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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dancoff-based Wigner-Seitz approximation for the subgroup resonance self-shielding in the VERA neutronic simulator MPACT

The MPACT neutronics module of the Virtual Environment for Reactor Analysis (VERA) has used the subgroup method for resonance self-shielding calculation, for which two-dimensional (2D) fixed-source transport calculations are performed using the method of characteristics for resonance energy groups. When considering thermal feedbacks, the subgroup calculation must be performed at each outer iteration. Therefore, the computing time for cross section processing is a significant burden for computational efficiency. The Dancoff-based Wigner-Seitz approximation (DWA) capability has been implemented into MPACT in conjunction with the subgroup method, which has been used in SCALE/XSProc since SCALE version 6.0 and has recently been called an equivalent Dancoff-factor cell (EDC) method. The issue of relatively large reactivity bias in DWA for the gadolinia rods was resolved by introducing multiple Dancoff factors. Benchmark results for the VERA pressurized and boiling water reactor benchmark suites show that the DWA capability would significantly enhance computational efficiency with comparable accuracy. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

VERA BWR progression problems

During the first phase of the Consortium for Advanced Simulation of Light Water Reactors (CASL) program, the Virtual Environment for Reactor Applications (VERA) was developed with a focus on capabilities for high-fidelity, multiphysics simulation of pressurized water reactors (PWRs). During this development effort, a set of progression problems was created ranging from smaller pin cell calculations to larger 3D full-core calculations. These progression problems helped to guide the development of the software and served as benchmarks against which to test VERA. Since 2019, efforts have been made to extend the capabilities of VERA to model boiling water reactors (BWRs). Because BWR simulations come with many unique challenges, a set of BWR progression problems was developed to aid in this new effort. The BWR progression problems range from 2D lattice calculations to 3D mini-core problems, and reference neutronic solutions were computed using continuous-energy Monte Carlo codes. MPACT, one of the neutronics code in VERA, was benchmarked using the BWR progression problems. The code is capable of computing solutions to all problems. The eigenvalues computed by MPACT agree well with the Monte Carlo reference solutions. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Multiscale thermal hydraulic coupling methods for boiling water reactor simulation

During the last two years, the Virtual Environment for Reactor Applications (VERA) has been extended to simulate boiling water reactors (BWRs). The thermal hydraulic effects present in BWRs are far more complex than those in pressurized water reactors (PWRs). Therefore, the runtime is significantly increase and convergence behavior worse compared to PWRs. Most of the additional runtime is spent during the first few coupled iterations, when the power shape is still rapidly evolving, dramatically affecting the thermal hydraulics (TH). To alleviate the increased computational expense, a multiscale TH coupling approach was developed in VERA in which a highly efficient, simplified TH model is solved for several coupled iterations until the power shape is partially converged. The simplified solution is used to inform the assembly-wise flow distribution in the high-fidelity TH solver CTF, reducing the amount of work required to properly balance the pressure drop in each channel and reducing runtime for the couple calculation. Because the final TH calculations are performed with CTF, there is ultimately no impact on the accuracy of the converged solution. This paper presents the details of this multiscale TH coupling approach, along with results for a 4x4 array of GE-14 fuel bundles and whole-core coupled simulations of the Hatch core. These two cases show that the multiscale approach dramatically reduces the runtime of coupled BWR simulations. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

FY20 Verification of BISON Using Analytic and Manufactured Solutions

In 2010, the U.S. Department of Energy created its first Energy Innovation Hub, which is focused on developing high-fidelity and high-resolution Modeling and Simulation (M&S) tools for modeling of Light Water Reactors (LWRs). This hub, Consortium for Advanced Simulation of LWRs (CASL), has developed an LWR simulation tool called Virtual Environment for Reactor Applications (VERA). The multi-physics capability of VERA is achieved through the coupling of single-physics codes, including BISON, CTF, MPACT, and MAMBA. BISON is a fuel performance code which models the thermo-mechanical behavior of nuclear fuel using high performance M&S. It is capable of modeling traditional LWR fuel rods, fuel plates, and TRi-structural ISOtropic (TRISO) fuel particles. It can employ three-dimensional Cartesian, two-dimensional axisymmetric cylindrical, or one-dimensional radial spherical geometry. It includes empirical models for a large variety of fuel physics: temperature- and burnup-dependent thermal properties, fuel swelling and densification, fission gas production, cladding creep, fracture, cladding plasticity, and gap/plenum models. This document details a series of code verification test problems that are used to test BISON. These problems add confidence that the BISON code is a faithful representation of its underlying mathematical model. The suite of verification tests are mapped to the underlying conservation equations solved by the code: heat conduction, mechanics, and species conservation. Twenty-two problems are added for the heat conduction solution, two for the mechanics solution, and none for species conservation. Method of Manufactured Solutions (MMS) capability is demonstrated with three problems, and temperature drops across the fuel gap are tested.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Separate Effects Validation for Subcooled Boiling in CTF

In 2010, the U.S. Department of Energy created its first Energy Innovation Hub, which is focused on developing high-fidelity and high-resolution modeling and simulation (M&S) tools for modeling of light water reactors (LWRs). This hub, the Consortium for Advanced Simulation of LWRs (CASL), has developed an LWR simulation tool called the Virtual Environment for Reactor Applications (VERA). The multi-physics capability of VERA is achieved through the coupling of single-physics codes, including CTF (the CASL version of Coolant Boiling in Rod Arrays— Three Field (COBRA-TF)), Michigan Parallel Characteristics Transport (MPACT), BISON, and Materials Performance and Optimization (MPO) Advanced Model for Boron Analysis (MAMBA). As part of its M&S efforts, CASL has identified various challenge problems, including Crud Induced Power Shift (CIPS), Crud-Induced Localized Corrosion (CILC), Pellet-Cladding Interaction (PCI), and Departure from Nucleate Boiling (DNB). This work addresses CASL milestone L2:VVI.P19.03, which focuses on uncertainty quantification of crud, which is relevant to both CIPS and CILC. This is achieved through an analysis and separate effects validation of the thermal hydraulic phenomenon known as subcooled boiling. As part of this work, various sources of experimental data are examined and compared to different options for empirical modeling of subcooled boiling. Through this analysis, a complete understanding of the underlying models and their implementation details are understood. A subset of these data are incorporated into a separate effects validation study of CTF. The Westinghouse Advanced Loop Tester (WALT) and Rohsenow experiments are modeled, and it is shown that the newly-implemented Gorenflo correlation is more accurate than the existing Chen and Thom correlations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Risk Importance Ranking of Fire Data Parameters to Enhance Fire PRA Model Realism

Fire is historically and analytically a significant contributor to nuclear power plant risk. The level of fire risk and the methods, tools and data for modeling this risk is highly debated by experts. One area of debate is the input data used in fire modeling and how to deal with this data’s high uncertainty. This report outlines initial work performed for determining the key parameters causing this uncertainty and how it propagates into nuclear power plant models. This research paves the way for the development of methods to reduce fire data uncertainty used in modeling. The Nuclear Regulatory Commission has mandated that nuclear power plants perform fire risk modeling. However, there are several issues with the current risk modeling implementation that affect the results. Approved modeling methods can be overly conservative and often do not match plant experience. Also, the data used in the modeling can have high uncertainties and is influenced by expert judgement. To evaluate input data uncertainty, researchers performed an initial review of several fire experiments done at Sandia National Laboratories. Uncertainties for fire data can come from many sources, such as experiment design constraints, environmental conditions, or other plant-specific aspects. There are many different significant and insignificant parameters driving the uncertainty. Additionally, the uncertainty of the different input data used in the fire modeling could have a significant or insignificant effect on the entire plant risk. A four-step methodology was developed to perform Integrated Probabilistic Risk Assessment Importance Ranking. A demonstration case using these steps was set up and three of the four steps were completed in fiscal year (FY) 2019 and the fourth step done FY 2020. These steps are: 1. The qualitative analysis of potential sources was conducted with the following items identified for the demonstration. • Maximum heat release rate • Time to maximum heat release rate • Duration of max heat release rate • Time to decay • Thermal conductivity of concrete • Specific heat of concrete • Density of concrete • Cable jacket thickness 2. A quantitative characterization of dominant sources of uncertainty was performed. A list of distributions and determined values of the dominant sources is shown in Appendix A. 3. A quantitative screening of the potential sources of uncertainty using Morris Elementary Effects Analysis was completed. An experimental model using the physics-based fire modeling tool Fire Dynamics Simulator was developed and coupled with the Risk Analysis Virtual Environment. The Morris analysis identified at least two parameters that can be eliminated as significant contributors (specific heat of concrete and cable jacket thickness). 4. Global importance measure (Global IM) analysis to generate a comprehensive ranking based on their influence on the plant risk. In this research, a moment-independent Global IM is used since it can address (a) uncertainty in the input parameters of the fire model, (b) uncertainty in the risk outputs, and (c) non-linearity and interactions among input parameters in the fire model, more accurately than the correlation-based and variance-based global methods. The observations from the research showed that, depending on the initial and boundary conditions of the fire scenarios, fire-induced damage could have a very small probability and could be dominated by the tail of the uncertainty distribution; hence, the accuracy of the correlation-based and variance-based methods is questionable. The moment-independent Global IM analysis in this research provides a better understanding of how experimental uncertainty data affects industry’s plant models and where improvements in that data will have the largest benefit for improving fire modeling accuracy in causing core damage. Among the five unscreened parameters obtained from the Morris EE analysis, the Global IM analysis results for the case study indicated that max heat release rate and fire location are the most important parameters. The report also outlines benefits of using a unified computational platform that integrates the underlying simulations (e.g., a fire progression model), quantitative screening (using the Morris EE method), and the Global IM analysis. A unified platform can (i) facilitate the ranking of input parameters considering multiple key fire scenarios simultaneously, rather than considering one scenario at a time, (ii) contribute to more explicit and accurate treatment of dependencies at multiple levels of Fire PRA, (iii) facilitate the sampling-based uncertainty quantification for Fire PRA, and (iv) help generating both “industry-wide” and "plant-specific" ranking of uncertainty sources in Fire PRA. Future research should be done to include additional parameters such as detection/suppression or cable fire spread. Adding a PRA software such as SAPHIRE to the RAVEN platform would help with plant model integration and improve treatment of fire-induced dependency. The I-PRA risk importance ranking methodology offered in this report can provide valuable information for efficiently (a) enhancing the realism of Fire PRA for existing plants and (b) supporting the development of Dynamic Fire PRA for advanced reactors and new plants.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Subcritical Multiplication Ex-Core Calculations with Shift

This report details the development and testing of Virtual Environment for Reactor Applications (VERA) as applied to full core subcritical multiplication ex-core calculations with Shift. The limiting factor in being able to run these detector calculations with Monte Carlo is the amount of computational memory used by a fully-loaded full core problem. The main development features added to VERA in this effort were enabling source biasing and separable weight windows and integrating multithreading in Shift. With these capabilities, a subcritical multiplication detector response calculation on a full core Watts Bar Nuclear Plant Unit 1 (WBN1) ex-core model was successfully run on a moderately sized computing cluster.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Improvements to CTF for Modeling of Boiling Water Reactor Geometry and Operating Conditions

This report documents work done to improve CTF modeling of boiling water reactor (BWR) designs during FY 2020. Several improvements were made to the geometry modeling capabilities, including adding support for modeling of inlet flow orifices, axially varying large water rods, channel boxes with large corner round radii, and quarter symmetry models. Work was also done to improve on the numerical stability and run-time performance of CTF in Virtual Environment for Reactor Applications (VERA) for core-scale BWR problems. An outer iteration loop was implemented that ensures mass and energy are conserved before moving on to the next time step in the solution. The ability to use a direct solver for the pressure matrix was also added, which reduces the matrix solution error and improves code stability and run-time performance. Improvements to the pressure balance iteration loop were needed to allow CTF to be used in a coupled VERA solution of a model of Hatch that was developed. Finally, various improvements have led to a 2×reduction in the total VERA walltime for the Hatch model.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Evaluation of Hybrid FPOG Applications in Regulated and Deregulated Markets Using HERON

Recent changes in the U.S. energy market, such as low natural gas prices and increased electricity production for variable renewable energy (VRE) sources, have led to an economic crisis for existing light-water reactor (LWR) nuclear power plants (NPP). Many owners and operators of LWRs have elected to decommission these plants rather than continue using them as consistent sources of clean baseload power. This has led to exploration of various possibilities to increase the economic viability of these units, including market restructuring to monetize benefits LWRs already provide to the grid through ancillary markets, load following and economic dispatch, and possible integration of secondary systems directly to the NPP for production of additional products through technologies such as hydrogen electrolysis or water desalination. Previous studies have considered the technologies associated with these Integrated Energy Systems (IES) activities, and the analysis of markets for these secondary products. To analyze the economic viability of various system configurations including IES, especially given the uncertainty surrounding load demand, electricity prices, and the availability of VRE resources, the stochastic technoeconomic analysis package HERON (Heuristic Energy Resource Optimization Network) was released earlier this year as an extension of the risk analysis framework RAVEN (Risk Analysis Virtual Environment). HERON focuses foremost on making the complex uncertainty quantification analysis tools approachable for energy systems analysts, also providing general dispatch optimization algorithms for those workflows. HERON continues to be improved and tested as a significant part of the IES viability analyses performed in this work. HERON is not a capacity expansion model. To consider market and grid energy system development in a variety of scenarios, HERON is best used in coupling with modelling tools such as US-REGEN, which sacrifice some of the uncertainty analysis and resolution of HERON's modelling for the ability to efficiently predict the change in the grid energy system's profile due to economic drivers over decades. HERON can then use this information to explore the economic viability of introducing changes to the predicted outcomes, such as the introduction of an IES. In this work, experts at EPRI using US-REGEN provide six projection scenarios for use in HERON stochastic technoeconomic analysis (STEA) in considering the options available for increasing LWR economic viability through introduction of a hydrogen-centric IES using a high-temperature steam electrolysis plant (HTSE), hydrogen storage, and a constant-rate contracted hydrogen consumer. The results obtained are differential in nature; they do not report expected profits for any configuration, but rather report on the possible increase in the NPV of a configuration with respect to a baseline no-IES configuration. Due to the uncertainty captured in the variable net load of the systems, there is likewise uncertainty in the mean values reported. We consider this viability both in terms of a regulated market, where the energy producers and IES are owned and operated by single entity, as well as a deregulated market, where the IES chooses its bid for electricity generation and is then dispatched by the grid system operator. Results indicate that for deregulated markets, the inclusion of the IES is often statistically beneficial. This is especially true in policies that are not favorable towards nuclear, as nuclear is less often dispatched and is forced to deal with frequent idle capacity. In the nominal case as well as the case of carbon tax policies, inclusion of the IES clearly benefited the economic performance of the NPP. In the regulated case, however, there was a trend towards minimizing the IES, likely due to the optimal sizing performed by US-REGEN of the NPP within the system as well as the lack of penalty for idle capacity at the NPP in the regulated market analyses.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Coupling of CTF and TRANSFORM using the Functional Mockup Interface

An in-memory coupling between the sub-channel thermal hydraulics code COBRA-TF (CTF), which is included in the Virtual Environment for Reactor Applications (VERA), and the systems code Transient Simulation Framework of Reconfigurable Models (TRANSFORM) was developed in this work. Data exchange is accomplished by using the Functional Mock-Up Interface (FMI), an open standard for coupling dynamic systems models together. The FMI-based coupling necessitated the development of a novel FORTRAN wrapper for communicating with Functional Mock-Up Units. This wrapper will facilitate future FMI-based code couplings with other FORTRAN-based programs. CTF-TRANSFORM is exercised on a simplified Molten Salt Reactor Experiment (MSRE) model in steady-state and transient configurations. The coupled CTF-TRANSFORM model is shown to predict core temperature deltas similar to those available in historical MSRE operational data and is shown to be robust to fast power transients.The coupling paves the way to performing sensitivity and design studies impossible with VERA/CTF alone, in which secondary and tertiary loop operating conditions and design parameters may be perturbed and their impact on the core operating conditions studied.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Emergent Concepts from a Community Ideation on AI4ESP

This AI4ESP white paper is the outcome of an open ideation session led by PNNL that numerous institutions participated in. The leadership team included Amy Goldman, Huiying Ren, Tim Scheibe, and James Stegen. The white paper is broken into two sections: (1) A summary of the ideation session, and (2) a short summary of a ‘meta idea’ that emerged from combining multiple ideas spanning the three primary focal area themes articulated in BER’s AI4ESP guidance: A - Data Acquisition and Assimilation, B - Predictive Modeling, and C - Insight from Complex Data. The white paper, therefore, has two goals. The first section is meant to be a resource for innovating around how to pursue open, community-based ideation in virtual environments. The second section is meant as an example of the kinds of ‘meta ideas’ that can emerge from bringing diverse ideas together in a single shared space. We consider the second section to be a submission to BER’s request for white papers around AI4ESP.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗
DOE OSTI2020

Coupling MOOSE-Wrapped MPACT to BISON

As part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, an effort is being made to leverage codes like Virtual Environment for Reactor Analysis (VERA) and Michigan Parallel Characteristics Transport (MPACT) by coupling them with other NEAMS codes. To facilitate coupling with other Multiphysics Objected Oriented Simulation Environment (MOOSE) applications, a MOOSE-wrapped MPACT app is created. The capability of this app, named Trogdor, is demonstrated by coupling it with another MOOSE app, BISON. Several single pin problems were run to test the Trogdor and BISON coupling.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Using ROS for Robotic Control [Slides]

The use of robots is important, to help prevent people from being exposed to hazardous materials within a glovebox. The research proposal for the summer was to make a pick and place demo for a seven degrees-of-freedom Motoman Sia5d robot. The Robot Operating System (ROS) was used and the knowledge of C++ and Linux had to be applied. The robot was used to pick up and sort four objects (cylinder, sphere, rectangular prism, and cone) within a virtual environment.

42 ENGINEERING↗
DOE OSTI2021

Summary of CTF Modeling and Numerical Improvements for Boiling Water Reactor Simulation

This report documents geometry and numerical improvements made to CTF for the modeling of boiling water reactor (BWR) geometry and operating conditions. These activities are part of a larger program to extend the Virtual Environment for Reactor Applications (VERA) to better support BWR modeling and simulation. The activities documented in this report added features to CTF, including support for mixed-fuel cores, modeling of the upper plenum, and modeling of the lower tie plate form losses. A review of the spacer grid modeling approach was also performed, and a plan was discussed for future improvement. The parallelization of the model was improved, leading to a roughly 2× improvement in CTF runtime and a 1.6× improvement in total VERA runtime. An in-depth review of the governing equations and their linearization was performed and is documented in this report. Once implemented, this new linearization will allow CTF to take much larger timesteps, leading to more significant reductions in CTF and VERA runtimes.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

VERAIO Software Management Plan

VERAIO is a set of utility codes used to provide a common set of input and outputs to the Virtual Environment for Reactor Applications (VERA). VERA is a collection of several different computer codes that all have a common input and output. This prevents the need to manage input and output from each individual code, allowing for ease of use and reducing errors associated with code operability. The VERAIO utilities include VERAIn, VERAView, and VERARun. Each of these utilities is described below. VERAIn is an input processor that reads an ASCII input file generated by users, parses the file, performs some error checking, and writes an XML file to be read by other VERA codes. The main purpose of VERAIn is to provide a common input to all of the VERA codes so users only need to learn one input. VERAIn is written in Perl and uses YAML configuration files to provide flexibility. VERAView is a graphical user interface (GUI) that reads a VERA HDF output file and allows users to visualize results. VERAView is written in Python. VERARun is a script that drives the VERA execution in a high performance computing (HPC) environment. Work performed at the code level supports the Quality Assurance Program Plan (QAPP) (VERA-QA-001), and VERA Software Quality Assurance Plan (VERA-QA-002).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

NEAMS Milestone Report: M2MS–20OR030102 FW–CADIS PWR Ex-Core Analysis with Shift Through VERA

This report presents the work completed for the NEAMS milestone M2MS–20OR030102 titled "FW–CADIS PWR Ex-Core Analysis with Shift through VERA." The work completed for this milestone includes the implementation, integration, and optimization of memory and performance improvement methods in Shift for fully coupled ex-core calculations through Virtual Environment for Reactor Applications (VERA). Fully coupled in this context means the transfer of moderator boron concentration, pin-wise fission source, depleted compositions, temperatures, and moderator densities from MPACT (with COBRA-TF (CTF)) to Shift. The ability to run ex-core calculations with VERA has been enabled and used for several years by Consortium for Advanced Simulation of Light Water Reactors (CASL) partners. However, this implementation was limited and potentially computationally burdensome. This work has enabled the ability to run higher-fidelity ex-core calculations on moderate computing clusters by focusing on multithreading, domain decomposition, and Forward-Weighted CADIS (FW-CADIS) variance reduction. Tests performed on small cores, a small modular reactor (SMR), and CASL progression problems show very promising memory reduction and computational performance. Recommendations for settings when running fully coupled high-fidelity ex-core calculations with VERA are documented. Without these optimization methods, many processors on a compute node would be left unused for the entire ex-core calculation. Therefore, these methods enable the user to better use the resources available and reduce computation time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Internet Access Index: Measuring the availability and household adoption of high-speed internet

Access to broadband or high-speed internet has taken on increased importance during the COVID-19 pandemic as many workplaces and schools shifted to a virtual environment. The Internet Access Index (IAI) was developed to better understand the challenges many households face in connecting to high-speed internet, whether due to lack of broadband availability from internet service providers or difficulties in subscribing to a broadband service. The IAI is calculated as the product of 3 factors. The first two factors gauge the quality and availability of high-speed internet and the third factor represents the public’s ability to subscribe to high-speed internet services. The IAI scores United States’ census tracts on a [0,1] scale, where values near 0 represent areas with less internet access and values approaching 1 represent more internet access. The maximum score (1.0) implies that all census blocks within a census tract have high speed internet available at the highest national speed (currently 1000 mbps), and that all households within the tract have a fixed broadband subscription of some type.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗