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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

ARENA: Adversary-Resistant Evolving Neural Architectures

Neural networks are becoming the cornerstone for national security prediction tasks. However, designing them requires significant research and trial/error, as they have many hyperparameters, including their computation graph (“architecture”). Neural architecture search (NAS) employs secondary optimizers to search for architectures maximizing objectives like accuracy. Evolutionary algorithms (EAs) are the most used class of optimizer for NAS. However, existing Python libraries for writing EAs limit the complexity of experiments a user can design. In this project, we built ARENA, a Python framework that encodes complex, hyper-realistic EAs. ARENA collects detailed information as it runs and is flexible enough to encode non-EA search algorithms. We tested ARENA on 4 toy optimization problems by encoding 3 search algorithms for each—random search, an EA, and simulated annealing. We also designed an EA that performs NAS on the MNIST dataset. Our experiments suggest the potential for immediate mission impact through solving lab-wide optimization problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Integrating Artificial Intelligence into Science Gateways

Science gateways are altering the manner in which people interact with high performance computing (HPC) by providing a web browser based interface to advanced computing platforms. In particular, science gateways lower the barrier to using HPC by simplifying the process of submitting workloads to such systems and by offloading the efforts required to use HPC to the maintainers of the system. While science gateways decrease the time-to-science that comes with using such advanced systems, progress can still be made in improving the user's experience. In this paper we explore two strategies for integrating artificial intelligence tools commonly found in non-HPC service workflows: voice activated assistants and chatbots. Since August 2021, the HPC group at Idaho National Laboratory answers an average of 581 support tickets per month of which a large percentage could be addressed via these two strategies. This work defines the key capabilities that an HPC voice activated assistant and chatbot would need to address for a userbase consisting of largely non-expert users as well as a design for integration into the Open OnDemand science gateway.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

Advancing User Supports with a Structured How-To Knowledge Base for Earth Science Data

It is a challenge to access and process fast growing Earth science data from satellites and numerical models, which may be archived in very different data format and structures. NASA data centers, managed by the Earth Observing System Data and Information System (EOSDIS), have developed a rich and diverse set of data services and tools with features intended to simplify finding, downloading, and working with these data. Although most data services and tools have user guides, many users still experience difficulties with accessing or reading data due to varying levels of familiarity with data services, tools, and/or formats. A type of structured online document, data recipe, were created in beginning 2013 by Goddard Earth Science Data and Information Services Center (GES DISC). A data recipe is the How-To document created by using the fixed template, containing step-by-step instructions with screenshots and examples of accessing and working with real data. The recipes has been found to be very helpful, especially to first-time-users of particular data services, tools, or data products. Online traffic to the data recipe pages is significant to some recipes. In 2014, the NASA Earth Science Data System Working Group (ESDSWG) for data recipes was established, aimed to initiate an EOSDIS-wide campaign for leveraging the distributed knowledge within EOSDIS and its user communities regarding their respective services and tools. The ESDSWG data recipe group started with inventory and analysis of existing EOSDIS-wide online help documents, and provided recommendations and guidelines and for writing and grouping data recipes. This presentation will overview activities of creating How-To documents at GES DISC and ESDSWG. We encourage feedback and contribution from users for improving the data How-To knowledge base.

how-to↗
DOE OSTI2024

MaDEVIoT: Cyberattacks on EV Charging Can Disrupt Power Grid Operation

Extensive roll-out of electric vehicles (EVs) requires large-scale deployment of high-power EV Charging Stations (EVCSs). EVCSs are connected to the internet using Internetof- Things (IoT) such as smartphones, to improve the charging experience of users and increase their profitability. This paper studies the feasibility of demand-side cyberattacks launched on power grids via such internet-connected highpower EVCSs. The attack mechanism distorts power grid frequency and voltage, and has the potential to trigger systemwide outages. The case study, based on the power grid and EV deployment plans in Manhattan, New York, illustrates potential impacts of such attacks. The results show that such attacks will become feasible in Manhattan, New York in 2030, as EV adoption increases. Furthermore, the attacks in 2030 are feasible even compromising a single company’s EVCS server in Manhattan, New York. The attacks can cause line overloads and trip over-frequency protection relays, causing system-side blackout in the power grid in Manhattan, New York. The paper informs planning authorities and power grid operators involved with the roll-out of EV charging infrastructure about potential cyberthreats to power grids via manipulating internet-connected high-power EVCSs.

Acharya, Samrat S.↗
DOE OSTI2021

Status of the Optical Dilatometer Method of Evaluating the Peak Irradiation Temperatures of SiC Passive Monitors

The main objective of this project was to conduct a comparative assessment between the optical dilatometer method and resistivity method, using all 10 SiC temperature monitors provided by two Nuclear Science User Facility experiments: BSU-8242 and General Electric Hitachi. Unfortunately, due to multiple delays in acquiring, shipping, and cleaning the SiC temperature monitors, the project was only able to process one (1) SiC temperature monitor during this period. SiC temperature monitor KGT-3357 was evaluated via the optical dilatometer method to determine its peak irradiation temperature. The KGT-3357 sample was from the BSU-8242 experiment and designed for a temperature of 300°C and an exposure of 1 dpa. The optical dilatometer measurements indicated that the KGT-3357 SiC temperature monitor’s peak irradiation temperature range was 240–267°C, with sensitivity of approximately ±20°C. Additionally, this temperature range falls within the evaluated melt wire temperature range of 238.6–271.5 °C. The remaining six (6) SiC temperature monitors from the BSU-8242 experiment and three (3) from the General Electric Hitachi experiment will be used in the future work to further validate the optical dilatometer method for measuring SiC peak irradiation temperatures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Fostering Geothermal Machine Learning Success: Elevating Big Data Accessibility and Automated Data Standardization in the Geothermal Data Repository

The Department of Energy's (DOE) Geothermal Data Repository (GDR) has implemented improvements to both its data lakes and its data standards and automated data pipelines. The GDR data lakes have reduced storage and compute-related barriers to using large geothermal datasets, enabling these large datasets to be accessed by anyone with a modern computer and internet access. More recently, the GDR has been working to further reduce barriers through streamlining the data intake process, educating users on the process and requirements, and aiding users in accessing data from the data lakes. These improvements have augmented the quantity of datasets the GDR is able to accept into its data lakes and have enabled users who are new to cloud tools to access these datasets more easily, overall increasing the accessibility of big geothermal data for use in machine learning and other projects. In addition, the GDR now has built-in data standards and pipelines for drilling data, geospatial data, and distributed acoustic sensing (DAS) data. These standardization efforts aim to enhance the real-world applicability of geothermal machine learning outcomes by improving the quality of training data. Specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, thus allowing more time for actual research. By automating this process, the burden of standardization is lifted from the user, ultimately increasing the availability of standardized data.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

A Portable Wave Tank and Wave Energy Converter for Engineering Dissemination and Outreach

Wave energy converters are a nascent energy generation technology that harnesses the power in ocean waves. To assist in communicating both fundamental and complex concepts of wave energy, a small-scale portable wave tank and wave energy converter have been developed. The system has been designed using commercial off-the-shelf components, and all design hardware and software are openly available for replication. This project builds on prior research conducted at Sandia National Laboratories, particularly in the areas of WEC device design and control systems. By showcasing the principles of causal feedback control and innovative device design, SIWEED not only serves as a practical demonstration tool but also enhances the educational experience for users. This paper presents the detailed system design of this tool. Furthermore, via testing and analysis, we demonstrate the basic functionality of the system.

educational↗
DOE OSTI2026

PVDeg: Enhancing Usability and AI-Driven Multi-Mechanism Degradation Modeling

PVDeg version 0.7.0, released in December 2025, introduced major enhancements to improve usability and performance. This update reorganized tutorials and tool notebooks to create a more intuitive experience, enabling users to easily follow and adapt workflows for their specific analyses. In addition to structural improvements, both the notebooks and core logic underwent significant optimization for efficiency, robustness, and style. These refinements were supported by new testing frameworks built on nbval and pytest, adherence to PEP8 standards, and extensive code refactoring, which collectively simplify onboarding for new developers. Looking ahead, version 0.8.0 will deliver advanced AI-driven capabilities. The primary focus is to further develop and automate the degradation workflow, designed to analyze PV module degradation across diverse locations and system configurations. By integrating large language models (LLMs) to scan literature and compile a comprehensive database of materials and degradation rates, this feature will enable modeling of multiple materials and mechanisms within a single, streamlined workflow. Users will be able to evaluate degradation impacts on different system architectures under varying environmental conditions, facilitating informed decisions on bill-of-materials optimization for specific deployment scenarios. These advancements position PVDeg as a powerful, user-friendly tool for accelerating PV reliability research and system design.

14 SOLAR ENERGY↗
DOE OSTI2020

Electrification Futures Study Flexible Load Profiles

This data set includes hourly profiles for flexible load developed for the Electrification Futures Study (EFS). The load profiles represent projected end-use electricity demand that is assumed to be flexible (i.e., can be shifted throughout a day) for various scenarios of flexibility (Base, Enhanced), electrification (Reference, Medium, High), and technology advancement (Slow, Moderate, Rapid), and were developed as inputs into the ReEDS model. The quantity of flexible load is estimated using assumptions on the level of flexibility and customer participation within each subsector modeled in the EFS. Detailed assumptions and modeling implementation will be documented in ongoing EFS analyses. Flexible load profiles are provided for a subset of years (2018, 2020, 2024, 2030, 2040, 2050) and are aggregated to the state and sector level. Total electricity load profiles can be found in a related EFS data set (https://dx.doi.org/10.7799/1593122). NOTE: Due to the file size, Mac users may experience issues decompressing the zip files using the Mac Archive Utility. In those cases, decompressing using the command line is recommended. - Mai, Trieu, Paige Jadun, Jeffrey Logan, Colin McMillan, Matteo Muratori, Daniel Steinberg, Laura Vimmerstedt, Ryan Jones, Benjamin Haley, and Brent Nelson. 2018. Electrification Futures Study: Scenarios of Electric Technology Adoption and Power Consumption for the United States. National Renewable Energy Laboratory. NREL/TP-6A20-71500. https://doi.org/10.2172/1459351. - Murphy, Caitlin, Trieu Mai, Yinong Sun, Paige Jadun, Matteo Muratori, Brent Nelson, Ryan Jones. Forthcoming. Electrification Futures Study: Scenarios of Power System Evolution and Infrastructure Development for the United States. National Renewable Energy Laboratory. - Sun, Yinong, Paige Jadun, Brent Nelson, Matteo Muratori, Caitlin Murphy, Jeffrey Logan, and Trieu Mai. Forthcoming. Electrification Futures Study: Methodological Approaches for Assessing Long-Term Power System Impacts of End-Use Electrification. National Renewable Energy Laboratory.

buildings↗
NASA NTRS1975

NASA Office of Aeronautics and Space Technology Summer Workshop. Volume 4: Power technology panel

Technology requirements in the areas of energy sources and conversion, power processing, distribution, conversion, and transmission, and energy storage are identified for space shuttle payloads. It is concluded that the power system technology currently available is adequate to accomplish all missions in the 1973 Mission Model, but that further development is needed to support space opportunities of the future as identified by users. Space experiments are proposed in the following areas: power generation in space, advanced photovoltaic energy converters, solar and nuclear thermoelectric technology, nickel-cadmium batteries, flywheels (mechanical storage), satellite-to-ground transmission and reconversion systems, and regenerative fuel cells.

Source record↗
NASA NTRS1980

The spatial resolving power of earth resources satellites: A review

The significance of spatial resolving power on the utility of current and future Earth resources satellites is critically discussed and the relative merits of different approaches in defining and estimating spatial resolution are outlined. It is shown that choice of a particular measure of spatial resolution depends strongly on the particular needs of the user. Several experiments have simulated the capabilities of future satellite systems by degradation of aircraft images. Surprisingly, many of these indicated that improvements in resolution may lead to a reduction in the classification accuracy of land cover types using computer assisted methods. However, where the frequency of boundary pixels is high, the converse relationship is found. Use of imagery dependent upon visual interpretation is likely to benefit more consistently from higher resolutions. Extraction of information from images will depend upon several other factors apart from spatial resolving power: these include characteristics of the terrain being sensed, the image processing methods that are applied as well as certain sensor characteristics.

Townshend, J. R. G.↗
NASA NTRS1985

Advanced software tools space station focused technology

Information is given in outline form on advanced software tools for the Space Station data management system. The Space Station data management system is identified as a highly distributed system with payload users controlling experiments and processing payload data from home facilities.

Nelson, Robert W.↗
NASA NTRS1989

Land image data processing requirements for the EOS era

Requirements are proposed for a hybrid approach to image analysis that combines the functionality of a general-purpose image processing system with the knowledge representation and manipulation capabilities associated with expert systems to improve the productivity of scientists in extracting information from remotely sensed image data. The overall functional objectives of the proposed system are to: (1) reduce the level of human interaction required on a scene-by-scene basis to perform repetitive image processing tasks; (2) allow the user to experiment with ad hoc rules and procedures for the extraction, description, and identification of the features of interest; and (3) facilitate the derivation, application, and dissemination of expert knowledge for target recognition whose scope of application is not necessarily limited to the image(s) from which it was derived.

Wharton, Stephen W.↗
NASA NTRS1991

Spatial orientation and dynamics in virtual reality systems - Lessons from flight simulation

Artificial representations of virtual worlds are becoming more common due to advances in the technology of image generation and display systems. Application areas include flight simulation, mission rehearsal, teleoperator systems, and virtual reality systems. System developers should be forewarned that some proportion of users will experience perceptual anomalies and symptoms of motion sickness as a result of travel through virtual space.

Mccauley, Michael E.↗
NASA NTRS1993

Timing in private digital telecommunication networks

For proper operation of today's large digital private networks, high quality synchronization must be achieved. A general telecommunication performance objective is to maintain long-term frequency accuracy of ten parts per trillion at all synchronous digital equipment in the network. Many times, however, this is not achieved in private networks. Low quality clocks, errored transmission facilities, and incorrectly designed synchronization plans are often cause for poor performance. It is shown that properly-designed private networks can operate with long term frequency averages between ten parts per trillion to ten parts per million. These performance levels can adversely impact customer applications. The most demanding applications are digital and voice band data, encrypted voice, facsimile, and video. In a typical private network operating at 0.01 parts per million, the user would experience reduced data throughput, dropped encrypted calls, unreadable facsimile pages, or interrupted video transmission dozens of times per day. The major contribution to poor private network synchronization performance is the interaction of Customer Premises Equipment (CPE) clocks and the network facilities used to distribute timing. The performance of typical CPE clocks and facilities, and their impact on customer applications, are discussed. CPE clock performance issues, along with private network architectural constraints, make synchronization planning extremely difficult. Planning is usually costly and requires specialized expertise.

Abate, J. E.↗
NASA NTRS1994

Interface issues for on-board propulsion systems

Integration issues associated with the use of new chemical and electric propulsion technologies are a primary concern to the user community. Experience indicates that integration impacts must be addressed to the satisfaction of both spacecraft builders and operators prior to the acceptance of new propulsion systems. The NASA Lewis Research Center (LeRC) conducts an aggressive program to develop and transfer new propulsion technologies and this includes a major effort to identify and address integration issues associated with their use. This paper provides an overview of integration issues followed by a brief description of the spacecraft integration program at LeRC.

Curran, Frank M.↗