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At least 109 records · Page 6

Consequence Based Framework for Deployment of Cloud Solutions in the Digital Energy Transition

This study proposes a framework for evaluating cloud computing deployment in the electric sector, focusing on the digital transition of energy systems. It assesses the implications of cloud technology adoption, particularly in terms of security, operational resilience, and efficiency. The paper introduces a framework for consequence-driven applied risk analysis, enabling utilities to prioritize and mitigate potential threats effectively, and responsibly deploy cloud applications. It also discusses the shared responsibility model in cloud computing, highlighting the need for collaborative security efforts. The research aims to provide utilities with a strategic assessment tool for cloud adoption, emphasizing the importance of security culture in enhancing cloud computing's role in critical infrastructure.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Could a Kilonova Kill: A Threat Assessment

Abstract Binary neutron star mergers produce high-energy emissions from several physically different sources, including a gamma-ray burst (GRB) and its afterglow, a kilonova (KN), and, at late times, a remnant many parsecs in size. Ionizing radiation from these sources can be dangerous for life on Earth-like planets when located too close. Work to date has explored the substantial danger posed by the GRB to on-axis observers; here we focus instead on the potential threats posed to nearby off-axis observers. Our analysis is based largely on observations of the GW170817/GRB 170817A multi-messenger event, as well as theoretical predictions. For baseline KN parameters, we find that the X-ray emission from the afterglow may be lethal out to ∼1 pc and the off-axis gamma-ray emission may threaten a range out to ∼4 pc, whereas the greatest threat comes years after the explosion, from the cosmic rays accelerated by the KN blast, which can be lethal out to distances up to ∼11 pc. The distances quoted here are typical, but the values have significant uncertainties and depend on the viewing angle, ejected mass, and explosion energy in ways we quantify. Assessing the overall threat to Earth-like planets, KNe have a similar kill distance to supernovae, but are far less common. However, our results rely on the scant available KN data, and multi-messenger observations will clarify the danger posed by such events.

Astronomy & Astrophysics↗

Analysis of Surface Charging for a Candidate Solar Sail Mission Using Nascap-2k

The characterization of the electromagnetic interaction for a solar sail in the solar wind environment, and identification of viable charging mitigation strategies, is a critical solar sail mission design task, as spacecraft charging has important implications both for science applications and for sail lifetime. To that end, we have pexformed some preliminary surface charging calculations of a candidate 150 meter class solar sail spacecraft for the 0.5 AU solar polar orbit and a 1.0 AU L1 orbit. We construct a model of the spacecraft with candidate materials having appropriate electrical properties using Object Toolkit and perform the spacecraft charging analysis using Nascap-2k, the NASA/AFRL sponsored spacecraft charging analysis tool. We use mean and extreme solar wind environments appropriate for the 0.5 AU and 1.0 AU missions to establish current collection of solar wind ions and electrons. In addition, we include a geostationary orbit case to demonstrate a bounding example of extreme (negative) charging of a solar sail spacecraft in the geostationary orbit environment. Results from the charging analysis demonstrate that minimal differential potentials (and resulting threat of electrostatic discharge) occur when the spacecraft is constructed entirely of conducting materials, as expected. Examples with dielectric materials exposed to the space environment exhibit differential potentials ranging from a few volts to extreme potentials in the kilovolt range. Recommendations for further analyses include calculations of wake effects, surface current densities, and environments effects on conductivities.

Neergaard, Linda F.↗

Analysis Of Surface Charging For A Candidate Solar Sail Mission Using Nascap-2k

The characterization of the electromagnetic interaction for a solar sail in the solar wind environment, and identification of viable charging mitigation strategies, is a critical solar sail mission design task, as spacecraft charging has important implications both for science applications and for sail lifetime. To that end, we have performed surface charging calculations of a candidate 150-meter-class solar sail spacecraft for the 0.5 solar polar orbit and a 1.0 AU L1 orbit. We construct a model of the spacecraft with candidate materials having appropriate electrical properties using Object Toolkit and perform the spacecraft charging analysis using NASCAP-2k, the NASA/AFRL sponsored spacecraft charging analysis tool. We use nominal and atypical solar wind environments appropriate for the 0.5 AU and 1.0 AU missions to establish current collection of solar wind ions and electrons. In addition, we include a geostationary orbit case to demonstrate a bounding example of extreme (negative) charging of a solar sail spacecraft in the geostationary orbit environment. Results form the charging analysis demonstrate that minimal differential potentials (and resulting threat of electrostatic discharge) occur when the spacecraft is constructed entirely of conducting materials, as expected. Examples with dielectric materials exposed to the space environment exhibit differential potentials ranging from a few volts to extreme potentials in the kilovolt range.

Minow, Joseph↗

Analysis of Surface Charging for a Candidate Solar Sail Mission Using NASCAP-2K

The characterization of the electromagnetic interaction for a solar sail in the solar wind environment, and identification of viable charging mitigation strategies, is a critical solar sail mission design task, as spacecraft charging has important implications both for science applications and for sail lifetime. To that end, we have performed surface charging calculations of a candidate 150-meter-class solar sail spacecraft for the 0.5 AU solar polar orbit and a 1.0 AU L1 orbit. We construct a model of the spacecraft with candidate materials having appropriate electrical properties using Object Toolkit and perform the spacecraft charging analysis using NASCAP-2k, the NASA/AFRL sponsored spacecraft charging analysis tool. We use nominal and atypical solar wind environments appropriate for the 0.5 AU and 1.0 AU missions to establish current collection of solar wind ions and electrons. In addition, we include a geostationary orbit case to demonstrate a bounding example of extreme (negative) charging of a solar sail spacecraft in the geostationary orbit environment. Results from the charging analysis demonstrate that minimal differential potentials (and resulting threat of electrostatic discharge) occur when the spacecraft is constructed entirely of conducting materials, as expected. Examples with dielectric materials exposed to the space environment exhibit differential potentials ranging from a few volts to extreme potentials in the kilovolt range.

Parker, Linda Neergaard↗

Analysis of Lunar Surface Charging for a Candidate Spacecraft Using NASCAP-2K

The characterization of the electromagnetic interaction for a spacecraft in the lunar environment, and identification of viable charging mitigation strategies, is a critical lunar mission design task, as spacecraft charging has important implications both for science applications and for astronaut safety. To that end, we have performed surface charging calculations of a candidate lunar spacecraft for lunar orbiting and lunar landing missions. We construct a model of the spacecraft with candidate materials having appropriate electrical properties using Object Toolkit and perform the spacecraft charging analysis using Nascap-2k, the NASA/AFRL sponsored spacecraft charging analysis tool. We use nominal and atypical lunar environments appropriate for lunar orbiting and lunar landing missions to establish current collection of lunar ions and electrons. In addition, we include a geostationary orbit case to demonstrate a bounding example of extreme (negative) charging of a lunar spacecraft in the geostationary orbit environment. Results from the charging analysis demonstrate that minimal differential potentials (and resulting threat of electrostatic discharge) occur when the spacecraft is constructed entirely of conducting materials, as expected. We compare charging results to data taken during previous lunar orbiting or lunar flyby spacecraft missions.

Parker, Linda↗

Probabilistic Blast Damage Modeling Uncertainties and Sensitivities

Blast overpressure is the predominant source of ground damage posed by potentially hazardous asteroid strikes. Estimates of the extent, severity, and likelihoods of potential blast damage regions will be one of the key metrics needed to mount civil defense or disaster response plans in the face of an impending impact. However, there are many inherent sources of uncertainty in evaluating the damage, both in characterizing the properties of the incoming object and in the approaches used to model the entry/impact and resulting damage, which make it difficult to produce a single ‘accurate’ or ‘best guess’ prediction of ground damage. The current 2021 PDC hypothetical impact scenario poses a particular challenge due to its short warning time. The need for rapid disaster response to prepare for an immanent impact, combined with lack of observational opportunities to refine basic knowledge about the object’s basic size and properties, make understanding the range and relative likelihood of consequences particularly critical. The potential damage caused by these blasts can be evaluated using a range of modeling and simulation approaches and levels of fidelity. Fast-running engineering-level models can be used to run large numbers of probabilistically sampled cases covering wide variations of uncertain properties or parameters. High-fidelity simulations, on the other hand, can capture more detailed/accurate blast physics, but can only be performed for a small selection of specific cases, requiring many assumptions to be made about the initial object and its unpredictable entry/breakup characteristics. In order to provide a more complete picture of the potential threat for effective disaster response, both types of analysis need to be employed together. In this approach, high-fidelity simulations are used to refine and anchor engineering models, and the probabilistic engineering models are used to evaluate broad parameters spaces and guide selection of the most pertinent simulation cases for a given scenario. This presentation expands upon the probabilistic asteroid impact risk assessments being performed as part of the 2021 PDC hypothetical impact exercise, focusing on key aspects of blast damage modeling uncertainties and sensitivities. We review the current modeling and simulation approaches employed in the current assessment, compare the relative levels of uncertainty stemming from each main element of the problem (i.e., knowledge of the asteroid properties, modeling of the atmospheric entry/breakup and airburst, and estimates of the ground damage from the resulting blasts waves), and highlight any notable trends and sensitivities for the current scenario case.

SMD↗

A thermodynamic analysis of hypervelocity impacts on metals

Hypervelocity impacts on solid surfaces generate and propagate shock waves and create extreme density, pressure, and temperature conditions. Understanding hypervelocity impacts requires a multi-physics approach at the intersection of fluid dynamics, solid mechanics, and quantum theory, which has the capability of spanning multiple different dominating physics regimes. These strong shock conditions found in hypervelocity impacts are studied in the context of high-speed collisions between spacecraft and meteoroids and debris. We study the problem of hypervelocity impacts on metals with the lens of understanding the processes that lead to the creation of an impact generated plasma. In order to characterize the impacting particle as well as its threat to spacecraft from the subsequent radiating plasma an analysis was performed that highlights how the kinetic energy of the impactor is deposited into a target, how the shock wave and shocked material in the target evolve, and how these effects can lead towards the creation of an impact plasma through heating. The analysis suggests that at low velocities the majority of the energy from a hypervelocity impact is stored in reversible elastic energy and does not contribute to strong heating. At higher impact velocities, nucleus and electron thermal components dominate, increasing the energy available for ionization. Overall, this work provides the complete set of state variable initial conditions for any study of hypervelocity impact plasma expansion and its effects.

42 ENGINEERING↗

Analyzing Risks of Virtual Private Network Connections

The use of Splunk for analyzing VPN logs is an effective approach for identifying vulnerabilities in network endpoints. Splunk, a powerful platform for searching, monitoring, and analyzing machine-generated data, enables organizations to aggregate VPN logs in real-time, providing insights into network activity, user behavior, and potential security risks. By indexing VPN traffic and authentication logs, security teams can track abnormal patterns such as multiple failed login attempts, unusual IP addresses, or unexpected changes in bandwidth usage, all of which could indicate potential vulnerabilities or breaches. With Splunk’s advanced search and reporting capabilities, users can create custom dashboards and alerts to detect suspicious activities. Automated searches can flag endpoints exhibiting unusual behavior, while correlation analysis can identify links between compromised devices and broader network vulnerabilities. In particular, Splunk's machine learning capabilities can be leveraged to predict and prevent threats by identifying trends that might otherwise be missed in traditional log analysis. This proactive approach to monitoring VPN logs allows for the early detection of security weaknesses, enabling rapid response and minimizing potential damage to network integrity. By enhancing endpoint visibility, Splunk plays a crucial role in securing remote connections and safeguarding sensitive information. Additionally, Splunk’s automation and alerting features allow teams to create custom workflows that notify them of vulnerable or misconfigured endpoints identified through Shodan. This synergy between Splunk’s log analysis and Shodan’s device intelligence enhances an organization’s ability to proactively identify and mitigate security risks, improving the overall resilience of their VPN infrastructure.

97 MATHEMATICS AND COMPUTING↗

Quantitative Power System Resilience Metrics and Evaluation Approach

Power system resilience is an emerging topic and plays an essential role in helping the power industry understand and respond to the increasing threats of extreme weather events. The first step of power system resilience analysis is to introduce metrics to quantify the resilience reasonably. Existing resilience metrics are typically restrained by the limited data for extreme event modeling and fall short in terms of physical interpretation and comparability. This paper develops novel quantitative metrics to evaluate power system resilience in pre- and post-event contexts. The developed metrics illustrate clear physical meanings and can be effectively used to compare resilience across different systems under different extreme events. Moreover, the developed metrics can be applied to both transmission and distribution systems. Simulation on a distribution system is employed to validate the effectiveness of the proposed resilience metrics and resilience evaluation approach.

power system resilience↗

Cyber Security for the Spaceport Command and Control System: Vulnerability Management and Compliance Analysis

With the rapid development of the Internet, the number of malicious threats to organizations is continually increasing. In June of 2015, the United States Office of Personnel Management (OPM) had a data breach resulting in the compromise of millions of government employee records. The National Aeronautics and Space Administration (NASA) is not exempt from these attacks. Cyber security is becoming a critical facet to the discussion of moving forward with projects. The Spaceport Command and Control System (SCCS) project at the Kennedy Space Center (KSC) aims to develop the launch control system for the next generation launch vehicle in the coming decades. There are many ways to increase the security of the network it uses, from vulnerability management to ensuring operating system images are compliant with securely configured baselines recommended by the United States Government.

Cyber Security↗

Defensive Cybersecurity Architecture Design Using Force-on-Force Cyber-Physical Modeling

Currently, nuclear power plant physical security systems are highly dependent on air-gaps as a protective measure against cyber-threats. Cyber-physical threats become more likely as advanced cyber-threat capabilities to jump air-gaps transition into common use. Defending against the emerging threat of cyber-enabled physical intrusions is poorly understood. The consequence of these cyber-physical attacks has no quantitative analysis method to inform risk-informed, performance-based cybersecurity approaches. By modifying the physical security simulation tool Dante, cyber-physical threat consequence was able to be analyzed on a notional facility. The results of this analysis are used to design a Defensive Cybersecurity Architecture (DCSA) for the physical security system to produce example resilience measures for this notional facility. A DCSA defines security levels to provide a graded approach for defending plant functions, and security zones for trusted communication between systems. This approach can be applied to real world systems to produce physical protection systems and response measures that are resilient to cyber-physical threats.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Organizational strategies for protection against back contamination

The organizational issues pertaining to the prevention of inbound contamination associated with possible Viking missions to Mars are considered. The completed Apollo missions, which returned samples from the moon, provide a convenient base for analysis of inbound contamination issues. Despite concern over the threat of inbound contamination from the moon and efforts to prevent back contamination, the back contamination efforts in the Apollo missions were considered ineffective had these missions encountered living organisms. Several alternatives for consideration in the design of future programs dealing with back contamination are examined and proposed for special consideration.

Mahoney, T. A.↗

Design, Development, and Innovation of an Interactive Multimedia Training Simulator for Responding to Air Transportation Bomb Threats

This paper describes an interactive multimedia simulator for air transportation bomb threat training. The objective of this project is to improve the air transportation sector s capability to respond to bomb threats received by commercial airports and aircraft. The simulator provides realistic training on receiving and responding to a variety of bomb threats that might not otherwise be possible due to time, cost, or operational constraints. Validation analysis indicates that the use of the simulator resulted in statistically significant increases in individual ability to respond to these types of bomb threats.

Chung, Christopher A.↗

Portable Wireless LAN Device and Two-Way Radio Threat Assessment for Aircraft VHF Communication Radio Band

This document summarizes the safety analysis performed on a Flight Guidance System (FGS) requirements model. In particular, the safety properties desired of the FGS model are identified and the presence of the safety properties in the model is formally verified. Chapter 1 provides an introduction to the entire project, while Chapter 2 gives a brief overview of the problem domain, the nature of accidents, model based development, and the four-variable model. Chapter 3 outlines the approach. Chapter 4 presents the results of the traditional safety analysis techniques and illustrates how the hazardous conditions associated with the system trace into specific safety properties. Chapter 5 presents the results of the formal methods analysis technique model checking that was used to verify the presence of the safety properties in the requirements model. Finally, Chapter 6 summarizes the main conclusions of the study, first and foremost that model checking is a very effective verification technique to use on discrete models with reasonable state spaces. Additional supporting details are provided in the appendices.

Nguyen, Truong X.↗

PipeSight: A High-Performance Computing Platform for Pipeline Integrity Management

The Phase I feasibility study completed as part of this project has led to a number of innovative technologies being developed and has laid the foundation for a successful Phase II effort to commercialize a platform for managing the integrity of pipelines for the damage mechanisms of the new, hybrid-energy based economy. To ground the development efforts and direction of the project, an extensive market research and customer discovery effort was undertaken early in Phase I. Through this effort, a number of pipeline owners and operators were interviewed, and the following key findings were discovered about the pipeline industry: • Small pipeline operators do not have the central engineering groups necessary to perform their own independent analysis of inspection data, but instead rely on summarized tally sheets provided to them by inspection service providers. • The time it takes to go from an inspection to a completed engineering assessment, even for small segments of pipeline, can take anywhere from 30-120 days. During this delay, critical threats can (and have been known to) cause failures. • Uncertainty is often not accounted for in the assessment of pipeline integrity. The tally sheets provided by third-party service providers are almost always deterministic in nature, identifying threats that present a concern only to the current (not the future) integrity of the pipeline. • It is uncommon to apply the latest technologies to perform advanced assessments of damaged pipelines. There is a desire to use more advanced analysis capabilities to assess threats. Many pipeline operators indicated that they would often excavate a pipeline to perform an inspection and find that the damage was not as bad as they anticipated, thus using limited resources unnecessarily. Companies are not consistent in their use of inspection data to determine corrosion rates, and those that do only calculate deterministic corrosion rates. • The industry has prominently relied on time-based inspections but has recently started to transition to risk-based inspections. However, there appears to be no uniform guidance on how to do so while properly accounting for all sources of uncertainty. • Companies are not storing inspection data in a manner that allows for the ready determination of temporal trends. • Predictive maintenance principles and practices are beginning to be used by early adopters • Some pipelines are being re-purposed to transport different process fluids than they were designed for, e.g., H 2 and CO 2 rich process streams to serve the new hybrid-energy based economy, which are presenting new integrity concerns for the existing pipeline network that crisscrosses the United States. As a result of these discoveries, we were able to target the development efforts in Phase I to best serve the needs of the industry. In Phase I, we developed a way to correlate multiple large-scale scans of the pipeline to determine a probabilistic corrosion rate that accounts for all sources of error and uncertainty in the inspection process. This probabilistic corrosion rate can be used to predict the future thickness distribution of the pipe wall. We demonstrate how this analysis may be performed in an analytical fashion and has been implemented in such a manner that it can be readily distributed using GPU computing through integration of the Kokkos programming model. We also make a very novel extension of the analytical corrosion rate model to Bayesian Networks (an explainable AI technique) that can account for non-parametric distributions of corrosion rates. With the predictions made above for the probabilistic corrosion rate and corresponding future distribution of the pipe wall thickness, we can assess the integrity of the pipeline through the use of a probabilistic engineering assessment. We developed a novel screening data analysis approach that can rapidly identify ‘hotspots’ (local thin areas) where the integrity of the pipeline is a concern. Once more, we implemented this screening approach in C++ to leverage GPU computing via the Kokkos programming model. After the critical hotspots are identified, we developed a program that can automatically generate an advanced finite element model of the damaged regions. Since the number of damaged regions that require advanced analysis can number in the thousands, we integrated an open-source container-native workflow engine for orchestrating parallel jobs on the cloud. Initially, these advanced numerical models were only designed to account for loading due to internal pressure. However, in a slight pivot from the initial Phase I proposal, we developed a complete pipe stress analysis program (called Simflex) which can simulate the complete pipeline and its response to thermal expansion, pressure, thermal bowing, weight, wind, earthquake, support displacement, support friction and external forces. This pipe stress analysis program was written generically, to handle any piping system, but contains the features needed to model long pipelines (i.e., it incorporates a model for soil mechanics and can account for the nonlinear boundary conditions necessary to simulate long underground pipelines). This pipe stress analysis program can simulate any segment of the pipeline (simple or complex) under any set of conditions and loads, to determine the supplemental loads (axial forces and bending moments) at the location of damage. This enables the most accurate state of stress to be accounted for in the pipeline, which can prove critical when evaluating the integrity of a damaged region. In the process of developing the technologies to perform the integrity assessment of the pipeline, we also extended one of the industry standard approaches for performing the assessment of local thin areas that extend more in the circumferential direction than the longitudinal direction of the pipeline. This approach was presented to the API 579-1/AS ME FFS-1 steering committee in November 2021 for consideration in the next edition of the industry standard for Fitness-For-Service (expected to be released in 2023). To help pipeline operators make decisions with the results on any integrity assessment, we developed a new approach to the life-cycle management of pipelines which uses a Bayesian Decision Network. The network is designed to help pipeline operators plan and prioritize inspection activities and ultimately make smarter, more cost-effective decisions. The Bayesian approach accounts for all sources of uncertainty and carries them through to the final optimal decisions, providing a probabilistic framework for optimizing inspection intervals. The proof-of-concept networks developed in the feasibility study are complete, verified, and are focused on a subset of the pipeline. To expand this novel approach to the scale necessary for an entire network of pipelines in Phase II, we will leverage the DOE-funded Bengi solver for industrial-scale decision making with Bayesian Networks [22]. Once implemented, we will be able to provide the pipeline industry with a much-needed tool for optimal inspection planning using truly explainable artificial intelligence (XAI). To handle all of these advanced capabilities into a cloud-based platform, the architecture of the Equity Engineering Cloud (EEC) was extended to include Argo Workflows, a framework capable of distributing and managing a massive number of jobs that consume their own resources, such that thousands of serial finite element simulations can be run in parallel. As part of this substantial undertaking, we also integrated Argo Continuous Delivery (CD) into the EEC, to aid with the rapid prototyping and iterations that will be imperative to the success of the PipeSight platform’s Agile development process in Phase II. As part of the pipe stress analysis program, we also developed a custom visualizer that leverages the DOE-funded VTK visualization library. We added custom contouring capabilities and a means for interacting visually with both the inputs and outputs of the pipe stress analysis program. We also developed routines for automating the post-processing of the finite element simulations to determine if any failure criteria are met and to visualize the deformations, stresses and strains in ParaView using the exodus II file format (a subset of netCDF).

24 POWER TRANSMISSION AND DISTRIBUTION↗

Performing Numerical Analysis of Cybersecurity Options Using Dynamic Risk Analysis Tool EMRALD

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Considering a cyber threat should involve defense-in-depth methods and a quantitative or numerical evaluation of overall effectiveness against dynamic, time-dependent attacks to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related safety is a requirement set by North American Electric Reliability and the U.S. Nuclear Regulatory Commission. They are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks may focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want to know business reliability and recovery from those threats, and that requires modeling physical behavior of the targets. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with different tools having issues such as state-base explosion. Dynamic modeling enables time and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic numerical risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies. Keywords: cyber modeling; cyber-physical systems; numerical cyber modeling

97 - MATHEMATICS AND COMPUTING↗