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Designing resilient engineered systems

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Abstract

The resiliency research to identify important characteristics of resiliency to assess and improve resilience systems to avoid failures and disastrous consequences is discussed. An important area of resiliency research involves self-healing materials, that ruptures the microcapsules after forming the crack and releases the healing agent into the crack. Shape-memory alloys (SMA) have been incorporated into material composites to allow the development of self-healing. Nanoparticles have been used in the development of self-healing composite materials, that form a barrier to further crack extension in case of cracks. The identification of dominant variables may assist in the development of correlations to describe a system's resilience.

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... Material resilience, in other words, is the extent to which energy may be stored in a material by elastic deformation (Nostrand [2]). Likewise, resilience of a process system can also be defined as the amount of energy the system can store before reaching its point of instability (Mitchell and Mannan [3]). System instability may be understood as inability of the system to perform efficiently at its targeted performance levels. ...
... Flexibility and resiliency of process systems were first described by Morari [4]. Designing of resilient engineered systems and its usefulness in the design were described by Mitchell and Mannan [3]. Guha and Das [5] recently reported that in an insulated pipe segment system which carries superheated steam as process fluid, magnitude of inherent system resilience decreases from 927.8 KJ/m 3 -sec to 43 KJ/m 3 -sec and 31.5 KJ/m 3 -sec for variation of mass flow rate, inlet pressure and inlet temperature respectively. ...
... As described above, system resilience can be defined as the amount of energy a system can store before reaching a point of instability (Mitchell and Mannan[3]). Mitchell and Mannan [3] also described that when there is a deviation in the input thermodynamic value, the absorbed exergy loads change. Moreover, like material resilience which can be visualized and quantified using a stress-strain diagram, similar diagrams for system resilience can be developed and used to evaluate resilience modulus (Ur) for a system. ...
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Resilience of a material is commonly understood as the ability of the material to absorb energy when deformed elastically and to return it when unloaded. However, in the domain of process systems, a formal definition and quantification of the magnitude of resilience is still elusive. The discussions and data provided in this paper illustrate that quantification of resilience for process systems is feasible and the quantitative model is aligned with fundamental concept of resilience. This paper provides general formulae for quantification of system resilience for many kinds of process systems. Based on the approach presented, it is possible to quantify resilience modulus, elastic modulus, and yield stress for an absorber column system. This work uses fundamentals of thermodynamic availability analysis for achieving this goal. It is found that resilience figure becomes considerably poor for increment of any operating variable from mid operating point visa -vis decrement of the same. Likewise a material, absorber system resilience modulus varies inversely with its modulus of elasticity. Additionally, a new efficiency parameter termed as " Thermodynamic Coefficient of Performance (THCOP) " has been conceived. Finally, an example is described detailing the procedure of incorporating 50% over capacity resiliency in the absorber by adding 4 new valve trays.
... Morari [5] first time described the flexibility and resiliency of process systems. Mitchell and Mannan [4] described the designing of resilient engineered systems and its usefulness in the design. Slocum [6] assessed system resilience for a known stress gradient, applied by introducing experimental disturbances and then measuring recovery rates. ...
... [9] identified the challenges in the procedure of building resilience or "adaptive capacity" of a chemical plant. Modulus of resilience U R may be expressed (Mitchell and Mannan [4]) as: ...
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A pipe segment system has been used to estimate its inherent resilience properties for the variation of mass flow rate, inlet temperature and inlet pressure. Superheated steam is taken as the process fluid. The magnitude of the resilience decreases from 927.8 kJ/m3s to 43 kJ/m3s and 31.5 kJ/m3s for variation of mass flow rate, inlet pressure and inlet temperature respectively. In this work, a novel methodology has been described for quantification of inherent system resilience and resilience magnitude has been found to be highest (927.8 kJ/m3s) in case of variation of mass flow rate through the pipe segment system. A useful correlation T = Ta(1-e-nL)+Tse-nL has been formulated for estimation of process fluid temperature, T at any pipe length, L.
... This study focuses on methods synergizing more than one of the methods involving NNs, FL, and GAs to capture the best features of the individual methods (Jang et al. 1997;Tsoukalas and Uhrig 1997;Nguyen et al. 2003;Karray and De Silva 2004;Konar 2005;Kasabov 2007;Sumathi et al. 2008). It further looks at the direction of developing an integrated structure by blending (see Ovaska et al. 2002) SC techniques and conventional hardcontrol or computing (HC) techniques comprising optimal control (Naidu 2003), model predictive control (Camacho and Bordons 2004), robust control (Sinha 2007), reconfigurable control (Benítez-Pérez 148 VOLUME 17, NUMBER 2, APRIL 2011 and García-Nocetti 2005; Isermann 2006), adaptive control (Ú ström and Wittenmark 1995), networked control (Wang and Liu 2008), and resilient control systems (Mitchell and Mannan 2006;Amin and Horowitz 2007;Hollnagel et al. 2008;Weiss 2010) with specific applications to HVAC&R systems. The integration of SC and HC methodologies, shown in Figure 1, has the following attractive features (see Ovaska et al. 2002;Tettamanzi and Tomassini 2001): ...
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A chronological overview of the advanced control strategies for HVAC&R is presented. The overview focuses on hard-computing or control techniques, such as proportional-integral-derivative, optimal, nonlinear, adaptive, and robust; soft-computing or control techniques, such as neural networks, fuzzy logic, genetic algorithms; and the fusion or hybrid of hard and soft control techniques. Part I focused on hard-control strategies; Part II focuses on soft and fusion control and some future directions in HVA&R research. This overview is not intended to be an exhaustive survey on this topic, and any omissions of other works is purely unintentional.
... Even though experimental disturbances provide important information about the system and can be used as resilience "probes" by evaluating the recovery rate, it should not be used as a sole evaluation of the stress caused on the system because it also depends on other factors. Mitchell and Mannan (2006) developed a concept of system resilience which was defined as "the amount of energy a system can store before reaching a point of instability". If the input thermodynamic values change, then, the absorbed exergy loads change. ...
... The broad concept of resilience has been investigated from several different perspectives (Bhamra, Dani, & Burnard, 2011; de Bruijne, Boin, & van Eeten, 2010; Ponis & Koronis, 2012). Research relating to resilience occurs within psychology (e.g., Coutu, 2002), ecology (e.g., Folke et al., 2010; Holling, 1996; Walker & Salt, 2006), organisation studies (e.g., Ates & Bititci, 2011; Sutcliffe & Vogus, 2003), supply chain management (e.g., Pettit, Fiksel, & Croxton, 2010; Ponis & Koronis, 2012), engineering (e.g., Mitchell & Mannan, 2006), IT (e.g., Almeida, Madeira, & Vieira, 2010; Back, Furniss, Hildebrandt, & Blandford, 2008), and safety (Hollnagel et al., 2008; Hollnagel et al., 2011; Nemeth, Hollnagel, & Dekker, 2009; Woods, 2006). The above research has focused on defining and characterising resilience and on identifying ways that resilience can be enhanced. ...
Conference Paper
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Modern industry is facing increasing internal and external complexity, performance pressures and technological and social change. In the last decade, much has been written about organisational resilience being an important attribute needed by industry to successfully manage the risks associated with modern industrial systems. To date, most of the resilience literature focuses on defining and describing the concept, with some articles providing insight into how organisations might measure, assess and build resilience in practice. There seems to be little focus on industry practitioners’ perspectives on organisational resilience. To address this gap we surveyed industry practitioners from both Australian and International companies to obtain their perceptions of organisational resilience. Our results show that most survey respondents thought that building organisational resilience is very important but their companies were not ‘very resilient’ because more needs to be done to help practitioners understand resilience and how to build it within industry.
... Resilience engineering, as a discipline, has been interpreted differently by different scientific communities. Various approaches and methods have been tailored to support applications in civil engineering problems [6], critical infrastructures [20], strength of materials [14], resilient control [9] [17], and resilient network systems [21] [16] [13]. Part of the underlying design philosophy is about understanding threats, mission uncertainty, fault occurrence, damage prediction and propagation modeling, as well as how systems must be designed to conform to dynamic effects, to withstand adversity and maintain mission effectiveness. ...
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The DoD's ERS initiative calls for affordable, effective, and adaptable systems development. In support of this, a metrics-based analysis framework is introduced to address certain challenges for the design of future C2 military System-of-Systems (SoS). The interpretation of the concept of resilience, as well as a supporting threat analysis procedure for military SoS applications, have been the key driver for the evaluation of a system's ability to maintain its mission capability and health, when under attack due to given threats. An agent-based C2 UAV communication network application has been developed for the demonstration of the framework. Scenario-based case studies that involved communication jamming by the adversary forces are introduced for the evaluation the C2 system's response to a threat, including both degradation and recovery periods.
... Operational normalcy corresponds to the maintenance of "stability and integrity of core processes" according to [62] and resilience is described by Wreathall [100] as the ability to "keep, or recover quickly to, a stable state". These definitions confirm the previous description as resilience focuses on some operational stability even if systems are supposed to "tolerate fluctuations via their structure, design parameters, control structure and control parameters" [63]. A new point highlighted by this definition is the need to collect and fusion data concerning the current state of the system. ...
Thesis
The property of resilience began to be studied in the fields of ecology and psychology before becoming of interest to researchers in economics, anthropology, civil infrastructure and more recently in computer science and information technology. Resilience is originally concerned with the survival and adaptation of a population to changes, but the case of infrastructures is different as survival may not be considered as an end goal but rather as a mean to another end: providing goods or services. Nevertheless, the protection of such infrastructures remains necessary and has long been accomplished in accordance with the paradigms of safety and dependability. However, these approaches require a detailed knowledge of the feared events that may affect the systems. Several events such as the accident at the Fukushima nuclear power plant or cyber-attacks such as StuxNet and BlackEnergy have highlighted several weaknesses in these paradigms.Research is therefore being conducted on the resilience of systems to address these weaknesses. The work presented in this thesis proposes a new model for assessing the resilience of a system by only having to detail its components and their relationships, whereas previous evaluation models focused on describing the threats and their impacts on the system.
... In the most classical significance, it is the physical property that characterises the capacity of any material to return to the original shape or position after deformation that has not exceeded its elastic limits (GarciaSerna et al., 2007). Following this definition, with regards to the process engineering, Mitchel andMannan (2006)have given to the term resilience a practical meaning: it is the energy limit of a disturbance that a system can absorb before becoming unstable. In analogy with these definitions, Steen and Aven (2011) have defined the concept of resilience as the probability of a system of succumbing to any negative event, and have formalized it as a function depending on different parameters such as safety barriers, consequences, uncertainty, incidental events. ...
Article
Resilience can be defined as the ability of a system to recover from any failure or disturbance. In this light, Resilience Engineering should be then devoted to the comprehension of the evolution of any system when losing its dynamic stability, due to the erosion of safety level. Recently, several authors have discussed over the significance and possibility of applying these concepts to industrial safety. In their view, any methodology for resilience differs from classical risk assessment as it depends on either known or unknown initiating-accident events. Or, resilience can be assumed as the ability of the industrial system to sustain required operational safety under both expected and unexpected conditions. This definition can be defined if holistic risk assessment is adopted. To this aim, however, due to the intrinsic complexity of the analysis, specific tools as System Dynamics (and Causal Loop Diagrams) are suggested for the quantitative evaluation of resilience of industrial systems. In this paper, this opportunity has been preliminary evaluated and the application for a simple storage plant of LPG is presented.
... For engineering systems Mitchell et al. [2006], the resilience has been studied mostly in the form of fault tolerant and/or robust control. Recently, a new discipline of resilient control has been investigated for uncertain dynamical systems Mahmoud [2004]. ...
Article
This work proposes the first steps for studying resilient control for uncertain hybrid systems. We take a rather radical approach and consider the situations of severe uncertainty. This requires the replacement of classical Kolmogorov probabilities with special concepts from the generalized measure theory. To achieve this goal, we need a rigorous and carefully developed mathematical framework, which constitutes the major contribution of this paper. Technically, the resilience framework of hybrid systems is defined in two steps. First, we introduce the contingent hybrid system that is a mathematical model where uncertainty is quantized using both probabilities and generalized measures. Then, the concept of lithe decision is introduced for this model. The new method combines decision theory with model predictive control and statistics for uncertainty measures.
... • Process Safety adapt, and grow in the face of unforeseen changes, even catastrophic incidents. With the increase in complexity of chemical plants and the increase in the difficulty of predicting potential failures, the desire to design systems resilient to potential faults has increased (135). Process resilience is the intrinsic ability of a system to adjust its functioning prior to, during, or following changes and disturbances, so that it can sustain required operations under both expected and unexpected conditions (136). ...
Article
The advent of the industrial revolution in the nineteenth century increased the volume and variety of manufactured goods and enriched the quality of life for society as a whole. However, industrialization was also accompanied by new manufacturing and complex processes that brought about the use of hazardous chemicals and difficult-to-control operating conditions. Moreover, human-process-equipment interaction plus on-the-job learning resulted in further undesirable outcomes and associated consequences. These problems gave rise to many catastrophic process safety incidents that resulted in thousands of fatalities and injuries, losses of property, and environmental damages. These events led eventually to the necessity for and gradual development of a new multidisciplinary field, referred to as process safety. From its inception in the early 1970s to the current state of the art, process safety has come to represent a wide array of issues, including safety culture, process safety management systems, process safety engineering, loss prevention, risk assessment, risk management, and inherently safer technology. Governments and academic/research organizations have kept pace with regulatory programs and research initiatives, respectively. Understanding how major incidents impact regulations and contribute to industrial and academic technology development provides a firm foundation to address new challenges, and to continue applying science and engineering to develop and implement programs to keep hazardous materials within containment. Here the most significant incidents in terms of their impact on regulations and the overall development of the field of process safety are described. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering Volume 7 is June 07, 2016. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.
... Except for contributions, which propose a generalized, yet heuristics-based approach on resilience assessment [9] other formulations have remained application-specific. Initiatives in civil engineering have been leading the evolution of resilience engineering, with proposed assessment frameworks on infrastructures [12], and strength of materials [13]. In other engineering domains, applications include resilient control, and resilient network systems, for instance communication networks, or air transportation systems [14]. ...
Conference Paper
System survivability is one of the key requirements for the conceptual design of an Integrated Reconfigurable Intelligent (IRIS) system. Current approaches in survivability engineering may not effectively address the challenges in designing revolutionary, large scale complex and multi-capable systems. The main objective of this study is to investigate the concept of resilience in the context of system safety and survivability and suggest a technique for assessing resilience in systems engineering. Resilience is expected to be the enabler for integrating safety and survivability in the early conceptual design. For this purpose, a small scale cooling network system architecture has been utilized to demonstrate the technique, both for a 32-valve baseline, as well as for six other configurations. The application of the technique allowed for the comparative assessment and tradeoff investigation of resilience function capacities, as well for the identification of solution feasibility, under adaptability and robustness constraints.
... An essential attribute of a resilient control system is graceful degradation of performance rather than a complete shutdown. It is notable that resilient control systems are those that tolerate fluctuations via their structure, design parameters, control structure and control parameters [11]. ...
Conference Paper
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This paper presents multi-agent based control of networked linear time invariant systems in a noisy environment. The control protocol is based on output information received from other subsystems through the communication channel, which imparts noise to the sensor data. We show that the sum of the mean square state errors between various subsystems converges to a small bound for the multi-agent system. It is apparent that a higher controller gain tends to make the networked system arrive at a consensus faster, while at the same time has the detrimental effect of enlarging the radius of consensus. Resilience of consensus is demonstrated in that the controller maintains collective stability in the event of communication or subsystem failures.
... In considering a definition of resilience, it has been suggested that "Resilient control systems are those that tolerate fluctuations via their structure, design parameters, control structure and control parameters [4]." While this definition is broad, it does not directly consider the presence and necessity of malicious actors. ...
Conference Paper
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Since digital control systems were introduced to the market more than 30 years ago, the operational efficiency and stability gained through their use have fueled our migration and ultimate dependence on them for the monitoring and control of critical infrastructure. While these systems have been designed for functionality and reliability, a hostile cyber environment and uncertainties in complex networks and human interactions have placed additional parameters on the design expectations for control systems.
... Resilient control systems (RCSs), which are a part of CPSs, are a new control design paradigm that considers all possible threats, namely, cyber and physical aspects. In [9], it is suggested that 'Resilient control systems are those that tolerate fluctuations via their structure, design parameters, control structure and control parameters', where the presence of malicious actors is not considered. Another definition refers to as 'an effective reconstitution of control under attack from intelligent adversaries', being the resiliency only defined in terms of response to intelligent actors. ...
... Creating a comprehensive model of interconnected, for example, socio-technical systems allows system administrators to identify weaknesses, plan countermeasures, correct errors, and prepare for complex heterogeneous threats in a comprehensive manner. Unlike a risk-based design that focuses on one component at a time, the resilience construction identifies critical system functions that are valuable to stakeholders (Mitchell and Sam Mannan (2006)). It also includes the development of customized methods and solutions to ensure that these functions are maintained within broad threats. ...
Article
This paper attempts to summarize information related to ensuring system resilience across disciplines. The first part outlines the reasons why the security in current systems is inadequate, generating the need to deepen the knowledge of the second generation of safety (Safety II). The authors also compare the views on safety from the perspectives of the current methods and resilience. Further, the paper also discusses the basic features required for a resilient system and presents the ideal definition of such a system. The final analysis then characterizes the methods to be applied in ensuring the resilience of industrial systems; importantly, this section also provides an example of how the current security scenarios can fail in high complexity systems. In this context, the demands on an industrial resilient control system are outlined, together with how the second generation safety approaches differ from the previously applied concept.
... The DHS definition is similar to the standard definition of resilience in control systems. Mitchell et al define resilient control systems as "those that tolerate fluctuations via their structure, design parameters, control structure, and control parameters" [5]. Other definitions in control system also talk about operating through failure by means of control designs, and evaluating the resiliency based on performance measures [6,7]. ...
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This study presents a tool to study the cyber-physical resiliency (CyPhyR) of critical energy infrastructure system, in particular the effect of cyber attacks on the microgrid's resiliency. The developed tool enables measuring resiliency using data from cyber and physical systems and suggests control decisions for resilient planning and operation of the microgrid. The microgrid resiliency is formulated based on graph theory based indices and cyber-power system characteristics. A Common Vulnerability Scoring System based metric called the Cyber Asset Impact Potential is developed and used in the planning phase, and another metric, Cyber Impact Severity is introduced to study the system performance in the operational phase. The information from these two phases is provided to the operator to make informed and proactive decisions to ensure the resilient operation of the microgrid. The performance of the developed tool has been tested using comprehensive real-time cyber-power testbed for a Consortium for Electric Reliability Technology Solutions microgrid test system.
... However, this response has not considered the multi-faceted, multidisciplinary nature of the problem. A need exists for resiliency in control systems [15]. ...
Conference Paper
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Digital control system technology has pervaded most industries, leading to improvements in the efficiency and reliability of the associated operations. However, the ease of distributing and connecting related control systems for the purposes of increasing performance has resulted in interdependencies that can lead to unexpected conditions. Even with less complex designs, operators and engineers alike are often left with competing goals that are difficult to resolve. A fundamental reason for this dichotomy is that responsibilities lie with different disciplines, and operations are hosted on separate control systems. In addition, with the rising awareness of cyber security and diverse human interactions with control systems, an understanding of human actions from a malicious and benevolent standpoint is necessary. Resilience considers the multiple facets of requirements that drive the performance of control systems in a holistic fashion, whether they are security or stability, stability or efficiency, human interactions or complex interdependencies. As will be shown by example, current research philosophies lack the depth or the focus on the control system application to satisfy these requirements, such as graceful degradation of hierarchical control while under cyber attack. A resilient control system promises to purposefully consider these diverse requirements, developing an adaptive capacity to complex events that can lead to failure of traditional control system designs.
... Operational normalcy corresponds to the maintenance of "stability and integrity of core processes" according to McDonald [17] and resilience was described by Wreathall [18] as the ability to "keep, or recover quickly to, a stable state". These definitions confirm the previous description as resilience focuses on some operational stability even if systems are supposed to "tolerate fluctuations via their structure, design parameters, control structure and control parameters" [19] . A new point highlighted by this definition is the need to collect and fusion data concerning the current state of the system. ...
... Operational normalcy corresponds to the maintenance of "stability and integrity of core processes" according to McDonald [17] and resilience was described by Wreathall [18] as the ability to "keep, or recover quickly to, a stable state". These definitions confirm the previous description as resilience focuses on some operational stability even if systems are supposed to "tolerate fluctuations via their structure, design parameters, control structure and control parameters" [19] . A new point highlighted by this definition is the need to collect and fusion data concerning the current state of the system. ...
Article
Aim: Resilience is discussed among researchers and practitioners for several decades, but its definition has been questioned even recently and many methods are proposed to evaluate the resilience of systems. This paper presents a review of historic and recent research articles that define and/or propose a way to measure resilience of systems. Methods: While definitions are classified according to the ideas they focus on, different categories of metrics are described, such as quantitative or qualitative approaches. Results: This paper points out that many metrics tend to valuate resilience similarly. In fact, they are generally built upon a specific definition. On the other hand metrics can also be really heterogeneous and do not capture the same meaning of system resilience when different definitions of resilience are considered. Conclusion: This paper aims at gathering and comparing metrics and definitions of resilience in order to determine the origins of the particularities and classify them according to the attributes they take into account.
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The paper presents the construction of a rolling robot able to move in the horizontal plane due to an original structure of a regular dodecahedron shape with twelve extending legs disposed in a radial manner in the centers of its faces. A mathematical model is developed and the robot functioning is simulated. Simulation results were validated by preliminary testing. A control algorithm developed by the authors takes advantage of the symmetric shape of the robot and allows recovering from perturbations, thus increasing the resilience of the robotic system.
Conference Paper
To monitor and control industrial machinery and processes, industrial control systems play an important role in daily life. Resilient control is a new topic of control technologies which studies how to maintain acceptable level of operation or service in face of undesirable incidents. This emerging technology, applied to industrial control systems, can provide a certain degree of protection for critical infrastructure, such as electric power generation, transmission and distribution, oil and gas production, water treatment. This paper proposes a 3-layer system model and resilience curve, discusses the concept and presents definition, properties and some insights of resilient industrial control systems. The metrics to estimate resilience quantitatively is disclosed. The general approaches to build, operate and improve a resilience industrial control system are proposed as well. Cyber attack resilient power grid automation system is discussed to illustrate the proposed approaches.
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The project supported the Nuclear Regulatory Commission (NRC) in identifying and evaluating the regulatory implications concerning the control and protection systems proposed for use in the Department of Energy's (DOE) Next-Generation Nuclear Plant (NGNP). The NGNP, using modular high-temperature gas-cooled reactor (HTGR) technology, is to provide commercial industries with electricity and high-temperature process heat for industrial processes such as hydrogen production. Process heat temperatures range from 700 to 950 C, and for the upper range of these operation temperatures, the modular HTGR is sometimes referred to as the Very High Temperature Reactor or VHTR. Initial NGNP designs are for operation in the lower temperature range. The defining safety characteristic of the modular HTGR is that its primary defense against serious accidents is to be achieved through its inherent properties of the fuel and core. Because of its strong negative temperature coefficient of reactivity and the capability of the fuel to withstand high temperatures, fast-acting active safety systems or prompt operator actions should not be required to prevent significant fuel failure and fission product release. The plant is designed such that its inherent features should provide adequate protection despite operational errors or equipment failure. Figure 1 shows an example modular HTGR layout (prismatic core version), where its inlet coolant enters the reactor vessel at the bottom, traversing up the sides to the top plenum, down-flow through an annular core, and exiting from the lower plenum (hot duct). This research provided NRC staff with (a) insights and knowledge about the control and protection systems for the NGNP and VHTR, (b) information on the technologies/approaches under consideration for use in the reactor and process heat applications, (c) guidelines for the design of highly integrated control rooms, (d) consideration for modeling of control and protection system designs for VHTR, and (e) input for developing the bases for possible new regulatory guidance to assist in the review of an NGNP license application. This NRC project also evaluated reactor and process heat application plant simulation models employed in the protection and control system designs for various plant operational modes and accidents, including providing information about the models themselves, and the appropriateness of the application of the models for control and protection system studies. A companion project for the NRC focused on the potential for new instrumentation that would be unique to modular HTGRs, as compared to light-water reactors (LWRs), due to both the higher temperature ranges and the inherent safety features.
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This paper proposes an approach to quantify the concept of resiliency in terms of Quality of Control (QoC) of a control system. Based on this concept, an intelligent resilient control algorithm (RCA) is presented for wireless networked control systems (WNCS) to maintain operational normalcy in face of wireless interference incidents, such as Radio Frequency (RF) jamming and signal blocking. The proposed algorithm closes the control loop with wireless sensors feasible by significantly increasing control system’s tolerance to data packet loss and delay caused by wireless interference. The proposed algorithm, along with other well developed wireless technologies, has the potential to enable implementing wireless sensors widely in the next generation of industrial automation and control systems. KeywordsResilient control–NCS–wireless interference–wireless sensors
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Oil and gas facilities used in the petroleum industry can be considered as complex dynamic systems in that they require different types of equipment with various causal relationships among components and process variables under monitoring. As the systems grow increasingly large, high speed, automated and intelligent, the nonlinear relations among these process variables and their effects on accidents are to be fully understood for both system reliability and safety assurance. Failures that occur during the process can both cause tremendous loss to the petroleum industry and compromise product quality and affect the environment. Therefore, failures should be detected as soon as possible, and the root causes need to be identified so that corrections can be made in time to avoid further loss, which relate to the safety prognostic technology. By investigation of the relationship of accident causing factors in complex systems, new progress into diagnosis and prognostic technology from international research institutions is reviewed, and research highlights from China University of Petroleum (Beijing) in this area are also presented. By analyzing the present domestic and overseas research situations, the current problems and future directions in the fundamental research and engineering applications are proposed.
Conference Paper
This paper presents multi-agent based control of networked systems in the presence of environmental noise. The subsystems are assumed to be linear time invariant with Gaussian white noise appearing as an exogenous input. The control protocol is based on output information received from other subsystems through the communication channel. We show that the multi-agent system arrives at a collective weak consensus in the sense that the sum of the mean square state errors between various subsystems converges to a small bound. Resilience is demonstrated in that the controller maintains collective stability in the event of communication or subsystem failures, with a degradation of performance. Simulation results are presented to illustrate the methodology.
Conference Paper
This paper presents consensus control of a system of multi-agent systems represented as an interconnection of platoons. The agents in each platoon are interconnected through their own communication network while only the platoon leaders are connected to global system level leader network. It is assumed that all agents are identical and are linear time invariant. For consensus control, we assume a two stage protocol: an intra-platoon protocol for platoon consensus, and an inter-platoon protocol for global system-wide consensus. The intra-platoon control is based on output information received from agents within the platoon while the inter-platoon control uses only output information of platoon leaders. We show that the system of multi-agent systems arrives at a collective consensus in the sense that each platoon arrives its own platoon consensus and at the same time all platoons collectively achieve global system-wide consensus. Simulation results are presented to illustrate the methodology.
Conference Paper
Resilience engineering is a recent paradigm for the development, analysis and control of systems that interact with their environment and are subject to perturbances or part failures. Resilience engineering has many facets, some of them being well studied in control engineering like fault tolerance or robust control. In this paper, we propose a mathematical model that considers the following aspects relevant to resilience engineering: uncertainty, autonomy, and system-environment interaction. The model extends stochastic hybrid systems with Markov decision processes to capture system autonomy, and game theory to capture the system-environment interaction. For this model, we consider the state-constrained reachability problem as defined for stochastic hybrid systems. We give a characterization of the solutions of this problem in terms of the value function of an ergodic stochastic game.
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This article analyzes the properties of unknown faults in knowledge management and Big Data systems processing Big Data in real-time. These faults introduce risks and threaten the knowledge pyramid and decisions based on knowledge gleaned from volumes of complex data. The authors hypothesize that not yet encountered faults may require fault handling, an analytic model, and an architectural framework to assess and manage the faults and mitigate the risks of correlating or integrating otherwise uncorrelated Big Data, and to ensure the source pedigree, quality, set integrity, freshness, and validity of the data. New architectures, methods, and tools for handling and analyzing Big Data systems functioning in real-time will contribute to organizational knowledge and performance. System designs must mitigate faults resulting from real-time streaming processes while ensuring that variables such as synchronization, redundancy, and latency are addressed. This article concludes that with improved designs, real-time Big Data systems may continuously deliver the value of streaming Big Data. Copyright © 2018, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Chapter
Processing big data in real time creates threats to the validity of the knowledge produced. This chapter discusses problems that may occur within the real-time data and the risks to the knowledge pyramid and decisions made based upon the knowledge gleaned from the volumes of data processed in real-time environments. The authors hypothesize that not yet encountered faults may require fault handling, analytic models and an architectural framework to manage the faults and mitigate the risks of correlating or integrating otherwise uncorrelated big data and to ensure the source pedigree, quality, set integrity, freshness, and validity of the data. This chapter provides a number of examples to support the hypothesis. The objectives of the designers of these knowledge management systems must be to mitigate the faults resulting from real-time streaming processes while ensuring that variables such as synchronization, redundancy, and latency are addressed. This chapter concludes that with improved designs, real-time big data systems may continuously deliver the value of streaming big data.
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Protecting modern engineered systems has become increasingly difficult due to their complexity and the difficulty of predicting potential failures. With the added threat of terrorism, the desire to design systems resilient to potential faults has increased. The concept of a resilient system – one that can withstand unanticipated failures without disastrous consequences – provides promise for designing safer systems. Resilience has been recognized in research settings as a desired end product of specific systems, but resilience as a general, inherent, measurable property of systems had yet to be established. To achieve this goal, system resilience was related to an established concept, the resiliency of a material. System resilience was defined as the amount of energy a system can store before reaching a point of instability. The energy input into each system as well as the system’s exergy were used to develop system stress and system strain variables. Process variable changes to four test systems – a steam pipe, a water pipe, a water pump, and a heat exchanger – were applied to obtain series of system stress and system strain data that were then graphed to form characteristic system response curves. Resilience was quantified by performing power-law regression on each curve to determine the variable ranges where the regression line accurately described the data and where the data began to deviate from that power-law trend. Finally, the four test systems were analyzed in depth by combining them into an overall system using the process simulator ASPEN. The ranges predicted by the overall system data were compared to the ranges predicted for the individual equipment. Finally, future work opportunities were outlined to show potential areas for expansion of the methodology.
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A unified approach to science teaching based upon a certain class of quantities which play fundamental roles in classical and modern physics is introduced. These quantities share the property of being substance-like, that is, each can be pictured to be contained in bodies and to flow from one body to another like a kind of ``stuff.'' Such quantities include, for example, energy (=mass), momentum, angular momentum, electric charge, particle number (=amount of substance), and entropy. When emphasizing substance-like quantities, the breakup of physics into sub-branches is nothing more than a classification of natural processes according to the substance-like quantity playing the dominant role in each case. The method of presentation, however, remains the same from one sub-branch to another: different natural processes can be simply visualized and quantitatively described according to the same formal rules in terms of the increasing, decreasing, and flowing of the respective substance-like quantities in each case. Thus knowledge of a single branch of physics already provides an analogy for the ways and means by which processes are described in other branches (including chemistry and biology) as well. These claims are illustrated with the help of a few simple examples.