Probability and Statistics in Complex Systems, Introduction to

Accidents in complex systems seldom arise from a single source, and are most often the result of multiple factors occurring at different levels of the system. Understanding the “systems” aspects of human performance (and performance error) in complex systems is a necessary part of any effort to avoid serious mishaps due to human error. This panel is intended to coincide with the development of a major research effort at the University of Wisconsin to address these issues. The Center for Human Performance in Complex Systems will apply the disciplines of systems engineering and ergonomics design to improve complex systems processes from the perspective of human performance. The purpose of this panel is to foster and demonstrate the Center's interest in bringing together a variety of perspectives and expertise bases to improve the overall quality and breadth of its activities. Each of the participants has a longstanding interest in improving the quality of human performance in complex and critical systems environments. Although they cannot represent the entire spectrum of relevant disciplines and perspectives of ergonomics and systems analysis, they provide a balance of insights, experience, and enthusiasm. This balance is essential to improving our understanding of factors affecting complex socio-technical systems, and implementing strategies to prevent and ameliorate the effects of system degradation and breakdown.

Change in a complex system—for example, to its technology, procedures, or information flows— no matter how small, has the potential to create large effects and ripples of disruption. A complex system’s dynamics cannot be fully known, and the effects and disruptions produced by change are difficult to predict. Nonetheless, complex systems can be at least partly understood in terms of patterns in their dynamics, generalizable principles, and mechanisms of control, balance, and adaptation. This panel will focus on complex systems research and what they suggest about how to introduce change into a complex system such that the work system resilience and health are disrupted minimally. Case studies may be discussed, as well; examples of changes to established complex work systems. These changes include introducing remotely piloted aircraft systems (RPAS) into the National Airspace System (NAS), additional automation into air traffic control, and new technology into military air combat training.

Systems engineering is the branch of engineering concerned with the development of large and complex systems, where a system is understood to be an assembly or combination of interrelated elements or parts working together toward a common objective. Past experience has shown that formal systems engineering methodologies have not always been successfully applied to large and complex cybersecurity systems. These complex systems have become commonplace when applying cyberstrategies in cybersecurity operations. The ability to build, operate and maintain such systems is crucial to the effectiveness of cybersecurity operations. Most importantly, a cyberstrategy program must surround these systems on a global scale across multiple inter-related platforms. In this chapter, the authors demonstrate why a systems engineering approach is best suited for large and complex information systems used in cybersecurity, as well as the overall cyberstrategies that must also reside over these systems.

Integrative physiology and systems biology: reductionism, emergence and causality

The presented review analyzes the approaches and methods of using simulation models in the maintenance and repair organization of the complex technical objects and systems. The development of the concept of "Industry 4.0" and the Internet of things involves the transition from periodic and preventive maintenance to predictive maintenance based on the study of processes during the object operation. It is shown that system models based on Petri nets are convenient for describing and analyzing technological processes and equipment maintenance. The effectiveness of timed stochastic colored Petri nets for virtual tests in the design of maintenance and repair procedures in complex systems is revealed. The use of hierarchical Petri nets allows building complex models that describe interrelated processes. A general model based on a hierarchical network is proposed to study the processes of deterioration and degradation of the technical object aggregates and elements and to form a predictive maintenance strategy. The model includes a Gantt chart of production tasks, a set of active and reserve units, maintenance and repair modules. The examples of simulation models on Petri nets for various technical systems are considered. Solutions for flexible production systems, railway bridges, offshore wind turbines, an aircraft fleet, a group of robotic vehicles, and a complex of computer equipment of an enterprise are given. The models of various maintenance strategies are considered and the generality of the models based on hierarchical Petri nets is shown. The article formulates methodological principles for constructing hierarchical networks to simulate the operation and maintenance of technical systems. The article analyzes known software tools for the implementation of timed stochastic colored Petri nets. The summary concludes that the use of simulation models on Petri nets is promising for organizing maintenance and repair of complex technical objects and systems.

The complexity of problems facing society continues to grow, and decision-makers and problem-solvers are finding many of today's emerging problems to be beyond their capability to adequately address. There is agreement in the literature that problems of this nature are complex system problems, inextricably linked to some highly complex system of systems. Establishing a clear understanding of the specific complex system context is fundamental to the process of understanding and analyzing complex systems and complex system problems across all of the different systems-based disciplines. While complex system context is widely referred to in systems literature, there is no clear characterization of exactly what system context is, making this foundational system concept ambiguous. This research addressed this gap in the systems body of knowledge by providing the needed detail and clarity to the concept of complex system context. A rigorous research methodology, employing the grounded theory method, was used to analyze data collected through a series of semi-structured interviews conducted with individuals reflecting a wide range of systems education and practical experience. Two research questions were identified as integral to increasing the understanding of context within complex systems. (1) What are the constituent elements of complex system context, and what attributes and dimensions characterize these elements? (2) What systems-based framework can be developed for constructing and articulating complex system context? Using the grounded theory method, a theory of system context was constructed, adding to the systems body of knowledge and substantiating a comprehensive and unambiguous theoretical construct for system context within complex systems. Then, based on this theory, a conceptual model to articulate and capture system-specific complex system context was developed---the Complex System Contextual Framework (CSCF). The CSCF shows significant promise for contribution to systems practitioners by supporting the future development of tools to help practitioners capture system context as a part of complex system problem formulation. The research also made a contribution in the area of research methodologies by furthering the use of the grounded theory method in the engineering management and systems engineering domain, an area where its application has been very limited.

Linguistic Geometry for autonomous navigation

Mass and energy rate (ER) data have been collected for a wide variety of (complex) systems from the biological, cultural, and cosmological realms. They range from the cytochrome oxidase protein (10-22 kg and 6x10-19 W) to the observable universe (1.5x1053 kg and 1048 W) and, thus, span 75 mass and 66 ER orders of magnitude. Many of these systems are relevant for the big history (BH) narrative, i.e., the development of complexity over “big time” from the Big Bang up to the human society on Earth of today. The purpose of this paper is not per se to describe their history though, but to explore a master plot of ER vs. mass. Notably, the development of systems over big time has followed a rather tortuous path criss-crossing over this ER vs. mass master plot. The true mass of the system as a whole is used (for example trees including the non-living wood, living organisms including their intrinsic water, and social systems including the built constructs), because these inactive parts are essential for the performance of the system and facilitate its ER. A double logarithmic master plot of all ER vs. mass data shows clusters of data points. To some extent, this provides quantitative support for the distinction between the (sub-)realms, which is based on a qualitative description of their material structure and energy processing. In the master plot, small systems with low mass and ER converge into larger systems with larger mass and ER, which is typically accompanied by a decrease of the energy rate density (ERD = ER/mass). Correlation of ER with mass for various groups of systems demonstrates both sub- and supra-linear scaling with the power law β constant varying between 0.5 and 4.0, showing that the mechanisms of self-organisation are quite different for the corresponding system groups. The combination of convergence and scaling with β always larger than zero explains why the ER & mass data points fall in a diagonal band with a width of 17 orders of magnitude.
 ER and mass have changed over wide ranges during the evolution of groups of systems, suggesting that evolution can be viewed as a process of systems exploring a larger ER vs. mass area until they run into ER and/or mass limitations. Indeed, there is a diagonal ER vs. mass limit for stable systems in all realms, corresponding to an ERD value of around 105 W/kg. Systems with ER & mass combinations above this limit, such as bombs, super-novae and cosmological transients, are unstable and “explosive”. This raises the interesting question of whether such an ERD maximum puts a limit on the development of complexity over big time. It seems that the low, right side of the master plot is empty. However, it is argued here that it is full of systems with low ER, such as dormant, living organisms, technological systems with their power adjusted or even switched off, as well as cooling, cosmological objects. Such systems are typically considered of less interest in a BH context, but they are viewed here as simple, complex systems which are out of equilibrium with matter, energy and information stored in their structure. While ERD appears to increase with the ‘advancement’ of systems over big time [5,51,52], there are quite some confounding factors regarding the efficacy of ERD as a metric for complexity in BH. For example, ERD decreases during the lifetime of a human and the human society (the mass of human-made constructs has grown faster than the global energy consumption), as well as during the evolution of living organisms and stars, whereas complexity is considered to increase. High ERD values of system parts may be illustrative for the complexity of the larger system, but are not representative for ERD of the system itself. Machines with an increased efficiency of energy conversion have a lower ERD, but could be considered more complex. The smallest and largest ERD values observed for the various realms appear to correlate with activity level and reciprocally with size, which do not per se reflect complexity. It is hoped that the raw data collected and the major trends observed in this paper will offer new insights into various aspects of the evolution of the universe over big time, and serve as an important resource for other related studies.

ASTRAL is a formal specification language for realtime systems. It is intended to support formal software development, and therefore has been formally defined. In ASTRAL a realtime system is modeled by a collection of state machine specifications and a single global specification. This paper focuses on extending the ASTRAL methodology to allow the composition of ASTRAL system specifications into specifications of larger and more complex systems. The ASTRAL language includes structuring mechanisms that allow one to build modularized specifications of complex systems with layering. In this paper we concentrate on how to combine these complex system specifications into specifications of even more complex realtime systems. This is accomplished by adding a COMPOSE section to the language that provides the needed information to combine two or more ASTRAL specifications into a single new one. In this paper we also introduce the necessary proof obligations to assure that the assumptions of each of the components of the larger system are satisfied by the other components of the system that replace the previous external environment. We also discuss how some exported transitions become internal transitions of the new system. A telephony example with local central controls that interface to long distance units is used to motivate the extensions.

Cultural goods are documents that concentrate many resources and work. Cultural heritage needs numerous investments for its own maintenance and safeguard, but it is also an historical testimony through which community renews itself and its own culture. Cultural heritage is even a tool able to attract tourism and revitalise culture chain. Therefore cultural goods express economic social and cultural values for the benefit of community and territories. We will use two different approaches to study cultural economic impact: firstly, the micro approach to study cultural organizations, their inner dynamics and their contribution to cultural system; secondly, the macro approach, to analyze economic dynamics of complex and wider cultural heritage systems. As in every complex system these approaches are tightly interrelated, and it is necessary to contemplate both of them in order to analyze the phenomenon as a whole. The present job illustrates two different models of analysis: the first belonging to the micro approach, the second instead affiliate to macro approaches.

Telecommunication systems have evolved, from being simple monolithic structures to complex ones. The present paper is an attempt to recast telecom systems in the language of complex systems. As a specific application of complex systems science to telecom systems, we tackle the problem of self-organizing frequency allocation. For this purpose, we model the problem of frequency assignment within the framework of cellular automata and we present an algorithm that reaches an interference-free allocation of the channels in a finite number of steps. By applying a measure of spatial structure and pattern to the two-dimensional lattice representing the frequency allocation, our study shows that autonomous networks assigning frequencies to their cells in a self-organized way, can be defined and therefore studied as complex systems. On the contrary, traditional networks based on centralized pre-planned frequency allocation cannot be considered as complex, according to the meaning given to the word by complex systems science. The present paper is to be considered as a step towards a comprehensive and rigorous study of Complex Communication Systems (CCS), adopting in communication networks design and analysis, the results and philosophy underlying the emerging multi-disciplinary field of Complex Systems Science.

As chief-editor of an academic journal, one has the prerogative to read a lot of “raw material”; (concepts of-) papers that may (or may not) make it as a publication to the journal. Jointly, these “raw” papers certainly give a most interesting insight in ongoing research activities in the academic and industrial world. We as authors, recognize availability of “highly important sub-system A” as of crucial importance for the operation of “complex system B”. Therefore we have done a case-study on how to improve the availability of “sub-system A” using the following method “variant of a availability/maintenance analysis/optimization method already existing since the mid-20th century”. It has led to the following improvement… Especially when “sub-system A” is of a very traditional, often mechanical, nature we have to decline this paper due the fact that only very limited conceptual new knowledge is generated in spite of the, without any doubt, valuable contribution to the owners of “complex system B.” We as authors have studied the following methodological concepts “A, B, C, D, …” and have come to the conclusion that it is worthwhile to develop a new concept “E” which looks as follows “complex mathematical description”. Compared to the earlier described methods this leads to the following, conceptual, advantages “list of tables/graphs”. Application: highly conceptual or absent. Also, in this case, papers are often declined since the innovative contribution to the resolution of real-world (engineering) problems is often very limited. And, in the real-world, major engineering challenges remain unsolved. I am writing this paper for a very specific reason: in our daily life, society has become increasingly dependent on the availability of complex systems. With the recent hurricanes Harvey, Irma, and Maria, we have seen that the destruction caused not only the traditional primary systems to fail (water, food, etc.) but also the more recent primary systems (transportation, energy, communication/internet, etc.) The unavailability of, especially, these more recent primary systems is also often causing delay in the restauration of the more traditional primary systems. In all cases, the impact for the people involved is considerable. What amazes me in this context is that, although major events like hurricanes have happened in the past and will happen (according to some models even increasingly) also in the future, no case studies have been proposed to journals like this on how to analyze the availability of these highly important (but also highly complex and interwoven) systems under these extreme conditions. Even more valuable would be proposals not only on how to analyze these systems but also on how engineers could make them more robust. In the 21st century, we have become highly dependent on the availability of highly sophisticated systems like the Internet because of the most valuable services they provide but studies on how to analyze and improve their availability in a 21st-century context are still missing!

The power transmission grid, as well as many other complex critical infrastructure systems, display characteristics of a critical or near critical complex system with the risk of large cascading failures. Understanding this risk and its relation to the system state as it evolves, could allow for a more realistic risk assessment over time and even for mitigation or at least preparation if in a high risk state. In order to facilitate this type of analysis in the context of the power grid as a complex system, we develop a new measure of the complex system state, the generalized autonomous generational average Lambda-gaga, which correlates with the risk. The Lambda-gaga measure is an extension of the standard cascading propagation measure lambda but avoids the contamination of that measure by small events.

Conspectus: Redox reactions of Fe- and Mn-oxides play important roles in the fate and transformation of many contaminants in natural environments. Due to experimental and analytical challenges associated with complex environments, there has been a limited understanding of the reaction kinetics and mechanisms in actual environmental systems, and most of the studies so far have only focused on simple model systems. To bridge the gap between simple model systems and complex environmental systems, it is necessary to increase the complexity of model systems and examine both the involved interaction mechanisms and how the interactions affected contaminant transformation. In this Account, we primarily focused on (1) the oxidative reactivity of Mn- and Fe-oxides and (2) the reductive reactivity of Fe(II)/iron oxides in complex model systems toward contaminant degradation. The effects of common metal ions such as Mn2+, Ca2+, Ni2+, Cr3+ and Cu2+, ligands such as small anionic ligands and natural organic matter (NOM), and second metal oxides such as Al, Si and Ti oxides on the redox reactivity of the systems are briefly summarized.

Nowadays, the electricity generation industry works with complex systems. A complex system can be defined as composed of several subsystems, elements, components, or different equipments, interacting spatially and temporarily in a nonlinear way. A system's complexity is related to the amount of different elements, intensity of the relations, and the functions that each element carries out to reach the expected operational performance. Oil production platforms and nuclear plants are examples of complex and dynamic systems. This paper presents a proposal based on the application of non homogenous Markovian Processes for availability estimation and for the decision making related to the design modification of a complex system. In this proposal the operational state are modeled according to the system failure scenario. The transition rates between those scenarios are failure rate (lambda(t)) and repair rate (mu(t)). The probabilities analysis of each operational state, calculated from the Markovian analysis process, are used as input to the decision making process. That process is based on the calculation of the expected mean cost of each decision alternative. The method is applied for the decision making on installing a water-supply redundant system of heat recovery steam generator used in a combined cycle thermal power plant operating in Brazil.