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At least 757 records · Page 42

Magnetic Sorbent for the Removal of Selenium(IV) from Simulated Industrial Wastewaters: Determination of Column Kinetic Parameters

A novel meso- and microporous tire-derived-carbon support with magnetic iron oxide nanoparticle adsorbents that selectively adsorbs Se(IV) ions from simulated contaminated water has been developed. In this work, the physicochemical characteristics of the composite adsorbent are characterized with respect to porosity and surface area, chemical composition, and microstructure morphology. The kinetics of this composite adsorbent in a fixed-bed setting has been determined. Several column runs were conducted and analyzed by inductively coupled plasma-optical emission spectroscopy (ICP-OES) to determine the concentration gradient vs time. These results were then fit to a pseudo-second order rate law to obtain equilibrium values. Combining calculated equilibrium values with effluent concentration data, enabled the application of the Adams–Bohart model to determine reaction constants and column coefficients. Column parameters obtained from different flow rates and fittings of the Adams–Bohart model were remarkably consistent. These findings enable the application of this sorbent to fixed-bed column systems and opens up further research into mixed pollutants tests with real wastewater and scaling of selenium pollutant removal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Artificial gravity intermittent centrifugation as a space flight countermeasure

Head-down bed rest was used to simulate weightlessness in an experiment that examined variations in dose, time, and frequency of +Gz stimuli countermeasures. Results indicate that 4 hr. standing was most effective for orthostatic intolerance, walking was most effective in achieving peak oxygen consumption, 4 hr. of standing or walking had the best effect on plasma volume, and 4 hr. of walking was most effective in maintaining urinary calcium excretion.

NASA Discipline General Space Life Sciences↗

Twins Bed Rest Project: LBNP/Exercise Minimizes Changes in Lean Leg Mass, Strength and Endurance

Decreases in muscle strength and endurance frequently are observed in non-weightbearing conditions such as bed rest (BR), spaceflight or limb immobilization. Purpose: Ow purpose was to determine if supine treadmill exercise against simulated gravity, by application of lower body negative pressure (LBNP), prevents loss of lean leg mass, strength and endurance during 30 d of 6deg head-down bed rest (BR). Methods: Fifteen pairs of monozygous twins (8 male, 7 female pairs; 26+/-4 yrs; 170+/-12 cm; 62.6+/-11.3 kg; mean+/-SD) were subjects in the present study. One sibling of each pair of twins was randomly assigned to either an exercise (EX) or non-exercise (CON) group. The EX twin walked/jogged on a vertical treadmill within LBNP chamber 6 d/wk using a 40-min interval exercise protocol at 40-80% of pre-BR VO(sub 2peak). LBNP was adjusted individually for each subject such that footward force was between 1.0 and 1.2 times body weight (-53+/-5 mmHg LBNP). The CON twin performed no exercise during BR. Subjects performed isokinetic knee (60 and 120deg/s) and ankle (60deg/s) testing to assess strength and endurance (End) before and after BR. They also had their lean leg mass (L(sub mass)) evaluated by DEXA before and after BR. Results: Changes in peak torque (T(sub pk)) were smaller for flexion (flex) than for extension (ext) after BR and did not differ between groups. The CON group had larger decreases (P<0.05) in L(sub mass), knee and ankle ext T(sub pk), and knee ext End.

Amorim, Fabiano T.↗

Pilot Testing of a Modular Oxygen Production System Using Oxygen Binding Adsorbents (Final Report)

In this project, RTI and Air Liquide have focused on the development of innovative oxygen separation materials and technologies based on reversibly binding of oxygen to enable smaller and cheaper air separations. In alignment with that object the team has had multiple achievements to advance the technology including: Synthesized and characterized novel M-CoSalen (RTIO2Sorb-1) material which showed a dynamic oxygen adsorption capacity in excess of 1wt%. Developed synthesis routes for RTIO2Sorb-1 with commercially relevant techniques and produced batches of 0.25kg and over 4 kg of total synthesis. Synthesized and characterized extrudate forms of the RTIO2Sorb-1 with relevant crush strength and maintained dynamic oxygen adsorption capacity in near 1wt%. Developed techniques for forming structured beds in fiber shapes with conventional materials. Developed a model for O 2 sorption processes to analyze various bed configurations and cycle parameters. Studied classic O 2 solid sorbents reported in the literature to learn oxygen binding mechanisms. Design a 10 kg/day O 2 VPSA pilot system with 2 or 4-bed operation. Completed a techno-economic analysis based on the experimental results and modeling. The overall objective of the project was to design, fabricate, and test a modular O 2 production system and perform a techno-economic analysis (TEA) after testing to determine the cost-benefit of the advanced modular air separation system. The goals of this technology development project were to achieve a bed-size factor (BSF) of less than 600 lb-adsorbent/TPD O 2 (ton/day O 2 ) (as compared with the state-of-the-art BSF of 850), and O 2 -purity greater than 95% at a cost that is projected to be equivalent or lower than the current state of the art (SOTA), commercially available large-scale cryogenic air separation systems. To achieve these goals and objective, the project team executed on (1) oxygen binding adsorbent optimization and scale up, (2) adsorbent material formation process studies to form the adsorbent material into structured beds for rapid pressure swing adsorption (PSA) cycles with low pressure drop, fast mass transfer, and low attrition, (3) cycle development studies to optimize the PSA process, and (4) develop simulation tools for rapid cycle modeling and numerical evaluation/optimization.

20 FOSSIL-FUELED POWER PLANTS↗

Mercury Speciation During Vitrification of LAW

n this work, laboratory and engineering-scale tests were conducted that mimic the reactive environment of the Hanford Tank Waste Treatment and Immobilization Plant (WTP) low activity waste (LAW) melter and off-gas system in order to assess the speciation of mercury at select points in the processing system. The experimental protocols, test equipment, feed materials used, and rationale for testing are detailed in the Test Plan for this work. Particular attention was paid to the amount and speciation of mercury in submerged bed scrubber (SBS) solutions, which are intended to be recycled back to the melter feed at the WTP. Results are presented from detailed mercury analysis of these solutions using Environmental Protection Agency (EPA) Method 1630 and modifications to this method for dimethyl mercury and methyl mercury as well as EPA Method 1631 and modifications to this method for total, dissolved, elemental, suspended, and ionic mercury. Testing was conducted in two separate sets of experiments: (1) One set of tests (crucible-scale furnace tests) that involved heating small batches of mercury-spiked melter feed in crucibles to determine the amount of mercury retained in the glass and the species of mercury in the exhaust gases; (2) A second set of tests (DM10 melter tests) was planned that involved creating LAW melter plenum gas compositions using the DM10 melter system, injecting mercury into the off-gas stream, and passing that stream though a reactor that simulates various plenum gas conditions. Operational issues led to the need to use one of the VSL DM100 melters in place of the planned DM10 melter for these tests. The speciation of mercury after exposure to those conditions was monitored. In both sets of tests, the exhaust gases were run through a scrubber that was intended to mimic the LAW SBS in order to determine how much of the mercury exiting the melter would be retained in the primary off-gas system fluids and in what form. After passing through the SBS, the exhaust stream was analyzed to determine particulate, ionic, elemental, and total mercury passing downstream of the SBS. In tests employing gases derived from the DM100 melter that were spiked with elemental mercury, the processing system provided gas temperatures and residence times that are representative of the WTP LAW vitrification system in order to assess the effect of those conditions on mercury speciation. The Decontamination Factor (DF) across the system in the tests with mercury-spiked DM100 melter exhaust was determined using the analytical data from EPA Method 30B (Fluegas Adsorption Mercury Speciation (FAMS TM )) exhaust samples and the amount of mercury detected in the SBS solutions. Mercury species used in melter feed crucible scale tests were divalent (chloride and iodide), monovalent (chloride and fluoride), and elemental mercury. Individual tests included only a single form of mercury in the feed. The results for total mercury mass balances in the crucible tests are also presented.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Development of a Filtered CFD-DEM Drag Model with Multiscale Markers Using an Artificial Neural Network and Nonlinear Regression

Here, the accuracy of coarse-grained Euler-Lagrangian simulations of fluidized beds heavily depends on the mesoscale drag models to account for the influences of the unresolved sub-grid structures. Traditional filtered drag models are regressed with mesoscale markers such as voidage and slip velocities. In this research, a filtered drag was regressed with both mesoscale and macro-scale markers using fine grid Computational Fluid Dynamics - Discrete Element Method (CFD-DEM) simulations. The traditional non-linear regression method was compared with machine learning regression using an Artificial Neural Network (ANN) implemented in PyTorch and coupled with MFiX. The new drag showed higher accuracy than the Wen-Yu drag and another filtered drag derived from the two-fluid model. The nonlinear regression shows slightly better results than ANN regression in cases with similar R 2 values. The utilization of the gas inlet velocity as an additional macro-scale marker reduced the errors by up to 55.3% in the tested cases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Arcjet thruster research and technology. Phase 1: Executive summary

The principal objective of this two phase program is to conduct the development research required to make the low power arcjet a flight ready technology. Many important results were obtained during Phase 1 to move closer to this objective. Fundamental analyses were performed of the arcjet nozzle, the gas kinetic reaction effects, the thermal environment, and the arc stabilizing vortex. These aided the conceptual understanding of the arcjet and guided design work. A hydrazine (N2H4) arcjet was designed that combined a flight qualified catalyst bed with a modular arcjet. Extensive testing was performed which demonstrated the feasibility of using this propellant in an arcjet for the first time. Startup techniques were developed, stability maintained, material compatibility tests conducted, and performance mapping tests performed. Specific impulse values from 400 to 730 seconds were produced with a non-optimized design. These levels are higher than were originally thought possible and proved that extremely high enthalpy values can be obtained with constricted arc technology. Erosion rate data are promising for lifetime extensions to meet flight application requirements. Power control unit (PCU) development was started with the design and fabrication of a laboratory high switching frequency supply. Valuable data were obtained on PCU operation and on the interaction with the dynamic arc. Phase 2 efforts presently underway are resolving key issues for multi-hundred hour lifetimes, are continuing to investigate arcjet/PCU interactions, and will demonstrate duty cycle N2H4 arcjet/PCU operation in a simulated flight mode for lifetimes consistent with initial applications.

Source record↗

A Better ARED Squat

The 0-G ARED squat under loads the legs relative to the 1g ARED squat. In 1g the knee extensor/flexor muscles are primarily engaged due to the body's center of gravity is behind the knees during the motion of the squat. As body weight does not play a sufficient role 0 G, a crewmember's load exposure is limited by the load delivered by ARED through the exercise bar. Prescription loads for lowerbody resistance exercise in microgravity aim to include 1-G exercise bar load in addition to the crewmember's Earth body weight (BW); however, pressure points from the bar and the 1BW increased load at the shoulders translating to higher loads on the back have been a historical limitation for shoulders, requiring a decrease in exercise load at the start of the mission. Analogous to crewmembers, bed rest subjects report limitations of exercising with high loads on the back while performing squats on the horizontal exercise fixture (HEF), a custom exercise device that serves as an analog to 0-G ARED. Improvements for increasing loads on the HEF squat were suggested by distributing total exercise load between the hips and the bar1. The same is recommended for the 0-G ARED squat, with using current equipment on the ISS, which include the T2 running harness and T2 bungees. Quantification of this improvement has been accessed through computational modeling. The purpose of this study is to characterize joint torque during a squat with a distribution in exercise load on the ARED in 0 G. The analysis used existing models from NASA's Digital Astronaut Project. The biomechanics squat model was integrated with the ARED model and T2 bungees. The spring constant for the bungees were derived from ground testing. Forward dynamic simulation was performed for various conditions including anchor point attachments on the footplate of the ARED, bar load, hip load, and gravitational environment. The model confirms joint torques at knees is lower relative to 1G conditions primarily because the load delivery system is just with the exercise bar in 0 G. By distributing partial loads through use of the bungees to the hips joint-torque profiles were altered during a squat and provided options to enhance targeting lower-body loading in aims as for an improved countermeasure.

Caldwell, E. E.↗

An Airborne Parachute Compartment Test Bed for the Orion Parachute Test Program

The test program developing parachutes for the Orion/MPCV includes drop tests with parachutes deployed from an Orion-like parachute compartment at a wide range of dynamic pressures. Aircraft and altitude constraints precluded the use of an Orion boilerplate capsule for several test points. Therefore, a dart-shaped test vehicle with a hi-fidelity mock-up of the Orion parachute compartment has been developed. The available aircraft options imposed constraints on the test vehicle development and concept of operations. Delivery of this test vehicle to the desired velocity, altitude, and orientation required for the test is a di cult problem involving multiple engineering disciplines. This paper describes the development of the test technique. The engineering challenges include extraction from an aircraft, reposition of the extraction parachute, and mid-air separation of two vehicles, neither of which has an active attitude control system. The desired separation behavior is achieved by precisely controlling the release point using on-board monitoring of the motion. The design of the test vehicle is also described. The trajectory simulations and other analyses used to develop this technique and predict the behavior of the test vehicle are reviewed in detail. The application of the technique on several successful drop tests is summarized.

Moore, James W.↗

Predicting rare events using neural networks and short-trajectory data

Estimating the likelihood, timing, and nature of events is a major goal of modeling stochastic dynamical systems. When the event is rare in comparison with the timescales of simulation and/or measurement needed to resolve the elemental dynamics, accurate prediction from direct observations becomes challenging. In such cases a more effective approach is to cast statistics of interest as solutions to Feynman-Kac equations (partial differential equations). Here, we develop an approach to solve Feynman-Kac equations by training neural networks on short-trajectory data. Our approach is based on a Markov approximation but otherwise avoids assumptions about the underlying model and dynamics. This makes it applicable to treating complex computational models and observational data. Additionally, we illustrate the advantages of our method using a low-dimensional model that facilitates visualization, and this analysis motivates an adaptive sampling strategy that allows on-the-fly identification of and addition of data to regions important for predicting the statistics of interest. Finally, we demonstrate that we can compute accurate statistics for a 75-dimensional model of sudden stratospheric warming. This system provides a stringent test bed for our method.

97 MATHEMATICS AND COMPUTING↗

Nested Pebble Bed Blanket (NesPeB)

Recent advances in magnetic confinement fusion technology have attracted billions of dollars of investments in startups from venture capitals and corporations, resulting in the development of devices aiming to demonstrate net energy gain in a self-heated burning plasma, such as SPARC (under construction) and others. However, future fusion power plants must operate in regimes that will require technologies far beyond current experience. According to a National Academies of Science, Engineering, and Medicine report, to have nuclear fusion power plants contributing in a timely manner to the planned reduction of atmospheric carbon dioxide, a pilot plant should be built by 2035, and it should demonstrate fusion power production and the performance of the tritium fuel system (requiring a high enough tritium breeding) by 2040. A recognized key technology gap by [26] is the fusion first wall and blanket since no current blanket concept is considered satisfactory or has been built and proven. The first wall and blanket in magnetic fusion reactors form a vital and complex system, as it must satisfy different functions such as power extraction, tritium breeding, plasma containment, radiation shielding, and safety. The list of design requirements is even longer: high enough tritium production for fusion self-sufficiency, low material activation, decay heat and shutdown dose rates, high thermal efficiency, high-capacity factor, high magnets-divertor-vacuum vessel-first wall life, low corrosion, low cost, and intrinsically safe (requiring minimal licensing). Despite fifty-plus years of research, the first wall and blanket concepts proposed suffer from fundamental technical problems and immaturity (TRL=2-3) that jeopardize the timely delivery of a commercial fusion power plant. A fusion first-wall blanket has never been built nor tested, and a "winning", practical functioning design requires enough engineering margins (high enough tritium breeding considering the uncertainty, etc.), manufacturing simplicity, ease of continuous operation, maintenance, and low cost. A new, groundbreaking blanket concept called "Nested Pebble Bed Blanket" (NesPeB) was developed at ORNL under the successful ARPA-E GAMOW FERMI project (patent application allowed by the USPTO). The NesPeB blanket concept addresses current blanket concepts' shortcomings and technical immaturity, paving the way for accelerated delivery of fusion power plants. NesPeB is based on nested pebbles, which are binary-sized lithium-ceramic pebbles enclosed in "Beryllide" perforated and coated spherical shells, which are also binary-sized, stacked on top of each other, forming a "bed" and cooled by Nitrogen gas also "sweeping" the Helium and Tritium generated by the neutron irradiation of Lithium; the vacuum vessel plasma facing material is Molybdenum-96 and -97 with the first wall cooled by Helium while the divertor armor is made of Tungsten. The simulations of the NesPeB blanket using Fusion Reactors Models Integrator (FERMI) are encouraging as they estimate a tritium breeding ratio (TBR) greater than 1.2 using natural Lithium, acceptable pressure drop, and excellent heat transfer properties. Furthermore, the NesPeB blanket is not limited by magneto-hydro-dynamics (MHD) effects, is designed for online refueling, relies on existing tritium extraction technologies, has a simple construction, and limits the corrosion and chemical reactivity problems. NesPeB has the potential to be transformational and disruptive since it can solve all the main, challenging technical problems of fusion device blankets and accelerate a pilot plant delivery for 10 or more years.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Artificial Intelligence Application to D and D - 20492

As aging facilities across the DOE complex await decommissioning, there is an ongoing need to understand any changes in the structural conditions. Many of these facilities were built over 50 years ago and, in some cases, these facilities have gone beyond the expected operational lifetime. Many facilities have been placed in a state of 'cold and dark,' sitting unused and awaiting decommissioning. Especially challenging are the aging facilities that provide unique operational/production capabilities to support critical DOE missions and cannot be shut down. In any of these scenarios, the structural integrity of these facilities may become compromised as time passes. It is critical that adequate inspections be performed on a continual basis and that the data collected undergoes sufficient analysis to support timely identification of any new or worsening structural issues as well as prompt needed maintenance and repairs to maintain the facilities in a safe condition. In recent days, Artificial Intelligence (AI) [1] and its application to various domains are growing at fast speed. FIU is performing research in this area and exploring the associated technologies to solve nuclear decommissioning problems. Artificial intelligence refers to the capability of a program to autonomously act, react and adapt to the working environment. AI enables the machine to behave like humans and perform the cognitive functions such as 'learning' and 'problem solving'. AI systems gradually moving from traditional approaches (algorithms and expert systems) towards more efficient and advanced technologies (machine learning [1] and deep learning [2] [3]). AI is the study of algorithms and statistical models that is being used by computers to perform specific tasks without using explicit instructions. FIU is working to develop a pilot-scale infrastructure to implement structural health monitoring using AI technologies with focus on machine learning, deep learning. This research is focused on Computer Vision/Image Classification area of AI applications. This can also be expanded to other areas of AI related to Object Recognition and Character Recognition in images. In addition to utilizing existing data sets, FIU will collect and investigate image and video data using FIU test-bed mockups to monitor structural health of the facility. Resulting data will be processed and analyzed using machine learning/deep learning technologies. The proposed pilot system is intended to serve as a starting point to engage the DOE field sites on related data sets and their decision making needs. It is anticipated that proposed machine learning/deep learning technologies can be effectively employed using anomaly detection to solve EM challenges in surveillance and maintenance of the D and D facilities. FIU will work with research stakeholders to identify applications at various sites and other DOE facilities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Evaluating the Adsorptive Capabilites of Chemsorb 1000 and Chemsorb 1425

The removal of trace contaminants from spacecraft cabin air is necessary for crew health and comfort during long duration space exploration missions. The air revitalization technologies used in these future exploration missions will evolve from current ISS ISS State-of-Art (SOA) and is being designed and tested by the Advanced Exploration Systems (AES) Program's Atmosphere Resource Recovery and Environmental Monitoring (ARREM) project. The ARREM project is working to mature optimum atmosphere revitalization and environmental monitoring system architectures to enable exploration beyond Lower Earth Orbit (LEO). The Air Revitalization Lab at KSC is one of six NASA field centers participating in the ARREM that specializes in adsorbent and catalyst characterization with simulated spacecraft gas streams using combinations of pressure, O2 partial pressure, CO2 partial pressure, and humidity that are representative of a range of anticipated cabin atmospheric conditions and loads. On board ISS, the Trace Contaminant Control Subassembly (TCCS) provides active control of trace contaminants from the cabin atmosphere utilizing physical adsorption, thermal catalytic oxidation, and chemical adsorption processes. High molecular weight contaminants and ammonia (NH3) are removed a granular activated carbon treated with approx. 10% by weight phosphoric acid (H3PO4) (B-S Type 3032 4×6 mesh), which is expendable and is periodically refurbished. The Type 3032 granular activated carbon bed is no longer commercially available and therefore it is important to characterize the efficiency and capacity of commercially available NH3 sorbents. This paper describes the characterization of two Molecular Products LTD activated carbons: Chemsorb 1000 and Chemsorb 1425. Untreated activated carbons (e.g. Chemsorb 1000) remove contaminants by physisorption, which concentrates the contaminant within the pores of the carbon while letting air to pass through the sorbent4. Low molecular weight or polar gases (e.g. HCl, SO2, formaldehyde, and NH3) are not removed by physisorption and typically require chemisorption for removal. Treated activated carbons (e.g. Chemsorb 1425) are impregnated with a a chemical agent (e.g. phosphoric acid) that reacts with those gases, converting them to solids or salts within the carbon and removes them from the air stream. This process occurs via neutralization or catalysis reactions and adsorption capacity is exhaustedwhen the available impregnated chemicals are consumed. Moisture affects removal performance since adsorption sites within the pores are filled with water. The performance of impregnated carbons may be enhanced by moisture content because the mechanisms of contaminant removal are chemical reactions that occur in reagents contained within the pores. The adsorptive capacity data (mol/kg) of Chemsorb 1000 and 1425 for gas mixtures (ethanol, acetone, toluene, acetaldehyde, dichloromethane, and xylene) was measured with 40% relative humidity at 23 deg C air temperature. The adsorptive capacity data (mol/kg) of Chemsorb 1425 was measured using NH3 gas streams.

adsorptive capacities↗

Multi-physics Topology OPtimization and Additive Manufacturing for High-temperature Heat Exchangers

This research significantly advances the understanding of high-temperature heat exchanger design through an integrated approach that combines topology optimization (TO), triply periodic minimal surface (TPMS) structures, additive manufacturing (AM) and thermohydraulic testing. Each of these components contributes uniquely to a unified, high-performance design, fabrication and testing workflow. Topology optimization serves as the foundation of the design methodology by providing a systematic way to determine the most effective material layout for separating hot and cold fluids while maximizing thermal performance. The researchers introduced a novel three-material optimization framework using two density fields to represent hot fluid, cold fluid, and solid domains. This approach enables automated discovery of optimal shapes and flow paths that cannot be intuitively designed, especially under constraints imposed by manufacturing technologies. Furthermore, constraints such as minimal wall thickness and overhang angles were embedded into the optimization process, ensuring that resulting designs are not only thermally efficient but also manufacturable using modern additive techniques. In parallel, the study delves into the use of Gyroid-based TPMS geometries for constructing the core of the heat exchanger. TPMS structures are known for their high surface area, excellent fluid mixing capabilities, and minimal pressure drop characteristics. The researchers applied a data-driven modeling framework using Heteroscedastic Sparse Gaussian Process Regression (HSGPR) combined with genetic algorithms. This allowed for the rapid evaluation and optimization of key geometric parameters such as frequency, iso-value, and phase shift. The result was a set of Gyroid structures tailored for high heat transfer and low flow resistance, demonstrating clear improvements over conventional straight-channel designs. After the designing process, additive manufacturing played a critical role by turning these highly complex, optimized geometries into physical components. Utilizing Laser Powder Bed Fusion (LPBF) with Haynes 282, the study demonstrated the feasibility of fabricating these heat exchangers at high precision. Post-processing methods, including dilation-erosion operations, were applied to ensure local features adhered to self-supporting constraints. The fabricated structures were then subjected to thermohydraulic testing under conditions representative of supercritical CO 2 Brayton cycles, validating the predicted performance and confirming the viability of the full design-to-fabrication pipeline. Finally, thermohydraulic testing across the above studies served as a crucial experimental validation of advanced heat exchanger. Under consistent high-temperature and high-pressure conditions using supercritical CO 2 , the testing demonstrated that both TO and Gyroid-based TPMS designs significantly outperformed conventional straight-channel HXs. The TO design achieved a 115% increase in UA and NTU and a 27.6% boost in gravimetric power density, while the data-driven optimized Gyroid design delivered a 166% increase in UA and NTU and improved effectiveness from 68.7% to 86.1%. These results validate the simulation models, confirm the manufacturability of complex geometries under AM constraints, and provide key insights into design-performance trade-offs, thereby advancing the development of high-efficiency, compact heat exchangers for extreme environments.

36 MATERIALS SCIENCE↗

Itegrated Test and Evaluation of a 4-Bed Molecular Sieve (4BMS) Carbon Dioxide Removtal System (CDRA), Mechanical Compressor Engineering Development Unit (EDU), and Sabitier Engineering Development Unit (EDU)

Currently on the International Space Station s (ISS) U.S. Segment, carbon dioxide (CO2) scrubbed from the cabin by a 4-Bed Molecular Sieve (4BMS) Carbon Dioxide Removal Assembly (CDRA) is vented overboard as a waste product. Likewise, the product hydrogen (H2) that will be generated by the Oxygen Generation Assembly (OGA) planned for installation will also be vented. A flight experiment has been proposed that will take the waste CO2 removed from the cabin, and via the catalytic Sabatier process, reduce it with waste H2 to generate water and methane. The water produced may provide cost and logistics savings for ISS by reducing the amount of water periodically re-supplied to orbit. To make this concept viable, a mechanical piston compressor and accumulator were developed for collecting and storing the CO2 from the CDRA. The compressor, accumulator and Sabatier system would be packaged together as one unit and referred to as the Carbon Dioxide Reduction Assembly (CRA). Testing was required to evaluate the performance of a 4BMS CDRA, compressor, accumulator, and Sabatier performance along with their operating rules when integrated together. This had been numerically modeled and simulated; however, testing was necessary to verify the results from the engineering analyses. Testing also allowed a better understanding of the practical inefficiencies and control issues involved in a fully integrated system versus the theoretical ideals in the model. This paper presents and discusses the results of an integrated engineering development unit test.

Knox, James C.↗

Initial use of Nek5000/Cardinal to improve closure models in Pronghorn

Heat transfer coefficient closure models for pebble bed reactors are built using a data-driven approach by leveraging the capabilities of an Evolutionary Algorithm entitled Particle Swarm Optimization (PSO). In the present work, the Computational Fluid Dynamics code nekRS was used in order to collect the high-fidelity flow data for a core with 1,568 pebbles. To characterize the heat transfer, multiple concentric regions were considered to extract the physical quantities of interest, e.g./ the Reynolds number. The PSO algorithm is employed as part of an inverse problem targeting determine what are the coefficients for a Nusselt number correlation to match the collected data. Such correlation should follow any given format that is defined a priori. Finally, two correlations are proposed, one with an implicit dependence on the pebbles’ wall temperatures and another expressed as a fully explicit correlation depending on the flow conditions and the position within the core. Anyway, given the generic nature of the proposed approach, correlations following different formats could be tested. Preliminary results for the high-fidelity simulation of a fast MSR core are presented. The target Reynolds number is currently 20K, with the expectation that this will increase, pending the availability of further computational resources. These simulations will be used to inform lower fidelity models, including a coarse CFD turbulence model in Pronghorn. Additionally, they will serve as a reference for the RANS models in Nek5000/NekRS.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Sensitivity of meteorological-forcing resolution on hydrologic variables

Projecting the spatiotemporal changes in water resources under a no-analog future climate requires physically based integrated hydrologic models which simulate the transfer of water and energy across the earth's surface. These models show promise in the context of unprecedented climate extremes given their reliance on the underlying physics of the system as opposed to empirical relationships. However, these techniques are plagued by several sources of uncertainty, including the inaccuracy of input datasets such as meteorological forcing. These datasets, usually derived from climate models or satellite-based products, are typically only resolved on the order of tens to hundreds of kilometers, while hydrologic variables of interest (e.g., discharge and groundwater levels) require a resolution at much smaller scales. In this work, a high-resolution hydrologic model is forced with various resolutions of meteorological forcing (0.5 to 40.5 km) generated by a dynamical downscaling analysis from the regional climate model Weather Research and Forecasting (WRF). The Cosumnes watershed, which spans the Sierra Nevada and Central Valley interface of California (USA), exhibits semi-natural flow conditions due to its rare undammed river basin and is used here as a test bed to illustrate potential impacts of various resolutions of meteorological forcing on snow accumulation and snowmelt, surface runoff, infiltration, evapotranspiration, and groundwater levels. Results show that the errors in spatial distribution patterns impact land surface processes and can be delayed in time. Localized biases in groundwater levels can be as large as 5–10 m and 3 m in surface water. Most hydrologic variables reveal that biases are seasonally and spatially dependent, which can have serious implications for model calibration and ultimately water management decisions.

54 ENVIRONMENTAL SCIENCES↗

Investigation of the Effect of Chrome and Nickel Concentrations During Two-Piston Splat Quenching of Austenitic Stainless Steels

For solidification rates at or near equilibrium solidification conditions the effects of chrome (Cr) and nickel (Ni) on stainless steel solidification modes and microstructures are well detailed. However, fusion-based additive manufacturing (FBAM) processes that rely on faster, more rapid solidification rates call for a more in-depth understanding of the effects of rapid solidification on the solidification behavior and how these change with variations in alloy composition. Eleven custom stainless steel (SS) alloys with unique compositions based on 316L were made using targeted alloying element additions to generate feedstock with Cr/Ni eq ratios ranging from 0.9 to 2.1. Two-piston splat quenching (SQ) was used to produce rapid solidification conditions similar to those achieved in powder bed fusion processes in a fraction of the time and cost of traditional methods. Employing heat transfer simulations, SEM, TEM, and STEM characterization techniques, the SQ process was found to consistently produce solidification rates estimated to be between ~ 0.4 and 1.6 m/s. Five unique solidification microstructures were identified within the rapidly solidified SQ samples (primary austenite, massively transformed ferrite to austenite, primary austenite and massively transformed ferrite to austenite, primary ferrite, and primary ferrite and massively transformed ferrite to austenite). Both the primary ferrite solidification mode and primary ferrite phase were found to form at lower Cr/Ni eq values than previously predicted. SQ samples with compositions that were within the compositional specifications for 316L SS, an alloy which is commonly used in FBAM processes, demonstrated a wider range of potential solidification modes and microstructures that could form at rapid solidification rates than expected. Finally, by using SQ as a means to simulate rapid solidification conditions similar to those observed in FBAM processes, potential new alloy compositions can be screened faster and more cost effectively than purchasing and running test batches of the metallic powder.

36 MATERIALS SCIENCE↗