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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Space shuttle orbiter digital data processing system timing sensitivity analysis OFT ascent phase

Dynamic loads were investigated to provide simulation and analysis of the space shuttle orbiter digital data processing system (DDPS). Segments of the ascent test (OFT) configuration were modeled utilizing the information management system interpretive model (IMSIM) in a computerized simulation modeling of the OFT hardware and software workload. System requirements for simulation of the OFT configuration were defined, and sensitivity analyses determined areas of potential data flow problems in DDPS operation. Based on the defined system requirements and these sensitivity analyses, a test design was developed for adapting, parameterizing, and executing IMSIM, using varying load and stress conditions for model execution. Analyses of the computer simulation runs are documented, including results, conclusions, and recommendations for DDPS improvements.

Lagas, J. J.↗
NASA NTRS1976

Digital data processing system dynamic loading analysis

Simulation and analysis of the Space Shuttle Orbiter Digital Data Processing System (DDPS) are reported. The mated flight and postseparation flight phases of the space shuttle's approach and landing test configuration were modeled utilizing the Information Management System Interpretative Model (IMSIM) in a computerized simulation modeling of the ALT hardware, software, and workload. System requirements simulated for the ALT configuration were defined. Sensitivity analyses determined areas of potential data flow problems in DDPS operation. Based on the defined system requirements and the sensitivity analyses, a test design is described for adapting, parameterizing, and executing the IMSIM. Varying load and stress conditions for the model execution are given. The analyses of the computer simulation runs were documented as results, conclusions, and recommendations for DDPS improvements.

Lagas, J. J.↗
NASA NTRS1983

On the flight derived/aerodynamic data base performance comparisons for the NASA Space Shuttle entries during the hypersonic regime

Aerodynamic performance data from the first four Shuttle reentry flights are compared with preflight predictions covering hypersonic longitudinal mode down to Mach 2. The extraction of the flight coefficients, as measured by the spacecraft angular rates and the linear accelerations, derived from the inertial measurement unit, the best estimate trajectory, and the remotely measured atmosphere are discussed. The ground predictions were developed from 30,000 hr of wind tunnel testing. Actual flight data are presented for 80-260 kft, from Mach 2-26, comprising the dynamic pressure, the vehicle air relative attitude angles, control surface deflections, reaction jet activity, and body axis rates and accelerations. The second and fourth flights gave results which deviated from predictions between 230-260 kft. The accuracy limits of the derived atmospheric densities are considered, together with potential data base updates in the light of limitations imposed on the corrections by available flight data.

Findlay, J. T.↗
NASA NTRS1998

Optical Data Storage Capabilities of Bacteriorhodopsin

We present several measurements of the data storage capability of bacteriorhodopsin films to help establish the baseline performance of this material as a medium for holographic data storage. In particular, we examine the decrease in diffraction efficiency with the density of holograms stored at one location in the film, and we also analyze the recording schedule needed to produce a set of equal intensity holograms at a single location in the film. Using this information along with the assumptions about the performance of the optical system, we can estimate potential data storage densities in bacteriorhodopsin.

Gary, Charles↗
DOE OSTI2025

Artificial Intelligence for Enhancing Multiscale Analysis: Buildings Focus

This project aims to develop multi-scale building energy data, potentially improving the representation of the U.S. buildings sector in GCAM-USA, an U.S.-focused human-energy-Earth systems model. Existing building energy datasets are typically limited to national or regional levels, which constrains the ability of models to capture fine-scale human-energy-Earth systems interactions and reduces their relevance for decision-making on issues such as energy security, resilience, and energy planning. By leveraging AI and advanced data integration methods, this work fuses multiple existing datasets to enhance the physical and geographic representation of both residential and commercial building energy use. So far, progress includes processing residential building data, designing the data structure for commercial buildings, and testing AI approaches for integrating datasets and addressing spatial-temporal gaps. This effort can not only advances GCAM-USA’s capability in modeling the buildings sector but also supports broader DOE missions, such as developing digital testbeds, enhancing grid resilience analysis, and improving building–energy system modeling at decision-relevant scales.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Potential Ideas for an El Capitan Center of Excellence (COE) Around Intelligent Simulation

Proposing a Center of Excellence under the CORAL-2 NRE is a mandatory requirement. The current Sierra COE (CORAL-1) is largely focused on helping LLNL applications make the disruptive transition to a heterogeneous GPU-based system by 2018. We expect a continuation of COE activities around optimizing our broad and diverse application base (of so-called “traditional” simulation codes) optimized for the El Capitan architecture, as well as supporting the underlying software stack (compilers, tools, programming models, etc.) – but do not expect this to require as much effort in the El Capitan COE (assuming a heterogeneous node architecture). What follows are some thoughts on 3 potential topics of interest for an El Capitan COE at LLNL – largely focused around AI and machine learning and the concept of advancing our goal of intelligent simulation or cognitive computing in the timeframe of deployment and production use of El Capitan (2023-2038). We believe vendor engagement through a COE in this area will provide a natural point-of-interest between LLNL and our vendor partner for common advancement of machine learning capabilities focused on scientific data – potentially greatly broadening the ecosystem around HPC architectures and the supporting software stack for scientific simulation-based AI.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

The Evolving Solar Energy Innovation Ecosystem in Puerto Rico

This report presents initial findings from the research project, “Developing socially and economically generative, resilient PV-energy systems for low- and moderate-income communities: Applications for Puerto Rico.” This material is based upon work supported primarily by the US Department of Energy’s Office of Energy Efficiency and Renewable Energy under the Solar Energy Technology Office Fiscal Year 2018 Funding Program award number DE-EE0008570 and in part by the National Science Foundation (NSF) and the Department of Energy (DOE) under NSF CA No. EEC-1041895. This project is a joint effort of Arizona State University’s Center for Energy and Society; the University of Puerto Rico-Mayaguez’s Center for Hemispheric Cooperation in Research and Education in Engineering and Applied Science, Sustainable Energy Center, and National Institute for Energy and Island Sustainability; and the National Renewable Energy Laboratory. The project seeks to understand the place of energy in low-income communities in Puerto Rico, the opportunities for solar energy to provide solutions to the energy challenges facing these communities, and the capacity of the solar energy innovation ecosystem in Puerto Rico to deliver relevant solar solutions for these communities. We define the solar energy innovation ecosystem as the diverse actors and stakeholders whose collective networks and actions—and the flows among them of ideas, knowledge, data, influence, money, and equipment, as well as the rules that govern those flows—are essential to the success of renewable energy markets and projects. This report presents results from the first year of the project’s research, which has concentrated on several key goals: (1) characterizing the trajectory of solar energy development in Puerto Rico in the three years since Hurricane María; (2) mapping and characterizing the current solar energy innovation ecosystem in Puerto Rico, including the technical potential for solar energy in Puerto Rico, and the business and policy landscape shaping solar developments; and (3) beginning to characterize the broad landscape of community energy initiatives underway in Puerto Rico. To pursue these goals, we engaged in a systematic review of solar energy developments in Puerto Rico and conducted interviews with over 100 members of the solar energy innovation, including policy, business, finance, research, and civil society leaders, as well as solar users. Solar technical potential data for Puerto Rico was developed by the National Renewable Energy Laboratory (NREL) and is publicly available at: https://data.nrel.gov/submissions/144. The documentation for the NREL dataset is included as Appendix A.

14 SOLAR ENERGY↗
DOE OSTI2020

Machine learning for international freight transportation management: A comprehensive review

Machine learning (ML) offers a promising avenue for international freight transportation management (IFTM) given its capability to harness the power of data that have become increasingly available to freight transportation researchers and practitioners. This paper conducts a comprehensive investigation of the state-of-the-art in developing ML models for applications to different aspects of IFTM. We start by giving an overview of various fundamental ML methods. Then, how different ML methods have been employed, adapted, and applied to a multitude of subject areas in IFTM are discussed, including demand forecast, operation and asset maintenance, and vehicle trajectory and on-time performance prediction. The potential data sources that may be used to develop ML models are further examined. Subsequently, a synthesis of the exiting work is performed to identify the specific topics addressed in the existing research, ML methods used, the trends of research, and opportunities for further explorations. Four directions for future research are proposed in the end.

Data sources↗
NASA NTRS1988

Temporal evolution of collisionless sheaths

Experimental measurements have been performed to determine the temporal evolution of Langmuir sheaths near an electrode to which a negative step bias is applied in a collisionless argon plasma. The plasma was produced by a hot-filament discharge in a multidipole device. Plasma potential data were obtained using emissive probes with two different techniques: time-resolved sampling and time-averaged techniques. The sheath is found to initially form close to the electrode, to extend to a maximum separation, and to contract to a steady-state value. The time scale required to reach a steady state is close to the time scale of the presheath relaxation. Characteristics of sheaths in RF plasmas are also measured using a parallel-plate plasma capacitor. It is observed that the plasma potential profile has significant variation with frequency, even for frequencies as low as 1 kHz which are far below the ion plasma frequency (about 1 MHz).

Cho, M. H.↗
NASA NTRS1999

Technology Assessment of High Capacity Data Storage Systems: Can We Avoid a Data Survivability Crisis?

In a recent address at the California Science Center in Los Angeles, Vice President Al Gore articulated a Digital Earth Vision. That vision spoke to developing a multi-resolution, three-dimensional visual representation of the planet into which we can roam and zoom into vast quantities of embedded geo-referenced data. The vision was not limited to moving through space, but also allowing travel over a time-line, which can be set for days, years, centuries, or even geological epochs. A working group of Federal Agencies, developing a coordinated program to implement the Vice President's vision, developed the definition of the Digital Earth as a visual representation of our planet that enables a person to explore and interact with the vast amounts of natural and cultural geo-referenced information gathered about the Earth. One of the challenges identified by the agencies was whether the technology existed that would be available to permanently store and deliver all the digital data that enterprises might want to save for decades and centuries. Satellite digital data is growing by Moore's Law as is the growth of computer generated data. Similarly, the density of digital storage media in our information-intensive society is also increasing by a factor of four every three years. The technological bottleneck is that the bandwidth for transferring data is only growing at a factor of four every nine years. This implies that the migration of data to viable long-term storage is growing more slowly. The implication is that older data stored on increasingly obsolete media are at considerable risk if they cannot be continuously migrated to media with longer life times. Another problem occurs when the software and hardware systems for which the media were designed are no longer serviced by their manufacturers. Many instances exist where support for these systems are phased out after mergers or even in going out of business. In addition, survivability of older media can suffer from physical breakdown of components (e.g. tapes simply lose their magnetic properties after a long time in storage). As a result, a potential data survivability crisis is emerging. The scale of the crisis is comparable to that facing the Social Security System. Sometime in one or two decades, the exponential growth of data will become so great that many enterprises will not be able to migrate through their data to more permanent media during the lifetime of the media on which it resides. This will result in significant losses of data and their resultant impacts. To avoid this crisis, we need to plan and devote greater financial and intellectual resources are needed for the development and refinement of new storage media and migration technologies in order to preserve all data any organization determines worth saving permanently. This talk will explore technological solutions and suggested recommendations to address this technological data crisis.

Halem, Milton↗
NASA NTRS1993

Historical MOBLAS system characterization

This paper is written as a direct response to the published NASA Laser Geodynamic Satellite (LAGEOS) orbital solution SL7.1, in order to close the data information loop with an emphasis on the NASA Mobile Laser Ranging System's (MOBLAS) LAGEOS full rate data since November 1, 1983. A preliminary analysis of the supporting information (i.e. satellite laser ranging system eccentricities and system dependent range and time bias corrections) contained in SL7.1 indicated centimeter (cm) level discrepancies. In addition, a preliminary analysis of the computed monthly MOBLAS range biases from SL7.1 appear to show cm level systematic trends, some of which appear to be 'real', particularly in the 1984 to 1987 time period. This paper is intended to be a reference document for known MOBLAS systematic errors (magnitude and direction) and for supporting MOBLAS information (eccentricities, hardware configurations, and potential data problem periods). Therefore, this report is different than your typical system characterization report, but will be more valuable to the user. The MOBLAS error models and supporting information contained in this paper will be easily accessible from the Crustal Dynamics Data Information System (CDDIS).

Husson, Van S.↗
NASA NTRS2001

Retrieval of Polar Stratospheric Cloud Microphysical Properties from Lidar Measurements: Dependence on Particle Shape Assumptions

A retrieval algorithm has been developed for the microphysical analysis of polar stratospheric cloud (PSC) optical data obtained using lidar instrumentation. The parameterization scheme of the PSC microphysical properties allows for coexistence of up to three different particle types with size-dependent shapes. The finite difference time domain (FDTD) method has been used to calculate optical properties of particles with maximum dimensions equal to or less than 2 mu m and with shapes that can be considered more representative of PSCs on the scale of individual crystals than the commonly assumed spheroids. Specifically. these are irregular and hexagonal crystals. Selection of the optical parameters that are input to the inversion algorithm is based on a potential data set such as that gathered by two of the lidars on board the NASA DC-8 during the Stratospheric Aerosol and Gas Experiment 0 p (SAGE) Ozone Loss Validation experiment (SOLVE) campaign in winter 1999/2000: the Airborne Raman Ozone and Temperature Lidar (AROTEL) and the NASA Langley Differential Absorption Lidar (DIAL). The 0 microphysical retrieval algorithm has been applied to study how particle shape assumptions affect the inversion of lidar data measured in leewave PSCs. The model simulations show that under the assumption of spheroidal particle shapes, PSC surface and volume density are systematically smaller than the FDTD-based values by, respectively, approximately 10-30% and approximately 5-23%.

Reichardt, J.↗
DOE OSTI2024

Filaments in and between galaxy clusters at low and mid-frequency with the SKA

Context. Understanding the magnetised Universe is a major challenge in modern astrophysics, and cosmic magnetism has been acknowledged as one of the key scientific drivers of the most ambitious radio instrument ever planned, the Square Kilometre Array. Aims. With this work, we aim to investigate the potential of the Square Kilometre Array and its precursors and pathfinders in the study of magnetic fields in galaxy clusters and filaments through diffuse synchrotron radio emission. Galaxy clusters and filaments of the cosmic web are indeed unique laboratories in which to investigate turbulent fluid motions and large-scale magnetic fields in action, and much of what is known about magnetic fields in galaxy clusters comes from sensitive radio observations. Methods. Based on cosmological magneto-hydrodynamic simulations, we predict radio properties (total intensity and polarisation) of a pair of galaxy clusters connected by a cosmic-web filament. Results. We use our theoretical expectations to explore the potential of polarimetric observations to study large-scale structure magnetic fields in the frequency ranges 50–350 MHz and 950–1760 MHz. We also present predictions for galaxy cluster polarimetric observations with the Square Kilometre Array precursors and pathfinders, such as the LOw frequency ARray 2.0 and the MeerKAT+ telescope. Conclusions. Our findings point out that polarisation observations are particularly powerful for the study of large-scale magnetic fields, since they are not significantly affected by confusion noise. The unprecedented sensitivity and spatial resolution of the intermediatefrequency radio telescopes make them the favourite instruments for the study of these sources through polarimetric data, potentially allowing us to understand if the energy density of relativistic electrons is in equipartition with the magnetic field or rather coupled with the thermal gas density. Our results show that low-frequency instruments also represent a precious tool to study diffuse synchrotron emission in total intensity and polarisation.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2008

Formation of Clustered DNA Damage after High-LET Irradiation: A Review

Radiation can cause as well as cure cancer. The risk of developing radiation-induced cancer has traditionally been estimated from cancer incidence among survivors of the atomic bombs in Hiroshima and Nagasaki. These data provide the best estimate of human cancer risk over the dose range for low linear energy transfer (LET) radiations, such as X- or gamma-rays. The situation of estimating the real biological effects becomes even more difficult in the case of high LET particles encountered in space or as the result of domestic exposure to particles from radon gas emitters or other radioactive emitters like uranium-238. Complex DNA damage, i.e., the signature of high-LET radiations comprises by closely spaced DNA lesions forming a cluster of DNA damage. The two basic groups of complex DNA damage are double strand breaks (DSBs) and non-DSB oxidative clustered DNA lesions (OCDL). Theoretical analysis and experimental evidence suggest there is increased complexity and severity of complex DNA damage with increasing LET (linear energy transfer) and a high mutagenic or carcinogenic potential. Data available on the formation of clustered DNA damage (DSBs and OCDL) by high-LET radiations are often controversial suggesting a variable response to dose and type of radiation. The chemical nature and cellular repair mechanisms of complex DNA damage have been much less characterized than those of isolated DNA lesions like an oxidized base or a single strand break especially in the case of high-LET radiation. This review will focus on the induction of clustered DNA damage by high-LET radiations presenting the earlier and recent relative data.

Hada, Megumi↗
NASA NTRS1995

Development and Applications of a Self-Contained, Non-Invasive EVA Joint Angle and Muscle Fatigue Sensor System

The University of Maryland Space Systems Laboratory, as a participant in NASA's INSTEP program, is developing a non-invasive, self-contained sensor system which can provide quantitative measurements of joint angles and muscle fatigue in the hand and forearm. The goal of this project is to develop a system with which hand/forearm motion and fatigue metrics can be determined in various terrestrial and zero-G work environments. A preliminary study of the prototype sensor systems and data reduction techniques for the fatigue measurement system are presented. The sensor systems evaluated include fiberoptics, used to measure joint angle, surface electrodes, which measure the electrical signals created in muscle as it contracts; microphones, which measure the noise made by contracting muscle; and accelerometers, which measure the lateral muscle acceleration during contraction. The prototype sensor systems were used to monitor joint motion of the metacarpophalangeal joint and muscle fatigue in flexor digitorum superficialis and flexor carpi ulnaris in subjects performing gripping tasks. Subjects were asked to sustain a 60-second constant-contraction (isometric) exercise and subsequently to perform a repetitive handgripping task to failure. Comparison of the electrical and mechanical signals of the muscles during the different tasks will be used to evaluate the applicability of muscle signal measurement techniques developed for isometric contraction tasks to fatigue prediction in quasi-dynamic exercises. Potential data reduction schemes are presented.

Ranniger, C. U.↗
DOE OSTI2025

Survey-wide asteroid discovery with a high-performance computing enabled non-linear digital tracking framework

Modern astronomical surveys detect asteroids by linking together their appearances across multiple images taken over time. This approach faces limitations in detecting faint asteroids and handling the computational complexity of trajectory linking. Here, we present a novel method that adapts “digital tracking” – traditionally used for short-term linear asteroid motion across images – to work with large-scale synoptic surveys such as the Vera Rubin Observatory Legacy Survey of Space and Time (Rubin/LSST). Our approach combines hundreds of sparse observations of individual asteroids across their non-linear orbital paths to enhance detection sensitivity by several magnitudes. To address the computational challenges of processing massive data sets and dense orbital phase spaces, we developed a specialized high-performance computing architecture. We demonstrate the effectiveness of our method through experiments that take advantage of the extensive computational resources at Lawrence Livermore National Laboratory. This work enables the detection of significantly fainter asteroids in existing and future survey data, potentially increasing the observable asteroid population by orders of magnitude across different orbital families, from near-Earth objects (NEOs) to Kuiper belt objects (KBOs).

Asteroid discovery↗
NASA NTRS2015

Classifying Floating Potential Measurement Unit Data Products as Science Data

We are Co-Investigators for the Floating Potential Measurement Unit (FPMU) on the International Space Station (ISS) and members of the FPMU operations and data analysis team. We are providing this memo for the purpose of classifying raw and processed FPMU data products and ancillary data as NASA science data with unrestricted, public availability in order to best support science uses of the data.

Coffey, Victoria↗
NASA NTRS1983

Some potential research applications of GOES/VAS data in meteorology

The understanding and utilization of radiance data from the VAS instrument for meteorological purposes which requires an extensive and organized research plan whose ultimate goal is to provide quantitative measurements of the structure/dynamics of the atmosphere is outlined. The unique multispectral VAS data are potentially useful in almost all aspects of meteorology but have immediate applications in the mesoscale and severe storm research area since measurements are available over regional areas at time intervals of less than 1 hour. The higher priority research applications of VAS data pertaining to the interpretation and utilization of the passive VAS radiance measurements for mesoscale and severe-storm research are reviewed.

Wilson, G. S.↗