Guest Editorial: Special Section on Reliability, Resilience, and Prognostics Modeling of Complex Engineering Systems

Guest Editorial

Engineering systems are becoming increasingly complex.They need to meet advanced requirements, especially in mission-critical fields with a low failure tolerance.As unexpected failures during the designed lifespan of a system may lead to catastrophic consequences, their reliability modeling and assessment are of utmost importance.The reliability

Chapter 4 - Review on mechanical system reliability models

Cyberphysical system is the integration of physical space (equipment, devices and people) with computing, communication and control systems (cyberspace). The National Institute of Standards and Terminology (NIST) has defined CFS as cyberphysical systems (CFS), which are designed systems built on the continuous integration of computational algorithms and physical components. Improving the CFS provides greater opportunities for performance, adaptability, scalability, stability, security and usability, far exceeding today's simple embedded systems. CFS technology will transform the interaction of people with the engineering system [1, 2]. Today, cyberphysical systems exist in various fields, such as automotive, aerospace, civil, railway, medical. Large productions seek to increase the availability of the asset, while reducing maintenance costs through cyberphysical systems. With the development of the industry and the use of systems in production, the proposed maintenance is used constantly to avoid failures. CFS maintenance is performed when certain indicators signal that the condition of the system has deteriorated. One way to solve this problem is to provide systems with resistance properties. Such systems are able to recover quickly and continue to function in changing conditions [3-9]. Therefore, the urgent task is to develop approaches that will predict the resilience of cyberphysical systems based on cloud computing. It is necessary to build methods and tools that will monitor the condition of the CFS and predict the timely replacement of their components that may fail. The application of the process of predicting the resilience of cyberphysical systems using cloud-oriented increases the effective reliability and availability of cyberphysical systems in its life cycle by identifying future failures and reducing unscheduled maintenance. The forecasting process involves the assessment of the useful life, and the implementation of a post-forecast decision on maintenance measures in accordance with the rules. The method of predicting the resilience of cloud-oriented cyberphysical systems allows to determine the state of the cyberphysical systems using cloud computing. The mechanism used to reduce the cost of maintenance and detailed planning of maintenance operations, the apparatus of genetic algorithms.

An important aspect of modern engineering systems is their great diversity. Often they include interactions among different physical domains, contain control subsystems, and are large-scale and complex. The bond graph is a powerful and versatile tool that can help the engineer to design modern engineering systems. Three issues are explored from a bond graph perspective: modeling of engineering systems, simulation of their behavior, and teaching about engineering systems. It is the author’s observation that bond graph methodology is one of the most useful engineering system techniques available and belongs in the problem-solving tool kit of every mechanical engineer. This paper develops a rationale for this viewpoint both for readers familiar with bond graph methods and for readers to whom they are new.

As the risk associated with wildfires in the western United States increases every year, it becomes fundamental to research alternatives to both improve the resilience and reliability of engineering systems against those types of events, as well as mitigate the effects that wildfire emergencies may have on human population and critical infrastructure. An often- overlooked cause of wildfire emergencies are failures in power line systems and electricity distribution networks. Given the immense number of factors that can affect the probability of a power line ignition occurring, the analysis quickly becomes intractable for traditional probabilistic inference methodologies. In this paper, a quantum-enhanced probabilistic sampling and inference application is proposed for improving the acceptance ratio of queries of the form P(Q|E = e) when compared to traditional Monte-Carlo approaches. For this purpose, the system of interest is first modeled as a Bayesian network. Then, quantum computing is used to translate that Bayesian network into an equivalent quantum circuit using a set of basic quantum gates. Finally, the sampling process is enhanced by applying a quantum protocol called Amplitude Amplification to the resulting quantum circuit. Empirical results are presented using as a case study a non-trivial six-node Bayesian network.

<div class="section abstract"><div class="htmlview paragraph">A study of the cockpit information system architecture of current single-engine single-pilot aircraft was performed to establish a baseline for the evaluation of the reliability of new cockpit systems being developed through the Advanced General Aviation Transport Experiments (AGATE) program. That study defines a “typical” General Aviation (GA) cockpit information system architecture consisting of 38 components making up 32 subsystems. It also developed a reliability (fault tree) model for the system and utilized a proprietary analysis tool to compute system reliability.</div><div class="htmlview paragraph">Fault tree reliability models have gained wide acceptance since their introduction in the 1960’s to analyze the probability of success of military defense systems. Fault trees use logic gates to express the relationships between failures of the components and resulting failures of subsystems and of the system.</div><div class="htmlview paragraph">In a subsequent study an analytical model corresponding to the specific cockpit system reliability model was developed and implemented in a spreadsheet format. In addition to the system reliability equation, all of the subsystem reliability equations were also derived. From the analytic reliability model, the sensitivities of all of the subsystem and system reliabilities to changes in the component reliabilities were derived. These equations were also implemented in the spreadsheet tool. The resulting tool allows a user to modify the component reliability parameters and compute and display the system and subsystem reliabilities and the sensitivities of these reliabilities to changes in the component reliabilities.</div><div class="htmlview paragraph">This paper describes the single-engine single-pilot aircraft cockpit information system reliability model, explains the derivation of the analytical model for reliability and sensitivity computation, discusses the insight obtained from the analytical model, and presents the application of the spreadsheet tool.</div></div>

A general framework is proposed for cyber-physical system reliability modeling and evaluation considering some typical cyber attacks. The impacts of attacks from cyber space on physical space are analyzed, including the denial of service attack and deception attack. The cyber intrusion is modeled by a semi-Markov process, which decides the occurrence probability of cyber-attacks. The occurrence probability is related to the attacker level and defender level, therefore the cyber intrusion process is more practical and applicable for most attack situations. A case study on industrial heat exchanger system is provided to quantify the influences of cyber attacks on system performance and reliability. Some important conclusions are also drawn, which will be useful in designing resilient cyber-physical systems.

Coupling, as an important characteristic of cyber-physical systems (CPS), brings opportunities and challenges to the control and application of industrial systems. This article mainly analyses the role of the cyber layer in the process of controlling the physical layer and gives a security state assessment method for the CPS after the Denial-of-Service (DoS) attack. First, we develop an advanced CPS coupling model that intricately captures the interactions between the physical and cyber layers, emphasizing both data and topology coupling. Unlike existing models that often overlook these aspects, our model offers a more comprehensive understanding of the complex interdependencies within CPS. Second, we propose a unique method for partitioning network layer nodes based on the physical layer's control requirements. Unlike traditional approaches that treat network layer nodes as homogeneous, our method categorizes nodes into sensor, controller, and actuator areas, each with distinct roles in the control process. This differentiation ensures that data flow within the network layer follows a fixed and logical direction, enhancing the overall system efficiency and reliability. Third, we introduce a security state evaluation factor that leverages the network layer partitioning to assess the system's resilience under cyber-attacks. This evaluation provides a detailed analysis of the system's security status, ensuring that potential vulnerabilities are identified and mitigated. Together, these innovations contribute to a more robust and practical framework for CPS design and analysis, with significant implications for enhancing system security and performance in real-world applications.

This paper will explore the concept of resilience from its roots in ecology to the application of this ecological concept of resilience to social and community resilience in the context of climate change. In this context, resilience is seen as a property of complex adaptive communities rather than of individuals. This paper will explore how this ecological concept of resilience has been taken up both by climate adaptation research and by the Transition Town movement. This ecological concept of resilience is at odds with the individualism of both psychological and economic approaches to resilience in relation to climate change.

On the Probabilistic Characterization of Robustness and Resilience

In this paper, structural systems reliability analysis was used to estimate the system reliability of a typical semi-submersible based on the characteristic structure failure mechanisms under extreme wave loads. First, a three-dimensional simulation model was created for the chosen semi-submersible platform using an elastic-perfectly plastic material model, neglecting the effect of the strain hardening assumption. Then, under design wave conditions, and characteristic structural failure mechanisms of a semi-submersible platform were examined, and a system reliability model was developed based on the failure mechanism of the chosen platform. Finally, system reliability methods were used to determine the platform’s system reliability. It was discovered that the main node’s system reliability makes a significant contribution to the overall structure reliability, so it is strongly advised that the reliability of the main nodes be taken into account when determining the overall structure’s reliability. This research aims to apply reliability theory in offshore engineering and, ideally, to encourage the reliability-based design of semi-submersible platforms and other similar structures.

Purpose: The assessment of risks and prediction of reliability of complex engineering systems, in particular onshore gas pipelines subjected to external corrosion. Two methods are proposed using the structural reliability analysis.Methodology: Two strategies are considered for inspection and maintenance service of hazardous production facilities.Research findings: The model of structural reliability is proposed to estimate the metal rupture from external corrosion of the pipe section. Models are presented for its mechanical failure with respect to stochastic processes of loads and resistance.Value: The inhomogeneous Poisson point process is used to simulate the formation of new defects, and the Poisson distribution is used to simulate their growth. The first method focuses on the analysis of external corrosion of gas pipelines with metal loss and predicts rupture at a reference pipe segment, constructed with respect to average pipe rupture characteristics from the PHMSA database. The second model predicts reliability for untreated sections subject to external corrosion with metal loss.

Complex decision making is an important aspect in planning large man-made systems. These systems tend to be of high complexity, which requires an automated, intelligent approach to realize all dimensions of the problem. Decision Support Systems (DSS) are one approach to automate this process by providing modeling and analytical capabilities that assist users in making decisions. In this paper, we present the architecture of a web-based DSS platform for multidimensional modeling (including functional, spatial, and temporal dimensions) of complex engineering systems. We describe the breakdown of the modeling process of such systems in a multidimensional hierarchical manner. We present a case study for power planning in Saudi Arabia.

An approach to modeling and thermodynamic analysis of modern power engineering systemsThe new efficient method of modeling and thermodynamic analysis of power engineering systems has been presented. With its help a comparison of different structures and investigation of the influence of a particular constituent process onto the whole system efficiency is possible. The shaft work or the exergy is the main thermodynamic quantity taken into account in analyses, and the appropriate dimensionless modeling parameter has been introduced.