SEARCH · Search NASA
Results for “MatLab”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
A cascading failure analysis tool for post processing TRANSCARE simulations
This is a MATLAB-based tool to post process simulation results in the EPRI software TRANSCARE, for massive cascading failure analysis following severe disturbances. There are a few key modules available in this tool, including: 1. automatically creating a contingency list to run TRANSCARE simulations, including substation outages above a certain kV threshold, N-k (1, 2 or 3) generator outages and branch outages; 2. read in and analyze a CKO file of PCG definition, an initiating event list, and a CDN file; 3. post process all the simulation results saved in a CDN file and perform critical event corridor analysis; 4. provide a summary of TRANSCARE simulations; 5. Identify the most frequently occurring event corridors in the system; and 6. Rank the contingencies using a user defined security index to quantify consequences in terms of total load loss, total number of cascades, etc.
slaclab/smurf-matlab-ioc
SLAC's Matlab support IOC Docker image for the SMuRF project.
Learning Planar Ising Models Software
Learning Planar Ising Models is a software package written in Matlab for learning relationships among variable in a dataset using graphical models. The software package implements a generally-applicable algorithm for learning planar Ising models from any multivariate dataset. The code provides an algorithm for learning the best planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. The software includes demonstrations of the algorithm in simulations and for applications on publicly available datasets. Details of the algorithm, demonstration simulations, and applications are given in Johnson, et al; 2016. Reference: Johnson, J. K., Oyen, D., Chertkov, M., and Netrapalli, P. (2016). Learning planar Ising models. Journal of Machine Learning Research.
pnnl/Chemometric_Toolbox
The PNNL Chemometric Toolbox is a software collection of common MATLAB scripts that implement core chemometric algorithms for regression analysis. The three core regression techniques within this toolbox are classical least squares (CLS), principal component regression (PCR), and partial least squares (PLS). This is demonstrated using a supplied dataset of infrared (FTIR) spectral data with their corresponding concentrations
centroid identification from cloud photon-sparse images
A Matlab script that allows the computation of single-photon centroids from photon-sparse cloud images.
Parameter Identification for Battery Abuse Reaction Kinetics Models Using DSC Analysis [SWR-23-87]
This code estimates the parameters as inputs for NREL’s abuse reaction kinetics model using Differential scanning calorimetry (DSC) experimental data. The parameters for calculating the rates of abuse reactions among battery cell components at elevated temperatures include frequency factor, activation energy, and reaction orders. The least-squared method is employed to fit the reaction model to DSC data. The code is implemented in MATLAB.
Generalized Environment for Modeling Systems
GEMS is an integrated environment that allows technical analysts, modelers, researchers, etc. to integrate and deploy models and/or decision tools with associated data to the internet for direct use by customers. GEMS does not require that the model developer know how to code or script and therefore delivers this capability to a large group of technical specialists. Customers gain the benefit of being able to execute their own scenarios directly without need for technical support. GEMS is a process that leverages commercial software products with specialized codes that add connectivity and unique functions to support the overall capability. Users integrate pre-existing models with a commercial product and store parameters and input trajectories in a companion commercial database. The model is then exposed into a commercial web environment and a graphical user interface (GUI) is applied by the model developer. Users execute the model through the web based GUI and GEMS manages supply of proper inputs, execution of models, routing of data to models and display of results back to users. GEMS works in layers, the following description is from the bottom up. Modelers create models in the modeling tool of their choice such as Excel, Matlab, or Fortran. They can also use models from a library of previously wrapped legacy codes (models). Modelers integrate the models (or a single model) by wrapping and connecting the models using the Phoenix Integration tool entitled ModelCenter. Using a ModelCenter/SAS plugin (DOE copyright CW-10-08) the modeler gets data from either an SAS or SQL database and sends results back to SAS or SQL. Once the model is working properly, the ModelCenter file is saved and stored in a folder location to which a SharePoint server tool created at INL is pointed. This enables the ModelCenter model to be run from SharePoint. The modeler then goes into Microsoft SharePoint and creates a graphical user interface (GUI) using the ModelCenter WebPart (CW-12-04) created at INL to work inside SharePoint. The GUI tool links slider bars and drop downs to specific inputs and output of the ModelCenter model that is executable from SharePoint. The modeler also creates in SAS, dashboards, graphs and tables that are exposed by links and SAS and ModelCenter Web Parts into the SharePoint system. The user can then log into SharePoint, move slider bars and select drop down lists to configure the model parameters, click to run the model, and then view the output results that are based on their particular input choices. The main point is that GEMS eliminates the need for a programmer to connect and create the web artifacts necessary to implement and deliver an executable model or decision aid to customers.
Surface Method Raytracer
Matlab based experiments that implement multiple ray tracing methods for deterministic radiation transport, including the Surface Method as described in the PhD Thesis, "CONSERVATIVE FIRSTCOLLISION SOURCE TREATMENT FOR RAY EFFECT MITIGATION IN DISCRETE-ORDINATE RADIATION TRANSPORT SOLUTIONS" by Alex Christensen.
RadSim: Math, Utility & RTK
This package includes three parts, (1) gov.llnl.math, (2)gov.llnl.utility and (3)gov.llnl.rtk, which are utilized in the development of Radiation Detector Simulator (RadSim) project. RadSim is being developed to provide the capability to: (1) simulate radiation source emissions, (2) interpolate results from radiation transport tools into a common format to prepare incident flux, and (3) model radiation detector response to rapidly produce synthetic radiation measurement templates. RadSim is targeted for open-source release, which will enable researchers and industry partners to model gamma-ray detectors response to simulated flux from the transport tool of their choice. The techniques and implementation will be entirely transparent, which will allow for improvements and boutique modifications by future researchers beyond the lifespan of this specific project. The first tool of the package, gov.llnl.math, includes classes and functions to define and perform basic math operations. Some of the example features available in the package include defining statistical distributions and performing algebra and matrix operations, all of which are already accessible on publicly available software packages such as MATLAB and ROOT. The second package gov.llnl.utility includes tools commonly used to enable optimization and readability of various data structures such as Java lists and external xml files. Lastly, the gov.llnl.rtk package includes classes and functions to implement methods commonly used in radiation physics, such as data structures to represent and characterize photon spectra and tools to apply well-defined and published methods to calibrate a given spectra.
Cylindrical battery design app
Software that delivers optimal design parameters and performance predictions for cylindrical cells, which can range in size from microbatteries to EV batteries, is developed. The software utilizes machine learning and includes a graphical user interface to enable rapid prototyping and to accelerate energy storage research, development, and manufacturing. The Cylindrical battery design V1.0 comprises of three types of cylindrical batteries, Microbattery (Primary), Microbattery (Secondary) and 18650/21700/xxxxx Cylindrical battery. The software was developed in MATLAB. The software has the capability to output the cell design with the capacity ranges from several mAh to several million Ah.
pnnl/ZebrafishBMD
ZebrafishBMD: A software tool to perform benchmark dose calculations using toxicity screening data of high-throughput zebrafish assays. High-content imaging of larval zebrafish behavior can be used as a screening approach to rapidly evaluate the relative potential for chemicals to cause toxicity. However, most statistical methods applied to these data transform movement values to incidence-based “hits” and calculate lowest effect levels (LELs), which loses individual fish resolution of behavior and defies hazard ranking due to reliance on applied dose levels. We developed a parallelizable workflow to calculate benchmark dose (BMD) values from dynamic, high-content zebrafish behavior data that scales for high throughput chemical screening. To capture the zebrafish movement response from light to dark stimulus, we summarized time-dependent data using both area under the curve and the immediate change at the transition point into two novel metrics that characterized abnormal behavior as a function of chemical concentration. The BMD workflow was applied to calculate BMD10 values of 1,060 ToxCast chemicals for 24 zebrafish endpoints, including behavior, mortality and morphology. ZebrafishBMD implements the BMD workflow and provides Matlab scripts to read the data (stored in a specific structure) from a .mat file, to calculate the behavioral endpoint values from movement versus time data, to construct concentrationresponse curves, to perform curve-fitting, and to calculate BMD10 values.
JGCRI/hydro-emulator
The hydrological emulator (HE) was built to mimic complex global hydrological models (GHMs) at a range of spatial scales. The HE was written in MATLAB and utilizes a genetic algorithm to calibrate the a, b, c, d, m parameters from the ABCD runoff algorithm to observed runoff from GHMs when forced by the same climate data. The HE employs two methods to choose from when processing basin data: lumped (by basin) and distributed (gridded). Both methods can be evaluated using the built-in Kling-Gupta efficiency as a measure of model performance when compared to the outputs from the more complex GHM. Testing shows that the HE is 7 orders of magnitude faster then the widely used Variable Infiltration Capacity (VIC) GHM.
Fast Combinatorial Nonnegative Least Squares v 1.0
Software that employs an algorithm that rapidly and rigorously solves nonnegative least squares problems with many right hand sides. This is the latest internal version of MATLAB pseudocode that was described in a published in M. H. Van Benthem and M. R. Keenan, "Fast algorithm for the solution of largescale non-negativity-constrained least squares problems," J. Chemom. 18(10), 441-450 (2004). Example code of this algorithm was included in the publication. This algorithm was also patented in M. H. Van Benthem and M. R. Keenan, "Fast combinatorial algorithm for the solution of linearly constrained least squares problems,"USPTO, Ed., Sandia Corporation, USA (2008). SAND2019-10098 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.
DISCO GUI v.1
SAND2024-08619O The DISCO GUI software, written in MATLAB, allows for data calibration for X-ray diffraction work at Sandia National Labs’ Z Machine. The program manually identifies and manipulates images from seven fiber bundles based on a calibration reticle. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Codes for sub-resolution modeling of the apparent mass loss in quantitative broadband X-ray radiography
SAND2022-3463 O This code is intended to accompany the journal manuscript, “Sub-resolution modeling of the apparent mass loss in quantitative broadband X-ray radiography." The manuscript covers in detail how to improve the quantitative mass distribution measurements made for optical diagnostics of multiphase flows. The code contains four separate script files in MATLAB format to support the objective of improving mass measurements. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
yuwangcn/C4_dynamic_model
A dynamic systems model of C4 photosynthesis was developed based on the previous NADP-ME metabolic model for maize (Wang et al., 2014 ab). The NADP-ME metabolic model is an ordinary differential equation model including all individual steps in C4 photosynthetic carbon metabolism. Here, the model is extended to include posttranslational regulation and temperature response of enzyme activities, dynamic stomata conductance, and leaf energy balance. This model is written in Matlab (R2019a) Steady-state and dynamic gas exchange data for maize (B73), sugarcane (CP88-1762) and sorghum (Tx430) were measured in a greenhouse in Urbana, IL from July 25, 2019 through August 8, 2019. Data include: CO2 response curves Light response curves Photosynthetic induction curves measured in the transition from darkness to high light (1800 μmol m-2 s-1), data logged every 1 min. Photosynthetic induction in the transition from darkness to high light (1800 μmol m-2 s-1) to determine the kinetics of rubisco activation in these C4 crops (τ_Rubisco), data logged every 10 s. Gas exchange under fluctuating light. After dark adaptation, the leaves undergo three light change steps, light intensity was set as 1800 µmol m-2 s-1, 200 µmol m-2 s-1 and 1800 µmol m-2 s-1 for each 1800 s step.
FuelLib (Fuel Library) [SWR-25-26]
FuelLib is a library that utilizes the group contribution method (GCM) for calculating thermodynamic properties of hydro-carbon jet fuels. FuelLib utilizes the tables and functions of the GCM as proposed by Constantinou and Gani (1994) and Constantinou, Gani and O'Connel (1995), with additional physical properties discussed in Govindaraju & Ihme (2016). The code is based on Pavan B. Govindaraju's Matlab implementation of the GCM, and has been expanded to include additional thermodynamic properties and mixture properties. The fuel library contains gas chromatography (GC x GC) data for a variety of fuels ranging from simple single component fuels to complex jet fuels. The GC x GC data for POSF jet fuels comes from Edwards (2020).