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At least 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Comparing XRISM Cluster Velocity Dispersions with Predictions from Cosmological Simulations: Are Feedback Models Too Ejective?

The dynamics of the intracluster medium (ICM), the hot plasma that fills galaxy clusters, are shaped by gravity-driven cluster mergers and feedback from supermassive black holes (SMBHs) in the cluster cores. XRISM measurements of ICM velocities in several clusters offer insights into these processes. We compare XRISM measurements for nine galaxy clusters (Virgo, Perseus, Centaurus, Hydra-A, PKS 0745–19, A2029, Coma, A2319, and Ophiuchus) with predictions from three state-of-the-art cosmological simulation suites, TNG-Cluster, the Three Hundred Project GADGET-X, and GIZMO-SIMBA, that employ different models of feedback. In cool cores, XRISM reveals systematically lower velocity dispersions than the simulations predict, with all 10 measurements below the median simulated values by a factor of 1.5–1.7 on average and all falling within the bottom 10% of the predicted distributions. The observed kinetic-to-total pressure ratio is also lower, with a median value of 2.2%, compared to the predicted 5.0%–6.5% for the three simulations. Outside the cool cores and in non-cool-core (NCC) clusters, simulations show better agreement with XRISM measurements, except for the outskirts of the relaxed, cool-core cluster A2029, which exhibits an exceptionally low kinetic pressure support (<1%), with none of the simulated systems in either of the three suites reaching such low levels. The NCC Coma and A2319 exhibit dispersions at the lower end but within the simulated spread. Our comparison suggests that the three numerical models may overestimate the kinetic effects of SMBH feedback in cluster cores. Additional XRISM observations of NCC clusters will clarify if there is a systematic tension in the gravity-dominated regime as well.

galaxy clusters↗
DOE OSTI2020

An Empirical Study on the Use of the Rancor Microworld Simulator to Support Full-scope Data Collection

A lack of data has been identified as a major challenge in human reliability analysis (HRA). Accordingly, several institutes and researchers have tried to collect HRA data from different data sources such as actual historical measurements, expert judgements, or simulator studies. While the most recent studies predominantly focus on collecting data using full-scope simulators with actual operators, Idaho National Laboratory (INL) has begun to collect HRA data using a simplified simulator, i.e., the Rancor Microworld simulator, with student participants. Full-scope studies have been known to have several intrinsic challenges to securing enough quantity of the data due to many reasons like the high cost for performing experiments or requiring actual operators’ cooperation. The ultimate goal of INL’s effort aims to infer actual operators’ data collected from a full-scope simulator on the basis of microworld data with student subjects as well as collect additional data that could be missed in the full-scope research. As a first step to achieve this goal, this paper projects an experimental plan for investigating the differences in human performance between individuals in two groups: 1) an actual operator and 2) a student when using the Rancor Microworld simulator. A randomized factorial experiment design has been developed with two independent variables, i.e., type of scenario and type of subject. Six human performance measures, i.e., 1) time, 2) error, 3) workload, 4) situation awareness, 5) patterns of attention and 6) the number of manipulations were selected. A couple of scenarios and their procedures available to the Rancor Microworld simulator have been developed.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

Simulating Microbial Community Patterning Using Biocellion

Mathematical modeling and computer simulation are important tools for understanding complex interactions between cells and their biotic and abiotic environment: similarities and differences between modeled and observed behavior provide the basis for hypothesis forma- tion. Momeni et al. [5] investigated pattern formation in communities of yeast strains engaging in different types of ecological interactions, comparing the predictions of mathematical modeling and simulation to actual patterns observed in wet-lab experiments. However, simu- lations of millions of cells in a three-dimensional community are ex- tremely time-consuming. One simulation run in MATLAB may take a week or longer, inhibiting exploration of the vast space of parameter combinations and assumptions. Improving the speed, scale, and accu- racy of such simulations facilitates hypothesis formation and expedites discovery. Biocellion is a high performance software framework for ac- celerating discrete agent-based simulation of biological systems with millions to trillions of cells. Simulations of comparable scale and accu- racy to those taking a week of computer time using MATLAB require just hours using Biocellion on a multicore workstation. Biocellion fur- ther accelerates large scale, high resolution simulations using cluster computers by partitioning the work to run on multiple compute nodes. Biocellion targets computational biologists who have mathematical modeling backgrounds and basic C++ programming skills. This chap- ter describes the necessary steps to adapt the original Momeni et al.'s model to the Biocellion framework as a case study.

metabolic interaction↗
DOE OSTI2014

FNCS: A Framework for Power System and Communication Networks Co-Simulation

This paper describes the Fenix framework that uses a federated approach for integrating power grid and communication network simulators. Compared existing approaches, Fenix al- lows co-simulation of both transmission and distribution level power grid simulators with the communication network sim- ulator. To reduce the performance overhead of time synchro- nization, Fenix utilizes optimistic synchronization strategies that make speculative decisions about when the simulators are going to exchange messages. GridLAB-D (a distribution simulator), PowerFlow (a transmission simulator), and ns-3 (a telecommunication simulator) are integrated with the frame- work and are used to illustrate the enhanced performance pro- vided by speculative multi-threading on a smart grid applica- tion. Our speculative multi-threading approach achieved on average 20% improvement over the existing synchronization methods

Co-simulation↗
DOE OSTI2017

Optimizing for Large Planar Fractures in Multistage Horizontal Wells in Enhanced Geothermal Systems Using a Coupled Fluid and Geomechanics Simulator

Enhanced Geothermal Systems (EGS) could potentially use technological advancements in coupled implementation of horizontal drilling and multistage hydraulic fracturing techniques in tight oil and shale gas reservoirs along with improvements in reservoir simulation techniques to design and create EGS reservoirs. In this study, a commercial hydraulic fracture simulation package, Mangrove by Schlumberger, was used in an EGS model with largely distributed pre-existing natural fractures to model fracture propagation during the creation of a complex fracture network. The main goal of this study is to investigate optimum treatment parameters in creating multiple large, planar fractures to hydraulically connect a horizontal injection well and a horizontal production well that are 10,000 ft. deep and spaced 500 ft. apart from each other. A matrix of simulations for this study was carried out to determine the influence of reservoir and treatment parameters on preventing (or aiding) the creation of large planar fractures. The reservoir parameters investigated during the matrix simulations include the in-situ stress state and properties of the natural fracture set such as the primary and secondary fracture orientation, average fracture length, and average fracture spacing. The treatment parameters investigated during the simulations were fluid viscosity, proppant concentration, pump rate, and pump volume. A final simulation with optimized design parameters was performed. The optimized design simulation indicated that high fluid viscosity, high proppant concentration, large pump volume and pump rate tend to minimize the complexity of the created fracture network. Additionally, a reservoir with 'friendly' formation characteristics such as large stress anisotropy, natural fractures set parallel to the maximum horizontal principal stress (SHmax), and large natural fracture spacing also promote the creation of large planar fractures while minimizing fracture complexity.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Fast Learning for Immersive Engagement in Energy Simulations

The fast computation which is critical for immersive engagement with and learning from energy simulations would be furthered by developing a general method for creating rapidly computed simplified versions of NREL's computation-intensive energy simulations. Created using machine learning techniques, these 'reduced form' simulations can provide statistically sound estimates of the results of the full simulations at a fraction of the computational cost with response times - typically less than one minute of wall-clock time - suitable for real-time human-in-the-loop design and analysis. Additionally, uncertainty quantification techniques can document the accuracy of the approximate models and their domain of validity. Approximation methods are applicable to a wide range of computational models, including supply-chain models, electric power grid simulations, and building models. These reduced-form representations cannot replace or re-implement existing simulations, but instead supplement them by enabling rapid scenario design and quality assurance for large sets of simulations. We present an overview of the framework and methods we have implemented for developing these reduced-form representations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Multi-physics Object Oriented Simulation Environment (MOOSE)

This two-day workshop is a hands-on introduction to the Multi-Physics Object Oriented Simulation Environment (MOOSE). MOOSE is a simulation framework built from PETSc that enables efficient simulation of complex physical systems with minimal programming background. Attendees are encouraged to visit the MOOSE website at www.mooseframework.org and walk through the step by step process of installing the framework on their computer. Support through this process is provided through the MOOSE Google Group message board. The workshop itself will consist of interactive modules where instructors from the MOOSE development team will work with attendees to build a simple plasma model. Each module will build on previous modules to introduce fundamental MOOSE features that will combine to demonstrate simulation capabilities for low temperature plasma modeling. The intention is not to provide an exhaustive overview of simulation capabilities but to instead provide attendees with the necessary tools to build unique simulation capabilities for their specific research challenges. Users should attend the workshop with laptop computers with MOOSE installed to allow for interactive instruction. At the completion of the workshop attendees will be able to install and run MOOSE and associated applications as well as carry out plasma simulations studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

VALIDATION AND DETERMINATION OF SIGNIFICANT SIMULATION PARAMETERS USING THE SMOOTHED PARTICLE HYDRODYNAMIC CODE NEUTRINO

In recent years there has been an increase in flooding concern to nuclear power plants; thus, tools to reduce the cost of mitigation efforts are valuable to industry. Simulating flooding events is achieved through different methods and at varied levels of detail. However, these simulations must be able to match application conditions, which requires code validation as well as knowledge of which parameters affect the accuracy of the simulation. To validate and determine the significant parameters for these tools, a sloshing experiment was conducted at the George Washington University and then simulated with the smoothed particle hydrodynamic code Neutrino. The simulation setup was constructed to match the experiment as closely as possible, and the end-wall pressure results were analysed. The 90% and 50% end-wall pressure bounds were compared along with the pressure impulse. The simulation bounds fell mostly within the experimental bounds, with exceptions in insignificant low-pressure areas, such as at the beginning (~40% difference) and the end of the cycle (~40% difference). Another exception was seen at a point in the peak pressure (~75% difference). The simulated pressure impulse matched the experiments well and was within 10%. Additionally, seven parameters were qualitatively assessed and then investigated to determine their significance. The parameters’ significance was determined by sampling five values across the parameters’ range using the Risk Analysis Virtual Environment, then comparing the average pressure for each run. All seven parameters were identified as having some significance. However, the particle size, interaction-radius to particle-size ratio, and fluid settling seem to have a greater effect due to the larger fluctuation of the results. Now that the significant parameters are identified, further research is being done to quantify the significance of each parameter.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

SimNet: Accurate and High-Performance Computer Architecture Simulation using Deep Learning

While cycle-accurate simulators are essential tools for architecture research, design, and development, their practicality is limited by an extremely long time-to-solution for realistic applications under investigation. This work describes a concerted effort, where machine learning (ML) is used to accelerate microarchitecture simulation. First, an ML-based instruction latency prediction framework that accounts for both static instruction properties and dynamic processor states is constructed. Then, a GPU-accelerated parallel simulator is implemented based on the proposed instruction latency predictor, and its simulation accuracy and throughput are validated and evaluated against a state-of-the-art simulator. Leveraging modern GPUs, the ML-based simulator outperforms traditional CPU-based simulators significantly.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Roadmap for IES Modeling and Simulation Activities

Since inception of the DOE-NE Integrated Energy Systems (IES) program, several program and modeling visions and roadmaps have been published. In 2017, the last modeling and simulation capability development plan was published. In 2020, a comprehensive roadmap for the DOE-NE Integrated Energy Systems program has been published. The current report is meant to update the 2017 modeling and simulation capability roadmap and complement the IES overall program roadmap published in 2020. The role of modeling and simulation within IES is to support the demonstration of new coupled integrated technologies along every step of the technology maturation from the strategic analysis of preferred system architecture to preliminary design, to laboratory testing, up to full commercial testing and integration. To achieve this role, modeling and simulation must be able to assess the technical performance and the economic viability of potential IES. Also, modeling and simulation must provide support for experimental evaluations, i.e., support component design and real time operations of experimental demonstration systems. Finally, modeling and simulation can help scale-up experimental systems to the final commercial systems. This report details the current state of the modeling and simulation efforts within IES for the above-mentioned areas, provides a gap analysis and proposes next steps for a time horizon over the next 4 to 5 years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Simulating the Effect of Fracture Connectivity on Repository Performance with GDSA Framework - 18589

This work examines the possible migration of radionuclides from a deep geologic nuclear waste repository sited in fractured crystalline host rock. The key safety concern is the potential effect on waste isolation of the inter-connectivity of the fracture network, which is primarily established by the temporal evolution of the temperature and stress fields at the time of original rock intrusion and cooling. Two end members are considered in these simulations, one with a high degree of connectivity to the biosphere, such that advective transport through the fracture and fault network controls radionuclide migration, and the other with a low degree of connectivity, such that slow diffusive transport through the crystalline rock matrix is the controlling process for radionuclide migration to the biosphere. Both end members have several areally extensive, high-transmissivity deformation zones, whose distance to the repository is an important factor for waste isolation capability. Uncertainties in fracture properties (transmissivity, orientation, radius) and fracture distribution also give rise to uncertainty in waste isolation capability (i.e., the overall connectivity of the repository with the surface biosphere). These types of natural system uncertainties are generally present in any geologic site-characterization program and thus represent an important factor in assessing repository performance in hard rock environments. The waste considered in these simulations are spent fuel rod assemblies from the U.S. commercial nuclear reactor fleet. Thermal output of the waste must be considered in the simulations and can influence the rate and timing of waste package failure, waste form degradation, and fluid flux due to thermal expansion around the repository horizon. To achieve a high-fidelity representation of radionuclide transport in fractures and rock matrix, combined with thermal energy transport and fluid flow in fractures and matrix, the mathematical model is solved numerically in a parallel high-performance computing (HPC) environment on a finite volume unstructured grid consisting of approximately 5 million cells, using Geologic Disposal Safety Assessment (GDSA) Framework (https://pa.sandia.gov), an open-source performance assessment tool for deep underground disposal of nuclear waste. GDSA Framework uses PFLOTRAN to solve the balance equations on a three-dimensional grid with heterogeneous properties, using multiple processors in a parallel configuration based on domain decomposition. The fracture networks in these simulations are originally generated as discrete fracture networks (DFNs), which are sets of two-dimensional planes distributed in a three-dimensional domain. The method used in GDSA Framework maps the stochastically generated DFN to an equivalent continuous porous medium (ECPM) domain that allows for the simulation of coupled heat flow, fluid flow, and radionuclide transport, including heat conduction through the matrix of the fractured rock, which is a process not easily modeled in a DFN representation. Computational efficiency is also greatly enhanced using the ECPM method, allowing for a realistic representation and analysis of uncertainties in a multi-realization performance assessment of a deep geologic repository. The effect of fracture connectivity on the waste isolation safety function, as brought to light by these GDSA Framework simulations, points to the importance of including a realistic representation of uncertainties in fracture properties and distribution (effectively, uncertainty in spatial heterogeneity) in repository safety assessment simulations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

The Next Generation System Analysis Model: Capabilities for Simulating a Waste Management System - 19131

The U.S. Department of Energy (DOE) Office of Nuclear Energy Office of Spent Fuel and Waste Disposition's Integrated Waste Management System (IWMS) program is applying integrated waste management system architecture analysis, system engineering, and decision analysis principles to inform potential future decisions regarding potential nuclear waste management system architectures. Architecture analyses of the IWMS are being conducted to support the future deployment of a comprehensive system for managing nuclear waste that considers all major aspects of the back end of the nuclear fuel cycle (i.e., transportation, storage, and disposal). The system architecture analyses consider alternative disposition pathways for commercial spent nuclear fuel (SNF) being stored dry in at-reactor Independent Spent Fuel Storage Installations (ISFSIs) or wet in spent-fuel pools. One method for evaluating these alternatives is simulating the movement of SNF throughout the system components. Successfully simulating a system on the scale of a national waste management system requires - accurate baseline information (e.g., historic fuel discharges from reactors and dry storage loadings at reactor sites), - modeling all logistic interactions between components of the proposed system, and - tracking and reporting all relevant details regarding the simulation's execution. The Next Generation System Analysis Model (NGSAM) is an agent-based simulation software tool designed for the express purpose of modeling the IWMS. It is based on the Performance Analysis Tool, a simulation platform that has been used to model logistics for the Department of Defense and the Federal Emergency Management Agency. Using existing, government-owned software allows NGSAM developers to modify the software at the level of source code and to develop flexible usability and modeling solutions for developing and running simulations of the IWMS. NGSAM imports data from the Oak Ridge National Laboratory (ORNL) Unified Database (e.g., historic assembly information, thermal profiles for assembly heat, at-reactor dry storage loadings) to ensure that the simulation initializes with a realistic representation of the state of commercial SNF in the United States. NGSAM is designed with the flexibility to model and track the behavior of virtually any IWMS architecture assumptions or design considerations. For example, NGSAM can model multiple interim storage facilities or repositories or none at all. Similarly, all assumptions regarding shipment schedules, operating schedules, and reactor operation assumptions can be modeled and adjusted in NGSAM with relative ease. The development of NGSAM was targeted to waste management system analysts as the primary users. With that in mind, analysts from ORNL, Sandia National Laboratories (SNL), and Argonne National Laboratory (ANL) were intimately involved in the development process. That involvement extended beyond merely defining requirements. System analysts have been involved with design decisions and software benchmarking and tests, and they have provided subject-matter expertise where necessary. The result is a high degree of interaction between professional software developers and system analysts, with a multitude of benefits to both groups. This paper explores some of the underlying methodology of the agile software development process used in the creation of NGSAM. It illustrates the capabilities of NGSAM. Some example use cases are discussed as well, with relevant results providing context for how NGSAM is used by system analysts to gain a greater understanding of alternative waste management system architectures. This is a technical paper that does not take into account the contractual limitations under the Standard Contract for Disposal of Spent Nuclear Fuel and/or High-Level Radioactive Waste (Standard Contract) (10 CFR Part 961). Under the provisions of the Standard Contract, DOE does not consider spent nuclear fuel in multi-assembly canisters to be an acceptable waste form, absent a mutually agreed-to contract amendment. To the extent discussions or recommendations in this paper conflict with the provisions of the Standard Contract, the Standard Contract provisions prevail. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Kinetic Monte Carlo Simulations of Chemical Reactions on Surfaces

Lattice based kinetic Monte Carlo (kMC) simulations are a powerful tool for micro-kinetic modeling. The kinetic Monte Carlo technique stochastically simulates chemical reaction processes (e.g. adsorption, desorption, diffusion), where the probability of a given reaction process being selected is weighted by its rate constant. The open source software package, KMOS1, allows fast construction of kMC simulations by automatically implementing a computationally efficient kMC framework, thus allowing the researcher to focus on accurate parameterization and formulation of the kinetic model. From this, the spatiotemporal evolution (e.g. concentration, surface configuration, turnover frequencies) of crystal surfaces or bulk crystalline structures is obtained. KMOS uses the variable step-size method implementation of kMC. At each step, the VSSM updates available events, calculates the corresponding transition rates and simulation time, and selects one of the available events. The lattice based kMC technique has many potential applications within SRNL where chemical kinetics are of interest. By transitioning through time along a trajectory of configuration space, fundamental insights to a system's dominant reactions and parameters can be gained, leading to improved materials and process design. In this work, we have established capabilities for fast implementation of kMC simulations through the installation and testing of the KMOS software on SRNL high performance computing resources. The parameterization of kMC simulations is often performed from first-principles energetic calculations. For the purposes of this work, the test cases use arbitrary species and thus, have arbitrary parameterization. In order to demonstrate the use of KMOS, two primary test cases are shown. Case 1 involves simple adsorption and desorption. Case 2 involves a slightly more complex mechanism. The evolution of the surface concentration and the final surface configuration for simulation Case 2 is shown. Rate-limiting processes and rate-limiting configurations are not always known or understood, but kMC provides information pertaining to both. The capability to implement efficient micro-kinetic models using the kinetic Monte Carlo technique has been established through the testing and installation of KMOS on SRNL HPC resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Spacer Grid and Mixing Vanes Effects Study on Two-phase Flow Using Bubble Tracking Simulations

In Light Water Reactor (LWR) cores, the nuclear fuel rods are arranged together as rod bundles in a triangular or square pattern. The fuel rod bundles are supported by the spacer grids with mixing vanes. An understanding of spacer grid and mixing vanes effect is important since it has a direct impact on the turbulence structure in the flow and the heat removal efficiency from the fuel rod surface. Although a considerable amount of literature has been published on the experimental investigation of spacer grid and mixing vanes effect, the measurements were mainly focused on single-phase flow. The influence of spacer grid and mixing vanes on two-phase flow is yet to be fully understood. Some preliminary research efforts have been invested in nuclear community. For example, Wheeler et al. experimentally studied the effects of spacer grid in air-water two-phase flow. Although mixing vanes are not considered, they presented interesting results of time-averaged two-phase flow quantities at upstream and downstream locations of the spacer grid. Over the past decades, the rapid development of High-Performance Computing (HPC) is allowing for the increasingly larger-scale high-fidelity simulations. Thanks to this favorable historical trend, Direct Numerical Simulation (DNS), integrated with Interface Tracking Methods (ITM), has been emerging as a valuable tool to complement and expand our ability to understand the two-phase flow phenomenon. Meanwhile, in order to make best use of the large-scale two-phase flow simulations, advanced data analysis techniques are being developed, as they enable the extraction of detailed parameters about individual bubble behavior. The level set ITM is utilized in our DNS flow solver, which makes use of a signed distance field. The gas-liquid interface is modeled by the zero level set. The level set method can be readily used to distinguish different phases based on the sign of corresponding level set value (e.g. the sign is positive in the liquid phase while negative in the gas phase.). However, the traditional level set approach is not able to collect calculated values and associate with specific bubbles when multiple (even thousands of) bubbles present in the simulations of two-phase flow. This drawback hinders the collection of useful bubble information, which can give us valuable insights about bubbly flows. For example, how the different local fluid conditions could affect bubble interfacial forces, bubble deformation level, and eventually the bubble distribution throughout the whole domain. A bubble tracking methodology has been developed to address the drawbacks and improve the data collection efficiency of level set based two-phase flow simulations. In the present work, a single Pressurized Water Reactor (PWR) subchannel with reduced size spacer grid and mixing vanes is chosen as the computational domain. The springs and dimples of the spacer grid are not represented for simplicity in the present investigation. The bubble tracking methodology is applied to the simulations of two-phase bubbly flow through spacer grid and mixing vanes region. In the intended simulation, the liquid turbulence will be fully resolved by DNS while the two-phase behaviors are captured by level set ITM. Bubble tracking data are to be processed to investigate the spacer grid and mixing vanes effect on two-phase bubbly flow. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Comsol multiphysics simulation of the 1958 Y-12 criticality accident - 14654

This paper presents the simulation of the 1958 Y-12 criticality excursion using the commercial multiphysics code COMSOL Multiphysics. ICNC 2011 reported the initial effort to simulate the Y-12 accident power history using a fully coupled neutronic and computational fluid dynamic (CFD) approach with the Imperial College London FETCH code. That simulation included the initial spike and a subsequent power history 30 seconds afterwards. A time-dependent lumped parameter excursion model was later developed at Imperial in November 2014 and taken to 20 min. The COMSOL simulation is viewed as a hybrid treatment of these efforts. The use of COMSOL as a platform for criticality excursion simulation had been previously demonstrated with SILENE step reactivity insertion benchmarks. The Y-12 accident represented a unique time dependent reactivity insertion mechanism by dilution of the fissile concentration over time that facilitated the excursion termination. The COMSOL model includes a moving mesh vertical boundary, compartment radiolytic gas model, coupled turbulent fluid flow and conjugate heat transfer. The results are compared with both FETCH and lumped parameter simulations. The COMSOL power history results are in agreement with the reported and reconstructed initial spike fissions, power and total fissions over time. The simulated power trace shows explicit subsequent spikes approximately 10-20 seconds apart from the initial spike, over the first three minutes of the excursion. This result qualitatively confirms the radiation dose rate trace from a far field monitor located well beyond the affected facility. Additionally, the COMSOL model shows the onset of boiling after 3 minutes, as postulated in the literature. The combination of boiling and fissile solution dilution contributed to the shutdown mechanism. (authors)

42 ENGINEERING↗
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↗
DOE OSTI2014

Evaluation of CMIP5 continental precipitation simulations relative to satellite-based gauge-adjusted observations

Numerous studies have emphasized that climate simulations are subject to various biases and uncertainties. The objective of this study is to cross-validate 34 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of precipitation against the Global Precipitation Climatology Project (GPCP) data, quantifying model pattern discrepancies and biases for both entire data distributions and their upper tails. The results of the Volumetric Hit Index (VHI) analysis of the total monthly precipitation amounts show that most CMIP5 simulations are in good agreement with GPCP patterns in many areas, but that their replication of observed precipitation over arid regions and certain sub-continental regions (e.g., northern Eurasia, eastern Russia, central Australia) is problematical. Overall, the VHI of the multi-model ensemble mean and median also are superior to that of the individual CMIP5 models. However, at high quantiles of reference data (e.g., the 75th and 90th percentiles), all climate models display low skill in simulating precipitation, except over North America, the Amazon, and central Africa. Analyses of total bias (B) in CMIP5 simulations reveal that most models overestimate precipitation over regions of complex topography (e.g. western North and South America and southern Africa and Asia), while underestimating it over arid regions. Also, while most climate model simulations show low biases over Europe, inter-model variations in bias over Australia and Amazonia are considerable. The Quantile Bias (QB) analyses indicate that CMIP5 simulations are even more biased at high quantiles of precipitation. Lastly, we found that a simple mean-field bias removal improves the overall B and VHI values, but does not make a significant improvement in these model performance metrics at high quantiles of precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Impact of Resolution on Simulation of Closed Mesoscale Cellular Convection Identified by Dynamically Guided Watershed Segmentation

Organized mesoscale cellular convection (MCC) is a common feature of marine stratocumulus that forms in response to a balance between mesoscale dynamics and smaller scale processes such as cloud radiative cooling and microphysics. We use the Weather Research and Forecasting model with chemistry (WRF-Chem) and fully coupled cloud-aerosol interactions to simulate marine low clouds during the VOCALS-REx campaign over the southeast Pacific. A suite of experiments with 3- and 9-km grid spacing indicates resolution-dependent behavior. The simulations with finer grid spacing have smaller liquid water paths and cloud fractions, while cloud tops are higher. The observed diurnal cycle is reasonably well simulated. To isolate organized MCC characteristics we develop a new automated method, which uses a variation of the watershed segmentation technique that combines the detection of cloud boundaries with a test for coincident vertical velocity characteristics. This ensures that the detected cloud fields are dynamically consistent for closed MCC, the most common MCC type over the VOCALS-REx region. We demonstrate that the 3-km simulation is able to reproduce the scaling between horizontal cell size and boundary layer height seen in satellite observations. However, the 9-km simulation is unable to resolve smaller circulations corresponding to shallower boundary layers, instead producing invariant MCC horizontal scale for all simulated boundary layers depths. The results imply that climate models with grid spacing of roughly 3 km or smaller may be needed to properly simulate the MCC structure in the marine stratocumulus regions.

58 GEOSCIENCES↗