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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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Charge-discharge controller contains punched-tape programmer capable of programming 305 discrete steps in the battery load. The indicating instrumentation includes meters for ampere-hours, watt-hours, voltage, current, and internal temperature and pressure. It also generates analog signals for recording the displayed data.
Lithium-ion (Li-ion) batteries can deliver electrical power across a large range of applications, and large format versions of these batteries are common in aerospace for their low mass and energy dense properties. Li-ion cells usage has increased as they are more power dense than fuel cells and have overall higher performance over lead-acid/NiCd batteries. However, Li-ion cells can experience Thermal Runaway (TR) via electro-chemical, mechanical, or thermal abuse. TR is a phenomenon where the stored energy in a cell is rapidly released along with vented gases and other effluents. A cell is generally determined to be in TR if its internal heat generation has surpassed its ability to dissipate that heat. If a Li-ion cell enters TR, propagation within the battery may occur. Propagation is the chain reaction that can occur to nearby cells due to a cell that has entered TR initially. Understanding a battery’s susceptiveness to propagation is necessary to evaluate risks associated with TR phenomenon. To determine if a battery is designed in a sufficient manner to prevent battery propagation if single cell TR occurs, testing and thermal analysis of the battery must be conducted. The presentation for TFAWS 2026 will cover considerations for battery TR thermal analysis, such as: testing methods, influences on the cells, failure mechanisms, and TR parameters. This presentation will include a walkthrough of an example battery TR thermal analysis, and the results thereof.
The NASA/OAST Telerobot Testbed will reach its next increment in development by the end of FY-89. The testbed will have the capability for: force reflection in teleoperation, shared control, traded control, operator designate and relative update. These five capabilities will be shown in a module release and exchange operation using mockups of Orbital Replacement Units (ORU). This development of the testbed shows examples of the technologies needed for remote servicing, particularly under conditions of delay in transmissions to the servicing site. Here, the following topics are presented: the system architecture of the testbed which incorporates these telerobotic technologies for servicing, the implementation of the five capabilities and the operation of the ORU mockups.
The effects of the space environment on the thermal expansion stability of metal matrix composites (graphite/Al and graphite/Mg) will be presented. A sample from each category of metal matrix composites mounted on the leading and trailing edge was chosen for analysis of the temperature-time-thermal strain histories. Typical thermal expansion curves over the same range of temperature were selected at the beginning, mid, and end of the recording duration. The thermal expansion of selected post-flight LDEF samples were measured over the same range of temperature in the laboratory using a Michelson laser interferometer. The thermal strains were monitored concurrently with a laser interferometer and a mounted strain gage.
Individual papers presented at the conference address the following topics: development of a micro-fiber nickel electrode for nickel-hydrogen cell, high performance nickel electrodes for space power application, bending properties of nickel electrodes for nickel-hydrogen batteries, effect of KOH concentration and anions on the performance of a Ni-H2 battery positive plate, advanced dependent pressure vessel nickel hydrogen spacecraft cell and battery design, electrolyte management considerations in modern nickel hydrogen and nickel cadmium cell and battery design, a novel unitized regenerative proton exchange membrane fuel cell, fuel cell systems for first lunar outpost - reactant storage options, the TMI regenerable solid oxide fuel cell, engineering development program of a closed aluminum-oxygen semi-cell system for an unmanned underwater vehicle, SPE OBOGS on-board oxygen generating system, hermetically sealed aluminum electrolytic capacitor, sol-gel technology and advanced electrochemical energy storage materials, development of electrochemical supercapacitors for EMA applications, and high energy density electrolytic capacitor.
This work presents a multiscale modeling approach to predict the fracture strength of fibrous Thermal Protection System (TPS) materials. The model assumes that system failure is initiated at the joints between individual fibers. We investigated three distinct TPS compositions: amorphous silica, alumina and aluminosilicate fibers. Molecular dynamics (MD) simulations were employed to determine the fracture strength values of these fiber joints for both material systems. These fracture strength values were then integrated into simulations of 3D randomly populated fiber structures, where tensile load transfer occurs through the fiber joints. These microscale properties are upscaled through a renormalization approach [1] to predict macroscale tensile strength of 3D random fiber networks, accounting for joint-dominated failure and effective load-bearing area. The study concludes by demonstrating the resulting strength variation as a function of material composition, fiber density, and morphology. We also show validation of results by comparing them against explicit fiber finite element (FE) modeling [2] where fiber joint fracture is represented by cohesive elements.
The Battery Failure Databank contains thermal runaway results gathered from nearly 300 small format fractional thermal runaway calorimetry (S-FTRC) experiments. A majority of these experiments were conducted at synchrotron facilities where high-speed x-ray videography was conducted of the cell while tested inside of the S-FTRC. The databank is a two-component system which consists of a Microsoft ExcelTM spreadsheet which provides S-FTRC results in tabular format and a radiographic video library containing the high-speed x-ray videos. Overall, the databank provides thermal results from S-FTRC experiments conducted on a mixture of commercially available lithium-ion (Li-ion) cells and specialized Li-ion test cells with varying cell format (18650, 21700, and D-cell) and trigger mechanism (heaters, heaters plus internal short circuiting device, and nail penetration). The radiography video component provides insight into the initiation and propagation of TR in the cells, in addition to consequences of TR measured by the FTRC. Fractions of mass ejected for the cell types are separated into regimes based on the different failure modes of the cells, such as purely venting, partial ejection, and total ejection. With knowledge of the rate and characterization of the internal degradation of the cells during TR, and the amounts of mass ejected and unrecovered, the extent of TR, and therefore the mitigation of TR, is revealed relative to cell types and failure modes.
A rechargeable lithium molybdenum disulfide battery which has a number of superior performance characteristics which includes a high energy density, a high power density, and a long charge retention time was developed. The first cell sizes developed included a C size cell and an AA size cell. Over the last two years, a project to demonstrate the feasibility of the scale up to this technology to a BC size cell with 65 Ah capacity was undertaken. The objective was to develop, build, and test a .6 kWh storage battery consisting of 6 BC cells in series.
High-power batteries generally consist of a series connection of many cells or cell banks. In order to maintain high performance over battery life, it is desirable to keep the state of charge of all the cell banks equal. A method provides individual charging for battery cells in a large, high-voltage battery array with a minimum number of transformers while maintaining reasonable efficiency. This is designed to augment a simple highcurrent charger that supplies the main charge energy. The innovation will form part of a larger battery charge system. It consists of a transformer array connected to the battery array through rectification and filtering circuits. The transformer array is connected to a drive circuit and a timing and control circuit that allow individual battery cells or cell banks to be charged. The timing circuit and control circuit connect to a charge controller that uses battery instrumentation to determine which battery bank to charge. It is important to note that the innovation can charge an individual cell bank at the same time that the main battery charger is charging the high-voltage battery. The fact that the battery cell banks are at a non-zero voltage, and that they are all at similar voltages, can be used to allow charging of individual cell banks. A set of transformers can be connected with secondary windings in series to make weighted sums of the voltages on the primaries.
Electrochemical study of prospective electrode- electrolyte systems for high-energy primary battery with minimum of 200 watt hours per pound of total battery weight
The initial design for the NASA-Lewis advanced nickel-hydrogen battery is discussed. Fabrication of two 10-cell boilerplate battery stacks will soon begin. The test batteries will undergo characterization testing and low Earth orbit life cycling. The design effectively deals with waste heat generated in the cell stack. Stack temperatures and temperature gradients are maintained to acceptable limits by utilizing the bipolar conduction plate as a heat path to the active cooling fluid panel external to the edge of the cell stack. The thermal design and mechanical design of the battery stack together maintain a materials balance within the cell. An electrolyte seal on each cell frame prohibits electrolyte bridging. An oxygen recombination site and electrolyte reservoir/separator design does not allow oxygen to leave the cell in which it was generated.
Previous reports have shown how a battery model was developed using porous electrode theory. Since then the model has been upgraded and expanded. These upgrades include oxygen reation and positive electrode intercalation and proton diffusion. The effects of additional details of the solid state physics of the nickel electrode will be reported here.
Effective thermal management systems, designed to handle the impacts of thermal runaway (TR) and to prevent cell-to-cell propagation, are key to safe operation of lithium-ion (Li-ion) battery assemblies. Critical factors for optimising these systems include the total energy released during a single cell TR event and the fraction of the total energy that is released through the cell casing versus through the ejecta material. A unique fractional thermal runaway calorimeter (FTRC), designed to characterise said critical factors, was utilised to examine the TR behaviour of Li-ion cells). Delegates will be provided with an in-depth discussion on what fractional thermal runaway calorimetry is and how it benefits the development of safe and optimised battery assemblies that protect against thermal runaway. Delegates will see calorimetry data associated with a variety of Li-ion cells. Data presented is relevant to any industry that utilises high-energy Li-ion cells in closed environments and has a need to focus on safety.
The arrival of the Nanoracks Airlock to the International Space Station (ISS) has provided the ISS program the capability to dispose of common trash items. The concept of operations involved the crew bagging up those items into a trash bag and then utilizing the robotic arm and the airlock to jettison the trash bag. Because of the unknown thermal vacuum stability of some of the items, a molecular contamination concern was raised by the ISS program as the trash is exposed to vacuum upon the evacuation of air from the airlock and the robotic arm moving the airlock to its jettison location. In order to characterize the representative outgassing rates for ISS trash, thermal vacuum testing was performed at White Sands Test Facility. Trash was sorted into a “lower” outgassing bag and a “mixed” bag. The “mixed” trash bag contained more items that were suspected to be not vacuum stable. Load cells were chosen as the primary means for measuring mass loss. A sharp decay in the outgassing rate was observed in the first 30 minutes followed by a slower decay. As expected, the “mixed” bag lost more mass. While Quartz Crystal Microbalances (QCMs) are often utilized to measure long term outgassing rates and the sticking coefficients of contaminants at different operating temperatures for vacuum stable materials, these measurements proved difficult due to the amount and the inclusion of materials with suspect thermal vacuum stability. Because of high rates of material outgassing, the facility was unable to maintain the CQCM temperature setpoint of 80 K QCMs.. The QCMs operating at the warmer temperatures also saturated on occasion due to high levels of condensed matter. Though testing was able to confirm high risk of outgassing contamination for the program, true sticking coefficients could not be determined, available measurements are provided herein.
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.
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.
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.
Battery Health Management (BHM) is a core enabling technology for the success and widespread adoption of the emerging electric vehicles of today. Although battery chemistries have been studied in detail in literature, an accurate run-time battery life prediction algorithm has eluded us. Current reliability-based techniques are insufficient to manage the use of such batteries when they are an active power source with frequently varying loads in uncertain environments. The amount of usable charge of a battery for a given discharge profile is not only dependent on the starting state-of-charge (SOC), but also other factors like battery health and the discharge or load profile imposed. This paper presents a Particle Filter (PF) based BHM framework with plug-and-play modules for battery models and uncertainty management. The batteries are modeled at three different levels of granularity with associated uncertainty distributions, encoding the basic electrochemical processes of a Lithium-polymer battery. The effects of different choices in the model design space are explored in the context of prediction performance in an electric unmanned aerial vehicle (UAV) application with emulated flight profiles.