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At least 1,351 records · Page 75

ASCR Workshop on In Situ Data Management

In January 2019, the U.S. Department of Energy, Office of Science program in Advanced Scientific Computing Research, convened a workshop to identify priority research directions for in situ data management (ISDM). The workshop defined ISDM as the practices, capabilities, and procedures to control the organization of data and enable the coordination and communication among heterogeneous tasks, executing simultaneously in a high-performance computing system, cooperating toward a common objective. The workshop revealed two primary, interdependent motivations for processing and managing data in situ. The first motivation is that the in situ methodology enables scientific discovery from a broad range of data sources over a wide scale of computing platforms: leadership-class systems, clusters, clouds, workstations, and embedded devices at the edge. The successful development of ISDM capabilities will benefit real-time decision-making, design optimization, and data-driven scientific discovery. The second motivation is the need to decrease data volumes. ISDM can make critical contributions to managing large data volumes from computations and experiments to minimize data movement, save storage space, and boost resource efficiency, often while simultaneously increasing scientific precision.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Microreactor Automated Control System - Digital Twin Models and Advanced Control Systems Updates

Automation of control systems is expected to be important in the economic and safe operation of microreactors. Therefore, there is a need to develop and demonstrate automated control for microreactors, along with the development of testbeds for this purpose. This report provides updates on the status of a nonnuclear microreactor automated control system (MACS)—a real-time, hardware-in-the-loop testbed for non-nuclear testing of microreactor control system automation. A real-time hardware-in-the-loop testbed incorporates the realistic dynamics of physical systems into control system development and testing. The collaborative effort between Oak Ridge National Laboratory (ORNL) and Idaho National Laboratory (INL) resulted in the development of a prototypic microreactor plant-level digital twin that includes the reactor and a balance of plant system. Advanced control strategies were incorporated to demonstrate testing of control automation solutions. The gRPC communication protocol, which was implemented in the hardware-in-the-loop testbed by INL, was coupled to a digital twin model developed using the TRANsient Simulation Framework of Reconfigurable Models (TRANSFORM) library in Modelica. This digital twin simulation was tested with the ViBRANT hardware for realistic feedback and visual representation of control action in real time. A modular Python client structure was developed to manage functional mock-up unit-based simulation and real-time gRPC communication. Hardware-in-the-loop testing indicated that the modeled reactor—a natural-convection, molten-salt coolant loop configuration—responds well to control of drum positioning for modulation of reactor core power, as well as system-level control and downstream demand changes. Ongoing research is focused on integrating additional control algorithms that utilize data from newly included sensors within the MACS hardware testbed, as well as demonstrating and assessing the performance of the different automated control algorithms on multiple additional operational scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

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↗

Effects of social structure and management on risk of disease establishment in wild pigs

Contact heterogeneity among hosts determines invasion and spreading dynamics of infectious disease, thus its characterization is essential for identifying effective disease control strategies. Yet, little is known about the factors shaping contact networks in many 28 wildlife species and how wildlife management actions might affect contact networks. Wild pigs in North America are an invasive, socially-structured species that pose a health concern for domestic swine given their ability to transmit numerous devastating diseases 2 such as African swine fever (ASF). Using proximity loggers and GPS data from 48 wild pigs in Florida and South Carolina, USA, we employed a probabilistic framework to estimate weighted contact networks. We determined the effects of sex, social group, and spatial distribution (monthly home range overlap and distance) on wild pig contact. We also estimated the impacts of management-induced perturbations on contact and inferred their effects on ASF establishment in wild pigs with simulation. Social group membership was the primary factor influencing contacts. Between-group contacts depended primarily on space use characteristics, with fewer contacts among groups separated by >2 km and no contacts among groups >4 km apart within a month. Modeling ASF dynamics on the contact network demonstrated that indirect contacts resulting from baiting (a typical method of attracting wild pigs or game species to a site to enhance recreational hunting) increased the risk of disease establishment by ~33% relative to direct contact. Low-intensity population reduction (<5.9% of the population) had no detectable impact on contact structure but reduced predicted ASF establishment risk relative to no population reduction. Here, we demonstrate an approach for understanding the relative role of spatial, social, and individual-level characteristics in shaping contact networks and predicting their effects on disease establishment risk, thus providing insight for optimizing disease control in spatially- and socially-structured wildlife species.

59 BASIC BIOLOGICAL SCIENCES↗

A Data Science and Machine Learning Platform Supporting Large Particle Accelerator Control and Diagnostics Applications Final Report: SBIR Initial Phase II DE-SC0022583

The Machine Learning Data Platform (MLDP) is a product providing full-stack support for data science, Machine Learning, and Artificial Intelligence (ML/AI) applications at particle accelerator and large experimental physics facilities. It supports ML/AI applications from front-end, high-speed acquisition of heterogeneous, time-series data, through data archiving and management, to back-end analysis. The MLDP embodies a “data-science ready” platform for data analysis and ML/AI applications in diagnosis, modelling, control, and optimization of these facilities. It provides data scientists and applications a consistent, datacentric interface to archive data standardizing implementation and deployment of ML/AI algorithms to different operations configurations within the same facility, or between facilities. Being an open-source, public-domain project, the MLDP is intended for broadest possible impact by increasing accessibility and minimizing the required expertise for installation and operation. The MLDP can also be deployed at user facilities for experimental data collection, archiving, and analysis. It is capable of acquisition and archiving of heterogeneous data from experimental equipment (e.g., images, arrays, structures, etc.) along with system hardware configurations (e.g., scalars, tables), control system process variables, and any metadata required for provenance. Thus, the MLDP can manage experimental data through its entire lifecycle, from acquisition and archiving, through analysis and investigation, to release and final publication.

43 PARTICLE ACCELERATORS↗

Intelligent Load Control

Intelligent Load Control (ILC) is a PNNL-developed technology that enables buildings to manage energy consumption to a desired level. This video provides basic information about ILC and its applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Opdefender Network Monitoring And Control System

OpDefender is a new system designed to enhance the cyber security of control system networks. It accomplishes this by inspecting each network packet using a novel, patent-pending method that extends software defined networking into the application/ICS protocol layer. OpDefender consists of two key components: 1. Smart, “ICS-aware” network switches that analyze and filter network traffic in real time. 2. A network management human machine interface (HMI) that allows an operator to monitor and control network traffic in real time. The “ICS-aware” switches can serve as a drop-in replacement for typical network switches, or they can be used in conjunction with existing network switches. OpDefender is configured and controlled in real time via a custom-built, web-based HMI designed with the operator in mind.

Johnson, BriamE.↗

Python Display Manager Tutorial

PyDM is a PyQt-based framework for building user interfaces for control systems. The goal is to provide a no-code, drag-and-drop system to make simple screens, as well as a straightforward python framework to build complex applications.

Gibbs, Matt↗

Implementation and Evaluation of IEC 61850-based Distributed Control System for Microgrid Applications

This paper presents a resilient, modular and scalable distributed control architecture for microgrid systems which uses distributed agents controlling individual loads, network switches, generators or storage devices to provide intelligent power management and efficient microgrid operation. The communication between the distributed agents is realized by implementing IEC 61850 data models and GOOSE messages. The data models include state representation, measurements at various points, and dispatch requests for reliable operation of microgrid control system. System resiliency is enhanced through implementing distributed agent architecture with no single point of failure.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Monitoring and Documentation of Forest Management Activities at Los Alamos National Laboratory

Forest management treatments at Los Alamos National Laboratory (LANL) are administered by the Emergency Management Division (EMD-DO) Wildland Fire Program within the Wildland Fire and Forest Management Program (WFFM Program or the Program). Open space forest inventory monitoring is conducted by Forest Health Program staff and students within the Environmental Stewardship Group (EPC-ES). The goals of the integrated Wildland Fire and Forest Management Program are to reduce impacts to Laboratory operations from climate driven events by implementing forest management and healthy forest initiatives such as forest thinning and erosion control. The LANL Wildland Fire Mitigation and Forest Health Plan (EMD PLAN-200, LA-UR-19-25122; LANL 2019) presents treatment standards for LANL property to meet the following goals: 1) Restore and maintain landscapes: LANL landscapes are resilient to disturbances; 2) Develop a fire-adapted community: LANL workforce, neighbors, and infrastructure can withstand a wildland fire without loss of life and property; 3) Ensure wildland fire mitigation implementation: All wildland fire mitigation working group organizations participate in making and implementing safe, effective, efficient risk-based wildland fire management decisions.

54 ENVIRONMENTAL SCIENCES↗

Characterization of Medium- and Heavy-Duty Vehicle Operations from In-Use Data: An Analysis of Starts, Soak Time, and Warm-Up Duration

In recent years, advanced technologies for emission control have developed so significantly that exhaust emissions from hot-stabilized operation can be reduced to almost zero. Thereby, the emissions from cold operations contribute the most significant portion of the total emissions from a trip. As such, the Manufacturers of Emissions Controls Association (MECA) was interested in conducting a quantitative assessment of the engine cold-start operations for medium- and heavy-duty vehicles, using real-world operational data. In addition to providing valuable information to MECA, this study will also be valuable to engine manufacturers for developing more specific emission control technology strategies targeted on engine cold-start performance, fleet managers for determining more suitable driving cycles for their fleets to further reduce fuel cost and engine emissions and policymakers for gaining a better understanding of the real-world emissions impacts from cold-start operations.

33 ADVANCED PROPULSION SYSTEMS↗

How the Hydrophobic Interface between a Perfluorosulfonic Acid Polymer and Water Vapor Controls Membrane Hydration

Stable hydration in perfluorinated polyelectrolyte membranes such as Nafion is essential to maintain good ion conductivity and manage permeation, especially in vapor-fed devices where water content depends on relative humidity in a gas stream. Extensive studies in the literature have shown that Nafion hydration in water vapor is controlled by its interfacial transport resistance. Nafion forms a fluorine-rich layer at the polymer-gas interface, and it has been proposed that this layer blocks water transport due to its hydrophobicity. To develop a molecular-level description of the physics underlying transport resistance in this system, we have performed a computational reaction-diffusion kinetics study of water evaporation from Nafion. Two distinct models are examined, one mimicking the blocking function proposed in the literature and the other assuming that there is no blocking, treating instead water evaporation as a dynamic balance between uptake from the gas and desorption from the polymer surface. Simulation results are compared to time-dependent infrared data over a range of 100-0% relative humidity from the literature. Only the dynamic model successfully reproduces experimental observations. This indicates that the physical nature of interfacial transport resistance is not slow diffusion across an interfacial layer; rather, it is due to the competition between dehydration and rehydration. The simulation data provide details on the accompanying water distributions throughout the membrane and on interfacial kinetics, showing that they are characterized by strong fluctuations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nuclear Safety [Vol. 33, No. 1, January-March 1992]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 1 Technical Note: A New Approach to Fission Reactor Safety, Yu. V. Petrov; 5 Erratum; ACCIDENT ANALYSIS: 6 Analysis and Modeling of Fission Product Release from Various Uranium-Aluminum Plate-Type Reactor Fuels, R. P. Taleyarkhan; CONTROL AND INSTRUMENTATION: 23 Applications of a Surveillance and Diagnostics Methodology Using Neutron Noise From a Pressurized-Water Reactor, R. T. Wood, L. F. Miller, and R. B. Perez; DESIGN FEATURES: 36 Westinghouse Advanced Passive 600 Plant, B. A. McIntyre and R. K. Beck; 47 System 80+™ PWR Safety Design, C. W. Bagnal, R. A. Matzie, and R. S. Turk; ENVIRONMENTAL EFFECTS: 58 The MATS Experiments—Mesoscale Atmospheric Transport Studies at the Savannah River Site, A. H. Weber, S. Berman, R. J. Kurzeja, and R. P. Addis; 75 Book Review: Environmental Radioactivity in the European Community 1984-1985-1986, C. A. Little; WASTE AND SPENT FUEL MANAGEMENT: 76 Activities Related to Waste and Spent Fuel Management, M. D. Muhlheim and E. G. Silver; OPERATING EXPERIENCES: 87 Aging Assessment of BWR Control Rod Drive Systems, R. H. Greene; 100 Reactor Shutdown Experience, Compiled by J. W. Cletcher; 103 Selected Safety-Related Events, Compiled by G. A. Murphy; 110 Operating U.S. Power Reactors, Compiled by M. D. Muhlheim and E. G. Silver; RECENT DEVELOPMENTS: 129 General Administrative Activities, Compiled by M. D. Muhlheim and E. G. Silver; 139 Reports, Standards, and Safety Guides, D. S. Queener; 143 Proposed Rule Changes as of Sept. 30 1991; ANNOUNCEMENTS: 128 Harvard School of Public Health Announces Short Courses; 128 16th Biennial ANS Topical Meeting on Reactor Operating Experience: Present and Future Technologies—Applying Lessons Learned (Call for Papers); 147 The Authors; 150 Indexes to Nuclear Safety, Volume 32; 154 Errata.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Gd-cobalt selenite as an efficient nanocomposite for aniline synthesis from photocatalytic reduction of nitrobenzene

Highlights: • Gd-CoSeO{sub 3} nanocomposites were prepared via Sol- Gel method. • The effect of weight percent of Gd on the morphology of products were investigated. • 0.3 wt% Gd-CoSeO{sub 3} exhibited the highest catalytic activity for reduction of nitrobenzene under visible light. - Abstract: In this investigation, Gd-CoSeO{sub 3} nanocomposite with controlled Gd doping contents was synthesized using a sol gel method. The resultant specimen was found to have large specific surface area (115 m{sup 2}/g) and limited particle size (15 nm). TEM examination illustrated that the synthesized Gd-CoSeO{sub 3} nanocomposite exhibited nanospherical morphology. Also, it was revealed that band gap controlling of the CoSeO{sub 3} nanoparticles could be accomplished via managing the Gd contents. The photocatalytic activity of the Gd-CoSeO{sub 3} nanocomposite samples was inspected via Nitrobenzene – aniline transformation applying visible light irradiation. Gadolinium doping was adopted to improve the photo-catalytic of the synthesized CoSeO{sub 3}. This can be accredited to band gap decrease of CoSeO{sub 3} by Gd doping as well as life time increase of e-h recombination rate which occur via electron trapping by Gd metal. Therefore, we can prepare an efficient photocatalyst by sol- gel method and photoassisted deposition method to control band gap and e-h recombination rate.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Plug Load Management System Field Study

In 2018, NREL performed a demonstration of the IBIS InteliNetwork(TM) plug load management system, which includes: intelligent socket devices, which plug into existing electrical outlets and collect energy usage information; a gateway, which manages communication between the intelligent sockets and the PLM cloud service; and a PLM network, which is a cloud-based measurement and control network for the entire system. Two retail stores served as the field study sites. The PLM system was found to be effective at reducing plug load energy use, with a projected annual plug load reduction of 11% and 18% at the test locations. Retail staff reported that the hardware was easy to use, but no one used the online data management system, intended to analyze and control the hardware. This PLM solution shows promise as an effective means to monitor, control, and reduce plug load energy use, but the economics of the system need to be improved.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Reinforcement Learning-based Traffic Control to Optimize Energy Usage and Throughput (CRADA report)

The US roadways are critical to meeting the mobility and economic needs of the nation. The United States uses 28% of its energy in moving goods and people, with approximately 60% of that utilized by cars, light trucks, and motorcycles. Thus, improved transportation efficiency is vital to America’s economic progress. The increasing congestion and energy resource requirements of transportation systems for metropolitan areas require research in methods to improve and optimize control methods. Coordinating and optimizing traffic in urban areas may introduce hundreds of thousands of vehicles and traffic management systems, which can require high performance computing (HPC) resources to model and manage. In this work, we seek to use machine learning, computer vision, and HPC to improve the energy efficiency aspects of traffic control by leveraging GRIDSMART traffic cameras as sensors for adaptive traffic control, with a sensitivity to the fuel consumption characteristics of the traffic in the camera’s visual field. Traffic control use cases using reinforcement learning have been published and achieved good results. Surveys from DOE national laboratories estimate that the fuel cost of idling is 6 billion gallons wasted annually [Argonne National Laboratory, 2019]. GRIDSMART cameras—an existing, fielded commercial product—sense the presence of vehicles at intersections and replace more conventional sensors (such as inductive loops) to issue calls to traffic control. These cameras, which have horizon-to-horizon view, offer the potential for an improved view of the traffic environment which can be used to generate better control algorithms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

OIE Collaborating Centre for Biorisk Management Strategic Plan.

Due to efforts by individual nations and the international community to monitor and control natural occurring outbreaks of animal and zoonotic diseases, any number and variety of select agents and especially dangerous pathogens can be found at diagnostic laboratories around the world. Diagnostic testing is a crucial aspect of disease surveillance, but the organized collection and testing of diagnostic samples from the animal and human population at laboratories has created a repository of disease agents and toxins that could cause serious harm if released or acquired by nefarious means. The delicate balance between public health disease surveillance and the management of biorisks at facilities utilized in surveillance is a necessary goal of veterinary public health.

60 APPLIED LIFE SCIENCES↗

Transferring biodiversity-ecosystem function research to the management of ‘real-world’ ecosystems

Biodiversity-ecosystem functioning (BEF) research rose quickly following concerns that biodiversity loss would negatively affect ecosystem functions and the ecosystem services they underpin. However, despite evidence that biodiversity strongly affects ecosystem functioning, the influence of BEF research upon policy and the management of ‘real-world’ ecosystems, i.e., semi-natural habitats and agroecosystems, has been limited. In this work, we address this concern by classifying BEF research into three clusters based on the degree of human control over species composition and the spatial scale, in terms of grain, of the study, and discussing how the research of each cluster is best suited to inform particular fields of ecosystem management. Research in the first cluster, small-grain highly controlled studies, is best able to provide general insights into mechanisms and to inform the management of species-poor and highly managed systems such as croplands, plantations, and the restoration of heavily degraded ecosystems. Research from the second cluster, small-grain observational studies, and species removal and addition studies, may allow for direct predictions of the impacts of species loss in specific semi-natural ecosystems. Research in the third cluster, large-grain uncontrolled studies, may best inform landscape-scale management and national-scale policy. We discuss barriers to transfer within each cluster and suggest how new research and knowledge exchange mechanisms may overcome these challenges. To meet the potential for BEF research to address global challenges, we recommend transdisciplinary research that goes beyond these current clusters and considers the social-ecological context of the ecosystems in which BEF knowledge is generated. This requires recognizing the social and economic value of biodiversity for ecosystem services at scales, and in units, that matter to land managers and policy makers.

54 ENVIRONMENTAL SCIENCES↗