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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Experimental and Numerical Characterization of High Temperature Deformation Behavior of 347H Stainless Steel

This study investigates how temperature affects the plasticity and thermal creep behavior of 347H stainless steel under uniaxial tension. The research combined experimental testing with advanced computational modeling. Two types of experiments were conducted: uniaxial tensile tests at temperatures from 100°C to 750°C using strain rates of ~10⁻⁴ s⁻¹, and creep tests at temperatures between 600°C and 750°C under various stress levels. These experimental results were used to develop and validate a new integrated mechanistic model that can predict material behavior under any loading condition while accounting for both stress and temperature effects. The model was implemented using a polycrystalline microstructure simulation framework based on elasto-viscoplastic Fast Fourier Transform (EVPFFT). It incorporates three key deformation mechanisms: thermally activated dislocation glide, dislocation climb, and vacancy diffusional creep. The model accounts for internal stress distribution within single crystals and considers how precipitates and solute atoms (both interstitial and substitutional) affect dislocation movement. After validation against experimental data, the model was used to generate Ashby-Weertman deformation mechanism maps for 347H steel, providing new insights into how microstructure influences the activation of different creep mechanisms.

Joy, Jobin K.↗
NASA NTRS1989

Fatigue delamination onset prediction in tapered composite laminates

Tapered (0 deg) laminates of S2/CE9000 and S2/SP250 glass/epoxies, and IM6/1827I graphite/epoxy were tested in cyclic tension. The specimens usually showed some initial stable delaminations in the tapered region, but these did not affect the stiffness of the specimens, and loading was continued until the specimens either delaminated unstably, or reached 10(exp 6) to 2 x 10(exp 7) million cycles with no unstable delamination. The final unstable delamination originated at the junction of the thin and tapered regions. A finite-element model was developed for the tapered laminate with and without the initial stable delaminations observed in the tests. The analysis showed that for both cases the most likely place for an opening (Mode 1) delamination to originate is at the junction of the taper and thin regions. For each material type, the models were used to calculate the strain energy release rate, G, associated with delaminations originating at that junction and growing either into the thin region or tapered region. For the materials tested, cyclic G(sub Imax) values from DCB tests were used with the maximum strain energy release rates calculated from the finite-element analysis to predict the onset of unstable delamination at the junction as a function of fatigue cycles. The predictions were compared to experimental values of maximum cyclic load as a function of cycles to unstable delamination from fatigue tests in tapered laminates. For the IM6/1827I and S2/SP250 laminates, the predictions agreed very well with the test data. Predicted values for the S2/CE9000 were conservative compared to the test data.

Murri, Gretchen Bostaph↗
NASA NTRS1991

Fatigue delamination onset prediction in unidirectional tapered laminates

Tapered (0 deg) laminates of S2/CE9000 and S2/SP250 glass/epoxies, and IM6/1827I graphite/epoxy were tested in cyclic tension. The specimens usually showed some initial stable delaminations in the tapered region, but these did not affect the stiffness of the specimens, and loading was continued until the specimens either delaminated unstably, or reached 10(exp 6) to 2 x 10 (exp 7) million cycles with no unstable delamination. The final unstable delamination originated at the junction of the thin and tapered regions. A finite-element model was developed for the tapered laminate with and without the initial stable delaminations observed in the tests. The analysis showed that for both cases the most likely place for an opening (Mode I) delamination to originate is at the junction of the taper and thin regions. For each material type, the models were used to calculate the strain energy release rate, G, associated with delaminations originating at that junction and growing either into the thin region or tapered region. For the materials tested, cyclic G(sub Imax) values from DCB tests were used with the maximum strain energy release rates calculated from the finite-element analysis to predict the onset of unstable delamination at the junction as a function of fatigue cycles. The predictions were compared to experimental values of maximum cyclic load as a function of cycles to unstable delamination from fatigue tests in tapered laminates. For the IM6/1827I and S2/SP250 laminates, the predictions agreed very well with the test data. Predicted values for the S2/CE9000 were conservative compared to the test data.

Murri, Gretchen B.↗
NASA NTRS2018

Helium Pressurization Modeling of the EDU Submerged Diffuser Using Thermal Desktop

NASA is currently working on developing its predictive modeling capabilities to support future missions that require long term storage of cryogenic propellants. Through the Evolvable Cryogenics project, Development and Validation of Analysis Tools (DVAT) task, both CFD and multi-node fluid modeling tools are being validated against to increase the following cryogenic fluid management technologies: Self-Pressurization, Pressure Control, Helium Pressurization, de-stratification, jet mixing, Tank and transfer line chill-down, tank filling and transfer. NASA is using previous and future micro-gravity experiments to validate both types of models. Recent activities include: Validation of the Tank Pressure Control Experiment (TPCE), Hydrogen and Helium pressurization, and Completion of the Zero Boil Off Tank (ZBOT) experiment on ISS. Future activities include validation of the ZBOT experiment with both CFD and multi-node analysis tools, validation of the Cryogenic Demonstration System of the Robotic Refueling Mission (RRM3).

low-gravity fluid modeling↗
NASA NTRS2016

Modeling ARRM Xenon Tank Pressurization Using 1D Thermodynamic and Heat Transfer Equations

As a first step in understanding what ground support equipment (GSE) is required to provide external cooling during the loading of 5,000 kg of xenon into 4 aluminum lined composite overwrapped pressure vessels (COPVs), a modeling analysis was performed using Microsoft Excel. The goals of the analysis were to predict xenon temperature and pressure throughout loading at the launch facility, estimate the time required to load one tank, and to get an early estimate of what provisions for cooling xenon might be needed while the tanks are being filled. The model uses the governing thermodynamic and heat transfer equations to achieve these goals. Results indicate that a single tank can be loaded in about 15 hours with reasonable external coolant requirements. The model developed in this study was successfully validated against flight and test data. The first data set is from the Dawn mission which also utilizes solar electric propulsion with xenon propellant, and the second is test data from the rapid loading of a hydrogen cylindrical COPV. The main benefit of this type of model is that the governing physical equations using bulk fluid solid temperatures can provide a quick and accurate estimate of the state of the propellant throughout loading which is much cheaper in terms of computational time and licensing costs than a Computation Fluid Dynamics (CFD) analysis while capturing the majority of the thermodynamics and heat transfer.

Xenon storage↗
NASA NTRS2017

Modeling Xenon Tank Pressurization using One-Dimensional Thermodynamic and Heat Transfer Equations

As a first step in understanding what ground support equipment (GSE) is required to provide external cooling during the loading of 5,000 kg of xenon into 4 aluminum lined composite overwrapped pressure vessels (COPVs), a modeling analysis was performed using Microsoft Excel. The goals of the analysis were to predict xenon temperature and pressure throughout loading at the launch facility, estimate the time required to load one tank, and to get an early estimate of what provisions for cooling xenon might be needed while the tanks are being filled. The model uses the governing thermodynamic and heat transfer equations to achieve these goals. Results indicate that a single tank can be loaded in about 15 hours with reasonable external coolant requirements. The model developed in this study was successfully validated against flight and test data. The first data set is from the Dawn mission which also utilizes solar electric propulsion with xenon propellant, and the second is test data from the rapid loading of a hydrogen cylindrical COPV. The main benefit of this type of model is that the governing physical equations using bulk fluid solid temperatures can provide a quick and accurate estimate of the state of the propellant throughout loading which is much cheaper in terms of computational time and licensing costs than a Computation Fluid Dynamics (CFD) analysis while capturing the majority of the thermodynamics and heat transfer.

Thermodynamic tank modeling↗
DOE OSTI2023

Accurate Prediction of Algal Biomass Lipid, Protein, and Carbohydrate Composition with Machine Learning Regression Modelling of Near-IR Spectra

During large scale algal biomass cultivation, it is difficult to reliably control relative composition to target levels. Rapid determination of chemical composition is feasible by using near infrared (NIR) spectral data. We sought to build and improve on reliable high-throughput screening prediction method based on partial least squares regression (PLSR) by the application of artificial neural networks (ANN) and associated optimization strategies. The algal biomass sample set was designed and created in an iterative process of culturing in physiologically diverse conditions at the GAI field site, followed by compositional analyses at NREL. The workflow allowed us to identify gaps in compositional space for informing the subsequent cultivation and sampling efforts and generated a high quality set of 210 unique samples with chemical analysis results, spectral scanning data, and cultivation metadata. We observed a significant improvement in the performance of carbohydrate content predictions using an optimized ANN model compared to PLSR, with > 16% reduction in mean absolute percent error (MAPE) when tested on the same set of reserved data. The optimized ANN models for FAME and protein prediction performed exceptionally well with 5.99% and 5.09% MAPE, respectively. Application of these methods to detection and quantification of minor biomass constituents that are relevant to certain product streams has shown positive preliminary results, opening the possibility for extensions to the outputs of this powerful data type. All models are accompanied by prediction uncertainties and unsupervised spectral outlier detection to alert an operator to unreliable spectral data. These tools can be deployed for rapid determination of algal culture status, and cultivation and biomass quality improvement.

algal biofuels↗
DOE OSTI2020

Reduced type-A carbohydrate-binding module interactions to cellulose I leads to improved endocellulase activity

Dissociation of nonproductively bound cellulolytic enzymes from cellulose is hypothesized to be a key rate-limiting factor impeding cost-effective biomass conversion to fermentable sugars. However, the role of carbohydrate-binding modules (CBMs) in enabling nonproductive enzyme binding is not well understood. Here, we examine the subtle interplay of CBM binding and cellulose hydrolysis activity for three models type-A CBMs (Families 1, 3a, and 64) tethered to multifunctional endoglucanase (CelE) on two distinct cellulose allomorphs (i.e., cellulose I and III). We generated a small library of mutant CBMs with varying cellulose affinity, as determined by equilibrium binding assays, followed by monitoring cellulose hydrolysis activity of CelE–CBM fusion constructs. Finally, kinetic binding assays using quartz crystal microbalance with dissipation were employed to measure CBM adsorption and desorption rate constants kon and koff, respectively, towards nanocrystalline cellulose derived from both allomorphs. Overall, our results indicate that reduced CBM equilibrium binding affinity towards cellulose I alone, resulting from increased desorption rates (koff) and reduced effective adsorption rates (nkon), is correlated to overall improved endocellulase activity. Future studies could employ similar approaches to unravel the role of CBMs in nonproductive enzyme binding and develop improved cellulolytic enzymes for industrial applications.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2013

Modeling Circumstellar Disks of B-Type Stars with Observations from the Palomar Testbed Interferometer

Geometrical (uniform disk) and numerical models were calculated for a set of B-emission (Be) stars observed with the Palomar Testbed Interferometer (PTI). Physical extents have been estimated for the disks of a total of15 stars via uniform disk models. Our numerical non-LTE models used parameters for the B0, B2, B5, and B8spectral classes and following the framework laid by previous studies, we have compared them to infrared K-band interferometric observations taken at PTI. This is the first time such an extensive set of Be stars observed with long-baseline interferometry has been analyzed with self-consistent non-LTE numerical disk models.

Grzenia, B. J.↗
NASA NTRS2018

Quantifying Boreal Forest Structure and Composition Using UAV Structure from Motion

The vast extent and inaccessibility of boreal forest ecosystems are barriers to routine monitoring of forest structure and composition. In this research, we bridge the scale gap between intensive but sparse plot measurements and extensive remote sensing studies by collecting forest inventory variables at the plot scale using an unmanned aerial vehicle (UAV) and a structure from motion (SfM) approach. At 20 Forest Inventory and Analysis (FIA) subplots in interior Alaska, we acquired overlapping imagery and generated dense, 3D, RGB (red, green, blue) point clouds. We used these data to model forest type at the individual crown scale as well as subplot-scale tree density (TD), basal area (BA), and aboveground biomass (AGB). We achieved 85% cross-validation accuracy for five species at the crown level. Classification accuracy was maximized using three variables representing crown height, form, and color. Consistent with previous UAV-based studies, SfM point cloud data generated robust models of TD (r(sup 2) = 0.91), BA (r(sup 2) = 0.79), and AGB (r(sup 2) = 0.92), using a mix of plot- and crown-scale information. Precise estimation of TD required either segment counts or species information to differentiate black spruce from mixed white spruce plots. The accuracy of species-specific estimates of TD, BA, and AGB at the plot scale was somewhat variable, ranging from accurate estimates of black spruce TD (+/−1%) and aspen BA (−2%) to misallocation of aspen AGB (+118%) and white spruce AGB (−50%). These results convey the potential utility of SfM data for forest type discrimination in FIA plots and the remaining challenges to develop classification approaches for species-specific estimates at the plot scale that are more robust to segmentation error.

aboveground biomass↗
DOE OSTI2023

DeePMD-kit v2: A software package for deep potential models

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features, such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, DP-range correction, DP long range, graphics processing unit support for customized operators, model compression, non-von Neumann molecular dynamics, and improved usability, including documentation, compiled binary packages, graphical user interfaces, and application programming interfaces. This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, this article presents a comprehensive procedure for conducting molecular dynamics as a representative application, benchmarks the accuracy and efficiency of different models, and discusses ongoing developments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Deep learning inversion of gravity data for detection of CO 2 plumes in overlying aquifers

In this work, we developed an effective U-Net based deep learning (DL) model for inversion of surface gravity data on a rectangular grid to predict 2-D high-resolution subsurface CO 2 distribution along a vertical cross-section due to CO 2 leakage through a wellbore within a deep CO 2 storage reservoir. We used synthetic data to model two types of CO 2 leakage scenarios: one CO 2 plume in a shallow aquifer (single plume case), and two plumes present at different depths (double plume case). The 3-D synthetic plume samples were created by sampling among predetermined CO 2 plume depths, saturations, and volumes. The corresponding surface gravity data on a rectangular grid were generated by a 3-D forward model. The U-Net model detected 72% of single-plume samples, and one or both plumes in 75% of double-plume samples. Most of the undetected single plumes have small gravity field strengths below the typical noise level of 5 μGal. This model generated reproducible, reliable predictions with acceptable errors and demonstrated improved spatial resolution over the conventional least-squares inversion. In contrast to the conventional least-squares inversion, which often overestimates the size of its target and underestimates its density, this U-Net model accurately delineated the boundary of a target. Furthermore, this DL inversion detected deep, small, or low saturation CO 2 plumes that are often more difficult to resolve with conventional gravity inversion methods. We note the limitations of this feasibility study, including the use of synthetic data with regular CO 2 plume shapes, and the prediction of a 2-D plume cross-section rather than the full 3-D plume, as well, we recognize the lower detection fraction for double-plume scenarios. Nevertheless, this study demonstrates that DL gravity inversion is a promising and potentially superior method to conventional least-squares inversion. Our U-Net based deep learning inversion approach may be adapted for inversion of other types of geophysical data. DL inversion can facilitate near real-time monitoring of geologic carbon sequestration to provide site operators with prompt information about subsurface CO 2 distribution for risk management and mitigation.

58 GEOSCIENCES↗
NASA NTRS1993

Orthopyroxenes as recorders of diogenite petrogenesis: Trace element systematics

Eucrite, howardite, and diogenite members of the achondrites are considered, by many, to be genetically related. Therefore, each provide a piece of the puzzle for reconstructing magmatic processes on the eucrite parent body (EPB). The relationship between eucrites and diogenites can be viewed within the context of two distinctly different models: (1) fractional crystallization; and (2) partial melting. In fractional crystallization models, eucrites and diogenites represent a complementary continuum of planetary fractional crystallization products in which the diogenites represent crystal accumulations during the crystallization of eucritic magmas at shallow to deep levels in the EPB. Alternatively, experimental studies may be interpreted as indicating eucrites represent peritectic partial melts of a primitive, chondritic EPB mantle. Within this type of model, the diogenites are also generally considered to be cumulates; however, their petrogenetic relationship to the eucrites is less clear. Sack et al. proposed that the olivine diogenites represent residua from the partial melting events that produced eucritic liquids. Initial trace element studies of orthopyroxene (OPX) are consistent with this model. However, this trace element modeling of the olivine diogenites is nonunique. As a further test of these models, we did the following three things: (1) analyzed OPX from cumulate diogenites to compare with the olibine diogenite data; (2) improved ion microprobe analytical techniques for the analysis of elements critical to our interpretations; and (3) selected more relevant Kd's for OPX-eucritic melt.

Shearer, C. K.↗
NASA NTRS1993

Steady induction effects in geomagnetism. Part 1C: Geomagnetic estimation of steady surficial core motions: Application to the definitive geomagnetic reference field models

In the source-free mantle/frozen-flux core magnetic earth model, the non-linear inverse steady motional induction problem was solved using the method presented in Part 1B. How that method was applied to estimate steady, broad-scale fluid velocity fields near the top of Earth's core that induce the secular change indicated by the Definitive Geomagnetic Reference Field (DGRF) models from 1945 to 1980 are described. Special attention is given to the derivation of weight matrices for the DGRF models because the weights determine the apparent significance of the residual secular change. The derived weight matrices also enable estimation of the secular change signal-to-noise ratio characterizing the DGRF models. Two types of weights were derived in 1987-88: radial field weights for fitting the evolution of the broad-scale portion of the radial geomagnetic field component at Earth's surface implied by the DGRF's, and general weights for fitting the evolution of the broad-scale portion of the scalar potential specified by these models. The difference is non-trivial because not all the geomagnetic data represented by the DGRF's constrain the radial field component. For radial field weights (or general weights), a quantitatively acceptable explication of broad-scale secular change relative to the 1980 Magsat epoch must account for 99.94271 percent (or 99.98784 percent) of the total weighted variance accumulated therein. Tolerable normalized root-mean-square weighted residuals of 2.394 percent (or 1.103 percent) are less than the 7 percent errors expected in the source-free mantle/frozen-flux core approximation.

Voorhies, Coerte V.↗
NASA NTRS1994

Spectral properties of blast-wave models of gamma-ray burst sources

We calculate the spectrum of blast-wave models of gamma-ray burst sources, for various assumptions about the magnetic field density and the relativistic particle acceleration efficiency. For a range of physically plausible models we find that the radiation efficiency is high and leads to nonthermal spectra with breaks at various energies comparable to those observed in the gamma-ray range. Radiation is also predicted at other wavebands, in particular at X-ray, optical/UV, and GeV/TeV energies. We discuss the spectra as a function of duration for three basic types of models, and for cosmological, halo, and galactic disk distances. We also evaluate the gamma-ray fluences and the spectral characteristics for a range of external densities. Impulsive burst models at cosmological distances can satisfy the conventional X-ray paucity constraint S(sub x)/S(sub gamma)less than a few percent over a wide range of durations, but galactic models can do so only for bursts shorter than a few seconds, unless additional assumptions are made. The emissivity is generally larger for bursts in a denser external environment, with the efficiency increasing up to the point where all the energy input is radiated away.

Meszaros, P.↗
NASA NTRS1997

An Ecosystem Simulation Model for Methane Production and Emission from Wetlands

Previous experimental studies suggest that methane emission from wetland is influenced by multiple interactive pathways of gas production and transport through soil and sediment layers to the atmosphere. The objective of this study is to evaluate a new simulation model of methane production and emission in wetland soils that was developed initially to help identify key processes that regulate methanogenesis and net flux of CH4 to the air, but which is designed ultimately for regional simulation using remotely sensed inputs for land cover characteristics. The foundation for these computer simulations is based on a well-documented model (CASA) of ecosystem production and carbon cycling in the terrestrial blaspheme. Modifications to represent flooded wetland soils and anaerobic decomposition include three new sub-models for: (1) layered soil temperature and water table depth (WTD) as a function of daily climate drivers, (2) CH4 production within the anoxic soil layer as a function of WTD and CO2 production under poorly drained conditions, and (3) CH4 gaseous transport pathways (molecular diffusion, ebullition, and plant vascular transport) as a function of WTD and ecosystem type. The model was applied and tested using climate and ecological data to characterize tundra wetland sites near Fairbanks, Alaska studied previously by Whalen and Reeburgh. Comparison of model predictions to measurements of soil temperature and thaw depth, water-table depth, and CH4 emissions over a two year period suggest that inter-site differences in soil physical conditions and methane fluxes could be reproduced accurately for selected periods. Day-to-day comparison of predicted emissions to measured CH4 flux rates reveals good agreement during the early part of the thaw season, but the model tends to underestimate production of CH4 during the months of July and August in both test years. Important seasonal effects, including that of falling WTD during these periods, are apparently overlooked in the model formulation. Nevertheless, reasonably close agreement was achieved between the model's mean daily and seasonal estimates of CH4 flux and observed emission rates for northern wetland ecosystems. Several features of the model are identified as crucial to more accurate prediction of wetland methane emission, including the capacity to incorporate influences of localized topographic and hydrologic features on site-specific soil temperature and WTD dynamics, and mechanistic simulation of methane emission transport pathways from within the soil profile.

Potter, C. S.↗
DOE OSTI2022

Phase-field framework with constraints and its applications to ductile fracture in polycrystals and fatigue

Abstract Modeling of ductile fracture in polycrystalline structures is challenging, since it requires integrated modeling of cracks, crystal plasticity, and grains. Here we extend the typical phase-field framework to the situations with constraints on the order parameters, and formulate two types of phase-field models on ductile fracture. The Type-I model incorporates three sets of order parameters, which describe the distributions of cracks, plastic strain, and grains, respectively. Crystal plasticity is employed within grain interiors accommodated by J 2 plasticity at grain boundaries. The applications of the Type-I model to single crystals and bicrystals demonstrate the influences of grain orientations and grain boundaries on crack growth. In the Type-II model, J 2 plasticity is assumed for the whole system and grain structures are neglected. Taking advantage of the efficiency of the fast Fourier transform, our Type-II model is employed to study low cycle fatigue. Crack closure and striation-like patterning of plastic strain are observed in the simulations. Crack growth rate is analyzed as a function of the J -integral, and the simulated fatigue life as a function of plastic strain agrees with the Coffin–Manson relation without a priori assumption.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Energy balance in the solar transition region. I - Hydrostatic thermal models with ambipolar diffusion

The energy balance in the lower transition region is analyzed by constructing theoretical models which satisfy the energy balance constraint. The energy balance is achieved by balancing the radiative losses and the energy flowing downward from the corona. This energy flow is mainly in two forms: conductive heat flow and hydrogen ionization energy flow due to ambipolar diffusion. Hydrostatic equilibrium is assumed, and, in a first calculation, local mechanical heating and Joule heating are ignored. In a second model, some mechanical heating compatible with chromospheric energy-balance calculations is introduced. The models are computed for a partial non-LTE approach in which radiation departs strongly from LTE but particles depart from Maxwellian distributions only to first order. The results, which apply to cases where the magnetic field is either absent, or uniform and vertical, are compared with the observed Lyman lines and continuum from the average quiet sun. The approximate agreement suggests that this type of model can roughly explain the observed intensities in a physically meaningful way, assuming only a few free parameters specified as chromospheric boundary conditions.

Fontenla, J. M.↗