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At least 811 records · Page 45

Demonstration of Bison/TRACE Coupling (CRAB) Through Validation Case LOFT L2-5

The postulated pressurized water reactor (PWR) accident known as a large-break loss of coolant accident (LOCA) is still of great concern to the current nuclear reactor fleet. Research through experiments, modeling, and simulation is active in the field of LOCAs and new modeling tools are under continuous development. The BISON fuel performance code, developed at the Idaho National Laboratory (INL), is one such tool that has been very active in the development of models and the simulation of accidents. With recent model developments, Bison has been used to simulate LOCA cladding burst experiments and full integral LOCA experiments with favorable results. Bison is a thermomechanical code that must be fed boundary conditions (BC) for phenomena occurring outside of the fuel rod. These BCs include moderator or outer cladding temperature, coolant pressure, and rod linear power or neutron flux. These BCs can be supplied from a function or, preferably, another coupled code. Bison is built on the Multiphysics Object Oriented Simulation Environment (MOOSE) framework which allows for ease of code coupling. A framework is currently in place that allows codes external to MOOSE to communicate with MOOSE applications as if they were a MOOSE application. Through a recent MOOSE/BISON development, with collaboration from the U.S. Nuclear Regulatory Commission (NRC), BISON has been coupled with the NRC system code TRAC/RELAP Advanced Computational Engine (TRACE). Simulation results of the initial validation loss of flow test (LOFT) L2-5 case from this research will be presented.

42 ENGINEERING↗

UPDATES FROM THE INVOLUTE WORKING GROUP

The HFIR, RHF, and FRM II reactors represent a particular class of Research and Test Reactors that provide some of the most intense and continuous neutron fluxes for science, industry, and medical applications. These high-performance reactors have achieved compact cores by operating with Highly Enriched Uranium fuel (HEU, 235U/U ≥ 20 wt. %) and utilizing fuel plates curved as an involute. Due to the proliferation risks, the international community aims to reduce or eliminate, when possible, the use of HEU fuel in civilian facilities by converting them to a Low-Enriched Uranium fuel (LEU, 235U/U < 20 wt. %). Conversion of these reactors without significantly compromising their performance or safety is a challenging endeavor that can tremendously benefit from advanced computational tools and thus, eliminate unnecessary conservatism to ensure sufficient thermal margins. Therefore, models are being developed using modern Computational Fluid Dynamics (CFD) and Computational Structural Mechanics (CSM) software to evaluate the steady-state safety margins of various LEU designs instead of being reliant on the more traditional, conservative methods. To gain the confidence and acceptance of high-fidelity modeling by the nuclear regulators, Argonne National Laboratory (ANL) and the involute reactors have formed an informal scientific group, the Involute Working Group (IWG). The IWG facilitates inter-organizational collaboration on experimental benchmarking, code-to-code comparisons, and Verification and Validation (V&V). This paper describes some of the recent IWG efforts in validating software against the existing experimental data, as well as code-to-code comparisons of different software used by the IWG members.

Bergeron, Aurelien↗

NREL Stratus - Enabling Workflows to Fuse Data Streams, Modeling, Simulation, and Machine Learning

Integrating cloud services into advanced computing facilities provides significant new capabilities over focusing solely on traditional high performance computing (HPC) workloads. This brings complementary capabilities as well as enabling new focused roles for HPC. They are especially potent for workflows that fuse data streams, modeling and simulation ('modsim') and machine learning. A key challenge to adopting a hybrid edge-cloud-HPC model is to align optimal capability, data, and user intent on the right resources for each step in a workflow.?The NREL Stratus service provides a basis for this: Stratus layers capabilities needed to make?cloud services accessible to a lab-based scientific community on commercial offerings, and; currently supports upwards of 200 projects ranging from IOT integration to traditional modeling and simulation. This provides a real-world inventory of scientific workflow elements. A growing knowledge base enables placing these elements appropriately between the edge, cloud, and traditional HPC. This paper outlines a vision via reference architecture and the application of that architecture in a typical workflow highlighting multiple components: sensor data intake, cleaning and transforming (edge/cloud suitable); generation of synthetic data through modsim, computationally heavy ML training and hyperparameter optimization (HPC suitable), and; inference and deployment (cloud ideal). Every step in such a workflow involves a cost-benefit analysis regarding the data movement, computational efficiency, availability, latency, and resource capabilities. The reference architecture and examples outlined allow for understanding new opportunities in the context of emerging workflows that combine IOT, cloud, and HPC to bolster scientific productivity.

AI↗

28 NREL Stratus - Enabling Workflows to Fuse Data Streams, Modeling, Simulation, and Machine Learning: Preprint

Integrating cloud services into advanced computing facilities provides significant new capabilities over focusing solely on traditional high performance computing (HPC) workloads. This brings complementary capabilities as well as enabling new focused roles for HPC. They are especially potent for workflows that fuse data streams, modeling and simulation ('modsim') and machine learning. A key challenge to adopting a hybrid edge-cloud-HPC model is to align optimal capability, data, and user intent on the right resources for each step in a workflow.?The NREL Stratus service provides a basis for this: Stratus layers capabilities needed to make?cloud services accessible to a lab-based scientific community on commercial offerings, and; currently supports upwards of 200 projects ranging from IOT integration to traditional modeling and simulation. This provides a real-world inventory of scientific workflow elements. A growing knowledge base enables placing these elements appropriately between the edge, cloud, and traditional HPC. This paper outlines a vision via reference architecture and the application of that architecture in a typical workflow highlighting multiple components: sensor data intake, cleaning and transforming (edge/cloud suitable); generation of synthetic data through modsim, computationally heavy ML training and hyperparameter optimization (HPC suitable), and; inference and deployment (cloud ideal). Every step in such a workflow involves a cost-benefit analysis regarding the data movement, computational efficiency, availability, latency, and resource capabilities. The reference architecture and examples outlined allow for understanding new opportunities in the context of emerging workflows that combine IOT, cloud, and HPC to bolster scientific productivity.

AI↗

Next-generation system analysis model for studying alternative Waste Management Systems - 15232

The U.S. Department of Energy's Office of Nuclear Energy (DOE-NE) is conducting planning activities within the Nuclear Fuels Storage and Transportation Planning Project (NFST). The plans involve (1) laying the groundwork for implementing interim storage (including dealing with any associated transportation that is needed) per the Administration's Strategy for the Management and Disposal of Used Nuclear Fuel and High-Level Radioactive Waste of January 2013 and (2) developing a foundation for a new nuclear waste management organization. An overarching goal is to develop options for designing an integrated system that will be considered by decision-makers. Based on the dynamic system analysis and software specification requirements that must be met, Argonne National Laboratory (Argonne) is leading the development of a consolidated waste management system tool known as the Next-Generation System Analysis Model (NGSAM). The development of NGSAM leverages the approaches and methods used previously to develop the Transportation Storage Logistics (TSL) and Total System Model (TSM) system analysis tools, but the new tool takes advantage of advanced computational capabilities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Effective Long-term Monitoring Strategies by Integrating Reactive Transport Models with In situ Geochemical Measurements - 16212

Long-term monitoring of contaminant transport in groundwater is expected to account for a large fraction of future life-cycle cleanup costs at the DOE sites. The Attenuation-Based Remedies in the Subsurface Applied Field Research Initiative (ABRS AFRI) is developing an innovative approach for cost-effective in situ long-term monitoring. The approach is based on strategically adding the measurements of controlling variables (such as pH, redox potential, electrical conductivity, and groundwater level), which control the plume mobility and its spatial and temporal distribution. In situ measurements of these variables - supplemented with a reduced number of standard periodic groundwater samples - are expected to lead to more cost-effective monitoring, and can also serve as an early warning system for detecting unexpected plume migration. The objective of this study is to support the development of such a long-term monitoring approach through the application of advanced computational methods, including (1) statistical data mining and analysis, and (2) three-dimensional flow and reactive chemical transport modeling. We have performed the statistical data analysis of historical and current monitoring data at the Savannah River Site (SRS) F-Area to quantify the correlations between the controlling variables and radioactive contaminant concentrations. In parallel, we have used 3D modeling of flow and contaminant transport to provide the prediction of the contaminant plume evolution. The results of both data analysis and modeling confirmed that the correlations between controlling variables and contaminant concentrations are significant. Modeling results also suggest that the correlation parameters will change in the future, which is important to assess the long-term efficacy of the proposed monitoring approach. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Assessment of boric acid accumulation in a reactor core blocked by debris

To examine the potential for boron precipitation in the core during sump recirculation when latent debris has formed a blockage at the core inlet, TRACE simulations of long term cooling following a loss-of-coolant accident (LOCA) in a Westinghouse four loop pressurized water reactor (PWR) were performed. The TRAC/RELAP Advanced Computational Engine (TRACE) was modified to account for the higher fluid densities and viscosities that occur when the coolant contains boric acid. Previous versions of TRACE calculated the transport of boron in the RCS, but assumed coolant properties to be the same as pure water. This was appropriate for very low concentrations of boric acid, but not when the concentrations approach those where precipitation is possible. These modifications allow TRACE to simulate natural circulation caused by a concentration difference in addition to the buoyancy induced by temperature differences. The results of the TRACE calculations suggest that there is margin to boric acid precipitation during long term cooling following a large break LOCA even if debris significantly affects flow at the core inlet. Significant blockages at either the lower core plate or bottom fuel nozzles did not result in boric acid concentrations likely to cause precipitation in the core. The calculations do show that precipitation can occur in the upper head where coolant can become trapped and in the steam generators where entrained fluid can evaporate and deposit the boron carried by the droplets. Of particular importance, is that the boric acid concentration and coolant temperature in the lower plenum and regions near debris blockage remained well below precipitation levels supporting a conclusion that precipitation is not likely to make the blockage more severe. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Validation Study in SAS4A Code in Simulated Mild TOP Condition

Model improvements and validation efforts for SAS4A code, which is the most advanced computer code for simulating the the primary phase of the Core Disruptive Accident (CDA) of MOX-fueled Sodium-cooled Fast Reactors, have been performed utilizing the experimental data from the CABRI programs by JAEA (Japan Atomic Energy Agency), IRSN (Institut de Radioprotection et de Surete Nucleaire), CEA (Commissariat a l'Energie Atomique et aux Energies Alternatives) and KIT (Karlsruhe Institute of Technology). In order to confirm validity of improved models of SAS4A, a systematic and comprehensive validation plan was defined. It was based on the PIRT (Phenomena Identification and Ranking Table) result for CDA of MOX-fueled fast reactors. The fuel failure position and time are the most important parameters, which dominate the analytical results in a reactor calculation. The failure position will affect the reactivity feedback due to the fuel distribution after failure and consequently would have an effect on the energy release in the initiating phase. This paper describes the preliminary result of validation study for SAS4A code in simulated Transient Over-Power (TOP) condition. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NUCLEI (SciDAC-4) effort at The University of Tennessee, Knoxville

This Report summarizes the accomplishments of NUCLEI researchers at The University of Tennessee, Knoxville (UTK) and those supported via subcontracts at the University of North Carolina at Chapel Hill (UNC) and Iowa State University (ISU). The SciDAC-4 NUCLEI collaboration had the goal to advance the computation of atomic nuclei and to make reliable predictions including uncertainty estimates for observables of interest. These goals were achieved by developing improved nuclear interactions and currents that are input to the computations, and by advancing the algorithms and techniques used for computing nuclear observables of interest. The computed results advanced our understanding of how nuclei work; they helped to guide and interpret experiments at existing low-energy nuclear physics facilities, the Facility for Rare Isotope Beams, Jefferson Laboratory, and neutrino experiments. In addition, predictions were made that await confrontation with experimental results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

GASP Advancements With Symbolic Computations, Optimization, and Decoupled Numerical Methods

NASA is exploring advancements in hybrid-electric propulsion concepts for aircraft design. A new analysis capability has been deployed at NASA’s Ames Research Center using a new mathematical modeling framework in Python that leverages symbolic representation of mathematical expressions, optimization-based problem formulations, and standalone numerical methods. This capability, called Gascon, has been verified against NASA’s General Aviation Synthesis Program (GASP) results for several vehicles that exercise the analysis capability for a variety of aircraft classes and engine models, including both turbofans and turboprops. We believe this capability will set the stage for more rapid development of novel aircraft models with more flexible design assessments using optimization, and more traceable analysis for reproducibility. Additionally, a novel Pareto optimization-based design space exploration that shows the trade between range flown and fuel burn by manipulating the thrust split during cruise for a true parallel hybrid aircraft was developed by leveraging the unique features of Gascon.

aircraft design↗

Advanced Simulation and Computing (ASC) Software Quality Plan: ASC Software Quality Engineering Practices (V.4.0)

The purpose of the Sandia National Laboratories (SNL) Advanced Simulation and Computing (ASC) Software Quality Plan is to clearly identify the software quality engineering practices that are the basis for continually improving the quality of ASC software products. This plan defines the SNL ASC Program software quality engineering practices and provides a mapping of these practices to Laboratory Policy System IT008: Provide Quality Software Policy. This plan also identifies ASC Program Management and the software project teams' responsibilities in implementing quality software engineering practices and in assessing progress towards achieving their software quality goals.

97 MATHEMATICS AND COMPUTING↗

Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing

In the first week of January 2014 Dagstuhl hosted a Perspectives Workshop on “Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing”. The event brought together two previously separate communities – from Visualization and HPC Performance Analysis – to discuss a long term joined research agenda. The goal was to identify and address the challenges in using visual representations to understand and optimize the performance of extreme-scale applications running on today’s most powerful computing systems like climate modeling, combustion, material science or astro-physics simulations.

97 MATHEMATICS AND COMPUTING↗

Future Computer Requirements for Computational Aerodynamics

Recent advances in computational aerodynamics are discussed as well as motivations for and potential benefits of a National Aerodynamic Simulation Facility having the capability to solve fluid dynamic equations at speeds two to three orders of magnitude faster than presently possible with general computers. Two contracted efforts to define processor architectures for such a facility are summarized.

Source record↗

Computational aerodynamics on large computers

Three examples of advances in computational aerodynamics; (1) three-dimensional inviscid transonic analysis, (2) design calculations for wings, and (3) the computation of viscous-induced aileron buzz, are reviewed. Attention is given to wing surface pressures, design optimization, computer memory, speed and advanced solution methods on parallel computer architecture. It is determined that many implicit approximate-factorization schemes, that have been developed for Navier-Stokes equations, can be coded to run efficiently on microprocessors.

Ballhaus, W. F.↗

Advanced Simulation and Computing FY13 Implementation Plan

The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational enhancements to support these programs.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗