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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 559 records · Page 31

All sources NASA NTRS DOE OSTI

DOE OSTI2026

Building the Business Case with JUSTIFI: Quantifying Multiple Benefits in the Automotive Industry

The Michigan State University Industrial Training and Assessment Center (MSU ITAC) conducted a pilot study at an automotive parts manufacturer in Michigan. The study identified energy-productivity enhancements through the application of the JUSTIFI software. Key recommendations included replacing six inefficient rooftop units (RTUs) with a new air rotational unit. By quantifying operational savings for this project, the expected payback period went from 6.6 years to 1.4 years. Additionally, the installation of variable frequency drives (VFDs) on condenser tower motors was suggested. By including all operational benefits, the payback period was reduced from 8.2 years to 1.3 years. This comprehensive analysis aims to bolster the manufacturer's goals of reducing energy while enhancing overall operational efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

A Physics-Informed Reinforcement Learning Framework for Economic-Thermal Co-Optimization of Crypto Mining Data Centers: Preprint

The rapid expansion of cryptocurrency mining has created a new class of high-density data centers characterized by extreme thermal flux and high sensitivity to volatile economic markets. Traditional thermal management strategies, typically reliant on rule-based control, maintain static setpoints that fail to account for fluctuating electricity prices and cryptocurrency values - factors critical to mining profitability. To address this, we present a physics-informed reinforcement learning (PIRL) framework for economic-thermal co-optimization in crypto mining data centers. This framework consists of a proximal policy optimization (PPO) agent, a virtual testbed powered by high-fidelity physics-based models, and an interactive frontend dashboard. The PPO agent is trained using the virtual testbed and strict hardware safety limits. This physics-informed approach allows the agent to learn a stochastic policy that dynamically balances mining revenue against operational costs by co-optimizing HVAC cooling setpoints and IT computational hashrate. The simulation results demonstrate that the integrated framework achieved an 8.62% increase in net operational profit compared to traditional baseline strategies while strictly adhering to safety-critical temperature constraints (coolant supply temperature < 32 degrees C). This work provides a scalable template for the deployment of reinforcement learning in mission critical facilities where economic volatility and physical safety must be managed simultaneously.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Unlocking Synergistic Benefits of Colocation of Data Centers at Airports

This white paper evaluates the potential of a new energy system configuration: Strategic colocation of data centers - on airport property or adjacent to airports - in order to realize significant operational, economic, and environmental benefits to airports, data centers, and the communities they serve. While increasing demand from both airports and data centers requires both parties to make significant infrastructure investments, colocation can mitigate some of the energy, land use, permitting, and connectivity challenges of siting and powering these industries.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Energy Technology Innovation Partnership Project (Bilingual)

The U.S. Department of Energy's (DOE) Energy Technology Innovation Partnership Project (ETIPP) helps coastal, remote, and island communities increase the affordability, reliability, and security of their energy systems through energy planning and deep-dive technical assistance. This is a English and Spanish translation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

Radon-induced backgrounds in the NEXT-100 experiment

The NEXT-100 detector at the LSC aims at the first competitive search for the 0νββ decay using a high-pressure $^{136}$Xe electroluminescent time projection chamber. The first low-background run of NEXT-100 at 3.95 bar has been devoted to the measurement of the radon-induced backgrounds impacting this search. The contributions from both the internal and external airborne radon have been evaluated. The internal $^{222}$Rn activity is found to be (0.95±0.04(stat)±0.09(sys)) Bq/m$^{3}$, while no traces of $^{220}$Rn have been observed. Most of the $^{222}$Rn progeny plate-out on the surface of the cathode of the detector, leading to a rate of Rn-induced $^{214}$Bi of (0.97±0.05(stat)±0.10(sys)) Hz for visible energies above 400 keV. The corresponding background index in the 0νββ region of interest is evaluated as (7.3±1.5(stat)±0.8(sys))×10$^{−4}$ counts/(keV·kg·yr) after selection of the fully contained events. This background index is reduced to ∼4×10$^{−5}$ counts/(keV·kg·yr) by applying a topological selection requiring only one double-electron-like track in the events. This value is one order of magnitude below the total radiogenic background expectation in NEXT-100. By analyzing the correlation of the airborne radon activity and the measured rate of events in NEXT-100, it is concluded that the detector operates in a virtually radon-free environment thanks to the radon abatement system of the LSC.[graphic not available: see fulltext]

Cortes-Parra, C. [Valencia U., IFIC] (ORCID:000000↗

DOE OSTI2026

Navigating Large Chemical Spaces Using Graph Theory and Integer Programming

Navigating and analyzing large chemical spaces are necessary to accelerate the design and discovery of new molecules and chemical processes. In this work, we introduce a computational framework that integrates graph theory and integer programming to enable the efficient navigation of large chemical spaces. Our framework represents the chemical space as a graph, wherein nodes represent molecules and edges represent the degree of similarity or connectivity based on domain-specific information. Using the graph representation, we identify representative molecules by computing the so-called minimum dominating set (MDS), which in our context is the minimum set of molecules that is connected to all other molecules. We present a suite of solution strategies for the MDS problem including heuristic and rigorous integer programming (IP) approaches. We show that these approaches allow us to capture physicochemical properties and domain-specific logic and constraints, facilitating the identification of molecules with the target properties. We demonstrate the effectiveness of the proposed approach by navigating the chemical space of per- and polyfluoroalkyl substances (PFAS); this comprises approximately 15,000 molecular structures. We compare our framework against traditional dimensionality reduction and clustering methods such as t-SNE and K-means clustering.

Chemical structure↗

DOE OSTI2026

Unraveling TeV halos with the Cherenkov Telescope Array

Pulsars are observed to emit bright and spatially extended gamma-ray emission at multi-TeV energies. These so-called "TeV halos" are now understood to be a nearly universal feature of middle-aged pulsars. However, many of the key physical processes that govern these systems, particularly those affecting particle diffusion, remain poorly constrained. We aim to evaluate the ability of the Cherenkov Telescope Array (CTA) to probe the physical properties of TeV halos, with a focus on the nearby and well-studied case of the Geminga pulsar. We simulate gamma-ray emission from various TeV halo models, incorporating different assumptions for the injected electron spectrum, spin-down evolution, and energy-dependent diffusion. These models are then used to forecast CTA's sensitivity to spectral and spatial differences, based on realistic mock observations and instrument response simulations. We find that CTA will be able to distinguish between a wide range of TeV halo models that are currently consistent with existing data. In particular, CTA observations can constrain the normalization, energy dependence, and spatial extent of the diffusion coefficient surrounding Geminga, as well as the spectral shape of the injected electron population.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

AmeriFlux US-LMA Mississippi ARS Arant ASP

This is the AmeriFlux version of the carbon flux data for the site US-LMA Mississippi ARS Arant ASP. Site Description - Field

Witthaus, Lindsey [USDA ARS]↗

DOE OSTI2026

AmeriFlux US-NYa NYSM - Voorheesville

This is the AmeriFlux version of the carbon flux data for the site US-NYa NYSM - Voorheesville. Site Description - Located in an orchard/vineyard setting. It is an open area surrounded by orchards and some larger trees. Obstructions within 100m include some orchards/trees. The soil type is chenango gravelly silt loam, loamy substratum. This site is a part of the New York State Mesonet Flux Network, one of multiple subnetworks (e.g. Profiler, Snow) operated by the New York State Mesonet. It also operates as a Standard meteorological site.