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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Hexagonal Geometries in MPACT

The MPACT code is a high-fidelity light-water reactor analysis code using whole-core pin-resolved neutron transport calculations on modern parallel-computing hardware. MPACT uses the 2D/1D method to solve 3D neutron transport problems by decomposing the problem into a stack of 2D slices, each of which is solved independently using the method of characteristics (MOC). The slices are then coupled axially using the P3 nodal expansion method (NEM-P3) for the 1D axial calculations. MPACT also employs the coarse mesh finite difference (CMFD) method to accelerate calculations. This manuscript details work supporting advanced reactor designs using hexagonal pins and hexagonal assemblies such as the VVER-1000. If performed correctly, MOC is geometry agnostic. However, MPACT previously had optimizations in place for Cartesian geometries, specifically in the modularization and current calculations. Sections 2 and 3 detail the changes made to MPACT to support MOC and CMFD calculations on hexagonal geometries. Section 4 reports results demonstrating solution consistency for problems run with and without CMFD acceleration, results demonstrating solution consistency when run in serial and parallel, and pincell results using the Monte Carlo code, McCard’s benchmark results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Assessment of verification and validation status - RELAP5-3D and RAVEN

The United States nuclear industry is facing a strong challenge to ensure maximum safety while enhancing economic benefit. Safety is a key parameter to all aspects related to light water reactor (LWR) nuclear power plants (NPPs), especially cost savings. Since the goal is to extend the lifetimes of these NPPs, the traditional deterministic safety concept may not guarantee a current economic asset. The Light Water Reactor Sustainability (LWRS) Program has been promoting a wide range of research and development (R&D) in this field to maximize the safety, economics, and performance of these NPPs through improved scientific understanding. One of the best practices to achieve this goal is to identify and optimize safety margins, which can lead to cost reduction. To do this, under the LWRS framework, the Risk-Informed Systems Analysis (RISA) Pathway will focus on the optimization of safety margin and minimization of uncertainties to ensure both safety and economics at the highest level. The RISA Pathway will provide enhanced capabilities for analyzing and characterizing LWR systems performance by developing and demonstrating methods, tools, and data to enable risk-informed margins management (RIMM). The goals of the RISA Pathway are twofold: (1) deploy the risk-informed tools and methods that enable better representation of safety margins and factors that contribute to cost and safety; and (2) conduct advanced risk assessment applications with industry to support margin management strategies that enable more cost-effective plant operation. The tools and methods provided by the RISA Pathway will support effective margin management for both active and passive safety systems, structures, and components (SSC) of an NPP. The tools and methods used in the RISA Pathway should have high confidence and highest technical maturity for and implementation to industry at its current setting. They should also have a capability to support risk-informed decision making for both probabilistic and deterministic elements of safety. The RISA Pathway will, therefore, perform a comprehensive assessment of verification and validation (V&V) status of RISA Toolkit to enhance credibility RISA Toolkit which be used by industry. This report summarizes assessment technical maturity of RISA thermal-hydraulics accident analysis code RELAP5-3D and multi-purpose probabilistic risk analysis tool RAVEN V&V status including specific information of the tool such as capability and features, quality assurance program, developer/independent V&V record, separation/integral tests history, user documents, and feedback.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

SAM Code Validation using the Compact Integral Effects Test (CIET) Experimental Data

The primary objective of this study is to validate the system analysis code, SAM, using experimental data from the Compact Integral Effects Test (CIET) facility. The System Analysis Module (SAM) is an advanced and modern system analysis tool being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. Originally aiming at supporting sodium fast reactor (SFR) design, it is now extended to cover other non-light water reactor (non-LWR) concepts, such as high-temperature gas-cooled reactor (HTGR) designs, molten salt-fueled, and molten salt-cooled reactor designs. To support SAM code development for the wide range of non-LWR applications, it is of paramount importance to validate the code against experiments relevant to these reactor concepts. The Compact Integral Effects Test (CIET) facility, which was designed to reproduce the thermal-hydraulics response of fluoride salt-cooled high-temperature reactors (FHR) under both forced- and natural-circulation conditions, has been identified and selected as one of benchmark test facilities for SAM code validation. Among available CIET experiments, three sets of them with distinctive characteristics were selected for SAM code validation purpose. The three sets experiments are: 1) Power step change transient tests; 2) DHX-DRACS natural circulation tests; and 3) heater frequency response tests. For all tests, steady-state or transient, SAM-predicted results show very good agreement with experimental data. The successful validation of SAM against these selected CIET experiments demonstrates that the computer code is well suited for thermal-hydraulics analysis of FHR designs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Safety Risk Reliability Model Library

SR2ML is a software package which contains a set of safety and reliability models designed to be interfaced with the INL developed RAVEN code. These models can be employed to perform both static and dynamic system risk analysis and determine risk importance of specific elements of the considered system. Two classes of reliability models have been developed; the first class includes all classical reliability models (Fault-Trees, Event-Trees, Markov models and Reliability Block Diagrams) which have been extended to deal not only with Boolean logic values but also time dependent values. The second class includes several components aging models. Models of these two classes are designed to be included in a RAVEN ensemble model to perform time dependent system reliability analysis (dynamic analysis). Similarly, these models can be interfaced with system analysis codes to determine failure time of systems and evaluate accident progression (static analysis).

Wang, Congjian↗
DOE OSTI2023

Model Energy Codes End-Use Opportunity Analysis

Model energy codes (ASHRAE Standard 90.1 and IECC) has significantly impacted programs and policies aimed at improving energy efficiency both in United States and across the globe. Standard 90.1, first published in 1975 (originally referred to as Standard 90) provides minimum energy efficiency guidelines for designing, constructing, operating, and maintaining new construction and renovated buildings. It is updated continuously, with new editions published every 3 years. Pacific Northwest National Laboratory (PNNL) conducts simulated energy and cost savings analysis of model energy codes to determine their expected impact and to track progress toward net-zero goals and efficiency targets. Additionally, the simulation outputs are examined to assess how energy is used across primary systems within prominent U.S. commercial building types to understand how energy is used in each building type at the end-use level and to identify areas for improvements in future code cycles. This end-use opportunity analysis of model energy codes provides ASHRAE technical committees and other interested parties a better understanding of how the Standard affects various building systems and end uses, specifically, those in the Standard that most prominently influence energy efficiency. Additionally, findings provide industry stakeholders guidance in identifying building types and end-uses with the most potential for energy efficiency improvements through energy codes and those that may require beyond code measures to meet energy use reduction targets. This paper summarizes features and functionalities of a webtool created by PNNL to explore and visualize the End-Use opportunity analysis.

ASHRAE 90.1, Energy Codes, Tableau↗
DOE OSTI2021

SCALE 6.2.4 Validation for Light Water Reactor Decay Heat Analysis

Energy release from the decay of radionuclides in nuclear fuel after its discharge from reactor is a critical parameter for design, safety, and licensing analyses of used nuclear fuel storage, transportation, and repository systems. Well-validated computational tools and nuclear data are essential for decay heat prediction. This paper summarizes the validation of the SCALE nuclear analysis code system version 6.2.4, used with ENDF/B-VII.1 libraries, for decay heat analysis of light water reactor used fuel. The experimental data used for validation include full-assembly decay heat measurements that cover assembly burnups of 5 to 51 GWd/tonne U, cooling times after discharge in the 2- to 27-year range, and initial fuel enrichments up to 4 wt% 235U. The comparison between calculated (C) and experimental (E) decay heat showed very good agreement, with an average C/E over all considered measurements of 1.006 (σ = 0.016) for pressurized water reactor and 0.984 (σ = 0.077) for boiling water reactor assembly measurements. The effect of using assembly-average versus axially varying modeling data on the calculated decay heat, important to thermal analyses for used fuel transportation and storage systems, is discussed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Isotopic Analysis using FRAM [Slides]

FRAM is an isotopic analysis code nominally designed for plutonium and uranium. It stands for Fixed-energy Response-function Analysis with Multiple efficiencies. It has self-calibration using several gamma-ray peaks and can analyze gamma ray data from 30keV to >1MeV of HPGe, CdTe, or LaBr3 detector. The key difference between the MGA family of codes (from LLNL) and FRAM is the use of user-editable analysis parameters in the latter.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

FY17 Status Report on NEAMS Neutronics Activities

Under the U.S. DOE NEAMS program, the high-fidelity neutronics code system has been developed to support the multiphysics modeling and simulation capability named SHARP. The neutronics code system includes the high-fidelity neutronics code PROTEUS, the cross section library and preprocessing tools, the multigroup cross section generation code MC2-3, the in-house meshing generation tool, the perturbation and sensitivity analysis code PERSENT, and post-processing tools. The main objectives of the NEAMS neutronics activities in FY17 are to continue development of an advanced nodal solver in PROTEUS for use in nuclear reactor design and analysis projects, implement a simplified sub-channel based thermal-hydraulic (T/H) capability into PROTEUS to efficiently compute the thermal feedback, improve the performance of PROTEUS-MOCEX using numerical acceleration and code optimization, improve the cross section generation tools including MC2-3, and continue to perform verification and validation tests for PROTEUS.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Code Benchmark of the HTTF Pressurized Conduction Cooldown Test Using SAM

The High Temperature Test Facility (HTTF) at Oregon State University is an integral system test facility to simulate postulated reactor transients of prismatic high-temperature gas-cooled reactors(HTGRs). A series of test campaigns was launched, providing abundant test data that could be used to benchmark reactor system analysis codes like the System Analysis Module (SAM). In this study, a SAM model of the facility is developed based on the two-dimensional (2D) ring model approach. All components including the ceramic matrix, graphite heaters, helium coolant channels, core barrel, upcomer, pressure vessel, and reactor cavity cooling system are modeled as concentric cylindrical rings. The model is used to simulate one of the benchmark problems-Pressurized Conduction Cooldown (PCC)-within the scope of the Organisation for Economic Co-operation and Development Nuclear Energy Agency International HTTF Benchmark. The simulations consist of two parts. In the first part, operating and boundary conditions as well as thermophysical properties of materials are specified for the benchmark problem. In this work, results from the first part will be used in code-to-code comparison. In the second part, the SAM model is used to simulate Test PG-27, which is the first PCC test carried out in the HTTF, with only two of the ten heater banks activated. The results in the second part are used for code-to-data comparison. Because the helium coolant flow rate is not measured in this facility, it is estimated using the input power and inlet/outlet coolant temperatures. Additionally, radial heat flow in the ceramic blocks is complicated by hundreds of cylindrical coolant channels and heater rods embedded in them. As such, it is necessary to deduce an effective thermal conductivity for the ceramic to analyze the core thermal behavior. SAM predictions of the helium coolant and ceramic temperatures are compared with test data measured in three equivalent sectors. Overall, the SAM results agree reasonably well with test data within the variation of data among the three sectors, which demonstrates SAM's capability in capturing transient effects in HTGR using the simplified 2D ring model.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

GPU-Based Static Data-Flow Analysis for Fast and Scalable Android App Vetting

Many popular vetting tools for Android applications use static code analysis techniques. In particular, Interprocedural Data-Flow Graph (IDFG) construction is the computation at the core of Android static data-flow analysis and consumes most of the analysis time. Many analysis tools use a worklist algorithm, an iterative fixed-point approach, to construct the IDFG. In this paper, we observe that a straightforward GPU parallelization of the worklist algorithm leads to significant underutilization of the GPU resources. We identify four performance bottlenecks, namely, frequent dynamic memory allocations, high branch divergence, workload imbalance, and irregular memory access patterns. Accordingly, we propose GDroid, a GPU-based worklist algorithm implementation with multiple fine-grained optimizations tailored to common characteristics of Android applications. The optimizations considered are: matrix-based data structure, memory access-based node grouping, and worklist merging. Our experimental evaluation, performed on 1000 Android applications, shows that the proposed optimizations are beneficial to performance, and GDroid can achieve up to 128X speedups against a plain GPU implementation.

Android security↗
DOE OSTI2020

Data for Robust Paths to Net Greenhouse Gas Mitigation and Negative Emissions via Advanced Biofuels

This zip file contains a UNIX-format DayCent model executable, input files, automation code, and associated directory structure necessary to re-produce the DayCent analysis underlying the manuscript. The main script “autodaycent.py” (written for Python 2.7) opens an interactive command line routine that facilitates: Calibrating the DayCent pine growth model; Initializing DayCent for a set of case studies sites; Executing an ensemble of model runs representing case study site reforestation, grassland restoration, or conversion to switchgrass cultivation; and Results analysis & generation of manuscript Fig. 3. Note that the interactive analysis code requires that all input files to be contained in the directory structure as uploaded, without modification. Executable versions of the DayCent model compatible with other operating systems are available upon request.

Feedstock Production↗
DOE OSTI2023

SOFE2023 Presentation: "Tritium Safety and Sensitivity Analysis of Tritium Extraction eXperiment (TEX) PbLi Loop Using MELCOR-TMAP"

The efficient extraction of tritium from the breeder blanket (BB) in a fusion reactor is vital for maintaining the tritium economy for a sustainable and self-sufficient fusion power plant. The vacuum permeator (VP) design is one of several promising technology platforms for extracting tritium from the BB with the advantages of being capable of operating continuously at high temperatures with the aim of achieving high tritium extraction efficiencies. The Tritium Extraction eXperiment (TEX), under construction at the Safety and Tritium Applied Research (STAR) Facility at Idaho National Laboratory (INL), is designed to test the viability of VP technology by introducing atomic hydrogen (H, D, and T) from a source permeator (SP) into a forced convection lead lithium eutectic (PbLi) loop and determining the hydrogen extraction rates from the vanadium VP. Presented here is a computational analysis of the hydrogen inventory and permeation behavior in TEX using the hydrogen transport and accident analysis code MELCOR-TMAP developed at INL. The results of a sensitivity analysis based on MELCOR-TMAP simulations of hydrogen extraction efficiencies from the TEX test section using varying PbLi flow rates, hydrogen source rates from the SP, and material property uncertainties are also reported. Operation scenarios for TEX in consideration of the analyses based on results from MELCOR-TMAP are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Methods for a blind analysis of isobar data collected by the STAR collaboration

In 2018, the STAR collaboration collected data from $_{44}^{96}{\mathrm{Ru}}+_{44}^{96}{\mathrm{Ru}}$ and $_{40}^{96}{\mathrm{Zr}}+_{40}^{96}{\mathrm{Zr}}$ at $\sqrt{s_\text {NN}}=200$ GeV to search for the presence of the chiral magnetic effect in collisions of nuclei. The isobar collision species alternated frequently between $_{44}^{96}{\mathrm{Ru}}+_{44}^{96}{\mathrm{Ru}}$ and $_{40}^{96}{\mathrm{Zr}}+_{40}^{96}{\mathrm{Zr}}$ . In order to conduct blind analyses of studies related to the chiral magnetic effect in these isobar data, STAR developed a three-step blind analysis procedure. Analysts are initially provided a “reference sample” of data, comprised of a mix of events from the two species, the order of which respects time-dependent changes in run conditions. After tuning analysis codes and performing time-dependent quality assurance on the reference sample, analysts are provided a species-blind sample suitable for calculating efficiencies and corrections for individual $\approx 30$-min data-taking runs. For this sample, species-specific information is disguised, but individual output files contain data from a single isobar species. Only run-by-run corrections and code alteration subsequent to these corrections are allowed at this stage. Following these modifications, the “frozen” code is passed over the fully un-blind data, completing the blind analysis. As a check of the feasibility of the blind analysis procedure, analysts completed a “mock data challenge,” analyzing data from Au + Au collisions at $\sqrt{s_\text {NN}}=27$ GeV, collected in 2018. The Au + Au data were prepared in the same manner intended for the isobar blind data. Finally, the details of the blind analysis procedure and results from the mock data challenge are presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Decaf: Decoupled Dataflows for In Situ High-Performance Workflows

Decaf is a dataflow system for the parallel communication of coupled tasks in an HPC workflow. The dataflow can perform arbitrary data transformations ranging from simply forwarding data to complex data redistribution. Decaf does this by allowing the user to allocate resources and execute custom code in the dataflow. All communication through the dataflow is efficient parallel message passing over MPI. The runtime for calling tasks is entirely message-driven; Decaf executes a task when all messages for the task have been received. Such a messagedriven runtime allows cyclic task dependencies in the workflow graph, for example, to enact computational steering based on the result of downstream tasks. Decaf includes a simple Python API for describing the workflow graph. This allows Decaf to stand alone as a complete workflow system, but Decaf can also be used as the dataflow layer by one or more other workflow systems to form a heterogeneous task-based computing environment. In one experiment, we couple a molecular dynamics code with a visualization tool using the FlowVR and Damaris workflow systems and Decaf for the dataflow. In another experiment, we test the coupling of a cosmology code with Voronoi tessellation and density estimation codes using MPI for the simulation, the DIY programming model for the two analysis codes, and Decaf for the dataflow. Such workflows consisting of heterogeneous software infrastructures exist because components are developed separately with different programming models and runtimes, and this is the first time that such heterogeneous coupling of diverse components was demonstrated in situ on HPC systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Comparative Study of Layer Heating and Continuous Heating Methods on Prediction Accuracy of Residual Stresses in Selective Laser Melted Tube Samples

Thermal distortion and residual stresses are two important factors that affect the quality and reliability of steel parts manufactured by laser powder bed fusion (LPBF) processes. A cost-effective model for evaluation of those heat effects is needed to refine the manufacturing process and provides insights into the product design and heat treatment. In this study, the layer heating method and sophisticated track-layer scanning method were applied to simulate the thermo-mechanical response of IN625 tube parts built by LPBF. Based on the similarity of temperature field in each layer deposit, a swept mesh was constructed to perform the thermal analysis for top layer, with the rest of layers referring to the temperature by node number offsetting. A novel explicit finite element analysis code accelerated by graphics processing unit was used for the massive-element numerical analysis. The computational accuracy and efficiency of the layer heating and track-layer scanning methods were compared in detail. It is shown that layer heating method can efficiently capture the pattern of stress distribution with reasonable accuracy in stress magnitude. The grouped track-layer scanning method can predict the residual stress and strain more accurately at a higher cost (5 ~ 10×). The elastic strain distribution was compared with the measurement by X-ray diffraction, confirming the accuracy of residual stress prediction.

36 MATERIALS SCIENCE↗
DOE OSTI2016

The Nuclear Energy Knowledge and Validation Center Summary of Activities Conducted in FY16

The Nuclear Energy Knowledge and Validation Center (NEKVaC) is a new initiative by the Department of Energy (DOE) and Idaho National Laboratory (INL) to coordinate and focus the resources and expertise that exist with the DOE toward solving issues in modern nuclear code validation and knowledge management. In time, code owners, users, and developers will view the NEKVaC as a partner and essential resource for acquiring the best practices and latest techniques for validating codes, providing guidance in planning and executing experiments, facilitating access to and maximizing the usefulness of existing data, and preserving knowledge for continual use by nuclear professionals and organizations for their own validation needs. The scope of the NEKVaC covers many interrelated activities that will need to be cultivated carefully in the near term and managed properly once the NEKVaC is fully functional. Three areas comprise the principal mission: (1) identify and prioritize projects that extend the field of validation science and its application to modern codes, (2) develop and disseminate best practices and guidelines for high-fidelity multiphysics/multiscale analysis code development and associated experiment design, and (3) define protocols for data acquisition and knowledge preservation and provide a portal for access to databases currently scattered among numerous organizations. These mission areas, while each having a unique focus, are interdependent and complementary. Likewise, all activities supported by the NEKVaC, both near term and long term, must possess elements supporting all three areas. This cross cutting nature is essential to ensuring that activities and supporting personnel do not become “stove piped” (i.e., focused a specific function that the activity itself becomes the objective rather than achieving the larger vision). This report begins with a description of the mission areas; specifically, the role played by each major committee and the types of activities for which they are responsible. It then lists and describes the proposed near term tasks upon which future efforts can build.

##CAI suggestions##↗
DOE OSTI2017

Using Whisper-1.1 to Guide Improvements to Nuclear Data Evaluations

Along with the latest release of the general purpose Monte Carlo radiation transport code, MCNP6.2, came the first officially released version of Whisper, version 1.1, a statistical analysis code used for nuclear criticality safety (NCS) validation. The Whisper software package is primarily used to calculate the upper subcritical limit (USL) of a particular application case along with components of the margin of subcriticality (MOS). In the calculation of the MOS due to nuclear data uncertainties, Whisper uses the generalized linear-least-squares (GLLS) approach to obtain adjusted nuclear data uncertainties which are then propagated to estimate the nuclear data uncertainties in the k eff of the application. Due to the fact that Whisper contains the simulated and measured k eff values for over 1100 benchmarks, nuclear data sensitivity profiles for each benchmark along with the nuclear data covariance matrices, all of which are used in the GLLS method, it is possible to easily utilize these data available to help guide improvements to nuclear data evaluations. In the present work, the Whisper data and the GLLS method are used together to suggest an adjusted nuclear data cross section evaluation specifically for 233 U such that the agreement between the calculated and experimental k eff measurements of the relevant benchmarks are improved. With this adjusted nuclear data available, feedback to the theoretical and experimental nuclear data community is provided.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Using Whisper-1.1 to guide improvements to nuclear data evaluations

Along with the latest release of the general purpose Monte Carlo radiation transport code, MCNP6.2, came the first officially released version of Whisper, version 1.1, a statistical analysis code used for nuclear criticality safety (NCS) validation. The Whisper software package is primarily used to calculate the upper subcritical limit (USL) of a particular application case along with components of the margin of subcriticality (MOS). In the calculation of the MOS due to nuclear data uncertainties, Whisper uses the generalized linear-least-squares (GLLS) approach to obtain adjusted nuclear data uncertainties which are then propagated to estimate the nuclear data uncertainties in the k{sub eff} of the application. Due to the fact that Whisper contains the simulated and measured k{sub eff} values for over 1100 benchmarks, nuclear data sensitivity profiles for each benchmark along with the nuclear data covariance matrices, all of which are used in the GLLS method, it is possible to easily utilize these data available to help guide improvements to nuclear data evaluations. In the present work, the Whisper data and the GLLS method are used together to suggest an adjusted nuclear data cross section evaluation specifically for {sup 233}U such that the agreement between the calculated and experimental k{sub eff} measurements of the relevant benchmarks are improved. With this adjusted nuclear data available, feedback to the theoretical and experimental nuclear data community is provided. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗