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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Cost effective development of a Shuttle-based astronomical instrument control system

The high level language FORTH is used for the electronic control of the Space Shuttle-based Ultraviolet Imaging Telescope, in a flight computer system which minimizes costs. The greater part of the breadboard version of the flight computer is assembled from commercially available components, reducing novel circuit design features and permitting simultaneous development of both hardware and software. The commercial boards are then refabricated on aluminum core heat conducting stock, using high reliability parts to produce the flight versions of the system. The system's ground support equipment employs a MINC-25 minicomputer which performs such functions as flight computer software development, PROM programming, test and integration support, and flight operations support. The implementation of these concepts in flight computer telescope controls is described.

Parise, R. A.↗
DOE OSTI2019

Learning concave-convex profiles of data transport over dedicated connections

Dedicated data transport infrastructures are increasingly being deployed to support distributed big-data and high-performance computing scenarios. These infrastructures employ data transfer nodes that use sophisticated software stacks to support network transport among sites, which often house distributed file and storage systems. Throughput measurements collected over such infrastructures for a range of round trip times (RTTs) reflect the underlying complex end-to-end connections, and have revealed dichotomous throughput profiles as functions of RTT. In particular, concave regions of throughput profiles at lower RTTs indicate near-optimal performance, and convex regions at higher RTTs indicate bottlenecks due to factors such as buffer or credit limits. We present a machine learning method that explicitly infers these concave and convex regions and transitions between them using sigmoid functions. We also provide distribution-free confidence estimates for the generalization error of these concave-convex profile estimates. Throughput profiles for data transfers over 10 Gbps connections with 0–366 ms RTT provide important performance insights, including the near optimality of transfers performed with the XDD tool between XFS filesystems, and the performance limits of wide-area Lustre extensions using LNet routers. A direct application of generic machine learning packages does not adequately highlight these critical performance regions or provide as precise confidence estimates.

Rao, Nageswara↗
NASA NTRS1998

Development of an Experimental Data Base to Validate Compressor-Face Boundary Conditions Used in Unsteady Inlet Flow Computations

The ability to predict the dynamics of integrated inlet/compressor systems is an important part of designing high-speed propulsion systems. The boundaries of the performance envelope are often defined by undesirable transient phenomena in the inlet (unstart, buzz, etc.) in response to disturbances originated either in the engine or in the atmosphere. Stability margins used to compensate for the inability to accurately predict such processes lead to weight and performance penalties, which translate into a reduction in vehicle range. The prediction of transients in an inlet/compressor system requires either the coupling of two complex, unsteady codes (one for the inlet and one for the engine) or else a reliable characterization of the inlet/compressor interface, by specifying a boundary condition. In the context of engineering development programs, only the second option is viable economically. Computations of unsteady inlet flows invariably rely on simple compressor-face boundary conditions (CFBC's). Currently, customary conditions include choked flow, constant static pressure, constant axial velocity, constant Mach number or constant mass flow per unit area. These conditions are straightforward extensions of practices that are valid for and work well with steady inlet flows. Unfortunately, it is not at all likely that any flow property would stay constant during a complex system transient. At the start of this effort, no experimental observation existed that could be used to formulate of verify any of the CFBC'S. This lack of hard information represented a risk for a development program that has been recognized to be unacceptably large. The goal of the present effort was to generate such data. Disturbances reaching the compressor face in flight may have complex spatial structures and temporal histories. Small amplitude disturbances may be decomposed into acoustic, vorticity and entropy contributions that are uncoupled if the undisturbed flow is uniform. This study is focused on the response of an inlet/compressor system to acoustic disturbances. From the viewpoint of inlet computations, acoustic disturbances are clearly the most important, since they are the only ones capable of moving upstream. Convective and entropy disturbances may also produce upstream-moving acoustic waves, but such processes are outside the scope of the present study.

Sajben, Miklos↗
DOE OSTI2022

GASNet-EX RMA Communication Performance on Recent Supercomputing Systems

Partitioned Global Address Space (PGAS) programming models, typified by systems such as Unified Parallel C (UPC) and Fortran coarrays, expose one-sided Remote Memory Access (RMA) communication as a key building block for High Performance Computing (HPC) applications. Architectural trends in supercomputing make such programming models increasingly attractive, and newer, more sophisticated models such as UPC++, Legion and Chapel that rely upon similar communication paradigms are gaining popularity. GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of PGAS runtime systems and other alternative models in emerging exascale machines. The library is an evolution of the popular GASNet communication system, building upon 20 years of lessons learned. We present microbenchmark results which demonstrate the RMA performance of GASNet-EX is competitive with MPI implementations on four recent, high-impact, production HPC systems. These results are an update relative to previously published results on older systems. The networks measured here are representative of hardware currently used in six of the top ten fastest supercomputers in the world, and all of the exascale systems on the U.S. DOE road map.

Hargrove, Paul H↗
DOE OSTI2018

Optimal Black Start Allocation for Power System Restoration

Equipment failures, operator errors, natural disasters and cyber-attacks can and have caused extended blackouts of the electric grid. Even though such events are rare, preparedness for them is critical because extended power outages endanger human lives, compromise national security, or result in economic losses of billions of dollars. Since most of the generating units cannot restart without connecting to an energized grid, the system operator relies on a few units with the ability to start autonomously, called Black Start (BS) units, to restore the power system. Allocating and maintaining these units is costly and can severely impact the restoration security and time. We formulate an optimization problem to optimally allocate BS units in the grid, while simultaneously optimizing over the restoration sequence. We extend existing optimal allocation models by including grid considerations such as active power nodal balance, transmission switching, nodal reactive power support and voltage limits. In order to aid the branch and bound tree that solves the resulting large scale mixed integer program, we propose a randomized heuristic that is executed multiple times in parallel on a high-performance computing environment to find feasible solutions. Here, we proceed to solve the IEEE-39, the IEEE-118, and a simplified WECC system with 225 nodes and 136 generators to near optimality.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1998

NASA's Participation in the National Computational Grid

Over the last several years it has become evident that the character of NASA's supercomputing needs has changed. One of the major missions of the agency is to support the design and manufacture of aero- and space-vehicles with technologies that will significantly reduce their cost. It is becoming clear that improvements in the process of aerospace design and manufacturing will require a high performance information infrastructure that allows geographically dispersed teams to draw upon resources that are broader than traditional supercomputing. A computational grid draws together our information resources into one system. We can foresee the time when a Grid will allow engineers and scientists to use the tools of supercomputers, databases and on line experimental devices in a virtual environment to collaborate with distant colleagues. The concept of a computational grid has been spoken of for many years, but several events in recent times are conspiring to allow us to actually build one. In late 1997 the National Science Foundation initiated the Partnerships for Advanced Computational Infrastructure (PACI) which is built around the idea of distributed high performance computing. The Alliance lead, by the National Computational Science Alliance (NCSA), and the National Partnership for Advanced Computational Infrastructure (NPACI), lead by the San Diego Supercomputing Center, have been instrumental in drawing together the "Grid Community" to identify the technology bottlenecks and propose a research agenda to address them. During the same period NASA has begun to reformulate parts of two major high performance computing research programs to concentrate on distributed high performance computing and has banded together with the PACI centers to address the research agenda in common.

Feiereisen, William J.↗
DOE OSTI2023

Mastering HPC Runtime Prediction: From Observing Patterns to a Methodological Approach

The continual expansion of high-performance computing (HPC) brings with it an increasing need for efficiency. Heavy investment in energy, hardware, and software infrastructure to support peta- and exascale computing requires the optimization of existing systems and, wherever possible, the discernment and adoption of best-practices towards these goals. Such is the case for runtime prediction. When a job is submitted to an HPC system, an estimate of its runtime is provided by the user in the form of "requested wallclock". Error in this user-provided estimate can lead to jobs being prematurely killed by the scheduler, increased wait time on the queue, and decreased system utilization. More than fifteen years of research has been directed at mitigating these effects by using data-driven runtime predictions. Codified here is a set of commonalities and insights emerging from this body of work, which we present as recommendations and best practices. These practices are combined into a methodological approach described and evaluated on an 11-million-job dataset from the National Renewable Energy Laboratory's petascale HPC system, Eagle. This dataset and the accompanying codebase have been released to the public domain for the benefit of the wider HPC research community.

high performance computing↗
DOE OSTI2023

Mastering HPC Runtime Prediction: From Observing Patterns to a Methodological Approach: Preprint

The continual expansion of high-performance computing (HPC) brings with it an increasing need for efficiency. Heavy investment in energy, hardware, and software infrastructure to support peta- and exascale computing requires the optimization of existing systems and, wherever possible, the discernment and adoption of best-practices towards these goals. Such is the case for runtime prediction. When a job is submitted to an HPC system, an estimate of its runtime is provided by the user in the form of "requested wallclock''. Error in this user-provided estimate can lead to jobs being prematurely killed by the scheduler, increased wait time on the queue, and decreased system utilization. More than fifteen years of research has been directed at mitigating these effects by using data-driven runtime predictions. Codified here is a set of commonalities and insights emerging from this body of work, which we present as recommendations and best practices. These practices are combined into a methodological approach described and evaluated on an 11-million-job dataset from the National Renewable Energy Laboratory's petascale HPC system, Eagle. This dataset and the accompanying codebase have been released to the public domain for the benefit of the wider HPC research community.

high performance computing↗
NASA NTRSDate not supplied

High-Fidelity Aerodynamic Analysis and Optimization of the SUSAN Electrofan Concept

The Subsonic Single Aft Engine (SUSAN) Electrofan is a new single-aisle regional jet class transport aircraft being studied by NASA, which benefits from reduced fuel consumption through a reduction in the number of hydrocarbon fuel-burning engines from two to one. This is achieved through a hybrid-electric system architecture, where a series of generators are used to extract power from a fuel-consuming tail cone thruster to drive electric propulsors mounted on the wings. To support the development of these propulsion systems, which involve high levels of propulsion-airframe integration, this paper presents high-fidelity analyses through computational fluid dynamics (CFD) simulations provided by the Launch Ascent and Vehicle Aerodynamics (LAVA) framework, which also includes capabilities for modeling the effect of active propulsors. A trade space exploration is performed to investigate the advantages of several wing mounted distributed electric propulsion system configurations, including over-wing, under-wing, and trailing-edge arrangements. For the aft fuselage propulsor, focus is on the sizing of the inlet, core, and bypass ducts. High-fidelity aerodynamic shape optimization is also used to help minimize the inlet distortion intensity experienced by the aft propulsor fan through a reshaping of the fuselage.

CAS↗
NASA NTRS2003

Large-Eddy Simulation Code Developed for Propulsion Applications

A large-eddy simulation (LES) code was developed at the NASA Glenn Research Center to provide more accurate and detailed computational analyses of propulsion flow fields. The accuracy of current computational fluid dynamics (CFD) methods is limited primarily by their inability to properly account for the turbulent motion present in virtually all propulsion flows. Because the efficiency and performance of a propulsion system are highly dependent on the details of this turbulent motion, it is critical for CFD to accurately model it. The LES code promises to give new CFD simulations an advantage over older methods by directly computing the large turbulent eddies, to correctly predict their effect on a propulsion system. Turbulent motion is a random, unsteady process whose behavior is difficult to predict through computer simulations. Current methods are based on Reynolds-Averaged Navier- Stokes (RANS) analyses that rely on models to represent the effect of turbulence within a flow field. The quality of the results depends on the quality of the model and its applicability to the type of flow field being studied. LES promises to be more accurate because it drastically reduces the amount of modeling necessary. It is the logical step toward improving turbulent flow predictions. In LES, the large-scale dominant turbulent motion is computed directly, leaving only the less significant small turbulent scales to be modeled. As part of the prediction, the LES method generates detailed information on the turbulence itself, providing important information for other applications, such as aeroacoustics. The LES code developed at Glenn for propulsion flow fields is being used to both analyze propulsion system components and test improved LES algorithms (subgrid-scale models, filters, and numerical schemes). The code solves the compressible Favre-filtered Navier- Stokes equations using an explicit fourth-order accurate numerical scheme, it incorporates a compressible form of Smagorinsky s model for the subgrid-scale turbulence, and it uses generalized curvilinear coordinates to allow analysis of a wide range of geometries. The code runs in parallel on shared memory multiprocessor computers and is written in Fortran 90 with dynamic memory allocation. A sample result for a Mach-1.4 round jet is presented in the figure. Instantaneous Mach number contours in several cross-planes downstream of the nozzle exit are shown, illustrating how an LES captures the large unsteady three-dimensional turbulent structures present in the jet.

DeBonis, James R.↗
DOE OSTI2025

A dynamic 2D Borehole Thermal Energy Storage (BTES) model for enhanced computational efficiency

Progressing toward a future increasingly reliant on renewable energy sources, the development of effective, durable energy storage solutions becomes essential to balance supply and demand fluctuations. Borehole Thermal Energy Storage (BTES) is a long-duration thermal energy storage technology that captures excess heat generated from renewable energy sources and stores it underground for later use, enabling the efficient utilization of sustainable energy. This approach is particularly valuable in district energy networks when integrated with Ground Source Heat Pumps (GSHP) to provide stable heating and cooling. However, traditional three-dimensional (3D) numerical models of BTES systems demand extensive computational resources, limiting their practicality for real-time and large-scale applications. This study introduces a novel two-dimensional (2D) modeling approach that reduces computational costs while maintaining high accuracy. By employing a radial ring-based discretization method, the model simulates heat injection, retention, and retrieval dynamics over seasonal cycles. A new thermal-mass weighted-average temperature parameter is introduced to evaluate the performance of BTES systems. Model validation against FEFLOW simulations demonstrates a 17-fold improvement in computational speed compared to traditional Computational Fluid Dynamics (CFD) models while achieving a mean absolute percentage error (MAPE) of 2 % during charging and 4 % during discharging. Additionally, a trade-off analysis between computational efficiency and accuracy is conducted, ensuring the model's applicability for real-world scenarios. The findings of this research contribute to the development of computationally efficient BTES models, facilitating better optimization, control, and integration into renewable energy systems. This work provides a foundation for further studies in techno-economic analysis, multi-year performance evaluation, and real-time operational strategies for BTES applications, supporting a more sustainable energy future.

2D modeling↗
NASA NTRS1981

The Control Point Library Building System

The Earth Resources Observation System (EROS) Data Center in Sioux Falls, South Dakota distributes precision corrected Landsat MSS and RBV data. These data are derived from master data tapes produced by the Master Data Processor (MDP), NASA's system for computing and applying corrections to the data. Included in the MDP is the Control Point Library Building System (CPLBS), an interactive, menu-driven system which permits a user to build and maintain libraries of control points. The control points are required to achieve the high geometric accuracy desired in the output MSS and RBV data. This paper describes the processing performed by CPLBS, the accuracy of the system, and the host computer and special image viewing equipment employed.

Niblack, W.↗
DOE OSTI2020

Compiler and Runtime Approaches to Enable Large-Scale Irregular Programs. Final report, July 2013 - July 2019

While regular algorithms, characterized by operations on dense matrices and arrays, have long been the mainstay of scientific, high-performance computing, irregular algorithms, which feature unpredictable accesses to pointer-based data structures, are becoming increasingly common in high performance computing, arising in graph analysis, data mining and visualization, among other domains. Unfortunately, the defining characteristics of irregular applications, their dynamic, unpredictable, data-dependent access patterns and data layouts, make achieving high performance on large scale systems difficult. Scaling applications to peta- and exa-scale requires carefully controlling communication and data movement and placement, an inherently difficult task when access patterns and data layouts are unpredictable! Most irregular applications that attain high performance must be painstakingly hand-written and hand-tuned, with few common principles or paradigms uniting various implementations and easing future development. Despite the increasing importance of irregular applications, there is little programmer knowledge, and even less compiler ability, devoted to optimizing them. This project aims to solve these problems. By allowing programmers to write irregular applications in high level forms, with at most a few annotations highlighting key structural properties, programmers can focus on developing their algorithms and methods. The compiler and run-time system can take on the tedious task of optimizing the application for execution at large scales, and can automatically provide efficient implementations. This will provide portability and ease maintenance for existing irregular applications, but, more importantly, open up whole new domains of computational science to large-scale, high-performance simulation codes.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Research and Development Annual Report, 1992

Issued as a companion to Johnson Space Center's Research and Technology Annual Report, which reports JSC accomplishments under NASA Research and Technology Operating Plan (RTOP) funding, this report describes 42 additional JSC projects that are funded through sources other than the RTOP. Emerging technologies in four major disciplines are summarized: space systems technology, medical and life sciences, mission operations, and computer systems. Although these projects focus on support of human spacecraft design, development, and safety, most have wide civil and commercial applications in areas such as advanced materials, superconductors, advanced semiconductors, digital imaging, high density data storage, high performance computers, optoelectronics, artificial intelligence, robotics and automation, sensors, biotechnology, medical devices and diagnosis, and human factors engineering.

Source record↗
NASA NTRS1994

The JSC Research and Development Annual Report 1993

Issued as a companion to Johnson Space Center's Research and Technology Annual Report, which reports JSC accomplishments under NASA Research and Technology Operating Plan (RTOP) funding, this report describes 47 additional projects that are funded through sources other than the RTOP. Emerging technologies in four major disciplines are summarized: space systems technology, medical and life sciences, mission operations, and computer systems. Although these projects focus on support of human spacecraft design, development, and safety, most have wide civil and commercial applications in areas such as advanced materials, superconductors, advanced semiconductors, digital imaging, high density data storage, high performance computers, optoelectronics, artificial intelligence, robotics and automation, sensors, biotechnology, medical devices and diagnosis, and human factors engineering.

Source record↗
DOE OSTI2022

Exploring the Use of Novel Spatial Accelerators in Scientific Applications

Driven by the need to find alternative accelerators which can viably replace GPUs in next-generation Supercomputing systems, this paper proposes a methodology to enable agile application/hardware co-design. The application-first methodology provides the ability to come up with design of accelerators while working with real-world workloads, available accelerators, and system software. The iterative design process targets a set of kernels in a workload for performance estimates that can prune the design space for later phases of detailed architectural evaluations. To this effect, in this paper, a novel data-parallel device model is introduced that simulates the latency of performance-sensitive operations in an accelerator including data transfers and kernel computation using multi-core CPUs. The use of off-the-shelf simulators, such as pre-RTL simulator Aladdin or multiple tools available for exploring the design of deep neural network accelerators (e.g., Timeloop) is demonstrated for evaluation of various accelerator designs using applications with realistic inputs. Examples of multiple device configurations that are instantiable in a system are explored to evaluate the performance benefit of deploying novel accelerators. The proposed device is integrated with a programming model and system software to potentially explore the impacts of high-level programming languages/compilers and low-level effects such as task scheduling on multiple accelerators. We analyze our methodology for a set of applications that represent high-performance computing (HPC) and graph analytics. The applications include a computational chemistry kernel realized using tensor contractions, triangle counting, GraphSAGE and Breadth-first Search. These applications include kernels such as dense matrix-dense matrix multiplication, sparse matrix-spare matrix multiplication, and sparse matrix-dense vector multiplication. Our results indicate potential performance benefits and insights for system design by including accelerators that realize these kernels along-side general purpose accelerators.

AI, codesign, Accelerated Computing, Modeling and ↗
NASA NTRS2005

Experimentation and Modeling of Jet A Thermal Stability in a Heated Tube

High performance aircraft typically use hydrocarbon fuel to regeneratively cool the airframe and engine components. As the coolant temperatures increase, the fuel may react with dissolved oxygen forming deposits that limit the regenerative cooling system performance. This study investigates the deposition of Jet A using a thermal stability experiment and computational fluid dynamics (CFD) modeling. The experimental portion of this study is performed with a high Reynolds number thermal stability (HiRets) tester in which fuel passes though an electrically heated tube and the fuel outlet temperature is held constant. If the thermal stability temperature of the fuel is exceeded, deposits form and adhere to the inside of the tube creating an insulating layer between the tube and the fuel. The HiRets tester measures the tube outer wall temperatures near the fuel outlet to report the effect of deposition occurring inside the tube. Final deposits are also estimated with a carbon burn off analysis. The CFD model was developed and used to simulate the fluid dynamics, heat transfer, chemistry, and transport of the deposit precursors. The model is calibrated to the experiment temperature results and carbon burn-off deposition results. The model results show that the dominant factor in deposition is the heated wall temperature and that most of the deposits are formed in the laminar sublayer. The models predicted a 7.0E-6 kilograms per square meter-sec deposition rate, which compared well to the carbon burn-off analysis deposition rate of 1.0E-6 kilograms per square meter-sec.

Khodabandeh, Julia W.↗