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At least 91 records · Page 5

Development of Plant Reload Optimization Framework Capabilities for Core Design and Fuel Performance Analysis

The United States (U.S.) nuclear industry faces a challenge in maintaining required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects of light water reactor (LWR) nuclear power plant (NPP) operations. Safety can become more economical by using a risk-informed ecosystem, such as the one being developed by the Risk-Informed Systems Analysis (RISA) Pathway under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. The LWRS Program promotes a wide range of research and development activities with the goal of maximizing both the safety and economic efficiency of NPPs through improved scientific understanding, especially given many plants are now considering second license renewals. The RISA Pathway has two main goals: (1) deploy methodologies and technologies that better represent safety margins and cost and safety factors and (2) develop advanced applications that enable cost-effective plant operation. The Plant Reload Optimization Platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses, and also uses artificial intelligence to support optimization of core design solutions. This report summarizes Fiscal Year 2022 (FY-22) activity in platform capability developments in RAVEN. This platform performs simulations using industry codes for core design (i.e., PARCS) and fuel performance (i.e., TRANSURANUS) which will allow expansion of the capabilities to include advanced fuel designs such as accident-tolerant fuel (ATF)s with high burnup.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Performance Analysis of Data Processing in Distributed File Systems with Near Data Processing

In the era of big data, the escalating volume and velocity of data generation pose significant challenges in data processing. Traditional systems like Spark and Hadoop manage the increasing amount and velocity of data by improving data placement and processing speeds. However, they face inherent limitations due to the essential data movement required for processing. In this paper, we explore the Skyhook framework, a novel extension of the Ceph distributed system, which significantly reduces the need for data movement. We present an extensive case study using the Skyhook framework, applying it with the TPC-H and K-means clustering algorithms. More specifically, we leverage the TPC-H benchmark to distinguish between CPU-intensive and I/O-intensive tasks. We explore the integration of K-means clustering into SQL, coupled with a near-data processing system to offload the computational burden of the K-means clustering algorithm to storage nodes. We conduct a comprehensive performance evaluation of distributed data processing applications across three processing approaches: traditional layout (baseline), optimized layout, and near-data processing. Additionally, we introduce the use of the FIO tool to simulate real-world system workloads, enabling the measurement of performance metrics such as average latency and CPU utilization. Our research is a significant advance in understanding how to optimize data processing systems to meet the demands of the modern data landscape.

Hou, Shiyue↗

Experimental performance analysis of a dual source heat pump integrated with thermal energy storage

To mitigate disturbances to the electric grid resulting from the growing penetration of intermittent and decentralized renewable generation, a dual-source (air source and ground source) heat pump (DSHP) integrated with thermal energy storage (TES) was developed. The DSHP can use either ambient air or the shallow subsurface of the ground to provide space heating or space cooling to the building as the conventional heat pump and produce hot/cold water for charging TES. Using dual sources (air and ground) can reduce the required size of the expensive ground heat exchangers while retaining high energy efficiency. During the off-peak period, the DSHP cools/heats the TES with low-cost electricity or overproduced renewable power. The stored cooling/heating energy in the TES is released during peak hours of the electric grid to meet the thermal demands of the building without consuming electricity to run the DSHP. A 2-ton (7 kW) prototype DSHP was developed and integrated with a 50-gallon (189 L) TES tank filled with a phase change material. Field tests were conducted to characterize the performance of the integrated system operating in various operation modes.

Wang, Lingshi↗

Performance Analysis of Speculative Parallel Adaptive Local Timestepping for Conservation Laws

Stable simulation of conservation laws, such as those used to model fluid dynamics and plasma physics applications, requires the satisfaction of the so-called Courant-Friedrichs-Lewy condition. By allowing regions of the mesh to advance with different timesteps that locally satisfy this stability constraint, significant work reduction can be attained when compared to a time integration scheme using a single timestep size. However, parallelizing this algorithm presents considerable difficulty. Since the stability condition depends on the state of the system, dependencies become dynamic and potentially non-local. In this article, we present an adaptive local timestepping algorithm using an optimistic (Timewarp-based) parallel discrete event simulation. We introduce waiting heuristics to limit misspeculation and a semi-static load balancing scheme to eliminate load imbalance as parts of the mesh require finer or coarser timesteps. Last, we outline an interface for separating the physics of the specific conservation law from the temporal integration allowing for productive adoption of our proposed algorithm. We present a misspeculation study for three conservation laws, demonstrating both the productivity of the local timestepping API, for which 74% of the lines of code are reused across different conservation laws, and the robustness of the waiting heuristics—at most 1.5% of element updates are rolled back. Our performance studies demonstrate up to a 2.8× speedup versus a baseline unoptimized local timestepping approach, a 4x improvement in per-node throughput compared to an MPI parallelization of synchronous timestepping, and scalability up to 3,072 cores on NERSC’s Cori Haswell partition.

97 MATHEMATICS AND COMPUTING↗

High-burnup boiling water reactor steady-state operating conditions and fuel performance analysis

The primary operational costs for existing nuclear reactors are plant operation costs, maintenance costs, and fuel costs, all of which are influenced by the materials used and the design of the reactor core. Optimizing core design parameters—including burnup limits and enrichment levels—can lengthen cycles, reduce outages, reduce reload batch fractions and spent fuel storage requirements, and lower maintenance and operating expenses, thereby enhancing economic viability. Furthermore, developing higher-fidelity tools to simulate these parameters enables better identification of the available margin, improves overall plant safety, and improves the understanding a given plant’s responses to accident scenarios. Here, in the US, much of the research and development focus has traditionally been on pressurized water reactors (PWRs), but boiling water reactors (BWRs) comprise approximately one-third of the US reactor fleet. Modeling and simulation advances for BWRs and PWRs—particularly those achieved through the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program—are crucial to the long-term viability of the light–water reactor industry. A key research area of the high burnup and increased enriched fuel initiative is focused on addressing issues related to postulated loss-of-coolant accident (LOCA) scenarios. NEAMS has dedicated significant effort to enhancing tools to better support BWRs. A current focus is showcasing the BWR framework for high-burnup LOCA analysis. This high-fidelity steady-state analysis is a first step toward demonstrating a best-estimate, pin-by-pin high-burnup BWR LOCA analysis to assess full-core cladding rupture behavior for a representative BWR. The objective of this effort is to provide a modeling capability that will help elucidate and provide a best-estimate evaluation for cladding rupture susceptibility in BWRs. This modeling capability could then be used to prevent and/or mitigate cladding ruptures in postulated accident scenarios without penalizing operational parameters. Additionally, the results of this work will help identify strategies for finding additional margins or potentially limiting cladding ruptures through core design optimizations to enable more efficient core designs.

Capps, Nathan [Oak Ridge National Laboratory (ORNL↗

Performance analysis and tank test validation of a hybrid ocean wave-current energy converter with a single power takeoff

This paper introduces a hybrid ocean wave-current energy converter (HWCEC) that harvests energy from ocean waves and current simultaneously with a single power takeoff (PTO). Specifically, the wave energy is extracted through relative heaving motion between a floating buoy and a submerged second body, while the current energy is extracted using a marine current turbine (MCT). Energy from both sources are integrated by a hybrid PTO whose concept is based on a mechanical motion rectifier (MMR). The hybrid PTO with two one-way clutches converts bidirectional, up-and-down motion from the waves into unidirectional rotation of the generator. Meanwhile a third one-way clutch couples the MCT with the same generator. The wave and current can simultaneously or separately drive the same generator through different engagement and disengagement statuses of the one-way clutches. Time-domain simulation is conducted with hydrodynamic coefficients obtained from computational fluid dynamics analysis and boundary element method. Tank tests were conducted for a HWCEC under co-existing wave and current inputs. For comparison, separate baseline tests of a turbine and a two-body point absorber, each acting in isolation, are conducted. Experimental results validate the dynamic modeling and show that a HWCEC can increase the output power with a range between 29-87% over either current turbine and wave energy converter acting individually, and it can reduce by up to 70% the peak-to-average power ratio compared with the wave energy converter on the tested conditions.

16 TIDAL AND WAVE POWER↗

Performance analysis of functionally graded multifunctional piezoelectric energy harvesting microgyroscopes

Functionally graded materials (FGMs) are composite materials with varying material properties in one or more directions. These materials possess distinct characteristics compared to their constituent components. The ability to control material distribution and compositions in FGMs offers improved constraints over the natural frequencies of the system, making them highly suitable for energy harvesting applications. In this study, we focus on a piezoelectric FGM composed of Platinum (Pt) and Lead Titanate Zirconate (PZT). By utilizing FGMs for energy harvesting, we simplify the system from a multilayer structure to a single-layer system, thereby increasing power density by reducing volume. In this work, a power law distribution is used to model the material variation throughout the thickness of the single-layered beam. The governing equations of motion and boundary conditions for FG energy harvesting microgyroscope are derived using Euler-Bernoulli beam theory, the constitutive piezoelectric principle, and the extended Hamilton's principle. To simulate the nonlinear motion of the FG energy harvester, we employ the differential quadrature method (DQM). Subsequently, an investigation is carried out to examine the effects of various factors including material distribution, platinum percentage, base rotation, DC voltage, and electrical load resistance on the energy harvesting microgyroscope with functionally graded materials. Here, the findings suggest that functionally graded energy harvesting gyroscopes can be adjusted to obtain effective energy harvesting and sensing capabilities by carefully selecting the material distribution, input voltage, and electrical load resistance.

42 ENGINEERING↗

Performance analysis of photodetectors based on 2D materials and heterostructures

The unprecedented demand for sophisticated, self-powered, compact, ultrafast, cost-effective, and broadband light sensors for a myriad of applications has spurred a lot of research, precipitating in a slew of studies over the last decade. Apart from the photosensing ability of an active element in the light sensor, the device architecture is crucial in terms of photoinduced charge carrier generation and separation. Since the inception of graphene and the subsequent research growth in the atomically thin 2D materials, researchers have developed and adapted different families of 2D materials and device architectures, including single element 2D, 0D/2D, 2D/2D, 1D/2D stacked structures, and so on. Here this review discusses the recent reports on the light-sensing properties of various 2D materials, their heterostructures, and characteristics applicable to the ultraviolet-near infrared (UV-NIR), short-wave IR (SWIR), mid-wave IR (MWIR), long-wave IR (LWIR), and terahertz (THz) spectral ranges. It highlights the novelty of the burgeoning field, the heightened activity at the boundaries of engineering and materials science, particularly in the generation of charge carriers, their separation, and extraction, and the increased understanding of the underpinning science through modern experimental approaches. Devices based on the simultaneous effects of the pyro-phototronic effect (PPE) and the localized surface plasmon resonance (LSPR) effect, the photothermoelectric effect (PTE)-assisted photodetectors (PDs), waveguide-integrated silicon-2D PDs, metal-2D-metal PDs, and organic material PDs are examined rigorously. Theoretical treatment utilizing various computational approaches to investigate 2D materials and heterostructures for photodetection applications is also briefly discussed. At the end, current challenges and solutions to enhance the figures of merit of photodetectors are proposed.

2D transition metal chalcogenides↗

Performance analysis of superconductor-constriction-superconductor transmon qubits

Here, this work presents a computational analysis of a superconducting transmon qubit design, in which the superconductor-insulator-superconductor (SIS) Josephson junction is replaced by a coplanar, superconductor-constriction-superconductor (ScS) nanobridge junction. Within the scope of Ginzburg-Landau theory, we find that the nanobridge ScS transmon has an improved charge dispersion compared to the SIS transmon, with a tradeoff of smaller anharmonicity. These calculations provide a framework for estimating the superconductor material properties and junction dimensions compatible with gigahertz frequency ScS transmon operation.

36 MATERIALS SCIENCE↗