled precipitation was then used as inputs to the super tank model (runoff model for flood prediction. The case study was conducted for the Thu Bon River Basin, located in Central Vietnam. Study results showed that the precipitation predicted by MLP outperformed that directly obtained from model outputs or downscaled using multiple linear regression. Consequently, flood forecast based on the downscaled precipitation was very encouraging. It has demonstrated as a robust technology, simple to implement, reliable, and universal application for flood prediction through the combination of downscaling model and super tank model.

Study of cumulative fatigue damage detection for used parts with nonlinear output frequency response functions based on NARMAX modelling

Science.gov (United States)

Huang, Honglan; Mao, Hanying; Mao, Hanling; Zheng, Weixue; Huang, Zhenfeng; Li, Xinxin; Wang, Xianghong

2017-12-01

Cumulative fatigue damage detection for used parts plays a key role in the process of remanufacturing engineering and is related to the service safety of the remanufactured parts. In light of the nonlinear properties of used parts caused by cumulative fatigue damage, the based nonlinear output frequency response functions detection approach offers a breakthrough to solve this key problem. First, a modified PSO-adaptive lasso algorithm is introduced to improve the accuracy of the NARMAX model under impulse hammer excitation, and then, an effective new algorithm is derived to estimate the nonlinear output frequency response functions under rectangular pulse excitation, and a based nonlinear output frequency response functions index is introduced to detect the cumulative fatigue damage in used parts. Then, a novel damage detection approach that integrates the NARMAX model and the rectangular pulse is proposed for nonlinear output frequency response functions identification and cumulative fatigue damage detection of used parts. Finally, experimental studies of fatigued plate specimens and used connecting rod parts are conducted to verify the validity of the novel approach. The obtained results reveal that the new approach can detect cumulative fatigue damages of used parts effectively and efficiently and that the various values of the based nonlinear output frequency response functions index can be used to detect the different fatigue damages or working time. Since the proposed new approach can extract nonlinear properties of systems by only a single excitation of the inspected system, it shows great promise for use in remanufacturing engineering applications.

Simulation of Distributed PV Power Output in Oahu Hawaii

Energy Technology Data Exchange (ETDEWEB)

Lave, Matthew Samuel [Sandia National Lab. (SNL-CA), Livermore, CA (United States)

2016-08-01

Distributed solar photovoltaic (PV) power generation in Oahu has grown rapidly since 2008. For applications such as determining the value of energy storage, it is important to have PV power output timeseries. Since these timeseries of not typically measured, here we produce simulated distributed PV power output for Oahu. Simulated power output is based on (a) satellite-derived solar irradiance, (b) PV permit data by neighborhood, and (c) population data by census block. Permit and population data was used to model locations of distributed PV, and irradiance data was then used to simulate power output. PV power output simulations are presented by sub-neighborhood polygons, neighborhoods, and for the whole island of Oahu. Summary plots of annual PV energy and a sample week timeseries of power output are shown, and a the files containing the entire timeseries are described.

The input and output management of solid waste using DEA models: A case study at Jengka, Pahang

Science.gov (United States)

Mohamed, Siti Rosiah; Ghazali, Nur Fadzrina Mohd; Mohd, Ainun Hafizah

2017-08-01

Data Envelopment Analysis (DEA) as a tool for obtaining performance indices has been used extensively in several of organizations sector. The ways to improve the efficiency of Decision Making Units (DMUs) is impractical because some of inputs and outputs are uncontrollable and in certain situation its produce weak efficiency which often reflect the impact for operating environment. Based on the data from Alam Flora Sdn. Bhd Jengka, the researcher wants to determine the efficiency of solid waste management (SWM) in town Jengka Pahang using CCRI and CCRO model of DEA and duality formulation with vector average input and output. Three input variables (length collection in meter, frequency time per week in hour and number of garbage truck) and 2 outputs variables (frequency collection and the total solid waste collection in kilogram) are analyzed. As a conclusion, it shows only three roads from 23 roads are efficient that achieve efficiency score 1. Meanwhile, 20 other roads are in an inefficient management.

Robust output synchronization of heterogeneous nonlinear agents in uncertain networks.

Science.gov (United States)

Yang, Xi; Wan, Fuhua; Tu, Mengchuan; Shen, Guojiang

2017-11-01

This paper investigates the global robust output synchronization problem for a class of nonlinear multi-agent systems. In the considered setup, the controlled agents are heterogeneous and with both dynamic and parametric uncertainties, the controllers are incapable of exchanging their internal states with the neighbors, and the communication network among agents is defined by an uncertain simple digraph. The problem is pursued via nonlinear output regulation theory and internal model based design. For each agent, the input-driven filter and the internal model compose the controller, and the decentralized dynamic output feedback control law is derived by using backstepping method and the modified dynamic high-gain technique. The theoretical result is applied to output synchronization problem for uncertain network of Lorenz-type agents. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Input-Output Economics : Theory and Applications - Featuring Asian Economies

NARCIS (Netherlands)

Ten Raa, T.

2009-01-01

Thijs ten Raa, author of the acclaimed text The Economics of Input–Output Analysis, now takes the reader to the forefront of the field. This volume collects and unifies his and his co-authors' research papers on national accounting, Input–Output coefficients, economic theory, dynamic models,

Unit 16 - Output

OpenAIRE

Unit 16, CC in GIS; Star, Jeffrey L.

1990-01-01

This unit discusses issues related to GIS output, including the different types of output possible and the hardware for producing each. It describes text, graphic and digital data that can be generated by a GIS as well as line printers, dot matrix printers/plotters, pen plotters, optical scanners and cathode ray tubes (CRTs) as technologies for generating the output.

Stabilization of nonlinear systems using sampled-data output-feedback fuzzy controller based on polynomial-fuzzy-model-based control approach.

Science.gov (United States)

Lam, H K

2012-02-01

This paper investigates the stability of sampled-data output-feedback (SDOF) polynomial-fuzzy-model-based control systems. Representing the nonlinear plant using a polynomial fuzzy model, an SDOF fuzzy controller is proposed to perform the control process using the system output information. As only the system output is available for feedback compensation, it is more challenging for the controller design and system analysis compared to the full-state-feedback case. Furthermore, because of the sampling activity, the control signal is kept constant by the zero-order hold during the sampling period, which complicates the system dynamics and makes the stability analysis more difficult. In this paper, two cases of SDOF fuzzy controllers, which either share the same number of fuzzy rules or not, are considered. The system stability is investigated based on the Lyapunov stability theory using the sum-of-squares (SOS) approach. SOS-based stability conditions are obtained to guarantee the system stability and synthesize the SDOF fuzzy controller. Simulation examples are given to demonstrate the merits of the proposed SDOF fuzzy control approach.

Towards systematic evaluation of crop model outputs for global land-use models

Science.gov (United States)

Leclere, David; Azevedo, Ligia B.; Skalský, Rastislav; Balkovič, Juraj; Havlík, Petr

2016-04-01

Land provides vital socioeconomic resources to the society, however at the cost of large environmental degradations. Global integrated models combining high resolution global gridded crop models (GGCMs) and global economic models (GEMs) are increasingly being used to inform sustainable solution for agricultural land-use. However, little effort has yet been done to evaluate and compare the accuracy of GGCM outputs. In addition, GGCM datasets require a large amount of parameters whose values and their variability across space are weakly constrained: increasing the accuracy of such dataset has a very high computing cost. Innovative evaluation methods are required both to ground credibility to the global integrated models, and to allow efficient parameter specification of GGCMs. We propose an evaluation strategy for GGCM datasets in the perspective of use in GEMs, illustrated with preliminary results from a novel dataset (the Hypercube) generated by the EPIC GGCM and used in the GLOBIOM land use GEM to inform on present-day crop yield, water and nutrient input needs for 16 crops x 15 management intensities, at a spatial resolution of 5 arc-minutes. We adopt the following principle: evaluation should provide a transparent diagnosis of model adequacy for its intended use. We briefly describe how the Hypercube data is generated and how it articulates with GLOBIOM in order to transparently identify the performances to be evaluated, as well as the main assumptions and data processing involved. Expected performances include adequately representing the sub-national heterogeneity in crop yield and input needs: i) in space, ii) across crop species, and iii) across management intensities. We will present and discuss measures of these expected performances and weight the relative contribution of crop model, input data and data processing steps in performances. We will also compare obtained yield gaps and main yield-limiting factors against the M3 dataset. Next steps include

A Markovian model of evolving world input-output network.

Directory of Open Access Journals (Sweden)

Vahid Moosavi

Full Text Available The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, so far there has not been a full investigation of evolving world economic networks with Markov chain formalism. In this work, using the recently available world input-output database, we investigated the evolution of the world economic network from 1995 to 2011 through analysis of a time series of finite Markov chains. We assessed different aspects of this evolving system via different known properties of the Markov chains such as mixing time, Kemeny constant, steady state probabilities and perturbation analysis of the transition matrices. First, we showed how the time series of mixing times and Kemeny constants could be used as an aggregate index of globalization. Next, we focused on the steady state probabilities as a measure of structural power of the economies that are comparable to GDP shares of economies as the traditional index of economies welfare. Further, we introduced two measures of systemic risk, called systemic influence and systemic fragility, where the former is the ratio of number of influenced nodes to the total number of nodes, caused by a shock in the activity of a node, and the latter is based on the number of times a specific economic node is affected by a shock in the activity of any of the other nodes. Finally, focusing on Kemeny constant as a global indicator of monetary flow across the network, we showed that there is a paradoxical effect of a change in activity levels of economic nodes on the overall flow of the world economic network. While the economic slowdown of the majority of nodes with high structural power results to a slower average monetary flow over the network, there are some nodes, where their slowdowns improve the overall quality of the network in terms of connectivity and the average flow of the money.

A Markovian model of evolving world input-output network.

Science.gov (United States)

Moosavi, Vahid; Isacchini, Giulio

2017-01-01

The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, so far there has not been a full investigation of evolving world economic networks with Markov chain formalism. In this work, using the recently available world input-output database, we investigated the evolution of the world economic network from 1995 to 2011 through analysis of a time series of finite Markov chains. We assessed different aspects of this evolving system via different known properties of the Markov chains such as mixing time, Kemeny constant, steady state probabilities and perturbation analysis of the transition matrices. First, we showed how the time series of mixing times and Kemeny constants could be used as an aggregate index of globalization. Next, we focused on the steady state probabilities as a measure of structural power of the economies that are comparable to GDP shares of economies as the traditional index of economies welfare. Further, we introduced two measures of systemic risk, called systemic influence and systemic fragility, where the former is the ratio of number of influenced nodes to the total number of nodes, caused by a shock in the activity of a node, and the latter is based on the number of times a specific economic node is affected by a shock in the activity of any of the other nodes. Finally, focusing on Kemeny constant as a global indicator of monetary flow across the network, we showed that there is a paradoxical effect of a change in activity levels of economic nodes on the overall flow of the world economic network. While the economic slowdown of the majority of nodes with high structural power results to a slower average monetary flow over the network, there are some nodes, where their slowdowns improve the overall quality of the network in terms of connectivity and the average flow of the money.

Inflation, inflation uncertainty and output growth in the USA

Science.gov (United States)

Bhar, Ramprasad; Mallik, Girijasankar

2010-12-01

Employing a multivariate EGARCH-M model, this study investigates the effects of inflation uncertainty and growth uncertainty on inflation and output growth in the United States. Our results show that inflation uncertainty has a positive and significant effect on the level of inflation and a negative and significant effect on the output growth. However, output uncertainty has no significant effect on output growth or inflation. The oil price also has a positive and significant effect on inflation. These findings are robust and have been corroborated by use of an impulse response function. These results have important implications for inflation-targeting monetary policy, and the aim of stabilization policy in general.

Predicting Output Power for Nearshore Wave Energy Harvesting

Directory of Open Access Journals (Sweden)

Henock Mamo Deberneh

2018-04-01

Full Text Available Energy harvested from a Wave Energy Converter (WEC varies greatly with the location of its installation. Determining an optimal location that can result in maximum output power is therefore critical. In this paper, we present a novel approach to predicting the output power of a nearshore WEC by characterizing ocean waves using floating buoys. We monitored the movement of the buoys using an Arduino-based data collection module, including a gyro-accelerometer sensor and a wireless transceiver. The collected data were utilized to train and test prediction models. The models were developed using machine learning algorithms: SVM, RF and ANN. The results of the experiments showed that measurements from the data collection module can yield a reliable predictor of output power. Furthermore, we found that the predictors work better when the regressors are combined with a classifier. The accuracy of the proposed prediction model suggests that it could be extremely useful in both locating optimal placement for wave energy harvesting plants and designing the shape of the buoys used by them.

The role of ice particles in the microphysics and dynamics of deep convective storms in various latitudes

Science.gov (United States)

Huang, Y. C.; Wang, P. K.

2017-12-01

The role of ice particles in the microphysics and dynamics of deep convective storms in various latitudes Yi-Chih Huang and Pao K. Wang Ice particles contribute to the microphysics and dynamics of severe storms in various regions of the world to a degree that is not commonly recognized. This study is motivated by the need to understand the role of ice particles plays in the development of severe storms so that their impact on various aspects of the storm behavior can be properly assessed. In this study, we perform numerical simulations of thunderstorms using a cloud resolving model WISCDYMM that includes parameterized microphysical processes to understand the role played by ice processes. We simulate thunderstorms occurred over various regions of the world including tropics, substropics and midlatitudes. We then perform statistical analysis of the simulated results to show the formation of various categories of hydrometeors to reveal the importance of ice processes. We will show that ice hydrometeors (cloud ice, snow, graupel/hail) account for 80% of the total hydrometeor mass for the High Plains storms but 50% for the subtropical storms. In addition, the melting of large ice particles (graupel and hail) is the major production process of rain in tropical storms although the ratio of ice-phase mass is responsible for only 40% of the total hydrometeor mass. Furthermore, hydrometeors have their own special microphysical processes in development and depletion over various latitudes. Microphysical structures depend on atmospheric dynamical and thermodynamical conditions which determine the partitioning of hydrometeors. This knowledge would benefit the microphysics parameterization in cloud models and cumulus parameterization in global circulation models.

Nonlinear observer output-feedback MPC treatment scheduling for HIV

Directory of Open Access Journals (Sweden)

Zurakowski Ryan

2011-05-01

Full Text Available Abstract Background Mathematical models of the immune response to the Human Immunodeficiency Virus demonstrate the potential for dynamic schedules of Highly Active Anti-Retroviral Therapy to enhance Cytotoxic Lymphocyte-mediated control of HIV infection. Methods In previous work we have developed a model predictive control (MPC based method for determining optimal treatment interruption schedules for this purpose. In this paper, we introduce a nonlinear observer for the HIV-immune response system and an integrated output-feedback MPC approach for implementing the treatment interruption scheduling algorithm using the easily available viral load measurements. We use Monte-Carlo approaches to test robustness of the algorithm. Results The nonlinear observer shows robust state tracking while preserving state positivity both for continuous and discrete measurements. The integrated output-feedback MPC algorithm stabilizes the desired steady-state. Monte-Carlo testing shows significant robustness to modeling error, with 90% success rates in stabilizing the desired steady-state with 15% variance from nominal on all model parameters. Conclusions The possibility of enhancing immune responsiveness to HIV through dynamic scheduling of treatment is exciting. Output-feedback Model Predictive Control is uniquely well-suited to solutions of these types of problems. The unique constraints of state positivity and very slow sampling are addressable by using a special-purpose nonlinear state estimator, as described in this paper. This shows the possibility of using output-feedback MPC-based algorithms for this purpose.

The assessment of different models to predict solar module temperature, output power and efficiency for Nis, Serbia

International Nuclear Information System (INIS)

Pantic, Lana S.; Pavlović, Tomislav M.; Milosavljević, Dragana D.; Radonjic, Ivana S.; Radovic, Miodrag K.; Sazhko, Galina

2016-01-01

Five different models for calculating solar module temperature, output power and efficiency for sunny days with different solar radiation intensities and ambient temperatures are assessed in this paper. Thereafter, modeled values are compared to the experimentally obtained values for the horizontal solar module in Nis, Serbia. The criterion for determining the best model was based on the statistical analysis and the agreement between the calculated and the experimental values. The calculated values of solar module temperature are in good agreement with the experimentally obtained ones, with some variations over and under the measured values. The best agreement between calculated and experimentally obtained values was for summer months with high solar radiation intensity. The nonlinear model for calculating the output power is much better than the linear model and at the same time predicts better the total electrical energy generated by the solar module during the day. The nonlinear model for calculating the solar module efficiency predicts the efficiency higher than the STC (Standard Test Conditions) value of solar module efficiency for all conditions, while the linear model predicts the solar module efficiency very well. This paper provides a simple and efficient guideline to estimate relevant parameters of a monocrystalline silicon solar module under the moderate-continental climate conditions. - Highlights: • Linear model for solar module temperature gives accurate predictions for August. • The nonlinear model better predicts the solar module power than the linear model. • For calculating solar module power for Nis we propose the nonlinear model. • For calculating solar model efficiency for Nis we propose adoption of linear model. • The adopted models can be used for calculations throughout the year.

Input-output supervisor

International Nuclear Information System (INIS)

Dupuy, R.

1970-01-01

The input-output supervisor is the program which monitors the flow of informations between core storage and peripheral equipments of a computer. This work is composed of three parts: 1 - Study of a generalized input-output supervisor. With sample modifications it looks like most of input-output supervisors which are running now on computers. 2 - Application of this theory on a magnetic drum. 3 - Hardware requirement for time-sharing. (author) [fr

A grey neural network and input-output combined forecasting model. Primary energy consumption forecasts in Spanish economic sectors

International Nuclear Information System (INIS)

Liu, Xiuli; Moreno, Blanca; García, Ana Salomé

2016-01-01

A combined forecast of Grey forecasting method and neural network back propagation model, which is called Grey Neural Network and Input-Output Combined Forecasting Model (GNF-IO model), is proposed. A real case of energy consumption forecast is used to validate the effectiveness of the proposed model. The GNF-IO model predicts coal, crude oil, natural gas, renewable and nuclear primary energy consumption volumes by Spain's 36 sub-sectors from 2010 to 2015 according to three different GDP growth scenarios (optimistic, baseline and pessimistic). Model test shows that the proposed model has higher simulation and forecasting accuracy on energy consumption than Grey models separately and other combination methods. The forecasts indicate that the primary energies as coal, crude oil and natural gas will represent on average the 83.6% percent of the total of primary energy consumption, raising concerns about security of supply and energy cost and adding risk for some industrial production processes. Thus, Spanish industry must speed up its transition to an energy-efficiency economy, achieving a cost reduction and increase in the level of self-supply. - Highlights: • Forecasting System Using Grey Models combined with Input-Output Models is proposed. • Primary energy consumption in Spain is used to validate the model. • The grey-based combined model has good forecasting performance. • Natural gas will represent the majority of the total of primary energy consumption. • Concerns about security of supply, energy cost and industry competitiveness are raised.

Estimation of international output-energy relation. Effects of alternative output measures

International Nuclear Information System (INIS)

Shrestha, R.M.

2000-01-01

This paper analyzes the output-energy relationship with alternative measures of output and energy. Our analysis rejects the hypothesis of non-diminishing returns to energy consumption when GDP at purchasing power parities is used as the output measure unlike the case with GNP at market exchange rates. This finding also holds when energy input includes the usage of both commercial and traditional fuels. 13 refs

Analysis and evaluation of WRF microphysical schemes for deep moist convection over south-eastern South America (SESA) using microwave satellite observations and radiative transfer simulations

Science.gov (United States)

Sol Galligani, Victoria; Wang, Die; Alvarez Imaz, Milagros; Salio, Paola; Prigent, Catherine

2017-10-01

In the present study, three meteorological events of extreme deep moist convection, characteristic of south-eastern South America, are considered to conduct a systematic evaluation of the microphysical parameterizations available in the Weather Research and Forecasting (WRF) model by undertaking a direct comparison between satellite-based simulated and observed microwave radiances. A research radiative transfer model, the Atmospheric Radiative Transfer Simulator (ARTS), is coupled with the WRF model under three different microphysical parameterizations (WSM6, WDM6 and Thompson schemes). Microwave radiometry has shown a promising ability in the characterization of frozen hydrometeors. At high microwave frequencies, however, frozen hydrometeors significantly scatter radiation, and the relationship between radiation and hydrometeor populations becomes very complex. The main difficulty in microwave remote sensing of frozen hydrometeor characterization is correctly characterizing this scattering signal due to the complex and variable nature of the size, composition and shape of frozen hydrometeors. The present study further aims at improving the understanding of frozen hydrometeor optical properties characteristic of deep moist convection events in south-eastern South America. In the present study, bulk optical properties are computed by integrating the single-scattering properties of the Liu(2008) discrete dipole approximation (DDA) single-scattering database across the particle size distributions parameterized by the different WRF schemes in a consistent manner, introducing the equal mass approach. The equal mass approach consists of describing the optical properties of the WRF snow and graupel hydrometeors with the optical properties of habits in the DDA database whose dimensions might be different (Dmax') but whose mass is conserved. The performance of the radiative transfer simulations is evaluated by comparing the simulations with the available coincident

Geochemical modelling of CO2-water-rock interactions for carbon storage : data requirements and outputs

International Nuclear Information System (INIS)

Kirste, D.

2008-01-01

A geochemical model was used to predict the short-term and long-term behaviour of carbon dioxide (CO 2 ), formation water, and reservoir mineralogy at a carbon sequestration site. Data requirements for the geochemical model included detailed mineral petrography; formation water chemistry; thermodynamic and kinetic data for mineral phases; and rock and reservoir physical characteristics. The model was used to determine the types of outputs expected for potential CO 2 storage sites and natural analogues. Reaction path modelling was conducted to determine the total reactivity or CO 2 storage capability of the rock by applying static equilibrium and kinetic simulations. Potential product phases were identified using the modelling technique, which also enabled the identification of the chemical evolution of the system. Results of the modelling study demonstrated that changes in porosity and permeability over time should be considered during the site selection process.

Artificial Neural Networks to Predict the Power Output of a PV Panel

Directory of Open Access Journals (Sweden)

Valerio Lo Brano

2014-01-01

Full Text Available The paper illustrates an adaptive approach based on different topologies of artificial neural networks (ANNs for the power energy output forecasting of photovoltaic (PV modules. The analysis of the PV module’s power output needed detailed local climate data, which was collected by a dedicated weather monitoring system. The Department of Energy, Information Engineering, and Mathematical Models of the University of Palermo (Italy has built up a weather monitoring system that worked together with a data acquisition system. The power output forecast is obtained using three different types of ANNs: a one hidden layer Multilayer perceptron (MLP, a recursive neural network (RNN, and a gamma memory (GM trained with the back propagation. In order to investigate the influence of climate variability on the electricity production, the ANNs were trained using weather data (air temperature, solar irradiance, and wind speed along with historical power output data available for the two test modules. The model validation was performed by comparing model predictions with power output data that were not used for the network's training. The results obtained bear out the suitability of the adopted methodology for the short-term power output forecasting problem and identified the best topology.

ROBUST CONTROL ALGORITHM FOR MULTIVARIABLE PLANTS WITH QUANTIZED OUTPUT

Directory of Open Access Journals (Sweden)

A. A. Margun

2017-01-01

Full Text Available The paper deals with robust output control algorithm for multivariable plants under disturbances. A plant is described by the system of linear differential equations with known relative degrees. Plant parameters are unknown but belong to the known closed bounded set. Plant state vector is unmeasured. Plant output is measured only via static quantizer. Control system algorithm is based on the high gain feedback method. Developed controller provides exponential convergence of tracking error to the bounded area. The area bounds depend on quantizer parameters and the value of external disturbances. Experimental approbation of the proposed control algorithm is performed with the use of Twin Rotor MIMO System laboratory bench. This bench is a helicopter like model with two degrees of freedom (pitch and yaw. DC motors are used as actuators. The output signals are measured via optical encoders. Mathematical model of laboratory bench is obtained. Proposed algorithm was compared with proportional - integral – differential controller in conditions of output quantization. Obtained results have confirmed the efficiency of proposed controller.

Non-fragile observer-based output feedback control for polytopic uncertain system under distributed model predictive control approach

Science.gov (United States)

Zhu, Kaiqun; Song, Yan; Zhang, Sunjie; Zhong, Zhaozhun

2017-07-01

In this paper, a non-fragile observer-based output feedback control problem for the polytopic uncertain system under distributed model predictive control (MPC) approach is discussed. By decomposing the global system into some subsystems, the computation complexity is reduced, so it follows that the online designing time can be saved.Moreover, an observer-based output feedback control algorithm is proposed in the framework of distributed MPC to deal with the difficulties in obtaining the states measurements. In this way, the presented observer-based output-feedback MPC strategy is more flexible and applicable in practice than the traditional state-feedback one. What is more, the non-fragility of the controller has been taken into consideration in favour of increasing the robustness of the polytopic uncertain system. After that, a sufficient stability criterion is presented by using Lyapunov-like functional approach, meanwhile, the corresponding control law and the upper bound of the quadratic cost function are derived by solving an optimisation subject to convex constraints. Finally, some simulation examples are employed to show the effectiveness of the method.

Simulation model structure numerically robust to changes in magnitude and combination of input and output variables

DEFF Research Database (Denmark)

Rasmussen, Bjarne D.; Jakobsen, Arne

1999-01-01

Mathematical models of refrigeration systems are often based on a coupling of component models forming a “closed loop” type of system model. In these models the coupling structure of the component models represents the actual flow path of refrigerant in the system. Very often numerical...... instabilities prevent the practical use of such a system model for more than one input/output combination and for other magnitudes of refrigerating capacities.A higher numerical robustness of system models can be achieved by making a model for the refrigeration cycle the core of the system model and by using...... variables with narrow definition intervals for the exchange of information between the cycle model and the component models.The advantages of the cycle-oriented method are illustrated by an example showing the refrigeration cycle similarities between two very different refrigeration systems....

Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

DEFF Research Database (Denmark)

Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

2006-01-01

A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

The role of updraft velocity in temporal variability of cloud hydrometeor number

Science.gov (United States)

Sullivan, Sylvia; Nenes, Athanasios; Lee, Dong Min; Oreopoulos, Lazaros

2016-04-01

Significant effort has been dedicated to incorporating direct aerosol-cloud links, through parameterization of liquid droplet activation and ice crystal nucleation, within climate models. This significant accomplishment has generated the need for understanding which parameters affecting hydrometer formation drives its variability in coupled climate simulations, as it provides the basis for optimal parameter estimation as well as robust comparison with data, and other models. Sensitivity analysis alone does not address this issue, given that the importance of each parameter for hydrometer formation depends on its variance and sensitivity. To address the above issue, we develop and use a series of attribution metrics defined with adjoint sensitivities to attribute the temporal variability in droplet and crystal number to important aerosol and dynamical parameters. This attribution analysis is done both for the NASA Global Modeling and Assimilation Office Goddard Earth Observing System Model, Version 5 and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1. Within the GEOS simulation, up to 48% of temporal variability in output ice crystal number and 61% in droplet number can be attributed to input updraft velocity fluctuations, while for the CAM simulation, they explain as much as 89% of the ice crystal number variability. This above results suggest that vertical velocity in both model frameworks is seen to be a very important (or dominant) driver of hydrometer variability. Yet, observations of vertical velocity are seldomly available (or used) to evaluate the vertical velocities in simulations; this strikingly contrasts the amount and quality of data available for aerosol-related parameters. Consequentially, there is a strong need for retrievals or measurements of vertical velocity for addressing this important knowledge gap that requires a significant investment and effort by the atmospheric community. The attribution metrics as a

Calculation and decomposition of indirect carbon emissions from residential consumption in China based on the input–output model

International Nuclear Information System (INIS)

Zhu Qin; Peng Xizhe; Wu Kaiya

2012-01-01

Based on the input–output model and the comparable price input–output tables, the current paper investigates the indirect carbon emissions from residential consumption in China in 1992–2005, and examines the impacts on the emissions using the structural decomposition method. The results demonstrate that the rise of the residential consumption level played a dominant role in the growth of residential indirect emissions. The persistent decline of the carbon emission intensity of industrial sectors presented a significant negative effect on the emissions. The change in the intermediate demand of industrial sectors resulted in an overall positive effect, except in the initial years. The increase in population prompted the indirect emissions to a certain extent; however, population size is no longer the main reason for the growth of the emissions. The change in the consumption structure showed a weak positive effect, demonstrating the importance for China to control and slow down the increase in the emissions while in the process of optimizing the residential consumption structure. The results imply that the means for restructuring the economy and improving efficiency, rather than for lowering the consumption scale, should be adopted by China to achieve the targets of energy conservation and emission reduction. - Highlights: ► We build the input–output model of indirect carbon emissions from residential consumption. ► We calculate the indirect emissions using the comparable price input–output tables. ► We examine the impacts on the indirect emissions using the structural decomposition method. ► The change in the consumption structure showed a weak positive effect on the emissions. ► China's population size is no longer the main reason for the growth of the emissions.

Input/Output linearizing control of a nuclear reactor

International Nuclear Information System (INIS)

Perez C, V.

1994-01-01

The feedback linearization technique is an approach to nonlinear control design. The basic idea is to transform, by means of algebraic methods, the dynamics of a nonlinear control system into a full or partial linear system. As a result of this linearization process, the well known basic linear control techniques can be used to obtain some desired dynamic characteristics. When full linearization is achieved, the method is referred to as input-state linearization, whereas when partial linearization is achieved, the method is referred to as input-output linearization. We will deal with the latter. By means of input-output linearization, the dynamics of a nonlinear system can be decomposed into an external part (input-output), and an internal part (unobservable). Since the external part consists of a linear relationship among the output of the plant and the auxiliary control input mentioned above, it is easy to design such an auxiliary control input so that we get the output to behave in a predetermined way. Since the internal dynamics of the system is known, we can check its dynamics behavior on order of to ensure that the internal states are bounded. The linearization method described here can be applied to systems with one-input/one-output, as well as to systems with multiple-inputs/multiple-outputs. Typical control problems such as stabilization and reference path tracking can be solved using this technique. In this work, the input/output linearization theory is presented, as well as the problem of getting the output variable to track some desired trayectories. Further, the design of an input/output control system applied to the nonlinear model of a research nuclear reactor is included, along with the results obtained by computer simulation. (Author)

Gridded Calibration of Ensemble Wind Vector Forecasts Using Ensemble Model Output Statistics

Science.gov (United States)

Lazarus, S. M.; Holman, B. P.; Splitt, M. E.

2017-12-01

A computationally efficient method is developed that performs gridded post processing of ensemble wind vector forecasts. An expansive set of idealized WRF model simulations are generated to provide physically consistent high resolution winds over a coastal domain characterized by an intricate land / water mask. Ensemble model output statistics (EMOS) is used to calibrate the ensemble wind vector forecasts at observation locations. The local EMOS predictive parameters (mean and variance) are then spread throughout the grid utilizing flow-dependent statistical relationships extracted from the downscaled WRF winds. Using data withdrawal and 28 east central Florida stations, the method is applied to one year of 24 h wind forecasts from the Global Ensemble Forecast System (GEFS). Compared to the raw GEFS, the approach improves both the deterministic and probabilistic forecast skill. Analysis of multivariate rank histograms indicate the post processed forecasts are calibrated. Two downscaling case studies are presented, a quiescent easterly flow event and a frontal passage. Strengths and weaknesses of the approach are presented and discussed.

Robust model reference adaptive output feedback tracking for uncertain linear systems with actuator fault based on reinforced dead-zone modification.

Science.gov (United States)

Bagherpoor, H M; Salmasi, Farzad R

2015-07-01

In this paper, robust model reference adaptive tracking controllers are considered for Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) linear systems containing modeling uncertainties, unknown additive disturbances and actuator fault. Two new lemmas are proposed for both SISO and MIMO, under which dead-zone modification rule is improved such that the tracking error for any reference signal tends to zero in such systems. In the conventional approach, adaption of the controller parameters is ceased inside the dead-zone region which results tracking error, while preserving the system stability. In the proposed scheme, control signal is reinforced with an additive term based on tracking error inside the dead-zone which results in full reference tracking. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed approach. Closed loop system stability and zero tracking error are proved by considering a suitable Lyapunov functions candidate. It is shown that the proposed control approach can assure that all the signals of the close loop system are bounded in faulty conditions. Finally, validity and performance of the new schemes have been illustrated through numerical simulations of SISO and MIMO systems in the presence of actuator faults, modeling uncertainty and output disturbance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Hydrological Modeling in Northern Tunisia with Regional Climate Model Outputs: Performance Evaluation and Bias-Correction in Present Climate Conditions

Directory of Open Access Journals (Sweden)

Asma Foughali

2015-07-01

Full Text Available This work aims to evaluate the performance of a hydrological balance model in a watershed located in northern Tunisia (wadi Sejnane, 378 km2 in present climate conditions using input variables provided by four regional climate models. A modified version (MBBH of the lumped and single layer surface model BBH (Bucket with Bottom Hole model, in which pedo-transfer parameters estimated using watershed physiographic characteristics are introduced is adopted to simulate the water balance components. Only two parameters representing respectively the water retention capacity of the soil and the vegetation resistance to evapotranspiration are calibrated using rainfall-runoff data. The evaluation criterions for the MBBH model calibration are: relative bias, mean square error and the ratio of mean actual evapotranspiration to mean potential evapotranspiration. Daily air temperature, rainfall and runoff observations are available from 1960 to 1984. The period 1960–1971 is selected for calibration while the period 1972–1984 is chosen for validation. Air temperature and precipitation series are provided by four regional climate models (DMI, ARP, SMH and ICT from the European program ENSEMBLES, forced by two global climate models (GCM: ECHAM and ARPEGE. The regional climate model outputs (precipitation and air temperature are compared to the observations in terms of statistical distribution. The analysis was performed at the seasonal scale for precipitation. We found out that RCM precipitation must be corrected before being introduced as MBBH inputs. Thus, a non-parametric quantile-quantile bias correction method together with a dry day correction is employed. Finally, simulated runoff generated using corrected precipitation from the regional climate model SMH is found the most acceptable by comparison with runoff simulated using observed precipitation data, to reproduce the temporal variability of mean monthly runoff. The SMH model is the most accurate to

Using High Frequency Passive Microwave, A-train, and TRMM Data to Evaluate Hydrometer Structure in the NASA GEOS-5 Data Assimilation System

Science.gov (United States)

Robertson, Franklin; Bacmeister, Julio; Bosilovich, Michael; Pittman, Jasna

2007-01-01

Validating water vapor and prognostic condensate in global models remains a challenging research task. Model parameterizations are still subject to a large number of tunable parameters; furthermore, accurate and representative in situ observations are very sparse, and satellite observations historically have significant quantitative uncertainties. Progress on improving cloud / hydrometeor fields in models stands to benefit greatly from the growing inventory ofA-Train data sets. ill the present study we are using a variety of complementary satellite retrievals of hydrometeors to examine condensate produced by the emerging NASA Modem Era Retrospective Analysis for Research and Applications, MERRA, and its associated atmospheric general circulation model GEOS5. Cloud and precipitation are generated by both grid-scale prognostic equations and by the Relaxed Arakawa-Schubert (RAS) diagnostic convective parameterization. The high frequency channels (89 to 183.3 GHz) from AMSU-B and MRS on NOAA polar orbiting satellites are being used to evaluate the climatology and variability of precipitating ice from tropical convective anvils. Vertical hydrometeor structure from the Tropical Rainfall Measuring Mission (TRMM) and CloudSat radars are used to develop statistics on vertical hydrometeor structure in order to better interpret the extensive high frequency passive microwave climatology. Cloud liquid and ice water path data retrieved from the Moderate Resolution Imaging Spectroradiometer, MODIS, are used to investigate relationships between upper level cloudiness and tropical deep convective anvils. Together these data are used to evaluate cloud / ice water path, gross aspects of vertical hydrometeor structure, and the relationship between cloud extent and surface precipitation that the MERRA reanalysis must capture.

Output Error Method for Tiltrotor Unstable in Hover

Directory of Open Access Journals (Sweden)

Lichota Piotr

2017-03-01

Full Text Available This article investigates unstable tiltrotor in hover system identification from flight test data. The aircraft dynamics was described by a linear model defined in Body-Fixed-Coordinate System. Output Error Method was selected in order to obtain stability and control derivatives in lateral motion. For estimating model parameters both time and frequency domain formulations were applied. To improve the system identification performed in the time domain, a stabilization matrix was included for evaluating the states. In the end, estimates obtained from various Output Error Method formulations were compared in terms of parameters accuracy and time histories. Evaluations were performed in MATLAB R2009b environment.

Auxetic piezoelectric energy harvesters for increased electric power output

Directory of Open Access Journals (Sweden)

Qiang Li

2017-01-01

Full Text Available This letter presents a piezoelectric bimorph with auxetic (negative Poisson’s ratio behaviors for increased power output in vibration energy harvesting. The piezoelectric bimorph comprises a 2D auxetic substrate sandwiched between two piezoelectric layers. The auxetic substrate is capable of introducing auxetic behaviors and thus increasing the transverse stress in the piezoelectric layers when the bimorph is subjected to a longitudinal stretching load. As a result, both 31- and 32-modes are simultaneously exploited to generate electric power, leading to an increased power output. The increasing power output principle was theoretically analyzed and verified by finite element (FE modelling. The FE modelling results showed that the auxetic substrate can increase the transverse stress of a bimorph by 16.7 times. The average power generated by the auxetic bimorph is 2.76 times of that generated by a conventional bimorph.

Sensitivity analysis of model output - a step towards robust safety indicators?

International Nuclear Information System (INIS)

Broed, R.; Pereira, A.; Moberg, L.

2004-01-01

The protection of the environment from ionising radiation challenges the radioecological community with the issue of harmonising disparate safety indicators. These indicators should preferably cover the whole spectrum of model predictions on chemo-toxic and radiation impact of contaminants. In question is not only the protection of man and biota but also of abiotic systems. In many cases modelling will constitute the basis for an evaluation of potential impact. It is recognised that uncertainty and sensitivity analysis of model output will play an important role in the 'construction' of safety indicators that are robust, reliable and easy to explain to all groups of stakeholders including the general public. However, environmental models of transport of radionuclides have some extreme characteristics. They are, a) complex, b) non-linear, c) include a huge number of input parameters, d) input parameters are associated with large or very large uncertainties, e) parameters are often correlated to each other, f) uncertainties other than parameter-driven may be present in the modelling system, g) space variability and time-dependence of parameters are present, h) model predictions may cover geological time scales. Consequently, uncertainty and sensitivity analysis are non-trivial tasks, challenging the decision-maker when it comes to the interpretation of safety indicators or the application of regulatory criteria. In this work we use the IAEA model ISAM, to make a set of Monte Carlo calculations. The ISAM model includes several nuclides and decay chains, many compartments and variable parameters covering the range of nuclide migration pathways from the near field to the biosphere. The goal of our calculations is to make a global sensitivity analysis. After extracting the non-influential parameters, the M.C. calculations are repeated with those parameters frozen. Reducing the number of parameters to a few ones will simplify the interpretation of the results and the use

Output hardcopy devices

CERN Document Server

Durbeck, Robert

1988-01-01

Output Hardcopy Devices provides a technical summary of computer output hardcopy devices such as plotters, computer output printers, and CRT generated hardcopy. Important related technical areas such as papers, ribbons and inks, color techniques, controllers, and character fonts are also covered. Emphasis is on techniques primarily associated with printing, as well as the plotting capabilities of printing devices that can be effectively used for computer graphics in addition to their various printing functions. Comprised of 19 chapters, this volume begins with an introduction to vector and ras

Forecasting the Romanian sectoral economy using the input-output method

Directory of Open Access Journals (Sweden)

Liliana DUGULEANĂ

2017-07-01

Full Text Available The purpose of this paper is to forecast the sectoral output in 2013 based on the input-output structure of Romanian economy in 2010. Considering that the economic linkage mechanisms do not easily change during certain time periods, the forecasting is possible, even if not in the sequence of the time passing. Using the technical matrix of the sectoral structure described for year 2010 and some known indicators of the economic sectors, as the value added for each sector in 2013, the sectoral output is projected for 2013. The Romanian GDP in 2013 is estimated based on the input-output model. From a managerial perspective, this study is useful to forecast the sectoral output and to understand the sectoral behaviour, based on the input-output analysis of the value added, the compensation for employees and the final demand, which were considered here.

An Optimized Grey Dynamic Model for Forecasting the Output of High-Tech Industry in China

Directory of Open Access Journals (Sweden)

Zheng-Xin Wang

2014-01-01

Full Text Available The grey dynamic model by convolution integral with the first-order derivative of the 1-AGO data and n series related, abbreviated as GDMC(1,n, performs well in modelling and forecasting of a grey system. To improve the modelling accuracy of GDMC(1,n, n interpolation coefficients (taken as unknown parameters are introduced into the background values of the n variables. The parameters optimization is formulated as a combinatorial optimization problem and is solved collectively using the particle swarm optimization algorithm. The optimized result has been verified by a case study of the economic output of high-tech industry in China. Comparisons of the obtained modelling results from the optimized GDMC(1,n model with the traditional one demonstrate that the optimal algorithm is a good alternative for parameters optimization of the GDMC(1,n model. The modelling results can assist the government in developing future policies regarding high-tech industry management.

Brief communication: On the influence of vertical wind shear on the combined power output of two model wind turbines in yaw

Directory of Open Access Journals (Sweden)

J. Schottler

2017-08-01

Full Text Available The effect of vertical wind shear on the total power output of two aligned model wind turbines as a function of yaw misalignment of the upstream turbine is studied experimentally. It is shown that asymmetries of the power output of the downstream turbine and the combined power of both with respect to the upstream turbine's yaw misalignment angle can be linked to the vertical wind shear of the inflow.

A model and variance reduction method for computing statistical outputs of stochastic elliptic partial differential equations

International Nuclear Information System (INIS)

Vidal-Codina, F.; Nguyen, N.C.; Giles, M.B.; Peraire, J.

2015-01-01

We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basis approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method

Market power and output-based refunding of environmental policy revenues

International Nuclear Information System (INIS)

Fischer, Carolyn

2011-01-01

Output-based refunding of environmental policy revenues combines a tax on emissions with a production subsidy, typically in a revenue-neutral fashion. With imperfect competition, subsidies can alleviate output underprovision. However, when market shares are significant, endogenous refunding reduces abatement incentives and the marginal net tax or subsidy. If market shares differ, marginal abatement costs will not be equalized, and production is shifted among participants. In an asymmetric Cournot duopoly, endogenous refunding leads to higher output, emissions, and overall costs compared with a fixed rebate program targeting the same emissions intensity. These results hold whether emissions rates are determined simultaneously with output or strategically in a two-stage model. (author)

Global sensitivity analysis for fuzzy inputs based on the decomposition of fuzzy output entropy

Science.gov (United States)

Shi, Yan; Lu, Zhenzhou; Zhou, Yicheng

2018-06-01

To analyse the component of fuzzy output entropy, a decomposition method of fuzzy output entropy is first presented. After the decomposition of fuzzy output entropy, the total fuzzy output entropy can be expressed as the sum of the component fuzzy entropy contributed by fuzzy inputs. Based on the decomposition of fuzzy output entropy, a new global sensitivity analysis model is established for measuring the effects of uncertainties of fuzzy inputs on the output. The global sensitivity analysis model can not only tell the importance of fuzzy inputs but also simultaneously reflect the structural composition of the response function to a certain degree. Several examples illustrate the validity of the proposed global sensitivity analysis, which is a significant reference in engineering design and optimization of structural systems.

INPUT-OUTPUT STRUCTURE OF LINEAR-DIFFERENTIAL ALGEBRAIC SYSTEMS

NARCIS (Netherlands)

KUIJPER, M; SCHUMACHER, JM

Systems of linear differential and algebraic equations occur in various ways, for instance, as a result of automated modeling procedures and in problems involving algebraic constraints, such as zero dynamics and exact model matching. Differential/algebraic systems may represent an input-output

CO2 emissions, energy usage, and output in Central America

International Nuclear Information System (INIS)

Apergis, Nicholas; Payne, James E.

2009-01-01

This study extends the recent work of Ang (2007) [Ang, J.B., 2007. CO 2 emissions, energy consumption, and output in France. Energy Policy 35, 4772-4778] in examining the causal relationship between carbon dioxide emissions, energy consumption, and output within a panel vector error correction model for six Central American countries over the period 1971-2004. In long-run equilibrium energy consumption has a positive and statistically significant impact on emissions while real output exhibits the inverted U-shape pattern associated with the Environmental Kuznets Curve (EKC) hypothesis. The short-run dynamics indicate unidirectional causality from energy consumption and real output, respectively, to emissions along with bidirectional causality between energy consumption and real output. In the long-run there appears to be bidirectional causality between energy consumption and emissions.

Linearised model for PV panel power output variation with changes ...

Indian Academy of Sciences (India)

PALLAVI BHARADWAJ

2017-10-26

Oct 26, 2017 ... change in system input, namely: irradiance and temperature, with its output, namely: array current and power. ... of a solar cell as shown in figure 1, with appropriate scaling according to ... measurement-based methods [8–13].

Influence of deleting some of the inputs and outputs on efficiency status of units in DEA

Directory of Open Access Journals (Sweden)

Abbas ali Noora

2013-06-01

Full Text Available One of the important issues in data envelopment analysis (DEA is sensitivity analysis. This study discusses about deleting some of the inputs and outputs and investigates the influence of it on efficiency status of Decision Making Units (DMUs. To this end some models are presented for recognizing this influence on efficient DMUs. Model 2 (Model 3 in section 3 investigates the influence of deleting i(th input (r(th output on an efficient DMU. Thereafter these models are improved for deleting multiple inputs and outputs. Furthermore, a model is presented for recognizing the maximum number of inputs and (or outputs from among specified inputs and outputs which can be deleted, whereas an efficient DMU preserves its efficiency. Finally, the presented models are utilized for a set of DMUs and the results are reported.

From Static Output Feedback to Structured Robust Static Output Feedback: A Survey

OpenAIRE

Sadabadi , Mahdieh ,; Peaucelle , Dimitri

2016-01-01

This paper reviews the vast literature on static output feedback design for linear time-invariant systems including classical results and recent developments. In particular, we focus on static output feedback synthesis with performance specifications, structured static output feedback, and robustness. The paper provides a comprehensive review on existing design approaches including iterative linear matrix inequalities heuristics, linear matrix inequalities with rank constraints, methods with ...

Global Sensitivity Analysis for multivariate output using Polynomial Chaos Expansion

International Nuclear Information System (INIS)

Garcia-Cabrejo, Oscar; Valocchi, Albert

2014-01-01

Many mathematical and computational models used in engineering produce multivariate output that shows some degree of correlation. However, conventional approaches to Global Sensitivity Analysis (GSA) assume that the output variable is scalar. These approaches are applied on each output variable leading to a large number of sensitivity indices that shows a high degree of redundancy making the interpretation of the results difficult. Two approaches have been proposed for GSA in the case of multivariate output: output decomposition approach [9] and covariance decomposition approach [14] but they are computationally intensive for most practical problems. In this paper, Polynomial Chaos Expansion (PCE) is used for an efficient GSA with multivariate output. The results indicate that PCE allows efficient estimation of the covariance matrix and GSA on the coefficients in the approach defined by Campbell et al. [9], and the development of analytical expressions for the multivariate sensitivity indices defined by Gamboa et al. [14]. - Highlights: • PCE increases computational efficiency in 2 approaches of GSA of multivariate output. • Efficient estimation of covariance matrix of output from coefficients of PCE. • Efficient GSA on coefficients of orthogonal decomposition of the output using PCE. • Analytical expressions of multivariate sensitivity indices from coefficients of PCE

Coordination between Understanding Historic Buildings and BIM Modelling: A 3D-Output Oriented and typological Data Capture Method

Directory of Open Access Journals (Sweden)

K. Li

2015-08-01

Full Text Available At the present, in trend of shifting the old 2D-output oriented survey to a new 3D-output oriented survey based on BIM technology, the corresponding working methods and workflow for data capture, process, representation, etc. have to be changed.Based on case study of two buildings in the Summer Palace of Beijing, and Jiayuguan Pass at the west end of the Great Wall (both World Heritage sites, this paper puts forward a “structure-and-type method” by means of typological method used in archaeology, Revit family system, and the tectonic logic of building to realize a good coordination between understanding of historic buildings and BIM modelling.

Forecasting the daily power output of a grid-connected photovoltaic system based on multivariate adaptive regression splines

International Nuclear Information System (INIS)

Li, Yanting; He, Yong; Su, Yan; Shu, Lianjie

2016-01-01

Highlights: • Suggests a nonparametric model based on MARS for output power prediction. • Compare the MARS model with a wide variety of prediction models. • Show that the MARS model is able to provide an overall good performance in both the training and testing stages. - Abstract: Both linear and nonlinear models have been proposed for forecasting the power output of photovoltaic systems. Linear models are simple to implement but less flexible. Due to the stochastic nature of the power output of PV systems, nonlinear models tend to provide better forecast than linear models. Motivated by this, this paper suggests a fairly simple nonlinear regression model known as multivariate adaptive regression splines (MARS), as an alternative to forecasting of solar power output. The MARS model is a data-driven modeling approach without any assumption about the relationship between the power output and predictors. It maintains simplicity of the classical multiple linear regression (MLR) model while possessing the capability of handling nonlinearity. It is simpler in format than other nonlinear models such as ANN, k-nearest neighbors (KNN), classification and regression tree (CART), and support vector machine (SVM). The MARS model was applied on the daily output of a grid-connected 2.1 kW PV system to provide the 1-day-ahead mean daily forecast of the power output. The comparisons with a wide variety of forecast models show that the MARS model is able to provide reliable forecast performance.

The inflation-output nexus:empirical evidence from India, Brazil and South Africa

OpenAIRE

Paresh Kumar Narayan; Seema Narayan

2011-01-01

In this paper we study the relationship between output and inflation for India, Brazil, and South Africa using the EGARCH model. For India and South Africa, we find evidence for: (1) the Cukierman and Meltzer hypothesis that inflation volatility raises inflation; (2) the Friedman hypothesis that inflation raises inflation volatility; and (3) the Black hypothesis that output volatility raises output growth, and that output volatility reduces inflation. For Brazil, we do not find any evidence o...

Impacts of manure application on SWAT model outputs in the Xiangxi River watershed

Science.gov (United States)

Liu, Ruimin; Wang, Qingrui; Xu, Fei; Men, Cong; Guo, Lijia

2017-12-01

SWAT (Soil and Water Assessment Tool) model has been widely used to simulate agricultural non-point source (ANPS) pollution; however, the impacts of livestock manure application on SWAT model outputs have not been well studied. The objective of this study was to investigate the environmental effects of livestock manure application based on the SWAT model in the Xiangxi River watershed, which is one of the largest tributaries of the Three Gorges Reservoir in China. Three newly-built manure databases (NB) were created and applied to different subbasins based on the actual livestock manure discharging amount. The calibration and validation values of SWAT model outputs obtained from the NB manure application and the original mixed (OM) manure were compared. The study results are as follows: (1) The livestock industry of Xingshan County developed quickly between 2005 and 2015. The downstream of the Xiangxi River (Huangliang, Shuiyuesi and Xiakou) had the largest livestock amount, and largely accounted for manure, total nitrogen (TN) and total phosphorus (TP) production (>50%). (2) The NB manure application resulted in less phosphorus pollution (1686.35 kg for ORGP and 31.70 kg for MINP) than the OM manure application. Compared with the upstream, the downstream was influenced more by the manure application. (3) The SWAT results obtained from the NB manure had a better calibration and validation values than those from the OM manure. For ORGP, R2 and NSE values were 0.77 and 0.65 for the NB manure calibration; and the same values for the OM manure were 0.72 and 0.61, respectively. For MINP, R2 values were 0.65 and 0.62 for the NB manure and the OM manure, and the NSE values were 0.60 and 0.58, respectively. The results indicated that the built-in fertilizer database in SWAT has its limitation because it is set up for the simulation in the USA. Thus, when livestock manure is considered in a SWAT simulation, a newly built fertilizer database needs to be set up to represent

A neural network based computational model to predict the output power of different types of photovoltaic cells.

Science.gov (United States)

Xiao, WenBo; Nazario, Gina; Wu, HuaMing; Zhang, HuaMing; Cheng, Feng

2017-01-01

In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.

A neural network based computational model to predict the output power of different types of photovoltaic cells.

Directory of Open Access Journals (Sweden)

WenBo Xiao

Full Text Available In this article, we introduced an artificial neural network (ANN based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-, multi-crystalline (multi-, and amorphous (amor- crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.

Robust MPC with Output Feedback of Integrating Systems

Directory of Open Access Journals (Sweden)

J. M. Perez

2012-01-01

Full Text Available In this work, it is presented a new contribution to the design of a robust MPC with output feedback, input constraints, and uncertain model. Multivariable predictive controllers have been used in industry to reduce the variability of the process output and to allow the operation of the system near to the constraints, where it is usually located the optimum operating point. For this reason, new controllers have been developed with the objective of achieving better performance, simpler control structure, and robustness with respect to model uncertainty. In this work, it is proposed a model predictive controller based on a nonminimal state space model where the state is perfectly known. It is an infinite prediction horizon controller, and it is assumed that there is uncertainty in the stable part of the model, which may also include integrating modes that are frequently present in the process plants. The method is illustrated with a simulation example of the process industry using linear models based on a real process.

Can High-resolution WRF Simulations Be Used for Short-term Forecasting of Lightning?

Science.gov (United States)

Goodman, S. J.; Lapenta, W.; McCaul, E. W., Jr.; LaCasse, K.; Petersen, W.

2006-01-01

A number of research teams have begun to make quasi-operational forecast simulations at high resolution with models such as the Weather Research and Forecast (WRF) model. These model runs have used horizontal meshes of 2-4 km grid spacing, and thus resolved convective storms explicitly. In the light of recent global satellite-based observational studies that reveal robust relationships between total lightning flash rates and integrated amounts of precipitation-size ice hydrometeors in storms, it is natural to inquire about the capabilities of these convection-resolving models in representing the ice hydrometeor fields faithfully. If they do, this might make operational short-term forecasts of lightning activity feasible. We examine high-resolution WRF simulations from several Southeastern cases for which either NLDN or LMA lightning data were available. All the WRF runs use a standard microphysics package that depicts only three ice species, cloud ice, snow and graupel. The realism of the WRF simulations is examined by comparisons with both lightning and radar observations and with additional even higher-resolution cloud-resolving model runs. Preliminary findings are encouraging in that they suggest that WRF often makes convective storms of the proper size in approximately the right location, but they also indicate that higher resolution and better hydrometeor microphysics would be helpful in improving the realism of the updraft strengths, reflectivity and ice hydrometeor fields.

WATER TEMPERATURE, SALINITY, and currents speed from 2011-04-01 to 2013-07-30 from model output (NCEI Accession 0166079)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data contains output of a regional implementation of the Massachusetts Institute of Technology general circulation model (MITgcm) at a 1-km spatial resolution...

WATER TEMPERATURE, SALINITY, and currents speed from 2011-04-01 to 2013-07-30 from model output (NCEI Accession 0131071)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data contains output of a regional implementation of the Massachusetts Institute of Technology general circulation model (MITgcm) at a 1-km spatial resolution...

Output Feedback M-MRAC Backstepping With Aerospace Applications

Science.gov (United States)

Stepanyan, Vahram; Krishnakumar, Kalmanje Sriniva

2014-01-01

The paper presents a certainty equivalence output feedback backstepping adaptive control design method for the systems of any relative degree with unmatched uncertainties without over-parametrization. It uses a fast prediction model to estimate the unknown parameters, which is independent of the control design. It is shown that the system's input and output tracking errors can be systematically decreased by the proper choice of the design parameters. The approach is applied to aerospace control problems and tested in numerical simulations.

Design and Output Performance Model of Turbodrill Blade Used in a Slim Borehole

Directory of Open Access Journals (Sweden)

Yu Wang

2016-12-01

Full Text Available Small-diameter turbodrills have great potential for use in slim boreholes because of their lower cost and higher efficiency when used in geothermal energy and other underground resource applications. Multistage hydraulic components consisting of stators and rotors are key aspects of turbodrills. This study aimed to develop a suitable blade that can be used under high temperature in granite formations. First, prediction models for single- and multi-stage blades were established based on Bernoulli’s Equation. The design requirement of the blade for high-temperature geothermal drilling in granite was proposed. A Φ89 blade was developed based on the dimensionless parameter method and Bezier curve; the parameters of the blade, including its radial size, symotric parameters, and blade profiles, were input into ANASYS and CFX to establish a calculation model of the single-stage blade. The optimization of the blade structure of the small-diameter turbodrill enabled a multistage turbodrill model to be established and the turbodrill’s overall output performance to be predicted. The results demonstrate that the design can meet the turbodrill’s performance requirements and that the multistage model can effectively improve the accuracy of the prediction.

Modeling of Turbine Cycles Using a Neuro-Fuzzy Based Approach to Predict Turbine-Generator Output for Nuclear Power Plants

Directory of Open Access Journals (Sweden)

Yea-Kuang Chan

2012-01-01

Full Text Available Due to the very complex sets of component systems, interrelated thermodynamic processes and seasonal change in operating conditions, it is relatively difficult to find an accurate model for turbine cycle of nuclear power plants (NPPs. This paper deals with the modeling of turbine cycles to predict turbine-generator output using an adaptive neuro-fuzzy inference system (ANFIS for Unit 1 of the Kuosheng NPP in Taiwan. Plant operation data obtained from Kuosheng NPP between 2006 and 2011 were verified using a linear regression model with a 95% confidence interval. The key parameters of turbine cycle, including turbine throttle pressure, condenser backpressure, feedwater flow rate and final feedwater temperature are selected as inputs for the ANFIS based turbine cycle model. In addition, a thermodynamic turbine cycle model was developed using the commercial software PEPSE® to compare the performance of the ANFIS based turbine cycle model. The results show that the proposed ANFIS based turbine cycle model is capable of accurately estimating turbine-generator output and providing more reliable results than the PEPSE® based turbine cycle models. Moreover, test results show that the ANFIS performed better than the artificial neural network (ANN, which has also being tried to model the turbine cycle. The effectiveness of the proposed neuro-fuzzy based turbine cycle model was demonstrated using the actual operating data of Kuosheng NPP. Furthermore, the results also provide an alternative approach to evaluate the thermal performance of nuclear power plants.

Current and future groundwater recharge in West Africa as estimated from a range of coupled climate model outputs

Science.gov (United States)

Verhoef, Anne; Cook, Peter; Black, Emily; Macdonald, David; Sorensen, James

2017-04-01

This research addresses the terrestrial water balance for West Africa. Emphasis is on the prediction of groundwater recharge and how this may change in the future, which has relevance to the management of surface and groundwater resources. The study was conducted as part of the BRAVE research project, "Building understanding of climate variability into planning of groundwater supplies from low storage aquifers in Africa - Second Phase", funded under the NERC/DFID/ESRC Programme, Unlocking the Potential of Groundwater for the Poor (UPGro). We used model output data of water balance components (precipitation, surface and subsurface run-off, evapotranspiration and soil moisture content) from ERA-Interim/ERA-LAND reanalysis, CMIP5, and high resolution model runs with HadGEM3 (UPSCALE; Mizielinski et al., 2014), for current and future time-periods. Water balance components varied widely between the different models; variation was particularly large for sub-surface runoff (defined as drainage from the bottom-most soil layer of each model). In-situ data for groundwater recharge obtained from the peer-reviewed literature were compared with the model outputs. Separate off-line model sensitivity studies with key land surface models were performed to gain understanding of the reasons behind the model differences. These analyses were centered on vegetation, and soil hydraulic parameters. The modelled current and future recharge time series that had the greatest degree of confidence were used to examine the spatiotemporal variability in groundwater storage. Finally, the implications for water supply planning were assessed. Mizielinski, M.S. et al., 2014. High-resolution global climate modelling: the UPSCALE project, a large-simulation campaign. Geoscientific Model Development, 7(4), pp.1629-1640.

The value of risk: measuring the service output of U.S. commercial banks

OpenAIRE

Basu, Susanto; Inklaar, Robert; Wang, J. Christina

2011-01-01

Rather than charging direct fees, banks often charge implicitly for their services via interest spreads. As a result, much of bank output has to be estimated indirectly. In contrast to current statistical practice, dynamic optimizing models of banks argue that compensation for bearing systematic risk is not part of bank output. We apply these models and find that between 1997 and 2007, in the U.S. National Accounts, on average, bank output is overestimated by 21 percent and GDP is overestimat...

GDP Growth, Potential Output, and Output Gaps in Mexico

OpenAIRE

Ebrima A Faal

2005-01-01

This paper analyzes the sources of Mexico's economic growth since the 1960s and compares various decompositions of historical growth into its trend and cyclical components. The role of the implied output gaps in the inflationary process is then assessed. Looking ahead, the paper presents medium-term paths for GDP based on alternative assumptions for productivity growth rates. The results indicate that the most important factor underlying the slowdown in output growth was a decline in trend to...

Transiently chaotic neural networks with piecewise linear output functions

Energy Technology Data Exchange (ETDEWEB)

Chen, S.-S. [Department of Mathematics, National Taiwan Normal University, Taipei, Taiwan (China); Shih, C.-W. [Department of Applied Mathematics, National Chiao Tung University, 1001 Ta-Hsueh Road, Hsinchu, Taiwan (China)], E-mail: cwshih@math.nctu.edu.tw

2009-01-30

Admitting both transient chaotic phase and convergent phase, the transiently chaotic neural network (TCNN) provides superior performance than the classical networks in solving combinatorial optimization problems. We derive concrete parameter conditions for these two essential dynamic phases of the TCNN with piecewise linear output function. The confirmation for chaotic dynamics of the system results from a successful application of the Marotto theorem which was recently clarified. Numerical simulation on applying the TCNN with piecewise linear output function is carried out to find the optimal solution of a travelling salesman problem. It is demonstrated that the performance is even better than the previous TCNN model with logistic output function.

Modelling Implicit Communication in Multi-Agent Systems with Hybrid Input/Output Automata

Directory of Open Access Journals (Sweden)

Marta Capiluppi

2012-10-01

Full Text Available We propose an extension of Hybrid I/O Automata (HIOAs to model agent systems and their implicit communication through perturbation of the environment, like localization of objects or radio signals diffusion and detection. To this end we decided to specialize some variables of the HIOAs whose values are functions both of time and space. We call them world variables. Basically they are treated similarly to the other variables of HIOAs, but they have the function of representing the interaction of each automaton with the surrounding environment, hence they can be output, input or internal variables. Since these special variables have the role of simulating implicit communication, their dynamics are specified both in time and space, because they model the perturbations induced by the agent to the environment, and the perturbations of the environment as perceived by the agent. Parallel composition of world variables is slightly different from parallel composition of the other variables, since their signals are summed. The theory is illustrated through a simple example of agents systems.

The output characteristic of cantilever-like tactile sensor based on the inverse magnetostrictive effect

Directory of Open Access Journals (Sweden)

Lili Wan

2017-05-01

Full Text Available The output characteristic model of a magnetostrictive cantilever-like tactile sensor has been founded based on the inverse-magnetostrictive effect, the flexure mode, and the Jiles-Atherton model. The magnetostrictive sensor has been designed and an output voltage is analyzed under the conditions of bias magnetic field, contact pressure and deflection of cantilever beam. The experiment has been performed to determine the relation among the induced output voltage, bias magnetic field, and pressure. It is found that the peak of the induced output voltage increases with an increasing pressure under the bias magnetic field of 4.8kA/m. The experimental result agrees well with the theoretical one and it means that the model can describe the relation among the induced output voltage, bias magnetic field, and pressure. The sensor with a Galfenol sheet may hold potentials in sample characterization and deformation predication in artificial intelligence area.

Linear and Non-linear Multi-Input Multi-Output Model Predictive Control of Continuous Stirred Tank Reactor

Directory of Open Access Journals (Sweden)

Muayad Al-Qaisy

2015-02-01

Full Text Available In this article, multi-input multi-output (MIMO linear model predictive controller (LMPC based on state space model and nonlinear model predictive controller based on neural network (NNMPC are applied on a continuous stirred tank reactor (CSTR. The idea is to have a good control system that will be able to give optimal performance, reject high load disturbance, and track set point change. In order to study the performance of the two model predictive controllers, MIMO Proportional-Integral-Derivative controller (PID strategy is used as benchmark. The LMPC, NNMPC, and PID strategies are used for controlling the residual concentration (CA and reactor temperature (T. NNMPC control shows a superior performance over the LMPC and PID controllers by presenting a smaller overshoot and shorter settling time.

Statistics-based optimization of the polarimetric radar hydrometeor classification algorithm and its application for a squall line in South China

Science.gov (United States)

Wu, Chong; Liu, Liping; Wei, Ming; Xi, Baozhu; Yu, Minghui

2018-03-01

A modified hydrometeor classification algorithm (HCA) is developed in this study for Chinese polarimetric radars. This algorithm is based on the U.S. operational HCA. Meanwhile, the methodology of statistics-based optimization is proposed including calibration checking, datasets selection, membership functions modification, computation thresholds modification, and effect verification. Zhuhai radar, the first operational polarimetric radar in South China, applies these procedures. The systematic bias of calibration is corrected, the reliability of radar measurements deteriorates when the signal-to-noise ratio is low, and correlation coefficient within the melting layer is usually lower than that of the U.S. WSR-88D radar. Through modification based on statistical analysis of polarimetric variables, the localized HCA especially for Zhuhai is obtained, and it performs well over a one-month test through comparison with sounding and surface observations. The algorithm is then utilized for analysis of a squall line process on 11 May 2014 and is found to provide reasonable details with respect to horizontal and vertical structures, and the HCA results—especially in the mixed rain-hail region—can reflect the life cycle of the squall line. In addition, the kinematic and microphysical processes of cloud evolution and the differences between radar-detected hail and surface observations are also analyzed. The results of this study provide evidence for the improvement of this HCA developed specifically for China.

Energy efficiency of selected OECD countries: A slacks based model with undesirable outputs

International Nuclear Information System (INIS)

Apergis, Nicholas; Aye, Goodness C.; Barros, Carlos Pestana; Gupta, Rangan; Wanke, Peter

2015-01-01

This paper presents an efficiency assessment of selected OECD countries using a Slacks Based Model with undesirable or bad outputs (SBM-Undesirable). In this research, SBM-Undesirable is used first in a two-stage approach to assess the relative efficiency of OECD countries using the most frequent indicators adopted by the literature on energy efficiency. Besides, in the second stage, GLMM–MCMC methods are combined with SBM-Undesirable results as part of an attempt to produce a model for energy performance with effective predictive ability. The results reveal different impacts of contextual variables, such as economic blocks and capital–labor ratio, on energy efficiency levels. - Highlights: • We analyze the energy efficiency of selected OECD countries. • SBM-Undesirable and MCMC–GLMM are combined for this purpose. • Find that efficiency levels are high but declining over time. • Analysis with contextual variables shows varying efficiency levels across groups. • Capital-intensive countries are more energy efficient than labor-intensive countries.

Improvement of a mesoscale atmospheric dynamic model PHYSIC. Utilization of output from synoptic numerical prediction model for initial and boundary condition

International Nuclear Information System (INIS)

Nagai, Haruyasu; Yamazawa, Hiromi

1995-03-01

This report describes the improvement of the mesoscale atmospheric dynamic model which is a part of the atmospheric dispersion calculation model PHYSIC. To introduce large-scale meteorological changes into the mesoscale atmospheric dynamic model, it is necessary to make the initial and boundary conditions of the model by using GPV (Grid Point Value) which is the output of the numerical weather prediction model of JMA (Japan Meteorological Agency). Therefore, the program which preprocesses the GPV data to make a input file to PHYSIC was developed and the input process and the methods of spatial and temporal interpolation were improved to correspond to the file. Moreover, the methods of calculating the cloud amount and ground surface moisture from GPV data were developed and added to the model code. As the example of calculation by the improved model, the wind field simulations of a north-west monsoon in winter and a sea breeze in summer in the Tokai area were also presented. (author)

Aggregate Supply and Potential Output

OpenAIRE

Razin, Assaf

2004-01-01

The New-Keynesian aggregate supply derives from micro-foundations an inflation-dynamics model very much like the tradition in the monetary literature. Inflation is primarily affected by: (i) economic slack; (ii) expectations; (iii) supply shocks; and (iv) inflation persistence. This paper extends the New Keynesian aggregate supply relationship to include also fluctuations in potential output, as an additional determinant of the relationship. Implications for monetary rules and to the estimati...

Industrial and ecological cumulative exergy consumption of the United States via the 1997 input-output benchmark model

International Nuclear Information System (INIS)

Ukidwe, Nandan U.; Bakshi, Bhavik R.

2007-01-01

This paper develops a thermodynamic input-output (TIO) model of the 1997 United States economy that accounts for the flow of cumulative exergy in the 488-sector benchmark economic input-output model in two different ways. Industrial cumulative exergy consumption (ICEC) captures the exergy of all natural resources consumed directly and indirectly by each economic sector, while ecological cumulative exergy consumption (ECEC) also accounts for the exergy consumed in ecological systems for producing each natural resource. Information about exergy consumed in nature is obtained from the thermodynamics of biogeochemical cycles. As used in this work, ECEC is analogous to the concept of emergy, but does not rely on any of its controversial claims. The TIO model can also account for emissions from each sector and their impact and the role of labor. The use of consistent exergetic units permits the combination of various streams to define aggregate metrics that may provide insight into aspects related to the impact of economic sectors on the environment. Accounting for the contribution of natural capital by ECEC has been claimed to permit better representation of the quality of ecosystem goods and services than ICEC. The results of this work are expected to permit evaluation of these claims. If validated, this work is expected to lay the foundation for thermodynamic life cycle assessment, particularly of emerging technologies and with limited information

CO{sub 2} emissions, energy usage, and output in Central America

Energy Technology Data Exchange (ETDEWEB)

Apergis, Nicholas [Department of Banking and Financial Management, University of Piraeus, Karaoli and Dimitriou 80, Piraeus, ATTIKI 18534 (Greece); Payne, James E. [College of Arts and Sciences, Illinois State University, Campus Box 4100, Normal, IL 61790-4100 (United States)

2009-08-15

This study extends the recent work of Ang (2007) [Ang, J.B., 2007. CO{sub 2} emissions, energy consumption, and output in France. Energy Policy 35, 4772-4778] in examining the causal relationship between carbon dioxide emissions, energy consumption, and output within a panel vector error correction model for six Central American countries over the period 1971-2004. In long-run equilibrium energy consumption has a positive and statistically significant impact on emissions while real output exhibits the inverted U-shape pattern associated with the Environmental Kuznets Curve (EKC) hypothesis. The short-run dynamics indicate unidirectional causality from energy consumption and real output, respectively, to emissions along with bidirectional causality between energy consumption and real output. In the long-run there appears to be bidirectional causality between energy consumption and emissions. (author)

Multiple regression approach to predict turbine-generator output for Chinshan nuclear power plant

International Nuclear Information System (INIS)

Chan, Yea-Kuang; Tsai, Yu-Ching

2017-01-01

The objective of this study is to develop a turbine cycle model using the multiple regression approach to estimate the turbine-generator output for the Chinshan Nuclear Power Plant (NPP). The plant operating data was verified using a linear regression model with a corresponding 95% confidence interval for the operating data. In this study, the key parameters were selected as inputs for the multiple regression based turbine cycle model. The proposed model was used to estimate the turbine-generator output. The effectiveness of the proposed turbine cycle model was demonstrated by using plant operating data obtained from the Chinshan NPP Unit 2. The results show that this multiple regression based turbine cycle model can be used to accurately estimate the turbine-generator output. In addition, this study also provides an alternative approach with simple and easy features to evaluate the thermal performance for nuclear power plants.

Multiple regression approach to predict turbine-generator output for Chinshan nuclear power plant

Energy Technology Data Exchange (ETDEWEB)

Chan, Yea-Kuang; Tsai, Yu-Ching [Institute of Nuclear Energy Research, Taoyuan City, Taiwan (China). Nuclear Engineering Division

2017-03-15

The objective of this study is to develop a turbine cycle model using the multiple regression approach to estimate the turbine-generator output for the Chinshan Nuclear Power Plant (NPP). The plant operating data was verified using a linear regression model with a corresponding 95% confidence interval for the operating data. In this study, the key parameters were selected as inputs for the multiple regression based turbine cycle model. The proposed model was used to estimate the turbine-generator output. The effectiveness of the proposed turbine cycle model was demonstrated by using plant operating data obtained from the Chinshan NPP Unit 2. The results show that this multiple regression based turbine cycle model can be used to accurately estimate the turbine-generator output. In addition, this study also provides an alternative approach with simple and easy features to evaluate the thermal performance for nuclear power plants.

Cut-off Grade Optimization for Maximizing the Output Rate

Directory of Open Access Journals (Sweden)

A. Khodayari

2012-12-01

Full Text Available In the open-pit mining, one of the first decisions that must be made in production planning stage, after completing the design of final pit limits, is determining of the processing plant cut-off grade. Since this grade has an essential effect on operations, choosing the optimum cut-off grade is of considerable importance. Different goals may be used for determining optimum cut-off grade. One of these goals may be maximizing the output rate (amount of product per year, which is very important, especially from marketing and market share points of view. Objective of this research is determining the optimum cut-off grade of processing plant in order to maximize output rate. For performing this optimization, an Operations Research (OR model has been developed. The object function of this model is output rate that must be maximized. This model has two operational constraints namely mining and processing restrictions. For solving the model a heuristic method has been developed. Results of research show that the optimum cut-off grade for satisfying pre-stated goal is the balancing grade of mining and processing operations, and maximum production rate is a function of the maximum capacity of processing plant and average grade of ore that according to the above optimum cut-off grade must be sent to the plant.

Using neuro-fuzzy based approach for the evaluation of turbine-generator outputs

International Nuclear Information System (INIS)

Chan, Y. K.; Lu, C. C.; Chang, C. J.; Kao, L.; Hong, L. C.

2010-01-01

The objective of this study is to develop a hybrid soft-computing modeling technique used to develop the steam turbine cycle model for Chinshan Nuclear Power Station (CNPS). The technique uses neuro-fuzzy model to predict the turbine-generator output. Firstly, the station past three fuel cycles operating data above 95% load were collected and validated as the baseline performance data set. Then, the signal errors for new operating data were detected by comparison with the baseline data set and their allowable range of variations. Finally, the most important parameters were selected as an input of the neuro-fuzzy based steam turbine cycle model. After training and testing with key parameters including throttle pressure, condenser back pressure, feedwater mass flow, and final feedwater temperature, the proposed model can be applied to predict the turbine-generator output. The analysis results show this neuro-fuzzy based turbine cycle model can be used to predict the generator output with a good agreement. Moreover, the achievement of this study provides an alternative approach in thermal performance evaluation for nuclear power stations. (authors)

A hybrid method for forecasting the energy output of photovoltaic systems

International Nuclear Information System (INIS)

Ramsami, Pamela; Oree, Vishwamitra

2015-01-01

Highlights: • We propose a novel hybrid technique for predicting the daily PV energy output. • Multiple linear regression, FFNN and GRNN artificial neural networks are used. • Stepwise regression is used to select the most relevant meteorological parameters. • SR-FFNN reduces the average dispersion and overall bias in prediction errors. • Accuracy metrics of hybrid models are better than those of single-stage models. - Abstract: The intermittent nature of solar energy poses many challenges to renewable energy system operators in terms of operational planning and scheduling. Predicting the output of photovoltaic systems is therefore essential for managing the operation and assessing the economic performance of power systems. This paper presents a new technique for forecasting the 24-h ahead stochastic energy output of photovoltaic systems based on the daily weather forecasts. A comparison of the performances of the hybrid technique with conventional linear regression and artificial neural network models has also been reported. Initially, three single-stage models were designed, namely the generalized regression neural network, feedforward neural network and multiple linear regression. Subsequently, a hybrid-modeling approach was adopted by applying stepwise regression to select input variables of greater importance. These variables were then fed to the single-stage models resulting in three hybrid models. They were then validated by comparing the forecasts of the models with measured dataset from an operational photovoltaic system. The accuracy of the each model was evaluated based on the correlation coefficient, mean absolute error, mean bias error and root mean square error values. Simulation results revealed that the hybrid models perform better than their corresponding single-stage models. Stepwise regression-feedforward neural network hybrid model outperformed the other models with root mean square error, mean absolute error, mean bias error and

SARAH 3.2: Dirac gauginos, UFO output, and more

Science.gov (United States)

Staub, Florian

2013-07-01

SARAH is a Mathematica package optimized for the fast, efficient and precise study of supersymmetric models beyond the MSSM: a new model can be defined in a short form and all vertices are derived. This allows SARAH to create model files for FeynArts/FormCalc, CalcHep/CompHep and WHIZARD/O'Mega. The newest version of SARAH now provides the possibility to create model files in the UFO format which is supported by MadGraph 5, MadAnalysis 5, GoSam, and soon by Herwig++. Furthermore, SARAH also calculates the mass matrices, RGEs and 1-loop corrections to the mass spectrum. This information is used to write source code for SPheno in order to create a precision spectrum generator for the given model. This spectrum-generator-generator functionality as well as the output of WHIZARD and CalcHep model files has seen further improvement in this version. Also models including Dirac gauginos are supported with the new version of SARAH, and additional checks for the consistency of the implementation of new models have been created. Program summaryProgram title:SARAH Catalogue identifier: AEIB_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIB_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 3 22 411 No. of bytes in distributed program, including test data, etc.: 3 629 206 Distribution format: tar.gz Programming language: Mathematica. Computer: All for which Mathematica is available. Operating system: All for which Mathematica is available. Classification: 11.1, 11.6. Catalogue identifier of previous version: AEIB_v1_0 Journal reference of previous version: Comput. Phys. Comm. 182 (2011) 808 Does the new version supersede the previous version?: Yes, the new version includes all known features of the previous version but also provides the new features mentioned below

Enhanced performance CCD output amplifier

Science.gov (United States)

Dunham, Mark E.; Morley, David W.

1996-01-01

A low-noise FET amplifier is connected to amplify output charge from a che coupled device (CCD). The FET has its gate connected to the CCD in common source configuration for receiving the output charge signal from the CCD and output an intermediate signal at a drain of the FET. An intermediate amplifier is connected to the drain of the FET for receiving the intermediate signal and outputting a low-noise signal functionally related to the output charge signal from the CCD. The amplifier is preferably connected as a virtual ground to the FET drain. The inherent shunt capacitance of the FET is selected to be at least equal to the sum of the remaining capacitances.

Structural Estimation of the Output Gap: A Bayesian DSGE Approach for the U.S. Economy

OpenAIRE

Yasuo Hirose; Saori Naganuma

2007-01-01

We estimate the output gap that is consistent with a fully specified DSGE model. Given the structural parameters estimated using Bayesian methods, we estimate the output gap that is defined as a deviation of output from its flexible-price equilibrium. Our output gap illustrates the U.S. business cycles well, compared with other estimates. We find that the main source of the output gap movements is the demand shocks, but that the productivity shocks contributed to the stable output gap in the ...

Classification and modelling of functional outputs of computation codes. Application to accidental thermal-hydraulic calculations in pressurized water reactor (PWR)

International Nuclear Information System (INIS)

Auder, Benjamin

2011-01-01

This research thesis has been made within the frame of a project on nuclear reactor vessel life. It deals with the use of numerical codes aimed at estimating probability densities for every input parameter in order to calculate probability margins at the output level. More precisely, it deals with codes with one-dimensional functional responses. The author studies the numerical simulation of a pressurized thermal shock on a nuclear reactor vessel, i.e. one of the possible accident types. The study of the vessel integrity relies on a thermal-hydraulic analysis and on a mechanical analysis. Algorithms are developed and proposed for each of them. Input-output data are classified using a clustering technique and a graph-based representation. A method for output dimension reduction is proposed, and a regression is applied between inputs and reduced representations. Applications are discussed in the case of modelling and sensitivity analysis for the CATHARE code (a code used at the CEA for the thermal-hydraulic analysis)

Optimization of the output of a solar cell per theoretical and experimental study of the models to one and two exponential

Directory of Open Access Journals (Sweden)

Benyoucef B.

2012-06-01

Full Text Available The production of electricity based on the conversion of the sunlight by photovoltaic cells containing crystalline silicon is the way most used on the technological and industrial level Consequently, the development of the terrestrial applications for the energy production requires high-output cells and low cost.The aim of our work is to present a comparative study between both theoretical and experimental models of a solar cell based silicon type PHYWE (connecting four cells in series of 80 mm diameter to improve photovoltaic performance.This study led to the determination of the parameters of the cell starting from the current-voltage characteristic, the influence of luminous flow on this characteristic as well as the effect of the incidental photons on the solar cell. We justify the interest to use the model with two exponential for the optimization of the output by underlining the insufficiency of the model to one exponential.

IMPACT OF TRADE OPENNESS ON OUTPUT GROWTH: CO INTEGRATION AND ERROR CORRECTION MODEL APPROACH

Directory of Open Access Journals (Sweden)

Asma Arif

2012-01-01

Full Text Available This study analyzed the long run relationship between trade openness and output growth for Pakistan using annual time series data for 1972-2010. This study follows the Engle and Granger co integration analysis and error correction approach to analyze the long run relationship between the two variables. The Error Correction Term (ECT for output growth and trade openness is significant at 5% level of significance and indicates a positive long run relation between the variables. This study has also analyzed the causality between trade openness and output growth by using granger causality test. The results of granger causality show that there is a bi-directional significant relationship between trade openness and economic growth.

Modeling and notation of DEA with strong and weak disposable outputs.

Science.gov (United States)

Kuntz, Ludwig; Sülz, Sandra

2011-12-01

Recent articles published in Health Care Management Science have described DEA applications under the assumption of strong and weak disposable outputs. As we confidently assume that these papers include some methodical deficiencies, we aim to illustrate a revised approach.

Evaluation of an assimilation scheme to estimate snow water equivalent in the High Atlas of Morocco.

Science.gov (United States)

Baba, W. M.; Baldo, E.; Gascoin, S.; Margulis, S. A.; Cortés, G.; Hanich, L.

2017-12-01

The snow melt from the Atlas mountains represents a crucial water resource for crop irrigation in Morocco. Due to the paucity of in situ measurements, and the high spatial variability of the snow cover in this semi-arid region, assimilation of snow cover area (SCA) from high resolution optical remote sensing into a snowpack energy-balance model is considered as a promising method to estimate the snow water equivalent (SWE) and snow melt at catchment scales. Here we present a preliminary evaluation of an uncalibrated particle batch smoother data assimilation scheme (Margulis et al., 2015, J. Hydrometeor., 16, 1752-1772) in the High-Atlas Rheraya pilot catchment (225 km2) over a snow season. This approach does not require in situ data since it is based on MERRA-2 reanalyses data and satellite fractional snow cover area data. We compared the output of this prior/posterior ensemble data assimilation system to output from the distributed snowpack evolution model SnowModel (Liston and Elder, 2006, J. Hydrometeor. 7, 1259-1276). SnowModel was forced with in situ meteorological data from five automatic weather stations (AWS) and some key parameters (precipitation correction factor and rain-snow phase transition parameters) were calibrated using a time series of 8-m resolution SCA maps from Formosat-2. The SnowModel simulation was validated using a continuous snow height record at one high elevation AWS. The results indicate that the open loop simulation was reasonably accurate (compared to SnowModel results) in spite of the coarse resolution of the MERRA-2 forcing. The assimilation of Formosat-2 SCA further improved the simulation in terms of the peak SWE and SWE evolution over the melt season. During the accumulation season, the differences between the modeled and estimated (posterior) SWE were more substantial. The differences appear to be due to some observed precipitation events not being captured in MERRA-2. Further investigation will determine whether additional

Effect of Aspect Ratio on the Light Output of Scintillators

CERN Document Server

Pauwels, Kristof; Gundacker, S.; Knapitsch, A.; Lecoq, P.

2012-01-01

The influence of the geometry of the scintillators is presented in this paper. We focus on the effect of narrowing down the section of crystals that have a given length. The light output of a set of crystals with very similar scintillating properties but different geometries measured with several coupling/wrapping configurations is provided. We observe that crystals shaped in thin rods have a lower light output as compared to bulk or sliced crystals. The effect of unpolishing the crystal faces is also investigated, and it is shown that highest light outputs are not necessarily obtained with crystals having all faces polished. Simulation results based on a realistic model of the crystal that implements light scattering on the crystal edges are in agreement with the experimental data. Fine-tuning of this model would allow us to further explore the details of light propagation in scintillators and would be highly valuable to fast timing detection and highly granular detectors.

Analyzing the impacts of final demand changes on total output using input-output approach: The case of Japanese ICT sectors

Science.gov (United States)

Zuhdi, Ubaidillah

2014-03-01

The purpose of this study is to analyze the impacts of final demand changes on total output of Japanese Information and Communication Technologies (ICT) sectors in future time. This study employs one of analysis tool in Input-Output (IO) analysis, demand-pull IO quantity model, in achieving the purpose. There are three final demand changes used in this study, namely (1) export, (2) import, and (3) outside households consumption changes. This study focuses on "pure change" condition, the condition that final demand changes only appear in analyzed sectors. The results show that export and outside households consumption modifications give positive impact while opposite impact could be seen in import change.

Forecasted Changes in West Africa Photovoltaic Energy Output by 2045

Directory of Open Access Journals (Sweden)

Serge Dimitri Yikwe Buri Bazyomo

2016-10-01

Full Text Available The impacts of climate change on photovoltaic (PV output in the fifteen countries of the Economic Community of West African States (ECOWAS was analyzed in this paper. Using a set of eight climate models, the trends of solar radiation and temperature between 2006–2100 were examined. Assuming a lifetime of 40 years, the future changes of photovoltaic energy output for the tilted plane receptor compared to 2006–2015 were computed for the whole region. The results show that the trends of solar irradiation are negative except for the Irish Centre for High-End Computing model which predicts a positive trend with a maximum value of 0.17 W/m2/year for Cape Verde and the minimum of −0.06 W/m2/year for Liberia. The minimum of the negative trend is −0.18 W/m2/year predicted by the Model for Interdisciplinary Research on Climate (MIROC, developed at the University of Tokyo Center for Climate System Research for Cape Verde. Furthermore, temperature trends are positive with a maximum of 0.08 K/year predicted by MIROC for Niger and minimum of 0.03 K/year predicted by Nature Conservancy of Canada (NCC, Max Planck Institute (MPI for Climate Meteorology at Hamburg, French National Meteorological Research Center (CNRM and Canadian Centre for Climate Modelling and Analysis (CCCMA for Cape Verde. Photovolataic energy output changes show increasing trends in Sierra Leone with 0.013%/year as the maximum. Climate change will lead to a decreasing trend of PV output in the rest of the countries with a minimum of 0.032%/year in Niger.

Money, Output and Price Level in Nigeria: A Test of the Monetary ...

African Journals Online (AJOL)

This paper presents and tests a model to determine either or both how anticipated or unanticipated money affects real output and inflation in Nigeria. The Barro two –step estimation procedure was explored. Also, the effects of devaluation and business cycles in the industrialized countries on output fluctuation in Nigeria ...

Quantifying uncertainties in radar forward models through a comparison between CloudSat and SPartICus reflectivity factors

Science.gov (United States)

Mascio, Jeana; Mace, Gerald G.

2017-02-01

Interpretations of remote sensing measurements collected in sample volumes containing ice-phase hydrometeors are very sensitive to assumptions regarding the distributions of mass with ice crystal dimension, otherwise known as mass-dimensional or m-D relationships. How these microphysical characteristics vary in nature is highly uncertain, resulting in significant uncertainty in algorithms that attempt to derive bulk microphysical properties from remote sensing measurements. This uncertainty extends to radar reflectivity factors forward calculated from model output because the statistics of the actual m-D in nature is not known. To investigate the variability in m-D relationships in cirrus clouds, reflectivity factors measured by CloudSat are combined with particle size distributions (PSDs) collected by coincident in situ aircraft by using an optimal estimation-based (OE) retrieval of the m-D power law. The PSDs were collected by 12 flights of the Stratton Park Engineering Company Learjet during the Small Particles in Cirrus campaign. We find that no specific habit emerges as preferred, and instead, we find that the microphysical characteristics of ice crystal populations tend to be distributed over a continuum-defying simple categorization. With the uncertainties derived from the OE algorithm, the uncertainties in forward-modeled backscatter cross section and, in turn, radar reflectivity is calculated by using a bootstrapping technique, allowing us to infer the uncertainties in forward-modeled radar reflectivity that would be appropriately applied to remote sensing simulator algorithms.

Decoupling Analysis of China’s Product Sector Output and Its Embodied Carbon Emissions—An Empirical Study Based on Non-Competitive I-O and Tapio Decoupling Model

Directory of Open Access Journals (Sweden)

Jianbo Hu

2017-05-01

Full Text Available This paper uses the non-competitive I-O model and the Tapio decoupling model to comprehensively analyze the decoupling relationship between the output of the product sector in China and its embodied carbon emissions under trade openness. For this purpose, the Chinese input and output data in 2002, 2005, 2007, 2010, and 2012 are used. This approach is beneficial to identify the direct mechanism for the increased carbon emission in China from a micro perspective and provides a new perspective for the subsequent study about low-carbon economy. The obtained empirical results are as follows: (1 From overall perspective, the decoupling elasticity between the output of the product sector and its embodied carbon emissions decreased. Output and embodied carbon emissions showed a growth link from 2002 to 2005 and a weak decoupling relationship for the rest of the study period. (2 Among the 28 industries in the product sector, the increased growth rate of output in more and more product sectors was no longer accompanied by large CO2 emissions. The number of industries with strong decoupling relationships between output and embodied carbon emissions increased. (3 From the perspective of three industries, the output and embodied carbon emissions in the second and third industries exhibited a growth link only from 2002 to 2005; the three industries presented weak or strong decoupling for the rest of the study period. Through empirical analysis, this paper mainly through the construction of ecological and environmental protection of low carbon agriculture, low carbon cycle industrial system, as well as intensive and efficient service industry to reduce the carbon emissions of China’s product sector.

Antiretroviral therapy increases thymic output in children with HIV

DEFF Research Database (Denmark)

Schou Sandgaard, Katrine; Lewis, Joanna; Adams, Stuart

2014-01-01

OBJECTIVE: Disease progression and response to antiretroviral therapy (ART) in HIV-infected children is different to that of adults. Immune reconstitution in adults is mainly from memory T cells, whereas in children it occurs predominantly from the naive T-cell pool. It is unclear however what...... with a recently described mathematical model to give explicit measures of thymic output. RESULTS: We found that age-adjusted thymic output is reduced in untreated children with HIV, which increases significantly with length of time on ART. CONCLUSION: Our results suggest that a highly active thymus in early...

Modeling DPOAE input/output function compression: comparisons with hearing thresholds.

Science.gov (United States)

Bhagat, Shaum P

2014-09-01

Basilar membrane input/output (I/O) functions in mammalian animal models are characterized by linear and compressed segments when measured near the location corresponding to the characteristic frequency. A method of studying basilar membrane compression indirectly in humans involves measuring distortion-product otoacoustic emission (DPOAE) I/O functions. Previous research has linked compression estimates from behavioral growth-of-masking functions to hearing thresholds. The aim of this study was to compare compression estimates from DPOAE I/O functions and hearing thresholds at 1 and 2 kHz. A prospective correlational research design was performed. The relationship between DPOAE I/O function compression estimates and hearing thresholds was evaluated with Pearson product-moment correlations. Normal-hearing adults (n = 16) aged 22-42 yr were recruited. DPOAE I/O functions (L₂ = 45-70 dB SPL) and two-interval forced-choice hearing thresholds were measured in normal-hearing adults. A three-segment linear regression model applied to DPOAE I/O functions supplied estimates of compression thresholds, defined as breakpoints between linear and compressed segments and the slopes of the compressed segments. Pearson product-moment correlations between DPOAE compression estimates and hearing thresholds were evaluated. A high correlation between DPOAE compression thresholds and hearing thresholds was observed at 2 kHz, but not at 1 kHz. Compression slopes also correlated highly with hearing thresholds only at 2 kHz. The derivation of cochlear compression estimates from DPOAE I/O functions provides a means to characterize basilar membrane mechanics in humans and elucidates the role of compression in tone detection in the 1-2 kHz frequency range. American Academy of Audiology.

Analyzing the impacts of final demand changes on total output using input-output approach: The case of Japanese ICT sectors

International Nuclear Information System (INIS)

Zuhdi, Ubaidillah

2014-01-01

The purpose of this study is to analyze the impacts of final demand changes on total output of Japanese Information and Communication Technologies (ICT) sectors in future time. This study employs one of analysis tool in Input-Output (IO) analysis, demand-pull IO quantity model, in achieving the purpose. There are three final demand changes used in this study, namely (1) export, (2) import, and (3) outside households consumption changes. This study focuses on ''pure change'' condition, the condition that final demand changes only appear in analyzed sectors. The results show that export and outside households consumption modifications give positive impact while opposite impact could be seen in import change

Impact of Technology on Smallholder Wheat Production in Bale Highlands of Ethiopia: Application of Output Decomposition Model

Directory of Open Access Journals (Sweden)

Mengistu Ketema

2016-06-01

Full Text Available In Ethiopia, the national agricultural research system has been generating and disseminating different agricultural technologies since its establishment in 1966. Although these technologies are meant to increase agricultural productivity, they have to be evaluated for their impact on production and for the benefit that the farmers get out of them. Hence, the main objectives of this study were to examine the impact of technological innovations on wheat production and to decompose the total change in wheat output resulting from the introduction of new technologies into its constituent parts. Cobb-Douglas production function was employed to estimate the regression coefficients under old variety growers, new variety growers, and pooled data cases. Output decomposition model was applied to decompose the total change in output into its constituent parts. The econometric results of this study indicated that, out of 55% of the observed productivity difference between old and new variety grown plots, technological change and change in associated input levels contributed about 24% and 31%, respectively. Of the 31% increment attributed to input use levels, an increased use of herbicides and fertilizers caused the biggest jump in the productivity of improved wheat varieties (15.5% and 11% respectively. The major implications included the need to exploit the full potential of new varieties using recommended input levels, strengthening the research system, fostering coordinated efforts among various actors in agricultural development, and strengthening the technology instrument in rural development and poverty reduction strategies of the country.

Output variability caused by random seeds in a multi-agent transport simulation model

DEFF Research Database (Denmark)

Paulsen, Mads; Rasmussen, Thomas Kjær; Nielsen, Otto Anker

2018-01-01

Dynamic transport simulators are intended to support decision makers in transport-related issues, and as such it is valuable that the random variability of their outputs is as small as possible. In this study we analyse the output variability caused by random seeds of a multi-agent transport...... simulator (MATSim) when applied to a case study of Santiago de Chile. Results based on 100 different random seeds shows that the relative accuracies of estimated link loads tend to increase with link load, but that relative errors of up to 10 % do occur even for links with large volumes. Although...

The output, incomes and assets-capital relations in individual farms

Directory of Open Access Journals (Sweden)

Roma Ryś-Jurek

2009-01-01

Full Text Available In this article an attempt was made to analyse the output, incomes as well as other components of assets and sources that provided their financing in Polish individual farms, in comparison with farms from other EU countries. A special emphasis was put on examination of the interrelations between income, output and stocks observed within individual farms. Research was based on the FADN database that included basic information about average individual farms in years 2004-2006. The research showed, that (among other things the average output and family farm income were three times lower in Poland than the average in the Union. Also the increase of income was possible only thanks to the subsidies from the Union. According to the regression models, in Poland the positive influence on the increase of family farm income had stocks, crops and livestock output. While in the EU positive influence had crops and livestock production and negative influence had the stocks on an income’s growth.

Outputs of shock-loaded small piezoceramic disks

International Nuclear Information System (INIS)

Charest, Jacques A.; Mace, Jonathan Lee

2002-01-01

Thin small-diameter polycrystalline Lead-Zirconate-Titanate piezoceramic disks were shock loaded in the D33 orientation over a stress range of 0.1-30 GPa. Their electrical outputs were discharged into 50 Ω viewing resistors, producing typically 0.15 μs quasi-triangular impulses ranging from 50-700 V. The gas gun flat plate impact approach and the high explosives (HE) plane wave lens approach were used to load piezoceramic elements. These piezoceramic elements consisted of 0.25 mm thick and 1.32 mm diameter disks that were ultrasonically machined from 25 mm piezocrystal disks of type APC 850, commercially produced by American Piezo Ceramic Inc. To facilitate our experiments, the piezoceramic elements were coaxially mounted at the tip of a 2.35 mm diameter brass tube, an arrangement that is commercialized by Dynasen, Inc. under the name Piezopin of model CA-1136. Simple calculations on the electrical outputs produced by these piezoceramic disks reveal electrical outputs in excess of 3000 W. Such short bursts of electrical energy have the potential for numerous applications where critical timing is needed to observe fast transient events

SU-E-T-136: Assessment of Seasonal Linear Accelerator Output Variations and Associated Impacts

International Nuclear Information System (INIS)

Bartolac, S; Letourneau, D

2015-01-01

Purpose: Application of process control theory in quality assurance programs promises to allow earlier identification of problems and potentially better quality in delivery than traditional paradigms based primarily on tolerances and action levels. The purpose of this project was to characterize underlying seasonal variations in linear accelerator output that can be used to improve performance or trigger preemptive maintenance. Methods: Review of runtime plots of daily (6 MV) output data acquired using in house ion chamber based devices over three years and for fifteen linear accelerators of varying make and model were evaluated. Shifts in output due to known interventions with the machines were subtracted from the data to model an uncorrected scenario for each linear accelerator. Observable linear trends were also removed from the data prior to evaluation of periodic variations. Results: Runtime plots of output revealed sinusoidal, seasonal variations that were consistent across all units, irrespective of manufacturer, model or age of machine. The average amplitude of the variation was on the order of 1%. Peak and minimum variations were found to correspond to early April and September, respectively. Approximately 48% of output adjustments made over the period examined were potentially avoidable if baseline levels had corresponded to the mean output, rather than to points near a peak or valley. Linear trends were observed for three of the fifteen units, with annual increases in output ranging from 2–3%. Conclusion: Characterization of cyclical seasonal trends allows for better separation of potentially innate accelerator behaviour from other behaviours (e.g. linear trends) that may be better described as true out of control states (i.e. non-stochastic deviations from otherwise expected behavior) and could indicate service requirements. Results also pointed to an optimal setpoint for accelerators such that output of machines is maintained within set tolerances

SU-E-T-136: Assessment of Seasonal Linear Accelerator Output Variations and Associated Impacts

Energy Technology Data Exchange (ETDEWEB)

Bartolac, S; Letourneau, D [Princess Margaret Cancer Centre, Toronto, Ontario (Canada); University of Toronto, Toronto, Ontario (Canada)

2015-06-15

Purpose: Application of process control theory in quality assurance programs promises to allow earlier identification of problems and potentially better quality in delivery than traditional paradigms based primarily on tolerances and action levels. The purpose of this project was to characterize underlying seasonal variations in linear accelerator output that can be used to improve performance or trigger preemptive maintenance. Methods: Review of runtime plots of daily (6 MV) output data acquired using in house ion chamber based devices over three years and for fifteen linear accelerators of varying make and model were evaluated. Shifts in output due to known interventions with the machines were subtracted from the data to model an uncorrected scenario for each linear accelerator. Observable linear trends were also removed from the data prior to evaluation of periodic variations. Results: Runtime plots of output revealed sinusoidal, seasonal variations that were consistent across all units, irrespective of manufacturer, model or age of machine. The average amplitude of the variation was on the order of 1%. Peak and minimum variations were found to correspond to early April and September, respectively. Approximately 48% of output adjustments made over the period examined were potentially avoidable if baseline levels had corresponded to the mean output, rather than to points near a peak or valley. Linear trends were observed for three of the fifteen units, with annual increases in output ranging from 2–3%. Conclusion: Characterization of cyclical seasonal trends allows for better separation of potentially innate accelerator behaviour from other behaviours (e.g. linear trends) that may be better described as true out of control states (i.e. non-stochastic deviations from otherwise expected behavior) and could indicate service requirements. Results also pointed to an optimal setpoint for accelerators such that output of machines is maintained within set tolerances

Preliminary evaluation of techniques for transforming regional climate model output to the potential repository site in support of Yucca Mountain future climate synthesis

International Nuclear Information System (INIS)

Church, H.W.; Zak, B.D.; Behl, Y.K.

1995-06-01

The report describes a preliminary evaluation of models for transforming regional climate model output from a regional to a local scale for the Yucca Mountain area. Evaluation and analysis of both empirical and numerical modeling are discussed which is aimed at providing site-specific, climate-based information for use by interfacing activities. Two semiempirical approaches are recommended for further analysis

Does the DHET research output subsidy model penalise high-citation publication? A case study

Directory of Open Access Journals (Sweden)

Yolande X. Harley

2016-05-01

Full Text Available South African universities are awarded annual subsidy from the Department of Higher Education and Training (DHET based on their research publication output. Journal article subsidy is based on the number of research publications in DHET-approved journals as well as the proportional contribution of authors from the university. Co-authorship with other institutions reduces the subsidy received by a university, which may be a disincentive to collaboration. Inter-institutional collaboration may affect the scientific impact of resulting publications, as indicated by the number of citations received. We analysed 812 journal articles published in 2011 by authors from the University of Cape Town’s Faculty of Health Sciences to determine if there was a significant relationship between subsidy units received and (1 citation count and (2 field-weighted citation impact. We found that subsidy units had a significant inverse relationship with both citation count (r= -0.247; CI = -0.311 – -0.182; p"less than"0.0001 and field-weighted citation impact (r= -0.192; CI= -0.258 – -0.125; p"less than"0.0001. These findings suggest that the annual subsidy awarded to universities for research output may inadvertently penalise high-citation publication. Revision of the funding model to address this possibility would better align DHET funding allocation with the strategic plans of the South African Department of Science and Technology, the National Research Foundation and the South African Medical Research Council, and may better support publication of greater impact research.

Output Current Ripple Reduction Algorithms for Home Energy Storage Systems

Directory of Open Access Journals (Sweden)

Jin-Hyuk Park

2013-10-01

Full Text Available This paper proposes an output current ripple reduction algorithm using a proportional-integral (PI controller for an energy storage system (ESS. In single-phase systems, the DC/AC inverter has a second-order harmonic at twice the grid frequency of a DC-link voltage caused by pulsation of the DC-link voltage. The output current of a DC/DC converter has a ripple component because of the ripple of the DC-link voltage. The second-order harmonic adversely affects the battery lifetime. The proposed algorithm has an advantage of reducing the second-order harmonic of the output current in the variable frequency system. The proposed algorithm is verified from the PSIM simulation and experiment with the 3 kW ESS model.

A controls engineering approach for analyzing airplane input-output characteristics

Science.gov (United States)

Arbuckle, P. Douglas

1991-01-01

An engineering approach for analyzing airplane control and output characteristics is presented. State-space matrix equations describing the linear perturbation dynamics are transformed from physical coordinates into scaled coordinates. The scaling is accomplished by applying various transformations to the system to employ prior engineering knowledge of the airplane physics. Two different analysis techniques are then explained. Modal analysis techniques calculate the influence of each system input on each fundamental mode of motion and the distribution of each mode among the system outputs. The optimal steady state response technique computes the blending of steady state control inputs that optimize the steady state response of selected system outputs. Analysis of an example airplane model is presented to demonstrate the described engineering approach.

Timber products output and timber harvests in Alaska: projections for 1992-2010.

Science.gov (United States)

D.J. Brooks; R.W. Haynes

1994-01-01

Projections of Alaska timber products output, the derived demand for raw material, and timber harvest by owner are developed from a trend-based analysis. By using a spread-sheet model, material flows in the Alaska forest sectorare fully accounted for. Demand for Alaska national forest timber is projected and depends on product output and harvest by other owners. Key...

Assessment of the Suitability of High Resolution Numerical Weather Model Outputs for Hydrological Modelling in Mountainous Cold Regions

Science.gov (United States)

Rasouli, K.; Pomeroy, J. W.; Hayashi, M.; Fang, X.; Gutmann, E. D.; Li, Y.

2017-12-01

The hydrology of mountainous cold regions has a large spatial variability that is driven both by climate variability and near-surface process variability associated with complex terrain and patterns of vegetation, soils, and hydrogeology. There is a need to downscale large-scale atmospheric circulations towards the fine scales that cold regions hydrological processes operate at to assess their spatial variability in complex terrain and quantify uncertainties by comparison to field observations. In this research, three high resolution numerical weather prediction models, namely, the Intermediate Complexity Atmosphere Research (ICAR), Weather Research and Forecasting (WRF), and Global Environmental Multiscale (GEM) models are used to represent spatial and temporal patterns of atmospheric conditions appropriate for hydrological modelling. An area covering high mountains and foothills of the Canadian Rockies was selected to assess and compare high resolution ICAR (1 km × 1 km), WRF (4 km × 4 km), and GEM (2.5 km × 2.5 km) model outputs with station-based meteorological measurements. ICAR with very low computational cost was run with different initial and boundary conditions and with finer spatial resolution, which allowed an assessment of modelling uncertainty and scaling that was difficult with WRF. Results show that ICAR, when compared with WRF and GEM, performs very well in precipitation and air temperature modelling in the Canadian Rockies, while all three models show a fair performance in simulating wind and humidity fields. Representation of local-scale atmospheric dynamics leading to realistic fields of temperature and precipitation by ICAR, WRF, and GEM makes these models suitable for high resolution cold regions hydrological predictions in complex terrain, which is a key factor in estimating water security in western Canada.

Convective-stratiform rainfall separation of Typhoon Fitow (2013: A 3D WRF modeling study

Directory of Open Access Journals (Sweden)

Huiyan Xu

2018-01-01

Full Text Available Surface precipitation budget equation in a three-dimensional (3D WRF model framework is derived. By applying the convective-stratiform partition method to the surface precipitation budget equation in the 3D model, this study separated convective and stratiform rainfall of typhoon Fitow (2013. The separations are further verified by examining statistics of vertical velocity, surface precipitation budget, and cloud microphysical budget. Results show that water vapor convergence moistens local atmosphere and offsets hydrometeor divergence, and producing convective rainfall, while hydrometeor convergence primarily supports stratiform rainfall, since water vapor divergence and local atmospheric drying generally cancelled out. Mean ascending motions are prevailing in the entire troposphere in the convective region, whereas mean descending motions occur below 5 km and mean ascending motions occur above in the stratiform region. The frequency distribution of vertical velocity shows vertical velocity has wide distribution with the maximum values up to 13 m s-1 in the convective regions, whereas it has narrow distribution with absolute values confined within 7 m s-1 in the stratiform region. Liquid cloud microphysics is dominant in convective regions and ice cloud microphysics is dominant in stratiform regions. These indicate that the statistics results are generally consistent with the corresponding physical characteristics of the convective-stratiform rainfall structures generalized by previous studies.

A Network DEA Model with Super Efficiency and Undesirable Outputs: An Application to Bank Efficiency in China

Directory of Open Access Journals (Sweden)

Jianhuan Huang

2014-01-01

Full Text Available There are two typical subprocesses in bank production—deposit generation and loan generation. Aiming to open the black box of input-output production of banks and provide comprehensive and accurate assessment on the efficiency of each stage, this paper proposes a two-stage network model with bad outputs and supper efficiency (US-NSBM. Empirical comparisons show that the US-NSBM may be promising and practical for taking the nonperforming loans into account and being able to rank all samples. Applying it to measure the efficiency of Chinese commercial banks from 2008 to 2012, this paper explores the characteristics of overall and divisional efficiency, as well as the determinants of them. Some interesting results are discovered. The polarization of efficiency occurs in the bank level and deposit generation, yet does not in the loan generation. Five hypotheses work as expected in the bank level, but not all of them are supported in the stage level. Our results extend and complement some earlier empirical publications in the bank level.

Oil migration through unsaturated soils and its effect on the Vadose Zone Interactive Processes (VIP) model output

International Nuclear Information System (INIS)

Joseph, A.T.; Grenney, W.J.; Stevens, D.K.

1994-01-01

The VIP model, which simulates the concentration profiles of the hazardous compounds in the soil, water, and the air phases, assumes a fixed oily phase. The purpose of this study was to measure oil migration in soil systems and to determine its effect on the VIP model output. Experiments were conducted to demonstrate the mobility of an oil through the unsaturated zone of the soil. The studies were conducted in laboratory scale glass columns. A light petroleum oil and two types of soil were used. The experiments demonstrated that oil migrates down significantly through the soil columns. The extent of migration depended on the volume of oil applied and the type of soil. However, the applied oil was completely immobilized in the columns. The model was modified to incorporate oil migration. The modified model can be expected to produce more realistic contaminant concentration profiles during land treatment of oily wastes when compared to that produced by the present version of the VIP model. (Author)

Multiregional input-output model for China's farm land and water use.

Science.gov (United States)

Guo, Shan; Shen, Geoffrey Qiping

2015-01-06

Land and water are the two main drivers of agricultural production. Pressure on farm land and water resources is increasing in China due to rising food demand. Domestic trade affects China's regional farm land and water use by distributing resources associated with the production of goods and services. This study constructs a multiregional input-output model to simultaneously analyze China's farm land and water uses embodied in consumption and interregional trade. Results show a great similarity for both China's farm land and water endowments. Shandong, Henan, Guangdong, and Yunnan are the most important drivers of farm land and water consumption in China, even though they have relatively few land and water resource endowments. Significant net transfers of embodied farm land and water flows are identified from the central and western areas to the eastern area via interregional trade. Heilongjiang is the largest farm land and water supplier, in contrast to Shanghai as the largest receiver. The results help policy makers to comprehensively understand embodied farm land and water flows in a complex economy network. Improving resource utilization efficiency and reshaping the embodied resource trade nexus should be addressed by considering the transfer of regional responsibilities.

Cardiac output measurement

Directory of Open Access Journals (Sweden)

Andreja Möller Petrun

2014-02-01

Full Text Available In recent years, developments in the measuring of cardiac output and other haemodynamic variables are focused on the so-called minimally invasive methods. The aim of these methods is to simplify the management of high-risk and haemodynamically unstable patients. Due to the need of invasive approach and the possibility of serious complications the use of pulmonary artery catheter has decreased. This article describes the methods for measuring cardiac output, which are based on volume measurement (Fick method, indicator dilution method, pulse wave analysis, Doppler effect, and electrical bioimpedance.

Prediction of Francis Turbine Prototype Part Load Pressure and Output Power Fluctuations with Hydroelectric Model

Science.gov (United States)

Alligné, S.; Nicolet, C.; Béguin, A.; Landry, C.; Gomes, J.; Avellan, F.

2017-04-01

The prediction of pressure and output power fluctuations amplitudes on Francis turbine prototype is a challenge for hydro-equipment industry since it is subjected to guarantees to ensure smooth and reliable operation of the hydro units. The European FP7 research project Hyperbole aims to setup a methodology to transpose the pressure fluctuations induced by the cavitation vortex rope from the reduced scale model to the prototype generating units. A Francis turbine unit of 444MW with a specific speed value of ν = 0.29, is considered as case study. A SIMSEN model of the power station including electrical system, controllers, rotating train and hydraulic system with transposed draft tube excitation sources is setup. Based on this model, a frequency analysis of the hydroelectric system is performed for all technologies to analyse potential interactions between hydraulic excitation sources and electrical components. Three technologies have been compared: the classical fixed speed configuration with Synchronous Machine (SM) and the two variable speed technologies which are Doubly Fed Induction Machine (DFIM) and Full Size Frequency Converter (FSFC).

Spectroscopic output of {sup 125}I and {sup 103}Pd low dose rate brachytherapy sources

Energy Technology Data Exchange (ETDEWEB)

Usher-Moga, Jacqueline; Beach, Stephen M.; DeWerd, Larry A. [Department of Medical Physics, University of Wisconsin--Madison, Madison, Wisconsin 53705 (United States); Global Physics Solutions, St. Joseph, Michigan 49085 (United States); Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin 53705 (United States)

2009-01-15

The spectroscopic output of low dose rate (LDR) brachytherapy sources is dependent on the physical design and construction of the source. Characterization of the emitted photons from 12 {sup 125}I and 3 {sup 103}Pd LDR brachytherapy source models is presented. Photon spectra, both along the transverse bisector and at several polar angles, were measured in air with a high-purity reverse electrode germanium (REGe) detector. Measured spectra were corrected to in vacuo conditions via Monte Carlo and analytical methods. The tabulated and plotted spectroscopic data provide a more complete understanding of each source model's output characteristics than can be obtained with other measurement techniques. The variation in fluorescence yield of the {sup 125}I sources containing silver caused greater differences in the emitted spectra and average energies among these seed models than was observed for the {sup 103}Pd sources or the {sup 125}I sources that do not contain silver. Angular spectroscopic data further highlighted the effects of source construction unique to each model, as well as the asymmetric output of many seeds. These data demonstrate the need for the incorporation of such physically measured output characteristics in the Monte Carlo modeling process.

Dynamic Estimation on Output Elasticity of Highway Capital Stock in China

Science.gov (United States)

Li, W. J.; Zuo, Q. L.; Bai, Y. F.

2017-12-01

By using the Perpetual Inventory Method to calculate the capital stock of highway in China from 1988 to 2016, the paper builds the State Space Model based on Translog Production Function, according to the Ridge Regression and Kalman Filter Method, the dynamic estimation results of output elasticity are measured continuously and analyzed. The conclusions show that: Firstly, China’s growth speed on highway industry capital stock are divided into three stages which are respectively from 1988 to 2000, from 2001 to 2009 and from 2010 to 2016, during which shows steady growth, between which reflect rapid growth; Secondly, the output elasticity of highway capital stock, being between 0.154 and 0.248, is slightly larger than the output elasticity of human input factor, lower than the output elasticity of the technical level, shows positive effect on transport economy and rises steadily, but the output efficiency is low on the whole; Thirdly, around the year of 2010, the scale pay on highway industry begins to highlight the characteristic of increase.

Probabilistic Output Analysis by Program Manipulation

DEFF Research Database (Denmark)

Rosendahl, Mads; Kirkeby, Maja Hanne

2015-01-01

The aim of a probabilistic output analysis is to derive a probability distribution of possible output values for a program from a probability distribution of its input. We present a method for performing static output analysis, based on program transformation techniques. It generates a probability...

Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs

NARCIS (Netherlands)

Kuosmanen, T.K.

2005-01-01

Environmental Economics and Natural Resources Group at Wageningen University in The Netherlands Weak disposability of outputs means that firms can abate harmful emissions by decreasing the activity level. Modeling weak disposability in nonparametric production analysis has caused some confusion.

Inverter communications using output signal

Science.gov (United States)

Chapman, Patrick L.

2017-02-07

Technologies for communicating information from an inverter configured for the conversion of direct current (DC) power generated from an alternative source to alternating current (AC) power are disclosed. The technologies include determining information to be transmitted from the inverter over a power line cable connected to the inverter and controlling the operation of an output converter of the inverter as a function of the information to be transmitted to cause the output converter to generate an output waveform having the information modulated thereon.

Integration of TMVA Output into Jupyter notebooks

CERN Document Server

Saliji, Albulena

2016-01-01

The purpose of this report is to describe the work that I have been doing during these past eight weeks as a Summer Student at CERN. The task which was assigned to me had to do with the integration of TMVA Output into Jupyter notebooks. In order to integrate the TMVA Output into the Jupyter notebook, first, improvement of the TMVA Output in the terminal was required. Once the output was improved, it needed to be transformed into HTML output and at the end it would be possible to integrate that output into the Jupyter notebook.

Modeling imbalanced economic recovery following a natural disaster using input-output analysis.

Science.gov (United States)

Li, Jun; Crawford-Brown, Douglas; Syddall, Mark; Guan, Dabo

2013-10-01

Input-output analysis is frequently used in studies of large-scale weather-related (e.g., Hurricanes and flooding) disruption of a regional economy. The economy after a sudden catastrophe shows a multitude of imbalances with respect to demand and production and may take months or years to recover. However, there is no consensus about how the economy recovers. This article presents a theoretical route map for imbalanced economic recovery called dynamic inequalities. Subsequently, it is applied to a hypothetical postdisaster economic scenario of flooding in London around the year 2020 to assess the influence of future shocks to a regional economy and suggest adaptation measures. Economic projections are produced by a macro econometric model and used as baseline conditions. The results suggest that London's economy would recover over approximately 70 months by applying a proportional rationing scheme under the assumption of initial 50% labor loss (with full recovery in six months), 40% initial loss to service sectors, and 10-30% initial loss to other sectors. The results also suggest that imbalance will be the norm during the postdisaster period of economic recovery even though balance may occur temporarily. Model sensitivity analysis suggests that a proportional rationing scheme may be an effective strategy to apply during postdisaster economic reconstruction, and that policies in transportation recovery and in health care are essential for effective postdisaster economic recovery. © 2013 Society for Risk Analysis.

Using Economic Input/Output Tables to Predict a Country's Nuclear Status

International Nuclear Information System (INIS)

Weimar, Mark R.; Daly, Don S.; Wood, Thomas W.

2010-01-01

Both nuclear power and nuclear weapons programs should have (related) economic signatures which are detectible at some scale. We evaluated this premise in a series of studies using national economic input/output (IO) data. Statistical discrimination models using economic IO tables predict with a high probability whether a country with an unknown predilection for nuclear weapons proliferation is in fact engaged in nuclear power development or nuclear weapons proliferation. We analyzed 93 IO tables, spanning the years 1993 to 2005 for 37 countries that are either members or associates of the Organization for Economic Cooperation and Development (OECD). The 2009 OECD input/output tables featured 48 industrial sectors based on International Standard Industrial Classification (ISIC) Revision 3, and described the respective economies in current country-of-origin valued currency. We converted and transformed these reported values to US 2005 dollars using appropriate exchange rates and implicit price deflators, and addressed discrepancies in reported industrial sectors across tables. We then classified countries with Random Forest using either the adjusted or industry-normalized values. Random Forest, a classification tree technique, separates and categorizes countries using a very small, select subset of the 2304 individual cells in the IO table. A nation's efforts in nuclear power, be it for electricity or nuclear weapons, are an enterprise with a large economic footprint -- an effort so large that it should discernibly perturb coarse country-level economics data such as that found in yearly input-output economic tables. The neoclassical economic input-output model describes a country's or region's economy in terms of the requirements of industries to produce the current level of economic output. An IO table row shows the distribution of an industry's output to the industrial sectors while a table column shows the input required of each industrial sector by a given

An extended environmental input-output lifecycle assessment model to study the urban food-energy-water nexus

Science.gov (United States)

Sherwood, John; Clabeaux, Raeanne; Carbajales-Dale, Michael

2017-10-01

We developed a physically-based environmental account of US food production systems and integrated these data into the environmental-input-output life cycle assessment (EIO-LCA) model. The extended model was used to characterize the food, energy, and water (FEW) intensities of every US economic sector. The model was then applied to every Bureau of Economic Analysis metropolitan statistical area (MSA) to determine their FEW usages. The extended EIO-LCA model can determine the water resource use (kGal), energy resource use (TJ), and food resource use in units of mass (kg) or energy content (kcal) of any economic activity within the United States. We analyzed every economic sector to determine its FEW intensities per dollar of economic output. This data was applied to each of the 382 MSAs to determine their total and per dollar of GDP FEW usages by allocating MSA economic production to the corresponding FEW intensities of US economic sectors. Additionally, a longitudinal study was performed for the Los Angeles-Long Beach-Anaheim, CA, metropolitan statistical area to examine trends from this singular MSA and compare it to the overall results. Results show a strong correlation between GDP and energy use, and between food and water use across MSAs. There is also a correlation between GDP and greenhouse gas emissions. The longitudinal study indicates that these correlations can shift alongside a shifting industrial composition. Comparing MSAs on a per GDP basis reveals that central and southern California tend to be more resource intensive than many other parts of the country, while much of Florida has abnormally low resource requirements. Results of this study enable a more complete understanding of food, energy, and water as key ingredients to a functioning economy. With the addition of the food data to the EIO-LCA framework, researchers will be able to better study the food-energy-water nexus and gain insight into how these three vital resources are interconnected

Wind resource and plant output data sets for wind integration studies

Energy Technology Data Exchange (ETDEWEB)

Frank, Jaclyn D.; Manobianco, John; Alonge, Charles J.; Brower, Michael C. [AWS Truepower, Albany, NY (United States)

2010-07-01

One of the first step towards understanding the impact of increasing penetrations of wind is developing data sets of wind power output over large regions. To facilitate the development of these data sets, AWS Truepower (AWST) generated wind speeds over multiple years (2-3) using the Mesoscale Atmospheric Simulation System (MASS). These simulations were performed with high spatial resolution (1-2 km) to capture the wind flows over each area of interest. Output was saved in 10-minute interval to capture variations in wind speed so that plant output could be analyzed against utility load and system operations. This paper will describe the methodology of mesoscale modeling, site selection, conversion to power, and downscaling to high frequency output. Additionally, the generation of synthetic forecasts will be discussed. The validation results from recent studies in the eastern United States and Hawaii will be highlighted. (orig.)

World Input-Output Network.

Directory of Open Access Journals (Sweden)

Federica Cerina

Full Text Available Production systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale. Only recently becoming available, the World Input-Output Database (WIOD is one of the first efforts to construct the global multi-regional input-output (GMRIO tables. By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods flows between industries, we analyze respectively the global, regional, and local network properties of the so-called world input-output network (WION and document its evolution over time. At global level, we find that the industries are highly but asymmetrically connected, which implies that micro shocks can lead to macro fluctuations. At regional level, we find that the world production is still operated nationally or at most regionally as the communities detected are either individual economies or geographically well defined regions. Finally, at local level, for each industry we compare the network-based measures with the traditional methods of backward linkages. We find that the network-based measures such as PageRank centrality and community coreness measure can give valuable insights into identifying the key industries.

A Constraint programming-based genetic algorithm for capacity output optimization

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Kate Ean Nee Goh

2014-10-01

Full Text Available Purpose: The manuscript presents an investigation into a constraint programming-based genetic algorithm for capacity output optimization in a back-end semiconductor manufacturing company.Design/methodology/approach: In the first stage, constraint programming defining the relationships between variables was formulated into the objective function. A genetic algorithm model was created in the second stage to optimize capacity output. Three demand scenarios were applied to test the robustness of the proposed algorithm.Findings: CPGA improved both the machine utilization and capacity output once the minimum requirements of a demand scenario were fulfilled. Capacity outputs of the three scenarios were improved by 157%, 7%, and 69%, respectively.Research limitations/implications: The work relates to aggregate planning of machine capacity in a single case study. The constraints and constructed scenarios were therefore industry-specific.Practical implications: Capacity planning in a semiconductor manufacturing facility need to consider multiple mutually influenced constraints in resource availability, process flow and product demand. The findings prove that CPGA is a practical and an efficient alternative to optimize the capacity output and to allow the company to review its capacity with quick feedback.Originality/value: The work integrates two contemporary computational methods for a real industry application conventionally reliant on human judgement.

Stochastic Short-term High-resolution Prediction of Solar Irradiance and Photovoltaic Power Output

Energy Technology Data Exchange (ETDEWEB)

Melin, Alexander M. [ORNL; Olama, Mohammed M. [ORNL; Dong, Jin [ORNL; Djouadi, Seddik M. [ORNL; Zhang, Yichen [University of Tennessee, Knoxville (UTK), Department of Electrical Engineering and Computer Science

2017-09-01

The increased penetration of solar photovoltaic (PV) energy sources into electric grids has increased the need for accurate modeling and prediction of solar irradiance and power production. Existing modeling and prediction techniques focus on long-term low-resolution prediction over minutes to years. This paper examines the stochastic modeling and short-term high-resolution prediction of solar irradiance and PV power output. We propose a stochastic state-space model to characterize the behaviors of solar irradiance and PV power output. This prediction model is suitable for the development of optimal power controllers for PV sources. A filter-based expectation-maximization and Kalman filtering mechanism is employed to estimate the parameters and states in the state-space model. The mechanism results in a finite dimensional filter which only uses the first and second order statistics. The structure of the scheme contributes to a direct prediction of the solar irradiance and PV power output without any linearization process or simplifying assumptions of the signal’s model. This enables the system to accurately predict small as well as large fluctuations of the solar signals. The mechanism is recursive allowing the solar irradiance and PV power to be predicted online from measurements. The mechanism is tested using solar irradiance and PV power measurement data collected locally in our lab.

Fault Modeling and Testing for Analog Circuits in Complex Space Based on Supply Current and Output Voltage

Directory of Open Access Journals (Sweden)

Hongzhi Hu

2015-01-01

Full Text Available This paper deals with the modeling of fault for analog circuits. A two-dimensional (2D fault model is first proposed based on collaborative analysis of supply current and output voltage. This model is a family of circle loci on the complex plane, and it simplifies greatly the algorithms for test point selection and potential fault simulations, which are primary difficulties in fault diagnosis of analog circuits. Furthermore, in order to reduce the difficulty of fault location, an improved fault model in three-dimensional (3D complex space is proposed, which achieves a far better fault detection ratio (FDR against measurement error and parametric tolerance. To address the problem of fault masking in both 2D and 3D fault models, this paper proposes an effective design for testability (DFT method. By adding redundant bypassing-components in the circuit under test (CUT, this method achieves excellent fault isolation ratio (FIR in ambiguity group isolation. The efficacy of the proposed model and testing method is validated through experimental results provided in this paper.

High Output Piezo/Triboelectric Hybrid Generator

Science.gov (United States)

Jung, Woo-Suk; Kang, Min-Gyu; Moon, Hi Gyu; Baek, Seung-Hyub; Yoon, Seok-Jin; Wang, Zhong-Lin; Kim, Sang-Woo; Kang, Chong-Yun

2015-03-01

Recently, piezoelectric and triboelectric energy harvesting devices have been developed to convert mechanical energy into electrical energy. Especially, it is well known that triboelectric nanogenerators have a simple structure and a high output voltage. However, whereas nanostructures improve the output of triboelectric generators, its fabrication process is still complicated and unfavorable in term of the large scale and long-time durability of the device. Here, we demonstrate a hybrid generator which does not use nanostructure but generates much higher output power by a small mechanical force and integrates piezoelectric generator into triboelectric generator, derived from the simultaneous use of piezoelectric and triboelectric mechanisms in one press-and-release cycle. This hybrid generator combines high piezoelectric output current and triboelectric output voltage, which produces peak output voltage of ~370 V, current density of ~12 μA.cm-2, and average power density of ~4.44 mW.cm-2. The output power successfully lit up 600 LED bulbs by the application of a 0.2 N mechanical force and it charged a 10 μF capacitor to 10 V in 25 s. Beyond energy harvesting, this work will provide new opportunities for developing a small, built-in power source in self-powered electronics such as mobile electronics.

High Output Piezo/Triboelectric Hybrid Generator

Science.gov (United States)

Jung, Woo-Suk; Kang, Min-Gyu; Moon, Hi Gyu; Baek, Seung-Hyub; Yoon, Seok-Jin; Wang, Zhong-Lin; Kim, Sang-Woo; Kang, Chong-Yun

2015-01-01

Recently, piezoelectric and triboelectric energy harvesting devices have been developed to convert mechanical energy into electrical energy. Especially, it is well known that triboelectric nanogenerators have a simple structure and a high output voltage. However, whereas nanostructures improve the output of triboelectric generators, its fabrication process is still complicated and unfavorable in term of the large scale and long-time durability of the device. Here, we demonstrate a hybrid generator which does not use nanostructure but generates much higher output power by a small mechanical force and integrates piezoelectric generator into triboelectric generator, derived from the simultaneous use of piezoelectric and triboelectric mechanisms in one press-and-release cycle. This hybrid generator combines high piezoelectric output current and triboelectric output voltage, which produces peak output voltage of ~370 V, current density of ~12 μA·cm−2, and average power density of ~4.44 mW·cm−2. The output power successfully lit up 600 LED bulbs by the application of a 0.2 N mechanical force and it charged a 10 μF capacitor to 10 V in 25 s. Beyond energy harvesting, this work will provide new opportunities for developing a small, built-in power source in self-powered electronics such as mobile electronics. PMID:25791299

Expanded Large-Scale Forcing Properties Derived from the Multiscale Data Assimilation System and Its Application to Single-Column Models

Science.gov (United States)

Feng, S.; Li, Z.; Liu, Y.; Lin, W.; Toto, T.; Vogelmann, A. M.; Fridlind, A. M.

2013-12-01

We present an approach to derive large-scale forcing that is used to drive single-column models (SCMs) and cloud resolving models (CRMs)/large eddy simulation (LES) for evaluating fast physics parameterizations in climate models. The forcing fields are derived by use of a newly developed multi-scale data assimilation (MS-DA) system. This DA system is developed on top of the NCEP Gridpoint Statistical Interpolation (GSI) System and is implemented in the Weather Research and Forecasting (WRF) model at a cloud resolving resolution of 2 km. This approach has been applied to the generation of large scale forcing for a set of Intensive Operation Periods (IOPs) over the Atmospheric Radiation Measurement (ARM) Climate Research Facility's Southern Great Plains (SGP) site. The dense ARM in-situ observations and high-resolution satellite data effectively constrain the WRF model. The evaluation shows that the derived forcing displays accuracies comparable to the existing continuous forcing product and, overall, a better dynamic consistency with observed cloud and precipitation. One important application of this approach is to derive large-scale hydrometeor forcing and multiscale forcing, which is not provided in the existing continuous forcing product. It is shown that the hydrometeor forcing poses an appreciable impact on cloud and precipitation fields in the single-column model simulations. The large-scale forcing exhibits a significant dependency on domain-size that represents SCM grid-sizes. Subgrid processes often contribute a significant component to the large-scale forcing, and this contribution is sensitive to the grid-size and cloud-regime.

PENDUGAAN ELASTISITAS PENAWARAN OUTPUT DAN PERMINTAAN INPUT USAHATANI JAGUNG

Directory of Open Access Journals (Sweden)

Adang Agustian

2012-12-01

Full Text Available This study aims to determine the effect of changes in output and input prices, corn research expenditures and road infrastructure on output supply and input demand for corn in the Province of East Java and West Java. The data that are analyzed are those of structure of costs of corn farming in the Province of East Java and West Java in 1985-2009. Estimation model employed is the method of Seemingly Unrelated Regression. The results showed that the output supply of corn both in the province of East Java and West Java are elastic to its price changes, however it is inelastic to the price changes of: seed, urea, TSP and labor. Input demand of seed, urea, TSP and labor area inelastic to their price changes. Policy implications of this research is efforts to increase the supply of corn can be carried out by increasing its price, expenditures of corn research, and road infrastructure.

Time-response shaping using output to input saturation transformation

Science.gov (United States)

Chambon, E.; Burlion, L.; Apkarian, P.

2018-03-01

For linear systems, the control law design is often performed so that the resulting closed loop meets specific frequency-domain requirements. However, in many cases, it may be observed that the obtained controller does not enforce time-domain requirements amongst which the objective of keeping a scalar output variable in a given interval. In this article, a transformation is proposed to convert prescribed bounds on an output variable into time-varying saturations on the synthesised linear scalar control law. This transformation uses some well-chosen time-varying coefficients so that the resulting time-varying saturation bounds do not overlap in the presence of disturbances. Using an anti-windup approach, it is obtained that the origin of the resulting closed loop is globally asymptotically stable and that the constrained output variable satisfies the time-domain constraints in the presence of an unknown finite-energy-bounded disturbance. An application to a linear ball and beam model is presented.

Decentralized guaranteed cost static output feedback vibration control for piezoelectric smart structures

International Nuclear Information System (INIS)

Jiang, Jian-ping; Li, Dong-xu

2010-01-01

This paper is devoted to the study of the decentralized guaranteed cost static output feedback vibration control for piezoelectric smart structures. A smart panel with collocated piezoelectric actuators and velocity sensors is modeled using a finite element method, and then the size of the model is reduced in the state space using the modal Hankel singular value. The necessary and sufficient conditions of decentralized guaranteed cost static output feedback control for the reduced system have been presented. The decentralized and centralized static output feedback matrices can be obtained from solving two linear matrix inequalities. A comparison between centralized control and decentralized control is performed in order to investigate their effectiveness in suppressing vibration of a smart panel. Numerical results show that when the system is subjected to initial displacement or white noise disturbance, the decentralized and centralized controls are both very effective and the control results are very close

Waste Isolation Pilot Plant environmental impact report: an outline of the input--output model and the impact projections methodology. Technical document, socioeconomic portion

International Nuclear Information System (INIS)

1978-07-01

A static model in the form of a regional input-output model was constructed for Eddy and Lea Counties, New Mexico. Besides the WIPP project, the model was also used for several other projects to determine the economic impact of proposed new facilities and developments. Both private and public sectors are covered. Sub-sectors for WIPP below-ground construction, above-ground construction, and operation and transport are included

Monte Carlo modeling of small photon fields: Quantifying the impact of focal spot size on source occlusion and output factors, and exploring miniphantom design for small-field measurements

International Nuclear Information System (INIS)

Scott, Alison J. D.; Nahum, Alan E.; Fenwick, John D.

2009-01-01

The accuracy with which Monte Carlo models of photon beams generated by linear accelerators (linacs) can describe small-field dose distributions depends on the modeled width of the electron beam profile incident on the linac target. It is known that the electron focal spot width affects penumbra and cross-field profiles; here, the authors explore the extent to which source occlusion reduces linac output for smaller fields and larger spot sizes. A BEAMnrc Monte Carlo linac model has been used to investigate the variation in penumbra widths and small-field output factors with electron spot size. A formalism is developed separating head scatter factors into source occlusion and flattening filter factors. Differences between head scatter factors defined in terms of in-air energy fluence, collision kerma, and terma are explored using Monte Carlo calculations. Estimates of changes in kerma-based source occlusion and flattening filter factors with field size and focal spot width are obtained by calculating doses deposited in a narrow 2 mm wide virtual ''milliphantom'' geometry. The impact of focal spot size on phantom scatter is also explored. Modeled electron spot sizes of 0.4-0.7 mm FWHM generate acceptable matches to measured penumbra widths. However the 0.5 cm field output factor is quite sensitive to electron spot width, the measured output only being matched by calculations for a 0.7 mm spot width. Because the spectra of the unscattered primary (Ψ Π ) and head-scattered (Ψ Σ ) photon energy fluences differ, miniphantom-based collision kerma measurements do not scale precisely with total in-air energy fluence Ψ=(Ψ Π +Ψ Σ ) but with (Ψ Π +1.2Ψ Σ ). For most field sizes, on-axis collision kerma is independent of the focal spot size; but for a 0.5 cm field size and 1.0 mm spot width, it is reduced by around 7% mostly due to source occlusion. The phantom scatter factor of the 0.5 cm field also shows some spot size dependence, decreasing by 6% (relative) as

Basic study on dynamic reactive-power control method with PV output prediction for solar inverter

Directory of Open Access Journals (Sweden)

Ryunosuke Miyoshi

2016-01-01

Full Text Available To effectively utilize a photovoltaic (PV system, reactive-power control methods for solar inverters have been considered. Among the various methods, the constant-voltage control outputs less reactive power compared with the other methods. We have developed a constant-voltage control to reduce the reactive-power output. However, the developed constant-voltage control still outputs unnecessary reactive power because the control parameter is constant in every waveform of the PV output. To reduce the reactive-power output, we propose a dynamic reactive-power control method with a PV output prediction. In the proposed method, the control parameter is varied according to the properties of the predicted PV waveform. In this study, we performed numerical simulations using a distribution system model, and we confirmed that the proposed method reduces the reactive-power output within the voltage constraint.

AFSC/REFM: FEAST (Forage Euphausiid in Space and Time NPRB B.70 Model output for 1970-2009 Hindcast (Run V146), Kerim Aydin and Andre Punt

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Weekly biophysical and fish model output of FEAST. Part of The Bering Sea Project, FEAST is a high resolution (~10km2) spatial model that uses a Regional Ocean...

Super short term forecasting of photovoltaic power generation output in micro grid

Science.gov (United States)

Gong, Cheng; Ma, Longfei; Chi, Zhongjun; Zhang, Baoqun; Jiao, Ran; Yang, Bing; Chen, Jianshu; Zeng, Shuang

2017-01-01

The prediction model combining data mining and support vector machine (SVM) was built. Which provide information of photovoltaic (PV) power generation output for economic operation and optimal control of micro gird, and which reduce influence of power system from PV fluctuation. Because of the characteristic which output of PV rely on radiation intensity, ambient temperature, cloudiness, etc., so data mining was brought in. This technology can deal with large amounts of historical data and eliminate superfluous data, by using fuzzy classifier of daily type and grey related degree. The model of SVM was built, which can dock with information from data mining. Based on measured data from a small PV station, the prediction model was tested. The numerical example shows that the prediction model is fast and accurate.

Output Feedback Adaptive Control of Non-Minimum Phase Systems Using Optimal Control Modification

Science.gov (United States)

Nguyen, Nhan; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

2018-01-01

This paper describes output feedback adaptive control approaches for non-minimum phase SISO systems with relative degree 1 and non-strictly positive real (SPR) MIMO systems with uniform relative degree 1 using the optimal control modification method. It is well-known that the standard model-reference adaptive control (MRAC) cannot be used to control non-SPR plants to track an ideal SPR reference model. Due to the ideal property of asymptotic tracking, MRAC attempts an unstable pole-zero cancellation which results in unbounded signals for non-minimum phase SISO systems. The optimal control modification can be used to prevent the unstable pole-zero cancellation which results in a stable adaptation of non-minimum phase SISO systems. However, the tracking performance using this approach could suffer if the unstable zero is located far away from the imaginary axis. The tracking performance can be recovered by using an observer-based output feedback adaptive control approach which uses a Luenberger observer design to estimate the state information of the plant. Instead of explicitly specifying an ideal SPR reference model, the reference model is established from the linear quadratic optimal control to account for the non-minimum phase behavior of the plant. With this non-minimum phase reference model, the observer-based output feedback adaptive control can maintain stability as well as tracking performance. However, in the presence of the mismatch between the SPR reference model and the non-minimum phase plant, the standard MRAC results in unbounded signals, whereas a stable adaptation can be achieved with the optimal control modification. An application of output feedback adaptive control for a flexible wing aircraft illustrates the approaches.

Finding the Root Causes of Statistical Inconsistency in Community Earth System Model Output

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Milroy, D.; Hammerling, D.; Baker, A. H.

2017-12-01

Baker et al (2015) developed the Community Earth System Model Ensemble Consistency Test (CESM-ECT) to provide a metric for software quality assurance by determining statistical consistency between an ensemble of CESM outputs and new test runs. The test has proved useful for detecting statistical difference caused by compiler bugs and errors in physical modules. However, detection is only the necessary first step in finding the causes of statistical difference. The CESM is a vastly complex model comprised of millions of lines of code which is developed and maintained by a large community of software engineers and scientists. Any root cause analysis is correspondingly challenging. We propose a new capability for CESM-ECT: identifying the sections of code that cause statistical distinguishability. The first step is to discover CESM variables that cause CESM-ECT to classify new runs as statistically distinct, which we achieve via Randomized Logistic Regression. Next we use a tool developed to identify CESM components that define or compute the variables found in the first step. Finally, we employ the application Kernel GENerator (KGEN) created in Kim et al (2016) to detect fine-grained floating point differences. We demonstrate an example of the procedure and advance a plan to automate this process in our future work.

Estimation of continuous multi-DOF finger joint kinematics from surface EMG using a multi-output Gaussian Process.

Science.gov (United States)

Ngeo, Jimson; Tamei, Tomoya; Shibata, Tomohiro

2014-01-01

Surface electromyographic (EMG) signals have often been used in estimating upper and lower limb dynamics and kinematics for the purpose of controlling robotic devices such as robot prosthesis and finger exoskeletons. However, in estimating multiple and a high number of degrees-of-freedom (DOF) kinematics from EMG, output DOFs are usually estimated independently. In this study, we estimate finger joint kinematics from EMG signals using a multi-output convolved Gaussian Process (Multi-output Full GP) that considers dependencies between outputs. We show that estimation of finger joints from muscle activation inputs can be improved by using a regression model that considers inherent coupling or correlation within the hand and finger joints. We also provide a comparison of estimation performance between different regression methods, such as Artificial Neural Networks (ANN) which is used by many of the related studies. We show that using a multi-output GP gives improved estimation compared to multi-output ANN and even dedicated or independent regression models.

Discovering the energy, economic and environmental potentials of urban wastes: An input–output model for a metropolis case

International Nuclear Information System (INIS)

Song, Junnian; Yang, Wei; Li, Zhaoling; Higano, Yoshiro; Wang, Xian’en

2016-01-01

Highlights: • A waste-to-energy system is constructed incorporating various urban wastes and technologies. • Waste-to-energy industries are formed and introduced into current socioeconomic system. • A novel input–output simulation model is developed and applied to a metropolis. • Complete energy, economic and environmental potentials of urban wastes are discovered. - Abstract: Tremendous amounts of wastes are generated in urban areas due to accelerating industrialization and urbanization. The current unreasonable waste disposal patterns and potential energy value of urban wastes necessitates the promotion of waste-to-energy implementation. This study is intent on discovering the complete energy, economic and environmental potentials of urban wastes taking municipal solid wastes, waste oil, organic wastewater and livestock manure into consideration. A waste-to-energy system is constructed incorporating these wastes and five waste-to-energy technologies. A novel input–output simulation model is developed and applied to a metropolis to introduce the waste-to-energy system into the current socioeconomic system and form five waste-to-energy industries. The trends in waste generation and energy recovery potential, economic benefits and greenhouse gas mitigation contribution for the study area are estimated and explored from 2011 to 2025. By 2025, biodiesel production and power generation could amount to 72.11 thousand t and 1.59 billion kW h respectively. Due to the highest energy recovery and the most subsidies, the organic wastewater biogas industry has the highest output and net profit, followed by the waste incineration power generation industry. In total 17.97 million t (carbon dioxide-equivalent) accumulative greenhouse gas emission could be mitigated. The organic wastewater biogas industry and waste incineration power generation industry are more advantageous for the study area in terms of better energy, economic and environmental performances. The

Determining the Frequency for Load-Independent Output Current in Three-Coil Wireless Power Transfer System

Directory of Open Access Journals (Sweden)

Longzhao Sun

2015-09-01

Full Text Available Conditions for load-independent output voltage or current in two-coil wireless power transfer (WPT systems have been studied. However, analysis of load-independent output current in three-coil WPT system is still lacking in previous studies. This paper investigates the output current characteristics of a three-coil WPT system against load variations, and determines the operating frequency to achieve a constant output current. First, a three-coil WPT system is modeled by circuit theory, and the analytical expression of the root-mean-square of the output current is derived. By substituting the coupling coefficients, the quality factor, and the resonant frequency of each coil, we propose a method of calculating the frequency for load-independent output current in a three-coil WPT system, which indicates that there are two frequencies that can achieve load-independent output current. Experiments are conducted to validate these analytical results.

Measurement of Cardiac Output by Constant Injection of Radioactive Xenon

Energy Technology Data Exchange (ETDEWEB)

Kishon, Y.; Avasthey, P.; Barnett, A.; Shillingford, J. P. [MRC Cardiovascular Research Unit and Department of Medicine, Royal Postgraduate Medical School, Hammersmith Hospital, London (United Kingdom)

1971-02-15

The method of determining cardiac output by the injection of {sup 133}Xe solution has been initially tested in a suitable hydrodynamic model, simulating the cardiovascular system. The indicator was infused in a constant rate into a ''pre-ventricular'' site through a fine polyethylene tubing, and samples were taken from a ''post-ventricular'' site through similar tubing. Specific activity was determined with the use of a universal well-type scintillation counter and output values were derived from the dilutional factor of the specific activity and the rate of the infusion. Good correlation with direct output measurements were demonstrated over a wide range of outputs, stroke volumes and end-diastolic volumes. The method remained valid when either the ''pre-ventricular'' or the ''post-ventricular'' valve was made incompetent. The method was then evaluated in anaesthetized dogs and cardiac output determinations were compared with those obtained by the Fick and dye-dilution techniques. The indicator was injected into the right atrium, and samples were obtained from the pulmonary artery through similar tubings. The method was found to be reliable over a wide range of cardiac outputs (drugs- and bleeding-induced) and in the presence of severe tricuspid incompetence (performed by a valvotome). Finally, the technique was used in six patients, both at rest and after exercise, and the cardiac output values were compared with those obtained by the Fick and the photoelectric-earpiece dye-dilution techniques. It is concluded that, provided the appropriate speed of injection (about 1.5 - 3.5 {mu}Ci/sec) and the time of sampling is carefully observed, good correlation between the method under investigation and other conventional methods could be shown. This method is more convenient for repeated determinations, simpler to perform and final values are obtained almost immediately. (author)

Model outputs for each hotspot site to identify the likely environmental, economic and social effects of proposed remediation strategies

DEFF Research Database (Denmark)

Fleskens, Luuk; Irvine, Brian; Kirkby, Mike

2012-01-01

Portuguese sites) a fire severity index under current conditions and under different technologies. The DESMICE model is informed by WB3 WOCAT database records, economic WB4 experimental results, additionally requested data on spatial variability of costs and benefits, and secondary data. It applies spatially...... multiple stakeholders in very different contexts into the modelling process, in order to enhance both the realism and relevance of outputs for policy and practice; b) site-selection modelling is being applied to land degradation mitigation to enable landscape-scale assessments of the most economically....... Biophysical models (e.g. PESERA) should be able to separate immediate and gradual aspects. Ongoing degradation in the without case is not yet implicitly considered. Analysis of robustness to climatic variability and prices is also essential. Finally, factors such as attitude towards conservation and risk...

Investigation on output capacity control strategy of variable refrigerant flow air conditioning system with multi-compressor

International Nuclear Information System (INIS)

Tu, Qiu; Zou, Deqiu; Deng, Chenmian; Zhang, Jie; Hou, Lifeng; Yang, Min; Nong, Guicai; Feng, Yuhai

2016-01-01

Highlights: • The control model of compressor output capacity has been built. • The control strategy of compressor switching has been presented. • The switching process of standard compressor has been described. • The characteristics of EER and noise have been presented. • The control strategy and model have been proved by experiments. - Abstract: A set of 14 HP variable refrigerant flow air conditioning system (VRF AC) with multi-compressor has been designed, and the output capacity control strategy of compressor(s) including the switching control model of standard compressor has been built. In the output capacity control model, a certain suction pressure is used as the pressure control target to adjust the output capacity of compressors, and a little pressure fluctuation is taken into account to amend the target pressure. Furthermore, in the compressor switching control model, the most favorable operation frequency region is determined on base of the energy efficiency characteristic and noise characteristic of the compressor. And, in order to solve the large fluctuation problem of the system running and frequent ON-OFF action of the standard compressor, the equal output capacity switching principle can be used to determine the thermo-on and thermo-off switched frequency points, and control the switching process of the compressor. Experiments demonstrate the feasibility of this control strategy to ensure the stability and reliability, improve the energy efficiency and reduce the compressor noise.

Non-linear Membrane Properties in Entorhinal Cortical Stellate Cells Reduce Modulation of Input-Output Responses by Voltage Fluctuations

Science.gov (United States)

Fernandez, Fernando R.; Malerba, Paola; White, John A.

2015-01-01

The presence of voltage fluctuations arising from synaptic activity is a critical component in models of gain control, neuronal output gating, and spike rate coding. The degree to which individual neuronal input-output functions are modulated by voltage fluctuations, however, is not well established across different cortical areas. Additionally, the extent and mechanisms of input-output modulation through fluctuations have been explored largely in simplified models of spike generation, and with limited consideration for the role of non-linear and voltage-dependent membrane properties. To address these issues, we studied fluctuation-based modulation of input-output responses in medial entorhinal cortical (MEC) stellate cells of rats, which express strong sub-threshold non-linear membrane properties. Using in vitro recordings, dynamic clamp and modeling, we show that the modulation of input-output responses by random voltage fluctuations in stellate cells is significantly limited. In stellate cells, a voltage-dependent increase in membrane resistance at sub-threshold voltages mediated by Na+ conductance activation limits the ability of fluctuations to elicit spikes. Similarly, in exponential leaky integrate-and-fire models using a shallow voltage-dependence for the exponential term that matches stellate cell membrane properties, a low degree of fluctuation-based modulation of input-output responses can be attained. These results demonstrate that fluctuation-based modulation of input-output responses is not a universal feature of neurons and can be significantly limited by subthreshold voltage-gated conductances. PMID:25909971

Robust fuzzy output feedback controller for affine nonlinear systems via T-S fuzzy bilinear model: CSTR benchmark.

Science.gov (United States)

Hamdy, M; Hamdan, I

2015-07-01

In this paper, a robust H∞ fuzzy output feedback controller is designed for a class of affine nonlinear systems with disturbance via Takagi-Sugeno (T-S) fuzzy bilinear model. The parallel distributed compensation (PDC) technique is utilized to design a fuzzy controller. The stability conditions of the overall closed loop T-S fuzzy bilinear model are formulated in terms of Lyapunov function via linear matrix inequality (LMI). The control law is robustified by H∞ sense to attenuate external disturbance. Moreover, the desired controller gains can be obtained by solving a set of LMI. A continuous stirred tank reactor (CSTR), which is a benchmark problem in nonlinear process control, is discussed in detail to verify the effectiveness of the proposed approach with a comparative study. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

The UK waste input-output table: Linking waste generation to the UK economy.

Science.gov (United States)

Salemdeeb, Ramy; Al-Tabbaa, Abir; Reynolds, Christian

2016-10-01

In order to achieve a circular economy, there must be a greater understanding of the links between economic activity and waste generation. This study introduces the first version of the UK waste input-output table that could be used to quantify both direct and indirect waste arisings across the supply chain. The proposed waste input-output table features 21 industrial sectors and 34 waste types and is for the 2010 time-period. Using the waste input-output table, the study results quantitatively confirm that sectors with a long supply chain (i.e. manufacturing and services sectors) have higher indirect waste generation rates compared with industrial primary sectors (e.g. mining and quarrying) and sectors with a shorter supply chain (e.g. construction). Results also reveal that the construction, mining and quarrying sectors have the highest waste generation rates, 742 and 694 tonne per £1m of final demand, respectively. Owing to the aggregated format of the first version of the waste input-output, the model does not address the relationship between waste generation and recycling activities. Therefore, an updated version of the waste input-output table is expected be developed considering this issue. Consequently, the expanded model would lead to a better understanding of waste and resource flows in the supply chain. © The Author(s) 2016.

One output function: a misconception of students studying digital systems - a case study

Science.gov (United States)

Trotskovsky, E.; Sabag, N.

2015-05-01

Background:Learning processes are usually characterized by students' misunderstandings and misconceptions. Engineering educators intend to help their students overcome their misconceptions and achieve correct understanding of the concept. This paper describes a misconception in digital systems held by many students who believe that combinational logic circuits should have only one output. Purpose:The current study aims to investigate the roots of the misconception about one-output function and the pedagogical methods that can help students overcome the misconception. Sample:Three hundred and eighty-one students in the Departments of Electrical and Electronics and Mechanical Engineering at an academic engineering college, who learned the same topics of a digital combinational system, participated in the research. Design and method:In the initial research stage, students were taught according to traditional method - first to design a one-output combinational logic system, and then to implement a system with a number of output functions. In the main stage, an experimental group was taught using a new method whereby they were shown how to implement a system with several output functions, prior to learning about one-output systems. A control group was taught using the traditional method. In the replication stage (the third stage), an experimental group was taught using the new method. A mixed research methodology was used to examine the results of the new learning method. Results:Quantitative research showed that the new teaching approach resulted in a statistically significant decrease in student errors, and qualitative research revealed students' erroneous thinking patterns. Conclusions:It can be assumed that the traditional teaching method generates an incorrect mental model of the one-output function among students. The new pedagogical approach prevented the creation of an erroneous mental model and helped students develop the correct conceptual understanding.

Simulated and measured neutron/gamma light output distribution for poly-energetic neutron/gamma sources

Science.gov (United States)

Hosseini, S. A.; Zangian, M.; Aghabozorgi, S.

2018-03-01

In the present paper, the light output distribution due to poly-energetic neutron/gamma (neutron or gamma) source was calculated using the developed MCNPX-ESUT-PE (MCNPX-Energy engineering of Sharif University of Technology-Poly Energetic version) computational code. The simulation of light output distribution includes the modeling of the particle transport, the calculation of scintillation photons induced by charged particles, simulation of the scintillation photon transport and considering the light resolution obtained from the experiment. The developed computational code is able to simulate the light output distribution due to any neutron/gamma source. In the experimental step of the present study, the neutron-gamma discrimination based on the light output distribution was performed using the zero crossing method. As a case study, 241Am-9Be source was considered and the simulated and measured neutron/gamma light output distributions were compared. There is an acceptable agreement between the discriminated neutron/gamma light output distributions obtained from the simulation and experiment.

Directional output distance functions: endogenous directions based on exogenous normalization constraints

Science.gov (United States)

In this paper we develop a model for computing directional output distance functions with endogenously determined direction vectors. We show how this model is related to the slacks-based directional distance function introduced by Fare and Grosskopf and show how to use the slacks-based function to e...

Tourism and Economic Development in Romania: Input-Output Analysis Perspective

Directory of Open Access Journals (Sweden)

MARIUS SURUGIU

2010-12-01

Full Text Available Tourism provides a lot of opportunities for sustainable economic development. At local level, by its triggering effect it could represent a factor of economic recovery, by putting to good use the local material and human potential. By its position of predominantly final-branch, tourism exercises to a large impact on national economy by the vector of final demand, for which the possible and/or desirable variant for the future is an economic-social demand that must be satisfied by variants of total output. Using the input-output model (IO model a comparison was made of the matrix of direct technical coefficients (aij and the one of the total requirement coefficients (bij with the assistance of which the direct and propagated effects were determined for this activity by the indicators defining the dimensions of national economy.

Transport, atom blockade, and output coupling in a Tonks-Girardeau gas

International Nuclear Information System (INIS)

Rutherford, L.; McCann, J. F.; Goold, J.; Busch, Th.

2011-01-01

Recent experiments have demonstrated how quantum-mechanical impurities can be created within strongly correlated quantum gases and used to probe the coherence properties of these systems [S. Palzer, C. Zipkes, C. Sias, and M. Koehl, Phys. Rev. Lett. 103, 150601 (2009).]. Here we present a phenomenological model to simulate such an output coupler for a Tonks-Girardeau gas that shows qualitative agreement with the experimental results for atom transport and output coupling. Our model allows us to explore nonequilibrium transport phenomena in ultracold quantum gases and leads us to predict a regime of atom blockade, where the impurity component becomes localized in the parent cloud despite the presence of gravity. We show that this provides a stable mixed-species quantum gas in the strongly correlated limit.

Dynamic Output Feedback Robust Model Predictive Control via Zonotopic Set-Membership Estimation for Constrained Quasi-LPV Systems

Directory of Open Access Journals (Sweden)

Xubin Ping

2015-01-01

Full Text Available For the quasi-linear parameter varying (quasi-LPV system with bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC is investigated. The estimation error set is represented by a zonotope and refreshed by the zonotopic set-membership estimation method. By properly refreshing the estimation error set online, the bounds of true state at the next sampling time can be obtained. Furthermore, the feasibility of the main optimization problem at the next sampling time can be determined at the current time. A numerical example is given to illustrate the effectiveness of the approach.

Oil output's changing fortunes

International Nuclear Information System (INIS)

Eldridge, D.

1994-01-01

The Petroleum Economist, previously the Petroleum Press Service, has been making annual surveys of output levels of petroleum in all the oil-producing countries since its founding in 1934. This article documents trends and changes in the major oil-producing countries output from 1934 until the present. This analysis is linked with the political and historical events accompanying these changes, notably the growth of Middle Eastern oil production, the North Sea finds and most recently, Iraq's invasion of Kuwait in 1990. (UK)

DIST/AVC Out-Put Definition.

Science.gov (United States)

Wilkinson, Gene L.

The first stage of development of a management information system for DIST/AVC (Division of Instructional Technology/Audio-Visual Center) is the definition of out-put units. Some constraints on the definition of output units are: 1) they should reflect goals of the organization, 2) they should reflect organizational structure and procedures, and…

Quasi-homogeneous partial coherent source modeling of multimode optical fiber output using the elementary source method

Science.gov (United States)

Fathy, Alaa; Sabry, Yasser M.; Khalil, Diaa A.

2017-10-01

Multimode fibers (MMF) have many applications in illumination, spectroscopy, sensing and even in optical communication systems. In this work, we present a model for the MMF output field assuming the fiber end as a quasi-homogenous source. The fiber end is modeled by a group of partially coherent elementary sources, spatially shifted and uncorrelated with each other. The elementary source distribution is derived from the far field intensity measurement, while the weighting function of the sources is derived from the fiber end intensity measurement. The model is compared with practical measurements for fibers with different core/cladding diameters at different propagation distances and for different input excitations: laser, white light and LED. The obtained results show normalized root mean square error less than 8% in the intensity profile in most cases, even when the fiber end surface is not perfectly cleaved. Also, the comparison with the Gaussian-Schell model results shows a better agreement with the measurement. In addition, the complex degree of coherence, derived from the model results, is compared with the theoretical predictions of the modified Van Zernike equation showing very good agreement, which strongly supports the assumption that the large core MMF could be considered as a quasi-homogenous source.

Water resources and environmental input-output analysis and its key study issues: a review

Science.gov (United States)

YANG, Z.; Xu, X.

2013-12-01

Used to study the material and energy flow in socioeconomic system, Input-Output Analysis(IOA) had been an effective analysis tool since its appearance. The research fields of Input-Output Analysis were increasingly expanded and studied in depth with the development of fundamental theory. In this paper, starting with introduction of theory development, the water resources input-output analysis and environmental input-output analysis had been specifically reviewed, and two key study issues mentioned as well. Input-Occupancy-Output Analysis and Grey Input-Output Analysis whose proposal and development were introduced firstly could be regard as the effective complements of traditional IOA theory. Because of the hypotheses of homogeneity, stability and proportionality, Input-Occupancy-Output Analysis and Grey Input-Output Analysis always had been restricted in practical application inevitably. In the applied study aspect, with investigation of abundant literatures, research of water resources input-output analysis and environmental input-output analysis had been comprehensively reviewed and analyzed. The regional water resources flow between different economic sectors had been systematically analyzed and stated, and several types of environmental input-output analysis models combined with other effective analysis tools concluded. In two perspectives in terms of external and inland aspect, the development of water resources and environmental input-output analysis model had been explained, and several typical study cases in recent years listed respectively. By the aid of sufficient literature analysis, the internal development tendency and study hotspot had also been summarized. In recent years, Chinese literatures reporting water resources consumption analysis and virtue water study had occupied a large share. Water resources consumption analysis had always been the emphasis of inland water resources IOA. Virtue water study had been considered as the new hotspot of

A new solar power output prediction based on hybrid forecast engine and decomposition model.

Science.gov (United States)

Zhang, Weijiang; Dang, Hongshe; Simoes, Rolando

2018-06-12

Regarding to the growing trend of photovoltaic (PV) energy as a clean energy source in electrical networks and its uncertain nature, PV energy prediction has been proposed by researchers in recent decades. This problem is directly effects on operation in power network while, due to high volatility of this signal, an accurate prediction model is demanded. A new prediction model based on Hilbert Huang transform (HHT) and integration of improved empirical mode decomposition (IEMD) with feature selection and forecast engine is presented in this paper. The proposed approach is divided into three main sections. In the first section, the signal is decomposed by the proposed IEMD as an accurate decomposition tool. To increase the accuracy of the proposed method, a new interpolation method has been used instead of cubic spline curve (CSC) fitting in EMD. Then the obtained output is entered into the new feature selection procedure to choose the best candidate inputs. Finally, the signal is predicted by a hybrid forecast engine composed of support vector regression (SVR) based on an intelligent algorithm. The effectiveness of the proposed approach has been verified over a number of real-world engineering test cases in comparison with other well-known models. The obtained results prove the validity of the proposed method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Theoretical analysis of magnetic sensor output voltage

International Nuclear Information System (INIS)

Liu Haishun; Dun Chaochao; Dou Linming; Yang Weiming

2011-01-01

The output voltage is an important parameter to determine the stress state in magnetic stress measurement, the relationship between the output voltage and the difference in the principal stresses was investigated by a comprehensive application of magnetic circuit theory, magnetization theory, stress analysis as well as the law of electromagnetic induction, and a corresponding quantitative equation was derived. It is drawn that the output voltage is proportional to the difference in the principal stresses, and related to the angle between the principal stress and the direction of the sensor. This investigation provides a theoretical basis for the principle stresses measurement by output voltage. - Research highlights: → A comprehensive investigation of magnetic stress signal. → Derived a quantitative equation about output voltage and the principal stresses. → The output voltage is proportional to the difference of the principal stresses. → Provide a theoretical basis for the principle stresses measurement.

Output-based allocations and revenue recycling. Implications for the New Zealand Emissions Trading Scheme

International Nuclear Information System (INIS)

Lennox, James A.; Nieuwkoop, Renger van

2010-01-01

The New Zealand Emissions Trading Scheme (NZ ETS) is more comprehensive in its coverage of emissions than schemes introduced or proposed to date in any other country in that it includes agricultural greenhouse gases, which account for half of New Zealand's total emissions. But, motivated by concerns for the international competitiveness of emissions-intensive, trade-exposed industrial and agricultural activities, current legislation provides for substantial ongoing free allocations to such activities, linked to their output. Here we use a computable general equilibrium model to analyse the impacts of output-based allocation, given the possibility of recycling net revenues to reduce prior distorting taxes. Unlike previous modelling studies of alternative NZ ETS designs, we allow for a more realistic modelling both of capital and labour supply. We find that, as suggested by theoretical results, interactions between the ETS and existing taxes are important. Given any level of output-based allocation, the negative macroeconomic impacts can be reduced by recycling net revenues as efficiently as possible. Less obviously, we find that there may be an optimal non-zero level of output-based allocation. This optimal level increases as the carbon price and/or factor supply elasticities increase, but decreases if revenues are recycled with greater efficiency. (author)

Output-based allocations and revenue recycling. Implications for the New Zealand Emissions Trading Scheme

Energy Technology Data Exchange (ETDEWEB)

Lennox, James A. [Landcare Research NZ, Lincoln (New Zealand); Nieuwkoop, Renger van [Center for Energy Policy and Economy, Zuerich (Switzerland)

2010-12-15

The New Zealand Emissions Trading Scheme (NZ ETS) is more comprehensive in its coverage of emissions than schemes introduced or proposed to date in any other country in that it includes agricultural greenhouse gases, which account for half of New Zealand's total emissions. But, motivated by concerns for the international competitiveness of emissions-intensive, trade-exposed industrial and agricultural activities, current legislation provides for substantial ongoing free allocations to such activities, linked to their output. Here we use a computable general equilibrium model to analyse the impacts of output-based allocation, given the possibility of recycling net revenues to reduce prior distorting taxes. Unlike previous modelling studies of alternative NZ ETS designs, we allow for a more realistic modelling both of capital and labour supply. We find that, as suggested by theoretical results, interactions between the ETS and existing taxes are important. Given any level of output-based allocation, the negative macroeconomic impacts can be reduced by recycling net revenues as efficiently as possible. Less obviously, we find that there may be an optimal non-zero level of output-based allocation. This optimal level increases as the carbon price and/or factor supply elasticities increase, but decreases if revenues are recycled with greater efficiency. (author)

Firm productivity, pollution, and output: theory and empirical evidence from China.

Science.gov (United States)

Tang, Erzi; Zhang, Jingjing; Haider, Zulfiqar

2015-11-01

Using a theoretical model, this paper argues that as firm productivity increases, there is a decrease in firm-level pollution intensity. However, as productivity increases, firms tend to increase their aggregate output, which requires the use of additional resources that increase pollution. Hence, an increase in productivity results in two opposing effects where increased productivity may in fact increase pollution created by a firm. We describe the joint effect of these two mechanisms on pollution emissions as the "productivity dilemma" of pollution emission. Based on firm-level data from China, we also empirically test this productivity dilemma hypothesis. Our empirical results suggest that, in general, firm productivity has a positive and statistically significant impact on pollution emission in China. However, the impact of productivity on pollution becomes negative when we control for increases in firm output. The empirical evidence also confirms the positive influence of productivity on output, which suggests that the main determinant of pollution is the firm's output. The empirical results provide evidence of the existence of, what we describe as, the productivity dilemma of pollution emission.

Scintillation camera with improved output means

International Nuclear Information System (INIS)

Lange, K.; Wiesen, E.J.; Woronowicz, E.M.

1978-01-01

In a scintillation camera system, the output pulse signals from an array of photomultiplier tubes are coupled to the inputs of individual preamplifiers. The preamplifier output signals are coupled to circuitry for computing the x and y coordinates of the scintillations. A cathode ray oscilloscope is used to form an image corresponding with the pattern in which radiation is emitted by a body. Means for improving the uniformity and resolution of the scintillations are provided. The means comprise biasing means coupled to the outputs of selected preamplifiers so that output signals below a predetermined amplitude are not suppressed and signals falling within increasing ranges of amplitudes are increasingly suppressed. In effect, the biasing means make the preamplifiers non-linear for selected signal levels

Multi-regional input–output model and ecological network analysis for regional embodied energy accounting in China

International Nuclear Information System (INIS)

Zhang, Yan; Zheng, Hongmei; Yang, Zhifeng; Su, Meirong; Liu, Gengyuan; Li, Yanxian

2015-01-01

Chinese regions frequently exchange materials, but regional differences in economic development create unbalanced flows of these resources. In this study, we examined energy by assessing embodied energy consumption to describe the energy-flow structure in China's seven regions. Based on multi-regional monetary input–output tables and energy statistical yearbooks for Chinese provinces in 2002 and 2007, we accounted for both direct and indirect energy consumption, respectively, and the integral input and output of the provinces. Most integral inputs of energy flowed from north to south or from east to west, whereas integral output flows were mainly from northeast to southwest. This differed from the direct flows, which were predominantly from north to south and west to east. This demonstrates the importance of calculating both direct and indirect energy flows. Analysis of the distance and direction traveled by the energy consumption centers of gravity showed that the centers for embodied energy consumption and inputs moved southeast because of the movements of the centers of the Eastern region. However, the center for outputs moved northeast because the movement of the Central region. These analyses provide a basis for identifying how regional economic development policies influence the embodied energy consumption and its flows among regions. - Highlights: • We integrated multi-regional input–output analysis with ecological network analysis. • We accounted for both direct and indirect energy consumption. • The centers of gravity for embodied energy flows moved southeast from 2002 to 2007. • The results support planning of energy consumption and energy flows among regions.

Generic uncertainty model for DETRA for environmental consequence analyses. Application and sample outputs

International Nuclear Information System (INIS)

Suolanen, V.; Ilvonen, M.

1998-10-01

Computer model DETRA applies a dynamic compartment modelling approach. The compartment structure of each considered application can be tailored individually. This flexible modelling method makes it possible that the transfer of radionuclides can be considered in various cases: aquatic environment and related food chains, terrestrial environment, food chains in general and food stuffs, body burden analyses of humans, etc. In the former study on this subject, modernization of the user interface of DETRA code was carried out. This new interface works in Windows environment and the usability of the code has been improved. The objective of this study has been to further develop and diversify the user interface so that also probabilistic uncertainty analyses can be performed by DETRA. The most common probability distributions are available: uniform, truncated Gaussian and triangular. The corresponding logarithmic distributions are also available. All input data related to a considered case can be varied, although this option is seldomly needed. The calculated output values can be selected as monitored values at certain simulation time points defined by the user. The results of a sensitivity run are immediately available after simulation as graphical presentations. These outcomes are distributions generated for varied parameters, density functions of monitored parameters and complementary cumulative density functions (CCDF). An application considered in connection with this work was the estimation of contamination of milk caused by radioactive deposition of Cs (10 kBq(Cs-137)/m 2 ). The multi-sequence calculation model applied consisted of a pasture modelling part and a dormant season modelling part. These two sequences were linked periodically simulating the realistic practice of care taking of domestic animals in Finland. The most important parameters were varied in this exercise. The performed diversifying of the user interface of DETRA code seems to provide an easily

Output-based allocation as a form of protection for internationally competitive industries

International Nuclear Information System (INIS)

Haites, Erik

2003-12-01

Policies adopted by Annex B Parties to reduce their greenhouse gas (GHG) emissions are likely to increase costs for industries vulnerable to international competition in domestic or export markets. Domestic emissions trading, by enabling the aggregate emissions target to be met at least cost, helps to reduce the adverse impacts on these industries. An output-based allocation of allowances reduces the output decline due to imposition of the emissions trading program relative to a lump-sum (historic) allocation and so helps reduce the adverse impacts on these industries. The effectiveness of an output-based allocation in maintaining production must be assessed empirically because it depends on the characteristics of all of the firms covered by the trading program as well as other factors. Modeling results for a possible emissions trading program for Alberta confirm the expected impacts of an output-based allocation and indicate that the effectiveness varies across industries. While encouraging greater production, an output-based allocation lowers profits relative to a lump-sum allocation and leads to a different distribution of costs. Other policy options for reducing the output decline in industries vulnerable to international competition include lump-sum allocations or auctioned allowances combined with assistance programs for emission reduction actions or a requirement to meet 'world best' emission performance standard. These policy options should be compared with an output-based allocation in terms of effectiveness, total cost and other impacts, before a policy is adopted

Monte Carlo based electron treatment planning and cutout output factor calculations

Science.gov (United States)

Mitrou, Ellis

Electron radiotherapy (RT) offers a number of advantages over photons. The high surface dose, combined with a rapid dose fall-off beyond the target volume presents a net increase in tumor control probability and decreases the normal tissue complication for superficial tumors. Electron treatments are normally delivered clinically without previously calculated dose distributions due to the complexity of the electron transport involved and greater error in planning accuracy. This research uses Monte Carlo (MC) methods to model clinical electron beams in order to accurately calculate electron beam dose distributions in patients as well as calculate cutout output factors, reducing the need for a clinical measurement. The present work is incorporated into a research MC calculation system: McGill Monte Carlo Treatment Planning (MMCTP) system. Measurements of PDDs, profiles and output factors in addition to 2D GAFCHROMICRTM EBT2 film measurements in heterogeneous phantoms were obtained to commission the electron beam model. The use of MC for electron TP will provide more accurate treatments and yield greater knowledge of the electron dose distribution within the patient. The calculation of output factors could invoke a clinical time saving of up to 1 hour per patient.

A stock-flow consistent input-output model with applications to energy price shocks, interest rates, and heat emissions

Science.gov (United States)

Berg, Matthew; Hartley, Brian; Richters, Oliver

2015-01-01

By synthesizing stock-flow consistent models, input-output models, and aspects of ecological macroeconomics, a method is developed to simultaneously model monetary flows through the financial system, flows of produced goods and services through the real economy, and flows of physical materials through the natural environment. This paper highlights the linkages between the physical environment and the economic system by emphasizing the role of the energy industry. A conceptual model is developed in general form with an arbitrary number of sectors, while emphasizing connections with the agent-based, econophysics, and complexity economics literature. First, we use the model to challenge claims that 0% interest rates are a necessary condition for a stationary economy and conduct a stability analysis within the parameter space of interest rates and consumption parameters of an economy in stock-flow equilibrium. Second, we analyze the role of energy price shocks in contributing to recessions, incorporating several propagation and amplification mechanisms. Third, implied heat emissions from energy conversion and the effect of anthropogenic heat flux on climate change are considered in light of a minimal single-layer atmosphere climate model, although the model is only implicitly, not explicitly, linked to the economic model.

Linear summation of outputs in a balanced network model of motor cortex.

Science.gov (United States)

Capaday, Charles; van Vreeswijk, Carl

2015-01-01

Given the non-linearities of the neural circuitry's elements, we would expect cortical circuits to respond non-linearly when activated. Surprisingly, when two points in the motor cortex are activated simultaneously, the EMG responses are the linear sum of the responses evoked by each of the points activated separately. Additionally, the corticospinal transfer function is close to linear, implying that the synaptic interactions in motor cortex must be effectively linear. To account for this, here we develop a model of motor cortex composed of multiple interconnected points, each comprised of reciprocally connected excitatory and inhibitory neurons. We show how non-linearities in neuronal transfer functions are eschewed by strong synaptic interactions within each point. Consequently, the simultaneous activation of multiple points results in a linear summation of their respective outputs. We also consider the effects of reduction of inhibition at a cortical point when one or more surrounding points are active. The network response in this condition is linear over an approximately two- to three-fold decrease of inhibitory feedback strength. This result supports the idea that focal disinhibition allows linear coupling of motor cortical points to generate movement related muscle activation patterns; albeit with a limitation on gain control. The model also explains why neural activity does not spread as far out as the axonal connectivity allows, whilst also explaining why distant cortical points can be, nonetheless, functionally coupled by focal disinhibition. Finally, we discuss the advantages that linear interactions at the cortical level afford to motor command synthesis.

A new measure of output ranking performance in automatic document retrieval systems

International Nuclear Information System (INIS)

Ebinuma, Yukio

1987-01-01

A new measure of output ranking performance is proposed on the basis of recall-precision pairs corresponding to ranks of relevant documents when documents are arranged in decreasing order of their scores given by a ranking function. This measure is constructed to take a single value in starting from the area under a recall-precision graph for a ranked output and to distinguish meaningful ranking with a positive value between 0 and 1 from meaningless ranking with a negative value. It is clarified too that the measure must be useful in practice to evaluate the ranking performance made by various ranking function models and to choose the best ranking models among them. (author)

Redesign lifts prep output 288%

Energy Technology Data Exchange (ETDEWEB)

Hamric, J

1987-02-01

This paper outlines the application of engineering creativity and how it brought output at an Ohio coal preparation plant up from 12,500 tpd to nearly four times that figure, 48,610 tpd. By streamlining the conveyor systems, removing surplus belt length and repositioning subplants the whole operation was able to run far more efficiently with a greater output. Various other alterations including the raw material supply and management and operating practices were also undertaken to provide a test for the achievements possible with such reorganization. The new developments have been in the following fields: fine coal cleaning, heavy media cyclones, feeders, bins, filter presses, dewatering equipment and settling tanks. Output is now limited only by the reduced demand by the Gavin power station nearby.

Selection Input Output by Restriction Using DEA Models Based on a Fuzzy Delphi Approach and Expert Information

Science.gov (United States)

Arsad, Roslah; Nasir Abdullah, Mohammad; Alias, Suriana; Isa, Zaidi

2017-09-01

Stock evaluation has always been an interesting problem for investors. In this paper, a comparison regarding the efficiency stocks of listed companies in Bursa Malaysia were made through the application of estimation method of Data Envelopment Analysis (DEA). One of the interesting research subjects in DEA is the selection of appropriate input and output parameter. In this study, DEA was used to measure efficiency of stocks of listed companies in Bursa Malaysia in terms of the financial ratio to evaluate performance of stocks. Based on previous studies and Fuzzy Delphi Method (FDM), the most important financial ratio was selected. The results indicated that return on equity, return on assets, net profit margin, operating profit margin, earnings per share, price to earnings and debt to equity were the most important ratios. Using expert information, all the parameter were clarified as inputs and outputs. The main objectives were to identify most critical financial ratio, clarify them based on expert information and compute the relative efficiency scores of stocks as well as rank them in the construction industry and material completely. The methods of analysis using Alirezaee and Afsharian’s model were employed in this study, where the originality of Charnes, Cooper and Rhodes (CCR) with the assumption of Constant Return to Scale (CSR) still holds. This method of ranking relative efficiency of decision making units (DMUs) was value-added by the Balance Index. The interested data was made for year 2015 and the population of the research includes accepted companies in stock markets in the construction industry and material (63 companies). According to the ranking, the proposed model can rank completely for 63 companies using selected financial ratio.

Simulation of the output power of copper bromide lasers by the MARS method

International Nuclear Information System (INIS)

Iliev, I P; Voynikova, D S; Gocheva-Ilieva, S G

2012-01-01

The dependence of the output power of CuBr lasers (operating at wavelengths of 510.6 and 578.2 nm) on ten input physical parameters has been statistically analysed based on a large amount of experimental data accumulated for these lasers. Regression models have been built using the flexible nonparametric method of multivariate adaptive regression splines (MARS) to describe both linear and nonlinear local dependences. These models cover more than 97% initial data with an error comparable with the experimental error; they are applied to estimate and predict the output powers of both existing and future lasers. The advantage of the models constructed for estimating laser parameters over the standard parametric methods of multivariate factor and regression analysis is demonstrated.

Output controllability of nonlinear systems with bounded control

International Nuclear Information System (INIS)

Garcia, Rafael; D'Attellis, Carlos

1990-01-01

The control problem treated in this paper is the output controllability of a nonlinear system in the form: x = f(x) + g(x)u(t); y = h(x), using bounded controls. The approach to the problem consists of a modification in the system using dynamic feedback in such a way that the input/output behaviour of the closed loop matches the input/output behaviour of a completely output-controllable system with bounded controls. Sufficient conditions are also put forward on the system so that a compact set in the output space may be reached in finite time using uniformally bounded controls, and a result on output regulation in finite time with asymptotic state stabilization is obtained. (Author)

A Monte Carlo Study on Multiple Output Stochastic Frontiers

DEFF Research Database (Denmark)

Henningsen, Géraldine; Henningsen, Arne; Jensen, Uwe

, dividing all other output quantities by the selected output quantity, and using these ratios as regressors (OD). Another approach is the stochastic ray production frontier (SR) which transforms the output quantities into their Euclidean distance as the dependent variable and their polar coordinates......In the estimation of multiple output technologies in a primal approach, the main question is how to handle the multiple outputs. Often an output distance function is used, where the classical approach is to exploit its homogeneity property by selecting one output quantity as the dependent variable...... of both specifications for the case of a Translog output distance function with respect to different common statistical problems as well as problems arising as a consequence of zero values in the output quantities. Although, our results partly show clear reactions to statistical misspecifications...

Output synchronization control of ship replenishment operations: theory and experiments

NARCIS (Netherlands)

Kyrkjebø, E.; Pettersen, K.Y.; Wondergem, M.; Nijmeijer, H.

2007-01-01

A leader–follower synchronization output feedback control scheme is presented for the ship replenishment problem where only positions are measured. No mathematical model of the leader ship is required, and the control scheme relies on nonlinear observers to estimate velocity and acceleration of all

Public Infrastructure Investment, Output Dynamics, and Balanced Budget Fiscal Rules

NARCIS (Netherlands)

Duarte Bom, P.R.; Ligthart, J.E.

2011-01-01

We study the dynamic output and welfare effects of public infrastructure investment under a balanced budget fiscal rule, using an overlapping generations model of a small open economy. The government finances public investment by employing distortionary labor taxes. We find a negative short-run

The use of output-dependent data scaling with artificial neural networks and multilinear regression for modeling of ciprofloxacin removal from aqueous solution

Directory of Open Access Journals (Sweden)

Ulaş Yurtsever

2017-03-01

Full Text Available In this study, an experimental system entailing ciprofloxacin hydrochloride (CIP removal from aqueous solution is modeled by using artificial neural networks (ANNs. For modeling of CIP removal from aqueous solution using bentonite and activated carbon, we utilized the combination of output-dependent data scaling (ODDS with ANN, and the combination of ODDS with multivariable linear regression model (MVLR. The ANN model normalized via ODDS performs better in comparison with the ANN model scaled via standard normalization. Four distinct hybrid models, ANN with standard normalization, ANN with ODDS, MVLR with standard normalization, and MVLR with ODDS, were also applied. We observed that ANN and MVLR estimations’ consistency, accuracy ratios and model performances increase as a result of pre-processing with ODDS.

The economic impacts of Lake States forestry: an input-output study.

Science.gov (United States)

Larry Pedersen; Daniel E. Chappelle; David C. Lothner

1989-01-01

The report describes 1985 and 1995 levels of forest-related economic activity in the three-state area of Michigan, Minnesota, and Wisconsin, and their impacts on other economic sectors based on a regional input-output model.

Experimental and theoretical analysis of cell module output performance for a thermophotovoltaic system

International Nuclear Information System (INIS)

Xu, Xiaojie; Ye, Hong; Xu, Yexin; Shen, Mingrong; Zhang, Xiaojing; Wu, Xi

2014-01-01

Highlights: • An accurate theoretical model for thermophotovoltaic system is constructed. • Parallel connected module is superior if radiator temperature is uneven. • Series connected module is superior if cell temperature is uneven. • Short circuit current of series module rises when the shunt resistance decreases. • Fill factor is not always accurate to evaluate the module performance. - Abstract: An experimental thermophotovoltaic (TPV) system with a cylindrical-geometry radiator was established to test the output performances of modules under different conditions. The results demonstrate that the output performance of a cell module decreases when the combustion power increases because of the uneven temperature of the radiator or cells. On this basis, a theoretical model for a TPV system was constructed to compare the performance under different conditions of the series-connected (SC) module and the parallel-connected (PC) module, and was verified by the experimental results. The influences of the temperature gradient of the radiator or the cell module, and the series and shunt resistance of the TPV cell on the module performance were analyzed in detail. The results demonstrate that the PC module can effectively reduce the mismatch loss of output power caused by the uneven radiator temperature. The PC module, for instance, has a maximum output power of 2.54 times higher than that of the SC module when the radiator temperature difference is 500 K. However, the output performance of the module connected in series is superior to the PC module while the cell temperature is non-uniform. The output power of the SC module is 9.93% higher than that of the PC module at the cell temperature difference of 125 K. The short circuit current of the SC module is sensitive to the series and shunt resistance if the radiator temperature distribution is non-uniform. As the shunt resistance falls from ∞ to 0.5 Ω, the current varies from 1.757 A to 4.488 A when the

Towards Measures to Establish the Relevance of Climate Model Output for Decision Support

Science.gov (United States)

Clarke, L.; Smith, L. A.

2007-12-01

to weight climate model output in the decision process; one obvious example is the question of over what spatial and time averages modelers expect information in current climate distributions to be robust. The IPCC itself suggests continental/seasonal, while distributions over 10's of kilometers/hourly is on offer. Our aim here is not to resolve this discrepancy, but to develop methods with which it can be addressed. This is illustrated in the context of using another physically based, imperfect model setting: using Newton's laws in an actual case of NASA hazard evaluation. Our aim is to develop transparent standards of good practice managing expectations, which will allow model improvements over the next decades to be seen as progress by the users of climate science.

Fast multi-output relevance vector regression

OpenAIRE

Ha, Youngmin

2017-01-01

This paper aims to decrease the time complexity of multi-output relevance vector regression from O(VM^3) to O(V^3+M^3), where V is the number of output dimensions, M is the number of basis functions, and V

Comparison of aerosol effects on simulated spring and summer hailstorm clouds

Science.gov (United States)

Yang, Huiling; Xiao, Hui; Guo, Chunwei; Wen, Guang; Tang, Qi; Sun, Yue

2017-07-01

Numerical simulations are carried out to investigate the effect of cloud condensation nuclei (CCN) concentrations on microphysical processes and precipitation characteristics of hailstorms. Two hailstorm cases are simulated, a spring case and a summer case, in a semiarid region of northern China, with the Regional Atmospheric Modeling System. The results are used to investigate the differences and similarities of the CCN effects between spring and summer hailstorms. The similarities are: (1) The total hydrometeor mixing ratio decreases, while the total ice-phase mixing ratio enhances, with increasing CCN concentration; (2) Enhancement of the CCN concentration results in the production of a greater amount of small-sized hydrometeor particles, but a lessening of large-sized hydrometeor particles; (3) As the CCN concentration increases, the supercooled cloud water and rainwater make a lesser contribution to hail, while the ice-phase hydrometeors take on active roles in the growth of hail; (4) When the CCN concentration increases, the amount of total precipitation lessens, while the role played by liquid-phase rainfall in the amount of total precipitation reduces, relatively, compared to that of ice-phase precipitation. The differences between the two storms include: (1) An increase in the CCN concentration tends to reduce pristine ice mixing ratios in the spring case but enhance them in the summer case; (2) Ice-phase hydrometeor particles contribute more to hail growth in the spring case, while liquid water contributes more in the summer case; (3) An increase in the CCN concentration has different effects on surface hail precipitation in different seasons.

Evaluation of scientific output in Dentistry in Spanish Universities.

Science.gov (United States)

De la Flor-Martínez, M; Galindo-Moreno, P; Sánchez-Fernández, E; Abadal, E; Cobo, M-J; Herrera-Viedma, E

2017-07-01

The aim of this study was to assess the scientific output of Spanish universities that offer a bachelor's degree in dentistry through the use of various bibliometric indicators. A total of 21 universities offered a bachelor's degree in dentistry in academic year 2016-2017. The search for papers published by authors associated with these institutions was carried out using the selection of journals listed in the Journal Citation Reports (JCR) and the Web of Knowledge database for the period 1986-2017. On the basis of these data, we determined the output, the h-, g- and hg-indexes, the most productive authors, international collaborations, and the most relevant journals. Public universities obtained better results than private universities. The University of Valencia was ranked first, followed by the Complutense University of Madrid and the University of Granada. The most productive author was José Vicente Bagán, but the author with the highest h-index was Mariano Sanz and Manuel Toledado. The universities with the greatest output and highest citation rates had more international collaborations. The most developed fields in Spanish universities were Oral surgery, Oral medicine and Dental materials. The universities had different models of production. At universities such as Barcelona or Valencia, the production was focused on very few departments and authors. At the other extreme, the University of Granada had various sources of research and authors, which meant that its output and citation rate could increase more. University faculties must provide suitable academic and research training, and therefore must be assessed using objective criteria and bibliometric tools. Although the number of university schools and faculties that teach dentistry has increased, and particularly the number of private universities, there is no correlation between their quality and output and the number of places offered on their courses.

Stimulation of Respiratory Motor Output and Ventilation in a Murine Model of Pompe Disease by Ampakines.

Science.gov (United States)

ElMallah, Mai K; Pagliardini, Silvia; Turner, Sara M; Cerreta, Anthony J; Falk, Darin J; Byrne, Barry J; Greer, John J; Fuller, David D

2015-09-01

Pompe disease results from a mutation in the acid α-glucosidase gene leading to lysosomal glycogen accumulation. Respiratory insufficiency is common, and the current U.S. Food and Drug Administration-approved treatment, enzyme replacement, has limited effectiveness. Ampakines are drugs that enhance α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor responses and can increase respiratory motor drive. Recent work indicates that respiratory motor drive can be blunted in Pompe disease, and thus pharmacologic stimulation of breathing may be beneficial. Using a murine Pompe model with the most severe clinical genotype (the Gaa(-/-) mouse), our primary objective was to test the hypothesis that ampakines can stimulate respiratory motor output and increase ventilation. Our second objective was to confirm that neuropathology was present in Pompe mouse medullary respiratory control neurons. The impact of ampakine CX717 on breathing was determined via phrenic and hypoglossal nerve recordings in anesthetized mice and whole-body plethysmography in unanesthetized mice. The medulla was examined using standard histological methods coupled with immunochemical markers of respiratory control neurons. Ampakine CX717 robustly increased phrenic and hypoglossal inspiratory bursting and reduced respiratory cycle variability in anesthetized Pompe mice, and it increased inspiratory tidal volume in unanesthetized Pompe mice. CX717 did not significantly alter these variables in wild-type mice. Medullary respiratory neurons showed extensive histopathology in Pompe mice. Ampakines stimulate respiratory neuromotor output and ventilation in Pompe mice, and therefore they have potential as an adjunctive therapy in Pompe disease.

Estimating direct and indirect rebound effects by supply-driven input-output model: A case study of Taiwan's industry

International Nuclear Information System (INIS)

Wu, Kuei-Yen; Wu, Jung-Hua; Huang, Yun-Hsun; Fu, Szu-Chi; Chen, Chia-Yon

2016-01-01

Most existing literature focuses on the direct rebound effect on the demand side for consumers. This study analyses direct and indirect rebound effects in Taiwan's industry from the perspective of producers. However, most studies on the producers' viewpoint may overlook inter-industry linkages. This study applies a supply-driven input-output model to quantify the magnitude of rebound effects by explicitly considering inter-industry linkages. Empirical results showed that total rebound effects for most Taiwan's sectors were less than 10% in 2011. A comparison among the sectors yields that sectors with lower energy efficiency had higher direct rebound effects, while sectors with higher forward linkages generated higher indirect rebound effects. Taking the Mining sector (S3) as an example, which is an upstream supplier and has high forward linkages; it showed high indirect rebound effects that are derived from the accumulation of additional energy consumption by its downstream producers. The findings also showed that in almost all sectors, indirect rebound effects were higher than direct rebound effects. In other words, if indirect rebound effects are neglected, the total rebound effects will be underestimated. Hence, the energy-saving potential may be overestimated. - Highlights: • This study quantifies rebound effects by a supply-driven input-output model. • For most Taiwan's sectors, total rebound magnitudes were less than 10% in 2011. • Direct rebound effects and energy efficiency were inverse correlation. • Indirect rebound effects and industrial forward linkages were positive correlation. • Indirect rebound effects were generally higher than direct rebound effects.

Output levels of commercially available portable compact disc players and the potential risk to hearing.

Science.gov (United States)

Fligor, Brian J; Cox, L Clarke

2004-12-01

To measure the sound levels generated by the headphones of commercially available portable compact disc players and provide hearing healthcare providers with safety guidelines based on a theoretical noise dose model. Using a Knowles Electronics Manikin for Acoustical Research and a personal computer, output levels across volume control settings were recorded from headphones driven by a standard signal (white noise) and compared with output levels from music samples of eight different genres. Many commercially available models from different manufacturers were investigated. Several different styles of headphones (insert, supra-aural, vertical, and circumaural) were used to determine if style of headphone influenced output level. Free-field equivalent sound pressure levels measured at maximum volume control setting ranged from 91 dBA to 121 dBA. Output levels varied across manufacturers and style of headphone, although generally the smaller the headphone, the higher the sound level for a given volume control setting. Specifically, in one manufacturer, insert earphones increased output level 7-9 dB, relative to the output from stock headphones included in the purchase of the CD player. In a few headphone-CD player combinations, peak sound pressure levels exceeded 130 dB SPL. Based on measured sound pressure levels across systems and the noise dose model recommended by National Institute for Occupational Safety and Health for protecting the occupational worker, a maximum permissible noise dose would typically be reached within 1 hr of listening with the volume control set to 70% of maximum gain using supra-aural headphones. Using headphones that resulted in boosting the output level (e.g., insert earphones used in this study) would significantly decrease the maximum safe volume control setting; this effect was unpredictable from one manufacturer to another. In the interest of providing a straightforward recommendation that should protect the hearing of the majority of

Comparison of Laboratory Experimental Data to XBeach Numerical Model Output

Science.gov (United States)

Demirci, Ebru; Baykal, Cuneyt; Guler, Isikhan; Sogut, Erdinc

2016-04-01

generating data sets for testing and validation of sediment transport relationships for sand transport in the presence of waves and currents. In these series, there is no structure in the basin. The second and third series of experiments were designed to generate data sets for development of tombolos in the lee of detached 4m-long rubble mound breakwater that is 4 m from the initial shoreline. The fourth series of experiments are conducted to investigate tombolo development in the lee of a 4m-long T-head groin with the head section in the same location of the second and the third tests. The fifth series of experiments are used to investigate tombolo development in the lee of a 3-m-long rubble-mound breakwater positioned 1.5 m offshore of the initial shoreline. In this study, the data collected from the above mentioned five experiments are used to compare the results of the experimental data with XBeach numerical model results, both for the "no-structure" and "with-structure" cases regarding to sediment transport relationships in the presence of only waves and currents as well as the shoreline changes together with the detached breakwater and the T-groin. The main purpose is to investigate the similarities and differences between the laboratory experimental data behavior with XBeach numerical model outputs for these five cases. References: Baykal, C., Sogut, E., Ergin, A., Guler, I., Ozyurt, G.T., Guler, G., and Dogan, G.G. (2015). Modelling Long Term Morphological Changes with XBeach: Case Study of Kızılırmak River Mouth, Turkey, European Geosciences Union, General Assembly 2015, Vienna, Austria, 12-17 April 2015. Gravens, M.B. and Wang, P. (2007). "Data report: Laboratory testing of longshore sand transport by waves and currents; morphology change behind headland structures." Technical Report, ERDC/CHL TR-07-8, Coastal and Hydraulics Laboratory, US Army Engineer Research and Development Center, Vicksburg, MS. Roelvink, D., Reniers, A., van Dongeren, A., van Thiel de

Nonlinear Output Feedback Control of Underwater Vehicle Propellers using Advance Speed Feedback

DEFF Research Database (Denmark)

Fossen, T.I.; Blanke, M.

1999-01-01

More accurate propeller shaft speed controllers can be designed by using nonlinear control theory. In this paper, an output feedback controller reconstructing the advance speed (speed of water going into the propeller) from vehicle speed measurements is derived. For this purpose a three-state model...... minimizes thruster losses due to variations in propeller axial inlet flow which is a major problem when applying conventional vehicle-propeller control systems. The proposed controller is simulated for an underwater vehicle equipped with a single propeller. From the simulations it can be concluded...... of propeller shaft speed, forward (surge) speed of the vehicle and axial inlet flow of the propeller is applied. A nonlinear observer in combination with an output feedback integral controller are derived by applying Lyapunov stability theory and exponential stability is proven. The output feedback controller...

Waste Isolation Pilot Plant environmental impact report: socioeconomic portion. An outline of the input-output model and the impact projections methodology

International Nuclear Information System (INIS)

1978-07-01

A static model in the form of a regional input-output model was constructed for Eddy and Lea Counties, New Mexico. This modeling process has been used to assess the economic impacts of the following activities and for the following agencies: San Juan Generating Units Nos. 1, 3, and 4 for Public Service Company of New Mexico, and general economic impacts (an ongoing process) for the Bureau of Business and Economic Research, University of New Mexico. The regional modeling process adjusts a national model by means of location quotients and aggregating techniques. The national model, or base model, used in this process contains 407 economic categories or subsectors of the economy, 389 of which represent the private economy, and 18 of which represent activities mostly dealing with the public sector. The 389 identified sub-sectors were used in the modeling process; the government impact was computed after the private sector analysis

Characterization and modeling of the magnetic field-induced strain and work output in Ni2MnGa magnetic shape memory alloys

International Nuclear Information System (INIS)

Kiefer, B.; Karaca, H.E.; Lagoudas, D.C.; Karaman, I.

2007-01-01

This paper is concerned with the experimental characterization and the constitutive modeling of magnetic shape memory alloys (MSMA), in terms of their applicability as actuator materials. The key properties that determine the actuation characteristics are the magnetic field-induced strain (MFIS) and the blocking stress. With the goal of increasing the corresponding actuation output, a material selection strategy was followed which was aimed at obtaining a higher magnetocrystalline anisotropy energy, while keeping the detwinning stress low. This was achieved by choosing a composition in which the separation of the Curie temperature and the martensitic transformation temperatures was large, and then selecting an operating temperature just below the phase transformation temperature. In the selected Ni 51.1 Mn 24.0 Ga 24.9 composition a more than 50% increase of the actuation work output was observed, compared to corresponding data reported in the literature for other off-stoichiometric compositions of the Ni 2 MnGa intermetallic compound. The second part of the paper describes a phenomenological constitutive model that predicts the MFIS hysteresis curves observed in the first part. The model is concerned with the field-induced reorientation of martensitic variants and changes in the magnetic microstructure. Dissipative effects are captured by introducing internal state variables into the free energy function. In its most general form the contributing energy terms are the elastic strain energy, the Zeeman energy, the magnetocrystalline anisotropy energy and appropriate mixing terms. Typical loading cases are considered and the accuracy of the model predictions is evaluated by comparison with the experimental data presented in the first part of this work

Economic and Environmental Impacts of Dietary Changes in Iran: An Input-Output Analysis

Directory of Open Access Journals (Sweden)

Roham Rahmani

2012-03-01

Full Text Available  Iran's simple and environmentally extended commodity by commodity input-output (IO model was used to determine the impacts of dietary changes on the Iranian economy and on the environmental load. The original model is based on the status-quo diet and was modified to include the World Health Organization (WHO, the World Cancer Research Fund (WCRF and Mediterranean alternative dietary scenarios. A range of impacts occurred depending upon the relative changes in food items. The direction of changes was similar in the three alternative scenarios. The greatest and smallest impact occurred in the WHO and the Mediterranean scenarios respectively. Total changes in output in WHO, WCRF and Mediterranean dietary scenarios were calculated to be 7010.1, 4802.8 and 3330.8 billion Rials respectively. The outputs of rice, vegetables, fruit, bread and macaroni decreased, but those of live and other animal products increased. The output of non-food commodities and services increased as well. The environmental load increased for three dietary scenarios in comparison with the status-quo diet. The greatest and smallest environmental load occurred in WHO and Mediterranean dietary scenarios respectively. Thus, although dietary changes can have positive effects on economic output, in order to avoid negative environmental effects, it is necessary to consider strategies such as applying capabilities, particularly natural resources in an optimal healthy and environmentally diet, planning for improving forest covering and green space simultaneously with increasing economic activities and using indirect incentives, such as taxes and insurance, for promoting sustainable and healthy foods and reducing greenhouse gas emissions.

Possible factors determining the non-linearity in the VO2-power output relationship in humans: theoretical studies.

Science.gov (United States)

Korzeniewski, Bernard; Zoladz, Jerzy A

2003-08-01

At low power output exercise (below lactate threshold), the oxygen uptake increases linearly with power output, but at high power output exercise (above lactate threshold) some additional oxygen consumption causes a non-linearity in the overall VO(2) (oxygen uptake rate)-power output relationship. The functional significance of this phenomenon for human exercise tolerance is very important, but the mechanisms underlying it remain unknown. In the present work, a computer model of oxidative phosphorylation in intact skeletal muscle developed previously is used to examine the background of this relationship in different modes of exercise. Our simulations demonstrate that the non-linearity in the VO(2)-power output relationship and the difference in the magnitude of this non-linearity between incremental exercise mode and square-wave exercise mode (constant power output exercise) can be generated by introducing into the model some hypothetical factor F (group of associated factors) that accumulate(s) in time during exercise. The performed computer simulations, based on this assumption, give proper time courses of changes in VO(2) and [PCr] after an onset of work of different intensities, including the slow component in VO(2), well matching the experimental results. Moreover, if it is assumed that the exercise terminates because of fatigue when the amount/intensity of F exceed some threshold value, the model allows the generation of a proper shape of the well-known power-duration curve. This fact suggests that the phenomenon of the non-linearity of the VO(2)-power output relationship and the magnitude of this non-linearity in different modes of exercise is determined by some factor(s) responsible for muscle fatigue.

Output Control Using Feedforward And Cascade Controllers

Science.gov (United States)

Seraji, Homayoun

1990-01-01

Report presents theoretical study of open-loop control elements in single-input, single-output linear system. Focus on output-control (servomechanism) problem, in which objective is to find control scheme that causes output to track certain command inputs and to reject certain disturbance inputs in steady state. Report closes with brief discussion of characteristics and relative merits of feedforward, cascade, and feedback controllers and combinations thereof.

Correlation between renew able energy source's energy output and load

International Nuclear Information System (INIS)

Ali, G.H.M.; El-Zeftawy, A.A.

1996-01-01

The common problem to all renew energy sources (RESs) is the mismatch between their energy output and load demand. In remote areas, the solution of this problem is in general employing a small diesel-generator or a storage battery. But, the storage battery is a major cost element of RESs and small diesel-generator is unreliable and costly. Therefore, a proposed technique has been introduced in this work to determine correlation between the energy output of wind energy systems (WES) and isolated loads. solar photovoltaic power system (PVS) and two of energy storage facilities are used here for this correlation. The proposed technique includes also two models for optimizing the generation and costs of WES accompanied with PVS, storage battery and water storage (reservoir) to accommodate an isolated load. The proposed technique is applied with the dynamic programming to coordinate the energy output of a WES with residential and pumping load in remote area of egypt. The results of this application reveal that minimization of both capacity of the storage battery and the whole power system cost are obtained. 4 figs

Validation of models with multivariate output

International Nuclear Information System (INIS)

Rebba, Ramesh; Mahadevan, Sankaran

2006-01-01

This paper develops metrics for validating computational models with experimental data, considering uncertainties in both. A computational model may generate multiple response quantities and the validation experiment might yield corresponding measured values. Alternatively, a single response quantity may be predicted and observed at different spatial and temporal points. Model validation in such cases involves comparison of multiple correlated quantities. Multiple univariate comparisons may give conflicting inferences. Therefore, aggregate validation metrics are developed in this paper. Both classical and Bayesian hypothesis testing are investigated for this purpose, using multivariate analysis. Since, commonly used statistical significance tests are based on normality assumptions, appropriate transformations are investigated in the case of non-normal data. The methodology is implemented to validate an empirical model for energy dissipation in lap joints under dynamic loading

Evaluating the economic damages of transport disruptions using a transnational and interregional input-output model for Japan, China, and South Korea

Science.gov (United States)

Irimoto, Hiroshi; Shibusawa, Hiroyuki; Miyata, Yuzuru

2017-10-01

Damage to transportation networks as a result of natural disasters can lead to economic losses due to lost trade along those links in addition to the costs of damage to the infrastructure itself. This study evaluates the economic damages of transport disruptions such as highways, tunnels, bridges, and ports using a transnational and interregional Input-Output Model that divides the world into 23 regions: 9 regions in Japan, 7 regions in China, and 4 regions in Korea, Taiwan, ASEAN5, and the USA to allow us to focus on Japan's regional and international links. In our simulation, economic ripple effects of both international and interregional transport disruptions are measured by changes in the trade coefficients in the input-output model. The simulation showed that, in the case of regional links in Japan, a transport disruption in the Kanmon Straits causes the most damage to our targeted world, resulting in economic damage of approximately 36.3 billion. In the case of international links among Japan, China, and Korea, damage to the link between Kanto in Japan and Huabei in China causes economic losses of approximately 31.1 billion. Our result highlights the importance of disaster prevention in the Kanmon Straits, Kanto, and Huabei to help ensure economic resilience.

Design and characterization of a high-power ultrasound driver with ultralow-output impedance

Science.gov (United States)

Lewis, George K.; Olbricht, William L.

2009-11-01

We describe a pocket-sized ultrasound driver with an ultralow-output impedance amplifier circuit (less than 0.05 Ω) that can transfer more than 99% of the voltage from a power supply to the ultrasound transducer with minimal reflections. The device produces high-power acoustical energy waves while operating at lower voltages than conventional ultrasound driving systems because energy losses owing to mismatched impedance are minimized. The peak performance of the driver is measured experimentally with a PZT-4, 1.54 MHz, piezoelectric ceramic, and modeled using an adjusted Mason model over a range of transducer resonant frequencies. The ultrasound driver can deliver a 100 Vpp (peak to peak) square-wave signal across 0-8 MHz ultrasound transducers in 5 ms bursts through continuous wave operation, producing acoustic powers exceeding 130 W. Effects of frequency, output impedance of the driver, and input impedance of the transducer on the maximum acoustic output power of piezoelectric transducers are examined. The small size, high power, and efficiency of the ultrasound driver make this technology useful for research, medical, and industrial ultrasonic applications.

Output characteristics of Stirling thermoacoustic engine

International Nuclear Information System (INIS)

Sun Daming; Qiu Limin; Wang Bo; Xiao Yong; Zhao Liang

2008-01-01

A thermoacoustic engine (TE), which converts thermal energy into acoustic power by the thermoacoustic effect, shows several advantages due to the absence of moving parts, such as high reliability and long lifetime associated with reduced manufacturing costs. Power output and efficiency are important criteria of the performance of a TE. In order to increase the acoustic power output and thermal efficiency of a Stirling TE, the acoustic power distribution in the engine is studied with the variable load method. It is found that the thermal efficiency is independent of the output locations along the engine under the same acoustic power output. Furthermore, when the pressure ratio is kept constant at one location along the TE, it is beneficial to increasing the thermal efficiency by exporting more acoustic power. With nitrogen of 2.5 MPa as working gas and the pressure ratio at the compliance of 1.20 in the experiments, the acoustic power is measured at the compliance and the resonator simultaneously. The maximum power output, thermal efficiency and exergy efficiency reach 390.0 W, 11.2% and 16.0%, which are increased by 51.4%, 24.4% and 19.4%, respectively, compared to those with a single R-C load with 750 ml reservoir at the compliance. This research will be instructive for increasing the efficiency and making full use of the acoustic energy of a TE

Effect of material constants on power output in piezoelectric vibration-based generators.

Science.gov (United States)

Takeda, Hiroaki; Mihara, Kensuke; Yoshimura, Tomohiro; Hoshina, Takuya; Tsurumi, Takaaki

2011-09-01

A possible power output estimation based on material constants in piezoelectric vibration-based generators is proposed. A modified equivalent circuit model of the generator was built and was validated by the measurement results in the generator fabricated using potassium sodium niobate-based and lead zirconate titanate (PZT) ceramics. Subsequently, generators with the same structure using other PZT-based and bismuth-layered structure ferroelectrics ceramics were fabricated and tested. The power outputs of these generators were expressed as a linear functions of the term composed of electromechanical coupling coefficients k(sys)(2) and mechanical quality factors Q*(m) of the generator. The relationship between device constants (k(sys)(2) and Q*(m)) and material constants (k(31)(2) and Q(m)) was clarified. Estimation of the power output using material constants is demonstrated and the appropriate piezoelectric material for the generator is suggested.

Using the Yield Curve in Forecasting Output Growth and In‡flation

DEFF Research Database (Denmark)

Hillebrand, Eric Tobias; Huang, Huiyu; Lee, Tae-Hwy

Following Diebold and Li (2006), we use the Nelson-Siegel (NS, 1987) yield curve factors. However the NS yield curve factors are not supervised for a specifi…c forecast target in the sense that the same factors are used for forecasting different variables, e.g., output growth or infl‡ation. We...... analytically and numerically how supervision works. For both CF and CI schemes, principal components (PC) may be used in place of the NS factors. In out-of-sample forecasting of U.S. monthly output growth and infl‡ation, we fi…nd that supervised CF-factor models (CF-NS, CF-PC) are substantially better than...

Are output measurements always necessary after CT tube replacement?

Directory of Open Access Journals (Sweden)

Paul J Stauduhar

2014-03-01

Full Text Available Purpose: TX regulations and the ACR require that CT radiation output be measured within 30 days of major service. The most common major service is tube replacement. We hypothesized that historical QC data could be used instead to determine if output measurements are necessary, reducing the need for costly output measurements.Methods: We reviewed 66 records of tube replacements to determine with what frequency output falls outside specifications. We also conducted an experiment to verify that clinically significant output changes could be identified by comparing image noise in historical QC data with the same data after tube replacement. We used 30 days of historical QC data to establish a baseline noise level and 95% confidence interval (CI for individual noise measurements. To simulate output changes, we acquired phantom images with our QC protocol while manually changing output (mA. We acquired 10 images using the baseline output and 10 images at each different “output”. We evaluated individual images and subsets of images at each “output” to determine if the system was within the manufacturer’s specifications.Results: None of the 66 tube replacements resulted in an output change that exceeded specifications. Analysis of 30 days of historic QC data for our experimental system indicated a mean noise of 5.4 HU with 95% CI of 5.1 ‒ 5.7 HU. When using the mean noise of 10 images acquired at each of the varying outputs, we were able to identify, with 100% accuracy, images acquired at outputs outside manufacturer’s specifications.Conclusion: The results of our review of historical tube replacement data indicated the likelihood of output falling outside manufacturer’s specifications is low. Considering this, it is likely that by using QC data from programs required by regulation and the ACR physicists can reliably verify radiation output stability remotely instead of making physical measurements.--------------------Cite this article

Metop SG Ice Cloud Imager data analysis preparations

Science.gov (United States)

Eriksson, Patrick; Mendrok, Jana; Ekelund, Robin; Rydberg, Bengt; Brath, Manfred; Buehler, Stefan A.

2017-04-01

The Ice Cloud Imager (ICI), one the instruments to be onboard the second generation (SG) of Metop satellites, will be the first operational instrument making use of sub-millimeter wavelengths. Increasing the sensitivity of microwave ice hydrometeor measurements with at least two orders of magnitude, its primary aim is to characterize the bulk mass of ice hydrometeors, where the basic retrieval products will be ice water path, mean mass size, and mean mass altitude. With the expected competitive accuracy it can e.g. complement the narrow horizontal coverage of active instruments. Here we present our activities to develop and improve the data analysis for passive sub-millimeter sensors and ICI in particular, where for the latter we are also developing the froaen hydrometeor retrieval algorithm on behalf of EUMETSAT and its NWC-SAF. One crucial aspect in the data analysis is the quality of the forward modeling, the ability to produce realistic, statistically representative synthetic measurements and to reproduce the performed observations, which poses challenges regarding representation of hydrometeor microphysical as well as optical properties and of the radiative transfer problem itself (atmospheric dimensionality, polarization, etc.). One of our core activities is the creation of a consistent database of ice hydrometeor single scattering properties that covers not only ICI applications, but passive and active sensors in the whole microwave region. The database will fill the gaps (spectral, temperature, habits) of and between existing databases (e.g. by Liu, Hong, Ding, Kuo) and will also hold data for oriented particles. Furthermore, sensitivity to forward modeling assumptions is tested, and the results are validated statistically versus existing (satellite microwave and airborne sub-millimeter) observations. These assumptions include microphysics (e.g. size distributions, habit choices, particle orientation) as well as model complexity (e.g. 3D effects

A Study on Damage Detection Using Output-Only Modal Data

DEFF Research Database (Denmark)

Kharrazi, M. K. H.; Ventura, Carlos E.; Brincker, Rune

2002-01-01

detection using output-only data from the vibration study. A one-third scale model of a four story steel frame at the University of British Columbia was used as the test specimen. A series of forced and ambient vibration tests on this frame for various levels of damage were conducted. Damage was simulated...

Dynamic Output Feedback Robust MPC with Input Saturation Based on Zonotopic Set-Membership Estimation

Directory of Open Access Journals (Sweden)

Xubin Ping

2016-01-01

Full Text Available For quasi-linear parameter varying (quasi-LPV systems with bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC with the consideration of input saturation is investigated. The saturated dynamic output feedback controller is represented by a convex hull involving the actual dynamic output controller and an introduced auxiliary controller. By taking both the actual output feedback controller and the auxiliary controller with a parameter-dependent form, the main optimization problem can be formulated as convex optimization. The consideration of input saturation in the main optimization problem reduces the conservatism of dynamic output feedback controller design. The estimation error set and bounded disturbance are represented by zonotopes and refreshed by zonotopic set-membership estimation. Compared with the previous results, the proposed algorithm can not only guarantee the recursive feasibility of the optimization problem, but also improve the control performance at the cost of higher computational burden. A nonlinear continuous stirred tank reactor (CSTR example is given to illustrate the effectiveness of the approach.

Influence of Special Weather on Output of PV System

Science.gov (United States)

Zhang, Zele

2018-01-01

The output of PV system is affected by different environmental factors, therefore, it is important to study the output of PV system under different environmental conditions. Through collecting data on the spot, collecting the output of photovoltaic panels under special weather conditions, and comparing the collected data, the output characteristics of the photovoltaic panels under different weather conditions are obtained. The influence of weather factors such as temperature, humidity and irradiance on the output of photovoltaic panels was investigated.

Dense Output for Strong Stability Preserving Runge–Kutta Methods

KAUST Repository

Ketcheson, David I.

2016-12-10

We investigate dense output formulae (also known as continuous extensions) for strong stability preserving (SSP) Runge–Kutta methods. We require that the dense output formula also possess the SSP property, ideally under the same step-size restriction as the method itself. A general recipe for first-order SSP dense output formulae for SSP methods is given, and second-order dense output formulae for several optimal SSP methods are developed. It is shown that SSP dense output formulae of order three and higher do not exist, and that in any method possessing a second-order SSP dense output, the coefficient matrix A has a zero row.

Observability of linear systems with saturated outputs

NARCIS (Netherlands)

Koplon, R.; Sontag, E.D.; Hautus, M.L.J.

1994-01-01

We present necessary and sufficient conditions for observability of the class of output-saturated systems. These are linear systems whose output passes through a saturation function before it can be measured.

Output gap uncertainty and real-time monetary policy

Directory of Open Access Journals (Sweden)

Francesco Grigoli

2015-12-01

Full Text Available Output gap estimates are subject to a wide range of uncertainty owing principally to the difficulty in distinguishing between cycle and trend in real time. We show that country desks tend to overestimate economic slack, especially during recessions, and that uncertainty in initial output gap estimates persists several years. Only a small share of output gap revisions is predictable based on output dynamics, data quality, and policy frameworks. We also show that for a group of Latin American inflation targeters the prescriptions from monetary policy rules are subject to large changes due to revised output gap estimates. These explain a sizable proportion of the deviation of inflation from target, suggesting this information is not accounted for in real-time policy decisions.

Peripheral vasodilatation determines cardiac output in exercising humans

DEFF Research Database (Denmark)

Bada, A A; Svendsen, J H; Secher, N H

2012-01-01

In dogs, manipulation of heart rate has no effect on the exercise-induced increase in cardiac output. Whether these findings apply to humans remain uncertain, because of the large differences in cardiovascular anatomy and regulation. To investigate the role of heart rate and peripheral...... arterial ATP infusion at rest. Exercise and ATP infusion increased cardiac output, leg blood flow and vascular conductance (P heart rate by up to 54 beats min(−1), cardiac output did not change in any of the three...... demonstrate that the elevated cardiac output during steady-state exercise is regulated by the increase in skeletal muscle blood flow and venous return to the heart, whereas the increase in heart rate appears to be secondary to the regulation of cardiac output....

Improving the Output Power Stability of a High Concentration Photovoltaic System with Supercapacitors: A Preliminary Evaluation

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Yu-Pei Huang

2015-01-01

Full Text Available The output power of a high concentration photovoltaic (HCPV system is very sensitive to fluctuating tracking errors and weather patterns. To help compensate this shortcoming, supercapacitors have been successfully incorporated into photovoltaic systems to improve their output power stability. This study examined the output power stability improvement of an HCPV module with a supercapacitor integrated into its circuit. Furthermore, the equivalent model of the experimental circuit is presented and analyzed. Experimental results suggest that integrating a supercapacitor into an HCPV module could improve its output power stability and further extend its acceptance angle. This paper provides preliminary data of the improvement and its evaluation method, which could be utilized for further improvements to an HCPV system.

Forecasting Lightning Threat using Cloud-resolving Model Simulations

Science.gov (United States)

McCaul, E. W., Jr.; Goodman, S. J.; LaCasse, K. M.; Cecil, D. J.

2009-01-01

As numerical forecasts capable of resolving individual convective clouds become more common, it is of interest to see if quantitative forecasts of lightning flash rate density are possible, based on fields computed by the numerical model. Previous observational research has shown robust relationships between observed lightning flash rates and inferred updraft and large precipitation ice fields in the mixed phase regions of storms, and that these relationships might allow simulated fields to serve as proxies for lightning flash rate density. It is shown in this paper that two simple proxy fields do indeed provide reasonable and cost-effective bases for creating time-evolving maps of predicted lightning flash rate density, judging from a series of diverse simulation case study events in North Alabama for which Lightning Mapping Array data provide ground truth. One method is based on the product of upward velocity and the mixing ratio of precipitating ice hydrometeors, modeled as graupel only, in the mixed phase region of storms at the -15\\dgc\\ level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domainwide statistics of the peak values of simulated flash rate proxy fields against domainwide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. A blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Weather Research and Forecast Model simulations of selected North Alabama cases show that this model can distinguish the general character and intensity of most convective events, and that the proposed methods show promise as a means of generating

Magnetic Field and Torque Output of Packaged Hydraulic Torque Motor

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Liang Yan

2018-01-01

Full Text Available Hydraulic torque motors are one key component in electro-hydraulic servo valves that convert the electrical signal into mechanical motions. The systematic characteristics analysis of the hydraulic torque motor has not been found in the previous research, including the distribution of the electromagnetic field and torque output, and particularly the relationship between them. In addition, conventional studies of hydraulic torque motors generally assume an evenly distributed magnetic flux field and ignore the influence of special mechanical geometry in the air gaps, which may compromise the accuracy of analyzing the result and the high-precision motion control performance. Therefore, the objective of this study is to conduct a detailed analysis of the distribution of the magnetic field and torque output; the influence of limiting holes in the air gaps is considered to improve the accuracy of both numerical computation and analytical modeling. The structure and working principle of the torque motor are presented first. The magnetic field distribution in the air gaps and the magnetic saturation in the iron blocks are analyzed by using a numerical approach. Subsequently, the torque generation with respect to the current input and assembly errors is analyzed in detail. This shows that the influence of limiting holes on the magnetic field is consistent with that on torque generation. Following this, a novel modified equivalent magnetic circuit is proposed to formulate the torque output of the hydraulic torque motor analytically. The comparison among the modified equivalent magnetic circuit, the conventional modeling approach and the numerical computation is conducted, and it is found that the proposed method helps to improve the modeling accuracy by taking into account the effect of special geometry inside the air gaps.

The Association Between Urine Output, Creatinine Elevation, and Death.

Science.gov (United States)

Engoren, Milo; Maile, Michael D; Heung, Michael; Jewell, Elizabeth S; Vahabzadeh, Christie; Haft, Jonathan W; Kheterpal, Sachin

2017-04-01

Acute kidney injury can be defined by a fall in urine output, and urine output criteria may be more sensitive in identifying acute kidney injury than traditional serum creatinine criteria. However, as pointed out in the Kidney Disease Improving Global Outcome guidelines, the association of urine output with subsequent creatinine elevations and death is poorly characterized. The purpose of this study was to determine what degrees of reduced urine output are associated with subsequent creatinine elevation and death. This was a retrospective cohort study of adult patients (age ≥18 years) cared for in a cardiovascular intensive care unit after undergoing cardiac operations in a tertiary care university medical center. All adult patients who underwent cardiac operations and were not receiving dialysis preoperatively were studied. The development of acute kidney injury was defined as an increase in creatinine of more than 0.3 mg/dL or by more than 50% above baseline by postoperative day 3. Acute kidney injury developed in 1,061 of 4,195 patients (25%). Urine output had moderate discrimination in predicting subsequent acute kidney injury (C statistic = .637 ± .054). Lower urine output and longer duration of low urine output were associated with greater odds of developing acute kidney injury and death. We found that there is similar accuracy in using urine output corrected for actual, ideal, or adjusted weight to discriminate future acute kidney injury by creatinine elevation and recommend using actual weight for its simplicity. We also found that low urine output is associated with subsequent acute kidney injury and that the association is greater for lower urine output and for low urine output of longer durations. Low urine output (creatinine elevation, is independently associated with mortality. Copyright © 2017 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Economic and environmental impacts of dietary changes in Iran : an input-output analysis

NARCIS (Netherlands)

Rahmani, R.; Bakhshoodeh, M.; Zibaei, M.; Heijman, W.J.M.; Eftekhari, M.H.

2012-01-01

Iran's simple and environmentally extended commodity by commodity input-output (IO) model was used to determine the impacts of dietary changes on the Iranian economy and on the environmental load. The original model is based on the status-quo diet and was modified to include the World Health

Multiple-output support vector machine regression with feature selection for arousal/valence space emotion assessment.

Science.gov (United States)

Torres-Valencia, Cristian A; Álvarez, Mauricio A; Orozco-Gutiérrez, Alvaro A

2014-01-01

Human emotion recognition (HER) allows the assessment of an affective state of a subject. Until recently, such emotional states were described in terms of discrete emotions, like happiness or contempt. In order to cover a high range of emotions, researchers in the field have introduced different dimensional spaces for emotion description that allow the characterization of affective states in terms of several variables or dimensions that measure distinct aspects of the emotion. One of the most common of such dimensional spaces is the bidimensional Arousal/Valence space. To the best of our knowledge, all HER systems so far have modelled independently, the dimensions in these dimensional spaces. In this paper, we study the effect of modelling the output dimensions simultaneously and show experimentally the advantages in modeling them in this way. We consider a multimodal approach by including features from the Electroencephalogram and a few physiological signals. For modelling the multiple outputs, we employ a multiple output regressor based on support vector machines. We also include an stage of feature selection that is developed within an embedded approach known as Recursive Feature Elimination (RFE), proposed initially for SVM. The results show that several features can be eliminated using the multiple output support vector regressor with RFE without affecting the performance of the regressor. From the analysis of the features selected in smaller subsets via RFE, it can be observed that the signals that are more informative into the arousal and valence space discrimination are the EEG, Electrooculogram/Electromiogram (EOG/EMG) and the Galvanic Skin Response (GSR).

Does the central bank directly respond to output and 
inflation uncertainties in Turkey?

Directory of Open Access Journals (Sweden)

Pelin Öge Güney

2016-06-01

Full Text Available This paper investigates the role of inflation and output uncertainties on monetary policy rules in Turkey for the period 2002:01–2014:02. In the literature it is suggested that uncertainty is a key element in monetary policy, hence empirical models of monetary policy should regard to uncertainty. In this study, we estimate a forward-looking monetary reaction function of the Central Bank of the Republic of Turkey (CBRT. In addition to inflation and output gap variables, our reaction function also includes both the inflation and output growth uncertainties. Our results suggest that the Central Bank of the Republic of Turkey (CBRT concerns with mainly price stability and significantly responds to inflation and growth uncertainties.

Integration of artificial intelligence methods and life cycle assessment to predict energy output and environmental impacts of paddy production.

Science.gov (United States)

Nabavi-Pelesaraei, Ashkan; Rafiee, Shahin; Mohtasebi, Seyed Saeid; Hosseinzadeh-Bandbafha, Homa; Chau, Kwok-Wing

2018-08-01

Prediction of agricultural energy output and environmental impacts play important role in energy management and conservation of environment as it can help us to evaluate agricultural energy efficiency, conduct crops production system commissioning, and detect and diagnose faults of crop production system. Agricultural energy output and environmental impacts can be readily predicted by artificial intelligence (AI), owing to the ease of use and adaptability to seek optimal solutions in a rapid manner as well as the use of historical data to predict future agricultural energy use pattern under constraints. This paper conducts energy output and environmental impact prediction of paddy production in Guilan province, Iran based on two AI methods, artificial neural networks (ANNs), and adaptive neuro fuzzy inference system (ANFIS). The amounts of energy input and output are 51,585.61MJkg -1 and 66,112.94MJkg -1 , respectively, in paddy production. Life Cycle Assessment (LCA) is used to evaluate environmental impacts of paddy production. Results show that, in paddy production, in-farm emission is a hotspot in global warming, acidification and eutrophication impact categories. ANN model with 12-6-8-1 structure is selected as the best one for predicting energy output. The correlation coefficient (R) varies from 0.524 to 0.999 in training for energy input and environmental impacts in ANN models. ANFIS model is developed based on a hybrid learning algorithm, with R for predicting output energy being 0.860 and, for environmental impacts, varying from 0.944 to 0.997. Results indicate that the multi-level ANFIS is a useful tool to managers for large-scale planning in forecasting energy output and environmental indices of agricultural production systems owing to its higher speed of computation processes compared to ANN model, despite ANN's higher accuracy. Copyright © 2018 Elsevier B.V. All rights reserved.

Input-output linearizing tracking control of induction machine with the included magnetic saturation

DEFF Research Database (Denmark)

Dolinar, Drago; Ljusev, Petar; Stumberger, Gorazd

2003-01-01

The tracking control design of an induction motor, based on input-output linearisation with magnetic saturation included is addressed. The magnetic saturation is represented by a nonlinear magnetising curve for the iron core and is used in the control, the observer of the state variables......, and in the load torque estimator. An input-output linearising control is used to achieve better tracking performances. It is based on the mixed 'stator current - rotor flux linkage' induction motor model with magnetic saturation considered in the stationary reference frame. Experimental results show...... that the proposed input-output linearising tracking control with saturation included behaves considerably better than the one without saturation, and that it introduces smaller position and speed errors, and better motor stiffness on account of the increased computational complexity....

Uncertainty Modeling and Robust Output Feedback Control of Nonlinear Discrete Systems: A Mathematical Programming Approach

Directory of Open Access Journals (Sweden)

Olav Slupphaug

2001-01-01

Full Text Available We present a mathematical programming approach to robust control of nonlinear systems with uncertain, possibly time-varying, parameters. The uncertain system is given by different local affine parameter dependent models in different parts of the state space. It is shown how this representation can be obtained from a nonlinear uncertain system by solving a set of continuous linear semi-infinite programming problems, and how each of these problems can be solved as a (finite series of ordinary linear programs. Additionally, the system representation includes control- and state constraints. The controller design method is derived from Lyapunov stability arguments and utilizes an affine parameter dependent quadratic Lyapunov function. The controller has a piecewise affine output feedback structure, and the design amounts to finding a feasible solution to a set of linear matrix inequalities combined with one spectral radius constraint on the product of two positive definite matrices. A local solution approach to this nonconvex feasibility problem is proposed. Complexity of the design method and some special cases such as state- feedback are discussed. Finally, an application of the results is given by proposing an on-line computationally feasible algorithm for constrained nonlinear state- feedback model predictive control with robust stability.

The efficiency of the agricultural sector in Poland in the light output-input model1

Directory of Open Access Journals (Sweden)

Czyżewski Andrzej

2015-05-01

Full Text Available The study turns attention to the use of the input-output model (account of interbranch flows in macroeconomic assessments of the effectiveness of the agricultural sector. In the introductory part the essence of the account of interbranch flows has been specified, pointing to its historical origin and place in the economic theory, and the morphological structure of the individual parts (quarters of the model has been presented. Then the study discusses the application of the account of interbranch flows in macroeconomic assessments of the effectiveness of the agricultural sector, defining and characterizing a number of indicators which allow to conclude on the effectiveness of the agricultural sector on the basis of the account of interbranch flows. The last, empirical part of the study assesses the effectiveness of the agricultural sector in Poland on the basis of interbranch flows statistics for the years 2000 and 2005. The analyses allowed to demonstrate increased efficiency of the agricultural sector in Poland after Poland joined the EU, and also to say that the account of interbranch flows is an important tool enabling comprehensive assessment of the effectiveness of the agricultural sector in the macro-scale, through the prism of the effect - disbursement, which accounts for its exceptional suitability in this kind of analyses.

Output factors and scatter ratios

Energy Technology Data Exchange (ETDEWEB)

Shrivastava, P N; Summers, R E; Samulski, T V; Baird, L C [Allegheny General Hospital, Pittsburgh, PA (USA); Ahuja, A S; Dubuque, G L; Hendee, W R; Chhabra, A S

1979-07-01

Reference is made to a previous publication on output factors and scatter ratios for radiotherapy units in which it was suggested that the output factor should be included in the definitions of scatter-air ratio and tissue-maximum ratio. In the present correspondence from other authors and from the authors of the previous publication, the original definitions and the proposed changes are discussed. Radiation scatter from source and collimator degradation of beam energy and calculation of dose in tissue are considered in relation to the objective of accurate dosimetry.

Robust output-feedback control to eliminate stick-slip oscillations in drill-string systems

NARCIS (Netherlands)

Vromen, T.G.M.; Dai, C.H.; van de Wouw, N.; Oomen, T.A.E.; Astrid, P.; Nijmeijer, H.

2015-01-01

The aim of this paper is to design a robust output-feedback controller to eliminate torsional stick-slip vibrations. A multi-modal model of the torsional dynamics with a nonlinear bit-rock interaction model is used. The controller design is based on skewed-μ DK-iteration and the stability of the

Residual gravimetric method to measure nebulizer output.

Science.gov (United States)

Vecellio None, Laurent; Grimbert, Daniel; Bordenave, Joelle; Benoit, Guy; Furet, Yves; Fauroux, Brigitte; Boissinot, Eric; De Monte, Michele; Lemarié, Etienne; Diot, Patrice

2004-01-01

The aim of this study was to assess a residual gravimetric method based on weighing dry filters to measure the aerosol output of nebulizers. This residual gravimetric method was compared to assay methods based on spectrophotometric measurement of terbutaline (Bricanyl, Astra Zeneca, France), high-performance liquid chromatography (HPLC) measurement of tobramycin (Tobi, Chiron, U.S.A.), and electrochemical measurements of NaF (as defined by the European standard). Two breath-enhanced jet nebulizers, one standard jet nebulizer, and one ultrasonic nebulizer were tested. Output produced by the residual gravimetric method was calculated by weighing the filters both before and after aerosol collection and by filter drying corrected by the proportion of drug contained in total solute mass. Output produced by the electrochemical, spectrophotometric, and HPLC methods was determined after assaying the drug extraction filter. The results demonstrated a strong correlation between the residual gravimetric method (x axis) and assay methods (y axis) in terms of drug mass output (y = 1.00 x -0.02, r(2) = 0.99, n = 27). We conclude that a residual gravimetric method based on dry filters, when validated for a particular agent, is an accurate way of measuring aerosol output.

Development of the GUI environments of MIDAS code for convenient input and output processing

International Nuclear Information System (INIS)

Kim, K. L.; Kim, D. H.

2003-01-01

MIDAS is being developed at KAERI as an integrated Severe Accident Analysis Code with easy model modification and addition by restructuring the data transfer scheme. In this paper, the input file management system, IEDIT and graphic simulation system, SATS, are presented as MIDAS input and output GUI systems. These two systems would form the basis of the MIDAS GUI system for input and output processing, and they are expected to be useful tools for severe accidents analysis and simulation

Output formatting in Apple-Soft Basic

International Nuclear Information System (INIS)

Navale, A.S.

1987-01-01

Personal computers are being used extensively in various fields. BASIC is a very popular and widely used language in personal computers. Apple computer is one of the popular machines used for scientific and engineering applications. Presenting output from computers in a neat and easy to read form is very important. Languages like FORTRAN have utility command 'FORMAT' which takes care of the formatting of the output in user-defined form. In some versions of BASIC a PRINT USING facility is available but it is not as powerful as the FORTRAN statement 'FORMAT'. Applesoft basic does not have even this PRINT USING command. Programmers have to write their own program segments to handle output formatting in Applesoft BASIC. Generally, such user written programs are of limited use as they cannot be used easily with other programs. A general purpose and easily transportable subroutine in Applesoft BASIC is presented here for handling output formatting in user-defined structure. The subroutine is nearly as powerful as the FORMAT statement in FORTRAN. It can also be used in other versions of BASIC with very little modifications. 3 tables, 4 refs. (author)

A Novel Variable Stiffness Mechanism Capable of an Infinite Stiffness Range and Unlimited Decoupled Output Motion

Directory of Open Access Journals (Sweden)

Stefan Groothuis

2014-06-01

Full Text Available In this paper, a novel variable stiffness mechanism is presented, which is capable of achieving an output stiffness with infinite range and an unlimited output motion, i.e., the mechanism output is completely decoupled from the rotor motion, in the zero stiffness configuration. The mechanism makes use of leaf springs, which are engaged at different positions by means of two movable supports, to realize the variable output stiffness. The Euler–Bernoulli leaf spring model is derived and validated through experimental data. By shaping the leaf springs, it is shown that the stiffness characteristic of the mechanism can be changed to fulfill different application requirements. Alternative designs can achieve the same behavior with only one leaf spring and one movable support pin.

INFLUENCE OF FISCAL POLICY DYNAMICS ON OUTPUT MANAGEMENT

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