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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 NTRS2002

Development and Flight Testing of an Adaptive Vehicle Health-Monitoring Architecture

On going development and testing of an adaptable vehicle health-monitoring architecture is presented. The architecture is being developed for a fleet of vehicles. It has three operational levels: one or more remote data acquisition units located throughout the vehicle; a command and control unit located within the vehicle, and, a terminal collection unit to collect analysis results from all vehicles. Each level is capable of performing autonomous analysis with a trained expert system. The expert system is parameterized, which makes it adaptable to be trained to both a user's subject reasoning and existing quantitative analytic tools. Communication between all levels is done with wireless radio frequency interfaces. The remote data acquisition unit has an eight channel programmable digital interface that allows the user discretion for choosing type of sensors; number of sensors, sensor sampling rate and sampling duration for each sensor. The architecture provides framework for a tributary analysis. All measurements at the lowest operational level are reduced to provide analysis results necessary to gauge changes from established baselines. These are then collected at the next level to identify any global trends or common features from the prior level. This process is repeated until the results are reduced at the highest operational level. In the framework, only analysis results are forwarded to the next level to reduce telemetry congestion. The system's remote data acquisition hardware and non-analysis software have been flight tested on the NASA Langley B757's main landing gear. The flight tests were performed to validate the following: the wireless radio frequency communication capabilities of the system, the hardware design, command and control; software operation and, data acquisition, storage and retrieval.

Woodard, Stanley E.↗
NASA NTRS2003

Development and Flight Testing of an Autonomous Landing Gear Health-Monitoring System

Development and testing of an adaptable vehicle health-monitoring architecture is presented. The architecture is being developed for a fleet of vehicles. It has three operational levels: one or more remote data acquisition units located throughout the vehicle; a command and control unit located within the vehicle; and, a terminal collection unit to collect analysis results from all vehicles. Each level is capable of performing autonomous analysis with a trained expert system. Communication between all levels is done with wireless radio frequency interfaces. The remote data acquisition unit has an eight channel programmable digital interface that allows the user discretion for choosing type of sensors; number of sensors, sensor sampling rate and sampling duration for each sensor. The architecture provides framework for a tributary analysis. All measurements at the lowest operational level are reduced to provide analysis results necessary to gauge changes from established baselines. These are then collected at the next level to identify any global trends or common features from the prior level. This process is repeated until the results are reduced at the highest operational level. In the framework, only analysis results are forwarded to the next level to reduce telemetry congestion. The system's remote data acquisition hardware and non-analysis software have been flight tested on the NASA Langley B757's main landing gear. The flight tests were performed to validate the following: the wireless radio frequency communication capabilities of the system, the hardware design, command and control; software operation; and, data acquisition, storage and retrieval.

Woodard, Stanley E.↗
DOE OSTI2026

ReMU: regional minimal updating for model-based derivative-free optimization

Derivative-free optimization (DFO) problems are optimization problems where derivative information is unavailable or extremely difficult to obtain. Model-based DFO solvers have been applied extensively in scientific computing. Powell's NEWUOA (2004) [Powell, The NEWUOA software for unconstrained optimization without derivatives, in Large-Scale Nonlinear Optimization, Nonconvex Optimization and its Applications Vol. 83, G. Di Pillo and M. Roma, eds., Springer, 2006, pp. 255–297] and Wild's POUNDerS (2014) [Wild, Solving derivative-free nonlinear least squares problems with POUNDERS, in Advances and Trends in Optimization with Engineering Applications, T. Terlaky, M.F. Anjos, and S. Ahmed, eds., SIAM, 2017, pp. 529–540] explore the numerical power of the minimal norm Hessian (MNH) model for DFO and contributed to the open discussion on building better models with fewer data to achieve faster numerical convergence. Another decade later, we propose the regional minimal updating (ReMU) models, and extend the previous models into a broader class, including the H 2 norm models [Xie and Yuan, Least H 2 norm updating of quadratic interpolation models for derivative-free trust-region algorithms, IMA J. Numer. Anal. 46 (2025), pp. 21–50]. This paper shows motivation behind ReMU models, computational details, theoretical and numerical results on particular extreme points and the barycentre of ReMU's weight coefficient region, and the associated KKT matrix error and distance. Novel metrics, such as the truncated Newton step error, are proposed to numerically understand the new models' properties. A new algorithmic strategy, based on iteratively adjusting the ReMU model type, is also proposed, and shows numerical advantages by combining and switching between the barycentric model and the classic least Frobenius norm model in an online fashion.

derivative-free trust-region methods↗
NASA NTRS1994

An agent-oriented approach to automated mission operations

As we plan for the next generation of Mission Operations Control Center (MOCC) systems, there are many opportunities for the increased utilization of innovative knowledge-based technologies. The innovative technology discussed is an advanced use of agent-oriented approaches to the automation of mission operations. The paper presents an overview of this technology and discusses applied operational scenarios currently being investigated and prototyped. A major focus of the current work is the development of a simple user mechanism that would empower operations staff members to create, in real time, software agents to assist them in common, labor intensive operations tasks. These operational tasks would include: handling routine data and information management functions; amplifying the capabilities of a spacecraft analyst/operator to rapidly identify, analyze, and correct spacecraft anomalies by correlating complex data/information sets and filtering error messages; improving routine monitoring and trend analysis by detecting common failure signatures; and serving as a sentinel for spacecraft changes during critical maneuvers enhancing the system's capabilities to support nonroutine operational conditions with minimum additional staff. An agent-based testbed is under development. This testbed will allow us to: (1) more clearly understand the intricacies of applying agent-based technology in support of the advanced automation of mission operations and (2) access the full set of benefits that can be realized by the proper application of agent-oriented technology in a mission operations environment. The testbed under development addresses some of the data management and report generation functions for the Explorer Platform (EP)/Extreme UltraViolet Explorer (EUVE) Flight Operations Team (FOT). We present an overview of agent-oriented technology and a detailed report on the operation's concept for the testbed.

Truszkowski, Walt↗
DOE OSTI2026

Sintering effects on NpO 2 grain size and morphology: The role of precursor Np phase

Neptunium dioxide (NpO 2 ) is a key phase in nuclear material processing as a target material for the production of plutonium-238 ( 238 Pu) and has been historically synthesized via the calcination of a Np oxalate precursor. Alternative synthesis methods for NpO 2 are now more prevalent, necessitating their study and comparison with the more common oxalate route. The purpose of this work was to investigate the microstructural properties of NpO 2 synthesized from a nitrate-based Np precursor phase via the assessment of NpO 2 particle size and morphology as a function of calcination temperature and time. Scanning electron microscopy (SEM) was used to probe the primary grain size and morphology of NpO 2 after calcination at temperatures ranging from 700 to 1100 °C and hold times ranging from 1 to 10 h. Post-image analysis using ImageJ software enabled the quantification of mean particle diameter. This analysis indicated that particle diameter increases with both increasing calcination temperature and hold time. Primary particles were shown to be clumped in irregular patterns into the overall rough, blocky aggregates, but this macroscopic morphology was not affected by calcination time or temperature. Although trends in primary grain size of NpO 2 were consistent with available literature from other Np precursor phases, the macroscopic morphology of the NpO 2 aggregates was quite different than reported for other precursors. Through comparison with historical literature on Np oxalate, this work emphasizes the importance of Np precursor on the physical properties of NpO 2 .

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

Status Report on IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENviroment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report provides discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity is maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In addition to the investigative work being conducted on FMUs and FMIs, a series of updates to the hybrid repository has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and opensourcing the HYBRID repository with an integrated regression system.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1989

Highly automated optical characterization with FTIR spectrometry

The procedure for evaluating the characteristics of II-VI semiconducting infrared sensor materials with a Fourier Transform Infrared (FTIR) spectrometer system will be discussed. While the method of mapping optical characteristics with a spectrometer has been employed previously, this system is highly automated compared to other systems where the optical transmission data are obtained using a FTIR system with a small stationary aperture in the optical path and moving the specimen behind the aperture. The hardware and software, including an algorithm developed for extracting cut-on wavelengths of spectra, as well as several example results, are described to illustrate the advanced level of the system. Additionally, data from transverse slices and longitudinal wafers of the aforementioned semiconductors will be used to show the accuracy of the system in predicting trends in materials such as shapes of growth interfaces and compositional uniformity.

Perry, G. L. E.↗
DOE OSTI2021

Multi-Scenario Extreme Weather Simulator

The Multi-scenario Extreme Weather Simulator (MEWS) takes existing historical weather data and inserts trends and extreme events such as heat waves, hurricanes, extreme precipitation, or winter storms. The code includes functionality for projecting increasing frequency and duration of such events over a large range of statistically sampled realizations of the future. These weather files can then be used in building energy simulations through the Energy Plus software created by DOE. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-8658 O

Villa, Daniel↗
DOE OSTI2021

Wind Energy Forecasting with the Weather Research and Forecasting Model

This was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Siemens Energy, Inc. (Siemens) to develop a wind resource forecasting tool. LLNL was to develop an independent high-resolution mesoscale modeling capability forecasting tool that could be implemented in conjunction with existing wind farm control and monitoring software to provide forecasting of wind resources using local observations of winds and temperature. Research with LLNL’s state-of-the-art large-eddy simulation meteorological prediction model, based on the community WRF model and innovative turbulence parameterizations, would improve that model’s applicability to large wind farms offshore and in complex terrain. The modeling capability would include uncertainty quantification. Finally, the application of the modeling tool and existing global climate change predictions would enable the delineation of the likely effects of climate change on wind resources. Siemens was to provide high time resolution hub-height wind speed and other meteorological data streams, including temperature profiles from wind farms, for LLNL to incorporate into the modeling system, to validate and tune this forecasting model for their locations of interest. These data streams would also be used for longer-term studies of correlations of wind resources to climate oscillations to indicate how long-term climate change trends may affect the available wind resource. Siemens would also provide information and observations of turbine wakes for incorporation into the modeling tool. By implementing state-of-the-art turbulence parameterizations into a simulation model and/or ensembles of simulation models, and by integrating real-time hub height wind speed and other meteorological datastreams from wind farms into that model or ensemble of models, LLNL would develop a forecasting tool that could be implemented by Siemens as an add-on to existing wind farm control and monitoring software to provide owners with useful resource forecasting. The desired outcome was that the accuracy level of the output would be sufficient to substantiate power output commitments. The final deliverable for this work would consist of a document outlining the algorithms and software tools that could be integrated into Siemens Wind Park Supervisor.

17 WIND ENERGY↗
NASA NTRSDate not supplied

Impact of Emerging Computing Architectures and Opportunities for Process Systems Engineering Applications

Moore’s “law” was the observation that the number of transistors in an integrated circuit doubled approximately every two years. This trend has distinctly failed to hold in recent years. The death of Moore’s law has left researchers and practitioners in the computational sciences searching for technologies to provide the speedups formerly supported by Moore’s law. Previously overlooked chip architectures and other computing technologies are now receiving more development resources. Critically, these technologies are gaining more mature software support, opening their adoption by researchers in algorithms and applications. In this article, we review some of these computing technologies, their relationship with various algorithms and applications, and their potential benefits (or pitfalls). We close with recommendations for future work by the process systems engineering community specifically.

Emerging hardware↗
DOE OSTI2020

All Hands On Deck: Raising the Bar on Whole Building Performance-Based Code Compliance and Above-Code Programs

In 2019 a large-scale national effort was launched with support from U.S. Department of Energy, Pacific Northwest National Laboratory and Northwest Energy Efficiency Alliance (NEEA). The project aimed to develop a long-term vision and a roadmap for achieving a practical application of whole building performance-based code and above code program compliance in commercial buildings. The work was aided by engaging over 70 stakeholders across the country representing jurisdictions, above-code programs such as LEED and ENERGY STAR Multifamily Program, members of the ASHRAE Standard 90.1 and other Standard committees, IBPSA and software developers. The performance path requires whole building energy modeling and is gaining momentum. Many see it as the future of the commercial energy codes and the main pathway for achieving zero energy buildings. The paper describes the findings from a stakeholder survey funded by NEEA on the current state of performance-based path, its market penetration, trends, implementation practices and adoption challenges. It discusses the patterns revealed by experience of the states with decades-long history of performance-based compliance such as Florida and California and opportunities for taking advantage of the synergies between code and above-code programs. In addition, the paper provides an overview of the tools and resources developed as part of the effort including the compliance form for ASHRAE Standard 90.1 Section 11 and Appendix G, modeling submittal review manual, and modeler and reviewer qualification requirements. The tools and resources would help remove market barriers, deliver immediate benefits to jurisdictions and rating authorities, and achieve energy efficiency through whole-building performance path.

TSPR, Performance Based Complinace, Washington Sta↗
DOE OSTI2020

The state of algal genome quality and diversity

The genomic era of biology has created unprecedented opportunity to study how life works, including understanding evolutionary principles, bioprospecting for novel antibiotics, and genetic manipulation of bioeconomically-relevant species. While genome sequencing and genomic analysis was previously restricted to large-scale projects and consortia, sequencing has become democratized. However, as genomics has become commonplace, the cataloging of sequenced organisms has become challenging, and standardized practices for sequencing, assembly, and annotation have not been adopted. This is equally true in research fields such as algal biology, despite the growing importance of algae in a bio-based economy. Here, in this study, we provide a comprehensive review of the state of eukaryotic algal genomics, explore the quality of algal genome assemblies, and identify the biases and gaps in the current species distribution to inform the development of future genome projects. Overall, we find a trend of declining quality of genomic resources, including a reduction in assembly quality, gene annotation quality, and genome completeness. Potential solutions to improve genome quality include widespread utilization of long read and scaffolding technologies, implementation of standards for assembly quality, evidence-based gene annotation and requisite publication, and support of continued development of gene prediction and genome assessment software.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Zapiary: Creating Visibility in IOT Networks

Zigbee and Z-Wave are the main networking protocols used by low-power Internet of Things (IOT) devices. These protocols use low frequencies. Mesh architecture, and unique address formats that make them not compatible with traditional network traffic tools like IX-Discovery Tools. Zapiary is a software that takes CSV files with Zigbee and Z-Wave traffic and generates Structured Threat Information eXpression (STIX) JSON bundles illustrating the communication within IOT networks. The bundles can then be viewed within Structured Threat Intelligence Graph (STIG) or used with AI/ML models to provide deeper visibility into nodes that make up the network and the ability to trend the mesh network over time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Exploring Architectural-Aware Affinity Policies in Modern HPC Runtimes

Modern commodity and High-Performance Computing (HPC) systems are evolving with complex CPU architectures. These architectures now feature higher core and NUMA domain counts and implement features such as hyperthreading. When considering significant differences in hardware configurations, library availability, and hardware-tailored system/software stacks, which could substantially vary from one system to another, performance portability is hard to achieve. Throughout the years, this trend resulted in an increasingly high burden on application developers to fine-tune their workloads for each architecture. This work explores how hardware-dependent aspects such as locality/process/thread affinity affect performance in modern CPU architectures. We focus our study on the Global Memory and Threading (GMT) distributed runtime system as a representative of Partitioned Global Address Space (PGAS) software stacks commonly adopted for productivity. In particular, to appreciate performance implications, we evaluate GMT’s thread affinity policies, and, introduce two new ones which exploit architectural awareness. Finally, we explore alternative NUMA configurations via different process bindings and perform a scalability study on three HPC clusters with varying CPU architectures and NUMA layouts. Our analysis indicates that more complex architectures are more affected by affinity and binding policies and highlights the importance of setting proper runtime configurations to achieve superior performance.

Di Dio Lavore, Ian↗
NASA NTRS1985

Beyond the sterile cockpit

Consideration is given to some of the negative aspects of the trend toward increased automation of aircraft flight decks. The history of automated devices for navigation, communications and detection on board aircraft is reviewed. Instances of automatic system failure are identified which have led to accidents, and the events surrounding the downing of Korean Airlines Flight 747 are reexamined within the context of a computer-based system failure. Finally, new software and interactive systems to reduce navigational error due to inadequate computer-assisted flight instruction (CAI) are described, with emphasis given to speech processing and intelligent CAI systems.

Wiener, E. L.↗
DOE OSTI2021

Resilient Information Architecture Platform for Smart Grid (RIAPS)

A number of emerging trends will substantially alter the operation and control of the electric grid over the next several decades. These trends include ensuring resiliency under severe weather events, increasing integration of renewable electricity generation, supporting changing electricity demand patterns, and the improving cost effectiveness of distributed energy resources. To address these challenges, the future “Smart Grid” management will need to transition from centralized to coordinated distributed control paradigm. Reliable operation of the Smart Grid depends on distributed intelligence realized through software applications that run on distributed computing devices attached to the power system to collect data and collaboratively manage resources. However, much of the existing software for Smart Grid-enabled devices is either proprietary or developed with custom solutions, which limits interoperability among the heterogeneous devices and hinders the ability to manage system-level reliability, security, and resiliency requirements. Additionally, this approach makes Smart Grid applications hard to maintain, evolve, verify, and replace; resulting in high development and deployment costs. Further development of the Smart Grid requires a reusable software base-layer to move from hard-coded functionality to a plug-and-play architecture capable of managing system-level objectives and constraints in addition to providing consistent common services across heterogeneous devices and applications. Vanderbilt University, in collaboration with North Carolina State University and Washington State University has developed a foundation ‘software platform’ for developing and deploying robust, reliable, effective and secure software applications for the Smart Grid. The Resilient Information Architecture Platform for the Smart Grid (RIAPS) provides core services for building effective and powerful smart grid applications. It offers unique services for real-time data dissemination, fault tolerance, and coordination across apps distributed over the network.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Benchmark Tracking System for Performance Monitoring

Benchmarking is essential for high-performance software development, particularly for monitoring performance across code iterations. This project focused on enhancing the benchmarking process for Lamellar, an asynchronous runtime for High-Performance Computing (HPC) systems developed at Pacific Northwest National Laboratory. Prior to this work, benchmark results were difficult to track and compare across code versions, presenting significant challenges in identifying performance regressions and long-term trends. The primary objective was to establish a systematic, reproducible approach for measuring performance and detecting regressions following code commits. Our methodology involved three key components: standardizing benchmark outputs, implementing data versioning, and developing analysis tools. We standardized the benchmark output format to JSON Line records containing specific fields (execution time, hardware specifications, and environmental variables). To address data management challenges, we evaluated several options and eventually chose a git repository dedicated to benchmark data. We developed a suite of Python tools that processed benchmark results, enriched them with metadata, and facilitated search in the repository. The resulting system enables more efficient filtering and comparison of performance metrics across commit histories, hardware configurations, and benchmark variants through a unified query interface. Our implementation reduces computational overhead by first checking for existing results through configuration matching before initiating new benchmark runs, thereby conserving resources. The system has been validated by Lamellar developers. It organizes results by benchmark type and build configurations for efficient retrieval. Future developments include a planned Large Language Model interface for predicting benchmark performance, incorporating the criterion package for statistical analysis, which will enable automated detection of statistically significant performance changes, and integration with continuous integration pipelines. Despite these enhancements being reserved for future work, this project has successfully provided the Lamellar development team with a framework for maintaining consistent performance standards and identifying optimization opportunities across workloads and hardware environments.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

A Multi-Architecture Approach for Implicit Computational Fluid Dynamics on Unstructured Grids

High-performance computing (HPC) architectures are trending toward manycore paradigms such as graphics processing units (GPUs). Approximately half of the top 100 publicly disclosed supercomputers in the world utilize GPU accelerators for performance. This is in contrast to a decade ago, where there were only a few such machines in the top 100. It is not currently possible to compile and run legacy central processing unit (CPU) software efficiently on GPUs without significant refactoring. Though a number of frameworks offering performance portability exist, none offer a standardized specification that is supported by all major hardware vendors. Additionally, experiences show that obtaining a high percentage of peak performance often requires architecture-specific code. This work details a pragmatic multi-architecture computational fluid dynamics library focused on aerospace problems across the speed range from low subsonic to hypersonic flows involving thermochemical nonequilibrium. A thin abstraction layer above NVIDIA CUDA C++ is utilized, which enables primarily single-source software currently capable of running efficiently on multicore CPUs, NVIDIA GPUs, AMD GPUs, and Intel GPUs. Results on various problems of interest across the speed range are presented and performance is compared between various architectures.

GPU↗