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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2021

UKy-CAER Heat Integrated Transformative CO 2 Capture Process in Pulverized Coal Power Plants

The goal of this Phase II Topical Report is to summarize the work for public domain conducted on project DE-FE0031583. Building upon the Design Basis completed during Phase I and in accordance with the Statement of Project Objectives (SOPO), the University of Kentucky (UK) Center for Applied Energy Research (CAER) (Recipient) along with team members has completed the Front End Engineering Design (FEED) for its advanced, versatile post-combustion CO 2 capture system (CCS) at the 10 MWe large pilot scale to be installed at the Wyoming (WY) Integrated Test Center (ITC), using a heat integrated process with split-rich fed, two-stage stripping and any advanced solvent to enhance the CO 2 absorber performance and lower the cost of CO 2 capture. The proposed project (Phases I-III) involves the design, fabrication, installation, testing and evaluation of a large pilot scale facility that will demonstrate the UK CAER transformative CCS integrated with an operating power plant. The work performed in Phase I, detailed in the Phase I Topical Report that was submitted in March 2019, included formation of a project team, securing the host site, and completing pre-FEED design basis, a cost estimation, a preliminary techno-economic analysis (TEA) and an environmental information volume (EIV). The work performed in Phase II, detailed in this Phase II Topical Report, includes completion of FEEDs, completion of a process risk analysis (PRA), obtaining necessary permits, updating the EIV and TEA, updating the cost and schedule estimate for the Phase III scope of work (SOW) and securing the necessary cost share. Updated information is provided on the current status of the UK CAER CCS technology and the project is ready to begin immediately detailed design, construction and operation of the proposed pilot.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Artificial Intelligence for Power Electronics in Electric Vehicles: Challenges and Opportunities

We report progress in the field of power electronics within electric vehicles has generally been driven by conventional engineering design principles and experiential learning. Power electronics is inherently a multidomain field where semiconductor physics and electrical, thermal, and mechanical design knowledge converge to achieve a practical realization of desired targets in the form of conversion efficiency, power density, and reliability. Due to the promising nature of artificial intelligence in delivering rapid results, engineers are starting to explore the ways in which it can contribute to making power electronics more compact and reliable. Here, we conduct a brief review of the foray of artificial intelligence in three distinct subtechnologies within a power electronics system in the context of electric vehicles: semiconductor devices, power electronics module design and prognostics, and thermal management design. The intent is not to report an exhaustive literature review, but to identify the state of the art and opportunities for artificial intelligence to play a meaningful role in power electronics design from a mechanical and thermal standpoint, as well as to discuss a few promising future research directions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

sCO2 Primary Power Large-Scale Pilot Plant FEED Summary

Echogen Power Systems and its project partners the Electric Power Research Institute, CDM Smith, Riley Power Inc. (a Babcock Power Inc. company), and the University of Missouri completed the Front-End Engineering Design (FEED) study of a nominal 10 MWe supercritical carbon dioxide (sCO2) large-scale pilot plant based on Recompression Brayton Cycle (RCBC) architecture. The FEED study was completed under Phase II of the U.S. Department of Energy Fossil Fuel Large-Scale Pilots program. The FEED study scope included the preliminary design of the combustion and environmental control systems, the primary heater, the sCO2 power cycle and its associated turbomachinery, and the balance of plant equipment to determine accurate cost and schedule requirements for fabrication and installation of the system at the University of Missouri’s Combined Cooling, Heat, and Power Plant, located in Columbia, Missouri. The RCBC sCO2 cycle presents superior thermodynamic efficiency compared to steam-Rankine cycles and is adaptable to a broad range of heat sources. The risk aversion of the power generation industry requires a successful large-scale pilot plant demonstration to enable financing and deployment of commercial-scale plants. Therefore, successful construction and demonstration of a 10 MWe RCBC sCO2 power plant would empower a transformational step forward for the efficiency of the next generation of utility power plants. This paper provides details on the primary heater, environmental control systems, and sCO2 power cycle design and performance.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Enhancing Gaussian Process Surrogates for Optimization and Posterior Approximation via Random Exploration

This paper proposes novel noise-free Bayesian optimization strategies that rely on a random exploration step to enhance the accuracy of Gaussian process surrogate models. The new algorithms retain the ease of implementation of the classical GP-UCB algorithm, but the additional random exploration step accelerates their convergence, nearly achieving the optimal convergence rate. Furthermore, to facilitate Bayesian inference with intractable likelihoods, we propose to utilize optimization iterates for maximum a posteriori estimation to build a Gaussian process surrogate model for the unnormalized log-posterior density. We provide bounds for the Hellinger distance between the true and the approximate posterior distributions in terms of the number of design points. We demonstrate the effectiveness of our Bayesian optimization algorithms in nonconvex benchmark objective functions, in a machine learning hyperparameter tuning problem, and in a black-box engineering design problem. The effectiveness of our posterior approximation approach is demonstrated in two Bayesian inference problems for parameters of dynamical systems.

Bayesian inference↗
DOE OSTI2021

Rapid Construction of Validated Chemistry Models for Advanced Biofuels (Co-Optima Final Report)

Computer methods were developed and demonstrated that make it possible to predict the combustion and pyrolysis chemistry of proposed biofuels, even before the biofuels are ever manufactured or experimentally tested. The methods are based on first-principles calculations of reaction rates and equilibria. A large number of complicated calculations are required, so we developed a computer workflow that automates many of the steps. With the chemical structure of the biofuel and the system conditions (temperature, pressure, compositions, etc.) as the input, the computer methods can construct a detailed kinetic model with refined parameters without intense human intervention. The automation of model construction makes it practical for a single engineer to make the predictions in a reasonable time period. The accuracy of the computer predictions was tested by measuring the time-profiles of various reaction intermediates (carbon monoxide, carbon dioxide, water, formaldehyde, methane, and ethylene) formed as the biofuels pyrolyze or ignite using sophisticated laser shock tube methods. Several biofuels, including methyl propyl ether, cyclopentanone, butyl acetate isomers, etc., were carefully studied to demonstrate the validity of the proposed computational and experimental methodology. This research project opens up the possibility for assessing some proposed biofuels on the computer without expensive experimental campaigns. The new computer methods are open source and well-documented, allowing a knowledgeable modeler to easily access the developed methods and implement them in their work routine. Moreover, they are also convenient and powerful, promising for developing the fuel chemistry models needed for use in engine simulators, facilitating co-optimization of new engine designs with new fuels.

09 BIOMASS FUELS↗
DOE OSTI2021

Environmental life cycle impacts of small wastewater treatment plants: Design recommendations for impact mitigation

The objective of this study was to quantify potential mitigation of environmental impacts from the operation and construction of wastewater treatment plants (WWTP) from implementing specific design recommendations. The study investigated small WWTPs, many of which are serving slow growing or declining populations. Life Cycle Assessment methodology was used to evaluate and compare the inventory and environmental impacts of nine small WWTP case studies. Detailed inventory data was collected from the facilities’ engineering design plans and utility bills. One recommended practice was to avoid significant overdesign by planning for no lower than a 75% capacity utilization by the facilities’ end-of-life. A theoretical correction to a 75% capacity utilization was estimated to mitigate 0.4% of lifetime electricity usage and 1% of secondary process concrete for every 1% reduction in design average flow rate. Relatedly, a 0.4% mitigation in the Carcinogenic and Global Warming impacts could be achieved for every 1% reduction in design average flow toward a 75% capacity utilization. Other suggested practices were focused on conveyance, namely, to minimize non-process facility area and to use polyvinyl chloride pipe instead of ductile iron pipe where possible. Furthermore, the latter practice was estimated to mitigate between 1.1 and 4.8% of the Carcinogenic impact in the nine case studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

TRUST Sensors in Environments: Thermocouples (SE-TC) Report Release FY24

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainty in Simulations and Tests (TRUST) project is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to the development, on-target assessment, and qualification of current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. This work uses and provides feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development.

42 ENGINEERING↗
DOE OSTI2022

TRUST Nonlinear Dynamics (ND) Report: FY22

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainty in Simulations and Tests (TRUST) work package, is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are relevant to the current and future stockpile. This work will use and provide feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development: engineering common model framework (ECMF), engineering quantification of margins and uncertainties (EQMU), and the test information management system (TIMS). Additionally, this work is being used to test a newly available framework in W-13, Weapons Analysis for Verified Engineering Simulation (WAVES).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

High magnetic field response of superconductivity dome in quantum artificial high−⁢𝑇 𝐶 superlattices with variable geometry

It is known that cuprate artificial high-𝑇 𝐶 superlattices (AHTS) with period 𝑑, composed of quantum wells confining interface space charge in stoichiometric Mott insulator layers (𝑆), with thickness 𝐿, at the interface with overdoped normal metallic cuprate layers (𝑁) show a superconducting dome by tuning the geometric 𝐿 over 𝑑 ratio of the SNSN superlattice with the top predicted by quantum material design engineering quantum size effects. Here we report high-field magnetotransport measurements up to 41 Tesla of AHTS across the entire superconducting dome. The results show the universal upward-concave behavior of the temperature-dependent upper critical magnetic field in low-𝑇 𝐶 samples at the rising edge and drop edge of the dome, providing strong evidence consistent with two-band superconductivity in agreement with multigap theory used for quantum design of the SNSN superlattices. The measured superconducting coherence length demonstrates that atomic-scale engineering controls not only the critical temperature but also the intrinsic pair size at Fano-Feshbach resonances physics paving the way toward next-generation quantum devices and shedding light on unconventional superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Design methodologies and engineering applications for ecosystem biomimicry: an interdisciplinary review spanning cyber, physical, and cyber-physical systems

Abstract Ecosystem biomimicry is a promising pathway for sustainable development. However, while typical form- and process-level biomimicry is prevalent, system-level ecosystem biomimicry remains a nascent practice in numerous engineering fields. This critical review takes an interdisciplinary approach to synthesize trends across case studies, evaluate design methodologies, and identify future opportunities when applying ecosystem biomimicry to engineering practices, including cyber systems (CS), physical systems (PS), and cyber-physical systems (CPS). After systematically sourcing publications from major databases, the papers were first analyzed at a meta level for their bibliographic context and for statistical correlations among categorical variables. Then, we investigated deeper into the engineering applications and design methodologies. Results indicate that CPS most frequently mimic organisms and ecosystems, while CS and PS frequently mimic populations-communities and molecules-tissues-organ systems, respectively (statistically highly significant). An indirect approach is most often used for mimicry at organizational levels from populations to ecosystems, while a direct approach frequently suits levels from molecules to organisms (highly significant). Dominant themes across engineering applications include symbiotic organism search algorithms for CS and ecological network analysis for CPS, while PS are highly diverse. For design methodologies, this work summarizes and details ten well-documented biomimetic process models among literature, which addresses an outdated concern for a lack of systematic methods for ecosystem biomimicry. In addition to the Biomimetics Standard ISO 18458, these methods include the Natural Step and Techno-Ecological Synergy framework, among others. Further, the analyses revealed future opportunities from less utilized design methods (e.g. interdisciplinary teams tackling indirect, ecosystem-level projects) to well-established engineering concepts ready for technological advancement (e.g. implementing membrane computing for physical applications). For future studies, this review provides a comprehensive reference for ecosystem biomimetic design practices and application opportunities across multiple engineering domains.

42 ENGINEERING↗
DOE OSTI2020

A Domestic Program for Liquid Metal PFC Research in Fusion

While high-Z solid plasma-facing components (PFCs) are the leading candidates for reactors, it is unclear that they can survive the intense plasma material interaction (PMI). Liquid metals (LM) PFCs offer potential solutions since they are not susceptible to the same type of damage, and can be “self-healing”. Following the Fusion Energy System Study on Liquid Metal Plasma Facing Components study that recently was completed by Kessel et al. (Fusion Sci Technnol 75:886, 2019) a domestic LM PFC design program has been initiated to develop reactor-relevant LM PFC concepts. This program seeks to evaluate LM PFC concepts for a Fusion Nuclear Science Facility (FNSF) or a Compact Pilot Plant via engineering design calculations, modeling of PMI and PFC components and laboratory experiments. The latter involves experiments in dedicated test stands and confinement devices and seeks to identify and answer open questions in LM PFC design. The new national LM PFC program is first investigating lithium as the plasma facing material for a flowing divertor PFC concept. Several flow speeds will be evaluated, ranging from ~ cm/s to m/s. The surface temperature will initially be held below the strongly evaporative limit in the first design; higher temperatures with strong evaporation will be considered in future concepts. Other topics of interest include: understanding of the hydrogen and helium interaction with the liquid lithium; single effect experiments on wetting, compatibility and embrittlement; and prototypical experiments for control and characterization of flowing LM. A path to plasma and future tokamak exposure of these concepts will be developed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

CFD modeling of near-wall combustion and unburned methane prediction in natural gas spark ignition engines

Natural gas-powered engines play a critical role in gas drilling, compression, and transmission sectors, but methane (CH 4 ) from engine combustion slip can be significant over their lifespan, contributing to atmospheric pollution and signaling reduced engine efficiency. Here, to address this challenge, computational fluid dynamics (CFD) simulations offer valuable insights into the in-cylinder combustion process, enabling the optimization of combustion strategies and engine designs to minimize unburned CH 4 slip. This study aims to evaluate and improve combustion models for simulating the combustion process and predicting unburned CH 4 concentrations in natural gas spark-ignition (SI) engines, including engines that are part of combined reformer-engine systems. Specifically, the performance of two flamelet-based combustion models—the Extended Coherent Flame Model (ECFM) and the G-equation model—was assessed using experimental engine data collected under varying excess-air ratio (λ) conditions and fuel compositions, including natural gas and syngas blends. In addition, to enhance the predictive capabilities of the G-equation model, a flame-wall interaction (FWI) sub-model was integrated into its framework. The effects of its model parameters, such as quenching and influence distance, on combustion behavior and unburned methane predictions were analyzed in detail. The ECFM tended to predict delayed combustion phasing under diluted mixture conditions, resulting in overprediction of unburned CH 4 concentrations. In contrast, the G-equation model provided reasonable predictions of combustion pressure, while representing higher the CH 4 reduction rate across the operating condition compared to experimental data. Incorporating the FWI sub-model—with the quenching distance calculated based on a pressure-dependent relation (P -0.48 ) and a fixed influence distance of 1.5 mm—further improved the G-equation model’s accuracy in predicting CH 4 reduction rates without compromising its ability to simulate the combustion process.

Combustion model↗
DOE OSTI2025

Calculating the Effects of Solids Input and Removal as a Temperature Control in the Advanced Scale Up Reactor Experiment (ASURE) Facility at NETL Using Aspen

The Advanced Scale Up Reactor Experiment (ASURE) facility at NETL is being designed to be a fuel-flexible multi-purpose reactor that can be used for pyrolysis/gasification or evaluation of other high pressure “circulating fluidized bed” (CFB) chemical processes. The initial system design calculations for pyrolysis/gasification are presented in this work showing the expected performance of the ASURE facility when used as a biomass conversion reactor. Several other areas of application include gasification of any carbonaceous fuel including biomass, coal, plastics, and other waste materials. The reactor can therefore be used to produce SYNGAS of various compositions and hydrogen as well as other high value chemicals resulting from a typical tuned gasification process. This paper discusses an ASPEN model of the facility, focusing on the riser of the CFB reactor and the solids recirculation loop. The ASPEN model divides the riser into two sections. A bottom section which receives ash, char and sand which have been recirculated from a return loop. In this section an inert fluidization gas, (N2 or CO2), is introduced which acts as the primary mover of the solids through the system. The bottom section is equipped with a restricted air feed so that the recirculated char can be partially oxidized. This oxidation process along with the inventory of recirculating sand are used to effectively control the temperature in the following two chemical conversion sections of the reactor which are the pyrolysis zone followed by a tar cracking zone. Fresh fuel is added to the pyrolysis zone and undergoes drying and devolatilization. The products ash, char, volatile matter, and water vapor exit the pyrolysis zone and enter the reaction block for tar cracking. Steam and CO2 gasification reactions will be incorporated into the tar cracking zone, however at the design operating temperature, conversion from these reactions is expected to be essentially zero. The unit when completed in 2026 will test mixtures of biomass, plastics, and waste coal. This presentation discusses the basic ASPEN engineering design model for this project and provides preliminary sensitivity studies to determine how the various parts of the reactor will perform.

ASSURE↗
DOE OSTI2025

Calculating the Effects of Solids Input and Removal as a Temperature Control in the Advanced Scale Up Reactor Experiment (ASURE) Facility at NETL Using Aspen

The Advanced Scale Up Reactor Experiment (ASURE) facility at NETL is being designed to be a fuel-flexible multi-purpose reactor that can be used for pyrolysis/gasification or evaluation of other high pressure “circulating fluidized bed” (CFB) chemical processes. The initial system design calculations for pyrolysis/gasification are presented in this work showing the expected performance of the ASURE facility when used as a biomass conversion reactor. Several other areas of application include gasification of any carbonaceous fuel including biomass, coal, plastics, and other waste materials. The reactor can therefore be used to produce SYNGAS of various compositions and hydrogen as well as other high value chemicals resulting from a typical tuned gasification process. This paper discusses an ASPEN model of the facility, focusing on the riser of the CFB reactor and the solids recirculation loop. The ASPEN model divides the riser into two sections. A bottom section which receives ash, char and sand which have been recirculated from a return loop. In this section an inert fluidization gas, (N2 or CO2), is introduced which acts as the primary mover of the solids through the system. The bottom section is equipped with a restricted air feed so that the recirculated char can be partially oxidized. This oxidation process along with the inventory of recirculating sand are used to effectively control the temperature in the following two chemical conversion sections of the reactor which are the pyrolysis zone followed by a tar cracking zone. Fresh fuel is added to the pyrolysis zone and undergoes drying and devolatilization. The products ash, char, volatile matter, and water vapor exit the pyrolysis zone and enter the reaction block for tar cracking. Steam and CO2 gasification reactions will be incorporated into the tar cracking zone, however at the design operating temperature, conversion from these reactions is expected to be essentially zero. The unit when completed in 2026 will test mixtures of biomass, plastics, and waste coal. This paper presents the basic ASPEN engineering design model for this project and provides preliminary sensitivity studies to determine how the various parts of the reactor will perform.

ASSURE↗
DOE OSTI2021

Bayesian analysis for estimating statistical parameter distributions of elasto-viscoplastic material models

High temperature design methods rely on constitutive models for inelastic deformation and failure typically calibrated against the mean of experimental data without considering the associated scatter. Variability may arise from the experimental data acquisition process, from heat-to-heat material property variations, or both and need to be accurately captured to predict parameter bounds leading to efficient component design. Applying the Bayesian Markov Chain Monte Carlo (MCMC) method to produce statistical models capturing the underlying uncertainty in the experimental data is an area of ongoing research interest. This work varies aspects of the Bayesian MCMC method and explores their effect on the posterior parameter distributions for a uniaxial elasto-viscoplastic damage model using synthetically generated reference data. From our analysis with the uniaxial inelastic model we determine that an informed prior distribution including different types of test conditions results in more accurate posterior parameter distributions. The parameter posterior distributions, however, do not improve when increasing the number of similar experimental data. Additionally, changing the amount of scatter in the data affects the quality of the posterior distributions, especially for the less sensitive model parameters. Moreover, we perform a sensitivity study of the model parameters against the likelihood function prior to the Bayesian analysis. The results of the sensitivity analysis help to determine the reliability of the posterior distributions and reduce the dimensionality of the problem by fixing the insensitive parameters. The comprehensive study described in this work demonstrates how to efficiently apply the Bayesian MCMC methodology to capture parameter uncertainties in high temperature inelastic material models. Quantifying these uncertainties in inelastic models will improve high temperature engineering design practices and lead to safer, more effective component designs.

42 ENGINEERING↗
DOE OSTI2024

Project DarkStar: Vision for LLNL in 2030

DarkStar was a Strategic Initiative (FY2021-FY2024) to investigate applications of Artificial Intelligence (AI) and Machine Learning (ML) to scientific problems of complex hydrodynamics, shockwave physics and energetic materials. The research focused on physics and engineering design as a process that can be tremendously accelerated through merging AI with advanced physics simulation on exascale-class platforms, and to experimentally validate this revolutionary new approach through dynamic materials campaigns. A central thread of scientific inquiry was in the application of AI to enable human understanding of how to control hydrodynamic instability (which has impacts to areas such as inertial confinement fusion) via engineering features and time-dependent sources. Motivated by an unfinished line of research started by Dr. Johnny von Neumann, AI-enabled simulation approaches were developed that allowed DarkStar researchers to uncover several ground-breaking discoveries regarding hydrodynamic instability, including how to completely suppress Richtmyer-Meshkov instability (RMI). These S&T discoveries, along with other advances, have shown the way for an entirely new approach to time-dependent problems known as inverse design – the idea that complex systems can be developed directly from a final state that is to be achieved and resolve the initial design via satisfying several constraints simultaneously via AI/ML. Through experimental campaigns conducted across a wide range of facilities in the NNSA complex (the High Explosive Application Facility at LLNL, the Dynamic Compression Sector/Advanced Photon Source at Argonne National Lab, and Special Technologies Laboratory at MSTS) the radical new AI/ML approach to engineering complex material dynamics was verified, establishing a new field of study within the realm of shock physics. As advanced manufacturing capabilities continue to develop, the great importance of inverse design as a means to apply that technology effectively for NNSA missions will feature prominently over this decade. DarkStar has positioned NNSA as a world-leader in this newly emerging cross-disciplinary area of AI methods for advanced physics simulation and pioneered multiple novel approaches that have enabled the broader scientific community. By allowing us to see past the horizon, to 2030 and beyond, DarkStar has illuminated the vast potential of AI/ML to impact a wide range of new national security missions and, consequently, multiple areas of further research have already emerged across the NNSA and DOD complex.

42 ENGINEERING↗
DOE OSTI2021

Conceptual design of HTS magnets for fusion nuclear science facility

Second-generation high temperature superconductors (HTS) are available for producing >20 T at the magnet bore compared to 13–16 T for lower temperature superconducting (LTS) toroidal field magnets proposed in recent fusion energy systems studies (FESS) of Fusion Nuclear Science Facility (FNSF). HTS may enable higher fusion power density and smaller device size. High current density cables of multi-layered REBCO tapes have achieved >10 kA at 4–20 K operation in short sample tests for fusion. High current density cables are required for engineering design of FNSF to allow space for interior plasma components. High current density HTS magnets are particularly attractive in reducing the size of a fusion device, beneficial for compact tokamaks, due to their space constraints. Successful HTS magnet development may enable the design of smaller and cheaper fusion pilot plants with a mission of demonstrating net electricity. It may also offer significant cost and performance advantages in non-fusion applicants such as nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI). Furthermore, we developed HTS magnet design concepts for a compact FNSF radial build in order to define the coil size, winding pack mechanical loading and engineering requirements. Partnering with vendors in the US, PPPL is also testing high current cable prototypes aiming at enabling low cost cable technology toward 100 A/mm 2 engineering current density over the winding pack desired in high field model coil development for compact fusion pilot plants.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗