Development and deployment of a credible unstructured, six-DOF, implicit low-Mach overset simulation tool for wave energy applications
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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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This paper presents a theoretical study of the DNA damage due to the effect of the composite electric fields of H{sub 2}O{sup +} ions produced from the irradiation of a heavy ion onto a cell. It is found that a much larger number of electrons, which are produced from electron impact ionization, is trapped near the track of an incident ion in the case of C{sup 6+} ion irradiation with the energy of 3 MeV/u than that of proton irradiation. Therefore, the irradiation of carbon ions may produce a larger number of cluster DNA damage than that in the irradiation of protons. This may lead to the understanding of relative biological effectiveness (RBE).
Injection of high energy beams of neutral particles is a method for plasma heating in fusion devices. The ITER injector, and its prototype MITICA (Megavolt ITER Injector and Concept Advancement), are large extrapolations from existing devices: therefore numerical modeling is needed to set thermo-mechanical requirements for all beam-facing components. As the power and charge deposition originates from several sources (primary beam, co-accelerated electrons, and secondary production by beam-gas, beam-surface, and electron-surface interaction), the beam propagation along the beam line is simulated by comprehensive 3D models. This paper presents a comparative study between two codes: BTR has been used for several years in the design of the ITER HNB/DNB components; SAMANTHA code was independently developed and includes additional phenomena, such as secondary particles generated by collision of beam particles with the background gas. The code comparison is valuable in the perspective of the upcoming experimental operations, in order to prepare a reliable numerical support to the interpretation of experimental measurements in the beam test facilities. The power density map calculated on the Electrostatic Residual Ion Dump (ERID) is the chosen benchmark, as it depends on the electric and magnetic fields as well as on the evolution of the beam species via interaction with the gas. Finally the paper shows additional results provided by SAMANTHA, like the secondary electrons produced by volume processes accelerated by the ERID fringe-field towards the Cryopumps.
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The Simulation Toolkit for Renewable Energy and Advanced Materials Modeling (STREAMM) is a python package that generates structures and input files for quantum chemical and molecular dynamics codes. STREAMM does not directly conduct simulations rather it is meant to drive quantum chemical and molecular dynamics codes to allow for high-throughput computational analysis of materials. The STREAMM package is written for python2.7 (https://www.python.org/download/releases/2.7/) and incorporates some of the core modules from the pymatgen (http://pymatgen.org/) code.
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The overall objective of this multi-faceted program is to develop epitaxial growth systems that meet a goal of 75% (4X) cost reduction in the epitaxy phase of HB-LED manufacture. A 75% reduction in yielded epitaxy cost is necessary in order to achieve the cost goals for widespread penetration of HB-LED's into back-lighting units (BLU) for LCD panels and ultimately for solid-state lighting (SSL). To do this, the program will address significant improvements in overall equipment Cost of Ownership, or CoO. CoO is a model that includes all costs associated with the epitaxy portion of production. These aspects include cost of yield, capital cost, operational costs, and maintenance costs. We divide the program into three phases where later phases will incorporate the gains of prior phases. Phase one activities are enabling technologies. In collaboration with Sandia National Laboratories we develop a Fluent-compatible chemistry predictive model and a set of mid-infrared and near-ultraviolet pyrometer monitoring tools. Where previously the modeling of the reactor dynamics were studied within FLUENT alone, here, FLUENT and Chemkin are integrated into a comprehensive model of fluid dynamics and the most advanced transport equations developed for Chemkin. Specifically, the Chemkin model offered the key reaction terms for gas-phase nucleation, a key consideration in the optimization of the MOCVD process. This new predictive model is used to design new MOCVD reactors with optimized growth conditions and the newly developed pyrometers are used monitor and control the MOCVD process temperature to within 0.5°C run-to-run and within each wafer. This portion of the grant is in collaboration with partners at Sandia National Laboratories. Phase two activities are continuous improvement projects which extend the current reactor platform along the lines of improved operational efficiency, improved systems control for throughput, and carrier modifications for increased yield. Programmatically, improvements made in Phase I are applied to developments of Phase II when applicable. Phase three is the culmination of the individual tasks from both phases one and two applied to proposed production platforms. We selectively combine previously demonstrated tasks and other options to develop a high-volume production-worthy MOCVD system demonstrating >3x throughput, 1.3x capital efficiency, and 0.7x cost of ownership. In a parallel demonstration we validate the concept of an improved, larger deposition system which utilizes the predictive modeling of chemistry-based flow analysis and extensions of the improvements demonstrated on the current platforms. This validation includes the build and testing of a prototype version of the hardware and demonstration of 69% reduction in the cost of ownership. Also, in this phase we present a stand-alone project to develop a high-temperature system which improves source efficiency by 30% while concurrently increasing growth rate by 1.3x. The material quality is held to the same material quality specifications of our existing baseline processes. The merits of other line item tasks in phase three are discussed for inclusion on next-generation platforms.
Nuclear power currently provides a significant fraction of the United States’ non-carbon emitting power generation. In future years, nuclear power must continue to generate a significant portion of the nation’s electricity to meet the growing electricity demand, clean energy goals, and ensure energy independence. New reactors will be an essential part of the expansion of nuclear power. However, given limits on new builds imposed by economics and industrial capacity, the extended service of the existing fleet will also be required.
Control of beam trajectory is essential in particle accelerators. The trajectory of a beam is sensitive to various types of imperfections that cause it to deviate from its desired path along the accelerator. Orbit correction is hence fundamental for the control of beam trajectory. In this work we aim demonstrate orbit correction using singular value decomposition techniques applied to distorted orbits generated in the CBETA-V Virtual Machine. In particular we present two concrete examples of such correction in different sections of the CBETA Fractional Arc Test layout. Our goal is to construct the backbone of an orbit correction software toolkit to be tested in the CBETA-V Virtual Machine and eventually implemented in the completed CBETA control system.
MLIR (Multi-Level Intermediate Representation), is an extensible compiler framework that supports high-level data structures and operation constructs. These higher-level code representations are particularly applicable to the artificial intelligence and machine learning (AI/ML) domain, allowing developers to more easily support upcoming heterogeneous AI/ML accelerators and develop flexible domain specific compilers/frameworks with higher-level intermediate representations (IRs) and advanced compiler optimizations. The result of using MLIR within the LLVM compiler framework is expected to yield significant improvement in the quality of generated machine code, which in turn will result in improved performance and hardware efficiency
The venture project Tool to Improve Urban Search Planning (LL14-V-Urban Search Planning ToolPD3RS) supported two major types of effort: 1) development of a software prototype search planning tool, with the goal of transitioning the tool to operational users for evaluation and possible adoption; 2) enabling research to better understand the radiation characteristics of an urban environment, with implications for deployment of radiation detection systems in that environment. The first effort has resulted in prototype software, Optimization Planning Tool for Urban Search (OPTUS), that has been distributed to a limited set of potential users, including users within the NNSA emergency response community. The second effort supported various research topics including high fidelity radiation transport modeling in urban environments, measurement campaigns for model validation, development of vehicle-based high purity germanium (HPGe) detector systems and supporting data analysis, and computational capabilities for archiving and managing large data sets. While some of these related efforts have informed the models and software design of the OPTUS tool, in large part they pursued more basic research, some of which has evolved into separate DNN R&D projects. Project performers included Oak Ridge National Laboratory (ORNL), Lawrence Berkeley National Laboratory (LBNL) and the Remote Sensing Laboratory (RSL), in addition to Lawrence Livermore Laboratory (LLNL), the project lead. The project also supported university research, including several internships at the laboratories.
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This project focuses on developing a thermo-metallurgical-mechanical modeling method to accurately predict the microstructural evolution and residual stress in laser welding between dissimilar metals, such as HSLA steel and high carbon equivalent (CE) gear steel. The method leverages a comprehensive material database to model the temperature and rate dependent phase transformations, along with their associated effects on material properties, such as thermal expansion and flow stress, throughout the welding process. A key innovation is the incorporation of phase transformation and phase-specific properties, which enhances the accuracy of residual stress predictions. The mixture material in the fusion zone due to the dissimilar metals will also be addressed in the numerical model. This is especially critical in scenarios involving phase transformations in the fusion zone and heat-affected zone (HAZ), where the phase changes can induce substantial residual stress variations. The material database has been generated using JMatPro. The modeling approach is implemented through a custom User Material (UMAT) subroutine, executed with the commercial finite element software Abaqus.
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This project focuses on developing a thermo-metallurgical-mechanical modeling method to accurately predict the microstructural evolution and residual stress in laser welding between dissimilar metals, such as HSLA steel and high carbon equivalent (CE) gear steel. The method leverages a comprehensive material database to model the temperature and rate dependent phase transformations, along with their associated effects on material properties, such as thermal expansion and flow stress, throughout the welding process. A key innovation is the incorporation of phase transformation and phase-specific properties, which enhances the accuracy of residual stress predictions. The mixture material in the fusion zone due to the dissimilar metals will also be addressed in the numerical model. This is especially critical in scenarios involving phase transformations in the fusion zone and heat-affected zone (HAZ), where the phase changes can induce substantial residual stress variations. The material database has been generated using JMatPro. The modeling approach is implemented through a custom User Material (UMAT) subroutine, executed with the commercial finite element software Abaqus.