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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 271 records · Page 15

Thermal fatigue resistance of NASA WAZ-20 alloy with three commercial coatings

Screening tests using three commercial coatings (Jocoat, HI-15, and RT-1A) on the nickel-base alloy NASA WAZ-20 were performed by cyclic exposure in a Mach 1 burner facility. These tests showed Jocoated WAZ-20 to have the best cracking resistance. The thermal fatigue resistance of Jocoated WAZ-20 in both the random polycrystalline and directionally solidified polycrystalline forms relative to that of other superalloys was then evaluated in a fluidized-bed facility. This investigation showed that Jocoated random polycrystalline WAZ-20 ranked approximately in midrange in thermal fatigue life. The thermal fatigue life of directionally solidified Jocoated WAZ-20 was shorter than that of other directionally solidified alloys but still longer than that of all alloys in the random polycrystalline form.

Bizon, P. T.↗

Effects of automobile steering characteristics on driver/vehicle system performance in discrete maneuvers

A series of discrete maneuver tasks were used to evaluate the effects of steering gain and directional mode dynamic parameters on driver/vehicle responses. The importance and ranking of these parameters were evaluated through changes in subjective driver ratings and performance measures obtained from transient maneuvers such as a double lane change, an emergency lane change, and an unexpected obstacle. The unexpected obstacle maneuver proved more sensitive to individual driver differences than to vehicle differences. Results were based on full scale tests with an experienced test driver evaluating many different dynamic configurations plus seventeen ordinary drivers evaluating six key configurations.

Klein, R. H.↗

Improving Efficacy and Safety of Pharmacological Treatment Through Precision Health and Pharmacogenomics

INTRODUCTION: Future spaceflight will require increased crew medical autonomy as exploration class missions expand in duration and distance from Earth, especially for Mars missions. As mission duration increases, it will be essential to have appropriate amounts of effective medication to ensure the maintenance of crew health and performance. Conversely, mass and volume constraints will become more severe as future spaceflight expands beyond low Earth orbit, where resupply is difficult or becomes impossible. These constraints thus convey an urgency to tailor medications for individual crewmembers and further examine appropriate dosing regimens. BACKGROUND: Precision Health is an exciting area of medicine focused on maintaining an individual’s health and performance through in-depth understanding of an individual’s unique clinical and environmental history, genetic makeup, and molecular profiles. This approach can be adapted to better predict, monitor, and address physiological responses to the spaceflight environment. A subset of this field is pharmacogenomics (PGX), the study of how the expressed genome impacts drug responses with the goal of prescribing the right dose of the right drug at the right time. Specifically, PGX testing provides valuable information on an individual’s precise allelic variations to guide physicians in making informed decisions on drug choice and dosing to avoid adverse events and maximize efficacy. The study goal was to identify which current space pharmacy drugs could be evaluated using PGX testing and to understand the potential impact on the health and wellness of the astronaut population. Additionally, we sought to evaluate clinically available FDA-approved PGX testing solutions to better understand its applicability. METHODS: A complete list of drugs on the ISS was analyzed for risk and likelihood of drug failure and PGX actionability. This analysis encompassed both astronauts’ personal medications, including supplements and over the counter drugs (n=151) contained in the ISS medical accessory kit (IMAK), and ISS MedKit formulary medications (n=95). Duplicate medications and different formulations were removed, which resulted in a total of 157 drugs used in the subsequent analysis. A 5x5 risk assessment table was produced by examining the likelihood of drug failure compared to the consequence of drug failure (LxC). Likelihood of individual drug failure was defined by whether existing processes are sufficient to prevent ineffective treatment or impactful side effect events, as ranked from 1 (very low, can easily be prevented) to 5 (very high, cannot be prevented) during a Mars mission. In contrast, the consequence of drug failure was defined by impact to safety, schedule, cost, or technical criteria and ranked from 1 (very low) to 5 (very high). An assessment of PGX reference laboratories is currently underway to evaluate sample requirements, benefit analysis (cost vs. utility of allele variant analysis), relevance to inflight medication usage, quality of reporting in enabling clinical application, and ease of integration into electronic medical records. RESULTS: Risk assessments (LxC 5x5 table) indicated 128 medications were in the green zone where risk is acceptable, with the remaining 29 of the medications in the yellow or red zone driven predominantly due to drug failure or safety concerns. We found that current PGX testing results could impact 21% of the total medications in the ISS MedKit and IMAK; of these, 9 medications currently have direct clinically actionable guidance available. Results of the clinical PGX solution evaluations as related to these medications will be presented. CONCLUSION: PGX testing has demonstrated clear benefits in terrestrial medicine and clinical environments for the selection of proper medications, avoiding adverse drug reactions, and maximizing drug efficacy. We propose that similar benefits would be bestowed on the astronaut and commercial spaceflight passenger population by performing preemptive preflight PGX testing to reduce risk of mission failure due to ineffective or toxic medications, improve drug efficacy, and further open the door to countermeasure research. For example, PGX results could allow tailoring of specific medications at optimal doses more precisely to each individual astronaut, particularly in areas of space motion sickness, sleep aids, and analgesics. An additional benefit is that PGX results could provide information for better planning of the components of a space pharmacy for deep space missions to be more effective and efficient in the utilization of limited pharmaceutical resources. Finally, while PGX testing of the astronaut corps is not currently conducted, this approach could provide immediate impact in support of mission success by reducing risks, optimizing astronaut performance, and providing valuable insights into long-term astronaut health. Such advancements in clinical decision making are important next steps in building dynamic individual risk profiles for astronauts, increasing selection of the best treatment choice, and providing tailored countermeasures for individual crewmembers.

Pharmacogenomics↗

Ultrasonic ranking of toughness of tungsten carbide

The feasibility of using ultrasonic attenuation measurements to rank tungsten carbide alloys according to their fracture toughness was demonstrated. Six samples of cobalt-cemented tungsten carbide (WC-Co) were examined. These varied in cobalt content from approximately 2 to 16 weight percent. The toughness generally increased with increasing cobalt content. Toughness was first determined by the Palmqvist and short rod fracture toughness tests. Subsequently, ultrasonic attenuation measurements were correlated with both these mechanical test methods. It is shown that there is a strong increase in ultrasonic attenuation corresponding to increased toughness of the WC-Co alloys. A correlation between attenuation and toughness exists for a wide range of ultrasonic frequencies. However, the best correlation for the WC-Co alloys occurs when the attenuation coefficient measured in the vicinity of 100 megahertz is compared with toughness as determined by the Palmqvist technique.

Vary, A.↗

Testing the radiometric stability of HCMM thermal infrared data

A study conducted to test the radiometric stability of thermal infrared (TIR) data from the heat-capacity mapping mission (HCMM) satellites is considered. The radiance values associated with various land use and cover types in a regional study area centered on Washington, D.C. are examined. The study shows that for three different day TIR-data sets, the relative ranking of mean thermal values associated with five Level I and three Level II land-use/land-cover categories remains constant over time. Although HCMM predicted temperatures show variability up to 5 C from ground observed temperatures, the thermal measurements recorded by the satellite are fairly stable as indicators of surface temperature. A method for combining HCMM thermal data and Landsat multispectral scanner (MSS) data to improve the classification of Level I land-cover categories, and in particular the separability of urban and nonurban areas is described. A merged HCMM-MSS data set is found to yield the best results in terms of thematic-map accuracy.

Witt, R. G.↗

Is the Sky Really Falling? An Overview of Orbital Debris

Orbital debris has been a prominent topic for a while, even before the movie Gravity came out. An anti-satellite test and a collision with an operational satellite both produced large highly-publicized debris clouds within recent years. While large objects like abandoned satellites and rocket bodies may be the most recognizable and identifiable concerns, a majority of the daily threat comes from the much more numerous smaller particles. In fact, small particle penetration continues to rank among the leading risks for manned space missions to the International Space Station and beyond. How much 'stuff' is up there, where did it come from, what harm can it do, and what is being done about it? These questions and more will be discussed.

Orbital Debris↗

Design, Processing, and Properties of WTaCrV-Hf Multi-principal Element Alloys

Refractory multi-principal element alloys are candidates for high-temperature structural components due, in part, to their high strength and high melting points. Single-phase materials are initially preferred for isotropic material properties as a function of time and temperature in service conditions. This work outlines a computational rank-ordering and experimental validation methodology for single-phase body-centered-cubic phase stability in WTaCrV-Hf alloys using order–disorder transition temperature. Eight compositions were fabricated by arc-melting and heat-treated at 1400 °C for 24 hrs. X-ray diffraction, energy-dispersive x-ray spectroscopy, and Vickers hardness testing showed alloys with order–disorder transition temperatures below 600 °C formed a single-phase body-centered-cubic structure during solidification and remained single-phase after heat-treatment. The sample possessing the lowest order–disorder transition temperature exhibited slip traces suggestive of room-temperature plastic deformation under Vickers indentation, with both heat-treated single-phase samples exhibiting hardnesses over 800 HV with little cracking compared to tungsten. These results establish order–disorder transition temperature as a viable predictive parameter for multi-principal element alloy phase stability. The methodology outlined in this work provides a framework for future design, fabrication, and characterization of high-temperature structural multi-principal element alloys.

CALPHAD↗

Item Retrieval as Utility Estimation

Retrieval systems have greatly improved over the last half century, estimating relevance to a latent user need in a wide variety of areas. One area that has not enjoyed such advancements is searching for items by attribute values, a common activity in e-commerce and science, particularly given numeric values. Existing item retrieval systems assume the user has a firm grasp of their own desires and can formulate a good Boolean or SQL-style query to retrieve items, as one would do with a database. A contrasting approach would be to estimate how well items match the user?s latent desires and return items ranked by this estimation. Towards this end, we present a retrieval model inspired by multi-criteria decision making theory, concentrating on numeric attributes. We evaluate our novel approach, the de-facto standard of Boolean retrieval, and several models proposed in the literature, in two user studies using Amazon Mechanical Turk. We use a competitive game to motivate test subjects and compare methods based on the results of the subjects? initial query and their success in the game. In our experiments, our new method signi cantly outperformed the others, whereas the Boolean approaches had the worst performance.

operations research↗

Optical Analysis of Transparent Polymeric Material Exposed to Simulated Space Environment

Transparent polymeric materials are being designed and utilized as solar concentrating lenses for spacecraft power and propulsion systems. These polymeric lenses concentrate solar energy onto energy conversion devices such as solar cells and thermal energy systems. The conversion efficiency is directly related to the transmissivity of the polymeric lens. The Environmental Effects Group of the Marshall Space Flight Center's Materials, Processes, and Manufacturing Department exposed a variety of materials to a simulated space environment and evaluated them for an, change in optical transmission. These materials include Lexan(TM), polyethylene terephthalate (PET). several formulations of Tefzel(TM). and Teflon(TM), and silicone DC 93-500. Samples were exposed to a minimum of 1000 Equivalent Sun Hours (ESH) of near-UV radiation (250 - 400 nm wavelength). Data will be presented on materials exposed to charged particle radiation equivalent to a five-year dose in geosynchronous orbit. These exposures were performed in MSFC's Combined Environmental Effects Test Chamber, a unique facility with the capability to expose materials simultaneously or sequentially to protons, low-energy electrons, high-energy electrons, near UV radiation and vacuum UV radiation.Prolonged exposure to the space environment will decrease the polymer film's transmission and thus reduce the conversion efficiency. A method was developed to normalize the transmission loss and thus rank the materials according to their tolerance to space environmental exposure. Spectral results and the material ranking according to transmission loss are presented.

Edwards, David L.↗

Cibachrome testing

The use of Cibachrome products as a solution to problems encountered when contact printing Kodak film type SO-397 onto Kodak Ektrachrome color reversal paper type 1993 is investigated. A roll of aerial imagery consisting of Kodak film types SO-397 and 2443 was contact printed onto Cibachrome and Kodak materials and compared in terms of color quality, resolution, cost, and compatibility with existing equipment and techniques. Objective measurements are given in terms of resolution and sensitometric response. Comparison prints and transparencies were viewed and ranked according to overall quality and aesthetic appeal. It is recommended that Cibachrome Print material be used in place of Kodak Ektachrome paper because it is more easily processed, the cost is equivalent, and it provides improved resolution, color quality, and image fade resistance.

Weinstein, M. S.↗

Tool for Ranking Research Options

Tool for Research Enhancement Decision Support (TREDS) is a computer program developed to assist managers in ranking options for research aboard the International Space Station (ISS). It could likely also be adapted to perform similar decision-support functions in industrial and academic settings. TREDS provides a ranking of the options, based on a quantifiable assessment of all the relevant programmatic decision factors of benefit, cost, and risk. The computation of the benefit for each option is based on a figure of merit (FOM) for ISS research capacity that incorporates both quantitative and qualitative inputs. Qualitative inputs are gathered and partly quantified by use of the time-tested analytical hierarchical process and used to set weighting factors in the FOM corresponding to priorities determined by the cognizant decision maker(s). Then by use of algorithms developed specifically for this application, TREDS adjusts the projected benefit for each option on the basis of levels of technical implementation, cost, and schedule risk. Based partly on Excel spreadsheets, TREDS provides screens for entering cost, benefit, and risk information. Drop-down boxes are provided for entry of qualitative information. TREDS produces graphical output in multiple formats that can be tailored by users.

Ortiz, James N.↗

Porosity Area Fraction Analysis of Bonded Borosilicate Specimens From in-Situ Optical Imagery

Image segmentation methods are routinely used to analyze data derived in nondestructive testing scenarios. A typical problem in this area is to estimate porosity from X-ray Computed Tomography (CT) inspections. This investigation aims to understand the effectiveness of open-source image segmentation methods for porosity estimation from optical images in the context of strength analysis of bonded materials and provides a benchmark of performance against a standard commercial software package. The rank ordering of the specimens by porosity area fraction is consistent across both methods.

Porosity area fraction↗

Porosity Area Fraction Analysis of Bonded Borosilicate Specimens From in-Situ Optical Imagery

Image segmentation methods are routinely used to analyze data derived in nondestructive testing scenarios. A typical problem in this area is to estimate porosity from X-ray Computed Tomography (CT) inspections. This investigation aims to understand the effectiveness of open-source image segmentation methods for porosity estimation from optical images in the context of strength analysis of bonded materials and provides a benchmark of performance against a standard commercial software package. The rank ordering of the specimens by porosity area fraction is consistent across both methods.

Porosity area fraction↗

Learning epistatic polygenic phenotypes with Boolean interactions

Detecting epistatic drivers of human phenotypes is a considerable challenge. Traditional approaches use regression to sequentially test multiplicative interaction terms involving pairs of genetic variants. For higher-order interactions and genome-wide large-scale data, this strategy is computationally intractable. Moreover, multiplicative terms used in regression modeling may not capture the form of biological interactions. Building on the Predictability, Computability, Stability (PCS) framework, we introduce the epiTree pipeline to extract higher-order interactions from genomic data using tree-based models. The epiTree pipeline first selects a set of variants derived from tissue-specific estimates of gene expression. Next, it uses iterative random forests (iRF) to search training data for candidate Boolean interactions (pairwise and higher-order). We derive significance tests for interactions, based on a stabilized likelihood ratio test, by simulating Boolean tree-structured null (no epistasis) and alternative (epistasis) distributions on hold-out test data. Finally, our pipeline computes PCS epistasis p-values that probabilisticly quantify improvement in prediction accuracy via bootstrap sampling on the test set. We validate the epiTree pipeline in two case studies using data from the UK Biobank: predicting red hair and multiple sclerosis (MS). In the case of predicting red hair, epiTree recovers known epistatic interactions surrounding MC1R and novel interactions, representing non-linearities not captured by logistic regression models. In the case of predicting MS, a more complex phenotype than red hair, epiTree rankings prioritize novel interactions surrounding HLA-DRB1 , a variant previously associated with MS in several populations. Taken together, these results highlight the potential for epiTree rankings to help reduce the design space for follow up experiments.

59 BASIC BIOLOGICAL SCIENCES↗

SSME HPOTP post-test diagnostic system enhancement project

An assessment of engine and component health is routinely made after each test or flight firing of a space shuttle main engine (SSME). Currently, this health assessment is done by teams of engineers who manually review sensor data, performance data, and engine and component operating histories. Based on review of information from these various sources, an evaluation is made as to the health of each component of the SSME and the preparedness of the engine for another test or flight. The objective of this project is to further develop a computer program which automates the analysis of test data from the SSME high-pressure oxidizer turbopump (HPOTP) in order to detect and diagnose anomalies. This program fits into a larger system, the SSME Post-Test Diagnostic System (PTDS), which will eventually be extended to assess the health and status of most SSME components on the basis of test data analysis. The HPOTP module is an expert system, which uses 'rules-of-thumb' obtained from interviews with experts from NASA Marshall Space Flight Center (MSFC) to detect and diagnose anomalies. Analyses of the raw test data are first performed using pattern recognition techniques which result in features such as spikes, shifts, peaks, and drifts being detected and written to a database. The HPOTP module then looks for combination of these features which are indicative of known anomalies, using the rules gathered from the turbomachinery experts. Results of this analysis are then displayed via a graphical user interface which provides ranked lists of anomalies and observations by engine component, along with supporting data plots for each.

Bickmore, Timothy W.↗

Post-impact fatigue of cross-plied, through-the-thickness reinforced carbon/epoxy composites

An experimental investigation of the post-impact fatigue response of integrally woven carbon/epoxy composites was conducted. Five different through-the-thickness (TTT) reinforcing fibers were used in an experimental textile process that produced an integrally woven (0/90/0/90/0/90/0/90/0)(sub T) ply layup with 21K AS4 carbon tow fiber. The resin was Hercules 3501-6, and the five TTT reinforcing fibers were Kevlar, Toray carbon, AS4 carbon, glass, and IM6 carbon. The purpose of this investigation was to study the post-impact fatigue response of these material systems and to identify the optimum TTT fiber. Samples were impacted with one half inch diameter aluminum balls with an average velocity of 543 ft/sec. Post-impact static compression and constant amplitude tension-compression fatigue tests were conducted. Fatigue tests were conducted with a loading ratio of R=-5, and frequency of 4 Hz. Damage growth was monitored using x-radiographic and sectioning techniques and by examining the stress-strain response (across the impact site) throughout the fatigue tests. The static compressive stress versus far-field strain response was nearly linear for all material groups. All the samples had a transverse shear failure mode. The average compressive modulus (from far-field strain) was about 10 Msi. The average post-impact static compressive strength was about 35.5 Ksi. The IM6 carbon sample had a strength of over 40 Ksi, more than 16 percent stronger than average. There was considerable scatter in the S-N data. However, the IM6 carbon samples clearly had the best fatigue response. The response of the other materials, while worse than IM6 carbon, could not be ranked definitively. The initial damage zones caused by the impact loading and damage growth from fatigue loading were similar for all five TTT reinforcing materials. The initial damage zones were circular and consisted of delaminations, matrix cracks and ply cracks. Post-impact fatigue loading caused delamination growth, ply cracking and fiber bundle failures, typically 45 deg from impact load direction. During the initial 97 percent of fatigue life, delaminations, ply cracks and fiber bundle failures primarily grew at and near the impact site. During the final 3 percent of life, damage grew rapidly transverse to the loading direction as a through-the-thickness transverse shear failure. The stress-strain response was typically linear during the initial 50 percent of life, and stiffness dropped about 20 percent during this period. During the next 47 percent of life, stiffness dropped about 34 percent, and the stress-strain response was no longer linear. The stiffness decreased about 23 percent during the final 3 percent of life. These trends were typical of all the materials tested. Therefore, by monitoring stiffness loss, fatigue failure could be accurately anticipated.

Serdinak, Thomas E.↗

Replace Human Intelligence with Fast and Smart Geometric Reasoning and Graph Neural Network to Accelerate Next Gen ModSim Workflows

We present an agent-guided approach to CAD geometry decomposition that automates hex/hybrid meshing with graph neural networks (GNNs) to accelerate next-generation ModSim workflows. Our end-to-end pipeline (i) reduces 3D boundary-representation (B-Rep) models to a 2D chordal axis skeleton (CAT) and then to a 1D bipartite graph of surface and curve nodes, (ii) assigns per node labels as Cubit® WebCut actions, (iii) trains a multi-action GNN under supervised learning, and (iv) predicts five surface-node and three curve-node actions on out-of-distribution test geometries. Each graph node carries geometric, topological, and meshing attributes drawn from the B-Rep “skin” and CAT “skeleton,” with two-way mappings across 3D↔2D↔1D representations to maintain traceability back to 3D CAD. The supervised learning model exhibits stable convergence of the binary cross-entropy loss and achieves 98.7% accuracy on unseen lattice models. To operationalize decision-making, we rank predicted commands by geometric significance and prototyped the agent-guided workflow through the Cubit® Meshing PowerTool GUI. As a stretch goal, we explore reinforcement learning (RL) to reduce or remove label requirements and to learn policies for action sequences that maximize total reward (e.g., size of hex-meshable regions and resulting hex mesh quality). When all-hex meshing is not feasible, the agent assists in producing hybrid meshes—prioritizing hex in critical regions and transitioning to tetrahedral elements (tets) elsewhere—maintaining fidelity while ensuring robustness. The overarching objective is to replace manual, heuristics-based decomposition with data-driven, reproducible automation, cutting meshing turnaround time by orders of magnitude. We anticipate direct impact on simulation workflows through intelligent, scalable decomposition of complex CAD models into hex-meshable subdomains.

97 MATHEMATICS AND COMPUTING↗

Closing the Loop between In Situ Stress Complexity and EGS Fracture Complexity

We present an agent-guided approach to CAD geometry decomposition that automates hex/hybrid meshing with graph neural networks (GNNs) to accelerate next-generation ModSim workflows. Our end-to-end pipeline (i) reduces 3D boundary-representation (B-Rep) models to a 2D chordal axis skeleton (CAT) and then to a 1D bipartite graph of surface and curve nodes, (ii) assigns per node labels as Cubit® WebCut actions, (iii) trains a multi-action GNN under supervised learning, and (iv) predicts five surface-node and three curve-node actions on out-of-distribution test geometries. Each graph node carries geometric, topological, and meshing attributes drawn from the B-Rep “skin” and CAT “skeleton,” with two-way mappings across 3D↔2D↔1D representations to maintain traceability back to 3D CAD. The supervised learning model exhibits stable convergence of the binary cross-entropy loss and achieves 98.7% accuracy on unseen lattice models. To operationalize decision-making, we rank predicted commands by geometric significance and prototyped the agent-guided workflow through the Cubit® Meshing PowerTool GUI. As a stretch goal, we explore reinforcement learning (RL) to reduce or remove label requirements and to learn policies for action sequences that maximize total reward (e.g., size of hex-meshable regions and resulting hex mesh quality). When all-hex meshing is not feasible, the agent assists in producing hybrid meshes—prioritizing hex in critical regions and transitioning to tetrahedral elements (tets) elsewhere—maintaining fidelity while ensuring robustness. The overarching objective is to replace manual, heuristics-based decomposition with data-driven, reproducible automation, cutting meshing turnaround time by orders of magnitude. We anticipate direct impact on simulation workflows through intelligent, scalable decomposition of complex CAD models into hex-meshable subdomains.

42 ENGINEERING↗