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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Fission gas bubble identification using MATLAB's image processing toolbox

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. This study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods. - Highlights: •Automated image processing can aid in the fuel qualification process. •Routines are developed to characterize fission gas bubbles in irradiated U–Mo fuel. •Frequency domain filtration effectively eliminates FIB curtaining artifacts. •Adaptive thresholding proved to be the most accurate segmentation method. •The techniques established are ready to be applied to large scale data extraction testing.

36 MATERIALS SCIENCE↗
DOE OSTI2014

CPMC-Lab: A Matlab package for Constrained Path Monte Carlo calculations

We describe CPMC-Lab, a Matlab program for the constrained-path and phaseless auxiliary-field Monte Carlo methods. These methods have allowed applications ranging from the study of strongly correlated models, such as the Hubbard model, to ab initio calculations in molecules and solids. The present package implements the full ground-state constrained-path Monte Carlo (CPMC) method in Matlab with a graphical interface, using the Hubbard model as an example. The package can perform calculations in finite supercells in any dimensions, under periodic or twist boundary conditions. Importance sampling and all other algorithmic details of a total energy calculation are included and illustrated. This open-source tool allows users to experiment with various model and run parameters and visualize the results. It provides a direct and interactive environment to learn the method and study the code with minimal overhead for setup. Furthermore, the package can be easily generalized for auxiliary-field quantum Monte Carlo (AFQMC) calculations in many other models for correlated electron systems, and can serve as a template for developing a production code for AFQMC total energy calculations in real materials. Several illustrative studies are carried out in one- and two-dimensional lattices on total energy, kinetic energy, potential energy, and charge- and spin-gaps.

Computer Science↗
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 OSTI2011

Matlab Based LOCO

The LOCO algorithm has been used by many accelerators around the world. Although the uses for LOCO vary, the most common use has been to find calibration errors and correct the optics functions. The light source community in particular has made extensive use of the LOCO algorithms to tightly control the beta function and coupling. Maintaining high quality beam parameters requires constant attention so a relatively large effort was put into software development for the LOCO application. The LOCO code was originally written in FORTRAN. This code worked fine but it was somewhat awkward to use. For instance, the FORTRAN code itself did not calculate the model response matrix. It required a separate modeling code such as MAD to calculate the model matrix then one manually loads the data into the LOCO code. As the number of people interested in LOCO grew, it required making it easier to use. The decision to port LOCO to Matlab was relatively easy. It's best to use a matrix programming language with good graphics capability; Matlab was also being used for high level machine control; and the accelerator modeling code AT, [5], was already developed for Matlab. Since LOCO requires collecting and processing a relative large amount of data, it is very helpful to have the LOCO code compatible with the high level machine control, [3]. A number of new features were added while porting the code from FORTRAN and new methods continue to evolve, [7][9]. Although Matlab LOCO was written with AT as the underlying tracking code, a mechanism to connect to other modeling codes has been provided.

43 PARTICLE ACCELERATORS↗
DOE OSTI2011

Linking Advanced Visualization and MATLAB for the Analysis of 3D Gene Expression Data

Three-dimensional gene expression PointCloud data generated by the Berkeley Drosophila Transcription Network Project (BDTNP) provides quantitative information about the spatial and temporal expression of genes in early Drosophila embryos at cellular resolution. The BDTNP team visualizes and analyzes Point-Cloud data using the software application PointCloudXplore (PCX). To maximize the impact of novel, complex data sets, such as PointClouds, the data needs to be accessible to biologists and comprehensible to developers of analysis functions. We address this challenge by linking PCX and Matlab via a dedicated interface, thereby providing biologists seamless access to advanced data analysis functions and giving bioinformatics researchers the opportunity to integrate their analysis directly into the visualization application. To demonstrate the usefulness of this approach, we computationally model parts of the expression pattern of the gene even skipped using a genetic algorithm implemented in Matlab and integrated into PCX via our Matlab interface.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

SU-E-T-157: CARMEN: A MatLab-Based Research Platform for Monte Carlo Treatment Planning (MCTP) and Customized System for Planning Evaluation

Purpose: Although there exist several radiotherapy research platforms, such as: CERR, the most widely used and referenced; SlicerRT, which allows treatment plan comparison from various sources; and MMCTP, a full MCTP system; it is still needed a full MCTP toolset that provides users complete control of calculation grids, interpolation methods and filters in order to “fairly” compare results from different TPSs, supporting verification with experimental measurements. Methods: This work presents CARMEN, a MatLab-based platform including multicore and GPGPU accelerated functions for loading RT data; designing treatment plans; and evaluating dose matrices and experimental data.CARMEN supports anatomic and functional imaging in DICOM format, as well as RTSTRUCT, RTPLAN and RTDOSE. Besides, it contains numerous tools to accomplish the MCTP process, managing egs4phant and phase space files.CARMEN planning mode assist in designing IMRT, VMAT and MERT treatments via both inverse and direct optimization. The evaluation mode contains a comprehensive toolset (e.g. 2D/3D gamma evaluation, difference matrices, profiles, DVH, etc.) to compare datasets from commercial TPS, MC simulations (i.e. 3ddose) and radiochromic film in a user-controlled manner. Results: CARMEN has been validated against commercial RTPs and well-established evaluation tools, showing coherent behavior of its multiple algorithms. Furthermore, CARMEN platform has been used to generate competitive complex treatment that has been published in comparative studies. Conclusion: A new research oriented MCTP platform with a customized validation toolset has been presented. Despite of being coded with a high-level programming language, CARMEN is agile due to the use of parallel algorithms. The wide-spread use of MatLab provides straightforward access to CARMEN’s algorithms to most researchers. Similarly, our platform can benefit from the MatLab community scientific developments as filters, registration algorithms etc. Finally, CARMEN arises the importance of grid and filtering control in treatment plan comparison.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-590: Optimizing Magnetic Field Strengths with Matlab for An Ion-Optic System in Particle Therapy Consisting of Two Quadrupole Magnets for Subsequent Simulations with the Monte-Carlo Code FLUKA

Purpose: Aim of this study was to optimize the magnetic field strengths of two quadrupole magnets in a particle therapy facility in order to obtain a beam quality suitable for spot beam scanning. Methods: The particle transport through an ion-optic system of a particle therapy facility consisting of the beam tube, two quadrupole magnets and a beam monitor system was calculated with the help of Matlab by using matrices that solve the equation of motion of a charged particle in a magnetic field and field-free region, respectively. The magnetic field strengths were optimized in order to obtain a circular and thin beam spot at the iso-center of the therapy facility. These optimized field strengths were subsequently transferred to the Monte-Carlo code FLUKA and the transport of 80 MeV/u C12-ions through this ion-optic system was calculated by using a user-routine to implement magnetic fields. The fluence along the beam-axis and at the iso-center was evaluated. Results: The magnetic field strengths could be optimized by using Matlab and transferred to the Monte-Carlo code FLUKA. The implementation via a user-routine was successful. Analyzing the fluence-pattern along the beam-axis the characteristic focusing and de-focusing effects of the quadrupole magnets could be reproduced. Furthermore the beam spot at the iso-center was circular and significantly thinner compared to an unfocused beam. Conclusion: In this study a Matlab tool was developed to optimize magnetic field strengths for an ion-optic system consisting of two quadrupole magnets as part of a particle therapy facility. These magnetic field strengths could subsequently be transferred to and implemented in the Monte-Carlo code FLUKA to simulate the particle transport through this optimized ion-optic system.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

PDMATLAB2D: A Peridynamics MATLAB Two-dimensional Code

PDMATLAB2D is a meshfree peridynamics implementation in MATLAB suitable for simulation of two-dimensional fracture problems. The purpose of this code is twofold. First, it provides an entry-level peridynamics computational tool for educational and training purposes. Second, it serves as an accessible and easily modifiable computational tool for peridynamics researchers who would like to adapt the code for a multitude of peridynamics simulation scenarios. The current version of the code implements a bond-based brittle elastic peridynamic model and a critical stretch criterion for bond breaking. However, the code is designed to be extendable for other peridynamic models and computational features. In this paper, we provide an overview of the code structure and functions with illustrative examples. In conclusion, due to the integrated computation and postprocessing MATLAB capabilities, PDMATLAB2D can serve as an effective testbed for testing new constitutive models and advanced numerical features for peridynamics computations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Determining Spatial Resolution of Gamma Cameras Using MATLAB

It is important to monitor the spatial resolution of a gamma camera on a weekly basis to acquire medical images with accurate quantitative information. A simple and fast computer program with a graphical user interface to analyze spatial resolution was successfully developed using MATLAB. The results were compared with those obtained from the standard processing system available in our gamma camera. The spatial resolution calculated using MATLAB was 1.24% lower than using the standard processing system. The developed program is cost effective, faster, and provides an easy platform for the physicists and technologists to analyze the spatial resolution based on the image of the line source.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Poster - 09: A MATLAB-based Program for Automated Quality Assurance of a Prostate Brachytherapy Ultrasound System

Purpose: A robust Quality Assurance (QA) program is essential for prostate brachytherapy ultrasound systems due to the importance of imaging accuracy during treatment and planning. Task Group 128 of the American Association of Physicists in Medicine has recommended a set of QA tests covering grayscale visibility, depth of penetration, axial and lateral resolution, distance measurement, area measurement, volume measurement, and template/electronic grid alignment. Making manual measurements on the ultrasound system can be slow and inaccurate, so a MATLAB program was developed for automation of the described tests. Methods: Test images were acquired using a BK Medical Flex Focus 400 ultrasound scanner and 8848 transducer with the CIRS Brachytherapy QA Phantom – Model 045A. For each test, the program automatically segments the inputted image(s), makes the appropriate measurements, and indicates if the test passed or failed. The program was tested by analyzing two sets of images, where the measurements from the first set were used as baseline values. Results: The program successfully analyzed the images for each test and determined if any action limits were exceeded. All tests passed – the measurements made by the program were consistent and met the requirements outlined by Task Group 128. Conclusions: The MATLAB program we have developed can be used for automated QA of an ultrasound system for prostate brachytherapy. The GUI provides a user-friendly way to analyze images without the need for any manual measurement, potentially removing intra- and inter-user variability for more consistent results.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Matlab Code for Multiscale Topology Optimization

This Matlab script implements a simple topology optimization algorithm that minimizes the compliance of a structure within a 3D prismatic design domain. It uses a simple linear elastic finite element solver to solve the equilibrium equations, and the optimality criterion (00) method to update the design iteratively. This functionality is identical to, or the simplest possible extension from 2D to 3D of, a 99-line Matlab code released in 2001 in a journal article by Sigmund. What is new in this code is our implementation of simple surrogate models for several truss micro-architectures, which converts this code to a multiscale design tool, whereas the original code is single-scale. The development of these surrogate models and their implementation is described in a journal article we intend to submit. We plan to include the full source code in an Appendix in this paper. The code’s primary function is as a pedagogical tool rather than as a finished software product. Sigmund’s 2001 paper describes the implementation line-by-line. We are including this updated version of the code to allow the reader to understand exactly what changes must be made to a “standard” topology optimization code to implement the surrogate models and thus multiscale design optimization.

Watts, Seth↗
DOE OSTI2015

Matlab-Excel Interface for OpenDSS

The software allows users of the OpenDSS grid modeling software to access their load flow models using a GUI interface developed in MATLAB. The circuit definitions are entered into a Microsoft Excel spreadsheet which makes circuit creation and editing a much simpler process than the basic text-based editors used in the native OpenDSS interface. Plot tools have been developed which can be accessed through a MATLAB GUI once the desired parameters have been simulated.

Source record↗
DOE OSTI2022

MatLab Package for Whispering Gallery Mode Data

Dye-doped whispering gallery mode resonator (WGMR) microspheres yield highly structured emission spectra that are extremely sensitive to their environment and are of intense interest for use in a variety of sensing applications. Efforts to leverage the unique sensitivities of WGMRs have relied on stringent experimental requirements to correlate specific spectral shifts/changes to an analyte/stimulus such as 1) precise positional knowledge, 2) reference spectra for each microsphere, and 3) high mechanical stability. Consequently, these can hinder adequate mixing or incorporation of analytes and creates challenges for remote sensing. The MATLAB codes provided here are to be used in conjunction with a continuous flow technique for measuring WGM spectra of dye-doped microspheres suspended in solution. One MATLAB script, smooths the data, automatically baseline corrects it to isolate the whispering gallery modes (WGM) from the unwanted bulk emission, and assesses the similarity of each spectrum to aid in selecting a set of unique WGM spectra for further analysis. The next script is designed to analyze WGM spectra to determine the size of the resonator and the refractive index (RI) of its local environment without a priori knowledge of the individual microsphere. The final script allows the user to cluster spheres based on the product of their RI and radius and the contrast ratio of the RI of the sphere material and that of its environment by using a shared nearest neighbor spectral clustering algorithm.

Lilley, Laura↗
DOE OSTI2023

Deep Lynx Matlab Adapter

The Deep Lynx MATLAB Adapter is a Python application that connects the Deep Lynx data warehouse with any MATLAB simulation.

Wilsdon, KatherineN [Idaho National Laboratory] (0↗
DOE OSTI2014

Applying Matlab LOCO to the NSLSII Storage Ring Commissioning

Linear Optics from Closed Orbits (LOCO) has been a powerful beam-based diagnostics and optics control method for storage rings and synchrotrons worldwide ever since it was established at NSLS by J. Safranek. This method measures the orbit response matrix and optionally the dispersion function of the machine. The data are then fitted to a lattice model by adjusting parameters such as quadrupole and skew quadrupole strengths in the model, BPM gains and rolls, corrector gains and rolls of the measurement system. Any abnormality of the machine that affects the machine optics can then be identified. The resulting lattice model is equivalent to the real machine lattice as seen by the BPMs. Since there are usually two or more BPMs per betatron period in modern circular accelerators, the model is often a very accurate representation of the real machine. According to the fitting result, one can correct the machine lattice to the design lattice by changing the quadrupole and skew quadrupole strengths. LOCO is so important that it is routinely performed at many electron storage rings to guarantee machine performance, especially after the Matlab-based LOCO code became available. The Matlab version includes a user-friendly interface, with many useful fitting and analysis options.

36 MATERIALS SCIENCE↗
DOE OSTI2016

The Sandia Matlab AnalysiS Hierarchy (SMASH) toolbox

The SMASH (Sandia Matlab AnalysiS Hierarchy) toolbox is a collection of MATLAB code for data analysis. The toolbox contains general purpose functions, custom class definitions, and self-contained programs aimed at the needs of experimental physicists working in pulsed power research. The initial release (version 1.0) supports file access, signal/image analysis, and user interface creation; custom graphics and generic system tools are also provided. Much of the package is object oriented, encouraging users to build new capabilities from established classes. Future releases will continue this goal, expanding capabilities and streamlining application development.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗