Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Fractional operators”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Fed-DeepONet: Stochastic Gradient-Based Federated Training of Deep Operator Networks

The Deep Operator Network (DeepONet) framework is a different class of neural network architecture that one trains to learn nonlinear operators, i.e., mappings between infinite-dimensional spaces. Traditionally, DeepONets are trained using a centralized strategy that requires transferring the training data to a centralized location. Such a strategy, however, limits our ability to secure data privacy or use high-performance distributed/parallel computing platforms. To alleviate such limitations, in this paper, we study the federated training of DeepONets for the first time. That is, we develop a framework, which we refer to as Fed-DeepONet, that allows multiple clients to train DeepONets collaboratively under the coordination of a centralized server. To achieve Fed-DeepONets, we propose an efficient stochastic gradient-based algorithm that enables the distributed optimization of the DeepONet parameters by averaging first-order estimates of the DeepONet loss gradient. Then, to accelerate the training convergence of Fed-DeepONets, we propose a moment-enhanced (i.e., adaptive) stochastic gradient-based strategy. Finally, we verify the performance of Fed-DeepONet by learning, for different configurations of the number of clients and fractions of available clients, (i) the solution operator of a gravity pendulum and (ii) the dynamic response of a parametric library of pendulums.

Moya, Christian↗
DOE OSTI2026

Cryogenics and purification systems of the ICARUS T600 detector installation at Fermilab

This paper describes the cryogenic and purification systems of the ICARUS T600 detector in its present implementation at the Fermi National Laboratory, Illinois, U.S.A. The ICARUS T600 detector is made of four large Time Projection Chambers, installed in two separate containers of about 275 m 3 each. The detector uses liquid argon both as target and as active medium. For the correct operation of the detector, the liquid argon must be kept in very stable thermal conditions and the contamination of electronegative impurities must be consistently kept at the level of small fractions of parts per billion. The detector was previously operated in Italy, at the INFN Gran Sasso Underground Laboratory (LNGS), in a three-year run on the CERN to LNGS Long Baseline Neutrino Beam. For its operation on the Booster and NuMI neutrino beams at Fermilab, for the search of sterile neutrinos and measurements of neutrino-argon cross sections, the detector was moved from Gran Sasso to CERN for the upgrades required for operation at shallow depth with high intensity neutrino beams. The liquid argon containers, the thermal insulation and all the cryogenic equipment have been completely re-designed and rebuilt, following the schemes of the previous installation in Gran Sasso. The detector and all the equipment have been transported to Fermilab, where they have been installed, tested and recently put into operation. The work described in this paper has been conducted as a joint responsibility of CERN and Fermilab with the supervision provided by the ICARUS Collaboration. Design, installation, testing, commissioning and operation are the result of a common effort of CERN, Fermilab and INFN groups.

Cryogenic detectors↗
DOE OSTI2024

Mechanical structure of the nucleon and the baryon octet: twist-2 case

We investigate the gravitational form factors (GFFs) of the nucleon and the baryon octet, decomposed into their flavor components, utilizing a pion mean-field approach grounded in the large N c limit of Quantum Chromodynamics (QCD). Our focus is on the contributions from the twist-2 operators to the flavor-triplet and octet GFFs, and we decompose the mass, angular momentum, and D-term form factors of the nucleon into their respective flavors. The strange quark contributions are found to be relatively mild for the mass and angular momentum form factors, while providing significant corrections to the D-term form factor. In the course of examining the flavor decomposition of the GFFs, we uncover that the effects of twist-4 operators play a crucial role. While the gluonic contributions are suppressed by the packing fraction of the instanton vacuum in the twist-2 case, contributions from twist-4 operators are of order unity, necessitating its explicit consideration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Steam caps in geothermal reservoirs can be monitored using seismic noise interferometry

Harvesting geothermal energy often leads to a pressure drop in reservoirs, decreasing their profitability and promoting the formation of steam caps. While steam caps are valuable energy resources, they also alter the reservoir thermodynamics. Accurately measuring the steam fraction in reservoirs is essential for both operational and economic perspectives. However, steam content estimations are very limited both in space and time since current methods rely on direct measurements within production wells. Besides, these estimations normally present large uncertainties. Here, we present a pioneering method for indirectly sampling the steam content in the subsurface using the ever-present seismic background noise. We observe a consistent annual velocity drop in the Hengill geothermal field (Iceland) and establish a correlation between the velocity drop and steam buildup using in-situ borehole data. This application opens new avenues to track the evolution of any gas reservoir in the crust with a surface-based and cost-effective method.

58 GEOSCIENCES↗
DOE OSTI2023

Partial wet oxidation of dairy manure as a pretreatment process to produce acetic acid ‘a Source Growth of Methanogens’

Wet oxidation can be an effective process for the pretreatment of complex biomass such as lignocellulose. However, studies on the use of wet oxidation for treating solid waste such as dairy manure are limited. The use of partial wet oxidation to convert dairy manure into low molecular weight carboxylic acids as final products were investigated. This work focuses on the performance of the sub-critical wet oxidation treatment of dairy cattle manure as a conversion/pretreatment process to release matter from the lignocellulosic fraction rather than a destructive process. The operating conditions were controlled at the short residence time and optimal temperature in the presence of oxygen under a pressure of 120 psi. The thermal hydrolysis under wet oxidation significantly affected conversion manure slurry into organic acids. The concentration of acetic acid reached 1778 mg L –1 , achieved at 190°C (60 minutes reaction time) as the reaction temperature increased within the range of 150°C–200°C, total organic carbon was reduced and monomers in the process liquids decreased. On the other hand, soluble COD in process liquids increased with an increment in reaction temperature. The results provide insights into technical options to pretreat dairy manure to improve biochemical conversion yield.

09 BIOMASS FUELS↗
DOE OSTI2026

Geothermal Direct-Use Applications for the District Energy System in Bucharest, Romania

The city of Bucharest, Romania, hosts the second-largest district energy system (DES) in the world. Geothermal resources can be considered as a supplementary heat source to support the demand for domestic hot water and space heating in the winter and shoulder seasons. The National Laboratory of the Rockies (NLR) has conducted a study that considers geothermal energy to serve a fraction of the existing district heating network operated by Electrocentrale Bucure?ti (ELCEN), the utility operating the DES. Lower Cretaceous and Jurassic limestones make up the main geothermal aquifer underlying Bucharest, which hosts temperatures suitable for district heating (up to 90 degrees C to the north of the city). Anomalous geothermal gradients have been observed to the north of the city, where a pumped well has produced 82 degrees C brine at the wellhead to feed the Therme Bucharest Spa. An anomalous gradient has also been reported to the southeast of the city (35 degrees C/km). NLR modeled the building heating loads of a small portion of the DES (a block of nine prototypical buildings) in its Urban Renewable Building and Neighborhood Optimization (URBANopt ) platform. To simulate meeting a baseload benchmark of 20 MWth deliverable to a small portion of the DES, the NLR team used GEOPHIRES to model production scenarios for (1) hydrothermal systems coupled with heat pumps targeting the main geothermal aquifer in the north, (2) enhanced geothermal systems targeting hot dry rock in the southeast, and (3) huff-and-puff systems targeting a gradient of 25 degrees C/km. Finally, NLR conducted a high-level sensitivity study around the techno-economics of these systems. The outcomes of this work indicate that hot dry rock geothermal resources that can deliver at least 90 degrees C hot water to the Geothermal District Energy System (GeoDES) offer a possible solution for supplemental geothermal heat delivered to the existing DES.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

IM3 Projected US Data Center Locations

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

Mongird, Kendall (ORCID:0000000328077088)↗
DOE OSTI2026

IM3 Projected US Data Center Locations

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

Mongird, Kendall (ORCID:0000000328077088)↗
DOE OSTI2021

Improving energy yield in photovoltaic modules with photonic structures

When installed outdoors, Si solar cells typically operate 20 – 30 K above ambient conditions. These elevated operating temperatures lead to diminished performance, reducing efficiency by ~0.4%/K for crystalline Si cells and decreasing module lifetime. Since much of the elevated temperature of the modules derives from parasitic absorption of sub-bandgap sunlight by the contacts, encapsulants, or other materials, reflectors that remove the sub-bandgap radiation from the module before it is absorbed promise to reduce the operating temperature. However, there are many competing strategies to reject this light: selective reflectors could be integrated into the outer module glass, at the textured Si-encapsulant interface, or on the rear. Furthermore, many of these approaches are complex and expensive to fabricate. The issue of heating can be even more critical in bifacial modules: high fractions of rear irradiance can lead to higher operating temperatures. Prior to this project, relatively little was known about the optical strategies for temperature reduction in bifacial modules. The goal of this project was to quantitatively assess optical strategies for improving the energy yield via a combination of improved anti-reflection and sub-bandgap light rejection. We studied two complementary concepts: the performance of ideal structures to determine the upper limits to performance, and low-complexity structures made from standard materials as cost-effective implementations. We also studied the performance of these reflectors in different types of modules, including Al BSF, PERC, and bifacial. Here we build from our prior accomplishments in developing mirror optimization techniques, and make use of simulation methods that accurately capture the optical properties of the modules throughout the visible and near-infrared spectrum. We connect these optical properties to energy yield under realistic, outdoor conditions. We also experimentally fabricated mirrors, incorporated them into mini-modules, and performed outdoor testing of performance at NREL. We found definitively that spectrally-selective mirrors on the outside of the module cover glass offer the best performance, both under ideal conditions and for realistic, low- complexity mirrors. Mirrors at the Si cell/encapsulant interface are limited by the multiple reflections needed to remove sub-bandgap light. Mirrors at the cell surface and mirrors on the rear also cannot remove all the sub-bandgap light, since parasitic absorption also occurs in the cover glass, encapsulant, and front contacts, depending on the module configuration. Also, cell texturing places higher demands on any cell-surface mirror because multiple interactions with the mirror are required to reject sub bandgap light which compounds losses. For bifacial modules, mirrors on the back do provide additional cooling and energy yield improvements, and the mirrors can have the same structure. In the monofacial case up to 3.3K of cooling is possible for mirrors on the front, compared to 2.2K at the cell surface and 1.2K at the rear. For bifacial modules, up to 2.4K of cooling is possible when mirrors are included at both the front and back. Our realistic designs utilize 4 – 6 layers of common photovoltaic materials such as SiO 2 , TiO 2 , and SiN x , making them more cost effective. Finally, we used our models to study thermal management in bifacial modules with different back lamination materials, finding that glass-glass laminated modules operated hotter than equivalent glass-polymer backsheet modules, due solely to the increased absorption of light incident from the rear of the module. Improving the energy yield by 2%, which is achievable with these realistic designs, would lead to LCOE reductions of $0.03/kWh by 2030. These benefits make photovoltaic panels more accessible to the public and may reduce associated maintenance costs.

14 SOLAR ENERGY↗
DOE OSTI2020

Bilevel optimization, deep learning and fractional Laplacian regularization with applications in tomography

Here we consider a generalized bilevel optimization framework for solving inverse problems. We introduce fractional Laplacian as a regularizer to improve the reconstruction quality, and compare it with the total variation regularization. We emphasize that the key advantage of using fractional Laplacian as a regularizer is that it leads to a linear operator, as opposed to the total variation regularization which results in a nonlinear degenerate operator. Inspired by residual neural networks, to learn the optimal strength of regularization and the exponent of fractional Laplacian, we develop a dedicated bilevel optimization neural network with a variable depth for a general regularized inverse problem. We illustrate how to incorporate various regularizer choices into our proposed network. As an example, we consider tomographic reconstruction as a model problem and show an improvement in reconstruction quality, especially for limited data, via fractional Laplacian regularization. We successfully learn the regularization strength and the fractional exponent via our proposed bilevel optimization neural network. We observe that the fractional Laplacian regularization outperforms total variation regularization. This is specially encouraging, and important, in the case of limited and noisy data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A discrete dislocation dynamics study of precipitate bypass mechanisms in nickel-based superalloys

Order strengthening in nickel-based superalloys is associated with the extra stress required for dislocations to bypass the $\gamma'$ precipitates distributed in the $\gamma$ matrix. Depending on the operating conditions and microstructure, a rich variety of bypass mechanism has been identified, with various shearing and Orowan looping processes gradually giving way to climb bypass as the operating conditions change from the low/intermediate temperatures and high stress regime, to the high temperature and low stress regime. When anti phase boundary (APB) shearing and Orowan looping mechanisms operate, the classical picture is that, at for a given volume fraction, the bypass mechanism changes from shearing to looping with increased particle size and within a broad coexistence size window. Another possibility, which is supported by indirect experimental evidence, is that a third “hybrid” transition mechanism may operate. Here, in this paper we use discrete dislocation dynamics (DDD) simulations to study dislocation bypass mechanisms in Ni-based superalloys. We develop a new method to compute generalized stacking fault forces in DDD simulations, based on a concept borrowed from complex analysis and known as the winding number of a closed curve about a point. We use this method to study the mechanisms of bypass of a square lattice of spherical $\gamma'$ precipitates by $a/2\langle110\rangle$ {111} edge dislocations, as a function of the precipitates volume fraction and size. We show that not only the hybrid mechanism is possible, but also that it operates as the transition mechanism between the shearing and looping regimes over a wide range of precipitates volume fraction and radii. Based on our simulation results, we propose a simple model for the strength of this mechanism. We also consider the effects of a $\gamma$/$\gamma'$ lattice misfit on the bypass mechanisms, which we approximate by an additional precipitate stress computed according to Eshelby’s inclusion theory. We show that in the shearing and hybrid looping-shearing regimes, a lattice misfit generally results in an increased bypass stress. For sufficiently high lattice misfit, the critical bypass configuration in attractive dislocation-precipitates interactions changes dramatically, and the bypass stress is controlled by the pinning of the trailing dislocation on the exit side of the precipitates, similar to what has been reported in the high-temperature creep literature.

36 MATERIALS SCIENCE↗
DOE OSTI2023

MACHINE LEARNING-ENABLED PREDICTION OF TRANSIENT INJECTION MAP IN AUTOMOTIVE INJECTORS WITH UNCERTAINTY QUANTIFICATION

Accurate prediction of injection profiles is a critical aspect of linking injector operation with engine performance and emissions. However, highly resolved injector simulations can take one to two weeks of wall-clock time, which is incompatible with engine design cycles with desired turnaround times of less than a day. Hence, it is important to reduce the time-to-solution of the internal flow simulations by several orders of magnitude to make it compatible with engine simulations. This work demonstrates a data-driven approach for tackling the computational overhead of injector simulations, whereby the transient injection profiles are emulated for a side-oriented, single-hole diesel injector using a Bayesian machine-learning framework. First, an interpretable Bayesian learning strategy was employed to understand the effect of design parameters on the total void fraction field. Then, autoencoders are utilized for efficient dimensionality reduction of the flowfields. Gaussian process models are finally used to predict the spatiotemporal void fraction field at the injector exit for unknown operating conditions. The Gaussian process models produce principled uncertainty estimates associated with the emulated flowfields, which provide the engine designer with valuable information of where the data-driven predictions can be trusted in the design space. The Bayesian flowfield predictions are compared with the corresponding predictions from a deep neural network, which has been transfer-learned from static needle simulations from a previous work by the authors. The emulation framework can predict the void fraction field at the exit of the orifice within a few seconds, thus achieving a speed-up factor of up to 38 x 10(6) over the traditional simulation-based approach of generating transient injection maps.

machine learning↗
DOE OSTI2024

High-Burnup BWR LOCA Burst Analysis Framework Development and Demonstration

Nuclear power currently contributes approximately 20% of total electricity generation in the United States and more than 10% globally. Given the increasing reliance on nuclear energy to achieve our nation’s goal of reaching net-zero carbon emissions by 2050, there is significant pressure on the existing nuclear industry to extend plant operational licenses and improve efficiency. This is crucial as the existing nuclear fleet serves as a vital bridge until new light water and advanced reactors can be developed and deployed, bolstering the supply of carbon-free energy to meet domestic demands. Operational costs primarily consist of plant operation and maintenance and fuel costs, influenced by materials and reactor core designs. These factors, coupled with heavily subsidized renewable energy markets, create a challenging economic environment for the existing light water reactor fleet, as well as for new build projects. To address these economic challenges, the nuclear industry has developed a strategic blueprint aimed at enhancing nuclear power’s economic sustainability. Past initiatives, such as efforts to eliminate fuel failures by 2010 and reduce operating costs by 30% before 2020, have laid the groundwork. Optimizing core design parameters, including burnup limits and enrichment levels, can lengthen cycles, reduce outages, reduce batch reload batch fractions and spent fuel storage requirements, and lower maintenance and operating expenses, thereby enhancing economic viability. In the United States, boiling water reactors (BWRs) comprise approximately one-third of the fleet, although much of the research and development focus has traditionally been on pressurized water reactors (PWRs). Advances in modeling and simulation, particularly through the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, are crucial to the long-term viability of BWRs, just as they are for PWRs. A key research area of the high burnup/increased enriched fuel initiative is focused on addressing loss-of-coolant-accident (LOCA)-related issues. NEAMS has dedicated significant effort to enhancing tools to better support BWRs, with a current focus on showcasing the BWR framework for high-burnup LOCA analysis. This high-fidelity work will demonstrate a best estimate pin-by-pin high-burnup BWR LOCA analysis to assess full-core cladding rupture behavior. This modeling capability will help with better understanding and realistic evaluation of fuel fragmentation, relocation, and dispersal (FFRD) phenomena at BWRs, which then could be used to prevent FFRD at BWRs without penalizing operational parameters. In addition, the results of this work will help identify strategies to identify additional margins or to potentially limit cladding rupture through core design optimizations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Partially cracked ammonia mixture combustion in gas turbine combustors

Ammonia is gaining popularity for single fuel use in existing gas turbines, as it is carbonless, has higher hydrogen content per unit volume than liquid hydrogen, and facilitates easy storage and handling. However, the low flame speed of ammonia makes it prone to flame blow off and remains the chief concern for its use in power generation. Following previous studies that have shown improved combustion performance by partially cracking the fuel, in this computational study, efficacy of partially cracked ammonia as a replacement fuel for natural gas is evaluated. A high-pressure optically accessible combustor operated at ~10 bar pressure with non-vitiated heated air was used as the test platform. This combustor was equipped with a novel multifuel multi-tube micromixing injector (M3 injector). High resolution simulations of the flow fields both in the injector as well as the combustor were performed to understand the fuel mixing in the injector and in the inlet region of the combustor. These modeling results showed that the injector was highly effective for achieving mixture homogeneity at the entrance of the combustor for ammonia and natural gas injection, whereas, for hydrogen an earlier injection facilitating longer residence time would be beneficial. Also, these simulations show that while harnessing waste heat the ideal fuel dissociation fraction is between 0.4 and 0.55 for optimal operation.

Ammonia↗
DOE OSTI2021

Absorbing the Sun: Operational Practices and Balancing Reserves in Florida's Municipal Utilities

The Florida Reliability Coordinating Council (FRCC) power system is comprised of multiple balancing authorities ranging in size from Gainesville Regional Utilities (GRU) with a 2019 summer net firm demand of 429 MW to Florida Power & Light with a 2019 summer net firm demand of 22,510 MW; and including cooperative, municipal, and investor-owned utilities. As all of these balancing authorities are and have plants to continue installing significant quantities of utility-scale solar photovoltaics, one relevant question is how much operating reserves they will need to hold as solar penetrations increase. While there are estimates of how regulating and flexibility reserve requirements change with solar penetration, the literature almost exclusively focuses on large balancing authorities with sub-hourly dispatch. In this work we analyze how reserve needs change not only with solar photovoltaic penetration, but also balancing authority size and operational practices. We find that, measured as a fraction of load, smaller balancing authorities with less frequent load and solar forecasts and less frequent dispatch need more reserves. Such utilities' reserve needs also increase more with increasing solar deployment as compared to larger or more frequently dispatched balancing authorities. These impacts are most acute for GRU. We find that moving from day-ahead to hour-ahead load and solar forecasting and system dispatch could enable GRU to incorporate 32% solar generation with median reserves at 20% instead of 60% of load; and that median reserve needs could drop further to about 10% of load if Florida's municipal utilities formed a reserve sharing group and moved to sub-hourly dispatch.

balancing authority↗
DOE OSTI2021

Tunable quantum-cascade VECSEL operating at 19 THz

We report a terahertz quantum-cascade vertical-external-cavity surface-emitting laser (QC-VECSEL) emitting around 1.9 THz with up to 10% continuous fractional frequency tuning of a single laser mode. The device shows lasing operation in pulsed mode up to 102 K in a high-quality beam, with the maximum output power of 37 mW and slope efficiency of 295 mW/A at 77 K. Challenges for up-scaling the operating wavelength in QC metasurface VECSELs are identified.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Operability of a Natural Gas–Air Rotating Detonation Engine

A combustor was developed to operate with natural gas and air as the primary propellants at elevated chamber pressures and air preheat temperatures representative of land-based power generation gas turbine engines. Detonation dynamics were studied to characterize the operability of rotating detonation-based pressure gain combustion systems for this application. Measurements of chamber wave dynamics were performed using high-frequency pressure transducers and high-speed imaging of broadband combustion chemiluminescence. The rotating detonation engine was tested with two injector configurations across a broad range of mass flux (200–500 kg/m 2 /s), equivalence ratio (0.85–1.2), and oxygen mass fraction (23.2–35%) conditions to determine the effect of operating parameters on the propagation of detonation waves in the combustor. Wave propagation speeds of up to 70% of the mixture Chapman–Jouguet detonation velocity and chamber pressure fluctuations greater than 4 times the mean chamber pressure were observed. Supplementing the air with additional oxygen, varying the equivalence ratio, and enriching the fuel with hydrogen revealed that combustor operability is sensitive to the chemical kinetics of the propellant mixture. Comparing the operational trends of the two injector configurations suggests that one design mixes the incoming propellants more effectively. Although most test conditions exhibited counter-rotating detonation waves within the chamber, the injector design with superior mixing characteristics was able to support single-wave propagation.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Fission gas trapped in Chornobyl fuel microparticles reveals details of reactor operations

The isotopic ratios of fission gas would provide important source information of a nuclear fuel sample found in the environment. However, it is believed that during a reactor accident like Chornobyl all fission gas is lost and that the radioactive particles found in the Chornobyl Exclusion Zone today are depleted in gases by the initial explosion and subsequent fire. We disprove this hypothesis by detection and analysis of trapped krypton and xenon in these particles. Our analysis of krypton and xenon isotopes by noble gas mass spectroscopy in combination with resonance ionization mass spectrometry establishes that important information about reactor operations like age, neutron flux and plutonium fission fraction can still be reconstructed from individual micrometer-sized particles even after decades of weathering in the environment.

Chornobyl↗