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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Historic Significance and Current Condition Assessment of Building 06-CP-170, the Yucca Flat Weather Station, Area 6, Nevada National Security Site, Nye County, Nevada

This report was produced in partial fulfillment of the mitigation of adverse effects to Building 06-CP-170, the Yucca Flat Weather Station on the Nevada National Security Site (NNSS), and is intended to comply with the 2021 Memorandum of Agreement DE-GM58-21NA25543 Between the U.S. Department of Energy and the Nevada State Historic Preservation Officer Regarding Demolition of Fourteen Buildings and Structures in Area 6 of the Nevada National Security Site, Nye County, Nevada (hereafter referred to as the MOA). This MOA was executed to resolve adverse effects from the U.S. Department of Energy (DOE) plan to demolish 14 architectural resources at the Control Point and in the vicinity in Area 6 of the NNSS. The management and operations contractor for the NNSS identified these 14 architectural resources as environmental hazards unsafe for human occupation due to deterioration and rodent infestation. Building 06-CP-170 is scheduled for demolition as part of this undertaking. Building 06-CP-170 was originally recorded in 2018 during a Section 106 cultural resources inventory for a proposed installation of a 138-kilovolt transmission line on the NNSS. The building was determined individually eligible by the DOE, in consultation with the Nevada State Historic Preservation Office, for inclusion in the National Register of Historic Places under the Secretary of the Interior’s Significance Criterion A because of its association with nuclear testing. Pursuant to Stipulation III.D.3 of the MOA, this report provides a summary of the historic significance of Building 06-CP-170 and a description of its current condition and accessory resources. In addition, an updated Architectural Resource Assessment (ARA) form with new information and photographs is included in the appendix in fulfillment of Stipulation III.D.2.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Historic Significance and Current Condition Assessment of Building 06-CP-10, Device Assembly Building, Area 6, Nevada National Security Site, Nye County, Nevada

This report was produced in partial fulfillment of the mitigation of adverse effects to Building 06-CP-10, the first device assembly building on the Nevada National Security Site (NNSS), and is intended to comply with the 2021 Memorandum of Agreement DE-GM58-21NA25543 Between the U.S. Department of Energy and the Nevada State Historic Preservation Officer Regarding Demolition of Fourteen Buildings and Structures in Area 6 of the Nevada National Security Site, Nye County (hereafter referred to as the MOA). This MOA was executed to resolve adverse effects from the U.S. Department of Energy (DOE) plan to demolish 14 architectural resources at the Control Point and in the vicinity in Area 6 of the NNSS. The management and operations contractor for the NNSS identified these 14 architectural resources as environmental hazards unsafe for human occupation due to deterioration and rodent infestation. Building 06-CP-10 and two small magazine bunkers (06-CP-10A and 06-CP-805) associated with Building 06-CP-10 are scheduled for demolition as part of this undertaking. Building 06-CP-10 was originally recorded in 2003 during a historical evaluation of four buildings in Area 6. In consultation with the Nevada State Historic Preservation Office, the building was determined individually eligible for inclusion in the NRHP under the Secretary of the Interior’s Significance Criterion A because of its association with nuclear testing and under Significance Criterion C as a distinct type of construction associated with the nuclear industry. Building 06-CP-10A, a munitions magazine, and 06- CP-805, a cap-and-fuse bunker, have been recorded as contributing accessory resources to 06-CP-10. Pursuant to Stipulation III.C.3 of the MOA, this report provides a summary of the historic significance of Building 06-CP-10 and a description of its current condition and accessory resources. In addition, an updated Architectural Resource Assessment (ARA) form with new information and photographs is included in the appendix in fulfillment of Stipulation III.C.2.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Real-Time Operations Manual for the IEEE 118 Bus Transmission Model

This document presents a sample operations manual for the IEEE 118 Bus Model, which is a synthetic test case developed in 1962 from a section of the transmission grid operated by American Electric Power (AEP). The model is one of the most used synthetic test cases for development of power system applications and is referenced by over 9000 papers. However, the model lacks any context for use with real-time energy management system (EMS) applications, including common considerations, such as generator ramp rates, reactive capabilities, operating limits, and other information typically used by power system operators for real-time decision making. This manual divides the IEEE 118 Bus Model into three operating areas, defines various operating limits, and sets recommended operating procedures for responding to a few types of emergency operating conditions. The manual can be used in support of a wide variety of human-in-the-loop evaluation methodologies for new advanced power applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Assessment of Potential Ergonomic Injury Risk in the Nuclear Material Processing Glovebox Environment [Capstone Project]

Gloveboxes are isolation barriers that are used within many different industries such as pharmaceuticals, electronic parts fabrication, nuclear, and biological. The research on glovebox ergonomics is currently limited with few ergonomic professionals that focusing exclusively on glovebox working environments. There is existing documentation on occupational injuries, such as musculoskeletal disorders (MSD), sustained as a direct result of working in gloveboxes. The main elements that pose ergonomic risks to glovebox workers are operational repetition, duration, force, vibration, lifting heavy (more than 15lbs with two hands) objects, and awkward postures. This paper examines a small sample of the potential causal or risk factors that lead to the ergonomic injuries. A meta-analysis utilizing a random effect model is used to examine data from several studies which focus on, dexterity and strength changes as result of glove thickness, and robotic assistive technology as a means to improve postural mechanics. With the meta-analysis technique, similar data sets from different research studies can be coalesced into a single weighted, statistically significant result for subsequent consideration. The results from the analysis show that increased glove thickness results in decreased dexterity for operators thus increasing ergonomic risk factors such as task duration. It is also shown that glove thickness decreases grip strength but a similar decrease in pinch strength is not definitively demonstrated. With decreased grip strength, operators will need to exert more force (a known ergonomic risk factor) on processing tools, etc. during operations thus increasing the risk of ergonomic injury. The use of robotic assistive technology as a means to improve operator posture (risk factor) was also examined. Although it may be intuitively assumed that human-robotic collaboration would be beneficial in reducing risk factors, the result from this study’s analysis was not statistically significant. It is inferred that with additional directed research on this topic another study/analysis could be statistically significant demonstrating the benefits of the technology.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

A microbial survey of the International Space Station (ISS)

Background: Modern advances in sequencing technology have enabled the census of microbial members of many natural ecosystems. Recently, attention is increasingly being paid to the microbial residents of human-made, built ecosystems, both private (homes) and public (subways, office buildings, and hospitals). Here, we report results of the characterization of the microbial ecology of a singular built environment, the International Space Station (ISS). This ISS sampling involved the collection and microbial analysis (via 16S rDNA PCR) of 15 surfaces sampled by swabs onboard the ISS. This sampling was a component of Project MERCCURI (Microbial Ecology Research Combining Citizen and University Researchers on ISS). Learning more about the microbial inhabitants of the “buildings” in which we travel through space will take on increasing importance, as plans for human exploration continue, with the possibility of colonization of other planets and moons. Results: Sterile swabs were used to sample 15 surfaces onboard the ISS. The sites sampled were designed to be analogous to samples collected for (1) the Wildlife of Our Homes project and (2) a study of cell phones and shoes that were concurrently being collected for another component of Project MERCCURI. Sequencing of the 16S rDNA genes amplified from DNA extracted from each swab was used to produce a census of the microbes present on each surface sampled. We compared the microbes found on the ISS swabs to those from both homes on Earth and data from the Human Microbiome Project. Conclusions: While significantly different from homes on Earth and the Human Microbiome Project samples analyzed here, the microbial community composition on the ISS was more similar to home surfaces than to the human microbiome samples. The ISS surfaces are species-rich with 1,036–4,294 operational taxonomic units (OTUs per sample). There was no discernible biogeography of microbes on the 15 ISS surfaces, although this may be a reflection of the small sample size we were able to obtain.

International space station↗
DOE OSTI2012

Improving landscape-level environmental impact evaluations.

New spatial data and advancements in GIS tools allow much more comprehensive and quantitative analyses of the large datasets required when making programmatic evaluations of the ecological effects of proposed activities that cover a large area or region. Understanding the environmental impacts of proposed human developments is critical to making appropriate siting decisions and designing mitigation strategies to reduce impacts on important resources. Impact analyses conducted under the National Environmental Policy Act (NEPA) in Environmental Impact Statements (EISs) or Environmental Assessments (EAs) are intended to determine the resource-specific impacts of proposed activities of federal agencies and their alternatives using the best available information. Impacts to ecological resources are often a primary focus of these analyses. Information used in NEPA analyses include some measure of the known or probable presence of plants and wildlife in the project area, with special emphasis placed on threatened, endangered, and other special-status species. Site-specific information pertaining to ecological resources is usually easier to obtain for small-scale activities such as a local facility, road, or transmission upgrade project, where the ability to conduct fieldwork is more often feasible. However, site-specific data is more difficult-and sometimes impossible-to obtain for proposed activities that could affect a large area or region. These types of analyses often are considered in programmatic NEPA documents, in which a federal agency evaluates the implementation of a broad program or plan. Under these programmatic evaluations, the exact location and size of developments are often not known. Because obtaining quantitative information for ecological resources at such large spatial scales is difficult, programmatic impact evaluations typically rely on sketchy or partial information such as recorded species occurrences, species ranges, and general habitat descriptions. However, new spatial data and improved GIS tools allow much more comprehensive and quantitative analyses using large, readily available datasets. The availability of large-scale regional data such as GAP land-cover models or species habitat suitability models, combined with more robust spatial analysis procedures available through ArcGIS for Desktop software, allowed the analysis of multiple datasets at large spatial scales. This enabled researchers to surpass previous qualitative evaluations by developing a more accurate and quantitative approach for determining the environmental impacts of human activities at larger spatial scales. These approaches, combined with the utility of ModelBuilder and operability of Python scripts in ArcGIS, allow a more timely and cost-effective synthesis of available spatial data for programmatic evaluations and add a quantitative basis to environmental decision making.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Deep Learning for Automated Identification of Eels in Sonar Data

Freshwater eels, such as the American eel (Anguilla rostrata) present numerous challenges related to safe downstream fish passage at hydroelectric facilities. One of those challenges is effective monitoring of their abundance, movements, and behavior to facilitate design and operation of eel protection and passage facilities. A previous EPRI study documented the ability of human analysts to reliably identify American eels in data obtained with a 1100/1800 kHz, multibeam sonar. This report describes a project to develop deep learning (a subset of artificial intelligence) tools to automate the time-consuming, subjective process of eel identification in multibeam sonar data. The project exploited new data collected in the laboratory and the existing data from the prior EPRI field study to develop and test deep learning and other data analytic tools, including wavelet filtering, differencing for static object removal, and convolutional neural network analysis. The analysis of the laboratory data demonstrated feasibility of the approach, revealed object characteristics observed with the sonar that distinguish eels from similarly sized and shaped acoustic targets, and provided additional data for algorithm selection and training. Deep learning algorithms trained and tested on the laboratory data alone achieved accuracy rates of greater than 98% when classifying acoustic images of eels and similar-sized neutrally buoyant sticks. The algorithm trained and tested on the pre-existing field data alone, and yielded classification accuracy of 9.3% false positives and 13.3% false negatives when distinguishing between eels and sticks/PVC pipes based on video clips (i.e., multiple, consecutive images). This performance is comparable to the classification accuracy achieved by human analysts in the prior study. The deep learning algorithm trained on a combination of video clips obtained in the laboratory and the field and tested on video clips from the field, was able to distinguish eels from sticks and PVC pipes (a river debris analog) of similar size with 100% accuracy. Outreach to the hardware, software, and end-user communities early in the project helped to identify needs and specify the application space. Outreach to those communities at the end of the project communicated project results and opportunities for further development. The project achieved proof of concept for automated identification of eel in multibeam sonar data. Future work should focus on acquisition of additional data for more robust algorithm training and testing; modification of the software tools to accommodate multiple acoustic targets in the acoustic field at a given time; identification of additional object classes; incorporation of motion in the object identification and classification algorithms; operationalizing the software tools, including integration with other existing sonar data analysis tools; and partnering with hardware and software providers for distribution of the software tools with their commercial products.

13 HYDRO ENERGY↗
DOE OSTI2023

An Agenda for Multimodal Foundation Models for Earth Observation

Archives of remote sensing (RS) data are increasing swiftly as new sensing modalities with enhanced spatiotemporal resolution become operational. While promising new breakthroughs, the sheer volume of RS archives stretches the limits of human analysts and existing AI tools, as most models are: i) limited to single data modalities; ii) task-specific; iii) heavily reliant on labeled data. The emerging Foundation Models (FMs) have the potential to address these limitations. Trained on vast unlabeled datasets through self-supervised learning, FMs enable generic feature extraction that facilitate specialization to a wide variety of downstream tasks. This paper describes a vision towards an FM for multimodal Earth Observation data (FM4EO), discussing key building blocks and open challenges. We put particular emphasis on multimodal reasoning, a topic underexplored in EO. Our ultimate goal is a practical path toward FM4EO with capacity to unlock breakthroughs in few-shot learning scenarios, multimodal geographic knowledge integration, synthesis, and hypothesis generation.

Ambrozio Dias, Philipe↗
DOE OSTI2017

Modular Platforms for Advanced Inspection, Locomotion, and Manipulation - 17150

Robots can provide remote access, manipulation, and inspection capabilities to augment human workers and improve safety in potentially dangerous decommissioning, radioactive waste management, and emergency response operations. However, such activities may require navigating challenging and unstructured environments, such as those with uneven terrain, obstacles, or loose debris. This remains a difficult task, even for modern robots. What's more, a robot's physical design can inhibit it from accessing hard-to-reach areas such as the tight spaces around, underneath, or inside piping and equipment. To address these challenges, we have developed a series of physically robust hardware modules that can be configured into a variety of robot morphologies, specialized to support different operational needs. Each hardware module consists of a number of onboard sensors and a high performance actuator with a series elastic element to sense and control interaction forces for improved locomotion and manipulation. Using this hardware, we have designed several robotic platforms that support the access, manipulation, and inspection requirements of decommissioning and radioactive waste management. To highlight current capabilities and potential opportunities for technological improvement, we present the outcomes from field demonstrations of our modular platforms at the Office of Environmental Management's Science of Safety Portsmouth Gaseous Diffusion Plant Robotics Challenge. Specifically, results include a serpentine robot climbing vertical structures such as pipes, posts, and supports to demonstrate advanced inspection. Additionally, we discuss field trials of a similar modular configuration that yields a highly dexterous manipulator arm and camera system capable of adding manipulation and inspection functionality to existing structures. Results are presented from inspection tasks in which the manipulator is installed on another mobile robotic platform. Finally, we show our hardware modules can be reconfigured into platforms capable of withstanding significant impacts and of alternative means of locomotion, as may be required to cross terrain too challenging for traditional wheeled robots. Results describe the performance of a hexapod robot that uses proprioceptive feedback to locomote in outdoor trials reminiscent of emergency response conditions. (authors)

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

CASTLE: Conflict Analysis Strategy Testing Laboratory Environment v.1.0.0

SAND2024-01743O The Conflict Analysis Strategy Testing Laboratory Environment (CASTLE) is a software framework that enables and simplifies building a novel, turn-based strategy game in which it can define its own rules, maps, pieces, and interactions. The software is for novice to experienced programmers with some knowledge of Unity3D, a tool used in game production. CASTLE includes a library of common game mechanics used for strategic wargames and traditional board games, such as cards, tokens, dice, and grid maps. It follows design principles popularized by the video game industry and uses singletons for managing portions of the code. CASTLE builds on Unity's component-based design and can respond to engine events during execution. Among the numerous user-friendly features: Build games quickly and cost-effectively Network in real-time and apply data to new games developed on the framework Host multiple participants online Connect rule- or machine learning-based agents to a CASTLE game to serve as opponents or to simulate games Collect data collection from players and in-game behaviors Create a survey to gather demographics or opinions from players Store data locally or save it to an external database through Representational State Transfer (REST) functions CASTLE, which was prototyped using Microsoft Azure, is also designed for easily distributing online games using popular cloud services. The multiplayer functionality includes an agent interface, allowing developers to construct AI players that can substitute for humans in any of the games. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Fabian, Nathan↗
DOE OSTI2021

Viral Inhibitors Derived from Macroalgae, Microalgae, and Cyanobacteria: A review of antiviral potential throughout pathogenesis

Viruses are abiotic obligate parasites utilizing complex mechanisms to hijack cellular machinery and reproduce, causing multiple harmful effects in the process. Viruses represent a growing global health concern; at the time of writing, COVID-19 has killed at least two million people around the world and devastated global economies. Lingering concern regarding the virus’ prevalence yet hampers return to normalcy. While catastrophic in and of itself, COVID-19 further heralds in a new era of human-disease interaction characterized by the emergence of novel viruses from natural sources with heretofore unseen frequency. Due to deforestation, population growth, and climate change, we are encountering more viruses that can infect larger groups of people with greater ease and increasingly severe outcomes. The devastation of COVID-19 and forecasts of future human/disease interactions call for a creative reconsideration of global response to infectious disease. There is an urgent need for accessible, cost-effective antiviral (AV) drugs that can be mass-produced and widely distributed to large populations. Development of AV drugs should be informed by a thorough understanding of viral structure and function as well as human biology. To maximize efficacy, minimize cost, and reduce development of drug-resistance, these drugs would ideally operate through a varied set of mechanisms at multiple stages throughout the course of infection. Due to their abundance and diversity, natural compounds are ideal for such comprehensive therapeutic interventions. Promising sources of such drugs are found throughout nature; especially remarkable are the algae, a polyphyletic grouping of phototrophs that produce diverse bioactive compounds. While not much literature has been published on the subject, studies have shown that these compounds exert antiviral effects at different stages of viral pathogenesis. In this review, we follow the course of viral infection in the human body and evaluate the AV effects of algae-derived compounds at each stage. Specifically, we examine the AV activities of algae-derived compounds at the entry of viruses into the body, transport through the body via the lymph and blood, infection of target cells, and immune response. We discuss what is known about algae-derived compounds that may interfere with the infection pathways of SARS-CoV-2; and review which algae are promising sources for AV agents or AV precursors that, with further investigation, may yield life-saving drugs due to their diversity of mechanisms and exceptional pharmaceutical potential.

Algae, antiviral, SARS-CoV-2, seaweed, cyanobacter↗
DOE OSTI2025

Airport Ground Support Equipment Infrastructure & Logistics Electrification Assessment Tool: 2025 Data Development, Modeling and Analysis for DFW

The aviation industry is increasingly turning to modernize freight facilities by integrating electric Ground Support Equipment (eGSE) to enhance operational efficiency of freight facility moving vehicles and equipment. Airports worldwide are adopting eGSE to streamline cargo movement, reduce fuel and maintenance costs, and improve logistics coordination.1 North America, with its advanced aviation infrastructure, leads this transition, leveraging Internet of things (IoT)-enabled automation and zero emission technologies to boost reliability and reduce human errors.2 Electrification of freight facility moving vehicles and equipment boosts turnaround times, improves equipment reliability, and optimizes logistics coordination, giving operators a competitive advantage. With rising fuel price volatility and the pressure to meet stringent performance benchmarks, airports are focusing on cost-effective, scalable solutions for long-term financial and operational gains. To further accelerate electrification, airports are integrating Zero Emission Vehicles (ZEVs) into rental car fleets and deploying electric baggage carts, requiring strategic investments in charging infrastructure. 3 The shift, however, presents challenges, such as limited technical expertise, high capital costs, and complex procurement processes. By forging strategic partnerships, leveraging advanced technologies, and optimizing infrastructure investments, airports can create a resilient, future-ready ecosystem that enhances the movement of people and goods through electrification-driven efficiency. Supported by the U.S. Department of Energy (DOE) Vehicle Technologies Office (VTO), this electrification effort provides a scalable, cost-effective solution to improve airport freight operations. Through targeted investments and innovation, airports enhance efficiency, reduce costs, and meet performance benchmarks while advancing toward a resilient, electrified future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Real-time and Autonomous Water Quality Monitoring System Based on Remotely Operated Vehicle

Existing water quality monitoring systems near hydropower facilities are limited by the lack of mobility of the sensors’ carrier platform. Most systems use a buoy, a mounting fixture attached to a solid structure, or a human worker, which significantly limits the selection of the sampling sites and poses safety risks during data collection and equipment maintenance. To improve on this technology, we developed an autonomous water quality monitoring system that can operate in dangerous water environments near hydropower facilities for water sampling at multiple locations. The goal is to enable safe, timely, and comprehensive water-quality data collection; maximize power generation revenue with improved operational control; and reduce Federal Energy Regulatory Commission and state water quality monitoring costs for compliance. The system incorporates a remotely operated vehicle as the mobile monitoring platform, a dissolved oxygen sensor for monitoring water quality, a tether management system for automatically winding the tether, a solar mobile docking platform for suppling power to the ROV, and a web-based graphical user interface for data post-processing and visualization. In addition, preliminary field research are presented to demonstrate the system capabilities.

Salalila, Aljon L.↗
DOE OSTI2015

Bridging the gap: adapting advanced display technologies for use in hybrid control rooms

The Institute for Energy Technology (IFE), runs the OECD Halden Reactor Project (HRP), featuring a state-of-the-art research simulator facility in Halden, Norway, called HAMMLAB. HAMMLAB serves two main purposes: the study of human behaviour in interaction with complex process systems; and the development, test and evaluation of prototype control centres and their individual systems. By studying operator performance in HAMMLAB and integrating the knowledge gained into new designs, the HRP contributes to improving operational safety, reliability, efficiency and productivity. The U.S. Department of Energy’s (DOE) Light Water Reactor Sustainability (LWRS) Program has contracted IFE to assist DOE national laboratory staff at Idaho National Laboratory (INL) in adapting HAMMLAB design concepts for the purpose of control room modernization at nuclear power plants in the U.S. In support of this effort, the DOE has built a simulator research facility at INL called the Human Systems Simulation Laboratory (HSSL). The HSSL is centered on control room modernization, in which industry provided plant instrumentation and controls are modified for upgrade opportunities. The HSSL houses the LWRS simulator, which is a reconfigurable full-scale and full-scope control room simulator. Consisting of 45 large touchscreens on 15 panels, the LWRS simulator is currently using this glass top technology to digitally represent and replicate the functionality of the analog I&C systems in existing control rooms. The LWRS simulator is reconfigurable in that different plant training simulator models obtained from the utilities can be run on the panels, and the panels can be physically moved and arranged to mimic the layout of those control rooms. The glass top technology and reconfigurability capabilities allow the LWRS simulator to be the research platform that is necessary to design, prototype, and validate human-system interface (HSI) technologies that can replace existing analog I&C. IFE has recently assisted INL in establishing the technical infrastructure for implementation of HSI prototypes from HAMMLAB into the HSSL to demonstrate relevant control room replacement systems in support of the LWRS program. In March, 2014, IFE delivered the first HSI prototype utilizing this infrastructure — a large screen overview display for INL's simulator. The co-operation now continues by developing Procedure Support Displays targeted for operators in hybrid control room settings. These prototypes are being validated with U.S. reactor operators in the HSSL and optimized to enhance their performance. This research serves as a crucial stepping stone toward incorporation of advanced display technologies into conventional main control rooms.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Effects of the distribution and evolution of the coefficient of friction along a fault on the assessment of the seismic activity associated with a hypothetical industrial-scale geologic CO 2 sequestration operation

Carbon capture and storage (CCS) in geological formations is considered as a promising option that could limit CO 2 emissions from human activities into the atmosphere. However, there is a risk that pressure buildup inside the storage formation can induce slip along preexisting faults and create seismic event felt by the population. To prevent this to happen a geomechanical fault stability analysis should be performed, considering uncertainties of input parameters. In this paper, we investigate how the distribution of the coefficient of friction and the applied frictional law could influence the assessment of fault stability and the characteristics of potential injection-induced seismic events. Our modelling study is based on a hypothetical industrial-scale carbon sequestration project located in the Southern San Joaquin Basin in California, USA, where the stability on a major (25 km long) fault that bounds the sequestration site is assessed during 50 years of CO 2 injection. We conduct nine simulations in which the distributions of the coefficients of static and dynamic friction are changed to simulate a hardening and softening phase before and during rupture. Here, our main findings are: (i) variations in friction along the fault have an important effect on the predicted seismic activity, with maximum magnitude ranging from 1.88 to 5.88 and number of seismic events ranging from 338 to 3272; (ii) the extreme values of the coefficient of friction (lowest and highest) present along the rupture area control how much stress is accumulated before rupture; and (iii) an argillaceous caprock can prevent the development of large magnitude seismic events but favor the occurrence of a large number of smaller events.

58 GEOSCIENCES↗
DOE OSTI2021

Occupant-Centric key performance indicators to inform building design and operations

Building performance indicators are widely used to guide building design and track and benchmark operational performance. Traditional building performance indicators mostly focus on the energy efficiency perspective. As occupants are the primary building service recipients in residential and most commercial buildings, their comfort and wellbeing are crucial. As such, this study first identified significant attributes of occupant-centric key performance indicators (KPIs) and analyzed the diverse factors that should be considered in formulating an occupant-centric KPI. Then a suite of occupant-centric KPIs were synthesized from the review and enhancement of existing occupant-related performance metrics. The proposed occupant KPIs represent the occupant lens on three integrative aspects of building performance: resource use (including energy and water), indoor environmental quality, and human–building interactions. A simulation-based case study was conducted to demonstrate how occupant-centric KPIs can be used to quantify the impacts of building operation changes from the occupants’ point of view. Highlights: Occupant-centric metrics are currently ad hoc and limited, yet crucial to inform building design and operations. Literature was reviewed to reveal the state-of-the-art and gaps of occupant-centric metrics. A suite of occupant-centric key performance indicators (KPIs) covering five groups of building services were synthesized. Proposed occupant KPIs represent three aspects of performance: resource use and demand, occupant comfort and health, and human–building interactions. A case study using whole building simulation was conducted to demonstrate the use of occupant-centric KPIs in evaluating building operations during a power outage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Closeout of CRADA JSA 2012S004: Chapter 5, Integrated Control System, of the document of the ESS Conceptual Design Report, publicly available at https://europeanspallationsource.se/accelerator-documents

The integrated control system (ICS) is responsible for the whole ESS machine and facility: accelerator, target, neutron scattering instruments and conventional facilities. This unified approach keeps the costs of development, maintenance and support relatively low. ESS has selected a standardised, field-proven controls framework, the Experimental Physics and Industrial Control System (EPICS), which was originally developed jointly by Argonne and Los Alamos National Laboratories. Complementing this selection are best practices and experience from similar facilities regarding platform standardisation, control system development and device integration and commissioning. The components of ICS include the control system core, the control boxes, the BLED database management system, and the human machine interface. The control system core is a set of systems and tools that make it possible for the control system to provide required data, information and services to engineers, operators, physicists and the facility itself. The core components are the timing system that makes possible clock synchronisation across the facility, the machine protection system (MPS) and the personnel protection system (PPS) that prevent damage to the machine and personnel, and a set of control system services. Control boxes are servers that control a collection of equipment (for example a radio frequency cavity). The integrated control system will include many control boxes that can be assigned to one supplier, such as an internal team, a collaborating institute or a commercial vendor. This approach facilitates a clear division of responsibilities and makes integration much easier. A control box is composed of a standardised hardware platform, components, development tools and services. On the top level, it interfaces with the core control system components (timing, MPS, PPS) and with the human-machine interface. At the bottom, it interfaces with the equipment and parts of the facility through a set of analog and digital signals, real-time control loops and other communication buses. The ICS central data management system is named BLED (beam line element databases). BLED is a set of databases, tools and services that is used to store, manage and access data. It holds vital control system configuration and physics-related (lattice) information about the accelerator, target and instruments. It facilitates control system configuration by bringing together direct input-output controller (IOC) con guration and real-time data from proton and neutron beam line models. BLED also simplifies development and speeds up the code-test-debug cycle. The set of tools that access BLED will be tailored to the needs of different categories of users, such as ESS staff physicists, engineers, and operators; external partner laboratories; and visiting experimental instrument users. The human-machine interface is vital to providing a high-quality experience to ICS users. It encompasses a wide array of devices and software tools, from control room screens to engineer terminal windows; from beam physics data tools to post-mortem data analysis tools. It serves users with a wide range of skills from widely varied backgrounds. The Controls Group is developing a set of user profiles to accommodate this diverse range of use-cases and users.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2017

A HUMAN FACTORS ENGINEERING PROCESS TO SUPPORT HUMAN-SYSTEM INTERFACE DESIGN IN CONTROL ROOM MODERNIZATION

The primary objective of the United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program is to sustain operation of the existing commercial nuclear power plants (NPPs) through a multi-pathway approach in conducting research and development (R&D). The Advanced Instrumentation, Information, and Control (II&C) System Technologies pathway conducts targeted R&D to address aging and reliability concerns with legacy instrumentation and control (I&C) and other information systems in existing U.S. NPPs. Control room modernization is an important part following this pathway, and human factors experts at Idaho National Laboratory (INL) have been involved in conducting R&D to support migration of new digital main control room (MCR) technologies from legacy analog and legacy digital I&C. This paper describes a human factors engineering (HFE) process that supports human-system interface (HSI) design in MCR modernization activities, particularly with migration of old digital to new digital I&C. The process described in this work is an expansion from the LWRS Report INL/EXT-16-38576, and is a requirements-driven approach that aligns with NUREG-0711 requirements. The work described builds upon the existing literature by adding more detail around key tasks and decisions to make when transitioning from HSI Design into Verification and Validation (V&V). The overall objective of this process is to inform HSI design and elicit specific, measurable, and achievable human factors criteria for new digital technologies. Upon following this process, utilities should have greater confidence with transitioning from HSI design into V&V.

99 GENERAL AND MISCELLANEOUS↗