Parameter Sensitivity Analysis of the SparTen High Performance Sparse Tensor Decomposition Software.
Abstract not provided.
Myers, Jeremy↗
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Parameter Sensitivity Analysis of the SparTen High Performance Sparse Tensor Decomposition Software.
Abstract not provided.
Myers, Jeremy↗
Improving E3SM Land Model Photosynthesis Parameterization via Satellite SIF, Machine Learning, and Surrogate Modeling
The parameterization of key photosynthesis parameters is one of the key uncertain sources in modeling ecosystem gross primary productivity (GPP). Solar-induced chlorophyll fluorescence (SIF) offers a good proxy for GPP since it marks the actual process of photosynthesis; while machine learning (ML) provides a robust approach to model the GPP-SIF relationship. Here, we trained the boosted regressing tree (BRT) and the Random Forest ML models with Greenhouse Gases Observing Satellite SIF data and in situ GPP observations from 49 eddy covariance towers. These trained ML GPP-SIF models were fed into the Energy Exascale Earth System Model (E3SM) Land Model (ELM) to generate ELM-simulated global SIF estimates, which were then benchmarked against satellite SIF observations with a surrogate modeling approach. Our results indicated good modeling performance of the ML-based GPP-SIF relationship. The ELM model when fed with the ML GPP-SIF models also can well predict the spatial-temporal variations in SIF. We also found high model accuracy for the surrogate modeling. Model parameter sensitivity analysis suggested that the fraction of leaf nitrogen in RuBisCO (flnr) is the most sensitive parameter to the SIF; other sensitive parameters include the Ball-Berry stomatal conductance slope (mbbopt) and the vcmax entropy (vcmaxse). The posterior uncertainty in simulated GPP was greatly reduced after benchmarking, and the model produced improved spatial patterns of mean GPP relative to FLUXCOM GPP. Our integrated approach provides a new avenue for improving land models and using remote-sensing SIF, which can be further improved in the future with more ground- and satellite-based observations.
54 ENVIRONMENTAL SCIENCES↗
Preliminary Investigation of Ice Shape Sensitivity to Parameter Variations
A parameter sensitivity study was conducted at the NASA Glenn Research Center's Icing Research Tunnel (IRT) using a 36 in. chord (0.91 m) NACA-0012 airfoil. The objective of this preliminary work was to investigate the feasibility of using ice shape feature changes to define requirements for the simulation and measurement of SLD icing conditions. It was desired to identify the minimum change (threshold) in a parameter value, which yielded an observable change in the ice shape. Liquid Water Content (LWC), drop size distribution (MVD), and tunnel static temperature were varied about a nominal value, and the effects of these parameter changes on the resulting ice shapes were documented. The resulting differences in ice shapes were compared on the basis of qualitative and quantitative criteria (e.g., mass, ice horn thickness, ice horn angle, icing limits, and iced area). This paper will provide a description of the experimental method, present selected experimental results, and conclude with an evaluation of these results, followed by a discussion of recommendations for future research.
Miller, Dean R.↗
Additional Investigations of Ice Shape Sensitivity to Parameter Variations
A second parameter sensitivity study was conducted at the NASA Glenn Research Center's Icing Research Tunnel (IRT) using a 36 in. chord (0.91 m) NACA-0012 airfoil. The objective of this work was to further investigate the feasibility of using ice shape feature changes to define requirements for the simulation and measurement of SLD and appendix C icing conditions. A previous study concluded that it was feasible to use changes in ice shape features (e.g., ice horn angle, ice horn thickness, and ice shape mass) to detect relatively small variations in icing spray condition parameters (LWC, MVD, and temperature). The subject of this current investigation extends the scope of this previous work, by also examining the effect of icing tunnel spray-bar parameter variations (water pressure, air pressure) on ice shape feature changes. The approach was to vary spray-bar water pressure and air pressure, and then evaluate the effects of these parameter changes on the resulting ice shapes. This paper will provide a description of the experimental method, present selected experimental results, and conclude with an evaluation of these results.
Miller, Dean R.↗
Utilization of ACE nuclear data file toolkit ACEtk to calculate relative sensitivity coefficients of point-kinetics parameters
Sensitivity and uncertainty methods are quintessential for nuclear criticality safety and experiment design. This type of analysis relies on calculations of sensitivity coefficients; sensitivity coefficients of the effective neutron multiplication factor with respect to some nuclear data are predominantly calculated and used. As a part of the Laboratory Directed Research & Development project EUCLID (Experiments Underpinned by Computational Learning for Improvements in nuclear Data) at Los Alamos National Laboratory, sensitivity coefficients of many radiation detector measurement responses with respect to nuclear data were investigated. Specifically, this paper outlines a method to calculate point-kinetics parameters relative sensitivity coefficients with respect to nuclear data. Point-kinetics parameters such as the prompt neutron decay constant, effective delayed neutron fraction, and neutron generation time are especially important to experimenters and reactor operators designing systems with dynamic neutron populations. This method couples capabilities of the ACE (A Compact ENDF) nuclear data file toolkit, ACEtk, with the ability to load cross sections into the radiation transport code Monte Carlo N-Particle (MCNP). In conclusion, key aspects of optimizing this method for a particular application and sensitivity profiles of the Jezebel criticality experiment are examined and discussed.
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
A functional global sensitivity measure and efficient reliability sensitivity analysis with respect to statistical parameters
Sensitivity analysis and reliability assessment are two important aspects of structural and system safety. Epistemic uncertainty with respect to probabilistic model of input parameters due to lack of knowledge is present in many scarce-data applications and complicates the characterization of uncertainty in model response. In this article, we present two importance measures to evaluate the impact of distribution parameters on the probability distribution function (PDF) of the output and the failure probability. The epistemic uncertainty associated with the distribution parameters is modeled as random variables. Additionally, a modified extended polynomial chaos expansion (MEPCE) approach is introduced in which aleatory and epistemic random variables are modeled and propagated simultaneously while allowing the separate assessment for any single epistemic variable. A MEPCE-based kernel density estimation (KDE) construction provides a composite map from each epistemic variable to the response PDF. The functional global sensitivity index of the PDF with respect to the distribution parameters is thus derived, as a function of output, which is both more informative and more efficient than standard scalar sensitivity measures. Reliability sensitivity indices can be readily evaluated by integrating the global sensitivity index function over the failure zone. Three illustrative examples are used to demonstrate the proposed methodology.
42 ENGINEERING↗
Sensitivity study of parameters important to Molten Salt Reactor Safety
This paper presents a molten salt reactor (MSR) design parameter sensitivity study using a nodal dynamic modelling methodology with explicitly modified point kinetics equation and Mann’s model for heat transfer. Six parameters that can impact MSR safety are evaluated. A MATLAB-Simulink model inspired by Thorcon’s 550MW th MSR is used for parameter evaluations. A safety envelope was formed to encapsulate power, maximum and minimum temperature, and temperature-induced reactivity feedback. The parameters are perturbed by ±30%. The parameters were then ranked by their subsequent impact on the considered safety envelope, which ranks acceptable parameter uncertainty. The model is openly available on GitHub.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Calculating Closed-Loop Sensitivity to Parameter Variations
Performance sensitivity calculated by back substitution. Original Lyapunov equation differentiated two times with respect to parameter p. Each differential turns out to yield Lyapunov equation for first and second derivatives with respective to parameter p of steady-state covariance of state variables. Derivatives desired closed-loop performance sensitivities.
Schaechter, D. B.↗
Improved calculation of optimum design sensitivity
Optimum design parameter sensitivity analysis has become an important topic in recent years. The principal reasons for obtaining optimum design sensitivity information with respect to various problem parameters are (l) to predict revised optimum designs, associated with specified perturbations of the problem parameters, without re-optimizing the problem and, (2) to provide sensitivity information in multilevel optimization strategies. Methods for calculating these derivatives were proposed by several authors. The most important drawback in estimating parameter sensitivities by the current methods is that they do not allow for changes in the active constraint set. Changes in the active constraint set produce discontinuities in the optimum design sensitivities, and therefore, a correct formulation has to be cast in terms of directional derivatives. Optimum design parameter sensitivity analysis is addressed in terms of directional derivatives so as to include possible discontinuities and it also presents a method for estimating optimum design sensitivities using finite differences.
Sepulveda, Abdon E.↗
Hyper-Differential Sensitivity Analysis of Uncertain Parameters in PDE-Constrained Optimization
Many problems in engineering and sciences require the solution of large scale optimization constrained by partial differential equations (PDEs). Though PDE-constrained optimization is itself challenging, most applications pose additional complexity, namely, uncertain parameters in the PDEs. Uncertainty quantification (UQ) is necessary to characterize, prioritize, and study the influence of these uncertain parameters. Sensitivity analysis, a classical tool in UQ, is frequently used to study the sensitivity of a model to uncertain parameters. In this article, we introduce "hyper-differential sensitivity analysis" which considers the sensitivity of the solution of a PDE-constrained optimization problem to uncertain parameters. Our approach is a goal-oriented analysis which may be viewed as a tool to complement other UQ methods in the service of decision making and robust design. We formally define hyper-differential sensitivity indices and highlight their relationship to the existing optimization and sensitivity analysis literatures. Assuming the presence of low rank structure in the parameter space, computational efficiency is achieved by leveraging a generalized singular value decomposition in conjunction with a randomized solver which converts the computational bottleneck of the algorithm into an embarrassingly parallel loop. Two multi-physics examples, consisting of nonlinear steady state control and transient linear inversion, demonstrate efficient identification of the uncertain parameters which have the greatest influence on the optimal solution.
97 MATHEMATICS AND COMPUTING↗
Sensitivity and uncertainty analysis of PWR spent fuel observables to operational and model parameters
Sensitivity and uncertainty analyses of spent nuclear fuel (SNF) observables - decay heat, neutron and γ-ray emission rate - to operational and model parameters have been performed. A 2D model representing a typical PWR 17x17 UO{sub 2} fuel assembly has been taken as reference. The Serpent code and ENDF/B-VII.1 evaluated nuclear data library have been used for the analyses. Relative uncertainty of decay heat, neutron and γ-ray emission rates due to Monte Carlo counting statistics, as well as the number of fuel pin radial regions required for an accurate characterization of SNF neutron emission, have been estimated. A parametric study has been carried out to investigate the impact of the homogenization to an average value of the fuel and moderator temperature, boron concentration power and burnup on the prediction of the selected observables. In addition, linear sensitivity coefficients have been calculated. (authors)
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Evolution of Geometric Sensitivity Derivatives from Computer Aided Design Models
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.
Jones, William T.↗
VIC-Global Parameter Dataset Sensitivity with the Variable Infiltration Capacity Model: Evaluating the importance of dynamic land surface parameters when using the VIC-Global parameter dataset
Accurate prediction of runoff is essential to water resources management, flood risk assessment, and ecosystem protection. However, many hydrological models still have relatively substantial limitations when representing the influence of land use and land cover (LULC) on runoff generation and routing. Changes in LULC, such as deforestation, urban expansion, agricultural intensification, and wetland loss, have been shown to alter the water balance at the land surface through fundamental hydrologic processes (e.g., interception, infiltration, evapotranspiration, and soil storage). However, it remains an open question what the exact magnitude and timing of these impacts are for the spatial and temporal scales commonly used in engineering applications. In this analysis we focus on one aspect of recent LULC change for assessing human impacts, which is urbanization. Specifically we seek to determine the impacts of urbanization on the magnitude and timing of surface runoff and baseflow in HUC-12 basins in Clark County, Nevada which has experienced rapid urbanization. We use the Variable Infiltration Capacity (VIC) hydrology model with a widely used off-the-shelf dataset of land surface parameters, VIC-Global, both of which have been commonly used in the past for water and energy balance modeling for large scale hydrologic studies. We examine two scenarios where the first scenario removes all urbanized land cover and parameterizes those areas of the basins as barren or open shrubland. The second scenario tests the opposite case where all areas of the basins are classified as urban regardless of their present classification. The results from the VIC model show there is a low sensitivity for daily surface runoff between scenarios. The daily baseflow values indicate similar low sensitivity to the classification change during specific periods, but then have substantial differences during other period when large precipitation events are occurring. This is likely due to the assumed parameter values for the urban land cover classification made by the VIC-Global dataset. Using a static land cover parameterization is reasonable for large domain hydrology models that are being used for near-term planning horizons (<30 years). However, longer planning horizons where feedbacks between the atmosphere and land surface are important, especially in transient climate situations, considerations for how to update land surface parameters should be incorporated.
42 ENGINEERING↗
Closed loop control performance sensitivity to parameter variations
A very efficient technique for computing the closed loop performance sensitivities to parameter variations of a dynamic system with a reduced order controller has been developed. The eigensystem of the closed loop system is computed once. With this information, the closed loop filter and state rms responses, and the first and second derivatives of these rms values with respect to given parameters are computed. Detailed numerical examples using the JPL flexible beam and a 55 meter offset fed, wrap-rib antenna are included.
Schaechter, D. B.↗
Investigation of Dynamic Temperature-Sensitive Electrical Parameters for Medium-Voltage Low-Current Silicon Carbide and Silicon Devices
This paper presents five dynamic temperature-sensitive electrical parameters (TSEPs) for the medium-voltage silicon carbide (SiC) and silicon (Si) devices. The theoretical temperature dependence of these parameters is analyzed. A test platform that enables to implement the temperature relevant dynamic characterization is developed. The tested TSEPs are summarized in terms of their relationship with junction temperature, drain/collector current, DC voltage, and external gate resistance. The comparison between the 3 kV 12 A Si IGBT and 3.3 kV 5 A SiC MOSFET with the identical TO-263 package is conducted. The results verify that the turn-off drain-source voltage switching rate achieves better thermal sensitivity for medium-voltage low-current SiC MOSFETs compared with Si IGBTs. Both the turn-on and turn-off delay time exhibit better thermal linearity for the two devices. The turn-off delay time further achieves five times better thermal sensitivity than the turn-on delay time for investigated medium-voltage SiC MOSFETs.
Ni, Ze↗
Impact of Increased Monte Carlo Parameters on Sensitivity Calculations with SCALE [Slides]
For both models and tests, NPG and NSK parameters have only small effects on calculated sensitivity coefficients. Outside of NPG=100, only differences in CFP affected sensitivity coefficient values. Fission reactions ( 235 U) require more NPG values than scattering ( 238 U) reactions – more particles are needed to locate fission sources in the model more accurately. This work confirms the previous results with the IFP method where the CFP parameter has the greatest impact on calculated sensitivity coefficients. While immediate work focuses on fast systems, other model specifications may require a different set of MC parameters.
97 MATHEMATICS AND COMPUTING↗
Balloon Thermal Model Design Parameters and Sensitivities
This presentation covers recent process improvements regarding environmental parameters, w.r.t convection, and future plans for thermal models.
Thermal. Parameter↗