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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.

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At least 19 records

Remote sensing requirements as suggested by watershed model sensitivity analyses

A continuous simulation watershed model has been used to perform sensitivity analyses that provide guidance in defining remote sensing requirements for the monitoring of watershed features and processes. The results show that out of 26 input parameters having meaningful effects on simulated runoff, 6 appear to be obtainable with existing remote sensing techniques. Of these six parameters, 3 require the measurement of the areal extent of surface features (impervious areas, water bodies, and the extent of forested area), two require the descrimination of land use that can be related to overland flow roughness coefficient or the density of vegetation so as to estimate the magnitude of precipitation interception, and one parameter requires the measurement of distance to get the length over which overland flow typically occurs. Observational goals are also suggested for monitoring such fundamental watershed processes as precipitation, soil moisture, and evapotranspiration. A case study on the Patuxent River in Maryland shows that runoff simulation is improved if recent satellite land use observations are used as model inputs as opposed to less timely topographic map information.

Salomonson, V. V.↗

Uncertainty and Sensitivity Analyses of Duct Propagation Models

This paper presents results of uncertainty and sensitivity analyses conducted to assess the relative merits of three duct propagation codes. Results from this study are intended to support identification of a "working envelope" within which to use the various approaches underlying these propagation codes. This investigation considers a segmented liner configuration that models the NASA Langley Grazing Incidence Tube, for which a large set of measured data was available. For the uncertainty analysis, the selected input parameters (source sound pressure level, average Mach number, liner impedance, exit impedance, static pressure and static temperature) are randomly varied over a range of values. Uncertainty limits (95% confidence levels) are computed for the predicted values from each code, and are compared with the corresponding 95% confidence intervals in the measured data. Generally, the mean values of the predicted attenuation are observed to track the mean values of the measured attenuation quite well and predicted confidence intervals tend to be larger in the presence of mean flow. A two-level, six factor sensitivity study is also conducted in which the six inputs are varied one at a time to assess their effect on the predicted attenuation. As expected, the results demonstrate the liner resistance and reactance to be the most important input parameters. They also indicate the exit impedance is a significant contributor to uncertainty in the predicted attenuation.

Nark, Douglas M.↗

Design concepts/parameters assessment and sensitivity analyses of select composite structural components

Formal approaches are summarized to evaluate design concepts and perform sensitivity analyses on design parameters of composite structural components for vehicles. The formal approaches include structural analyses coupled with composite micromechanics to assess the structural response of beams made from various intraply hybrids, finite element analysis in conjunction with composite mechanics to assess the structural response of panels made from strip hybrids, and sensitivity analysis through optimization to assess the effects of various design parameters on the optimum design of a panel made from angleplied composite laminates. Results obtained from these approaches are presented in graphical and tabular form to illustrate parametric studies and acceptable ranges of various design parameters.

Chamis, C. C.↗

Global Sensitivity Analyses for Test Planning with Black-Box Models for Mars Sample Return

This work describes sensitivity analyses performed on complex black-box models used to support experimental test planning under limited resources in the context of the Mars Sample Return program, which aims at bringing to Earth rock and atmospheric samples from Mars. We develop a systematic workflow that allows the analysts to simultaneously obtain quantitative insights on key drivers of uncertainty, on the direction of impact, and the presence of interactions. We apply novel optimal transport-based global sensitivity measures to tackle the multivariate nature of the output. On the modeling side, we apply multi-fidelity techniques that leverage low-fidelity models to speed up the calculations and make up for the limited amount of high-fidelity samples, while keeping these in the loop for accuracy guarantees. The sensitivity analysis reveals insights useful for the analysts to understand the model's behavior and identify the factors to focus on during testing in order to maximize the value of information extracted from them to ensure mission success when limited resources are available.

Giuseppe Cataldo↗

Coupled neutronics, thermochemistry, corrosion modeling and sensitivity analyses for isotopic evolution in molten salt reactors

This study presents a computational methodology for analyzing isotopic evolution and associated uncertainties in molten salt reactors (MSRs), focusing on both fluoride- and chloride-based fuel salts. The primary goal is to enhance the understanding of isotopic behavior in MSRs and provide data to support future experimental efforts. The methodology integrates transport-coupled depletion calculations using OpenMC, equilibrium thermodynamics modeling with Thermochimica, and a corrosion model. Sensitivity analyses are performed to evaluate the impact of power density, air ingress, and humidity content on isotopic evolution in MSR concepts. This study examines representative F- and Cl-based MSR designs, highlighting the dominant influence of power density on isotopic composition, which significantly affects isotope production and depletion rates, accounting for approximately 76% of the observed variance in element concentration. Air ingress and humidity content also affect the redox potential, solubility of heavier elements, and corrosion rates, thereby altering the expected isotopic evolution in the reactor. On average, air ingress accounts for around 17% of the variance in element concentrations, while humidity explains the remaining 7%. These variances differ significantly from element to element, depending on the element’s role in depletion, redox potential evolution, and galvanic corrosion. The findings indicate that power density, air ingress, and humidity content are all critical factors for optimizing reactor design and operational strategies. Furthermore, the study provides expected ranges for key impurities in the fuel salt, which are crucial for guiding future experimental studies and refining MSR designs. Finally, this study demonstrates the importance of modeling depletion coupled with the evolution of redox potential and chemical interactions in MSR fuel salts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Application of machine learning approaches in the analysis of mass absorption cross-section of black carbon aerosols: Aerosol composition dependencies and sensitivity analyses

Physics-based models typically require an in-depth understanding of a phenomenon and assumptions of the underlying process(es), which are often hard to obtain in practice, whereas data-driven machine learning models learn the structure and patterns in the training data without any prior theoretical assumptions and then use inference to develop useful predictions. A novel machine learning-based algorithm has been previously developed for the prediction of black carbon mass absorption cross-section (MAC BC ) and applied to a variety of different atmospheric environments. In contrast to light scattering theories which require assumptions about the underlying physics, this algorithm uses time-series data of aerosol properties to estimate the temporally-varying MAC BC at 870 nm. Here, we analyze our algorithm and discuss the influence of aerosol optical properties (such as Ångström exponents and single scattering albedo) and chemical composition on the model outputs and the associated accuracy. Additionally, we conduct sensitivity analyses on our models to understand how the predictions change in response to different sets of input variables. Our support vector machine (SVM) for regression model is the least sensitive to variations in the input variables, although all models tend to exhibit a degradation to their accuracy when scattering Ångström exponents are less than one.

54 ENVIRONMENTAL SCIENCES↗

Chemical kinetic interactions and sensitivity analyses for 2-ethylhexyl nitrate-doped PRF91 using a reduced mechanism

A numerical and experimental investigation about the chemical kinetic interactions between 2-ethylhexylnitrate (EHN) and PRF91 was performed in this study. Rapid compression machine experiments were conducted to investigate the effect of EHN on the autoignition reactivity of the fuel, and a reduced chemical kinetic mechanism was developed including an EHN sub-model. Experiments showed that the ignition delay decreases as the fuel is doped with EHN, but the effect of the doping level of EHN on the ignition is highly non-linear. Moreover, experiments showed that the EHN effectiveness is lowest during the transition between the low-temperature regime and the negative temperature coefficient (NTC) regime, and it rapidly increases as the temperature increases. Both detailed and (developed) reduced mechanisms were validated against the experimental results, allowing a more in-depth EHN-fuel chemistry study. Additionally, ignition delay sensitivity and EHN effectiveness sensitivity analyses were performed with the reduced mechanism to identify the reactions that control the interaction between EHN and the fuel. As the result, EHN thermal decomposition is only relevant for very low temperatures. The chemistry of EHN-doped fuel is more sensitive to intermediate temperature reactions than that of straight fuel, especially at lower temperatures, due to the effect of EHN on the NTC behavior of the fuel. Finally, the chemistry of EHN-doped fuel is very sensitive to NO 2 -to-NO reactions, especially at high temperatures, because these reactions transform the NO 2 generated by EHN into NO, which is a very effective fuel reactivity enhancer.

2-ethylhexyl nitrate↗

Prediction of the thermal-hydraulic-mechanical response of a geological repository at large scale and sensitivity analyses

To better understand the Thermal-Hydraulic-Mechanical (THM) response of the rock caused by the high-level radioactive waste (HLW) released heat in the Callovo-Oxfordian formation (COx) in the near-field and far-field areas, a series of coupled THM modelling is performed. This study presents a case study based on the French geological repository for HLW (Cigéo project) to better assess modelling of deep geological repositories (DGR) within the DECOVALEX-2019 framework. In this study, the proposed coupled THM model, implemented in the platform of COMSOL, is validated by comparing the modelled THM results for a point heat source in an infinite rock mass with an analytical solution. It is also validated by comparing its thermal component for the Base Case with accurate results calculated using another numerical method. To shorten the calculation time, the DGR is modelled using six cuboid blocks representing 162 HLW cells and only six central HLW cells of interest modelled in detail. This simplification is validated. This model can easily be used to model not only the near-field THM response of the rock but also the far-field THM response. The influence of the boundary conditions applied on the gallery wall, HLW cell walls, and external surfaces of the model and the influence of different vertical dimensions of the geometry are studied. The sensitivity analyses of the THM parameters of COx on the THM response at different locations are performed. Finally, the influence of using a 2-dimensional (2D) model to represent a 3-dimensional (3D) repository is also investigated.

58 GEOSCIENCES↗

On the characterization of biases arising from methods and approximations used for sensitivity analyses

The preliminary assessment of the performance and safety of advanced reactors, as well as the identification of research and development needs, rely on computer simulations due to the lack of operational experience. Those simulations should be based on verified and validated computational tools, calculation schemes, and nuclear data libraries, and should be accompanied of a proper characterization of the involved uncertainties, providing confidence in the computational-based predictions. Thus, sensitivity and uncertainty studies, together with integral experiments, play an essential role in that process. Sensitivities are then a critical element and guidelines about how to produce accurate enough sensitivities depending on the subsequent analyses to be performed are of interest. The present study addresses the sensitivities biases arising from the use of different nuclear data libraries, computational methods and the assumption of modelling simplifications. Not only sensitivities for multiplication factor but also for safety-relevant reactivity responses have been analyzed. In the study, propagated uncertainties are also included for the considered parameters to illustrate the impact of the sensitivity profiles obtained for each case on the final uncertainty. Then, relevant recommendations are given for sensitivity analyses of highly complex systems. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Phase 1 Specifications and preliminary sensitivity analyses of the OECD-NRC liquid metal fast reactor core thermal-hydraulics benchmark

The developments in wire-wrapped fuel bundle thermal-hydraulics research have become increasingly diverse and this makes comparisons across studies difficult. This paper describes an ongoing benchmark that will address this issue by directly comparing computational results with experimental data from two unique wire-wrapped thermal-hydraulic facilities. Preliminary subchannel sensitivity / uncertainty analyses show largely expected behavior for the presented cases, where rod diameter and friction factor show the greatest sensitivities to geometrical perturbations. Guidelines for computational fluid dynamics evaluations have been prepared and highlight the need for consolidated modeling strategies. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Grid and aerodynamic sensitivity analyses of airplane components

An algorithm is developed to obtain the grid sensitivity with respect to design parameters for aerodynamic optimization. The procedure is advocating a novel (geometrical) parameterization using spline functions such as NURBS (Non-Uniform Rational B-Splines) for defining the wing-section geometry. An interactive algebraic grid generation technique, known as Two-Boundary Grid Generation (TBGG) is employed to generate C-type grids around wing-sections. The grid sensitivity of the domain with respect to geometric design parameters has been obtained by direct differentiation of the grid equations. A hybrid approach is proposed for more geometrically complex configurations such as a wing or fuselage. The aerodynamic sensitivity coefficients are obtained by direct differentiation of the compressible two-dimensional thin-layer Navier-Stokes equations. An optimization package has been introduced into the algorithm in order to optimize the wing-section surface. Results demonstrate a substantially improved design due to maximized lift/drag ratio of the wing-section.

Sadrehaghighi, Ideen↗

Grid and design variables sensitivity analyses for NACA four-digit wing-sections

Two distinct parameterization procedures are developed for investigating the grid sensitivity with respect to design parameters of a wing-section example. The first procedure is based on traditional (physical) relations defining NACA four-digit wing-sections. The second is advocating a novel (geometrical) parameterization using spline functions such as NURBS (Non-Uniform Rational B-Splines) for defining the wing-section geometry. An interactive algebraic grid generation technique, known as Hermite Cubic Interpolation, is employed to generate C-type grids around wing-sections. The grid sensitivity of the domain with respect to design and grid parameters has been obtained by direct differentiation of the grid equations. A hybrid approach is proposed for more geometrically complex configurations. A comparison of the sensitivity coefficients with those obtained using a finite-difference approach has been made to verify the feasibility of the approach. The aerodynamic sensitivity coefficients are obtained using the compressible two-dimensional thin-layer Navier-Stokes equations.

Sadrehaghighi, Ideen↗

Probabilistic Sensitivity Analyses Incorporating Surrogate Models for the Structural Response of a Representative Inflatable Space Structure

This study concentrates on results from probabilistic analysis and numerical simulation tools to identify parameter sensitivities and assess surrogate model suitability for a novel inflatable airlock concept, specifically the Non-Axisymmetric Inflatable Pressure Structure (NAIPS) under NASA's Minimalistic Advanced Softgoods Hatch (MASH) Program. The current studies extended the demonstration of probabilistic analysis tools to identify parameter sensitivities by: incorporating nonlinear material load-strain property curves and orthotropic representation of the fabric; and exploring the use of surrogate models to facilitate rapid evaluations as new information becomes available, as well as enable optimizations. The airlock model has been simplified to focus on the end dome section. Brief overviews of the finite element model and associated surrogate models are provided along with the probabilistic sensitivity analysis approaches. Responses of interest include the sensitivities of various loads in the structural elements of the NAIPS to material properties, cord lengths, inflation pressure and friction between softgoods components. The use of surrogate models was explored to facilitate rapid sensitivity evaluations as parameter ranges change. The completion of the sensitivity studies improved understanding of the dependence of load responses to several uncertain parameters and confidence in the ability to use surrogate models to represent the finite element simulations.

Lyle, Karen H.↗

Sensitivity Analyses for Monte Carlo Sampling-Based Particle Simulations

Computational design-based optimization is a well-used tool in science and engineering. Our report documents the successful use of a particle sensitivity analysis for design-based optimization within Monte Carlo sampling-based particle simulation—a currently unavailable capability. Such a capability enables the particle simulation communities to go beyond forward simulation and promises to reduce the burden on overworked analysts by getting more done with less computation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Validation and Sensitivity Analyses of Arc-Jet Performance of Woven Thermal Protection Entry Systems

A material response model is developed for the determination of erosion rates and thermal response of woven materials to enable accurate thermal protection material sizing and future missions to Venus and giant planets. The stagnation-point thermal response is further evaluated using a Monte Carlo global sensitivity analysis to determine the interactions between key parameters in the material surface energy balance, such as, convective blowing correction parameter and weave material properties including isotropic and orthotropic thermal conductivites. The time-accurate material response for the dual layer weave erosion and surface temperatures show excellent agreement with stagnation flat face arc-jet tests involving time-varying aeroheating-cooling cycles. The high-fidelity Monte Carlo sensitivity analysis technique was used to address challenges in thermal protection sizing for the Adaptive Deployable Entry and Placement Technology (ADEPT) system, a low ballistic coefficient hypersonic decelerator. The results represent new correlations for such weaves involving Carbon-air oxidation equilibrium chemistry. Through the multi-variate regression analyses and uncertainty rankings performed, only three properties were found to contribute to the transient thermal response of the gore, with emissivity contributing to nearly 95% of the total output uncertainty.

Pratibha Raghunandan↗

Validation and Sensitivity Analyses of Arc-Jet Performance of Woven Thermal Protection Entry Systems

A material response model is developed for the determination of erosion rates and thermal response of woven materials to enable accurate thermal protection material sizing and future missions to Venus and giant planets. The stagnation-point thermal response is further evaluated using a Monte Carlo global sensitivity analysis to determine the interactions between key parameters in the material surface energy balance, such as, convective blowing correction parameter and weave material properties including isotropic and orthotropic thermal conductivites. The time-accurate material response for the dual layer weave erosion and surface temperatures show excellent agreement with stagnation flat face arc-jet tests involving time-varying aeroheating-cooling cycles. The high-fidelity Monte Carlo sensitivity analysis technique was used to address challenges in thermal protection sizing for the Adaptive Deployable Entry and Placement Technology (ADEPT) system, a low ballistic coefficient hypersonic decelerator. The results represent new correlations for such weaves involving Carbon-air oxidation equilibrium chemistry. Through the multi-variate regression analyses and uncertainty rankings performed, only three properties were found to contribute to the transient thermal response of the gore, with emissivity contributing to nearly 95% of the total output uncertainty.

Pratibha Raghunandan↗

Demonstration of Probabilistic Sensitivity Analyses Tools on the Structural Response of a Representative Inflatable Space Structure

This work provides an initial step toward demonstrating a probabilistic numerical simulation capability to support trade studies and the development of a certification plan for inflatable space habitats. This study concentrates on interpreting the results from probabilistic analysis and numerical simulation tools to identify parameter sensitivities for a novel inflatable airlock concept, specifically the Non‐Axisymmetric Inflatable Pressure Structure (NAIPS) that was designed and tested under NASA's Minimalistic Advanced Softgoods Hatch (MASH) Program. A brief overview of the finite element model is provided along with the probabilistic sensitivity analysis approach. The sensitivity studies required a model that was numerically stable and efficient enough that hundreds of simulations could be completed in the allotted time. Therefore, the existing full model was simplified by: extracting a quarter symmetry section of the dome; focusing on a single inflation pressure; and replacing the non‐linear material stress‐strain curves with linear, isotropic materials defined by elastic moduli. Responses of interest include the sensitivity of various structural component loads to material properties, cord lengths, inflation pressure and friction. Multiple sensitivity studies were completed and three are reported here. The first study focused on utilizing wide input parameter ranges to provide an opportunity to assess numerical robustness. The next two studies narrowed the parameter ranges to enable focus on understanding uncertainty at a fixed operating condition. The completion of the sensitivity studies improved understanding of the interdependence of multiple inputs on the responses. In addition, numerical stability of the simulations over wide parameter ranges, shows the feasibility of incorporating uncertainty‐based methods in the design and certification of inflatable space habitats. With the experience and trust gained, it is anticipated that these same methods will be applied to nonlinear, orthotropic models in the future.

Lyle, Karen H.↗