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At least 469 records · Page 26

Performance Simulation and Analysis of Occupancy-Based Control for Office Buildings with Variable-Air-Volume Systems

Variable-air-volume (VAV) systems are used in many office buildings. The minimum airflow rate setting of VAV terminal boxes has a significant impact on both energy consumption and indoor air quality. Conventional controls usually have the terminal’s minimum airflow rate at a constant (e.g., 30% or more of the terminal design airflow rate), irrespective of the occupancy status, which may cause problems, such as excessive simultaneous heating and cooling, under ventilation, and thermal comfort issues. This paper examines the potential of energy savings from occupancy-based controls (OBCs). The sensed occupancy information, either occupant presence or people count, is used to determine the airflow rate of terminal boxes, the thermostat setpoints, and the lighting control. Using EnergyPlus, a whole-building energy modeling software, the energy savings of OBC strategies are evaluated for representative existing medium office buildings in the U.S. The simulation results show that the conventional OBC, based on occupant presence sensing, can save 8% of whole-building energy use in Miami (hot climate) for systems without air-side economizer and about 13% in both Baltimore (mixed climate) and Chicago (cold climate). Comparatively, the advanced OBC, based on people counting, can save 8% in Miami to 23% in Baltimore for systems with economizers. The outdoor-air fraction of the supply air from air-handling units significantly affects the potential energy savings from the advanced OBC strategy. In addition to energy savings, the advanced OBC satisfies the zone ventilation during all occupied hours over the whole year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Modeling, Performance Assessment, and Nodal Data Analysis of TRISO-Fueled Systems with Shift

This technical report documents several enhancements to the Shift Monte Carlo (MC) code under the US Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in fiscal year (FY) 2022. Performance enhancements were added to Shift specifically for tristructural isotropic (TRISO)–fueled reactor systems and guided based on performance analysis in FY 2021. For the pebble performance model developed in previous studies, the runtime improved by ~ 91× compared to the original model and ~ 2× compared to the user-optimized model. Compared to Serpent, Shift is ~ 3× slower if Serpent delta-tracking is enabled but ~ 2× faster when delta-tracking is disabled. The multigroup cross section generation was improved through simplifying tally input definitions, porting several post-processing tally operations from Python scripts into the Shift code base, and accounting for production reactions in the scattering multiplicity. Progress was also made on two emerging capabilities: (1) the development of Titan (a Shift reactor physics user interface) and (2) initial investigation into path-length tallies for computing multigroup scattering matrices.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Experimental Analysis of the Effects of Simulator Complexity on Human Performance

Human Reliability Analysis predicts accidents caused by human errors and is an important factor in Probabilistic Safety Assessment that comprehensively evaluates the safety of nuclear power plants. This study compares and analyzes the human performance of nuclear power plant operators according to the simulator complexity as part of the HRA data collection support method development project conducted by Idaho National Laboratory. This experiment was conducted by setting two types of simulators and scenarios as independent variables. The data collected by conducting the experiments in two different simulators were analyzed using an analysis of variance test and a correlation analysis, and four human performance charts were derived.

99 GENERAL AND MISCELLANEOUS↗

Analysis of leading edge protection application on wind turbine performance through energy and power decomposition approaches

Abstract Wind power production is driven by, and varies with, the stochastic yet uncontrollable wind and environmental inputs. To compare a wind turbine's performance, a direct comparison on power outputs is always confounded by the stochastic effect of weather inputs. It is therefore crucial to control for the weather and environmental influence. Toward that objective, our study proposes an energy decomposition approach. We start with comparing the change in the total energy production and refer to the change in total energy as delta energy. On this delta energy, we apply our decomposition method, which is to separate the portion of energy change due to weather effects from that due to the turbine itself. We derive a set of mathematical relationships allowing us to perform this decomposition and examine the credibility and robustness of the proposed decomposition approach through extensive cross‐validation and case studies. We then apply the decomposition approach to Supervisory Control and Data Acquisition data associated with several wind turbines to which leading‐edge protection was carried out. Our study shows that the leading‐edge protection applied on blades may cause a small decline to the power production efficiency in the short term, although we expect the leading‐edge protection to benefit the blade's reliability in the long term.

17 WIND ENERGY↗

A geospatial risk analysis graphical user interface for identifying hazardous chemical emission sources

Background: Performing back trajectory and forward trajectory using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) is a reliable approach for assessing particle transport after release among mid-field atmospheric models. HYSPLIT has an externally facing online interface that allows non-expert users to run the model trajectories without requiring extensive training or programming. However, the existing HYSPLIT interface is limited if simulations have a large amount of meteorological data and timesteps that are not coincident. The objective of this study is to design and develop a more robust tool to rapidly evaluate hazard transport conditions and to perform risk analysis, while still maintaining an intuitive and user-friendly interface. Methods: HYSPLIT calculates forward and backward trajectories of particles based on wind speed, wind direction, and the corresponding location, timestamp, and Pasquill stability classes of the regions of the atmosphere in terms of the wind speed, the amount of solar radiation, and the fractional cloud cover. The computed particle transport trajectories, combined with the online Proton Transfer Reaction-Mass Spectrometry (PTR-MS) data (https://figshare.com/articles/dataset/ARL_Data_from_PROS_station_at_Hanford_site/19993964), can be used to identify and quantify the sources and affected area of the hazardous chemicals’ emission using the potential source distribution function (PSDF). PSDF is an improved statistical function based on the well-known potential source contribution function (PSCF) in establishing the air pollutant source and receptor relationship. Performing this analysis requires a range of meteorological and pollutant concentration measurements to be statistically meaningful. The existing HYSPLIT graphical user interface (GUI) does not easily permit computations of trajectories of a dataset of meteorological data in high temporal frequency. To improve the performance of HYSPLIT computations from a large dataset and enhance risk analysis of the accidental release of material at risk, a geospatial risk analysis tool (GRAT-GUI) is created to allow large data sets to be processed instantaneously and to provide ease of visualization. Results: The GRAT-GUI is a native desktop-based application and can be run in any Windows 10 system without any internet access requirements, thus providing a secure way to process large meteorological datasets even on a standalone computer. GRAT-GUI has features to import, integrate, and convert meteorological data with various formats for hazardous chemical emission source identification and risk analysis as a self-explanatory user interface. The tool is available at https://figshare.com/articles/software/GRAT/19426742.

97 MATHEMATICS AND COMPUTING↗

Data-driven analysis and prediction of wastewater treatment plant performance: Insights and forecasting for sustainable operations

Here this study presents a comprehensive performance and forecasting analysis of the As-Samra wastewater treatment plant (WWTP) in Jordan, with two main objectives. Firstly, a thorough evaluation of the plant's performance is conducted. The analysis involves independently assessing historical operational conditions, plant production, and their statistical correlations using various statistical techniques. The second objective focuses on developing a data-driven forecasting approach to predict the plant's production one month in advance, using multiple machine learning models. The results highlight the effectiveness of principal component analysis (PCA) in simplifying operational data, revealing distinct operational clusters, and identifying seasonal production patterns while showing correlations between operational conditions and overall power production. The support vector machine (SVM) forecasting model emerged as the top performer, showcasing the potential of a hybrid forecasting approach. The findings offer valuable perspectives for enhancing operational efficiency, refining production planning, and ultimately improving the environmental impact of the plant.

42 ENGINEERING↗

Updated Estimate of Tritium Permeation from TPBAR Disposal Containers in ILV (U)

A tritium source term analysis was performed for TPBAR disposal in the E-Area Intermediate Level Vaults for the E-Area Low-Level Waste Facility Performance Assessment (PA). This analysis is based on an earlier source term analysis which treated the bulk oft he tritium residual as tightly bound by the TPBAR getter material, with only a small fraction existing as tritiated moisture in the lithium aluminate ceramic pellets. Together with atmospheric moisture trapped in the free volume, the tritiated water vapor is assumed to corrode steel surfaces inside the disposal container, covering them with a magnetite film while generating hydrogen. The carbon steel walls of the disposal container are permeable to hydrogen, providing a path way for tritium to escape containment. The rate of hydrogen generation is assumed to be limited by the rate of corrosion, which is assumed to be governed by parabolic reaction kinetics obtained from the literature. This relies on the further assumption that the water vapor consumed by the corrosion reaction is continually replaced by moisture from the lithium aluminate pellets until all of that moisture is gone. In addition to tritium permeation, the analysis also includes a slow leak through the disposal container walls at the maximum allowable leak rate, 1 x 1CH standard cm3/s. Results were obtained for four different combinations of internal and container wall temperatures, established in an earlier thermal analysis that considered two different vault loadings and two different TPBAR activity levels. Instantaneous release rates for these four cases are plotted in Figure ES-1 below

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

PWR Core Analysis for Cycle Extension and Uprates with LEU+ Accident Tolerant Fuel and 80 GWd/Tonne Burnup Limit

The U.S. Nuclear Regulatory Commission has recently drafted a rule enabling fuel burnup increase in light water reactors up to 80 GWd/t. In conjunction with use of fuel enrichment up to 10%, and accident tolerant fuel (ATF), this is anticipated to facilitate 24-month cycles in PWRs, along with further power uprates. In this paper, PWR core analysis is performed for 20% increased PWR power output along with cycle extension up to 24 months, in combination with use of chromia-doped fuel and chromium-coated clad, considered to be the most near-term ATF concepts. In combination, these lead to challenging conditions with a core average discharge burnup of up to ~74 GWd/t, challenging even the 80 GWd/t burnup limit. Analysis is performed using the 2-step method with POLARIS (within SCALE) used for the lattice calculations and PARCS for the core calculations. Core designs are first baselined for current operating conditions (LEU, 62 GWd/t discharge burnup limit) and then derived that meet cycle constraints on power distribution and the updated lead pin discharge burnup limit while maintaining at least two batches of fuel in the core. Gadolina loadings in fuel pins of up to 8% are used, with enrichment zoning both within the core and, to a limited extent, within assemblies. Here, doped fuel with coated cladding can utilize the same core designs as the reference UOX cores, exhibiting slightly lower burnup due to higher fuel density, which also offsets the slight reactivity penalty from the doping and coating. For the analysis performed here, doped fuel enabled a core with 24-month cycle and 20% uprate to stay within the 80 GWd/t lead pin discharge burnup limit.

LEU+↗

Studying CPU and memory utilization of applications on Fujitsu A64FX and Nvidia Grace Superchip

ARM-based manycore CPU architectures are well-positioned to provide the rising memory throughput requirements of modern data intensive scientific applications in High Performance Computing (HPC). The Fujitsu A64FX CPU platform is based on the ARM v8.2A architecture, and is the processor of the flagship Japanese supercomputer - "Fugaku", which was previously ranked as the #1 supercomputer in the world according to the Top500 list. The Nvidia Grace superchip features 144 Neoverse V2 cores based on the ARMv9 architecture with 4x128b SVE2, providing exceptional computational power. The chip supports up to 480GB of memory, making it ideal for AI, machine learning, and scientific computing workloads. In this paper, we conduct a thorough performance exploration of a variety of parallel bandwidth-sensitive benchmarks and applications compiled with the native Fujitsu compiler on a Fugaku A64FX compute node and ARM (LLVM) Compiler on an NVIDIA Grace superchip compute node, engaging all the computational cores per cluster using OpenMP multithreading (assuming the cores can drive the available bandwidth). Our ultimate goals are to study the resource utilization of scientific applications and benchmarks on A64FX and Grace superchip, considering graph application scenarios ( GAP Benchmark suite) and eleven appli- cation proxies from the Rodinia heterogeneous benchmark suite (considering domains such as Data Mining, Bioinformatics, Fluid Dynamics, Pattern Recognition, etc.). Through exhaustive performance monitoring, we quantify the resource utilization of diverse OpenMP-based HPC applications on both the Fujitsu A64FX and the Nvidia Grace Superchip platforms.

benchmarking, Performance Analysis, High performan↗

Calculation of Moisture-Dependent, Anisotropic Parameters Supporting the Hanford Site's Composite Analysis, Cumulative Impact Evaluation, and Performance Assessments

Variable, moisture (tension) dependent anisotropy (MDA) in unsaturated soils is an effective, large-scale (macroscopic) flow property that results from media heterogeneities at a smaller scale. The purpose of this environmental calculation file (ECF) is to document the variable MDA calculations using a script routine. The accuracy of the script calculations are cross-checked against results using other software. Appendices for this ECF are Appendix A, which documents supporting script use; Appendix B, which provides supporting spreadsheet calculations; and Appendix C, which provides supporting utility calculations. The work is in support of vadose zone flow and transport models used in performance assessment (PA), composite analysis (CA), and cumulative impact evaluation (CIE) at the Hanford Site.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Temperature‐Dependent Crystallization in Two‐Step Perovskite Deposition Revealed by In Situ GIWAXS and Machine Learning‐Guided Analysis

The performance and stability of perovskite solar cells are strongly governed by the crystallization behavior of their active layer. In two-step sequential deposition, early-stage film formation plays a decisive role in determining final phase purity and device quality. Guided by a data-driven analysis of nearly 39 000 devices in the FAIR perovskite database, we identified solvent-mediated quenching and thermal processing as key variables affecting power conversion efficiency (PCE), particularly in two-step fabrication. Here, to investigate these effects in real time, we designed and implemented a custom-built, temperature-controlled spin-coating system, enabling precise thermal modulation during precursor deposition. Using this platform, we performed in situ GIWAXS measurements to study the crystallization dynamics of FA 0.5 MA 0.5 PbI 3 films over a temperature range of 30°C–90°C. Our results reveal a non-monotonic relationship between spin-coating temperature and α-phase formation, governed by the interplay between precursor interdiffusion, PbI 2 crystallinity, and δ-phase suppression. The custom thermal control enabled us to isolate and quantify these competing effects during the earliest stages of film formation, providing mechanistic insight into how spin-coating temperature governs both phase purity and kinetic pathways in two-step perovskite systems. Temperature-dependent SEM and photovoltaic device measurements further demonstrate that early-stage crystallization pathways directly translate into differences in morphology, charge-transport continuity, and device performance. These findings inform targeted strategies for optimizing deposition protocols to balance rapid nucleation, phase stability, and device performance.

Saadawy, Ahmed [King Fahd University of Petroleum ↗

Physical Security Timeline Analysis in Support of Advanced Reactor Demonstration and Deployment

This report presents the regulatory requirements and directions on the physical security of advanced nuclear reactors in USA. Presently, a rule is being proposed that allows for a performance-based analysis. In determining the physical security requirements for an advanced reactor, new tools may be desired to conduct a performance-based analysis. These tools should incorporate dynamic analysis methods to provide as much realism as possible. In comparison, the security requirements for existing light water reactors (LWRs) are much more prescriptive and the analysis conducted to establish the required physical security strategies were more easily performed with static analysis. In order to achieve the cost goals that advanced reactors require for adoption; the nuclear security force required should not be excessive. Dynamic physical security analysis methods and tools have been developed by the US Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program. This report details how the dynamic risk analysis tools developed in the LWRS program using the dynamic risk modelling tool, EMRALD, may be adapted for use in analyzing the physical security designs for advanced reactors accounting for variable performance-based requirements. This report provides an example analysis of a hypothetical SFR using publicly available information and generic assumptions to demonstrate the methods and potential presentation and analysis of the results. No actual plant information is used in this example analysis. Future work in this area will create additional models that can be adapted for any advanced reactor concept and use various security features to create a physical security system that provides adequate protection from radiological theft and sabotage.

97 MATHEMATICS AND COMPUTING↗

Production of Fischer-Tropsch Synfuels at Nuclear Plants

A case study analysis was performed to evaluate nuclear-powered synthetic fuel production in the midwestern United States (U.S.). A Fischer-Tropsch (FT) fuel synthesis plant design was used as the basis for the analysis. The FT plant design was configured to produce a product slate consisting of diesel fuel, jet fuel, and motor gasoline blend stocks from carbon dioxide (CO 2 ) and hydrogen (H 2 ) feedstocks. The CO 2 feedstock for the FT plant was assumed to be sourced from biorefineries in the region around a Midwest light water reactor (LWR) nuclear power plant (NPP). The analysis specifies that power from the LWR is used to produce H 2 via high-temperature steam electrolysis and to operate the FT synfuel production plant. Capital costs were estimated for the FT plant while capital costs for the electrolysis plant were based on previous Idaho National Laboratory (INL) studies. In addition to labor and maintenance costs for the FT and electrolysis plants, operating costs also include the costs for CO 2 feedstock transport. An analysis was performed to determine the cost of transporting CO 2 from the distributed biorefinery sources to the centralized fuel synthesis plant as a function of the synfuel plant capacity and corresponding CO 2 demand. The primary revenue streams are associated with sales of the synthetic fuel products. The synthetic fuel products will likely follow the same market trends as the conventional fuel products. The synfuel price data was thus based on projections made by the U.S. Energy Information Administration (EIA) 2021 Annual Energy Outlook (AEO) for conventional fuel products minus federal and state taxes, as well as marketing and distribution costs. The economic analysis also considered cases that included and excluded revenues from the 2022 Inflation Reduction Act (IRA) clean hydrogen production tax credit (PTC) of $\$ $3.00/kg for the first ten years of operation. The economic analysis calculated the net present value (NPV) for cases involving steady-state synfuel production for comparison with the NPV for a business-as-usual case in which NPP continues to sell only electric power to the grid. A synfuel production “Reference Case” was considered in addition to sensitivity cases in which the plant capacity, electricity price, and synthetic fuel product prices were perturbed. The synfuel production Reference Case considered a scenario in which the electrolysis and synfuel plants utilized a combined electrical load of 1000 megawatt electrical (MWe) from the LWR with the balance of the LWR power output being sold to the electric grid. The economic analysis suggests that the synfuel production Reference Case evaluated in this analysis would lead to considerable economic potential for near-term deployment of a nuclear-based synfuel production plant. Specifically, the economic analysis suggests that the deployment of a 1000 megawatt (MW) nuclear-powered synfuel plant could result in a NPV increase of approximately $\$ $1.7 billion for a case with no clean synfuel price premium relative to conventional petroleum fuels when accounting for the additional revenues from the 2022 IRA clean hydrogen PTCs of $\$ $3/kg. Sensitivity analysis was performed to evaluate the effect of perturbation of selected model input parameters on the NPV for the synfuel production Reference Case. The sensitivity analysis indicates that the plant capacity has the largest impact on the differential NPV, with a smaller synfuel production capacity resulting in a decrease in revenue when a larger fraction of the power from the NPP is sold to the grid and a smaller fraction of the power is used to produce synthetic fuel products. The synfuel product pricing has the next largest impact on the differential NPV, with lower synfuel prices resulting in decreased NPV from decreased synfuel sales revenue while higher synfuel prices result in increased NPV from increased synfuel sales revenue. Electricity pricing has a smaller effect on the NPV than the fuel sales price since, in the Reference Case, most of the energy from the NPP is used for synfuel production and a smaller amount of the system revenues are associated with electrical power sales. However, the electricity price sensitivity does indicate that the Synfuel Integrated Energy System (IES) would have a greater NPV than the business-as-usual case (e.g., grid power sales only) when electricity market prices are low, suggesting that synfuel production could provide a strategy for decreasing the economic risks to NPPs posed by a loss of revenues attributed to falling electricity market prices.

10 SYNTHETIC FUELS↗

Geant4-based Analysis of Faraday Cup Performance for PIP-II Laser Wire Scanner System

The Proton Improvement Plan-II (PIP-II) accelerator upgrade at Fermilab marks a significant advancement in high-energy physics research. This initiative aims to enhance Fermilab's accelerator complex by replacing the existing linear accelerator (linac) with a warm front end (WFE) capable of accelerating H- beams up to 2.1 MeV. Subsequently, a superconducting linac (SCL), that further accelerates these beams up to 800 MeV. To accurately measure the transverse beam profile, traditional wire scanners will be utilized in the WFE section, while Laser wire scanners will be implemented along the SCL. The Faraday cup for the Laser wire scanners has been designed using the GEANT4 simulation toolkit. This poster presents a detailed analysis of its performance along the SCL, focusing on electron absorption, secondary electron emission, backscattering, etc.

Wijethunga, S. A.K.↗