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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Molecular insights into the complex mechanics of plant epidermal cell walls

Computational analysis of cell walls Layers of intertwined fibers make up plant cell walls. The various types of fibers respond differently to deformation. Cellulose microfibrils, for example, can stretch or curve, changing their end-to-end length, and can also slide past each other, reorient relative directions, and bundle with neighboring microfibrils. Zhang et al. developed a computational model based on observations of onion skin epidermis that describes how these complex changes in space govern cell wall mechanics. The results inform ways to engineer multifunctional fibrous materials. Science , this issue p. 706

Science & Technology - Other Topics↗
DOE OSTI2023

Dynamic Network Analysis of Nuclear Science Literature for Research Influence Assessment

Analyzing nuclear science literature via data-driven methods is a critical step for assessing research influence and technology advancements. Indicators of scholarly activities may be buried in large volumes of nuclear research publications and collaboration networks over time. Mining for relevant scholarly influence trends in large volumes of text can be computationally challenging; however, open-source information on research collaborations over time can offer opportunities to extract meaningful insights. While network centrality analysis of scholarly research provides topology-based insights, additional emphasis on dynamics associated with the diffusion of information through these networks is important. Here this paper represents a step in that direction through the development of a novel dynamic network analysis framework and computational engine to identify key entities and capabilities over time within global scholarly nuclear science collaboration networks. Network theoretic, stochastic simulation, and optimization methods are leveraged to address variability in scholarly interactions, influence propagation, and collaboration patterns via network connections. A topic-aware influence maximization algorithm is developed to address the goal of identifying key influential authors in diverse research topics over time. Efficient parallelized implementation of the algorithm is applied to reduce computational costs. A proof-of-concept case study using open-source Scopus data with 33,517 published nuclear research papers from 2000-2019 is presented and representative analytic insights are generated. Broad implications of these insights are discussed and future research directions are also identified.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS1993

Optical information processing at NASA Ames Research Center

The combination of analog optical processors with digital electronic systems offers the potential of tera-OPS computational performance, while often requiring less power and weight relative to all-digital systems. NASA is working to develop and demonstrate optical processing techniques for on-board, real time science and mission applications. Current research areas and applications under investigation include optical matrix processing for space structure vibration control and the analysis of Space Shuttle Main Engine plume spectra, optical correlation-based autonomous vision for robotic vehicles, analog computation for robotic path planning, free-space optical interconnections for information transfer within digital electronic computers, and multiplexed arrays of fiber optic interferometric sensors for acoustic and vibration measurements.

Reid, Max B.↗
DOE OSTI2022

Perspectives on the integration between first-principles and data-driven modeling

Efficiently embedding and/or integrating mechanistic information with data-driven models is essential if it is desired to simultaneously take advantage of both engineering principles and data-science. Further the opportunity for hybridization occurs in many scenarios, such as the development of a faster model of an accurate high-fidelity computer model; the correction of a mechanistic model that does not fully-capture the physical phenomena of the system; or the integration of a data-driven component approximating an unknown correlation within a mechanistic model. At the same time, different techniques have been proposed and applied in different literatures to achieve this hybridization, such as hybrid modeling, physics-informed Machine Learning (ML) and model calibration. In this paper we review the methods, challenges, applications and algorithms of these three research areas and discuss them in the context of the different hybridization scenarios. Moreover, we provide a comprehensive comparison of the hybridization techniques with respect to their differences and similarities, as well as advantages and limitations and future perspectives. Finally, we apply and illustrate hybrid modeling, physics-informed ML and model calibration via a chemical reactor case study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Fission of 240 Pu with Symmetry-Restored Density Functional Theory

Nuclear fission plays an important role in fundamental and applied science, from astrophysics to nuclear engineering, yet it remains a major challenge to nuclear theory. Theoretical methods used so far to compute fission observables rely on symmetry-breaking schemes where basic information on the number of particles, angular momentum, and parity of the fissioning nucleus is lost. In this letter, we analyze the impact of restoring broken symmetries in the benchmark case of 240 Pu.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1995

NASA Tech Briefs, March 1995

This issue contains articles with a special focus on Computer-Aided design and engineering amd a research report on the Ames Research Center. Other subjects in this issue are: Electronic Components and Circuits, Electronic Systems, Physical Sciences, Materials, Computer Programs, Mechanics, Machinery, Manufacturing/Fabrication, Mathematics and Information Sciences and Life Sciences

Source record↗
NASA NTRS2011

Towards a Standard for Provenance and Context for Preservation of Data for Earth System Science

Long-term data sets with data from many missions are needed to study trends and validate model results that are typical in Earth System Science research. Data and derived products originate from multiple missions (spaceborne, airborne and/or in situ) and from multiple organizations. During the missions as well as well past their termination, it is essential to preserve the data and products to support future studies. Key aspects of preservation are: preserving bits and ensuring data are uncorrupted, preserving understandability with appropriate documentation, and preserving reproducibility of science with appropriate documentation and other artifacts. Computer technology provides adequate standards to ensure that, with proper engineering, bits are preserved as hardware evolves. However, to ensure understandability and reproducibility, it is essential to plan ahead to preserve all the relevant data and information. There are currently no standards to identify the content that needs to be preserved, leading to non-uniformity in content and users not being sure of whether preserved content is comprehensive. Each project, program or agency can specify the items to be preserved as a part of its data management requirements. However, broader community consensus that cuts across organizational or national boundaries would be needed to ensure comprehensiveness, uniformity and long-term utility of archived data. The Federation of Earth Science Information Partners (ESIP), a diverse network of scientists, data stewards and technology developers, has a forum for ESIP members to collaborate on data preservation issues. During early 2011, members discussed the importance of developing a Provenance and Context Content Standard (PCCS) and developed an initial list of content items. This list is based on the outcome of a NASA and NOAA meeting held in 1998 under the auspices of the USGCRP, documentation requirements from NOAA and our experience with some of the NASA Earth science missions. The items are categorized into the following 8 high level categories: Preflight/Pre-Operations, Products (Data), Product Documentation, Mission Calibration, Product Software, Algorithm Input, Validation, Software Tools.

Ramaprian, Hampapuram K.↗
NASA NTRS2013

Educational NASA Computational and Scientific Studies (enCOMPASS)

Educational NASA Computational and Scientific Studies (enCOMPASS) is an educational project of NASA Goddard Space Flight Center aimed at bridging the gap between computational objectives and needs of NASA's scientific research, missions, and projects, and academia's latest advances in applied mathematics and computer science. enCOMPASS achieves this goal via bidirectional collaboration and communication between NASA and academia. Using developed NASA Computational Case Studies in university computer science/engineering and applied mathematics classes is a way of addressing NASA's goals of contributing to the Science, Technology, Education, and Math (STEM) National Objective. The enCOMPASS Web site at http://encompass.gsfc.nasa.gov provides additional information. There are currently nine enCOMPASS case studies developed in areas of earth sciences, planetary sciences, and astrophysics. Some of these case studies have been published in AIP and IEEE's Computing in Science and Engineering magazines. A few university professors have used enCOMPASS case studies in their computational classes and contributed their findings to NASA scientists. In these case studies, after introducing the science area, the specific problem, and related NASA missions, students are first asked to solve a known problem using NASA data and past approaches used and often published in a scientific/research paper. Then, after learning about the NASA application and related computational tools and approaches for solving the proposed problem, students are given a harder problem as a challenge for them to research and develop solutions for. This project provides a model for NASA scientists and engineers on one side, and university students, faculty, and researchers in computer science and applied mathematics on the other side, to learn from each other's areas of work, computational needs and solutions, and the latest advances in research and development. This innovation takes NASA science and engineering applications to computer science and applied mathematics university classes, and makes NASA objectives part of the university curricula. There is great potential for growth and return on investment of this program to the point where every major university in the U.S. would use at least one of these case studies in one of their computational courses, and where every NASA scientist and engineer facing a computational challenge (without having resources or expertise to solve it) would use enCOMPASS to formulate the problem as a case study, provide it to a university, and get back their solutions and ideas.

Memarsadeghi, Nargess↗
NASA NTRS1985

A report from the Space Science and Engineering Center, the University of Wisconsin-Madison, Madison, Wisconsin

Operational forecasters have habitually been plagued with the problems associated with acquisition, display, and dissemination of data used in preparing forecasts. The centralized storm information system (CSIS) experiment provided an operational forecaster with an interactive computer system which could perform these preliminary tasks more quickly and accurately than any human could. CSIS objectives pertaining to improved severe storms forecasting and warning procedures are addressed.

Source record↗
DOE OSTI2022

Pyomo.DOE: An open-source package for model-based design of experiments in Python

Predictive mathematical models are a cornerstone of science and engineering. Yet selecting, calibrating, and validating said science-based models often remains an art in practice. Model-based design of experiments (MBDoE) provides a systematic framework to maximize information gain from experiments while minimizing time and resource costs. But MBDoE remains limited to niche application areas, in part because practitioners must integrate expertise in statistics, computational optimization, and modeling. To help reduce this barrier, we introduce Pyomo.DOE, an open-source package for MBDoE. Pyomo.DOE uses a nonlinear sensitivity analysis code k_aug to quickly approximate the Fisher information matrix and leverages a new stochastic programming abstraction. We demonstrate Pyomo.DOE with the first application of MBDoE to fixed-bed breakthrough experiments, which highlights the power of Pyomo.DOE to quantify the value of experimental modifications a priori for large-scale partial differential-algebraic equation (PDAE) models. Here we also provide a mathematical primer on MBDoE targeted at general chemical engineers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Reproducibility Practice in High-Performance Computing: Community Survey Results

The integrity of science and engineering research is grounded in assumptions of rigor and transparency on the part of those engaging in such research. HPC community effort to strengthen rigor and transparency take the form of reproducibility efforts. In a recent survey of the SC conference community, we collected information about the SC Reproducibility Initiative activities. Here, we present the survey results in this paper. Results show that the reproducibility initiative activities have contributed to higher levels of awareness on the part of SC conference technical program participants, and hint at contributing to greater scientific impact for the published papers of the SC conference series. Stringent point-of-manuscript-submission verification is problematic for reasons we point out, as are inherent difficulties of computational reproducibility in HPC. Future efforts should better decouple the community educational goals from goals that specifically strengthen a research work's potential for long-term impact through reuse 5-10 years down the road.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Interplay of Magnetism and Superconductivity in van der Waals Heterostructures (Final report)

This project has investigated the magnetic and electric properties of 2D materials, with emphasis on the (anti-)ferromagnetic properties of 2D crystalline magnets and a new concept for stacking engineering of 2D ferroelectricity. The new basic physics fundamental knowledge obtained through this research may have important implications for future technologies based on magnetism and ferroelectricity, for example spintronics, quantum information science, or neuromorphic computing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1990

Deep space telecommunications, navigation, and information management - Support of the Space Exploration Initiative

The principal challenges in providing effective deep space navigation, telecommunications, and information management architectures and designs for Mars exploration support are presented. The fundamental objectives are to provide the mission with the means to monitor and control mission elements, obtain science, navigation, and engineering data, compute state vectors and navigate, and to move these data efficiently and automatically between mission nodes for timely analysis and decision making. New requirements are summarized, and related issues and challenges including the robust connectivity for manned and robotic links, are identified. Enabling strategies are discussed, and candidate architectures and driving technologies are described.

Hall, Justin R.↗
NASA NTRS2021

New Observing Strategies Testbed (NOS-T)

The New Observing Strategies (NOS) initiative within the NASA Earth Science Technology Office(ESTO)Advanced Information Systems Technology(AIST) program envisions future Earth science missions with distributed sensors(nodes) interconnected by a communications fabric that enables dynamic and intelligent operations [1].Some NOS concepts resemble systems-of-systems or collaborative systems where operational authority is distributed among multiple systems, necessitating new methods for systems engineering and design to cope with more decentralized control over constituent systems[2].The New Observing Strategies Testbed (NOS-T, verbalized as "enoh es tee") is a computational environment to develop, test, mature, and socialize new operating concepts and technology for NOS. NOS-T provides infrastructure to integrate and orchestrate user-contributed applications for system-of-systems test cases with true distributed control over constituent systems. The overall concept, illustrated in Figure 1, interconnects individual user applications and a NOS-T manager application via common information system infrastructure to coordinate the execution of virtual Earth science missions. NOS-T enables principal investigators to conduct test runs in the same environment, systematically changing variables to assess the overall efficacy of the proposed new observing strategies. Recorded data and outcomes provide evidence to advance technology readiness level and improve or innovate upon existing Earth science measurement techniques

Paul Grogan↗
DOE OSTI2026

Visualization for Insight and Data Analysis in Energy Research

This talk explores how advanced visualization technologies are transforming analytical reasoning and knowledge discovery in energy research, drawing on recent work at the National Laboratory of the Rockies' Computational Science Center. Through a series of scientific case studies, we demonstrate how immersive and high-resolution visualization environments enable scientists and engineers to identify previously unseen patterns and features - insights that often remain hidden in traditional desktop-based analysis. By embedding richer information into interactive analytics tools, these approaches support the exploration of complex, multivariate parameter spaces, where interaction itself catalyzes understanding. Beyond capability, we emphasize the critical role of visualization design grounded in perception and cognition, showing how visual encodings directly influence analytical outcomes. Spanning applications from materials science to integrated energy systems, these visualization approaches accelerate innovation and improve decision-making by enabling deeper, more reliable insight into increasingly complex energy data.

97 MATHEMATICS AND COMPUTING↗