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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Monte Carlo modeling and simulations of the High Definition (HD120) micro MLC and validation against measurements for a 6 MV beam

Purpose: The most recent Varian micro multileaf collimator (MLC), the High Definition (HD120) MLC, was modeled using the BEAMNRC Monte Carlo code. This model was incorporated into a Varian medical linear accelerator, for a 6 MV beam, in static and dynamic mode. The model was validated by comparing simulated profiles with measurements. Methods: The Varian Trilogy (2300C/D) accelerator model was accurately implemented using the state-of-the-art Monte Carlo simulation program BEAMNRC and validated against off-axis and depth dose profiles measured using ionization chambers, by adjusting the energy and the full width at half maximum (FWHM) of the initial electron beam. The HD120 MLC was modeled by developing a new BEAMNRC component module (CM), designated HDMLC, adapting the available DYNVMLC CM and incorporating the specific characteristics of this new micro MLC. The leaf dimensions were provided by the manufacturer. The geometry was visualized by tracing particles through the CM and recording their position when a leaf boundary is crossed. The leaf material density and abutting air gap between leaves were adjusted in order to obtain a good agreement between the simulated leakage profiles and EBT2 film measurements performed in a solid water phantom. To validate the HDMLC implementation, additional MLC static patterns were also simulated and compared to additional measurements. Furthermore, the ability to simulate dynamic MLC fields was implemented in the HDMLC CM. The simulation results of these fields were compared with EBT2 film measurements performed in a solid water phantom. Results: Overall, the discrepancies, with and without MLC, between the opened field simulations and the measurements using ionization chambers in a water phantom, for the off-axis profiles are below 2% and in depth-dose profiles are below 2% after the maximum dose depth and below 4% in the build-up region. On the conditions of these simulations, this tungsten-based MLC has a density of 18.7 g cm{sup -3} and an overall leakage of about 1.1 {+-} 0.03%. The discrepancies between the film measured and simulated closed and blocked fields are below 2% and 8%, respectively. Other measurements were performed for alternated leaf patterns and the agreement is satisfactory (to within 4%). The dynamic mode for this MLC was implemented and the discrepancies between film measurements and simulations are within 4%. Conclusions: The Varian Trilogy (2300 C/D) linear accelerator including the HD120 MLC was successfully modeled and simulated using the Monte Carlo BEAMNRC code by developing an independent CM, the HDMLC CM, either in static and dynamic modes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

SU-E-T-314: The Application of Cloud Computing in Pencil Beam Scanning Proton Therapy Monte Carlo Simulation

Purpose: Monte Carlo simulation plays an important role for proton Pencil Beam Scanning (PBS) technique. However, MC simulation demands high computing power and is limited to few large proton centers that can afford a computer cluster. We study the feasibility of utilizing cloud computing in the MC simulation of PBS beams. Methods: A GATE/GEANT4 based MC simulation software was installed on a commercial cloud computing virtual machine (Linux 64-bits, Amazon EC2). Single spot Integral Depth Dose (IDD) curves and in-air transverse profiles were used to tune the source parameters to simulate an IBA machine. With the use of StarCluster software developed at MIT, a Linux cluster with 2–100 nodes can be conveniently launched in the cloud. A proton PBS plan was then exported to the cloud where the MC simulation was run. Results: The simulated PBS plan has a field size of 10×10cm{sup 2}, 20cm range, 10cm modulation, and contains over 10,000 beam spots. EC2 instance type m1.medium was selected considering the CPU/memory requirement and 40 instances were used to form a Linux cluster. To minimize cost, master node was created with on-demand instance and worker nodes were created with spot-instance. The hourly cost for the 40-node cluster was $0.63 and the projected cost for a 100-node cluster was $1.41. Ten million events were simulated to plot PDD and profile, with each job containing 500k events. The simulation completed within 1 hour and an overall statistical uncertainty of < 2% was achieved. Good agreement between MC simulation and measurement was observed. Conclusion: Cloud computing is a cost-effective and easy to maintain platform to run proton PBS MC simulation. When proton MC packages such as GATE and TOPAS are combined with cloud computing, it will greatly facilitate the pursuing of PBS MC studies, especially for newly established proton centers or individual researchers.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

SU-F-I-79: Validation of a Monte Carlo Radiographic Simulation

Purpose: To validate a radiographic simulation in order to estimate patient dose due to clinically-used radiography protocols. Methods: A Monte Carlo simulation was created to simulate a radiographic x-ray beam using GEANT4. Initial validation was performed according to a portion of TG 195. Computational NURBS-based phantoms were used simulate patients of varying ages and sizes. The deposited energy in the phantom is output by the simulation. The exposure in air from a clinically used radiography unit was measured at 100 cm for various tube potentials. 10 million photons were simulated with 1 cubic centimeter of air located 100 cm from the source, and the total absorbed dose was noted. The normalization factor was determined by taking a ratio of the measured dose in air to the simulated dose in air. Dose to individual voxels is calculated using the energy deposition map along with the voxelized and segmented phantom and the normalization factor. Finally, the effective dose is calculated using the ICRP methodology and tissue weighting factors. Results: This radiography simulation allows for the calculation and visualization of the energy deposition map within a voxelized phantom. The ratio of exposure, measured using an ionization chamber, to air in the simulation was determined. Since the simulation output is calibrated to match the exposure of a given clinical radiographic x-ray tube, the dose map may be visualized. This will also allow for absorbed dose estimation in specific organs or tissues as well as a whole body effective dose estimation. Conclusion: This work indicates that our Monte Carlo simulation may be used to estimate the radiation dose from clinical radiographic protocols. This will allow for an estimate of radiographic dose from various examinations without the use of traditional methods such as thermoluminescent dosimeters and body phantoms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-H-BRA-04: Biological Geometries for the Monte Carlo Simulation Toolkit TOPASNBio

Purpose: New advances in radiation therapy are most likely to come from the complex interface of physics, chemistry and biology. Computational simulations offer a powerful tool for quantitatively investigating radiation interactions with biological tissue and can thus help bridge the gap between physics and biology. The aim of TOPAS-nBio is to provide a comprehensive tool to generate advanced radiobiology simulations. Methods: TOPAS wraps and extends the Geant4 Monte Carlo (MC) simulation toolkit. TOPAS-nBio is an extension to TOPAS which utilizes the physics processes in Geant4-DNA to model biological damage from very low energy secondary electrons. Specialized cell, organelle and molecular geometries were designed for the toolkit. Results: TOPAS-nBio gives the user the capability of simulating biological geometries, ranging from the micron-scale (e.g. cells and organelles) to complex nano-scale geometries (e.g. DNA and proteins). The user interacts with TOPAS-nBio through easy-to-use input parameter files. For example, in a simple cell simulation the user can specify the cell type and size as well as the type, number and size of included organelles. For more detailed nuclear simulations, the user can specify chromosome territories containing chromatin fiber loops, the later comprised of nucleosomes on a double helix. The chromatin fibers can be arranged in simple rigid geometries or within factual globules, mimicking realistic chromosome territories. TOPAS-nBio also provides users with the capability of reading protein data bank 3D structural files to simulate radiation damage to proteins or nucleic acids e.g. histones or RNA. TOPAS-nBio has been validated by comparing results to other track structure simulation software and published experimental measurements. Conclusion: TOPAS-nBio provides users with a comprehensive MC simulation tool for radiobiological simulations, giving users without advanced programming skills the ability to design and run complex simulations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-CD-207A-08: Simulated Real-Time Image Guidance for Lung SBRT Patients Using Scatter Imaging

Purpose: To develop a comprehensive Monte Carlo-based model for the acquisition of scatter images of patient anatomy in real-time, during lung SBRT treatment. Methods: During SBRT treatment, images of patient anatomy can be acquired from scattered radiation. To rigorously examine the utility of scatter images for image guidance, a model is developed using MCNP code to simulate scatter images of phantoms and lung cancer patients. The model is validated by comparing experimental and simulated images of phantoms of different complexity. The differentiation between tissue types is investigated by imaging objects of known compositions (water, lung, and bone equivalent). A lung tumor phantom, simulating materials and geometry encountered during lung SBRT treatments, is used to investigate image noise properties for various quantities of delivered radiation (monitor units(MU)). Patient scatter images are simulated using the validated simulation model. 4DCT patient data is converted to an MCNP input geometry accounting for different tissue composition and densities. Lung tumor phantom images acquired with decreasing imaging time (decreasing MU) are used to model the expected noise amplitude in patient scatter images, producing realistic simulated patient scatter images with varying temporal resolution. Results: Image intensity in simulated and experimental scatter images of tissue equivalent objects (water, lung, bone) match within the uncertainty (∼3%). Lung tumor phantom images agree as well. Specifically, tumor-to-lung contrast matches within the uncertainty. The addition of random noise approximating quantum noise in experimental images to simulated patient images shows that scatter images of lung tumors can provide images in as fast as 0.5 seconds with CNR∼2.7. Conclusions: A scatter imaging simulation model is developed and validated using experimental phantom scatter images. Following validation, lung cancer patient scatter images are simulated. These simulated patient images demonstrate the clinical utility of scatter imaging for real-time tumor tracking during lung SBRT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Evaluation of Turbulence and Dispersion in Multiscale Atmospheric Simulations over Complex Urban Terrain during the Joint Urban 2003 Field Campaign

Abstract This paper evaluates the representation of turbulence and its effect on transport and dispersion within multiscale and microscale-only simulations in an urban environment. These simulations, run using the Weather Research and Forecasting Model with the addition of an immersed boundary method, predict transport and mixing during a controlled tracer release from the Joint Urban 2003 field campaign in Oklahoma City, Oklahoma. This work extends the results of a recent study through analysis of turbulence kinetic energy and turbulence spectra and their role in accurately simulating wind speed, direction, and tracer concentration. The significance and role of surface heat fluxes and use of the cell perturbation method in the numerical simulation setup are also examined. Our previous study detailed the model development necessary for our multiscale simulations, examined model skill at predicting wind speeds and tracer concentrations, and demonstrated that dynamic downscaling from mesoscale to microscale through a sequence of nested simulations can improve predictions of transport and dispersion relative to a microscale-only simulation forced by idealized meteorology. Here, predictions are compared with observations to assess qualitative agreement and statistical model skill at predicting wind speed, wind direction, tracer concentration, and turbulent kinetic energy at locations throughout the city. We also investigate the scale distribution of turbulence and the associated impact on model skill, particularly for predictions of transport and dispersion. Our results show that downscaled large-scale turbulence, which is unique to the multiscale simulations, significantly improves predictions of tracer concentrations in this complex urban environment. Significance Statement Simulations of atmospheric transport and mixing in urban environments have many applications, including pollution modeling for urban planning or informing emergency response following a hazardous release. These applications include phenomena with spatial scales spanning from millimeters to kilometers. Most simulations resolve flow only within the urban area of interest, omitting larger scales of turbulence and regional influences. This study examines a method that resolves both the small and large-scale flow features. We evaluate simulation accuracy by comparing predictions with observations from an experiment involving the release of a tracer gas in Oklahoma City, Oklahoma, with emphasis on correctly modeling turbulent fluctuations. Our results demonstrate the importance of resolving large-scale flow features when predicting transport and dispersion in urban environments.

42 ENGINEERING↗
DOE OSTI2011

Comparing the Calibration and Simulation Data of the Cryogenic Dark Matter Search

The Cryogenic Dark Matter Search, or CDMS, collaboration is preparing a new experiment called SuperCDMS. CDMS uses Germanium detectors to attempt the direct detection of dark matter. To do this, they measure the ionization and heat produced during an event where a WIMP scatters off of germanium crystal lattice. To prepare for the experiment the detectors are calibrated with various radioactive sources. The response of the detectors is also modeled by a Monte Carlo simulation. These simulations include modeling everything from the radiation production to the raw data collected by the detector. The experimental data will be used to validate the results of the detector simulation. This research will look only at the phonons produced during events that occur very close to the detector surface. From the raw data and simulation output three parameters will be determined: the rise time, the decay time, and time to position independence. It was found that the simulation's risetime and time to position independence was generally smaller than that of the data, while the decay time was found to be larger in the simulation than in the data. These differences show that the simulation is not complete. The difference in risetime implies that the phonons are not spread out enough when they reach the detector walls, which would be improved by a look at the Luke phonon and charge transport. The long decay time in the simulation implies that the rate phonons are being absorbed is underestimated. Finally, the small time to position independence in the simulation could be due to a low phonon scattering rate. A simple solution may be to alter the parameters that control the simulation, while still remaining physically sensible, to help match simulation and data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

Development of K-Basin High-Strength Homogeneous Sludge Simulants and Correlations Between Unconfined Compressive Strength and Shear Strength

K-Basin sludge will be stored in the Sludge Transport and Storage Containers (STSCs) at an interim storage location on Central Plateau before being treated and packaged for disposal. During the storage period, sludge in the STSCs may consolidate/agglomerate, potentially resulting in high-shear-strength material. The Sludge Treatment Project (STP) plans to use water jets to retrieve K-Basin sludge after the interim storage. STP has identified shear strength to be a key parameter that should be bounded to verify the operability and performance of sludge retrieval systems. Determining the range of sludge shear strength is important to gain high confidence that a water-jet retrieval system can mobilize stored K-Basin sludge from the STSCs. The shear strength measurements will provide a basis for bounding sludge properties for mobilization and erosion. Thus, it is also important to develop potential simulants to investigate these phenomena. Long-term sludge storage tests conducted by Pacific Northwest National Laboratory (PNNL) show that high-uranium-content K-Basin sludge can self-cement and form a strong sludge with a bulk shear strength of up to 65 kPa. Some of this sludge has 'paste' and 'chunks' with shear strengths of approximately 3-5 kPa and 380-770 kPa, respectively. High-uranium-content sludge samples subjected to hydrothermal testing (e.g., 185 C, 10 hours) have been observed to form agglomerates with a shear strength up to 170 kPa. These high values were estimated by measured unconfined compressive strength (UCS) obtained with a pocket penetrometer. Due to its ease of use, it is anticipated that a pocket penetrometer will be used to acquire additional shear strength data from archived K-Basin sludge samples stored at the PNNL Radiochemical Processing Laboratory (RPL) hot cells. It is uncertain whether the pocket penetrometer provides accurate shear strength measurements of the material. To assess the bounding material strength and potential for erosion, it is important to compare the measured shear strength to penetrometer measurements and to develop a correlation (or correlations) between UCS measured by a pocket penetrometer and direct shear strength measurements for various homogeneous and heterogeneous simulants. This study developed 11 homogeneous simulants, whose shear strengths vary from 4 to 170 kPa. With these simulants, we developed correlations between UCS measured by a Geotest E-280 pocket penetrometer and shear strength values measured by a Geonor H-60 hand-held vane tester and a more sophisticated bench-top unit, the Haake M5 rheometer. This was achieved with side-by-side measurements of the shear strength and UCS of the homogeneous simulants. The homogeneous simulants developed under this study consist of kaolin clay, plaster of Paris, and amorphous alumina CP-5 with water. The simulants also include modeling clay. The shear strength of most of these simulants is sensitive to various factors, including the simulant size, the intensity of mixing, and the curing time, even with given concentrations of simulant components. Table S.1 summarizes these 11 simulants and their shear strengths.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Strategy and gaps for modeling, simulation, and control of hybrid systems

The purpose of this report is to establish a strategy for modeling and simulation of candidate hybrid energy systems. Modeling and simulation is necessary to design, evaluate, and optimize the system technical and economic performance. Accordingly, this report first establishes the simulation requirements to analysis candidate hybrid systems. Simulation fidelity levels are established based on the temporal scale, real and synthetic data availability or needs, solution accuracy, and output parameters needed to evaluate case-specific figures of merit. Accordingly, the associated computational and co-simulation resources needed are established; including physical models when needed, code assembly and integrated solutions platforms, mathematical solvers, and data processing. This report first attempts to describe the figures of merit, systems requirements, and constraints that are necessary and sufficient to characterize the grid and hybrid systems behavior and market interactions. Loss of Load Probability (LOLP) and effective cost of Effective Cost of Energy (ECE), as opposed to the standard Levelized Cost of Electricty (LCOE), are introduced as technical and economical indices for integrated energy system evaluations. Financial assessment methods are subsequently introduced for evaluation of non-traditional, hybrid energy systems. Algorithms for coupled and iterative evaluation of the technical and economic performance are subsequently discussed. This report further defines modeling objectives, computational tools, solution approaches, and real-time data collection and processing (in some cases using real test units) that will be required to model, co-simulate, and optimize; (a) an energy system components (e.g., power generation unit, chemical process, electricity management unit), (b) system domains (e.g., thermal, electrical or chemical energy generation, conversion, and transport), and (c) systems control modules. Co-simulation of complex, tightly coupled, dynamic energy systems requires multiple simulation tools, potentially developed in several programming languages and resolved on separate time scales. Whereas further investigation and development of hybrid concepts will provide a more complete understanding of the joint computational and physical modeling needs, this report highlights areas in which co-simulation capabilities are warranted. The current development status, quality assurance, availability and maintainability of simulation tools that are currently available for hybrid systems modeling is presented. Existing gaps in the modeling and simulation toolsets and development needs are subsequently discussed. This effort will feed into a broader Roadmap activity for designing, developing, and demonstrating hybrid energy systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2011

High resolution simulations of ignition capsule designs for the National Ignition Facility

Ignition capsule designs for the National Ignition Facility (NIF) [G. H. Miller, E. I. Moses, and C. R. Wuest, Opt. Eng. 443, 2841 (2004)] have continued to evolve in light of improved physical data inputs, improving simulation techniques, and - most recently - experimental data from a growing number of NIF sub-ignition experiments. This paper summarizes a number of recent changes to the cryogenic capsule design and some of our latest techniques in simulating its performance. Specifically, recent experimental results indicated harder x-ray drive spectra in NIF hohlraums than were predicted and used in previous capsule optimization studies. To accommodate this harder drive spectrum, a series of high-resolution 2-D simulations, resolving Legendre mode numbers as high as two thousand, were run and the germanium dopant concentration and ablator shell thicknesses re-optimized accordingly. Simultaneously, the possibility of cooperative or nonlinear interaction between neighboring ablator surface defects has motivated a series of fully 3-D simulations run with the massively parallel HYDRA code. These last simulations include perturbations seeded on all capsule interfaces and can use actual measured shell surfaces as initial conditions. 3-D simulations resolving Legendre modes up to two hundred on large capsule sectors have run through ignition and burn, and higher resolution simulations resolving as high as mode twelve hundred have been run to benchmark high-resolution 2-D runs. Finally, highly resolved 3-D simulations have also been run of the jet-type perturbation caused by the fill tube fitted to the capsule. These 3-D simulations compare well with the more typical 2-D simulations used in assessing the fill tube's impact on ignition. Coupled with the latest experimental inputs from NIF, our improving simulation capability yields a fuller and more accurate picture of NIF ignition capsule performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2010

Simulation of dynamic fracture using peridynamics, finite element modeling, and contact.

Peridynamics is a nonlocal extension of classical solid mechanics that allows for the modeling of bodies in which discontinuities occur spontaneously. Because the peridynamic expression for the balance of linear momentum does not contain spatial derivatives and is instead based on an integral equation, it is well suited for modeling phenomena involving spatial discontinuities such as crack formation and fracture. In this study, both peridynamics and classical finite element analysis are applied to simulate material response under dynamic blast loading conditions. A combined approach is utilized in which the portion of the simulation modeled with peridynamics interacts with the finite element portion of the model via a contact algorithm. The peridynamic portion of the analysis utilizes an elastic-plastic constitutive model with linear hardening. The peridynamic interface to the constitutive model is based on the calculation of an approximate deformation gradient, requiring the suppression of possible zero-energy modes. The classical finite element portion of the model utilizes a Johnson-Cook constitutive model. Simulation results are validated by direct comparison to expanding tube experiments. The coupled modeling approach successfully captures material response at the surface of the tube and the emerging fracture pattern. The coupling of peridynamics and finite element analysis via a contact algorithm has been shown to be a viable means for simulating material fracture in a high-velocity impact experiment. A combined peridynamics/finite element approach was applied to model an expanding tube experiment performed by Vogler, et al., in which loading on the tube is a result of Lexan slugs impacting inside the tube. The Lexan portion of the simulation was modeled with finite elements and a Johnson-Cook elastic-plastic material model in conjunction with an equation-of-state law. The steel tube portion of the simulation was modeled with peridynamics, an elastic-plastic material model, and a critical stretch bond damage model. The application of peridynamics to the tube portion of the model allowed the capture of the formation of cracks and eventual fragmentation of the tube. The simulation results yielded good agreement with the experimental results published by Vogler, et al., for the velocity and displacement profiles on the surface of the tube and the resulting fragment distribution. Numerical difficulties were encountered that required removal of hexahedron elements from the Lexan portion of the model over the course of the simulation. The significant number of inverted and nearly-inverted elements appearing over the course of the simulation is believed to be a result of irregularities in the contact between the Lexan and AerMet portions of the model, and was likely exacerbated by the ultra-high strength of the AerMet tube. Future simulations are planned in which the Lexan portion of the simulation is modeled with peridynamics, or with an alternative method such as smoothed particle hydrodynamics, with the goal of reducing these numerical difficulties.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Estimating Building Simulation Parameters via Bayesian Structure Learning

Many key building design policies are made using sophisticated computer simulations such as EnergyPlus (E+), the DOE flagship whole-building energy simulation engine. E+ and other sophisticated computer simulations have several major problems. The two main issues are 1) gaps between the simulation model and the actual structure, and 2) limitations of the modeling engine's capabilities. Currently, these problems are addressed by having an engineer manually calibrate simulation parameters to real world data or using algorithmic optimization methods to adjust the building parameters. However, some simulations engines, like E+, are computationally expensive, which makes repeatedly evaluating the simulation engine costly. This work explores addressing this issue by automatically discovering the simulation's internal input and output dependencies from 20 Gigabytes of E+ simulation data, future extensions will use 200 Terabytes of E+ simulation data. The model is validated by inferring building parameters for E+ simulations with ground truth building parameters. Our results indicate that the model accurately represents parameter means with some deviation from the means, but does not support inferring parameter values that exist on the distribution's tail.

Energy Modeling↗
DOE OSTI2016

Multiple RANS Scheme for the CFD Simulation of PWR

Though best-estimate system codes have been well established, the assumptions for the simplification of the conservation equations will be invalid when 3D effects play an important role in the object. The inner domain of PWR can create high 3D effects because of the disturbance of mixing vanes and the complex distribution of flow resistance. With the finest mesh to study the flow and heat transfer process of a nuclear reactor, a CFD simulation can give a perfect understanding of the physical processes in a whole reactor. However, more than 10 thousands of subchannels exist in a typical pressurized water reactor (PWR). These subchannels are narrow, comprising complex spacer grids and mixing vanes. The need of both the computational resources and the simulation time is great, which is not good for the simulation efficiency. However, the efficiency is critical for the CFD simulation of a PWR. It is meaningless if the simulation does not end. To improve the efficiency, one approach is to well consider the turbulence model used in a CFD simulation, because some models are complex and require great computing resources and time. On the contrary, some models are simple, but are also suitable to reflect the physical status in a PWR. Furthermore, the effects of the typical structures of PWR should also be clarified. They are closely related to the flow mechanism. The CFD simulation may be simplified by such effects. The objective of this research is to study the flow characteristics affected by the turbulence models and typical structures. The authors then design a scheme based on the regularities of the flow characteristics to improve the efficiency of the CFD simulation for PWR. By this research, we found: 1) The mixing vanes, a typical structure of a PWR, make the anisotropic eddy viscosity cannot be ignored for the region with short distance downstream of this structure; 2) Outside of this region, the RANS models, regardless of whether they are isotropic or anisotropic, can obtain similar results. To improve the simulation efficiency, a CFD scheme is designed by the hybrid application of multiple RANS models (MRANS). In this scheme, the major domain with low anisotropic viscosity uses the turbulence model which requires the least time. The difference is just little in the comparison with a simulation using the anisotropic RANS model for the whole computational domain. The MRANS scheme thus will be significant to improve the efficiency of the CFD simulation for a whole PWR.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Constant-depth circuits for dynamic simulations of materials on quantum computers

Abstract Dynamic simulation of materials is a promising application for near-term quantum computers. Current algorithms for Hamiltonian simulation, however, produce circuits that grow in depth with increasing simulation time, limiting feasible simulations to short-time dynamics. Here, we present a method for generating circuits that are constant in depth with increasing simulation time for a specific subset of one-dimensional (1D) materials Hamiltonians, thereby enabling simulations out to arbitrarily long times. Furthermore, by removing the effective limit on the number of feasibly simulatable time-steps, the constant-depth circuits enable Trotter error to be made negligibly small by allowing simulations to be broken into arbitrarily many time-steps. For an N -spin system, the constant-depth circuit contains only $\mathcal {O}(N^{2})$ O ( N 2 ) CNOT gates. Such compact circuits enable us to successfully execute long-time dynamic simulation of ubiquitous models, such as the transverse field Ising and XY models, on current quantum hardware for systems of up to 5 qubits without the need for complex error mitigation techniques. Aside from enabling long-time dynamic simulations with minimal Trotter error for a specific subset of 1D Hamiltonians, our constant-depth circuits can advance materials simulations on quantum computers more broadly in a number of indirect ways.

Materials simulation↗
DOE OSTI2011

Computational Particle Dynamic Simulations on Multicore Processors (CPDMu) Final Report Phase I

Statement of Problem - Department of Energy has many legacy codes for simulation of computational particle dynamics and computational fluid dynamics applications that are designed to run on sequential processors and are not easily parallelized. Emerging high-performance computing architectures employ massively parallel multicore architectures (e.g., graphics processing units) to increase throughput. Parallelization of legacy simulation codes is a high priority, to achieve compatibility, efficiency, accuracy, and extensibility. General Statement of Solution - A legacy simulation application designed for implementation on mainly-sequential processors has been represented as a graph G. Mathematical transformations, applied to G, produce a graph representation {und G} for a high-performance architecture. Key computational and data movement kernels of the application were analyzed/optimized for parallel execution using the mapping G {yields} {und G}, which can be performed semi-automatically. This approach is widely applicable to many types of high-performance computing systems, such as graphics processing units or clusters comprised of nodes that contain one or more such units. Phase I Accomplishments - Phase I research decomposed/profiled computational particle dynamics simulation code for rocket fuel combustion into low and high computational cost regions (respectively, mainly sequential and mainly parallel kernels), with analysis of space and time complexity. Using the research team's expertise in algorithm-to-architecture mappings, the high-cost kernels were transformed, parallelized, and implemented on Nvidia Fermi GPUs. Measured speedups (GPU with respect to single-core CPU) were approximately 20-32X for realistic model parameters, without final optimization. Error analysis showed no loss of computational accuracy. Commercial Applications and Other Benefits - The proposed research will constitute a breakthrough in solution of problems related to efficient parallel computation of particle and fluid dynamics simulations. These problems occur throughout DOE, military and commercial sectors: the potential payoff is high. We plan to license or sell the solution to contractors for military and domestic applications such as disaster simulation (aerodynamic and hydrodynamic), Government agencies (hydrological and environmental simulations), and medical applications (e.g., in tomographic image reconstruction). Keywords - High-performance Computing, Graphic Processing Unit, Fluid/Particle Simulation. Summary for Members of Congress - Department of Energy has many simulation codes that must compute faster, to be effective. The Phase I research parallelized particle/fluid simulations for rocket combustion, for high-performance computing systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Final Report for Project "Framework Application for Core-Edge Transport Simulations (FACETS)"

This is the final report for the Colorado State University Component of the FACETS Project. FACETS was focused on the development of a multiphysics, parallel framework application that could provide the capability to enable whole-device fusion reactor modeling and, in the process, the development of the modeling infrastructure and computational understanding needed for ITER. It was intended that FACETS be highly flexible, through the use of modern computational methods, including component technology and object oriented design, to facilitate switching from one model to another for a given aspect of the physics, and making it possible to use simplified models for rapid turnaround or high-fidelity models that will take advantage of the largest supercomputer hardware. FACETS was designed in a heterogeneous parallel context, where different parts of the application can take advantage through parallelism based on task farming, domain decomposition, and/or pipelining as needed and applicable. As with all fusion simulations, an integral part of the FACETS project was treatment of the coupling of different physical processes at different scales interacting closely. A primary example for the FACETS project is the coupling of existing core and edge simulations, with the transport and wall interactions described by reduced models. However, core and edge simulations themselves involve significant coupling of different processes with large scale differences. Numerical treatment of coupling is impacted by a number of factors including, scale differences, form of information transferred between processes, implementation of solvers for different codes, and high performance computing concerns. Operator decomposition involving the computation of the individual processes individually using appropriate simulation codes and then linking/synchronizing the component simulations at regular points in space and time, is the defacto approach to high performance simulation of multiphysics, multiscale systems. Various forms of operator decomposition are used in nearly all fusion simulations. However, operator decomposition generally has a complex effect on accuracy and stability of numerical simulations. Yet, these effects can be difficult to detect. The Colorado State University component of the FACETS team led by P.I.D. Estep was focused on analyzing the effects of operator decomposition on fusion simulations. The approach was based on a posteriori error analysis employing adjoint problems, computable residuals, and variational analysis to produce accurate computational error estimates for quantities of interest. Computable residuals are used to quantify the effects of various discretization choices. The generalized Greens function satisfying the adjoint problem quantities the effects of stability. Technical issues to be addressed included: (1) defining appropriate adjoint operators for operator decomposition discretizations; (2) determining the appropriate residuals for the multifaceted aspects involved with multiphysics discretizations; (3) producing the estimates within the computational framework of existing fusion codes; (4) carrying out the analysis for discretizations used in fusion simulations; and (5) devising efficient approaches to mitigating the effects of discretization. This report provides a summary of the accomplished research and a detailed description of personnel, activities, outcomes and achievements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Iterative sampling of expensive simulations for faster deep surrogate training

Deep neural network (DNN) surrogates of expensive physics simulations are enabling a rapid change in the way that common experimental design and analysis tasks are approached. Surrogate models allow simulations to be performed in parallel and separately from downstream tasks, thereby enabling analyses that would be impossible with the simulation in-the-loop; surrogates based on DNNs can effectively emulate diverse non-scalar data of the types collected in fusion and laboratory-astrophysics experiments. The challenge is in training the surrogate model, for which large ensembles of physics simulations must be run, preferably without wasting computational effort on uninteresting simulations. Here, in this paper, we present an iterative sampling scheme that can preferentially propose simulations in interesting regions of parameter space without neglecting unexplored regions, allowing high-quality and wide-ranging surrogate models to be trained using 2–3 times fewer simulations compare to space-filling designs. Our approach uses an explicit importance function defined on the simulation output space, balanced against a measure of simulation density which serves as a proxy for surrogate accuracy. It is easy to implement and can be tuned to find interesting simulations early in the study, allowing surrogates to be trained quickly and refined as new simulations become available; this represents an important step towards the routine generation of deep surrogate models quickly enough to be truly relevant to experimental work.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Uncertainty and feasibility of dynamical downscaling for modeling tropical cyclones for storm surge simulation

This paper presents a modeling study conducted to evaluate the uncertainty of a regional model in simulating hurricane wind and pressure fields, and the feasibility of driving coastal storm surge simulation using an ensemble of region model outputs produced by 18 combinations of three convection schemes and six microphysics parameterizations, using Hurricane Katrina as a test case. Simulated wind and pressure fields were compared to observed H*Wind data for Hurricane Katrina and simulated storm surge was compared to observed high-water marks on the northern coast of the Gulf of Mexico. The ensemble modeling analysis demonstrated that the regional model was able to reproduce the characteristics of Hurricane Katrina with reasonable accuracy and can be used to drive the coastal ocean model for simulating coastal storm surge. Results indicated that the regional model is sensitive to both convection and microphysics parameterizations that simulate moist processes closely linked to the tropical cyclone dynamics that influence hurricane development and intensification. The Zhang and McFarlane (ZM) convection scheme and the Lim and Hong (WDM6) microphysics parameterization are the most skillful in simulating Hurricane Katrina maximum wind speed and central pressure, among the three convection and the six microphysics parameterizations. Error statistics of simulated maximum water levels were calculated for a baseline simulation with H*Wind forcing and the 18 ensemble simulations driven by the regional model outputs. The storm surge model produced the overall best results in simulating the maximum water levels using wind and pressure fields generated with the ZM convection scheme and the WDM6 microphysics parameterization.

Yang, Zhaoqing↗