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At least 397 records · Page 22

Low-temperature solar thermal-power systems for residential electricity supply under various seasonal and climate conditions

In this work, the performance of low-temperature (<100 degrees C) solar thermal-power systems to satisfy residential electric loads was analyzed. The solar-driven system was designed to provide a fraction of the total electricity demand in a complementary operation with the electric grid. The analysis was conducted for an coperation during seven days each season, considering real solar and climate variables and residential loads at different climate zones in the United States. The efficiency of the system strongly depends on the solar radiation profile and the ambient temperature. Maximum efficiencies of around 9.5% were obtained in the cold and marine climate zones due to the high solar energy input and low heat dissipation temperatures. In these two zones, the system could supply more than 98% of the electricity demand all seasons. At mixed-humid and hot-humid regions, the system supplied around 50% of the electric load in three of the four seasons, but it only supplies about 27% of the electricity needs in the mixed-humid zone during summer and hot-humid zone during winter. The effect of the solar collector field area and the tank volume was also analyzed. In general, larger solar fields positively impact the efficiency. However, the impact of the tank volume varies depending on the solar radiation profile and the load requirements. Average efficiencies for the seven-day operation can be larger than 6% with a proper selection of the solar collector area and tank volume for an Organic Rankine Cycle with a capacity of about 2.6 kW. Finally, an economic analysis of the system was conducted, and the results were compared with a solar PV + battery system of similar capacity. It is expected that the cost for the analyzed solar-thermal system decreases in the coming years with the increased interest on low temperature applications.

14 SOLAR ENERGY↗

End-Use Savings Shapes Upgrade Package Documentation: Wall and Roof Insulation, New Windows, LED Lighting, HP-RTU and ASHP-Boiler

Building on the successfully completed effort to calibrate and validate the U.S. Department of Energy’s ResStock™ and ComStock™ models over the past 3 years, the objective of this work is to produce national data sets that empower analysts working for federal, state, utility, city, and manufacturer stakeholders to answer a broad range of analysis questions. The goal of this work is to develop energy efficiency, electrification, and demand flexibility enduse load shapes (electricity, gas, propane, or fuel oil) that cover a majority of the high-impact, market-ready (or nearly market-ready) upgrade measures, or upgrades. “Measures” refers to energy efficiency variables that can be applied to buildings during modeling. An end-use savings shape is the difference in energy consumption between a baseline building and a building with an energy efficiency, electrification, or demand flexibility upgrade applied. It results in a time-series profile that is broken down by end use and fuel (electricity or on-site gas, propane, or fuel oil use) at each time step.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Review of data-driven models for quantifying load shed by non-residential buildings in the United States

Shifting and shedding power demand in buildings can be cost-effective techniques for grids to function reliably and for end users to earn compensation. Grid operators reimburse customers in proportion to the quantity of load shed. Simple data-driven methods are used to quantify this shed, which is the difference between a measured load during the event and modeled "baseline" that would have occurred in absence of the event. These methods have evolved over the years and in many cases have been integrated with building physics, to make them a hybrid between physics based and empirical models. However, there is no comprehensive analysis that provides guidance to building operators, grid operators and researchers in selecting appropriate models based on their specific needs and available data. Here, this work aims to fill this gap by critically assessing the performance of baseline models put forward from the year 2000 through 2023. The literature reviewed includes reports generated by grid operators, reports from national laboratories and academic journal articles. The work outlines modeling features like the inputs, training period, estimation method, adjustments to fine tune the predictions and metrics to evaluate the performance. A comprehensive list of 50 models has been provided. For each model, the study explores the applicability of the model to weather sensitive buildings, variability in the building profile, timing of the event, and whether the building reduces energy consumption before an event. The work identifies the situations in which a particular model works and draws lessons based on evidence of performance. Finally, recommendations to aid in model selection are given.

97 MATHEMATICS AND COMPUTING↗

Shock Compression of Fluorapatite to 120 GPa

Apatite is a phosphate mineral relevant to shock metamorphism in planetary materials. Here, we report on the response of natural fluorapatite from Durango, Mexico under shock wave loading between 14.5 and 119.5 GPa. Wave profile measurements were obtained in plate-impact experiments conducted on [0001]-oriented fluorapatite single crystals. To GPa peak stresses, we observed a two-wave structure indicating an elastic-inelastic response with elastic wave amplitudes of 10.5–13.1 GPa. Between 39.1 and 62.1 GPa, a complex wave structure was observed involving the propagation of three waves. At and above 73.7 GPa, only a single shock wave was observed. The data above 73.7 GPa provided the following linear shock velocity – particle velocity relationship: U s = 6.5(2) + 0.78(6) u p , (mm/μs). Above 80 GPa, the densities in the shocked state exceed both the extrapolated 300-K density of fluorapatite and the predicted 300-K density for a mixture of the high-pressure assemblage, tuite and CaF 2 . Furthermore, this result indicates that fluorapatite undergoes a transition to a denser structure under shock loading at these conditions. The shock response of fluorapatite is observed to be similar to enstatite but stiffer than quartz and albite at the stresses examined in this work.

58 GEOSCIENCES↗

Characterization of a Human Platelet Lysate-Loaded Keratin Hydrogel for Wound Healing Applications In Vitro

One of the promising approaches to facilitate healing and regenerative capacity includes the application of growth-factor-loaded biomaterials. Human platelet lysate (hPL) derived from platelet-rich plasma through a freeze-thaw process has been used as a growth factor rich therapeutic in many regenerative applications. To provide sustained local delivery of the hPL-derived growth factors such as epidermal growth factor (EGF), the hPL can be loaded into biomaterials that do not degrade rapidly in vivo. Keratin (KSO), a strong filamentous protein found in human hair, when formulated as a hydrogel, is shown to sustain the release of drugs and promote wound healing. In the current study, we created a KSO biomaterial that spontaneously forms a hydrogel when rehydrated with hPL that is capable of controlled and sustained release of pro-regenerative molecules. Our study demonstrates that the release of hPL is controlled by changing the KSO hydrogel and hPL-loading concentrations, with hPL loading concentrations having a greater effect in changing release profiles. In addition, the 15% KSO concentration proved to form a stable hydrogel, and supported cell proliferation over 3 days without cytotoxic effects in vitro. The hPL-loaded keratin hydrogels show promise in potential applications for wound healing with the sustained release of pro-regenerative growth factors with easy tailoring of hydrogel properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantifying the Influence of Size, Shape, and Density of Microplastics on Their Transport Modes: A Modeling Approach

Microplastics (MPs) pose significant risks to marine ecosystems and human health, necessitating accurate predictions of their distributions in aquatic environments for effective risk mitigation. However, understanding MP transport dynamics is challenging because of the inadequate representation of MP characteristics such as size, shape, and density in numerical models. Further, the accuracy of the MP vertical profiles in existing models has not been thoroughly validated. Thus, we developed an MP transport model within the Finite Volume Community Ocean Model framework (FVCOM-MP) by integrating MP characteristics. We validated FVCOM-MP against experimental and analytical data, focusing on various MP transport modes and transitions. FVCOM-MP successfully replicates MP profiles in different transport modes, including the bedload, surface-load, suspended-load, and mixed-load modes. Additionally, we introduce phase diagrams for classifying MP transport modes based on particle characteristics, enhancing our understanding of MP dynamics in aquatic systems. The transport modes for a number of real-world MP particles, including fishing line, plastic bag/bottle fragments, synthetic fibers, tire wear particles, polyvinyl chloride and expanded polystyrene pellets, were analyzed with these phase diagrams.

Microplastic transport, Settling velocity, Rising ↗

A System-Level Model for Estimating Residual Strain and Life of Nuclear Reactor Coolant System Components Under Connected-System-Thermal–Mechanical Boundary Conditions

Background: Environmental-assisted fatigue (EAF) is a major issue for the long-term survival of nuclear power plant fleets in the U.S. and worldwide. Multi-material welded regions (e.g., nozzles) and other high-stress regions of reactor coolant system (RCS) components are prone to EAF-related damage. Objective: The discussed work describes a system-level finite element (FE) model of RCS components of a pressurized water reactor (PWR). This is with the goal of predicting the stress hotspots, strain residuals, strain amplitudes and the resulting fatigue lives. Methods: Herein, the FE model was developed considering system-level loading conditions (under connected system thermal-mechanical boundary conditions). Thermal-mechanical stress analysis was performed considering thermal stratification and a design-basis reactor loading cycle. Based on the FE model results, the strain residuals, strain amplitudes and resulting fatigue lives of RCS components were predicted. Results: The results show that some of the RCS components can have significantly different strain amplitudes, residual strain, and fatigue lives, despite having similar geometry and material. Higher residual strain can lead to accelerated cyclic hardening of material and the associated effect of EAF. The simulated component-level strain profile (under realistic multi-axial-multi-physics loading cycle) can guide the selection of appropriate test inputs for conducting laboratory-scale EAF tests, which is a focus of future works. Conclusions: Despite similar geometry and material the RCS component can have significantly different strain profiles and resulting fatigue lives. The discussed approach can help to identify and prioritize the RCS components for conducting expensive nondestructive evaluation (NDE) inspections.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Real-Time Dynamic Brake Assessment for Heavy Commercial Vehicle Safety

This paper summarizes initial results and findings of a model developed to determine the braking performance of commercial motor vehicles in motion regardless of brake type or gross weight. Real-world data collected by Oak Ridge National Laboratory for a U.S. Department of Energy study was used to validate the model. Expanding on previous proof-of-concept research showing the linear relationship of brake application pressure and deceleration additional parameters such as elevation were added to the model. Outputs from the model consist of coefficients calculated for every constant pressure braking event from a vehicle that can be used to calculate a deceleration and thus compute a stopping distance for a given scenario. Using brake application pressure profiles derived from the dataset, stopping distances for light and heavy loads of the same vehicle were compared for various speed and road grades. For a constant brake application pressure profile (i.e. the pressure is relatively constant throughout the entire stop) it was shown that the lighter vehicle was able to stop in a shorter distance than the heavier vehicle in most scenarios other than large uphill grades. Significant changes in weight can be observed through the fuel efficiency of the vehicle to determine if the model needs to be calibrated with new or additional braking events. The model was initially developed for tracking brake performance to inform routine maintenance and the ordering of vehicles in a platoon but can be expanded to other connected and automated research areas.

Siekmann, Adam↗

IM3 Data Center Driven Grid Stress Dataset for the U.S. Western Interconnection

This dataset provides projected grid stress and reliability results (including all model inputs and outputs from an open-source grid operations modeling framework - GO), for the Integrated Multisector, Multiscale Modeling (IM3) project, under varying levels of data center demand growth between 2025 and 2035 in the U.S. Western Interconnection. The scenarios and sensitivity experiments are combinations of different data center demand growth rates and energy, weather, population and economic pathways. Data center demand growth projections were sourced from the Electric Power Research Institute (EPRI). The data center demand growth projection names are: Low (3.71% annual data center demand growth) Moderate (5% annual data center demand growth) High (10% annual data center demand growth) Higher (15% annual data center demand growth) Energy, weather, population and economic pathways are informed by two Shared Socioeconomic Pathways (SSP3 and SSP5) and two Representative Concentration Pathways (RCP4.5 and RCP8.5) following the hotter general circulation model (GCM) forcing group from a set of perturbed thermodynamics simulations. The resulting pathway names are: rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 The main scenarios and sensitivity experiments are detailed below. Reference scenario: The projected grid stress and reliability results for the U.S. Western Interconnection from a previous study. This scenario does not consider data center demand growth explicitly. Data center scenario: Building on the reference scenario, this scenario considers various data center growth rates and how they impact the U.S. Western Interconnection. Data center loads are modeled as flat 8760-hr profiles. This scenario does not consider new generation and transmission capacities specifically designed to meet the new data center demands. The related folder is named "flat". Delayed generator retirements sensitivity experiment: Building on the data center scenario, this experiment explores the impact of different levels of natural gas and nuclear generator retirement delays. The resulting scenario names are: (1) postponing 100% nuclear retirements; (2) postponing 100% nuclear and 25% natural gas retirements; (3) postponing only 50% natural gas retirements; (4) postponing 100% nuclear and 50% natural gas retirements; (5) postponing 100% nuclear and 75% natural gas retirements; and (6) postponing 100% nuclear and 100% natural gas retirements. The related folder names are: no_gen_retire_0_gas, no_gen_retire_25_gas, no_gen_retire_50_gas, no_gen_retire_50_gas_only, no_gen_retire_75_gas, and no_gen_retire_100_gas. Demand response through curtailment sensitivity experiment: Building on the data center scenario, this experiment explores the impact of different participation and compensation levels of data center demand response. The resulting scenario names are: (1) 5% demand available for curtailment with 750 $/MWh compensation; (2) 5% demand available for curtailment with 500 $/MWh compensation; (3) 5% demand available for curtailment with 250 $/MWh compensation; (4) 15% demand available for curtailment with 750 $/MWh compensation; (5) 15% demand available for curtailment with 500 $/MWh compensation; and (6) 15% demand available for curtailment with 250 $/MWh compensation. The related folder names are: dr_cost_250_drup_0_drdown_5, dr_cost_250_drup_0_drdown_15, dr_cost_500_drup_0_drdown_5, dr_cost_500_drup_0_drdown_15, dr_cost_750_drup_0_drdown_5, and dr_cost_750_drup_0_drdown_15. Combination of delayed generator retirements and demand response through curtailment sensitivity experiment: The impact of combining postponing 100% nuclear and 25% natural gas retirements with 5% demand available for curtailment with 750 $/MWh compensation is simulated. The related folder is named "dr_cost_750_drup_0_drdown_5_nuc_100_gas_25". Please refer to the README file for a detailed description of the dataset including individual files and references.

Artificial Intelligence↗

Energy management system, method of controlling one or more energy storage devices and control unit for one or more power storage units

Systems, methods and apparatuses are provided for reducing peak energy demand and to smooth intermittent energy profiles from onsite variable energy sources and loads. Some embodiments use system level and device level analysis and optimization to adaptively adjust the operation of a behind the meter energy storage (BMES) to smooth out energy generation variabilities and follow a reference load signal, including at short time resolutions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

MODELS FOR ESTIMATING THE AUTOFRETTAGE PRESSURE AND RESIDUAL STRESSES IN WALLS OF TYPE 2 PRESSURE VESSELS

Autofrettage is a manufacturing process used during fabrication of Type 2 pressure vessels designed for usage at high pressures to enhance the fatigue life. The process locks high compressive residual stresses in the vessel’s liner wall that reduce the maximum and the mean stress during service loading. To achieve a consistent residual stress profile across the wall of the vessel, the choice of autofrettage pressure is critical. Several finite element analyses runs were conducted to estimate the correct autofrettage pressure that is a function of the yield strength of the liner material, the wall thickness, and the outside diameter of the liner for a wrap thickness of 17.06 mm (48 wire layers). From the finite element analyses results, models were developed to estimate the correct autofrettage pressure and the residual stress distribution across the liner wall as a function of the yield strength of the liner material, the wall thickness, and the outside diameter of the liner.

08 HYDROGEN↗

AGC-2 Graphite Preirradiation Data Analysis Report

This report describes the specimen loading order and documents all preirradiation examination material property measurement data for graphite specimens contained within the Second Advanced Graphite Capsule (AGC 2) irradiation capsule. The AGC 2 capsule is the second in six planned irradiation capsules comprising the Advanced Graphite Creep (AGC) test series. The AGC test series is used to irradiate graphite specimens in order to garner quantitative data necessary for predicting the irradiation behavior and operating performance of new nuclear grade graphites. This testing will ascertain the in service behavior of the graphite for pebble bed and prismatic very high temperature reactor designs. Similar to the First Advanced Graphite Capsule (AGC 1) preirradiation examination report, material property tests were conducted on specimens from 18 nuclear grade graphite types. However, AGC 2 tested an increased number of specimens (i.e., 512) prior to loading them into the AGC 2 irradiation assembly. All AGC 2 specimen testing was conducted at Idaho National Laboratory from July 2009 to August 2010. This report also details the specimen loading methodology for graphite specimens inside the AGC 2 irradiation capsule. The AGC 2 capsule design requires “matched pair” creep specimens that have similar dose levels above and below the neutron flux profile mid plane. This provides similar specimens with and without an applied load. Analysis in this document utilizes the neutron flux profile calculated for the AGC 2 capsule design, the capsule dimensions, and the size (i.e., length) of the selected graphite specimens to create a stacking order that produces “matched pairs” of graphite specimens above and below the AGC 2 capsule elevation mid point, thus providing specimens with similar neutron dose levels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Multi-agent voltage control in distribution systems using GAN-DRL-based approach

Active distribution grids can experience voltage fluctuations and violations due to the high penetration of variable distributed energy resources (DERs). These problems might occur because of the uncertain and variable generation natures of these resources, especially solar photovoltaic resources, during panel shadowing scenarios. Volt-VAR control (VVC) is an efficient method that controls the reactive power set-points of the inverters to regulate the voltage of distribution grids. Although several VVC approaches have been proposed recently, the performance of these approaches degrades significantly if behind-the-meter solar generation data are unobservable/missing. Therefore, it is necessary to impute missing/unobservable PV data accurately to be utilized in VVC approaches. Further, this paper proposes a model-free, data-driven, centrally trained, and decentrally executed multi-agent deep reinforcement learning-based VVC architecture to regulate the voltage of distribution networks. A generative adversarial network (GAN) is incorporated to impute the unobservable PV data accurately, which improves the performance of the proposed control architecture. The proposed multi-agent-soft-actor–critic algorithm (MASAC)-based VVC technique utilizes the actual PV dataset as well as the imputed dataset from the GAN framework to learn the optimal coordinated control policy for controlling the optimal reactive power set-points of PV inverters. The effectiveness of the proposed approach is analyzed on a modified IEEE 34-bus test case with added PV inverters. The results are compared and analyzed with a base case model with no VVC and VVC with a local droop control approach, genetic algorithm optimization, and a centralized soft actor–critic-based approach. Moreover, the performance of the proposed approach is compared with that of a multi-agent VVC framework without using the PV generation data and load information as the system state. The results illustrate that the proposed method with more state input improves the voltage profile and reduces the power loss of the network across various loading and PV generation scenarios.

14 SOLAR ENERGY↗

TEMPEST (Thermo-Electric Model for Powering Energy Storage Technologies)

NREL's TEMPEST model combines electrical and thermal modeling for residential-scale battery systems. The model and default parameters are based off of two common commercial residential batteries. Key inputs to the model include house load, temperature of the battery location, and the solar profile. The key output of the TEMPEST model is the battery profile and internal battery temperature. If internal battery temperature exceeds limits, a derating will occur and this will be reflected in the battery profile. In addition to thermal modeling, the TEMPEST model uses realistic operating principals that are common in today's residential batteries. Mainly, the TEMPEST model incorporates "modes" of operation that constrain battery setpoint based on house load, solar output, and state of charge. The TEMPEST model can be used to analyze the effect of battery temperature, deratings, and mode setpoints on utility network loading and customer bills.

Blonsky, Michael↗

Comparison of Probabilistic Forecasts for Predictive Voltage Control

This paper explores predictive cooperative voltage control in distribution systems with highly variable sources such as photovoltaics (PV). The goal is to maintain the voltage profile within the limits despite the fluctuations due to sudden changes in solar power generation. The predictive voltage control method relies on probabilistic solar power and load forecasts to select the optimum Voltage Regulator (VR) taps appropriately. VR taps are selected to minimize the risk of voltage violation. A modified version of the IEEE 123 system is used as the case study. A 100% penetration of solar power is assumed for the distribution system with profiles for solar generation and loads added to the system. Three different probabilistic forecast models (Quantile Regression (QR), Gaussian distribution and volatility forecasting using Generalized Autoregressive Conditional Heteroskedasticity (GARCH)) are explored in this study. The results for the VR taps and Voltage Deviation Index (VDI) are compared to find the most effective forecast model.

Panamtash, Hossein↗

Electromagnetic turbulence simulation of tokamak edge plasma dynamics and divertor heat load during thermal quench

Abstract The edge plasma turbulence and transport dynamics, as well as the divertor power loads during the thermal-quench phase of tokamak disruptions, are numerically investigated with BOUT++’s flux-driven six-field electromagnetic turbulence model. Here, transient yet intense particle and energy sources are applied at the pedestal top to mimic the plasma power drive at the edge induced by a core thermal collapse, which flattens the core temperature profile. Interesting features, such as surging of divertor heat load (up to 50 times) and broadening of heat-flux width (up to four times) on the outer-divertor target plate, are observed in the simulation, in qualitative agreement with experimental observations. The dramatic changes in divertor heat load and width are due to the enhanced plasma turbulence activities inside the separatrix. Two cross-field transport mechanisms, namely, the E × B turbulent convection and the stochastic parallel advection/conduction, are identified to play important roles in this process. First, an elevated edge pressure gradient drives instabilities and subsequent turbulence in the entire pedestal region. The enhanced turbulence not only transports particles and energy radially across the separatrix via the E × B convection, which causes the initial divertor heat-load burst, but it also induces amplified magnetic fluctuation B ˜ . Once themagnetic fluctuation is large enough to break the magnetic flux surface, magnetic flutter effect provides an additional radial transport channel. In the late stage of our simulation, | B ˜ r / B 0 | reaches to 10 −4 level that completely breaks magnetic flux surfaces such that stochastic field lines are directly connecting pedestal top plasma to the divertor target plates or first wall, further contributing to the divertor heat-flux width broadening.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fatigue behavior of fine-grained magnesium under tension-tension loading at 0 °C

Here, this study investigated low-temperature fatigue behavior of fine-grained magnesium through tension–tension fatigue testing at the temperature of 0 °C. The applied stress profiles of fatigue testing were selected to cover a wide range of loading conditions including low, medium, and high loading stresses. Even when the maximum applied stress of fatigue testing was as high as 88% of the ultimate tensile strength of the material, the corresponding fatigue life was long, i.e., 3973 cycles. Deformation accumulation per loading cycle reduced with the progression of fatigue testing for all studied loading conditions. Fatigue life analyses were performed using both Smith-Watson-Topper (SWT) model and Jahed-Varvani energy-based (JV) model. The fatigue life predictions through both models agree well with the experimental data.

36 MATERIALS SCIENCE↗

Thermal and structural analysis of a new WEST reciprocating probe head with Titanium-Zirconium-Molybdenum armour material

The Tore Supra tokamak was transformed into an X-point divertor fusion device in the frame of the WEST (W-for tungsten-Environment in Steady-state Tokamak) project, launched in support of the ITER tungsten divertor strategy. WEST began operation in 2017. A new reciprocating probe head, equipped with a Titanium-Zirconium-Molybdenum (TZM) heat shield, was recently built and operated on WEST during the C9 Campaign in early 2024. TZM was chosen as armour material for its very good mechanical properties between 700 °C and 1400 °C. This material was already extensively used for probe heads and other plasma facing components on the Alcator C-Mod tokamak. Here, this paper presents the design of the new WEST probe head. It is equipped with tungsten filaments that can be heated to emit electrons and provide a direct measurement of the plasma potential in the scrape-off layer, and it is also equipped with a pair of Langmuir probes. The probe plunges vertically into the plasma, reaches its maximum dive depth, then returns to its protected resting position in about 0.25 s. Thermal loads are calculated using as input the thermal properties of TZM and radial profiles of the heat flux measured in the past by other reciprocating probes, and scaled upwards to the expected heat loads in the WEST scrape-off layer. An analytical estimation of Electromagnetic (EM) loads will also be presented, as well as a thermal and structural analysis of the probe for 15 cycles at maximum plunge depth. The probe is observed by an infrared camera. Comparisons between the heat flux deduced by the Langmuir probe and the infrared radiance of the probe housing during plasma exposure are finally presented.

Diagnostic↗