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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Radiative Transfer Modeling of a Large Pool Fire by Discrete Ordinates, Discrete Transfer, Ray Tracing, Monte Carlo and Moment Methods

Five computational methods for solution of the radiative transfer equation in an absorbing-emitting and non-scattering gray medium were compared on a 2 m JP-8 pool fire. The temperature and absorption coefficient fields were taken from a synthetic fire due to the lack of a complete set of experimental data for fires of this size. These quantities were generated by a code that has been shown to agree well with the limited quantity of relevant data in the literature. Reference solutions to the governing equation were determined using the Monte Carlo method and a ray tracing scheme with high angular resolution. Solutions using the discrete transfer method, the discrete ordinate method (DOM) with both S(sub 4) and LC(sub 11) quadratures, and moment model using the M(sub 1) closure were compared to the reference solutions in both isotropic and anisotropic regions of the computational domain. DOM LC(sub 11) is shown to be the more accurate than the commonly used S(sub 4) quadrature technique, especially in anisotropic regions of the fire domain. This represents the first study where the M(sub 1) method was applied to a combustion problem occurring in a complex three-dimensional geometry. The M(sub 1) results agree well with other solution techniques, which is encouraging for future applications to similar problems since it is computationally the least expensive solution technique. Moreover, M(sub 1) results are comparable to DOM S(sub 4).

Jensen, K. A.↗
DOE OSTI2022

5G Enabled Transformative Co-design and Co-simulation Framework for Grid Decarbonization and Modernization

5G is a breakthrough technology to enable a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for clean energy economy and grid modernization. The clean energy transformation not only requires innovative manufacturing, algorithm, application, and cross-domain co-simulation, but also a systematic evaluation and comprehensive support on the microelectronic and architectural computing customization to enable and maximize the high renewable penetration in the future power grid. The co-design of decarbonized grid, reliable yet efficient communication, and affordable yet ubiquitous computing will unlock the potential of almost any available tools for the undergoing clean energy transformation. 5G is also an opportunity to rethink the paradigm of infrastructure planning, as computing will be one of the core services for society alongside electricity and communication services.

5G↗
DOE OSTI2017

Seventy Years of Computing in the Nuclear Weapons Program

Los Alamos has continuously been on the forefront of scientific computing since it helped found the field. This talk will explore the rich history of computing in the Los Alamos weapons program. The current status of computing will be discussed, as will the expectations for the near future.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS2001

CDDIS Data Center Report

This report summarizes activities for the year 2000 and future plans of the Crustal Dynamics Data Information System (CDDIS) with respect to the International Very Long Base Interferometry (VLBI) Service for Geodesy and Astrometry (IVS). Included in this report are background information about the CDDIS, the computer architecture, staffing supporting the system, archive contents, and future plans for the CDDIS within the IVS.

Noll, Carey E.↗
DOE OSTI2021

Randomized Algorithms for Scientific Computing (RASC)

Randomized algorithms have propelled advances in artificial intelligence (AI) and represent a foundational research area in advancing AI for Science. Future advancements in DOE Office of Science priority areas such as climate science, astrophysics, fusion, advanced materials, combustion, and quantum computing all require randomized algorithms for surmounting challenges of complexity, robustness, and scalability. Advances in data collection and numerical simulation have changed the dynamics of scientific research and motivate the need for randomized algorithms. For instance, advances in imaging technologies such as X-ray ptychography, electron microscopy, electron energy loss spectroscopy, or adaptive optics lattice light-sheet microscopy collect hyperspectral imaging and scattering data in terabytes, at breakneck speed enabled by state-of-the-art detectors. The data collection is exceptionally fast compared with its analysis. Likewise, advances in high-performance architectures have made exascale computing a reality and changed the economies of scientific computing in the process. Floating-point operations that create data are essentially free in comparison with data movement. Thus far, most approaches have focused on creating faster hardware. Ironically, this faster hardware has exacerbated the problem by making data still easier to create. Under such an onslaught, scientists often resort to heuristic deterministic sampling schemes (e.g., low-precision arithmetic, sampling every nth element) and sacrifice potentially valuable accuracy. Dramatically better results can be achieved via randomized algorithms, reducing the data size as much as or more than naive deterministic subsampling can achieve, while retaining the high accuracy of computing on the full data set. By randomized algorithms we mean those algorithms that employ some form of randomness in internal algorithmic decisions to accelerate time to solution, increase scalability, or improve reliability. Examples include matrix sketching for solving large-scale least-squares problems (see Figure 1) and stochastic gradient descent for training machine learning models. We are not recommending heuristic methods but rather randomized algorithms that have certificates of correctness and probabilistic guarantees of optimality and near-optimality. Such approaches can be useful beyond acceleration, for example, in understanding how to avoid measure zero worst-case scenarios that plague methods such as QR matrix factorization.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1983

Calculation of potential flow past non-lifting bodies at angle of attack using axial and surface singularity methods

Two different singularity methods have been utilized to calculate the potential flow past a three dimensional non-lifting body. Two separate FORTRAN computer programs have been developed to implement these theoretical models, which will in the future allow inclusion of the fuselage effect in a pair of existing subcritical wing design computer programs. The first method uses higher order axial singularity distributions to model axisymmetric bodies of revolution in an either axial or inclined uniform potential flow. Use of inset of the singularity line away from the body for blunt noses, and cosine-type element distributions have been applied to obtain the optimal results. Excellent agreement to five significant figures with the exact solution pressure coefficient value has been found for a series of ellipsoids at different angles of attack. Solutions obtained for other axisymmetric bodies compare well with available experimental data. The second method utilizes distributions of singularities on the body surface, in the form of a discrete vortex lattice. This program is capable of modeling arbitrary three dimensional non-lifting bodies. Much effort has been devoted to finding the optimal method of calculating the tangential velocity on the body surface, extending techniques previously developed by other workers.

Shu, J. Y.↗
DOE OSTI2021

DUNE Software and Computing Challenges

The DUNE experiment will begin running in the late 2020's. The goals of the experiment include 1) studying neutrino oscillations using a beam of neutrinos from Fermilab in Illinois to the Sanford Underground Research Facility, 2) studying astrophysical neutrino sources and rare processes and 3) understanding the physics of neutrino interactions in matter. The DUNE Far Detector, consisting of four 17 kt LArTPC modules, will produce "events" rang-ing in size from 6 GBs to more than 100 TBs, posing unique challenges for DUNE software and computing. The data processing algorithms, particularly for raw data, drive the requirements for the future DUNE software framework documented here.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2019

Concept Evaluation: NASA Reference Model 2-Side by Side

Urban Air Mobility (UAM) is an up and coming topic in the world of aerosciences. A variety of companies, most notably Uber, has begun working towards making air taxis a regular part of day to day life. However, the implementation of this system into society will require a significant amount of work: making helicopters that can handle these flights and operate safely in urban environments, having landing zones, and working out new technologies to lower costs. NASA has also taken interest in this new idea and has formed a focus group of interns to tackle some of these problems. They have started by designing a few concept models for what these air taxis could look like, focusing on low noise, multiple passenger configurations, and the potential for electric or hybrid helicopters. One particular model is known as NR2, or the "Side by Side," which features two rotors spinning in opposite directions. Though these models are purely conceptual at this point, understanding the real-world aerodynamics and performance of this model is crucial to its future development. Using a program known as Rotorcraft Computational Fluid Dynamics (RotCFD), the performance characteristics of the rotors and aircraft, such as the lift, drag, thrust and power can be determined. These simulations can be run in a variety of flight configurations, with hover, forward flight, and climb being focused on in this study. The rotor collective angle can also be changed and used to get results about the lift and drag for the blades and the model body. These simulations can provide information for future model construction and wind tunnel testing.

Reference Model↗
DOE OSTI2023

Ising-Traffic: Using Ising Machine Learning to Predict Traffic Congestion under Uncertainty

This paper addresses the challenges in accurate and realtime traffic congestion prediction with uncertainty by proposing Ising-Traffic, a novel quantum-inspired dual-model Ising based traffic prediction framework which delivers higher accuracy and lower latency than SOTA solutions. While traditional and deep learning methods face the trade-off between algorithm complexity and computational efficiency, our Ising-based method leverages Ising’s inherent and unique capability of finding the state of a system with the lowest energy and applying it to traffic prediction. In this work, traffic prediction under uncertainty is formulated into two separate Ising models: Reconstruct-Ising and Predict-Ising. Reconstruct-Ising is mapped onto modern Ising machine and handles uncertainty in traffic accurately with negligible latency and energy consumption, while Predict-Ising is mapped onto traditional processors and predicts future congestion precisely with only at most 1.8% computational demands of existing solutions. Our evaluation shows Ising-Traffic delivers on average 98× speedups and 5% accuracy improvement over SOTA.

traffic flow control, Ising↗
NASA NTRSDate not supplied

Magnetohydrodynamic and Aerodynamic Assessment of Ballistic Entry of a 70deg Spherecone at Mars and Venus

An electrical conductivity database for continuum flow in a CO2 atmosphere over a 70 deg spherecone was created using the Data Parallel Line Relaxation Code computational fluid dynamics software to inform development of future magnetohydrodynamic subsystems at Venus and Mars. Sixteen freestream conditions were considered at Mars with atmospheric relative velocities from 5 to 8 km/s and altitudes between 20 and 80 km. Sixteen freestream conditions were considered at Venus with atmospheric relative velocities from 9 to 12 km/s and altitudes between 85 and 115 km. Results indicate that the total electrical conductivity in the flow volume always increases as velocity increases. At low velocities, the electrical conductivity is higher at high altitudes, while at high velocities, the electrical conductivity is higher at low altitudes. Three of the 80 km altitude computational fluid dynamics solutions show good agreement with Direct Simulation Monte Carlo results. In general, computational fluid dynamics predicts thinner shocks, higher electron number density, and similar vibrational temperatures as direct simulation Monte Carlo. The magnetohydrodynamic force was calculated at both Mars and Venus. Results indicate there may not be sufficient control authority to use magnetohydrodynamics as a trajectory control mechanism at Mars without artificially increasing the electrical conductivity of the flow, but there may be appreciable control authority for a drag-modulated aerocapture at Venus.

Destiny M Fawley↗
DOE OSTI2024

Transformational Regional-Scale Earthquake Simulations with the DOE EarthQuake SIMulation Exascale Framework

Earthquakes present worldwide risk to economic and human safety. The 2023 earthquakes in Turkiye provided a reminder of the potential for catastrophic consequences with 50,700 deaths and 15.7 million people affected. The ability to predict ground motions and infrastructure damage for earthquakes continues to be a challenging problem for scientists and engineers. Until now, estimates of ground motions have been performed empirically by looking at sparse data from past earthquakes. This approach can provide statistical information on intensity amplitudes but cannot inform site-specific ground motions essential to developing the most effective resilience. Interest has grown in large-scale computational models to simulate earthquakes at regional scale. The U.S. Department of Energy EarthQuake SIMulation (EQSIM) framework was developed for regional-scale earthquake simulations at unprecedented fidelity, taking advantage of emerging GPU-accelerated systems. This article describes the EQSIM workflow and demonstrates regional-scale simulations with the new computational capability available to scientists in their quest to mitigate future disasters.

58 GEOSCIENCES↗
NASA NTRS1973

Results of solar electric thrust vector control system design, development and tests

Efforts to develop and test a thrust vector control system TVCS for a solar-energy-powered ion engine array are described. The results of solar electric propulsion system technology (SEPST) III real-time tests of present versions of TVCS hardware in combination with computer-simulated attitude dynamics of a solar electric multi-mission spacecraft (SEMMS) Phase A-type spacecraft configuration are summarized. Work on an improved solar electric TVCS, based on the use of a state estimator, is described. SEPST III tests of TVCS hardware have generally proved successful and dynamic response of the system is close to predictions. It appears that, if TVCS electronic hardware can be effectively replaced by control computer software, a significant advantage in control capability and flexibility can be gained in future developmental testing, with practical implications for flight systems as well. Finally, it is concluded from computer simulations that TVCS stabilization using rate estimation promises a substantial performance improvement over the present design.

Fleischer, G. E.↗
NASA NTRS1984

Automated mesoscale winds derived from GOES multispectral imagery

An automated technique for extracting mesoscale winds from sequences of GOES VISSR image pairs was developed, tested and configured for quasi-real time/research applications on a computing system which gives mesoscale wind estimates at the highest spatial/temporal resolution possible from the VISSR imagery down to a wind vector separation of 10 km. Preprocessing of imagery using IR resampling, VIS edge preserving filtering, and reduced VIS resolution averaging improved height assignments and vector extraction for 10, 15, and 30 min imagery. An objective quality control system provides much greater than 99% accuracy in eliminating questionable wind estimates. Automated winds generally have better spatial coverage and density, and have random error estimates half as large as the manual winds. Dynamical analysis of cloud wind divergence revealed temporally consistent convergence centers on the meso beta scale that are highly correlated with on going and future developing convective storms. The entire system of computer codes was successfully vectorized for execution on an array processor resulting in job turnaround in less than one hour.

Wilson, G. S.↗
DOE OSTI2022

Technical Characterization and Benefit Evaluation of 5G-Enabled Grid Data Transport and Applications

This report summarizes the Year 1 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research Program. 5G is a breakthrough technology that enables a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for a clean energy economy and grid modernization. In collaboration with PNNL’s Advanced Wireless Communication team and Center for Advanced Technology Evaluation team, the project team has been evaluating the system performance of 5G testbeds in the PNNL 5G Innovation Studio, and has formulated a co-simulation test case of power system transmission, distribution, and communication (T&D&C) networks considering 5G technology and high penetration of distributed energy resources. The methodology developed in the 5G Energy FRAME project can be customized to fit different future grid scenarios to evaluate multiple (dynamic) configurations (computing, sensing, communication, environment) for different stakeholders. In summary, our main technical highlights in project Year 1 are as follows: 1) Technical characterization of 5G standalone architectures, 2) Formulation of co-simulation test case of T&D&C networks embedded with 5G, 3) Initial benefit evaluation of 5G communication platform for grid use cases, and 4) Additional extended discussions on edge computing, artificial intelligence and machine learning, and high-performance computing and cloud computing adoptions. In addition, a collection of system performance data is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2018

Increasing Flight Software Reuse with OpenSatKit

In January 2015 the NASA Goddard Space Flight Center (GSFC) released the Core Flight System (cFS) as open source under the NASA Open Source Agreement (NOSA) license. The cFS is based on flight software (FSW) developed for 12 spacecraft spanning nearly two decades of effort and it can provide about a third of the FSW functionality for a low-earth orbiting scientific spacecraft. The cFS is a FSW framework that is portable, configurable, and extendable using a product line deployment model. However, the components are maintained separately so the user must configure, integrate, and deploy them as a cohesive functional system. This can be very challenging especially for organizations such as universities building cubesats that have minimal experience developing FSW. Supporting universities was one of the primary motivators for releasing the cFS under NOSA. This paper describes the OpenSatKit that was developed to address the cFS deployment challenges and to serve as a cFS training platform for new users. It provides a fully functional out-of-the box software system that includes NASA's cFS, Ball Aerospace's command and control system COSMOS, and a NASA dynamic simulator called 42. The kit is freely available since all of the components have been released as open source. The kit runs on a Linux platform, includes 8 cFS applications, several kit-specific applications, and built in demos illustrating how to use key application features. It also includes the software necessary to port the cFS to a Raspberry Pi and instructions for configuring COSMOS to communicate with the target. All of the demos and test scripts can be rerun unchanged with the cFS running on the Raspberry Pi. The cFS uses a 3-tiered layered architecture including a platform abstraction layer, a Core Flight Executive (cFE) middle layer, and an application layer. Similar to smart phones, the cFS application layer is the key architectural feature for users to extend the FSW functionality to meet their mission-specific requirements. The platform abstraction layer and the cFE layers go a step further than smart phones by providing a platform-agnostic Application Programmer Interface (API) that allows applications to run unchanged on different platforms. OpenSatKit can serve two significant architectural roles that will further help the adoption of the cFS and help create a community of users that can share assets. First, the kit is being enhanced to automate the integration of applications with the goal of creating a virtual cFS "App Store".. Second, a platform certification test suite can be developed that would allow users to verify the port of the cFS to a new platform. This paper will describe the current state of these efforts and future plans.

Computer Programming and Software↗
NASA NTRSDate not supplied

Exploring Cryogenic Propellant Behavior in Low-Gravity Environments, Insights from the Saturn AS-203 Vent Experiments and CFD Analysis

In the 1960s, NASA embarked on a series of groundbreaking flight tests on the Saturn AS-203, aiming to understand the complex dynamics of propellants in the distinctive low-gravity lunar environment. These tests centered on venting experiments, subjecting cryogenic liquid hydrogen to conditions beneath its saturation pressure while accelerating the vehicle to manage the propellant's positioning. During these experiments, NASA meticulously scrutinized the propellant tank using a suite of instruments, including temperature and pressure sensors, as well as a camera placed internal to the liquid hydrogen tank. The outcomes provided anecdotal evidence revealing the phenomenon of boiling along the tank's walls and the intriguing formation of liquid globules and droplets in the ullage during the venting process. Notably, the substantial drop in liquid temperature during these tests suggests adiabatic cooling as liquid hydrogen evaporates. This evaporation leads to a cooling of the remaining hydrogen due to the heat it releases. This paper presents the outcomes of our initial analysis, wherein CFD models were used to simulate the observed boiling phenomena and the bulk movement of the liquid hydrogen propellant, both qualitatively and quantitatively. The implications of these findings may extend to mission and vehicle designers, providing invaluable insights for crafting more efficient and effective in-space propulsion systems utilizing cryogenic propellant including impacts to vehicle control systems. Understanding propellant behavior under these conditions may better inform GNC teams, ensuring more stable vehicle operations when utilizing cryogenic propellants. This includes essential considerations for cryogenic propellant transfer and storage systems, integral to NASA's forthcoming Artemis missions. While we recognize the challenges tied to CFD models, this study represents a step forward, highlighting current progress and signaling the potential for refining our predictive understanding in the future.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

Exploring Cryogenic Propellant Behavior in Low-Gravity Environments, Insights from the Saturn AS-203 Vent Experiments and CFD Analysis

In the 1960s, NASA embarked on a series of groundbreaking flight tests on the Saturn AS-203, aiming to understand the complex dynamics of propellants in the distinctive low-gravity lunar environment. These tests centered on venting experiments, subjecting cryogenic liquid hydrogen to conditions beneath its saturation pressure while accelerating the vehicle to manage the propellant's positioning. During these experiments, NASA meticulously scrutinized the propellant tank using a suite of instruments, including temperature and pressure sensors, as well as a camera placed internal to the liquid hydrogen tank. The outcomes provided anecdotal evidence revealing the phenomenon of boiling along the tank's walls and the intriguing formation of liquid globules and droplets in the ullage during the venting process. Notably, the substantial drop in liquid temperature during these tests suggests adiabatic cooling as liquid hydrogen evaporates. This evaporation leads to a cooling of the remaining hydrogen due to the heat it releases. This paper presents the outcomes of our initial analysis, wherein CFD models were used to simulate the observed boiling phenomena and the bulk movement of the liquid hydrogen propellant, both qualitatively and quantitatively. The implications of these findings may extend to mission and vehicle designers, providing invaluable insights for crafting more efficient and effective in-space propulsion systems utilizing cryogenic propellant including impacts to vehicle control systems. Understanding propellant behavior under these conditions may better inform GNC teams, ensuring more stable vehicle operations when utilizing cryogenic propellants. This includes essential considerations for cryogenic propellant transfer and storage systems, integral to NASA's forthcoming Artemis missions. While we recognize the challenges tied to CFD models, this study represents a step forward, highlighting current progress and signaling the potential for refining our predictive understanding in the future.

Computational Fluid Dynamics↗