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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Practical Guide to Chemometric Analysis of Optical Spectroscopic Data

The methodology and mathematical treatment of several classic multivariate methods for the analysis of spectroscopic data is demonstrated in a straightforward way that can be used as a basis for teaching an undergraduate introductory course on chemometric analysis. The multivariate techniques of classical least squares (CLS), principal component regression (PCR), and partial least squares (PLS), as well as the univariate Beer’s law method have been described and compared, building students’ understanding by starting with the univariate method and progressing step by step into the multivariate methods. Equations for the production of regression vectors from training set spectral data is described and their use demonstrated for the prediction of constituent concentrations on a separate validation set of spectra. Extreme care is taken to ensure consistency in variable formatting of data matrices. This provides a key foundation to understanding how spectral data are manipulated using these different mathematical approaches for building quantitative regression models. Each method is applied to a real-world data set, and the results are discussed to show students the types of information that can be gleaned from each method. A training set comprised of 20 infrared absorbance spectra containing 3 constituents (benzene, polystyrene, and gasoline) of known composition are used to demonstrate the matrix operations for each regression method. A separate set of 12 real-world napalm samples (containing benzene, polystyrene and gasoline) are used as a validation set to demonstrate the ability to utilize the regression models on an unknown dataset. A toolbox (PNNL Chemometric Toolbox) written in MATLAB language is supplied in the Supplemental Information file and can be used as a companion for understanding the development and deployment of the chemometric algorithms described in this paper. The datasets of the infrared spectra are also supplied, allowing users to build and inspect the chemometric models on their own. Finally, the Toolbox includes scripts to assist users in loading their own datasets into MATLAB and performing CLS, PCR, and PLS on their data.

Upper-Division Undergraduate, Analytical Chemistry↗
DOE OSTI2020

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↗
DOE OSTI2015

IBEX: An open infrastructure software platform to facilitate collaborative work in radiomics

Purpose: Radiomics, which is the high-throughput extraction and analysis of quantitative image features, has been shown to have considerable potential to quantify the tumor phenotype. However, at present, a lack of software infrastructure has impeded the development of radiomics and its applications. Therefore, the authors developed the imaging biomarker explorer (IBEX), an open infrastructure software platform that flexibly supports common radiomics workflow tasks such as multimodality image data import and review, development of feature extraction algorithms, model validation, and consistent data sharing among multiple institutions. Methods: The IBEX software package was developed using the MATLAB and C/C++ programming languages. The software architecture deploys the modern model-view-controller, unit testing, and function handle programming concepts to isolate each quantitative imaging analysis task, to validate if their relevant data and algorithms are fit for use, and to plug in new modules. On one hand, IBEX is self-contained and ready to use: it has implemented common data importers, common image filters, and common feature extraction algorithms. On the other hand, IBEX provides an integrated development environment on top of MATLAB and C/C++, so users are not limited to its built-in functions. In the IBEX developer studio, users can plug in, debug, and test new algorithms, extending IBEX’s functionality. IBEX also supports quality assurance for data and feature algorithms: image data, regions of interest, and feature algorithm-related data can be reviewed, validated, and/or modified. More importantly, two key elements in collaborative workflows, the consistency of data sharing and the reproducibility of calculation result, are embedded in the IBEX workflow: image data, feature algorithms, and model validation including newly developed ones from different users can be easily and consistently shared so that results can be more easily reproduced between institutions. Results: Researchers with a variety of technical skill levels, including radiation oncologists, physicists, and computer scientists, have found the IBEX software to be intuitive, powerful, and easy to use. IBEX can be run at any computer with the windows operating system and 1GB RAM. The authors fully validated the implementation of all importers, preprocessing algorithms, and feature extraction algorithms. Windows version 1.0 beta of stand-alone IBEX and IBEX’s source code can be downloaded. Conclusions: The authors successfully implemented IBEX, an open infrastructure software platform that streamlines common radiomics workflow tasks. Its transparency, flexibility, and portability can greatly accelerate the pace of radiomics research and pave the way toward successful clinical translation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Small Scale WEC Performance Modeling Data

Small Scale WEC Performance Modeling Data is performance data from downscaled models of common WEC devices and their calculated performance outputs. This data is used by the Small WEC interactive modeling tool hosted by PRIMRE. The devices include a point absorber, a two-body point absorber (RM3), an oscillating surge device (OSWEC), and an attenuator type device (McCabe Wave Pump). One of the primary use cases for this work is to give an easy way to compare power output for a variety of WECs and model sizes.

16 TIDAL AND WAVE POWER↗
DOE OSTI2016

SU-F-T-458: Tracking Trends of TG-142 Parameters Via Analysis of Data Recorded by 2D Chamber Array

Purpose: With increasing QA demands of medical physicists in clinical radiation oncology, the need for an effective method of tracking clinical data has become paramount. A tool was produced which scans through data automatically recorded by a 2D chamber array and extracts relevant information recommended by TG-142. Using this extracted information a timely and comprehensive analysis of QA parameters can be easily performed enabling efficient monthly checks on multiple linear accelerators simultaneously. Methods: A PTW STARCHECK chamber array was used to record several months of beam outputs from two Varian 2100 series linear accelerators and a Varian NovalisTx−. In conjunction with the chamber array, a beam quality phantom was used to simultaneously to determine beam quality. A minimalist GUI was created in MatLab that allows a user to set the file path of the data for each modality to be analyzed. These file paths are recorded to a MatLab structure and then subsequently accessed by a script written in Python (version 3.5.1) which then extracts values required to perform monthly checks as outlined by recommendations from TG-142. The script incorporates calculations to determine if the values recorded by the chamber array fall within an acceptable threshold. Results: Values obtained by the script are written to a spreadsheet where results can be easily viewed and annotated with a “pass” or “fail” and saved for further analysis. In addition to creating a new scheme for reviewing monthly checks, this application allows for able to succinctly store data for follow up analysis. Conclusion: By utilizing this tool, parameters recommended by TG-142 for multiple linear accelerators can be rapidly obtained and analyzed which can be used for evaluation of monthly checks.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2018

An Automated, High-Throughput Method for Interpreting the Tandem Mass Spectra of Glycosaminoglycans

The biological interactions between glycosaminoglycans (GAGs) and other biomolecules are heavily influenced by structural features of the glycan. The structure of GAGs can be assigned using tandem mass spectrometry (MS{sup 2}), but analysis of these data, to date, requires manually interpretation, a slow process that presents a bottleneck to the broader deployment of this approach to solving biologically relevant problems. Automated interpretation remains a challenge, as GAG biosynthesis is not template-driven, and therefore, one cannot predict structures from genomic data, as is done with proteins. The lack of a structure database, a consequence of the non-template biosynthesis, requires a de novo approach to interpretation of the mass spectral data. We propose a model for rapid, high-throughput GAG analysis by using an approach in which candidate structures are scored for the likelihood that they would produce the features observed in the mass spectrum. To make this approach tractable, a genetic algorithm is used to greatly reduce the search-space of isomeric structures that are considered. The time required for analysis is significantly reduced compared to an approach in which every possible isomer is considered and scored. The model is coded in a software package using the MATLAB environment. This approach was tested on tandem mass spectrometry data for long-chain, moderately sulfated chondroitin sulfate oligomers that were derived from the proteoglycan bikunin. The bikunin data was previously interpreted manually. Our approach examines glycosidic fragments to localize SO{sub 3} modifications to specific residues and yields the same structures reported in literature, only much more quickly. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

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.

Wang, Yu↗
DOE OSTI2020

Data, Photographs, Videos, and Information for the Niwot Ridge Subalpine Forest (US-NR1) AmeriFlux site

This data package contains data and information about the operation of the Niwot Ridge Subalpine Forest AmeriFlux site (US-NR1) between Nov 1998 to the present (2020). This data archive supplements the primary 30-min data storage for the US-NR1 data (i.e., https://doi.org/10.17190/AMF/1246088) by providing the following: (i) five-minute statistics (means, variances, covariances) of all data measured by the data system between Nov 1998 and September 2020 in netCDF format, (ii) CSV data files saved within the memory of the CR23X data loggers (as well as an archive of the data logger programs), (iii) an archive of previous 30-min ASCII data versions of the US-NR1 AmeriFlux data and information related to each data release (a replica of what can be found at http://urquell.colorado.edu/data_ameriflux/), (iv) a web calendar (in HTML format) documenting activity at the site (a replica of http://urquell.colorado.edu/calendar/), (v) photos (over 15,000) and video taken at the site between years 2001 and present day (2020), and (vi) several auxiliary datasets, primary related to trees near the site, soil moisture and soil temperature, and subcanopy radiation data. The data package is setup so that the web calendar, photos, and electronic logbook can be easily accessed on a local computer using a web browser. The provided data files are in either netCDF, CSV, ASCII, or MATLAB format. To obtain a better understanding about the archive, please start by reading the PDF: README_ESS_DIVE_USNR1_readme_first.pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

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↗
DOE OSTI2015

SHMTools: Structural Health Monitoring Software for Aerospace, Civil, and Mechanical Infrastructure

Structural Health Monitoring (SHM) involves a multitude of processes designed to detect damage in situ on various types of structures, from aircraft and buildings to bridges and mechanical infrastructure. In an early example of SHM, railroad wheeltappers used a hammer to strike train wheels to determine if there was damage present. At Los Alamos, scientists have developed SHMTools, a software suite that provides more than 100 advanced algorithms that quickly prototype and evaluate damage-detection processes. The software consists of modular MATLAB routines covering the three main stages of SHM: data acquisition, feature extraction, and feature classification. Multiple sensing modalities are supported, including acceleration, strain, and guided-wave data, all of which have been widely used in SHM practice.

42 ENGINEERING↗
DOE OSTI2016

ROMUSE 2.0 User Manual

ROMUSE (Reduced Order Modeling Based Uncertainty/Sensitivity Estimator) is an effort within the Consortium for Advanced Simulation of Light water reactors (CASL) to provide an analysis tool to be used in conjunction with reactor core simulators, especially the Virtual Environment for Reactor Applications (VERA). ROMUSE is written in C++ and is currently capable of performing various types of parameters perturbations, uncertainty quantification, surrogate models construction and subspace analysis. Version 2.0 has the capability to interface with DAKOTA which gives ROMUSE access to the various algorithms implemented within DAKOTA. ROMUSE is mainly designed to interface with VERA and the Comprehensive Modeling and Simulation Suite for Nuclear Safety Analysis and Design (SCALE) [1,2,3], however, ROMUSE can interface with any general model (e.g. python and matlab) with Input/Output (I/O) format that follows the Hierarchical Data Format 5 (HDF5). In this brief user manual, the use of ROMUSE will be overviewed and example problems will be presented and briefly discussed. The algorithms provided here range from algorithms inspired by those discussed in Ref.[4] to nuclear-specific algorithms discussed in Ref. [3].

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

SFDBSI_GLS v. 1.0

Matlab code for inversion of frequency domain, electrostatic geophysical data in terms of scalar scattering amplitudes in the subsurface. The data is assumed to be the difference between two measurements: electric field measurements prior to the injection of an electrically conductive proppant, and the electric field measurements after proppant injection. The proppant is injected into the subsurface via a well, and its purpose is to prop open fractures created by hydraulic fracturing. In both cases the illuminating electric field is assumed to be a vertically incident plane wave. The inversion strategy is to solve a set of linear system of equations, where each equation defines the amplitude of a candidate scattering volume. The model space is defined by M potential scattering locations and the frequency domain (of which there are k frequencies) data are recorded on N receivers. The solution thus solves a kN x M system of linear equations for M scalar amplitudes within the user-defined solution space. Practical Application: Oilfield environments where observed electrostatic geophysical data can reasonably be assumed to be scattered by subsurface proppant volumes. No field validation examples have so far been provided.

Poppeliers, Christian↗
DOE OSTI2023

BLAST-Lite (Battery Lifetime Analysis and Simulation Tool - Lite) [SWR-22-69] Related to: BLAST aka: BLAST-Py

Battery Lifetime Analysis and Simulation Toolsuite (BLAST) provides a library of battery lifetime and degradation models for various commercial lithium-ion batteries from recent years. Degradation models are identified from publicly available lab-based aging data using NREL's battery life model identification toolkit. The battery life models predicted the expected lifetime of batteries used in mobile or stationary applications as functions of their temperature and use (state-of-charge, depth-of-discharge, and charge/discharge rates). Model implementation is in both Python and MATLAB programming languages. The MATLAB code also provides example applications (stationary storage and EV), climate data, and simple thermal management options. For more information on battery health diagnostics, prediction, and optimization, see NREL's Battery Lifespan webpage.

Smith, Kandler↗
DOE OSTI2017

General Mode Scanning Probe Microscopy

A critical part of SPM measurements is the information transfer from the probe-sample junction to the measurement system. Current information transfer methods heavily compress the information-rich data stream by averaging the data over a time interval, or via heterodyne detection approaches such as lock-in amplifiers and phase-locked loops. As a consequence, highly valuable information at the sub-microsecond time scales or information from frequencies outside the measurement band is lost. We have developed a fundamentally new approach called General Mode (G-mode), where we can capture the complete information stream from the detectors in the microscope. The availability of the complete information allows the microscope operator to analyze the data via information-theory analysis or comprehensive physical models. Furthermore, the complete data stream enables advanced data-driven filtering algorithms, multi-resolution imaging, ultrafast spectroscropic imaging, spatial mapping of multidimensional variability in material properties, etc. Though we applied this approach to scanning probe microscopy, the general philosophy of G-mode can be applied to many other modes of microscopy. G-mode data is captured by completely custom software written in LabVIEW and Matlab. The software generates the waveforms to electrically, thermally, or mechanically excite the SPM probe. It handles real-time communications with the microscope software for operations such as moving the SPM probe position and also controls other instrumentation hardware. The software also controls multiple variants of high-speed data acquisition cards to excite the SPM probe with the excitation waveform and simultaneously measure multiple channels of information from the microscope detectors at sampling rates of 1-100 MHz. The software also saves the raw data to the computer and allows the microscope operator to visualize processed or filtered data during the experiment. The software performs all these features while offering a user-friendly interface.

Somnath, Suhas↗
DOE OSTI2017

Beam Based RF Voltage Measurements and Longitudinal Beam Tomography at the Fermilab Booster

Increasing proton beam power on neutrino production targets is one of the major goals of the Fermilab long term accelerator programs. In this effort, the Fermilab 8 GeV Booster synchrotron plays a critical role for at least the next two decades. Therefore, understanding the Booster in great detail is important as we continue to improve its performance. For example, it is important to know accurately the available RF power in the Booster by carrying out beam-based measurements in order to specify the needed upgrades to the Booster RF system. Since the Booster magnetic field is changing continuously measuring/calibrating the RF voltage is not a trivial task. Here, we present a beam based method for the RF voltage measurements. Data analysis is carried out using computer programs developed in Python and MATLAB. The method presented here is applicable to any RCS which do not have flat-bottom and flat-top in the acceleration magnetic ramps. We have also carried out longitudinal beam tomography at injection and extraction energies with the data used for RF voltage measurements. Beam based RF voltage measurements and beam tomography were never done before for the Fermilab Booster. The results from these investigations will be very useful in future intensity upgrades.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

SU-F-T-399: Migration of Treatment Planning Systems Without Beam Data Measurement

Purpose: Data acquisition for commissioning is steered by Treatment Planning System (TPS) requirements which can be cumbersome and time consuming involving significant clinic downtime. The purpose of this abstract is to answer if we could circumvent this by extracting data from existing TPS and speed up the process. Methods: Commissioning beam data was obtained from a clinically commissioned TPS (Pinnacle™) using Matlab™ generated Pinnacle™ executable scripts to commission a secondary 3D dose verification TPS (Eclipse™). Profiles and output factors for commissioning as required by Eclipse™ were computed on a 50 cm{sup 3} water phantom at a dose grid resolution of 2mm3. Verification doses were computed and compared to clinical TPS dose profiles as per TG-106 guidelines. Standard patient plans from Pinnacle™ including IMRT and VMAT plans were re-computed keeping the same monitor units (in order to perform true comparison) using Eclipse™. Computed dose was exported back to Pinnacle for comparison to original plans. This methodology enables us to alleviate all ambiguities that arise in such studies. Results: Profile analysis using in-house software for 6x, showed that for all field sizes including small MLC generated fields, 100% of infield and penumbra data points of Eclipse™ match Pinnacle™ generated and measured profiles with 2%/2 mm gamma criteria. Excellent agreement was observed in the penumbra regions, with all data points passing DTA criteria for complex C-shaped and S-shaped profiles. Patient plan dose volume histograms (DVHs) and isodose lines agreed well to within a 1.5% for target coverage. Conclusion: Secondary 3D dose checking is of utmost importance with advanced techniques such as IMRT and VMAT. Migration of TPS is possible without compromising accuracy or enduring the cumbersome measurement of commissioning data. Economizing time for commissioning such a verification system or for migration of TPS can add great QA value and minimize downtime.

60 APPLIED LIFE SCIENCES↗