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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Thermal-Hydrological-Mechanical Modelling of Stockton University Reservoir Cooling System, Large Scale Grid

Mesh, properties, initial conditions, injection/withdrawal rates for modeling thermal, hydrological, and mechanical effects of fluid injection to and withdrawal from ground for Stockton University reservoir cooling system (aquifer storage cooling system), Galloway, New Jersey, on large scale grid, with some results. First simulation of J.T. Smith, E. Sonnenthal, P. Dobson, P. Nico, and M. Worthington, 2021. Thermal-hydrological-mechanical modeling of Stockton University reservoir cooling system, Proceedings of the 46th Workshop on Geothermal Reservoir Engineering, Stanford University, SGP-TR-218, from which Figures 1-5 pertain.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Assessing Impacts on Pressure Stabilization and Leasing Acreage for CO 2 Storage Utilizing Oil Migration Concepts

Favorable geological storage for CO 2 has long been pictured as large anticlines with thick sandstones, similar to oil reservoirs in the petroleum system. Unlike oil, however, stored CO 2 does not need to be recoverable, which raises the possibility of using dissolution and residual trapping to augment the capacity of buoyant traps and tap more of the bulk rock volume. The work presented builds on that idea, asking the following question: If we inject CO 2 down to a syncline – analogous to the carrier bed in the petroleum system – how would this injection mechanism impact storage capacity and plume shape, migration, and stabilization? To address this question, we built a reservoir model, based on seismic interpretation of Middle Miocene strata, offshore Galveston, Texas. 3-D seismic and well logs were used to characterize key intervals. Reservoirs chosen for modeling are progradational-aggradational sands with mud intercalation. They have a higher degree of heterogeneity than the more conventional reservoirs commonly targeted for CO 2 storage. Modeling investigated how far the CO 2 plume would migrate under two scenarios: (1) injecting CO 2 at the base of the salt withdrawal basin (syncline scenario) and (2) injecting CO 2 at the base of the structural closure, similar to a common injection well location for EOR purposes (base scenario). For each scenario, we separately simulated injection of 30 MT of CO 2 and 60 MT of CO 2 continuously for 30 years and observe the plume and pressure evolution for 100 years after the injection stops. The simulation shows that injecting the CO 2 into a syncline limits the vertical migration of CO 2 , thus making synclinal injection more secure. In the syncline scenario, the geological layer around the injection point is more heterogeneous than the layer in the base scenario; thus, the CO 2 tends to migrate laterally. Additionally, in the syncline scenario, the plume does not even reach the upper part of the anticline, allowing us to safely store an additional amount of CO 2 into the reservoir. Furthermore, the simulation also shows that in the syncline scenario, the times needed for the reservoir to reach its stabilized pressure after the end of injections are faster. To summarize, CO 2 injection at the base of a syncline could provide additional storage, increase the safety of the project from the limited vertical plume migration, and expedite plume stabilization, which could result in the decrease of monitoring frequency as the project runs, thus lowering the operating cost of the project in the long run.

58 GEOSCIENCES↗
DOE OSTI2025

Modeling Co2 Flow Through Faulted/Fractured Reservoirs Using Tedfm in Corner-Point Grids

Interest in underground CO2 storage has increased significantly over the last decade, driven by growing concern about global warming and rising levels of greenhouse gases in the atmosphere. Given that CO2 accounts for 80% of these greenhouse gases, carbon capture, utilization, and storage (CCUS) is considered one of the most direct approaches to achieving the net-zero carbon target. Although CO2 storage in deep saline aquifers and depleted gas reservoirs has been studied extensively, most studies use commercial simulators that model faults/fractures by simply modifying the transmissibility in the direction perpendicular to the fault surfaces. This work shows that this simplistic approach ignores the accelerated flow in the directions parallel to the fault plane, leading to significantly higher leakage along the fault surface. To accurately model CO2 flow in faulted reservoirs, we present the first transient embedded discrete-fracture model for corner-point grids (tEDFM-CPG). By comparing the tEDFM-CPG results with high-resolution reference solutions, we show that this approach is accurate and efficient at predicting CO2 flow in faulted/fractured reservoirs. In conclusion, this work presents the use of mixed reality (MR) to efficiently observe CO2 gas migration in the interior of these corner-point grid systems.

02 PETROLEUM↗
DOE OSTI2022

Assessment of chemo-mechanical impacts of CO 2 sequestration on the caprock formation in Farnsworth oil field, Texas

This study evaluates the chemo-mechanical influence of injected CO 2 on the Morrow B sandstone reservoir and the upper Morrow shale caprock utilizing data from the inverted 5-spot pattern centered on Well 13-10A within the Farnsworth unit (FWU). This study also seeks to evaluate the integrity of the caprock and the long-term CO 2 storage capability of the FWU. The inverted 5-spot pattern was extracted from the field-scale model and tuned with the available field observed data before the modeling work. Two coupled numerical simulation models were utilized to continue the study. First, a coupled hydro-geochemical model was constructed to simulate the dissolution and precipitation of formation minerals by modeling three intra-aqueous and six mineral reactions. In addition, a coupled hydro-geomechanical model was constructed and employed to study the effects of stress changes on the caprock’s porosity, permeability, and ground displacement. The Mohr–Coulomb circle and failure envelope were used to determine caprock failure. In this work, the CO 2 -WAG injection is followed by the historical field-observed strategy. During the forecasting period, a Water Alternating Gas (WAG) injection ratio of 1:3 was utilized with a baseline bottom-hole pressure constraint of 5500 psi for 20 years. A post-injection period of 1000 years was simulated to monitor the CO 2 plume and its effects on the CO 2 storage reservoir and caprock integrity. The simulation results indicated that the impacts of the geochemical reactions on the porosity of the caprock were insignificant as it experienced a decrease of about 0.0003% at the end of the 1000-year post-injection monitoring. On the other hand, the maximum stress-induced porosity change was about a 1.4% increase, resulting in about 4% in permeability change. It was estimated that about 3.3% of the sequestered CO 2 in the formation interacted with the caprock. Despite these petrophysical property alterations and CO 2 interactions in the caprock, the caprock still maintained its elastic properties and was determined to be far from its failure.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2023

Simple Statistical Models for Predicting Overpressure Due to CO2 and Low-Salinity Waste-Fluid Injection into Deep Saline Formations

Deep saline aquifers have been used for waste-fluid disposal for decades and are the proposed targets for large-scale CO2 storage to mitigate CO2 concentration in the atmosphere. Due to relatively limited experience with CO2 injection in deep saline formations and given that the injection targets for CO2 sometimes are the same as waste-fluid disposal formations, it could be beneficial to model and compare both practices and learn from the waste-fluid disposal industry. In this paper, we model CO2 injection in the Patterson Field, which has been proposed as a site for storage of 50 Mt of industrial CO2 over 25 years. We propose general models that quickly screen the reservoir properties and calculate pressure changes near and far from the injection wellbore, accounting for variable reservoir properties. The reservoir properties we investigated were rock compressibility, injection rate, vertical-to-horizontal permeability ratio, average reservoir permeability and porosity, reservoir temperature and pressure, and the injectant total dissolved solids (TDS) in cases of waste-fluid injection. We used experimental design to select and perform simulation runs, performed a sensitivity analysis to identify the important variables on pressure build-up, and then fit a regression model to the simulation runs to obtain simple proxy models for changes in average reservoir pressure and bottomhole pressure. The CO2 injection created more pressure compared to saline waste-fluids, when similar mass was injected. However, we found a more significant pressure buildup at the caprock-reservoir interface and lower pressure buildup at the bottom of the reservoir when injecting CO2 compared with waste-fluid injection.

Ansari, Esmail↗
DOE OSTI2024

Accelerating Multiphase Simulations With Denoising Diffusion Model Driven Initializations

This study introduces a hybrid fluid simulation approach that integrates generative diffusion models with physics‐based simulations, aiming at reducing the computational costs of flow simulations while still honoring all the physical properties of interest. Pore‐scale simulations enhance our understanding of applications such as assessing hydrogen and storage efficiency in underground reservoirs. Nevertheless, they are computationally expensive and the presence of non‐unique solutions can require multiple simulations within a single geometry. To overcome the computational cost hurdle, we propose a method that couples generative diffusion models and physics‐based simulations. While training the data‐driven model, we simultaneously generate initial conditions and perform physics‐based simulations using these. This integrated approach enables us to receive real‐time feedback on a single compute node equipped with both CPUs and GPUs. By efficiently managing these processes within a single compute node, we can continuously monitor performance and halt training once the model meets the specified criteria. To test our model, we generate realizations in a real Berea sandstone fracture which shows that our technique is up to 4.4 times faster than commonly used flow simulation initializations.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Modeling CO 2 flow through faulted/fractured reservoirs using tEDFM in corner-point grids

The interest in underground CO 2 storage has increased significantly over the last decade because of the rising concern about global warming due to the growing levels of greenhouse gases in the atmosphere. Considering that CO 2 accounts for 80% of these greenhouse gases, carbon capture, utilization, and storage (CCUS) is regarded as one of the most direct approaches to achieving the net zero carbon target. Although CO 2 storage in deep saline aquifers and depleted gas reservoirs has been studied extensively, most studies use commercial simulators that model faults/fractures by simply modifying the transmissibility in the direction perpendicular to the fault surfaces. Here, this work shows that this simplistic approach ignores the accelerated flow in the directions parallel to the fault plane, leading to significantly higher leakage along the fault surface. To accurately model the flow of CO 2 in faulted reservoirs, we present the first transient embedded discrete fracture model for corner-point grids (tEDFM-CPG). By comparing the results of the tEDFM-CPG to high-resolution reference solutions, we show that this approach is accurate and efficient at predicting CO 2 flow in faulted/fractured reservoirs. Finally, this work presents the use of mixed reality (MR) to efficiently observe CO 2 gas migration in the interior of these corner-point grid systems.

25 ENERGY STORAGE↗
DOE OSTI2024

Roles of kaolinite-oil-gas molecular interactions in hydrogen storage within depleted reservoirs

Hydrogen is a clean alternative to fossil fuels, emitting only water vapor during combustion. In a future hydrogen economy, large-scale storage will be an important component of the supply chain. Due to its low volumetric density, conventional surface storage methods are inadequate. Underground hydrogen storage (UHS) offers a viable solution, enabling the storage of millions of cubic meters. Among potential geological sites, including salt caverns, aquifers, and depleted gas reservoirs, depleted oil reservoirs show promise. Studying hydrogen interactions with residual oil and reservoir minerals is vital for understanding the properties of hydrogen and the reservoir post-injection. In this work, we employed molecular dynamics simulations to gain molecular-level insights into these interactions. We investigated hydrogen dissolution in oil, adsorption at kaolinite/oil interfaces, the role of CO 2 as a cushion gas, and the influence of kaolinite’s hydrophobicity on H 2 behavior. The main findings include: (1) hydrogen dissolves more in oil than in water, (2) the introduction of CO 2 suppresses hydrogen dissolution in oil and reduces the interfacial tension (IFT) between oil and gas, (3) CO 2 decreases H 2 partitioning near kaolinite surfaces due to its strong affinity for the hydrophilic gibbsite surface of kaolinite, and (4) CO 2 is more effective than H 2 in reducing IFT between kaolinite and the oil–gas mixture. These findings emphasize the effectiveness of CO 2 as a cushion gas and the important role of clay hydrophobicity in UHS, providing insights that are challenging to obtain experimentally.

08 HYDROGEN↗
DOE OSTI2021

Pumped-Storage Hydropower using Abandoned Underground Mines (PSH-AUM) as an Innovative Energy Storage Technology for Fossil-Integrated Systems

Pumped-storage hydropower (PSH) provides around 95% of all utility-scale energy storage in the U.S. and globally. Additional deployment of PSH is hampered by excessively long permitting and commissioning requirements and is constrained to locations for which natural topography provides suitable elevation relief between the upper and lower reservoirs (the ΔH challenge). The purpose of this research was to evaluate Pumped-Storage Hydropower using Abandoned Underground Mines (PSH-AUM) as a means to solve the ΔH challenge and initiate the commercialization pathway for a promising new energy storage technology. Four primary tasks were conducted: Screening and ranking of candidate sites for project development; multiphase reservoir modeling to evaluate mine performance; techno-economic analysis and preliminary designs for PSH-AUM systems integrated with fossil-fuel power units; and stakeholder engagement to identify pathways to commercialization of this new technology. Key results were achieved in each of the four primary tasks. Candidate site screening determined that nearly 10,000 underground mines were spatially locatable, of which more than 100 sites appear suitable for integration with existing fossil power plants that are expected to remain in longer-term operation. Mine reservoir models were developed using PNNL’s STOMP simulator and parameterized using candidate site data to evaluate interactions with the surrounding groundwater system and confirm the potential for some mines to accommodate inflows and outflows on the order of 100 m3/s over 8-hour durations (1.6 GWh system) without excessive aqueous pressures. Techno-economic analysis resulted in a project cost optimization scheme to identify key sensitivities and the development of preliminary designs that can minimize overall costs of deployment. Finally, stakeholder engagement with industry, state government, and local economic development leaders confirmed the viability of PSH-AUM as a promising new technology. Our Phase I project results suggest that PSH-AUM technology has a domestic market potential on the order of $100+ Billion with ample space for technology development to commercialization within the next decade.

13 HYDRO ENERGY↗
DOE OSTI2023

Arctic tropospheric ozone: assessment of current knowledge and model performance

As the third most important greenhouse gas (GHG) after carbon dioxide (CO 2 ) and methane (CH 4 ), tropospheric ozone (O 3 ) is also an air pollutant causing damage to human health and ecosystems. This study brings together recent research on observations and modeling of tropospheric O 3 in the Arctic, a rapidly warming and sensitive environment. At different locations in the Arctic, the observed surface O 3 seasonal cycles are quite different. Coastal Arctic locations, for example, have a minimum in the springtime due to O 3 depletion events resulting from surface bromine chemistry. In contrast, other Arctic locations have a maximum in the spring. The 12 state-of-the-art models used in this study lack the surface halogen chemistry needed to simulate coastal Arctic surface O 3 depletion in the springtime; however, the multi-model median (MMM) has accurate seasonal cycles at non-coastal Arctic locations. There is a large amount of variability among models, which has been previously reported, and we show that there continues to be no convergence among models or improved accuracy in simulating tropospheric O 3 and its precursor species. The MMM underestimates Arctic surface O 3 by 5% to 15% depending on the location. The vertical distribution of tropospheric O 3 is studied from recent ozonesonde measurements and the models. The models are highly variable, simulating free-tropospheric O 3 within a range of ±50% depending on the model and the altitude. The MMM performs best, within ±8% for most locations and seasons. However, nearly all models overestimate O 3 near the tropopause (~300 hPa or ~8 km), likely due to ongoing issues with underestimating the altitude of the tropopause and excessive downward transport of stratospheric O 3 at high latitudes. For example, the MMM is biased high by about 20% at Eureka. Observed and simulated O 3 precursors (CO, NO x , and reservoir PAN) are evaluated throughout the troposphere. Models underestimate wintertime CO everywhere, likely due to a combination of underestimating CO emissions and possibly overestimating OH. Throughout the vertical profile (compared to aircraft measurements), the MMM underestimates both CO and NO x but overestimates PAN. Perhaps as a result of competing deficiencies, the MMM O 3 matches the observed O 3 reasonably well. Our findings suggest that despite model updates over the last decade, model results are as highly variable as ever and have not increased in accuracy for representing Arctic tropospheric O 3 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Socio-Techno-Economic Feasibility of Deep Geothermal with EGS for Residential District Heating in the Northeastern United States

In this paper, we present socio-techno-economic simulation results for enhanced geothermal system (EGS) district heating systems in the northeastern United States. We applied the geospatial Distributed Geothermal Market Demand (dGeo) tool coupled with GEOPHIRES to evaluate the feasibility of geothermal deep direct-use, utilizing EGS reservoirs for providing residential heating with district heating systems. The results were combined with JEDI results to assess social impacts. Simulation results assuming doublet EGS reservoirs with target production temperature of 80 degrees C and newly constructed district heating systems indicate a wide range in system levelized cost of heat (LCOH) values ranging from ~$15/MMBtu to over $1,000/MMBtu, with most the attractive regions urban areas with high total thermal demand and high thermal demand density. We estimate about 60 GWth in potential installed capacity with LCOH values under $50/MMBtu and 100 GWth in potential capacity with LCOH values under $100/MMBtu, respectively.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

A cloud computing approach to massively-parallel distributed stochastic optimization with application to geomechanical reservoir characterization

Many search strategies used to optimize parameters during hydrologic model calibration are inherently limited in that simulations must be performed sequentially in order for the algorithm to converge. As a result, the overall time required to reach a solution increases linearly with the number of steps necessary. In contrast, sampling strategies that attempt to approximate the posterior distribution of the parameters do not require the model simulations to be run in sequence and therefore invite the use of a massively parallel approach across heterogeneous computing environments. We apply a cloud computing methodology to this problem where a head node running on Amazon Web Services continuously produces candidate models that are distributed to arbitrary compute environments to run the simulation, in our case Clemson’s Palmetto cluster computer. Thus the time required to obtain a sufficient number of samples to produce an adequate approximation of the posterior distribution of the parameters is limited by the number of available compute sites. Monte Carlo sampling of the posterior space would be duplicative and inefficient, thus we combine Latin hypercube methods with genetic algorithms to ensure that no large regions of the parameter space are left unexplored, and that high probability regions are investigated thoroughly. We independently assess the fit to different types of data sets without the need to construct a single objective function. Sets of Pareto optimal models are particularly valuable when the quality and information content of data is poorly known or conceptual model errors exist in our simulation. We illustrate our approach for a problem where in situ strain data are used to calibrate the parameters of an oil reservoir in the Avant oil field in Oklahoma. We use well injection and shut-in to stress a deep (500m) confined formation, and observe the geomechanical response using borehole strainmeters installed in the shallow subsurface (30m). These data were then used to calibrate the poroelastic properties of the reservoir and caprock along with the geometry of an elliptic channel associated with the formation. Using our approach we are able to identify issues with model error as well as substantial tradeoffs that occur within the parameters.

inversion, stochastic, geomechanics, poroelastic, ↗
DOE OSTI2021

A coupled thermo-hydro-mechanical model for simulating leakoff-dominated hydraulic fracturing with application to geologic carbon storage

A potential risk of injecting CO2 into storage reservoirs with marginal permeability (≲ 10 mD (1 mD = 10 –15 m 2 )) is that commercial injection rates could induce fracturing of the reservoir and/or the caprock. Such fracturing is essentially fluid-driven fracturing in the leakoff-dominated regime. Recent studies suggested that fracturing, if contained within the lower portion of the caprock complex, could substantially improve the injectivity without compromising the overall seal integrity. Modeling this phenomenon entails complex coupled interactions among the fluids, the fracture, the reservoir, and the caprock. Here, we develop a simple method to capture all these interplays in high fidelity by sequentially coupling a hydraulic fracturing module with a coupled thermal-hydrological-mechanical (THM) model for nonisothermal multiphase flow. The model was made numerically tractable by taking advantage of self-stabilizing features of leakoff-dominated fracturing. The model is validated against the PKN solution in the leakoff-dominated regime. Moreover, we employ the model to study thermo-poromechanical responses of a fluid-driven fracture in a field-scale carbon storage reservoir that is loosely based on the In Salah project's Krechba reservoir. The model reveals complex yet intriguing behaviors of the reservoir-caprock-fluid system with fracturing induced by cold CO 2 injection. We also study the effects of the in situ stress contrast between the reservoir and caprock and thermal contraction on the vertical containment of the fracture. The proposed model proves effective in simulating practical problems on length and time scales relevant to geological carbon storage.

58 GEOSCIENCES↗
DOE OSTI2020

Assessing mechanical response of CO 2 storage into a depleted carbonate reef using a site-scale geomechanical model calibrated with field tests and InSAR monitoring data

Geomechanical risks of injection have raised concerns regarding secure CO 2 storage. In this work, a combined monitoring and modeling approach is used to assess the stress changes and surface uplift associated with CO 2 injection into a depleted carbonate reef of the Michigan basin. A site-scale geomechanical model is built by assigning mechanical properties of formations using well-log and experimental data. Gravity load is applied to the model to estimate the vertical component of stress as well as different lateral boundary displacement scenarios to estimate horizontal stresses. We used a poroelastic pressure-dependent model (instead of a linear elastic mechanical earth model) to calibrate initial stresses using hydraulic fracture test data measured at depleted reservoir status. Multi-phase fluid flow-geomechanical simulations are performed to estimate the poroelastic response during (1) primary depletion (2) field-scale CO 2 injection phase (3) a hypothetical forecast scenario in which well bottom hole pressure (BHP) reach 45000 KPa. The predicted surface uplift is less than 1 mm at the end of the field-scale CO 2 injection phase which is in good agreement with Interferometric Synthetic Aperture Radar (InSAR) uplift measurement. Although the InSAR data shows an insignificant uplift, hydromechanical modeling of injection shows that CO 2 injection still causes reservoir deformation emphasizing the role of carbonate overburden and reservoir formation mechanical properties and limited size of reef on diminishing the surface deformation. Modeling indicates poroelastic response of caprock matters to estimate uplift. The lower permeability of the top two layers provides additional barrier to large uplift. Also, history of subsidence due to production should be accounted to predict uplift due to a follow up injection correctly. This report shows the significance of combining a calibrated geomechanical model with field measured stresses and monitoring data to be used as a tool to ensure the safety of CO 2 storage.

42 ENGINEERING↗
DOE OSTI2024

Dynamic Binary Complexes (DBC) as Super-Adjustable Viscosity Modifiers for Hydraulic Fracturing Fluids

In the preceding project year two, we refined three DBC formulations from a selection of over 50 different chemistries. The optimization study primarily encompassed testing for (i) reversibility extent, (ii) performance in the presence of chemical additives, (iii) adhesion and friction behavior during displacement in wellbores and pipelines, (iv) corrosion protection performance, and (v) injection performance with model fracture systems at the laboratory scale. Highly promising results obtained from all these tests signify the significant potential of DBCs in enhancing hydrocarbon recovery from unconventional reservoirs. The primary activities in the third project year included publishing experimental findings across multiple articles and conducting outreach initiatives. Throughout the year, we undertook tasks such as replicating experimental results, further optimizing various formulations and their associated experimental sets, and conducting additional tests to address missing components based on reviewer feedback and suggestions. We also explored the surfactant and friction-reduction aspects of selected formulations through drag reduction tests. In addition, we constructed an improved fracturing performance setup and performed flow injection tests. The specific DBC formulations focused on during this project period were A8/B1, A12/B5, and A10/B12. We also obtained results for additional DBC formulations and a select few commercial fracturing fluids for the purpose of comparison. Within the project's scope, we aim to enhance the experimental findings with the development of various models. The first two years focused on two key aspects: (i) the creation of a high-fidelity hydraulic fracturing model for non-Newtonian fluids to gain insights into the implementation of DBC fluids in fracking environments, and (ii) the development of a multiphase flow simulator for estimating total production, fluid saturation in the reservoir, and the creation of a fracture propagation model and kinetic Monte Carlo (kMC) models for diverse applications. In the third year, we delved into the fundamental nanostructural properties of DBCs, exploring aspects such as material chemistry, pH tunability, and control of DBC formation and stability. Subsequently, in the extension year, we conducted a systematic investigation of various building blocks containing primary, secondary, and tertiary amine functional groups to understand their impact on rheological and viscoelastic properties. Furthermore, we explored a Dissipative Particle Dynamics (DPD) model to simulate self-assembly processes with precision, creating a high-fidelity representation of relevant nanostructures. The tasks performed this year with the significant results obtained have been discussed in Section 2.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Tuning the Legacy Survey of Space and Time (LSST) Observing Strategy for Solar System Science

Abstract The Vera C. Rubin Observatory is expected to start the Legacy Survey of Space and Time (LSST) in early to mid-2025. This multiband wide-field synoptic survey will transform our view of the solar system, with the discovery and monitoring of over five million small bodies. The final survey strategy chosen for LSST has direct implications on the discoverability and characterization of solar system minor planets and passing interstellar objects. Creating an inventory of the solar system is one of the four main LSST science drivers. The LSST observing cadence is a complex optimization problem that must balance the priorities and needs of all the key LSST science areas. To design the best LSST survey strategy, a series of operation simulations using the Rubin Observatory scheduler have been generated to explore the various options for tuning observing parameters and prioritizations. We explore the impact of the various simulated LSST observing strategies on studying the solar system’s small body reservoirs. We examine what are the best observing scenarios and review what are the important considerations for maximizing LSST solar system science. In general, most of the LSST cadence simulations produce ±5% or less variations in our chosen key metrics, but a subset of the simulations significantly hinder science returns with much larger losses in the discovery and light-curve metrics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Explaining Neural Spike Activity for Simulated Bio-plausible Network through Deep Sequence Learning

With significant improvements in large-scale simulations of brain models, there is a growing need to develop tools for rapid analysis and interpreting the simulation results. In this work, we explore the potential of sequential deep learning models to understand and explain the network dynamics among the neurons extracted from a large-scale neural simulation in STACS (Simulation Tool for Asynchronous Cortical Stream). Our method employs a representative neuroscience model that abstracts the cortical dynamics with a reservoir of randomly connected spiking neurons with a low stable spike firing rate throughout the simulation duration. We subsequently analyze the spike dynamics of the simulated spiking neural network through an autoencoder model and an attention-based mechanism.

Kulkarni, Shruti↗
DOE OSTI2021

Thermal-Hydrological-Mechanical Modelling of Stockton University Reservoir Cooling System, Fine Scale Stress Test Modelling

Mesh, properties, initial conditions, injection/withdrawal rates for modelling thermal, hydrological, and mechanical effects of fluid injection to and withdrawal from ground for Stockton University reservoir cooling system (aquifer storage cooling system), Galloway, New Jersey, for unscheduled two hour injection at 133 % designed capacity, on fine scale grid, with some results. Second simulation of J.T. Smith, E. Sonnenthal, P. Dobson, P. Nico, and M. Worthington, 2021. Thermal-hydrological-mechanical modeling of Stockton University reservoir cooling system, Proceedings of the 46th Workshop on Geothermal Reservoir Engineering, Stanford University, SGP-TR-218, from which Figures 6-9, pertain.

15 GEOTHERMAL ENERGY↗