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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Cellular Shade Energy Savings in a Commercial Setting

Windows cause approximately 1.7 quad of heating and cooling energy consumption in the United States. This energy consumption can be reduced by using high-efficiency window attachments. Common Venetian blinds and planar shades, such as roller shades, might block solar radiation, but they do not provide a significant improvement to window system thermal transmittance. Cellular shades have better thermal performance compared to other shading devices because of the honeycomb structure that traps air in pockets to create thermal insulation. However, evaluating the energy savings potential of cellular shades using experimental testing in commercial settings is limited. Moreover, the effect of cellular shades on daylighting and glare is yet to be evaluated using field testing. In this study, experimental testing of cellular shades was performed in a real building with emulated occupancy for both a cooling and a heating season. Compared with a room without shades, the use of cellular shades in experimental testing showed incremental energy savings of 4.6% to 9.4% for cooling and higher than 20% for heating. The experimental data were used to calibrate the baseline energy model and validate the cellular shades model. Annual simulation of cellular shades was performed for a medium office prototype building using the validated cellular shades model. The annual simulation was performed in Phoenix, Nashville, and Rochester. The annual savings for HVAC energy was 25% for Phoenix, 27% for Nashville, and 19% for Rochester.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Assessment of Low-Cost Minisplit Heat Pump Connection System

This project was funded by SCE's Emerging Technologies Program, and evaluates the feasibility of a connection system that can pave the path to accelerated, cost-effective adoption of high-efficiency Minisplit Heat Pump (MSHP) systems. This report details the characterization of this connection system and a heat pump enabled with this technology in a laboratory setting, and assesses the energy and cost impact applicable to residential buildings in SCE service territory. The energy and economic analysis leverages NREL's ResStock TM modeling approach based on the EnergyPlus ® hourly simulation platform. The connection system can be incorporated into existing MSHP architectures. This reduces installation time from 10 to 20 man hours to approximately one hour or less, dramatically lowering total installation costs without adversely impacting heat pump performance. This report characterizes the connection system's leakage performance while connected and disconnected, as well as leakage over several connection/disconnection cycles, commensurate with manufacturer specifications for the individual components. The connector was incorporated into an off-the-shelf MSHP. Performance was compared to an identical unmodified heat pump. The connector had no impact on performance. Large-scale hourly energy simulations were performed for 22,574 homes across 15 counties in SCE service territory. The analysis was performed using baseline assumptions about the penetrations of window air conditioners (~18%) and six upgrade scenarios for these air conditioners. All scenarios assumed 100% adoption of the Connector-Supported Heat Pump (CSHP) in place of window air conditioners: MSHPs at Seasonal Energy Efficiency Ratio (SEER) 17, 25, and 33, and CSHPs at SEER 17, 25, and 33. Results show the increased adoption of high-efficiency heat pumps can result in up to 29% air conditioning energy savings for homes with window air conditioners.

42 ENGINEERING↗
DOE OSTI2023

Technical Evaluation of Accelerated Basin De-Inventory Material Addition to Sludge Batch 11 (Rev. 1)

The Accelerated Basin De-inventory (ABD) program involves discarding spent nuclear fuel that is currently stored in L-Basin to the Defense Waste Processing Facility (DWPF) for vitrification. The first ABD discards will occur during the preparation of Sludge Batch (SB) 11. Savannah River Mission Completion has requested that the Savannah River National Laboratory assess the technical gaps related to the increased gadolinium poisoning requirement and the impacts of performing the Low Temperature Aluminum Dissolution (LTAD) process in Tank 51 with H-Canyon discards present. The following summarizes the evaluation of the impacts of increasing the quantity of gadolinium (and related topics) from what was previously evaluated in the SRNL studies of gadolinium-poisoned ABD material solubility, the overall ABD flowsheet review, and increasing the fissile mass loading in glass: 1) Based on literature surveys, there is no indication that organic interactions with gadolinium will be significant at the high pH (typically >13) conditions of the Concentration, Storage, and Transfer Facilities. Any interactions of gadolinium with organics in DWPF are not expected to adversely impact DWPF or downstream facilities. Thus, there is little-to-no residual risk from organic interactions with gadolinium [Gap closed]; 2) Adding depleted uranium to ABD material, targeting 235 U enrichment of 4.90% within each transfer window, will mitigate potential impacts from an increase in soluble 235 U enrichment during sludge washing and LTAD. The plan to take advantage of previous transfers and allow 235 U enrichment of >5% during the final transfer window carries a risk that Tank 51 supernate will have a 235 U enrichment of >5%, which should be evaluated for acceptance; 3) Increasing the gadolinium mass ratio to 3.0:1 Gd: 235 U(eq SLU ) should lead to the same or higher partitioning of gadolinium into the solid phase within the DWPF Chemical Process Cell, resulting in both liquid and solid phases with expected partitioning of Gd consistent with the prior solubility study [Gap closed for SB11]; 4) There are no expected impacts on DWPF melt temperature and melter operations due to the minimal ~0.2 weight percent (wt%) increase in Gd concentration relative to previous sludge batches [Gap closed for SB11]; 5) As observed previously, Gd is expected to enter the off-gas system via physical entrainment, but at a slightly higher concentration than what was observed for SB9 melter off-gas pluggage deposits (0.07 wt%) [Gap closed for SB11] ; 6) There are no expected impacts on DWPF recycle or the Recycle Collection Tank glycolate destruction process. [Gap closed for SB11]; 7) Gd is projected to be a trace component in the SB11 glass (<0.5 wt%) and can be ignored for process control. Trace components do not significantly impact glass durability, thus the conclusions of the previous Product Consistency Test evaluation at a fissile mass loading of 2,500 g fissile/m3 glass still applies to SB11. The ~0.1 wt% increase in Gd2O3 concentration relative to the previous study will not impact the predictability of SB11 glass with the DWPF Product Composition Control System (PCCS) models for durability or the acceptability of glass according to the Waste Acceptance Product Specifications (WAPS) criterion for product consistency [Gap closed for SB11]; 8) No additional Toxicity Characteristic Leaching Procedure testing is necessary for SB11 and the hazardous waste specification of the SB11 DWPF waste form is unchanged after the addition of the ABD stream [Gap closed for SB11]. The following summarizes the evaluation of the impacts of adding two-thirds of the ABD material to Tank 51 prior to LTAD: 1) The addition of two-thirds of the ABD increases overall aluminum mass from 1.39×10 4 kg to 1.64×10 4 kg (15.5% ABD Al). The form of the insoluble portion of the Al resulting from ABD addition should be the more readily dissolved Al(OH) 3 and amorphous forms. The portion of the ABD aluminum that is processed by LTAD is expected to be completely soluble, thus requiring that less of the boehmite in the sludge be dissolved to reach the same Al target in the SB. [Gap closed for SB11]; The expected LTAD impact on other components, as related primarily to the components in ABD, are discussed. Gd is expected to remain insoluble during LTAD and not impact the solubility of other components. [Gap closed for SB11]; The addition of two-thirds of the ABD increases overall projected SB11 uranium mass from 4,740 kg to 13,100 kg (63% ABD U) and the projected plutonium mass from 86.0 kg to 89.5 kg (3.9% ABD Pu). The addition of all of the ABD increases overall projected SB11 uranium mass from 4,740 kg to 16,100 kg (70% ABD U) and the projected plutonium mass from 86.0 kg to 90.4 kg (5.3% ABD Pu). The 235 U enrichment will be ≤5%. The fissile uranium will be adequately poisoned by Gd and the fissile Pu will be adequately poisoned by Fe from the sludge. [Gap closed for SB11]; There is a low risk that ABD addition will impact the rheology or pumpability of the slurry. There is a low but higher risk of ABD addition prior to LTAD impacting the settling rate; Based on the evaluation of adding two-thirds of the ABD material and all of the ABD material prior to the LTAD process, there is no volume or mass limit that would need to be imposed on ABD additions prior to LTAD. [Gap closed for SB11]. Revision 1 of this report addresses a variation on the ABD additions and LTAD strategy where sodium hydroxide additions for LTAD may be performed intermittently or concurrently with an ABD addition window. The proposed change does not alter the conclusions of this evaluation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

TESTING AND PROCESSING OF PRE-PRODUCTION 325 MHZ SINGLE SPOKE RESONATOR POWER COUPLERS FOR PIP-II PROJECT

Fundamental 325 MHz power couplers are designed, built and tested for SSR cavities in PIP-II project [1]. Couplers should work in CW mode at power level 7.5kW w/o beam and ~15 kW with the 2 mA beam. At pre-production stage we built and tested 6 couplers, produced by CPI (FNAL) and PMB (IJCLab) and 4 more couplers will be tested soon. Two of tested couplers had TiN coated ceramic window. In warm test stand two couplers were mounted on the coupling chamber and tested in SW regime at full reflection with phase controlled by position of short and reflection insert. Couplers were tested at pulse mode (up to 25kW) and cw mode (12kW) with HV bias or without bias. Test results demonstrated that 3.5 kV DC bias completely suppresses multipactor in coupler. Vacuum activity in coupler was controlled by e-pickups and build-in vacuum gauges, located near the vacuum side of window. Power processing without DC bias was done for several couplers with and without TiN coating on ceramic window. Test results are presented and discussing in paper.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

End-Use Savings Shapes Measure Documentation: Dispatch Schedule Generation for Demand Flexibility Measures

This supplemental document describes the methodology used for determining the dispatch timing of various EUSS demand flexibility measures. Demand flexibility measures are designed to reduce/dispatch electricity demand in buildings during especially beneficial/critical times. The method used in this work utilizes predictions of building loads to generate a schedule that reflects the periods when the building's daily peak load occurs to support decision making in demand flexibility measures. The dispatch schedule generation method described in this document creates an hourly schedule that includes a load dispatch (peak) window for each day for a whole year based on load prediction, with options using different prediction methods: perfect prediction, bin-sampling method, fixed schedule, and outdoor air temperature (OAT)-based prediction method. The perfect prediction method performs a simulation to obtain the annual load profile as predicted load, representing the scenario of perfect load prediction. The bin-sampling method (1) categorizes days into representative bins by temperature characteristics, (2) performs simulations on sample days from each of those bins to create representative (or predicted) load, and (3) assigns representative loads for all days in a year based on the bin categorization. The fixed schedule method defines uniform start and end time of peak window with assumed fixed daily peak time, for all days in a season or a year. The OAT-based prediction method uses the statistics of OAT (minimum and maximum) as the indicators of peak load, with specified delay response time from building loads to temperature. Given the load prediction, daily peak periods are determined as a time window with specified length in each day that include the predicted daily peak load and with a secondary rule such as maximizing energy saving potential. The dispatch schedule generation method is not a standalone measure and is intended to be combined with other demand flexibility measures that could leverage the peak schedule and apply demand controls on specific systems or devices for demand response, such as measures described in "Measure Documentation - Thermostat Control for Load Shedding" and "Measure Documentation - Thermostat Control for Load Shifting".

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Predicting Selective Laser Printing Print Quality of Polymer Powders through Melt Flow Index

Selective Laser Sintering (SLS) uses a precisely controlled laser to fuse polymer powder to build complex 3D shapes. While SLS covers a wide application space, the processing knowledge of polymer powder is limited, restricting the number of commercial powders available. This study serves to expand the processing knowledge of polypropylene and polyethylene in parallel with a “mature” SLS feedstock, nylon, through melt flow index (MFI) characterization. Differential Scanning Calorimetry (DSC) was used to explore the sintering window of the polymers. Polyethylene and polypropylene exhibited a relatively narrow sintering window between 4 – 5 °C, whereas the sintering window of nylon was much wider, between 23 – 24 °C. This suggests that the print quality between polyethylene and polypropylene would be similar; however, X-ray computed tomography revealed a higher volume of print defects, voids, and de lamination in polyethylene than in polypropylene. MFI analysis provided additional insight into the difference in print quality, as the MFI of polyethylene was 7.16 g/10 min, 9.95 g/10 min for polypropylene, and 17.23 g/10 min for nylon. MFI is inversely correlated to melt viscosity, and a low melt viscosity is desired for proper coalescing between the layers and particles. These results suggest that MFI is a promising tool, in conjunction with traditional thermal analysis, for screening candidate powder feedstocks for SLS and optimization of print parameters for novel powders.

36 MATERIALS SCIENCE↗
DOE OSTI2025

ComStock Measure Documentation: Lighting Control for Load Shedding

This report describes the modeling methodology for a single end-use savings shape measure - lighting control for load shedding - and briefly introduces key results. The lighting control for load shedding measure applies lighting dimming control to reduce the lighting load during the building's electricity peak window every weekday. The measure takes daily peak load schedule inputs generated by the method "Dispatch Schedule Generation" described in the "Supplemental Documentation: Dispatch Schedule Generation for Demand Flexibility Measures" to determine the start and end times of the predicted peak window, and then adjusts the lighting dimming level by a percentage reduction from the original schedules during the peak window to reduce the peak demand. The measure is applicable to (large, medium and small) offices, warehouses, and primary and secondary schools, which correspond to approximately 68% of the stock floor area of commercial buildings in ComStock analysis. The measure demonstrates 2%-7% daily peak demand reduction performance for applicable buildings, and 0.43% total site energy savings (0 trillion British thermal units [TBtu]) for the U.S. commercial building stock modeled in ComStock.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

ComStock Measure Documentation: Thermostat and Lighting Control for Load Shedding

This report describes the modeling methodology for an upgrade package of two end-use savings shape measures - Thermostat Control for Load Shedding and Lighting Control for Load Shedding - and briefly introduces key results. The package combines thermostat control for load shedding and lighting control for load shedding measures to reduce the HVAC and lighting load during the building's electricity peak window every weekday. The measure takes daily peak load schedule inputs generated by the method "Dispatch Schedule Generation" described in the "Supplemental Documentation: Dispatch Schedule Generation for Demand Flexibility Measures" to determine the start and end times of the predicted peak window, and then relaxes the thermostat setpoints and dims the lighting level from the original schedules during the peak window to reduce the peak demand. The measure is applicable to (large, medium and small) offices, warehouses, and primary and secondary schools, which correspond to approximately 68% of the stock floor area of commercial buildings in ComStock analysis. The measure demonstrates 3%-10% daily peak demand reduction performance for applicable buildings, and 0.97% total site energy savings (0 trillion British thermal units [TBtu]) for the U.S. commercial building stock modeled in ComStock.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

ComStock Measure Documentation: Thermostat and Lighting Control for Load Shedding + Photovoltaics With 40% Rooftop Coverage

This report describes the modeling methodology for an upgrade package of two end-use savings shape measures - Thermostat Control for Load Shedding and Lighting Control for Load Shedding - and briefly introduces key results. The package combines thermostat control for load shedding, lighting control for load shedding, and PV with 40% rooftop coverage measures to reduce the net building load during the building's electricity peak window every weekday. The measure takes daily peak load schedule inputs generated by the method "Dispatch Schedule Generation" described in the "Supplemental Documentation: Dispatch Schedule Generation for Demand Flexibility Measures" to determine the start and end times of the predicted peak window, and then relaxes the thermostat setpoints and dims the lighting level from the original schedules during the peak window to reduce the peak demand, while applying the fixed rooftop PV application for onsite electricity generation. The measure is applicable to (large, medium and small) offices, warehouses, and primary and secondary schools, which correspond to approximately 68% of the stock floor area of commercial buildings in ComStock analysis. The measure demonstrates 5%-15% daily peak demand reduction performance for applicable buildings, and around 1% total site energy savings (0 trillion British thermal units [TBtu]) for the U.S. commercial building stock modeled in ComStock.

14 SOLAR ENERGY↗
DOE OSTI2025

Advanced Fuels Campaign Time-at-Temperature Irradiation Campaign and Post-Irradiation Examination Plan

With increasing per capita energy consumption and rapidly growing energy consumption predicted for data centers, the US faces challenges in meeting projected energy demands. The current administration is attempting to accelerate the deployment of new nuclear construction by providing significant investments in advanced nuclear and by modernizing regulatory approaches for the licensing new reactors. However, enabling extended power uprates (EPUs) for the current nuclear reactor fleet would provide a shorter-term solution to better calibrate near-term energy generation capacity to the ever-growing energy demands of the modern era. One pathway to achieve power uprates is to increase the operational window by reassessing fuel safety limits around anticipated transients. Existing light-water reactors (LWRs) utilize a targeted operational window with well-defined operational efficiencies, yet this window is also often bound by conservative safety limits that result in suboptimal operational performance. For example, the operation of the existing fleet is highly constrained by safeguards to operation related to anticipated operational occurrences (AOOs), which are moderate-frequency transients expected with a frequency greater than 0.01 per reactor-year. These AOOs include temperature excursions where the critical heat flux for the system is exceeded, resulting in a departure from nucleate boiling (DNB) at the cladding surface. This DNB event is a thermohydraulic condition that, with current conservative fuel safety limits, results in the fuel rods being classified as “failed,” meaning that the cladding may not be returned to service.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Advanced Fuels Campaign Time-at-Temperature Irradiation Campaign and Post-Irradiation Examination Plan

With increasing per capita energy consumption and rapidly growing energy consumption predicted for data centers, the US faces challenges in meeting projected energy demands. The current administration is attempting to accelerate the deployment of new nuclear construction by providing significant investments in advanced nuclear and by modernizing regulatory approaches for the licensing new reactors. However, enabling extended power uprates (EPUs) for the current nuclear reactor fleet would provide a shorter-term solution to better calibrate near-term energy generation capacity to the ever-growing energy demands of the modern era. One pathway to achieve power uprates is to increase the operational window by reassessing fuel safety limits around anticipated transients. Existing light-water reactors (LWRs) utilize a targeted operational window with well-defined operational efficiencies, yet this window is also often bound by conservative safety limits that result in suboptimal operational performance. For example, the operation of the existing fleet is highly constrained by safeguards to operation related to anticipated operational occurrences (AOOs), which are moderate-frequency transients expected with a frequency greater than 0.01 per reactor-year. These AOOs include temperature excursions where the critical heat flux for the system is exceeded, resulting in a departure from nucleate boiling (DNB) at the cladding surface. This DNB event is a thermohydraulic condition that, with current conservative fuel safety limits, results in the fuel rods being classified as “failed,” meaning that the cladding may not be returned to service.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Energy and Comfort Impacts of High Performance Facades in Office Buildings

Building facades have a major effect on energy use, occupant comfort, and well-being. Yet adoption of high-performance facades is often slowed by limited data and unclear cost benefits. To address this gap, Oak Ridge National Laboratory, in collaboration with the Facade Tectonics Institute, conducted whole-building energy simulations to evaluate fenestration technologies for small and medium office buildings across three weather locations: hot (Tampa, Florida, weather zone 2A), mixed (New York, New York, weather zone 4A), and cold (Rochester, Minnesota, weather zone 6A). The simulations included parametric variations in window-to-wall ratio (30%–70%), U-values (0.1–1 Btu/h∙ft 2 ∙°F), solar heat gain coefficients (0.2–0.8), and solar control strategies and devices (e.g., interior shades and switchable glazing). Performance metrics included annual cooling, heating, and total heating, ventilation and air-conditioning (HVAC) energy use intensity, as well as nonenergy factors such as useful daylight illuminance, glare frequency, and thermal comfort during typical office hours (8 a.m.–6 p.m.). Results indicate that cooling energy consumption is most sensitive to solar heat gain coefficient (SHGC) in hot weather, whereas heating energy consumption is strongly influenced by U-value in cold weather. Total HVAC reflects these trade-offs, showing up to 60% difference for a window in total HVAC energy use intensity between different combinations of U-value and SHGC. Daylight dimming generally reduces cooling loads but can increase heating demands in colder locations. Interior solar shades improve useful daylight and reduce discomfort glare, whereas switchable glazing delivers the largest cooling reductions in hot weather but may increase heating loads in winter by limiting passive solar gains. Thermal comfort improves with lower window-to-wall ratios and lower SHGC in hot locations and with lower U-values in cold locations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Automatic point Cloud Building Envelope Segmentation (Auto-CuBES) using Machine Learning

Modern retrofit construction practices use 3D point cloud data of the building envelope to obtain the as-built dimensions. However, manual segmentation by a trained professional is required to identify and measure window openings, door openings, and other architectural features, making the use of 3D point clouds labor-intensive. In this study, the Automatic point Cloud Building Envelope Segmentation (Auto-CuBES) algorithm is described, which can significantly reduce the time spent during point cloud segmentation. The Auto-CuBES algorithm inputs a 3D point cloud generated by commonly available surveying equipment and outputs a wire-frame model of the building envelope. Unsupervised machine learning methods were used to identify facades, windows, and doors while minimizing the number of calibration parameters. Additionally, Auto-CuBES generates a heat map of each facade indicating non-planar characteristics that are crucial for the optimization of connections used in overclad envelope retrofits. With a scan resolution of 3 mm, the resulting window dimensions showed a mean absolute error of 4.2 mm compared to manual laser measurements.

Maldonado Puente, Bryan↗
DOE OSTI2022

Low-energy astrophysics with KamLAND

We present two results of a search for MeV-scale neutrino and anti-neutrino events correlated with gravitational wave events/candidates and large solar flares with KamLAND. The KamLAND detector is a large-volume neutrino detector using liquid scintillator, which is located at 1 km underground under the top of Mt. Ikenoyama in Kamioka, Japan. KamLAND has multiple reaction channels to detect neutrinos. Electron antineutrino can be detected via inverse-beta decay with 1.8 MeV neutrino energy threshold. All flavors of neutrinos can be detected via neutrino-electron scattering without neutrino energy threshold. KamLAND has continued the neutrino observation since 2002 March. We use the data set of 60 gravitational waves provided by the LIGO/Virgo collaboration during their second and third observing runs and search for coincident electron antineutrino events in KamLAND. We find no significant coincident signals within a ±500 s timing window from each gravitational wave and present 90% C.L. upper limits on the electron antineutrino fluence between 10 8 –10 13 cm -2 for neutrino energies of 1.8–111 MeV. For a solar-flare neutrino search at KamLAND, we determine the timing window using the solar X-ray data set provided by the GOES satellite series from 2002 to 2019 and search for the excess of coincident event rate on the all-flavor neutrinos. We find no significant event rate excess in the flare time windows and get 90% C.L. upper limits on the fluence of neutrinos of all flavors (electron anti-neutrinos) between 10 10 –10 13 cm -2 (10 8 –10 13 cm -2 ) for neutrino energies in the energy range of 0.4–35 MeV.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Evaluating Image Classification Deep Convolutional Neural Network Architectures for Remaining Useful Life Estimation of Turbofan Engines

Accurate estimation of the remaining useful life (RUL) is a key component of condition-based maintenance (CBM) and prognosis and health management (PHM). Data-based models for the estimation of RUL are of particular interest because expert knowledge of systems is not always available, and physical modeling is often not feasible. Additionally, using data-based models, which make decisions based on raw sensor data, allow features to be learned instead of manually determined. In this work, deep convolutional neural network (CNN) architectures are investigated for their ability to estimate the RUL of turbofan engines. To improve the accuracy of the models, CNN architectures, which have proven successful in image classification, are implemented and tested. Specifically, the blocks used in the Visual Geometry Group (VGG) architecture, inception modules used in the GoogLeNet architecture, and residual blocks used in the ResNet architecture are incorporated. To account for varying flight lengths, the input to the models is a window of time series data collected from the engine under test. Window locations at the climb, cruise, and descent stages are considered. To further improve the RUL estimations, multiple overlapping windows at each location are used. This increases the amount of training data available and is found to increase the accuracy of the resulting RUL estimations by averaging the estimates from all overlapping segments. The model is trained and tested using the new Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS) data set, and high prognosis accuracy was achieved. Furthermore, this work expands on the model developed and used in the 2021 PHM Society Data Challenge, which received second place.

convolutional neural networks↗
DOE OSTI2025

Limits on the Low-energy Electron Antineutrino Flux from the Brightest Gamma-Ray Burst of All Time

The electron antineutrino flux limits are presented for the brightest gamma-ray burst (GRB) of all time, GRB221009A, over a range of 1.8–200 MeV using the Kamioka Liquid Scintillator Antineutrino Detector. Using multiple time windows ranging from minutes to days surrounding the event to search for electron antineutrinos coincident with the GRB, we set an upper limit on the flux under the assumption of several power-law neutrino source spectra, with power-law indices ranging from 1.5 to 3 in steps of 0.5. No excess was observed in any time windows ranging from seconds to days around the event trigger time T 0 . For a power-law index of 2 and a time window of T 0 ± 500 s, a flux upper limit of 2.34 × 10 9 cm −2 was calculated. The limits are compared to the results presented by IceCube.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series

Abstract. Improving the quantification of soil thermal and physical properties is key to achieving a better understanding and prediction of soil hydro-biogeochemical processes and their responses to changes in atmospheric forcing. Obtaining such information at numerous locations and/or over time with conventional soil sampling is challenging. The increasing availability of low-cost, vertically resolved temperature sensor arrays offers promise for improving the estimation of soil thermal properties from temperature time series, and the possible indirect estimation of physical properties. Still, the reliability and limitations of such an approach need to be assessed. In the present study, we develop a parameter estimation approach based on a combination of thermal modeling, sliding time windows, Bayesian inference, and Markov chain Monte Carlo simulation to estimate thermal diffusivity and its uncertainty over time, at numerous locations and at an unprecedented vertical spatial resolution (i.e., down to 5 to 10 cm vertical resolution) from soil temperature time series. We provide the necessary framework to assess under which environmental conditions (soil temperature gradient, fluctuations, and trend), temperature sensor characteristics (bias and level of noise), and deployment geometries (sensor number and position) soil thermal diffusivity can be reliably inferred. We validate the method with synthetic experiments and field studies. The synthetic experiments show that in the presence of median diurnal fluctuations ≥ 1.5 ∘C at 5 cm below the ground surface, temperature gradients > 2 ∘C m−1, and a sliding time window of at least 4 d the proposed method provides reliable depth-resolved thermal diffusivity estimates with percentage errors ≤ 10 % and posterior relative standard deviations ≤ 5 % up to 1 m depth. Reliable thermal diffusivity under such environmental conditions also requires temperature sensors to be spaced precisely (with accuracy to a few millimeters), with a level of noise ≤ 0.02 ∘C, and with a bias defined by a standard deviation ≤ 0.01 ∘C. Finally, the application of the developed approach to field data indicates significant repeatability in results and similarity with independent measurements, as well as promise in using a sliding time window to estimate temporal changes in soil thermal diffusivity, as needed to potentially capture changes in bulk density or water content.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Technical note: Using long short-term memory models to fill data gaps in hydrological monitoring networks

Abstract. Quantifying the spatiotemporal dynamics in subsurface hydrological flows over a long time window usually employs a network of monitoring wells. However, such observations are often spatially sparse with potential temporal gaps due to poor quality or instrument failure. In this study, we explore the ability of recurrent neural networks to fill gaps in a spatially distributed time-series dataset. We use a well network that monitors the dynamic and heterogeneous hydrologic exchanges between the Columbia River and its adjacent groundwater aquifer at the U.S. Department of Energy's Hanford site. This 10-year-long dataset contains hourly temperature, specific conductance, and groundwater table elevation measurements from 42 wells with gaps of various lengths. We employ a long short-term memory (LSTM) model to capture the temporal variations in the observed system behaviors needed for gap filling. The performance of the LSTM-based gap-filling method was evaluated against a traditional autoregressive integrated moving average (ARIMA) method in terms of error statistics and accuracy in capturing the temporal patterns of river corridor wells with various dynamics signatures. Our study demonstrates that the ARIMA models yield better average error statistics, although they tend to have larger errors during time windows with abrupt changes or high-frequency (daily and subdaily) variations. The LSTM-based models excel in capturing both high-frequency and low-frequency (monthly and seasonal) dynamics. However, the inclusion of high-frequency fluctuations may also lead to overly dynamic predictions in time windows that lack such fluctuations. The LSTM can take advantage of the spatial information from neighboring wells to improve the gap-filling accuracy, especially for long gaps in system states that vary at subdaily scales. While LSTM models require substantial training data and have limited extrapolation power beyond the conditions represented in the training data, they afford great flexibility to account for the spatial correlations, temporal correlations, and nonlinearity in data without a priori assumptions. Thus, LSTMs provide effective alternatives to fill in data gaps in spatially distributed time-series observations characterized by multiple dominant frequencies of variability, which are essential for advancing our understanding of dynamic complex systems.

54 ENVIRONMENTAL SCIENCES↗