Results for “Collaborative Learning” — Page 34

DOE OSTI2020

Ubiquitous Traffic Volume Estimation through Machine-Learning Procedure

Traffic volume data is one of the most important metrics for accurate assessment of the performance of a transportation system. Quality volume data is required to effectively assess extent of delay and congestion, detect real-time perturbations to the network, and understand traffic patterns during major weather events. Traffic volume on freeways are typically collected through continuous count stations installed by state DOTs, while there is lack of traffic volume observability on off-freeway roads. The National Renewable Energy Laboratory (NREL), in Collaboration with the I-95 Corridor Coalition and the University of Maryland, extended its research into estimating volumes anywhere anytime from industry probe based data for off-freeway roads. NREL combined vehicle probe count data with several other data sets (speed, whether, roadway geometry, time-of-day, day-of-week, etc.) to estimate hourly volumes as well as AADTs. The research validated and demonstrated the machine learning model, namely XGBoost, using data collected from Pennsylvania, North Carolina, and Tennessee.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Crowd-Sourced Data and Analysis Tools for Advancing the Chemical Vapor Deposition of Graphene: Implications for Manufacturing

Industrial production of graphene by chemical vapor deposition (CVD) requires more than the ability to synthesize large domain, high-quality graphene in a lab reactor. The integration of graphene in the fabrication process of electronic devices requires the cost-effective and environmentally friendly production of graphene on dielectric substrates, but current approaches can only produce graphene on metal catalysts. Sustainable manufacturing of graphene should also conserve the catalyst and reaction gases, but today the metal catalysts are typically dissolved after synthesis. Progress toward these objectives is hindered by the hundreds of coupled synthesis parameters that can strongly affect CVD of low-dimensional materials and poor communication in the published literature of the rich experimental data that exists in individual laboratories. We report here on a platform, "graphene recipes for synthesis of high quality material" (Gr-ResQ: pronounced graphene rescue), which includes powerful new tools for data-driven graphene synthesis. At the core of Gr-ResQ is a crowd-sourced database of CVD synthesis recipes and associated experimental results. The database captures similar to 300 parameters ranging from synthesis conditions such as a catalyst material and preparation steps, to ambient lab temperature and reactor details, as well as resulting Raman spectra and microscopy images. These parameters are carefully selected to unlock the potential of machine-learning models to advance synthesis. A suite of associated tools enable fast, automated, and standardized processing of Raman spectra and scanning electron microscopy images. To facilitate community-based efforts, Gr-ResQ provides tools for cyber-physical collaborations among research groups, allowing experiments to be designed, executed, and analyzed by different teams. Gr-ResQ also allows publication and discovery of recipes via the Materials Data Facility, which assigns each recipe a unique identifier when published and collects parameters in a search index. We envision that this holistic approach to data-driven synthesis can accelerate CVD recipe discovery and production control and open opportunities for advancing not only graphene but also many other 1D and 2D materials.

36 MATERIALS SCIENCE↗

NASA NTRS1996

Development of Collaborative Research Initiatives to Advance the Aerospace Sciences-via the Communications, Electronics, Information Systems Focus Group

The primary goal of the Adaptive Vision Laboratory Research project was to develop advanced computer vision systems for automatic target recognition. The approach used in this effort combined several machine learning paradigms including evolutionary learning algorithms, neural networks, and adaptive clustering techniques to develop the E-MOR.PH system. This system is capable of generating pattern recognition systems to solve a wide variety of complex recognition tasks. A series of simulation experiments were conducted using E-MORPH to solve problems in OCR, military target recognition, industrial inspection, and medical image analysis. The bulk of the funds provided through this grant were used to purchase computer hardware and software to support these computationally intensive simulations. The payoff from this effort is the reduced need for human involvement in the design and implementation of recognition systems. We have shown that the techniques used in E-MORPH are generic and readily transition to other problem domains. Specifically, E-MORPH is multi-phase evolutionary leaming system that evolves cooperative sets of features detectors and combines their response using an adaptive classifier to form a complete pattern recognition system. The system can operate on binary or grayscale images. In our most recent experiments, we used multi-resolution images that are formed by applying a Gabor wavelet transform to a set of grayscale input images. To begin the leaming process, candidate chips are extracted from the multi-resolution images to form a training set and a test set. A population of detector sets is randomly initialized to start the evolutionary process. Using a combination of evolutionary programming and genetic algorithms, the feature detectors are enhanced to solve a recognition problem. The design of E-MORPH and recognition results for a complex problem in medical image analysis are described at the end of this report. The specific task involves the identification of vertebrae in x-ray images of human spinal columns. This problem is extremely challenging because the individual vertebra exhibit variation in shape, scale, orientation, and contrast. E-MORPH generated several accurate recognition systems to solve this task. This dual use of this ATR technology clearly demonstrates the flexibility and power of our approach.

Knasel, T. Michael↗

DOE OSTI2016

TU-AB-204-00: CDRH/FDA Regulatory Processes and Device Science Activities

The responsibilities of the Food and Drug Administration (FDA) have increased since the inception of the Food and Drugs Act in 1906. Medical devices first came under comprehensive regulation with the passage of the 1938 Food, Drug, and Cosmetic Act. In 1971 FDA also took on the responsibility for consumer protection against unnecessary exposure to radiation-emitting devices for home and occupational use. However it was not until 1976, under the Medical Device Regulation Act, that the FDA was responsible for the safety and effectiveness of medical devices. This session will be presented by the Division of Radiological Health (DRH) and the Division of Imaging, Diagnostics, and Software Reliability (DIDSR) from the Center for Devices and Radiological Health (CDRH) at the FDA. The symposium will discuss on how we protect and promote public health with a focus on medical physics applications organized into four areas: pre-market device review, post-market surveillance, device compliance, current regulatory research efforts and partnerships with other organizations. The pre-market session will summarize the pathways FDA uses to regulate the investigational use and commercialization of diagnostic imaging and radiation therapy medical devices in the US, highlighting resources available to assist investigators and manufacturers. The post-market session will explain the post-market surveillance and compliance activities FDA performs to monitor the safety and effectiveness of devices on the market. The third session will describe research efforts that support the regulatory mission of the Agency. An overview of our regulatory research portfolio to advance our understanding of medical physics and imaging technologies and approaches to their evaluation will be discussed. Lastly, mechanisms that FDA uses to seek public input and promote collaborations with professional, government, and international organizations, such as AAPM, International Electrotechnical Commission (IEC), Image Gently, and the Quantitative Imaging Biomarkers Alliance (QIBA) among others, to fulfill FDA’s mission will be discussed. Learning Objectives: Understand FDA’s pre-market and post-market review processes for medical devices Understand FDA’s current regulatory research activities in the areas of medical physics and imaging products Understand how being involved with AAPM and other organizations can also help to promote innovative, safe and effective medical devices J. Delfino, nothing to disclose.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-AB-204-01: Device Approval Process

The responsibilities of the Food and Drug Administration (FDA) have increased since the inception of the Food and Drugs Act in 1906. Medical devices first came under comprehensive regulation with the passage of the 1938 Food, Drug, and Cosmetic Act. In 1971 FDA also took on the responsibility for consumer protection against unnecessary exposure to radiation-emitting devices for home and occupational use. However it was not until 1976, under the Medical Device Regulation Act, that the FDA was responsible for the safety and effectiveness of medical devices. This session will be presented by the Division of Radiological Health (DRH) and the Division of Imaging, Diagnostics, and Software Reliability (DIDSR) from the Center for Devices and Radiological Health (CDRH) at the FDA. The symposium will discuss on how we protect and promote public health with a focus on medical physics applications organized into four areas: pre-market device review, post-market surveillance, device compliance, current regulatory research efforts and partnerships with other organizations. The pre-market session will summarize the pathways FDA uses to regulate the investigational use and commercialization of diagnostic imaging and radiation therapy medical devices in the US, highlighting resources available to assist investigators and manufacturers. The post-market session will explain the post-market surveillance and compliance activities FDA performs to monitor the safety and effectiveness of devices on the market. The third session will describe research efforts that support the regulatory mission of the Agency. An overview of our regulatory research portfolio to advance our understanding of medical physics and imaging technologies and approaches to their evaluation will be discussed. Lastly, mechanisms that FDA uses to seek public input and promote collaborations with professional, government, and international organizations, such as AAPM, International Electrotechnical Commission (IEC), Image Gently, and the Quantitative Imaging Biomarkers Alliance (QIBA) among others, to fulfill FDA’s mission will be discussed. Learning Objectives: Understand FDA’s pre-market and post-market review processes for medical devices Understand FDA’s current regulatory research activities in the areas of medical physics and imaging products Understand how being involved with AAPM and other organizations can also help to promote innovative, safe and effective medical devices J. Delfino, nothing to disclose.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-AB-204-02: Device Adverse Events and Compliance

The responsibilities of the Food and Drug Administration (FDA) have increased since the inception of the Food and Drugs Act in 1906. Medical devices first came under comprehensive regulation with the passage of the 1938 Food, Drug, and Cosmetic Act. In 1971 FDA also took on the responsibility for consumer protection against unnecessary exposure to radiation-emitting devices for home and occupational use. However it was not until 1976, under the Medical Device Regulation Act, that the FDA was responsible for the safety and effectiveness of medical devices. This session will be presented by the Division of Radiological Health (DRH) and the Division of Imaging, Diagnostics, and Software Reliability (DIDSR) from the Center for Devices and Radiological Health (CDRH) at the FDA. The symposium will discuss on how we protect and promote public health with a focus on medical physics applications organized into four areas: pre-market device review, post-market surveillance, device compliance, current regulatory research efforts and partnerships with other organizations. The pre-market session will summarize the pathways FDA uses to regulate the investigational use and commercialization of diagnostic imaging and radiation therapy medical devices in the US, highlighting resources available to assist investigators and manufacturers. The post-market session will explain the post-market surveillance and compliance activities FDA performs to monitor the safety and effectiveness of devices on the market. The third session will describe research efforts that support the regulatory mission of the Agency. An overview of our regulatory research portfolio to advance our understanding of medical physics and imaging technologies and approaches to their evaluation will be discussed. Lastly, mechanisms that FDA uses to seek public input and promote collaborations with professional, government, and international organizations, such as AAPM, International Electrotechnical Commission (IEC), Image Gently, and the Quantitative Imaging Biomarkers Alliance (QIBA) among others, to fulfill FDA’s mission will be discussed. Learning Objectives: Understand FDA’s pre-market and post-market review processes for medical devices Understand FDA’s current regulatory research activities in the areas of medical physics and imaging products Understand how being involved with AAPM and other organizations can also help to promote innovative, safe and effective medical devices J. Delfino, nothing to disclose.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-AB-204-03: Research Activities in Medical Physics

The responsibilities of the Food and Drug Administration (FDA) have increased since the inception of the Food and Drugs Act in 1906. Medical devices first came under comprehensive regulation with the passage of the 1938 Food, Drug, and Cosmetic Act. In 1971 FDA also took on the responsibility for consumer protection against unnecessary exposure to radiation-emitting devices for home and occupational use. However it was not until 1976, under the Medical Device Regulation Act, that the FDA was responsible for the safety and effectiveness of medical devices. This session will be presented by the Division of Radiological Health (DRH) and the Division of Imaging, Diagnostics, and Software Reliability (DIDSR) from the Center for Devices and Radiological Health (CDRH) at the FDA. The symposium will discuss on how we protect and promote public health with a focus on medical physics applications organized into four areas: pre-market device review, post-market surveillance, device compliance, current regulatory research efforts and partnerships with other organizations. The pre-market session will summarize the pathways FDA uses to regulate the investigational use and commercialization of diagnostic imaging and radiation therapy medical devices in the US, highlighting resources available to assist investigators and manufacturers. The post-market session will explain the post-market surveillance and compliance activities FDA performs to monitor the safety and effectiveness of devices on the market. The third session will describe research efforts that support the regulatory mission of the Agency. An overview of our regulatory research portfolio to advance our understanding of medical physics and imaging technologies and approaches to their evaluation will be discussed. Lastly, mechanisms that FDA uses to seek public input and promote collaborations with professional, government, and international organizations, such as AAPM, International Electrotechnical Commission (IEC), Image Gently, and the Quantitative Imaging Biomarkers Alliance (QIBA) among others, to fulfill FDA’s mission will be discussed. Learning Objectives: Understand FDA’s pre-market and post-market review processes for medical devices Understand FDA’s current regulatory research activities in the areas of medical physics and imaging products Understand how being involved with AAPM and other organizations can also help to promote innovative, safe and effective medical devices J. Delfino, nothing to disclose.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-AB-204-04: Partnerships

The responsibilities of the Food and Drug Administration (FDA) have increased since the inception of the Food and Drugs Act in 1906. Medical devices first came under comprehensive regulation with the passage of the 1938 Food, Drug, and Cosmetic Act. In 1971 FDA also took on the responsibility for consumer protection against unnecessary exposure to radiation-emitting devices for home and occupational use. However it was not until 1976, under the Medical Device Regulation Act, that the FDA was responsible for the safety and effectiveness of medical devices. This session will be presented by the Division of Radiological Health (DRH) and the Division of Imaging, Diagnostics, and Software Reliability (DIDSR) from the Center for Devices and Radiological Health (CDRH) at the FDA. The symposium will discuss on how we protect and promote public health with a focus on medical physics applications organized into four areas: pre-market device review, post-market surveillance, device compliance, current regulatory research efforts and partnerships with other organizations. The pre-market session will summarize the pathways FDA uses to regulate the investigational use and commercialization of diagnostic imaging and radiation therapy medical devices in the US, highlighting resources available to assist investigators and manufacturers. The post-market session will explain the post-market surveillance and compliance activities FDA performs to monitor the safety and effectiveness of devices on the market. The third session will describe research efforts that support the regulatory mission of the Agency. An overview of our regulatory research portfolio to advance our understanding of medical physics and imaging technologies and approaches to their evaluation will be discussed. Lastly, mechanisms that FDA uses to seek public input and promote collaborations with professional, government, and international organizations, such as AAPM, International Electrotechnical Commission (IEC), Image Gently, and the Quantitative Imaging Biomarkers Alliance (QIBA) among others, to fulfill FDA’s mission will be discussed. Learning Objectives: Understand FDA’s pre-market and post-market review processes for medical devices Understand FDA’s current regulatory research activities in the areas of medical physics and imaging products Understand how being involved with AAPM and other organizations can also help to promote innovative, safe and effective medical devices J. Delfino, nothing to disclose.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

A 15-Year Retrospective on Immersive Visualization Lessons from the Applied Visualization Laboratory

This article shares the experiences of operating an immersive visualization laboratory over a 15-year period. The paper discusses valuable insights into the lessons learned from various projects, including the challenges they faced, such as technical difficulties, user adoption, and opportunities, and practical solutions for overcoming them. One crucial element for successful immersive visualization projects is interdisciplinary collaboration. The paper presents the advantages of immersive visualization technology, such as improved data comprehension, enhanced communication, and increased engagement in complex scenarios. We present the dynamic realm of virtual and augmented truth (VR/AR) technology in the context of a immersive laboratory system. We spotlight rising trends inside the integration of VR/AR tools for visualization. We also present our experience in dealing with the hardware and software additives in an immersive VR/AR labs, dropping light on the demanding situations and successes encountered throughout everyday operations. Furthermore, it offers practical knowledge and guidance based on years of experience in the field, which can help you overcome challenges and achieve success in your project.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

A Heterogeneous System for Eagle Detection, Deterrent, and Wildlife Collision Detection for Wind Turbines (Final Technical Report)

This report summarizes the design, implementation, and test of an integrated system for automated detection and deterrence of eagles, with included wind turbine blade strike detection and imaging functionality. A machine learning approach was used in conjunction with a 360° camera system for automated detection and classification of golden eagles. This was developed using footage obtained from trained golden eagles and other raptors, in collaboration with wildlife biologists and professional bird handlers. Oregon State University developed a visual deterrent system, which uses inflatable anthropomorphic sculptures with random, kinetic motion to deter eagles, and conducted limited field testing on live eagles; the deterrent can be triggered by the visual detection of eagles using the vision system. Finally, a multi-sensor module was developed that is mounted at the turbine blade root. This module measures vibration and other motions to detect blade strikes, and an integrated on-blade camera captures an image of any impacting objects. Long-term, this blade strike detection system is intended to support an automatic monitoring and certification system for the eagle detection and deterent system. Independent field testing of each system component is described. Testing of the integrated system on an operational wind turbine was conducted across three separate field tests. This includes multi-day fields tests on a General Electric 1.5MW wind turbine at the National Renewable Energy Laboratory (NREL) National Wind Technology Center (NWTC) in Boulder, CO in October 2018 and July 2019; installation procedures, test procedures, and a summary of collected data are presented. A third multi-day on-turbine field test is also presented, which was performed using a General Electric 1.5MW wind turbine at the North American Wind Research and Training Center (NAWRTC) at Mesalands Community College, Tucumcari, NM in April 2019. Across these field tests, the vision system was demonstrated using unmanned aerial vehicles (UAV), and the eagle classification algorithm was not tested; the visual deterrent system was demonstrated, including automatic, remote deployment following surrogate visual detections; and, multi-sensor on-blade data was recorded across multiple wind turbine operational conditions and through more than 100 surrogate blade strikes using soft projectiles, including the successful demonstration of automatic image capture of striking objects. This data set was also used for offline development and validation of enhanced collision detection algorithms. As summarized in this report, the development and field validation of an integrated detection, deterrent, and blade collision detection system represents a critical proof of concept for future technology development of related detection and deterrent technologies, where both deterrent as well as collision detection recording devices are needed for future siting, monitoring, and operation of wind turbine installations, both onshore and offshore.

17 WIND ENERGY↗

NASA NTRS2014

Behavioral Health and Performance at NASA JSC: Recent Successes and Future Plan for BHP Research and Operations

The Behavioral Health and Performance discipline at NASA Johnson Space Center is organized into two distinct Divisions (Biomedical Research and Environmental Science Division and Space and Clinical Operations Division) but is integrated and interrelated in its day‐to‐day work. Ongoing operations supporting NASA's spaceflight goals benefit from the research portfolios that address risks to mission success. Similarly, these research portfolios are informed by operations to ensure investigations stay relevant given the dynamic environment of spaceflight. There are many success stories that can be presented where initial work begun as a BHP Research project, and funded through the Human Research Program, was fully implemented in operations or addressed an operational need. Examples include improving effectiveness of the debriefings used within Mission Control by the Mission Operations Directorate and countermeasures for fatigue management. There is also ongoing collaboration with research and operations for developing selection methods for future generation astronauts, and to enhance and inform the current family support function. The objective of this panel is to provide examples of recent success stories, describe areas where close collaboration is benefitting ongoing research and operations, and summarize how this will come together as NASA plans for the one year ISS mission - a unique opportunity for both BHP operations and research to learn more about preparing and supporting crewmembers for extended missions in space. The proposed panel will be comprised of six presentations, each describing a unique aspect of research or operations and the benefits to current and future spaceflight.

Leveton, L. B.↗

NASA NTRS2019

UAS Service Supplier Checkout: How UTM Confirmed Readiness of Flight Tests with UAS Service Suppliers

NASA collaborated with industry partners to develop and test the small Unmanned Aircraft System (sUAS) Traffic Management (UTM) research platform, a software prototype used for developing airspace integration requirements for sUAS operations. The lessons learned from these activities will help inform the Federal Aviation Administration (FAA) on what is needed to safely manage sUAS operations. A core component of the UTM platform is the UAS Service Supplier (USS), which acts as a communications bridge to meet the regulatory and operational requirements. As the UTM partners began USS flight tests, NASA found that it was difficult to get all USSs functioning at comparable quality levels to ensure successful flight tests. Also, NASA anticipated that the FAA would encounter similar challenges when they begin to register USSs for operational use. These realizations led to the development of USS Checkout, a set of processes and tools designed to increase flight test efficiency. We learned that a good USS Checkout process is balanced for simplicity versus test coverage, and is amenable to automation. We also learned that when USS Checkout is a USS prerequisite for flight tests, flight tests were more efficient and effective.

Smith, Irene Skupniewicz↗

NASA NTRSDate not supplied

The PACE-MAPP Algorithm: Simultaneous Aerosol and Ocean Products From Combined Polarimeter and Shortwave Infrared Measurements

PACE-MAPP collaborative algorithm project - Produce accurate aerosol optical and microphysical properties and ocean properties - Use a coupled atmosphere-ocean vector radiative transfer (VRT) model - Use accurate but fast Mie/SS/T-matrix LUTs - Use scientific machine learning to speed-up retrievals by 1000x (PACE-MAPP Neural Network) - PACE-MAPP is a multi-instrument polarimeter algorithm for SPEXone, HARP2, OCI shortwave infrared channels

Snorre Alfred Moen Stamnes↗

DOE OSTI2025

In situ Detection of Plasma Induced Surface Interaction based on Deep Learning based Visual Diagnostics (Technical Report)

It is characteristic for many plasma devices to undergo plasma-material interaction leading to surface erosion. These processes, often not easily detectable, lead to changes in device performance and lifespan. State-of-the-art lifetime tests and wear experiments require over 1000s hours. A self-consistent model for accurately predicting the erosion's effects is not available. In situ detection of these processes is not a trivial task since the surface variations at the early stages have a micron scale. Such limitations not only restrict testing and prediction capabilities but also slow the development of new thrusters and limit mission duration. To address these challenges, an in-situ diagnostic for real-time erosion assessment has been developed, aiming to expedite lifetime testing and broaden experimental campaigns. Several works were dedicated to real-time and in situ monitoring of material erosion during plasma exposure using laser holography, microscopy, and with telemicroscopes. However, the applicability of these approaches is limited due to complexity, cost and less flexibility as they often require placing diagnostic equipment inside the vacuum chamber. In collaboration with Princeton Collaborative Research Facility (PCRF), Princeton Plasma Physics Laboratory (PPPL), a new diagnostic approach is developed, where geometry modifications to the ceramic channel walls were introduced that would result in accelerated channel erosion. We employed Long-distance microscope (LDM) imagery, combined with Deep-Learning based Shape from focus or depth from focus (DFF or SFF) approach, that provides an accessible and cost-effective solution. LDM employs focus variation techniques to continuously capture multiple images of the target object at distinct focal planes. DFF, an optical focus variation method, generates a 3D topographical surface depth map from a sequence of variably focused images. Combined with the developed diagnostic, this approach offers a controllable means to study erosion under accelerated conditions. In this work, we develop Neural Network-based DFF algorithm applicable for LDM data to quantitatively evaluate plasma induced surface modification from LDM data. Next, we develop Deep Learning-based super-resolution depth map image reconstruction technique to increase the resolution of depth maps obtained from DFF algorithm to improve the accuracy of erosion measurements. Thirdly, we develop several image processing techniques to remove noise and improve the quality of depth map image. Here we report the results of initial tests for this approach. An experimental setup designed and built in PPPL was employed that consists of a 3-cm gridded ion source that produces a neutralized argon beam with energies up to 600 eV. A hexagonal boron nitride (h-BN) ceramic target, designed based on computational predictions, was used. Tests were conducted to reconstruct the complex geometry of the target under the lighting conditions of the operated ion source.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2017

Solar Living House Final Technical Report

The Solar Living House is a high-performance solar-powered dwelling designed by a team of faculty and students from the University of Florida, in collaboration with Santa Fe College, the National University of Singapore, and Alachua Habitat for Humanity. The project was designed in accordance with the Solar Decathlon 2015, a research, design, education, and outreach program developed by the U.S. Department of Energy (DOE). The Solar Living House is fundamentally a house for living, centered on people and the activities of daily life while quietly introducing advanced design, construction, and engineering technologies. The 993 square-foot two-bedroom one-bath home was designed to embrace and frame an exterior courtyard space. This courtyard acts as an extension of the interior living spaces, maximizing the spatial potentials of a modest building footprint and introducing natural light into the primary living spaces of the house. Research Outcomes: The Solar Living House advances work on high-performance buildings through three principal technological innovations: wet/dry modular construction, a building automation system, and solar dehumidification systems. Wet / Dry Modular Construction: The house is designed as a series of five modules, including one that is designated as the “wet core.” The wet core consolidates the mechanical systems and bathroom into a single module to reduce plumbing runs, efficiency losses, and on-site construction time. The other four modules are designed to eliminate interior load bearing walls to allow for maximum flexibility in the reconfiguring of the space over time. The modules are designed to meet the structural challenges of both Florida’s hurricanes and California’s earthquakes. Building Automation System: The house is equipped with an integrated building automation system, allowing the houses environmental systems, lights, security systems, and smoke detectors to be programmed, monitored, and controlled through any mobile or computing device. These systems allow for more precise calibrations of temperature/humidity/lighting to correspond with user needs and preferences, minimizing energy losses with economical night- or day-time setbacks. Solar Dehumidification System: The most significant technological innovation in the Solar Living House is the solar thermal dehumidification system. This system generates hot water through two rooftop-mounted evacuated tube solar thermal collectors. The hot water is used to continually dry a regenerative solid desiccant material, typically white silica gel. The solid desiccant is used to adsorb moisture and humidity from the air without additional mechanical cooling. This strategy allows humidity to be modulated independently of air temperature, providing greater thermal comfort and reducing the opportunity for the growth of mold spores within the house while also reducing the overall energy consumption of the HVAC system. Economic Feasibility: The team set aggressive goals for affordability, targeting a construction cost of $138,710. An independent professional cost estimator determined the overall project costs, as designed, would be $333,799, or $336.15 per square foot of finished floor area. This is more than 2.4 times the target construction cost. By comparison, the average construction cost for a home in the United States in 2015 was $289,415, or $103.29 per square foot of finished floor area. Following work on the Solar Living House, team leaders incorporated many of its objectives into a net-zero energy home on a site in Gainesville, Florida. This site-built home avoided many of the constraints and complications of modular construction necessitated by the Solar Decathlon, allowing it to be built for a much more modest budget. This two-bedroom two bath 1,800 square foot home was constructed for $135.39 per square foot, including active photovoltaic solar systems, careful attention to continuous air barriers, increased insulation levels, and permanent site constructions. This project suggest that high-performance buildings can be realized for more modest budgets. Public Benefits: Work on the Solar Living House and Solar Decathlon 2015 offered our student team unparalleled learning opportunities. Because of the duration of the project, a number of students participated at different points in their education, from first year undergraduates all the way through to advanced graduate students. The opportunity for collaboration with students and faculty from the National University of Singapore was also extraordinary, allowing for a sharing of technical knowledge and cultural exchange. The wider public has benefited from this work as its findings have been shared through public presentations and publications. It serves as a useful stepping stone along the path towards affordable, high-performance buildings.

14 SOLAR ENERGY↗

DOE OSTI2021

Scalable Technologies Achieving Risk-Informed Condition-Based Predictive Maintenance Enhancing the Economic Performance of Operating Nuclear Power Plants

The primary objective of the research presented in this report is to develop scalable technologies that are deployable across plant assets and across the nuclear fleet to achieve risk-informed predictive maintenance (PdM) strategies at commercial nuclear power plants (NPPs). Over the years, the nuclear fleet has relied on labor-intensive and time-consuming preventive maintenance (PM) programs, driving up operation and maintenance (O&M) costs to achieve high capacity factors. A well-constructed risk-informed PdM approach for an identified plant asset has been developed in this research, taking advantage of advancements in data analytics, machine learning (ML), artificial intelligence (AI), physics-informed modeling, and visualization. These technologies would allow commercial NPPs to reliably transition from current labor-intensive PM programs to a technology driven PdM program, eliminating unnecessary O&M costs. The work presented in the report is being developed as part of a collaborative research effort between Idaho National Laboratory and Public Service Enterprise Group Nuclear, LLC. This report (1) reflects the results of work by LWRS Program researchers with PSEG, Nuclear LLC-owned Salem and Hope Creek Nuclear Power Plants; (2) presents utilization of circulating water system (CWS) heterogeneous data and fault modes from both the Salem and Hope Creek nuclear power plant sites to develop salient fault signatures associated with each fault mode; (3) describes the integration of component-level predictive models into a robust system-level model enabled by the federated-transfer learning; (4) describes the development of physics-informed model of circulating water pump and motor; (5) develops a scalable risk and economic model; and (6) outlines the development of a user-centric visualization application. The outcomes presented in this report lays the foundation and provides a much-needed technical basis to focus on explainability and trustworthiness of ML and AI-based technologies, as part of future research.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Open Architecture for Cost Savings in Advanced Nuclear Reactors

Recently, nuclear power plant build projects in the West have run over budget due to high capital costs and schedule overruns. Compared to other sources of energy, nuclear power plants have higher capital costs. Reactors are often different at every site, resulting in a lack of standardization. Nuclear is expected to compete with other low carbon sources of energy which have lower capital costs making it essential for nuclear to develop ways of reducing costs. Strategies such as standardization, learning rates, modularization, and schedule reduction in advanced reactors can reduce nuclear costs by about 40%. Standardization as a way of cutting capital costs has been explored even in large nuclear power plants. Standardization of certain plant components can result in lower component and installation costs and higher learning from experience. Standardization can be achieved by adopting a criterion of key performance indicators and general design principles for a specific system or component such as the balance of plant. Modularization allows the construction of certain components of SMRs in a factory, which saves time, increases productivity, and encourages higher learning rates. Production learning decreases the time and the cost related to an activity. The potential for modularized components of advanced reactors to be manufactured in factories makes it conducive to achieving higher learning rates. Developing large-capacity nuclear programs through sequential builds cultivates a higher learning rate, which in effect may reduce schedule overruns. Open architecture has been identified as a way to drive standardization among advanced reactor designs and result in cost savings. Open architecture (OA) is defined as a design enabling a diverse supply chain by defining and publishing requirements of systems or equipment in functional and/or interface terms, utilizing technical standards in widespread use. Currently, the nuclear industry’s approach is to use closed architecture, making most designs proprietary. However, collaboration between various advanced reactor vendors and suppliers utilizing the concept of open architecture can result in modular and standardized architecture of subsystems or subcomponents of a nuclear power plant. Completely standardizing nuclear power plants may be impossible, however, certain common subsystems amongst the various reactor designs could be standardized and/or access a wider supply chain and leverage existing learning from other sectors. Open architecture will save time and allocate resources to the parts of the plants that have the most unique features. A key advantage of open architecture is its ability to improve production learning across advanced reactors (AR) types in the industry, by providing and utilizing the same kind of component. Sodium fast reactor (SFR), High Temperature Gas Reactor (HTGR) and Molten Salt Reactor (MSR) are the advanced reactors considered for this project. This paper aims to determine the cost savings in advanced reactor programs due to open architecture learning rate. This work is an extension of work done on light water reactor small modular reactors; the cost methodology was utilized to investigate the impact of open architecture on advanced reactors with a particular focus on sodium fast reactors. The cost data on sodium fast reactors used in the model presented the most adequate information required for the analysis.

Advanced Nuclear Reactors↗

DOE OSTI2026

Developing Scenario‐Based Strategies for Health, Climate, and Environmental Preparedness: The One Health, One Earth Approach

Climate change amplifies many threats to human health. Despite advances in understanding climate change dynamics and impacts, there remains a critical gap in translating scientific knowledge into equitable, and community-driven health interventions. The inaugural One Earth, One Health workshop sought to explore this gap through human-centered design exercises involving interdisciplinary researchers from climate and Earth sciences, engineering, epidemiology, microbiology, and environmental health. Although participants did not co-develop solutions with affected communities, they used stakeholder role-playing to guide ideation and lay groundwork for actionable plans. Through these methods, participants identified community needs and proposed prototype solutions to alleviate health threats exacerbated by global environmental change. Prototypes were organized around infectious diseases, extreme weather, and air quality, as illustrative themes rather than an exhaustive set of risks. Key solutions included strategies for anticipatory systems and early warning (e.g., integrating environmental signals with health data), inclusive communication and infrastructure needs for responding to extreme weather events, and integrated platforms visualizing air quality trends to support tailored, context-aware guidance beyond one-size-fits-all alerts. The workshop highlighted opportunities such as leveraging machine learning, Earth observation, and real-time surveillance to protect communities, but also noted barriers including data quality, technological redundancy, privacy, and governance challenges. Additionally, participants emphasized the need for interdisciplinary teams capable of collaborating across sectors, breaking down silos and addressing gaps in training and education. Overall, the workshop illustrates how process-driven, human-centered approaches can help surface user needs and generate testable prototype concepts, while underscoring the importance of direct community partnership for implementation.

Abadi, Azar M. [University of Alabama, Birmingham,↗