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At least 1,027 records · Page 57

Multi-Fidelity Scheme for Accelerating 4D Finite Element Analysis for Mircoreactors

Next-generation microreactors are currently being designed to be operated terrestrial and extraterrestrial for remote surface power production. These systems will provide an alternative source of carbon-free energy that is versatile and can be utilized for various applications. These applications of microreactors have prompted the usage of high-fidelity unstructured finite element (FE) based approaches to provide time-dependent solutions for multiple physics fields. Computing these high-fidelity (4-D) solutions for multiple design iterations, physics fields, and transient events requires an immense computational cost. These high-fidelity solutions are computational expensive and the cost can be reduced through the implementation of less accurate low-fidelity solutions. Unlike the current fleet of commercial nuclear reactors, these next-gen systems present challenges due to the material and physical limitations required. Due to these constraints, the brute force technique of parameterizing important system characteristics determines whether a design meets the project objective. A system such as a nuclear reactor could have thousands of design parameters that affect system performance. In order to analyze the entire parameter space of such a complex system would require millions of CPU hours and countless design iterations. This costly approach is not practical due to regulatory and budget limitations. In this proposal, an approach that utilizes hybrid high-fidelity and low-fidelity FE models to reduce the computational cost of evaluating these applications in 4-D will be presented. The accuracy of the high-fidelity model and the computational efficiency of the low-fidelity model are taken advantage of to produce a solution that closely resembles the full order high-fidelity solution. By utilizing an unconverged coarse FE mesh, operation limits such as temperature, structural loading, etc., can be evaluated in an accelerated fashion and then can be spatially interpolated onto a finer mesh. The resulting error arising from the coarse mesh can be mitigated with a discrepancy function that actively quantifies and corrects the error in the coarse solution. This discrepancy function can be periodically updated with high-fidelity calculations across the temporal domain thus requiring less iterations on the fine mesh. As a result, the computational cost can be reduced for the evaluation and design iteration of microreactors. The proposal for this research contains three sections: Section 2 provides a literature review, Section 3 outlines the methodology for the proposed multi-fidelity scheme, and Section 4 displays preliminary results of the proposed research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Community College Energy Code Training Program

The U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) funded a series of research and training programs under the Advanced Building Construction with Energy Efficient Technologies and Practices (ABC) initiative. The aim is to develop new training programs to support the development of a skilled workforce in the building energy efficiency industry. In response, the University of Illinois Smart Energy Design Assistance Center (SEDAC), in collaboration with State Energy Offices in Illinois, Hawaii, and Nevada, developed the Community College Energy Code Training Program. The program is designed to prepare a new generation of energy-literate professionals that understand energy efficiency and its relation to energy codes for new construction and existing buildings through: a) the development of a curriculum and innovative pedagogical materials, b) dissemination through a national network of state energy offices: c) outreach targeting Community College students and instructors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Field Validation of Electrocoagulation Treatment for Oily Wastewater at Cleveland-Cliffs Steel Mill in Cleveland, OH

The Industrial Technology Validation (ITV) program aims to identify and demonstrate the performance of new, emerging, and underutilized technologies in the industrial sector to help inform decisions towards accelerating commercialization and deployment. This initiative aims to identify, validate, and showcase new, emerging, and underutilized technologies in the industrial sector to expedite their commercialization and widespread deployment. By conducting thorough validations and demonstrating the efficacy of these technologies, the ITV program facilitates informed decision-making among industry stakeholders, contributing to the transition towards more sustainable and efficient industrial processes. This ITV demonstration involved the testing of an electrocoagulation (EC) treatment system at a steel plant in Ohio. The system was designed to treat oily wastewater generated from cold rolling operations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Project 1: COLLECTS Project and Project 2: M&V for Saputo Cheese Project: Cooperative Research and Development (Final Report)

Project 1: Combined Power's Hyperlight Energy and NLR will collaborate on the DOE Concentrating Optics for Lower Levelized Energy CosTS (COLLECTS) project, DE-FOA-0001268. COLLECTS funding opportunity announcement (FOA) seeks to further concentrated solar power (CSP) system technologies by soliciting disruptive, transformative projects for the concentrating solar collectors in the CSP plant. These innovative projects will seek to surpass the targets set out in the SunShot Vision Study, enabling CSP to be cost-competitive with conventional forms of electric power generation. Projects will target the design and manufacturing of novel solar collectors with the ability to significantly reduce the solar field contribution to the overall levelized cost of energy (LCOE) of the CSP plant, and which have not been previously specifically targeted by CSP FOAs. Project 2: Hyperlight will perform measurement and verification (M&V) of Green House Gases and NLR will evaluate energy consumption reduction.

14 SOLAR ENERGY↗

Thermal Compton Scattering of Electron Beams on Blackbody Photons: A Monte Carlo Event Generator for Multi-Turn Tracking at the Electron-Ion Collider

Compton scattering of ultra-relativistic electrons on thermal (blackbody) photons is typically a subdominant process in electron storage rings, but at sufficiently high electron energy and low residual gas pressure it can become competitive with beam-gas scattering and contribute to dis tributed losses and backgrounds. We present a self-contained Monte Carlo event generator for thermal Compton scattering designed for integration into multi-turn tracking workflows. The im plementation follows H. Burkhardt’s proposal method: trial scattering angles are sampled from the Thomson differential cross section and accepted/rejected using the Klein-Nishina to Thomson ratio, yielding the correct Compton spectrum while retaining simple absolute-rate normalization. Ther mal photon energies are sampled from the blackbody photon-number spectrum via an exact mixture representation.

43 PARTICLE ACCELERATORS↗

Reducing the Cost of Fatigue Crack Growth Testing for Storage Vessel Steels in Hydrogen Gas

Hydrogen storage pressure vessels are designed against fatigue crack growth, and the ASME Boiler and Pressure Vessel Code requires the fatigue crack growth rate (da/dN) vs. stress-intensity factor range (ΔK) relationship of the construction steel to be measured directly in hydrogen gas. These measurements are notoriously slow and expensive: the cyclic loading frequencies prescribed by standards (often 0.1 Hz) are two or more orders of magnitude below those for conventional fatigue testing, individual tests run for days to weeks, and the high-pressure test-chamber set-up imposes a significant per-specimen labor cost. Due to these time and cost constraints, near-threshold data—the regime most valuable for extending design fatigue life—are rarely generated for ferritic storage vessel steels in hydrogen gas.

08 HYDROGEN↗

Event Selection at the DUNE Near Detector

The Deep Underground Neutrino Experiment (DUNE) is a next generation long-baseline experiment designed with a primary goal of providing definitive measurements of the neutrino mass ordering and the Charge Parity (CP)-violating phase. A key component in reaching these goals is the DUNE Near Detector (ND) complex, placed 574 m from the beam target, and tasked with characterising the neutrino beam and constraining systematic uncertainties before oscillation effects occur. We will present primary findings from the development of an event selection for $\nu_\mu$ CC interactions within the ND liquid argon time projection chamber (ND-LAr). These findings will include a discussion of the importance of defining metrics, such as efficiency and purity, such that we can meet the required sensitivity for DUNE's physics measurements.

Sabater Andres, Eva [Sussex U.] (ORCID:00090001748↗

Integrating Carbon Capture, Utilization, & Sequestration into Chemical Pulp Mills

The U.S. pulp and paper industry presents a unique and largely untapped opportunity for large- scale carbon dioxide removal (CDR). Unlike most industrial sectors, pulp mills rely heavily on biomass, meaning that much of their carbon emissions originate from atmospheric CO₂ that was recently captured by plants. If this biogenic CO₂ can be captured and permanently stored, pulp mills can be transformed from carbon emitters into net carbon removal facilities. This project was motivated by that opportunity and aimed to develop and evaluate integrated, low-cost strategies for capturing, utilizing, and sequestering CO₂ within existing chemical pulping operations. The scope of this work focused on four complementary innovations designed to integrate seamlessly into kraft pulp mill infrastructure: (1) in situ CO₂ capture within the recovery cycle, (2) oxy-fuel retrofitting of the rotary lime kiln to produce a high-purity CO₂ stream, (3) ex situ CO₂ capture and mineralization using pulp mill residues (dregs, grits, and lime mud), and (4) beneficial reuse of these residues as mineral carbonate fertilizers. The project combined process modeling, laboratory experimentation, life cycle assessment (LCA), and field trials to evaluate the technical feasibility, economic viability, and environmental impact of these approaches. The results demonstrate that pulp mills can serve as effective platforms for carbon removal when equipped with integrated carbon capture systems. Process modeling showed that combining sodium spiking with oxy-fuel calcination significantly enhances CO₂ capture efficiency while reducing costs by up to 31% compared to conventional configurations. Experimental work further revealed that calcination behavior in high-CO₂ environments differs substantially from traditional systems, leading to the development of a new kinetic model that predicts reaction rates under these conditions. This model provides essential design guidance for next-generation decarbonized lime kilns. In parallel, the project demonstrated that alkaline mineral residues generated during pulping operations can be repurposed as a sustainable alternative to agricultural lime. Across a wide range of soils in the southeastern United States, these materials performed equivalently to commercial lime in adjusting soil pH while offering lower greenhouse gas emissions and reduced cost. Field and greenhouse studies confirmed that crop and tree growth responses were comparable, supporting their viability as a drop-in replacement. This co-product pathway provides a practical utilization strategy that offsets costs and improves overall system economics. A major contribution of this project is the first comprehensive life cycle assessment of carbon removal in pulp and paper systems across multiple system boundaries. Results show that retrofitted mills can achieve carbon removal efficiencies ranging from 12% to 92%, depending on how the system is defined. This finding highlights a critical issue in carbon accounting: reported performance is highly sensitive to methodological choices. By explicitly quantifying these differences, this work provides valuable guidance for policymakers, carbon registries, and project developers working to standardize carbon removal metrics. From a commercialization perspective, the technologies investigated in this project are well- aligned with existing industrial infrastructure, minimizing the need for entirely new facilities. 3 DE-EE0009413 Industry engagement throughout the project—including collaboration with pulp and paper companies, equipment manufacturers, and carbon removal developers—has accelerated the transition from research to deployment. Notably, a commercial developer is actively pursuing carbon capture projects at pulp mills in the southeastern United States and has cited this research as a contributing foundation. The emergence of voluntary carbon markets and long-term offtake agreements further strengthens the business case for implementation. The broader public benefits of this work are significant. By enabling large-scale carbon removal using existing industrial systems, this approach offers a near-term pathway to reduce atmospheric CO₂ concentrations while supporting domestic manufacturing and rural economies. The reuse of industrial residues as fertilizers reduces reliance on mined materials, lowers costs for farmers, and decreases environmental impacts associated with conventional lime production. In addition, the project has supported workforce development by training graduate students and researchers in carbon capture technologies, helping to build capacity in a critical area of national interest. In conclusion, this project demonstrates that integrated carbon capture, utilization, and sequestration in pulp mills is both technically feasible and economically promising. By combining process innovation, experimental validation, and systems-level analysis, the work advances the understanding of how biomass-based industries can contribute to climate mitigation. The findings provide a strong foundation for commercial deployment and offer a scalable solution for transforming a major U.S. industry into a source of durable carbon removal.

09 BIOMASS FUELS↗

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence P - Raw Data

Sequence P: Wake Flow Visualization, Upwind (P) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 15 m/s. Yaw angles of 0° to –60° were achieved. The blade tip pitch was 3°. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. The aluminum blade tip designed to contain a smoke generator was installed, and counterweights were installed in the non-instrumented blade tip to compensate. The turbine was positioned at the appropriate yaw angle, and the smoke generator was ignited remotely. The campaign duration was 3 minutes for all tests except P1000000, which was 2 minutes. The file name convention was the standard format except for P10000A0, which indicated a 3° pitch angle. File P1000000 used a 12° pitch angle. After these two campaigns were collected, it was determined that all subsequent data should be collected with a 3° pitch angle. Pressure data were not acquired during this sequence, so all associated data values were flagged as not applicable by setting the measured values in the data file to 0.000 Pa. Corresponding pressure data are available from Sequence H for the 3° pitch angle test points. Flow visualization data obtained from wall- and ceiling-mounted video cameras were recorded to videotape. The camera locations and calibration procedures are described in Appendix J.

17 WIND ENERGY↗

Advances in Energy Hybridization for Resilient Supply: A Sustainable Approach to the Growing World Demand

Energy poverty, defined as a lack of access to reliable electricity and reliance on traditional biomass resources for cooking, affects over a billion people daily. The World Health Organization estimates that household air pollution from inefficient stoves causes more premature deaths than malaria, tuberculosis, and HIV/AIDS. Increasing demand for energy has led to dramatic increases in emissions. The need for reliable electricity and limiting emissions drives research on Resilient Hybrid Energy Systems (RHESs), which provide cleaner energy through combining wind, solar, and biomass energy with traditional fossil energy, increasing production efficiency and reliability and reducing generating costs and emissions. Microgrids have been shown as an efficient means of implementing RHESs, with some focused mainly on reducing the environmental impact of electric power generation. The technical challenges of designing, implementing, and applying microgrids involve conducting a cradle-to-grave Life Cycle Analysis (LCA) to evaluate these systems’ environmental and economic performance under diverse operating conditions to evaluate resiliency. A sample RHES was developed and used to demonstrate the implementation in rural applications, where the system can provide reliable electricity for heating, cooling, lighting, and pumping clean water. The model and findings can be utilized by other regions around the globe facing similar challenges.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Flexing the Limits of Land-Based Wind Turbine Rotor Growth

The Big Adaptive Rotor (BAR) project aims to design and enable the next generation of land-based wind turbines with 206-meter (m) rotors, which will increase capacity factors by 10% or more over a typical land-based turbine. High-energy-capture turbines have many advantages, but the length and width of larger turbine blades to enable these machines creates transportation challenges that must be overcome to make true on the adage, bigger is better.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

Flexing the Limits of Land-Based Wind Turbine Rotor Growth

The Big Adaptive Rotor (BAR) project works to design and enable the next generation of land-based wind turbines with rotors that stretch 206 meters (m) in diameter, which will increase capacity factors by 10% or more over a typical land-based turbine. These high-energy-capture turbines have lower specific-power ratings, meaning they have larger rotors relative to the size of their generator, which helps them capture more wind and perform better at lower wind speeds, thereby increasing the turbine capacity factor. High-energy-capture turbines with larger rotors have many advantages, but the length and width of their blades creates transportation challenges that must be overcome to make true on the adage, bigger is better.

wind, big, adaptive, rotor↗

BETO 2021 Peer Review - Electrocatalytic CO2 Utilization

The goal of the ChemCatBio DataHub project is to accelerate the catalyst and process development cycle by developing transformational tools for prediction and collaboration in catalyst R&D. The project is currently focused on the development of the Catalyst Property Database (CPD), a free and public resource released in September 2020. The CPD was designed to advance the state of the art for application of computational data. When computational data, such as computed reaction energetics, is used in catalyst design, it is almost always generated by the researchers seeking to use it, even if similar data has been published previously. One barrier to data reuse that results in this duplication of effort is the difficult process of finding and applying published data, which can be slow, error-prone, and manual. The CPD seeks to overcome these challenges by creating a centralized, searchable database of quality catalyst property data. At present, the CPD contains computed adsorption energies for intermediates along catalytic pathways. During FY21 and FY22, development of the CPD continues with a focus on external users and meeting their requirements. A batch upload capability, training and curation procedures, user interviews, and a demonstration of the CPD's utility in accelerating catalyst research are planned. Overall, the Data Hub project and CPD aim to reduce the time and cost of catalyst research by harnessing the power of data in catalyst discovery.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

BETO 2021 Peer Review - ChemCatBio Data Hub 2.6.2.500

The goal of the ChemCatBio DataHub project is to accelerate the catalyst and process development cycle by developing transformational tools for prediction and collaboration in catalyst R&D. The project is currently focused on the development of the Catalyst Property Database (CPD), a free and public resource released in September 2020. The CPD was designed in response to the observation that when data, such as computed reaction energetics, is used in catalyst design, it is almost always generated by the researchers seeking to use it, even if similar data has been published previously. One barrier to data reuse that results in this duplication of effort is the difficult process of finding and applying published data, which can be slow, error-prone, and manual. The CPD seeks to overcome these challenges by creating a centralized, searchable database of quality catalyst property data. At present, the CPD contains computed adsorption energies for intermediates along catalytic pathways. During FY21 and FY22, development of the CPD continues with a focus on external users and meeting their requirements. A batch upload capability, training and curation procedures, user interviews, and a demonstration of the CPD's utility in accelerating catalyst research are planned. Overall, the Data Hub project and CPD aim to reduce the time and cost of catalyst research by harnessing the power of data in catalyst discovery.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Hybrid Heat Pump Controls: Conventional Dual Fuel versus Seamlessly Fuel Flexible Heat Pump

This paper compares the performance of a novel seamlessly fuel flexible heat pump (SFFHP) and conventional dual fuel heat pump (DFHP) for space heating. The conventional dual fuel systems either run on the gas furnace or electric heat pump at any given moment, as a comparison, the proposed seamlessly fuel flexible heat pump simultaneously consumes gas and electricity by continuously optimizing the proportion of each. The process air flows across the heat pump condenser first and then flows across the furnace coil, therefore, the heat pump temperature lift is reduced. SFFHP delivers energy savings by allowing each subsystem, i.e., gas furnace and electric heat pump, to operate where it performs best.For DFHP, two operation control strategies, i.e., non-restricted control and restricted control, are available on market. For the non-restricted mode, the thermostat has a switching temperature-programmed according to the balancing point of heating load and capacity curve. Heat pump operates above the switching temperature, while the furnace takes over under the switching temperature. For the restricted control, the compressor of a heat pump is disabled below a predefined lockout outdoor temperature to let the furnace take over. For SFFHP, a model predictive control strategy is developed to continuously adjust the capacities of the electric heat pump and gas furnace based on the foreseen weather data, utility price signals, and marginal grid emission signals with the goal of minimizing the utility cost and CO2 emission while guaranteeing comfort requirements.In this paper, DFHP and SFFHP are simulated using high-fidelity heat pump performance curves generated from DOE/ORNL heat pump design model. Performance comparison of DFHP and SFFHP during 2019-2020 heating season in Los Angeles shows that SFFHP with model predictive control achieves 23% utility cost reduction and 17 % CO2 emission reduction. Case studies demonstrate that SFFHP can deliver significant reductions in peak demand, utility cost, and CO2 emission. As a result, SFFHP can deliver superior benefits for utility cost reduction and CO2 emission reduction over conventional dual fuel heat pump.

Li, Zhenning↗

Redox-flow batteries employing oligomeric organic active materials and size-selective microporous polymer membranes

Intermittent energy sources, including solar and wind, require scalable, low-cost, multi-hour energy storage solutions to be effectively incorporated into the grid. Redox-flow batteries offer a solution, but suffer from rapid capacity fade and low Coulombic efficiency due to the high permeability of redox-active species across the battery's membrane. Here we show that active-species crossover can be arrested by scaling the membrane's pore size to molecular dimensions and in turn increasing the size of the active material to be above the membrane's pore-size exclusion limit. When oligomeric redox-active organic molecules were paired with microporous polymer membranes, the rate of active-material crossover was either completely blocked or slowed more than 9,000-fold compared to traditional separators at minimal cost to ionic conductivity. In the case of the latter, this corresponds to an absolute rate of ROM crossover of less than 3 μmol cm−2 day−1 (for a 1.0 M concentration gradient), which exceeds performance targets recently set forth by the battery industry. This strategy was generalizable to both high and low-potential ROMs in a variety of electrolytes, highlighting the importance of macromolecular design in implementing next-generation redox-flow batteries.

Helms, Brett A.↗

Optimum Operation of Microgrid Systems that Employ PV Solar and Battery Systems

On a global scale, over 1.3 billion lack access to electricity (85% in rural areas), and approximately 2.8 billion people rely on traditional biomass for cooking. The World Health Organization estimates that household air pollution from inefficient stoves causes more premature deaths than malaria, tuberculosis, and HIV/AIDS. Increasing demand for energy has led to dramatic increases in emissions. The need for reliable electricity and limiting emissions drives research on Resilient Hybrid Energy Systems (RHESs), which provide cleaner energy by combining wind, solar, and biomass energy with traditional fossil energy, increasing production efficiency and reliability and reducing generating costs and emissions. Microgrids have been shown as an efficient means of implementing RHESs, with some focused mainly on reducing the environmental impact of electric power generation. The technical challenges of designing, implementing, and applying microgrids involve conducting a cradle-to-grave Life Cycle Analysis (LCA) to evaluate these systems’ environmental and economic performance under diverse operating conditions to evaluate resiliency. A sample RHES was developed and used to demonstrate the implementation in rural applications, where the system can provide reliable electricity for heating, cooling, lighting, and pumping clean water. The model and findings can be utilized by other regions around the globe facing similar challenges.

Nagapurkar, Prashant↗

The Role of Snowmelt Temporal Pattern in Flood Estimation for a Small Snow‐Dominated Basin in the Sierra Nevada

Abstract Prior research confirmed the substantial bias from using precipitation‐based intensity‐duration‐frequency curves (PREC‐IDF) in design flood estimates and proposed next‐generation IDF curves (NG‐IDF) that represent both rainfall and snow processes in runoff generation. This study improves the NG‐IDF technology for a snow‐dominated test basin in the Sierra Nevada. A well‐validated physics‐based hydrologic model, the Distributed Hydrology Soil Vegetation Model (DHSVM), is used to continuously simulate snowmelt and streamflow that are used as benchmark data sets to systematically assess the NG‐IDF technology. We find that, for the studied small snow‐dominated basin, the use of standard rainfall hyetographs in the NG‐IDF technology leads to substantial underestimation of design floods. Thus, we propose probabilistic hyetographs that can represent unique patterns of events with different underlying mechanisms. For the test basin where flooding events are generated entirely by snowmelt, we develop a hyetograph that characterizes snowmelt temporal patterns, which greatly improves the performance of NG‐IDF technology in design flood estimates. In contrast to the standard rainfall hyetographs characterized by a symmetrically peaked, bell‐shaped curve, the snowmelt hyetograph displays a more rapid rise (i.e., greater intensity) and a distinct diurnal pattern influenced by solar energy input. The results also show that the uncertainty of hyetography plays an important role in design flood estimation and can have important implications for future flood projections.

54 ENVIRONMENTAL SCIENCES↗