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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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At least 91 records · Page 5

Failure Analysis Study and Long-Term Reliability of Optical Assemblies with End-Face Damage

In June 2005, the NESC received a multi-faceted request to determine the long term reliability of fiber optic termini on the ISS that exhibited flaws not manufactured to best workmanship practices. There was a lack of data related to fiber optic workmanship as it affects the long term reliability of optical fiber assemblies in a harsh environment. A fiber optic defect analysis was requested which would find and/or create various types of chips, spalls, scratches, etc., that were identified by the ISS personnel. Once the defects and causes were identified the next step would be to perform long term reliability testing of similar assemblies with similar defects. The goal of the defect analysis would be for the defects to be observed and documented for deterioration of fiber optic performance. Though this report mostly discusses what has been determined as evidence of poor manufacturing processes, it also concludes the majority of the damage could have been avoided with a rigorous process in place.

Kichak, Robert A.↗

Preliminary evaluation of adhesion strength measurement devices for ceramic/titanium matrix composite bonds

The adhesive bond between ceramic cement and a titanium matrix composite substrate to be used in the National Aerospace Plane program is evaluated. Two commercially available adhesion testers, the Sebastian Adherence Tester and the CSEM REVETEST Scratch Tester, are evaluated to determine their suitability for quantitatively measuring adhesion strength. Various thicknesses of cements are applied to several substrates, and bond strengths are determined with both testers. The Sabastian Adherence Tester has provided limited data due to an interference from the sample mounting procedure, and has been shown to be incapable of distinguishing adhesion strength from tensile and shear properties of the cement itself. The data from the scratch tester has been found to be difficult to interpret due to the porosity and hardness of the cement. Recommendations are proposed for a more reliable adhesion test method.

Pohlchuck, Bobby↗

Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data

Abstract Artificial intelligence (AI) and machine learning (ML) have been increasingly used in materials science to build predictive models and accelerate discovery. For selected properties, availability of large databases has also facilitated application of deep learning (DL) and transfer learning (TL). However, unavailability of large datasets for a majority of properties prohibits widespread application of DL/TL. We present a cross-property deep-transfer-learning framework that leverages models trained on large datasets to build models on small datasets of different properties. We test the proposed framework on 39 computational and two experimental datasets and find that the TL models with only elemental fractions as input outperform ML/DL models trained from scratch even when they are allowed to use physical attributes as input, for 27/39 (≈ 69%) computational and both the experimental datasets. We believe that the proposed framework can be widely useful to tackle the small data challenge in applying AI/ML in materials science.

36 MATERIALS SCIENCE↗

Sim-to-real supervised domain adaptation for radioisotope identification

Machine learning has the potential to improve the speed and reliability of radioisotope identification using gamma spectroscopy. However, meticulously labeling an experimental dataset for training is often prohibitively expensive, while training models purely on synthetic data is risky due to the domain gap between simulated and experimental measurements. In this research, we demonstrate that supervised domain adaptation can substantially improve the performance of radioisotope identification models by transferring knowledge between synthetic and experimental data domains. We consider two domain adaptation scenarios: (1) a simulation-to-simulation adaptation, where we perform multi-label proportion estimation using simulated high-purity germanium detectors, and (2) a simulation-to-experimental adaptation, where we perform multi-class, single-label classification using measured spectra from handheld lanthanum bromide (LaBr) and sodium iodide (NaI) detectors. We begin by pretraining a spectral classifier on synthetic data using a custom transformer-based neural network. After subsequent fine-tuning on just 64 labeled experimental spectra, we achieve a test accuracy of 96% in the sim-to-real scenario with a LaBr detector, far surpassing a synthetic-only baseline model (75%) and a model trained from scratch (80%) on the same 64 spectra. Furthermore, we demonstrate that domain-adapted models learn more human-interpretable features than experiment-only baseline models. Overall, our results highlight the potential for supervised domain adaptation techniques to bridge the sim-to-real gap in radioisotope identification, enabling the development of accurate and explainable classifiers even in real-world scenarios where access to experimental data is limited.

Lalor, Peter W.↗

Deep convolutional autoencoders as generic feature extractors in seismological applications

The idea of using a deep autoencoder to encode seismic waveform features and then use them in different seismological applications is appealing. In this paper, we designed tests to evaluate this idea of using autoencoders as feature extractors for different seismological applications, such as event discrimination (i.e., earthquake vs. noise waveforms, earthquake vs. explosion waveforms), and phase picking. These tests involve training an autoencoder, either undercomplete or overcomplete, on a large amount of earthquake waveforms, and then using the trained encoder as a feature extractor with subsequent application layers (either a fully connected layer, or a convolutional layer plus a fully connected layer) to make the decision. By comparing the performance of these newly designed models against the baseline models trained from scratch, we conclude that the autoencoder feature extractor approach may only outperform the baseline under certain conditions, such as when the target problems require features that are similar to the autoencoder encoded features, when a relatively small amount of training data is available, and when certain model structures and training strategies are utilized. The model structure that works best in all these tests is an overcomplete autoencoder with a convolutional layer and a fully connected layer to make the estimation.

58 GEOSCIENCES↗

Mathematics Integrated with Computer Science through Scratch: Curricular Modules for the Middle Grades

A project funded by the National Science Foundation, Computer Science Integrated with Mathematics in Middle Schools (CSIMMS) (DRL-1640039), brought middle-school mathematics teachers together with university computer science (CS) faculty and STEM education faculty to design, develop, and test curriculum modules in which CS is integrated into instruction for middle-school general-mathematics courses. The project developed integrated math/CS curriculum modules (for grades 6, 7, and 8), complete with student tasks and teacher materials to guide classroom implementation. Across the project, sixteen teachers from four middle schools representing different school contexts (both urban and suburban, serving students from a range of demographic and socioeconomic backgrounds) participated as members of the design team and trial testers of the math/CS modules. All modules underwent multiple years of testing and refinement, with extensive input from the teachers who co-designed and implemented them. Approximately 50-100 middle-school students participated in the classes of those who taught each year. The modules in this volume feature a range of models for integrating mathematics and computer science at the 6th and 7th grade levels. All modules foreground the teaching of grade-level mathematics content, with computer science functioning to motivate and/or reinforce these ideas.

Andrews larson, Christine↗

High Strength and Fracture Resistance of Reduced-Activity W-Ta-Ti-V-Zr High-Entropy Alloy for Fusion Energy Applications

Refractory high-entropy alloys (HEAs) are promising candidates for next-generation nuclear applications, particularly fusion reactors, due to their excellent high-temperature mechanical properties and irradiation resistance. Here, the microstructure and mechanical behavior were investigated for an equimolar WTaTiVZr HEA, designed from a palette of low-activation elements. The as-cast alloy exhibited a dendritic microstructure composed of W-Ta rich dendrites and Zr-Ti-V rich inter-dendritic regions, both possessing a body-centered cubic (BCC) crystal structure. Room temperature bulk compression tests showed ultra-high strength of around 1.6 GPa and plastic strain ~6%, with fracture surfaces showing cleavage facets. The alloy also demonstrated excellent high-temperature strength of ~650 MPa at 500 °C. Scratch-based fracture toughness was ~38 MPa√m for the as-cast WTaTiVZr HEA compared to ~25 MPa√m for commercially used pure tungsten. This higher value of fracture toughness indicates superior damage tolerance relative to commercially used pure tungsten. These results highlight the alloy’s potential as a low-activation structural material for high-temperature plasma-facing components (PFCs) in fusion reactors.

Physics↗

A Lifetime of Shine

Moen Incorporated identified a market need for more durable polished brass plumbing fixtures. NASA's Glenn Research Center is a leader in surface coating technology, which enhances the physical properties of a wide range of materials. The collaborative efforts of Glenn and Moen resulted in a new polished brass finish called LifeShine(R). Based on testing results generated at NASA Glenn, Moen was able to manufacture an affordable, polished brass finish that is as durable as chrome, and resists deterioration. LifeShine is guaranteed to resist normal wear and tear and is even scratch-resistant to cleaning products as abrasive as steel wool. Moen was able to incorporate other colors into the LifeShine finish technology including classic gold, nickel, Satine(TM), Black Opal(TM), stainless, and copper. The company added titanium to LifeShine, making the finish even stronger and increasing its already superior durability. Highly resistant to salt and humidity, the LifeShine finish will remain intact even when the fixture is dented.

Source record↗

How Beneficial Is Pretraining on a Narrow Domain-Specific Corpus for Information Extraction about Photocatalytic Water Splitting?

Language models trained on domain-specific corpora have been employed to increase the performance in specialized tasks. However, little previous work has been reported on how specific a “domain-specific” corpus should be. Here, we test a number of language models trained on varyingly specific corpora by employing them in the task of extracting information from photocatalytic water splitting. We find that more specific corpora can benefit performance on downstream tasks. Furthermore, PhotocatalysisBERT, a pretrained model from scratch on scientific papers on photocatalytic water splitting, demonstrates improved performance over previous work in associating the correct photocatalyst with the correct photocatalytic activity during information extraction, achieving a precision of 60.8(+11.5)% and a recall of 37.2(+4.5)%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Handheld White Light Interferometer for Measuring Defect Depth in Windows

Accurate quantification of defects (scratches and impacts) is vital to the certification of flight hardware and other critical components. The amount of damage to a particular component contributes to the performance, reliability, and safety of a system, which ultimately affects the success or failure of a mission or test. The launch-commit criteria on a Space Shuttle Orbiter window are governed by the depth of the defects that are identified by a visual inspection. This measurement of a defect is not easy to obtain given the environment, size of the defect, and location of the window(s). The determination of depth has typically been performed by taking a mold impression and measuring the impression with an optical profiling instrument. Another method of obtaining an estimate of the depth is by using a refocus microscope. To use a refocus microscope, the surface of the glass and bottom of the defect are, in turn, brought into focus by the operator. The amount of movement between the two points corresponds to the depth of the defect. The refocus microscope requires a skilled operator and has been proven to be unreliable when used on Orbiter windows. White light interferometry was chosen as a candidate to replace the refocus microscope. The White Light Interferometer (WLI) was developed to replace the refocus microscope as the instrument used for measuring the depth of defects in Orbiter windows. The WLI consists of a broadband illumination source, interferometer, detector, motion control, displacement sensor, mechanical housing, and support electronics. The illumination source for the WLI is typically a visible light emitting diode (LED) or a near-infrared superluminescent diode (SLD) with power levels of less than a milliwatt. The interferometer is a Michelson configuration consisting of a 1-in. (2.5-cm) cube beam splitter, a 0.5-in. (1.3-cm) optical window as a movable leg (used to closely match the return intensity of the fixed leg from the window), and a mirrored prism to fold the optics into the mechanical housing. The detector may be one of many C-mount CCD (charge-coupled device) cameras. Motion is provided by a commercial nanostepping motor with a serial interface. The displacement sensor is a custom device specifically designed for this application. The mechanical housing and support electronics were designed to integrate the various components into an instrument that could be physically handled by a technician and easily transported.

Youngquist, Robert↗

Bubble formation in microgravity

An extensive experimental program was initiated for the purpose of understanding the mechanisms leading to bubble generation during fluid handling procedures in a microgravity environment. Several key fluid handling procedures typical for PCG experiments were identified for analysis in that program. Experiments were designed to specifically understand how such procedures can lead to bubble formation. The experiments were then conducted aboard the NASA KC-135 aircraft which is capable of simulating a low gravity environment by executing a parabolic flight attitude. However, such a flight attitude can only provide a low gravity environment of approximately 10-2go for a maximum period of 30 seconds. Thus all of the tests conducted for these experiments were designed to last no longer than 20 seconds. Several experiments were designed to simulate some of the more relevant fluid handling procedures during protein crystal growth experiments. These include submerged liquid jet cavitation, filling of a cubical vessel, submerged surface scratch, attached drop growth, liquid jet impingement, and geysering experiments. To date, four separate KC-135 flight campaigns were undertaken specifically for performing these experiments. However, different experiments were performed on different flights.

Antar, Basil N.↗

NASA Technologies that Benefit Society

Applications developed on Earth of technology needed for space flight have produced thousands of spinoffs that contribute to improving national security, the economy, productivity and lifestyle. Over the course of it s history, NASA has nurtured partnerships with the private sector to facilitate the transfer of NASA-developed technology. For every dollar spent on research and development in the space program, it receives back $7 back in the form of corporate and personal income taxes from increased jobs and economic growth. A new technology, known as Liquid-metal alloy, is the result of a project funded by NASA s Jet Propulsion Lab. The unique technology is a blend of titanium, zirconium, nickel, copper and beryllium that achieves a strength greater than titanium. NASA plans to use this metal in the construction of a drill that will help for the search of water beneath the surface of Mars. Many other applications include opportunities in aerospace, defense, military, automotive, medical instrumentation and sporting goods.Developed in the 1980 s, the original Sun Tigers Inc sunlight-filtering lens has withstood the test of time. This technology was first reported in 1987 by NASA s JPL. Two scientists from JPL were later tasked with studying the harmful effects of radiation produced during laser and welding work. They came up with a transparent welding curtain that absorbs, filters and scatters light to maximize protection of human eyes. The two scientists then began doing business as Eagle Eye Optics. Each pair of sunglasses comes complete with ultraviolet protection, dual layer scratch resistant coating, polarized filters for maximum protection against glare and high visual clarity. Sufficient evidence shows that damage to the eye, especially to the retina, starts much earlier than most people realize. Sun filtering sunglasses are important. Winglets seen at the tips of airplane wings are among aviations most visible fuel-saving, performance enhancing technology. Aerodynamics centers on two majors forces-lift and drag. Lift enables the plane to fly and drag is the resistance encountered while moving through the air. The air coming off the end of a standard wing, in a vortex, causes significant drag and turbulence, forcing the spacing between takeoffs. A Langley engineer for NASA published finding in 1976 and verified by test in 1977 that winglets produce a 7 percent increase in lift-drag ratio with a 20 percent decrease in drag. This configuration reduces emissions, allows for greater range and carry more payload and the planes fly more quietly. Winglet technology has saved 2 billion gallons of jet fuel worldwide in 2010. Aerogel represents what technology experts believe to be the best insulation material ever invented. It is very light, flexible and can withstand temperatures of minus 3000 deg F. Aerogel products will be found in everything from clothing, to building insulation to space vehicles. Corpo Nove incorporated the Spaceloft version of the NASA-developed aerogel material into this jacket which was test during an Antarctic expedition.

Griffin, Amanda↗

From natural language to control signals: a conceptual framework for semantic channel finding in complex experimental infrastructure

Modern experimental platforms such as particle accelerators, fusion devices, telescopes, and industrial process control systems expose tens to hundreds of thousands of control and diagnostic channels, accumulated over decades of hardware evolution. Operators and AI systems alike depend on informal expert knowledge, inconsistent naming conventions, and scattered documentation to locate the signals required for monitoring, troubleshooting, and automated control, creating a persistent bottleneck for reliability, scalability, and emerging language-model-driven interfaces. We formalize semantic channel finding, the task of mapping natural-language intent to concrete control-system signals, as a general problem in complex experimental infrastructure, and introduce a four-paradigm conceptual framework to guide architecture selection based on facility-specific data regimes. The paradigms span (i) direct in-context lookup over small, curated channel dictionaries, (ii) constrained hierarchical navigation through structured trees, (iii) interactive agent exploration using iterative reasoning and tool-based database queries, and (iv) ontology-grounded semantic search that decouples channel meaning from facility-specific naming conventions. We demonstrate the practical feasibility of each paradigm through proof-of-concept implementations at four operational facilities spanning two orders of magnitude in scale: from compact free-electron lasers to large synchrotron light sources, operating under diverse control-system architectures ranging from clean hierarchical naming schemes to legacy environments with decades of heterogeneous conventions. Where evaluated against expert-curated operational queries, these instantiations achieve 90%–97% accuracy, validating the framework’s applicability across real-world deployment scenarios. To accelerate adoption across the broader scientific and industrial control-system community, we release open-source, plug-and-play implementations of all three interactive paradigms-direct lookup, hierarchical navigation, and middle-layer exploration-within the Osprey framework, together with tools for channel database generation, interactive testing, and minimal-configuration deployment. This work establishes semantic channel finding as a foundational capability for human-centric and agentic AI interfaces at large-scale facilities, providing both a systematic framework for architecture design and practical resources to enable adoption without building custom infrastructure from scratch.

channel finding↗

MATEY: multiscale adaptive transformer models for spatiotemporal physical systems

Accurate representation of the multiscale features in spatiotemporal physical systems using vision transformer architectures requires extremely long, computationally prohibitive token sequences. To address this issue, we propose two novel adaptive tokenization schemes that dynamically adjust patch sizes based on local features: one ensures convergent behavior to uniform patch refinement, while the other offers better computational efficiency. Moreover, we present a set of spatiotemporal attention schemes, where the temporal or axial spatial dimensions are decoupled, to evaluate their baseline computational and data efficiencies and to determine whether adaptive tokenization can improve this performance. We assess the performance of the proposed multiscale adaptive model, MATEY, in a sequence of experiments. Compared to a full spatiotemporal attention scheme or a scheme that decouples only the temporal dimension, we find that fully decoupled axial attention is less efficient and expressive, requiring more training time and model parameters to achieve the same accuracy. The experiments on the adaptive tokenization schemes show that, compared to a uniformly refined model, the proposed schemes achieve comparable or improved accuracy at a much lower cost in the tested two-dimensional settings. While the asymptotic analysis suggests the potential for favorable scaling, empirical validation at substantially longer sequence lengths remains to be performed in future work. Finally, we demonstrate in two fine-tuning tasks featuring different physics that models pretrained on PDEBench data outperform the ones trained from scratch, especially in the low data regime with frozen attention.

adaptive tokenization↗

Implementation and Synthesis of Math Library Functions

Achieving speed and accuracy for math library functions like exp, sin, and log is difficult. This is because low-level implementation languages like C do not help math library developers catch mathematical errors, build implementations incrementally, or separate high-level and low-level decision making. This ultimately puts development of such functions out of reach for all but the most experienced experts. To address this, we introduce MegaLibm, a domain-specific language for implementing, testing, and tuning math library implementations. MegaLibm is safe, modular, and tunable. Implementations in MegaLibm can automatically detect mathematical mistakes like sign flips via semantic wellformedness checks, and components like range reductions can be implemented in a modular, composable way, simplifying implementations. Once the high-level algorithm is done, tuning parameters like working precisions and evaluation schemes can be adjusted through orthogonal tuning parameters to achieve the desired speed and accuracy. MegaLibm also enables math library developers to work interactively, compiling, testing, and tuning their implementations and invoking tools like Sollya and type-directed synthesis to complete components and synthesize entire implementations. MegaLibm can express 8 state-of-the-art math library implementations with comparable speed and accuracy to the original C code, and can synthesize 5 variations and 3 from-scratch implementations with minimal guidance.

97 MATHEMATICS AND COMPUTING↗

Launch Pad Coatings for Smart Corrosion Control

Corrosion is the degradation of a material as a result of its interaction with the environment. The environment at the KSC launch pads has been documented by ASM International (formerly American Society for Metals) as the most corrosive in the US. The 70 tons of highly corrosive hydrochloric acid that are generated by the solid rocket boosters during a launch exacerbate the corrosiveness of the environment at the pads. Numerous failures at the pads are caused by the pitting of stainless steels, rebar corrosion, and the degradation of concrete. Corrosion control of launch pad structures relies on the use of coatings selected from the qualified products list (QPL) of the NASA Standard 5008A for Protective Coating of Carbon Steel, Stainless Steel, and Aluminum on Launch Structures, Facilities, and Ground Support Equipment. This standard was developed to establish uniform engineering practices and methods and to ensure the inclusion of essential criteria in the coating of ground support equipment (GSE) and facilities used by or for NASA. This standard is applicable to GSE and facilities that support space vehicle or payload programs or projects and to critical facilities at all NASA locations worldwide. Environmental regulation changes have dramatically reduced the production, handling, use, and availability of conventional protective coatings for application to KSC launch structures and ground support equipment. Current attrition rate of qualified KSC coatings will drastically limit the number of commercial off the shelf (COTS) products available for the Constellation Program (CxP) ground operations (GO). CxP GO identified corrosion detection and control technologies as a critical, initial capability technology need for ground processing of Ares I and Ares V to meet Constellation Architecture Requirements Document (CARD) CxP 70000 operability requirements for reduced ground processing complexity, streamlined integrated testing, and operations phase affordability. Researchers at NASA's Corrosion Technology Laboratory at KSC are developing a smart, environmentally friendly coating system for early corrosion detection, inhibition, and self healing of mechanical damage without external intervention. This smart coating will detect and respond actively to corrosion and mechanical damage such as abrasion and scratches, in a functional and predictable manner, and will be capable of adapting its properties dynamically. This coating is being developed using corrosion sensitive microcapsules that deliver the contents of their core (corrosion inhibiting compounds, corrosion indicators, and self healing agents) on demand when corrosion or mechanical damage to the coating occurs.

Calle, Luz M.↗

Issues/considerations and performance prediction of LEO protective coatings

Organic materials can be used in low earth orbit for long periods only if they are made to be durable to atomic oxygen in addition to the threats of ultraviolet radiation, micrometeoroid and debris impact, thermal cycling, and charged particle radiation. In many materials applications, it is more cost-effective to utilize atomic oxygen protective coatings over materials which are vulnerable to attack by atomic oxygen rather than developing alternative materials which are inherently durable. Many metal and metal oxide coatings have been shown to be potentially suitable for long term protection of organic polymers in low earth orbit. The protection afforded by thin film coatings on polymeric substrates is highly dependent on the completeness of coverage of the coating. Thus, the prime indicator of durability is the size and abundance of pin windows and scratches in the protective coating. Such defects depend on the deposition technique, smoothness of the surface to be protected, and presence of particulate contaminants. Issues and considerations relevant to substrate preparation, deposition of protective coatings, ground laboratory simulation and evaluation of threats in low earth orbit to protective materials, results of in-space tests, and the use of Monte Carlo modeling techniques to predict in-space durability are presented in graphic form.

Banks, Bruce A.↗

NSI-1 Squib adapter development and final test report for usage on space shuttle gas sampler valve/bottle assembly 3270

The possibility of utilizing the NSI-1 squib in place cartridge assembly 2270 for the function of both events required for the Space Shuttle Gas Sampler Valve/Bottle Assembly 3270 was determined. Additionally, it was a requirement that the closure disk of the NSI-1 squib and explosive residue therefrom be retained from the valve cavity in so far as possible to prevent any significant particulate from scratching the valve bore and causing sample leakage following the postfire 2 event.

Siebel, J. E.↗