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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dakota A Multilevel Parallel Object-Oriented Framework for Design Optimization Parameter Estimation Uncertainty Quantification and Sensitivity Analysis (V.6.14) (User's Manual)

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a users manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Control Network Emulation Platform Software Package Description

The software package developed by Sandia National Laboratories is intended to allow the integration of Simulink models into emulations of control networks. To accomplish this, three programs are included: Simulink S-Function, Data Broker, and End Point

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Design and Performance of Kokkos Staging Space toward Scalable Resilient Application Couplings

With the growing number of applications designed for heterogeneous HPC devices, application programmers and users are finding it challenging to compose scalable workflows as ensembles of these applications, that are portable, performant and resilient. The Kokkos C++ library has been designed to simplify this cumbersome procedure by providing an intra-application uniform programming model and portable performance. However, assembling multiple Kokkos-enabled applications into a complex workflow is still a challenge. Although Kokkos enables a uniform programming model, the inter-application data exchange still remains a challenge from both performance and software development cost perspectives. In order to address this issue, we propose Kokkos data staging memory space, an extension of Kokkos' data abstraction (memory space) for heterogeneous computing systems. This new abstraction allows to express data on a virtual shared-space for multiple Kokkos applications, thus extending Kokkos to support inter-application data exchange to build an efficient application workflow. Additionally, we study the effectiveness of asynchronous data layout conversions for applications requiring different memory access patterns for the shared data. Our preliminary evaluation with a synthetic benchmark indicate the effectiveness of this conversion adapted to three different scenarios representing access frequency and use patterns of the shared data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Cooperative Research and Development Agreement between National Energy Technology Laboratory and VariGrid Explorations Inc. [Final Report]

The scope of this project is to advance the National Energy Technology Laboratory’s (NETL) Variable Grid Method (VGM) technology to commercial status thought enhancements upon prior work to produce a VGM application that can rapidly quantify multiple types of data and uncertainty commonly encountered by the subsurface energy industry. Along with development, the project will also include technology demonstrations, through applications using common industry data types and uncertainty metrics, to stress the value the VGM can offer the subsurface energy industry by providing an improved understanding of the strengths and limitations of their data, models, and analytical results. The resulting commercially ready VGM will offer interoperability with common industry software applications to ensure broad ‘plug and play’ functionality that will help keep costs relatively low and foster more rapid industry adoption.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Robust Real-Time Modeling of Distribution Systems with Data-Driven Grid-Wise Observability (Final Technical Report)

The overall objective of this project is to leverage existing and emerging sensor measurements to develop data-driven observability enhancement algorithms as well as robust state estimation and parameter identification techniques to enable real-time grid-wise monitoring and modeling of loads and distributed energy resources (DERs). The project resulted in a holistic framework with the following key components: 1) data-driven and machine learning-based grid-edge visibility enhancement, 2) robust branch-current-based state estimation (BCSE), and 3) robust real-time steady-state and dynamic-state modeling of loads and DERs. The research outcomes have provided utility companies better network visibility, higher-fidelity load/DER models, and more accurate assessment of DERs’ impacts, thus, facilitating the integration of renewable energy sources. The synergistic collaborative project among Iowa State University (ISU), Argonne National Laboratory (ANL), Electric Power Research Center (EPRC), SIEMENS Industry, Alliant Energy, Cedar Falls Utilities (CFU), and Maquoketa Valley Electric Cooperative (MVEC) to leverage the team’s extensive expertise and experience in power distribution systems, state estimation, online modeling and identification, and DER integrations. The proposed frameworks have been verified with industry adopted software and attempted integrated with existing tool wherever possible

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Hybrid Tandem Photovoltaics

Tandem solar cell structures are the only strategy demonstrated to surpass the detailed balance efficiency limit of high-quality single-junction solar cells. To continue to improve the efficiencies of cost-effective terrestrial solar power, hybrid tandems of dissimilar subcells are being considered by many around the world, especially designs that incorporate silicon solar cells as a bottom subcell. In this project, we studied a wide variety of tandem design possibilities including those with three-terminal (3T) and four-terminal (4T) configurations. The use of 3T and 4T designs could be useful for efficient and economical hybrid tandem designs that utilize the best available subcell materials such as emerging perovskite materials. Three-terminal configurations, in particular, have not been sufficiently studied previously. We have laid the foundational groundwork in this project for understanding the operation of 3T tandems: developing a taxonomy for naming, a methodology for measuring and interconnecting, and models for simply characterizing 3T tandems. Electrical and optical subcell coupling between the subcells was also measured and modeled. An important part of this work was the fabrication of novel example tandem structures, including 4T GaAs/Si, 3T GaInP/Si, 3T GaAs/Si, and 3T GaInP/GaAs devices. Using these high-quality tandem cells, we have been able to clearly demonstrate the achievability of high-efficiencies, and subtle physical effects such as photon recycling and luminescent coupling. We have developed and demonstrated essential building-block tools such as transparent conductive adhesives (TCA) and 3T silicon bottom cells with interdigitated back contacts (IBC) that can also be used in many other tandem designs. We have tested the reliability of these tools and devices under standardized testing and outdoor measurements. We have found 4T GaAs/Si tandems to be relatively straightforward to fabricate and robust in real-world outdoor conditions. While we have demonstrated working hybrid 3T III-V/TCA/Si IBC tandems, we experienced low yields even with our best process flows yet. Further work is still needed to improve the processing yield of these devices. We therefore also created tandem cells using an all-III-V 3T tandem process which was very robust with high yields, allowing for the creation of voltage-matched strings in many different configurations using 8 nearly identical 3T tandems. Using these robust 3T tandem examples, we were able measure and precisely characterize 3T tandem behaviors to predict their operation under changing spectrum and temperature. The optoelectronic equivalent-circuit model was shown to be very general and applicable to hybrid tandems, and encompassed the operation 3T Si IBC cells. This general model has been distributed to the public in as open-source Python-based software called PVcircuit. We have calculated the implications of these new tandem device designs on the real-world energy production and shown how the relative performance of different tandem configurations is situational and can be engineered using the tools developed here.

14 SOLAR ENERGY↗
DOE OSTI2023

Thermal Modeling of Advanced Test Reactor Fuel in a Generalized Dry Storage System Under Hypothetical Accident Conditions

Work was performed to investigate the thermal behavior of a sealed aluminum-clad spent nuclear fuel (ASNF) dry storage configuration under hypothetical accident conditions during long-term storage. The considered system consists of a concrete dry storage overpack; a welded over canister, backfilled with argon; and nine Department of Energy (DOE) standardized canisters (DOESCs) loaded with ASNF, backfilled with helium gas. One technical concern associated with the long-term storage of ASNF includes radiolytic hydrogen generation. The yield of large quantities of hydrogen could lead to DOESC over pressurization or a flammable internal atmosphere. While flammability concerns can be resolved by preventing the ingress of oxygen, the canister pressure is partially controlled by the atmosphere temperature. This memorandum summarizes the results of modeling and simulation (M&S) work completed with Star CCM+ (a computational fluid dynamics [CFD] software) considering the thermal effects of a fully engulfing flame and another scenario with the vent ports of the concrete dry storage overpack completely blocked. The goal was to determine the bounding maximum temperature of the DOESC internal atmosphere to evaluate a worst-case pressure scenario, as well as the critical vent port blockage durations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Complete Demonstration of a Prototype Version of FORCE User Interface and Conduct Analyst Survey Collecting Feedback on Interface Features and Usability

In 2024 the US Department of Energy (DOE) Office of Nuclear Energy (NE) Integrated Energy System (IES) program continued to develop the Framework for Optimization of Resources and Economics (FORCE) analysis ecosystem into a more traditional toolset with simplified software installation, automated workflows, and interactive results visualization. The DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench continued to be leveraged for user input, application workflow and runtime environment, and interactive results visualization capabilities. This report documents the demonstration of a FORCE User Interface (UI) prototype and the results of a survey of analysts’ using the Holistic Energy Resource Optimization Network (HERON) tool in FORCE with the prototype UI.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Constraints on the Gamma-Ray Emission from Small Solar System Bodies with the Fermi Large Area Telescope Data

All known small solar system bodies have diameters between a few meters and a few thousands of kilometers. Based on the collisional evolution of solar system bodies, a larger number of asteroids with diameters down to ~2 m is thought to exist. As all solar system bodies, small bodies can be passive sources of high-energy gamma-rays, produced by the interaction of energetic cosmic rays impinging on their surfaces. Since the majority of known asteroids are in orbits between Mars and Jupiter (in a region known as the Main Belt), we expect them to produce a diffuse emission close to the ecliptic plane. In this work, we have studied the gamma-ray emission coming from the ecliptic using the data collected by the Large Area Telescope (LAT) onboard the Fermi satellite. We have fit the results with simulations of the gamma-ray intensity at the source level (calculated with the software FLUKA) to constrain the small solar system bodies population. Finally, we have proposed a model describing the distribution of asteroid sizes and we have used the LAT data to constrain the gamma-ray emission expected from this model and, in turn, on the model itself.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Hybrid Curve Fitting For Reducing Motion Commands In Object Construction

Existing slicing software for additive manufacturing typically requires a triangulated mesh as its input. Triangulated meshes are approximate representations of exact CAD models. Despite the loss in dimensional accuracy, triangulated meshes are used because they are computationally easier to cross-section and offset than the exact geometry in CAD format. When a triangulated object is prepared, the resulting machine instructions include only linear motion commands. Numerous modern motion controllers can move in arc and spline motions; however, the absence of slicing software that supports curvature prevents these commands from being leveraged. To address this limitation, this paper presents a method for the hybrid reconstruction of arcs and splines as a post-processing step to traditional slicing. This method can greatly reduce the number of motion commands required to construct an object by printing smooth curved surfaces. This concise representation of tool-pathing allows for more even extrusion and is computed without a major impact on slicing time.

Wade, Charles↗
DOE OSTI2023

Supporting Nuclear Energy Research with MLOps

Artificial intelligence (AI) and machine learning (ML) have been shown to be increasingly helpful tools in a growing number of use-cases relevant to scientific research, despite significant software-related obstacles. There exist large technical costs to setting up, using, and maintaining AI/ML models in production. This often prevents researchers from utilizing these models in their work. The growing field of machine learning operations (MLOps) aims to automate much of the AI/ML life cycle while increasing access to these models. This paper presents our initial work in creating a nuclear energy MLOps platform for use by researchers at Idaho National Laboratory (INL) and aims to reduce the barriers of using AI/ML in scientific research. We hope to promote the integration of the latest AI/ML technologies into researchers' workflows and create more opportunity for scientific innovation. In this paper we discuss how our MLOps efforts aim to increase usage and the impact of AI/ML models created by engineers. We also present several use-cases that are currently integrated. Finally, we evaluate the maturity of our project as well as our plans for future functionality.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Hydrogeological assessment of CO2 containment assurance and wellbore integrity at a Gulf Coast storage site

Abstract A large-scale carbon capture and storage (CCS) initiative on the Texas Gulf Coast serves as a premier demonstration of the U.S. Department of Energy’s CarbonSAFE program. Targeting deep saline formations, specifically Oligo-Miocene deltaic sequences, the project aims to establish technical and commercial viability for geologic CO2 storage within a major industrial corridor. This study provides a rigorous hydrogeological assessment to support Class VI permitting by quantifying the high degree of containment security. Utilizing a compositional reservoir simulator, we developed a suite of 27 distinct simulation cases to evaluate vertical plume dynamics near both planned injection wells and proximal legacy infrastructure. To ensure numerical accuracy near wellbores, we implemented a refined mesh strategy, determining that a 5.6 ft × 5.6 ft grid refinement offered the optimal balance between computational efficiency and descriptive precision. The modeling framework utilized a systematic sensitivity-based approach to evaluate the mechanical redundancy of the subsurface system by performing a bounding analysis of wellbore interfaces against hypothetical high-permeability microannuli. By systematically isolating competing physical drivers, including permeability, porosity, gas hysteresis, thermal gradients, salinity, and solubility trapping (quantified via Henry’s law with dynamically adjusted coefficients), this work moves beyond binary assessments to establish a nuanced hierarchy of containment factors. The results confirm that primary trapping mechanisms (e.g., gas hysteresis and solubility), combined with the site's unique geomechanical stratigraphy, significantly restrict vertical mobility and reinforce the robust containment security of the reservoir. Baseline results demonstrate substantial vertical separation between the CO2 plume and the upper confining system, ensuring robust containment. Sensitivity analysis reveals that even under highly conservative bounding scenarios—assuming theoretical 10-Darcy pathways at specific wellbore locations—the 2,900-ft thick multi-layered confining zone remains a reliable barrier. In these hypothetical upper-bound cases, peak upward fluxes of CO2 and saltwater after 15 years of injection remain localized and dissipate rapidly within the lower sections of the confining interval, leaving the integrity of the seal uncompromised. Furthermore, the study identifies that while localized wellbore pathways define theoretical upper bounds of vertical migration, the Area of Review (AoR) is primarily sensitive to regional thermal gradients and hysteresis, which can influence the AoR by over 3,000 acres in pessimistic configurations. Also, primary trapping mechanisms, specifically gas hysteresis and solubility, work in tandem with the Gulf Coast’s unique geomechanical stratigraphy to significantly restrict vertical mobility. Ductile, smectite-rich mudstones facilitate natural borehole convergence and the self-healing of potential conduits, creating a natural geomechanical bridge that effectively mitigates migration potential at both current injection points and legacy-well locations. This comprehensive modeling effort demonstrates that the integration of high-resolution wellbore simulations and regional geomechanical observations confirms the long-term storage security of the studied site, providing a physics-based foundation for industrial-scale CCS deployments. This modeling framework establishes a baseline for future research into coupled geomechanical effects, such as time-dependent borehole convergence, to further refine long-term containment projections. Acknowledgements We thank the Gulf Coast Carbon Center (GCCC) at the Bureau of Economic Geology for foundational research support. We appreciate Alex Bump for technical guidance and David Hoffman for model mesh generation. This work used TACC’s Frontera cluster for simulations and CMG Ltd. software licenses provided to UT-Austin. This material is based upon work supported by the Department of Energy under Award Number DE-FE0032338. Disclaimer This material is based upon work supported by the U.S. Department of Energy’s Fossil Energy and Carbon Management Office under the CarbonSAFE program, award Number DE-FE0032338. The views expressed herein do not necessarily represent the views of the U.S. Department of Energy or the United States Government.

58 GEOSCIENCES↗
DOE OSTI2026

Hydrogeological assessment of CO2 containment assurance and wellbore integrity at a Gulf Coast storage site

Abstract A large-scale carbon capture and storage (CCS) initiative on the Texas Gulf Coast serves as a premier demonstration of the U.S. Department of Energy’s CarbonSAFE program. Targeting deep saline formations, specifically Oligo-Miocene deltaic sequences, the project aims to establish technical and commercial viability for geologic CO2 storage within a major industrial corridor. This study provides a rigorous hydrogeological assessment to support Class VI permitting by quantifying the high degree of containment security. Utilizing a compositional reservoir simulator, we developed a suite of 27 distinct simulation cases to evaluate vertical plume dynamics near both planned injection wells and proximal legacy infrastructure. To ensure numerical accuracy near wellbores, we implemented a refined mesh strategy, determining that a 5.6 ft × 5.6 ft grid refinement offered the optimal balance between computational efficiency and descriptive precision. The modeling framework utilized a systematic sensitivity-based approach to evaluate the mechanical redundancy of the subsurface system by performing a bounding analysis of wellbore interfaces against hypothetical high-permeability microannuli. By systematically isolating competing physical drivers, including permeability, porosity, gas hysteresis, thermal gradients, salinity, and solubility trapping (quantified via Henry’s law with dynamically adjusted coefficients), this work moves beyond binary assessments to establish a nuanced hierarchy of containment factors. The results confirm that primary trapping mechanisms (e.g., gas hysteresis and solubility), combined with the site's unique geomechanical stratigraphy, significantly restrict vertical mobility and reinforce the robust containment security of the reservoir. Baseline results demonstrate substantial vertical separation between the CO2 plume and the upper confining system, ensuring robust containment. Sensitivity analysis reveals that even under highly conservative bounding scenarios—assuming theoretical 10-Darcy pathways at specific wellbore locations—the 2,900-ft thick multi-layered confining zone remains a reliable barrier. In these hypothetical upper-bound cases, peak upward fluxes of CO2 and saltwater after 15 years of injection remain localized and dissipate rapidly within the lower sections of the confining interval, leaving the integrity of the seal uncompromised. Furthermore, the study identifies that while localized wellbore pathways define theoretical upper bounds of vertical migration, the Area of Review (AoR) is primarily sensitive to regional thermal gradients and hysteresis, which can influence the AoR by over 3,000 acres in pessimistic configurations. Also, primary trapping mechanisms, specifically gas hysteresis and solubility, work in tandem with the Gulf Coast’s unique geomechanical stratigraphy to significantly restrict vertical mobility. Ductile, smectite-rich mudstones facilitate natural borehole convergence and the self-healing of potential conduits, creating a natural geomechanical bridge that effectively mitigates migration potential at both current injection points and legacy-well locations. This comprehensive modeling effort demonstrates that the integration of high-resolution wellbore simulations and regional geomechanical observations confirms the long-term storage security of the studied site, providing a physics-based foundation for industrial-scale CCS deployments. This modeling framework establishes a baseline for future research into coupled geomechanical effects, such as time-dependent borehole convergence, to further refine long-term containment projections. Acknowledgements We thank the Gulf Coast Carbon Center (GCCC) at the Bureau of Economic Geology for foundational research support. We appreciate Alex Bump for technical guidance and David Hoffman for model mesh generation. This work used TACC’s Frontera cluster for simulations and CMG Ltd. software licenses provided to UT-Austin. This material is based upon work supported by the Department of Energy under Award Number DE-FE0032338. Disclaimer This material is based upon work supported by the U.S. Department of Energy’s Fossil Energy and Carbon Management Office under the CarbonSAFE program, award Number DE-FE0032338. The views expressed herein do not necessarily represent the views of the U.S. Department of Energy or the United States Government.

58 GEOSCIENCES↗
DOE OSTI2023

Creating a Simulation Platform for Research and Development of Advanced Control Methods

Advanced nuclear reactors are essential to meet the changing energy requirements throughout both the United States and the rest of world. In addition to other features, they are designed to enable deployment in remote locations and operate in a fully (or near-fully) autonomous manner, which will require a new control paradigm. To realize autonomously operating reactors, the U.S. Department of Energy’s Nuclear Energy Enabling Technologies Advanced Sensors and Instrumentation (NEET ASI) program conducts research and development into the enabling technologies and methods needed, including digital twins, machine learning, and risk modeling, in addition to various types of control methods. These technologies and methods are the key foundations needed to achieve fully autonomous systems. To develop and evaluate the technologies and methods necessary for achieving autonomous operations, it is critical to identify a software tool capable of integrating all the required elements. In surveying the available solutions, no software platforms were identified that could accomplish what was needed without introducing drawbacks. This challenge was the motivation for the current effort: to develop a software platform that can seamlessly integrate autonomouscontrol-enabling technologies and methods, allowing for accelerated research and development and transfer of ideas. The resulting platform, known as the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND), is Python-based, and leverages open-source tools to provide flexibility and facilitate building upon prior research. It is designed to enable advanced reactor developers to deploy and test advanced control technologies and methods coupled with their own models, solutions, and hardware. Given the substantial undertaking of developing such a platform, the current effort focused on laying down scalable, flexible software foundations and infrastructure, then demonstrating the platform via a use case. These foundations included developing generic modules, which contain the base variable and system blocks (the information and functional building blocks, respectively, that can be used to design a simulation) and the data handling and storage blocks needed to exchange information between the various blocks; as well as enablingtechnology-specific modules. This platform was evaluated via a use case, which was to simulate and control a process for the Microreactor Automated Control System (MACS) test bed. While MACS is not currently directly coupled to any specific microreactor physics, it was initially developed in concert with the Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and so the MARVEL physics are used here. As part of this use case, several enabling-technology-specific blocks within COMMAND were integrated, including a proportional integral derivative (PID) control block, a Reactor Excursion and Leak Analysis Program (RELAP5-3D) block, and an anomaly detection block. The COMMAND software platform was successfully demonstrated to achieve the scalability and flexibility objectives of this effort and will be leveraged by the program’s research efforts to advance state of the art control methodologies towards autonomous operations of advanced reactors. As new use cases are created and implemented, it is anticipated that COMMAND will continue to grow and evolve to meet new requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Automatically generated model for light alkene combustion

Light alkenes are common combustion intermediates for a variety of fuels. Therefore, understanding their oxidation and pyrolysis chemistry is key to building detailed mechanisms for heavier fuels. This work was focused on the development and evaluation of a detailed kinetic mechanism suitable for the combustion of light alkenes up to C 4 without the use of tuned parameters, instead, the parameter values come from first principles or direct measurements. The generated mechanism accurately estimates the laminar burning velocity (S u ) and ignition delay time (IDT) of light alkenes available in the literature, which represent fundamental combustion properties at a wide range of conditions. Because each parameter is thought to have a physically realistic value, not tuned to these measurements, the new model could be used as a sub-mechanism in models for other applications. The reaction network was generated with the open-source Reaction Mechanism Generator (RMG) software. Sensitivity analyses were performed under wide ranges of temperatures and pressures, allowing for the identification of the most impactful species and reactions. Based on these, a comprehensive thermochemistry database, including calculations on 550 molecules performed in this work at the CBS-QB3 level of theory, and a kinetic library, including theoretically-derived reaction rates retrieved from the literature, were built and used in the mechanism generation. The developed mechanism was compared against several existing detailed kinetic mechanisms for ethene, propene, 1-butene, 2-butene, and isobutene. Here, the newly generated model is the most accurate among the ones analyzed, in terms of fractional bias and normalized mean square error. Hence, this new model was used to analyze the chemistry of alkene combustion. Key rate coefficients were compared, to identify the cause of deviations between the models and possible areas for further improvements.

09 BIOMASS FUELS↗
DOE OSTI2024

Regional-scale fault-to-structure earthquake simulations with the EQSIM framework: Workflow maturation and computational performance on GPU-accelerated exascale platforms

Continuous advancements in scientific and engineering understanding of earthquake phenomena, combined with the associated development of representative physics-based models, is providing a foundation for high-performance, fault-to-structure earthquake simulations. However, regional-scale applications of high-performance models have been challenged by the computational requirements at the resolutions required for engineering risk assessments. The EarthQuake SIMulation (EQSIM) framework, a software application development under the US Department of Energy (DOE) Exascale Computing Project, is focused on overcoming the existing computational barriers and enabling routine regional-scale simulations at resolutions relevant to a breadth of engineered systems. This multidisciplinary software development—drawing upon expertise in geophysics, engineering, applied math and computer science—is preparing the advanced computational workflow necessary to fully exploit the DOE’s exaflop computer platforms coming online in the 2023 to 2024 timeframe. Achievement of the computational performance required for high-resolution regional models containing upward of hundreds of billions to trillions of model grid points requires numerical efficiency in every phase of a regional simulation. This includes run time start-up and regional model generation, effective distribution of the computational workload across thousands of computer nodes, efficient coupling of regional geophysics and local engineering models, and application-tailored highly efficient transfer, storage, and interrogation of very large volumes of simulation data. This article summarizes the most recent advancements and refinements incorporated in the workflow design for the EQSIM integrated fault-to-structure framework, which are based on extensive numerical testing across multiple graphics processing unit (GPU)-accelerated platforms, and demonstrates the computational performance achieved on the world’s first exaflop computer platform through representative regional-scale earthquake simulations for the San Francisco Bay Area in California, USA.

58 GEOSCIENCES↗