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At least 865 records · Page 48

Using multimodal X-ray computed tomography to advance 3D petrography: A non-destructive investigation of olivine inside a carbonaceous chondrite

Rocks form in three dimensions through time and studying them provides information from inside dynamic systems we cannot otherwise observe. Yet how we typically access the interior of the rocks themselves to gain that information may limit our understanding and influence how we reconstruct the processes that formed them. Here, we demonstrate combined non-destructive 3D X-ray imaging techniques that produce quantitative densitometric and crystallographic maps of entire individual grains inside a rock. Olivine grains throughout a sample of the carbonaceous chondrite Northwest Africa (NWA) 11346 were each characterized by size, shape, composition, zoning intensity, and crystallographic orientation. The addition of 3D crystallographic mapping to calibrated 3D densitometric analysis—used to calculate chemical composition—demonstrates a fully non-destructive petrographic method and provides unique insight. For instance, in our case, using crystallographic data to delineate individual grains and then measuring the 3D size, shape, and composition of each distinguishes variably reset relict grains from those later crystallized after a melting event. Intersection in a 2D slice could not have led to this interpretation because the integration of three-dimensional size, rounding, composition, location, and crystallographic orientation measured from each grain forms the key patterns. Multimodal laboratory X-ray imaging has strong potential to advance 3D petrography.

36 MATERIALS SCIENCE↗

Advanced Simulation and Computing Co-Design Strategy

This ASC Co-design Strategy lays out the full continuum and components of the co-design process, based on what we have experienced thus far and what we wish to do more in the future to meet the program’s mission of providing high performance computing (HPC) and simulation capabilities for NNSA to carry out its stockpile stewardship responsibility.

97 MATHEMATICS AND COMPUTING↗

Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing

The characterization, modeling, analysis, and tuning of software performance has been a central topic in High Performance Computing (HPC) since its early beginnings. The overall goal is to make HPC software run faster on particular hardware, either through better scheduling, on-node resource utilization, or more efficient distributed communication.

97 MATHEMATICS AND COMPUTING↗

High-order hydrodynamic algorithms for exascale computing

Hydrodynamic algorithms are at the core of many laboratory missions ranging from simulating ICF implosions to climate modeling. The hydrodynamic algorithms commonly employed at the laboratory and in industry (1) typically lack requisite accuracy for complex multi- material vortical flows and (2) are not well suited for exascale computing due to poor data locality and poor FLOP/memory ratios. Exascale computing requires advances in both computer science and numerical algorithms. We propose to research the second requirement and create a new high-order hydrodynamic algorithm that has superior accuracy, excellent data locality, and excellent FLOP/memory ratios. This proposal will impact a broad range of research areas including numerical theory, discrete mathematics, vorticity evolution, gas dynamics, interface instability evolution, turbulent flows, fluid dynamics and shock driven flows. If successful, the proposed research has the potential to radically transform simulation capabilities and help position the laboratory for computing at the exascale.

97 MATHEMATICS AND COMPUTING↗

Advanced Simulation and Computing Business Plan

To maintain a credible nuclear weapons program, the National Nuclear Security Administration’s (NNSA’s) Office of Defense Programs (DP) needs to make certain that the capabilities, tools, and expert staff are in place and are able to deliver validated assessments. This requires a complete and robust simulation environment backed by an experimental program to test ASC Program models. This ASC Business Plan document encapsulates a complex set of elements, each of which is essential to the success of the simulation component of the Nuclear Security Enterprise. The ASC Business Plan addresses the hiring, mentoring, and retaining of programmatic technical staff responsible for building the simulation tools of the nuclear security complex. The ASC Business Plan describes how the ASC Program engages with industry partners—partners upon whom the ASC Program relies on for today’s and tomorrow’s high performance architectures. Each piece in this chain is essential to assure policymakers, who must make decisions based on the results of simulations, that they are receiving all the actionable information they need.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Water Quality for High Performance Computing

To support future generations of high performance computers, the Advanced Simulation and Computing Program has a mission need for 80MW of peak power and cooling. Currently the water for the cooling towers at the Strategic Computing Complex (SCC) are cooled by the LANL waste water treated Sanitary Effluent Recovery Facility (SERF) or potable water from the county. The SCC cooling towers currently operate by cycling water between 2-3 cycles of concentration (COC), which is less than the ideal 6 cycles for maximizing water usage. SERF is the ideal water supplier, however when it’s not available potable water is used. The amount of water that the SCC needs nominally is around 45 Million-Gallons/Year (MGY). The future super computer infrastructure (FSI) will need around 125 MGY nominally. SERF is approaching its production limit for reclaimed water. In order to avoid using 100% potable water for the FSI, the option of using non-potable reuse water from Los Alamos County (LAC) was analyzed. This project scope is to focus on the water quality needed for the new super computer cooling towers. Once water quality needs are established, the ideal treatment process needs to be determined. Due to high silica content in water at Los Alamos, emphasis has been placed on treatment processes to remove silica. SERF’s current and future ability to treat water was assessed, as well as the cost of running a SERF like facility or alternative.

97 MATHEMATICS AND COMPUTING↗

Advanced Simulation and Computing FY18 Implementation Plan, Rev. 0

The ASC Program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Directed Stockpile Work (DSW) and major modernization programs also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these lifetime extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT. Specific work activities and scope contained in this Implementation Plan (IP) represent the full-year annual operating plan for FY18. The Initial IP effective October 1, 2017, should be consistent with: 1) the Department’s Base Table when operating under a Continuing Resolution (CR); and 2) the final signed appropriation or full-year CR once enacted.

97 MATHEMATICS AND COMPUTING↗

Advanced Simulation and Computing FY19 Implementation Plan, Rev. 1

The capabilities that the ASC Program provides at the national laboratories play a vital role in the Nuclear Security Enterprise and are necessary for fulfilling the stockpile stewardship and life extension requirements outlined for NNSA. The Program develops modern simulation tools that provide insights into stockpile aging issues, provide the computational and simulation tools that enable designers and analysts to certify the current stockpile and life-extended nuclear weapons, and inform the decision-making process when any modifications in nuclear warheads or the associated manufacturing processes are deemed necessary. Furthermore, ASC is enhancing the predictive simulation capabilities that are essential to evaluate weapons effects, design experiments, and ensure test readiness. The ASC Program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Directed Stockpile Work (DSW) and major modernization programs also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these lifetime extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT. Specific work activities and scope contained in this Implementation Plan (IP) represent the full-year annual operating plan for FY19. The Initial IP, effective August 8, 2018, should be consistent with the Department’s Base Table when operating under a Continuing Resolution (CR). The final IP, effective date TBD, is consistent with the final, enacted appropriation.

97 MATHEMATICS AND COMPUTING↗

Advanced Simulation and Computing FY18 Implementation Plan, Rev. 1

The capabilities that the ASC Program provides at the national laboratories play a vital role in the Nuclear Security Enterprise and are necessary for fulfilling the stockpile stewardship and life extension requirements outlined for NNSA. The Program develops modern simulation tools that provide insights into stockpile aging issues, provide the computational and simulation tools that enable designers and analysts to certify the current stockpile and life-extended nuclear weapons, and inform the decision-making process when any modifications in nuclear warheads or the associated manufacturing processes are deemed necessary. Furthermore, ASC is enhancing the predictive simulation capabilities that are essential to evaluate weapons effects, design experiments, and ensure test readiness. The ASC Program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Directed Stockpile Work (DSW) and major modernization programs also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these lifetime extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT. Specific work activities and scope contained in this Implementation Plan (IP) represent the full-year annual operating plan for FY18. The Initial IP effective October 1, 2017, should be consistent with the Department’s Base Table when operating under a Continuing Resolution (CR). The final IP, effective March 24, 2018, is consistent with the final, enacted appropriation.

97 MATHEMATICS AND COMPUTING↗

Advanced Simulation and Computing FY19 Implementation Plan, Rev. 0

The ASC Program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Directed Stockpile Work (DSW) and major modernization programs also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these lifetime extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT. Specific work activities and scope contained in this Implementation Plan (IP) represent the full-year annual operating plan for FY19. The Initial IP, effective August 8, 2018, should be consistent with the Department’s Base Table when operating under a Continuing Resolution (CR). The final IP, effective date TBD, is consistent with the final, enacted appropriation.

97 MATHEMATICS AND COMPUTING↗

Advanced Tool for Computer Aided Battery Engineering (SNL)

This project aims to provide experimental support, including support for validation and parameterization, for mechanical failure modeling work as part of DOE's Computer Aided Engineering for Electric-Drive Vehicle Batteries (CAEBAT) program. This work involves mechanical deformation testing on both charged and discharged cells, including abusive mechanical testing leading to battery failure. The mechanical data generated is provided to the modeling teams to provide empirical parameterization as well as validation for newly developed models. Testing fully charged cells and packs (abusive battery testing) also allows for a better understanding of what conditions are most likely to lead to a potentially hazardous thermal runaway event.

25 ENERGY STORAGE↗

Advancing Science Through Computation at NDSU (Final Report)

The Center for Computationally Assisted Science and Technology (CCAST), a research unit within the Office for the Vice President for Research and Creative Activity, is in its build-out phase at North Dakota State University (NDSU). CCAST is developing high-performance computing (HPC) capabilities, designed to support existing HPC-oriented NDSU programs as well as to support its own research program which will initially concentrate, but not be limited to, application of theory and computation toward development of high-value functional materials and systems for renewable energy and energy efficiency. The following initial priorities for the Center were established: (1) reconstruct the NDSU HPC hardware and software infrastructure, (2) define CCAST research focus, (3) hire research and HPC support staff, (4) fit-out CCAST computer rooms to ensure continuation and growth of the Center’s HPC activities and, (5) support the NDSU existing thrust in chemo- and bio-informatics (as applied to the high-throughput combinatorial chemistry, biology, and genomics). These priorities are subject to change as the Center grows and evolves.

97 MATHEMATICS AND COMPUTING↗

Management of Risk and Uncertainty Through Optimized Co-Operation of Transmission Systems and Microgrids with Responsive Loads (Final Report)

The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. Ambitious national and state-level goals around the decarbonization of electricity relies on the integration of very high levels of renewable resources, most of which are variable and intermittent. The use of demand response is an ideal approach to counterbalance the intermittency of renewable generation and brings the consumer into the spotlight. Until recently, very little research had been conducted on the co-optimization of these two systems due to computational limitations. However, advances in computational capabilities, and the judicious use of decomposition methods and innovative approximation methods for high-dimension dynamic programming made this goal a viable objective for this project, leading to a fundamental shift in the ability to integrate and fully utilize demand-side resources. To this end, the modeling framework developed introduces a novel co-optimization framework, to include the operations of both the transmission and distribution systems (or microgrids) in operational decision making. This framework was used to analyze renewable and distributed generation along with responsive demand and to compare the capability of co-optimized systems to perform with higher levels of variable renewables. Results show that the use of a bi-level optimization approach is an appropriate structure, capable of co-optimizing a transmission system with multiple distribution systems and microgrids. While increasing the number of connected systems provides increasing flexibility for renewables integration this can also the economic benefits to the low-voltage subsystems with each additional system connected. Comparison of a traditional single-level decision structure with the co-optimization approach illustrates a reduction in overall system cost under co-optimization, while specific cost allocations to transmission and distribution systems are changed.

24 POWER TRANSMISSION AND DISTRIBUTION↗