Results for “task programming” — Page 54

DOE OSTI2024

Pressurized-Water Reactor Core Design using Multi-Objective Plant Fuel Reload Optimization Platform

The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program Risk-Informed Systems Analysis (RISA) Pathway Plant Reload Optimization Project aims to develop an integrated, comprehensive framework offering an all-in-one solution for reload evaluations with a special focus on optimization of core design. The optimization of the fuel loading pattern is one of the most important considerations in reducing the amount of new fuel used in the core. Due to thousands of possible options of core configuration, finding optimal solutions is an unachievable task for a human. The Plant ReLoad Optimization (PRLO) platform which supports artificial-intelligence-based reactor core designing is now fully capable of handling realistic problems. The PRLO Platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses and uses artificial intelligence to support the optimization of core design solutions. The NSGA-II (Non-dominated Sorting Genetic Algorithm-II) optimizer was developed and tested within RAVEN (Risk Analysis and Virtual Environment) to handle many constraints by using an augmented objectives methodology. The demonstration was performed with constrained multi-objective optimization of a 17 × 17 pressurized-water reactor core loading patterns to minimize fuel cost and maximize fuel cycle length.

42 ENGINEERING↗

DOE OSTI2015

GPFA-AB_Phase1UtilizationTask4DataUpload

This submission of Utilization Analysis data to the Geothermal Data Repository (GDR) node of the National Geothermal Data System (NGDS) is in support of Phase 1 Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (project DE-EE0006726). The submission includes data pertinent to the methods and results of an analysis of the Surface Levelized Cost of Heat (SLCOH) for US Census Bureau ‘Places’ within the study area. This was calculated using a modification of a program called GEOPHIRES, available at http://koenraadbeckers.net/geophires/index.php. The MATLAB modules used in conjunction with GEOPHIRES, the MATLAB data input file, the GEOPHIRES output data file, and an explanation of the software components have been provided. Results of the SLCOH analysis appear on 4 .png image files as mapped ‘risk’ of heat utilization. For each of the 4 image (.png) files, there is an accompanying georeferenced TIF (.tif) file by the same name. In addition to calculating SLCOH, this Task 4 also identified many sites that may be prospects for use of a geothermal district heating system, based on their size and industry, rather than on the SLCOH. An industry sorted listing of the sites (.xlsx) and a map of these sites plotted as a layer onto different iterations of maps combining the three geological risk factors (Thermal Quality, Natural Reservoir Quality, and Risk of Seismicity) has been provided. In addition to the 6 image (.png) files of the maps in this series, a shape (.shp) file and 7 associated files are included as well. Finally, supporting files (.pdf) describing the utilization analysis methodology and summarizing the anticipated permitting for a deep district heating system are supplied.

15 GEOTHERMAL ENERGY↗

DOE OSTI2015

Utilization Analysis in Low-Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB)

This submission of Utilization Analysis data to the Geothermal Data Repository (GDR) node of the National Geothermal Data System (NGDS) is in support of Phase 1 Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin. The submission includes data pertinent to the methods and results of an analysis of the Surface Levelized Cost of Heat (SLCOH) for US Census Bureau Places within the study area. This was calculated using a modification of a program called GEOPHIRES, available at http://koenraadbeckers.net/geophires/index.php. The MATLAB modules used in conjunction with GEOPHIRES, the MATLAB data input file, the GEOPHIRES output data file, and an explanation of the software components have been provided. Results of the SLCOH analysis appear on 4 .png image files as mapped risk of heat utilization. For each of the 4 image (.png) files, there is an accompanying georeferenced TIF (.tif) file by the same name. In addition to calculating SLCOH, this Task 4 also identified many sites that may be prospects for use of a geothermal district heating system, based on their size and industry, rather than on the SLCOH. An industry sorted listing of the sites (.xlsx) and a map of these sites plotted as a layer onto different iterations of maps combining the three geological risk factors (Thermal Quality, Natural Reservoir Quality, and Risk of Seismicity) has been provided. In addition to the 6 image (.png) files of the maps in this series, a shape (.shp) file and 7 associated files are included as well. Finally, supporting files (.pdf) describing the utilization analysis methodology and summarizing the anticipated permitting for a deep district heating system are supplied. UPDATE: Newer version of the Utilization Analysis has been added here: https://gdr.openei.org/submissions/878

15 GEOTHERMAL ENERGY↗

DOE OSTI2018

Tomographic Event Reconstruction with MicroBooNE Data

Event reconstruction is one of the most challenging tasks in analyzing the data from current and future massive single-phase liquid argon time projection chambers (LArTPCs). The performance of event reconstruction is critical to the potency of the eventual physics result. In this note, we describe a novel event reconstruction method, known as Wire-Cell tomographic imaging, applied to MicroBooNE data. MicroBooNE is an 85 metric ton single-phase LArTPC and the first of a trio of LArTPCs in the Short Baseline Neutrino (SBN) program. MicroBooNE’s principal aims are to understand the MiniBooNE low energy excess, measure neutrino-argon interaction cross sections, and improve the understanding and capability of single-phase LArTPCs through detector R&D.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Evaluation of Portable Acceleration Solutions for LArTPC Simulation Using Wire-Cell Toolkit

The Liquid Argon Time Projection Chamber (LArTPC) technology plays an essential role in many current and future neutrino experiments. Accurate and fast simulation is critical to developing efficient analysis algorithms and precise physics model projections. The speed of simulation becomes more important as Deep Learning algorithms are getting more widely used in LArTPC analysis and their training requires a large simulated dataset. Heterogeneous computing is an efficient way to delegate computationally intensive tasks to specialized hardware. However, as the landscape of compute accelerators quickly evolves, it becomes increasingly difficult to manually adapt the code to the latest hardware or software environments. A solution which is portable to multiple hardware architectures without substantially compromising performance would thus be very beneficial, especially for long-term projects such as the LArTPC simulations. In search of a portable, scalable and maintainable software solution for LArTPC simulations, we have started to explore high-level portable programming frameworks that support several hardware backends. In this paper, we present our experience porting the LArTPC simulation code in the Wire-Cell Toolkit to NVIDIA GPUs, first with the CUDA programming model and then with a portable library called Kokkos. Preliminary performance results on NVIDIA V100 GPUs and multi-core CPUs are presented, followed by a discussion of the factors affiecting the performance and plans for future improvements.

Yu, Haiwang↗

DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Optimizing Alabama’s CO 2 Storage in Shelby County (Project OASIS): Task 4.0 Deliverable – Geologic Analysis Report

Project OASIS (Optimizing Alabama’s CO 2 Storage in Shelby County) is a geologic and reservoir characterization study designed to evaluate deep saline formations for potential long-term carbon dioxide (CO 2 ) storage in central Alabama near the National Carbon Capture Center (NCCC) and Alabama Power’s Plant Gaston. The project centers on the Cambro-Ordovician Knox Group and underlying strata such as the Conasauga and Rome Formations, which were investigated through the drilling of two stratigraphic test wells to obtain electronic well logs, core, and sidewall core plugs. These data provide direct measurements of porosity, permeability, and lithologic variability critical for reservoir characterization. Complementing the well program, a limited 2D seismic survey was acquired to help select the site for Westover #2, and a more regional Seismic Exchange (SEI) seismic survey was licensed and interpreted to define structural and stratigraphic frameworks in a new Static Earth Model (SEM), map reservoir continuity, and identify potential sealing intervals. Integrated with geologic and reservoir modeling, these datasets form the basis for evaluating storage capacity, injectivity, and containment.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Reconfigurable perovskite nickelate electronics for artificial intelligence

Reconfigurable devices offer the ability to program electronic circuits on demand. Here, in this work, we demonstrated on-demand creation of artificial neurons, synapses, and memory capacitors in post-fabricated perovskite NdNiO 3 devices that can be simply reconfigured for a specific purpose by single-shot electric pulses. The sensitivity of electronic properties of perovskite nickelates to the local distribution of hydrogen ions enabled these results. With experimental data from our memory capacitors, simulation results of a reservoir computing framework showed excellent performance for tasks such as digit recognition and classification of electrocardiogram heartbeat activity. Using our reconfigurable artificial neurons and synapses, simulated dynamic networks outperformed static networks for incremental learning scenarios. The ability to fashion the building blocks of brain-inspired computers on demand opens up new directions in adaptive networks.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2016

PcapDB: Search Optimized Packet Capture, Version 0.1.0.0

PcapDB is a packet capture system designed to optimize the captured data for fast search in the typical (network incident response) use case. The technology involved in this software has been submitted via the IDEAS system and has been filed as a provisional patent. It includes the following primary components: capture: The capture component utilizes existing capture libraries to retrieve packets from network interfaces. Once retrieved the packets are passed to additional threads for sorting into flows and indexing. The sorted flows and indexes are passed to other threads so that they can be written to disk. These components are written in the C programming language. search: The search components provide a means to find relevant flows and the associated packets. A search query is parsed and represented as a search tree. Various search commands, written in C, are then used resolve this tree into a set of search results. The tree generation and search execution management components are written in python. interface: The PcapDB web interface is written in Python on the Django framework. It provides a series of pages, API's, and asynchronous tasks that allow the user to manage the capture system, perform searches, and retrieve results. Web page components are written in HTML,CSS and Javascript.

Ferrell, Paul↗

DOE OSTI2018

Development Plan for the MOX Fuel Fabrication Process

The Advanced Fuel Campaign (AFC) in Fuel Cycle Research and Development (FCRD) has tasks of near term Accident Tolerant Fuel (ATF) for light water reactor (LWR) and long term advanced reactor fuel research and development. Mixed Oxide (MOX) is one of the options for the advanced reactor fuel and development plan for the fabrication and characterization of MOX is described. The efforts will include the confirmation of the MOX fabrication capability and development of processing parameters for the stable fabrication of MOX fuel to support future MOX work if the need arises from the program. Establishing a robust fabrication process of desired stoichiometry utilizing the fabrication equipment recently added to Fuel Manufacturing Facility (FMF) glove box sintering furnace would be the main goal of the development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

PcapDB: Search Optimized Packet Capture, Version 0.1.0.0

PcapDB is a packet capture system designed to optimize the captured data for fast search in the typical (network incident response) use case. The technology involved in this software has been submitted via the IDEAS system and has been filed as a provisional patent. It includes the following primary components: capture: The capture component utilizes existing capture libraries to retrieve packets from network interfaces. Once retrieved the packets are passed to additional threads for sorting into flows and indexing. The sorted flows and indexes are passed to other threads so that they can be written to disk. These components are written in the C programming language. search: The search components provide a means to find relevant flows and the associated packets. A search query is parsed and represented as a search tree. Various search commands, written in C, are then used resolve this tree into a set of search results. The tree generation and search execution management components are written in python. interface: The PcapDB web interface is written in Python on the Django framework. It provides a series of pages, API's, and asynchronous tasks that allow the user to manage the capture system, perform searches, and retrieve results. Web page components are written in HTML,CSS and Javascript.

Ferrell, Paul↗

DOE OSTI2020

Remote Radiation Sensing Using Aerial and Ground Platforms

Remote sensing of ionizing radiation has a significant role in waste management, nuclear material management and nonproliferation, and radiation safety. Robotic platforms can surpass the number of tasks that are achieved by humans. With this technique, the operator's radiation exposure can be decreased. Remote sensing allows for the evaluation and monitoring of radiological contamination. Gamma-ray and neutron sensors were integrated onto the robotic platforms. This approach allows for the radiation sensor data to be dynamically tracked and mapped thus enabling further analysis of the radiation flux in temporal and spatial domains. The goal is to complete scheduled tasks while the robot is being irradiated. To achieve this, electronic components must be shielded and radiation hardened. CZT Detector: Cadmium Zinc Telluride (CZT) detector technology has been a promising solution for gamma-ray and x-ray measurements. Detector data is transferred to the Odroid minicomputer that controls and powers the module via the USB. Robot Operating System (ROS) was utilized for data acquisition and data fusion. The Mariscotti method was employed for the spectrum analysis. A function was programmed in ROS for the automatic identification of photopeaks. CLYC Detector: A Cs{sub 2}LiYCl{sub 6}:Ce{sup 3+} (CLYC) detector was used for simultaneous medium-resolution gamma-ray measurements and neutron counting. A 2.54 cm diameter photomultiplier tube (PMT) was equipped with a high voltage supply and a miniature digitizer. Gamma-ray excitation: fast core-to-valence luminescence (CVL) with 1 ns decay constant, and prompt Ce{sup 3+} emission with 50 ns decay constant. Neutron excitation: slow cerium self-trapped excitation (Ce{sup 3+} STE), 1000 ns decay constant. Radiation Source Localization: Maximum Likelihood Estimation (MLE) and gradient-based methods were used to locate the position of a radiation source based on measured radiation intensities. Multi-Particle Transport Code FLUKA: Estimation of radiation damage of the electronic components is important in order to optimize the robot's operational time while it is irradiated. Displacement per atom (DPA) represents the radiation damage in materials exposed to the ionizing radiation. Various shielding layers of different thickness t were analyzed (< 5% statistical error). The model of the controller of the UAS was designed in FLUKA. Conclusion: CZT and CLYC detectors were integrated onto the robotic platforms. Radiation source localization and contour mapping using robotic platforms were studied. Functions for data analysis and fusion were developed in ROS. FLUKA code was utilized to analyze DPA values. Layers of low-density and high-density materials were used to shield the UAS electronics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Multi-Mechanism Flood Hazard Assessment: Critical Review of Current Practice and Approaches

This report documents the initial findings from the Nuclear Regulatory commission (NRC)-sponsored research project Methods for Estimating Joint Probabilities of Coincident and Correlated Flooding Mechanisms for Nuclear Power Plant Flood Hazard Assessments.1 This research project is a part of NRC’s Probabilistic Flood Hazard Assessment (PFHA) Research Program and will aid the development of guidance on the use of PFHA methods to evaluate infrastructure safety for existing and proposed US nuclear power plants (NPPs). More specifically, this project intends to provide technical background for the development of flood hazard curves for multi-mechanism floods (MMFs). MMFs are flood events caused by more than one flooding mechanism (e.g., flood events due to the simultaneous occurrence of precipitation-induced river flooding and storm surge). Project activities include three main tasks: Task 1—Survey of current concepts and methods in assessing MMF hazards; Task 2—Critical assessment of selected methods and approaches for quantifying probabilistic MMF hazard risk; Task 3—Development of example case studies to illustrate best practices for quantifying probabilistic MMF hazard risk The initial findings from Tasks 1 and 2 are documented in this report. Task 1 comprised a survey of approaches and methods that have been applied to understand and assess flood hazards due to MMFs. Task 2 involved a critical review of the selected approaches and methods. To that end, the scope of this report includes documentation of (1) a reconnaissance-level survey of the current state of concepts and practice for MMF hazard assessment; (2) a generalized MMF assessment framework to address the distinctions among various types of flood-forcing phenomena, flood mechanisms (grouped into three mechanism types), and flood severity metrics; (3) a wide-ranging survey of approaches and methods that have been applied to various flooding phenomena and settings; and (4) a critical assessment of MMF hazard assessment methods. Studies were identified involving MMFs related to coastal flooding mechanisms, fluvial (rivers/streams) flooding mechanisms, and associated combinations of coastal and fluvial flooding mechanisms. Studies were also identified that address MMFs involving coastal and fluvial flooding mechanisms as well as coastal flooding mechanisms along with extreme precipitation (without specific attribution to fluvial or pluvial mechanisms). The studies identified for review in this report included assessments at varying spatial scales (from local to global) with differing geographic regions of focus using both observed and synthetic data. The majority of studies identified and reviewed were site-specific assessments focusing on relatively short return periods. Studies considered a range of flood severity metrics, made differing assumptions regarding the occurrence of extrema, and used multiple statistical techniques; the use of copulas for the development of joint distributions was a particularly popular analysis technique. The literature review highlighted the differences among existing studies relative to terminology used, means of presenting results, framework and techniques employed, and level of sophistication regarding the number and types of variables considered. Despite the significant diversity in existing studies, the review identified several promising techniques that will be considered in future work under this project, including the development of joint distributions for MMFs using copula and Bayesian-motivated approaches.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2018

Beyond Relaxation and Newton–Raphson: Solving AC OPF for Multi-Phase Systems With Renewables

This paper focuses on the AC Optimal Power Flow (OPF) problem for multi-phase systems. Particular emphasis is given to systems with high integration of renewables, where adjustments of the real and reactive output powers from renewable sources of energy are necessary in order to enforce voltage regulation. The AC OPF problem is known to be nonconvex (and, in fact, NP-hard). Convex relaxation techniques have been recently explored to solve the OPF task with reduced computational burden; however, sufficient conditions for tightness of these relaxations are only available for restricted classes of system topologies and problem setups. Identifying feasible power-flow solutions remains hard in more general problem formulations, especially in unbalanced multi-phase systems with renewables. To identify feasible and optimal AC OPF solutions in challenging scenarios where existing methods may fail, this paper leverages the Feasible Point Pursuit - Successive Convex Approximation algorithm - a powerful approach for general nonconvex quadratically constrained quadratic programs. The merits of the approach are illustrated using single- and multiphase distribution networks with renewables, as well as several transmission systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

Validating the simulation of large-scale parallel applications using statistical characteristics

Simulation is a widely adopted method to analyze and predict the performance of large-scale parallel applications. Validating the hardware model is highly important for complex simulations with a large number of parameters. Common practice involves calculating the percent error between the projected and the real execution time of a benchmark program. However, in a high-dimensional parameter space, this coarse-grained approach often suffers from parameter insensitivity, which may not be known a priori. Moreover, the traditional approach cannot be applied to the validation of software models, such as application skeletons used in online simulations. In this work, we present a methodology and a toolset for validating both hardware and software models by quantitatively comparing fine-grained statistical characteristics obtained from execution traces. Although statistical information has been used in tasks like performance optimization, this is the first attempt to apply it to simulation validation. Lastly, our experimental results show that the proposed evaluation approach offers significant improvement in fidelity when compared to evaluation using total execution time, and the proposed metrics serve as reliable criteria that progress toward automating the simulation tuning process.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

HSI Prototypes for Human Systems Simulation Laboratory

This report describes in detail the design and features of three Human System Interface (HSI) prototypes developed by the Institutt for Energiteknikk (IFE) in support of the U.S. Department of Energy’s Light Water Reactor Sustainability Program under Contract 128420 through Idaho National Laboratory (INL). The prototypes are implemented for the Generic Pressurized Water Reactor simulator and installed in the Human Systems Simulation Laboratory at INL. The three prototypes are: 1) Power Ramp display 2) RCS Heat-up and Cool-down display 3) Estimated time to limit display The power ramp display and the RCS heat-up/cool-down display are designed to provide good visual indications to the operators on how well they are performing their task compared to their target ramp/heat-up/cool-down rate. The estimated time to limit display is designed to help operators restore levels or pressures before automatic or required manual actions are activated.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

Evaluation of Roadmap to Achieve Energy Delivery Systems Cybersecurity

The Department of Energy/Office of Electricity Delivery and Energy Reliability (DOE/OE) Cybersecurity for Energy Delivery Systems (CEDS) program is currently evaluating the Roadmap to Achieve Energy Delivery Systems Cybersecurity document that sets a vision and outlines a set of milestones. The milestones are divided into five strategic focus areas that include: 1. Build a Culture of Security; 2. Assess and Monitor Risk; 3. Develop and Implement New Protective Measures to Reduce Risk; 4. Manage Incidents; and 5. Sustain Security Improvements. The most current version of the roadmap was last updated in September of 2016. Sandia National Laboratories (SNL) has been tasked with revisiting the roadmap to update the current state of energy delivery systems cybersecurity protections. SNL is currently working with previous and current partners to provide feedback on which of the roadmap milestones have been met and to identify any preexisting or new gaps that are not addressed by the roadmap. The specific focus areas SNL was asked to evaluate are: 1. Develop and Implement New Protective Measures to Reduce Risk and 2. Sustain Security Improvements. SNL has formed an Industry Advisory Board (IAB) to assist in answering these questions. The IAB consists of previous partners on past CEDS funded efforts as well as new collaborators that have unique insights into the current state of cybersecurity within energy delivery systems. The IAB includes asset owners, utilities and vendors of control systems. SNL will continue to maintain regular communications with the IAB to provide various perspectives on potential future updates to further improve the breadth of cybersecurity coverage of the roadmap.

24 POWER TRANSMISSION AND DISTRIBUTION↗