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Results for “Sensitivity analysis”

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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Silicon solar cells, a manufacturing cost analysis

A detailed cost analysis of solar cell module manufacturing, utilizing process sequences incorporating near-term technology, has been performed. The entire structuring of a factory to manufacture solar cell modules, starting from supplied polycrystalline silicon and other raw materials, was specified. This analysis then formed the basis for a sensitivity analysis of the major cost factors. The results of the cost and sensitivity analyses are presented here.

Grenon, L. A.↗
DOE OSTI2015

Improvement of the management of residual waste in areas without thermal treatment facilities: A life cycle analysis of an Italian management district

Highlights: • LCA analysis of two option for residual waste management. • Exploitation of mechanical physical sorting facility for extracting recyclable from RMSW. • Processing the mechanically sorted organic fraction in bioreactor landfill. • Sensitivity analysis demonstrate high influence for impact assessment of substitution ratio for recycle materials. - Abstract: Starting from an existing waste management district without thermal treatment facilities, two different management scenarios for residual waste were compared by life cycle assessment (LCA). The adoption of a bioreactor landfill for managing the mechanically sorted organic fraction instead of bio-stabilization led to reduction of global warming and fresh water eutrophication by 50% and 10%, respectively. Extraction of recyclables from residual waste led to avoided emissions for particulate matter, acidification and resource depletion impact categories. Marginal energy and the amount of energy recovered from landfill gas marginally affected the LCA results. On the contrary the quality of the recyclables extracted can significantly modify the eco profile of the management schemes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Dakota-MCNP Coupling for Uncertainty Analysis using Polynomial Chaos Expansions

Uncertainty quantification (UQ) seeks to characterize the total uncertainty in a system's response given the cumulative effect of uncertainties found in the physical input parameters. UQ is closely related to, and is often followed by, sensitivity analysis (SA). SA seeks to characterize the contribution individual uncertain parameters have on the total uncertainty in the system. UQ and SA are important, because it is often difficult to establish confidence levels in numerical predictions. This arises due to the differences between noumenal reality and computer modeled simulations. Often, these are due either to a lack of knowledge about the problem being analyzed (epistemic uncertainty), or impracticality associated with modeling and simulating a physical phenomenon sufficiently accurately. It is the primary goal of UQ and SA to first quantify the difference between reality and simulation, and second to determine the significance this difference has on relevant physical responses.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2004

Multidisciplinary Analysis and Optimal Design: As Easy as it Sounds?

The viewgraph presentation examines optimal design for precision, large aperture structures. Discussion focuses on aspects of design optimization, code architecture and current capabilities, and planned activities and collaborative area suggestions. The discussion of design optimization examines design sensitivity analysis; practical considerations; and new analytical environments including finite element-based capability for high-fidelity multidisciplinary analysis, design sensitivity, and optimization. The discussion of code architecture and current capabilities includes basic thermal and structural elements, nonlinear heat transfer solutions and process, and optical modes generation.

design optimization↗
DOE OSTI2025

Life-cycle cost-benefit analysis of a novel self-heating pavement made from coal-derived solid carbon

Winter weather events challenge the safety, efficiency, and sustainability of roadway networks, particularly road bridges vulnerable to climate impacts. Although effective, conventional de-icing methods incur high expenses and cause significant environmental contamination. To address these longstanding issues, a low-cost novel coal-derived carbon enabled smart pavement (CDC-SP) de-icing system was developed, aiming to alleviate traffic delays, severe corrosion, compromised safety, and environmental pollution. However, the economic performance of CDC-SP has not been quantified to guide decision-making. To this end, this paper presents a Life-Cycle Cost-Benefit Analysis (LCCBA) to assess the economic feasibility of the CDC-SP de-icing system for road bridges in five representative urban and rural areas across cool humid and cold humid climate zones. Given the variations and uncertainties of several factors that determine the costs and benefits, a sensitivity analysis was conducted to determine the system’s economic reliability. Additionally, a Monte Carlo simulation (MCS) was performed to quantify the impacts of important factors and identify the most beneficial scenarios. Furthermore, the CDC-SP de-icing systems have demonstrated substantial economic benefits and short payback periods, showing great applicability for rural and urban road bridges with different service levels across multiple climate zones as compared to conventional de-icing methods.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Neural Active Manifolds: Nonlinear Dimensionality Reduction for Uncertainty Quantification

We present a new approach for nonlinear dimensionality reduction, specifically designed for computationally expensive mathematical models. We leverage autoencoders to discover a one-dimensional neural active manifold (NeurAM) capturing the model output variability, through the aid of a simultaneously learnt surrogate model with inputs on this manifold. Our method only relies on model evaluations and does not require the knowledge of gradients. The proposed dimensionality reduction framework can then be applied to assist outer loop many-query tasks in scientific computing, like sensitivity analysis and multifidelity uncertainty propagation. In particular, we prove, both theoretically under idealized conditions, and numerically in challenging test cases, how NeurAM can be used to obtain multifidelity sampling estimators with reduced variance by sampling the models on the discovered low-dimensional and shared manifold among models. Several numerical examples illustrate the main features of the proposed dimensionality reduction strategy and highlight its advantages with respect to existing approaches in the literature.

Autoencoders↗
DOE OSTI2020

Sensitivity Study for Forecasting Variables of WRF-Solar Using a Tangent Linear Approach

Integrating solar generation in recent years has highlighted the need for improved accuracy in predicting solar power. Confidence in solar power forecasting can be achieved by designing an ensemble that provides reliable probabilistic information for solar radiation with reduced uncertainty and error. Ideally, ensemble members are created through the optimized perturbation of the initial conditions in numerical weather prediction (NWP) models. Tangent linear models are capable of efficiently investigating the sensitivity of solar radiation to model input parameters because they do not require individual perturbation of each variable. This sensitivity study using tangent linear models provide us the capability to identify the right variables to perturb in an ensemble prediction system. In this study, we developed tangent linear models for WRF-Solar modules that directly impact the computation of solar radiation and the simulation of cloud formation and dissipation including the Fast All-sky Model for Solar Applications (FARMS), the Noah land surface model (LSM), the Thompson microphysics, the Mello-Yamada-Nakanishi-Niino (MYNN) boundary layer parameterization, and the Deng scheme for a shallow-convection parameterization. A sensitivity analysis was conducted under various scenarios based on satellite observations and model simulations from the National Solar Radiation Data Base (NSRDB) and WRF-Solar, respectively. Critical forecasting variables that are highly sensitive to the forecasting of global horizontal irradiance (GHI), direct normal irradiance (DNI), cloud mixing ratio, cloud tendency, cloud fraction, and sensible and latent heat fluxes were determined using the relevant WRF-Solar module. This study will be used as a guidance on future research leading to high-quality probabilistic solar forecasting. In this presentation, we discuss the validation of tangent linear approach for WRF-Solar modules and illustrate how the sensitivity results are valuable in the improvement of probabilistic solar prediction.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

On the importance of phase saturation heterogeneity in the analysis of laboratory studies of hydrate dissociation

Methane hydrates (MHs) have been considered as the future source of energy because of its vast resource volume and high energy density. Energy recovery from MH-bearing sediments has attracted intensifying research activities. Fundamentally, heat transfer, fluid flow through porous media, and the kinetics of hydrate reaction are the three key processes controlling the behavior of MH dissociation and the associated fluid production. Earlier studies have suggested that heterogeneous spatial distribution of SH is inevitable in MH-bearing samples synthesized in laboratory. In this paper, we extend our study to analyze numerically the simulation results from the two realizations of the samples (homogeneous and heterogeneous) to identify differences in the fluid production and to determine if they are sufficiently different. Additionally, we conduct a sensitivity analysis and a statistical analysis on the key transport and kinetic rate parameters that could affect hydrate dissociation and fluid production in the context of a heterogeneous hydrate-bearing sample, in an effort to provide insights that could lead to improved designs for laboratory experiments and (possibly) field applications. Our results suggest that the approximation of an artificial hydrate-bearing core with heterogeneous phase saturations by an assumption of uniform phase saturation distributions results in practically similar fluid production profile except for the very early stage with maximum 20.0% deviation in the water production. From the sensitivity and statistical analysis, we determine that gas production depends strongly on the kinetic rate constant, K d 0 and the composite thermal conductivity of the hydrate-bearing sediments, λ θ ; while, water production is very sensitive to K d 0 and the absolute permeability of the sandy medium, k. Understanding the effect of phase heterogeneity and the relative importance of key parameters on the production behavior of hydrate-bearing sediments could provide basis for novel production technologies that lead to enhanced gas production and energy efficiency in the energy recovery process.

42 ENGINEERING↗
DOE OSTI2022

The influence of random packed column parameters on the liquid holdup and interfacial area

Abstract Carbon dioxide capture via solvent absorption in packed columns has emerged as a potential technology to mitigate coal‐fired power plant CO 2 emissions. Parameters, including packing types, solvent properties, and operating conditions, could potentially affect the packed column CO 2 capture efficiency. To understand the importance of those parameters and help packed column optimization, a design of experiments (DoEs) method was proposed to generate input parameter matrix. Combined with multiphase computational fluid dynamics (CFD), the random packed column parameter influence on the liquid holdup and interfacial area can be efficiently investigated. Surrogate‐based sensitivity analysis shows that the solvent flow rate and contact angle are key factors dictating liquid holdup and interfacial area. On the other hand, solvent viscosity has a marginal impact on the interfacial area. The sensitivity scores were calculated for each input parameter to guide the selection of dimensionless numbers for the liquid holdup and interfacial area correlation development.

42 ENGINEERING↗
DOE OSTI2020

Effect of Nuclear Data Covariances on Integral Experiment Design with Sensitivity and Uncertainty Analysis

Washington River Protection Solutions (WRPS) uses MCNP6.2 and the Whisper code for criticality safety analyses of the Hanford Tank Farm. Together the codes derive baseline upper subcritical limits (USLs) for the waste models using experimental benchmarks. Whisper returns higher USLs, i.e. , has less of a conservative penalty, when the neutronic similarity of the experimental benchmarks to the application is high. Unfortunately, few critical benchmarks have high similarity to the Hanford tanks. The waste in the tanks is highly dilute in plutonium and contains large masses of weakly neutron-absorbing elements like iron and manganese. Experimental benchmarks typically have low sensitivity to these absorbers because they are present as structural materials. Lacking similar benchmarks, new Thermal Epithermal eXperiment (TEX) configurations with high Pu content and interstitial iron absorbers have been designed for the criticality safety validation. The features of the design have been iterated upon to maximize the similarity between the experiment and different Hanford waste models. The similarity is quantified with sensitivity analysis and uncertainty quantification using the representativity coefficient, or c k . The representativity calculation requires nuclear data covariances, which may differ between nuclear data libraries and between library versions. Because of these variations, the optimal design may depend on the nuclear data covariances library. A scenario can be envisioned where an experiment is designed, and c k is maximized, with one set of covariance data. However, when the covariance data is changed, say from ENDF/B-VII.1 to ENDF/B-VIII.0, and the benchmark is used in a criticality safety evaluation, the experiment becomes suboptimal with respect to c k . In this paper, we present how the optimal design of the new TEX experiments varied depending on the nuclear data covariances used to calculate c k . We compare ENDF/B-VII.1 and ENDF/B-VIII.0, as if the library had been updated since the design of the experiment. Additionally, we use JEFF3.3 to simulate if the covariance data of a different library had been used. The results show that the covariances do have an important effect on the designs, less so for thermal systems (where the data are more consistent between evaluations) and more so for epithermal systems where more differences exist.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

CO2 Push-Pull Dual (Conjugate) Faults Injection Simulations

This submission contains datasets and a final manuscript associated with a project simulating carbon dioxide push-pull into a conjugate fault system modeled after Dixie Valley- sensitivity analysis of significant parameters and uncertainty prediction by data-worth analysis. Datasets include: (1) Forward simulation runs of standard cases (push & pull phases), (2) Local sensitivity analyses (push & pull phases), and (3) Data-worth analysis (push & pull phases).

15 GEOTHERMAL ENERGY↗
DOE OSTI2013

Integrated system modeling analysis of a cryogenic multi-cell deflecting-mode cavity resonator

A deflecting mode cavity is the integral element for six-dimensional phase-space beam control in bunch compressors and emittance transformers at high energy beam test facilities. RF performance of a high-Q device is, however, highly sensitive to operational conditions, in particular in a cryo-cooling environment. Using analytic calculations and RF simulations, we examined cavity parameters and deflecting characteristics of TM{sub 110,π} mode of a 5 cell resonator in a liquid nitrogen cryostat, which has long been used at the Fermilab A0 Photoinjector (A0PI). The sensitivity analysis indicated that the cavity could lose 30%–40% of deflecting force due to defective input power coupling accompanying non-uniform field distribution across the cells with 40 ∼ 50 MeV electron beam and 70–80 kW klystron power. Vacuum-cryomodules of the 5 cell cavity are planned to be installed at the Fermilab Advanced Superconducting Test Accelerator facility. Comprehensive modeling analysis integrated with multi-physics simulation tools showed that RF loading of 1 ms can cause a ∼5 K maximum temperature increase, corresponding to a ∼4.3 μm/ms deformation and a 1.32 MHz/K maximum frequency shift. The integrated system modeling analysis will improve design process of a high-Q cavity with more accurate prediction of cryogenic RF performance under a high power pulse operation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

RISMC Analysis Framework in Response to Proposed 10 CFR 50.46c Rulemaking

The results obtained from the demonstration calculations indicate that as an automation tool in LOCA analyses, LOTUS has the capability to provide integrated evaluation through seamless interfaces of the data stream in multiple disciplines. With further more development, LOTUS will provide a systematic way to perform uncertainty quantification, sensitivity analysis and risk assessment of the multiple physics involved in the LOCA analysis in response to the proposed 10 CFR 50.46c rulemaking. It can be used to obtain quantitative estimate of design or operational margin loss or gain as well as to assess the impact on LOCA analysis safety metrics associated with various combinations of changes in LOCA analysis inputs. It can also aid plant owners to make decision on evaluating design changes as well as resolving operational issues. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Bistability analysis in mathematical model of M-phase control in Xenopus oocyte extracts

To gain more insight into the molecular mechanism that regulates eukaryotic cell cycle, we propose a modification to an existing Mathematical model of mitosis-promoting factor control in Xenopus oocyte extract. To achieve this, we redirect how cell exits from mitosis using ubiquitin ligase enzyme APCP:Cdc20 which is acting as a modifier in cyclin degradation. We present a modified wiring map using combination of mass action kinetics and Michaelis–Menten kinetics to represent the biochemical processes. This results in a system of non-linear ordinary differential equations. The equilibria of the system were analyzed analytically. Using MPF as a bifurcation parameter, we analytically derived conditions under which bistability can occur in the MPF activation module. We find that for bistability to occur, it is necessary that the rate of phosphorylation of Wee1 must be greater than the rate of its dephosphorylation and that the concentration of MPF must lie in certain range of parameter values. Numerical simulations conducted show that the time taken to exit the cell cycle is shorter than those published in some reports and the sensitivity analysis results suggest that the rate of synthesis of cyclin is the most sensitive parameter in the dynamics of cell cycle. Through numerical experiments, we found new parameter sets that will give rise to bistability in the MPF activation module.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Lyapunov spectrum of the separated flow around the NACA 0012 airfoil and its dependence on numerical discretization

We investigate the impact of numerical discretization on the Lyapunov spectrum of separated flow simulations. The two-dimensional chaotic flow around the NACA 0012 airfoil at a low Reynolds number and large angle of attack is considered to that end. Time, space and accuracy-order refinement studies are performed to examine each of these effects separately. Numerical results show that the time discretization has a small impact on the dynamics of the system, whereas the spatial discretization can dramatically change them. Also, the finite-time Lyapunov exponents associated to unstable modes are shown to be positively skewed, and quasi-homoclinic tangencies are observed in the attractor of the system. The implications of these results on flow physics and sensitivity analysis of chaotic flows are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Modeling Effects of Annealing on Coal Char Reactivity to O 2 and CO 2 , Based on Preparation Conditions

Oxy-fired coal combustion is a promising potential carbon capture technology. Predictive computational fluid dynamics (CFD) simulations are valuable tools in evaluating and deploying oxyfuel and other carbon capture technologies, either as retrofit technologies or for new construction. However, accurate predictive combustor simulations require physically realistic submodels with low computational requirements. A recent sensitivity analysis of a detailed char conversion model (Char Conversion Kinetics (CCK)) found thermal annealing to be an extremely sensitive submodel. In the present work, further analysis of the previous annealing model revealed significant disagreement with numerous datasets from experiments performed after that annealing model was developed. The annealing model was accordingly extended to reflect experimentally observed reactivity loss, because of the thermal annealing of a variety of coals under diverse char preparation conditions. The model extension was informed by a Bayesian calibration analysis. In addition, since oxyfuel conditions include extraordinarily high levels of CO 2 , the development of a first-ever CO 2 reactivity loss model due to annealing is presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions

Abstract Wetlands are the largest natural source of methane (CH 4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH 4 , but interpreting its spatiotemporal variations is challenging due to the co‐occurrence of CH 4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data‐model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data‐constrained model—iPEACE—reasonably reproduced CH 4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH 4 production appeared to be the most important process, followed by oxidation in explaining inter‐site variations in CH 4 emissions. Based on a sensitivity analysis, CH 4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant‐mediated transport appeared to be the major pathway for CH 4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH 4 production and CH 4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH 4 production, plant‐mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH 4 emissions across biomes. These processes and associated parameters for CH 4 emissions among and within the wetlands provide useful insights for interpreting observed net CH 4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH 4 fluxes.

Ueyama, Masahito↗