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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8

Sensitivity Analysis and Emulation for Functional Data using Bayesian Adaptive Splines

When a computer code is used to simulate a complex system, one of the fundamental tasks is to assess the sensitivity of the simulator to the different input parameters. In the case of computationally expensive simulators, this is often accomplished via a surrogate statistical model, a statistical output emulator. An effective emulator is one that provides good approximations to the computer code output for wide ranges of input values. In addition, an emulator should be able to handle large dimensional simulation output for a relevant number of inputs; it should flexibly capture heterogeneities in the variability of the response surface; it should be fast to evaluate for arbitrary combinations of input parameters, and it should provide an accurate quantification of the emulation uncertainty. In this paper we discuss the Bayesian approach to multivariate adaptive regression splines (BMARS) as an emulator for a computer model that outputs curves. We introduce modifications to traditional BMARS approaches that allow for fitting large amounts of data and allow for more efficient MCMC sampling. We emphasize the ease with which sensitivity analysis can be performed in this situation. We present a sensitivity analysis of a computer model of the deformation of a protective plate used in pressure-driven experiments. Our example serves as an illustration of the ability of BMARS emulators to fulfill all the necessities of computability, flexibility and reliable calculation on relevant measures of sensitivity.

97 MATHEMATICS AND COMPUTING↗

Sensitivity analysis and optimization issues in NASTRAN

The purpose is to develop procedures to extract sensitivity analysis information from COSMIC/NASTRAN and to couple it with a mathematical optimization package. At present, the analysis will be limited to stress, displacement, and frequency constraints with structures modeled with membrane elements, rods, and bar elements. Two types of sensitivity analysis are discussed: an adjoint variable approach which is most effective when the number of active constraints is significantly less than the number of physical variables, and an approach based on a first order approximation of a Taylor series. The latter approach is more effective when the number of independent design variables is significantly less than the number of active constraints.

Tischler, V. A.↗

Adjoint sensitivity analysis and data assimilation for verification of dry storage cask contents

Dry cask storage is a method for interim storage of spent fuel assemblies which contain fissile isotopes of uranium and plutonium. These can present a proliferation concern and consequently there is a need for non-destructive testing methods to verify a dry cask's contents for proliferation protection. We present an application of adjoint sensitivity analysis and data assimilation to a multigroup diffusion model of dry cask storage. Adjoint sensitivity analysis allows the efficient calculation of sensitivities for use in data assimilation to calibrate imprecisely known parameter values and data consistency tests to detect diversion scenarios. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Recent developments in structural sensitivity analysis

Recent developments in two areas of structural sensitivity analysis are reviewed. These are the sensitivity of static and transient response, and the sensitivity of vibration and buckling eigenproblems. Recent developments from the point of view of computational cost, accuracy, and ease of implementation are considered.

Haftka, Raphael T.↗

Development of high concentration photovoltaics (HCPV) power plants in the US Southwest: Economic assessment and sensitivity analysis

High concentration photovoltaic (HCPV) technologies offer several advantages over typical PV systems. In this study, a detailed economic assessment and sensitivity analysis of deploying HCPV plants in the US southwest is performed. To do this, a 20 MWdc HCPV power plant is designed using the System Advisor Model (SAM) and is evaluated from both technical and financial aspects. The sensitivity analysis shows that reducing the installed cost per capacity of the HCPV system can significantly improve the economics and reduce the levelized cost of electricity (LCOE) and levelized power purchase agreement (LPPA). Also, providing proper incentives including both investment tax credits (ITC) and production tax credit (PTC), loan debt ratio, and interest rate are among the most influential parameters. The analysis shows that with the 30% ITC, the LCOE, and LPPA of the designed HCPV projects are between $65.4/MWh and $69.3/MWh and between $71.0/MWh and $75.2/MWh, respectively. The estimated LCOE and LPPA values are almost 50% higher than the utility-scale PV projects. If proper funding is provided to continue the support of the HCPV system, they would become more economical and competitive with PV plants. Federal and state government policies must also be established to advocate HCPV systems.

14 SOLAR ENERGY↗

Sensitivity Analysis of Lbloca In Response To 10 Cfr50.46c New Rulemaking

The Nuclear Regulatory Commission (NRC) is proposing a new rulemaking on emergency core system/loss-of-coolant accident (LOCA) performance analysis. In the proposed rulemaking, designated as 10 CFR 50.46c, the US NRC puts forward an equivalent cladding oxidation criterion as a function of cladding pre-transient hydrogen content. The proposed rulemaking imposes more restrictive and burnupdependent cladding embrittlement criteria; consequently more fuel rods need to be analyzed under LOCA conditions to maintain the safety margin, in contrast to the current practice with which only one hot rod needs to be analyzed. New multi-physics analysis methods are required to provide a thorough characterization of the reactor core in order to identify the locations of the limiting rods and quantify safety margins under LOCA conditions. The U.S. DOE’s Light Water Reactor Sustainability (LWRS) Program has initiated a project to develop multi-physics analytical capabilities, called LOTUS, to support the industry in the transition to the proposed rule. An approach to uncertainty quantification and sensitivity analysis with LOTUS was developed. A typical four-loop PWR plant model was developed and simulated by RELAP5-3D with inputs generated from core design and fuel performance analyses, and uncertainty quantification and sensitivity analysis were performed with seventeen uncertain input parameters. The maximum equivalent cladding reacted ratio (ECRR) and peak clad temperature ratio (PCTR) were selected as the figures of merit (FOM). Pearson, Spearman, partial correlation coefficients, and Sobol indices were considered for all of the figures of merit in the sensitivity analysis.

10CFR50.46c↗

The case for aerodynamic sensitivity analysis

No specific solutions are offered, nor verified by applications, for its subject problem which is sensitivity analysis in Computational Fluid Dynamics (CFD). Instead, a plea is made to the CFD community for extending their present capability to include sensitivity analysis. The plea is made from the viewpoint of an aeronautical engineer, not an expert in CFD methods, who needs the sensitivity information when working at the junction of aerodynamics, structures, active controls, and other disciplines whose inputs need to be integrated in aircraft design.

Sobieszczanski-Sobieski, Jaroslaw↗

The Role of Sensitivity Analysis in the Building Performance Analysis: A Critical Review

A building system is highly nonlinear and commonly includes a variety of parameters ranging from the architectural design to the building mechanical and energy system. Serving as a powerful tool to understand the complicated building system, sensitivity analysis (SA) has been receiving increasing attention in the recent decade. This review paper focused on the application of SA in the building performance analysis (BPA). First, the existing review papers on the application of SA for BPA were briefly reviewed and summarized. Then, a large amount of recent SA case studies in BPA were reviewed. The critical information regarding the implementation of a SA, such as the sampling method, the SA method, etc., were extracted and summarized. Next, an extensive analysis was performed to evaluate the role of the SA in the BPA. This includes: 1) The typical selection of the input and output parameters for the SA were visualized; 2) The uncertainty level and sampling strategies for the input parameters were investigated; 3) The principles, benefits, and drawbacks of the SA methods were analyzed and summarized; and 4) The various tools used in the SA, including the simulation software, sampling tools, and SA tools were introduced to facilitate the practitioners. Lastly, several conclusions were summarized on the role of the SA in the BPA. Suggestions were also provided to offer practical solutions to the current challenges.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Surrogate-driven Variance-based Sensitivity Analysis of Thermal Storage Tanks in Integrated Energy Systems

Sensitivity analysis and uncertainty quantification are essential steps for enhancing the accuracy of computational models by identifying and mitigating uncertainties. This study focuses on these steps for the Thermal Energy Delivery System at Idaho National Laboratory, specifically targeting the thermocline tank. Using a Modelica/Dymola simulation model, the study perturbed various design parameters and boundary conditions, including shape factor, porosity, outlet temperature, inlet mass flow rate, and system pressure, to predict and quantify uncertainty in the tank’s ax- ial temperature. A dataset of over 1,000 simulations was generated, and surrogate models were developed using the pyMAISE (Michigan Artificial Intelligence Standard Environment) library, which is an Automatic Machine Learning library for nuclear engineering applications. The optimal model, a feedforward neural network with two hidden layers, achieved an R2 score above 0.99 and a mean absolute error below 1 Kelvin. Sensitivity analyses using Sobol indices and Fourier amplitude sensitivity testing methods on this surrogate model revealed that the inlet mass flow rate at initial timestamps and porosity significantly impacts predicted temperatures across all sensors and time steps.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Uncertainty and Sensitivity Analysis of TREAT Transient Test no. 15

The U.S. Department of Energy (DOE) is preparing for the resumption of transient testing using the Transient Reactor Test Facility (TREAT) located at the Idaho National Laboratory (INL). In order to support the analysis of TREAT operation and experiment planning, the MAMMOTH reactor physics team has recently begun development of uncertainty and sensitivity analysis for the TREAT core simulated via MAMMOTH. MAMMOTH is a high-fidelity three-dimensional transient multi-physics code developed at INL under the DOE-NE Advanced Modeling and Simulation program (NEAMS). This research is part of the development presenting some initial uncertainty and sensitivity analysis of TREAT Transient Test no. 15. In this summary, we employ the Sobol sampling strategy implemented in RAVEN to efficiently perform the sensitivity and uncertainty analysis. The idea is using Sobol functional decomposition with generalized polynomial chaos (gPC) expansions to estimate the responses of interest. The gPC coefficients are then computed via the sparse grid spectral projection method. In addition, this strategy includes evaluation of the second or higher order sensitivity indices, allowing the study of interactions between several input variables. The principal focus of this analysis is to quantify the uncertainties in the total power and maximum fuel temperatures with respect to uncertainties in the initial transient conditions, such as rated power, fuel temperature, graphite fuel density and control rod boron concentration. In addition, both the first order and second order time-dependent sensitivity indices are computed and analyzed. The results show that the interactions between initial control rod boron concentration and the rated power will contribute at most 1% to the total uncertainty of the power peak.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Uncertainty and Sensitivity Analysis of TREAT Transient Test #15

The U.S. Department of Energy (DOE) is preparing for the resumption of transient testing using the Transient Reactor Test Facility (TREAT) located at the Idaho National Laboratory (INL). In order to support the analysis of TREAT operation and experiment planning, the MAMMOTH reactor physics team has recently begun development of uncertainty and sensitivity analysis for the TREAT core simulated via MAMMOTH. MAMMOTH is a high-fidelity three-dimensional transient multi-physics code developed at INL under the DOE-NE Advanced Modeling and Simulation program (NEAMS) [1]. This research is part of the development presenting some initial uncertainty and sensitivity analysis of TREAT Transient Test #15 [2]. In this summary, we employ the Sobol sampling strategy implemented in RAVEN [3] to efficiently perform the sensitivity and uncertainty analysis. The idea is using Sobol functional decomposition with generalized polynomial chaos (gPC) expansions to estimate the responses of interest [4]. The gPC coefficients are then computed via the spectral projection method with sparse grid approach. In addition, this strategy includes evaluation of the second or higher order sensitivity indices, allowing the study of interactions between several input variables. The principal focus of this analysis is to quantify the uncertainties in the total power and maximum fuel temperatures with respect to uncertainties in the initial transient conditions, such as rated power, fuel temperature, graphite fuel density and control rod boron concentration. In addition, both the first order and second order time-dependent sensitivity indices are computed and analyzed. The results show that the interactions between initial control rod boron concentration and the rated power will contribute at most 1% to the total uncertainty of the power peak.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

GPU code optimization using abstract kernel emulation and sensitivity analysis

In this paper, we develop a novel approach to GPU kernel optimization by focusing on identification of bottleneck resources and determining optimization parameters that can alleviate the bottleneck. Performance modeling for GPUs is done by abstract kernel emulation along with latency/gap modeling of resources. Sensitivity analysis with respect to resource latency/gap parameters is used to predict the bottleneck resource for a given kernel's execution. Here, the utility of the bottleneck analysis is demonstrated in two contexts: 1) Enhancing the OpenTuner auto-tuner with the new bottleneck-driven optimization strategy. Experimental results on all kernels from the Rodinia suite and GPU tensor contraction kernels from the NWChem computational chemistry suite demonstrate effectiveness. 2) Manual code optimization: two case studies illustrate the use of the bottleneck analysis to iteratively improve performance of code from state-of-the-art DSL code generators.

97 MATHEMATICS AND COMPUTING↗

Methodology for sensitivity analysis, approximate analysis, and design optimization in CFD for multidisciplinary applications

Fundamental equations of aerodynamic sensitivity analysis and approximate analysis for the two dimensional thin layer Navier-Stokes equations are reviewed, and special boundary condition considerations necessary to apply these equations to isolated lifting airfoils on 'C' and 'O' meshes are discussed in detail. An efficient strategy which is based on the finite element method and an elastic membrane representation of the computational domain is successfully tested, which circumvents the costly 'brute force' method of obtaining grid sensitivity derivatives, and is also useful in mesh regeneration. The issue of turbulence modeling is addressed in a preliminary study. Aerodynamic shape sensitivity derivatives are efficiently calculated, and their accuracy is validated on two viscous test problems, including: (1) internal flow through a double throat nozzle, and (2) external flow over a NACA 4-digit airfoil. An automated aerodynamic design optimization strategy is outlined which includes the use of a design optimization program, an aerodynamic flow analysis code, an aerodynamic sensitivity and approximate analysis code, and a mesh regeneration and grid sensitivity analysis code. Application of the optimization methodology to the two test problems in each case resulted in a new design having a significantly improved performance in the aerodynamic response of interest.

Taylor, Arthur C., III↗

Analytical Sensitivity Analysis of a Spent Nuclear Fuel Cask

Here, we report nuclear science and engineering is a field increasingly dominated by computational studies resulting from increasingly powerful computational tools. As a result, analytical studies, which previously pioneered nuclear engineering, are increasingly viewed as secondary or unnecessary. However, analytical solutions to reduced-fidelity models can provide important information concerning the underlying physics of a problem and aid in guiding computational studies. Similarly, there is increased interest in sensitivity analysis studies. These studies commonly use computational tools. However, providing a complementary sensitivity study of relevant analytical models can lead to a deeper analysis of a problem. This work provides the analytical sensitivity analysis of the one-dimensional (1D) cylindrical mono-energetic neutron diffusion equation using the forward sensitivity analysis procedure (FSAP) developed by Cacuci. Further, these results are applied to a reduced-fidelity model of a spent nuclear fuel cask, demonstrating how computational analysis might be improved with a complementary analytic sensitivity analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Analytical Voltage Sensitivity Analysis for Unbalanced Power Distribution System

Large scale integration of distributed energy resources and electric vehicles in a transactive energy environment present new challenges in terms of voltage stability and fluctuations in a power distribution system. The impact of different level of DER/EV penetration on the voltages across the network is typically quantified through voltage sensitivity analyses. Existing methods of voltage sensitivity analysis are computationally expensive and prior efforts to develop analytical approximation lacks generality and have not been effectively validated. The objective of this work is to provide a new analytical method of voltage sensitivity analysis that has low computational cost and also allows for stochastic analysis of voltage change. This paper first derives an analytical approximation of change in voltage at a particular bus due to change in power consumption at other bus in a radial three phase unbalanced power distribution system. Then, the proposed method is shown to be valid for different load configurations, which demonstrates its generality. The results from our analytical approach is validated via classical load flow simulation of the test system based on IEEE 37 bus network. The proposed method is shown to have good accuracy, and computation complexity is of order O(1), compared to O(n3) in classical sensitivity analysis approaches.

Munikoti, Sai↗

Design sensitivity analysis and optimization of built-up structures

Developments during the course of the research in design sensitivity analysis and optimization of built-up structures, with both sizing and shape design variables, show clearly that a unified variational approach to design sensitivity analysis can yield derivatives of structural response with respect to design. Rigorous and practically computable results for structural components and built-up structures have been demonstrated and used to solve design optimization problems.

Choi, Kyung K.↗