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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Supplier Research & Analysis Approach

"The implementation of NASA GSFC's portfolio of mission projects relies upon inter-connected, multi-tiered supply chains of organizations operating under direct and indirect contracts and other agreements throughout the U.S. and around the world. These supply chains are subject to an inter-related array of technical/production, business, market and security risks that are amplified by the ongoing globalization of industry and technology and which can disrupt or threaten the production and delivery of products and services when needed and in conformance with requirements. In recognition of such risks and associated challenges, GSFC's SMA directorate launched an innovative Supplier Research and Analysis (SRA) capability three years ago to gain greater insight into the operating environment, performance, capabilities and viability of current and prospective suppliers for GSFC projects and proposals. The capability uses business intelligence techniques and primarily open source information resources as part of a cost-effective, non-intrusive methodology to produce several types of research and analysis reports. The reports are based on a holistic analytical framework encompassing key technical/production, business enterprise management, market and security factors, and feature in-depth information, summary information profiles, SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis, and candidate risk concerns in order to pro-actively support SMA and project management needs. The SRA capability, which is designed to complement and support ongoing SMA/project management activities and practices, has produced over 95 reports since its start-up in early 2015. This presentation addresses the approach, methodology and performance of the Supplier Research and Analysis (SRA) capability and its value in assuring the success of NASA mission projects. In doing so, the presentation provides lessons-learned, best practices, case examples and address how it fits into the development of an enterprise-level Supply Chain Risk Management capability."

supplier research and analysis↗
NASA NTRS2018

Supply Chain Research and Analysis for Space Systems

The implementation of NASA GSFC's portfolio of mission projects relies upon inter-connected, multi-tiered supply chains of organizations operating under direct and indirect contracts and other agreements throughout the U.S. and around the world. These supply chains are subject to an inter-related array of technical/production, business, market and security risks that are amplified by the ongoing globalization of industry and technology and which can disrupt or threaten the production and delivery of products and services when needed and in conformance with requirements. In recognition of such risks and associated challenges, GSFC's SMA directorate launched an innovative Supply Chain Research and Analysis capability three years ago to gain greater insight into the operating environment, performance, capabilities and viability of current and prospective suppliers for GSFC projects and proposals. The capability uses business intelligence techniques and primarily open source information resources as part of a cost-effective, non-intrusive methodology to produce several types of research and analysis reports. The reports are based on a holistic analytical framework encompassing key technical/production, business enterprise management, market and security factors, and feature in-depth information, summary information profiles, SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis, and candidate risk concerns in order to pro-actively support SMA and project management needs. The SRA capability, which is designed to complement and support ongoing SMA/project management activities and practices, has produced over 105 reports since its start-up in early 2015.This presentation addresses the approach, methodology and performance of the Supply Chain Research and Analysiscapability and its value in assuring the success of NASA mission projects. In doing so, the presentation provides lessons-learned, best practices, case examples and address how it fits into the development of an enterprise-level Supply Chain Risk Management capability.

supply chain risk management↗
NASA NTRS2007

Program Management Tool

The Program Management Tool (PMT) is a comprehensive, Web-enabled business intelligence software tool for assisting program and project managers within NASA enterprises in gathering, comprehending, and disseminating information on the progress of their programs and projects. The PMT provides planning and management support for implementing NASA programmatic and project management processes and requirements. It provides an online environment for program and line management to develop, communicate, and manage their programs, projects, and tasks in a comprehensive tool suite. The information managed by use of the PMT can include monthly reports as well as data on goals, deliverables, milestones, business processes, personnel, task plans, monthly reports, and budgetary allocations. The PMT provides an intuitive and enhanced Web interface to automate the tedious process of gathering and sharing monthly progress reports, task plans, financial data, and other information on project resources based on technical, schedule, budget, and management criteria and merits. The PMT is consistent with the latest Web standards and software practices, including the use of Extensible Markup Language (XML) for exchanging data and the WebDAV (Web Distributed Authoring and Versioning) protocol for collaborative management of documents. The PMT provides graphical displays of resource allocations in the form of bar and pie charts using Microsoft Excel Visual Basic for Application (VBA) libraries. The PMT has an extensible architecture that enables integration of PMT with other strategic-information software systems, including, for example, the Erasmus reporting system, now part of the NASA Integrated Enterprise Management Program (IEMP) tool suite, at NASA Marshall Space Flight Center (MSFC). The PMT data architecture provides automated and extensive software interfaces and reports to various strategic information systems to eliminate duplicative human entries and minimize data integrity issues among various NASA systems that impact schedules and planning.

Gawadiak, Yuri↗
DOE OSTI2018

Radiology and Enterprise Medical Imaging Extensions (REMIX)

Radiology and Enterprise Medical Imaging Extensions (REMIX) is a platform originally designed to both support the medical imaging-driven clinical and clinical research operational needs of Department of Radiology of The Ohio State University Wexner Medical Center. REMIX accommodates the storage and handling of “big imaging data,” as needed for large multi-disciplinary cancer-focused programs. The evolving REMIX platform contains an array of integrated tools/software packages for the following: (1) server and storage management; (2) image reconstruction; (3) digital pathology; (4) de-identification; (5) business intelligence; (6) texture analysis; and (7) artificial intelligence. These capabilities, along with documentation and guidance, explaining how to interact with a commercial system (e.g., PACS, EHR, commercial database) that currently exists in clinical environments, are to be made freely available.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

The moving target of visualization software for an increasingly complex world

Visualization has evolved into a mature scientific field and it has also become widely accepted as a standard approach in diverse fields, including physics, life sciences, and business intelligence. However, despite its successful development, there are still many open research questions that require customized implementations in order to explore and establish concepts, and to perform experiments and take measurements. Many methods and tools have been developed and published but most are stand-alone prototypes and have not reached a mature state that can be used in a reliable manner by collaborating domain scientists or a wider audience. In this study, we discuss the challenges, solutions, and open research questions that affect the development of sophisticated, relevant, and novel scientific visualization solutions with minimum overheads. Furthermore, we summarize and discuss the results of a recent National Institute of Informatics Shonan seminar on these topics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Inventory for Crystalline Silicon Module Recycling: Cooperative Research and Development (Final Report)

A critical challenge for the continued expansion of photovoltaics (PV) is to develop technically feasible, inexpensive and environmentally friendly practices for handling and recycling modules at the end of their usable life. The National Renewable Energy Laboratory (NREL) is requested by the Electric Power Research Institute (EPRI) to collect primary data regarding the environmental performance of currently operational PV module recycling facilities in Europe. Very little has been published regarding crystalline silicon (C-Si) module recycling. Thus, much effort will be needed in direct industry outreach, collection of information and other business intelligence strategies similar to NREL's approaches for developing cost models for PV manufacturing. The goal of this work effort is to produce a detailed inventory that accounts for physical (e.g., energy, water, materials) flows through each step of a C-Si recycling process. The inventory (a life cycle inventory, or LCI) shall be designed so that it can be extended to include an accounting of costs for each process step, inputs, etc. This work effort shall leverage prior LCI data collection NREL performed for the United States Department of Energy, Solar Energy Technologies Office, under the auspices of the U.S. contribution to International Energy Agency's Photovoltaics Power Systems (PVPS) Task 12 (Environmental Health and Safety), which SETO nominated NREL to chair. The primary purpose of this work effort is to augment the prior data collection to increase the sample size of manufacturers' primary data in the LCI.

14 SOLAR ENERGY↗
NASA NTRS2011

Deep Space Network-Wide Portal Development: Planning Service Pilot Project

The Deep Space Network (DSN) is an international network of antennas that supports interplanetary spacecraft missions and radio and radar astronomy observations for the exploration of the solar system and the universe. DSN provides the vital two-way communications link that guides and controls planetary explorers, and brings back the images and new scientific information they collect. In an attempt to streamline operations and improve overall services provided by the Deep Space Network a DSN-wide portal is under development. The project is one step in a larger effort to centralize the data collected from current missions including user input parameters for spacecraft to be tracked. This information will be placed into a principal repository where all operations related to the DSN are stored. Furthermore, providing statistical characterization of data volumes will help identify technically feasible tracking opportunities and more precise mission planning by providing upfront scheduling proposals. Business intelligence tools are to be incorporated in the output to deliver data visualization.

project development↗
NASA NTRS2019

Supply Chain Research and Analysis: Illuminating Risks in Complex Systems

Framing the strategic challenge posed by the interconnected, multitiered supply chains of mission projects managed by the NASA Goddard Space Flight Center. Discussing conditions and risks which can disrupt or threaten the availability, production and delivery of products and services for complex space systems. Utilizing a holistic analytical framework, business intelligence techniques, an integrated information system platform and analytics to produce insight into suppliers / supply chains and associated risks. Advancing supply chain risk management capabilities to support the successful performance of space missions.

supply chain risk management↗
NASA NTRS2018

Climate Lecture 20: The Educational Global Climate Model (EdGCM)

Climate change will profoundly impact Earth's environmental health as well as the world's economic and geopolitical landscape over the coming decades. The impacts of climate change are, in fact, already beginning to be experienced and have the potential to affect every living plant and animal on Earth within decades. Given this reality, every citizen of this planet should have the right to knowledge about the Earth's climate system and have the option to adapt to, or help mitigate the profound changes that are coming. In addition, a portion of the workforce needs to be capable of interpreting and analyzing climate information because, since the impacts of climate change will be widespread, pervasive, and continue to change over time, more professions will be interacting with climate data. We are already at, or past, the point where educators and their students require access to the scientific and technological resources - computer models, data, and visualization tools - that scientists use daily in the study of climate change. Although scientists use many methods to study Earth's climate system, global climate models (GCMs) have become the primary tools for exploring the complex interactions between components of the entire system: atmosphere, oceans, and land. GCMs are used to make projections of future climate change, to simulate climates of the past, and even to help scientists look for life on other planets. Like any model, a GCM can help people evaluate actions before they are taken. Like Business Intelligence software, they are Climate Intelligence tools. Unfortunately, GCMs are black boxes to most people. A previous chapter in this book by Gary Russell, entitled Building a Climate Model, is one example of the growing body of literature aimed at the general public describing the inner workings of global climate models. This literature goes a long way toward explaining climate model fundamentals. However, it will not be enough to alleviate their black-box nature unless people are afforded hands-on, authentic learning experiences as well.

Chandler, Mark A.↗
DOE OSTI2016

NDMAS implementation and data qualification for accident tolerant fuel experiments

In order to meet quality and regulatory requirements associated with the U.S. Department of Energy Accident Tolerant Fuels (ATF) experiments, all data and documentation associated with ATF component fabrication, characterization, traceability, testing and post irradiation examination are being managed using the Nuclear Data Management and Analysis System (NDMAS). NDMAS melds commercial off-the-shelf software to provide the full range of needed functionality. The core component of NDMAS is the SAS Enterprise Business Intelligence software, which provides data manipulation, statistical and graphical capabilities, and delivery of live content to web pages. Content delivery to both Idaho National Laboratory researchers and external users via a web interface is managed using SharePoint, which is access-controlled. Additionally, scripts, macros, and commercial wrappers may be used or written by the NDMAS team to control interfaces between SAS and the structured query language server, where much of the data reside. ATF experiment data and documentation stored in the NDMAS database may be utilized to support Nuclear Regulatory Commission licensing of ATF concepts for commercial Light Water Reactor demonstration. Therefore, Data Qualification Plans are being developed to screen and tag all document and data input for ATR water loop testing, Transient Reactor Testing (TREAT), and post irradiation examination. A project-wide document library has been created in the ATF NDMAS SharePoint Site for general unrestricted document and information access. Restricted libraries have also been created to allow individual customer access to restricted documents. Data from ATR water loop instrumented lead experimentation, TREAT, and post-irradiation examination will be available to program participants on the SharePoint site as they are collected. This offers a unique capability for team collaboration while these tests are being conducted. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

The Building Business Network (B-Biz): Addressing Gaps in the High-Performance Building Technology Market, Especially for Underserved Customers

Increased market intelligence and business model innovation is needed to build contractor confidence in high-performance building technologies in order to increase the speed and scale of adoption to meet the U.S. Department of Energy's building stock decarbonization goals. Although there have been important innovations in energy efficiency, affordability, and decarbonization of building technologies, consumers are not purchasing these technologies at the necessary speed and scale partially due to a gap in institutional understanding around barriers contractors face in providing and servicing these technologies. Small businesses in this market must mitigate risk around high-performance building technologies, limiting their opportunities in the market and impacting the rate of adoption. The Building Business Network (B-Biz) aims to provide high-performance building technology solutions to underserved customers by collaborating with local small businesses that provide and service high-performance building technologies in communities with the lowest rates of adoption. This research explores the current market, the importance of business models, and the opportunity to utilize small businesses to address market gaps in underserved communities.

B-Biz↗
NASA NTRS2002

Using the Web for Competitive Intelligence (CI) Gathering

Businesses use the Internet as a way to communicate company information as a way of engaging their customers. As the use of the Web for business transactions and advertising grows, so too, does the amount of useful information for practitioners of competitive intelligence (CI). CI is the legal and ethical practice of information gathering about competitors and the marketplace. Information sources like company webpages, online newspapers and news organizations, electronic journal articles and reports, and Internet search engines allow CI practitioners analyze company strengths and weaknesses for their customers. More company and marketplace information than ever is available on the Internet and a lot of it is free. Companies should view the Web not only as a business tool but also as a source of competitive intelligence. In a highly competitive marketplace can any organization afford to ignore information about the other players and customers in that same marketplace?

Rocker, JoAnne↗
DOE OSTI2018

Complex Network Analysis and Intelligent Monitoring Platform

Data Products has particular interest in developing an efficient network analysis and monitoring system that utilizes advanced machine learning methods to mine complex network data of the type generated within large data centers, with an objective to provide tangible business-usable intelligence. The Laboratory is currently the lead institution for a U.S. Department of Energy Office of Science (DOE/SC) network research project called BigData Express (BDE). The project seeks to provide an orchestration service for high-performance data movement of data sets for large-scale science. This collaboration is believed to potentially be a highly symbiotic one, with Data Products platform development benefiting from the rich sets of network data available in the BDE development environment, and BDE benefiting from the Data Products machine learning analysis of BDE-generated data movement.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Business Case Analysis for Artificial Intelligence-Large Language Model Technology Integration

AI-assisted processes are expected to enhance operational efficiency and improve decision-making, supporting the long-term economic viability of nuclear power plants. However, detailed business analyses of AI-generated cost savings are rarely performed. Given the recent industry interest in Large Language Model (LLM), the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program has conducted a comprehensive business case analysis of LLM Artificial Intelligence (AI) implementation in nuclear plant engineering workflows. The research employed three complementary business case approaches to evaluate impact of an LLM, using three representative engineering processes as use-cases: Boric Acid Corrosion (BAC) Evaluations, Maintenance Rule Evaluations, and 10 CFR 50.59 Screenings. Through detailed workload analyses and structured interviews, the study quantified significant efficiency improvements ranging from 11% to 59% across these processes. The research further considers how these efficiency gains could translate into tangible reliability improvements through enhanced engineering capacity. Analysis of historical plant trip data indicates that enabling engineers to focus on proactive reliability activities could provide substantial financial benefits through avoided outages, potentially generating greater value than the direct efficiency improvements alone. By documenting successful applications, implementation challenges, and strategic opportunities, this research provides nuclear utilities with a practical framework for evaluating the value of AI technology to support long-term operations through advanced digital technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

DOE SBIR Phase II Final Technical Report - Assessing Climate Change Effects on Wind Energy

Specialized Vertum Partners software tools were prototyped, tested and commercialized to allow wind energy stakeholders to assess the uncertainties of climate change on wind power production and distribution. This project resulted in three commercially proven products and a marketing tool. The first was a Weather Research and Forecasting Model (WRF) based resource evaluation system. The second was a web-based service providing global 10m wind data from multiple sources to wind industry subscription customers. The third product addressed the needs of our utility clients looking at climate change effects on electricity distribution. For this we collaborated on the Santa Ana Wildfire Threat Index (SAWTi), which was released publicly last quarter. Finally to promote these products and educate potential users we released “Gust or Bust”, a graphic-novel styled marketing publication.

17 WIND ENERGY↗
NASA NTRS1997

Intelligent Fasteners

Under a Small Business Innovation Research contract from Marshall Space Flight Center, Ultrafast, Inc. developed the world's first, high-temperature resistant, "intelligent" fastener. NASA needed a critical-fastening appraisal and validation of spacecraft segments that are coupled together in space. The intelligent-bolt technology deletes the self-defeating procedure of having to untighten the fastener, and thus upset the joint, during inspection and maintenance. The Ultrafast solution yielded an innovation that is likely to revolutionize manufacturing assembly, particularly the automobile industry. Other areas of application range from aircraft, computers and fork-lifts to offshore platforms, buildings, and bridges.

Source record↗
DOE OSTI2016

Beyond Benchmarking : Unlocking the Value for Utilities

This document provides guidance to help utilities identify new, untapped datasets related to the energy performance of buildings, and how this information can be applied to expand market intelligence and create business value.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1994

An intelligent ground operator support system

This paper presents first results of the project 'Technologien fuer die intelligente Kontrolle von Raumfahrzeugen' (TIKON). The TIKON objective was the demonstration of feasibility and profit of the application of artificial intelligence in the space business. For that purpose a prototype system has been developed and implemented for the operation support of the Roentgen Satellite (ROSAT), a scientific spacecraft designed to perform the first all-sky survey with a high-resolution X-ray telescope and to investigate the emission of specific celestial sources. The prototype integrates a scheduler and a diagnosis tool both based on artificial intelligence techniques. The user interface is menu driven and provides synoptic displays for the visualization of the system status. The prototype has been used and tested in parallel to an already existing operational system.

Goerlach, Thomas↗