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Software for recording machining tracks in abrasive lapping is described. The software permits prediction of the shape and magnitude of the tool’s surface wear at the stage of process design, on the basis of the dimensions of the workpiece and the lap, their relative velocity, and the machining trajectory.
The commercial and industrial sectors account for nearly half of the total U.S. energy consumption. To help these sectors reduce their energy intensity, the U.S. Department of Energy (DOE) designed the Better Buildings, Better Plants Initiative. Through this initiative, more than 900 industrial, commercial, public and residential organizations commit to long-term sustainability goals and share their proven energy efficiency strategies, which inspire others to tap into the continued potential for energy efficiency. Collectively, these organizations have saved 2.5 quadrillion BTUs of energy, equivalent to US$15.3 billion, and 155 million metric tons of carbon dioxide. Within the initiative, the Better Plants side of the program focuses specifically on the industrial sector. More than 270 industrial partners have taken advantage of the unique selection of resources offered including workforce development programs, information sharing, peer-to-peer networking, diagnostic tool loans and software tools. One of the most powerful tools off ered is a revitalization of the legacy DOE software tools used by industry for decades. These have been transformed into a new, free, opensource software tool suite: MEASUR (Manufacturing Energy Assessment Software for Utility Reduction)
Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.
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.
The mission of this CRADA with Agilent was to couple powerful MS platforms (QQQ, IM-QTOF-MS) with Agilent’s novel Ultra-High-Performance Liquid Chromatography (UHPLC) fast metabolomic workflows and perform ABF Machine Learning (ML) to generated datasets. Agilent transferred UHPLC methods to PNNL and LBNL and methods were implemented and demonstrated in both labs, achieving total acquisition times of < 10 min. Metabolites analyzed using Agilent’s shared methods included metabolites from central carbon metabolism, common across hosts, and metabolites unique to engineered strains. Standards were acquired in an UHPLC-Drift Tube Ion Mobility Mass Spectrometer (DTIMS) system for the first time within the context of ABF and methods were optimized based on Agilent’s protocols. Samples from ABF hosts Pseudomonas putida, Aspergillus pseudoterreus, Aspergillus niger and Rhodosporidium toruloides were analyzed using the UHPLC-DTIMS platform for a total of 276 runs. A data analysis workflow compatible with the Experimental Data Depot (EDD) and completely shareable was developed for the acquired UHPLC-DTIMS data. Samples were analyzed using a Data Independent Acquisition Approach (DIA), which for most of the standards provided more transitions therefore increasing detection confidence. Using the data acquired by PNNL, LBNL, and Agilent’s specifications from previous ML projects, SNL applied an ensemble ML strategy to pick the best performing model for automated LC-method selection. Finally, with the contribution of the participant labs and Agilent, SNL developed an Automated Method Selection (AMS) software tool to predict the best liquid chromatography method for analysis of any new molecules of interest. Samples with novel pathways and new metabolite targets of interest are generated at a high pace in the ABF. Therefore, our accomplishment in this CRADA improved the efficiency and accuracy of strain testing by developing and implementing fast analytical methods, robust processing tools, and software for predicting the best methods for UHPLC analysis.
NREL has developed a software tool to enable Renewance to estimate the degradation of batteries from basic information such as the type of battery and the application of that battery during its first life, so that used batteries may be evaluated for potential repurposing at low cost. This software tool utilizes NREL's BLAST-Lite battery degradation modeling code, which was updated with additional models for commercially produced lithium-ion batteries as a part of this CRADA. The software tool enables users to input details such as battery type and application so that lifetime estimates can be made without any programming or expert battery knowledge. The application input loads in saved values for parameters such as cycles per year, depth-of-discharge, and other battery operating parameters from a file defined by Renewance. These parameters may be modified to refine simulations for specific batteries. The software tool also incorporates a degradation model optimization tool, whereby existing battery degradation models may be tuned according to measured battery health. This ensures that new models still predict degradation behaviors expected from a certain battery chemistry, but with the overall degradation rate tuned to a specific battery make and model. The new model can then be saved for estimating the degradation of other similar batteries. An additional task was planned to utilize machine-learning to enable battery health diagnosis from rapid EIS measurements to accelerate the screening of used batteries. This task was not completed due to lack of available data for training a machine-learning model. CRADA benefit to DOE, Participant, and US Taxpayer: Further development of open-source software tool BLAST-Lite for predicting the lifetime of commercially produced Lithium-ion batteries (NREL SWR-22-69).
PurposeTo compare, in an interventional radiology setting, peak skin doses (PSDs) delivered as calculated using a dedicated software tool and as measured using radiochromic film. To assess the utility of this dose calculation software tool in routine clinical practice.Materials and MethodsFirst, radiochromic films were positioned on the examination table in the back of an adult anthropomorphic phantom to measure PSD, and X-ray examinations were simulated. Then, films were again positioned in the patient’s back for 59 thoracic or abdominopelvic endovascular interventions. The results obtained with the radiochromic films were taken as a reference and were statistically compared with those of the software.ResultsWith measured PSDs ranging from 100 to 7000 mGy, the median software–film difference was 8.5%. Lin’s concordance coefficient was 0.98 [0.97; 0.99] (p < 0.001), meaning that concordance was excellent between the two methods. For the films where PSD exceeded 1000 mGy, the median difference in the measured value was 8.7% [− 1.3; 21.1], with a maximum discrepancy of 34%. Lin’s concordance coefficient was 0.98 [0.96; 1] (p < 0.001), meaning that concordance was excellent between the two methods.ConclusionComparison between radiochromic films and the software tool showed that the software is a suitable tool for a simple and reliable estimation of PSD. The software seems to be a good alternative to films, whose use remains complex.
High Performance Computing clusters and supercomputers are expensive and complex systems to manage. The software tools to manage these systems are also aging to the point where they are no longer actively developed and their methodology is antiquated. There has been a surge of new methodologies and software tools developed by the cloud providers to maximize availability of services and scalability of server deployment. The authors would like to utilize these new software tools to distribute our proof of concept, named Kraken, that will be responsible for booting and managing LANL's HPC systems in the future
Modern software development has gradually become more complex, leveraging available open-source software and third party components. This practice has raised questions about the provenance, licensing, versioning and compliance of reused code and its dependencies. Furthermore, it is par ticularly important to review such code fragments and third party components for known-vulnerabilities before they are included in a software product. A Software Bill of Materials (SBoM) is a mechanism to achieve such an analysis, provid ing transparency and visibility into a software product to both the software developer and its respective consumer. An SBoM lists information and details about all the elements constituting a piece of software and can, therefore, be used to evaluate associated security risk. While the concept of SBoMs is growing in popularity, it is still fairly new to many organizations, causing them to potentially struggle with pro ducing and processing SBoMs and limiting their widespread adoption. In this work, we delve into the area of SBoMs and present the state-of-the-art SBoM tools, creating a framework for analysis and categorizing them based on a diverse set of features and functionalities. We are the first to provide a detailed analysis of 83 open-source SBoM tools along with a perspective on how a potential SBoM user can select a tool based on their specific requirements. Our work aims to help promote understanding of this domain, thereby encouraging and furthering its overall adoption. We additionally seek to pave a path for future work in this area by providing recommendations to tool developers and users, researchers, and standardizing organizations.
Software applications for high resolution mass spectrometry (HRMS)-based non-targeted analysis (NTA) continue to enhance chemical identification capabilities. Given the variety of available applications, determining the most fit-for-purpose tools and workflows can be difficult. The Critical Assessment of Small Molecule Identification (CASMI) contests were initiated in 2012 to provide a means to evaluate compound identification tools on a standardized set of blinded tandem mass spectrometry (MS/MS) data. Five CASMI contests have resulted in recommendations, publications, and invaluable datasets for practitioners of HRMS-based screening studies. The US Environmental Protection Agency’s (EPA) CompTox Chemicals Dashboard is now recognized as a valuable resource for compound identification in NTA studies. However, this application was too new and immature in functionality to participate in the five previous CASMI contests. In this work, we performed compound identification on all five CASMI contest datasets using Dashboard tools and data in order to critically evaluate Dashboard performance relative to that of other applications. CASMI data was accessed via the CASMI webpage and processed for use in our spectral matching and identification workflow. Relative to applications used by former contest participants, our tools, data, and workflow performed well, placing more challenge compounds in the top five of ranked candidates than did the winners of three contest years and tying in a fourth. In addition, we conducted an in-depth review of the CASMI structure sets and made these reviewed sets available via the Dashboard. Our results suggest that Dashboard data and tools would enhance chemical identification capabilities for practitioners of HRMS-based NTA.
Abstract—: The development of software for calculating the cutting parameters in the course of machining or in simulations is discussed. The software developed may be used to create and test new cutting tools.
Integrating monitoring-based commissioning (MBCx) software tools into performance contracts is a timely topic given recent developments in MBCx software offerings and the growing number of MBCx deployments nationwide. Many commercial building owners have started to install MBCx software tools that tie in advanced metering infrastructure, building automation systems, and local weather data to enable ongoing commissioning and identify energy conservation measures. To support federal and commercial building owners in understanding, procuring, and implementing MBCx software tools, this report provides an overview of their capabilities, the MBCx process, and how MBCx can be integrated into - and benefit - each phase of a performance contract. This report is intended to spur increased use of MBCx in performance contracts, whether an agency has previously installed or is considering adding MBCx at the time of their project. Additionally, case studies illustrate successful experiences using MBCx within performance contracts at a university campus and across a large number of buildings managed by the General Services Administration.
Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities
Software is a workflow management system designed to capture documents and route for compliance and peer reviews. Software does not in itself contain any technical information but is used as a business system to manage and release information from a research organization.
While confidence in photovoltaic (PV) modeling software has always been essential, the rapid pace of new PV plant developments makes accuracy and credibility more critical than ever. Independent assessments, particularly through blind modeling comparisons, are therefore necessary to ensure unbiased benchmarking across PV modeling software. Previous studies have been limited by a narrow range of models compared, anonymized results, or system size. This study presents results from the first-ever onymous blind modeling comparison, evaluated using both lab- and utility-scale fixed-tilt, monofacial, south-facing systems at sub-hourly time intervals. Seven commercially used PV software tools were compared: 3E SynaptiQ, PlantPredict, PVsyst, RatedPower, SAM, SolarFarmer, and Solargis Evaluate. Predictions were submitted directly by software representatives, providing unique insights into each software’s implementation and resulting prediction behavior. Notable features, including plane-of-array (POA) transposition model, module temperature model, shading model, and performance model were analyzed and compared. Four summary tables compile these features of the software, serving as a resource to help users understand the methodological differences and select the most suitable software for their applications. The software tools show deviations from mean error in annual yield up to 2.5 % in the lab-scale system, increasing to 6.0 % for the utility-scale system. These differences arise from a combination of user decisions and the inherent behavior of the software, indicating the need for continuous and rigorous validation of modeling methods using these software tools against complex, real-world systems.
SAND2025-11738O Wind Turbine Airfoil Design Tools is a software tool that connects existing open-source airfoil analysis tools with optimization software to produce modern airfoil design for wind turbine applications. 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.
U.S. Department of Energy (DOE) energy system-analysis software tools have been used for years helping to identify over 170 TBTU/year of energy savings through the Save Energy Now “Energy Savings Assessment” and Better Plants “In-Plant Training” Programs. While most of the fundamental energy savings opportunities do not evolve much with time, computer technology never stops, leaving most of these software tools inoperable on modern computers.This has sparked an initiative to revitalize the DOE energy system analysis tools into a new, open-source, integrated software tool suite - MEASUR. Designed for industrial energy coordinators, engineers, utility-program implementers and individuals who are interested in improving system efficiency, MEASUR can aide users in identifying, assessing, and quantifying energy savings opportunities within pump, fan, process heating, steam, motors, and compressed air systems. In addition, the software contains over 40 equipment and property calculators for simple energy-related calculations and analyses.This paper will present a results comparison for each energy-consuming system using data from past DOE-sponsored energy assessments (to establish the accuracy of the savings algorithms) to validate and verify the accuracy of the energy and cost savings calculated by MEASUR. Additionally, an example highlighting 3rd-party development of the tool’s opensource framework into real-time sensor systems and efficiency-optimization will be presented.
Application Binary Interface (ABI) compatibility is essential for system or software updates to ensure that libraries continue to function. Tools that can assess a binary or library ABI can thus be used to make predictions about compatibility, and predict downstream bugs by informing developers and users about issues. In this work, we are interested in describing a set of well-known tools for assessing ABI, and testing them in a controlled set experiments to assess tool agreement. We run 7660 smaller experiments across tools (N=30,640 total results) to evaluate not only predictions, but also each tool’s ability to provide detail about underlying issues. In this paper, along with highlighting the problem of assessing ABI compatibility and critiquing the pros and cons of currently available tools, we provide guidance to developers interested to test ABI based on our empirical results and suggestions for future work.