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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Interpolant Improvements and Lessons Learned

This presentation is for the OpenMDAO workshop 2022 and updates users on recent improvements to interpolant methods. Specifically, we discuss computational improvements, visualization capabilities, and suggested best practices for using interpolants. The term interpolants is used synonymously with metamodels and surrogate models. The goal of the presentation is to increase adoption of efficient interpolant methods and increase users’ awareness to built-in features within OpenMDAO.

Multidisciplinary Design Optimization↗
DOE OSTI2024

Thermodynamic modeling of CsF with LiF-NaF-KF for molten fluoride-fueled reactors

Gibbs energy models were developed to describe the thermochemical behavior of CsF in molten FLiNaK (46.5LiF-11.5NaF-42KF mol%), a proposed molten salt reactor (MSR) fuel solvent and coolant, as cesium is of concern due to its high radiotoxicity and volatility. Initially, it was necessary to obtain a more accurate Gibbs energy function for CsF which required fitting parameters to reported vapor pressures over condensed phase CsF. The pseudo-binary systems CsF-LiF, CsF-NaF and CsF-KF were then evaluated utilizing phase equilibria and enthalpy of mixing (Δ mix H) values, together with original differential scanning calorimetry (DSC) measurements performed for the CsF-LiF and CsF-KF systems. The CsF-LiF-NaF, CsF-LiF-KF and CsF-NaF-KF pseudo-ternary system representations were obtained by interpolation of the constituent pseudo-binary systems, with DSC measurements performed for the CsF-LiF-NaF system to corroborate the calculated liquidus temperature. Ultimately, the pseudo-ternary systems were interpolated to obtain Gibbs energy models for the pseudo-quaternary CsF-LiF-NaF-KF system, supported by DSC measurements at low CsF compositions (1–10 mol%), yielding computed equilibria and cesium-containing vapor pressures that compare favorably with reported values. In conclusion, the Molten Salt Thermal Properties Database – Thermochemical (MSTDB-TC) was subsequently expanded to include these Gibbs energy models allowing description of the thermochemical behavior of the CsF-LiF-NaF-KF system.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1984

A climatically-derived global soil moisture data set for use in the GLAS atmospheric circulation model seasonal cycle experiment

Algorithms for point interpolation and contouring on the surface of the sphere and in Cartesian two-space are developed from Shepard's (1968) well-known, local search method. These mapping procedures then are used to investigate the errors which appear on small-scale climate maps as a result of the all-too-common practice of of interpolating, from irregularly spaced data points to the nodes of a regular lattice, and contouring Cartesian two-space. Using mean annual air temperatures field over the western half of the northern hemisphere is estimated both on the sphere, assumed to be correct, and in Cartesian two-space. When the spherically- and Cartesian-approximted air temperature fields are mapped and compared, the magnitudes (as large as 5 C to 10 C) and distribution of the errors associated with the latter approach become apparent.

Willmott, C. J.↗
NASA NTRS1985

Numerical analysis of flow non-uniformity in the hot gas manifold of the Space Shuttle main engine

Three-dimensional viscous flow in a conceptual hot gas manifold (HGM) for the Space Shuttle Main Engine High Pressure Fuel Turbopump (SSME HPFTP) was numerically analyzed. A finite difference scheme was used to solve the Navier-Stokes equations. The exact geometry of the SSME HGM was modeled using boundary fitted curvilinear coordinates and the General Interpolants Method (GIM) code. Slight compressibility of the subsonic flow was modeled using a linearized equation of state with artificial compressibility. A time relaxation method was used to obtain a steady state solution. The feasibility and potential usefulness of computational methods in assisting the design of SSME components which involves the flow of fluids within complex geometrical shapes is demonstrated.

Thoenes, J.↗
DOE OSTI2020

The effect of geographic sampling on evaluation of extreme precipitation in high-resolution climate models

Traditional approaches for comparing global climate models and observational data products typically fail to account for the geographic location of the underlying weather station data. For modern global high-resolution models with a horizontal resolution of tens of kilometers, this is an oversight since there are likely grid cells where the physical output of a climate model is compared with a statistically interpolated quantity instead of actual measurements of the climate system. In this paper, we quantify the impact of geographic sampling on the relative performance of high-resolution climate model representations of precipitation extremes in boreal winter (December–January–February) over the contiguous United States (CONUS), comparing model output from five early submissions to the HighResMIP subproject of the CMIP6 experiment. We find that properly accounting for the geographic sampling of weather stations can significantly change the assessment of model performance. Across the models considered, failing to account for sampling impacts the different metrics (extreme bias, spatial pattern correlation, and spatial variability) in different ways (both increasing and decreasing). We argue that the geographic sampling of weather stations should be accounted for in order to yield a more straightforward and appropriate comparison between models and observational data sets, particularly for high-resolution models with a horizontal resolution of tens of kilometers. While we focus on the CONUS in this paper, our results have important implications for other global land regions where the sampling problem is more severe.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Recommendations for developing, documenting, and distributing data products derived from NEON data

The National Ecological Observatory Network (NEON) provides over 180 distinct data products from 81 sites (47 terrestrial and 34 freshwater aquatic sites) within the United States and Puerto Rico. These data products include both field and remote sensing data collected using standardized protocols and sampling schema, with centralized quality assurance and quality control (QA/QC) provided by NEON staff. Such breadth of data creates opportunities for the research community to extend basic and applied research while also extending the impact and reach of NEON data through the creation of derived data products—higher level data products derived by the user community from NEON data. Derived data products are curated, documented, reproducibly-generated datasets created by applying various processing steps to one or more lower level data products—including interpolation, extrapolation, integration, statistical analysis, modeling, or transformations. Derived data products directly benefit the research community and increase the impact of NEON data by broadening the size and diversity of the user base, decreasing the time and effort needed for working with NEON data, providing primary research foci through the development via the derivation process, and helping users address multidisciplinary questions. Creating derived data products also promotes personal career advancement to those involved through publications, citations, and future grant proposals. However, the creation of derived data products is a nontrivial task. Here we provide an overview of the process of creating derived data products while outlining the advantages, challenges, and major considerations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1980

Instrumented aircraft verification of clear-air radar detection of low-level wind shear

A technique is described in which the longitudinal wind component at airports, measured by Doppler radar, is put through a Fourier transformation to produce an energy density spectrum. The result is multiplied by the aircraft response characteristics to produce quantitative data on aircraft performance in a wind shear situation. The Doppler radar measurements are made along the intended flight path. Two case studies, along a 3 deg approach path, are described from measurements in two modes: Lagrangian, where predictions were computed one range gate ahead of the plane, and Eulerian, where samples were measured instantaneously along the flight path. Wind data obtained every second were interpolated to fit a numerical model by using a cubic spline. Eulerian data were superior to Lagrangian data in terms of ranging, and nearly equal for wind speeds. Improvements in current 75% accuracy are noted to be possible with shrouded antennas to reduce sidelobes and use of Doppler radar with higher resolution to eliminate effects of small scale disturbances within the pulse volume.

Mccarthy, J.↗
NASA NTRS1983

Relative Elevation Determination from LANDSAT Imagery

In LANDSAT imagery, spectral and spatial information can be used to detect the drainage network as well as the relative elevation model in mountainous terrain. To do this, the mixed information of material reflectance and topographic modulation in the original LANDSAT imagery must be first separated. From the material reflectance information, big visible rivers can be detected. From the topographic modulation information, ridges and valleys can be detected and assigned relative elevations. Finally, a relative elevation model can be generated by interpolating values for nonridge and nonvalley pixels.

Haralick, R. M.↗
NASA NTRS1986

Physical and numerical sources of computational inefficiency in integration of chemical kinetic rate equations: Etiology, treatment and prognosis

The design of a very fast, automatic black-box code for homogeneous, gas-phase chemical kinetics problems requires an understanding of the physical and numerical sources of computational inefficiency. Some major sources reviewed in this report are stiffness of the governing ordinary differential equations (ODE's) and its detection, choice of appropriate method (i.e., integration algorithm plus step-size control strategy), nonphysical initial conditions, and too frequent evaluation of thermochemical and kinetic properties. Specific techniques are recommended (and some advised against) for improving or overcoming the identified problem areas. It is argued that, because reactive species increase exponentially with time during induction, and all species exhibit asymptotic, exponential decay with time during equilibration, exponential-fitted integration algorithms are inherently more accurate for kinetics modeling than classical, polynomial-interpolant methods for the same computational work. But current codes using the exponential-fitted method lack the sophisticated stepsize-control logic of existing black-box ODE solver codes, such as EPISODE and LSODE. The ultimate chemical kinetics code does not exist yet, but the general characteristics of such a code are becoming apparent.

Pratt, D. T.↗
NASA NTRS1985

Analysis/forecast experiments with a multivariate statistical analysis scheme using FGGE data

A three-dimensional, multivariate, statistical analysis method, optimal interpolation (OI) is described for modeling meteorological data from widely dispersed sites. The model was developed to analyze FGGE data at the NASA-Goddard Laboratory of Atmospherics. The model features a multivariate surface analysis over the oceans, including maintenance of the Ekman balance and a geographically dependent correlation function. Preliminary comparisons are made between the OI model and similar schemes employed at the European Center for Medium Range Weather Forecasts and the National Meteorological Center. The OI scheme is used to provide input to a GCM, and model error correlations are calculated for forecasts of 500 mb vertical water mixing ratios and the wind profiles. Comparisons are made between the predictions and measured data. The model is shown to be as accurate as a successive corrections model out to 4.5 days.

Baker, W. E.↗
NASA NTRS1992

Coupled 2D-3D finite element method for analysis of a skin panel with a discontinuous stiffener

This paper describes a computationally efficient analysis method which was used to predict detailed stress states in a typical composite compression panel with a discontinuous hat stiffener. A global-local approach was used. The global model incorporated both 2D shell and 3D brick elements connected by newly developed transition elements. Most of the panel was modeled with 2D elements, while 3D elements were employed to model the stiffener flange and the adjacent skin. Both linear and geometrically nonlinear analyses were performed on the global model. The effect of geometric nonlinearity induced by the eccentric load path due to the discontinuous hat stiffener was significant. The local model used a fine mesh of 3D brick elements to model the region at the end of the stiffener. Boundary conditions of the local 3D model were obtained by spline interpolation of the nodal displacements from the global analysis. Detailed in-plane and through-the-thickness stresses were calculated in the flange-skin interface near the end of the stiffener.

Wang, J. T.↗
NASA NTRS2015

Maintaining Atmospheric Mass and Water Balance Within Reanalysis

This report describes the modifications implemented into the Goddard Earth Observing System Version-5 (GEOS-5) Atmospheric Data Assimilation System (ADAS) to maintain global conservation of dry atmospheric mass as well as to preserve the model balance of globally integrated precipitation and surface evaporation during reanalysis. Section 1 begins with a review of these global quantities from four current reanalysis efforts. Section 2 introduces the modifications necessary to preserve these constraints within the atmospheric general circulation model (AGCM), the Gridpoint Statistical Interpolation (GSI) analysis procedure, and the Incremental Analysis Update (IAU) algorithm. Section 3 presents experiments quantifying the impact of the new procedure. Section 4 shows preliminary results from its use within the GMAO MERRA-2 Reanalysis project. Section 5 concludes with a summary.

IAU↗
DOE OSTI2022

Uncertainty Quantification of Calculated Temperatures for the AGR 5/6/7 Experiment

This report documents the quantification of uncertainty of the calculated temperature data for the Advanced Gas Reactor (AGR) 5/6/7 fuel irradiation experiment conducted in the Advanced Test Reactor at Idaho National Laboratory in support of the Advanced Reactor Technologies? research and development program. Recognizing uncertainties inherent in physics and thermal simulations of the AGR 5/6/7 capsules, the results of the numerical simulations are used in combination with statistical analysis methods to improve qualification of measured data. The calculated fuel temperatures for AGR tests are also used for validation of the fission product transport and fuel performance simulation models. These crucial roles of the calculated fuel temperatures in ensuring achievement of the AGR experimental program objectives require accurate determination of the model temperature uncertainties. This report covers temperature uncertainty results for each of the five AGR 5/6/7 capsules. To quantify the uncertainty of calculated temperatures determined using the ABAQUS finite element heat transfer code, this study identifies and analyzes model parameters of potential importance to the calculated temperatures of fuel compacts and thermocouples. The selection of input parameters for uncertainty quantification is based on the ranking of their influences upon temperature predictions. Thus, selected input parameters include those with high sensitivity and those with the largest uncertainty. Propagation of model parameter uncertainty and sensitivity is then used to quantify the overall uncertainty of calculated temperatures. Measurement uncertainty, analysis of modeling assumptions, and expert judgment are used as the basis to quantify the uncertainty range for selected input parameters. The input uncertainties are dynamic, accounting for the effect of unplanned events and changes in thermal properties of capsule components over extended exposure to high temperatures and fast neutron irradiation. The sensitivity analysis performed in this work went beyond the traditional local sensitivity. Using experimental design, analysis of pairwise interactions of model parameters was performed to establish sufficiency of the time dependent first order (linear) expansion terms in constructing the temperature response surface. To achieve completeness, uncertainty propagation made use of pairwise noise correlations of model parameters. Furthermore, using an interpolation scheme over the input parameter domain, the analysis obtains time dependent sensitivity over the test campaign duration. This allows computation of uncertainty for the calculated fuel temperatures and the calculated graphite temperatures at thermocouple locations during the entire irradiation period.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Metamodeling Time-Temperature Creep Parameters

Abstract There exist many time-temperature parameter (TTP) models for creep rupture prediction of components including the Larson–Miller (LM), Manson–Haferd (MH), Manson–Brown (MB), Orr–Sherby–Dorn (OSD), Manson–Succop (MS), Graham–Walles (GW), Chitty–Duval (CD), Goldhoff–Sherby (GS) models. It remains a challenge to determine which model is “best”, capable of accurate interpolation and physically realistic extrapolation of creep rupture data for a given material. In this study, metamodeling is applied to create a unified TTP metamodel that combines and regresses into twelve TTP models (eight existing and four newly derived). An analysis of the mathematical problems that exist in TTP models is provided. A matlab code is written that can: (1) calibrate the material constants of any of the twelve TTP models (using the metamodel); (2) determine the most suitable stress-parameter function; (3) and report the normalized mean square error (NMSE) of rupture predictions for a given material database. Using the metamodel, and code, a design engineer can make an intelligent selection of the “best” TTP model for creep resistant design. This process is demonstrated using four isotherms of alloy P91 creep rupture data. To assess the influence of material, further validation is performed on alloys Hastelloy X, 304SS, and 316SS. It is determined that the “best” model is dependent on material type and the quality and quantity of available data.

Engineering↗
NASA NTRS2022

Assimilation of GPM-retrieved Ocean Surface Meteorology Data for Two Snowstorm Events during ICE-POP 2018

As a component of the National Aeronautics and Space Administration (NASA) Weather Focus Area and Global Precipitation Measurement (GPM) Ground Validation participation in the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018) field research and forecast demonstration programs, hourly ocean surface meteorology properties were retrieved from the GPM microwave observations for January – March 2018. In this study, the retrieved ocean surface meteorological products – 2-m temperature, 2-m specific humidity, and 10-m wind speed were assimilated into a regional numerical weather prediction (NWP) framework to explore the application of these observations for two heavy snowfall events during the ICE-POP 2018: 27-28 February, and 7-8 March 2018. The Weather Research and Forecasting (WRF) model and the community Gridpoint Statistical Interpolation (GSI) were used to conduct high resolution simulations and data assimilation experiments. The results indicate that the data assimilation has a large influence on surface thermodynamic and wind fields in the model initial condition for both events. With cycled data assimilation, significantly positive influence of the retrieved surface observation was found for the March case with improved quantitative precipitation forecast and reduced error in temperature forecast. A slightly smaller yet positive impact was also found in the forecast of the February case.

assimilation↗
NASA NTRSDate not supplied

Impact of Thermoplastic Composites: Testing and Modeling

Thermoplastic Composites (TPCs) are being increasingly considered for aerospace applications given their faster manufacturing cycles and lower cost. The NASA High-Rate Composite Aircraft Manufacturing (HiCAM) project aims to evaluate and mature thermoplastic manufacturing technologies to achieve a 4X – 6X increase in the production rate of Next Generation Single Aisle (NGSA) commercial aircraft. Within the purview of the NASA HiCAM project, this work investigates the response of thermoplastic composites under High Energy Dynamic Impact (HEDI) conditions. HEDI tests were conducted on panels fabricated with a carbon fiber reinforced low melt semi-crystalline resin TC1225 LMPAEK T700G (T700/LMPAEK) material system. A blunt metal projectile was chosen as the impactor which impacted the T700/LMPAEK panels over a range of impact velocities imparted by a gas gun test setup. As expected, lower velocity impacts caused the projectile to rebound, whereas higher velocity impacts resulted in the projectile penetrating the test panels. For the test cases in which the projectile rebounded, the predominant damage modes recorded with Ultrasonic (UT) scans included interlaminar delaminations which exhibited a “rotating fan” like structure when viewed in the through-thickness direction. Additionally, the dynamic deflection of the center point of the back face of the test panels and the velocity of the projectile was also measured during the test. Finite element models were developed to model a test case in which the projectile rebounded. These models were developed using LS-DYNA® wherein the primary objective was to evaluate the ability of the material model MAT299 to capture the dynamic response and damage modes in the T700/LMPAEK test panels. MAT299 is a Deformation Gradient Decomposition (DGD) based Continuum Damage Mechanics (CDM) material model. The interlaminar delaminations were modeled using the cohesive contact formulation available within LS-DYNA, wherein the mixed-mode fracture is captured via the Benzegaggh-Kenane (B-K) mode-dependent fracture energy interpolation law. The above-mentioned modeling methods have mostly been applied to thermoset composites and adapting them to TPCs involves addressing challenges associated with appropriately representing material behavior. Therefore, the proposed paper would discuss the systematic approach taken to adapt thermoset composites modeling practices for applications to TPCs, while appropriately addressing material behavior. The proposed paper would show that the predicted back face center point deflection correlated reasonably well with experimental data and the peak deflection was predicted to be within 5% of the experimental measurements. The projectile rebound velocity, while predicted to be higher than the experimental measurement, was within reasonable bounds. Additionally, it will be shown that the predicted delamination shapes were in reasonable agreement with experimental data.

Composite Materials↗
DOE OSTI2020

Dynamic PRA-Based Estimation of PWR Coping Time Using a Surrogate Model for Accident Tolerant Fuel

In this study, we propose an interpolation-based response surface surrogate methodology to manage a large number of scenarios in dynamic probabilistic risk assessment. It adopts the shape Dynamic Time Warping algorithm to cluster the interpolation neighborhood from time series sample data. The interpolation method was adapted from Taylor Kriging to allow a reduced-order model of the Taylor series. In order to demonstrate its applicability to complex issues in risk assessment for nuclear engineering, an example risk response surface to estimate emergency core cooling system (ECCS) criteria for triplex silicon carbide (SiC) accident-tolerant fuel was constructed. The response surface was exploited to estimate the cumulative failure probability of the fuel cladding structure due to the uncertainties in operator actions and safety systems. The functional failures were assessed based on a combination of individual layer failures computed by coupling Risk Analysis Virtual Environment software with a pressurized water reactor 1000-MW(electric) RELAP5 model and the in-house fuel performance assessment module. Results showed that SiC cladding failure probability spiked less than 1 min after a large-break loss-of- coolant accident whenever the current ECCS criteria for Zircaloy-4 (Zr-4) cladding was used. However, it still provides an increased safety margin of three orders of magnitude compared to Zr-4. This positive margin could be utilized to relax active ECCS requirements by allowing deviations of up to 450 s in its actuation time. The proposed surrogate methodology generated a response surface of SiC cladding failure probability reasonably well, with a significant savings of computation time. This methodology is expected to be useful in the analysis of system response with complex uncertainty sources.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1999

A Priori Subgrid Analysis of Temporal Mixing Layers with Evaporating Droplets

Subgrid analysis of a transitional temporal mixing layer with evaporating droplets has been performed using three sets of results from a Direct Numerical Simulation (DNS) database, with Reynolds numbers (based on initial vorticity thickness) as large as 600 and with droplet mass loadings as large as 0.5. In the DNS, the gas phase is computed using a Eulerian formulation, with Lagrangian droplet tracking. The Large Eddy Simulation (LES) equations corresponding to the DNS are first derived, and key assumptions in deriving them are first confirmed by computing the terms using the DNS database. Since LES of this flow requires the computation of unfiltered gas-phase variables at droplet locations from filtered gas-phase variables at the grid points, it is proposed to model these by assuming the gas-phase variables to be the sum of the filtered variables and a correction based on the filtered standard deviation; this correction is then computed from the Subgrid Scale (SGS) standard deviation. This model predicts the unfiltered variables at droplet locations considerably better than simply interpolating the filtered variables. Three methods are investigated for modeling the SGS standard deviation: the Smagorinsky approach, the Gradient model and the Scale-Similarity formulation. When the proportionality constant inherent in the SGS models is properly calculated, the Gradient and Scale-Similarity methods give results in excellent agreement with the DNS.

Okongo, Nora↗