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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.

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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Modular Finite Element Methods

MFEM is a free, lightweight, scalable C++ library for finite element methods. The goal of MFEM is to enable research and development of scalable finite element discretization and solver algorithms through general finite element abstractions, accurate and flexible visualization, and tight integration with the hypre library. Conceptually, MFEM can be viewed as a finite element toolbox that provides the building blocks for developing finite element algorithms in a manner similar to that of MATLAB for linear algebra methods.

ECP↗
DOE OSTI2020

MATBOX (Microstructure Analysis Toolbox) [SWR-20-76]

MATBOX is a MATLAB application for performing various microstructure-related tasks including microstructure numerical generation, image filtering and microstructure segmentation, microstructure characterization, result three-dimensional visualization and result correlation, and microstructure meshing. MATBOX was originally developed to analyze electrode microstructures for lithium ion batteries; however, the algorithms provided by the toolbox are widely applicable to other heterogeneous materials. The toolbox provides a user-friendly experience thanks to a Graphic-User Interface.

Usseglio Viretta, Francois↗
DOE OSTI2020

fbWecCntrl

fbWecCntrl is set of MATLAB functions and scripts demonstrating a causal impedance matching approach to wave energy converter (WEC) control design. SAND2020-12219 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.

Coe, Ryan↗
DOE OSTI2020

SNL Fugu to IBM's TrueNorth Corelet Programming Environment Transcompiler

This code is written in python and will take a defined network x graph and return a MATLAB file that defines a Truenorth Corelet of the network x graph. The network x graph is designed to be based on the FUGU specification (an internally developed Sandia spiking network definition). SAND2020-12195 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.

Hill, Aaron↗
DOE OSTI2020

Semi-analytic model of magnetized liner inertial fusion

The code that was developed is called SAMM (Semi-Analytic MagLIF Model). In 2015, McBride and Slutz published all of the equations that are solved by the code in the original SAMM paper: R. D. McBride and S. A. Slutz, ?A semi-analytic model of magnetized liner inertial fusion?, Phys. Plasmas 22, 052708 (2015); http://doi.org/10.1063/1.4918953. The SAMM code is now implemented in both the MATLAB and Python programming languages. Students from multiple universities have requested copies of the code so that they can become more familiar with the MagLIF concept. We would like to seek an open-source solution. There is no market value to this code, as there are plenty of more sophisticated simulation codes already available; SAMM is merely a simplified model that is purely for educational purposes. In fact, at least one graduate student (from the University of California, San Diego) has already implemented and published his own modified version of the model: J. Narkis, H. U. Rahman, J. C. Valenzuela, F. Conti, R. D. McBride, D. Venosa, and F. N. Beg, ?A semi-analytic model of gas-puff liner-on-target magneto-inertial fusion?, Phys. Plasmas 26, 032708 (2019); https://doi.org/10.1063/1.5086056. SAND2020-12244 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.

Moore, Thomas↗
DOE OSTI2020

Multivariate Curve Resolution (MCR) using Principal Components Inputs and Rigorous Equality and Inequality Constraints

This MATLAB pseudocode perform multivariate curve resolution (MCR) using PCA scores & loadings of data as inputs. It employs rigorous least squares equality and inequality constraints for all elements in the solution factor matrices. It also can be used to perform nonnegative matrix factorization. SAND2020-12650 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.

Van Benthem, Mark↗
DOE OSTI2020

sta-imex (scripts to investigate stability of IMEX methods)

Set of Matlab scripts to investigate properties of IMEX time stepping methods. Scripts include discretization of a system of linearized equations. One script plots numerical dispersion against analytical dispersion of the system. Another set of scripts uses the system to break it into stiff and non stiff part to investigate stability of Implicit-Explicit Runge-Kutta methods. Scripts are based on Thuburn, J. and Woollings, T. J., Vertical Discretizations for Compressible Euler Equation Atmospheric Models Giving Optimal Representation of Normal Modes , 2005 and Lock, S.-J. and Wood, N. and Weller, H., Numerical analyses of Runge-Kutta implicit-explicit schemes for horizontally explicit, vertically implicit solutions of atmospheric models, 2014 expanding ideas from these two papers. Scripts are used to develop IMEX schemes. SAND2020-12594 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.

Guba, Oksana↗
DOE OSTI2014

Prony Ringdown GUI (CERTS Prony Ringdown, part of the DSI Tool Box)

The PNNL Prony Ringdown graphical user interface is one analysis tool included in the Dynamic System Identification toolbox (DSI Toolbox). The Dynamic System Identification toolbox is a MATLAB-based collection of tools for parsing and analyzing phasor measurement unit data, especially in regards to small signal stability. It includes tools to read the data, preprocess it, and perform small signal analysis. 5. Method of Solution: The Dynamic System Identification Toolbox (DSI Toolbox) is designed to provide a research environment for examining phasor measurement unit data and performing small signal stability analysis. The software uses a series of text-driven menus to help guide users and organize the toolbox features. Methods for reading in populate phasor measurement unit data are provided, with appropriate preprocessing options for small-signal-stability analysis. The toolbox includes the Prony Ringdown GUI and basic algorithms to estimate information on oscillatory modes of the system, such as modal frequency and damping ratio.

Tuffner, Francis↗
DOE OSTI2017

Generalized Preconditioned Locally Harmonic Residual Eigensolver (GPLHR) v0.1

The software contains a MATLAB implementation of the Generalized Preconditioned Locally Harmonic Residual (GPLHR) method for solving standard and generalized non-Hermitian eigenproblems. The method is particularly useful for computing a subset of eigenvalues, and their eigen- or Schur vectors, closest to a given shift. The proposed method is based on block iterations and can take advantage of a preconditioner if it is available. It does not need to perform exact shift-and-invert transformation. Standard and generalized eigenproblems are handled in a unified framework.

Vecharynski, Eugene↗
DOE OSTI2021

F3C v0.1

Fast Free Fermion Compiler (F3C) is an application-specific quantum circuit compiler for time-evolution circuits of spin Hamiltonian systems that can be mapped to free fermions. F3C is the Matlab software version and the related F3C++ is the C++ software version.

Van Beeumen, RoelMaria Franciscus↗
DOE OSTI2020

pySMARTS: SMARTS Python Wrapper (Simple Model of the Atmospheric Radiative Transfer of Sunshine)

The pySMARTS module contains functions for calling SMARTS: Simple Model of the Atmospheric Radiative Transfer of Sunshine, from NREL, developed by Dr. Christian Gueymard. SMARTS software can be obtained from: https://www.nrel.gov/grid/solar-resource/smarts.html Users will be responsible to obtain a copy of SMARTS from NREL, honor it's license, and download the SMART files into their PVLib folder. This wrapper is shared under a BSD-3-Clause License, and was originally coded in Matlab by Juan Russo (2001), updated and ported to python by Silvana Ayala (2019-2020).

Ayala Pelaez, Silvana↗
DOE OSTI2021

Multi-Energy Differential Evolution Reconstruction (MEnDER 1D) for Proton Deflectometry

This code is designed to reconstruct magnetic field deflections, and thus the path-integrated magnetic field, from sets of proton images at two distinct proton probe energies. A differential evolution (DE) algorithm is used to iteratively update a population of solution candidates of the magnetic deflections of the protons for reconstructing the input images, selecting improved candidates as they are discovered. This algorithm was written using MATLAB (R2019a) and makes use of the Image Processing and Parallel Processing Toolboxes.

Levesque, Joseph↗
DOE OSTI2021

stacked predictive sparse decomposition (SPSD) v1.0

It is an unsupervised representation algorithm used to learn morphometric properties from cellular objects. Many similar/identical open source implementations are widely available in tensorflow, pytorch, etc. And ours is implemented in matlab.

Chang, Hang↗
DOE OSTI2021

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul↗
DOE OSTI2021

The Power and Energy Storage Systems Toolbox -- PSTess v.1.0

The Power and Energy Storage Systems Toolbox (PSTess) is a MATLAB-based computing package for dynamic simulation and analysis of utility-scale battery storage systems. This codebase is a fork of the Power Systems Toolbox Version 3.0, developed at Rensselaer Polytechnic Institute (RPI) and Cherry Tree Scientific Software. While PSTess shares a common lineage with PST, it is a substantially different application. As the name implies, the main distinguishing characteristic of PSTess is its ability to model inverter-based energy storage systems (ESS). The model that enables this is called ess.m, and it serves the dual role of representing ESS operational constraints and the generator/converter interface. With PSTess, the generator/converter interface is modeled as a controllable current source with the ability to modulate both active and reactive current. The model ess.m permits four-quadrant modulation, which allows it to represent a wide variety of inverter-based resources beyond energy storage when paired with an appropriate supplemental control model. Examples include utility-scale photovoltaic (PV) power plants, type 4 wind plants, and static synchronous compensators (STATCOM). This capability is especially useful for modeling hybrid plants that combine energy storage with renewable resources. 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. SAND2021-8322 O

Elliott, RyanT.↗
DOE OSTI2021

Light Transport with Weak Angular Dependence in Fog: Supplemental Code

A MATLAB script for calculating the optical properties of different fog types. This is a supplemental code intended to be published along with a journal paper. 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. SAND2021-1504 O

Bentz, BrianZ.↗
DOE OSTI2019

Plant density and enhanced plant vigor estimation for high-resolution images v1

The package contains algorithms for the estimation of sprout/plant density and the corresponding enhanced plant vigor from remotely sensed (RS) images. These algorithms aim to improve the plant characterization and monitoring in the early season when the soil component is significant compared to the plant spatial coverage. In such a scenario, the identification of sprouts (or plants) and the estimation of plant vegetation indexes can be performed only using UAV-acquired images. Additionally, because of the extremely high resolution, gridding becomes necessary to improve visualization and provide more informative maps. However, to capture the real range of values of the VIs, it is important to avoid the inclusion of those pixels belonging to the soil component. The sprout/plant density estimation algorithm takes in input a classification map and uses the vegetation class to estimates the plant density within a user-defined grid using a floating window. Similarly, the enhanced plant vigor algorithm takes in input the vegetation index and the classification map. The enhanced vegetation index is computed for each pixel as the average value among those pixels that belong to the vegetation class within a floating window. The software is developed for the MATLAB environment.

Falco, Nicola↗