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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

UNIX-based operating systems robustness evaluation

Robust operating systems are required for reliable computing. Techniques for robustness evaluation of operating systems not only enhance the understanding of the reliability of computer systems, but also provide valuable feed- back to system designers. This thesis presents results from robustness evaluation experiments on five UNIX-based operating systems, which include Digital Equipment's OSF/l, Hewlett Packard's HP-UX, Sun Microsystems' Solaris and SunOS, and Silicon Graphics' IRIX. Three sets of experiments were performed. The methodology for evaluation tested (1) the exception handling mechanism, (2) system resource management, and (3) system capacity under high workload stress. An exception generator was used to evaluate the exception handling mechanism of the operating systems. Results included exit status of the exception generator and the system state. Resource management techniques used by individual operating systems were tested using programs designed to usurp system resources such as physical memory and process slots. Finally, the workload stress testing evaluated the effect of the workload on system performance by running a synthetic workload and recording the response time of local and remote user requests. Moderate to severe performance degradations were observed on the systems under stress.

Chang, Yu-Ming↗
DOE OSTI2025

A Practical Comparison of Data-Driven Prognostics Methods for Energy Systems

This study explores data-driven prognostics for nuclear power plant (NPP) condensers, focusing on tube fouling. We utilized the Asherah nuclear power plant simulator (ANS) to compare four methods: Random Forest (RF), Support Vector Regressor (SVR), Fully Connected Neural Network (FCNN), and Long Short-Term Memory Neural Network (LSTM). By simulating various fouling scenarios in the ANS, we generated data with different degradation rates under transient operations. The models were trained and tested on these data, with performance evaluated visually and numerically including uncertainty assessment. The LSTM model excelled, exhibiting minimal prediction noise and the most accurate remaining useful life estimates across all degradation levels. Its ability to capture long-term dependencies and produce cleaner outputs makes it a strong candidate, although accurate training data across the entire component lifespan are crucial. The RF model emerged as a robust alternative, providing reliable predictions with high confidence. The FCNN and SVR models, while less effective overall, showed potential under specific conditions. FCNN offers a less complex alternative to LSTM and might benefit from larger datasets. SVR excels in precision when the quality of the training data is high. Furthermore, this study highlights the operational benefits of advanced prognostics in the energy sector and emphasizes the need for further research in NPP condenser health management through real-life experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2016

System Assessment of a High Power 3-U CubeSat

The Advanced eLectrical Bus (ALBus) CubeSat project is a technology demonstration mission of a 3-UCubeSat with an advanced, digitally controlled electrical power system capability and novel use of Shape Memory Alloy (SMA) technology for reliable deployable solar array mechanisms. The objective of the project is to, through an on orbit demonstration, advance the state of power management and distribution (PMAD) capabilities to enable future missions requiring higher power, flexible and reliable power systems. The goals of the mission include demonstration of: 100 Watt distribution to a target electrical load, efficient battery charging in the orbital environment, flexible power system distribution interfaces, adaptation of power system control on orbit, and reliable deployment of solar arrays and antennas utilizing re-settable SMA mechanisms. The power distribution function of the ALBus PMAD system is unique in the total power to target load capability of 100 W, the flexibility to support centralized or point-to-load regulation and ability to respond to fast transient power requirements. Power will be distributed from batteries at 14.8 V, 6.5 A to provide 100 W of power directly to a load. The deployable solar arrays utilize NASA Glenn Research Center superelastic and activated Nitinol(Nickel-Titanium alloy) Shape Memory Alloy (SMA) technology for hinges and a retention and release mechanism. The deployable solar array hinge design features utilization of the SMA material properties for dual purpose. The hinge uses the shape memory properties of the SMA to provide the spring force to deploy the arrays. The electrical conductivity properties of the SMA also enables the design to provide clean conduits for power transfer from the deployable arrays to the power management system. This eliminates the need for electrical harnesses between the arrays and the PMAD system in the ALBus system design. The uniqueness of the SMA retention and release mechanism design is the ability to reset the mechanism, allowing functional tests of the mechanisms prior to flight with no degradation of performance. The project is currently in preparation at the NASA Glenn Research Center for a launch in late calendar year of 2017. The 100 Watt power distribution and dual purpose, re-settable SMA mechanisms introduced several system level challenges due to the physical constraints in volume, mass and surface area of 3-U CubeSats. Several trade studies and design cycles have been completed to develop a system which supports the project objectives. This paper is a report on the results of the system level trade studies and assessments. The results include assessment of options for thermal control of 100 Watts of power dissipation, data from system analyses and engineering development tests, limitations of the 3-U system and extensibility to larger scale CubeSat missions.

CubeSat↗
DOE OSTI2024

ZFP: A compressed array representation for numerical computations

HPC trends favor algorithms and implementations that reduce data motion relative to FLOPS. We investigate the use of lossy compressed data arrays in place of traditional IEEE floating point arrays to store the primary data of calculations. Simulation is fundamentally an exercise in controlled approximation, and error introduced by finite-precision arithmetic (or lossy compression) is just one of several sources of error that need to be managed to ensure sufficient accuracy in a computed result. We describe ZFP, a compressed numerical format designed for in-memory storage of multidimensional arrays, and summarize theoretical results that demonstrate that the error of repeated lossy compression can be bounded and controlled. Furthermore, we establish a relationship between grid resolution and compression-induced errors and show that, contrary to conventional floating point, ZFP reduces finite-difference errors with finer grids. We present example calculations that demonstrate data reduction by 4x or more with negligible impact on solution accuracy. Our results further demonstrate several orders-of-magnitude increase in accuracy using ZFP over IEEE floating point and Posits for the same storage budget.

Lindstrom, Peter↗
DOE OSTI2022

Application of Dimensionality Reduction in Machine Learning Modeling of CO2 Storage

In this study, we developed deep learning models that are capable of predicting spatio-temporal outputs of CO2 saturation, pressure, and brine production in a 3D saline storage reservoir over 30 years of continuous CO2 injection and a 50-year post-injection timeframe. To improve computational efficiency and maintain performance accuracy, the model framework involves ensembling multi-layer autoencoder networks that provide dimensionality reduction of geologic inputs with fully connected long short-term memory (LSTM) neural networks that generate time-series prediction. This study was presented as poster at the 2022 Carbon Management Project Review Meeting held in Pittsburgh, PA (August 15 – 19, 2022).

Bello, Kolawole↗
NASA NTRS1992

Automated support for experience-based software management

To effectively manage a software development project, the software manager must have access to key information concerning a project's status. This information includes not only data relating to the project of interest, but also, the experience of past development efforts within the environment. This paper describes the concepts and functionality of a software management tool designed to provide this information. This tool, called the Software Management Environment (SME), enables the software manager to compare an ongoing development effort with previous efforts and with models of the 'typical' project within the environment, to predict future project status, to analyze a project's strengths and weaknesses, and to assess the project's quality. In order to provide these functions the tool utilizes a vast corporate memory that includes a data base of software metrics, a set of models and relationships that describe the software development environment, and a set of rules that capture other knowledge and experience of software managers within the environment. Integrating these major concepts into one software management tool, the SME is a model of the type of management tool needed for all software development organizations.

Valett, Jon D.↗
DOE OSTI2023

Los Alamos National Laboratory Internal Audit Strategic Plan

Los Alamos National Laboratory (LANL or the Laboratory) is managed under a management and operations (M&O) contract by Triad National Security, LLC (Triad), a nonprofit, public-focused consortium that includes Battelle Memorial Institute, the Texas A&M University System, and the University of California. The Internal Audit Group (IA) at LANL creates a formal strategic plan every five years in order to establish longer-range goals and initiatives to ensure the group fulfills its purpose as established in the Audit Charter, conforms with relevant standards, and is focused on continuous improvement. This document establishes the five-year strategic plan for fiscal year’s (FY) 2024 - 2028.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

LLM Generation of Online Courses from a Curated Set of Documents in the Nuclear Safeguards Domain

A multidisciplinary team at Argonne National Laboratory explores the application of advanced technologies to enhance knowledge transfer and retention within the nuclear safeguards domain. Specifically, it examines the feasibility of leveraging secure large language models (LLMs) to streamline the creation of e-learning modules for the U.S. National Nuclear Security Administration (NNSA) Office of International Nuclear Safeguards (NA-241). The initiative addresses the critical need for preserving institutional memory and accelerating skill development amidst the imminent retirement of senior professionals in the field in addition to supporting good knowledge management practices. The project integrates instructional design theory with cutting-edge AI technologies to transform curated document sets from the Safeguards Knowledge Repository (SKR) into modular online courses. By automating the generation of learning objectives and instructional content, the effort aims to reduce manual effort while maintaining high-quality educational outcomes. A limited measure of human supervision, however, ensures accuracy, relevance, and alignment with NNSA’s strategic priorities. Key findings highlight the potential of AI-assisted course generation to support safeguards professionals by creating structured, interactive learning experiences. The report underscores the importance of SME validation to address limitations in AI-generated content, such as terminology errors and gaps in coverage. Recommendations include adopting a structured workflow combining LLM acceleration with expert oversight to ensure accuracy, usability, and alignment with learner needs. This work demonstrates Argonne’s commitment to advancing national security and scientific excellence through innovative knowledge management solutions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1975

Man-rated flight software for the F-8 DFBW program

The design, implementation, and verification of the flight control software used in the F-8 DFBW program are discussed. Since the DFBW utilizes an Apollo computer and hardware, the procedures, controls, and basic management techniques employed are based on those developed for the Apollo software system. Program Assembly Control, simulator configuration control, erasable-memory load generation, change procedures and anomaly reporting are discussed. The primary verification tools--the all-digital simulator, the hybrid simulator, and the Iron Bird simulator--are described, as well as the program test plans and their implementation on the various simulators. Failure-effects analysis and the creation of special failure-generating software for testing purposes are described. The quality of the end product is evidenced by the F-8 DFBW flight test program in which 42 flights, totaling 58 hours of flight time, were successfully made without any DFCS inflight software, or hardware, failures.

Bairnsfather, R. R.↗
NASA NTRS1976

Man-rated flight software for the F-8 DFBW program

The design, implementation, and verification of the flight control software used in the F-8 DFBW program are discussed. Since the DFBW utilizes an Apollo computer and hardware, the procedures, controls, and basic management techniques employed are based on those developed for the Apollo software system. Program assembly control, simulator configuration control, erasable-memory load generation, change procedures and anomaly reporting are discussed. The primary verification tools are described, as well as the program test plans and their implementation on the various simulators. Failure effects analysis and the creation of special failure generating software for testing purposes are described.

Bairnsfather, R. R.↗
NASA NTRS1993

NASA space and Earth science data on CD-ROM

The National Space Science Data Center (NSSDC) is very interested in facilitating the widest possible use of the scientific data acquired through NASA spaceflight missions. Therefore, NSSDC has participated with projects and data management elements throughout the NASA science environment in the creation, archiving, and dissemination of data using Compact Disk-Read Only Memory (CD-ROM). This CD-ROM technology has the potential to enable the dissemination of very large data volumes at very low prices to a great many researchers, students and their teachers, and others. This catalog identifies and describes the scientific CD-ROM's now available from NSSDC including the following data sets: Einstein Observatory CD-ROM, Galileo Cruise Imaging on CD-ROM, International Halley Watch, IRAS Sky Survey Atlas, Infrared Thermal Mapper (IRTM), Magellan (MIDR), Magellan (ARCDR's), Magellan (GxDR's), Mars Digital Image Map (MDIM), Outer Planets Fields & Particles Data, Pre-Magellan, Selected Astronomical Catalogs, TOMS Gridded Ozone Data, TOMS Ozone Image Data, TOMS Update, Viking Orbiter Images of Mars, and Voyager Image.

Towheed, Syed S.↗
NASA NTRS2009

Porting Gravitational Wave Signal Extraction to Parallel Virtual Machine (PVM)

Laser Interferometer Space Antenna (LISA) is a planned NASA-ESA mission to be launched around 2012. The Gravitational Wave detection is fundamentally the determination of frequency, source parameters, and waveform amplitude derived in a specific order from the interferometric time-series of the rotating LISA spacecrafts. The LISA Science Team has developed a Mock LISA Data Challenge intended to promote the testing of complicated nested search algorithms to detect the 100-1 millihertz frequency signals at amplitudes of 10E-21. However, it has become clear that, sequential search of the parameters is very time consuming and ultra-sensitive; hence, a new strategy has been developed. Parallelization of existing sequential search algorithms of Gravitational Wave signal identification consists of decomposing sequential search loops, beginning with outermost loops and working inward. In this process, the main challenge is to detect interdependencies among loops and partitioning the loops so as to preserve concurrency. Existing parallel programs are based upon either shared memory or distributed memory paradigms. In PVM, master and node programs are used to execute parallelization and process spawning. The PVM can handle process management and process addressing schemes using a virtual machine configuration. The task scheduling and the messaging and signaling can be implemented efficiently for the LISA Gravitational Wave search process using a master and 6 nodes. This approach is accomplished using a server that is available at NASA Ames Research Center, and has been dedicated to the LISA Data Challenge Competition. Historically, gravitational wave and source identification parameters have taken around 7 days in this dedicated single thread Linux based server. Using PVM approach, the parameter extraction problem can be reduced to within a day. The low frequency computation and a proxy signal-to-noise ratio are calculated in separate nodes that are controlled by the master using message and vector of data passing. The message passing among nodes follows a pattern of synchronous and asynchronous send-and-receive protocols. The communication model and the message buffers are allocated dynamically to address rapid search of gravitational wave source information in the Mock LISA data sets.

Thirumalainambi, Rajkumar↗
DOE OSTI2020

Ten-Year Review of US/German Collaboration in Salt Repository Research - 20069

A multinational collaboration on salt repository research, design and operation has enjoyed remarkable success since reinvigorating efforts in 2010. Nations now engaged in the shared salt repository research agenda include Germany, the United States, the United Kingdom, the Netherlands, and Poland. The scientific basis for safe and permanent disposal of nuclear waste in salt formations has been strengthened by annual workshops that recognize and address contemporary research, including breakout sessions to stimulate open discussion and focus planning for ongoing investigations. Collaboration not only identifies pertinent technical issues, but facilitates timely, expert, and cost-effective consideration. Contemporary workshops have been held annually since 2010 and are documented in yearly state-of-the-art Proceedings, which summarize content and conclusions. The Proceedings help preserve scientific understanding and provide timely source references. These workshops often produce valuable joint publications coordinated with the Nuclear Energy Agency and other suitable external forums for dissemination. Nuclear waste management programs face growing challenges, while permanent disposal in salt formations provides a robust, safe option for several nations. Workshop format and publications provide a cost-effective insurance against loss of scientific expertise and institutional memory. This paper summarizes ten US/German workshops since formal reinitiation, reexamines key technical issues, discusses the evolving research agenda, and highlights successes and challenges. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1998

The SGI/Cray T3E: Experiences and Insights

The NASA Goddard Space Flight Center is home to the fifth most powerful supercomputer in the world, a 1024 processor SGI/Cray T3E-600. The original 512 processor system was placed at Goddard in March, 1997 as part of a cooperative agreement between the High Performance Computing and Communications Program's Earth and Space Sciences Project (ESS) and SGI/Cray Research. The goal of this system is to facilitate achievement of the Project milestones of 10, 50 and 100 GFLOPS sustained performance on selected Earth and space science application codes. The additional 512 processors were purchased in March, 1998 by the NASA Earth Science Enterprise for the NASA Seasonal to Interannual Prediction Project (NSIPP). These two "halves" still operate as a single system, and must satisfy the unique requirements of both aforementioned groups, as well as guest researchers from the Earth, space, microgravity, manned space flight and aeronautics communities. Few large scalable parallel systems are configured for capability computing, so models are hard to find. This unique environment has created a challenging system administration task, and has yielded some insights into the supercomputing needs of the various NASA Enterprises, as well as insights into the strengths and weaknesses of the T3E architecture and software. The T3E is a distributed memory system in which the processing elements (PE's) are connected by a low latency, high bandwidth bidirectional 3-D torus. Due to the focus on high speed communication between PE's, the T3E requires PE's to be allocated contiguously per job. Further, jobs will only execute on the user specified number of PE's and PE timesharing is possible but impractical. With a highly varied job mix in both size and runtime of jobs, the resulting scenario is PE fragmentation and an inability to achieve near 100% utilization. SGI/Cray has provided several scheduling and configuration tools to minimize the impact of fragmentation. These tools include PScheD (the political scheduler), GRM (the global resource manager) and NQE (the Network Queuing Environment). Features and impact of these tools will be discussed, as will resulting performance and utilization data. As a distributed memory system, the T3E is designed to be programmed through explicit message passing. Consequently, certain assumptions related to code design are made by the operating system (UNICOS/mk) and its scheduling tools. With the exception of HPF, which does run on the T3E, however poorly, alternative programming styles have the potential to impact the T3E in unexpected and undesirable ways. Several examples will be presented (preceeded with the disclaimer, "Don't try this at home! Violators will be prosecuted!")

Bernard, Lisa Hamet↗
NASA NTRS2012

CoNNeCT Baseband Processor Module Boot Code SoftWare (BCSW)

This software provides essential startup and initialization routines for the CoNNeCT baseband processor module (BPM) hardware upon power-up. A command and data handling (C&DH) interface is provided via 1553 and diagnostic serial interfaces to invoke operational, reconfiguration, and test commands within the code. The BCSW has features unique to the hardware it is responsible for managing. In this case, the CoNNeCT BPM is configured with an updated CPU (Atmel AT697 SPARC processor) and a unique set of memory and I/O peripherals that require customized software to operate. These features include configuration of new AT697 registers, interfacing to a new HouseKeeper with a flash controller interface, a new dual Xilinx configuration/scrub interface, and an updated 1553 remote terminal (RT) core. The BCSW is intended to provide a "safe" mode for the BPM when initially powered on or when an unexpected trap occurs, causing the processor to reset. The BCSW allows the 1553 bus controller in the spacecraft or payload controller to operate the BPM over 1553 to upload code; upload Xilinx bit files; perform rudimentary tests; read, write, and copy the non-volatile flash memory; and configure the Xilinx interface. Commands also exist over 1553 to cause the CPU to jump or call a specified address to begin execution of user-supplied code. This may be in the form of a real-time operating system, test routine, or specific application code to run on the BPM.

Yamamoto, Clifford K.↗
NASA NTRSDate not supplied

Advanced eLectrical Bus (ALBus) CubeSat: From Build to Flight

The Advanced eLectrical Bus (ALBus) CubeSat project is a technology demonstration mission of a 3-U CubeSat with an advanced, digitally controlled electrical power system capability and novel use of Shape Memory Alloy (SMA) technology for reliable deployable solar array mechanisms. The objective of the project was to advance the state of power management and distribution (PMAD) capabilities to enable future missions requiring flexible and reliable power systems with higher output power capabilities. The goals of the mission were to demonstrate 100W distribution to a target electrical load, respond to continuous and fast transient power requirements, and show reliable deployment of solar arrays and antennas utilizing re-settable SMA mechanisms. The power distribution function of the ALBus PMAD system is unique in the total power to target load capability. Power is distributed from batteries to provide 100W of power directly to a resistive load. The deployable solar arrays utilize NASA Glenn Research Center’s Nickel-Titanium-Palladium-Platinum high-temperature SMAs for the retention and release mechanism, and a super-elastic binary NiTi alloy for the hinge component. The deployable solar array hinge design features the utilization of SMA material properties for a dual purpose. First, the hinge uses the super-elastic SMA properties to provide the spring force to deploy the arrays. Second, the electrical conductivity properties of the SMA enables the design to provide clean conduits for power transfer from the deployable arrays to the power management system. This eliminates the need for electrical harnesses between the arrays and the PMAD system in the ALBus system design. The uniqueness of the SMA retention and release mechanism design is the ability to reset the mechanism and reuse the same hardware. This allow functional tests of the mechanisms before flight with no degradation of performance and flying the hardware that is tested. The project launched as part of the CubeSat Launch Initiative Educational Launch of Nanosatellites (ELaNa) XIX mission on Rocket Lab’s Electron in December 2018. This paper summarizes the final launched design of ALBus and lessons learned from the technology and overall project from development through flight.

Deboshri Sadhukhan↗
NASA NTRS2009

Communication Optimizations for a Wireless Distributed Prognostic Framework

Distributed architecture for prognostics is an essential step in prognostic research in order to enable feasible real-time system health management. Communication overhead is an important design problem for such systems. In this paper we focus on communication issues faced in the distributed implementation of an important class of algorithms for prognostics - particle filters. In spite of being computation and memory intensive, particle filters lend well to distributed implementation except for one significant step - resampling. We propose new resampling scheme called parameterized resampling that attempts to reduce communication between collaborating nodes in a distributed wireless sensor network. Analysis and comparison with relevant resampling schemes is also presented. A battery health management system is used as a target application. A new resampling scheme for distributed implementation of particle filters has been discussed in this paper. Analysis and comparison of this new scheme with existing resampling schemes in the context for minimizing communication overhead have also been discussed. Our proposed new resampling scheme performs significantly better compared to other schemes by attempting to reduce both the communication message length as well as number total communication messages exchanged while not compromising prediction accuracy and precision. Future work will explore the effects of the new resampling scheme in the overall computational performance of the whole system as well as full implementation of the new schemes on the Sun SPOT devices. Exploring different network architectures for efficient communication is an importance future research direction as well.

Saha, Sankalita↗
DOE OSTI2024

Scalable Implicit Solvers with Dynamic Mesh Adaptation for a Relativistic Drift-Kinetic Fokker–Planck–Boltzmann Model

In this work we consider a relativistic drift-kinetic model for runaway electrons along with a Fokker–Planck operator for small-angle Coulomb collisions, a radiation damping operator, and a secondary knock-on (Boltzmann) collision source. Here, we develop a new scalable fully implicit solver utilizing finite volume and conservative finite difference schemes and dynamic mesh adaptivity. A new data management framework in the PETSc library based on the p4est library is developed to enable simulations with dynamic adaptive mesh refinement (AMR), distributed memory parallelization, and dynamic load balancing of computational work. This framework and the runaway electron solver building on the framework are able to dynamically capture both bulk Maxwellian at the low-energy region and a runaway tail at the high-energy region. To effectively capture features via the AMR algorithm, a new AMR indicator prediction strategy is proposed that is performed alongside the implicit time evolution of the solution. This strategy is complemented by the introduction of computationally cheap feature-based AMR indicators that are analyzed theoretically. Numerical results quantify the advantages of the prediction strategy in better capturing features compared with nonpredictive strategies; and we demonstrate trade-offs regarding computational costs. The robustness with respect to model parameters, algorithmic scalability, and parallel scalability are demonstrated through several benchmark problems including manufactured solutions and solutions of different physics models. We focus on demonstrating the advantages of using implicit time stepping and AMR for runaway electron simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗