Understanding Complex Systems - Böcker

This book presents an innovative control system design process motivated by renewable energy electric grid integration problems. The concepts developed result from the convergence of research and development goals which have important concepts in common: exergy flow, limit cycles, and balance between competing power flows.A unique set of criteria is proposed to design controllers for a class of nonlinear systems. A combination of thermodynamics with Hamiltonian systems provides the theoretical foundation which is then realized in a series of connected case studies. It allows the process of control design to be viewed as a power flow control problem, balancing the power flowing into a system against that being dissipated within it and dependent on the power being stored in it – an interplay between kinetic and potential energies. Human factors and the sustainability of self-organizing systems are dealt with as advanced topics.

Topics that are treated include: interactive continuation tools, higher-dimensional continuation, the computation of invariant manifolds, and continuation techniques for slow-fast systems, for symmetric Hamiltonian systems, for spatially extended systems and for systems with delay.

Nonlinear dynamics has become an important field of research in recent years in many areas of the natural sciences. In particular, it has potential applications in biology and medicine; nonlinear data analysis has helped to detect the progress of cardiac disease, physiological disorders, for example episodes of epilepsy, and others. This book focuses on the current trends of research concerning the prediction of sudden cardiac death and the onset of epileptic seizures, using the nonlinear analysis based on ECG and EEG data. Topics covered include the analysis of cardiac models and neural models. The book is a collection of recent research papers by leading physicists, mathematicians, cardiologists and neurobiologists who are actively involved in using the concepts of nonlinear dynamics to explore the functional behaviours of heart and brain under normal and pathological conditions. This collection is intended for students in physics, mathematics and medical sciences, and researchers in interdisciplinary areas of physics and biology.

It allows the process of control design to be viewed as a power flow control problem, balancing the power flowing into a system against that being dissipated within it and dependent on the power being stored in it – an interplay between kinetic and potential energies.

This book attempts to explain why and how humans behave much like atoms in some aspects of their collective lives. The authors then suggest ways that this knowledge could serve as the key to a dramatic leap forwards in social freedom in the real world.

Product and service innovations are the result of mutually interacting creative and coordination tasks within a system that has to balance technical decisions, marketplace taste, personnel management, and stakeholder commitment. The constituent elements of such systems are often scattered across multiple firms and across the globe and constitute a complex system consisting of many interacting parts.In the spirit of the "butterfly effect", metaphorically describing the sensitivity to initials conditions of chaotic systems, this book builds an argument that "innovation butterflies" can, in the short term, take up significant amounts of effort and sap efficiencies within individual innovation projects. Such "innovation butterflies" can be prompted by external forces such as government legislation or unexpected spikes in the price of basic goods (such as oil), unexpected shifts in market tastes, or from a company manager’s decisions or those of its competitors. Even the smallest change, the smallest disruption, to this system can steer a firm down an unpredictable and irreversibly different path in terms of technology and market evolution.In the long term, they can shift the balance of the entire innovation portfolio into unplanned directions. More importantly, we describe how innovation leaders can influence the emergent behavior of the system for good or ill.  The first half of the book draws parallels from physics, economics, and sociology as well as evidence from multiple industries to describe the structural and behavioral causes of emergent phenomena in innovation settings as well as their often negative impacts. In the second half of the book, we turn to distributed management of innovation under emergence. We show that innovation butterflies, if improperly managed, most often lead to negative outcomes. On the other hand, it is also argued that while the complexity of the innovation system and the desireto experiment and try new and emergent alternatives precludes precise planning, innovation leaders can actually tame innovation butterflies through the design and implementation of appropriate processes, strategies, tools and leadership choices.

In this book, experts from biology, physics and the social sciences examine the unification of all design phenomena in nature and apply this knowledge to designs in engineering, such as vascularization for self-healing and self-cooling materials for aircraft.

Through the development of an exact path integral for use in transferring information from observations to a model of the observed system, the author provides a general framework for the discussion of model building and evaluation across disciplines.

The roles and applications of various modeling approaches, aimed at improving the usefulness of energy policy models in public decision making, are covered by this book. The development, validation, and applications of system dynamics and agent-based models in service of energy policy design and assessment in the 21st century is a key focus. A number of modeling approaches and models for energy policy, with a particular focus on low-carbon economic development of regions and states are covered. Chapters on system dynamics methodology, model-based theory, fuzzy system dynamics frame-work, and optimization modeling approach are presented, along with several chapters on future research opportunities for the energy policy modeling community.The use of model-based analysis and scenarios in energy policy design and assessment has seen phenomenal growth during the past several decades. In recent years, renewed concerns about climate change and energy security have posed unique modeling challenges. By utilizing the validation techniques and procedures which are effectively demonstrated in these contributions, researchers and practitioners in energy systems domain can increase the appeal and acceptance of their policy models.

Design happens everywhere, whether in animate objects (e.g., dendritic lung structures, bacterial colonies, and corals), inanimate patterns (river basins, beach slope, and dendritic crystals), social dynamics (pedestrian traffic flows), or engineered systems (heat dissipation in electronic circuitry). This “design in nature” often takes on remarkably similar patterns, which can be explained under one unifying Constructal Law. This book explores the unifying power of the Constructal Law and its applications in all domains of design generation and evolution, ranging from biology and geophysics to globalization, energy, sustainability, and security.  The Constructal Law accounts for the universal tendency of flow systems to morph into evolving configurations that provide greater and easier access over time. The Constructal Law resolves the many and contradictory ad hoc statements of “optimality”, end design, and destiny in nature, such as minimum and maximum entropy production and minimum and maximum flow resistance, and also explains the designs that are observed and copied in biomimetics.Constructal Law and the Unifying Principle of Design covers the fundamentals of Constructal Theory and Design, as well as presenting a variety of state-of-the-art applications. Experts from the biological, physical and social sciences demonstrate the unification of all design phenomena in nature, and apply this knowledge to novel designs in modern engineering, such as vascularization for self-healing and self-cooling materials for aircraft, and tree fins and cavities for heat transfer enhancement.

Product and service innovations are the result of mutually interacting creative and coordination tasks within a system that has to balance technical decisions, marketplace taste, personnel management, and stakeholder commitment. The constituent elements of such systems are often scattered across multiple firms and across the globe and constitute a complex system consisting of many interacting parts.In the spirit of the "butterfly effect", metaphorically describing the sensitivity to initials conditions of chaotic systems, this book builds an argument that "innovation butterflies" can, in the short term, take up significant amounts of effort and sap efficiencies within individual innovation projects. Such "innovation butterflies" can be prompted by external forces such as government legislation or unexpected spikes in the price of basic goods (such as oil), unexpected shifts in market tastes, or from a company manager’s decisions or those of its competitors. Even the smallest change, the smallest disruption, to this system can steer a firm down an unpredictable and irreversibly different path in terms of technology and market evolution.In the long term, they can shift the balance of the entire innovation portfolio into unplanned directions. More importantly, we describe how innovation leaders can influence the emergent behavior of the system for good or ill.  The first half of the book draws parallels from physics, economics, and sociology as well as evidence from multiple industries to describe the structural and behavioral causes of emergent phenomena in innovation settings as well as their often negative impacts. In the second half of the book, we turn to distributed management of innovation under emergence. We show that innovation butterflies, if improperly managed, most often lead to negative outcomes. On the other hand, it is also argued that while the complexity of the innovation system and the desireto experiment and try new and emergent alternatives precludes precise planning, innovation leaders can actually tame innovation butterflies through the design and implementation of appropriate processes, strategies, tools and leadership choices.

A variety of new models and approaches are presented here, including Dynamic Network Analysis, DIME/PMESII models, percolation models and emergent models of insurgency.

This pioneering text provides a comprehensive introduction to systems structure, function, and modeling as applied in all fields of science and engineering. Systems understanding is increasingly recognized as a key to a more holistic education and greater problem solving skills, and is also reflected in the trend toward interdisciplinary approaches to research on complex phenomena. While the concepts and components of systems science will continue to be distributed throughout the various disciplines, undergraduate degree programs in systems science are also being developed, including at the authors’ own institutions. However, the subject is approached, systems science as a basis for understanding the components and drivers of phenomena at all scales should be viewed with the same importance as a traditional liberal arts education.Principles of Systems Science contains many graphs, illustrations, side bars, examples, and problems to enhance understanding. Frombasic principles of organization, complexity, abstract representations, and behavior (dynamics) to deeper aspects such as the relations between information, knowledge, computation, and system control, to higher order aspects such as auto-organization, emergence and evolution, the book provides an integrated perspective on the comprehensive nature of systems. It ends with practical aspects such as systems analysis, computer modeling, and systems engineering that demonstrate how the knowledge of systems can be used to solve problems in the real world. Each chapter is broken into parts beginning with qualitative descriptions that stand alone for students who have taken intermediate algebra. The second part presents quantitative descriptions that are based on pre-calculus and advanced algebra, providing a more formal treatment for students who have the necessary mathematical background. Numerous examples of systems from every realm of life, including the physical and biological sciences,humanities, social sciences, engineering, pre-med and pre-law, are based on the fundamental systems concepts of boundaries, components as subsystems, processes as flows of materials, energy, and messages, work accomplished, functions performed, hierarchical structures, and more. Understanding these basics enables further understanding both of how systems endure and how they may become increasingly complex and exhibit new properties or characteristics.Serves as a textbook for teaching systems fundamentals in any discipline or for use in an introductory course in systems science degree programsAddresses a wide range of audiences with different levels of mathematical sophisticationIncludes open-ended questions in special boxes intended to stimulate integrated thinking and class discussion Describes numerous examples of systems in science and societyCaptures the trend towards interdisciplinary research and problem solving

This book follows the methodologies of complex adaptive systems research in their application to addressing the problems of terrorism, specifically terrorist networks, their structure and various methods of mapping and interdicting them as well as exploring the complex landscape of network-centric and irregular warfare. A variety of new models and approaches are presented here, including Dynamic Network Analysis, DIME/PMESII models, percolation models and emergent models of insurgency. In addition, the analysis is informed by practical experience, with analytical and policy guidance from authors who have served within the U.S. Department of Defense, the British Ministry of Defence as well as those who have served in a civilian capacity as advisors on terrorism and counter-terrorism.

The roles and applications of various modeling approaches, aimed at improving the usefulness of energy policy models in public decision making, are covered by this book. The development, validation, and applications of system dynamics and agent-based models in service of energy policy design and assessment in the 21st century is a key focus. A number of modeling approaches and models for energy policy, with a particular focus on low-carbon economic development of regions and states are covered. Chapters on system dynamics methodology, model-based theory, fuzzy system dynamics frame-work, and optimization modeling approach are presented, along with several chapters on future research opportunities for the energy policy modeling community.The use of model-based analysis and scenarios in energy policy design and assessment has seen phenomenal growth during the past several decades. In recent years, renewed concerns about climate change and energy security have posed unique modeling challenges. By utilizing the validation techniques and procedures which are effectively demonstrated in these contributions, researchers and practitioners in energy systems domain can increase the appeal and acceptance of their policy models.

Do humans behave much like atoms? Sociophysics, which uses tools and concepts from the physics of disordered matter to describe some aspects of social and political behavior, answers in the affirmative. But advocating the use of models from the physical sciences to understand human behavior could be perceived as tantamount to dismissing the existence of human free will and also enabling those seeking manipulative skills . This thought-provoking book argues it is just the contrary.Indeed, future developments and evaluation will either show sociophysics to be inadequate, thus supporting the hypothesis that people can primarily be considered to be free agents, or valid, thus opening the path to a radically different vision of society and personal responsibility. This book attempts to explain why and how humans behave much like atoms, at least in some aspects of their collective lives, and then proposes how this knowledge can serve as a unique key to a dramatic leap forwards in achieving more social freedom in the real world. At heart, sociophysics and this book are about better comprehending the richness and potential of our social interaction, and so distancing ourselves from inanimate atoms.

This pioneering text provides a comprehensive introduction to systems structure, function, and modeling as applied in all fields of science and engineering. Systems understanding is increasingly recognized as a key to a more holistic education and greater problem solving skills, and is also reflected in the trend toward interdisciplinary approaches to research on complex phenomena. While the concepts and components of systems science will continue to be distributed throughout the various disciplines, undergraduate degree programs in systems science are also being developed, including at the authors’ own institutions. However, the subject is approached, systems science as a basis for understanding the components and drivers of phenomena at all scales should be viewed with the same importance as a traditional liberal arts education.Principles of Systems Science contains many graphs, illustrations, side bars, examples, and problems to enhance understanding. Frombasic principles of organization, complexity, abstract representations, and behavior (dynamics) to deeper aspects such as the relations between information, knowledge, computation, and system control, to higher order aspects such as auto-organization, emergence and evolution, the book provides an integrated perspective on the comprehensive nature of systems. It ends with practical aspects such as systems analysis, computer modeling, and systems engineering that demonstrate how the knowledge of systems can be used to solve problems in the real world. Each chapter is broken into parts beginning with qualitative descriptions that stand alone for students who have taken intermediate algebra. The second part presents quantitative descriptions that are based on pre-calculus and advanced algebra, providing a more formal treatment for students who have the necessary mathematical background. Numerous examples of systems from every realm of life, including the physical and biological sciences,humanities, social sciences, engineering, pre-med and pre-law, are based on the fundamental systems concepts of boundaries, components as subsystems, processes as flows of materials, energy, and messages, work accomplished, functions performed, hierarchical structures, and more. Understanding these basics enables further understanding both of how systems endure and how they may become increasingly complex and exhibit new properties or characteristics.Serves as a textbook for teaching systems fundamentals in any discipline or for use in an introductory course in systems science degree programsAddresses a wide range of audiences with different levels of mathematical sophisticationIncludes open-ended questions in special boxes intended to stimulate integrated thinking and class discussion Describes numerous examples of systems in science and societyCaptures the trend towards interdisciplinary research and problem solving

Through the development of an exact path integral for use in transferring information from observations to a model of the observed system, the author provides a general framework for the discussion of model building and evaluation across disciplines.

This book gives the definitive mathematical answer to what thermodynamics really is: a variational calculus applied to probability distributions. Extending Gibbs's notion of ensemble, the Author imagines the ensemble of all possible probability distributions and assigns probabilities to them by selection rules that are fairly general. The calculus of the most probable distribution in the ensemble produces the entire network of mathematical relationships we recognize as thermodynamics. The first part of the book develops the theory for discrete and continuous distributions while the second part applies this thermodynamic calculus to problems in population balance theory and shows how the emergence of a giant component in aggregation, and the shattering transition in fragmentation may be treated as formal phase transitions.While the book is intended as a research monograph, the material is self-contained and the style sufficiently tutorial to be accessible forself-paced study by an advanced graduate student in such fields as physics, chemistry, and engineering.

After a short introduction to the fundamentals, this book provides a detailed account of major advances in applying fractional calculus to dynamical systems. Fractional order dynamical systems currently continue to gain further importance in many areas of science and engineering.As with many other approaches to mathematical modeling, the first issue to be addressed is the need to couple a definition of the fractional differentiation or integration operator with the types of dynamical systems that are analyzed. As such, for the fundamentals the focus is on basic aspects of fractional calculus, in particular stability analysis, which is required to tackle synchronization in coupled fractional order systems, to understand the essence of estimators for related integer order systems, and to keep track of the interplay between synchronization and parameter observation. This serves as the common basis for the more advanced topics and applications presented in the subsequent chapters, which include an introduction to the 'Immersion and Invariance' (I&I) methodology, the masterslave synchronization scheme for partially known nonlinear fractional order systems, Fractional Algebraic Observability (FAO) and Fractional Generalized quasi-Synchronization (FGqS) to name but a few.This book is intended not only for applied mathematicians and theoretical physicists, but also for anyone in applied science dealing with complex nonlinear systems.

This book presents the latest tools, techniques, and solutions that decision makers use to overcome the challenges faced by their sustainable supply chains.

This book describes the ontology structure, types of actors, their potential actions, and ways that actions can affect the things that are part of the conflict. An ontology of unconventional conflict supports the understanding of unconventional conflict in general.

This book is part of a two volume set which presents the analysis of nonlinear phenomena as a long-standing challenge for research in basic and applied science as well as engineering.

This book presents collaborative research presented by experts in the field of nonlinear science provides the reader with contemporary, cutting-edge, research works that bridge the gap between theory and device realizations of nonlinear phenomena.

This edited volume presents chapters on the dynamics of global climate change and global warming in the Middle East. The audience for this volume includes policy makers, researchers, and students unified by the common goal of making better decisions in the sustainable production and consumption of energy.

This book focuses on a central question in the field of complex systems: Given a fluctuating (in time or space), uni- or multi-variant sequentially measured set of experimental data (even noisy data), how should one analyse non-parametrically the data, assess underlying trends, uncover characteristics of the fluctuations (including diffusion and jump contributions), and construct a stochastic evolution equation?Here, the term "non-parametrically" exemplifies that all the functions and parameters of the constructed stochastic evolution equation can be determined directly from the measured data.The book provides an overview of methods that have been developed for the analysis of fluctuating time series and of spatially disordered structures.  Thanks to its feasibility and simplicity, it has been successfully applied to fluctuating time series and spatially disordered structures of complex systems studied in scientific fields such as physics, astrophysics, meteorology, earth science, engineering, finance, medicine and the neurosciences, and has led to a number of important results.The book also includes the numerical and analytical approaches to the analyses of complex time series that are most common in the physical and natural sciences. Further, it is self-contained and readily accessible to students, scientists, and researchers who are familiar with traditional methods of mathematics, such as ordinary, and partial differential equations.The codes for analysing continuous time series are available in an R package developed by the research group Turbulence, Wind energy and Stochastic (TWiSt) at the Carl von Ossietzky University of Oldenburg under the supervision of Prof. Dr. Joachim Peinke. This package makes it possible to extract the (stochastic) evolution equation underlying a set of data or measurements.

This book focuses on a central question in the field of complex systems: Given a fluctuating (in time or space), uni- or multi-variant sequentially measured set of experimental data (even noisy data), how should one analyse non-parametrically the data, assess underlying trends, uncover characteristics of the fluctuations (including diffusion and jump contributions), and construct a stochastic evolution equation?Here, the term "non-parametrically" exemplifies that all the functions and parameters of the constructed stochastic evolution equation can be determined directly from the measured data.The book provides an overview of methods that have been developed for the analysis of fluctuating time series and of spatially disordered structures.  Thanks to its feasibility and simplicity, it has been successfully applied to fluctuating time series and spatially disordered structures of complex systems studied in scientific fields such as physics, astrophysics, meteorology, earth science, engineering, finance, medicine and the neurosciences, and has led to a number of important results.The book also includes the numerical and analytical approaches to the analyses of complex time series that are most common in the physical and natural sciences. Further, it is self-contained and readily accessible to students, scientists, and researchers who are familiar with traditional methods of mathematics, such as ordinary, and partial differential equations.The codes for analysing continuous time series are available in an R package developed by the research group Turbulence, Wind energy and Stochastic (TWiSt) at the Carl von Ossietzky University of Oldenburg under the supervision of Prof. Dr. Joachim Peinke. This package makes it possible to extract the (stochastic) evolution equation underlying a set of data or measurements.

​This book emerged out of international conferences organized as part of the AAAI Fall Symposia series, and the Swarmfest 2017 conference. It brings together researchers from diverse fields studying these complex systems using CAS and agent-based modeling tools and techniques. In the past, the knowledge gained in each domain has largely remained exclusive to that domain. By bringing together scholars who study these phenomena, the book takes knowledge from one domain to provide insight into others.Most interesting phenomena in natural and social systems include constant transitions and oscillations among their various phases –  wars, companies, societies, markets, and humans rarely stay in a stable, predictable state for long. Randomness, power laws, and human behavior ensure that the future is both unknown and challenging. How do events unfold? When do they take hold? Why do some initial events cause an avalanche while others do not? What characterizes these events? What are the thresholds that differentiate a sea change from a non-event?Complex adaptive systems (CAS) have proven to be a powerful tool for exploring these and other related phenomena. The authors characterize a general CAS model as having a large number of self-similar agents that: 1) utilize one or more levels of feedback; 2) exhibit emergent properties and self-organization; and 3) produce non-linear dynamic behavior. Advances in modeling and computing technology have led not only to a deeper understanding of complex systems in many areas, but they have also raised the possibility that similar fundamental principles may be at work across these systems, even though the underlying principles may manifest themselves differently.

This is the first book devoted to chimera states - peculiar partial synchronization patterns in networks.