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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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23 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Effective Defect Detection Using Instance Segmentation for NDI

Ultrasonic testing is a common Non-Destructive Inspection (NDI) method used in aerospace manufacturing. However, the complexity and size of the ultrasonic scans make it challenging to identify defects through visual inspection or machine learning models. Using computer vision techniques to identify defects from ultrasonic scans is an evolving research area. In this study, we used instance segmentation to identify the presence of defects in the ultrasonic scan images of composite panels that are representative of real components manufactured in aerospace. We used two models based on Mask- RCNN (Detectron 2) and YOLO 11 respectively. Additionally, we implemented a simple statistical pre-processing technique that reduces the burden of requiring custom-tailored pre-processing techniques. Our study demonstrates the feasibility and effectiveness of using instance segmentation in the NDI pipeline by significantly reducing data pre-processing time, inspection time, and overall costs.

computer vision techniques↗
DOE OSTI2024

Mechanochemical in Situ Encapsulation of Palladium in Covalent Organic Frameworks

Palladium-encapsulated covalent organic frameworks (Pd/COFs) have garnered enormous attention in heterogeneous catalysis. However, the dominant ex situ encapsulation synthesis is tedious (multistep), time-consuming (typically 4 days or more), and involves the use of noxious solvents. Here we develop a mechanochemical in situ encapsulation strategy that enables the one-step, time-efficient, and environmentally benign synthesis of Pd/COFs. By ball milling COF precursors along with palladium acetate (Pd(OAc) 2 ) in one pot under air at room temperature, Pd/COF hybrids were readily synthesized within an hour, exhibiting high crystallinity, uniform Pd dispersion, and superb scalability up to gram scale. Moreover, this versatile strategy can be extended to the synthesis of three Pd/COFs. Remarkably, the resulting Pd/DMTP-TPB showcases extraordinary activity (96-99% yield in 1 h at room temperature) and broad substrate scope (>10 functionalized biaryls) for the Suzuki-Miyaura coupling reaction of aryl bromides and arylboronic acids. Furthermore, the heterogeneity of Pd/DMTP-TPB is verified by recycling and leaching tests. Finally, the mechanochemical in situ encapsulation strategy disclosed herein paves a facile, rapid, scalable, and environmentally benign avenue to access metal/COF catalysts for efficient heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Are humans still necessary? Expanding the discussion

The rise of automation, artificial intelligence (AI), and autonomous systems raises important questions about the future role of humans and the field of human factors/ergonomics in workplaces. This paper builds on Dr. Peter Hancock’s 2023 ‘Are Humans Still Necessary?’ article published in the Ergonomics journal. Using a multi-method approach that included a debate, opinion polling, roundtable discussions, and AI queries, the current effort examined the necessity of human involvement in future work environments. Debate team members presented arguments for and against the need for human workers, considering human factors, technology, and socioeconomic factors. Observations indicate that while AI may handle routine tasks, humans will likely remain essential for complex decision making, creativity, and ethical considerations. The paper advocates for viewing workplace dynamics as collaborative human-AI partnerships rather than competition, highlighting the need for a transdisciplinary approach in which human factors/ergonomics professionals play a vital role in enhancing these relationships.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

A haplotype‐resolved reference genome of Quercus alba sheds light on the evolutionary history of oaks

Summary White oak ( Quercus alba ) is an abundant forest tree species across eastern North America that is ecologically, culturally, and economically important. We report the first haplotype‐resolved chromosome‐scale genome assembly of Q. alba and conduct comparative analyses of genome structure and gene content against other published Fagaceae genomes. We investigate the genetic diversity of this widespread species and the phylogenetic relationships among oaks using whole genome data. Despite strongly conserved chromosome synteny and genome size across Quercus , certain gene families have undergone rapid changes in size, including defense genes. Unbiased annotation of resistance (R) genes across oaks revealed that the overall number of R genes is similar across species – as are the chromosomal locations of R gene clusters – but, gene number within clusters is more labile. We found that Q. alba has high genetic diversity, much of which predates its divergence from other oaks and likely impacts divergence time estimations. Our phylogenetic results highlight widespread phylogenetic discordance across the genus. The white oak genome represents a major new resource for studying genome diversity and evolution in Quercus . Additionally, we show that unbiased gene annotation is key to accurately assessing R gene evolution in Quercus .

Larson, Drew A. [Department of Biology Indiana Uni↗
DOE OSTI2025

Framework and Tool for Artificial Intelligence & Machine Learning (AI/ML) Enabled Automated Non-Destructive Inspection of Composites Aerostructures Manufacturing

Vehicles and systems in the field of aerospace have two major requirements: a high demand for a large quantity and an expectation to perform for their lifetime with little to no failures. Thus, there is a need for a fast production rate of aerospace products with high quality. Improvements to production rate have many benefits, including a reduction in energy consumption per unit manufactured. This would be from factory energy usage, which is required to build and verify a product. Manufacturing process specifications require inspection of parts to determine if any flaws are present. Depending on factory planning and product quality, especially at higher rates, the evaluation process can pose a production rate bottleneck. This project was comprised of using artificial intelligence and machine learning (AI/ML) methods on inspection evaluations with the objective of reducing the required time to produce an aerospace structure or product and without reducing the final quality.

42 ENGINEERING↗