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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 253 records · Page 14

Quantum Computing Technology Roadmaps and Capability Assessment for Scientific Computing - An analysis of use cases from the NERSC workload

The National Energy Research Scientific Computing Center (NERSC), as the high-performance computing (HPC) facility for the Department of Energy’s Office of Science, recognizes the essential role of quantum computing in its future mission. In this report, we analyze the NERSC workload and identify materials science, quantum chemistry, and high-energy physics as the science domains and application areas that stand to benefit most from quantum computers. These domains jointly make up over 50% of the current NERSC production workload, which is illustrative of the impact quantum computing could have on NERSC’s mission going forward. We perform an extensive literature review and determine the quantum resources required to solve classically intractable problems within these science domains. This review also shows that the quantum resources required have consistently decreased over time due to algorithmic improvements and a deeper understanding of the problems. At the same time, public technology roadmaps from a collection of ten quantum computing companies predict a dramatic increase in capabilities over the next five to ten years. Our analysis reveals a significant overlap emerging in this time frame between the technological capabilities and the algorithmic requirements in these three scientific domains. We anticipate that the execution time of large-scale quantum workflows will become a major performance parameter and propose a simple metric, the Sustained Quantum System Performance (SQSP), to compare system-level performance and throughput for a heterogeneous workload.

97 MATHEMATICS AND COMPUTING↗

Web Map Apps using NASA's Earth Observing Fleet

Through the miracle of open web mapping services for satellite imagery, a garden of new applications has sprouted to monitor the planet across a variety of domains. The Global Imagery Browse Services (GIBS) provide free and open access to full resolution imagery captured by NASAs Earth observing fleet. Spanning 15+ years and running through as recently as a few hours ago, GIBS aims to provide a general-purpose window into NASA's vast archive of the planet. While the vast nature of this archive can be daunting, many domain-specific applications have been built to meet the needs of their respective communities. This presentation will demonstrate a diverse set of these new applications which can take planetarium visitors into (virtual) orbit, guide fire resource managers to hotspots, help anglers find their next catch, illustrate global air quality patterns to local regulators, and even spur a friendly competition to find clouds which are shaped the most like cats. We hope this garden will continue to grow and will illustrate upcoming upgrades to GIBS which may open new pathways for development. data visualization, web services, open access

data visualization↗

Approach to derivation of SIR-C science requirements for calibration

A study undertaken to determine SIR-C (Shuttle Imaging Radar-C) science requirements for polarimetric calibration is described. A model describing the effect of miscalibration is presented, followed by a description of specific experiments and the resulting requirements levied on the system. The effects of miscalibration on some commonly used measures which can be extracted from SAR (synthetic aperture radar) data are also discussed. It is concluded that polarimetric calibration requirements are strongly application-dependent, and that a compromise must be made to maximize the domain of application of the data without prohibitive cost. Data summarizing SIR-C polarimetric calibration goals are also presented.

Dubois, Pascale↗

Design of Rigid-Flex PCB Robotics Leveraging Validated Finite Element Simulations

The use of rigid-flex printed circuit board (PCB) as primary structure has the potential to reduce the weight and volume of robotic systems. In the case of robotics for interplanetary exploration, these systems can leverage origami-inspired folding for increased mobility options and reduced storage volume. Folding rigid-flex PCB robotics can be constructed with rigid PCB connected by short Nomex fabric hinges coupled with flex PCB ribbon cables that permits enhanced system flexibility and energy dissipation to promote impact survivability. This paper presents a design methodology of rigid-flex PCB systems with an emphasis on impact resistance. The design process considers solder joint adequacy, panel bending, and fracture using a finite element (FE) model. The proposed design methodology is developed using a case study with NASA JPL's Pop-Up Folding Flat Explorer Robot (PUFFER). First, the finite-element (FE) modeling methodology is presented with consideration to both frequency and time-domain modeling applications, which include operational self-contact analysis and high impact scenarios. The time-domain impact modeling methodology utilizes hyperelastic material properties for the Nomex hinges. This modeling method is validated using image correlation of PUFFER drop tests. A flowchart is presented to guide users through a validated Abaqus modeling procedure for highly flexible rigid-flex systems. Next, a case study is presented in which PUFFER is subject to drop heights representative of falls into Lunar pits and then the design is refined for a more optimum impact performance. Finally, the results of the case study are used to inform a generalized design methodology for rigid-flex PCB robotics subject to high-impact loads with the considerations presented.

John Bell↗

Design of Rigid-Flex PCB Robotics Leveraging Validated Finite Element Simulations

The use of rigid-flex printed circuit board (PCB) as primary structure has the potential to reduce the weight and volume of robotic systems. In the case of robotics for interplanetary exploration, these systems can leverage origamiinspired folding for increased mobility options and reduced storage volume. Folding rigid-flex PCB robotics can be constructed with rigid PCB connected by short Nomex fabric hinges coupled with flex PCB ribbon cables that permits enhanced system flexibility and energy dissipation to promote impact survivability. This paper presents a design methodology of rigidflex PCB systems with an emphasis on impact resistance. The design process considers solder joint adequacy, panel bending, and fracture using a finite element (FE) model. The proposed design methodology is developed using a case study with NASA JPL’s Pop-Up Folding Flat Explorer Robot (PUFFER). First, the finite-element (FE) modeling methodology is presented with consideration to both frequency and time-domain modeling applications, which include operational self-contact analysis and high impact scenarios. The time-domain impact modeling methodology utilizes hyperelastic material properties for the Nomex hinges. This modeling method is validated using image correlation of PUFFER drop tests. A flowchart is presented to guide users through a validated Abaqus modeling procedure for highly flexible rigid-flex systems. Next, a case study is presented in which PUFFER is subject to drop heights representative of falls into Lunar pits and then the design is refined for a more optimum impact performance. Finally, the results of the case study are used to inform a generalized design methodology for rigid-flex PCB robotics subject to high-impact loads with the considerations presented.

de la Croix, Jean-Pierre↗

Updated Stagnation Point Aeroheating Correlations for Mars Entry

The objective of this work was to develop new engineering correlations for stagnation point aeroheating for Mars entry vehicles. New convective and radiative heating relations have been formulated over a wide range of entry conditions. These relations have been formulated using information from recent experimental testing and modeling enhancements. The new correlations are compared to existing relations commonly used in engineering design and analysis. Finally the correlations are tested by applying them to the Mars Pathfinder entry trajectory to demonstrate their applicability. These new correlations are a significant improvement over existing relations in terms of the accuracy, domain of applicability, and the captured physics.

Brandis, A. M.↗

EUROPA2: Plan Database Services for Planning and Scheduling Applications

NASA missions require solving a wide variety of planning and scheduling problems with temporal constraints; simple resources such as robotic arms, communications antennae and cameras; complex replenishable resources such as memory, power and fuel; and complex constraints on geometry, heat and lighting angles. Planners and schedulers that solve these problems are used in ground tools as well as onboard systems. The diversity of planning problems and applications of planners and schedulers precludes a one-size fits all solution. However, many of the underlying technologies are common across planning domains and applications. We describe CAPR, a formalism for planning that is general enough to cover a wide variety of planning and scheduling domains of interest to NASA. We then describe EUROPA(sub 2), a software framework implementing CAPR. EUROPA(sub 2) provides efficient, customizable Plan Database Services that enable the integration of CAPR into a wide variety of applications. We describe the design of EUROPA(sub 2) from the perspective of both modeling, customization and application integration to different classes of NASA missions.

Bedrax-Weiss, Tania↗

Pattern Identification - A Foundation for Research in the Emphasis of Design Patterns in Systems Engineering and Knowledge Capture

Pattern Language describes the morphology and functionality of a system in the absence of design particulars. Harnessing this capability will provide the Systems Engineering discipline a means of managing the development of increasingly complex systems with increasingly distributed design teams while capturing and retaining knowledge for future generations. Pattern Language is a syntax for describing, and structurally relating, design patterns. Design patterns contextually describe the application of domain knowledge in the engineered solution to the force balance problem. The parallels between pattern recognition and application, as a fundamental stage of human learning, and pattern observation within a complex system, suggests pattern language may be a valuable tool in the capture and dissemination of knowledge. Pattern application has enjoyed considerable study over the last several decades, however much of this work has focused on the replication of design particulars. This work returns to the roots of Pattern Language and explores the utility of patterns as an architectural description and guide, and knowledge capture method, for complex system development beginning with the identification of a time proven design pattern.

Russell, Samuel P.↗

Constrained GAN-Generated X-Ray CT Data For Self-Supervised And Foundation-Model Segmentation Of Concrete Microstructures

Three-dimensional characterization of materials using X-ray computed tomography (XCT) is challenging due to the complexity of internal structures, noise, and variations in resolution. Traditional computer vision models often struggle to accurately segment these images, particularly in domain-specific applications like materials science. While supervised deep learning approaches have been developed to address the limitations of conventional algorithms, they typically require large amounts of labeled training data and often fail to generalize across different datasets. Self-supervised, few-and zero-shot learning methods have gained prominence in natural image processing and segmentation tasks, but their application to scientific imaging remains limited due to the unique structural complexity, noise, and textural artifacts present in materials science data. In this work, we investigate how domain adaptation, leveraging physics-based and GAN-generated synthetic data, impacts segmentation performance. We introduce a modified Contrastive Unpaired Translation (CUT) model designed to generate realistic labeled data, which can be used for training, pre-training, and fine-tuning segmentation models for real XCT microstructure data. We evaluate the performance of two segmentation approaches: a self-supervised network (SSL-ALPNet) and a foundation model (Segment Anything Model), assessing their improvements when pre-trained and/or fine-tuned on the synthesized data. Our results demonstrate that leveraging synthetic data significantly enhances segmentation performance, particularly in challenging materials science applications.

Ziabari, Amir [ORNL] (ORCID:000000034776457X)↗

LLMs for Mfg.—On the State of Large Language Models and Applications to Manufacturing

Additive Manufacturing (AM), referred to as 3D printing, has emerged as a key pillar of Industry 4.0 enabling layer-by-layer fabrication of intricate geometries from CAD models. In parallel, Large Language Models (LLMs), deep learning models for natural language generation trained on vast text corpora, have demonstrated unprecedented capabilities in understanding and generating human-like text. The convergence of these trends opens new opportunities at the intersection of AM and AI/ML, where LLMs can assist engineers and researchers in design, manufacture planning, and knowledge discovery. Recent academic work has begun to explore LLM applications in AM and adjacent fields, such as material science, mechanical engineering, and design for additive manufacturing. This exploration ranges from intelligent process planning to domain-specific knowledge retrieval. This survey provides a comprehensive review of current developments, focusing on peer-reviewed literature contributions that apply, adapt, and advance LLMs in general and domain-specific domains. We analyze state-of-the-art (SOTA) techniques, such as fine-tuning foundational models for specific domains, retrieval-augmented generation (RAG) pipelines, knowledge graph integration, and delve into the architectures and evaluation methods employed. The goal of this survey is to inform researchers and practitioners of the current capabilities and limitations of LLMs in general and in domain-specific applications, and to outline how these models are being tailored to meet the requirements of these applications.

36 MATERIALS SCIENCE↗

Graphitic Carbon Nitride Quantum Dots (g‐C 3 N 4 QDs): From Chemistry to Applications

Since their emergence in 2014, graphitic carbon nitride quantum dots (g-C 3 N 4 QDs) have attracted much interest from the scientific community due to their distinctive physicochemical features, including structural, morphological, electrochemical, and optoelectronic properties. Owing to their desirable characteristics, such as non-zero band gap, ability to be chemically functionalized or doped, possessing tunable properties, outstanding dispersibility in different media, and biocompatibility, g-C 3 N 4 QDs have shown promise for photocatalysis, energy devices, sensing, bioimaging, solar cells, optoelectronics, among other applications. As these fields are rapidly evolving, it is very strenuous to pinpoint the emerging challenges of the g-C 3 N 4 QDs development and application during the last decade, mainly due to the lack of critical reviews of the innovations in the g-C 3 N 4 QDs synthesis pathways and domains of application. Herein, an extensive survey is conducted on the g-C 3 N 4 QDs synthesis, characterization, and applications. Scenarios for the future development of g-C 3 N 4 QDs and their potential applications are highlighted and discussed in detail. In conclusion, the provided critical section suggests a myriad of opportunities for g-C 3 N 4 QDs, especially for their synthesis and functionalization, where a combination of eco-friendly/single step synthesis and chemical modification may be used to prepare g-C 3 N 4 QDs with, for example, enhanced photoluminescence and production yields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phase I Final Technical Report on Energy-Efficient Reconfigurable Universal Accelerator Interconnect

It is well known that application specific computing systems, optimally designed and configured for a given workload, offer much higher energy-efficiency and throughput than general purpose systems. In modern computing systems, heterogeneous computing systems have emerged that exploit the energy and performance benefits of combining various different domain-specific processor architectures. Application domains such as high-performance computing and machine learning now process terabyte-sized data sets, requiring enormous processing and memory resources. These applications have very high-power consumption due to bottlenecks in the electrical interconnection between processing units. This project aims to reduce both communication energy and latency by integrating universally available accelerators with silicon photonics. It also aims to increase system throughput by exploiting emerging technologies in silicon photonic reconfigurable interconnects; this will allow the system to balance itself in real time to accommodate changes in workloads and data flows.

2.5D/3D integration↗

Application of augmented-Lagrangian methods in meteorology: Comparison of different conjugate-gradient codes for large-scale minimization

A Lagrange multiplier method using techniques developed by Bertsekas (1982) was applied to solving the problem of enforcing simultaneous conservation of the nonlinear integral invariants of the shallow water equations on a limited area domain. This application of nonlinear constrained optimization is of the large dimensional type and the conjugate gradient method was found to be the only computationally viable method for the unconstrained minimization. Several conjugate-gradient codes were tested and compared for increasing accuracy requirements. Robustness and computational efficiency were the principal criteria.

Navon, I. M.↗

Frequency-Domain Deconvolution for Flight Dynamics Applications

A deconvolution method is presented for estimating input data from measured output data and a model of the dynamic process involved. The method uses an optimal Wiener filter for separating the measured data into signal and noise components, and a high-accuracy Fourier transform for inverting the model dynamics in the frequency domain. The method is an extension of optimal Fourier smoothing, and uses a technique to enhance the contrast between the signal and noise spectra in designing the Wiener filter. The deconvolution method was applied to simulation and flight test data for the purposes of removing unwanted distortions introduced by signal-conditioning filters and sensor dynamics, and for reconstructing turbulence inputs from measured sensor data. Results indicated hat the method performs well given good signal-to-noise levels and accurate models of the dynamic process.

Grauer, Jared A.↗

Transport of Space Environment Electrons: A Simplified Rapid-Analysis Computational Procedure

A computational procedure for describing transport of electrons in condensed media has been formulated for application to effects and exposures from spectral distributions typical of electrons trapped in planetary magnetic fields. The procedure is based on earlier parameterizations established from numerous electron beam experiments. New parameterizations have been derived that logically extend the domain of application to low molecular weight (high hydrogen content) materials and higher energies (approximately 50 MeV). The production and transport of high energy photons (bremsstrahlung) generated in the electron transport processes have also been modeled using tabulated values of photon production cross sections. A primary purpose for developing the procedure has been to provide a means for rapidly performing numerous repetitive calculations essential for electron radiation exposure assessments for complex space structures. Several favorable comparisons have been made with previous calculations for typical space environment spectra, which have indicated that accuracy has not been substantially compromised at the expense of computational speed.

Nealy, John E.↗