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At least 1,783 records · Page 99

Hyperon III: $$K^{-}p - \pi \varSigma $$ coupled-channel dynamics in the $$\varLambda (1405)$$ mass region

Abstract Low-energy data on the three charge states in $$\gamma p \rightarrow K^+(\varSigma \pi )$$ γ p → K + ( Σ π ) from CLAS at JLab, on $$K^-p\rightarrow \pi ^0\pi ^0\varLambda $$ K - p → π 0 π 0 Λ and $$\pi ^0\pi ^0\varSigma $$ π 0 π 0 Σ from the Crystal Ball at BNL, bubble chamber data on $$K^-p\rightarrow \pi ^-\pi ^+\pi ^{\pm }\varSigma ^{\mp }$$ K - p → π - π + π ± Σ ∓ , low-energy total cross sections on $$K^-$$ K - induced reactions, and data on the $$K^-p$$ K - p atom are fitted with the BnGa partial-wave-analysis program. We find that the data can be fitted well with just one isoscalar spin-1/2 negative-parity pole, the $$\varLambda (1405)$$ Λ ( 1405 ) , and background contributions. In a fit with one isocsalar state, the $$\varLambda (1405)$$ Λ ( 1405 ) structure can be determined as a dominantly SU(3) singlet state. A fit with two isoscalar singlet states, with imposed properties of the low-mass state, is, however, also not incompatible with data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Food resources affect territoriality of invasive wild pig sounders with implications for control

Abstract Interest in control methods for invasive wild pigs ( Sus scrofa ) has increased due to their range expansion, population growth, and an improved understanding of their destructive ecological and economic effects. Recent technological advances in traps for control of pig populations facilitate capture of entire social groups (sounders), but the efficacy of “whole-sounder” trapping strategies is heavily dependent on the degree of territoriality among sounders, a topic little research has explored. We assessed territoriality in wild pig sounders on the Savannah River Site, South Carolina, USA, and examined whether availability of food resources provided by a municipal-waste landfill affected among-sounder territoriality. We estimated utilization distribution overlap and dynamic interactions among 18 neighboring sounders around a landfill. We found that although neighboring sounders overlapped in space, intensity of use in shared areas was uniformly low, indicating territorial behavior. Neighbors tended to share slightly more space when closer to the landfill waste cells, indicating availability of a super-abundant resource somewhat weakens the degree of territoriality among sounders. Nevertheless, we conclude that sounders behaved in a generally territorial manner, and we discuss implications for whole-sounder trapping programs, particularly near concentrated resources such as landfills and crop fields.

60 APPLIED LIFE SCIENCES↗

Mass calibration of the CODEX cluster sample using SPIDERS spectroscopy – I. The richness–mass relation

Abstract We use galaxy dynamical information to calibrate the richness–mass scaling relation of a sample of 428 galaxy clusters that are members of the CODEX sample with redshifts up to z ∼ 0.7. These clusters were X-ray selected using the ROSAT All-Sky Survey (RASS) and then cross-matched to associated systems in the redMaPPer (the red sequence Matched-filter Probabilistic Percolation) catalogue from the Sloan Digital Sky Survey. The spectroscopic sample we analyse was obtained in the SPIDERS program and contains ∼7800 red member galaxies. Adopting NFW mass and galaxy density profiles and a broad range of orbital anisotropy profiles, we use the Jeans equation to calculate halo masses. Modelling the scaling relation as $\lambda \propto \text{A}_{\lambda } {M_{\text{200c}}}^{\text{B}_{\lambda }} ({1+z})^{\gamma _{\lambda }}$, we find the parameter constraints $\text{A}_{\lambda }=38.6^{+3.1}_{-4.1}\pm 3.9$, $\text{B}_{\lambda }=0.99^{+0.06}_{-0.07}\pm 0.04$, and $\gamma _{\lambda }=-1.13^{+0.32}_{-0.34}\pm 0.49$, where we present systematic uncertainties as a second component. We find good agreement with previously published mass trends with the exception of those from stacked weak lensing analyses. We note that although the lensing analyses failed to account for the Eddington bias, this is not enough to explain the differences. We suggest that differences in the levels of contamination between pure redMaPPer and RASS + redMaPPer samples could well contribute to these differences. The redshift trend we measure is more negative than but statistically consistent with previous results. We suggest that our measured redshift trend reflects a change in the cluster galaxy red sequence (RS) fraction with redshift, noting that the trend we measure is consistent with but somewhat stronger than an independently measured redshift trend in the RS fraction. We also examine the impact of a plausible model of correlated scatter in X-ray luminosity and optical richness, showing it has negligible impact on our results.

Capasso, R.↗

Microgrids for Service Restoration to Critical Load in a Resilient Distribution System

icrogrids can act as emergency sources to serve critical loads when utility power is unavailable. This paper proposes a resiliency-based methodology that uses microgrids to restore critical loads on distribution feeders after a major disaster. Due to limited capacity of distributed generators (DGs) within microgrids, dynamic performance of the DGs during the restoration process becomes essential. In this paper, the stability of microgrids, limits on frequency deviation, and limits on transient voltage and current of DGs are incorporated as constraints of the critical load restoration problem. The limits on the amount of generation resources within microgrids are also considered. By introducing the concepts of restoration tree and load group, restoration of critical loads is transformed into a maximum coverage problem, which is a linear integer program (LIP). The restoration paths and actions are determined for critical loads by solving the LIP. A 4-feeder, 1069-bus unbalanced test system with four microgrids is utilized to demonstrate the effectiveness of the proposed method. The method is applied to the distribution system in Pullman, WA, resulting in a strategy that uses generators on the Washington State University campus to restore service to the Hospital and City Hall in Pullman.

Xu, Yin (ORCID:0000000209459024)↗

Evaluation of CFD Methods for Simulation of Two-Phase Boiling Flow Phenomena in a Helical Coil Steam Generator

The U.S. Department of Energy, Office of Nuclear Energy charges participants in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program with the development of advanced modeling and simulation capabilities that can be used to address design, performance and safety challenges in the development and deployment of advanced reactor technology. The NEAMS has established a high impact problem (HIP) team to demonstrate the applicability of these tools to identification and mitigation of sources of steam generator flow induced vibration (SGFIV). The SGFIV HIP team is working to evaluate vibration sources in an advanced helical coil steam generator using computational fluid dynamics (CFD) simulations of the turbulent primary coolant flow over the outside of the tubes and CFD simulations of the turbulent multiphase boiling secondary coolant flow inside the tubes integrated with high resolution finite element method assessments of the tubes and their associated structural supports. This report summarizes the demonstration of a methodology for the multiphase boiling flow analysis inside the helical coil steam generator tube. A helical coil steam generator configuration has been defined based on the experiments completed by Polytecnico di Milano in the SIET helical coil steam generator tube facility. Simulations of the defined problem have been completed using the Eulerian-Eulerian multi-fluid modeling capabilities of the commercial CFD code STAR-CCM+. Simulations suggest that the two phases will quickly stratify in the slightly inclined pipe of the helical coil steam generator. These results have been successfully benchmarked against both empirical correlations for pressure drop and simulations using an alternate CFD methodology, the dispersed phase mixture modeling capabilities of the open source CFD code Nek5000.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DARMA-Kokkos Data and Execution Interoperability WBS 2.3.1.04 Milestone 16 (ECP Milestone Report)

DARMA (Distributed Asynchronous Resilient Models for Applications) is a runtime library supporting the Sandia ATDM (Advanced Technology Development and Mitigation) program. The main application drivers fall within the ECP milestone 2.2.5.03 ADNN03-ASC ATDM SNL Application, which includes applications that require load balancing and asynchronous communication for high performance. The DARMA runtime infrastructure has been modified to be compatible with Kokkos/OpenMP parallelization within tasks, which is a critical requirement for high performance for the Sandia ATDM apps. DARMA development has occurred in parallel with a verification milestone for ATDM in FY18. For FY19, DARMA should impact ATDM by enabling dynamic load balancing and communication through only incremental changes to the existing verified MPI codes. DARMA can now support the intra-kernel thread parallelization in the parent MPI apps, allowing DARMA to be easily added without rewriting individual math kernels. The results presented here demonstrate the DARMA results for an MPI mini-app.

97 MATHEMATICS AND COMPUTING↗

Evaluation of Used Fuel Disposition in Clay-Bearing Rock

The DOE R&D program under the Spent Fuel Waste Science Technology (SFWST) campaign has made key advances in experimental and modeling aspects of chemical and physical phenomena towards the long-term safety assessment of nuclear waste disposition in deep clay/shale/argillaceous rock. Experimental activities on clay barrier interactions with fluids and radionuclides provide the much needed knowledge to evaluate engineered barrier system (EBS) performance. Thermal-Hydrological-Mechanical-Chemical (THMC) model development of clay provides a rigorous simulation platform to assess the complex dynamic behavior of engineered and natural barrier materials in response to coupled process phenomena induced by heat-generating nuclear waste. This report describes the ongoing disposal R&D efforts on the advancement and refinement of coupled THMC process models, hydrothermal experiments and geochemical modeling of on barrier material (clay/metal) interactions, spent fuel and canister material degradation, radiolytic phenomena and UO 2 degradation, and thermodynamic database development. These play an important role to the evaluation of sacrificial zones as part of the EBS exposure to thermally-driven chemical and transport processes. Clay-zeolite phase equilibria play a key role in the mineralogical transformations of clay barrier conducive to loss in swelling properties but also in controlling H 2 0 uptake/release through hydration/dehydration reactions. The result is volume changes can affect the interface / bulk phase porosities, transport, and the mechanical (stress) state of the bentonite barrier. Characterization studies on barrier samples (bentonite/cement) from controlled tests at underground research laboratories (URLs) provide key insights into barrier materials interactions at EBS interfaces. Spent fuel degradation modeling coupled with canister and cladding corrosion effects demonstrate the strong influence of H 2 generation on the source term.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Dynamic root exudate chemistry and microbial substrate preferences drive patterns in rhizosphere microbial community assembly

Like all higher organisms, plants have evolved in the context of a microbial world, shaping both their evolution and their contemporary ecology. Interactions between plant roots and soil microorganisms are critical for plant fitness in natural environments. Given this co-evolution and the pivotal importance of plant–microbial interactions, it has been hypothesized, and a growing body of literature suggests, that plants may regulate the composition of their rhizosphere to promote the growth of microorganisms that improve plant fitness in a given ecosystem. In this paper, using a combination of comparative genomics and exometabolomics, we show that pre-programmed developmental processes in plants (Avena barbata) result in consistent patterns in the chemical composition of root exudates. This chemical succession in the rhizosphere interacts with microbial metabolite substrate preferences that are predictable from genome sequences. Specifically, we observed a preference by rhizosphere bacteria for consumption of aromatic organic acids exuded by plants (nicotinic, shikimic, salicylic, cinnamic and indole-3-acetic). The combination of these plant exudation traits and microbial substrate uptake traits interact to yield the patterns of microbial community assembly observed in the rhizosphere of an annual grass. Finally, this discovery provides a mechanistic underpinning for the process of rhizosphere microbial community assembly and provides an attractive direction for the manipulation of the rhizosphere microbiome for beneficial outcomes.

54 ENVIRONMENTAL SCIENCES↗

Development of Automated Software Program for the Analysis of Alzheimer's Disease Scans: Evaluation of PET imaging with PBR-111 in HV and AD subjects

Study goal: A Phase 1 evaluation of the kinetics, clearance and cerebral distribution of one novel peripheral benzodiazepine receptors(PBR)positron emission tomography (PET) imaging agent, 18F-PBR-111 following intravenous administration in healthy volunteers and Alzheimer's disease (AD) patients. Short title: Evaluation of PET imaging with PBR-111 in HV and AD subjects Proof of Mechanism. Primary Objective: To evaluate the cerebral distribution of PBR-111 positron emission tomography (PET) for detection/exclusion of microglial activation in patients with Alzheimer's disease subjects compared to healthy volunteers. Secondary objectives: - To assess the dynamic uptake and washout of [18F]PBR-111, a potential imaging bio-marker for inflammatory changes in brain, using positron emission tomography in subjects with Alzheimer's disease (AD) and healthy volunteers (HV). - To perform blood metabolite characterization of [18F]PBR-111 in subjects with AD and HV to determine the nature of metabolites in assessment of [18F]-PBR-111 as a PET brain imaging agent. Name of radioactive drug substance: PBR-111 Dose(s): The applied PBR-111 radioactive dose will be up to 5.0 mCi, diluted in a maximum of 10 ml of saline. The radioligand will be administered as a slow intravenous bolus injection (i.e., 6 sec/ml) into a large vein (e.g., antecubital vein). Route of administration: Intravenous injection Duration of treatment: Single administration of a diagnostic agent Indication: PBR-111 positron emission tomography (PET) imaging has the potential to detect microglial activation. In the presence of PBR-111 uptake (representative of microglial activation), inflammation in the brain can be detected. Diagnosis and main criteria for inclusion: Study participants will be HVs and patients diagnosed with probable AD. HVs must be 18 years of age (at least four subjects 50 years of age) and have no evidence of cognitive impairment or other neurologic disease by medical history. The lack of cognitive impairment will also be based on a Clinical Dementia Rating (CDR) of 0. Patients with probable AD must be 50 years of age and must fulfill the National Institute of Neurological and Communicative Disorders and Stroke, Alzheimer's Disease and Related Disorders Association [NINCDS-ADRDA] criteria for probable AD. The CDR score must be 1.0 and 2.0 and have a modified Hachinski of 4. All HVs and all patients with probable AD must be able to comply with all study procedures. Study design: This is a Phase 1, open-label, single-center, non-randomized single dose study to assess the kinetics, clearance and cerebral distribution of PBR-111 PET imaging in detecting microglial activation in the brain in patients with probable AD compared to HVs. All aspects related to image acquisition, processing, and visual as well as quantitative evaluation will be developed, optimized, and validated (where required). Each subject will be required to visit the study center during the screening phase and on the PBR-111 PET imaging day (baseline). A telephone follow-up visit will be performed 7 days (± 3 days) after PBR-111 PET administration. At the screening visit, each subject (or caregiver in the case of AD subjects) will be asked to provide written informed consent or assent. During the screening phase (maximum duration of 60 days) subject medical, neurological, and surgical history, clinical assessments, and a neuro-psychiatric evaluation will be performed on all eligible subjects. Subjects will be allowed to leave the center after all evaluations have been completed. During this period an MRI of the brain will be performed during the screening period. If an MRI of the brain has been performed within six months of the imaging visit using the methods described in the protocol, and there has been no medically significant events in the interim, the previous MRI may be used. During the PBR-111 PET imaging day, all subjects will receive a single intravenous injection of PBR-111 and scanning will be performed over a 3.5 hour period. Each subject will have a telephone follow-up 7 days (± 3 days) thereafter to assess for adverse events. Methodology: - Assessments to provide clinical characterization of the AD subjects will be performed. - After administration of PBR-111, images will be generated with state-of-the-art PET imaging. Images will be assessed quantitatively for the presence of microglial activation by a nuclear physician blinded to clinical data. - Total radioactivity and estimation of the fraction of radioactivity associated to the un-metabolized tracer will be determined. In addition, the metabolite patterns of PBR-111 are determined in venous plasma and arterial samples based on high-performance liquid chromatography (HPLC) analyses. - Arterial sampling will be acquired in the initial two AD and two HV subjects and modeling will be assessed to determine if additional arterial sampling is necessary.

97 MATHEMATICS AND COMPUTING↗

Statistical Study of Primary Knock-on Atoms under Neutron Irradiation in RMC Code

Materials in high flux neutron condition will suffer from an evolution of damage which ultimately restricts the lifetime of the fuel clad and reactor pressure vessel. Atoms in irradiated material transform to primary knock-on atoms (PKAs) by absorbing the kinetic energy transferred from neutrons, and the energy released from nuclear reactions. The secondary collision cascades which are induced by PKAs create point defects within the material, with residual vacancies and interstitials eventually causing swelling and embrittlement that degrades mechanical behavior. For a long time, Displacements per Atom (DPA) index has been identified as a measure of radiation damage in material. Nowadays, several advanced methods, such as Molecular Dynamics (MD) and Kinetic Monte Carlo (KMC) simulations, have been developed for more accurately simulating the evolution of the damage. However, all of these techniques need more comprehensive information of PKA, such as the type, energy, direction and spatial distribution. The limitations of DPA emerge and a method should be provided to simulate the generative process of PKAs. Recently, a deterministic analysis code SPECTRA-PKA has been developed by Gilbert to calculate the energy spectra of almost all types PKAs by solving the group-to-group cross-section matrices equation which includes neutron scattering, light charged particles, and recoils of the residual nuclei. But this deterministic analysis code could not give the direction, spatial and time distribution of PKAs. Based on the Geant4 program, Cui Zhenguo has simulated the irradiation by neutrons with 1 MeV energy in zirconium, while only the two adjacent elastic collisions between injected neutron and target atoms are taken into consideration. In this paper, Monte Carlo method to calculate PKAs information during neutron transport in RMC code is introduced. RMC is a continuous-energy Reactor Monte Carlo neutron and photon transport code being developed by Department of Engineering Physics at Tsinghua University, Beijing. PKAs in zirconium are calculated in fixed neutron source mode. Statistical information of PKAs in PWR fuel cell and SFR fuel cell is shown and compared. The results show that Monte Carlo method can provide more comprehensive information of PKAs. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Multi-Omics Reveals Temporal Scales of Carbon Metabolism in Synechococcus Elongatus PCC 7942 Under Light Disturbance

Central carbon metabolism in model cyanobacteria involves multiple pathways to adapt to energy-light limitations across diel cycles. However, the success in mechanistic modeling for phenotypic prediction of the protein regulators in the metabolic state depends on capturing the vast possibilities emerging from multiple regulatory pathways in complex biological processes. Here, we developed a physics-informed machine learning approach based on energy-landscape concepts to predict regulatory proteins responding to cyclic circadian and unforeseen light perturbations in cyanobacterial metabolic networks. Our approach provides interpretable de novo models for inferring gene expression dynamics from Synechococcus elongatus over diel cycles and using redox proteome analysis to distinguish immediate light-responsive elements from circadian-regulated processes in carbon metabolism pathways. We identified distinct temporal signatures with the analysis of the redox proteome: there was an immediate shift in cysteine redox states accompanied by a limited change in protein abundance under constant illumination and after 2 hours of darkness. This discovery indicates that the generation of reductants coordinates photoinduced electron transport with redox metabolic pathways in two discernable molecular mechanisms: fast redox-based protein modifications occur immediately after the light disturbance, followed by slow transcriptional regulations across networks. This temporal regulation reveals how metabolic networks integrate rapid light responses with programmed circadian rhythms to maintain cellular homeostasis under the light-energy limitations over the diel cycle.

Biomolecular & subcellular processes↗

Manage OpenMP GPU Data Environment Under Unified Address Space

OpenMP has supported the offload of computations to accelerators such as GPUs since version 4.0. A crucial aspect in OpenMP offloading is to manage the accelerator data environment. Currently, this has to be explicitly programmed by users, which is non-trival and often results in suboptimal performance. The unified memory feature available in recent GPU architectures introduces another option, implicit management. However, our experiments show that it incurs several performance issues, especially under GPU memory oversubscription. In this paper, we propose a compiler and runtime collaborative approach to manage OpenMP GPU data under unified memory. In our framework, the compiler performs data reuse analysis to assist runtime data management. The runtime combines static and dynamic information to make optimized data management decisions.We have implement the proposed technology in the LLVM framework. The evaluation shows our method can achieve significant performance improvement for OpenMP GPU offloading.

97 MATHEMATICS AND COMPUTING↗

Regional surrogates for predictive control of digital twins

Digital twins of complex systems must involve a model that is fast, generalizable, and usable for real-time control. For example, high-fidelity nonlinear multiphysics simulations can capture laser-material interactions, but are too slow for optimization or model predictive control (MPC). Reduced-order models, used to accelerate such computation, frequently fail to generalize to unseen inputs or control states. We show theoretically that this failure is intrinsic, i.e., that a learned model is non-unique outside the sampled subspace when its low-rank structure arises from limited excitation and clustered eigenvalues, rather than from a user-imposed truncation alone. Motivated by this result, we propose a control-ready regional surrogate-construction framework for both autonomous and nonautonomous dynamics; it employs Koopman lifting to represent nonlinearities, while preserving spatial locality. We illustrate our approach by constructing a control-ready surrogate for the digital twin of a thermal component of additive-manufacturing process. Our surrogate, localized in space through a von Neumann stencil, is learned from noisy high-fidelity simulations that emulate thermal-camera images collected during the manufacturing. It is linear in thermo-physically augmented states so that MPC reduces to a convex quadratic program. The surrogate requires no online correction, generalizes to unseen scan paths and power profiles of the laser, and is more than three orders of magnitude faster than a finite-difference solver. Furthermore, when the MPC sequence computed on the digital twin is applied to this solver, closed-loop temperature regulation is recovered, showing that the surrogate preserves control-relevant input-output behavior.

Data-driven model↗

Turbulent properties from Doppler lidar

Permanent and mobile facilities deployed by the ARM program cover a wide range of climatic regions, with a suite of active remote-sensing of cloud and aerosol profiles complemented by comprehensive in-situ measurements of the chemical, physical and optical properties of aerosol measured at the surface. To be able to fully exploit these datasets requires an understanding of the transport from the surface and within the atmosphere, especially within the planetary boundary layer. This requires a method of identifying when the surface and atmosphere are dynamically-linked. Determining the state of the boundary layer, and defining a well-mixed boundary-layer, is therefore suitably described in terms of mixing; here, we will assume that mixing essentially means turbulent mixing. This necessitates accurate measurements of the winds and turbulent mixing in the atmosphere. Doppler lidar is an excellent tool for observing turbulent properties, and ARM has deployed commercially available Doppler lidars at many of the fixed and mobile facilities. Doppler lidars have been shown to provide accurate retrievals of wind and turbulent properties within the boundary layer , however, robust characterization and calculation of the Doppler lidar measurement uncertainties is required before deriving higher level data products.

54 ENVIRONMENTAL SCIENCES↗

An agent-based framework for fuel cycle simulation with recycling

Simulation of the nuclear fuel cycle is an established field with multiple players. Prior development work has utilized techniques such as system dynamics to provide a solution structure for the matching of supply and demand in these simulations. In general, however, simulation infrastructure development has occurred in relatively closed circles, each effort having unique considerations as to the cases which are desired to be modeled. Accordingly, individual simulators tend to have their design decisions driven by specific use cases. Presented in this work is a proposed supply and demand matching algorithm that leverages the techniques of the well-studied field of mathematical programming. A generic approach is achieved by treating facilities as individual entities and actors in the supply-demand market which denote preferences amongst commodities. Using such a framework allows for varying levels of interaction fidelity, ranging from low-fidelity, quick solutions to high-fidelity solutions that model individual transactions (e.g. at the fuel-assembly level). The power of the technique is that it allows such flexibility while still treating the problem in a generic manner, encapsulating simulation engine design decisions in such a way that future simulation requirements can be relatively easily added when needed. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Comparison of Surrogate Models with Physical Models for Dynamic Probabilistic Risk Analysis Using the RAVEN Code

Dynamic probabilistic risk analysis (DPRA) has emerged in the nuclear industry as an effective tool to identify points of weakness in nuclear reactors and create a comprehensive approach to quantifying risk. While DPRA allows for detailed analysis, it usually requires thousands of runs due to the necessity of exploring low probability, high consequence events, which can be computationally prohibitively difficult to assess. Risk Analysis Virtual Environment (RAVEN) is a software package being developed under the Nuclear Energy Advanced Modeling and Simulation program at the Idaho National Laboratory. It is able to manage complex control logic to drive a RELAP-7 simulation and to handle sampling strategies including Monte Carlo, Latin Hypercube, Grid and Adaptive samplers. By performing a thorough investigation of the possibility space of an accident scenario with RELAP-7, RAVEN is able to identify consequences of accident scenarios that have not been encountered. The most computational resource intensive step of a RAVEN analysis is running the RELAP-7 code modeling the physical system behavior. Using surrogate models to represent the outcomes of more complex simulations rather than the full model can greatly reduce the computation effort required. In situations where the uncertainty distributions of a model are unknown, or when there are multiple sets of uncertainty distributions, DPRA generally requires rerunning the physical model for each set of uncertainty distributions used. By taking an unbiased sample of the physical model and creating a surrogate model from the results, the surrogate model can be sampled under a different set of uncertainty distributions to provide equivalent results. This paper presents an example of this approach. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Multi-objective sizing and dispatch for building thermal and battery storage towards economic and environmental synergy

The role of building thermal and battery storage is pivotal in advancing smart cities and achieving sustainability goals through effective energy management. Despite their significance, there are several limitations in the sizing approach and value stream analysis with various objectives for their widespread adoption in buildings. This work proposes a flexible and scalable multi-objective optimization framework for optimal sizing and dispatch of building thermal and battery storage, addressing conflicting objectives simultaneously using mixed-integer linear programming. The weighted-sum method is adapted, combining multiple objectives into a single function. The two-stage procedure iterates over different weights, generating optimal solutions and forming the Pareto front. Case studies are performed to assess the energy, economic, and environmental benefits of building energy storage systems for a large office building in three climate locations. The results demonstrate that the proposed framework efficiently determines optimal sizing and dispatch strategies, addressing the balance between economic viability and emission reduction. The dynamic relationship between time-of-use energy charges and emission factors leads to significantly different strategies based on whether economic or environmental concerns are prioritized. This research enhances our understanding of the benefits of TES and BES systems in buildings, providing valuable guidance to stakeholders.

25 ENERGY STORAGE↗

3D CFD Model Validation Using Benchmark Data of 1/16th Scaled VHTR Upper Plenum and Development of Wall Heat-Transfer Correlation For Laminar Flow

With support from the U.S. Department of Energy-Office of Nuclear Energy’s (DOE-NE’s) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, an effort has been pursued to support high-temperature gas-cooled reactor (HTGR) technology development and its modeling and simulation needs. There is a particular need for advanced modeling and simulation tools to predict thermal-fluid behavior in the nuclear reactor primary system, especially in the core and the lower and upper plena, during safety-related transients. In this report, two main such activities are presented relevant to the HTGRs: (1) three-dimensional (3D) computational fluid dynamics (CFD) validation using benchmark data from the upper plenum of Texas A&M University’s 1/16th scaled very-high-temperature gas-cooled reactor (VHTR), and (2) development of wall heat-transfer correlation for laminar flow in a wall-heated pipe. The CFD tool validation exercises can be helpful to choose the models and CFD tools to simulate and design specific components of the HTRGs such as upper plenum where jet mixing is a complex phenomenon. In a loss of forced circulation event, the laminar flow can be observed during the development of natural circulation flow. This work includes the development and validation of heat transfer correlations for laminar flow using the Nek5000 CFD code due to limited available experimental data for laminar flow conditions to guide low-order models (1D). In this report, the flow characteristics of a single isothermal jet discharging into the upper plenum was investigated using the Nek5000 Large-Eddy Simulation (LES) CFD tool. Several numerical simulations were performed for various jet-discharged Reynolds numbers ranging from 3,413 to 12,819. A grid-independent study was performed. The numerical results of mean velocity, root-mean-square fluctuating velocity, and Reynolds stress were compared against the benchmark data. Good agreement was obtained between simulated and measured data for axial mean velocities, except near the upper plenum hemisphere. The maximum predicted errors for axial mean velocities at various normalized coolant channel diameter heights of 1, 5, and 10 are 1.56%, 1.88%, and 3.82%, respectively. In addition, the predicted root-mean-square fluctuating velocity and Reynolds stress are qualitatively in agreement with the experimental data. The Nek5000 code was used to develop wall-heat transfer correlation for laminar flow in a cylindrical tube. Several simulations were performed for various Reynolds flow and wall-heat fluxes. A new heat transfer correlation was developed using data from Nek5000 simulation results and regression functions in Matlab. The developed heat transfer correlation is valid for various Reynolds flows from 200 to 2000. The predicted R² value for model fit was 0.875, which ensures that 87.5% of the model data lies on the Nek5000 data. Moreover, a machine learning (ML) tool was used to train and test the Nek5000 data. A good fit of the ML-based model was observed with the test data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗