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At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Sensitivity of Precipitation to Parameter Values in the Community Atmosphere Model Version 5

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.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

A methodology for optimal MSW management, with an application in the waste transportation of Attica Region, Greece

Highlights: • A two-step (strategic and detailed optimal planning) methodology is used for solving complex MSW management problems. • A software package is outlined, which can be used for generating detailed optimal plans. • Sensitivity analysis compares alternative scenarios that address objections and/or wishes of local communities. • A case study shows the application of the above procedure in practice and demonstrates the results and benefits obtained. - Abstract: The paper describes a software system capable of formulating alternative optimal Municipal Solid Wastes (MSWs) management plans, each of which meets a set of constraints that may reflect selected objections and/or wishes of local communities. The objective function to be minimized in each plan is the sum of the annualized capital investment and annual operating cost of all transportation, treatment and final disposal operations involved, taking into consideration the possible income from the sale of products and any other financial incentives or disincentives that may exist. For each plan formulated, the system generates several reports that define the plan, analyze its cost elements and yield an indicative profile of selected types of installations, as well as data files that facilitate the geographic representation of the optimal solution in maps through the use of GIS. A number of these reports compare the technical and economic data from all scenarios considered at the study area, municipality and installation level constituting in effect sensitivity analysis. The generation of alternative plans offers local authorities the opportunity of choice and the results of the sensitivity analysis allow them to choose wisely and with consensus. The paper presents also an application of this software system in the capital Region of Attica in Greece, for the purpose of developing an optimal waste transportation system in line with its approved waste management plan. The formulated plan was able to: (a) serve 113 Municipalities and Communities that generate nearly 2 million t/y of comingled MSW with distinctly different waste collection patterns, (b) take into consideration several existing waste transfer stations (WTS) and optimize their use within the overall plan, (c) select the most appropriate sites among the potentially suitable (new and in use) ones, (d) generate the optimal profile of each WTS proposed, and (e) perform sensitivity analysis so as to define the impact of selected sets of constraints (limitations in the availability of sites and in the capacity of their installations) on the design and cost of the ensuing optimal waste transfer system. The results show that optimal planning offers significant economic savings to municipalities, while reducing at the same time the present levels of traffic, fuel consumptions and air emissions in the congested Athens basin.

42 ENGINEERING↗
NASA NTRS1983

Optimum sensitivity derivatives of objective functions in nonlinear programming

The feasibility of eliminating second derivatives from the input of optimum sensitivity analyses of optimization problems is demonstrated. This elimination restricts the sensitivity analysis to the first-order sensitivity derivatives of the objective function. It is also shown that when a complete first-order sensitivity analysis is performed, second-order sensitivity derivatives of the objective function are available at little additional cost. An expression is derived whose application to linear programming is presented.

Barthelemy, J.-F. M.↗
DOE OSTI2015

Life cycle assessment of integrated waste management systems for alternative legacy scenarios of the London Olympic Park

Highlights: • Application of LCA in planning integrated waste management systems. • Environmental valuation of 3 legacy scenarios for the Olympic Park. • Hot-spot analysis highlights the importance of energy and materials recovery. • Most environmental savings are achieved through materials recycling. • Sensitivity analysis shows importance of waste composition and recycling rates. - Abstract: This paper presents the results of the life cycle assessment (LCA) of 10 integrated waste management systems (IWMSs) for 3 potential post-event site design scenarios of the London Olympic Park. The aim of the LCA study is to evaluate direct and indirect emissions resulting from various treatment options of municipal solid waste (MSW) annually generated on site together with avoided emissions resulting from energy, materials and nutrients recovery. IWMSs are modelled using GaBi v6.0 Product Sustainability software and results are presented based on the CML (v.Nov-10) characterisation method. The results show that IWMSs with advanced thermal treatment (ATT) and incineration with energy recovery have the lowest Global Warming Potential (GWP) than IWMSs where landfill is the primary waste treatment process. This is due to higher direct emissions and lower avoided emissions from the landfill process compared to the emissions from the thermal treatment processes. LCA results demonstrate that significant environmental savings are achieved through substitution of virgin materials with recycled ones. The results of the sensitivity analysis carried out for IWMS 1 shows that increasing recycling rate by 5%, 10% and 15% compared to the baseline scenario can reduce GWP by 8%, 17% and 25% respectively. Sensitivity analysis also shows how changes in waste composition affect the overall result of the system. The outcomes of such assessments provide decision-makers with fundamental information regarding the environmental impacts of different waste treatment options necessary for sustainable waste management planning.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

An Evaluation of the Potential for Shifting of Freight from Truck to Rail and Its Impacts on Energy Use and GHG Emissions

This report summarizes our evaluation of the potential energy-use and GHG-emissions reduction achieved by shifting freight from truck to rail under a most-likely scenario. A sensitivity analysis is also included. The sensitivity analysis shows changes in energy use and GHG emissions when key parameters are varied. The major contribution and distinction from previous studies is that this study considers the rail level of service (LOS) and commodity movements at the origin-destination (O-D) level. In addition, this study considers the fragility and time sensitivity of each commodity type.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Visual HPC Workflows for the Analysis of System Dynamics Models

Visual analytics supported by high performance computing (HPC) accelerates and enhances the discovery, exploration, and analysis of causal patterns in complex system dynamics (SD) models. We present a suite of visualization-assisted ensemble-based techniques for hypothesis generation and testing, and for sensitivity analysis. By employing HPC to provide parallel, on-demand simulation of SD models, one can “steer” an ensemble of simulated scenarios in real time as one first formulates and then informally tests those hypotheses: this provides rapid feedback for analysts to refine their understanding of the causal relationships emergent from a model. Such understandings can be followed and augmented by rigorous application of statistical methods, namely global variance-based sensitivity analysis, Monte-Carlo filtering, adaptive regional sensitivity analysis, and self-organized maps: here timely computation relies on HPC, while effective presentation emphasizes high-dimensional multivariate data visualization. Immersive visualization in virtual 3D environments provides an excellent adjunct to the traditional 2D graphics typically used for SD models, as it generates an embodied understanding of model behavior and facilitates an active, collaborative critique of model structure and output. Finally, we summarize prospects for HPC-enabled visual analytics applied to SD modeling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1992

Multidisciplinary analysis and sensitivity derivatives for isolated helicopter rotors in hover

A new method is presented for using Navier-Stokes results in the system analysis and sensitivity derivative computations for a helicopter rotor in hover. The system coupling includes the interactions between rotor performance, rotor structural properties and aerodynamics (i.e., airfoil shape). Emphasis is placed on the use of high fidelity Navier-Stokes algorithms for the aerodynamic problem. The present formulation is chosen to reduce the number of sensitivity derivative equations and their dimensions as much as possible. In addition, an alternative adjoint formulation is presented which dramatically reduces the computational requirement for disciplines in which there may be a large number of design variables (e.g., aerodynamics). The theoretical method makes use of a combination of derivatives from each discipline; the computation of these derivatives has already been shown to be feasible. Sample computations for the aerodynamic-rotor model coupling and an associated sensitivity derivative are also presented.

Jones, Henry E.↗
DOE OSTI2021

Sizing Energy Storage System for Energy Arbitrage in Extreme Fast Charging Station

This paper proposes a non-linear programming (NLP) model to optimally size the energy storage system (ESS) and obtain an optimal energy management for energy arbitrage of an extreme fast charging station (XFCS) for electric vehicles (EVs), with minimized total cost of XFCS operation and ESS investment. Different from most reported work on sizing the ESS for EV charging stations, this paper proposes a pragmatic approach to model the ESS life degradation and accurately count the ESS cycles. Moreover, this work incorporates the peak demand charges in the operational cost of the charging station which are often overlooked in the literature. The proposed model is formulated and solved using AIMMS. Finally, a thorough sensitivity analysis is performed to offer insights into how different input parameters impact the ESS sizing and savings from the energy arbitrage perspective.

25 ENERGY STORAGE↗
NASA NTRS1993

A sensitive continuum analysis method for gamma ray spectra

In this work we examine ways to improve the sensitivity of the analysis procedure for gamma ray spectra with respect to small differences in the continuum (Compton) spectra. The method developed is applied to analyze gamma ray spectra obtained from planetary mapping by the Mars Observer spacecraft launched in September 1992. Calculated Mars simulation spectra and actual thick target bombardment spectra have been taken as test cases. The principle of the method rests on the extraction of continuum information from Fourier transforms of the spectra. We study how a better estimate of the spectrum from larger regions of the Mars surface will improve the analysis for smaller regions with poorer statistics. Estimation of signal within the continuum is done in the frequency domain which enables efficient and sensitive discrimination of subtle differences between two spectra. The process is compared to other methods for the extraction of information from the continuum. Finally we explore briefly the possible uses of this technique in other applications of continuum spectra.

Thakur, Alakh N.↗
DOE OSTI2020

Probabilistic modeling and prediction of out-of-plane unidirectional composite lamina properties

Computational simulation provides an efficient means to predict the behavior of customized hybrid material configurations using validated, physics-based models. One limitation to this approach is the quality and quantity of available data to characterize the many constituent input properties. Therefore, a systematic approach to identify the most influential parameters on the hybrid behavior and quantify the corresponding uncertainty in predictive capabilities is required. Here, an approach using Bayesian multimodel inference and imprecise global sensitivity analysis is presented to investigate the effects of sparse constituent data on the prediction of composite material properties. The methodology allows the identification, using quantified uncertainties, of the most influential constituent material parameters for specified homogenized properties. This sensitivity analysis further enables a dimension reduction when assessing the influence of uncertainties on material properties and can be used to inform testing programs of the constituent properties that require additional testing/data collection in order to minimize uncertainty in macro-scale composite properties. The methodology is specifically demonstrated on the prediction and sensitivity analysis of out-of-plane mechanical properties of a unidirectional lamina.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Sensitivity-based Similarity Metrics for New Experiment Design Optimization

The nuclear data used in advanced reactor simulations requires validation. Data from nuclear criticality experiments can provide this validation. New nuclear criticality experiment design requires extensive knowledge and expert judgement such that the experimental design parameters are selected in such a way to keep the experiment subcritical. To aide in this experimental design process, professionals can utilize sensitivity and uncertainty analysis. Sensitivity and uncertainty analysis relies on matching new application experiments with currently existing benchmark experiments. Currently, there is functionality in the Whisper 1.1 software package to calculate a similarity metric based on neutron multiplication factor sensitivity coefficients between a new application designed by the user and existing International Criticality Safety Benchmark Experiment Project (ICSBEP) benchmarks. The Whisper 1.1 software package is included in Monte Carlo N-Particle ® Code Version 6.21 (MCNP ® 6.2). This work is geared toward expanding this capability to new similarity metrics based on beta-effective sensitivity coefficients and reactivity coefficient sensitivity coefficients. While the investigation of these sensitivity coefficients is presented in detail in separate works at this same conference, this work will be primarily focused on studying the similarity metrics in more detail. These similarity metrics will then be incorporated into the optimization algorithms used for experiment design in EUCLID (Experiments Underpinned by Computational Learning for Improvements in nuclear Data), which is a Los Alamos National Laboratory (LANL) project designed to constrain nuclear data of interest, such that adjustments can be made to possible inaccuracies. A more detailed optimization can be subsequently performed by breaking down these similarity metrics by isotope, reaction, and energy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1990

Application of advanced multidisciplinary analysis and optimization methods to vehicle design synthesis

Advanced multidisciplinary analysis and optimization methods, namely system sensitivity analysis and non-hierarchical system decomposition, are applied to reduce the cost and improve the visibility of an automated vehicle design synthesis process. This process is inherently complex due to the large number of functional disciplines and associated interdisciplinary couplings. Recent developments in system sensitivity analysis as applied to complex non-hierarchic multidisciplinary design optimization problems enable the decomposition of these complex interactions into sub-processes that can be evaluated in parallel. The application of these techniques results in significant cost, accuracy, and visibility benefits for the entire design synthesis process.

Consoli, Robert David↗
NASA NTRS1993

An adjoint sensitivity study of blocking in a two-layer isentropic model

This paper presents a new methodology for adjoint sensitivity analysis, previously developed in general terms by Cacuci, into a form directly applicable 10 meteorological problems. This technique is illustrated by examining the sensitivity of a blocking index in a two-layer isentropic model. The index represents a response function for the sensitivity analysis that unlike previous meteorological applications, is an operator and not a functional, and thus extends the scope of adjoint sensitivity to general operator-type responses depending on time and/or space. The sensitivity of the blocking index to perturbations introduced into the model atmosphere, as well as to model parameters, is discussed. The methodology of generalized adjoint sensitivity analysis described in this paper constitutes a prototype for further applications in the atmospheric and/or oceanic sciences.

Zou, X.↗
DOE OSTI2024

National Wind Workforce Assessment Methods Report: Surveys and System Dynamics Model

This report documents the methodology for the National Wind Workforce Assessment: Challenges, Opportunities, and Future Needs (McDowell et al. 2023) report. Here, the authors will describe how multiple survey efforts and system dynamics modeling have been used to estimate wind energy workforce needs and conduct a sensitivity analysis. We conducted workforce estimation and sensitivity analysis to help inform actions that can be used to ensure that workforce planning in the industry is done in a way that is sustainable.

17 WIND ENERGY↗
DOE OSTI2017

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

The Colorado River basin is a fundamentally important river for society, ecology and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model. Here, we combine global sensitivity analysis with a space-filling Latin Hypercube sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Efficient Adjoint Computation of Hybrid Systems of Differential Algebraic Equations with Applications in Power Systems

Sensitivity analysis is an important tool to describe power system dynamic behavior in response to parameter variations. It is a central component in preventive and corrective control applications. The existing approaches for sensitivity calculations, namely, finite-difference and forward sensitivity analysis, require a computational effort that increases linearly with the number of sensitivity parameters. In this work, we investigate, implement, and test a discrete adjoint sensitivity approach whose computational effort is effectively independent of the number of sensitivity parameters. The proposed approach is highly efficient for calculating trajectory sensitivities of larger systems and is consistent, within machine precision, with the function whose sensitivity we are seeking. This is an essential feature for use in optimization applications. Moreover, our approach includes a consistent treatment of systems with switching, such as DC exciters, by deriving and implementing the adjoint jump conditions that arise from state and time-dependent discontinuities. The accuracy and the computational efficiency of the proposed approach are demonstrated in comparison with the forward sensitivity analysis approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Thermal Analysis for SRS Saltstone Disposal Unit Facility

Saltstone Disposal Units (SDU) are long term disposal units for low activity grout produced from the solidification of decontaminated non-hazardous salt waste at SRS. The unit is a cylindrical disposal vault of 150 ft. in diameter and 23 ft. in height. The total volume the SDU can hold is 3 million gallons of grout. The hydration process of the grout material produces heat from an exothermic chemical reaction. If the grout reaches temperatures higher than the maximum safety temperature of 95 deg. C, cracks can start forming leading to contamination of the environment. The purpose of this study is to develop the optimal baseline domain boundary conditions and to perform a sensitivity analysis with respect to the baseline modeling conditions. The following assumptions were made for the modeling calculations: - The system geometry is axisymmetric; - The system was at steady state; - Ambient temperature was set to 100 deg. F; - Air was assumed to be an incompressible ideal gas; - Radiation was neglected for a conservative estimation; - Natural convection for the SDU vapor space is assumed to be turbulent because Rayleigh number based on typical operating conditions is higher than 10{sup 8}; - Water tables were not taken into consideration. The following sensitivity analyses were performed to find the optimal domain boundary: - Mesh size sensitivity; - Soil depth sensitivity - Soil depth varied from 30 ft to 250 ft with a soil thickness of 90 ft; - Soil thickness sensitivity - Soil thickness varied from 30 ft to 270 ft with a soil depth of 180 ft; - Soil conductivity sensitivity - Soil thermal conductivity varied from 0.25 W/m-K to 1 W/m-K; - Ambient Temperature Sensitivity - Ambient temperature varied from 70 deg. F to 110 deg. F. For the thermal calculations, the temperature of the bottom of the soil was set to 17.4 deg. C. The heat flux on the roof of the building and surface of the earth is 163.2 W/m{sup 2}. The soil sides are set to be adiabatic. The sensitivity analysis shows that the mesh size has no effect on the numerical results. This is mainly due to a small convection zone and large conduction zones in the modeling domain. The optimal domain boundary was found to be a soil thickness of 90 ft and a soil depth of 150 ft. The different sensitivity analysis performed here shows the optimal boundary domain to be used for thermal calculations is a soil depth of 150 ft beneath the SDU and a soil thickness of 90 ft. Anything larger would produce similar solutions but at a longer computational time to solve. The maximum temperature was more sensitive to soil properties as shown here. While the ambient temperature affected the max temperature linearly. Most of the heat transfer takes place downward vertically between the SDU and the soil beneath it. Using the optimal domain boundary determined by the sensitivity analyses, the maximum thermal loading to keep the maximum grout temperature below 95 deg. C is 1.646 W/m{sup 3}.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Reduced Order Models Generation for HTGRs Pebble Shuffling Procedure Optimization Studies

This report provides an initial study for producing reduced-order models (ROMs) of pebble-bed high temperature gas reactor (HTGR) models for the purposes of design optimization. As an initial study, this work is meant to be exploratory---identifying useful workflows and methods for ROM generation---and not meant to be a catch-all analysis of HTGR ROM generation and usage for optimization. This report summarizes three tasks performed in Fiscal Year 2022: 1) the creation of HTGR model, 2) the sensitivity analysis of model design parameters, and 3) an introduction to ROM generation techniques. The representative HTGR model created in this work is a multiphysics equilibrium-core using the BlueCRAB (comprehensive reactor analysis bundle) reactor analysis application, coupling four physical phenomena: neutronics, streamline depletion, porous flow thermal hydraulics, and pebble heat conduction. Part of the model creation was identifying some design parameters and quantities of interest that are relevant in an optimization analysis and adjustable in the model. The sensitivity analysis utilized a polynomial chaos expansion methodology to compute global sensitivity metrics. This analysis showed that thermal hydraulics parameters and quantities of interest had a relatively small impact on simulation results. Finally, the ROM generation work involved exploring three different ROM methodologies: polynomial regression, a Gaussian process, and artificial neural networks. Using a cross-validation technique to characterize ROM performance, the Gaussian process and single-layer artificial neural networks showed the most promising results. Overall, this study was insightful and the lessons learned will be invaluable for the eventual development of an HTGR design optimization workflow.

97 MATHEMATICS AND COMPUTING↗