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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Model, data, and code for paper "Modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x"

The data package includes data, model, and code that support the analyses and conclusions in the paper titled “modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x”. The primary goal of this paper is to demonstrate that key streamflow properties such as water depth, flow velocity, and dynamic pressure in a natural river at 30-kilometer scale over 5 years can be reliably and efficiently modeled using the computational framework presented in this paper. To support the paper, various data types from remote sensing, field observations, and computational models are used. Specific details are described as follows. Firstly, the river bathymetry data was obtained from a Light Detection and Ranging (LiDAR) survey. This data is then converted to a triangulated surface format, STL, for mesh generation in OpenFOAM. The STL data can be found in Model_Setups/BaseCase_2013To2015/constant/triSurface. The OpenFOAM mesh generated using this STL file can be found in constant/polyMesh. Other model setups, boundary and initial conditions can be found in /system and /0.org under folder BaseCase_2013To2015. A similar data structure can also be found in BaseCase_2018To2019 for the simulations during 2018 and 2019. Secondly, the OpenFOAM simulations need the upstream discharge and water depth information at the upstream boundary to drive the model. These data are generated from a one-dimensional hydraulic model and the data can be found under the folder Model_Setups /1D model Mass1 data. The mass1_65.csv and mass1_191.csv files include the results of the 1D model at the model inlet and outlet, respectively. The Matlab source code Mass1ToOFBC20182019.m is used to convert these data into OpenFOAM boundary condition setups.With the above OpenFOAM model, it can generate data for water surface elevation, flow velocity, and dynamic pressure. In this paper, the water surface elevation was measured at 7 locations during different periods between 2011 and 2019. The exact survey locations (see Fig1_SurveyLocations.txt) can be found in folder Fig_1. The variation of water stage over time at the 7 locations can be found in folder /Observation_WSE. The data type include .txt, .csv, .xlsx, and .mat. The .mat data can be loaded by Matlab.We also measured the flow velocities at 12 cross-sections along the river. At each cross-section, we recorded the x, y locations, depth, three velocity components u,v,w. These data are saved to a Matlab format which can be found under folder /Observation_Velocity and /Fig_1. The relative locations of velocity survey locations to the river bathymetry can be found in Figure 1c.The water stage data at the 7 locations from OpenFOAM, 1D, and 2D hydraulic models are also provided to evaluate the long-term performance of 3D models vs 1D/2D models. The water stage data for the 7 locations from OpenFOAM have been saved to .mat format and can be found in /OpenFOAM_WSE. The water stage data from the 1D model are saved in .csv format and can be found in /Mass1_WSE. The water stage from the 2D model is saved as .mat format and can be found in / Mass2_WSEIn addition, the OpenFOAM model outputs the information of hydrostatic and hydrodynamic pressure. They are saved as .mat format under folder /Fig_11/2013_1. As the files are too large, we only uploaded the data for January 2013. The area of different ratio of dynamic pressure to static pressure for all simulation range, i.e., 2013-2015, are saved to .mat format. They can be found in /Fig_11/PA. Further, the data of wall clock time versus the solution time of the OpenFOAM modeling are also saved to .mat format under folder /Fig_13/LogsMat. In summary, the data package contains seven data types, including .txt, .csv, .xlsx, .dat, .stl, .m, and .mat. The former 4 types can be directly open using a text editor or Microsoft Office. The .mat format needs to be read by Matlab. The Matlab source code .m files need to be run with Matlab. The OpenFOAM setups can be visualized in ParaView. The .stl file can be opened in ParaView or Blender. The data in subfolders Fig_1 to Fig_10 and Fig_12 are copied from the aforementioned data folders to generate specific figures for the paper. A readME.txt file is included in each subfolder to further describe how the data in each folder are generated and used to support the paper.Please use the data package's DOI to cite the data package. Please contact yunxiang.chen@pnnl.gov if you need more data related to the paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Substantial and overlooked greenhouse gas emissions from deep Arctic lake sediment - supporting data and code

This data package contains data, descriptions, and code-based analyses that were used to support conclusions drawn in “Substantial and overlooked greenhouse gas emissions from deep Arctic lake sediment”, by Freitas et al. (2025) (https://doi.org/10.1038/s41561-024-01614-y). The study evaluated greenhouse gas production along a deep sediment core (20 m) taken in 2018 from below Goldstream Lake, a field site approximately 15 km north of Fairbanks, Alaska.The file “ESSDive_NFreitas_2024_flmd.csv” includes an overview of all other csv files in this data package, namely: sediment descriptions (depth and type of sediment), sediment characterizations (bulk density, gravimetric water content, total carbon, etc.), calculated respiration and temperature sensitivity values associated with year-long incubations of the sediment core, and the R code used to process the dataset. Additional details regarding the content of these files and how the calculations were performed are described in the Methods section of this archive. The “data_dictionary_ESSDive_NFreitas_2024_dd.csv” is a data dictionary for all files included in the data package. Each row in the data dictionary represents a column name in a given file. 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).Data package updates- August 2024: Title was updated, R code now includes a process for calculating potential production across the whole sediment column, the "sediment_column_production_potentials_ESSDive_NFreitas_2024.csv" is the associated data output file, and the file level metadata and data dictionaries were updated to reflect the contents of the additional csv file.- October 2024: Title was updated, and a statement was added to Step 2 of the Methods that describes that samples were collected (and exported) in a responsible manner and in accordance with relevant permits and local laws.- January 2025: Updated the associated manuscript details in the Abstract (manuscript title, publication date, DOI link) and in the Related References section (full citation).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Estimating soil thermal inertia profiles from the passive equilibration of a temperature probe: Supporting data and code

This dataset contains measurements of soil thermal properties and organic layer thickness at three field sites on the Seward Peninsula near Nome, Alaska, USA. Code is also provided for estimation of soil thermal properties from temperature data, including a forward heat transfer mode, a library of simulated temperature data, and an inversion scheme to retrieve thermal properties from temperature measurements (Lamb et al., 2025). This dataset and code is published in support of the manuscript “Estimating Soil Thermal Inertia Profiles from the Passive Equilibration of a Temperature Probe” by Lamb et al., 2025, in which an experimental thermal measurements technique is developed. The dataset contains measurements of soil thermal properties and organic layer thickness obtained with an industry standard thermal properties analyzer and direct observations, as well as data generated using the experimental technique to estimate thermal properties and soil structure from temperature observations. All data is reported in .csv format, and all code is written in Python 3.7 using standard packages. This research was performed as a part of the NGEE Arctic project, which aims to advance model predictions of arctic carbon cycle responses to a changing climate over the 21st Century.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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Amazon windthrow disturbances are likely to increase with storm frequency under global warming: Data and Codes

This zipfile includes datasets and codes that were used to produce the results in the paper entitled Amazon windthrow disturbances are likely to increase with storm frequency under global warming. Datasets include: 1. Windthrow density across the entire Amazon - GIS shapefile format 2. Current ERA 5 mean afternoon convective available potential energy (CAPE) (1990-2019) - Remote Sensing TIFF format 3. Estimated future mean CAPE from 10 models in CMIP 6 (2070-2099) - Remote Sensing TIFF format 4. Python codes in jupyter notebook and processed datasets used to generate Fig.2a and Table 1 in the paper. You will need to use Jupyter Notebook and Python for accessing and reading the codes. Please contact Yanlei Feng (ylfeng@berkeley.edu) for any questions. Paper associated with this dataset: Feng, Y., Negrón-Juárez, R.I., Romps, D.M. and Chambers, J.Q., 2023. Amazon windthrow disturbances are likely to increase with storm frequency under global warming. Nature communications, 14(1), p.101.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Comprehensive Benchmark Suite for Simulation of Particle Laden Flows Using the Discrete Element Method with Performance Profiles from the Multiphase Flow with Interface eXchanges (MFiX) Code

Five benchmark problems are developed and simulated with the computational fluid dynamics and discrete element model code MFiX. The benchmark problems span dilute and dense regimes, consider statistically homogeneous and inhomogeneous (both clusters and bubbles) particle concentrations and a range of particle and fluid dynamic computational loads. Several variations of the benchmark problems are also discussed to extend the computational phase space to cover granular (particles only), bidisperse and heat transfer cases. A weak scaling analysis is performed for each benchmark problem and, in most cases, the scalability of the code appears reasonable up to approx. 103 cores. Profiling of the benchmark problems indicate that the most substantial computational time is being spent on particle-particle force calculations, drag force calculations and interpolating between discrete particle and continuum fields. Hardware performance analysis was also carried out showing significant Level 2 cache miss ratios and a rather low degree of vectorization. These results are intended to serve as a baseline for future developments to the code as well as a preliminary indicator of where to best focus performance optimizations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Mathematical Formulation used by MATLAB Code to Convert FTIR Interferograms to Calibrated Spectra

This report discusses the mathematical procedures used to convert raw interferograms from Fourier transform infrared (FTIR) sensors to calibrated spectra. The work discussed in this report was completed as part of the Helios project at Los Alamos National Laboratory. MATLAB code was developed to convert the raw interferograms to calibrated spectra. The report summarizes the developed MATLAB scripts and functions, along with a description of the mathematical methods used by the code. The first step in working with raw interferograms is to convert them to uncalibrated spectra by applying an apodization function to the raw data and then by performing a Fourier transform. The developed MATLAB code also addresses phase error correction by applying the Mertz method. This report provides documentation for the MATLAB scripts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Simulation of IST Turbomachinery Power-Neutral Tests with the ANL Plant Dynamics Code

The validation of the Plant Dynamics Code (PDC) developed at Argonne National Laboratory (ANL) for the steady-state and transient analysis of supercritical carbon dioxide (sCO2) systems has been continued with new test data from the Naval Nuclear Laboratory (operated by Bechtel Marine Propulsion Corporation) Integrated System Test (IST). Although data from three runs were provided to ANL, only two of the data sets were analyzed and described in this report. The common feature of these tests is the power-neutral operation of the turbine-compressor shaft, where no external power through the alternator was provided during the tests. Instead, the shaft speed was allowed to change dictated by the power balance between the turbine, the compressor, and the power losses in the shaft. The new test data turned out to be important for code validation for several reasons. First, the power-neutral operation of the shaft allows validation of the shaft dynamics equations in asynchronous mode, when the shaft is disconnected from the grid. Second, the shaft speed control with the compressor recirculation (CR) valve not only allows for testing the code control logic itself, but it also serves as a good test for validation of both the compressor surge control and the turbine bypass control actions, since the effect of the CR action on the loop conditions is similar for both of these controls. Third, the varying compressor-inlet temperature change test allows validation of the transient response of the precooler, a shell-and-tube heat exchanger. The first transient simulation of the compressor-inlet temperature variation Test 64661 showed a much slower calculated response of the precooler in the calculations than the test data. Further investigation revealed an error in calculating the heat exchanger tube mass for the PDC dynamic equations that resulted in a slower change in the tube wall temperature than measured. The transient calculations for both tests were done in two steps. The first step was done in the same fashion as the FY15 IST analysis, where the CR valve position and the turbine-compressor shaft speed were specified through the PDC input based on the test values. On the second step, the turbine-compressor shaft dynamics equations were invoked by specifying that the shaft is disconnected from the grid. In addition, the CR valve control was used to control the shaft speed, based on the turbine bypass control logic already implemented in the PDC. For the shaft power balance, the friction (windage) loss is calculated based on the shaft balance at the steady-state conditions and is assumed to be scaled to the third power of shaft speed in the transient. Both the steady-state and transient simulations of both tests showed good agreement with the test data. The only significant difference was the turbine performance, which was not predicted as well as it was in the previous IST simulation, resulting in the prediction of a somewhat different flow split between the two turbines. This flow split difference is believed to be the result of not addressing the recent turbine modifications in the model. In addition, the full simulation of the turbine-compressor speed variation Test 65261-P with shaft speed control showed greater a difference with the test data later in the transient than the other test. Further analysis of the results revealed that this difference is most likely due to scaling the shaft windage losses only with the shaft speed and ignoring its dependency on the fluid density in the shaft cavity. Based on the results of steady state and transient calculations of the Tests 64661 and 65216-P, several areas of future improvements for the PDC simulation of the IST are identified.

42 ENGINEERING↗
DOE OSTI2017

RAZORBACK - A Research Reactor Transient Analysis Code Version 1.0 - Volume 3: Verification and Validation Report.

This report describes the work and results of the verification and validation (V&V) of the version 1.0 release of the Razorback code. Razorback is a computer code designed to simulate the operation of a research reactor (such as the Annular Core Research Reactor (ACRR)) by a coupled numerical solution of the point reactor kinetics equations, the energy conservation equation for fuel element heat transfer, the equation of motion for fuel element thermal expansion, and the mass, momentum, and energy conservation equations for the water cooling of the fuel elements. This V&V effort was intended to confirm that the code shows good agreement between simulation and actual ACRR operations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Modification of the SAS4A Safety Analysis Code for Integration with the ADAPT Discrete Dynamic Event Tree Framework.

It is difficult to assess the consequences of a transient in a sodium-cooled fast reactor (SFR) using traditional probabilistic risk assessment (PRA) methods, as numerous safety-related sys- tems have passive characteristics. Often there is significant dependence on the value of con- tinuous stochastic parameters rather than binary success/failure determinations. One form of dynamic PRA uses a system simulator to represent the progression of a transient, tracking events through time in a discrete dynamic event tree (DDET). In order to function in a DDET environment, a simulator must have characteristics that make it amenable to changing physical parameters midway through the analysis. The SAS4A SFR system analysis code did not have these characteristics as received. This report describes the code modifications made to allow dynamic operation as well as the linking to a Sandia DDET driver code. A test case is briefly described to demonstrate the utility of the changes.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2017

Sensitivity Analysis and Uncertainty Quantification for the LAMMPS Molecular Dynamics Simulation Code

We examine sensitivity analysis and uncertainty quantification for molecular dynamics simulation. Extreme (large or small) output values for the LAMMPS code often occur at the boundaries of input regions, and uncertainties in those boundary values are overlooked by common SA methods. Similarly, input values for which code outputs are consistent with calibration data can also occur near boundaries. Upon applying approaches in the literature for imprecise probabilities (IPs), much more realistic results are obtained than for the complacent application of standard SA and code calibration.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Tri-Lab Co-Design Milestone: In-Depth Performance Portability Analysis of Improved Integrated Codes on Advanced Architecture.

This milestone is a tri-lab deliverable supporting ongoing Co-Design efforts impacting applications in the Integrated Codes (IC) program element Advanced Technology Development and Mitigation (ATDM) program element. In FY14, the trilabs looked at porting proxy application to technologies of interest for ATS procurements. In FY15, a milestone was completed evaluating proxy applications in multiple programming models and in FY16, a milestone was completed focusing on the migration of lessons learned back into production code development. This year, the co-design milestone focuses on extracting the knowledge gained and/or code revisions back into production applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Debugging Computer Code [Slides]

Debugging? Klingons do not debug. Our software does not coddle the weak. For the rest of us, finding and removing defects in code is a fundamental programming skill. Besides preventing code from performing its intended function, bugs destroy users’ confidence in the reliability of code even when no errors are obvious. A through discussion of debugging techniques could easily fill a semester course in computer science. We have an hour here today. I will take that time to discuss broad principles rather than fine points of debugging.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Software Requirements for a Point Kinetics Neutronics Code for Simulating TREAT Reactor Transients

This document provides the software requirements for a computer code to perform point kinetics-based simulations of nuclear reactor transients. These requirements address all aspects of code development and use, including input and output parameters and structure, software capabilities, and supporting documentation. This software is intended to replace the existing point kinetics code TREKIN, which is currently used for the analysis of the Transient Reactor Test Facility (TREAT).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Development of ASME Division 5 Code proposal on temperature limits for simplified design methods

This report establishes proposed upper temperature limits for the ASME BP&V Code Section III, Division 5, Nonmandatory Appendix HBB-T design by elastic analysis provisions for bounding ratcheting strain and creep-fatigue damage in Class A high temperature nuclear reactor components. Limitations on the use of these design options are required because the design by elastic analysis methods rely on bounding theories that assume a non-unified, decoupled model of creep-plasticity. However, at high temperatures creep and plastic deformation become coupled and bounding theorems relying a decoupled material response may fail. The report describes a method for selecting appropriate upper temperature limits, demonstrates directly through a comparison to full inelastic simulations that the existing Code provisions can be nonconservative at high temperatures, and develops the requisite Code language required to implement the temperature limits in Section III, Division 5.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Construction of an Object-Oriented Interface to an Enhanced EGS Monte Carlo Code

The version of SLAC’s EGS Code System (known as EGS4) was clearly recognized throughout the world as a “gold standard” for solving physics and engineering problems related to the transport of electrons and photons in any element, compound, or mixture. However, EGS4 was written in a computer language called Mortran3 and the learning curve for this rather obscure language was difficult and steep. One major objective of this project was to convert the EGS4 Mortran3 coding into Fortran77, making it much simpler for first-time users to understand and appreciate. In addition, since the introduction of EGS4 in 1985, a number of enhancements in electron-photon transport, as well as a growing need for additional physics processes, had been developed, and the new code (called EGS5) would incorporate more than 20 of these improvements. Of course, many key benchmark simulations had to be made during its development in order to prove that EGS5 was just as credible as its predecessor, EGS4. All of the above was tasked to SLAC, with outside support coming from colleagues at the University of Michigan (Nuclear Engineering Department) and at the High Energy Accelerator Research Organization (KEK) in Japan.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

MC 2 -3: Multigroup Cross Section Generation Code for Fast Reactor Analysis Nuclear

The MC 2 -3 code is a Multigroup Cross section generation Code for fast reactor analysis, developed by improving the resonance self-shielding and spectrum calculation methods of MC 2 -2 and integrating the one-dimensional cell calculation capabilities of SDX. The code solves the consistent P1 multigroup transport equation using basic neutron data from ENDF/B data files to determine the fundamental mode spectra for use in generating multigroup neutron cross sections.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

H2OI95: A Stand-Alone Fortran Code for Evaluating the IAPWS-95 Equation-of-State Model for Water

H2OI95 is a stand-alone Fortran code for evaluating the IAPWS-95 equation-of-state model (Wagner and Pruss, 2002) for the thermodynamic properties of water. It further evaluates the corresponding thermochemical properties of water consistent with the CODATA recommendations (Cox et al., 1989). The IAPWS-95 model is based on a model equation for the dimensionless Helmholtz energy for which the primary variables are the inverse reduced temperature (τ = T cr /T) and reduced density ( δ= ρ/ρ cr ). Here T is the absolute temperature (K), ρ is density (kg/m 3 ), and the subscript “cr” refers to the critical point of water (647.096 K and 22.064 MPa pressure in this model, for which ρ cr is 322 kg/m 3 ). The code solves four basic types of problems, distinguished by the specified inputs: 1, Temperature (K) and density (ρ kg/m 3 ) or reduced density (δ) 2. Temperature (K) and pressure (MPa). 3. Temperature (K) on the saturation (liquid-vapor equilibrium) curve 4. Pressure (MPa) on the saturation curve Each type of problem is run using a corresponding input (text) file. All but the first type of problem require iteration. For example, to solve for desired temperature and pressure, the reduced density must be adjusted to give the desired pressure. Iteration is accomplished using the Newton-Raphson method, though the secant method is also used in solving the fourth type of problem. H2OI95 has been used to conduct numerical studies of convergence and the problem of multiple numerical solutions, only some of which correspond to valid results. Obtaining valid results depends mainly on appropriate choice of starting values. The default values in H2OI95 appear to consistently lead to generally desired results. With modification (not addressed here), H2OI95 can be used to support SUPCRT92 (Johnson et al., 1992) and similar codes that compute chemical thermodynamic properties of species and reactions over a wide range of temperature and pressure (273.16-1273K and 0-1000 MPa).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Relative Credits for Extra Efficiency Code Measures

Energy codes have traditionally contained mandatory and prescriptive items. Mandatory measures must be complied with in all situations while prescriptive measures can be traded with other efficiency measures by following a performance path. Recent editions of the International Energy Conservation Code (IECC) also contain additional efficiency packages, where one or more optional measures must be selected to satisfy an ‘additional’ efficiency requirement. Such a structure is currently employed in section C406 of the IECC, and similar approaches have been considered for ASHRAE Standard 90.1 as well as state building codes. This approach has the advantage of providing increasing levels of performance, while maintaining flexibility in allowing the designer to optimize the most appropriate technologies and efficiency measured based on the attributes of a particular project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗