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High-Fidelity CFD Assessments of Flow Resistance in a 61-Pin Wire-Wrapped Assembly with Partially Blocked Channels
The examination of thermal-hydraulic behaviors in wire-wrapped rod bundles continues to be an active area of research. The sodium fast reactor, a prominent candidate in next-generation nuclear designs, utilizes a hexagonal configuration of wire-wrapped fuel pins. Here, the potential for channel blockage within this compact arrangement poses a significant safety challenge, spurring a number of recent experimental and computational investigations to evaluate its impact on flow and heat transfer. The present work aims to benchmark the high-fidelity NekRS computational fluid dynamics (CFD) solver in predicting the pressure drops associated with substantial blockages, using available experimental data as a reference. A 61-pin wire-wrapped fuel assembly with two flow blockage configurations has been simulated and investigated at a range of low to moderate Reynolds numbers (487 ≤ Re ≤ 14 600). The NekRS solver demonstrates an exponential reduction of spatial discretization error with increasing polynomial order. The high level of agreement between the numerical results and measured data confirms the accuracy and consistency of the present numerical approach. This benchmark study establishes the capability of NekRS to perform reliable hydrodynamic simulations for sodium fast reactor applications and supports its use in design, licensing, and safety analyses.
Internal aerodynamics of a generic three-dimensional scramjet inlet at Mach 10
A combined computational and experimental parametric study of the internal aerodynamics of a generic three-dimensional sidewall compression scramjet inlet configuration at Mach 10 has been performed. The study was designed to demonstrate the utility of computational fluid dynamics as a design tool in hypersonic inlet flow fields, to provide a detailed account of the nature and structure of the internal flow interactions, and to provide a comprehensive surface property and flow field database to determine the effects of contraction ratio, cowl position, and Reynolds number on the performance of a hypersonic scramjet inlet configuration. The work proceeded in several phases: the initial inviscid assessment of the internal shock structure, the preliminary computational parametric study, the coupling of the optimized configuration with the physical limitations of the facility, the wind tunnel blockage assessment, and the computational and experimental parametric study of the final configuration. Good agreement between computation and experimentation was observed in the magnitude and location of the interactions, particularly for weakly interacting flow fields. Large-scale forward separations resulted when the interaction strength was increased by increasing the contraction ratio or decreasing the Reynolds number.
Effects of microgravity on osteoblast growth
Studies from space flights over the past two decades have demonstrated that basic physiological changes occur in humans during space flight. These changes include cephalic fluid shifts, loss of fluid and electrolytes, loss of muscle mass, space motion sickness, anemia, reduced immune response, and loss of calcium and mineralized bone. The cause of most of these manifestations is not known and until recently, the general approach was to investigate general systemic changes, not basic cellular responses to microgravity. Recently analyzed data from the 1973-1974 Skylabs disclose that there is a rise in the systemic hormone, cortisol, which may play a role in bone loss in flight. In two flights where bone growth was measured (Skylabs 3 and 4), the crew members had a significant loss of calcium accompanied by a rise in 24 hour urinary cortisol during the entire flight period. In ground-based work on osteoblasts, we have demonstrated that equivalent amounts of glucocorticoids can inhibit osteoblast cell growth. In addition, this laboratory has recently studied gene growth and activation of mouse osteoblasts (MC3T3-E1) during spaceflight. Osteoblast cells were grown on glass coverslips, loaded in the Biorack plunger boxes 18 hours before launch and activated 19 hours after launch in the Biorack incubator under microgravity conditions. The osteoblasts were launched in a serum deprived state, activated and collected in microgravity. Samples were collected at 29 hours after sera activation (0-g, n=4; 1-g, n=4). The osteoblasts were examined for changes in gene expression and cell morphology. Approximately one day after growth activation, remarkable differences were observed in gene expression in 0-g and 1-g flight samples. The 0-g activated cells had increased c-fos mRNA when compared to flight 1-g controls. The message of immediate early growth gene, cox-2 was decreased in the microgravity activated cells when compared to ground or 1-g flight controls. Cox-1 was not detected in any of the samples. There were no significant differences in the expression of actin mRNA between the 0-g and 1-g samples. These data indicate that quiescent osteoblasts are slower to enter the cell cycle in microgravity, suggesting that the force of gravity itself may be a significant factor in bone loss in spaceflight. Preliminary data from our STS 76 flight experiment support our hypothesis that a basic biological response occurs at the tissue, cellular, and molecular level in 0-g. Here we examine ground-based and space flown data on osteoblast growth in ground-based experiments mimicking space flight conditions and in microgravity to simulate lack of gravity stress to help us understand the mechanism of bone loss by experiments.
Surface chemistry models for GaAs epitaxial growth and hydride cracking using reacting flow simulations
Hydride vapor phase epitaxy (HVPE) is a promising technology that can aid in the cost reduction of III-V materials and devices manufacturing, particularly high-efficiency solar cells for space and terrestrial applications. However, recent demonstrations of ultrafast growth rates (~500 µm/h) via uncracked hydrides are not well described by present models for the growth. Therefore, it is necessary to understand the kinetics of the growth process and its coupling with transport phenomena, so as to enable fast and uniform epitaxial growth. In this work, we derive a kinetic model using experimental data and integrate it into a computational fluid dynamics simulation of an HVPE growth reactor. We also modify an existing hydride cracking model that we validate against numerical simulations and experimental data. Here, we show that the developed growth model and the improved cracking model are able to reproduce experimental growth measurements of GaAs in an existing HVPE system.
Symbolic diagnostics to interpret and analyze neural network models
Embedded machine-learned models (EMLMs) have the promise to improve the predictive accuracy of engineering simulators in environments of national interest. EMLMs often comprise complex input-output maps (e.g., neural networks), which make them unamenable to rigorous analysis and generally difficult to interpret. In the face of decades of theory, this lack of interpretability is a significant barrier to building confidence in these models. This work outlines an approach to interpret EMLMs using sparse polynomial regression for comparison with theoretical understanding. To do so, we build on the concept of Locally Interpretable Model-agnostic Explanations (LIME) using physics-informed clustering, prototype selection, and library construction. While general, we demonstrate our method on tensor-basis neural networks used in Reynolds-Averaged Navier-Stokes simulations of hypersonic fluid flows. Results are presented for a simulated toy model and for direct numerical simulations (DNS) of turbulent flows over a flat plate.
Electromagnetic Energy-Assisted Thermal Conversion of Fossil-Based Hydrocarbons to Low-Cost Hydrogen
The goal of this project was to develop and optimize catalysts for methane decomposition, particularly focusing on regeneration via an electromagnetic energy-assisted mechanism, to produce hydrogen more cost-effectively compared to electrolysis routes. To achieve this goal, the project pursued several key objectives. The project began with the preparation and testing of various catalysts. A nickel-silica based catalyst was identified as the most promising material for the pyrolysis of methane into carbon and hydrogen. Kinetic parameters for methane decomposition were determined, aiding in computational modeling efforts. Structured catalysts were investigated, highlighting the need for frequent cleaning or regeneration to maintain performance, with methane conversion rates exceeding 70% in tube furnace tests. Computational fluid dynamics modeling was employed to optimize reactor designs and electrode angles, leading the project team to propose a multi-compartment thermal conversion system for larger setups. This modeling work was important in understanding reaction characteristics, carbon deposition rates, and temperature profiles under various conditions. A bench-scale reactor system was assembled to evaluate catalyst regeneration using electromagnetic energy-assisted mechanisms. Experiments demonstrated the potential for carbon removal, though further optimization is needed. The carbon produced from the methane conversion process was evaluated for potential use in lithium-ion battery electrodes. The carbon exhibited properties similar to commercially available high-purity multi-walled carbon nanotubes and nanofibers, with a carbon content greater than 95%. Coin cell batteries assembled with this carbon showed that lower replacement levels (10% to 33%) outperformed the control group, improving specific capacity density and stability. However, higher replacement levels (100%) demonstrated poorer performance, suggesting that excessive carbon substitution negatively impacts battery performance. These findings indicate the potential marketability of the produced carbon as a component in lithium-ion batteries, though further testing is necessary to confirm long-term advantages and disadvantages associated with the use of the carbon product. These results however justified further technoeconomic assessments to determine if the process can provide low-cost hydrogen. The economic feasibility and technical performance of methane decomposition for hydrogen production were assessed, focusing on three plant configurations: 100E (electrically heated), 100C (combustion heated using produced hydrogen), and PE-Hybrid (a combination of pyrolysis (indicating decomposition) and electrolysis). The Levelized Cost of Hydrogen (LCOH) for the pyrolysis configurations was found to be approximately 25% lower than that of electrolysis. The 100E configuration had the lowest LCOH at $\$$3.12/kg. Including carbon product sales significantly improved the economics, with the 100C configuration achieving a negative LCOH of -$\$$0.35/kg. The PE-Hybrid configuration was not economically advantageous compared to pure pyrolysis plants due to its complexity and additional equipment requirements. Ultimately, methane pyrolysis presents a viable method for near carbon dioxide-free hydrogen production, with significant economic advantages over electrolysis, especially when considering the sale of carbon byproducts. The 100E and 100C configurations showed the most promise, with the choice between them ultimately depending on the prices of power and natural gas. In conclusion, this technology has the potential to lower hydrogen production costs by leveraging the methane decomposition process with the sale of valuable carbon byproducts. By optimizing catalyst performance and integrating electromagnetic energy-assisted regeneration, the process can achieve higher efficiency and economic viability, making it a competitive alternative to traditional hydrogen production methods.
Abstract for CRADA among NETL, Mälardalen University, University College Cork (acting through its Tyndall National Institute), and Micro Electricity Generation Association
GeoCoHorT aims to accelerate the transition to 4 th generation district heating and cooling (4GDHC) in Europe and globally, by assessing, optimizing, and demonstrating the integration of shallow geothermal heat extraction with other renewable sources and smart buildings. The target geo-source is ground water from River Shannon (Limerick, Ireland), which will provide both an efficiency and noise-reduction benefit to the micro-district and a method of combatting climate-change-warming of the Shannon Estuary. The heat from this low-temperature source will be recycled and supplied to a smart district located in Limerick, Ireland, through heat pumps powered by renewable electricity and by means of a suitable DH network design. The mandate is to find solutions that work for entire communities in a fair and sustainable manner, with the involvement of the communities themselves to highlight their needs. The project brings together four partners from Ireland, Sweden, and the U.S.A. with strong multi-disciplinary competencies. The Tyndall Institute at University of Cork (UCC) and Mälardalen University (MDU) will design and optimize the 4GDH micro-district system, and the Micro Electricity Generation Association (MEGA) will work with the community to build a sense of ownership of the Climate Challenge and ensure close community involvement. The National Energy Technology Laboratory of the U.S. Department of Energy (NETL) will design the prospective geo-fluid loop to optimize heat-extraction effectiveness with ecological safety and assess the environmental benefits of the proposed solutions. Industrial advisors (Eskilstuna Strängnäs Energi och Miljö (ESEM) and Mimer in Sweden, and Smart MPOWER in Ireland) will steer the technology development to meet the needs of public utilities and consumers. Current infrastructure in the smart district in Limerick (demonstration site of an EU Lighthouse project) will be exploited and modified with support of MEGA, UCC, and MPOWER to integrate micro-DH from low-temperature heat sources, such as the river heat, and to allow increasing penetration of prosumers in the grid. Additional case studies will be developed with the help of industrial advisors to extend the results to other regions (e.g., Sweden and USA) and provide valuable insights for the development of 4GDH worldwide.
The effect of temperature induced surface tension gradients on bubble mechanics
Experiments were conducted to examine in detail the influence of surface tension gradient induced flow, the Marangoni effect. One set of studies provided visual results that demonstrated the occurrence and magnitude of the Marangoni effect. Another portion of the work was directed to bubble force measurements. These studies used in deflection of a very fine cantilevered wire with an attached bubble as a means of measuring force with and without temperature gradients. The experimental force data were found to check existing theoretical predictions reasonably well except for the case where the test fluid had a sizeable vapor pressure. In this situation the thermophoretic force on the bubble was much higher than predicted.
Accurate and Data‐Efficient Micro X‐ray Diffraction Phase Identification Using Multitask Learning: Application to Hydrothermal Fluids
Traditional analysis of highly distorted micro X‐ray diffraction (μ‐XRD) patterns from hydrothermal fluid environments is a time‐consuming process, often requiring substantial data preprocessing and labeled experimental data. Herein, the potential of deep learning with a multitask learning (MTL) architecture to overcome these limitations is demonstrated. MTL models are trained to identify phase information in μ‐XRD patterns, minimizing the need for labeled experimental data and masking preprocessing steps. Notably, MTL models show superior accuracy compared to binary classification convolutional neural networks. Additionally, introducing a tailored cross‐entropy loss function improves MTL model performance. Most significantly, MTL models tuned to analyze raw and unmasked XRD patterns achieve close performance to models analyzing preprocessed data, with minimal accuracy differences. This work indicates that advanced deep learning architectures like MTL can automate arduous data handling tasks, streamline the analysis of distorted XRD patterns, and reduce the reliance on labor‐intensive experimental datasets.
Fiber Sorbents – A Versatile Platform for Sorption-Based Gas Separations
Increasing demand for high-purity fine chemicals and a drive for process intensification of large-scale separations have driven significant work on the development of highly engineered porous materials with promise for sorption-based separations. While sorptive separations in porous materials offer energy-efficient alternatives to longstanding thermal-based methods, the particulate nature of many of these sorbents has sometimes limited their large-scale deployment in high-throughput applications such as gas separations, for which the necessary high feed flow rates and gas velocities accrue prohibitive operational costs. These processability limitations have been historically addressed through powder shaping methods aimed at the fabrication of structured sorbent contactors based on pellets, beads or monoliths, commonly obtained as extrudates. These structures overcome limitations such as elevated pressure drops commonly recorded across powder adsorption beds but often accrue thermal limitations arising from elevated particle density and aggregation, which ultimately cap their maximum separation performance. Furthermore, the harsh mechanical strain to which powder particles are subjected during contactor fabrication, in the form of extrusion/compression forces, can result in partial pore occlusion and framework degradation, further limiting their performance. Here, we present the development of porous fiber sorbents as an alternative sorbent contactor design capable of addressing sorbent processability limitations while enabling an array of performance-maximizing heat integration capabilities. This new sorbent form factor leverages pre-existing know-how from hollow fiber spinning to produce fiber-shaped sorbent contactors through the phase inversion of known polymers in a process known as dry-jet/wet quenching. The process of phase inversion allows microporous sorbent particles to be latched onto a macroporous polymer matrix under mild processing conditions, thus making it compatible with soft porous materials prone to amorphization under traditional pelletization conditions. Sorbent fibers can be created with different geometries through control of the spinning apparatus and process, offering the possibility to produce monolithic and hollow fibers alike, the latter of which can be integrated with thermalization fluid flows. In this Account, we summarize our progress in the field of fiber sorbents from both design and application standpoints. We further guide the reader through the evolution of this field from the early inceptive work on zeolite hollow fibers to recent developments on MOF fibers. We highlight the versatile nature of fiber sorbents, both from the composition, fabrication and structure points of view, and further demonstrate how fiber sorbents offer alternative paths in tackling new and challenging chemical separation challenges like direct air capture (DAC), with a final perspective on the future of the field.
Stabilizing effect of enhanced resistivity on peeling-ballooning instabilities on EAST
Previous stability analysis of NSTX equilibrium with lithium-conditioning demonstrates that enhanced resistivity due to the increased effective charge number Z eff (i.e. increased impurity level) can provide a stabilizing effect on low-n edge localized modes. This paper extends the resistivity stabilizing effect to the intermediate-n peeling-ballooning (PB) instabilities with the linear stability analysis of EAST high-confinement mode equilibria in NIMROD two-fluid calculations. However, in this work, the resistivity stabilizing effect on PB instabilities in the EAST tokamak appears weaker than that found in NSTX. This work may provide better insight into the physical mechanism behind the beneficial effects of impurities on pedestal stability.
Novel Thermal Powered Technology for UUV Persistent Surveillance
Buoyancy Generation: Various technology attempts include melting a wax, which pushes directly against a piston (U.S. Patent 5,291,847) or against a bladder (Webb Research), using ammonia or Freon 21 (U.S. Patent 5,303,552), and using solar heat to expand an oil (www.space.com, April, 10, 2002). All these heat-activated buoyancy control designs have thus far proved impractical and have ultimately failed during repeated cycling in ocean testing. JPL has demonstrated fully reversible 10 C encapsulated wax phase change, which can be used to change buoyancy without electrical hydraulic pumps. This technique has greatly improved heat transfer and much better reversibility than previous designs. Power Generation: Ocean Thermal Energy Conversion (OTEC) systems have been designed that transfer deep, cold sea water to the surface to generate electricity using turbine cycles with ammonia or water as the working fluid. JPL has designed several UUV systems: 1) Using a propeller water turbine to generate power on a gliding submersible; 2) Employing a compact CO2 turbine cycle powered by moving through thermoclines; and 3) Using melted wax to directly produce power through a piston-geared generator.
Processing and Preparation of Advanced Stirling Convertors for Extended Operation at NASA Glenn Research Center
The U.S. Department of Energy (DOE), Lockheed Martin Space Company (LMSC), Sunpower Inc., and NASA Glenn Research Center (GRC) have been developing an Advanced Stirling Radioisotope Generator (ASRG) for use as a power system on space science missions. This generator will make use of the free-piston Stirling convertors to achieve higher conversion efficiency than currently available alternatives. NASA GRC is supporting the development of the ASRG by providing extended operation of several Sunpower Inc. Advanced Stirling Convertors (ASCs). In the past year and a half, eight ASCs have operated in continuous, unattended mode in both air and thermal vacuum environments. Hardware, software, and procedures were developed to prepare each convertor for extended operation with intended durations on the order of tens of thousands of hours. Steps taken to prepare a convertor for long-term operation included geometry measurements, thermocouple instrumentation, evaluation of working fluid purity, evacuation with bakeout, and high purity charge. Actions were also taken to ensure the reliability of support systems, such as data acquisition and automated shutdown checkouts. Once a convertor completed these steps, it underwent short-term testing to gather baseline performance data before initiating extended operation. These tests included insulation thermal loss characterization, low-temperature checkout, and full-temperature and power demonstration. This paper discusses the facilities developed to support continuous, unattended operation, and the processing results of the eight ASCs currently on test.
Processing and Preparation of Advanced Stirling Convertors for Extended Operation
The U.S. Department of Energy (DOE), Lockheed Martin Space Company (LMSC), Sunpower Inc., and NASA Glenn Research Center (GRC) have been developing an Advanced Stirling Radioisotope Generator (ASRG) for use as a power system on space science missions. This generator will make use of the free-piston Stirling convertors to achieve higher conversion efficiency than currently available alternatives. NASA GRC is supporting the development of the ASRG by providing extended operation of several Sunpower Inc. Advanced Stirling Convertors (ASCs). In the past year and a half, eight ASCs have operated in continuous, unattended mode in both air and thermal vacuum environments. Hardware, software, and procedures were developed to prepare each convertor for extended operation with intended durations on the order of tens of thousands of hours. Steps taken to prepare a convertor for long-term operation included geometry measurements, thermocouple instrumentation, evaluation of working fluid purity, evacuation with bakeout, and high purity charge. Actions were also taken to ensure the reliability of support systems, such as data acquisition and automated shutdown checkouts. Once a convertor completed these steps, it underwent short-term testing to gather baseline performance data before initiating extended operation. These tests included insulation thermal loss characterization, low-temperature checkout, and full-temperature and power demonstration. This paper discusses the facilities developed to support continuous, unattended operation, and the processing results of the eight ASCs currently on test.
Synthetic Jet Interaction With A Turbulent Boundary Layer Flow
Perhaps one of the more notable advances to have occurred in flow control technology in the last fifteen years is the application of surface-issuing jets for separation control on aerodynamic surfaces. The concept was introduced by Johnston and Night (1990) who proposed using circular jets, skewed and inclined to the wall, to generate streamwise vortices for the purpose of mitigating boundary layer separation. The skew and inclination angles have subsequently been shown to affect the strength and sign of the ensuing vortices. With a non-circular orifice, in addition to skew and inclination, the yaw angle of the major axis of the orifice can influence the flow control effectiveness of the jet. In particular, a study by Chang arid Collins (1997) revealed that a non-circular orifice, yawed relative to the freestream, can be used to control the size and strength of the vortices produced by the control jet. This early work used jets with only a steady injection of mass. Seifert et al. revealed that an unsteady blowing jet, could be as effective at separation control as a steady jet but with less mass flow. Seifert et al. showed that small amplitude blowing oscillations superimposed on a low momentum steady jet Was the most effective approach to delaying separation on a NACA 0015 airfoil at post-stall angles of attack. More recent work suggests that perhaps the most efficient jet control effect comes from a synthetic (oscillatory) jet where the time-averaged mass flux through the orifice is zero, but the net wall normal momentum is non-zero. The control effectiveness of synthetic jets has been demonstrated for several internal and external flow fields used synthetic jet control on a thick, blunt-nosed airfoil to delay stall well beyond the stall angles for the uncontrolled airfoil and with a dramatic increase in the lift-to-drag performance. Amitay et al. used an array of synthetic jets to mitigate flow separation in curved and diffusing ducts. While the control effectiveness of synthetic jet actuators in an application setting has been confirmed through a number of studies, the fluid dynamic mechanism by which control is effected is not well understood. Issues like yaw angle arid velocity ratio that have been studied for steady control jets have not been investigated for synthetic jets. Moreover, the role played by the inherently unsteady nature of a synthetic jet in the interaction with the controlled flow is not known. Some recent work by Rinehart and Glazer and Smith suggests that away from tile immediate vicinity of the jet orifice the flow field is steady in the mean, and that the interaction of a synthetic jet and a boundary layer creates a secondary flow in the boundary layer consisting primarily of streamwise vortices.
Validation and parameterization of a novel physics-constrained neural dynamics model applied to turbulent fluid flow
We report, in fluid physics, data-driven models to enhance or accelerate time to solution are becoming increasingly popular for many application domains, such as alternatives to turbulence closures, system surrogates, or for new physics discovery. In the context of reduced order models of high-dimensional time-dependent fluid systems, machine learning methods grant the benefit of automated learning from data, but the burden of a model lies on its reduced-order representation of both the fluid state and physical dynamics. In this work, we build a physics-constrained, data-driven reduced order model for Navier–Stokes equations to approximate spatiotemporal fluid dynamics in the canonical case of isotropic turbulence in a triply periodic box. The model design choices mimic numerical and physical constraints by, for example, implicitly enforcing the incompressibility constraint and utilizing continuous neural ordinary differential equations for tracking the evolution of the governing differential equation. We demonstrate this technique on a three-dimensional, moderate Reynolds number turbulent fluid flow. In assessing the statistical quality and characteristics of the machine-learned model through rigorous diagnostic tests, we find that our model is capable of reconstructing the dynamics of the flow over large integral timescales, favoring accuracy at the larger length scales. More significantly, comprehensive diagnostics suggest that physically interpretable model parameters, corresponding to the representations of the fluid state and dynamics, have attributable and quantifiable impact on the quality of the model predictions and computational complexity.
Simulations of edge and SOL turbulence in diverted negative and positive triangularity plasmas
Optimizing the performance of magnetic confinement fusion devices is critical to achieving an attractive fusion reactor design. Negative triangularity (NT) scenarios have been shown to achieve excellent levels of energy confinement, while avoiding edge localized modes. Modeling turbulent transport in the edge and SOL is key in understanding the impact of NT on turbulence and extrapolating the results to future devices and regimes. Previous gyrokinetic turbulence studies have reported beneficial effects of NT across a broad range of parameters. However, most simulations have focused on the inner plasma region, neglecting the impact of NT on the outermost edge. In this work, we investigate the effect of NT in edge and scrape-off layer simulations, including the magnetic X-point and separatrix. For the first time, we employ a multi-fidelity approach, combining global, non-linear gyrokinetic simulations with drift-reduced fluid simulations, to gain a deeper understanding of the underlying physics at play. First-principles simulations using the GENE-X code demonstrate that in comparable NT and PT geometries, similar profiles are achieved, while the turbulent heat flux is reduced by more than 50% in NT. Comparisons with results from the drift-reduced fluid turbulence code GRILLIX suggest that the turbulence is driven by trapped electron modes. The parallel heat flux width on the divertor targets is reduced in NT, primarily due to a lower spreading factor S.