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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

AMPHION: Specification-based programming for scientific subroutine libraries

AMPHION is a knowledge-based software engineering (KBSE) system that guides a user in developing a diagram representing a formal problem specification. It then automatically implements a solution to this specification as a program consisting of calls to subroutines from a library. The diagram provides an intuitive domain oriented notation for creating a specification that also facilitates reuse and modification. AMPHION'S architecture is domain independent. AMPHION is specialized to an application domain by developing a declarative domain theory. Creating a domain theory is an iterative process that currently requires the joint expertise of domain experts and experts in automated formal methods for software development.

Lowry, Michael↗
NASA NTRSDate not supplied

Performance Risk Model (PRisM) Proof-of-Concept: An Operational Decision Support Tool to Predict Crew Performance in Space from Available Performance Tests

The Crew Health and Performance-Probabilistic Risk Assessment (CHP-PRA) team at NASA Glenn Research Center has developed a range of tools to evaluate astronaut health during spaceflight and to optimize the medical set required for missions. Among these, the Performance Risk Model (PRisM) represents a novel advancement, extending CHP-PRA’s focus beyond medical systems into the domain of human performance. Such tool could be pivotal in optimizing astronaut capabilities during space travel, thereby enhancing overall mission success. PRisM leverages data from well-established performance assessments conducted during previous crewed space missions and Earth analogs to strategically predict outcomes for planned tasks, even when direct performance testing has not been conducted for those specific tasks. To evaluate performance, PRisM references the various metrics outlined in NASA-STD-3001 and employs a methodology to integrate different performance scales. This framework analyzes the contribution of various human system task categories (HSTCs) to task execution and compares these contributions to the HSTCs’ involvement in other known tests. The model further employs a Monte Carlo simulation to sample performance scores from their distribution in operationally relevant tests such as those in Mulavara et al. (2018) and, by leveraging similarities in HSTC involvement, transfers this knowledge to actual mission tasks, such as those outlined in the "Human Exploration of Mars: Preliminary List of Crew Tasks”. The current PRisM proof-of-concept includes analyses of the impact of exercise and specific medications on astronauts’ performance, with provisions to incorporate additional countermeasures as data becomes available. Furthermore, the tool is customizable to include any system necessary to fully encompass the domain of human systems and can be adapted to evaluate performance for any spaceflight activities as requested by operational stakeholders. PRisM has the potential to assist the Human Research Program in exploring the capabilities trade space for optimized crew performance.

performance modeling↗
DOE OSTI2026

Predicting Atomistic Transitions with Transformers

Accurate knowledge of the atomistic transition pathways in materials and material surfaces is crucial for many material science problems. However, conventional simulation techniques used to find these transitions are extremely computationally intensive. Even with large-scale, accelerated material simulations, the computational cost constrains the applicable domain in practice. Machine learning models, with the potential to learn the complex emergent behaviors governing atomistic transitions as a fast surrogate model, have great promise to predict transitions with a vastly reduced computational cost. Here, we demonstrate how transformers can be trained to predict atomistic transitions in nano-clusters. We show how we evaluate physical validity of the predictions and how a multitude of additional, different microstates can be generated by slightly varying the data provided to the model.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The challenges of theory-software translation

Background: Software is now ubiquitous within research. In addition to the general challenges common to all software development projects, research software must also represent, manipulate, and provide data for complex theoretical constructs. Ensuring this process of theory-software translation is robust is essential to maintaining the integrity of the science resulting from it, and yet there has been little formal recognition or exploration of the challenges associated with it. Methods: We thematically analyse the outputs of the discussion sessions at the Theory-Software Translation Workshop 2019, where academic researchers and research software engineers from a variety of domains, and with particular expertise in high performance computing, explored the process of translating between scientific theory and software. Results: We identify a wide range of challenges to implementing scientific theory in research software and using the resulting data and models for the advancement of knowledge. We categorise these within the emergent themes of design, infrastructure, and culture, and map them to associated research questions. Conclusions: Systematically investigating how software is constructed and its outputs used within science has the potential to improve the robustness of research software and accelerate progress in its development. We propose that this issue be examined within a new research area of theory-software translation, which would aim to significantly advance both knowledge and scientific practice.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Cyber Physical Subsystems under Adverse Conditions

The United States power grid is built upon complex cyber-physical systems (CPS), including many distributed energy resources (DERs) and microgrid structures. Due to cross-disciplinary domains that govern the interplay between cyber and physical technologies that sustain DERs, it is difficult to confidently predict how these systems will react under adverse conditions such as faults and cyberattacks. This project utilized power hardware in the loop (PHiL) to gain system behavior knowledge and robust understanding through experimentation and observational science. It also produced a large volume of datasets to feed into other efforts to advance high-fidelity model simulations and to support the design of novel control approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1994

Learning procedures from interactive natural language instructions

Despite its ubiquity in human learning, very little work has been done in artificial intelligence on agents that learn from interactive natural language instructions. In this paper, the problem of learning procedures from interactive, situated instruction is examined in which the student is attempting to perform tasks within the instructional domain, and asks for instruction when it is needed. Presented is Instructo-Soar, a system that behaves and learns in response to interactive natural language instructions. Instructo-Soar learns completely new procedures from sequences of instruction, and also learns how to extend its knowledge of previously known procedures to new situations. These learning tasks require both inductive and analytic learning. Instructo-Soar exhibits a multiple execution learning process in which initial learning has a rote, episodic flavor, and later executions allow the initially learned knowledge to be generalized properly.

Huffman, Scott B.↗
NASA NTRS2017

Network Analysis of Rodent Transcriptomes in Spaceflight

Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.

genomics↗
NASA NTRSDate not supplied

NASA Life Sciences Portal (NLSP): Supporting Scientific Transparency and Reproducibility

NASA’s Life Sciences Ports (NLSP) serves the scientific community by providing curated data from space life science experiment. The Human Research Program (HRP) with the help of NLSP is currently transforming their life sciences data archive systems and processes to improve compliance with the FAIR principles [1]. Some of these improvements will at the same time support the twin pillars of Open Science [2]: transparency of methods and reproducibility of results. Scientific transparency is marked by the easily intelligible communication of what has been investigated: what were the procedures for collecting sample and the characteristics of samples collected? what kinds of measurements were made, what were the environmental conditions of the measurements? What were the analysis techniques of the collected data? Reproducibility of the results and findings from the investigation requires a high level of transparency for all but the simplest investigations; the slightest deviation in communicating and replicating complex experimental procedures or data analyses can often yield quite different data and even findings, thwarting their validation. One of the ways the NLSP is aiming to improve the communication of scientific information is through the use of ontology-driven metadata. Ontologies are powerful, graph-based knowledge representation structures, which can be leveraged to increase data interoperability, the area of the FAIR principles in which many data systems most lack compliance. Over the past decade, there has been a concerted effort in the biomedical community to develop modular and narrowly focused domain and application-specific ontologies in a common, open-source framework, the Open Biological and Biomedical Ontology (OBO) Foundry [3]. The open sharing and modular nature of this effort promises huge increases in harmonized data sharing for systems that leverage these models. Which is in line with the FAIR Data Principles of Findability, Accessibility, Interoperability, and Reuse for scientific data management and stewardship. 1. Wilkinson, M.D., et al., The FAIR Guiding Principles for scientific data management and stewardship. Sci Data, 2016. 3: p. 160018. 2. National Academies of Sciences, E. and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. 2018, Washington, DC: The National Academies Press. 232. 3. Smith, B., et al., The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol, 2007. 25(11): p. 1251-5.

Life Sciences data↗
NASA NTRSDate not supplied

NASA Life Sciences Portal (NLSP): Supporting Scientific Transparency and Reproducibility

NASA’s Life Sciences Ports (NLSP) serves the scientific community by providing curated data from space life science experiment. The Human Research Program (HRP) with the help of NLSP is currently transforming their life sciences data archive systems and processes to improve compliance with the FAIR principles [1]. Some of these improvements will at the same time support the twin pillars of Open Science [2]: transparency of methods and reproducibility of results. Scientific transparency is marked by the easily intelligible communication of what has been investigated: what were the procedures for collecting sample and the characteristics of samples collected? what kinds of measurements were made, what were the environmental conditions of the measurements? What were the analysis techniques of the collected data? Reproducibility of the results and findings from the investigation requires a high level of transparency for all but the simplest investigations; the slightest deviation in communicating and replicating complex experimental procedures or data analyses can often yield quite different data and even findings, thwarting their validation. One of the ways the NLSP is aiming to improve the communication of scientific information is through the use of ontology-driven metadata. Ontologies are powerful, graph-based knowledge representation structures, which can be leveraged to increase data interoperability, the area of the FAIR principles in which many data systems most lack compliance. Over the past decade, there has been a concerted effort in the biomedical community to develop modular and narrowly focused domain and application-specific ontologies in a common, open-source framework, the Open Biological and Biomedical Ontology (OBO) Foundry [3]. The open sharing and modular nature of this effort promises huge increases in harmonized data sharing for systems that leverage these models. Which is in line with the FAIR Data Principles of Findability, Accessibility, Interoperability, and Reuse for scientific data management and stewardship.

Life Sciences data↗
DOE OSTI2023

User Guide to the Facility Cybersecurity Framework Internet of Things (IoT) Self-Assessment

The FEMP Facility Cybersecurity Framework (FCF) Internet of Things (IoT) Self-Assessment is a comprehensive tool aimed at illuminating the foggy domains of IoT and Industrial Internet of Things (IIoT) security. The assessment was developed using insights from recognized standards and guidelines to identify, address, and mitigate the challenges posed by the massive surge of interconnected devices. The FCF IoT Self-Assessment was created using the knowledge from established National Institute of Standards and Technology (NIST) publications such as NIST SP 800-53, NIST SP 800-213, and NIST Cybersecurity Framework (CSF). Additionally, integrating NIST SP 800-213A IoT Device Cybersecurity Guidance for the Federal Government ensures federal agencies are equipped with specific IoT security insights. This user guide has been developed to facilitate a thorough understanding of the tool. As users delve into the assessment, the guide offers a clear navigation walkthrough, report generation, and interpretation of the report.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Simple and Accurate Energy-Detector-Based Transient Waveform Detection for Smart Grids: Real-World Field Data Performance

Integration of distributed energy sources, advanced meshed operation, sensors, automation, and communication networks all contribute to autonomous operations and decision-making processes utilized in the grid. Therefore, smart grid systems require sophisticated supporting structures. Furthermore, rapid detection and identification of disturbances and transients are a necessary first step towards situationally aware smart grid systems. This way, high-level monitoring is achieved and the entire system kept operational. Even though smart grid systems are unavoidably sophisticated, low-complexity algorithms need to be developed for real-time sensing on the edge and online applications to alert stakeholders in the event of an anomaly. In this study, the simplest form of anomaly detection mechanism in the absence of any a priori knowledge, namely, the energy detector (also known as radiometer in the field of wireless communications and signal processing), is investigated as a triggering mechanism, which may include automated alerts and notifications for grid anomalies. In contrast to the mainstream literature, it does not rely on transform domain tools; therefore, utmost design and implementation simplicity are attained. Performance results of the proposed energy detector algorithm are validated by real power system data obtained from the DOE/EPRI National Database of power system events and the Grid Signature Library.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1990

Interface preconditionings for domain-decomposed convection-diffusion operators

The performance of five different interface preconditionings for domain-decomposed convection-diffusion problems, including a novel one known as the spectral probe is tested in a three-dimensional parameter space consisting of mesh parameters, Reynolds number, and domain aspect ratio. The preconditioners are representative of the range of practically computable possibilities that have appeared in the literature for the treatment of nonoverlapping subdomains. Numerical examples show that no single preconditioner can be considered uniformly superior or uniformly inferior to the rest, but that knowledge of the particulars of the shape and strength of the convection is important in selecting among them in a given problem.

Chan, Tony F.↗
NASA NTRS2015

A Synthesis of Hybrid RANS/LES CFD Results for F-16XL Aircraft Aerodynamics

A synthesis is presented of recent numerical predictions for the F-16XL aircraft flow fields and aerodynamics. The computational results were all performed with hybrid RANS/LES formulations, with an emphasis on unsteady flows and subsequent aerodynamics, and results from five computational methods are included. The work was focused on one particular low-speed, high angle-of-attack flight test condition, and comparisons against flight-test data are included. This work represents the third coordinated effort using the F-16XL aircraft, and a unique flight-test data set, to advance our knowledge of slender airframe aerodynamics as well as our capability for predicting these aerodynamics with advanced CFD formulations. The prior efforts were identified as Cranked Arrow Wing Aerodynamics Project International, with the acronyms CAWAPI and CAWAPI-2. All information in this paper is in the public domain.

Luckring, James M.↗
NASA NTRS2019

Implementation of Human System Integration Workshop at NASA for Human Spaceflight

The human is a key element in the complex system of systems underlying space exploration missions. As a critical system, its operating bands and requirements need to be characterized and integrated with other systems. Optimal integration of the human system with hardware and software elements has an impact on multiple aspects of mission execution, including human health and performance, risk mitigation, effective design and functionality, enhanced safety, and reduced lifecycle costs. The field of Human Systems Integration (HSI) represents an interdisciplinary and comprehensive cross-cutting approach encompassing technical and management processes for integrating human as a system consideration and objective within and across all other system components and multiple domains. In addition to human activities, HSI covers training, operations and support dimensions. Moreover, HSI is an essential enabler to systems engineering practice, emphasizing human system aspects toward optimizing fully integrated system of systems performance while systematically infusing the needs of all users during the earliest stages of development. Consistent with the National Space Exploration Campaign, NASA is developing the Gateway, a lunar orbiting platform that will serve as astronaut habitat, support transit to deep space, validate new technologies and systems, and function as a science laboratory and communications hub, among other uses. It is an essential element of a phase that will extend human exploration into deep space through evolvable infrastructure and advanced technology, supporting assembly and logistics of other exploration architecture elements. In an effort to explore the current status and forward plan of HSI implementation in the mission (system of systems) lifecycle, the HSI Employee Resource Group conducted an HSI workshop using the Gateway Program as a case study. It revealed how different organizations at the Johnson Space Center incorporate HSI in their processes in preparation for the development and operation of the Gateway. The workshop focused on HSI methodology for implementation of the six NASA HSI domains: Human Factors Engineering, Operations Resources, Habitability and Environment, Maintainability and Supportability, Safety, and Training. Results from the workshop are reported on this paper, as well as some historical background of HSI at NASA, and the success in using an Employee Resource Group to promote technical knowledge. The authors hope that this information can be used to disseminate best practices for translational applications to other space exploration systems.

Silva-Martinez, Jackelynne↗
NASA NTRS2019

Implementation of Human System Integration Workshop at NASA for Human Spaceflight

The human is a key element in the complex system of systems underlying space exploration missions. As a critical system, its operating bands and requirements need to be characterized and integrated with other systems. Optimal integration of the human system with hardware and software elements has an impact on multiple aspects of mission execution, including human health and performance, risk mitigation, effective design and functionality, enhanced safety, and reduced lifecycle costs. The field of Human Systems Integration (HSI) represents an interdisciplinary and comprehensive cross-cutting approach encompassing technical and management processes for integrating human as a system consideration and objective within and across all other system components and multiple domains. In addition to human activities, HSI covers training, operations and support dimensions. Moreover, HSI is an essential enabler to systems engineering practice, emphasizing human system aspects toward optimizing fully integrated system of systems performance while systematically infusing the needs of all users during the earliest stages of development. Consistent with the National Space Exploration Campaign, NASA is developing the Gateway, a lunar orbiting platform that will serve as astronaut habitat, support transit to deep space, validate new technologies and systems, and function as a science laboratory and communications hub, among other uses. It is an essential element of a phase that will extend human exploration into deep space through evolvable infrastructure and advanced technology, supporting assembly and logistics of other exploration architecture elements. In an effort to explore the current status and forward plan of HSI implementation in the mission (system of systems) lifecycle, the HSI Employee Resource Group conducted an HSI workshop using the Gateway Program as a case study. It revealed how different organizations at the Johnson Space Center incorporate HSI in their processes in preparation for the development and operation of the Gateway. The workshop focused on HSI methodology for implementation of the six NASA HSI domains: Human Factors Engineering, Operations Resources, Habitability and Environment, Maintainability and Supportability, Safety, and Training. Results from the workshop are reported on this paper, as well as some historical background of HSI at NASA, and the success in using an Employee Resource Group to promote technical knowledge. The authors hope that this information can be used to disseminate best practices for translational applications to other space exploration systems.

Silva-Martinez, Jackelynne↗
NASA NTRS1992

Autonomous Frequency-Domain Indentification

Test and data-processing system determines plant models and uncertainties. Integrated system of methods, digital signal-processing, and algorithms identifies parametric model of large, flexible structures. Experiments in development of system conducted on laboratory model intended to represent large space antenna or flexible spacecraft. Also applicable to many terrestrial systems, robust control of dynamic plants and processes, robust control of systems about which knowledge uncertain or incomplete, decentralized control, and knowledge-based control systems.

Mettler, Edward↗
DOE OSTI2020

PPINN: Parareal physics-informed neural network for time-dependent PDEs

Physics-informed neural networks (PINNs) encode physical conservation laws and prior physical knowledge into the neural networks, ensuring the correct physics is represented accurately while alleviating the need for supervised learning to a great degree. While effective for relatively short-term time integration, when long time integration of the time-dependent PDEs is sought, the time–space domain may become arbitrarily large and hence training of the neural network may become prohibitively expensive. To this end, we develop a parareal physics-informed neural network (PPINN), hence decomposing a long-time problem into many independent short-time problems supervised by an inexpensive/fast coarse-grained (CG) solver. In particular, the serial CG solver is designed to provide approximate predictions of the solution at discrete times, while initiate many fine PINNs simultaneously to correct the solution iteratively. There is a two-fold benefit from training PINNs with small-data sets rather than working on a large-data set directly, i.e., training of individual PINNs with small-data is much faster, while training the fine PINNs can be readily parallelized. Consequently, compared to the original PINN approach, the proposed PPINN approach may achieve a significant speed-up for long-time integration of PDEs, assuming that the CG solver is fast and can provide reasonable predictions of the solution, hence aiding the PPINN solution to converge in just a few iterations. To investigate the PPINN performance on solving time-dependent PDEs, we first apply the PPINN to solve the Burgers equation, and subsequently we apply the PPINN to solve a two-dimensional nonlinear diffusion–reaction equation. Furthermore, our results demonstrate that PPINNs converge in a few iterations with significant speed-ups proportional to the number of time-subdomains employed.

42 ENGINEERING↗
DOE OSTI2020

Direct Correlation of Charge Carrier Transport to Local Crystal Quality in Lead Halide Perovskites

Although solution processing methods provide an attractive route toward development of low-cost functional materials, these accessible fabrication approaches can engender high concentrations of microscopic structural defects that are detrimental to performance. In lead halide perovskites, structural disorder derived from solution processing has been implicated as an important determiner of photophysical properties. However, a direct correlation between the functional properties of these materials and the local crystal structure in which non-equilibrium states evolve has remained elusive, in part because structural heterogeneities occur on length scales that defy conventional characterization techniques. To address this knowledge gap, in this work we have combined ultrafast pump–probe microscopy and electron backscattering diffraction to directly correlate charge carrier transport with the local diffraction pattern contrast, an indicator of crystal quality. Spatial correlation of these measurements strongly suggests that even on individual single crystal CsPbBr3 domains, microscopic variability in the crystal quality profoundly impacts the efficiency of charge carrier transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗