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An imaging and fractal approach towards understanding reservoir scale changes in coal due to bioconversion

Microbially enhanced coalbed methane (MECBM) aims to replicate the natural process of microbial methane generation in coal under in situ conditions. Considerable work has been reported over the years to optimize the associated microbial geo-chemistry. However, there is very little insight with regards to changes in the physical structure of coal due to bioconversion, and its impact on fluid flow properties. Here this paper presents the result of an image and fractal-based approach used to evaluate the changes in physical properties of coal. Samples of coal treated over 30, 60 and 120 days respectively were imaged before and after bioconversion. The results revealed that coal bioconversion resulted in swelling of the coal matrix. Cleats narrower than 5 µm reduced in its width post-bioconversion. A 77% drop in the permeability of coal is expected from the obtained results. Bioconversion also resulted in separation of thin layers of coal flakes from the coal surface, serving as a potential source of fines. Fractal analysis of the images revealed a decrease in the fractal dimension post bioconversion, which is in agreement with the previously reported studies, thus corroborating the variations in sorption-trends observed due to bioconversion. Additionally, the methodology to determine the fractal dimension via two-dimensional image processing was modified to improve its accuracy, and remove the dependency of the dimension to the scale of the obtained images. Bioconversion also resulted in formation of new pores/fractures. Shorter treatment duration resulted in nanometer-scale discontinuous pores, which do not contribute to Darcian flow. Longer treatment periods resulted in sub-micron wide continuous pores. Also, few larger fractures (>5 µm wide) saw an increase in its aperture post-treatment. This opens up new avenues, such as, utilizing artificially induced fracturing techniques to enhance biogenic methane production in future.

01 COAL, LIGNITE, AND PEAT↗

Geomechanical and flow implications with continued bioconversion of coal to methane: Experiments and modeling

Microbial conversion of coal to methane is a promising technology during transition of coal-based energy from conventional coal mining to natural gas recovery from coal. Significant research advances have been made towards engineering ideal microbial communities and nutrients for bio-stimulation of coal. However, actual field applications require geomechanical and flow behavior characterization of coal during the bioconversion process as well as gas production over the life of the created “biogenic gas reservoirs”. This work presents the results of an experimental investigation to estimate gas/methane production using bioconversion of coal and analyses of variations in bulk modulus, strain and permeability. Bulk modulus of coal demonstrated time-dependent behavior with continued bioconversion of solid coal. The phenomenon was modeled using mass balancing in a closed environment and the logistic equation based biogenic gas production with time. The modeled gas production and changes in modulus of coal showed excellent agreement with the corresponding experimental results. Next, numerical simulation of biogenic conversion of coal in a constant stress in-situ condition, replicating the Huff ‘n Puff method under field conditions, was carried out. The results showed that bioconversion can lead to decrease in effective stress, increase in permeability and decrease in the modulus of coal with time. Repeated recharge of coal with nutrients and recovering the produced gas, that is, sequential cycles of Huff n’ Puff, showed further increase in permeability and decrease in coal strength, potentially leading to coal failure in-situ, further increasing the permeability, thus enhancing the prospect of field application of the technology.

01 COAL, LIGNITE, AND PEAT↗

Geochemical reactions and alteration of pore architecture in saturated shale after injection of stimulation fluid

Pore architecture regulates fluid flow between unconventional shale reservoir and hydraulically-induced fractures. Imbibition of stimulation fluid may change this architecture and alter hydrocarbon flow. Hydrothermal experiments were conducted at reservoir conditions (125 °C, 45 MPa) to test two hypotheses: 1) Shale, not stimulation fluid, dominates the geochemistry of an unconventional reservoir containing formation water; and 2) Mineral dissolution and precipitation induced by stimulation fluid is transient and manifests across micro-, meso-, and macro-scales of pore architecture. Experiments replicated a shut-in well in the Cretaceous Baxter Shale, Green River Basin, Wyoming USA. Stimulation fluid was injected into one experiment after formation water (I = 0.35 mol/kg, pH = 6.4) and core reacted for 48 days. This novel approach equilibrated rock and formation water and saturated pores with formation water before introducing stimulation fluid. The second experiment served as a control. Trends of aqueous calcium, silica and aluminum in the injection experiment suggest transient dissolution of calcite and feldspar and/or quartz as well as clay and barite precipitation; mineralogic evidence was limited to calcite dissolution and barite precipitation. The rock maintained reducing conditions (Eh = +0.08 to -0.16 V) despite injection of oxidizing stimulation fluid (Eh = 1.1 V). pH of the stimulation fluid-formation water mixture evolved from 2.3 to pre-injection values (~6) within 24 h. The results indicate that mineral dissolution and precipitation manifest in macropores with barely detectable alteration to micro- and mesopores. Formation water or organic matter in pores may have inhibited access of stimulation fluid to micro- and mesopores

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupling dynamic in situ X-ray micro-imaging and indentation: A novel approach to evaluate micromechanics applied to oil shale

Oil and gas shales are a system where understanding the mechanical properties at the microscale is of paramount importance, e.g. to better understand the behavior of proppant-shale contacts and their role in the evolution of propped fractures in unconventional reservoirs. Here we show for the first time an experiment coupling indentation testing with in situ X-ray imaging in a Green River shale sample. A full compliance curve has been measured with the sample in water, allowing to visualize the indentation of the sample in function of axial load, in a purpose-built system for combined in situ indentation and X-ray imaging. A series of 3D datasets were used for a digital volume correlation study to obtain local strain fields. This analysis has been complemented with the analysis of cracks. Finally, geomechanical modeling has been carried out to replicate and generalize the observed behavior in the shale. This study validated this experimental approach, providing a breakthrough in understanding micro-mechanics in shales, and demonstrates how this class of experiments can be important for studies involving the prediction of the evolution of propped fractures in shale reservoirs, with possible applications in a much larger number of application fields (geothermal, materials science, etc.)

04 OIL SHALES AND TAR SANDS↗

Neural network model of neutral beam injection in the EAST tokamak to enable fast transport simulations

The neutral beam injection (NBI) system in EAST produces energetic neutral particles, which collide with electrons and ions in tokamak plasmas and heat the plasmas through Coulomb collisions. Moreover, it drives a non-inductive source of current, due to the charge-exchange collision between neutral particles and ions, and injects toroidal torque, which generates a toroidal rotation of the plasma. The effect caused by the NBI system, such as plasma heating, current drive, total neutron rate, momentum transfer, and shine-through, are modeled by a comprehensive module called NUBEAM. However, NUBEAM is computationally intensive since it relies on Monte Carlo methods. In this work, a neural network model has been developed as a surrogate model for NUBEAM in EAST. The database for neural-network model training, validation and testing is generated by running TRANSP for experimental discharges from recent EAST campaigns (after the latest NBI upgrade) while using the NUBEAM module. Simulation results illustrate that the trained neural network has the capability of replicating the predictions made by NUBEAM while demanding a significantly shorter execution time. Finally, these results indicate that surrogate models like the one proposed in this work could enable fast transport simulations for EAST after integrating them into a control-oriented predictive code such as COTSIM.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Bridging the gap between peak and average loads on science networks

Backbone networks are typically overprovisioned in order to support peak loads. Research and education networks (RENs), for example, are often designed to operate at 20–30% of capacity. Thus, Internet2 upgrades its backbone interconnects when the weekly 95th-percentile load is reliably above 30% of link capacity, and analysis of ESnet traffic between major laboratories shows a substantial gap between peak and average utilization. As science data volumes increase exponentially, it is unclear whether this overprovisioning trend can continue into the future. Even if overprovisioning is possible, it may not be the most cost-effective (and desirable) approach going forward. Under the current mode of free access to RENs, traffic at peak load may include both flows that need to be transferred in near-real time–for example, for computation and instrument monitoring and steering–and flows that are less time-critical, for example, archival and storage replication operations. Thus, peak load does not necessarily indicate the capacity that is absolutely required at that moment. We thus examine how data transfers are impacted when the average network load is increased while the network capacity is kept at the current levels. We also classify data transfers into on-demand (time-critical) and best-effort (less time-critical) and study the impact on both classes for different proportions of both the number of on-demand transfers and amount of bandwidth allocated for on-demand transfers. For our study, we use real transfer logs from production GridFTP servers to do simulation-based experiments as well as real experiments on a testbed. We find that when the transfer load is doubled and the network capacity is fixed at the current level, the gap between peak and average throughput decreases by an average of 18% in the simulation experiments and 16% in the testbed experiments, and the average slowdown experienced by the data transfers is under 1.5×. Moreover, when transfers are classified as on-demand or best-effort, on-demand transfers experience almost no slowdown and the mean slowdown experienced by best-effort transfers is under 2× in the simulation experiments and under 1.2× in the testbed experiments.

97 MATHEMATICS AND COMPUTING↗

A survey on checkpointing strategies: Should we always checkpoint à la Young/Daly?

The Young/Daly formula provides an approximation of the optimal checkpointing period for a parallel application executing on a supercomputing platform. It was originally designed to handle fail-stop errors for preemptible tightly-coupled applications, but has been extended to other application and resilience frameworks. Here, we provide some background and survey various scenarios to assess the usefulness and limitations of the formula, both for preemptible applications and workflow applications represented as a graph of tasks. We also discuss scenarios with uncertainties, and extend the study to silent errors. We exhibit cases where the optimal period is of a different order than that dictated by the Young/Daly formula, and finally we explain how checkpointing can be further combined with replication.

97 MATHEMATICS AND COMPUTING↗

Scalable Generation of High-fidelity Synthetic Population Ensembles

Used within social simulations, synthetic population ensembles enable uncertainty quantification (UQ) methods for obtaining more robust model inference and prediction. A synthetic population ensemble is a series of plausible virtual reconstructions of an area’s population at the granularity of people and residences, generated stochastically to preserve privacy of the source population survey’s respondents. In this paper, we demonstrate the production of large synthetic population ensembles for the U.S. via Oak Ridge National Laboratory’s UrbanPop framework to support modeling of high spatial resolution energy affordability metrics from nationwide social surveys in collaboration with the fusionACS project. The study involves two scenarios: creating ensembles for (1) 17 U.S. metropolitan areas in 2019 and (2) full U.S. Census Divisions in 2023, with each scenario consisting of 41 population instances (a base realization and 40 replicates). To accomplish this task at scale, we configured an integrated system within a research cloud, comprised of virtual containerizations, GPU-enhanced functionality, and orchestrated deployments of UrbanPop’s maturing Likeness Python ecosystem. Results demonstrate we maintained high-fidelity approximations of residential totals by areas of interest and the demographic characteristics of neighborhoods while reducing manual workflow burdens. Finally, we discuss plans to fine-tune and further develop our automated workflows for truly distributed job orchestration to increase computational efficiency, as well as provide an outlook for broadening applications of the ensembles.

Cluster computing↗

Evaluation of accessible mineral surface areas for improved prediction of mineral reaction rates in porous media

The rates of mineral dissolution reactions in porous media are difficult to predict, in part because of a lack of understanding of mineral reactive surface area in natural porous media. Common estimates of mineral reactive surface area used in reactive transport models for porous media are typically ad hoc and often based on average grain size, increased to account for surface roughness or decreased by several orders of magnitude to account for reduced surface reactivity of field as opposed to laboratory samples. In this paper, accessible mineral surface areas are determined for a sample from the reservoir formation at the Nagaoka pilot CO 2 injection site (Japan) using a multi-scale image analysis based on synchrotron X-ray microCT, SEM QEMSCAN, XRD, SANS, and FIB-SEM. This analysis not only accounts for accessibility of mineral surfaces to macro-pores, but also accessibility through connected micro-pores in smectite, the most abundant clay mineral in this sample. While the imaging analysis reveals that most of the micro- and macro-pores are well connected, some pore regions are unconnected and thus inaccessible to fluid flow and diffusion. To evaluate whether mineral accessible surface area accurately reflects reactive surface area a flow-through core experiment is performed and modeled at the continuum scale. The core experiment is performed under conditions replicating the pilot site and the evolution of effluent solutes in the aqueous phase is tracked. Various reactive surface area models are evaluated for their ability to capture the observed effluent chemistry, beginning with parameter values determined as a best fit to a disaggregated sediment experiment (Beckingham et al., 2016) described previously. Simulations that assume that all mineral surfaces are accessible (as in the disaggregated sediment experiment) over-predict the observed mineral reaction rates, suggesting that a reduction of RSA by a factor of 10–20 is required to match the core flood experimental data. While the fit of the effluent chemistry (and inferred mineral dissolution rates) greatly improve when the pore-accessible mineral surface areas are used, it was also necessary to include highly reactive glass phases to match the experimental observations, in agreement with conclusions from the disaggregated sediment experiment. Finally, it is hypothesized here that the 10–20 reduction in reactive surface areas based on the limited pore accessibility of reactive phases in core flood experiment may be reasonable for poorly sorted and cemented sediments like those at the Nagaoka site, although this reflects pore rather than larger scale heterogeneity.

58 GEOSCIENCES↗

The solubility and speciation of REE phosphate endmembers (CePO 4 and YPO 4 ) in Cl-rich aqueous fluids from 350 to 450 °C and implications for natural systems

The rare earth elements (REE) are important metals used increasingly in advanced technologies. Within the crust, the elements Ce and Y are commonly more abundant compared to other lanthanides and comprise important end-member constituents of REE-bearing minerals. Specifically, Ce is part of the light (L) REE which have larger ionic radii than the heavy (H) REE, which are grouped together with Y. These differences in ionic radius can lead to important physico-chemical trends within the lanthanide group. Despite a recent increase in experimental and thermodynamic data for the REE at high temperature and pressure, there is still a significant lack of these data at supercritical conditions. In this study we conducted batch-type experiments to measure the solubility of REE phosphates (CePO 4 and YPO 4 ) at varying starting pH (1.5–10), and salinity (0.01–1.4 mol/kg NaCl) at 350 and P sat , and from 400 to 450 °C at 700 bar. Results show that the solubility of Ce (33–0.14 ppb) is generally higher than Y (13–0.13 ppb) and that Ce complexes more strongly with both chloride and hydroxyl ligands compared to Y. The solubilities of both REE phosphates are highly pH-dependent and, to a lesser extent, depend on salinity at the studied conditions. The solubility data from this study were implemented into the GEMSFITS program to optimize the thermodynamic properties of Ce and Y hydroxyl and chloride species. The updated standard partial molal Gibbs energies of formation (Δ f G 0 T,P ) are used within the experimental temperature and pressure range to accurately predict the CePO 4 and YPO 4 solubility and Ce and Y speciation behavior. Based on the updated thermodynamic properties we also provide formation constants (log β n Cl,OH ) for Ce and Y hydroxyl and chloride species. Updated thermodynamic properties are applied to model REE-apatite dissolution and REE mobility based on the Pea Ridge iron oxide apatite deposit in Missouri, USA. The apatite dissolution model replicates natural observations including the replacement of monazite and xenotime after apatite and is an example of the utility of the new thermodynamic constants applied to supercritical crustal fluids. Furthermore, the findings of this study advance the predictive capabilities of geochemical models, our understanding of the behavior of individual REE, and permit modeling the overarching fractionation trends between LREE and HREE in supercritical crustal fluids.

58 GEOSCIENCES↗

Assessing the sensitivity and repeatability of permanganate oxidizable carbon as a soil health metric: An interlab comparison across soils

Soil organic matter is central to the soil health framework. Therefore, reliable indicators of Soil organic matter is central to the soil health framework. Therefore, reliable indicators of changes in soil organic matter are essential to inform land management decisions. Permanganate oxidizable carbon (PDXC), an emerging soil health indicator, has shown promise for being sensitive to soil management. However, strict standardization is required for widespread implementation in research and commercial contexts. Here, we used 36 soils-three from each of the 12 USDA soil orders-to determine the effects of sieve size and soil mass of analysis on PDXC results. Using replicated measurements across 12 labs in the US and the EU (n = 7951 samples), we quantified the relative importance of 1) variation between labs, 2) variation within labs, 3) effect soil mass, and 4) effect of soil sieve size on the repeatability of PDXC. We found a wide range of overall variability in PDXC values across labs (0.03 to 171.8%; mean = 13.4%), and much of this variability was attributable to within-lab variation (median = 6.5%) independently of soil mass or sieve size. Greater soil mass (2.5 g) decreased absolute PDXC values by a mean of 177 mg kg -1 soil and decreased analytical variability by 6.5%. For soils with organic carbon (SOC) >10%, greater soil mass (2.5 g) resulted in more frequent PDXC values above the limit of detection whereas the lower soil mass (0.75 g) resulted in PDXC values below the limit of detection for SOC contents <5%. A finer sieve size increased absolute values of PDXC by 124 mg kg -1 while decreasing the analytical variability by 1.8%. In general, soils with greater SOC contents had lower analytical variability. These results point to potential standardizations of the PDXC protocol that can decrease the variability of the metric. We recommend that the PDXC protocol be standardized to use 2.5 g for soils <10% SOC. Sieve size was a relatively small contributor to analytical variability and therefore we recommend that this decision be tailored to the study purpose. Tradeoffs associated with these standardizations can be mitigated, ultimately providing guidance on how to standardize PDXC for routine analysis.

54 ENVIRONMENTAL SCIENCES↗

Soil carbon change in intensive agriculture after 25 years of conservation management

Changes in soil organic carbon (SOC) and nitrogen (SON) are strongly affected by land management but few long-term comparative studies have surveyed changes throughout the whole soil profile. We quantified 25-year SOC and SON changes to 1 m in 10 replicate ecosystems at an Upper Midwest, USA site. We compared four annual cropping systems in maize (Zea mays)-soybean (Glycine max)-winter wheat (Triticum aestivum) rotations, each managed differently (Conventional, No-till, Reduced input, and Biologically based); in three managed perennial systems (hybrid Poplar (Populus × euramericana), Alfalfa (Medicago sativa), and Conifer (Pinus spp.); and in three successional systems (Early, Mid- and Late succession undergoing a gradual change in species composition and structure over time). Both Reduced input and Biologically based systems included winter cover crops. Neither SOC nor SON changed significantly in the Conventional or Late successional systems over 25 years. All other systems gained SOC and SON to different degrees. SOC accrual was fastest in the Early successional system (0.8 ± 0.1 Mg C ha –1 y –1 ) followed by Alfalfa and Conifer (avg. 0.7 ± 0.1 Mg C ha –1 y –1 ), Poplar, Reduced input, and Biologically based systems (avg. 0.4 ± 0.1 Mg C ha –1 y –1 ), and Mid-successional and No-till systems (0.3 and 0.2 Mg C ha –1 y –1 , respectively). Over the most recent 12 years, rates of SOC accrual slowed in all systems except Reduced input and Mid-successional. There was no evidence of SOC loss at depth in any system, including No-till. Rates of SON accrual ranged from 64.7 to 0.8 kg N ha –1 y –1 in the order Alfalfa ≥ Early successional > Reduced input and Biologically based ≥ Poplar > No-till and Conifer > Mid-successional systems. Pyrogenic C levels in the Conventional, Early, and Late successional systems were similar despite 17 years of annual burning in the Early successional system (~ 15 % of SOC to 50 cm, on average, and ~40 % of SOC from 50 to 100 cm). Results underscore the importance of cover crops, perennial crops, and no-till options for sequestering whole profile C in intensively managed croplands.

60 APPLIED LIFE SCIENCES↗

Effect of pore fluid chemistry on the mechanical behavior of a divalent compacted bentonite, an experimental and constitutive study

Ongoing research in isolating high-level nuclear waste and spent fuel has highlighted compacted bentonite as a suitable material for engineered barrier systems in deep geological repositories due to its extraordinary swelling and retention properties. This research focuses on the chemo-mechanical behavior of compacted bentonite exposed to different pore fluids with different concentrations and loading conditions. The study involves swelling pressure and compressibility experiments along with mineralogy analysis employing X-ray diffraction (XRD) and Cation exchange. The tests were conducted on BCV (a Mg/Ca- bentonite) compacted at a dry density of 1.48 ± .02 Mg/m 3 . An advanced chemical-mechanical constitutive model for unsaturated highly expansive clays was adopted to simulate the material response and better understand its behavior. The model is able to account for the main phenomena at both macro and microstructural levels and the interactions between them. The model successfully replicated experimental observations. The XRD analyses support the macroscopic observation, indicating that salinity impacts crystalline swelling as demonstrated by the reduction of basal spacing from 19.27 Å to 15.68 Å when the osmotic suction increases from 0 MPa to 33 MPa. The results suggested that the osmotic pressure generated by the concentration in the pore fluids promotes a reduction in swelling pressures, swelling strains, and crystalline swelling of clay minerals. Also, it affects the pre-consolidation stress and the compressibility of the compacted samples. In conclusion, it was also observed that both solution type and solution concentration impact the clay swelling pressure.

Chemo-mechanical constitutive model↗

Surrogate models for development of unconventional shale reservoirs by an integrated numerical approach of hydraulic fracturing, flow and geomechanics, and machine learning

We develop well-completion surrogate models by taking an integrated workflow of hydraulic fracturing, flow, geomechanics, and machine learning simulation. There are three steps in the proposed workflow. First, history-matching processes are conducted with the field data including pumping and production data for characterization. Second, full-physics simulation is performed with various parameters of the field development (e.g., cluster spacing, clusters per stage, pumping rates and times, amount of proppant, and well spacing) to generate multiple simulation results by changing the parameters of the completion design with well-known hydraulic fracturing, reservoir, geomechanics simulators to calculate fracture geometry, reservoir depressurization, induced stress changes. The workflow is demonstrated over a field in the Southern Midland Basin. Here, we take two completion scenarios: a single well case followed by a multi-well case. Finally, a Long Short-Term Memory (LSTM) machine learning algorithm is employed to create surrogate models that can replicate the full-physics simulation results. Furthermore, results show that the trained models applied in the single well and multi-well cases for a particular geological system can provide good accuracy close to those provided by full-physics simulations. Specifically, the site-specific surrogate models can predict fracture parameters (length, height, and surface area) and cumulative production accurately with computational efficiency, suggesting our proposed workflow can be used as a pragmatic tool for expediting the well completion optimization process.

Geomechanics↗

A plasma deflagration accelerator as a platform for laboratory astrophysics

The replication of astrophysical flows in the laboratory is critical for isolating particular phenomena and dynamics that appear in complex, highly-coupled natural systems. Particularly, plasma jets are observed in astrophysical contexts at a variety of scales, typically at high magnetic Reynolds number and driven by internal currents. In this paper, we present detailed measurements of the plasma parameters within deflagration-produced plasma jets, the scaling of these parameters against both machine operating conditions and the corresponding astrophysical phenomena. Using optical and spectroscopic diagnostics, including Schlieren cinematography, we demonstrate the production of current-driven plasma jets of »100 km/s and magnetic Reynolds numbers of »100, and discuss the dynamics of their acceleration into vacuum. Finally, the results of this study will contribute to the reproduction of various types of astrophysical jets in the laboratory and indicate the ability to further probe active research areas such as jet collimation, stability, and interaction.

79 ASTRONOMY AND ASTROPHYSICS↗

Progress toward NIF opacity measurements

The opacities of iron and other mid-Z elements help to regulate the transport of energy in the sun. Recent experiments on the Sandia National Laboratories Z machine have shown large discrepancies between the measured and calculated opacities of iron at certain solar conditions. To replicate these opacity measurements a platform is being developed on the National Ignition Facility to measure the opacities of iron and other elements at the same conditions as in the Z experiments. The NIF platform consists of a hohlraum to heat the opacity sample to the desired conditions, a separate backlighter to radiograph the sample, and a spectrometer to give the spectrally resolved opacity. Not only must the opacity be measured but the temperature and density of the sample must also be accurately determined. This platform has now produced its first iron transmission measurements. Overall, these measurements will be presented along with plans for future measurements and details on how the measurements will be improved.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Shock wave formation in the thermosphere by an earthgrazing fireball: Empirical evidence for volatile-enhanced hydrodynamic shielding

Hydrodynamic shielding is a theoretically well-established but observationally elusive and experimentally difficult-to-replicate phenomenon with implications that extend far beyond meteor physics. Rare earthgrazing meteoroids with infrasound signatures that penetrate to the ground can be used to probe hydrodynamic shielding that leads to strong shock formation at high altitude. Here, we report the first coordinated optical and multi-station infrasound observations of a centimeter-scale earthgrazing fireball that generated sustained cylindrical line shock at thermospheric altitudes near 92 km. The event was recorded by numerous optical stations and three infrasound arrays, allowing trajectory reconstruction, ablation behavior, acoustic source localization, and shock characteristics. Optical observations indicate early mechanical erosion and ablation/evaporation at exceptionally low dynamic pressure, consistent with a cometary or a porous, volatile-bearing CM chondritic object. Independent infrasound detections localize shock generation to multiple points along a 164 km trajectory segment near perigee. Weak-shock modeling yields a consistent blast radius of ∼30 m, implying an acoustic-equivalent source size far exceeding the physical dimensions of the ∼45 g nucleus. We demonstrate that classical gas dynamics and ablation-driven hydrodynamic shielding alone cannot account for these observations under ambient thermospheric conditions. We show that volatile release provides the additional flow-field density enhancement required to amplify hydrodynamic shielding, reduce the effective local Knudsen number, and sustain a shock envelope capable of radiating detectable infrasound. Furthermore, these results demonstrate that small, volatile-rich meteoroids can transiently establish continuum-like flow in rarefied environments.

Astrometry↗

After the hurricane: Validating a resilience assessment methodology

With increasing utility grid outages in the United States, there is growing interest in assessing risk and developing mitigation strategies to reduce the impact of grid outages. Working with the U.S. Air Force, the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) developed a replicable energy resilience assessment methodology and investment decision tool to: (1) identify and score hazards and vulnerabilities at the site level; (2) analyze risks to energy infrastructure; and (3) identify and prioritize energy resilience investments. This work improves on existing resilience assessment methodologies and tools by combining a bottom-up, all-hazards assessment methodology with top-down geographic information system mapping capabilities to provide an innovative, dynamic tool for identifying and prioritizing actionable solutions. This process combines probabilistic forecasting with an iterative approach for continuously updating and reassessing risks to address temporal dynamism. Relationships among systems are modeled and visualized to estimate the effectiveness of resilience actions across multiple interdependent systems and inform financial priorities through cost-difficulty-impact trade-offs. The approach is validated in a case study at Tyndall Air Force Base (AFB) in Florida, which experienced a Category 5 hurricane in 2018. The risks and mitigation strategies identified pre-hurricane are compared with post-hurricane, realized impacts. The assessment effectively identifies risks and actions to increase site energy resilience, but the methodology can be enhanced though greater consideration of the interdependencies between the energy system and related systems like transportation, communication, and food/water systems, which impact the recovery of the energy system and the base.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗