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At least 397 records · Page 22

Surface Water Quality Data from Beaver-Impacted Streams; Trail Creek and East River, Colorado 2025

This data package contains surface water chemistry measurements collected in 2025 to evaluate how beaver damming and low-tech process-based stream restoration influence water quality and metal mobility in mountainous headwater systems of the Upper Colorado River Basin. Sampling was conducted at Trail Creek (Taylor Park watershed, Colorado), a tributary undergoing restoration through installation of low-tech process-based structures (i.e., beaver dam analogs), and at off-channel beaver ponds within the East River floodplain (East River watershed, Colorado). Samples were collected along longitudinal transects spanning upstream control reaches, beaver-influenced ponded reaches, and downstream segments. Additional samples were collected from near-surface pore waters within a beaver dam seepage face. The dataset includes concentrations of major and trace elements measured by inductively coupled plasma–mass spectrometry (ICP-MS) and inductively coupled plasma–optical emission spectrometry (ICP-OES), major anions measured by ion chromatography (IC), and dissolved organic carbon (DOC; reported as non-purgeable organic carbon, NPOC). Samples were size-fractionated at 0.45 micrometers (µm), 0.22 µm, and 0.02 µm to distinguish particulate (>0.45 µm), colloidal (0.22–0.02 µm), and dissolved (<0.02 µm) fractions. The data package consists of comma-separated value (.csv) files containing tabulated chemical concentration data, sample metadata (site identifiers, geographic coordinates, sampling dates, fraction type), and quality control flags. All files are provided in open, non-proprietary formats that can be accessed using standard data analysis software such as Microsoft Excel, R, Python, MATLAB, or other programs capable of reading .csv files. Units, detection limits, and analytical methods are documented in accompanying metadata files. The dataset is designed to support analyses of (1) how beaver impoundment and restoration structures alter elemental partitioning and transport, (2) the role of iron and organic carbon in mediating trace metal mobility, and (3) reach-scale changes in water quality across restoration gradients. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

Anions↗

Chamber flux measurements at US-ORv located in Columbus, OH from 2010 to 2014

Closed and flow through chamber methane and carbon dioxide flux measurements were taken at different water depths, vegetation cover types, and times of day at the Wilma H. Schiermeier Olentangy River Wetland Research Park (ORWRP) from 2010 to 2014 to investigate the effects of these variables on gas exchange. The ORWRP consists of two urban experimental wetland basins constructed in 1994 within the footprint of the AmeriFlux tower US-ORv that was functional from 2011 to 2016. Chamber measurements are separated into flow through and closed chamber files (flow_through.csv, closed_chamber.csv) with location labels corresponding with coordinates listed in the metadata file (Location_ID.csv). All files are .csv and could be viewed or analyzed with Excel, MATLAB, Python, or R.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC CHEMISTRY↗

Data from: "Towards CONUS-Wide ML-Augmented Conceptually-Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics"

This data package was generated to support the manuscript “Towards CONUS-Wide Machine Learning-Augmented Conceptually Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics.” It provides input files, model outputs, plotting data, scripts, notebooks, and documentation used to develop, evaluate, and reproduce Mass-Conserving Perceptron (MCP)-based hydrologic modeling experiments across 513 selected Catchment Attributes and Meteorology for Large-sample Studies in the United States (CAMELS-US) basins. The files are organized by modeling component and analysis purpose, including rainfall–runoff experiments, snow module experiments, coupled hydrologic-snow experiments, Long Short-Term Memory (LSTM) benchmark results, model skill metrics, initialization and epoch records, cell-state normalization files, Akaike Information Criterion (AIC)-based model comparison files, and data used to generate manuscript figures. Tabular files can be opened using standard spreadsheet software or Python/R data-analysis tools. Python scripts, Jupyter notebooks, and selected MATLAB scripts are included for model execution, postprocessing, plotting, and statistical analysis. Quality assurance and quality control were conducted through the source-data selection and modeling workflow. Meteorological forcing, streamflow, and static catchment attributes were derived from the CAMELS-US dataset, and snow water equivalent data were derived from the University of Arizona (UA) Snow Water Equivalent dataset. Selected basins and time periods were screened during the associated research workflow to avoid missing observations or poor-quality cases. Static geospatial features were processed primarily using Quantum Geographic Information System (QGIS) and Geospatial Data Abstraction Library (GDAL) workflows. Additional details are provided in the associated manuscript and documentation.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗

Field and Model Data Associated with the Manuscript “Drivers of Streamflow Intermittency in Humid Regions: 2. Evaluating Controls on Flow Persistence in an Urbanized Catchment”

This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in an urbanized catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, distributed temperature sensing (DTS), continuous self-potential (SP) monitoring, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Field_Application subfolder contains the ATS XML input scripts, data files, output data for the SP site. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. The flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.m can only be used with COMSOL with MATLAB) is executed using the ATS output data to simulate the potential field. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) DTS Contains collated DTS data including raw Stokes and anti-Stokes measurement (provided as .h5 file). It also includes DTS processing.ipynb, a Jupyter notebook for calibrating the DTS data using dts_calibration Python package. cooler_calibration.csv is the DTS calibration CSV used in the calibration sequence. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion. 6) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 7) SP Contains the SP data collected in field at the SP sites (provided as CSV files). 8) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). Note: Code files (.ipynb, .py, .xml) can be opened in any standard code editor, .exo file can be viewed using Paraview, .h5 files can be opened using HDFView software and h5py Python package, and .resipy file can be opened with the open-source ResIPy software.

ATS↗

Task 5 Field Scale Stress Modeling Scripts and Data

Project data and Matlab scripts for Task 5 of the project “A Non-Invasive Approach for Elucidating the Spatial Distribution of In Situ Stress in Deep Subsurface Geologic Formations Considered for CO2 Storage”. Project includes the static earth models, grids and other data used for simulation and calibration of the two case studies addressed in the project, referred to herein as the “FutureGen2” model (Illinois) and the “Perch” model (Otsego county, Michigan). Large Dataset, please contact EDXSupport@netl.doe.gov

FutureGen2↗

AP4

The NETL-CMU Air Pollution Emissions Experiments and Policy version 4 (AP4) MATLAB to Octave model.

AS↗

Proton pulse charge calculation algorithm in Beam Power Limiting System at Spallation Neutron Source

A proton pulse charge calculation algorithm in the Beam Power Limiting System (BPLS) at the Spallation Neutron Source (SNS) was developed and implemented in an FPGA. The algorithm calculates one-minute running average of the pulse charges and issues a fault to the Personal Protection System (PPS) and the Machine Protection System (MPS) when a limit is reached. A bit-accurate model of the algorithm was first developed and tested in Matlab® and then implemented and simulated in VHDL using Vivado® design environment. Finally, the algorithm was verified on a µTCA-based hardware platform.

Bobrek, Miljko [ORNL] (ORCID:0000000332763451)↗

Prototype HB650 Cryomodule Heat Loads Simulations

During the design stages of the PIP-II cryomodules, many analytical calculations and FEA have been performed on simpler geometry in order to estimate the heat loads and also to optimize the design. To better analyze the cryomodule cold tests, simulations have been performed with MATLAB to determine the temperature of the main components during cool down and to determine the heat loads of the cryomodule. These simulations have been applied to the High Beta 650 MHz prototype cryomodule design and compared to the cold tests performed on it.

43 PARTICLE ACCELERATORS↗

Automatic Calibration of a Geomechanical Model from Sparse Data for Estimating Stress in Deep Geological Formations

Summary In this study, we demonstrate geomechanical modeling with fully automatic parameter calibration to estimate the full geomechanical stress fields of a prospective US carbon dioxide (CO2) storage site, based on sparse measurement data. The goal is to compute full stress tensor field estimates (principal stresses and orientations) that are maximally compatible with observations within the constraints of the model assumptions, thereby extending pointwise, incomplete partial stress measurement to a simulated full formation stress field, as well as a rough assessment of the associated error. We use the Perch site, located in Otsego County, Michigan, USA, as our case study. The input data consist of partial stress tensor information inferred from in-situ borehole tests, geophysical well logs, and processing of seismic data. A static earth model (SEM) of the site was developed, and geomechanical simulation functionality of the open-source MATLAB Reservoir Simulation Toolbox (MRST) was used to model the stress field. Adjoint-based nonlinear optimization was used to adjust boundary conditions and material properties to calibrate simulated results of observations. Results were interpreted through a Bayesian framework. The focus of this paper is to demonstrate how the fully automatic calibration procedure works and discuss the results obtained; it does not attempt a detailed analysis of the stress field in the context of the proposed CO2 storage initiatives. Our work is part of a larger effort to noninvasively determine in-situ stresses in deep formations considered for CO2 storage. Guided by previously published research on geomechanical model calibration, our work presents a novel calibration approach supporting a potentially large number of linear or nonlinear calibration parameters to produce results optimally agreeing with available measurements and thus extend partial pointwise estimates to full tensor fields compatible with the physics of the site.

Engineering↗

QSpace - An open-source tensor library for Abelian and non-Abelian symmetries

This is the documentation for the tensor library QSpace (v4.0), a toolbox to exploit ‘quan tum symmetry spaces’ in tensor network states in the quantum many-body context. QSpace permits arbitrary combinations of symmetries including the abelian symmetries $\mathbb{Z}_n$ and U(1), as well as all non-abelian symmetries based on the semisimple classical Lie algebras: A n , B n , C n , and D n , or respectively, the special unitary group SU(n), the odd orthogonal group SO(2n+1), the symplectic group Sp(2n), and the even orthogonal group SO(2n). The code (C++ embedded via the MEX interface into Matlab) is available open source as of QSpace v4.0 on bitbucket under the Apache 2.0 license. QSpace is designed as a bottom-up approach for non-abelian symmetries. It starts from the defining representation and the respective Lie algebra. By explicitly comput ing and tabulating generalized Clebsch-Gordan coefficient tensors, QSpace is versatile in the type of operations that it can perform across all symmetries. At the level of an ap plication, much of the symmetry-related details are hidden within the QSpace C++ core libraries. Hence when developing tensor network algorithms with QSpace, these can be coded (nearly) as if there are no symmetries at all, despite being able to fully exploit general non-abelian symmetries.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Preliminary Enhanced LAW Glass Formulation Algorithm

This report summarizes the Preliminary Enhanced LAW Glass Formulation Algorithm, its background information, and the calculations it performs. The Preliminary Enhanced LAW Glass Formulation Algorithm is a tool that has been developed in MATLAB to formulate glass at a given a waste composition, while attempting to maximize waste loading. It is intended for use at the Hanford Waste Treatment and Immobilization Plant, where nuclear waste will be vitrified into glass for safe, long-term storage. The formulated glass is required to meet several processing and product quality constraints. In addition, calculations must account for associated uncertainties in constraint prediction and measurement. The algorithm also allows for the ability to hold glass compositions closer to tested regions in order to increase confidence in the output. The algorithm must also follow nuclear quality assurance procedures and submit to rigorous validation and verification testing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Simcenter TestLab Error in uploading reference profiles

Our team exports data from Matlab to a Simcenter TestLab formatted .mat file. The .mat file is then uploaded as a reference profile for Environmental Random Control vibration testing. Operations are applied to the data before export that introduce floating point errors. We are experiencing errors uploading the generated reference profiles if the frequency values have a certain level of floating point error (1 Hz vs 1.000000000000001 Hz). I generated some test cases of reference profiles that were giving us trouble, and outlined the errors we were seeing. Two different errors, depending on how the control frequency range is defined. Error is fixed by copy/pasting the frequency column in the Profile Editor.

97 MATHEMATICS AND COMPUTING↗

Distributed Accelerometer IMU-2: An Interim Development Report

This report details the development of DAIMU-2, a MEMS accelerometer-based Gyro-Free Inertial Measurement Unit (GF-IMU). Previously, a GF-IMU called the Distributed Accelerometer IMU (DAIMU) was developed at LLNL using traditional analog accelerometers. This project leverages the experience gained from DAIMU and recent advances in sensor and embedded systems technology to develop DAIMU-2. The report introduces the theory and mathematics of a GF-IMU, followed by the design of an Unscented Kalman Filter (UKF) and simulation results. Finally, the DAIMU-2 prototypes developed to date are presented. After approximately one year of development work, the project was suspended, to be resumed in the future. Because of this, some efforts were partially completed, and this report attempts to indicate areas where further work is needed. MATLAB files, drawings, and other design documents have been archived for future project resumption.

42 ENGINEERING↗

3D CFD Model Validation Using Benchmark Data of 1/16th Scaled VHTR Upper Plenum and Development of Wall Heat-Transfer Correlation For Laminar Flow

With support from the U.S. Department of Energy-Office of Nuclear Energy’s (DOE-NE’s) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, an effort has been pursued to support high-temperature gas-cooled reactor (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 in the nuclear reactor primary system, especially in the core and the lower and upper plena, during safety-related transients. In this report, two main such activities are presented relevant to the HTGRs: (1) three-dimensional (3D) computational fluid dynamics (CFD) validation using benchmark data from the upper plenum of Texas A&M University’s 1/16th scaled very-high-temperature gas-cooled reactor (VHTR), and (2) development of wall heat-transfer correlation for laminar flow in a wall-heated pipe. The CFD tool validation exercises can be helpful to choose the models and CFD tools to simulate and design specific components of the HTRGs such as upper plenum where jet mixing is a complex phenomenon. In a loss of forced circulation event, the laminar flow can be observed during the development of natural circulation flow. This work includes the development and validation of heat transfer correlations for laminar flow using the Nek5000 CFD code due to limited available experimental data for laminar flow conditions to guide low-order models (1D). In this report, the flow characteristics of a single isothermal jet discharging into the upper plenum was investigated using the Nek5000 Large-Eddy Simulation (LES) CFD tool. Several numerical simulations were performed for various jet-discharged Reynolds numbers ranging from 3,413 to 12,819. A grid-independent study was performed. The numerical results of mean velocity, root-mean-square fluctuating velocity, and Reynolds stress were compared against the benchmark data. Good agreement was obtained between simulated and measured data for axial mean velocities, except near the upper plenum hemisphere. The maximum predicted errors for axial mean velocities at various normalized coolant channel diameter heights of 1, 5, and 10 are 1.56%, 1.88%, and 3.82%, respectively. In addition, the predicted root-mean-square fluctuating velocity and Reynolds stress are qualitatively in agreement with the experimental data. The Nek5000 code was used to develop wall-heat transfer correlation for laminar flow in a cylindrical tube. Several simulations were performed for various Reynolds flow and wall-heat fluxes. A new heat transfer correlation was developed using data from Nek5000 simulation results and regression functions in Matlab. The developed heat transfer correlation is valid for various Reynolds flows from 200 to 2000. The predicted R² value for model fit was 0.875, which ensures that 87.5% of the model data lies on the Nek5000 data. Moreover, a machine learning (ML) tool was used to train and test the Nek5000 data. A good fit of the ML-based model was observed with the test data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Nested Comments in BNFC

Many languages such as Lua, Haskell and MATLAB support the ability to create nested comments. My proposal is to add a nested comment pragma to BNFC which would allow it to support the parsing of code. In this proposal I will provide sample implementations of nested comments for each of the lexer generators used by BNFC and outline the extension points by which I will add the functionality to the codebase.

97 MATHEMATICS AND COMPUTING↗

Oak Ridge National Laboratory Current Magnitude and Frequency Response of SIPROTEC Relays

This project examined the current magnitude and frequency response of 7SJ61 and 7SJ62 SIPROTEC relays. The measured sample frequencies for the 7SJ61 and 7SJS62 relays were 800 and 960 Hz, respectively. The relays were tested at frequencies of up to 1 and 20.16 kHz. Two experiments were run in a lab environment. The first experiment was run at frequencies of up to 1 kHz every 10 Hz. The second one was run at frequencies of up to 20.16 kHz every 200 and 240 Hz (common factors of sample rate frequency) for the 7SJ61 and 7SJ62 SIPROTEC relays, respectively. Both experiments were set at a current magnitude of 0.1 and 0.5 Arms. A testbed with a Relay Test Equipment (RTE) was set to run the experiment at frequencies of up to 1 kHz, while a testbed with a RTE and High Frequency Power Source/ Amplifier (HFPS/A) was set to run at frequencies of up to 20.16 kHz. Currents of 0.1 and 0.5 Arms at different frequencies were connected at Phase A of the relays, and a current of 1 Arms (60 Hz) was connected at Phase B of relays. The 1 Arms current allowed the relays to trip and saved their record events by setting both relays at a definite-time overcurrent protection function. The record events were collected after the 7SJ61 and 7SJ62 relays tripped, and the current magnitude and frequency were plotted. The record events from the relays were collected using the DIGSI® 4 software. The SYNCHROWAVE® Event and MATLAB® software were then used to plot the current magnitude and frequency, respectively, from the relay record events. The current magnitude and frequency were plotted at time and frequency domain, respectively.The 7SJ61 and 7SJ62 relays measured source frequencies of up to 400 and 480 Hz, respectively. The percentage error of frequency for the relays increased after 400 and 480 Hz, respectively. The 7SJ62 relay with 0.1 and 0.5 Arms measured the alias frequency up to 1440 Hz. The 7SJ61 relay with 0.1 and 0.5 Arms measured the alias frequency up to 1000 and 1200 Hz, respectively. At frequencies higher than the alias frequency, the relays measured a DC amplitude current instead of an AC amplitude current. In the DC amplitude current zone, non-desired frequencies were measured by both relays. The current magnitude intensity (dB) for the 7SJ61 and 7SJ62 relays from 1 to 20.16 kHz were plotted. The current magnitude intensity for the 7SJ61 relay decreased up to 2600 and 1200 Hz for 0.5 and 0.1 Arms tests, respectively. However, the current magnitude intensity for the 7SJ62 relay decreased up to 4800 and 2640 Hz for 0.5 and 0.1 Arms tests, respectively. The current magnitude and frequency response study for the 7SJ61 and 7SJ62 relays was performed satisfactorily, observing the source, alias, and non-desired measured frequency zones for both relays.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Integrated Optimization and Control of a Hybrid Gas Turbine/sCO 2 Power System

During phase-I, the project team led by Echogen Power Systems (EPS) had two primary objectives based on investigating the application of gas turbines with supercritical carbon dioxide (sCO 2 ) power cycles. The first objective was to improve the overall efficiency and performance of a hybrid gas turbine/sCO 2 power system through a joint optimization of the two subsystems (gas turbine and sCO 2 power cycle) using non-linear optimization techniques that simultaneously evaluate thermal performance of the combined cycle. The hybrid power system included several points of interaction, including (but not limited to) gas turbine exhaust, fuel heating, inlet chilling and turbine cooling. The second objective was to establish a baseline transient response model of the hybrid power system and a notional microgrid and begin steps to integrate the control systems of the three major elements (gas turbine, sCO 2 cycle and grid controller). The project team established a baseline performance for a combined cycle power plant using a production gas turbine and scaled sCO 2 power cycle only utilizing exhaust heat recovery. Echogen’s non-linear techno-economic optimization code was extended by adding gas turbine component models derived from a in-house developed gas turbine design code. With the two cycles coupled by the gas turbine exhaust, design parameters of both cycles were allowed to vary simultaneously to determine performance opportunity versus isolated designs. Returning to the baseline gas turbine/sCO 2 power cycle transient models: Echogen had in-house developed sCO 2 cycle transient model in GT-Suite system simulation software, and had partnered with Siemens Finspång for gas turbine transient model, and Siemens PTI group to provide micro-grid load profile as well as hybrid power cycle generated load (power and frequency) analysis. The transient model for the SGT-750 Siemens gas turbine was a “black-box” functional mock-up interface (FMI) model developed by Siemens Industrial Turbomachinery in Finspång, Sweden. The SGT-750 is a twin-shaft gas turbine that produces 40 MW electricity with an efficiency of about 40% at ISO conditions. At 100% gas turbine throttle (load), the SGT-750 has average exhaust conditions of 114.6 kg/s and 469.8°C. The transient model for sCO 2 power cycle was developed by Echogen in GT-SUITE 1D system simulation software platform. The basic CO 2 flow circuit has single-shaft turbomachinery with net 11.5 MW electrical power output at design conditions. The power turbine has a double-ended shaft with one end connected to synchronous generator through a fixed-ratio gearbox. The other end of power turbine is connected to the compressor through a continuously variable transmission. The major components of the sCO 2 power cycle modeled include air cooled condenser/cooler, CO 2 compressor, recuperator, two waste heat exchanger coils, power turbine, continuous variable transmission, gearbox and generator. Integration of SGT-750 transient model and sCO 2 power cycle transient model was done in Matlab Simulink. In the integrated model, the gas turbine and sCO 2 power cycle interacted at two points, first one being the gas turbine exhaust gas flow rate and temperature, which were inputs to sCO 2 power cycle model. The second point was the distribution of micro-grid load demand signal between the SGT-750 generator and sCO 2 cycle generator. For a given combined-cycle load demand, the gas turbine load demand was equal to the total demand minus the sCO 2 cycle power generated. In the present study the integrated model was simulated for two cases of grid load demand: (i) for a step change, both positive-step and negative-step, in grid load demand (ii) for a micro-grid load demand curve provided by Siemens PTI group. Finally, the time series plots representing load demand versus integrated system response were presented including the sCO 2 power cycle control system performance plots. The actual generated power and frequency of both the generators, gas turbine and sCO 2 power cycle, was supplied to Siemens PTI group for dynamic grid assessment, results of which are provided in appendices.

03 NATURAL GAS↗

SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking (FY2020 Progress Report)

The development of algorithms for machine learning and data analysis for the 3013 Surveillance Program is a collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). For corrosion detection, Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS) data is extracted from large binary files, with software written to convert the data to physical attributes (e.g. height, color and grayscale values; all as functions of a location in a plane projection). It is the objective of this project to produce a user-friendly interface that incorporated all operations needed to perform surface examination. For this reason, a Matlab-based Graphical User Interface (GUI) was created to integrate data input with software developed for processing and evaluation. In summary, the GUI permits selective downloading of binary data, interrogation of attributes, data labeling, flagging of significant features, execution of Machine Learning (ML) algorithms, output of parameters for trained ML algorithms, reports of ML model accuracy with respect to labeled data, and generation of graphical representations of various analyses.

3013 corrosion↗