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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Easy and Enticing: How a Collaborative Approach to Emerging Technology Adoption in the Commercial Building Sector Has Made its Mark

In 2012, the U.S. Department of Energy (DOE), in collaboration with interested partners (e.g., applicable trade groups), initiated a novel market transformation approach, technology adoption campaigns, to speed the adoption of new technologies that save energy and money in buildings - first with lighting and later with other building technologies. This approach couples technical performance evaluation, guidance, data tracking and technical assistance with recognition for exemplary performance and best practices. Campaigns can be designed around emerging technologies that have significant, cost-effective national energy savings potential and where there is strong public- and private-sector interest in sharing performance criteria and outcomes. Participants in the campaigns share project data with the national laboratories and DOE, benefit from technical support and assistance from objective experts, and highly value recognition for their accomplishments. DOE and its campaign partners benefit from accelerated adoption of new energy-saving technologies and engagement with manufacturers and end users that allows for data collection and insights into technology research needs. This paper documents the success, challenges, lessons learned, and energy and cost savings of lighting campaigns, and in many cases compares these findings with other campaign efforts. This paper also presents recommendations for how other programs of various sizes can employ this model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Easy and Enticing: How a Collaborative Approach to Emerging Technology Adoption in the Commercial Building Sector Has Made Its Mark

In 2012, the U.S. Department of Energy (DOE), in collaboration with interested partners (e.g., applicable trade groups), initiated a novel market transformation approach, technology adoption campaigns, to speed the adoption of new technologies that save energy and money in buildings—first with lighting and later with other building technologies. This approach couples technical performance evaluation, guidance, data tracking and technical assistance with recognition for exemplary performance and best practices. Campaigns can be designed around emerging technologies that have significant, cost-effective national energy savings potential and where there is strong public- and private-sector interest in sharing performance criteria and outcomes. Participants in the campaigns share project data with the national laboratories and DOE, benefit from technical support and assistance from objective experts, and highly value recognition for their accomplishments. DOE and its campaign partners benefit from accelerated adoption of new energy-saving technologies and engagement with manufacturers and end users that allows for data collection and insights into technology research needs. This paper documents the success, challenges, lessons learned, and energy and cost savings of lighting campaigns, and in many cases compares these findings with other campaign efforts. This paper also presents recommendations for how other programs of various sizes can employ this model.

Myer, Michael↗
DOE OSTI2017

Accelerated Thermal Aging of Harvested Hypalon Jacket for Remaining Useful Life Determination and Diagnosis

For nuclear power plants (NPPs) considering second license renewal for their operation beyond 60 years, knowledge of long-term operation, condition monitoring, and viability for the reactor components including reactor pressure vessel, concrete structures, and cable systems is essential. Such knowledge will provide NPPs with a game plan to predict performance and to estimate costs that are associated with monitoring or replacement programs for the affected systems. For cable systems that encompass a wide variety of materials, manufacturers, and in-plant location, accelerated aging of harvested cable jacket and insulation can provide insight as to remaining useful life and methods for monitoring. Accelerated thermal aging in air at temperatures between 80°C and 120°C was carried out on a multi-conductor control rod cable that had been in-service for over 30 years and was made by Boston Insulated Wire with Hypalon™ cable jacket and ethylene-propylene rubber insulation. From elongation at break (EAB) measurements and supporting Arrhenius analysis of the jacket material, an activation energy of 97.84 kJ/mol was estimated and the time to degradation, as represented by 50% EAB at the expected maximum operating temperature of 45°C, was estimated to be 80 years. These values were slightly below previous measurements on similar BIW Hypalon cable jacket and could either be attributed to in-service degradation or variations in material properties from process variations. In addition, results from indenter modulus measurements and Fourier transform infrared spectroscopy suggest possible markers that could be beneficial to monitor cable conditions.

cable aging, cable insulation, Hypalon, second lic↗
DOE OSTI2025

Reimagining Disassembly Interfaces With Visualization: Combining Instruction Tracing and Control Flow With DisViz

In applications where efficiency is critical, developers may examine their compiled binaries, seeking to understand how the compiler transformed their source code and what performance implications that transformation may have. This analysis is challenging due to the vast number of disassembled binary instructions and the many-to-many mappings between them and the source code. These problems are exacerbated as source code size increases, giving the compiler more freedom to map and disperse binary instructions across the disassembly space. Interfaces for disassembly typically display instructions as an unstructured listing or sacrifice the order of execution. Here, we design a new visual interface for disassembly code that combines execution order with control flow structure, enabling analysts to both trace through code and identify familiar aspects of the computation. Central to our approach is a novel layout of instructions grouped into basic blocks that displays a looping structure in an intuitive way. We add to this disassembly representation a unique block-based mini-map that leverages our layout and shows context across thousands of disassembly instructions. Finally, we embed our disassembly visualization in a web-based tool, DisViz, which adds dynamic linking with source code across the entire application. DizViz was developed in collaboration with program analysis experts following design study methodology and was validated through evaluation sessions with ten participants from four institutions. Participants successfully completed the evaluation tasks, hypothesized about compiler optimizations, and noted the utility of our new disassembly view. Our evaluation suggests that our new integrated view helps application developers in understanding and navigating disassembly code.

Computer science↗
DOE OSTI2018

Development of Mixed-Salt Technology for CO 2 Capture from Coal Power Plants

SRI International (SRI), in collaboration with Stanford University, OLI Systems (OLI), Politecnico de Milano (PoliMi), and Aqueous Systems Aps (ASApS) performed a 45-month effort to develop a promising Mixed-Salt Process (MSP) for carbon dioxide capture. The MSP combines existing ammonia and potassium-carbonate technologies with improved absorption steps for rate enhancement and ammonia emission reduction and a novel selective regeneration process with a high-pressure CO 2 product to introduce a new and advanced transformational solvent-based technology. The striking advantages of the SRI MSP include: low heat of reaction, high loading of CO 2 , high-pressure regeneration of > 99% pure dry CO 2 , low sensitivity to impurities, low process cost, use of a non-degradable low-cost solvent with a very low carbon footprint for its production, low emissions, and reduced water use compared to the state-of-the-art ammonia-based and amine technologies. The overall objective of the project was to develop and test a solvent-based CO 2 capture technology that can capture CO 2 from existing or new pulverized coal (PC) power plants at low cost. Our specific goal was to test SRI’s newly developed MSP at the large bench-scale level to demonstrate that the process could capture CO 2 at high efficiency (> 90%) with very high CO 2 loading (> 10 wt.%), require less than 2 GJ/tonne for solvent regeneration, and produce a CO 2 stream at high pressure with a purity > 95 vol.%. This 45-month MSP development program was designed to conduct (1) extensive test campaigns with different process flowsheet variants, and (2) detailed thermodynamic, kinetic, and process modeling. These tests and models were very important to identify any issues associated with the process in the early stages and then resolve them before moving into the next scale-up (> 1 MWe scale) testing. The technology development plan consisted of balanced experimental and process modeling activities as shown in Figure i. Such an approach reduces the risks associated with the process operability at large scales and provides capital and operating expenditure (CAPEX/OPEX) predictions with improved accuracies. Under the MSP development program at SRI, we performed an aggressive testing campaign with individual subsystems as well as integrated CO 2 capture and regeneration system to identify the best operating conditions. The project was carried out in two budget periods (BP1 & BP2).

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2017

Accelerated thermal aging of harvested hypalon jacket for remaining useful life determination and diagnosis - 210

For nuclear power plants (NPPs) considering second license renewal for their operation beyond 60 years, knowledge of long-term operation, condition monitoring, and viability for the reactor components including reactor pressure vessel, concrete structures, and cable systems is essential. Such knowledge will provide NPPs with a game plan to predict performance and to estimate costs that are associated with monitoring or replacement programs for the affected systems. For cable systems that encompass a wide variety of materials, manufacturers, and in-plant location, accelerated aging of harvested cable jacket and insulation can provide insight as to remaining useful life and methods for monitoring. Accelerated thermal aging in air at temperatures between 80 deg. C and 120 deg. C was carried out on a multi-conductor control rod cable that had been inservice for over 30 years and was made by Boston Insulated Wire with Hypalon{sup TM} cable jacket and ethylene-propylene rubber insulation. From elongation at break (EAB) measurements and supporting Arrhenius analysis of the jacket material, an activation energy of 97.84 kJ/mol was estimated and the time to degradation, as represented by 50% EAB at the expected maximum operating temperature of 45 deg. C, was estimated to be 80 years. These values were slightly below previous measurements on similar BIW Hypalon cable jacket and could either be attributed to inservice degradation or variations in material properties from process variations. In addition, results from indenter modulus measurements and Fourier transform infrared spectroscopy suggest possible markers that could be beneficial to monitor cable conditions. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Artificial Intelligence/Machine Learning Technology in Power System Applications

The primary purpose of this report is to provide an overview of the advancement in artificial intelligence and machine learning (AI/ML) technologies and their applications in power systems. It offers a foundation for understanding the transformative role of AI/ML in power systems and aims to stimulate further research and development in this area. This report begins with a historical perspective of AI/ML technologies, then explores their advancement to today’s prominence. The document highlights key contributors to the success of AI/ML technologies, including increased computational power, greater data availability, innovative algorithms, and advanced tools. It further introduces various AI/ML techniques, including supervised, unsupervised and reinforcement learning, graph neural networks, and generative AI. It also emphasizes the critical importance of ensuring the safety, security, and trustworthiness of these AI/ML techniques within this sector. The report reviews the recent representative advancements in various power system applications enhanced by AI/ML techniques, underscoring key developments and their transformative impact as evidenced by numerous studies. It also explores both the opportunities and challenges associated with the application of AI/ML technologies to improve power system applications. While the report extensively covers AI/ML applications in power systems, focusing primarily on the technical and operational aspects, it may not thoroughly explore the sociopolitical, economic, and broader regulatory implications of AI/ML integration in power systems. AI/ML techniques hold significant potential for enhancing power system applications; however, they are not omnipotent. It is crucial to acknowledge their limitations and understand that they may not be able to address all challenges in the power system domain. Various factors must be considered that influence the implementation, adoption, and effectiveness of AI/ML solutions, including but not limited to safety, security, transparency, and trustworthiness. Additionally, the incorporation of advanced human–machine interfaces is essential, as it enables humans to validate the effectiveness of AI/ML solutions while remaining actively engaged, fostering trust in AI/ML deployment. Finally, the report summarizes AI/ML research activities supported by the Department of Energy (DOE) Office of Electricity (OE) through the Advanced Grid Modeling (AGM) program. The work aligns with the interests and mission of DOE-OE AGM, with the report serving as a resource for identifying existing progress and for pinpointing future applications within AI/ML that need further exploration and support.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Basic Research Needs for High Energy Physics Detector Research & Development: Report of the Office of Science Workshop on Basic Research Needs for HEP Detector Research and Development: December 11-14, 2019

Transformative discovery in science is driven by innovation in technology. Our boldest undertakings in particle physics have at their foundation precision instrumentation. To reveal the profound connections underlying everything we see from the smallest scales to the largest distances in the Universe, to understand its fundamental constituents, and to reveal what is still unknown, we must invent, develop, and deploy advanced instrumentation. Investments in High Energy Physics (HEP) enabled by instrumentation have been richly rewarded with discoveries of the tiny masses of the neutrinos, the origin of mass itself: the enigmatic Higgs boson, and the surprising accelerating expansion of the Universe. What we have learned is remarkable, unexpected, exciting and mysterious; raising many new questions waiting to be answered. The quest to answer them drives innovation that improves the nation's health, wealth, and security, inspiring the public and drawing young people to science. Excellence and innovation come most effectively from diverse teams of people. Success, therefore, depends critically on attracting, engaging, and supporting a diverse cadre of young people to the field, and ensuring an inclusive environment at all levels. The program laid out in the 2014 Particle Physics Projects Prioritization Panel (P5) report "Building for Discovery - A Strategic Plan for U.S. Particle Physics in a Global Context" guides current and near future experiments to exploit these and other discoveries, and the instrumentation innovation they require, to push the frontiers of science into new territory. To explore this territory HEP will soon embark on planning the next generation of experiments. Realizing these experiments will require giant leaps in capabilities beyond the instrumentation of today. Accordingly, now is a pivotal moment to invest in the accelerated development of cost-effective instrumentation with greatly improved sensitivity and performance that will make measurable the unmeasurable, enabling a tool-driven revolution to open the door to future discoveries. Historic scientific opportunities await us, enabled by executing the instrumentation research plan outlined here.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Scale-Up of Coal-Based Supercritical CO 2 cycle technology

The Allam Cycle is a transformational technology that enables a step change in the performance, efficiency, and cost of electricity for electrical generating units by using supercritical CO 2 (sCO 2 ) as the working fluid in the turbine for power generation. The objectives of this Phase I effort were to select a host site for a large pilot system through a process of down selection, develop a conceptual design, and conduct a pre-front-end engineering design (pre-FEED) study for a sCO 2 cycle pilot plant that uses domestic coal reserves as the primary feedstock, thereby furthering technology development of the coal-based Allam Cycle. The project was divided into four main tasks: 1) Project Management and Planning; 2) Conceptual Pilot Plant Definition and Host Site Selection; 3) Preliminary Design, Cost, and Schedule Development; and 4) Commitments and Environmental Information Volume (EIV). All project management activities occurred in Task 1. Host site selection was conducted in Task 2, while conceptual design and pre-FEED activities took place under Task 3. Task 4 enhanced the project by securing commitments for the next phase of the program and completing an initial EIV. The Great Plains Synfuels Plant (GPSP) has been selected as the host site for the large-scale pilot, and its owner, Dakota Gasification Company (DGC), is a committed partner. GPSP was compared to two other host site candidates during Phase I: the existing natural gas Allam Cycle facility in La Porte, Texas, and the Energy & Environmental Research Center’s (EERC) high-bay demonstration facility in Grand Forks, North Dakota. Costs for hosting the pilot plant were estimated for each facility, and those costs are shown in Table ES-1. Based on these estimates, the DGC site was clearly shown to be the lowest cost option and was selected as the host site for the project.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2017

Evaluation of Used Fuel Disposition in Clay-Bearing Rock

The DOE R&D program under the Spent Fuel Waste Science Technology (SFWST) campaign has made key advances in experimental and modeling aspects of chemical and physical phenomena towards the long-term safety assessment of nuclear waste disposition in deep clay/shale/argillaceous rock. Experimental activities on clay barrier interactions with fluids and radionuclides provide the much needed knowledge to evaluate engineered barrier system (EBS) performance. Thermal-Hydrological-Mechanical-Chemical (THMC) model development of clay provides a rigorous simulation platform to assess the complex dynamic behavior of engineered and natural barrier materials in response to coupled process phenomena induced by heat-generating nuclear waste. This report describes the ongoing disposal R&D efforts on the advancement and refinement of coupled THMC process models, hydrothermal experiments and geochemical modeling of on barrier material (clay/metal) interactions, spent fuel and canister material degradation, radiolytic phenomena and UO 2 degradation, and thermodynamic database development. These play an important role to the evaluation of sacrificial zones as part of the EBS exposure to thermally-driven chemical and transport processes. Clay-zeolite phase equilibria play a key role in the mineralogical transformations of clay barrier conducive to loss in swelling properties but also in controlling H 2 0 uptake/release through hydration/dehydration reactions. The result is volume changes can affect the interface / bulk phase porosities, transport, and the mechanical (stress) state of the bentonite barrier. Characterization studies on barrier samples (bentonite/cement) from controlled tests at underground research laboratories (URLs) provide key insights into barrier materials interactions at EBS interfaces. Spent fuel degradation modeling coupled with canister and cladding corrosion effects demonstrate the strong influence of H 2 generation on the source term.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Population-based heteropolymer design to mimic protein mixtures

Biological fluids, the most complex blends, have compositions that constantly vary and cannot be molecularly defined. Despite these uncertainties, proteins fluctuate, fold, function and evolve as programmed. We propose that in addition to the known monomeric sequence requirements, protein sequences encode multi-pair interactions at the segmental level to navigate random encounters; synthetic heteropolymers capable of emulating such interactions can replicate how proteins behave in biological fluids individually and collectively. Here, we extracted the chemical characteristics and sequential arrangement along a protein chain at the segmental level from natural protein libraries and used the information to design heteropolymer ensembles as mixtures of disordered, partially folded and folded proteins. For each heteropolymer ensemble, the level of segmental similarity to that of natural proteins determines its ability to replicate many functions of biological fluids including assisting protein folding during translation, preserving the viability of fetal bovine serum without refrigeration, enhancing the thermal stability of proteins and behaving like synthetic cytosol under biologically relevant conditions. Molecular studies further translated protein sequence information at the segmental level into intermolecular interactions with a defined range, degree of diversity and temporal and spatial availability. This framework provides valuable guiding principles to synthetically realize protein properties, engineer bio/abiotic hybrid materials and, ultimately, realize matter-to-life transformations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Decaf: Decoupled Dataflows for In Situ High-Performance Workflows

Decaf is a dataflow system for the parallel communication of coupled tasks in an HPC workflow. The dataflow can perform arbitrary data transformations ranging from simply forwarding data to complex data redistribution. Decaf does this by allowing the user to allocate resources and execute custom code in the dataflow. All communication through the dataflow is efficient parallel message passing over MPI. The runtime for calling tasks is entirely message-driven; Decaf executes a task when all messages for the task have been received. Such a messagedriven runtime allows cyclic task dependencies in the workflow graph, for example, to enact computational steering based on the result of downstream tasks. Decaf includes a simple Python API for describing the workflow graph. This allows Decaf to stand alone as a complete workflow system, but Decaf can also be used as the dataflow layer by one or more other workflow systems to form a heterogeneous task-based computing environment. In one experiment, we couple a molecular dynamics code with a visualization tool using the FlowVR and Damaris workflow systems and Decaf for the dataflow. In another experiment, we test the coupling of a cosmology code with Voronoi tessellation and density estimation codes using MPI for the simulation, the DIY programming model for the two analysis codes, and Decaf for the dataflow. Such workflows consisting of heterogeneous software infrastructures exist because components are developed separately with different programming models and runtimes, and this is the first time that such heterogeneous coupling of diverse components was demonstrated in situ on HPC systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Development of a Pre-Combustion CO 2 Capture Process Using High-Temperature PBI Hollow-Fiber Membranes

The overall objective of this project was to evaluate the advantages of transformational polybenzimidazole (PBI) polymer hollow-fiber membrane (HFM)-based, carbon dioxide (CO 2 ) capture and purification technology at bench-scale using an actual coal-derived syngas stream from a coal gasification facility. The project was carried out over two budget periods. The technical objectives in Budget Period 1 (BP1) included preparing HFs and modules and upgrading the available skid for field testing. The technical objectives for BP2 were to field-test the skid unit with actual coal-derived syngas from an oxygen-blown gasifier to obtain performance data, update the Techno-Economic Analysis (TEA) that would assist with future process scale-up, and provide information on the design of a small pilot-scale test unit. The goal was to advance the PBI-HFM CO 2 capture and gas separation system for pre-combustion applications beyond second-generation economic performance predictions and make progress toward meeting overall fossil energy performance goals of CO 2 capture with 95% CO 2 purity at a cost of electricity (COE) 30% less than baseline capture approaches. The research program was designed with progressive technical tasks leading to both dynamic and steady-state testing of the PBI-HFM skid with actual coal-derived syngas. The work plan was to: (1) fabricate sufficient Generation-2 (GEN-2) fibers for module fabrication; (2) upgrade the fiber skid to accommodate large fiber modules for bench-scale field testing; (3) conduct dynamic and steady-state testing with coal-derived syngas from an oxygen-blown gasifier and obtain system performance data; (4) perform a TEA and environmental, health, and safety (EH&S) assessment; (5) update the State-Point Data Table, Technology Gap Analysis (TGA), and Technology Maturation Plan (TMP); (6) uninstall and return the test skid to the Recipient’s facilities; and (7) submit a Final Report that describes the results and analysis of the project research effort.

03 NATURAL GAS↗
DOE OSTI2024

Initial Development of Fusion Magnet Simulation Capabilities for Performance and Safety Evaluation Using the MOOSE Framework

Fusion energy holds the promise of being a transformative technology as a carbon-neutral, sustainable source of energy. Whole device modeling and the development of fusion digital twins will be increasingly important for emerging fusion device concepts at both national laboratories and within the commercial fusion industry. However, meeting the challenge of whole device modeling of fusion energy devices requires robust, multiphysics, multiscale modeling and simulation technologies capable of running on large-scale supercomputers. Detailed analysis of individual systems at-scale is also required to ensure safe and efficient operation as well as provide the safety basis for future device designs and licensing activities. In a tokamak, toroidal and poloidal magnets confine and shape the fusion plasma to promote the fusion reaction. High plasma temperatures and high magnetic field requirements in modern design concepts (leading to high amounts of energy stored within each magnet) impose electrical, thermal, and mechanical loads on the magnet components, which in turn impacts the safety considerations of the magnet and their supporting systems. Idaho National Laboratory (INL) has a history of working in this space, including development and benchmarking of the Magnetic System Circuitry Analysis Program (MSCAP) and Magnet Arcing (MAGARC) codes to study magnet quench events; notably, MAGARC was used to study quenching during the ITER Engineering Design Activity. However, these legacy codes and capabilities are not parallel and scalable, and new tools are required for future advances in this area, which leads to the INL-developed Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Developed originally for fission reactor systems under United States Department of Energy, Office of Nuclear Energy modeling and simulation programs, the MOOSE framework has been well-suited to multiscale, multiphysics modeling and simulation needs for nuclear systems. The framework is open-source, well-tested, under continuous development and deployment, and developed to a Nuclear Quality Assurance, Level 1 software quality standard. MOOSE has also been used in the fusion space previously in several projects: INL’s Tritium Migration Analysis Program, Version 8 (TMAP8) for tritium migration, UK Atomic Energy Authority’s A Unified Resource for OpenMC (fusion) Reactor Applications (AURORA) code for fusion thermo-mechanical and neutronics analysis, and Argonne National Laboratory’s Cardinal for high-fidelity computational fluid dynamics and neutronics. However, to model superconducting magnets, several MOOSE enhancements are required: additions to the current MOOSE electromagnetic capabilities, new material libraries for superconductors of interest (such as YBCO), as well as fusion-specific models for thermo-mechanics. This talk will discuss initial development activities to build these capabilities in MOOSE, focusing on initial validation and benchmarking activities. Proposed coupling workflows and future work to support the simulation of fusion magnets and magnet structural assemblies for performance and safety evaluation in MOOSE will also be discussed.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Artificial Intelligence for (AI) Nuclear Security: Expert Perspectives on AI Priorities for the Office of International Nuclear Security

Artificial intelligence (AI) has the potential to transform nuclear security operations, offering opportunities to enhance effectiveness while simultaneously introducing new challenges. As AI technologies rapidly evolve, agencies across the United States Government (USG) are researching, implementing, and evaluating various AI models and systems. Given the broad capabilities and applications of these technologies, it is essential for each agency to identify and articulate those areas where it can make meaningful contributions aligned with its mission and expertise. To address this need for strategic focus, in late Fiscal Year 2025 (FY2025), the Office of International Nuclear Security (INS) established an AI Task Force (AITF) to gather input from subject matter experts (SMEs) regarding the most appropriate role INS could serve in researching, evaluating, or implementing AI for nuclear security. The AITF engaged 15 experts from national laboratories with backgrounds in cyber security, physical security, transport security, insider threat mitigation, nuclear engineering, human-systems engineering, and AI/ML development. This white paper summarizes the insights gathered from these SMEs and presents a potential roadmap for INS engagement with AI technologies. The recommendations outlined here are intended to inform INS leadership as they make strategic decisions about resource allocation and program direction in this rapidly evolving technological domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Construction Methodology Transformation for the Benefit of Workforce Development

Construction is a key economic engine driving both national and global economies. While manual, onsite construction methods dominate the U.S. construction industry, a major shift towards offsite methods has been underway due to its efficiency, speed, and potential cost savings. The workforce necessary for offsite construction growth does not exist in its current form because of the focus on onsite methodologies and the lack of exposure to offsite building methods at all levels of a student’s learning journey. The growth of the U.S. construction industry and competitiveness in an increasingly global construction market over the coming decades can only be supported by a dramatic increase in the use of offsite methods, which requires ramping up workforce training for certain skillsets. The goal of Construction Methodology Transformation for the Benefit of Workforce Development was to understand the opportunities and barriers in both education and industry and to identify best practices for offering curriculum and training to educators, industry, and students that would support skills needed for careers in offsite construction. Our team proposed combining three offsite construction workforce development needs: content development, exposure and training, and job placement - under a single Platform model that would increase experience and career opportunities for students and help match them with potential industry members. Through our proposed solution we expected to see: developed offsite curriculum being utilized by educators and students; an increase in the identification of construction technology and offsite construction methods; an average increase in knowledge gain of at least 25% after participation in pilots; better equipped candidates who are prepared for jobs in offsite construction; and a beta workforce development platform that helps build more pathways for students looking for careers in offsite construction. The two pilots included almost 250 students and resulted in an average knowledge gain of 37 percent. Our research has identified areas of opportunity, for both education and industry to make collaborative training programs more efficient and successful. The chosen techniques for this program are extremely effective when both the school and factory have solid processes and cultures in place to accept students into training programs. This project serves as an important stepping stone to industrywide collaboration to move workforce development for offsite construction forward across the country. With continued collaboration programs like this can provide much needed early exposure and training in offsite construction and we can begin to fill important positions for the future of construction.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1991

Solar-A Prelaunch Mission Operation Report (MOR)

The Solar-A mission is a Japanese-led program with the participation of the United States and the United Kingdom. The Japanese Institute of Space and Astronautical Science (ISAS) is providing the Solar-A spacecraft, two of the four science instruments, the launch vehicle and launch support, and the principal ground station with Operational Control Center. NASA is providing a science instrument, the Soft X-ray Telescope (SXT)and tracking support using the Deep Space Network (DSN) ground stations. The United Kingdom s Science and Engineering Research Council (SERC) provides the Bragg Crystal Spectrometer. The Solar-A mission will study solar flares using a cluster of instruments on a satellite in a 600 km altitude, 31 degree inclination circular orbit. The emphasis of the mission is on imaging and spectroscopy of hard and soft X-rays. The principal instruments are a pair of X-ray imaging instruments, one for the hard X-ray range and one for the soft X-ray range. The Hard X-Ray Telescope (HXT), provided by ISAS, operates in the energy range of 10-100 keV and uses an array of modulation collimators to record Fourier transform images of the non-thermal and hot plasmas that are formed during the early phases of a flare. These images are thought to be intimately associated with the sites of primary energy release. The Soft X-Ray Telescope (SXT), jointly provided by NASA and ISAS, operates in the wavelength range of 3-50 Angstroms and uses a grazing incidence mirror to form direct images of the lower temperature (but still very hot) plasmas that form as the solar atmosphere responds to the injection of energy. The SXT instrument is a joint development effort between the Lockheed Palo Alto Research Laboratory and the National Astronomical Observatory of Japan. The U.S. effort also involves Stanford University, the University of California at Berkeley and the University of Hawaii, who provide support in the areas of theory, data analysis and interpretation, and ground-based observations. The hard and soft X-ray telescopes both have an alignment sensor, operating in the visual region of the spectrum, to provide co-alignment information.

Source record↗
DOE OSTI2016

FORTÉ Machine Learning

Of the non-corrupted data collected by the Orbiting Experiment (forté) satellite’s Photo-Diode Detector during the year 2001, I estimate that 7.9% of 914 894 signals are noise. My result differs dramatically from Guillen’s estimate of 96%. To arrive at this estimate, I used Gaussian mixture model (GMM) clustering–unsupervised machine learning–to aggregate the wave forms into groups based on the absolute value of the lowest 25 positive frequency discrete Fourier transform coefficients. Then, I marked several of the groups as noise by inspecting a random sampling of wave forms from each group. Marking groups as either noise or non-noise is a supervised binary classification operation. After removing the signals in noise groups from further consideration, I clustered the remaining signals into families. Again, I used a GMM, but for the familial clustering I used a Non-Negative Matrix Factorization feature vector transform. The result was 9 distinct families of lightning signals, as well as a second stage of noise filtering. To efficiently represent the entirety of the signal space, I broke each family into deciles based on their distance from the family mean. In this case, distance means the log-likelihood based on the GMM. Signals in lower deciles are more similar in shape and amplitude to their family average. I took the top 200 samples from each decile of each group, resulting in 18 000 signals. These signal approximately represent the entirety of the forté observations. To represent outliers, I also kept a zoo of the 1000 signals furthest from any family’s average. All told, the resulting data set represents the forté data with a reduction of about 51:1. To allow synthesis of an arbitrarily large number of test signals, I also captured each family’s average signal and the time-sample covariance matrix over the signals in each family. Using these two pieces of information, I can synthesize new waveforms by using a Gaussian random realization from the family average and covariance matrix. I wrote a program to test the synthesis quality. The program shows me two signals on the screen, one synthesized and one randomly drawn from the data. I attempted to identify the synthesized signal. Although the synthesis is imperfect, in an A/B comparison I only correctly chose the synthesized signal 36% of the time.

97 MATHEMATICS AND COMPUTING↗