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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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NASA NTRS2019

Trends in Human Spaceflight: Failure Tolerance, High Reliability and Correlated Failure History

In a half century of human spaceflight, NASA has continuously refined agency safety and reliability requirements in response to mission demands, critical failures, and technology development. Early spacecraft, including Mercury, Gemini and Apollo vehicles, were highly reliant on dissimilar redundancy and demonstrated test margins. Later programs, such as the reusable Space Transportation System (STS) and International Space Station (ISS), introduced probabilistic studies and isolated two-failure tolerance to improve robustness at the expense of added complexity. More recently, the Orion Multi-Program Crew Vehicle (MPCV) program adopted universal single-failure tolerance with two categorical exceptions; Zero-Failure Tolerant (0FT) and Design for Minimum Risk (DFMR) hardware. Failure tolerance variances are defined and managed in accordance with agency human-rating requirements, and require concurrence from program Technical Authorities (TA) as well as the MPCV Safety and Mission Assurance Safety and Engineering Review Panel (MSERP). To understand and reaffirm standards applied to Apollo, Space Shuttle and Orion vehicles, Orion and Deep Space Gateway Safety and Mission Assurance (S&MA) representatives conducted accelerated research to compare unique safety and reliability criteria against ground and flight anomalies, based on information contained in post-mission reports and the Problem Reporting and Corrective Action (PRACA) database. In some cases, high-profile failures and narrow escapes have reinforced decisions to maintain or adapt safety requirements. In others, empirical trends have highlighted the need for vigilance and innovative safety guidelines. Given the inability to achieve absolute compliance with evolving safety and reliability requirements, the team conducted a targeted review of DFMR and 0FT propulsion elements within the framework of changing system design, inspection, materials and process developments to formulate conclusions on technological maturity, failure density, and net changes in safety risk. Based on the aggregate performance of high-reliability and failure-tolerant systems, the authors have attempted to establish best practices and guidelines to inform future program decisions. On a somewhat cautionary note, this study is not intended to direct a universal set of requirements for future missions based on prior lessons learned. Spacecraft safety is a multi-variable problem, and attempts to mitigate past failures will not guarantee future success. However, this assessment offers a retrospective review of policy changes, implementation and effectiveness. In the future, NASA, European Space Agency (ESA) and industry partners may benefit from a more robust correlation between requirements and performance, as space-faring nations work toward more challenging, complex and long-duration commercial and deep-space ventures.

Green, Carrie↗

DOE OSTI2025

Keeping LAMMPS cutting edge

Since its inception 30 years ago, LAMMPS has grown to be a world-class molecular dynamics code and a cornerstone of computational materials science research. This project aimed to keep LAMMPS at the forefront of molecular dynamics simulations by adapting LAMMPS to the latest developments in machine learning technology and hardware. Initially, the project set out to provide a unified implementation of active learning for efficient training data generation in LAMMPS, but the research trajectory pivoted to address more immediate and impactful opportunities. On the hardware side, recent record-breaking molecular dynamics simulations were developed on the Cerebras wafer-scale AI chip, and this project has developed an interface between LAMMPS and the hardware-specific molecular dynamics code to accelerate and simplify development and user adoption. On the software side, PyTorch’s Ahead-of-Time (AOT) compilation features promised increased performance for state-of-the-art equivariant neural network potentials, and this project laid the groundwork for their adoption in LAMMPS, resulting in a nearly 20x acceleration in extreme cases. Combined with a comprehensive benchmark study of LAMMPS across all current exascale systems, this project has reinforced LAMMPS’s role as a versatile, high-performance tool for current and future materials science applications.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Biopolymer-Templated Titania Film Formation for Nanostructured Coatings Revealed by Machine Learning-Supported Time-Resolved Analysis

This study presents a machine learning approach to derive the film formation of biopolymer-templated titania nanostructures during spray deposition, in combination with in situ grazing-incidence small-angle X-ray scattering (GISAXS). A neural network trained on synthetic GISAXS data directly predicts domain-size distributions from experimental two-dimensional scattering patterns, capturing the full kinetics of nanostructure evolution with high temporal resolution. The predictions reveal hierarchical size distributions and periodic growth features, consistent with layer-by-layer spray deposition and validated by complementary scanning electron microscopy (SEM) imaging. Quantitative comparison with conventional parametric GISAXS fits shows good qualitative agreement, with systematic differences explained by domain-shape assumptions and resolved by applying a geometric scaling factor. Simulated SEM-like surfaces derived from neural network outputs reproduce the porous, foam-like nanoscale morphology observed experimentally, reinforcing the method’s credibility. This integrated approach enables real-time, nondestructive, statistically averaged monitoring of bulk nanostructure development in functional coatings, offering a scalable methodology to accelerate the characterization and process control of sustainably manufactured nanostructured titania films for energy-related applications such as photocatalysis and photovoltaics.

Heger, JulianEliah↗

NASA NTRS2004

Unifying Temporal and Structural Credit Assignment Problems

Single-agent reinforcement learners in time-extended domains and multi-agent systems share a common dilemma known as the credit assignment problem. Multi-agent systems have the structural credit assignment problem of determining the contributions of a particular agent to a common task. Instead, time-extended single-agent systems have the temporal credit assignment problem of determining the contribution of a particular action to the quality of the full sequence of actions. Traditionally these two problems are considered different and are handled in separate ways. In this article we show how these two forms of the credit assignment problem are equivalent. In this unified frame-work, a single-agent Markov decision process can be broken down into a single-time-step multi-agent process. Furthermore we show that Monte-Carlo estimation or Q-learning (depending on whether the values of resulting actions in the episode are known at the time of learning) are equivalent to different agent utility functions in a multi-agent system. This equivalence shows how an often neglected issue in multi-agent systems is equivalent to a well-known deficiency in multi-time-step learning and lays the basis for solving time-extended multi-agent problems, where both credit assignment problems are present.

Agogino, Adrian K.↗

DOE OSTI2024

DOC-DICAM: Domain Aware One Class Defect Identification in Composite Aerostructure Material

Fiber-reinforced composites are a common material used in the design of aircraft structures due to their good tensile strength and resistance to compression. During the manufacturing process, these structures are thoroughly inspected for flaws and defects to ensure structural integrity during commercial use. Non-destructive testing (NDT) is a collection of inspection methods that allow inspectors to evaluate material without altering it. Due to the high safety standards in aerospace manufacturing, the NDT process is done manually and can be a significant bottleneck in the development workflow. In this paper, we develop an AI-based assistance tool to drastically reduce inspection time. Typical AI workflows require large amounts of annotated data, but defects rarely occur resulting in strong class imbalance. To overcome this, we formulate the problem of defect identification as an anomaly detection task in which our primary focus is learning non-defect characteristics. To do this, we develop a multi-task self-supervised learning framework that embeds problem specific domain knowledge into the deep learning model. We verify our method using fuselage data generated in a production environment. As a result, we show that our method can effectively identify defects and requires minimal training and inference time.

anomaly detection↗

NASA NTRS2011

Cognitive Behavioral Training and Education for Spaceflight Operations

Cognitive behavioral-training (CBT) is an evidence-based practice commonly used to help treat insomnia, and is part of NASA's countermeasure regimen for Fatigue Management. CBT addresses the life style and habits of individuals that are maladaptive to managing stress and fatigue. This includes addressing learned behavioral responses that may cause stress and lead to an increased sense of fatigue. While the initial cause of onset of fatigue in the individual may be no longer present, the perception and engrained anticipation of fatigue persist and cause an exaggerated state of tension. CBT combined with relaxation training allows the individual to unlearn the maladaptive beliefs and behaviors and replace them with routines and techniques that allow cognitive restructuring and resultant relief from stress. CBT allows for elimination in individuals of unwanted ruminating thoughts and anticipatory anxiety by, for example, training the individuals to practice stressful situations in a relaxed state. As a result of CBT, relaxation can be accomplished in many ways, such as progressive muscle relaxation, meditation and guided imagery. CBT is not therapy, but rather the synthesis of behavioral countermeasures. CBT utilizes progressive relaxation as a means of reinforcing educational and cognitive countermeasures. These countermeasures include: masking, elimination of distracting thoughts, anxiety control, split attention, cognitive restructuring and other advanced psychological techniques.

Moonmaw, Ronald↗

DOE OSTI2025

Damage progression and failure of SiC/SiC composite tubes under hard-contact radial expansion

The response of silicon carbide (SiC) fiber-reinforced SiC matrix (SiC/SiC) composite cladding to mechanical interaction with fissile fuel is a knowledge gap that must be overcome to design and assess SiC-based cladding systems for advanced nuclear applications. This study developed the relevant mechanical testing capability and identified the failure behavior and the critical microstructural features and processing defects. Sections of SiC composite tube were subjected to a modified expansion-due-to-compression (EDC) test in an X-ray computed tomography microscope: a polyurethane plug pressed surrogate Al 2 O 3 into the inner walls of the SiC/SiC composite tubes to achieve hard contact. A pure EDC test with just a polyurethane plug was also performed as a reference. Through the use of displacement fields, digital volume correlation revealed inhomogeneous deformation fields in the tubes, even for pure EDC, which was related to the inherent defects in the structure. Deep learning–aided segmentation and systematic data analysis revealed that the presence of inhomogeneous deformation applied by the hard contact was exaggerated by the presence of inner surface imperfections left behind from the matrix densification process. In conclusion, the findings provide insights into the applications, highlighting the necessity for improvements in inner surface roughness and the incorporation of localized contacts in pellet–cladding mechanical interaction computational models.

Composites↗

NASA NTRS2002

My Big Wall

It was June and I was in Yosemite National Park in California, 2,000-feet off the ground. I was climbing El Capitan, a majestic 3,000-foot high, mile-wide granite monolith--one of the most sought after and spectacular rock climbs in the world. After three days of climbing on its sheer face, and having completed the most difficult part of the route, my partner and I were heading down. A thunderstorm lasting all night and into the morning had soaked our tiny perch and all our worldly possessions. We began rappelling down the vertical wall by sliding to the ends of two 50meter ropes tied together and looped through a set of fixed rings bolted into the rock. At the end of the ropes was another rappel station consisting of a set of rings, placed by previous climbers for retreating parties, which we used to anchor ourselves to the rock face. We then pulled the ropes down from the rings above, threaded the ones in front of our noses and started down another rope length. Everything we brought up for our five-day climb to the summit we had to bring back down with us: ropes, climbing gear of every sort, sleeping bags, extra clothes, food, water, and other essentials. All this we either stuffed into a haul bag (an oversized reinforced duffel bag) or slung over our shoulders. The retreat was slow and methodical, akin to a train backing down a mountain, giving me ample time to think. My situation made me think about my work, mostly, about all the projects I have managed, or been involved in managing. As a NASA project manager, I have worked on a number of successful projects. I have also been involved in a number of projects I never saw the end of. I thought about all the projects I transferred off of for other opportunities, projects that were in full stride and ran out of funding, and ones put on the shelf because they would not meet a flight date. Oh yes, I have had many success, to be sure, or I would have burned out years ago. Lessons from both the successful and not-so-successful projects have taught me valuable lessons, but it has always been the failures where I've learned the most.

Espinosa, Paul S.↗

NASA NTRS1992

Thermostructural responses of carbon phenolics in a restrained thermal growth test

The thermostructural response of carbon phenolic components in a solid rocket motor (SRM) is a complex process. It involves simultaneous heat and mass transfer along with chemical reactions in a multiphase system with time-dependent material properties and boundary conditions. In contrast to metals, the fracture of fiber-reinforced composites is characterized by the initiation and progression of multiple failures of different modes such as matrix cracks, interfacial debonding, fiber breaks, and delamination. The investigation of thermostructural responses of SRM carbon phenolics is further complicated by different failure modes under static and dynamic load applications. Historically, there have been several types of post-firing anomalies found in the carbon phenolic composites of the Space Shuttle SRM nozzle. Three major failure modes which have been observed on SRM nozzles are pocketing (spallation), ply-lift, and wedge-out. In order to efficiently control these anomalous phenomena, an investigation of fracture mechanisms under NASA/MSFC RSRM (Redesigned Solid Rocket Motor) and SPIP (Solid Propulsion Integrity Program) programs have been conducted following each anomaly. This report reviews the current progress in understanding the effects of the thermostructural behavior of carbon phenolics on the failure mechanisms of the SRM nozzle. A literature search was conducted and a technical bibliography was developed to support consolidation and assimilation of learning from the RSRM and SPIP investigation efforts. Another important objective of this report is to present a knowledge-based design basis for carbon phenolics that combines the analyses of thermochemical decomposition, pore pressure stresses, and thermostructural properties. Possible areas of application of the knowledge-based design include critical material properties development, nozzle component design, and SRM materials control.

Wang, C. Jeff↗

DOE OSTI2026

A User-Friendly GUI Tool for Automated Microstructural Analysis of Fiber-Reinforced Composites and Porous Structures

Understanding and quantifying microstructural features such as fiber orientation and porosity is critical for predicting the mechanical behavior and performance of fiber-reinforced polymer composites. Traditional manual analysis is time-consuming, subjective, and unsuitable for high-throughput datasets. We present a graphical user interface (GUI) application that automates the analysis of microscopy images to extract key microstructural metrics, including fiber orientation tensors, fiber orientation distribution, porosity and pore size distribution. The app integrates multiple image segmentation techniques including global and local thresholding, clustering, and region-based approaches, offering flexibility for different types of image qualities and features. Users can load microstructural images, select regions of interest and segmentation techniques tailored to their image dataset. It also addresses a critical challenge in fiber orientation analysis: the ambiguities caused by touching, overlapping, or partially cut fibers. It supports autorun examples for standardized workflows, enabling reproducible analysis and facilitating training and benchmarking. This tool significantly reduces manual intervention, enhances consistency, and accelerates data generation for structure–property modeling, process optimization, and digital materials research. The tool is intended for use by materials scientists, engineers, and researchers engaged in composite characterization, quality control, and machine learning-based microstructural studies.

Chawla, Komal [ORNL] (ORCID:0000000190327565)↗

NASA NTRS2013

Aerogel-Based Multilayer Insulation with Micrometeoroid Protection

Ultra-low-density, highly hydrophobic, fiber-reinforced aerogel material integrated with MLI (aluminized Mylar reflectors and B4A Dacron separators) offers a highly effective insulation package by providing unsurpassed thermal performance and significant robustness, delivering substantial MMOD protection via the addition of a novel, durable, external aerogel layer. The hydrophobic nature of the aerogel is an important property for maintaining thermal performance if the material is exposed to the environment (i.e. rain, snow, etc.) during ground installations. The hybrid aerogel/MLI/MMOD solution affords an attractive alternative because it will perform thermally in the same range as MLI at all vacuum levels (including high vacuum), and offers significant protection from micrometeoroid damage. During this effort, the required low-density and resilient aerogel materials have been developed that are needed to optimize the thermal performance for space (high vacuum) cryotank applications. The proposed insulation/MMOD package is composed of two sections: a stack of interleaved aerogel layers and MLI intended for cryotank thermal insulation, and a 1.5- to 1-in. (.2.5- to 3.8- cm) thick aerogel layer (on top of the insulation portion) for MMOD protection. Learning that low-density aerogel cannot withstand the hypervelocity impact test conditions, the innovators decided during the course of the program to fabricate a high-density and strong material based on a cross-linked aerogel (X-aerogel; developed elsewhere by the innovators) for MMOD protection. This system has shown a very high compressive strength that is capable of withstanding high-impact tests if a proper configuration of the MMOD aerogel layer is used. It was learned that by stacking two X-aerogel layers [1.5-in. (.3.8-cm) thick] separated by an air gap, the system would be able to hold the threat at a speed of 5 km/s and gpass h the test. The first aerogel panel stopped the projectile from damaging the second aerogel panel. The impacted X-aerogel (the back specimen from the successful test) was further tested in comparison to another similar sample (not impacted) at Kennedy Space Center for thermal conductivity evaluation at cryogenic conditions. The specimens were tested under high vacuum and cryogenic temperatures, using Cryostat 500. The results show that the specimen did not lose a significant amount of thermal performance due to the impact test, especially at high vacuum.

Begag, Redouane↗

DOE OSTI2026

Large Language Model for Validation, Optical Calibration, and Learning (VOCAL) Distributed Temperature Sensing Interface

Distributed temperature sensing (DTS) using fiber optic sensors (FOS) offers a promising method for temperature measurements in advanced reactors, such as sodium fast reactors and molten salt cooled reactors. To support the calibration and validation of DTS measurements, Argonne National Laboratory developed the Validation, Optical Calibration, and Learning (VOCAL) software package. This report describes the integration of a local large language model (LLM) with a retrieval-augmented generation (RAG) system into the VOCAL interface to serve as an interactive user assistant. The LLM framework enhances the VOCAL platform’s accessibility to users by explaining interface components, clarifying inputs and outputs, and answering user queries dynamically in real-time. The accuracy of the LLM assistant performance was evaluated with 20 queries regarding the interface and its parameters using experimental data from the Thermal Hydraulic Experimental Test Article (THETA) facility. Results demonstrate that the LLM achieved a 95% accuracy rate, with a BERTScore of 0.8816 and SBERT value of 0.7417. Furthermore, validation of the RAG system within the LLM framework showed optimal accuracy with k-values between 1 and 2 using the k-refinement convergence test. The prompt perturbation analysis demonstrated good initial consistency for the RAG system, exhibiting the highest accuracy under punctuation variations and the greatest sensitivity under query reordering. Notably, the model’s errors were limited to data retrieval failures rather than factual hallucinations, reinforcing its baseline reliability. The integration of LLM provides a highly accurate, userfriendly enhancement to the VOCAL platform without disrupting its core computational capabilities for FOS calibration and validation.

Hong, Evan↗

NASA NTRS2009

Expedition Earth and Beyond: Using NASA Data Resources and Integrated Educational Strategies to Promote Authentic Research in the Classroom

Teachers in today s classrooms are bound by state required skills, education standards, and high stakes testing. How can they gain skills and confidence to replace units or individual activities with curriculum that incorporates project and inquiry-based learning and promotes authentic research in the classroom? The key to promoting classroom authentic research experiences lies in educator professional development that is structured around teacher needs. The Expedition Earth and Beyond Program is a new geosciences program based at the NASA Johnson Space Center designed to engage, inspire and educate teachers and students in grades 5-14. The program promotes authentic research experiences for classrooms and uses strategies that will help NASA reach its education goals while still allowing educators to teach required standards. Teachers will have access to experts in terrestrial and planetary remote sensing and geoscience; this will enhance their use of content, structure, and relevant experiences to gain the confidence and skills they need to actively engage students in authentic research experiences. Integrated and powerful educational strategies are used to build skills and confidence in teachers. The strategies are as follows: 1) creating Standards-aligned, inquiry-based curricular resources as ready-to-use materials that can be modified by teachers to fit their unique classroom situation; 2) providing ongoing professional development opportunities that focus on active experiences using curricular materials, inquiry-based techniques and expanding content knowledge; 3) connecting science experts to classrooms to deepen content knowledge and provide relevance to classroom activities and real world applications; 4) facilitating students sharing research with their peers and scientists reinforcing their active participation and contributions to research. These components of the Expedition Earth and Beyond Education Program will be enhanced by providing exciting and diverse research opportunities that are inspired by views of Earth from space taken by astronauts on board the International Space Station. The interest and connection to viewing our home planet from space will inevitably spark questions that will drive students to pursue their research investigations, as well as forming a basis for comparisons to the exploration of other planetary bodies in our solar system.

Graffi, Paige Valderrama↗