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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Intelligent Process Visualization through Nuclear Operation Process Modeling, Reasoning, and Object Detection from Field Videos (Final Report)

This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Accelerating the Adoption of Energy Efficiency and Renewables in Warehouses and Distribution Centers

Commercial warehouses and storage facilities represent a large part of the commercial buildings in the United States, and their share increases every year. NREL is working with the U.S. Department of Energy to understand barriers, sector needs, and opportunities to enhance sustainability in the warehouse sector, driving ultra-high efficient, zero-energy design, while considering electrification in buildings and vehicles, grid-friendly operation, and decarbonization. After investigating literature about warehouse sustainability practices and high-performance warehouse case studies, several one-on-one interviews were carried out with warehouse managers and stakeholders. Data collected through literature and the interviews were captured to provide the current status of warehousing in the context of energy efficiency, renewables, carbon emissions, and overall sustainability. The results are intended to inform areas for new research and deployment activities to achieving zero energy and zero carbon goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Resilience Insights from New York State Stakeholders

A diverse set of New York State stakeholders—representing state agencies, authorities, utilities, and regulators—were interviewed on their perceptions of energy resilience. This summary synthesizes the 34 interviews to examine the degree of shared understanding around resilience, to identify opportunities to address common challenges, and to align stakeholder interests to better serve New York State's services, systems, and people.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

United States cool surfaces deployment plan

Solar-reflective building envelope surfaces, such as cool roofs and walls, can be especially helpful in disadvantaged communities that often have poorly insulated older homes, aging or absent air conditioning units, steep utility bills, polluted air, and high vulnerability and exposure to extreme heat. With support from the U.S. Department of Energy, our project seeks to dramatically increase the climate-appropriate deployment of cool surfaces across the United States with an emphasis on their application to disadvantaged communities. First, we sought to identify cool-surface deployment barriers, opportunities, and models by (a) reviewing the history of cool-surface deployment activities, (b) interviewing cool-surface stakeholders, (c) researching successful energy-efficiency/green building deployment models; and (d) interviewing the actors who have implemented these models. Second, we conducted a workshop to engage stakeholders in development of a deployment plan. Third, we asked several U.S. federal agencies (a) how cool surfaces and cool surface stakeholders could support their missions and (b) how agency activities could support cool-surface deployment. Fourth, we identified a set of transformative ideas that form the core of the deployment plan. Transformative ideas include but are not limited to initiatives to (a) launch an educational campaign to make the general public and building professionals aware of how cool roofs and walls exclude unwanted solar heat; (b) create a “Cool Roof Prize” stimulating the development of affordable, high-performance cool asphalt roofing shingles; (c) conduct high-profile, large-scale demonstration programs that bring cool surfaces to disadvantaged heat-vulnerable communities; and (d) support local, regional, and state climate action (heat mitigation) plans with cool surfaces.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Transactive Energy Practices Survey

For nearly two decades, the idea of using market-based approaches in field deployments that coordinate the flexible operation of electricity customer assets has occupied the efforts of transactive energy practitioners. While the purported benefits of this distributed decision-making approach encourage transactive energy designs have been well explored, the practical aspects of implementing such a system to address real-world problems are just beginning to emerge. This report surveyed 24 field-deployed programs and interviewed experts instrumental in these deployments. The results of the survey and interviews reveal the diversity of designs and applications. They highlight the technical promise of the approaches as well as challenges with system integration, sustainable business strategy, and regulatory policy obstacles. Insights from the survey offer considerations to direct future effort and investment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Evaluation of New Opportunities for Marine Energy To Power the Blue Economy: Green Hydrogen and Marine Carbon Dioxide Removal

This report examines the intersection of marine energy and the sectors of green hydrogen and marine Carbon Dioxide Removal, taking into account potential synergies, market maturity, barriers, policy enablers, and sustainability perspectives. Through desk research and interviews with a diverse range of subject matter experts from academia, government, industry, venture capital, and non-profit sectors, these emergent sectors were identified as the most promising new opportunities for marine energy integration beyond those explored in the 2019 Powering the Blue Economy Report. The findings presented are the combined result of desk research and information gathered through these interviews.

13 HYDRO ENERGY↗
DOE OSTI2019

Trade Compliance Insurance Product: Revisiting the feasibility of an insurance product to strengthen trade compliance and reduce proliferation risks

In October 2018, Pacific Northwest National Laboratory (PNNL) published a report (PNNL-28094) in collaboration with the Stimson Center on the feasibility of an insurance product that would reduce proliferation risks associated with small and medium-sized enterprises by encouraging stronger trade control compliance. This preliminary report concluded that a Trade Compliance Insurance Product (TCIP) is feasible and identified existing insurance analogs, challenges, and outstanding questions for further industry outreach. From October 2018 to September 2019, PNNL attempted to validate this preliminary report through a series interviews with representatives from the manufacturing, finance, insurance and shipping industries. This report follows up on the initial 2018 Report and summarizes the findings of the industry interviews related to the TCIP and makes recommendations for the next steps and insurance incentives more broadly.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

A Review of Resilience and Long-Term Planning in Power and Water Systems in the United States

There is recognition among power and water utilities that the frequency and magnitude of high consequence and low probability events could increase as a result of climate change. The interconnected nature of energy-water systems raises the possibility of cascading failures, increasing complexity and risks. Resilience and long-term planning are important ways of weathering the effects of climate change. First, to understand more about resilience, we reviewed existing literature on resilience definitions, metrics, and modeling, focusing on integrated water-power systems. Second, to understand how resilience and planning are being applied in practice, we interviewed utilities and organized, curated, and synthesized the interview data to arrive at several key findings, which are presented here. We found that there is not a consistent definition for resilience, yet it is something that utilities regularly plan for, often with different names and varying methods/measures. However, there is a tangible shift in the industry towards defining and determining measurable resilience metrics. While the exact metrics are a work in progress, utilities are taking steps forward by (1) putting people and culture at the center of resilience, (2) recognizing their own interdependencies, and (3) pursuing better cross-sector collaboration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Risk Assessment Considerations for Underground Hydrogen Storage in Depleted Gas Reservoirs

Underground hydrogen storage (UHS) in depleted reservoirs presents a promising solution for large-scale energy storage as hydrogen demand grows. As the UHS industry emerges, robust risk assessments are critical to ensuring safe operation of the storage facilities and minimizing the risk of accidents. This work explores risk assessment protocols for underground natural gas storage (UGS) in depleted reservoirs and identifies key considerations for repurposing these facilities for UHS. By examining the differences in physical and chemical properties between hydrogen and natural gas, this work highlights new and modified hazards that merits a reevaluation of traditional natural gas risk assessment practices. This investigation synthesizes insights from previous literature reviews and interviews with UGS industry experts and operators to identify key areas for adapting risk assessment methodologies for hydrogen. The insights gleaned from expert interviews indicate that existing risk assessment standards are non-prescriptive, leading to diverse company-specific risk assessment methodologies requiring substantial additions to become practical. Due to a lack of concrete risk assessment requirements, experience, and relevant data, this uncertainty is expected to be magnified considerably when considering hydrogen. This study identifies several areas for potential modification of existing risk assessment practices that could be considered by those developing standards or performing risk assessments for UHS. Specifically, risk assessments may be improved by including risks unique to hydrogen in existing standards, changing the magnitude of different risk factors in existing risk assessment protocols, and improving methods of data collection and communication across the industry to address large areas of uncertainty.

08 HYDROGEN↗
DOE OSTI2025

Yes, No, Maybe So: Human Factors Considerations for Fostering Calibrated Trust in Foundation Models Under Uncertainty

High-stakes analytical environments require analysts to evaluate evidence and generate conclusions to inform critical decisions often under conditions of uncertainty. Probabilistic decision-making based on incomplete or inaccurate information can reduce productivity, compromise national interests, and endanger public safety. Researchers are developing expert systems built on foundation models (FMs) to support analysts’ decision-making processes by enabling human-artificial intelligence (AI) teaming, in part through the quantification and expression of uncertainty information. As FMs continue to mature, it is imperative to correspondingly consider analysts’ needs for appropriately interpreting and using uncertainty information. However, prior research indicates that it remains unclear how analysts engage with FM-generated uncertainty information and the extent to which these interactions influence trust in, and reliance on, expert systems. We plan to review the state of the science and conduct an exploratory, qualitative study to (a) understand how properly communicated uncertainty can foster calibrated trust and appropriate reliance and (b) identify approaches for effectively conveying FM-generated uncertainty information during analytical workflows. We will administer semi-structured interviews with analysts from a specific high-stakes analytical environment to collect their current experiences with job-related uncertainty and their impressions when viewing FM-generated uncertainty information. During the interview protocol, participants will be presented with several different FM outputs and invited to discuss their thoughts and beliefs about the uncertainty information displayed. Participants may provide insights into how trust and reliance may be influenced by uncertainty. The results of this study will help us to better understand how analysts currently interpret and use uncertainty information. Our findings may inform human factors recommendations for effectively conveying uncertainty information to foster calibrated trust in, and appropriate reliance on, expert systems. Interaction designers and FM developers can use this knowledge to enhance human-AI teaming and ensure the responsible deployment of FM-based expert systems in analytical workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Voices from Rural Electric Cooperatives: A Call for a DER Integration Playbook for Rural and Agricultural Income & Savings from Renewable Energy (RAISE)

Rural-serving electric utilities (RSEUs)—including electric cooperatives, municipal systems, and small investor-owned utilities—are essential players in the evolving energy landscape. These community-focused entities are increasingly being asked to consider distributed energy resources (DERs) such as rooftop and ground-mounted solar, wind, battery storage, smart water heaters, and demand response programs (NRECA 2025; Lenhart et al. 2020). Yet the path to DER adoption is far from straightforward in the rural context. This report is based on in-depth interviews with managers of rural electric cooperatives across the United States. These conversations offer a grounded, unvarnished look at how DERs are perceived, what barriers exist, and what conditions might enable integration and adoption. While the utilities interviewed vary in geography, size, and DER experience, several clear and common themes emerged across electric cooperatives such that the report recommends the development of a DER Integration Runbook to help utilities assess readiness, define local use cases, engage stakeholders, pilot projects, and iterate, expanding over time.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Enabling Power at Sea: Opportunities for Expanded Ocean Observations through Marine Renewable Energy Integration

The blue economy is a dynamic and rapidly growing movement that captures the interplay between economic, social, and ecological sustainability of the ocean and encompasses numerous maritime sectors and activities (e.g., commerce and trade; living resources; renewable energy; minerals, materials, and freshwater; and ocean health and data). The demand for ocean data to inform scientific, risk reduction, and national security needs is leading to a large increase in the number of deployed ocean observation and monitoring systems, most of which require increased power. Because ocean observation systems are often placed in remote locations, they primarily rely on energy storage (or in some cases in situ energy generation) to power instruments and equipment, which imposes limits on sampling rates, deployment times, and spatiotemporal resolution of data. The U.S. Department of Energy Water Power Technologies Office is exploring the potential for marine renewable energy (MRE) devices (largely wave and tidal energy converters) to provide power to support multiple blue economy opportunities. A portion of these opportunities focus on power at sea markets for providing power in off-grid and offshore locations to support a variety of ocean-based activities, including ocean observation and navigation, underwater vehicle charging, marine aquaculture, marine algae farming, and seawater mining. Initially, research has focused on better understanding how and where MRE can provide a consistent source of reliable power to extend ocean observing missions, including operation of autonomous underwater vehicles. Online surveys as well as phone and in-person interviews were conducted with experts in the field of ocean observing systems and observatories to gather end-user requirements, determine energy needs, identify opportunities for codevelopment, and pinpoint constraints for MRE to meet those needs. The surveys and interviews provided feedback on the potential for powering devices and vehicles using MRE, including identifying common themes and challenges that will inform foundational research and development steps needed to advance the integration of MRE with ocean observing systems. In most cases, additional power generation on the order of watts was identified as significantly beneficial to enhancing ocean observations capabilities.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

UPGRADE-E: Understanding Patterns Guiding Residential Adoption and Decisions about Energy Efficiency

This work represents the largest and most comprehensive dataset to-date of responses surveyed from U.S. residents regarding home modifications and energy-related decision-making, including both objective measures describing the occupants and their homes and subjective measures describing the more unpredictable human factors behind residential decision-making. First, to develop the survey, we interviewed 121 individual decision-makers within their households regarding planned or completed projects. We used the insights of these interviews to design a survey that was distributed to 10,000 households across the U.S. The overarching topics approached in the survey include descriptive information about the respondent, their household, their home, home modifications they have made, and the human cognition-based contextual factors involved in home projects and decision-making, such as preferences, motivations, barriers, and information sources. The processed data from the survey was compiled into a dataset entitled UPGRADE-E: Understanding Patterns Guiding Residential Adoption and Decisions about Energy Efficiency and represents the basis for the analyses included in this paper. The dataset represents a rich repository of home energy technology and modification decision-making results, the largest of its kind to-date. The abundance of contextual considerations within this dataset provides a robust resource for continual analysis, with possibilities for considering cross-cuts of data from a variety of perspectives.

Fuentes, Tracy L↗
DOE OSTI2023

Toddler home math environment: Triangulating multi-method assessments in a U.S. Sample

Introduction Current research has documented the home math environment (HME) of preschoolers and kindergarteners. Very few studies, however, have explored the number and spatial activities in which parents engage with children during their toddler years. Methods This study examined the HME of 157 toddlers using several methodologies, including surveys, time diaries, and observations of math talk. Further, it examined correlations within and across data sources to identify areas of convergence and triangulation, and correlated HME measures with measures of toddlers’ number and spatial skills. Results Findings showed that, in general, uses of different types of math activities, including both number and spatial, were intercorrelated within method. Across methods, there was high intercorrelation between the frequency of math activities reported on parent surveys and the diversity of types of math activities endorsed in time diary interviews. Parent math talk gleaned from semi-structured interviews functioned as a separate aspect of the HME; different types of math talk shared few intercorrelations with engagement in math activities as reported in either surveys or time diaries. Finally, several HME measures positively correlated with toddlers’ math skills. Discussion Given extant research demonstrating that both math activities and math talk predict children’s math skills, our results stress the need for multimethod studies that differentiate among these HME opportunities.

Miller, Portia↗
DOE OSTI2023

Opportunities for human factors in machine learning

Introduction The field of machine learning and its subfield of deep learning have grown rapidly in recent years. With the speed of advancement, it is nearly impossible for data scientists to maintain expert knowledge of cutting-edge techniques. This study applies human factors methods to the field of machine learning to address these difficulties. Methods Using semi-structured interviews with data scientists at a National Laboratory, we sought to understand the process used when working with machine learning models, the challenges encountered, and the ways that human factors might contribute to addressing those challenges. Results Results of the interviews were analyzed to create a generalization of the process of working with machine learning models. Issues encountered during each process step are described. Discussion Recommendations and areas for collaboration between data scientists and human factors experts are provided, with the goal of creating better tools, knowledge, and guidance for machine learning scientists.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Co-Design of Engineered Hyporheic Zones to Improve In-Stream Stormwater Treatment and Facilitate Regulatory Approval

Green infrastructure is an increasingly popular approach to mitigate widespread degradation of urban waters from stormwater pollution. However, many stormwater best management practices (BMPs) have inconsistent water quality performance and are limited to on-site, land-based deployments. To address basin-wide pollutant loads still reaching urban streams, hyporheic zone engineering has been proposed as an in-stream treatment strategy. Recognizing that regulator and practitioner perspectives are essential for innovation in the water sector, we interviewed U.S. water management professionals about the perceived risks, opportunities, and knowledge gaps related to in-stream stormwater treatment. We used engineered hyporheic zones as a case study to understand interviewee perspectives on an emerging class of in-stream treatment technologies. Interviews revealed that many considerations for in-stream stormwater treatment are common to land-based BMPs, but in-stream BMPs have additional unique design and siting requirements. Here, we synthesize practitioner goals, their recommendations on in-stream BMP design, and open research questions related to in-stream BMPs. Many interviewees suggested pairing engineered hyporheic zones with other BMPs in a treatment train to improve in-stream treatment, while simultaneously reducing risk and cost. We discuss how treatment trains and other strategies might also help overcome regulatory hurdles for innovative stormwater treatment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Powering the Blue Economy: Progress Exploring Marine Renewable Energy Integration With Ocean Observations

The blue economy is a dynamic and rapidly growing movement that captures the interplay between economic, social, and ecological sustainability of the ocean and encompasses numerous maritime sectors and activities (e.g., commerce and trade; living resources; renewable energy; minerals, materials, and freshwater; and ocean health and data). The demand for ocean data to inform scientific, risk reduction, and national security needs is leading to a large increase in the number of deployed ocean observation and monitoring systems, most of which require increased power. Because ocean observation systems are often placed in remote locations, they primarily rely on energy storage (or in some cases in situ energy generation) to power instruments and equipment, which imposes limits on sampling rates, deployment times, and spatiotemporal resolution of data. The U.S. Department of Energy Water Power Technologies Office is exploring the potential for marine renewable energy (MRE) devices (largely wave and tidal energy converters) to provide power to support multiple blue economy opportunities. A portion of these opportunities focus on power at sea markets for providing power in off-grid and offshore locations to support a variety of ocean-based activities, including ocean observation and navigation, underwater vehicle charging, marine aquaculture, marine algae farming, and seawater mining. Initially, research has focused on better understanding how and where MRE can provide a consistent source of reliable power to extend ocean observing missions, including operation of autonomous underwater vehicles. Online surveys as well as phone and inperson interviews were conducted with experts in the field of ocean observing systems and observatories to gather end-user requirements, determine energy needs, identify opportunities for codevelopment, and pinpoint constraints for MRE to meet those needs. The surveys and interviews provided feedback on the potential for powering devices and vehicles using MRE, including identifying common themes and challenges that will inform foundational research and development steps needed to advance the integration of MRE with ocean observing systems. In most cases, additional power generation on the order of watts was identified as significantly beneficial to enhancing ocean observations capabilities.

marine renewable energy, powering the blue economy↗
DOE OSTI2023

Developing Confidence in Machine Learning Results

As the field of deep learning has emerged in recent years, the amount of knowledge and expertise that data scientists are expected to absorb and maintain has correspondingly increased. One of the challenges experienced by data scientists working with deep learning models is developing confidence in the accuracy of their approach and the resulting findings. In this study, we conducted semi-structured interviews with data scientists at a National Laboratory to understand the processes that data scientists use when attempting to develop their models and the ways that they gain confidence that the results they obtained were accurate. These interviews were analysed to provide an overview of the techniques currently used when working with machine learning (ML) models and opportunities for collaboration with human factors researchers to develop new tools are identified.

Baweja, Jessica A.↗