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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 91 records · Page 5

ORGANIC RANKINE CYCLE TURBINE AND HEAT EXCHANGER SIZING FOR LIQUID AIR COMBINED CYCLE

Cryogenic energy storage offers several opportunities to design turbomachinery and other equipment for novel cycles. This paper presents the design and analysis of turbomachinery and heat exchangers for an Organic Rankine Cycle (ORC) subsystem for a hybrid energy storage concept. The Liquid Air Combined Cycle is an energy storage system that stores air at cryogenic conditions at times with high variable renewable energy to be dispatched along with a gas turbine to recover the exhaust heat. In order to re-vaporize the air, the liquid air is coupled with an ORC as an additional bottoming cycle. The ORC turbine is expected to expand the fluid with a pressure ratio of nearly 30 and a flow rate of approximately 45 kg/s. Sizing calculations for both a radial and axial turbine solution were performed over a range of speeds and stages to determine the optimal design point. The results show that either an axial (8- or 9-stage) or radial (four stages at two shaft speeds) turbine are capable of handling the pressure ratios. Further trades of the two configurations would be required to determine the best option. The ORC system also incorporates five heat exchangers to distribute heat, vaporize the liquid air, or recover exhaust heat from the gas turbine. Three heat exchangers were analyzed to understand the size of heat exchangers and pressure drop for the overall system. Different types of heat exchangers were explored for the different purposes, including plate-fin heat exchangers, gasketed plate heat exchangers and shell-in-tube heat exchangers. It was determined that the ORC recuperator, liquid-air vaporizer, and vaporized air pre-heater would be counter-flow heat exchangers using a gasketed plate design. Keywords: Energy Storage, Liquid Air Energy Storage, Organic Rankine Cycle

Pryor, Owen↗

Predicting core transport in ITER baseline discharges with neon injections

Achieving self-consistent performance predictions for ITER requires integrated modeling of core transport and divertor power exhaust under realistic impurity conditions. We present results from a systematic power-flow and impurity-content study for the ITER 15 MA baseline scenario constrained directly by existing SOLPS-ITER neon-seeded divertor solutions. Using the OMFIT STEP workflow, stationary temperature and density profiles are predicted with TGYRO for $1.5 \unicode{x2A7D} Z_\textrm{eff} \unicode{x2A7D} 2.5$, and the corresponding power crossing the separatrix $P_\textrm{sep}$ is evaluated. We find that $P_\textrm{sep}$ varies by more than a factor of 1.7 across this scan and matches the ${\sim}100$ MW SOLPS-ITER prediction when $Z_\textrm{eff} \simeq 1.6$ or when auxiliary heating is reduced to ${\sim}75\%$ of nominal. Rotation-sensitivity studies show that plausible variations in toroidal flow magnitude modify $P_\textrm{sep}$ by $\lesssim 20\%$, while AURORA modeling confirms that charge-exchange radiation inside the separatrix is dynamically negligible under predicted ITER neutral densities. These results identify a restricted compatibility window, $Z_\textrm{eff} \approx 1.6$ –1.75 and $0.75 \lesssim f_{P_\textrm{aux}} \unicode{x2A7D} 1.0$, in which core transport predictions remain aligned with neon-seeded divertor protection targets. This self-consistent, model-constrained framework provides actionable guidance for impurity control and auxiliary-heating scheduling in early ITER operation and supports future whole-device scenario optimization.

ITER↗

A Topology Optimization Framework to Facilitate Adoption of Advanced District Thermal Energy Systems

Advanced district thermal energy systems, which circulate water at temperatures near ambient conditions, and facilitate the utilization of waste heat and renewable thermal sources, can lower the carbon-intensity of urban districts, advancing the U.N. Sustainable Development Goals. Optimization of the network topology — the selection of the best subset of buildings and the best network to connect them, to minimize life cycle cost — can increase adoption of these system in appropriate applications. The potential "solution space" of the topology optimization problem grows factorially with the number of buildings in the district, motivating the consideration of a design heuristic. In this study, a heuristic for the network selection was evaluated with an exhaustive search, for a prototypical four-building district. For the prototypical district considered, the heuristic was effective in selecting an optimal network topology. Additionally, it was found that, in this case, the selection of the subset of buildings was more influential on the life cycle cost than the selection of the network topology. This work is part of a larger effort to develop a topology optimization framework for district thermal energy systems, which is anticipated to address barriers to adoption of ambient-temperature systems.

28 EE - Advanced Manufacturing Office (EE-5A)↗

Dara: Automated Multiple-Hypothesis Phase Identification and Refinement from Powder X-ray Diffraction

Powder X-ray diffraction (XRD) is a foundational technique for characterizing crystalline materials. However, the reliable interpretation of XRD patterns, particularly in multiphase systems, remains a manual and expertise-demanding task. As a characterization method that only provides structural information, multiple reference phases can often be fit to a single pattern, leading to potential misinterpretation when alternative solutions are overlooked. To ease humans’ efforts and address the challenge, we introduce Dara (data-driven automated Rietveld analysis), a framework designed to automate the robust identification and refinement of multiple phases from powder XRD data. Dara performs an exhaustive tree search over all plausible phase combinations within a given chemical space and validates each hypothesis using the BGMN Rietveld refinement routine. Key features include structural database filtering, automatic clustering of isostructural phases during tree expansion, and peak-matching-based scoring to identify promising phases for refinement. When ambiguity exists, Dara generates multiple hypothesis which can then be decided between by human experts or with further characterization tools. By enhancing the reliability and accuracy of phase identification, Dara enables scalable analysis of realistic complex XRD patterns and provides a foundation for integration into multimodal characterization workflows, moving toward fully self-driving materials discovery.

Biological databases↗

Covariance Shaping Over Riemannian Manifolds for Massive MIMO Communication

Acquiring accurate instantaneous channel state information (CSI) is a challenging aspect of massive multi-input multi-output (MIMO) communication. Utilizing statistical information, such as channel covariance matrix, to design statistical beamforming vectors is robust when compared to instantaneous CSI. In this paper, we propose a novel MIMO covariance shaping scheme over Riemannian manifolds. It serves as an effective statistical beamforming solution to a number of close proximity user equipment (UE) that are undergoing substantial channel correlation. Proposed algorithm exploits the Hermitian positive definite nature of covariance matrices lying over Riemannian manifold. We introduce Wasserstein distance function as a Riemannian metric to measure distances between channel covariance matrices. Furthermore, K-means clustering technique is utilized to effectively identify the optimal shape of effective optimal covariance matrices. Our findings suggest that maximizing the geodesic distance between covariance matrices ultimately leads to a corresponding increase in the network throughput, as determined by the beamforming vector used to shape the covariance matrices. Simulation results validate that the proposed solution converges faster than Euclidean-based state-of-the-art, while maintaining the same computational complexity. Finally, the sum rate performance asymptotically achieves full capacity for two-UE case and more than 96% of the upper bound exhaustive search benchmark for multi-UE scenario.

42 ENGINEERING↗

Progress of Divertor Heat and Particle Flux Control in EAST for Advanced Steady-State Operation in the Last 10 Years

Active control of the excessively high heat and particle fluxes on the divertor target plates is of fundamental importance to the steady state operation of tokamaks, especially for fusion reactors. A series of experiments have been carried out on this critical issue to relieve the plasma-wall interactions in the experimental advanced superconducting tokamak (EAST) in the last ten years, not only contributing to the long pulse operation of EAST itself, but also providing physical understandings and potential techniques to the next-generation devices like ITER. Here we have characterized the power deposition pattern and broadened the divertor footprint width effectively. The plasma-wetted area is actively handled using either 3-dimentional edge magnetic topology or advanced plasma equilibrium, thereby peak heat flux around the strike point is reduced. Active control of detachment or radiation compatible with core plasma performance has progressed significantly in very recent years, with a series of active feedback control modules developed and utilized successfully, based on the divertor physics advances with both experiments and simulation. The upper divertor of EAST was upgraded from graphite to active water-cooling ITER-like tungsten in 2014, exhibiting much enhanced heat removal capability. As for the particle exhaust including both fueling and impurity particles, in addition to wall conditioning and impurity source control, the efficiency of particle flux exhaust is optimized by making full use of the divertor closure and the plasma drifts in both scrape-off layer and divertor volume. These heat and particle exhaust advances contribute greatly to a series of EAST achievements like H-mode operation over 100 s. A brief near-term plan on the integrated control of divertor plasma-wall interactions in long-time scale will also be introduced, aiming to provide favorable divertor operation solution for ITER and CFETR.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Testing of Materials and Coatings at up to 1150°C and 300 bar for use in Oxy-Combustion Turbine

Various materials that may be used in a supercritical carbon dioxide (sCO2) oxy-fuel turbine in the 150-300 MWe size range are being evaluated in various environments of interest. The inlet of the turbine must be capable of 1,150 °C at 300 bar and the exhaust temperature is expected to be within the 725-775 °C range. The design requirements are pushing the known limits of high temperature materials. Little is known about the oxidation of the metallic alloys considered for turbine nozzles and blades or about the resilience of thermal management solutions, such as thermal barrier coatings (TBC), required to accommodate these high temperatures. The combinations of high temperature resistant materials and coatings must be tested in sCO2 to evaluate their reliability in an oxy-fuel turbine environment. A total of 13 alloys were chosen to be tested. They included bare samples, with nano deposited MCrAlY bond coat only, or with the addition of a TBC. A unique test facility was developed to expose those materials in sCO2 at up to 300 bar and 1150 °C for up to 5,000 hours. This was accomplished by placing an induction heater inside an autoclave to achieve those high temperature locally while the pressurized vessel is cooled externally. The specimens are weighed before and after exposure to determine the oxidation rate. The integrity, morphology, and composition of some of the coatings and thermally grown oxide will be investigated by scanning electron microscopy (SEM). This paper presents the up-to-date results of the testing coated and uncoated superalloys in sCO2 at up to 1150 °C and up to 300 bar performed at Southwest Research Institute.

Bocher, Florent↗

Modeling the U.S. Western Electric Interconnection to Understand the Consequences of Hydrometeorological Extremes and Options for Risk Mitigation

Electricity grid operators around the world face a dual challenge; withstanding increasingly severe weather and the longer term impacts of climate change, while simultaneously decarbonizing. Extreme weather events such as heat waves and droughts are rising in both severity and frequency, which is threatening the reliability of electricity grids through increased demand, generation capacity losses, and equipment failures. Consequently, incorporating hydrometeorological stressors into computational power systems analysis is becoming an even more critical tool in long term planning and short term operations. However, there is a general lack of open-source customizable grid simulation software capable of exhaustively stress testing the grid under hydrometeorological uncertainty, and/or examining potential risk mitigation pathways. A related, persistent challenge for power system modelers is striking an appropriate balance between model fidelity (e.g. spatial scale and time resolution) and computational tractability (wall clock run-time). In this study, we are proposing a solution to this problem with open-source software that allows users to seamlessly customize the scale and track the accuracy of grid operations models. Our approach allows users to search over numerous model parameters (network topology, mathematical formulation, economic hurdle rates, and transmission line scaling) to identify model instantiations that accommodate experimental design. Further, we use this approach to demonstrate the importance of including extreme weather events in model validation and model selection. Focusing on the occurrence of heatwaves and droughts in the U.S. Western Interconnection, we examine role of extreme events in balancing tradeoffs between model fidelity and run-time at the model design stage.

Economics↗

Design of an Additively Manufactured Recuperator With 800 °C Inlet Temperature for sCO2 Power Cycle Application

Abstract Recuperators with design temperatures at and above 800 °C can further increase the thermal efficiency of supercritical CO2 power cycles by enabling higher turbine exhaust temperatures. Mar-M247 is a well-suited nickel-based superalloy for high temperature service due to its high creep strength that prevents excessive material thickness being required for pressure containment. Additive manufacturing using a high-speed laser-directed energy deposition (L-DED) process presents a promising solution, with build trials demonstrating the ability to produce nonconventional flow channels for enhanced heat transfer. A design process is presented that includes aerothermal and mechanical evaluation to maximize performance within the constraints of the manufacturing process. A 2-D heat transfer network and pressure drop code allows prediction of flow distribution and its effect on overall thermal performance. Established literature correlations, along with CFD simulation, inform the prediction of heat transfer coefficients and friction factors for the flowpaths and enhancement features in the heat exchanger core. Mechanical evaluation using finite element analysis (FEA) modeling with the intent of the ASME Boiler & Pressure Vessel Code (BPVC) Section VIII, Div. 2 assesses the operational safety of the design. The detailed design features annular finned passages that take advantage of helical flow paths to distribute the flow from separated headers to shared heat transfer surfaces. Performance predictions for the recuperator at a 50 kW scale provide insights into the feasibility of the additively manufactured (AM) process to produce recuperators on a commercial scale that extend existing operating envelopes.

Engineering↗

Machine-learning-based dynamic-importance sampling for adaptive multiscale simulations

Multiscale simulations are a well-accepted way to bridge the length and time scales required for scientific studies with the solution accuracy achievable through available computational resources. Traditional approaches either solve a coarse model with selective refinement or coerce a detailed model into faster sampling, both of which have limitations. Here, we present a paradigm of adaptive, multiscale simulations that couple different scales using a dynamic-importance sampling approach. Our method uses machine learning to dynamically and exhaustively sample the phase space explored by a macro model using microscale simulations and enables an automatic feedback from the micro to the macro scale, leading to a self-healing multiscale simulation. As a result, our approach delivers macro length and time scales, but with the effective precision of the micro scale. Our approach is arbitrarily scalable as well as transferable to many different types of simulations. Overall, our method made possible a multiscale scientific campaign of unprecedented scale to understand the interactions of RAS proteins with a plasma membrane in the context of cancer research running over several days on Sierra, which is currently the second-most-powerful supercomputer in the world.

59 BASIC BIOLOGICAL SCIENCES↗

Review of Experimental Decontamination Factors (DF) of Iodine in the Pilot-Scale Law Melter Off-Gas Systems

The Low Activity Waste (LAW) melters at the Hanford Tank Waste Treatment and Immobilization Plant (WTP) will convert low-activity tank wastes containing high concentrations of sodium salts into glass for onsite disposal. Much of the airborne particulates during the calcination/fusion of the feed solids will be removed by condensation and scrubbing of the melter exhaust in the Submerged Bed Scrubber (SBS) and Wet Electrostatic Precipitator (WESP)of the primary off-gas treatment system. The gases exiting the WESP enter a secondary off-gas treatment system, which includes a High-Efficiency Particulate Air (HEPA) filter, an activated carbon absorber, a Thermal Catalytic Oxidizer (TCO), a Selective Catalytic Reduction (SCR) unit, a caustic scrubber, and an exhauster. Much of the volatile organics and NOx will be removed in the TCO and SCR, respectively. Under WTP Direct Feed LAW (DFLAW) configuration, the liquid effluents from the SBS and WESP will be collected and evaporated under vacuum with the evaporator concentrate recycled back to the LAW melter, while the evaporator condensate will be merged with the caustic scrubber solution and sent to the Effluent Treatment Facility (ETF).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Electrochemical conversion of methane to ethylene, olefins, and paraffins using metal-supported solid oxide cells

Electrochemical oxidative coupling of methane (E-OCM) with Sr 2 Fe 1·5 Mo 0·5 O 6–δ (SFM) catalyst is demonstrated with metal-supported solid oxide cells (MS-SOC). SFM anode and Pr 6 O 11 cathode catalysts are loaded into a porous symmetric-architecture cell by infiltration and firing. The most effective chelating agent (citric acid/ethyl glycol) and optimal firing/reducing temperatures (850 °C/750 °C) for the SFM catalyst precursor solution are selected and confirmed by cell testing. Operating temperature, cell voltage, and oxygen concentration at the cathode greatly affect the methane conversion rate and product selectivity by controlling the oxygen ion flow. CH 4 conversion of 85.8% is obtained, with C 2 H 4 , C 2 H 6 , and H 2 concentrations of 10.5%, 12.3%, and 25.6% at 800 °C, respectively, in the product exhaust gas. Reasonable stability of the current density and methane conversion is demonstrated during 200 h operation. Furthermore, this research demonstrates technical progress in catalyst and device development for the E-OCM reaction to synthesize valuable chemicals.

30 DIRECT ENERGY CONVERSION↗

Progress in DIII-D towards validating divertor power exhaust predictions

In this study, UEDGE simulations highlight the role of cross-field drifts on the onset of detached conditions, and new calibrated divertor vacuum ultra violet (VUV) spectroscopy is used to challenge the predictions of radiative constituents in these simulations. UEDGE simulations for DIII-D H-mode plasmas with the open divertor with the ion ∇B-drift towards the X-point show a bifurcated onset of the low field side (LFS) divertor detachment, consistent with experimentally observed step-like detachment onset (Jaervinen A.E. et al 2018 Phys. Rev. Lett. 121 075001). The divertor plasma in the simulations exhibits hysteresis in upstream separatrix density between attached and detached solution branches. Reducing the drift magnitude by a factor of 3 eliminates the step-like detachment onset in the simulations, confirming the strong role of drifts in the bifurcated detachment onset. When measured local plasma densities and temperatures are within proximity of predicted values in the simulations, there is no shortfall of the local emission of the dominant resonant radiating lines. However, the simulations systematically predict a factor of two lower total integrated radiated power than measured by the bolometer with the difference lost through radial heat flow out of the computational domain. Even though there is no shortfall in the emission of the dominant lines, a shortfall of total radiated power can be caused by underpredicted spatial extent of the radiation front, indicating a potential upstream or divertor transport physics origin for the radiation shortfall, or shortfall of radiated power in the spectrum between the dominant lines. In addition to the underpredicted spatial extent, in detached conditions, the simulations overpredict the peak radiation and dominant carbon lines near the X-point, which can be alleviated by manually increasing divertor diffusivity in the simulations, highlighting the ad hoc cross-field transport as one of the key limitations of the predictive capability of these divertor fluid codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Primary Pump Motor Area - Transfer Fan Replacement PLC Design

My poster is about a project that I have worked on in my time at ATR as an intern. The Heating and Ventilation Control Panel (HVB-1) controls thirty-five heating and ventilation fans within the Advanced Test Reactor. This control panel needs replacement, as many of the components inside the existing panel are becoming old and degrading. In preparation for this replacement effort, concepts and component identification for the new control panel needed to be developed. Instead of replacing the new panel with replacement mechanical components, a Programmable Logic Controller (PLC) is proposed as a solution. Although multiple fans are associated with this panel, my poster focuses on the replacement design for the Primary Pump Motor Area Transfer Fan. This will provide an example of how the entire cabinet may be upgraded.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Recent progress in the design of the K-DEMO divertor

The preliminary conceptual design of the Korean fusion demonstration reactor (K-DEMO) with a major radius of 6.8 m and the fusion power of 2200 MW has been studied since 2012. The overall configuration of the K-DEMO divetor system based on the ITER-like water-cooled tungsten technology is a double-null type symmetric divertor subdivided into 32 toroidal modules for the vertical maintenance. A detached divertor scenario with impurity seeding was considered as the primary approach for the power exhaust to reduce the peak heat flux lower than the engineering limit of 10 MW/m 2 . The power exhaust performance at the scrap off layer was estimated by using UEDGE-2D code, a two-dimensional fluid transport code for collisional edge plasma and neutral species like N, Ne, and Ar. Particle and heat flux on inboard and outboard divertor targets were calculated for the detached cased depending on parameters such as the impurity seeding rate, pumping rate, and the pedestal density. On the other hand, a magnetic solution like X-divertor, snowflake divertor, and super X-divertor to expand the plasma wet area was considered for K-DEMO since the detached divertor increasing a radiation fraction by impurity seeding might be able to be unstable. However, the extremely high current of poloidal coils was required more than the engineering limit, 20 MA, to form magnetic field lines for the alternative divertors. Based on the physical calculation of the edge plasma, engineering analyses were carried out to find out the thermal and structural reliability. The thermo-hydraulic analysis confirmed thermal stability, whether all comprising materials are operating within their allowable temperature windows when the case of the peak heat flux is set to 10 MW/m 2 on the outboard divertor target. The response surface optimization method derived two optimal design candidates employing two kinds of heat sink materials, respectively: the reduced activation ferritic martensitic (RAFM) steel and CuCrZr alloy. Additionally, the drawbacks and merits of the two materials were definite. The optimal design with applying RAFM steel was vulnerable to withstand thermal and mechanical loads since low thermal conductivity caused too thin thickness of the heat sink. On the other hand, the CuCrZr alloy has critical drawbacks in terms of activation and radioactive waste despite its high thermal conductivity. Meanwhile, preliminary electromagnetic (EM) analysis was carried out to estimate the EM loads caused by the abnormal behaviors of plasma since EM loads are one of the most critical external loads for designing a DEMO divertor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Complete Evaluation on Advanced Reactor Machine Learning Subversion Attacks (Final)

Navigating through the world of Artificial Intelligence (AI) in nuclear reactors and their Instrumentation and Control (I&C) systems demands a careful, deliberate journey. AI’s capability to manage massive datasets and streamline control systems has indeed carved out a significant role in various sectors, including nuclear energy. However, while AI, and particularly Large Language Models (LLMs), bring a lot to the table in terms of operational efficiency and anomaly detection, they also expose the sector to a new breed of cybersecurity threats, like Inference Attacks, Adversarial Attacks, and Trojan Attacks. This guide is designed to be a straightforward manual, diving deep into the intertwining worlds of AI and cybersecurity within nuclear reactors, and tailoring insights for three crucial audiences: I&C Vendors/Developers, Nuclear Regulators, and Nuclear Reactor Operators and Cyber Defense Teams. (1) Section 2, directed at I&C Vendors/Developers, will provide a clear and focused look at several cybersecurity attacks, offering practical recommendations and detailed scenarios related to AI cybersecurity. This section isn’t just about identifying problems but also about giving solid, usable solutions. (2) Section 3, meant for Nuclear Regulators, gets straight to the point about regulations, policy suggestions, and guidelines that are needed to lay down a robust, secure, and ethical foundation for the application of AI in nuclear operations. The focus is on making sure that everything adheres to international standards and laws while being practicable and clear-cut. (3) Section 4, aimed at Nuclear Reactor Operators and Cyber Defense Teams, offers an exhaustive exploration and technical reports, with clear recommendations and scenario analyses vital to protect operational environments and guarantee the secure application of AI in nuclear reactor operations. The goal is simple: as we step into an era where AI becomes a fundamental element of our technological and energy infrastructures, this guide is here to act as a clear, direct handbook, ensuring that AI is implemented within the nuclear sector in a manner that is secure, responsible, and practical. It’s about striking a balance – optimizing the undeniable benefits offered by AI while securing and shielding against potential cyber threats as we move through this new and complex landscape.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Split HPWHs as an Efficient Solution for Multifamily Buildings with In-Unit Water Heaters

A quarter of all housing units in the United States are found in multifamily buildings, but few efficiency innovations have been made to improve electric water heating systems in this building type. Domestic hot water in multifamily buildings can either be provided by a large central water heater or smaller in-unit water heaters. Integrated heat pump water heaters that are installed in single-family homes are often a poor fit for individual multifamily units because the water heaters are often located in small internal closets. This confined space can limit the airflow to the heat pump, and the cold exhaust air can cause discomfort and reduced efficiency. Split CO2 HPWHs separate the tank from the heat pump, which allows for installation location flexibility. Further, CO2 heat pumps can operate under colder ambient conditions, making them a better fit for multifamily units across a wide range of climate regions. As part of a larger project to characterize split HPWH performance, we evaluated the feasibility of installing an additional, parallel tank that could provide hot water to a second housing unit using a single CO2 heat pump. This approach would reduce the first costs of these more expensive units. Based on the high draw volume that we imposed on both tanks, the same heat pump may be able to support more tanks, depending on hot water usage. This paper will describe the split CO2 HPWH technology, how the two-tank system was controlled, and results from our laboratory evaluation.

CO2 HPWH↗