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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Effect of alloying on intrinsic ductility in WTaCrV high entropy alloys

Tungsten (W) exhibits desirable properties for extreme applications, such as the divertor in magnetic fusion reactors, but its practicality remains limited due to poor formability and insufficient irradiation resistance. In this work, we study the intrinsic ductility of body-centered cubic WTaCrV based high entropy alloys (HEAs), which are known to exhibit excellent irradiation resistance. The ductility evaluations are carried out using a criterion based on the competition between the critical stress intensity factors for emission (K Ie ) and cleavage (K Ic ) in the {110} slip planes and {110} crack planes, which are evaluated within the linear elastic fracture mechanics framework and computed using density functional theory. The results suggest that increasing the alloying concentrations of V and reducing the concentrations of W can significantly improve the ductility in these HEAs. The elastic anisotropy for these HEAs is analyzed using the Zener anisotropy ratio and its correlation with the concentration of W in the alloys is studied. Results indicate that these alloys tend to be fairly isotropic independently from the concentration of W in them. The computed data for the elastic constants of these HEAs is also compared against available experimental data. The results are in good agreement, validating the robustness and accuracy of the computational methods. Multiple phenomenological ductility metrics were also computed and analyzed against the analytical model. Some metrics, mainly the surrogate D parameter, show a good correlation with the Rice model. The potential of these empirical metrics to serve as surrogate screening models for optimizing the compositional space is also discussed.

Anisotropy↗
NASA NTRS1996

Emission Spectral Measurements in the Plenum of an Arc Jet Wind Tunnel

Arc jet wind tunnel facilities are used to evaluate thermal protection system materials for re-entry vehicles. The high speed, high temperature flowfield generated by the arc jet can simulate the extreme aerodynamic heating environment experienced during re-entry so that the survivability of heat shield materials and performance of various designs options can be tested. Although the re-entry heating environment can be approximated in the arc jet facility, the flowfield only partially simulates the actual re-entry flight conditions. Reynolds numbers are not matched so that surface shear stress distributions and mass transfer rates due to ablation or other mechanisms are not modeled correctly. Unlike flight conditions the arc freestream air is in non-equilibrium because of the rapid expansion that occurs in the supersonic nozzle. To properly study the actual re-entry flow environment, computational fluid dynamics, computational chemistry and radiation models must be used. Arc jet tunnel tests serve to validate these models. To perform accurate simulations inlet and boundary-conditions are needed, which come from measurements of the flowfield. The present study is concerned with measurements in the plenum region of an arc heater. In the past, conditions in the arc heater flowfield have been predicted using simulations since conventional measurement techniques could not be used in the harsh extremely high temperature environment. The present study is part of a recent push to utilize optical techniques to help better characterize the arc jet flowfields. Emission measurements have been made in the shock layer and the constrictor section of the arc heater to determine temperatures and species number densities. LIF measurements have been made in the free stream to determine temperature and velocity.

Donohue, Jim↗
NASA NTRS2016

Extending the Operational Envelope of a Turbofan Engine Simulation into the Sub-Idle Region

In many non-linear gas turbine simulations, operation in the sub-idle region can lead to model instability. This paper lays out a method for extending the operational envelope of a map based gas turbine simulation to include the sub-idle region. This method develops a multi-simulation solution where the baseline component maps are extrapolated below the idle level and an alternate model is developed to serve as a safety net when the baseline model becomes unstable or unreliable. Sub-idle model development takes place in two distinct operational areas, windmilling/shutdown and purge/cranking/ startup. These models are based on derived steady state operating points with transient values extrapolated between initial (known) and final (assumed) states. Model transitioning logic is developed to predict baseline model sub-idle instability, and transition smoothly and stably to the backup sub-idle model. Results from the simulation show a realistic approximation of sub-idle behavior as compared to generic sub-idle engine performance that allows the engine to operate continuously and stably from shutdown to full power.

aerothermodynamics↗
NASA NTRS2016

Extending the Operational Envelope of a Turbofan Engine Simulation into the Sub-Idle Region

In many non-linear gas turbine simulations, operation in the sub-idle region can lead to model instability. This paper lays out a method for extending the operational envelope of a map based gas turbine simulation to include the sub-idle region. This method develops a multi-simulation solution where the baseline component maps are extrapolated below the idle level and an alternate model is developed to serve as a safety net when the baseline model becomes unstable or unreliable. Sub-idle model development takes place in two distinct operational areas, windmilling/shutdown and purge/cranking/startup. These models are based on derived steady state operating points with transient values extrapolated between initial (known) and final (assumed) states. Model transitioning logic is developed to predict baseline model sub-idle instability, and transition smoothly and stably to the backup sub-idle model. Results from the simulation show a realistic approximation of sub-idle behavior as compared to generic sub-idle engine performance that allows the engine to operate continuously and stably from shutdown to full power.

gas path dynamics↗
DOE OSTI2022

Thermochemical characterization of intumescent materials and their application in FEM models using Aria

Intumescent materials are in wide use as protective coatings in fire protection or thermal management applications. These materials undergo chemical reactions occurring from approximately 300°C to 900°C, which outgas and expand the material, providing an appreciable increase in insulative performance. However, the complicated chemical mechanisms and large changes in materials properties complicate the incorporation of these materials into predictive thermal models. This document serves to outline the thermochemical characterization of select intumescent materials, the extraction of relevant parameters, and the incorporation of these parameters into the ChemEQ reaction model implemented in Aria. This work was performed in 2016 and documented in a draft SAND report in March 2017. In 2022, the draft SAND report was discovered and put through R&A.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Strategies for Integrating Deep Learning Surrogate Models with HPC Simulation Applications

The emerging trend of the convergence of high performance computing (HPC), machine learning/deep learning (ML/DL), and big data analytics presents a host of challenges for large-scale computing campaigns that seek best practices to interleave traditional scientific simulation-based workloads with ML/DL models. A portfolio of systematic approaches to incorporate deep learning into modeling and simulation serves a vital need when we support AI for science at a computing facility. In this paper, we evaluate several strategies for deploying deep learning surrogate models in a representative physics application on supercomputers at the Oak Ridge Leadership Computing Facility (OLCF). We discuss a set of recommended deployment architectures and implementation approaches. We analyze and evaluate these alternatives and show their performance and scalability up to 1000 GPUs on two mainstream platforms equipped with different deep learning hardware and software stacks.

Yin, Junqi↗
NASA NTRS1999

Ionizing radiation-induced mutagenesis: radiation studies in Neurospora predictive for results in mammalian cells

Ionizing radiation was the first mutagen discovered and was used to develop the first mutagenicity assay. In the ensuing 70+ years, ionizing radiation became a fundamental tool in understanding mutagenesis and is still a subject of intensive research. Frederick de Serres et al. developed and used the Neurospora crassa ad-3 system initially to explore the mutagenic effects of ionizing radiation. Using this system, de Serres et al. demonstrated the dependence of the frequency and spectra of mutations induced by ionizing radiation on the dose, dose rate, radiation quality, repair capabilities of the cells, and the target gene employed. This work in Neurospora predicted the subsequent observations of the mutagenic effects of ionizing radiation in mammalian cells. Modeled originally on the mouse specific-locus system developed by William L. Russell, the N. crassa ad-3 system developed by de Serres has itself served as a model for interpreting the results in subsequent systems in mammalian cells. This review describes the primary findings on the nature of ionizing radiation-induced mutagenesis in the N. crassa ad-3 system and the parallel observations made years later in mammalian cells.

NASA Discipline Radiation Health↗
DOE OSTI2024

Insights into Probing the Effect of Molecular Weight of Poly(carboxybetaine methacrylate) on the Performance of Forward Osmosis Desalination

Zwitterionic polymers have proven to be a promising nonfouling material that can be applied in the design of selective layers of thin film composite (TFC) membranes. Extending the permeability and usage of TFC membranes have attracted increasing interest in membrane-based desalination processes since water-flux reduction associated with biofouling nowadays persists as a common challenge. By virtue of its strong hydration, this polymer category is very useful to counteract biofouling in marine and biomedical systems, but the benefits from their application in membrane technology are still emerging. The efficacy of the nonfouling property as a function of the polymer’s molecular weight remains unknown. In pursuit of that vision, this study fosters new scientific insights via probing different molecular weights of poly(carboxybetain methacrylate) (PCBMA) coated on the surface as a selective layer for the prepared TFC membranes. The coated zwitterionic membranes (zM) exhibited excellent performance in preventing water flux decay in a bench-scale forward osmosis system. The prepared zM membranes revealed enhanced hydrophilic properties and retained their operational water flux when compared to the control. Our results suggest that using an intermediate-size molecular weight (PCBMA M n 50,000) will result in the best operational performance. The intermediate size resulted in the lowest flux decline rate (R t ) of 0.01 ± 0.001 (zM-50) when compared to the unmodified control membrane 0.56 ± 0.071 (M0) after using a model BSA foulant solution. Furthermore, all coated membranes exhibited similar trends in the observed reverse salt flux profiles, as well. In conclusion, the constructed zM membranes will serve as a model to develop further selective layers in the construction of TFC membranes.

36 MATERIALS SCIENCE↗
NASA NTRS1999

Vestibular responses to linear acceleration are absent in otoconia-deficient C57BL/6JEi-het mice

Vestibular evoked potentials (VsEPs) were measured in normal mice and in mice homozygous for the head tilt mutation (het/het, abbr. het). The het mice lack otoconia, the inertial mass critical for natural stimulation of inner ear gravity receptors. Our findings demonstrate that vestibular neural responses to pulsed linear acceleration are absent in het mice. The results: (1) confirm that adequate sensory stimuli fail to activate gravity receptors in the het model; and (2) serve as definitive evidence that far-field vestibular responses to pulsed linear acceleration depend critically on otolith end organs. The C57BL/6JEi-het mouse may be an excellent model of gravity receptor sensory deprivation.

NASA Discipline Neuroscience↗
NASA NTRS1993

Space Station Freedom: a unique laboratory for gravitational biology research

The advent of Space Station Freedom (SSF) will provide a permanent laboratory in space with unparalleled opportunities to perform biological research. As with any spacecraft there will also be limitations. It is our intent to describe this space laboratory and present a picture of how scientists will conduct research in this unique environment we call space. SSF is an international venture which will continue to serve as a model for other peaceful international efforts. It is hoped that as the human race moves out from this planet back to the moon and then on to Mars that SSF can serve as a successful example of how things can and should be done.

NASA Program Life Sciences Management↗
NASA NTRS2010

NASA-Modified Precipitation Products to Improve EPA Nonpoint Source Water Quality Modeling for the Chesapeake Bay

The Environmental Protection Agency (EPA) has estimated that over 20,000 water bodies within the United States do not meet water quality standards. Ninety percent of the impairments are typically caused by nonpoint sources. One of the regulations in the Clean Water Act of 1972 requires States to monitor the Total Maximum Daily Load (TMDL), or the amount of pollution that can be carried by a water body before it is determined to be "polluted", for any watershed in the U.S.. In response to this mandate, the EPA developed Better Assessment Science Integrating Nonpoint Sources (BASINS) as a Decision Support Tool (DST) for assessing pollution and to guide the decision making process for improving water quality. One of the models in BASINS, the Hydrological Simulation Program -- Fortran (HSPF), computes daily stream flow rates and pollutant concentration at each basin outlet. By design, precipitation and other meteorological data from weather stations serve as standard model input. In practice, these stations may be unable to capture the spatial heterogeneity of precipitation events especially if they are few and far between. An attempt was made to resolve this issue by substituting station data with NASA modified/NOAA precipitation data. Using these data within HSPF, stream flow was calculated for seven watersheds in the Chesapeake Bay Basin during low flow periods, convective storm periods, and annual flows. In almost every case, the modeling performance of HSPF increased when using the NASA-modified precipitation data, resulting in better stream flow statistics and, ultimately, in improved water quality assessment.

Nigro, Joseph↗
DOE OSTI2021

MULTIPHYSICS-MODELING OF FIRE-INDUCED URANIUM AEROSOL FORMATION – A-POSTERIORI BENCHMARKING OF EXPERIMENTS

The formulation and solution of a model that properly described the temperature profiles of uranium in fire conditions was prepared, verified and validated, to support a-posteriori benchmarking of historical experiments. Data from the multi-physics model combined with data regression from the experiments provides a useful tool for exploring sources of potential bias in historical experiments. The approaches used are augmented by visual observations and photographic evidence allowing for correlations between various phenomena, independent of whether or not that specific phenomena are part of the validated model. In this manner, the validated model is a tool for a-posteriori benchmarking, and not a model designed to replicate the experimental output exactly for any specific experiment. For experiments like the Clark (2015) experiments, this integrated model (including chemistry) demonstrated that the largest bias was associated in the metallurgy of the coupons. The model developed does serve as a basis for defending which of the historical alloys tested are the most appropriate for any other alloy being considered (e.g., one that has not yet been tested). The model identifies key reactions that impact uranium chemistry and can significantly bias experimental results. Through use of the model and energy balances, data from historical experiments by Elder and Tinkle (1980) were regressed and benchmarked. This study identifies that all uranium alloys are not equal and that there are distinct differences between the dominant alloys representing distinct metallurgical phases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2001

Modeling of Multi-Tube Pulse Detonation Engine Operation

The present paper explores some preliminary issues concerning the operational characteristics of multiple-tube pulsed detonation engines (PDEs). The study is based on a two-dimensional analysis of the first-pulse operation of two detonation tubes exhausting through a common nozzle. Computations are first performed to assess isolated tube behavior followed by results for multi-tube flow phenomena. The computations are based on an eight-species, finite-rate transient flow-field model. The results serve as an important precursor to understanding appropriate propellant fill procedures and shock wave propagation in multi-tube, multi-dimensional simulations. Differences in behavior between single and multi-tube PDE models are discussed, The influence of multi-tube geometry and the preferred times for injecting the fresh propellant mixture during multi-tube PDE operation are studied.

Ebrahimi, Houshang B.↗
DOE OSTI2026

Livewire: A Model Platform for Data Quality Assessment and AI Readiness Across DOE Missions

High-quality, well-governed data is essential for accelerating discovery and achieving operational excellence across DOE and national laboratory missions. The Livewire Data Platform is a DOE-supported platform that offers automated assessments of data quality, standardization, provenance, and Artificial Intelligence (AI) readiness. It allows researchers and data practitioners to systematically and easily evaluate datasets against established governance criteria and prepare them for advanced analytics. Livewire addresses critical challenges in DOE's data ecosystem with integrated capabilities for metadata validation, provenance tracking, and schema alignment. This platform's automated workflows assist users in identifying data quality gaps, enhancing interoperability between datasets collected from various stakeholders, and ensuring compliance with DOE data standards, all while reducing manual curation efforts. Additionally, we will discuss its AI readiness framework, which is being developed to prepare datasets for training models, developing advanced analytic tools, and machine learning applications. Using some of the more than one hundred tabular datasets on Livewire, processed with this open-source methodology, we will demonstrate how Livewire can serve as a model for scalable, standards-driven data management. This approach provides a pathway to leverage existing and future datasets within the DOE, boosting innovation and efficiency across national laboratories.

33 - ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Towards a robust out-of-the-box neural network model for genomic data

The accurate prediction of biological features from genomic data is paramount for precision medicine and sustainable agriculture. For decades, neural network models have been widely popular in fields like computer vision, astrophysics and targeted marketing given their prediction accuracy and their robust performance under big data settings. Yet neural network models have not made a successful transition into the medical and biological world due to the ubiquitous characteristics of biological data such as modest sample sizes, sparsity, and extreme heterogeneity. Here, we investigate the robustness, generalization potential and prediction accuracy of widely used convolutional neural network and natural language processing models with a variety of heterogeneous genomic datasets. Mainly, recurrent neural network models outperform convolutional neural network models in terms of prediction accuracy, overfitting and transferability across the datasets under study. While the perspective of a robust out-of-the-box neural network model is out of reach, we identify certain model characteristics that translate well across datasets and could serve as a baseline model for translational researchers.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2011

Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation

An emerging approach in the field of aircraft engine controls and system health management is the inclusion of real-time, onboard models for the inflight estimation of engine performance variations. This technology, typically based on Kalman-filter concepts, enables the estimation of unmeasured engine performance parameters that can be directly utilized by controls, prognostics, and health-management applications. A challenge that complicates this practice is the fact that an aircraft engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. Through Kalman-filter-based estimation techniques, the level of engine performance degradation can be estimated, given that there are at least as many sensors as health parameters to be estimated. However, in an aircraft engine, the number of sensors available is typically less than the number of health parameters, presenting an under-determined estimation problem. A common approach to address this shortcoming is to estimate a subset of the health parameters, referred to as model tuning parameters. The problem/objective is to optimally select the model tuning parameters to minimize Kalman-filterbased estimation error. A tuner selection technique has been developed that specifically addresses the under-determined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine that seeks to minimize the theoretical mean-squared estimation error of the Kalman filter. This approach can significantly reduce the error in onboard aircraft engine parameter estimation applications such as model-based diagnostic, controls, and life usage calculations. The advantage of the innovation is the significant reduction in estimation errors that it can provide relative to the conventional approach of selecting a subset of health parameters to serve as the model tuning parameter vector. Because this technique needs only to be performed during the system design process, it places no additional computation burden on the onboard Kalman filter implementation. The technique has been developed for aircraft engine onboard estimation applications, as this application typically presents an under-determined estimation problem. However, this generic technique could be applied to other industries using gas turbine engine technology.

Simon, Donald L.↗
DOE OSTI2021

Plant-microbe interactions: from genes to ecosystems using Populus as a model system

Plant-microbe symbioses span a continuum from pathogenic to mutualistic with functional consequences for both organisms in the symbiosis. In order to increase sustainable food and fuel production in the future, it is imperative that we harness these symbioses. The tree genus Populus is an excellent model system for studies examining plant-microbe interactions due to the wealth of genomic information available and the molecular tools that have been developed to manipulate Populus-microbe symbioses. In this review, we highlight how Populus can serve as a model system to explore plant-microbe interactions. Specifically, highlighting research linking Populus-microbe interactions from the gene to the ecosystem level. We explore why Populus is an excellent model for perennial plant systems, the molecular underpinnings of Populus-microbe interactions, how host genetics influence microbial community composition, and how microbial communities vary at fine spatial scales and between Populus species. Further, we explore how the patterns of the microbiome may affect ecosystem level functions in managed and natural ecosystems. Understanding and manipulating these interactions in Populus has the potential to improve plant health and impact ecosystem sustainability and processes as Populus trees function as foundational species in many natural ecosystems and are also deployed in managed ecosystems for various agroforestry applications.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1997

Project Synopsis for High School/High Tech

To help increase the diversity of workers at NASA centers it is necessary to provide students with disabilities the opportunities to explore careers in high technology. HIGH SCHOOL/HIGH TECH, an enrichment program, pioneered at Goddard Space Flight Center, successfully introduces students with disabilities to high tech careers. This community-based partnership serves as a model for three additional NASA sites-Ames Research Center, Johnson Space Flight Center, and Lewis Research Center. For a three year period beginning August 15, 1995, provide financial and technical support to a local agency in each NASA center area which serves persons with disabilities to enable a High School/High Tech program to develop and stand alone. Each project will develop a basis of cooperation with Ames, Johnson, and Lewis as well as a variety of community groups including the public schools, high tech employers, post-secondary education and training programs, rehabilitation agencies, and community economic development organizations. Throughout the startup period and thereafter, local youths with disabilities will have early exposure to professions in mathematics, science, and technology-related fields. This exposure will be multifaceted to insure adequate opportunity for realistic career exploration so these youths have an opportunity to test their interests and abilities. The exposure will be presented in the most supportive environment that is feasible.

Source record↗