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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

AIC Computations Using Navier-Stokes Equations on Single Image Supercomputers For Design Optimization

A procedure to accurately generate AIC using the Navier-Stokes solver including grid deformation is presented. Preliminary results show good comparisons between experiment and computed flutter boundaries for a rectangular wing. A full wing body configuration of an orbital space plane is selected for demonstration on a large number of processors. In the final paper the AIC of full wing body configuration will be computed. The scalability of the procedure on supercomputer will be demonstrated.

Guruswamy, Guru↗
NASA NTRS2006

Simulated convective systems using a cloud resolving model: Impact of large-scale temperature and moisture forcing using observations and GEOS-3 reanalysis

The GCE (Goddard Cumulus Ensemble) model, which has been developed and improved at NASA Goddard Space Flight Center over the past two decades, is considered as one of the finer and state-of-the-art CRMs (Cloud Resolving Models) in the research community. As the chosen CRM for a NASA Interdisciplinary Science (IDS) Project, GCE has recently been successfully upgraded into an MPI (Message Passing Interface) version with which great improvement has been achieved in computational efficiency, scalability, and portability. By basically using the large-scale temperature and moisture advective forcing, as well as the temperature, water vapor and wind fields obtained from TRMM (Tropical Rainfall Measuring Mission) field experiments such as SCSMEX (South China Sea Monsoon Experiment) and KWAJEX (Kwajalein Experiment), our recent 2-D and 3-D GCE simulations were able to capture detailed convective systems typical of the targeted (simulated) regions. The GEOS-3 [Goddard EOS (Earth Observing System) Version-3] reanalysis data have also been proposed and successfully implemented for usage in the proposed/performed GCE long-term simulations (i.e., aiming at producing massive simulated cloud data -- Cloud Library) in compensating the scarcity of real field experimental data in both time and space (location). Preliminary 2-D or 3-D pilot results using GEOS-3 data have generally showed good qualitative agreement (yet some quantitative difference) with the respective numerical results using the SCSMEX observations. The first objective of this paper is to ensure the GEOS-3 data quality by comparing the model results obtained from several pairs of simulations using the real observations and GEOS-3 reanalysis data. The different large-scale advective forcing obtained from these two kinds of resources (i.e., sounding observations and GEOS-3 reanalysis) has been considered as a major critical factor in producing various model results. The second objective of this paper is therefore to investigate and present such an impact of large-scale forcing on various modeled quantities (such as hydrometeors, rainfall, and etc.). A third objective is to validate the overall GCE 3-D model performance by comparing the numerical results with sounding observations, as well as available satellite retrievals.

Shie, C.-L.↗
NASA NTRS2013

Towards Efficient Scientific Data Management Using Cloud Storage

A software prototype allows users to backup and restore data to/from both public and private cloud storage such as Amazon's S3 and NASA's Nebula. Unlike other off-the-shelf tools, this software ensures user data security in the cloud (through encryption), and minimizes users operating costs by using space- and bandwidth-efficient compression and incremental backup. Parallel data processing utilities have also been developed by using massively scalable cloud computing in conjunction with cloud storage. One of the innovations in this software is using modified open source components to work with a private cloud like NASA Nebula. Another innovation is porting the complex backup to- cloud software to embedded Linux, running on the home networking devices, in order to benefit more users.

He, Qiming↗
NASA NTRSDate not supplied

Computational Models of Trustworthiness and Trust in Autonomous Cyber-Physical-Human Systems

In this paper, we propose an approach to developing a concept of actionable trust in multi-agent,cyber-physical-human systems in safety-critical and time-critical environment of air transportation. Actionable trust requires computational models of trustworthiness and trust, for use during system design and in real time, during operations. We describe the models, examine their computability and scalability, as well as what remains to be done.

Autonomous Systems↗
NASA NTRS2019

Enabling Real-time Multi-messenger Astrophysics Discoveries with Deep Learning

Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that probe the Universe using different cosmic messengers: electromagnetic waves, cosmic rays, gravitational waves and neutrinos. In this Expert Recommendation, we review the key challenges of real-time observations of gravitational wave sources and their electromagnetic and astroparticle counterparts, and make a number of recommendations to maximize their potential for scientific discovery. These recommendations refer to the design of scalable and computationally efficient machine learning algorithms; the cyber-infrastructure to numerically simulate astrophysical sources, and to process and interpret multi-messenger astrophysics data; the management of gravitational wave detections to trigger real-time alerts for electromagnetic and astroparticle follow-ups; a vision to harness future developments of machine learning and cyber-infrastructure resources to cope with the big-data requirements; and the need to build a community of experts to realize the goals of multi-messenger astrophysics.

E A Huerta↗
NASA NTRS2023

Technical Note: NASAaccess – A Tool for Access, Reformatting, and Visualization of Remotely Sensed Earth Observation and Climate Data

The National Aeronautics and Space Administration (NASA) has launched a new initiative, the Open-Source Science Initiative (OSSI), to enable and support science towards openness. The OSSI supports open-source software development and dissemination. In this work, we present NASAaccess, which is an open-source software package and web-based environmental modeling application for earth observation data accessing, reformatting, and presenting quantitative data products. The main objective of developing the NASAaccess platform is to facilitate exploration, modeling, and understanding of earth data for scientists, stakeholders, and concerned citizens whose objectives align with the new OSSI goals. The NASAaccess platform is available as software packages (i.e., the R and conda packages) as well as an interactive-format web-based environmental modeling application for earth observation data developed with Tethys Platform. NASAaccess has been envisioned as lowering the technical barriers and simplifying the process of accessing scalable distributed computing resources and leveraging additional software for data and computationally intensive modeling frameworks. Specifically, NASAaccess has been developed to meet the need for seamless earth observation remote-sensing and climate data ingestion into various hydrological modeling frameworks. Moreover, NASAaccess is also contributing to keeping interested parties and stakeholders engaged with environmental modeling, accessing the information available in various remote-sensing products. NASAaccess' current capabilities cover various NASA datasets and products that include the Global Precipitation Measurement (GPM) data products, the Global Land Data Assimilation System (GLDAS) land surface states and fluxes, and the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) Coupled Model Intercomparison Project Phase 5 (CMIP5) and Coupled Model Intercomparison Project Phase 6 (CMIP6) climate change dataset products.

Ibrahim Nourein Mohammed↗
DOE OSTI2014

OpenARC: Extensible OpenACC Compiler Framework for Directive-Based Accelerator Programming Study

Directive-based, accelerator programming models such as OpenACC have arisen as an alternative solution to program emerging Scalable Heterogeneous Computing (SHC) platforms. However, the increased complexity in the SHC systems incurs several challenges in terms of portability and productivity. This paper presents an open-sourced OpenACC compiler, called OpenARC, which serves as an extensible research framework to address those issues in the directive-based accelerator programming. This paper explains important design strategies and key compiler transformation techniques needed to implement the reference OpenACC compiler. Moreover, this paper demonstrates the efficacy of OpenARC as a research framework for directive-based programming study, by proposing and implementing OpenACC extensions in the OpenARC framework to 1) support hybrid programming of the unified memory and separate memory and 2) exploit architecture-specific features in an abstract manner. Porting thirteen standard OpenACC programs and three extended OpenACC programs to CUDA GPUs shows that OpenARC performs similarly to a commercial OpenACC compiler, while it serves as a high-level research framework.

Lee, Seyong↗
DOE OSTI2020

High Performance Computing Traffic Simulations for Real-Time Traffic Control of Mobility in Chattanooga Region

In 2019, highway congestion wasted over 3 billion gallons of fuel and caused 8.8 billion hours of lost productivity.1 Research has shown that introducing near-real time traffic controls can significantly reduce congestion. Validated and calibrated traffic simulations enable the modeling of transportation systems and the evaluation of different traffic control actions and schemes given a variety of circumstances that represent likely future scenarios. The developed scenarios can inform the deployment of controls in near real-time to improve freight and passenger vehicle congestion and energy use. In this work, we present simulations used to model the traffic in the Chattanooga, Tennessee, metropolitan area. Simulations were constructed and calibrated using a variety of local, data science enhanced, data sources utilizing open source software including the Simulation of Urban Mobility (SUMO) simulator. High-Performance Computing (HPC) provides a scalable platform with enough computing for the high-fidelity simulation of many scenarios and the application of advance data science especially for large-scale systems. Our simulations include microscopic simulations at a corridor level for traffic signal control, and mesoscopic simulations to evaluate regional operational controls and infrastructure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

System and method for scalable optical interconnect for quantum computing

The present disclosure relates to an interconnect system for interfacing an electronic subsystem to a qubit package, wherein the qubit package has a plurality of independent qubits. The system makes use of an optical fiber cable having a plurality of optical fibers, which is interfaced to the electronic subsystem. A 3D optical structure is used which has a plurality of internal waveguides, and which is configured to interface the optical fiber cable to the qubit package. The 3D optical structure further has at least one subsystem for using the plurality of waveguides to receive signals of a first type from at least one of the qubits package or the optical fiber cable, to convert the signals from the first type to a second type, and to transmit the signals in the second type to the other one of the fiber optic cable or the qubit package.

Patra, Susant K.↗
DOE OSTI2024

Scalable Circuits for Preparing Ground States on Digital Quantum Computers: The Schwinger Model Vacuum on 100 Qubits

The vacuum of the lattice Schwinger model is prepared on up to 100 qubits of IBM’s Eagle-processor quantum computers. A new algorithm to prepare the ground state of a gapped translationally invariant system on a quantum computer is presented, which we call “scalable circuits ADAPT-VQE” (SC-ADAPT-VQE). This algorithm uses the exponential decay of correlations between distant regions of the ground state, together with ADAPT-VQE, to construct quantum circuits for state preparation that can be scaled to arbitrarily large systems. These scalable circuits can be determined with use of classical computers, avoiding the challenging task of optimizing parameterized circuits on a quantum computer. SC-ADAPT-VQE is applied to the Schwinger model, and is shown to be systematically improvable, with an accuracy that converges exponentially with circuit depth. Both the structure of the circuits and the deviations of prepared wave functions are found to become independent of the number of spatial sites, L . This allows a controlled extrapolation of the circuits, determined with use of small or modest-sized systems, to arbitrarily large L . The circuits for the Schwinger model are determined on lattices up to L = 14 (28 qubits) with the Qiskit classical simulator, and are subsequently scaled up to prepare the L = 50 (100 qubits) vacuum on IBM’s 127-superconducting-qubit quantum computers ibm_brisbane and ibm_cusco. After introduction of an improved error-mitigation technique, which we call “operator decoherence renormalization”, the chiral condensate and charge-charge correlators obtained from the quantum computers are found to be in good agreement with classical matrix product state simulations. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1994

A comparative study of serial and parallel aeroelastic computations of wings

A procedure for computing the aeroelasticity of wings on parallel multiple-instruction, multiple-data (MIMD) computers is presented. In this procedure, fluids are modeled using Euler equations, and structures are modeled using modal or finite element equations. The procedure is designed in such a way that each discipline can be developed and maintained independently by using a domain decomposition approach. In the present parallel procedure, each computational domain is scalable. A parallel integration scheme is used to compute aeroelastic responses by solving fluid and structural equations concurrently. The computational efficiency issues of parallel integration of both fluid and structural equations are investigated in detail. This approach, which reduces the total computational time by a factor of almost 2, is demonstrated for a typical aeroelastic wing by using various numbers of processors on the Intel iPSC/860.

Byun, Chansup↗
DOE OSTI2026

A mathematical framework for thermodynamic computing with applications to chemical reaction networks

The widespread adoption of energy-intensive computing applications has led to a growing need for energy-efficient computing approaches. Thermodynamic computing offers a promising approach for low-energy computation by leveraging the intrinsic computational capabilities of physical, chemical, or biological systems. However, the mathematical foundations of thermodynamic computing require further development to fully realize the potential energy efficiencies, as well as to assess factors like noise and operational speed. In this paper, we establish a mathematical framework for utilizing thermodynamic processes to perform fundamental operations, including addition, subtraction, multiplication, and division. We highlight the use of chemical reactions as potential computational units and explore synthetic chemical and biochemical systems as practical implementations. Additionally, we demonstrate how these principles can be applied to solving complex mathematical problems, such as ordinary differential equations (ODEs) and suggest the necessary components to implement the thermodynamic computing framework using chemical reactions based in a microfluidic device. This work enhances our understanding of thermodynamic processes for natural computing as a basis for scalable, energy-efficient computation in paradigm disruptive next-generation systems.

Cannon, William R. [Pacific Northwest National Lab↗