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At least 1,639 records · Page 91

Probabilistic Resilience of DER Systems - A Simulation Assisted Optimization Approach

Energy systems resilience is becoming increasingly important as the frequency of major grid outages increases. In this work, we present a methodology to optimize a behind-tlie-meter distributed energy resource system to sustain a site's critical loads during a pre-defined outage period. With the fixed system design, we then propose an outage simulation approach to estimate the resilience potential of the DER system to sustain loads beyond the fixed outage period - a yearlong resilience performance analysis. We apply statistical analysis to assess the system's resilience performance over a broader parametric problem space on an hourly, monthly, and yearly basis. We demonstrate the impact of the pre-defined outage period on the resilience performance through a case study. Results show that the probability of surviving a random outage of a given duration changes from 20% to 95% when the outage is modeled for a weekday instead of a weekend for the given load-profile.

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

Transcriptomic Network Analysis of Cyanobacterial-Methylotroph Interactions in Coculture and Axenic Conditions

A previous study demonstrated the potential for Cyanobacterial-Methylotroph cocultures to facilitate biogas processing as well as to be used in other biotechnological applications. To advance this technology, we investigated potential interactions between Cyanobacterium stanieri HL-69 (HL69) and Methylotuvimicrobium alkaliphilum 20Z (20Z) by inferring and analyzing gene co-expression networks under co-culture and axenic conditions. Five different co-expression networks were examined. These networks were inferred using gene expression profiles for 20Z axenic condition, HL-69 axenic, HL-69, 20Z coculture, HL-69 coculture, and cross-species HL-69-20Z coculture. Through the analysis of node (gene) betweenness and node normalized degree values in all five network cases, we compared adjustments in gene expression between growth conditions (axenic vs co-culture) as well as identify biological functions relevant to interspecies interactions. This analysis was done to distinguish between gene interactions within an organism and gene interactions between two organisms. Moreover, for all five cases we investigated two different network cutoff levels of 3,000 and 10,000. By shedding light on inter- and intra- species interactions, we hope to gain a better understanding of how these two organisms interact. This research will allow the investigation of further biotechnological applications of coculture systems and optimization of such applications for biotechnological purposes.

59 BASIC BIOLOGICAL SCIENCES↗

Probabilistic Resilience of DER Systems - A Simulation Assisted Optimization Approach

Energy systems resilience is becoming increasingly important as the frequency of major grid outages increases. In this work, we present a methodology to optimize a behind-the-meter distributed energy resource system to sustain a site's critical loads during a pre-defined outage period. With the fixed system design, we then propose an outage simulation approach to estimate the resilience potential of the DER system to sustain loads beyond the fixed outage period - a yearlong resilience performance analysis. We apply statistical analysis to assess the system's resilience performance over a broader parametric problem space on an hourly, monthly, and yearly basis. We demonstrate the impact of the pre-defined outage period on the resilience performance through a case study. Results show that the probability of surviving a random outage of a given duration changes from 20% to 95% when the outage is modeled for a weekday instead of a weekend for the given load-profile.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reducing Uncertainty in Hydrodynamic Modeling of ATR Experiments Via Flow Testing, Validation, and Optimization

The development, characterization, and qualification testing of nuclear fuel at Idaho National Laboratory’s Advanced Test Reactor (ATR) requires extensive design and analysis activities prior to the insertion of an irradiation experiment in-pile. Significant effort is made in the design and development phase of all in-pile experiments to ensure that the maximum feasible impacts of all necessary experimental requirements are satisfied. The advancement of fuel, cladding, and in-reactor materials technology in recent years has introduced complexities associated with the design and construct of in-pile experiments necessitating deeper understanding of boundary conditions and increasingly comprehensive observations resulting from the experiment. Each unique experiment must be assessed for neutronics response, thermal/hydraulic/hydrodynamic performance, and structural integrity. This is accomplished either analytically, computationally, or experimentally, or some combination thereof, prior to insertion into the ATR. The various effects are interrelated to various degrees, such as the case with the experiment temperature affecting the thermal cross section of the fuel or the increased temperature of the experiment’s materials reducing the mechanical strength of the assemblies. Additionally, the feedback between the experiment’s response to a reactor transient could alter the neutron flux profile of the reactor during the transient. Each experiment must therefore undergo a barrage of analyses to assure the ATR operational safety review committee that the insertion and irradiation of the experiment will not detrimentally affect the safe operational envelope of the reactor. In many cases, the nuclear fuel being tested can be double-encapsulated to ensure safety margins are adequately addressed, whereas failed fuel would be encased in a protective capsule. In other cases, the experiments can be inserted in a self-contained loop that passes through the reactor core, remaining isolated from the primary coolant. In the case of research reactor fuel, however, the fuel plates must be tested in direct contact with the reactor coolant, and being fuel designed for high neutron fluxes, they are inherently power-dense plates. The combination of plate geometry, high-power density, and direct contact with primary coolant creates a scenario where the neutronic/thermomechanic/hydrodynamic characteristics of the fuel plates are tightly coupled, necessitating as complete characterization as possible to support the safety and programmatic assessments, thus enabling a successful experiment. This paper explores the efforts of the U.S. High-Performance Research Reactor program to thermomechanically/hydromechanically characterize the program’s wide variety of experiments, which range from stacks of miniplate capsules to full-sized, geometrically representative curved plates. Special attention is given to instances where the combination of experimental characterization and analytical assessment has reduced uncertainties of the safety margins, allowing experiments to be irradiated that would otherwise not have passed the rigorous qualification process for irradiation in the ATR. In some cases, the combined processes have exposed flow and heat transfer characteristics that would have been missed using historical methods, which allows for more accurate and representative postirradiation assessments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Comparative cell-specific transcriptomics reveals differentiation of C 4 photosynthesis pathways in switchgrass and other C 4 lineages

Almost all C4 plants require the co-ordination of the adjacent and fully differentiated cell types, mesophyll (M) and bundle sheath (BS). The C4 photosynthetic pathway operates through two distinct subtypes based on how malate is decarboxylated in BS cells; through NAD-malic enzyme (NAD-ME) or NADP-malic enzyme (NADP-ME). The diverse or unique cell-specific molecular features of M and BS cells from separate C4 subtypes of independent lineages remain to be determined. We here provide an M/BS cell type-specific transcriptome data set from the monocot NAD-ME subtype switchgrass (Panicum virgatum). A comparative transcriptomics approach was then applied to compare the M/BS mRNA profiles of switchgrass, monocot NADP-ME subtype C4 plants maize and Setaria viridis, and dicot NAD-ME subtype Cleome gynandra. We evaluated the convergence in the transcript abundance of core components in C4 photosynthesis and transcription factors to establish Kranz anatomy, as well as gene distribution of biological functions, in these four independent C4 lineages. We also estimated the divergence between NAD-ME and NADP-ME subtypes of C4 photosynthesis in the two cell types within C4 species, including differences in genes encoding decarboxylating enzymes, aminotransferases, and metabolite transporters, and differences in the cell-specific functional enrichment of RNA regulation and protein biogenesis/homeostasis. We suggest that C4 plants of independent lineages in both monocots and dicots underwent convergent evolution to establish C4 photosynthesis, while distinct C4 subtypes also underwent divergent processes for the optimization of M and BS cell co-ordination. The comprehensive data sets in our study provide a basis for further research on evolution of C4 species.

09 BIOMASS FUELS↗

SU-E-J-23: Characteristics of X-Rays From ExacTrac and Patient Dose From Imaging Procedures

Purpose: The purpose of this investigation is 1) provide the beam characteristics of x-rays produced by a Novalis TX ExacTrac system; 2) present a method to commission such beams, 3) present radiation dose to patients resulting from the imaging procedures. Methods: The Monte Carlo simulations were used to obtain the characteristics of kV beams and validated by measurements. The calculated beam HVLs, profiles and depth-dose curves were benchmarked against measurements. Twelve different image acquisition protocols were studied. The x-ray tube voltage ranges from 70 - 145 kV and milliampere-second (mAs) ranges from 8 - 80 mAs depending on the selection of Cranium, Head & Neck, Thorax or Abdomen imaging protocols. The beam output of each image acquisition protocol was determined by using an ionization chamber. The air kerma calibration factors of the ion chamber were obtained from an Accredited Dosimetry Calibration Laboratory for specified HVLs. Results: The agreements between measured and simulated results were within the uncertainties for HVLs, dose profiles and depth-dose curves. When %dd was normalized at 1 cm depth, its values at depth of 5 cm ranged from 45% to 66% of in water for kV beams range from 70 kVp to 145 kVp respectively. For head images, a typical dose to eye resulting from single projection ranged from 0.008 cGy to 0.025 cGy depending on the cranial image protocols selected. For a single pelvic image the skin dose could reach up to 0.1 cGy from an abdominal protocol. Conclusion: Although multiple pairs of x-ray images are commonly acquired during a daily patient treatment, the imaging doses to patients resulting from the sum of these projected x-rays are generally much less than 0.5 cGy. The knowledge obtained from this investigation can be used to estimate the image dose and optimize the used of the system.

60 APPLIED LIFE SCIENCES↗

PyJMAK: An Open-Source Python Toolkit for Modeling Solid-State Metallurgical Phase Transformations

Accurate prediction of metallurgical phase transformations is an essential basis for autonomous optimization and rapid part qualification. Several methods can be used to estimate the evolution of phase fractions such as JMAK kinetics-based models, phase-field models, thermodynamic models, and data-driven machine learning models. Thermodynamic and phase-field-based methodologies solve multiphysics equations requiring numerous calibration parameters and significant computational resources. As a result, the computation domain is limited to a point or on order of micron-meters. The data-driven models rely on large datasets from experiments and simulations. While the JMAK model only provides information about phase fraction evolution, it can predict this evolution in near real-time using thermal history and thermodynamic data without restriction on the domain. JMAK models have been popularly used by researchers to model phase transformations occuring during additive manufacturing or over arbitrary temperature profiles. Commercial proprietary software such as Abaqus and Ansys or closed-source in-house implementations offer the ability to model JMAK based kinetics to predict phase transformation. However, these software packages are not open-source or freely available for use and development in conjunction with manufacturing machines, sensors, and machine learning algorithms. In addition, the use of the model is restricted by a license token. In contrast, given temperature profiles at multiple points in the domain, this Python-based PyJMAK model can compute phase evolution in parallel due to its stand-alone modular, voxel-based structure, and it can be executed on high-performance computing resources without any license restrictions.

Prabhune, Bhagya [Oak Ridge National Laboratory (O↗

Renewable Thermal Hybridization Framework for Industrial Process Heat Applications

Solar industrial process heat (SIPH) technologies, such as concentrating solar power collectors, could economically replace the steam or heat needs at many industrial sites by providing high-temperature heat transfer fluids (HTFs) such as pressurized water, synthetic-oil, or direct steam. Renewable thermal energy systems (RTES) could be hybridized with different renewable options e.g., flat plate collectors with parabolic trough collectors, or combined with existing heat supplies (e.g., fossil fuels), to give options for targeted SIPH applications, industrial decarbonization and the reduction of fuel consumption. Hybrid solutions and thermal energy storage will be important for the dispatch of heat at optimal times needed by the demand side of the buildings and industrial applications. At present, there is no integrated modeling tool for hybrid RTES, and this paper highlights the development of a renewable thermal hybridization framework for IPH use that is built from existing tools like System Advisor Model. The long-term vision for the framework (through significant further research) is to develop a coupled hybrid energy generation and cost analysis tool, where the tool could help the user in determining the most suitable and cost-effective technologies for their applications. Ongoing work will look to add costs for RTES options and further refinement on the selection of suitable technologies. This future tool could calculate the levelized cost of heat of various RTES hybrid options, by taking the user's solar resource, fuel costs, industrial heat demand profile, available land, and other factors into account to determine the applicability into their process.

concentrating solar power↗

Investigating the Implications of a Variable RBE on Proton Dose Fractionation Across a Clinical Pencil Beam Scanned Spread-Out Bragg Peak

Purpose: To investigate the clinical implications of a variable relative biological effectiveness (RBE) on proton dose fractionation. Using acute exposures, the current clinical adoption of a generic, constant cell killing RBE has been shown to underestimate the effect of the sharp increase in linear energy transfer (LET) in the distal regions of the spread-out Bragg peak (SOBP). However, experimental data for the impact of dose fractionation in such scenarios are still limited. Methods and Materials: Human fibroblasts (AG01522) at 4 key depth positions on a clinical SOBP of maximum energy 219.65 MeV were subjected to various fractionation regimens with an interfraction period of 24 hours at Proton Therapy Center in Prague, Czech Republic. Cell killing RBE variations were measured using standard clonogenic assays and were further validated using Monte Carlo simulations and parameterized using a linear quadratic formalism. Results: Significant variations in the cell killing RBE for fractionated exposures along the proton dose profile were observed. RBE increased sharply toward the distal position, corresponding to a reduction in cell sparing effectiveness of fractionated proton exposures at higher LET. The effect was more pronounced at smaller doses per fraction. Experimental survival fractions were adequately predicted using a linear quadratic formalism assuming full repair between fractions. Data were also used to validate a parameterized variable RBE model based on linear α parameter response with LET that showed considerable deviations from clinically predicted isoeffective fractionation regimens. Conclusions: The RBE-weighted absorbed dose calculated using the clinically adopted generic RBE of 1.1 significantly underestimates the biological effective dose from variable RBE, particularly in fractionation regimens with low doses per fraction. Coupled with an increase in effective range in fractionated exposures, our study provides an RBE dataset that can be used by the modeling community for the optimization of fractionated proton therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Anticipating Optical Availability in Hybrid RF/FSO Links Using RF Beacons and Deep Learning

Radiofrequency (RF) communications offer reliable but low data rates and energy-inefficient satellite links, while free-space optical (FSO) promises high bandwidth but struggles with disturbances imposed by atmospheric effects. A hybrid RF/FSO architecture aims to achieve optimal reliability along with high data rates for space communications. Accurate prediction of dynamic ground-to-satellite FSO link availability is critical for routing decisions in low-earth orbit constellations. In this paper, we propose a system leveraging ubiquitous RF links to proactively forecast FSO link degradation prior to signal drops below threshold levels. This enables pre-calculation of rerouting to maximally maintain high data rate FSO links throughout the duration of weather effects. We implement a supervised learning model to anticipate FSO attenuation based on the analysis of RF patterns. Through the simulation of a dense lower earth orbit (LEO) satellite constellation, we demonstrate the efficacy of our approach in a simulated satellite network, highlighting the balance between predictive accuracy and prediction duration. An emulated cloud attenuation model is proposed to provide insight into the temporal profiles of RF signals and their correlation to FSO channel dynamics. Our investigation sheds light on the trade-offs between prediction horizon and accuracy arising from RF beacon numbers and proximity.

FSO availability↗

Distinct Mechanisms and Hydricities of Cp*Ir-Based CO 2 Hydrogenation Catalysts in Basic Water

Transition metal-catalyzed reversible hydrogenation of CO 2 to formate in aqueous solutions under ambient conditions is an attractive environmentally friendly strategy for the storage and transportation of H 2 in a liquid chemical form. Here, mechanistic details for the CO 2 hydrogenation by a series of pentamethylcyclopentadienyl iridium(III) (Cp*Ir) complexes with picolinamidate ligands are investigated through density functional theory and kinetic isotope effects (KIEs) calculations. Additionally, adopting a speciation approach at a pH of 8.2, CO 2 hydrogenation mechanisms of 37 distinct protonation states and conformers of Cp*Ir type complexes are investigated. This imposes a challenging test for the computational modeling in terms of providing a consistent correlation with experimental kinetics and KIE studies of multiple catalysts instead of a single complex. Overall, H 2 heterolysis to generate an iridium hydride intermediate was demonstrated to be the rate determining step, which proceeds via distinct pathways depending on the stereoelectronic properties of the ligand. A peculiar iridium dihydride route was also uncovered, which could be optimized to accelerate the H 2 heterolysis. We have further computed the thermodynamic and kinetic hydricities of 74 complexes with [Cp*Ir(L)(H)] q ( q = -1, 0, 1 depending on the ligand charge by deprotonation or protonation events) general formula. Hydricity values do not show any noticeable correlation with the thermodynamics (Δ G ) of [Cp*Ir(L)(HCO 2 – )] formation but exhibit linear correlation with the kinetics (Δ G ‡ ) of electrophilic CO 2 attack to iridium hydride species, especially when the charges and local structural effects of the metal hydrides are considered. Insights gained in this study on (i) the factors determining the preferred pathway for the rate-limiting H 2 heterolysis step, (ii) the correlation between thermodynamic hydricity and the kinetics of CO 2 insertion to iridium hydride species, and (iii) mechanistic analysis via combination of free energy profiles and KIE studies for a series of iridium catalysts will provide guidelines for the design of next-generation catalysts for the reversible H 2 storage through CO 2 utilization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Intrinsic plasma rotation and Reynolds stress at the plasma edge in the HSX stellarator

Using multi-tipped Langmuir probes in the edge of the HSX stellarator, the radial electric field and parallel flows are found to deviate from the values calculated by the neoclassical transport code PENTA for the optimized quasi-helically symmetric (QHS) configuration. To understand whether Reynolds stress might explain the discrepancy, fluctuating floating potential measurements are made at two locations in the torus corresponding to the low field and high field sides of the device. The measurements at the two locations show clear evidence of a gradient in the Reynolds stress. However, the resulting flow due to the gradient in the stress is found to be large and in opposite directions for the two locations. This makes an estimation of the flux surface average using a small number of measurement locations impractical from an experimental perspective. These results neither confirm nor rule out whether Reynolds stress plays an important role for the QHS configuration. Measurements made in configurations with the quasi-symmetry degraded show even larger flows and greater deviations from the neoclassically calculated velocity profiles than the QHS configuration while the fluctuation magnitudes are reduced. Lastly, for these configurations in particular, the Reynolds stress is most likely not responsible for the additional momentum.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

TU-AB-BRC-11: Moving a GPU-OpenCL-Based Monte Carlo (MC) Dose Engine Towards Routine Clinical Use: Automatic Beam Commissioning and Efficient Source Sampling

Purpose: We have previously developed a GPU-OpenCL-based MC dose engine named goMC with built-in analytical linac beam model. To move goMC towards routine clinical use, we have developed an automatic beam-commissioning method, and an efficient source sampling strategy to facilitate dose calculations for real treatment plans. Methods: Our commissioning method is to automatically adjust the relative weights among the sub-sources, through an optimization process minimizing the discrepancies between calculated dose and measurements. Six models built for Varian Truebeam linac photon beams (6MV, 10MV, 15MV, 18MV, 6MVFFF, 10MVFFF) were commissioned using measurement data acquired at our institution. To facilitate dose calculations for real treatment plans, we employed inverse sampling method to efficiently incorporate MLC leaf-sequencing into source sampling. Specifically, instead of sampling source particles control-point by control-point and rejecting the particles blocked by MLC, we assigned a control-point index to each sampled source particle, according to MLC leaf-open duration of each control-point at the pixel where the particle intersects the iso-center plane. Results: Our auto-commissioning method decreased distance-to-agreement (DTA) of depth dose at build-up regions by 36.2% averagely, making it within 1mm. Lateral profiles were better matched for all beams, with biggest improvement found at 15MV for which root-mean-square difference was reduced from 1.44% to 0.50%. Maximum differences of output factors were reduced to less than 0.7% for all beams, with largest decrease being from1.70% to 0.37% found at 10FFF. Our new sampling strategy was tested on a Head&Neck VMAT patient case. Achieving clinically acceptable accuracy, the new strategy could reduce the required history number by a factor of ∼2.8 given a statistical uncertainty level and hence achieve a similar speed-up factor. Conclusion: Our studies have demonstrated the feasibility and effectiveness of our auto-commissioning approach and new efficient source sampling strategy, implying the potential of our GPU-based MC dose engine goMC for routine clinical use.

61 RADIATION PROTECTION AND DOSIMETRY↗

Proppant embedment in coal and shale: Impacts of stress hardening and sorption

During methane production in CBM reservoirs, the influence of proppant embedment and permeability damage cannot be neglected – especially where the wall-rock is soft. Effective stresses are elevated during methane recovery, increasing both normal loading stress and confinement and simultaneously overprinting sorption-induced volumetric strains. Experiments and analytic modeling are conducted to define key mechanisms controlling these competitive effects. We independently measure overall sample compaction (external LVDT) and local strain (strain gauge) in the matrix to deconvolve proppant embedment in a propped fracture for different conditions of confining stress. The results show symptomatic behaviors of elastic (shale) and elastoplastic (coal) responses of embedment. Different from shale, the evolution of embedment is convex upwards with increased stress where indented depth increases more rapidly as loading stress increases under constant confinement. In addition, a stress-hardening effect is found to play a pivotal role in determining the characteristics of indentation, which are examined in terms of evolution profiles, deformation regimes, embedment slopes, curvatures, yield points and irreversible indentations. Based on the experimental observations a semianalytical model predicts indentation and the evolution of propped permeability under recreated in-situ stress conditions. A simplified case study is conducted to further illustrate the evolution of aperture and permeability of a propped fracture in CBM reservoirs. The modeling results suggest that proppant embedment is significantly overestimated if the variable stress-hardening (VSH) effect is neglected, especially when effective stress is large. Moreover, a decrease in indentation depth possibly occurs during late stage methane production, resulting in a reversal/recovery in fracture closure. This is because desorption-induced shrinkage becomes the predominant effect, causing an increase in aperture and a reduction in the indented volume of proppant. The resulting recovery in permeability implies that the propped coal fracture has the potential to optimally facilitate methane production as a pathway, even at high closure stresses generated by methane drainage.

01 COAL, LIGNITE, AND PEAT↗

An Antibody Cocktail-Based Immunoaffinity-LC-MS Method Enabled Ultra-Sensitive and Robust Quantification of Circulating Proinsulin Proteoforms and C-Peptide

Accurately measuring circulating proinsulin proteoforms is crucial for clinical investigation of diabetes, but was previously not feasible owing to limited assay specificity/sensitivity. Here, in this study, we devised a highly sensitive LC-MS-based strategy to quantify intact proinsulin, des-31,32 and des-64,65 proinsulin, and C-peptide in circulation. The method involves: (i) quantitative, robust affinity capture using an optimized antibody cocktail, eliminating the severe quantitative bias across multiple proteoforms typically introduced when using a single antibody; (ii) Lys-C digestion producing unique signature peptides for each proteoform, and (iii) trapping-nano-LC coupled with FAIMS/dCV-MS for an ultrasensitive analysis. The selective trapping/delivery ensured sensitive/selective analysis of the targets while achieving excellent analytical robustness that is critical for clinical assays, and the FAIMS/dCV substantially reduces baseline noise/interferences, further enhancing S/N. The assay achieved exceptional sensitivity, with serum LOQs of 1.7, 2.3, and 3.6 pg/mL respectively for intact-proinsulin, des-31,32 and des-64,65, representing the first assay capable of sensitively quantifying these major circulating proinsulin proteoforms. We applied this assay to 78 subjects, including autoantibody positive (n = 20) and new-onset type 1 diabetes (T1D, n = 19) with respective age/sex/BMI-matched controls, enabling the first accurate profiling of proinsulin proteoforms in clinical groups. The assay results demonstrated a clear separation of control and new-onset T1D groups that a parallel total-proinsulin ELISA assay fails to capture. Furthermore, distinct expression patterns in relative abundance ratios among proteoforms were observed across clinical groups. This assay may provide valuable insights into the β-cell functions and the onset/progression of diabetes and other associated conditions. Moreover, the strategy is broadly applicable to targeted measurement of other biomarker proteoforms.

Shen, Qingqing [University at Buffalo, NY (United ↗

Numerical Simulation of a Natural Convection–Driven Air-Cooled Reactor Cavity Cooling System Experiment

Ensuring the efficient removal of decay heat from the reactor vessel is essential for the safety of advanced reactor technologies. Several Generation-IV concepts incorporate variations in the reactor vessel cooling systems to achieve this objective. High-temperature gas-cooled reactors utilize a reactor cavity cooling system (RCCS), a passive ex-vessel system designed to operate without active components or external power during accident conditions. The RCCS removes decay heat primarily through radiative and convective heat transfer mechanisms. Here, this study presents a comprehensive validation of a computational fluid dynamics Reynolds-averaged Navier-Stokes model for the University of Wisconsin-Madison air-cooled RCCS facility. Validation was conducted for both high- and low-power natural convection cases under a uniform heating profile. Near-wall resolution was found to be critical for accurately modeling natural convection in the RCCS; employing an all-𝑦 + wall treatment resulted in wall temperature discrepancies exceeding 50 °⁢𝐶 compared to a wall-resolved mesh. Thermal-hydraulic behaviors under natural and forced convection conditions were compared within the heated cavity and RCCS. A turbulence model sensitivity analysis indicated that low-Reynolds number k-ɛ, k-ω shear stress transport (SST), and Reynolds stress transport models produce similar wall temperature predictions. A buoyancy modeling sensitivity study revealed that the Boussinesq approximation significantly underpredicted thermal-hydraulic behavior in the RCCS. Based on these findings, modeling recommendations are provided. The validated data set along with identified sensitivities refine the modeling of natural convection in the RCCS. The information produced by this study supports RCCS design, optimization, and safety evaluations, enabling the calibration and verification of reduced-order thermal-hydraulic models.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Finch: Toxicity Dose Response Curve Prediction of Chemical Compounds and Mixtures

A paradigm shift in chemical risk assessment is emphasizing mixture testing over single compound analysis, eliminating animal testing, and adopting advanced modeling approaches to understand mixture activity profiles. However, existing computational models largely focus on single chemicals, with few effective solutions for modeling complex mixtures that account for synergistic or antagonistic effects and multiple Modes of Action (MoA). Conventional methods like concentration addition (CA) and independent action (IA) are insufficient for this task as they are designed for simplistic interactions and struggle to account for the dynamic and multifaceted nature of chemical mixtures, such as overlapping MoA and non-linear interactions. Finch offers a novel approach utilizing deep learning (DL) embeddings and multi-task quantitative structure-activity relationship (QSAR) models to improve chemical exposure prediction. By leveraging molecular descriptors, physiochemical properties, and large language model (LLM) embeddings from SMILES inputs, Finch preserves critical information in a latent space thereby enhancing predictive accuracy. The multi-task learning aspect of Finch is highly advantageous, as it simultaneously optimizes multiple loss functions, leveraging all available data across tasks to develop generalized representations that effectively capture complex ingredient interactions within mixtures.

59 BASIC BIOLOGICAL SCIENCES↗

The importance of maldistribution matching for thermal performance of compact heat exchangers

Compact heat exchangers have gained increased attention in recent years, particularly in demanding applications where high temperatures, high pressures, and/or high power densities are required. For decades, the heat exchanger (HX) community believes that flow maldistribution is a key factor for HX effectiveness, that is, reducing the degree of flow maldistribution (MALD) can help increase the HX effectiveness. Therefore, significant efforts have been devoted in the past to optimizing the header geometry to minimize flow maldistribution. This work was initially motivated by this, and the original goal was to figure out a HX header design with the lowest maldistribution. However, by systematically constructing a comprehensive maldistribution matrix, the analysis revealed that the HX effectiveness is not actually determined by the MALD, but instead dominated by the degree of maldistribution mismatch (MISM). This conclusion was also theoretically generalized, which indicated that matching of the local heat capacity rate is key for achieving maximum performance. The MISM provides a local means of tracking this information, while the MALD only provides a global approximation of the maldistribution itself. With this new perspective, flow maldistribution needs not necessarily be avoided, but instead matched between two fluid streams, to improve the HX performance. We demonstrated that by carefully designing the header geometry to match the velocity profiles of the two fluids in a 2 MW PCHE with molten salt and supercritical carbon dioxide (sCO2) as the heat transfer fluids, the HX could achieve a higher effectiveness even when the maldistribution increased. Finally, a technoeconomic study using a CSP system as an example revealed that the use of this new HX design paradigm could result in CSP capital cost savings as large as 16.6%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗