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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Directed Evolution Reveals the Functional Sequence Space of an Adenylation Domain Specificity Code

Nonribosomal peptides are important natural products biosynthesized by nonribosomal peptide synthetases (NRPSs). Adenylation (A) domains of NRPSs are highly specific for the substrate they recognize. This recognition is determined by 10 residues in the substrate-binding pocket, termed the specificity code. This finding led to the proposal that nonribosomal peptides could be altered by specificity code swapping. Unfortunately, this approach has proven, with few exceptions, to be unproductive; changing the specificity code typically results in broadened specificity or poor function. To enhance our understanding of A domain substrate selectivity, we carried out a detailed analysis of the specificity code from the A domain of EntF, an NRPS involved in enterobactin biosynthesis in Escherichia coli. Using directed evolution and a genetic selection, we determined which sites in the code have strict residue requirements and which are tolerant of variation. We showed that the EntF A domain, and other l-Ser-specific A domains, have a functional sequence space for l-Ser recognition, rather than a single code. This functional space is more expansive than the aggregate of all characterized l-Ser-specific A domains: we identified 152 new l-Ser specificity codes. Together, our data provide essential insights into how to overcome the barriers that prevent rational changes to A domain specificity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Liquid Hydrogen Heavy-Duty Vehicle Safety Review and Refueling Facility Design

Liquid hydrogen (LH 2 ) used as a fuel onboard a heavy-duty vehicle can result in increased storage capacity and faster refueling relative to compressed gas. However, there are concerns about hydrogen losses from boil-off, potential safety issues, gaps in codes and standards for cryogenic hydrogen fuel, and technical challenges with LH 2 systems for widespread transportation applications. A failure modes and effects analysis (FMEA), a safety codes and standards review, and a design review of the onboard liquid hydrogen system for a heavy-duty vehicle identified some of these potential safety issues and gaps in the codes and standards. The FMEA identified some medium and low risk failure points of the conceptual design, and the design review identified how carefully pressure relief needs to be considered for LH 2 systems. In addition, a conceptual design for a LH 2 refueling station was developed. Rough capital costs for the refueling station design were $\$1 million$ and the layout occupied approximately 13,000 ft 2 . These results can be used to inform future designs and analyses for LH 2 heavy-duty vehicles.

08 HYDROGEN↗
DOE OSTI2022

Modeling and Analysis of a Micro-reactor using the DireWolf Code Suite

Micro-reactors, specifically those cooled with heat pipes, are tightly coupled systems which require multi-physics tools to accurately model both steady-state and transient behavior. Idaho National Laboratory’s DireWolf code suite is tailor-built to model heat-pipe reactors. DireWolf’s ability to model the coupled steady-state behavior of a heat-pipe micro-reactor are demonstrated herein. The DireWolf modeling methodology is described, and a micro-reactor design is introduced. A full-core model is developed, and the steady-state coupled neutronics-thermal analysis is performed. Results of the analyses, including flux, power, and temperature distributions are presented and discussed. This is a Westinghouse Electric Company (WEC) led publication.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Analysis of HolosGen Sub-Scale Simulator with Plant Dynamics Code

The Subcritical Power Module Sub-scale Simulator (SPM-SS) has been designed and constructed by HolosGen LLC under the ARPA-E MEITNER program to simulate the thermal-hydraulic and heat transfer behavior of the full-scale Holos-Quad Subcritical Power Modules (SPMs). Four coupled SPMs, each rated at 5.5MW, form the Holos-Quad gas-cooled microreactor design. The SPM-SS represents a substantially scaled-down system with a power rating less than 40 kW, equipped with an electrically heated fuel cartridge heat exchanger, an electrically heated compressor heat exchanger, and a valve actuated turbine heat exchanger, in addition to a recuperator and a cooler heat exchanger. The fuel cartridge represents a portion of the full-scale SPM core, the compressor heat exchanger mimics the temperature changes resulting from the compressor’s turbomachinery inefficiencies, the turbine heat exchanger mimics the expansion process normally occurring through the turbine, while the recuperator and cooler heat exchangers complete the subscale simulator loop. The heaters equipping the fuel cartridge and the compressor heat exchangers are electronically controlled to simulate normal and off-normal SPM operating conditions. The full-scale Holos-Quad SPM design eliminates the traditional balance of plant and executes thermal-to-electric energy conversion by means of an intercooled Brayton cycle with decoupled compressor-turbine turbomachinery. The Holos-Quad full-scale design is equipped with a multi-stage axial Low- and High-Pressure compressor, and a multistage axial turbine. The SPM-SS is designed for testing and validation of selected components which are instead coupled by a traditional balance of plant. The SPMSS is not equipped with turbo-machinery (compressor and turbine) as the development of these components were excluded from the scope of work under the ARPA-E MEITNER funding program. The SPM-SS balance of plant enables modifications, replacement and testing of individual components with different working fluids and is designed to include the turbo-machinery components that will be developed in future research . The SPM-SS can be operated with different gases, variable mass-flow-rates, pressures, and temperatures to obtain test data for selected components, whose performance can be scaled to validate the computer model of the full-scale SPM at various conditions (e.g., start-up, transients conditions). The SPM-SS can operate at the maximum Holos-Quad design pressure of 7 MPa, and a maximum temperature limited to 650 °C by the electrical heaters. Several SPM-SS tests have been conducted and analyzed with the Plant Dynamics Code (PDC) developed at the Argonne National Laboratory (ANL). These tests aimed at validating the PDC modeled predictions of the full-scale Holos-Quad design with data from selected SPM-SS components. In order to address SPM-SS specific characteristics, such as components heat losses and absence of turbomachinery components, some modifications to the PDC have been implemented to factor the design differences from the full-scale Holos-Quad SPM to the SPM-SS. As the PDC offers capabilities to analyze systems with different working fluids, air, nitrogen, and helium were utilized as the SPM-SS working fluids. Air was utilized to fine-tune the SPM-SS Systems Structures and Components (SSCs), nitrogen was utilized to pressure test the SPM-SS loop at the SPMs design maximum pressure of 7MPa. Helium was utilized as the working fluid circulating through the SPM-SS SSCs for specific tests to validate the PDC predictions of the fuel cartridge heat exchanger. SPM-SS tests data were also analyzed with both the steady-state and transient analysis capabilities offered by the PDC. This report describes the PDC analysis of the SPM-SS tests data, including the necessary code modifications and comparison of the code results with the experimental data. Based on the results, a discussion is presented on how the analysis supports design and transient calculations of the full-scale Holos-Quad microreactor. Also based on the results of this work, recommendations are made for future optimizations of the SPM-SS components and PDC model development needs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

The RISMC Approach to Perform Advanced PRA Analyses

The existing fleet of nuclear power plants is in the process of extending its lifetime and increasing the power generated from these plants via power uprates. In order to evaluate the impact of these two factors on the safety of the plant, the RISMC Pathway aims to develop simulation-based tools and methods to assess risks for existing nuclear power plants in order to optimize safety. This pathway, by developing new methods, is extending the state-of-the-practice methods that have been traditionally based on logic structures such as Event-Trees and Fault-Trees. These static types of models mimic system response in an inductive and deductive way respectively, yet are restrictive in the ways they can represent spatial and temporal constructs. RISMC analyses are performed by using a combination of thermal-hydraulic codes and a stochastic analysis tool currently under development at the Idaho National Laboratory, i.e. RAVEN. This paper presents a case study in order to show the capabilities of the RISMC methodology to assess impact of power uprate of a boiling water reactor system during a station blackout accident scenario. We employ the system simulator code, RELAP5-3D, coupled with RAVEN which perform the stochastic analysis. Our analysis is in fact performed by: 1) sampling values of a set of parameters from the uncertainty space of interest, 2) simulating the system behavior for that specific set of parameter values and 3) analyzing the set of simulation runs. Results obtained give a detailed investigation of the issues associated with a plant power uprate including the effects of station blackout accident scenarios. We are able to quantify how the timing of specific events was impacted by a higher nominal reactor core power. Such safety insights can provide useful information to the decision makers to perform risk informed margins management.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Design and Optimization of a Gas-Cooled, Airfoil Fin Microchannel Heat Exchanger

High-performance microchannel heat exchangers are needed to supply heat for power conversion for nuclear microreactors. An airfoil fin microchannel design, constructed of Alloy 617 with helium as the working fluid, was analyzed and optimized using a design of experiments with artificial intelligence and machine learning techniques. The use of airfoil fins offers the potential to reduce pressure drop across the heat exchanger, as compared to other types of channel configurations. A framework for topology optimization of airfoil fin PCHEs has been developed that can be readily extended to different fin sizes and shapes, as well as different inlet and operating conditions, materials of construction, and working fluids. An optimization procedure was developed that employs computational fluid dynamics for a set of design points identified using Latin hypercube sampling. STAR-CCM+ was used to analyze a simplified two-channel configuration where five parameters were varied – inlet angle, fin scale, extent of staggering, transverse and longitudinal pitches. Two methods were compared for generating surrogate models – a 5D polynomial and a regression neural network. A response surface approximation was created from the surrogate models and input to a genetic algorithm. The genetic algorithm identified a set of optimal points on the Pareto front. The optimal geometry was found across six channel Reynolds numbers ranging from 1000 to 5000 to analyze how varying inlet conditions affects the optimal design. A set of optimal designs that maximizes heat transfer and minimizes pressure drop was identified, and a thermal stress analysis was performed on the optimal design. This work has developed a digital framework for the expedient topology design and evaluation of PCHE designs for gas-cooled microreactor applications. Correlations for the Nusselt number and Darcy friction factor were developed that can be useful for thermal hydraulic analyses using system codes. A thermal stress analysis was conducted and a brief discussion of the status of code cases of PCHEs for nuclear applications is given. Testing and thermomechanical modeling is needed to facilitate future code compliance of PCHEs for high pressure and high temperature applications.

42 ENGINEERING↗
DOE OSTI2018

Steady-State Thermal-Hydraulic Analysis and Bowing Reactivity Evaluation Methods Based on Neutron and Gamma Transport Calculations

With the advancement of computer technology, the variational nodal transport code VARIANT is now routinely used for sodium-cooled fast reactor (SFR) design analysis. In particular, VARIANT transport calculations are usually performed for whole core neutronics analyses and for fuel cycle analyses with REBUS-3. However, the steady-state thermal hydraulics analysis with the SE2-ANL coed and the assembly bowing reactivity calculation with the structural analysis with the NUBOW-3D code are still performed with the DIF3D finite difference diffusion theory code. Furthermore, the DIF3D diffusion calculation for these applications is performed with only six triangular meshes per hexagonal assembly, and the SE2-ANL code determines the pin power distributions approximately by assuming that the power distribution within an assembly is separable in the radial and axial directions. In order to overcome the limitations and to improve the accuracy of the existing methods, it was proposed to develop the relevant computational methods based on the transport calculations with the VARIANT and PROTEUS-SN codes. The objectives of this study are to develop a new heating calculation method based on the coupled neutron and gamma transport calculations with VARIANT, to implement the new heating calculation method into the SE2-ANL steady-state thermal-hydraulics analysis code with improved numerical algorithms and additional capabilities for automatic flow allocation calculations, and to develop a method to calculate bowing reactivity coefficients based on the VARIANT core solutions and the PROTEUS-SN assembly solutions, which can be used in NUBOW-3D calculations. A new, coupled neutron and gamma heating calculation procedure has been developed based on VARIANT transport calculations. In the new heating calculation procedure, the neutron flux distribution is first determined by solving an eigenvalue transport problem using the VARIANT transport code. Using the calculated neutron flux, the intra-nodal gamma source distributions are calculated to be consistent with the neutron flux distribution with the GAMSOR code. For this, the GAMSOR code has been updated to generate the intra-nodal gamma source distributions in the form of the VARSRC dataset of VARIANT. With this gamma source distribution, the gamma flux distribution is determined by solving a fixed source gamma transport problem using VARIANT again. With the neutron and gamma flux distributions, the heat generation rates are evaluated at individual fuel pins and assembly duct walls, without assuming separable axial and radial profiles for the intra-assembly power distribution.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Theory and Implementation of Nuclear Safety System Codes - Part II: System Code Closure Relations, Validation, and Limitations

This is Part II of two articles describing the details of thermal-hydraulic sys- tem codes. In this second part of the article series, the system code closure relationships (used to model thermal and mechanical non-equilibrium and the coupling of the phases) for the governing equations are discussed and evaluated. These include several thermal and hydraulic models, such as heat transfer coefficients for various flow regimes, two phase pressure correlations, two phase friction correlations, drag coefficients and interfacial models be- tween the fields. These models are often developed from experimental data. The experiment conditions should be understood to evaluate the efficacy of the closure models. Code verification and validation, including Separate Effects Tests (SETs) and Integral effects tests (IETs) is also assessed. It can be shown from the assessments that the test cases cover a significant section of the system code capabilities, but some of the more advanced reactor designs will push the limits of validation for the codes. Lastly, the limitations of the codes are discussed by considering next generation power plants, such as Small Modular Reactors (SMRs), analyz- ing not only existing nuclear power plants, but also next generation nuclear power plants. The nuclear industry is developing new, innovative reactor designs, such as Small Modular Reactors (SMRs), High-Temperature Gas-cooled Reactors (HTGRs) and others. Sub-types of these reactor designs utilize pebbles, prismatic graphite moderators, helical steam generators, in- novative fuel types, and many other design features that may not be fully analyzed by current system codes. This second part completes the series on the comparison and evaluation of the selected reactor system codes by discussing the closure relations, val- idation and limitations. These two articles indicate areas where the models can be improved to adequately address issues with new reactor design and development.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Benchmarking of Probabilistic Fracture Mechanics Models in Grizzly

In 2020, as part of contract/task order 31310019N0006/31310020F0060, the Nuclear Regulatory Commission tasked Idaho National Laboratory (INL) with benchmarking the MOOSE/GRIZZLY code against the NRC’s Fracture Analysis of Vessels - Oak Ridge (FAVOR), version 16.1 code. Both codes can predict large light-water reactor vessel integrity deterministically and probabilistically. In fact, such predictions are the primary purpose of the FAVOR code, and are a main focus of the GRIZZLY code, although GRIZZLY is capable of modeling a wider range of geometries and problems. The vessel integrity modeling capabilities of the GRIZZLY code are still under development and being gradually expanded, and the capability to model vessel fracture by crack growth has not yet been integrated into GRIZZLY (although it does exist in pre-release versions). Thus, the present benchmark study focused on comparing predictions for the conditional probability of crack growth initiation (CPI) between GRIZZLY and FAVOR v16.1. The present benchmarking study expands on a previous study completed in 2020, which focused on single plate regions, various flaw types, and full vessel studies. The previous study was limited in scope and revealed some relatively large discrepancies, particularly in the case of weld regions. In the present study, detailed investigations into the sources of discrepancies between GRIZZLY and FAVOR were performed, with a focus on weld regions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

A LOCA Analysis Tool: Coupling RELAP5-3D to BISON

Experimental evidence illustrates that at burnups slightly above the current regulatory limit of a rod-averaged burnup of 62 MWd/kgU, the ceramic UO 2 inside light-water reactor fuel rods becomes susceptible to a phenomenon known as fuel fragmentation, relocation, and dispersal (FFRD) during a loss of coolant accident (LOCA) transient. The severity of FFRD is strongly influenced by the zirconium-based (Zircaloy) cladding behavior during the LOCA transient. A Technology Commercialization Fund (TCF) project was awarded to an Electric Power Research Institute (EPRI)/Idaho National Laboratory team to create a LOCA analysis tool that couples BISON to the systems/thermal-hydraulics code RELAP5-3D [1] for analysis of LOCA scenarios. In addition, further refinements to existing BISON models were identified as necessary to more accurately represent more recent experimental evidence from the Studsvik Cladding Integrity Project (SCIP) and other experimental programs.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Opening the Door to Grid-Interactive Efficient Buildings with Energy Codes

Building codes represent standard design practice in the construction industry and must continually evolve to account for advancing technologies and innovative practices. Energy codes have historically focused on energy efficiency within buildings and across their systems. However, many of tomorrow's technologies go beyond efficiency and target increased flexibility. These demand flexibility (DF) measures can postpone or reduce building electric load based on price or other grid signals, and include smart appliances, connected lighting, and connected mechanical systems. Expanding codes to enable such grid-interactive efficient building (GEB) has the potential to influence their realization at scale, which will support renewable-energy grid-integration and building-sector decarbonization. However, considering DF measures in code development creates a new set of challenges for codes and the practices contained therein. This paper considers the role of building energy codes in enabling GEB. Specifically, it reviews the status of demand flexibility (DF) measures in current commercial building energy code. It examines the national model code development process and identifies components barring the consideration and inclusion of DF measures - including code scope, characterization and analysis of proposed new prescriptive measures, and accounting for time-of-day and geographic differences in their benefits. The paper presents findings from code development analyses that indicate the cost benefit of DF measures and the limitations associated with current code development conventions. To encourage building flexibility and improved energy resilience moving forward, recommendations are made for removing code development barriers and sanctioning DF measure consideration in future model codes.

Building Energy Codes and Standards, Grid-Interact↗
DOE OSTI2021

MOOSE Framework Meshing Enhancements to Support Reactor Analysis

MOOSE-based physics codes require an input finite element mesh on which the physics solution is calculated, reported, and transferred to other physics codes. The use of difficult-touse, external licensed software is often required to generate high quality meshes for reactor geometries. High-fidelity geometry modeling also requires elaborate tracking of groups of elements for material property assignment and output reporting which can be considerably complex for the user to identify and maintain. Under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, several meshingrelated enhancements have been developed for the MOOSE framework to address user challenges in creating finite element meshes for advanced reactor geometries. MOOSE mesh generators have been developed to mesh hexagonal geometries (pins, ducted assemblies, and cores) commonly found in liquid-metal cooled fast reactor concepts. The mesh generator used for hexagonal pin cells is generic for regular polygons and therefore may also be used for Cartesian pin cells. Hexagonal pin cells can be stitched into ducted assemblies, and assemblies can be stitched together into a core. The user may specify region ids, region names, and other preferences on the mesh. This control is useful for later material mapping in the MOOSE-based physics codes input. A capability was also developed for meshing rotating control drums including determination of material volume fractions in each mesh element as a function of time. Control drum meshes may be stitched to other hexagonal assemblies to create a core configuration. Additional mesh generators were developed that wrap around the hexagonal meshing capabilities and utilize “extra element integer” ID values on each element. In regular Cartesian or hexagonal assemblies or cores, the bookkeeping of element groups for both material assignment and output reporting can now be automated through assignment of pin, assembly, core, axial and depletion id values stored as extra element integers. The extra element tags on the mesh greatly speed the reactor analyst’s efforts to map materials to meshes, track depletion zones, and parse output such as axial pin power distributions. At the highest level, pin, assembly, and core mesh generators (with this reactor terminology) have also been developed to easily generate regular Cartesian and hexagonal cores, including axial extrusion. These reactor geometry builders call upon the previously mentioned capabilities to produce analysis-ready 3D meshes including material assignments. Open source mesh triangulation capabilities were also investigated for integration into the MOOSE framework to address the need for meshing the core periphery region which extends from the irregular outer assembly border to a cylindrical boundary. Options are limited due to licensing constraints, and the recommendation is pursue building a native MOOSE Delaunay triangulator routine with full functionality. Finally, a series of verification problems were performed with NEAMS physics tools. All developed capabilities will be available in the new open-source “Reactor” module of the MOOSE framework, which is accessible to any MOOSE-based NEAMS physics tool.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Ring Model Development and Validation for Prismatic HTGR Core Thermal-hydraulics and Safety Analysis

Because of the complex core geometry, prismatic high temperature gas-cooled reactors (prismatic HTGRs) often exhibit complex thermal fluid behaviors during both normal operating and transient conditions. Most HTGR designs rely on passive safety system for decay heat removal, such as the reactor cavity cooling system (RCCS). During postulated accidents like Pressurized Conduction Cooldown (PCC) event, the decay heat is first radially transferred from the core region to the reactor vessel outer surface, then to the RCCS cooling panels. The peak fuel temperature is controlled by heat transfer mechanisms with two distinctive characteristic length scales, i.e., the core-wise effective heat conduction and local heat conduction in the fuel pellet scale. As both length scales are essential to determine the fuel temperature, from the modeling perspective, computer codes must be able to capture heat transfer in both scales. This is challenging for both computational fluid dynamics (CFD) tools because of extremely large amount of computation resources required, and for system analysis codes because of the challenge to model the complex core geometry. Under the support of DOE-NE’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, efforts have been pursued to support HTGR technology development and its modeling and simulation needs. There is a particular need for advanced modeling and simulation tools to predict thermal-fluid behavior during safety-related transients. In our previous studies, the ring model was adopted in SAM and further developed to simulate the normal operating condition and a PCC event using the MHTGR-350 design of General Atomics as the reference design. This current work represents a continuation of these previous efforts, and the focus is to critically review and examine simplifications and assumptions made to develop the ring model, and to perform code validation using experimental data from an integral-effect test facility, the High Temperature Test Facility (HTTF) at the Oregon State University. In this study, the test PG-27 from the HTTF test suite was selected for code validation purpose. The test PG-27 is a transient test designed to simulate the PCC event of the MHTGR design. Very good agreements between SAM prediction and experimental measurements were found in both coolant and solid structure temperatures during the transient.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Additional Capability Being Developed from UNF-ST&DARDS Unified Database: System Analysis and Fuel Cycle Option Analysis

The Used Nuclear Fuel Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) is being developed for the U.S. Department of Energy’s Office of Nuclear Energy by the national laboratories. An important part of UNF-ST&DARDS is the Unified Database (UDB), which contains information that can support a variety of activities including fuel storage, fuel transportation, and disposal-related system analysis. Currently, the main application of the UDB is to support evaluation of the characteristics of discharged spent nuclear fuel (SNF) from the U.S. commercial reactors. However, because of the extensive amount of data that has been collected and analyzed for UNF-ST&DARDS, there are many more applications that can utilize the UDB including system analysis with the Next-Generation System Analysis Model (NGSAM) and fuel cycle analysis with fuel cycle simulation codes such as ORION. Going forward, NGSAM and fuel cycle transition analysis with ORION integrate UDB data wherever possible in the UDB’s development plan. Finally, these advances in NGSAM and fuel cycle analysis can be used in conjunction with the UDB to help answer more complex questions about the optimization, utilization, storage, and eventual disposal of SNF.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Coupled SAM/Griffin Model of a Reference Fluoride-Salt-Cooled High-Temperature Reactor for Multi-Physics Simulations

A multi-physics coupled simulation model of a reference pebble bed fluoride-salt-cooled high-temperature reactor (PB-FHR) has been developed with SAM and Griffin computer codes for transient safety analysis. The reference problem of a prototypical reactor design serves as the foundation for the U.S. NRC (Nuclear Regulatory Commission) to verify the adequacy of computer codes and evaluation models for specific reactor types. In this work, the previously developed SAM model for PB-FHR primary loop has been updated for the coupled simulation. The updated SAM PB-FHR model includes a 2-D axial symmetric core region and external core components in 0-D/1-D. In addition to the primary loop, a detailed model of the RCCS (reactor cavity cooling system) is added. The 2-D and 1-D domains are tightly coupled using the single-solve approach developed in SAM. In the pebble bed region, the SAM multiscale explicit pebble model is applied to calculate the pebble and TRISO fuel kernel temperatures. The Griffin model used in this work is based on a model developed at Idaho National Laboratory in collaboration with the U.S. NRC. The Griffin neutronics model and SAM thermal hydraulics model is coupled with the Comprehensive Reactor Analysis Bundle (CRAB or alternately BlueCRAB) application. Both steady-state and transient scenarios are simulated to demonstrate the model's suitability for multi-physics simulations of PB-FHR transients.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

HEP Software Foundation Community White Paper Working Group - Data Analysis and Interpretation

At the heart of experimental high energy physics (HEP) is the development of facilities and instrumentation that provide sensitivity to new phenomena. Our understanding of nature at its most fundamental level is advanced through the analysis and interpretation of data from sophisticated detectors in HEP experiments. The goal of data analysis systems is to realize the maximum possible scientific potential of the data within the constraints of computing and human resources in the least time. To achieve this goal, future analysis systems should empower physicists to access the data with a high level of interactivity, reproducibility and throughput capability. As part of the HEP Software Foundation Community White Paper process, a working group on Data Analysis and Interpretation was formed to assess the challenges and opportunities in HEP data analysis and develop a roadmap for activities in this area over the next decade. In this report, the key findings and recommendations of the Data Analysis and Interpretation Working Group are presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Predictive Maturity of Multi-Scale Simulation Models for Fuel Performance

The project proposed to provide a Predictive Maturity Framework with its companion metrics that (1) introduce a formalized, quantitative means to communicate information between interested parties, (2) provide scientifically dependable means to claim completion of Validation and Uncertainty Quantification (VU) activities, and (3) guide the decision makers in the allocation of Nuclear Energy’s resources for code development and physical experiments. The project team proposed to develop this framework based on two complimentary criteria: (1) the extent of experimental evidence available for the calibration of simulation models and (2) the sophistication of the physics incorporated in simulation models. The proposed framework is capable of quantifying the interaction between the required number of physical experiments and degree of physics sophistication. The project team has developed this framework and implemented it with a multi-scale model for simulating creep of a core reactor cladding. The multi-scale model is composed of the viscoplastic self-consistent (VPSC) code at the meso-scale, which represents the visco-plastic behavior and changing properties of a highly anisotropic material and a Finite Element (FE) code at the macro-scale to represent the elastic behavior and apply the loading. The framework developed takes advantage of the transparency provided by partitioned analysis, where independent constituent codes are coupled in an iterative manner. This transparency allows model developers to better understand and remedy the source of biases and uncertainties, whether they stem from the constituents or the coupling interface by exploiting separate-effect experiments conducted within the constituent domain and integral-effect experiments conducted within the full-system domain. The project team has implemented this procedure with the multi- scale VPSC-FE model and demonstrated its ability to improve the predictive capability of the model. Within this framework, the project team has focused on optimizing resource allocation for improving numerical models through further code development and experimentation. Related to further code development, we have developed a code prioritization index (CPI) for coupled numerical models. CPI is implemented to effectively improve the predictive capability of the coupled model by increasing the sophistication of constituent codes. In relation to designing new experiments, we investigated the information gained by the addition of each new experiment used for calibration and bias correction of a simulation model. Additionally, the variability of ‘information gain’ through the design domain has been investigated in order to identify the experiment settings where maximum information gain occurs and thus guide the experimenters in the selection of the experiment settings. This idea was extended to evaluate the information gain from each experiment can be improved by intelligently selecting the experiments, leading to the development of the Batch Sequential Design (BSD) technique. Additionally, we evaluated the importance of sufficiently exploring the domain of applicability in experiment-based validation of high-consequence modeling and simulation by developing a new metric to quantify coverage. This metric has also been incorporated into the design of new experiments. Finally, we have proposed a data-aware calibration approach for the calibration of numerical models. This new method considers the complexity of a numerical model (the number of parameters to be calibrated, parameter uncertainty, and form of the model) and seeks to identify the number of experiments necessary to calibrate the model based on the level of sophistication of the physics. The final component in the project team’s work to improve model calibration and validation methods is the incorporation of robustness to non-probabilistic uncertainty in the input parameters. This is an improvement to model validation and uncertainty quantification stemming beyond the originally proposed scope of the project. We have introduced a new metric for incorporating the concept of robustness into experiment-based validation of numerical models. This project has accounted for the graduation of two Ph.D. students (Kendra Van Buren and Josh Hegenderfer) and two M.S. students (Matthew Egeberg and Parker Shields). One of the doctoral students is now working in the nuclear engineering field and the other one is a post-doctoral fellow at the Los Alamos National Laboratory. Additionally, two more Ph.D. students (Garrison Stevens and Tunc Kulaksiz) who are working towards graduation have been supported by this project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Neutronics Calculation of Fast Reactor Using Modern Computing Systems

The possibility of using the LUCKY-A three-dimensional multiprocessor transport code as a neutronics module for the COREMELT integrated non-stationary code for performing safety analysis, which is used for fast sodium reactor safety validation, is discussed. In this application, more stringent requirements are imposed on the computing speed of the LUCKY-A code. To test LUCKY-A possibilities, a typical computational problem is examined in a formulation characteristic for the proposed use of the code. The possibilities of the code for parallelized calculations are shown, and a comparison is made with calculations performed with the MMKKENO and TRIGEX codes. The efficacy of a parallel computational process is investigated as a function of the number of computing kernels used.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗