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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗
NASA NTRS2025

Assembly of catalytic complexes from randomized oligonucleotides

The early evolution of life relied on catalytic RNAs (ribozymes) for central functions. To test whether early catalysts could have assembled from multiple short nucleic acid fragments in random sequence environments, we performed an in vitro selection from a short RNA library in the presence of 256 different DNA 20-nucleotide oligomers. High-throughput sequencing and biochemical analysis showed that most of the selected 1331 RNA sequences required at least one DNA for activity. Representatives for four of six RNA clusters that depended on DNA cofactors were active even when the 256 DNAs were replaced by completely random DNA 20-nucleotide oligomers. The formation of these catalytic complexes and the recruitment of oligonucleotide cofactors from completely random libraries demonstrate an important principle for the emergence of the earliest oligonucleotide catalysts.

Xu Han↗
NASA NTRS2022

Optical properties of morphologically complex black carbon aerosols: Effects of coatings

Optical properties are computed for fractal-like aggregate black carbon (BC) aerosols coated with different substances. Two models are used for these aerosols: (i) the coated aggregate model (model I), where coating is added to the voids and surroundings of BC fractal-like aggregates; and (ii) the closed-cell aggregate model (model II), where coating is added concentrically to each monomer of BC fractal-like aggregates. Our results favor choosing the coated aggregate model (model I) to simulate scattering and absorption by coated BC aerosols because this model is morphologically more realistic, and because this model yields mass absorption cross section (MAC) and backscattering linear depolarization ratio (LDR) values that are consistent with field measurements. Moreover the corresponding computed degree of linear polarization (DoLP) and LDR values are very sensitive to changes in the coating volume fraction (fvol) and the coating refractive index (m). With the same absorbing BC core, the MAC value increases steadily with increasing fvol and m values. For example, using a density of 1.8 g/cm 3 and BC refractive index 1.95 + i0.79, the calculated MAC values for uncoated BC aggregates range from 6.2 to 6.8 m 2 /g at 0.55 µm. When coating material is applied to the BC aggregates, the calculated MAC values for model I particles increase to between 9.8 and 13.2 m 2 /g (depending on m) when fvol = 87.5%. The backscattering LDR values also tend to increase with the increasing m values for the shapes and sizes considered in our study. For model I particles, the backscattering LDR values span a wide range of 4.2–27.8% at a wavelength of 0.35 µm at fvol = 87.5% when m increases from 1.33 to 1.55. Our results are relevant to analyses of polarimetric and lidar observations of smoke particles, especially when these particles undergo hygroscopic growth.

Black carbon aerosols↗
NASA NTRS2026

Unraveling the Complex History of Aqueous Alteration and Metamorphism in CV Chondrite, Camel Donga 040

Camel Donga (CD) 040 is a CV breccia collected from Australia in 1988. Initial studies of CD 040 revealed two lithologies, both containing chondrules up to 1 mm in diameter (some with fine-grained rims) and abundant troilite, but each with remarkably different olivine compositions. Lithology 1 was characterized as petrologic type 3 material, while lithology 2 was described as being “heated to ~1100°C”. CD 040 was initially classified as an ungrouped C3; however, subsequent analyses of oxygen isotopes and bulk rock compositions confirmed that both lithologies were CV chondrite material. Though CD 040 was one of the earliest examples of a CV chondrite containing metamorphosed material, it was never extensively studied. Here we report the results of a detailed study of CD 040, focusing primarily on the petrography and mineral chemistry of metamorphosed lithology.

T L Dunn↗
NASA NTRSDate not supplied

Emergence of Complex Modes in Lightly Damped Structural Systems

In this short presentation format, we will provide a set of useful equations, relationships, and physical interpretations direct from the damped two-mode interaction problem. We will demonstrate that the results from the two-mode interaction problem are in direct agreement with observed test data. Practical methods for estimating the parameters driving the relations direct from modal test data are provided. We finalize with two examples demonstrating weak and strong interactions.

spaceflight hardware↗
NASA NTRS1993

Evidence for the Interaction of the IRS 16 Wind With the Ionized and Molecular Gas at the Galactic Center

We present a number of high-resolution radio images showing evidence for the dynamical interaction of the outflow arising from the IRS 16 complex with the ionized gas associated with the Northern Arm of Sgr A West, and with the northwestern segment of the circumnuclear molecular disk which engulfs the inner few parsecs of the Galactic center. These interactions offer an opportunity to explain some important aspects of the complex morphology of ionized and molecular gas at the Galactic center. In particular we suggest that the wind disturbs the dynamics of the Northern Arm within 0.1 pc of the center, is responsible for the waviness of the arm at larger distances and is collimated by Sgr A West and the circumnuclear disk. The waviness is discussed in terms of the Rayleigh-Taylor instability induced by the ram pressure of the wind incident on the surface of the Northern Arm. Another consequence of this interaction is the strong mid IR polarization of the Northern Arm in the vicinity of the IRS 16 complex which is explained as a result of the ram pressure of the wind compressing the gas and the magnetic field. The IRS 16 complex must therefore lie close to the Northern Arm. On a large scale we argue that the wind has swept up the diffuse material in the inner parsec of the Galactic center and that the interaction with the inner part of the northwestern part of the circumnuclear ring is responsible for the H 2 v = 1-0 emission and the ionized streamers. Lastly, we discuss the possibility that the outflow from IRS 16 could be responsible for eating away the inner edge of the circumnuclear disk and provide friction needed for the infall of the material in the arms of Sgr A West.

IRS 16↗
NASA NTRSDate not supplied

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗
NASA NTRS1992

Science questions for the Magellan continuing mission

Magellan has completed two mapping cycles around the planet Venus, returning high resolution synthetic aperture images and altimetry data of over 95 percent of the planet's surface. Venus is dominated by low lying volcanic plains with an impact crater population indicating an average surface age of about 500 million years. Highland regions either tend to be characterized by volcanic shield complexes and rifting or by complex ridged terrain. Successful as the primary mission of Magellan has been, significant scientific questions remain to be addressed with imaging and gravity data that will be collected over the next several years.

Saunders, R. S.↗
NASA NTRS1993

Exploiting the Cannibalistic Traits of Reed-Solomon Codes

In Reed-Solomon codes and all other maximum distance separable codes, there is an intrinsic relationship between the size of the symbols in a codeword and the length of the codeword. Increasing the number of symbols in a codeword to improve the efficiency of the coding system thus requires using a larger set of symbols. However, long Reed-Solomon codes are difficult to implement and many communications or storage systems cannot easily accommodate an increased symbol size, e.g., M-ary frequency shift keying (FSK) and photon-counting pulse-position modulation demand a fixed symbol size. A technique for sharing redundancy among many different Reed-Solomon codewords to achieve the efficiency attainable in long Reed-Solomon codes without increasing the symbol size is described. Techniques both for calculating the performance of these new codes and for determining their encoder and decoder complexities is presented. These complexities are usually found to be substantially lower than conventional Reed-Solomon codes of similar performance.

O Collins↗
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 NTRS1994

What to Do Until the Money Runs Out: A Refinement Framework for Cognitive Engineering in the Real World

A case study is presented to illustrate some of the problems of applying cognitive science to complex human-machine systems. Disregard for facts about human cognition often undermines the safety, reliability, and cost-effectiveness of complex systems. Yet single-point methods (for example, better user-interface design), whether rooted in computer science or in experimental psychology, fall far short of addressing systems-level problems in a timely way using realistic resources. A model-based methodology is proposed for organizing and prioritizing the cognitive engineering effort, focusing appropriate expertise on major problems first, then moving to more sophisticated refinements if time and resources permit. This case study is based on a collaborative effort between the Human Factors Division at NASA-Ames and the Spaceborne Imaging Radar SIR-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) Project at the Jet Propulsion Laboratory (JPL), California institute of Technology. The first SIR-C/X-SAR Shuttle mission flew successfully in April, 1994. A series of such missions is planned to provide radar data to study Earth's ecosystems, climatic and geological processes, hydrologic cycle, and ocean circulation. In addition to JPL and NASA personnel, the SIR-C/X-SAR operations team included Scientists and engineers from the German and Italian space agencies.

Shafto, Michael G.↗
NASA NTRS2009

General Purpose Data-Driven Monitoring for Space Operations

As modern space propulsion and exploration systems improve in capability and efficiency, their designs are becoming increasingly sophisticated and complex. Determining the health state of these systems, using traditional parameter limit checking, model-based, or rule-based methods, is becoming more difficult as the number of sensors and component interactions grow. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults or failures. Data-driven techniques have a number of advantages over other methods for monitoring complex space vehicles. Unlike model-based systems, the developer does not need to understand or encode the internal operation of the system. The knowledge required to monitor the system is automatically derived from archived data from system operation. Unlike rule-based systems, data-driven systems do not require system analysts to define nominal relationships among sensors. Analysts can and often do determine these relationships for a system with few sensors; it is more difficult to analytically determine the nominal relationship among a large number of sensors. Data-driven techniques are not limited to low-dimensional spaces and work as effectively with dozens of parameters as they do with a few. Knowledge bases formed by data-driven techniques are also easy to update. As the operating envelope of the monitored system is expanded, data-driven techniques can be quickly retrained to incorporate the new behavior into the knowledge base. The expertise and time-consuming process of updating a model or rule base to maintain consistency with the new operation is not required. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. This characterization, or model, of nominal operation is stored in a knowledge base that can be used for real-time system monitoring or analysis of archived events. System data is compared with the nominal IMS model to produce a measure of how well current system behavior matches the normal behavior defined by the training data. Significant deviations from the nominal system model can provide alerts to system malfunctions or precursors of significant failures. The scope of IMS based data-driven monitoring applications continues to expand with current development activities. Successful IMS deployment in the International Space Station (ISS) flight control room to monitor ISS attitude control systems has led to applications in other ISS flight control disciplines, such as thermal control. It has also generated interest in data-driven monitoring capability for Constellation, NASA's program to replace the Space Shuttle with new launch vehicles and spacecraft capable of returning astronauts to the moon, and then on to Mars. Several projects are currently underway to evaluate and mature the IMS technology and complementary tools for use in the Constellation program. These include an experiment on board the Air Force TacSat-3 satellite, and ground systems monitoring for NASA's Ares I-X and Ares I launch vehicles. The TacSat-3 Vehicle System Management (TVSM) project is a software experiment to integrate fault and anomaly detection algorithms and diagnosis tools with executive and adaptive planning functions contained in the flight software on-board the Air Force Research Laboratory TacSat-3 satellite. The TVSM software package will be uploaded after launch to monitor spacecraft subsystems such as power and guidance, navigation, and control (GN&C). It will analyze data in real-time to demonstrate detection of faults and unusual conditions, diagnose problems, and react to threats to spacecraft health and mission goals. The experiment will demonstrate the feasibility and effectiveness of integrated system health management (ISHM) technologies with both ground and on-board experiments. Initially, the TVSM software will run open loop, providing system health information and recommendations to ground operators, without automatically performing fault-mitigating corrective actions. After the end of the satellite's mission, closed loop tests combining TVSM monitoring and diagnosis with reactive capabilities by the flight software will be performed. In addition to monitoring for long periods of actual operation, the experiment will include fault injection into TacSat-3 data as well as commanded operations to test and evaluate automatic ISHM monitoring and recovery under controlled conditions.

Satellites↗
NASA NTRSDate not supplied

Usage-based Lifing of Lithium-Ion Battery with HybridPhysics-Informed Neural Networks

Lithium-ion batteries are commonly used to power unmanned aircraft vehicles (UAVs).The ability to model and forecast the remaining useful life of these batteries enables UAV reliability assurance. Building accurate models for battery state of charge and state of health based on first principles is challenging due to the complex electrochemistry that governs battery operations and computational complexity required to solve them. Therefore, reduced order models are often used due to their ability to capture the overall battery discharge. Un-fortunately, these simplifications lead to residual discrepancy between model predictions and observed data. In this paper, we present a hybrid modeling approach merging reduced-order models and neural networks. In this approach, while most of the input-output relationship is captured by Nernst and Butler-Volmer equations, data-driven kernels reduce the gap between predictions and observations. We validate our approach using data publicly available through the NASA Prognostics Center of Excellence repository. Results showed that our hybrid battery prognosis model can be successfully calibrated, even with a limited number of observations.

Lithium-ion Battery↗
NASA NTRS2026

Hidden in Plain Sight: A New Main Belt Population of Aqueously Altered and Thermally Metamorphosed Asteroids

C-complex low albedo asteroids are understood to be related to aqueously altered carbonaceous chondrite meteorites. However, in recent years, a new subgroup of aqueously altered meteorites that have experienced significant heating after their initial interactions with water has been extensively studied. It remains unclear where the aqueously altered and heated parent bodies are located in the asteroid belt. To address this question, we reanalyzed the original dataset that defined the Bus-DeMeo spectral taxonomy of asteroids (DeMeo et al., 2009) using a machine learning approach trained with near-infrared archival meteorite spectra. Results show that ~50% of the C-complex asteroids first identified in the Bus-DeMeo asteroid spectral taxonomy are aqueously altered and heated. Though Ryugu has been shown to also have experienced both of these processes, this is the first evidence of a population of aqueously altered and thermally metamorphosed asteroids in the Main Asteroid Belt. Based on the expected velocity and frequency of impacts in the main belt population, we conclude that impacts are the most likely heat source driving thermal metamorphism we identify. Moreover, these aqueously altered and thermally metamorphosed asteroids may represent a primordial population of low-albedo material that formed in situ in the inner solar system. If these asteroids formed in place, rather than being brought in from the outer solar system during giant planet migration, they would have experienced more frequent and higher velocity impacts, resulting in their distinct mineralogy.

Main Belt asteroids↗
NASA NTRS2026

GVIPS Prediction of Cyclic Ratchetting Behavior and Cycles with Interrupted Relaxation Periods of TIMETAL 21S at 650 °C

The predictive performance of a multimechanism GVIPS model with saturating hardening function is assessed against a set of high temperature cyclic experiments under both strain-control and stress-control at varying rates of loading as well as several complex interrupted cyclic responses. The material specimens were composed of the titanium alloy, TIMETAL 21S, and tested at 650 °C, see Lissenden et al., 2007. The model did a very good job of predicting the variety of tests, particularly given the fact that only monotonic loading tests (tensile, creep, relaxation) and a single fully reversed cycle was used for characterization. It was particularly interesting that the model was capable of reasonably capturing the rate of accumulated strain during ratchetting under tensile mean stress. Given complex interrupted cyclic response, the model was able to both qualitatively and even quantitatively predict reasonably well both the cyclic and associated relaxation periods (in all quadrants of the stress-strain space) thus confirming the validity of the chosen functional forms for both hardening and thermal recovery. The quantitative inaccuracy is associated with the fact that the material specimens tested by Lissenden et al., 2007 was significantly “softer” than those tested by Castelli in Saleeb et al., 1994 which were used for characterization of the GVIPS model parameters.

Viscoplaticity↗
NASA NTRSDate not supplied

Phosphate Textural Diversity in CI Chondrites and C-Type Asteroids

Introduction: Apatite, Ca 5 (PO 4 ) 3 (CL/F/OH-), is a ubiquitous phosphate found throughout the solar system, including the most primitive solids, CI-chondrites [1,2] and related samples of carbonaceous asteroids Ryugu [3] and Bennu [4], returned by JAXA’s Hayabusa2 and NASA’s OSIRIS-REx missions, respectively. Apatite in these primitive solids is found as individual grains or mineral clusters and has been inferred to form from the hydrothermal sequence during cooling of their respective parent body or bodies. To better understand the formation history and reworking of these early phosphates we have undertaken a highly coordinated study of phosphate microstructures, geochemistry and U/Pb geochronology from a suite of CI meteorites and carbonaceous asteroid samples. These data have identified novel phosphate microstructures and complex relationships across a suite of apatite grains from the early solar system, indicating multiple episodes of growth and modification on the CI parent body(ies). Methods: Samples of CI chondrites, Alais, Ivuna, Orgueil, Oued Chebeika 002, Yamato (Y) 82162, Y980115, Y980134, and two chips of Hayabusa2 Ryugu particles (A0262 and C0263) have been acquired for analysis. The bulk texture of the samples were first scanned by X-ray Computed Tomography (XCT) using the Nikon XT H 320 within the XFACT facility at NASA JSC or the Xradia 620 Versa at the UTCT facility. Based on the identification of petrofabrics or features of interest from the XCT data, samples were chipped, oriented, potted in epoxy and thick sections were prepared. After anhydrously polishing the samples with silicon carbide and dry diamond powder down to 1 µm, the samples were ion polished using a Hitachi ArBlade. Energy dispersive Xray spectrometry (EDS) maps were collected to ID phosphates of interest using a JEOL 7900F SEM. The internal microstructures of identified phosphates were then mapped by electron backscatter diffraction (EBSD) using the JEOL 7900F. Based on the EDS and EBSD data, domains of interest were targeted for quantitative chemical analyses using a JEOL 8530 EPMA. Subsequently, in situ U-Pb and 207 Pb/ 206 Pb ages will be collected using a Cameca ims1290 secondary ion mass spectrometer at UCLA across a range of microstructures. Results: Apatite grains are ubiquitous throughout the CI chondrites and carbonaceous asteroid materials, found as individual grains, disseminated clusters or grain aggregates. Apatite grains are associated with serpentine, magnet-ite, and/or carbonate. Of particular interest, we have identified individual and aggregate polycrystalline grains ex-hibiting an internal ‘honeycomb’ texture (Fig. 1). Some of these grains appear overprinted by subsequent alteration while others remain unaltered. Apatite halogen sites are dominated by the missing component, assumed to be OH, and F, comparable to published values from Bennu, Ryugu and CM-chondrites [3-5]. However, the Yamato CI-like meteorites show a broader range of Cl values, and one grain from Alais is dominated by CL. Summary: Apatite growth features indicate a protracted and complex growth history, consistent with precipitation from an evolving fluid system. The ‘honeycomb’ texture identified in some CI meteorites is, to the best of our knowledge, the first report of such a microstructure in meteoritic phosphate. The microtextures and zoning will guide subsequent age analyses, to better constrain the formation and reworking of phosphate in CI(-like) materials. Acknowledgments: We thank the National Institute of Polar Research, Japan for samples of Y82162, 980115 and 980134 meteorites, ASU’s Buseck Center for Meteorite Studies for samples of Ivuna and Alais meteorites, and JAXA curation for chips of Ryugu material. This work was funded by NASA ROSES LARS grant 24-LARS24-0014. References: [1] Morlok et al., 2016, GCA 70:5371-5394. [2] Alfin g et al., 2019, Geochemistry 79:125532. [3] Nakamura et al. (2022) Science 379:1-15. [4] Seifert et al. (2026) MAPS 61:504-521. [5] Piralla et al. (2021) MAPS 56:809-828.

CI chondrites↗
NASA NTRSDate not supplied

A Simplified Model of VIPER Thermal Management System. Part I: Loop Heat Pipe

NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) uses a combination of loop heat pipes (LHPs) and heaters as the primary hardware to modulate the temperature of the electronic boxes and payloads instruments. LHPs have been designed and instrumented to be capable of passive and active shutdown. The goal of the passive shutdown, using a thermal control valve (TCV) to limit the flow of the working fluid, is to preserve thermal energy and avoid unnecessary heat leaks during lunar night. The goal of the active shutdown on the other hand, is to forcefully increase the vehicle internal temperature to bakeout the payload instruments. Several numerical modeling tools are available to analyze LHP performance under the complex set of operational requirements and environments levied on the VIPER Thermal Management System (TMS). Yet, while those numerical modeling tools are capable of detailed performance analysis, they tend to take large computational resources and long computational time. In this paper, a model of a single LHP developed based on control volume approach is presented. By using the control volume approach, the complex geometry of the LHP, and the components attached to it, are reduced to thermal lump capacitances, thus reducing the computation effort. This paper also describes the effort to correlate the proposed LHP model using thermal vacuum (TVAC) test data.

Loop Heat Pipe↗