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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 271 records · Page 15

Is Clean Hydrogen Production a Good Fit for Questa? Final Economic Impact Results

The Village of Questa, New Mexico is aiming to become a regional clean energy hub with robust and diverse employment opportunities for the local community supported by the energy sector and by other businesses inspired or attracted by abundant clean energy, outdoor recreation, and cultural opportunities. A coalition of stakeholders in the Village of Questa, comprising the Village, Kit Carson Electric Cooperative (KCEC), Questa Economic Development Fund, and Chevron, is exploring options to develop hydrogen production facilities as an opportunity to create jobs, provide reliable clean energy, and utilize former mine resources. Questa is home to a molybdenum mine owned by Chevron that closed in 2014. Several residents in Questa and surrounding communities lost their jobs when the mine closed and transitioned from active operations into environmental remediation. Although remediation efforts have been ongoing since 2014 and are expected to continue for at least 16 more years, the number of jobs with Chevron is much smaller now than it was before the closure. Between available workforce, brownfield land, and water rights formerly supporting mine operations but now in a transition period, there are considerable local resources that could be directed toward clean energy generation. Questa's electricity supply is already 100% solar during daylight hours thanks to Kit Carson Electric Cooperative's (KCEC's) strategic decision-making and partnering over the last decade. Now, Questa, KCEC, and Chevron are exploring the potential costs and benefits of siting an electrolytic hydrogen production facility and additional solar photovoltaic (PV) capacity in Questa to further advance the region's clean energy economy. In this report, we estimated the potential economic impacts (i.e., jobs, value added, gross output, tax revenue) of constructing and operating a combined hydrogen (32 MW polymer electrolyte membrane electrolizer + 7.5 MW fuel cell) and solar facility (22.5 MW) in the Village of Questa, as well as the resulting economic spillovers to Taos County and the state of New Mexico. We employ an input-output model that leverages IMPLAN's economic data for the region complemented by construction and operating expenses estimated by NREL and feedback from the local coalition to evaluate the direct, indirect and induced effects of the project construction (transient impacts) and operation (more permanent impacts). Based on the area's average trade profile, feedback from the coalition and current market conditions, these projects are expected to support 487 full-time equivalent jobs during construction, generating $\$24$ million in income for those workers and $\$82$ million in local economic activity in the state. Of those jobs, 106 are expected to be construction sector jobs. These investments are also estimated to add $\$36.5$ million to New Mexico's gross state product (GSP). In the Village of Questa, we estimate 16 jobs will be supported in construction and transportation industries, generating $\$0.9$ million in earnings. In Taos County, the construction phase is expected to support 285 jobs primarily in construction and professional services, while manufacturing jobs dominate the results for the Rest of New Mexico. The Village is also estimated to receive $\$0.9$ million in tax revenue from the construction phase alone. Once in operation, the project continues to impact the state and Questa. Around 20 jobs (full-time equivalent for each year of operation) are supported across New Mexico, with approximately 11 directly employed in Questa by both facilities. The total annual local economic activity supported by ongoing operations is just over $\$1.3$ million/yr, generating $\$1.6$ million/yr in additional income in the state. Annual operations are estimated to add $\$2.1$ million to the state's GSP. The Village is expected to receive around $\$43,000$/yr in tax revenue. Impacts vary significantly depending on which businesses are supplying materials, equipment and services, and where construction workers reside. Choosing local suppliers will most benefit Questa and the New Mexico economy, adding up to 500 jobs during construction and 13 long-term jobs. Local and state governments may consider ways to incentivize local businesses in order to maximize economic benefits.

08 HYDROGEN↗

Navigating Integration: Key Challenges for Data Centers, Nuclear Stakeholders, and Utility Operators

The rapid expansion of data centers, driven by the exponential growth in data-processing and storage needs, presents significant challenges and opportunities for various stakeholders, including data center developers, nuclear energy providers, and utility companies. Data centers are projected to consume 6.7–12% of United States (U.S.) electricity by 2028, driven by artificial intelligence (AI) and cloud-computing demands. Nuclear energy offers reliability and dispatchable baseload power, but data centers need power now while nuclear still needs time to address siting, fast power ramping, and regulatory hurdles. Utilities must keep pace with the unprecedented acceleration of large load interconnection requests and urgently adapt to high-density loads while maintaining grid stability, reliability, and accelerating interconnection timelines. This report dives into these challenges and proposes key collaboration strategies to streamline data center integration that aligns with recent federal initiatives like America’s AI Action Plan and related executive orders that emphasize the importance of data center growth, nuclear energy expansion, and maintaining a competitive edge in the global AI race.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Evaluation of Advanced COTS Passive Devices for Extreme Temperature Operation

Electronic sensors and circuits are often exposed to extreme temperatures in many of NASA deep space and planetary surface exploration missions. Electronics capable of operation in harsh environments would be beneficial as they simplify overall system design, relax thermal management constraints, and meet operational requirements. For example, cryogenic operation of electronic parts will improve reliability, increase energy density, and extend the operational lifetimes of space-based electronic systems. Similarly, electronic parts that are able to withstand and operate efficiently in high temperature environments will negate the need for thermal control elements and their associated structures, thereby reducing system size and weight, enhancing its reliability, improving its efficiency, and reducing cost. Passive devices play a critical role in the design of almost all electronic circuitry. To address the needs of systems for extreme temperature operation, some of the advanced and most recently introduced commercial-off-the-shelf (COTS) passive devices, which included resistors and capacitors, were examined for operation under a wide temperature regime. The types of resistors investigated included high temperature precision film, general purpose metal oxide, and wirewound.

Patterson, Richard↗

Bio-Inspired Energy-Efficient Nanofabricated Electrical Contacts

Nanoscale electrical contacts, especially those between materials of dissimilar electronic properties, often represent one of the main causes of drops in energy transfer efficiency. They are also among the sources of above-threshold noise, and their performance often decreases over the lifetime of the nanodevices. Scale-down limitations from mesoscopic to nanoscale devices, and likewise, of nanoscale to quantum-scale devices are also impeded by contacts’ quality. Making more reliable, energy-efficient electrical contacts is among the goals of the nanoelectronics research within the framework of energy-efficient electronic systems. This report focuses on the design, nanofabrication, and testing of novel shapes of electrical contacts. Lithography and nanofabrication were utilized to mimic the approximate shape of insect setae for mesoscale contacts design. The contacts are tested for elementary charge transport via I–V curves and for the broadband, 1/f noise. Tests show that contacts design leads to a measurable decrease in the energy necessary to operate a contact as a switch by at least 12–20%, depending on temperature, while broadband noise shows measurably lower power spectra, for bio-inspired contacts. The proposed method is open to modifications and improvements as required by various on-chip applications.

36 MATERIALS SCIENCE↗

2022 Prototype Installation and Testing Awardee: Windward Engineering

The 60-kilowatt (kW) Zephyr 21/60 wind turbine from Windward Engineering uses a low-cost, full-span independent pitch system that can act as a redundant aerodynamic braking system. This design uses a relatively simple pneumatic rotary vane actuator, allowing each of the turbine's three blades to be pitched independently and any single blade to activate emergency braking for the entire turbine. A previous Competitiveness Improvement Project (CIP) funding award enabled Windward Engineering to design and develop the Zephyr 21/60 wind turbine's aeroelastic model and pitch system. At the end of this current Competitiveness Improvement Project award, a fully validated aeroelastic model will make it possible to certify Windward Engineering's Zephyr 21/60 design and quantify the technology's levelized cost of energy in preparation for certification and entry into the distributed wind market. The Zephyr 21/60 will feature an attractive levelized cost of energy, improved reliability, and a full-span pitch system for safe and redundant protection against rotor overspeed (which occurs when the rotor turns beyond its design limit).

CIP↗

Enhanced Simulation Tools for Scheduling Solar Plus Storage Power Plants

This is the final technical report for the Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE) under the Solar Energy Technology's Office Balance of Systems program, Award Number 38429. This report summarizes the key outputs and findings of the project, which was focused on long-duration energy storage (LDES) and solar. In particular, one of the most significant challenges of maximizing the value of variable solar energy is the timing of charging and discharging stored energy from LDES devices. Power systems often fail to capture the benefits of LDES and can undervalue the role of storage in providing energy arbitrage, reliability support, and resiliency. This project examined those challenges and proposed alternative methodologies that better capture the value that LDES can provide.

14 SOLAR ENERGY↗

Improved Decarbonization Planning through Climate Resiliency Modeling

California has set ambitious decarbonization goals concerning both emissions and the portion of energy generated by renewable resources. However, climate change poses considerable uncertainties. Variation in load is driven both by the level of electrification as well as the impact of climate change on weather. Further, climate change stands to make weather more variable, impacting not just load but generation from renewable resources. In this paper, we approach the issue of the impacts of climate change on decarbonization planning from two perspectives. First, we look at the range of decarbonization pathways through 8 pathways that account for differences in socioeconomic development, global emissions, and warming. Second, we develop a more robust way of ensuring the reliability of energy resources planning than the commonly used planning reserve margin. We show that the proposed method can save between 6 and 14 billion dollars in investment and maintenance costs and outline critical policy implications concerning the reliance of power plants for satisfying planning reliability requirements, including the potential retirement of dozens of peaker power plants.

Anderson, Osten P.↗

Reliability and Integrity Management Program Implementation Approach

Nuclear energy is the most reliable and environmentally sustainable energy source available today. In the United States, nuclear-generated power accounts for approximately 20% of total electricity and over 55% of clean energy. New advanced reactors have enormous potential to help further decarbonize the energy market, enhance grid resiliency, create new jobs, and build a stronger economy. More than 50 new reactors are being developed in the United States, and the federal government realizes an urgent need to deploy nuclear technologies to meet the country’s energy, environmental, and national security goals. As such, the U.S. Department of Energy launched multiple programs to support advanced reactor deployment. The research described in this paper explores implementation strategies for the Reliability and Integrity Management Program that directly supports the U.S. Department of Energy goal to enable the near-term deployment of the advanced reactor technologies. The project is conducted under the Regulatory Development Program for advanced reactors sponsored by the U.S. Department of Energy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

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)↗

Scotty, I Need More Power - The Fission System Gateway to Abundant Power for Exploration

In planning and in crisis, electrical power has been a key consideration when humans venture into space. Since the 1950's, nuclear fission (splitting of atoms) power has been a logical alternative in both fact and fiction, due to its ability to provide abundant power with high energy density, reliability, and immunity to severe environments. Bringing space fission power to a state of readiness for exploration has depended on clearing the hurdle of technology readiness demonstration. Due to the happy coincidence of heritage from prior space fission development efforts such as the Prometheus program, foresight from NASA's Exploration Mission Systems Directorate in the mid-2000's, and relative budget stability through the late 2000's, National Aeronautics and Space Administration (NASA) and Department of Energy (DOE), with their industry partners, are poised to push through to this objective. Hardware for a 12 kWe non-nuclear Fission Power System Technology Demonstration Unit is being fabricated now on a schedule that will enable a low-cost demonstration of technology readiness in the mid-2010s, with testing beginning as early as 2012. With space fission power system technology demonstrated, exploration mission planners will have the flexibility to respond to a broad variety of missions and will be able to provide abundant power so that future explorers will, in planning or crisis, have the power they need when they most need it.

Palac, Donald T.↗

Report on the Creation and Progress of the Hydrogen Regulatory Research Review Group

The current U.S. nuclear generation fleet is increasingly recognized by governmental, scientific, public policy, and industrial communities as having a strategic role in support of the ongoing national transition to a clean energy future. Federal incentives and actions are aligning to expand the role of nuclear power as a viable and more flexible contributor to the evolving national clean energy mix through programs and initiatives such as nuclear power loan guarantees; the Inflation Reduction Act’s (IRA) clean nuclear electrical, steam, and hydrogen incentives; the Infrastructure Investment and Jobs Act (IIJA, also referred to as the Bipartisan Infrastructure Act or BIL); and near term Department of Energy (DOE) funding opportunities related to nuclear based hydrogen hubs and nuclear integrated hydrogen demonstration projects. . Additionally, leveraging clean nuclear electricity and steam is being explored by industries desiring to transition away from carbon-intensive energy sources. Even with all these emerging enablers, notable barriers remain for the widespread adoption of these opportunities within the U.S. nuclear fleet, including the following: • Assurance of the markets for alternate products needed to support decision-making for large capital modification investments • Electric utility mindset and business history centered solely on producing electricity • Design change complexity and regulatory uncertainty associated with plant modifications needed to support alternate product streams The DOE Light Water Reactor Sustainability (LWRS) Flexible Plant Operations and Generation (FPOG) Pathway is developing options to help U.S. nuclear power plants (NPP) in all these areas to enable NPPs designed for steady baseload operation to integrate with intermittent wind and solar capacity to assure reliable clean energy for the nation. Current and near-term laboratory research is focusing on the technical, regulatory, safety, demonstration, and economic elements in support of improving nuclear plant flexibility through hybrid production of electricity and other non-electric products such as hydrogen and energy arbitrage.

42 ENGINEERING↗

Properties and Performance Attributes of Novel Co-extruded Polyolefin Battery Separator Materials: Electrical Properties - Part 2

As NASA prepares for its next era of manned spaceflight missions, advanced energy storage technologies are being developed and evaluated to address and enhance future mission needs and technical requirements. Cell-level components for advanced lithium-ion batteries possessing higher energy, more reliable performance and enhanced, inherent safety characteristics have been under development within the NASA infrastructure. A key component for safe and reliable cell performance is the cell separator, which separates the two energetic electrodes and functions to inhibit the occurrence of an internal short circuit but preserves an ionic current. Recently, a new generation of co-extruded separator films has been developed by ExxonMobil Chemical and introduced into their battery separator product portfolio. Several grades of this new separator material were evaluated with respect to dynamic mechanical properties and safety-related performance attributes, and the results of these evaluations were previously reported in "Part 1: Mechanical Properties" of this publication. This current paper presents safety-related performance results for these novel materials obtained by employing a complementary experimental methodology, which involved the analysis of separator impedance characteristics as a function of temperature. The experimental results from this study are discussed with respect to potential cell safety enhancement for future aerospace as well as for terrestrial energy storage needs, and they are compared with pertinent mechanical properties of these materials, as well as with current state-of-the practice separator materials.

Baldwin, Richard S.↗

Characterization of Performance Degradation Mechanisms in Low-Cost High Throughput DI-O3 Layer for Passivated Contact Silicon Solar Cells

Characterization and mitigating performance limiting defects in Silicon (Si) PV is one of key areas to be addressed to improve PV hardware costs and energy yield in order to lower the levelized cost of energy (LCOE) of installed PV cost to $0.02/kWh. As Si PV cells efficiencies have surpassed 22% and approaching 23%, the recombination at the metal contacts have become the focus point to be addressed. Passivated contact technologies—having a heterojunction with a band-gap larger than silicon between the metal and silicon—have emerged as a great potential for future highand ultrahigh-efficiency solar cells, as it concurrently reduces recombination and increases carrier selectivity, by incorporating thin films within the contact structure. Passivated contact Si solar cell technologies use a wide variety of tunnel layers—playing a crucial role to passivate metal contacts and tunnel charge carriers—including stoichiometric silicon oxide (SiO 2 ) grown by thermal oxidation and Low-Pressure Chemical Vapor Deposition (LPCVD) technique and silicon oxide (SiO x ) by hot nitric acid. However, thorough investigations on understanding the failure and performance degradation mechanisms associated with tunnel layers are still limited to date. Unlocking those degradation characteristics in crucial tunnel layers could improve the reliability and energy yield of passivated contact Si solar cells. Besides, the technique of growing aforementioned tunneling layers are low throughput, and requires high temperature processes and/or a vacuum environment. In this project, we investigated the performance degradation mechanisms of a low-cost high-throughput ozonated oxide (DI-O 3 ) tunnel layer for the passivated contact Si solar cells.

14 SOLAR ENERGY↗

Carbon Capture Plant Front-End Engineering Design Study for Cement Manufacturing

The objective of this project was to conduct a Front-End Engineering Design (FEED) study for capturing carbon dioxide (CO₂) from cement plant flue gas using non-aqueous solvents (NAS) with a 95% capture efficiency. The study aimed to develop AACE (Association for the Advancement of Cost Engineering) Class 3 cost estimates for a commercial-scale CO₂ capture system with a capacity of 2.4 million tonnes of CO₂ per year (t-CO₂/yr). The results will provide Cemex and the U.S. Department of Energy with reliable data to support investment decisions, evaluate economic feasibility, and guide future project development and implementation.

20 FOSSIL-FUELED POWER PLANTS↗

Optimal Power Management for Large-Scale Battery Energy Storage Systems via Bayesian Inference

Large-scale battery energy storage systems (BESS) have found ever-increasing use across industry and society to accelerate clean energy transition and improve energy supply reliability and resilience. However, their optimal power management poses significant challenges: the underlying high-dimensional nonlinear nonconvex optimization lacks computational tractability in real-world implementation, and the uncertainty of the exogenous power demand makes exact optimization difficult. This paper presents a new solution framework to address these bottlenecks. The solution pivots on introducing power-sharing ratios to specify each cell’s power quota from the output power demand. To find the optimal power-sharing ratios, we formulate a nonlinear model predictive control (NMPC) problem to achieve power-loss-minimizing BESS operation while complying with safety, cell balancing, and power supply-demand constraints. We then propose a parameterized control policy for the power-sharing ratios, which utilizes only three parameters, to reduce the computational demand in solving the NMPC problem. This policy parameterization allows us to translate the NMPC problem into a Bayesian inference problem for the sake of 1) computational tractability, and 2) overcoming the nonconvexity of the optimization problem. We leverage the ensemble Kalman inversion technique to solve the parameter estimation problem. Concurrently, a low-level control loop is developed to seamlessly integrate our proposed approach with the BESS to ensure practical implementation. This low-level controller receives the optimal power-sharing ratios, generates output power references for the cells, and maintains a balance between power supply and demand despite uncertainty in output power. We conduct extensive simulations and experiments on a 20-cell prototype to validate the proposed approach.

Battery energy storage systems (BESSs)↗

Bayesian batch optimization for molybdenum versus tungsten inertial confinement fusion double shell target design

Access to reliable, clean energy sources is a major concern for national security. Much research is focused on the “grand challenge” of producing energy via controlled fusion reactions in a laboratory setting. For fusion experiments, specifically inertial confinement fusion (ICF), to produce sufficient energy, the fusion reactions in the ICF fuel need to become self-sustaining and burn deuterium-tritium (DT) fuel efficiently. The recent record-breaking NIF ignition shot was able to achieve this goal as well as produce more energy than used to drive the experiment. This achievement brings self-sustaining fusion-based power systems closer than ever before, capable of providing humans with access to secure, renewable energy. In order to further progress toward the actualization of such power systems, more ICF experiments need to be conducted at large laser facilities such as the United States's National Ignition Facility (NIF) or France's Laser Mega-Joule. The high cost per shot and limited number of shots that are possible per year make it prohibitive to perform large numbers of experiments. As such, experimental design relies heavily on complex predictive physics simulations for high-fidelity “preshot” analysis. These multidimensional, multi-physics, high-fidelity simulations have to account for a variety of input parameters as well as modeling the extreme conditions (pressures and densities) present at ignition. Such simulations (especially in 3D) can become computationally prohibitive to turn around for each ICF experiment. In this work, we explore using Bayesian optimization with Gaussian processes (GPs) to find optimal designs for ICF double shell targets, while keeping computational costs to manageable levels. These double shell targets have an inner shell that grades from beryllium on the outer surface to the higher Z material molybdenum, as opposed to the nominally used tungsten, on the inside in order to trade off between the high performance associated with high density inner shells and capsule stability. We describe our results for “capsule-only” xRAGE simulations to study the physics between different capsule designs, inner shell materials, and potential for future experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A multiscale recurrent neural network model for predicting energy production from geothermal reservoirs

Optimization of energy production from geothermal reservoirs requires reliable prediction of energy production performance under alternative operation and development scenarios. Traditionally, reservoir simulation models are used for the evaluation and screening of alternative production and development plans. However, simulation models require extensive data collection and modeling efforts and are time-consuming to build, run, and update. Data-driven predictive models, on the other hand, can serve as efficient prediction tools that can be used for decision support and management of daily operations and surveillance activities. Data-driven models become particularly attractive when a reservoir simulation model for a field does not exist and/or is difficult to build. Machine learning (ML)-based data-driven models that have recently become popular in several fields exploit statistical patterns and relations in training data to generate predictions. As such, they tend to perform better in interpolation problems (that is, prediction within the training data range) than when they are used to extrapolate beyond the training data. Production data from geothermal reservoirs tend to exhibit short-term variabilities as well as long-term trends, such as monotonically declining production temperatures. Capturing both short-term features and long-term trends with ML-based models is not trivial. We evaluate the use of recurrent neural networks (RNN) for the prediction of energy production from geothermal reservoirs. RNN is a class of ML architectures that are used to represent and predict sequential/dynamic data. Thus, it can be challenging to apply RNN to problems where long-term trends must be captured and extrapolation beyond the training data range is needed. We introduce the multiscale RNN architecture to extend the application of RNN to detect and predict both short-term variabilities and long-term trends in geothermal data. The developed architecture consists of a long-term component to only capture low-frequency data patterns, and a short-term component to detect features with higher frequency and more nonlinearity. The final prediction is obtained by combining the long-term and short-term predictions. Both synthetic and field data are used to evaluate the presented multiscale RNN model. The prediction performance of the multiscale RNN is compared against those obtained from the regular RNN and the autoregressive (AR) model. The results suggest that the multiscale architecture improves the long-term prediction performance of the regular RNN and enhances its robustness against noise.

15 GEOTHERMAL ENERGY↗