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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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515 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Technoeconomic Studies for the Rorex Creek Pumped Storage Hydro Project: An Evaluation of New Pumped Storage Hydro in the Tennessee Valley Authority System

This report evaluates the economic viability of the proposed 1,200 MW, 23,365 MWh Rorex Creek Pumped Storage Hydro (PSH) plant that would be located near Pisgah, Alabama. In addressing this question, this study has developed processes, models and data that better value PSH from a utility perspective, more specifically a vertically integrated utility, enabling optimal PSH design and deployment. This study is designed to enhance TVA’s toolset in making PSH investment decisions and contribute to the design of a more cost-effective, stable future grid. These techniques can then be applied to a broader range of assets and utilities.

Cohen, Stuart↗
NASA NTRS1973

Mariner Mars 1971 battery design, test, and flight performance

The design, integration, fabrication, test results, and flight performance of the battery system for the Mariner Mars spacecraft launched in May 1971 are presented. The battery consists of 26 20-Ah hermetically sealed nickel-cadmium cells housed in a machined magnesium chassis. The battery package weighs 29.5 kg and is unique in that the chassis also serves as part of the spacecraft structure. Active thermal control is accomplished by louvers mounted to the battery baseplate. Battery charge is accomplished by C/10 and C/30 constant current chargers. The switch from the high-rate to low-rate charge is automatic, based on terminal voltage. Additional control is possible by ground command or onboard computer. The performance data from the flight battery is compared to the data from various battery tests in the laboratory. Flight battery data was predictable based on ground test data.

Bogner, R. S.↗
DOE OSTI2026

Interface-induced fast Li+ transport in mixed ionic–electronic conductors

Interfacial instability between lithium metal and solid-state electrolytes limits the performance of all-solid-state lithium metal batteries (ASSLBs), leading to parasitic reactions, non-uniform Li+ flux, and dendrite growth. Here, we develop a composite interlayer composed of the anti-perovskite Li2OHCl0.75Br0.25 (AP) and carbon nanotubes (CNTs) to enhance both interfacial stability and ionic transport. The AP–CNT interlayer exhibits enhanced Li+ conductivity arising from interfacial electron transfer from AP to CNTs, which generates a built-in electric field that facilitates Li+ migration. Lithium symmetric cells incorporating this interlayer achieve a high critical current density of 2.4 mA cm−2 at 55 °C. This design integrates chemical robustness with coupled ion–electron transport, offering a generalizable strategy for safe, dendrite-free, and high-performance ASSLBs.

He, Chenche↗
DOE OSTI2026

Semi-Transparent Perovskite Solar Cells in a Stacked Tandem Module: Cooperative Research and Development Final Report, CRADA Number CRD-19-00810

This project seeks to develop device design, materials composition, and processing tools and parameters to fabricate semi-transparent perovskite solar cells and modules for application in stand-alone products or added to other solar cells in a mechanically stacked tandem configuration. This technology presents significant advanced manufacturing challenges and opportunities in getting to scale, including development of perovskite inks, scalable perovskite and heterojunction deposition and annealing processes, heterojunction composition, transparent electrode composition and deposition process, anti-reflection layer composition and deposition process, and cell to module integration processes. Modification 5: The proposed project seeks to develop device design, materials composition, and processing tools and parameters to fabricate semi-transparent perovskite solar cells and modules for application in stand-alone products or added to other solar cells in a mechanically-stacked tandem configuration. This technology presents significant advanced manufacturing challenges and opportunities in getting to scale, including development of perovskite inks, scalable perovskite and heterojunction deposition and annealing processes, heterojunction composition, transparent electrode composition and deposition process, passivation layers including in module scribes, anti-reflection layer composition and deposition process, and cell to module integration processes. Advanced metrology and characterization will be performed on perovskite films, cells and module. Furthermore, we will examine module or materials recycling for circular economy considerations. Modifcation 6: Gigahertz frequency microwave pump-probe spectroscopies are highly sensitive to thin film semiconductor photoconductivity of individual and stacks of layers that comprise perovskite solar cells. As such, these techniques will be used to qualify reproducibility and quality correlations during the manufacturing process. Modification 7: Mechanical adhesion of top contacts within perovskite modules significantly impacts the durability of the module when exposed to accelerated degradation testing. The adhesion between the perovskite/transport layer interface and the transport layer/top contact interface are both very sensitive small changes in processing. ALD processing conditions of the transport layer will be tuned to optimize the mechanical adhesion within the perovskite module stack.

14 SOLAR ENERGY↗
DOE OSTI2026

Predicting Band-Gap of Inorganic Materials Using Neuromorphic Graph Learning

Predicting properties of inorganic materials is a heavily researched topic, with several new prediction approaches emerging as competitors. One such competitor is graph neural networks, which leverage the structure of the graph to aid in the prediction process. In this work, we propose integration of neuromorphic computation into the graph neural network pipeline. We call this approach Neuromorphic Graph Learning (NGL). We utilize the NGL approach to leverage evolutionary algorithms and a novel Spike Pipeline for Raster Analysis (SPIRE) for the prediction of band gap in inorganic materials.

Mulet, Ian [University of Tennessee (UT)]↗
NASA NTRS1993

PC4CAST: A Tool for DSN Load Forecasting and Capacity Planning

Effectively planning the use and evolution of the Deep Space Network (DSN) is a complex problem involving many parameters. The tool that models many of these complexities, yet requires simple structured inputs and provides concise easy-to-understand metrics to aid in the planning process is discussed. The tool, PC4CAST, is used for both load forecasting (predicting how well planned that DSN resources meet expected demand) and as a decision support tool in the capacity-planning process (determining the relative benefits of capacity expansion options). It is now in use in the TDA Planning Office, has been used in numerous studies, and is also being used by the JPL Multimission Operations System Office (MOSO) as an integral part of Resource Allocation Team activities. Experience using the tool has helped to identify additional requirements that will further improve the planning process, which can be met by future PC4CAST versions.

S J Loyola↗
NASA NTRS2016

Global Precipitation Measurement (GPM) Spacecraft Lithium Ion Battery Micro-Cycling Investigation

The Global Precipitation Measurement (GPM) spacecraft was jointly developed by NASA and JAXA. It is a Low Earth Orbit (LEO) spacecraft launched on February 27, 2014. The power system is a Direct Energy Transfer (DET) system designed to support 1950 watts orbit average power. The batteries use SONY 18650HC cells and consist of three 8s by 84p batteries operated in parallel as a single battery. During instrument integration with the spacecraft, large current transients were observed in the battery. Investigation into the matter traced the cause to the Dual-Frequency Precipitation Radar (DPR) phased array radar which generates cyclical high rate current transients on the spacecraft power bus. The power system electronics interaction with these transients resulted in the current transients in the battery. An accelerated test program was developed to bound the effect, and to assess the impact to the mission.

Lithium Ion Battery Performance↗
DOE OSTI2025

32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery

Abstract Large language models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 32 total projects developed during the second annual LLM hackathon for applications in materials science and chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility.

Computer Science↗
DOE OSTI2026

SAVY-4000 Finite-Element Drop Test Analysis

PFE Auxiliary Systems conducted drop testing on SAVY-4000 containers to evaluate structural response under 12-foot drop conditions. In support of that effort, a finite-element modeling capability was developed to simulate drop response across multiple container sizes and impact orientations. The purpose of this work was to provide a consistent analysis framework that could support interpretation of testing, compare response trends across multiple configurations, and generate quantities of interest for later comparison with experimental data. More broadly, the analysis and testing were intended to assess whether the containers continued to perform their primary function after a 12-foot drop, namely maintaining structural integrity and containment of the contents. The modeling approach combined an implicit preload analysis with an explicit drop simulation so that each drop event began from a mechanically realistic assembled condition, including compression of the silicone O-ring. Separate models were developed for 2-quart, 5-quart, 12-quart, and 10-gallon containers. The results were evaluated in terms of strain-gauge response, collar-lid gap behavior, and accumulated plastic strain. In addition, parametric studies were performed on the 2-quart container to assess sensitivity to O-ring stiffness, friction, canister thickness, geometry tolerance, and mesh density. The simulations showed that predicted drop responses depended strongly on both container size and drop orientation. Gap metrics identified cases in which the predicted collar-lid opening exceeded the nominal O-ring cross-section threshold, while plastic strain metrics identified localized regions of elevated permanent deformation. Parametric studies showed that the predicted response was especially sensitive to the assumed O-ring stiffness and contact friction, while the geometry tolerance study produced smaller changes in the cases examined. The main value of this work was that it established a repeatable modeling and simulation workflow to support drop-test implementation, evaluate effects of future configuration changes, and understand modeling assumptions that most influenced predicted response. At the current stage, the results were viewed as preliminary model predictions rather than validated predictions. The next step would be to compare drop-test data to the model so that predictive values of the workflow could be refined and used with greater confidence to assess whether the containers maintained structural integrity and containment of the contents after a 12-foot drop.

42 ENGINEERING↗
DOE OSTI2026

EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation

The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.

15 GEOTHERMAL ENERGY↗
NASA NTRS1989

Computational Fluid Dynamics at the Lewis Research Center: An Overview

Lewis is a multidisciplinary Center with strong research and development programs in aeronautical and space propulsion, power, space communications, space experiments and materials. Computational fluid dynamics (CFD) is playing an important and growing role in most of these areas. Described here is how CFD is integrated into these programs and highlights elements of the CFD activities. Examples are presented of codes developed to predict flow fields in advanced propulsion systems and several of the code validation experiments are described. The CFD effort at Lewis ranges from basic research on new and improved algorithms through code development to the application of these codes to specific engineering problems. Because of the substantial improvement in CFD's predictive capability, its use at Lewis is on a steep growth path, spreading rapidly into new areas which had not traditionally taken advantage of the techniques of numerical simulation. Multidisciplinary codes and the future direction of CFD at Lewis are discussed.

Robert M Stubbs↗
DOE OSTI2026

Systems Engineering and Analysis in Support of a US Federal Staging Facility for UNF

The US Department of Energy Office of Nuclear Energy (DOE-NE) Office of Spent Fuel and High-Level Waste Disposition is examining a set of system options and conducting supporting analyses to inform the development of an integrated waste management system, which may include one or more federal staging facilities (FSFs) for used nuclear fuel (UNF ) sited using a collaborative siting process. This paper focuses on the ongoing activities in two systems engineering and analysis work areas: (1) data and tools development, validation, and maintenance and (2) systems engineering execution. Within the first work area, the STANDARDS 5.0 UNF data and analysis tool, formerly known as UNF-ST&DARDS, is being developed as a foundational resource to assist in the management of UNF data. It has the key capability to model UNF throughout the entire back end of the fuel cycle. STANDARDS also includes several compatible analysis tools for the time-dependent characterization of UNF and related systems by interfacing with the SCALE code system for nuclear analysis and COBRA-SFS for thermal analysis. Also, within the data and tools area is the Next Generation System Analysis Model (NGSAM), which is an agent-based simulation software tool expressly designed to be capable of modeling the waste management system, including the transportation of UNF to and from a FSF. NGSAM has been developed to enable informed decision-making by providing the capability to analyze various potential system options for the management of UNF and high-level radioactive waste. Finally, in the systems engineering execution area, the team has begun to apply a disciplined systems engineering approach at the system level along with supporting analysis to guide the development of the FSF project requirements (including associated transportation infrastructure). Systems engineering principles and practices and their adaptation/application to design and development activities will ensure that the waste management system is effectively implemented as work proceeds. Other activities include investigating the implications of changes in various assumptions and parameters related to waste management systems, such as UNF acceptance rates, receipt logic, facility capacities and capabilities, use of standardized canisters, and different assumed facility operation start dates. Keywords: federal staging facility (FSF), used nuclear fuel (UNF), integrated waste management (IWM) system, Next Generation System Analysis Model (NGSAM), STANDARDS, systems engineering

Joseph, Robert↗
DOE OSTI2025

Wettability of Two-Dimensional Carbon Allotropes from Molecular Simulations

Force-field Monte Carlo and Molecular Dynamics simulations are used to compare wetting behaviors of model carbon sheets mimicking neat graphene, its saturated derivative, graphane, and related planar allotropes penta-graphene, γ-graphyne, and ψ-graphene in contact with aqueous droplets or an aqueous film confined between parallel carbon sheets. Atomistic and area-integrated surface/water potentials are found to be essentially equivalent in capturing moderate differences between the wetting free energies of tested substrates. Despite notable differences in mechanical and electric properties of distinct allotropes, the predicted allotrope/water contact angles span a narrow window of weakly hydrophilic values. Contact angles in the range of 80 ± 10° indicate modest hydration repulsion incapable of competing with van der Waals attraction between carbon particles. Poor dispersibility in neat water is hence a common feature of studied materials.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Influence of Powder Characteristics and Processing Methods on Creep Performance of Powder Metallurgy Hot Isostatic Pressed SS316

The U.S. nuclear energy expansion goals are driving the demand for manufacturing routes that can rapidly produce large, complex, near net shape components. Powder metallurgy hot isostatic pressing (PM HIP) is an advanced manufacturing technique that can be economically scaled-up, while alleviating the supply chain challenges that forging and casting face in terms of cost and lead time constraints. This makes PM-HIP a viable technology to aid and accelerate large-scale part manufacturing for nuclear applications. However, large-scale qualification and deployment of this technology require a thorough understanding of the influence of powder feedstock quality, powder handling history, hot isostatic pressing (HIP) parameters, and subsequent heat treatment on microstructural evolution and elevated temperature mechanical performance. The present work focusses on 316 austenitic stainless steel (SS316) which is most commonly used in high temperature environments for nuclear applications Results from this study show that PM HIPed SS316 meets ASME tensile requirements at room temperature and at elevated temperature. However, creep performance of PM-HIPed SS316 remains inferior to its wrought counterpart, demonstrating that tensile performance alone is not a reliable metric for long duration high temperature integrity. Further, this report delineates powder derived microstructural features that govern creep damage, with key evidences pointing to “microstructural inheritance” from gas atomized powder feedstocks. Commercial SS316 powders of varying chemical compositions and recycling histories were studies, and the results showed large differences in elemental segregation, oxide surface layers and secondary phase distributions. Multi-scale characterization revealed segregation of chromium, molybdenum, manganese and silicon at the boundaries and the precipitation of manganese-, silicon-, and molybdenum-oxides. During HIP consolidation, these surface oxides transform into decorated prior particle boundaries (PPBs) and grain boundary inclusions that persist through conventional post-HIP solution annealing treatment. The retained oxides in post-HIP microstructures were found to influence grain growth, precipitation behavior, and ultimately creep cavitation and fracture. Such post-HIP heat treatments are therefore limited by a complex trade-off between grain growth, and oxide coarsening which aggravate creep damage by acting as nucleation sites for cavities. The objective of this work is to establish an integrated processing–structure–property framework for PM-HIP 316 stainless steel by investigating the influence of powder feedstock characteristics in pre- and post-HIP processing as well as to understand the significance of post-HIP heat treatment on microstructural evolution and creep properties. The results from this report emphasize the significance of powder feedstock integrity in improving creep performance of PM-HIPed SS316, by highlight the effect of rapid solidification, elemental segregation, oxide formation and powder recycling on microstructural defect inheritance following HIP consolidation. Rather than considering HIP processing, solution annealing, and mechanical performance independently, this report treats powder production, HIP consolidation, post-HIP thermal processing, and creep deformation as interconnected stages within a continuous metallurgical process. The resulting framework will provide a scientific basis for developing feedstock engineering strategies capable of improving long-term reliability of PM-HIP stainless steels and accelerating their qualification for advanced nuclear applications.

Ajjarapu, Pavan [Oak Ridge National Laboratory (OR↗
NASA NTRS1997

Future Aerospace Technology in the Service of the Alliance: Sustained Hypersonic Flight - Volume 3

Sustained Hypersonic Flight capability is envisioned for several future military and civilian applications, such as long range immediate reaction reconnaissance, high speed interception of air targets, long range precision strike against hardened or time critical targets, and access to space. The inherent reduction in time-to-target and low vulnerability will permit new operational tactics. The symposium outlined mission needs and operational scenarios for hypersonic vehicles. Addressed were: Technological issues and challenges in external hypersonic aerodynamics and design, propulsion and engine/airframe integration, military ramjet applications, overall system design including structures and materials development needs, and test facilities. Ground based test facilities cannot provide full simulation at Mach numbers above 5. Therefore, the use of Computational Fluid Dynamics design tools is essential. For routine use of the computational tools in analysis, design and optimization, it is necessary to reduce the time for the entire computational process by two orders of magnitude. Hypersonic boundary layer transition remains a critical design issue because of the important impact on engine drag and on heating, which can affect the choice of materials and thermal protection systems. In addition, reliable prediction of scramjet net thrust is an absolute must in resolving hypersonic air breathing vehicle design issues. Due to current facility and computational shortfalls, the development of future hypersonic flight systems requires research flight tests in the technology areas of boundary layer transition and air-breathing propulsion engine performance. For sustained hypersonic flight beyond Mach 6, the supersonic combustion ramjet (scramjet) engine is the only choice for the near future. Only this air-breathing concept offers a significant promise of large reductions in required propellant fractions, increased payload fractions, and reduced size vehicles, together with a foreseeable technological feasibility. Airframe/engine integration, combustor design and thermal management are the predominant engineering tasks. Fuels, hydrogen or hydrocarbon, must be matched to the operational needs of military or civil use. Experience in existing ramjet propelled missiles capable of speeds up to Mach 4 can support the development effort. The potential mission and cost benefits of sustained hypersonic flight to both military and civil applications are tremendous. From the budget point of view, the possibility of sharing development costs between military and civil programs offers a specific advantage.

Combustion chambers↗
NASA NTRS2024

Expansion of Check-Cases for 6DOF Simulation

This is the Appendix containing a description of the solution for Case 1 in the assessment, “Expansion of Check-Cases for 6DOF Simulation”. For cases of spherical gravity, it is possible to provide a two-body solution without recourse to numerical integration and thus it is accurate to machine precision. Python code for a Keplerian Propagator (propagate.py) which produced a reference trajectory for Case 1 is provided in this appendix. There is also code for generating test cases which was used as an independent verification of the propagator. This is a high-level description of the algorithm employed. The documentation of each function includes implementation details, including equations for each task.

Modeling↗
NASA NTRSDate not supplied

Extending mARC II Arc-Jet Test Duration via Design and Implementation of Model System Cooling Sleeve

The mARC II is a 30 kW arc-jet facility at NASA Ames Research Center used to generate high-enthalpy flows for low-cost thermal protection system (TPS) technology development. Sustained operation of downstream instrumentation and material samples is constrained by thermal loading transmitted through the arc-jet test environment, limiting achievable run times and experimental throughput. This work presents the design, integration, and validation of a cooling sleeve implemented on the sweep arm drive motor feedthrough to mitigate thermal accumulation during testing. The addition of the cooling sleeve is a simple, robust upgrade that translates directly into enhanced facility capability by supporting longer run durations, reduced turnaround time, and higher throughput.

numerical simulations↗
NASA NTRSDate not supplied

Harness Thermal Heat Loss Measurement for a Lunar Surface-Deployed LEMS Artemis III Payload

The Lunar Environment Monitoring Station (LEMS) is an autonomous, survive-the-lunar-night seismic suite to be deployed on the Lunar surface by the Artemis III crew and designed to operate continuously for two years. It will see the extremes of the Lunar south pole thermal environment where surface temperatures range from -200°C to +20°C and where nighttime duration is at least 354 hours. Given power and mass constraints, the thermal system is limited to 2.5 Watts of heat during the lunar night. The electrical harnessing named the Signal and Power Passthrough (SAPP) was designed to minimize heat loss while meeting power and signal integrity requirements. To mitigate risk due to uncertainty associated with the harnessing materials, routing, and tie-downs, a flight-like thermal conductance test was performed to measure the heat loss. The test methodology, results, and model correlation are presented.

TVAC↗