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At least 325 records · Page 18

An Oculometric Standard to Assess the Performance of the Ocular System for Long Duration Spaceflight

Changes in the human brain, due to spaceflight, have been a challenge to the space program since its inception; a challenge that is becoming more acute as extended International Space Station (ISS) missions become routine, a return to crewed lunar exploration is about to begin, and a multi-year crewed trip to Mars is being planned. Determining the extent to which neurophysiological adaptations may adversely impact performance in operational tasks, assessing the full-time course of these changes, and identifying/mitigating any potential long-term health consequences are crucial steps required to enable safe crew-autonomous, long-duration, deep-space missions. Vision is the predominant perceptual sense used to guide cognition and motor control in humans. Thus, it is critical for the success of any future, long-duration mission to understand how long-term exposure to microgravity and to other stressors of spaceflight and their interactions, impact visual function. This is an especially challenging task given the small and disparate samples from which we have been and will be able to collect human performance data. NASA has recently been carefully tracking spaceflight-induced ophthalmic changes, driven in large part by the fluid shifts related to microgravity. In particular, a recent study of Optical Coherence Tomography (OCT) postflight measures revealed that more than two-thirds of US crew members experience significant increases in retinal thickness after 6month or longer ISS missions. Space Associated Neuro-ocular Syndrome (SANS) also includes visual acuity decrements and other ocular structural changes that could adversely impact in-flight performance as missions become longer. However, the impact of spaceflight on the visual system is not limited to the retina. Recent comparisons of pre-and post-flight brain images have revealed structural changes throughout the brain that implicate visual, visuomotor, and visual-cognitive pathways, consistent with observed functional impacts (e.g., decreased speed/accuracy/timing of fine goal-oriented movements). Current limitations on inflight testing make it very difficult to determine when and under what conditions SANS and other disruptions of human neurological subsystems arise. Currently, one cannot anticipate the time course and extent of impairment and recovery. This study addresses this knowledge gap by creating an integrated framework of the relevant existing literature on visual and oculomotor function during spaceflight with an eye towards complementing current structural measures of visuomotor impairment with new oculometric standard measures. Using eye-movement based visual function assessment and diagnostics would provide a valuable enhancement of crew health and performance monitoring in support of deepspace exploration.

Vision↗

The Rapid Response Radiation Survey (R3S) Mission Using the HISat Conformal Satellite Architecture

The Rapid Response Radiation Survey (R3S) experiment, designed as a quick turnaround mission to make radiation measurements in LEO, will fly as a hosted payload in partnership with NovaWurks using their Hyper-integrated Satlet (HiSat) architecture. The need for the mission arises as the Nowcast of Atmospheric Ionization Radiation for Aviation Safety (NAIRAS) model moves from a research effort into an operational radiation assessment tool. The data collected by R3S, in addition to the complementary data from a NASA Langley Research Center (LaRC) atmospheric balloon mission entitled Radiation Dosimetry Experiment (RaDX), will validate exposure prediction capabilities of NAIRAS. This paper discusses the development of the R3S experiment as made possible by use of the HiSat architecture. The system design and operational modes of the experiment are described, as well as the experiment interfaces to the HiSat satellite via the user defined adapter (UDA) provided by NovaWurks. This paper outlines the steps taken by the project to execute the R3S mission in the 4 months of design, build, and test. Finally, description of the engineering process is provided, including the use of facilitated rapid/concurrent engineering sessions, the associated documentation, and the review process employed.

Miller, Nathanael↗

Specialized data analysis for the Space Shuttle Main Engine and diagnostic evaluation of advanced propulsion system components

The Marshall Space Flight Center is responsible for the development and management of advanced launch vehicle propulsion systems, including the Space Shuttle Main Engine (SSME), which is presently operational, and the Space Transportation Main Engine (STME) under development. The SSME's provide high performance within stringent constraints on size, weight, and reliability. Based on operational experience, continuous design improvement is in progress to enhance system durability and reliability. Specialized data analysis and interpretation is required in support of SSME and advanced propulsion system diagnostic evaluations. Comprehensive evaluation of the dynamic measurements obtained from test and flight operations is necessary to provide timely assessment of the vibrational characteristics indicating the operational status of turbomachinery and other critical engine components. Efficient performance of this effort is critical due to the significant impact of dynamic evaluation results on ground test and launch schedules, and requires direct familiarity with SSME and derivative systems, test data acquisition, and diagnostic software. Detailed analysis and evaluation of dynamic measurements obtained during SSME and advanced system ground test and flight operations was performed including analytical/statistical assessment of component dynamic behavior, and the development and implementation of analytical/statistical models to efficiently define nominal component dynamic characteristics, detect anomalous behavior, and assess machinery operational condition. In addition, the SSME and J-2 data will be applied to develop vibroacoustic environments for advanced propulsion system components, as required. This study will provide timely assessment of engine component operational status, identify probable causes of malfunction, and indicate feasible engineering solutions. This contract will be performed through accomplishment of negotiated task orders.

Source record↗

AI-Enabled Robots for Automated Nondestructive Evaluation and Repair of Power Plant Boilers. Final Report

Boiler failure could cause loss of life and safety issues, cost hundreds of thousands of dollars in equipment repairs, property damage and production losses, and drive up the cost of electric power. Boiler maintenance is challenging and risky for inspectors working on scaffolding in confined hazardous spaces inside of a boiler and sometimes the space is hard to access. The operation is also time-consuming due to the large area of vertical structures for inspection and the tremendous effort needed for scaffolding. Recently, the use of robotics (e.g., drones and crawlers) in power plants for maintenance is growing rapidly. However, the existing robotics solutions show two notable technological gaps: no live repair capability, and no Artificial Intelligence (AI) for smart autonomy. The objective of this project is to develop an integrated autonomous robotic platform that is equipped with compact non-destructive evaluation (NDE) sensors to perform live inspection, operates onboard repair devices to perform live repair, and uses AI for intelligent data fusion and predictive analysis for automated and smart spatiotemporal inspection, analysis and repair of the furnace walls in coal-fired boilers. The approach to achieve the objective includes developing NDE sensors with signal processing techniques, designing and evaluating repair devices for robots based on fusion and solid-state technologies, and an autonomous robotic platform that can attach to and navigate on boiler furnace walls using magnetic drive tracks. The robot is also powered by AI to automate data gathering (e.g., 3D mapping and damage localization) and predictive analysis. This project has advanced the state-of-the-art by providing technological breakthroughs including compact NDE and repair tools for robots, AI capabilities for smart autonomy, and a robotic platform for automated boiler maintenance. This project has great potential to result in significant benefits including limiting or eliminating the need to send operators to assess difficult-to-access or hazardous areas, enabling automated live inspection and repair, avoiding time consuming scaffolding (especially for partial maintenance during unplanned outage), collecting comprehensive and well-organized data smartly, and avoiding or limiting the need for onsite or remote piloting technicians. The impacts can be tremendous in terms of the time and cost savings, reducing the risk for human operators, and increasing boiler reliability, usability, and efficiency. In addition, by developing the new technologies on the autonomous inspection and repair robot, by involving multiple undergraduate and graduate students working together with the faculty members on this project, and by generating knowledge and building up collaborations with industrial partners, this effort will significantly update the education capabilities, support long-term fundamental research, and maintain the leadership of Colorado School of Mines and Michigan State University in energy fields.

20 FOSSIL-FUELED POWER PLANTS↗

Fuel Flow Modeling under Thermal Fluidics Considerations within Operational Domains of Molten Salt Reactors

Molten Salt Reactors (MSRs) offer significant versatility supported by their design flexibility and safety advantages due to high temperatures, design customization capabilities, strong negative reactivity feedback effects, and salt chemistry characteristics. Different control schedules and different mass flow rates in the MSR primary systems impact neutronics and thermal hydraulics coupling. The result is two-fold. First, it leads to adaptability in various applications when the customization of a MSR unit is desired. Second, it calls for the quantification of dynamics and safety characteristics to assess the operational domain and make sure reactor stability and inherent safety characteristics are maintained. This paper provides an in-depth transient analysis of the operational implications of MSRs having heat-generating fuel and heat-transporting salt mixed forming liquid fuel salts contained within primary systems. A coupling model was developed to simulate fuel flow in molten salt reactors. A zero-dimensional reactor kinetics model was used with a one-dimensional heat transfer model in the reactor core. The temperature reactivity feedbacks of the fuel salt resulting from the thermal-hydraulics model were used in the reactor kinetics model to complete the coupled code. The model was applied to simulate the Molten Salt Breeder Reactor (MSBR) response at steady state and transients. The developed model was shown to be a suitable tool for the dynamic analysis of molten salt reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Operational Use of Civil Space-Based Synthetic Aperture Radar (SAR)

Synthetic Aperture Radar (SAR) is a remote-sensing technology which uses the motion of the aircraft or spacecraft carrying the radar to synthesize an antenna aperture larger than the physical antenna to yield a high-spatial resolution imaging capability. SAR systems can thus obtain high-spatial resolution geophysical measurements of the Earth over wide surface areas, under all-weather, day/night conditions. This report was prepared to document the results of a six-month study by an Ad Hoc Interagency Working Group on the Operational Use of Civil (i.e., non-military) Space-based Synthetic Aperture Radar (SAR). The Assistant Administrator of NOAA for Satellite and Information Services convened this working group and chaired three meetings of the group over a six-month period. This action was taken in response to a request by the Associate Administrator of NASA for Mission to Planet Earth for an assessment of operational applications of SAR to be accomplished in parallel with a separate study requested of the Committee on Earth Studies of the Space Studies Board of the National Research Council on the scientific results of SAR research missions. The representatives of participating agencies are listed following the Preface. There was no formal charter for the working group or long term plans for future meetings. However, the working group may be reconstituted in the future as a coordination body for multiagency use of operational SAR systems.

Montgomery, Donald R.↗

An Investigation Into Transecting Satellites in Future Space Traffic Management Scenarios

The number of satellites expected to populate the near-Earth space environment is set to dramatically increase in the coming decade as new large constellations are approved and deployed. Current strategies for deploying new batches of these satellites often involve launching into an initial orbit, and then performing apogee raising maneuvers to reach a target altitude. Similarly, end-of-life planning for these constellation satellites can consist of de-orbit burns that lower perigee to permit disposal via re-entry. Both the raising and de-orbiting maneuvers can result in the individual satellites traveling in transecting orbits that have the potential to cross other spacecraft trajectories. While individual large constellations may be able to coexist in separate altitude and inclination bands, having thousands of satellites moving between these bands as new satellites are added and old satellites are removed could pose additional collision risks. Similar concerns have been raised regarding the impact that large numbers of university-class CubeSats might have in terms of their overall collision risk, especially as these satellites typically do not have propulsion systems for active maneuvering. To assess the impact that transecting satellites might have on future space traffic management strategies, this study explored a variety of realistic future scenarios using a high-fidelity simulation tool. The model can simulate the orbit of tens of thousands of resident space objects (RSOs) simultaneously, to include active satellites, debris, rocket bodies, or even future hypothetical satellite constellations, using a realistic force model that incorporates non-spherical gravity, atmospheric drag, and solar radiation pressure, as well as station-keeping. The simulation can be customized to accommodate different methods of calculating the probability of collision, as well as the process for determining probability ellipsoids and screening volumes. This makes it possible to replicate, and compare, different processes used by different spacecraft operators and space situational awareness (SSA) providers. As the model is run forward in time, each conjunction event is recorded, allowing for the analysis of statistics and meta-data related to these events, providing insight into the nature and frequency of potential collisions, such as whether are they active or passive objects, what size are the two objects, and who owns the objects (if known). This information makes it possible to characterize how changes to the status quo affect the number and type of conjunctions that occur, as well as the distributional effects on various types of satellite operators. To assess the general risks that transecting satellites might pose for hypothetical future space object environments, approximately 60,000 new large constellation satellites were considered, in addition to the existing catalog of approximately 7800 known resident space objects (RSOs), over a simulation period of one year. The results indicate that the future space environment will introduce a non-linear increase in conjunction events as the number of RSOs also increase. This will require adjustments to spacecraft fuel budgets in order to conduct the avoidance maneuvers necessary to minimize collision risk, both for existing and new satellites. This increase is due in large part to the higher density of RSOs and the overlap between some constellation orbits. Current catalog objects were shown to require three times more ∆V for collision avoidance (CA) maneuvers in the simulated future environment, and some constellation spacecraft were estimated to devote the majority of their annual ∆V to CA. The impact of small satellites was found to be proportional for the current space environment, and actually decreased in terms of percentage for the future scenario, suggesting that small satellites do not pose an outsized collision risk. Lastly, transecting satellites were found to contribute thousands of additional conjunctions outside of their operational orbit, and may require up to an additional 5% in CA maneuver fuel allocation.

conjunction assessment↗

A status report on the characterization of the microgravity environment of the International Space Station

A primary objective of the International Space Station is to provide a long-term quiescent environment for the conduct of scientific research for a variety of microgravity science disciplines. Since continuous human presence on the space station began in November 2000 through the end of Increment-6, over 1260 hours of crew time have been allocated to research. However, far more research time has been accumulated by experiments controlled on the ground. By the end of the time period covered by this paper (end of Increment-6), the total experiment hours performed on the station are well over 100,000 hours (Expedition 6 Press Kit: Station Begins Third Year of Human Occupation, Boeing/USA/NASA, October 25, 2002). This paper presents the results of the on-going effort by the Principal Investigator Microgravity Services project, at NASA Glenn Research Center, in Cleveland, Ohio, to characterize the microgravity environment of the International Space Station in order to keep the microgravity scientific community apprised of the reduced gravity environment provided by the station for the performance of space experiments. This paper focuses on the station microgravity environment for Increments 5 and 6. During that period over 580 Gbytes of acceleration data were collected, out of which over 34,790 hours were analyzed. The results presented in this paper are divided into two sections: quasi-steady and vibratory. For the quasi-steady analysis, over 7794 hours of acceleration data were analyzed, while over 27,000 hours were analyzed for the vibratory analysis. The results of the data analysis are presented in this paper in the form of a grand summary for the period under consideration. For the quasi-steady acceleration response, results are presented in the form of a 95% confidence interval for the station during "normal microgravity mode operations" for the following three attitudes: local vertical local horizontal, X-axis perpendicular to the orbit plane and the Russian torque equilibrium attitude. The same analysis was performed for the station during "non-microgravity mode operations" to assess the station quasi-steady acceleration environment over a long period of time. The same type of analysis was performed for the vibratory, but a 95th percentile benchmark was used, which shows the overall acceleration magnitude during Increments 5 and 6. The results, for both quasi-steady and vibratory acceleration response, show that the station is not yet meeting the microgravity requirements during the microgravity mode operations. However, it should be stressed that the requirements apply only at assembly complete, whereas the results presented below apply up to the station's configuration at the end of Increment-6. c2004 Elsevier Ltd. All rights reserved.

ISS Project↗

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

airport surface traffic↗

Potential of deep learning methods to enhance satellite-based monitoring of nuclear power plants focusing on remote operation evaluations

The anticipated expansion of the nuclear industry and the deployment of new nuclear reactors (200 + GW of new nuclear capacity by 2050) require the development of monitoring systems that align with safety and security concerns, providing enhanced evaluation capabilities. A remote monitoring system using satellites and deep learning techniques was evaluated for its ability to detect anomalies and capture various features of nuclear reactors independently of the conditions on the ground. Satellite images of current operational and under-construction nuclear power plants were collected from Google Earth Pro as a surrogate database. Subsequently, five datasets were created from the collected images. Transfer learning technique was used for several classification tasks utilizing VGG16, ResNet50V2, Xception, DenseNet121, and MobileNetV2 pre-trained models. In the first task, the capability of the monitoring system to detect abnormal conditions or processes in a nuclear power plant was investigated. In the second task, the ability to capture operational features remotely was examined. As an example, for the purposes of this study, these features included classifying reactors based on type, power range, or onsite condition. Several evaluation metrics were used to compare the performance of the pre-trained models and the overall monitoring system. Here, the evaluation results demonstrated that deep learning techniques and pre-trained models applied to satellite images have the potential to facilitate further and expand capabilities in monitoring systems to assess plant operation details.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Modified Universal Design Survey: Enhancing Operability of Launch Vehicle Ground Crew Worksites

Operability is a driving requirement for next generation space launch vehicles. Launch site ground operations include numerous operator tasks to prepare the vehicle for launch or to perform preflight maintenance. Ensuring that components requiring operator interaction at the launch site are designed for optimal human use is a high priority for operability. To promote operability, a Design Quality Evaluation Survey based on Universal Design framework was developed to support Human Factors Engineering (HFE) evaluation for NASA s launch vehicles. Universal Design per se is not a priority for launch vehicle processing however; applying principles of Universal Design will increase the probability of an error free and efficient design which promotes operability. The Design Quality Evaluation Survey incorporates and tailors the seven Universal Design Principles and adds new measures for Safety and Efficiency. Adapting an approach proven to measure Universal Design Performance in Product, each principle is associated with multiple performance measures which are rated with the degree to which the statement is true. The Design Quality Evaluation Survey was employed for several launch vehicle ground processing worksite analyses. The tool was found to be most useful for comparative judgments as opposed to an assessment of a single design option. It provided a useful piece of additional data when assessing possible operator interfaces or worksites for operability.

Blume, Jennifer L.↗

Workflow for Developing and Operating Subsurface Hydrogen Storage Facilities in Porous Reservoirs

Long-duration (seasonal) storage of natural gas (NG), which primarily consists of methane (CH 4 ), has been practiced for more than a hundred years at underground gas storage (UGS) facilities that use depleted hydrocarbon reservoirs, saline aquifers, and salt caverns. To enable hydrogen (H 2 ) to be used as a long-duration, energy-storage medium, similar facilities are envisioned for underground H 2 storage (UHS) of either H 2 or H 2 /NG mixtures. Experience with UGS can be used to guide recommended practices for developing and operating UHS facilities in porous reservoirs. The most important factors (formation/fluid properties and engineering choices) that influence the performance of UHS reservoirs have been identified and quantified in previous studies. These factors and choices influence phenomena that determine the sweep efficiency of the stored working gas. These phenomena include viscous fingering, hysteretic capillary trapping, and gravity override of the working gas, as well as the upconing of nonproductive fluid that determine the sweep efficiency of the stored working gas. This report describes initial recommended-practices and a project-development workflow for UHS facilities that utilize porous reservoirs, based on the current state-of-knowledge about H 2 behavior in the subsurface. The workflow sequentially addresses all aspects of UHS project development, including the identification of H 2 sources and users, site ranking and down-selection, geologic and reservoir-engineering characterization, reservoir design, testing, risk management, commissioning, operations, and monitoring for a UHS facility. The goal is to enable UHS facilities to be developed in an efficient and timely manner, while carefully managing project risks. This workflow is similar to that which has been developed for UGS facilities (see Figure 1 of API, 2022), with the addition of tasks and subtasks specific to H 2 and UHS. The project-development workflow is broken down into three major stages: (1) define the H 2 use case; (2) rank, down-select, and characterize potential, candidate UHS sites; and (3) reservoir design, integrity testing, risk assessment, commissioning, operations, and monitoring for selected UHS sites. Each major stage is further broken down into tasks and subtasks, which are described at a high level. This report also provides more detailed descriptions of all tasks and subtasks that involve reservoir analysis and testing.

08 HYDROGEN↗

Operational Collision Avoidance

This presentation will describe the early days of the EOS Aqua and Aura operational collision avoidance process. It will highlight EOS debris avoidance maneuvers, EOS high interest event statistic and A-Train systematic conjunctions and conclude with future challenges. This is related to earlier e-DAA (tracking number 21692) that an abstract was submitted to a different conference. Eric Moyer, ESMO Deputy Project Manager has reviewed and approved this presentation on May 6, 2015

collision avoidance↗

An Approach to Quantify Workload in a System of Agents

The role of humans in aviation and other domains continues to shift from manual control to automation monitoring. Studies have found that humans are often poorly suited for monitoring roles, and workload can easily spike in off-nominal situations. Current workload measurement tools, like NASA TLX, use human operators to assess their own workload after using a prototype system. Such measures are used late in the design process and can result in ex- pensive alterations when problems are discovered. Our goal in this work is to provide a quantitative workload measure for use early in the design process. We leverage research in human cognition to de ne metrics that can measure workload on belief-desire-intentions based multi-agent systems. These measures can alert designers to potential workload issues early in design. We demonstrate the utility of our approach by characterizing quantitative differences in the workload for a single pilot operations model compared to a traditional two pilot model.

Single Pilot Operations↗

A Gate-to-Gate Life Cycle Assessment for the CO 2 -EOR Operations at Farnsworth Unit (FWU)

Greenhouse gas (GHG) emissions related to the Farnsworth Unit’s (FWU) carbon dioxide enhanced oil recovery (CO 2 -EOR) operations were accounted for through a gate-to-gate life cycle assessment (LCA) for a period of about 10 years, since start of injection to 2020, and predictions of 18 additional years of the CO 2 -EOR operation were made. The CO 2 source for the FWU project has been 100% anthropogenically derived from the exhaust of an ethanol plant and a fertilizer plant. A cumulative amount of 5.25 × 106 tonnes of oil has been recovered through the injection of 1.64 × 106 tonnes of purchased CO 2 , of which 92% was stored during the 10-year period. An LCA analysis conducted on the various unit emissions of the FWU process yielded a net negative (positive storage) of 1.31 × 106 tonnes of CO 2 equivalent, representing 79% of purchased CO 2 . An optimized 18-year forecasted analysis estimated 86% storage of the forecasted 3.21 × 106 tonnes of purchased CO 2 with an equivalent 2.90 × 106 tonnes of crude oil produced by 2038. Major contributors to emissions were flaring/venting and energy usage for equipment. Improvements on the energy efficiency of equipment would reduce emissions further but this could be challenging. Improvement of injection capacity and elimination of venting/flaring or fugitive gas are methods more likely to be utilized for reducing net emissions and are the cases used for the optimized scenario in this work. This LCA illustrated the potential for the CO 2 -EOR operations in the FWU to store more CO 2 with minimal emissions.

54 ENVIRONMENTAL SCIENCES↗

Distributed Ledger Technology Preliminary Performance Assessment for Applications in Utilities Operational Technology

This paper provides descriptions of the key components of different distributed ledger technology platforms. Distributed ledger technology (DLT) allows for distribution of databases among different organizations and devices. The platforms use cryptographically linked “blocks” to store and verify transactional information between these organizations. DLT increases data security, data integrity, trust among its participants. Different organizations are looking to deploy this distributed and decentralized approach to avoid the single-point-of-failure vulnerabilities associated with centralized data repositories. In this study we examine twelve different DLT platforms. There is agreement within the community that of all the platforms considered here, Hyperledger and Ethereum are the most mature when it comes to privacy and permissions. These DLT platforms are being used for applications such as transactive energy, health care, and the food and goods supply chain. However, further development is required to realize the full promise of DLT. Our assessment includes a general description of each DLT and its key characteristics. Such characteristics include consensus protocol and cryptography used, public vs. private, and permissioned or permissionless. The selection and implementation of a DLT architecture depends heavily on the use case and performance requirements. During this research we found key parameters to measure performance and existing tools for assessment. Four different parameters were identified 1) consensus, 2) throughput, 3) latency, and 4) scalability. The architectures of Hyperledger Caliper and Blockbench are described as different performance assessment frameworks. From this preliminary study it is evident that there are dissimilarities on the performance assessments methods developers and users are characterizing DLT architectures. The purpose of this paper is to identify key parameters to test performance, tools that are being used and provide information on results from previous studies.

97 MATHEMATICS AND COMPUTING↗

Cybersecurity Resiliency of Marine Renewable Energy Systems Part 2: Cybersecurity Best Practices and Risk Management

Marine renewable energy (MRE) is an emerging source of power for marine applications, marine devices, and coastal communities. This energy source relies on industrial control systems and IT to support operations and maintenance activities, which create a pathway for an adversary to gain unauthorized access to systems and data and disrupt operations. Incorporating cybersecurity risk prevention measures and mitigation capabilities from inception, development, operation, to decommissioning of the MRE system and components is paramount to the protection of energy generation and the security of network architecture and infrastructure. To improve the resilience of MRE systems as a predictable, affordable, and reliable source of energy, cybersecurity guidance was developed to enable operators to assess cybersecurity risks and implement security measures commensurate with the risk. This publication is the second of a two-part series, with Part 1 addressing a framework to determine cybersecurity risk by assessing the vulnerability of an MRE system to potential cyber threats and the consequences a cyberattack would have on the end user. This Part 2 publication describes an approach to select appropriate cybersecurity best practices commensurate with the MRE system's cybersecurity risk. The guidance includes 86 cybersecurity best practices, which are associated with 36 cybersecurity domains and grouped into nine categories. The best practices follow the core functions of the National Institute of Science and Technology Cybersecurity Framework (e.g., identify, detect, protect, respond, and and recover) and insights from both maritime and energy industry guidance documents to identify security measures effective in protecting information and operational technology assets prevalent in MRE systems.

97 MATHEMATICS AND COMPUTING↗

CARA Risk Assessment Thresholds

Warning remediation threshold (Red threshold): Pc level at which warnings are issued, and active remediation considered and usually executed. Analysis threshold (Green to Yellow threshold): Pc level at which analysis of event is indicated, including seeking additional information if warranted. Post-remediation threshold: Pc level to which remediation maneuvers are sized in order to achieve event remediation and obviate any need for immediate follow-up maneuvers. Maneuver screening threshold: Pc compliance level for routine maneuver screenings (more demanding than regular Red threshold due to additional maneuver uncertainty).

conjunction↗