Optimized Microwave-Based Synthesis of Thermally Stable Inverse Catalytic Core-shell Motifs for CO2 Hydrogenation
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99 GENERAL AND MISCELLANEOUS↗
SEARCH · Engineering Papers
Results for “core optimization”
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CORE-BFS: Communication-Optimized REctangular-partitioned BFS Achieving 160.845 TeraTEPS on Frontier Supercomputer
Distributed Breadth-First Search (BFS) is fundamental to many large-scale graph applications, but its performance on parallel systems is often limited by high communication overhead. This paper presents CORE-BFS, an extremely scalable GPU-based BFS implementation that introduces a unique rectangular 2D partitioning-based design for Frontier supercomputer. To further improve performance, we propose four key optimizations: (1) Rectangular 2D-partition specific data formats that use two compressed row and one compressed column status array bitmaps combined with a Double Compressed Sparse Row (DCSR) format per partition, reducing memory footprint and inter-rank traffic; (2) Adaptive frontier & communication strategy that unifies top-down and bottom-up traversal on the rectangular layout, uses lazy synchronization in top-down levels, and switches variants based on frontier size to minimize communication overhead; (3) Frontier-split degree-aware update that maps frontier vertices to thread-centric, wavefront-centric, and block-centric kernels based on their degree to improve GPU utilization and memory coalescing; (4) Row-reduction pipeline that overlaps bottom-up adjacency list processing with row-wise bitmap reduction to hide inter-rank latency. Together, these techniques increase parallelism while reducing memory and communication overhead. On the Graph500 benchmark, CORE - BFS scales up to 9,248 Frontier nodes with scale-42 graphs and reaches 160.845 TTEPS, delivering a 5.42 × speedup over our previous Frontier implementation.
Yang, Haoshen [Rutgers University]↗
Pathways towards Valid Data: Assessment of Optimized Packaging Strategies for Core Components - 18158
Every company that runs nuclear power plants needs a strategy for disposal of the radioactive waste and for decommissioning and dismantling of its nuclear reactors. The dismantling progress of several German NPPs is already in an advanced stage. Hence, particularly highly activated core components have to be disposed of as radioactive waste. Nevertheless, this is also an issue during the operating phase due to necessary replacements of highly activated core components such as PWR control elements or RPV heads. The conditioning of waste packages for final disposal in the German repository Konrad requires the core components to be dismantled, packaged and dried. Therefore, a qualified packaging strategy is needed to ensure a reliable compliance with the protection objectives of the repository and an optimized utilization of prescribed contingents. Exemplified by PWR control elements a pathway is drawn how to perform an optimized packaging strategy in compliance with the protection objectives of the repository based on only few relevant radionuclides derived from activation calculations. For these calculations, particularly the influence of trace impurities in the materials has to be considered and their amounts have to be verified or analyzed by sampling. Furthermore, low nuclide activities from contamination cannot simply be neglected because some of them are obliged to be declared or their radiological relevance has not been sufficiently determined. Due to various influence factors, qualified sampling strategies need carefully considered concepts. Therefore, detailed planning facilitates the qualification and approval process and reduces the costs for analyses and the number of containers. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Bayesian Optimization for Reactor Design Optimization
This study present a test case in which the Bayesian Optimization method is applied to a simulation-based reactor core design optimization problem. The test case aims to showcase the potential of an automated design optimization algorithm for reactor designs by streamlining the reactor core design workflow, given the high computational cost of simulations. The contributions of this work are threefold. First, the existing HTGR model is converted into a simulation-based design optimization test case by developing a pipeline that enables modification of key design parameters and evaluates design performance based on simulation outputs. Second, Bayesian Optimization is implemented and adapted to demonstrate the feasibility of automatic design optimization for nuclear reactor core. Proposed approach leverages Gaussian Process models to characterize the relationship between design variables and performance metrics, while incorporating novel acquisition functions that balance exploration of the design space with exploitation of promising configurations. This implementation lays the foundation for the future developments of reactor design optimization algorithms.
22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
A Metaheuristic Optimization Tool for High Flux Isotope Reactor Low-Enriched Uranium Core Design
A metaheuristic optimization tool was developed for design optimization studies of a High Flux Isotope Reactor low-enriched uranium core. Low-enriched uranium core design presents a multidimensional, multi-objective optimization problem that requires a systematic approach to avoid arbitrary design decisions. This tool searches this multidimensional design space to generate an optimum design, considering a weighted design performance metric that includes several parameters. The search methods are discussed herein, and the tool is applied to uranium silicide fuel designs.
Variansyah, I.↗
PWR loading pattern optimization with reinforcement learning
The core loading pattern optimization problem belongs to the class of combinatorial optimization problem and has been studied since the dawn of commercial nuclear energy industry. It is characterized by multiple objectives and constraints, with a very high number of candidate patterns, which makes it impossible to solve explicitly. Stochastic optimization methodologies including Genetic Algorithms and Simulated Annealing are used by different nuclear utilities and vendors to perform fuel cycle reload design. Nevertheless, hand-designed solutions continue to be the prevalent method in the industry. To improve the state-of-the-art core reload patterns, we aim to create a method as scalable as possible, that agrees with the designer's goal of performance and safety. To help in this task Deep Reinforcement Learning (DRL), in particular Proximal Policy Optimization is leveraged. DRL has recently experienced a strong impetus from its successes applied to games, sometimes even reaching 'super-human' performances. This paper lays out the foundation of this method and proposes to study the behavior of several hyper-parameters that influence the DRL algorithm. The algorithm is highly dependent on multiple factors such as an exploration/exploitation trade-off that manifests through different parameters such as the number of loading patterns seen and the number of samples collected before a policy update, but also the shape of the objective function derived for the core design. Experimental results also demonstrate the effectiveness of the method in finding high-quality solutions from scratch within a reasonable amount of time. (authors)
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Stochastic Optimization to Find Optimum Beginning-of-Life Core Configuration of Stable Salt Reactor with Online Refueling
A stochastic optimization method has been developed to find an optimum equilibrium cycle core configuration of the waste-burning stable salt reactor, which is a fast-spectrum molten salt reactor with frequent online refueling. An optimum core configuration was determined with the goal of minimizing radial power peaking. Because of the vast number of potential candidate core configurations, stochastic optimization was applied based on simulated annealing and an additional acceleration method, which screened out unpromising core configurations. It has been demonstrated that the developed stochastic optimization method successfully finds the optimal core configuration regardless of the initial guess and outperforms the gradient descent approach. In addition, it has been observed that the use of a so-called out-in core configuration as the initial guess speeds up convergence of the iterative solution more than five times. Based on the searched optimum equilibrium cycle core configuration, new beginning-of-life (BOL) core configurations have been developed. In conclusion, the new BOL core configurations will be used in developing optimum refueling strategies.
Moltex static salt reactor↗
Metal oxide core shell nanostructures as building blocks for efficient light emission (SISGR)
The objective of this research is to synthesize core-shell nano-structured metal oxide materials and investigate their structural, electronic and optical properties to understand the microscopic pathways governing the energy conversion process, thereby controlling and improving their efficiency. Specifically, the goal is to use a single metal oxide core-shell nanostructure and a single excitation source to generate photons with long emission lifetime over the entire visible spectrum and when controlled at the right ratio, generating white light. In order to achieve this goal, we need to control the energy transfer between light emitting elements, which dictates the control of their interatomic spacing and spatial distribution. We developed an economical wet chemical process to form the nanostructured core and to control the thickness and composition of the shell layers. With the help from using DOE funded synchrotron radiation facility, we delineated the growth mechanism of the nano-structured core and the shell layers, thereby enhancing our understanding of structure-property relation in these materials. Using the upconversion luminescence and the lifetime measurements as effective feedback to materials sysnthes is and integration, we demonstrated improved luminescence lifetimes of the core-shell nano-structures and quantified the optimal core-multi-shell structure with optimum shell thickness and composition. We developed a rare-earths co-doped LaPO 4 core-multishell structure in order to produce a single white light source. It was decided that the mutli-shell method would produce the largest increase in luminescence efficiency while limiting any energy transfer that may occur between the dopant ions. All samples resulted in emission spectra within the accepted range of white light generation based on the converted CIE color coordinates. The white light obtained varied between warm and cool white depending on the layering architecture, allowing for the utilization into a wide range of applications. With DOE’s overall mandate to reduce the US’s dependence on rare-earth elements, this work demonstrated how to make every RE atom count toward white light generation by controlling their spatial distribution thereby significantly reducing the amount needed. This is one approach toward reducing the dependence on RE elements and the strategies we developed can be used in discovering RE-free systems. The project is of benefit to the general public as it improves the optical efficiency of these materials, while reducing US’s dependence on RE elements.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
ACHIEVING GROUNDWATER MONITORING OPTIMIZATION AT SRS: A CORE TEAM PROCESS BASED ON RIGOROUS TECHNICAL ASSESSMENT WM15 15273
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Lewis, C.↗
Ex-Core Thermo-Fluidics Optimization for Transformational Challenge Reactor
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Vegendla, Prasad↗
A strategy for automated core design to increase economic viability and minimize fuel fragmentation, relocation, and dispersal susceptibility in high-burnup cores
The nuclear industry aims to increase the cycle length of pressurized water reactors from 18 to 24 months to increase power plant capacity factors and economic viability. These cycle length extensions will inherently require fuel rods to exceed the current peak rod average burnup limit of 62 GWd/MTU. A chief concern of operating beyond the current burnup limit is the fuel fragmentation, relocation, and dispersal (FFRD) phenomenon in which pulverized fuel fragments can axially relocate and escape through a burst in the cladding formed during a loss-of-coolant accident. In this work, we demonstrate an approach for automating core design employing an optimization tool based on a penalty-free, parallel simulated annealing algorithm to produce pressurized water reactor core designs with two different optimization objectives. The two objectives were to produce core designs with (1) mitigated FFRD susceptibility while achieving 24-month cycle lengths (2) maximum cycle length with no regard for the likelihood of FFRD. Batch size was considered in tandem with both cases to maximize economic viability. The PARCS nodal model was the primary reactor physics tool used in the optimizations and used nuclear cross sections calculated with 2D Polaris lattice physics models. Reactor performance and safety characteristics of the optimized cores were verified using high-fidelity Virtual Environment for Reactor Applications models. The core designs produced by the optimization tool are compared with each other and to a high-burnup core design produced and analyzed in previous works to highlight the fuel management strategies that may enhance high-burnup reactor safety and economic viability. The optimized cores satisfied their respective objective functions, producing a maximum cycle length of 720 effective full-power days in one core design and one that may reduce FFRD susceptibility by up to 50% based on the first-order approximation to FFRD risk formulated in this work. The optimized cores met most constraints but exceeded the hot channel factor limit, especially in FFRD cases where fresh fuel carried more power. Furthermore, this highlights the need for future lattice-level optimizations and broader assembly options.
Cycle length↗
A Computational Tool Compatible with NEAMS Code Packages for Optimizing the Shape of Nuclear Reactor Components and of Whole Core Performance
We designed and implemented a shape optimization tool that functions with NEAMS codes, and that nuclear scientists and engineers can employ to optimize the shape of individual components and the whole core under the applicable single- or multi-physics model comprising the employed code(s). The shape-optimization tool enables varying the geometric shape itself as well as its dimensions to yield, potentially, new component designs that are not limited by the designer’s intuition and previous experience. In cases where the optimal-shape object is an individual component, we provide the capability for additional verification that the whole-core performance using the optimized component performs better, under the prescribed optimization criteria, than the initial design. Our shape-optimization tool couples to NEAMS codes via a flexible input- composer interface and enables the user to constrain the shape’s evolution to ensure the component’s manufacturability. Finally, we demonstrate our shape-optimization tool with single- and multi-physics NEAMS codes. This objective is motivated by the recent advances in manufacturing technology that, combined with rising interest in novel reactor concepts, are creating new opportunities for innovation in the design of individual components that affect the performance of the full reactor system. In particular, Additive Manufacturing (AM) enables mass production of highly precise, intricate and complex component shapes that are not feasible with traditional manufacturing techniques. To accomplish this goal we developed and implemented in MOOSE: (1) discrete shape optimization capability based on a state-space search that uses Artificial Intelligence strategies to find the optimal state/shape; (2) smooth shape optimization tool that employs PETSc’s toolkit for advanced optimization (TAO) to optimize node-displacement of the components’ model sidesets; (3) hierarchical core optimization workflow that recognizes the repeating patterns typical in a nuclear reactor and performs the optimization one level at a time with increasing length scale. Each of these tools is equipped with user-specified constraints to avoid optimal shapes that are not manufacturable. The developed shape optimization tool is verified and demonstrated on various nuclear reactor core components and models. The optimization process accounts for tightly coupled physics that govern the behavior of these target reactors, and exercises several NEAMS codes in a coupled multiphysics fashion. The impact of the delivered shape optimization tool will materialize in the optimal design, from the outset, of advanced reactors currently contemplated to regain the US’s leadership in nuclear energy R&D. Novel reactor concepts, e.g. Molten Salt Reactors, and sizes/capacities, e.g. micro- reactors, provide a unique opportunity to optimize performance from the early stages of development, before the investment in components’ production lines, validation experiments, and licensing regimes make future improvements in performance prohibitively expensive and force sub-optimal performance on the affected reactor concept in perpetuity. This benefit will be realized by the delivered shape optimization tool regardless of the applicable manufacturing process whether traditional or AM, thereby broadening the impact of this project on current and future reactor concepts and technologies
11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Exploring the All-to-All Collective Optimization Space with ConnectX CORE-Direct
The all-to-all collective communication operation is used by many scientific applications, and is one of the most time consuming and challenging collective operation to optimize. The algorithms for all-to-all operations typically fall into two classes, logarithmic and linear scaling algorithms, with Bruck's algorithm, a logarithmic scaling algorithm, used in many small-data all-to-all implementations. The recent addition of InfiniBand CORE-Direct support for network management of collective communications offers new opportunities for optimizing all-to-all operation as well as supporting truly asynchronous implementations of these operations. This paper presents several new enhancements to the Bruck small-data algorithm that leverage CORE-Direct and other InfiniBand network capabilities to produce efficient implementations of this collective operation. These include RDMA, SR-RNR, and SR-RTR algorithms. In addition, nonblocking implementations of these collective operations are also presented. Benchmark results show that the RDMA algorithm, which uses CORE-Direct capabilities to offload collective communication management to the Host Channel Adapter (HCA), hardware gather support for sending non-continuous data, and low-latency RDMA semantics, performs the best. For a 64 processes and 128 byte-per-process all-to-all, the RDMA algorithm performs 27% better than Bruck's algorithm implementation in Open MPI and 136% better than the SR-RTR algorithm. In addition, the nonblocking versions of these algorithms have the same performance characteristics as the blocking algorithms. Finally, measurements of computation/communication overlap capacity show that all offloaded algorithms achieve about 98% overlap for large data all-to-all, whereas implementations using host-based progress achieve only about 9.5% overlap.
Venkata, Manjunath Gorentla↗
Evaluating the Efficiency of a Multi-core Aware Multi-objective Optimization Tool for Calibrating the SWAT Model
The efficiency of calibrating physically-based complex hydrologic models is a major concern in the application of those models to understand and manage natural and human activities that affect watershed systems. In this study, we developed a multi-core aware multi-objective evolutionary optimization algorithm (MAMEOA) to improve the efficiency of calibrating a worldwide used watershed model (Soil and Water Assessment Tool (SWAT)). The test results show that MAMEOA can save about 1-9%, 26-51%, and 39-56% time consumed by calibrating SWAT as compared with sequential method by using dual-core, quad-core, and eight-core machines, respectively. Potential and limitations of MAMEOA for calibrating SWAT are discussed. MAMEOA is open source software.
97 MATHEMATICS AND COMPUTING↗
Reactor lifetime extension by limiting the RPV fluence increase
Lifetime extension of Pressurized Water Reactors must consider the embrittlement of the reactor pressure vessel. AREVA NP has a long history in developing and implementing problem oriented shielding measures. The main goal of these measures is the reduction of the fast flux at the original core periphery. Dependent on the size of the problem, the measures can be characterized as optimization of core design, insertion of neutron absorber material in regular fuel assemblies at the core periphery, partly inert assemblies, and fully inert assemblies. The first two solutions can in principal be handled with standard tools. Special measures had to be developed for the neutronic description of the other two options. These newly developed methodologies are based on the Equivalence Theory that was developed at AREVA NP in the late 1970's and early 1980's and is applied for the description of inert fuel assemblies as well as for reflectors in its code systems. The implemented solutions were accompanied by measurement programs for qualification of the design methods and for confirmation of the predicted shielding effect. The design shielding ratios of the developed measures cover a range of approximately 1.5 to 10 with the shielding ratio being defined as the ratio of vessel fluence per time interval of a core without shielding to a core with shielding provision. The comparisons of calculation and measurement verify the projected behavior of the shielding measures. (authors)
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
An evaluation of parallel optimization for OpenSolaris Network Stack
Computing is now shifting towards multiprocessing. The fundamental goal of multiprocessing is improved performance through the introduction of additional hardware threads or cores (referred to as 'cores' for simplicity). Modern network stacks can exploit parallel cores to allow either message-based parallelism or connection-based parallelism as a means to enhance performance. OpenSolaris has redesigned and parallelized to better utilize additional cores. Three special technologies, named Softring Set, Soft ring and Squeue are introduced in OpenSolaris for stack parallelization. In this paper, we study the OpenSolaris packet receiving process and its core parallelism optimization techniques. Experiment results show that these techniques allow OpenSolaris to achieve better network I/O performance in multiprocessing environments; however, network stack parallelization has also brought extra overheads for system. An effective and efficient network I/O optimization in multiprocessing environments is required to cross all levers of the network stack from network interface to application.
99 GENERAL AND MISCELLANEOUS↗
FOX: A Fault Oblivious Extreme-Scale Execution Environment
The FOX project, funded under the ASCR X-stack I program, developed systems software and runtime libraries for a new approach to the data and work distribution for massively parallel, fault oblivious application execution. Our work was motivated by the premise that exascale computing systems will provide a thousand-fold increase in parallelism and a proportional increase in failure rate relative to today’s machines. To deliver the capability of exascale hardware, the systems software must provide the infrastructure to support existing applications while simultaneously enabling efficient execution of new programming models that naturally express dynamic, adaptive, irregular computation; coupled simulations; and massive data analysis in a highly unreliable hardware environment with billions of threads of execution. Our OS research has prototyped new methods to provide efficient resource sharing, synchronization, and protection in a many-core compute node. We have experimented with alternative task/dataflow programming models and shown scalability in some cases to hundreds of thousands of cores. Much of our software is in active development through open source projects. Concepts from FOX are being pursued in next generation exascale operating systems. Our OS work focused on adaptive, application tailored OS services optimized for multi → many core processors. We developed a new operating system NIX that supports role-based allocation of cores to processes which was released to open source. We contributed to the IBM FusedOS project, which promoted the concept of latency-optimized and throughput-optimized cores. We built a task queue library based on distributed, fault tolerant key-value store and identified scaling issues. A second fault tolerant task parallel library was developed, based on the Linda tuple space model, that used low level interconnect primitives for optimized communication. We designed fault tolerance mechanisms for task parallel computations employing work stealing for load balancing that scaled to the largest existing supercomputers. Finally, we implemented the Elastic Building Blocks runtime, a library to manage object-oriented distributed software components. To support the research, we won two INCITE awards for time on Intrepid (BG/P) and Mira (BG/Q). Much of our work has had impact in the OS and runtime community through the ASCR Exascale OS/R workshop and report, leading to the research agenda of the Exascale OS/R program. Our project was, however, also affected by attrition of multiple PIs. While the PIs continued to participate and offer guidance as time permitted, losing these key individuals was unfortunate both for the project and for the DOE HPC community.
97 MATHEMATICS AND COMPUTING↗
Geometries of edge and mixed dislocations in bcc Fe from first principles calculations
We use density functional theory (DFT) to compute the core structures of $a_0[100](010)$ edge, $a_0[100](011)$ edge, $a_0/2[\bar{1}\bar{1}1](1\bar{1}0)$ edge, and $a_0/2[111](1\bar{1}0)$ $71^{\circ}$ mixed dislocations in body-centered cubic (bcc) Fe. The calculations are performed using flexible boundary conditions (FBC), which effectively allow the dislocations to relax as isolated defects by coupling the DFT core to an infinite harmonic lattice through the lattice Green function (LGF). We use the LGFs of the dislocated geometries in contrast to most previous FBC-based dislocation calculations that use the LGF of the bulk crystal. The dislocation LGFs account for changes in the topology of the crystal in the core as well as local strain throughout the crystal lattice. A simple bulk-like approximation for the force constants in a dislocated geometry leads to dislocation LGFs that optimize the core structures of the $a_0[100](010)$ edge, $a_0[100](011)$ edge, and $a_0/2[111](1\bar{1}0)$ $71^{\circ}$ mixed dislocations. This approximation fails for the $a_0/2[\bar{1}\bar{1}1](1\bar{1}0)$ dislocation however, so in this case we derive the LGF from more accurate force constants computed using a Gaussian approximation potential. The standard deviations of the dislocation Nye tensor distributions quantify the widths of the dislocation cores. The relaxed cores are compact, and the local magnetic moments on the Fe atoms closely follow the volumetric strain distributions in the cores. We also compute the core structures of these dislocations using eight different classical interatomic potentials, and quantify symmetry differences between the cores using the Fourier coefficients of their Nye tensor distributions. Most of the core structures computed using the classical potentials agree well with the DFT results. Furthermore the DFT core geometries provide benchmarking for classical potential studies of work-hardening, as well as substitutional and interstitial sites for computing solute-dislocation interactions that serve as inputs for mesoscale models of solute strengthening and solute diffusion near dislocations.
36 MATERIALS SCIENCE↗