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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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NASA NTRS1994

CESDIS

CESDIS, the Center of Excellence in Space Data and Information Sciences was developed jointly by NASA, Universities Space Research Association (USRA), and the University of Maryland in 1988 to focus on the design of advanced computing techniques and data systems to support NASA Earth and space science research programs. CESDIS is operated by USRA under contract to NASA. The Director, Associate Director, Staff Scientists, and administrative staff are located on-site at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The primary CESDIS mission is to increase the connection between computer science and engineering research programs at colleges and universities and NASA groups working with computer applications in Earth and space science. Research areas of primary interest at CESDIS include: 1) High performance computing, especially software design and performance evaluation for massively parallel machines; 2) Parallel input/output and data storage systems for high performance parallel computers; 3) Data base and intelligent data management systems for parallel computers; 4) Image processing; 5) Digital libraries; and 6) Data compression. CESDIS funds multiyear projects at U. S. universities and colleges. Proposals are accepted in response to calls for proposals and are selected on the basis of peer reviews. Funds are provided to support faculty and graduate students working at their home institutions. Project personnel visit Goddard during academic recess periods to attend workshops, present seminars, and collaborate with NASA scientists on research projects. Additionally, CESDIS takes on specific research tasks of shorter duration for computer science research requested by NASA Goddard scientists.

Source record↗
NASA NTRS1997

Rocket Engine Numerical Simulator (RENS)

Work is being done at three universities to help today's NASA engineers use the knowledge and experience of their Apolloera predecessors in designing liquid rocket engines. Ground-breaking work is being done in important subject areas to create a prototype of the most important functions for the Rocket Engine Numerical Simulator (RENS). The goal of RENS is to develop an interactive, realtime application that engineers can utilize for comprehensive preliminary propulsion system design functions. RENS will employ computer science and artificial intelligence research in knowledge acquisition, computer code parallelization and objectification, expert system architecture design, and object-oriented programming. In 1995, a 3year grant from the NASA Lewis Research Center was awarded to Dr. Douglas Moreman and Dr. John Dyer of Southern University at Baton Rouge, Louisiana, to begin acquiring knowledge in liquid rocket propulsion systems. Resources of the University of West Florida in Pensacola were enlisted to begin the process of enlisting knowledge from senior NASA engineers who are recognized experts in liquid rocket engine propulsion systems. Dr. John Coffey of the University of West Florida is utilizing his expertise in interviewing and concept mapping techniques to encode, classify, and integrate information obtained through personal interviews. The expertise extracted from the NASA engineers has been put into concept maps with supporting textual, audio, graphic, and video material. A fundamental concept map was delivered by the end of the first year of work and the development of maps containing increasing amounts of information is continuing. Find out more information about this work at the Southern University/University of West Florida. In 1996, the Southern University/University of West Florida team conducted a 4day group interview with a panel of five experts to discuss failures of the RL10 rocket engine in conjunction with the Centaur launch vehicle. The discussion was recorded on video and audio tape. Transcriptions of the entire proceedings and an abbreviated video presentation of the discussion highlights are under development. Also in 1996, two additional 3year grants were awarded to conduct parallel efforts that would complement the work being done by Southern University and the University of West Florida. Dr. Prem Bhalla of Jackson State University in Jackson, Mississippi, is developing the architectural framework for RENS. By employing the Rose Rational language and Booch Object Oriented Programming (OOP) technology, Dr. Bhalla is developing the basic structure of RENS by identifying and encoding propulsion system components, their individual characteristics, and cross-functionality and dependencies. Dr. Ruknet Cezzar of Hampton University, located in Hampton, Virginia, began working on the parallelization and objectification of rocket engine analysis and design codes. Dr. Cezzar will use the Turbo C++ OOP language to translate important liquid rocket engine computer codes from FORTRAN and permit their inclusion into the RENS framework being developed at Jackson State University. The Southern University/University of West Florida grant was extended by 1 year to coordinate the conclusion of all three efforts in 1999.

Davidian, Kenneth O.↗
NASA NTRSDate not supplied

The development and potential uses of an Adsorption Water Collection System for the Trash Compaction Processing System designed for operation in the International Space Station Express Rack

The use of adsorption as an alternative to current state of the art water collection and phase separation methods for human space flight is being investigated at NASA Ames Research Center. A system called the Adsorption Water Recovery System was designed to work with the Trash Compaction Processing System. The system uses modular adsorption columns that can be combined both in parallel and series and allow for relatively easy system sizing. The system is intended to be a standalone system that may also be adapted for other applications that involve adsorption. This paper describes the design and potential operating parameters and configurations of the Adsorption Water Recovery System.

trash↗
DOE OSTI2024

Streaming Matching and Edge Cover in Practice

Graph algorithms with polynomial space and time requirements often become infeasible for massive graphs with billions of edges or more. State-of-the-art approaches therefore employ approximate serial, parallel, and distributed algorithms to tackle these challenges. However, such approaches require storing the entire graph in memory and thus need access to costly computing resources such as clusters and supercomputers. In this paper, we present practical streaming approaches for solving massive graph problems using limited memory for two prototypical graph problems: maximum weighted matching and minimum weighted edge cover. For matching, we conduct a thorough computational study on two of the semi-streaming algorithms including a recent breakthrough result that achieves a $1/(2+\varepsilon)$-approximation of the weight while using $O( n \log W /\epsilon)$ memory (here $n$ is the number of vertices and $W$ is the maximum edge weight), designed by Paz and Schwartzman [SODA, 2017]. Empirically, we show that the semi-streaming algorithms produce matchings whose weight is close to the best $1/2$-approximate offline algorithm while requiring less time and an order-of-magnitude less memory. For minimum weighted edge cover, we develop three novel semi-streaming algorithms. Two of these algorithms require a single pass through the input graph, require $O(n \log n)$ memory, and provide a 2-approximation guarantee on the objective. We also leverage a relationship between approximate maximum weighted matching and approximate minimum weighted edge cover to develop a two-pass $3/2+\epsilon$-approximate algorithm with the memory requirement of Paz and Schwartzman's semi-streaming matching algorithm. These streaming approaches are compared against the state-of-the-art 3/2-approximate offline algorithm. The semi-streaming matching and the novel edge cover algorithms proposed in this paper can process graphs with several billions of edges in under 30 minutes using 6 GB of memory, which is at least an order of magnitude improvement from the offline (non-streaming) algorithms. For the largest graph, the best alternative offline parallel approximation algorithm (GPA+ROMA) could not finish in three hours even while employing hundreds of processors and 1 TB of memory. We also demonstrate an application of the semi-streaming algorithm by computing a matching using linearly bounded memory on item intersection graphs derived from three machine learning datasets, whereas the existing offline algorithms could not complete on one of these datasets since their memory requirements exceeded 1TB.

Ferdous, S M.↗
DOE OSTI2024

FENIX: Towards a Fully Integrated Multiphysics Framework for Plasma Facing Component Modeling

Computational tools have a crucial role to play in accelerating the deployment of fusion as a clean, reliable, abundant, and sustainable energy source. Multiphysics, high-fidelity simulation capabilities can help model, study, and predict intricate interactions between materials performance, plasma exposure, neutron irradiation, and engineering processes. As such, they can assist in the resolution of scientific and engineering challenges underpinning design, construction, and commission of fusion power plants. To address these needs, ongoing efforts are leveraging the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework and delivering new computational tools for the fusion community. These tools inherit crucial attributes from MOOSE. They are open-source, modular, integrated with nuclear industry-standard software quality assurance processes, and enable multiphysics, multi-fidelity, fully integrated, zero- to three-dimensional, and massively parallel simulations. After a short overview of these capabilities, we will present the development of Fusion ENergy Integrated multiphys-X (FENIX), a MOOSE-based application designed to enable plasma facing component design and performance evaluation. Throughout their lifetime, plasma facing components are exposed to extreme thermal loads, repeated thermal shocks, and irradiation by plasma ions, neutral particles, and high-energy neutrons. Consequently, designing a plasma facing component with acceptable lifetime degradation is extremely challenging. FENIX aims to model the multiphysics environment in which plasma facing components evolve to accelerate their design studies. To that end, FENIX couples existing MOOSE capabilities such as heat transfer, thermomechanics, and thermal hydraulics, with tritium transport via the MOOSE-based Tritium Migration Analysis Program, Version 8 (TMAP8), with neutronics via the MOOSE-based high-fidelity neutron-photon transport and fluid dynamics code Cardinal, and finally with Particle-in-Cell plasma simulation capabilities being developed in this project. In this study, we present the current FENIX capabilities and preliminary results of its application to model the Tritium Plasma Experiment set up at Idaho National Laboratory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2014

Dielectric Performance of a High Purity HTCC Alumina at High Temperatures - a Comparison Study with Other Polycrystalline Alumina

A very high purity (99.99+%) high temperature co-fired ceramic (HTCC) alumina has recently become commercially available. The raw material of this HTCC alumina is very different from conventional HTCC alumina, and more importantly there is no glass additive in this alumina material for co-firing processing. Previously, selected HTCC and LTCC (low temperature co-fired ceramic) alumina materials were evaluated at high temperatures as dielectric and compared to a regularly sintered 96% polycrystalline alumina (96% Al2O3), where 96% alumina was used as the benchmark. A prototype packaging system based on regular 96% alumina with Au thickfilm metallization successfully facilitated long term testing of high temperature silicon carbide (SiC) electronic devices for over 10,000 hours at 500 C. In order to evaluate this new high purity HTCC alumina for possible high temperature packaging applications, the dielectric properties of this HTCC alumina substrate were measured and compared with those of 96% alumina and a previously tested LTCC alumina from room temperature to 550 C at frequencies of 120 Hz, 1 KHz, 10 KHz, 100 KHz, and 1 MHz. A parallel-plate capacitive device with dielectric of the HTCC alumina and precious metal electrodes were used for measurements of the dielectric constant and dielectric loss of the co-fired alumina material in the temperature and frequency ranges. The capacitance and AC parallel conductance of the capacitive device were directly measured by an AC impedance meter, and the dielectric constant and parallel AC conductivity of the dielectric were calculated from the capacitance and conductance measurement results. The temperature and frequency dependent dielectric constant, AC conductivity, and dissipation factor of the HTCC alumina substrate are presented and compared to those of 96% alumina and a selected LTCC alumina. Other technical advantages of this new co-fired material for possible high packaging applications are also discussed.

Electronic packaging↗
DOE OSTI2022

Profiling the BLAST bioinformatics application for load balancing on high-performance computing clusters

Abstract Background The Basic Local Alignment Search Tool (BLAST) is a suite of commonly used algorithms for identifying matches between biological sequences. The user supplies a database file and query file of sequences for BLAST to find identical sequences between the two. The typical millions of database and query sequences make BLAST computationally challenging but also well suited for parallelization on high-performance computing clusters. The efficacy of parallelization depends on the data partitioning, where the optimal data partitioning relies on an accurate performance model. In previous studies, a BLAST job was sped up by 27 times by partitioning the database and query among thousands of processor nodes. However, the optimality of the partitioning method was not studied. Unlike BLAST performance models proposed in the literature that usually have problem size and hardware configuration as the only variables, the execution time of a BLAST job is a function of database size, query size, and hardware capability. In this work, the nucleotide BLAST application BLASTN was profiled using three methods: shell-level profiling with the Unix “time” command, code-level profiling with the built-in “profiler” module, and system-level profiling with the Unix “gprof” program. The runtimes were measured for six node types, using six different database files and 15 query files, on a heterogeneous HPC cluster with 500+ nodes. The empirical measurement data were fitted with quadratic functions to develop performance models that were used to guide the data parallelization for BLASTN jobs. Results Profiling results showed that BLASTN contains more than 34,500 different functions, but a single function, RunMTBySplitDB, takes 99.12% of the total runtime. Among its 53 child functions, five core functions were identified to make up 92.12% of the overall BLASTN runtime. Based on the performance models, static load balancing algorithms can be applied to the BLASTN input data to minimize the runtime of the longest job on an HPC cluster. Four test cases being run on homogeneous and heterogeneous clusters were tested. Experiment results showed that the runtime can be reduced by 81% on a homogeneous cluster and by 20% on a heterogeneous cluster by re-distributing the workload. Discussion Optimal data partitioning can improve BLASTN’s overall runtime 5.4-fold in comparison with dividing the database and query into the same number of fragments. The proposed methodology can be used in the other applications in the BLAST+ suite or any other application as long as source code is available.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Inverse chirality-induced spin selectivity effect in chiral assemblies of π -conjugated polymers

Coupling of spin and charge currents to structural chirality in non-magnetic materials, known as chirality-induced spin selectivity, is promising for application in spintronic devices at room temperature. Although the chirality-induced spin selectivity effect has been identified in various chiral materials, its Onsager reciprocal process, the inverse chirality-induced spin selectivity effect, remains unexplored. Here we report the observation of the inverse chirality-induced spin selectivity effect in chiral assemblies of π-conjugated polymers. Using spin-pumping techniques, the inverse chirality-induced spin selectivity effect enables quantification of the magnitude of the longitudinal spin-to-charge conversion driven by chirality-induced spin selectivity in different chiral polymers. By widely tuning conductivities and supramolecular chiral structures via a printing method, we found a very long spin relaxation time of up to several nanoseconds parallel to the chiral axis. Furthermore, our demonstration of the inverse chirality-induced spin selectivity effect suggests possibilities for elucidating the puzzling interplay between spin and chirality, and opens a route for spintronic applications using printable chiral assemblies.

36 MATERIALS SCIENCE↗
NASA NTRS1980

Application of a microprocessor to a spacecraft attitude control

The attitude control system (ACS) microprocessor development work spanned three main design areas: hardware and instruction set, ACS firmware, and hardware firmware verification testing. The processor hardware utilizes two parallel 4 bit microprocessors. The firmware includes data processing for five sensors, four attitude control laws, and telemetry and commands.

Brady, D. H.↗
NASA NTRS2002

Scaling NASA Applications to 1024 CPUs on Origin 3K

The long and highly successful joint SGI-NASA research effort in ever larger SSI systems was to a large degree the result of the successful development of the MLP scalable parallel programming paradigm developed at ARC: 1) MLP scaling in real production codes justified ever larger systems at NAS; 2) MLP scaling on 256p Origin 2000 gave SGl impetus to productize 256p; 3) MLP scaling on 512 gave SGI courage to build 1024p O3K; and 4) History of MLP success resulted in IBM Star Cluster based MLP effort.

Taft, Jim↗
NASA NTRS1997

VIGILANTE: An Advanced Sensing/Processing Testbed for ATR Applications

VIGILANTE consists of two major components:1. the Viewing Imager/Gimballed Instrumentation Laboratory (VIGIL)- advanced infrared, visible, and ultraviolet sensors with appropriate optics and camera electronics & 2. the Analog Neural Three-dimensional processing Experiment (ANTE)-a massively parallel, neural network-based, high-speed processor.

automatic↗
DOE OSTI2024

Scaling neural simulations in STACS

Abstract As modern neuroscience tools acquire more details about the brain, the need to move towards biological-scale neural simulations continues to grow. However, effective simulations at scale remain a challenge. Beyond just the tooling required to enable parallel execution, there is also the unique structure of the synaptic interconnectivity, which is globally sparse but has relatively high connection density and non-local interactions per neuron. There are also various practicalities to consider in high performance computing applications, such as the need for serializing neural networks to support potentially long-running simulations that require checkpoint-restart. Although acceleration on neuromorphic hardware is also a possibility, development in this space can be difficult as hardware support tends to vary between platforms and software support for larger scale models also tends to be limited. In this paper, we focus our attention on Simulation Tool for Asynchronous Cortical Streams (STACS), a spiking neural network simulator that leverages the Charm++ parallel programming framework, with the goal of supporting biological-scale simulations as well as interoperability between platforms. Central to these goals is the implementation of scalable data structures suitable for efficiently distributing a network across parallel partitions. Here, we discuss a straightforward extension of a parallel data format with a history of use in graph partitioners, which also serves as a portable intermediate representation for different neuromorphic backends. We perform scaling studies on the Summit supercomputer, examining the capabilities of STACS in terms of network build and storage, partitioning, and execution. We highlight how a suitably partitioned, spatially dependent synaptic structure introduces a communication workload well-suited to the multicast communication supported by Charm++. We evaluate the strong and weak scaling behavior for networks on the order of millions of neurons and billions of synapses, and show that STACS achieves competitive levels of parallel efficiency.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2004

Parallel 3D Mortar Element Method for Adaptive Nonconforming Meshes

High order methods are frequently used in computational simulation for their high accuracy. An efficient way to avoid unnecessary computation in smooth regions of the solution is to use adaptive meshes which employ fine grids only in areas where they are needed. Nonconforming spectral elements allow the grid to be flexibly adjusted to satisfy the computational accuracy requirements. The method is suitable for computational simulations of unsteady problems with very disparate length scales or unsteady moving features, such as heat transfer, fluid dynamics or flame combustion. In this work, we select the Mark Element Method (MEM) to handle the non-conforming interfaces between elements. A new technique is introduced to efficiently implement MEM in 3-D nonconforming meshes. By introducing an "intermediate mortar", the proposed method decomposes the projection between 3-D elements and mortars into two steps. In each step, projection matrices derived in 2-D are used. The two-step method avoids explicitly forming/deriving large projection matrices for 3-D meshes, and also helps to simplify the implementation. This new technique can be used for both h- and p-type adaptation. This method is applied to an unsteady 3-D moving heat source problem. With our new MEM implementation, mesh adaptation is able to efficiently refine the grid near the heat source and coarsen the grid once the heat source passes. The savings in computational work resulting from the dynamic mesh adaptation is demonstrated by the reduction of the the number of elements used and CPU time spent. MEM and mesh adaptation, respectively, bring irregularity and dynamics to the computer memory access pattern. Hence, they provide a good way to gauge the performance of computer systems when running scientific applications whose memory access patterns are irregular and unpredictable. We select a 3-D moving heat source problem as the Unstructured Adaptive (UA) grid benchmark, a new component of the NAS Parallel Benchmarks (NPB). In this paper, we present some interesting performance results of ow OpenMP parallel implementation on different architectures such as the SGI Origin2000, SGI Altix, and Cray MTA-2.

Feng, Huiyu↗
DOE OSTI2021

A Transient-Response methodology based on experiments and modeling for Cu-Redox Half-Cycle kinetic analysis on a Cu-SSZ-13 SCR catalyst

In this report the Standard SCR reaction catalyzed by Cu-SSZ-13 is a redox process consisting of a reduction half cycle (RHC) and an oxidation half cycle (OHC) that cycle the active Cu sites between the Cu(II) and Cu(I) states. In the current work, a transient-response methodology consisting of experimental transient response Cu-redox (TRCR) measurements and kinetic modeling was developed for detailed study of individual SCR Cu-redox half cycles. The TRCR protocol allows quantification of the reducible Cu density, Cu(II)-Cu(I) partitioning, relative native RHC and OHC rates, and limiting half cycle during SCR. The half-cycle kinetics are studied over a wide (170–450 °C) temperature, and in differential segments along the catalyst length using spatially resolved capillary inlet mass-spectrometry (SpaciMS). The protocol alone provides two independent measures indicating that OHC increases faster than RHC with temperature, and that at all but the lowest temperature SCR is RHC limited. Introducing the transient kinetic models allows half-cycle reaction pathways, orders and activation energies to be studied and determined; e.g., RHC involves surface and gas-phase NH 3 routes, and OHC with O 2 involves dimer formation. Application of the full methodology provides further confirmation and quantification of the protocol conclusions, and specifically the first measurements of RHC and OHC activation energies; specifically for parallel RHC surface and gas-phase routes, and experimentally obtained OHC activation energy vs. first-principle calculations in the literature. Beyond insights related to the degreened catalyst studied here, the methodology provides a broadly available approach for quantifying how aging processes selectively impact RHC and OHC.

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

Design optimization of semiconductor piezoresistors with Schottky diode contacts

A modeling theory is developed to predict the performance of piezoresistors which incorporate Schottky diode electrical contacts. This new theory allows the design of high performance gauges which can be fabricated using NonLithographically-Based Microfabrication (NLBM) techniques. These semiconductor piezoresistors can be designed in customizable sizes and fabricated in parallel in order to integrate position sensing into MEMS flexural positioners. Customizable nanopositioning platforms will enable advances in a range of nano-scale fabrication and metrology applications. A semiconductor piezoresistor with Schottky diode contacts was fabricated and attached to a titanium flexure. This device is shown to match predicted electrical performance within about 8% and to show a gauge factor of 116, within 2% of the predicted value. Performance limits for Schottky diode semiconductor piezoresistors are identified to be about 127dB full noise dynamic range for a quarter bridge over a 10kHz sensor bandwidth on a 600µm width titanium flexure, making them ideal for sensing on meso-/micro-scale flexural positioners. Methods of reaching these performance bound are suggested and their impact on the sensor dynamic range are studied.

42 ENGINEERING↗
DOE OSTI2025

Random Phase Approximation Correlation Energy Using Real-Space Density Functional Perturbation Theory

We present a real-space method for computing the random phase approximation (RPA) correlation energy within Kohn–Sham density functional theory, leveraging the low-rank nature of the frequency-dependent density response operator. In particular, we employ a cubic-scaling formalism based on density functional perturbation theory that circumvents the calculation of the response function matrix, instead relying on the ability to compute its product with a vector through the solution of the associated Sternheimer linear systems. We develop a large-scale parallel implementation of this formalism using the subspace iteration method in conjunction with the spectral quadrature method while employing the Kronecker product-based method for the application of the Coulomb operator and the conjugate orthogonal conjugate gradient method for the solution of the linear systems. We demonstrate convergence with respect to key parameters and verify the method’s accuracy by comparing with plane-wave results. We show that the framework achieves good strong scaling to many thousands of processors, reducing the time to solution for a lithium hydride system with 128 electrons to around 150 s on 4608 processors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Broadband unidirectional visible imaging using wafer-scale nano-fabrication of multi-layer diffractive optical processors

We present a broadband and polarization-insensitive unidirectional imager that operates at the visible part of the spectrum, where image formation occurs in one direction, while in the opposite direction, it is blocked. This approach is enabled by deep learning-driven diffractive optical design with wafer-scale nano-fabrication using high-purity fused silica to ensure optical transparency and thermal stability. Our design achieves unidirectional imaging across three visible wavelengths (covering red, green, and blue parts of the spectrum), and we experimentally validated this broadband unidirectional imager by creating high-fidelity images in the forward direction and generating weak, distorted output patterns in the backward direction, in alignment with our numerical simulations. This work demonstrates wafer-scale production of diffractive optical processors, featuring 16 levels of nanoscale phase features distributed across two axially aligned diffractive layers for visible unidirectional imaging. This approach facilitates mass-scale production of ~0.5 billion nanoscale phase features per wafer, supporting high-throughput manufacturing of hundreds to thousands of multi-layer diffractive processors suitable for large apertures and parallel processing of multiple tasks. Beyond broadband unidirectional imaging in the visible spectrum, this study establishes a pathway for artificial-intelligence-enabled diffractive optics with versatile applications, signaling a new era in optical device functionality with industrial-level, massively scalable fabrication.

36 MATERIALS SCIENCE↗