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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Improving Thermal Management Strategies for Data Centers: A Physical Testbed Incorporating Small Modular Reactor and Microreactor Technology

This study aims to accelerate the demonstration of various thermal management systems for data centers using nuclear-generated heat to enhance energy and grid reliability. Utilizing mobile containerized and stationary test beds at INL's High Performance Computing (HPC) facility, this project integrates with various nuclear-related energy systems testing facilities. Key components include immersion cooling apparatus, absorption chillers, and adjustable thermal management simulators. Tasks involve acquiring necessary hardware, sensors, and cooling apparatus, engaging with data center industry stakeholders, and providing a testing platform for algorithms, models, tools, and software. The objective is to expedite the deployment of nuclear-powered data centers, thereby improving energy reliability and affordability.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2026

Holistic energy analysis method for thermal management architectures of data centers

Modern high-performance computing (HPC) data centers (DCs), particularly those supporting energy-intensive artificial intelligence (AI) workloads, face escalating thermal management challenges that degrade performance through thermal throttling and drive up cooling power consumption and operational costs. To address this challenge, many have developed a wide variety of thermal management solutions (single-phase, two-phase, direct, indirect, hybrid, and more) which attempt to cool HPC DCs effectively while attempting to minimize overall system power consumption. However, the analysis of these solutions and methods to effectively compare one with another is lacking. Overall power usage effectiveness (PUE) and total-power usage effectiveness (TUE) provide a metric to quantify power consumption but fail to identify components in the system which require further optimization. To address this, we propose a holistic analytical framework – the waterfall diagram (WFD) – which leverages a waterfall chart methodology, offering a comprehensive visualization of both the thermal management system loop and heat flow pathways from individual server components to the outdoor ambient. Use of the WFD enables graphical estimations of power efficiency and cooling performance across each component of a DC cooling system and complements Sankey-style energy flow visualizations by additionally resolving stage-wise temperature changes and incremental TUE contributions. The framework is used in conjunction with simulation-based approaches, to conduct a detailed pressure drop and flow distribution analysis aimed at identifying the optimal coolant distribution architecture for a single-phase direct-to-chip water-cooled DC, which serves as the baseline for subsequent WFD analysis. Among the evaluated architectures, the 3 U modular coolant distribution architecture is found to demonstrate the best performance, considering minimal pressure drop and uniform flow distribution. In addition, TUE is calculated for each cooling loop component based on its associated pressure drop and corresponding pumping power, which are integrated into the WFD. This correlation between TUE and local temperature offers immediate insight into the power efficiency and thermal performance contributions of individual components, facilitating further development and optimization. Examples of WFD applications are presented under varying thermal loads and ambient conditions, demonstrating reasonable cooling strategies. Notably, the 3 U modular architecture maintains a consistent chip case temperature of 85°C, achieving a TUE of 1.016 at ambient temperature of 47°C, and a TUE of 1.026 at ambient temperature of 52°C. The WFD methodology provides an efficient, holistic, and streamlined framework for DC thermal management architecture assessment and enables design optimization which is important for addressing the thermal-fluidic energy challenges of current and next-generation DCs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Accelerating nuclear-integrated data center pursuits in the USA: SWOT analysis, power-thermal management strategies and demonstration plan

Here, this study explores the increasing interest in leveraging nuclear power to meet the escalating energy demands of data centers in the United States (U.S.) by focusing on key factors that contribute to accelerated deployment. The study highlights the importance of N+1/N+2 power supplies (where N is the required number of units), outlines research and innovations in nuclear-integrated data center thermal management and demonstration plan. It also provides updates about status and costing of various reactor system designs. A summarized strengths, weaknesses, opportunities, and threats (SWOT) analysis shows the potential options for grid connectivity, reactors, and site selection. Suitable site discussions consider land and water availability, grid access, and optical fiber connectivity, and the study presents graded prospects for Department of Energy (DOE) sites with a specific example. Community engagement and partnerships are emphasized, particularly the roles of local government, federal agencies, utilities, and data center industry partners, which are crucial for accelerating deployment, business outreach, and approvals. The study provides actionable insights for stakeholders to accelerate the deployment of nuclear-powered data centers.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2025

LC-Opt: Benchmarking Reinforcement Learning and Agentic AI for End-to-End Liquid Cooling Optimization in Data Centers

Liquid cooling is critical for thermal management in high-density data centers with the rising AI workloads. However, machine learning-based controllers are essential to unlock greater energy efficiency and reliability, promoting sustainability. We present LC-Opt, a Sustainable Liquid Cooling (LC) benchmark environment, for reinforcement learning (RL) control strategies in energy-efficient liquid cooling of high-performance computing (HPC) systems. Built on the baseline of a high-fidelity digital twin of Oak Ridge National Lab's Frontier Supercomputer cooling system, LC-Opt provides detailed Modelica-based end-to-end models spanning site-level cooling towers to data center cabinets and server blade groups. RL agents optimize critical thermal controls like liquid supply temperature, flow rate, and granular valve actuation at the IT cabinet level, as well as cooling tower (CT) setpoints through a Gymnasium interface, with dynamic changes in workloads. This environment creates a multi-objective real-time optimization challenge balancing local thermal regulation and global energy efficiency, and also supports additional components like a heat recovery unit (HRU). We benchmark centralized and decentralized multi-agent RL approaches, demonstrate policy distillation into decision and regression trees for interpretable control, and explore LLM-based methods that explain control actions in natural language through an agentic mesh architecture designed to foster user trust and simplify system management. LC-Opt democratizes access to detailed, customizable liquid cooling models, enabling the ML community, operators, and vendors to develop sustainable data center liquid cooling control solutions.

Naug, Avisek [Hewlett Packard Enterprise]↗
DOE OSTI2026

A Novel and Scalable Method for Microencapsulating Salt Hydrate Phase Change Materials in Core–Shell Fibers

Phase change materials (PCMs) are in high demand for applications such as thermal energy storage in buildings, electronics cooling, and thermal management of electric vehicle batteries and data centers. Among these materials, salt hydrate PCMs are particularly attractive due to their high thermal energy storage capacity and low cost. However, they suffer from two major issues: leakage in the melted phase and phase segregation during phase transitions. Microencapsulation is the primary process capable of addressing both of these challenges. However, there is no reliable or scalable method available for microencapsulating salt hydrate PCMs. As a result, the full potential of salt hydrates for building and data center applications has yet to be realized. In this work, we present an innovative method for the microencapsulation of salt hydrate PCMs using a co‐axial pushing technique. This process creates core–shell fibers, with the salt hydrate as the core and a polymer as the shell. Our approach demonstrates strong potential for scalable microencapsulation of salt hydrate PCMs. In conclusion, achieving scalability could enable their widespread use in applications such as data center cooling, battery thermal management, and building climate control.

Sharma, Jaswinder [Oak Ridge National Laboratory (↗
DOE OSTI2026

Revolutionizing thermal Management in Next-Generation AI data centers: Challenges and breakthrough innovations

Data centers (DCs) serve as critical infrastructure for powering the growth and evolution of AI. Next-generation AI DCs present unique challenges in thermal management driven by unprecedented computational demands. This paper provides a comprehensive summary of key stakeholder perspectives on technology gaps, infrastructure requirements, test bed needs, emerging opportunities, and preliminary solutions related to thermal management for AI DCs. It establishes six strategic pillars of thermal management for next generation AI DC: reliability, deployability, efficiency, resilience, measurability, and valorization. The discussion spans a range of critical topics, including advanced cooling technologies, thermal strategies for emerging modular and edge DCs, system-level optimization and control frameworks, infrastructure planning and grid integration designs, benchmarking approaches, and pathways for waste heat recovery and reuse. The proposed research, development, and demonstration efforts are aimed at accelerating the deployment of AI DCs while ensuring energy efficiency, reliability, safety, and regulatory compliance.

Wang, Pengtao [ORNL] (ORCID:0000000214713429)↗
DOE OSTI2026

Ultra-low thermal resistance and pressure drop copper and copper-tungsten diamond-shaped pin fin cold plates for liquid cooling of electronics

Modern and future data centers face increasing cooling challenges due to increasing chip thermal design power and die size, along with the need to reduce energy consumption used for cooling. High performance cooling solutions that maintain a low chip junction temperature are needed to ensure electronics reliability. This work develops an ultra-low thermal resistance and low pressure drop 75 mm × 75 mm cold plate, intended for next-generation electronics cooling. The cold plate features an array of diamond-shaped pin fins and integrated copper tungsten heat spreader, selected for its low coefficient of thermal expansion which reduces thermomechanical deformation and allows for closer integration of the cold plate with silicon dies. Starting with 300 candidate designs, three-dimensional computational fluid dynamics simulations predict the thermal-hydraulic performance of cold plate subsections. The highest performing geometries are evaluated with high fidelity simulations. Four cold plates are manufactured for experiments: three with diamond-shaped pin fins and one with straights fins for comparison purposes. The cold plates are fabricated from copper-tungsten (CuW), copper (Cu), or aluminum-silicon-magnesium alloy (AlSi10Mg). The diamond-shaped pin fins achieve a roughly 15 % lower thermal resistance compared to the conventional straight fin microchannel. The highest performing design achieves a chip-to-coolant (including thermal interface material) thermal resistance of 9.0 K/kW in CuW and 6.9 K/kW in Cu under a 1 kW heat load with an inlet-to-outlet pressure drop of 9.0 kPa and water as the working fluid. This work demonstrates ultra-low thermal resistance and pressure drop cold plates for large die, high heat load applications, and shows that CuW is an attractive cold plate material for improved reliability in next generation data center cooling.

Coefficient of thermal expansion↗
DOE OSTI2025

Accelerating Nuclear-Integrated Data Centers in the USA: SWOT Analysis, Power-Thermal Management Strategies, and Industrial-Scale Demonstration and Potential Deployment

Driven by the growth in digital services, cloud computing, AI, and manufacturing, data centers face rising energy demands that challenge traditional power sources and cooling efficiency. This study explores using nuclear power to meet these demands, focusing on accelerated reactor technology deployment and highlighting needs such as N+1/N+2 power supplies and integrated power-thermal management. A SWOT analysis addresses grid connectivity, reactors, and site selection, particularly DOE sites. Reactor technology demonstration and deployment could be accelerated by leveraging test facilities such as MARVEL, MAGNET, TED, FAS, DOME, LOTUS, ATR, Energy System Proving Grounds, and upcoming Energy Launch Pads, along with modeling and simulation tools such as RELAP5, MOOSE, VERA, RAVEN, and FORCE. The potential power and thermal management options, including various cooling technologies, waste-heat utilization, and an industrial-scale demonstration plan, aim to accelerate the integration of nuclear power and data centers in the USA, while emphasizing community and stakeholder engagement and synergistic efforts.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2026

Potential of Data Center Controls in Grid Services

The rapid proliferation of large data centers brings both challenges and opportunities for grid reliability. The data center resources and their potential flexibility have the potential to contribute resources to grid operations. Through capabilities like energy shifting and resource coordination, data centers can help reduce their net demand on the transmission network, as well as provide additional grid services to support reliable operation on the grid. While transient and long-term grid planning and operations are the scenarios that draw most attention, the quasi-steady state timeseries (QSTS) operation of data centers and grid bring interesting scenarios that can help evaluate the data center controls to aid grid services. This work is focused on modeling data centers for QSTS applications – incorporating the AI data center load profiles and building on the PNNL digital twin model for the thermal management loads to enable simulation studies to reveal the impact of data center controls on grid performance. This includes the integration of a QSTS battery and natural gas generator model to incorporate local resource impacts to the system. The simulation study is performed with a modified IEEE 24-Bus transmission system. Scenarios are focused on evaluating the data center load impacts on the transmission system and leveraging both data center and local generation controls to mitigate those impacts and provide additional grid services. The data center controls revealed the ability to contribute to two main kinds of grid services: preventing congestion on a weak grid by coordinating the data center resources with the collocated BESS and onsite generation; and the ability to help the grid operations during stressed times of operation like during a contingency. Leveraging these and other capabilities has the potential to help data centers become grid responsive assets, aiding in both their integration into the power system and grid reliability.

power grid simulation↗
NASA NTRS1992

Introduction to Space Station Freedom

NASA field centers and contractors are organized to develop 'work packages' for Space Station Freedom. Marshall Space Flight Center and Boeing are building the U.S. laboratory and habitation modules, nodes, and environmental control and life support system; Johnson Space Center and McDonnell Douglas are responsible for truss structure, data management, propulsion systems, thermal control, and communications and guidance; Lewis Research Center and Rocketdyne are developing the power system. The Canadian Space Agency (CSA) is contributing a Mobile Servicing Center, Special Dextrous Manipulator, and Mobile Servicing Center Maintenance Depot. The National Space Development Agency of Japan (NASDA) is contributing a Japanese Experiment Module (JEM), which includes a pressurized module, logistics module, and exposed experiment facility. The European Space Agency (ESA) is contributing the Columbus laboratory module. NASA ground facilities, now in various stages of development to support Space Station Freedom, include: Marshall Space Flight Center's Payload Operations Integration Center and Payload Training Complex (Alabama), Johnson Space Center's Space Station Control Center and Space Station Training Facility (Texas), Lewis Research Center's Power System Facility (Ohio), and Kennedy Space Center's Space Station Processing Facility (Florida). Budget appropriations impact the development of the Space Station. In Fiscal Year 1988, Congress appropriated only half of the funds that NASA requested for the space station program ($393 million vs. $767 million). In FY 89, NASA sought $967 million for the program, and Congress appropriated $900 million. NASA's FY 90 request was $2.05 billion compared to an appropriation of $1.75 billion; the FY 91 request was $2.45 billion, and the appropriation was $1.9 billion. After NASA restructured the Space Station Freedom program in response to directions from Congress, the agency's full budget request of $2.029 billion for Space Station Freedom in FY 92 was appropriated. For FY 93, NASA is seeking $2.25 billion for the program; the planned budget for FY 94 is $2.5 billion. Further alterations to the hardware configuration for Freedom would be a serious setback; NASA intends 'to stick with the current baseline' and continue planning for utilization.

Kohrs, Richard↗
DOE OSTI2026

Metal additively manufactured wavy fin cold-plate architecture for improved thermal-hydraulic performance

Rapid growth in artificial intelligence and data center workloads demands high-performance liquid cooling to manage increasing chip power. This study presents two metal-additive-manufactured cold plates with sinusoidal fins, constant-amplitude wavy fins and linearly variable-amplitude wavy fins and compares them against metal-additive-manufactured straight fins using experiments conducted at 1 kW heat dissipation as well as high-fidelity 3D conjugate computational fluid dynamic simulations. The cold plates were printed in AlSi10Mg material and underwent design using a Python-automated workflow prior to manufacture and testing. The experiments show that wavy fins reduce the normalized thermal resistance by 35 to 45 % at water flow rates from 1 to 4 LPM. At a fixed 20 kPa pressure drop, the variable-waviness design lowered peak surface temperature by 9 °C and thermal resistance by 51 %, while edge-channel maldistribution in the constant wavy fin design limited gains. A thermal resistance breakdown revealed that 55–63 % of the total thermal resistance in wavy designs comes from base heat conduction, 27–33 % from fin heat conduction, and 9–13 % from fin heat convection, indicating the need to address conduction bottlenecks. Parametric sweeps identify a 3 mm fin pitch as optimal, and that horizontal inlet/outlet manifolds further reduce pressure drop by 30–60 % and thermal resistance by 9–16 % relative to vertical inlet-outlet manifolds. The results yield comprehensive guidelines for fin geometry, manifold alignment, material selection and additive-manufacturing constraints to realize high-performance liquid-cooled cold plates for power-dense electronics.

3d printing↗
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↗
NASA NTRS2006

Estimating Temperature Retrieval Accuracy Associated With Thermal Band Spatial Resolution Requirements for Center Pivot Irrigation Monitoring and Management

This study explores the use of synthetic thermal center pivot irrigation scenes to estimate temperature retrieval accuracy for thermal remote sensed data, such as data acquired from current and proposed Landsat-like thermal systems. Center pivot irrigation is a common practice in the western United States and in other parts of the world where water resources are scarce. Wide-area ET (evapotranspiration) estimates and reliable water management decisions depend on accurate temperature information retrieval from remotely sensed data. Spatial resolution, sensor noise, and the temperature step between a field and its surrounding area impose limits on the ability to retrieve temperature information. Spatial resolution is an interrelationship between GSD (ground sample distance) and a measure of image sharpness, such as edge response or edge slope. Edge response and edge slope are intuitive, and direct measures of spatial resolution are easier to visualize and estimate than the more common Modulation Transfer Function or Point Spread Function. For these reasons, recent data specifications, such as those for the LDCM (Landsat Data Continuity Mission), have used GSD and edge response to specify spatial resolution. For this study, we have defined a 400-800 m diameter center pivot irrigation area with a large 25 K temperature step associated with a 300 K well-watered field surrounded by an infinite 325 K dry area. In this context, we defined the benchmark problem as an easily modeled, highly common stressing case. By parametrically varying GSD (30-240 m) and edge slope, we determined the number of pixels and field area fraction that meet a given temperature accuracy estimate for 400-m, 600-m, and 800-m diameter field sizes. Results of this project will help assess the utility of proposed specifications for the LDCM and other future thermal remote sensing missions and for water resource management.

Ryan, Robert E.↗
NASA NTRS2007

NASA Johnson Space Center SBIR STTR Program Technology Innovations

The Small Business Innovation Research (SBIR) Program increases opportunities for small businesses to participate in research and development (R&D), increases employment, and improves U.S. competitiveness. Specifically the program stimulates U.S. technological innovation by using small businesses to meet federal R&D needs, increasing private-sector commercialization of innovations derived from federal R&D, and fostering and encouraging the participation of socially disadvantaged businesses. In 2000, the Small Business Technology Transfer (STTR) Program extended and strengthened the SBIR Program, increasing its emphasis on pursuing commercial applications by awarding contracts to small business concerns for cooperative R&D with a nonprofit research institution. Modeled after the SBIR Program, STTR is nevertheless a separately funded activity. Technologies that have resulted from the Johnson Space Center SBIR STTR Program include: a device for regenerating iodinated resin beds; laser-assisted in-situ keratomileusis or LASIK; a miniature physiological monitoring device capable of collecting and analyzing a multitude of real-time signals to transmit medical data from remote locations to medical centers for diagnosis and intervention; a new thermal management system for fibers and fabrics giving rise to new line of garments and thermal-enhancing environments; and a highly electropositive material that attracts and retains electronegative particles in water.

Krishen, Kumar↗
NASA NTRS1976

Terminal area energy management regime investigations utilizing an 0.030-scale model (47-0) of the space shuttle vehicle orbiter configuration 140A/B/C/R in the Ames Research Center 11 x 11 foot transonic wind tunnel (OA148), volume 5

Data obtained in wind tunnel test OA148 are presented. The objectives of the test series were to: (1) obtain pressure distributions, forces and moments over the vehicle 5 orbiter in the thermal area energy management (TAEM) and approach phases of flight; (2) obtain elevon and rudder hinge moments in the TAEM and approach phases of flight; (3) obtain body flap and elevon loads for verification of loads balancing with integrated pressure distributions; and (4) obtain pressure distributions near the short OMS pods in the high subsonic, transonic and low supersonic Mach number regimes.

Hawthorne, P. J.↗
NASA NTRS2012

CRYogenic Orbital TEstbed Ground Test Article Thermal Analysis

The purpose of this study was to anchor thermal and fluid system models to CRYOTE ground test data. The CRYOTE ground test artide was jointly developed by Innovative Engineering Solutions, United Launch Alliance and NASA KSC. The test article was constructed out of a titanium alloy tank, Sapphire 77 composite skin (similar to G10), an external secondary payload adapter ring, thermal vent system, multi layer insulation and various data acquisition instrumentation. In efforts to understand heat loads throughout this system, the GTA (filled with liquid nitrogen for safety purposes) was subjected to a series of tests in a vacuum chamber at Marshall Space Flight Center. By anchoring analytical models against test data, higher fidelity thermal environment predictions can be made for future flight articles which would eventually demonstrate critical cryogenic fluid management technologies such as system chilldown, transfer, pressure control and long term storage. Significant factors that influenced heat loads included radiative environments, multi-layer insulation performance, tank fill levels and pressures and even contact conductance coefficients. This report demonstrates how analytical thermal/fluid networks were established and includes supporting rationale for specific thermal responses.

Piryk, David↗
NASA NTRS1990

High altitude aircraft remote sensing during the 1988 Yellowstone National Park wildfires

An overview is presented of the effects of the wildfires that occurred in the Yellowstone National Park during 1988 and the techniques employed to combat these fires with the use of remote sensing. The fire management team utilized King-Air and Merlin aircraft flying night missions with a thermal IR line-scanning system. NASA-Ames Research Center assisted with an ER-2 high altitude aircraft with the ability to down-link active data from the aircraft via a teledetection system. The ER-2 was equipped with a multispectral Thematic Mapper Simulator scanner and the resultant map data and video imagery was provided to the fire command personnel for field evaluation and fire suppression activities. This type of information proved very valuable to the fire control management personnel and to the continuing ecological research goals of NASA-Ames scientists analyzing the effects of burn type and severity on ecosystem recovery and development.

Ambrosia, Vincent G.↗
NASA NTRSDate not supplied

Space-based Sensor for Extreme Fire Weather Events

Catastrophic bushfires are becoming increasingly prevalent as climate change advances. Impacts extend beyond national borders. Multinational efforts can inform new science and management practices. Space-based sensors and integrated data facilities will play an important role. This paper describes a collaborative project between a consortium of Australian universities and NASA Centers to develop and implement a small satellite platform comprising highly integrated thermal and lightning sensors coupled with AI-based edge computing to help predict, detect, and track bushfires, supporting mitigation activities. This will fill an important capability gap since Australia does not currently have any sovereign Earth observation satellites. This program is enabled by and builds on Australia-NASA collaboration and will also support fire science and management activities in the broader global context.

wildfire↗