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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 NTRS2026

Thermoplastic Matrix Composite Design for Cryotanks Using Multiscale Modeling and Bayesian Optimization

Designing lightweight, robust cryogenic storage tanks is critical for future launch vehicles, in-space propellant storage, and hydrogen powered aircraft. This work presents a multiscale modeling and Bayesian optimization framework for the design of thermoplastic matrix composite cryotanks. Molecular dynamics simulations are first used to determine temperature-dependent constituent properties for candidate thermoplastic matrices, which are homogenized to the lamina scale using NASA’s Multiscale Analysis Tool (NASMAT). These lamina properties, in combination with laminate family generation rules, are evaluated in HyperX structural optimization software to identify stacking sequences that meet all cryogenic load requirements. A Bayesian optimization framework is applied, with HyperX in the loop (via the HyperX API) to efficiently search across material and laminate design variables, yielding an optimized cryotank configuration with significant reductions in design cycle time compared to exhaustive search approaches.

thermoplastics↗

NASA NTRS1981

Software error detection

Several methods were employed to detect both the occurrence and source of errors in the operational software of the AN/SLQ-32. A large embedded real time electronic warfare command and control system for the ROLM 1606 computer are presented. The ROLM computer provides information about invalid addressing, improper use of privileged instructions, stack overflows, and unimplemented instructions. Additionally, software techniques were developed to detect invalid jumps, indices out of range, infinte loops, stack underflows, and field size errors. Finally, data are saved to provide information about the status of the system when an error is detected. This information includes I/O buffers, interrupt counts, stack contents, and recently passed locations. The various errors detected, techniques to assist in debugging problems, and segment simulation on a nontarget computer are discussed. These error detection techniques were a major factor in the success of finding the primary cause of error in 98% of over 500 system dumps.

Buechler, W.↗

NASA NTRS1976

Hardware additions to microprocessor architecture aid software development

An address trap (breakpoint) mechanism and last-in-first-out (LIFO) address stack are suggested as two additions to the basic microprocessor architecture whose functions are solely to aid the programmer. These devices provide the programmer with the ability to specify address breakpoints and to trace program execution back through N instructions, where N is the depth of the stack. Both devices, plus interface logic and buffering, have been designed for an INTEL 8080-based system using approximately 25 integrated-circuit packages.

Sievers, M. W.↗

NASA NTRS2026

Smart Process Planning for Automated Fiber Placement

Many industries, including aerospace, automotive, wind energy, maritime, and sporting goods, rely on strong, lightweight materials called composites. These materials are made by layering fibers, which can come in the form of narrow strips or wider sheets, and setting them in a polymer matrix. One of the most advanced ways to make these parts is through automated fiber placement, where a machine lays down the fibers in precise patterns. This method can create very efficient and strong designs, but it is complex, expensive, and often depends heavily on the experience of skilled engineers. Today, the design, manufacturing, and inspection stages of composite production are usually handled separately. This separation means that important information, such as how a part will be built or what defects might occur, is not always shared between stages. As a result, parts may not be as lightweight, strong, or defect-free as possible, and the process can take longer and cost more. This research develops a smart process planning system that connects design, manufacturing, and inspection into one continuous process. Built as software that works with existing tools, the system can automatically plan how the fibers are placed, predicting and reducing defects while improving both manufacturability and strength. The system optimizes not only individual layers but also how defects are distributed across all layers, preventing them from stacking up in ways that weaken the final part. It also uses inspection results from completed parts to improve future designs, creating a feedback loop where each stage informs the others. The system was tested by designing a composite panel using this new approach and comparing it to a panel made with state-of-the-art manual planning methods. The results showed that the system could intentionally control where defects appeared and increase the efficiency of the planning process. By unifying design, manufacturing, and inspection, this research shows a way to make advanced composite manufacturing more efficient, consistent, and cost-effective. This approach lowers the barrier to using automated fiber placement and opens the door for its wider adoption not only in aerospace but also in industries such as automotive, wind energy, maritime, and sporting goods, where strong and lightweight structures are essential.

Computer-Aided Process Planning↗