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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 NTRS2016

A Spatiotemporal Indexing Approach for Efficient Processing of Big Array-Based Climate Data with MapReduce

Climate observations and model simulations are producing vast amounts of array-based spatiotemporal data. Efficient processing of these data is essential for assessing global challenges such as climate change, natural disasters, and diseases. This is challenging not only because of the large data volume, but also because of the intrinsic high-dimensional nature of geoscience data. To tackle this challenge, we propose a spatiotemporal indexing approach to efficiently manage and process big climate data with MapReduce in a highly scalable environment. Using this approach, big climate data are directly stored in a Hadoop Distributed File System in its original, native file format. A spatiotemporal index is built to bridge the logical array-based data model and the physical data layout, which enables fast data retrieval when performing spatiotemporal queries. Based on the index, a data-partitioning algorithm is applied to enable MapReduce to achieve high data locality, as well as balancing the workload. The proposed indexing approach is evaluated using the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. The experimental results show that the index can significantly accelerate querying and processing (10 speedup compared to the baseline test using the same computing cluster), while keeping the index-to-data ratio small (0.0328). The applicability of the indexing approach is demonstrated by a climate anomaly detection deployed on a NASA Hadoop cluster. This approach is also able to support efficient processing of general array-based spatiotemporal data in various geoscience domains without special configuration on a Hadoop cluster.

big data↗

NASA NTRS2020

Exploring Cognitive States: Methods for Detecting Physiological Temporal Fingerprints

Cognitive state detection and its relationship to observable physiologically telemetry has been utilized for many human-machine and human-cybernetic applications. This paper aims at understanding and addressing if there are unique psychophysiological patterns over time, a ”physiological temporal fingerprint”, that is associated with specific cognitive states. This preliminary work involves commercial airline pilots completing experimental benchmark task inductions of three cognitive states: 1) Channelized Attention (CA); 2) High Workload (HW); and 3) Low Workload (LW). We approach this objective by modeling these "fingerprints" through the use of Hidden Markov Models and Entropy analysis to evaluate if the transitions over time are complex or rhythmic/predictable by nature. Our results indicate that cognitive states do have unique complexity of physiological sequences that are statistically different from other cognitive states. More specifically, CA has a significantly higher temporal psychophysiological complexity than HW and LW in EEG and ECG telemetry signals. With regards to respiration telemetry, CA has a lower temporal psychophysiological complexity than HW and LW. Through our preliminary work, addressing this unique underpinning can inform whether these underlying dynamics can be utilized to understand how humans transition between cognitive states and for improved detection of cognitive states.

Napoli, Nicholas J.↗

DOE OSTI2026

Dataset of Generative AI Workload Power Profiles

This dataset provides a collection of high-resolution (5/10 Hz or every 0.2/0.1 seconds) power consumption profiles for generative artificial intelligence (GenAI) workloads executed on NLR's High Performance Computing (HPC) platform Kestrel. The dataset also includes examples of representative whole-facility power profiles generated using a bottom-up, event-driven, data center energy model . This dataset is designed to support research in energy modeling, infrastructure planning, energy system integration, and sustainability analysis for AI-driven computing systems. The dataset captures time-resolved electrical power measurements across a diverse set of configurations, including variations in job type (inference vs. training), workload (LLM vs. image generation), datasets, and number of compute nodes. Power traces are provided in a standardized format and include both raw/instantaneous and aggregated files. Each profile is accompanied by metadata describing workload parameters, enabling reproducibility and cross-study comparison. The dataset is intended for use in applications such as data center infrastructure planning, energy modeling, demand response and grid impact studies, and development and validation of system-level simulation tools. By making these workload-specific power profiles publicly available, this dataset aims to address the current lack of open, empirical energy data for generative AI systems and to facilitate transparent, reproducible research on the energy and environmental impacts of large-scale AI deployment. If you use this dataset, please cite the associated publication: Vercellino et al., “Measurement of Generative AI Workload Power Profiles for Whole-Facility Data Center Infrastructure Planning,” arXiv:2604.07345 (2026).

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2016

ICN Deicing Operations Analysis

Aircraft deicing and anti-icing on airport ground in winter weather conditions is important to ensure safe departure takeoff and enroute flying. At the same time, it imposes additional workload to controllers and airport operators, and causes delays to airlines and passengers.This presentation shows the initial results of analyzing the deicing related operations at Incheon International Airport (ICN). It describes the deicing operations concept, procedures, and deicing making processes at ICN. It also looks into the three-month ICN operation data from Dec 2015 to Feb 2016 to identify the characteristics of the current day deicing operation.This work is under the joint collaboration between Korea Aerospace Research Institute and NASA. The objective is to develop a deicing operation simulation capability in NASA's fast time simulation environment to study and improve deicing operations efficiency.

Airport Surface ATM↗

NASA NTRS1989

A performance assessment of a byzantine resilient fault-tolerant computer

This report presents the results of a performance analysis of a quad-redundant Fault-Tolerant Processor (FTP). The FTP is a computing system specifically designed for applications where very high reliability is required. Examples of such applications are flight control systems, nuclear power systems, and spacecraft control systems. The FTP performance was analyzed in a hierarchical manner encompassing the hardware, the operating system, and the application. At the hardware level, the hardware organization and design was assessed in relation to system throughput and response. Analysis at the operating system level revealed that the scheduler took only 3.2 percent of each 40ms frame, while the redundancy management software took 10.4 percent. The application level performance was analyzed via a synthetic workload and a representative flight control model. The estimated throughput for this application was found to be 317.6 KIPS if not exercising the voter. Exercising the voter to ensure fault tolerance will diminish this number linearly as the number of votes is increased. This performance analysis method was proven effective by uncovering undesirable behavior and anomalies in the FTP system.

Young, Steven D.↗

NASA NTRS2008

Design Analysis of Corridors-in-the-Sky

Corridors-in-the-sky or tubes is one of new concepts in dynamic airspace configuration. It accommodates high density traffic, which has similar trajectories. Less air traffic controllers workload is expected than classic airspaces, thus, corridors-in-the-sky may increase national airspace capacity and reduce flight delays. To design corridors-in-the-sky, besides identifying their locations, their utilization, altitudes, and impacts on remaining system need to be analyzed. This paper chooses one tube candidate and presents analyses of spatial and temporal utilization of the tube, the impact on the remaining traffic, and the potential benefit caused by off-loading the traffic from underlying sectors. Fundamental issues regarding to the benefits have been also clarified. Methods developed to assist the analysis are described. Analysis results suggest dynamic tubes in terms of varied utilizations during different time periods. And it is found that combined lane options would be a good choice to lower the impact on non-tube users. Finally, it shows significant reduction of peak aircraft count in underlying sectors with only one tube enabled.

Xue, Min↗

DOE OSTI2021

Parallel I/O Evaluation Techniques and Emerging HPC Workloads: A Perspective

Emerging workloads such as artificial intelligence, big data analytics and complex multi-step workflows alongside future exascale applications are anticipated future HPC workloads, which will result in a more diverse I/O system workload and even less predictable I/O behavior and access patterns. Along with the ever increasing gap between the compute and storage performance capabilities, the in-depth understanding of extreme-scale I/O behavior and the I/O performance modeling and prediction are essential tools of the large-scale I/O evaluation process for addressing the needs of extreme-scale hybrid workloads. In this survey article, we focus on the state-of-the-art of the I/O behavior and performance analysis process for HPC systems in a 5-year time window and identify future research challenges.

Neuwirth, Sarah↗

NASA NTRS1993

Primary display latency criteria based on flying qualities and performance data

With a pilots' increasing use of visual cue augmentation, much requiring extensive pre-processing, there is a need to establish criteria for new avionics/display design. The timeliness and synchronization of the augmented cues is vital to ensure the performance quality required for precision mission task elements (MTEs) where augmented cues are the primary source of information to the pilot. Processing delays incurred while transforming sensor-supplied flight information into visual cues are unavoidable. Relationships between maximum control system delays and associated flying qualities levels are documented in MIL-F-83300 and MIL-F-8785. While cues representing aircraft status may be just as vital to the pilot as prompt control response for operations in instrument meteorological conditions, presently, there are no specification requirements on avionics system latency. To produce data relating avionics system latency to degradations in flying qualities, the Navy conducted two simulation investigations. During the investigations, flying qualities and performance data were recorded as simulated avionics system latency was varied. Correlated results of the investigation indicates that there is a detrimental impact of latency on flying qualities. Analysis of these results and consideration of key factors influencing their application indicate that: (1) Task performance degrades and pilot workload increases as latency is increased. Inconsistency in task performance increases as latency increases. (2) Latency reduces the probability of achieving Level 1 handling qualities with avionics system latency as low as 70 ms. (3) The data suggest that the achievement of desired performance will be ensured only at display latency values below 120 ms. (4) These data also suggest that avoidance of inadequate performance will be ensured only at display latency values below 150 ms.

Funk, John D., Jr.↗

NASA NTRSDate not supplied

Automated Downlink Pipeline for Scientific Data Using TReK

ISS users generate scientific data files on orbit that require console operators to retrieve and deliver them for analysis. Automating the downlink process using TReK CFDP and DTN provides ground flight controllers and PD teams increased efficiency, reducing workload and resulting in cost savings without reduced services provided.

TReK↗

DOE OSTI2022

A Case For Intra-rack Resource Disaggregation in HPC

The expected halt of traditional technology scaling is motivating increased heterogeneity in high-performance computing (HPC) systems with the emergence of numerous specialized accelerators. As heterogeneity increases, so does the risk of underutilizing expensive hardware resources if we preserve today’s rigid node configuration and reservation strategies. This has sparked interest in resource disaggregation to enable finer-grain allocation of hardware resources to applications. However, there is currently no data-driven study of what range of disaggregation is appropriate in HPC. To that end, we perform a detailed analysis of key metrics sampled in NERSC’s Cori, a production HPC system that executes a diverse open-science HPC workload. In addition, we profile a variety of deep-learning applications to represent an emerging workload. We show that for a rack (cabinet) configuration and applications similar to Cori, a central processing unit with intra-rack disaggregation has a 99.5% probability to find all resources it requires inside its rack. In addition, ideal intra-rack resource disaggregation in Cori could reduce memory and NIC resources by 5.36% to 69.01% and still satisfy the worst-case average rack utilization.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2004

Computer-Aided Systems Engineering for Flight Research Projects Using a Workgroup Database

An online systems engineering tool for flight research projects has been developed through the use of a workgroup database. Capabilities are implemented for typical flight research systems engineering needs in document library, configuration control, hazard analysis, hardware database, requirements management, action item tracking, project team information, and technical performance metrics. Repetitive tasks are automated to reduce workload and errors. Current data and documents are instantly available online and can be worked on collaboratively. Existing forms and conventional processes are used, rather than inventing or changing processes to fit the tool. An integrated tool set offers advantages by automatically cross-referencing data, minimizing redundant data entry, and reducing the number of programs that must be learned. With a simplified approach, significant improvements are attained over existing capabilities for minimal cost. By using a workgroup-level database platform, personnel most directly involved in the project can develop, modify, and maintain the system, thereby saving time and money. As a pilot project, the system has been used to support an in-house flight experiment. Options are proposed for developing and deploying this type of tool on a more extensive basis.

Mizukami, Masahi↗

NASA NTRSDate not supplied

Initial Study of Tailored Trajectory Management for Multi-Vehicle Uncrewed Regional Air Cargo Operations

The primary contribution of this paper is an evaluation of the potential value of a tailored trajectory management (TTM) capability for uncrewed aircraft (UA) operators that is proactive in detecting conflicts and developing trajectory-based solutions for UA prior to air traffic control (ATC) performing conflict resolution. The experiment matrix is composed of one baseline simulation that models current air traffic operations without such a capability and four test simulations with different configurations of such a capability. In each simulation, five UA operations into Fort Worth Alliance airport were modeled in the presence of recorded tracks for about 4700 flights on January 18, 2022. The analysis focused on the extent to which such a capability was able to preclude an event that could spike UA operator workload. More specifically, in this study, the emulated UA operator TTM capability for multi-vehicle regional air cargo operations was able to reduce the number of instances of concurrent UA conflicts in the modeled ATC conflict resolution timeframe of 8 minutes or less from three to as low as one.

uncrewed aircraft, regional air cargo, tailored tr↗

NASA NTRS1992

Performance Evaluation and Modeling Techniques for Parallel Processors

In practice, the performance evaluation of supercomputers is still substantially driven by singlepoint estimates of metrics (e.g., MFLOPS) obtained by running characteristic benchmarks or workloads. With the rapid increase in the use of time-shared multiprogramming in these systems, such measurements are clearly inadequate. This is because multiprogramming and system overhead, as well as other degradations in performance due to time varying characteristics of workloads, are not taken into account. In multiprogrammed environments, multiple jobs and users can dramatically increase the amount of system overhead and degrade the performance of the machine. Performance techniques, such as benchmarking, which characterize performance on a dedicated machine ignore this major component of true computer performance. Due to the complexity of analysis, there has been little work done in analyzing, modeling, and predicting the performance of applications in multiprogrammed environments. This is especially true for parallel processors, where the costs and benefits of multi-user workloads are exacerbated. While some may claim that the issue of multiprogramming is not a viable one in the supercomputer market, experience shows otherwise. Even in recent massively parallel machines, multiprogramming is a key component. It has even been claimed that a partial cause of the demise of the CM2 was the fact that it did not efficiently support time-sharing. In the same paper, Gordon Bell postulates that, multicomputers will evolve to multiprocessors in order to support efficient multiprogramming. Therefore, it is clear that parallel processors of the future will be required to offer the user a time-shared environment with reasonable response times for the applications. In this type of environment, the most important performance metric is the completion of response time of a given application. However, there are a few evaluation efforts addressing this issue.

Dimpsey, Robert Tod↗

DOE OSTI2025

Business Case Analysis for Artificial Intelligence-Large Language Model Technology Integration

AI-assisted processes are expected to enhance operational efficiency and improve decision-making, supporting the long-term economic viability of nuclear power plants. However, detailed business analyses of AI-generated cost savings are rarely performed. Given the recent industry interest in Large Language Model (LLM), the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program has conducted a comprehensive business case analysis of LLM Artificial Intelligence (AI) implementation in nuclear plant engineering workflows. The research employed three complementary business case approaches to evaluate impact of an LLM, using three representative engineering processes as use-cases: Boric Acid Corrosion (BAC) Evaluations, Maintenance Rule Evaluations, and 10 CFR 50.59 Screenings. Through detailed workload analyses and structured interviews, the study quantified significant efficiency improvements ranging from 11% to 59% across these processes. The research further considers how these efficiency gains could translate into tangible reliability improvements through enhanced engineering capacity. Analysis of historical plant trip data indicates that enabling engineers to focus on proactive reliability activities could provide substantial financial benefits through avoided outages, potentially generating greater value than the direct efficiency improvements alone. By documenting successful applications, implementation challenges, and strategic opportunities, this research provides nuclear utilities with a practical framework for evaluating the value of AI technology to support long-term operations through advanced digital technologies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

SYMBIOSYS: A Methodology for Performance Analysis of Composable HPC Data Services

Microservices are a powerful new way of building, customizing, and deploying distributed services owing to their flexibility and maintainability. Several large-scale distributed platforms have emerged to serve the growing needs of data-centric workloads and services in commercial computing. Concurrently, high-performance computing (HPC) systems and software are rapidly evolving to meet the demands of diversified applications and heterogeneity. The interplay of hardware factors, software configuration parameters, and the flexibility offered with a microservice architecture makes it nontrivial to estimate the optimal service instantiation for a given application workload. Further, this problem is exacerbated when considering that these services operate in a dynamic and heterogeneous HPC environment. An optimally integrated service can be vastly more performant than a haphazardly integrated one. Existing performance tools for HPC either fail to understand the request-response model of communication inherent to microservices or they operate within a narrow scope, limiting the insight that can be gleaned from employing them in isolation. We propose a methodology for integrated performance analysis of HPC microservices frameworks and applications called SYMBIOSYS. We describe its design and implementation within the context of the Mochi framework. This integration is achieved by combining distributed callpath profiling and tracing with a performance data exchange strategy that collects fine-grained, low-level metrics from the RPC communication library and network layers. The result is a portable, low-overhead performance analysis setup that provides a holistic profile of the dependencies among microservices and how they interact with the Mochi RPC software stack. Using HEPnOS, a production-quality Mochi data service, we demonstrate the low-overhead operation of SYMBIOSYS at scale and use it to identify the root causes of poorly performing service configurations.

microservices↗

NASA NTRS1978

Adaptation of time line analysis program to single pilot instrument flight research

A data base was developed for SPIFR operation and the program was run. The outputs indicated that further work was necessary on the workload models. In particular, the workload model for the cognitive channel should be modified as the output workload appears to be too small. Included in the needed refinements are models to show the workload when in turbulence, when overshooting a radial or glideslope, and when copying air traffic control clearances.

Hinton, D. A.↗

DOE OSTI2024

The ATLAS Workflow Management System Evolution in the LHC Run3 and towards the High-Luminosity LHC era

The ATLAS experiment has 18+ years of experience using workload management systems to deploy and develop workflows to process and to simulate data on the distributed computing infrastructure. Simulation, processing and analysis of LHC experiment data require the coordinated work of heterogeneous computing resources. In particular, the ATLAS experiment utilizes the resources of 250 computing centers worldwide, the power of supercomputing centres, and national, academic and commercial cloud computing resources. In this contribution, we present new techniques for cost-effectively improving efficiency introduced in workflow management system software. The evolution from a mesh framework to new types of computing facilities such as cloud and HPCs is described, as well as new types of production and analysis workflows.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1978

Evaluation of several secondary tasks in the determination of permissible time delays in simulator visual and motion cues

The effect of secondary tasks in determining permissible time delays in visual-motion simulation of a pursuit tracking task was examined. A single subject, a single set of aircraft handling qualities, and a single motion condition in tracking a target aircraft that oscillates sinusoidally in altitude were used. In addition to the basic simulator delays the results indicate that the permissible time delay is about 250 msec for either a tapping task, an adding task, or an audio task and is approximately 125 msec less than when no secondary task is involved. The magnitudes of the primary task performance measures, however, differ only for the tapping task. A power spectraldensity analysis basically confirms the result by comparing the root-mean-square performance measures. For all three secondary tasks, the total pilot workload was quite high.

Miller, G. K., Jr.↗