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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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334 records · Page 13

Pressurized-Cell Experiment

Pressurized-cell detectors were developed and constructed at the Langley Research Center to obtain a direct measurement of the micrometeoroid puncture hazard to thin structural material. A total of 160 detectors were mounted around the periphery of the rocket motor used on the Explorer XIII satellite. (See fig. IX-1.) Material thicknesses of 0.001, 0.0015, 0.002, 0.0025, and 0.005 inch were used on the detectors. The exposed surface of the test material of each detector was 21.8 square inches and the total exposed surface of the 160 detectors was 24.2 square feet. The average weight of the detectors was 68 grams.

Micrometeoroid

Evaluation of Ultrasonic Battery Inspection Techniques

Lithium metal batteries are prone to subtle defects such as internal dendrites, which can cause internal short circuits and lead to catastrophic ignition. These defects are often undetectable by battery management systems, prompting the need to advance nondestructive evaluation (NDE) techniques for battery applications. In this work, two ultrasonic approaches were compared to establish their relative merits for this application: local ultrasonic resonance spectroscopy, and guided wave ultrasound. Benchtop experiments on batteries seeded with lithium chips emulating plating were used to demonstrate the two techniques. The results show the ability to identify and map local changes in cell structure.

Ultrasound

Numerical Predictions of the Flow and Heat Transfer Characteristics in the Film Boiling Regime During Tube Quenching

Cryogenic fluid management plays a major role in refueling of spacecrafts while in space for NASA’s future human space exploration missions. Due to the low boiling points of cryogens, storage, transport and handling of these fluids becomes difficult and may result in inefficient operation of the space propulsion systems. For refueling applications in space, the cryogenic fluids have to be transported across different locations and hence, the transfer of cryogenic fluids through pipes become critical. The cryogenic chill-down process is characterized by different regimes of flow boiling, viz., film boiling, transition boiling and nucleate boiling. The prediction of these regimes in a single CFD framework available in the literature is challenging and the present work attempts to address this challenge by initially modeling the film boiling regime accurately and to incorporate an user-defined function for transition and nucleate boiling at a later stage. Hence, the aim of the present work is to numerically model and validate the film boiling regime of the chilldown curve for liquid nitrogen experiments available in the literature. The validations are carried out at different inlet mass fluxes to have a robust simulation methodology. A dispersed mixture model is used to predict the vapor-liquid interface dynamics with the phase change phenomena modeled using the Lee model.

line chilldown

Evaluation of Ultrasonic Battery Inspection Techniques

Lithium metal batteries are prone to subtle defects such as internal dendrites, which can cause internal short circuits and lead to catastrophic ignition. These defects are often undetectable by battery management systems, prompting the need to advance nondestructive evaluation (NDE) techniques for battery applications. In this work, two ultrasonic approaches were compared to establish their relative merits for this application: local ultrasonic resonance spectroscopy, and guided wave ultrasound. Benchtop experiments on batteries seeded with lithium chips emulating plating were used to demonstrate the two techniques. The results show the ability to identify and map local changes in cell structure.

Ultrasound

The Growth of Zeolites A, X and Mordenite in Space

Zeolites are a class of crystalline aluminosilicate materials that form the backbone of the chemical process industry worldwide. They are used primarily as adsorbents and catalysts and support to a significant extent the positive balance of trade realized by the chemical industry in the United States (around $19 billion in 1991). The magnitude of their efforts can be appreciated when one realizes that since their introduction as 'cracking catalysts' in the early 1960's, they have saved the equivalent of 60 percent of the total oil production from Alaska's North Slope. Thus the performance of zeolite catalysts can have a profound effect on the U.S. economy. It is estimated that a 1 percent increase in yield of the gasoline fraction per barrel of oil would represent a savings of 22 million barrels of crude oil per year, representing a reduction of $400 million in the United States' balance of payments. Thus any activity that results in improvement in zeolite catalyst performance is of significant scientific and industrial interest. In addition, due to their 'stability,' uniformity, and, within limits, their 'engineerable' structures, zeolites are being tested as potential adsorbents to purify gases and liquids at the parts-per-billion levels needed in today's electronic, biomedical, and biotechnology industries and for the environment. Other exotic applications, such as host materials for quantum-confined semiconductor atomic arrays, are also being investigated. Because of the importance of this class of material, extensive efforts have been made to characterize their structures and to understand their nucleation and growth mechanisms, so as to be able to custom-make zeolites for a desired application. To date, both the nucleation mechanics and chemistry (such as what are the 'key' nutrients) are, as yet, still unknown for many, if not all, systems. The problem is compounded because there is usually a 'gel' phase present that is assumed to control the degree of supersaturation, and this gel undergoes a continuous 'polymerization' type reaction during nucleation and growth. Generally, for structure characterization and diffusion studies, which are useful in evaluating zeolites for improving yield in petroleum refining as well as for many of the proposed new applications (e.g., catalytic membranes, molecular electronics, chemical sensors) large zeolites (greater than 100 to 1000 times normal size) with minimum lattice defects are desired. Presently, the lack of understanding of zeolite nucleation and growth precludes the custom design of zeolites for these or other uses. It was hypothesized that the microgravity levels achieved in an orbiting spacecraft could help to isolate the possible effects of natural convection (which affects defect formation) and minimize sedimentation, which occurs since zeolites are twice as dense as the solution from which they are formed. This was expected to promote larger crystals by allowing growing crystals a longer residence time in a high-concentration nutrient field. Thus it was hypothesized that the microgravity environment of Earth orbit would allow the growth of large, more defect-free zeolite crystals in high yield.

A Sacco, Jr

Concept to Reality: Contributions of the Langley Research Center to US Civil Aircraft of the 1990s

This document is intended to be a companion to NASA/SP-2000-4519, Partners in Freedom: Contributions of the Langley Research Center to U.S. Military Aircraft of the 1990s . Material included in the combined set of volumes provides informative and significant examples of the impact of Langley's research on U.S. civil and military aircraft of the 1990s. This volume, 'Concept to Reality: Contributions of the NASA Langley Research Center to U.S. Civil Aircraft of the 1990s', highlights significant Langley contributions to safety, cruise performance, takeoff and landing capabilities, structural integrity, crashworthiness, flight deck technologies, pilot-vehicle interfaces, flight characteristics, stall and spin behavior, computational design methods, and other challenging technical areas for civil aviation. The contents of this volume include descriptions of some of the more important applications of Langley research to current civil fixed-wing aircraft (rotary-wing aircraft are not included), including commercial airliners, business aircraft, and small personal-owner aircraft. In addition to discussions of specific aircraft applications, the document also covers contributions of Langley research to the operation of civil aircraft, which includes operating problems. This document is organized according to disciplinary technologies, for example, aerodynamics, structures, materials, and flight systems. Within each discussion, examples are cited where industry applied Langley technologies to specific aircraft that were in operational service during the 1990s and the early years of the new millennium. This document is intended to serve as a key reference for national policy makers, internal NASA policy makers, Congressional committees, the media, and the general public. Therefore, it has been written for a broad general audience and does not presume any significant technical expertise. An extensive bibliography is provided for technical specialists and others who desire a more in-depth discussion of the contributions.

NASA History Series

Laser Beam Welding Advancements for In-Space Servicing, Assembly, and Manufacturing

NASA is currently working to develop in-space servicing, assembly, and manufacturing (ISAM) capabilities for low Earth orbit and the lunar surface. One crucial technology for this effort is laser beam welding. Laser systems can perform joining, cleaning, cutting, and repair activities, which will enable the construction of large in-space structures that could not fit on a single launch vehicle, such as trusses for solar panels, radiators, or communications infrastructure. Multiple projects studying laser welding for space applications are currently underway at NASA Marshall Space Flight Center. One of these, the DIsk-Shaped Configurable and Modular vAcuum uNit (DISCMAN), is a compact vacuum chamber designed to support parameter development for laser welding in microgravity. It contains a rotating platen with weld samples made from aluminum, steel, and titanium, a high-power infrared laser, and integrated pumps for pulling vacuum inside the sample cartridge. The DISCMAN payload is planned to launch to the International Space Station, where welds will be performed under sustained microgravity inside the Bishop Airlock. Another effort underway at Marshall is the Lunar Assembly and Servicing by Autonomous Robotics (LASAR) initiative. This project uses a space-rated robotic arm equipped with a laser weld head, wire feeder, and multiple cameras to perform welds in a thermal vacuum chamber simulating the lunar surface environment. Some of these welds are done on snowflake joints, which are specially designed to slot together to join segments of trussN structures, allowing for the construction of tall surface infrastructure. DISCMAN, LASAR, and other projects are being carried out to advance the technological maturity of in-space laser beam welding, collect data to inform computational models, and learn reliable processes for creating weld joints in space. This work supports NASA’s greater goals to expand humanity’s presence in low Earth orbit, establish a permanent moon base, and eventually send crewed missions to Mars and beyond.

Robotics

Laser Beam Welding Advancements for In-Space Servicing, Assembly, and Manufacturing

NASA is currently working to develop in-space servicing, assembly, and manufacturing (ISAM) capabilities for low Earth orbit and the lunar surface. One crucial technology for this effort is laser beam welding. Laser systems can perform joining, cleaning, cutting, and repair activities, which will enable the construction of large in-space structures that could not fit on a single launch vehicle, such as trusses for solar panels, radiators, or communications infrastructure. Multiple projects studying laser welding for space applications are currently underway at NASA Marshall Space Flight Center. One of these, the DIsk-Shaped Configurable and Modular vAcuum uNit (DISCMAN), is a compact vacuum chamber designed to support parameter development for laser welding in microgravity. It contains a rotating platen with weld samples made from aluminum, steel, and titanium, a high-power infrared laser, and integrated pumps for pulling vacuum inside the sample cartridge. The DISCMAN payload is planned to launch to the International Space Station, where welds will be performed under sustained microgravity inside the Bishop Airlock. Another effort underway at Marshall is the Lunar Assembly and Servicing by Autonomous Robotics (LASAR) initiative. This project uses a space-rated robotic arm equipped with a laser weld head, wire feeder, and multiple cameras to perform welds in a thermal vacuum chamber simulating the lunar surface environment. Some of these welds are done on snowflake joints, which are specially designed to slot together to join segments of trussN structures, allowing for the construction of tall surface infrastructure. DISCMAN, LASAR, and other projects are being carried out to advance the technological maturity of in-space laser beam welding, collect data to inform computational models, and learn reliable processes for creating weld joints in space. This work supports NASA’s greater goals to expand humanity’s presence in low Earth orbit, establish a permanent moon base, and eventually send crewed missions to Mars and beyond.

Manufacturing

Aerothermal Shape Optimization of Actively-Cooled Battery Packs Using Conjugate Heat Transfer

Thermal management for battery is important for electric aircraft because battery temperature is critically important to vehicle safety, and it also has direct impact on the efficiency of the battery system. Because ambient air is a readily available resource for aircraft, this paper considers an active cooling concept with forced convection of ambient air through the battery pack. Conjugate heat transfer analysis is used to solve the coupled aero-thermal problem, which consists of a finite-volume computational fluid dynamics solver for the fluid domain, and a conduction heat transfer solver for the solid domain. A mixed Neumann and Dirichlet boundary condition is developed for the fluid-solid interface, which allows the solid domain to completely submerge in the fluid domain. A gradient-based optimization method is adopted, and the discrete adjoint approach implemented in DAFoam is used to efficiently compute the gradients. The aero-thermal coupling for primal analysis and gradient computation is handled using the OpenMDAO-based MPhys framework. A constant heat source is prescribed for the battery cells, and the battery shape (design variable) is optimized to minimize cooling pump power and battery weight (composite objective function) while keeping the battery temperature below a threshold (constraint). The optimized design achieves a 44.6% and 1.5% reduction in the cooling pump power and battery weight, respectively, and the maximal temperature constraint is satisfied. This work has the potential to reduce battery-pack weight, improve performance, and reduce the weight of thermal management systems for electric vertical take-off and landing aircraft.

heat transfer

Riddles About the Origin and Thermal History of the Moon

Analyses of lunar rocks have confirmed that the interior of the Moon has been subjected to magmatic differentiation, as has been determined by calculation of the thermal history of the Moon. However, it appears that differentiation occurred so early that it could not have been related to heating by long-lived radioactive elements, but rather indicates a high initial temperature of the Moon. The reasons for the high initial temperature remain unknown. The presence of a central, partially melted area revealed by seismic observations forces us to reject convective models of the Moon, while the dimensions of this area, together with the measured heat fluxes from the interior, serve as "boundary conditions" for any new calculations of the thermal history for a two-layered differentiated model of the Moon operative over the past 3.5 billion years. If we start with the early differentiation of the Moon and the high content of long-lived radioactive elements in it, explanation of its current thermal properties represents no difficulty. But these prerequisites themselves remain unexplained. Due to the continuing controversy concerning the true nature of the process of magmatic differentiation of the Moon, estimation of the composition of the entire Moon on the basis of analyses of surface rock remains unreliable, and use of these estimates to clarify the origin of the Moon is premature. Existing hypotheses concerning the origin of the Moon encounter dynamic difficulties, as well as difficulties with explanation of the high initial temperature, to say nothing of the difficulty involved in explaining the proposed differences in the composition of the Earth and Moon.

B Yu Levin

Aerothermal Shape Optimization of Actively-Cooled Battery Packs using Conjugate Heat Transfer

Thermal management for battery is important for electric aircraft because battery temperature is critically important to vehicle safety, and it also has direct impact on the efficiency of the battery system. Because ambient air is a readily available resource for aircraft, this paper considers an active cooling concept with forced convection of ambient air through the battery pack. Conjugate heat transfer analysis is used to solve the coupled aero-thermal problem, which consists of a finite-volume computational fluid dynamics solver for the fluid domain, and a conduction heat transfer solver for the solid domain. A mixed Neumann and Dirichlet boundary condition is developed for the fluid-solid interface, which allows the solid domain to completely submerge in the fluid domain. A gradient-based optimization method is adopted, and the discrete adjoint approach implemented in DAFoam is used to efficiently compute the gradients. The aero-thermal coupling for primal analysis and gradient computation is handled using the OpenMDAO-based MPhys framework. A constant heat source is prescribed for the battery cells, and the battery shape (design variable) is optimized to minimize cooling pump power and battery weight (composite objective function) while keeping the battery temperature below a threshold (constraint). The optimized design achieves a 44.6% and 1.5% reduction in the cooling pump power and battery weight, respectively, and the maximal temperature constraint is satisfied. This work has the potential to reduce battery-pack weight, improve performance, and reduce the weight of thermal management systems for electric vertical take-off and landing aircraft.

thermal management

Insertion Loss and Noise-Temperature Contribution of High-Temperature Superconducting Bandpass Filters Centered at 2.3 and 8.45 GHz

Two superconducting Tl-Ca-Cu-Ba-O bandpass filters were fabricated for JPL by Superconductor Technologies Incorporated, Santa Barbara, California. The filters were designed to operate at 2.3 GHz (S-band) with a 0.5-dB bandwidth of 60 MHz and at 8.45 GHz (X-band) with a 0.5-dB bandwidth of 150 MHz. The structure selected for both filters incorporates half-wavelength thin-film resonators in a stripline configuration. The S-band filter uses an edge-coupled interdigital design and the X-band filter uses an end-coupled design. The insertion loss and the noise-temperature contribution were measured at 12 K for both filters.

J L Prater

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database

The NASA Turbulent Heat Flux (THX) Experiments: Summary and Lessons Learned

The Turbulent Heat Flux (THX) experiments were conducted at NASA Glenn Research Center (GRC) in order to collect measurements of velocities and temperatures for computational fluid dynamics (CFD) validation of heated flows, with a focus on propulsion system components. The experiments spanned 5 phases; four of which were conducted in the GRC AeroAcoustic Propulsion Laboratory (AAPL) using the Small Hot Jet Flow Rig (SHJAR). In addition to making velocity measurements with Particle Image Velocimetry (PIV), the THX experiments introduced a new Raman-scattering based capability to measure temperatures. Computational studies were also conducted for each of the experimental configurations, in order to provide a baseline of expected CFD results and conduct an assessment of the capability of various CFD approaches for calculating flows where the turbulent transport of heat was important. Two of the collected sets of data were used for American Institute of Aeronautics and Astronautics (AIAA) Propulsion Aerodynamic Workshops (PAWs). The data set from the 5th phase, collected for heated supersonic jets, was also used to construct new validation cases for the NASA Turbulence Model Resource (TMR). This paper provides an overview of the experiments and associated computations for each of the 5 test phases. Key experimental findings are presented. Lessons learned are provided concerning the effect of computational modeling choice on accuracy of predicting turbulent flows where thermal transport is important. Emphasis is placed on comparing Reynolds-averaged Navier-Stokes approaches with large-eddy simulation approaches. The benefits of utilizing a conjugate heat transfer method in conjunction with CFD solver for film cooling is demonstrated.

RANS

Proactive Wildfire Management: A Remote Sensing and Multimodal CNN-MLP Architecture for Ignition Risk Forecasting

As the frequency and intensity of wildfires increase, with fire seasons now starting earlier and ending later than they have over the past decades, current monitoring systems, such as lookout towers and satellites, are hindered by cloud cover, low-resolution imagery, and static data gaps that fail to track vegetation moisture levels fast enough to catch rapid pre-ignition changes. This report proposes a Machine Learning-enabled Wildfire Ignition Prediction framework that combines satellite monitoring with dynamic and high-resolution remote sensing from Unmanned Aerial Vehicle (UAV) swarms. The method would use multispectral and thermal data from the Landsat program to create a baseline for vegetation health, calculating a two-band Enhanced Vegetation Index (EVI2) and the moisture content of the vegetation. These inputs will later be fused with microscale UAV weather data, including thermal hotspots found through thick canopies, hyperspectral chemical signatures of pre-visual combustion, and local weather streams. The multispectral satellite, multispectral Light Detection and Ranging (LiDAR), and thermal data would then be processed through a Convolutional Neural Network (CNN), alongside a Multilayer Perceptron (MLP) for the micro-weather telemetry. The outputs of these networks would be fused into a single feature representation and passed through a final prediction network to generate real-time ignition risk scores and hotspot alerts. Model performance would be assessed using standard classification metrics, including a Receiver Operating Characteristic - Area Under the Curve (ROC AUC) and F1 score. This system would allow first responders to identify high-risk zones and intervene before ignition occurs, improving emergency response time compared to current approaches.

machine learning

Turbomachinery Simulation Impact on Design, Understanding, and Optimization

This presentation shows the impact of Turbomachinery Simulation from simple analytical simulation to high fidelity CFD and Finite Element Analysis on the design of turbomachinery and the understanding of flow physics that is then used to improve design approaches. The impact of Optimization is also presented. The best approach for the tool development is to work with a compressor, fan, or turbine designer or to work on the design process directly. The presentation represents the work and impact of the author over his 45-year career and provides insight for both new and experienced engineers. The presentation explores applications of distortion from a downstream fan frame, the first uses of 3D CFD for fan, compressor and turbine design, and approaches to optimization for performance and structures.

optimization

Time-History Statistics of Soot Formation in A Model Gas Turbine Combustor

Soot formation is a complex dynamic and intermittent process determined by properties of the fuel, combustor design, and combustor operation. Although the major steps in soot formation (i.e., formation of precursors, inception, growth and evolution) are similar for a variety of carbonaceous fuels, applications, and operating conditions, it remains unclear when the temporal transition between these steps occurs. An engineering prediction tool coupled with computational fluid physics (CFD), therefore needs to accurately model all these complex steps. To develop such a model, we propose the time-history concept for understanding the time dependency of soot formation as a function of local properties (i.e., temperature, velocity, local fuel air ratio, etc.). We continue our previous work with modeling the DLR aero-combustor [1] with our updated in-house CFD code, Open National Combustion Code (OpenNCC), that now includes a Multiple Time-Scale Flamelet Progress Variable approach and a the semi-empirical two-equation soot model. We injected massless tracer particles upstream of the injector region of the combustor to collect time-history statistics of the solution variables. The correlations between the collected statistics with respect to the experimental soot volume fraction data showed that time-history effect of certain flow variables, including turbulent kinetic energy (TKE), and multiple species is indeed important for soot formation. We then conducted a time-history based correlation analysis to determine the key species and the concentration ranges critical for soot formation (C6H5-based nucleation, acetylene-based surface growth, and oxidation with OH and O2). Based on the time-history correlation coefficient (THCC) analysis, we propose possible modifications to improve the current two-equation model.

LES