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At least 1,567 records · Page 87

The effect of temperature and burnup on U-10Zr metallic fuel chemical interaction with HT-9: A SEM-EDS study

The fuel cladding chemical interaction (FCCI) between Uranium-Zirconium-based metallic fuel and cladding materials during in-pile service is one of the most constraining phenomena affecting the performance of this fuel system. In this study, we investigated the effect of temperature and burnup on the FCCI development in two U-10 wt.% Zr (U-10Zr) fuel samples with HT-9 cladding irradiated as part of the MFF-3 irradiation test in the Fast Flux Test Facility (FFTF). One sample achieved a burnup of 13.1 at.% and operated with an average inner cladding temperature of 530°C, while the other achieved a burnup of 8.5 at.% and was subjected to an average inner cladding temperature of 615°C. Automated scanning electron microscopy (SEM) back-scattered electron (BSE) imaging of entire fuel cross-sections and SEM energy dispersive x-ray spectroscopy (EDS) analysis on specific fuel-cladding interface regions successfully provided a comprehensive characterization of the depth and type of interaction happening under different irradiation conditions. Further, our analysis shows that FCCI development on both fuel and cladding side is strongly influenced by the inner cladding temperature and, to some extent, the formation and integrity of Zr-rich layers between the fuel and cladding, while the impact of burnup and power is negligible. Measured FCCI thicknesses were compared to BISON simulations using both an empirical model based upon legacy data from the Experimental Breeder Reactor II (EBR II) irradiations and a mechanistic model currently under development for the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, showing satisfactory agreement. Nonetheless, this comparison supports the need for additional microstructural characterization in intermediate ranges of temperature, power, and burnups in prototypic-length pins.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Coupled Multiphysics Simulations of Heat Pipe Microreactors Using DireWolf

DireWolf is a multiphysics software driver application designed to simulate heat pipe–cooled nuclear microreactors. Developed under the U.S. Department of Energy, Office of Nuclear Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the DireWolf software application’s objective is to provide the nuclear community with a design and safety analysis simulation capability. Based upon the NEAMS program Multiphysics Object-Oriented Simulation Environment (MOOSE) computational framework, DireWolf tightly couples nuclear microreactor physics, reactor physics, radiation transport, nuclear fuel performance, heat pipe thermal hydraulics, power generation, and structural mechanics to resolve the interdependent nonlinearities. DireWolf is capable of simulating both steady and transient normal reactor operation and several postulated failure scenarios. We will present the fundamental physics of heat pipe–cooled nuclear microreactors and the MOOSE-based software employed in DireWolf. Both steady and transient results for coupled reactor physics, radiation transport, and nuclear fuel performance are demonstrated.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Nitric Acid and Water Extraction by T2EHDGA in n -Dodecane

Liquid-liquid distribution behavior of nitric acid (HNO3) and water by a diglycolamide ligand, N,N,N',N'-tetra-2-ethylhexyldiglycolamide (T2EHDGA) into n-dodecane diluent was investigated. Spectroscopic FTIR and NMR characterization of the organic extraction solutions indicate T2EHDGA carbonyl coordinates HNO3 and progressively aggregates at high acid conditions. Water extraction increases in the presence of HNO3. The experimentally observed distribution of HNO3 was modeled using the computer program, SXLSQI. The results indicated that the formation of two organic phase species—HNO3·T2EHDGA and (HNO3)2·T2EHDGA—satisfactory describes the acid transport behavior. Temperature dependent solvent extraction studies allowed for determination of thermodynamic extraction constants and ΔH and ΔS parameters for the corresponding extractive processes.

Campbell, Emily L.↗

Heterogeneous Hierarchical Workflow Composition

Workflow systems promise scientists an automated end-to-end path from hypothesis to discovery. However, expecting any single workflow system to deliver such a wide range of capabilities is impractical. A more practical solution is to compose the end-to-end workflow from more than one system. With this goal in mind, the integration of task-based and in situ workflows is explored, where the result is a hierarchical heterogeneous workflow composed of subworkflows, with different levels of the hierarchy using different programming, execution, and data models. Materials science use cases demonstrate the advantages of such heterogeneous hierarchical workflow composition.

distributed workflows↗

Endogenizing Probabilistic Resource Adequacy Risks in Deterministic Capacity Expansion Models

In this work, we demonstrate how power system capacity expansion models can understate the stochastic effects of thermal outages when considering resource availabilities on an hourly expected value basis, yielding system designs with multiple orders of magnitude more shortfall risk than stated adequacy targets. We develop a novel approximation approach to efficiently endogenize awareness of this risk in a deterministic, linear capacity expansion framework. We compare this approach to exogenous tuning of an energy reserve margin, the leading alternative method to compensate for unmodeled probabilistic shortfall risk. Empirical results from a test system show that the new endogenous method cost-effectively meets all regional reliability targets with a single optimization solve, and produces a near-identical system design as the incumbent method without the need for repeated re-optimizations to find an appropriate reserve level. The endogenous method may also use iterative re-optimizations to further improve solution quality, although these incremental benefits were modest in the system studied.

capacity expansion modeling↗

Quantum Distributed Unit Commitment: An Application in Microgrids

The dawn of quantum computing brings on a revolution in the way combinatorially complex power system problems such as Unit Commitment are solved. The Unit Commitment problem complexity is expected to increase in the future because of the trend toward the increase of penetration of intermittent renewables. Even though quantum computing has proven effective for solving a host of problems, its applications for power systems’ problems have been rather limited. Here, in this paper, a quantum unit commitment is innovatively formulated and the quantum version of the decomposition and coordination alternate direction method of multipliers (ADMM) is established. The above is achieved by devising quantum algorithms and by exploiting the superposition and entanglement of quantum bits (qubits) for solving subproblems, which are then coordinated through ADMM to obtain feasible solutions. The main contributions of this paper include: 1) the innovative development of a quantum model for Unit Commitment; 2) development of decomposition and coordination-supported framework which paves the way for the utilization of limited quantum resources to potentially solve the large-scale discrete optimization problems; 3) devising the novel quantum distributed unit commitment (QDUC) to solve the problem in a larger scale than currently available quantum computers are capable of solving. The QDUC results are compared with those from its classical counterpart, which validate the efficacy of quantum computing.

97 MATHEMATICS AND COMPUTING↗

Scalable parallel distance field construction for large-scale applications

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. Anew distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking overtime, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. In conclusion, our work greatly extends the usability of distance fields for demanding applications.

97 MATHEMATICS AND COMPUTING↗

Extreme-Scale Stochastic Particle Tracing for Uncertain Unsteady Flow Visualization and Analysis

We present an efficient and scalable solution to estimate uncertain transport behaviors-stochastic flow maps (SFMs)-for visualizing and analyzing uncertain unsteady flows. Computing flow maps from uncertain flow fields is extremely expensive because it requires many Monte Carlo runs to trace densely seeded particles in the flow. We reduce the computational cost by decoupling the time dependencies in SFMs so that we can process shorter sub time intervals independently and then compose them together for longer time periods. Adaptive refinement is also used to reduce the number of runs for each location. We parallelize over tasks-packets of particles in our design-to achieve high efficiency in MPI/thread hybrid programming. Such a task model also enables CPU/GPU coprocessing. We show the scalability on two supercomputers, Mira (up to 256K Blue Gene/Q cores) and Titan (up to 128K Opteron cores and 8K GPUs), that can trace billions of particles in seconds.

CPU-GPU hybrid parallelism↗

Patient-based estimation of organ dose for a population of 58 adult patients across 13 protocol categories

Purpose: This study aimed to provide a comprehensive patient-specific organ dose estimation across a multiplicity of computed tomography (CT) examination protocols. Methods: A validated Monte Carlo program was employed to model a common CT system (LightSpeed VCT, GE Healthcare). The organ and effective doses were estimated from 13 commonly used body and neurological CT examination. The dose estimation was performed on 58 adult computational extended cardiac-torso phantoms (35 male, 23 female, mean age 51.5 years, mean weight 80.2 kg). The organ dose normalized by CTDI{sub vol} (h factor) and effective dose normalized by the dose length product (DLP) (k factor) were calculated from the results. A mathematical model was derived for the correlation between the h and k factors with the patient size across the protocols. Based on this mathematical model, a dose estimation iPhone operating system application was designed and developed to be used as a tool to estimate dose to the patients for a variety of routinely used CT examinations. Results: The organ dose results across all the protocols showed an exponential decrease with patient body size. The correlation was generally strong for the organs which were fully or partially located inside the scan coverage (Pearson sample correlation coefficient (r) of 0.49). The correlation was weaker for organs outside the scan coverage for which distance between the organ and the irradiation area was a stronger predictor of dose to the organ. For body protocols, the effective dose before and after normalization by DLP decreased exponentially with increasing patient's body diameter (r > 0.85). The exponential relationship between effective dose and patient's body diameter was significantly weaker for neurological protocols (r < 0.41), where the trunk length was a slightly stronger predictor of effective dose (0.15 < r < 0.46). Conclusions: While the most accurate estimation of a patient dose requires specific modeling of the patient anatomy, a first order approximation of organ and effective doses from routine CT scan protocols can be reasonably estimated using size specific factors. Estimation accuracy is generally poor for organ outside the scan range and for neurological protocols. The dose calculator designed in this study can be used to conveniently estimate and report the dose values for a patient across a multiplicity of CT scan protocols.

60 APPLIED LIFE SCIENCES↗

SMT-Aware Instantaneous Footprint Optimization

Modern architectures employ simultaneous multithreading (SMT) to increase thread-level parallelism. SMT threads share many functional units and the whole memory hierarchy of a physical core. Without a careful code design, SMT threads can easily contend with each other for these shared resources, causing severe performance degradation. Minimizing SMT thread contention for HPC applications running on dedicated platforms is very challenging, because they usually spawn threads within Single Program Multiple Data (SPMD) models. To address this important issue, we introduce a simple scheme for SMT-aware code optimization, which aims to reduce the memory contention across SMT threads.

Instantaneous Footprint↗

ProgressiveHedging.jl

Implementation of the Progressive Hedging algorithm written in Julia utilizing JuMP. This is used to solve multistage optimization problems (e.g. Stochastic programs or capacity expansion models). The user uses the StructJuMP extension of JuMP to create the model and build up the scenario tree.

Sigler, Devon↗

PyChargeModel (Oriented Programming Based Electric Vehicle and Electric Vehicle Supply Equipment Charging Model in Python) [SWR-22-39]

The PyChargeModel creates two classes called "ElectricVehicles" and "evse_class", which can be used to create multiple instances of electric vehicles (EVs) and electric vehicle supply equipment (EVSE or charging ports) and simulate charging behavior. These objects can be instantiated with several properties such as battery chemistries, battery pack sizes, cell sizes, charging port power, dc or ac chargers etc. The objects can communicate with each other by calling different methods built within the classes. Through these methods, each EV object can be assigned to an EVSE, charged either using a default protocol or using setpoint values communicated from a site controller via the EVSE object.

Mishra, Partha↗

Numerical Simulation with Experimental Validation of the Draping Behavior of Woven Fabrics

Woven fabric composites are extensively used in molding complex geometrical shapes due to their high conformability compared to other fabrics. Preforming is an important step in the overall process. In this step, the two-dimensional fabric is draped to become the three-dimensional shape of the part prior to resin injection. During preforming, the orientation of the tows may change significantly compared to the initial orientations. Accurate prediction of the tow orientations after molding is important for evaluating the structural performance of the final part. This paper investigates the fiber angle changes for carbon fiber woven fabrics during draping over a truncated pyramid tool designed and fabricated at the General Motors Research Labs. This aspect of study is a subset of the broad study conducted under the purview of a Department of Energy project funded to GM in developing state of the art computational tools for integrated manufacturing and structural performance prediction of carbon fiber composites. Fabric bending, picture frame testing, and bias-extension evaluations were carried out to determine the material parameters for these fabrics. The PAM-FORM computer program was used to model the draping behavior of these fabrics. Following deformation, fiber angle changes at different locations on the truncated pyramid were measured experimentally. The predicted angles matched the experimental results well as measured along the centerline and at several different locations on the deformed fabric. Details of the test methods used as well as the numerical results with various simulation parameters will be provided.

42 ENGINEERING↗

Conceptual design and optimization for JET water detritiation system cryo-distillation facility

The aim of the Exhaust Detritiation System (EDS) of the JET Active Gas Handling System (AGHS) is to convert all Q-based species (Q{sub 2}, Q-hydrocarbons) into Q{sub 2}O (Q being indifferently H, D or T) which is then trapped on molecular sieve beds (MSB). Regenerating the saturated MSBs leads to the production of tritiated water which is stored in Briggs drums. An alternative disposal solution to offsite shipping, is to process the tritiated water onsite via the implementation of a Water Detritiation System (WDS) based, in part, on the combination of an electrolyser and a cryo-distillation (CD) facility. The CD system will separate a Q{sub 2} mixture into a de-tritiated hydrogen stream for safe release and a tritiated stream for further processing on existing AGHS subsystems. A sensitivity study of the Souers' model using the simulation program ProSimPlus (edited by ProSim S.A.) has then been undertaken in order to perform an optimised dimensioning of the cryo-distillation system in terms of available cooling technologies, cost of investment, cost of operations, process performance and safety. (authors)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Study of the Pygmy Dipole Resonance via ($d,p$) reactions

The low-lying E1 strength below, around, and partially above the neutron-separation threshold, S n , is often referred to as Pygmy Dipole Resonance (PDR). At the moment, it is not clear whether the PDR is a collective excitation mode and whether it is a general feature of the γ-ray strength function, which needs to be answered to reliably calculate capture rates for nucleosynthesis processes when using statistical Hauser-Feshbach approaches. To further understand the microscopic origin of the PDR and possible cancellation effects between isovector E1 matrix elements, which appear to be strongly model-dependant, an experimental program studying the neutron one-particle-one-hole (1p-1h) structure of the PDR via (d, p) and (d, pγ) reactions was started. Some results of the already published work will be discussed and additional remarks, including future plans, are made.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

International land Model Benchmarking (ILAMB) Package v001.00

As a contribution to International Land Model Benchmarking (ILAMB) Project, we are providing new analysis approaches, benchmarking tools, and science leadership. The goal of ILAMB is to assess and improve the performance of land models through international cooperation and to inform the design of new measurement campaigns and field studies to reduce uncertainties associated with key biogeochemical processes and feedbacks. ILAMB is expected to be a primary analysis tool for CMIP6 and future model-data intercomparison experiments. This team has developed initial prototype benchmarking systems for ILAMB, which will be improved and extended to include ocean model metrics and diagnostics.

54 ENVIRONMENTAL SCIENCES↗

International land Model Benchmarking (ILAMB) Package v002.00

As a contribution to International Land Model Benchmarking (ILAMB) Project, we are providing new analysis approaches, benchmarking tools, and science leadership. The goal of ILAMB is to assess and improve the performance of land models through international cooperation and to inform the design of new measurement campaigns and field studies to reduce uncertainties associated with key biogeochemical processes and feedbacks. ILAMB is expected to be a primary analysis tool for CMIP6 and future model-data intercomparison experiments. This team has developed initial prototype benchmarking systems for ILAMB, which will be improved and extended to include ocean model metrics and diagnostics.

54 ENVIRONMENTAL SCIENCES↗