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Resolving intragranular stress fields in plastically deformed titanium using point-focused high-energy diffraction microscopy

Abstract The response of a polycrystalline material to a mechanical load depends not only on the response of each individual grain, but also on the interaction with its neighbors. These interactions lead to local, intragranular stress concentrations that often dictate the initiation of plastic deformation and consequently the macroscopic stress–strain behavior. However, very few experimental studies have quantified intragranular stresses across bulk, three-dimensional volumes. In this work, a synchrotron X-ray diffraction technique called point-focused high-energy diffraction microscopy (pf-HEDM) is used to characterize intragranular deformation across a bulk, plastically deformed, polycrystalline titanium specimen. The results reveal the heterogenous stress distributions within individual grains and across grain boundaries, a stress concentration between a low and high Schmid factor grain pair, and a stress gradient near an extension twinning boundary. This work demonstrates the potential for the future use of pf-HEDM for understanding the local deformation associated with networks of grains and informing mesoscale models. Graphical abstract

36 MATERIALS SCIENCE↗

NPP Simulators for Coupled Thermal and Electric Power Dispatch

The Light Water Reactor Sustainability (LWRS) program within the United States Department of Energy supports extending the operation of the U.S. commercial nuclear power plant (NPP) fleet. Within the LWRS program, the Flexible Plant Operation and Generation (FPOG) Pathway works to diversify the revenue streams of light water reactors (LWRs) by opening opportunities for the co-generation of non-electric products in addition to supplying electrical power to the grid. Recent events have added greater motivation to these efforts. For example, the recent Inflation Reduction Act (IRA) passed by the U.S. federal government offers substantial tax incentives for producing clean hydrogen, the technology readiness level of dispatchable and high-efficiency hydrogen production has dramatically increased in a short time, and societal response to world climate change is driving a transition away from fossil fuels. Producing hydrogen with maximum efficiency using nuclear power requires dispatching both electrical and thermal power from the nuclear plant to the hydrogen plant, so testing concepts of operations for combined electrical and thermal power dispatch (TPD) from an NNP to a hydrogen plant is of interest. This report documents achievement of the Light Water Reactor Sustainability (LWRS) program milestone “Install and demonstrate a vendor-developed simulator on the Human Systems Simulation Laboratory (HSS) for dispatch of LWR electrical power to a close-coupled electrolysis plant” with a due date of Dec. 22, 2022. Several factors provide motivation for this effort. Coupling the power generation deck of a nuclear power plant to a hydrogen production facility introduces new possibilities for operational transients that must be addressed. In particular, the performance of the integrated system during startup and shutdown of the hydrogen production facility, as well as offnormal conditions, need to be evaluated to ensure there are no adverse effects on the operation of the existing NPP. The concept of operations involving the NPP, the hydrogen plant, and the electric power grid must be tested using NPP simulators and operating procedures that have been modified for TPD operations. These tests must also include dynamic simulations of the coupled tertiary thermal and electric loads as well as coordinated activities with NPP operators, tertiary load operators and grid power coordinators. The report summarizes progress in developing and testing full-scope NPP simulators at the HSSL, including a generic BWR simulator from GSE Systems, Inc. and generic PWR simulator from Westinghouse. In the case of the TPD-GBWR Simulator from GSE Systems, Inc., a BWR is thermally coupled to a high temperature electrolysis (HTE) plant that produces hydrogen and oxygen from de-ionized water. The hydrogen plant is not explicitly simulated but only included as a transient heat sink. A thermal power dispatch (TPD) system transfers heat between the steam systems at the BWR and the hydrogen plant. Operational results from two versions of the modified simulator are presented. The first version uses synthetic oil as a heat transfer fluid in a closed delivery heat loop (DHL) that generates steam at the hydrogen plant. The second version uses steam as the heat transfer fluid in a delivery steam line (DSL) to provide steam to the hydrogen plant. For both versions, the estimated thermal power delivery distance is approximately one kilometer. The amount of thermal power dispatched in the simulators is 15% of the total reactor thermal power such that the simulators provide a tool to study the feasibility of coupling a BWR to industrial processes that benefit from a combination electrical and thermal power dispatch. Ongoing work within a CRADA is also developing a full-scope PWR simulator provided by Westinghouse for both thermal and electric power coupling. This simulator is based on a PWR plant with two three-loop Westinghouse reactors. Westinghouse PWRs are sufficiently similar that a simulator of a three-loop reactor is an appropriate representation for two-loop and four-loop PWR reactors. The three-loop simulator will initially be modified for close-coupling to a 100 MW HTE hydrogen production plant that will require approximately 25 MW of thermal power while operating at its maximum rated capacity. The simulator testing will include full coupling to dynamic simulations of a hydrogen production plant and a representative bulk electric grid. The simulator provided by Westinghouse is similar to the GPWR simulator that INL has already obtained from GSE Systems but has a few important added benefits. First, the Westinghouse simulator is based on digital controls and has additional screens that can be called up to show parameter trends to assist operators in decision-making. The Westinghouse simulator also has upgrades to the controls and hardware representations, such as valve actuators, that make it more realistic and flexible in terms of accurately sim

99 GENERAL AND MISCELLANEOUS↗

Reevaluation of XPS Pt 4f peak fitting: Ti 3s plasmon peak interference and Pt metallic peak asymmetry in Pt@TiO2 system

The structural, electronic, and electrochemical properties of noble metals supported on transition metal oxides, such as Pt nanoparticles (NPs) supported on TiO2 (Pt@TiO2), have been extensively studied for their relevance to energy technologies, including photocatalysis, electrocatalysis, and electrochemical energy conversion. As the need to lower the amount of Pt and other noble metals used in energy conversion systems becomes urgent, it is essential to accurately quantify the loading of these metals and electronic density redistribution between them and their supports. X-ray photoelectron spectroscopy (XPS) is widely used for the identification and quantification of chemical species. In particular, fitting of the Pt 4f spectra for Pt@TiO2 is frequently performed to determine the chemical environment and oxidation state of Pt, which strongly affect the physical behavior and catalytic performance of this system. Here, we show that neglecting contributions due to the Pt surroundings and the asymmetry of the Pt metal peak in the line shape fitting can lead to severe mischaracterization of the oxidation state of Pt. We quantify the effects of background contributions that stem from the TiO2 support and discuss how factoring in the strong asymmetry of Pt 4f doublets, which stems from the shake-up type processes, affects the interpretation of Pt 4f XPS line shape.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Heat pump water heater enhanced with phase change materials thermal energy storage: Modeling study

A promising solution to improve the first hour rating (FHR) of a heat pump water heater (HPWH) involves employing a secondary tank which contains phase change material (PCM) capsules. To better understand the influence of PCM thermal storage on the HPWH operational performance, a dynamic model was developed to simulate and analyze the behavior of a newly developed HPWH technology that incorporates PCM storage into a standard HPWH to optimize key parameters such as the uniform energy factor and FHR. Mathematical models of several key components of the proposed HPWH-PCM integrated thermal energy storage (TES) system, e.g., water heater tank, PCM TES tank, evaporator, compressor, and expansion valve, have been elaborated. Also, a model-based control co-simulation platform was developed to integrate a embed PCM storage HPWH dynamic model with a control model for better supporting control design, analysis, verification, and validation. The model accuracy has been validated through comparing simulation results with lab test results, with a mean average percentage error of <5.5% for most of the selected performance variables. In addition, using the developed co-simulation platform, the demand response control strategy was studied to evaluate the load flexibility of the combined HPWH-PCM storage system by shifting system power usage to outside of the 3.5 h peak load period.

25 ENERGY STORAGE↗

Impact of Urban Pollution on Organic-Mediated New-Particle Formation and Particle Number Concentration in the Amazon Rainforest

A major challenge in assessing the impact of aerosols on climate change is to understand how human activities change aerosol loading and properties relative to the pristine-preindustrial baseline. Here we combine chemical transport simulation and field measurements to investigate the effect of anthropogenic pollution from an isolated metropolis on particle number concentration over the preindustrial-like Amazon rainforest through various new-particle formation (NPF) mechanisms and primary particle emissions. To represent organic-mediated NPF, we employ a state-of-the-art model that systematically simulates the formation chemistry and thermodynamics of extremely low volatility organic compounds as well as their roles in NPF processes, and further update the model to improve organic NPF simulations under human-influenced conditions. Results show that urban pollution from the metropolis increases particle number concentration by a factor of 5–25 over the downwind region (within 200 km from city center) compared to background conditions. Overall, our model indicates that NPF contributes over 70% of the total particle number in the downwind region except immediately adjacent to the sources. Among different NPF mechanisms, the ternary NPF involving organics and sulfuric acid overwhelmingly dominates. The improved understanding of particle formation mechanisms will help better quantify anthropogenic aerosol forcing from pristine-preindustrial times to present day.

54 ENVIRONMENTAL SCIENCES↗

Design and Prototyping of Advanced Control Systems for Advanced Reactors Operating in the Future Electric Grid (Final Report)

Despite its significant advantages as a baseload, low-carbon energy source, the U.S. nuclear power industry has faced increasing difficulties in maintaining economic competitiveness in a rapidly evolving energy market. The economic conditions faced by the current fleet of nuclear power plants (NPPs) in the U.S. deregulated electricity market require a concerted effort to mitigate specific cost factors. Many units are struggling to stay competitive, and some premature shutdowns have occurred. Besides, in response to the large penetration of renewable energy sources, the role of nuclear power plants as pure baseload units needs to be reconsidered. Based on these experiences, operational flexibility is considered a fundamental requirement for the next generation of nuclear reactors to be competitive in the future energy market. The deployment of advanced reactors capable of operating within a new power grid paradigm, known as the Integrated Energy System (IES) was investigated. This approach combines new reactor designs with Thermal Energy Storage (TES) technologies, allowing the nuclear reactor to maintain a steady power output without the need for constant adjustments in response to load demand fluctuations. With this configuration, the reactor operates as a baseload unit, experiencing only very gradual power transients, while the energy storage facility within the power conversion cycle acts as a peaking unit.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Integration of the Back End of the Nuclear Fuel Cycle

Management of spent nuclear fuel and high-level radioactive waste consists of three main phases – storage, transportation, and disposal – commonly referred to as the back end of the nuclear fuel cycle. Current practice for commercial spent nuclear fuel management in the United States (US) includes temporary storage of spent fuel in both pools and dry storage systems at operating or shutdown nuclear power plants. Storage pools are filling to their operational capacity, and management of the approximately 2,200 metric tons of spent fuel newly discharged each year requires transferring older and cooler spent fuel from pools into dry storage. Unless a repository becomes available that can accept spent fuel for permanent disposal, projections indicate that the US will have approximately 136,000 metric tons of spent fuel in dry storage systems by mid-century, when the last plants in the current reactor fleet are decommissioned. Current designs for dry storage systems rely on large multi-assembly canisters, the most common of which are so-called “dual-purpose canisters” (DPCs). DPCs are certified for both storage and transportation, but are not designed or licensed for permanent disposal. The large capacity (greater number of spent fuel assemblies) of these canisters can lead to higher canister temperatures, which can delay transportation and/or complicate disposal. This current management practice, in which the utilities continue loading an ever-increasing inventory of larger DPCs, does not emphasize integration among storage, transportation, and disposal. This lack of integration does not cause safety issues, but it does lead to a suboptimal system that increases costs, complicates storage and transportation operations, and limits options for permanent disposal. This paper describes strategies for improving integration of management practices in the US across the entire back end of the nuclear fuel cycle. The complex interactions between storage, transportation, and disposal make a single optimal solution unlikely. However, efforts to integrate various phases of nuclear waste management can have the greatest impact if they begin promptly and continue to evolve throughout the remaining life of the current fuel cycle. A key factor that influences the path forward for integration of nuclear waste management practices is the identification of the timing and location for a repository. The most cost-effective path forward would be to open a repository by mid-century with the capability to directly dispose of DPCs without repackaging the spent fuel into disposalready canisters. Options that involve repackaging of spent fuel from DPCs into disposalready canisters or that delay the repository opening significantly beyond mid-century could add 10s of billions of dollars to the total system life cycle cost.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory Protected Areas Database of the United States (PAD-US) areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway or within an airport area boundary Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory USGS Protected Areas Database of the United States (PAD-US) GAP status 1, 2, or 3 areas US National Parks Wetlands USFWS critical habitats BIA land areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗

Illuminating the mechanistic impacts of an Fe-quaterpyridine functionalized crystalline poly(triazine imide) semiconductor for photocatalytic CO 2 reduction

The strategy of incorporating earth-abundant catalytic centers into light-absorbing architectures is desirable from the viewpoint of low cost, low toxicity, and versatility for activating small molecules to produce solar-based fuels. Herein, we show that an Fe-quaterpyridine molecular catalyst can be anchored to a light-absorbing, crystalline, carbon nitride (PTI), to yield a molecular-catalyst/material hybrid, Fe-qpy-PTI, capable of facilitating CO 2 reduction to CO selectively (up to ∼97–98%) in aqueous solution under low-intensity light irradiation. This hybrid material leverages the ability of the Fe-qpy catalyst to bind CO 2 upon a one-electron reduction, as achieved by transfer of excited electrons from the carbon-nitride semiconductor. At a low incident power density of only 50 mW cm −2 , the catalytic activity of the hybrid material was measured across a range of catalyst loadings from 0.1–3.8 wt%, yielding CO rates of up to 596 μmol g −1 h −1 for a 3.8 wt% loading during a 3 h experiment. Over the course of 8 h, the hybrid material attained a CO evolution rate of 608 μmol g −1 h −1 and 305 turnovers for a TOF of ∼38 h −1 and an apparent quantum yield of 2.6%. Higher light intensities provided an initial increase in activity but negatively impacted photocatalytic rates with time, with an AQY of 0.6% at 150 mW cm −2 and 0.4% at 250 mW cm −2 . Transient absorption spectroscopy results showed electron survival probabilities consistent with the trends in observed product rates. Computational modeling was also used to evaluate and understand the mechanistic pathway of the high product selectivity for CO versus H 2 . These results thus help unveil key factors for leveraging the mechanistic understanding of molecular catalysts for CO 2 reduction for pairing with light absorbing semiconductors and establishing optimal conditions to attain maximal rates in aqueous solution.

McGuigan, Scott [Baylor University, Waco, TX (Unit↗

Modeling Nanoscale Ohmics in Carbon Supports of Fuel Cell Cathodes

Here, reducing platinum (Pt) loading in polymer electrolyte fuel cells (PEFCs) while meeting performace requirements is critical to their widespread deployment. However, significant polarization losses manifest at higher current densities in cathodes with lower Pt content. The morphology of the carbon supports in PEFC cathodes affects the location of Pt deposition into the micropits or onto the surface of the carbon support, translating into different kinetic and transport resistances. In this work, we derive an agglomerate scale model that differentiates the sink terms for Pt on the surface and in the pits of carbon supports. We develop an approach to assess the impact of nanoscale ohmic resistance to Pt in the micropits arising from weakly ionic solution in the carbon support on PEFC performance. Effectiveness factors relating the actual reaction rate to the maximum reaction rate (had all the Pt been exposed) are derived and embedded into a one-dimensional catalyst layer model. Parameters in the catalyst layer model are tuned based on experimental local oxygen transport resistances. Subsequently, we estimate bounds for the micropore resistances based on geometric and physical arguments. Lastly, polarization curves are simulated to assess the effect of the micropore resistance in fully-humidified and oxygen-rich environments.

25 ENERGY STORAGE↗

ACT University Collaboration Proposal: Role of manufacturing defects on material failure under dynamic loading for developing enhanced failure models and theories (Final Report)

Research on the tensile behavior of additively manufactured 316L stainless steel coupon specimens at increasing strain rates was conducted over the past year at Penn State. Dynamic loading rates into the 1000 1/s loading rates were performed on specimens with nearly 1.32” gage lengths. Stress-strain plots show ductile and plastic behavior well beyond 12% strain with necked specimens, having smaller effective gage lengths showing up to 56% ultimate strain. Additional tests performed on compact tension specimens helped with simulation work to understand the deformation behavior. Using finite elements, it was possible to determine the feasibility of a comprehensive experimental validation study towards an improved model for AM material failure – specifically, the Bai-Wierzbicki approach which accounts for lode angle and triaxiality. A non-significant number of tests are projected for eight specific failure nodes, with additional replicates to provide strain-rate capabilities to the existing formulation. One such correction factor is explored for quasi-static, notched specimens. Finally, stress intensity factor was explored using a set of compact-tension specimens which would also provide useful validation data for any simulation work.

36 MATERIALS SCIENCE↗

Physics analysis and design of heavy water reflected thermal test reactor

Here, this work investigates the option of modifying the Advanced Test Reactor by replacing the current beryllium reflector with heavy water. Such a change may provide some potential benefits for not only increasing the thermal irradiation capabilities but also resolving other problems such as reflector integrity issues due to fast fluence damage, which is always a limiting factor in the lifetime of the current beryllium reflector. This paper presents the analysis and estimation of the ATR core physics parameters by replacing the current beryllium reflector with heavy water (D 2 O). The paper first describes the details of two selected conceptual designs, which are partially reflected with either beryllium or graphite, and how they are derived from the baseline beryllium reflector concept. Then, reactor physics performance parameters for the two new concepts are assessed by comparing with those of the baseline concept. The performance parameters considered in this paper include in-pile tube neutron and gamma fluxes and heating rates, maximum loop voiding reactivity, core power behavior with different power splits, predicted cycle length with a given fuel loading, and thermal hydraulic analysis with a higher lobe power split. It is important to note that this study focuses on the reactor physics aspects and does not delve into the engineering challenges associated with such a design modification.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Dispatch Optimization, System Design and Cost Benefit Analysis of a Nuclear Reactor with Molten Salt Thermal Storage

Variable renewable energy availability has increased the volatility in energy prices in most markets. Nuclear power plants, with a large ratio of capital to variable costs, have historically operated as base load energy suppliers but the need for more flexible operation is increasing. We simulate the techno-economic performance of a 950 MWt nuclear power plant, based on the Westinghouse lead-cooled fast reactor, coupled with molten salt thermal storage as a method for flexible energy dispatch. We use the System Advisor Model to model the nuclear reactor thermal power input and power cycle operating modes. We combine this robust engineering model with a mixed-integer linear program model for optimized dispatch scheduling. We then simulate the coupled nuclear and thermal storage system under different market scenarios with varying price volatility. We find that the coupled plant outperforms the base plant under markets where energy price peaks fluctuate by a factor of two or more about the mean price. We show that a calculated power purchase agreement price for the plant improves by up to 10% when operating under California energy market conditions. Sensitivity analysis on the thermal storage cost shows that the optimal design remains unchanged even when doubling costs.

25 ENERGY STORAGE↗

Cooperative Transmission Expansion Planning Experiment Data and Results

GO WEST is an open-source power grid modeling framework for U.S. Western Interconnection, which allows users to tailor the model depending on their research study and science questions. It covers 28 balancing authorities (BA) and 12 states in U.S. Western Interconnection. GO WEST allows users to select different number of nodes and come up with a simplified network by utilizing 10,000 nodal topology of U.S. Western Interconnection created by Texas A&M University. Users can try and select different number of nodes, mathematical formulations (linear programming vs. mixed-integer linear programming), transmission line limit scaling factors, and hurdle rate scaling factors. GO WEST offers a unit commitment and economic dispatch (UC/ED) module to simulate grid operations on an hourly scale. In this sense, users can calibrate and validate their model versions by comparing model outputs to historical datasets. TEP is an open-source transmission capacity expansion model, built on GO WEST framework. It utilizes linear programming to optimize transmission capacity addition investment on existing lines within GO WEST framework. In this sense, TEP model only increases the thermal capacity of existing transmission lines and does not add new lines to the system, which leaves the topology preserved. TEP minimizes the total cost of the system which comprises the operational cost of satisfying electricity demand (i.e., generation cost), cost of loss of load (i.e., unserved energy), cost of power flow, and cost of new transmission capacity additions (i.e., investment cost). In order to use TEP model, users need to create scenarios with GO WEST framework. In this analysis, outputs from several models are used to create future inputs to GO WEST and TEP models, including GCAM-USA, TELL, CERF and reV. This dataset includes experiment inputs and outputs from three different transmission expansion scenarios (cooperative, intermediate, and individual) for 2019 and 2059. For 2019, a base scenario to illustrate the default (i.e., historical) power grid operations is also included. This study utilizes rcp45hotter_ssp3 scenario from a previous version of GCAM-USA simulations. Sources of the shapefiles in supplementary data are HIFLD Open and U.S. Energy Atlas. Please see the README file for a detailed description of the main and supplementary data.

Capacity Expansion Model↗

Research Highlight - Dispatch Optimization, System Design and Cost Benefit Analysis of a Nuclear Reactor with Molten Salt Thermal Storage

We highlight our work from our previous publication titled "Dispatch Optimization, System Design, and Cost Benefit Analysis of a Nuclear Reactor with Molten Salt Thermal Storage" published in MDPI Energies 2022 (doi.org/10.3390/en15103599). Variable renewable energy availability has increased the volatility in energy prices in most markets. Nuclear power plants, with a large ratio of capital to variable costs, have historically operated as base load energy suppliers but the need for more flexible operation is increasing. We simulate the techno-economic performance of a 950 MWt nuclear power plant, based on the Westinghouse lead-cooled fast reactor, coupled with molten salt thermal storage as a method for flexible energy dispatch. We use the System Advisor Model to model the nuclear reactor thermal power input and power cycle operating modes. We combine this robust engineering model with a mixed-integer linear program model for optimized dispatch scheduling. We then simulate the coupled nuclear and thermal storage system under different market scenarios with varying price volatility. We find that the coupled plant outperforms the base plant under markets where energy price peaks fluctuate by a factor of two or more about the mean price. We show that a calculated power purchase agreement price for the plant improves by up to 10% when operating under California energy market conditions. Sensitivity analysis on the thermal storage cost shows that the optimal design remains unchanged even when doubling costs.

97 MATHEMATICS AND COMPUTING↗

GPR Robotic Assisted Non-Destructive Evaluation of Concrete Structures - 20196

Reinforced concrete structures are always under exposure of internal or external deteriorations due to many factors such as environmental, nuclear radiation or even construction deficiencies. The use of nondestructive test is one of the reliable methods to inspect structural members. In this case, GPR has a good capability to detect inside deteriorations of concrete structures. However, in many cases it is hard to inspect structural members by hand due to safety issues or inaccessibility. Thus, an alternative way to reduce such risks is to employ robot to carry nondestructive equipment. In this research, twelve reinforced concrete RC beams (8 x 16 x 96, width, height and length) are cast in the lab. Three RC beams have no defect and nine others various defects such as corrosion, de-bonded bars, void, delamination and honeycombing. The one-point load is applied at the center of the RC beam. The loading level is carried out at three levels: 50%, 75% and 100% of maximum load and total load-displacement diagram are performed. The load is held at each level and the robotic GPR is used to scan the side of RC beams. Then, RADAN software is employed to find out any defects at different loading conditions and visualize the crack propagation. The RADAN results show that the pattern of crack propagation for corrosion and debonding are same. Also, the load-displacement results present that inside defect cause reduction of load-capacity of RC beam. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Energy-efficient sorption-based gas clothes dryer systems

Standard electric resistance and fuel-driven dehydration technologies exhibit a maximum coefficient of performance of well below 1 mainly due to enthalpy losses associated with the air leaving the dehydration system. To improve energy efficiency, condensing dryer systems condense the moisture captured from a product in a closed-loop air circulation cycle. Existing condensing dehydration systems including heat pump dryers, however, need to significantly cool the air to achieve dehumidification. The added cooling and subsequent heating to return the air to a desired drying temperature consume substantial energy and thus reduce drying performance. Here, an innovative sorption-based gas dehydration system is proposed to overcome barriers deteriorating energy efficiency in existing gas, electric, or heat pump dryer systems. Decoupling latent and sensible loads, the system employs a liquid-desiccant solution to directly capture air humidity, thereby allowing circulation of the air in a closed loop to achieve high drying energy efficiency. In other words, the system captures waste latent heat from the moisture produced during the dehydration process and reuses it to improve energy efficiency. This study focuses on a comprehensive quasi-steady-state thermodynamic modeling of the proposed sorption-based dehydration concept employed for a gas clothes dryer application to predict transient response and overall drying performance (i.e., time and energy metrics). The analysis indicates the proposed sorption-based gas clothes dryer system can deliver a specific moisture extraction rate of 1.71 kg of water per kWh (i.e., a combined energy factor of 3.167 kg (6.98 lbm) of dry cloth per kWh) with a drying time of 44 min. This is a 112% energy improvement compared with state-of-the-art gas clothes dryers exhibiting a combined energy factor of 1.50 kg (3.3 lbm) of dry cloth per kWh. The technology pursued here can potentially be employed as a platform for many fuel-driven equipment to take advantage of available waste thermal energy in the environment instead of simply burning a fuel.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗