Automated ToF-SIMS PCA Analysis Tool
Python software package for PCA analysis of ToF-SIMS spectra data
Welch, Cole↗
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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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TalkPipe
SAND2025-11168O TalkPipe is a software tool to help users create and manage complex data analysis tasks involving Large Language Models. Its easy-to-use interface allows users to combine different analytical processes. TalkPipe includes a Python library, a scripting language, and can be run in a Docker container, making it simple to customize and extend. 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.
Bauer, Travis [Sandia National Lab. (SNL-CA), Live↗
E-Area Low Level Waste Generator Inventory Uncertainty Estimation
This report describes the method used to estimate the uncertainty and bias in the low-level waste inventory, as reported by Waste Generators, for waste disposed in the E-Area Low-Level Waste Facility at SRS. The waste cut uncertainty and bias is summed to calculate the current total uncertainty and bias in each disposal unit in the E-Area Low-Level Waste Facility. This information is used to estimate the future uncertainty and bias when all disposal units are closed. For most waste cuts, there are two areas of inventory uncertainty and bias: in the isotopic characterization of the waste stream and in the measurement of total waste cut activity. Waste stream characterization is accomplished through a combination of process knowledge and analytical measurements. This characterization is documented by a technical baseline that describes the relative quantity of each isotope present in the waste stream. The total activity of each individual waste cut is usually measured directly or is calculated through a ratio of activity per weight or activity per volume. The waste cut total activity is multiplied by the waste stream isotopic fraction to calculate the total isotopic activity present in the waste cut. The waste cut uncertainty and bias is calculated by analyzing the uncertainties and biases in the waste stream characterization and waste cut measurements and adding the uncertainties in quadrature and multiplying the reported isotopic activities by the bias factors. The current isotopic inventory, uncertainty, and bias of a disposal unit is the sum of the currently disposed individual waste cut isotopic activities, uncertainties, and biases. The future uncertainty and bias is estimated based on the average “worst-case” (largest) uncertainties and biases of currently closed and operational disposal units. This report details the method, data sources, and calculation techniques used to calculate these values. It also presents some of the difficulties in working with the reported data and gives examples of the calculations and analysis. The software used to carryout the analysis is included and the location of the complete individual analyses is given. After discussion with waste generators, examination of multiple waste characterization documents, and a review of SRS Manual 1S, the reported ELLWF radionuclide activities are clearly conservative and likely represent reasonable upper bounds for the true activities. However, quantifying the bias and uncertainty in each waste cut requires detailed analysis of the documentation for each waste cut measurement and waste stream characterization.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
MAGSAT science investigations
Progress in the development and modification of software to accommodate total field anomaly data and for spectral analysis of aeromagnetic profile data and computation of depth to magnetic bottom is reported.
Source record↗
A program in global biology
NASA's Global Biology Research Program and its goals for greater understanding of planetary biological processes are discussed. Consideration is given to assessing major pathways and rates of exchange of elements such as carbon and nitrogen, extrapolating local rates of anaerobic activities, determining exchange rates of ocean nutrients, and developing models for the global cycles of carbon, nitrogen, sulfur, and phosphorus. Satellites and sensors operating today are covered: the Nimbus, NOAA, and Landsat series. Block diagrams of the software and hardware for a typical ground data processing and analysis system are provided. Samples of the surface cover data achieved with the Advanced Very High Resolution Radiometer, the Multispectral Scanner, and the Thematic Mapper are presented, as well as a productive capacity model for coastal wetlands. Finally, attention is given to future goals, their engineering requirements, and the necessary data analysis system.
Mooneyhan, D. W.↗
Study of application of space telescope science operations software for SIRTF use
The design and development of the Space Telescope Science Operations Ground System (ST SOGS) was evaluated to compile a history of lessons learned that would benefit NASA's Space Infrared Telescope Facility (SIRTF). Forty-nine specific recommendations resulted and were categorized as follows: (1) requirements: a discussion of the content, timeliness and proper allocation of the system and segment requirements and the resulting impact on SOGS development; (2) science instruments: a consideration of the impact of the Science Instrument design and data streams on SOGS software; and (3) contract phasing: an analysis of the impact of beginning the various ST program segments at different times. Approximately half of the software design and source code might be useable for SIRTF. Transportability of this software requires, at minimum, a compatible DEC VAX-based architecture and VMS operating system, system support software similar to that developed for SOGS, and continued evolution of the SIRTF operations concept and requirements such that they remain compatible with ST SOGS operation.
Dignam, F.↗
System integration report
Several areas that arise from the system integration issue were examined. Intersystem analysis is discussed as it relates to software development, shared data bases and interfaces between TEMPUS and PLAID, shaded graphics rendering systems, object design (BUILD), the TEMPUS animation system, anthropometric lab integration, ongoing TEMPUS support and maintenance, and the impact of UNIX and local workstations on the OSDS environment.
Badler, N. I.↗
Computerized structural mechanics for 1990's: Advanced aircraft needs
The needs for computerized structural mechanics (CSM) as seen from the standpoint of the aircraft industry are discussed. These needs are projected into the 1990's with special focus on the new advanced materials. Preliminary design/analysis, research, and detail design/analysis are identified as major areas. The role of local/global analyses in these different areas is discussed. The lessons learned in the past are used as a basis for the design of a CSM framework that could modify and consolidate existing technology and include future developments in a rational and useful way. A philosophy is stated, and a set of analyses needs driven by the emerging advanced composites is enumerated. The roles of NASA, the universities, and the industry are identified. Finally, a set of rational research targets is recommended based on both the new types of computers and the increased complexity the industry faces. Computerized structural mechanics should be more than new methods in structural mechanics and numerical analyses. It should be a set of engineering applications software products that combines innovations in structural mechanics, numerical analysis, data processing, search and display features, and recent hardware advances and is organized in a framework that directly supports the design process.
Viswanathan, A. V.↗
Computational Controls Workstation: Algorithms and hardware
The Computational Controls Workstation provides an integrated environment for the modeling, simulation, and analysis of Space Station dynamics and control. Using highly efficient computational algorithms combined with a fast parallel processing architecture, the workstation makes real-time simulation of flexible body models of the Space Station possible. A consistent, user-friendly interface and state-of-the-art post-processing options are combined with powerful analysis tools and model databases to provide users with a complete environment for Space Station dynamics and control analysis. The software tools available include a solid modeler, graphical data entry tool, O(n) algorithm-based multi-flexible body simulation, and 2D/3D post-processors. This paper describes the architecture of the workstation while a companion paper describes performance and user perspectives.
Venugopal, R.↗
Research & Technology Report Goddard Space Flight Center
The main theme of this edition of the annual Research and Technology Report is Mission Operations and Data Systems. Shifting from centralized to distributed mission operations, and from human interactive operations to highly automated operations is reported. The following aspects are addressed: Mission planning and operations; TDRSS, Positioning Systems, and orbit determination; hardware and software associated with Ground System and Networks; data processing and analysis; and World Wide Web. Flight projects are described along with the achievements in space sciences and earth sciences. Spacecraft subsystems, cryogenic developments, and new tools and capabilities are also discussed.
Soffen, Gerald A.↗
Neural Network and Regression Approximations in High Speed Civil Transport Aircraft Design Optimization
Nonlinear mathematical-programming-based design optimization can be an elegant method. However, the calculations required to generate the merit function, constraints, and their gradients, which are frequently required, can make the process computational intensive. The computational burden can be greatly reduced by using approximating analyzers derived from an original analyzer utilizing neural networks and linear regression methods. The experience gained from using both of these approximation methods in the design optimization of a high speed civil transport aircraft is the subject of this paper. The Langley Research Center's Flight Optimization System was selected for the aircraft analysis. This software was exercised to generate a set of training data with which a neural network and a regression method were trained, thereby producing the two approximating analyzers. The derived analyzers were coupled to the Lewis Research Center's CometBoards test bed to provide the optimization capability. With the combined software, both approximation methods were examined for use in aircraft design optimization, and both performed satisfactorily. The CPU time for solution of the problem, which had been measured in hours, was reduced to minutes with the neural network approximation and to seconds with the regression method. Instability encountered in the aircraft analysis software at certain design points was also eliminated. On the other hand, there were costs and difficulties associated with training the approximating analyzers. The CPU time required to generate the input-output pairs and to train the approximating analyzers was seven times that required for solution of the problem.
Patniak, Surya N.↗
F/NAS/Pressure Temperature Retrieval Techniques
The purpose of this investigation is to study methods and ways for rapid inversion programs involving the correlated k-method, and to modify the existing programs so that the rapid analysis of data can be accomplished. Extensive modifications of the software programs were introduced. These modifications were imposed on the radiative transfer models and inversion methods and resulted in incorporating some important atmospheric processes not previously considered. The software also was improved to handle several toxic gases, gases that were observed in Saturn's atmosphere, and to retrieve pressure-temperature profiles from infrared solar absorption spectra.
Poularikas. Alexander↗
Ocean Color Measurements with the Operational Land Imager on Landsat-8: Implementation and Evaluation in SeaDAS
The Operational Land Imager (OLI) is a multispectral radiometer hosted on the recently launched Landsat8 satellite. OLI includes a suite of relatively narrow spectral bands at 30 m spatial resolution in the visible to shortwave infrared, which makes it a potential tool for ocean color radiometry: measurement of the reflected spectral radiance upwelling from beneath the ocean surface that carries information on the biogeochemical constituents of the upper ocean euphotic zone. To evaluate the potential of OLI to measure ocean color, processing support was implemented in Sea-viewing Wide Field-of-View Sensor (SeaWiFS) Data Analysis System (SeaDAS), which is an open-source software package distributed by NASA for processing, analysis, and display of ocean remote sensing measurements from a variety of spaceborne multispectral radiometers. Here we describe the implementation of OLI processing capabilities within SeaDAS, including support for various methods of atmospheric correction to remove the effects of atmospheric scattering and absorption and retrieve the spectral remote sensing reflectance (Rrs; sr−1). The quality of the retrieved Rrs imagery will be assessed, as will the derived water column constituents, such as the concentration of the phytoplankton pigment chlorophyll a.
Measurements↗
An Introduction to Data Visualization
Data visualization can be used to present findings, explore data, and use the human eye to find patterns that a computer would struggle to locate. Borrowing tools from art, storytelling, data analytics and software development, data visualization is an indispensable part of the analysis process. While data visualization usage spans across multiple disciplines and sectors, most never receive formal training in the subject. As such, this tutorial will introduce key data visualization building blocks and how to best use those building blocks for different scenarios and audiences. We will also go over tips on accessibility, design and interactive elements. While this will by no means be a complete overview of the data visualization field, by building a foundation and introducing some rules of thumb, attendees will be better equipped for communicating their findings to their audience.
data visualization↗
Bayesian And Human Reliability Analysis (hra)-aided Method For The Reliability Analysis Of Software (bahamas)
The purpose of the BAHAMAS code is to provide a simplified process for performing quantitative evaluations of software reliability. The Bayesian and Human Reliability Analysis (HRA)-Aided method for the Reliability Analysis of software (BAHAMAS) was developed specifically to perform quantification under limited data conditions, i.e., when limited testing or operational data are available, such as during early development stages. BAHAMAS essentially examines the quality of a software development life cycle to determine the probability of specific types of software failure. BAHAMAS will have modules to support user input for detailed and simplified analyses. The user interface will also support software common cause failure analysis.
Wang, Congjian (0000000207789927)↗
Enabling Modular Autonomous Feedback‐Loops in Materials Science through Hierarchical Experimental Laboratory Automation and Orchestration
Abstract Materials acceleration platforms (MAPs) operate on the paradigm of integrating combinatorial synthesis, high‐throughput characterization, automatic analysis, and machine learning. Within a MAP, one or multiple autonomous feedback loops may aim to optimize materials for certain functional properties or to generate new insights. The scope of a given experiment campaign is defined by the range of experiment and analysis actions that are integrated into the experiment framework. Herein, the authors present a method for integrating many actions within a hierarchical experimental laboratory automation and orchestration (HELAO) framework. They demonstrate the capability of orchestrating distributed research instruments that can incorporate data from experiments, simulations, and databases. HELAO interfaces laboratory hardware and software distributed across several computers and operating systems for executing experiments, data analysis, provenance tracking, and autonomous planning. Parallelization is an effective approach for accelerating knowledge generation provided that multiple instruments can be effectively coordinated, which the authors demonstrate with parallel electrochemistry experiments orchestrated by HELAO. Efficient implementation of autonomous research strategies requires device sharing, asynchronous multithreading, and full integration of data management in experimental orchestration, which to the best of the authors’ knowledge, is demonstrated for the first time herein.
36 MATERIALS SCIENCE↗
Novel principal component analysis tool based on python for analysis of complex spectra of time-of-flight secondary ion mass spectrometry
Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful surface analysis tool, which can simultaneously provide elemental, isotopic, and molecular information with part per million (ppm) sensitivity. However, each spectrum may be composed of hundreds of ion signals, which makes the spectra data complex. Principal component analysis (PCA) is a multivariate analysis technique that has been widely used to figure out the variances among samples in ToF-SIMS spectra data analysis and is showing great success in the explanation of complex ToF-SIMS spectra. So far, several software tools have been developed for PCA of ToF-SIMS spectra; however, none of them are freely available. Such a situation leads to some difficulties in extending applications of PCA to various research fields. More importantly, it has long been challenging for common researchers to understand PCA plots and extract chemical differences among samples. In this work, we developed a new and flexible software tool (named “advanced spectra pca toolbox”) based on python for PCA of complex ToF-SIMS spectra along with an easy-to-read manual. It can generate data analysis reports automatically to explain chemical differences among samples, allowing less experienced researchers to easily understand tricky PCA results. Moreover, it is expandable and compatible with artificial intelligence/machine learning functions. Pure goethite and different lignin adsorbed goethite samples were used as a model system to demonstrate our new software tool, proving that our software tool can be readily used in complex spectra data processing. Our new software tool is open-source, convenient, flexible, and expandable. We expect this open-source tool will benefit the ToF-SIMS community.
47 OTHER INSTRUMENTATION↗
Using SFOC to fly the Magellan Venus mapping mission
Traditionally, spacecraft flight operations at the Jet Propulsion Laboratory (JPL) have been performed by teams of spacecraft experts utilizing ground software designed specifically for the current mission. The Jet Propulsion Laboratory set out to reduce the cost of spacecraft mission operations by designing ground data processing software that could be used by multiple spacecraft missions, either sequentially or concurrently. The Space Flight Operations Center (SFOC) System was developed to provide the ground data system capabilities needed to monitor several spacecraft simultaneously and provide enough flexibility to meet the specific needs of individual projects. The Magellan Spacecraft Team utilizes the SFOC hardware and software designed for engineering telemetry analysis, both real-time and non-real-time. The flexibility of the SFOC System has allowed the spacecraft team to integrate their own tools with SFOC tools to perform the tasks required to operate a spacecraft mission. This paper describes how the Magellan Spacecraft Team is utilizing the SFOC System in conjunction with their own software tools to perform the required tasks of spacecraft event monitoring as well as engineering data analysis and trending.
Bucher, Allen W.↗