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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Measurement of strains at high temperatures by means of a portable holographic moire camera

Electronic holographic moire is utilized to measure strains at temperatures up to 1000 C. A CW laser operating at 50 mW and at the wavelength of 632.8 nm is used to illuminate the objects under study. The main variables influencing the fringe patterns visibility are discussed and measurements are performed to obtain the values of these variables in the performed experiments. The coefficient of expansion of an alloy is measured at temperatures ranging from 797 C to 986 C. Excellent agreement is found between the measured values and those provided by the manufacturer.

Sciammarella, C. A.↗
NASA NTRS1998

Inverse Compton Scattering in Mildly Relativistic Plasma

We investigated the effect of inverse Compton scattering in mildly relativistic static and moving plasmas with low optical depth using Monte Carlo simulations, and calculated the Sunyaev-Zel'dovich effect in the cosmic background radiation. Our semi-analytic method is based on a separation of photon diffusion in frequency and real space. We use Monte Carlo simulation to derive the intensity and frequency of the scattered photons for a monochromatic incoming radiation. The outgoing spectrum is determined by integrating over the spectrum of the incoming radiation using the intensity to determine the correct weight. This method makes it possible to study the emerging radiation as a function of frequency and direction. As a first application we have studied the effects of finite optical depth and gas infall on the Sunyaev-Zel'dovich effect (not possible with the extended Kompaneets equation) and discuss the parameter range in which the Boltzmann equation and its expansions can be used. For high temperature clusters (k(sub B)T(sub e) greater than or approximately equal to 15 keV) relativistic corrections based on a fifth order expansion of the extended Kompaneets equation seriously underestimate the Sunyaev-Zel'dovich effect at high frequencies. The contribution from plasma infall is less important for reasonable velocities. We give a convenient analytical expression for the dependence of the cross-over frequency on temperature, optical depth, and gas infall speed. Optical depth effects are often more important than relativistic corrections, and should be taken into account for high-precision work, but are smaller than the typical kinematic effect from cluster radial velocities.

Molnar, S. M.↗
DOE OSTI2023

Interplanar Ferromagnetism Enhanced Ultrawide Zero Thermal Expansion in Kagome Cubic Intermetallic (Zr,Nb)Fe 2

A cubic metal exhibiting zero thermal expansion (ZTE) over a wide temperature window demonstrates significant applications in a broad range of advanced technologies but is extremely rare in nature. Here, enabled by high-temperature synthesis, we realize tunable thermal expansion via magnetic doping in the class of kagome cubic (Fd-3m) intermetallic (Zr,Nb)Fe 2 . A remarkably isotropic ZTE is achieved with a negligible coefficient of thermal expansion (+0.47 x 10 -6 K -1 ) from 4 to 425 K, almost wider than most ZTE in metals available. A combined in situ magnetization, neutron powder diffraction, and hyperfine Mössbauer spectrum analysis reveals that interplanar ferromagnetic ordering contributes to a large magnetic compensation for normal lattice contraction upon cooling. Trace Fe-doping introduces extra magnetic exchange interactions that distinctly enhance the ferromagnetism and magnetic ordering temperature, thus engendering such an ultrawide ZTE. Finally, this work presents a promising ZTE in kagome metallic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Uncertainty quantification for misspecified machine learned interatomic potentials

The use of high-dimensional regression techniques from machine learning has significantly improved the quantitative accuracy of interatomic potentials. Atomic simulations can now plausibly target quantitative predictions in a variety of settings, which has brought renewed interest in robust means to quantify uncertainties. In many practical settings where model complexity is constrained (e.g., due to performance considerations), misspecification — the inability of any one choice of model parameters to exactly match all training data — is a key contributor to errors that is often disregarded. Here, we employ a recent misspecification-aware regression technique to quantify parameter uncertainties, which is then propagated to a broad range of phase and defect properties in tungsten. The propagation is performed through both brute-force resampling and implicit Taylor expansion. The propagated misspecification uncertainties robustly quantify and bound errors on a broad range of material properties. We demonstrate application to recent foundational machine learning interatomic potentials, accurately predicting and bounding errors in MACE-MPA-0 energy predictions across the diverse materials project database.

36 MATERIALS SCIENCE↗
NASA NTRS1985

Volume and density changes of biological fluids with temperature

The thermal expansion of human blood, plasma, ultrafiltrate, and erythrocycte concentration at temperatures in the range of 4-48 C is studied. The mechanical oscillator technique which has an accuracy of 1 x 10 to the -5 th g/ml is utilized to measure fluid density. The relationship between thermal expansion, density, and temperature is analyzed. The study reveals that: (1) thermal expansion increases with increasing temperature; (2) the magnitude of the increase declines with increasing temperature; (3) thermal expansion increases with density at temperatures below 40 C; and (4) the thermal expansion of intracellular fluid is greater than that of extracellular fluid in the temperature range of 4-10 C, but it is equal at temperatures greater than or equal to 40 C.

Hinghofer-Szalkay, H.↗
NASA NTRS2004

Thermally Conductive Metal-Tube/Carbon-Composite Joints

An improved method of fabricating joints between metal and carbon-fiber-based composite materials in lightweight radiators and heat sinks has been devised. Carbon-fiber-based composite materials have been used in such heat-transfer devices because they offer a combination of high thermal conductivity and low mass density. Metal tubes are typically used to carry heat-transfer fluids to and from such heat-transfer devices. The present fabrication method helps to ensure that the joints between the metal tubes and the composite-material parts in such heat-transfer devices have both (1) the relatively high thermal conductances needed for efficient transfer of heat and (2) the flexibility needed to accommodate differences among thermal expansions of dissimilar materials in operation over wide temperature ranges. Techniques used previously to join metal tubes with carbon-fiber-based composite parts have included press fitting and bonding with epoxy. Both of these prior techniques have been found to yield joints characterized by relatively high thermal resistances. The present method involves the use of a solder (63 percent Sn, 37 percent Pb) to form a highly thermally conductive joint between a metal tube and a carbon-fiber-based composite structure. Ordinarily, the large differences among the coefficients of thermal expansion of the metal tube, solder, and carbon-fiber-based composite would cause the solder to pull away from the composite upon post-fabrication cooldown from the molten state. In the present method, the structure of the solder is modified (see figure) to enable it to deform readily to accommodate the differential thermal expansion.

Copeland, Robert J.↗
NASA NTRSDate not supplied

Informing Wildfire Needs: The Expanded User Interface of NASA's Fire Information for Resource Management System (Firms)

As the global community continues to experience, and respond to, living in a changing environment, access to tools, technologies, and timely data utilized by an increasingly diverse set of stakeholders is increasing. This year, 2023, has thus far seen an unprecedented number of extreme events, increasingly driven by changes in the climate and a strong 2023 ENSO pattern. In Canada, a record number of wildfires, and associated weather events, evacuations, and infrastructure and habitat destruction has taken place, and is ongoing. Large swaths of Greece have experienced similar wildfire destruction. Most recently, Maui has experienced destructive wildfires, and early 2023 saw massive wildfires in Chile. NASA's Fire Information for Resource Management System, or FIRMS, has a fifteen-year history of providing timely and comprehensive data and information on wildfires to stakeholders. FIRMS was initially developed in 2007 by the University of Maryland, with funds from NASA's Applied Sciences Program and the United Nations Food and Agriculture Organization (UN FAO), to provide near real-time active fire Locations to natural resource managers that faced challenges obtaining timely satellite-derived fire information. FIRMS has consistently evolved to address the needs of stakeholders Living in a changing environment; in 2012 it transitioned to NASA LANCE and in 2021 through a partnership between NASA and the US Forest Service, an updated version of FIRMS was released for the US and Canada. As NASA and other federal agencies continue to accelerate Open Science through integrated efforts such as the Year of Open Science, the provision of readily discoverable, findable, accessible, interoperable, reusable data represents a major focus to facilitate equitable outcomes. FIRMS supports this acceleration in Open Science by continuing to provision data and information for its traditional user base, while addressing the novel user needs of an increasingly diverse set of stakeholders seeking robust, reliable, transparently generated data and information. Increasingly, FIRMS is utilized by citizen scientists and individuals directly affected by wildfires - through evacuations, risks to structures/homes, poor air quality. etc. FIRMS has also been Leveraged to detect and assess the impacts resulting from ongoing conflicts. This further highlights the multi-faceted impacts of wildfires and other events. In the Fall of 2023, FIRMS will release an expanded User Interface (UI). This interface captures and reflects the needs of, and input from, a multitude of users. These users range from federal agency representatives to non-government organizations to the private sector to citizen science entities. To respond to this expansive and diverse user need base, the updated FIRMS UI will capture a range of features to support those beginning to explore the range of data and tools available to inform wildfire awareness and knowledge. These users are supported through a Basic Mode interface, furnishing access to a light set of functionalities that provision straight-forward, readily usable information and data, and ingestible knowledge. The Advanced Mode interface supports those stakeholder groups already proficient in navigating FIRMS. These stakeholders, representing fire managers and others, perform active fire management and tactical wildfire response activities. For these stakeholders, additional datasets have been included which require in-depth knowledge of both the utility as well as the caveats of such datasets. Additional functionalities have also been embedded to aid specific user queries. The expanded UI will introduce a new Experimental Mode. The focus of this UI will be to support the provision of emerging and innovative datasets that are in development for review and comment by the user community Examples include post-fire products generated by NASA's Earth Information System (EIS) Fire. This presentation will provide an overview of the expanded FIRMS UI. We will discuss how this UI is designed to be scalable and support the unique needs of an expanding and diverse user base. We will highlight key features, elements, and datasets, and describe how user needs have informed and guided the design of the UI. We will also share recent use cases to convey, and increase awareness, among conference participants. As the global community faces more extreme wildfires, due to climate variability and change, there is an increased need for reliable data to inform, manage, and mitigate the impacts of these events. Through this work, NASA FIRMS is striving to level the playing field, by making information accessible to all; from policy makers to the private sector to historically marginalized communities. In doing so, NASA is promoting the all-hands-on-deck response needed to minimize the impacts of wildfires and harness the strengths of open science to address the greatest environmental challenge faced.

Jenny Hewson↗
NASA NTRS1991

Expansion-cooled Lyman-alpha clouds

It is shown that recent observations by Pettini et al. (1990) which indicate that low-N H I Ly-alpha forest lines have small velocity widths and that the velocity widths are positively correlated with N (H I) can be understood as the result of adiabatic cooling of expanding clouds. It is argued that expansion cooling can efficiently lower temperatures and velocity widths of diffuse ionized clouds, and that this trend of diminishing temperature and velocity width in a wide range of plausible cloud models is consistent with double-quasar data. Expansion can provide a natural explanation for the steep z-evolution of the cloud numbers.

Duncan, Robert C.↗
NASA NTRS1976

Observations of the Gum Nebula with a Fabry-Perot spectrometer

Scans have been made of H-alpha, 6584-A forbidden N II, 5007-A forbidden O III, and 5876-A He I emissions in selected directions in the Gum Nebula. Analyses of the line profiles and line intensities indicate that much of the emitting gas in the Gum Nebula is confined to an expanding shell which has a radius of about 125 pc, an expansion velocity of approximately 20 km/s, an emission measure which ranges from about 15 units to about 500 units, and a temperature near 11,000 K. The ultraviolet flux from zeta Pup and gamma-2 Vel appears to be capable of producing most of the observed ionization, although the origin of the shell structure and high expansion velocity is not certain.-

Reynolds, R. J.↗
NASA NTRS1988

Thermal expansion measurements of metal matrix composites

The laser-interferometric-dilatometer system currently operational at NASA-Langley is described. The system, designed to characterize metal matrix composites, features high precision, automated data acquisition, and the ability to test a wide variety of specimen geometries over temperature ranges within 80-422 K. The paper presents typical thermal-expansion measurement data for a Gr/Al rod; Gr/Al and Gr/Mg unidirectional laminates; and a Gr/Mg (+ or -8)s laminate.

Tompkins, Stephen S.↗
NASA NTRS1992

Heat transfer in oscillating flows with sudden change in cross section

Oscillating fluid flow (zero mean) with heat transfer, between two parallel plates with a sudden change in cross section, was examined computationally. Over 30 different cases were examined; these cases cover wide ranges of Re sub max (187.5 to 30,000), Va (1 to 350), expansion ratio (1:2, 1:4, 1:8, and 1:12) and A sub r (0.68 to 4). Three different geometric cases were considered (asymmetric expansion and/or contraction, symmetric expansion/contraction, and symmetric blunt body). The heat transfer cases were based on constant wall temperature at higher (heating) or lower (cooling) value than the inflow fluid temperature. As a result of the oscillating flow, the fluid undergoes sudden expansion in one half of the cycle and sudden contraction in the other half. Instantaneous friction factors and heat transfer coefficients, for some ranges of Re sub max and Va, deviated substantially from those predicted with steady state correlations.

Ibrahim, Mounir↗
DOE OSTI2026

Validity of a finite temperature expansion for dense nuclear matter

In this work we provide a new, well-controlled expansion of the equation of state of dense matter from zero to finite temperatures (𝑇) while covering a wide range of charge fractions (𝑌 𝑄 ), from pure neutron to isospin symmetric nuclear matter. Our expansion can be used to describe neutron star mergers using the equation of state inferred from neutron star observations. We discuss how knowledge from low-energy nuclear experiments and heavy-ion collisions can be directly incorporated into the expansion. We also suggest new thermodynamic quantities of interest that can be calculated from theoretical models or directly inferred by experimental data that can be used to infer the finite temperature equation of state. With our new method, we can quantify the uncertainty in our finite 𝑇 and 𝑌 𝑄 expansions without making assumptions about the underlying degrees of freedom. We can reproduce results from a microscopic equation of state up to 𝑇 = 100 MeV for baryon chemical potential 𝜇 𝐵 ≳ 1100 MeV [≈(1–2)⁢𝑛 sat ] within 5% error, with even better results for larger 𝜇 𝐵 and/or lower 𝑇. We investigate the sources of numerical and theoretical uncertainty and discuss future directions of study.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1991

The evolution of field-aligned currents as a function of substorm phase

The average ionospheric extrapolated characteristics and properties of region 1 and 2 currents are determined as a function of the substorm phase via an examination of ISEE 1 and 2 measurements of magnetic changes across nightside field-aligned currents at middle altitudes in the inner magnetosphere. The properties of these currents under consideration include current intensity, density, layer width, and velocity, and they are consistent with earlier studies at lower altitudes. During a substorm, region 1 current intensity ranges from 0.4 to 0.6 A/m and peaks during the expansion phase. Region 2 intensity varies from 0.15 to 0.35 A/m and reaches a maximum during recovery. The density of region 2 currents remains essentially steady at 1.4 microamp/sq m, while region 1 decreases from 5 to 1.3 microamp/sq m. The width of these current sheets throughout a substorm remains in the range from 100 to 500 km. It is concluded that substorms play a major role in the generation of the nightside region 1 and 2 currents detected by the ISEE spacecraft.

Chun, Francis K.↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

42 ENGINEERING↗
NASA NTRS1993

Oscillating flow and heat transfer in a channel with sudden cross section change

We have computationally examined oscillating flow (zero mean) between two parallel plates with a sudden change in cross section. The flow was assumed to be laminar incompressible with the inflow velocity uniform over the channel cross section but varying sinusoidally with time. The cases studied cover wide ranges of Re(sub max) (from 187.5 to 2000), Va (from 1 to 10.66), the expansion ratio (1:2 and 1:4) and A(sub r) (2 and 4). Also, three different geometric cases were discussed: (1) asymmetric expansion/contraction; (2) symmetric expansion/contraction; and (3) symmetric blunt body. For these oscillating flow conditions, the fluid undergoes sudden expansion in one-half of the cycle and sudden contraction inthe other half. The instantaneous friction factor, for some ranges of Re(sub max) and Va, deviated substantially from the steady-state friction factor for the same flow parameters. A region has been identified below which the flow is laminar quasi-steady. A videotape showing computer simulations of the oscillating flow demonstrates the usefulness of the current analyses in providing information on the transient hydraulic phenomena.

Ibrahim, Mounir↗
DOE OSTI2023

Expanded modelling scenarios to understand the role of offshore wind in decarbonizing the United States

An assessment of decarbonization pathways in energy models reveals fundamental limitations in representing factors that are relevant for practical decision-making. Although these modelling limitations are widely acknowledged, their impact on the deployment of individual power generation types is not well understood. As a result, the societal value from such generation types could be vastly misrepresented. Here we explore a wide spectrum of factors that impact offshore wind deployment in the United States using a detailed capacity expansion model. Many factors prescribe a large future role for offshore wind, yet this diverges from what models often show. We extend the typically narrow modelling context through high spatial resolution, several cost and transmission possibilities and various energy-sector policies. Further, we estimate offshore wind to constitute 1-8% (31-256 gigawatts) of total US generation by 2050. This wide range suggests an uncertain but potentially important regional role. Our expansive scenarios demonstrate how to address many limitations of decarbonization modelling.

17 WIND ENERGY↗