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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Understanding Material Property Impacts on Co-Current Flame Spread: Improving Understanding Crucial for Fire Safety

The prospect of long-term manned space flight brings fresh urgency to the development of an integrated and fundamental approach to the study of material flammability. Currently, NASA uses two tests, the upward flame propagation test and heat and visible smoke release rate test, to assess the flammability properties of materials to be used in space under microgravity conditions. The upward flame propagation test can be considered in the context of the 2-D analysis of Emmons. This solution incorporates material properties by a "mass transfer number", B in the boundary conditions.

Ruff, Gary↗
DOE OSTI2020

Fast and stable deep-learning predictions of material properties for solid solution alloys

We present a novel deep learning (DL) approach to produce highly accurate predictions of macroscopic physical properties of solid solution binary alloys and magnetic systems. The major idea is to make use of the correlations between different physical properties in alloy systems to improve the prediction accuracy of neural network (NN) models. We use multitasking NN models to simultaneously predict the total energy, charge density and magnetic moment. These physical properties mutually serve as constraints during the training of the multitasking NN, resulting in more reliable DL models because multiple physics properties are correctly learned by a single model. Two binary alloys, copper–gold (CuAu) and iron–platinum (FePt), were studied. Our results show that once the multitasking NN's are trained, they can estimate the material properties for a specific configuration hundreds of times faster than first-principles density functional theory calculations while retaining comparable accuracy. We used a simple measure based on the root-mean-squared errors to quantify the quality of the NN models, and found that the inclusion of charge density and magnetic moment as physical constraints leads to more stable models that exhibit improved accuracy and reduced uncertainty for the energy predictions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Naturally-meaningful and efficient descriptors: machine learning of material properties based on robust one-shot ab initio descriptors

Establishing a data-driven pipeline for the discovery of novel materials requires the engineering of material features that can be feasibly calculated and can be applied to predict a material’s target properties. Here we propose a new class of descriptors for describing crystal structures, which we term Robust One-Shot Ab initio (ROSA) descriptors. ROSA is computationally cheap and is shown to accurately predict a range of material properties. These simple and intuitive class of descriptors are generated from the energetics of a material at a low level of theory using an incomplete ab initio calculation. We demonstrate how the incorporation of ROSA descriptors in ML-based property prediction leads to accurate predictions over a wide range of crystals, amorphized crystals, metal–organic frameworks and molecules. We believe that the low computational cost and ease of use of these descriptors will significantly improve ML-based predictions.

36 MATERIALS SCIENCE↗
NASA NTRS1991

Material properties and device evaluations of ECR-deposited a-Si:H and a-SiC:H films

Device-quality a-Si:H and a-SiC:H films have been deposited using electron cyclotron resonance (ECR) microwave plasmas of SiH4, CH4, and H2 mixtures. Typical material properties of ECR-deposited, photosensitive a-Si:H films are: (1) high photosensitivity up to 2 x 106 with a photoconductivity of 10 exp -5 to 10 exp -4/(Ohm-cm), (2) a Tauc gap of 1.75 to 1.85 eV, (3) an Urbach slope of 50-60 meV determined by the constant photocurrent method, and (4) an integrated defect density of 1-2 x 10 exp 16/cu cm determined by junction capacitance measurements. Highly conductive, p-type a-SiC:H films have been produced by ECR plasmas with a conductivity of 0.2/(Ohm-cm).

Shing, Y. H.↗
DOE OSTI2020

Analysis of Material Properties of Aged Rigid Polyurethane Foam

Foams are classified as either rigid or flexible and are commonly used in applications such as pipe insulation, carpet fibers, and chair foam cushions. Polyurethane foams are excellent thermal insulators, have excellent mechanical properties, and are chemically inert. With the addition of fire protective additives, polyurethane foams have the ability to intumescence when exposed to high temperatures. For the future storage of the 9977 nuclear shipping packages, the material properties of the General Plastics 3716 rigid polyurethane foam were evaluated for long term performance by comparing aged samples to unaged samples. General Plastics 3716 rigid polyurethane foam was aged from November 2014 to June 2019 at varying temperatures of: 160 deg. F, 160 deg. F + 50% relative humidity (RH), 185 deg. F, 215 deg. F, and 250 deg. F. The foam was then analyzed via Fourier Transform Infrared Spectroscopy (FTIR), 3D Optical Microscope, Thermal Gravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC). FTIR and Optical Microscope: No significant change to chemical or physical structure was evident by FTIR or optical microscope analysis. DSC: Decrease of heat capacity over time for all oven temperatures except a slight increase for the 185 deg. F conditioned foams. Largest decrease evident with foams conditioned at 250 deg. F. A slight increase in heat capacity for humid samples. Similar trends in heat capacities at 71 deg. C and 102 deg. C. TGA: As conditioning temperature increased, a decline was evident in the average percent weight loss, onset temperature, and first derivative peak temperature. No significant effect due to humidity except for a decrease in first derivative peak temperature. Unaged samples exhibited strong intumescence. Foams conditioned at 160 deg. F exhibited slight intumescence. Results suggest fire protective additives decomposed at higher temperatures, which contributed to a lower average percent mass loss in higher temperature conditioning. Further thermal degradation testing would be beneficial to evaluate the ability of the conditioned foams to intumesce. Evaluate irradiation dose rate effects on conditioned foam. Possible conditioning in an environment with a known humidity or analyzing a new aliquot of sample for each trial to achieve a more representative heat capacity calculation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

From material properties to multiscale modeling to improve lithium-ion energy storage safety

Energy storage using lithium-ion cells dominates consumer electronics and is rapidly becoming predominant in electric vehicles and grid-scale energy storage, but the high energy densities attained lead to the potential for release of this stored chemical energy. This article introduces some of the paths by which this energy might be unintentionally released, relating cell material properties to the physical processes associated with this potential release. The selected paths focus on the anode–electrolyte and cathode–electrolyte interactions that are of typical concern for current and near-future systems. Relevant material processes include bulk phase transformations, bulk diffusion, surface reactions, transport limitations across insulating passivation layers, and the potential for more complex material structures to enhance safety. We also discuss the development, parameterization, and application of predictive models for this energy release and give examples of the application of these models to gain further insight into the development of safer energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2022

Continuous conditional generative adversarial networks for data-driven solutions of poroelasticity with heterogeneous material properties

Machine learning-based data-driven modeling can allow computationally efficient time-dependent solutions of PDEs, such as those that describe subsurface multiphysical problems. In this work, our previous approach (Kadeethum et al., 2021d) of conditional generative adversarial networks (cGAN) developed for the solution of steady-state problems involving highly heterogeneous material properties is extended to time-dependent problems by adopting the concept of continuous cGAN (CcGAN). The CcGAN that can condition continuous variables is developed to incorporate the time domain through either element-wise addition or conditional batch normalization. Moreover, this framework can handle training data that contain different timestamps and then predict timestamps that do not exist in the training data. As a numerical example, the transient response of the coupled poroelastic process is studied in two different permeability fields: Zinn & Harvey transformation and a bimodal transformation. The proposed CcGAN uses heterogeneous permeability fields as input parameters while pressure and displacement fields over time are model output. Our results show that the model provides sufficient accuracy with computational speed-up. This robust framework will enable us to perform real-time reservoir management and robust uncertainty quantification in poroelastic problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Effect of material properties on batch‐to‐glass conversion kinetics

Abstract A recently developed model of the cold cap—the reacting glass batch (melter feeds) floating on molten glass in an electric glass melter—couples heat transfer with the feed‐to‐glass conversion kinetics. The model allows for determining the distributions of temperature and various properties within the cold cap. In the present study, this model is applied to four melter feeds designed for high‐level and low‐activity nuclear wastes. Profiles of temperature, conversion degree, cold cap porosity and density, condensed matter velocity, and heating rate were determined using the material properties of the cold cap. Effects of vigorous foaming at the cold cap bottom were considered. Density, thermal conductivity, and glass production rate strongly affect the cold cap thickness and the fraction of undissolved silica entering the melt under the cold cap. The heating rate profile in the cold cap is highly nonlinear, with high heating rates observed in the foam layer.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1985

Effect of measured material properties on the finite element analysis of an OH-58 composite tail boom

A static and dynamic finite element analysis is conducted on a U.S. Army OH-58 composite tail boom and compared with test data. The tail boom is a filament-wound graphite/epoxy monocoque structure. The structural design of the composite tail boom skin is based on 50-percent graphite fiber volume. However, material tests on representative samples of the tail boom skin reveal that the graphite fiber-volume fraction varied from 44.6 to 49.3 percent. To determine the effect of using measured material properties, static and dynamic finite element analyses are conducted for three fiber-volume conditions of 45, 48, and 50 percent. The static and dynamic model with the 45-percent fiber-volume graphite skins gives the closest agreement with test data.

Bowman, L. M.↗
NASA NTRS2002

Decreases in bone blood flow and bone material properties in aging Fischer-344 rats

The purpose of this study was to quantify precisely aging-induced changes in skeletal perfusion and bone mechanical properties in a small rodent model. Blood flow was measured in conscious juvenile (2 months old), adult (6 months old), and aged (24 months old) male Fischer-344 rats using radiolabeled microspheres. There were no significant differences in bone perfusion rate or vascular resistance between juvenile and adult rats. However, blood flow was lower in aged versus adult rats in the forelimb bones, scapulas, and femurs. To test for functional effects of this decline in blood flow, bone mineral density and mechanical properties were measured in rats from these two age groups. Bone mineral density and cross-sectional moment of inertia in femoral and tibial shafts and the femoral neck were significantly larger in the aged versus adult rats, resulting in increased (+14%-53%) breaking strength and stiffness. However, intrinsic material properties at midshaft of the long bones were 12% to 25% lower in the aged rats. Although these data are consistent with a potential link between decreased perfusion and focal alterations in bone remodeling activity related to clinically relevant bone loss, additional studies are required to establish the mechanisms for this putative relationship.

Non-NASA Center↗
DOE OSTI2020

In situ observation of short- and long-timescale material property evolution under extreme conditions

Directly observing the evolution of material performance in-situ under extreme conditions remains a great challenge. Emergent behavior, such as the transition from incubation to steady state void swelling, is often difficult to capture in these conditions. To fill this gap, transient grating spectroscopy (TGS) has been used to collect multi-property information in-situ under high temperature exposure to ion beam irradiation. This all-optical method returns elastic and thermal transport properties with second-scale time resolution. Here, recent work using this methodology to track the evolution of Ni-based solid-solution alloys using the in situ ion irradiation TGS (I3TGS) beamline will be described. Tracking material property evolution during long exposure times (hours) provides a clear indication of when void swelling has occurred. On short timescales (seconds to minutes), observing rapid changes in thermoelastic properties as defect generation is initiated allows a unique window into bulk transient defect populations which are otherwise difficult to observe.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Finite Element Modeling of Diffusion in Fractured Porous Media by Using Hierarchical Material Properties

Abstract Fractured porous media challenge modeling approaches due to high computational costs and excessive mesh refinement imposed by the extreme scale variability of fractures and the heterogeneity of the surrounding porous rock. To overcome such difficulties, we utilize the hierarchical finite element method ( Hi ‐FEM) that has been developed previously to simulate the electrical potential distribution in complex geologic environments. The method employs the hierarchical basis functions in classical finite element analysis to enable representation of material properties on each dimensional component of a given 3D unstructured finite element, thereby inherently allowing for interactions at the boundary between fracture and a host rock. In this study, we extend its application to transient fluid flow and heat conduction in the Laplace domain. Time‐domain flow solutions are obtained by numerical inverse Laplace transform. We evaluate the accuracy of the method using different flow models and demonstrate its robustness for large‐scale, rock mass models featuring complex fracture networks. Moreover, for the computation of nodal Darcian velocity fields in fractured porous media where the fractures are represented as 2D features, a new approach that employs the Yeh's Galerkin model for both volume and facet elements is proposed. Results show that Hi ‐FEM can produce accurate flow solutions for fractured porous media without any need of coupling or transfer mechanism while still being computationally economical and numerically robust, even for large‐scale simulations.

Beskardes, G. D.↗
DOE OSTI2024

Modeling the Impacts of Material Properties on Oscillatory Neuron Behavior

In this study, neuromorphic computing, which mimics the functions of biological brains, offers improvements in both latency and energy efficiency over typical von Neumann computing architectures. Spiking neural networks can be especially power-efficient because they encode information temporally and can use more sparse electrical inputs. Here, we study the design of volatile memristors (variable resistors with memory) for neuronal devices, with particular consideration toward the feasibility of all-on-chip oscillation using built-in capacitance. We use circuit simulations to model the behavior of oscillator neurons with a range of realistic material properties. We find that energy inputs increase with insulating-phase resistivity, thermal conductivity, and device aspect ratio. However, we also find that the minimum capacitance needed for oscillation decreases with increasing insulating-phase resistivity, which opposes the constraints for power efficiency. Based on published data on NbO 2 , VO 2 , and EuNiO 3 , we find that existing materials can be engineered for all-on-chip spiking using their parasitic capacitance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Dimorphos’s Material Properties and Estimates of Crater Size from the DART Impact

On 2022 September 26, the Double Asteroid Redirection Test (DART) spacecraft intentionally collided with Dimorphos, the moon of the binary asteroid system 65803 Didymos. This collision provided the first full-scale test of a kinetic impactor for planetary defense. Images from DART’s DRACO camera revealed Dimorphos to be an oblate spheroid covered in boulders of varying sizes and shapes. Very little was known about Dimorphos prior to DART’s impact, including its shape, structure, and material properties. Approach observations and those following the DART impact have provided crucial knowledge that narrows the parameter space relevant to modeling the impact into Dimorphos. Here we present the results of a suite of hydrocode simulations of the DART impact on Dimorphos. Despite remaining uncertainties, initial models of DART’s kinetic impact provide important information about the results of DART (e.g., potential crater size and morphology, ejecta mass) and the properties of Dimorphos. Simulations here suggest that Dimorphos has near-surface strength ranging from a few Pascals to tens of kPa, which corresponds to crater sizes of ~40–60 m. Simulated crater sizes provide a crucial comparison metric for the European Space Agency Hera mission when it arrives at the Didymos system. Hera’s measurement of crater size in combination with measurement of Dimorphos’s mass will allow us to assess our simulations and provide the information needed to make the DART impact experiment both the first test of a planetary defense mitigation mission and the first full-scale planetary defense simulation validation exercise.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Ultrasonic Characterization of Spatially Varying Material Properties in Metal Components Fabricated by Additive Manufacturing

We investigated the sensitivity of ultrasonic measurements to changes in the operating conditions during additive fabrication for 316L stainless steel samples by selective laser melting. We found that the velocity of the ultrasound propagation positively correlates with the energy density used to melt layers of metal powder during the fabrication. In the range of the investigated conditions, the faster ultrasonic propagation, observed with the increase in the energy density, was shown to correspond to the improved hardness and the modulus of 316L stainless steel. Overall, our results indicate the feasibility of ultrasonic characterization of heterogeneities in the material properties of metal components produced by additive manufacturing.

Walton, Kenneth↗
DOE OSTI2022

Physics-informed neural networks for identification of material properties using standing waves

A metallic structure in its initial stage of failure involves plastic deformation or environmental degradation that changes the elastic modulus and density. This work presents the detection of change in wave velocity (a function of elastic modulus and density) as a system identification problem. A physics-informed neural network (PINN) is proposed to solve the system identification problem. The PINN takes the spatial coordinates of scanning locations and time as inputs and provides the displacement and wave velocity as outputs. The governing partial differential equation of standing waves in a rod is incorporated into the neural network as physics in the form of a loss function. The wave velocity vector is randomly initiated. During the training of the network, physics is used to determine and update the wave velocity target vector from the network’s displacement predictions. The measured data, comprising sparse displacement response on the rod structure, are used to train the PINN. The wave velocity at the sparse locations on the rod is learned from the predicted displacements during the training. Using the predictions of the trained network, the response of free vibration or material property variation can be reconstructed at unscanned locations on the structure to obtain high-resolution maps for full-field imaging to detect and localize the changes caused by plastic deformation. The PINN’s sparse scanning and simultaneous prediction capability during training can lead to high scanning and data-processing speeds. This capability yields a nondestructive evaluation system that can predict the presence of degraded material locations as the structural vibrations are scanned and processed in real time.

Rathod, Vivek↗
NASA NTRS2000

Correlation Between Material Properties of Ferroelectric Thin Films and Design Parameters for Microwave Device Applications: Modeling Examples and Experimental Verification

The application of thin ferroelectric films for frequency and phase agile components is the topic of interest of many research groups worldwide. Consequently, proof-of-concepts (POC) of different tunable microwave components using either (HTS, metal)/ferroelectric thin film/dielectric heterostructures or (thick, thin) film "flip-chip" technology have been reported. Either as ferroelectric thin film characterization tools or from the point of view of circuit implementation approach, both configurations have their respective advantages and limitations. However, we believe that because of the progress made so far using the heterostructure (i.e., multilayer) approach, and due to its intrinsic features such as planar configuration and monolithic integration, a study on the correlation of circuit geometry aspects and ferroelectric material properties could accelerate the insertion of this technology into working systems. In this paper, we will discuss our study performed on circuits based on microstrip lines at frequencies above 10 GHz, where the multilayer configuration offers greater ease of insertion due to circuit's size reduction. Modeled results of relevant circuit parameters such as the characteristic impedance, effective dielectric constant, and attenuation as a function of ferroelectric film's dielectric constant, tans, and thickness, will be presented for SrTiO3 and Ba(x)Sr(1-x)TiO3 ferroelectric films. A comparison between the modeled and experimental data for some of these parameters will be presented.

Miranda, Felix A.↗