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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Obstetrical Forceps Would Limit Force On An Infant's Head

Improved obstetrical forceps proposed to reduce injuries to newborn infants. Fabricated mostly of thermoplastic material. Reinforcing fibers added in hinge region of forceps. Combination of material, size, and shape chosen to make forceps yield elastically by amount keeping applied force from rising beyond maximum allowable value. Fiber-optic sensors for measuring strains embedded in forceps. Strain measurements used to compute tensile and compressive forces applied to infant's head.

Smeltzer, Stan↗
NASA NTRS1995

Micromechanical models for textile structural composites

The objective is to develop micromechanical models for predicting the stiffness and strength properties of textile composite materials. Two models are presented to predict the homogeneous elastic constants and coefficients of thermal expansion of a textile composite. The first model is based on rigorous finite element analysis of the textile composite unit-cell. Periodic boundary conditions are enforced between opposite faces of the unit-cell to simulate deformations accurately. The second model implements the selective averaging method (SAM), which is based on a judicious combination of stiffness and compliance averaging. For thin textile composites, both models can predict the plate stiffness coefficients and plate thermal coefficients. The finite element procedure is extended to compute the thermal residual microstresses, and to estimate the initial failure envelope for textile composites.

Marrey, Ramesh V.↗
NASA NTRS2012

A Probabilistic Mass Estimation Algorithm for a Novel 7- Channel Capacitive Sample Verification Sensor

A document describes an algorithm created to estimate the mass placed on a sample verification sensor (SVS) designed for lunar or planetary robotic sample return missions. A novel SVS measures the capacitance between a rigid bottom plate and an elastic top membrane in seven locations. As additional sample material (soil and/or small rocks) is placed on the top membrane, the deformation of the membrane increases the capacitance. The mass estimation algorithm addresses both the calibration of each SVS channel, and also addresses how to combine the capacitances read from each of the seven channels into a single mass estimate. The probabilistic approach combines the channels according to the variance observed during the training phase, and provides not only the mass estimate, but also a value for the certainty of the estimate. SVS capacitance data is collected for known masses under a wide variety of possible loading scenarios, though in all cases, the distribution of sample within the canister is expected to be approximately uniform. A capacitance-vs-mass curve is fitted to this data, and is subsequently used to determine the mass estimate for the single channel s capacitance reading during the measurement phase. This results in seven different mass estimates, one for each SVS channel. Moreover, the variance of the calibration data is used to place a Gaussian probability distribution function (pdf) around this mass estimate. To blend these seven estimates, the seven pdfs are combined into a single Gaussian distribution function, providing the final mean and variance of the estimate. This blending technique essentially takes the final estimate as an average of the estimates of the seven channels, weighted by the inverse of the channel s variance.

Wolf, Michael↗
NASA NTRS2010

Mechanics of Re-Torquing in Bolted Flange Connections

It has been widely accepted that the phenomenon of time-dependent loosening of flange connections is a strong consequence of the viscous nature of the compression seal material. Characterizing the coupled interaction between gasket creep and elastic bolt stiffness has been useful in predicting conditions that facilitate leakage. Prior advances on this sub-class of bolted joints has lead to the development of (1) constitutive models for elastomerics, (2) initial tightening strategies, (3) etc. The effect of re-torque, which is a major consideration for typical bolted flange seals used on the Space Shuttle fleet, has not been fully characterized, however. The current study presents a systematic approach to characterizing bolted joint behavior as the consequence of sequentially applied torques. Based on exprimenta1 and numerical results, the optimal re-torquing parameters have been identified that allow for the negligible load loss after pre-load application

Gordon, Ali P.↗
NASA NTRS2018

New Levels of High Angular Resolution EBSD Performance via Inverse Compositional Gauss-Newton Digital Image Correlation

Conventional high angular resolution electron backscatter diffraction (HREBSD) uses cross-correlation to track features between diffraction patterns, which are then related to the relative elastic strain and misorientation between the diffracting volumes of material. This paper adapts inverse compositional Gauss Newton (ICGN) digital image correlation (DIC) to be compatible with HREBSD. ICGN works by efficiently tracking not just the shift in features, but also the change in their shape. Modeling a shape change as well as a shift results in greater accuracy. This method, ICGN HREBSD, is applied to a simulated data set, and its performance is compared to conventional cross-correlation HREBSD, and cross-correlation HREBSD with remapping. ICGN HREBSD is shown to have about half the strain error of the best cross-correlation method with a comparable computation time.

T. J. Ruggles↗
NASA NTRS2023

Shock- and Corrosion-Resistant Bearings for Space Mechanisms

Nickel-titanium (NiTi) alloys are an emerging class of materials for rolling element bearing applications that require superior corrosion resistance and/or high load capability. Certain space mechanisms fall into one or both of those categories. Often, due to size and mass considerations, space mechanism systems are limited in torque margin and necessarily require small, precision-instrument bearings with very little frictional drag (i.e., low torque). In addition, space mechanism bearings must survive launch conditions without suffering raceway dents known as brinnelling, which would increase operating torque and reduce overall smoothness. Consequently, a bearing material or design that reduces or eliminates brinnelling under high contact stress conditions would represent a beneficial technology advancement. One specific alloy, nickel-titanium-hafnium (NiTi-Hf), under development for several years at the NASA Glenn Research Center as a bearing material, has the potential to mitigate concerns about brinnelling under extreme load conditions due to its unusually high elastic strain capability. In the present work, a sample of small precision bearings produced with three different ball materials (steel, ceramic, and NiTi-Hf) is subjected to a range of load conditions sufficient to dent the races. The dent depth as a function of load is compared and demonstrates that NiTi-Hf has the potential to increase bearing load capacity from the perspective of brinnelling under severe load conditions; additional testing of full NiTi-Hf bearings demonstrates corrosion resistance superior to that of 440C bearings.

Bearings↗
DOE OSTI2022

Mechanical Characterization of Loblolly Pine

Biorefineries are faced with various material flow challenges during feeding and handling, due to inherent variability and inhomogeneity of biomass feedstocks. This impacts the efficiency of refinery processes and unit operations. Proper characterization of bulk properties allows for optimal process design and reduction of overall costs. This work is aimed at evaluating the physical and mechanical properties that impact bulk flow of loblolly pine. Cyclic axial compression tests are performed to elucidate consolidation behavior under different stress conditions. The results are then used to develop correlations between material parameters (particle size, tissue type, moisture content) and Elastic Modulus of bulk samples.

09 BIOMASS FUELS↗
DOE OSTI2025

Ultrasonic characterization of material heterogeneities in stainless steel components produced by laser powder bed fusion

We introduce pulse-echo ultrasound as a method for characterizing the impact of powder bed fusion parameters on the properties of additively manufactured stainless-steel components, their material anisotropy, and location-dependent heterogeneity. Our results indicate that accurate characterization requires careful selection of ultrasonic propagation paths, which must consider the direction of additive layering, variations in processing parameters, and the component's geometry. We employed two distinct methods to estimate material properties from ultrasonic data: One assumes isotropy, while the other accounts for anisotropic interactions during the propagation of elastic waves. When applied to samples fabricated with laser energy densities ranging from 24 to 42 J/mm³ , these methods revealed transverse isotropy and weak anisotropy (quantified by small Thomsen parameters, ε = 0.0651 and γ = 0.0092) and less than a ∼6 % change in acoustic impedance. The assumption of isotropy, in this case, leads to small errors (less than 4 % or 1 % for Young's modulus in the build or transverse directions) when estimating orthotropic material properties using ultrasonic data measured along just two orthogonal directions, one of which must align with the build direction. By comparing ultrasonic measurements — which aggregate the spatial variability in material properties along the length of elastic wave propagation into a single value — with localized measurements obtained from surface nanoindentation, we uncovered and spatially profiled significant differences between the surface and interior properties. Specifically, the surface Young's modulus decreased from approximately 210 GPa to 180 GPa within a depth of about 3 mm. We attribute this surface-localized heterogeneity in PBF-fabricated components to distinct thermal histories experienced by the surface and interior regions. Collectively, the results of this study establish a framework for the ultrasonic characterization of material heterogeneity and anisotropy in material properties and demonstrate its application in additively manufactured metal components.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Low-frequency Raman spectrum of 2D layered perovskites: Local atomistic motion or superlattice modes?

We report the low-frequency Raman spectrum (ω = 10 cm -1 –150 cm -1 ) of a wide variety of alkylammonium iodide based 2D lead halide perovskites (2D LHPs) as a function of A-site cation (MA = methylammonium and FA = formamidinium), octahedral layer thickness (n = 2–4), organic spacer chain length (butyl-, pentyl-, hexyl-), and sample temperature (T = 77 K–293 K). Using density functional theory calculations under the harmonic approximation for n = 2 BA:MAPbI, we assign several longitudinal/transverse optical phonon modes between 30 cm -1 and 100 cm -1 , the eigen displacements of which are analogous to that observed previously for octahedral twists/distortions in bulk MAPbI. Additionally, we propose an alternative assignment for low-frequency modes below this band (<30 cm -1 ) as zone-folded longitudinal acoustic phonons corresponding to the periodicity of the entire layered structure. Furthermore, we compare measured spectra to predictions of the Rytov elastic continuum model for zone-folded dispersion in layered structures. Our results are consistent across the various 2D LHPs studied herein, with energetic shifts of optical phonons corresponding to microscopic structural differences between materials and energetic shifts of acoustic phonons according to changes in the periodicity and elastic properties of the perovskite/organic subphases. This study highlights the importance of both the local atomic order and the superlattice structure on the vibrational properties of layered 2D materials.

2D materials↗
DOE OSTI2021

Elastic Wave Propagation in Curvilinear Coordinates with Mesh Refinement Interfaces by a Fourth Order Finite Difference Method

In this work, we develop a fourth order accurate finite difference method for the three dimensional elastic wave equation in isotropic media with the piecewise smooth material property. In our model, the material property can be discontinuous at curved interfaces. The governing equations are discretized in second order form on curvilinear meshes by using a fourth order finite difference operator satisfying a summation-by-parts property. The method is energy stable and high order accurate. The highlight is that mesh sizes can be chosen according to the velocity structure of the material so that computational efficiency is improved. At the mesh refinement interfaces with hanging nodes, physical interface conditions are imposed by using ghost points and interpolation. With a fourth order predictor-corrector time integrator, the fully discrete scheme is energy conserving. Numerical experiments are presented to verify the fourth order convergence rate and the energy conserving property.

58 GEOSCIENCES↗
DOE OSTI2022

Transition Metal Carbo-Chalcogenide “TMCC:” A New Family of 2D Materials

A new family of 2D transition metal carbo-chalcogenides (TMCCs) is reported, which can be considered a combination of two well-known families, TM carbides (MXenes) and TM dichalcogenides (TMDCs), at the atomic level. Single sheets are successfully obtained from multilayered Nb 2 S 2 C and Ta 2 S 2 C using electrochemical lithiation followed by sonication in water. The parent multilayered TMCCs are synthesized using a simple, scalable solid-state synthesis followed by a topochemical reaction. Superconductivity transition is observed at 7.55 K for Nb 2 S 2 C. The delaminated Nb 2 S 2 C outperforms both multilayered Nb 2 S 2 C and delaminated NbS 2 as an electrode material for Li-ion batteries. Ab initio calculations predict the elastic constant of TMCC to be over 50% higher than that of TMDC.

superconductors↗
DOE OSTI2023

Deep material network via a quilting strategy: visualization for explainability and recursive training for improved accuracy

Recent developments integrating micromechanics and neural networks offer promising paths for rapid predictions of the response of heterogeneous materials with similar accuracy as direct numerical simulations. The deep material network is one such approaches, featuring a multi-layer network and micromechanics building blocks trained on anisotropic linear elastic properties. Once trained, the network acts as a reduced-order model, which can extrapolate the material’s behavior to more general constitutive laws, including nonlinear behaviors, without the need to be retrained. However, current training methods initialize network parameters randomly, incurring inevitable training and calibration errors. Here, we introduce a way to visualize the network parameters as an analogous unit cell and use this visualization to “quilt” patches of shallower networks to initialize deeper networks for a recursive training strategy. The result is an improvement in the accuracy and calibration performance of the network and an intuitive visual representation of the network for better explainability.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1974

Investigation of Kevlar fabric based materials for use with inflatable structures

Design, manufacture and testing of laminated and coated composite materials incorporating a structural matrix of Kevlar are reported in detail. The practicality of using Kevlar in aerostat materials is demonstrated and data are provided on practical weaves, lamination and coating particulars, rigidity, strength, weight, elastic coefficients, abrasion resistance, crease effects, peel strength, blocking tendencies, helium permeability, and fabrication techniques. Properties of the Kevlar based materials are compared with conventional, Dacron reinforced counterparts. A comprehensive test and qualification program is discussed and quantitative biaxial tensile and shear test data are provided. The investigation shows that single ply laminates of Kevlar and plastic films offer significant strength to weight improvements, are less permeable than two ply coated materials, but have a lower flex life.

Niccum, R. J.↗
DOE OSTI2024

Assessment of effective elastic constants of U-10Mo fuel microstructures

Monolithic U-10Mo fuel undergoes significant microstructural changes during fuel burnup which degrades its mechanical properties. In this talk, we present results form a numerical method to assess the impact of the various microstructural features--grains, intragranular and intergranular Xe gas bubbles--on the elastic stiffness tensor. Using the Multiphysics Object-Oriented Simulation Environment (MOOSE), phase-field-based microstructures are combined with asymptotic expansion homogenization method to obtain effective elastic constants as a function of porosity and fission density. The results are verified and compared against analytical homogenization models. With this approach, elastic degradation in operating nuclear fuels can be quantified when the distributions of microstructural features are known from experimental characterization or rate-theory based models. We further develop an evolution model based on the virial equation of state for Xe gas and investigate the effect of growth and coalescence of the bubbles at the grain boundary faces and triple junctions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Antiferromagnetic real-space configuration probed by dichroism in scattered x-ray beams with orbital angular momentum

X-ray beams with orbital angular momentum (OAM) are a promising tool for x-ray characterization techniques. Beams with OAM have a helicity - an azimuthally varying phase - which leads to a gradient of the light field. New material properties can be probed by utilizing the helicity of an OAM beam. Here, we demonstrate a dichroic effect in resonant diffraction from an artificial antiferromagnet with a topological defect. We found that the scattered OAM beam has circular dichroism at the antiferromagnetic Bragg peak whose sign is coupled to its helicity, which reveals the real-space configuration of the antiferromagnetic ground state. Thermal cycling of the artificial antiferromagnet can change the ground state, as indicated by reversal of the sign of circular dichroism. This result is one of the first demonstrations of a soft x-ray spectroscopy characterization technique utilizing the OAM of x rays. In conclusion, this helicity-dependent circular dichroism exemplifies the potential to utilize OAM beams to probe matter in a way that is inaccessible using currently available x-ray techniques.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1980

Implementation of a trapezoidal ring element in NASTRAN for elastic-plastic analysis

The explicit expressions for an elastic-plastic trapezoidal ring element are presented and implemented in NASTRAN computer program. The material is assumed to obey the von Mises' yield criterion, isotropic hardening rule and the Prandtl-Reuss flow relations. For the purpose of demonstration, two elastic-plastic problems are solved and compared with previous results. The first is a plane-strain tube under uniform internal pressure and the second, a finite-length tube loaded over part of its inner surface. A very good agreement was found in both test problems.

Chen, P. C. T.↗
NASA NTRS1988

Constitutive modeling for isotropic materials

The third and fourth years of a 4-year research program, part of the NASA HOST Program, are described. The program goals were: (1) to develop and validate unified constitutive models for isotropic materials, and (2) to demonstrate their usefulness for structural analysis of hot section components of gas turbine engines. The unified models selected for development and evaluation were those of Bodner-Partom and of Walker. The unified approach for elastic-viscoplastic constitutive equations is a viable method for representing and predicting material response characteristics in the range where strain rate and temperature dependent inelastic deformations are experienced. This conclusion is reached by extensive comparison of model calculations against the experimental results of a test program of two high temperature Ni-base alloys, B1900+Hf and Mar-M247, over a wide temperature range for a variety of deformation and thermal histories including uniaxial, multiaxial, and thermomechanical loading paths. The applicability of the Bodner-Partom and the Walker models for structural applications has been demonstrated by implementing these models into the MARC finite element code and by performing a number of analyses including thermomechanical histories on components of hot sections of gas turbine engines and benchmark notch tensile specimens. The results of the 4-year program have been published in four annual reports. The results of the base program are summarized in this report. The tasks covered include: (1) development of material test procedures, (2) thermal history effects, and (3) verification of the constitutive model for an alternative material.

Chan, K. S.↗
DOE OSTI2024

Accelerating multiscale electronic stopping power predictions with time-dependent density functional theory and machine learning

Knowing the rate at which particle radiation releases energy in a material, the “stopping power,” is key to designing nuclear reactors, medical treatments, semiconductor and quantum materials, and many other technologies. While the nuclear contribution to stopping power, i.e., elastic scattering between atoms, is well understood in the literature, the route for gathering data on the electronic contribution has for decades remained costly and reliant on many simplifying assumptions, including that materials are isotropic. We establish a method that combines time-dependent density functional theory (TDDFT) and machine learning to reduce the time to assess new materials to hours on a supercomputer and provide valuable data on how atomic details influence electronic stopping. Our approach uses TDDFT to compute the electronic stopping from first principles in several directions and then machine learning to interpolate to other directions at a cost of 10 million times fewer core-hours. We demonstrate the combined approach in a study of proton irradiation in aluminum and employ it to predict how the depth of maximum energy deposition, the “Bragg Peak,” varies depending on the incident angle—a quantity otherwise inaccessible to modelers and far outside the scales of quantum mechanical simulations. The lack of any experimental information requirement makes our method applicable to most materials, and its speed makes it a prime candidate for enabling quantum-to-continuum models of radiation damage. The prospect of reusing valuable TDDFT data for training the model makes our approach appealing for applications in the age of materials data science.

36 MATERIALS SCIENCE↗