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

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

How Could Future Climate Conditions Reshape a Devastating Lake‐Effect Snow Storm?

Abstract Lake‐effect snow (LES) storms, characterized by heavy convective precipitation downwind of large lakes, pose significant coastal hazards with severe socioeconomic consequences in vulnerable areas. In this study, we investigate how devastating LES storms could evolve in the future by employing a storyline approach, using the LES storm that occurred over Buffalo, New York, in November 2022 as an example. Using a Pseudo‐Global Warming method with a fully three‐dimensional two‐way coupled lake‐land‐atmosphere modeling system at a cloud‐resolving 4 km resolution, we show a 14% increase in storm precipitation under the end‐century warming. This increase in precipitation is accompanied by a transition in the precipitation form from predominantly snowfall to nearly equal parts snowfall and rainfall. Through additional simulations with isolated atmospheric and lake warming, we discerned that the warmer lake contributes to increased storm precipitation through enhanced evaporation while the warmer atmosphere contributes to the increase in the storm's rainfall, at the expense of snowfall. More importantly, this shift from snowfall to rainfall was found to nearly double the area experiencing another winter hazard, Rain‐on‐Snow. Our study provides a plausible future storyline for the Buffalo LES storm, focusing on understanding the intricate interplay between atmospheric and lake warming in shaping the future dynamics of LES storms. It emphasizes the importance of accurately capturing the changing lake‐atmosphere dynamics during LES storms under future warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Impact of New Physics on the JUNO-Long-Baseline Synergy in Neutrino Mass Ordering Determination

The determination of the neutrino mass ordering is one of the flagship goals in particle physics. A well-known and powerful synergy emerges when combining high-precision measurements of the effective atmospheric mass-squared splitting from electron antineutrino disappearance in reactor experiments with that from muon (anti)neutrino disappearance in accelerator-based long-baseline experiments. To fully exploit this synergy, percent-level precision in the atmospheric mass splitting is required-a target that JUNO is expected to achieve within a few months of data taking. This motivated the formulation of a mass ordering sum rule for neutrino disappearance channels, which shows that by combining data from T2K and NOvA with JUNO after one year of operation, the neutrino mass ordering can be determined at the $3σ$ confidence level. Since JUNO has recently started taking data, it is timely to ask whether this sum rule remains robust in the presence of new physics. We identify the necessary conditions for new physics to affect the sum rule and demonstrate that, in some cases, such effects could lead to an incorrect inference of the mass ordering. As concrete examples, we consider Scalar Non-Standard Interactions (SNSI) and neutrinos coupled to an ultralight scalar field. We find that, for SNSI, current constraints render any modification of the sum rule negligible, whereas in the latter case, the inference of the ordering requires caution. Nevertheless, these effects can be disentangled, illustrating how the sum rule can also be used to search for new physics.

Alves, Gustavo F.S. [Fermilab; Northwestern U.; Sa↗
DOE OSTI2024

Modification of wind turbine wakes by large-scale, convective atmospheric boundary layer structures

In this study, we consider the impact of large-scale, convective structures in an unstable atmospheric boundary layer on wind turbine wakes. Simulation data from a high-fidelity large-eddy simulation (LES) of the AWAKEN wind farm site matching unstable atmospheric conditions were analyzed, and both turbine performance and wake behavior were affected based on their location relative to the convective structures. Turbines located in updraft regions of the flow experienced lower inflow velocity and generated less power, but their wakes were observed to recover faster and saw greater turbulent kinetic energy mixing higher in the boundary layer. The opposite effect was found for turbines in the downdraft regions of the convective structures. A simplified model of this wake behavior was also developed based on a two-dimensional k–ε Reynolds-Averaged Navier–Stokes formulation. This simplified model included the effects of vertical transport, but could be efficiently solved as a parabolic system, and was found to capture similar wake modifications observed in the high-fidelity LES computations.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Anomalous softening of 3D printed elastomeric foam irradiated under compressive strain

Elastomeric foam is an essential component in many industrial and technological settings, primarily as thermal insulators and as positional/mechanical support cushions. In particular, silicone foam is utilized in harsh environments due to exceptional thermal and chemical stability. Under service conditions within certain applications such material gets exposed to a high dosage of gamma radiation, which can permanently alter the material’s structural and mechanical response properties. Most studies on gamma-exposure under inert or oxidative atmosphere indicate hardening of silicone foam, which is attributed to radiation-induced enhancement in chemical cross-linking. Here we report two contrasting effects depending on whether (non-oxidative) radiation exposure is carried out with the foam under zero or finite compressive strain. While in the former case we observe radiation-hardening consistent with previous studies, in the latter case (50% porous foam under 30% uniaxial compression) we see a monotonic decrease in Young’s modulus with increasing dosage, although solvent swelling experiments on the constituent rubber indicate a net increase in cross-link density independent of the state of strain. We quantitatively model all dose-dependent data using the Ogden Hyperfoam strain-energy function within the framework of Tobolsky two-network scheme and attribute the above anomaly to a combined effect of radiation-induced thickness change (compression set) and inherent nonlinearity in the foam’s stress-strain response.

Coarse-grained models↗
DOE OSTI2025

Predictive numerical modeling of plasma-induced surface roughness and wettability evolution in LM-PAEK/CF tape

Plasma surface modification effectively enhances adhesion in thermoplastic composites, yet its impacts on high-performance polymers like low-melting polyaryletherketone (LM-PAEK) remain inadequately quantified. Here, this study integrates experimental analysis and numerical modeling to characterize surface roughness and wettability changes in LM-PAEK/carbon fiber composites treated with atmospheric plasma. Atomic Force Microscopy quantified surface topography (n = 10 per condition for contact angles), while static contact-angle assessments measured wettability. Roughness rapidly increased from ∼0.2 nm to 1.6 nm, and contact angle reduced from ∼90° to 24°, both stabilizing after 25–30 s of exposure. A semi-empirical, physics-informed framework was calibrated to these data, coupling surface chemistry via the Owens–Wendt decomposition with topography via the Wenzel roughness factor, and evaluated using out-of-sample (cross-validated) tests, while static contact angle assessments measured wettability. Numerical predictions matched experimental results closely (RMSE <5%, R 2 > 0.95). Incorporating material-specific parameters, the calibrated model supports plasma-treatment optimization and provides quantitative guidance for improving interfacial adhesion in thermoplastic composite manufacturing.

Atomic Force Microscopy↗
DOE OSTI2025

Influence of background sources and topographic resolution in the Weather Research and Forecasting Model on xenon plume characteristics at monitoring stations

For many atmospheric monitoring applications, networks of measurement sites—such as the radionuclide stations of the International Monitoring System—can be sparse. With measurement locations potentially hundreds to thousands of kilometers from a release it is important to quantify the effects of physical processes on transport and dispersion of plumes between source and measurement locations. This study addresses the effects of background sources and topography resolution near the release location of radionuclides. We use the Weather Research and Forecasting (WRF) model with inline chemistry to investigate (1) how an additional, time-varying source of 133 Xe, such as an operational medical isotope production facility, contributes to activity concentration measurements at monitoring sites, and (2) how complex topography influences on atmospheric conditions near emission sources impact plume concentrations at varying distances from the source. Two 133 Xe emission sources, including (1) a high flux rate of short duration representing an explosive event, and (2) a variable and continuous background source, are simulated. The continuous background source contributes significantly to total 133 Xe concentrations at several monitoring stations. Further, a WRF simulation at 9 km horizontal resolution is compared with a nested grid simulation, where the innermost domain has a resolution of 1 km. Increased topographic resolution leads to an improved representation of plume responses to local winds, with topographic influences greatest at locations closest to the sources. Differences between the two domain resolutions decrease at greater distances from the sources, as plumes have time to spread and mix and are influenced by synoptic scale circulation patterns that are represented similarly in both simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Worldwide benchmarking of cost-effective radiometers for direct and diffuse irradiance

Solar energy projects can benefit from direct normal irradiance (DNI) and diffuse horizontal irradiance (DHI) measurements during all project phases. Several commercial measurement systems for DNI and DHI are available. Sun trackers with pyranometers and pyrheliometers can provide highly accurate measurements but are often impractical in solar energy applications. For less expensive and more robust sensors, it is often unclear which accuracy can be expected under a project site's specific atmospheric conditions. We address this challenge through our dedicated experimental comparison of relevant sensor systems (rotating shadowband irradiometer [short RSI], Delta-T SPN1, EKO MS-90, PyranoCam, Sunto CaptPro, Kipp & Zonen CSD3) at up to six sites worldwide. The RSI systems (rRMSD 3 to 8.6%, DNI; 4.8 to 7.6%, DHI) and PyranoCam (rRMSD 2.6 to 5.2%, DNI; 4.4 to 5.8%, DHI) exhibit similar error metrics and are the most accurate systems in the test. Delta-T SPN1 and EKO MS-90 (rRMSD 6.8 to 15%, DNI; 10.6 to 20.1%, DHI) but especially Kipp & Zonen CSD3 and Sunto CaptPro show significant deviations (rRMSD 17.7 to 20%, DNI; 33 to 58%, DHI). We evaluate the influence of relevant atmospheric parameters on the sensors' accuracies by a rather unique measurement setup. MS-90's DNI errors depend on DNI itself, with overestimations for low reference DNI. The deviations of SPN1's DHI and DNI measurements increase sharply in situations with high circumsolar irradiance. Also CaptPro and CSD3's increased measurement errors are related to circumsolar irradiance. For RSI and PyranoCam, only moderate influences on the measurements are identified, indicating a general applicability of these instruments.

14 SOLAR ENERGY↗
DOE OSTI2025

Effects of Water Vapor on the Reactivity of Aluminosilicates in Vapor-Phase Propanal Aldol Condensation

Aluminosilicate materials have been extensively studied as efficient aldol catalysts for C-C coupling reactions due to their acidic nature, high surface area, thermal stability, and porous structure. This work investigated the impact of water vapor pressure on the catalytic reactivity of aluminosilicates for the aldol condensation of propanal to 2-methyl-2-pentenal (MP). The catalytic performance of amorphous SiO2-Al2O3 (A-Si-Al) and aluminated MCM-41 (Al-MCM-41) for the vapor-phase aldol condensation of propanal was evaluated at 200 degrees C as a function of vapor-phase water content at atmospheric pressure. Our findings demonstrate that co-feeding low water vapor pressures (1-18 kPa) with propanal enhances the rates of MP production at 200 degrees C on A-Si-Al. Conversely, water vapor pressures of 25 kPa result in a decrease in aldol dimer formation rates. The rate of MP production evaluated on Al-MCM-41 also increased in the presence of 5 kPa water compared to anhydrous conditions. Propylamine temperature-programmed desorption analyses revealed an increase in Bronsted acid site density when both catalysts were exposed to water, which likely accounts for the observed enhancement in aldol condensation reactivity under hydrous conditions. Reversibility testing of the water vapor effect under reaction conditions, combined with X-ray diffraction analysis of fresh, spent, and regenerated catalysts, revealed no structural changes in either aluminosilicate upon exposure to water or reaction conditions. The rates of aldol condensation and the impact of water vapor were highly consistent across both materials, suggesting that zeolite crystallinity has minimal influence on the catalytic performance.

acid catalysts↗
DOE OSTI2024

Controls on Stable Methane Isotope Values in Northern Peatlands and Potential Shifts in Values Under Permafrost Thaw Scenarios

Abstract Northern peatlands are a globally significant source of methane (CH 4 ), and emissions are projected to increase due to warming and permafrost loss. Understanding the microbial mechanisms behind patterns in CH 4 production in peatlands will be key to predicting annual emissions changes, with stable carbon isotopes (δ 13 C‐CH 4 ) being a powerful tool for characterizing these drivers. Given that δ 13 C‐CH 4 is used in top‐down atmospheric inversion models to partition sources, our ability to model CH 4 production pathways and associated δ 13 C‐CH 4 values is critical. We sought to characterize the role of environmental conditions, including hydrologic and vegetation patterns associated with permafrost thaw, on δ 13 C‐CH 4 values from high‐latitude peatlands. We measured porewater and emitted CH 4 stable isotopes, pH, and vegetation composition from five boreal‐Arctic peatlands. Porewater δ 13 C‐CH 4 was strongly associated with peatland type, with δ 13 C enriched values obtained from more minerotrophic fens (−61.2 ± 9.1‰) compared to permafrost‐free bogs (−74.1 ± 9.4‰) and raised permafrost bogs (−81.6 ± 11.5‰). Variation in porewater δ 13 C‐CH 4 was best explained by sedge cover, CH 4 concentration, and the interactive effect of peatland type and pH (r 2 = 0.50,p < 0.001). Emitted δ 13 C‐CH 4 varied greatly but was positively correlated with porewater δ 13 C‐CH 4 . We calculated a mixed atmospheric δ 13 C‐CH 4 value for northern peatlands of −65.3 ± 7‰ and show that this value is more sensitive to landscape drying than wetting under permafrost thaw scenarios. Our results suggest northern peatland δ 13 C‐CH 4 values are likely to shift in the future which has important implications for source partitioning in atmospheric inversion models.

Environmental Sciences & Ecology↗
DOE OSTI2025

Dependence of Convective Cloud Microphysical Properties on Environmental Conditions during the TRACER and ESCAPE Field Campaigns: A Synergistic Approach of Observations, Machine Learning and Parcel Models

The sensitivity of convective clouds to aerosols and their interactions with environment, combined with limited observational constraints in parameterizations, introduces significant uncertainties in atmospheric models. Here, this study investigates the dependence of convective cloud microphysical properties on environmental conditions using a synergistic approach that combines unique observations from the TRACER and ESCAPE field campaigns, machine learning techniques, and parcel model simulations with a super-droplet microphysics scheme. A random forest algorithm identifies in-situ vertical velocity (w), temperature (T), and surface fine-mode aerosol mass concentration as the three most important environmental conditions influencing cloud properties including liquid water content (LWC), number concentration for particles with D max < 50 μm (N c ,<50), 50 μm ≤ D max ≤ 3000 μm (N c,50–3000 ), and droplet effective diameter (D e ). Results show that LWC, N c,<50 , and N c,50–3000 significantly increase with w in updrafts. Across w bins, as T decreases, LWC, D e , and N c,50–3000 increase, while N c,<50 decreases, which are closely linked to the distance above cloud bases. Warmer cloud bases yield higher LWC, greater N c,50–3000 , and smaller N c,<50 , while polluted environments produce greater N c,<50 . Parcel model simulations successfully replicate these observed dependencies. The simulation results indicate that warmer cloud bases enhance condensation generating larger droplets, and differences in droplet sizes are then amplified through collision-coalescence, resulting in a greater N c,50–3000 . Polluted conditions result in a greater N c,<50 primarily due to enhanced cloud condensation nuclei activation despite increased collision-coalescence rates compared to pristine conditions. This study provides observed quantitative patterns characterizing cloud microphysical properties as a function of key environmental parameters, offering valuable constraints for improving physics parameterizations and numerical models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Heat Loss Effects on Emissions in an NH 3 RRQL Combustor

Ammonia (NH 3 ) is a carbon-free energy carrier with an infrastructure for production, storage, and distribution. There is interest in direct NH 3 combustion, but managing pollutant emissions is a key challenge, particularly nitric oxides (NO x ) due to the fuel-bound nitrogen atom, nitrous oxide (N 2 O), which is a potent greenhouse gas, and unburned NH 3 , which is harmful to humans and the environment. Rich staged combustor concepts with extended primary residence times (τ res,primary ), like Rich-Relax- Quick-mix-Lean (RRQL), offer a viable pathway for direct NH 3 combustion with low levels of NO x formation. However, minimizing secondary emissions such as N 2 O and unburned NH 3 and hydrogen (H 2 ) remains a critical challenge. Prior atmospheric-pressure studies have demonstrated that RRQL operation with sufficiently long τ res,primary enables substantial NO x relaxation and promotes NH 3 cracking to H 2 , if heat losses from the relaxation stage are limited. However, the combined influence of elevated pressure and long residence time on RRQL performance has not been explored. The present work examines RRQL operation at pressures up to 5 bar and elevated τ res,primary . Exhaust measurements of NO x , NH 3 , and N 2 O are used to quantify the extent of NO x relaxation and NH 3 cracking under nonadiabatic conditions. To contextualize and quantify the effects of heat losses in the experimental data, chemical reactor networks (CRNs) incorporating prescribed heat loss rates are employed to assess the sensitivity of emissions to thermal losses in the relaxation stage. Collectively, the results demonstrate that management and quantification of heat losses are essential to preserve NO x relaxation and limit NH 3 and N 2 O emissions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Electron Microscopy Transfer System to Protect Atmosphere‐Sensitive Materials for Scanning Electron Microscopy Characterization

Atmosphere- and/or moisture-sensitive materials can be challenging to characterize using electron microscopy techniques due to sample preparation workflows that generally require exposure to ambient conditions. Here, we describe a novel preparation method that uses aluminum foil in combination with a commercial cryo-EM transfer system to circumvent undesired exposure to the atmosphere. First, hygroscopic MgCl 2 was used as a model material, and prepared samples (both protected and unprotected) were placed in a controlled-humidity environment (> 80% relative humidity) for various exposure lengths (circa seconds to hours). Following this, the effectiveness of the sample preparation method was determined by comparing qualitative photos and quantitative X-ray diffraction patterns between the two sample subsets. The combined results of these experiments suggest that the outlined preparation method effectively protects MgCl 2 from atmospheric contamination compared to MgCl 2 samples that had no protective measures taken. Finally, the preparation method was utilized to protect a highly hygroscopic crystalline BaO thin film for characterization via scanning electron microscopy, thereby demonstrating a functional application of the outlined preparation technique and an additional use for the commercial cryo-EM transfer system beyond its intended application.

atmosphere-sensitive materials↗
DOE OSTI2025

Geospatial Diffusion for Land Cover Imperviousness Change Forecasting

Land-use and land-cover (LULC) has a significant effect on several Earth system processes. For example, impervious surfaces reduce infiltration and speed water flow, impacting regional hydrology and flood risk. While Earth System models have improved forecasting hydrologic and atmospheric processes at higher resolutions, the ability to forecast LULC change has lagged behind. In this paper, we propose a new paradigm exploiting Generative AI (GenAI) for land cover change forecasting by framing it as a data synthesis problem conditioned on historical and auxiliary data-sources. To demonstrate the feasibility of our methodology, we perform experiments where a diffusion model is trained for decadal forecasting of imperviousness change across the entire United States. We find that our model yields MAE lower than a no-change baseline for resolutions ≥ 0.7 X 0.7km2 on average, demonstrating its ability to capture and project accurate spatiotemporal patterns. Finally, we discuss future research to incorporate Earth's physical properties and enabling scenario simulations via driver variables.

Varshney, Debvrat [ORNL] (ORCID:0000000188981736)↗
DOE OSTI2024

Ocean internal tides suppress tropical cyclones in the South China Sea

Abstract Tropical Cyclones (TCs) are devastating natural disasters. Analyzing four decades of global TC data, here we find that among all global TC-active basins, the South China Sea (SCS) stands out as particularly difficult ocean for TCs to intensify, despite favorable atmosphere and ocean conditions. Over the SCS, TC intensification rate and its probability for a rapid intensification (intensification by ≥ 15.4 m s −1 day −1 ) are only 1/2 and 1/3, respectively, of those for the rest of the world ocean. Originating from complex interplays between astronomic tides and the SCS topography, gigantic ocean internal tides interact with TC-generated oceanic near-inertial waves and induce a strong ocean cooling effect, suppressing the TC intensification. Inclusion of this interaction between internal tides and TC in operational weather prediction systems is expected to improve forecast of TC intensity in the SCS and in other regions where strong internal tides are present.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Modeling and observations of North Atlantic cyclones: Implications for U.S. Offshore wind energy

To meet the Biden-Harris administration's goal of deploying 30 GW of offshore wind power by 2030 and 110 GW by 2050, expansion of wind energy into U.S. territorial waters prone to tropical cyclones (TCs) and extratropical cyclones (ETCs) is essential. This requires a deeper understanding of cyclone-related risks and the development of robust, resilient offshore wind energy systems. Here, this paper provides a comprehensive review of state-of-the-science measurement and modeling capabilities for studying TCs and ETCs, and their impacts across various spatial and temporal scales. We explore measurement capabilities for environments influenced by TCs and ETCs, including near-surface and vertical profiles of critical variables that characterize these cyclones. The capabilities and limitations of Earth system and mesoscale models are assessed for their effectiveness in capturing atmosphere–ocean–wave interactions that influence TC/ETC-induced risks under a changing climate. Additionally, we discuss microscale modeling capabilities designed to bridge scale gaps from the weather scale (a few kilometers) to the turbine scale (dozens to a few meters). We also review machine learning (ML)-based, data-driven models for simulating TC/ETC events at both weather and wind turbine scales. Special attention is given to extreme metocean conditions like extreme wind gusts, rapid wind direction changes, and high waves, which pose threats to offshore wind energy infrastructure. Finally, the paper outlines the research challenges and future directions needed to enhance the resilience and design of next-generation offshore wind turbines against extreme weather conditions.

17 WIND ENERGY↗
DOE OSTI2024

High-Temperature Oxidation Behavior of Wrought and Additive Manufactured H282 in Direct-Fired Supercritical CO2 Power Cycle Environments

Materials selection is a key concern for corrosion resistance in high temperature and pressure direct-fired supercritical CO2 power cycles. The effect of elevated pressure on corrosion resistance can be critical, as impurities within the supercritical fluid such as H2O and O2 can result in additional corrosion behaviors. Utilizing additive manufacturing (AM) methods for construction of power cycle components requiring both compact and complex designs could be advantageous. AM H282 produced by laser powder bed fusion was exposed to direct-fired conditions (95CO2 – 4H2O – 1 O2) at 750 °C at both atmospheric pressure and supercritical conditions (20 MPa) for up to 4,000 hours. Oxidation behavior, sub-surface carbide formation, and chromia scale volatilization was dependent upon AM preparation techniques and surface modifications. These results are discussed in terms of the potential compatibility issues that may arise when using AM alloys in high temperature regions of direct-fired sCO2 power cycles, particularly for thin-walled components.

Carney, Casey↗
DOE OSTI2025

Radiological Safety Analysis Computer (RSAC) Program Version 7.4 Users’ Manual

The Radiological Safety Analysis Computer (RSAC) Program Version 7.4 (RSAC-7) is the newest version of the RSAC legacy code. RSAC-7 calculates the consequences of a release of radionuclides to the atmosphere. Users generates a fission product inventory from either reactor operating history or a nuclear criticality event. RSAC-7 models the effects of high-efficiency particulate air filters or other cleanup systems and calculates the decay and ingrowth during transport through processes, facilities, and the environment. Doses are calculated for inhalation, air immersion, ground surface, ingestion, and cloud gamma pathways. RSAC-7 is used as a tool to evaluate accident conditions in emergency response scenarios, radiological sabotage events, and safety basis accident consequences. This users’ manual contains the mathematical models and operating instructions for RSAC-7. Instructions, screens, and examples are provided to guide the user through the functions provided by RSAC-7. This program is designed for users who are familiar with radiological dose assessment methods.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Hydrogen Dispersion Modeling for Development of Smart Distributed Monitoring

Studying hydrogen dispersion is crucial for ensuring the safe and effective deployment of hydrogen as an energy carrier. This study presents a comprehensive CFD modeling framework for simulating hydrogen dispersion at a real-world hydrogen production, storage, and utilization facility. Utilizing the Hydrogen Research Facility under the Advanced Research on Integrated Energy Systems (ARIES) at the National Renewable Energy Laboratory's (NREL) Flatirons campus, controlled hydrogen releases at 27 kg-H2/hr were simulated. The model incorporated site-specific atmospheric conditions, including hourly wind speeds and temperatures recorded between 8 AM and 8 PM from October to December 2023. To reduce computational demands, a statistical reduction technique was applied to condense the dataset to 100 representative scenarios, validated by statistical tests for wind speeds and power law coefficients. Simulations were conducted using the Reynolds-Averaged Navier-Stokes equations. Results demonstrated that wind speed substantially influences hydrogen dispersion, with low wind conditions forming concentrated clouds and higher wind speeds stretching the plume. Additionally, clustering analysis informed optimal sensor placement at various elevations with up to 10 sensor locations on each elevation. This framework offers a robust approach for understanding hydrogen behavior in ambient conditions and informing detection strategies.

08 HYDROGEN↗