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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Co-simulation of transactive energy markets: A framework for market testing and evaluation

The proliferation of distributed energy resources (DER)—and the ability to intelligently control these assets—is re-defining the electrical distribution system. As the number of controllable devices rapidly expands, grid operators must determine how to incorporate these assets while delivering reliable, equitable, and affordable electricity. One possible approach is to establish distribution-level electricity markets and allow devices/aggregations of devices to participate in price establishment. While this approach purports some of the same benefits as the highly successful wholesale electricity markets (i.e., open competition, efficient price discovery, reduced communication overhead), this needs to be researched and quantified via an analysis platform that models distribution-level markets at the appropriate fidelity. Specifically, the simultaneous evaluation of market performance, DER performance, DER bidding approaches, and distribution feeder power quality requires modeling that spans multiple technical areas. Co-simulation has emerged as a powerful tool in addressing this type of problem, where outputs depend on a range of underlying areas of expertise and associated models. In this paper we describe a solution, as implemented in the HELICS co-simulation platform, where we include (1) high fidelity house models, (2) intelligent bidding agents, (3) a modular market integration/design, and (4) a distribution feeder model. We then present a case study where we test two different market designs: (1) a pseudo-wholesale double-blind auction, and (2) an asynchronous matching market. In this work, the markets are run under two DER penetration levels and economic results are compared to full retail net energy metering and avoided cost net metering scenarios that bookend current approaches to remuneration of DER participation. We show the potential for transactive markets to provide increased value for most customers relative to net metering (and all customers relative to avoided cost scenarios) while decreasing costs for the utility.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Dual Passivation of Cathode and Anode through Electrode–Electrolyte Interface Engineering Enables Long-Lifespan Li Metal–SPAN Batteries

The reliability and durability of lithium metal (Li 0 )–sulfur batteries are largely limited by the undesired Li 0 plating-stripping irreversibility and the detrimental polysulfide dissolution, yet approaches that can simultaneously address the above anodic and cathodic problems are scarce. In this study, we report the stable operation of a Li 0 -SPAN (sulfurized polyacrylonitrile) battery via an anode–cathode dual-passivation approach. By combination of a fluorinated localized high concentration electrolyte (LHCE) and a Li 3 N-forming additive (TMS-N 3 ), robust and highly conductive electrode passivation layers are formed in situ on the surface of both the Li 0 anode and the SPAN cathode. The resulting highly reversible, dendrite-free, and high-density Li 0 plating morphology enables a high Coulombic efficiency of 99.4%. Advanced tender energy X-ray spectroscopy also reveals the eliminated Li 2 S formation and minimized polysulfide dissolution in SPAN cathodes, leading to a high capacity of 580 mAh/g SPAN and stable cycling with negligible capacity decay (0.7%) for 800 cycles. This electrode–electrolyte interphase engineering strategy has tackled the major limitations of Li–S batteries in both ether- and carbonate-based electrolyte systems and under a wide temperature range from –10 to +50 °C, thus providing insightful guidelines for the rational design of highly durable and high-energy-density Li 0 -S batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

Single-phase local-high-concentration solid polymer electrolytes for lithium-metal batteries

Solid polymers are promising electrolytes for Li-metal batteries, but they have limitations: they cannot simultaneously achieve high ionic conductivity, good mechanical strength and compatibility with high-voltage cathodes while suppressing Li dendrites. Here, we design a class of locally high-concentration solid polymer electrolytes based on polymer blends, which are termed Li-polymer in F diluter (LPIFD). The Li-polymer (polymer-in-salt) ensures continuous Li-ion conduction channels and contributes to the solid electrolyte interphase (SEI), and the F diluter (inert fluorinated polymer) adds mechanical strength. Studies reveal that a single-phase LPIFD, which is based on a miscible polymer blend, lacks phase boundaries and forms an organic-less and LiF-rich SEI, effectively suppressing lithium dendrites. The single-phase LPIFD delivers ionic conductivity of 3.0 x 10 -4 S cm -1 and enables the Li anode to reach a high coulombic efficiency of 99.1% and a critical current density of 3.7 mA cm -2 . Furthermore, the ability to form an F-rich cathode electrolyte interphase allows LiNi 0.8 Co 0.1 Mn 0.1 O 2 ||Li cells to achieve a cycle life of 450 cycles at a high operating voltage of 4.5 V. In conclusion, this design will inspire efforts to commercialize polymer electrolytes for high-energy Li-metal batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Valued peaks: Sustainable water allocation for small hydropower plants in an era of explicit ecological needs

Optimizing hydropower operations to balance economic profitability and support functioning ecosystem services is integral to river management policy. In this article, we propose a dynamic, constrained optimization framework for small hydropower plants (SHPs) to evaluate trade-offs between economic profitability and socio-ecological requirements. Specifically, we examine the balance between short-term losses in hydropower generation and the potential for compensatory benefits in the form of revenue from recreational ecosystem services, irrespective of the direct beneficiary. Our framework integrates a fish habitat model, a hydropower optimization model, and a recreational ecosystem service estimate to evaluate different environmental flow scenarios. The optimization process gives three outflow release scenarios, informed by previous streamflow realisations (dam inflow), and designed environmental flow constraints. The framework is applied and tested for the river Kuusinkijoki in North-eastern Finland, which is a habitat for migratory brown trout and grayling populations. We show that the revenue loss due to the environmental flow constraints arises through a reduction in revenue per generated energy unit and through a reduction in turbine efficiency. Additionally, the simulation results reveal that all the designed environmental flow constraints cannot be met simultaneously. Under the environmental flow scenario with both minimum flow and flow ramping rate constraints, the annual hydropower revenue decreases by 16.5 %. An annual increase of 8 % in recreational fishing visits offsets the revenue loss. In conclusion, the developed framework provides knowledge of the costs and benefits of hydropower environmental flow constraints and guides the prioritizing process of environmental measures.

13 HYDRO ENERGY↗
DOE OSTI2026

NiFeCo-based catalysts in high current zero-gap anion exchange membrane water electrolyzers

Understanding degradation mechanisms in pure water anion exchange membrane water electrolyzers is essential for developing durable and precious metal-free hydrogen production systems, yet electronic, chemical, and transport-driven pathways often occur simultaneously at the anode. To separate these effects, we establish a morphology invariant Ni/Fe/Co thin film model catalyst platform using physical vapor deposition and systematically compare composition-dependent behavior under both pure water and 0.1 M KOH feeds. Devices were operated under industrially relevant current density conditions, galvanostatically at 1 A cm −2 for 24 hours; metal dissolution, ionomer oxidation, and resistance growth were quantified using inductively coupled plasma mass spectrometry, X-ray photoelectron spectroscopy (XPS), and electrochemical impedance spectroscopy. Under pure-water operation, Ni-rich films showed voltage increases that correlated with rising total cell resistance (ΔV ≈ 243 mV, ΔR ≈ 0.17 Ω cm 2 ). Co-rich films maintained near constant voltages with minimal resistance change (ΔV < 10 mV, ΔR ≈ 0.03 Ω cm 2 ) but induced pronounced ionomer oxidation observed by XPS. In 0.1 M KOH, ionomer oxidation is suppressed, and impedance growth is minimized (<0.08 Ω cm 2 ) across all compositions, consistent with reduced transport limitations and improved ionic conduction relative to pure-water feeds. These results demonstrate how a controlled thin film model platform can isolate composition electrolyte relationships and provide mechanistic design principles for stable pure water anion exchange membrane electrolyzers.

Milenia Rojas Mendoza, B. [Stanford Univ., CA (Uni↗
DOE OSTI2025

Achievement of highly radiating plasma in negative triangularity and effect of reactor-relevant seeded impurities on confinement and transport

The first achievement of highly radiating plasmas in negative triangularity (NT) is shown with an operational space featuring high core radiation at high Greenwald fraction obtained with the injection of reactor-relevant seeded gases. These NT shape diverted discharges reach high values of normalized plasma pressure ( β N > 2) at high radiation fraction with no edge localized modes (ELMs) and a simultaneous reduction of the divertor heat flux. Here, we demonstrate that as long as the impurity level in the core is kept low to avoid excessive fuel dilution and impurity accumulation, integration of NT configuration with high radiation fraction not only is achievable but it can lead to confinement improvement with stabilization effects originating from collisionality, E × B shear and profiles changes due to impurity radiation cooling. The underlying physics mechanism is robust and reproducible and holds for a variety of impurity species. The absence of the requirement to stay in H-mode translates in a higher core radiation fraction potentially allowed in NT shape effectively mitigating the power exhaust issue. The results presented here demonstrate a path to high performance, ELM free and highly radiative regime with reactor-relevant seeding gases making this regime a potential new scenario for reactor design.

confinement improvement↗
DOE OSTI2023

Proactive Intrusion Detection and Mitigation System

SAND2023-05661O The proactive intrusion detection and mitigation system (PIDMS) provides grid-edge situational awareness for cybersecurity defense by capturing real-time distributed energy resource (DER) network traffic and performance data with a novel approach that improves the detection and prevention of cyber-physical attacks. The PIDMS addresses the grid-edge security gap with real-time analysis of both network traffic and photovoltaic performance data to deliver a novel, cyber-physical intrusion detection system (IDS) approach that increases the accuracy and effectiveness of detection and mitigation. This hybrid IDS analysis enables dual monitoring that increases the workload of the adversary; both cyber and physical data would have to be simultaneously spoofed to evade detection. Furthermore, monitoring and analyzing cyber data are insufficient in some cases. For example, in an insider threat aimed at disrupting inverter grid-support functions where proper credentials and authentication are achieved, only the altered PV performance would indicate abnormal behavior. All in all, the PIDMS provides novel capabilities for: • Distributed, real-time cyber-physical detection and mitigation analysis • Cybersecurity defense for grid-edge systems • Analysis framework that can provide situational awareness across the transmission, distribution, and DER systems The PIDMS sensor is designed to collect cyber-physical data, process the data using machine-learning algorithms, detect abnormal events, and deploy mitigations. With these goals, the main functional PIDMS objectives are: • Capability to collect cyber-physical data • Onboard storage of cyber-physical data • Peer-to-peer communication • Computationally efficient machine-learning algorithms • Online cyber-physical data analysis • Alerting/visualization capabilities • Mitigation deployment capability with bump-in-the-wire (BITW) implementation Each of these functional objectives enable PIDMS to perform effective cyber-physical intrusion detection and mitigation. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Jones, Christian↗
DOE OSTI2023

Sustainble dropwise condensation enabled ultraefficient heat pipes

Heat pipes play a critical role in determining the operations, safety, and energy efficiency of electronics. The main focus to improve the heat pipe performance is on the evaporator design or wicking structures. However, the intrinsic limitation comes from the condenser, which is fundamentally constrained by inefficient filmwise condensation (FWC). In this study, we successfully achieved a peak effective thermal conductivity (k eff ) of ~140 kW/(m·K) on widely used groove heat pipes by implementing sustainable dropwise condensation (DWC) and integrating with enhanced evaporator. To better understand the working mechanisms of the ultraefficient heat pipe, both the evaporator and condenser of the heat pipes have been modified accordingly. Our results show that up to 296% enhancements on the k eff can be achieved under various inclination angles by only inducing DWC in the condenser section. The drawback of temperature fluctuations induced by DWC in smooth heat pipes appears to be effectively solved using the grooves-wicking structure. Furthermore, by integrating the nanostructured evaporator, the k eff of the heat pipe can be boosted up to 517% compared to conventional groove heat pipes. This study, for the first time, demonstrates the huge potential of engineering both the condenser and evaporator simultaneously in developing ultraefficient heat pipes.

42 ENGINEERING↗
DOE OSTI2023

Synthetic Calcium Carbonate Production by Carbon Dioxide (CO 2 ) Mineralization of Industrial Waste Brines

The global scale of CO 2 emission has crossed 36 B tons, and the United State represents 14% of the total emissions. In light of the high cost associated with current CO 2 capture processes ($60-to-150 per ton of CO 2 ), carbon capture and utilization (CCU), wherein CO 2 is converted to beneficial products, provides a pragmatic path to overcome the economic barrier for CO 2 emissions control. In particular, CO 2 mineralization offers an attractive route as it produces high-value mineral carbonates that sequester CO 2 in a stable form. For instance, fine precipitated calcium carbonate, a valuable product with unit price in the range of $230-280/t and a global market projected to reach 99 M tons in 2020, can be produced by capturing CO 2 within aqueous Ca 2+ solution. However, two critical challenges need to be overcome—(i) the need for costly processes such as electrolysis or addition of alkali hydroxides to maintain alkalinity during mineralization, and (ii) the geographic availability of Ca-rich solutions (or brines) which often renders efficient integration with power plants impractical. To simultaneously address these challenges, this project developed two novel routes to enable carbonate production based on efficient CO 2 mineralization. In one variation, the project developed a new alkaline carbonation process to capture CO 2 and produce calcite precipitates from coal ashes. Herein, coal ash is carbonated first in a sodium carbonate solution. The carbonation reaction produces sodium hydroxide and raises the solution pH. This high-pH hydroxide solution is then used for CO 2 capture, which converts the sodium hydroxide solution back to sodium carbonate to repeat the carbonation cycle. The carbonated ash residue is refined with a CO 2 pressure swing step to produce high-purity precipitated calcium carbonate. In another variation, Ca-rich produced water brine serves as the Ca-source to mineralize CO 2 . An H + /Na + ion-exchange cycle was designed to provision alkalinity during mineralization and regenerate the ion-exchange reagent in brines with high salinity. Ca-depleted brines can then be treated within a centralized water treatment facility. Both variations beneficially utilize reject streams—such as coal ashes and brines from oil and gas extraction or CO 2 storage operations—that are available at substantial quantities in the vicinity of coal power plants within the U.S. In addition to technology development, this project included techno-economic and life-cycle analysis to identify technically and economically appropriate solutions for power plants in different geographic locations. Taken together, the project provides a unique route to integrate CO 2 emissions control and waste handling/treatment for coal power plants, while producing a high-value product to offset the economic burden associated with waste management. The developed processes utilize post-desulfurization flue gas from coal-fired power plants as is. The CO 2 conversion reactions are performed in alkaline brines at ambient pressure from the flue gas, thereby minimizing the energy burden. By beneficiation of industrial waste streams with low energy input, the processes offers significant technical advantages in energy and CO 2 footprint over the current paradigm of precipitated calcium carbonate production, which involves calcination of limestone at processing temperatures in excess of 800 °C. Overall, this project developed viable CO 2 mineralization processes while strategically maximizing the economic benefit.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Using dorsal surface for individual identification of dairy calves through 3D deep learning algorithms

Advances in machine learning techniques have allowed the development of computer vision systems (CVS) that can accurately predict several phenotypes of interest for livestock operations. In this context, 3D images taken from a top-down view are particularly useful for estimating body condition score, growth development, and body biometrics in cattle. Frequently, such CVS rely on identification (ID) systems, such as electronic tags, as a way to match animal ID and the predicted phenotype. However, the same 3D images used to predict body weight and other animal biometrics could be adopted for animal recognition as well. Such alternative would optimize CVS to recognize animal ID and monitor growth development simultaneously while leveraging the same hardware infrastructure. Furthermore, this strategy could be used to recognize animals with similar color patterns. Nonetheless, growing animals are continuously changing body shape, which could limit its use as an invariant feature for pattern recognition. Thus, the objectives of this study were: (1) to compare algorithms for different 3D object representations to identify individual animals; and (2) to evaluate how short-term changes in body shape due to animal growth affect the predictive performance of these algorithms. For objective 1, the algorithms were trained (n = 4,558) and tested (n = 1,139) using images from 38 Holstein calves. For objective 2, we designed three different experiments using images (n = 2,347) from five Holstein calves taken over six weeks during their growing period, always training and testing on different weeks. Each experiment evaluated how changing a different parameter of the image capturing procedure affected the predictive ability of the trained algorithms. In the first experiment, we varied the total number of images per animal in the training set; in the second experiment, we varied the number of weeks while keeping a fixed number of images in the training set; and in the third experiment, we skipped weeks between images in the training and test sets. The F 1 score for objective (1) was up to 0.804 when testing with the last frames of each video, and up to 0.959 when using random frames for testing. For objective (2), the F 1 score was up to 0.947 for the first experiment when using 130 images per animal; up to 0.979 for the second experiment when using all five weeks; and up to 0.917 when not skipping weeks between training and testing. In conclusion, these results show that deep learning algorithms can be used to identify individual animals through their dorsal area 3D surfaces, and, from our experiments using calves in their growing period, that they are robust enough to account for changes in body shape and size, making them a promising tool for animal recognition during growth.

3D neural networks↗
DOE OSTI2023

Sustainable chemistry with plasmonic photocatalysts

There is a pressing global need to increase the use of renewable energy sources and limit greenhouse gas emissions. Towards this goal, highly efficient and molecularly selective chemical processes that operate under mild conditions are critical. Plasmonic photocatalysis uses optically resonant metallic nanoparticles and their resulting plasmonic, electronic, and phononic light-matter interactions to drive chemical reactions. The promise of simultaneous high-efficiency and product-selective reactions with plasmon photocatalysis provides a compelling opportunity to rethink how chemistry is achieved. Plasmonic nanoparticles serve as nanoscale ‘antennas’ that enable strong light–matter interactions, surpassing the light-harvesting capabilities one would expect purely from their size. Complex composite structures, combining engineered light harvesters with more chemically active components, are a focal point of current research endeavors. In this review, we provide an overview of recent advances in plasmonic catalysis. We start with a discussion of the relevant mechanisms in photochemical transformations and explain hot-carrier generation and distributions from several ubiquitous plasmonic antennae. Then we highlight three important types of catalytic processes for sustainable chemistry: ammonia synthesis, hydrogen production and CO 2 reduction. To help elucidate the reaction mechanism, both state-of-art electromagnetic calculations and quantum mechanistic calculations are discussed. This review provides insights to better understand the mechanism of plasmonic photocatalysis with a variety of metallic and composite nanostructures toward designing and controlling improved platforms for green chemistry in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

CFD modeling of crystallization fouling with CO 2 desorption incorporated for a falling-film evaporator in thermal desalination

Seawater flowing around horizontal tubes in falling-film evaporators is a common configuration for thermal desalination. Heat is transferred from in-tube steam condensation to the shell-side seawater by conduction through the tube wall and scaling layer, and conduction and convection to the evaporating liquid film. CO 2 is simultaneously released from seawater and mixed with the produced vapor. Fouling coupled with CO 2 desorption has deleterious impacts on both evaporation and condensation. The evaluation of spatiotemporal dependent crystallization fouling and CO 2 desorption is vital to selecting optimal operating conditions. Here, in this work, a CO 2 desorption model is integrated into CFD modeling for predictions of coupled heat and mass transfer, to understand and predict scale formation and CO 2 desorption with local and transient profiles of temperature, carbonate species concentrations, pH, and total alkalinity. The porosity of the scale layer is experimentally determined as 67.7% and invoked in the calculation of effective thermal conductivity. The simulation results reveal that high steam temperatures increase seawater total alkalinity and accelerate scale formation. The scale thickness on the bottom tube reaches 0.30 μm and 5.24 μm for steam temperatures of 60 °C and 80 °C, respectively. High salinity leads to a large CO 2 desorption rates. The CO 2 desorption rate increases 43% when the seawater salinity increases from 35 to 55 g/kg. The effects of operating conditions on carbonate speciation and pH have been compared and analyzed. This model can serve as a comprehensive tool for the design of thermal desalination systems and optimal operation.

42 ENGINEERING↗
DOE OSTI2021

On the stability and stationarity of the Super H-mode combined with an ion transport barrier in the core

The Super H-mode, a regime with high pedestal pressure and stored energy, is explored on DIII-D and combined with an ion transport barrier in the plasma core to increase performance. A significant improvement of ion temperatures and confinement is facilitated by favorable conditions such as high rotational shear and high ion pedestal temperatures. As a result of a rise in density and simultaneous decrease in rotation, the ion transport barrier disappears during the discharge evolution, leading to a transition from a very high confinement state at early times, to a reduced but still high confinement phase. Additionally, in many discharges, a global MHD event consistent with the coupling of a destabilized internal mode to an edge localized mode (ELM) causes a large energy loss and leads to a reorganization of the plasma into a lower temperature, higher density state. Depending on the magnitude of the global MHD event, the plasma edge collisionality can increase significantly and shift the operational boundary from the peeling to the ballooning side, which can be understood as a drop out of the Super H-mode channel into standard H-mode. Hence, in Super H-mode discharges with ion transport barriers, both the improved pedestal height and rotational shear contribute to the high stored energy. Here, at very low levels of rotation, the confinement factor for SH modes is still expected to exceed standard H-mode by 20-30 %. With their overall stationarity and high-performance levels, Super H-mode discharges provide an attractive regime for ITER and may enable a more compact design of future fusion power plants.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Self-consistent equilibrium and transport simulations for NSTX-U plasmas enhanced via machine learning surrogate models

The Control-Oriented Transport SIMulator (COTSIM) is an advanced equilibrium and transport code designed for simulating tokamak discharges at computational speeds suitable for control applications. COTSIM’s modular framework enables users to select models that balance accuracy with speed according to specific needs, allowing the code to operate from fast to faster-than-real-time performance levels. This work presents recent enhancements to COTSIM’s predictive accuracy for NSTX-U scenarios, achieved by integrating neural-network-based surrogate models and self-consistent equilibrium calculations. To improve source deposition predictions, a surrogate model for NUBEAM has been incorporated. Additionally, a surrogate model for the Multi-Mode Module (MMM) now supports predictions of anomalous thermal, momentum, and particle diffusivities—key factors for modeling the evolution of temperature and rotation. Each surrogate model was specifically trained for the NSTX-U operational regime to enhance COTSIM’s accuracy while maintaining computational efficiency. Moreover, COTSIM now couples fixed-boundary equilibrium solvers with its transport solvers, enabling self-consistent predictions of plasma profiles and equilibrium evolution over the discharge. Simulation results demonstrate strong agreement between COTSIM and TRANSP predictions for NSTX-U discharges. These substantial advancements expand COTSIM’s utility in model-based control applications for NSTX-U. Potential applications include simultaneous optimization of equilibrium and transport scenarios, integration into digital twins, real-time profile estimation (e.g., temperature and rotation) from limited or noisy measurements, and advanced feedback-based scenario control.

Equilibrium and transport modeling↗
DOE OSTI2021

A Novel Multiagent Resource Sharing Algorithm for Control of Advanced Energy Systems

This paper implements a novel resource sharing control strategy on a fuel cell–gas turbine hybrid power system at the National Energy Technology Laboratory’s Hybrid Performance Facility (Hyper). In a fuel cell–gas turbine hybrid power system, the simultaneous interaction of the gas turbine and the fuel cell creates a tightly coupled environment characterized by conflicting dynamics. In this paper, a model-free control approach is applied to solve the tightly coupled control problem posed by this challenging environment. Specifically, this control problem is presented as a resource sharing problem that can be solved using a resource sharing algorithm that is defined based on the distribution construction concept. This algorithm creates computational agents and solves the problem through the distribution and redistribution of shared resources defined as blocks. Furthermore, two agents were created; the first agent (agent 1) controls the gas turbine speed by adjusting the electric load, and the second agent (agent 2) controls the cathode mass flow through the fuel cell using the cold-air bypass valve. A parametric study was performed over the course of 15 experimental tests for both agents 1 and 2 through an evaluation of the responses based on setpoint changes. The algorithm was shown to have behavior comparable to a previously implemented multi-input multioutput state-space controller, which was designed through a model-based control approach. The resource sharing algorithm was able to find stable performance during run-time operations without any prior system knowledge identification on the power plant and without creating models used in traditional control strategies.

25 ENERGY STORAGE↗
DOE OSTI2022

AN UPDATE ON THE STATUS OF A REDUCED FLOW TEST OF A 10MW 700⁰C SCO2 INTEGRALLY GEARED COMPANDER

In order to maintain viability as a future power-generating technology, concentrating solar power (CSP) must reduce its levelized cost of electricity (LCOE). One component of solving this problem is reducing the cost of the power block while simultaneously increasing the efficiency of the thermodynamic cycle. One disruptive technology that has the promise to accomplish this is supercritical CO2 based power cycles. These cycles are conceptually similar to steam cycles; however, they have substantially smaller turbomachinery at equivalent power while also delivering more efficiency at turbine inlet temperatures of 500-700℃. This paper will summarize the current status of a US Department of Energy project to develop machinery to support a 10 MW sCO2 power cycle. The team of Southwest Research Institute® (SwRI®) and Hanwha Power Systems America, proposed to develop an integrally-geared (IG) compressor-expander (compander) for use in a nominal 10 MW-scale CSP supercritical carbon dioxide (sCO2) plant application. This integrally-geared compander (IGC) comprises multiple pinion shafts interconnected on a single bull gear to create a compact package, and utilizes a low-cost, low-speed driver. In addition, the integrally-geared architecture allows each pinion to operate at different rotational speeds to optimize performance and easily allow for inter-stage cooling and turbine re-heat to further enhance both stage and cycle efficiency. The close integration of all turbomachinery elements into a single integrally-geared (IG) machine creates a design that lends itself to power block modularization, which makes it suitable for waste heat recovery, fossil fuel power plants, and especially CSP applications.

14 SOLAR ENERGY↗
DOE OSTI2020

Application of GOTHIC to Groundwater Transport Analysis - 20152

Migration of pollutants and hazardous wastes, potentially containing radioactive isotopes, via groundwater transport is a concern at most waste cleanup sites. Predictive analysis can be used to evaluate mitigating actions intended to minimize impact on the environment and public exposure. GOTHIC is a multipurpose thermal hydraulics code that is used extensively in the nuclear industry for design, licensing and operation evaluations. It combines the capabilities of typical one-dimensional system codes and the essential features of Computational Fluid Dynamics (CFD) codes for three-dimensional analysis. There are other codes that are specifically developed for groundwater transport analysis and the results presented here are consistent with prior analyses. However, GOTHIC has some unique features that offer advantages for applications related to nuclear waste. Most importantly, it has been developed and maintained under a Quality Assurance program in compliance with the requirements of 10CFR50 Appendix B [2] and applicable portions of ASME NQA-1 [3] since 1995. Available GOTHIC capabilities that make the code especially useful for groundwater transport of nuclear materials include: - Tracking of any number of tracer elements for contaminants and other species of interest; - Radioactive decay and progeny of tracer elements; - Adsorption/desorption of tracer elements; - Tracking of any number of dissolved gases; - Release and absorption for dissolved gases; - Vapor phase tracking; - Non-Newtonian fluid modeling. The general porous body modeling approach makes GOTHIC well suited to groundwater transport analysis. The multi-region modeling approach used by GOTHIC simplifies model construction for regions of varying hydrologic characteristics and focuses the computational effort on regions of particular interest while simultaneously capturing the macroscopic response and any feedback effects across the larger domain. The applicability of GOTHIC to groundwater transport applications is demonstrated by comparing code results with available analytic or semi-analytic solutions for groundwater behavior. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

3D ion gyro-orbit heat load predictions for NSTX-U

Abstract High power tokamaks operate with divertor heat loads capable of destroying the plasma facing components (PFCs). High fidelity heat load predictions are necessary to ascertain the PFC state for design and during operation. Typical heat flux calculations are 2D, time invariant, and assume that power flows directly along the magnetic field lines (the optical approximation). These assumptions neglect the complex 3D geometries employed to protect the PFCs, the time varying nature of the plasma and PFC thermal state, and the helical trajectories of ions with finite Larmor radii (the gyro-orbit approximation). An integrated software framework, the heat flux engineering analysis toolkit (HEAT), was developed to generate time varying optical heat loads applied to real engineering computer aided design (CAD) (Looby et al 2022 Fusion Sci. Technol. 78 10–27). Recently, an ion-gyro orbit module has been added to HEAT. This module calculates the helical trajectories of ions as they gyrate about the magnetic field lines using kinetic theory macro-particles to accelerate the calculation. First, the new gyro-orbit module will be presented. Next, a comparison to existing research is performed. Finally, an analysis of the gyro-orbit heat loads for NSTX-U is presented for diverted discharges using the engineering CAD models utilized for PFC fabrication. Including these gyro-orbit effects can enhance the PFC performance by ‘smearing’ out the magnetic shadows associated with the castellated fish-scaled geometry. Simultaneously, the helical trajectories can degrade performance when they load narrow regions on edges and corners with high heat fluxes. Analysis of the trade-offs between these competing effects is included, and regions for further investigation are identified.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗