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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Knowledge Graph Approach to Analyze Systems and Assets Health

Nuclear power plants collect large amounts of equipment reliability data elements that contain information on the statuses of component, assets, and systems. All these data elements precisely record asset and system performance and health throughout the lifecycle of those assets and systems. However, several challenges have proved to be roadblocks to this process. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly focuses on the integration of numeric and textual data elements in order to assist plant system engineers in analyzing equipment reliability data. This task begins with preprocessing the data by extracting knowledge from textual data via natural language processing methods and quantifying system, asset, and component health based on numeric data. We then employed model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Data elements were then associated with a single MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Extensible packet processing architecture

A technique for distributed packet processing includes sequentially passing packets associated with packet flows between a plurality of processing engines along a flow through data bus linking the plurality of processing engines in series. At least one packet within a given packet flow is marked by a given processing engine to signify by the given processing engine to the other processing engines that the given processing engine has claimed the given packet flow for processing. A processing function is applied to each of the packet flows within the processing engines and the processed packets are output on a time-shared, arbitered data bus coupled to the plurality of processing engines.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Predicting Critical Transitions in Multiscale Data

Predicting the dynamics of complex nonlinear systems remains a challenging problem both in dynamical systems theory as well as real world science and engineering applications. Data-driven methods utilizing the latest advances in machine learning (ML) provide a promising new paradigm for this task. Our work centered on Reservoir Computing (RC), which has shown itself to be capable of skillfully predicting chaotic dynamics in multiscale systems. In the first part of the work, the focus is on how to improve predictions of critical transitions in a class of slow-fast metastable systems in which the equations are known. An additional goal was to determine whether a relationship exists between RC and Koopman operator theory, to improve the efficiency and broaden the applicability of the approach. In the second part of this work, a variation on the RC model known as Reconstructive Reservoir Computing (RRC) is applied to real-world data to identify anomalies.

97 MATHEMATICS AND COMPUTING↗
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↗
NASA NTRS1999

Managing the Software Development Process

The goal of any software development project is to produce a product that is delivered on time, within the allocated budget, and with the capabilities expected by the customer and unfortunately, this goal is rarely achieved. However, a properly managed project in a mature software engineering environment can consistently achieve this goal. In this paper we provide an introduction to three project success factors, a properly managed project, a competent project manager, and a mature software engineering environment. We will also present an overview of the benefits of a mature software engineering environment based on 24 years of data from the Software Engineering Lab, and suggest some first steps that an organization can take to begin benefiting from this environment. The depth and breadth of software engineering exceeds this paper, various references are cited with a goal of raising awareness and encouraging further investigation into software engineering and project management practices.

Lubelczky, Jeffrey T.↗
NASA NTRS2001

Next-Generation Ion Propulsion Being Developed

The NASA Glenn Research Center ion-propulsion program addresses the need for high specific-impulse systems and technology across a broad range of mission applications and power levels. One activity is the development of the next-generation ion-propulsion system as a follow-on to the successful Deep Space 1 system. The system is envisioned to incorporate a lightweight ion engine that can operate over 1 to 10 kW, with a 550-kg propellant throughput capacity. The engine concept under development has a 40-cm beam diameter, twice the effective area of the Deep Space 1 engine. It incorporates mechanical features and operating conditions to maximize the design heritage established by the Deep Space 1 engine, while incorporating new technology where warranted to extend the power and throughput capability. Prototype versions of the engine have been fabricated and are under test at NASA, with an engineering model version in manufacturing. Preliminary performance data for the prototype engine have been documented over 1.1- to 7.3-kW input power. At 7.3 kW, the engine efficiency is 0.68, at 3615-sec specific impulse. Critical component temperatures, including those of the discharge cathode assembly and magnets, have been documented and are within established limits, with significant margins relative to the Deep Space 1 engine. The 1- to 10-kW ion thruster approach described here was found to provide the needed power and performance improvement to enable important NASA missions. The Integrated In-Space Transportation Planning (IISTP) studies compared many potential technologies for various NASA, Government, and commercial missions. These studies indicated that a high-power ion propulsion system is the most important technology for development because of its outstanding performance versus perceived development and recurring costs for interplanetary solar electric propulsion missions. One of the best applications of a highpower electric propulsion system was as an integral part of a solar electric propulsion (SEP) stage to send a payload to outer planet targets. The IISTP studies showed that either trip time or launch vehicle class could be significantly reduced when compared with state-of-the-art systems.

Patterson, Michael J.↗
NASA NTRS2020

Machine Learning-Based Predictive Analytics for Aircraft Engine Conceptual Design

Big data and artificial intelligence/machine learning are transforming the global business environment. Data is now the most valuable asset for enterprises in every industry. Companies are using data-driven insights for competitive advantage. With that, the adoption of machine learning-based data analytics is rapidly taking hold across various industries, producing autonomous systems that support human decision-making. This work explored the application of machine learning to aircraft engine conceptual design. Supervised machine-learning algorithms for regression and classification were employed to study patterns in an existing, open-source database of production and research turbofan engines, and resulting in predictive analytics for use in predicting performance of new turbofan designs. Specifically, the author developed machine learning-based analytics to predict cruise thrust specific fuel consumption (TSFC) and core sizes of high-efficiency turbofan engines, using engine design parameters as the input. The predictive analytics were trained and deployed in Keras, an open-source neural networks application program interface (API) written in Python, with Google’s TensorFlow (an open source library for numerical computation) serving as the backend engine. The promising results of the predictive analytics show that machine-learning techniques merit further exploration for application in aircraft engine conceptual design.

deep-learning↗
DOE OSTI2016

A SPATIOTEMPORAL APPROACH FOR HIGH RESOLUTION TRAFFIC FLOW IMPUTATION

Along with the rapid development of Intelligent Transportation Systems (ITS), traffic data collection technologies have been evolving dramatically. The emergence of innovative data collection technologies such as Remote Traffic Microwave Sensor (RTMS), Bluetooth sensor, GPS-based Floating Car method, automated license plate recognition (ALPR) (1), etc., creates an explosion of traffic data, which brings transportation engineering into the new era of Big Data. However, despite the advance of technologies, the missing data issue is still inevitable and has posed great challenges for research such as traffic forecasting, real-time incident detection and management, dynamic route guidance, and massive evacuation optimization, because the degree of success of these endeavors depends on the timely availability of relatively complete and reasonably accurate traffic data. A thorough literature review suggests most current imputation models, if not all, focus largely on the temporal nature of the traffic data and fail to consider the fact that traffic stream characteristics at a certain location are closely related to those at neighboring locations and utilize these correlations for data imputation. To this end, this paper presents a Kriging based spatiotemporal data imputation approach that is able to fully utilize the spatiotemporal information underlying in traffic data. Imputation performance of the proposed approach was tested using simulated scenarios and achieved stable imputation accuracy. Moreover, the proposed Kriging imputation model is more flexible compared to current models.

Han, Lee↗
NASA NTRS1982

LANDSAT-D assessment system library computer compatible tape (LASLIB-CCT/LAS-CCT)

The format for computer compatible tapes containing thematic mapper archival data and product data generated by the LANDSAT-D Assessment System (LAS). These data tapes are engineering products developed primarily for LAS internal use to assist in the early evaluation of thematic mapper data quality and ground data processing algorithms during the limited period of one year following the launch of LANDSAT-D.

Source record↗
NASA NTRS1992

A comparison of shuttle vernier engine plume contamination with CONTAM 3.4 code predictions

In 1985, using the CONTAM 3.2 code, it was predicted that the shuttle Primary Reaction Control System (PRCS) and Vernier Reaction Control System (VRCS) engines could be potential contamination sources to sensitive surfaces located within the shuttle payload bay. Spaceflight test data on these engines is quite limited. Shuttle mission STS-32, the Long Duration Exposure Facility retrieval mission, was instrumented with an experiment that provided the design engineer with evidence that contaminant species from the VRCS engines can enter the payload bay. More recently, the most recent version of the analysis code, CONTAM 3.4, has re-examined the contamination potential of these engines.

Maag, Carl R.↗
NASA NTRS1993

Bar-Chart-Monitor System For Wind Tunnels

Real-time monitor system provides bar-chart displays of significant operating parameters developed for National Full-Scale Aerodynamic Complex at Ames Research Center. Designed to gather and process sensory data on operating conditions of wind tunnels and models, and displays data for test engineers and technicians concerned with safety and validation of operating conditions. Bar-chart video monitor displays data in as many as 50 channels at maximum update rate of 2 Hz in format facilitating quick interpretation.

Jung, Oscar↗
DOE OSTI2018

STANDARDS-BASED TECHNOLOGIES FOR EXCHANGING FATIGUE TEST DATA

Fatigue testing campaigns are a common feature in the design and operation of advanced engineering systems in the aerospace and power generation sectors. The resulting data are typically of a high inherent technical and financial value. Presently, these data are typically transferred between departments and companies by way of ad-hoc solutions reliant on obsolete or proprietary technologies, including CSV files, MS Excel® files, and PDFs. In these circumstances there is significant potential for data loss, inconsistency, and error. To address these shortcomings, there is a need for a systematic means of transferring data between different digital systems. With this in mind, a series of CEN Workshops on engineering materials data have taken place with a view to developing technologies for representing and exchanging engineering materials data. Most recently, a CEN Workshop on the topic of fatigue test data has delivered data formats derived from the ISO 12106 standard for axial strain-controlled fatigue testing. This paper describes the methodology for developing the data formats and demonstrates their use in the scope of the INCEFA PLUS project on increasing safety in nuclear power plants by covering gaps in environmental fatigue assessment.

Austin, Timothy↗
NASA NTRS1986

Particle trajectory computation on a 3-dimensional engine inlet

A 3-dimensional particle trajectory computer code was developed to compute the distribution of water droplet impingement efficiency on a 3-dimensional engine inlet. The computed results provide the essential droplet impingement data required for the engine inlet anti-icing system design and analysis. The droplet trajectories are obtained by solving the trajectory equation using the fourth order Runge-Kutta and Adams predictor-corrector schemes. A compressible 3-D full potential flow code is employed to obtain a cylindrical grid definition of the flowfield on and about the engine inlet. The inlet surface is defined mathematically through a system of bi-cubic parametric patches in order to compute the droplet impingement points accurately. Analysis results of the 3-D trajectory code obtained for an axisymmetric droplet impingement problem are in good agreement with NACA experimental data. Experimental data are not yet available for the engine inlet impingement problem analyzed. Applicability of the method to solid particle impingement problems, such as engine sand ingestion, is also demonstrated.

Kim, J. J.↗
NASA NTRSDate not supplied

Py MILab: Capturing, Analyzing and Storing Test Data

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which is heavily dependent on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results. Populating searchable information management systems with such rich data sets is often burdensome for data producers, resulting in a lack of findable data for modelers to validate and verify their models. To overcome these cultural barriers to ICME, NASA has developed of various database-integration toolsets that perform both data management activities within the organization’s best practices with additional functionality that relieves the effort of the data producer and promotes adoption of information management system. One such tool currently under development is Py MILab, an automatic framework for automatic capturing, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. TMAnalysis is a Python-based tool that performs automatic data reduction and analysis of uniaxial thermomechanical test data. The TMAnalysis toolset can be implemented within the Analysis module of Py MILab, and thus requires a populated neutral file form the Raw Data Module of Py MILab and outputs a Analysis neutral file compatible with the Database Module of Py MILab. TMAnalysis is able to perform automatic segmentation of multistage tests and perform data analysis and reduction, including determination of point-wise properties in tension, compression, and shear, analysis of stress relaxation tests, creep analysis and zone identification, and combination of these stage types for tests with complex loading histories. The TMAnalysis code is accompanied with a graphical user interface (GUI) that allows users to easily analyze test data in bulk, verify the automatic, consistent analysis performed by the backend code, and edit stage segmentation if necessary before producing the output neutral files, ensuring data is properly analyzed and maintained with full traceability.

Data management↗
NASA NTRS2018

Collaborative Systems Engineering in the Ascent Abort-2 Crew Module/Separation Ring Project

Generally speaking, systems engineering (SE) tool-sets face a dilemma balancing power and accessibility. High-powered SE tools (MagicDraw, Cradle, Core, etc.) tend to be specialized and are available only to highly trained Systems Engineers, and/or through the use of a 'back room' developer team making the output products available to the broader team. On the other hand, highly accessible tools (MS Word, Excel, etc.) do not have the power to implement SE in a rigorous manner. NASA has to test all aspects of the new human-rated Orion Multi-Purpose Crew Vehicle spacecraft prior to its first crewed mission. The test program includes uncrewed launch abort flight tests to demonstrate the capability to save the crew in the event that a launch failure occurs. Orion's second abort flight test will be a low-altitude flight test known as "Ascent Abort 2 (AA-2)." This test is currently scheduled to be carried out at Cape Canaveral Air Force Station's Space Launch Complex 46 (SLC-46) in Florida in 2019. NASA's in-house AA-2 Crew Module and Separation Ring (CSR) Team is producing the crew module and separation ring. Operating jointly as both an Advanced Exploration Systems (AES) Project and an Orion Project, the CSR project charter includes development of innovative, streamlined and generally more efficient practices for creation of flight hardware and software. One result of this tasking has been development of a collaborative and data-centric systems engineering environment within the team's shared web environment (Microsoft SharePoint). Through the use of built-in, 'out of the box capabilities' present in MS SharePoint, the CSR Systems Engineering team has created (with some limited developer support) a data-centric architecture for the project's SE implementation, including functional and interface analysis, requirements development and management, risk management, verification planning and management, test results, and end item management. Data elements are linked between data structures so as to define and control relationships between item types, link requirements to parents and children, and link tests to the requirements that they verify. The overall project team integration is increased by also linking SE content to project management content over the project life cycle, including team communication, action items, configuration management, decisional and meeting materials, and life cycle reviews. This presentation will provide an overview of the collaborative SE environment, showing how it provides the power for a number of SE tasks while still providing the accessibility and transparency to allow the full project team to collaborate and succeed. Given the project phase, we'll be able to present a nearly full lifecycle discussion, from concept through verification and approaching delivery.

Systems Engineering environments↗
NASA NTRS1964

Inflight systems monitoring.

In flight monitoring to collect data for postflight engineering analysis and determine systems reliability

DATA LINK↗
NASA NTRS2001

Hyper-X Flight Engine Ground Testing for X-43 Flight Risk Reduction

Airframe-integrated scramjet engine testing has been completed at Mach 7 flight conditions in the NASA Langley 8-Foot High Temperature Tunnel as part of the NASA Hyper-X program. This test provided engine performance and operability data, as well as design and database verification, for the Mach 7 flight tests of the Hyper-X research vehicle (X-43), which will provide the first-ever airframe-integrated scramjet data in flight. The Hyper-X Flight Engine, a duplicate Mach 7 X-43 scramjet engine, was mounted on an airframe structure that duplicated the entire three-dimensional propulsion flowpath from the vehicle leading edge to the vehicle trailing edge. This model was also tested to verify and validate the complete flight-like engine system. This paper describes the subsystems that were subjected to flight-like conditions and presents supporting data. The results from this test help to reduce risk for the Mach 7 flights of the X-43.

Huebner, Lawrence D.↗