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An economic model was developed that incorporates spatially varying joint yield and price distributions for the multiple crop choices a farmer faces when choosing between conventional and bioenergy crops. The model is developed in Matlab, and has options for no, annual and upfront payment results.
This data package contains input files and simulation results for a two-dimensional (2D) reactive transport model used to quantitatively analyze the coupled hydrological and biogeochemical processes governing shale weathering and associated biogeochemical fluxes under realistic environmental conditions in the high-elevation East River Watershed. These data support the conclusions presented in Stolze et al. (Water Resources Research, under review), "Model-based interpretation of solute exports and carbon partitioning during shale weathering in a mountainous hillslope". The model simulates atmospheric-subsurface gas exchange, subsurface water flow, and shale weathering processes under dynamic, year-scale conditions along a shale-underlain hillslope located in the East River watershed. The simulations were performed using the PFLOTRAN flow and reactive transport code and executed on the Perlmutter supercomputer to leverage its large-scale parallel computing capabilities. The data package contains two zipped folders, "model_input_files" and "simulation_results", and one readme.txt file. "model_input_files" contains the necessary input files to run the calibrated base-base model presented in Stolze et al. (Water Resources Research, under review). "simulation_results" contains a single hdf5 file ("Output_2D_hillslope_model.h5") which includes the results of simulation performed using the base-case model. This file can be opened with HDFView 3.1.4, Python, or MATLAB. "readme.txt" contains relevant information about the base-case model and provides guidelines on how to run the associated input files provided in the folder "model_input_files". Furthermore, readme.txt provides information regarding the model results provided in "Output_2D_hillslope_model.h5" such as matrix dimensionality and output units. Field datasets used to evaluate model performance were collected at three monitoring wells located along a hillslope transect (PLM1, PLM2, and PLM3). Dissolved ion concentration data were collected from November 2016 to October 2021 for Ca, Mg, DIC, Na, K, SO4 (Dong et al., 2025 - dic_npoc_data_2014_2024.zip - DOI:10.15485/1660459; Williams et al., 2025 - anion_data_2014_2024.zip - DOI:10.15485/1668054; Dong et al., 2025 - cation_data_2014_2024.zip - DOI:10.15485/1668055). Note that we used the files named er_PLM1_xx_yy, er_PLM2_xx_yy, and er_PLM3_xx_yy where xx stands for the name of the aqueous species and yy stands for the depth where the measurements were performed. Soil water content ([0 - 1] m) and water table depth were collected from November 2016 to October 2021 (Wan et al., 2024 - Dynamic_water_table__depthsFig2b.csv and Soil_water_content_Fig4e.csv - DOI:10.15485/2322567). Gaseous CO2 concentration were collected from October 2020 to December 2021(Wan et al., 2024 - Soil_CO2_concentrations_Fig4h.csv - DOI:10.15485/2322567) Gaseous CO2 flux from the subsurface to the atmosphere were collected in the vicinity of PLM2 from October 2019 to May 2022 (Wu et al., 2025). Soil microbial biomass concentration was measured from August 2016 to June 2017 (Sorensen et al., 2019 - 2017_East_River_Pumphouse_Microbial_Biomass__1_.csv - DOI:10.15485/1577267) All field data are published as CSV files compatible with Microsoft Excel, MATLAB, and Python, or as text files. The coordinates of the monitoring wells and the CO2(g) flux sensor in the coordinate system WGS84 are: -PLM1: [38.9197710 ; -106.9492750] -PLM2: [38.9201580 ; -106.9487170] -PLM3: [38.9207843 ; -106.9483668] -PLM4: 38.9210060 ; -106.9479528] -CO2(g) flux sensor: [38.9199180 ; -106.9489906] ------------------------------------------------------------------------------------------- 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. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy User Facility using NERSC award BER-ERCAP 23980, BER-ERCAP 28550, and BER-ERCAP 33789.
This dataset contains processed data from a combination of survey flux chambers and long-term automated flux chambers. Soil flux measurements were conducted from June 2023 through December 2025 in a mature longleaf pine forest in Georgetown, SC. Soil respiration measurements were conducted approximately biweekly for two and a half years, before and after a root exclusion that took place on May 5, 2024. Processed, QAQC’d data for the treatment (root exclusion) and control (roots intact) before and after the root exclusion can be found in the file: 1_DATA_ESS_DOE_HR_RS_HB2_QAQC_Survey_Data_20260223.csv. Two multiday deployments were also conducted prior to the root exclusion using long-term automated chambers to continuously monitor greenhouse gas soil efflux. Processed, QAQC’d data for both long-term deployments can be found in the file: 2_DATA_ESS_DOE_HR_RS_HB2_QAQC_Longterm_Data_20260209.csv. Raw and working data files (.json, .81x, & .82z format) from LI-COR equipment are included for reference and can be accessed using SoilFluxPro software. CSV metadata files describe the raw data and modifications made using SoilFluxPro v5 and Matlab R2024b, as well as formatting and units for processed CSVs. Matlab code is included for reading in the processed CSVs, with sample figures comparing treatment and control. This research was performed as part of the project: “Improving models of stand and watershed carbon and water fluxes with more accurate representations of soil-plant-water dynamics in southern pine ecosystems”, which examines in part the effects hydraulic redistribution on soil efflux of carbon dioxide, water vapor and methane, as well as soil moisture and temperature in a southern pine ecosystem with sandy soils and high water table.
This dataset contains processed data from a combination of survey flux chambers and long-term automated flux chambers. Biweekly soil flux measurements were conducted from June 2023 through December 2025 at a longleaf pine restoration site in Georgetown, SC. Processed, QAQC’d data can be found in the file: 1_DATA_ESS_DOE_HR_RS_HB3_QAQC_Survey_Data_20260223.csv. Raw and working data files (.json, & .81x format) from LI-COR equipment are included for reference and can be accessed using SoilFluxPro software. CSV metadata files describe the raw data and modifications made using SoilFluxPro v5 and Matlab R2024b, as well as formatting and units for processed CSVs. Matlab code is included for reading in the processed CSVs. This research was performed as part of the project: “Improving models of stand and watershed carbon and water fluxes with more accurate representations of soil-plant-water dynamics in southern pine ecosystems”, which examines in part the effects hydraulic redistribution on soil efflux of carbon dioxide, water vapor and methane, as well as soil moisture and temperature in a southern pine ecosystem with sandy soils and high water table.
We developed a simplistic physics-based model of an all-optical neural network that mimics the encoder part of an autoencoder neural network for image compression. Our approach relies on the generation of a MATLAB-based model for both data compression and decompression and utilizes MATLAB's built-in autoencoder networks in combination with simple propagation of optical fields between layers constituting phase elements via Fourier transform. We optimize the phase elements using the particle swarm optimization technique and using our model, we demonstrate a compression ratio of 25% for 2828-pixel input images containing numeric digits from 0 to 9.
Pumped Storage Hydropower (PSH) is one of the most popular energy storage technologies in the world. It uses an upper reservoir to store water which can be later used during high-demand. In the United States, most of the energy storage capability actually corresponds to PSH. Moreover, PSH also brings multiple benefits to grid operation. This report presents the Simulink models of three common PSH technologies: Fixed-Speed (FS), Variable-Speed (VS), and Ternary (T)-PSH. These models are available to the general public on this GitHub repository, which contains the MATLAB model initialization files, the Simulink model files, and supplementary MATLAB code used to obtain the figures in this work. For each PSH model, an introductory description of the model components and other relevant functionalities are provided. For further information regarding the models and the initialization parameters, the reader is referred to the shared files in the repository. This report also presents the dynamic behavior of each model. The response of such models to a load event is analyzed and matched with each model's features. A custom IEEE 39 bus case is employed for the FS and T-PSH simulations, while the VS-PSH is simulated on a simplified three-bus test system due to the computational complexity of the model. For the T-PSH, the steady-state and the switching between several operating modes are also studied in this work.
This report summarizes the current progress in the development of a phenomenological model of aerosol transport, deposition, and plugging through microchannels. The purpose is to introduce a generic, reliable numerical model for the prediction of aerosol transport, deposition, and plugging in leak paths while accounting for potential plugging formation, to a user community involving researchers, regulators, and industry. In that regard, a Graphical User Interface (GUI) was generated by integrating the individual MATLAB scripts that make up the model and adding additional features to aid the general understanding of the problem to a user. This report focuses on the model development and features included. Further, predictions from the GUI are compared with experimental data for validation. The strength of the GUI is the ability of a user to plug in basic parameters such as the initial pressure conditions and canister model specifications in order to obtain a first principal approximation of vital information such as the blowdown pressure differential, aerosol penetration, and deposition as a function of time. The user can obtain this without the know-how of the underlying MATLAB scripts and thus enables the model to be readily applied by regulators, industry, and shareholders to reduce the uncertainty in the off-site radiological consequences. The report also lists future tasks under this work scope. This includes ongoing efforts to include additional crack geometries (divergent and divergent-convergent slots) to the model; GUI development and improvement based on feedback from users, and integration of aerosol source term data from Sibling Pin tests into the model as we approach realistic canister stress corrosion cracking–induced aerosol release scenarios.
I worked on two projects during my summer internship at Sandia. My official title was “Intern - Mission Tech Electrical Eng./Computer Eng.- R&D Undergraduate Summer.” I worked at the central location, which is Albuquerque, New Mexico. The department you are placed in at Sandia doesn’t always correspond to the people you will be working with. For example, I only directly worked with one person from my department this summer. On one of my projects, I worked with a diverse team of engineers from many different departments. On my other project, I mainly worked with two departments, as the project had two distinct parts. As mentioned earlier, I worked on two projects during my summer at Sandia. The first project focused on a lightweight embedded controller in an advanced FPGA System-on-Chip for radar signal processing applications. The term “controller” refers to a hardware device that directs the flow of data between two entities. An FPGA is a reprogrammable integrated circuit (as opposed to an integrated circuit with one purpose). An FPGA was used on this project so in order to protype various ideas for our System-on-Chip. My role on the project was to implement designs on the fabric of the FPGA and design a state machine (written in C) for the processor. My second project was also heavily involved with embedded systems but had a different application. It focused on using a Newton-Raphson control algorithm to stabilize an inverted pendulum using a novel microcontroller. The pendulum dynamics were derived, and it was successfully simulated in MATLAB. I worked on integrating the microcontroller with the inverted pendulum machinery, and converting the Newton-Raphson control algorithm from MATLAB into C. The inverted pendulum was successfully stabilized using a simple PID controller and industry-standard microcontroller. The project is still ongoing, and the team is gearing up for more tests using the novel Newton-Raphson control algorithm and novel microcontroller
Latimer Controls, Inc. was awarded two vouchers under the Department of Energy's American-Made Solar Prize Round 6 to conduct collaborative research at a national laboratory. The National Renewable Energy Laboratory (NREL) was selected as a partner to assist Latimer Controls in the performance evaluation of its photovoltaic (PV) control software. This collaboration focuses on developing a hardware-in-the-loop (HIL) testbed at NREL, which will be used to test and validate the Latimer PV control technology in a realistic yet de-risked environment. Both Latimer and NREL teams will work together to analyze the collected test data, derive insights, and disseminate the scientific findings. Recent studies underscore the potential of solar energy as a zero-marginal-cost and zero-emission flexibility resource within the bulk power system, particularly when integrated with advanced control systems. To enhance the performance of such systems, Latimer Controls has developed leading-edge technologies, including machine learning (ML) algorithms and hierarchical inverter set-point allocation methods. These innovations are designed to estimate the operational headroom of large PV plants for grid integration and control. However, comprehensive validation under real-world conditions remains necessary. To address this gap, the concurrent CRADA project proposes the real-world application and validation of the Latimer Control solution within a HIL environment. Initially, the Latimer algorithm was developed and tested within MATLAB Simulink, a platform suitable for research-level simulations and iterative development. However, transitioning this technology to a real solar site as an industry-ready solution necessitates implementation in a format compatible with widely used solar power plant controllers. In this additional CRADA work, the MATLAB Simulink-based logic will be translated into Structured Text, a programming language compliant with IEC 61131 standards, which is commonly used for custom logic implementations in industry-leading programmable logic controllers (PLCs), such as the Schweitzer SEL real-time automation controller (RTAC). This transition will facilitate the deployment of the Latimer Control solution in real-world solar power plants, thereby advancing the technology towards commercialization.
This dataset consists of soil temperature time series that were used to estimate soil thermal diffusivity and its uncertainty trough the probabilistic modelling approach developed and presented in the article named "Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series" and published in Earth Surface Dynamics. There are two compressed (.zip) files that contains synthetic (Synthetic_soiltemp_Teller.zip) and field (Field_soiltemp_Teller.zip) data. There is one MATLAB file that requires MATLAB to execute but any text editor can open it. The Synthetic_soiltemp_Teller.zip file includes 5 comma-delimited data files (.csv) each of which contains soil temperature time series generated through forward modeling (i.e., heat-conduction process in a heterogeneous medium using an explicit finite difference method) to mimic various types of temperature gradients, trend and fluctuations. These synthetic soil temperatures were used to investigate the impact of different environmental conditions on the uncertainty of thermal diffusivity estimates. The Field_soiltemp_Teller.zip file contains 28 comma-delimited data files (.csv) out of which (a) 27 files includes soil temperature time series recorded from 27 temperature probes located in a site along Teller Road about 40 km northwest of Nome, Alaska (64.72°N, 165.94°W), (b) one includes the name and coordinates of the 27 probes. These field soil temperatures were used to infer soil thermal diffusivity at numerous locations and depths in a discontinuous permafrost environment, and to evaluate the links between the estimated soil thermal diffusivity values and soil physical properties. The comma-delimited data files (.csv) of the synthetic and field soil temperature time series includes date and time (UTC) in the first column and soil temperature from 5 cm below the ground surface to 1.05 m depth (with 5 or 10 cm spacing between sensors) in the other columns. The measurements were acquired every 15 minutes. 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).
This repository includes data and code to accompany the manuscript 'Topography controls variability in circumpolar permafrost thaw pond expansion' by Abolt et al. The data include satellite imagery and derived maps of thermokarst pools from twenty-seven survey areas in North America and Siberia. The code, written in MATLAB (R2021a), contains demonstrations of the workflow for generating the maps. The demonstrations include training a generalized UNet for mapping thermokarst pools using data from three survey areas, 'fine tuning' the UNet for use at a specific survey area using transfer learning, applying a trained UNet to infer thermokarst pool extent within satellite imagery, and performing histogram matching as a pre-processing step to improve satellite imagery contrast. Contains MATLAB script files and M files, TIF files, shape files, XML, Excel, TXT, and CSV files.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).
A coupled physics problem consisting of radiation transport and heat transfer was modeled using COMSOL Multiphysics to simulate a criticality accident. Reduced order models (ROM) were created to accelerate the radiation transport calculation through Proper Orthogonal Decomposition (POD). Additionally, on-the-fly neutron cross sections were generated from a non-linear function through a feed forward neural network. The Livelink for MATLAB module allowed for data transfer between an otherwise independent solver and in-house modules. A data driven approach to POD was developed to act as a surrogate model to couple with heat transfer, with the POD module written in MATLAB coupled to an isolated heat transfer solve in COMSOL. A coupled transient solution resulted in a good approximation of the flux and temperature, with the maximum error being 3E-2 and 2.5E-3 respectively.
This paper presents a molten salt reactor (MSR) design parameter sensitivity study using a nodal dynamic modelling methodology with explicitly modified point kinetics equation and Mann’s model for heat transfer. Six parameters that can impact MSR safety are evaluated. A MATLAB-Simulink model inspired by Thorcon’s 550MW th MSR is used for parameter evaluations. A safety envelope was formed to encapsulate power, maximum and minimum temperature, and temperature-induced reactivity feedback. The parameters are perturbed by ±30%. The parameters were then ranked by their subsequent impact on the considered safety envelope, which ranks acceptable parameter uncertainty. The model is openly available on GitHub.
Interferometry is one of the most sensitive and successful diagnostic methods for plasmas. However, owing to the design of most common interferometric systems, the wavelengths of operation and, therefore, the range of densities and temperatures that can be probed are severely limited. Talbot–Lau interferometry offers the possibility of extending interferometry measurements to x-ray wavelengths by means of the Talbot effect. While there have been several proof-of-concept experiments showing the efficacy of this method, it is only recently that experiments to probe High Energy Density (HED) plasmas using Talbot–Lau interferometry are starting to take place. To improve these experimental designs, we present here the Talbot-Interferometry Analyzer (TIA) tool, a forward model for generating and postprocessing synthetic x-ray interferometry images from a Talbot–Lau interferometer. Although TIA can work with any two-dimensional hydrodynamic code to study plasma conditions as close to reality as possible, this software has been designed to work by default with output files from the hydrodynamic code FLASH, making the tool user-friendly and accessible to the general plasma physics community. Here, the model has been built into a standalone app, which can be installed by anyone with access to the MATLAB runtime installer and is available upon request to the authors.
Abstract Burnup estimation in nuclear fuels is vital for evaluating fuel performance, transportation, and safe fuel storage. Accurate assessments of burnup from service period and spent fuels involve tracking the consumption of fissile isotopes of uranium (U) offering a direct insight into energy changes within the fuels especially for thermal spectrum reactors. In current approach, mass spectroscopic technique in atom probe tomography (APT) is utilized for accurate quantification of U isotopes. Quantification of U peaks in mass spectrum is performed on asymmetric shapes due to delayed signals, known as thermal tails, particularly for poorly conducting samples analyzed in laser mode. In this study, we introduce a novel quantification tool for isotopic analysis from APT datasets by developing a fitting algorithm based on shapes of the peaks. A MATLAB-based dynamic peak fitting toolbox is developed and designed to adapt to various peak shapes, ensuring accurate quantification of U isotopes. The effectiveness of this approach is demonstrated in standard Ni-Cr sample, depleted and enriched U samples, and U-based fuels with different burnup levels. The viability of this approach for isotopic quantification is demonstrated on both metallic and ceramic fuels.
This paper presents a combined full-wave and circuit-based simulation study to investigate the important topic of cable insulation aging and physical damage. The analysis employs the time-frequency domain reflectometry (TFDR) technique that combines the advantages of both time domain reflectometry (TDR) and frequency domain reflectometry (FDR) for improved location identification and feature resolution. Coaxial cable sections with a location containing insulation aging or physical damage are simulated using Ansys High Frequency Structure Simulator (HFSS). Simulated scattering (S) parameters are then imported into the Advanced Design System (ADS) solver for time domain simulation where a Gaussian windowed chirp signal or ‘chirplet’ is launched. Finally, continuous wavelet transform (CWT) is applied in MATLAB to perform time-frequency analysis of the reflected waveforms. The results reveal that a small change in the relative permittivity of the insulation or the presence of a small point of physical damage on the insulation is reflected as a considerable change in the CWT magnitude demonstrating the efficacy of the method.
This dataset encompasses simulations of strain signatures from both hydraulically connected and "near-miss" fractures in enhanced geothermal systems (EGS). The files and results are presented from the perspective of digital acoustic sensing's (DAS) potential to differentiate the two fracture types. This dataset was acquired by the FOGMORE R&D project (Fiber Optic Geophysical MOnitoring of Reservoir Evolution), under Utah FORGE R&D Project 3-2417. Included are simulation and results via MatLab and COMSOL files, as well as a thesis and paper summarizing the results. Some stimulated fractures may be incomplete, approaching but not intersecting the production well. These "near-miss" fractures can be addressed in future stimulation stages or re-stimulated to complete the connection. We propose the use of fiber optic distributed acoustic sensing (DAS) as a method by which near-miss stimulated fractures may be identified and distinguished from hydraulically connected fractures. The low-frequency sub-nanostrain signatures of both complete and near-miss fractures in DAS data are simulated in this study using a hydrogeomechanical discrete fracture network model. The spatial distribution of strain was found to be an accurate indicator. However, this indicator must be evaluated in the context of DAS gauge length and spatial sampling. These simulations are a precursor to tests conducted at FORGE in 2023.
Included are experimental data recorded from shear experiments that specifically explore the link between fluid-injection rate and seismic moment resulting from shear reactivation of laboratory faults. Raw mechanical data from three experiments are included alongside corresponding MATLAB scripts that import and plot the data, as well as use it to calculate shear and normal stress. Experiments are performed on 2.5-3 inch long granitoid cores from the Utah FORGE EGS demonstration site, containing a single inclined fracture with small-scale roughness added to the fracture surface. The raw data included here were recorded from an aluminum triaxial pressure vessel (TEMCO) configured with three independent servo-controlled pumps, with distilled water used as the working fluid. The pumps control confining pressure, upstream pore pressure, and axial pressure, with each pump connected to a LabView interface to record applied pressures, cumulative injected water volumes, and pump flow rates. The downstream outlet from the fracture is closed to allow pressurization, which is measured by an external pressure transducer. A linear variable differential transformer (LVDT) attached to the axial piston measures axial displacement, from which we calculate shear displacement along the fracture. Additionally, P-wave transducers are used to record acoustic signatures, where acoustic emission events and maximum amplitudes are compared against seismic moment and shear slip velocity. Fluid injection rates range between 0.05 mL/min, 0.25 mL/min, and 0.75 mL/min for each experiment. Along-fault pressure distributions are progressively less uniform as injection rates increase, representing a switch from steady-state to transient conditions. Triggered shear displacement is used as a proxy for seismic moment and is indexed against cumulative injection volume and rate. Each experiment is performed under constant shear stress conditions, and the sample is fully saturated with DI water. Axial and confining stresses are applied to 3 MPa through pressure-stepping in 500 kPa increments. The pore pressure is held constant at 200 kPa prior to initiating the experiment, and initial axial displacement is recorded. The axial stress is then increased to initiate shear mobilization during the loading phase (run-in) until a peak steady state is achieved. The initial shear stress is reduced to approximately 80% of the peak shear stress by decreasing the axial stress, then held constant for the duration of each experiment.