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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

DEVELOP Poster: Medicine Bow Disasters

The Medicine Bow National Forest (MBNF) consists of approximately 1,383,790 acres of forested land, grassland, and sagebrush steppe in southeastern Wyoming. Cheatgrass (Bromus tectorum), an invasive plant species in the Western US, occurs in the grasslands throughout MBNF. Cheatgrass is known to rapidly colonize disturbed sites and dramatically alter historic fire regimes and nutrient/water dynamics as well as outcompete native plant species that are important forage for mule deer (Odocoileus hemionus) and elk (Cervus canadensis). In 2012, the Squirrel Creek Fire burned approximately 10,587 acres of land within MBNF, exacerbating the spread of cheatgrass. In 2015, the Wyoming Ecological Forecasting DEVELOP team identified areas of high cheatgrass abundance within the fire boundary in order to guide US Forest Service (USFS) herbicide spraying efforts to reduce cheatgrass in 2016. This research used Landsat 8 Operational Land Imager (OLI) and Sentinel-2 MultiSpectral Instrument (MSI) data to create a 2019 probabilistic cheatgrass occurrence map. This map allowed an analysis of the effectiveness of aerial spraying to inform future land management techniques for the USFS. Based on the results of the Generalized Linear Model, we found that treated areas decreased in cheatgrass cover by 36% while untreated areas increased in cheatgrass cover by 6%, suggesting that herbicide treatment has been effective.

Disasters↗
NASA NTRS2020

DEVELOP Poster: Louisville Urban Development

Greenness and land surface temperature (LST) have been extensively correlated to urban public health. Chronic diseases such as diabetes, asthma, and cardiovascular illnesses have been linked to regions of high LST and areas lacking urban green spaces. One of our partners, the University of Louisville Envirome Institute, champions the importance of urban green spaces. Their research has pioneered efforts in increasing the area and accessibility of urban parks and greenspaces as a way to improve public health and combat environmental inequality. Louisville, Kentucky, is currently working to plant and manage urban trees. Our team used NASA Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) imagery to calculate the Normalized Difference Vegetation Index (NDVI) in Louisville at the census tract level and automated the process for use in other cities. The New York University School of Medicine’s City Health Dashboard displays public health metrics across 500 US cities and will use our methods to complete the NDVI analysis for all of these locations plus an additional 293 cities they are adding to their dashboard in the near future. Our NDVI and LST calculations will allow cites across the US to make informed decisions about reducing environmental inequality by focusing on areas with low NDVI and high LST.

Urban Development↗
DOE OSTI2024

Architecture Design for Remote Operation of Microreactors: Poster

The nuclear sector is pursuing a number of advanced reactor concepts, one of which is the microreactor, an advanced reactor characterized by a power output of less than 20 MWth. These reactors are intended for use in applications where traditional power solutions are economically or logistically impractical. One key feature required for the successful deployment of microreactors is a remote operation capability, which can dramatically cut staffing expenses by eliminating the need for licensed operators to be present at the site of each reactor and instead concentrate in a centrally located operations center. In moving to a remote operations framework for nuclear reactors, the number of potential attack surfaces for a cyber adversary looking to cause harm or disruption increases. Therefore, a robust cybersecurity architecture is required to mitigate these potential vulnerabilities. This paper explores the functional infrastructure, security, and communication requirements to adapt remote operations to nuclear applications. It then presents a reference architecture for remote operations of microreactors that applies best practices in cybersecurity and remote communications in the context of a digital twin remote operation system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Poster Abstract: Leveraging Large Language Models to Reveal Interpretable Cooling Behaviors from Smart Thermostat Data

Frequent heatwaves and hot summers increasingly challenge occupant comfort, health, and energy grid stability. Addressing these challenges requires a detailed understanding of household cooling behaviors, such as thermostat adjustments and adaptive responses to extreme conditions. Traditional analyses often rely on aggregated numerical metrics that overlook subtle but important household-specific variations. In this study, we introduce a generalizable methodology that integrates large language models (LLMs) with vision capabilities to enable scalable and detailed analysis of residential thermostat data. Using Ecobee's Donate Your Data (DYD) dataset—which provides five-minute records of indoor temperatures, thermostat setpoints, and HVAC runtimes—we focus on two U.S. cities with contrasting summer climates : Austin (TX) and Phoenix (AZ). Because raw time-series data are not well suited for direct LLM analysis, we transform them into visual representations, such as daily indoor temperature trajectories and weekly runtime histograms, to better capture behavioral variations. Leveraging LLMs' visual interpretation, we extract descriptive behavioral features, including temperature preferences, time-of-day cooling orientation, anticipatory versus reactive heatwave responses, and behavioral consistency. These semantic features support unsupervised clustering to identify distinct occupant archetypes at scale, revealing differences—such as morning-centric anticipatory coolers versus households that shift toward warmer setpoints during heatwaves—that can inform demand response, resilience planning, and health-aware interventions. By converting raw numerical data into interpretable behavioral patterns, this methodology enables scalable and practical analysis of occupant behavior, supporting actionable insights for comfort, resilience, and energy management.

Nihar, Kopal↗
DOE OSTI2024

Enhanced PDV waveform search and analysis method using parallel circular-convolution / cross-correlation for improved dynamic surface velocity extraction [Poster]

Previous work on exhaustive search methodologies for extracting best-match parameters pertaining to dynamic surface quantities from PDV was done by cross-correlating synthetically generated PDV waveforms with observed counterparts using the circular-convolution theorem. This work was further developed into an open-source PDV analysis toolkit called CCPDVANALYSIS which expands upon and enhances the previously tested methods by parallelizing serial algorithmic components and incorporating a comprehensive script library for different flavors of instantaneous frequency functions utilized in generating synthetic PDV waveforms. Results of these enhancements have been shown to markedly decrease execution times of exhaustive search and extraction algorithms and produce improved velocity recoveries for low-velocity and dynamically varying velocity signals. The CCPDVANALYSIS script library demonstrates an advanced method for extracting velocities from low-velocity and non-constant velocity signals further extending and improving the methods beyond capabilities of traditional frequency domain tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

2024 Geothermal Rising Conference Poster

As part of a U.S. DOE Geothermal Technologies Office funding opportunity, Geysers Power Company, LLC, an indirect subsidiary of Calpine Corporation, partnered with Sandia National Labs, EGI at the University of Utah, and Texas A&M University to demonstrate increased drilling performance at The Geysers Geothermal Field. The performance target in the drilling demonstrations is at least a 25% improvement in rates of penetration with increased time on bottom for each bit. The planned drilling demonstrations are being conducted as part of an existing drilling campaign intended to enhance reservoir utilization. A major goal of the project is to assess the effectiveness of implementing mechanical specific energy (MSE) and drilling dysfunction diagnosis and remediation in these challenging environments, as well as alternate bit technologies. The first demonstration well has been completed, with a total of 15 PDC bit runs in the 17.5”, 12.25” and 8.5” sections. Initial analysis shows ROP gains in all three hole sections, especially in the 17.5” and 12.25” sections, compared with conventional roller cone bit runs in the demonstration well and offset wells. However in the 8.5” hole, wear and damage to the PDC bits resulted in relatively short bit runs. Analysis is underway to take advantage of the positive results and remediate the challenges.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

In Situ, Real-Time Diagnostic to Improve the Liquid Metal Jetting Additive Manufacturing Process [Poster]

Liquid Metal Jetting (LMJ) is a metal additive manufacturing technique that involves jetting molten metal droplets at high frequencies to build solid metal parts. As an alternative to industry standard Lazer Powder Bed Fusion (LPBF) and Direct Metal Writing (DMW) techniques, LMJ poses significant advantages including no powder feed stock, no post sintering process, very high deposition rates, and the capability to print various metals. This summer, I was tasked with improving my old system to process at much higher resolution, Increasing the capture rate, and implementing this diagnostic on various LMJ setups. This system provides a vital longitudinal study to understand individual droplets in the LMJ process.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Comparative Analysis of DNA LLM Classification Techniques Using Intra-Layer Feature Extraction with Autoencoder Stacks [Poster]

This project conducts a comparative analysis of DNA LLM classification techniques using Evo2, Grover, and UTRML, focusing on intra-layer feature extraction in Evo2. By extracting features from multiple layers of Evo2 and integrating them into an autoencoder stack with a binary classification head, we evaluate its effectiveness in classifying genomic sequences compared to smaller DNA language models. My findings demonstrate that Evo2 outperforms Grover and UTRML in classification accuracy on a dataset provided by department 08625, CAO2021, while UTRML offers competitive performance with lower computational costs. This study highlights the potential of advanced embedding techniques in enhancing genomic data analysis and informs future research in bioinformatics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Optimizing Adhesion: Evaluating B-Stage Epoxy for Bonding [Poster]

The application of increased pressure during the curing process of B-stage epoxy has been hypothesized to enhance the adhesive properties and bond strength in printed wiring board (PWB) assembly. This study aimed to investigate the correlation between pressure application and the performance of B-stage epoxy.

42 ENGINEERING↗
DOE OSTI2025

Broadband mm-Wave Substrate Integrated Waveguides [Poster]

At mm-wave frequencies, signals need to be supported by specialized, low-loss transmission lines such as waveguides. Substrate-integrated waveguides (SIWs) combine the good electrical properties of rectangular waveguides with the compactness of planar transmission lines. Additionally, SIWs can be fabricated using standard PCB manufacturing techniques and can be easily integrated with other mm-wave components. This study explores SIWs in the 50-75 GHz range, with designs optimized for simple fabrication.

42 ENGINEERING↗
DOE OSTI2025

Roxana Paramo Ramirez: MSIIP 2025-2026 Internship [Poster]

At Sandia National Laboratories, there is a high level of importance placed on identifying and developing solutions to the nation’s current and future security problems. One of these problem would be hardware electronics validation and verification.

42 ENGINEERING↗
DOE OSTI2025

Electrochemical Production of Calcium Hydroxide from Calcium Carbonate [Poster]

Cement production involves the decomposition of limestone (calcium carbonate) at high temperatures (~900°C) to produce CaO, a major constituent in Portland cement (60-70%). Our unique approach will eliminate the high temperature process and introduce a low-temperature electrochemical process to produce Ca(OH) 2 which can be converted into CaO through dehydration process. This program will allow SRNL to become a leading organization in an open and unexplored field that addresses many of the technical challenges.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Preliminary Comparison of Neutron Detector Sensitivities [Poster]

Nuclear data (ND) is vital to predictive simulations such as those completed with MCNP®. ND sensitivities are used to optimize the design of benchmark experiments. Diverse benchmarks (including neutron noise) are required to further our understanding of ND. Measured and simulated data of a 4.5-kg Pu sphere was used to calculate neutron noise parameters and associated ND Sensitivities

Nuclear Criticality Safety Program (NCSP)↗