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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Near real-time streaming analysis of big fusion data

Experiments on fusion plasmas produce high-dimensional data time series with ever-increasing magnitude and velocity, but turn-around times for analysis of this data have not kept up. For example, many data analysis tasks are often performed in a manual, ad-hoc manner some time after an experiment. In this article, we introduce the Delta framework that facilitates near real-time streaming analysis of big and fast fusion data. By streaming measurement data from fusion experiments to a high-performance compute center, Delta allows computationally expensive data analysis tasks to be performed in between plasma pulses. This article describes the modular and expandable software architecture of Delta and presents performance benchmarks of individual components as well as of an example workflow. Focusing on a streaming analysis workflow where electron cyclotron emission imaging (ECEi) data is measured at KSTAR on the National Energy Research Scientific Computing Center's (NERSC's) supercomputer we routinely observe data transfer rates of about 4 Gigabit per second. In NERSC, a demanding turbulence analysis workflow effectively utilizes multiple nodes and graphical processing units and executes them in under 5 min. We further discuss how Delta uses modern database systems and container orchestration services to provide web-based real-time data visualization. For the case of ECEi data we demonstrate how data visualizations can be augmented with outputs from machine learning models. Here, by providing session leaders and physics operators, results of higher-order data analysis using live visualizations may make more informed decisions on how to configure the machine for the next shot.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2004

Modular Wireless Data-Acquisition and Control System

A modular wireless data-acquisition and control system, now in operation at Kennedy Space Center, offers high performance at relatively low cost. The system includes a central station and a finite number of remote stations that communicate with each other through low-power radio frequency (RF) links. Designed to satisfy stringent requirements for reliability, integrity of data, and low power consumption, this system could be reproduced and adapted to use in a broad range of settings.

Perotti, Jose↗
NASA NTRS2003

Data-Mining Toolset Developed for Determining Turbine Engine Part Life Consumption

The current practice in aerospace turbine engine maintenance is to remove components defined as life-limited parts after a fixed time, on the basis of a predetermined number of flight cycles. Under this schedule-based maintenance practice, the worst-case usage scenario is used to determine the usable life of the component. As shown, this practice often requires removing a part before its useful life is fully consumed, thus leading to higher maintenance cost. To address this issue, the NASA Glenn Research Center, in a collaborative effort with Pratt & Whitney, has developed a generic modular toolset that uses data-mining technology to parameterize life usage models for maintenance purposes. The toolset enables a "condition-based" maintenance approach, where parts are removed on the basis of the cumulative history of the severity of operation they have experienced. The toolset uses data-mining technology to tune life-consumption models on the basis of operating and maintenance histories. The flight operating conditions, represented by measured variables within the engine, are correlated with repair records for the engines, generating a relationship between the operating condition of the part and its service life. As shown, with the condition-based maintenance approach, the lifelimited part is in service until its usable life is fully consumed. This approach will lower maintenance costs while maintaining the safety of the propulsion system. The toolset is a modular program that is easily customizable by users. First, appropriate parametric damage accumulation models, which will be functions of engine variables, must be defined. The tool then optimizes the models to match the historical data by computing an effective-cycle metric that reduces the unexplained variability in component life due to each damage mode by accounting for the variability in operational severity. The damage increment due to operating conditions experienced during each flight is used to compute the effective cycles and ultimately the replacement time. Utilities to handle data problems, such as gaps in the flight data records, are included in the toolset. The tool was demonstrated using the first stage, high-pressure turbine blade of the PW4077 engine (Pratt & Whitney, East Hartford, CT). The damage modes considered were thermomechanical fatigue and oxidation/erosion. Each PW4077 engine contains 82 first-stage, high-pressure turbine blades, and data from a fleet of engines were used to tune the life-consumption models. The models took into account not only measured variables within the engine, but also unmeasured variables such as engine health parameters that are affected by degradation of the engine due to aging. The tool proved effective at predicting the average number of blades scrapped over time due to each damage mode, per engine, given the operating history of the engine. The customizable tools are available to interested parties within the aerospace community.

Litt, Jonathan S.↗
DOE OSTI2012

E-center: A collaborative platform for wide area network users

The E-Center is a social collaborative web-based platform for assisting network users in understanding network conditions across network paths of interest to them. It is designed to give a user the necessary tools to isolate, identify, and resolve network performance-related problems. E-Center provides network path information on a link-by-link level, as well as from an end-to-end perspective. In addition to providing current and recent network path data, E-Center is intended to provide a social media environment for them to share issues, ideas, concerns, and problems. The product has a modular design that accommodates integration of other network services that make use of the same network path and performance data.

Grigoriev, M.↗
DOE OSTI2025

Hands-On, Heads-Up: Blending Cyber T&E with Data Science-Driven Training in Jupyter Notebooks

In an era of increasingly sophisticated threats to critical infrastructure, cybersecurity professionals must be more than just aware; they must be immersed, agile, and equipped to operate in environments where failure is not an option. Nowhere is this truer than in the nuclear sector, where cyber-physical systems, regulatory scrutiny, and insider threat potential demand a new generation of hands-on, technically fluent defenders. This paper presents a unified training approach that integrates Cybersecurity Test and Evaluation (T&E) with data science techniques using Jupyter Notebooks as the interactive lab environment. The program centers on a modular, scenario-driven curriculum designed to build not just knowledge but practical capability in the assessment and defense of radiation detection systems, firmware interfaces, and operational security postures.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗
NASA NTRS2006

An Integrated Snow Radiance and Snow Physics Modeling Framework for Cold Land Surface Modeling

Recent developments in forward radiative transfer modeling and physical land surface modeling are converging to allow the assembly of an integrated snow/cold lands modeling framework for land surface modeling and data assimilation applications. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. Together these form a flexible framework for self-consistent remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. Each element of this framework is modular so the choice of element can be tailored to match the emphasis of a particular study. For example, within our framework, four choices of a FRTM are available to simulate the brightness temperature of snow: Two models are available to model the physical evolution of the snowpack and underlying soil, and two models are available to handle the water/energy balance at the land surface. Since the framework is modular, other models-physical or statistical--can be accommodated, too. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster at the NASA Goddard Space Flight Center. The advantages of such an integrated modular framework built on the LIS will be described through examples-e.g., studies to analyze snow field experiment observations, and simulations of future satellite missions for snow and cold land processes.

Kim, Edward J.↗
DOE OSTI2024

Nuclear Power Plant Colocation with Data Centers

This presentation is an overview of the nuclear siting and licensing process, including specific considerations and challenges for nuclear power plant colocation with data centers.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Experimental Capabilities and Achievements of the Space Environment Dynamometer (SED)

The Space Environment Dynamometer (SED) chamber was designed to conduct research in cryobotics; an area of study that focuses on robotic systems and rotating machinery operating in extreme cold environments including Earth, low Earth orbit, Mars, Moon, asteroids, Solar orbit, planetary orbit, or those encountered during travel among these destinations. The test chamber incorporates a modular dynamometer, consisting of a variety of brakes, torque sensors and motors to be easily interchanged between tests. Each test employs a unique test profile that incorporates different setpoints of applied torques and velocities for a given period or number of rev- olutions. The modularity of the dynamometer setup allows for any combination of motor, gearbox to be tested. This chamber is one of a kind and resides at the Swamp Works facility within the Granular Mechanics and Regolith Operations laboratory (GMRO) at NASA Kennedy Space Center. Other cold chambers exist, however they are project specific and do not simultaneously output real time torque, temperature and efficiency data. The modularity of this extreme cold environment test chamber, coupled with the custom software and instrumentation, makes it one of a kind. The chamber is capable of stabilizing cryogenic temperatures and pressures to commensurate moon environments. Tests have successfully been conducted on motors and gearboxes for various cryogenic temperature set points, torques, and angular velocities. Relevant internal temperatures of the test article and chamber were recorded using a variety of temperature sensors. The temperature setpoints, on the motors and gearboxes tested, were stabilized by using PID gain scheduling of the PWM signal for the various heaters. The heat removal for the motor was provided by creating a thermally conductive path from a cryohead directly to the test article using copper straps. A variety of strainwave gears (SWGs), also known as Harmonic drives, planetary gear systems and DC motor actuator configurations have been tested in the chamber. The experiments performed were for various projects including Bulk Metallic Glass Gears (BMGG), Volatiles Investigating Polar Exploration Rover (VIPER), In-Situ Resource Utilization Pilot Excavator (IPEX) . Various upgrades have been made to the extreme cold environment test chamber for the use of cryobotic research. These upgrades greatly increased the autonomous capabilities of the test set up by providing redundancies in the hardware and software. The redundancies were primarily added to protect the integrity of the cryohead. A new strapping and insulation method was performed to create the thermal conductive path from the actuators to the cryohead. The software was upgraded to include temperature setpoint control, further increasing the autonomous capabilities of the test. This paper goes into detail regarding the upgrades made to the extreme cold environment test chamber, as well as highlights the results from a COLDArm acceptance test.

Casey J. Clark↗
DOE OSTI2024

Powering Data Centers with Clean Energy: A Techno-Economic Case Study of Nuclear and Renewable Energy Dependability

Rising data demands from artificial intelligence (AI) and large language models (LLMs) generating images, videos, and text have prompted increased need for larger and more robust data centers in the United States. Major companies interested in these larger data centers face the choice of linking them to existing regional grids, building stand-alone power supplies onsite, or a combination of both. The request, review, and approval process for new transmission lines to grids in the United States, however, has grown in recent years to times spans rivaling those of new construction for nuclear power plants. Building an islanded power supply for each data center is therefore becoming a prominent option. In this case study, several technologies are modeled in techno-economic simulations for long-term system costs subject to fixed electricity demand from a singular data center. A 250 MWe data center is assumed with additional 50 MWe for resiliency. Techno-economic simulations are conducted using the Holistic Energy Resource Optimization Network (HERON) software, which is a part of the Framework for Optimization of Resources and Economics (FORCE) tool suite. Technologies considered include solar, wind, lithium-ion batteries, and several types of nuclear reactors: large-scale reactors, small modular reactors, and microreactors. A low- and high-cost estimate for each technology is assumed to develop a range of expected economic performance. Low-cost estimates included several clean energy production tax credits. Different combinations of renewable energy generators with nuclear reactors are considered, ranging from a fully renewable-powered data center to a fully nuclear-powered data center. Historic time series of wind and solar availability from the Texas grid are used to train a reduced order model; this model then generates unique time series with similar characteristics of the training dataset. Multiple scenarios of weather and subsequent operations are simulated for each renewable-nuclear combination to determine total costs throughout the project lifetime. Fully renewable-powered configurations required large amounts of installed capacity (GW scale) in the simulations to meet the fixed demand of the data center. This is due to some scenarios in the historical dataset which captured low-wind and low-solar days, requiring over-building of these technologies as well as batteries to compensate for the low amounts of electricity generation. Fully nuclear-powered configurations outperformed the fully renewable and mixed renewable-nuclear configurations in terms of cost, with ranges between $1B and $10B in 2023 USDs compared to $40B+ for fully renewable configurations. Of the nuclear technologies, small modular reactors performed better economically than large-scale nuclear models due to lower projected capital costs, and both performed better than the microreactor models. These results demonstrate the applicability of firm, dispatchable electricity resources from baseload generators like nuclear power plants for operating facilities that run at constant power without daily variability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1994

Adaptation of a Control Center Development Environment for Industrial Process Control

In the control center, raw telemetry data is received for storage, display, and analysis. This raw data must be combined and manipulated in various ways by mathematical computations to facilitate analysis, provide diversified fault detection mechanisms, and enhance display readability. A development tool called the Graphical Computation Builder (GCB) has been implemented which provides flight controllers with the capability to implement computations for use in the control center. The GCB provides a language that contains both general programming constructs and language elements specifically tailored for the control center environment. The GCB concept allows staff who are not skilled in computer programming to author and maintain computer programs. The GCB user is isolated from the details of external subsystem interfaces and has access to high-level functions such as matrix operators, trigonometric functions, and unit conversion macros. The GCB provides a high level of feedback during computation development that improves upon the often cryptic errors produced by computer language compilers. An equivalent need can be identified in the industrial data acquisition and process control domain: that of an integrated graphical development tool tailored to the application to hide the operating system, computer language, and data acquisition interface details. The GCB features a modular design which makes it suitable for technology transfer without significant rework. Control center-specific language elements can be replaced by elements specific to industrial process control.

Killough, Ronnie L.↗
NASA NTRS1990

High performance VLSI telemetry data systems

NASA's deployment of major space complexes such as Space Station Freedom (SSF) and the Earth Observing System (EOS) will demand increased functionality and performance from ground based telemetry acquisition systems well above current system capabilities. Adaptation of space telemetry data transport and processing standards such as those specified by the Consultative Committee for Space Data Systems (CCSDS) standards and those required for commercial ground distribution of telemetry data, will drive these functional and performance requirements. In addition, budget limitations will force the requirement for higher modularity, flexibility, and interchangeability at lower cost in new ground telemetry data system elements. At NASA's Goddard Space Flight Center (GSFC), the design and development of generic ground telemetry data system elements, over the last five years, has resulted in significant solutions to these problems. This solution, referred to as the functional components approach includes both hardware and software components ready for end user application. The hardware functional components consist of modern data flow architectures utilizing Application Specific Integrated Circuits (ASIC's) developed specifically to support NASA's telemetry data systems needs and designed to meet a range of data rate requirements up to 300 Mbps. Real-time operating system software components support both embedded local software intelligence, and overall system control, status, processing, and interface requirements. These components, hardware and software, form the superstructure upon which project specific elements are added to complete a telemetry ground data system installation. This paper describes the functional components approach, some specific component examples, and a project example of the evolution from VLSI component, to basic board level functional component, to integrated telemetry data system.

Chesney, J.↗
NASA NTRS1974

Random-access technique for modular bathymetry data storage in a continental shelf wave refraction program

A study was conducted of an alternate method for storage and use of bathymetry data in the Langley Research Center and Virginia Institute of Marine Science mid-Atlantic continental-shelf wave-refraction computer program. The regional bathymetry array was divided into 105 indexed modules which can be read individually into memory in a nonsequential manner from a peripheral file using special random-access subroutines. In running a sample refraction case, a 75-percent decrease in program field length was achieved by using the random-access storage method in comparison with the conventional method of total regional array storage. This field-length decrease was accompanied by a comparative 5-percent increase in central processing time and a 477-percent increase in the number of operating-system calls. A comparative Langley Research Center computer system cost savings of 68 percent was achieved by using the random-access storage method.

Poole, L. R.↗
DOE OSTI2015

Nuclear hybrid energy infrastructure

The nuclear hybrid energy concept is becoming a reality for the US energy infrastructure where combinations of the various potential energy sources (nuclear, wind, solar, biomass, and so on) are integrated in a hybrid energy system. This paper focuses on challenges facing a hybrid system with a Small Modular Reactor at its core. The core of the paper will discuss efforts required to develop supervisory control center that collects data, supports decision-making, and serves as an information hub for supervisory control center. Such a center will also be a model for integrating future technologies and controls. In addition, advanced operations research, thermal cycle analysis, energy conversion analysis, control engineering, and human factors engineering will be part of the supervisory control center. Nuclear hybrid energy infrastructure would allow operators to optimize the cost of energy production by providing appropriate means of integrating different energy sources. The data needs to be stored, processed, analyzed, trended, and projected at right time to right operator to integrate different energy sources.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2012

Common Data Acquisition Systems (DAS) Software Development for Rocket Propulsion Test (RPT) Test Facilities

The advent of the commercial space launch industry and NASA's more recent resumption of operation of Stennis Space Center's large test facilities after thirty years of contractor control resulted in a need for a non-proprietary data acquisition systems (DAS) software to support government and commercial testing. The software is designed for modularity and adaptability to minimize the software development effort for current and future data systems. An additional benefit of the software's architecture is its ability to easily migrate to other testing facilities thus providing future commonality across Stennis. Adapting the software to other Rocket Propulsion Test (RPT) Centers such as MSFC, White Sands, and Plumbrook Station would provide additional commonality and help reduce testing costs for NASA. Ultimately, the software provides the government with unlimited rights and guarantees privacy of data to commercial entities. The project engaged all RPT Centers and NASA's Independent Verification & Validation facility to enhance product quality. The design consists of a translation layer which provides the transparency of the software application layers to underlying hardware regardless of test facility location and a flexible and easily accessible database. This presentation addresses system technical design, issues encountered, and the status of Stennis development and deployment.

Hebert, Phillip W., Sr.↗
NASA NTRS2012

Common Data Acquisition Systems (DAS) Software Development for Rocket Propulsion Test (RPT) Test Facilities - A General Overview

The advent of the commercial space launch industry and NASA's more recent resumption of operation of Stennis Space Center's large test facilities after thirty years of contractor control resulted in a need for a non-proprietary data acquisition system (DAS) software to support government and commercial testing. The software is designed for modularity and adaptability to minimize the software development effort for current and future data systems. An additional benefit of the software's architecture is its ability to easily migrate to other testing facilities thus providing future commonality across Stennis. Adapting the software to other Rocket Propulsion Test (RPT) Centers such as MSFC, White Sands, and Plumbrook Station would provide additional commonality and help reduce testing costs for NASA. Ultimately, the software provides the government with unlimited rights and guarantees privacy of data to commercial entities. The project engaged all RPT Centers and NASA's Independent Verification & Validation facility to enhance product quality. The design consists of a translation layer which provides the transparency of the software application layers to underlying hardware regardless of test facility location and a flexible and easily accessible database. This presentation addresses system technical design, issues encountered, and the status of Stennis' development and deployment.

Hebert, Phillip W., Sr.↗
NASA NTRSDate not supplied

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗
NASA NTRSDate not supplied

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗