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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Wireless Instrumented RB Experiment Preliminary Design and Analysis

The ability to deploy new nuclear fuels for current or future reactor concepts requires carefully designed experiments to generate data to support fuel qualification. Ideally these experiments would include state of-the-art sensing to maximize the amount of in situ data that can be collected during operation. Furthermore, advanced reactor systems can take advantage of integrated in-core sensing technologies to maximize fuel utilization, reduce unnecessary conservativism in design margins, and improve operator’s understanding of limiting peaking factors. Before any novel sensing technologies can be readily adopted for nuclear applications, they must first demonstrate acceptable performance in test reactors. This report summarizes the preliminary design and analysis of the most highly instrumented irradiation experiment ever performed in the removable beryllium (RB) positions of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). The Wireless Instrumented RB Experiment 2021 (WIRE-21) will test a wide range of sensors including wireless sensors being developed by Westinghouse Electric Company (WEC) that could provide in situ measurements of peak fuel temperatures and fuel rod pressurization due to fission gas release. The ability to wirelessly transmit a signal through the fuel rod’s cladding is critical to improving fuel monitoring capabilities without requiring signal penetrations through the cladding pressure boundary, which would significantly impact fuel fabrication, handling, and operation. Other sensors that will be tested in WIRE-21 include an array of thermocouples, self-powered neutron detectors (SPNDs), and spatially distributed fiber-optic temperature sensors. More generally, WIRE-21 will establish a flexible irradiation vehicle design to allow accelerated, economical testing of advanced sensor technologies while leveraging the extremely high neutron flux that is available in HFIR. This report summarizes the mechanical design for WIRE-21, the experimental test matrix, initial neutronic and thermal design analyses, and the active monitoring and control system enhancements necessary to support testing of advanced sensor technologies. The containment for WIRE-21 is similar to previous RB irradiation vehicles but includes a few modifications, most notably the use of integrated compression seals to pass a larger number of sensor leads through the experiment’s pressure boundary. In addition to the sensor leads, inert gas lines are passed into the experiment to enable active temperature control and the ability to pneumatically actuate a bellows-driven pressure sensor. WIRE-21 is targeting temperatures (300–350°C) and neutron fluence levels (~10 22 n/cm 2 ) relevant to light water reactors (LWRs), but the flexible design of the experiment vehicle allows much higher operating temperatures (>1,100°C). Neutronic calculations determine the neutron flux conditions as well as the nuclear heating within the experiments. These results are used as inputs to detailed thermal finite element calculations, which are required to evaluate the complex, three-dimensional heat transfer that occurs within WEC’s wireless sensor enclosures. Initial results show that the temperatures of the sensors’ enclosures and the metal bellows can be operated near the temperature range of LWR coolants and cladding while simultaneously increasing the temperature of a surrogate fuel material to values in the range of 800–1200°C to simulate centerline fuel temperatures during LWR operation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Current divisions and distributed Joule heating of two-dimensional grid microstructures

This work presents current divisions and distributed Joule heating of two-dimensional (2D) grid microstructures. The current divisions on 2×2, 4×4, and n×n grid microstructures made of the same conductive beams are analyzed theoretically, and Kirchhoff's voltage law (KVL) and Kirchhoff's current law (KCL) are employed to determine the current division factors and directions under different voltage input cases. The equivalent resistances and Joule heating power are therefore derived. 2D 2×2 grid microstructures made of gold (60 nm in thickness) and those made of near-equiatomic NiTi (850 nm in thickness) for various independent voltage input cases are fabricated by electron-beam evaporation and co-sputtering, respectively. The equivalent resistances of these grid microstructures are measured by four-terminal resistance measurement at ambient conditions, which show a good agreement with the theoretical results. Further investigation on the electrical resistivities of evaporated gold layer (4.85 × 10 -8 Ω ∙ m) and co-sputtered NiTi (1.23 × 10 -5 Ω ∙ m) reveals that the influences of scale effect and fabrication process on the resistivity cannot be neglected. As such, it is found to be necessary to consider the materials' resistivity in the fabricated grid microstructures before their electro-thermal analysis.

25 ENERGY STORAGE↗
DOE OSTI2020

A Potts Model parameter study of particle size, Monte Carlo temperature, and “Particle-Assisted Abnormal Grain Growth”

A Potts Model was proposed to account for temperature and particle heterogeneity-dependent Zener Pinning. This was accomplished by relating the random fluctuations of grain boundary position allowed by the Potts Model switching probability at finite simulation temperature to experimentally observed grain growth stagnation behavior. We assume that these fluctuations arise from random fluctuations in the thermodynamic and kinetic properties of the grain boundaries and/or interfaces as they change with temperature. As an application of this model, the grain growth kinetics of U-10 wt. % Mo nuclear fuels were simulated with the input of microstructural images during different heat treatment processes. Simulated average grain growth behavior is in good agreement with experiments.

Frazier, William E.↗
DOE OSTI2026

Towards fully predictive gyrokinetic full- f simulations: validation and triangularity studies in TCV

Designing economical magnetic confinement fusion power plants motivates computational tools that can estimate plasma behavior from engineering parameters without direct reliance on experimental measurement of the plasma profiles. In this work, we present full-f global long-wavelength gyrokinetic simulations of edge and scrape-off layer turbulence in tokamaks that use only magnetic geometry, heating power, and particle inventory as inputs. Unlike many modeling approaches that employ free parameters fitted to experimental data, raising uncertainties when extrapolating to reactor scales. This approach directly simulates turbulence and resulting profiles through gyrokinetics without such empirical adjustments. This is achieved via an adaptive sourcing algorithm in Gkeyll that strictly controls energy injection and emulates particle sourcing due to neutral recycling. We show that the simulated kinetic profiles compare reasonably well with Thomson scattering and Langmuir probe data for Tokamak á Configuration Variable (TCV) discharge #65125, and that the simulations reproduce characteristic features such as blob transport and self-organized electric fields. Applying the same framework to study triangularity effects suggests mechanisms contributing to the improved confinement reported for negative triangularity (NT). Simulations of TCV discharges #65125 and #65130 indicate that NT increases the E x B flow shear (by about 20% in these cases), which correlates with reduced turbulent losses and a modest change in the distribution of power exhaust to the vessel wall. While the physical models contain approximations that can be refined in future work, the predictive capability demonstrated here, evolving multiple profile relaxation times with kinetic electron and ion models in hundreds of GPU hours, indicates the feasibility of using Gkeyll to support design studies of fusion devices.

Hoffmann, Antoine Cyril David [Princeton Plasma Ph↗
DOE OSTI2023

LA100 Equity Strategies. Chapter 6: Universal Access to Safe and Comfortable Home Temperatures

The LA100 Equity Strategies project integrates community guidance with robust research, modeling, and analysis to identify strategy options that can increase equitable outcomes in Los Angeles' clean energy transition. This chapter focuses on housing weatherization and cooling technologies as means to increase access to safe and comfortable home temperatures. Lack of cooling access and use can have severe health impacts on building occupants during heat waves. Specifically, NREL developed and used a residential building stock model to simulate the energy use of 50,000 dwellings representing the diversity of housing types, appliances, climate zones, and household incomes across Los Angeles. We compared a baseline scenario with seven upgrade scenarios. Five scenarios cooled the entire household and featured cooling systems at varying efficiency levels with various improvements to the envelope, roof, and shading, and two scenarios cooled a single room in a household with no prior cooling using either a room air-conditioning or a heat pump system. For each scenario, we evaluated impacts on utility bills, payback periods, and changes in energy burdens, as well as ability to achieve safe and comfortable temperatures. We also examined the effects of building types (multifamily vs. single-family) on indoor air temperatures. Based on the results of modeling, analysis, and community guidance, we identified six short-term and two long-term strategies for improving access to building envelope upgrades and cooling strategies that could save lives and maintain safe home temperatures for Los Angeles' low-income households during heat waves. Research was guided by input from the community engagement process, and associated equity strategies are presented in alignment with that guidance.

air conditioning↗
DOE OSTI2023

LA100 Equity Strategies. Chapter 7: Housing Weatherization and Resilience

The LA100 Equity Strategies project integrates community guidance with robust research, modeling, and analysis to identify strategy options that can increase equitable outcomes in Los Angeles' clean energy transition. This chapter focuses on housing weatherization and access to cooling as means to achieve more equitable resilience to heat waves during unplanned power outages. Specifically, NREL used weather, housing, and socioeconomic data to characterize LA's residential building stock. We?developed a residential building stock model to simulate the energy use of 50,000 dwellings representing the diversity of housing types, appliances, climate zones, and household incomes across Los Angeles. We then simulated and evaluated the impacts of 10 building envelope and cooling upgrades on indoor temperature - a main cause of heat-induced health risks-over a 4-day power outage during a heat wave. We examined occupant exposure to extreme heat and how heat exposure changes with each upgrade across income, tenure (renter/owner status), building type, and disadvantaged community (DAC) status. We also examined upgrade costs and utility bills. Based on the results of our analysis and community guidance, we identified building envelope upgrades and cooling strategies that could save lives and maintain safe home temperatures for LA's low-income households in the event of a planned or unplanned power outage during a summer heat wave. Research was guided by input from the community engagement process, and associated equity strategies are presented in alignment with that guidance.

building envelope↗
DOE OSTI2025

HFIR LEU High Density Silicide Dispersion Optimized Design Neutronics Analyses with PHAME

A high-fidelity neutronics model of the Oak Ridge National Laboratory High Flux Isotope Reactor (HFIR) with the low-enriched uranium (LEU) high-density silicide dispersion Optimized fuel design was updated and analyzed to generate reactor physics-based metrics to support follow-on thermal hydraulic and transient analyses of this design. The Python HFIR Analysis and Measurement Engine (PHAME) was also updated to enhance the automation capabilities of the framework developed and maintained to perform these reactor physics modeling and simulation efforts. The automated framework significantly increases the efficiency and reproducibility to design and thoroughly analyzes HFIR LEU core designs, changes, and uncertainties. Reactor physics metrics evaluated include but are not limited to fuel depletion, cycle length, fission rate density distributions, axial power peaking factors, kinetics data, reactivity coefficients, control element worths, heat deposition rates, and decay heat. These neutronics results provide essential input to follow-on steady state thermal, thermal hydraulic and reactor transient analyses, which are subject of other reports. The Optimized design operates at 95 MW to maintain HFIR’s current highly enriched uranium core performance level at 85 MW.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

A multi-scale time-series dataset of anthropogenic heat from buildings in Los Angeles County

The dataset contains hourly Anthropogenic heat (AH) from buildings in Los Angeles County, based on weather data from 2018. The hourly AH is aggregated at three spatial resolutions: 450m x 450m grid, 12km x 12km grid, and census tract. The AH is broken down into three components: building envelope surface convection, heating, ventilation, and air conditioning (HVAC) system heat release, and zone exfiltration and exhaust air heat loss. The dataset is created with the physics-based EnergyPlus building energy models to calculate individual buildings' AH considering WRF-UCM simulated microclimate conditions. Please refer to the paper "A multi-scale time-series dataset of anthropogenic heat from buildings in Los Angeles County" for more information about the data generation workflow and the data validation procedure. The data set contains two folders: the "output_data" folder holds the simulation results (EP_output and EP_output_csv), building metadata (building_metadata.geojson and building_metadata.csv), aggregated heat emission and energy consumption time-series data (hourly_heat_energy), and geographical data (geo_data) associated with the GEOID referenced in heat and energy consumption data. The "input_data" folder contains the raw data used to generate files in the "output_data" folder as well as data sets used in the validation. The code repository (https://github.com/IMMM-SFA/xu_etal_2022_sdata) holds the processing scripts for data curation, validation, and visualization.

Energy↗
DOE OSTI2022

Machine Learning-based Prediction of Departure from Nucleate Boiling Power for the PSBT Benchmark

Machine Learning (ML) has seen an exponential growth in its applications due to its advanced data driven prediction capabilities. The study presents a data-driven approach as a preliminary attempt to predict the power at which departure from nucleate boiling (DNB) occurs in pressurized water reactors (PWRs) by constructing an advanced ML algorithm that takes outlet pressure, inlet temperature and inlet mass flux as the input features. DNB is a critical heat flux (CHF) phenomenon seen in PWRs. The experimental data from the PWR subchannel and bundle tests (PSBT) benchmark is first used to train an artificial neural network (ANN) to predict the DNB power, which produces a root mean square error (RMSE) of 6.89 kW/m when tested on a blind subset of the PSBT data. Since the PSBT dataset is relatively small to train an accurate ANN, a data augmentation methodology based on generative adversarial networks (GANs) is used to expand the training dataset. By assuming that the real data follows a certain distribution, GANs try to learn that underlying distribution to generate similar synthetic data to augment the database and to improve the predictive capabilities of the ANN. The data generated from GANs are validated using 1-nearest neighbor and kernel maximum mean discrepancy. To further ensure data from GAN is similar to PSBT, the data is tested and filtered out using the sub-channel thermal-hydraulic code CTF. The results indicate that with the addition of 120 data points from GAN the RMSE reduces to 4.84 kW/m showing promising results for future developments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Recrystallization and Grain Growth Simulations for Multiple-Pass Rolling and Annealing of U-10Mo

A simulation model of recrystallization and grain growth has been developed to investigate grain structure evolution during deformation and heat treatment in polycrystalline U-10wt% Mo (U-10Mo) fuel. Experimentally obtained U-10Mo microstructures were used as input for closed loop simulations of multiple rolling, intermediate heating and final annealing process. FEM calculations of deformation and Potts Model simulations of recrystallization and grain growth were used to iteratively inform each subsequent stage of simulation. Furthermore, the model was then applied to predict the grain structure evolution during multiple-pass hot rolling of U-10Mo, and benchmarked against experimentally observed U-10Mo recrystallization behavior. The results showed that our model was able to capture the coupling between deformation and recrystallization as a function of microstructure, including particle stimulated nucleation and recrystallization nucleation on grain boundaries. Additionally, we have achieved reasonable quantitative agreement with U-10Mo recrystallization and grain growth behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Inputs to GCAM-USA: IM3 Phase 2 Experiments

Overview This dataset contains XML input files for the IM3 Phase 2 version of GCAM-USA. The files are organized into two categories: Scenario-specific inputs represent hydroclimate and socioeconomic effects on water availability, heating and cooling degree-hours, and agricultural productivity. They support eight IM3 canonical scenarios: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 Model-improvement inputs extend GCAM-USA v5.3 with updated representations of coal and nuclear power plant retirements, electricity trade among U.S. interconnections, offshore carbon storage costs, and groundwater depletion constraints. Data structure Scenario-specific inputs rcp45_runoff/ and rcp85_runoff/XML files describing water availability by HUC2 basin under the RCP 4.5 and RCP 8.5 scenarios. rcp45_hdcd/ and rcp85_hdcd/XML files containing monthly-day and monthly-night heating and cooling degree-hours at the U.S. state level for different RCP-SSP combinations. rcp45_agyields/ and rcp85_agyields/XML files describing changes in agricultural productivity at the intersection of GCAM regions and HUC2 water basins for different RCP-SSP combinations. rcp45_emissions_pathway/The emissions-constraint XML file used to represent the RCP 4.5 pathway. Model-improvement inputs core_retire/Updates coal-fired power plant retirement schedules based on New England ISO. GCAMUSA_IM3_elec_trade_interconnect.xmlRestricts electricity trade to occur within the ERCOT, WECC, and IE interconnections. nuclear_USA.xmlUpdates the retirement schedules of the Diablo Canyon and Palisades nuclear power plants. high_cost_offshore_carbon.xmlUpdates the assumed cost of offshore carbon storage. water_supply_constrained_gleeson_5pct.xmlReplaces WaterGAP historical groundwater-depletion estimates with data from the Gleeson dataset and limits groundwater extraction to 5% of the available groundwater in each Superwell grid cell. How to use the data This dataset is designed for use with the IM3 version of GCAM-USA. Download or clone GCAM-USA from the IM3 GCAM GitHub repository at https://github.com/IMMM-SFA/gcam-core and check out the gcam-usa-im3 branch. Place the downloaded folder im3scenarios in the gcam-core/input directory while preserving the provided folder structure.

Energy↗
DOE OSTI2024

Utilization of an Advanced Sensor network to determine fuel heating value and Real-Time net unit heat rate during transient operation

Coal-fired utility boilers are being increasingly used as variable electricity generation to resolve the imbalance in the energy market from the expansion of intermittent renewable energy. The frequent transient operation required to meet residual energy demand has created a challenge for coal-fired units to operate efficiently. This work utilizes an advanced sensor network (ASN) to calculate net unit heat rate (NUHR) of a coal-fired boiler in real time through combustion calculations and statistical correlations to provide the tools for optimizing dynamic operation. Real-time heating values that were necessary to determine fuel input energy to calculate accurate NUHR were found using both fundamental and data-driven methods. Real-time NUHR shows distinct shifts that reflect changes in process conditions that will improve the ability to optimize transient operation. Data-driven heating value correlations had 24% lower root mean square error (RMSE) than the fundamental combustion calculation approach when compared to daily retrospective proximate analysis. Furthermore, the data-driven method RMSE improved by 7% with the inclusion of ASN data. Future work is to validate by comparing unit performance with and without the inclusion of NUHR as a control parameter for the dynamic neural network.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Steam generator model design parameter sensitivity study for small modular reactor system

Here, this study focuses on design parameter sensitivity studies pertaining to several Once-Through Steam Generator (OTSG) model cases both with and without a riser using python and advanced risk assessment and optimization tool, i.e. Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), to support a Small Modular Reactor (SMR) system. The presented Steam Generator (SG) python-based model is a mathematical representation of a steam-generating unit for a Pressurized Water Reactor (PWR)-type SMR system, including fluid flow and heat transfer equations, models, and correlations. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system, such as the Heat Transfer Coefficient (HTC), Reynolds number, Nusselt number, and heat transfer performance. Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in the input parameters. By using RAVEN, detailed design parametric sensitivity studies. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (i.e., ±1%, ±5% and ±10 % relative changes) for 600 samples. The analysis results give valuable insights into SG system performance, and provide justification for further research and development such as optimized sensor placement, design verification, validation, and optimization.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

An Efficient Annual-Performance Model of a Geothermal Network for Improved System Design, Operation, and Control: Preprint

Geothermal district energy systems (DES), and specifically geothermal networks, provide a viable solution for decarbonizing residential and commercial heating and cooling loads. District energy systems of all kinds enable a thermal resource with a relatively high capital cost (such as a geothermal borehole field) to be shared among a large number of users. While district heating and cooling has been studied for many years, geothermal networks, fifth generation DES that utilize water-source heat pumps and an ambient temperature loop to meet heating and cooling loads, have not been implemented extensively and thus require additional technical and economic optimization to obtain maximum benefits. This paper presents a newly developed reduced-order model that captures the flow of energy within the network, including the commercial and residential users' electrical usage, at an hourly rate over a year. The model includes building loads, heat pumps, borehole fields, and auxiliary heat/cool input, all connected with an ambient-temperature thermal loop model. In the model, operational control is possible for the borehole fields, circulation pump, and auxiliary system. For a given system, the model can output the complete state parameters for each component, the thermal loop, and the collective system, such as flow rate over time, average thermal loop temperature over time, and total electricity usage. The model can also be used to optimize the system control for maximizing system efficiency or minimizing system operational cost. For example, one initial assessment of the borehole controller for an example system showed that a controller with on/off operation of the borehole field reduces annual electrical usage by 33%, compared with continuous operation mode. Hence, the model can assist in optimizing a given system's operation to get the most value out of a geothermal network installation. Future work will consider the model's application to a demonstration project, including the model validation against operational data and system operation optimization.

ambient-temperature loop↗
DOE OSTI2020

10 MWE CDCL Large Pilot Plant – pre-FEED Study

Coal Direct Chemical Looping (CDCL) is an advanced oxy-combustion technology that has the potential to substantially reduce the energy penalty and the cost of electricity (COE) for coal-fired power generation with CO₂ capture. The Babcock & Wilcox Company (B&W) and The Ohio State University (OSU) have been collaborating on the development of an iron oxide oxygen-carrier based chemical looping technology for clean power generation with inherent carbon capture. In this process, coal is dried and pulverized prior to being transported into a moving-bed reducer. In the reducer, coal reacts with the oxygen-carrier particles, forming combustion byproducts, predominantly CO₂ and H₂O, while reducing the iron oxide oxidation state from Fe₂O₃ to a mixture of FeO and Fe. The reduced state particles are then transported to a combustor reactor and re-oxidized with air. Following the oxidation, the oxygen-carrier particles are regenerated, and a large amount of heat is released for steam production. The produced steam is sent to a turbine for electricity generation. Meanwhile, the CO₂–rich stream leaving the reducer is cooled, cleaned, and compressed for subsequent pipeline transportation and sequestration. By combining air separation and fuel conversion into a single system, the CDCL technology enables the intensification of oxy-combustion processes by eliminating the energy and cost intensive cryogenic air separation unit and thereby results in higher overall plant efficiencies and lower COE’s. The use of a moving-bed reducer results in high conversions of volatile hydrocarbons and high CO₂ purity, which reduces the cost of downstream CO₂ purification for sequestration or utilization. The Babcock & Wilcox Company in collaboration with The Ohio State University, Johnson & Matthey, The Electric Power Research Institute, and Dover Light & Power completed a Preliminary Front-End Engineering and Design (Pre-FEED) study of a 10 MWe coal-direct chemical looping (CDCL) pilot plant. The planned system is a modular 10 MWe CDCL large pilot facility consisting in 4 modules of 2.5 MWe each, working in parallel and to be hosted within the current structure at the City of Dover’s Municipal Power Plant. The CDCL system can achieve auto-thermal operation and includes a sub-critical steam cycle for power generation. The pilot system was designed to demonstrate full commercial operation at a reduced scale. The coal distribution per plan area is a representative slice of larger commercial arrangements. The system includes a CO₂ recycle system, but it does not include a compression system. The large pilot includes all the environmental control equipment and oxygen carrier and ash handling systems. As part of the project, the Team performed laboratory testing and carried out multiple pilot test campaigns to obtain design and performance information at the 250 kWth CDCL pilot facility at the Babcock & Wilcox Company’s Research Center. The Team demonstrated sustained operations at designed coal inputs, high coal conversion, high CO₂ purity, heat generation on the combustor, low carbon carryover between reactors and low particle attrition. Emissions generated in the reducer reactor were identified as SO₂ and NO x . The commercial manufacturing cost of oxygen carrier particle was evaluated by JM. A particle manufacturing report was generated and submitted to the DOE. Based on the results from the pilot tests and the pre-FEED design efforts, a techno-economic analysis was performed. The study shows that the CDCL process is a promising carbon-friendly technology capable of producing electricity with high efficiency. The estimated COE of the supercritical CDCL plant is $83.3 / MWh, which meets DOE’s target of less than 30% increase in COE when compared to a supercritical PC plant without CO₂ capture. This is the lowest among the existing carbon capture technologies (post-combustion and oxy-combustion) for fossil fuel power plant. CDCL is evaluated to be the most promising technology for carbon capture from the economic aspect.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

A hybrid method to evaluate the life cycle climate performance of heat pumps

Heat pumps have a significant impact on the climate, and numerous studies exist discussing the environmental impact of heat pumps quantitatively. Life Cycle Climate Performance (LCCP) is a widely accepted metric and can evaluate the carbon footprint of heat pumps from cradle to grave. LCCP calculation typically requires inputs like annual energy consumption, the material used, refrigerant type, and charge level, which are usually the intermediate or final results from heat pump simulation tools. Thus, a platform linking the heat pump simulation software, local weather conditions, and LCCP evaluation tool can simplify the heat pump design process, especially for complicated systems. This paper presents an LCCP evaluation tool accessing the outputs from the DOE Heat Pump Design Model and the building loads and temperature bin data from AHRI standard 210/240. As for case studies, this paper investigates the LCCP values and life cycle electricity costs (LCEC) of a given cooling-based heat pump with R410A in five typical US cities. In conclusion, this cooling-based heat pump has the highest LCCP value at Chicago and lowest LCCP value at Seattle. In contrast, the heat pump has the highest LCEC at Seattle and the lowest LCEC at Miami. As a future work, a more comprehensive carbon emission and cost analysis of heat pump systems will be conducted through all major cities around the world.

Shen, Bo↗
DOE OSTI2022

High gradient off-axis coupled C-band Cu and CuAg accelerating structures

Here, we report the high gradient testing results of two single-cell off-axis coupled standing wave accelerating structures. Two brazed standing wave off-axis coupled structures with the same geometry were tested: one made of pure copper (Cu) and one made of a copper–silver (CuAg) alloy with a silver concentration of 0.08%. A peak surface electric field of 450 MV/m was achieved in the CuAg structure for a klystron input power of 14.5 MW and a 1 μs pulse length, which was 25% higher than the peak surface electric field achieved in the Cu structure. The superb high gradient performance was achieved because of the two major optimizations in the cavity's geometry: (1) the shunt impedance of the cavity was maximized for a peak surface electric field to accelerating gradient ratio of ~2 for a fully relativistic particle, and (2) the peak magnetic field enhancement due to the input coupler was minimized to limit pulse heating. These tests allow us to conclude that C-band accelerating structures can operate at peak fields similar to those at higher frequencies while providing a larger beam iris for improved beam transport.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗