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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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3,221 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Anticipating Optical Availability in Hybrid RF/FSO Links Using RF Beacons and Deep Learning

Radiofrequency (RF) communications offer reliable but low data rates and energy-inefficient satellite links, while free-space optical (FSO) promises high bandwidth but struggles with disturbances imposed by atmospheric effects. A hybrid RF/FSO architecture aims to achieve optimal reliability along with high data rates for space communications. Accurate prediction of dynamic ground-to-satellite FSO link availability is critical for routing decisions in low-earth orbit constellations. In this paper, we propose a system leveraging ubiquitous RF links to proactively forecast FSO link degradation prior to signal drops below threshold levels. This enables pre-calculation of rerouting to maximally maintain high data rate FSO links throughout the duration of weather effects. We implement a supervised learning model to anticipate FSO attenuation based on the analysis of RF patterns. Through the simulation of a dense lower earth orbit (LEO) satellite constellation, we demonstrate the efficacy of our approach in a simulated satellite network, highlighting the balance between predictive accuracy and prediction duration. An emulated cloud attenuation model is proposed to provide insight into the temporal profiles of RF signals and their correlation to FSO channel dynamics. Our investigation sheds light on the trade-offs between prediction horizon and accuracy arising from RF beacon numbers and proximity.

FSO availability↗
NASA NTRSDate not supplied

Effects of Motion Fidelity on Pilot Performance Using Mixed-Reality Visuals

This paper investigates the effects of simulator motion fidelity on pilot performance using mixed-reality visuals. In NASA’s Vertical Motion Simulator, eleven pilots flew a lift-plus-cruise electric vertical takeoff and landing vehicle in a vertiport approach and landing task with four different motion conditions: no motion, small hexapod motion, large hexapod motion, and full motion. The simulator motion condition statistically significantly affected: 1) the severity of cybersickness, 2) motion ratings, 3) final approach and take-off boundary crossing groundspeed, 4) longitudinal touchdown point, and 5) battery time remaining after landing. The findings suggest that motion systems are essential in simulators with virtual- or mixed-reality visuals when it is required to have pilot flying performance similar to that in real flight.

mixed reality↗
NASA NTRS2026

Simulating the Lunar Thermal Environment for the Surface-Deployed LEMS Artemis III TVAC Test

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. Presented is the system thermal vacuum test plan and configuration to validate the thermal control system performance in a flight-like environment. The test will measure the nighttime heat leaks for the bus and 18 seismometers to ensure lunar night survival and operability.

Thermal↗
NASA NTRS2026

Simulating the Lunar Thermal Environment for the Surface-Deployed LEMS Artemis III TVAC Test

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. Presented is the system thermal vacuum test plan and configuration to validate the thermal control system performance in a flight-like environment. The test will measure the nighttime heat leaks for the bus and 18 seismometers to ensure lunar night survival and operability.

Thermal↗
NASA NTRS2026

Simulating the Lunar Thermal Environment for the Surface-Deployed LEMS Artemis III TVAC Test

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. Presented is the system thermal vacuum test plan and configuration to validate the thermal control system performance in a flight-like environment. The test will measure the nighttime heat leaks for the bus and 18 seismometers to ensure lunar night survival and operability.

TVAC↗
NASA NTRSDate not supplied

The Use of Immersion Rigs for High Temperature Hydrogen Exposure Testing Within the Nuclear Thermal Rocket Element Environmental Simulator (NTREES): NTREES-5 Hydrogen Heat Exchanger (N5HHX-01)

The Nuclear Thermal Rocket Element Environmental Simulator (NTREES) facility at NASA’s Marshall Space Flight Center (MSFC) subjects materials and components typically found on nuclear thermal propulsion (NTP) systems to non-nuclear simulations of prototypic NTP reactor thermohydraulic environments. With 1.2 MW of inductive power available, the currently employed methods to simulate nuclear heating in NTREES consist of 1) inductively heating a test specimen, which typically cannot be performed on ceramic materials, or 2) heating gas that envelops the test specimen. The latter of these has provided a basis for developing so-called “immersion rigs” to be used in NTREES. Furthermore, immersion rigs are especially useful in the case of smaller, technically challenging test specimens. One such device, the “NTREES-5 Hydrogen Heat Exchanger” (N5HHX-01), designed and deployed to test small material coupons to ~0.5 g/s of 2800 K, 500 psi Hydrogen, is discussed herein. To achieve this desired delivery temperature level, the most suitable material for the N5HHX’s construction was pure tungsten, which imposed budgetary and manufacturing challenges. Also discussed in this paper is the design of the N5HHX rig’s sample container, which became the first iteration of improving NTREES small material coupon test operations by permitting rapid changeout of different material samples.

Reactor Testing↗
DOE OSTI2026

SODAs: sparse optimization for the discovery of differential and algebraic equations

Differential-algebraic equations (DAEs) integrate ordinary differential equations (ODEs) with algebraic constraints, providing a fundamental framework for developing models of dynamical systems characterized by time-scale separation, conservation laws and physical constraints. While sparse optimization has revolutionized model development by allowing data-driven discovery of parsimonious models from a library of possible equations, existing approaches for dynamical systems assume DAEs can be reduced to ODEs by eliminating variables before model discovery. This assumption limits the applicability of such methods for DAE systems with unknown constraints and time scales. We introduce sparse optimization for differential-algebraic systems (SODAs), a data-driven method for the identification of DAEs in their explicit form. By discovering the algebraic and dynamic components sequentially without prior identification of the algebraic variables, this approach leads to a sequence of convex optimization problems. It has the advantage of discovering interpretable models that preserve the structure of the underlying physical system. To this end, SODAs improves since SODAs is singular numerical stability when handling high correlations between library terms, caused by near-perfect algebraic relationships, by iteratively refining the conditioning of the candidate library. We demonstrate the performance of our method on biological, mechanical and electrical systems, showcasing its robustness to noise in both simulated time series and real-time experimental data.

DAE↗
DOE OSTI2025

Engineering 2D Square Lattice Hubbard Models in 90° Twisted GeX/SnX (X =S, Se) Moiré Superlattices

Because of the large-period superlattices emerging in moiré two-dimensional (2D) materials, electronic states in such systems exhibit low energy flat bands that can be used to simulate strongly correlated physics in a highly tunable setup. While many investigations have thus far focused on moiré flat bands and emergent correlated electron physics in triangular, honeycomb, and quasi-one-dimensional lattices, tunable moiré realizations of square lattices subject to strong correlations remain elusive. Here, in this work, we propose a feasible scheme to construct moiré square lattice systems by twisting two or more layers of 2D materials in a rectangular lattice by 90°. We demonstrate the concept with twisted GeX/SnX (X =S, Se) moiré superlattices and calculate their electronic structures from first principles. We show that the lowest conduction flat band in these systems can be described by a square lattice Hubbard model with parameters which can be controlled by varying the choice of host materials, number of layers, and external electric fields. In particular, twisted double bilayer GeSe realizes a square lattice Hubbard model with strong frustration due to the next-nearest-neighbor hopping that could host unconventional superconductivity, in close analogy to the Hubbard model for copper-oxygen planes of cuprate high-temperature superconductors. The presented scheme uses 90° twisted 2D materials with rectangular unit cells as a promising platform for realizing the physical phenomena of square lattice Hubbard models, establishing a new route for studying its rich phase diagram of magnetism, charge order, and unconventional superconductivity in a highly tunable setting.

2-dimensional systems↗
DOE OSTI2025

Numerical simulation of frost formation and heat transfer on fin-and-tube heat exchangers in turbulent cross-flow

Frost formation in fin-and-tube heat exchangers in turbulent cross-flow presents significant challenges in industrial refrigeration applications, affecting heat transfer efficiency and operational reliability. The purpose of this work is to investigate frost deposition and growth on a staggered bank of a fin-and-tube freezer coil under turbulent forced convection conditions. The focus here is on investigating conditions that closely replicate real-world scenarios in large walk-in industrial freezers. Using a direct numerical simulation approach, we examine the flow dynamics and thermal behaviour in the presence of frost, considering turbulent regimes characterized by a Reynolds number in the range 1050 ≤ R e D , avg ≤ 4800 , with the characteristic length being the outer diameter of the tube and the velocity being the bulk fluid velocity between the plates (fins). Computational fluid dynamics simulations are employed to resolve the interactions between turbulent airflow and the frost layer. Our approach incorporates a modified immersed boundary method and a slow-time acceleration technique to address the complex dynamic interface between the continuously evolving frost layer and the flowing air stream. Our findings indicate that frost forms more on the sides of the finned surfaces (plates) and less on the tubes themselves. This article is part of the theme issue ‘Heat and mass transfer in frost and ice’.

Science & Technology - Other Topics↗
DOE OSTI2024

Theoretical design and performance of three-dimensional, pillared FeS 2 cathodes

Three-dimensional (3D) electrode design can provide improved capacities and rate capabilities over conventional two-dimensional electrodes by enhancing electrical and ionic transport. Here, expanding upon our previous modeling efforts for conversion chemistry lithium-ion batteries, we develop a pseudo-four-dimensional (P4D) approach that is subsequently used to investigate the design of a pillared FeS 2 electrode. The model considers transport in three dimensions with an additional “fourth” dimension corresponding to the solid-state lithium transport within the active material particles. Additionally, we allow for expansion of the active material during the conversion reaction to understand how internal stresses impact the electrochemical performance of the cell. By optimizing the model with respect to areal capacity, we are able to predict areal capacities up to 16.8 mAh/cm 2 for an areal current density of 1.78 mA/cm 2 and a 103% improvement for the three-dimensional electrodes over planar electrodes of equal volume. Despite the promising results, our simulations suggest that 3D design may be difficult for conversion cathode materials due to the large internal stresses that arise during conversion. Nevertheless, the model is robust and adaptable to other materials that may be more suitable for 3D electrodes due to a lesser change in volume during discharge.

Conversion cathode materials↗
DOE OSTI2026

Model-based, in-situ, non-destructive qualification and certification of parts made by autonomous additive manufacturing

To address the significant productivity challenges associated with the qualification and certification (Q&C) tasks of additively manufactured (AM) parts, which have traditionally relied on rigorous post‐build inspection and testing, we propose an integrated framework that combines model‐based qualification and certification (MBQ&C) with autonomous additive manufacturing (AAM). MBQ&C employs high‐fidelity predictive models, developed within the Integrated Computational Materials Engineering (ICME) paradigm, to simulate process–structure–property–performance relationships for assessing a part’s fitness for use. Since predictive models are commonly machine learning (ML)-based or reduced-order surrogates of validated physics models, they run efficiently, enabling timely inference. In parallel, the self-driving AAM utilises ML-based adaptive, closed‐loop control strategies to avoid, mitigate, or repair defects and anomalies during fabrication, thereby increasing the likelihood of producing acceptable parts. A key feature of the combined AAM-MBQ&C framework is that predictive models explicitly incorporate defects or anomalies that persist after the build, using instance-specific data captured via in-situ sensing. This customisation enables a build‐specific assessment of fitness for use, rather than relying on nominal or generic parameters. Such individualised evaluation provides a robust basis for Q&C-related acceptance decisions relating to each build. Additionally, the rapid solution capabilities of ML or reduced-order models enable the determination of a part’s suitability for service shortly after build completion. As the framework matures, it has the potential to substantially reduce reliance on conventional point‐design approaches—such as time‐consuming post‐build computed tomography scanning and costly destructive testing. Thus, the AAM-MBQ&C framework represents a transformative, scalable strategy for quality assurance of AM components, as parts produced within a stable, validated, and certified envelope can be certified with reduced testing. Key benefits include: (1) significant gains in Q&C productivity through efficient, model-centric assessment; (2) performance-based classification of defects into critical and non-critical categories; (3) the ability to predict potential deviations in the performance of parts affected by real-time, adaptive process control interventions relative to those produced under a certified process, and (4) the enabling of virtual Q&C for service environments that are difficult, hazardous, or impractical to access or reproduce experimentally. Collectively, these capabilities strengthen the business case for AM, particularly for high‐consequence and mission‐critical applications. Finally, although this work focuses on powder-based AM, the proposed techniques could be extended to AM processes employing alternative feedstock forms.

Gunasegaram, Dayalan↗
NASA NTRSDate not supplied

The Use of Immersion Rigs for High Temperature Hydrogen Exposure Testing within the Nuclear Thermal Rocket Element Environmental Simulator (NTREES): Thermal Soak Rig (TSR)

The Nuclear Thermal Rocket Element Environmental Simulator (NTREES) facility was purpose constructed to perform non-nuclear evaluations of nuclear thermal propulsion (NTP) system fuel materials and structures within prototypic thermochemical environments. This system has been utilized steadily in its ability to subject test specimens to thermochemical and thermohydraulic environments simulating that of an operating nuclear rocket engine. Fission heat is simulated by induction power and experiments are conducted within a ~1000 psi pressure vessel. Hydrogen is conventionally passed through the heated fuel surrogate test specimen while pressure, temperature, and gas species data are collected at various points along the experiment. In order to test fuel and material coupon samples, a class of test apparatus named “immersion rigs” are being developed and employed to more rapidly test these smaller and more technically challenging test specimen. One example of a promising potential fuel structure, Tristructural-isotropic (TRISO) particles, presents unique challenges for testing of this type. TRISO fuel micro-particles are spheroids typically on the order of 500 – 1000 μm in diameter, and exposing a batch sample to hot hydrogen requires purpose-built special test equipment. Thusly, an immersion rig was developed and successfully demonstrated to expose ~1 g of micro-particles to hydrogen gas at temperatures and pressures relevant to NTP systems for the purpose of fuel evaluation. The rig, comprised primarily of graphite and pure tungsten, houses in its core a batch of micro-particles between pucks of porous silicon carbide (SiC). This approach permits gas flow while simultaneously retaining the particles in place. Herein is a discussion of the design, analysis, fabrication, and testing of the NTREES Thermal Soak Rig (TSR).

Space Nuclear Propulsion↗
NASA NTRS2024

Performance of Two Battery Prognostic Applications used by Two Octocopters for Safe Low Altitude Autonomous Flight Operations

This paper addresses the problem of building trust in online predictions of the remaining available flying time for two different electric Unmanned Aerial Vehicles (eUAVs) powered by lithium-ion-polymer batteries. Flight tests for various automation research missions for the two vehicles were monitored using two on-board battery health management applications to make predictions of the remaining flying time (RFT) for each eUAV and to predict the state of the battery. Playback of the voltage, current and temperature profiles of the battery discharge were used to assess the accuracy of the estimation of the voltage and the charge states of the models as well as the estimate of the RFT. The reference ground truth values were the observed landing time and the measured battery pack resting pack voltage 20 minutes after the flight. The predicted RFT, state of charge (SoC), and state of energy (SoE) were compared with the observed results. Noise values of one standard deviation from the mean values of the internal charge states of the battery model during a reference run were used to vary the states during simulation. One application used an equivalent circuit model of the electrical dynamics of the battery pack, and the other application used a reduced-order electrochemistry model. The variation of the model state components was compared to the variation in the estimate of the RFT and the variation in the SoE to estimate a confidence factor. Variation in the estimates caused by factors affecting the off-line laboratory parameter identification experiments is considered. Variation in the estimates due to environmental factors are discussed.

Assurance↗
DOE OSTI2025

Decoupling thermal and irradiation effects on grain boundary segregation

Radiation-induced segregation (RIS) is most often measured by peak solute concentration at a boundary. However, this may give an incomplete picture of segregation quantity and phenomena. Radiation-induced and thermal segregation at grain boundaries was investigated in Fe-9.6 at.% Cr after 9 MeV Fe 3+ ion irradiation at 400 °C. The experimental results were compared to kinetic Monte Carlo (KMC) simulations. The study revealed that Cr enrichment (peak segregation) at the grain boundaries was comparable in both the irradiated and non-irradiated conditions, although irradiation resulted in broader segregation profiles in both experiments and simulations, indicating an overall increase in grain boundary segregation due to irradiation. This broadening is attributed to back diffusion into the grain interior. While it is an established phenomenon, this study offers a quantitative evaluation using experimental data and KMC modeling. Further, these results emphasize the importance of analyzing the entire segregation profile and decoupling the thermal and irradiation contributions to solute segregation.

Grain boundary segregation↗
NASA NTRS2026

Performance Evaluation of Intravehicular Activity Spacesuit Without the Use of a Liquid Cooling Garment

The Orion Crew Survival Systems (OCSS) suit is equipped with safety technology that protects the crew during launch and re-entry and Intravehicular Activities (IVA). It was designed to be used with a Liquid Cooling Garment (LCG), an undergarment with tubes that circulate water to remove excess heat from a crew member. The objective of this study is to determine if the Modified Advanced Crew Escape Suit (MACES), which has very similar material, assembly, and pressure characteristics as the OCSS suit, can be used without the LCG to maintain the crew within their heat storage requirements where exceedances can lead to cognitive and physiological impairment. Testing was completed for both hot and cold environments where test subjects wore varying configurations of the MACES suit ensemble without the LCG. The tests were conducted in a temperature and humidity-controlled chamber with four test subjects ranging from extra small to large. Target metabolic rates were reached using an arm ergometer. To represent the different suit configurations seen in the concept of operations, the suit was tested with visor-down, visor-up, and without helmet and gloves. The test data was analyzed to determine how the environment, test subject size, metabolic rate, and suit configuration affected heat storage. Furthermore, the test data was used to correlate the METMAN model, a transient metabolic man program that simulates the heat transfer within a crew member’s body and from a crew member to the surrounding environment. The METMAN correlation showed good agreement between predicted heat storage and test data at the end of the test duration, with a coefficient of determination (R 2 ) value of 0.8999 for visor-down cases and R 2 of 0.8902 for visor-up and helmet off cases. A correlated METMAN model allows for the analysis and prediction of IVA suit performance without an LCG in additional scenarios.

Spacesuit↗