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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↗

Filament-induced breakdown spectroscopy of solids through highly scattering media

Ultrafast laser pulse filamentation in the air can be used for remote sensing by exciting a characteristic optical emission, which is usually referred to as filamentation-induced breakdown spectroscopy. In environments that impede light propagation, such as fog, haze, or clouds, scattering makes it challenging to propagate laser beams and retrieve generated optical signatures. We demonstrate the effectiveness of laser filamentation for simultaneously clearing the path for intense femtosecond pulse propagation in a highly scattering medium, generation of luminous plasma on a solid target, and counter-propagation of a characteristic spectroscopic signal over a cleared channel along the filament path. In a dense cloud, the counter-propagating signal predominantly transits the cleared on-axis path but is highly affected by the negative thermal lensing of a Gaussian beam. Furthermore, these insights enhance our understanding of laser filamentation in atmospheric sensing and could substantially improve remote detection capabilities in poor visibility conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Weather radar utility in hazard detection and response

Publicly accessible weather radar data have significant capabilities for meteorological measurements and predictions and, further, have the potential to measure nonmeteorological events that include smoke, ash, and debris plumes as well as explosions. The ability to identify and track nonmeteorological events can be of assistance in emergency response, hazard mitigation, and related activities in locations where radar coverage both exists and is recorded and accessible to the user. Here, in this study, events from multiple locations in the United States that are reported in news outlets are assessed using a manual inspection process of Level 2 weather radar data to identify anthropogenic and nonbiological returns. Explosive events are also identified, and a large high-altitude debris cloud from the intentional destruction of the SpaceX Starship is tracked across a wide area. Finally, future efforts using a machine learning model are discussed as a means of automating the process and potentially enabling near-real-time nonmeteorological event identification in the same areas where the data are accessible. Using weather radar data can be a valuable new tool for Department of Defense systems to aid in military awareness, and for interagency emergency response and forensic mission experts to consider national weather service data in their mission profiles. Radar data can be effective in detecting several common types of emergencies and inform and aid response personnel.

54 ENVIRONMENTAL SCIENCES↗

Advancing Aerosol Chemical Characterization and Vertical Profiling over the Southern Great Plains Using Uncrewed Aerial Sampling and Offline Aerosol Mass Spectrometry

Recent advancements in uncrewed aerial systems (UASs) and particulate matter (PM) analytical techniques have provided opportunities for atmospheric research. In this study, we deployed the Department of Energy’s fixed-wing ArcticShark UAS to examine PM 2.5 composition at varying altitudes─within and above the planetary boundary layer (PBL)─over the Southern Great Plains atmospheric observatory (SGP). A total of 22 flights were conducted across March, June, and August 2023. Composite filter samples were collected during each flight and analyzed with offline aerosol mass spectrometry (AMS), complemented by on-board real-time sensors and ground-based instrumentation, to provide a comprehensive view of regional aerosol characteristics. Results show clear vertical and seasonal differences in the aerosol composition. Relative to ground-level measurements, aloft samples exhibited shifts in the distribution of organic and inorganic PM, with the organic composition varying distinctly across seasons. Particulate organic nitrogen (ON) was elevated, with bulk compositions similar in March and June but strongly altered in August, likely driven by biomass burning and enhanced photochemical activity. Combined AMS and chemical ionization mass spectrometry analyses detected amines, amides, and amino acids. PM above the planetary boundary layer was enriched in oxidized organic aerosols, while ground-level PM contained higher nitrate and sulfate. Seasonal differences in aqueous-phase processing were also observed, which were strongest in March during persistent cloud cover and weaker in the drier August period, suggesting a shift from aqueous- to gas-phase SOA formation. In conclusion, these findings highlight the value of UAS in advancing PM measurements and vertical profiling of aerosol composition.

54 ENVIRONMENTAL SCIENCES↗

Forecasting Dark Matter Subhalo Constraints from Stellar Streams using Implicit Likelihood Inference

The evidence for dark matter (DM) remains compelling, although attempts to understand its particle nature remain inconclusive. One promising method to study DM is detecting DM subhalos through their gravitational interactions with stellar streams. In this study, we apply Neural Posterior Estimation (NPE) to constrain subhalo interaction parameters, including mass, scale radius, velocity, and encounter geometry, from stellar stream kinematics. We generate particle spray simulations based on the Lagrange Cloud stripping technique, focusing on the ATLAS-Aliqa Uma stream as a test case. We train multiple NPE models across multiple observational scenarios, quantifying how kinematic completeness affects inference and forecasting constraints from upcoming surveys including LSST, 4MOST, and 10-year Gaia data. Our results demonstrate that NPE can produce accurate and well-calibrated posteriors. In the idealized case with full 6D coordinates, we achieve subhalo mass uncertainties of 15-20% for a $10^7 \, \mathrm{M_\odot}$ subhalo, with 5D coordinates (excluding radial velocities) achieving similar performance. Under realistic observational conditions, mass uncertainties range from 50% (present-day) to 20-40% (future scenarios), with comparable performance between the photometric-only LSST sample and a smaller sample that includes Gaia proper motions and 4MOST radial velocities. Most notably, we find that velocity bimodality emerges when phase space is poorly sampled, whether due to missing kinematic information or limited stellar tracers. Combining large photometric samples with targeted spectroscopic follow-up can effectively resolves this degeneracy. These results demonstrate the power of implicit likelihood inference for optimizing stellar stream observational strategies and forecasting DM subhalo constraints from upcoming surveys.

Nguyen, Tri [Northwestern U. (main); SkAI, Chicago↗

NSA Site Science: Use of ARM Observations from Northern Alaska to Evaluate and Improve Prediction Capabilities

The Arctic is warming at a rate nearly double that of the rest of the planet, leading to profound changes in atmospheric, oceanic, and ice processes. The U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility has played a significant role in Arctic research, operating observatories in Alaska's North Slope for over 25 years. These observatories provide a rich, and wide-reaching dataset that offers insight into atmospheric processes in northern Alaska. This report details the results of a nine-year research project (2015–2024) supported by the DOE Atmospheric Systems Research (ASR) program, that leverages data from ARM’s deployment of observing facilities at Utqiaġvik (known as the North Slope of Alaska, or NSA, site) and Oliktok Point, Alaska. The project was conducted in two phases: - Phase 1 (2015–2019): Focused on understanding key atmospheric processes at Oliktok Point, including cloud formation, high-latitude precipitation, aerosol-cloud interactions, and cloud properties. - Phase 2 (2019–2024): Extended the research to the broader North Slope region, using data from both Oliktok Point and Utqiaġvik. Topics explored included surface energy budgets, atmospheric stability, ice nucleation processes, and microphysics in Arctic clouds. The project resulted in numerous research products, including 50 peer-reviewed publications and dissertations, 169 presentations, and 10 data products. These products cover a variety of topics, including: - Cloud Macro- and Microphysical Properties: Arctic clouds play a crucial role in energy transfer, and accurate representation in models is critical. The study explored cloud transitions, ice crystal shapes, and dual-wavelength radar data to understand ice crystal habits and size distributions. - Aerosol Properties and Processes: The team examined aerosol sources in the Arctic, including industrial emissions and natural sources. Observations showed significant spatial gradients in aerosol concentrations due to human activities and wildfire smoke. The influence of aerosols on cloud formation and the surface energy budget was also assessed. - Aerosol-Cloud Interactions: Research revealed that aerosols might suppress cloud ice production, affecting cloud radiative forcing and precipitation. The impact of local industrial emissions on cloud properties was also investigated. - Contextualizing the North Slope of Alaska in the context of the broader Arctic: To understand broader trends, the project evaluated large-scale circulation patterns and the influence of weather systems on the Arctic. Studies indicated that large-scale processes play a significant role in temperature patterns and the timing of snowmelt. - Advancing ARM Observational and Modeling Capabilities: The project developed new radar data products and advanced measurement techniques, including clutter mitigation and drizzle detection. Uncrewed aerial systems (UAS) and tethered balloon systems (TBS) were deployed to gather detailed atmospheric data. Additionally, the project supported 10 early career scientists, providing training and mentorship to undergraduate interns, graduate students, postdoctoral researchers, and early career researchers. These efforts contributed to the advancement of ARM research capabilities and fostered a new generation of scientists skilled in Arctic atmospheric research. Ultimately, this ASR-supported project has provided valuable insights into Arctic atmospheric processes and their broader climate implications. Recommendations for future work include continuing support for long-term observing at Arctic locations to foster additional research, further exploration of aerosol-cloud interactions and the potential impacts of enhanced industrialization of the Arctic, and expanded use of uncrewed systems to gather data in this remote and harsh environment. Additionally, the data products developed by this work, and the data products developed through the ARM infrastructure, leave a treasure-trove of additional information that should be explored for many years to come to gain additional insight into physical processes in the Arctic atmosphere that drive the rapid changes occurring in at high latitudes and their global impact.

58 GEOSCIENCES↗

Experimental Report: Multi-Instrument Comparison of AAF Condensation Particle Counters

Condensation particle counters (CPCs), also known as condensation nucleus counters (CNCs) are sophisticated instruments designed to measure the concentration of aerosol particles in the atmosphere. These devices are pivotal in environmental monitoring, industrial applications, and scientific research, particularly in atmospheric studies. CPCs are vital for understanding the role of aerosols in climate systems. Aerosols influence cloud formation, radiative forcing, and atmospheric chemistry. By providing accurate measurements of particle concentrations and distributions, CPCs contribute to models that predict atmospheric impact and weather patterns (Mei et al. 2021). CPCs operate by enlarging submicron particles, including those as small as a few nanometers, to sizes detectable by optical methods. This report delves into the mechanisms, importance, and contributions of CPCs to atmospheric research at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF), highlighting their role in advancing air quality assessment, pollution control, and atmospheric studies.

54 ENVIRONMENTAL SCIENCES↗

Three Quenched, Faint Dwarf Galaxies in the Direction of NGC 300: New Probes of Reionization and Internal Feedback

We report the discovery of three faint and ultra-faint dwarf galaxies -- Sculptor A, Sculptor B and Sculptor C -- in the direction of NGC 300 (D=2.0 Mpc), a Large Magellanic Cloud-mass galaxy. Deep ground-based imaging with Gemini/GMOS resolves all three dwarf galaxies into stars, each displaying a red giant branch indicative of an old, metal-poor stellar population. No young stars or HI gas are apparent, and the lack of a GALEX UV detection suggests that all three systems are quenched. Sculptor C (D=2.04$^{+0.10}_{-0.13}$ Mpc; $M_V=-9.1\pm 0.1$ mag or $L_V=(3.7^{+0.4}_{-0.3})\times 10^5L_{\odot})$ is consistent with being a satellite of NGC 300. Sculptor A (D=1.35$^{+0.22}_{-0.08}$ Mpc; $M_V=-6.9\pm 0.3$ mag or $L_V=(5^{+1}_{-1})\times 10^4 L_{\odot})$ is likely in the foreground of NGC 300 and at the extreme edge of the Local Group, analogous to the recently discovered ultra-faint Tucana B in terms of its physical properties and environment. Sculptor B (D=2.48$^{+0.21}_{-0.24}$ Mpc; $M_V=-8.1\pm 0.3$ mag or $L_V=(1.5^{+0.5}_{-0.4})\times 10^5L_{\odot})$ is likely in the background, but future distance measurements are necessary to solidify this statement. It is also of interest due to its quiescent state and low stellar mass. Both Sculptor A and B are $\gtrsim 2-4 r_{vir}$ from NGC 300 itself. The discovery of three dwarf galaxies in isolated or low-density environments offers an opportunity to study the varying effects of ram pressure stripping, reionization and internal feedback in influencing the star formation history of the faintest stellar systems.

79 ASTRONOMY AND ASTROPHYSICS↗

Airborne LiDAR to Improve Canopy Fuels Mapping for Wildfire Modeling

Increasing conflict between wildfire and the built environment has increased the need for more up-to-date and finer resolution canopy fuels data to improve wildfire modeling and associated risk forecasts. The US Forest Service and US Department of the Interior’s LANDFIRE product, which provides 30-m resolution canopy fuels data for the entire US, is one of the most widely used sources of fuels data. However, the last complete mapping effort for LANDFIRE is based on 2016 conditions, and subsequent updates reflect disturbances 1-2 years behind the release year. Airborne systems equipped with Light Detection and Ranging (LiDAR) sensors can be deployed to actively sense canopy structure and estimate canopy fuels data (cover, height, base height, bulk density) at finer resolutions. Canopy base height (CBH) and canopy bulk density (CBD) are difficult to measure both in the field and in LiDAR point clouds. Still, they are important for accurately modeling crown fires, which are often intense and difficult to contain. Additionally, point cloud datasets are large, and calculations require efficient utilization of computational resources. To address these challenges, we are working on an approach that uses openly available National Ecological Observatory Network (NEON) airborne LiDAR data, with calculations processed in the R programming language and parallelized through the lidR package. CBH and CBD are often derived from tree height, diameter at breast height, and species-specific allometries using the Fire and Fuels Extension of the Forest Vegetation Simulator (FFE-FVS). We aim to test if airborne LiDAR can estimate CBH and CBD without the use of empirical equations. Reliable estimates of canopy fuels data directly from airborne LiDAR could streamline quick, fine-resolution updates for use in wildfire behavior models.

54 ENVIRONMENTAL SCIENCES↗

Organic Acid Aerosol Measurements from the Mount Airy Site for CoURAGE

This study investigates the prevalence and distribution of organic acid aerosols in a rural environment using filter-based measurements collected in Mount Airy, Maryland, during the CoURAGE campaign from March 19th through June 12th 2025. PM2.5 filters quantify a range of organic acids commonly associated with secondary organic aerosol formation and atmospheric oxidation processes. Each filter was collected using a 15 LPM sampler and was extracted in ultrapure Millipore water (>18 MΩ), allowing water-soluble organic acids to be extracted into solution for analysis. The extracts were then examined using a Waters Acquity I-Class PLUS liquid chromatography system coupled to a Bruker Maxis-II ultra-high-resolution Q-TOF mass spectrometer with electrospray ionization, providing high-sensitivity detection and separation of target compounds. Concentrations of several key organic acids were quantified, including acetic, propionic, pyruvic, butyric, oxalic, isovaleric, valeric, malonic, maleic, succinic, glutaric, malic, adipic, and citric acids. These findings contribute to ongoing efforts to understand regional aerosol composition and their impacts on aerosol-cloud interactions.

Acetic acid↗

Southern Ocean Aerosols Field Campaign Report

Atmospheric processes over the Southern Ocean have a profound influence on regional and global climate. This is a part of the world where global climate models perform particularly poorly, with models persistently overpredicting the amount of sunlight reaching the Earth's surface (Regayre et al. 2020). A major challenge when trying to improve the representation of atmospheric processes in this part of the globe is the scarcity of observations capable of constraining our understanding. During 2024/25 a U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility field campaign (CAPE-k) deployed a suite of instrumentation at the kennaook/Cape Grim atmospheric monitoring station in Tasmania, Australia to provide detailed cloud-aerosol observations in this region in order to address the greatest source of uncertainty in climate models – atmospheric aerosols and how they influence cloud formation (Carslaw et al. 2013). In support of the ARM observations, an Australian Research Council (ARC)-funded project “Southern Ocean aerosols: sources, sinks and impact on cloud properties,” led by the Queensland University of Technology, complemented the ARM measurements with a suite of chemical measurements at the kennaook/Cape Grim site in northwestern Tasmania to provide more information on the processes controlling aerosol formation and growth. The deployment of the University of York LIF-SO2 instrument (Temple et al. 2025) in the ARM mobile facility container was part of this chemistry-focused deployment. Increased observational efforts are critical for understanding sources and sinks of Southern Ocean aerosols, in particular the role of marine micro-organisms (phytoplankton, algae) on aerosols formation, their properties and growth, cloud droplet formation, and the conversion of cloud droplets to ice crystals and precipitation. The observational focus of the ARC-funded project is aerosol chemical composition and their gaseous precursors. The remote nature of the Southern Ocean poses a significant analytical challenge when studying gaseous precursors, as low concentrations are often below the limits of detection of commercial instrumentation. Historically this has meant that observations have had to be time-averaged over days to weeks to achieve the limits of detection required. Although useful when considering overall average levels of aerosol precursors, this time-averaging obscures temporal variability that can provide insight into the controlling processes. Over recent years advances in analytical techniques have made high-time-resolution measurements of key gas-phase aerosol precursors achievable with sufficiently low limits of detection.

54 ENVIRONMENTAL SCIENCES↗

Sea spray aerosol production flux retrieval based on Doppler lidar measurements

Supermicron sea spray aerosols (SSA) play a crucial role in stratocumulus cloud microphysics and drizzle formation. However, our understanding of SSA's spatiotemporal distribution, production mechanisms, and fluxes in the marine boundary layer remains limited. This study introduces a novel approach to determine supermicron SSA production flux and number concentration at various heights above the ocean surface. Our method leverages Doppler lidar data, specifically attenuated backscatter and vertical velocity, collected at a 105 m range gate during the Eastern Pacific Clouds and Aerosols for Precipitation Experiment (EPCAPE) at Scripps Pier, La Jolla, California. To focus on nascent SSA, we analyzed data from periods with wind directions between 225° and 315° and wind speeds exceeding 4 m s −1 . Cloud and precipitation events were excluded using relative humidity, backscatter thresholds, and 2D Video Disdrometer observations. Results show that calculated supermicron SSA number concentrations at 105 m ranged from 0.26 to 2.93 cm −3 for surface wind speeds between 4 and 6 ms −1 . When exceeding the method's Limit of Detection, estimated production fluxes ranged from 0.20 to 1.53 cm −2 s −1 . This methodology has potential for application in various oceanic locations, likely enhancing our understanding of SSA's role in atmospheric processes and climate interactions.

54 ENVIRONMENTAL SCIENCES↗

Gas-phase synthesis of anthracene and phenanthrene via radical-radical reaction induced ring expansions

Unraveling reaction mechanisms of aromatic and resonance-stabilized radicals is critical to understanding molecular mass growth processes to polycyclic aromatic hydrocarbons (PAHs) and carbonaceous nanoparticles in distinct astrophysical environments (molecular clouds, circumstellar envelopes) and combustion systems. Using photoelectron photoion coincidence spectroscopy (PEPICO), we explored the gas-phase reaction of the methyl radical (CH 3 • ) with the aromatic and resonance-stabilized fluorenyl radical (C 13 H 9 • ) under high-temperature conditions in a chemical microreactor. Anthracene and phenanthrene were detected isomer-selectively using photoionization efficiency (PIE) curves and mass-selected threshold photoelectron (ms-TPE) spectra. While phenanthrene is produced through a radical-radical recombination of the carbon-centered radicals, anthracene may plausibly be formed through an unconventional radical addition to a low spin-density fluorenyl carbon. These pathways result in five-membered ring expansion—a critical mechanism crucial to PAH mass growth converting bent PAHs into planar nanostructures.

Goettl, Shane J. [University of Hawai‘i at Mānoa, ↗

Detecting gravitational signatures of dark matter with atom gradiometers

We study the purely gravitational signatures of dark matter from the ultralight to the ultraheavy mass range in proposed long-baseline atom gradiometers, focusing on terrestrial designs, such as AION-km and MAGIS-km, as well as space-based concepts, such as MAGIS-space, AEDGE and AEDGE+. Due to its exceptional acceleration sensitivity and depending on astrophysical backgrounds, a detector similar to AEDGE+ could detect a dark matter subcomponent which constitutes 𝒪⁡(10%) of the local dark matter energy density and is populated by compact clumps of mass between 10 6 kg and 10 10 kg (10 −25 ⁢𝑀⊙ ≲ 𝑀 ≲10 −21⁢ 𝑀⊙) in an otherwise unexplored region of dark matter model space. Furthermore, because the gravitational observable depends on the relative gravitational time delay measured by spatially separated atomic clouds, we find that atom gradiometers are parametrically more sensitive than laser interferometers, such as LIGO and LISA, to fast-oscillating spacetime perturbations sourced by energy density and pressure fluctuations of ultralight dark matter. Depending on astrophysical backgrounds, a detector akin to AEDGE+ could probe a DM overdensity of 𝒪⁡(10) times the local dark matter energy density for masses 𝑚 ≲10 −17 eV.

79 ASTRONOMY AND ASTROPHYSICS↗

Causal Directions Matter: How Environmental Factors Drive Convective Cloud Detrainment Heights

This study investigates how environmental factors influence the level of maximum detrainment (LMD) in deep convective clouds. Through a novel application of the Linear Non‐Gaussian Acyclic Model (LiNGAM), we discover causal structures between environmental variables and LMD, observed at six tropical sites operated by the Atmospheric Radiation Measurement (ARM) user facility. LiNGAM effectively identifies causal directions among variables of interest, revealing robust relationships such as those among the lifting condensation level (LCL), level of free convection (LFC), and convective inhibition (CIN), aligning with prior knowledge. Relative humidity is shown to directly influence LMD; however, this relationship exhibits strong nonlinearity and becomes difficult to detect when the contrast between oceanic and continental environments is excluded from the analysis. This study highlights the importance of establishing causal relationships before performing statistical inference.

54 ENVIRONMENTAL SCIENCES↗

Characterization of dynamics and decay in the St. Benedict Paul trap

The St. Benedict experiment includes a linear Paul trap designed to measure the beta-neutrino angular correlation coefficient 𝑎 𝛽ν of mixed superallowed 𝛽-decay transitions between mirror nuclei via coincidence detection of 𝛽-particles and recoiling ions. The emitted 𝛽 particle and daughter ion are detected with plastic scintillators and micro-channel plate detectors, respectively, allowing for accurate measurements of their time-of-flights. From the shape of the coincidence time-of-flight distribution, a value of 𝑎 𝛽ν can be determined. This manuscript presents detailed simulations of the St. Benedict Paul trap, with a focus on ion cloud dynamics and recoiling daughter trajectories.

Linear Paul trap↗

Diaspora: Resilience-Enabling Services for Real-Time Distributed Workflows

The need for real-time processing to enable automated decision making and experimental steering has driven a shift from high-performance computing workflows on a centralized system to a distributed approach that integrates remote data sources, edge devices, and diverse compute facilities. Under this paradigm, data can be processed close to the source where it is generated, thus reducing latency and bandwidth usage. System resilience is thus a key challenge, requiring distributed workflows to survive component failures and to meet stringent quality-of-service requirements, which results in the need to mitigate anomalies such as congestion and low availability of resources. To address these challenges, we propose Diaspora, a unified resilience framework that is inspired by event-driven communication patterns used in public clouds. Specifically, we propose an event fabric that extends across sites, facilities, and computations to provide timely, reliable, and accurate information about data, application, and resource status. On top of the event fabric, we build resilience-enabling services that combine QoS-aware data streaming, resilient data views, resilient compute and data resources, and anomaly detection and prediction, all of which collectively enhance workflow resilience for these scientific cases.

Rao, Nageswara↗

Fractal Scaling of Explosively Driven Product Gases

ABSTRACT Characterization of the interface between explosive product gases and ambient air in an explosion is a complicated task due to the turbulent mixing and inherently three‐dimensional expansion of the interface. This study aims to quantify the evolution of the interface as a temporally varying Hausdorff dimension. Two test series were conducted with Composition C‐4 charges with masses of 105 and 880 g. Imaging data were collected from the time of detonation until shock wave detachment using ultra‐high‐speed cameras. Gas cloud profiles were extracted using automated image processing algorithms, and the Hausdorff dimension of these two‐dimensional slices of the gas cloud was then estimated using boxcounting algorithms. When scaled with standard gas dynamic nondimensional scalings, the Hausdorff dimension of all explosive events appears to collapse towards a single curve. The fireball was initially nonfractal and began to develop fractal properties as the shock wave separated from the detonation products. Artificial perturbation of the charged surface had no detectable impact on the evolution of the Hausdorff dimension in the early development of the fireball outside of error, despite visible phenomenological differences in the early development of mixing on the fireball surface.

42 ENGINEERING↗