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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Analytic Thermoelectric Couple Modeling: Variable Material Properties and Transient Operation

To gain a deeper understanding of the operation of a thermoelectric couple a set of analytic solutions have been derived for a variable material property couple and a transient couple. Using an analytic approach, as opposed to commonly used numerical techniques, results in a set of useful design guidelines. These guidelines can serve as useful starting conditions for further numerical studies, or can serve as design rules for lab built couples. The analytic modeling considers two cases and accounts for 1) material properties which vary with temperature and 2) transient operation of a couple. The variable material property case was handled by means of an asymptotic expansion, which allows for insight into the influence of temperature dependence on different material properties. The variable property work demonstrated the important fact that materials with identical average Figure of Merits can lead to different conversion efficiencies due to temperature dependence of the properties. The transient couple was investigated through a Greens function approach; several transient boundary conditions were investigated. The transient work introduces several new design considerations which are not captured by the classic steady state analysis. The work helps to assist in designing couples for optimal performance, and also helps assist in material selection.

Seebeck Effect↗
NASA NTRS1972

Material variability as measured by low temperature electrical resistivity.

Low temperature electrical resistivity was used to determine the material variability (1) between different manufacturers, (2) between different heats from the same manufacturer, and (3) within a given heat for Al 2024, Al-5% Mg alloys, Inconel 718, A286 stainless, and AISI 316. Generally, the coefficient of variation for solution annealed alloys ranged from 1.2 to 14% between manufacturers, 0.8 to 5.1% between heats, and 0.1 to 1.6% within a heat with stainless steels at the low ends and Al 2024 at the high ends. The variability is increased if the material is in a precipitation-hardened condition. A statistical analysis suggests that the variability within a heat is non-normal.

Clark, A. F.↗
DOE OSTI2020

Geometric and Material Variability Influences Stress States Relevant to Coastal Permafrost Bluff Failure

Scientific knowledge and engineering tools for predicting coastal erosion are largely confined to temperate climate zones that are dominated by non-cohesive sediments. The pattern of erosion exhibited by the ice-bonded permafrost bluffs in Arctic Alaska, however, is not well-explained by these tools. Investigation of the oceanographic, thermal, and mechanical processes that are relevant to permafrost bluff failure along Arctic coastlines is needed. We conducted physics-based numerical simulations of mechanical response that focus on the impact of geometric and material variability on permafrost bluff stress states for a coastal setting in Arctic Alaska that is prone to toppling mode block failure. Our three-dimensional geomechanical boundary-value problems output static realizations of compressive and tensile stresses. We use these results to quantify variability in the loci of potential instability. We observe that niche dimension affects the location and magnitude of the simulated maximum tensile stress more strongly than the bluff height, ice wedge polygon size, ice wedge geometry, bulk density, Young's Modulus, and Poisson's Ratio. Our simulations indicate that variations in niche dimension can produce radically different potential failure areas and that even relatively shallow vertical cracks can concentrate displacement within ice-bonded permafrost bluffs. These findings suggest that stability assessment approaches, for which the geometry of the failure plane is delineated a priori, may not be ideal for coastlines similar to our study area and could hamper predictions of erosion rates and nearshore sediment/biogeochemical loading.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Material Variability Effects on Damage Development Within Composite Adhesively Bonded Joints

Use of composite adhesively bonded joints (ABJ) is of critical importance to the adoption of composite materials in the automotive industry, as ABJ enable lower stress concentrations as compared to conventional mechanically fastened joints. ABJ are better suited for joining composite materials as compared to fastened joints because fastened joints require drilling of holes which locally affect composite material structure. Composite materials and adhesives are subject to unavoidable stochastic local material variations which make different failure scenarios possible. An experimentally tested ABJ configuration is simulated using finite element analysis (FEA). Experimentally, under tension, the joints failed by three major failure modes, with peak loads ranging from 13.0-16.1 kips. Progressive failure analysis tools are used to simulate damage development within each material within the joint. The simulation agreed well with the average experimental peak load. Stochastically occurring adhesive porosity and matrix-fiber micro-disbonding were numerically simulated. The simulations revealed a similar trend as observed experimentally: joints which failed at higher peak loads had lower levels of damage within the face-sheets of the composite panels which were adhesively bonded; these joints which failed at higher peak loads also had greater damage in the doubler of the experimentally tested double lap joint configuration.

Richard Larson↗
NASA NTRS1989

Variable-Resistivity Material For Memory Circuits

Nonvolatile memory elements packed densely. Electrically-erasable, programmable, read-only memory matrices made with newly-synthesized organic material of variable electrical resistivity. Material, polypyrrole doped with tetracyanoquinhydrone (TCNQ), changes reversibly between insulating or higher-resistivity state and conducting or low-resistivity state. Thin film of conductive polymer separates layer of row conductors from layer of column conductors. Resistivity of film at each intersection and, therefore, resistance of memory element defined by row and column, increased or decreased by application of suitable switching voltage. Matrix circuits made with this material useful for experiments in associative electronic memories based on models of neural networks.

Nagasubramanian, Ganesan↗
DOE OSTI2020

Initial development of a high temperature life prediction method directly accounting for variability in material properties

This report presents the initial development of a life prediction method that accounts for the variability of the material properties in Grade 91 steel. We account for material variability by both fitting a variable 3-parameter Weibull distribution to the rupture data of the material and by quantifying the effect that the creep deformation properties have on stresses via a Monte Carlo approach. To ensure a reasonable time frame when applying Monte Carlo to the creep stress, we propose a methodology that models the material as an extremely viscous Stokes flow with a non-Newtonian viscosity, therefore solving the problem in a single step. We use the final probabilistic model for structural failure developed in this document to evaluate a Flat Head Vessel designed with the Section III, Division 5 ASME Boiler Pressure and Vessel Code rules with a 100,000h design life and assess its probability of premature failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

A remapping scheme for history-dependent material state variables

Here, we present an interpolation scheme for use with material models involving history-dependent state variables. The interpolation scheme is based on the solution of a constrained optimization problem, to identify the smoothest monotone curve which produces an admissible solution. Unlike classical schemes used for transport equations, the proposed methodology accounts for the interdependence of the history variables and produces admissible interpolations of the material's state variables. After introducing a general solution scheme for the problem, a simplified and more computationally efficient method is derived. Finally, as a validation problem for the proposed methods, we consider the advection of internal state variables belonging to material models with highly nonlinear yield surfaces.

42 ENGINEERING↗
NASA NTRS1988

Dynamic shear of granular material under variable gravity conditions

This paper describes some experiments with granular materials which recently have been conducted aboard the NASA KC-135 aircraft during variable gravity maneuvers. The main experimental apparatus consisted of a small drum containing granular material which was rotated slowly while the angle assumed by the slip surface with respect to the horizontal was observed and recorded photographically. Conventional wisdom has held that this 'dynamic angle of response' was a material constant, independent of (among other things) gravitational level. The results presented here are quite contrary, suggesting instead an angle that varies with the reciprocal of the square root of gravity. This finding may have important consequences on the understanding of many active processes in Planetary Geology involving granular materials and may provide qualitative confirmation of some of the theoretical predictions of modern models of granular shear flows.

White, B. R.↗
DOE OSTI2025

Correlating processing variables to material properties in recycled polypropylene: A data‐driven approach

Abstract Polypropylene (PP) is one of the most widely used plastics, yet its recycling remains limited, with less than 1% of solid waste PP being reprocessed. Mechanical recycling through extrusion is the most practical method, but inconsistent reprocessing conditions introduce variability in material properties. While temperature, screw speed, and residence time influence the thermomechanical stress applied during reprocessing, there are no standardized guidelines for optimizing these parameters. This study examines how these factors shape the properties of recycled PP, using conditions designed to mimic post‐industrial recycled (PIR) scrap. Residence time was measured using colorimetric tracking and correlated with molecular weight, viscosity, and mechanical properties over multiple extrusion cycles. Data‐driven modeling, including response surface methodology, support vector machines, and artificial neural networks, identified processing temperature as the dominant factor in material degradation, followed by residence time. Mechanical properties remained stable, while viscosity decreased predictably with increasing residence time. By linking reprocessing conditions to property evolution, this study provides a method to optimize processing parameters and reduce variability in recycled PP. These findings help manufacturers improve process control, making recycled PP more predictable for reuse in manufacturing. Highlights Study of PIR‐quality PP without additives or compatibilizers. Residence time analysis shows processing temperature drives PP property changes. Mark‐Houwink enables quick molecular weight checks for quality control. Models predict mechanical and rheological shifts in reprocessing. Optimized processing parameters minimize property degradation in recycling.

Estela‐García, John E. [Polymer Engineering Center↗
DOE OSTI2022

Descriptor Aided Bayesian Optimization for Many-Level Qualitative Variables With Materials Design Applications

Abstract Engineering design often involves qualitative and quantitative design variables, which requires systematic methods for the exploration of these mixed-variable design spaces. Expensive simulation techniques, such as those required to evaluate optimization objectives in materials design applications, constitute the main portion of the cost of the design process and underline the need for efficient search strategies—Bayesian optimization (BO) being one of the most widely adopted. Although recent developments in mixed-variable Bayesian optimization have shown promise, the effects of dimensionality of qualitative variables have not been well studied. High-dimensional qualitative variables, i.e., with many levels, impose a large design cost as they typically require a larger dataset to quantify the effect of each level on the optimization objective. We address this challenge by leveraging domain knowledge about underlying physical descriptors, which embody the physics of the underlying physical phenomena, to infer the effect of unobserved levels that have not been sampled yet. We show that physical descriptors can be intuitively embedded into the latent variable Gaussian process approach—a mixed-variable GP modeling technique—and used to selectively explore levels of qualitative variables in the Bayesian optimization framework. This physics-informed approach is particularly useful when one or more qualitative variables are high dimensional (many-level) and the modeling dataset is small, containing observations for only a subset of levels. Through a combination of mathematical test functions and materials design applications, our method is shown to be robust to certain types of incomplete domain knowledge and significantly reduces the design cost for problems with high-dimensional qualitative variables.

Engineering↗
DOE OSTI2023

Fabrication-conscious neural network based inverse design of single-material variable-index multilayer films

Multilayer films with continuously varying indices for each layer have attracted great deal of attention due to their superior optical, mechanical, and thermal properties. However, difficulties in fabrication have limited their application and study in scientific literature compared to multilayer films with fixed index layers. In this work we propose a neural network based inverse design technique enabled by a differentiable analytical solver for realistic design and fabrication of single material variable-index multilayer films. This approach generates multilayer films with excellent performance under ideal conditions. We furthermore address the issue of how to translate these ideal designs into practical useful devices which will naturally suffer from growth imperfections. By integrating simulated systematic and random errors just as a deposition tool would into the optimization process, we demonstrated that the same neural network that produced the ideal device can be retrained to produce designs compensating for systematic deposition errors. Furthermore, the proposed approach corrects for systematic errors even in the presence of random fabrication imperfections. The results outlined in this paper provide a practical and experimentally viable approach for the design of single material multilayer film stacks for an extremely wide variety of practical applications with high performance.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Understanding Material Strength Variabilities and Uncertainties for Component Qualification (2020 LDRD Final Report)

At its core, material specification and materials qualification require an understanding of the uncertainties in relation to a given performance metric. When simulations are used to inform the design and evaluation of these metrics, it is essential to understand the uncertainties in the underlying models and parameters that feed into those simulations. In this work, we have created a statistical framework to address uncertainties in the materials strength modeling used in integrated simulations. The framework is based on the Bayesian methodology, which allows for uncertainties to be updated as new data become available. The results of this work show how model parameters and their uncertainties can be updated as new and different types of strength data are added, as well as methods for determining which future experiment has the greatest potential to reduce the uncertainty. The statistical framework developed in this project will be utilized to assess and propagate the uncertainties in the strength models used in the programmatic simulations and to create a way to formally update those uncertainties as new data become available.

36 MATERIALS SCIENCE↗
NASA NTRS2004

Synthesis, Characterization, and Modeling of Nanotube Materials with Variable Stiffness Tethers

Synthesis, mechanical testing, and modeling have been performed for carbon nanotube based materials. Tests using nanoindentation indicated a six-fold enhancement in the storage modulus when comparing the base material (no nanotubes) to the composite that contained 5.3 wt% of nanotubes. To understand how crosslinking the nanotubes may further alter the stiffness, a model of the system was constructed using nanotubes crosslinked with a variable stiffness tether (VST). The model predicted that for a composite with 5 wt% nanotubes at random orientations, crosslinked with the VST, the bulk Young's modulus was reduced by 30% compared to the noncrosslinked equivalent.

Frankland, S. J. V.↗
DOE OSTI2021

A method for predicting failure statistics for steady state elevated temperature structural components

This paper presents the initial development of a high temperature life prediction method that accounts for the variability in the material properties of Grade 91 steel. The method accounts for material variability by fitting a variable 3-parameter Weibull distribution to experimental rupture data and accounts for the variability of creep deformation on the steady-state stresses via a Monte Carlo approach. To ensure reasonable computational times, the model represents the material as an extremely viscous Stokes fluid with a non-Newtonian viscosity, therefore solving the stress relaxation problem with a steady, static, instead of transient, analysis. Furthermore, the complete statistical analysis combines this model for creep deformation with a probabilistic model for creep rupture to evaluate the probability of premature failure for a set of sample problems, comparing the predicted failure statistics to the design life predicted by the ASME Boiler and Pressure Vessel Code rules.

42 ENGINEERING↗
NASA NTRS2004

Cross-Linked Nanotube Materials with Variable Stiffness Tethers

The constitutive properties of a cross-linked single-walled carbon nanotube material are predicted with a multi-scale model. The material is modeled as a transversely isotropic solid using concepts from equivalent-continuum modeling. The elastic constants are determined using molecular dynamics simulation. Some parameters of the molecular force field are determined specifically for the cross-linker from ab initio calculations. A demonstration of how the cross-linked nanotubes may affect the properties of a nanotube/polyimide composite is included using a micromechanical analysis.

Frankland, Sarah-Jane V.↗
DOE OSTI2025

Compact in situ probe for magnetotransport measurements of 2D materials under variable tensile strain

The recent development of freestanding oxide membranes has opened new opportunities for strain engineering of transition metal oxides beyond values accessible in bulk samples. While a number of studies have been performed with fixed strain, the ability to dynamically control the strain state during measurement would be greatly enabling. To this end, we present an in situ uniaxial strain probe optimized for transport measurements of tensile-strained 2D or quasi-2D materials down to 2 K. Utilizing a flexible polyimide substrate as the stress transfer medium, our platform simplifies the sample preparation process and allows precise alignment of strain fields relative to the crystalline axes. An in situ optical microscope monitors the macroscopic strain state operando and makes it possible to complete an entire magnetotransport study at cryogenic temperatures under continuous strain variations. We demonstrate the capabilities of the probe on a freestanding LaNiO 3 membrane, where we induce tensile strain up to 8% and observe a corresponding strong transport anisotropy. In view of the rapid developments in low-dimensional materials synthesis and the plethora of novel quantum phenomena they exhibit, this strain probe provides general instrumentation for examining and controlling these properties via strain.

2D materials↗
DOE OSTI2020

A thermodynamics-based damage model for the non-linear mechanical behavior of SiC/SiC ceramic matrix composites in irradiation and thermal environments

A damage model is developed and validated with experimental data for the non-linear mechanical behavior of SiC/SiC composite materials in nuclear applications. Cyclic thermal and mechanical loading associated with neutron irradiation effects of these composites leads to wide-spread and progressive micro-cracking that leads to loss of thermal conductivity and further enhancement of thermo-mechanical damage. A physics-based model of wide-spread micro-cracking is developed within the thermodynamic framework of continuum damage mechanics. Evolution equations for damage parameters that describe the growth of continuum damage are developed, where the material variables are obtained from experiments. The model novelty is in coupling mechanical, thermal, and irradiation damage through a consistent thermodynamic framework, including loss of thermal conductivity due to the evolution of mechanically induced micro-cracks. A number of thermo-mechanical experiments were conducted to confirm model assumptions. The model is shown to be validated with out-of-pile experiments, and then implemented using commercial finite element code COMSOL to the fuel cladding problem with normal and high radiation dose cases.

Materials Science↗