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At least 19 records

Power Flow Geometry and Approximation

Here, the power flow equations are important in numerous power systems problems of practical interest which consider alternating current power flow (ACPF) physics. Perhaps the most well studied being the alternating current optimal power flow problem (ACOPF), seeking to optimize the operation of an electric power system. Due to their non-linearity, problems which include the power flow equations are typically challenging, particularly in optimization. Interestingly, the set of solutions to the power flow equations forms a smooth manifold. As a result, differential geometry can be used to describe and analyze this set of equations. This approach has proven effective in several engineering applications (e.g., solving ACOPF and analyzing the solution space boundary). Central to the success of this approach is an understanding of the power flow manifold's geometry. In this work, we develop the geometric and topological properties of this manifold using concepts from differential geometry. After demonstrating the convenience of this manifold's representation as a function's graph, computational methods are emphasized: we develop retractions, error bounds for linear approximation, and formulas for evaluating the Riemannian metric (including associated objects such as geodesics and the curvature tensor). Scalar curvature and the second fundamental form play a new role in quantifying the quality of linear approximations, like the popular direct current approximation. All functions are implemented in Julia and available in an online repository. Proofs are included for completeness.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Bayesian parameter estimation and evaluation of the K -ω shear stress transport model for plane impinging jets

Numerical simulations with semi-empirical turbulence models are commonly used to model impinging jets, often used for cooling solid surfaces. In this work, the constants in the k-ω shear stress transport model in ANSYS FLUENT are calibrated to experimental velocity and heat transfer data for a plane turbulent impinging air jet to determine if Kennedy-O'Hagan calibration (Kennedy and O'Hagan 2001 J. R. Stat. Soc. B 63 425–64) can improve predictions of near-surface velocities and surface Nusselt numbers for similar flows. Impinging jets have been proposed to cool the target plates of the divertor in future magnetic fusion energy reactors, where simulations are used to estimate divertor performance. The flat-plate divertor (Wang et al 2009 Fusion Sci. Technol .56 1023–7) uses a plane jet of helium issuing from a B = 0.5 mm slot to cool a surface with radius of curvature of 44 B at a distance 4 B from the slot. Predictions from the calibrated numerical model are compared with independent experimental data at different flow conditions, as well as surface temperature data for a flat plate divertor test section. The contribution of this work is evaluation of the accuracy of a calibrated turbulence model for modest extrapolations in flow geometry and flow conditions for a plane impinging jet.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optimizing microfluidic flow cell geometry for in situ resonant soft X-ray characterization of molecular nanostructures

Liquid-phase resonant soft X-ray scattering (LP-RSoXS) is an emerging label-free technique to probe chemically resolved nanostructures of molecular or hybrid materials in liquid environments. Still, quantitative analysis is hindered by the pressure-induced deformation of thin silicon nitride (SiN) membranes used as windows in microfluidic flow cells, which attenuates the signal in nonlinear ways, making experimental optimization difficult. Here, in this work, we directly characterize this deformation under experimental conditions for a variety of cell configurations. We use this to develop a predictive model that combines transmission effects of SiN bowing, incident X-ray beam profiles, and material-dependent resonant scattering cross sections to simulate the effective scattering intensity at the detector across the carbon K-edge. Maps of the total signal across the flow cell window reveal that increasing the window width and polymer concentration shifts the anisotropic intensity distributions from the center toward the edges of the window. It was determined that an optimal SiN thickness of 50 nm, with a window aperture of 104 μm, maximizes the total signal for typical solute concentrations and energies across the carbon K-edge. Our results overturn the assumption that corner regions dominate the scattering signal, offering explicit design guidelines for maximizing LP-RSoXS signals and significantly advancing the quantitative application of this technique to the characterization of molecular and hybrid nanostructured materials in liquids.

Grabner, Devin [Washington State Univ., Pullman, W↗

Using 3D Measurements from MRI to Improve VVUQ

Magnetic resonance velocimetry (MRV) is a diagnostic that can measure 3D, three-component turbulent velocity fields in arbitrarily complex flow configurations. The approach uses magnetic resonance imaging (MRI), which is a system commonly available in radiology departments or medical research centers. MRV acquires signal from hydrogen protons in water channel flows. Despite the obvious utility of the measurements for investigating a variety of flows, comparisons with computational fluid dynamic (CFD) simulations largely retain traditional metrics, comparing velocity profiles and planes at discrete regions within the flow rather than using the 3D nature of the measured field. In this effort, MRV was conducted in a simple water channel with six spanwise-centered periodic obstacles roughly shaped as cubes. At a fully turbulent Reynolds number of 15,000, the channel includes two flows: a main streamwise flow and, in the wake of the second obstacle, an injected flow oriented perpendicular to the streamwise flow. The flow geometry includes partial obstacles on the side walls and is inherently 3D because of the interaction of the two streams and the wake features, making the flow challenging to completely measure with traditional optical techniques. Aside from line profiles and planar comparisons, two 3D metrics are used to compare the data with a steady Reynolds-averaged Navier–Stokes (RANS) simulation result. A brief discussion about the comparison is provided, including comments about uncertainty.

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

A methodology for domain overlapping coupling of thermal-hydraulic systems

Multi-scale coupling has increasingly drawn attention as a promising approach for modeling thermal systems. Traditional system codes provide fast and robust predictions at the plant scale, while high-fidelity computational fluid dynamics (CFD)-based tools resolve localized flow and heat transfer phenomena with greater accuracy. By combining these complementary strengths, co-simulations enable multi-scale analysis that would otherwise be computationally prohibitive for a standalone CFD code. Here, this work introduces a robust and problem-agnostic domain overlapping (DO) coupling between the system thermal-hydraulic (STH) code System Analysis Module (SAM) and the coarse-mesh CFD code Pronghorn. Both applications belong to the Comprehensive Reactor Analysis Bundle (BlueCRAB) code suite, a code suite in active development at the Idaho National Laboratory (INL), tailored for multi-physics analysis of advanced reactors. Unlike previous approaches, BlueCRAB supports an agnostic interface between codes based on different fidelity, while its coupling formulation can address arbitrary flow geometries with multiple inlets and outlets in coupled components. The implemented method leads to consistent pressure drops, enthalpies, and scalar concentrations between coupled SAM and Pronghorn simulations. The methodology is demonstrated through two verification tests, which ensure the numerical consistency and conservation across the codes, and through one validation test against experimental data. The proposed problems explore different physical aspects inherent to thermal systems, with particular attention given to nuclear reactor analysis. These include buoyancy-driven flows, complex flow patterns, and setups with multiple inlets and outlets, representing challenges in advanced reactor applications.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Approaches for Water Removal in Direct-Fired sCO 2 Power Cycles

There is interest in investigation of water removal processes in direct fired sCO 2 flows, as this may potentially lead to greater system efficiency as the removal of this contaminant will result in sCO 2 behaving close to idealized behaviors. Water removal should be split into a two-step process, condensation of the water, followed by separation of the liquid phase water from the sCO 2 . The two main avenues of condensation are manipulation of pressure and temperature for phase change. For this paper, temperature-based phase change is the primary focus through the implementation of heat exchangers. Of the heat exchangers investigated it was found that printed circuit heat exchangers (PCHEs) could be an alternative for this use case, though the specific design of flow channel geometry and flow direction depends on the specific system case and cannot be determined at this point. For water separation there were four processes identified, all of which already assume water is in liquid phase at that point in the system. Of these separation avenues the best candidate is the hydrocyclone as it has a proven history of separating liquid-liquid phase mixtures with small density differences in oilfield use, in addition they have been investigated and modeled specifically for water separation for sCO 2 flows and the footprint is relatively small.

20 FOSSIL-FUELED POWER PLANTS↗

Influence of conical wire array geometry on plasma flow and temperature profiles of radiatively cooled jets

The influence of conical wire array geometry on the formation and dynamics of pulsed-power driven plasma jets is investigated. In the experiments, the jet becomes isolated from the inflows as it passes through an aperture, allowing the study of its intrinsic evolution for different conical angles. Here, our results show that, regardless of the array opening angle, the jets are supersonic, highly collisional, and exhibit an exponential axial density decay with a characteristic scale length of 𝐿 𝑛 ≈ 3 mm, significantly shorter than the overall length of the jet. In contrast, axial velocity systematically increases with larger array opening angles. The near invariance of the density profile is attributed to a compensating mechanism between geometric divergence and axial acceleration, consistent with an asymptotically steady flow regime. Additionally, temperature measurements reveal ion-electron thermal decoupling near the base of the jet, with equilibration downstream. Analysis of radiative cooling and collisional energy exchange timescales indicates that the plasma evolves in a radiatively stable regime and that the two-temperature profile is fully described by the competition between both methods. These findings provide valuable information into the internal structure and evolution of pulsed-power plasma jets in regimes dominated by geometric shaping and radiative cooling, demonstrating experimental control over flow acceleration and collimation relevant to both laboratory and astrophysical contexts.

Physics - Plasma physics↗

Counter-Current Flow Limitation Studies in Complex Geometries Utilizing Interface Capturing Simulations Coupled with PID Flow Rate Controller

In nuclear thermal-hydraulic studies, counter-current flow limitation (CCFL) typically refers to steam rising at a fast rate such that it prevents coolant from draining down within a confined channel. CCFL is a crucial issue in nuclear reactor safety analysis. This study investigates CCFL in debris bed channels using high-resolution interface-capturing simulations. A novel proportional-integral-derivative flow rate controller is developed to efficiently achieve the CCFL conditions. Verification studies confirm that CCFL occurs under the same conditions with or without the controller, demonstrating that PID control ensures accurate prediction. Three debris bed channel geometries were examined: a cylindrical channel, a channel with small obstacles, and a channel with large obstacles. Results show that obstacles significantly impact flow behavior, interfacial shear, wall shear, and pressure gradients required for CCFL. Furthermore, the comparison with experimental data confirmed that simulations incorporating geometric complexities align more closely with experimental CCFL conditions. A pressure gradient correlation was also developed for CCFL prediction.

Counter-current flow limitation↗

Two-phase flow numerical analysis of electrode geometry for alkaline water electrolyzers

Hydrogen is a promising component of a future energy-secure and efficient economy, but its competitiveness depends on reducing production costs. One strategy is to operate alkaline water electrolyzers at higher current densities to increase output. However, this intensifies performance losses due to gas bubble accumulation, which blocks transport pathways and deactivates electrochemically active surfaces. Enhancing bubble evacuation through electrode design is therefore essential. Previous studies have explored various approaches — such as modifying surface morphology, applying sonication or pressure modulation, and introducing surfactants — but these efforts have addressed a limited range of conditions due to the complexity of two-phase flow and electrode geometries. Experiments have also largely been focused on either cell level improvements, which lack the information necessary to isolate each contributing factor, or on modified geometries that are not relevant to practical cell operation. From a modeling perspective, conventional Eulerian multiphase models do not track the complex gas–liquid interfacial dynamics and often neglect surface tension and contact angle effects, reducing their predictive accuracy. To provide insights on the effects of different electrode geometries on the performance of alklaine water electrolyzers this work employs an immersed boundary volume-of-fluid method to simulate bubble behavior in 3D porous electrodes. Multiple base electrode geometries, typically used in practice, with varying porosity are evaluated under a constant surface gas generation rate. Simulation data is analyzed to quantify electrode gas coverage, bubble size dynamics and other relevant metrics. Results show that porosity strongly influences bubble accumulation on electrode surfaces, with higher porosity reducing gas coverage, and its not strictly dependent on the electrode geometry. However, the electrode’s base geometry significantly affects gas accumulation at the separator gap, independent of porosity. A foam electrode geometry resulted in the lowest gas coverage of all electrodes with a median volumetric gas coverage of 11%, but at the cost of a 70% reduction in active area compared with the largest surface area electrode, while gyroid electrodes showed the best trade-off between gas coverage, particularly at the separator surface, and electrochemically active area. In conclusion, the results highlight the need for holistic electrode design strategies.

Alkaline↗

Window Cooling Studies and Disk Vibration Testing on a Subset of Mo-100 Disks

Production of metastable Technetium-99 (Tc-99m), a radioactive tracer that emits gamma rays, is vital to the medical imaging community. Tc-99m is extracted from the decay of Molybdenum-99 (Mo-99) which has a half-life of about 2-3 days. The work presented in this report is part of the NNSA’s mission to produce Mo-99 commercially, within the US, without the use of highly enriched uranium (HEU) in support of nonproliferation and global security. Los Alamos National Laboratory (LANL) is working with NorthStar Medical Radioisotopes (NMR) on their efforts to produce Mo-99 through the irradiation of Mo-100 targets using an electron beam. The NMR target comprises a stack of approximately 60-70 Mo-100 disks with diameter 24 mm and thickness 0.74 mm held in stainless steel laminations, each separated using 0.25 mm thick stainless-steel spacers. The symmetric target stack is housed in an Inconel vessel with two Inconel windows on either side. Two electron accelerators are used to produce 40 MeV, 3.16 µA electron beams each that penetrate the Inconel windows and irradiate the Mo-100 disks. Approximately 90% of the total 250 kW beam power is deposited in the NMR target during the irradiation process, with a smaller percentage adding up to 2.2 kW of heat deposited on the Inconel window. During irradiation, pressurized helium gas flows through thin gaps between the disks cooling the beam window, target disks, disk laminations and spacers. Both NMR and LANL have found during cold testing of the target system (no heat deposition) that the Mo 100 disks undergo significant mass loss and disk breakage due to vibrations induced by the flowing helium gas. The mass loss is not only undesirable due to monetary loss from reduced final quantities of Mo-99, but also due to the hazards associated with radioactive material trapped in the cooling lines and particle filters. The effect of flow rate and target geometry on the flow induced vibrations need to be quantified, and recommendations provided to minimize this mass loss. LANL has previously also tested NMR’s Inconel beam window by heating the window, while flowing pressurized helium, using the average heat deposited on the window. However, the NMR beam is pulsed with a duty cycle of 12.5%, which introduces oscillation in temperature around the nominal 600 °C steady state value with each pulse. Available fatigue curves for Inconel are few, established for room temperature, and they are based on mechanical strain cycles not thermally induced strain as in the NMR target. The effect of pulsed beam heating on the Inconel window therefore needs to be quantified. This report details the experiments conducted to assess the factors that lead to mass loss in the NMR target disks as well as to understand the effect of a pulsed beam on NMR’s Inconel window. This work describes LANL’s experimental characterization of the flow induced vibrations and disk mass loss in a reduced scale set-up containing 5 to 10 Mo-100 disks. We use high speed imaging, displacement measurements and microphone measurements combined with signal processing to estimate the vibration frequency of each disk. The effect of disk thickness, target fit and duration of testing on the mass loss is described. We find that in the current configuration of NMR targets, the vibrations and mass loss on the first disk are minimized, while those in the adjacent disks are highest. The microphone and high-speed image data show that increased flow rates and increased duration of testing increases vibration frequency and mass loss. The mass loss is due to both disk rotation and back and forth motion. There are visible wear marks on the disks with the highest mass loss. We also note that the current NMR window gap reduces flow induced vibrations compared to the previous smaller gaps. Improved target holders significantly reduce disk mass loss to almost negligible quantities. This work finds that the larger window to first disk gap and improved target holder geometry should allow NMR to successfully conduct irradiations with minimal mass loss. The window tests were conducted to understand the effect of a pulsed beam on both the window longevity and to estimate the window temperature and displacement during pulsing. The experiments presented here were performed at significantly low power, due to the limitations of the induction heating system. The window temperature rose to approximately 73 °C with a significantly reduced power of 45 W without beam pulsing. With a 5 Hz pulse rate, 12.5% duty cycle, the window temperature remained constant at 26 °C. These experiments will be repeated with improved coil geometry and reported in upcoming journal papers.

42 ENGINEERING↗

Fine-tuning machine-learned particle-flow reconstruction for new detector geometries in future colliders

We demonstrate transfer learning capabilities in a machine-learned algorithm trained for particle-flow reconstruction in high energy particle colliders. This paper presents a cross-detector fine-tuning study, where we initially pretrain the model on a large full simulation dataset from one detector design, and subsequently fine-tune the model on a sample with a different collider and detector design. Specifically, we use the Compact Linear Collider detector (CLICdet) model for the initial training set and demonstrate successful knowledge transfer to the CLIC-like detector (CLD) proposed for the Future Circular Collider in electron-positron mode. We show that with an order of magnitude less samples from the second dataset, we can achieve the same performance as a costly training from scratch, across particle-level and event-level performance metrics, including jet and missing transverse momentum resolution. Furthermore, we find that the fine-tuned model achieves comparable performance to the traditional rule-based particle-flow approach on event-level metrics after training on 100,000 CLD events, whereas a model trained from scratch requires at least 1 million CLD events to achieve similar reconstruction performance. To our knowledge, this represents the first full-simulation cross-detector transfer learning study for particle-flow reconstruction. These findings offer valuable insights towards building large foundation models that can be fine-tuned across different detector designs and geometries, helping to accelerate the development cycle for new detectors and opening the door to rapid detector design and optimization using machine learning.

43 PARTICLE ACCELERATORS↗

Power performance and loads characterization of laboratory-scale cross-flow rotors fabricated using additive manufacturing

Tidal energy conversion is a relatively new application for additive manufacturing (AM), where the focus has been on fabricating axial-flow turbine blades. AM techniques add material precisely where it is needed, creating more complex shapes with less waste. Cross-flow rotor geometry presents an opportunity for AM to improve rotor performance by fabricating features that cannot be created economically via conventional manufacturing. The challenges associated with using AM in cross-flow design include water resistance and degradation over time while retaining a level of quality equivalent to conventionally machined parts. In this work, AM materials were tested by environmentally conditioning samples in a seawater tank for 5 months, followed by performance and phase-resolved load testing of laboratory-scale rotors in a hydraulic flume. We found that while metals like titanium and Inconel have excellent performance in marine environments, achieving the desired geometry and performance is difficult. Thermoplastics degraded in seawater but were easier to form into desired geometries and could exceed the performance of an aluminum control rotor. Warping and surface finish were significant detractors from AM rotor performance. These results suggest that the primary benefits of using AM for cross-flow rotors is to quickly fabricate and test unconventional rotor geometries.

16 TIDAL AND WAVE POWER↗

Surrogates for Valve-Controlled Pipe Flow: Accelerating Nuclear Reactor Design

Neural surrogate models are developed to replace expensive steady-state RANS CFD simulations for valve-controlled pipe flow in nuclear reactor design. Using parametric CFD data generated with MOOSE Pronghorn across a range of valve geometry and flow conditions, three approaches are compared: a POD-based reduced-order model, a structured UNet on a cylindrical grid, and unstructured models (DeepONet and BiStride MeshGraphNet) on nondimensionalized point clouds. POD achieves the highest accuracy (99%) with fast inference but requires storing all solution snapshots, while the DeepONet and BSMS-GNN both achieve ~89% accuracy at sub-second inference, with the BSMS-GNN offering superior geometric generalizability. These surrogates enable rapid ranking of candidate valve designs and can warm-start CFD solvers to accelerate convergence, supporting agentic design iteration on the Prometheus platform.

42 - ENGINEERING↗

Characterizing in-stream turbulent flow for tidal energy converter siting in Cook Inlet, Alaska

Cook Inlet in Alaska is the most promising location for tidal energy development in the U.S. due to its significant tidal range of approximately 10 meters and high volume flux. The inlet's unique geometry and flow characteristics make it the most energetic tidal stream in the nation, with GW-scale potential energy capacity. With the growing interest in tidal energy converter (TEC) deployment in this area, we implemented a regional-scale, 3D hydrodynamic modeling framework to predict tidal current and turbulence characteristics that can assist TEC designers and project managers. We validated the model results extensively using various datasets collected with bottom-mounted acoustic Doppler current profilers and velocimeters. The comparison between the model outputs and observational data highlighted the effectiveness of the 3D FVCOM model and the Mellor-Yamada Level 2.5 Turbulence Model in accurately assessing macro-scale kinetic energy, turbulence intensity, and the production and dissipation rates at a prospective TEC site. Using two months of model simulation data, we examined the channel cross-section for TEC deployment, focusing on undisturbed power density and macro-scale turbulent properties. Further, our findings indicate that understanding the turbulence characteristics and flow properties can enhance Stage I/II resource characterization by identifying optimal locations for TECs and their layouts within the channel. Furthermore, we demonstrated that TEC designers can utilize macro-scale turbulence data from 3D coastal models as boundary conditions for other turbulence models, allowing for a more detailed resolution of the turbulence structure at TEC siting locations. Ultimately, this work emphasizes the importance of estimating flow and turbulence conditions in energetic systems to understand turbulent sites better and improve resource characterization.

16 TIDAL AND WAVE POWER↗

Flow instabilities in helical-coil steam generators for small modular reactors: A review

Here, this study covers the research and discoveries in two-phase flow-boiling instabilities available in the literature—specifically for a helical-coil steam generator (HCSG), including experimental findings, theoretical research, computational models, and system code analyses—supporting research and development of representative small modular reactors (SMRs). Like other new and advanced reactor systems, water-cooled SMRs require experimental data from both integral and separate thermal-hydraulics test facilities for the verification and validation (V&V) of the computational models and computer codes in order to design and obtain regulatory approval. The complex dynamics of two-phase flow-boiling instabilities includes flow regimes physics phenomena, flow-channel geometries, heat-transfer behavior, and interactions among the solid–liquid-gas within the system boundary, all of which are pivotal for understanding the design and operational challenges of SMRs. This study focuses on identifying the relevant knowledge gaps on boiling instabilities—specifically for a HCSG—and provides insights about future research direction optimizing the transport of thermal energy, mass-flow rates, and boundary conditions that ensure the adequate heat-transfer performance, operational stability, and safety associated with SMR systems.

20 FOSSIL-FUELED POWER PLANTS↗

Bipolar plate flow channel designs for vanadium redox flow battery: a review

Vanadium redox flow battery is one of the preferred systems for grid scale energy storage due to long service life (>20000 cycles), higher efficiency (>85 %), deep discharge capability (>95 % DoD), and inherent scalability and safety. Among system components, flow field is most critical as it governs electrolyte distribution, mass transport and hydraulic performance. Here, this review examines emerging flow channel geometries, highlighting the impact of channel width (0.66 to 1.5 mm), depth (1 to 1.5 mm) and land width (0.5 to 1.5 mm) can reduce pressure drop to <10 kPa while enabling power densities above 600 mW.cm -2 . A key finding is that low channel width to depth ratio (<1) enhances voltage and energy efficiencies by improving under rib convection. The review also provides an overview of progress and perspective in bipolar plate materials, manufacturability, and shunt current mitigation strategies for stack scaling up. Cost analysis emphasizes the influence of flow field designs on the levelized cost of storage and pathways towards the US DOE's $\$$0.05 per kWh energy generation cost target. In addition, opportunities for AI/ML/DT tools assisted design and data driven optimization strategies are also outlined to accelerate next generation flow field development.

Efficiency optimization↗