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DOE OSTI2021

Turbulence-driven flow dynamics in general axisymmetric toroidal geometry

The present work gives the equations governing the generation of toroidally axisymmetric flows by turbulent Reynolds and Maxwell stresses in finite aspect ratio, general cross section tokamak plasmas. Inclusion of the divergence-free flow constraint in lowest order changes the time scale for evolution of the poloidal flows driven by turbulence by substantial factors. In the pedestal region for present day machines, comparing to earlier cylindrical models, the time scale evaluated using a large aspect ratio circular cross section model can be two orders of magnitude longer while the present, general geometry result can be about one order of magnitude longer. Inclusion of gyroviscosity in the calculation shows that the only lowest order radial velocity fluctuations that enter the problem are those due to fluctuating E×B flows. Toroidal and poloidal flow effects on the toroidally axisymmetric flows are inextricably coupled due to the neoclassical poloidal viscosity. Accordingly, the physics is inherently three dimensional and measurements of all three velocity components are required to obtain the information needed to quantitatively test the theory. The parallel and angular momentum equations for the lowest order, toroidally axisymmetric flows look like radial transport equations when the turbulence is included. The turbulence terms provide the radial transport fluxes. In standard neoclassical theory, the parallel flow equation is local on each flux surface; there is no radial derivative term. However, adding turbulence gives a way, in principle, for radial transport to lead to poloidal flows that deviate from the neoclassical prediction. As a result, the inclusion of the Maxwell stress provides a mechanism for MHD fluctuations to alter the toroidally axisymmetric flows.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Moment extraction using an unfolding protocol without binning

Deconvolving (“unfolding”) detector distortions is a critical step in the comparison of cross-section measurements with theoretical predictions in particle and nuclear physics. However, most existing approaches require histogram binning while many theoretical predictions are at the level of statistical moments. We develop a new approach to directly unfold distribution moments as a function of another observable without having to first discretize the data. Our moment unfolding technique uses machine learning and is inspired by Boltzmann weight factors and generative adversarial networks (GANs). We demonstrate the performance of this approach using jet substructure measurements in collider physics. With this illustrative example, we find that our moment unfolding protocol is more precise than bin-based approaches and is as or more precise than completely unbinned methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

Topology-Aware Performance Optimization and Modeling of Adaptive Mesh Refinement Codes for Exascale

Here, we introduce a topology-aware performance optimization and modeling workflow for AMR simulation that includes two new modeling tools, ProgrAMR and Mota Mapper, which interface with the BoxLib AMR framework and the SSTmacro network simulator. ProgrAMR allows us to generate and model the execution of task dependency graphs from high-level specifications of AMR-based applications, which we demonstrate by analyzing two example AMR-based multigrid solvers with varying degrees of asynchrony. Mota Mapper generates multiobjective, network topology-aware box mappings, which we apply to optimize the data layout for the example multigrid solvers. While the sensitivity of these solvers to layout and execution strategy appears to be modest for balanced scenarios, the impact of better mapping algorithms can be significant when performance is highly constrained by network hop latency. Furthermore, we show that network latency in the multigrid bottom solve is the main contributing factor preventing good scaling on exascale-class machines.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

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↗

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

A structured data model frame for human factors application - 175

Building a Human Factors analysis and Verification and Validation case for new control rooms and even for control room modifications is a highly labor intensive project. Any optimization that can be made in the process translates into savings in the overall control room project schedule and budget. Several support tools from word, to excel, mind maps and databases have been traditionally used by human factors practitioners to conduct the analysis and document its results. While the use of these tools has had satisfactory results, they don't provide in our experience strong enough means for configuration control management, to avoid duplicities, streamline the analysis processes and allow collaborative team efforts. This paper documents how the established practices (methods, processes and tools) were questioned, which were the sources for comparison and how the results were translated into requirements for the new tool constituting the data frame model for Human Factors Engineering applications. The exercise has allowed us to evaluate the efficiency of our current practices in comparison to previous ones while improving our compliance with the quality assurance standards. (authors)

42 ENGINEERING↗

DOE OSTI2017

Development of NUREG-0700, rev 3 - 229

The U.S. Nuclear Regulatory Commission (NRC) evaluates the human factors engineering (HFE) of nuclear power plant design and operations to protect public health and safety. The HFE safety reviews encompass both the design process and its products. Detailed guidance for these reviews is provided in two key documents: the HFE Program Review Model (NUREG-0711) and the Human-System Interface Design Review Guidelines (NUREG-0700). The NRC is committed to the periodic update and improvement of the guidance to ensure that they remain state-of-the-art design evaluation tools. In this paper, we will describe the updates made to NUREG-0700 that resulted in Revision 3 of the guidance. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Human Factors Principles in Information Dashboard Design - 278

Refueling outages remain one of the largest opportunities for improving capacity factor and reducing costs available to commercial nuclear power plants. Although the nuclear industry has made steady improvement in outage optimization, each day of a refueling outage still represents an opportunity to save millions of dollars and each day an outage extends past its planned end date represents millions of dollars that may have been spent unnecessarily. Reducing planned outage duration or preventing outage extensions requires careful management of the outage schedule as well as constant oversight and monitoring of work completion during the outage execution. During a typical outage, there are typically more than 10,000 activities on the schedule that, if not managed efficiently, may cause expensive outage delays. Management of outages currently relies largely on paper-based resources and general-purpose office software. A typical method currently used to monitor work performance is a burn-down curve, where total remaining activities are plotted against the baseline schedule to track bulk work completion progress. While methods like this are useful, there is still considerable uncertainty during a typical outage whether bulk work progress is adequate and therefore a lot of management time is spent analyzing the situation on a daily basis. This paper is a case study of how new technology, in combination with established human-factors and user-centered design knowledge, can be used to support Outage Control Center (OCC) personnel decision making. In particular, we describe recent advances made in developing a framework for the design of visual outage information presentation, as well as an overview of the human factors principles that informed the development of the visualizations. To test the utility of advanced visual outage information presentation, an outage management dashboard software application was created as part of the Department of Energy's Advanced Outage Control Center project (AOCC). This dashboard is intended to present all the critical information an outage manager would need to understand the current status of a refueling outage. The dashboard presents the critical path, bulk work performance, key performance indicators, outage milestones and metrics relating current performance to historical performance. Additionally, the dashboard includes data analysis tools to allow outage managers to drill down into the underlying data to understand the drivers of the indicators. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Instrumentation, control, and human system interface contributions to historical severe accidents - 301

In 2015 EPRI completed a study of historical severe accidents. This study was intended to identify the lessons that these events had for instrumentation and control (I and C), and human systems interfaces (HSI) for nuclear power plants. The project studied 19 severe accidents that were identified by a parallel study that was underway for the International Atomic Energy Agency. I and C or HSI issues made significant contributions to 18 of the 19 events studied. This paper will summarize the I and C and HSI deficiencies that contributed to the propagation of the accidents, discuss the likely causes of these deficiencies and describe the role of I and C and HSI in finally terminating the events. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

A review of human-system interface design issues observed during analog-to-digital and digital-to-digital migrations in U.S. nuclear power plants - 312

The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program is developing a scientific basis through targeted research and development (R and D) to support the U.S. nuclear power plant (NPP) fleet in extending their existing licensing period and ensuring their long-term reliability, productivity, safety, and security. Over the last several years, human factors engineering (HFE) professionals at the Idaho National Laboratory (INL) have supported the LWRS Advanced Instrumentation, Information, and Control (II and C) System Technologies pathway across several U.S. commercial NPPs in analog-to-digital migrations (i.e., turbine control systems) and digital-to-digital migrations (i.e., Safety Parameter Display System). These efforts have included in-depth human factors evaluation of proposed human-system interface (HSI) design concepts against established U.S. Nuclear Regulatory Commission (NRC) design guidelines from NUREG-0700, Rev 2 to inform subsequent HSI design prior to transitioning into Verification and Validation. This paper discusses some of the overarching design issues observed from these past HFE evaluations. In addition, this work presents some observed challenges such as common tradeoffs utilities are likely to face when introducing new HSI technologies into NPP hybrid control rooms. The primary purpose of this work is to distill these observed design issues into general HSI design guidance that industry can use in early stages of HSI design. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Study on main control room and human-system interface of generation III in China - 313

This paper focuses on the study on Main Control Room (MCR) and Human-System Interface (HSI) of Generation III in China. An intelligent HSI has been developed to enhance the safety and availability of Nuclear Power Plant (NPP) by improving operational reliability. The key elements of the proposed HSI such as Advanced Alarm System, State Oriented Procedures (SOP), Large Display Panel (LDP), Computerized-base procedures..., that affects what information the operator sees or the system's response to a control input must be empirically evaluated to ensure that the new design does not compromise HSI effectiveness. Based on CPR1000's experience in China, this paper presents the approach used as well as the most relevant aspects of this kind of project for the next generation. This approach will be used in new Generation III nuclear power plant, and also used in modernizing I and C system in currently operative nuclear power plants, in addition to meeting safety requirements and the plant's operational requirements, to improve cost-effective plant and human performance and to reduce likelihood of human errors, to gain maximum benefit of the implemented technology and to increase the performance, resulting in improved plant safety, availability, reliability, and cost-effective operation. The proposed HSI has been validated and demonstrated using the CPR1000 simulator of National Key Laboratory. After sufficient validation, the characteristic design features of the proposed HSI will be reflected in the design of the main control room of the next generation reactors in China. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

Training and certification of human organizational factors designers in nuclear plant engineering - 344

Performing an increasing number of small and large-scope nuclear Human Factors Programs, AREVA NP is facing the challenging situation that (1) well-trained experts in Human Factors or Usability Engineering are currently hard to find and (2) newly hired ones need at least two years 'on the job' to become familiar with the nuclear field and the complexity of engineering Human Factors in this field. To innovatively meet this challenge we focus instead on company-internal engineers. Demonstrated nuclear engineering knowledge and skills and pronounced interest to extend both renders them optimal applicants to the AREVA NP two years Human Organizational Factors Training and Certification program. The AREVA NP training shall convey Human Factors knowledge and skills within the limited time of two years. We also stress the need to change participants' mindset from a technically-biased to a human-centered approach, committed to involve end-users throughout design. Next to psychology principles, user testing, user-centered design, plant operation principles, and the acquisition and documentation of users' requirements, design constraints, and inherent tradeoffs, participants will be trained to apply learned methods in a real environment and meet the challenges of real projects. The following sections provide insights in the training conception and preparation phase, the identification of appropriate candidates, the development of course syllabuses, and the schedule of lectures and tests. The promising experiences made thus far are reported as well. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Integrated Operations for Nuclear: Work Reduction Opportunity Demonstration

Integrated Operations for Nuclear: Work Reduction Opportunity Demonstration The DI BCA document also identifies specific, digitally enabled WRO categories for further study. These were selected as most relevant by Reference Plant personnel from a larger list of WRO areas identified across the nuclear industry as captured INL/RPT-21-64134, “Process for Significant Nuclear Work Function Innovation Based on Integrated Operations Concepts.” This ION WRO demonstration report was developed to provide illustrative, specific, and actionable direction for intertwined PTPG changes associated with digital modernization efforts. The coordinated changes in these areas are intended to maximize safe plant operational and economic performance. This includes enabling WROs associated with detailed configuration, implementation, and use of digital systems and how they are supported over their lifecycle. Illustrating this direction through a minimum set of advanced technology examples establishes a model PTPG framework that can be leveraged across the spectrum of nuclear plant digital modernization efforts going forward. This document addresses many related concepts. To promote an integrated understanding of the topics that make up this work, this document contains an extensive set of internal hyperlinks. This set includes hyperlinks to page numbers in the table of contents, section numbers, items in lists, figures, tables, and references to other documents within the report. When hovering the cursor above hyperlinked text in Adobe, the cursor will change from “ ” to “ .” When the “ ” appears, a left mouse click will take the reader to the referenced location in the document. To return to the original location in the document, the reader need only press and hold the “alt” button on the keyboard and then simultaneously press the “<” directional key on the keyboard.

42 ENGINEERING↗

DOE OSTI2016

HPSim, Version 1.0

HPSim is a GPU-accelerated online multi-particle beam dynamics simulation tool for ion linacs. It was originally developed for use on the Los Alamos 800-MeV proton linac. It is a “z-code” that contains typical linac beam transport elements. The linac RF-gap transformation utilizes transit-time-factors to calculate the beam acceleration therein. The space-charge effects are computed using the 2D SCHEFF (Space CHarge EFFect) algorithm, which calculates the radial and longitudinal space charge forces for cylindrically symmetric beam distributions. Other space- charge routines to be incorporated include the 3D PICNIC and a 3D Poisson solver. HPSim can simulate beam dynamics in drift tube linacs (DTLs) and coupled cavity linacs (CCLs). Elliptical superconducting cavity (SC) structures will also be incorporated into the code. The computational core of the code is written in C++ and accelerated using the NVIDIA CUDA technology. Users access the core code, which is wrapped in Python/C APIs, via Pythons scripts that enable ease-of-use and automation of the simulations. The overall linac description including the EPICS PV machine control parameters is kept in an SQLite database that also contains calibration and conversion factors required to transform the machine set points into model values used in the simulation.

Pang, Xiaoying↗

DOE OSTI2016

HPSim, Version 1.0

Pang, Xiaoying↗

DOE OSTI2024

Machine learning-guided design of direct methanol fuel cells with a platinum group metal-free cathode

Direct methanol fuel cells (DMFCs) offer a promising solution for clean electricity generation, particularly in small electronics and remote auxiliary power units. However, optimizing their efficiency and performance is challenging due to the complex interactions between various factors. Here, we present a novel approach that integrates experiments with machine learning to model and predict the performance of these fuel cells using atomically dispersed platinum group metal (PGM)-free catalysts at the cathode. Further, our machine learning models, trained on diverse input parameters, allow for the comprehensive optimization of DMFC performance prior to fabrication and testing. Through extensive experimental validation, we demonstrate that this data-driven approach accurately predicts key performance metrics, such as maximum power output and polarization curves. By combining our models with interpretable game-theory methods, we provide deep insights into the factors governing fuel cell performance, ultimately paving the way for the design of scalable and efficient DMFC technologies.

25 ENERGY STORAGE↗

DOE OSTI2026

Steady Spills, Stronger Signals: Machine Learning for Slow Spill Analysis

Particle accelerator experiments rely on stable, consistent proton beams to maximize scientific discovery. This presentation introduces beam spills, duty factor, and beam stability using a meteor shower analogy before exploring how feedback control and machine learning, including recurrent neural networks (RNNs), can analyze spill data, identify patterns, and predict beam behavior. Together, these approaches support beam optimization and improve our understanding of accelerator performance for experiments such as Mu2e.

Prescott, Matthew J. [Fermilab]↗

DOE OSTI2023

Machine-learning-based investigation of the variables affecting summertime lightning occurrence over the Southern Great Plains

Lightning is affected by many factors, many of which are not routinely measured, well understood, or accounted for in physical models. Several commonly used machine learning (ML) models have been applied to analyze the relationship between Atmospheric Radiation Measurement (ARM) data and lightning data from the Earth Networks Total Lightning Network (ENTLN) in order to identify important variables affecting lightning occurrence in the vicinity of the Southern Great Plains (SGP) ARM site during the summer months (June, July, August and September) of 2012 to 2020. Testing various ML models, we found that the random forest model is the best predictor among common classifiers. When convective clouds were detected, it predicts lightning occurrence with an accuracy of 76.9 % and an area under the curve (AUC) of 0.850. Using this model, we further ranked the variables in terms of their effectiveness in nowcasting lightning and identified geometric cloud thickness, rain rate and convective available potential energy (CAPE) as the most effective predictors. The contrast in meteorological variables between no-lightning and frequent-lightning periods was examined for hours with CAPE values conducive to thunderstorm formation. Besides the variables considered for the ML models, surface variables and mid-altitude variables (e.g., equivalent potential temperature and minimum equivalent potential temperature, respectively) have statistically significant contrasts between no-lightning and frequent-lightning hours. For example, the minimum equivalent potential temperature from 700 to 500 hPa is significantly lower during frequent-lightning hours compared with no-lightning hours. Finally, a notable positive relationship between the intracloud (IC) flash fraction and the square root of CAPE ($\sqrt{CAPE}$) was found, suggesting that stronger updrafts increase the height of the electrification zone, resulting in fewer flashes reaching the surface and consequently a greater IC flash fraction.

54 ENVIRONMENTAL SCIENCES↗