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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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102 records · Page 5

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)

A Sensitivity-driven Wide Area Protection (SWAP) Coordination Tool for High Penetration of Inverter-based Resources (IBR)

Traditionally, power system generation sources have been composed of synchronous generators, of which the fault current behavior is understood with minimal differences between generation size and types due to the physics of their construction. Present protection schemes and modeling methods are based upon these understood characteristics. Most renewable generation is composed of inverter-based resources (IBR), in which fault current is determined by switching control software and hardware limitations, each of which can vary between manufacturers and even between models of the same manufacturer. The resulting fault current is low in magnitude, low in negative-sequence current, unpredictable phase angles, and is a challenge to model. These characteristics also result in a challenge to traditional protection schemes and fault simulation software. To address several of these concerns, the project has the following goals: 1. Improve IBR models: Improve IBR models used in short circuit (SC) programs to accurately capture the response of IBRs at the bulk power system (BPS) level for fault and protection studies. 2. Develop automation tool: Develop an automation tool that allows engineers to identify protection coordination and sensitivity issues by performing SC and protection coordination studies in a high IBR-penetrated grid by applying variations to the IBR models, faults, contingencies, etc. 3. Develop schemes: Develop new protection mitigation solution schemes that complement the existing protection systems to ensure safe operation of the BPS with higher IBR penetration levels. The project team did not achieve this final goal, as the Department of Energy (DOE) stopped the project early due to changes in DOE funding priorities. The termination notice came at the beginning of the final project phase, while the team was identifying and beginning to investigate protection issues. It should be noted that the team discussed a 100% penetration scenario. However, this scenario would require the use of grid-forming IBR models that are not presently available. Since developing these models requires additional effort, the 100% penetration scenario was not pursued during this project. In the future, developing the methodology and models for the 100% scenario could benefit the industry.

14 SOLAR ENERGY

CAE for Thermal Management of Aerospace Electronic Boards Using the BETAsoft Program

Aerospace electronic boards require special attention to thermal management due to constraints such as their need to be light, small, and maintain high power densities. Also, cooling is mainly through conductive and radiative modes with minor or negligible convective cooling. Due to these particular requirements, thermal design has become an integrated part of the electronic design process in order to avoid expensive repeat prototyping and to ensure high reliability. To achieve high speed simulations, the BETAsoft code uses semi-empirical formulations and an advanced finite difference scheme that incorporates local adaptive grids. Detailed conduction, convection and radiation heat transfer is considered. Various benchmark verifications of the software simulation compared to infrared images typically prove to be within 10% of each other. The thermal analysis of a sample avionic card in a natural convection environment is shown. Then, the individual effects of attaching metal screws to the casing, increasing radiative emissivities of the casing, increasing the conductance of the wedge lock, adding an aluminum core to the board, adding metal strips in board layers, inserting conduction pads under components, and adding heat sinks to components are demonstrated.

Kimberly Bobish

Extensional Flow Convecting a Reactant Undergoing a First Order Homogeneous Reaction and Diffusional Mass Transfer From a Sphere at Low to Intermediate Peclet and Damkohler Numbers

Forced convective diffusion-reaction is considered for viscous axisymmetric extensional convecting velocity in the neighborhood of a sphere. For Peclet numbers in the range 0.1 ≤ Pe ≤ 500 and for Damkohler numbers increasing with increasing Pe but in the overall range 0.02 ≤ Da ≤ 10, average and local Sherwood numbers have been computed. By introducing the eigenfunction expansion c(r,Θ) = Σ c n (r)P n (cosΘ) into the forced convective diffusion equation for the concentration of a chemical species undergoing a first order homogeneous reaction and by using properties of the Legendre functions P n (cosΘ), the variable coefficient PDE can be reduced to a system of N+1 second order ODEs for the radial functions C n (r), n=0,1,2, ... ,N. The adaptive grid algorithm of Pereyra and Lentini can be used to solve the corresponding 2(N+ 1) first order differential equations as a two-point boundary value problem on 1 ≤ r ≤ r •• . Convergence of the expansion for a specific value of N can thus be established and provides "spectral" behavior as well as the full concentration field c(r,Θ).

N Y Shah

Exceedance Probabilities and Recurrence Intervals for Extended Power Outages in the United States

This report provides estimates of recurrence intervals and conditional exceedance probabilities for major power outages by U.S. region between 2015 and 2021. Additionally, we provide estimates for grid management, particularly outages caused by California’s public safety power shutoffs (PSPS), and for natural outages caused by major hurricanes. Outage recurrence intervals are the average number of years between outage events, and conditional exceedance probabilities are the likelihoods that a customer who experiences a major power outage will experience an outage exceeding a given duration. Major outage events are those that affect 10,000 or more customers, as defined by the U.S. Department of Energy’s (DOE’s) Electric Emergency Incident and Disturbance Report, called OE-417 (DOE 2020). These results can be applied to determine the likelihood of experiencing long-duration outages, which can be integrated into cost-benefit analyses of resilience solutions and broader energy resilience studies.

Ericson, Sean [National Renewable Energy Laborator

CFD-Assisted Nodal Modeling of Sloshing in a Cryogenic Propellant Tank

During autogenous pressurization, tank sloshing causes a significant increase in pressurant consumption to maintain constant ullage pressure during draining of the tank. This increase in pressurant consumption is caused by a significant increase in condensation at the liquid-vapor interface. Sloshing strongly affects the liquid side heat transfer coefficient and thereby the condensation rate. Traditionally, sloshing is modeled by CFD code using the VOF (Volume of Fluid) method to track the liquid vapor interface during sloshing. CFD calculations require a very fine grid to accurately compute the heat and mass transfer at the interface. Therefore, computations are time consuming and prohibit performing many parametric studies often needed during the design of a new system. This paper describes an alternative approach by developing a CFD-assisted nodal model to predict system parameters more economically with reasonable accuracy. In this approach, a multi-node model of tank pressurization was developed using GFSSP. A multi-node model was needed to account for stratification. The model computes heat and mass transfer at the interface to calculate the condensation rate. The liquid side heat transfer is computed using the parameters of sloshing dynamics such as frequency, wave amplitude, and interface area. The parameters of sloshing dynamics are computed by the CFD code LOCI-Stream. The model predictions were compared with test data for several cases.

Cryogenic Tank Sloshing

Challenges and Opportunities for HVAC + Phase Change Material Thermal Energy Storage in Buildings

Phase-change material (PCM) thermal-energy storage (TES) integrated with HVAC and domestic hot water (DHW) can shift a large share of building thermal loads. By flattening and shifting loads, PCM TES reduces peak electricity use, eases stress on local and grid infrastructure, and lowers costs. It can also defer costly upgrades to service panels, distribution, and transmission. Higher energy density relative to chilled or hot water storage makes PCM TES practical for small, space limited, and retrofit projects, while packaged HVAC-integrated systems expand cost-effective load shifting to commercial buildings that previously lacked options. Despite this promise, deployment faces barriers. This paper presents challenges, opportunities, and lessons learned from lab and field integrations of PCM TES with packaged HVAC systems. Key challenges include misalignment between default heat pump controls tuned for direct-to-load operation and TES charge/discharge objectives, PCM properties that diverge from manufacturer claims and evolve with cycling, and high integration and deployment costs with off-the-shelf products. These studies underscore the need for factory built, integrated systems that arrive as prepackaged modules with proven controls, reducing design and installation effort and delivering predictable performance across projects. The paper outlines steps to enable viable and scalable PCM TES HVAC and DHW systems, including 1) validated methods that can be used to characterize PCM properties and TES system performance, 2) supervisory controls that optimize charge/discharge scheduling, and 3) factory integrated packaging that eliminates bespoke field engineering.

Dutton, Spencer

Oceanic fronts shape hemispheric contrasts in polar stratospheric extremes

Sudden Stratospheric Warmings (SSWs) and Polar Stratospheric Clouds (PSCs) exhibit striking inter-hemispheric asymmetries: SSWs are frequent in the Arctic but rare in the Antarctic, while PSCs are more persistent in the Antarctic. Although land–sea thermal contrast and orography (LSCO) have been traditionally invoked to explain these asymmetries, here we show using semi-idealized model experiments that even though LSCO strongly impacts the mean state of SSWs and PSCs, it alone cannot fully account for the observed differences. Using model experiments, we reveal that midlatitude oceanic sea surface temperature (SST) fronts represent a crucial supporting additional driver of the hemispheric stratospheric differences. Like LSCO, SST fronts enhance stratospheric convergence of resolved waves, strengthening the Brewer–Dobson Circulation and inducing high-latitude adiabatic warming. This warming significantly enhances Arctic SSW frequency and strongly suppresses PSC formation. Sub-grid-scale non–resolved wave forcing modulates the stratospheric resolved waves effect. The oceanic impact is dominated by North Pacific SST fronts. Our results highlight the indispensable role of SST fronts in shaping Arctic–Antarctic asymmetries in stratospheric dynamics and associated extremes.

Omrani, Nour-Eddine [Univ. of Bergen (Norway)] (OR

From Bricks to Clicks: Mapping the White Space in Building Innovation

It is a critical national imperative to transform the buildings sector, yet innovation is impeded by deployment failures that leave promising technologies stranded. Conventional market reports and techno-economic analysis provide an insufficient understanding of markets and resource allocation for emerging building technologies. They omit crucial commercialization factors such as ecosystem maturity and adoption friction, where the coordinated participation of a network of suppliers, contractors, financiers, regulators, and integrators is required to scale solutions. This study addresses these gaps by introducing an evaluation framework grounded in front-line data from six years of the DOE's IMPEL incubator, comprising experience from 300 building-sector innovators and the adjacent, complex ecosystem. Our methodology synthesizes top-down market analysis with bottom-up, practitioner-level data across five megatrends: (M1) Affordable materials and industrialized construction; (M2) Healthy and efficient mechanical systems; (M3) Intelligent building operations; (M4) Buildings as grid assets; and (M5) High-density power and cooling for data centers and therein identify twelve "white space" technology opportunities. Next, we develop a multi-criteria scoring rubric to rank these opportunities based on parameters, i.e., Affordability, Quality of Life, Reliability, and Security, yielding composite ‘Demand’ and ‘Maturity’ indices. Our results indicate that the most significant white spaces may not be incremental products but a new class of ‘Ecosystem Enablers’, such as logistics platforms, orchestration layers, and automated compliance software that solve structural deployment gaps. This paper summarizes this transparent, evidence-based, practitioner-informed evaluation framework for policymakers and investors to re-evaluate policy and resource allocation and unlock scalable market transformation.

Singh, Reshma

Trust-Based Detection and Mitigation of Cyber Attacks in Distributed Cooperative Control of Islanded AC Microgrids

In this study, we address the challenge of detecting and mitigating cyber attacks in the distributed cooperative control of islanded AC microgrids, with a particular focus on detecting False Data Injection Attacks (FDIAs), a significant threat to the Smart Grid (SG). The SG integrates traditional power systems with communication networks, creating a complex system with numerous vulnerable links, making it a prime target for cyber attacks. These attacks can lead to the disclosure of private data, control network failures, and even blackouts. Unlike machine learning-based approaches that require extensive datasets and mathematical models dependent on accurate system modeling, our method is free from such dependencies. To enhance the microgrid’s resilience against these threats, we propose a resilient control algorithm by introducing a novel trustworthiness parameter into the traditional cooperative control algorithm. Our method evaluates the trustworthiness of distributed energy resources (DERs) based on their voltage measurements and exchanged information, using Kullback-Leibler (KL) divergence to dynamically adjust control actions. We validated our approach through simulations on both the IEEE-34 bus feeder system with eight DERs and a larger microgrid with twenty-two DERs. The results demonstrated a detection accuracy of around 100%, with millisecond range mitigation time, ensuring rapid system recovery. Additionally, our method improved system stability by up to almost 100% under attack scenarios, showcasing its effectiveness in promptly detecting attacks and maintaining system resilience. These findings highlight the potential of our approach to enhance the security and stability of microgrid systems in the face of cyber threats.

Computer Science

Measuring Climate and Water Risk across the Bulk Power System

As climate impacts increase and power systems transition to renewables, planners and operators need insights into climate risks to power generation and infrastructure to ensure reliable decision-making in the short and long-term. We present a standardized, consistent mechanism for utilities and system operators to evaluate the climate- and water-related risks of their current and future grid assets. Using a risk-based approach on the combined outcomes of high-fidelity climate drivers together with water and power system models, we examine the temperature and water availability impacts within the contiguous United States to power system assets at the water basin level in three different time periods and report resulting outcomes on lost capacity across different expansion scenarios and climate models. The results indicate that air temperature has the highest effect on derating. Changes in streamflow do not have a large impact on generation capacity at the national level. Electric sector buildout scenarios each have a unique regional risk profile, depending on the technology mix and total capacity, although risks from high temperatures are significant for both traditional and renewable energy generation. Stakeholders can use this approach to monitor effects of generation capacity losses and potential impacts as climate, generation mix, and infrastructure change.

24 POWER TRANSMISSION AND DISTRIBUTION

MRV Challenge 3: velocity and passive scalar comparison in a 3D turbulent flow

The third iteration of a magnetic resonance velocimetry (MRV) challenge comparison activity consisting of 3D flow measurements for a turbulent flow in a water channel moving past centrally positioned cubic obstacles is reported. In this challenge iteration, MRV measurements are coupled with either temperature or concentration measurements to extend the diagnostic utility. Five research teams from around the world conducted the measurements on a single shared apparatus. The water channel included partial elements along the channel sidewalls that varied in height and precluded easy optical accessibility. In addition to a turbulent mainstream flow, a secondary flow entered the channel between the second and third cubic elements from a square injector hole at the channel bottom wall. The injector jet interacts with the mainstream flow and mixes turbulently as it advects downstream. For the selected flow regime and water solutions used as working fluids, the mixing of the higher temperature or concentration through the secondary flow with the mainstream flow satisfies the same dynamics so that both temperature and concentration fields behave as passive scalars and can be directly compared. The measurements are explained in detail by each participating team, and the results are interpolated onto a common grid and compared using line profiles, contour plots, and isosurfaces.

Benson, Mike [ORNL] (ORCID:000000023210116X)

A review of United States energy-only generator interconnection service policy and considerations for reform

Grid interconnection has emerged as a significant obstacle to the development of new electricity resources. There is growing interest in energy-only interconnection, which is an interconnection service option meant to allow the interconnection of new generators without ensuring their energy deliverability during all hours through the transmission system to customers. This approach potentially avoids upfront congestion-related transmission upgrades but could increase curtailment risk. Interest in energy-only interconnection is shaped by incomplete understanding of how interconnection policy functions in different jurisdictions, a knowledge gap that makes it difficult to determine how energy-only interconnection might be better used or re-designed. In this paper, we provide a regulatory review of energy-only interconnection in U.S. interconnection policy and practice, identifying jurisdictions in which rules are close to -or farther from-the theoretical concept of energy-only interconnection service. We find substantial jurisdictional differences in how energy-only interconnection is implemented, driven by differences in resource adequacy frameworks, real-time transmission operations, and state-level procurement practices. U.S. regulators have preferred local jurisdictional flexibility over federal prescription of interconnection study methods and procedures, which also contributes to differences among regions. Such findings raise fundamental questions about whether competition policies in electricity markets should extend beyond spot energy markets and into more prescriptive guidelines around interconnection rules and market entry. This paper sheds light on tensions that energy-only interconnection raises in allowing generators to access the transmission system on an as available basis and discusses how controlling thresholds for congestion-related network upgrades may be a barrier to electricity market entry.

Gorman, Will

Optimal binning of correlated measurements

Experimental measurements are commonly represented on a discrete grid, requiring a balance between granularity and statistical noise. Two strategies have traditionally been used to improve such representations: selecting an appropriate bin width to control discretization error and applying kernel-based smoothing to suppress fluctuations. Despite their shared goal, these approaches have largely developed independently, without a unified statistical description of how discretization and correlation jointly determine measurement precision. Here, we extend the discussion of optimal interval averaging to a correlation-aware setting by Gaussian process regression, which explicitly accounts for correlations among neighboring bins. Starting from first principles, we derive the mean-squared error of discretized measurements and obtain closed-form asymptotic expressions for the optimal bin width and correlation length. When recast in reduced variables, the theory reveals distinct universal scaling laws governing the error in the correlation-free and correlation-controlled regimes. Characterized by intrinsically smooth intensity profiles and counting-based statistics, neutron scattering measurements are well suited for demonstrating the enhanced error contraction enabled by inter-bin correlations. We show that such improvement is achievable over the experimentally accessible Q-range and across multiple instruments and material systems. These results show that explicitly accounting for correlations systematically reshapes the limits of precision in discretized, noise-limited measurements. More broadly, the framework provides a transferable statistical foundation for optimizing data representation, inference, and experimental design across the physical and data sciences.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)

Humins-Derived Hard Carbon as a Low-Cost Material for Sodium-Ion Battery Anodes

The growing demand for sodium-ion batteries (SIBs) in grid storage underscores the need for electrode materials that balance performance and cost, including sustainable and robust carbon sources. The equitable and abundant distribution of materials for SIBs, along with their superior low-temperature performance, safety, and fast-charging capability, further distinguishes them from lithium-ion batteries (LIBs). Hard carbon (HC) is the state-of-the-art anode for SIBs, but current commercial HC production is localized mostly to one region of the world, raising concerns about supply chain vulnerability, critical material dependency, and environmental aspects. Here, the first demonstration of humins, an abundant biorefinery byproduct, as a precursor for HC anodes for sodium-ion storage is reported. Humins were carbonized at 1100 degrees C-1300 degrees C, and the resulting materials were subjected to comprehensive materials and electrochemical characterization. Among the temperatures studied, humins-derived hard carbon synthesized at 1200 degrees C delivers an initial reversible capacity 270mA h g-1 , with stable cycling performance up to 500 cycles and excellent rate capability, representing the optimal performance. This study establishes humins as a promising and low-cost carbon source that provides a route to mitigate supply chain risks and valorizes an underutilized biorefinery waste stream for high-performance SIB anodes.

25 ENERGY STORAGE

SAM Finite Volume Method Development Status Update: GCR Application, Restart, and MultiApp

The System Analysis Module (SAM) is being developed as a modern system analysis code for advanced non-light-water-reactor safety analysis under the U.S. DOE NEAMS program. Previous feasibility studies have demonstrated that a staggered-grid finite volume method (SG-FVM), implemented under the MOOSE framework, can deliver more than an order of magnitude speedup over the existing continuous Galerkin finite element method (CG-FEM) solver for liquid-cooled, incompressible but thermally expandable flow systems. This work extends the previous effort to compressible, gas-cooled reactor applications, where pressure couples directly into the mass equation adding additional nonlinearity into the equation system. New code capabilities are implemented for pebble bed high-temperature gas-cooled reactor (PB-HTGR) analysis, including a pebble bed CoreChannel component, built-in pebble bed effective thermal conductivity model and channel-to-channel crossflow model. The capabilities are tested, benchmarked, and demonstrated for problems with increased level of model and physical complexities, including the HTTU effective thermal conductivity test, the SANA passive cooling test, and a demonstration case using the GPBR200 reactor design covering steady-state operation, DLOFC and PLOFC transients. Across all cases, the SG-FVM solver demonstrated strong robustness and efficiency, and the solutions agree well with reference results and data. The finding of this work proves that SG-FVM is a viable and efficient solver pathway for compressible, gas-cooled reactor system analysis in SAM. In addition, work has been done to successfully support SAM-FVM recover/restart code feature that is essential to reactor safety analysis applications, and MultiApp code feature that is essential to multi-scale and multi-physics simulations. In summary, this work continued from previous feasibility studies, and further demonstrated that the SG-FVM will serve as a strong foundation for SAM’s advanced solver algorithm for future deployment.

Zou, Ling

PowerModelsGAT-AI: Physics-Informed Graph Attention for Multi-System Power Flow With Continual Learning

Solving the alternating current power flow equations in real time is essential for secure grid operation, yet classical Newton–Raphson solvers can be slow under stressed conditions. Existing graph neural networks for power flow are typically trained on a single system and often degrade on different systems. We present PowerModelsGAT-AI, a physics-informed graph attention network that predicts bus voltages and generator injections. The model uses bus-type-aware masking to handle different bus types and balances multiple loss terms, including a power-mismatch penalty, using learned weights. We evaluate the model on 14 benchmark systems (4 to 6,470 buses) and train a unified model on 13 of these under contingency conditions with up to two branch outages, achieving an average normalized mean absolute error of 0.89% for voltage magnitudes and R 2 >0.99 for voltage angles. We also show continual learning: when adapting a base model to a new 1,354-bus system, standard fine-tuning causes severe forgetting with error increases exceeding 1000% on base systems, while our experience replay and elastic weight consolidation strategy keeps error increases below 2% and in some cases improves base-system performance. Interpretability analysis shows that learned attention weights correlate with physical branch parameters (susceptance: r=0.38 ; thermal limits: r=0.22 ), and feature importance analysis supports that the model captures established power flow relationships.

24 POWER TRANSMISSION AND DISTRIBUTION

Envelope-driven comfort risk in residential demand response

Residential demand response (DR) is a valuable resource for grid reliability, but remains challenging because the highly heterogeneous residential building stock leads to widely varying and hard-to-predict load and comfort responses during DR events. Although prior research has estimated the technical potential of DR-capable technologies for achieving energy demand savings, little is known about how they affect thermal comfort. In particular, it remains unclear how indoor thermal conditions due to DR depend on the thermal envelope characteristics of the housing stock. To address this gap, this study provides a systematic, location-specific assessment of indoor thermal performance during DR-events across the US housing stock using both typical DR weather data and detailed building metadata. We evaluate how envelope characteristics influence indoor temperatures during realistic simulated summer and winter DR events across 37 US locations, applying both temperature threshold and rate of temperature change criteria to estimate region-level probabilities of discomfort. Additionally, we show the impact of distinct weather patterns that intensify or abate thermal stress on comfort outcomes. Results show a near-universal overheating risk in summer DR events, where comfort outcomes are strongly influenced by rapid risk of comfort violations. In contrast, overall winter DR discomfort risk is lower, risk escalation is more gradual and shows greater sensitivity to event duration. These findings offer a data-driven quantification of comfort risk across diverse climates and building envelopes, demonstrating the need for region-specific DR scheduling and discomfort mitigation strategies tailored to local weather patterns and the performance of existing residential buildings.

Demand response