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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Wyandotte Integrated Renewable Energy Strategy (WIRES 2) (Final Technical Report)

Wyandotte Municipal Services (WMS), a Michigan Municipal Utility offering electric generation, transmission & distribution, water filtration & distribution and Broadband/Video sought to deploy a set of renewable energy projects for their Electric Utility that contributed to reducing the City’s environmental and energy impact, provided examples that would encourage businesses and citizens to adopt cleaner energy practices and help WMS meet the required renewable energy standards of the State of Michigan (10% in 2015, 15% in 2021). WMS generates and delivers roughly 280,000 megawatt hours (MWh) of electricity annually to more than 10,000 homes and 1,000 businesses within the City of Wyandotte. The Wyandotte Integrated Renewable Energy Strategy – WIRES 2 resulted in deployment of a set of community-scale micro-wind turbines, evaluation and installation of energy-efficient and low-maintenance light-emitting diode (LED) street lights and park lights in highly visible locations in the City and expansion of the geothermal heating and cooling district that already included residential geothermal systems, to include larger scale business/institutional systems at the Utility’s largest electric customer and at the City Library. Finally, WMS identified the need for job training in energy efficiency and renewable energy technologies to further develop a local skilled workforce in these areas. Partially funded by the grant, the wind turbine project provides a benchmark for WMS, local businesses and residents in the evaluation of utility-scale wind v. micro-wind in an urban environment as a renewable energy strategy. Also partially funded by the grant, the LED project benefited the City of Wyandotte by reducing load on the electric system for the public utility but also reduced City costs for streetlighting, parking lot lighting and park lighting without a compromise in security. The project also resulted in a visual success that has led to additional approvals for non-Grant related LED lighting installations resulting in further reduction in the electric load in the City. Commercial Geothermal installations resulted in the Utility being able to eliminate steam customers who formerly utilized the byproduct of steam from WMS electric production. Due to the reduction in natural gas prices and the overall reduction in market purchased power, it was no longer feasible for WMS to operate its Power Plant as a base load plant and to only operate on a market dispatch philosophy when market prices dictated that WMS could produce electricity cheaper than the market purchase price. This has resulted in fewer operating days for the WMS Power Plant, resulting in less environmental impact. WMS has now completely exited the steam business and the ability to offer a geothermal option to two (2) former steam customers (BASF-Wyandotte and the Bacon Memorial Library) allowed for that. In addition, peak loads have been shaved for these two (2) large customers due to the consistent temperature offered by geothermal heating and cooling, reducing the swings associated with thermostat changes caused by outside temperature changes during extreme high and low temperatures. Finally, energy efficiency and renewable energy college-level classes at Wayne County Community College allowed a group of interested students to pursue studies in those technologies through grant provided tuition, books and course materials. This effort provided a foundation of potential future employees not only for WMS but other energy efficiency/renewable energy employers such as Franklin Energy, a partner with WMS in energy optimization efforts with Wyandotte businesses.

17 WIND ENERGY↗
DOE OSTI2023

The Princeton Field-Reversed Configuration for Compact Nuclear Fusion Power Plants

The Princeton Field-Reversed Configuration (PFRC) nuclear fusion reactor concept is an innovative approach to fusion power generation prioritizing low neutron production and small size. Here, a combination of analytical modeling and numerical simulation shows that the novel heating approach generates an FRC with closed field lines. Simulation data from a single-particle Hamiltonian code predicts ms-scale plasma heating in reactor-scale conditions while PIC codes predict formation of warm FRC plasmas from initial mirror fields. The PFRC-1 and PFRC-2 experiments have heated electrons to energies well in excess of 100 eV and plasma durations to 300 ms, more than 10 4 times longer than the predicted tilt instability growth time. From these data, we have created a development plan and anticipated performance metrics for a fusion reactor based on the PFRC concept. The resulting 1–10 MW PFRC reactors would be suitable for diverse applications, from submarines to urban environments to space propulsion. PFRC is a steady-state, driven magnetic confinement device. Plasma, inside a cylindrical array of coils, is confined and heated by external RF antennae. PFRC would be ultra-low radiation due to both its fuel and small size. The choice of advanced fuels, deuterium and helium-3 (D– 3 He), may be enabled by the high-β FRC configuration. The small size of the reactor would enable rapid exhaust of the dangerous tritium ash. Low radiation would make the reactor safer to operate and, in combination with simple geometry and small size, dramatically lowers development and maintenance costs. This review paper gives an introduction to the physics of the PFRC and a summary of the PFRC-2 experiment results to date. It then discusses the future program plan and how PFRC reactors would be commercialized.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Layered CAD/CSG geometry for spatially complex radiation transport scenarios

Many spatially complex fission, fusion, and national security Monte Carlo (MC) radiation transport scenarios involve combining computer-aided design (CAD) models with constructive solid geometry (CSG) models. A layered geometry method has been implemented in the Shift MC code to address this need. With layered geometry, multiple CAD and/or CSG models can be clipped, translated, rotated, and placed in overlapping layers to form transport-ready geometries. Here, the utility of this method is demonstrated with two problems: (1) a fixed-source simulation with a layered geometry consisting of a LiDAR-generated CAD model of the Combined Arms Collective Training Facility urban environment overlaid with CSG models of a mock hotel and a detector apparatus, and (2) a k-eigenvalue calculation using a layered geometry model of the Transformational Challenge Reactor consisting of CAD fuel elements placed in a CSG core. Tallied particle flux distributions match expectations, but tracking robustness must be improved prior to general-purpose use.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Modeling and analysis of heat emissions from buildings to ambient air

Heat emissions from buildings is a significant source of anthropogenic heat influencing the urban microclimate; however, they are usually oversimplified in urban climate and microclimate modeling. This study developed a bottom-up physics-based approach to calculate heat emissions from buildings to the ambient air and implemented the approach in EnergyPlus. In this work, a simple result verification was conducted by comparing the EnergyPlus simulated results against the spreadsheet calculations. Simulations covering 16 commercial building types, four climates, and two energy efficiency levels were conducted to understand and evaluate the building heat emissions and their temporal patterns as well as three major components: (1) building envelope (convective heat transfer to ambient air), (2) zones (air exfiltration and exhaust air), and (3) HVAC systems (relief air and heat rejection from condensers or cooling towers). The main findings are: (1) heat emissions are usually higher than the site energy use (about 2.5 times), and their dynamics should be considered; (2) building characteristics and their energy systems lead to differences in heat emission contributions from the three components, and their dynamics, for example, in the warehouse models, the envelope component accounts for 90.4%, while it is 12.7% for the large office models; (3) for most building typologies, the climate has a strong impact on heat emissions, for example, buildings with dominant heat emissions from the zone exhaust air and/or the HVAC reject heat, a general decrease in heat emissions in hotter climates is observed, while envelope-dominated buildings show the opposite; and (4) building technologies that reduce energy use in buildings may perform differently in reducing heat emissions. The developed heat emissions calculation method can be adopted in EnergyPlus and most other building energy modeling programs. It can provide dynamic building heat emissions as an input to urban climate computational fluid dynamics (CFD) models at a higher spatial and temporal resolution than is currently available, to improve the simulation accuracy of the urban microclimate and capture the urban heat island effect and urban overheating.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Bayes_Opt-SWMM: A Gaussian process-based Bayesian optimization tool for real-time flood modeling with SWMM

Real-time flood model plays a pivotal role in averting urban flood damage, particularly when there is minimal lead time for preparatory measures. However, urban flood modeling in real-time often contends with inherent uncertainties arising from input data uncertainty and parameter ambiguities. Here this study introduces a real-time calibration (RTC) tool called Bayes_Opt-SWMM, specifically tailored for real-time urban flood modeling and uncertainty optimization. This tool leverages the Gaussian process-based Bayesian optimization algorithm and interfaces seamlessly with the Stormwater Management Model (SWMM). It integrates real-time model forcing data and flood monitoring collected through sensors and gauges which are strategically placed within critical locations of urban drainage systems. Our approach hinges on the Surrogate Model based Uncertainty Optimization (SMUO) concept, providing an avenue for enhancing real-time flood modeling. Bayes_Opt-SWMM runs the optimization process using a surrogate model called Gaussian Process emulator with two inference methods: (1) the Gaussian Process (GP) model and (2) Markov Chain Monte Carlo (MCMC) algorithm in GP model (GP_MCMC). Furthermore, three acquisition functions, namely Expected Improvement (EI), Maximum Probability of Improvement (MPI), and Lower Confidence Bound (LCB), facilitate optimal parameter fitting within the surrogate models. The efficiency of GP-based surrogate models in learning SWMM model parameters, leads to an improved uncertainty quantification and accelerated real-time flood modeling in urban areas. Overall, Bayes_Opt-SWMM emerges as a cost-effective and valuable tool for real-time flood modeling and monitoring, with significant potential for managing intelligent storm water systems in urban environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Decontamination of urban surfaces contaminated with radioactive materials and consequent onsite recycling of the waste water

Enhancing rapid remediation strategies is paramount for recovery after a large-scale nuclear contamination event in an urban environment. Some current strategies recommend use of readily available equipment, materials, and facilities to expedite recovery. For example, applying pressurized water to contaminated surfaces may effectively remove radioactive contamination. In this study, a commercial power washer removes soluble forms of 152 Eu 3 + , 85 Sr 2 + , and 137 Cs + contamination from common porous building materials, and computer simulations characterize the recycling of the resultant contaminated wash water. Pressure washing the porous building materials under spray conditions typical with do-it-yourself units improved decontamination factors (DFs) for 152 Eu compared to low-pressure application of tap water (majority of two-tailed t-test p-values < 0.1), but pressure did not improve DFs for 137 Cs or 85 Sr. For both pressurized and low-pressure applications, adding potassium ions (K + ) to promote ion exchange reactions produced significantly higher DFs for tested radionuclides on asphalt, brick, and concrete. The resultant contaminated wash water can be processed through self-prepared chemical filtration beds of clay and sand. Modeled in a prior study, the beds yielded linear trends (R 2 > 0.98) in sensitivity analyses between most bed configuration variables and bed performance variables, permitting flexible ad-hoc bed design. The experimental and simulation results led to estimates of the remediation rate and waste generated after cleaning 250 m 2 of cesium-contaminated concrete from the combined deployment of a power washer and two different mobile treatment beds. Furthermore, the first treatment bed was designed to reduce treatment time and processed 1900 L of wash solution in 70 min using 880 kg of clay/sand infill material. Designed to reduce the solid waste generated, the second bed processed the same solution volume in 1040 min (17 h) using 170 kg of clay/sand infill material. The results of this analysis warrant further investigation of power washing with recycled salt solution as an effective rapid decontamination method with manageable waste.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Deployment of a double scatter system for directional detection of background neutron radiation

The detection of special nuclear materials (SNM) requires the understanding of nuclear signatures that allow the discrimination against background. In particular, understanding neutron background characteristics such as count rates and energies and their correlations with environmental conditions and surroundings of measurement locations is important in enhancing SNM detection capabilities. The Mobile Imager of Neutrons for Emergency Responders (MINER) was deployed for 8 weeks in downtown San Francisco (CA) to study such neutron background characteristics in an urban environment. Of specific interest was the investigation of the impact of surrounding buildings on the neutron background count rates and to answer the question whether buildings act as absorber of neutrons or as sources via the so-called ship effect. MINER consists of 16 liquid scintillator detector elements and can be operated as a neutron spectrometer, as a neutron imager, or simply as a counter of fast neutrons. As expected, the neutron background rate was found to be inversely proportional to the atmospheric pressure. In the energy range where MINER is most sensitive, approximately 1–10 MeV, it was found that the shape of the detected background spectrum is similar to that of a detected fission spectrum, indicating the limited discrimination power of the neutron energy. The similarities between the detected background neutron spectrum and fission sources makes it difficult to discriminate SNM from background based solely on the energies observed. The images produced using maximum likelihood expectation maximization revealed that neutrons preferentially are coming from areas in the environment that have open sky, indicating that the surrounding buildings act as absorbers of neutrons rather than sources as expected by the ship effect. Here, the inherent properties of a neutron scatter camera limit the achievable image quality and the effective deployment to systematically map neutron background signatures due to the low count rate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Impact of Extreme Heat on Emergency Department Admissions for Childhood and Adult Asthma: An Evaluation of Earth Observations and Heat Wave Definitions

Extreme heat has been associated with adverse health outcomes, yet its impact on asthma exacerbations remains understudied. This is, in part, due to data limitations: research that relies on weather station records and aggregated health statistics cannot resolve fine-scale differences in heat impacts. This study investigates the association between heat wave definitions and summertime asthma-related emergency department visits in Baltimore, Maryland from 2016 to 2022, including 819 adult and 695 pediatric exacerbations. Using geocoded electronic health records and air temperature measurements at several spatial resolutions, we applied a case-crossover design with conditional logistic regressions at the census block group and tract levels. We found strong associations between asthma exacerbations and nighttime heat wave definitions based on relative thresholds of minimum temperatures when census block group or tract level temperature estimates were used. These relationships were significant for both age groups and showed elevated risks in socially vulnerable areas. In contrast, heat wave definitions derived from the city's primary National Weather Service synoptic weather station show associations between asthma and daytime heat extremes, suggesting that the character of the heat hazard depends on the scale at which it is defined. The extreme heat event definition used by Baltimore City's Code Red system showed no significant association with exacerbations. These findings highlight the importance of data resolution in shaping health inferences related to extreme heat in urban environments. Further, this study demonstrates that, regardless of spatial scale, extreme heat is associated with asthma exacerbations in both age groups.

Corpuz, B. [Johns Hopkins University, Baltimore, M↗
DOE OSTI2026

Importance of Spatially Continuous Urban Surface Properties in Urban‐Resolving Earth System Modeling

Accurate representation of urban properties and processes at higher resolutions in global modeling systems is essential for advancing our ability to capture the complexities of urban systems and informing effective resilience strategies. However, the prescription of coarse global-scale urban properties in most state-of-the-art Earth system models (ESMs) is limiting their potential for capturing urban signals as they advance toward kilometer-scale simulation capabilities. To bridge this gap in inadequate urban property representation and to advance urban-resolving Earth system modeling, this work integrates the newly-developed global 1 km-resolution facet-level urban surface property data set, U-Surf, into the land component of Community Earth System Model (CESM)—Community Terrestrial System Model (CTSM). The land-only CTSM simulations are validated against satellite measurements, ground-based urban weather stations, flux tower observations, and reanalysis data. Results demonstrate that the enhanced urban properties allow improved simulations of urban meteorology and surface energy fluxes compared to the default coarse-resolution categorical urban canopy parameters. Spatial scaling analysis reveals regime-dependent information loss during resolution aggregation, as well as substantial scale-dependent variations in urban surface energy flux representation. Furthermore, these findings have critical implications for coupled Earth system modeling when including the effect of land-atmosphere interaction. This work establishes a foundation for future urban-resolving kilometer-scale ESM development, which will enable systematic intra- and inter-city comparisons that inform urban adaptation strategies across diverse global urban environments.

Cheng, Yifan [University of Illinois Urbana-Champa↗
DOE OSTI2026

Compound flood simulations indicate rising public exposure to sewage-contaminated waters in Waikīkī, Hawai‘i

Waikīkī, Hawai‘i serves as a valuable case study for flood vulnerability due to its low elevation, present-day exposure to multiple flood sources, and role as the state’s economic engine. This study applies the high-resolution, open-source WRF-Hydro-CUFA (Coastal Urban Flood Application) model to simulate compound flood interactions among pluvial, fluvial, coastal, storm drain-driven, and subsurface processes, and to evaluate how flood characteristics in Waikīkī evolve under projected sea-level rise (SLR). Simulated water levels in an estuarine drainage canal, serving as the primary outlet for gravity-flow drainage from Waikīkī, show strong agreement with observations (r ≥ 0.935, R 2 ≥ 0.874), accurately reproducing flooding observed during recent 5-year and 50-year storm events. Simulations incorporating SLR demonstrate a shift in dominant flood drivers as sea levels rise. In addition, results identify critical thresholds at which elevated estuarine tailwater conditions cause widespread drainage backflow, eventually occurring in the absence of rainfall. These findings suggest that tidally driven flooding will progressively dominate over rainfall-driven events, increasing public exposure to highly contaminated canal and groundwater sources. The results underscore the urgent need to integrate water quality issues and drainage failure into coastal flood management strategies for low-lying urban environments, particularly those reliant on polluted estuarine waterways for stormwater management.

Compound flooding↗
DOE OSTI2026

Lab-Scale Cable-Driven Parallel Robot Prototype for Automated Prefabricated Component Manipulation

This paper presents the design and evaluation of a lab-scale cable-driven parallel robot (CDPR) developed as a flexible platform for automated installation of prefabricated components onto exterior building envelopes. Traditional manual installation methods for prefabricated components, which depend on scaffolding, cranes, cherry pickers, and verbal coordination, are not only labor-intensive and error-prone but also face significant limitations in dense urban environments due to site access constraints. To address these challenges, we developed a lab-scale CDPR platform capable of autonomously transporting building envelope components from a designated pickup zone to their target installation location, minimizing the need for human intervention. This study describes the system’s mechanical design, actuation architecture, real-time feedback system, and control strategy of the CDPR, and evaluates its performance in a laboratory environment. The robot’s actuation system uses torque control for end-effector manipulation. The robot’s real-time pose feedback comes from a construction-grade total station and a wireless inertial measurement unit (IMU), which together support precise end-effector control. Experimental results demonstrate the successful integration of the hardware, sensing, state estimation, and control subsystems. Preliminary tests showed that our lab-scale prototype can position the end effector with an error of less than 3 mm, which is a level of precision not previously achieved by existing CDPRs in construction applications. The key findings are twofold: (1) torque-only control is necessary but not sufficient for minimizing final pose error, and (2) incorporating real-time pose feedback can achieve the desired placement accuracy.

Liu, Yifang [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2026

Mechanistic Investigation of Co(II) Extraction by TODGA to Aid Nuclear Forensic Separations

Nuclear forensic (NF) analysis supports law enforcement inquiries by analyzing evidence tainted with radioactive substances. Separation techniques can be used to identify and quantify actinides and fission 15 products in post-detonation (PD) debris. Environmental transition metals, also present in PD residues, have been observed to impact critical isotope extractions. For example, radio stable cobalt (Co), ubiquitous in urban environments, particularly in corrosion-resistant alloys, paint-drying agents, dyes, and pigments, can impact the separation of important actinides and fission products. The presented work aims to elucidate the chemistry Q2 governing Co extraction in samples pertinent to PDNF. Chemistry between Co and N,N,N,‘N’-tetraoctyl diglyco- 20 lamide (TODGA), the ligand present in the commercial chromatographic resin diglycolamide (DGA), were studied via solvent and chromatographic extraction and spectroscopic analyses. These results indicate that a tetrahedral Co(II) species is extracted by TODGA from highly acidic (>5M HCl) solutions via a spontaneous entropy-driven reaction. Furthermore, extraction trends in varied acid concentrations are consistent between solvent extraction and chromatographic extraction methods.

activation product↗
DOE OSTI2023

Minimizing Ground Risk in Cellular-Connected Drone Corridors With mmWave Links

Unmanned Aircraft Systems (UASs) have been receiving significant interest and support from academia, industry, and regulatory bodies over the past decade due to their various use cases. To safely integrate UAS operations into the national airspace, particularly overpopulated regions, the risk posed to ground users, buildings, and vehicles due to unmanned aerial vehicle (UAV) flight should be minimized. This risk can be represented by a numerical metric, which we refer to in this article as the “ground risk.” Many UAS applications also depend on the presence of a reliable wireless communication link between the UAV and a control station for the transmission of UAV position, surveillance video, UAV payload commands, and other mission-related data. Such wireless communication requirements also need to be considered in the design of UAS operations. In this article, we consider both these aspects and study the design of nonintersecting trajectories for UAS operations to minimize ground risk, subject to constraints on the wireless signal strength and geometry of the trajectory, specified in terms of: 1) an enclosing cylinder within which the trajectory must lie and 2) an integrated angular change along the UAV's trajectory. The performance of a computationally expensive optimal algorithm is compared with that of a computationally faster heuristic approach within the dense urban environment of Manhattan, NY, USA. Performance evaluation using ray-tracing simulations shows that the heuristic approach performs close to the optimal algorithm at a reduced computation cost. In conclusion, this research can be utilized to make UAS operations safe and reliable and accelerate their adoption.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Improved Gas Plume Identification Using Nearest Neighbor Methods for Background Estimation

Longwave infrared (LWIR) hyperspectral imaging (HSI) can be used for many tasks in remote sensing, including detecting and identifying effluent gases by LWIR sensors on airborne platforms. Identification is used after detection to increase confidence in weakly detected plumes, reduce false positives from detection, and distinguish between similar and confounding material signatures. Background estimation is an important step used to reveal the unique spectral characteristics of the detected gas, allowing the identification model to determine what the gas is specifically. The importance of proper background estimation increases when dealing with weak signals, large libraries of gases of interest, and uncommon or heterogeneous backgrounds. In this article, we propose two methods for background estimation: a novel k-nearest segments (KNS) algorithm and the standard k-nearest neighbors (KNN) algorithm. We test our methods and three existing background estimation methods for comparison against global background estimation to determine which performs best at estimating the true background radiance under a plume and for increasing identification confidence using a neural network classification model. We compare the different methods using 640 simulated weak plumes in an urban environment. For identification, our KNS algorithm improves median neural network identification confidence by 53.2%. For background radiance estimation, the KNN algorithm provides a median of 49 times less RMSE than global background estimation. Furthermore, KNN is the easiest method to tune for different plumes, making it an excellent “out of the box” background estimator.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Simulations of Sparse Static Detector Networks for City-Scale Radiological/Nuclear Detection

Sparse static detector networks in urban environments can be used in efforts to detect illicit radioactive sources, such as stolen nuclear material or radioactive "dirty bombs." We use detailed simulations to evaluate multiple configurations of detector networks and their ability to detect sources moving through a $6\times 6$ km 2 area of downtown Chicago. A detector network's probability of detecting a source increases with detector density but can also be increased with strategic node placement. Here, we show that the ability to fuse correlated data from a source-carrying vehicle passing by multiple detectors can significantly contribute to the overall detection probability. In this article, we distinguish static sensor deployments operated as networks able to correlate signals between sensors, from deployments operated as arrays where each sensor is operated individually. In particular, we show that additional visual attributes of source-carrying vehicles, such as vehicle color and make, can greatly improve the ability of a detector network to detect illicit sources.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2026

Characterization of Precipitation-Induced Radon Progeny Deposition Events Using a City-Scale Sensor Network

Networks of radiation detectors provide a platform for real-time radioactive source detection and identification in urban environments. Detection algorithms in these systems must adapt to naturally-occurring changes in background, which requires well-characterized relationships between precipitation events and their corresponding radiological signature. Here, we present a quantitative and qualitative description of rain-induced radon progeny deposition events occurring in Chicago from September 2023 to February 2024. We measure ambient gamma radiation levels, precipitation rate, temperature, pressure, and relative humidity in a network of sensor nodes. For each identified precipitation period, we decompose spectra into static- and radon-associated components as defined by a non-negative matrix factorization (NMF) algorithm. We find a consistent power-law relationship between a precipitation-dependent peak of the radon progeny proxy (RPP) and the peak strength of the radon-associated NMF component for most precipitation events. We conduct a case study of a rainfall period with abnormally high levels of implied radon progeny concentration and describe its temporal and spatial evolution. We hypothesize that this phenomenon is due to the air mass path that intersects a uranium-rich region of Wyoming. Finally, we cluster precipitation events into three distinct categories. One category roughly corresponds to events with deep low-pressure systems and high relative radon concentration, while another is characteristic of light stratiform rain with slightly higher temperatures and intermediate relative radon concentration. The third category appears to contain weak-gradient or lake breeze convection showers with intermittent precipitation and low relative radon concentration. These findings suggest that radiological anomaly detection could be improved by training unique background models corresponding to each category of meteorological event.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

RADAI: A Large-Scale Realistic Dataset for Radiation Detection Algorithm Development

Open, realistic datasets are essential for developing and benchmarking radiation detection algorithms, yet they remain scarce. The Radiological Anomaly Detection and Identification (RADAI) project was develop to create datasets that meet the training and testing needs for sophisticated radiation detection algorithms. The RADAI dataset is a large-scale synthetic resource that integrates high-fidelity Monte Carlo simulations with realistic urban scenarios to capture both background variability and source signatures. RADAI models construction-material NORM, people and vehicles, urban clutter, and dynamic environmental effects such as cosmic-ray and rain-induced transients, and they provide list-mode detector data with motion and response modeling suitable for algorithm training and evaluation. The RADAI project resulted in three publicly-released complementary datasets together with an online scoring portal for standardized performance assessment and an open software toolkit that supports data access, augmentation, model development, and evaluation. These resources enable reproducible comparisons across methods and promote rigorous studies at the scale required by contemporary machine learning. By grounding algorithm development in realistic, well-documented conditions, RADAI supports progress toward more robust detection, identification, and localization in complex urban environments.

Ghawaly, James M. [Division of Computer Science an↗
DOE OSTI2026

Unified Modeling Architecture for Load Management in Extreme Heat: The New York City Case

Integration of renewable resources to meet growing energy demand is becoming a global priority under decarbonization mandates. This study contributes to ongoing efforts on this key subject by assessing the feasibility of using coastal-urban renewable energy resources, namely, offshore wind and rooftop photovoltaic systems, to meet electricity demand of New York City during the intense recent heat wave period of June 2025. A unified modeling framework, based on the urbanized weather research and forecasting model, is used to simulate climate, renewable resources, and energy demand variables. Findings show significant energy load mismatch of approximately 1150 GWh over the month, between the demand and the combined renewable generation outcome. Three storage integration scenarios are analyzed to mitigate the deficits, reducing said deficits by a minimum of approximately 9% over the duration of the month. This study provides a transferable modeling framework tool for evaluating renewable integration in dense urban environments that can be used by grid operators to support grid resilience during extreme heat events.

54 ENVIRONMENTAL SCIENCES↗