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

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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Sensitivity Analysis of the Bone Fracture Risk Model

Introduction: The probability of bone fracture during and after spaceflight is quantified to aid in mission planning, to determine required astronaut fitness standards and training requirements and to inform countermeasure research and design. Probability is quantified with a probabilistic modeling approach where distributions of model parameter values, instead of single deterministic values, capture the parameter variability within the astronaut population and fracture predictions are probability distributions with a mean value and an associated uncertainty. Because of this uncertainty, the model in its current state cannot discern an effect of countermeasures on fracture probability, for example between use and non-use of bisphosphonates or between spaceflight exercise performed with the Advanced Resistive Exercise Device (ARED) or on devices prior to installation of ARED on the International Space Station. This is thought to be due to the inability to measure key contributors to bone strength, for example, geometry and volumetric distributions of bone mass, with areal bone mineral density (BMD) measurement techniques. To further the applicability of model, we performed a parameter sensitivity study aimed at identifying those parameter uncertainties that most effect the model forecasts in order to determine what areas of the model needed enhancements for reducing uncertainty. Methods: The bone fracture risk model (BFxRM), originally published in (Nelson et al) is a probabilistic model that can assess the risk of astronaut bone fracture. This is accomplished by utilizing biomechanical models to assess the applied loads; utilizing models of spaceflight BMD loss in at-risk skeletal locations; quantifying bone strength through a relationship between areal BMD and bone failure load; and relating fracture risk index (FRI), the ratio of applied load to bone strength, to fracture probability. There are many factors associated with these calculations including environmental factors, factors associated with the fall event, mass and anthropometric values of the astronaut, BMD characteristics, characteristics of the relationship between BMD and bone strength and bone fracture characteristics. The uncertainty in these factors is captured through the use of parameter distributions and the fracture predictions are probability distributions with a mean value and an associated uncertainty. To determine parameter sensitivity, a correlation coefficient is found between the sample set of each model parameter and the calculated fracture probabilities. Each parameters contribution to the variance is found by squaring the correlation coefficients, dividing by the sum of the squared correlation coefficients, and multiplying by 100. Results: Sensitivity analyses of BFxRM simulations of preflight, 0 days post-flight and 365 days post-flight falls onto the hip revealed a subset of the twelve factors within the model which cause the most variation in the fracture predictions. These factors include the spring constant used in the hip biomechanical model, the midpoint FRI parameter within the equation used to convert FRI to fracture probability and preflight BMD values. Future work: Plans are underway to update the BFxRM by incorporating bone strength information from finite element models (FEM) into the bone strength portion of the BFxRM. Also, FEM bone strength information along with fracture outcome data will be incorporated into the FRI to fracture probability.

mathematical models↗
DOE OSTI2021

Flow boiling transient critical heat flux tests with stainless steel and FeCrAl: Transient correlation implementation, model calibration, and sensitivity analysis

In this study, steady-state and transient internal-flow critical heat flux (CHF) experiments were carried out under two flow conditions, at atmospheric pressure, on 316 stainless steel (316-SS) and iron-chromium-aluminum (FeCrAl) tubes. Slow power transients at a low mass flow (300 kg/m 2 - s) with very low subcooling (X e =-0.0054) generated premature CHFs, which were prevented by faster power transients and high mass flow (1000 kg/m 2 - s). The measured transient CHFs increased linearly with increasing power transients, compared with the steady-state CHF. Yet, the wall superheat at the CHFs decreased with faster power transients. Transient CHF correlations highlighting heterogeneous spontaneous nucleation were calibrated to the measured CHFs and compared with other existing correlations. Transient CHF multipliers were acquired from pool and flow boiling empirical CHF correlations that were generated. The multipliers were applied to the RELAP5-3D nuclear system code to analyze the discrepancies between the measured data and the predicted CHF and post-CHF behavior, which improved peak cladding temperature predictions by 24.6%. A variance-based global sensitivity study perturbing the experimental uncertainties and cladding material thermal properties showed the diminishing influence of flow boiling heat transfer with increasing power transients, highlighting the significance of the volumetric heat capacity for the cladding integrity during transients. Transient CHF correlations were applied to the most limiting design basis accident: a hot-zero-power reactivity-initiated accident on a generic pressurized water reactor RELAP5-3D model.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tropical dry forest response to nutrient fertilization: a model validation and sensitivity analysis

Abstract. Soil nutrients, especially nitrogen (N) and phosphorus (P), regulate plant growth and hence influence carbon fluxes between the land surface and atmosphere. However, how forests adjust biomass partitioning to leaves, wood, and fine roots in response to N and/or P fertilization remains puzzling. Recent work in tropical forests suggests that trees increase fine root production under P fertilization, but it is unclear whether mechanistic models can reproduce this dynamic. In order to better understand mechanisms governing nutrient effects on plant allocation and improve models, we used the nutrient-enabled ED2 model to simulate a fertilization experiment being conducted in a secondary tropical dry forest in Costa Rica. We evaluated how different allocation parameterizations affected model performance. These parameterizations prescribed a linear relationship between relative allocation to fine roots and soil P concentrations. The slope of the linear relationship was allowed to be positive, negative, or zero. Some parameterizations realistically simulated leaf, wood, and fine root production, and these parameterizations all assumed a positive relationship between relative allocation to fine roots and soil P concentration. Model simulations of a 30-year timeframe indicated strong sensitivity to parameterization and fertilization treatment. Without P fertilization, the simulated aboveground biomass (AGB) accumulation was insensitive to the parameterization. With P fertilization, the model was highly sensitive to the parameterization and the greatest AGB accumulation occurred when relative allocation to fine roots was independent of soil P. Our study demonstrates the need for simultaneous measurements of leaf, wood, and fine root production in nutrient fertilization experiments and for longer-term experiments. Models that do not accurately represent allocation to fine roots may be highly biased in their simulations of AGB, especially on multi-decadal timescales.

Environmental Sciences & Ecology↗
NASA NTRS1994

Sensitivity Analysis of Flutter Response of a Wing Incorporating Finite-Span Corrections

Flutter analysis of a wing is performed in compressible flow using state-space representation of the unsteady aerodynamic behavior. Three different expressions are used to incorporate corrections due to the finite-span effects of the wing in estimating the lift-curve slope. The structural formulation is based on a Rayleigh-Pitz technique with Chebyshev polynomials used for the wing deflections. The aeroelastic equations are solved as an eigen-value problem to determine the flutter speed of the wing. The flutter speeds are found to be higher in these cases, when compared to that obtained without accounting for the finite-span effects. The derivatives of the flutter speed with respect to the shape parameters, namely: aspect ratio, area, taper ratio and sweep angle, are calculated analytically. The shape sensitivity derivatives give a linear approximation to the flutter speed curves over a range of values of the shape parameter which is perturbed. Flutter and sensitivity calculations are performed on a wing using a lifting-surface unsteady aerodynamic theory using modules from a system of programs called FAST.

Issac, Jason Cherian↗
NASA NTRS2009

Sensitivity Analysis of Linear Programming and Quadratic Programming Algorithms for Control Allocation

The Next Generation (NextGen) transport aircraft configurations being investigated as part of the NASA Aeronautics Subsonic Fixed Wing Project have more control surfaces, or control effectors, than existing transport aircraft configurations. Conventional flight control is achieved through two symmetric elevators, two antisymmetric ailerons, and a rudder. The five effectors, reduced to three command variables, produce moments along the three main axes of the aircraft and enable the pilot to control the attitude and flight path of the aircraft. The NextGen aircraft will have additional redundant control effectors to control the three moments, creating a situation where the aircraft is over-actuated and where a simple relationship does not exist anymore between the required effector deflections and the desired moments. NextGen flight controllers will incorporate control allocation algorithms to determine the optimal effector commands and attain the desired moments, taking into account the effector limits. Approaches to solving the problem using linear programming and quadratic programming algorithms have been proposed and tested. It is of great interest to understand their relative advantages and disadvantages and how design parameters may affect their properties. In this paper, we investigate the sensitivity of the effector commands with respect to the desired moments and show on some examples that the solutions provided using the l2 norm of quadratic programming are less sensitive than those using the l1 norm of linear programming.

Frost, Susan A.↗
DOE OSTI2016

Sensitivity analysis of high resolution gamma-ray detection for safeguards monitoring at natural uranium conversion facilities

Under the policies proposed by recent International Atomic Energy Agency (IAEA) circulars and policy papers, implementation of safeguards exists when any purified aqueous uranium solution or uranium oxides suitable for isotopic enrichment or fuel fabrication exists. Under IAEA Policy Paper 18, the starting point for nuclear material under safeguards was reinterpreted, suggesting that purified uranium compounds should be subject to safeguards procedures no later than the first point in the conversion process. In response to this technical need, a combination of simulation models and experimental measurements were employed in previous work to develop and validate gamma-ray nondestructive assay monitoring systems in a natural uranium conversion plant (NUCP). In particular, uranyl nitrate (UO 2 (NO 3 ) 2 ) solution exiting solvent extraction was identified as a key measurement point (KMP). Passive nondestructive assay techniques using high resolution gamma-ray spectroscopy were evaluated to determine their viability as a technical means for drawing safeguards conclusions at NUCPs, and if the IAEA detection requirements of 1 significant quantity (SQ) can be met in a timely manner. Building upon the aforementioned previous validation work on detector sensitivity to varying concentrations of uranyl nitrate via a series of dilution measurements, this work investigates detector response parameter sensitivities to gamma-ray signatures of uranyl nitrate. The full energy peak efficiency of a detection system is dependent upon the sample, geometry, absorption, and intrinsic efficiency parameters. Perturbation of these parameters translates into corresponding variations of the 185.7 keV peak area of the 235 U in uranyl nitrate. Such perturbations in the assayed signature impact the quality or versatility of the safeguards conclusions drawn. Given the potentially high throughput of uranyl nitrate in NUCPs, the ability to assay 1 SQ of material requires uncertainty «1%. Accounting for material self-shielding properties, pipe thickness, and source-detector orientation is instrumental in determining the robustness of gamma-ray detection in the process monitoring of uranyl nitrate in NUCPs. Monte Carlo models and ray-tracing models were employed to determine the sensitivity of the detected 185.7 keV photon to self-shielding properties, pipe thickness, and source-detector geometry. Considering the implementation of the detection of 1 SQ, diversion of 1 SQ becomes essentially undetectable given the systematic uncertainty, in addition to considerations such as propagating uncertainties due to pipe offset/position, as well as minor variations in pipe thickness. Consequently, pipe thickness was the most sensitive variable in affecting full energy efficiency of the 185.7 keV signature peak with up to 8% variation in efficiency for ±0.5 mm changes in Schedule 40 304L stainless steel piping. Furthermore, computation of the attenuation correction factor of the uranyl nitrate solution [CF(AT) (i.e. εsample)] using Parker's method using with the approximation for the geometrical factor κ≈π/4 was validated through experimental, Monte Carlo and ray-tracing calculations for a uranyl nitrate filled transfer pipe segment. Furthermore, quantifying sensitivity in detector position, as well as voiding effects due to bubbly flow or laminar flow with an air gap in the uranyl nitrate becomes increasingly important as considerations from (static) design-scale measurements translate into (dynamic) field operations tests.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2015

Can Simulation Credibility Be Improved Using Sensitivity Analysis to Understand Input Data Effects on Model Outcome?

Model and simulation (MS) credibility is defined as, the quality to elicit belief or trust in MS results. NASA-STD-7009 [1] delineates eight components (Verification, Validation, Input Pedigree, Results Uncertainty, Results Robustness, Use History, MS Management, People Qualifications) that address quantifying model credibility, and provides guidance to the model developers, analysts, and end users for assessing the MS credibility. Of the eight characteristics, input pedigree, or the quality of the data used to develop model input parameters, governing functions, or initial conditions, can vary significantly. These data quality differences have varying consequences across the range of MS application. NASA-STD-7009 requires that the lowest input data quality be used to represent the entire set of input data when scoring the input pedigree credibility of the model. This requirement provides a conservative assessment of model inputs, and maximizes the communication of the potential level of risk of using model outputs. Unfortunately, in practice, this may result in overly pessimistic communication of the MS output, undermining the credibility of simulation predictions to decision makers. This presentation proposes an alternative assessment mechanism, utilizing results parameter robustness, also known as model input sensitivity, to improve the credibility scoring process for specific simulations.

Credibility↗
DOE OSTI2020

$\mathrm{UPDATED}$ $\mathrm{U3SI2}$ thermal creep model and sensitivity analysis of the $\mathrm{U3SI2-SIC}$ accident tolerant $\mathrm{FUEL}$

U 3 Si 2 is a candidate accident tolerant fuel (ATF) replacement for UO 2 . U 3 Si 2 ’s high uranium density and high thermal conductivity are favorable properties in steady-state and accident conditions. Low power performance of this U3Si2-SiC concept fuel is compared to that of UO 2 -Zr4 fuels by implementing models that describe the properties of U 3 Si 2 and SiC-SiC into Idaho National Laboratory's (INL) fuel performance code, BISON. Included in these material models is a thermal creep model for U 3 Si 2 based on compressive creep data. The simulated results are in keeping with community knowledge that the U 3 Si 2 -SiC concept fuel may serve as a replacement for UO 2 -Zr4 fuels during steady-state operation, provided the mSiC layer remains under compression. Through a moderate power history and three 24-month fuel cycles, the mSiC layer remains under compressive stress through a burnup of 80 MWd/kgU. During low power operation, failure of the mSiC layer generally occurs prior to significant thermal creep in U 3 Si 2 . Generally, U 3 Si 2 creep is temperature sensitive and of little importance at the temperatures and stresses simulated during steady operation and during fuel-to-cladding contact. A parameter variation study including 11,520 individual simulations with variations in nominal fuel thermal creep rate, cladding thermal conductivity, cladding irradiation creep and swelling, cladding gap size, and cladding thickness demonstrated that research priorities for this ATF should revolve around reducing cladding thickness as a means to minimize cladding failure. Generally, despite advances in SiC-SiC compliance, the brittle nature of mSiC excludes U 3 Si 2 -SiC for use where fuel cladding contact may occur.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence.

Efficiently performing predictive studies of irradiated particle-laden turbulent flows has the potential of providing significant contributions towards better understanding and optimizing, for example, concentrated solar power systems. As there are many uncertainties inherent in such flows, conducting uncertainty quantification analyses is fundamental to improve the predictive capabilities of the numerical simulations. For largescale, multi-physics problems exhibiting high-dimensional uncertainty, characterizing the stochastic solution presents a significant computational challenge as many methods require a large number of high-fidelity, forward model solves. This requirement results in the need for a possibly infeasible number of simulations when a typical converged high-fidelity simulation requires intensive computational resources. To reduce the cost of quantifying high-dimensional uncertainties, we investigate the application of a non-intrusive, bi-fidelity approximation to estimate statistics of quantities of interest associated with an irradiated particle-laden turbulent flow. This method relies on exploiting the low-rank structure of the solution to accelerate the stochastic sampling and approximation processes by means of cheaper-to-run, lower fidelity representations. The application of this bi-fidelity approximation results in accurate estimates of the QoI statistics while requiring a small number of high-fidelity model evaluations. It also enables efficient computation of sensitivity analyses which highlight that epistemic uncertainty plays an important role in the solution of irradiated, particle-laden turbulent flow.

42 ENGINEERING↗
DOE OSTI2021

Formic Acid Electrooxidation on Pt or Pd Monolayer on Transition-Metal Single Crystals: A First-Principles Structure Sensitivity Analysis

Here, we present a density functional theory analysis of trends for the electrooxidation of formic acid (FAO) on a single Pt or Pd monolayer supported on the close-packed (111) facet of transition metals (Pt*/M or Pd*/M): Au, Ag, Cu, Pt, Pd, Ir, and Rh, the close-packed (0001) facet of Os, Ru, and Re, and the open (100) facet of Au, Ag, Pt, Pd, Ir, and Rh. We show that the deposition of Pt or Pd pseudomorphic monolayers on these single crystals modifies the electronic structure of the Pt or Pd monolayer. Specifically, we found a direct correlation between the d-band center of the Pt and Pd monolayer and the free energy of adsorbed CO*, the latter being a reactivity descriptor for FAO. Together with the free energy of adsorbed OH* as a second reactivity descriptor, we depict the thermochemistry of the reaction network as phase diagrams showing calculated free energies across regions of rate-determining steps. We found that FAO is structure-sensitive on most surfaces studied. Pt*/Au(111) is predicted to be the most active among all Pt*/M(111/0001) surfaces studied, despite binding CO*, the strongest among the close-packed facets. This is the case because of its superiority in activating water to OH*, thus removing CO* at lower potentials than other surfaces. On similar grounds, Pt*/Pd(100), Pd*/Re(0001), Pd*/Au(111), Pd*/Ag(111), and Pd*/Pt(111) are predicted to show higher FAO activity than the corresponding monometallic Pt and Pd surfaces.

(100) facets↗
DOE OSTI2021

Sensitivity Analysis of Tunable Equation of State Material Model In Pulsed Mercury Target Simulation

A pulsed neutron spallation target is subjected to very short but intense loads from repeated proton pulses. Approximately 60% of the energy from each proton pulse is deposited into the mercury target material and the stainless-steel target structure, leading to a high-pressure region in both the stationary target structure and the flowing mercury. The high-pressure region propagates and leads to fluid-structure interaction. The resultant loading on the target structure containing liquid mercury is difficult to predict, although various simulation approaches and material models for the mercury have been tried. To date, the best match of simulation to experimental data is obtained by using an equation of state (EOS) material model with a specified tensile cutoff pressure, which simulates the cavitation threshold. The inclusion of a threshold to represent cavitation is key to the successful predictions of stress waves triggered by the high-energy pulse striking the mercury and vessel. However, recent measurements of target structure strain show that significant discrepancies remain between the measured and simulated strain values in the EOS mercury model. These differences grow when noncondensable helium gas is intentionally injected into the flowing mercury to reduce the loading on the structure. An EOS-based proportional–integral–derivative (PID) mercury model has been proposed to reduce the gap between the measured and simulated vessel strain responses for targets with gas injection. The conceptual and numerical description and initial investigation of the PID model are presented in previous work. Further studies of this PID model — including the sensitivity of the structure’s strain response to model parameters (the tensile cutoff, PID parameters Kp, Ki, and Kd) — are reported in this article. Results show the strain response is more sensitive to changes in the tensile cutoff value than to changes in the model parameters Kp, Ki, and Kd. These results will aid in future work where the model parameters will be optimized to match simulation data to strain measurements.

Lin, Lianshan↗
DOE OSTI2022

Extraction of low-energy constants of single- and double-β decays from lattice QCD: A sensitivity analysis

Lattice quantum chromodynamics (LQCD) has the promise of constraining low-energy constants (LECs) of nuclear effective field theories (EFTs) from first-principles calculations that incorporate the dynamics of quarks and gluons. Given the Euclidean and finite-volume nature of LQCD outputs, complex mappings are developed in recent years to obtain the Minkowski and infinite-volume counterparts of LQCD observables. In particular, as LQCD is moving toward computing a set of important few-nucleon matrix elements at the physical values of the quark masses, it is important to investigate whether the anticipated precision of LQCD spectra and matrix elements will be sufficient to guarantee tighter constraints on the relevant LECs than those already obtained from phenomenology, considering the nontrivial mappings involved. With a focus on the leading-order LECs of the pionless EFT, L 1,A and $g$$^{NN}_{v}$, which parametrize, respectively, the strength of the isovector axial two-body current in a single-β decay (and other related processes such pp fusion), and of the isotensor contact two-body operator in the neutrinoless double-β decay within the light neutrino exchange scenario, the expected uncertainty on future extractions of L 1,A and $g$$^{NN}_{v}$ are examined using synthetic data at the physical values of the quark masses. It is observed that achieving small uncertainties in L 1,A will be challenging, and (sub)percent-level precision in the two-nucleon spectra and matrix elements is essential in reducing the uncertainty on this LEC compared to the existing constraints. On the other hand, the short-distance coupling of the neutrinoless double-β decay, $g$$^{NN}_{v}$, is shown to be less sensitive to uncertainties on both LQCD energies and the matrix element, and can likely be constrained with percent-level precision in the upcoming LQCD calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Solution and sensitivity analysis of nonlinear equations using a hypercomplex-variable Newton-Raphson method

Here, the classical Newton-Raphson (NR) method for solving nonlinear equations is enhanced in two ways through the use of hypercomplex variables and algebra. In particular, i) the Jacobian is computed in a highly accurate and automated way, and ii) the derivative of the solution to the nonlinear equations is computed with respect to any parameter contained within the system of equations. These advances provide two significant enhancements in that it is straightforward to provide an accurate Jacobian and to construct a reduced order model (ROM) of arbitrary order with respect to any parameter of the system. The ROM can then be used to approximate the solution for other parameter values without requiring additional solutions of the nonlinear equations. Several case studies are presented including 1D and 2D academic examples with fully functioning Python code provided. Additionally, a case of study of the catenary of an elastic cable subject to its own weight and a vertical point load. Derivatives up to 10th order were computed with respect to material, loading, and geometrical parameters. The derivatives were used to generate reduced order models of the cable deformation and reaction forces at its ends with respect to multiple input parameters. Results show that from a single hypercomplex evaluation of the cable under a single vertical point load, it is possible to generate an accurate reduced order model capable of predicting the cable deformation with 1.5 times the load in the opposite direction and with 3.5 times the load in the same direction without resolving the system of equations.

97 MATHEMATICS AND COMPUTING↗