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Operator-in-the-Loop Study for a Computerized Operator Support System (COSS) – Cross-System and System-Independent Evaluations

The Computerized Operator Support System (COSS) is an operator assistive technology funded by the U.S. Department of Energy Office of Nuclear Energy and developed at Idaho National Laboratory. The project works in collaboration with an advanced prognostics system called PRO-AID developed at Argonne National Laboratory. The COSS provides a human-machine interface to help operators maintain situation awareness and detect faults earlier than would be possible using conventional control room technologies at nuclear power plants. This report represents a status report outlining third-year efforts to develop and validate the COSS. The COSS has now been implemented as a prototype system, with multiple interaction design concepts on multiple plant systems in the simulator from a commercial nuclear power plant. Two studies involving three licensed reactor crews were conducted to evaluate the COSS. This report captures insights into the development of COSS as well as operator feedback and future development guidance derived from the operator-in-the-loop simulator studies.

99 GENERAL AND MISCELLANEOUS↗

Seroprevalence and risk factors for brucellosis amongst livestock and humans in a multi-herd ranch system in Kagera, Tanzania

Background Brucellosis remains a significant health and economic challenge for livestock and humans globally. Despite its public health implications, the factors driving the endemic persistence ofBrucellaat the human-livestock interface in Tanzania remain poorly elucidated. This study aimed to identify the seroprevalence ofBrucellainfection in livestock and humans within a ranching system and determine associated risk factors for disease endemicity. Methods A cross-sectional sero-epidemiological study was conducted in 2023 in Tanzania’s Karagwe District, involving 725 livestock (cattle, goats, sheep) from 10 herds and 112 humans from associated camps. Seroprevalence was assessed using competitive ELISA while epidemiological data were collected via questionnaires. Generalized Linear Models and Contrast Analysis were used to identify risk factors for infection. Results Overall seroprevalence was 34% in livestock and 41% in humans. Goats exhibited the highest prevalence (69.2%), while cattle had the lowest (22.6%). Mixed-species herds (Odds Ratio, OR = 2.96, CI [1.90–4.60]) and small ruminants-only herds (OR = 6.54, CI [3.65–11.72]) showed a significantly higher risk of seropositivity compared to cattle-only herds. Older cattle (OR = 5.23, CI [2.70–10.10]) and lactating females (OR = 2.87, CI [1.78–4.63]) represented significant risks for brucellosis in livestock. In humans, close contact with animals (OR = 7.20, CI [1.97–36.31]) and handling animals during parturition or aborted fetuses (OR = 2.37, CI [1.01–5.58]) were significant risk factors. Notably, no spatial association was found in seroprevalence between herds and nearby human communities. Conclusion The lack of spatial correlation between livestock and human seroprevalence suggests complex transmission dynamics, potentially involving endemic circulation in livestock and human infections from multiple sources of exposure to livestock. This study highlights the need for comprehensive zoonotic risk education and targeted intervention strategies. Further research is crucial to elucidate transmission pathways and improveBrucellainfection control. This includes developing robust methods for identifying infective species and implementing effective strategies to mitigateBrucellainfection in endemic regions.

Public, Environmental & Occupational Health↗

Automated Work Packages Prototype: Initial Design, Development, and Evaluation. Light Water Reactor Sustainability Program

The goal of the Automated Work Packages (AWP) project is to demonstrate how to enhance work quality, cost management, and nuclear safety through the use of advanced technology. The work described in this report is part of the digital architecture for a highly automated plant project of the technical program plan for advanced instrumentation, information, and control (II&C) systems technologies. This report addresses the DOE Milestone M2LW-15IN0603112: Describe the outcomes of field evaluations/demonstrations of the AWP prototype system and plant surveillance and communication framework requirements at host utilities. A brief background to the need for AWP research is provided, then two human factors field evaluation studies are described. These studies focus on the user experience of conducting a task (in this case a preventive maintenance and a surveillance test) while using an AWP system. The remaining part of the report describes an II&C effort to provide real time status updates to the technician by wireless transfer of equipment indications and a dynamic user interface.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Standardized Procedure Content And Data Structure Based On Human Factors Requirements For Computer-Based Procedures

Most activities that involve human interaction with systems in a nuclear power plant are guided by procedures. Traditionally, the use of procedures has been a paper-based process that supports safe operation of the nuclear power industry. However, the nuclear industry is constantly trying to find ways to decrease the human error rate, especially the human errors associated with procedure use. Advances in digital technology make computer-based procedures (CBPs) a valid option that provides further enhancement of safety by improving human performance related to procedure use. The transition from paper-based procedures (PBPs) to CBPs creates a need for a computer-based procedure system (CBPS). A CBPS needs to have the ability to perform logical operations in order to adjust to the inputs received from either users or real time data from plant status databases. Without the ability for logical operations the procedure is just an electronic copy of the paper-based procedure. In order to provide the CBPS with the information it needs to display the procedure steps to the user, special care is needed in the format used to deliver all data and instructions to create the steps. The procedure should be broken down into basic elements and formatted in a standard method for the CBPS. One way to build the underlying data architecture is to use an Extensible Markup Language (XML) schema, which utilizes basic elements to build each step in the smart procedure. The attributes of each step will determine the type of functionality that the system will generate for that step. The CBPS will provide the context for the step to deliver referential information, request a decision, or accept input from the user. The XML schema needs to provide all data necessary for the system to accurately perform each step without the need for the procedure writer to reprogram the CBPS. The research team at the Idaho National Laboratory has developed a prototype CBPS for field workers as well as the underlying data structure for such CBPS. The objective of the research effort is to develop guidance on how to design both the user interface and the underlying schema. This paper will describe the result and insights gained from the research activities conducted to date.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

BWR modernization project: installation of a new digital feedwater control system - 295

A European BWR plant carried out a relevant and pioneering modernization project regarding the Feedwater and Feed Pump Turbine Control System, replacing the legacy analogic control with the new General Electric MarkVIe digital system. This digital instrumentation and control modernization, motivated by obsolescence, had a great impact on the main control room and on the plant operation. Tecnatom collaborated with the nuclear power plant in the project performing the following activities: early installation of the system in the full scope and classroom simulators, Human Factors Engineering (HFE) Verification and Validation (V and V), Simulation Assisted Engineering (SAE), design and implementation of cyber secure communication with the Plant Process Computer (PPC), operating procedures modification and plant operators training. Those activities contributed to the success of the project that was completed during the refueling outage as planned. Scheduling HFE verification before the design freeze allowed the plant to modify the Human Machine Interface (HMI) to comply with the standards and increase safety without overcharging the project. SAE resulted in the reduction of costs and time during the system commissioning through the detection of discrepancies and improvements in the control, covering different plant scenarios. All the activities carried out in the simulators before the implementation of the system in the plant contributed to validate it and to build confidence in the new control among the plant personnel. New digital system communication interfaces with the PPC saved cable laying works and allowed future expansions. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Design Philosophy for Accelerator Control Rooms

This report describes the foundational human factors principles needed to design user interfaces for accelerator control rooms. These principles are presented as recommendations for accelerator control system interface design and are illustrated with examples drawn from accelerator operations at Fermi National Accelerator Laboratory (Fermilab). These high-level principles are intended to serve as design objectives that apply generally across all control system interfaces developed for the accelerator complex. This design philosophy document is a high-level roadmap to approach the general interface design for the accelerator complex. This philosophy applies state-of-the-art human factors principles and evidence-based design standards to an accelerator environment, which will transform the next era of accelerator interfaces as outlined by the Accelerator Controls Operations Research Network (ACORN) Project. Further work will include mapping the general design principles included in this report to more specific guidance in the form of a user interface style guide.

43 PARTICLE ACCELERATORS↗

Robust High-Throughput Phenotyping with Deep Segmentation Enabled by a Web-Based Annotator

The abilities of plant biologists and breeders to characterize the genetic basis of physiological traits are limited by their abilities to obtain quantitative data representing precise details of trait variation, and particularly to collect this data at a high-throughput scale with low cost. Although deep learning methods have demonstrated unprecedented potential to automate plant phenotyping, these methods commonly rely on large training sets that can be time-consuming to generate. Intelligent algorithms have therefore been proposed to enhance the productivity of these annotations and reduce human efforts. We propose a high-throughput phenotyping system which features a Graphical User Interface (GUI) and a novel interactive segmentation algorithm: Semantic-Guided Interactive Object Segmentation (SGIOS). By providing a user-friendly interface and intelligent assistance with annotation, this system offers potential to streamline and accelerate the generation of training sets, reducing the effort required by the user. Our evaluation shows that our proposed SGIOS model requires fewer user inputs compared to the state-of-art models for interactive segmentation. As a case study of the use of the GUI applied for genetic discovery in plants, we present an example of results from a preliminary genome-wide association study (GWAS) of in planta regeneration in Populus trichocarpa (poplar). We further demonstrate that the inclusion of a semantic prior map with SGIOS can accelerate the training process for future GWAS, using a sample of a dataset extracted from a poplar GWAS of in vitro regeneration. The capabilities of our phenotyping system surpass those of unassisted humans to rapidly and precisely phenotype our traits of interest. The scalability of this system enables large-scale phenomic screens that would otherwise be time-prohibitive, thereby providing increased power for GWAS, mutant screens, and other studies relying on large sample sizes to characterize the genetic basis of trait variation. Our user-friendly system can be used by researchers lacking a computational background, thus helping to democratize the use of deep segmentation as a tool for plant phenotyping.

54 ENVIRONMENTAL SCIENCES↗

Programmable soft valves for digital and analog control

In soft devices, complex actuation sequences and precise force control typically require hard electronic valves and microcontrollers. Existing designs for entirely soft pneumatic control systems are capable of either digital or analog operation, but not both, and are limited by speed of actuation, range of pressure, time required for fabrication, or loss of power through pull-down resistors. Using the nonlinear mechanics intrinsic to structures composed of soft materials—in this case, by leveraging membrane inversion and tube kinking—two modular soft components are developed: a piston actuator and a bistable pneumatic switch. These two components combine to create valves capable of analog pressure regulation, simplified digital logic, controlled oscillation, nonvolatile memory storage, linear actuation, and interfacing with human users in both digital and analog formats. Three demonstrations showcase the capabilities of systems constructed from these valves: 1) a wearable glove capable of analog control of a soft artificial robotic hand based on input from a human user’s fingers, 2) a human-controlled cushion matrix designed for use in medical care, and 3) an untethered robot which travels a distance dynamically programmed at the time of operation to retrieve an object. This work illustrates pathways for complementary digital and analog control of soft robots using a unified valve design.

42 ENGINEERING↗

Concept of Operations for Data Fusion Visualization

Situational awareness in the operations and supervision of a industrial system means that decision making entity, whether machine or human, have the important data presented in a timely manner. An optimal presentation of information such that the operator has the best opportunity accurately interpret and react to anomalies due to system degradation, failures or adversaries. Anticipated problems are a matter for system design; however, the paper will focus on concepts for situational awareness enhancement for a human operator when the unanticipated or unaddressed event types occur. Methodology for human machine interface development and refinement strategy is described for a synthetic fuels plant model. A novel concept for adaptively highlighting the most interesting information in the system and a plan for testing the methodology is described.

10 SYNTHETIC FUELS↗

High Dexterity Robotics for Safety and Emergency Response - 17104

Recently, significant advances in robotics have led to increased use in industrial and military applications. For example, the military has used explosive ordnance disposal (EOD) robots to enable responders to remotely investigate hazardous environments. While EOD robots have saved many lives, their utility is hampered by: 1) limited ability to manipulate complex objects and mechanisms (e.g. open a car door, operate power tools or turn valves), and 2) the requirement for significant operator training using joystick-type interfaces. Most robots today have simplistic manipulators and cannot easily operate in environments designed for humans as evidenced by the recent Amazon Picking Challenge and the DARPA Robotics Challenge. Simple tasks that humans perform easily, such as picking up objects or operating a cutting tool, require customized rigs that are expensive and time-consuming to use. The specialized nature of these robots limits their utility in highly unstructured environments, for example during emergency situations where a robot may need to be rapidly re-purposed for an unanticipated situation (i.e. the Fukushima nuclear disaster). Robots are needed that can perform complex human-like tasks and are easy to use for everyday and emergency tasks. In 2005 the Defense Advanced Research Projects Agency (DARPA) initiated the Revolutionizing Prosthetics (RP) Program with the goal of creating prosthetics as capable as the human arm and a human-machine interface enabling highly intuitive operation. The Johns Hopkins University Applied Physics Laboratory (JHU/APL) created the Modular Prosthetic Limb (MPL), originally developed for amputees and paralyzed individuals as part of the RP Program, to replicate the capability of the human hand and arm to the extent technologically possible. With 26 joints and over 180 sensors, it is one of the most sophisticated and fully integrated robotic arms in the world. We have also demonstrated human-machine interface techniques that are highly intuitive requiring minimal training. While the MPL was originally designed as a prosthetic, it has also been incorporated into mobile robotic systems to project human capability. Using tele-operation, we have demonstrated the ability to perform dual-arm remote operations in complex environments. For nuclear facilities, high dexterity robots combined with tele-operation offer the potential to enhance worker safety, productivity and quality. Safety enhancements include enabling remote operation in hazardous environments, remote handling of heavy or dangerous materials, and elimination of injury due to repetitive motions. Because the MPL is designed to function like a human limb, the robot can work in environments designed for humans with limited need for specialized tools. When used for routine operations, it can also maintain a level of familiarity and confidence that effectively accomplishes reinforcement training for use in emergency situations, unlike a specialized robot that might sit unused for months or years at a time. In August 2016 we demonstrated the use of the MPL at the Portsmouth Gaseous Diffusion Plant in Piketon, Ohio. Two robotic platform technologies were demonstrated to familiarize the DOE Emergency Management's (EM) workforce on the potential benefits of this technology. Here we present the results of those efforts, highlight the lessons learned during 'EM Week,' and outline potential future developments that could further advance application of these technologies to enhance worker safety. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Nanoparticles and amyloid systems: A fatal encounter?

Nanoparticles (NPs) are used in many products of our daily life, however, there has been concern that they may also be harmful to human health. Recently NPs have been found to accelerate the fibrillation kinetics of amyloid systems. In the past this has been preliminarily attributed to a nucleation effect. Nanoparticle surfaces and interfaces appear to limit the degrees of freedom of amyloid systems (i.e., peptides and proteins) due to a phase space constraint such that rapid cross-beta structures are formed faster than without interface interactions and in turn fibril formation is enhanced significantly. Here we explore if lipid bilayers in the form of liposomes (140nm) also accelerate fibril formation for amyloid systems. We have investigated a fragment NNFGAIL of the Human islet amyloid polypeptide (hIAPP) in contact with 1,2-diphytanoyl-sn-glycero-3-phosphocholine (DPhPC) liposomes in aqueous solution. We found that the lipid bilayer vesicles do accelerate fibril formation in time-resolved off-line detected atomic force microscopy experiments. Characteristic Thioflavine-T fluorescence on the same structures verify that the structures consist of aggregated peptides in a typical cross-β-structure arrangement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DAQExpert the service to increase CMS data-taking efficiency

The Data Acquisition (DAQ) system of the Compact Muon Solenoid (CMS) experiment at the LHC is a complex system responsible for the data readout, event building and recording of accepted events. Its proper functioning plays a critical role in the data-taking efficiency of the CMS experiment. In order to ensure high availability and recover promptly in the event of hardware or software failure of the subsystems, an expert system, the DAQ Expert, has been developed. It aims at improving the data taking efficiency, reducing the human error in the operations and minimising the on-call expert demand. Introduced in the beginning of 2017, it assists the shift crew and the system experts in recovering from operational faults, streamlining the post mortem analysis and, at the end of Run 2, triggering fully automatic recovery without human intervention. DAQ Expert analyses the real-time monitoring data originating from the DAQ components and the high-level trigger updated every few seconds. It pinpoints data flow problems, and recovers them automatically or after given operator approval. We analyse the CMS downtime in the 2018 run focusing on what was improved with the introduction of automated recovery; present challenges and design of encoding the expert knowledge into automated recovery jobs. Furthermore, we demonstrate the web-based, ReactJS interfaces that ensure an effective cooperation between the human operators in the control room and the automated recovery system. We report on the operational experience with automated recovery.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Challenges at the Frontiers of Matter and Energy: Transformative Opportunities for Discovery Science

FIVE TRANSFORMATIVE OPPORTUNITIES FOR DISCOVERY SCIENCE As a result of this effort, it has become clear that the progress made to date on the five Grand Challenges has created a springboard for seizing five new Transformative Opportunities that have the potential to further transform key technologies involving matter and energy. These five new Transformative Opportunities and the evidence supporting them are discussed in this new report, “Challenges at the Frontiers of Matter and Energy: Transformative Opportunities for Discovery Science.” Mastering Hierarchical Architectures and Beyond-Equilibrium Matter Complex materials and chemical processes transmute matter and energy, for example from CO2 and water to chemical fuel in photosynthesis, from visible light to electricity in solar cells and from electricity to light in light emitting diodes (LEDs) Such functionality requires complex assemblies of heterogeneous materials in hierarchical architectures that display time-dependent away-from-equilibrium behaviors. Much of the foundation of our understanding of such transformations however, is based on monolithic single- phase materials operating at or near thermodynamic equilibrium. The emergent functionalities enabling next-generation disruptive energy technologies require mastering the design, synthesis, and control of complex hierarchical materials employing dynamic far-from-equilibrium behavior. A key guide in this pursuit is nature, for biological systems prove the power of hierarchical assembly and far- from-equilibrium behavior. The challenges here are many: a description of the functionality of hierarchical assemblies in terms of their constituent parts, a blueprint of atomic and molecular positions for each constituent part, and a synthesis strategy for (a) placing the atoms and molecules in the proper positions for the component parts and (b) arranging the component parts into the required hierarchical structure. Targeted functionality will open the door to significant advances in the harvesting, transforming (e.g., reducing CO2, splitting water, and fixing nitrogen), storing, and use of energy to create new materials, manufacturing processes, and technologies—the lifeblood of human societies and economic growth. Beyond Ideal Materials and Systems: Understanding the Critical Roles of Heterogeneity, Interfaces, and Disorder Real materials, both natural ones and those we engineer, are usually a complex mixture of compositional and structural heterogeneities, interfaces, and disorder across all spatial and temporal scales. It is the fluctuations and disorderly states of these heterogeneities and interfaces that often determine the system’s properties and functionality. Much of our fundamental scientific knowledge is based on “ideal” systems, meaning materials that are observed in “frozen” states or represented by spatially or temporally averaged states. Too often, this approach has yielded overly simplistic models that hide important nuances and do not capture the complex behaviors of materials under realistic conditions. These behaviors drive vital chemical transformations such as catalysis, which initiates most industrial manufacturing processes, and friction and corrosion, the parasitic effects of which cost the U.S. economy billions of dollars annually. Expanding our scientific knowledge from the relative simplicity of ideal, perfectly ordered, or structurally averaged materials to the true complexity of real-world heterogeneities, interfaces, and disorder should enable us to realize enormous benefits in the materials and chemical sciences, which translates to the energy sciences, including solar and nuclear power, hydraulic fracturing, power conversion, airframes, and batteries. Harnessing Coherence in Light and Matter Quantum coherence in light and matter is a measure of the extent to which a wave field vibrates in unison with itself at neighboring points in space and time. Although this phenomenon is expressed at the atomic and electronic scales, it can dominate the macroscopic properties of materials and chemical reactions such as superconductivity and efficient photosynthesis. In recent years, enormous progress has been made in recognizing, manipulating, and exploiting quantum coherence. This progress has already elucidated the role that symmetry plays in protecting coherence in key materials, taught us how to use light to manipulate atoms and molecules, and provided us with increasingly sophisticated techniques for controlling and probing the charges and spins of quantum coherent systems. With the arrival of new sources of coherent light and electron beams, thanks in large part to investments by the U.S. Department of Energy’s Office of Basic Energy Sciences (BES), there is now an opportunity to engineer coherence in heterostructures that incorporate multiple types of materials and to control complex, multistep chemical transformations. This approach will pave the way for quantum information processing and next-generation photovoltaic cells and sensors. Revolutionary Advances in Models, Mathematics, Algorithms, Data, and Computing Science today is benefiting from a convergence of theoretical, mathematical, computational, and experimental capabilities that put us on the brink of greatly accelerating our ability to predict, synthesize, and control new materials and chemical processes, and to understand the complexities of matter across a range of scales. Imagine being able to chart a path through a vast sea of possible new materials to find a select few with desired properties. Instead of the time-honored forward approach, in which materials with desired properties are found through either trial-and-error experiments or lucky accidents, we have the opportunity to inversely design and create new materials that possess the properties we desire. The traditional approach has allowed us to make only a tiny fraction of all the materials that are theoretically possible. The inverse design approach, through the harmonious convergence of theoretical, mathematical, computational, and experimental capabilities, could usher in a virtual cornucopia of new materials with functionalities far beyond what nature can provide. Similarly, enhanced mathematical and computational capabilities significantly enhance our ability to extract physical and chemical insights from vastly larger data streams gathered during multimodal and multidimensional experiments using advanced characterization facilities. Exploiting Transformative Advances in Imaging Capabilities across Multiple Scales Historically, improvements in imaging capabilities have always resulted in improved understanding of scientific phenomena. A prime challenge today is finding ways to reconstruct raw data, obtained by probing and mapping matter across multiple scales, into analyzable images. BES investments in new and improved imaging facilities, most notably synchrotron x-ray sources, free-electron lasers, electron microscopes, and neutron sources, have greatly advanced our powers of observation, as have substantial improvements in laboratory- scale technologies. Furthermore, BES is now planning or actively discussing exciting new capabilities. Taken together, these advances in imaging capabilities provide an opportunity to expand our ability to observe and study matter from the 3D spatial perspectives of today to true “4D” spatially and temporally resolved maps of dynamics that allow quantitative predictions of time-dependent material properties and chemical processes. The knowledge gained will impact data storage, catalyst design, drug delivery, structural materials, and medical implants, to name just a few key technologies. ENABLING SUCCESS Seizing each of these five Transformative Opportunities, as well as accelerating further progress on Grand Challenge research, will require specific, targeted investments from BES in the areas of synthesis, meaning the ability to make the materials and architectures that are envisioned; instrumentation and tools, a category that includes theory and computation; and human capital, the most important asset for advancing the Grand Challenges and Transformative Opportunities. While “Challenges at the Frontiers of Matter and Energy: Transformative Opportunities for Discovery Science” could be viewed as a sequel to the original Grand Challenges report, it breaks much new ground in its assessment of the scientific landscape today versus the scientific landscape just a few years ago. In the original Grand Challenges report, it was noted that if the five Grand Challenges were met, our ability to direct matter and energy would be measured only by the limits of human imagination. This new report shows that, prodded by those challenges, the scientific community is positioned today to seize new opportunities whose impacts promise to be transformative for science and society, as well as dramatically accelerate progress in the pursuit of the original Grand Challenges.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Deciphering the source of primary biological aerosol particles: a pollen case study

Primary biological aerosol particles (PBAPs) are microscopic solids suspended in the atmosphere emitted by biological systems and play critical roles in the atmosphere and at the atmosphere-biosphere interface, impacting human health, climate, and the ecosystem function. Understanding the sources of PBAPs is necessary to decipher the mechanistic interactions between aerosols, climate, and distinct ecosystem components. However, the detection of specific PBAPs in complex ambient aerosol samples is challenging. We performed metabolomics analyses of pollen from three pollinating tree species and ambient samples collected during the peak pollination period of each species. Random Forest and sPLS-DA machine learning methods were employed to evaluate whether metabolic signatures of ambient samples can reveal the source of the main pollen particles present in the atmosphere. Our results suggest that atmospheric eco-metabolomics techniques combined with sophisticated statistical methods can decipher the origin of abundant PBAPs from complex ambient samples. Developing complete libraries containing high-resolution metabolomic fingerprints of the major PBAPs present in the atmosphere would significantly advance future research to accurately understand the role of PBAPs in the atmosphere, ecosystems and human health.

Rivas-Ubach, Albert↗

Power Consumption During Neuronal Computation

Maintaining the ability of the nervous system to perceive, remember, process, and react to the outside world necessitates a continuous energy supply. However, the overall power consumption is remarkably low, which has inspired engineers to mimic nervous systems in designing artificial cochlea, retinal implants, and brain–computer interfaces (BCIs) to improve the quality of life in patients. Such neuromorphic devices are both energy efficient and increasingly able to emulate many functions of the human nervous system. We explore the energy constraints of neuronal signaling within biology, review the quantitative tradeoff between energy use and information processing, and ask whether the biophysics and design of nerve cells minimizes energy consumption.

42 ENGINEERING↗

Exploring the Psychometrics of Common Post-Scenario Human Factors Questionnaires of Workload, Situation Awareness, and Perceived Difficulty

Abstract: The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program has the primary mission of sustaining operation of the existing commercial nuclear power plants (NPPs) through a multi-pathway approach in conducting research and development (R&D). In this effort, the role of human factors engineering (HFE) has been an integral in ensuring new digital upgrades that are part of the overall main control room modernization strategy for various U.S. NPPs optimize human-system performance and do not introduce new human failure modes. In this process, testing and evaluation of concept (i.e., prototype) human machine interfaces (HMIs) are done in operator-in-the-loop studies at various stages of the HFE modification process, such as during design and verification and validation (V&V) [1]. During these studies, licensed operators go through select scenarios using a testbed, such as a full-scale simulator or at a NPP’s training simulator, to identify potential usability issues and provide general design feedback regarding the new digital HMIs. Human-system performance is measured and evaluated through a range of objective and self-report measures that capture aspects of plant performance, task performance, workload, situation awareness, and anthropometric and ergonomic concerns [2]. The use of post-scenario questionnaires is an acceptable method for gathering measures of workload and situation awareness. To this end, the NASA-Task Load Index (TLX) [e.g., 3, 4, & 5] and Situation Awareness Rating Technique (SART) [e.g., 6 & 7] are common standardized questionnaires used for evaluating workload and situation awareness, respectively. When combined, these questionnaires consist of a total of 15 questions, each using a different rating scale. Debriefs are also done through interviews with operators to gather design insight after each scenario. Since operator- and training simulator-time is limited, a concern during this post-scenario period of operator-in-the-loop studies is the limited time available to run scenarios, administer post-scenario questionnaires, and debrief within the allotted simulator time. To address this potential problem, this paper explores the psychometric characteristics of NASA-TLX, SART, and a common one-question post-scenario usability questionnaire (i.e., the single ease question – SEQ [8]) in effort to inform future development of a condensed questionnaire that captures aspects of workload and situation awareness. This exploratory work uses data from four different operator-in-the-loop studies completed under prior LWRS operator-in-the-loop studies. Findings from this paper should support future development of a consolidated questionnaire that may be used in operator-in-the-loop studies, when time is compressed, that conforms to the HFE scientific and regulatory requirements set for NPP control room modernization.

99 GENERAL AND MISCELLANEOUS↗

Data Centers and Digital Assurance Workshop 2 – Prioritizing Digital Assurance Challenges, Session 2

The second session of the TADA (Technical Assistance for Digital Assurance) Data Centers Cohort, held on November 10, 2025, focused on prioritizing digital assurance challenges at the intersection of data centers and the electric grid. Building on the foundational concepts introduced in Workshop 1, this session deepened the application of the Threat–Vulnerability–Consequence (TVC) framework and emphasized the urgency of addressing cybersecurity, supply chain integrity, and operational reliability. Participants explored the growing convergence of digital and physical systems, the expanding attack surface due to global supply chain dependencies, and the implications of AI-driven load behavior. Real-world incidents—including the Volt Typhoon campaign and vulnerabilities in Solarman and Deye platforms—were analyzed to illustrate the risks of unpatched systems, insecure APIs, and inadequate vendor oversight. Key themes included architecture and interface weaknesses, governance gaps, and human and procedural shortcomings. The workshop also examined the evolving regulatory landscape, highlighting new federal mandates around Foreign Entity of Concern (FEOC) compliance and large-load reliability standards. Through interactive exercises, stakeholders ranked and mapped digital assurance risks from their respective perspectives—utilities, operators, and vendors—laying the groundwork for mitigation strategies and shared accountability models to be developed in Workshop 3. Session 2 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Enabling Situation Awareness Under High Levels of Automation: Results From An Experimental Study

The Department of Energy’s Advanced Reactor Technologies (ART) program sponsors research, development and deployment activities through its Next Generation Nuclear Plant, Advanced Reactor Concepts, and Advanced Small Modular Reactor (aSMR) programs to promote safety, technical, economical, and environmental advancements of innovative Generation IV nuclear energy technologies. The Human Automation Collaboration (HAC) research project is located under the aSMR program, which identifies developing advanced instrumentation and controls and human-machine interfaces as one of four key research areas. New nuclear plants are expected to employ significantly more advanced technology than the systems in the current reactor fleet as well as utilize automation to a greater extent. However, advancing technology and increasing automation does not necessarily imply improved efficiency and safety of the plant. Instead, a number of concerns about how these technologies will affect human performance and the overall safety of the plant need to be addressed. More specifically, it is important to investigate how the operator and the automation work as a team to ensure effective and safe plant operation, also known as the human-automation collaboration (HAC). The HAC project at INL, investigates collaboration methods between a system’s automation and human operators and how that collaboration impacts the performance and reliability of overall system performance. Some well documented human performance issues associated with typical human automation collaboration methods include reduced operator situation awareness (SA), complacency, and over reliance on the system automation (Endsley, 1995, 1996, 1997; Endsley & Kaber, 1999; Kaber & Endsley, 1997, 2004; Parasuraman et al., 2000; Sheridan, 2002; Wickens & Hollands, 2000; Wright & Kaber, 2005). The HAC research effort addresses how to best design the collaboration between the operators and the automated systems in a manner that has the greatest positive impact on overall plant performance and reliability, hence addressing many of the documented issues. The ultimate goal of the HAC research effort is to develop design guidance that supports optimal interaction between humans and automated systems.

99 GENERAL AND MISCELLANEOUS↗