Sensitivity of a Shallow-Water Model to Parameters
Kazantsev, Eugene
2011-01-01
An adjoint based technique is applied to a shallow water model in order to estimate the influence of the model's parameters on the solution. Among parameters the bottom topography, initial conditions, boundary conditions on rigid boundaries, viscosity coefficients Coriolis parameter and the amplitude of the wind stress tension are considered. Their influence is analyzed from three points of view: 1. flexibility of the model with respect to a parameter that is related to the lowest value of the cost function that can be obtained in the data assimilation experiment that controls this parameter; 2. possibility to improve the model by the parameter's control, i.e. whether the solution with the optimal parameter remains close to observations after the end of control; 3. sensitivity of the model solution to the parameter in a classical sense. That implies the analysis of the sensitivity estimates and their comparison with each other and with the local Lyapunov exponents that characterize the sensitivity of the mode...
Universally sloppy parameter sensitivities in systems biology models.
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Ryan N Gutenkunst
2007-10-01
Full Text Available Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.
Modelling of intermittent microwave convective drying: parameter sensitivity
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Zhang Zhijun
2017-06-01
Full Text Available The reliability of the predictions of a mathematical model is a prerequisite to its utilization. A multiphase porous media model of intermittent microwave convective drying is developed based on the literature. The model considers the liquid water, gas and solid matrix inside of food. The model is simulated by COMSOL software. Its sensitivity parameter is analysed by changing the parameter values by ±20%, with the exception of several parameters. The sensitivity analysis of the process of the microwave power level shows that each parameter: ambient temperature, effective gas diffusivity, and evaporation rate constant, has significant effects on the process. However, the surface mass, heat transfer coefficient, relative and intrinsic permeability of the gas, and capillary diffusivity of water do not have a considerable effect. The evaporation rate constant has minimal parameter sensitivity with a ±20% value change, until it is changed 10-fold. In all results, the temperature and vapour pressure curves show the same trends as the moisture content curve. However, the water saturation at the medium surface and in the centre show different results. Vapour transfer is the major mass transfer phenomenon that affects the drying process.
Modelling of intermittent microwave convective drying: parameter sensitivity
Zhang, Zhijun; Qin, Wenchao; Shi, Bin; Gao, Jingxin; Zhang, Shiwei
2017-06-01
The reliability of the predictions of a mathematical model is a prerequisite to its utilization. A multiphase porous media model of intermittent microwave convective drying is developed based on the literature. The model considers the liquid water, gas and solid matrix inside of food. The model is simulated by COMSOL software. Its sensitivity parameter is analysed by changing the parameter values by ±20%, with the exception of several parameters. The sensitivity analysis of the process of the microwave power level shows that each parameter: ambient temperature, effective gas diffusivity, and evaporation rate constant, has significant effects on the process. However, the surface mass, heat transfer coefficient, relative and intrinsic permeability of the gas, and capillary diffusivity of water do not have a considerable effect. The evaporation rate constant has minimal parameter sensitivity with a ±20% value change, until it is changed 10-fold. In all results, the temperature and vapour pressure curves show the same trends as the moisture content curve. However, the water saturation at the medium surface and in the centre show different results. Vapour transfer is the major mass transfer phenomenon that affects the drying process.
Considerations for parameter optimization and sensitivity in climate models.
Neelin, J David; Bracco, Annalisa; Luo, Hao; McWilliams, James C; Meyerson, Joyce E
2010-12-14
Climate models exhibit high sensitivity in some respects, such as for differences in predicted precipitation changes under global warming. Despite successful large-scale simulations, regional climatology features prove difficult to constrain toward observations, with challenges including high-dimensionality, computationally expensive simulations, and ambiguity in the choice of objective function. In an atmospheric General Circulation Model forced by observed sea surface temperature or coupled to a mixed-layer ocean, many climatic variables yield rms-error objective functions that vary smoothly through the feasible parameter range. This smoothness occurs despite nonlinearity strong enough to reverse the curvature of the objective function in some parameters, and to imply limitations on multimodel ensemble means as an estimator of global warming precipitation changes. Low-order polynomial fits to the model output spatial fields as a function of parameter (quadratic in model field, fourth-order in objective function) yield surprisingly successful metamodels for many quantities and facilitate a multiobjective optimization approach. Tradeoffs arise as optima for different variables occur at different parameter values, but with agreement in certain directions. Optima often occur at the limit of the feasible parameter range, identifying key parameterization aspects warranting attention--here the interaction of convection with free tropospheric water vapor. Analytic results for spatial fields of leading contributions to the optimization help to visualize tradeoffs at a regional level, e.g., how mismatches between sensitivity and error spatial fields yield regional error under minimization of global objective functions. The approach is sufficiently simple to guide parameter choices and to aid intercomparison of sensitivity properties among climate models.
Parameter sensitivity in satellite-gravity-constrained geothermal modelling
Pastorutti, Alberto; Braitenberg, Carla
2017-04-01
The use of satellite gravity data in thermal structure estimates require identifying the factors that affect the gravity field and are related to the thermal characteristics of the lithosphere. We propose a set of forward-modelled synthetics, investigating the model response in terms of heat flow, temperature, and gravity effect at satellite altitude. The sensitivity analysis concerns the parameters involved, as heat production, thermal conductivity, density and their temperature dependence. We discuss the effect of the horizontal smoothing due to heat conduction, the superposition of the bulk thermal effect of near-surface processes (e.g. advection in ground-water and permeable faults, paleoclimatic effects, blanketing by sediments), and the out-of equilibrium conditions due to tectonic transients. All of them have the potential to distort the gravity-derived estimates.We find that the temperature-conductivity relationship has a small effect with respect to other parameter uncertainties on the modelled temperature depth variation, surface heat flow, thermal lithosphere thickness. We conclude that the global gravity is useful for geothermal studies.
Bates, P. D.; Neal, J. C.; Fewtrell, T. J.
2012-12-01
In this we paper we consider two related questions. First, we address the issue of how much physical complexity is necessary in a model in order to simulate floodplain inundation to within validation data error. This is achieved through development of a single code/multiple physics hydraulic model (LISFLOOD-FP) where different degrees of complexity can be switched on or off. Different configurations of this code are applied to four benchmark test cases, and compared to the results of a number of industry standard models. Second we address the issue of how parameter sensitivity and transferability change with increasing complexity using numerical experiments with models of different physical and geometric intricacy. Hydraulic models are a good example system with which to address such generic modelling questions as: (1) they have a strong physical basis; (2) there is only one set of equations to solve; (3) they require only topography and boundary conditions as input data; and (4) they typically require only a single free parameter, namely boundary friction. In terms of complexity required we show that for the problem of sub-critical floodplain inundation a number of codes of different dimensionality and resolution can be found to fit uncertain model validation data equally well, and that in this situation Occam's razor emerges as a useful logic to guide model selection. We find also find that model skill usually improves more rapidly with increases in model spatial resolution than increases in physical complexity, and that standard approaches to testing hydraulic models against laboratory data or analytical solutions may fail to identify this important fact. Lastly, we find that in benchmark testing studies significant differences can exist between codes with identical numerical solution techniques as a result of auxiliary choices regarding the specifics of model implementation that are frequently unreported by code developers. As a consequence, making sound
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Xiao-meng SONG
2013-01-01
Full Text Available Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on (1 a screening method (Morris for qualitative ranking of parameters, and (2 a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model (RSMSobol. First, the Morris screening method was used to qualitatively identify the parameters’ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model (RSM were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.
An approach to measure parameter sensitivity in watershed hydrological modelling
Hydrologic responses vary spatially and temporally according to watershed characteristics. In this study, the hydrologic models that we developed earlier for the Little Miami River (LMR) and Las Vegas Wash (LVW) watersheds were used for detail sensitivity analyses. To compare the...
Land Building Models: Uncertainty in and Sensitivity to Input Parameters
2013-08-01
Louisiana Coastal Area Ecosystem Restoration Projects Study , Vol. 3, Final integrated ERDC/CHL CHETN-VI-44 August 2013 24 feasibility study and... Nourishment Module, Chapter 8. In Coastal Louisiana Ecosystem Assessment and Restoration (CLEAR) Model of Louisiana Coastal Area (LCA) Comprehensive...to Input Parameters by Ty V. Wamsley PURPOSE: The purpose of this Coastal and Hydraulics Engineering Technical Note (CHETN) is to document a
Parameter sensitivity and uncertainty analysis for a storm surge and wave model
Bastidas, Luis A.; Knighton, James; Kline, Shaun W.
2016-09-01
Development and simulation of synthetic hurricane tracks is a common methodology used to estimate hurricane hazards in the absence of empirical coastal surge and wave observations. Such methods typically rely on numerical models to translate stochastically generated hurricane wind and pressure forcing into coastal surge and wave estimates. The model output uncertainty associated with selection of appropriate model parameters must therefore be addressed. The computational overburden of probabilistic surge hazard estimates is exacerbated by the high dimensionality of numerical surge and wave models. We present a model parameter sensitivity analysis of the Delft3D model for the simulation of hazards posed by Hurricane Bob (1991) utilizing three theoretical wind distributions (NWS23, modified Rankine, and Holland). The sensitive model parameters (of 11 total considered) include wind drag, the depth-induced breaking γB, and the bottom roughness. Several parameters show no sensitivity (threshold depth, eddy viscosity, wave triad parameters, and depth-induced breaking αB) and can therefore be excluded to reduce the computational overburden of probabilistic surge hazard estimates. The sensitive model parameters also demonstrate a large number of interactions between parameters and a nonlinear model response. While model outputs showed sensitivity to several parameters, the ability of these parameters to act as tuning parameters for calibration is somewhat limited as proper model calibration is strongly reliant on accurate wind and pressure forcing data. A comparison of the model performance with forcings from the different wind models is also presented.
Geomagnetically induced currents in Uruguay: Sensitivity to modelling parameters
Caraballo, R.
2016-11-01
According to the traditional wisdom, geomagnetically induced currents (GIC) should occur rarely at mid-to-low latitudes, but in the last decades a growing number of reports have addressed their effects on high-voltage (HV) power grids at mid-to-low latitudes. The growing trend to interconnect national power grids to meet regional integration objectives, may lead to an increase in the size of the present energy transmission networks to form a sort of super-grid at continental scale. Such a broad and heterogeneous super-grid can be exposed to the effects of large GIC if appropriate mitigation actions are not taken into consideration. In the present study, we present GIC estimates for the Uruguayan HV power grid during severe magnetic storm conditions. The GIC intensities are strongly dependent on the rate of variation of the geomagnetic field, conductivity of the ground, power grid resistances and configuration. Calculated GIC are analysed as functions of these parameters. The results show a reasonable agreement with measured data in Brazil and Argentina, thus confirming the reliability of the model. The expansion of the grid leads to a strong increase in GIC intensities in almost all substations. The power grid response to changes in ground conductivity and resistances shows similar results in a minor extent. This leads us to consider GIC as a non-negligible phenomenon in South America. Consequently, GIC must be taken into account in mid-to-low latitude power grids as well.
An approach to measure parameter sensitivity in watershed hydrologic modeling
U.S. Environmental Protection Agency — Abstract Hydrologic responses vary spatially and temporally according to watershed characteristics. In this study, the hydrologic models that we developed earlier...
Multi-objective global sensitivity analysis of the WRF model parameters
Quan, Jiping; Di, Zhenhua; Duan, Qingyun; Gong, Wei; Wang, Chen
2015-04-01
Tuning model parameters to match model simulations with observations can be an effective way to enhance the performance of numerical weather prediction (NWP) models such as Weather Research and Forecasting (WRF) model. However, this is a very complicated process as a typical NWP model involves many model parameters and many output variables. One must take a multi-objective approach to ensure all of the major simulated model outputs are satisfactory. This talk presents the results of an investigation of multi-objective parameter sensitivity analysis of the WRF model to different model outputs, including conventional surface meteorological variables such as precipitation, surface temperature, humidity and wind speed, as well as atmospheric variables such as total precipitable water, cloud cover, boundary layer height and outgoing long radiation at the top of the atmosphere. The goal of this study is to identify the most important parameters that affect the predictive skill of short-range meteorological forecasts by the WRF model. The study was performed over the Greater Beijing Region of China. A total of 23 adjustable parameters from seven different physical parameterization schemes were considered. Using a multi-objective global sensitivity analysis method, we examined the WRF model parameter sensitivities to the 5-day simulations of the aforementioned model outputs. The results show that parameter sensitivities vary with different model outputs. But three to four of the parameters are shown to be sensitive to all model outputs considered. The sensitivity results from this research can be the basis for future model parameter optimization of the WRF model.
Quantification of remodeling parameter sensitivity - assessed by a computer simulation model
DEFF Research Database (Denmark)
Thomsen, J.S.; Mosekilde, Li.; Mosekilde, Erik
1996-01-01
We have used a computer simulation model to evaluate the effect of several bone remodeling parameters on vertebral cancellus bone. The menopause was chosen as the base case scenario, and the sensitivity of the model to the following parameters was investigated: activation frequency, formation...
Edouard, C.; Petit, M.; Forgez, C.; Bernard, J.; Revel, R.
2016-09-01
In this work, a simplified electrochemical and thermal model that can predict both physicochemical and aging behavior of Li-ion batteries is studied. A sensitivity analysis of all its physical parameters is performed in order to find out their influence on the model output based on simulations under various conditions. The results gave hints on whether a parameter needs particular attention when measured or identified and on the conditions (e.g. temperature, discharge rate) under which it is the most sensitive. A specific simulation profile is designed for parameters involved in aging equations in order to determine their sensitivity. Finally, a step-wise method is followed to limit the influence of parameter values when identifying some of them, according to their relative sensitivity from the study. This sensitivity analysis and the subsequent step-wise identification method show very good results, such as a better fitting of the simulated cell voltage with experimental data.
Directory of Open Access Journals (Sweden)
Farzin Shabani
Full Text Available Using CLIMEX and the Taguchi Method, a process-based niche model was developed to estimate potential distributions of Phoenix dactylifera L. (date palm, an economically important crop in many counties. Development of the model was based on both its native and invasive distribution and validation was carried out in terms of its extensive distribution in Iran. To identify model parameters having greatest influence on distribution of date palm, a sensitivity analysis was carried out. Changes in suitability were established by mapping of regions where the estimated distribution changed with parameter alterations. This facilitated the assessment of certain areas in Iran where parameter modifications impacted the most, particularly in relation to suitable and highly suitable locations. Parameter sensitivities were also evaluated by the calculation of area changes within the suitable and highly suitable categories. The low temperature limit (DV2, high temperature limit (DV3, upper optimal temperature (SM2 and high soil moisture limit (SM3 had the greatest impact on sensitivity, while other parameters showed relatively less sensitivity or were insensitive to change. For an accurate fit in species distribution models, highly sensitive parameters require more extensive research and data collection methods. Results of this study demonstrate a more cost effective method for developing date palm distribution models, an integral element in species management, and may prove useful for streamlining requirements for data collection in potential distribution modeling for other species as well.
Institute of Scientific and Technical Information of China (English)
PANG Lei; ZHANG Jixian; YAN Qin
2010-01-01
For the high-resolution airborne synthetic aperture radar (SAR) stereo geolocation application, the final geolocation accuracy is influenced by various error parameter sources. In this paper, an airborne SAR stereo geolocation parameter error model,involving the parameter errors derived from the navigation system on the flight platform, has been put forward. Moreover, a kind of near-direct method for modeling and sensitivity analysis of navigation parameter errors is also given. This method directly uses the ground reference to calculate the covariance matrix relationship between the parameter errors and the eventual geolocation errors for ground target points. In addition, utilizing true flight track parameters' errors, this paper gave a verification of the method and a corresponding sensitivity analysis for airborne SAR stereo geolocation model and proved its efficiency.
Sensitivity analysis of CLIMEX parameters in modelling potential distribution of Lantana camara L.
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Subhashni Taylor
Full Text Available A process-based niche model of L. camara L. (lantana, a highly invasive shrub species, was developed to estimate its potential distribution using CLIMEX. Model development was carried out using its native and invasive distribution and validation was carried out with the extensive Australian distribution. A good fit was observed, with 86.7% of herbarium specimens collected in Australia occurring within the suitable and highly suitable categories. A sensitivity analysis was conducted to identify the model parameters that had the most influence on lantana distribution. The changes in suitability were assessed by mapping the regions where the distribution changed with each parameter alteration. This allowed an assessment of where, within Australia, the modification of each parameter was having the most impact, particularly in terms of the suitable and highly suitable locations. The sensitivity of various parameters was also evaluated by calculating the changes in area within the suitable and highly suitable categories. The limiting low temperature (DV0, limiting high temperature (DV3 and limiting low soil moisture (SM0 showed highest sensitivity to change. The other model parameters were relatively insensitive to change. Highly sensitive parameters require extensive research and data collection to be fitted accurately in species distribution models. The results from this study can inform more cost effective development of species distribution models for lantana. Such models form an integral part of the management of invasive species and the results can be used to streamline data collection requirements for potential distribution modelling.
Characterization of uncertainty and sensitivity of model parameters is an essential and often overlooked facet of hydrological modeling. This paper introduces an algorithm called MOESHA that combines input parameter sensitivity analyses with a genetic algorithm calibration routin...
Parameter estimation and sensitivity analysis for a mathematical model with time delays of leukemia
Cândea, Doina; Halanay, Andrei; Rǎdulescu, Rodica; Tǎlmaci, Rodica
2017-01-01
We consider a system of nonlinear delay differential equations that describes the interaction between three competing cell populations: healthy, leukemic and anti-leukemia T cells involved in Chronic Myeloid Leukemia (CML) under treatment with Imatinib. The aim of this work is to establish which model parameters are the most important in the success or failure of leukemia remission under treatment using a sensitivity analysis of the model parameters. For the most significant parameters of the model which affect the evolution of CML disease during Imatinib treatment we try to estimate the realistic values using some experimental data. For these parameters, steady states are calculated and their stability is analyzed and biologically interpreted.
The sensitivity of flowline models of tidewater glaciers to parameter uncertainty
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E. M. Enderlin
2013-10-01
Full Text Available Depth-integrated (1-D flowline models have been widely used to simulate fast-flowing tidewater glaciers and predict change because the continuous grounding line tracking, high horizontal resolution, and physically based calving criterion that are essential to realistic modeling of tidewater glaciers can easily be incorporated into the models while maintaining high computational efficiency. As with all models, the values for parameters describing ice rheology and basal friction must be assumed and/or tuned based on observations. For prognostic studies, these parameters are typically tuned so that the glacier matches observed thickness and speeds at an initial state, to which a perturbation is applied. While it is well know that ice flow models are sensitive to these parameters, the sensitivity of tidewater glacier models has not been systematically investigated. Here we investigate the sensitivity of such flowline models of outlet glacier dynamics to uncertainty in three key parameters that influence a glacier's resistive stress components. We find that, within typical observational uncertainty, similar initial (i.e., steady-state glacier configurations can be produced with substantially different combinations of parameter values, leading to differing transient responses after a perturbation is applied. In cases where the glacier is initially grounded near flotation across a basal over-deepening, as typically observed for rapidly changing glaciers, these differences can be dramatic owing to the threshold of stability imposed by the flotation criterion. The simulated transient response is particularly sensitive to the parameterization of ice rheology: differences in ice temperature of ~ 2 °C can determine whether the glaciers thin to flotation and retreat unstably or remain grounded on a marine shoal. Due to the highly non-linear dependence of tidewater glaciers on model parameters, we recommend that their predictions are accompanied by
The sensitivity of flowline models of tidewater glaciers to parameter uncertainty
Directory of Open Access Journals (Sweden)
E. M. Enderlin
2013-06-01
Full Text Available Depth-integrated (1-D flowline models have been widely used to simulate fast-flowing tidewater glaciers and predict future change because their computational efficiency allows for continuous grounding line tracking, high horizontal resolution, and a physically-based calving criterion, which are all essential to realistic modeling of tidewater glaciers. As with all models, the values for parameters describing ice rheology and basal friction must be assumed and/or tuned based on observations. For prognostic studies, these parameters are typically tuned so that the glacier matches observed thickness and speeds at an initial state, to which a perturbation is applied. While it is well know that ice flow models are sensitive to these parameters, the sensitivity of tidewater glacier models has not been systematically investigated. Here we investigate the sensitivity of such flowline models of outlet glacier dynamics to uncertainty in three key parameters that influence a glacier's resistive stress components. We find that, within typical observational uncertainty, similar initial (i.e. steady-state glacier configurations can be produced with substantially different combinations of parameter values, leading to differing transient responses after a perturbation is applied. In cases where the glacier is initially grounded near flotation across a basal overdeepening, as typically observed for rapidly changing glaciers, these differences can be dramatic owing to the threshold of stability imposed by the flotation criterion. The simulated transient response is particularly sensitive to the parameterization of ice rheology: differences in ice temperature of ∼ 2 °C can determine whether the glaciers thin to flotation and retreat unstably or remain grounded on a marine shoal. Due the highly non-linear dependence of tidewater glaciers on model parameters, we recommend that their predictions are accompanied by sensitivity tests that take parameter uncertainty
Energy Technology Data Exchange (ETDEWEB)
Maynard, K.; Royer, J.F. [Meteo-France CNRM, 42 Avenue G. Coriolis, 31057, Toulouse Cedex 1 (France)
2004-06-01
During the last two decades, several land surface schemes for use in climate, regional and/or mesoscale, hydrological and ecological models have been designed. Incorrect parametrization of land-surface processes and prescription of the surface parameters in atmospheric modeling, can result in artificial changes of the horizontal gradient of the sensible heat flux. Thus, an error in horizontal temperature gradient within the lower atmosphere may be introduced. The reliability of the model depends on the quality of boundary layer scheme implemented and its sensitivity to the bare soil and vegetation parameters. In this study, a series of sensitivity experiments has been conducted over broad time scales, using a version of the ARPEGE Climate Model coupled to the ISBA land surface scheme in order to investigate model sensitivity to separate changes in land surface parameters over Africa. Effects of perturbing vegetation cover, distribution of soil depth, albedo of vegetation, roughness length, leaf area index and minimum stomatal resistance were explored by using a simple statistical analysis. Identifying which parameters are important in controlling turbulent energy fluxes, temperature and soil moisture is dependent on which variables are used to determine sensibility, which type of vegetation and climate regime is being simulated and the magnitude and sign of the parameter change. This study does not argue that a particular parameter is important in ISBA, rather it shows that no general ranking of parameters is possible. So, it is essential to specify all land surface parameters with greater precision when attempting to determine the climate response to modification of the land surface. The implication of ISBA being sensitive to parameters that cannot be validated suggests that there will always be considerable doubt over the predictive quality of land-surface schemes. (orig.)
Parameter sensitivity analysis of stochastic models provides insights into cardiac calcium sparks.
Lee, Young-Seon; Liu, Ona Z; Hwang, Hyun Seok; Knollmann, Bjorn C; Sobie, Eric A
2013-03-05
We present a parameter sensitivity analysis method that is appropriate for stochastic models, and we demonstrate how this analysis generates experimentally testable predictions about the factors that influence local Ca(2+) release in heart cells. The method involves randomly varying all parameters, running a single simulation with each set of parameters, running simulations with hundreds of model variants, then statistically relating the parameters to the simulation results using regression methods. We tested this method on a stochastic model, containing 18 parameters, of the cardiac Ca(2+) spark. Results show that multivariable linear regression can successfully relate parameters to continuous model outputs such as Ca(2+) spark amplitude and duration, and multivariable logistic regression can provide insight into how parameters affect Ca(2+) spark triggering (a probabilistic process that is all-or-none in a single simulation). Benchmark studies demonstrate that this method is less computationally intensive than standard methods by a factor of 16. Importantly, predictions were tested experimentally by measuring Ca(2+) sparks in mice with knockout of the sarcoplasmic reticulum protein triadin. These mice exhibit multiple changes in Ca(2+) release unit structures, and the regression model both accurately predicts changes in Ca(2+) spark amplitude (30% decrease in model, 29% decrease in experiments) and provides an intuitive and quantitative understanding of how much each alteration contributes to the result. This approach is therefore an effective, efficient, and predictive method for analyzing stochastic mathematical models to gain biological insight.
Institute of Scientific and Technical Information of China (English)
Youlong XIA; Zong-Liang YANG; Paul L. STOFFA; Mrinal K. SEN
2005-01-01
Most previous land-surface model calibration studies have defined global ranges for their parameters to search for optimal parameter sets. Little work has been conducted to study the impacts of realistic versus global ranges as well as model complexities on the calibration and uncertainty estimates. The primary purpose of this paper is to investigate these impacts by employing Bayesian Stochastic Inversion (BSI)to the Chameleon Surface Model (CHASM). The CHASM was designed to explore the general aspects of land-surface energy balance representation within a common modeling framework that can be run from a simple energy balance formulation to a complex mosaic type structure. The BSI is an uncertainty estimation technique based on Bayes theorem, importance sampling, and very fast simulated annealing.The model forcing data and surface flux data were collected at seven sites representing a wide range of climate and vegetation conditions. For each site, four experiments were performed with simple and complex CHASM formulations as well as realistic and global parameter ranges. Twenty eight experiments were conducted and 50 000 parameter sets were used for each run. The results show that the use of global and realistic ranges gives similar simulations for both modes for most sites, but the global ranges tend to produce some unreasonable optimal parameter values. Comparison of simple and complex modes shows that the simple mode has more parameters with unreasonable optimal values. Use of parameter ranges and model complexities have significant impacts on frequency distribution of parameters, marginal posterior probability density functions, and estimates of uncertainty of simulated sensible and latent heat fluxes.Comparison between model complexity and parameter ranges shows that the former has more significant impacts on parameter and uncertainty estimations.
Parameter sensitivity study of the biogeochemical model in the China coastal seas
Institute of Scientific and Technical Information of China (English)
JI Xuanliang; LIU Guimei; GAO Shan; WANG Hui
2015-01-01
In order to develop a coupled basin scale model of ocean circulation and biogeochemical cycling, we present a biogeochemical model including 12 components to study the ecosystem in the China coastal seas (CCS). The formulation of phytoplankton mortality and zooplankton growth are modified according to biological characteristics of CCS.The four sensitivity biological parameters, zooplankton assimilation efficiency rate (ZooAE_N), zooplankton basal metabolism rate (ZooBM), maximum specific growth rate of zooplankton (μ20) and maximum chlorophyll to carbon ratio (Chl2C_m) are obtained in sensitivity experiments for the phytoplankton, and experiments about the parameterμ20, half-saturation for phytoplankton NO3 uptake ( KNO3 ) and remineralization rate of small detritusN (SDeRRN) are conducted. The results demonstrate that the biogeochemical model is quite sensitive to the zooplankton grazing parameter when it ranges from 0.1 to 1.2 d–1. The KNO3 and SDeRRN also play an important role in determining the nitrogen cycle within certain ranges.The sensitive interval of KNO3 is from 0.1 to 1.5 (mmol/m3)–1, and interval of SEdRRN is from 0.01 and 0.1 d–1. The observational data from September 1998 to July 2000 obtained at SEATS station are used to validate the performance of biological model after parameters optimization. The results show that the modified model has a good capacity to reveal the biological process features, and the sensitivity analysis can save computational resources greatly during the model simulation.
Directory of Open Access Journals (Sweden)
W. Castaings
2009-04-01
Full Text Available Variational methods are widely used for the analysis and control of computationally intensive spatially distributed systems. In particular, the adjoint state method enables a very efficient calculation of the derivatives of an objective function (response function to be analysed or cost function to be optimised with respect to model inputs.
In this contribution, it is shown that the potential of variational methods for distributed catchment scale hydrology should be considered. A distributed flash flood model, coupling kinematic wave overland flow and Green Ampt infiltration, is applied to a small catchment of the Thoré basin and used as a relatively simple (synthetic observations but didactic application case.
It is shown that forward and adjoint sensitivity analysis provide a local but extensive insight on the relation between the assigned model parameters and the simulated hydrological response. Spatially distributed parameter sensitivities can be obtained for a very modest calculation effort (~6 times the computing time of a single model run and the singular value decomposition (SVD of the Jacobian matrix provides an interesting perspective for the analysis of the rainfall-runoff relation.
For the estimation of model parameters, adjoint-based derivatives were found exceedingly efficient in driving a bound-constrained quasi-Newton algorithm. The reference parameter set is retrieved independently from the optimization initial condition when the very common dimension reduction strategy (i.e. scalar multipliers is adopted.
Furthermore, the sensitivity analysis results suggest that most of the variability in this high-dimensional parameter space can be captured with a few orthogonal directions. A parametrization based on the SVD leading singular vectors was found very promising but should be combined with another regularization strategy in order to prevent overfitting.
Castaings, W.; Dartus, D.; Le Dimet, F.-X.; Saulnier, G.-M.
2009-04-01
Variational methods are widely used for the analysis and control of computationally intensive spatially distributed systems. In particular, the adjoint state method enables a very efficient calculation of the derivatives of an objective function (response function to be analysed or cost function to be optimised) with respect to model inputs. In this contribution, it is shown that the potential of variational methods for distributed catchment scale hydrology should be considered. A distributed flash flood model, coupling kinematic wave overland flow and Green Ampt infiltration, is applied to a small catchment of the Thoré basin and used as a relatively simple (synthetic observations) but didactic application case. It is shown that forward and adjoint sensitivity analysis provide a local but extensive insight on the relation between the assigned model parameters and the simulated hydrological response. Spatially distributed parameter sensitivities can be obtained for a very modest calculation effort (~6 times the computing time of a single model run) and the singular value decomposition (SVD) of the Jacobian matrix provides an interesting perspective for the analysis of the rainfall-runoff relation. For the estimation of model parameters, adjoint-based derivatives were found exceedingly efficient in driving a bound-constrained quasi-Newton algorithm. The reference parameter set is retrieved independently from the optimization initial condition when the very common dimension reduction strategy (i.e. scalar multipliers) is adopted. Furthermore, the sensitivity analysis results suggest that most of the variability in this high-dimensional parameter space can be captured with a few orthogonal directions. A parametrization based on the SVD leading singular vectors was found very promising but should be combined with another regularization strategy in order to prevent overfitting.
Abusam, A.A.A.; Keesman, K.J.; Straten, van G.; Spanjers, H.; Meinema, K.
2001-01-01
This paper demonstrates the application of the factorial sensitivity analysis methodology in studying the influence of variations in stoichiometric, kinetic and operating parameters on the performance indices of an oxidation ditch simulation model (benchmark). Factorial sensitivity analysis investig
Liu, M.; He, B.; Lü, A.; Zhou, L.; Wu, J.
2014-06-01
Parameters sensitivity analysis is a crucial step in effective model calibration. It quantitatively apportions the variation of model output to different sources of variation, and identifies how "sensitive" a model is to changes in the values of model parameters. Through calibration of parameters that are sensitive to model outputs, parameter estimation becomes more efficient. Due to uncertainties associated with yield estimates in a regional assessment, field-based models that perform well at field scale are not accurate enough to model at regional scale. Conducting parameters sensitivity analysis at the regional scale and analyzing the differences of parameter sensitivity between stations would make model calibration and validation in different sub-regions more efficient. Further, it would benefit the model applied to the regional scale. Through simulating 2000 × 22 samples for 10 stations in the Huanghuaihai Plain, this study discovered that TB (Optimal temperature), HI (Normal harvest index), WA (Potential radiation use efficiency), BN2 (Normal fraction of N in crop biomass at mid-season) and RWPC1 (Fraction of root weight at emergency) are more sensitive than other parameters. Parameters that determine nutrition supplement and LAI development have higher global sensitivity indices than first-order indices. For spatial application, soil diversity is crucial because soil is responsible for crop parameters sensitivity index differences between sites.
Hostache, R.; Hissler, C.; Matgen, P.; Guignard, C.; Bates, P.
2014-09-01
Fine sediments represent an important vector of pollutant diffusion in rivers. When deposited in floodplains and riverbeds, they can be responsible for soil pollution. In this context, this paper proposes a modelling exercise aimed at predicting transport and diffusion of fine sediments and dissolved pollutants. The model is based upon the Telemac hydro-informatic system (dynamical coupling Telemac-2D-Sysiphe). As empirical and semiempirical parameters need to be calibrated for such a modelling exercise, a sensitivity analysis is proposed. An innovative point in this study is the assessment of the usefulness of dissolved trace metal contamination information for model calibration. Moreover, for supporting the modelling exercise, an extensive database was set up during two flood events. It includes water surface elevation records, discharge measurements and geochemistry data such as time series of dissolved/particulate contaminants and suspended-sediment concentrations. The most sensitive parameters were found to be the hydraulic friction coefficients and the sediment particle settling velocity in water. It was also found that model calibration did not benefit from dissolved trace metal contamination information. Using the two monitored hydrological events as calibration and validation, it was found that the model is able to satisfyingly predict suspended sediment and dissolve pollutant transport in the river channel. In addition, a qualitative comparison between simulated sediment deposition in the floodplain and a soil contamination map shows that the preferential zones for deposition identified by the model are realistic.
Parameter uncertainty, sensitivity, and sediment coupling in bioenergetics-based food web models
Energy Technology Data Exchange (ETDEWEB)
Barron, M.G.; Cacela, D.; Beltman, D. [Hagler Bailly, Boulder, CO (United States)
1995-12-31
A bioenergetics-based food web model was developed and calibrated using measured PCB water and sediment concentrations in two Great Lakes food webs: Green Bay, Michigan and Lake Ontario. The model incorporated functional based trophic levels and sediment, water, and food chain exposures of PCBs to aquatic biota. Sensitivity analysis indicated the parameters with the greatest influence on PCBs in top predators were lipid content of plankton and benthos, planktivore assimilation efficiency, Kow, prey selection, and ambient temperature. Sediment-associated PCBs were estimated to contribute over 90% of PCBs in benthivores and less than 50% in piscivores. Ranges of PCB concentrations in top predators estimated by Monte Carlo simulation incorporating parameter uncertainty were within one order of magnitude of modal values. Model applications include estimation of exceedences of human and ecological thresholds. The results indicate that point estimates from bioenergetics-based food web models have substantial uncertainty that should be considered in regulatory and scientific applications.
Sensitivity of precipitation to parameter values in the community atmosphere model version 5
Energy Technology Data Exchange (ETDEWEB)
Johannesson, Gardar; Lucas, Donald; Qian, Yun; Swiler, Laura Painton; Wildey, Timothy Michael
2014-03-01
One objective of the Climate Science for a Sustainable Energy Future (CSSEF) program is to develop the capability to thoroughly test and understand the uncertainties in the overall climate model and its components as they are being developed. The focus on uncertainties involves sensitivity analysis: the capability to determine which input parameters have a major influence on the output responses of interest. This report presents some initial sensitivity analysis results performed by Lawrence Livermore National Laboratory (LNNL), Sandia National Laboratories (SNL), and Pacific Northwest National Laboratory (PNNL). In the 2011-2012 timeframe, these laboratories worked in collaboration to perform sensitivity analyses of a set of CAM5, 2° runs, where the response metrics of interest were precipitation metrics. The three labs performed their sensitivity analysis (SA) studies separately and then compared results. Overall, the results were quite consistent with each other although the methods used were different. This exercise provided a robustness check of the global sensitivity analysis metrics and identified some strongly influential parameters.
An Investigation on the Sensitivity of the Parameters of Urban Flood Model
M, A. B.; Lohani, B.; Jain, A.
2015-12-01
Global climatic change has triggered weather patterns which lead to heavy and sudden rainfall in different parts of world. The impact of heavy rainfall is severe especially on urban areas in the form of urban flooding. In order to understand the effect of heavy rainfall induced flooding, it is necessary to model the entire flooding scenario more accurately, which is now becoming possible with the availability of high resolution airborne LiDAR data and other real time observations. However, there is not much understanding on the optimal use of these data and on the effect of other parameters on the performance of the flood model. This study aims at developing understanding on these issues. In view of the above discussion, the aim of this study is to (i) understand that how the use of high resolution LiDAR data improves the performance of urban flood model, and (ii) understand the sensitivity of various hydrological parameters on urban flood modelling. In this study, modelling of flooding in urban areas due to heavy rainfall is carried out considering Indian Institute of Technology (IIT) Kanpur, India as the study site. The existing model MIKE FLOOD, which is accepted by Federal Emergency Management Agency (FEMA), is used along with the high resolution airborne LiDAR data. Once the model is setup it is made to run by changing the parameters such as resolution of Digital Surface Model (DSM), manning's roughness, initial losses, catchment description, concentration time, runoff reduction factor. In order to realize this, the results obtained from the model are compared with the field observations. The parametric study carried out in this work demonstrates that the selection of catchment description plays a very important role in urban flood modelling. Results also show the significant impact of resolution of DSM, initial losses and concentration time on urban flood model. This study will help in understanding the effect of various parameters that should be part of a
Xi, Qing; Li, Zhao-Fu; Luo, Chuan
2014-05-01
Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.
Bertozzi, Luigi; Stagni, Rita; Fantozzi, Silvia; Cappello, Angelo
2007-01-01
If the biomechanic function of the different anatomical sub-structures of the knee joint was needed in physiological conditions, the only possible way is a modelling approach. Subject-specific geometries and kinematic data, acquired from the same living subject, were the foundations of the 3D quasi-static knee model developed. Each cruciate ligament was modelled by means of 25 elastic springs, paying attention to the anatomical twisting of the fibres. The sensitivity of the model to the cross-sectional area was performed during the anterior/posterior tibial translations, the sensitivity to all the cruciate ligaments parameters was performed during the internal/external rotations. The model reproduced very well the mechanical behaviour reported in literature during anterior/posterior translations, in particular considering 30% of the mean insertional area. During the internal/external tibial rotations, similar behaviour of the axial torques was obtained in the three sensitivity analyses. The overlapping of the ligaments was assessed at about 25 degrees of internal axial rotation. The presented model featured a good level of accuracy in combination with a low computational weight, and it could provide an in vivo estimation of the role of the cruciate ligaments during the execution of daily living activities.
Sensitivity of subject-specific models to Hill muscle-tendon model parameters in simulations of gait
Carbone, Vincenzo; van der Krogt, Marjolein; Koopman, Hubertus F.J.M.; Verdonschot, Nicolaas Jacobus Joseph
2016-01-01
Subject-specific musculoskeletal (MS) models of the lower extremity are essential for applications such as predicting the effects of orthopedic surgery. We performed an extensive sensitivity analysis to assess the effects of potential errors in Hill muscle–tendon (MT) model parameters for each of
Sensitivity of subject-specific models to Hill muscle-tendon model parameters in simulations of gait
Carbone, V.; Krogt, M.M. van der; Koopman, H.F.J.M.; Verdonschot, N.J.
2016-01-01
Subject-specific musculoskeletal (MS) models of the lower extremity are essential for applications such as predicting the effects of orthopedic surgery. We performed an extensive sensitivity analysis to assess the effects of potential errors in Hill muscle-tendon (MT) model parameters for each of th
Sensitivity of subject-specific models to Hill muscle-tendon model parameters in simulations of gait
Carbone, Vincenzo; van der Krogt, Marjolein; Koopman, Hubertus F.J.M.; Verdonschot, Nicolaas Jacobus Joseph
2016-01-01
Subject-specific musculoskeletal (MS) models of the lower extremity are essential for applications such as predicting the effects of orthopedic surgery. We performed an extensive sensitivity analysis to assess the effects of potential errors in Hill muscle–tendon (MT) model parameters for each of th
Sensitivity testing practice on pre-processing parameters in hard and soft coupled modeling
Directory of Open Access Journals (Sweden)
Z. Ignaszak
2010-01-01
Full Text Available This paper pays attention to the problem of practical applicability of coupled modeling with the use of hard and soft models types and necessity of adapted to that models data base possession. The data base tests results for cylindrical 30 mm diameter casting made of AlSi7Mg alloy were presented. In simulation tests that were applied the Calcosoft system with CAFE (Cellular Automaton Finite Element module. This module which belongs to „multiphysics” models enables structure prediction of complete casting with division of columnar and equiaxed crystals zones of -phase. Sensitivity tests of coupled model on the particular values parameters changing were made. On these basis it was determined the relations of CET (columnar-to-equaiaxed transition zone position influence. The example of virtual structure validation based on real structure with CET zone location and grain size was shown.
Parameter Sensitivity of High–Order Equivalent Circuit Models Of Turbine Generator
Directory of Open Access Journals (Sweden)
T. Niewierowicz–Swiecicka
2010-01-01
Full Text Available This work shows the results of a parametric sensitivity analysis applied to a state–space representation of high–order two–axis equivalent circuits (ECs of a turbo generator (150 MVA, 120 MW, 13.8 kV y 50 Hz. The main purpose of this study is to evaluate each parameter impact on the transient response of the analyzed two–axis models –d–axis ECs with one to five damper branches and q–axis ECs from one to four damper branches–. The parametric sensitivity concept is formulated in a general context and the sensibility function is established from the generator response to a short circuit condition. Results ponder the importance played by each parameter in the model behavior. The algorithms were design within MATLAB® environment. The study gives way to conclusions on electromagnetic aspects of solid rotor synchronous generators that have not been previously studied. The methodology presented here can be applied to any other physical system.
A practical method to assess model sensitivity and parameter uncertainty in C cycle models
Delahaies, Sylvain; Roulstone, Ian; Nichols, Nancy
2015-04-01
The carbon cycle combines multiple spatial and temporal scales, from minutes to hours for the chemical processes occurring in plant cells to several hundred of years for the exchange between the atmosphere and the deep ocean and finally to millennia for the formation of fossil fuels. Together with our knowledge of the transformation processes involved in the carbon cycle, many Earth Observation systems are now available to help improving models and predictions using inverse modelling techniques. A generic inverse problem consists in finding a n-dimensional state vector x such that h(x) = y, for a given N-dimensional observation vector y, including random noise, and a given model h. The problem is well posed if the three following conditions hold: 1) there exists a solution, 2) the solution is unique and 3) the solution depends continuously on the input data. If at least one of these conditions is violated the problem is said ill-posed. The inverse problem is often ill-posed, a regularization method is required to replace the original problem with a well posed problem and then a solution strategy amounts to 1) constructing a solution x, 2) assessing the validity of the solution, 3) characterizing its uncertainty. The data assimilation linked ecosystem carbon (DALEC) model is a simple box model simulating the carbon budget allocation for terrestrial ecosystems. Intercomparison experiments have demonstrated the relative merit of various inverse modelling strategies (MCMC, ENKF) to estimate model parameters and initial carbon stocks for DALEC using eddy covariance measurements of net ecosystem exchange of CO2 and leaf area index observations. Most results agreed on the fact that parameters and initial stocks directly related to fast processes were best estimated with narrow confidence intervals, whereas those related to slow processes were poorly estimated with very large uncertainties. While other studies have tried to overcome this difficulty by adding complementary
Ricciuto, D. M.; Mei, R.; Mao, J.; Hoffman, F. M.; Kumar, J.
2015-12-01
Uncertainties in land parameters could have important impacts on simulated water and energy fluxes and land surface states, which will consequently affect atmospheric and biogeochemical processes. Therefore, quantification of such parameter uncertainties using a land surface model is the first step towards better understanding of predictive uncertainty in Earth system models. In this study, we applied a random-sampling, high-dimensional model representation (RS-HDMR) method to analyze the sensitivity of simulated photosynthesis, surface energy fluxes and surface hydrological components to selected land parameters in version 4.5 of the Community Land Model (CLM4.5). Because of the large computational expense of conducting ensembles of global gridded model simulations, we used the results of a previous cluster analysis to select one thousand representative land grid cells for simulation. Plant functional type (PFT)-specific uniform prior ranges for land parameters were determined using expert opinion and literature survey, and samples were generated with a quasi-Monte Carlo approach-Sobol sequence. Preliminary analysis of 1024 simulations suggested that four PFT-dependent parameters (including slope of the conductance-photosynthesis relationship, specific leaf area at canopy top, leaf C:N ratio and fraction of leaf N in RuBisco) are the dominant sensitive parameters for photosynthesis, surface energy and water fluxes across most PFTs, but with varying importance rankings. On the other hand, for surface ans sub-surface runoff, PFT-independent parameters, such as the depth-dependent decay factors for runoff, play more important roles than the previous four PFT-dependent parameters. Further analysis by conditioning the results on different seasons and years are being conducted to provide guidance on how climate variability and change might affect such sensitivity. This is the first step toward coupled simulations including biogeochemical processes, atmospheric processes
Qi, Wei; Zhang, Chi; Fu, Guangtao; Zhou, Huicheng
2016-02-01
It is widely recognized that optimization algorithm parameters have significant impacts on algorithm performance, but quantifying the influence is very complex and difficult due to high computational demands and dynamic nature of search parameters. The overall aim of this paper is to develop a global sensitivity analysis based framework to dynamically quantify the individual and interactive influence of algorithm parameters on algorithm performance. A variance decomposition sensitivity analysis method, Analysis of Variance (ANOVA), is used for sensitivity quantification, because it is capable of handling small samples and more computationally efficient compared with other approaches. The Shuffled Complex Evolution method developed at the University of Arizona algorithm (SCE-UA) is selected as an optimization algorithm for investigation, and two criteria, i.e., convergence speed and success rate, are used to measure the performance of SCE-UA. Results show the proposed framework can effectively reveal the dynamic sensitivity of algorithm parameters in the search processes, including individual influences of parameters and their interactive impacts. Interactions between algorithm parameters have significant impacts on SCE-UA performance, which has not been reported in previous research. The proposed framework provides a means to understand the dynamics of algorithm parameter influence, and highlights the significance of considering interactive parameter influence to improve algorithm performance in the search processes.
Investigations of the sensitivity of a coronal mass ejection model (ENLIL) to solar input parameters
DEFF Research Database (Denmark)
Falkenberg, Thea Vilstrup; Vršnak, B.; Taktakishvili, A.;
2010-01-01
investigate the parameter space of the ENLILv2.5b model using the CME event of 25 July 2004. ENLIL is a time‐dependent 3‐D MHD model that can simulate the propagation of cone‐shaped interplanetary coronal mass ejections (ICMEs) through the solar system. Excepting the cone parameters (radius, position...... (CMEs), but in order to predict the caused effects, we need to be able to model their propagation from their origin in the solar corona to the point of interest, e.g., Earth. Many such models exist, but to understand the models in detail we must understand the primary input parameters. Here we......, and initial velocity), all remaining parameters are varied, resulting in more than 20 runs investigated here. The output parameters considered are velocity, density, magnetic field strength, and temperature. We find that the largest effects on the model output are the input parameters of upper limit...
Zhao, J.; Tiede, C.
2011-05-01
An implementation of uncertainty analysis (UA) and quantitative global sensitivity analysis (SA) is applied to the non-linear inversion of gravity changes and three-dimensional displacement data which were measured in and active volcanic area. A didactic example is included to illustrate the computational procedure. The main emphasis is placed on the problem of extended Fourier amplitude sensitivity test (E-FAST). This method produces the total sensitivity indices (TSIs), so that all interactions between the unknown input parameters are taken into account. The possible correlations between the output an the input parameters can be evaluated by uncertainty analysis. Uncertainty analysis results indicate the general fit between the physical model and the measurements. Results of the sensitivity analysis show quite different sensitivities for the measured changes as they relate to the unknown parameters of a physical model for an elastic-gravitational source. Assuming a fixed number of executions, thirty different seeds are observed to determine the stability of this method.
Bifurcations, chaos, and sensitivity to parameter variations in the Sato cardiac cell model
Otte, Stefan; Berg, Sebastian; Luther, Stefan; Parlitz, Ulrich
2016-08-01
The dynamics of a detailed ionic cardiac cell model proposed by Sato et al. (2009) is investigated in terms of periodic and chaotic action potentials, bifurcation scenarios, and coexistence of attractors. Starting from the model's standard parameter values bifurcation diagrams are computed to evaluate the model's robustness with respect to (small) parameter changes. While for some parameters the dynamics turns out to be practically independent from their values, even minor changes of other parameters have a very strong impact and cause qualitative changes due to bifurcations or transitions to coexisting attractors. Implications of this lack of robustness are discussed.
DEFF Research Database (Denmark)
Sørensen, Jacob Viborg Tornfeldt; Madsen, Henrik; Madsen, H.
2006-01-01
sensitivity study of three well known Kalman filter approaches for the assimilation of water levels in a three dimensional hydrodynamic modelling system. The filters considered are the ensemble Kalman filter (EnKF), the reduced rank square root Kalman filter (RRSQRT) and the steady Kalman filter....... A sensitivity analysis of key parameters in the schemes is undertaken for a setup in an idealised bay. The sensitivity of the resulting root mean square error (RMSE) is shown to be low to moderate. Hence the schemes are robust within an acceptable range and their application even with misspecified parameters...... is to be encouraged in this perspective. However, the predicted uncertainty of the assimilation results are sensitive to the parameters and hence must be applied with care. The sensitivity study further demonstrates the effectiveness of the steady Kalman filter in the given system as well as the great impact...
Energy Technology Data Exchange (ETDEWEB)
K. Zhang; Y.S. Wu; J.E. Houseworth
2006-03-21
The unsaturated fractured volcanic deposits at Yucca Mountain have been intensively investigated as a possible repository site for storing high-level radioactive waste. Field studies at the site have revealed that there exist large variabilities in hydrological parameters over the spatial domain of the mountain. This paper reports on a systematic analysis of hydrological parameters using the site-scale 3-D unsaturated zone (UZ) flow model. The objectives of the sensitivity analyses are to evaluate the effects of uncertainties in hydrologic parameters on modeled UZ flow and contaminant transport results. Sensitivity analyses are carried out relative to fracture and matrix permeability and capillary strength (van Genuchten a), through variation of these parameter values by one standard deviation from the base-case values. The parameter variation results in eight parameter sets. Modeling results for the eight UZ flow sensitivity cases have been compared with field observed data and simulation results from the base-case model. The effects of parameter uncertainties on the flow fields are discussed and evaluated through comparison of results for flow and transport. In general, this study shows that uncertainties in matrix parameters cause larger uncertainty in simulated moisture flux than corresponding uncertainties in fracture properties for unsaturated flow through heterogeneous fractured rock.
Energy Technology Data Exchange (ETDEWEB)
Zhang, Keni; Wu, Yu-Shu; Houseworth, James E
2006-02-01
The unsaturated fractured volcanic deposits at Yucca Mountain in Nevada, USA, have been intensively investigated as a possible repository site for storing high-level radioactive waste. Field studies at the site have revealed that there exist large variabilities in hydrological parameters over the spatial domain of the mountain. Systematic analyses of hydrological parameters using a site-scale three-dimensional unsaturated zone (UZ) flow model have been undertaken. The main objective of the sensitivity analyses was to evaluate the effects of uncertainties in hydrologic parameters on modeled UZ flow and contaminant transport results. Sensitivity analyses were carried out relative to fracture and matrix permeability and capillary strength (van Genuchten {alpha}) through variation of these parameter values by one standard deviation from the base-case values. The parameter variation resulted in eight parameter sets. Modeling results for the eight UZ flow sensitivity cases have been compared with field observed data and simulation results from the base-case model. The effects of parameter uncertainties on the flow fields were evaluated through comparison of results for flow and transport. In general, this study shows that uncertainties in matrix parameters cause larger uncertainty in simulated moisture flux than corresponding uncertainties in fracture properties for unsaturated flow through heterogeneous fractured rock.
Characterizing parameter sensitivity and uncertainty for a snow model across hydroclimatic regimes
He, M.; Hogue, T.S.; Franz, K.J.; Margulis, S.A.; Vrugt, J.A.
2011-01-01
The National Weather Service (NWS) uses the SNOW17 model to forecast snow accumulation and ablation processes in snow-dominated watersheds nationwide. Successful application of the SNOW17 relies heavily on site-specific estimation of model parameters. The current study undertakes a comprehensive
Characterizing parameter sensitivity and uncertainty for a snow model across hydroclimatic regimes
He, M.; Hogue, T.S.; Franz, K.J.; Margulis, S.A.; Vrugt, J.A.
2011-01-01
The National Weather Service (NWS) uses the SNOW17 model to forecast snow accumulation and ablation processes in snow-dominated watersheds nationwide. Successful application of the SNOW17 relies heavily on site-specific estimation of model parameters. The current study undertakes a comprehensive sen
Shaw, Jeremy A.; Daescu, Dacian N.
2017-08-01
This article presents the mathematical framework to evaluate the sensitivity of a forecast error aspect to the input parameters of a weak-constraint four-dimensional variational data assimilation system (w4D-Var DAS), extending the established theory from strong-constraint 4D-Var. Emphasis is placed on the derivation of the equations for evaluating the forecast sensitivity to parameters in the DAS representation of the model error statistics, including bias, standard deviation, and correlation structure. A novel adjoint-based procedure for adaptive tuning of the specified model error covariance matrix is introduced. Results from numerical convergence tests establish the validity of the model error sensitivity equations. Preliminary experiments providing a proof-of-concept are performed using the Lorenz multi-scale model to illustrate the theoretical concepts and potential benefits for practical applications.
Correlation between oncogenic mutations and parameter sensitivity of the apoptosis pathway model.
Directory of Open Access Journals (Sweden)
Jia Chen
2014-01-01
Full Text Available One of the major breakthroughs in oncogenesis research in recent years is the discovery that, in most patients, oncogenic mutations are concentrated in a few core biological functional pathways. This discovery indicates that oncogenic mechanisms are highly related to the dynamics of biologic regulatory networks, which govern the behaviour of functional pathways. Here, we propose that oncogenic mutations found in different biological functional pathways are closely related to parameter sensitivity of the corresponding networks. To test this hypothesis, we focus on the DNA damage-induced apoptotic pathway--the most important safeguard against oncogenesis. We first built the regulatory network that governs the apoptosis pathway, and then translated the network into dynamics equations. Using sensitivity analysis of the network parameters and comparing the results with cancer gene mutation spectra, we found that parameters that significantly affect the bifurcation point correspond to high-frequency oncogenic mutations. This result shows that the position of the bifurcation point is a better measure of the functionality of a biological network than gene expression levels of certain key proteins. It further demonstrates the suitability of applying systems-level analysis to biological networks as opposed to studying genes or proteins in isolation.
DEFF Research Database (Denmark)
Sayar, N.A.; Chen, B.H.; Lye, G.J.
2009-01-01
In this paper we have used a proposed mathematical model, describing the carbon-carbon bond format ion reaction between beta-hydroxypyruvate and glycolaldehyde to synthesise L-erythrulose, catalysed by the enzyme transketolase, for the analysis of the sensitivity of the process to its kinetic par....... (C) 2009 Elsevier B.V. All rights reserved....
Clustering of Parameter Sensitivities: Examples from a Helicopter Airframe Model Updating Exercise
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H. Shahverdi
2009-01-01
Full Text Available The need for high fidelity models in the aerospace industry has become ever more important as increasingly stringent requirements on noise and vibration levels, reliability, maintenance costs etc. come into effect. In this paper, the results of a finite element model updating exercise on a Westland Lynx XZ649 helicopter are presented. For large and complex structures, such as a helicopter airframe, the finite element model represents the main tool for obtaining accurate models which could predict the sensitivities of responses to structural changes and optimisation of the vibration levels. In this study, the eigenvalue sensitivities with respect to Young's modulus and mass density are used in a detailed parameterisation of the structure. A new methodology is developed using an unsupervised learning technique based on similarity clustering of the columns of the sensitivity matrix. An assessment of model updating strategies is given and comparative results for the correction of vibration modes are discussed in detail. The role of the clustering technique in updating large-scale models is emphasised.
Data Assimilation and Sensitivity of the Black Sea Model to Parameters
Kazantsev, Eugene
2011-01-01
An adjoint based technique is applied to a Shallow Water Model in order to estimate influence of the model's parameters on the solution. Among parameters the bottom topography, initial conditions, boundary conditions on rigid boundaries, viscosity coefficients and the amplitude of the wind stress tension are considered. Their influence is analyzed from different points of view. Two configurations have been analyzed: an academic case of the model in a square box and a more realistic case simulating Black Sea currents. It is shown in both experiments that the boundary conditions near a rigid boundary influence the most the solution. This fact points out the necessity to identify optimal boundary approximation during a model development.
DEFF Research Database (Denmark)
Smets, Barth F.; Lardon, Laurent
2009-01-01
of the outcomes to the various plasmid dynamic parameters. For our analysis, we developed a set of user-friendly MatLab® routines, which are deposited in the public domain. We hope that the availability of these routines will encourage the computationally untrained microbiologist to make use of these mathematical...... models. Finally, further permutations, as well as limitations of these mass action models in view of the structured complexity of most microbial systems are addressed....
Lee, Jaewoo; Jeon, J. H.; Je, C. H.; Lee, S. Q.; Yang, W. S.; Lee, S.-G.
2016-03-01
An empirical-based open-circuit sensitivity model for a capacitive-type MEMS acoustic sensor is presented. To intuitively evaluate the characteristic of the open-circuit sensitivity, the empirical-based model is proposed and analysed by using a lumped spring-mass model and a pad test sample without a parallel plate capacitor for the parasitic capacitance. The model is composed of three different parameter groups: empirical, theoretical, and mixed data. The empirical residual stress from the measured pull-in voltage of 16.7 V and the measured surface topology of the diaphragm were extracted as +13 MPa, resulting in the effective spring constant of 110.9 N/m. The parasitic capacitance for two probing pads including the substrate part was 0.25 pF. Furthermore, to verify the proposed model, the modelled open-circuit sensitivity was compared with the measured value. The MEMS acoustic sensor had an open- circuit sensitivity of -43.0 dBV/Pa at 1 kHz with a bias of 10 V, while the modelled open- circuit sensitivity was -42.9 dBV/Pa, which showed good agreement in the range from 100 Hz to 18 kHz. This validates the empirical-based open-circuit sensitivity model for designing capacitive-type MEMS acoustic sensors.
DEFF Research Database (Denmark)
Sørensen, Jacob Viborg Tornfeldt; Madsen, Henrik; Madsen, H.
2006-01-01
sensitivity study of three well known Kalman filter approaches for the assimilation of water levels in a three dimensional hydrodynamic modelling system. The filters considered are the ensemble Kalman filter (EnKF), the reduced rank square root Kalman filter (RRSQRT) and the steady Kalman filter...... is to be encouraged in this perspective. However, the predicted uncertainty of the assimilation results are sensitive to the parameters and hence must be applied with care. The sensitivity study further demonstrates the effectiveness of the steady Kalman filter in the given system as well as the great impact...
Energy Technology Data Exchange (ETDEWEB)
Aceves, S; Dibble, R; Flowers, D; Smith, J R; Westbrook, C K
1999-07-19
This paper uses the HCT (Hydrodynamics, Chemistry and Transport) chemical kinetics code to analyze natural gas HCCI combustion in an engine. The HCT code has been modified to better represent the conditions existing inside an engine, including a wall heat transfer correlation. Combustion control and low power output per displacement remain as two of the biggest challenges to obtaining satisfactory performance out of an HCCI engine, and these are addressed in this paper. The paper considers the effect of natural gas composition on HCCI combustion, and then explores three control strategies for HCCI engines: DME (dimethyl ether) addition, intake heating and hot EGR addition. The results show that HCCI combustion is sensitive to natural gas composition, and an active control may be required to compensate for possible changes in composition. The three control strategies being considered have a significant effect in changing the combustion parameters for the engine, and should be able to control HCCI combustion.
High sensitivity of p-modes near the acoustic cutoff frequency to solar model parameters
Guenther, D. B.
1991-01-01
The p-mode frequencies of low l have been calculated for solar models with initial helium mass fraction varying from Y = 0.2753-0.2875. The differences in frequency of the p-modes in the frequency range, 2500-4500 microHz, do not exceed 1-5 microHz among the models. But in the vicinity of the acoustic cutoff frequency, near 5000 microHz the p-mode frequency differences are enhanced by a factor of 4. The enhanced sensitivity of p-modes near the acoustic cutoff frequency was further tested by calculating and comparing p-mode frequencies of low l for two solar models one incorporating the Eddington T-tau relation and the other the Krishna Swamy T-tau relation. Again, it is found that p-modes with frequencies near the acoustic cutoff frequency show a significant increase in sensitivity to the different T-tau relations, compared to lower frequency p-modes. It is noted that frequencies above the acoustic cutoff frequency are complex, hence, cannot be modeled by the adiabatic pulsation code (assumes real eigenfrequencies) used in these calculations.
Flow analysis with WaSiM-ETH – model parameter sensitivity at different scales
Directory of Open Access Journals (Sweden)
J. Cullmann
2006-01-01
Full Text Available WaSiM-ETH (Gurtz et al., 2001, a widely used water balance simulation model, is tested for its suitability to serve for flow analysis in the context of rainfall runoff modelling and flood forecasting. In this paper, special focus is on the resolution of the process domain in space as well as in time. We try to couple model runs with different calculation time steps in order to reduce the effort arising from calculating the whole flow hydrograph at the hourly time step. We aim at modelling on the daily time step for water balance purposes, switching to the hourly time step whenever high-resolution information is necessary (flood forecasting. WaSiM-ETH is used at different grid resolutions, thus we try to become clear about being able to transfer the model in spatial resolution. We further use two different approaches for the overland flow time calculation within the sub-basins of the test watershed to gain insights about the process dynamics portrayed by the model. Our findings indicate that the model is very sensitive to time and space resolution and cannot be transferred across scales without recalibration.
Bakopoulou, C.; Bulygina, N.; Butler, A. P.; McIntyre, N. R.
2012-04-01
Land surface models (LSMs) are recognised as important components of Global Circulation Models (GCMs). Simulating exchanges of the moisture, carbon and energy between land surface and atmosphere in a consistent manner requires physics-based LSMs of high complexity, fine vertical resolution and a large number of parameters that need to be estimated. The "physics" that is incorporated in such models is generally based on our knowledge of point (or very small) scale hydrological processes. Therefore, while larger GCM grid-scale performance may be the ultimate goal, the ability of the model to simulate the point-scale processes is, intuitively, a pre-requisite for its reliable use at larger scales. Critical evaluation of model performance and parameter uncertainty at point scales is therefore a rational starting point for critical evaluation of LSMs; and identification of optimal parameter sets at the point scale is a significant stage of the model evaluation at larger scales. The Joint UK Land Environment Simulator (JULES) is a complex LSM, which is used to represent surface exchanges in the UK Met Office's forecast and climate change models. This complexity necessitates a large number of model parameters (in total 108) some of which are incapable of being measured directly at large (i.e. kilometer) scales. For this reason, a parameter sensitivity analysis is a vital confidence building process within the framework of every LSM, and as a part of the calibration strategy. The problem of JULES parameter estimation and uncertainty at the point scale with a view to assessing the accuracy and the uncertainty in the default parameter values is addressed. The sensitivity of the JULES output of soil moisture is examined using parameter response surface analysis. The implemented technique is based on the Regional Sensitivity Analysis method (RSA), which evaluates the model response surface over a region of parameter space using Monte Carlo sampling. The modified version of RSA
Zhang, Jianying; Chen, Gangling; Gong, Xuedong
2017-06-01
The quantitative structure-property relationship (QSPR) methodology was applied to describe and seek the relationship between the structures and energetic properties (and sensitivity) for some common energy compounds. An extended series of structural and energetic descriptors was obtained with density functional theory (DFT) B3LYP and semi-empirical PM3 approaches. Results indicate that QSPR model constructed using quantum descriptors can be applied to verify the confidence of calculation results compared with experimental data. It can be extended to predict the properties of similar compounds.
The power of sensitivity analysis and thoughts on models with large numbers of parameters
Energy Technology Data Exchange (ETDEWEB)
Havlacek, William [Los Alamos National Laboratory
2008-01-01
The regulatory systems that allow cells to adapt to their environments are exceedingly complex, and although we know a great deal about the intricate mechanistic details of many of these systems, our ability to make accurate predictions about their system-level behaviors is severely limited. We would like to make such predictions for a number of reasons. How can we reverse dysfunctional molecular changes of these systems that cause disease? More generally, how can we harness and direct cellular activities for beneficial purposes? Our ability to make accurate predictions about a system is also a measure ofour fundamental understanding of that system. As evidenced by our mastery of technological systems, a useful understanding ofa complex system can often be obtained through the development and analysis ofa mathematical model, but predictive modeling of cellular regulatory systems, which necessarily relies on quantitative experimentation, is still in its infancy. There is much that we need to learn before modeling for practical applications becomes routine. In particular, we need to address a number of issues surrounding the large number of parameters that are typically found in a model for a cellular regulatory system.
Institute of Scientific and Technical Information of China (English)
QIU Zhongfeng; Andrea M. DOGLIOLI; HE Yijun; Francois CARLOTTI
2011-01-01
This paper presents two comparisons or tests for a Lagrangian model of zooplankton dispersion: numerical schemes and time steps. Firstly, we compared three numerical schemes using idealized circulations. Results show that the precisions of the advanced Adams-Bashfold-Moulton (ABM) method and the Runge-Kutta (RK) method were in the same order and both were much higher than that of the Euler method. Furthermore, the advanced ABM method is more efficient than the RK method in computational memory requirements and time consumption. We therefore chose the advanced ABM method as the Lagrangian particle-tracking algorithm. Secondly, we performed a sensitivity test for time steps, using outputs of the hydrodynamic model, Symphonie. Results show that the time step choices depend on the fluid response time that is related to the spatial resolution of velocity fields. The method introduced by Oliveira et al. in 2002 is suitable for choosing time steps of Lagrangian particle-tracking models, at least when only considering advection.
DEFF Research Database (Denmark)
Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen
2011-01-01
Uncertainty derived from one of the process models – such as one-dimensional secondary settling tank (SST) models – can impact the output of the other process models, e.g., biokinetic (ASM1), as well as the integrated wastewater treatment plant (WWTP) models. The model structure and parameter...... uncertainty of settler models can therefore propagate, and add to the uncertainties in prediction of any plant performance criteria. Here we present an assessment of the relative significance of secondary settling model performance in WWTP simulations. We perform a global sensitivity analysis (GSA) based....... The outcome of this study contributes to a better understanding of uncertainty in WWTPs, and explicitly demonstrates the significance of secondary settling processes that are crucial elements of model prediction under dry and wet-weather loading conditions....
Directory of Open Access Journals (Sweden)
Thomas Cornelissen
2016-05-01
Full Text Available Parameterization of physically based and distributed hydrological models for mesoscale catchments remains challenging because the commonly available data base is insufficient for calibration. In this paper, we parameterize a mesoscale catchment for the distributed model HydroGeoSphere by transferring evapotranspiration parameters calibrated at a highly-equipped headwater catchment in addition to literature data. Based on this parameterization, the sensitivity of the mesoscale catchment to spatial variability in land use, potential evapotranspiration and precipitation and of the headwater catchment to mesoscale soil and land use data was conducted. Simulations of the mesoscale catchment with transferred parameters reproduced daily discharge dynamics and monthly evapotranspiration of grassland, deciduous and coniferous vegetation in a satisfactory manner. Precipitation was the most sensitive input data with respect to total runoff and peak flow rates, while simulated evapotranspiration components and patterns were most sensitive to spatially distributed land use parameterization. At the headwater catchment, coarse soil data resulted in a change in runoff generating processes based on the interplay between higher wetness prior to a rainfall event, enhanced groundwater level rise and accordingly, lower transpiration rates. Our results indicate that the direct transfer of parameters is a promising method to benefit highly equipped simulations of the headwater catchments.
Metzger, Christine; Nilsson, Mats B.; Peichl, Matthias; Jansson, Per-Erik
2016-12-01
In contrast to previous peatland carbon dioxide (CO2) model sensitivity analyses, which usually focussed on only one or a few processes, this study investigates interactions between various biotic and abiotic processes and their parameters by comparing CoupModel v5 results with multiple observation variables. Many interactions were found not only within but also between various process categories simulating plant growth, decomposition, radiation interception, soil temperature, aerodynamic resistance, transpiration, soil hydrology and snow. Each measurement variable was sensitive to up to 10 (out of 54) parameters, from up to 7 different process categories. The constrained parameter ranges varied, depending on the variable and performance index chosen as criteria, and on other calibrated parameters (equifinalities). Therefore, transferring parameter ranges between models needs to be done with caution, especially if such ranges were achieved by only considering a few processes. The identified interactions and constrained parameters will be of great interest to use for comparisons with model results and data from similar ecosystems. All of the available measurement variables (net ecosystem exchange, leaf area index, sensible and latent heat fluxes, net radiation, soil temperatures, water table depth and snow depth) improved the model constraint. If hydraulic properties or water content were measured, further parameters could be constrained, resolving several equifinalities and reducing model uncertainty. The presented results highlight the importance of considering biotic and abiotic processes together and can help modellers and experimentalists to design and calibrate models as well as to direct experimental set-ups in peatland ecosystems towards modelling needs.
Clustering of Parameter Sensitivities: Examples from a Helicopter Airframe Model Updating Exercise
Shahverdi, H.; C. Mares; W. Wang; J. E. Mottershead
2009-01-01
The need for high fidelity models in the aerospace industry has become ever more important as increasingly stringent requirements on noise and vibration levels, reliability, maintenance costs etc. come into effect. In this paper, the results of a finite element model updating exercise on a Westland Lynx XZ649 helicopter are presented. For large and complex structures, such as a helicopter airframe, the finite element model represents the main tool for obtaining accurate models which could pre...
Energy Technology Data Exchange (ETDEWEB)
Xu, S.; Peddle, D.R.; Coburn, C.A.; Kienzle, S. [Univ. of Lethbridge, Dept. of Geography, Lethbridge, Alberta (Canada)
2008-06-15
Net primary productivity (NPP) is a key component of the terrestrial carbon cycle and is important in ecological, watershed, and forest management studies, and more broadly in global climate change research. Determining the relative importance and magnitude of uncertainty of NPP model inputs is important for proper carbon reporting over larger areas and time periods. This paper presents a systematic evaluation of the boreal ecosystem productivity simulator (BEPS) model in mountainous terrain using an established montane forest test site in Kananaskis, Alberta, in the Canadian Rocky Mountains. Model runs were based on forest (land cover, leaf area index (LAI), biomass) and climate-water inputs (solar radiation, temperature, precipitation, humidity, soil water holding capacity) derived from digital elevation model (DEM) derivatives, climate data, geographical information system (GIS) functions, and topographically corrected satellite imagery. Four sensitivity analyses were conducted as a controlled series of experiments involving (i) NPP individual parameter sensitivity for a full growing season, (ii) NPP independent variation tests (parameter {mu} {+-} 1{sigma}), (iii) factorial analyses to assess more complex multiple-factor interactions, and (iv) topographic correction. The results, validated against field measurements, showed that modeled NPP was sensitive to most inputs measured in the study area, with LAI and forest type the most important forest input, and solar radiation the most important climate input. Soil available water holding capacity expressed as a function of wetness index was only significant in conjunction with precipitation when both parameters represented a moisture-deficit situation. NPP uncertainty resulting from topographic influence was equivalent to 140 kg C ha{sup -1}{center_dot}year{sup -1}. This suggested that topographic correction of model inputs is important for accurate NPP estimation. The BEPS model, designed originally for flat
De Groote, F; Van Campen, A; Jonkers, I; De Schutter, J
2010-07-20
We assessed and compared sensitivities of dynamic simulations to musculotendon (MT) parameters for gait and dynamometer experiments. Our aim with this comparison was to investigate whether dynamometer experiments could provide information about MT-parameters that are important to reliably study MT-function during gait. This would mean that dynamometer experiments could be used to estimate these parameters. Muscle contribution to the joint torque (MT-torque) rather than relative MT-force primarily affects the resulting gait pattern and torque measured by the dynamometer. In contrast to recent studies, therefore, we assessed the sensitivity of the MT-torque, rather than the sensitivity of the relative MT-force. Based on sensitivity of the MT-torque to a parameter perturbation, MT-parameters of the knee flexors and extensors were classified in three categories: low, medium, and high. For gait, classification was based on the average sensitivity during a gait cycle. For isometric and isokinetic dynamometer experiments, classification was based on the highest sensitivity found in the experiments. The calculated muscle contributions to the knee torque during gait and dynamometer experiments had a high sensitivity to only a limited number of MT-parameters of the knee flexors and extensors, suggesting that not all MT-parameters need to be estimated. In general, the highest sensitivity was found for tendon slack length. However, for some muscles the sensitivity to the optimal fibre length or the maximal isometric muscle force was also high or medium. The classification of the individual MT-parameters for gait and dynamometer experiments was largely similar. We therefore conclude that dynamometer experiments provide information about MT-parameters important to reliably study MT-function during gait, so that subject-specific estimates of MT-parameters could be made based on dynamometer experiments.
Rosso, M.; Sesenna, R.; Magni, L.; Demurtas, L.; Uras, G.
2009-04-01
bidimensional and monodimensional commercial models for the simulation of debris flow, in particular because of the reconstruction of famous and expected events in the river basin of the Comboè torrent (Aosta Valley, Italy), it has been possible to reach careful consideration about the calibration of the rheological parameters and the sensitivity of simulation models, specifically about the variability of them. The geomechanical and volumetric characteristics of the sediment at the bottom of the debris could produce uncertainties in model implementation, above all in not exclusively cinematic models, mostly influenced by the rheological parameters. The parameter that mainly influences the final result of the applied numerical models is the volumetric solid concentration that is variable in space and time during the debris flow propagation. In fact rheological parameters are described by a power equation of volumetric concentration. The potentiality and the suitability of a numerical code in the engineering environmental application have to be consider not referring only to the quality and amount of results, but also to the sensibility regarding the parameters variability that are bases of the inner ruotines of the program. Therefore, a suitable model will have to be sensitive to the variability of parameters that the customer can calculate with greater precision. On the other side, it will have to be sufficiently stable to the variation of those parameters that the customer cannot define univocally, but only by range of variation. One of the models utilized for the simulation of debris flow on the Comboè Torrent has been demonstrated as an heavy influenced example by small variation of rheological parameters. Consequently, in spite of the possibility to lead accurate procedures of back-analysis about a recent intense event, it has been found a difficulty in the calibration of the concentration for new expected events. That involved an extreme variability of the final results
Garavaglia, F.; Seyve, E.; Gottardi, F.; Le Lay, M.; Gailhard, J.; Garçon, R.
2014-12-01
MORDOR is a conceptual hydrological model extensively used in Électricité de France (EDF, French electric utility company) operational applications: (i) hydrological forecasting, (ii) flood risk assessment, (iii) water balance and (iv) climate change studies. MORDOR is a lumped, reservoir, elevation based model with hourly or daily areal rainfall and air temperature as the driving input data. The principal hydrological processes represented are evapotranspiration, direct and indirect runoff, ground water, snow accumulation and melt and routing. The model has been intensively used at EDF for more than 20 years, in particular for modeling French mountainous watersheds. In the matter of parameters calibration we propose and test alternative multi-criteria techniques based on two specific approaches: automatic calibration using single-objective functions and a priori parameter calibration founded on hydrological watershed features. The automatic calibration approach uses single-objective functions, based on Kling-Gupta efficiency, to quantify the good agreement between the simulated and observed runoff focusing on four different runoff samples: (i) time-series sample, (I) annual hydrological regime, (iii) monthly cumulative distribution functions and (iv) recession sequences.The primary purpose of this study is to analyze the definition and sensitivity of MORDOR parameters testing different calibration techniques in order to: (i) simplify the model structure, (ii) increase the calibration-validation performance of the model and (iii) reduce the equifinality problem of calibration process. We propose an alternative calibration strategy that reaches these goals. The analysis is illustrated by calibrating MORDOR model to daily data for 50 watersheds located in French mountainous regions.
DEFF Research Database (Denmark)
Ferrari, A.; Gutierrez, S.; Sin, Gürkan
2016-01-01
A steady state model for a production scale milk drying process was built to help process understanding and optimization studies. It involves a spray chamber and also internal/external fluid beds. The model was subjected to a comprehensive statistical analysis for quality assurance using sensitiv...
Fang, Z.; Ward, A. L.; Fang, Y.; Yabusaki, S.
2011-12-01
High-resolution geologic models have proven effective in improving the accuracy of subsurface flow and transport predictions. However, many of the parameters in subsurface flow and transport models cannot be determined directly at the scale of interest and must be estimated through inverse modeling. A major challenge, particularly in vadose zone flow and transport, is the inversion of the highly-nonlinear, high-dimensional problem as current methods are not readily scalable for large-scale, multi-process models. In this paper we describe the implementation of a fully automated approach for addressing complex parameter optimization and sensitivity issues on massively parallel multi- and many-core systems. The approach is based on the integration of PNNL's extreme scale Subsurface Transport Over Multiple Phases (eSTOMP) simulator, which uses the Global Array toolkit, with the Beowulf-Cluster inspired parallel nonlinear parameter estimation software, BeoPEST in the MPI mode. In the eSTOMP/BeoPEST implementation, a pre-processor generates all of the PEST input files based on the eSTOMP input file. Simulation results for comparison with observations are extracted automatically at each time step eliminating the need for post-process data extractions. The inversion framework was tested with three different experimental data sets: one-dimensional water flow at Hanford Grass Site; irrigation and infiltration experiment at the Andelfingen Site; and a three-dimensional injection experiment at Hanford's Sisson and Lu Site. Good agreements are achieved in all three applications between observations and simulations in both parameter estimates and water dynamics reproduction. Results show that eSTOMP/BeoPEST approach is highly scalable and can be run efficiently with hundreds or thousands of processors. BeoPEST is fault tolerant and new nodes can be dynamically added and removed. A major advantage of this approach is the ability to use high-resolution geologic models to preserve
Jang, Jinwoo; Smyth, Andrew W.
2017-01-01
The objective of structural model updating is to reduce inherent modeling errors in Finite Element (FE) models due to simplifications, idealized connections, and uncertainties of material properties. Updated FE models, which have less discrepancies with real structures, give more precise predictions of dynamic behaviors for future analyses. However, model updating becomes more difficult when applied to civil structures with a large number of structural components and complicated connections. In this paper, a full-scale FE model of a major long-span bridge has been updated for improved consistency with real measured data. Two methods are applied to improve the model updating process. The first method focuses on improving the agreement of the updated mode shapes with the measured data. A nonlinear inequality constraint equation is used to an optimization procedure, providing the capability to regulate updated mode shapes to remain within reasonable agreements with those observed. An interior point algorithm deals with nonlinearity in the objective function and constraints. The second method finds very efficient updating parameters in a more systematic way. The selection of updating parameters in FE models is essential to have a successful updating result because the parameters are directly related to the modal properties of dynamic systems. An in-depth sensitivity analysis is carried out in an effort to precisely understand the effects of physical parameters in the FE model on natural frequencies. Based on the sensitivity analysis, cluster analysis is conducted to find a very efficient set of updating parameters.
Directory of Open Access Journals (Sweden)
Li Wang
2017-02-01
Full Text Available The ability to obtain appropriate parameters for an advanced pressurized water reactor (PWR unit model is of great significance for power system analysis. The attributes of that ability include the following: nonlinear relationships, long transition time, intercoupled parameters and difficult obtainment from practical test, posed complexity and difficult parameter identification. In this paper, a model and a parameter identification method for the PWR primary loop system were investigated. A parameter identification process was proposed, using a particle swarm optimization (PSO algorithm that is based on random perturbation (RP-PSO. The identification process included model variable initialization based on the differential equations of each sub-module and program setting method, parameter obtainment through sub-module identification in the Matlab/Simulink Software (Math Works Inc., Natick, MA, USA as well as adaptation analysis for an integrated model. A lot of parameter identification work was carried out, the results of which verified the effectiveness of the method. It was found that the change of some parameters, like the fuel temperature and coolant temperature feedback coefficients, changed the model gain, of which the trajectory sensitivities were not zero. Thus, obtaining their appropriate values had significant effects on the simulation results. The trajectory sensitivities of some parameters in the core neutron dynamic module were interrelated, causing the parameters to be difficult to identify. The model parameter sensitivity could be different, which would be influenced by the model input conditions, reflecting the parameter identifiability difficulty degree for various input conditions.
On Non-Linear Sensitivity of Marine Biological Models to Parameter Variations
2007-01-01
M.B., 2002. Understanding uncertain enviromental systems. In: Grasman, J., van Straten, G. (Eds.), Predictability and Nonlinear Modelling in Natural...Lekien, F., 2006. Quantifying uncertainities in ocean predictions. In: Paluszkiewicz, T., Harper, S. (Eds.), Oceanography, special issue on Advances in
Sensitivity Analysis of Empirical Parameters in the Ionosphere-Plasmasphere Model
2011-03-01
drift that is calculated within the model. The most significant results from this comparison occur during the day near Mada - gascar (45◦E) and in the...cases. Although the decrease near Mada - gascar occurs for this case with a maximum decrease of 50% (29 TECU) at 0600UT, the increase in the Southeast
Kinnison, D. E.; Brasseur, G. P.; Walters, S.; Garcia, R. R.; Marsh, D. R.; Sassi, F.; Harvey, V. L.; Randall, C. E.; Emmons, L.; Lamarque, J. F.; Hess, P.; Orlando, J. J.; Tie, X. X.; Randel, W.; Pan, L. L.; Gettelman, A.; Granier, C.; Diehl, T.; Niemeier, U.; Simmons, A. J.
2007-10-01
The Model for Ozone and Related Chemical Tracers, version 3 (MOZART-3), which represents the chemical and physical processes from the troposphere through the lower mesosphere, was used to evaluate the representation of long-lived tracers and ozone using three different meteorological fields. The meteorological fields are based on (1) the Whole Atmosphere Community Climate Model, version 1b (WACCM1b), (2) the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis, and (3) a new reanalysis for year 2000 from ECMWF called EXP471. Model-derived tracers (methane, water vapor, and total inorganic nitrogen) and ozone are compared to data climatologies from satellites. Model mean age of air was also derived and compared to in situ CO2 and SF6 data. A detailed analysis of the chemical fields simulated by MOZART-3 shows that even though the general features characterizing the three dynamical sets are rather similar, slight differences in winds and temperature can produce substantial differences in the calculated distributions of chemical tracers. The MOZART-3 simulations that use meteorological fields from WACCM1b and ECMWF EXP471 represented best the distribution of long-lived tracers and mean age of air in the stratosphere. There was a significant improvement using the ECMWF EXP471 reanalysis data product over the ECMWF operational data product. The effect of the quasi-biennial oscillation circulation on long-lived tracers and ozone is examined.
Parameter sensitivity study of a Field II multilayer transducer model on a convex transducer
DEFF Research Database (Denmark)
Bæk, David; Jensen, Jørgen Arendt; Willatzen, Morten
2009-01-01
.ResultsPredictions using the ZR give a pressure pulse error (PPE) and an intensity error (IE) of 32 % and 23 %, respectively, relative to the measured. Altering the piezoelectric permittivity +12 % from ZR decreases the PPE to 30 % and the IE to 2 % relative to the measured. Changing the stiffness constant of the lens -4......A multilayer transducer model for predicting a transducer impulse response has in earlier works been developed and combined with the Field II software. This development was tested on current, voltage, and intensity measurements on piezoceramics discs (Bæk et al. IUS 2008) and a convex 128 element...... ultrasound imaging transducer (Bæk et al. ICU 2009). The model benefits from its 1D simplicity and hasshown to give an amplitude error around 1.7‐2 dB. However, any prediction of amplitude, phase, and attenuation of pulses relies on the accuracy of manufacturer supplied material characteristics, which may...
The sensitivity of conduit flow models to basic input parameters: there is no need for magma trolls!
Thomas, M. E.; Neuberg, J. W.
2012-04-01
Many conduit flow models now exist and some of these models are becoming extremely complicated, conducted in three dimensions and incorporating the physics of compressible three phase fluids (magmas), intricate conduit geometries and fragmentation processes, to name but a few examples. These highly specialised models are being used to explain observations of the natural system, and there is a danger that possible explanations may be getting needlessly complex. It is coherent, for instance, to propose the involvement of sub-surface dwelling magma trolls as an explanation for the change in a volcanoes eruptive style, but assuming the simplest explanation would prevent such additions, unless they were absolutely necessary. While the understanding of individual, often small scale conduit processes is increasing rapidly, is this level of detail necessary? How sensitive are these models to small changes in the most basic of governing parameters? Can these changes be used to explain observed behaviour? Here we will examine the sensitivity of conduit flow models to changes in the melt viscosity, one of the fundamental inputs to any such model. However, even addressing this elementary issue is not straight forward. There are several viscosity models in existence, how do they differ? Can models that use different viscosity models be realistically compared? Each of these viscosity models is also heavily dependent on the magma composition and/or temperature, and how well are these variables constrained? Magma temperatures and water contents are often assumed as "ball-park" figures, and are very rarely exactly known for the periods of observation the models are attempting to explain, yet they exhibit a strong controlling factor on the melt viscosity. The role of both these variables will be discussed. For example, using one of the available viscosity models a 20 K decrease in temperature of the melt results in a greater than 100% increase in the melt viscosity. With changes of
Jiang, S C; Zhang, X X
2005-12-01
A two-dimensional model was developed to model the effects of dynamic changes in the physical properties on tissue temperature and damage to simulate laser-induced interstitial thermotherapy (LITT) treatment procedures with temperature monitoring. A modified Monte Carlo method was used to simulate photon transport in the tissue in the non-uniform optical property field with the finite volume method used to solve the Pennes bioheat equation to calculate the temperature distribution and the Arrhenius equation used to predict the thermal damage extent. The laser light transport and the heat transfer as well as the damage accumulation were calculated iteratively at each time step. The influences of different laser sources, different applicator sizes, and different irradiation modes on the final damage volume were analyzed to optimize the LITT treatment. The numerical results showed that damage volume was the smallest for the 1,064-nm laser, with much larger, similar damage volumes for the 980- and 850-nm lasers at normal blood perfusion rates. The damage volume was the largest for the 1,064-nm laser with significantly smaller, similar damage volumes for the 980- and 850-nm lasers with temporally interrupted blood perfusion. The numerical results also showed that the variations in applicator sizes, laser powers, heating durations and temperature monitoring ranges significantly affected the shapes and sizes of the thermal damage zones. The shapes and sizes of the thermal damage zones can be optimized by selecting different applicator sizes, laser powers, heating duration times, temperature monitoring ranges, etc.
Rodrigo-Ilarri, Javier; Segura-Sobrino, Francisco; Rodrigo-Clavero, Maria-Elena
2014-05-01
Landfills are commonly used as the final deposit of urban solid waste. Despite the waste is previously processed on a treatment plant, the final amount of organic matter which reaches the landfill is large however. The biodegradation of this organic matter forms a mixture of greenhouse gases (essentially Methane and Carbon-Dioxide as well as Ammonia and Hydrogen Sulfide). From the environmental point of view, solid waste landfills are therefore considered to be one of the main greenhouse gas sources. Different mathematical models are usually applied to predict the amount of biogas produced on real landfills. The waste chemical composition and the availability of water in the solid waste appear to be the main parameters of these models. Results obtained when performing a sensitivity analysis over the biogas production model parameters under real conditions are shown. The importance of a proper characterizacion of the waste as well as the necessity of improving the understanding of the behaviour and development of the water on the unsaturated mass of waste are emphasized.
Energy Technology Data Exchange (ETDEWEB)
Moriyama, Kiyofumi; Park, Hyun Sun, E-mail: hejsunny@postech.ac.kr; Hwang, Byoungcheol; Jung, Woo Hyun
2016-06-15
Highlights: • Application of JASMINE code to melt jet breakup and coolability in APR1400 condition. • Coolability indexes for quasi steady state breakup and cooling process. • Typical case in complete breakup/solidification, film boiling quench not reached. • Significant impact of water depth and melt jet size; weak impact of model parameters. - Abstract: The breakup of a melt jet falling in a water pool and the coolability of the melt particles produced by such jet breakup are important phenomena in terms of the mitigation of severe accident consequences in light water reactors, because the molten and relocated core material is the primary heat source that governs the accident progression. We applied a modified version of the fuel–coolant interaction simulation code, JASMINE, developed at Japan Atomic Energy Agency (JAEA) to a plant scale simulation of melt jet breakup and cooling assuming an ex-vessel condition in the APR1400, a Korean advanced pressurized water reactor. Also, we examined the sensitivity on seven model parameters and five initial/boundary condition variables. The results showed that the melt cooling performance of a 6 m deep water pool in the reactor cavity is enough for removing the initial melt enthalpy for solidification, for a melt jet of 0.2 m initial diameter. The impacts of the model parameters were relatively weak and that of some of the initial/boundary condition variables, namely the water depth and melt jet diameter, were very strong. The present model indicated that a significant fraction of the melt jet is not broken up and forms a continuous melt pool on the containment floor in cases with a large melt jet diameter, 0.5 m, or a shallow water pool depth, ≤3 m.
Zhang, Y. Y.; Shao, Q. X.; Ye, A. Z.; Xing, H. T.; Xia, J.
2016-02-01
Integrated water system modeling is a feasible approach to understanding severe water crises in the world and promoting the implementation of integrated river basin management. In this study, a classic hydrological model (the time variant gain model: TVGM) was extended to an integrated water system model by coupling multiple water-related processes in hydrology, biogeochemistry, water quality, and ecology, and considering the interference of human activities. A parameter analysis tool, which included sensitivity analysis, autocalibration and model performance evaluation, was developed to improve modeling efficiency. To demonstrate the model performances, the Shaying River catchment, which is the largest highly regulated and heavily polluted tributary of the Huai River basin in China, was selected as the case study area. The model performances were evaluated on the key water-related components including runoff, water quality, diffuse pollution load (or nonpoint sources) and crop yield. Results showed that our proposed model simulated most components reasonably well. The simulated daily runoff at most regulated and less-regulated stations matched well with the observations. The average correlation coefficient and Nash-Sutcliffe efficiency were 0.85 and 0.70, respectively. Both the simulated low and high flows at most stations were improved when the dam regulation was considered. The daily ammonium-nitrogen (NH4-N) concentration was also well captured with the average correlation coefficient of 0.67. Furthermore, the diffuse source load of NH4-N and the corn yield were reasonably simulated at the administrative region scale. This integrated water system model is expected to improve the simulation performances with extension to more model functionalities, and to provide a scientific basis for the implementation in integrated river basin managements.
Messina, Palmira; Lathière, Juliette; Sindelarova, Katerina; Vuichard, Nicolas; Granier, Claire; Ghattas, Josefine; Cozic, Anne; Hauglustaine, Didier A.
2016-11-01
A new version of the biogenic volatile organic compounds (BVOCs) emission scheme has been developed in the global vegetation model ORCHIDEE (Organizing Carbon and Hydrology in Dynamic EcosystEm), which includes an extended list of biogenic emitted compounds, updated emission factors (EFs), a dependency on light for almost all compounds and a multi-layer radiation scheme. Over the 2000-2009 period, using this model, we estimate mean global emissions of 465 Tg C yr-1 for isoprene, 107.5 Tg C yr-1 for monoterpenes, 38 Tg C yr-1 for methanol, 25 Tg C yr-1 for acetone and 24 Tg C yr-1 for sesquiterpenes. The model results are compared to state-of-the-art emission budgets, showing that the ORCHIDEE emissions are within the range of published estimates. ORCHIDEE BVOC emissions are compared to the estimates of the Model of Emissions of Gases and Aerosols from Nature (MEGAN), which is largely used throughout the biogenic emissions and atmospheric chemistry community. Our results show that global emission budgets of the two models are, in general, in good agreement. ORCHIDEE emissions are 8 % higher for isoprene, 8 % lower for methanol, 17 % higher for acetone, 18 % higher for monoterpenes and 39 % higher for sesquiterpenes, compared to the MEGAN estimates. At the regional scale, the largest differences between ORCHIDEE and MEGAN are highlighted for isoprene in northern temperate regions, where ORCHIDEE emissions are higher by 21 Tg C yr-1, and for monoterpenes, where they are higher by 4.4 and 10.2 Tg C yr-1 in northern and southern tropical regions compared to MEGAN. The geographical differences between the two models are mainly associated with different EF and plant functional type (PFT) distributions, while differences in the seasonal cycle are mostly driven by differences in the leaf area index (LAI). Sensitivity tests are carried out for both models to explore the response to key variables or parameters such as LAI and light-dependent fraction (LDF). The ORCHIDEE and
Advancing sensitivity analysis to precisely characterize temporal parameter dominance
Guse, Björn; Pfannerstill, Matthias; Strauch, Michael; Reusser, Dominik; Lüdtke, Stefan; Volk, Martin; Gupta, Hoshin; Fohrer, Nicola
2016-04-01
Parameter sensitivity analysis is a strategy for detecting dominant model parameters. A temporal sensitivity analysis calculates daily sensitivities of model parameters. This allows a precise characterization of temporal patterns of parameter dominance and an identification of the related discharge conditions. To achieve this goal, the diagnostic information as derived from the temporal parameter sensitivity is advanced by including discharge information in three steps. In a first step, the temporal dynamics are analyzed by means of daily time series of parameter sensitivities. As sensitivity analysis method, we used the Fourier Amplitude Sensitivity Test (FAST) applied directly onto the modelled discharge. Next, the daily sensitivities are analyzed in combination with the flow duration curve (FDC). Through this step, we determine whether high sensitivities of model parameters are related to specific discharges. Finally, parameter sensitivities are separately analyzed for five segments of the FDC and presented as monthly averaged sensitivities. In this way, seasonal patterns of dominant model parameter are provided for each FDC segment. For this methodical approach, we used two contrasting catchments (upland and lowland catchment) to illustrate how parameter dominances change seasonally in different catchments. For all of the FDC segments, the groundwater parameters are dominant in the lowland catchment, while in the upland catchment the controlling parameters change seasonally between parameters from different runoff components. The three methodical steps lead to clear temporal patterns, which represent the typical characteristics of the study catchments. Our methodical approach thus provides a clear idea of how the hydrological dynamics are controlled by model parameters for certain discharge magnitudes during the year. Overall, these three methodical steps precisely characterize model parameters and improve the understanding of process dynamics in hydrological
Kramers, G.; Dam, van J.C.; Ritsema, C.J.; Stagnitti, F.; Oostindie, K.; Dekker, L.W.
2005-01-01
A modified version of the popular agrohydrological model SWAP has been used to evaluate modelling of soil water flow and crop growth at field situations in which water repellency causes preferential flow. The parameter sensitivity in such situations has been studied. Three options to model soil
Yanagi, Sílvia N M; Costa, Marcos H
2011-12-01
This study evaluates the sensitivity of the surface albedo simulated by the Integrated Biosphere Simulator (IBIS) to a set of Amazonian tropical rainforest canopy architectural and optical parameters. The parameters tested in this study are the orientation and reflectance of the leaves of upper and lower canopies in the visible (VIS) and near-infrared (NIR) spectral bands. The results are evaluated against albedo measurements taken above the K34 site at the INPA (Instituto Nacional de Pesquisas da Amazônia) Cuieiras Biological Reserve. The sensitivity analysis indicates a strong response to the upper canopy leaves orientation (χup) and to the reflectivity in the near-infrared spectral band (ρNIR,up), a smaller sensitivity to the reflectivity in the visible spectral band (ρVIS,up) and no sensitivity at all to the lower canopy parameters, which is consistent with the canopy structure. The combination of parameters that minimized the Root Mean Square Error and mean relative error are χup = 0.86, ρVIS,up = 0.062 and ρNIR,up = 0.275. The parameterizations performed resulted in successful simulations of tropical rainforest albedo by IBIS, indicating its potential to simulate the canopy radiative transfer for narrow spectral bands and permitting close comparison with remote sensing products.
Energy Technology Data Exchange (ETDEWEB)
Ibsen, Lars Bo; Liingaard, M.
2006-12-15
A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. In this technical report the steps of establishing a lumped-parameter model are presented. Following sections are included in this report: Static and dynamic formulation, Simple lumped-parameter models and Advanced lumped-parameter models. (au)
Fujimura, Kazumasa; Iseri, Yoshihiko; Kanae, Shinjiro; Murakami, Masahiro
2014-05-01
Accurate estimation of low flow can contribute to better water resources management and also lead to more reliable evaluation of climate change impacts on water resources. In the early study, the nonlinearity of low flow related to the storage in the basin was suggested by Horton (1937) as the exponential function of Q=KSN, where Q is the discharge, S is the storage, K is a constant and N is the exponent value. In the recent study by Ding (2011) showed the general storage-discharge equation of Q = KNSN. Since the constant K is defined as the fractional recession constant and symbolized as Au by Ando et al. (1983), in this study, we rewrite this equation as Qg=AuNSgN, where Qg is the groundwater runoff and Sg is the groundwater storage. Although this equation was applied to a short-term runoff event of less than 14 hours using the unit hydrograph method by Ding, it was not yet applied for a long-term runoff event including low flow more than 10 years. This study performed a sensitive analysis of two parameters of the constant Au and exponent value N by using the hourly hydrological model for two mountainous basins in Japan. The hourly hydrological model used in this study was presented by Fujimura et al. (2012), which comprise the Diskin-Nazimov infiltration model, groundwater recharge and groundwater runoff calculations, and a direct runoff component. The study basins are the Sameura Dam basin (SAME basin) (472 km2) located in the western Japan which has variability of rainfall, and the Shirakawa Dam basin (SIRA basin) (205km2) located in a region of heavy snowfall in the eastern Japan, that are different conditions of climate and geology. The period of available hourly data for the SAME basin is 20 years from 1 January 1991 to 31 December 2010, and for the SIRA basin is 10 years from 1 October 2003 to 30 September 2013. In the sensitive analysis, we prepared 19900 sets of the two parameters of Au and N, the Au value ranges from 0.0001 to 0.0100 in steps of 0
Figueiro, Thiago; Choi, Kang-Hoon; Gutsch, Manuela; Freitag, Martin; Hohle, Christoph; Tortai, Jean-Hervé; Saib, Mohamed; Schiavone, Patrick
2012-11-01
In electron proximity effect correction (PEC), the quality of a correction is highly dependent on the quality of the model. Therefore it is of primary importance to have a reliable methodology to extract the parameters and assess the quality of a model. Among others the model describes how the energy of the electrons spreads out in the target material (via the Point Spread Function, PSF) as well as the influence of the resist process. There are different models available in previous studies, as well as several different approaches to obtain the appropriate value for their parameters. However, those are restricted in terms of complexity, or require a prohibitive number of measurements, which is limited for a certain PSF model. In this work, we propose a straightforward approach to obtain the value of parameters of a PSF. The methodology is general enough to apply for more sophisticated models as well. It focused on improving the three steps of model calibration procedure: First, it is using a good set of calibration patterns. Secondly, it secures the optimization step and avoids falling into a local optimum. And finally the developed method provides an improved analysis of the calibration step, which allows quantifying the quality of the model as well as enabling a comparison of different models. The methodology described in the paper is implemented as specific module in a commercial tool.
Directory of Open Access Journals (Sweden)
N. Montaldo
2003-01-01
Full Text Available Recent developments have made land-surface models (LSMs more complex through the inclusion of more processes and controlling variables, increasing numbers of parameters and uncertainty in their estimates. To overcome these uncertainties, prior to applying a distributed LSM over the whole Toce basin (Italian Alps, a field campaign was carried out at an experimental plot within the basin before exploring the skill and parameter importance (sensitivity using the TOPLATS model, an existing LSM. In the summer and autumn of 1999, which included both wet (atmosphere controlled and dry (soil controlled periods, actual evapotranspiration estimates were performed using Bowen ratio and, for a short period, eddy correlation methods. Measurements performed with the two methods are in good agreement. The calibrated LSM predicts actual evapotranspiration quite well over the whole observation period. A sensitivity analysis of the evapotranspiration to model parameters was performed through the global multivariate technique during both wet and dry periods of the campaign. This approach studies the influence of each parameter without conditioning on certain values of the other variables. Hence, all parameters are varied simultaneously using, for instance, a uniform sampling strategy through a Monte Carlo simulation framework. The evapotranspiration is highly sensitive to the soil parameters, especially during wet periods. However, the evapotranspiration is also sensitive to some vegetation parameters and, during dry periods, wilting point is the most critical for evapotranspiration predictions. This result confirms the importance of correct representation of vegetation properties which, in water-limited conditions, control evapotranspiration. Keywords: evapotranspiration, sensitivity analysis, land surface model, eddy correlation, Alpine basin
TSUNAMI DISPERSION SENSITIVITY TO SEISMIC SOURCE PARAMETERS
Directory of Open Access Journals (Sweden)
Oleg Igorevich Gusev
2016-05-01
Full Text Available The study focuses on the sensitivity of frequency dispersion effects to the form of initial surface elevation of seismic tsunami source. We vary such parameters of the source as rupture depth, dip-angle and rake-angle. Some variations in magnitude and strike angle are considered. The fully nonlinear dispersive model on a rotating sphere is used for wave propagation simulations. The main feature of the algorithm is the splitting of initial system on two subproblems of elliptic and hyperbolic type, which allows implementation of well-suitable numerical methods for them. The dispersive effects are estimated through differences between computations with the dispersive and nondispersive models. We consider an idealized test with a constant depth, a model basin for near-field tsunami simulations and a realistic scenario. Our computations show that the dispersion effects are strongly sensitive to the rupture depth and the dip-angle variations. Waves generated by sources with lager magnitude may be even more affected by dispersion.
Ren, Huiying; Hou, Zhangshuan; Huang, Maoyi; Bao, Jie; Sun, Yu; Tesfa, Teklu; Ruby Leung, L.
2016-05-01
The Community Land Model (CLM) represents physical, chemical, and biological processes of the terrestrial ecosystems that interact with climate across a range of spatial and temporal scales. As CLM includes numerous sub-models and associated parameters, the high-dimensional parameter space presents a formidable challenge for quantifying uncertainty and improving Earth system predictions needed to assess environmental changes and risks. This study aims to evaluate the potential of transferring hydrologic model parameters in CLM through sensitivity analyses and classification across watersheds from the Model Parameter Estimation Experiment (MOPEX) in the United States. The sensitivity of CLM-simulated water and energy fluxes to hydrological parameters across 431 MOPEX basins are first examined using an efficient stochastic sampling-based sensitivity analysis approach. Linear, interaction, and high-order nonlinear impacts are all identified via statistical tests and stepwise backward removal parameter screening. The basins are then classified according to their parameter sensitivity patterns (internal attributes), as well as their hydrologic indices/attributes (external hydrologic factors) separately, using Principal component analysis (PCA) and expectation-maximization (EM) - based clustering approach. Similarities and differences among the parameter sensitivity-based classification system (S-Class), the hydrologic indices-based classification (H-Class), and the Koppen climate classification systems (K-Class) are discussed. Within each parameter sensitivity-based classification system (S-Class) with similar parameter sensitivity characteristics, similar inversion modeling setups can be used for parameter calibration, and the parameters and their contribution or significance to water and energy cycling may also be more transferrable. This classification study provides guidance on identifiable parameters, and on parameterization and inverse model design for CLM but the
Ballarini, E; Bauer, S; Eberhardt, C; Beyer, C
2012-06-01
Transverse dispersion represents an important mixing process for transport of contaminants in groundwater and constitutes an essential prerequisite for geochemical and biodegradation reactions. Within this context, this work describes the detailed numerical simulation of highly controlled laboratory experiments using uranine, bromide and oxygen depleted water as conservative tracers for the quantification of transverse mixing in porous media. Synthetic numerical experiments reproducing an existing laboratory experimental set-up of quasi two-dimensional flow through tank were performed to assess the applicability of an analytical solution of the 2D advection-dispersion equation for the estimation of transverse dispersivity as fitting parameter. The fitted dispersivities were compared to the "true" values introduced in the numerical simulations and the associated error could be precisely estimated. A sensitivity analysis was performed on the experimental set-up in order to evaluate the sensitivities of the measurements taken at the tank experiment on the individual hydraulic and transport parameters. From the results, an improved experimental set-up as well as a numerical evaluation procedure could be developed, which allow for a precise and reliable determination of dispersivities. The improved tank set-up was used for new laboratory experiments, performed at advective velocities of 4.9 m d(-1) and 10.5 m d(-1). Numerical evaluation of these experiments yielded a unique and reliable parameter set, which closely fits the measured tracer concentration data. For the porous medium with a grain size of 0.25-0.30 mm, the fitted longitudinal and transverse dispersivities were 3.49×10(-4) m and 1.48×10(-5) m, respectively. The procedures developed in this paper for the synthetic and rigorous design and evaluation of the experiments can be generalized and transferred to comparable applications.
Gibson, G. A.; Spitz, Y. H.
2011-11-01
We use a series of Monte Carlo experiments to explore simultaneously the sensitivity of the BEST marine ecosystem model to environmental forcing, initial conditions, and biological parameterizations. Twenty model output variables were examined for sensitivity. The true sensitivity of biological and environmental parameters becomes apparent only when each parameter is allowed to vary within its realistic range. Many biological parameters were important only to their corresponding variable, but several biological parameters, e.g., microzooplankton grazing and small phytoplankton doubling rate, were consistently very important to several output variables. Assuming realistic biological and environmental variability, the standard deviation about simulated mean mesozooplankton biomass ranged from 1 to 14 mg C m - 3 during the year. Annual primary productivity was not strongly correlated with temperature but was positively correlated with initial nitrate and light. Secondary productivity was positively correlated with primary productivity and negatively correlated with spring bloom timing. Mesozooplankton productivity was not correlated with water temperature, but a shift towards a system in which smaller zooplankton undertake a greater proportion of the secondary production as the water temperature increases appears likely. This approach to incorporating environmental variability within a sensitivity analysis could be extended to any ecosystem model to gain confidence in climate-driven ecosystem predictions.
Energy Technology Data Exchange (ETDEWEB)
Yang, Ben; Qian, Yun; Berg, Larry K.; Ma, Po-Lun; Wharton, Sonia; Bulaevskaya, Vera; Yan, Huiping; Hou, Zhangshuan; Shaw, William J.
2016-07-21
We evaluate the sensitivity of simulated turbine-height winds to 26 parameters applied in a planetary boundary layer (PBL) scheme and a surface layer scheme of the Weather Research and Forecasting (WRF) model over an area of complex terrain during the Columbia Basin Wind Energy Study. An efficient sampling algorithm and a generalized linear model are used to explore the multiple-dimensional parameter space and quantify the parametric sensitivity of modeled turbine-height winds. The results indicate that most of the variability in the ensemble simulations is contributed by parameters related to the dissipation of the turbulence kinetic energy (TKE), Prandtl number, turbulence length scales, surface roughness, and the von Kármán constant. The relative contributions of individual parameters are found to be dependent on both the terrain slope and atmospheric stability. The parameter associated with the TKE dissipation rate is found to be the most important one, and a larger dissipation rate can produce larger hub-height winds. A larger Prandtl number results in weaker nighttime winds. Increasing surface roughness reduces the frequencies of both extremely weak and strong winds, implying a reduction in the variability of the wind speed. All of the above parameters can significantly affect the vertical profiles of wind speed, the altitude of the low-level jet and the magnitude of the wind shear strength. The wind direction is found to be modulated by the same subset of influential parameters. Remainder of abstract is in attachment.
Ohara, Masaki; Noguchi, Toshihiko
This paper describes a new method for a rotor position sensorless control of a surface permanent magnet synchronous motor based on a model reference adaptive system (MRAS). This method features the MRAS in a current control loop to estimate a rotor speed and position by using only current sensors. This method as well as almost all the conventional methods incorporates a mathematical model of the motor, which consists of parameters such as winding resistances, inductances, and an induced voltage constant. Hence, the important thing is to investigate how the deviation of these parameters affects the estimated rotor position. First, this paper proposes a structure of the sensorless control applied in the current control loop. Next, it proves the stability of the proposed method when motor parameters deviate from the nominal values, and derives the relationship between the estimated position and the deviation of the parameters in a steady state. Finally, some experimental results are presented to show performance and effectiveness of the proposed method.
Directory of Open Access Journals (Sweden)
Sílvia N. M. Yanagi
2011-12-01
Full Text Available This study evaluates the sensitivity of the surface albedo simulated by the Integrated Biosphere Simulator (IBIS to a set of Amazonian tropical rainforest canopy architectural and optical parameters. The parameters tested in this study are the orientation and reflectance of the leaves of upper and lower canopies in the visible (VIS and near-infrared (NIR spectral bands. The results are evaluated against albedo measurements taken above the K34 site at the INPA (Instituto Nacional de Pesquisas da Amazônia Cuieiras Biological Reserve. The sensitivity analysis indicates a strong response to the upper canopy leaves orientation (x up and to the reflectivity in the near-infrared spectral band (rNIR,up, a smaller sensitivity to the reflectivity in the visible spectral band (rVIS,up and no sensitivity at all to the lower canopy parameters, which is consistent with the canopy structure. The combination of parameters that minimized the Root Mean Square Error and mean relative error are Xup = 0.86, rVIS,up = 0.062 and rNIR,up = 0.275. The parameterizations performed resulted in successful simulations of tropical rainforest albedo by IBIS, indicating its potential to simulate the canopy radiative transfer for narrow spectral bands and permitting close comparison with remote sensing products.Este estudo avalia a sensibilidade do albedo da superfície pelo Simulador Integrado da Biosfera (IBIS a um conjunto de parâmetros que representam algumas propriedades arquitetônicas e óticas do dossel da floresta tropical Amazônica. Os parâmetros testados neste estudo são a orientação e refletância das folhas do dossel superior e inferior nas bandas espectrais do visível (VIS e infravermelho próximo (NIR. Os resultados são avaliados contra observações feitas no sítio K34 pertencente ao Instituto Nacional de Pesquisas da Amazônia (INPA na Reserva Biológica de Cuieiras. A análise de sensibilidade indica uma forte resposta aos parâmetros de orienta
Yang, Ben; Qian, Yun; Berg, Larry K.; Ma, Po-Lun; Wharton, Sonia; Bulaevskaya, Vera; Yan, Huiping; Hou, Zhangshuan; Shaw, William J.
2017-01-01
We evaluate the sensitivity of simulated turbine-height wind speeds to 26 parameters within the Mellor-Yamada-Nakanishi-Niino (MYNN) planetary boundary-layer scheme and MM5 surface-layer scheme of the Weather Research and Forecasting model over an area of complex terrain. An efficient sampling algorithm and generalized linear model are used to explore the multiple-dimensional parameter space and quantify the parametric sensitivity of simulated turbine-height wind speeds. The results indicate that most of the variability in the ensemble simulations is due to parameters related to the dissipation of turbulent kinetic energy (TKE), Prandtl number, turbulent length scales, surface roughness, and the von Kármán constant. The parameter associated with the TKE dissipation rate is found to be most important, and a larger dissipation rate produces larger hub-height wind speeds. A larger Prandtl number results in smaller nighttime wind speeds. Increasing surface roughness reduces the frequencies of both extremely weak and strong airflows, implying a reduction in the variability of wind speed. All of the above parameters significantly affect the vertical profiles of wind speed and the magnitude of wind shear. The relative contributions of individual parameters are found to be dependent on both the terrain slope and atmospheric stability.
Yang, Ben; Qian, Yun; Berg, Larry K.; Ma, Po-Lun; Wharton, Sonia; Bulaevskaya, Vera; Yan, Huiping; Hou, Zhangshuan; Shaw, William J.
2016-07-01
We evaluate the sensitivity of simulated turbine-height wind speeds to 26 parameters within the Mellor-Yamada-Nakanishi-Niino (MYNN) planetary boundary-layer scheme and MM5 surface-layer scheme of the Weather Research and Forecasting model over an area of complex terrain. An efficient sampling algorithm and generalized linear model are used to explore the multiple-dimensional parameter space and quantify the parametric sensitivity of simulated turbine-height wind speeds. The results indicate that most of the variability in the ensemble simulations is due to parameters related to the dissipation of turbulent kinetic energy (TKE), Prandtl number, turbulent length scales, surface roughness, and the von Kármán constant. The parameter associated with the TKE dissipation rate is found to be most important, and a larger dissipation rate produces larger hub-height wind speeds. A larger Prandtl number results in smaller nighttime wind speeds. Increasing surface roughness reduces the frequencies of both extremely weak and strong airflows, implying a reduction in the variability of wind speed. All of the above parameters significantly affect the vertical profiles of wind speed and the magnitude of wind shear. The relative contributions of individual parameters are found to be dependent on both the terrain slope and atmospheric stability.
Eldyasti, Ahmed; Nakhla, George; Zhu, Jesse
2012-05-01
Biofilm models are valuable tools for process engineers to simulate biological wastewater treatment. In order to enhance the use of biofilm models implemented in contemporary simulation software, model calibration is both necessary and helpful. The aim of this work was to develop a calibration protocol of the particulate biofilm model with a help of the sensitivity analysis of the most important parameters in the biofilm model implemented in BioWin® and verify the predictability of the calibration protocol. A case study of a circulating fluidized bed bioreactor (CFBBR) system used for biological nutrient removal (BNR) with a fluidized bed respirometric study of the biofilm stoichiometry and kinetics was used to verify and validate the proposed calibration protocol. Applying the five stages of the biofilm calibration procedures enhanced the applicability of BioWin®, which was capable of predicting most of the performance parameters with an average percentage error (APE) of 0-20%.
Energy Technology Data Exchange (ETDEWEB)
Leng, Guoyong; Huang, Maoyi; Tang, Qiuhong; Sacks, William J.; Lei, Huimin; Leung, Lai-Yung R.
2013-09-16
Previous studies on irrigation impacts on land surface fluxes/states were mainly conducted as sensitivity experiments, with limited analysis of uncertainties from the input data and model irrigation schemes used. In this study, we calibrated and evaluated the performance of irrigation water use simulated by the Community Land Model version 4 (CLM4) against observations from agriculture census. We investigated the impacts of irrigation on land surface fluxes and states over the conterminous United States (CONUS) and explored possible directions of improvement. Specifically, we found large uncertainty in the irrigation area data from two widely used sources and CLM4 tended to produce unrealistically large temporal variations of irrigation demand for applications at the water resources region scale over CONUS. At seasonal to interannual time scales, the effects of irrigation on surface energy partitioning appeared to be large and persistent, and more pronounced in dry than wet years. Even with model calibration to yield overall good agreement with the irrigation amounts from the National Agricultural Statistics Service (NASS), differences between the two irrigation area datasets still dominate the differences in the interannual variability of land surface response to irrigation. Our results suggest that irrigation amount simulated by CLM4 can be improved by (1) calibrating model parameter values to account for regional differences in irrigation demand and (2) accurate representation of the spatial distribution and intensity of irrigated areas.
de Lima Neves Seefelder, Carolina; Mergili, Martin
2016-04-01
We use the software tools r.slope.stability and TRIGRS to produce factor of safety and slope failure susceptibility maps for the Quitite and Papagaio catchments, Rio de Janeiro, Brazil. The key objective of the work consists in exploring the sensitivity of the geotechnical (r.slope.stability) and geohydraulic (TRIGRS) parameterization on the model outcomes in order to define suitable parameterization strategies for future slope stability modelling. The two landslide-prone catchments Quitite and Papagaio together cover an area of 4.4 km², extending between 12 and 995 m a.s.l. The study area is dominated by granitic bedrock and soil depths of 1-3 m. Ranges of geotechnical and geohydraulic parameters are derived from literature values. A landslide inventory related to a rainfall event in 1996 (250 mm in 48 hours) is used for model evaluation. We attempt to identify those combinations of effective cohesion and effective internal friction angle yielding the best correspondence with the observed landslide release areas in terms of the area under the ROC Curve (AUCROC), and in terms of the fraction of the area affected by the release of landslides. Thereby we test multiple parameter combinations within defined ranges to derive the slope failure susceptibility (fraction of tested parameter combinations yielding a factor of safety smaller than 1). We use the tool r.slope.stability (comparing the infinite slope stability model and an ellipsoid-based sliding surface model) to test and to optimize the geotechnical parameters, and TRIGRS (a coupled hydraulic-infinite slope stability model) to explore the sensitivity of the model results to the geohydraulic parameters. The model performance in terms of AUCROC is insensitive to the variation of the geotechnical parameterization within much of the tested ranges. Assuming fully saturated soils, r.slope.stability produces rather conservative predictions, whereby the results yielded with the sliding surface model are more
Energy Technology Data Exchange (ETDEWEB)
van Drongelen, W.; Lee, H. C.; Koch, H.; Elsen, F.; Carroll, M. S.; Hereld, M.; Stevens, R. L.; Mathematics and Computer Science; Univ. of Chicago
2004-01-01
We examined the effects of both intrinsic neuronal membrane properties and network parameters on oscillatory activity in a model of neocortex. A scalable network model with six different cell types was built with the pGENESIS neural simulator. The neocortical network consisted of two types of pyramidal cells and four types of inhibitory interneurons. All cell types contained both fast sodium and delayed rectifier potassium channels for generation of action potentials. A subset of the pyramidal neurons contained an additional slow inactivating (persistent) sodium current (NaP). The neurons with the NaP current showed spontaneous bursting activity in the absence of external stimulation. The model also included a routine to calculate a simulated electroencephalogram (EEG) trace from the population activity. This revealed emergent network behavior which ranged from desynchronized activity to different types of seizure-like bursting patterns. At settings with weaker excitatory network effects, the propensity to generate seizure-like behavior increased. Strong excitatory network connectivity destroyed oscillatory behavior, whereas weak connectivity enhanced the relative importance of the spontaneously bursting cells. Our findings are in contradiction with the general opinion that strong excitatory synaptic and/or insufficient inhibition effects are associated with seizure initiation, but are in agreement with previously reported behavior in neocortex.
Directory of Open Access Journals (Sweden)
Quan Zhou
2015-01-01
Full Text Available Eddy current brake (ECB is an attractive contactless brake whereas it suffers from braking torque attenuation when the rotating speed increases. To stabilize the ECB’s torque generation property, this paper introduces the concept of anti-magneto-motive force to develop the ECB model on the fundamental of magnetic circles. In the developed model, the eddy current demagnetization and the influence of temperature which make the braking torque attenuation are clearly presented. Using the developed model of ECB, the external and internal characteristics of the ECB are simulated through programming by MATLAB. To find the sensibility of the influences on ECB’s torque generation stability, the stability indexes are defined and followed by a sensibility analysis on the internal parameters of an ECB. Finally, this paper indicates that (i the stability of ECB’s torque generating property could be enhanced by obtaining the optimal combination of “demagnetization speed point and the nominal maximum braking torque.” (ii The most remarkable influencing factor on the shifting the demagnetization speed point of ECB was the thickness of the air-gap. (iii The radius of pole shoe’s cross section area and the distance from the pole shoe center to the rotation center are both the most significant influences on the nominal maximum braking torque.
HSPF 模型水文水质参数敏感性分析%Sensitivity Analysis of Hydrological and Water Quality Parameters of HSPF Model
Institute of Scientific and Technical Information of China (English)
罗川; 李兆富; 席庆; 潘剑君
2014-01-01
参数敏感性分析是模型不确定性量化的重要环节，有助于对关键参数的识别，减少参数的不确定性影响，进而提高参数优化效率。以太湖地区典型小流域为研究区，采用扰动分析法对 HSPF 模型水文模块、泥沙模块以及氮磷输移等水文、水质模拟过程的参数进行了敏感性分析。研究结果显示：水文模块选取的17个参数中有7个敏感：UZSN、INFILT、AGWRC 对径流的敏感级别为芋类，LZSN、DEEPFR、INTFW、IRC 敏感级别为域类。泥沙透水地面模块选取的9个参数中，KSER、KGER、JGER 为芋类敏感参数， JSER 为郁类敏感参数；不透水地面模块选取的4个参数中，KEIM、JEIM、ACCSDP 对泥沙产量的敏感级别为芋类；河道模块选取的5个参数中，KSAND、EXPSND 为芋类敏感参数，TAUCS、TAUCD 为域类敏感参数。总氮模拟选取了23个参数分析敏感性，其中WSQOP、SQOLIM、MON-GRND-CONC 为郁类敏感参数，KATM20、MON-IFLW-CONC 为芋类敏感参数，TCNIT、PHYSET、MALGR敏感级别为域类。磷素输移模拟选取了12个参数，MON-GRND-CONC 敏感级别为芋类，MON-POTFW、MON-IFLW-CONC、MALGR、PHYSET 敏感级别为域类。研究结果对于开展基于 HSPF 模型的流域水文水质研究工作参数的选取具有一定的参考价值，尤其对于太湖周边地区众多低山丘陵小流域进行 HSPF 模型水文水质模拟时敏感性参数的选取具有借鉴意义。%Model sensitivity analysis measures the variability of output variables caused by perturbations in parameter values and input data. It is important for parameter selection, model calibration, and model improvement. As one of the integrated watershed model, HSPF(Hydro-logical Simulation Program-Fortran)model has a lot of parameters related to the physical characteristics of local watershed. In order to as-certain the sensitive parameters for hydrology and water quality simulation of HSPF model
DEFF Research Database (Denmark)
Ibsen, Lars Bo; Liingaard, Morten
A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. The lumped-parameter model development have been reported by (Wolf 1991b; Wolf 1991a; Wolf and Paronesso 1991; Wolf and Paronesso 19...
Pelletier, Maud; Bonvallot, Nathalie; Ramalho, Olivier; Blanchard, Olivier; Mercier, Fabien; Mandin, Corinne; Le Bot, Barbara; Glorennec, Philippe
2017-02-26
Recent research has demonstrated the importance of dermal exposure for some semivolatile organic compounds (SVOCs) present in the gas phase of indoor air. Though models for estimating dermal intake from gaseous SVOCs exist, their predictions can be subject to variations in input parameters, which can lead to large variation in exposure estimations. In this sensitivity analysis for a steady state model, we aimed to assess these variations and their determinants using probabilistic Monte Carlo sampling for 8 SVOCs from different chemical families: phthalates, bisphenols, polycyclic aromatic hydrocarbons (PAHs), organophosphorus (OPs), organochlorines (OCs), synthetic musks, polychlorinated biphenyls (PCBs) and polybromodiphenylethers (PBDEs). Indoor SVOC concentrations were found to be the most influential parameters. Both Henry's law constant (H) and octanol/water partition coefficient (Kow) uncertainty also had significant influence. While exposure media properties such as volume fraction of organic matter in the particle phase (fom-part), particle density (ρpart), concentration ([TSP]) and transport coefficient (ɣd) had a slight influence for some compounds, human parameters such as body weight (W), body surface area (A) and daily exposure (t) make a marginal or null contribution to the variance of dermal intake for a given age group. Inclusion of a parameter sensitivity analysis appears essential to reporting uncertainties in dermal exposure assessment.
Response model parameter linking
Barrett, Michelle Derbenwick
2015-01-01
With a few exceptions, the problem of linking item response model parameters from different item calibrations has been conceptualized as an instance of the problem of equating observed scores on different test forms. This thesis argues, however, that the use of item response models does not require
Deciphering Parameter Sensitivity in the BvgAS Signal Transduction
Mapder, Tarunendu; Talukder, Srijeeta; Chattopadhyay, Sudip; Banik, Suman K.
2016-01-01
To understand the switching of different phenotypic phases of Bordetella pertussis, we propose an optimized mathematical framework for signal transduction through BvgAS two-component system. The response of the network output to the sensory input has been demonstrated in steady state. An analysis in terms of local sensitivity amplification characterizes the nature of the molecular switch. The sensitivity analysis of the model parameters within the framework of various correlation coefficients helps to decipher the contribution of the modular structure in signal propagation. Once classified, the model parameters are tuned to generate the behavior of some novel strains using simulated annealing, a stochastic optimization technique. PMID:26812153
Deciphering Parameter Sensitivity in the BvgAS Signal Transduction.
Directory of Open Access Journals (Sweden)
Tarunendu Mapder
Full Text Available To understand the switching of different phenotypic phases of Bordetella pertussis, we propose an optimized mathematical framework for signal transduction through BvgAS two-component system. The response of the network output to the sensory input has been demonstrated in steady state. An analysis in terms of local sensitivity amplification characterizes the nature of the molecular switch. The sensitivity analysis of the model parameters within the framework of various correlation coefficients helps to decipher the contribution of the modular structure in signal propagation. Once classified, the model parameters are tuned to generate the behavior of some novel strains using simulated annealing, a stochastic optimization technique.
Deciphering Parameter Sensitivity in the BvgAS Signal Transduction.
Mapder, Tarunendu; Talukder, Srijeeta; Chattopadhyay, Sudip; Banik, Suman K
2016-01-01
To understand the switching of different phenotypic phases of Bordetella pertussis, we propose an optimized mathematical framework for signal transduction through BvgAS two-component system. The response of the network output to the sensory input has been demonstrated in steady state. An analysis in terms of local sensitivity amplification characterizes the nature of the molecular switch. The sensitivity analysis of the model parameters within the framework of various correlation coefficients helps to decipher the contribution of the modular structure in signal propagation. Once classified, the model parameters are tuned to generate the behavior of some novel strains using simulated annealing, a stochastic optimization technique.
Loth, Bettina; Graf, Hans-F.
1998-05-01
In order to find an optimal complexity for snow-cover models in climate studies, the influence of single snow processes on both the snow mass balance and the energy fluxes between snow surface and atmosphere has been investigated. Using a sophisticated model, experiments were performed under several different atmospheric and regional conditions (Arctic, midlatitudes, alpine regions). A high simulation quality can be achieved with a multilayered snow-cover model resolving the internal snow processes (cf. part 1,[Loth and Graf, this issue]). Otherwise, large errors can occur, mostly in zones which are of paramount importance for the entire climate dynamics. Owing to simplifications of such a model, the mean energy balance of the snow cover, the turbulent heat fluxes, and the long-wave radiation at the snow surface may alter by between 1 W/m2 and 8 W/m2. The snow-surface temperatures can be systematically changed by about 10 K.
Welivitiya, W. D. Dimuth P.; Willgoose, Garry R.; Hancock, Greg R.; Cohen, Sagy
2016-08-01
This paper generalises the physical dependence of the relationship between contributing area, local slope, and the surface soil grading using a pedogenesis model and allows an exploration of soilscape self-organisation. A parametric study was carried out using different parent materials, erosion, and weathering mechanisms. These simulations confirmed the generality of the area-slope-d50 relationship. The relationship is also true for other statistics of soil grading (e.g. d10,d90) and robust for different depths within the profile. For small area-slope regimes (i.e. hillslopes with small areas and/or slopes) only the smallest particles can be mobilised by erosion and the area-slope-d50 relationship appears to reflect the erosion model and its Shield's Stress threshold. For higher area-slope regimes, total mobilization of the entire soil grading occurs and self-organisation reflects the relative entrainment of different size fractions. Occasionally the interaction between the in-profile weathering and surface erosion draws the bedrock to the surface and forms a bedrock outcrop. The study also shows the influence on different depth-dependent in-profile weathering functions in the formation of the equilibrium soil profile and the grading characteristics of the soil within the profile. We outline the potential of this new model and its ability to numerically explore soil and landscape properties.
Sensitivity analysis of soil parameters based on interval
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Interval analysis is a new uncertainty analysis method for engineering struc-tures. In this paper, a new sensitivity analysis method is presented by introducing interval analysis which can expand applications of the interval analysis method. The interval anal-ysis process of sensitivity factor matrix of soil parameters is given. A method of parameter intervals and decision-making target intervals is given according to the interval analysis method. With FEM, secondary developments are done for Marc and the Duncan-Chang nonlinear elastic model. Mutual transfer between FORTRAN and Marc is implemented. With practial examples, rationality and feasibility are validated. Comparison is made with some published results.
Estimation of parameter sensitivities for stochastic reaction networks
Gupta, Ankit
2016-01-07
Quantification of the effects of parameter uncertainty is an important and challenging problem in Systems Biology. We consider this problem in the context of stochastic models of biochemical reaction networks where the dynamics is described as a continuous-time Markov chain whose states represent the molecular counts of various species. For such models, effects of parameter uncertainty are often quantified by estimating the infinitesimal sensitivities of some observables with respect to model parameters. The aim of this talk is to present a holistic approach towards this problem of estimating parameter sensitivities for stochastic reaction networks. Our approach is based on a generic formula which allows us to construct efficient estimators for parameter sensitivity using simulations of the underlying model. We will discuss how novel simulation techniques, such as tau-leaping approximations, multi-level methods etc. can be easily integrated with our approach and how one can deal with stiff reaction networks where reactions span multiple time-scales. We will demonstrate the efficiency and applicability of our approach using many examples from the biological literature.
Distributed Parameter Modelling Applications
DEFF Research Database (Denmark)
2011-01-01
Here the issue of distributed parameter models is addressed. Spatial variations as well as time are considered important. Several applications for both steady state and dynamic applications are given. These relate to the processing of oil shale, the granulation of industrial fertilizers and the d......Here the issue of distributed parameter models is addressed. Spatial variations as well as time are considered important. Several applications for both steady state and dynamic applications are given. These relate to the processing of oil shale, the granulation of industrial fertilizers...... sands processing. The fertilizer granulation model considers the dynamics of MAP-DAP (mono and diammonium phosphates) production within an industrial granulator, that involves complex crystallisation, chemical reaction and particle growth, captured through population balances. A final example considers...
SWMM模型径流参数全局灵敏度分析%Global Sensitivity Analysis of Runoff Parameters of SWMM Model
Institute of Scientific and Technical Information of China (English)
孙艳伟; 把多铎; 王文川; 姜体胜; 王富强
2012-01-01
Based on practicability analysis of SWMM model parameters in the calibration process, four parameters of subcatchment slope, subcatchment width, Manning coefficient and depression depth on pervious area and three infiltration parameters were selected. Two popular infiltration models of Horton and Green - Ampt were examined respectively. Global sensitivity analysis method of Morris was used. Flow metrics of total rainfall depth and peak discharge were simulated for single rainfall events with different rainfall types and return periods while runoff coefficient was examined for the long-term rainfall data. Main results were: sensitivity analysis results for Tl and T2 rainfall events indicated great differences and T2 rainfall event with small return period was not suitable for parameters calibration; for Horton model, peak discharge of large Tl rainfall can be used for calibrating subcatchment width and slope while total runoff of large T2 can be used for calibrating infiltration parameters; for Green - Ampt model, peak discharge of small Tl rainfall can be used to calibrate subcatchement width and that of large T2 rainfall can be used to calibrate minimum infiltration rate and water deficiency; for the runoff coefficient, sensitivity analysis results of the two methods are similar.%选取基于Horton和Green-Ampt入渗模型的入渗参数,以及区域坡度、区域宽度、透水性区域的曼宁系数和可积水深度共7个SWMM模型参数,采用Morris方法进行全局灵敏度分析.并分别采用不同降水类型、不同重现期的单个降水事件及长期降水序列,分析各模型参数对总产流量、洪峰流量及径流系数3个输出变量的全局灵敏度.结果表明:T1和T2型降水的参数灵敏度分析结果呈现较大差异,T2型较小降水事件不适宜用于参数校核;对Horton入渗模型而言,可利用T1型较大降水事件的洪峰流量对区域形状系数进行校核,利用T2型较大降水事件的总产流量对最
Sensitivity of footbridge vibrations to stochastic walking parameters
Pedersen, Lars; Frier, Christian
2010-06-01
Some footbridges are so slender that pedestrian traffic can cause excessive vibrations and serviceability problems. Design guidelines outline procedures for vibration serviceability checks, but it is noticeable that they rely on the assumption that the action is deterministic, although in fact it is stochastic as different pedestrians generate different dynamic forces. For serviceability checks of footbridge designs it would seem reasonable to consider modelling the stochastic nature of the main parameters describing the excitation, such as for instance the load amplitude and the step frequency of the pedestrian. A stochastic modelling approach is adopted for this paper and it facilitates quantifying the probability of exceeding various vibration levels, which is useful in a discussion of serviceability of a footbridge design. However, estimates of statistical distributions of footbridge vibration levels to walking loads might be influenced by the models assumed for the parameters of the load model (the walking parameters). The paper explores how sensitive estimates of the statistical distribution of vertical footbridge response are to various stochastic assumptions for the walking parameters. The basis for the study is a literature review identifying different suggestions as to how the stochastic nature of these parameters may be modelled, and a parameter study examines how the different models influence estimates of the statistical distribution of footbridge vibrations. By neglecting scatter in some of the walking parameters, the significance of modelling the various walking parameters stochastically rather than deterministically is also investigated providing insight into which modelling efforts need to be made for arriving at reliable estimates of statistical distributions of footbridge vibrations. The studies for the paper are based on numerical simulations of footbridge responses and on the use of Monte Carlo simulations for modelling the stochastic nature of
Robl, Jörg; Hergarten, Stefan
2015-04-01
along the flow path by more than one order of magnitude and beyond. We should be are aware that even state of the art models provide only a crude numerical description of the debris flow dynamics and forthcoming hazardous events may significantly deviate from predictions based on numerical models. This may be caused by limitations of the numerical models itself, by not fully appropriate flow resistance laws or by large uncertainties regarding involved masses, their release position and initial geometry and rheological parameters. Therefore, it is essential that beside of all these uncertainties we have a clear understanding of impact and sensitivity of these parameters on numerical model results that are commonly used for the delineation of hazard zone and the development of mitigation strategies against natural hazards.
Energy Technology Data Exchange (ETDEWEB)
Lopez Garcia, I.; Escalera Perez, R. [Universidad Autonoma Metropolitana - Azcapotzalco (Mexico)]. E-mail: irvinlopez@yahoo.com; r.escalera@ieee.org; Niewierowicz Swiecicka, T. [Instituto Politecnico Nacional, U.P. Adolfo Lopez Mateos (Mexico)]. E-mail: tniewi@ipn.mx; Campero Littlewood, E.[Universidad Autonoma Metropolitana - Azcapotzalco (Mexico)]. E-mail: ecl@correo.azc.uam.mx
2010-01-15
This work shows the results of a parametric sensitivity analysis applied to a state-space representation of high-order two-axis equivalent circuits (Ecs) of a turbo generator (150 MVA, 120 MW, 13.8 kV y 50 Hz). The main purpose of this study is to evaluate each parameter impact on the transient response of the analyzed two axis models -d axis Ecs with one to five damper branches and q axis Ecs from one to four damper branches-. The parametric sensitivity concept is formulated in a general context and the sensibility function is established from the generator response to a short circuit condition. Results ponder the importance played by each parameter in the model behavior. The algorithms were design within MATLAB environment. The study gives way to conclusion on electromagnetic aspects of solid rotor synchronous generators that have not been previously studied. The methodology presented here can be applied to any other physical system. [Spanish] En este trabajo se presentan los resultados del analisis de sensibilidad parametrica realizado a modelos de circuitos equivalentes de orden superior de un turbogenerador (150 MVA, 120 MW, 13.8 kV y 50 Hz). La representacion del generador sincrono se hace en el espacio de estados, utilizando la teoria de dos ejes (d y a). El objetivo del estudio de sensibilidad es evaluar el impacto que tiene cada uno de los parametros en la respuesta transitoria de los modelos analizados -circuitos equivalentes desde una hasta cinco ramas de amortiguamiento en el eje d y de una a cuatro ramas en el eje q-. En este trabajo el concepto de sensibilidad parametrica se formula en terminos generales, planteando la funcion de sensibilidad a partir de condiciones de cortocircuito en las terminales del generador. Los resultados se presentan senalando el nivel de importancia de cada parametro en el comportamiento del modelo. Los algoritmos utilizados fueron disenados en MATLAB. Asi, este estudio permite inferir aspectos electromagneticos de los
Energy Technology Data Exchange (ETDEWEB)
Ren, Huiying; Hou, Zhangshuan; Huang, Maoyi; Bao, Jie; Sun, Yu; Tesfa, Teklu; Ruby Leung, L.
2016-05-01
Effective uncertainty quantification approaches are needed to identify important parameters or factors that affect complex Earth system models that composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in Community Land Model (CLM) simulations of runoff and latent heat flux in a watershed are evaluated. Simple residual statistics, the Nash-Sutcliffe coefficient, and log mean square error are used as alternative measures of the deviations between the simulated and field observed values. The effects of the input parameters on the deviations are evaluated quantitatively using analysis of variance (ANOVA) based on the generalized linear model (GLM), and using generalized cross validation (GCV) based on the multivariate adaptive regression splines (MARS) model. These analyses 1) help identify how to adjust parameter values and therefore the calibration of the CLM parameters and to improve the model’s simulations, and 2) can approximately predict the model calibration performance. The convergence behavior of the sensitivity analysis with number of sampling points for both ANOVA and GCV is also examined relative to different combinations of input parameters and output response variables and their metrics.
Directory of Open Access Journals (Sweden)
B. Likozar
2012-09-01
Full Text Available Mathematical models for a batch process were developed to predict concentration distributions for an active ingredient (vancomycin adsorption on a representative hydrophobic-molecule adsorbent, using differently diluted crude fermentation broth with cells as the feedstock. The kinetic parameters were estimated using the maximization of the coefficient of determination by a heuristic algorithm. The parameters were estimated for each fermentation broth concentration using four concentration distributions at initial vancomycin concentrations of 4.96, 1.17, 2.78, and 5.54 g l−¹. In sequence, the models and their parameters were validated for fermentation broth concentrations of 0, 20, 50, and 100% (v/v by calculating the coefficient of determination for each concentration distribution at the corresponding initial concentration. The applicability of the validated models for process optimization was investigated by using the models as process simulators to optimize the two process efficiencies.
Efficient parameter sensitivity computation for spatially extended reaction networks
Lester, C.; Yates, C. A.; Baker, R. E.
2017-01-01
Reaction-diffusion models are widely used to study spatially extended chemical reaction systems. In order to understand how the dynamics of a reaction-diffusion model are affected by changes in its input parameters, efficient methods for computing parametric sensitivities are required. In this work, we focus on the stochastic models of spatially extended chemical reaction systems that involve partitioning the computational domain into voxels. Parametric sensitivities are often calculated using Monte Carlo techniques that are typically computationally expensive; however, variance reduction techniques can decrease the number of Monte Carlo simulations required. By exploiting the characteristic dynamics of spatially extended reaction networks, we are able to adapt existing finite difference schemes to robustly estimate parametric sensitivities in a spatially extended network. We show that algorithmic performance depends on the dynamics of the given network and the choice of summary statistics. We then describe a hybrid technique that dynamically chooses the most appropriate simulation method for the network of interest. Our method is tested for functionality and accuracy in a range of different scenarios.
Sensitivity of transient synchrotron radiation to tokamak plasma parameters
Energy Technology Data Exchange (ETDEWEB)
Fisch, N.J.; Kritz, A.H.
1988-12-01
Synchrotron radiation from a hot plasma can inform on certain plasma parameters. The dependence on plasma parameters is particularly sensitive for the transient radiation response to a brief, deliberate, perturbation of hot plasma electrons. We investigate how such a radiation response can be used to diagnose a variety of plasma parameters in a tokamak. 18 refs., 13 figs.
Sensitivity of lumbar spine loading to anatomical parameters.
Putzer, Michael; Ehrlich, Ingo; Rasmussen, John; Gebbeken, Norbert; Dendorfer, Sebastian
2016-04-11
Musculoskeletal simulations of lumbar spine loading rely on a geometrical representation of the anatomy. However, this data has an inherent inaccuracy. This study evaluates the influence of defined geometrical parameters on lumbar spine loading utilising five parametrised musculoskeletal lumbar spine models for four different postures. The influence of the dimensions of vertebral body, disc, posterior parts of the vertebrae as well as the curvature of the lumbar spine was studied. Additionally, simulations with combinations of selected parameters were conducted. Changes in L4/L5 resultant joint force were used as outcome variable. Variations of the vertebral body height, disc height, transverse process width and the curvature of the lumbar spine were the most influential. These parameters can be easily acquired from X-rays and should be used to morph a musculoskeletal lumbar spine model for subject-specific approaches with respect to bone geometry. Furthermore, the model was very sensitive to uncommon configurations and therefore, it is advised that stiffness properties of discs and ligaments should be individualised.
Robust estimation of hydrological model parameters
Directory of Open Access Journals (Sweden)
A. Bárdossy
2008-11-01
Full Text Available The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.
Neutrino Oscillation Parameter Sensitivity in Future Long-Baseline Experiments
Energy Technology Data Exchange (ETDEWEB)
Bass, Matthew [Colorado State Univ., Fort Collins, CO (United States)
2014-01-01
The study of neutrino interactions and propagation has produced evidence for physics beyond the standard model and promises to continue to shed light on rare phenomena. Since the discovery of neutrino oscillations in the late 1990s there have been rapid advances in establishing the three flavor paradigm of neutrino oscillations. The 2012 discovery of a large value for the last unmeasured missing angle has opened the way for future experiments to search for charge-parity symmetry violation in the lepton sector. This thesis presents an analysis of the future sensitivity to neutrino oscillations in the three flavor paradigm for the T2K, NO A, LBNE, and T2HK experiments. The theory of the three flavor paradigm is explained and the methods to use these theoretical predictions to design long baseline neutrino experiments are described. The sensitivity to the oscillation parameters for each experiment is presented with a particular focus on the search for CP violation and the measurement of the neutrino mass hierarchy. The variations of these sensitivities with statistical considerations and experimental design optimizations taken into account are explored. The effects of systematic uncertainties in the neutrino flux, interaction, and detection predictions are also considered by incorporating more advanced simulations inputs from the LBNE experiment.
Sensitivity analysis on parameters and processes affecting vapor intrusion risk.
Picone, Sara; Valstar, Johan; van Gaans, Pauline; Grotenhuis, Tim; Rijnaarts, Huub
2012-05-01
A one-dimensional numerical model was developed and used to identify the key processes controlling vapor intrusion risks by means of a sensitivity analysis. The model simulates the fate of a dissolved volatile organic compound present below the ventilated crawl space of a house. In contrast to the vast majority of previous studies, this model accounts for vertical variation of soil water saturation and includes aerobic biodegradation. The attenuation factor (ratio between concentration in the crawl space and source concentration) and the characteristic time to approach maximum concentrations were calculated and compared for a variety of scenarios. These concepts allow an understanding of controlling mechanisms and aid in the identification of critical parameters to be collected for field situations. The relative distance of the source to the nearest gas-filled pores of the unsaturated zone is the most critical parameter because diffusive contaminant transport is significantly slower in water-filled pores than in gas-filled pores. Therefore, attenuation factors decrease and characteristic times increase with increasing relative distance of the contaminant dissolved source to the nearest gas diffusion front. Aerobic biodegradation may decrease the attenuation factor by up to three orders of magnitude. Moreover, the occurrence of water table oscillations is of importance. Dynamic processes leading to a retreating water table increase the attenuation factor by two orders of magnitude because of the enhanced gas phase diffusion.
Sensitivity analysis on parameters and processes affecting vapor intrusion risk
Picone, Sara
2012-03-30
A one-dimensional numerical model was developed and used to identify the key processes controlling vapor intrusion risks by means of a sensitivity analysis. The model simulates the fate of a dissolved volatile organic compound present below the ventilated crawl space of a house. In contrast to the vast majority of previous studies, this model accounts for vertical variation of soil water saturation and includes aerobic biodegradation. The attenuation factor (ratio between concentration in the crawl space and source concentration) and the characteristic time to approach maximum concentrations were calculated and compared for a variety of scenarios. These concepts allow an understanding of controlling mechanisms and aid in the identification of critical parameters to be collected for field situations. The relative distance of the source to the nearest gas-filled pores of the unsaturated zone is the most critical parameter because diffusive contaminant transport is significantly slower in water-filled pores than in gas-filled pores. Therefore, attenuation factors decrease and characteristic times increase with increasing relative distance of the contaminant dissolved source to the nearest gas diffusion front. Aerobic biodegradation may decrease the attenuation factor by up to three orders of magnitude. Moreover, the occurrence of water table oscillations is of importance. Dynamic processes leading to a retreating water table increase the attenuation factor by two orders of magnitude because of the enhanced gas phase diffusion. © 2012 SETAC.
Institute of Scientific and Technical Information of China (English)
张静潇; 苏伟
2012-01-01
为有效识别作物模型关键参数,减少模型模拟的不适用性,根据中国农业大学上庄实验站小麦田间实测数据,应用EFAST方法对CERES-Wheat模型输入参数进行定量的全局敏感性分析,分析小麦模拟产量对作物参数、土壤参数和田间管理参数变化的敏感性。结果表明：CERES-Wheat模型的作物品种型参数中,标准籽粒质量参数对模拟结果影响最大,而生态型参数中影响最大的是营养生长末期叶片面积质量比率;土壤参数中的矿化系数对模拟结果影响最显著;管理参数中的施氮量、播种日期、施肥日期、播种深度对模拟结果影响较显著。基于EFAST方法的敏感性分析对作物模型修正具有指导意义,可为确定模型关键参数及模型进一步优化提供参考依据。%In order to effectively identify the key parameters of crop models and reduce the inapplicability of model simulation,the Extend Fourier Amplitude Sensitivity Test(EFAST) was used to analyze the global sensitivity of CERES-Wheat model parameters in Shangzhuang experimental station of China Agricultural University in Beijing.The sensitivity of crop,soil and field management parameters was analyzed.The results of the sensitivity analysis showed that standard kernel size under optimum conditions had the greatest impact on the simulation wheat yields among crop cultivar parameters while lamina area to weight ratio of phase 2 was the most significant one in crop ecotype parameters.For soil parameters,nitrogen mineralized factor was the most critical input.The amount of nitrogenous fertilizer,planting date,fertilization date and planting depth among all of field management parameters had the most significant influence on the simulation results.The research showed that the global sensitivity analysis based on EFAST had guiding significance for crop model correction and provided reference for parameter selection and crop model optimization.
Datta, S.; Jones, W. L.; Ebrahimi, H.; Chen, R.; Payne, V.; Kroodsma, R.
2014-12-01
The first step in radiometric inter-calibration is to ascertain the self-consistency and reasonableness of the observed brightness temperature (Tb) for each individual sensor involved. One of the widely used approaches is to compare the observed Tb with a simulated Tb using a forward radiative transfer model (RTM) and input geophysical parameters at the geographic location and time of the observation. In this study we intend to test the sensitivity of the RTM to uncertainties in the input geophysical parameters as well as to the underlying physical assumptions of gaseous absorption and surface emission in the RTM. SAPHIR, a cross track scanner onboard Indo-French Megha-Tropique Satellite, gives us a unique opportunity of studying 6 dual band 183 GHz channels at an inclined orbit over the Tropics for the first time. We will also perform the same sensitivity analysis using the Advance Technology Microwave Sounder (ATMS) 23 GHz and five 183 GHz channels. Preliminary analysis comparing GDAS and an independent retrieved profile show some sensitivity of the RTM to the input data. An extended analysis of this work using different input geophysical parameters will be presented. Two different absorption models, the Rosenkranz and the MonoRTM will be tested to analyze the sensitivity of the RTM to spectroscopic assumptions in each model. Also for the 23.8 GHz channel, the sensitivity of the RTM to the surface emissivity model will be checked. Finally the impact of these sensitivities on radiometric inter-calibration of radiometers at sounding frequencies will be assessed.
Delineating parameter unidentifiabilities in complex models
Raman, Dhruva V.; Anderson, James; Papachristodoulou, Antonis
2017-03-01
Scientists use mathematical modeling as a tool for understanding and predicting the properties of complex physical systems. In highly parametrized models there often exist relationships between parameters over which model predictions are identical, or nearly identical. These are known as structural or practical unidentifiabilities, respectively. They are hard to diagnose and make reliable parameter estimation from data impossible. They furthermore imply the existence of an underlying model simplification. We describe a scalable method for detecting unidentifiabilities, as well as the functional relations defining them, for generic models. This allows for model simplification, and appreciation of which parameters (or functions thereof) cannot be estimated from data. Our algorithm can identify features such as redundant mechanisms and fast time-scale subsystems, as well as the regimes in parameter space over which such approximations are valid. We base our algorithm on a quantification of regional parametric sensitivity that we call `multiscale sloppiness'. Traditionally, the link between parametric sensitivity and the conditioning of the parameter estimation problem is made locally, through the Fisher information matrix. This is valid in the regime of infinitesimal measurement uncertainty. We demonstrate the duality between multiscale sloppiness and the geometry of confidence regions surrounding parameter estimates made where measurement uncertainty is non-negligible. Further theoretical relationships are provided linking multiscale sloppiness to the likelihood-ratio test. From this, we show that a local sensitivity analysis (as typically done) is insufficient for determining the reliability of parameter estimation, even with simple (non)linear systems. Our algorithm can provide a tractable alternative. We finally apply our methods to a large-scale, benchmark systems biology model of necrosis factor (NF)-κ B , uncovering unidentifiabilities.
Photovoltaic module parameters acquisition model
Cibira, Gabriel; Koščová, Marcela
2014-09-01
This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I-V and P-V characteristics for PV module based on equivalent electrical circuit. Then, limited I-V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model.
Delineating Parameter Unidentifiabilities in Complex Models
Raman, Dhruva V; Papachristodoulou, Antonis
2016-01-01
Scientists use mathematical modelling to understand and predict the properties of complex physical systems. In highly parameterised models there often exist relationships between parameters over which model predictions are identical, or nearly so. These are known as structural or practical unidentifiabilities, respectively. They are hard to diagnose and make reliable parameter estimation from data impossible. They furthermore imply the existence of an underlying model simplification. We describe a scalable method for detecting unidentifiabilities, and the functional relations defining them, for generic models. This allows for model simplification, and appreciation of which parameters (or functions thereof) cannot be estimated from data. Our algorithm can identify features such as redundant mechanisms and fast timescale subsystems, as well as the regimes in which such approximations are valid. We base our algorithm on a novel quantification of regional parametric sensitivity: multiscale sloppiness. Traditional...
Mode choice model parameters estimation
Strnad, Irena
2010-01-01
The present work focuses on parameter estimation of two mode choice models: multinomial logit and EVA 2 model, where four different modes and five different trip purposes are taken into account. Mode choice model discusses the behavioral aspect of mode choice making and enables its application to a traffic model. Mode choice model includes mode choice affecting trip factors by using each mode and their relative importance to choice made. When trip factor values are known, it...
Extreme parameter sensitivity of transient persistence in spatially coupled ecological systems
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
This paper investigates persistence of transient dynamics depending on parameters in spatially coupled ecological systems. We emphasis that the persistence time can be obtained by populations of species or Lyapunov exponents of transient dynamics. It is found that extreme sensitive dependence of persistence on parameters occurs commonly in ecological models. A non-zero uncertainty exponent is used to characterize the high sensitivity in a reasonable parameter region. The result of a small uncertainty expone...
Sensitivity analysis of influencing parameters in cavern stability
Institute of Scientific and Technical Information of China (English)
Abolfazl Abdollahipour; Reza Rahmannejad
2012-01-01
In order to analyze the stability of the underground rock structures,knowing the sensitivity of geomechanical parameters is important.To investigate the priority of these geomechanical properties in the stability of cavern,a sensitivity analysis has been performed on a single cavern in various rock mass qualities according to RMR using Phase 2.The stability of cavern has been studied by investigating the side wall deformation.Results showed that most sensitive properties are coefficient of lateral stress and modulus of deformation.Also parameters of Hoek-Brown criterion and σc have no sensitivity when cavern is in a perfect elastic state.But in an elasto-plastic state,parameters of Hoek-Brown criterion and σc affect the deformability; such effect becomes more remarkable with increasing plastic area.Other parameters have different sensitivities concerning rock mass quality (RMR).Results have been used to propose the best set of parameters for study on prediction of sidewall displacement.
Second-order sensitivity of eigenpairs in multiple parameter structures
Institute of Scientific and Technical Information of China (English)
Su-huan CHEN; Rui GUO; Guang-wei MENG
2009-01-01
This paper presents methods for computing a second-order sensitivity matrix and the Hessian matrix of eigenvalues and eigenvectors of multiple parameter structures. Second-order perturbations of eigenvalues and eigenvectors are transformed into multiple parameter forms, and the second-order perturbation sensitivity matrices of eigenvalues and eigenvectors are developed. With these formulations, the efficient methods based on the second-order Taylor expansion and second-order perturbation are obtained to estimate changes of eigenvalues and eigenvectors when the design parameters are changed. The presented method avoids direct differential operation, and thus reduces difficulty for computing the second-order sensitivity matrices of eigenpairs. A numerical example is given to demonstrate application and accuracy of the proposed method.
Importance and sensitivity of parameters affecting the Zion Seismic Risk
Energy Technology Data Exchange (ETDEWEB)
George, L.L.; O' Connell, W.J.
1985-06-01
This report presents the results of a study on the importance and sensitivity of structures, systems, equipment, components and design parameters used in the Zion Seismic Risk Calculations. This study is part of the Seismic Safety Margins Research Program (SSMRP) supported by the NRC Office of Nuclear Regulatory Research. The objective of this study is to provide the NRC with results on the importance and sensitivity of parameters used to evaluate seismic risk. These results can assist the NRC in making decisions dealing with the allocation of research resources on seismic issues. This study uses marginal analysis in addition to importance and sensitivity analysis to identify subject areas (input parameter areas) for improvements that reduce risk, estimate how much the improvement dfforts reduce risk, and rank the subject areas for improvements. Importance analysis identifies the systems, components, and parameters that are important to risk. Sensitivity analysis estimates the change in risk per unit improvement. Marginal analysis indicates the reduction in risk or uncertainty for improvement effort made in each subject area. The results described in this study were generated using the SEISIM (Systematic Evaluation of Important Safety Improvement Measures) and CHAIN computer codes. Part 1 of the SEISIM computer code generated the failure probabilities and risk values. Part 2 of SEISIM, along with the CHAIN computer code, generated the importance and sensitivity measures.
Sensitivity Analysis of Hardwired Parameters in GALE Codes
Energy Technology Data Exchange (ETDEWEB)
Geelhood, Kenneth J.; Mitchell, Mark R.; Droppo, James G.
2008-12-01
The U.S. Nuclear Regulatory Commission asked Pacific Northwest National Laboratory to provide a data-gathering plan for updating the hardwired data tables and parameters of the Gaseous and Liquid Effluents (GALE) codes to reflect current nuclear reactor performance. This would enable the GALE codes to make more accurate predictions about the normal radioactive release source term applicable to currently operating reactors and to the cohort of reactors planned for construction in the next few years. A sensitivity analysis was conducted to define the importance of hardwired parameters in terms of each parameter’s effect on the emission rate of the nuclides that are most important in computing potential exposures. The results of this study were used to compile a list of parameters that should be updated based on the sensitivity of these parameters to outputs of interest.
Probabilistic and Nonprobabilistic Sensitivity Analyses of Uncertain Parameters
Directory of Open Access Journals (Sweden)
Sheng-En Fang
2014-01-01
Full Text Available Parameter sensitivity analyses have been widely applied to industrial problems for evaluating parameter significance, effects on responses, uncertainty influence, and so forth. In the interest of simple implementation and computational efficiency, this study has developed two sensitivity analysis methods corresponding to the situations with or without sufficient probability information. The probabilistic method is established with the aid of the stochastic response surface and the mathematical derivation proves that the coefficients of first-order items embody the parameter main effects on the response. Simultaneously, a nonprobabilistic interval analysis based method is brought forward for the circumstance when the parameter probability distributions are unknown. The two methods have been verified against a numerical beam example with their accuracy compared to that of a traditional variance-based method. The analysis results have demonstrated the reliability and accuracy of the developed methods. And their suitability for different situations has also been discussed.
Investigation of parameter sensitivity of short channel mosfets
Selberherr, S.; Schütz, A.; Pötzl, H.
1982-02-01
A strategy to examine the sensitivity of electrical device parameters on geometrical and technological tolerances is described. An approach is offered to determine the limit of device miniaturzation for a given fabrication process and a desired operating condition. As a didactic example of practical relevance the minimum channel length for a modern silicon gate, double implant process due to threshold uncertainty is estimated. A method to calculate global sensitivity numbers for the reproducability of miniaturized devices is suggested. As an experimental determination of sensitivities is extremely difficult and expensive, numerical simulations are ideally suited for this purpose.
Directory of Open Access Journals (Sweden)
narges javidan
2017-02-01
. Hydrological modeling deals with calculation of watershed hydrograph using hydro-meteorological information and terrain data, and processes of transforming rainfall into a flood hydrograph and the translation of hydrographs throughout a watershed. Flow routing subjects hydrography transformation and translation throughout a river basin. The Wet Spa model used in this study is a simple grid-based distributed runoff and water balance simulation model that runs on an hourly time step. It predicts hourly overland flow occurring at any point in a watershed, hydrography at the outlet, and provides spatially distributed hydrologic characteristics in the basin, in which all hydrologic processes are simulated within a GIS framework (Bahremand, 2007. The Wet Spa model was originally developed by Wang et al. (1997 and adapted for flood prediction by De Smedt et al. (2000 and Liu et al. (2003. Materials and Methods: The outlet is accomplished using the ﬁrst passage time response function based on the mean and variance of the ﬂow time distribution, which is derived from the advection–dispersion transport equation. The ﬂow velocity is location dependent and calculated in each cell by the Manning equation based on the local slope, roughness coefﬁcient and hydraulic radius. The hydraulic radius is determined according to the geophysical properties of the catchment and the ﬂood frequency. The total direct runoff at the basin outlet is obtained by superimposing all contributions from every grid cell. The routing of overland flow and channel flow is implemented by the method of the diffusive wave approximation. This method has been used in some recent GIS-based flood models (Fortin et al., 2001; Olivera and Maidment, 1999. Liu et al 2003 has presented the flow routing method of the WetSpa model in detail. A two-parameter response function, based on the average flow time and the standard deviation of the flow time, is proposed in this study. The flow time and its variance are
Kim, Y.; Hwang, T.; Vose, J. M.; Martin, K. L.; Band, L. E.
2016-12-01
Hydrologic models reflect our understanding of factors that regulate stream discharge and range from simple empirical models to highly complex process-based models. Sensitivity analysis is a commonly used tool to detect the parameters that significantly impact model results. In this study, we hypothesized that (1) analysis of patterns in parameter sensitivity could be used to better understand variation in controls on hydrologic behavior within and across a mountain-piedmont-coastal gradient, and (2) shifts in parameter significance among wet, dry, and average precipitation years could reveal differing sensitivities to variation in precipitation. To test our hypotheses, we applied the Soil and Water Assessment Tool (SWAT) to several small headwater sub-watersheds in the Yadkin-Pee Dee basin, located in North and South Carolina, USA. In global sensitivity analyses, we found that main channel routing and curve number for surface runoff parameters were the most significant parameters across all of the study watersheds. Parameters influence on hydrologic behavior varied across the physiographic gradient as well. Soil parameters were more sensitive in the Mountains, while the surface runoff lag coefficient and the plant uptake compensation factor were significant in the Piedmont and Coastal Plain watersheds. The groundwater revap coefficient was significant only in the Piedmont watersheds. We also found noticeable shifts in the behavioral ranges of parameters along the geographical gradient, including surface runoff, main channel routing and soil related parameters. There were also inter-annual variations across the dry, wet, and normal water yield years at the study watersheds. Mountain watersheds exhibited noticeable temporal variation in the behavior of parameters driving evapotranspiration, main channel routing, and soil properties. Two Piedmont watersheds had different temporal variations in parameter behavior, which might be due to the difference in landuse
A Modified Sensitive Driving Cellular Automaton Model
Institute of Scientific and Technical Information of China (English)
GE Hong-Xia; DAI Shi-Qiang; DONG Li-Yun; LEI Li
2005-01-01
A modified cellular automaton model for traffic flow on highway is proposed with a novel concept about the variable security gap. The concept is first introduced into the original Nagel-Schreckenberg model, which is called the non-sensitive driving cellular automaton model. And then it is incorporated with a sensitive driving NaSch model,in which the randomization brake is arranged before the deterministic deceleration. A parameter related to the variable security gap is determined through simulation. Comparison of the simulation results indicates that the variable security gap has different influence on the two models. The fundamental diagram obtained by simulation with the modified sensitive driving NaSch model shows that the maximumflow are in good agreement with the observed data, indicating that the presented model is more reasonable and realistic.
Determining extreme parameter correlation in ground water models
DEFF Research Database (Denmark)
Hill, Mary Cole; Østerby, Ole
2003-01-01
In ground water flow system models with hydraulic-head observations but without significant imposed or observed flows, extreme parameter correlation generally exists. As a result, hydraulic conductivity and recharge parameters cannot be uniquely estimated. In complicated problems, such correlation...... correlation coefficients, but it required sensitivities that were one to two significant digits less accurate than those that required using parameter correlation coefficients; and (3) both the SVD and parameter correlation coefficients identified extremely correlated parameters better when the parameters...
Energy Technology Data Exchange (ETDEWEB)
Prindle, R.W.; Hopkins, P.L.
1990-10-01
The Hydrologic Code Intercomparison Project (HYDROCOIN) was formed to evaluate hydrogeologic models and computer codes and their use in performance assessment for high-level radioactive-waste repositories. This report describes the results of a study for HYDROCOIN of model sensitivity for isothermal, unsaturated flow through layered, fractured tuffs. We investigated both the types of flow behavior that dominate the performance measures and the conditions and model parameters that control flow behavior. We also examined the effect of different conceptual models and modeling approaches on our understanding of system behavior. The analyses included single- and multiple-parameter variations about base cases in one-dimensional steady and transient flow and in two-dimensional steady flow. The flow behavior is complex even for the highly simplified and constrained system modeled here. The response of the performance measures is both nonlinear and nonmonotonic. System behavior is dominated by abrupt transitions from matrix to fracture flow and by lateral diversion of flow. The observed behaviors are strongly influenced by the imposed boundary conditions and model constraints. Applied flux plays a critical role in determining the flow type but interacts strongly with the composite-conductivity curves of individual hydrologic units and with the stratigraphy. One-dimensional modeling yields conservative estimates of distributions of groundwater travel time only under very limited conditions. This study demonstrates that it is wrong to equate the shortest possible water-travel path with the fastest path from the repository to the water table. 20 refs., 234 figs., 10 tabs.
Sensitivity analysis on parameters and processes affecting vapor intrusion risk
Picone, S.; Valstar, J.R.; Gaans, van P.; Grotenhuis, J.T.C.; Rijnaarts, H.H.M.
2012-01-01
A one-dimensional numerical model was developed and used to identify the key processes controlling vapor intrusion risks by means of a sensitivity analysis. The model simulates the fate of a dissolved volatile organic compound present below the ventilated crawl space of a house. In contrast to the v
DEFF Research Database (Denmark)
Sun, Shu; Rappaport, Theodore S.; Thomas, Timothy
2016-01-01
This paper compares three candidate large-scale propagation path loss models for use over the entire microwave and millimeter-wave (mmWave) radio spectrum: the alpha–beta–gamma (ABG) model, the close-in (CI) free-space reference distance model, and the CI model with a frequency-weighted path loss...
Roe, Byron
2013-01-01
The effect of correlations between model parameters and nuisance parameters is discussed, in the context of fitting model parameters to data. Modifications to the usual $\\chi^2$ method are required. Fake data studies, as used at present, will not be optimum. Problems will occur for applications of the Maltoni-Schwetz \\cite{ms} theorem. Neutrino oscillations are used as examples, but the problems discussed here are general ones, which are often not addressed.
Institute of Scientific and Technical Information of China (English)
狄长江; 戴晓江; 王孝东; 刘佶林; 宇文巍
2015-01-01
对于露天金属矿山的开采规划模型,会有不同的变量参数且每个参数对模型的影响程度不同. 以某露天铜矿为工程背景,利用3 Dmine软件在不同的变量参数组合作用下得出其开采规划模型和相应的优化方案,将正交设计与方差分析有机结合,通过对优化方案当年净现值的分析来求解模型中每一个参数的灵敏度. 结果显示,精矿价格对开采规划模型的影响最大.%There are different variable parameters in production planning model of open-pit metallic mines and each parameter has influence on the model in different magnitude. The paper takes one open-pit copper mine as the engineering background,by using 3Dmine software under different combination of variable parameters concludes their production planning model and the corresponding optimization solution. Through the organic combination of orthogonal design and variance analysis and the analysis of the contemporary net present value of the optimization scheme,the sensitivity of each parameter in the model is calculated. Results show that the concentrates price has the largest impact on the production planning model.
narges javidan; Abdolreza Bahremand
2017-01-01
Introduction: Flood routing is a procedure to calculate flood stage and water depth along a river or to estimate flood hydrograph at river downstream or at reservoir outlets using the upstream hydrography . In river basins, excess rainfall is routed to the basin outlet using flow routing techniques to generate flow hydrograph. A GIS-based distributed hydrological model, Wet Spa, has been under development suitable for flood prediction and watershed management on a catchment scale. The mo...
Sensitivity Assessment of Ozone Models
Energy Technology Data Exchange (ETDEWEB)
Shorter, Jeffrey A.; Rabitz, Herschel A.; Armstrong, Russell A.
2000-01-24
The activities under this contract effort were aimed at developing sensitivity analysis techniques and fully equivalent operational models (FEOMs) for applications in the DOE Atmospheric Chemistry Program (ACP). MRC developed a new model representation algorithm that uses a hierarchical, correlated function expansion containing a finite number of terms. A full expansion of this type is an exact representation of the original model and each of the expansion functions is explicitly calculated using the original model. After calculating the expansion functions, they are assembled into a fully equivalent operational model (FEOM) that can directly replace the original mode.
Sensitivity of lumbar spine loading to anatomical parameters
DEFF Research Database (Denmark)
Putzer, Michael; Ehrlich, Ingo; Rasmussen, John
2016-01-01
models for four different postures. The in uence of the dimensions of vertebral body, disc, posterior parts of the vertebrae as well as the curvature of the lumbar spine were studied. Additionally, simulations with combinations of selected parameters were conducted. Changes in L4/L5 resultant joint force......Musculoskeletal simulations of lumbar spine loading rely on a geometrical representation of the anatomy. However, this data has an inherent inaccuracy. This study evaluates the in uence of dened geometrical parameters on lumbar spine loading utilizing ve parametrized musculoskeletal lumbar spine...... were used as outcome variable. Variations of the vertebral body height, disc height, transverse process width and the curvature of the lumbar spine were the most in uential. The results indicated that measuring these parameters from X-rays would be most important to morph an existing musculoskeletal...
Karmali, M. S.; Phatak, A. V.
1982-01-01
Results of a study to investigate, by means of a computer simulation, the performance sensitivity of helicopter IMC DSAL operations as a function of navigation system parameters are presented. A mathematical model representing generically a navigation system is formulated. The scenario simulated consists of a straight in helicopter approach to landing along a 6 deg glideslope. The deceleration magnitude chosen is 03g. The navigation model parameters are varied and the statistics of the total system errors (TSE) computed. These statistics are used to determine the critical navigation system parameters that affect the performance of the closed-loop navigation, guidance and control system of a UH-1H helicopter.
A specialized ODE integrator for the efficient computation of parameter sensitivities
Directory of Open Access Journals (Sweden)
Gonnet Pedro
2012-05-01
Full Text Available Abstract Background Dynamic mathematical models in the form of systems of ordinary differential equations (ODEs play an important role in systems biology. For any sufficiently complex model, the speed and accuracy of solving the ODEs by numerical integration is critical. This applies especially to systems identification problems where the parameter sensitivities must be integrated alongside the system variables. Although several very good general purpose ODE solvers exist, few of them compute the parameter sensitivities automatically. Results We present a novel integration algorithm that is based on second derivatives and contains other unique features such as improved error estimates. These features allow the integrator to take larger time steps than other methods. In practical applications, i.e. systems biology models of different sizes and behaviors, the method competes well with established integrators in solving the system equations, and it outperforms them significantly when local parameter sensitivities are evaluated. For ease-of-use, the solver is embedded in a framework that automatically generates the integrator input from an SBML description of the system of interest. Conclusions For future applications, comparatively ‘cheap’ parameter sensitivities will enable advances in solving large, otherwise computationally expensive parameter estimation and optimization problems. More generally, we argue that substantially better computational performance can be achieved by exploiting characteristics specific to the problem domain; elements of our methods such as the error estimation could find broader use in other, more general numerical algorithms.
Sensitivity analysis on parameter changes in underground mine ventilation systems
Institute of Scientific and Technical Information of China (English)
LI Gary; KOCSIS Charles; HARDCASTLE Steve
2011-01-01
A more efficient mine ventilation system,the ventilation-on-demand (VOD) system,has been proposed and tested in Canadian mines recently.In order to supply the required air volumes to the production areas of a mine,operators need to know the cause and effect of any changes requested from the VOD system.The sensitivity analysis is developed through generating a cause and effect matrix of sensitivity factors on given parameter changes in a ventilation system.This new utility,which was incorporated in the 3D-CANVENT mine ventilation simulator,is able to predict the airflow distributions in a ventilation network when underground conditions and ventilation controls are changed.For a primary ventilation system,the software can determine the optimal operating speed of the main fans to satisfy the airflow requirements in underground workings without necessarily using booster fans and regulators locally.An optimized fan operating speed time-table would assure variable demand-based fresh air delivery to the production areas effectively,while generating significant savings in energy consumption and operating cost.
Sensitivity analysis of periodic matrix population models.
Caswell, Hal; Shyu, Esther
2012-12-01
Periodic matrix models are frequently used to describe cyclic temporal variation (seasonal or interannual) and to account for the operation of multiple processes (e.g., demography and dispersal) within a single projection interval. In either case, the models take the form of periodic matrix products. The perturbation analysis of periodic models must trace the effects of parameter changes, at each phase of the cycle, on output variables that are calculated over the entire cycle. Here, we apply matrix calculus to obtain the sensitivity and elasticity of scalar-, vector-, or matrix-valued output variables. We apply the method to linear models for periodic environments (including seasonal harvest models), to vec-permutation models in which individuals are classified by multiple criteria, and to nonlinear models including both immediate and delayed density dependence. The results can be used to evaluate management strategies and to study selection gradients in periodic environments.
Sensitivity analysis of permeability parameters for flows on Barcelona networks
Rarità, Luigi; D'Apice, Ciro; Piccoli, Benedetto; Helbing, Dirk
We consider the problem of optimizing vehicular traffic flows on an urban network of Barcelona type, i.e. square network with streets of not equal length. In particular, we describe the effects of variation of permeability parameters, that indicate the amount of flow allowed to enter a junction from incoming roads. On each road, a model suggested by Helbing et al. (2007) [11] is considered: free and congested regimes are distinguished, characterized by an arrival flow and a departure flow, the latter depending on a permeability parameter. Moreover we provide a rigorous derivation of the model from fluid dynamic ones, using recent results of Bretti et al. (2006) [3]. For solving the dynamics at nodes of the network, a Riemann solver maximizing the through flux is used, see Coclite et al. (2005) [4] and Helbing et al. (2007) [11]. The network dynamics gives rise to complicate equations, where the evolution of fluxes at a single node may involve time-delayed terms from all other nodes. Thus we propose an alternative hybrid approach, introducing additional logic variables. Finally we compute the effects of variations on permeability parameters over the hybrid dynamics and test the obtained results via simulations.
Sensitivity Analysis of the Gap Heat Transfer Model in BISON.
Energy Technology Data Exchange (ETDEWEB)
Swiler, Laura Painton; Schmidt, Rodney C.; Williamson, Richard (INL); Perez, Danielle (INL)
2014-10-01
This report summarizes the result of a NEAMS project focused on sensitivity analysis of the heat transfer model in the gap between the fuel rod and the cladding used in the BISON fuel performance code of Idaho National Laboratory. Using the gap heat transfer models in BISON, the sensitivity of the modeling parameters and the associated responses is investigated. The study results in a quantitative assessment of the role of various parameters in the analysis of gap heat transfer in nuclear fuel.
Parametric sensitivity analysis for techno-economic parameters in Indian power sector
Energy Technology Data Exchange (ETDEWEB)
Mallah, Subhash; Bansal, N.K. [Shri Mata Vaishno Devi University, Katra, Jammu and Kashmir 182 320 (India)
2011-03-15
Sensitivity analysis is a technique that evaluates the model response to changes in input assumptions. Due to uncertain prices of primary fuels in the world market, Government regulations for sustainability and various other technical parameters there is a need to analyze the techno-economic parameters which play an important role in policy formulations. This paper examines the variations in technical as well as economic parameters that can mostly affect the energy policy of India. MARKAL energy simulation model has been used to analyze the uncertainty in all techno-economic parameters. Various ranges of input parameters are adopted from previous studies. The results show that at lower discount rate coal is the least preferred technology and correspondingly carbon emission reduction. With increased gas and nuclear fuel prices they disappear from the allocations of energy mix. (author)
Institute of Scientific and Technical Information of China (English)
刘国明; 程和平; 邵增
2012-01-01
在聚变-裂变混合能源堆球模型基础上,使用蒙特卡罗方法中子学程序对中子源、铀水体积比、产氚区等相关参数进行了中子学的敏感性计算.分析了各参数对混合能源堆能量放大倍数M和氚增殖比TBR的影响,并总结其基本规律,为开展进一步的混合能源堆概念设计提供了重要参考.%The sensitivity analysis on neutronics parameters related to neutron source, uranium-water ratio and tritium breeding layers for spherical blanket model of fusion-fission hybrid reactor were presented. By using a Monte-Carlo method based neutron transport code, the effects of the parameters on energy multiplication factor M and tritium breeding ratio TBR were analyzed, and the general various laws of M and TBR were summarized, which were significant for the further conceptual design of fusion-fission hybrid energy reactor.
Economic modeling and sensitivity analysis.
Hay, J W
1998-09-01
The field of pharmacoeconomics (PE) faces serious concerns of research credibility and bias. The failure of researchers to reproduce similar results in similar settings, the inappropriate use of clinical data in economic models, the lack of transparency, and the inability of readers to make meaningful comparisons across published studies have greatly contributed to skepticism about the validity, reliability, and relevance of these studies to healthcare decision-makers. Using a case study in the field of lipid PE, two suggestions are presented for generally applicable reporting standards that will improve the credibility of PE. Health economists and researchers should be expected to provide either the software used to create their PE model or a multivariate sensitivity analysis of their PE model. Software distribution would allow other users to validate the assumptions and calculations of a particular model and apply it to their own circumstances. Multivariate sensitivity analysis can also be used to present results in a consistent and meaningful way that will facilitate comparisons across the PE literature. Using these methods, broader acceptance and application of PE results by policy-makers would become possible. To reduce the uncertainty about what is being accomplished with PE studies, it is recommended that these guidelines become requirements of both scientific journals and healthcare plan decision-makers. The standardization of economic modeling in this manner will increase the acceptability of pharmacoeconomics as a practical, real-world science.
Evolution of Geometric Sensitivity Derivatives from Computer Aided Design Models
Jones, William T.; Lazzara, David; Haimes, Robert
2010-01-01
The generation of design parameter sensitivity derivatives is required for gradient-based optimization. Such sensitivity derivatives are elusive at best when working with geometry defined within the solid modeling context of Computer-Aided Design (CAD) systems. Solid modeling CAD systems are often proprietary and always complex, thereby necessitating ad hoc procedures to infer parameter sensitivity. A new perspective is presented that makes direct use of the hierarchical associativity of CAD features to trace their evolution and thereby track design parameter sensitivity. In contrast to ad hoc methods, this method provides a more concise procedure following the model design intent and determining the sensitivity of CAD geometry directly to its respective defining parameters.
PARAMETER ESTIMATION OF ENGINEERING TURBULENCE MODEL
Institute of Scientific and Technical Information of China (English)
钱炜祺; 蔡金狮
2001-01-01
A parameter estimation algorithm is introduced and used to determine the parameters in the standard k-ε two equation turbulence model (SKE). It can be found from the estimation results that although the parameter estimation method is an effective method to determine model parameters, it is difficult to obtain a set of parameters for SKE to suit all kinds of separated flow and a modification of the turbulence model structure should be considered. So, a new nonlinear k-ε two-equation model (NNKE) is put forward in this paper and the corresponding parameter estimation technique is applied to determine the model parameters. By implementing the NNKE to solve some engineering turbulent flows, it is shown that NNKE is more accurate and versatile than SKE. Thus, the success of NNKE implies that the parameter estimation technique may have a bright prospect in engineering turbulence model research.
Breathing dynamics based parameter sensitivity analysis of hetero-polymeric DNA
Energy Technology Data Exchange (ETDEWEB)
Talukder, Srijeeta; Sen, Shrabani; Chaudhury, Pinaki, E-mail: pinakc@rediffmail.com [Department of Chemistry, University of Calcutta, 92 A P C Road, Kolkata 700 009 (India); Chakraborti, Prantik; Banik, Suman K., E-mail: skbanik@jcbose.ac.in [Department of Chemistry, Bose Institute, 93/1 A P C Road, Kolkata 700 009 (India); Metzler, Ralf, E-mail: rmetzler@uni-potsdam.de [Institute for Physics and Astronomy, University of Potsdam, D-14476 Potsdam-Golm, Germany and Physics Department, Tampere University of Technology, FI-33101 Tampere (Finland)
2014-03-28
We study the parameter sensitivity of hetero-polymeric DNA within the purview of DNA breathing dynamics. The degree of correlation between the mean bubble size and the model parameters is estimated for this purpose for three different DNA sequences. The analysis leads us to a better understanding of the sequence dependent nature of the breathing dynamics of hetero-polymeric DNA. Out of the 14 model parameters for DNA stability in the statistical Poland-Scheraga approach, the hydrogen bond interaction ε{sub hb}(AT) for an AT base pair and the ring factor ξ turn out to be the most sensitive parameters. In addition, the stacking interaction ε{sub st}(TA-TA) for an TA-TA nearest neighbor pair of base-pairs is found to be the most sensitive one among all stacking interactions. Moreover, we also establish that the nature of stacking interaction has a deciding effect on the DNA breathing dynamics, not the number of times a particular stacking interaction appears in a sequence. We show that the sensitivity analysis can be used as an effective measure to guide a stochastic optimization technique to find the kinetic rate constants related to the dynamics as opposed to the case where the rate constants are measured using the conventional unbiased way of optimization.
Sensitivity Analyses for Cross-Coupled Parameters in Automotive Powertrain Optimization
Directory of Open Access Journals (Sweden)
Pongpun Othaganont
2014-06-01
Full Text Available When vehicle manufacturers are developing new hybrid and electric vehicles, modeling and simulation are frequently used to predict the performance of the new vehicles from an early stage in the product lifecycle. Typically, models are used to predict the range, performance and energy consumption of their future planned production vehicle; they also allow the designer to optimize a vehicle’s configuration. Another use for the models is in performing sensitivity analysis, which helps us understand which parameters have the most influence on model predictions and real-world behaviors. There are various techniques for sensitivity analysis, some are numerical, but the greatest insights are obtained analytically with sensitivity defined in terms of partial derivatives. Existing methods in the literature give us a useful, quantified measure of parameter sensitivity, a first-order effect, but they do not consider second-order effects. Second-order effects could give us additional insights: for example, a first order analysis might tell us that a limiting factor is the efficiency of the vehicle’s prime-mover; our new second order analysis will tell us how quickly the efficiency of the powertrain will become of greater significance. In this paper, we develop a method based on formal optimization mathematics for rapid second-order sensitivity analyses and illustrate these through a case study on a C-segment electric vehicle.
Sensitivity of viscosity Arrhenius parameters to polarity of liquids
Kacem, R. B. H.; Alzamel, N. O.; Ouerfelli, N.
2017-09-01
Several empirical and semi-empirical equations have been proposed in the literature to estimate the liquid viscosity upon temperature. In this context, this paper aims to study the effect of polarity of liquids on the modeling of the viscosity-temperature dependence, considering particularly the Arrhenius type equations. To achieve this purpose, the solvents are classified into three groups: nonpolar, borderline polar and polar solvents. Based on adequate statistical tests, we found that there is strong evidence that the polarity of solvents affects significantly the distribution of the Arrhenius-type equation parameters and consequently the modeling of the viscosity-temperature dependence. Thus, specific estimated values of parameters for each group of liquids are proposed in this paper. In addition, the comparison of the accuracy of approximation with and without classification of liquids, using the Wilcoxon signed-rank test, shows a significant discrepancy of the borderline polar solvents. For that, we suggested in this paper new specific coefficient values of the simplified Arrhenius-type equation for better estimation accuracy. This result is important given that the accuracy in the estimation of the viscosity-temperature dependence may affect considerably the design and the optimization of several industrial processes.
Younes, A.; Delay, F.; Fajraoui, N.; Fahs, M.; Mara, T. A.
2016-08-01
The concept of dual flowing continuum is a promising approach for modeling solute transport in porous media that includes biofilm phases. The highly dispersed transit time distributions often generated by these media are taken into consideration by simply stipulating that advection-dispersion transport occurs through both the porous and the biofilm phases. Both phases are coupled but assigned with contrasting hydrodynamic properties. However, the dual flowing continuum suffers from intrinsic equifinality in the sense that the outlet solute concentration can be the result of several parameter sets of the two flowing phases. To assess the applicability of the dual flowing continuum, we investigate how the model behaves with respect to its parameters. For the purpose of this study, a Global Sensitivity Analysis (GSA) and a Statistical Calibration (SC) of model parameters are performed for two transport scenarios that differ by the strength of interaction between the flowing phases. The GSA is shown to be a valuable tool to understand how the complex system behaves. The results indicate that the rate of mass transfer between the two phases is a key parameter of the model behavior and influences the identifiability of the other parameters. For weak mass exchanges, the output concentration is mainly controlled by the velocity in the porous medium and by the porosity of both flowing phases. In the case of large mass exchanges, the kinetics of this exchange also controls the output concentration. The SC results show that transport with large mass exchange between the flowing phases is more likely affected by equifinality than transport with weak exchange. The SC also indicates that weakly sensitive parameters, such as the dispersion in each phase, can be accurately identified. Removing them from calibration procedures is not recommended because it might result in biased estimations of the highly sensitive parameters.
Sensitivity Study of Stochastic Walking Load Models
DEFF Research Database (Denmark)
Pedersen, Lars; Frier, Christian
2010-01-01
On flexible structures such as footbridges and long-span floors, walking loads may generate excessive structural vibrations and serviceability problems. The problem is increasing because of the growing tendency to employ long spans in structural design. In many design codes, the vibration...... serviceability limit state is assessed using a walking load model in which the walking parameters are modelled deterministically. However, the walking parameters are stochastic (for instance the weight of the pedestrian is not likely to be the same for every footbridge crossing), and a natural way forward...... investigates whether statistical distributions of bridge response are sensitive to some of the decisions made by the engineer doing the analyses. For the paper a selected part of potential influences are examined and footbridge responses are extracted using Monte-Carlo simulations and focus is on estimating...
Quantifying uncertainty and sensitivity in sea ice models
Energy Technology Data Exchange (ETDEWEB)
Urrego Blanco, Jorge Rolando [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hunke, Elizabeth Clare [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Urban, Nathan Mark [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-07-15
The Los Alamos Sea Ice model has a number of input parameters for which accurate values are not always well established. We conduct a variance-based sensitivity analysis of hemispheric sea ice properties to 39 input parameters. The method accounts for non-linear and non-additive effects in the model.
An automatic and effective parameter optimization method for model tuning
Directory of Open Access Journals (Sweden)
T. Zhang
2015-05-01
Full Text Available Physical parameterizations in General Circulation Models (GCMs, having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determines parameter sensitivity and the other chooses the optimum initial value of sensitive parameters, are introduced before the downhill simplex method to reduce the computational cost and improve the tuning performance. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9%. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameters tuning during the model development stage.
Temperature Sensitivity as a Microbial Trait Using Parameters from Macromolecular Rate Theory
Directory of Open Access Journals (Sweden)
Charlotte Jean Alster
2016-11-01
Full Text Available The activity of soil microbial extracellular enzymes is strongly controlled by temperature, yet the degree to which temperature sensitivity varies by microbe and enzyme type is unclear. Such information would allow soil microbial enzymes to be incorporated in a traits-based framework to improve prediction of ecosystem response to global change. If temperature sensitivity varies for specific soil enzymes, then determining the underlying causes of variation in temperature sensitivity of these enzymes will provide fundamental insights for predicting nutrient dynamics belowground. In this study, we characterized how both microbial taxonomic variation as well as substrate type affects temperature sensitivity. We measured β-glucosidase, leucine aminopeptidase, and phosphatase activities at six temperatures: 4, 11, 25, 35, 45, and 60°C, for seven different soil microbial isolates. To calculate temperature sensitivity, we employed two models, Arrhenius, which predicts an exponential increase in reaction rate with temperature, and Macromolecular Rate Theory (MMRT, which predicts rate to peak and then decline as temperature increases. We found MMRT provided a more accurate fit and allowed for more nuanced interpretation of temperature sensitivity in all of the enzyme × isolate combinations tested. Our results revealed that both the enzyme type and soil isolate type explain variation in parameters associated with temperature sensitivity. Because we found temperature sensitivity to be an inherent and variable property of an enzyme, we argue that it can be incorporated as a microbial functional trait, but only when using the MMRT definition of temperature sensitivity. We show that the Arrhenius metrics of temperature sensitivity are overly sensitive to test conditions, with activation energy changing depending on the temperature range it was calculated within. Thus, we propose the use of the MMRT definition of temperature sensitivity for accurate
Temperature Sensitivity as a Microbial Trait Using Parameters from Macromolecular Rate Theory.
Alster, Charlotte J; Baas, Peter; Wallenstein, Matthew D; Johnson, Nels G; von Fischer, Joseph C
2016-01-01
The activity of soil microbial extracellular enzymes is strongly controlled by temperature, yet the degree to which temperature sensitivity varies by microbe and enzyme type is unclear. Such information would allow soil microbial enzymes to be incorporated in a traits-based framework to improve prediction of ecosystem response to global change. If temperature sensitivity varies for specific soil enzymes, then determining the underlying causes of variation in temperature sensitivity of these enzymes will provide fundamental insights for predicting nutrient dynamics belowground. In this study, we characterized how both microbial taxonomic variation as well as substrate type affects temperature sensitivity. We measured β-glucosidase, leucine aminopeptidase, and phosphatase activities at six temperatures: 4, 11, 25, 35, 45, and 60°C, for seven different soil microbial isolates. To calculate temperature sensitivity, we employed two models, Arrhenius, which predicts an exponential increase in reaction rate with temperature, and Macromolecular Rate Theory (MMRT), which predicts rate to peak and then decline as temperature increases. We found MMRT provided a more accurate fit and allowed for more nuanced interpretation of temperature sensitivity in all of the enzyme × isolate combinations tested. Our results revealed that both the enzyme type and soil isolate type explain variation in parameters associated with temperature sensitivity. Because we found temperature sensitivity to be an inherent and variable property of an enzyme, we argue that it can be incorporated as a microbial functional trait, but only when using the MMRT definition of temperature sensitivity. We show that the Arrhenius metrics of temperature sensitivity are overly sensitive to test conditions, with activation energy changing depending on the temperature range it was calculated within. Thus, we propose the use of the MMRT definition of temperature sensitivity for accurate interpretation of
Selection of body sway parameters according to their sensitivity and repeatability
Directory of Open Access Journals (Sweden)
Nejc Sarabon
2010-03-01
Full Text Available For the precise evaluation of body balance, static type of tests performed on a force plate are the most commonly used ones. In these tests, body sway characteristics are analyzed based on the model of inverted pendulum and looking at the center of pressure (COP movement in time. Human body engages different strategies to compensate for balance perturbations. For this reason, there is a need to identify parameters which are sensitive to specific balance changes and which enable us to identify balance sub-components. The aim of our study was to investigate intra-visit repeatability and sensibility of the 40 different body sway parameters. Twenty-nine subjects participated in the study. They performed three different balancing tasks of different levels of difficulty, three repetitions each. The hip-width parallel stance and the single leg stance, both with open eyes, were used as ways to compare different balance intensities due to biomechanical changes. Additionally, deprivation of vision was used in the third balance task to study sensitivity to sensory system changes. As shown by intraclass correlation coefficient (ICC, repeatability of cumulative parameters such as COP, maximal amplitude and frequency showed excellent repeatability (ICC>0,85. Other parameters describing sub-dynamics through single repetition proved to have unsatisfying repeatability. Parameters most sensitive to increased intensity of balancing tasks were common COP, COP in medio-lateral and in antero-posterior direction, and maximal amplitues in the same directions. Frequency of oscilations has proved to be sensitive only to deprivation of vision. As shown in our study, cumulative parameters describing the path which the center of pressure makes proved to be the most repeatable and sensitive to detect different increases of balancing tasks enabling future use in balance studies and in clinical practice.
Adjoint sensitivity of global cloud droplet number to aerosol and dynamical parameters
Directory of Open Access Journals (Sweden)
V. A. Karydis
2012-10-01
Full Text Available We present the development of the adjoint of a comprehensive cloud droplet formation parameterization for use in aerosol-cloud-climate interaction studies. The adjoint efficiently and accurately calculates the sensitivity of cloud droplet number concentration (CDNC to all parameterization inputs (e.g., updraft velocity, water uptake coefficient, aerosol number and hygroscopicity with a single execution. The adjoint is then integrated within three dimensional (3-D aerosol modeling frameworks to quantify the sensitivity of CDNC formation globally to each parameter. Sensitivities are computed for year-long executions of the NASA Global Modeling Initiative (GMI Chemical Transport Model (CTM, using wind fields computed with the Goddard Institute for Space Studies (GISS Global Circulation Model (GCM II', and the GEOS-Chem CTM, driven by meteorological input from the Goddard Earth Observing System (GEOS of the NASA Global Modeling and Assimilation Office (GMAO. We find that over polluted (pristine areas, CDNC is more sensitive to updraft velocity and uptake coefficient (aerosol number and hygroscopicity. Over the oceans of the Northern Hemisphere, addition of anthropogenic or biomass burning aerosol is predicted to increase CDNC in contrast to coarse-mode sea salt which tends to decrease CDNC. Over the Southern Oceans, CDNC is most sensitive to sea salt, which is the main aerosol component of the region. Globally, CDNC is predicted to be less sensitive to changes in the hygroscopicity of the aerosols than in their concentration with the exception of dust where CDNC is very sensitive to particle hydrophilicity over arid areas. Regionally, the sensitivities differ considerably between the two frameworks and quantitatively reveal why the models differ considerably in their indirect forcing estimates.
Gupta, Manika; Garg, Naveen Kumar; Srivastava, Prashant K.
2014-05-01
The sensitivity and uncertainty analysis has been carried out for the scalar parameters (soil hydraulic parameters (SHPs)), which govern the simulation of soil water content in the unsaturated soil zone. The study involves field experiments, which were conducted in real field conditions for wheat crop in Roorkee, India under irrigated conditions. Soil samples were taken for the soil profile of 60 cm depth at an interval of 15 cm in the experimental field to determine soil water retention curves (SWRCs). These experimentally determined SWRCs were used to estimate the SHPs by least square optimization under constrained conditions. Sensitivity of the SHPs estimated by various pedotransfer functions (PTFs), that relate various easily measurable soil properties like soil texture, bulk density and organic carbon content, is compared with lab derived parameters to simulate respective soil water retention curves. Sensitivity analysis was carried out using the monte carlo simulations and the one factor at a time approach. The different sets of SHPs, along with experimentally determined saturated permeability, are then used as input parameters in physically based, root water uptake model to ascertain the uncertainties in simulating soil water content. The generalised likelihood uncertainty estimation procedure (GLUE) was subsequently used to estimate the uncertainty bounds (UB) on the model predictions. It was found that the experimentally obtained SHPs were able to simulate the soil water contents with efficiencies of 70-80% at all the depths for the three irrigation treatments. The SHPs obtained from the PTFs, performed with varying uncertainties in simulating the soil water contents. Keywords: Sensitivity analysis, Uncertainty estimation, Pedotransfer functions, Soil hydraulic parameters, Hydrological modelling
Sensitivity of Land Surfaces Model to Dynamic Land Surface Parameters%陆面过程模型对下垫面参数动态变化的敏感性分析
Institute of Scientific and Technical Information of China (English)
蔡福; 周广胜; 李荣平; 明惠青
2011-01-01
Using continuous flux data, meteorological data and biological data in 2006 (from June 1 to August 9) from Jinzhou agricultural ecosystem research station, based on BATSIe model, the sensitivity of land surface model to dynamic assignment of roughness( Z0 ), leaf area index(LAI) and fractional vegetation coverage (FVEG)and albedo(α) were investigated. The results show that dynamic assignment of Z0 has effect on simulating surface soil temperature(SST) and sensible heat flux (SH) especially on the time when maize field surface covered changes from bare soil to vegetation. Dynamic LAIplays important role in improving the simulation of SST, net absorbed solar energy flux(Frs), SH and surface soil water content(SWC), at the same time affects simulation of latent heat flux (LE). Dynamic FVEG affects obviously simulations of all above-mentioned variables and shows greater sensitivity when they are smaller. Also, dynamical change of a can affect simulations of SST, LE and SH, especially for the latter. Furthermore, the interactions among different dynamic parameters are ignored by the model. The improvement of single land surface parameter might be helpful for simulating one or multivariate but not for all variables. In short, it is necessary to set up a parameterization scheme with the interactions of different land surface parameters.%利用2006年锦州玉米农田生态系统野外观测站动态连续的通量、气象及生物因子观测数据,分析了BATSl e陆面模型对动态的粗糙度(Z0)、叶面积指数(LAI)、植被履盖度(FVEG)及反照率(α)变化的敏感性.结果表明:Z0的动态变化对表层土壤温度(SST)和感热(SH)的模拟有一定影响,主要发生在玉米农田从裸土向有植被覆盖转变这一阶段.LAI的动态赋值可以改善SST、净入射短波辐射(frs)、SH和SWC的模拟效果,对潜热(LE)的模拟也有一定影响.动态FVEG对上述各变量的模拟影响最为明显,当FVEG较小时敏感性最大.α的动
The sensitivity of wind technology utilization to cost and market parameters
Energy Technology Data Exchange (ETDEWEB)
Dodd, H.M. (Sandia National Labs., Albuquerque, NM (USA)); Hock, S.M.; Thresher, R.W. (Solar Energy Research Inst., Golden, CO (USA))
1990-11-01
This study explores the sensitivity of future wind energy market penetration to available wind resources, wind system costs, and competing energy system fuel costs for several possible energy market evolution scenarios. The methodology for the modeling is described in general terms. Cost curves for wind technology evolution are presented and used in conjunction with wind resource estimates and energy market projections to estimate wind penetration into the market. Results are presented that show the sensitivity of the growth of wind energy use to key cost parameters and to some of the underlying modeling assumptions. In interpreting the results, the authors place particular emphasis on the relative influence of the parameters studied. 4 refs., 8 figs., 1 tab.
Sensitivity Analysis of WEC Array Layout Parameters Effect on the Power Performance
DEFF Research Database (Denmark)
Ruiz, Pau Mercadé; Ferri, Francesco; Kofoed, Jens Peter
2015-01-01
This study assesses the effect that the array layout choice has on the power performance. To this end, a sensitivity analysis is carried out with six array layout parameters, as the simulation inputs, the array power performance (q-factor), as the simulation output, and a simulation model specially...... developed in cooperation with the DTOcean research project, which aims to provide design tools for the deployment of the first generation of ocean energy converter arrays. The sensitivity analysis is performed for the particular case of an array of floating cylinders moving in the usual six rigid body...
An efficient parameter identification procedure for soft sensitive clays
Institute of Scientific and Technical Information of China (English)
Liang YE; Yin-fu JIN; Shui-long SHEN; Ping-ping SUN; Cheng ZHOU
2016-01-01
The creep and destructuration characteristics of soft clay are always coupled under loading, making it difficult for engineers to determine these related parameters. This paper proposes a simple and efficient optimization procedure to identify both creep and destructuration parameters based on low cost experiments. For this purpose, a simplex algorithm (SA) with random samplings is adopted in the optimization. Conventional undrained triaxial tests are performed on Wenzhou clay. The newly de-veloped creep model accounting for the destructuration is enhanced by anisotropy of elasticity and adopted to simulate tests. The optimal parameters are validated first by experimental measurements, and then by simulating other tests on the same clay. Finally, the proposed procedure is successfully applied to soft Shanghai clay. The results demonstrate that the proposed optimization procedure is efficient and reliable in identifying creep and destructuration related parameters.%中文概要题目：一个结构性软土参数的确定方法目的：软土流变和结构破坏的相互耦合导致结构性软土的参数难以准确得到。本文拟建立一个有效的参数确定方法，期望仅基于常规的室内试验得到可靠的、合理的本构参数。创新点：1.通过采用优化方法来实现结构性软土参数的确定；2.仅基于常规的室内试验得到本构参数；3.采用最近提出的考虑各向异性、流变和结构破坏的超应力本构模型。方法：1.建立数值模拟和试验数据之间的误差计算公式；2.通过流变本构模拟室内常规试验，并计算模拟误差；3.采用下山单纯形法（simplex）优化方法，寻找模拟误差的最小值；此最小值对应的这组模拟参数即为土体的最优参数；4.利用最优参数模拟其他类型的试验，验证参数的合理性和可靠性。结论：本文提出的优化程序可以有效的找到结构性土体的流变和结构破坏参数，并
Sensitivities in global scale modeling of isoprene
Directory of Open Access Journals (Sweden)
R. von Kuhlmann
2004-01-01
Full Text Available A sensitivity study of the treatment of isoprene and related parameters in 3D atmospheric models was conducted using the global model of tropospheric chemistry MATCH-MPIC. A total of twelve sensitivity scenarios which can be grouped into four thematic categories were performed. These four categories consist of simulations with different chemical mechanisms, different assumptions concerning the deposition characteristics of intermediate products, assumptions concerning the nitrates from the oxidation of isoprene and variations of the source strengths. The largest differences in ozone compared to the reference simulation occured when a different isoprene oxidation scheme was used (up to 30-60% or about 10 nmol/mol. The largest differences in the abundance of peroxyacetylnitrate (PAN were found when the isoprene emission strength was reduced by 50% and in tests with increased or decreased efficiency of the deposition of intermediates. The deposition assumptions were also found to have a significant effect on the upper tropospheric HOx production. Different implicit assumptions about the loss of intermediate products were identified as a major reason for the deviations among the tested isoprene oxidation schemes. The total tropospheric burden of O3 calculated in the sensitivity runs is increased compared to the background methane chemistry by 26±9 Tg( O3 from 273 to an average from the sensitivity runs of 299 Tg(O3. % revised Thus, there is a spread of ± 35% of the overall effect of isoprene in the model among the tested scenarios. This range of uncertainty and the much larger local deviations found in the test runs suggest that the treatment of isoprene in global models can only be seen as a first order estimate at present, and points towards specific processes in need of focused future work.
Harshan, S.; Roth, M.; Velasco, E.
2014-12-01
Forecasting of the urban weather and climate is of great importance as our cities become more populated and considering the combined effects of global warming and local land use changes which make urban inhabitants more vulnerable to e.g. heat waves and flash floods. In meso/global scale models, urban parameterization schemes are used to represent the urban effects. However, these schemes require a large set of input parameters related to urban morphological and thermal properties. Obtaining all these parameters through direct measurements are usually not feasible. A number of studies have reported on parameter estimation and sensitivity analysis to adjust and determine the most influential parameters for land surface schemes in non-urban areas. Similar work for urban areas is scarce, in particular studies on urban parameterization schemes in tropical cities have so far not been reported. In order to address above issues, the town energy balance (TEB) urban parameterization scheme (part of the SURFEX land surface modeling system) was subjected to a sensitivity and optimization/parameter estimation experiment at a suburban site in, tropical Singapore. The sensitivity analysis was carried out as a screening test to identify the most sensitive or influential parameters. Thereafter, an optimization/parameter estimation experiment was performed to calibrate the input parameter. The sensitivity experiment was based on the "improved Sobol's global variance decomposition method" . The analysis showed that parameters related to road, roof and soil moisture have significant influence on the performance of the model. The optimization/parameter estimation experiment was performed using the AMALGM (a multi-algorithm genetically adaptive multi-objective method) evolutionary algorithm. The experiment showed a remarkable improvement compared to the simulations using the default parameter set. The calibrated parameters from this optimization experiment can be used for further model
PARAMETER ESTIMATION IN BREAD BAKING MODEL
Hadiyanto Hadiyanto; AJB van Boxtel
2012-01-01
Bread product quality is highly dependent to the baking process. A model for the development of product quality, which was obtained by using quantitative and qualitative relationships, was calibrated by experiments at a fixed baking temperature of 200°C alone and in combination with 100 W microwave powers. The model parameters were estimated in a stepwise procedure i.e. first, heat and mass transfer related parameters, then the parameters related to product transformations and finally pro...
Parameter counting in models with global symmetries
Energy Technology Data Exchange (ETDEWEB)
Berger, Joshua [Institute for High Energy Phenomenology, Newman Laboratory of Elementary Particle Physics, Cornell University, Ithaca, NY 14853 (United States)], E-mail: jb454@cornell.edu; Grossman, Yuval [Institute for High Energy Phenomenology, Newman Laboratory of Elementary Particle Physics, Cornell University, Ithaca, NY 14853 (United States)], E-mail: yuvalg@lepp.cornell.edu
2009-05-18
We present rules for determining the number of physical parameters in models with exact flavor symmetries. In such models the total number of parameters (physical and unphysical) needed to described a matrix is less than in a model without the symmetries. Several toy examples are studied in order to demonstrate the rules. The use of global symmetries in studying the minimally supersymmetric standard model (MSSM) is examined.
On parameter estimation in deformable models
DEFF Research Database (Denmark)
Fisker, Rune; Carstensen, Jens Michael
1998-01-01
Deformable templates have been intensively studied in image analysis through the last decade, but despite its significance the estimation of model parameters has received little attention. We present a method for supervised and unsupervised model parameter estimation using a general Bayesian...... method is based on a modified version of the EM algorithm. Experimental results for a deformable template used for textile inspection are presented...
Cosmological models with constant deceleration parameter
Energy Technology Data Exchange (ETDEWEB)
Berman, M.S.; de Mello Gomide, F.
1988-02-01
Berman presented elsewhere a law of variation for Hubble's parameter that yields constant deceleration parameter models of the universe. By analyzing Einstein, Pryce-Hoyle and Brans-Dicke cosmologies, we derive here the necessary relations in each model, considering a perfect fluid.
Xie, Hui; Shen, Zhenyao; Chen, Lei; Qiu, Jiali; Dong, Jianwei
2017-11-15
Environmental models can be used to better understand the hydrologic and sediment behavior in a watershed system. However, different processes may dominate at different time periods and timescales, which highly complicate the model interpretation. The related parameter uncertainty may be significant and needs to be addressed to avoid bias in the watershed management. In this study, we used the time-varying and multi-timescale (TVMT) method to characterize the temporal dynamics of parameter sensitivity at different timescales in hydrologic and sediment modeling. As a case study, the first order sensitivity indices were estimated with the Fourier amplitude sensitivity test (FAST) method for the Hydrological Simulation Program - Fortran (HSPF) model in the Zhangjiachong catchment in the Three Gorge Reservoir Region (TGRR) in China. The results were compared to those of the traditional aggregate method to demonstrate the merits of the TVMT method. The time-varying nature of the hydrologic and sediment parameters was revealed and explained mainly by the variation of hydro-climatic conditions. The baseflow recession parameter, evapotranspiration (ET) parameter for the soil storage, and sediment washoff parameter showed high sensitivities almost across the whole period. However, parameters related to canopy interception and channel sediment scour varied notably over time due to changes in the climate forcing. The timescale-dependent characteristics was observed and was most evident for the baseflow recession parameter and ET parameter. At last, the parameters affecting the sediment export and transport were discussed together with the inferred conservation practices. Reasonable controls for sediment must be storm-dependent. Compared to management practices on the land surface, practices affecting channel process would be more effective during storm events. Our results present one of the first investigations for sediment modeling in terms of the importance of parameter
Sensitivity of detachment extent to magnetic configuration and external parameters
Lipschultz, Bruce; Parra, Felix I.; Hutchinson, Ian H.
2016-05-01
Divertor detachment may be essential to reduce heat loads to magnetic fusion tokamak reactor divertor surfaces. Yet in experiments it is difficult to control the extent of the detached, low pressure, plasma region. At maximum extent the front edge of the detached region reaches the X-point and can lead to degradation of core plasma properties. We define the ‘detachment window’ in a given position control variable C (for example, the upstream plasma density) as the range in C within which the front location can be stably held at any position from the target to the X-point; increased detachment window corresponds to better control. We extend a 1D analytic model [1] to determine the detachment window for the following control variables: the upstream plasma density, the impurity concentration and the power entering the scrape-off layer (SOL). We find that variations in magnetic configuration can have strong effects; increasing the ratio of the total magnetic field at the X-point to that at the target, {{B}×}/{{B}t} , (total flux expansion, as in the super-x divertor configuration) strongly increases the detachment window for all control variables studied, thus strongly improving detachment front control and the capability of the divertor plasma to passively accommodate transients while still staying detached. Increasing flux tube length and thus volume in the divertor, through poloidal flux expansion (as in the snowflake or x-divertor configurations) or length of the divertor, also increases the detachment window, but less than the total flux expansion does. The sensitivity of the detachment front location, z h , to each control variable, C, defined as \\partial {{z}h}/\\partial C , depends on the magnetic configuration. The size of the radiating volume and the total divertor radiation increase \\propto {{≤ft({{B}×}/{{B}t}\\right)}2} and \\propto {{B}×}/{{B}t} , respectively, but not by increasing divertor poloidal flux expansion or field line length. We
A global sensitivity analysis approach for morphogenesis models
Boas, Sonja E. M.
2015-11-21
Background Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such ‘black-box’ models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. Results To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. Conclusions We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all ‘black-box’ models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.
Mohamed, Mohamed M; Saleh, Nawal E; Sherif, Mohsen M
2010-04-01
Dissolved benzene was detected in the shallow unconfined Liwa aquifer (UAE). This aquifer represents the main freshwater source for a nearby residence camp area. A finite element model is used to simulate the fate, transport, and attenuation of the dissolved benzene plume to help decision makers assess natural attenuation as a viable remediation option. Sensitivity of benzene attenuation to uncertainties in the estimation of some of the kinetic and transport parameters is studied. It was found that natural attenuation is more sensitive to microbial growth rate and half saturation coefficients of both benzene and oxygen than initial biomass concentration and dispersivity coefficients. Increasing microbial growth rate by fourfold increased natural attenuation effectiveness after 40 years by 10%; while decreasing it by fourfold decreased natural attenuation effectiveness by 77%. On the other hand, increasing half saturation coefficient by fourfold decreased natural attenuation effectiveness by 46% in 40 years. Decreasing the same parameter fourfold caused natural attenuation effectiveness to increase by 9%.
Zaghloul, Nabil A.
The use of the SWMM model to simulate the Runoff-Transport phenomenon necessitates the proper calibration of the different parameters involved in the process and the effect of these parameters on the routed hydrograph. A detailed sensitivity analysis is conducted on the main parameters of the Runoff-Transport Blocks to establish which are the most sensitive parameters affecting the Runoff-Transport simulation. The result of the study indicates a relative influence of the major parameters used in both the Runoff and Transport Blocks. Hence, the SWMM default values can be used adequately. The costs of setting up and running a SWMM simulation are largely determined by the level of discretisation used for a particular catchment. The purpose of this part of the study is to investigate the level of discretisation needed to adequately represent an urban watershed and to illustrate the effects of reducing the number of subcatchments on the accuracy of runoff simulation. A methodology is defined to achieve a representative equivalent catchment from theoretical considerations. Verification of the procedures involved a series of applications on both hypothetical and real areas.
Directory of Open Access Journals (Sweden)
M. Santhakumar
2009-01-01
Full Text Available Hydrodynamic parameters play a major role in the dynamics and control of Autonomous Underwater Vehicles (AUVs. The performance of an AUV is dependent on the parameter variations and a proper understanding of these parametric influences is essential for the design, modeling, and control of high-performance AUVs. In this paper, the sensitivity of hydrodynamic parameters on the control of a flatfish type AUV is analyzed using robust design techniques such as Taguchi's design method and statistical analysis tools such as Pareto-ANOVA. Since the pitch angle of an AUV is one of the crucial variables in the control applications, the sensitivity analysis of pitch angle variation is studied here. Eight prominent hydrodynamic coefficients are considered in the analysis. The results show that there are two critical hydrodynamic parameters, that is, hydrodynamic force and hydrodynamic pitching moment in the heave direction that influence the performance of a flatfish type AUV. A near-optimal combination of the parameters was identified and the simulation results have shown the effectiveness of the method in reducing the pitch error. These findings are significant for the design modifications as well as controller design of AUVs.
Trait Characteristics of Diffusion Model Parameters
Directory of Open Access Journals (Sweden)
Anna-Lena Schubert
2016-07-01
Full Text Available Cognitive modeling of response time distributions has seen a huge rise in popularity in individual differences research. In particular, several studies have shown that individual differences in the drift rate parameter of the diffusion model, which reflects the speed of information uptake, are substantially related to individual differences in intelligence. However, if diffusion model parameters are to reflect trait-like properties of cognitive processes, they have to qualify as trait-like variables themselves, i.e., they have to be stable across time and consistent over different situations. To assess their trait characteristics, we conducted a latent state-trait analysis of diffusion model parameters estimated from three response time tasks that 114 participants completed at two laboratory sessions eight months apart. Drift rate, boundary separation, and non-decision time parameters showed a great temporal stability over a period of eight months. However, the coefficients of consistency and reliability were only low to moderate and highest for drift rate parameters. These results show that the consistent variance of diffusion model parameters across tasks can be regarded as temporally stable ability parameters. Moreover, they illustrate the need for using broader batteries of response time tasks in future studies on the relationship between diffusion model parameters and intelligence.
Parameter identification in the logistic STAR model
DEFF Research Database (Denmark)
Ekner, Line Elvstrøm; Nejstgaard, Emil
We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter is that th......We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter...
da Silva, Ricardo Siqueira; Kumar, Lalit; Shabani, Farzin; Picanço, Marcelo Coutinho
2017-02-01
A sensitivity analysis can categorize levels of parameter influence on a model's output. Identifying parameters having the most influence facilitates establishing the best values for parameters of models, providing useful implications in species modelling of crops and associated insect pests. The aim of this study was to quantify the response of species models through a CLIMEX sensitivity analysis. Using open-field Solanum lycopersicum and Neoleucinodes elegantalis distribution records, and 17 fitting parameters, including growth and stress parameters, comparisons were made in model performance by altering one parameter value at a time, in comparison to the best-fit parameter values. Parameters that were found to have a greater effect on the model results are termed "sensitive". Through the use of two species, we show that even when the Ecoclimatic Index has a major change through upward or downward parameter value alterations, the effect on the species is dependent on the selection of suitability categories and regions of modelling. Two parameters were shown to have the greatest sensitivity, dependent on the suitability categories of each species in the study. Results enhance user understanding of which climatic factors had a greater impact on both species distributions in our model, in terms of suitability categories and areas, when parameter values were perturbed by higher or lower values, compared to the best-fit parameter values. Thus, the sensitivity analyses have the potential to provide additional information for end users, in terms of improving management, by identifying the climatic variables that are most sensitive.
Parameter Estimation of Partial Differential Equation Models
Xun, Xiaolei
2013-09-01
Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from long-range infrared light detection and ranging data. Supplementary materials for this article are available online. © 2013 American Statistical Association.
Application of lumped-parameter models
Energy Technology Data Exchange (ETDEWEB)
Ibsen, Lars Bo; Liingaard, M.
2006-12-15
This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil. Subsequently, the assembly of the dynamic stiffness matrix for the foundation is considered, and the solution for obtaining the steady state response, when using lumped-parameter models is given. (au)
Study of influence of the fiber optic coatings parameters on optical acoustic sensitivity
Lavrov, V. S.; Kulikov, A. V.; Plotnikov, M. U.; Efimov, M. E.; Varzhel, S. V.
2016-08-01
The paper presents the optical fiber acoustic sensitivity dependence on the coating parameters and the thickness of coating layer. A comparison of data obtained from the theoretical research and experimental estimates of real samples sensitivity in air and water.
Sensitivities in global scale modeling of isoprene
Directory of Open Access Journals (Sweden)
R. von Kuhlmann
2003-06-01
Full Text Available A sensitivity study of the treatment of isoprene and related parameters in 3D atmospheric models was conducted using the global model of tropospheric chemistry MATCH-MPIC. A total of twelve sensitivity scenarios which can be grouped into four thematic categories were performed. These four categories consist of simulations with different chemical mechanisms, different assumptions concerning the deposition characteristics of intermediate products, assumptions concerning the nitrates from the oxidation of isoprene and variations of the source strengths. The largest differences in ozone compared to the reference simulation occured when a different isoprene oxidation scheme was used (up to 30–60% or about 10 nmol/mol. The largest differences in the abundance of peroxyacetylnitrate (PAN were found when the isoprene emission strength was reduced by 50% and in tests with increased or decreased efficiency of the deposition of intermediates. The deposition assumptions were also found to have a significant effect on the upper tropospheric HO_{x} production. Different implicit assumptions about the loss of intermediate products were identified as a major reason for the deviations among the tested isoprene oxidation schemes. The total tropospheric burden of O_{3} calculated in the sensitivity runs is increased compared to the background methane chemistry by 26±9 Tg(O_{3} from 273 to 299 Tg(O(_{3}. Thus, there is a spread of ±35% of the overall effect of isoprene in the model among the tested scenarios. This range of uncertainty and the much larger local deviations found in the test runs suggest that the treatment of isoprene in global models can only be seen as a first order estimate at present, and points towards specific processes in need of focused future work.
PARAMETER ESTIMATION IN BREAD BAKING MODEL
Directory of Open Access Journals (Sweden)
Hadiyanto Hadiyanto
2012-05-01
Full Text Available Bread product quality is highly dependent to the baking process. A model for the development of product quality, which was obtained by using quantitative and qualitative relationships, was calibrated by experiments at a fixed baking temperature of 200°C alone and in combination with 100 W microwave powers. The model parameters were estimated in a stepwise procedure i.e. first, heat and mass transfer related parameters, then the parameters related to product transformations and finally product quality parameters. There was a fair agreement between the calibrated model results and the experimental data. The results showed that the applied simple qualitative relationships for quality performed above expectation. Furthermore, it was confirmed that the microwave input is most meaningful for the internal product properties and not for the surface properties as crispness and color. The model with adjusted parameters was applied in a quality driven food process design procedure to derive a dynamic operation pattern, which was subsequently tested experimentally to calibrate the model. Despite the limited calibration with fixed operation settings, the model predicted well on the behavior under dynamic convective operation and on combined convective and microwave operation. It was expected that the suitability between model and baking system could be improved further by performing calibration experiments at higher temperature and various microwave power levels. Abstrak PERKIRAAN PARAMETER DALAM MODEL UNTUK PROSES BAKING ROTI. Kualitas produk roti sangat tergantung pada proses baking yang digunakan. Suatu model yang telah dikembangkan dengan metode kualitatif dan kuantitaif telah dikalibrasi dengan percobaan pada temperatur 200oC dan dengan kombinasi dengan mikrowave pada 100 Watt. Parameter-parameter model diestimasi dengan prosedur bertahap yaitu pertama, parameter pada model perpindahan masa dan panas, parameter pada model transformasi, dan
Improved parameter estimation for hydrological models using weighted object functions
Stein, A.; Zaadnoordijk, W.J.
1999-01-01
This paper discusses the sensitivity of calibration of hydrological model parameters to different objective functions. Several functions are defined with weights depending upon the hydrological background. These are compared with an objective function based upon kriging. Calibration is applied to pi
Energy Technology Data Exchange (ETDEWEB)
Adelman, D.D. [Water Resources Engineer, Lincoln, NE (United States); Stansbury, J. [Univ. of Nebraska-Lincoln, Omaha, NE (United States)
1997-12-31
The Resource Conservation and Recovery Act (RCRA) Subtitle C, Comprehensive Environmental Response, Compensation, And Liability Act (CERCLA), and subsequent amendments have formed a comprehensive framework to deal with hazardous wastes on the national level. Key to this waste management is guidance on design (e.g., cover and bottom leachate control systems) of hazardous waste landfills. The objective of this research was to investigate the sensitivity of leachate volume at hazardous waste disposal sites to climatic, soil cover, and vegetative cover (Leaf Area Index) conditions. The computer model HELP3 which has the capability to simulate double bottom liner systems as called for in hazardous waste disposal sites was used in the analysis. HELP3 was used to model 54 combinations of climatic conditions, disposal site soil surface curve numbers, and leaf area index values to investigate how sensitive disposal site leachate volume was to these three variables. Results showed that leachate volume from the bottom double liner system was not sensitive to these parameters. However, the cover liner system leachate volume was quite sensitive to climatic conditions and less sensitive to Leaf Area Index and curve number values. Since humid locations had considerably more cover liner system leachate volume than and locations, different design standards may be appropriate for humid conditions than for and conditions.
Statefinder parameters in two dark energy models
Panotopoulos, Grigoris
2007-01-01
The statefinder parameters ($r,s$) in two dark energy models are studied. In the first, we discuss in four-dimensional General Relativity a two fluid model, in which dark energy and dark matter are allowed to interact with each other. In the second model, we consider the DGP brane model generalized by taking a possible energy exchange between the brane and the bulk into account. We determine the values of the statefinder parameters that correspond to the unique attractor of the system at hand. Furthermore, we produce plots in which we show $s,r$ as functions of red-shift, and the ($s-r$) plane for each model.
Parameter Symmetry of the Interacting Boson Model
Shirokov, A M; Smirnov, Yu F; Shirokov, Andrey M.; Smirnov, Yu. F.
1998-01-01
We discuss the symmetry of the parameter space of the interacting boson model (IBM). It is shown that for any set of the IBM Hamiltonian parameters (with the only exception of the U(5) dynamical symmetry limit) one can always find another set that generates the equivalent spectrum. We discuss the origin of the symmetry and its relevance for physical applications.
Ambient pressure sensitivity of microbubbles investigated through a parameter study
DEFF Research Database (Denmark)
Andersen, Klaus Scheldrup; Jensen, Jørgen Arendt
2009-01-01
Measurements on microbubbles clearly indicate a relation between the ambient pressure and the acoustic behavior of the bubble. The purpose of this study was to optimize the sensitivity of ambient pressure measurements, using the subharmonic component, through microbubble response simulations...... cycles driving pulse, a reduction of 4.6 dB is observed when changing pov from 0 to 25 kPa. Increasing the pulse duration makes the reduction even more clear. For a pulse with 64 cycles, the reduction is 9.9 dB. This simulation is in good correspondence with measurement results presented by Shi et al....... 1999, who found a linear reduction of 9.6 dB. Further simulations of Levovist show that also the shape and the acoustic pressure of the driving pulse are very important factors. The best pressure sensitivity of Levovist was found to be 0.88 dB/kPa. For Sonazoid, a sensitivity of 1.14 dB/kPa has been...
Wind Farm Decentralized Dynamic Modeling With Parameters
DEFF Research Database (Denmark)
Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran;
2010-01-01
Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...
Setting Parameters for Biological Models With ANIMO
Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Post, Janine Nicole; van de Pol, Jan Cornelis; Langerak, Romanus; André, Étienne; Frehse, Goran
2014-01-01
ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions
Rosero, Enrique; Yang, Zong-Liang; Wagener, Thorsten; Gulden, Lindsey E.; Yatheendradas, Soni; Niu, Guo-Yue
2009-01-01
We use sensitivity analysis to identify the parameters that are most responsible for shaping land surface model (LSM) simulations and to understand the complex interactions in three versions of the Noah LSM: the standard version (STD), a version enhanced with a simple groundwater module (GW), and version augmented by a dynamic phenology module (DV). We use warm season, high-frequency, near-surface states and turbulent fluxes collected over nine sites in the US Southern Great Plains. We quantify changes in the pattern of sensitive parameters, the amount and nature of the interaction between parameters, and the covariance structure of the distribution of behavioral parameter sets. Using Sobol s total and first-order sensitivity indexes, we show that very few parameters directly control the variance of the model output. Significant parameter interaction occurs so that not only the optimal parameter values differ between models, but the relationships between parameters change. GW decreases parameter interaction and appears to improve model realism, especially at wetter sites. DV increases parameter interaction and decreases identifiability, implying it is overparameterized and/or underconstrained. A case study at a wet site shows GW has two functional modes: one that mimics STD and a second in which GW improves model function by decoupling direct evaporation and baseflow. Unsupervised classification of the posterior distributions of behavioral parameter sets cannot group similar sites based solely on soil or vegetation type, helping to explain why transferability between sites and models is not straightforward. This evidence suggests a priori assignment of parameters should also consider climatic differences.
Directory of Open Access Journals (Sweden)
Baker Syed
2011-01-01
Full Text Available Abstract In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. What differentiates this approach is the integration of an orthogonal-based local identifiability method into the unscented Kalman filter (UKF, rather than using the more common observability-based method which has inherent limitations. It also introduces a variable step size based on the system uncertainty of the UKF during the sensitivity calculation. This method identified 10 out of 12 parameters as identifiable. These ten parameters were estimated using the UKF, which was run 97 times. Throughout the repetitions the UKF proved to be more consistent than the estimation algorithms used for comparison.
Baker, Syed Murtuza; Poskar, C Hart; Junker, Björn H
2011-10-11
In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. What differentiates this approach is the integration of an orthogonal-based local identifiability method into the unscented Kalman filter (UKF), rather than using the more common observability-based method which has inherent limitations. It also introduces a variable step size based on the system uncertainty of the UKF during the sensitivity calculation. This method identified 10 out of 12 parameters as identifiable. These ten parameters were estimated using the UKF, which was run 97 times. Throughout the repetitions the UKF proved to be more consistent than the estimation algorithms used for comparison.
Masterlark, Timothy; Donovan, Theodore; Feigl, Kurt L.; Haney, Matthew; Thurber, Clifford H.; Tung, Sui
2016-04-01
The eruption cycle of a volcano is controlled in part by the upward migration of magma. The characteristics of the magma flux produce a deformation signature at the Earth's surface. Inverse analyses use geodetic data to estimate strategic controlling parameters that describe the position and pressurization of a magma chamber at depth. The specific distribution of material properties controls how observed surface deformation translates to source parameter estimates. Seismic tomography models describe the spatial distributions of material properties that are necessary for accurate models of volcano deformation. This study investigates how uncertainties in seismic tomography models propagate into variations in the estimates of volcano deformation source parameters inverted from geodetic data. We conduct finite element model-based nonlinear inverse analyses of interferometric synthetic aperture radar (InSAR) data for Okmok volcano, Alaska, as an example. We then analyze the estimated parameters and their uncertainties to characterize the magma chamber. Analyses are performed separately for models simulating a pressurized chamber embedded in a homogeneous domain as well as for a domain having a heterogeneous distribution of material properties according to seismic tomography. The estimated depth of the source is sensitive to the distribution of material properties. The estimated depths for the homogeneous and heterogeneous domains are 2666 ± 42 and 3527 ± 56 m below mean sea level, respectively (99% confidence). A Monte Carlo analysis indicates that uncertainties of the seismic tomography cannot account for this discrepancy at the 99% confidence level. Accounting for the spatial distribution of elastic properties according to seismic tomography significantly improves the fit of the deformation model predictions and significantly influences estimates for parameters that describe the location of a pressurized magma chamber.
Parameter Estimation, Model Reduction and Quantum Filtering
Chase, Bradley A
2009-01-01
This dissertation explores the topics of parameter estimation and model reduction in the context of quantum filtering. Chapters 2 and 3 provide a review of classical and quantum probability theory, stochastic calculus and filtering. Chapter 4 studies the problem of quantum parameter estimation and introduces the quantum particle filter as a practical computational method for parameter estimation via continuous measurement. Chapter 5 applies these techniques in magnetometry and studies the estimator's uncertainty scalings in a double-pass atomic magnetometer. Chapter 6 presents an efficient feedback controller for continuous-time quantum error correction. Chapter 7 presents an exact model of symmetric processes of collective qubit systems.
An Effective Parameter Screening Strategy for High Dimensional Watershed Models
Khare, Y. P.; Martinez, C. J.; Munoz-Carpena, R.
2014-12-01
Watershed simulation models can assess the impacts of natural and anthropogenic disturbances on natural systems. These models have become important tools for tackling a range of water resources problems through their implementation in the formulation and evaluation of Best Management Practices, Total Maximum Daily Loads, and Basin Management Action Plans. For accurate applications of watershed models they need to be thoroughly evaluated through global uncertainty and sensitivity analyses (UA/SA). However, due to the high dimensionality of these models such evaluation becomes extremely time- and resource-consuming. Parameter screening, the qualitative separation of important parameters, has been suggested as an essential step before applying rigorous evaluation techniques such as the Sobol' and Fourier Amplitude Sensitivity Test (FAST) methods in the UA/SA framework. The method of elementary effects (EE) (Morris, 1991) is one of the most widely used screening methodologies. Some of the common parameter sampling strategies for EE, e.g. Optimized Trajectories [OT] (Campolongo et al., 2007) and Modified Optimized Trajectories [MOT] (Ruano et al., 2012), suffer from inconsistencies in the generated parameter distributions, infeasible sample generation time, etc. In this work, we have formulated a new parameter sampling strategy - Sampling for Uniformity (SU) - for parameter screening which is based on the principles of the uniformity of the generated parameter distributions and the spread of the parameter sample. A rigorous multi-criteria evaluation (time, distribution, spread and screening efficiency) of OT, MOT, and SU indicated that SU is superior to other sampling strategies. Comparison of the EE-based parameter importance rankings with those of Sobol' helped to quantify the qualitativeness of the EE parameter screening approach, reinforcing the fact that one should use EE only to reduce the resource burden required by FAST/Sobol' analyses but not to replace it.
Application of simplified model to sensitivity analysis of solidification process
Directory of Open Access Journals (Sweden)
R. Szopa
2007-12-01
Full Text Available The sensitivity models of thermal processes proceeding in the system casting-mould-environment give the essential information concerning the influence of physical and technological parameters on a course of solidification. Knowledge of time-dependent sensitivity field is also very useful in a case of inverse problems numerical solution. The sensitivity models can be constructed using the direct approach, this means by differentiation of basic energy equations and boundary-initial conditions with respect to parameter considered. Unfortunately, the analytical form of equations and conditions obtained can be very complex both from the mathematical and numerical points of view. Then the other approach consisting in the application of differential quotient can be applied. In the paper the exact and approximate approaches to the modelling of sensitivity fields are discussed, the examples of computations are also shown.
A qualitative model structure sensitivity analysis method to support model selection
Van Hoey, S.; Seuntjens, P.; van der Kwast, J.; Nopens, I.
2014-11-01
The selection and identification of a suitable hydrological model structure is a more challenging task than fitting parameters of a fixed model structure to reproduce a measured hydrograph. The suitable model structure is highly dependent on various criteria, i.e. the modeling objective, the characteristics and the scale of the system under investigation and the available data. Flexible environments for model building are available, but need to be assisted by proper diagnostic tools for model structure selection. This paper introduces a qualitative method for model component sensitivity analysis. Traditionally, model sensitivity is evaluated for model parameters. In this paper, the concept is translated into an evaluation of model structure sensitivity. Similarly to the one-factor-at-a-time (OAT) methods for parameter sensitivity, this method varies the model structure components one at a time and evaluates the change in sensitivity towards the output variables. As such, the effect of model component variations can be evaluated towards different objective functions or output variables. The methodology is presented for a simple lumped hydrological model environment, introducing different possible model building variations. By comparing the effect of changes in model structure for different model objectives, model selection can be better evaluated. Based on the presented component sensitivity analysis of a case study, some suggestions with regard to model selection are formulated for the system under study: (1) a non-linear storage component is recommended, since it ensures more sensitive (identifiable) parameters for this component and less parameter interaction; (2) interflow is mainly important for the low flow criteria; (3) excess infiltration process is most influencing when focussing on the lower flows; (4) a more simple routing component is advisable; and (5) baseflow parameters have in general low sensitivity values, except for the low flow criteria.
Parameter Estimation for Thurstone Choice Models
Energy Technology Data Exchange (ETDEWEB)
Vojnovic, Milan [London School of Economics (United Kingdom); Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-04-24
We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one or more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.
Ickes, Luisa; Welti, André; Lohmann, Ulrike
2017-02-01
Heterogeneous ice formation by immersion freezing in mixed-phase clouds can be parameterized in general circulation models (GCMs) by classical nucleation theory (CNT). CNT parameterization schemes describe immersion freezing as a stochastic process, including the properties of insoluble aerosol particles in the droplets. There are different ways to parameterize the properties of aerosol particles (i.e., contact angle schemes), which are compiled and tested in this paper. The goal of this study is to find a parameterization scheme for GCMs to describe immersion freezing with the ability to shift and adjust the slope of the freezing curve compared to homogeneous freezing to match experimental data. We showed in a previous publication that the resulting freezing curves from CNT are very sensitive to unconstrained kinetic and thermodynamic parameters in the case of homogeneous freezing. Here we investigate how sensitive the outcome of a parameter estimation for contact angle schemes from experimental data is to unconstrained kinetic and thermodynamic parameters. We demonstrate that the parameters describing the contact angle schemes can mask the uncertainty in thermodynamic and kinetic parameters. Different CNT formulations are fitted to an extensive immersion freezing dataset consisting of size-selected measurements as a function of temperature and time for different mineral dust types, namely kaolinite, illite, montmorillonite, microcline (K-feldspar), and Arizona test dust. We investigated how accurate different CNT formulations (with estimated fit parameters for different contact angle schemes) reproduce the measured freezing data, especially the time and particle size dependence of the freezing process. The results are compared to a simplified deterministic freezing scheme. In this context, we evaluated which CNT-based parameterization scheme able to represent particle properties is the best choice to describe immersion freezing in a GCM.
Parameter uncertainty and sensitivity analysis in sediment flux calculation
Directory of Open Access Journals (Sweden)
B. Cheviron
2011-01-01
Full Text Available This paper examines uncertainties in the calculation of annual sediment budgets at the outlet of rivers. Emphasis is put on the sensitivity of power-law rating curves to degradations of the available discharge-concentration data. The main purpose is to determine how predictions arising from usual or modified power laws resist to the infrequence of concentration data and to relative uncertainties affecting source data. This study identifies cases in which the error on the estimated sediment fluxes remains of the same order of magnitude or even inferior to these in source data, provided the number of concentration data is high enough. The exposed mathematical framework allows considering all limitations at once in further detailed investigations. It is applied here to bound the error on sediment budgets for the major French rivers to the sea.
Sensitivity of adjustment to parameter correlations and to response-parameter correlations
Energy Technology Data Exchange (ETDEWEB)
Wagschal, J.J. [Racah Inst. of Physics, Hebrew Univ. of Jerusalem, Edmond J. Safra Campus, Jerusalem, 91904 (Israel)
2011-07-01
The adjusted parameters and response, and their respective posterior uncertainties and correlations, are presented explicitly as functions of all relevant prior correlations for the two parameters, one response case. The dependence of these adjusted entities on the various prior correlations is analyzed and portrayed graphically for various valid correlation combinations on a simple criticality problem. (authors)
Systematic parameter inference in stochastic mesoscopic modeling
Lei, Huan; Yang, Xiu; Li, Zhen; Karniadakis, George Em
2017-02-01
We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are "sparse". The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.
Simulation of multi-scale heterogeneity of porous media and parameter sensitivity analysis
Institute of Scientific and Technical Information of China (English)
ZHANG; Yong; (张; 勇); G.E.; Fogg
2003-01-01
Because of the inherent multi-scale heterogeneity of porous media and the limitation of single-subject observed data, we propose to combine deterministic and stochastic techniques to simulate heterogeneity. We select a coastal plain sediment system as an example to demonstrate and verify this approach. Firstly, we apply transition probability matrix to determine and delineate the nonstationary unconformity, and combine hydro-stratigraphy analyses to establish the field/large-scale, deterministic stratigraphy model. Secondly, we apply fence diagrams and CPT data to infer the horizontal mean length of hydrofacies, and then build Markov chain models for each depositional system and simulate the local/intermediate-scale, stochastic hydrofacies model. Finally, we combine the stratigraphy and hydrofacies models to get a multi-scale heterogeneous model embedded with quantitative and qualitative observed data, with both deterministic and stochastic characteristics. In order to study the influence of uncertainty in model parameters on solute transport, we build multiple realizations of two types of heterogeneous model and use them to simulate groundwater flow and solute transport. The parameter sensitivity analysis shows the 1st and 2nd spatial moments of the contaminant plume increase with the lateral average length of hydrofacies.
Application of lumped-parameter models
DEFF Research Database (Denmark)
Ibsen, Lars Bo; Liingaard, Morten
This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil (section 1.1). Subse...
Models and parameters for environmental radiological assessments
Energy Technology Data Exchange (ETDEWEB)
Miller, C W [ed.
1984-01-01
This book presents a unified compilation of models and parameters appropriate for assessing the impact of radioactive discharges to the environment. Models examined include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Chapters have been entered separately into the data base. (ACR)
Directory of Open Access Journals (Sweden)
Sankar N. Bhattacharya
2015-11-01
Full Text Available Sensitivity kernels or partial derivatives of phase velocity (c and group velocity (U with respect to medium parameters are useful to interpret a given set of observed surface wave velocity data. In addition to phase velocities, group velocities are also being observed to find the radial anisotropy of the crust and mantle. However, sensitivities of group velocity for a radially anisotropic Earth have rarely been studied. Here we show sensitivities of group velocity along with those of phase velocity to the medium parameters VSV, VSH , VPV, VPH , h and density in a radially anisotropic spherical Earth. The peak sensitivities for U are generally twice of those for c; thus U is more efficient than c to explore anisotropic nature of the medium. Love waves mainly depends on VSH while Rayleigh waves is nearly independent of VSH . The sensitivities show that there are trade-offs among these parameters during inversion and there is a need to reduce the number of parameters to be evaluated independently. It is suggested to use a nonlinear inversion jointly for Rayleigh and Love waves; in such a nonlinear inversion best solutions are obtained among the model parameters within prescribed limits for each parameter. We first choose VSH, VSV and VPH within their corresponding limits; VPV and h can be evaluated from empirical relations among the parameters. The density has small effect on surface wave velocities and it can be considered from other studies or from empirical relation of density to average P-wave velocity.
Latent sensitization: a model for stress-sensitive chronic pain.
Marvizon, Juan Carlos; Walwyn, Wendy; Minasyan, Ani; Chen, Wenling; Taylor, Bradley K
2015-04-01
Latent sensitization is a rodent model of chronic pain that reproduces both its episodic nature and its sensitivity to stress. It is triggered by a wide variety of injuries ranging from injection of inflammatory agents to nerve damage. It follows a characteristic time course in which a hyperalgesic phase is followed by a phase of remission. The hyperalgesic phase lasts between a few days to several months, depending on the triggering injury. Injection of μ-opioid receptor inverse agonists (e.g., naloxone or naltrexone) during the remission phase induces reinstatement of hyperalgesia. This indicates that the remission phase does not represent a return to the normal state, but rather an altered state in which hyperalgesia is masked by constitutive activity of opioid receptors. Importantly, stress also triggers reinstatement. Here we describe in detail procedures for inducing and following latent sensitization in its different phases in rats and mice. Copyright © 2015 John Wiley & Sons, Inc.
Improvement of Continuous Hydrologic Models and HMS SMA Parameters Reduction
Rezaeian Zadeh, Mehdi; Zia Hosseinipour, E.; Abghari, Hirad; Nikian, Ashkan; Shaeri Karimi, Sara; Moradzadeh Azar, Foad
2010-05-01
Hydrological models can help us to predict stream flows and associated runoff volumes of rainfall events within a watershed. There are many different reasons why we need to model the rainfall-runoff processes of for a watershed. However, the main reason is the limitation of hydrological measurement techniques and the costs of data collection at a fine scale. Generally, we are not able to measure all that we would like to know about a given hydrological systems. This is very particularly the case for ungauged catchments. Since the ultimate aim of prediction using models is to improve decision-making about a hydrological problem, therefore, having a robust and efficient modeling tool becomes an important factor. Among several hydrologic modeling approaches, continuous simulation has the best predictions because it can model dry and wet conditions during a long-term period. Continuous hydrologic models, unlike event based models, account for a watershed's soil moisture balance over a long-term period and are suitable for simulating daily, monthly, and seasonal streamflows. In this paper, we describe a soil moisture accounting (SMA) algorithm added to the hydrologic modeling system (HEC-HMS) computer program. As is well known in the hydrologic modeling community one of the ways for improving a model utility is the reduction of input parameters. The enhanced model developed in this study is applied to Khosrow Shirin Watershed, located in the north-west part of Fars Province in Iran, a data limited watershed. The HMS SMA algorithm divides the potential path of rainfall onto a watershed into five zones. The results showed that the output of HMS SMA is insensitive with the variation of many parameters such as soil storage and soil percolation rate. The study's objective is to remove insensitive parameters from the model input using Multi-objective sensitivity analysis. Keywords: Continuous Hydrologic Modeling, HMS SMA, Multi-objective sensitivity analysis, SMA Parameters
Parameters influencing deposit estimation when using water sensitive papers
Directory of Open Access Journals (Sweden)
Emanuele Cerruto
2013-10-01
Full Text Available The aim of the study was to assess the possibility of using water sensitive papers (WSP to estimate the amount of deposit on the target when varying the spray characteristics. To identify the main quantities influencing the deposit, some simplifying hypotheses were applied to simulate WSP behaviour: log-normal distribution of the diameters of the drops and circular stains randomly placed on the images. A very large number (4704 of images of WSPs were produced by means of simulation. The images were obtained by simulating drops of different arithmetic mean diameter (40-300 μm, different coefficient of variation (0.1-1.5, and different percentage of covered surface (2-100%, not considering overlaps. These images were considered to be effective WSP images and then analysed using image processing software in order to measure the percentage of covered surface, the number of particles, and the area of each particle; the deposit was then calculated. These data were correlated with those used to produce the images, varying the spray characteristics. As far as the drop populations are concerned, a classification based on the volume median diameter only should be avoided, especially in case of high variability. This, in fact, results in classifying sprays with very low arithmetic mean diameter as extremely or ultra coarse. The WSP image analysis shows that the relation between simulated and computed percentage of covered surface is independent of the type of spray, whereas impact density and unitary deposit can be estimated from the computed percentage of covered surface only if the spray characteristics (arithmetic mean and coefficient of variation of the drop diameters are known. These data can be estimated by analysing the particles on the WSP images. The results of a validation test show good agreement between simulated and computed deposits, testified by a high (0.93 coefficient of determination.
Numerical modeling of piezoelectric transducers using physical parameters.
Cappon, Hans; Keesman, Karel J
2012-05-01
Design of ultrasonic equipment is frequently facilitated with numerical models. These numerical models, however, need a calibration step, because usually not all characteristics of the materials used are known. Characterization of material properties combined with numerical simulations and experimental data can be used to acquire valid estimates of the material parameters. In our design application, a finite element (FE) model of an ultrasonic particle separator, driven by an ultrasonic transducer in thickness mode, is required. A limited set of material parameters for the piezoelectric transducer were obtained from the manufacturer, thus preserving prior physical knowledge to a large extent. The remaining unknown parameters were estimated from impedance analysis with a simple experimental setup combined with a numerical optimization routine using 2-D and 3-D FE models. Thus, a full set of physically interpretable material parameters was obtained for our specific purpose. The approach provides adequate accuracy of the estimates of the material parameters, near 1%. These parameter estimates will subsequently be applied in future design simulations, without the need to go through an entire series of characterization experiments. Finally, a sensitivity study showed that small variations of 1% in the main parameters caused changes near 1% in the eigenfrequency, but changes up to 7% in the admittance peak, thus influencing the efficiency of the system. Temperature will already cause these small variations in response; thus, a frequency control unit is required when actually manufacturing an efficient ultrasonic separation system.
Lambert, Joseph Michael
2013-01-01
The purpose of this study was to determine whether altering parameters of positive and negative reinforcement in identical ways could influence behavior maintained by each in different ways. Three undergraduate students participated in a series of assessments designed to identify preferred and aversive sounds with similar reinforcing values. Following reinforcer identification, we conducted parameter sensitivity assessments for both positive and negative reinforcers. Parameter manipulation...
Energy Technology Data Exchange (ETDEWEB)
Tonk, Elisa C.M., E-mail: ilse.tonk@rivm.nl [Department of Toxicogenomics, Maastricht University, Maastricht (Netherlands); Laboratory for Health Protection Research, National Institute for Public Health and the Environment (RIVM), Bilthoven (Netherlands); Verhoef, Aart; Gremmer, Eric R. [Laboratory for Health Protection Research, National Institute for Public Health and the Environment (RIVM), Bilthoven (Netherlands); Loveren, Henk van [Department of Toxicogenomics, Maastricht University, Maastricht (Netherlands); Laboratory for Health Protection Research, National Institute for Public Health and the Environment (RIVM), Bilthoven (Netherlands); Piersma, Aldert H. [Laboratory for Health Protection Research, National Institute for Public Health and the Environment (RIVM), Bilthoven (Netherlands); Institute for Risk Assessment Sciences, Veterinary Faculty, Utrecht University, Utrecht (Netherlands)
2012-04-01
The developing immune system displays a relatively high sensitivity as compared to both general toxicity parameters and to the adult immune system. In this study we have performed such comparisons using di(2-ethylhexyl) phthalate (DEHP) as a model compound. DEHP is the most abundant phthalate in the environment and perinatal exposure to DEHP has been shown to disrupt male sexual differentiation. In addition, phthalate exposure has been associated with immune dysfunction as evidenced by effects on the expression of allergy. Male wistar rats were dosed with corn oil or DEHP by gavage from postnatal day (PND) 10–50 or PND 50–90 at doses between 1 and 1000 mg/kg/day. Androgen-dependent organ weights showed effects at lower dose levels in juvenile versus adult animals. Immune parameters affected included TDAR parameters in both age groups, NK activity in juvenile animals and TNF-α production by adherent splenocytes in adult animals. Immune parameters were affected at lower dose levels compared to developmental parameters. Overall, more immune parameters were affected in juvenile animals compared to adult animals and effects were observed at lower dose levels. The results of this study show a relatively higher sensitivity of juvenile versus adult rats. Furthermore, they illustrate the relative sensitivity of the developing immune system in juvenile animals as compared to general toxicity and developmental parameters. This study therefore provides further argumentation for performing dedicated developmental immune toxicity testing as a default in regulatory toxicology. -- Highlights: ► In this study we evaluate the relative sensitivities for DEHP induced effects. ► Results of this study demonstrate the age-dependency of DEHP toxicity. ► Functional immune parameters were more sensitive than structural immune parameters. ► Immune parameters were affected at lower dose levels than developmental parameters. ► Findings demonstrate the susceptibility of the
Energy Technology Data Exchange (ETDEWEB)
Schuchardt, Karen L.; Agarwal, Khushbu; Chase, Jared M.; Rockhold, Mark L.; Freedman, Vicky L.; Elsethagen, Todd O.; Scheibe, Timothy D.; Chin, George; Sivaramakrishnan, Chandrika
2010-07-15
The Support Architecture for Large-Scale Subsurface Analysis (SALSSA) provides an extensible framework, sophisticated graphical user interface, and underlying data management system that simplifies the process of running subsurface models, tracking provenance information, and analyzing the model results. Initially, SALSSA supported two styles of job control: user directed execution and monitoring of individual jobs, and load balancing of jobs across multiple machines taking advantage of many available workstations. Recent efforts in subsurface modelling have been directed at advancing simulators to take advantage of leadership class supercomputers. We describe two approaches, current progress, and plans toward enabling efficient application of the subsurface simulator codes via the SALSSA framework: automating sensitivity analysis problems through task parallelism, and task parallel parameter estimation using the PEST framework.
Estimation of Model Parameters for Steerable Needles
Park, Wooram; Reed, Kyle B.; Okamura, Allison M.; Chirikjian, Gregory S.
2010-01-01
Flexible needles with bevel tips are being developed as useful tools for minimally invasive surgery and percutaneous therapy. When such a needle is inserted into soft tissue, it bends due to the asymmetric geometry of the bevel tip. This insertion with bending is not completely repeatable. We characterize the deviations in needle tip pose (position and orientation) by performing repeated needle insertions into artificial tissue. The base of the needle is pushed at a constant speed without rotating, and the covariance of the distribution of the needle tip pose is computed from experimental data. We develop the closed-form equations to describe how the covariance varies with different model parameters. We estimate the model parameters by matching the closed-form covariance and the experimentally obtained covariance. In this work, we use a needle model modified from a previously developed model with two noise parameters. The modified needle model uses three noise parameters to better capture the stochastic behavior of the needle insertion. The modified needle model provides an improvement of the covariance error from 26.1% to 6.55%. PMID:21643451
Estimation of Model Parameters for Steerable Needles.
Park, Wooram; Reed, Kyle B; Okamura, Allison M; Chirikjian, Gregory S
2010-01-01
Flexible needles with bevel tips are being developed as useful tools for minimally invasive surgery and percutaneous therapy. When such a needle is inserted into soft tissue, it bends due to the asymmetric geometry of the bevel tip. This insertion with bending is not completely repeatable. We characterize the deviations in needle tip pose (position and orientation) by performing repeated needle insertions into artificial tissue. The base of the needle is pushed at a constant speed without rotating, and the covariance of the distribution of the needle tip pose is computed from experimental data. We develop the closed-form equations to describe how the covariance varies with different model parameters. We estimate the model parameters by matching the closed-form covariance and the experimentally obtained covariance. In this work, we use a needle model modified from a previously developed model with two noise parameters. The modified needle model uses three noise parameters to better capture the stochastic behavior of the needle insertion. The modified needle model provides an improvement of the covariance error from 26.1% to 6.55%.
An Optimization Model of Tunnel Support Parameters
Directory of Open Access Journals (Sweden)
Su Lijuan
2015-05-01
Full Text Available An optimization model was developed to obtain the ideal values of the primary support parameters of tunnels, which are wide-ranging in high-speed railway design codes when the surrounding rocks are at the III, IV, and V levels. First, several sets of experiments were designed and simulated using the FLAC3D software under an orthogonal experimental design. Six factors, namely, level of surrounding rock, buried depth of tunnel, lateral pressure coefficient, anchor spacing, anchor length, and shotcrete thickness, were considered. Second, a regression equation was generated by conducting a multiple linear regression analysis following the analysis of the simulation results. Finally, the optimization model of support parameters was obtained by solving the regression equation using the least squares method. In practical projects, the optimized values of support parameters could be obtained by integrating known parameters into the proposed model. In this work, the proposed model was verified on the basis of the Liuyang River Tunnel Project. Results show that the optimization model significantly reduces related costs. The proposed model can also be used as a reliable reference for other high-speed railway tunnels.
Sensitivity Analysis of a Simplified Fire Dynamic Model
DEFF Research Database (Denmark)
Sørensen, Lars Schiøtt; Nielsen, Anker
2015-01-01
This paper discusses a method for performing a sensitivity analysis of parameters used in a simplified fire model for temperature estimates in the upper smoke layer during a fire. The results from the sensitivity analysis can be used when individual parameters affecting fire safety are assessed...... are the most significant in each case. We apply the Sobol method, which is a quantitative method that gives the percentage of the total output variance that each parameter accounts for. The most important parameter is found to be the energy release rate that explains 92% of the uncertainty in the calculated...... results for the period before thermal penetration (tp) has occurred. The analysis is also done for all combinations of two parameters in order to find the combination with the largest effect. The Sobol total for pairs had the highest value for the combination of energy release rate and area of opening...
Sensitivity Analysis in a Complex Marine Ecological Model
Directory of Open Access Journals (Sweden)
Marcos D. Mateus
2015-05-01
Full Text Available Sensitivity analysis (SA has long been recognized as part of best practices to assess if any particular model can be suitable to inform decisions, despite its uncertainties. SA is a commonly used approach for identifying important parameters that dominate model behavior. As such, SA address two elementary questions in the modeling exercise, namely, how sensitive is the model to changes in individual parameter values, and which parameters or associated processes have more influence on the results. In this paper we report on a local SA performed on a complex marine biogeochemical model that simulates oxygen, organic matter and nutrient cycles (N, P and Si in the water column, and well as the dynamics of biological groups such as producers, consumers and decomposers. SA was performed using a “one at a time” parameter perturbation method, and a color-code matrix was developed for result visualization. The outcome of this study was the identification of key parameters influencing model performance, a particularly helpful insight for the subsequent calibration exercise. Also, the color-code matrix methodology proved to be effective for a clear identification of the parameters with most impact on selected variables of the model.
Analysis of Modeling Parameters on Threaded Screws.
Energy Technology Data Exchange (ETDEWEB)
Vigil, Miquela S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brake, Matthew Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vangoethem, Douglas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-06-01
Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation prop- erties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connec- tion. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.
Iterative integral parameter identification of a respiratory mechanics model
Directory of Open Access Journals (Sweden)
Schranz Christoph
2012-07-01
Full Text Available Abstract Background Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual’s model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. Methods An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS patients. Results The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. Conclusion These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.
Sensitivity Analysis of the Land Surface Model NOAH-MP for Different Model Fluxes
Mai, Juliane; Thober, Stephan; Samaniego, Luis; Branch, Oliver; Wulfmeyer, Volker; Clark, Martyn; Attinger, Sabine; Kumar, Rohini; Cuntz, Matthias
2015-04-01
Land Surface Models (LSMs) use a plenitude of process descriptions to represent the carbon, energy and water cycles. They are highly complex and computationally expensive. Practitioners, however, are often only interested in specific outputs of the model such as latent heat or surface runoff. In model applications like parameter estimation, the most important parameters are then chosen by experience or expert knowledge. Hydrologists interested in surface runoff therefore chose mostly soil parameters while biogeochemists interested in carbon fluxes focus on vegetation parameters. However, this might lead to the omission of parameters that are important, for example, through strong interactions with the parameters chosen. It also happens during model development that some process descriptions contain fixed values, which are supposedly unimportant parameters. However, these hidden parameters remain normally undetected although they might be highly relevant during model calibration. Sensitivity analyses are used to identify informative model parameters for a specific model output. Standard methods for sensitivity analysis such as Sobol indexes require large amounts of model evaluations, specifically in case of many model parameters. We hence propose to first use a recently developed inexpensive sequential screening method based on Elementary Effects that has proven to identify the relevant informative parameters. This reduces the number parameters and therefore model evaluations for subsequent analyses such as sensitivity analysis or model calibration. In this study, we quantify parametric sensitivities of the land surface model NOAH-MP that is a state-of-the-art LSM and used at regional scale as the land surface scheme of the atmospheric Weather Research and Forecasting Model (WRF). NOAH-MP contains multiple process parameterizations yielding a considerable amount of parameters (˜ 100). Sensitivities for the three model outputs (a) surface runoff, (b) soil drainage
Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean
Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.
2011-12-01
Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling
Discussion on Failure Sensitive Parameters of an EED Life Performance in Storage
Institute of Scientific and Technical Information of China (English)
YAN Nan; JIANG Min-rong
2005-01-01
An issue to distinguish sensitive parameters of storage life prior to the failure of a bridgewire electro-explosive device (EED) is studied. The degradations of bridgewire resistance, 50% firing current, ignition delay time, bridgewire molten time and powder color with the storage time were measured under a simulating accelerated life test of high-temperature and high-humidity. The most sensitive parameter suitable to evaluate the EED storage life is discussed. It is concluded that the standard deviation of resistance change is the most sensitive degradation variable, and the next is bridgewire molten time, 50% firing current and ignition delay time. The mean of resistance is an insensitive degradation parameter.
Analysis of the sensitivity properties of a model of vector-borne bubonic plague.
Buzby, Megan; Neckels, David; Antolin, Michael F; Estep, Donald
2008-09-06
Model sensitivity is a key to evaluation of mathematical models in ecology and evolution, especially in complex models with numerous parameters. In this paper, we use some recently developed methods for sensitivity analysis to study the parameter sensitivity of a model of vector-borne bubonic plague in a rodent population proposed by Keeling & Gilligan. The new sensitivity tools are based on a variational analysis involving the adjoint equation. The new approach provides a relatively inexpensive way to obtain derivative information about model output with respect to parameters. We use this approach to determine the sensitivity of a quantity of interest (the force of infection from rats and their fleas to humans) to various model parameters, determine a region over which linearization at a specific parameter reference point is valid, develop a global picture of the output surface, and search for maxima and minima in a given region in the parameter space.
Sensitivity analysis in a Lassa fever deterministic mathematical model
Abdullahi, Mohammed Baba; Doko, Umar Chado; Mamuda, Mamman
2015-05-01
Lassa virus that causes the Lassa fever is on the list of potential bio-weapons agents. It was recently imported into Germany, the Netherlands, the United Kingdom and the United States as a consequence of the rapid growth of international traffic. A model with five mutually exclusive compartments related to Lassa fever is presented and the basic reproduction number analyzed. A sensitivity analysis of the deterministic model is performed. This is done in order to determine the relative importance of the model parameters to the disease transmission. The result of the sensitivity analysis shows that the most sensitive parameter is the human immigration, followed by human recovery rate, then person to person contact. This suggests that control strategies should target human immigration, effective drugs for treatment and education to reduced person to person contact.
The Lund Model at Nonzero Impact Parameter
Janik, R A; Janik, Romuald A.; Peschanski, Robi
2003-01-01
We extend the formulation of the longitudinal 1+1 dimensional Lund model to nonzero impact parameter using the minimal area assumption. Complete formulae for the string breaking probability and the momenta of the produced mesons are derived using the string worldsheet Minkowskian helicoid geometry. For strings stretched into the transverse dimension, we find probability distribution with slope linear in m_T similar to the statistical models but without any thermalization assumptions.
IMPROVEMENT OF FLUID PIPE LUMPED PARAMETER MODEL
Institute of Scientific and Technical Information of China (English)
Kong Xiaowu; Wei Jianhua; Qiu Minxiu; Wu Genmao
2004-01-01
The traditional lumped parameter model of fluid pipe is introduced and its drawbacks are pointed out.Furthermore, two suggestions are put forward to remove these drawbacks.Firstly, the structure of equivalent circuit is modified, and then the evaluation of equivalent fluid resistance is change to take the frequency-dependent friction into account.Both simulation and experiment prove that this model is precise to characterize the dynamic behaviors of fluid in pipe.
Nonlinear mathematical modeling and sensitivity analysis of hydraulic drive unit
Kong, Xiangdong; Yu, Bin; Quan, Lingxiao; Ba, Kaixian; Wu, Liujie
2015-09-01
The previous sensitivity analysis researches are not accurate enough and also have the limited reference value, because those mathematical models are relatively simple and the change of the load and the initial displacement changes of the piston are ignored, even experiment verification is not conducted. Therefore, in view of deficiencies above, a nonlinear mathematical model is established in this paper, including dynamic characteristics of servo valve, nonlinear characteristics of pressure-flow, initial displacement of servo cylinder piston and friction nonlinearity. The transfer function block diagram is built for the hydraulic drive unit closed loop position control, as well as the state equations. Through deriving the time-varying coefficient items matrix and time-varying free items matrix of sensitivity equations respectively, the expression of sensitivity equations based on the nonlinear mathematical model are obtained. According to structure parameters of hydraulic drive unit, working parameters, fluid transmission characteristics and measured friction-velocity curves, the simulation analysis of hydraulic drive unit is completed on the MATLAB/Simulink simulation platform with the displacement step 2 mm, 5 mm and 10 mm, respectively. The simulation results indicate that the developed nonlinear mathematical model is sufficient by comparing the characteristic curves of experimental step response and simulation step response under different constant load. Then, the sensitivity function time-history curves of seventeen parameters are obtained, basing on each state vector time-history curve of step response characteristic. The maximum value of displacement variation percentage and the sum of displacement variation absolute values in the sampling time are both taken as sensitivity indexes. The sensitivity indexes values above are calculated and shown visually in histograms under different working conditions, and change rules are analyzed. Then the sensitivity
Consistent Stochastic Modelling of Meteocean Design Parameters
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Sterndorff, M. J.
2000-01-01
Consistent stochastic models of metocean design parameters and their directional dependencies are essential for reliability assessment of offshore structures. In this paper a stochastic model for the annual maximum values of the significant wave height, and the associated wind velocity, current...... velocity, and water level is presented. The stochastic model includes statistical uncertainty and dependency between the four stochastic variables. Further, a new stochastic model for annual maximum directional significant wave heights is presented. The model includes dependency between the maximum wave...... height from neighboring directional sectors. Numerical examples are presented where the models are calibrated using the Maximum Likelihood method to data from the central part of the North Sea. The calibration of the directional distributions is made such that the stochastic model for the omnidirectional...
An Efficient Finite Difference Method for Parameter Sensitivities of Continuous Time Markov Chains
Anderson, David F
2011-01-01
We present an efficient finite difference method for the computation of parameter sensitivities for a wide class of continuous time Markov chains. The motivating class of models, and the source of our examples, are the stochastic chemical kinetic models commonly used in the biosciences, though other natural application areas include population processes and queuing networks. The method is essentially derived by making effective use of the random time change representation of Kurtz, and is no harder to implement than any standard continuous time Markov chain algorithm, such as "Gillespie's algorithm" or the next reaction method. Further, the method is analytically tractable, and, for a given number of realizations of the stochastic process, produces an estimator with substantially lower variance than that obtained using other common methods. Therefore, the computational complexity required to solve a given problem is lowered greatly. In this work, we present the method together with the theoretical analysis de...
Sensitivity analysis on various parameters for lattice analysis of DUPIC fuel with WIMS-AECL code
Energy Technology Data Exchange (ETDEWEB)
Roh, Gyu Hong; Choi, Hang Bok; Park, Jee Won [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)
1997-12-31
The code WIMS-AECL has been used for the lattice analysis of DUPIC fuel. The lattice parameters calculated by the code is sensitive to the choice of number of parameters, such as the number of tracking lines, number of condensed groups, mesh spacing in the moderator region, other parameters vital to the calculation of probabilities and burnup analysis. We have studied this sensitivity with respect to these parameters and recommend their proper values which are necessary for carrying out the lattice analysis of DUPIC fuel.
Sensitivity analysis of the age-structured malaria transmission model
Addawe, Joel M.; Lope, Jose Ernie C.
2012-09-01
We propose an age-structured malaria transmission model and perform sensitivity analyses to determine the relative importance of model parameters to disease transmission. We subdivide the human population into two: preschool humans (below 5 years) and the rest of the human population (above 5 years). We then consider two sets of baseline parameters, one for areas of high transmission and the other for areas of low transmission. We compute the sensitivity indices of the reproductive number and the endemic equilibrium point with respect to the two sets of baseline parameters. Our simulations reveal that in areas of either high or low transmission, the reproductive number is most sensitive to the number of bites by a female mosquito on the rest of the human population. For areas of low transmission, we find that the equilibrium proportion of infectious pre-school humans is most sensitive to the number of bites by a female mosquito. For the rest of the human population it is most sensitive to the rate of acquiring temporary immunity. In areas of high transmission, the equilibrium proportion of infectious pre-school humans and the rest of the human population are both most sensitive to the birth rate of humans. This suggests that strategies that target the mosquito biting rate on pre-school humans and those that shortens the time in acquiring immunity can be successful in preventing the spread of malaria.
Rakovec, O.; Hill, M.C.; Clark, M.P.; Weerts, A.H.; Teuling, A.J.; Uijlenhoet, R.
2014-01-01
1] This paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA
Sensitivity analysis and dynamic modification of modal parameter in mechanical transmission system
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Sensitivity analysis is one of the effective methods in the dynamic modification. The sensitivity of the modal parameters such as the natural frequencies and mode shapes in undamped free vibration of mechanical transmission system is analyzed in this paper.In particular,the sensitivities of the modal parameters to physical parameters of shaft system such as the inertia and stiffness are given.A calculation formula for dynamic modification is presented based on the analysis of modal parameter.With a mechanical transmission system as an example, the sensitivities of natural frequencies and modes shape are calculated and analyzed. Furthermore, the dynamic modification is also carried out and a good result is obtained.
Hou, Zhi-chao; Lao, Yao-xin; Lu, Qiu-hai
2008-11-01
Tensioner is a critical mechanism to ensure a constant tension level within a serpentine belt drive that is widely used in modern passenger vehicles. For a belt drive with n pulleys, generic and explicit formulae about sensitivities of both frequency and steady harmonic responses are established in terms of system matrices with respect to any design parameter of the system. Deductions from the formulae results in frequency and steady response sensitivities relative to key tensioner parameters and the belt speed. Based on sensitivity analysis, optimizations are conducted on tensioner so as to suppress dynamic responses of the system by frequency detuning. A new approach for searching optimal parameters is put forward by incorporating sensitivity information into a classical coordinate alternating procedure. Examples are given to validate the analytical formulae of the frequency sensitivity and to demonstrate the effect of optimization.
Finite element model of needle electrode sensitivity
Høyum, P.; Kalvøy, H.; Martinsen, Ø. G.; Grimnes, S.
2010-04-01
We used the Finite Element (FE) Method to estimate the sensitivity of a needle electrode for bioimpedance measurement. This current conducting needle with insulated shaft was inserted in a saline solution and current was measured at the neutral electrode. FE model resistance and reactance were calculated and successfully compared with measurements on a laboratory model. The sensitivity field was described graphically based on these FE simulations.
Order Parameters of the Dilute A Models
Warnaar, S O; Seaton, K A; Nienhuis, B
1993-01-01
The free energy and local height probabilities of the dilute A models with broken $\\Integer_2$ symmetry are calculated analytically using inversion and corner transfer matrix methods. These models possess four critical branches. The first two branches provide new realisations of the unitary minimal series and the other two branches give a direct product of this series with an Ising model. We identify the integrable perturbations which move the dilute A models away from the critical limit. Generalised order parameters are defined and their critical exponents extracted. The associated conformal weights are found to occur on the diagonal of the relevant Kac table. In an appropriate regime the dilute A$_3$ model lies in the universality class of the Ising model in a magnetic field. In this case we obtain the magnetic exponent $\\delta=15$ directly, without the use of scaling relations.
Testing Linear Models for Ability Parameters in Item Response Models
Glas, Cees A.W.; Hendrawan, Irene
2005-01-01
Methods for testing hypotheses concerning the regression parameters in linear models for the latent person parameters in item response models are presented. Three tests are outlined: A likelihood ratio test, a Lagrange multiplier test and a Wald test. The tests are derived in a marginal maximum like
Energy Technology Data Exchange (ETDEWEB)
Samper, J.; Dewonck, S.; Zheng, L.; Yang, Q.; Naves, A.
2009-10-01
DIR (Diffusion of Inert and Reactive tracers) is an experimental program performed by ANDRA at Bure underground research laboratory in Meuse/Haute Marne (France) to characterize diffusion and retention of radionuclides in Callovo-Oxfordian (C-Ox) argillite. In situ diffusion experiments were performed in vertical boreholes to determine diffusion and retention parameters of selected radionuclides. C-Ox clay exhibits a mild diffusion anisotropy due to stratification. Interpretation of in situ diffusion experiments is complicated by several non-ideal effects caused by the presence of a sintered filter, a gap between the filter and borehole wall and an excavation disturbed zone (EdZ). The relevance of such non-ideal effects and their impact on estimated clay parameters have been evaluated with numerical sensitivity analyses and synthetic experiments having similar parameters and geometric characteristics as real DIR experiments. Normalized dimensionless sensitivities of tracer concentrations at the test interval have been computed numerically. Tracer concentrations are found to be sensitive to all key parameters. Sensitivities are tracer dependent and vary with time. These sensitivities are useful to identify which are the parameters that can be estimated with less uncertainty and find the times at which tracer concentrations begin to be sensitive to each parameter. Synthetic experiments generated with prescribed known parameters have been interpreted automatically with INVERSE-CORE{sup 2D} and used to evaluate the relevance of non-ideal effects and ascertain parameter identifiability in the presence of random measurement errors. Identifiability analysis of synthetic experiments reveals that data noise makes difficult the estimation of clay parameters. Parameters of clay and EdZ cannot be estimated simultaneously from noisy data. Models without an EdZ fail to reproduce synthetic data. Proper interpretation of in situ diffusion experiments requires accounting for filter
Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model
Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Ruget, F.; Gabrielle, B.
2012-12-01
Agro-Land Surface Models (agro-LSM) have been developed from the coupling of specific crop models and large-scale generic vegetation models. They aim at accounting for the spatial distribution and variability of energy, water and carbon fluxes within soil-vegetation-atmosphere continuum with a particular emphasis on how crop phenology and agricultural management practice influence the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty in these models is related to the many parameters included in the models' equations. In this study, we quantify the parameter-based uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS on a multi-regional approach with data from sites in Australia, La Reunion and Brazil. First, the main source of uncertainty for the output variables NPP, GPP, and sensible heat flux (SH) is determined through a screening of the main parameters of the model on a multi-site basis leading to the selection of a subset of most sensitive parameters causing most of the uncertainty. In a second step, a sensitivity analysis is carried out on the parameters selected from the screening analysis at a regional scale. For this, a Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used. First, we quantify the sensitivity of the output variables to individual input parameters on a regional scale for two regions of intensive sugar cane cultivation in Australia and Brazil. Then, we quantify the overall uncertainty in the simulation's outputs propagated from the uncertainty in the input parameters. Seven parameters are identified by the screening procedure as driving most of the uncertainty in the agro-LSM ORCHIDEE-STICS model output at all sites. These parameters control photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), root
Modelling spin Hamiltonian parameters of molecular nanomagnets.
Gupta, Tulika; Rajaraman, Gopalan
2016-07-12
Molecular nanomagnets encompass a wide range of coordination complexes possessing several potential applications. A formidable challenge in realizing these potential applications lies in controlling the magnetic properties of these clusters. Microscopic spin Hamiltonian (SH) parameters describe the magnetic properties of these clusters, and viable ways to control these SH parameters are highly desirable. Computational tools play a proactive role in this area, where SH parameters such as isotropic exchange interaction (J), anisotropic exchange interaction (Jx, Jy, Jz), double exchange interaction (B), zero-field splitting parameters (D, E) and g-tensors can be computed reliably using X-ray structures. In this feature article, we have attempted to provide a holistic view of the modelling of these SH parameters of molecular magnets. The determination of J includes various class of molecules, from di- and polynuclear Mn complexes to the {3d-Gd}, {Gd-Gd} and {Gd-2p} class of complexes. The estimation of anisotropic exchange coupling includes the exchange between an isotropic metal ion and an orbitally degenerate 3d/4d/5d metal ion. The double-exchange section contains some illustrative examples of mixed valance systems, and the section on the estimation of zfs parameters covers some mononuclear transition metal complexes possessing very large axial zfs parameters. The section on the computation of g-anisotropy exclusively covers studies on mononuclear Dy(III) and Er(III) single-ion magnets. The examples depicted in this article clearly illustrate that computational tools not only aid in interpreting and rationalizing the observed magnetic properties but possess the potential to predict new generation MNMs.
Coupled 1D-2D hydrodynamic inundation model for sewer overflow: Influence of modeling parameters
Directory of Open Access Journals (Sweden)
Adeniyi Ganiyu Adeogun
2015-10-01
Full Text Available This paper presents outcome of our investigation on the influence of modeling parameters on 1D-2D hydrodynamic inundation model for sewer overflow, developed through coupling of an existing 1D sewer network model (SWMM and 2D inundation model (BREZO. The 1D-2D hydrodynamic model was developed for the purpose of examining flood incidence due to surcharged water on overland surface. The investigation was carried out by performing sensitivity analysis on the developed model. For the sensitivity analysis, modeling parameters, such as mesh resolution Digital Elevation Model (DEM resolution and roughness were considered. The outcome of the study shows the model is sensitive to changes in these parameters. The performance of the model is significantly influenced, by the Manning's friction value, the DEM resolution and the area of the triangular mesh. Also, changes in the aforementioned modeling parameters influence the Flood characteristics, such as the inundation extent, the flow depth and the velocity across the model domain.
Sensitivity analysis of a sound absorption model with correlated inputs
Chai, W.; Christen, J.-L.; Zine, A.-M.; Ichchou, M.
2017-04-01
Sound absorption in porous media is a complex phenomenon, which is usually addressed with homogenized models, depending on macroscopic parameters. Since these parameters emerge from the structure at microscopic scale, they may be correlated. This paper deals with sensitivity analysis methods of a sound absorption model with correlated inputs. Specifically, the Johnson-Champoux-Allard model (JCA) is chosen as the objective model with correlation effects generated by a secondary micro-macro semi-empirical model. To deal with this case, a relatively new sensitivity analysis method Fourier Amplitude Sensitivity Test with Correlation design (FASTC), based on Iman's transform, is taken into application. This method requires a priori information such as variables' marginal distribution functions and their correlation matrix. The results are compared to the Correlation Ratio Method (CRM) for reference and validation. The distribution of the macroscopic variables arising from the microstructure, as well as their correlation matrix are studied. Finally the results of tests shows that the correlation has a very important impact on the results of sensitivity analysis. Assessment of correlation strength among input variables on the sensitivity analysis is also achieved.
Systematic parameter inference in stochastic mesoscopic modeling
Lei, Huan; Li, Zhen; Karniadakis, George
2016-01-01
We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are sparse. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space....
Sensitivity Analysis of the Optimal Parameter Settings of an LTE Packet Scheduler
Fernandez Diaz, I.; Litjens, R.; Berg, J.L. van den; Dimitrova, D.C.; Spaey, K.
2010-01-01
Advanced packet scheduling schemes in 3G/3G+ mobile networks provide one or more parameters to optimise the trade-off between QoS and resource efficiency. In this paper we study the sensitivity of the optimal parameter setting for packet scheduling in LTE radio networks with respect to various traff
Sensitivity analysis of fine sediment models using heterogeneous data
Kamel, A. M. Yousif; Bhattacharya, B.; El Serafy, G. Y.; van Kessel, T.; Solomatine, D. P.
2012-04-01
Sediments play an important role in many aquatic systems. Their transportation and deposition has significant implication on morphology, navigability and water quality. Understanding the dynamics of sediment transportation in time and space is therefore important in drawing interventions and making management decisions. This research is related to the fine sediment dynamics in the Dutch coastal zone, which is subject to human interference through constructions, fishing, navigation, sand mining, etc. These activities do affect the natural flow of sediments and sometimes lead to environmental concerns or affect the siltation rates in harbours and fairways. Numerical models are widely used in studying fine sediment processes. Accuracy of numerical models depends upon the estimation of model parameters through calibration. Studying the model uncertainty related to these parameters is important in improving the spatio-temporal prediction of suspended particulate matter (SPM) concentrations, and determining the limits of their accuracy. This research deals with the analysis of a 3D numerical model of North Sea covering the Dutch coast using the Delft3D modelling tool (developed at Deltares, The Netherlands). The methodology in this research was divided into three main phases. The first phase focused on analysing the performance of the numerical model in simulating SPM concentrations near the Dutch coast by comparing the model predictions with SPM concentrations estimated from NASA's MODIS sensors at different time scales. The second phase focused on carrying out a sensitivity analysis of model parameters. Four model parameters were identified for the uncertainty and sensitivity analysis: the sedimentation velocity, the critical shear stress above which re-suspension occurs, the shields shear stress for re-suspension pick-up, and the re-suspension pick-up factor. By adopting different values of these parameters the numerical model was run and a comparison between the
Krenn, Julia; Mergili, Martin
2016-04-01
r.randomwalk is a GIS-based, multi-functional conceptual tool for mass movement routing. Starting from one to many release points or release areas, mass points are routed down through the digital elevation model until a defined break criterion is reached. Break criteria are defined by the user and may consist in an angle of reach or a related parameter (empirical-statistical relationships), in the drop of the flow velocity to zero (two-parameter friction model), or in the exceedance of a maximum runup height. Multiple break criteria may be combined. A constrained random walk approach is applied for the routing procedure, where the slope and the perpetuation of the flow direction determine the probability of the flow to move in a certain direction. r.randomwalk is implemented as a raster module of the GRASS GIS software and, as such, is open source. It can be obtained from http://www.mergili.at/randomwalk.html. Besides other innovative functionalities, r.randomwalk serves with built-in functionalities for the derivation of an impact indicator index (III) map with values in the range 0-1. III is derived from multiple model runs with different combinations of input parameters varied in a random or controlled way. It represents the fraction of model runs predicting an impact at a given pixel and is evaluated against the observed impact area through an ROC Plot. The related tool r.ranger facilitates the automated generation and evaluation of many III maps from a variety of sets of parameter combinations. We employ r.randomwalk and r.ranger for parameter optimization and sensitivity analysis. Thereby we do not focus on parameter values, but - accounting for the uncertainty inherent in all parameters - on parameter ranges. In this sense, we demonstrate two strategies for parameter sensitivity analysis and optimization. We avoid to (i) use one-at-a-time parameter testing which would fail to account for interdependencies of the parameters, and (ii) to explore all possible
Influence of task parameters on rotarod performance and sensitivity to ethanol in mice.
Rustay, Nathan R; Wahlsten, Douglas; Crabbe, John C
2003-05-15
Motor performance in mice can be assessed with multiple apparatus and protocols. Use of the rotarod (a.k.a. rotorod, rota-rod, roto-rod, or accelerod) is very common, and it is often used with the apparent assumption by the experimenters that it is a straightforward and simple assay of coordination. The rotarod is sensitive to drugs that affect motor coordination, including ethanol. However, there are few systematic data assessing the range of "normal" performance in mice. There are also few data exploring optimal task parameters (e.g. the influence of different speeds of rotation). In these experiments, we show that both accelerating and fixed-speed rotarod (FSRR) performance vary under different test protocols and conditions, and that moderate to high doses of ethanol disrupt performance. Under certain conditions, low doses of ethanol were found to enhance performance on the accelerating rotarod (ARR). Therefore, it is not possible to characterize individual differences fully using a single set of test parameters. For example, because of the biphasic effect of ethanol on performance, at least two doses of the drug are necessary to explore individual sensitivity differences. We offer recommendations of parameters we believe to be generally suitable for exploring the performance of new genotypes using the rotarod. We suggest that other putative tests of "ataxia" are similarly complex, and that characterizing the contribution of genetic differences will require similar attention to the details of task apparatus and protocols. These data also underscore the need to employ multiple behavioral assays in order to model a complex domain such as "ataxia" or "coordination."
On the Influence of Material Parameters in a Complex Material Model for Powder Compaction
Staf, Hjalmar; Lindskog, Per; Andersson, Daniel C.; Larsson, Per-Lennart
2016-10-01
Parameters in a complex material model for powder compaction, based on a continuum mechanics approach, are evaluated using real insert geometries. The parameter sensitivity with respect to density and stress after compaction, pertinent to a wide range of geometries, is studied in order to investigate completeness and limitations of the material model. Finite element simulations with varied material parameters are used to build surrogate models for the sensitivity study. The conclusion from this analysis is that a simplification of the material model is relevant, especially for simple insert geometries. Parameters linked to anisotropy and the plastic strain evolution angle have a small impact on the final result.
Modelling tourists arrival using time varying parameter
Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.
2017-06-01
The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.
Climate stability and sensitivity in some simple conceptual models
Energy Technology Data Exchange (ETDEWEB)
Bates, J. Ray [University College Dublin, Meteorology and Climate Centre, School of Mathematical Sciences, Dublin (Ireland)
2012-02-15
A theoretical investigation of climate stability and sensitivity is carried out using three simple linearized models based on the top-of-the-atmosphere energy budget. The simplest is the zero-dimensional model (ZDM) commonly used as a conceptual basis for climate sensitivity and feedback studies. The others are two-zone models with tropics and extratropics of equal area; in the first of these (Model A), the dynamical heat transport (DHT) between the zones is implicit, in the second (Model B) it is explicitly parameterized. It is found that the stability and sensitivity properties of the ZDM and Model A are very similar, both depending only on the global-mean radiative response coefficient and the global-mean forcing. The corresponding properties of Model B are more complex, depending asymmetrically on the separate tropical and extratropical values of these quantities, as well as on the DHT coefficient. Adopting Model B as a benchmark, conditions are found under which the validity of the ZDM and Model A as climate sensitivity models holds. It is shown that parameter ranges of physical interest exist for which such validity may not hold. The 2 x CO{sub 2} sensitivities of the simple models are studied and compared. Possible implications of the results for sensitivities derived from GCMs and palaeoclimate data are suggested. Sensitivities for more general scenarios that include negative forcing in the tropics (due to aerosols, inadvertent or geoengineered) are also studied. Some unexpected outcomes are found in this case. These include the possibility of a negative global-mean temperature response to a positive global-mean forcing, and vice versa. (orig.)
Sensitivity-based research prioritization through stochastic characterization modeling
DEFF Research Database (Denmark)
Wender, Ben A.; Prado-Lopez, Valentina; Fantke, Peter
2017-01-01
Product developers using life cycle toxicity characterization models to understand the potential impacts of chemical emissions face serious challenges related to large data demands and high input data uncertainty. This motivates greater focus on model sensitivity toward input parameter variability...... to guide research efforts in data refinement and design of experiments for existing and emerging chemicals alike. This study presents a sensitivity-based approach for estimating toxicity characterization factors given high input data uncertainty and using the results to prioritize data collection according...
Sensitivity analysis of the fission gas behavior model in BISON.
Energy Technology Data Exchange (ETDEWEB)
Swiler, Laura Painton; Pastore, Giovanni; Perez, Danielle; Williamson, Richard
2013-05-01
This report summarizes the result of a NEAMS project focused on sensitivity analysis of a new model for the fission gas behavior (release and swelling) in the BISON fuel performance code of Idaho National Laboratory. Using the new model in BISON, the sensitivity of the calculated fission gas release and swelling to the involved parameters and the associated uncertainties is investigated. The study results in a quantitative assessment of the role of intrinsic uncertainties in the analysis of fission gas behavior in nuclear fuel.
Sensitivity of storage field performance to geologic and cavern design parameters in salt domes.
Energy Technology Data Exchange (ETDEWEB)
Ehgartner, Brian L. (Sandia National Laboratories, Albuquerque, NM); Park, Byoung Yoon
2009-03-01
A sensitivity study was performed utilizing a three dimensional finite element model to assess allowable cavern field sizes for strategic petroleum reserve salt domes. A potential exists for tensile fracturing and dilatancy damage to salt that can compromise the integrity of a cavern field in situations where high extraction ratios exist. The effects of salt creep rate, depth of salt dome top, dome size, caprock thickness, elastic moduli of caprock and surrounding rock, lateral stress ratio of surrounding rock, cavern size, depth of cavern, and number of caverns are examined numerically. As a result, a correlation table between the parameters and the impact on the performance of storage field was established. In general, slower salt creep rates, deeper depth of salt dome top, larger elastic moduli of caprock and surrounding rock, and a smaller radius of cavern are better for structural performance of the salt dome.
Directory of Open Access Journals (Sweden)
Y. Sun
2013-04-01
Full Text Available This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4. Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Two inversion strategies, the deterministic least-square fitting and stochastic Markov-Chain Monte-Carlo (MCMC Bayesian inversion approaches, are evaluated by applying them to CLM4 at selected sites. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the least-square fitting provides little improvements in the model simulations but the sampling-based stochastic inversion approaches are consistent – as more information comes in, the predictive intervals of the calibrated parameters become narrower and the misfits between the calculated and observed responses decrease. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty
Directory of Open Access Journals (Sweden)
Zeng-hui Zhao
2013-01-01
Full Text Available According to the geological characteristics of Xinjiang Ili mine in western area of China, a physical model of interstratified strata composed of soft rock and hard coal seam was established. Selecting the tunnel position, deformation modulus, and strength parameters of each layer as influencing factors, the sensitivity coefficient of roadway deformation to each parameter was firstly analyzed based on a Mohr-Columb strain softening model and nonlinear elastic-plastic finite element analysis. Then the effect laws of influencing factors which showed high sensitivity were further discussed. Finally, a regression model for the relationship between roadway displacements and multifactors was obtained by equivalent linear regression under multiple factors. The results show that the roadway deformation is highly sensitive to the depth of coal seam under the floor which should be considered in the layout of coal roadway; deformation modulus and strength of coal seam and floor have a great influence on the global stability of tunnel; on the contrary, roadway deformation is not sensitive to the mechanical parameters of soft roof; roadway deformation under random combinations of multi-factors can be deduced by the regression model. These conclusions provide theoretical significance to the arrangement and stability maintenance of coal roadway.
Zhao, Zeng-hui; Wang, Wei-ming; Gao, Xin; Yan, Ji-xing
2013-01-01
According to the geological characteristics of Xinjiang Ili mine in western area of China, a physical model of interstratified strata composed of soft rock and hard coal seam was established. Selecting the tunnel position, deformation modulus, and strength parameters of each layer as influencing factors, the sensitivity coefficient of roadway deformation to each parameter was firstly analyzed based on a Mohr-Columb strain softening model and nonlinear elastic-plastic finite element analysis. Then the effect laws of influencing factors which showed high sensitivity were further discussed. Finally, a regression model for the relationship between roadway displacements and multifactors was obtained by equivalent linear regression under multiple factors. The results show that the roadway deformation is highly sensitive to the depth of coal seam under the floor which should be considered in the layout of coal roadway; deformation modulus and strength of coal seam and floor have a great influence on the global stability of tunnel; on the contrary, roadway deformation is not sensitive to the mechanical parameters of soft roof; roadway deformation under random combinations of multi-factors can be deduced by the regression model. These conclusions provide theoretical significance to the arrangement and stability maintenance of coal roadway.
Parameter estimation, model reduction and quantum filtering
Chase, Bradley A.
This thesis explores the topics of parameter estimation and model reduction in the context of quantum filtering. The last is a mathematically rigorous formulation of continuous quantum measurement, in which a stream of auxiliary quantum systems is used to infer the state of a target quantum system. Fundamental quantum uncertainties appear as noise which corrupts the probe observations and therefore must be filtered in order to extract information about the target system. This is analogous to the classical filtering problem in which techniques of inference are used to process noisy observations of a system in order to estimate its state. Given the clear similarities between the two filtering problems, I devote the beginning of this thesis to a review of classical and quantum probability theory, stochastic calculus and filtering. This allows for a mathematically rigorous and technically adroit presentation of the quantum filtering problem and solution. Given this foundation, I next consider the related problem of quantum parameter estimation, in which one seeks to infer the strength of a parameter that drives the evolution of a probe quantum system. By embedding this problem in the state estimation problem solved by the quantum filter, I present the optimal Bayesian estimator for a parameter when given continuous measurements of the probe system to which it couples. For cases when the probe takes on a finite number of values, I review a set of sufficient conditions for asymptotic convergence of the estimator. For a continuous-valued parameter, I present a computational method called quantum particle filtering for practical estimation of the parameter. Using these methods, I then study the particular problem of atomic magnetometry and review an experimental method for potentially reducing the uncertainty in the estimate of the magnetic field beyond the standard quantum limit. The technique involves double-passing a probe laser field through the atomic system, giving
Qiu, Yujun; Lu, Chunsong
2016-09-01
When millimeter-wave cloud radar data are used for the forward iterative retrieval of the liquid water content (LWC) and effective radius of cloud droplets ( R e) in a cloud layer, the prior values and tolerance ranges of the cloud droplet number density ( N t), scale parameter ( R g) and spectral width parameter ( W g) in the iterative algorithm are the main factors that affect the retrieval accuracy. In this study, we used data from stratus and convective clouds that were simultaneously observed by CloudSat and aircraft to conduct a sensitivity analysis of N t, R g, and W g for the retrieval accuracies of LWC and R e in both stratus and convective clouds. N t is the least sensitive parameter for accurately retrieving stratus LWC and R e in both stratus and convective clouds, except for retrieving the convective cloud LWC. Opposite to N t, R g is the most sensitive parameter for both LWC and R e retrievals. As to the effects of parameter tolerance ranges on the retrievals of LWC and R e, the least important parameter is the N t tolerance range; the most important one is the W g tolerance range for retrieving convective cloud LWC and R e, the R g is the important parameter for retrieving stratus LWC and R e. To obtain accurate retrieved values for clouds in a specific region, it is important to use typical values of the sensitive parameters, which could be calculated from in situ observations of cloud droplet size distributions. In addition, the sensitivities of the LWC and R e to the three parameters are stronger in convective clouds than in stratus clouds. This may be related to the melting and merging of solid cloud droplets during the convective mixing process in the convective clouds.
Directory of Open Access Journals (Sweden)
Anne Schützenberger
2016-01-01
Full Text Available The current use of laryngeal high-speed videoendoscopy in clinic settings involves subjective visual assessment of vocal fold vibratory characteristics. However, objective quantification of vocal fold vibrations for evidence-based diagnosis and therapy is desired, and objective parameters assessing laryngeal dynamics have therefore been suggested. This study investigated the sensitivity of the objective parameters and their dependence on recording frame rate. A total of 300 endoscopic high-speed videos with recording frame rates between 1000 and 15 000 fps were analyzed for a vocally healthy female subject during sustained phonation. Twenty parameters, representing laryngeal dynamics, were computed. Four different parameter characteristics were found: parameters showing no change with increasing frame rate; parameters changing up to a certain frame rate, but then remaining constant; parameters remaining constant within a particular range of recording frame rates; and parameters changing with nearly every frame rate. The results suggest that (1 parameter values are influenced by recording frame rates and different parameters have varying sensitivities to recording frame rate; (2 normative values should be determined based on recording frame rates; and (3 the typically used recording frame rate of 4000 fps seems to be too low to distinguish accurately certain characteristics of the human phonation process in detail.
Sensitivities and uncertainties of modeled ground temperatures in mountain environments
Directory of Open Access Journals (Sweden)
S. Gubler
2013-08-01
discretization parameters. We show that the temporal resolution should be at least 1 h to ensure errors less than 0.2 °C in modeled MAGT, and the uppermost ground layer should at most be 20 mm thick. Within the topographic setting, the total parametric output uncertainties expressed as the length of the 95% uncertainty interval of the Monte Carlo simulations range from 0.5 to 1.5 °C for clay and silt, and ranges from 0.5 to around 2.4 °C for peat, sand, gravel and rock. These uncertainties are comparable to the variability of ground surface temperatures measured within 10 m × 10 m grids in Switzerland. The increased uncertainties for sand, peat and gravel are largely due to their sensitivity to the hydraulic conductivity.
Parameter optimization in S-system models
Directory of Open Access Journals (Sweden)
Vasconcelos Ana
2008-04-01
Full Text Available Abstract Background The inverse problem of identifying the topology of biological networks from their time series responses is a cornerstone challenge in systems biology. We tackle this challenge here through the parameterization of S-system models. It was previously shown that parameter identification can be performed as an optimization based on the decoupling of the differential S-system equations, which results in a set of algebraic equations. Results A novel parameterization solution is proposed for the identification of S-system models from time series when no information about the network topology is known. The method is based on eigenvector optimization of a matrix formed from multiple regression equations of the linearized decoupled S-system. Furthermore, the algorithm is extended to the optimization of network topologies with constraints on metabolites and fluxes. These constraints rejoin the system in cases where it had been fragmented by decoupling. We demonstrate with synthetic time series why the algorithm can be expected to converge in most cases. Conclusion A procedure was developed that facilitates automated reverse engineering tasks for biological networks using S-systems. The proposed method of eigenvector optimization constitutes an advancement over S-system parameter identification from time series using a recent method called Alternating Regression. The proposed method overcomes convergence issues encountered in alternate regression by identifying nonlinear constraints that restrict the search space to computationally feasible solutions. Because the parameter identification is still performed for each metabolite separately, the modularity and linear time characteristics of the alternating regression method are preserved. Simulation studies illustrate how the proposed algorithm identifies the correct network topology out of a collection of models which all fit the dynamical time series essentially equally well.
Modeling of Parameters of Subcritical Assembly SAD
Petrochenkov, S; Puzynin, I
2005-01-01
The accepted conceptual design of the experimental Subcritical Assembly in Dubna (SAD) is based on the MOX core with a nominal unit capacity of 25 kW (thermal). This corresponds to the multiplication coefficient $k_{\\rm eff} =0.95$ and accelerator beam power 1 kW. A subcritical assembly driven with the existing 660 MeV proton accelerator at the Joint Institute for Nuclear Research has been modelled in order to make choice of the optimal parameters for the future experiments. The Monte Carlo method was used to simulate neutron spectra, energy deposition and doses calculations. Some of the calculation results are presented in the paper.
Heat and Mass Transfer of Vacuum Cooling for Porous Foods-Parameter Sensitivity Analysis
Directory of Open Access Journals (Sweden)
Zhijun Zhang
2014-01-01
Full Text Available Based on the theory of heat and mass transfer, a coupled model for the porous food vacuum cooling process is constructed. Sensitivity analyses of the process to food density, thermal conductivity, specific heat, latent heat of evaporation, diameter of pores, mass transfer coefficient, viscosity of gas, and porosity were examined. The simulation results show that the food density would affect the vacuum cooling process but not the vacuum cooling end temperature. The surface temperature of food was slightly affected and the core temperature is not affected by the changed thermal conductivity. The core temperature and surface temperature are affected by the changed specific heat. The core temperature and surface temperature are affected by the changed latent heat of evaporation. The core temperature is affected by the diameter of pores. But the surface temperature is not affected obviously. The core temperature and surface temperature are not affected by the changed gas viscosity. The parameter sensitivity of mass transfer coefficient is obvious. The core temperature and surface temperature are affected by the changed mass transfer coefficient. In all the simulations, the end temperature of core and surface is not affected. The vacuum cooling process of porous medium is a process controlled by outside process.
Model Driven Development of Data Sensitive Systems
DEFF Research Database (Denmark)
Olsen, Petur
2014-01-01
Model-driven development strives to use formal artifacts during the development process. Formal artifacts enables automatic analyses of some aspects of the system under development. This serves to increase the understanding of the (intended) behavior of the system as well as increasing error...... detection and pushing error detection to earlier stages of development. The complexity of modeling and the size of systems which can be analyzed is severely limited when introducing data variables. The state space grows exponentially in the number of variable and the domain size of the variables...... to the values of variables. This theses strives to improve model-driven development of such data-sensitive systems. This is done by addressing three research questions. In the first we combine state-based modeling and abstract interpretation, in order to ease modeling of data-sensitive systems, while allowing...
Accelerated gravitational wave parameter estimation with reduced order modeling.
Canizares, Priscilla; Field, Scott E; Gair, Jonathan; Raymond, Vivien; Smith, Rory; Tiglio, Manuel
2015-02-20
Inferring the astrophysical parameters of coalescing compact binaries is a key science goal of the upcoming advanced LIGO-Virgo gravitational-wave detector network and, more generally, gravitational-wave astronomy. However, current approaches to parameter estimation for these detectors require computationally expensive algorithms. Therefore, there is a pressing need for new, fast, and accurate Bayesian inference techniques. In this Letter, we demonstrate that a reduced order modeling approach enables rapid parameter estimation to be performed. By implementing a reduced order quadrature scheme within the LIGO Algorithm Library, we show that Bayesian inference on the 9-dimensional parameter space of nonspinning binary neutron star inspirals can be sped up by a factor of ∼30 for the early advanced detectors' configurations (with sensitivities down to around 40 Hz) and ∼70 for sensitivities down to around 20 Hz. This speedup will increase to about 150 as the detectors improve their low-frequency limit to 10 Hz, reducing to hours analyses which could otherwise take months to complete. Although these results focus on interferometric gravitational wave detectors, the techniques are broadly applicable to any experiment where fast Bayesian analysis is desirable.
Energy Technology Data Exchange (ETDEWEB)
Rottlaender, Iris
2008-08-15
An evaluation of the discovery potential for NMSSM Higgs bosons of the ATLAS experiment at the LHC is presented. For this purpose, seven two-dimensional benchmark planes in the six-dimensional parameter space of the NMSSM Higgs sector are defined. These planes include different types of phenomenology for which the discovery of NMSSM Higgs bosons is especially challenging and which are considered typical for the NMSSM. They are subsequently used to give a detailed evaluation of the Higgs boson discovery potential based on Monte Carlo studies from the ATLAS collaboration. Afterwards, the possibility of discovering NMSSM Higgs bosons via the H{sub 1}{yields}A{sub 1}A{sub 1}{yields}4{tau}{yields}4{mu}+8{nu} decay chain and with the vector boson fusion production mode is investigated. A particular emphasis is put on the mass reconstruction from the complex final state. Furthermore, a study of the jet reconstruction performance at the ATLAS experiment which is of crucial relevance for vector boson fusion searches is presented. A good detectability of the so-called tagging jets that originate from the scattered partons in the vector boson fusion process is of critical importance for an early Higgs boson discovery in many models and also within the framework of the NMSSM. (orig.)
Baker Syed; Poskar C; Junker Björn
2011-01-01
Abstract In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. Wh...
Performance Model and Sensitivity Analysis for a Solar Thermoelectric Generator
Rehman, Naveed Ur; Siddiqui, Mubashir Ali
2017-01-01
In this paper, a regression model for evaluating the performance of solar concentrated thermoelectric generators (SCTEGs) is established and the significance of contributing parameters is discussed in detail. The model is based on several natural, design and operational parameters of the system, including the thermoelectric generator (TEG) module and its intrinsic material properties, the connected electrical load, concentrator attributes, heat transfer coefficients, solar flux, and ambient temperature. The model is developed by fitting a response curve, using the least-squares method, to the results. The sample points for the model were obtained by simulating a thermodynamic model, also developed in this paper, over a range of values of input variables. These samples were generated employing the Latin hypercube sampling (LHS) technique using a realistic distribution of parameters. The coefficient of determination was found to be 99.2%. The proposed model is validated by comparing the predicted results with those in the published literature. In addition, based on the elasticity for parameters in the model, sensitivity analysis was performed and the effects of parameters on the performance of SCTEGs are discussed in detail. This research will contribute to the design and performance evaluation of any SCTEG system for a variety of applications.
Performance Model and Sensitivity Analysis for a Solar Thermoelectric Generator
Rehman, Naveed Ur; Siddiqui, Mubashir Ali
2017-03-01
In this paper, a regression model for evaluating the performance of solar concentrated thermoelectric generators (SCTEGs) is established and the significance of contributing parameters is discussed in detail. The model is based on several natural, design and operational parameters of the system, including the thermoelectric generator (TEG) module and its intrinsic material properties, the connected electrical load, concentrator attributes, heat transfer coefficients, solar flux, and ambient temperature. The model is developed by fitting a response curve, using the least-squares method, to the results. The sample points for the model were obtained by simulating a thermodynamic model, also developed in this paper, over a range of values of input variables. These samples were generated employing the Latin hypercube sampling (LHS) technique using a realistic distribution of parameters. The coefficient of determination was found to be 99.2%. The proposed model is validated by comparing the predicted results with those in the published literature. In addition, based on the elasticity for parameters in the model, sensitivity analysis was performed and the effects of parameters on the performance of SCTEGs are discussed in detail. This research will contribute to the design and performance evaluation of any SCTEG system for a variety of applications.
Wang, Xuan; Tandeo, Pierre; Fablet, Ronan; Husson, Romain; Guan, Lei; Chen, Ge
2016-01-01
The swell propagation model built on geometric optics is known to work well when simulating radiated swells from a far located storm. Based on this simple approximation, satellites have acquired plenty of large samples on basin-traversing swells induced by fierce storms situated in mid-latitudes. How to routinely reconstruct swell fields with these irregularly sampled observations from space via known swell propagation principle requires more examination. In this study, we apply 3-h interval pseudo SAR observations in the ensemble Kalman filter (EnKF) to reconstruct a swell field in ocean basin, and compare it with buoy swell partitions and polynomial regression results. As validated against in situ measurements, EnKF works well in terms of spatial–temporal consistency in far-field swell propagation scenarios. Using this framework, we further address the influence of EnKF parameters, and perform a sensitivity analysis to evaluate estimations made under different sets of parameters. Such analysis is of key interest with respect to future multiple-source routinely recorded swell field data. Satellite-derived swell data can serve as a valuable complementary dataset to in situ or wave re-analysis datasets. PMID:27898005
Wang, Xuan; Tandeo, Pierre; Fablet, Ronan; Husson, Romain; Guan, Lei; Chen, Ge
2016-11-25
The swell propagation model built on geometric optics is known to work well when simulating radiated swells from a far located storm. Based on this simple approximation, satellites have acquired plenty of large samples on basin-traversing swells induced by fierce storms situated in mid-latitudes. How to routinely reconstruct swell fields with these irregularly sampled observations from space via known swell propagation principle requires more examination. In this study, we apply 3-h interval pseudo SAR observations in the ensemble Kalman filter (EnKF) to reconstruct a swell field in ocean basin, and compare it with buoy swell partitions and polynomial regression results. As validated against in situ measurements, EnKF works well in terms of spatial-temporal consistency in far-field swell propagation scenarios. Using this framework, we further address the influence of EnKF parameters, and perform a sensitivity analysis to evaluate estimations made under different sets of parameters. Such analysis is of key interest with respect to future multiple-source routinely recorded swell field data. Satellite-derived swell data can serve as a valuable complementary dataset to in situ or wave re-analysis datasets.
Sensitivity analysis of distributed parameter elements In high-speed circuit networks
Institute of Scientific and Technical Information of China (English)
Lei DOU; Zhiquan WANG
2007-01-01
This paper presents an analysis method,based on MacCormack's technique,for the evaluation of the time domain sensitivity of distributed parameter elements in high-speed circuit networks.Sensitivities can be calculated from electrical and physical parameters of the distributed parameter elements.The proposed method is a direct numerical method of time-space discretization and does not require complicated mathematical deductive process.Therefore,it is very convenient to program this method.It can be applied to sensitivity analysis of general transmission lines in linear or nonlinear circuit networks.The proposed method is second-order-accurate.Numerical experiment is presented to demonstrate its accuracy and efficiency.
Tracer SWIW tests in propped and un-propped fractures: parameter sensitivity issues, revisited
Ghergut, Julia; Behrens, Horst; Sauter, Martin
2017-04-01
Single-well injection-withdrawal (SWIW) or 'push-then-pull' tracer methods appear attractive for a number of reasons: less uncertainty on design and dimensioning, and lower tracer quantities required than for inter-well tests; stronger tracer signals, enabling easier and cheaper metering, and shorter metering duration required, reaching higher tracer mass recovery than in inter-well tests; last not least: no need for a second well. However, SWIW tracer signal inversion faces a major issue: the 'push-then-pull' design weakens the correlation between tracer residence times and georeservoir transport parameters, inducing insensitivity or ambiguity of tracer signal inversion w. r. to some of those georeservoir parameters that are supposed to be the target of tracer tests par excellence: pore velocity, transport-effective porosity, fracture or fissure aperture and spacing or density (where applicable), fluid/solid or fluid/fluid phase interface density. Hydraulic methods cannot measure the transport-effective values of such parameters, because pressure signals correlate neither with fluid motion, nor with material fluxes through (fluid-rock, or fluid-fluid) phase interfaces. The notorious ambiguity impeding parameter inversion from SWIW test signals has nourished several 'modeling attitudes': (i) regard dispersion as the key process encompassing whatever superposition of underlying transport phenomena, and seek a statistical description of flow-path collectives enabling to characterize dispersion independently of any other transport parameter, as proposed by Gouze et al. (2008), with Hansen et al. (2016) offering a comprehensive analysis of the various ways dispersion model assumptions interfere with parameter inversion from SWIW tests; (ii) regard diffusion as the key process, and seek for a large-time, asymptotically advection-independent regime in the measured tracer signals (Haggerty et al. 2001), enabling a dispersion-independent characterization of multiple
Moose models with vanishing $S$ parameter
Casalbuoni, R; Dominici, Daniele
2004-01-01
In the linear moose framework, which naturally emerges in deconstruction models, we show that there is a unique solution for the vanishing of the $S$ parameter at the lowest order in the weak interactions. We consider an effective gauge theory based on $K$ SU(2) gauge groups, $K+1$ chiral fields and electroweak groups $SU(2)_L$ and $U(1)_Y$ at the ends of the chain of the moose. $S$ vanishes when a link in the moose chain is cut. As a consequence one has to introduce a dynamical non local field connecting the two ends of the moose. Then the model acquires an additional custodial symmetry which protects this result. We examine also the possibility of a strong suppression of $S$ through an exponential behavior of the link couplings as suggested by Randall Sundrum metric.
Model parameters for simulation of physiological lipids
McGlinchey, Nicholas
2016-01-01
Coarse grain simulation of proteins in their physiological membrane environment can offer insight across timescales, but requires a comprehensive force field. Parameters are explored for multicomponent bilayers composed of unsaturated lipids DOPC and DOPE, mixed‐chain saturation POPC and POPE, and anionic lipids found in bacteria: POPG and cardiolipin. A nonbond representation obtained from multiscale force matching is adapted for these lipids and combined with an improved bonding description of cholesterol. Equilibrating the area per lipid yields robust bilayer simulations and properties for common lipid mixtures with the exception of pure DOPE, which has a known tendency to form nonlamellar phase. The models maintain consistency with an existing lipid–protein interaction model, making the force field of general utility for studying membrane proteins in physiologically representative bilayers. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. PMID:26864972
Energy Technology Data Exchange (ETDEWEB)
Lin, Guangxing [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Wan, Hui [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Zhang, Kai [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Qian, Yun [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Ghan, Steven J. [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA
2016-07-10
Efficient simulation strategies are crucial for the development and evaluation of high resolution climate models. This paper evaluates simulations with constrained meteorology for the quantification of parametric sensitivities in the Community Atmosphere Model version 5 (CAM5). Two parameters are perturbed as illustrating examples: the convection relaxation time scale (TAU), and the threshold relative humidity for the formation of low-level stratiform clouds (rhminl). Results suggest that the fidelity and computational efficiency of the constrained simulations depend strongly on 3 factors: the detailed implementation of nudging, the mechanism through which the perturbed parameter affects precipitation and cloud, and the magnitude of the parameter perturbation. In the case of a strong perturbation in convection, temperature and/or wind nudging with a 6-hour relaxation time scale leads to non-negligible side effects due to the distorted interactions between resolved dynamics and parameterized convection, while a 1-year free running simulation can satisfactorily capture the annual mean precipitation sensitivity in terms of both global average and geographical distribution. In the case of a relatively weak perturbation the large-scale condensation scheme, results from 1-year free-running simulations are strongly affected by noise associated with internal variability, while nudging winds effectively reduces the noise, and reasonably reproduces the response of precipitation and cloud forcing to parameter perturbation. These results indicate that caution is needed when using nudged simulations to assess precipitation and cloud forcing sensitivities to parameter changes in general circulation models. We also demonstrate that ensembles of short simulations are useful for understanding the evolution of model sensitivities.
Parameter and Process Significance in Mechanistic Modeling of Cellulose Hydrolysis
Rotter, B.; Barry, A.; Gerhard, J.; Small, J.; Tahar, B.
2005-12-01
The rate of cellulose hydrolysis, and of associated microbial processes, is important in determining the stability of landfills and their potential impact on the environment, as well as associated time scales. To permit further exploration in this field, a process-based model of cellulose hydrolysis was developed. The model, which is relevant to both landfill and anaerobic digesters, includes a novel approach to biomass transfer between a cellulose-bound biofilm and biomass in the surrounding liquid. Model results highlight the significance of the bacterial colonization of cellulose particles by attachment through contact in solution. Simulations revealed that enhanced colonization, and therefore cellulose degradation, was associated with reduced cellulose particle size, higher biomass populations in solution, and increased cellulose-binding ability of the biomass. A sensitivity analysis of the system parameters revealed different sensitivities to model parameters for a typical landfill scenario versus that for an anaerobic digester. The results indicate that relative surface area of cellulose and proximity of hydrolyzing bacteria are key factors determining the cellulose degradation rate.
Geometrical parameter analysis of the high sensitivity fiber optic angular displacement sensor
Sakamoto, João M S; Kitano, Cláudio; Tittmann, Bernhard R
2015-01-01
In this work, we present an analysis of the influence of the geometrical parameters on the sensitivity and linear range of the fiber optic angular displacement sensor, through computational simulations and experiments. The geometrical parameters analyzed were the lens focal length, the gap between fibers, the fibers cladding radii, the emitting fiber critical angle (or, equivalently, the emitting fiber numerical aperture), and the standoff distance (distance between the lens and the reflective surface). Besides, we analyzed the sensor sensitivity regarding any spurious linear displacement. The simulation and experimental results showed that the parameters which play the most important roles are the emitting fiber core radius, the lens focal length, and the light coupling efficiency, while the remaining parameters have little influence on sensor characteristics. This paper was published in Applied Optics and is made available as an electronic reprint with the permission of OSA. The paper can be found at the fo...
Applying incentive sensitization models to behavioral addiction
DEFF Research Database (Denmark)
Rømer Thomsen, Kristine; Fjorback, Lone; Møller, Arne
2014-01-01
The incentive sensitization theory is a promising model for understanding the mechanisms underlying drug addiction, and has received support in animal and human studies. So far the theory has not been applied to the case of behavioral addictions like Gambling Disorder, despite sharing clinical...
A Workflow for Global Sensitivity Analysis of PBPK Models
Directory of Open Access Journals (Sweden)
Kevin eMcNally
2011-06-01
Full Text Available Physiologically based pharmacokinetic models have a potentially significant role in the development of a reliable predictive toxicity testing strategy. The structure of PBPK models are ideal frameworks into which disparate in vitro and in vivo data can be integrated and utilised to translate information generated, using alternative to animal measures of toxicity and human biological monitoring data, into plausible corresponding exposures. However, these models invariably include the description of well known non-linear biological processes such as, enzyme saturation and interactions between parameters such as, organ mass and body mass. Therefore, an appropriate sensitivity analysis technique is required which can quantify the influences associated with individual parameters, interactions between parameters and any non-linear processes. In this report we have defined a workflow for sensitivity analysis of PBPK models that is computationally feasible, accounts for interactions between parameters, and can be displayed in the form of a bar chart and cumulative sum line (Lowry plot, which we believe is intuitive and appropriate for toxicologists, risk assessors and regulators.
Anne Schützenberger; Melda Kunduk; Michael Döllinger; Christoph Alexiou; Denis Dubrovskiy; Marion Semmler; Anja Seger; Christopher Bohr
2016-01-01
The current use of laryngeal high-speed videoendoscopy in clinic settings involves subjective visual assessment of vocal fold vibratory characteristics. However, objective quantification of vocal fold vibrations for evidence-based diagnosis and therapy is desired, and objective parameters assessing laryngeal dynamics have therefore been suggested. This study investigated the sensitivity of the objective parameters and their dependence on recording frame rate. A total of 300 endoscopic high-sp...
Institute of Scientific and Technical Information of China (English)
ZENG Guo; LAI Xin-min; YU Zhong-qi; LIN Zhong-qin
2009-01-01
Cold roll forming is a high production but complex metal forming process under the conditions of coupled effects with multi-factor.A new booting finite element method (FEM) model using the updated Lagrangian (UL) method for multistand roll forming process is developed and validated.Compared with most of the literatures related to roll forming simulation,the new model can take the roll rotation into account and is well suited for simulating multistand roll forming.Based on the model,the process of a channel section with outer edge formed with twelve passes is simulated and the sensitivity analysis of parameters is conducted with orthogonal design combined FEM model.It is found that the multiatand roll forming process can he efficiently analyzed by the new booting model,and sensitivity analysis shows that the yield strength plays an important role in controlling the quality of the products.
Li, Xin; Cai, Yu; Moloney, Brendan; Chen, Yiyi; Huang, Wei; Woods, Mark; Coakley, Fergus V; Rooney, William D; Garzotto, Mark G; Springer, Charles S
2016-08-01
Dynamic-Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has been used widely for clinical applications. Pharmacokinetic modeling of DCE-MRI data that extracts quantitative contrast reagent/tissue-specific model parameters is the most investigated method. One of the primary challenges in pharmacokinetic analysis of DCE-MRI data is accurate and reliable measurement of the arterial input function (AIF), which is the driving force behind all pharmacokinetics. Because of effects such as inflow and partial volume averaging, AIF measured from individual arteries sometimes require amplitude scaling for better representation of the blood contrast reagent (CR) concentration time-courses. Empirical approaches like blinded AIF estimation or reference tissue AIF derivation can be useful and practical, especially when there is no clearly visible blood vessel within the imaging field-of-view (FOV). Similarly, these approaches generally also require magnitude scaling of the derived AIF time-courses. Since the AIF varies among individuals even with the same CR injection protocol and the perfect scaling factor for reconstructing the ground truth AIF often remains unknown, variations in estimated pharmacokinetic parameters due to varying AIF scaling factors are of special interest. In this work, using simulated and real prostate cancer DCE-MRI data, we examined parameter variations associated with AIF scaling. Our results show that, for both the fast-exchange-limit (FXL) Tofts model and the water exchange sensitized fast-exchange-regime (FXR) model, the commonly fitted CR transfer constant (K(trans)) and the extravascular, extracellular volume fraction (ve) scale nearly proportionally with the AIF, whereas the FXR-specific unidirectional cellular water efflux rate constant, kio, and the CR intravasation rate constant, kep, are both AIF scaling insensitive. This indicates that, for DCE-MRI of prostate cancer and possibly other cancers, kio and kep may be more suitable imaging
Li, Xin; Cai, Yu; Moloney, Brendan; Chen, Yiyi; Huang, Wei; Woods, Mark; Coakley, Fergus V.; Rooney, William D.; Garzotto, Mark G.; Springer, Charles S.
2016-08-01
Dynamic-Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has been used widely for clinical applications. Pharmacokinetic modeling of DCE-MRI data that extracts quantitative contrast reagent/tissue-specific model parameters is the most investigated method. One of the primary challenges in pharmacokinetic analysis of DCE-MRI data is accurate and reliable measurement of the arterial input function (AIF), which is the driving force behind all pharmacokinetics. Because of effects such as inflow and partial volume averaging, AIF measured from individual arteries sometimes require amplitude scaling for better representation of the blood contrast reagent (CR) concentration time-courses. Empirical approaches like blinded AIF estimation or reference tissue AIF derivation can be useful and practical, especially when there is no clearly visible blood vessel within the imaging field-of-view (FOV). Similarly, these approaches generally also require magnitude scaling of the derived AIF time-courses. Since the AIF varies among individuals even with the same CR injection protocol and the perfect scaling factor for reconstructing the ground truth AIF often remains unknown, variations in estimated pharmacokinetic parameters due to varying AIF scaling factors are of special interest. In this work, using simulated and real prostate cancer DCE-MRI data, we examined parameter variations associated with AIF scaling. Our results show that, for both the fast-exchange-limit (FXL) Tofts model and the water exchange sensitized fast-exchange-regime (FXR) model, the commonly fitted CR transfer constant (Ktrans) and the extravascular, extracellular volume fraction (ve) scale nearly proportionally with the AIF, whereas the FXR-specific unidirectional cellular water efflux rate constant, kio, and the CR intravasation rate constant, kep, are both AIF scaling insensitive. This indicates that, for DCE-MRI of prostate cancer and possibly other cancers, kio and kep may be more suitable imaging
Shape sensitivity analysis in numerical modelling of solidification
Directory of Open Access Journals (Sweden)
E. Majchrzak
2007-12-01
Full Text Available The methods of sensitivity analysis constitute a very effective tool on the stage of numerical modelling of casting solidification. It is possible, among others, to rebuilt the basic numerical solution on the solution concerning the others disturbed values of physical and geometrical parameters of the process. In this paper the problem of shape sensitivity analysis is discussed. The non-homogeneous casting-mould domain is considered and the perturbation of the solidification process due to the changes of geometrical dimensions is analyzed. From the mathematical point of view the sensitivity model is rather complex but its solution gives the interesting information concerning the mutual connections between the kinetics of casting solidification and its basic dimensions. In the final part of the paper the example of computations is shown. On the stage of numerical realization the finite difference method has been applied.
Sensitivity analysis in the WWTP modelling community – new opportunities and applications
DEFF Research Database (Denmark)
Sin, Gürkan; Ruano, M.V.; Neumann, Marc B.
2010-01-01
A mainstream viewpoint on sensitivity analysis in the wastewater modelling community is that it is a first-order differential analysis of outputs with respect to the parameters – typically obtained by perturbing one parameter at a time with a small factor. An alternative viewpoint on sensitivity ...
Uncertainty and Sensitivity in Surface Dynamics Modeling
Kettner, Albert J.; Syvitski, James P. M.
2016-05-01
Papers for this special issue on 'Uncertainty and Sensitivity in Surface Dynamics Modeling' heralds from papers submitted after the 2014 annual meeting of the Community Surface Dynamics Modeling System or CSDMS. CSDMS facilitates a diverse community of experts (now in 68 countries) that collectively investigate the Earth's surface-the dynamic interface between lithosphere, hydrosphere, cryosphere, and atmosphere, by promoting, developing, supporting and disseminating integrated open source software modules. By organizing more than 1500 researchers, CSDMS has the privilege of identifying community strengths and weaknesses in the practice of software development. We recognize, for example, that progress has been slow on identifying and quantifying uncertainty and sensitivity in numerical modeling of earth's surface dynamics. This special issue is meant to raise awareness for these important subjects and highlight state-of-the-art progress.
Sensitivity analysis of DSMC parameters for an 11-species air hypersonic flow
Higdon, Kyle J.; Goldstein, David B.; Varghese, Philip L.
2016-11-01
This research investigates the influence of input parameters in the direct simulation Monte Carlo (DSMC) method for the simulation of a hypersonic flow scenario. Simulations are performed using the Computation of Hypersonic Ionizing Particles in Shocks (CHIPS) code to reproduce NASA Ames Electric Arc Shock Tube (EAST) experimental results for a 10.26 km/s, 0.2 Torr scenario. Since the chosen nominal simulation involves an energetic flow, an electronic excitation model is introduced into CHIPS to complement the pre-existing 11-species air models. A global Monte Carlo sensitivity analysis was completed for this chosen scenario and three quantities of interest (QoIs) were investigated: translational temperature, electronic temperature, and electron number density. The electron impact ionization reaction, N + e- ⇌ N+ + e- + e-, was determined to have the greatest effect on all three QoIs as it defines the electron cascade that occurs post-shock. In addition, molecular nitrogen dissociation, associative ionization, and the N + NO+ ⇌ N+ + NO charge exchange reaction were all found to be important for these QoIs.
Uncertainty Quantification for Optical Model Parameters
Lovell, A E; Sarich, J; Wild, S M
2016-01-01
Although uncertainty quantification has been making its way into nuclear theory, these methods have yet to be explored in the context of reaction theory. For example, it is well known that different parameterizations of the optical potential can result in different cross sections, but these differences have not been systematically studied and quantified. The purpose of this work is to investigate the uncertainties in nuclear reactions that result from fitting a given model to elastic-scattering data, as well as to study how these uncertainties propagate to the inelastic and transfer channels. We use statistical methods to determine a best fit and create corresponding 95\\% confidence bands. A simple model of the process is fit to elastic-scattering data and used to predict either inelastic or transfer cross sections. In this initial work, we assume that our model is correct, and the only uncertainties come from the variation of the fit parameters. We study a number of reactions involving neutron and deuteron p...
Numerical modeling of partial discharges parameters
Directory of Open Access Journals (Sweden)
Kartalović Nenad M.
2016-01-01
Full Text Available In recent testing of the partial discharges or the use for the diagnosis of insulation condition of high voltage generators, transformers, cables and high voltage equipment develops rapidly. It is a result of the development of electronics, as well as, the development of knowledge about the processes of partial discharges. The aim of this paper is to contribute the better understanding of this phenomenon of partial discharges by consideration of the relevant physical processes in isolation materials and isolation systems. Prebreakdown considers specific processes, and development processes at the local level and their impact on specific isolation material. This approach to the phenomenon of partial discharges needed to allow better take into account relevant discharge parameters as well as better numerical model of partial discharges.
Sensitivity analysis of large system of chemical kinetic parameters for engine combustion simulation
Energy Technology Data Exchange (ETDEWEB)
Hsieh, H; Sanz-Argent, J; Petitpas, G; Havstad, M; Flowers, D
2012-04-19
In this study, the authors applied the state-of-the art sensitivity methods to downselect system parameters from 4000+ to 8, (23000+ -> 4000+ -> 84 -> 8). This analysis procedure paves the way for future works: (1) calibrate the system response using existed experimental observations, and (2) predict future experiment results, using the calibrated system.
DEFF Research Database (Denmark)
Pingen, Georg; Evgrafov, Anton; Maute, Kurt
2009-01-01
We present an adjoint parameter sensitivity analysis formulation and solution strategy for the lattice Boltzmann method (LBM). The focus is on design optimization applications, in particular topology optimization. The lattice Boltzmann method is briefly described with an in-depth discussion...
Stubberud, Marlene Waege; Myhre, Ane Marlene; Holand, Håkon; Kvalnes, Thomas; Ringsby, Thor Harald; Saether, Bernt-Erik; Jensen, Henrik
2017-02-16
The ratio between the effective and the census population size, Ne/N, is an important measure of the long-term viability and sustainability of a population. Understanding which demographic processes that affect Ne/N most will improve our understanding of how genetic drift and the probability of fixation of alleles is affected by demography. This knowledge may also be of vital importance in management of endangered populations and species. Here, we use data from 13 natural populations of house sparrow (Passer domesticus) in Norway to calculate the demographic parameters that determine Ne/N. Using the global variance-based Sobol' method for the sensitivity analyses, we found that Ne/N was most sensitive to demographic variance, especially among older individuals. Furthermore, the individual reproductive values (that determine the demographic variance) were most sensitive to variation in fecundity. Our results draw attention to the applicability of sensitivity analyses in population management and conservation. For population management aiming to reduce the loss of genetic variation, a sensitivity analysis may indicate the demographic parameters towards which resources should be focused. The result of such an analysis may depend on the life history and mating system of the population or species under consideration, because the vital rates and sex-age classes that Ne/N is most sensitive to may change accordingly.
Gu, Yueqing; Bourke, Vincent; Kim, Jae Gwan; Xia, Mengna; Constantinescu, Anca; Mason, Ralph P.; Liu, Hanli
2003-07-01
Three oxygen-sensitive parameters (arterial hemoglobin oxygen saturation SaO2, tumor vascular oxygenated hemoglobin concentration [HbO2], and tumor oxygen tension pO2) were measured simultaneously by three different optical techniques (pulse oximeter, near infrared spectroscopy, and FOXY) to evaluate dynamic responses of breast tumors to carbogen (5% CO2 and 95% O2) intervention. All three parameters displayed similar trends in dynamic response to carbogen challenge, but with different response times. These response times were quantified by the time constants of the exponential fitting curves, revealing the immediate and the fastest response from the arterial SaO2, followed by changes in global tumor vascular [HbO2], and delayed responses for pO2. The consistency of the three oxygen-sensitive parameters demonstrated the ability of NIRS to monitor therapeutic interventions for rat breast tumors in-vivo in real time.
Sensitivity analysis of dimensionless parameters for physical simulation of water-flooding reservoir
Institute of Scientific and Technical Information of China (English)
BAI Yuhu; LI Jiachun; ZHOU Jifu
2005-01-01
A numerical approach to optimize dimensionless parameters of water-flooding porous media flows is proposed based on the analysis of the sensitivity factor defined as the variation ration of a target function with respect to the variation of dimensionless parameters. A complete set of scaling criteria for water-flooding reservoir of five-spot well pattern case is derived from the 3-D governing equations, involving the gravitational force,the capillary force and the compressibility of water, oil and rock. By using this approach,we have estimated the influences of each dimensionless parameter on experimental results, and thus sorting out the dominant ones with larger sensitivity factors ranging from 10-4 to 100.
Sensitivities and uncertainties of modeled ground temperatures in mountain environments
Directory of Open Access Journals (Sweden)
S. Gubler
2013-02-01
Full Text Available Before operational use or for decision making, models must be validated, and the degree of trust in model outputs should be quantified. Often, model validation is performed at single locations due to the lack of spatially-distributed data. Since the analysis of parametric model uncertainties can be performed independently of observations, it is a suitable method to test the influence of environmental variability on model evaluation. In this study, the sensitivities and uncertainty of a physically-based mountain permafrost model are quantified within an artificial topography consisting of different elevations and exposures combined with six ground types characterized by their hydraulic properties. The analyses performed for all combinations of topographic factors and ground types allowed to quantify the variability of model sensitivity and uncertainty within mountain regions. We found that modeled snow duration considerably influences the mean annual ground temperature (MAGT. The melt-out day of snow (MD is determined by processes determining snow accumulation and melting. Parameters such as the temperature and precipitation lapse rate and the snow correction factor have therefore a great impact on modeled MAGT. Ground albedo changes MAGT from 0.5 to 4°C in dependence of the elevation, the aspect and the ground type. South-exposed inclined locations are more sensitive to changes in ground albedo than north-exposed slopes since they receive more solar radiation. The sensitivity to ground albedo increases with decreasing elevation due to shorter snow cover. Snow albedo and other parameters determining the amount of reflected solar radiation are important, changing MAGT at different depths by more than 1°C. Parameters influencing the turbulent fluxes as the roughness length or the dew temperature are more sensitive at low elevation sites due to higher air temperatures and decreased solar radiation. Modeling the individual terms of the energy
DEFF Research Database (Denmark)
Ottosen, Thor Bjørn; Ketzel, Matthias; Skov, Henrik
2016-01-01
Pollution Model (OSPM®). To assess the predictive validity of the model, the data is split into an estimation and a prediction data set using two data splitting approaches and data preparation techniques (clustering and outlier detection) are analysed. The sensitivity analysis, being part......Mathematical models are increasingly used in environmental science thus increasing the importance of uncertainty and sensitivity analyses. In the present study, an iterative parameter estimation and identifiability analysis methodology is applied to an atmospheric model – the Operational Street...
Climate Sensitivity and Solar Cycle Response in Climate Models
Liang, M.; Lin, L.; Tung, K. K.; Yung, Y. L.
2011-12-01
Climate sensitivity, broadly defined, is a measure of the response of the climate system to the changes of external forcings such as anthropogenic greenhouse emissions and solar radiation, including climate feedback processes. General circulation models provide a means to quantitatively incorporate various feedback processes, such as water-vapor, cloud and albedo feedbacks. Less attention is devoted so far to the role of the oceans in significantly affecting these processes and hence the modelled transient climate sensitivity. Here we show that the oceanic mixing plays an important role in modifying the multi-decadal to centennial oscillations of the sea surface temperature, which in turn affect the derived climate sensitivity at various phases of the oscillations. The eleven-year solar cycle forcing is used to calibrate the response of the climate system. The GISS-EH coupled atmosphere-ocean model was run twice in coupled mode for more than 2000 model years, each with a different value for the ocean eddy mixing parameter. In both runs, there is a prominent low-frequency oscillation with a period of 300-500 years, and depending on the phase of such an oscillation, the derived climate gain factor varies by a factor of 2. The run with the value of the eddy ocean mixing parameter that is half that used in IPCC AR4 study has the more realistic low-frequency variability in SST and in the derived response to the known solar-cycle forcing.
Parameter Optimisation for the Behaviour of Elastic Models over Time
DEFF Research Database (Denmark)
Mosegaard, Jesper
2004-01-01
Optimisation of parameters for elastic models is essential for comparison or finding equivalent behaviour of elastic models when parameters cannot simply be transferred or converted. This is the case with a large range of commonly used elastic models. In this paper we present a general method...... that will optimise parameters based on the behaviour of the elastic models over time....
Applying incentive sensitization models to behavioral addiction
DEFF Research Database (Denmark)
Rømer Thomsen, Kristine; Fjorback, Lone; Møller, Arne
2014-01-01
The incentive sensitization theory is a promising model for understanding the mechanisms underlying drug addiction, and has received support in animal and human studies. So far the theory has not been applied to the case of behavioral addictions like Gambling Disorder, despite sharing clinical...... symptoms and underlying neurobiology. We examine the relevance of this theory for Gambling Disorder and point to predictions for future studies. The theory promises a significant contribution to the understanding of behavioral addiction and opens new avenues for treatment....
Model Identification of Linear Parameter Varying Aircraft Systems
Fujimore, Atsushi; Ljung, Lennart
2007-01-01
This article presents a parameter estimation of continuous-time polytopic models for a linear parameter varying (LPV) system. The prediction error method of linear time invariant (LTI) models is modified for polytopic models. The modified prediction error method is applied to an LPV aircraft system whose varying parameter is the flight velocity and model parameters are the stability and control derivatives (SCDs). In an identification simulation, the polytopic model is more suitable for expre...
Models for patients' recruitment in clinical trials and sensitivity analysis.
Mijoule, Guillaume; Savy, Stéphanie; Savy, Nicolas
2012-07-20
Taking a decision on the feasibility and estimating the duration of patients' recruitment in a clinical trial are very important but very hard questions to answer, mainly because of the huge variability of the system. The more elaborated works on this topic are those of Anisimov and co-authors, where they investigate modelling of the enrolment period by using Gamma-Poisson processes, which allows to develop statistical tools that can help the manager of the clinical trial to answer these questions and thus help him to plan the trial. The main idea is to consider an ongoing study at an intermediate time, denoted t(1). Data collected on [0,t(1)] allow to calibrate the parameters of the model, which are then used to make predictions on what will happen after t(1). This method allows us to estimate the probability of ending the trial on time and give possible corrective actions to the trial manager especially regarding how many centres have to be open to finish on time. In this paper, we investigate a Pareto-Poisson model, which we compare with the Gamma-Poisson one. We will discuss the accuracy of the estimation of the parameters and compare the models on a set of real case data. We make the comparison on various criteria : the expected recruitment duration, the quality of fitting to the data and its sensitivity to parameter errors. We discuss the influence of the centres opening dates on the estimation of the duration. This is a very important question to deal with in the setting of our data set. In fact, these dates are not known. For this discussion, we consider a uniformly distributed approach. Finally, we study the sensitivity of the expected duration of the trial with respect to the parameters of the model : we calculate to what extent an error on the estimation of the parameters generates an error in the prediction of the duration.
Iosjpe, M.
2011-10-01
A sensitivity analysis has been carried out on the basis of the local and global sensitivity indexes for selected radionuclides ( 3H, 137Cs, 238Pu, 241Am and 244Cm) and main parameters describing the water-sediment interaction (sediment reworking rate, pore-water turnover rate, sediment distribution coefficient, suspended sediment load in water column, sedimentation rate, molecular diffusion coefficient, surface sediment thickness, porosity of bottom sediment and density of sediment material). Sensitivity analysis has been carried out using a compartment model for dose assessment to man and biota, which includes the processes of advection of radioactivity between compartments, sedimentation, diffusion of radioactivity through pore water in sediments, particle mixing, pore water mixing and a burial process of radioactivity in deep sediment layers. The sensitivity analysis indicates that for the conditions in the Norwegian Current (the Norwegian Sea) particle mixing dominates the transfer of radioactivity between the bottom water and surface sediment compartments. For the conditions in the Ob Bay (the Kara Sea), the sedimentation process has also been found to be significant. The calculated dynamics of the sensitivity indexes demonstrate clearly the complexities encountered when modeling water-sediment interactions. It is also shown that the results can be strongly dependent on the time of analysis. For example, given a specific change of parameters the radionuclide concentration will be either increased or decreased, depending on the temporal interval. Information provided by the sensitivity analysis can contribute to a better understanding of experimental data and might further improve the parameterization process. The obtained results show that water-sediment interactions can play a key role in the marine coastal environment, thus demonstrating the need to further deepen our understanding of them, as well as improve the models describing them.
Sensitivity of Footbridge Response to Load Modeling
DEFF Research Database (Denmark)
Pedersen, Lars; Frier, Christian
The paper considers a stochastic approach to modeling the actions of walking and has focus on the vibration serviceability limit state of footbridges. The use of a stochastic approach is novel but useful as it is more advanced than the quite simplistic deterministic load models seen in many desig...... matter to foresee their impact. The paper contributes by examining how some of these decisions influence the outcome of serviceability evaluations. The sensitivity study is made focusing on vertical footbridge response to single person loading....
Sensitivity of Footbridge Response to Load Modeling
DEFF Research Database (Denmark)
Pedersen, Lars; Frier, Christian
2012-01-01
The paper considers a stochastic approach to modeling the actions of walking and has focus on the vibration serviceability limit state of footbridges. The use of a stochastic approach is novel but useful as it is more advanced than the quite simplistic deterministic load models seen in many design...... matter to foresee their impact. The paper contributes by examining how some of these decisions influence the outcome of serviceability evaluations. The sensitivity study is made focusing on vertical footbridge response to single person loading....
Sensitivity of Footbridge Response to Load Modeling
DEFF Research Database (Denmark)
Pedersen, Lars; Frier, Christian
The paper considers a stochastic approach to modeling the actions of walking and has focus on the vibration serviceability limit state of footbridges. The use of a stochastic approach is novel but useful as it is more advanced than the quite simplistic deterministic load models seen in many design...... matter to foresee their impact. The paper contributes by examining how some of these decisions influence the outcome of serviceability evaluations. The sensitivity study is made focusing on vertical footbridge response to single person loading....
Sensitivity Analysis of the Bone Fracture Risk Model
Lewandowski, Beth; Myers, Jerry; Sibonga, Jean Diane
2017-01-01
Introduction: The probability of bone fracture during and after spaceflight is quantified to aid in mission planning, to determine required astronaut fitness standards and training requirements and to inform countermeasure research and design. Probability is quantified with a probabilistic modeling approach where distributions of model parameter values, instead of single deterministic values, capture the parameter variability within the astronaut population and fracture predictions are probability distributions with a mean value and an associated uncertainty. Because of this uncertainty, the model in its current state cannot discern an effect of countermeasures on fracture probability, for example between use and non-use of bisphosphonates or between spaceflight exercise performed with the Advanced Resistive Exercise Device (ARED) or on devices prior to installation of ARED on the International Space Station. This is thought to be due to the inability to measure key contributors to bone strength, for example, geometry and volumetric distributions of bone mass, with areal bone mineral density (BMD) measurement techniques. To further the applicability of model, we performed a parameter sensitivity study aimed at identifying those parameter uncertainties that most effect the model forecasts in order to determine what areas of the model needed enhancements for reducing uncertainty. Methods: The bone fracture risk model (BFxRM), originally published in (Nelson et al) is a probabilistic model that can assess the risk of astronaut bone fracture. This is accomplished by utilizing biomechanical models to assess the applied loads; utilizing models of spaceflight BMD loss in at-risk skeletal locations; quantifying bone strength through a relationship between areal BMD and bone failure load; and relating fracture risk index (FRI), the ratio of applied load to bone strength, to fracture probability. There are many factors associated with these calculations including
Directory of Open Access Journals (Sweden)
Carlos Giraldo
2014-04-01
Full Text Available Naturally occurring gas hydrates are regarded as an important future source of energy and considerable efforts are currently being invested to develop methods for an economically viable recovery of this resource. The recovery of natural gas from gas hydrate deposits has been studied by a number of researchers. Depressurization of the reservoir is seen as a favorable method because of its relatively low energy requirements. While lowering the pressure in the production well seems to be a straight forward approach to destabilize methane hydrates, the intrinsic kinetics of CH4-hydrate decomposition and fluid flow lead to complex processes of mass and heat transfer within the deposit. In order to develop a better understanding of the processes and conditions governing the production of methane from methane hydrates it is necessary to study the sensitivity of gas production to the effects of factors such as pressure, temperature, thermal conductivity, permeability, porosity on methane recovery from naturally occurring gas hydrates. A simplified model is the base for an ensemble of reservoir simulations to study which parameters govern productivity and how these factors might interact.
Morshed, Monjur; Ingalls, Brian; Ilie, Silvana
2017-01-01
Sensitivity analysis characterizes the dependence of a model's behaviour on system parameters. It is a critical tool in the formulation, characterization, and verification of models of biochemical reaction networks, for which confident estimates of parameter values are often lacking. In this paper, we propose a novel method for sensitivity analysis of discrete stochastic models of biochemical reaction systems whose dynamics occur over a range of timescales. This method combines finite-difference approximations and adaptive tau-leaping strategies to efficiently estimate parametric sensitivities for stiff stochastic biochemical kinetics models, with negligible loss in accuracy compared with previously published approaches. We analyze several models of interest to illustrate the advantages of our method.
Global Sensitivity Analysis for Multiple Scenarios and Models of Nitrogen Processes
Chen, Z.; Shi, L.; Ye, M.
2015-12-01
Modeling nitrogen process in soil is a long-lasting challenge partly because of the uncertainties from parameters, models and scenarios. It may be difficult to identify a suitable model and its corresponding parameters.This study assesses the global sensitivity indices for parameters of multiple models and scenarios on nitrogen processes. The majority of existing nitrogen dynamics models consider nitrification and denitrification as a first-order decay process or a Michaelis-Menten model, while various reduction functions are used to reflect the impact of environmental soil conditions. To determine the model uncertainty, 9 alternative models were designed based on NP2D model in this study. These models have the similar descriptions of nitrogen process but are different in the cal reduction functions of soil water and temperature. A global sensitivity analysis of each models under various scenarios was evaluated. Results show that in our synthetic cases of nitrogen transport and transformation, the global sensitivity indices vary between each models and scenarios. Larger indices for parameters of nitrification are obtained than the ones of denitrification in 6 models, while an inverse relationship is revealed in the rest 3 models. Parameters of soil temperature reduction functions are more sensitive than those of soil water reduction functions. When the soil water and temperature increase separately or together, parameters of denitrification gain their sensitivity, but the indices for parameters of soil temperature reduction functions decrease simultaneously. Our results indicate that identifying important parameters may be biased if ignoring the model and scenario uncertainties. This problem can be resolved by using the global sensitivity indices for multiple models and multiple scenarios. The new indices is useful to determine the relative contributions from different models and scenarios.
Kwon, Yong-Seok; Naeem, Khurram; Jeon, Min Yong; Kwon, Il-bum
2017-04-01
We analyze the relations of parameters in moving average method to enhance the event detectability of phase sensitive optical time domain reflectometer (OTDR). If the external events have unique frequency of vibration, then the control parameters of moving average method should be optimized in order to detect these events efficiently. A phase sensitive OTDR was implemented by a pulsed light source, which is composed of a laser diode, a semiconductor optical amplifier, an erbium-doped fiber amplifier, a fiber Bragg grating filter, and a light receiving part, which has a photo-detector and high speed data acquisition system. The moving average method is operated with the control parameters: total number of raw traces, M, number of averaged traces, N, and step size of moving, n. The raw traces are obtained by the phase sensitive OTDR with sound signals generated by a speaker. Using these trace data, the relation of the control parameters is analyzed. In the result, if the event signal has one frequency, then the optimal values of N, n are existed to detect the event efficiently.
[Calculation of parameters in forest evapotranspiration model].
Wang, Anzhi; Pei, Tiefan
2003-12-01
Forest evapotranspiration is an important component not only in water balance, but also in energy balance. It is a great demand for the development of forest hydrology and forest meteorology to simulate the forest evapotranspiration accurately, which is also a theoretical basis for the management and utilization of water resources and forest ecosystem. Taking the broadleaved Korean pine forest on Changbai Mountain as an example, this paper constructed a mechanism model for estimating forest evapotranspiration, based on the aerodynamic principle and energy balance equation. Using the data measured by the Routine Meteorological Measurement System and Open-Path Eddy Covariance Measurement System mounted on the tower in the broadleaved Korean pine forest, the parameters displacement height d, stability functions for momentum phi m, and stability functions for heat phi h were ascertained. The displacement height of the study site was equal to 17.8 m, near to the mean canopy height, and the functions of phi m and phi h changing with gradient Richarson number R i were constructed.
Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models
Rakovec, O.; Hill, M. C.; Clark, M. P.; Weerts, A. H.; Teuling, A. J.; Uijlenhoet, R.
2014-01-01
This paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based "local" methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative "bucket-style" hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models.
Cho, Hee-Suk
2015-01-01
We study the validity of the inspiral templates in gravitational wave data analysis for nonspinning binary black holes with Advanced LIGO sensitivity. We use the phenomenological waveform model, which contains the inspiral-merger-ring down (IMR) phases defined in the Fourier domain. For parameter estimation purposes, we calculate the statistical errors assuming the IMR signals and IMR templates for the binaries with total masses M $\\leq$ 30Msun. Especially, we explore the systematic biases caused by a mismatch between the IMR signal model (IMR) and inspiral template model (Imerg), and investigate the impact on the parameter estimation accuracy by comparing the biases with the statistical errors. For detection purposes, we calculate the fitting factors of the inspiral templates with respect to the IMR signals. We find that the valid criteria for Imerg templates are obtained by Mcrit ~ 24Msun (if M < Mcrit, the fitting factor is higher than 0.97) for detection and M < 26Msun (where the systematic bias is ...
Sensitivity Analysis of Depletion Parameters for Heat Load Evaluation of PWR Spent Fuel Storage Pool
Energy Technology Data Exchange (ETDEWEB)
Kim, In Young; Lee, Un Chul [Seoul National University, Seoul (Korea, Republic of)
2011-12-15
As necessity of safety re-evaluation for spent fuel storage facility has emphasized after the Fukushima accident, accuracy improvement of heat load evaluation has become more important to acquire reliable thermal-hydraulic evaluation results. As groundwork, parametric and sensitivity analyses of various storage conditions for Kori Unit 4 spent fuel storage pool and spent fuel depletion parameters such as axial burnup effect, operation history, and specific heat are conducted using ORIGEN2 code. According to heat load evaluation and parametric sensitivity analyses, decay heat of last discharged fuel comprises maximum 80.42% of total heat load of storage facility and there is a negative correlation between effect of depletion parameters and cooling period. It is determined that specific heat is most influential parameter and operation history is secondly influential parameter. And decay heat of just discharged fuel is varied from 0.34 to 1.66 times of average value and decay heat of 1 year cooled fuel is varied from 0.55 to 1.37 times of average value in accordance with change of specific power. Namely depletion parameters can cause large variation in decay heat calculation of short-term cooled fuel. Therefore application of real operation data instead of user selection value is needed to improve evaluation accuracy. It is expected that these results could be used to improve accuracy of heat load assessment and evaluate uncertainty of calculated heat load.
Studying the physics potential of long-baseline experiments in terms of new sensitivity parameters
Singh, Mandip
2016-01-01
We investigate physics opportunities to constraint leptonic CP-violation phase $\\delta_{CP}$ through numerical analysis of working neutrino oscillation probability parameters, in the context of long base line experiments. Numerical analysis of two parameters, the " transition probability $\\delta_{CP}$ phase sensitivity parameter ($A^M$) " and " CP-violation probability $\\delta_{CP}$ phase sensitivity parameter ($A^{CP}$) ", as function of beam energy and/or base line has been preferably carried out. It is an elegant technique to broadly analyze different experiments to constraint $\\delta_{CP}$ phase and also to investigate mass hierarchy in the leptonic sector. The positive and negative values of parameter $A^{CP}$ corresponding to either of hierarchy in the specific beam energy ranges, could be a very promising way to explore mass hierarchy and $\\delta_{CP}$ phase. The keys to more robust bounds on $\\delta_{CP}$ phase are improvements of the involved detection techniques to explore bit low energy and relativ...
Photovoltaic System Modeling. Uncertainty and Sensitivity Analyses
Energy Technology Data Exchange (ETDEWEB)
Hansen, Clifford W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Martin, Curtis E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-08-01
We report an uncertainty and sensitivity analysis for modeling AC energy from ph otovoltaic systems . Output from a PV system is predicted by a sequence of models. We quantify u ncertainty i n the output of each model using empirical distribution s of each model's residuals. We propagate uncertainty through the sequence of models by sampli ng these distributions to obtain a n empirical distribution of a PV system's output. We consider models that: (1) translate measured global horizontal, direct and global diffuse irradiance to plane - of - array irradiance; (2) estimate effective irradiance; (3) predict cell temperature; (4) estimate DC voltage, current and power ; (5) reduce DC power for losses due to inefficient maximum power point tracking or mismatch among modules; and (6) convert DC to AC power . O ur analysis consider s a notional PV system com prising an array of FirstSolar FS - 387 modules and a 250 kW AC inverter ; we use measured irradiance and weather at Albuquerque, NM. We found the uncertainty in PV syste m output to be relatively small, on the order of 1% for daily energy. We found that unce rtainty in the models for POA irradiance and effective irradiance to be the dominant contributors to uncertainty in predicted daily energy. Our analysis indicates that efforts to reduce the uncertainty in PV system output predictions may yield the greatest improvements by focusing on the POA and effective irradiance models.
Dependence of mis-alignment sensitivity of ring laser gyro cavity on cavity parameters
Energy Technology Data Exchange (ETDEWEB)
Sun Feng; Zhang Xi; Zhang Hongbo; Yang Changcheng, E-mail: sunok1234@sohu.com [Huazhong Institute of Electro-Optics - Wuhan National Lab for Optoelectronics, Wuhan, Hubei (China)
2011-02-01
The ring laser gyroscope (RLG), as a rotation sensor, has been widely used for navigation and guidance on vehicles and missiles. The environment of strong random-vibration and large acceleration may deteriorate the performance of the RLG due to the vibration-induced tilting of the mirrors. In this paper the RLG performance is theoretically analyzed and the parameters such as the beam diameter at the aperture, cavity mirror alignment sensitivities and power loss due to the mirror tilting are calculated. It is concluded that by carefully choosing the parameters, the significant loss in laser power can be avoided.
Transfer function modeling of damping mechanisms in distributed parameter models
Slater, J. C.; Inman, D. J.
1994-01-01
This work formulates a method for the modeling of material damping characteristics in distributed parameter models which may be easily applied to models such as rod, plate, and beam equations. The general linear boundary value vibration equation is modified to incorporate hysteresis effects represented by complex stiffness using the transfer function approach proposed by Golla and Hughes. The governing characteristic equations are decoupled through separation of variables yielding solutions similar to those of undamped classical theory, allowing solution of the steady state as well as transient response. Example problems and solutions are provided demonstrating the similarity of the solutions to those of the classical theories and transient responses of nonviscous systems.
Yu, Xiaolin; Zhang, Shaoqing; Lin, Xiaopei; Li, Mingkui
2017-03-01
The uncertainties in values of coupled model parameters are an important source of model bias that causes model climate drift. The values can be calibrated by a parameter estimation procedure that projects observational information onto model parameters. The signal-to-noise ratio of error covariance between the model state and the parameter being estimated directly determines whether the parameter estimation succeeds or not. With a conceptual climate model that couples the stochastic atmosphere and slow-varying ocean, this study examines the sensitivity of state-parameter covariance on the accuracy of estimated model states in different model components of a coupled system. Due to the interaction of multiple timescales, the fast-varying atmosphere with a chaotic nature is the major source of the inaccuracy of estimated state-parameter covariance. Thus, enhancing the estimation accuracy of atmospheric states is very important for the success of coupled model parameter estimation, especially for the parameters in the air-sea interaction processes. The impact of chaotic-to-periodic ratio in state variability on parameter estimation is also discussed. This simple model study provides a guideline when real observations are used to optimize model parameters in a coupled general circulation model for improving climate analysis and predictions.
On the modeling of internal parameters in hyperelastic biological materials
Giantesio, Giulia
2016-01-01
This paper concerns the behavior of hyperelastic energies depending on an internal parameter. First, the situation in which the internal parameter is a function of the gradient of the deformation is presented. Second, two models where the parameter describes the activation of skeletal muscle tissue are analyzed. In those models, the activation parameter depends on the strain and it is important to consider the derivative of the parameter with respect to the strain in order to capture the proper behavior of the stress.
Yang, G.; Maher, K.; Caers, J.
2015-12-01
Groundwater contamination associated with remediated uranium mill tailings is a challenging environmental problem, particularly within the Colorado River Basin. To examine the effectiveness of in-situ bioremediation of U(VI), acetate injection has been proposed and tested at the Rifle pilot site. There have been several geologic modeling and simulated contaminant transport investigations, to evaluate the potential outcomes of the process and identify crucial factors for successful uranium reduction. Ultimately, findings from these studies would contribute to accurate predictions of the efficacy of uranium reduction. However, all these previous studies have considered limited model complexities, either because of the concern that data is too sparse to resolve such complex systems or because some parameters are assumed to be less important. Such simplified initial modeling, however, limits the predictive power of the model. Moreover, previous studies have not yet focused on spatial heterogeneity of various modeling components and its impact on the spatial distribution of the immobilized uranium (U(IV)). In this study, we study the impact of uncertainty on 21 parameters on model responses by means of recently developed distance-based global sensitivity analysis (DGSA), to study the main effects and interactions of parameters of various types. The 21 parameters include, for example, spatial variability of initial uranium concentration, mean hydraulic conductivity, and variogram structures of hydraulic conductivity. DGSA allows for studying multi-variate model responses based on spatial and non-spatial model parameters. When calculating the distances between model responses, in addition to the overall uranium reduction efficacy, we also considered the spatial profiles of the immobilized uranium concentration as target response. Results show that the mean hydraulic conductivity and the mineral reaction rate are the two most sensitive parameters with regard to the overall
Determination of new electroweak parameters at the ILC. Sensitivity to new physics
Energy Technology Data Exchange (ETDEWEB)
Beyer, M.; Schmidt, E.; Schroeder, H. [Rostock Univ. (Germany). Inst. fuer Physik; Kilian, W. [Siegen Univ. (Gesamthochschule) (Germany). Fach Physik]|[Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Krstonosic, P.; Reuter, J. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Moenig, K. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany)
2006-04-15
We present a study of the sensitivity of an International Linear Collider (ILC) to electroweak parameters in the absence of a light Higgs boson. In particular, we consider those parameters that have been inaccessible at previous colliders, quartic gauge couplings. Within a generic effective-field theory context we analyze all processes that contain quasi-elastic weak-boson scattering, using complete six-fermion matrix elements in unweighted event samples, fast simulation of the ILC detector, and a multidimensional parameter fit of the set of anomalous couplings. The analysis does not rely on simplifying assumptions such as custodial symmetry or approximations such as the equivalence theorem. We supplement this by a similar new study of triple weak-boson production, which is sensitive to the same set of anomalous couplings. Including the known results on triple gauge couplings and oblique corrections, we thus quantitatively determine the indirect sensitivity of the ILC to new physics in the electroweak symmetry-breaking sector, conveniently parameterized by real or fictitious resonances in each accessible spin/isospin channel. (Orig.)
The Effect of Nondeterministic Parameters on Shock-Associated Noise Prediction Modeling
Dahl, Milo D.; Khavaran, Abbas
2010-01-01
Engineering applications for aircraft noise prediction contain models for physical phenomenon that enable solutions to be computed quickly. These models contain parameters that have an uncertainty not accounted for in the solution. To include uncertainty in the solution, nondeterministic computational methods are applied. Using prediction models for supersonic jet broadband shock-associated noise, fixed model parameters are replaced by probability distributions to illustrate one of these methods. The results show the impact of using nondeterministic parameters both on estimating the model output uncertainty and on the model spectral level prediction. In addition, a global sensitivity analysis is used to determine the influence of the model parameters on the output, and to identify the parameters with the least influence on model output.
The identifiability of parameters in a water quality model of the Biebrza River, Poland
Perk, van der M.; Bierkens, M.F.P.
1997-01-01
The identifiability of model parameters of a steady state water quality model of the Biebrza River and the resulting variation in model results was examined by applying the Monte Carlo method which combines calibration, identifiability analysis, uncertainty analysis, and sensitivity analysis. The wa
Model comparisons and genetic and environmental parameter ...
African Journals Online (AJOL)
arc
South African Journal of Animal Science 2005, 35 (1) ... Genetic and environmental parameters were estimated for pre- and post-weaning average daily gain ..... and BWT (and medium maternal genetic correlations) indicates that these traits ...
Nestorov, I A; Aarons, L J; Rowland, M
1997-08-01
Sensitivity analysis studies the effects of the inherent variability and uncertainty in model parameters on the model outputs and may be a useful tool at all stages of the pharmacokinetic modeling process. The present study examined the sensitivity of a whole-body physiologically based pharmacokinetic (PBPK) model for the distribution kinetics of nine 5-n-alkyl-5-ethyl barbituric acids in arterial blood and 14 tissues (lung, liver, kidney, stomach, pancreas, spleen, gut, muscle, adipose, skin, bone, heart, brain, testes) after i.v. bolus administration to rats. The aims were to obtain new insights into the model used, to rank the model parameters involved according to their impact on the model outputs and to study the changes in the sensitivity induced by the increase in the lipophilicity of the homologues on ascending the series. Two approaches for sensitivity analysis have been implemented. The first, based on the Matrix Perturbation Theory, uses a sensitivity index defined as the normalized sensitivity of the 2-norm of the model compartmental matrix to perturbations in its entries. The second approach uses the traditional definition of the normalized sensitivity function as the relative change in a model state (a tissue concentration) corresponding to a relative change in a model parameter. Autosensitivity has been defined as sensitivity of a state to any of its parameters; cross-sensitivity as the sensitivity of a state to any other states' parameters. Using the two approaches, the sensitivity of representative tissue concentrations (lung, liver, kidney, stomach, gut, adipose, heart, and brain) to the following model parameters: tissue-to-unbound plasma partition coefficients, tissue blood flows, unbound renal and intrinsic hepatic clearance, permeability surface area product of the brain, have been analyzed. Both the tissues and the parameters were ranked according to their sensitivity and impact. The following general conclusions were drawn: (i) the overall
Parameter estimation for models of ligninolytic and cellulolytic enzyme kinetics
Energy Technology Data Exchange (ETDEWEB)
Wang, Gangsheng [ORNL; Post, Wilfred M [ORNL; Mayes, Melanie [ORNL; Frerichs, Joshua T [ORNL; Jagadamma, Sindhu [ORNL
2012-01-01
While soil enzymes have been explicitly included in the soil organic carbon (SOC) decomposition models, there is a serious lack of suitable data for model parameterization. This study provides well-documented enzymatic parameters for application in enzyme-driven SOC decomposition models from a compilation and analysis of published measurements. In particular, we developed appropriate kinetic parameters for five typical ligninolytic and cellulolytic enzymes ( -glucosidase, cellobiohydrolase, endo-glucanase, peroxidase, and phenol oxidase). The kinetic parameters included the maximum specific enzyme activity (Vmax) and half-saturation constant (Km) in the Michaelis-Menten equation. The activation energy (Ea) and the pH optimum and sensitivity (pHopt and pHsen) were also analyzed. pHsen was estimated by fitting an exponential-quadratic function. The Vmax values, often presented in different units under various measurement conditions, were converted into the same units at a reference temperature (20 C) and pHopt. Major conclusions are: (i) Both Vmax and Km were log-normal distributed, with no significant difference in Vmax exhibited between enzymes originating from bacteria or fungi. (ii) No significant difference in Vmax was found between cellulases and ligninases; however, there was significant difference in Km between them. (iii) Ligninases had higher Ea values and lower pHopt than cellulases; average ratio of pHsen to pHopt ranged 0.3 0.4 for the five enzymes, which means that an increase or decrease of 1.1 1.7 pH units from pHopt would reduce Vmax by 50%. (iv) Our analysis indicated that the Vmax values from lab measurements with purified enzymes were 1 2 orders of magnitude higher than those for use in SOC decomposition models under field conditions.
Stability and Sensitive Analysis of a Model with Delay Quorum Sensing
Directory of Open Access Journals (Sweden)
Zhonghua Zhang
2015-01-01
Full Text Available This paper formulates a delay model characterizing the competition between bacteria and immune system. The center manifold reduction method and the normal form theory due to Faria and Magalhaes are used to compute the normal form of the model, and the stability of two nonhyperbolic equilibria is discussed. Sensitivity analysis suggests that the growth rate of bacteria is the most sensitive parameter of the threshold parameter R0 and should be targeted in the controlling strategies.
NEW DOCTORAL DEGREE Parameter estimation problem in the Weibull model
Marković, Darija
2009-01-01
In this dissertation we consider the problem of the existence of best parameters in the Weibull model, one of the most widely used statistical models in reliability theory and life data theory. Particular attention is given to a 3-parameter Weibull model. We have listed some of the many applications of this model. We have described some of the classical methods for estimating parameters of the Weibull model, two graphical methods (Weibull probability plot and hazard plot), and two analyt...
Sensitivity of the NMR density matrix to pulse sequence parameters: a simplified analytic approach.
Momot, Konstantin I; Takegoshi, K
2012-08-01
We present a formalism for the analysis of sensitivity of nuclear magnetic resonance pulse sequences to variations of pulse sequence parameters, such as radiofrequency pulses, gradient pulses or evolution delays. The formalism enables the calculation of compact, analytic expressions for the derivatives of the density matrix and the observed signal with respect to the parameters varied. The analysis is based on two constructs computed in the course of modified density-matrix simulations: the error interrogation operators and error commutators. The approach presented is consequently named the Error Commutator Formalism (ECF). It is used to evaluate the sensitivity of the density matrix to parameter variation based on the simulations carried out for the ideal parameters, obviating the need for finite-difference calculations of signal errors. The ECF analysis therefore carries a computational cost comparable to a single density-matrix or product-operator simulation. Its application is illustrated using a number of examples from basic NMR spectroscopy. We show that the strength of the ECF is its ability to provide analytic insights into the propagation of errors through pulse sequences and the behaviour of signal errors under phase cycling. Furthermore, the approach is algorithmic and easily amenable to implementation in the form of a programming code. It is envisaged that it could be incorporated into standard NMR product-operator simulation packages.
A Fault Alarm and Diagnosis Method Based on Sensitive Parameters and Support Vector Machine
Zhang, Jinjie; Yao, Ziyun; Lv, Zhiquan; Zhu, Qunxiong; Xu, Fengtian; Jiang, Zhinong
2015-08-01
Study on the extraction of fault feature and the diagnostic technique of reciprocating compressor is one of the hot research topics in the field of reciprocating machinery fault diagnosis at present. A large number of feature extraction and classification methods have been widely applied in the related research, but the practical fault alarm and the accuracy of diagnosis have not been effectively improved. Developing feature extraction and classification methods to meet the requirements of typical fault alarm and automatic diagnosis in practical engineering is urgent task. The typical mechanical faults of reciprocating compressor are presented in the paper, and the existing data of online monitoring system is used to extract fault feature parameters within 15 types in total; the inner sensitive connection between faults and the feature parameters has been made clear by using the distance evaluation technique, also sensitive characteristic parameters of different faults have been obtained. On this basis, a method based on fault feature parameters and support vector machine (SVM) is developed, which will be applied to practical fault diagnosis. A better ability of early fault warning has been proved by the experiment and the practical fault cases. Automatic classification by using the SVM to the data of fault alarm has obtained better diagnostic accuracy.
Krzyżak, A. T.; Jasiński, A.; Adamek, D.
2006-07-01
Qualification of the most statistically "sensitive" diffusion parameters using Magnetic Resonance (MR) Diffusion Tensor Imaging (DTI) of the control and injured spinal cord of a rat in vivo and in vitro after the trauma is reported. Injury was induced in TH12/TH13 level by a controlled "weight-drop". In vitro experiments were performed in a home-built MR microscope, with a 6.4 T magnet, in vivo samples were measured in a 9.4 T/21 horizontal magnet The aim of this work was to find the most effective diffusion parameters which are useful in the statistically significant detection of spinal cord tissue damage. Apparent diffusion tensor (ADT) weighted data measured in vivo and in vitro on control and injured rat spinal cord (RSC) in the transverse planes and analysis of the diffusion anisotropy as a function of many parameters, which allows statisticall expose of the existence of the damage are reported.
Parameter optimization model in electrical discharge machining process
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Electrical discharge machining (EDM) process, at present is still an experience process, wherein selected parameters are often far from the optimum, and at the same time selecting optimization parameters is costly and time consuming. In this paper,artificial neural network (ANN) and genetic algorithm (GA) are used together to establish the parameter optimization model. An ANN model which adapts Levenberg-Marquardt algorithm has been set up to represent the relationship between material removal rate (MRR) and input parameters, and GA is used to optimize parameters, so that optimization results are obtained. The model is shown to be effective, and MRR is improved using optimized machining parameters.
Three-dimensional lake water quality modeling: sensitivity and uncertainty analyses.
Missaghi, Shahram; Hondzo, Miki; Melching, Charles
2013-11-01
Two sensitivity and uncertainty analysis methods are applied to a three-dimensional coupled hydrodynamic-ecological model (ELCOM-CAEDYM) of a morphologically complex lake. The primary goals of the analyses are to increase confidence in the model predictions, identify influential model parameters, quantify the uncertainty of model prediction, and explore the spatial and temporal variabilities of model predictions. The influence of model parameters on four model-predicted variables (model output) and the contributions of each of the model-predicted variables to the total variations in model output are presented. The contributions of predicted water temperature, dissolved oxygen, total phosphorus, and algal biomass contributed 3, 13, 26, and 58% of total model output variance, respectively. The fraction of variance resulting from model parameter uncertainty was calculated by two methods and used for evaluation and ranking of the most influential model parameters. Nine out of the top 10 parameters identified by each method agreed, but their ranks were different. Spatial and temporal changes of model uncertainty were investigated and visualized. Model uncertainty appeared to be concentrated around specific water depths and dates that corresponded to significant storm events. The results suggest that spatial and temporal variations in the predicted water quality variables are sensitive to the hydrodynamics of physical perturbations such as those caused by stream inflows generated by storm events. The sensitivity and uncertainty analyses identified the mineralization of dissolved organic carbon, sediment phosphorus release rate, algal metabolic loss rate, internal phosphorus concentration, and phosphorus uptake rate as the most influential model parameters.
Sensitivity Analysis of Fatigue Crack Growth Model for API Steels in Gaseous Hydrogen
Amaro, Robert L; Rustagi, Neha; Drexler, Elizabeth S; Slifka, Andrew J
2014-01-01
A model to predict fatigue crack growth of API pipeline steels in high pressure gaseous hydrogen has been developed and is presented elsewhere. The model currently has several parameters that must be calibrated for each pipeline steel of interest. This work provides a sensitivity analysis of the model parameters in order to provide (a) insight to the underlying mathematical and mechanistic aspects of the model, and (b) guidance for model calibration of other API steels. PMID:26601024
Sensitivity Analysis of Fatigue Crack Growth Model for API Steels in Gaseous Hydrogen.
Amaro, Robert L; Rustagi, Neha; Drexler, Elizabeth S; Slifka, Andrew J
2014-01-01
A model to predict fatigue crack growth of API pipeline steels in high pressure gaseous hydrogen has been developed and is presented elsewhere. The model currently has several parameters that must be calibrated for each pipeline steel of interest. This work provides a sensitivity analysis of the model parameters in order to provide (a) insight to the underlying mathematical and mechanistic aspects of the model, and (b) guidance for model calibration of other API steels.
Test and Sensitivity Analysis of Hydrological Modeling in the Coupled WRF-Urban Modeling System
Wang, Z.; yang, J.
2013-12-01
Rapid urbanization has emerged as the source of many adverse effects that challenge the environmental sustainability of cities under changing climatic patterns. One essential key to address these challenges is to physically resolve the dynamics of urban-land-atmospheric interactions. To investigate the impact of urbanization on regional climate, physically-based single layer urban canopy model (SLUCM) has been developed and implemented into the Weather Research and Forecasting (WRF) platform. However, due to the lack of realistic representation of urban hydrological processes, simulation of urban climatology by current coupled WRF-SLUCM is inevitably inadequate. Aiming at improving the accuracy of simulations, recently we implemented urban hydrological processes into the model, including (1) anthropogenic latent heat, (2) urban irrigation, (3) evaporation over impervious surface, and (4) urban oasis effect. In addition, we couple the green roof system into the model to verify its capacity in alleviating urban heat island effect at regional scale. Driven by different meteorological forcings, offline tests show that the enhanced model is more accurate in predicting turbulent fluxes arising from built terrains. Though the coupled WRF-SLUCM has been extensively tested against various field measurement datasets, accurate input parameter space needs to be specified for good model performance. As realistic measurements of all input parameters to the modeling framework are rarely possible, understanding the model sensitivity to individual parameters is essential to determine the relative importance of parameter uncertainty to model performance. Thus we further use an advanced Monte Carlo approach to quantify relative sensitivity of input parameters of the hydrological model. In particular, performance of two widely used soil hydraulic models, namely the van Genuchten model (based on generic soil physics) and an empirical model (viz. the CHC model currently adopted in WRF
Precipitates/Salts Model Sensitivity Calculation
Energy Technology Data Exchange (ETDEWEB)
P. Mariner
2001-12-20
The objective and scope of this calculation is to assist Performance Assessment Operations and the Engineered Barrier System (EBS) Department in modeling the geochemical effects of evaporation on potential seepage waters within a potential repository drift. This work is developed and documented using procedure AP-3.12Q, ''Calculations'', in support of ''Technical Work Plan For Engineered Barrier System Department Modeling and Testing FY 02 Work Activities'' (BSC 2001a). The specific objective of this calculation is to examine the sensitivity and uncertainties of the Precipitates/Salts model. The Precipitates/Salts model is documented in an Analysis/Model Report (AMR), ''In-Drift Precipitates/Salts Analysis'' (BSC 2001b). The calculation in the current document examines the effects of starting water composition, mineral suppressions, and the fugacity of carbon dioxide (CO{sub 2}) on the chemical evolution of water in the drift.
Improved environmental multimedia modeling and its sensitivity analysis.
Yuan, Jing; Elektorowicz, Maria; Chen, Zhi
2011-01-01
Modeling of multimedia environmental issues is extremely complex due to the intricacy of the systems with the consideration of many factors. In this study, an improved environmental multimedia modeling is developed and a number of testing problems related to it are examined and compared with each other with standard numerical and analytical methodologies. The results indicate the flux output of new model is lesser in the unsaturated zone and groundwater zone compared with the traditional environmental multimedia model. Furthermore, about 90% of the total benzene flux was distributed to the air zone from the landfill sources and only 10% of the total flux emitted into the unsaturated, groundwater zones in non-uniform conditions. This paper also includes functions of model sensitivity analysis to optimize model parameters such as Peclet number (Pe). The analyses results show that the Pe can be considered as deterministic input variables for transport output. The oscillatory behavior is eliminated with the Pe decreased. In addition, the numerical methods are more accurate than analytical methods with the Pe increased. In conclusion, the improved environmental multimedia model system and its sensitivity analysis can be used to address the complex fate and transport of the pollutants in multimedia environments and then help to manage the environmental impacts.
Estimation of shape model parameters for 3D surfaces
DEFF Research Database (Denmark)
Erbou, Søren Gylling Hemmingsen; Darkner, Sune; Fripp, Jurgen;
2008-01-01
Statistical shape models are widely used as a compact way of representing shape variation. Fitting a shape model to unseen data enables characterizing the data in terms of the model parameters. In this paper a Gauss-Newton optimization scheme is proposed to estimate shape model parameters of 3D s...
Compositional modelling of distributed-parameter systems
Maschke, Bernhard; Schaft, van der Arjan; Lamnabhi-Lagarrigue, F.; Loría, A.; Panteley, E.
2005-01-01
The Hamiltonian formulation of distributed-parameter systems has been a challenging reserach area for quite some time. (A nice introduction, especially with respect to systems stemming from fluid dynamics, can be found in [26], where also a historical account is provided.) The identification of the
Ojeda, David; Le Rolle, Virginie; Romero-Ugalde, Hector M.; Gallet, Clément; Bonnet, Jean-Luc; Henry, Christine; Bel, Alain; Mabo, Philippe; Carrault, Guy; Hernández, Alfredo I.
2016-01-01
Although the therapeutic effects of Vagus Nerve Stimulation (VNS) have been recognized in pre-clinical and pilot clinical studies, the effect of different stimulation configurations on the cardiovascular response is still an open question, especially in the case of VNS delivered synchronously with cardiac activity. In this paper, we propose a formal mathematical methodology to analyze the acute cardiac response to different VNS configurations, jointly considering the chronotropic, dromotropic and inotropic cardiac effects. A latin hypercube sampling method was chosen to design a uniform experimental plan, composed of 75 different VNS configurations, with different values for the main parameters (current amplitude, number of delivered pulses, pulse width, interpulse period and the delay between the detected cardiac event and VNS onset). These VNS configurations were applied to 6 healthy, anesthetized sheep, while acquiring the associated cardiovascular response. Unobserved VNS configurations were estimated using a Gaussian process regression (GPR) model. In order to quantitatively analyze the effect of each parameter and their combinations on the cardiac response, the Sobol sensitivity method was applied to the obtained GPR model and inter-individual sensitivity markers were estimated using a bootstrap approach. Results highlight the dominant effect of pulse current, pulse width and number of pulses, which explain respectively 49.4%, 19.7% and 6.0% of the mean global cardiovascular variability provoked by VNS. More interestingly, results also quantify the effect of the interactions between VNS parameters. In particular, the interactions between current and pulse width provoke higher cardiac effects than the changes on the number of pulses alone (between 6 and 25% of the variability). Although the sensitivity of individual VNS parameters seems similar for chronotropic, dromotropic and inotropic responses, the interacting effects of VNS parameters provoke
Parameter Estimation and Experimental Design in Groundwater Modeling
Institute of Scientific and Technical Information of China (English)
SUN Ne-zheng
2004-01-01
This paper reviews the latest developments on parameter estimation and experimental design in the field of groundwater modeling. Special considerations are given when the structure of the identified parameter is complex and unknown. A new methodology for constructing useful groundwater models is described, which is based on the quantitative relationships among the complexity of model structure, the identifiability of parameter, the sufficiency of data, and the reliability of model application.
Modelling of NOx emissions from pressurized fluidized bed combustion - A parameter study
DEFF Research Database (Denmark)
Jensen, Anker; Johnsson, Jan Erik
1997-01-01
Simulations with a mathematical model of a pressurized bubbling fluidized-bed combustor (PFBC) combined with a kinetic model for NO formation and reduction are reported. The kinetic model for NO formation and reduction considers NO and NH3 as the fixed nitrogen species, and includes homogeneous....... The sensitivity of the simulated NO emission with respect to hydrodynamic and combustion parameters in the model is investigated and the mechanisms by which the parameters influence the emission of NO is explained. The analysis shows that the most important hydrodynamic parameters are the minimum fluidization...
Scanning laser polarimetry: »number« parameter sensitivity and specificity in glaucoma diagnostics
Directory of Open Access Journals (Sweden)
Barbara Cvenkel
2005-10-01
Full Text Available Background: Scanning laser polarimetry (SLP is a method that enables quantitative assessment of retinal nerve fibre layer (RNFL thickness surrounding the optic nerve. The commercially available device GDx (GDx, Laser Diagnostics Technologies, San Diego, CA yields an outprint consisting of a reflectance image, colour-coded retardation map, and the 14 parameters, of which the »Number« was shown to be the single best parameter to discriminate between glaucomatous and normal eyes. The »Number« is a probability score, ranging from 1 (low probability of glaucoma to 100 (high probability of glaucoma. In our study we determined the sensitivity and the specificity of the »Number« at cutoff values of 23 and 30. Methods: Thirty patients with different stage of glaucoma and 14 patients with typical glaucomatous changes of the ONH without visual field loss (preperimetric glaucoma were included in the analysis. The control group was represented by 27 adults without ocular pathology with intraocular pressure of < 21 mmHg and normal visual fields. The sensitivity and specificity of the »Number« was determined at a cut-off level of 23 and 30. Results: The sensitivity of the »Number« at a cut-off level of 30 for the glaucoma group was 74% at a specificity of 86%, at a cut-off of 23 the sensitivity increased to 83% at a specificity of 76%. The discriminating ability of the »Number« in the group with preperimetric glaucoma was low, with the sensitivities of 36% and 50% at a cut-off value of 30 and 23, respectively.Conclusions: The parameter »Number« yielded good separation between normal eyes and eyes with moderate and advanced glaucoma. However, the sensitivity of the »Number« in eyes with mild glaucoma and especially with preperimetric glaucoma was low. Because of the great interindividual variability of the RNFL, the assessment of RNFL thickness change over time would be more appropriate to detect early glaucomatous changes.
Sensitivity Analysis of a Riparian Vegetation Growth Model
Directory of Open Access Journals (Sweden)
Michael Nones
2016-11-01
Full Text Available The paper presents a sensitivity analysis of two main parameters used in a mathematic model able to evaluate the effects of changing hydrology on the growth of riparian vegetation along rivers and its effects on the cross-section width. Due to a lack of data in existing literature, in a past study the schematization proposed here was applied only to two large rivers, assuming steady conditions for the vegetational carrying capacity and coupling the vegetal model with a 1D description of the river morphology. In this paper, the limitation set by steady conditions is overcome, imposing the vegetational evolution dependent upon the initial plant population and the growth rate, which represents the potential growth of the overall vegetation along the watercourse. The sensitivity analysis shows that, regardless of the initial population density, the growth rate can be considered the main parameter defining the development of riparian vegetation, but it results site-specific effects, with significant differences for large and small rivers. Despite the numerous simplifications adopted and the small database analyzed, the comparison between measured and computed river widths shows a quite good capability of the model in representing the typical interactions between riparian vegetation and water flow occurring along watercourses. After a thorough calibration, the relatively simple structure of the code permits further developments and applications to a wide range of alluvial rivers.
Bayesian approach to decompression sickness model parameter estimation.
Howle, L E; Weber, P W; Nichols, J M
2017-03-01
We examine both maximum likelihood and Bayesian approaches for estimating probabilistic decompression sickness model parameters. Maximum likelihood estimation treats parameters as fixed values and determines the best estimate through repeated trials, whereas the Bayesian approach treats parameters as random variables and determines the parameter probability distributions. We would ultimately like to know the probability that a parameter lies in a certain range rather than simply make statements about the repeatability of our estimator. Although both represent powerful methods of inference, for models with complex or multi-peaked likelihoods, maximum likelihood parameter estimates can prove more difficult to interpret than the estimates of the parameter distributions provided by the Bayesian approach. For models of decompression sickness, we show that while these two estimation methods are complementary, the credible intervals generated by the Bayesian approach are more naturally suited to quantifying uncertainty in the model parameters.
Animal models to study gluten sensitivity.
Marietta, Eric V; Murray, Joseph A
2012-07-01
The initial development and maintenance of tolerance to dietary antigens is a complex process that, when prevented or interrupted, can lead to human disease. Understanding the mechanisms by which tolerance to specific dietary antigens is attained and maintained is crucial to our understanding of the pathogenesis of diseases related to intolerance of specific dietary antigens. Two diseases that are the result of intolerance to a dietary antigen are celiac disease (CD) and dermatitis herpetiformis (DH). Both of these diseases are dependent upon the ingestion of gluten (the protein fraction of wheat, rye, and barley) and manifest in the gastrointestinal tract and skin, respectively. These gluten-sensitive diseases are two examples of how devastating abnormal immune responses to a ubiquitous food can be. The well-recognized risk genotype for both is conferred by either of the HLA class II molecules DQ2 or DQ8. However, only a minority of individuals who carry these molecules will develop either disease. Also of interest is that the age at diagnosis can range from infancy to 70-80 years of age. This would indicate that intolerance to gluten may potentially be the result of two different phenomena. The first would be that, for various reasons, tolerance to gluten never developed in certain individuals, but that for other individuals, prior tolerance to gluten was lost at some point after childhood. Of recent interest is the concept of non-celiac gluten sensitivity, which manifests as chronic digestive or neurologic symptoms due to gluten, but through mechanisms that remain to be elucidated. This review will address how animal models of gluten-sensitive disorders have substantially contributed to a better understanding of how gluten intolerance can arise and cause disease.
Animal Models to Study Gluten Sensitivity1
Marietta, Eric V.; Murray, Joseph A.
2012-01-01
The initial development and maintenance of tolerance to dietary antigens is a complex process that, when prevented or interrupted, can lead to human disease. Understanding the mechanisms by which tolerance to specific dietary antigens is attained and maintained is crucial to our understanding of the pathogenesis of diseases related to intolerance of specific dietary antigens. Two diseases that are the result of intolerance to a dietary antigen are celiac disease (CD) and dermatitis herpetiformis (DH). Both of these diseases are dependent upon the ingestion of gluten (the protein fraction of wheat, rye, and barley) and manifest in the gastrointestinal tract and skin, respectively. These gluten-sensitive diseases are two examples of how devastating abnormal immune responses to a ubiquitous food can be. The well-recognized risk genotype for both is conferred by either of the HLA class II molecules DQ2 or DQ8. However, only a minority of individuals who carry these molecules will develop either disease. Also of interest is that the age at diagnosis can range from infancy to 70–80 years of age. This would indicate that intolerance to gluten may potentially be the result of two different phenomena. The first would be that, for various reasons, tolerance to gluten never developed in certain individuals, but that for other individuals, prior tolerance to gluten was lost at some point after childhood. Of recent interest is the concept of non-celiac gluten sensitivity, which manifests as chronic digestive or neurologic symptoms due to gluten, but through mechanisms that remain to be elucidated. This review will address how animal models of gluten-sensitive disorders have substantially contributed to a better understanding of how gluten intolerance can arise and cause disease. PMID:22572887
Directory of Open Access Journals (Sweden)
K. D. Maurer
2014-11-01
parameters to be highly variable, but were able to find positive relationships between displacement height and maximum canopy height, aerodynamic canopy height and maximum canopy height and leaf area index, and eddy-penetration depth and gap fraction. We also found negative relationships between aerodynamic canopy height and gap fraction, and between eddy-penetration depth and maximum canopy height and leaf area index. Using a decade of wind and canopy structure observations in a site in Michigan, we tested the effectiveness of our model-resolved parameters in predicting the frictional velocity over heterogeneous and disturbed canopies. We compared it with three other semi-empirical models and with a decade of meteorological observations. We found that parameterizations with fixed representations of roughness performed relatively well. Nonetheless, some empirical approaches that incorporate seasonal and inter-annual changes to the canopy structure performed even better than models with temporally fixed parameters.
Combined calibration and sensitivity analysis for a water quality model of the Biebrza River, Poland
Perk, van der M.; Bierkens, M.F.P.
1995-01-01
A study was performed to quantify the error in results of a water quality model of the Biebrza River, Poland, due to uncertainties in calibrated model parameters. The procedure used in this study combines calibration and sensitivity analysis. Finally,the model was validated to test the model capabil
Brink, C.v.d.; Zaadnoordijk, W.J.; Burgers, S.; Griffioen, J.
2008-01-01
Groundwater quality management relies more and more on models in recent years. These models are used to predict the risk of groundwater contamination for various land uses. This paper presents an assessment of uncertainties and sensitivities to input parameters for a regional model. The model had
Kavetski, D.; Clark, M. P.; Fenicia, F.
2011-12-01
Hydrologists often face sources of uncertainty that dwarf those normally encountered in many engineering and scientific disciplines. Especially when representing large scale integrated systems, internal heterogeneities such as stream networks, preferential flowpaths, vegetation, etc, are necessarily represented with a considerable degree of lumping. The inputs to these models are themselves often the products of sparse observational networks. Given the simplifications inherent in environmental models, especially lumped conceptual models, does it really matter how they are implemented? At the same time, given the complexities usually found in the response surfaces of hydrological models, increasingly sophisticated analysis methodologies are being proposed for sensitivity analysis, parameter calibration and uncertainty assessment. Quite remarkably, rather than being caused by the model structure/equations themselves, in many cases model analysis complexities are consequences of seemingly trivial aspects of the model implementation - often, literally, whether the start-of-step or end-of-step fluxes are used! The extent of problems can be staggering, including (i) degraded performance of parameter optimization and uncertainty analysis algorithms, (ii) erroneous and/or misleading conclusions of sensitivity analysis, parameter inference and model interpretations and, finally, (iii) poor reliability of a calibrated model in predictive applications. While the often nontrivial behavior of numerical approximations has long been recognized in applied mathematics and in physically-oriented fields of environmental sciences, it remains a problematic issue in many environmental modeling applications. Perhaps detailed attention to numerics is only warranted for complicated engineering models? Would not numerical errors be an insignificant component of total uncertainty when typical data and model approximations are present? Is this really a serious issue beyond some rare isolated
Impact of the hard-coded parameters on the hydrologic fluxes of the land surface model Noah-MP
Cuntz, Matthias; Mai, Juliane; Samaniego, Luis; Clark, Martyn; Wulfmeyer, Volker; Attinger, Sabine; Thober, Stephan
2016-04-01
Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The process descriptions contain a number of parameters that can be soil or plant type dependent and are typically read from tabulated input files. Land surface models may have, however, process descriptions that contain fixed, hard-coded numbers in the computer code, which are not identified as model parameters. Here we searched for hard-coded parameters in the computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the importance of the fixed values on restricting the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options, which are mostly spatially constant values. This is in addition to the 71 standard parameters of Noah-MP, which mostly get distributed spatially by given vegetation and soil input maps. We performed a Sobol' global sensitivity analysis of Noah-MP to variations of the standard and hard-coded parameters for a specific set of process options. 42 standard parameters and 75 hard-coded parameters were active with the chosen process options. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated. These sensitivities were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's hydrologic output fluxes are sensitive to two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for evaporation, which proved to be oversensitive in other land surface models as well. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs. These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the
Modelling survival: exposure pattern, species sensitivity and uncertainty.
Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B; Van den Brink, Paul J; Veltman, Karin; Vogel, Sören; Zimmer, Elke I; Preuss, Thomas G
2016-07-06
The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.
Modelling survival: exposure pattern, species sensitivity and uncertainty
Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I.; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B.; van den Brink, Paul J.; Veltman, Karin; Vogel, Sören; Zimmer, Elke I.; Preuss, Thomas G.
2016-07-01
The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.
Yi, S; Oemler, A E; Yi, Sukyoung; Demarque, Pierre; Oemler, Augustus
1997-01-01
We present models of the late stages of stellar evolution intended to explain the UV upturn phenomenon in elliptical galaxies. Such models are sensitive to values of a number of poorly-constrained physical parameters, including metallicity, age, stellar mass loss, helium enrichment, and the distribution of stars on the zero age horizontal branch (HB). We explore the sensitivity of the results to values of these parameters, and reach the following conclusions. Old, metal rich galaxies, such as giant ellipticals, naturally develop a UV upturn within a reasonable time scale - less than a Hubble time - without the presence of young stars. The most likely stars to dominate the UV flux of such populations are low mass, core helium burning (HB and evolved HB) stars. Metal-poor populations produce a higher ratio of UV-to-V flux, due to opacity effects, but only metal-rich stars develop a UV upturn, in which the flux increases towards shorter UV wavelengths. Model color-magnitude diagrams and corresponding integrated ...
A Sensitivity Analysis of fMRI Balloon Model
Zayane, Chadia
2015-04-22
Functional magnetic resonance imaging (fMRI) allows the mapping of the brain activation through measurements of the Blood Oxygenation Level Dependent (BOLD) contrast. The characterization of the pathway from the input stimulus to the output BOLD signal requires the selection of an adequate hemodynamic model and the satisfaction of some specific conditions while conducting the experiment and calibrating the model. This paper, focuses on the identifiability of the Balloon hemodynamic model. By identifiability, we mean the ability to estimate accurately the model parameters given the input and the output measurement. Previous studies of the Balloon model have somehow added knowledge either by choosing prior distributions for the parameters, freezing some of them, or looking for the solution as a projection on a natural basis of some vector space. In these studies, the identification was generally assessed using event-related paradigms. This paper justifies the reasons behind the need of adding knowledge, choosing certain paradigms, and completing the few existing identifiability studies through a global sensitivity analysis of the Balloon model in the case of blocked design experiment.
Structure-activity models for contact sensitization.
Fedorowicz, Adam; Singh, Harshinder; Soderholm, Sidney; Demchuk, Eugene
2005-06-01
Allergic contact dermatitis (ACD) is a widespread cause of workers' disabilities. Although some substances found in the workplace are rigorously tested, the potential of the vast majority of chemicals to cause skin sensitization remains unknown. At the same time, exhaustive testing of all chemicals in workplaces is costly and raises ethical concerns. New approaches to developing information for risk assessment based on computational (quantitative) structure-activity relationship [(Q)SAR] methods may be complementary to and reduce the need for animal testing. Virtually any number of existing, de novo, and even preconceived compounds can be screened in silico at a fraction of the cost of animal testing. This work investigates the utility of ACD (Q)SAR modeling from the occupational health perspective using two leading software products, DEREK for Windows and TOPKAT, and an original method based on logistic regression methodology. It is found that the correct classification of (Q)SAR predictions for guinea pig data achieves values of 73.3, 82.9, and 87.6% for TOPKAT, DEREK for Windows, and the logistic regression model, respectively. The correct classification using LLNA data equals 73.0 and 83.2% for DEREK for Windows and the logistic regression model, respectively.
Leue, Anja; Beauducel, André
2008-11-01
J. A. Gray's Reinforcement Sensitivity Theory (RST) has produced a wealth of quasi-experimental studies in more than 35 years of research on personality and reinforcement sensitivity. The present meta-analysis builds on this literature by investigating RST in conflict and nonconflict reinforcement tasks in humans. Based on random-effects meta-analysis, we confirmed RST predictions of performance parameters (e.g., number of responses, reaction time) in reinforcement tasks for impulsivity- and anxiety-related traits. In studies on anxiety-related traits, the effect size variance was smaller for conflict tasks than for nonconflict tasks. A larger mean effect size and a larger variability of effect sizes were found for conflict compared to nonconflict tasks in studies on impulsivity-related traits. Our results suggest that problems with RST confirmation in reinforcement tasks are at least partly caused by insufficient statistical power of primary studies, and thus, encourage future research on RST.
Energy Technology Data Exchange (ETDEWEB)
Dai, Heng [Pacific Northwest National Laboratory, Richland Washington USA; Chen, Xingyuan [Pacific Northwest National Laboratory, Richland Washington USA; Ye, Ming [Department of Scientific Computing, Florida State University, Tallahassee Florida USA; Song, Xuehang [Pacific Northwest National Laboratory, Richland Washington USA; Zachara, John M. [Pacific Northwest National Laboratory, Richland Washington USA
2017-05-01
Sensitivity analysis is an important tool for quantifying uncertainty in the outputs of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a hierarchical sensitivity analysis method that (1) constructs an uncertainty hierarchy by analyzing the input uncertainty sources, and (2) accounts for the spatial correlation among parameters at each level of the hierarchy using geostatistical tools. The contribution of uncertainty source at each hierarchy level is measured by sensitivity indices calculated using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport in model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally as driven by the dynamic interaction between groundwater and river water at the site. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed parameters.
Directory of Open Access Journals (Sweden)
Gesine Flehmig
Full Text Available In obesity, elevated fat mass and ectopic fat accumulation are associated with changes in adipokine secretion, which may link obesity to inflammation and the development of insulin resistance. However, relationships among individual adipokines and between adipokines and parameters of obesity, glucose metabolism or inflammation are largely unknown. Serum concentrations of 20 adipokines were measured in 141 Caucasian obese men (n = 67 and women (n = 74 with a wide range of body weight, glycemia and insulin sensitivity. Unbiased, distance-based hierarchical cluster analyses were performed to recognize patterns among adipokines and their relationship with parameters of obesity, glucose metabolism, insulin sensitivity and inflammation. We identified two major adipokine clusters related to either (1 body fat mass and inflammation (leptin, ANGPTL3, DLL1, chemerin, Nampt, resistin or insulin sensitivity/hyperglycemia, and lipid metabolism (vaspin, clusterin, glypican 4, progranulin, ANGPTL6, GPX3, RBP4, DLK1, SFRP5, BMP7, adiponectin, CTRP3 and 5, omentin. In addition, we found distinct adipokine clusters in subgroups of patients with or without type 2 diabetes (T2D. Logistic regression analyses revealed ANGPTL6, DLK1, Nampt and progranulin as strongest adipokine correlates of T2D in obese individuals. The panel of 20 adipokines predicted T2D compared to a combination of HbA1c, HOMA-IR and fasting plasma glucose with lower sensitivity (78% versus 91% and specificity (76% versus 94%. Therefore, adipokine patterns may currently not be clinically useful for the diagnosis of metabolic diseases. Whether adipokine patterns are relevant for the predictive assessment of intervention outcomes needs to be further investigated.
Directory of Open Access Journals (Sweden)
Yun-ah Han
2013-03-01
Full Text Available The effects of structural design parameters on the performance of nano-replicated photonic crystal (PC label-free biosensors were examined by the analysis of simulated reflection spectra of PC structures. The grating pitch, duty, scaled grating height and scaled TiO2 layer thickness were selected as the design factors to optimize the PC structure. The peak wavelength value (PWV, full width at half maximum of the peak, figure of merit for the bulk and surface sensitivities, and surface/bulk sensitivity ratio were also selected as the responses to optimize the PC label-free biosensor performance. A parametric study showed that the grating pitch was the dominant factor for PWV, and that it had low interaction effects with other scaled design factors. Therefore, we can isolate the effect of grating pitch using scaled design factors. For the design of PC-label free biosensor, one should consider that: (1 the PWV can be measured by the reflection peak measurement instruments, (2 the grating pitch and duty can be manufactured using conventional lithography systems, and (3 the optimum design is less sensitive to the grating height and TiO2 layer thickness variations in the fabrication process. In this paper, we suggested a design guide for highly sensitive PC biosensor in which one select the grating pitch and duty based on the limitations of the lithography and measurement system, and conduct a multi objective optimization of the grating height and TiO2 layer thickness for maximizing performance and minimizing the influence of parameter variation. Through multi-objective optimization of a PC structure with a fixed grating height of 550 nm and a duty of 50%, we obtained a surface FOM of 66.18 RIU−1 and an S/B ratio of 34.8%, with a grating height of 117 nm and TiO2 height of 210 nm.
Parameter and Uncertainty Estimation in Groundwater Modelling
DEFF Research Database (Denmark)
Jensen, Jacob Birk
The data basis on which groundwater models are constructed is in general very incomplete, and this leads to uncertainty in model outcome. Groundwater models form the basis for many, often costly decisions and if these are to be made on solid grounds, the uncertainty attached to model results must...... be quantified. This study was motivated by the need to estimate the uncertainty involved in groundwater models.Chapter 2 presents an integrated surface/subsurface unstructured finite difference model that was developed and applied to a synthetic case study.The following two chapters concern calibration...... and uncertainty estimation. Essential issues relating to calibration are discussed. The classical regression methods are described; however, the main focus is on the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. The next two chapters describe case studies in which the GLUE methodology...
DEFF Research Database (Denmark)
Bjerg, Poul Løgstrup; Rügge, Kirsten; Pedersen, Jørn K.;
1995-01-01
, dinitrogen oxide, nitrite, nitrate, and oxygen in the groundwater samples indicate that methane production, sulfate reduction, iron reduction, manganese reduction, and nitrate reduction take place in the plume. Adjacent to the landfill, methanogenic and sulfatereducing zones were identified, while aerobic......The leachate plume stretching 300 m downgradient from the Grindsted Landfill (Denmark) has been characterized in terms of redox-sensitive groundwater quality parameters along two longitudinal transects (285 samples). Variations in the levels of methane, sulfide, iron(ll), manganese(ll), ammonium...
The impact of Ag nanoparticles on the parameters of DSS- cells sensitized by Z907
Ibrayev, N. Kh; Aimukhanov, A. K.; Zeinidenov, A. K.
2016-02-01
Research of influence of Ag nanoparticles are in-process undertaken on absorption and on parameters CVC DSS-cells sensitized Z907. It is set that with the height of concentration Ag nanoparticles in tape to the concentration of 0.3% wt%. the absorbance of Z907 in a short-wave stripe grew to the value 1,6. It is set that under reaching the concentration of Ag nanoparticles in the cell of value the 0.3% wt%. efficiency of cell increased to 2.2%.
Fernández-Pato, Javier; Caviedes-Voullième, Daniel; García-Navarro, Pilar
2016-05-01
One of the most difficult issues in the development of hydrologic models is to find a rigorous source of data and specific parameters to a given problem, on a given location that enable reliable calibration. In this paper, a distributed and physically based model (2D Shallow Water Equations) is used for surface flow and runoff calculations in combination with two infiltration laws (Horton and Green-Ampt) for estimating infiltration in a watershed. This technique offers the capability of assigning a local and time-dependent infiltration rate to each computational cell depending on the available surface water, soil type or vegetation. We investigate how the calibration of parameters is affected by transient distributed Shallow Water model and the complexity of the problem. In the first part of this work, we calibrate the infiltration parameters for both Horton and Green-Ampt models under flat ponded soil conditions. Then, by means of synthetic test cases, we perform a space-distributed sensitivity analysis in order to show that this calibration can be significantly affected by the introduction of topography or rainfall. In the second part, parameter calibration for a real catchment is addressed by comparing the numerical simulations with two different sets of experimental data, corresponding to very different events in terms of the rainfall volume. We show that the initial conditions of the catchment and the rainfall pattern have a special relevance in the quality of the adjustment. Hence, it is shown that the topography of the catchment and the storm characteristics affect the calibration of infiltration parameters.
Parameter redundancy in discrete state‐space and integrated models
McCrea, Rachel S.
2016-01-01
Discrete state‐space models are used in ecology to describe the dynamics of wild animal populations, with parameters, such as the probability of survival, being of ecological interest. For a particular parametrization of a model it is not always clear which parameters can be estimated. This inability to estimate all parameters is known as parameter redundancy or a model is described as nonidentifiable. In this paper we develop methods that can be used to detect parameter redundancy in discrete state‐space models. An exhaustive summary is a combination of parameters that fully specify a model. To use general methods for detecting parameter redundancy a suitable exhaustive summary is required. This paper proposes two methods for the derivation of an exhaustive summary for discrete state‐space models using discrete analogues of methods for continuous state‐space models. We also demonstrate that combining multiple data sets, through the use of an integrated population model, may result in a model in which all parameters are estimable, even though models fitted to the separate data sets may be parameter redundant. PMID:27362826
Parameter redundancy in discrete state-space and integrated models.
Cole, Diana J; McCrea, Rachel S
2016-09-01
Discrete state-space models are used in ecology to describe the dynamics of wild animal populations, with parameters, such as the probability of survival, being of ecological interest. For a particular parametrization of a model it is not always clear which parameters can be estimated. This inability to estimate all parameters is known as parameter redundancy or a model is described as nonidentifiable. In this paper we develop methods that can be used to detect parameter redundancy in discrete state-space models. An exhaustive summary is a combination of parameters that fully specify a model. To use general methods for detecting parameter redundancy a suitable exhaustive summary is required. This paper proposes two methods for the derivation of an exhaustive summary for discrete state-space models using discrete analogues of methods for continuous state-space models. We also demonstrate that combining multiple data sets, through the use of an integrated population model, may result in a model in which all parameters are estimable, even though models fitted to the separate data sets may be parameter redundant. © 2016 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Sman, van der R.G.M.; Willigenburg, van G.; Vollebregt, H.M.; Eisner, V.; Mepschen, A.
2015-01-01
A first principles microfiltration model based on shear-induced diffusion is compared to experiments performed on the clarification of beer. After performing an identifiability and sensitivity analysis, the model parameters are estimated using global minimization of the sum of least squares. The
An automatic and effective parameter optimization method for model tuning
Directory of Open Access Journals (Sweden)
T. Zhang
2015-11-01
simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.
Ney, Michael; Abdulhalim, Ibrahim
2016-03-01
Skin cancer detection at its early stages has been the focus of a large number of experimental and theoretical studies during the past decades. Among these studies two prominent approaches presenting high potential are reflectometric sensing at the THz wavelengths region and polarimetric imaging techniques in the visible wavelengths. While THz radiation contrast agent and source of sensitivity to cancer related tissue alterations was considered to be mainly the elevated water content in the cancerous tissue, the polarimetric approach has been verified to enable cancerous tissue differentiation based on cancer induced structural alterations to the tissue. Combining THz with the polarimetric approach, which is considered in this study, is examined in order to enable higher detection sensitivity than previously pure reflectometric THz measurements. For this, a comprehensive MC simulation of radiative transfer in a complex skin tissue model fitted for the THz domain that considers the skin`s stratified structure, tissue material optical dispersion modeling, surface roughness, scatterers, and substructure organelles has been developed. Additionally, a narrow beam Mueller matrix differential analysis technique is suggested for assessing skin cancer induced changes in the polarimetric image, enabling the tissue model and MC simulation to be utilized for determining the imaging parameters resulting in maximal detection sensitivity.
Seddigi, Zaki S.; Ahmed, Saleh A.; Sardar, Samim; Pal, Samir Kumar
2016-03-01
Four key parameters namely light trapping, density of light harvesting centre, photoinduced electron injection and electron transport without self-recombination are universally important across all kinds of solar cells. In the present study, we have considered the parameters in the context of a model Dye Sensitized Solar Cell (DSSC). Our experimental studies reveal that carbonate doping of TiO2 mesoporous microspheres (doped MS) makes positive influence to all the above mentioned key parameters responsible for the enhanced solar cell efficiency. A simple method has been employed to synthesize the doped MS for the photoanode of a N719 (ruthenium dye)-based DSSC. A detail electron microscopy has been used to characterize the change in morphology of the MS upon doping. The optical absorption spectrum of the doped MS reveals significant shift of TiO2 (compared to that of the MS without doping) towards maximum solar radiance (~500 nm) and the excellent scattering in the entire absorption band of the sensitizing dye (N719). Finally, and most importantly, for the first time we have demonstrated that the solar cells with doped MS offers better efficiency (7.6%) in light harvesting compared to MS without doping (5.2%) and also reveal minimum self recombination of photoelectrons in the redox chain.
Ternary interaction parameters in calphad solution models
Energy Technology Data Exchange (ETDEWEB)
Eleno, Luiz T.F., E-mail: luizeleno@usp.br [Universidade de Sao Paulo (USP), SP (Brazil). Instituto de Fisica; Schön, Claudio G., E-mail: schoen@usp.br [Universidade de Sao Paulo (USP), SP (Brazil). Computational Materials Science Laboratory. Department of Metallurgical and Materials Engineering
2014-07-01
For random, diluted, multicomponent solutions, the excess chemical potentials can be expanded in power series of the composition, with coefficients that are pressure- and temperature-dependent. For a binary system, this approach is equivalent to using polynomial truncated expansions, such as the Redlich-Kister series for describing integral thermodynamic quantities. For ternary systems, an equivalent expansion of the excess chemical potentials clearly justifies the inclusion of ternary interaction parameters, which arise naturally in the form of correction terms in higher-order power expansions. To demonstrate this, we carry out truncated polynomial expansions of the excess chemical potential up to the sixth power of the composition variables. (author)
Razavi, S.; Gupta, H. V.
2014-12-01
Sensitivity analysis (SA) is an important paradigm in the context of Earth System model development and application, and provides a powerful tool that serves several essential functions in modelling practice, including 1) Uncertainty Apportionment - attribution of total uncertainty to different uncertainty sources, 2) Assessment of Similarity - diagnostic testing and evaluation of similarities between the functioning of the model and the real system, 3) Factor and Model Reduction - identification of non-influential factors and/or insensitive components of model structure, and 4) Factor Interdependence - investigation of the nature and strength of interactions between the factors, and the degree to which factors intensify, cancel, or compensate for the effects of each other. A variety of sensitivity analysis approaches have been proposed, each of which formally characterizes a different "intuitive" understanding of what is meant by the "sensitivity" of one or more model responses to its dependent factors (such as model parameters or forcings). These approaches are based on different philosophies and theoretical definitions of sensitivity, and range from simple local derivatives and one-factor-at-a-time procedures to rigorous variance-based (Sobol-type) approaches. In general, each approach focuses on, and identifies, different features and properties of the model response and may therefore lead to different (even conflicting) conclusions about the underlying sensitivity. This presentation revisits the theoretical basis for sensitivity analysis, and critically evaluates existing approaches so as to demonstrate their flaws and shortcomings. With this background, we discuss several important properties of response surfaces that are associated with the understanding and interpretation of sensitivity. Finally, a new approach towards global sensitivity assessment is developed that is consistent with important properties of Earth System model response surfaces.
Wentworth, Mami Tonoe
techniques for model calibration. For Bayesian model calibration, we employ adaptive Metropolis algorithms to construct densities for input parameters in the heat model and the HIV model. To quantify the uncertainty in the parameters, we employ two MCMC algorithms: Delayed Rejection Adaptive Metropolis (DRAM) [33] and Differential Evolution Adaptive Metropolis (DREAM) [66, 68]. The densities obtained using these methods are compared to those obtained through the direct numerical evaluation of the Bayes' formula. We also combine uncertainties in input parameters and measurement errors to construct predictive estimates for a model response. A significant emphasis is on the development and illustration of techniques to verify the accuracy of sampling-based Metropolis algorithms. We verify the accuracy of DRAM and DREAM by comparing chains, densities and correlations obtained using DRAM, DREAM and the direct evaluation of Bayes formula. We also perform similar analysis for credible and prediction intervals for responses. Once the parameters are estimated, we employ energy statistics test [63, 64] to compare the densities obtained by different methods for the HIV model. The energy statistics are used to test the equality of distributions. We also consider parameter selection and verification techniques for models having one or more parameters that are noninfluential in the sense that they minimally impact model outputs. We illustrate these techniques for a dynamic HIV model but note that the parameter selection and verification framework is applicable to a wide range of biological and physical models. To accommodate the nonlinear input to output relations, which are typical for such models, we focus on global sensitivity analysis techniques, including those based on partial correlations, Sobol indices based on second-order model representations, and Morris indices, as well as a parameter selection technique based on standard errors. A significant objective is to provide
Time-dependent global sensitivity analysis with active subspaces for a lithium ion battery model
Constantine, Paul G
2016-01-01
Renewable energy researchers use computer simulation to aid the design of lithium ion storage devices. The underlying models contain several physical input parameters that affect model predictions. Effective design and analysis must understand the sensitivity of model predictions to changes in model parameters, but global sensitivity analyses become increasingly challenging as the number of input parameters increases. Active subspaces are part of an emerging set of tools to reveal and exploit low-dimensional structures in the map from high-dimensional inputs to model outputs. We extend a linear model-based heuristic for active subspace discovery to time-dependent processes and apply the resulting technique to a lithium ion battery model. The results reveal low-dimensional structure that a designer may exploit to efficiently study the relationship between parameters and predictions.
Sensitivity of NTCP parameter values against a change of dose calculation algorithm
DEFF Research Database (Denmark)
Brink, Carsten; Berg, Martin; Nielsen, Morten
2007-01-01
with a collapsed cone algorithm (CC) to compare the NTCP estimates for radiation pneumonitis with those obtained from the clinically used pencil beam algorithm (PB). For the PB calculations the NTCP parameters were taken from previously published values for three different models. For the CC calculations...
Fragoso, Wallace; Allegrini, Franco; Olivieri, Alejandro C
2016-08-24
Generalized analytical sensitivity (γ) is proposed as a new figure of merit, which can be estimated from a multivariate calibration data set. It can be confidently applied to compare different calibration methodologies, and helps to solve literature inconsistencies on the relationship between classical sensitivity and prediction error. In contrast to the classical plain sensitivity, γ incorporates the noise properties in its definition, and its inverse is well correlated with root mean square errors of prediction in the presence of general noise structures. The proposal is supported by studying simulated and experimental first-order multivariate calibration systems with various models, namely multiple linear regression, principal component regression (PCR) and maximum likelihood PCR (MLPCR). The simulations included instrumental noise of different types: independently and identically distributed (iid), correlated (pink) and proportional noise, while the experimental data carried noise which is clearly non-iid.
Parameter estimation and error analysis in environmental modeling and computation
Kalmaz, E. E.
1986-01-01
A method for the estimation of parameters and error analysis in the development of nonlinear modeling for environmental impact assessment studies is presented. The modular computer program can interactively fit different nonlinear models to the same set of data, dynamically changing the error structure associated with observed values. Parameter estimation techniques and sequential estimation algorithms employed in parameter identification and model selection are first discussed. Then, least-square parameter estimation procedures are formulated, utilizing differential or integrated equations, and are used to define a model for association of error with experimentally observed data.
Directory of Open Access Journals (Sweden)
Jonathan R Karr
2015-05-01
Full Text Available Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.
Parameter estimation of hydrologic models using data assimilation
Kaheil, Y. H.
2005-12-01
The uncertainties associated with the modeling of hydrologic systems sometimes demand that data should be incorporated in an on-line fashion in order to understand the behavior of the system. This paper represents a Bayesian strategy to estimate parameters for hydrologic models in an iterative mode. The paper presents a modified technique called localized Bayesian recursive estimation (LoBaRE) that efficiently identifies the optimum parameter region, avoiding convergence to a single best parameter set. The LoBaRE methodology is tested for parameter estimation for two different types of models: a support vector machine (SVM) model for predicting soil moisture, and the Sacramento Soil Moisture Accounting (SAC-SMA) model for estimating streamflow. The SAC-SMA model has 13 parameters that must be determined. The SVM model has three parameters. Bayesian inference is used to estimate the best parameter set in an iterative fashion. This is done by narrowing the sampling space by imposing uncertainty bounds on the posterior best parameter set and/or updating the "parent" bounds based on their fitness. The new approach results in fast convergence towards the optimal parameter set using minimum training/calibration data and evaluation of fewer parameter sets. The efficacy of the localized methodology is also compared with the previously used Bayesian recursive estimation (BaRE) algorithm.
GIS-Based Hydrogeological-Parameter Modeling
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
A regression model is proposed to relate the variation of water well depth with topographic properties (area and slope), the variation of hydraulic conductivity and vertical decay factor. The implementation of this model in GIS environment (ARC/TNFO) based on known water data and DEM is used to estimate the variation of hydraulic conductivity and decay factor of different lithoiogy units in watershed context.
Institute of Scientific and Technical Information of China (English)
Wei DUAN
2008-01-01
Many stochastic parameters have an effect on the reliability of a steam turbine blade during practical operation. To improve the reliability of blade design, it is necessary to take these stochastic parameters into account. An equal cross-section blade is investigated and a finite element model is built parametrically. Geometrical parameters, material parameters and load parameters of the blade are considered as input random variables while the maximum deflection and maximum equivalent stress are output random variables. Analysis file of the blade is compiled by deterministic finite element method and applied to be loop file to create sample points. A quadratic polynomial with cross terms is chosen to regress these samples by step-forward regression method and employed as a surrogate of numerical solver to drastically reduce the number of solvers call. Then, Monte Carlo method is used to obtain the statistical characteristics and cumulative distribution function of the maximum deflection and maximum equivalent stress of the blade. Probability sensitivity analysis, which combines the slope of the gradient and the width of the scatter range of the random input variables, is applied to evaluate how much the output parameters are influenced by the random input para-meters. The scatter plots of structural responses with respect to the random input variables are illustrated to analyze how to change the input random variables to improve the reliability of the blade. The results show that combination of the finite element method, the response surface method and Monte Carlo method is an ideal way for the reliability analysis and probability strength design of the blade.
Estimation of Kinetic Parameters in an Automotive SCR Catalyst Model
DEFF Research Database (Denmark)
Åberg, Andreas; Widd, Anders; Abildskov, Jens;
2016-01-01
A challenge during the development of models for simulation of the automotive Selective Catalytic Reduction catalyst is the parameter estimation of the kinetic parameters, which can be time consuming and problematic. The parameter estimation is often carried out on small-scale reactor tests, or p...
Mirror symmetry for two parameter models, 2
Candelas, Philip; Katz, S; Morrison, Douglas Robert Ogston; Philip Candelas; Anamaria Font; Sheldon Katz; David R Morrison
1994-01-01
We describe in detail the space of the two K\\"ahler parameters of the Calabi--Yau manifold \\P_4^{(1,1,1,6,9)}[18] by exploiting mirror symmetry. The large complex structure limit of the mirror, which corresponds to the classical large radius limit, is found by studying the monodromy of the periods about the discriminant locus, the boundary of the moduli space corresponding to singular Calabi--Yau manifolds. A symplectic basis of periods is found and the action of the Sp(6,\\Z) generators of the modular group is determined. From the mirror map we compute the instanton expansion of the Yukawa couplings and the generalized N=2 index, arriving at the numbers of instantons of genus zero and genus one of each degree. We also investigate an SL(2,\\Z) symmetry that acts on a boundary of the moduli space.
Mockler, E. M.; O'Loughlin, F.; Bruen, M. P.
2013-12-01
Conceptual rainfall runoff (CRR) models aim to capture the dominant hydrological processes in a catchment in order to predict the flows in a river. Most flood forecasting models focus on predicting total outflows from a catchment and often perform well without the correct distribution between individual pathways. However, modelling of water flow paths within a catchment, rather than its overall response, is specifically needed to investigate the physical and chemical transport of matter through the various elements of the hydrological cycle. Focus is increasingly turning to accurately quantifying the internal movement of water within these models to investigate if the simulated processes contributing to the total flows are realistic in the expectation of generating more robust models. Parameter regionalisation is required if such models are to be widely used, particularly in ungauged catchments. However, most regionalisation studies to date have typically consisted of calibrations and correlations of parameters with catchment characteristics, or some variations of this. In order for a priori parameter estimation in this manner to be possible, a model must be parametrically parsimonious while still capturing the dominant processes of the catchment. The presence of parameter interactions within most CRR model structures can make parameter prediction in ungauged basins very difficult, as the functional role of the parameter within the model may not be uniquely identifiable. We use a variance based sensitivity analysis method to investigate parameter sensitivities and interactions in the global parameter space of three CRR models, simulating a set of 30 Irish catchments within a variety of hydrological settings over a 16 year period. The exploration of sensitivities of internal flow path partitioning was a specific focus and correlations between catchment characteristics and parameter sensitivities were also investigated to assist in evaluating model performances
Techno-economic sensitivity study of heliostat field parameters for micro-gas turbine CSP
Landman, Willem A.; Gauché, Paul; Dinter, Frank; Myburgh, J. T.
2017-06-01
Concentrating solar power systems based on micro-gas turbines potentially offer numerous benefits should they become commercially viable. Heliostat fields for such systems have unique requirements in that the number of heliostats and the focal ratios are typically much lower than conventional central receiver systems. This paper presents a techno-economic sensitivity study of heliostat field parameters for a micro-gas turbine central receiver system. A 100 kWe minitower system is considered for the base case and a one-at-a-time strategy is used to investigate parameter sensitivities. Increasing heliostat focal ratios are found to have significant optical performance benefits due to both a reduction in astigmatic aberrations and a reduction in the number of facet focal lengths required; confirming the hypothesis that smaller heliostats offer a techno-economic advantage. Fixed Horizontal Axis tracking mechanism is shown to outperform the conventional Azimuth Zenith tracking mechanism in high density heliostat fields. Although several improvements to heliostat field performance are discussed, the capex fraction of the heliostat field for such system is shown to be almost half that of a conventional central receiver system and optimum utilization of the higher capex components, namely; the receiver and turbine subsystems, are more rewarding than that of the heliostat field.
Accuracy of Parameter Estimation in Gibbs Sampling under the Two-Parameter Logistic Model.
Kim, Seock-Ho; Cohen, Allan S.
The accuracy of Gibbs sampling, a Markov chain Monte Carlo procedure, was considered for estimation of item and ability parameters under the two-parameter logistic model. Memory test data were analyzed to illustrate the Gibbs sampling procedure. Simulated data sets were analyzed using Gibbs sampling and the marginal Bayesian method. The marginal…
Bailer-Jones, C A L
2009-01-01
I introduce an algorithm for estimating parameters from multidimensional data based on forward modelling. In contrast to many machine learning approaches it avoids fitting an inverse model and the problems associated with this. The algorithm makes explicit use of the sensitivities of the data to the parameters, with the goal of better treating parameters which only have a weak impact on the data. The forward modelling approach provides uncertainty (full covariance) estimates in the predicted parameters as well as a goodness-of-fit for observations. I demonstrate the algorithm, ILIUM, with the estimation of stellar astrophysical parameters (APs) from simulations of the low resolution spectrophotometry to be obtained by Gaia. The AP accuracy is competitive with that obtained by a support vector machine. For example, for zero extinction stars covering a wide range of metallicity, surface gravity and temperature, ILIUM can estimate Teff to an accuracy of 0.3% at G=15 and to 4% for (lower signal-to-noise ratio) sp...
On linear models and parameter identifiability in experimental biological systems.
Lamberton, Timothy O; Condon, Nicholas D; Stow, Jennifer L; Hamilton, Nicholas A
2014-10-07
A key problem in the biological sciences is to be able to reliably estimate model parameters from experimental data. This is the well-known problem of parameter identifiability. Here, methods are developed for biologists and other modelers to design optimal experiments to ensure parameter identifiability at a structural level. The main results of the paper are to provide a general methodology for extracting parameters of linear models from an experimentally measured scalar function - the transfer function - and a framework for the identifiability analysis of complex model structures using linked models. Linked models are composed by letting the output of one model become the input to another model which is then experimentally measured. The linked model framework is shown to be applicable to designing experiments to identify the measured sub-model and recover the input from the unmeasured sub-model, even in cases that the unmeasured sub-model is not identifiable. Applications for a set of common model features are demonstrated, and the results combined in an example application to a real-world experimental system. These applications emphasize the insight into answering "where to measure" and "which experimental scheme" questions provided by both the parameter extraction methodology and the linked model framework. The aim is to demonstrate the tools' usefulness in guiding experimental design to maximize parameter information obtained, based on the model structure.
Institute of Scientific and Technical Information of China (English)
王永龙; 潘毅群
2014-01-01
The calibration methods and procedures of building energy simulation are briefly summa-rized, as well as the application and effect of sensitivity analysis during calibration. The software e-QUEST3-64 is utilized to establish an energy model of prototypical office building. A series of single factor sensitivity analysis is obtained about these input parameters from the envelope of the structure, internal loads and HVAC systems. Through analyzing the results of dynamic simulation for the whole year, the lev-els of sensitivity for all input parameters are compared, not only to provide a basis for calibration of exist-ing office building energy simulation, but also to point out the emphasis of energy-saving designs of new buildings and retrofitting of existing buildings by selecting the parameters which are the most significant and suitable.%简要概括了建筑能耗模拟的校验方法与步骤，以及敏感性分析在校验模拟中的应用方法和意义。办公建筑的建筑和设备系统模型采用eQUEST3-64建立，单因子敏感性分析涉及3个方面的模型输入参数，包括建筑围护结构参数、建筑内部负荷参数以及空调系统参数。通过全年的动态模拟结果分析，指出和比较各个输入参数的敏感性大小，为已有办公类型建筑能耗模型的校验提供依据，也相应的指出了新建建筑节能设计或既有建筑节能改造的重点，为建筑节能设计和节能改造所需参数的选取提供依据。
Naujokaitis-Lewis, Ilona R; Curtis, Janelle M R; Arcese, Peter; Rosenfeld, Jordan
2009-02-01
Population viability analysis (PVA) is an effective framework for modeling species- and habitat-recovery efforts, but uncertainty in parameter estimates and model structure can lead to unreliable predictions. Integrating complex and often uncertain information into spatial PVA models requires that comprehensive sensitivity analyses be applied to explore the influence of spatial and nonspatial parameters on model predictions. We reviewed 87 analyses of spatial demographic PVA models of plants and animals to identify common approaches to sensitivity analysis in recent publications. In contrast to best practices recommended in the broader modeling community, sensitivity analyses of spatial PVAs were typically ad hoc, inconsistent, and difficult to compare. Most studies applied local approaches to sensitivity analyses, but few varied multiple parameters simultaneously. A lack of standards for sensitivity analysis and reporting in spatial PVAs has the potential to compromise the ability to learn collectively from PVA results, accurately interpret results in cases where model relationships include nonlinearities and interactions, prioritize monitoring and management actions, and ensure conservation-planning decisions are robust to uncertainties in spatial and nonspatial parameters. Our review underscores the need to develop tools for global sensitivity analysis and apply these to spatial PVA.
Supplementary Material for: A global sensitivity analysis approach for morphogenesis models
Boas, Sonja
2015-01-01
Abstract Background Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such ‘black-box’ models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. Results To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. Conclusions We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all ‘black-box’ models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.
Uniqueness, scale, and resolution issues in groundwater model parameter identification
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Tian-chyi J. Yeh
2015-07-01
Full Text Available This paper first visits uniqueness, scale, and resolution issues in groundwater flow forward modeling problems. It then makes the point that non-unique solutions to groundwater flow inverse problems arise from a lack of information necessary to make the problems well defined. Subsequently, it presents the necessary conditions for a well-defined inverse problem. They are full specifications of (1 flux boundaries and sources/sinks, and (2 heads everywhere in the domain at at least three times (one of which is t = 0, with head change everywhere at those times must being nonzero for transient flow. Numerical experiments are presented to corroborate the fact that, once the necessary conditions are met, the inverse problem has a unique solution. We also demonstrate that measurement noise, instability, and sensitivity are issues related to solution techniques rather than the inverse problems themselves. In addition, we show that a mathematically well-defined inverse problem, based on an equivalent homogeneous or a layered conceptual model, may yield physically incorrect and scenario-dependent parameter values. These issues are attributed to inconsistency between the scale of the head observed and that implied by these models. Such issues can be reduced only if a sufficiently large number of observation wells are used in the equivalent homogeneous domain or each layer. With a large number of wells, we then show that increase in parameterization can lead to a higher-resolution depiction of heterogeneity if an appropriate inverse methodology is used. Furthermore, we illustrate that, using the same number of wells, a highly parameterized model in conjunction with hydraulic tomography can yield better characterization of the aquifer and minimize the scale and scenario-dependent problems. Lastly, benefits of the highly parameterized model and hydraulic tomography are tested according to their ability to improve predictions of aquifer responses induced by
Global sensitivity analysis applied to drying models for one or a population of granules
DEFF Research Database (Denmark)
Mortier, Severine Therese F. C.; Gernaey, Krist; Thomas, De Beer;
2014-01-01
compared to our earlier work. beta(2) was found to be the most important factor for the single particle model which is useful information when performing model calibration. For the PBM-model, the granule radius and gas temperature were found to be most sensitive. The former indicates that granulator......The development of mechanistic models for pharmaceutical processes is of increasing importance due to a noticeable shift toward continuous production in the industry. Sensitivity analysis is a powerful tool during the model building process. A global sensitivity analysis (GSA), exploring...... sensitivity in a broad parameter space, is performed to detect the most sensitive factors in two models, that is, one for drying of a single granule and one for the drying of a population of granules [using population balance model (PBM)], which was extended by including the gas velocity as extra input...
Sensitivity analysis of numerical model of prestressed concrete containment
Energy Technology Data Exchange (ETDEWEB)
Bílý, Petr, E-mail: petr.bily@fsv.cvut.cz; Kohoutková, Alena, E-mail: akohout@fsv.cvut.cz
2015-12-15
Graphical abstract: - Highlights: • FEM model of prestressed concrete containment with steel liner was created. • Sensitivity analysis of changes in geometry and loads was conducted. • Steel liner and temperature effects are the most important factors. • Creep and shrinkage parameters are essential for the long time analysis. • Prestressing schedule is a key factor in the early stages. - Abstract: Safety is always the main consideration in the design of containment of nuclear power plant. However, efficiency of the design process should be also taken into consideration. Despite the advances in computational abilities in recent years, simplified analyses may be found useful for preliminary scoping or trade studies. In the paper, a study on sensitivity of finite element model of prestressed concrete containment to changes in geometry, loads and other factors is presented. Importance of steel liner, reinforcement, prestressing process, temperature changes, nonlinearity of materials as well as density of finite elements mesh is assessed in the main stages of life cycle of the containment. Although the modeling adjustments have not produced any significant changes in computation time, it was found that in some cases simplified modeling process can lead to significant reduction of work time without degradation of the results.
CHAMP: Changepoint Detection Using Approximate Model Parameters
2014-06-01
positions as a Markov chain in which the transition probabilities are defined by the time since the last changepoint: p(τi+1 = t|τi = s) = g(t− s), (1...experimentally verified using artifi- cially generated data and are compared to those of Fearnhead and Liu [5]. 2 Related work Hidden Markov Models (HMMs) are...length α, and maximum number of particles M . Output: Viterbi path of changepoint times and models // Initialize data structures 1: max path, prev queue
SENSITIVITY OF STRUCTURAL RESPONSE TO GROUND MOTION SOURCE AND SITE PARAMETERS.
Safak, Erdal; Brebbia, C.A.; Cakmak, A.S.; Abdel Ghaffar, A.M.
1985-01-01
Designing structures to withstand earthquakes requires an accurate estimation of the expected ground motion. While engineers use the peak ground acceleration (PGA) to model the strong ground motion, seismologists use physical characteristics of the source and the rupture mechanism, such as fault length, stress drop, shear wave velocity, seismic moment, distance, and attenuation. This study presents a method for calculating response spectra from seismological models using random vibration theory. It then investigates the effect of various source and site parameters on peak response. Calculations are based on a nonstationary stochastic ground motion model, which can incorporate all the parameters both in frequency and time domains. The estimation of the peak response accounts for the effects of the non-stationarity, bandwidth and peak correlations of the response.
Directory of Open Access Journals (Sweden)
Guang-zhou Chen
2015-01-01
Full Text Available Parameter identification plays a crucial role for simulating and using model. This paper firstly carried out the sensitivity analysis of the 2-chlorophenol oxidation model in supercritical water using the Monte Carlo method. Then, to address the nonlinearity of the model, two improved differential search (DS algorithms were proposed to carry out the parameter identification of the model. One strategy is to adopt the Latin hypercube sampling method to replace the uniform distribution of initial population; the other is to combine DS with simplex method. The results of sensitivity analysis reveal the sensitivity and the degree of difficulty identified for every model parameter. Furthermore, the posteriori probability distribution of parameters and the collaborative relationship between any two parameters can be obtained. To verify the effectiveness of the improved algorithms, the optimization performance of improved DS in kinetic parameter estimation is studied and compared with that of the basic DS algorithm, differential evolution, artificial bee colony optimization, and quantum-behaved particle swarm optimization. And the experimental results demonstrate that the DS with the Latin hypercube sampling method does not present better performance, while the hybrid methods have the advantages of strong global search ability and local search ability and are more effective than the other algorithms.
Energy Technology Data Exchange (ETDEWEB)
Dai, Heng [Pacific Northwest National Laboratory, Richland Washington USA; Ye, Ming [Department of Scientific Computing, Florida State University, Tallahassee Florida USA; Walker, Anthony P. [Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge Tennessee USA; Chen, Xingyuan [Pacific Northwest National Laboratory, Richland Washington USA
2017-04-01
Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averaging methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.
WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...
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[3, 9]. However, mainly due to the simplicity of Winkler's model in practical applications and .... this case, the coefficient B takes the dimension of a ... In plane-strain problems, the assumption of ... loaded circular region; s is the radial coordinate.
Schuhmann, Kai; Xu, Aimin; Schulte, Klaus-Martin; Simeonovic, Charmaine J.; Schwarz, Peter E. H.; Bornstein, Stefan R.; Shevchenko, Andrej; Graessler, Juergen
2016-01-01
Objective Glucolipotoxicity is a major pathophysiological mechanism in the development of insulin resistance and type 2 diabetes mellitus (T2D). We aimed to detect subtle changes in the circulating lipid profile by shotgun lipidomics analyses and to associate them with four different insulin sensitivity indices. Methods The cross-sectional study comprised 90 men with a broad range of insulin sensitivity including normal glucose tolerance (NGT, n = 33), impaired glucose tolerance (IGT, n = 32) and newly detected T2D (n = 25). Prior to oral glucose challenge plasma was obtained and quantitatively analyzed for 198 lipid molecular species from 13 different lipid classes including triacylglycerls (TAGs), phosphatidylcholine plasmalogen/ether (PC O-s), sphingomyelins (SMs), and lysophosphatidylcholines (LPCs). To identify a lipidomic signature of individual insulin sensitivity we applied three data mining approaches, namely least absolute shrinkage and selection operator (LASSO), Support Vector Regression (SVR) and Random Forests (RF) for the following insulin sensitivity indices: homeostasis model of insulin resistance (HOMA-IR), glucose insulin sensitivity index (GSI), insulin sensitivity index (ISI), and disposition index (DI). The LASSO procedure offers a high prediction accuracy and and an easier interpretability than SVR and RF. Results After LASSO selection, the plasma lipidome explained 3% (DI) to maximal 53% (HOMA-IR) variability of the sensitivity indexes. Among the lipid species with the highest positive LASSO regression coefficient were TAG 54:2 (HOMA-IR), PC O- 32:0 (GSI), and SM 40:3:1 (ISI). The highest negative regression coefficient was obtained for LPC 22:5 (HOMA-IR), TAG 51:1 (GSI), and TAG 58:6 (ISI). Conclusion Although a substantial part of lipid molecular species showed a significant correlation with insulin sensitivity indices we were able to identify a limited number of lipid metabolites of particular importance based on the LASSO approach. These
Improved Methodology for Parameter Inference in Nonlinear, Hydrologic Regression Models
Bates, Bryson C.
1992-01-01
A new method is developed for the construction of reliable marginal confidence intervals and joint confidence regions for the parameters of nonlinear, hydrologic regression models. A parameter power transformation is combined with measures of the asymptotic bias and asymptotic skewness of maximum likelihood estimators to determine the transformation constants which cause the bias or skewness to vanish. These optimized constants are used to construct confidence intervals and regions for the transformed model parameters using linear regression theory. The resulting confidence intervals and regions can be easily mapped into the original parameter space to give close approximations to likelihood method confidence intervals and regions for the model parameters. Unlike many other approaches to parameter transformation, the procedure does not use a grid search to find the optimal transformation constants. An example involving the fitting of the Michaelis-Menten model to velocity-discharge data from an Australian gauging station is used to illustrate the usefulness of the methodology.
A simulation of water pollution model parameter estimation
Kibler, J. F.
1976-01-01
A parameter estimation procedure for a water pollution transport model is elaborated. A two-dimensional instantaneous-release shear-diffusion model serves as representative of a simple transport process. Pollution concentration levels are arrived at via modeling of a remote-sensing system. The remote-sensed data are simulated by adding Gaussian noise to the concentration level values generated via the transport model. Model parameters are estimated from the simulated data using a least-squares batch processor. Resolution, sensor array size, and number and location of sensor readings can be found from the accuracies of the parameter estimates.
Sensitivity Analysis on the Reliability of an Offshore Winch Regarding Selected Gearbox Parameters
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Lothar Wöll
2017-04-01
Full Text Available To match the high expectations and demands of customers for long-lasting machines, the development of reliable products is crucial. Furthermore, for reasons of competitiveness, it is necessary to know the future product lifetime as accurately as possible to avoid over-dimensioning. Additionally, a more detailed system understanding enables the designer to influence the life expectancy of the product without performing an extensive amount of expensive and time-consuming tests. In early development stages of new equipment only very basic information about the future system design, like the ratio or the system structure, is available. Nevertheless, a reliable lifetime prediction of the system components and subsequently of the system itself is necessary to evaluate possible design alternatives and to identify critical components beforehand. Lifetime predictions, however, require many parameters, which are often not known in these early stages. Therefore, this paper performs a sensitivity analysis on the drivetrain of an offshore winch with active heave compensation for two typical load cases. The influences of the parameters gear center distance and ambient temperature are investigated by varying the parameters within typical ranges and evaluating the quantitative effect on the lifetime.
On retrial queueing model with fuzzy parameters
Ke, Jau-Chuan; Huang, Hsin-I.; Lin, Chuen-Horng
2007-01-01
This work constructs the membership functions of the system characteristics of a retrial queueing model with fuzzy customer arrival, retrial and service rates. The α-cut approach is used to transform a fuzzy retrial-queue into a family of conventional crisp retrial queues in this context. By means of the membership functions of the system characteristics, a set of parametric non-linear programs is developed to describe the family of crisp retrial queues. A numerical example is solved successfully to illustrate the validity of the proposed approach. Because the system characteristics are expressed and governed by the membership functions, more information is provided for use by management. By extending this model to the fuzzy environment, fuzzy retrial-queue is represented more accurately and analytic results are more useful for system designers and practitioners.
Solar parameters for modeling interplanetary background
Bzowski, M; Tokumaru, M; Fujiki, K; Quemerais, E; Lallement, R; Ferron, S; Bochsler, P; McComas, D J
2011-01-01
The goal of the Fully Online Datacenter of Ultraviolet Emissions (FONDUE) Working Team of the International Space Science Institute in Bern, Switzerland, was to establish a common calibration of various UV and EUV heliospheric observations, both spectroscopic and photometric. Realization of this goal required an up-to-date model of spatial distribution of neutral interstellar hydrogen in the heliosphere, and to that end, a credible model of the radiation pressure and ionization processes was needed. This chapter describes the solar factors shaping the distribution of neutral interstellar H in the heliosphere. Presented are the solar Lyman-alpha flux and the solar Lyman-alpha resonant radiation pressure force acting on neutral H atoms in the heliosphere, solar EUV radiation and the photoionization of heliospheric hydrogen, and their evolution in time and the still hypothetical variation with heliolatitude. Further, solar wind and its evolution with solar activity is presented in the context of the charge excha...
Linear Sigma Models With Strongly Coupled Phases -- One Parameter Models
Hori, Kentaro
2013-01-01
We systematically construct a class of two-dimensional $(2,2)$ supersymmetric gauged linear sigma models with phases in which a continuous subgroup of the gauge group is totally unbroken. We study some of their properties by employing a recently developed technique. The focus of the present work is on models with one K\\"ahler parameter. The models include those corresponding to Calabi-Yau threefolds, extending three examples found earlier by a few more, as well as Calabi-Yau manifolds of other dimensions and non-Calabi-Yau manifolds. The construction leads to predictions of equivalences of D-brane categories, systematically extending earlier examples. There is another type of surprise. Two distinct superconformal field theories corresponding to Calabi-Yau threefolds with different Hodge numbers, $h^{2,1}=23$ versus $h^{2,1}=59$, have exactly the same quantum K\\"ahler moduli space. The strong-weak duality plays a crucial r\\^ole in confirming this, and also is useful in the actual computation of the metric on t...
Siamphukdee, Kanjana; Collins, Frank; Zou, Roger
2013-06-01
Chloride-induced reinforcement corrosion is one of the major causes of premature deterioration in reinforced concrete (RC) structures. Given the high maintenance and replacement costs, accurate modeling of RC deterioration is indispensable for ensuring the optimal allocation of limited economic resources. Since corrosion rate is one of the major factors influencing the rate of deterioration, many predictive models exist. However, because the existing models use very different sets of input parameters, the choice of model for RC deterioration is made difficult. Although the factors affecting corrosion rate are frequently reported in the literature, there is no published quantitative study on the sensitivity of predicted corrosion rate to the various input parameters. This paper presents the results of the sensitivity analysis of the input parameters for nine selected corrosion rate prediction models. Three different methods of analysis are used to determine and compare the sensitivity of corrosion rate to various input parameters: (i) univariate regression analysis, (ii) multivariate regression analysis, and (iii) sensitivity index. The results from the analysis have quantitatively verified that the corrosion rate of steel reinforcement bars in RC structures is highly sensitive to corrosion duration time, concrete resistivity, and concrete chloride content. These important findings establish that future empirical models for predicting corrosion rate of RC should carefully consider and incorporate these input parameters.
Parameter identification in tidal models with uncertain boundaries
Bagchi, Arunabha; ten Brummelhuis, P.G.J.; ten Brummelhuis, Paul
1994-01-01
In this paper we consider a simultaneous state and parameter estimation procedure for tidal models with random inputs, which is formulated as a minimization problem. It is assumed that some model parameters are unknown and that the random noise inputs only act upon the open boundaries. The
Exploring the interdependencies between parameters in a material model.
Energy Technology Data Exchange (ETDEWEB)
Silling, Stewart Andrew; Fermen-Coker, Muge
2014-01-01
A method is investigated to reduce the number of numerical parameters in a material model for a solid. The basis of the method is to detect interdependencies between parameters within a class of materials of interest. The method is demonstrated for a set of material property data for iron and steel using the Johnson-Cook plasticity model.
An Alternative Three-Parameter Logistic Item Response Model.
Pashley, Peter J.
Birnbaum's three-parameter logistic function has become a common basis for item response theory modeling, especially within situations where significant guessing behavior is evident. This model is formed through a linear transformation of the two-parameter logistic function in order to facilitate a lower asymptote. This paper discusses an…
Parameter identification in tidal models with uncertain boundaries
Bagchi, Arunabha; Brummelhuis, ten Paul
1994-01-01
In this paper we consider a simultaneous state and parameter estimation procedure for tidal models with random inputs, which is formulated as a minimization problem. It is assumed that some model parameters are unknown and that the random noise inputs only act upon the open boundaries. The hyperboli
A compact cyclic plasticity model with parameter evolution
DEFF Research Database (Denmark)
Krenk, Steen; Tidemann, L.
2017-01-01
, and it is demonstrated that this simple formulation enables very accurate representation of experimental results. An extension of the theory to account for model parameter evolution effects, e.g. in the form of changing yield level, is included in the form of extended evolution equations for the model parameters...
Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds
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Indrajeet Chaubey
2010-11-01
Full Text Available There has been a steady shift towards modeling and model-based approaches as primary methods of assessing watershed response to hydrologic inputs and land management, and of quantifying watershed-wide best management practice (BMP effectiveness. Watershed models often require some degree of calibration and validation to achieve adequate watershed and therefore BMP representation. This is, however, only possible for gauged watersheds. There are many watersheds for which there are very little or no monitoring data available, thus the question as to whether it would be possible to extend and/or generalize model parameters obtained through calibration of gauged watersheds to ungauged watersheds within the same region. This study explored the possibility of developing regionalized model parameter sets for use in ungauged watersheds. The study evaluated two regionalization methods: global averaging, and regression-based parameters, on the SWAT model using data from priority watersheds in Arkansas. Resulting parameters were tested and model performance determined on three gauged watersheds. Nash-Sutcliffe efficiencies (NS for stream flow obtained using regression-based parameters (0.53–0.83 compared well with corresponding values obtained through model calibration (0.45–0.90. Model performance obtained using global averaged parameter values was also generally acceptable (0.4 ≤ NS ≤ 0.75. Results from this study indicate that regionalized parameter sets for the SWAT model can be obtained and used for making satisfactory hydrologic response predictions in ungauged watersheds.
NWP model forecast skill optimization via closure parameter variations
Järvinen, H.; Ollinaho, P.; Laine, M.; Solonen, A.; Haario, H.
2012-04-01
We present results of a novel approach to tune predictive skill of numerical weather prediction (NWP) models. These models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. The current practice is to specify manually the numerical parameter values, based on expert knowledge. We developed recently a concept and method (QJRMS 2011) for on-line estimation of the NWP model parameters via closure parameter variations. The method called EPPES ("Ensemble prediction and parameter estimation system") utilizes ensemble prediction infra-structure for parameter estimation in a very cost-effective way: practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating an ensemble of predictions so that each member uses different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In this presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an ensemble prediction system emulator, based on the ECHAM5 atmospheric GCM show that the model tuning capability of EPPES scales up to realistic models and ensemble prediction systems. Finally, preliminary results of EPPES in the context of ECMWF forecasting system are presented.
Bayesian estimation of parameters in a regional hydrological model
Directory of Open Access Journals (Sweden)
K. Engeland
2002-01-01
Full Text Available This study evaluates the applicability of the distributed, process-oriented Ecomag model for prediction of daily streamflow in ungauged basins. The Ecomag model is applied as a regional model to nine catchments in the NOPEX area, using Bayesian statistics to estimate the posterior distribution of the model parameters conditioned on the observed streamflow. The distribution is calculated by Markov Chain Monte Carlo (MCMC analysis. The Bayesian method requires formulation of a likelihood function for the parameters and three alternative formulations are used. The first is a subjectively chosen objective function that describes the goodness of fit between the simulated and observed streamflow, as defined in the GLUE framework. The second and third formulations are more statistically correct likelihood models that describe the simulation errors. The full statistical likelihood model describes the simulation errors as an AR(1 process, whereas the simple model excludes the auto-regressive part. The statistical parameters depend on the catchments and the hydrological processes and the statistical and the hydrological parameters are estimated simultaneously. The results show that the simple likelihood model gives the most robust parameter estimates. The simulation error may be explained to a large extent by the catchment characteristics and climatic conditions, so it is possible to transfer knowledge about them to ungauged catchments. The statistical models for the simulation errors indicate that structural errors in the model are more important than parameter uncertainties. Keywords: regional hydrological model, model uncertainty, Bayesian analysis, Markov Chain Monte Carlo analysis
Energy Technology Data Exchange (ETDEWEB)
Rafique, Rashid; Kumar, Sandeep; Luo, Yiqi; Kiely, Gerard; Asrar, Ghassem R.
2015-02-01
he accurate calibration of complex biogeochemical models is essential for the robust estimation of soil greenhouse gases (GHG) as well as other environmental conditions and parameters that are used in research and policy decisions. DayCent is a popular biogeochemical model used both nationally and internationally for this purpose. Despite DayCent’s popularity, its complex parameter estimation is often based on experts’ knowledge which is somewhat subjective. In this study we used the inverse modelling parameter estimation software (PEST), to calibrate the DayCent model based on sensitivity and identifi- ability analysis. Using previously published N2 O and crop yield data as a basis of our calibration approach, we found that half of the 140 parameters used in this study were the primary drivers of calibration dif- ferences (i.e. the most sensitive) and the remaining parameters could not be identified given the data set and parameter ranges we used in this study. The post calibration results showed improvement over the pre-calibration parameter set based on, a decrease in residual differences 79% for N2O fluxes and 84% for crop yield, and an increase in coefficient of determination 63% for N2O fluxes and 72% for corn yield. The results of our study suggest that future studies need to better characterize germination tem- perature, number of degree-days and temperature dependency of plant growth; these processes were highly sensitive and could not be adequately constrained by the data used in our study. Furthermore, the sensitivity and identifiability analysis was helpful in providing deeper insight for important processes and associated parameters that can lead to further improvement in calibration of DayCent model.
A computational model that predicts behavioral sensitivity to intracortical microstimulation
Kim, Sungshin; Callier, Thierri; Bensmaia, Sliman J.
2017-02-01
Objective. Intracortical microstimulation (ICMS) is a powerful tool to investigate the neural mechanisms of perception and can be used to restore sensation for patients who have lost it. While sensitivity to ICMS has previously been characterized, no systematic framework has been developed to summarize the detectability of individual ICMS pulse trains or the discriminability of pairs of pulse trains. Approach. We develop a simple simulation that describes the responses of a population of neurons to a train of electrical pulses delivered through a microelectrode. We then perform an ideal observer analysis on the simulated population responses to predict the behavioral performance of non-human primates in ICMS detection and discrimination tasks. Main results. Our computational model can predict behavioral performance across a wide range of stimulation conditions with high accuracy (R 2 = 0.97) and generalizes to novel ICMS pulse trains that were not used to fit its parameters. Furthermore, the model provides a theoretical basis for the finding that amplitude discrimination based on ICMS violates Weber’s law. Significance. The model can be used to characterize the sensitivity to ICMS across the range of perceptible and safe stimulation regimes. As such, it will be a useful tool for both neuroscience and neuroprosthetics.
A discourse on sensitivity analysis for discretely-modeled structures
Adelman, Howard M.; Haftka, Raphael T.
1991-01-01
A descriptive review is presented of the most recent methods for performing sensitivity analysis of the structural behavior of discretely-modeled systems. The methods are generally but not exclusively aimed at finite element modeled structures. Topics included are: selections of finite difference step sizes; special consideration for finite difference sensitivity of iteratively-solved response problems; first and second derivatives of static structural response; sensitivity of stresses; nonlinear static response sensitivity; eigenvalue and eigenvector sensitivities for both distinct and repeated eigenvalues; and sensitivity of transient response for both linear and nonlinear structural response.
Energy Technology Data Exchange (ETDEWEB)
Yan, Huiping; Qian, Yun; Lin, Guang; Leung, Lai-Yung R.; Yang, Ben; Fu, Q.
2014-03-25
Convective parameterizations used in weather and climate models all display sensitivity to model resolution and variable skill in different climatic regimes. Although parameters in convective schemes can be calibrated using observations to reduce model errors, it is not clear if the optimal parameters calibrated based on regional data can robustly improve model skill across different model resolutions and climatic regimes. In this study, this issue is investigated using a regional modeling framework based on the Weather Research and Forecasting (WRF) model. To quantify the response and sensitivity of model performance to model parameters, we identified five key input parameters and specified their ranges in the Kain-Fritsch (KF) convection scheme in WRF and calibrated them across different spatial resolutions, climatic regimes, and radiation schemes using observed precipitation data. Results show that the optimal values for the five input parameters in the KF scheme are close and model sensitivity and error exhibit similar dependence on the input parameters for all experiments conducted in this study despite differences in the precipitation climatology. We found that the model overall performances in simulating precipitation are more sensitive to the coefficients of downdraft (Pd) and entrainment (Pe) mass flux and starting height of downdraft (Ph). However, we found that rainfall biases, which are probably more related to structural errors, still exist over some regions in the simulation even with the optimal parameters, suggesting further studies are needed to identify the sources of uncertainties and reduce the model biases or structural errors associated with missed or misrepresented physical processes and/or potential problems with the modeling framework.
[Local sensitivity and its stationarity analysis for urban rainfall runoff modelling].
Lin, Jie; Huang, Jin-Liang; Du, Peng-Fei; Tu, Zhen-Shun; Li, Qing-Sheng
2010-09-01
Sensitivity analysis of urban-runoff simulation is a crucial procedure for parameter identification and uncertainty analysis. Local sensitivity analysis using Morris screening method was carried out for urban rainfall runoff modelling based on Storm Water Management Model (SWMM). The results showed that Area, % Imperv and Dstore-Imperv are the most sensitive parameters for both total runoff volume and peak flow. Concerning total runoff volume, the sensitive indices of Area, % Imperv and Dstore-Imperv were 0.46-1.0, 0.61-1.0, -0.050(-) - 5.9, respectively; while with respect to peak runoff, they were 0.48-0.89, 0.59-0.83, 0(-) -9.6, respectively. In comparison, the most sensitive indices (Morris) for all parameters with regard to total runoff volume and peak flow appeared in the rainfall event with least rainfall; and less sensitive indices happened in the rainfall events with heavier rainfall. Furthermore, there is considerable variability in sensitive indices for each rainfall event. % Zero-Imperv's coefficient variations have the largest values among all parameters for total runoff volume and peak flow, namely 221.24% and 228.10%. On the contrary, the coefficient variations of conductivity among all parameters for both total runoff volume and peak flow are the smallest, namely 0.
Some tests for parameter constancy in cointegrated VAR-models
DEFF Research Database (Denmark)
Hansen, Henrik; Johansen, Søren
1999-01-01
Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations, and anot...... be applied to test the constancy of the long-run parameters in the cointegrated VAR-model. All results are illustrated using a model for the term structure of interest rates on US Treasury securities. ...
Spatio-temporal modeling of nonlinear distributed parameter systems
Li, Han-Xiong
2011-01-01
The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s
Adjoint-based sensitivity of flames to ignition parameters in non-premixed shear-flow turbulence
Capecelatro, Jesse; Bodony, Daniel; Freund, Jonathan
2016-11-01
The adjoint of the linearized and perturbed compressible flow equations for a mixture of chemically reacting ideal gases is used to assess the sensitivity of ignition in non-premixed shear-flow turbulence. Direct numerical simulations are used to provide an initial prediction, and the corresponding space-time discrete-exact adjoint is used to provide a sensitivity gradient for a specific quantity of interest (QoI). Owing to the ultimately binary outcome of ignition (i.e., it succeeds or fails after some period), a QoI is defined that both quantifies ignition success and varies smoothly near its threshold based on the heat release parameter in a short-time horizon during the ignition process. We use the resulting gradient to quantify the flow properties and model parameters that most affect the initiation of a sustained flame. A line-search algorithm is used to identify regions of high ignition probability and map the boundary between successful and failed ignition. The approach is demonstrated on a non-premixed turbulent shear layer and on a reacting jet-in-crossflow.
Thermal hydraulic simulations, error estimation and parameter sensitivity studies in Drekar::CFD
Energy Technology Data Exchange (ETDEWEB)
Smith, Thomas Michael; Shadid, John N; Pawlowski, Roger P; Cyr, Eric C; Wildey, Timothy Michael
2014-01-01
This report describes work directed towards completion of the Thermal Hydraulics Methods (THM) CFD Level 3 Milestone THM.CFD.P7.05 for the Consortium for Advanced Simulation of Light Water Reactors (CASL) Nuclear Hub effort. The focus of this milestone was to demonstrate the thermal hydraulics and adjoint based error estimation and parameter sensitivity capabilities in the CFD code called Drekar::CFD. This milestone builds upon the capabilities demonstrated in three earlier milestones; THM.CFD.P4.02 [12], completed March, 31, 2012, THM.CFD.P5.01 [15] completed June 30, 2012 and THM.CFD.P5.01 [11] completed on October 31, 2012.
A method of evaluating quantitative magnetospheric field models by an angular parameter alpha
Sugiura, M.; Poros, D. J.
1979-01-01
The paper introduces an angular parameter, termed alpha, which represents the angular difference between the observed, or model, field and the internal model field. The study discusses why this parameter is chosen and demonstrates its usefulness by applying it to both observations and models. In certain areas alpha is more sensitive than delta-B (the difference between the magnitude of the observed magnetic field and that of the earth's internal field calculated from a spherical harmonic expansion) in expressing magnetospheric field distortions. It is recommended to use both alpha and delta-B in comparing models with observations.
Weigand, M.; Kemna, A.
2016-06-01
Spectral induced polarization (SIP) data are commonly analysed using phenomenological models. Among these models the Cole-Cole (CC) model is the most popular choice to describe the strength and frequency dependence of distinct polarization peaks in the data. More flexibility regarding the shape of the spectrum is provided by decomposition schemes. Here the spectral response is decomposed into individual responses of a chosen elementary relaxation model, mathematically acting as kernel in the involved integral, based on a broad range of relaxation times. A frequently used kernel function is the Debye model, but also the CC model with some other a priorly specified frequency dispersion (e.g. Warburg model) has been proposed as kernel in the decomposition. The different decomposition approaches in use, also including conductivity and resistivity formulations, pose the question to which degree the integral spectral parameters typically derived from the obtained relaxation time distribution are biased by the approach itself. Based on synthetic SIP data sampled from an ideal CC response, we here investigate how the two most important integral output parameters deviate from the corresponding CC input parameters. We find that the total chargeability may be underestimated by up to 80 per cent and the mean relaxation time may be off by up to three orders of magnitude relative to the original values, depending on the frequency dispersion of the analysed spectrum and the proximity of its peak to the frequency range limits considered in the decomposition. We conclude that a quantitative comparison of SIP parameters across different studies, or the adoption of parameter relationships from other studies, for example when transferring laboratory results to the field, is only possible on the basis of a consistent spectral analysis procedure. This is particularly important when comparing effective CC parameters with spectral parameters derived from decomposition results.
Identification of hydrological model parameter variation using ensemble Kalman filter
Deng, Chao; Liu, Pan; Guo, Shenglian; Li, Zejun; Wang, Dingbao
2016-12-01
Hydrological model parameters play an important role in the ability of model prediction. In a stationary context, parameters of hydrological models are treated as constants; however, model parameters may vary with time under climate change and anthropogenic activities. The technique of ensemble Kalman filter (EnKF) is proposed to identify the temporal variation of parameters for a two-parameter monthly water balance model (TWBM) by assimilating the runoff observations. Through a synthetic experiment, the proposed method is evaluated with time-invariant (i.e., constant) parameters and different types of parameter variations, including trend, abrupt change and periodicity. Various levels of observation uncertainty are designed to examine the performance of the EnKF. The results show that the EnKF can successfully capture the temporal variations of the model parameters. The application to the Wudinghe basin shows that the water storage capacity (SC) of the TWBM model has an apparent increasing trend during the period from 1958 to 2000. The identified temporal variation of SC is explained by land use and land cover changes due to soil and water conservation measures. In contrast, the application to the Tongtianhe basin shows that the estimated SC has no significant variation during the simulation period of 1982-2013, corresponding to the relatively stationary catchment properties. The evapotranspiration parameter (C) has temporal variations while no obvious change patterns exist. The proposed method provides an effective tool for quantifying the temporal variations of the model parameters, thereby improving the accuracy and reliability of model simulations and forecasts.
Institute of Scientific and Technical Information of China (English)
王盛春; 沈卫东; 徐嘉锋; 李赟
2014-01-01
The structural-acoustic coupling model for isotropic thin elastic plate was extended to honeycomb sandwich plate (HSP) by applying Green function method. Then an equivalent circuit model of the weakly-strongly coupled system was proposed. Based on that, the estimation formulae of the coupled eigenfrequency were derived. The accuracy of the theoretical predictions was checked against experimental data, with good agreement achieved. Finally, the effects of HSP design parameters on the system coupling degree, the acoustic cavity eigenfrequency, and sound pressure response were analyzed. The results show that mechanical and acoustical characteristics of HSP can be improved by increasing the thickness of face sheet and reducing the mass density of material.
Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model
Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami
2017-06-01
A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.
Tube-Load Model Parameter Estimation for Monitoring Arterial Hemodynamics
Directory of Open Access Journals (Sweden)
Guanqun eZhang
2011-11-01
Full Text Available A useful model of the arterial system is the uniform, lossless tube with parametric load. This tube-load model is able to account for wave propagation and reflection (unlike lumped-parameter models such as the Windkessel while being defined by only a few parameters (unlike comprehensive distributed-parameter models. As a result, the parameters may be readily estimated by accurate fitting of the model to available arterial pressure and flow waveforms so as to permit improved monitoring of arterial hemodynamics. In this paper, we review tube-load model parameter estimation techniques that have appeared in the literature for monitoring wave reflection, large artery compliance, pulse transit time, and central aortic pressure. We begin by motivating the use of the tube-load model for parameter estimation. We then describe the tube-load model, its assumptions and validity, and approaches for estimating its parameters. We next summarize the various techniques and their experimental results while highlighting their advantages over conventional techniques. We conclude the review by suggesting future research directions and describing potential applications.
Tube-Load Model Parameter Estimation for Monitoring Arterial Hemodynamics
Zhang, Guanqun; Hahn, Jin-Oh; Mukkamala, Ramakrishna
2011-01-01
A useful model of the arterial system is the uniform, lossless tube with parametric load. This tube-load model is able to account for wave propagation and reflection (unlike lumped-parameter models such as the Windkessel) while being defined by only a few parameters (unlike comprehensive distributed-parameter models). As a result, the parameters may be readily estimated by accurate fitting of the model to available arterial pressure and flow waveforms so as to permit improved monitoring of arterial hemodynamics. In this paper, we review tube-load model parameter estimation techniques that have appeared in the literature for monitoring wave reflection, large artery compliance, pulse transit time, and central aortic pressure. We begin by motivating the use of the tube-load model for parameter estimation. We then describe the tube-load model, its assumptions and validity, and approaches for estimating its parameters. We next summarize the various techniques and their experimental results while highlighting their advantages over conventional techniques. We conclude the review by suggesting future research directions and describing potential applications. PMID:22053157
Energy parameters of lasers utilizing erbium glasses sensitized with ytterbium and chromium
Energy Technology Data Exchange (ETDEWEB)
Lunter, S.G.; Murzin, A.G.; Tolstoi, M.N.; Fedorov, Y.K.; Fromzel' , V.A.
1984-01-01
An experimental investigation was made of the effect of sensitizing ytterbium- and erbium-activated lead barium phosphate glasses with Cr/sup 3 +/ ions on the energy parameters of lasing due to the /sup 4/I/sub 13//sub ///sub 2/--/sup 4/I/sub 15//sub ///sub 2/ transition in Er/sup 3 +/ ions (lambda/sub l/ = 1.54 ..mu..). It was found that substantial sensitization was achieved in phosphate glasses for only low concentrations of Cr/sup 3 +/ ions (< or approx. =0.07 wt.%) so that the efficiency of flashlamp-pumped erbium lasers could be improved by a factor of 1.5--4. The optimal conditions for achieving the best energy parameters of these lasers under free-lasing conditions were determined allowing for the spectral and energy distributions of the flashlamp radiation in the absorption range of the coactivator ions. By implementing these conditions using active elements 6 mm in diameter and 85 mm long, containing 17 wt.% Yb/sub 2/O/sub 3/, 0.25 wt.% Er/sub 2/O/sub 3/, and 0.07 wt.% Cr/sub 2/O/sub 3/, it was possible to achieve an efficiency of 1.2% for an electrical pump energy of 1 kJ. This was the highest efficiency achieved so far for erbium lasers. Measurements were made of the efficiency of transfer of the excitation energy from Cr/sup 3 +/ ions to Yb/sup 3 +/ ions at high levels of excitation of the medium.
Mun, J S; Han, M Y
2012-01-01
The appropriate design and evaluation of a rainwater harvesting (RWH) system is necessary to improve system performance and the stability of the water supply. The main design parameters (DPs) of an RWH system are rainfall, catchment area, collection efficiency, tank volume and water demand. Its operational parameters (OPs) include rainwater use efficiency (RUE), water saving efficiency (WSE) and cycle number (CN). The sensitivity analysis of a rooftop RWH system's DPs to its OPs reveals that the ratio of tank volume to catchment area (V/A) for an RWH system in Seoul, South Korea is recommended between 0.03 and 0.08 in terms of rate of change in RUE. The appropriate design value of V/A is varied with D/A. The extra tank volume up to V/A of 0.15∼0.2 is also available, if necessary to secure more water. Accordingly, we should figure out suitable value or range of DPs based on the sensitivity analysis to optimize design of an RWH system or improve operation efficiency. The operational data employed in this study, which was carried out to validate the design and evaluation method of an RWH system, were obtained from the system in use at a dormitory complex at Seoul National University (SNU) in Korea. The results of these operational data are in good agreement with those used in the initial simulation. The proposed method and the results of this research will be useful in evaluating and comparing the performance of RWH systems. It is found that RUE can be increased by expanding the variety of rainwater uses, particularly in the high rainfall season.
Wehbe, Mahmoud S; Yamamura, Jin; Fischer, Roland; Grosse, Regine; Berliner, Christoph; Graessner, Joachim; Lund, Gunner; Adam, Gerhard; Schoennagel, Bjoern P
2017-02-01
To determine the impact of myocardial iron overload on left atrial (LA) volume and function using MR in patients with systemic iron overload. Thirty-eight patients with systemic iron overload disease and 10 controls underwent 1.5 Tesla MR performing steady state free precession short-axis cine-series of the LA. Three-dimensional-volumetry was assessed to calculate LA volumes and function. Parameters were indexed (i) to body surface area. The myocardial transverse relaxation rate R2* was determined in the ventricular septum using a multi-echo GRE sequence (breathhold; electrocardiography triggered; 12 echoes; echo time = 1.3-25.7 ms). Significantly decreased active atrial emptying fraction (AAEF) (23% [95%-range, 7-34] versus 36% [95%-range, 14-49], P = 0.009), active atrial emptying volume (AAEVi) (5.5 mL/m(2) [95%-range, 2-11] versus 11.9 mL/m(2) [95%-range, 3-23], P = 0.008), and active peak emptying rate (APERi) (46 mL/s/m(2) [95%-range, 29-69] versus 75 mL/s/m(2) [95%-range, 45-178], P 40 s(-1) ) compared with patients with normal myocardial iron levels (R2* sensitivities and specificities of 82% (AAEF), 79% (APERi), 73% (AAEVi), and 57% (LAEF). MR parameters of active LA contractile function were associated with myocardial iron overload. This cross-sectional study suggests impaired active LA contractile function to be sensitive to myocardial iron toxicity. 3 J. Magn. Reson. Imaging 2017;45:535-541. © 2016 International Society for Magnetic Resonance in Medicine.
Directory of Open Access Journals (Sweden)
Jianbin Hao
2014-01-01
Full Text Available Based on the back-propagation algorithm of artificial neural networks (ANNs, this paper establishes an intelligent model, which is used to predict the maximum lateral displacement of composite soil-nailed wall. Some parameters, such as soil cohesive strength, soil friction angle, prestress of anchor cable, soil-nail spacing, soil-nail diameter, soil-nail length, and other factors, are considered in the model. Combined with the in situ test data of composite soil-nail wall reinforcement engineering, the network is trained and the errors are analyzed. Thus it is demonstrated that the method is applicable and feasible in predicting lateral displacement of excavation retained by composite soil-nailed wall. Extended calculations are conducted by using the well-trained intelligent forecast model. Through application of orthogonal table test theory, 25 sets of tests are designed to analyze the sensitivity of factors affecting the maximum lateral displacement of composite soil-nailing wall. The results show that the sensitivity of factors affecting the maximum lateral displacement of composite soil nailing wall, in a descending order, are prestress of anchor cable, soil friction angle, soil cohesion strength, soil-nail spacing, soil-nail length, and soil-nail diameter. The results can provide important reference for the same reinforcement engineering.