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This dataset contains model code (including input data) to replicate the outcomes for "Assessing the Efficiency Implications of Renewable Fuel Policy Design in the United States". The model consists of: (1) The replication codes and data for the model. To run the model, using GAMS to run the "Models.gms" file.
Homogenized fuel assembly (FA) data is a typical input data for nodal codes. Generating that data, however, could be time-consuming. One of promising ways to mitigate the computational burden of generating macroscopic cross-sections is to use trained artificial neural network (ANN) models for predicting nuclear data. However, there is a challenge to make the model support variable FA geometry. In this work, two most common types of FA were combined in one ANN model. Since there could be multiple ways of converting 2-dimensional FA data into 1-dimensional input vector for ANN, three different approaches of data flattening were evaluated. The input parameters included each fuel pin enrichment, fuel temperature, moderator temperature and boron concentration. The output parameters were 2-group macroscopic cross-sections (XS) and pin power distribution (HFF). A fully connected deep neural network (DNN) model was trained and tested using pre-generated data obtained with lattice physics code STREAM. The results of this study showed no statistically significant difference in the accuracy of XS and HFF generation for all 3 tested input vector orders. This means that fully connected DNN for XS generation demonstrated input sequence invariance. Results of comparing predicted XS data with reference solutions were found sufficiently close considering the reduction of computation time offered by ANN. Mean relative difference (MRD) for all output XS parameters was found below 0.7%, while HFF MRD was found higher compared to XS values, in some cases slightly exceeding 1%, mostly near guide tube locations. (authors)
The Shift Monte Carlo code will be introduced in SCALE 6.3 as an alternative to the KENO V.a, KENO-VI, and Monaco codes. Calculations were performed to establish the performance of Shift for criticality safety analyses within the criticality safety analyses sequence (CSAS) based on models in the Verified, Archived Library of Inputs and Data (VALID). This test suite contains over 600 critical experiment models covering a broad range of fissile materials and neutron energy spectra. The comparisons presented include calculated k eff values and runtime performance for serial calculations and a selection of parallel calculations. Comparisons are presented for multigroup (MG) and continuous-energy (CE) calculations for KENO V.a and KENO-VI models. Results generated with a beta version of SCALE 6.3 indicate excellent agreement in k eff values between KENO and Shift. The largest differences in the average k eff value calculated for the 15 categories of KENO V.a models are 0.00020 ± 0.00011 Δ k for MG calculations and 0.00011 ± 0.00005 Δ k for CE calculations. Similar comparisons in three categories using KENO-VI result in the largest differences for MG calculations: as 0.00004 ± 0.00003 Δ k , and -0.00002 ± 0.00003 Δ k for CE. The preliminary results also indicate that Shift is faster than KENO on a per particle basis, especially for fast spectrum systems. The uncertainty per history is also higher, however, so the Monte Carlo figure of merit is higher for KENO for thermal and intermediate spectrum systems. As expected, Shift generally has better speedup than KENO for parallel calculations, regardless of neutron energy spectrum.
Supported by recent computational studies, there is increasing evidence that a wide range of neuronal responses can be understood as an emergent property of nonnegative sparse coding (NSC), an efficient population coding scheme based on dimensionality reduction and sparsity constraints. We review evidence that NSC might be employed by sensory areas to efficiently encode external stimulus spaces, by some associative areas to conjunctively represent multiple behaviorally relevant variables, and possibly by the basal ganglia to coordinate movement. In addition, NSC might provide a useful theoretical framework under which to understand the often complex and nonintuitive response properties of neurons in other brain areas. Although NSC might not apply to all brain areas (for example, motor or executive function areas) the success of NSC-based models, especially in sensory areas, warrants further investigation for neural correlates in other regions.
This repository contains R code and associated datasets for reproducing the analysis described in the manuscript titled “Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability” (DOI: 10.1029/2024JG008604). The provided scripts facilitate a comprehensive analysis of snow depth variability influenced by microtopography and vegetation distribution in a subarctic watershed. Included datasets are high-resolution spatial maps of snow depth, terrain elevation, vegetation height, and distance from shrubs taller than 1 meter, all formatted as text files (.txt). These data are fully describe in doi:10.15485/2316038. Users can adapt the provided R scripts to accommodate different data formats or larger spatial domains, noting that some output files may require modification due to their size.The code includes implementations for boosted regression tree analysis adapted from methods outlined in Elith et al. (2008). Users interested in understanding or modeling landscape-scale snow distribution patterns, particularly in Arctic or subarctic ecosystems, will find this package useful. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
Polarization lifetime for He3 using two and six snakes are studied using the T-BMT Spin Resonance Tracker code. This code integrates a reduced spinor form of the T-BMT equation including only several spin resonances and the kinematics of synchrotron motion. It was previously benchmarked against RHIC polarization lifetime under the two snake system *. * Phys. Rev.Accel. Beams 22 (2019) 9, 091001
Scientific Computational Imaging Code (SCICO) is a Python package for solving the inverse problems that arise in scientific imaging applications. Its primary focus is providing methods for solving ill-posed inverse problems by using an appropriate prior model of the reconstruction space. SCICO includes a growing suite of operators, cost functionals, regularizers, and optimization routines that may be combined to solve a wide range of problems, and is designed so that it is easy to add new building blocks. SCICO is built on top of JAX rather than NumPy, enabling GPU/TPU acceleration, just-in-time compilation, and automatic gradient functionality, which is used to automatically compute the adjoints of linear operators. An example of how to solve a multi-channel tomography problem with SCICO is shown in Figure 1. The SCICO source code is available from GitHub, and pre-built packages are available from PyPI. It has extensive online documentation, including API documentation and usage examples, which can be run online at Google Colab and binder.
PeleLMeX simulates chemically reacting low Mach number flows with block-structured adaptive mesh refinement (AMR). The code is built upon the AMReX library, which provides the underlying data structures and tools to manage and operate on them across massively parallel computing architectures. PeleLMeX algorithmic features are inherited from its predecessor PeleLM but key improvements allow representation of more complex physical processes. Together with its compressible flow counterpart PeleC, the thermo-chemistry library PelePhysics and the multi-physics library PeleMP, it forms the Pele suite of open-source reactive flow simulation codes.
One of the most pressing unexplained phenomena standing in the way of ICF ignition is understanding mix and how it interacts with burn. Experiments were being designed and fielded as part of the Defect-Induced Mix Experiment (DIME) project to obtain data about the extent of material mix and how this mix influenced burn. Experiments on the Omega laser and National Ignition Facility (NIF) provided detailed data for comparison to the Eulerian code RAGE1. The Omega experiments were able to resolve the mix and provide “proof of principle” support for subsequent NIF experiments, which were fielded from July 2012 through June 2013. The Omega shots were fired at least once per year between 2009 and 2012. RAGE was not originally designed to model inertial confinement fusion (ICF) implosions. It still lacks lasers, so the code has been validated using an energy source. To test RAGE, the simulation output is compared to data and by means of postprocessing tools that were developed. Here, the various postprocessing tools are described with illustrative examples.
The purpose of this document is to identify laws, rules, model codes, codes, standards, regulations, specifications (CSR) related to safety that could apply to stationary energy storage systems (ESS) and experiences to date securing approval of ESS in relation to CSR. This information is intended to assist in securing approval of ESS under current CSR and to identification of new CRS or revisions to existing CRS and necessary supporting research and documentation that can foster the deployment of safe ESS.
Residential rooftop solar panel installations are limited in part by the high cost of structural related code requirements for field installation. Permitting solar installations is difficult because there is a belief among residential permitting authorities that typical residential rooftops may be structurally inadequate to support the additional load associated with a photovoltaic (PV) solar installation. Typical engineering methods utilized to calculate stresses on a roof structure involve simplifying assumptions that render a complex non-linear structure to a basic determinate beam. This method of analysis neglects the composite action of the entire roof structure, yielding a conservative analysis based on a rafter or top chord of a truss. Consequently, the analysis can result in an overly conservative structural analysis. A literature review was conducted to gain a better understanding of the conservative nature of the regulations and codes governing residential construction and the associated structural system calculations.
This document serves as a detailed companion to the powerpoint slides presented as part of the ASC L2 milestone review for Integrated Codes milestone #4782 titled “Assess Newly Emerging Programming and Memory Models for Advanced Architectures on Integrated Codes”, due on 9/30/2014, and presented for formal program review on 9/12/2014. The program review committee is represented by Mike Zika (A Program Project Lead for Kull), Brian Pudliner (B Program Project Lead for Ares), Scott Futral (DEG Group Lead in LC), and Mike Glass (Sierra Project Lead at Sandia). This document, along with the presentation materials, and a letter of completion signed by the review committee will act as proof of completion for this milestone.
This report documents an inspection of the Whisper Fortran source code. As a result of this inspection, this report explains how (and confirms) the methodology was implemented in the source code. The following sections document the algorithms, data structures, and program structure in Whisper. When Whisper implements a specific equation in LA-UR-14-26558, a cross reference to the equation is made. Also, Appendix A provides a cross reference from the equations in LA-UR-14-26558 to the implementing subroutine or function.
This report describes the R5EXEC coupling interface in the RELAP5-3D computer code from the users perspective. The information in the report is intended for users who want to couple RELAP5-3D to other thermal-hydraulic, neutron kinetics, or control system simulation codes.
An implementation of both ALICE code and TENDL evaluated nuclear data library in order to describe nuclear reactions induced by low-energy projectiles in the Monte Carlo code MARS15 is presented. Comparisons between results of modeling and experimental data on reaction cross sections and secondary particle distributions are shown.
The mission of the U.S. Department of Energy (DOE), Office of Nuclear Energy is to advance nuclear power in order to meet the nation's energy, environmental, and energy security needs. Advanced high temperature reactor systems such as sodium fast reactors and high and very high temperature gas-cooled reactors are being considered for the next generation of nuclear reactor plant designs. The coolants for these high temperature reactor systems include liquid sodium and helium gas. Supercritical carbon dioxide (sCO₂), a fluid at a temperature and pressure above the supercritical point of CO₂, is currently being investigated by DOE as a working fluid for a nuclear or fossil-heated recompression closed Brayton cycle energy conversion system that operates at 550°C (1022°F) at 200 bar (2900 psi). Higher operating temperatures are envisioned in future developments. All of these design concepts require a highly effective heat exchanger that transfers heat from the nuclear or chemical reactor to the chemical process fluid or the to the power cycle. In the nuclear designs described above, heat is transferred from the primary to the secondary loop via an intermediate heat exchanger (IHX) and then from the intermediate loop to either a working process or a power cycle via a secondary heat exchanger (SHX). The IHX is a component in the primary coolant loop which will be classified as "safety related." The intermediate loop will likely be classified as "not safety related but important to safety." These safety classifications have a direct bearing on heat exchanger design approaches for the IHX and SHX. The very high temperatures being considered for the VHTR will require the use of very high temperature alloys for the IHX and SHX. Material cost considerations alone will dictate that the IHX and SHX be highly effective; that is, provide high heat transfer area in a small volume. This feature must be accompanied by low pressure drop and mechanical reliability and robustness. Classic shell and tube designs will be large and costly, and may only be appropriate in steam generator service in the SHX where boiling inside the tubes occurs. For other energy conversion systems, all of these features can be met in a compact heat exchanger design. This report will examine some of the ASME Code issues that will need to be addressed to allow use of a Code-qualified compact heat exchanger in IHX or SHX nuclear service. Most effort will focus on the IHX, since the safety-related (Class A) design rules are more extensive than those for important-to-safety (Class B) or commercial rules that are relevant to the SHX.
Through its Advanced Scientific Computing (ASC) and Inertial Confinement Fusion (ICF) code development efforts, Lawrence Livermore National Laboratory (LLNL) provides a world leading numerical simulation capability for the National HED/ICF program in support of the Stockpile Stewardship Program (SSP). In addition the ASC effort provides high performance computing platform capabilities upon which these codes are run. LLNL remains committed to, and will work with, the national HED/ICF program community to help insure numerical simulation needs are met and to make those capabilities available, consistent with programmatic priorities and available resources.
TOGA is a numerical reservoir simulator for modeling non-isothermal flow and transport of water, CO 2 , multicomponent oil, and related gas components for applications including CO 2 -enhanced oil recovery (CO 2 -EOR) and geologic carbon sequestration in depleted oil and gas reservoirs. TOGA uses an approach based on the Peng-Robinson equation of state (PR-EOS) to calculate the thermophysical properties of the gas and oil phases including the gas/oil components dissolved in the aqueous phase, and uses a mixing model to estimate the thermophysical properties of the aqueous phase. The phase behavior (e.g., occurrence and disappearance of the three phases, gas + oil + aqueous) and the partitioning of non-aqueous components (e.g., CO 2 , CH 4 , and n-oil components) between coexisting phases are modeled using K-values derived from assumptions of equal-fugacity that have been demonstrated to be very accurate as shown by comparison to measured data. Models for saturated (water) vapor pressure and water solubility (in the oil phase) are used to calculate the partitioning of the water (H 2 O) component between the gas and oil phases. All components (e.g., CO 2 , H 2 O, and n hydrocarbon components) are allowed to be present in all phases (aqueous, gaseous, and oil). TOGA uses a multiphase version of Darcy’s Law to model flow and transport through porous media of mixtures with up to three phases over a range of pressures and temperatures appropriate to hydrocarbon recovery and geologic carbon sequestration systems. Transport of the gaseous and dissolved components is by advection and Fickian molecular diffusion. New methods for phase partitioning and thermophysical property modeling in TOGA have been validated against experimental data published in the literature for describing phase partitioning and phase behavior. Flow and transport has been verified by testing against related TOUGH2 EOS modules and CMG. The code has also been validated against a CO 2 -EOR experimental core flood involving flow of three phases and 12 components. Results of simulations of a hypothetical 3D CO 2 -EOR problem involving three phases and multiple components are presented to demonstrate the field-scale capabilities of the new code. This user guide provides instructions for use and sample problems for verification and demonstration.