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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Toxicity of Pyrolysis Gases from Elastomers

The toxicity of the pyrolysis gases from six elastomers was investigated. The elastomers were polyisoprene (natural rubber), styrene-butadiene rubber (SBR), ethylene propylene diene terpolymer (EPDM), acrylonitrile rubber, chlorosulfonated polyethylene rubber, and polychloroprene. The rising temperature and fixed temperature programs produced exactly the same rank order of materials based on time to death. Acryltonitrile rubber exhibited the greatest toxicity under these test conditions; carbon monoxide was not found in sufficient concentrations to be the primary cause of death.

Hilado, Carlos J.↗
NASA NTRS1982

Photothermal characterization of encapsulant materials for photovoltaic modules

A photothermal test matrix and a low cost testing apparatus for encapsulant materials of photovoltaic modules were defined. Photothermal studies were conducted to screen and rank existing as well as future encapsulant candidate materials and/or material formulations in terms of their long term physiochemical stability under accelerated photothermal aging conditions. Photothermal characterization of six candidate pottant materials and six candidate outer cover materials were carried out. Principal products of photothermal degradation are identified. Certain critical properties are also monitored as a function of photothermal aging.

Liang, R. H.↗
NASA NTRS1988

ASTM Committee G-4 metals flammability test program - Data and discussion

Results of metals flammability tests performed on twenty-six metals in the NASA/White Sands Test Facility are discussed together with the test systems. The promoted combustion and ignition characteristics of these metals are described, and the metals are ranked according to their suitability for use in oxygen systems. In general, alloys with high copper and nickel contents and low iron content were found to rank higher than those that had high iron content, while alloys that had high aluminum content were ranked the lowest.

Stoltzfus, Joel M.↗
NASA NTRSDate not supplied

Thermal, Structural, and Rotordynamics Refinements to the Superconducting Rotor of A 1.4 Mw Partially Superconducting Machine for Electrified Aircraft

NASA is developing the high efficiency megawatt motor (HEMM), a 1.4 MW partially superconducting machine, to ad-dress the need for highly efficient, lightweight, MW-class ma-chines to support aviation sustainability efforts. This paper presents progress on the thermal, structural, and rotordynamics aspects of HEMM’s superconducting rotor. Emissivity measurements of gold coated cobalt iron and titanium parts are presented and then used to correlate a thermal model of the rotor to existing data from a thermo-electrical test of the full-scale rotor. Lessons learned from the correlated model are presented, including a rank ordering of the contributors to the temperature of the superconducting coils. An updated structural design of the HEMM rotor is presented and compared to the prior design. Finite element analysis demonstrates that the updated design improves stress margins while reducing magnetic flux leakage and retaining thermal performance. The key conclusions of the rotordynamics design are presented.

electrified aircraft propulsion↗
DOE OSTI2026

matsim-agents v1.0

matsim-agents is a multi-agent AI framework for atomistic materials simulation and discovery. It orchestrates large language models (LLMs), machine-learned interatomic potentials (MLIPs), and DFT codes into a single agentic loop running on laptops and DOE leadership-class supercomputers. MULTI-AGENT ORCHESTRATION A LangGraph state machine with three nodes: a Planner that converts a natural-language research objective into structured tasks; an Executor that dispatches atomistic tools and loops until the queue is empty; and an Analyst that summarizes results into a human-readable report. State is checkpointed after every step and human-in-the-loop gates can be inserted at any edge. HYPOTHESIS-DRIVEN DISCOVERY CHAT An interactive REPL (matsim-agents chat) that couples LLM dialogue with atomistic simulation. Chemical formulas are automatically detected in conversation turns and trigger a full crystal-phase exploration: structure generation → relaxation → stability scoring → result injection back into the conversation, creating a closed hypothesis-refinement loop. CRYSTAL PHASE ENUMERATION Given a composition, the phase explorer enumerates prototypes by stoichiometry: elemental (fcc/bcc/hcp/sc/diamond), binary 1:1 (rocksalt/CsCl/zincblende/ wurtzite/fluorite/rutile), ternary 1:1:3 (cubic perovskite), ternary 1:2:4 (perovskite + spinel), quaternary 1:1:2:6 (Fm-3m double perovskite). 2-D prototypes (graphene, h-BN, MoS2 2H/1T) and multilayer stacking are also supported via --include-2d and --num-layers. SUPERCELL GENERATION AND SITE DECORATION Auto-tiling to a minimum atom count (--min-atoms), explicit NxNxN tiling (--supercell), symmetry-distinct site decorations (--n-orderings), and isotropic lattice-scale sweeps (--lattice-scales) for volume bracketing. MLFF RELAXATION AND STABILITY SCORING HydraGNN (multi-headed GNN) drives structure relaxation via ASE with FIRE, BFGS, or BFGSLineSearch. Stability output: delta-E/atom ranking across phases and a max-residual-force dynamical-stability proxy. Other MLIPs (MACE, NequIP, Orb) can be plugged in through the same interface. DFT BACKENDS Quantum ESPRESSO pw.x and VASP 6.6 are first-class labellers. Both have validated GPU builds and SLURM/PBS launchers for three DOE platforms: Frontier (AMD MI250X, ROCm), Aurora (Intel PVC, oneAPI), Perlmutter (NVIDIA A100, CUDA). QE produces ~100 binaries (pw.x, ph.x, epw.x, ...). VASP supports scf, relax, vc-relax, and vc-relax-shape run types. ACTIVE-LEARNING LOOP matsim-agents al run CONFIG.yaml drives an iterative HydraGNN-DFT loop: MD generates candidates → ensemble/MC-dropout uncertainty selects the most informative → DFT labels them in parallel inside one allocation → dataset grows → HydraGNN retrains → repeat. DFT backend is a single YAML toggle (dft.backend: vasp | qe). LLM-generated seed structures are supported (no curated POSCAR library needed). Config uses ${VAR}, ${VAR:-default}, ${VAR:?msg} shell-style substitution for cross-user/cross-site portability. LLM BACKENDS Ollama (local, default), vLLM (HPC multi-GPU serving), OpenAI, Anthropic, HuggingFace Transformers+Accelerate. Selected at runtime via flag or env var with no code changes. HPC PORTABILITY Same Python entry points run on Frontier (ROCm 7.2), Aurora (oneAPI), and Perlmutter (CUDA 12). DFT and ML stacks are never co-loaded in the same shell; they couple through the scheduler and filesystem. Advanced multi-node launchers (serve, discovery-chat, single-relaxation, active-learning, QE warm-start) are provided for all three platforms. CODABENCH COMPETITION BUNDLE A self-contained benchmark: 159 atomistic test structures across 11 material classes, 5 tasks (formation energy, forces, ML relaxation, AI-DFT relaxation, phase stability ranking), public/private leaderboard split (30/70), and four ready-to-run baselines: MACE-MP-0, HydraGNN, UMA, AllScAIP.

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗
NASA NTRS1984

Selection of burn-resistant materials for oxygen-driven turbopumps

NASA goals for reusable space-based, high-performance orbit transfer vehicle propulsion systems have resulted in a need for oxygen/hydrogen engines which include lightweight, highly reliable, liquid oxygen pumps. The selection of ignition- and burn-resistant materials is a major factor in the design of a compact 75,000-rpm turbopump which can deliver 6 lbM/sec of liquid oxygen at 5,000 psia. The potential operational hazards of rubbing friction and impact of foreign particles at high velocity were investigated experimentally for a wide range of candidate materials, i.e., nickel, copper, monel, 316 Stainless Steel, Hastelloy-X, Invar-36, and silicon carbide. Test parameters included oxygen pressure and temperature up to 5,000 psia and 800 F, respectively. The effect of increasing the O2 pressure from 1000 to 5000 psi is discussed. The applicability of the candidate materials to oxygen pump design was ranked by comparing the experimental results among themselves and with an analytically determined parameter, i.e., the burn factor. Nickel and copper demonstrated superior resistance to ignition and burn in the friction rubbing and particle impact tests relative to monel, stainless steel, and nickel-iron base superalloys.

Schoenman, L.↗
NASA NTRS2001

Characterization of a Laminate Flat Plate Diffusion Flame in Microgravity using PIV, Visible and CH Emissions

Motivated by fire safety concerns and the advent of long-term micro-gravity facilities, a cooperative program has been developed to study the mechanisms and material properties that control flow assisted (co-current) flame spread. This program has used as a common fire scenario a reacting steady-state boundary layer. Preliminary studies explored the aerodynamics of a reacting boundary layer by simulating a condensed fuel by means of a gas burner. Stability curves for ethane air flames were obtained and different burning regimes were identified. An important feature of this study was the independent identification of the different mechanisms leading to the instability of the flow. It was observed that fuel injection velocity and thermal expansion independently contributed to the separation of the flow at the leading edge of the burner. The occurrence of separation resulted in complex three-dimensional flow patterns that have a dominant effect on critical fire safety parameters such as the stand-off distance and flame length. This work was extended to a solid fuel (PMMA) leading to a Sounding Rocket experiment (Mini-Texus-6). The solid phase showed similar flow patterns, mostly present at low flow velocities (<100 mm/s) but the results clearly demonstrated that the thermal balance at the pyrolyzing fuel surface is the dominant mechanism that controls both stand-off distance and flame length. This thermal balance could be described in a global manner by means of a total mass transfer or "B" number. This "B" number incorporates surface re-radiation, radiative feedback and in-depth heat conduction as first prescribed by Emmons. The mass transfer number becomes the single parameter that determines the evolution of these fire safety variables (flame length, stand-off distance) and therefore can be used as a ranking criterion to assess the flammability of materials. The particular configuration is representative of the NASA upward flame spread test (Test 1) therefore this approach can be used in the interpretation of the results obtained from this test. Nevertheless, complete validation of this approach has not been fully achieved due, mainly because all the measurements necessary to compare with the theoretical predictions have not been obtained. Following these studies two different directions have been taken. The first attempts to elucidate the details of the gas phase combustion reaction and the associated flow field by means of quantitative and qualitative measurements. The second approach, a more practical one, is to apply this methodology to the assessment of material flammability. The former is currently being conducted with a gas burner because it allows for easier control and longer experimentation time. The results obtained so far will be presented in more detail. The latter is a new program therefore only a brief summary of the objectives will be presented.

Joulain, P.↗
NASA NTRS2004

Statistical Analysis of CMC Constituent and Processing Data

Ceramic Matrix Composites (CMCs) are the next "big thing" in high-temperature structural materials. In the case of jet engines, it is widely believed that the metallic superalloys currently being utilized for hot structures (combustors, shrouds, turbine vanes and blades) are nearing their potential limits of improvement. In order to allow for increased turbine temperatures to increase engine efficiency, material scientists have begun looking toward advanced CMCs and SiC/SiC composites in particular. Ceramic composites provide greater strength-to-weight ratios at higher temperatures than metallic alloys, but at the same time require greater challenges in micro-structural optimization that in turn increases the cost of the material as well as increases the risk of variability in the material s thermo-structural behavior. to model various potential CMC engine materials and examines the current variability in these properties due to variability in component processing conditions and constituent materials; then, to see how processing and constituent variations effect key strength, stiffness, and thermal properties of the finished components. Basically, this means trying to model variations in the component s behavior by knowing what went into creating it. inter-phase and manufactured by chemical vapor infiltration (CVI) and melt infiltration (MI) were considered. Examinations of: (1) the percent constituents by volume, (2) the inter-phase thickness, (3) variations in the total porosity, and (4) variations in the chemical composition of the Sic fiber are carried out and modeled using various codes used here at NASA-Glenn (PCGina, NASALife, CEMCAN, etc...). The effects of these variations and the ranking of their respective influences on the various thermo-mechanical material properties are studied and compared to available test data. The properties of the materials as well as minor changes to geometry are then made to the computer model and the detrimental effects observed using statistical analysis software. The ultimate purpose of this study is to determine what variations in material processing can lead to the most critical changes in the materials property. The work I have taken part in this summer explores, in general, the key properties needed In this study SiC/SiC composites of varying architectures, utilizing a boron-nitride (BN)

Fornuff, Jonathan↗
NASA NTRS2000

Cyclic Oxidation Testing and Modelling: A NASA Lewis Perspective

The Materials Division of the NASA Lewis Research Center has been heavily involved in the cyclic oxidation of high temperature materials for 30 years. Cyclic furnace and burner rig apparati have been developed, refined, and replicated to provide a large scale facility capable of evaluating many materials by a standard technique. Material behavior is characterized by weight change data obtained throughout the test, which has been modelled in a step-wise process of scale growth and spallation. This model and a coupled diffusion model have successfully described cyclic behavior for a number of systems and have provided insights regarding life prediction and variations in the spalling process. Performance ranking and mechanistic studies are discussed primarily for superalloys and coating alloys. Similar cyclic oxidation studies have been performed on steels, intermetallic compounds, thermal barrier coatings, ceramics, and ceramic composites. The most common oxidation test was performed in air at temperatures ranging from 800 deg. to 1600 C, for times up to 10000 h, and for cycle durations of 0.1 to 1000 h. Less controlled, but important, test parameters are the cooling temperature and humidity level. Heating and cooling rates are not likely to affect scale spallation. Broad experience has usually allowed for considerable focus and simplification of these test parameters, while still revealing the principal aspects of material behavior and performance. Extensive testing has been performed to statistically model the compositional effects of experimental alloys and to construct a comprehensive database of complex commercial alloys.

Smialek, J. L.↗
DOE OSTI2026

An improved dataset for predicting mammal infecting viruses from genetic sequence information

There have been several attempts to develop machine learning (ML) models to identify human infecting viruses from their genomic sequences, with varying degrees of success. Direct comparison between models is problematic, because these models are typically trained and evaluated on different datasets with alternative data splitting schemes, features, and model performance metrics. In this paper we present a standardized dataset of mammal infecting and non-infecting viral pathogens, refined from the previous work of Mollentze et al. to include the latest literature evidence, roughly doubling the number of curated host-virus records available to the community, and new host target labels, primate and mammal. The new host labels were included for several reasons, including previous reports that classification performance is better at broader taxonomic ranks and the idea that there may be more data for primate infection that might serve as a suitable proxy for zoonotic potential and avoidance of false positives for human infection due to absence of evidence. On this dataset, we report the performance of eight machine learning models for predicting mammal-infecting viruses from their genomic sequences. We find that randomly assigning cases in our improved dataset to training/testing sets, when compared to the original assignments into training/testing in Mollentze et al., increases the overall average ROC AUC of prediction of human infection from 0.663 ± 0.070 to 0.784 ± 0.013, consistent with the reduction in phylogenetic distance between train and test sets (relative entropy change from 3.00 to 0.08). The broadest host category of mammal infection can be predicted most reliably at 0.850 ± 0.020. We share our improved dataset and code to enable standardized comparisons of machine learning methods to predict human host infections. Overall, we have presented preliminary evidence that classification of virus host infection is more tractable at higher taxonomic ranks, that unsurprisingly reducing the phylogenetic distance between training and test sets can improve predictive performance, that peptide kmer features appear to be harmful to out of sample model performance, and we are left with the question of whether models for virus host prediction can reasonably be expected to perform well in out of sample scenarios given the likelihood that viruses do not share a common ancestor. Consistent with this concern, when the data is resampled such that there is no overlap between viral families in training and test sets (relative entropy > 24), models perform no better than random chance at prediction of human infection regardless of whether kmers are included (ROC AUC 0.50 ± 0.08) or not (ROC AUC 0.50 ± 0.04).

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1983

Convergence and stability properties of minimal polynomial and reduced rank extrapolation algorithms

The minimal polynomial and reduced rank extrapolation algorithms are two acceleration of convergence methods for sequences of vectors. In a recent survey these methods were tested and compared with the scalar, vector, topological epsilon algorithms, and were observed to be more efficient than the latter. It was also observed that the two methods have similar convergence properties. The convergence and stability properties of these methods are analyzed and the performance of the acceleration methods when applied to a class of vector sequences that includes those sequences obtained from systems of linear equations by using matrix iterative methods is discussed.

Sidi, A.↗
NASA NTRS1999

Cyclic Oxidation of Single-Crystal NiAl-X Alloys

Several single-crystal NiAl-X alloys (X = Hf, Ti, Cr, Ga) were cyclically oxidized at 1000 C for up to 1000 1-hr cycles. The alloys all showed protective, adherent alpha-Al2O3 scale formation with positive weight change behavior throughout the test. There was no clear correlation between the composition of the various alloys and the specific weight gain although the ranking by weight change was relatively consistent for two duplicate series of samples. The presence of Hf (0.5 - 0.8 at.%) resulted in the internal formation of Al2O3/HfO2 "stringers." Diffusion of Hf to the growing oxide stringers resulted in the development of a near-surface layer depleted of these precipitates.

Nesbitt, James A.↗
NASA NTRS2011

Estimated Accuracy of Three Common Trajectory Statistical Methods

Three well-known trajectory statistical methods (TSMs), namely concentration field (CF), concentration weighted trajectory (CWT), and potential source contribution function (PSCF) methods were tested using known sources and artificially generated data sets to determine the ability of TSMs to reproduce spatial distribution of the sources. In the works by other authors, the accuracy of the trajectory statistical methods was estimated for particular species and at specified receptor locations. We have obtained a more general statistical estimation of the accuracy of source reconstruction and have found optimum conditions to reconstruct source distributions of atmospheric trace substances. Only virtual pollutants of the primary type were considered. In real world experiments, TSMs are intended for application to a priori unknown sources. Therefore, the accuracy of TSMs has to be tested with all possible spatial distributions of sources. An ensemble of geographical distributions of virtual sources was generated. Spearman s rank order correlation coefficient between spatial distributions of the known virtual and the reconstructed sources was taken to be a quantitative measure of the accuracy. Statistical estimates of the mean correlation coefficient and a range of the most probable values of correlation coefficients were obtained. All the TSMs that were considered here showed similar close results. The maximum of the ratio of the mean correlation to the width of the correlation interval containing the most probable correlation values determines the optimum conditions for reconstruction. An optimal geographical domain roughly coincides with the area supplying most of the substance to the receptor. The optimal domain s size is dependent on the substance decay time. Under optimum reconstruction conditions, the mean correlation coefficients can reach 0.70 0.75. The boundaries of the interval with the most probable correlation values are 0.6 0.9 for the decay time of 240 h and 0.5 0.95 for the decay time of 12 h. The best results of source reconstruction can be expected for the trace substances with a decay time on the order of several days. Although the methods considered in this paper do not guarantee high accuracy they are computationally simple and fast. Using the TSMs in optimum conditions and taking into account the range of uncertainties, one can obtain a first hint on potential source areas.

Kabashnikov, Vitaliy P.↗
NASA NTRS1990

A volatile organics concentrator for use in monitoring Space Station water quality

The process used to identify, select, and design an approach to the isolation and concentration of volatile organic compounds from a water sample prior to chemical analysis in a microgravity environment is discerned. The trade analysis leading to the recommended volatile organics concentrator (VOC) concept to be tested in a breadboard device is presented. The system covers the areas of gases, volatile separation from water, and water removal/gas chromatograph/mass spectrometer interface. Five options for potential use in the VOC and GC/MS system are identified and ranked, and also nine options are presented for separation of volatiles from the water phase. Seven options for use in the water removal/GC column and MS interface are also identified and included in the overall considerations. A final overall recommendation for breadboard VOC testing is given.

Ehntholt, Daniel J.↗
NASA NTRS1992

A statistical analysis of elevated temperature gravimetric cyclic oxidation data of 36 Ni- and Co-base superalloys based on an oxidation attack parameter

A large body of high temperature cyclic oxidation data generated from tests at NASA Lewis Research Center involving gravimetric/time values for 36 Ni- and Co-base superalloys was reduced to a single attack parameter, K(sub a), for each run. This K(sub a) value was used to rank the cyclic oxidation resistance of each alloy at 1000, 1100, and 1150 C. These K(sub a) values were also used to derive an estimating equation using multiple linear regression involving log(sub 10)K(sub a) as a function of alloy chemistry and test temperature. This estimating equation has a high degree of fit and could be used to predict cyclic oxidation behavior for similar alloys and to design an optimum high strength Ni-base superalloy with maximum high temperature cyclic oxidation resistance. The critical alloy elements found to be beneficial were Al, Cr, and Ta.

Barrett, Charles A.↗
NASA NTRS1997

10,000-Hour Cyclic Oxidation Behavior at 982 C (1800 F) of 68 High-Temperature Co-, Fe-, and Ni-Base Alloys

Sixty-eight high temperature Co-, Fe-, and Ni-base alloys were tested for 10-one thousand hour cycles in static air at 982 C (1800 F). The oxidation behavior of the test samples was evaluated by specific weight change/time data, x-ray diffraction of the post-test samples, and their final appearance. The gravimetric and appearance data were combined into a single modified oxidation parameter, KB4 to rank the cyclic oxidation resistance from excellent to catastrophic. The alloys showing the 'best' resistance with no significant oxidation attack were the alumina/aluminate spinel forming Ni-base turbine alloys: U-700, NASA-VIA and B-1900; the Fe-base ferritic alloys with Al: TRW-Valve, HOS-875, NASA-18T, Thermenol and 18SR; and the Ni-base superalloy IN-702.

Barrett, Charles A.↗
NASA NTRS1999

Structural Optimization for Reliability Using Nonlinear Goal Programming

This report details the development of a reliability based multi-objective design tool for solving structural optimization problems. Based on two different optimization techniques, namely sequential unconstrained minimization and nonlinear goal programming, the developed design method has the capability to take into account the effects of variability on the proposed design through a user specified reliability design criterion. In its sequential unconstrained minimization mode, the developed design tool uses a composite objective function, in conjunction with weight ordered design objectives, in order to take into account conflicting and multiple design criteria. Multiple design criteria of interest including structural weight, load induced stress and deflection, and mechanical reliability. The nonlinear goal programming mode, on the other hand, provides for a design method that eliminates the difficulty of having to define an objective function and constraints, while at the same time has the capability of handling rank ordered design objectives or goals. For simulation purposes the design of a pressure vessel cover plate was undertaken as a test bed for the newly developed design tool. The formulation of this structural optimization problem into sequential unconstrained minimization and goal programming form is presented. The resulting optimization problem was solved using: (i) the linear extended interior penalty function method algorithm; and (ii) Powell's conjugate directions method. Both single and multi-objective numerical test cases are included demonstrating the design tool's capabilities as it applies to this design problem.

El-Sayed, Mohamed E.↗
NASA NTRS1986

Application of multiple objective optimization techniques to finite element model tuning

This report examines tuning a finite element model using vector optimization techniques. Structural models using finite element theory often need to be adjusted so they can accurately simulate the real structure. The goal is to tune the model such that it will reproduce data derived from structural tests. First, the performance indices are extremized using multiple objective optimization theory, producing a set of possible solutions. Next, the solutions are rank ordered according to a decision maker's preferences to select the best answer. The tuning process was applied to a T-38 horizontal stabilizer. Numerous weighted solutions contained a best static deformation model, a best frequency model and three intermediate combinations of these two models. This automated procedure proved to be a versatile method capable of producing solutions for many types of tuning problems.

Devore, Charles R.↗