Search NASA⌕ Search

SEARCH · Search NASA

Results for “sensitivity analyses”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Sensitivity analysis for characterizing the impact of HNGD model on the prediction of hydrogen redistribution in Zircaloy cladding using BISON code

Hydrogen in zirconium cladding is able to precipitate into zirconium hydrides which impacts cladding integrity. The Hydride Nucleation-Growth-Dissolution (HNGD) model in the BISON code accounts for the precipitation and dissolution kinetics of hydride in Zircaloy material. This paper presents global sensitivity analyses of the HNGD model aiming to enhance our understanding of the hydride precipitation phenomena by quantifying the variance that key parameters have on the prediction of hydrogen behavior under various environmental conditions. Here, model predictions are compared to experimental data obtained under two different conditions: 1) with uniformly precharged specimens subjected to a linear thermal gradient, and 2) specimens precharged with a cathodically applied hydride rim at one end of the sample and subjected to an asymmetric thermal gradient. The Sobol sensitivity analysis identifies the key parameters in the HNGD model for both types of specimens. For linear temperature cases, the heat of transport dominates the accuracy of predictions when no precipitation occurs at the cold end, while Terminal Solid Solubility for Dissolution (TSSD) is the most important parameter when precipitation occurs. A large variation in the predicted hydrogen concentration profiles is found in the range of high TSSD due to the occurrence of precipitation. For asymmetric temperature cases, the solubility coefficient gives the largest impact on the predicted hydrogen distribution, as it determines the amount of solute hydrogen dissolved from the initially applied hydride rim. A large discrepancy in hydrogen distribution between simulations and experiments exists with the asymmetric specimens because BISON simulations fail to predict the precipitation of hydride at the cooler end. Comparative studies using former and updated models verifies the significant impact of the hydride growth mechanism on predicted hydrogen concentration profiles. In particular, when hydride initially exists, changes in TSSD generate a large variation in the predicted amount of precipitation by hydride growth, giving large uncertainty in predicting the hydrogen distribution over the sample length. The outputs characterize the significant impact of the hydride growth mechanism in the HNGD model on predicting hydrogen behavior, and improve the understanding of the precipitation of hydride in Zircaloy cladding within a range of expected environmental conditions. The analyses indicate work is still needed to improve the hydride solvus models in the BISON code to accurately predict experimentally observed hydride concentrations and distributions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Investigating uncertainties in human adaptation and their impacts on water scarcity in the Colorado river Basin, United States

The Colorado River Basin (CRB) supports the water supply for seven states and forty million people in the Western United States (US) and has been suffering an extensive drought for more than two decades. As climate change continues to reshape water resources distribution in the CRB, its impact can differ in intensity and location, resulting in variations in human adaptation behaviors. The feedback from human systems in response to the environmental changes and the associated uncertainty is critical to water resources management, especially for water-stressed basins. This paper investigates how human adaptation affects water scarcity uncertainty in the CRB and highlights the uncertainties in human behavior modeling. Our focus is on agricultural water consumption, as approximately 80% of the water consumption in the CRB is used in agriculture. We adopted a coupled agent-based and water resources modeling approach for exploring human-water system dynamics, in which an agent is a human behavior model that simulates a farmer’s water consumption decisions. We examined uncertainties at the system, agent, and parameter levels through uncertainty, clustering, and sensitivity analyses. The uncertainty analysis results suggest that the CRB water system may experience 13 to 30 years of water shortage during the 2019–2060 simulation period, depending on the paths of farmers’ adaptation. The clustering analysis identified three decision-making classes: bold, prudent, and forward-looking, and quantified the probabilities of an agent belonging to each class. The sensitivity analysis results indicated agents whose decision-making models require further investigation and the parameters with the higher uncertainty reduction potentials. Here, by conducting numerical experiments with the coupled model, this paper presents quantitative and qualitative information about farmers’ adaptation, water scarcity uncertainties, and future research directions for improving human behavior modeling.

Agent-based modeling↗
NASA NTRS1998

Nonlinear Analysis of the Space Shuttle Superlightweight LO2 Tank: Behavior Under 3g End-of-Flight Loads - Part 2

Results of linear bifurcation and nonlinear analyses of the Space Shuttle super lightweight (SLWT) external liquid-oxygen (LO2) tank are presented for an important end-of-flight loading condition. These results illustrate an important type of response mode for thin-walled shells, that are subjected to combined mechanical and thermal loads, that may be encountered in the design of other liquid-fuel launch vehicles. Linear bifurcation analyses are presented that predict several nearly equal eigenvalues that correspond to local buckling modes in the aft dome of the LO2 tank. In contrast, the nonlinear response phenomenon is shown to consist of a short-wavelength bending deformation in the aft elliptical dome of the LO2 tank that grows in amplitude in a stable manner with increasing load. Imperfection sensitivity analyses are presented that show that the presence of several nearly equal eigenvalues does not lead to a premature general instability mode for the aft dome. For the linear bifurcation and nonlinear analyses, the results show that accurate predictions of the response of the shell generally require a large-scale, high fidelity finite-element model. Results are also presented that show that the SLWT LO2 tank can support loads in excess of approximately 1.9 times the values of the operational loads considered.

Nemeth, Michael P.↗
NASA NTRS1998

Nonlinear Analysis of the Space Shuttle Superlightweight LO2 Tank: Bahavior Under Booster Ascent Loads - Part 1

Results of linear bifurcation and nonlinear analyses of the Space Shuttle superlightweight (SLWT) external liquid-oxygen (LO2) tank for an important early booster ascent loading condition are presented. These results for thin-walled linear elastic shells that are subjected to combined mechanical and thermal loads illustrate an important type of response mode that may be encountered in the design of other liquid-fuel launch vehicles. Linear bifurcation analyses are presented that predict several nearly equal eigenvalues that correspond to local buckling modes in the forward ogive section of the LO2 tank. In contrast, the nonlinear response phenomenon is shown to consist of short-wavelength bending deformations in the forward ogive and barrel sections of the LO2 tank that growing amplitude in a stable manner increasing load. Imperfection sensitivity analyses are presented that show that the presence of several nearly equal eigenvalues does not lead to a premature general instability mode for the forward ogive section. For the linear bifurcation and nonlinear analyses, the results show that accurate predictions of the response of the shield generally require a large-scale, high-fidelity finite-element model. Results are also presented that show that the SLWT LO2 tank can support loads in excess of approximately 2.6 times the values of the operational loads considered.

Young, Richard D.↗
DOE OSTI2022

Investigation of enhanced CO 2 storage in deep saline aquifers by WAG and brine extraction in the Minnelusa sandstone, Wyoming

Geological CO 2 sequestration in deep saline aquifers has been extendedly investigated to reach the goal of carbon neutral as large amount of CO 2 can be reduced in a short time. Here, this study investigates the feasibility of water-alternating-gas (WAG) injection and brine extraction on enhancing CO 2 storage in a target deep saline aquifer, Minnelusa Sandstone in the Powder River Basin (PRB) of Wyoming. An integrated numerical model is developed to account for four scenarios: (1) CO 2 continuous injection (CI) through one injection well, (2) WAG injection through one injection well, (3) CO 2 CI through one injection well and brine extraction through one producer, (4) WAG injection through one injection well and brine extraction through one producer. Simulation results suggest that WAG injection and brine extraction corporately make it possible to enhance CO 2 injectivity while securing CO 2 storage safety. For instance, WAG injection considerably reduces structural trapping contribution while enhances dissolved and residual trapping contributions. As for brine extraction, it can decrease the maximum averaged reservoir pressure by 37% and 22% for CI and WAG injection, respectively. Besides, sensitive analyses of the operational parameters for the fourth scenarios are performed. Results reveal that, when the amount of total CO 2 injection has been predetermined, CO 2 injection time and rate within each period of WAG should be small whereas it is preferable to have large water injection time and rate. This is to secure desirable dissolved and residual trapping contributions (store CO 2 with safety). Sensitive degree results confirm that CO 2 injection rate, water injection time, and CO 2 injection time of WAG injection exhibit significant effects on CO 2 storage whereas the impacts of producer bottom-hole pressure (BHP), water injection rate, and CO 2 -water injection time are relatively weaker. This study not only sheds light on achieving double-win goal: enhance CO 2 injectivity and store CO 2 with safety, but also can be a critical reference for other CO 2 storage in deep saline aquifers.

58 GEOSCIENCES↗
NASA NTRS2017

Sensitivity Analysis and Uncertainty Quantification of a Mars Ascent Vehicle Concept

The design of a conceptual Mars ascent vehicle is a challenging problem. In order to aid the vehicle and mission concept design it is important to understand the driving design parameters and the expected performance in the presence of model errors and uncertainties. An existing six degree of freedom simulation model is analyzed on a statistical basis using the methods available in the Design Analysis Kit for Optimization and Terascale Applications toolkit. The methods utilized include conventional Monte Carlo techniques, metamodeling via polynomial chaos expansions, and global variance-based sensitivity analyses. Two additional analysis methods referred to as “Monte Carlo filtering” and ”Classification trees” are used to determine which uncertain parameters are driving the performance of the vehicle. Monte Carlo filtering provides a methodology to determine which parameters cause qualitatively different behavior while the classification trees use heuristics to partition the input space and assign probabilities to each partition. These methods serve as qualitative descriptors of model sensitivity while variance-based global sensitivity analysis seeks a quantitative mapping from total output variance to the variance of individual inputs. Application of these techniques to several outputs of a Mars ascent vehicle concept simulation indicates that only a select few input factors dominate their variance.

Noyes, Connor↗
DOE OSTI2020

Effects of Photovoltaic Module Materials and Design on Module Deformation Under Load

Static structural finite element models of an aluminum-framed crystalline silicon (c-Si) photovoltaic (PV) module and a glass-glass thin film PV module were constructed and validated against experimental measurements of deflection under uniform pressure loading. Parametric analyses using Latin Hypercube Sampling (LHS) were performed to propagate simulation input uncertainties related to module material properties, dimensions, and manufacturing tolerances into expected uncertainties in simulated deflection predictions. This exercise verifies the applicability and validity of finite element modeling for predicting mechanical behavior of solar modules across architectures and enables computational models to be used with greater confidence in assessment of module mechanical stressors and design for reliability. Sensitivity analyses were also performed on the uncertainty quantification data sets using linear correlation coefficients to elucidate the key parameters influencing module deformation. This information has implications on which materials or parameters may be optimized to best increase module stiffness and reliability, whether the key optimization parameters change with module architecture or loading magnitudes, and whether parameters such as frame design and racking must be replicated in reduced-scale reliability studies to adequately capture full module mechanical behavior.

14 SOLAR ENERGY↗
DOE OSTI2021

Sensitivity and Effective Parameterization of a Multi-Scale Model of Proton-Exchange-Membrane Water Electrolysis

The development of proton-exchange-membrane water electrolysis (PEMWE) is crucial to establishing a green-hydrogen infrastructure. Active research in hydrogen technologies is focused on minimizing costs, improving efficiency, and mitigating safety risks. In this study, sensitivity analyses were performed using a physics-based model and used to identify critical parameters capable of reducing overpotentials and safety risks. These parameters include operational (i.e. temperature), structural (i.e. thickness of the components), and material properties (i.e. exchange current density). Simulated results suggest that better engineering of the membrane electrode assemblies (MEA) can offset intrinsic limitations. Membrane thickness and conductivity yielded the largest percent change on performance. Gas crossover was observed to be sensitive to diffusion, solubility, and bubble formation. Current density regimes were identified, where each crossover parameter was most influential. MEA parameterization serves as a framework for theoretical PEMWE optimization simulations and input for design criteria for future research targets.

Dizon, A↗
DOE OSTI2024

The Core-collapse Supernova Sensitivity Machine (Final Technical Report)

Core-collapse supernovae are vital phenomena for understanding the extreme physics of stellar evolution, nuclear interactions, and the origins of elements in the universe. This project developed high-resolution 3D simulations and innovative 1D turbulence models to study the explosion mechanisms, yielding critical insights into the role of turbulence, magnetohydrodynamics, and neutrino physics. The outcomes include enhanced sensitivity analyses connecting nuclear physics inputs to observable supernovae characteristics, tools for the broader research community, and substantial contributions to the training of future scientists.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Estimating the Acute Health Impacts of Fire-Originated PM 2.5 Exposure During the 2017 California Wildfires: Sensitivity to Choices of Inputs

Exposure to wildfire smoke increases the risk of respiratory and cardiovascular hospital admissions. Health impact assessments, used to inform decision-making processes, characterize the health impacts of environmental exposures by combining preexisting epidemiological concentration–response functions (CRFs) with estimates of exposure. These two key inputs influence the magnitude and uncertainty of the health impacts estimated, but for wildfire-related impact assessments the extent of their impact is largely unknown. We first estimated the number of respiratory, cardiovascular, and asthma hospital admissions attributable to fire-originated PM 2.5 exposure in central California during the October 2017 wildfires, using Monte Carlo simulations to quantify uncertainty with respect to the exposure and epidemiological inputs. We next conducted sensitivity analyses, comparing four estimates of fire-originated PM 2.5 and two CRFs, wildfire and nonwildfire specific, to understand their impact on the estimation of excess admissions and sources of uncertainty. We estimate the fires accounted for an excess 240 (95% CI: 114, 404) respiratory, 68 (95% CI: -10, 159) cardiovascular, and 45 (95% CI: 18, 81) asthma hospital admissions, with 56% of admissions occurring in the Bay Area. Although differences between impact assessment methods are not statistically significant, the admissions estimates' magnitude is particularly sensitive to the CRF specified while the uncertainty is most sensitive to estimates of fire-originated PM 2.5 . Not accounting for the exposure surface's uncertainty leads to an underestimation of the uncertainty of the health impacts estimated. Employing context-specific CRFs and using accurate exposure estimates that combine multiple data sets generates more certain estimates of the acute health impacts of wildfires.

58 GEOSCIENCES↗
NASA NTRS2011

The Fate of Saharan Dust Across the Atlantic and Implications for a Central American Dust Barrier

Saharan dust was observed over the Caribbean basin during the summer 2007 NASA Tropical Composition, Cloud, and Climate Coupling (TC4) field experiment. Airborne Cloud Physics Lidar (CPL) and satellite observations from MODIS suggest a barrier to dust transport across Central America into the eastern Pacific. We use the NASA GEOS-5 atmospheric transport model with online aerosol tracers to perform simulations of the TC4 time period in order to understand the nature of this barrier. Our simulations are driven by the Modem Era Retrospective-Analysis for Research and Applications (MERRA) meteorological analyses. We evaluate our baseline simulated dust distributions using MODIS and CALIOP satellite and ground-based AERONET sun photometer observations. GEOS-5 reproduces the observed location, magnitude, and timing of major dust events, but our baseline simulation does not develop as strong a barrier to dust transport across Central America as observations suggest. Analysis of the dust transport dynamics and lost processes suggest that while both mechanisms play a role in defining the dust transport barrier, loss processes by wet removal of dust are about twice as important as transport. Sensitivity analyses with our model showed that the dust barrier would not exist without convective scavenging over the Caribbean. The best agreement between our model and the observations was obtained when dust wet removal was parameterized to be more aggressive, treating the dust as we do hydrophilic aerosols.

Nowottnick, E.↗
NASA NTRS1984

An analysis of the AVE-SESAME I period using statistical structure and correlation functions

Structure and correlation functions are used to describe atmospheric variability during the 10-11 April day of AVE-SESAME 1979 that coincided with the Red River Valley tornado outbreak. The special mesoscale rawinsonde data are employed in calculations involving temperature, geopotential height, horizontal wind speed and mixing ratio. Functional analyses are performed in both the lower and upper troposphere for the composite 24 h experiment period and at individual 3 h observation times. Results show that mesoscale features are prominent during the composite period. Fields of mixing ratio and horizontal wind speed exhibit the greatest amounts of small-scale variance, whereas temperature and geopotential height contain the least. Results for the nine individual times show that small-scale variance is greatest during the convective outbreak. The functions also are used to estimate random errors in the rawinsonde data. Finally, sensitivity analyses are presented to quantify confidence limits of the structure functions.

Fuelberg, H. E.↗
DOE OSTI2022

Development of k{sub eff} in the unfolding process of the LOTUS reactor design

An innovative small thermal reactor concept named LOTUS, which is a pool-type reactor aimed at heat supply. The passive concept applied in the LOTUS and it has a separable core. It means that its core can passively unfold into four parts along its central axis only with the buoyancy and gravity when some accidents happen, especially the wall rupture of the pool caused by earthquake, aircraft impact and so on. This idea can effectively enhance the ability of pool-type reactor for resisting some severe accidents. We have executed some pre-computations in order to check a non-supercritical system for the transient simulation. In this paper, the development of k{sub eff} have been calculated by both stepwise steady-state and transient modes using Serpent, as well as including some sensitivity analyses about the k{sub eff} to unfolding velocity, inserting velocity of control rod (CR) and time step. The result showed that k{sub eff} value decreased definitely as the reactor unfolded and the consistent change exposed between the stepwise steady state and transient result when the unfolding angle varied from 0 to 1 degree. However, the stepwise steady state k{sub eff} negatively declined after that angle, which demonstrated that for such a dynamic unfolding change the transient mode was more suitable, peculiarly for considering delayed neutrons and neutron moderation. For sensitivity calculation, the k{sub eff} decreased more rapidly as the unfolding velocity and inserting velocity of CR increased, and a smaller time step corresponded to a more stable change. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2018

Impact of Fluid Flow Pressure drop on Temperature of Components Controlled by Mechanically Pumped Fluid Loop Thermal Control System

In a typical thermal control system that employs a mechanically pumped fluid loop to control component temperatures, fluid flow pressure drop is minimized to ensure that adequate fluid flow can be provided by the pump. Engineers often are overly concerned about violating a maximum pressure drop, almost treating it as a “wall” that should not be crossed. The true “wall” is the control of the temperatures of the components served by the loop to ensure that their temperatures do not violate their allowed limits. As a case study, for assessing this “constraint,” sensitivity analyses were undertaken to understand if this is truly a major constraint, and to assess the impact of pressure drop exceedance on the controlled components’ temperatures. The flow impedance is varied as a parameter to understand how it affects the controlled components’ temperatures. One key finding was that the temperatures of the controlled components is relatively insensitive to the flow impedance increases. This finding is obviously most relevant to this particular case study; however, this also provides the process and guidance for assessing the performance of other pump/loop combinations in terms of their sensitivity to pressure drop impedances.

Mastropietro, Arthur J.↗
NASA NTRS2007

Blurring the Inputs: A Natural Language Approach to Sensitivity Analysis

To document model parameter uncertainties and to automate sensitivity analyses for numerical simulation codes, a natural-language-based method to specify tolerances has been developed. With this new method, uncertainties are expressed in a natural manner, i.e., as one would on an engineering drawing, namely, 5.25 +/- 0.01. This approach is robust and readily adapted to various application domains because it does not rely on parsing the particular structure of input file formats. Instead, tolerances of a standard format are added to existing fields within an input file. As a demonstration of the power of this simple, natural language approach, a Monte Carlo sensitivity analysis is performed for three disparate simulation codes: fluid dynamics (LAURA), radiation (HARA), and ablation (FIAT). Effort required to harness each code for sensitivity analysis was recorded to demonstrate the generality and flexibility of this new approach.

Kleb, William L.↗
DOE OSTI2021

Bidirectional LCC-LCC -Compensated 20 kW Wireless Power Transfer System for Medium-Duty Vehicle Charging

This paper presents the design and demonstration of a bidirectional 20 kW wireless charging system (WCS) with a significantly large airgap (11 inches) and asymmetrical input-output voltage levels. Analytical and experimental sensitivity analyses of the WCS resonant tank were conducted to verify the optimal operating region under the load and frequency variation. The inverter and rectifier were designed with switching components, the charging pads were designed with double-D (DD) coils, and the tuning networks were designed with an LCC-LCC tuning circuit. The grid and vehicle side tuning circuits were designed separately to achieve a ~1:2 gain for the asymmetrical input (800 V dc ) and output (350 V dc ) voltage. The proposed WCS was designed, simulated, and tested to verify the efficiency, power transfer capacity, and sensitivity under load variation. The experimental results show that, at 20-kW output power, the achieved grid to vehicle dc-dc efficiency was 96.1%, and vehicle to grid dc-dc efficiency was 96.2%. The proposed system is the largest-airgap bidirectional WCS with the highest efficiency and power density.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2017

Accounting for Epistemic Uncertainty in Mission Supportability Assessment: A Necessary Step in Understanding Risk and Logistics Requirements

Future crewed missions to Mars present a maintenance logistics challenge that is unprecedented in human spaceflight. Mission endurance – defined as the time between resupply opportunities – will be significantly longer than previous missions, and therefore logistics planning horizons are longer and the impact of uncertainty is magnified. Maintenance logistics forecasting typically assumes that component failure rates are deterministically known and uses them to represent aleatory uncertainty, or uncertainty that is inherent to the process being examined. However, failure rates cannot be directly measured; rather, they are estimated based on similarity to other components or statistical analysis of observed failures. As a result, epistemic uncertainty – that is, uncertainty in knowledge of the process – exists in failure rate estimates that must be accounted for. Analyses that neglect epistemic uncertainty tend to significantly underestimate risk. Epistemic uncertainty can be reduced via operational experience; for example, the International Space Station (ISS) failure rate estimates are refined using a Bayesian update process. However, design changes may re-introduce epistemic uncertainty. Thus, there is a tradeoff between changing a design to reduce failure rates and operating a fixed design to reduce uncertainty. This paper examines the impact of epistemic uncertainty on maintenance logistics requirements for future Mars missions, using data from the ISS Environmental Control and Life Support System (ECLS) as a baseline for a case study. Sensitivity analyses are performed to investigate the impact of variations in failure rate estimates and epistemic uncertainty on spares mass. The results of these analyses and their implications for future system design and mission planning are discussed.

Owens, Andrew↗