Boccara, Nino
2010-01-01
Modeling Complex Systems, 2nd Edition, explores the process of modeling complex systems, providing examples from such diverse fields as ecology, epidemiology, sociology, seismology, and economics. It illustrates how models of complex systems are built and provides indispensable mathematical tools for studying their dynamics. This vital introductory text is useful for advanced undergraduate students in various scientific disciplines, and serves as an important reference book for graduate students and young researchers. This enhanced second edition includes: . -recent research results and bibliographic references -extra footnotes which provide biographical information on cited scientists who have made significant contributions to the field -new and improved worked-out examples to aid a student’s comprehension of the content -exercises to challenge the reader and complement the material Nino Boccara is also the author of Essentials of Mathematica: With Applications to Mathematics and Physics (Springer, 2007).
International Nuclear Information System (INIS)
Schreckenberg, M
2004-01-01
This book by Nino Boccara presents a compilation of model systems commonly termed as 'complex'. It starts with a definition of the systems under consideration and how to build up a model to describe the complex dynamics. The subsequent chapters are devoted to various categories of mean-field type models (differential and recurrence equations, chaos) and of agent-based models (cellular automata, networks and power-law distributions). Each chapter is supplemented by a number of exercises and their solutions. The table of contents looks a little arbitrary but the author took the most prominent model systems investigated over the years (and up until now there has been no unified theory covering the various aspects of complex dynamics). The model systems are explained by looking at a number of applications in various fields. The book is written as a textbook for interested students as well as serving as a comprehensive reference for experts. It is an ideal source for topics to be presented in a lecture on dynamics of complex systems. This is the first book on this 'wide' topic and I have long awaited such a book (in fact I planned to write it myself but this is much better than I could ever have written it!). Only section 6 on cellular automata is a little too limited to the author's point of view and one would have expected more about the famous Domany-Kinzel model (and more accurate citation!). In my opinion this is one of the best textbooks published during the last decade and even experts can learn a lot from it. Hopefully there will be an actualization after, say, five years since this field is growing so quickly. The price is too high for students but this, unfortunately, is the normal case today. Nevertheless I think it will be a great success! (book review)
Computational models of complex systems
Dabbaghian, Vahid
2014-01-01
Computational and mathematical models provide us with the opportunities to investigate the complexities of real world problems. They allow us to apply our best analytical methods to define problems in a clearly mathematical manner and exhaustively test our solutions before committing expensive resources. This is made possible by assuming parameter(s) in a bounded environment, allowing for controllable experimentation, not always possible in live scenarios. For example, simulation of computational models allows the testing of theories in a manner that is both fundamentally deductive and experimental in nature. The main ingredients for such research ideas come from multiple disciplines and the importance of interdisciplinary research is well recognized by the scientific community. This book provides a window to the novel endeavours of the research communities to present their works by highlighting the value of computational modelling as a research tool when investigating complex systems. We hope that the reader...
Models of complex attitude systems
DEFF Research Database (Denmark)
Sørensen, Bjarne Taulo
search algorithms and structural equation models. The results suggest that evaluative judgments of the importance of production system attributes are generated in a schematic manner, driven by personal value orientations. The effect of personal value orientations was strong and largely unmediated...... that evaluative affect propagates through the system in such a way that the system becomes evaluatively consistent and operates as a schema for the generation of evaluative judgments. In the empirical part of the paper, the causal structure of an attitude system from which people derive their evaluations of pork......Existing research on public attitudes towards agricultural production systems is largely descriptive, abstracting from the processes through which members of the general public generate their evaluations of such systems. The present paper adopts a systems perspective on such evaluations...
Thermodynamic modeling of complex systems
DEFF Research Database (Denmark)
Liang, Xiaodong
after an oil spill. Engineering thermodynamics could be applied in the state-of-the-art sonar products through advanced artificial technology, if the speed of sound, solubility and density of oil-seawater systems could be satisfactorily modelled. The addition of methanol or glycols into unprocessed well...... is successfully applied to model the phase behaviour of water, chemical and hydrocarbon (oil) containing systems with newly developed pure component parameters for water and chemicals and characterization procedures for petroleum fluids. The performance of the PCSAFT EOS on liquid-liquid equilibria of water...... with hydrocarbons has been under debate for some vii years. An interactive step-wise procedure is proposed to fit the model parameters for small associating fluids by taking the liquid-liquid equilibrium data into account. It is still far away from a simple task to apply PC-SAFT in routine PVT simulations and phase...
Modeling complex work systems - method meets reality
van der Veer, Gerrit C.; Hoeve, Machteld; Lenting, Bert
1996-01-01
Modeling an existing task situation is often a first phase in the (re)design of information systems. For complex systems design, this model should consider both the people and the organization involved, the work, and situational aspects. Groupware Task Analysis (GTA) as part of a method for the
Modeling Power Systems as Complex Adaptive Systems
Energy Technology Data Exchange (ETDEWEB)
Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.
2004-12-30
Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.
Complex Systems and Self-organization Modelling
Bertelle, Cyrille; Kadri-Dahmani, Hakima
2009-01-01
The concern of this book is the use of emergent computing and self-organization modelling within various applications of complex systems. The authors focus their attention both on the innovative concepts and implementations in order to model self-organizations, but also on the relevant applicative domains in which they can be used efficiently. This book is the outcome of a workshop meeting within ESM 2006 (Eurosis), held in Toulouse, France in October 2006.
Intrinsic Uncertainties in Modeling Complex Systems.
Energy Technology Data Exchange (ETDEWEB)
Cooper, Curtis S; Bramson, Aaron L.; Ames, Arlo L.
2014-09-01
Models are built to understand and predict the behaviors of both natural and artificial systems. Because it is always necessary to abstract away aspects of any non-trivial system being modeled, we know models can potentially leave out important, even critical elements. This reality of the modeling enterprise forces us to consider the prospective impacts of those effects completely left out of a model - either intentionally or unconsidered. Insensitivity to new structure is an indication of diminishing returns. In this work, we represent a hypothetical unknown effect on a validated model as a finite perturba- tion whose amplitude is constrained within a control region. We find robustly that without further constraints, no meaningful bounds can be placed on the amplitude of a perturbation outside of the control region. Thus, forecasting into unsampled regions is a very risky proposition. We also present inherent difficulties with proper time discretization of models and representing in- herently discrete quantities. We point out potentially worrisome uncertainties, arising from math- ematical formulation alone, which modelers can inadvertently introduce into models of complex systems. Acknowledgements This work has been funded under early-career LDRD project #170979, entitled "Quantify- ing Confidence in Complex Systems Models Having Structural Uncertainties", which ran from 04/2013 to 09/2014. We wish to express our gratitude to the many researchers at Sandia who con- tributed ideas to this work, as well as feedback on the manuscript. In particular, we would like to mention George Barr, Alexander Outkin, Walt Beyeler, Eric Vugrin, and Laura Swiler for provid- ing invaluable advice and guidance through the course of the project. We would also like to thank Steven Kleban, Amanda Gonzales, Trevor Manzanares, and Sarah Burwell for their assistance in managing project tasks and resources.
FRAM Modelling Complex Socio-technical Systems
Hollnagel, Erik
2012-01-01
There has not yet been a comprehensive method that goes behind 'human error' and beyond the failure concept, and various complicated accidents have accentuated the need for it. The Functional Resonance Analysis Method (FRAM) fulfils that need. This book presents a detailed and tested method that can be used to model how complex and dynamic socio-technical systems work, and understand both why things sometimes go wrong but also why they normally succeed.
Structured analysis and modeling of complex systems
Strome, David R.; Dalrymple, Mathieu A.
1992-01-01
The Aircrew Evaluation Sustained Operations Performance (AESOP) facility at Brooks AFB, Texas, combines the realism of an operational environment with the control of a research laboratory. In recent studies we collected extensive data from the Airborne Warning and Control Systems (AWACS) Weapons Directors subjected to high and low workload Defensive Counter Air Scenarios. A critical and complex task in this environment involves committing a friendly fighter against a hostile fighter. Structured Analysis and Design techniques and computer modeling systems were applied to this task as tools for analyzing subject performance and workload. This technology is being transferred to the Man-Systems Division of NASA Johnson Space Center for application to complex mission related tasks, such as manipulating the Shuttle grappler arm.
Chaos from simple models to complex systems
Cencini, Massimo; Vulpiani, Angelo
2010-01-01
Chaos: from simple models to complex systems aims to guide science and engineering students through chaos and nonlinear dynamics from classical examples to the most recent fields of research. The first part, intended for undergraduate and graduate students, is a gentle and self-contained introduction to the concepts and main tools for the characterization of deterministic chaotic systems, with emphasis to statistical approaches. The second part can be used as a reference by researchers as it focuses on more advanced topics including the characterization of chaos with tools of information theor
Sandpile model for relaxation in complex systems
International Nuclear Information System (INIS)
Vazquez, A.; Sotolongo-Costa, O.; Brouers, F.
1997-10-01
The relaxation in complex systems is, in general, nonexponential. After an initial rapid decay the system relaxes slowly following a long time tail. In the present paper a sandpile moderation of the relaxation in complex systems is analysed. Complexity is introduced by a process of avalanches in the Bethe lattice and a feedback mechanism which leads to slower decay with increasing time. In this way, some features of relaxation in complex systems: long time tails relaxation, aging, and fractal distribution of characteristic times, are obtained by simple computer simulations. (author)
On sampling and modeling complex systems
International Nuclear Information System (INIS)
Marsili, Matteo; Mastromatteo, Iacopo; Roudi, Yasser
2013-01-01
The study of complex systems is limited by the fact that only a few variables are accessible for modeling and sampling, which are not necessarily the most relevant ones to explain the system behavior. In addition, empirical data typically undersample the space of possible states. We study a generic framework where a complex system is seen as a system of many interacting degrees of freedom, which are known only in part, that optimize a given function. We show that the underlying distribution with respect to the known variables has the Boltzmann form, with a temperature that depends on the number of unknown variables. In particular, when the influence of the unknown degrees of freedom on the known variables is not too irregular, the temperature decreases as the number of variables increases. This suggests that models can be predictable only when the number of relevant variables is less than a critical threshold. Concerning sampling, we argue that the information that a sample contains on the behavior of the system is quantified by the entropy of the frequency with which different states occur. This allows us to characterize the properties of maximally informative samples: within a simple approximation, the most informative frequency size distributions have power law behavior and Zipf’s law emerges at the crossover between the under sampled regime and the regime where the sample contains enough statistics to make inferences on the behavior of the system. These ideas are illustrated in some applications, showing that they can be used to identify relevant variables or to select the most informative representations of data, e.g. in data clustering. (paper)
Complex systems modeling by cellular automata
Kroc, J.; Sloot, P.M.A.; Rabuñal Dopico, J.R.; Dorado de la Calle, J.; Pazos Sierra, A.
2009-01-01
In recent years, the notion of complex systems proved to be a very useful concept to define, describe, and study various natural phenomena observed in a vast number of scientific disciplines. Examples of scientific disciplines that highly benefit from this concept range from physics, mathematics,
Modeling Complex Chemical Systems: Problems and Solutions
van Dijk, Jan
2016-09-01
Non-equilibrium plasmas in complex gas mixtures are at the heart of numerous contemporary technologies. They typically contain dozens to hundreds of species, involved in hundreds to thousands of reactions. Chemists and physicists have always been interested in what are now called chemical reduction techniques (CRT's). The idea of such CRT's is that they reduce the number of species that need to be considered explicitly without compromising the validity of the model. This is usually achieved on the basis of an analysis of the reaction time scales of the system under study, which identifies species that are in partial equilibrium after a given time span. The first such CRT that has been widely used in plasma physics was developed in the 1960's and resulted in the concept of effective ionization and recombination rates. It was later generalized to systems in which multiple levels are effected by transport. In recent years there has been a renewed interest in tools for chemical reduction and reaction pathway analysis. An example of the latter is the PumpKin tool. Another trend is that techniques that have previously been developed in other fields of science are adapted as to be able to handle the plasma state of matter. Examples are the Intrinsic Low Dimension Manifold (ILDM) method and its derivatives, which originate from combustion engineering, and the general-purpose Principle Component Analysis (PCA) technique. In this contribution we will provide an overview of the most common reduction techniques, then critically assess the pros and cons of the methods that have gained most popularity in recent years. Examples will be provided for plasmas in argon and carbon dioxide.
Integrated Modeling of Complex Optomechanical Systems
Andersen, Torben; Enmark, Anita
2011-09-01
Mathematical modeling and performance simulation are playing an increasing role in large, high-technology projects. There are two reasons; first, projects are now larger than they were before, and the high cost calls for detailed performance prediction before construction. Second, in particular for space-related designs, it is often difficult to test systems under realistic conditions beforehand, and mathematical modeling is then needed to verify in advance that a system will work as planned. Computers have become much more powerful, permitting calculations that were not possible before. At the same time mathematical tools have been further developed and found acceptance in the community. Particular progress has been made in the fields of structural mechanics, optics and control engineering, where new methods have gained importance over the last few decades. Also, methods for combining optical, structural and control system models into global models have found widespread use. Such combined models are usually called integrated models and were the subject of this symposium. The objective was to bring together people working in the fields of groundbased optical telescopes, ground-based radio telescopes, and space telescopes. We succeeded in doing so and had 39 interesting presentations and many fruitful discussions during coffee and lunch breaks and social arrangements. We are grateful that so many top ranked specialists found their way to Kiruna and we believe that these proceedings will prove valuable during much future work.
Size and complexity in model financial systems
Arinaminpathy, Nimalan; Kapadia, Sujit; May, Robert M.
2012-01-01
The global financial crisis has precipitated an increasing appreciation of the need for a systemic perspective toward financial stability. For example: What role do large banks play in systemic risk? How should capital adequacy standards recognize this role? How is stability shaped by concentration and diversification in the financial system? We explore these questions using a deliberately simplified, dynamic model of a banking system that combines three different channels for direct transmission of contagion from one bank to another: liquidity hoarding, asset price contagion, and the propagation of defaults via counterparty credit risk. Importantly, we also introduce a mechanism for capturing how swings in “confidence” in the system may contribute to instability. Our results highlight that the importance of relatively large, well-connected banks in system stability scales more than proportionately with their size: the impact of their collapse arises not only from their connectivity, but also from their effect on confidence in the system. Imposing tougher capital requirements on larger banks than smaller ones can thus enhance the resilience of the system. Moreover, these effects are more pronounced in more concentrated systems, and continue to apply, even when allowing for potential diversification benefits that may be realized by larger banks. We discuss some tentative implications for policy, as well as conceptual analogies in ecosystem stability and in the control of infectious diseases. PMID:23091020
Smart modeling and simulation for complex systems practice and theory
Ren, Fenghui; Zhang, Minjie; Ito, Takayuki; Tang, Xijin
2015-01-01
This book aims to provide a description of these new Artificial Intelligence technologies and approaches to the modeling and simulation of complex systems, as well as an overview of the latest scientific efforts in this field such as the platforms and/or the software tools for smart modeling and simulating complex systems. These tasks are difficult to accomplish using traditional computational approaches due to the complex relationships of components and distributed features of resources, as well as the dynamic work environments. In order to effectively model the complex systems, intelligent technologies such as multi-agent systems and smart grids are employed to model and simulate the complex systems in the areas of ecosystem, social and economic organization, web-based grid service, transportation systems, power systems and evacuation systems.
Advances in dynamic network modeling in complex transportation systems
Ukkusuri, Satish V
2013-01-01
This book focuses on the latest in dynamic network modeling, including route guidance and traffic control in transportation systems and other complex infrastructure networks. Covers dynamic traffic assignment, flow modeling, mobile sensor deployment and more.
Narrowing the gap between network models and real complex systems
Viamontes Esquivel, Alcides
2014-01-01
Simple network models that focus only on graph topology or, at best, basic interactions are often insufficient to capture all the aspects of a dynamic complex system. In this thesis, I explore those limitations, and some concrete methods of resolving them. I argue that, in order to succeed at interpreting and influencing complex systems, we need to take into account slightly more complex parts, interactions and information flows in our models.This thesis supports that affirmation with five a...
Applications of Nonlinear Dynamics Model and Design of Complex Systems
In, Visarath; Palacios, Antonio
2009-01-01
This edited book is aimed at interdisciplinary, device-oriented, applications of nonlinear science theory and methods in complex systems. In particular, applications directed to nonlinear phenomena with space and time characteristics. Examples include: complex networks of magnetic sensor systems, coupled nano-mechanical oscillators, nano-detectors, microscale devices, stochastic resonance in multi-dimensional chaotic systems, biosensors, and stochastic signal quantization. "applications of nonlinear dynamics: model and design of complex systems" brings together the work of scientists and engineers that are applying ideas and methods from nonlinear dynamics to design and fabricate complex systems.
Mathematical Models to Determine Stable Behavior of Complex Systems
Sumin, V. I.; Dushkin, A. V.; Smolentseva, T. E.
2018-05-01
The paper analyzes a possibility to predict functioning of a complex dynamic system with a significant amount of circulating information and a large number of random factors impacting its functioning. Functioning of the complex dynamic system is described as a chaotic state, self-organized criticality and bifurcation. This problem may be resolved by modeling such systems as dynamic ones, without applying stochastic models and taking into account strange attractors.
Hierarchical Models of the Nearshore Complex System
National Research Council Canada - National Science Library
Werner, Brad
2004-01-01
.... This grant was termination funding for the Werner group, specifically aimed at finishing up and publishing research related to synoptic imaging of near shore bathymetry, testing models for beach cusp...
Understanding complex urban systems integrating multidisciplinary data in urban models
Gebetsroither-Geringer, Ernst; Atun, Funda; Werner, Liss
2016-01-01
This book is devoted to the modeling and understanding of complex urban systems. This second volume of Understanding Complex Urban Systems focuses on the challenges of the modeling tools, concerning, e.g., the quality and quantity of data and the selection of an appropriate modeling approach. It is meant to support urban decision-makers—including municipal politicians, spatial planners, and citizen groups—in choosing an appropriate modeling approach for their particular modeling requirements. The contributors to this volume are from different disciplines, but all share the same goal: optimizing the representation of complex urban systems. They present and discuss a variety of approaches for dealing with data-availability problems and finding appropriate modeling approaches—and not only in terms of computer modeling. The selection of articles featured in this volume reflect a broad variety of new and established modeling approaches such as: - An argument for using Big Data methods in conjunction with Age...
Understanding complex urban systems multidisciplinary approaches to modeling
Gurr, Jens; Schmidt, J
2014-01-01
Understanding Complex Urban Systems takes as its point of departure the insight that the challenges of global urbanization and the complexity of urban systems cannot be understood – let alone ‘managed’ – by sectoral and disciplinary approaches alone. But while there has recently been significant progress in broadening and refining the methodologies for the quantitative modeling of complex urban systems, in deepening the theoretical understanding of cities as complex systems, or in illuminating the implications for urban planning, there is still a lack of well-founded conceptual thinking on the methodological foundations and the strategies of modeling urban complexity across the disciplines. Bringing together experts from the fields of urban and spatial planning, ecology, urban geography, real estate analysis, organizational cybernetics, stochastic optimization, and literary studies, as well as specialists in various systems approaches and in transdisciplinary methodologies of urban analysis, the volum...
A Framework for Modeling and Analyzing Complex Distributed Systems
National Research Council Canada - National Science Library
Lynch, Nancy A; Shvartsman, Alex Allister
2005-01-01
Report developed under STTR contract for topic AF04-T023. This Phase I project developed a modeling language and laid a foundation for computational support tools for specifying, analyzing, and verifying complex distributed system designs...
Stability of Rotor Systems: A Complex Modelling Approach
DEFF Research Database (Denmark)
Kliem, Wolfhard; Pommer, Christian; Stoustrup, Jakob
1996-01-01
A large class of rotor systems can be modelled by a complex matrix differential equation of secondorder. The angular velocity of the rotor plays the role of a parameter. We apply the Lyapunov matrix equation in a complex setting and prove two new stability results which are compared...
The semiotics of control and modeling relations in complex systems.
Joslyn, C
2001-01-01
We provide a conceptual analysis of ideas and principles from the systems theory discourse which underlie Pattee's semantic or semiotic closure, which is itself foundational for a school of theoretical biology derived from systems theory and cybernetics, and is now being related to biological semiotics and explicated in the relational biological school of Rashevsky and Rosen. Atomic control systems and models are described as the canonical forms of semiotic organization, sharing measurement relations, but differing topologically in that control systems are circularly and models linearly related to their environments. Computation in control systems is introduced, motivating hierarchical decomposition, hybrid modeling and control systems, and anticipatory or model-based control. The semiotic relations in complex control systems are described in terms of relational constraints, and rules and laws are distinguished as contingent and necessary functional entailments, respectively. Finally, selection as a meta-level of constraint is introduced as the necessary condition for semantic relations in control systems and models.
Systems Engineering Metrics: Organizational Complexity and Product Quality Modeling
Mog, Robert A.
1997-01-01
Innovative organizational complexity and product quality models applicable to performance metrics for NASA-MSFC's Systems Analysis and Integration Laboratory (SAIL) missions and objectives are presented. An intensive research effort focuses on the synergistic combination of stochastic process modeling, nodal and spatial decomposition techniques, organizational and computational complexity, systems science and metrics, chaos, and proprietary statistical tools for accelerated risk assessment. This is followed by the development of a preliminary model, which is uniquely applicable and robust for quantitative purposes. Exercise of the preliminary model using a generic system hierarchy and the AXAF-I architectural hierarchy is provided. The Kendall test for positive dependence provides an initial verification and validation of the model. Finally, the research and development of the innovation is revisited, prior to peer review. This research and development effort results in near-term, measurable SAIL organizational and product quality methodologies, enhanced organizational risk assessment and evolutionary modeling results, and 91 improved statistical quantification of SAIL productivity interests.
Model-based safety architecture framework for complex systems
Schuitemaker, Katja; Rajabali Nejad, Mohammadreza; Braakhuis, J.G.; Podofillini, Luca; Sudret, Bruno; Stojadinovic, Bozidar; Zio, Enrico; Kröger, Wolfgang
2015-01-01
The shift to transparency and rising need of the general public for safety, together with the increasing complexity and interdisciplinarity of modern safety-critical Systems of Systems (SoS) have resulted in a Model-Based Safety Architecture Framework (MBSAF) for capturing and sharing architectural
Modelling methodology for engineering of complex sociotechnical systems
CSIR Research Space (South Africa)
Oosthuizen, R
2014-10-01
Full Text Available Different systems engineering techniques and approaches are applied to design and develop complex sociotechnical systems for complex problems. In a complex sociotechnical system cognitive and social humans use information technology to make sense...
Semiotic aspects of control and modeling relations in complex systems
Energy Technology Data Exchange (ETDEWEB)
Joslyn, C.
1996-08-01
A conceptual analysis of the semiotic nature of control is provided with the goal of elucidating its nature in complex systems. Control is identified as a canonical form of semiotic relation of a system to its environment. As a form of constraint between a system and its environment, its necessary and sufficient conditions are established, and the stabilities resulting from control are distinguished from other forms of stability. These result from the presence of semantic coding relations, and thus the class of control systems is hypothesized to be equivalent to that of semiotic systems. Control systems are contrasted with models, which, while they have the same measurement functions as control systems, do not necessarily require semantic relations because of the lack of the requirement of an interpreter. A hybrid construction of models in control systems is detailed. Towards the goal of considering the nature of control in complex systems, the possible relations among collections of control systems are considered. Powers arguments on conflict among control systems and the possible nature of control in social systems are reviewed, and reconsidered based on our observations about hierarchical control. Finally, we discuss the necessary semantic functions which must be present in complex systems for control in this sense to be present at all.
Parametric Linear Hybrid Automata for Complex Environmental Systems Modeling
Directory of Open Access Journals (Sweden)
Samar Hayat Khan Tareen
2015-07-01
Full Text Available Environmental systems, whether they be weather patterns or predator-prey relationships, are dependent on a number of different variables, each directly or indirectly affecting the system at large. Since not all of these factors are known, these systems take on non-linear dynamics, making it difficult to accurately predict meaningful behavioral trends far into the future. However, such dynamics do not warrant complete ignorance of different efforts to understand and model close approximations of these systems. Towards this end, we have applied a logical modeling approach to model and analyze the behavioral trends and systematic trajectories that these systems exhibit without delving into their quantification. This approach, formalized by René Thomas for discrete logical modeling of Biological Regulatory Networks (BRNs and further extended in our previous studies as parametric biological linear hybrid automata (Bio-LHA, has been previously employed for the analyses of different molecular regulatory interactions occurring across various cells and microbial species. As relationships between different interacting components of a system can be simplified as positive or negative influences, we can employ the Bio-LHA framework to represent different components of the environmental system as positive or negative feedbacks. In the present study, we highlight the benefits of hybrid (discrete/continuous modeling which lead to refinements among the fore-casted behaviors in order to find out which ones are actually possible. We have taken two case studies: an interaction of three microbial species in a freshwater pond, and a more complex atmospheric system, to show the applications of the Bio-LHA methodology for the timed hybrid modeling of environmental systems. Results show that the approach using the Bio-LHA is a viable method for behavioral modeling of complex environmental systems by finding timing constraints while keeping the complexity of the model
Nostradamus 2014 prediction, modeling and analysis of complex systems
Suganthan, Ponnuthurai; Chen, Guanrong; Snasel, Vaclav; Abraham, Ajith; Rössler, Otto
2014-01-01
The prediction of behavior of complex systems, analysis and modeling of its structure is a vitally important problem in engineering, economy and generally in science today. Examples of such systems can be seen in the world around us (including our bodies) and of course in almost every scientific discipline including such “exotic” domains as the earth’s atmosphere, turbulent fluids, economics (exchange rate and stock markets), population growth, physics (control of plasma), information flow in social networks and its dynamics, chemistry and complex networks. To understand such complex dynamics, which often exhibit strange behavior, and to use it in research or industrial applications, it is paramount to create its models. For this purpose there exists a rich spectrum of methods, from classical such as ARMA models or Box Jenkins method to modern ones like evolutionary computation, neural networks, fuzzy logic, geometry, deterministic chaos amongst others. This proceedings book is a collection of accepted ...
Modelling, Estimation and Control of Networked Complex Systems
Chiuso, Alessandro; Frasca, Mattia; Rizzo, Alessandro; Schenato, Luca; Zampieri, Sandro
2009-01-01
The paradigm of complexity is pervading both science and engineering, leading to the emergence of novel approaches oriented at the development of a systemic view of the phenomena under study; the definition of powerful tools for modelling, estimation, and control; and the cross-fertilization of different disciplines and approaches. This book is devoted to networked systems which are one of the most promising paradigms of complexity. It is demonstrated that complex, dynamical networks are powerful tools to model, estimate, and control many interesting phenomena, like agent coordination, synchronization, social and economics events, networks of critical infrastructures, resources allocation, information processing, or control over communication networks. Moreover, it is shown how the recent technological advances in wireless communication and decreasing in cost and size of electronic devices are promoting the appearance of large inexpensive interconnected systems, each with computational, sensing and mobile cap...
On the general procedure for modelling complex ecological systems
International Nuclear Information System (INIS)
He Shanyu.
1987-12-01
In this paper, the principle of a general procedure for modelling complex ecological systems, i.e. the Adaptive Superposition Procedure (ASP) is shortly stated. The result of application of ASP in a national project for ecological regionalization is also described. (author). 3 refs
Predictive modelling of complex agronomic and biological systems.
Keurentjes, Joost J B; Molenaar, Jaap; Zwaan, Bas J
2013-09-01
Biological systems are tremendously complex in their functioning and regulation. Studying the multifaceted behaviour and describing the performance of such complexity has challenged the scientific community for years. The reduction of real-world intricacy into simple descriptive models has therefore convinced many researchers of the usefulness of introducing mathematics into biological sciences. Predictive modelling takes such an approach another step further in that it takes advantage of existing knowledge to project the performance of a system in alternating scenarios. The ever growing amounts of available data generated by assessing biological systems at increasingly higher detail provide unique opportunities for future modelling and experiment design. Here we aim to provide an overview of the progress made in modelling over time and the currently prevalent approaches for iterative modelling cycles in modern biology. We will further argue for the importance of versatility in modelling approaches, including parameter estimation, model reduction and network reconstruction. Finally, we will discuss the difficulties in overcoming the mathematical interpretation of in vivo complexity and address some of the future challenges lying ahead. © 2013 John Wiley & Sons Ltd.
Reduced Complexity Volterra Models for Nonlinear System Identification
Directory of Open Access Journals (Sweden)
Hacıoğlu Rıfat
2001-01-01
Full Text Available A broad class of nonlinear systems and filters can be modeled by the Volterra series representation. However, its practical use in nonlinear system identification is sometimes limited due to the large number of parameters associated with the Volterra filter′s structure. The parametric complexity also complicates design procedures based upon such a model. This limitation for system identification is addressed in this paper using a Fixed Pole Expansion Technique (FPET within the Volterra model structure. The FPET approach employs orthonormal basis functions derived from fixed (real or complex pole locations to expand the Volterra kernels and reduce the number of estimated parameters. That the performance of FPET can considerably reduce the number of estimated parameters is demonstrated by a digital satellite channel example in which we use the proposed method to identify the channel dynamics. Furthermore, a gradient-descent procedure that adaptively selects the pole locations in the FPET structure is developed in the paper.
Bridging Mechanistic and Phenomenological Models of Complex Biological Systems.
Transtrum, Mark K; Qiu, Peng
2016-05-01
The inherent complexity of biological systems gives rise to complicated mechanistic models with a large number of parameters. On the other hand, the collective behavior of these systems can often be characterized by a relatively small number of phenomenological parameters. We use the Manifold Boundary Approximation Method (MBAM) as a tool for deriving simple phenomenological models from complicated mechanistic models. The resulting models are not black boxes, but remain expressed in terms of the microscopic parameters. In this way, we explicitly connect the macroscopic and microscopic descriptions, characterize the equivalence class of distinct systems exhibiting the same range of collective behavior, and identify the combinations of components that function as tunable control knobs for the behavior. We demonstrate the procedure for adaptation behavior exhibited by the EGFR pathway. From a 48 parameter mechanistic model, the system can be effectively described by a single adaptation parameter τ characterizing the ratio of time scales for the initial response and recovery time of the system which can in turn be expressed as a combination of microscopic reaction rates, Michaelis-Menten constants, and biochemical concentrations. The situation is not unlike modeling in physics in which microscopically complex processes can often be renormalized into simple phenomenological models with only a few effective parameters. The proposed method additionally provides a mechanistic explanation for non-universal features of the behavior.
Stability of rotor systems: A complex modelling approach
DEFF Research Database (Denmark)
Kliem, Wolfhard; Pommer, Christian; Stoustrup, Jakob
1998-01-01
The dynamics of a large class of rotor systems can be modelled by a linearized complex matrix differential equation of second order, Mz + (D + iG)(z) over dot + (K + iN)z = 0, where the system matrices M, D, G, K and N are real symmetric. Moreover M and K are assumed to be positive definite and D...... approach applying bounds of appropriate Rayleigh quotients. The rotor systems tested are: a simple Laval rotor, a Laval rotor with additional elasticity and damping in the bearings, and a number of rotor systems with complex symmetric 4 x 4 randomly generated matrices.......The dynamics of a large class of rotor systems can be modelled by a linearized complex matrix differential equation of second order, Mz + (D + iG)(z) over dot + (K + iN)z = 0, where the system matrices M, D, G, K and N are real symmetric. Moreover M and K are assumed to be positive definite and D...
Predicting the future completing models of observed complex systems
Abarbanel, Henry
2013-01-01
Predicting the Future: Completing Models of Observed Complex Systems provides a general framework for the discussion of model building and validation across a broad spectrum of disciplines. This is accomplished through the development of an exact path integral for use in transferring information from observations to a model of the observed system. Through many illustrative examples drawn from models in neuroscience, fluid dynamics, geosciences, and nonlinear electrical circuits, the concepts are exemplified in detail. Practical numerical methods for approximate evaluations of the path integral are explored, and their use in designing experiments and determining a model's consistency with observations is investigated. Using highly instructive examples, the problems of data assimilation and the means to treat them are clearly illustrated. This book will be useful for students and practitioners of physics, neuroscience, regulatory networks, meteorology and climate science, network dynamics, fluid dynamics, and o...
Socio-Environmental Resilience and Complex Urban Systems Modeling
Deal, Brian; Petri, Aaron; Pan, Haozhi; Goldenberg, Romain; Kalantari, Zahra; Cvetkovic, Vladimir
2017-04-01
The increasing pressure of climate change has inspired two normative agendas; socio-technical transitions and socio-ecological resilience, both sharing a complex-systems epistemology (Gillard et al. 2016). Socio-technical solutions include a continuous, massive data gathering exercise now underway in urban places under the guise of developing a 'smart'(er) city. This has led to the creation of data-rich environments where large data sets have become central to monitoring and forming a response to anomalies. Some have argued that these kinds of data sets can help in planning for resilient cities (Norberg and Cumming 2008; Batty 2013). In this paper, we focus on a more nuanced, ecologically based, socio-environmental perspective of resilience planning that is often given less consideration. Here, we broadly discuss (and model) the tightly linked, mutually influenced, social and biophysical subsystems that are critical for understanding urban resilience. We argue for the need to incorporate these sub system linkages into the resilience planning lexicon through the integration of systems models and planning support systems. We make our case by first providing a context for urban resilience from a socio-ecological and planning perspective. We highlight the data needs for this type of resilient planning and compare it to currently collected data streams in various smart city efforts. This helps to define an approach for operationalizing socio-environmental resilience planning using robust systems models and planning support systems. For this, we draw from our experiences in coupling a spatio-temporal land use model (the Landuse Evolution and impact Assessment Model (LEAM)) with water quality and quantity models in Stockholm Sweden. We describe the coupling of these systems models using a robust Planning Support System (PSS) structural framework. We use the coupled model simulations and PSS to analyze the connection between urban land use transformation (social) and water
A computational framework for modeling targets as complex adaptive systems
Santos, Eugene; Santos, Eunice E.; Korah, John; Murugappan, Vairavan; Subramanian, Suresh
2017-05-01
Modeling large military targets is a challenge as they can be complex systems encompassing myriad combinations of human, technological, and social elements that interact, leading to complex behaviors. Moreover, such targets have multiple components and structures, extending across multiple spatial and temporal scales, and are in a state of change, either in response to events in the environment or changes within the system. Complex adaptive system (CAS) theory can help in capturing the dynamism, interactions, and more importantly various emergent behaviors, displayed by the targets. However, a key stumbling block is incorporating information from various intelligence, surveillance and reconnaissance (ISR) sources, while dealing with the inherent uncertainty, incompleteness and time criticality of real world information. To overcome these challenges, we present a probabilistic reasoning network based framework called complex adaptive Bayesian Knowledge Base (caBKB). caBKB is a rigorous, overarching and axiomatic framework that models two key processes, namely information aggregation and information composition. While information aggregation deals with the union, merger and concatenation of information and takes into account issues such as source reliability and information inconsistencies, information composition focuses on combining information components where such components may have well defined operations. Since caBKBs can explicitly model the relationships between information pieces at various scales, it provides unique capabilities such as the ability to de-aggregate and de-compose information for detailed analysis. Using a scenario from the Network Centric Operations (NCO) domain, we will describe how our framework can be used for modeling targets with a focus on methodologies for quantifying NCO performance metrics.
Modelling of the quenching process in complex superconducting magnet systems
International Nuclear Information System (INIS)
Hagedorn, D.; Rodriguez-Mateos, F.
1992-01-01
This paper reports that the superconducting twin bore dipole magnet for the proposed Large Hadron Collider (LHC) at CERN shows a complex winding structure consisting of eight compact layers each of them electromagnetically and thermally coupled with the others. This magnet is only one part of an electrical circuit; test and operation conditions are characterized by different circuits. In order to study the quenching process in this complex system, design adequate protection schemes, and provide a basis for the dimensioning of protection devices such as heaters, current breakers and dump resistors, a general simulation tool called QUABER has been developed using the analog system analysis program SABER. A complete set of electro-thermal models has been crated for the propagation of normal regions. Any network extension or modification is easy to implement without rewriting the whole set of differential equations
Equation-free model reduction for complex dynamical systems
International Nuclear Information System (INIS)
Le Maitre, O. P.; Mathelin, L.; Le Maitre, O. P.
2010-01-01
This paper presents a reduced model strategy for simulation of complex physical systems. A classical reduced basis is first constructed relying on proper orthogonal decomposition of the system. Then, unlike the alternative approaches, such as Galerkin projection schemes for instance, an equation-free reduced model is constructed. It consists in the determination of an explicit transformation, or mapping, for the evolution over a coarse time-step of the projection coefficients of the system state on the reduced basis. The mapping is expressed as an explicit polynomial transformation of the projection coefficients and is computed once and for all in a pre-processing stage using the detailed model equation of the system. The reduced system can then be advanced in time by successive applications of the mapping. The CPU cost of the method lies essentially in the mapping approximation which is performed offline, in a parallel fashion, and only once. Subsequent application of the mapping to perform a time-integration is carried out at a low cost thanks to its explicit character. Application of the method is considered for the 2-D flow around a circular cylinder. We investigate the effectiveness of the reduced model in rendering the dynamics for both asymptotic state and transient stages. It is shown that the method leads to a stable and accurate time-integration for only a fraction of the cost of a detailed simulation, provided that the mapping is properly approximated and the reduced basis remains relevant for the dynamics investigated. (authors)
Energy Technology Data Exchange (ETDEWEB)
Goldsby, Michael E.; Mayo, Jackson R.; Bhattacharyya, Arnab (Massachusetts Institute of Technology, Cambridge, MA); Armstrong, Robert C.; Vanderveen, Keith
2008-09-01
The goal of this research was to examine foundational methods, both computational and theoretical, that can improve the veracity of entity-based complex system models and increase confidence in their predictions for emergent behavior. The strategy was to seek insight and guidance from simplified yet realistic models, such as cellular automata and Boolean networks, whose properties can be generalized to production entity-based simulations. We have explored the usefulness of renormalization-group methods for finding reduced models of such idealized complex systems. We have prototyped representative models that are both tractable and relevant to Sandia mission applications, and quantified the effect of computational renormalization on the predictive accuracy of these models, finding good predictivity from renormalized versions of cellular automata and Boolean networks. Furthermore, we have theoretically analyzed the robustness properties of certain Boolean networks, relevant for characterizing organic behavior, and obtained precise mathematical constraints on systems that are robust to failures. In combination, our results provide important guidance for more rigorous construction of entity-based models, which currently are often devised in an ad-hoc manner. Our results can also help in designing complex systems with the goal of predictable behavior, e.g., for cybersecurity.
Integrated modeling tool for performance engineering of complex computer systems
Wright, Gary; Ball, Duane; Hoyt, Susan; Steele, Oscar
1989-01-01
This report summarizes Advanced System Technologies' accomplishments on the Phase 2 SBIR contract NAS7-995. The technical objectives of the report are: (1) to develop an evaluation version of a graphical, integrated modeling language according to the specification resulting from the Phase 2 research; and (2) to determine the degree to which the language meets its objectives by evaluating ease of use, utility of two sets of performance predictions, and the power of the language constructs. The technical approach followed to meet these objectives was to design, develop, and test an evaluation prototype of a graphical, performance prediction tool. The utility of the prototype was then evaluated by applying it to a variety of test cases found in the literature and in AST case histories. Numerous models were constructed and successfully tested. The major conclusion of this Phase 2 SBIR research and development effort is that complex, real-time computer systems can be specified in a non-procedural manner using combinations of icons, windows, menus, and dialogs. Such a specification technique provides an interface that system designers and architects find natural and easy to use. In addition, PEDESTAL's multiview approach provides system engineers with the capability to perform the trade-offs necessary to produce a design that meets timing performance requirements. Sample system designs analyzed during the development effort showed that models could be constructed in a fraction of the time required by non-visual system design capture tools.
Sulis, William H
2017-10-01
Walter Freeman III pioneered the application of nonlinear dynamical systems theories and methodologies in his work on mesoscopic brain dynamics.Sadly, mainstream psychology and psychiatry still cling to linear correlation based data analysis techniques, which threaten to subvert the process of experimentation and theory building. In order to progress, it is necessary to develop tools capable of managing the stochastic complexity of complex biopsychosocial systems, which includes multilevel feedback relationships, nonlinear interactions, chaotic dynamics and adaptability. In addition, however, these systems exhibit intrinsic randomness, non-Gaussian probability distributions, non-stationarity, contextuality, and non-Kolmogorov probabilities, as well as the absence of mean and/or variance and conditional probabilities. These properties and their implications for statistical analysis are discussed. An alternative approach, the Process Algebra approach, is described. It is a generative model, capable of generating non-Kolmogorov probabilities. It has proven useful in addressing fundamental problems in quantum mechanics and in the modeling of developing psychosocial systems.
Automated sensitivity analysis: New tools for modeling complex dynamic systems
International Nuclear Information System (INIS)
Pin, F.G.
1987-01-01
Sensitivity analysis is an established methodology used by researchers in almost every field to gain essential insight in design and modeling studies and in performance assessments of complex systems. Conventional sensitivity analysis methodologies, however, have not enjoyed the widespread use they deserve considering the wealth of information they can provide, partly because of their prohibitive cost or the large initial analytical investment they require. Automated systems have recently been developed at ORNL to eliminate these drawbacks. Compilers such as GRESS and EXAP now allow automatic and cost effective calculation of sensitivities in FORTRAN computer codes. In this paper, these and other related tools are described and their impact and applicability in the general areas of modeling, performance assessment and decision making for radioactive waste isolation problems are discussed
The utility of Earth system Models of Intermediate Complexity
Weber, S.L.
2010-01-01
Intermediate-complexity models are models which describe the dynamics of the atmosphere and/or ocean in less detail than conventional General Circulation Models (GCMs). At the same time, they go beyond the approach taken by atmospheric Energy Balance Models (EBMs) or ocean box models by
A modeling process to understand complex system architectures
Robinson, Santiago Balestrini
2009-12-01
In recent decades, several tools have been developed by the armed forces, and their contractors, to test the capability of a force. These campaign level analysis tools, often times characterized as constructive simulations are generally expensive to create and execute, and at best they are extremely difficult to verify and validate. This central observation, that the analysts are relying more and more on constructive simulations to predict the performance of future networks of systems, leads to the two central objectives of this thesis: (1) to enable the quantitative comparison of architectures in terms of their ability to satisfy a capability without resorting to constructive simulations, and (2) when constructive simulations must be created, to quantitatively determine how to spend the modeling effort amongst the different system classes. The first objective led to Hypothesis A, the first main hypotheses, which states that by studying the relationships between the entities that compose an architecture, one can infer how well it will perform a given capability. The method used to test the hypothesis is based on two assumptions: (1) the capability can be defined as a cycle of functions, and that it (2) must be possible to estimate the probability that a function-based relationship occurs between any two types of entities. If these two requirements are met, then by creating random functional networks, different architectures can be compared in terms of their ability to satisfy a capability. In order to test this hypothesis, a novel process for creating representative functional networks of large-scale system architectures was developed. The process, named the Digraph Modeling for Architectures (DiMA), was tested by comparing its results to those of complex constructive simulations. Results indicate that if the inputs assigned to DiMA are correct (in the tests they were based on time-averaged data obtained from the ABM), DiMA is able to identify which of any two
Green IT engineering concepts, models, complex systems architectures
Kondratenko, Yuriy; Kacprzyk, Janusz
2017-01-01
This volume provides a comprehensive state of the art overview of a series of advanced trends and concepts that have recently been proposed in the area of green information technologies engineering as well as of design and development methodologies for models and complex systems architectures and their intelligent components. The contributions included in the volume have their roots in the authors’ presentations, and vivid discussions that have followed the presentations, at a series of workshop and seminars held within the international TEMPUS-project GreenCo project in United Kingdom, Italy, Portugal, Sweden and the Ukraine, during 2013-2015 and at the 1st - 5th Workshops on Green and Safe Computing (GreenSCom) held in Russia, Slovakia and the Ukraine. The book presents a systematic exposition of research on principles, models, components and complex systems and a description of industry- and society-oriented aspects of the green IT engineering. A chapter-oriented structure has been adopted for this book ...
Complex system modelling and control through intelligent soft computations
Azar, Ahmad
2015-01-01
The book offers a snapshot of the theories and applications of soft computing in the area of complex systems modeling and control. It presents the most important findings discussed during the 5th International Conference on Modelling, Identification and Control, held in Cairo, from August 31-September 2, 2013. The book consists of twenty-nine selected contributions, which have been thoroughly reviewed and extended before their inclusion in the volume. The different chapters, written by active researchers in the field, report on both current theories and important applications of soft-computing. Besides providing the readers with soft-computing fundamentals, and soft-computing based inductive methodologies/algorithms, the book also discusses key industrial soft-computing applications, as well as multidisciplinary solutions developed for a variety of purposes, like windup control, waste management, security issues, biomedical applications and many others. It is a perfect reference guide for graduate students, r...
Can Models Capture the Complexity of the Systems Engineering Process?
Boppana, Krishna; Chow, Sam; de Weck, Olivier L.; Lafon, Christian; Lekkakos, Spyridon D.; Lyneis, James; Rinaldi, Matthew; Wang, Zhiyong; Wheeler, Paul; Zborovskiy, Marat; Wojcik, Leonard A.
Many large-scale, complex systems engineering (SE) programs have been problematic; a few examples are listed below (Bar-Yam, 2003 and Cullen, 2004), and many others have been late, well over budget, or have failed: Hilton/Marriott/American Airlines system for hotel reservations and flights; 1988-1992; 125 million; "scrapped"
Complex groundwater flow systems as traveling agent models
Directory of Open Access Journals (Sweden)
Oliver López Corona
2014-10-01
Full Text Available Analyzing field data from pumping tests, we show that as with many other natural phenomena, groundwater flow exhibits complex dynamics described by 1/f power spectrum. This result is theoretically studied within an agent perspective. Using a traveling agent model, we prove that this statistical behavior emerges when the medium is complex. Some heuristic reasoning is provided to justify both spatial and dynamic complexity, as the result of the superposition of an infinite number of stochastic processes. Even more, we show that this implies that non-Kolmogorovian probability is needed for its study, and provide a set of new partial differential equations for groundwater flow.
Teleconnections in complex human-Earth system models
Calvin, K. V.; Edmonds, J.
2017-12-01
Human systems and physical Earth systems are closely coupled and interact in complex ways that are sometimes surprising. This presentation discusses a few examples of system interactions. We consider the coupled energy-water-land-economy systems. We show how reductions in fossil fuel emissions are inversely coupled to land rents, food prices and deforestation. We discuss how water shortages in one part of the world is propagated to other distant parts of the world. We discuss the sensitivity of international trade patterns to energy and land systems technology and markets, and the potentially unanticipated results that can emerge.
Computer modeling of properties of complex molecular systems
Energy Technology Data Exchange (ETDEWEB)
Kulkova, E.Yu. [Moscow State University of Technology “STANKIN”, Vadkovsky per., 1, Moscow 101472 (Russian Federation); Khrenova, M.G.; Polyakov, I.V. [Lomonosov Moscow State University, Chemistry Department, Leninskie Gory 1/3, Moscow 119991 (Russian Federation); Nemukhin, A.V. [Lomonosov Moscow State University, Chemistry Department, Leninskie Gory 1/3, Moscow 119991 (Russian Federation); N.M. Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Kosygina 4, Moscow 119334 (Russian Federation)
2015-03-10
Large molecular aggregates present important examples of strongly nonhomogeneous systems. We apply combined quantum mechanics / molecular mechanics approaches that assume treatment of a part of the system by quantum-based methods and the rest of the system with conventional force fields. Herein we illustrate these computational approaches by two different examples: (1) large-scale molecular systems mimicking natural photosynthetic centers, and (2) components of prospective solar cells containing titan dioxide and organic dye molecules. We demonstrate that modern computational tools are capable to predict structures and spectra of such complex molecular aggregates.
Risk Modeling of Interdependent Complex Systems of Systems: Theory and Practice.
Haimes, Yacov Y
2018-01-01
The emergence of the complexity characterizing our systems of systems (SoS) requires a reevaluation of the way we model, assess, manage, communicate, and analyze the risk thereto. Current models for risk analysis of emergent complex SoS are insufficient because too often they rely on the same risk functions and models used for single systems. These models commonly fail to incorporate the complexity derived from the networks of interdependencies and interconnectedness (I-I) characterizing SoS. There is a need to reevaluate currently practiced risk analysis to respond to this reality by examining, and thus comprehending, what makes emergent SoS complex. The key to evaluating the risk to SoS lies in understanding the genesis of characterizing I-I of systems manifested through shared states and other essential entities within and among the systems that constitute SoS. The term "essential entities" includes shared decisions, resources, functions, policies, decisionmakers, stakeholders, organizational setups, and others. This undertaking can be accomplished by building on state-space theory, which is fundamental to systems engineering and process control. This article presents a theoretical and analytical framework for modeling the risk to SoS with two case studies performed with the MITRE Corporation and demonstrates the pivotal contributions made by shared states and other essential entities to modeling and analysis of the risk to complex SoS. A third case study highlights the multifarious representations of SoS, which require harmonizing the risk analysis process currently applied to single systems when applied to complex SoS. © 2017 Society for Risk Analysis.
Model order reduction for complex high-tech systems
Lutowska, A.; Hochstenbach, M.E.; Schilders, W.H.A.; Michielsen, B.; Poirier, J.R.
2012-01-01
This paper presents a computationally efficient model order reduction (MOR) technique for interconnected systems. This MOR technique preserves block structures and zero blocks and exploits separate MOR approximations for the individual sub-systems in combination with low rank approximations for the
Siegfried, Robert
2014-01-01
Robert Siegfried presents a framework for efficient agent-based modeling and simulation of complex systems. He compares different approaches for describing structure and dynamics of agent-based models in detail. Based on this evaluation the author introduces the "General Reference Model for Agent-based Modeling and Simulation" (GRAMS). Furthermore he presents parallel and distributed simulation approaches for execution of agent-based models -from small scale to very large scale. The author shows how agent-based models may be executed by different simulation engines that utilize underlying hard
An advanced modelling tool for simulating complex river systems.
Trancoso, Ana Rosa; Braunschweig, Frank; Chambel Leitão, Pedro; Obermann, Matthias; Neves, Ramiro
2009-04-01
The present paper describes MOHID River Network (MRN), a 1D hydrodynamic model for river networks as part of MOHID Water Modelling System, which is a modular system for the simulation of water bodies (hydrodynamics and water constituents). MRN is capable of simulating water quality in the aquatic and benthic phase and its development was especially focused on the reproduction of processes occurring in temporary river networks (flush events, pools formation, and transmission losses). Further, unlike many other models, it allows the quantification of settled materials at the channel bed also over periods when the river falls dry. These features are very important to secure mass conservation in highly varying flows of temporary rivers. The water quality models existing in MOHID are base on well-known ecological models, such as WASP and ERSEM, the latter allowing explicit parameterization of C, N, P, Si, and O cycles. MRN can be coupled to the basin model, MOHID Land, with computes runoff and porous media transport, allowing for the dynamic exchange of water and materials between the river and surroundings, or it can be used as a standalone model, receiving discharges at any specified nodes (ASCII files of time series with arbitrary time step). These features account for spatial gradients in precipitation which can be significant in Mediterranean-like basins. An interface has been already developed for SWAT basin model.
Modelling of complex heat transfer systems by the coupling method
Energy Technology Data Exchange (ETDEWEB)
Bacot, P.; Bonfils, R.; Neveu, A.; Ribuot, J. (Centre d' Energetique de l' Ecole des Mines de Paris, 75 (France))
1985-04-01
The coupling method proposed here is designed to reduce the size of matrices which appear in the modelling of heat transfer systems. It consists in isolating the elements that can be modelled separately, and among the input variables of a component, identifying those which will couple it to another component. By grouping these types of variable, one can thus identify a so-called coupling matrix of reduced size, and relate it to the overall system. This matrix allows the calculation of the coupling temperatures as a function of external stresses, and of the state of the overall system at the previous instant. The internal temperatures of the components are determined from for previous ones. Two examples of applications are presented, one concerning a dwelling unit, and the second a solar water heater.
Stochastic Modelling and Optimization of Complex Infrastructure Systems
DEFF Research Database (Denmark)
Thoft-Christensen, Palle
In this paper it is shown that recent progress in stochastic modelling and optimization in combination with advanced computer systems has now made it possible to improve the design and the maintenance strategies for infrastructure systems. The paper concentrates on highway networks and single large...... bridges. united states has perhaps the largest highway networks in the world with more than 0.5 million highway bridges; see Chase, S.B. 1999. About 40% of these bridges are considered deficient and more than $50 billion is estimated needed to correct the deficiencies; see Roberts, J.E. 2001...
DEFF Research Database (Denmark)
Eby, M.; Weaver, A. J.; Alexander, K.
2013-01-01
Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE...... and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20...
Energy Technology Data Exchange (ETDEWEB)
Kremers, Enrique
2013-10-01
Complexity science aims to better understand the processes of both natural and man-made systems which are composed of many interacting entities at different scales. A disaggregated approach is proposed for simulating electricity systems, by using agent-based models coupled to continuous ones. The approach can help in acquiring a better understanding of the operation of the system itself, e.g. on emergent phenomena or scale effects; as well as in the improvement and design of future smart grids.
Development of structural model of adaptive training complex in ergatic systems for professional use
Obukhov, A. D.; Dedov, D. L.; Arkhipov, A. E.
2018-03-01
The article considers the structural model of the adaptive training complex (ATC), which reflects the interrelations between the hardware, software and mathematical model of ATC and describes the processes in this subject area. The description of the main components of software and hardware complex, their interaction and functioning within the common system are given. Also the article scrutinizers a brief description of mathematical models of personnel activity, a technical system and influences, the interactions of which formalize the regularities of ATC functioning. The studies of main objects of training complexes and connections between them will make it possible to realize practical implementation of ATC in ergatic systems for professional use.
Small System dynamics models for big issues : Triple jump towards real-world complexity
Pruyt, E.
2013-01-01
System Dynamics (SD) is a method to describe, model, simulate and analyze dynamically complex issues and/or systems in terms of the processes, information, organizational boundaries and strategies. Quantitative SD modeling, simulation and analysis facilitates the (re)design of systems and design of
Computerized models : tools for assessing the future of complex systems?
Ittersum, van M.K.; Sterk, B.
2015-01-01
Models are commonly used to make decisions. At some point all of us will have employed a mental model, that is, a simplification of reality, in an everyday situation. For instance, when we want to make the best decision for the environment and consider whether to buy our vegetables in a large
Modeling of Complex Adaptive Systems in Air Operations
National Research Council Canada - National Science Library
Busch, Timothy E; Trevisani, Dawn A
2006-01-01
.... Model predictive control theory provides the basis for this investigation. Given some set of objectives the military commander must devise a sequence of actions that transform the current state to the desired one...
Using multi-criteria analysis of simulation models to understand complex biological systems
Maureen C. Kennedy; E. David. Ford
2011-01-01
Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...
Model-Based Optimal Experimental Design for Complex Physical Systems
2015-12-03
choose the belief state to be the posterior xk,b = θ|d0, y0, . . . , dk−1, yk−1, system dynamics to be Bayes’ theorem , and terminal reward to be the...Kullback-Leibler (KL) divergence from the final posterior to the initial prior—an information- measuring criterion. 5 DISTRIBUTION A: Distribution
Visualizing project management: models and frameworks for mastering complex systems
National Research Council Canada - National Science Library
Forsberg, Kevin; Mooz, Hal; Cotterman, Howard
2005-01-01
...- and beyond that on parameters such as return on investment, market acceptance, or sustainability. Anyone who has lived with the space program, or any other hightech industrial product development, can immediately appreciate this acclaimed book. It addresses and "visualizes" the multidimensional interactions of project management and systems engineering i...
Watershed System Model: The Essentials to Model Complex Human-Nature System at the River Basin Scale
Li, Xin; Cheng, Guodong; Lin, Hui; Cai, Ximing; Fang, Miao; Ge, Yingchun; Hu, Xiaoli; Chen, Min; Li, Weiyue
2018-03-01
Watershed system models are urgently needed to understand complex watershed systems and to support integrated river basin management. Early watershed modeling efforts focused on the representation of hydrologic processes, while the next-generation watershed models should represent the coevolution of the water-land-air-plant-human nexus in a watershed and provide capability of decision-making support. We propose a new modeling framework and discuss the know-how approach to incorporate emerging knowledge into integrated models through data exchange interfaces. We argue that the modeling environment is a useful tool to enable effective model integration, as well as create domain-specific models of river basin systems. The grand challenges in developing next-generation watershed system models include but are not limited to providing an overarching framework for linking natural and social sciences, building a scientifically based decision support system, quantifying and controlling uncertainties, and taking advantage of new technologies and new findings in the various disciplines of watershed science. The eventual goal is to build transdisciplinary, scientifically sound, and scale-explicit watershed system models that are to be codesigned by multidisciplinary communities.
Catastrophes in nature and society mathematical modeling of complex systems
Khlebopros, Rem G; Fet, Abram I
2007-01-01
Many people are concerned about crises leading to disasters in nature, in social and economic life. The book offers a popular account of the causative mechanisms of critical states and breakdown in a broad range of natural and cultural systems - which obey the same laws - and thus makes the reader aware of the origin of catastrophic events and the ways to avoid and mitigate their negative consequences. The authors apply a single mathematical approach to investigate the revolt of cancer cells that destroy living organisms and population outbreaks that upset natural ecosystems, the balance between biosphere and global climate interfered lately by industry, the driving mechanisms of market and related economic and social phenomena, as well as the electoral system the proper use of which is an arduous accomplishment of democracy.
Hierarchical modeling and robust synthesis for the preliminary design of large scale complex systems
Koch, Patrick Nathan
Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: (1) Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis, (2) Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration, and (3) Noise modeling techniques for implementing robust preliminary design when approximate models are employed. The method developed and associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system; the turbofan system-level problem is partitioned into engine cycle and configuration design and a compressor module is integrated for more detailed subsystem-level design exploration, improving system evaluation.
Use of probabilistic relational model (PRM) for dependability analysis of complex systems
Medina-Oliva , Gabriela; Weber , Philippe; Levrat , Eric; Iung , Benoît
2010-01-01
International audience; This paper proposes a methodology to develop a aided decision-making tool for assessing the dependability and performances (i.e. reliability) of an industrial system. This tool is built on a model based on a new formalism, called the probabilistic relational model (PRM) which is adapted to deal with large and complex systems. The model is formalized from functional, dysfunctional and informational studies of the technical industrial systems. An application of this meth...
Mathematical modeling of complexing in the scandium-salicylic acid-isoamyl alcohol system
International Nuclear Information System (INIS)
Evseev, A.M.; Smirnova, N.S.; Fadeeva, V.I.; Tikhomirova, T.I.; Kir'yanov, Yu.A.
1984-01-01
Mathematical modeling of an equilibrium multicomponent physicochemical system for extraction of Sc salicylate complexes by isoamyl alcohol was conducted. To calculate the equilibrium concentrations of Sc complexes different with respect to the content and composition, the system of nonlinear algebraic mass balance equations was solved. Experimental data on the extraction of Sc salicylates by isoamyl alcohol versus the pH of the solution at a constant Sc concentration and different concentration of salicylate-ions were used for construction of the mathematical model. The stability constants of ScHSal 2+ , Sc(HSal) 3 , ScOH(HSal) 2 , ScoH(HSal) 2 complexes were calculated
Directory of Open Access Journals (Sweden)
Олег Богданович ЗАЧКО
2016-03-01
Full Text Available The methods and models of safety-oriented project management of the development of complex systems are proposed resulting from the convergence of existing approaches in project management in contrast to the mechanism of value-oriented management. A cognitive model of safety oriented project management of the development of complex systems is developed, which provides a synergistic effect that is to move the system from the original (pre condition in an optimal one from the viewpoint of life safety - post-project state. The approach of assessment the project complexity is proposed, which consists in taking into account the seasonal component of a time characteristic of life cycles of complex organizational and technical systems with occupancy. This enabled to take into account the seasonal component in simulation models of life cycle of the product operation in complex organizational and technical system, modeling the critical points of operation of systems with occupancy, which forms a new methodology for safety-oriented management of projects, programs and portfolios of projects with the formalization of the elements of complexity.
OPERATING OF MOBILE MACHINE UNITS SYSTEM USING THE MODEL OF MULTICOMPONENT COMPLEX MOVEMENT
Directory of Open Access Journals (Sweden)
A. Lebedev
2015-07-01
Full Text Available To solve the problems of mobile machine units system operating it is proposed using complex multi-component (composite movement physical models. Implementation of the proposed method is possible by creating of automatic operating systems of fuel supply to the engines using linear accelerometers. Some examples to illustrate the proposed method are offered.
Operating of mobile machine units system using the model of multicomponent complex movement
A. Lebedev; R. Kaidalov; N. Artiomov; M. Shulyak; M. Podrigalo; D. Abramov; D. Klets
2015-01-01
To solve the problems of mobile machine units system operating it is proposed using complex multi-component (composite) movement physical models. Implementation of the proposed method is possible by creating of automatic operating systems of fuel supply to the engines using linear accelerometers. Some examples to illustrate the proposed method are offered.
New approaches in agent-based modeling of complex financial systems
Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei
2017-12-01
Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.
Energy Technology Data Exchange (ETDEWEB)
Tsao, Jeffrey Y. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Trucano, Timothy G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kleban, Stephen D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Naugle, Asmeret Bier [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Verzi, Stephen Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Swiler, Laura Painton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Johnson, Curtis M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Smith, Mark A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Flanagan, Tatiana Paz [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vugrin, Eric D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gabert, Kasimir Georg [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lave, Matthew Samuel [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Chen, Wei [Northwestern Univ., Evanston, IL (United States); DeLaurentis, Daniel [Purdue Univ., West Lafayette, IN (United States); Hubler, Alfred [Univ. of Illinois, Urbana, IL (United States); Oberkampf, Bill [WLO Consulting, Austin, TX (United States)
2016-08-01
This report contains the written footprint of a Sandia-hosted workshop held in Albuquerque, New Mexico, June 22-23, 2016 on “Complex Systems Models and Their Applications: Towards a New Science of Verification, Validation and Uncertainty Quantification,” as well as of pre-work that fed into the workshop. The workshop’s intent was to explore and begin articulating research opportunities at the intersection between two important Sandia communities: the complex systems (CS) modeling community, and the verification, validation and uncertainty quantification (VVUQ) community The overarching research opportunity (and challenge) that we ultimately hope to address is: how can we quantify the credibility of knowledge gained from complex systems models, knowledge that is often incomplete and interim, but will nonetheless be used, sometimes in real-time, by decision makers?
Models, methods and software tools for building complex adaptive traffic systems
International Nuclear Information System (INIS)
Alyushin, S.A.
2011-01-01
The paper studies the modern methods and tools to simulate the behavior of complex adaptive systems (CAS), the existing systems of traffic modeling in simulators and their characteristics; proposes requirements for assessing the suitability of the system to simulate the CAS behavior in simulators. The author has developed a model of adaptive agent representation and its functioning environment to meet certain requirements set above, and has presented methods of agents' interactions and methods of conflict resolution in simulated traffic situations. A simulation system realizing computer modeling for simulating the behavior of CAS in traffic situations has been created [ru
System Testability Analysis for Complex Electronic Devices Based on Multisignal Model
International Nuclear Information System (INIS)
Long, B; Tian, S L; Huang, J G
2006-01-01
It is necessary to consider the system testability problems for electronic devices during their early design phase because modern electronic devices become smaller and more compositive while their function and structure are more complex. Multisignal model, combining advantage of structure model and dependency model, is used to describe the fault dependency relationship for the complex electronic devices, and the main testability indexes (including optimal test program, fault detection rate, fault isolation rate, etc.) to evaluate testability and corresponding algorithms are given. The system testability analysis process is illustrated for USB-GPIB interface circuit with TEAMS toolbox. The experiment results show that the modelling method is simple, the computation speed is rapid and this method has important significance to improve diagnostic capability for complex electronic devices
Directory of Open Access Journals (Sweden)
Sergey Viktorovich Kuznetsov
2017-01-01
Full Text Available Modern aircraft are equipped with complicated systems and complexes of avionics. Aircraft and its avionics tech- nical operation process is observed as a process with changing of operation states. Mathematical models of avionics pro- cesses and systems of technical operation are represented as Markov chains, Markov and semi-Markov processes. The pur- pose is to develop the graph-models of avionics technical operation processes, describing their work in flight, as well as during maintenance on the ground in the various systems of technical operation. The graph-models of processes and sys- tems of on-board complexes and functional avionics systems in flight are proposed. They are based on the state tables. The models are specified for the various technical operation systems: the system with control of the reliability level, the system with parameters control and the system with resource control. The events, which cause the avionics complexes and func- tional systems change their technical state, are failures and faults of built-in test equipment. Avionics system of technical operation with reliability level control is applicable for objects with constant or slowly varying in time failure rate. Avion- ics system of technical operation with resource control is mainly used for objects with increasing over time failure rate. Avionics system of technical operation with parameters control is used for objects with increasing over time failure rate and with generalized parameters, which can provide forecasting and assign the borders of before-fail technical states. The pro- posed formal graphical approach avionics complexes and systems models designing is the basis for models and complex systems and facilities construction, both for a single aircraft and for an airline aircraft fleet, or even for the entire aircraft fleet of some specific type. The ultimate graph-models for avionics in various systems of technical operation permit the beginning of
Jetha, Arif; Pransky, Glenn; Hettinger, Lawrence J
2016-01-01
Work disability (WD) is characterized by variable and occasionally undesirable outcomes. The underlying determinants of WD outcomes include patterns of dynamic relationships among health, personal, organizational and regulatory factors that have been challenging to characterize, and inadequately represented by contemporary WD models. System dynamics modeling (SDM) methodology applies a sociotechnical systems thinking lens to view WD systems as comprising a range of influential factors linked by feedback relationships. SDM can potentially overcome limitations in contemporary WD models by uncovering causal feedback relationships, and conceptualizing dynamic system behaviors. It employs a collaborative and stakeholder-based model building methodology to create a visual depiction of the system as a whole. SDM can also enable researchers to run dynamic simulations to provide evidence of anticipated or unanticipated outcomes that could result from policy and programmatic intervention. SDM may advance rehabilitation research by providing greater insights into the structure and dynamics of WD systems while helping to understand inherent complexity. Challenges related to data availability, determining validity, and the extensive time and technical skill requirements for model building may limit SDM's use in the field and should be considered. Contemporary work disability (WD) models provide limited insight into complexity associated with WD processes. System dynamics modeling (SDM) has the potential to capture complexity through a stakeholder-based approach that generates a simulation model consisting of multiple feedback loops. SDM may enable WD researchers and practitioners to understand the structure and behavior of the WD system as a whole, and inform development of improved strategies to manage straightforward and complex WD cases.
Modeling of Complex Structures for the Ship's Power Complex Using Xilinx System
Directory of Open Access Journals (Sweden)
Chernyi Sergei
2015-02-01
Full Text Available One of the most essential tasks for a number of systems of the automatic controls in the autonomous electric power systems of the water transport is accurate calculation of variable harmonic components in the non-sinusoidal signal. In the autonomous electric power systems operating with full semiconductor capacity, the forms of line currents and voltages are greatly distorted, and generator devices generate voltage with inconsistent frequency, phase and amplitude. It makes calculation of harmonic composition of the distorted signals be a non-trivial task. The present paper provides a mathematical set for solution of the outlined problem including the realization in the discrete form. The simplicity and efficiency of the system proposed make possible to perform its practical realization with the help of cheap FPGA. The test of the developed system has been performed in the medium Matlab.
Brodsky, Yu. I.
2015-01-01
The work is devoted to the application of Bourbaki's structure theory to substantiate the synthesis of simulation models of complex multicomponent systems, where every component may be a complex system itself. An application of the Bourbaki's structure theory offers a new approach to the design and computer implementation of simulation models of complex multicomponent systems—model synthesis and model-oriented programming. It differs from the traditional object-oriented approach. The central concept of this new approach and at the same time, the basic building block for the construction of more complex structures is the concept of models-components. A model-component endowed with a more complicated structure than, for example, the object in the object-oriented analysis. This structure provides to the model-component an independent behavior-the ability of standard responds to standard requests of its internal and external environment. At the same time, the computer implementation of model-component's behavior is invariant under the integration of models-components into complexes. This fact allows one firstly to construct fractal models of any complexity, and secondly to implement a computational process of such constructions uniformly-by a single universal program. In addition, the proposed paradigm allows one to exclude imperative programming and to generate computer code with a high degree of parallelism.
Logic-based hierarchies for modeling behavior of complex dynamic systems with applications
International Nuclear Information System (INIS)
Hu, Y.S.; Modarres, M.
2000-01-01
Most complex systems are best represented in the form of a hierarchy. The Goal Tree Success Tree and Master Logic Diagram (GTST-MLD) are proven powerful hierarchic methods to represent complex snap-shot of plant knowledge. To represent dynamic behaviors of complex systems, fuzzy logic is applied to replace binary logic to extend the power of GTST-MLD. Such a fuzzy-logic-based hierarchy is called Dynamic Master Logic Diagram (DMLD). This chapter discusses comparison of the use of GTST-DMLD when applied as a modeling tool for systems whose relationships are modeled by either physical, binary logical or fuzzy logical relationships. This is shown by applying GTST-DMLD to the Direct Containment Heating (DCH) phenomenon at pressurized water reactors which is an important safety issue being addressed by the nuclear industry. (orig.)
Juckem, Paul F.; Clark, Brian R.; Feinstein, Daniel T.
2017-05-04
The U.S. Geological Survey, National Water-Quality Assessment seeks to map estimated intrinsic susceptibility of the glacial aquifer system of the conterminous United States. Improved understanding of the hydrogeologic characteristics that explain spatial patterns of intrinsic susceptibility, commonly inferred from estimates of groundwater age distributions, is sought so that methods used for the estimation process are properly equipped. An important step beyond identifying relevant hydrogeologic datasets, such as glacial geology maps, is to evaluate how incorporation of these resources into process-based models using differing levels of detail could affect resulting simulations of groundwater age distributions and, thus, estimates of intrinsic susceptibility.This report describes the construction and calibration of three groundwater-flow models of northeastern Wisconsin that were developed with differing levels of complexity to provide a framework for subsequent evaluations of the effects of process-based model complexity on estimations of groundwater age distributions for withdrawal wells and streams. Preliminary assessments, which focused on the effects of model complexity on simulated water levels and base flows in the glacial aquifer system, illustrate that simulation of vertical gradients using multiple model layers improves simulated heads more in low-permeability units than in high-permeability units. Moreover, simulation of heterogeneous hydraulic conductivity fields in coarse-grained and some fine-grained glacial materials produced a larger improvement in simulated water levels in the glacial aquifer system compared with simulation of uniform hydraulic conductivity within zones. The relation between base flows and model complexity was less clear; however, the relation generally seemed to follow a similar pattern as water levels. Although increased model complexity resulted in improved calibrations, future application of the models using simulated particle
PeTTSy: a computational tool for perturbation analysis of complex systems biology models.
Domijan, Mirela; Brown, Paul E; Shulgin, Boris V; Rand, David A
2016-03-10
Over the last decade sensitivity analysis techniques have been shown to be very useful to analyse complex and high dimensional Systems Biology models. However, many of the currently available toolboxes have either used parameter sampling, been focused on a restricted set of model observables of interest, studied optimisation of a objective function, or have not dealt with multiple simultaneous model parameter changes where the changes can be permanent or temporary. Here we introduce our new, freely downloadable toolbox, PeTTSy (Perturbation Theory Toolbox for Systems). PeTTSy is a package for MATLAB which implements a wide array of techniques for the perturbation theory and sensitivity analysis of large and complex ordinary differential equation (ODE) based models. PeTTSy is a comprehensive modelling framework that introduces a number of new approaches and that fully addresses analysis of oscillatory systems. It examines sensitivity analysis of the models to perturbations of parameters, where the perturbation timing, strength, length and overall shape can be controlled by the user. This can be done in a system-global setting, namely, the user can determine how many parameters to perturb, by how much and for how long. PeTTSy also offers the user the ability to explore the effect of the parameter perturbations on many different types of outputs: period, phase (timing of peak) and model solutions. PeTTSy can be employed on a wide range of mathematical models including free-running and forced oscillators and signalling systems. To enable experimental optimisation using the Fisher Information Matrix it efficiently allows one to combine multiple variants of a model (i.e. a model with multiple experimental conditions) in order to determine the value of new experiments. It is especially useful in the analysis of large and complex models involving many variables and parameters. PeTTSy is a comprehensive tool for analysing large and complex models of regulatory and
Koh, E. H.; Lee, E.; Kaown, D.; Lee, K. K.; Green, C. T.
2017-12-01
Timing and magnitudes of nitrate contamination are determined by various factors like contaminant loading, recharge characteristics and geologic system. Information of an elapsed time since recharged water traveling to a certain outlet location, which is defined as groundwater age, can provide indirect interpretation related to the hydrologic characteristics of the aquifer system. There are three major methods (apparent ages, lumped parameter model, and numerical model) to date groundwater ages, which differently characterize groundwater mixing resulted by various groundwater flow pathways in a heterogeneous aquifer system. Therefore, in this study, we compared the three age models in a complex aquifer system by using observed age tracer data and reconstructed history of nitrate contamination by long-term source loading. The 3H-3He and CFC-12 apparent ages, which did not consider the groundwater mixing, estimated the most delayed response time and a highest period of the nitrate loading had not reached yet. However, the lumped parameter model could generate more recent loading response than the apparent ages and the peak loading period influenced the water quality. The numerical model could delineate various groundwater mixing components and its different impacts on nitrate dynamics in the complex aquifer system. The different age estimation methods lead to variations in the estimated contaminant loading history, in which the discrepancy in the age estimation was dominantly observed in the complex aquifer system.
Model-based identification and use of task complexity factors of human integrated systems
International Nuclear Information System (INIS)
Ham, Dong-Han; Park, Jinkyun; Jung, Wondea
2012-01-01
Task complexity is one of the conceptual constructs that are critical to explain and predict human performance in human integrated systems. A basic approach to evaluating the complexity of tasks is to identify task complexity factors and measure them. Although a great deal of task complexity factors have been studied, there is still a lack of conceptual frameworks for identifying and organizing them analytically, which can be generally used irrespective of the types of domains and tasks. This study proposes a model-based approach to identifying and using task complexity factors, which has two facets—the design aspects of a task and complexity dimensions. Three levels of design abstraction, which are functional, behavioral, and structural aspects of a task, characterize the design aspect of a task. The behavioral aspect is further classified into five cognitive processing activity types. The complexity dimensions explain a task complexity from different perspectives, which are size, variety, and order/organization. Twenty-one task complexity factors are identified by the combination of the attributes of each facet. Identification and evaluation of task complexity factors based on this model is believed to give insights for improving the design quality of tasks. This model for complexity factors can also be used as a referential framework for allocating tasks and designing information aids. The proposed approach is applied to procedure-based tasks of nuclear power plants (NPPs) as a case study to demonstrate its use. Last, we compare the proposed approach with other studies and then suggest some future research directions.
Hettinger, Lawrence J.; Kirlik, Alex; Goh, Yang Miang; Buckle, Peter
2015-01-01
Accurate comprehension and analysis of complex sociotechnical systems is a daunting task. Empirically examining, or simply envisioning the structure and behaviour of such systems challenges traditional analytic and experimental approaches as well as our everyday cognitive capabilities. Computer-based models and simulations afford potentially useful means of accomplishing sociotechnical system design and analysis objectives. From a design perspective, they can provide a basis for a common mental model among stakeholders, thereby facilitating accurate comprehension of factors impacting system performance and potential effects of system modifications. From a research perspective, models and simulations afford the means to study aspects of sociotechnical system design and operation, including the potential impact of modifications to structural and dynamic system properties, in ways not feasible with traditional experimental approaches. This paper describes issues involved in the design and use of such models and simulations and describes a proposed path forward to their development and implementation. Practitioner Summary: The size and complexity of real-world sociotechnical systems can present significant barriers to their design, comprehension and empirical analysis. This article describes the potential advantages of computer-based models and simulations for understanding factors that impact sociotechnical system design and operation, particularly with respect to process and occupational safety. PMID:25761227
DEFF Research Database (Denmark)
Rasmussen, Jens; Lind, Morten
The paper describes a model of operators' decision making in complex system control, based on studies of event reports and performance in control rooms. This study shows how operators base their decisions on knowledge of system properties at different levels of abstraction depending on their perc...... representation of system properties in a multilevel flow model is described to provide a basis for an integrated control system design.......The paper describes a model of operators' decision making in complex system control, based on studies of event reports and performance in control rooms. This study shows how operators base their decisions on knowledge of system properties at different levels of abstraction depending...... on their perception of the system's immediate control requirements. These levels correspond to the abstraction hierarchy including system purpose, functions, and physical details, which is generally used to describe a formal design process. In emergency situations the task of the operator is to design a suitable...
The maintenance management framework models and methods for complex systems maintenance
Crespo Márquez, Adolfo
2010-01-01
“The Maintenance Management Framework” describes and reviews the concept, process and framework of modern maintenance management of complex systems; concentrating specifically on modern modelling tools (deterministic and empirical) for maintenance planning and scheduling. It will be bought by engineers and professionals involved in maintenance management, maintenance engineering, operations management, quality, etc. as well as graduate students and researchers in this field.
A novel approach for modelling complex maintenance systems using discrete event simulation
International Nuclear Information System (INIS)
Alrabghi, Abdullah; Tiwari, Ashutosh
2016-01-01
Existing approaches for modelling maintenance rely on oversimplified assumptions which prevent them from reflecting the complexity found in industrial systems. In this paper, we propose a novel approach that enables the modelling of non-identical multi-unit systems without restrictive assumptions on the number of units or their maintenance characteristics. Modelling complex interactions between maintenance strategies and their effects on assets in the system is achieved by accessing event queues in Discrete Event Simulation (DES). The approach utilises the wide success DES has achieved in manufacturing by allowing integration with models that are closely related to maintenance such as production and spare parts systems. Additional advantages of using DES include rapid modelling and visual interactive simulation. The proposed approach is demonstrated in a simulation based optimisation study of a published case. The current research is one of the first to optimise maintenance strategies simultaneously with their parameters while considering production dynamics and spare parts management. The findings of this research provide insights for non-conflicting objectives in maintenance systems. In addition, the proposed approach can be used to facilitate the simulation and optimisation of industrial maintenance systems. - Highlights: • This research is one of the first to optimise maintenance strategies simultaneously. • New insights for non-conflicting objectives in maintenance systems. • The approach can be used to optimise industrial maintenance systems.
Alexandrov, Natalia (Technical Monitor); Kuby, Michael; Tierney, Sean; Roberts, Tyler; Upchurch, Christopher
2005-01-01
This report reviews six classes of models that are used for studying transportation network topologies. The report is motivated by two main questions. First, what can the "new science" of complex networks (scale-free, small-world networks) contribute to our understanding of transport network structure, compared to more traditional methods? Second, how can geographic information systems (GIS) contribute to studying transport networks? The report defines terms that can be used to classify different kinds of models by their function, composition, mechanism, spatial and temporal dimensions, certainty, linearity, and resolution. Six broad classes of models for analyzing transport network topologies are then explored: GIS; static graph theory; complex networks; mathematical programming; simulation; and agent-based modeling. Each class of models is defined and classified according to the attributes introduced earlier. The paper identifies some typical types of research questions about network structure that have been addressed by each class of model in the literature.
The Modeling and Complexity of Dynamical Systems by Means of Computation and Information Theories
Directory of Open Access Journals (Sweden)
Robert Logozar
2011-12-01
Full Text Available We present the modeling of dynamical systems and finding of their complexity indicators by the use of concepts from computation and information theories, within the framework of J. P. Crutchfield's theory of ε-machines. A short formal outline of the ε-machines is given. In this approach, dynamical systems are analyzed directly from the time series that is received from a properly adjusted measuring instrument. The binary strings are parsed through the parse tree, within which morphologically and probabilistically unique subtrees or morphs are recognized as system states. The outline and precise interrelation of the information-theoretic entropies and complexities emanating from the model is given. The paper serves also as a theoretical foundation for the future presentation of the DSA program that implements the ε-machines modeling up to the stochastic finite automata level.
Functional modelling for integration of human-software-hardware in complex physical systems
International Nuclear Information System (INIS)
Modarres, M.
1996-01-01
A framework describing the properties of complex physical systems composed of human-software-hardware interactions in terms of their functions is described. It is argued that such a framework is domain-general, so that functional primitives present a language that is more general than most other modeling methods such as mathematical simulation. The characteristics and types of functional models are described. Examples of uses of the framework in modeling physical systems composed of human-software-hardware (hereby we refer to them as only physical systems) are presented. It is concluded that a function-centered model of a physical system provides a capability for generating a high-level simulation of the system for intelligent diagnostic, control or other similar applications
Fuzzy Modeling and Synchronization of a New Hyperchaotic Complex System with Uncertainties
Directory of Open Access Journals (Sweden)
Hadi Delavari
2015-07-01
Full Text Available In this paper, the synchronization of a new hyperchaotic complex system based on T-S fuzzy model is proposed. First the considered hyperchaotic system is represented by T-S fuzzy model equivalently. Then by using the parallel distributed compensation (PDC method and by applying linear system theory and exact linearization (EL technique, a fuzzy controller is designed to realize the synchronization. Finally, simulation results are carried out to demonstrate the performance of our proposed control scheme, and also the robustness of the designed fuzzy controller to uncertainties.
Recommended Research Directions for Improving the Validation of Complex Systems Models.
Energy Technology Data Exchange (ETDEWEB)
Vugrin, Eric D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Trucano, Timothy G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Swiler, Laura Painton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Finley, Patrick D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Flanagan, Tatiana Paz [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Naugle, Asmeret Bier [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Tsao, Jeffrey Y. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Verzi, Stephen Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-02-01
Improved validation for models of complex systems has been a primary focus over the past year for the Resilience in Complex Systems Research Challenge. This document describes a set of research directions that are the result of distilling those ideas into three categories of research -- epistemic uncertainty, strong tests, and value of information. The content of this document can be used to transmit valuable information to future research activities, update the Resilience in Complex Systems Research Challenge's roadmap, inform the upcoming FY18 Laboratory Directed Research and Development (LDRD) call and research proposals, and facilitate collaborations between Sandia and external organizations. The recommended research directions can provide topics for collaborative research, development of proposals, workshops, and other opportunities.
Directory of Open Access Journals (Sweden)
Tskhovrebov Eduard Stanislavovich
2015-09-01
Full Text Available In 2011 in Russia a Strategy of Production Development of Construction Materials and Industrial Housing Construction for the period up to 2020 was approved as one of strategic documents in the sphere of construction. In the process of this strategy development all the needs of construction complex were taken into account in all the spheres of economy, including transport system. The strategy also underlined, that the construction industry is a great basis for use and application in secondary economic turnover of dangerous waste from different production branches. This gives possibility to produce construction products of recycled materials and at the same time to solve the problem of environmental protection. The article considers and analyzes scientific methodological approaches to creation of a model of a complex control system for the streams of building waste in frames of organizing uniform ecologically safe and economically effective complex system of waste treatment in country regions.
International Nuclear Information System (INIS)
Lu, Yunfan; Wang, Jun; Niu, Hongli
2015-01-01
An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model
Energy Technology Data Exchange (ETDEWEB)
Lu, Yunfan, E-mail: yunfanlu@yeah.net; Wang, Jun; Niu, Hongli
2015-06-12
An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model.
Agent-Based and Macroscopic Modeling of the Complex Socio-Economic Systems
Directory of Open Access Journals (Sweden)
Aleksejus Kononovičius
2013-08-01
Full Text Available Purpose – The focus of this contribution is the correspondence between collective behavior and inter-individual interactions in the complex socio-economic systems. Currently there is a wide selection of papers proposing various models for the both collective behavior and inter-individual interactions in the complex socio-economic systems. Yet the papers directly relating these two concepts are still quite rare. By studying this correspondence we discuss a cutting edge approach to the modeling of complex socio-economic systems. Design/methodology/approach – The collective behavior is often modeled using stochastic and ordinary calculus, while the inter-individual interactions are modeled using agent-based models. In order to obtain the ideal model, one should start from these frameworks and build a bridge to reach another. This is a formidable task, if we consider the top-down approach, namely starting from the collective behavior and moving towards inter-individual interactions. The bottom-up approach also fails, if complex inter-individual interaction models are considered, yet in this case we can start with simple models and increase the complexity as needed. Findings – The bottom-up approach, considering simple agent-based herding model as a model for the inter-individual interactions, allows us to derive certain macroscopic models of the complex socio-economic systems from the agent-based perspective. This provides interesting insights into the collective behavior patterns observed in the complex socio-economic systems. Research limitations/implications –The simplicity of the agent-based herding model might be considered to be somewhat limiting. Yet this simplicity implies that the model is highly universal. It reproduces universal features of social behavior and also can be further extended to fit different socio-economic scenarios. Practical implications – Insights provided in this contribution might be used to modify existing
Hall, Laverne
1995-01-01
Modeling of the Multi-mission Image Processing System (MIPS) will be described as an example of the use of a modeling tool to design a distributed system that supports multiple application scenarios. This paper examines: (a) modeling tool selection, capabilities, and operation (namely NETWORK 2.5 by CACl), (b) pointers for building or constructing a model and how the MIPS model was developed, (c) the importance of benchmarking or testing the performance of equipment/subsystems being considered for incorporation the design/architecture, (d) the essential step of model validation and/or calibration using the benchmark results, (e) sample simulation results from the MIPS model, and (f) how modeling and simulation analysis affected the MIPS design process by having a supportive and informative impact.
Modelling small-angle scattering data from complex protein-lipid systems
DEFF Research Database (Denmark)
Kynde, Søren Andreas Røssell
This thesis consists of two parts. The rst part is divided into five chapters. Chapter 1 gives a general introduction to the bio-molecular systems that have been studied. These are membrane proteins and their lipid environments in the form of phospholipid nanodiscs. Membrane proteins...... the techniques very well suited for the study of the nanodisc system. Chapter 3 explains two different modelling approaches that can be used in the analysis of small-angle scattering data from lipid-protein complexes. These are the continuous approach where the system of interest is modelled as a few regular...... combine the bene ts of each of the methods and give unique structural information about relevant bio-molecular complexes in solution. Chapter 4 describes the work behind a proposal of a small-angle neutron scattering instrument for the European Spallation Source under construction in Lund. The instrument...
Modeling complexity in engineered infrastructure system: Water distribution network as an example
Zeng, Fang; Li, Xiang; Li, Ke
2017-02-01
The complex topology and adaptive behavior of infrastructure systems are driven by both self-organization of the demand and rigid engineering solutions. Therefore, engineering complex systems requires a method balancing holism and reductionism. To model the growth of water distribution networks, a complex network model was developed following the combination of local optimization rules and engineering considerations. The demand node generation is dynamic and follows the scaling law of urban growth. The proposed model can generate a water distribution network (WDN) similar to reported real-world WDNs on some structural properties. Comparison with different modeling approaches indicates that a realistic demand node distribution and co-evolvement of demand node and network are important for the simulation of real complex networks. The simulation results indicate that the efficiency of water distribution networks is exponentially affected by the urban growth pattern. On the contrary, the improvement of efficiency by engineering optimization is limited and relatively insignificant. The redundancy and robustness, on another aspect, can be significantly improved through engineering methods.
Directory of Open Access Journals (Sweden)
Tinggui Chen
2013-01-01
Full Text Available Complex engineering system optimization usually involves multiple projects or tasks. On the one hand, dependency modeling among projects or tasks highlights structures in systems and their environments which can help to understand the implications of connectivity on different aspects of system performance and also assist in designing, optimizing, and maintaining complex systems. On the other hand, multiple projects or tasks are either happening at the same time or scheduled into a sequence in order to use common resources. In this paper, we propose a dynamic intelligent decision approach to dependency modeling of project tasks in complex engineering system optimization. The approach takes this decision process as a two-stage decision-making problem. In the first stage, a task clustering approach based on modularization is proposed so as to find out a suitable decomposition scheme for a large-scale project. In the second stage, according to the decomposition result, a discrete artificial bee colony (ABC algorithm inspired by the intelligent foraging behavior of honeybees is developed for the resource constrained multiproject scheduling problem. Finally, a certain case from an engineering design of a chemical processing system is utilized to help to understand the proposed approach.
NHL and RCGA Based Multi-Relational Fuzzy Cognitive Map Modeling for Complex Systems
Directory of Open Access Journals (Sweden)
Zhen Peng
2015-11-01
Full Text Available In order to model multi-dimensions and multi-granularities oriented complex systems, this paper firstly proposes a kind of multi-relational Fuzzy Cognitive Map (FCM to simulate the multi-relational system and its auto construct algorithm integrating Nonlinear Hebbian Learning (NHL and Real Code Genetic Algorithm (RCGA. The multi-relational FCM fits to model the complex system with multi-dimensions and multi-granularities. The auto construct algorithm can learn the multi-relational FCM from multi-relational data resources to eliminate human intervention. The Multi-Relational Data Mining (MRDM algorithm integrates multi-instance oriented NHL and RCGA of FCM. NHL is extended to mine the causal relationships between coarse-granularity concept and its fined-granularity concepts driven by multi-instances in the multi-relational system. RCGA is used to establish high-quality high-level FCM driven by data. The multi-relational FCM and the integrating algorithm have been applied in complex system of Mutagenesis. The experiment demonstrates not only that they get better classification accuracy, but it also shows the causal relationships among the concepts of the system.
New Modeling of Steady-State Modes of Complex Electrical Grids of Power Systems
Directory of Open Access Journals (Sweden)
Akhmetbayev Arman
2018-01-01
Full Text Available Classical methods for modeling the steady-state modes of complex electrical networks and systems are based on the application of nonlinear node equations. Nonlinear equations are solved by iterative methods, which are connected by known difficulties. To a certain extent, these difficulties can be weakened by applying topological methods. In this paper, we outline the theoretical foundations for the formation of the inverse form of nodal stress equations based on the topology of electrical networks and systems. A new topological method for calculating the distribution coefficients of node currents is proposed based on all possible trees of a directed graph of a complex electrical network. A complex program for calculating current distribution coefficients and forming steady-state parameters in the MATLAB environment has been developed.
Farmer, J. Doyne; Gallegati, M.; Hommes, C.; Kirman, A.; Ormerod, P.; Cincotti, S.; Sanchez, A.; Helbing, D.
2012-11-01
We outline a vision for an ambitious program to understand the economy and financial markets as a complex evolving system of coupled networks of interacting agents. This is a completely different vision from that currently used in most economic models. This view implies new challenges and opportunities for policy and managing economic crises. The dynamics of such models inherently involve sudden and sometimes dramatic changes of state. Further, the tools and approaches we use emphasize the analysis of crises rather than of calm periods. In this they respond directly to the calls of Governors Bernanke and Trichet for new approaches to macroeconomic modelling.
Data-assisted reduced-order modeling of extreme events in complex dynamical systems.
Directory of Open Access Journals (Sweden)
Zhong Yi Wan
Full Text Available The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more
Data-assisted reduced-order modeling of extreme events in complex dynamical systems.
Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis
2018-01-01
The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in
Polystochastic Models for Complexity
Iordache, Octavian
2010-01-01
This book is devoted to complexity understanding and management, considered as the main source of efficiency and prosperity for the next decades. Divided into six chapters, the book begins with a presentation of basic concepts as complexity, emergence and closure. The second chapter looks to methods and introduces polystochastic models, the wave equation, possibilities and entropy. The third chapter focusing on physical and chemical systems analyzes flow-sheet synthesis, cyclic operations of separation, drug delivery systems and entropy production. Biomimetic systems represent the main objective of the fourth chapter. Case studies refer to bio-inspired calculation methods, to the role of artificial genetic codes, neural networks and neural codes for evolutionary calculus and for evolvable circuits as biomimetic devices. The fifth chapter, taking its inspiration from systems sciences and cognitive sciences looks to engineering design, case base reasoning methods, failure analysis, and multi-agent manufacturing...
Model-Based Development and Evaluation of Control for Complex Multi-Domain Systems
DEFF Research Database (Denmark)
Grujic, Ivan; Nilsson, Rene
A Cyber-Physical System (CPS) incorporates sensing, actuating, computing and communicative capabilities, which are often combined to control the system. The development of CPSs poses a challenge, since the complexity of the physical system dynamics must be taken into account when designing...... Unmanned Aerial Vehicle (UAV) has been constructed and used to develop an attitude controller based on Model Predictive Control (MPC). The MPC controller has been compared to an existing open source Proportional Integral Derivative (PID) attitude controller. This thesis contributes to the discipline...
Qi, Di
Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are
A Model-Based Approach to Engineering Behavior of Complex Aerospace Systems
Ingham, Michel; Day, John; Donahue, Kenneth; Kadesch, Alex; Kennedy, Andrew; Khan, Mohammed Omair; Post, Ethan; Standley, Shaun
2012-01-01
One of the most challenging yet poorly defined aspects of engineering a complex aerospace system is behavior engineering, including definition, specification, design, implementation, and verification and validation of the system's behaviors. This is especially true for behaviors of highly autonomous and intelligent systems. Behavior engineering is more of an art than a science. As a process it is generally ad-hoc, poorly specified, and inconsistently applied from one project to the next. It uses largely informal representations, and results in system behavior being documented in a wide variety of disparate documents. To address this problem, JPL has undertaken a pilot project to apply its institutional capabilities in Model-Based Systems Engineering to the challenge of specifying complex spacecraft system behavior. This paper describes the results of the work in progress on this project. In particular, we discuss our approach to modeling spacecraft behavior including 1) requirements and design flowdown from system-level to subsystem-level, 2) patterns for behavior decomposition, 3) allocation of behaviors to physical elements in the system, and 4) patterns for capturing V&V activities associated with behavioral requirements. We provide examples of interesting behavior specification patterns, and discuss findings from the pilot project.
Research Area 3: Mathematics (3.1 Modeling of Complex Systems)
2017-10-31
Title: RESEARCH AREA 3: MATHEMATICS (3.1 Modeling of Complex Systems). Proposal should be directed to Dr. John Lavery Report Term: 0-Other Email ...Paolo Rosso Email : prosso@dsic.upv.es values of the profile characteristics taken by the users), intersection (they represent the relationship between...accuracy, especially when adding fully connected layers at the end of the network. This work has resulted in the writing of a manuscript for the Journal
Complex Systems: An Introduction
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 14; Issue 9. Complex Systems: An Introduction - Anthropic Principle, Terrestrial Complexity, Complex Materials. V K Wadhawan. General Article Volume 14 Issue 9 September 2009 pp 894-906 ...
Using environmental tracers in modeling flow in a complex shallow aquifer system
DEFF Research Database (Denmark)
Troldborg, Lars; Jensen, Karsten Høgh; Engesgaard, Peter Knudegaard
2008-01-01
shapes and sizes without being similar to the assumed age distributions used in the analytical approach. The shape of age distribution to some extent depends on sampling size and on whether the system is modeled in a transient or in a steady state, but shape and size were largely driven......Using environmental tracers in groundwater dating partly relies on the assumption that groundwater age distribution can be described analytically. To investigate the applicability of age dating in complex multiaquifer systems, a methodology for simulating well specific groundwater age distribution...... was developed. Using a groundwater model and particle tracking we modeled age distributions at screen locations. By enveloping modeled age distributions and estimated recharge concentrations, environmental tracer breakthroughs were simulated for specific screens. Simulated age distributions are of irregular...
DEFF Research Database (Denmark)
Carugati, Andrea
2002-01-01
has been initiated with the scope of investigating the questions that mathematical modelling technology poses to traditional information systems development projects. Based on the past body of research, this study proposes a framework to guide decision making for managing projects of information......The advancements in complexity and sophistication of mathematical models for manufacturing scheduling and control and the increase of the ratio power/cost of computers are beginning to provide the manufacturing industry with new software tools to improve production. A Danish action research project...... systems development. In a presented case the indications of the model are compared with the decisions taken during the development. The results highlight discrepancies between the structure and predictions of the model and the case observations, especially with regard to the importance given to the users...
Urban systems complexity in sustainability and health: an interdisciplinary modelling study
Directory of Open Access Journals (Sweden)
Nici Zimmermann, PhD
2018-05-01
Full Text Available Background: Improving urban health and sustainability raises complex questions that are best addressed through interdisciplinary and even transdisciplinary approaches, in which scientific research and analysis and stakeholder engagement have important roles. In this study we report pilot work in Nairobi (Kenya and London (UK that uses innovative methods to integrate qualitative and quantitative modelling to provide evidence to support policy development for health and sustainability in these cities. Methods: We used two primary modelling methods, system dynamics and microsimulation, and sought to understand the value of these tools in combination to support policy decisions. System dynamics was used to establish an aggregated and non-linear causal map of the interconnections between diverse variables, and thus to gain insight into the policies and specific processes that need to be examined in further depth. System dynamics was a key tool for city-level stakeholder engagement. In part informed by the outcome of the system dynamics process, microsimulation was then used to quantify local effects on health of selected policy options. The results were mapped using geographic information systems methods. Findings: The combination of system dynamics and microsimulation models provided a framework that enhanced collective knowledge about the interrelationships of policy decisions, funding, public awareness, and environmental and health effects. Our initial participatory system dynamics work on air pollution in Nairobi found that a combination of policies that focus on households and outdoor air could reduce household air pollution by about 50%, leaving it still above WHO-recommended levels. Yet, the investments in monitoring and health impact assessment have the potential to trigger reinforcing mechanisms that create synergies among existing policies and increase the return on investment. Preliminary 106-year microsimulation runs of the effects of PM2
Complexity of Economical Systems
Directory of Open Access Journals (Sweden)
G. P. Pavlos
2015-01-01
Full Text Available In this study new theoretical concepts are described concerning the interpretation of economical complex dynamics. In addition a summary of an extended algorithm of nonlinear time series analysis is provided which is applied not only in economical time series but also in other physical complex systems (e.g. [22, 24]. In general, Economy is a vast and complicated set of arrangements and actions wherein agents—consumers, firms, banks, investors, government agencies—buy and sell, speculate, trade, oversee, bring products into being, offer services, invest in companies, strategize, explore, forecast, compete, learn, innovate, and adapt. As a result the economic and financial variables such as foreign exchange rates, gross domestic product, interest rates, production, stock market prices and unemployment exhibit large-amplitude and aperiodic fluctuations evident in complex systems. Thus, the Economics can be considered as spatially distributed non-equilibrium complex system, for which new theoretical concepts, such as Tsallis non extensive statistical mechanics and strange dynamics, percolation, nonGaussian, multifractal and multiscale dynamics related to fractional Langevin equations can be used for modeling and understanding of the economical complexity locally or globally.
Data-Driven Modeling of Complex Systems by means of a Dynamical ANN
Seleznev, A.; Mukhin, D.; Gavrilov, A.; Loskutov, E.; Feigin, A.
2017-12-01
The data-driven methods for modeling and prognosis of complex dynamical systems become more and more popular in various fields due to growth of high-resolution data. We distinguish the two basic steps in such an approach: (i) determining the phase subspace of the system, or embedding, from available time series and (ii) constructing an evolution operator acting in this reduced subspace. In this work we suggest a novel approach combining these two steps by means of construction of an artificial neural network (ANN) with special topology. The proposed ANN-based model, on the one hand, projects the data onto a low-dimensional manifold, and, on the other hand, models a dynamical system on this manifold. Actually, this is a recurrent multilayer ANN which has internal dynamics and capable of generating time series. Very important point of the proposed methodology is the optimization of the model allowing us to avoid overfitting: we use Bayesian criterion to optimize the ANN structure and estimate both the degree of evolution operator nonlinearity and the complexity of nonlinear manifold which the data are projected on. The proposed modeling technique will be applied to the analysis of high-dimensional dynamical systems: Lorenz'96 model of atmospheric turbulence, producing high-dimensional space-time chaos, and quasi-geostrophic three-layer model of the Earth's atmosphere with the natural orography, describing the dynamics of synoptical vortexes as well as mesoscale blocking systems. The possibility of application of the proposed methodology to analyze real measured data is also discussed. The study was supported by the Russian Science Foundation (grant #16-12-10198).
International Nuclear Information System (INIS)
Rasmussen, J.; Lind, M.
1982-04-01
The paper describes a model of operators' decision making in complex system control, based on studies of event reports and performance in control rooms. This study shows how operators base their decisions on knowledge of system properties at different levels of abstraction depending on their preception of the system's immediate control requirements. These levels correspond to the abstraction hierarchy including system purpose, functions, and physical details, which is generally used to describe a formal design process. In emergency situations the task of the operator is to design a suitabel control strategy for systems recovery, and the control systems designer should provide a man-machine interface, supporting the operator in identification of his task and in communication with the system at the level of abstraction corresponding to the immedite control requirement. A formalized representation of system properties in a multilevel flow model is described to provide a basis for an integrated control system design. (author)
Lorenzo Alvarez, Jose; Metselaar, Harold; Amiaux, Jerome; Saavedra Criado, Gonzalo; Gaspar Venancio, Luis M.; Salvignol, Jean-Christophe; Laureijs, René J.; Vavrek, Roland
2016-08-01
In the last years, the system engineering field is coming to terms with a paradigm change in the approach for complexity management. Different strategies have been proposed to cope with highly interrelated systems, system of systems and collaborative system engineering have been proposed and a significant effort is being invested into standardization and ontology definition. In particular, Model Based System Engineering (MBSE) intends to introduce methodologies for a systematic system definition, development, validation, deployment, operation and decommission, based on logical and visual relationship mapping, rather than traditional 'document based' information management. The practical implementation in real large-scale projects is not uniform across fields. In space science missions, the usage has been limited to subsystems or sample projects with modeling being performed 'a-posteriori' in many instances. The main hurdle for the introduction of MBSE practices in new projects is still the difficulty to demonstrate their added value to a project and whether their benefit is commensurate with the level of effort required to put them in place. In this paper we present the implemented Euclid system modeling activities, and an analysis of the benefits and limitations identified to support in particular requirement break-down and allocation, and verification planning at mission level.
Interacting with complex systems. Models and games for a sustainable economy
Energy Technology Data Exchange (ETDEWEB)
De Vries, H.J.M.
2010-09-15
In the last decades the science-policy interface has become more important and more complex too. In this report we search for novel ways to extend or reframe the economic and environmental theories and models upon which policy recommendations are, or should be, based. The methods and applications of Complex System Science, in particular, have been explored and are found to be still fragmented. But they certainly can and should form the basis for introducing behavioural and innovation dynamics which make these theories and models more like what happens in the real world. In combination with interactive simulation and games, of which some examples are discussed in this report, science can in a post-modern context contribute more effectively to the strategic decision making in government and other institutions regarding sustainable development. This will direly be needed in view of the new and global challenges facing us.
Albertos, Pedro; Blanke, Mogens; Isidori, Alberto; Schaufelberger, Walter; Sanz, Ricardo
2001-01-01
The world of artificial systems is reaching complexity levels that es cape human understanding. Surface traffic, electricity distribution, air planes, mobile communications, etc. , are examples that demonstrate that we are running into problems that are beyond classical scientific or engi neering knowledge. There is an ongoing world-wide effort to understand these systems and develop models that can capture its behavior. The reason for this work is clear, if our lack of understanding deepens, we will lose our capability to control these systems and make they behave as we want. Researchers from many different fields are trying to understand and develop theories for complex man-made systems. This book presents re search from the perspective of control and systems theory. The book has grown out of activities in the research program Control of Complex Systems (COSY). The program has been sponsored by the Eu ropean Science Foundation (ESF) which for 25 years has been one of the leading players in stimula...
International Nuclear Information System (INIS)
Sig Drellack, Lance Prothro
2007-01-01
The Underground Test Area (UGTA) Project of the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office is in the process of assessing and developing regulatory decision options based on modeling predictions of contaminant transport from underground testing of nuclear weapons at the Nevada Test Site (NTS). The UGTA Project is attempting to develop an effective modeling strategy that addresses and quantifies multiple components of uncertainty including natural variability, parameter uncertainty, conceptual/model uncertainty, and decision uncertainty in translating model results into regulatory requirements. The modeling task presents multiple unique challenges to the hydrological sciences as a result of the complex fractured and faulted hydrostratigraphy, the distributed locations of sources, the suite of reactive and non-reactive radionuclides, and uncertainty in conceptual models. Characterization of the hydrogeologic system is difficult and expensive because of deep groundwater in the arid desert setting and the large spatial setting of the NTS. Therefore, conceptual model uncertainty is partially addressed through the development of multiple alternative conceptual models of the hydrostratigraphic framework and multiple alternative models of recharge and discharge. Uncertainty in boundary conditions is assessed through development of alternative groundwater fluxes through multiple simulations using the regional groundwater flow model. Calibration of alternative models to heads and measured or inferred fluxes has not proven to provide clear measures of model quality. Therefore, model screening by comparison to independently-derived natural geochemical mixing targets through cluster analysis has also been invoked to evaluate differences between alternative conceptual models. Advancing multiple alternative flow models, sensitivity of transport predictions to parameter uncertainty is assessed through Monte Carlo simulations. The
The evolution model of Uppsala in light of the complex adaptive systems approach
Directory of Open Access Journals (Sweden)
Rennaly Alves da Silva
2013-11-01
Full Text Available The behavioral approach to the internationalization of companies explains that the movements toward external markets occur in accordance with the increasing commitment of resources to mitigate the effects of uncertainty and reduce the perception of risk. Evidence indicates that the theories and practices developed in the domestic market may not be able to explain the reality of companies that operate in international markets. Thus, the Paradigm of Complexity presents itself as a comprehensive alternative to realize the relationships within organizations and markets. Accordingly, the aim of this theoretical paper is to analyze the evolution of the Uppsala Model between years 1975 and 2010 with the understanding of the companies in the process of internationalization as Complex Adaptive Systems, in accordance with the Model Kelly and Allison (1998. Four propositions are presented that show the links between the approaches. The most surprising is the perception that the conceptual evolution of the Uppsala Model seems to accompany the evolution of complexity levels, presented in Model Kelly and Allison.
Predictive Surface Complexation Modeling
Energy Technology Data Exchange (ETDEWEB)
Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences
2016-11-29
Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO_{2} and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.
Forbes, Valery E; Calow, Peter
2013-07-01
Ecological risk assessments (ERAs) are not used as well as they could be in risk management. Part of the problem is that they often lack ecological relevance; that is, they fail to grasp necessary ecological complexities. Adding realism and complexity can be difficult and costly. We argue that predictive systems models (PSMs) can provide a way of capturing complexity and ecological relevance cost-effectively. However, addressing complexity and ecological relevance is only part of the problem. Ecological risk assessments often fail to meet the needs of risk managers by not providing assessments that relate to protection goals and by expressing risk in ratios that cannot be weighed against the costs of interventions. Once more, PSMs can be designed to provide outputs in terms of value-relevant effects that are modulated against exposure and that can provide a better basis for decision making than arbitrary ratios or threshold values. Recent developments in the modeling and its potential for implementation by risk assessors and risk managers are beginning to demonstrate how PSMs can be practically applied in risk assessment and the advantages that doing so could have. Copyright © 2013 SETAC.
Modeling Networks and Dynamics in Complex Systems: from Nano-Composites to Opinion Formation
Shi, Feng
Complex networks are ubiquitous in systems of physical, biological, social or technological origin. Components in those systems range from as large as cities in power grids, to as small as molecules in metabolic networks. Since the dawn of network science, significant attention has focused on the implications of dynamics in establishing network structure and the impact of structural properties on dynamics on those networks. The first part of the thesis follows this direction, studying the network formed by conductive nanorods in nano-materials, and focuses on the electrical response of the composite to the structure change of the network. New scaling laws for the shear-induced anisotropic percolation are introduced and a robust exponential tail of the current distribution across the network is identified. These results are relevant especially to "active" composite materials where materials are exposed to mechanical loading and strain deformations. However, in many real-world networks the evolution of the network topology is tied to the states of the vertices and vice versa. Networks that exhibit such a feedback are called adaptive or coevolutionary networks. The second part of the thesis examines two closely related variants of a simple, abstract model for coevolution of a network and the opinions of its members. As a representative model for adaptive networks, it displays the feature of self-organization of the system into a stable configuration due to the interplay between the network topology and the dynamics on the network. This simple model yields interesting dynamics and the slight change in the rewiring strategy results in qualitatively different behaviors of the system. In conclusion, the dissertation aims to develop new network models and tools which enable insights into the structure and dynamics of various systems, and seeks to advance network algorithms which provide approaches to coherently articulated questions in real-world complex systems such as
Agent-based model with asymmetric trading and herding for complex financial systems.
Chen, Jun-Jie; Zheng, Bo; Tan, Lei
2013-01-01
For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors' asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. With the model parameters determined for six representative stock-market indices in the world, respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. We reveal that for the leverage and anti-leverage effects, both the investors' asymmetric trading and herding are essential generation mechanisms. Among the six markets, however, the investors' trading is approximately symmetric for the five markets which exhibit the leverage effect, thus contributing very little. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex
Agent-based model with asymmetric trading and herding for complex financial systems.
Directory of Open Access Journals (Sweden)
Jun-Jie Chen
Full Text Available BACKGROUND: For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. METHODS: To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors' asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. RESULTS: With the model parameters determined for six representative stock-market indices in the world, respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. CONCLUSIONS: We reveal that for the leverage and anti-leverage effects, both the investors' asymmetric trading and herding are essential generation mechanisms. Among the six markets, however, the investors' trading is approximately symmetric for the five markets which exhibit the leverage effect, thus contributing very little. These two microscopic mechanisms and the methods for the
Aviation Safety: Modeling and Analyzing Complex Interactions between Humans and Automated Systems
Rungta, Neha; Brat, Guillaume; Clancey, William J.; Linde, Charlotte; Raimondi, Franco; Seah, Chin; Shafto, Michael
2013-01-01
The on-going transformation from the current US Air Traffic System (ATS) to the Next Generation Air Traffic System (NextGen) will force the introduction of new automated systems and most likely will cause automation to migrate from ground to air. This will yield new function allocations between humans and automation and therefore change the roles and responsibilities in the ATS. Yet, safety in NextGen is required to be at least as good as in the current system. We therefore need techniques to evaluate the safety of the interactions between humans and automation. We think that current human factor studies and simulation-based techniques will fall short in front of the ATS complexity, and that we need to add more automated techniques to simulations, such as model checking, which offers exhaustive coverage of the non-deterministic behaviors in nominal and off-nominal scenarios. In this work, we present a verification approach based both on simulations and on model checking for evaluating the roles and responsibilities of humans and automation. Models are created using Brahms (a multi-agent framework) and we show that the traditional Brahms simulations can be integrated with automated exploration techniques based on model checking, thus offering a complete exploration of the behavioral space of the scenario. Our formal analysis supports the notion of beliefs and probabilities to reason about human behavior. We demonstrate the technique with the Ueberligen accident since it exemplifies authority problems when receiving conflicting advices from human and automated systems.
Local difference measures between complex networks for dynamical system model evaluation.
Lange, Stefan; Donges, Jonathan F; Volkholz, Jan; Kurths, Jürgen
2015-01-01
A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation.Building on a recent study by Feldhoff et al. [8] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system [corrected]. types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node
Modelling methodology for assessing the impact of new technology on complex sociotechnical systems
CSIR Research Space (South Africa)
Oosthuizen, R
2014-11-01
Full Text Available Developing complex sociotechnical systems often involves integrating new technology into existing systems by applying systems engineering processes. This requires an understanding of the problem space and the possible impact of the new technology...
Modeling and Performance Considerations for Automated Fault Isolation in Complex Systems
Ferrell, Bob; Oostdyk, Rebecca
2010-01-01
The purpose of this paper is to document the modeling considerations and performance metrics that were examined in the development of a large-scale Fault Detection, Isolation and Recovery (FDIR) system. The FDIR system is envisioned to perform health management functions for both a launch vehicle and the ground systems that support the vehicle during checkout and launch countdown by using suite of complimentary software tools that alert operators to anomalies and failures in real-time. The FDIR team members developed a set of operational requirements for the models that would be used for fault isolation and worked closely with the vendor of the software tools selected for fault isolation to ensure that the software was able to meet the requirements. Once the requirements were established, example models of sufficient complexity were used to test the performance of the software. The results of the performance testing demonstrated the need for enhancements to the software in order to meet the demands of the full-scale ground and vehicle FDIR system. The paper highlights the importance of the development of operational requirements and preliminary performance testing as a strategy for identifying deficiencies in highly scalable systems and rectifying those deficiencies before they imperil the success of the project
Akinwumiju, Akinola S.; Olorunfemi, Martins O.
2018-05-01
This study attempted to model the groundwater flow system of a drainage basin within the Basement Complex environment of Southwestern Nigeria. Four groundwater models were derived from Vertical Electrical Sounding (VES) Data, remotely sensed data, geological information (hydrolineaments and lithology) and borehole data. Subsequently, two sub-surface (local and regional) flow systems were delineated in the study area. While the local flow system is controlled by surface topography, the regional flow system is controlled by the networks of intermediate and deep seated faults/fractures. The local flow system is characterized by convergence, divergence, inflow and outflow in places, while the regional flow system is dominated by NNE-SSW and W-E flow directions. Minor flow directions include NNW-SSE and E-W with possible linkages to the main flow-paths. The NNE-SSW regional flow system is a double open ended flow system with possible linkage to the Niger Trough. The W-E regional flow system is a single open ended system that originates within the study area (with possible linkage to the NNE-SSW regional flow system) and extends to Ikogosi in the adjoining drainage basin. Thus, the groundwater drainage basin of the study area is much larger and extensive than its surface drainage basin. The all year round flowing (perennial) rivers are linked to groundwater outcrops from faults/fractures and contact zones. Consequently, larger percentage of annual rainwater usually leaves the basin in form of runoff and base flow. Therefore, the basin is categorized as a donor basin but with suspected subsurface water input at its northeastern axis.
A Modeling Framework for the Concurrent Design of Complex Space Systems
Ridolfi, G.; Mooij, E.; Chiesa, S.
2010-01-01
The design of complex systems has become more and more articulated during the last decade, thus forcing radical modifications on the overall methodological approach. The authors developed a design methodology, which allows the user to design a particular category of complex systems usually called
Role of Reactive Mn Complexes in a Litter Decomposition Model System
Nico, P. S.; Keiluweit, M.; Bougoure, J.; Kleber, M.; Summering, J. A.; Maynard, J. J.; Johnson, M.; Pett-Ridge, J.
2012-12-01
The search for controls on litter decomposition rates and pathways has yet to return definitive characteristics that are both statistically robust and can be understood as part of a mechanistic or numerical model. Herein we focus on Mn, an element present in all litter that is likely an active chemical agent of decomposition. Berg and co-workers (2010) found a strong correlation between Mn concentration in litter and the magnitude of litter degradation in boreal forests, suggesting that litter decomposition proceeds more efficiently in the presence of Mn. Although there is much circumstantial evidence for the potential role of Mn in lignin decomposition, few reports exist on mechanistic details of this process. For the current work, we are guided by the hypothesis that the dependence of decomposition on Mn is due to Mn (III)-oxalate complexes act as a 'pretreatment' for structurally intact ligno-carbohydrate complexes (LCC) in fresh plant cell walls (e.g. in litter, root and wood). Manganese (III)-ligand complexes such as Mn (III)-oxalate are known to be potent oxidizers of many different organic and inorganic compounds. In the litter system, the unique property of these complexes may be that they are much smaller than exo-enzymes and therefore more easily able to penetrate LCC complexes in plant cell walls. By acting as 'diffusible oxidizers' and reacting with the organic matrix of the cell wall, these compounds can increase the porosity of fresh litter thereby facilitating access of more specific lignin- and cellulose decomposing enzymes. This possibility was investigated by reacting cell walls of single Zinnia elegans tracheary elements with Mn (III)-oxalate complexes in a continuous flow reactor. The uniformity of these individual plant cells allowed us to examine Mn (III)-induced changes in cell wall chemistry and ultrastructure on the micro-scale using fluorescence and electron microscopy as well as IR and X-ray spectromicroscopy. This presentation will
State-Dependence of the Climate Sensitivity in Earth System Models of Intermediate Complexity
Pfister, Patrik L.; Stocker, Thomas F.
2017-10-01
Growing evidence from general circulation models (GCMs) indicates that the equilibrium climate sensitivity (ECS) depends on the magnitude of forcing, which is commonly referred to as state-dependence. We present a comprehensive assessment of ECS state-dependence in Earth system models of intermediate complexity (EMICs) by analyzing millennial simulations with sustained 2×CO2 and 4×CO2 forcings. We compare different extrapolation methods and show that ECS is smaller in the higher-forcing scenario in 12 out of 15 EMICs, in contrast to the opposite behavior reported from GCMs. In one such EMIC, the Bern3D-LPX model, this state-dependence is mainly due to the weakening sea ice-albedo feedback in the Southern Ocean, which depends on model configuration. Due to ocean-mixing adjustments, state-dependence is only detected hundreds of years after the abrupt forcing, highlighting the need for long model integrations. Adjustments to feedback parametrizations of EMICs may be necessary if GCM intercomparisons confirm an opposite state-dependence.
Jatobá, Alessandro; de Carvalho, Paulo Victor R; da Cunha, Amauri Marques
2012-01-01
Work in organizations requires a minimum level of consensus on the understanding of the practices performed. To adopt technological devices to support the activities in environments where work is complex, characterized by the interdependence among a large number of variables, understanding about how work is done not only takes an even greater importance, but also becomes a more difficult task. Therefore, this study aims to present a method for modeling of work in complex systems, which allows improving the knowledge about the way activities are performed where these activities do not simply happen by performing procedures. Uniting techniques of Cognitive Task Analysis with the concept of Work Process, this work seeks to provide a method capable of providing a detailed and accurate vision of how people perform their tasks, in order to apply information systems for supporting work in organizations.
Complex Systems and Dependability
Zamojski, Wojciech; Sugier, Jaroslaw
2012-01-01
Typical contemporary complex system is a multifaceted amalgamation of technical, information, organization, software and human (users, administrators and management) resources. Complexity of such a system comes not only from its involved technical and organizational structure but mainly from complexity of information processes that must be implemented in the operational environment (data processing, monitoring, management, etc.). In such case traditional methods of reliability analysis focused mainly on technical level are usually insufficient in performance evaluation and more innovative meth
2016-04-30
current methodologies used in risk assessment are heavily subjective and inaccurate in various life cycle phases of complex engineered systems. The...complexity content of the system. Many of the system’s life cycle risks are currently assessed subjectively by imprecise methodologies such as color...evaluated for multiple entities such as galaxies, stars, planets , plants, animals, societies, and technological systems, and also has been mapped
Anderson, Gregory B.; Freeman, Mary C.; Hagler, Megan M.; Freeman, Byron J.
2012-01-01
Documenting the status of rare fishes is a crucial step in effectively managing populations and implementing regulatory mechanisms of protection. In recent years, site occupancy has become an increasingly popular metric for assessing populations, but species distribution models that do not account for imperfect detection can underestimate the proportion of sites occupied and the strength of the relationship with a hypothesized covariate. However, valid detection requires temporal or spatial replication, which is often not feasible due to logistical or budget constraints. In this study, we used a method that allowed for spatial replication during a single visit to evaluate the current status of the holiday darter species complex, Etheostoma sp. cf. E. brevirostrum, within the Etowah River system. Moreover, the modeling approach used in this study facilitated comparisons of factors influencing stream occupancy as well as species detection within sites. The results suggest that there is less habitat available for the Etowah holiday darter form (Etheostoma sp. cf. E. brevirostrum B) than for the Amicalola holiday darter form (Etheostoma sp. cf. E. brevirostrum A). Additionally, occupancy models suggest that even small decreases in forest cover within these headwater systems adversely affect holiday darter populations.
Agent-based model with multi-level herding for complex financial systems
Chen, Jun-Jie; Tan, Lei; Zheng, Bo
2015-02-01
In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.
Directory of Open Access Journals (Sweden)
Oleg Svatos
2013-01-01
Full Text Available In this paper we analyze complexity of time limits we can find especially in regulated processes of public administration. First we review the most popular process modeling languages. There is defined an example scenario based on the current Czech legislature which is then captured in discussed process modeling languages. Analysis shows that the contemporary process modeling languages support capturing of the time limit only partially. This causes troubles to analysts and unnecessary complexity of the models. Upon unsatisfying results of the contemporary process modeling languages we analyze the complexity of the time limits in greater detail and outline lifecycles of a time limit using the multiple dynamic generalizations pattern. As an alternative to the popular process modeling languages there is presented PSD process modeling language, which supports the defined lifecycles of a time limit natively and therefore allows keeping the models simple and easy to understand.
The use of high fidelity CAD models as the basis for training on complex systems
Miller, Kellie; Tanner, Steve
1993-01-01
During the design phases of large and complex systems such as NASA's Space Station Freedom (SSF), there are few, if any physical prototypes built. This is often due to their expense and the realization that the design is likely to change. This poses a problem for training, maintainability, and operations groups who are tasked to lay the foundation of plans for using these systems. The Virtual Reality and Visualization Laboratory at the Boeing Advanced Computing Group's Huntsville facility is supporting the use of high fidelity, detailed design models that are generated during the initial design phases, for use in training, maintainability and operations exercises. This capability was used in its non-immersive form to great effect at the SSF Critical Design Review (CDR) during February, 1993. Allowing the user to move about within a CAD design supports many efforts, including training and scenario study. We will demonstrate via a video of the Maintainability SSF CDR how this type of approach can be used and why it is so effective in conveying large amounts of information quickly and concisely. We will also demonstrate why high fidelity models are so important for this type of training system and how it's immersive aspects may be exploited as well.
International Nuclear Information System (INIS)
Belov, O.V.
2008-01-01
The mathematical model describing kinetics of the inducible genes of the protein complexes, formed during SOS response in bacteria Escherichia coli is developed. Within the bounds of developed approaches the auxiliary mathematical model describing changes in concentrations of the dimers, which are the components of final protein complexes, is developed. The solutions of both models are based on the experimental data concerning expression of the basic genes of the SOS system in bacteria Escherichia coli
International Nuclear Information System (INIS)
Monte, L.; Haakanson, L.; Gallego Diaz, E.
1999-01-01
The present report is composed of a set of articles written by the partners of the MOIRA project (a model-based computerized system for management support to identify optimal remedial strategies for restoring radionuclide contaminated aquatic ecosystems and drainage areas). The report describes models for predicting the behaviour of radionuclides in complex aquatic systems and the effects of countermeasures for their restoration [it
Anderson, James; Chaturvedi, Alok; Cibulskis, Mike
2007-12-01
The U.S. Committee for Refugees and Immigrants estimated that there were over 33 million refugees and internally displaced persons (IDPs) in the world at the beginning of 2005. IDP/Refugee communities behave in complex ways making it difficult to make policy decisions regarding the provision of humanitarian aid and health and safety. This paper reports the construction of an agent-based model that has been used to study humanitarian assistance policies executed by governments and NGOs that provide for the health and safety of refugee communities. Agent-based modeling (ABM) was chosen because the more widely used alternatives impose unrealistic restrictions and assumptions on the system being modeled and primarily apply to aggregate data. We created intelligent agents representing institutions, organizations, individuals, infrastructure, and governments and analyzed the resulting interactions and emergent behavior using a Central Composite Design of Experiments with five factors. The resulting model allows policy makers and analysts to create scenarios, to make rapid changes in parameters, and provides a test bed for concepts and strategies. Policies can be examined to see how refugee communities might respond to alternative courses of action and how these actions are likely to affect the health and well-being of the community.
International Nuclear Information System (INIS)
Sawan, M.; Wilson, P.; El-Guebaly, L.; Henderson, D.; Sviatoslavsky, G.; Bohm, T.; Kiedrowski, B.; Ibrahim, A.; Smith, B.; Slaybaugh, R.; Tautges, T.
2007-01-01
Fusion systems are, in general, geometrically complex requiring detailed three-dimensional (3-D) nuclear analysis. This analysis is required to address tritium self-sufficiency, nuclear heating, radiation damage, shielding, and radiation streaming issues. To facilitate such calculations, we developed an innovative computational tool that is based on the continuous energy Monte Carlo code MCNP and permits the direct use of CAD-based solid models in the ray-tracing. This allows performing the neutronics calculations in a model that preserves the geometrical details without any simplification, eliminates possible human error in modeling the geometry for MCNP, and allows faster design iterations. In addition to improving the work flow for simulating complex 3- D geometries, it allows a richer representation of the geometry compared to the standard 2nd order polynomial representation. This newly developed tool has been successfully tested for a detailed 40 degree sector benchmark of the International Thermonuclear Experimental Reactor (ITER). The calculations included determining the poloidal variation of the neutron wall loading, flux and nuclear heating in the divertor components, nuclear heating in toroidal field coils, and radiation streaming in the mid-plane port. The tool has been applied to perform 3-D nuclear analysis for several fusion designs including the ARIES Compact Stellarator (ARIES-CS), the High Average Power Laser (HAPL) inertial fusion power plant, and ITER first wall/shield (FWS) modules. The ARIES-CS stellarator has a first wall shape and a plasma profile that varies toroidally within each field period compared to the uniform toroidal shape in tokamaks. Such variation cannot be modeled analytically in the standard MCNP code. The impact of the complex helical geometry and the non-uniform blanket and divertor on the overall tritium breeding ratio and total nuclear heating was determined. In addition, we calculated the neutron wall loading variation in
International Nuclear Information System (INIS)
Brown, T.W.
2010-11-01
The same complex matrix model calculates both tachyon scattering for the c=1 non-critical string at the self-dual radius and certain correlation functions of half-BPS operators in N=4 super- Yang-Mills. It is dual to another complex matrix model where the couplings of the first model are encoded in the Kontsevich-like variables of the second. The duality between the theories is mirrored by the duality of their Feynman diagrams. Analogously to the Hermitian Kontsevich- Penner model, the correlation functions of the second model can be written as sums over discrete points in subspaces of the moduli space of punctured Riemann surfaces. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Brown, T.W.
2010-11-15
The same complex matrix model calculates both tachyon scattering for the c=1 non-critical string at the self-dual radius and certain correlation functions of half-BPS operators in N=4 super- Yang-Mills. It is dual to another complex matrix model where the couplings of the first model are encoded in the Kontsevich-like variables of the second. The duality between the theories is mirrored by the duality of their Feynman diagrams. Analogously to the Hermitian Kontsevich- Penner model, the correlation functions of the second model can be written as sums over discrete points in subspaces of the moduli space of punctured Riemann surfaces. (orig.)
A Review of Accident Modelling Approaches for Complex Critical Sociotechnical Systems
National Research Council Canada - National Science Library
Qureshi, Zahid H
2008-01-01
.... This report provides a review of key traditional accident modelling approaches and their limitations, and describes new system-theoretic approaches to the modelling and analysis of accidents in safety-critical systems...
Forecasting in Complex Systems
Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Turcotte, D. L.; Donnellan, A.
2014-12-01
Complex nonlinear systems are typically characterized by many degrees of freedom, as well as interactions between the elements. Interesting examples can be found in the areas of earthquakes and finance. In these two systems, fat tails play an important role in the statistical dynamics. For earthquake systems, the Gutenberg-Richter magnitude-frequency is applicable, whereas for daily returns for the securities in the financial markets are known to be characterized by leptokurtotic statistics in which the tails are power law. Very large fluctuations are present in both systems. In earthquake systems, one has the example of great earthquakes such as the M9.1, March 11, 2011 Tohoku event. In financial systems, one has the example of the market crash of October 19, 1987. Both were largely unexpected events that severely impacted the earth and financial systems systemically. Other examples include the M9.3 Andaman earthquake of December 26, 2004, and the Great Recession which began with the fall of Lehman Brothers investment bank on September 12, 2013. Forecasting the occurrence of these damaging events has great societal importance. In recent years, national funding agencies in a variety of countries have emphasized the importance of societal relevance in research, and in particular, the goal of improved forecasting technology. Previous work has shown that both earthquakes and financial crashes can be described by a common Landau-Ginzburg-type free energy model. These metastable systems are characterized by fat tail statistics near the classical spinodal. Correlations in these systems can grow and recede, but do not imply causation, a common source of misunderstanding. In both systems, a common set of techniques can be used to compute the probabilities of future earthquakes or crashes. In this talk, we describe the basic phenomenology of these systems and emphasize their similarities and differences. We also consider the problem of forecast validation and verification
Ballet, Pascal; Rivière, Jérémy; Pothet, Alain; Théron, Michaël; Pichavant, Karine; Abautret, Frank; Fronville, Alexandra; Rodin, Vincent
2017-01-01
International audience; Modelling and teaching complex biological systems is a difficult process. Multi-Agent Based Simulations (MABS) have proved to be an appropriate approach both in research and education when dealing with such systems including emergent, self-organizing phenomena. This chapter presents NetBioDyn, an original software aimed at biologists (students, teachers, researchers) to easily build and simulate complex biological mechanisms observed in multicellular and molecular syst...
International Nuclear Information System (INIS)
Goelzer, H; Huybrechts, P; Raper, S C B; Loutre, M-F; Goosse, H; Fichefet, T
2012-01-01
Sea-level is expected to rise for a long time to come, even after stabilization of human-induced climatic warming. Here we use simulations with the Earth system model of intermediate complexity LOVECLIM to project sea-level changes over the third millennium forced with atmospheric greenhouse gas concentrations that stabilize by either 2000 or 2100 AD. The model includes 3D thermomechanical models of the Greenland and Antarctic ice sheets coupled to an atmosphere and an ocean model, a global glacier melt algorithm to account for the response of mountain glaciers and ice caps, and a procedure for assessing oceanic thermal expansion from oceanic heat uptake. Four climate change scenarios are considered to determine sea-level commitments. These assume a 21st century increase in greenhouse gases according to SRES scenarios B1, A1B and A2 with a stabilization of the atmospheric composition after the year 2100. One additional scenario assumes 1000 years of constant atmospheric composition from the year 2000 onwards. For our preferred model version, we find an already committed total sea-level rise of 1.1 m by 3000 AD. In experiments with greenhouse gas concentration stabilization at 2100 AD, the total sea-level rise ranges between 2.1 m (B1), 4.1 m (A1B) and 6.8 m (A2). In all scenarios, more than half of this amount arises from the Greenland ice sheet, thermal expansion is the second largest contributor, and the contribution of glaciers and ice caps is small as it is limited by the available ice volume of maximally 25 cm of sea-level equivalent. Additionally, we analysed the sensitivity of the sea-level contributions from an ensemble of nine different model versions that cover a large range of climate sensitivity realized by model parameter variations of the atmosphere–ocean model. Selected temperature indices are found to be good predictors for sea-level contributions from the different components of land ice and oceanic thermal expansion after 1000 years. (letter)
International Nuclear Information System (INIS)
Vasileiadis, N.; Tatsios, G.; Misdanitis, S.; Valougeorgis, D.
2016-01-01
Highlights: • An integrated s/w for modeling complex rarefied gas distribution systems is presented. • Analysis is based on kinetic theory of gases. • Code effectiveness is demonstrated by simulating the ITER divertor pumping system. • The present s/w has the potential to support design work in large vacuum systems. - Abstract: An integrated software tool for modeling and simulation of complex gas distribution systems operating under any vacuum conditions is presented and validated. The algorithm structure includes (a) the input geometrical and operational data of the network, (b) the definition of the fundamental set of network loops and pseudoloops, (c) the formulation and solution of the mass and energy conservation equations, (d) the kinetic data base of the flow rates for channels of any length in the whole range of the Knudsen number, supporting, in an explicit manner, the solution of the conservation equations and (e) the network output data (mainly node pressures and channel flow rates/conductance). The code validity is benchmarked under rough vacuum conditions by comparison with hydrodynamic solutions in the slip regime. Then, its feasibility, effectiveness and potential are demonstrated by simulating the ITER torus vacuum system with the six direct pumps based on the 2012 design of the ITER divertor. Detailed results of the flow patterns and paths in the cassettes, in the gaps between the cassettes and along the divertor ring, as well as of the total throughput for various pumping scenarios and dome pressures are provided. A comparison with previous results available in the literature is included.
Equation-free modeling unravels the behavior of complex ecological systems
DeAngelis, Donald L.; Yurek, Simeon
2015-01-01
Ye et al. (1) address a critical problem confronting the management of natural ecosystems: How can we make forecasts of possible future changes in populations to help guide management actions? This problem is especially acute for marine and anadromous fisheries, where the large interannual fluctuations of populations, arising from complex nonlinear interactions among species and with varying environmental factors, have defied prediction over even short time scales. The empirical dynamic modeling (EDM) described in Ye et al.’s report, the latest in a series of papers by Sugihara and his colleagues, offers a promising quantitative approach to building models using time series to successfully project dynamics into the future. With the term “equation-free” in the article title, Ye et al. (1) are suggesting broader implications of their approach, considering the centrality of equations in modern science. From the 1700s on, nature has been increasingly described by mathematical equations, with differential or difference equations forming the basic framework for describing dynamics. The use of mathematical equations for ecological systems came much later, pioneered by Lotka and Volterra, who showed that population cycles might be described in terms of simple coupled nonlinear differential equations. It took decades for Lotka–Volterra-type models to become established, but the development of appropriate differential equations is now routine in modeling ecological dynamics. There is no question that the injection of mathematical equations, by forcing “clarity and precision into conjecture” (2), has led to increased understanding of population and community dynamics. As in science in general, in ecology equations are a key method of communication and of framing hypotheses. These equations serve as compact representations of an enormous amount of empirical data and can be analyzed by the powerful methods of mathematics.
Modeling the Thermal Rocket Fuel Preparation Processes in the Launch Complex Fueling System
Directory of Open Access Journals (Sweden)
A. V. Zolin
2015-01-01
hydrocarbon fuel returning to the storage tank.Mathematical models of cooling and heating processes are built on the assumption that the heat exchange process of storage and environment is quasistationary.The paper presents relationships for determining the relative masses of nitrogen and time to perform the operation of cooling fuel from the initial to the desired final temperature as well as relationships to define the time of heating operation for a given capacity of the heat exchanger-heater and the pump station fueling system.The results of calculations of the relative liquid nitrogen costs during cooling of hydrocarbon gases depending on the mass flow rate of nitrogen in the cooling fuel system are shown in comparison with experimental data and numerical calculations. The maximum error of analytical calculation results and experimental values of the relative cost of liquid nitrogen does not exceed 4.5% and the error in determining the time required for operations of temperature preparation does not exceed 5%.Analytical relationships and results of calculations obtained on their basis are adequate and in compliance with experimental results, in accuracy are on a par with results of numerical calculations and, as compared to numerical solution, greatly simplify a procedure of implemented design calculations of fuel temperature preparation processes. Using these relationships allows to analyze the effectiveness of the operations of heating and cooling hydrocarbon fuel depending on the design parameters of the storage capacity, its thermal insulation, mass of fuel, thermal power of the heating devices, flow of nitrogen, as well as to determine the required mass of liquid nitrogen and the operation parameters of cooling (heating fuel for filling systems of launch complexes for different values of the environmental parameters, the initial and desired final temperaturesof the fuel.
Decentralized control of complex systems
Siljak, Dragoslav D
2011-01-01
Complex systems require fast control action in response to local input, and perturbations dictate the use of decentralized information and control structures. This much-cited reference book explores the approaches to synthesizing control laws under decentralized information structure constraints.Starting with a graph-theoretic framework for structural modeling of complex systems, the text presents results related to robust stabilization via decentralized state feedback. Subsequent chapters explore optimization, output feedback, the manipulative power of graphs, overlapping decompositions and t
Simulation in Complex Modelling
DEFF Research Database (Denmark)
Nicholas, Paul; Ramsgaard Thomsen, Mette; Tamke, Martin
2017-01-01
This paper will discuss the role of simulation in extended architectural design modelling. As a framing paper, the aim is to present and discuss the role of integrated design simulation and feedback between design and simulation in a series of projects under the Complex Modelling framework. Complex...... performance, engage with high degrees of interdependency and allow the emergence of design agency and feedback between the multiple scales of architectural construction. This paper presents examples for integrated design simulation from a series of projects including Lace Wall, A Bridge Too Far and Inflated...... Restraint developed for the research exhibition Complex Modelling, Meldahls Smedie Gallery, Copenhagen in 2016. Where the direct project aims and outcomes have been reported elsewhere, the aim for this paper is to discuss overarching strategies for working with design integrated simulation....
Holder, Lauren N.; Scherer, Hannah H.; Herbert, Bruce E.
2017-01-01
Engaging students in problem-solving concerning environmental issues in near-surface complex Earth systems involves developing student conceptualization of the Earth as a system and applying that scientific knowledge to the problems using practices that model those used by professionals. In this article, we review geoscience education research…
Complex logistics audit system
Directory of Open Access Journals (Sweden)
Zuzana Marková
2010-02-01
Full Text Available Complex logistics audit system is a tool for realization of logistical audit in the company. The current methods for logistics auditare based on “ad hok” analysis of logisticsl system. This paper describes system for complex logistics audit. It is a global diagnosticsof logistics processes and functions of enterprise. The goal of logistics audit is to provide comparative documentation for managementabout state of logistics in company and to show the potential of logistics changes in order to achieve more effective companyperformance.
Modelling complex systems of heterogeneous agents to better design sustainability transitions policy
Mercure, J.F.A.; Pollitt, H.; Bassi, A.M.; Viñuales, J.E.; Edwards, N.R.
2016-01-01
This article proposes a fundamental methodological shift in the modelling of policy interventions for sustainability transitions in order to account for complexity (e.g. self-reinforcing mechanisms, such as technology lock-ins, arising from multi-agent interactions) and agent heterogeneity (e.g.
Dirnbeck, Matthew R.
Biological systems pose a challenge both for learners and teachers because they are complex systems mediated by feedback loops; networks of cause-effect relationships; and non-linear, hierarchical, and emergent properties. Teachers and scientists routinely use models to communicate ideas about complex systems. Model-based pedagogies engage students in model construction as a means of practicing higher-order reasoning skills. One such modeling paradigm describes systems in terms of their structures, behaviors, and functions (SBF). The SBF framework is a simple modeling language that has been used to teach about complex biological systems. Here, we used student-generated SBF models to assess students' causal reasoning in the context of a novel biological problem on an exam. We compared students' performance on the modeling problem, their performance on a set of knowledge/comprehension questions, and their performance on a set of scientific reasoning questions. We found that students who performed well on knowledge and understanding questions also constructed more networked, higher quality models. Previous studies have shown that learners' mental maps increase in complexity with increased expertise. We wanted to investigate if biology students with varying levels of training in biology showed a similar pattern when constructing system models. In a pilot study, we administered the same modeling problem to two additional groups of students: 1) an animal physiology course for students pursuing a major in biology (n=37) and 2) an exercise physiology course for non-majors (n=27). We found that there was no significant difference in model organization across the three student populations, but there was a significant difference in the ability to represent function between the three populations. Between the three groups the non-majors had the lowest function scores, the introductory majors had the middle function scores, and the upper division majors had the highest function
2011-01-01
The domain of nonlinear dynamical systems and its mathematical underpinnings has been developing exponentially for a century, the last 35 years seeing an outpouring of new ideas and applications and a concomitant confluence with ideas of complex systems and their applications from irreversible thermodynamics. A few examples are in meteorology, ecological dynamics, and social and economic dynamics. These new ideas have profound implications for our understanding and practice in domains involving complexity, predictability and determinism, equilibrium, control, planning, individuality, responsibility and so on. Our intention is to draw together in this volume, we believe for the first time, a comprehensive picture of the manifold philosophically interesting impacts of recent developments in understanding nonlinear systems and the unique aspects of their complexity. The book will focus specifically on the philosophical concepts, principles, judgments and problems distinctly raised by work in the domain of comple...
Marek, Michael W.; Wu, Wen-Chi Vivian
2014-01-01
This conceptual, interdisciplinary inquiry explores Complex Dynamic Systems as the concept relates to the internal and external environmental factors affecting computer assisted language learning (CALL). Based on the results obtained by de Rosnay ["World Futures: The Journal of General Evolution", 67(4/5), 304-315 (2011)], who observed…
Chen, Pei; Liu, Rui; Li, Yongjun; Chen, Luonan
2016-07-15
Identifying the critical state or pre-transition state just before the occurrence of a phase transition is a challenging task, because the state of the system may show little apparent change before this critical transition during the gradual parameter variations. Such dynamics of phase transition is generally composed of three stages, i.e. before-transition state, pre-transition state and after-transition state, which can be considered as three different Markov processes. By exploring the rich dynamical information provided by high-throughput data, we present a novel computational method, i.e. hidden Markov model (HMM) based approach, to detect the switching point of the two Markov processes from the before-transition state (a stationary Markov process) to the pre-transition state (a time-varying Markov process), thereby identifying the pre-transition state or early-warning signals of the phase transition. To validate the effectiveness, we apply this method to detect the signals of the imminent phase transitions of complex systems based on the simulated datasets, and further identify the pre-transition states as well as their critical modules for three real datasets, i.e. the acute lung injury triggered by phosgene inhalation, MCF-7 human breast cancer caused by heregulin and HCV-induced dysplasia and hepatocellular carcinoma. Both functional and pathway enrichment analyses validate the computational results. The source code and some supporting files are available at https://github.com/rabbitpei/HMM_based-method lnchen@sibs.ac.cn or liyj@scut.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Replicating the Ice-Volume Signal of the Early Pleistocene with a Complex Earth System Model
Tabor, C. R.; Poulsen, C. J.; Pollard, D.
2013-12-01
Milankovitch theory proposes high-latitude summer insolation intensity paces the ice ages by controlling perennial snow cover amounts (Milankovitch, 1941). According to theory, the ~21 kyr cycle of precession should dominate the ice-volume records since it has the greatest influence on high-latitude summer insolation. Modeling experiments frequently support Milankovitch theory by attributing the majority of Northern Hemisphere high-latitude summer snowmelt to changes in the cycle of precession (e.g. Jackson and Broccoli, 2003). However, ice-volume proxy records, especially those of the Early Pleistocene (2.6-0.8 Ma), display variability with a period of ~41 kyr (Raymo and Lisiecki, 2005), indicative of insolation forcing from obliquity, which has a much smaller influence on summer insolation intensity than precession. Several hypotheses attempt to explain the discrepancies between Milkankovitch theory and the proxy records by invoking phenomena such as insolation gradients (Raymo and Nisancioglu, 2003), hemispheric offset (Raymo et al., 2006; Lee and Poulsen, 2009), and integrated summer energy (Huybers, 2006); however, all of these hypotheses contain caveats (Ruddiman, 2006) and have yet to be supported by modeling studies that use a complex GCM. To explore potential solutions to this '41 kyr problem,' we use an Earth system model composed of the GENESIS GCM and Land Surface model, the BIOME4 vegetation model, and the Pennsylvania State ice-sheet model. Using an asynchronous coupling technique, we run four idealized transient combinations of obliquity and precession, representing the orbital extremes of the Pleistocene (Berger and Loutre, 1991). Each experiment is run through several complete orbital cycles with a dynamic ice domain spanning North America and Greenland, and fixed preindustrial greenhouse-gas concentrations. For all orbital configurations, model results produce greater ice-volume spectral power at the frequency of obliquity despite significantly
Epidemic modeling in complex realities.
Colizza, Vittoria; Barthélemy, Marc; Barrat, Alain; Vespignani, Alessandro
2007-04-01
In our global world, the increasing complexity of social relations and transport infrastructures are key factors in the spread of epidemics. In recent years, the increasing availability of computer power has enabled both to obtain reliable data allowing one to quantify the complexity of the networks on which epidemics may propagate and to envision computational tools able to tackle the analysis of such propagation phenomena. These advances have put in evidence the limits of homogeneous assumptions and simple spatial diffusion approaches, and stimulated the inclusion of complex features and heterogeneities relevant in the description of epidemic diffusion. In this paper, we review recent progresses that integrate complex systems and networks analysis with epidemic modelling and focus on the impact of the various complex features of real systems on the dynamics of epidemic spreading.
Complexity in Dynamical Systems
Moore, Cristopher David
The study of chaos has shown us that deterministic systems can have a kind of unpredictability, based on a limited knowledge of their initial conditions; after a finite time, the motion appears essentially random. This observation has inspired a general interest in the subject of unpredictability, and more generally, complexity; how can we characterize how "complex" a dynamical system is?. In this thesis, we attempt to answer this question with a paradigm of complexity that comes from computer science, we extract sets of symbol sequences, or languages, from a dynamical system using standard methods of symbolic dynamics; we then ask what kinds of grammars or automata are needed a generate these languages. This places them in the Chomsky heirarchy, which in turn tells us something about how subtle and complex the dynamical system's behavior is. This gives us insight into the question of unpredictability, since these automata can also be thought of as computers attempting to predict the system. In the culmination of the thesis, we find a class of smooth, two-dimensional maps which are equivalent to the highest class in the Chomsky heirarchy, the turning machine; they are capable of universal computation. Therefore, these systems possess a kind of unpredictability qualitatively different from the usual "chaos": even if the initial conditions are known exactly, questions about the system's long-term dynamics are undecidable. No algorithm exists to answer them. Although this kind of unpredictability has been discussed in the context of distributed, many-degree-of -freedom systems (for instance, cellular automata) we believe this is the first example of such phenomena in a smooth, finite-degree-of-freedom system.
Modeling complexes of modeled proteins.
Anishchenko, Ivan; Kundrotas, Petras J; Vakser, Ilya A
2017-03-01
Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C α RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Bone, M.; Cloutier, R.L.; Gill, E.K.A.; Verma, D.
2009-01-01
There is increased recognition of the role of systems engineering in reducing the risk (technical, cost, and schedule) on complex space systems development and integration projects. A number of international systems engineering standards have been published in the last five years (ISO 15288, IEEE
Managing Complex Dynamical Systems
Cox, John C.; Webster, Robert L.; Curry, Jeanie A.; Hammond, Kevin L.
2011-01-01
Management commonly engages in a variety of research designed to provide insight into the motivation and relationships of individuals, departments, organizations, etc. This paper demonstrates how the application of concepts associated with the analysis of complex systems applied to such data sets can yield enhanced insights for managerial action.
Analysis of Social Network Dynamics with Models from the Theory of Complex Adaptive Systems
Lymperopoulos , Ilias; Lekakos , George
2013-01-01
Part 4: Protocols, Regulation and Social Networking; International audience; The understanding and modeling of social dynamics in a complex and unpredictable world, emerges as a research target of particular importance. Success in this direction can yield valuable knowledge as to how social phenomena form and evolve in varying socioeconomic contexts comprising economic crises, societal disasters, cultural differences and security threats among others. The study of social dynamics occurring in...
Vernon, Ian; Liu, Junli; Goldstein, Michael; Rowe, James; Topping, Jen; Lindsey, Keith
2018-01-02
Many mathematical models have now been employed across every area of systems biology. These models increasingly involve large numbers of unknown parameters, have complex structure which can result in substantial evaluation time relative to the needs of the analysis, and need to be compared to observed data of various forms. The correct analysis of such models usually requires a global parameter search, over a high dimensional parameter space, that incorporates and respects the most important sources of uncertainty. This can be an extremely difficult task, but it is essential for any meaningful inference or prediction to be made about any biological system. It hence represents a fundamental challenge for the whole of systems biology. Bayesian statistical methodology for the uncertainty analysis of complex models is introduced, which is designed to address the high dimensional global parameter search problem. Bayesian emulators that mimic the systems biology model but which are extremely fast to evaluate are embeded within an iterative history match: an efficient method to search high dimensional spaces within a more formal statistical setting, while incorporating major sources of uncertainty. The approach is demonstrated via application to a model of hormonal crosstalk in Arabidopsis root development, which has 32 rate parameters, for which we identify the sets of rate parameter values that lead to acceptable matches between model output and observed trend data. The multiple insights into the model's structure that this analysis provides are discussed. The methodology is applied to a second related model, and the biological consequences of the resulting comparison, including the evaluation of gene functions, are described. Bayesian uncertainty analysis for complex models using both emulators and history matching is shown to be a powerful technique that can greatly aid the study of a large class of systems biology models. It both provides insight into model behaviour
Torres-Pomales, Wilfredo
2014-01-01
A system is safety-critical if its failure can endanger human life or cause significant damage to property or the environment. State-of-the-art computer systems on commercial aircraft are highly complex, software-intensive, functionally integrated, and network-centric systems of systems. Ensuring that such systems are safe and comply with existing safety regulations is costly and time-consuming as the level of rigor in the development process, especially the validation and verification activities, is determined by considerations of system complexity and safety criticality. A significant degree of care and deep insight into the operational principles of these systems is required to ensure adequate coverage of all design implications relevant to system safety. Model-based development methodologies, methods, tools, and techniques facilitate collaboration and enable the use of common design artifacts among groups dealing with different aspects of the development of a system. This paper examines the application of model-based development to complex and safety-critical aircraft computer systems. Benefits and detriments are identified and an overall assessment of the approach is given.
Weyers, Benjamin; Burkolter, Dina; Luther, Wolfram; Kluge, Annette
2012-01-01
Controlling and observing complex systems is central to the study of human-machine interaction. In our understanding, there is much to be gained from integrating formal modeling and analysis, including the reconfiguration of user interfaces, with the development of user interfaces with high
Friedrich, T.; Timmermann, A.; Menviel, L.; Elison Timm, O.; Mouchet, A.; Roche, D.M.V.A.P.
2010-01-01
The mechanism triggering centennial-to-millennial-scale variability of the Atlantic Meridional Overturning Circulation (AMOC) in the earth system model of intermediate complexity LOVECLIM is investigated. It is found that for several climate boundary conditions such as low obliquity values (∼22.1 )
Luo, Weiqi
The key to understanding and predicting the behavior of materials is the knowledge of their structures. Many properties of materials samples are not solely determined by their average chemical compositions which one may easily control. Instead, they are profoundly influenced by structural features of different characteristic length scales. Starting in the last century, metallurgical engineering has mostly been microstructure engineering. With the further evolution of materials science, structural features of smaller length scales down to the atomic structure, have become of interest for the purpose of properties engineering and functionalizing materials and are, therefore, subjected to study. As computer modeling is becoming more powerful due to the dramatic increase of computational resources and software over the recent decades, there is an increasing demand for atomistic simulations with the goal of better understanding materials behavior on the atomic scale. Density functional theory (DFT) is a quantum mechanics based approach to calculate electron distribution, total energy and interatomic forces with high accuracy. From these, atomic structures and thermal effects can be predicted. However, DFT is mostly applied to relatively simple systems because it is computationally very demanding. In this thesis, the current limits of DFT applications are explored by studying relatively complex systems, namely, carbynes, carbon nanotube (CNT) devices and bulk metallic glasses (BMGs). Special care is taken to overcome the limitations set by small system sizes and time scales that often prohibit DFT from being applied to realistic systems under realistic external conditions. In the first study, we examine the possible existence of a third solid phase of carbon with linear bonding called carbyne, which has been suggested in the literature and whose formation has been suggested to be detrimental to high-temperature carbon materials. We have suggested potential structures for
Validation of a Perceptual Distraction Model in a Complex Personal Sound Zone System
DEFF Research Database (Denmark)
Rämö, Jussi; Marsh, Steven; Bech, Søren
2016-01-01
This paper evaluates a previously proposed perceptual model predicting user’s perceived distraction caused by interfering audio programmes. The distraction model was originally trained using a simple sound reproduction system for music-on-music interference situations and it has not been formally...
Energy Technology Data Exchange (ETDEWEB)
Bykova, E V
1982-01-01
The author proposes an interactive method employing a semantic network representation of knowledge. Her model operates in 2 stages: intrinsic evaluation of the quality of the system; and analysis of the functioning of the system, which accumulates expert experience in an adaptive dialogue process. 6 references.
Appropriate complexity landscape modeling
Larsen, Laurel G.; Eppinga, Maarten B.; Passalacqua, Paola; Getz, Wayne M.; Rose, Kenneth A.; Liang, Man
Advances in computing technology, new and ongoing restoration initiatives, concerns about climate change's effects, and the increasing interdisciplinarity of research have encouraged the development of landscape-scale mechanistic models of coupled ecological-geophysical systems. However,
Zonal NePhRO scoring system: a superior renal tumor complexity classification model.
Hakky, Tariq S; Baumgarten, Adam S; Allen, Bryan; Lin, Hui-Yi; Ercole, Cesar E; Sexton, Wade J; Spiess, Philippe E
2014-02-01
Since the advent of the first standardized renal tumor complexity system, many subsequent scoring systems have been introduced, many of which are complicated and can make it difficult to accurately measure data end points. In light of these limitations, we introduce the new zonal NePhRO scoring system. The zonal NePhRO score is based on 4 anatomical components that are assigned a score of 1, 2, or 3, and their sum is used to classify renal tumors. The zonal NePhRO scoring system is made up of the (Ne)arness to collecting system, (Ph)ysical location of the tumor in the kidney, (R)adius of the tumor, and (O)rganization of the tumor. In this retrospective study, we evaluated patients exhibiting clinical stage T1a or T1b who underwent open partial nephrectomy performed by 2 genitourinary surgeons. Each renal unit was assigned both a zonal NePhRO score and a RENAL (radius, exophytic/endophytic properties, nearness of tumor to the collecting system or sinus in millimeters, anterior/posterior, location relative to polar lines) score, and a blinded reviewer used the same preoperative imaging study to obtain both scores. Additional data points gathered included age, clamp time, complication rate, urine leak rate, intraoperative blood loss, and pathologic tumor size. One hundred sixty-six patients underwent open partial nephrectomy. There were 37 perioperative complications quantitated using the validated Clavien-Dindo system; their occurrence was predicted by the NePhRO score on both univariate and multivariate analyses (P = .0008). Clinical stage, intraoperative blood loss, and tumor diameter were all correlated with the zonal NePhRO score on univariate analysis only. The zonal NePhRO scoring system is a simpler tool that accurately predicts the surgical complexity of a renal lesion. Copyright © 2014 Elsevier Inc. All rights reserved.
Sung, Dia; You, Yeongmahn; Song, Ji Hoon
2008-01-01
The purpose of this research is to explore the possibility of viable learning organizations based on identifying viable organizational learning mechanisms. Two theoretical foundations, complex system theory and viable system theory, have been integrated to provide the rationale for building the sustainable organizational learning mechanism. The…
Directory of Open Access Journals (Sweden)
Krzysztof Małecki
2017-12-01
Full Text Available A complex system is a set of mutually interacting elements for which it is possible to construct a mathematical model. This article focuses on the cellular automata theory and the graph theory in order to compare various types of cellular automata and to analyse applications of graph structures together with cellular automata. It proposes a graph cellular automaton with a variable configuration of cells and relation-based neighbourhoods (r–GCA. The developed mechanism enables modelling of phenomena found in complex systems (e.g., transport networks, urban logistics, social networks taking into account the interaction between the existing objects. As an implementation example, modelling of moving vehicles has been made and r–GCA was compared to the other cellular automata models simulating the road traffic and used in the computer simulation process.
Energy Technology Data Exchange (ETDEWEB)
Brown, D L
2009-05-01
Many complex systems of importance to the U.S. Department of Energy consist of networks of discrete components. Examples are cyber networks, such as the internet and local area networks over which nearly all DOE scientific, technical and administrative data must travel, the electric power grid, social networks whose behavior can drive energy demand, and biological networks such as genetic regulatory networks and metabolic networks. In spite of the importance of these complex networked systems to all aspects of DOE's operations, the scientific basis for understanding these systems lags seriously behind the strong foundations that exist for the 'physically-based' systems usually associated with DOE research programs that focus on such areas as climate modeling, fusion energy, high-energy and nuclear physics, nano-science, combustion, and astrophysics. DOE has a clear opportunity to develop a similarly strong scientific basis for understanding the structure and dynamics of networked systems by supporting a strong basic research program in this area. Such knowledge will provide a broad basis for, e.g., understanding and quantifying the efficacy of new security approaches for computer networks, improving the design of computer or communication networks to be more robust against failures or attacks, detecting potential catastrophic failure on the power grid and preventing or mitigating its effects, understanding how populations will respond to the availability of new energy sources or changes in energy policy, and detecting subtle vulnerabilities in large software systems to intentional attack. This white paper outlines plans for an aggressive new research program designed to accelerate the advancement of the scientific basis for complex networked systems of importance to the DOE. It will focus principally on four research areas: (1) understanding network structure, (2) understanding network dynamics, (3) predictive modeling and simulation for complex
International Nuclear Information System (INIS)
Brown, D.L.
2009-01-01
Many complex systems of importance to the U.S. Department of Energy consist of networks of discrete components. Examples are cyber networks, such as the internet and local area networks over which nearly all DOE scientific, technical and administrative data must travel, the electric power grid, social networks whose behavior can drive energy demand, and biological networks such as genetic regulatory networks and metabolic networks. In spite of the importance of these complex networked systems to all aspects of DOE's operations, the scientific basis for understanding these systems lags seriously behind the strong foundations that exist for the 'physically-based' systems usually associated with DOE research programs that focus on such areas as climate modeling, fusion energy, high-energy and nuclear physics, nano-science, combustion, and astrophysics. DOE has a clear opportunity to develop a similarly strong scientific basis for understanding the structure and dynamics of networked systems by supporting a strong basic research program in this area. Such knowledge will provide a broad basis for, e.g., understanding and quantifying the efficacy of new security approaches for computer networks, improving the design of computer or communication networks to be more robust against failures or attacks, detecting potential catastrophic failure on the power grid and preventing or mitigating its effects, understanding how populations will respond to the availability of new energy sources or changes in energy policy, and detecting subtle vulnerabilities in large software systems to intentional attack. This white paper outlines plans for an aggressive new research program designed to accelerate the advancement of the scientific basis for complex networked systems of importance to the DOE. It will focus principally on four research areas: (1) understanding network structure, (2) understanding network dynamics, (3) predictive modeling and simulation for complex networked systems
Tobert, Conrad M; Shoemaker, Allen; Kahnoski, Richard J; Lane, Brian R
2015-04-01
To investigate whether a combination of variables from each nephrometry system improves performance. There are 3 first-generation systems that quantify tumor complexity: R.E.N.A.L. nephrometry score (RNS), preoperative aspects and dimensions used for an anatomical (PADUA) classification (PC), and centrality index (CI). Although each has been subjected to validation and comparative analysis, to our knowledge, no work has been done to combine variables from each method to optimize their performance. Scores were assigned to each of 276 patients undergoing partial nephrectomy (PN) or radical nephrectomy (RN). Individual components of all 3 systems were evaluated in multivariable logistic regression analysis of surgery type (PN vs. RN) and combined into a "second-generation model." In multivariable analysis, each scoring system was a significant predictor of PN vs. RN (Psystems, CI was most highly correlated with surgery type (area under the curve [AUC] = 0.91), followed by RNS (AUC = 0.90) and PC (AUC = 0.88). Each individual component of these scoring systems was also a predictor of surgery type (Psystem (RNS), location along the lateral rim (PC), and centrality (CI). A novel model in which these 4 variables were rescaled outperformed each first-generation system (AUC = 0.91). Optimization of first-generation models of renal tumor complexity results in a novel scoring system, which strongly predicts surgery type. This second-generation model should aid comprehension, but future work is still needed to establish the most clinically useful model. Copyright © 2015 Elsevier Inc. All rights reserved.
Modeling complex biological flows in multi-scale systems using the APDEC framework
Trebotich, David
2006-09-01
We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscous flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.
Gromek, Katherine Emily
A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.
Novikov, Vladimir
2010-01-01
The article deals with categorical apparatus of information management systems to build a model pairing SWOT-matrix and the quality management system, which is especially important for the energytion industry.
Modeling of complex premixed burner systems by using flamelet-generated manifolds
Oijen, van J.A.; Lammers, F.A.; Goey, de L.P.H.
2001-01-01
The numerical modeling of realistic burner systems puts a very high demand on computational recources.The computational cost of combustion simulations can be reduced by reduction techniques which simplify the chemical kinetics. In this paper the recently introduced Flamelet-Generated Manifold method
Directory of Open Access Journals (Sweden)
Aloah J Pope
2015-08-01
Full Text Available Interdependencies of ecologic, hydrologic, and social systems challenge traditional approaches to natural resource management in semi-arid regions. As a complex social-ecological system, water demands in the Sonoran Desert from agricultural and urban users often conflicts with water needs for its ecologically-significant riparian corridors. To explore this system, we developed an agent-based model to simulate complex feedbacks between human decisions and environmental conditions in the Rio Sonora Watershed. Cognitive mapping in conjunction with stakeholder participation produced a Bayesian model of conditional probabilities of local human decision-making processes resulting to changes in water demand. Probabilities created in the Bayesian model were incorporated into the agent-based model, so that each agent had a unique probability to make a positive decision based on its perceived environment at each point in time and space. By using a Bayesian approach, uncertainty in the human decision-making process could be incorporated. The spatially-explicit agent-based model simulated changes in depth-to-groundwater by well pumping based on an agent’s water demand. Changes in depth-to-groundwater feedback to influence agent behavior, as well as determine unique vegetation classes within the riparian corridor. Each vegetation class then provides varying stakeholder-defined quality values of ecosystem services. Using this modeling approach allowed us to examine effects on both the ecological and social system of semi-arid riparian corridors under various scenarios. The insight provided by the model contributes to understanding how specific interventions may alter the complex social-ecological system in the future.
Increase of Organization in Complex Systems
Georgiev, Georgi Yordanov; Daly, Michael; Gombos, Erin; Vinod, Amrit; Hoonjan, Gajinder
2013-01-01
Measures of complexity and entropy have not converged to a single quantitative description of levels of organization of complex systems. The need for such a measure is increasingly necessary in all disciplines studying complex systems. To address this problem, starting from the most fundamental principle in Physics, here a new measure for quantity of organization and rate of self-organization in complex systems based on the principle of least (stationary) action is applied to a model system -...
Virtual skeletal complex model- and landmark-guided orthognathic surgery system.
Lee, Sang-Jeong; Woo, Sang-Yoon; Huh, Kyung-Hoe; Lee, Sam-Sun; Heo, Min-Suk; Choi, Soon-Chul; Han, Jeong Joon; Yang, Hoon Joo; Hwang, Soon Jung; Yi, Won-Jin
2016-05-01
In this study, correction of the maxillofacial deformities was performed by repositioning bone segments to an appropriate location according to the preoperative planning in orthognathic surgery. The surgery was planned using the patient's virtual skeletal models fused with optically scanned three-dimensional dentition. The virtual maxillomandibular complex (MMC) model of the patient's final occlusal relationship was generated by fusion of the maxillary and mandibular models with scanned occlusion. The final position of the MMC was simulated preoperatively by planning and was used as a goal model for guidance. During surgery, the intraoperative registration was finished immediately using only software processing. For accurate repositioning, the intraoperative MMC model was visualized on the monitor with respect to the simulated MMC model, and the intraoperative positions of multiple landmarks were also visualized on the MMC surface model. The deviation errors between the intraoperative and the final positions of each landmark were visualized quantitatively. As a result, the surgeon could easily recognize the three-dimensional deviation of the intraoperative MMC state from the final goal model without manually applying a pointing tool, and could also quickly determine the amount and direction of further MMC movements needed to reach the goal position. The surgeon could also perform various osteotomies and remove bone interference conveniently, as the maxillary tracking tool could be separated from the MMC. The root mean square (RMS) difference between the preoperative planning and the intraoperative guidance was 1.16 ± 0.34 mm immediately after repositioning. After surgery, the RMS differences between the planning and the postoperative computed tomographic model were 1.31 ± 0.28 mm and 1.74 ± 0.73 mm for the maxillary and mandibular landmarks, respectively. Our method provides accurate and flexible guidance for bimaxillary orthognathic surgery based on
Complex adaptive systems ecology
DEFF Research Database (Denmark)
Sommerlund, Julie
2003-01-01
In the following, I will analyze two articles called Complex Adaptive Systems EcologyI & II (Molin & Molin, 1997 & 2000). The CASE-articles are some of the more quirkyarticles that have come out of the Molecular Microbial Ecology Group - a groupwhere I am currently making observational studies....... They are the result of acooperation between Søren Molin, professor in the group, and his brother, JanMolin, professor at Department of Organization and Industrial Sociology atCopenhagen Business School. The cooperation arises from the recognition that bothmicrobial ecology and sociology/organization theory works...
On modeling complex interplay in small-scale self-organized socio-hydrological systems
Muneepeerakul, Rachata
2017-04-01
Successful and sustainable socio-hydrological systems, as in any coupled natural human-systems, require effective governance, which depends on the existence of proper infrastructure (both hard and soft). Recent work has addressed systems in which resource users and the organization responsible for maintaining the infrastructure are separate entities. However, many socio-hydrological systems, especially in developing countries, are small and without such formal division of labor; rather, such division of labor typically arises from self-organization within the population. In this work, we modify and mathematically operationalize a conceptual framework by developing a system of differential equations that capture the strategic behavior within such a self-organized population, its interplay with infrastructure characteristics and hydrological dynamics, and feedbacks between these elements. The model yields a number of insightful conditions related to long-term sustainability and collapse of the socio-hydrological system in the form of relationships between biophysical and social factors. These relationships encapsulate nonlinear interactions of these factors. The modeling framework is grounded in a solid conceptual foundation upon which additional modifications and realism can be built for potential reconciliation between socio-hydrology with other related fields and further applications.
The complex modelling of various effects of the sub-slab ventilation systems
International Nuclear Information System (INIS)
Svoboda, Z.
2004-01-01
Sub-slab ventilation systems and, in particular, sub-slab depressurization (SSD) systems are among the most efficient radon protective and remedial measures. Numerical modelling can serve as a very powerful tool in the design stage of such systems. The calculations include estimation of the pressure field in the ground under the house with an SSD system and estimation of the radon concentration field. The SSD system also affects the temperature and relative humidity distribution, and therefore those fields should be calculated as well. All the analyses can be carried out applying the simplification of a non-transient steady-state behavior. The numerical solution can be obtained by using the finite difference method or the finite element method. The results of numerical calculation comprise the air pressure field under the building with SSD system, radon concentration field, and temperature and relative humidity fields. The reliability of the numerical models has been verified on six houses with different SSD systems. The results obtained from one house are presented to demonstrate the complete process of verification. The remedial action consisted in the installation of an SSD system in combination with rebuilding of the floors. Soil air temperature, relative humidity, pressure difference and soil air radon concentration were measured continuously. All measurements were carried out for the two modes, i.e. with the SSD system operational or disabled. The first numerical analysis was the calculation of the three-dimensional air pressure field in the whole sub-slab space of the experimental house. The correlation between the calculated and observed values was very good (agreement better than 10%). The calculation of the two-dimensional steady-state temperature and relative humidity field also exhibited a good agreement with the observed values, with differences below 15%. The two-dimensional steady-state field of radon concentrations in the soil under the experimental
Freua, Mateus Castelani; Santana, Miguel Henrique de Almeida; Ventura, Ricardo Vieira; Tedeschi, Luis Orlindo; Ferraz, José Bento Sterman
2017-08-01
The interplay between dynamic models of biological systems and genomics is based on the assumption that genetic variation of the complex trait (i.e., outcome of model behavior) arises from component traits (i.e., model parameters) in lower hierarchical levels. In order to provide a proof of concept of this statement for a cattle growth model, we ask whether model parameters map genomic regions that harbor quantitative trait loci (QTLs) already described for the complex trait. We conducted a genome-wide association study (GWAS) with a Bayesian hierarchical LASSO method in two parameters of the Davis Growth Model, a system of three ordinary differential equations describing DNA accretion, protein synthesis and degradation, and fat synthesis. Phenotypic and genotypic data were available for 893 Nellore (Bos indicus) cattle. Computed values for parameter k 1 (DNA accretion rate) ranged from 0.005 ± 0.003 and for α (constant for energy for maintenance requirement) 0.134 ± 0.024. The expected biological interpretation of the parameters is confirmed by QTLs mapped for k 1 and α. QTLs within genomic regions mapped for k 1 are expected to be correlated with the DNA pool: body size and weight. Single nucleotide polymorphisms (SNPs) which were significant for α mapped QTLs that had already been associated with residual feed intake, feed conversion ratio, average daily gain (ADG), body weight, and also dry matter intake. SNPs identified for k 1 were able to additionally explain 2.2% of the phenotypic variability of the complex ADG, even when SNPs for k 1 did not match the genomic regions associated with ADG. Although improvements are needed, our findings suggest that genomic analysis on component traits may help to uncover the genetic basis of more complex traits, particularly when lower biological hierarchies are mechanistically described by mathematical simulation models.
System model the processing of heterogeneous sensory information in robotized complex
Nikolaev, V.; Titov, V.; Syryamkin, V.
2018-05-01
Analyzed the scope and the types of robotic systems consisting of subsystems of the form "a heterogeneous sensors data processing subsystem". On the basis of the Queuing theory model is developed taking into account the unevenness of the intensity of information flow from the sensors to the subsystem of information processing. Analytical solution to assess the relationship of subsystem performance and uneven flows. The research of the obtained solution in the range of parameter values of practical interest.
International Nuclear Information System (INIS)
Thien, Bruno M.J.; Kulik, Dmitrii A.; Curti, Enzo
2014-01-01
Highlights: • There are several models able to describe trace element partitioning in growing minerals. • To describe complex systems, those models must be embedded in a geochemical code. • We merged two models into a unified one suitable for implementation in a geochemical code. • This unified model was tested against coprecipitation experimental data. • We explored how our model reacts to solution depletion effects. - Abstract: Thermodynamics alone is usually not sufficient to predict growth-rate dependencies of trace element partitioning into host mineral solid solutions. In this contribution, two uptake kinetic models were analyzed that are promising in terms of mechanistic understanding and potential for implementation in geochemical modelling codes. The growth Surface Entrapment Model (Watson, 2004) and the Surface Reaction Kinetic Model (DePaolo, 2011) were shown to be complementary, and under certain assumptions merged into a single analytical expression. This Unified Uptake Kinetics Model was implemented in GEMS3K and GEM-Selektor codes ( (http://gems.web.psi.ch)), a Gibbs energy minimization package for geochemical modelling. This implementation extends the applicability of the unified uptake kinetics model to accounting for non-trivial factors influencing the trace element partitioning into solid solutions, such as the changes in aqueous solution composition and speciation, or the depletion effects in closed geochemical systems
Directory of Open Access Journals (Sweden)
Katarzyna Grzybowska
2015-06-01
Full Text Available Background: In her previous research, the author of this publication indicates that coordination is a dependent variable which has a great driving force and is a very unstable factor. This results in the fact that all of the actions connected with coordination have an impact on other factors of cooperation as well as the integration of the enterprises in the structures of a supply chain type structure. Material and methods: The article has been divided into two basic parts. The first part regards the reference models in complex systems (supply chain systems. They can constitute a starting point for the modelling of target processes in the built supply chain structure. The second part presents template process models (Reference Models for selected action coordination mechanisms during enterprise cooperation. The aim of the article is the presentation the model an Electronic Bulletin Board (EBB, as a mechanism of coordination of actions in complex systems. Results: The article was prepared on the basis of literature from the researched area. The material was also prepared on the basis of interviews with practitioners. They have allowed for the preparation of template process models (Reference Models for selected action coordination methods in the supply chain. Conclusions: The result of the work is a prepared model as well as its description in the use of IDEF0. The presented model is a demonstrative model. The proposed reference model makes it possible to define the parameters of a selected mechanism of coordination of actions, and forms a basis for affecting the progression of the process through an analysis of values of identified parameters. The parameterization of elements constitutes the foundation for the monitoring of the process via 1 unambiguous identification of the object of monitoring and 2 analysis of different variants of the progression of the process.
Simulation modeling and analysis of a complex system of a thermal power plant
Directory of Open Access Journals (Sweden)
Sorabh Gupta
2009-09-01
Full Text Available The present paper deals with the opportunities for the modeling of flue gas and air system of a thermal power plant by making the performance evaluation using probabilistic approach. The present system of thermal plant under study consists of four subsystems with three possible states: full working, reduced capacity working and failed. Failure and repair rates for all the subsystems are assumed to be constant. Formulation of the problem is carried out using Markov Birth-Death process using probabilistic approach and a transition diagram represents the operational behavior of the system. Interrelationship among the full working and reduced working has been developed. A probabilistic model has been developed, considering some assumptions. Data in feasible range are selected from a survey of thermal plant and the effect of each subsystem on the system availability is tabulated in the form of availability matrices, which provides various performance/availability levels for different combinations of failure and repair rates of all subsystems. Based upon various availability values obtained in availability matrices and graphs of failure/repair rates of different subsystems, performance and optimum values of failure/repair rates for maximum availability, of each subsystem is analyzed and then maintenance priorities are decided for all subsystems.
Energy Technology Data Exchange (ETDEWEB)
Monte, L. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dipt. Ambiente; Brittain, J.E. [Oslo Univ., Oslo (Norway); Zoological Museum, Oslo (Norway); Haakanson, L. [Uppsala Univ., Uppsala (Sweden). Inst. of Earth Science; Gallego Diaz, E. [Madrid Univ. Politecnica, Madrid (Spain). Dept. de Ingenieria Nuclear
1999-07-01
The present report is composed of a set of articles written by the partners of the MOIRA project (a model-based computerized system for management support to identify optimal remedial strategies for restoring radionuclide contaminated aquatic ecosystems and drainage areas). The report describes models for predicting the behaviour of radionuclides in complex aquatic systems and the effects of countermeasures for their restoration. [Italian] Il rapporto contiene articoli preparati nell'ambito del progetto MOIRA (a model-based computerized system for management support to identify optimal remedial strategies for restoring radionuclide contaminated aquatic ecosystems and drainage areas), che descrive alcuni modelli per la previsione del comportamento di radionuclidi in sistemi acquatici complessi e per la valutazione dell'effetto delle contromisure per il loro recupero.
Energy Technology Data Exchange (ETDEWEB)
Monte, L [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dipt. Ambiente; Brittain, J E [Oslo Univ., Oslo (Norway); Zoological Museum, Oslo [Norway; Haakanson, L [Uppsala Univ., Uppsala (Sweden). Inst. of Earth Science; Gallego Diaz, E [Madrid Univ. Politecnica, Madrid (Spain). Dept. de Ingenieria Nuclear
1999-07-01
The present report is composed of a set of articles written by the partners of the MOIRA project (a model-based computerized system for management support to identify optimal remedial strategies for restoring radionuclide contaminated aquatic ecosystems and drainage areas). The report describes models for predicting the behaviour of radionuclides in complex aquatic systems and the effects of countermeasures for their restoration. [Italian] Il rapporto contiene articoli preparati nell'ambito del progetto MOIRA (a model-based computerized system for management support to identify optimal remedial strategies for restoring radionuclide contaminated aquatic ecosystems and drainage areas), che descrive alcuni modelli per la previsione del comportamento di radionuclidi in sistemi acquatici complessi e per la valutazione dell'effetto delle contromisure per il loro recupero.
International Nuclear Information System (INIS)
Makanjee, Chandra R.; Bergh, Anne-Marie; Hoffmann, Willem A.
2014-01-01
Using experiences from the South African public healthcare system with limited resources, this review proposes a model that captures a holistic perspective of diagnostic imaging services embedded in a network of negotiated decision-making processes. Professional interdependency and interprofessional collaboration, cooperation and coordination are built around the central notion of integration in order to achieve a seamless transition through the continuum of various types of services needed to come to a diagnosis. Health-system role players interact with patients who enter the system from the perspective of their life-world. The distribution of diagnostic imaging services – within one setting or at multiple levels of care – demonstrates how fragments of information are filtered, interpreted and transformed at each point of care. The proposed model could contribute to alignment towards a common goal: services providing holistic quality of care within and beyond a complex healthcare system
A rat model system to study complex disease risks, fitness, aging, and longevity.
Koch, Lauren Gerard; Britton, Steven L; Wisløff, Ulrik
2012-02-01
The association between low exercise capacity and all-cause morbidity and mortality is statistically strong yet mechanistically unresolved. By connecting clinical observation with a theoretical base, we developed a working hypothesis that variation in capacity for oxygen metabolism is the central mechanistic determinant between disease and health (aerobic hypothesis). As an unbiased test, we show that two-way artificial selective breeding of rats for low and high intrinsic endurance exercise capacity also produces rats that differ for numerous disease risks, including the metabolic syndrome, cardiovascular complications, premature aging, and reduced longevity. This contrasting animal model system may prove to be translationally superior relative to more widely used simplistic models for understanding geriatric biology and medicine. Copyright © 2012 Elsevier Inc. All rights reserved.
Hulme, A; Salmon, P M; Nielsen, R O; Read, G J M; Finch, C F
2017-11-01
There is a need for an ecological and complex systems approach for better understanding the development and prevention of running-related injury (RRI). In a previous article, we proposed a prototype model of the Australian recreational distance running system which was based on the Systems Theoretic Accident Mapping and Processes (STAMP) method. That model included the influence of political, organisational, managerial, and sociocultural determinants alongside individual-level factors in relation to RRI development. The purpose of this study was to validate that prototype model by drawing on the expertise of both systems thinking and distance running experts. This study used a modified Delphi technique involving a series of online surveys (December 2016- March 2017). The initial survey was divided into four sections containing a total of seven questions pertaining to different features associated with the prototype model. Consensus in opinion about the validity of the prototype model was reached when the number of experts who agreed or disagreed with survey statement was ≥75% of the total number of respondents. A total of two Delphi rounds was needed to validate the prototype model. Out of a total of 51 experts who were initially contacted, 50.9% (n = 26) completed the first round of the Delphi, and 92.3% (n = 24) of those in the first round participated in the second. Most of the 24 full participants considered themselves to be a running expert (66.7%), and approximately a third indicated their expertise as a systems thinker (33.3%). After the second round, 91.7% of the experts agreed that the prototype model was a valid description of the Australian distance running system. This is the first study to formally examine the development and prevention of RRI from an ecological and complex systems perspective. The validated model of the Australian distance running system facilitates theoretical advancement in terms of identifying practical system
Directory of Open Access Journals (Sweden)
E. A. Yushkov
2016-12-01
Full Text Available Purpose. Designing of diagrams to optimize mathematic model of the ship power plant (SPP combined propulsion complexes (CPC for decreasing operational loss and increasing fuel efficiency with simultaneous load limiting on medium revolutions diesel generator (MRDG by criterion reducing of wear and increasing operation time between repairs. Methodology. After analyzing of ship power plant modes of CPC proposed diagrams to optimize mathematic model of the above mentioned complex. The model based on using of electronic controllers in automatic regulation and control systems for diesel and thruster which allow to actualize more complicated control algorithm with viewpoint of increasing working efficiency of ship power plant at normal and emergency modes. Results. Determined suitability of comparative computer modeling in MatLab Simulink for building of imitation model objects based on it block diagrams and mathematic descriptions. Actualized diagrams to optimize mathematic model of the ship’s power plant (SPP combined propulsion complexes (CPC with Azipod system in MatLab Simulink software package Ships_CPC for decreasing operational loss and increasing fuel efficiency with simultaneous load limiting on medium revolutions diesel generator (MRDG by criterion reducing of wear and increasing operation time between repairs. The function blocks of proposed complex are the main structural units which allow to investigate it normal and emergency modes. Originality. This model represents a set of functional blocks of the components SPP CPC, built on the principle of «input-output». For example, the function boxes outputs of PID-regulators of MRDG depends from set excitation voltage and rotating frequency that in turn depends from power-station load and respond that is a ship moving or dynamically positioning, and come on input (inputs of thruster rotating frequency PID-regulator models. Practical value. The results of researches planned to use in
Complex Networks in Psychological Models
Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.
We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.
International Nuclear Information System (INIS)
FORSYTHE, JAMES C.; WENNER, CAREN A.
1999-01-01
The history of high consequence accidents is rich with events wherein the actions, or inaction, of humans was critical to the sequence of events preceding the accident. Moreover, it has been reported that human error may contribute to 80% of accidents, if not more (dougherty and Fragola, 1988). Within the safety community, this reality is widely recognized and there is a substantially greater awareness of the human contribution to system safety today than has ever existed in the past. Despite these facts, and some measurable reduction in accident rates, when accidents do occur, there is a common lament. No matter how hard we try, we continue to have accidents. Accompanying this lament, there is often bewilderment expressed in statements such as, ''There's no explanation for why he/she did what they did''. It is believed that these statements are a symptom of inadequacies in how they think about humans and their role within technological systems. In particular, while there has never been a greater awareness of human factors, conceptual models of human involvement in engineered systems are often incomplete and in some cases, inaccurate
Clancey, William J.; Linde, Charlotte; Seah, Chin; Shafto, Michael
2013-01-01
anomalous condition, as occurred during the accident. Brahms-GUeM thus implicitly defines a class of scenarios, which include as an instance what occurred at Überlingen. Brahms-GUeM is a modeling framework enabling "what if" analysis of alternative work system configurations and thus facilitating design of alternative operations concepts. It enables subsequent adaption (reusing simulation components) for modeling and simulating NextGen scenarios. This project demonstrates that BRAHMS provides the capacity to model the complexity of air transportation systems, going beyond idealized and simple flights to include for example the interaction of pilots and ATCOs. The research shows clearly that verification and validation must include the entire work system, on the one hand to check that mechanisms exist to handle failures of communication and alerting subsystems and/or failures of people to notice, comprehend, or communicate problematic (unsafe) situations; but also to understand how people must use their own judgment in relating fallible systems like TCAS to other sources of information and thus to evaluate how the unreliability of automation affects system safety. The simulation shows in particular that distributed agents (people and automated systems) acting without knowledge of each others' actions can create a complex, dynamic system whose interactive behavior is unexpected and is changing too quickly to comprehend and control.
Directory of Open Access Journals (Sweden)
Leszek CHYBOWSKI
2012-04-01
Full Text Available In the paper the concept of a system structure with particular emphasis on the reliability structure has been presented. Advantages and disadvantages of modeling the reliability structure of a system using reliability block diagrams (RBD have been shown. RBD models of a marine steam‐water system constructed according to the concept of ‘multi‐component’, ‘one component’ and mixed models have been discussed. Critical remarks on the practical application of models which recognize only the structural surplus have been dealt with. The significant value of the model by professors Smalko and Jaźwiński called by them ‘default reliability structure’ has been pointed out. The necessity of building a new type of models: quality‐quantity, useful in the methodology developed by the author's multi-criteria analysis of importance of elements in the reliability structure of complex technical systems.
Pezzulo, Giovanni; Levin, Michael
2016-11-01
It is widely assumed in developmental biology and bioengineering that optimal understanding and control of complex living systems follows from models of molecular events. The success of reductionism has overshadowed attempts at top-down models and control policies in biological systems. However, other fields, including physics, engineering and neuroscience, have successfully used the explanations and models at higher levels of organization, including least-action principles in physics and control-theoretic models in computational neuroscience. Exploiting the dynamic regulation of pattern formation in embryogenesis and regeneration requires new approaches to understand how cells cooperate towards large-scale anatomical goal states. Here, we argue that top-down models of pattern homeostasis serve as proof of principle for extending the current paradigm beyond emergence and molecule-level rules. We define top-down control in a biological context, discuss the examples of how cognitive neuroscience and physics exploit these strategies, and illustrate areas in which they may offer significant advantages as complements to the mainstream paradigm. By targeting system controls at multiple levels of organization and demystifying goal-directed (cybernetic) processes, top-down strategies represent a roadmap for using the deep insights of other fields for transformative advances in regenerative medicine and systems bioengineering. © 2016 The Author(s).
International Nuclear Information System (INIS)
Beugin, J.; Renaux, D.; Cauffriez, L.
2007-01-01
Safety analysis in guided transportation systems is essential to avoid rare but potentially catastrophic accidents. This article presents a quantitative probabilistic model that integrates Safety Integrity Levels (SIL) for evaluating the safety of such systems. The standardized SIL indicator allows the safety requirements of each safety subsystem, function and/or piece of equipment to be specified, making SILs pivotal parameters in safety evaluation. However, different interpretations of SIL exist, and faced with the complexity of guided transportation systems, the current SIL allocation methods are inadequate for the task of safety assessment. To remedy these problems, the model developed in this paper seeks to verify, during the design phase of guided transportation system, whether or not the safety specifications established by the transport authorities allow the overall safety target to be attained (i.e., if the SIL allocated to the different safety functions are sufficient to ensure the required level of safety). To meet this objective, the model is based both on the operating situation concept and on Monte Carlo simulation. The former allows safety systems to be formalized and their dynamics to be analyzed in order to show the evolution of the system in time and space, and the latter make it possible to perform probabilistic calculations based on the scenario structure obtained
Modeling complex dispersed energy and clean water systems for the United States/Mexico border
Herrera, Hugo Francisco Lopez
As world population grows, and its technology evolves, the demand for electricity inexorably increases. Until now most of this electricity has been produced via fossil fuels, non-renewable energy resources that are irreversibly deteriorating our environment. On the economical aspect it does not get any better. Let's not forget market rules, the higher the demand and lower the offer, the higher the price we will have to pay. Oil is an excellent example. Some countries try to solve this situation with Pharaohnic projects, i.e. investing absurd amounts of money in 'green electricity' building monstrous dams to power equally monstrous hydroelectric power plants. The only problem with this is that it is not green at all---it does have an enormous environmental impact---it is extremely complicated and expensive to implement. It is important to point out, that this research project does not try to solve world's thirst for electricity. It is rather aimed to help solve this problematic at a much lower scale---it should be considered as an extremely small step in the right direction. It focuses on satisfying the local electricity needs with renewable, non-contaminating and locally available resources. More concisely, this project focuses on the attainment and use of hydrogen as an alternate energy source in El Paso/Juarez region. Clean technology is nowadays available to produce hydrogen and oxygen, i.e. the photoelectrolysis process. Photovoltaic cells coupled with electrolytic devices can be used to produce hydrogen and oxygen in a sustainable manner. In this research, simulation models of hybrid systems were designed and developed. They were capable to compare, predict and evaluate different options for hydrogen generation. On the other hand, with the produced hydrogen from the electrolysis process it was possible to generate electricity through fuel cells. The main objectives of the proposed research were to define how to use the resources for the attainment of hydrogen
Hulme, Adam; Thompson, Jason; Nielsen, Rasmus Oestergaard; Read, Gemma J M; Salmon, Paul M
2018-06-18
There have been recent calls for the application of the complex systems approach in sports injury research. However, beyond theoretical description and static models of complexity, little progress has been made towards formalising this approach in way that is practical to sports injury scientists and clinicians. Therefore, our objective was to use a computational modelling method and develop a dynamic simulation in sports injury research. Agent-based modelling (ABM) was used to model the occurrence of sports injury in a synthetic athlete population. The ABM was developed based on sports injury causal frameworks and was applied in the context of distance running-related injury (RRI). Using the acute:chronic workload ratio (ACWR), we simulated the dynamic relationship between changes in weekly running distance and RRI through the manipulation of various 'athlete management tools'. The findings confirmed that building weekly running distances over time, even within the reported ACWR 'sweet spot', will eventually result in RRI as athletes reach and surpass their individual physical workload limits. Introducing training-related error into the simulation and the modelling of a 'hard ceiling' dynamic resulted in a higher RRI incidence proportion across the population at higher absolute workloads. The presented simulation offers a practical starting point to further apply more sophisticated computational models that can account for the complex nature of sports injury aetiology. Alongside traditional forms of scientific inquiry, the use of ABM and other simulation-based techniques could be considered as a complementary and alternative methodological approach in sports injury research. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Directory of Open Access Journals (Sweden)
Andrey V. Tokar
2014-03-01
Full Text Available The structure and spectral properties for molecular complexes, which formed by added monomer form of pentaplast as well as N-phenylbenzamide with some species of intermolecular interaction in system «penton-terlon» have been investigated at ab initio level of theory. It is shown, that the main contribution in total energy of molecules have included by dispersion forces, which realized between Chlorine atom of CH2Cl-group and Hydrogen atoms of benzene rings with amide fragment. The proposed theoretical models are validated in reflection of spectral and energetic characteristics of investigating system. Finally, the results of calculations are in good agreement with that data, which have been obtained for such type modeling previously.
International Nuclear Information System (INIS)
Pires, Thiago S.; Cruz, Manuel E.; Colaço, Marcelo J.
2013-01-01
This work presents the application of a surrogate model – a response surface – to replace the objective function to be minimized in the thermoeconomic optimization of a complex thermal system modeled with the aid of an expert process simulator. The objective function accounts for fuel, capital, operation and maintenance costs of the thermal system, and depends on nine decision variables. The minimization task is performed through the computational integration of two professional programs, a process simulator and a mathematical platform. Five algorithms are used to perform the optimization: the pattern search and genetic algorithms, both available in the mathematical platform, plus three custom-coded algorithms, differential evolution, particle swarm and simulated annealing. A comparative analysis of the performance of all five methods is presented, together with a critical appraisal of the surrogate model effectiveness. In the course of the optimization procedure, the process simulator computes the thermodynamic properties of all flows of the thermal system and solves the mass and energy balances each time the objective function has to be evaluated. By handling a set of radial basis functions as an approximation model to the original computationally expensive objective function, it is found here that the number of function evaluations can be appreciably reduced without significant deviation of the optimal value. The present study indicates that, for a thermoeconomic system optimization problem with a large number of decision variables and/or a costly objective function, the application of the response surface surrogate may prove more efficient than the original simulation model, reducing substantially the computational time involved in the optimization. - Highlights: ► A successful response surface method was proposed. ► The surrogate model may be more efficient than the original simulation model. ► Relative differences of less than 5% were found for the
Efficient Parameterization for Grey-box Model Identification of Complex Physical Systems
DEFF Research Database (Denmark)
Blanke, Mogens; Knudsen, Morten Haack
2006-01-01
Grey box model identification preserves known physical structures in a model but with limits to the possible excitation, all parameters are rarely identifiable, and different parametrizations give significantly different model quality. Convenient methods to show which parameterizations are the be...... that need be constrained to achieve satisfactory convergence. Identification of nonlinear models for a ship illustrate the concept....
Greiner, Maximilian; Sonnleitner, Bettina; Mailänder, Markus; Briesen, Heiko
2014-02-01
Additional benefits of foods are an increasing factor in the consumer's purchase. To produce foods with the properties the consumer demands, understanding the micro- and nanostructure is becoming more important in food research today. We present molecular dynamics (MD) simulations as a tool to study complex and multi-component food systems on the example of chocolate conching. The process of conching is chosen because of the interesting challenges it provides: the components (fats, emulsifiers and carbohydrates) contain diverse functional groups, are naturally fluctuating in their chemical composition, and have a high number of internal degrees of freedom. Further, slow diffusion in the non-aqueous medium is expected. All of these challenges are typical to food systems in general. Simulation results show the suitability of present force fields to correctly model the liquid and crystal density of cocoa butter and sucrose, respectively. Amphiphilic properties of emulsifiers are observed by micelle formation in water. For non-aqueous media, pulling simulations reveal high energy barriers for motion in the viscous cocoa butter. The work for detachment of an emulsifier from the sucrose crystal is calculated and matched with detachment of the head and tail groups separately. Hydrogen bonding is shown to be the dominant interaction between the emulsifier and the crystal surface. Thus, MD simulations are suited to model the interaction between the emulsifier and sugar crystal interface in non-aqueous media, revealing detailed information about the structuring and interactions on a molecular level. With interaction parameters being available for a wide variety of chemical groups, MD simulations are a valuable tool to understand complex and multi-component food systems in general. MD simulations provide a substantial benefit to researchers to verify their hypothesis in dynamic simulations with an atomistic resolution. Rapid rise of computational resources successively
Energy Technology Data Exchange (ETDEWEB)
Christiansen, J. H.
2000-06-15
The Dynamic Information Architecture System (DIAS) is a flexible, extensible, object-based framework for developing and maintaining complex multidisciplinary simulations. The DIAS infrastructure makes it feasible to build and manipulate complex simulation scenarios in which many thousands of objects can interact via dozens to hundreds of concurrent dynamic processes. The flexibility and extensibility of the DIAS software infrastructure stem mainly from (1) the abstraction of object behaviors, (2) the encapsulation and formalization of model functionality, and (3) the mutability of domain object contents. DIAS simulation objects are inherently capable of highly flexible and heterogeneous spatial realizations. Geospatial graphical representation of DIAS simulation objects is addressed via the GeoViewer, an object-based GIS toolkit application developed at ANL. DIAS simulation capabilities have been extended by inclusion of societal process models generated by the Framework for Addressing Cooperative Extended Transactions (FACET), another object-based framework developed at Argonne National Laboratory. By using FACET models to implement societal behaviors of individuals and organizations within larger DIAS-based natural systems simulations, it has become possible to conveniently address a broad range of issues involving interaction and feedback among natural and societal processes. Example DIAS application areas discussed in this paper include a dynamic virtual oceanic environment, detailed simulation of clinical, physiological, and logistical aspects of health care delivery, and studies of agricultural sustainability of urban centers under environmental stress in ancient Mesopotamia.
Directory of Open Access Journals (Sweden)
Tien M. Nguyen
2018-03-01
Full Text Available This paper provides a high-level discussion and propositions of frameworks and models for acquisition strategy of complex systems. In particular, it presents an innovative system engineering approach to model the Department of Defense (DoD acquisition process and offers several optimization modules including simulation models using game theory and war-gaming concepts. Our frameworks employ Advanced Game-based Mathematical Framework (AGMF and Unified Game-based Acquisition Framework (UGAF, and related advanced simulation and mathematical models that include a set of War-Gaming Engines (WGEs implemented in MATLAB statistical optimization models. WGEs are defined as a set of algorithms, characterizing the Program and Technical Baseline (PTB, technology enablers, architectural solutions, contract type, contract parameters and associated incentives, and industry bidding position. As a proof of concept, Aerospace, in collaboration with the North Carolina State University (NCSU and University of Hawaii (UH, successfully applied and extended the proposed frameworks and decision models to determine the optimum contract parameters and incentives for a Cost Plus Incentive Fee (CPIF contract. As a result, we can suggest a set of acquisition strategies that ensure the optimization of the PTB.
Embedding complex hydrology in the climate system - towards fully coupled climate-hydrology models
DEFF Research Database (Denmark)
Butts, M.; Rasmussen, S.H.; Ridler, M.
2013-01-01
Motivated by the need to develop better tools to understand the impact of future management and climate change on water resources, we present a set of studies with the overall aim of developing a fully dynamic coupling between a comprehensive hydrological model, MIKE SHE, and a regional climate...... distributed parameters using satellite remote sensing. Secondly, field data are used to investigate the effects of model resolution and parameter scales for use in a coupled model. Finally, the development of the fully coupled climate-hydrology model is described and some of the challenges associated...... with coupling models for hydrological processes on sub-grid scales of the regional climate model are presented....
Multi-agent and complex systems
Ren, Fenghui; Fujita, Katsuhide; Zhang, Minjie; Ito, Takayuki
2017-01-01
This book provides a description of advanced multi-agent and artificial intelligence technologies for the modeling and simulation of complex systems, as well as an overview of the latest scientific efforts in this field. A complex system features a large number of interacting components, whose aggregate activities are nonlinear and self-organized. A multi-agent system is a group or society of agents which interact with others cooperatively and/or competitively in order to reach their individual or common goals. Multi-agent systems are suitable for modeling and simulation of complex systems, which is difficult to accomplish using traditional computational approaches.
A business process modeling experience in a complex information system re-engineering.
Bernonville, Stéphanie; Vantourout, Corinne; Fendeler, Geneviève; Beuscart, Régis
2013-01-01
This article aims to share a business process modeling experience in a re-engineering project of a medical records department in a 2,965-bed hospital. It presents the modeling strategy, an extract of the results and the feedback experience.
International Nuclear Information System (INIS)
Williams, Mark D.; Cole, Charles R.; Foley, Michael G.; Zinina, Galina A.; Zinin, Alexander I.; Vasil'Kova, Nelly A.; Samsonova, Lilia M.
2001-01-01
A joint Russian and U.S. model intercomparison study was undertaken for developing more realistic contaminant transport models of the Mayak Site, Southern Urals. The test problems were developed by the Russian Team based on their experience modeling contaminant migration near Lake Karachai. The intercomparison problems were designed to address lake and contaminant plume interactions, as well as river interactions and plume density effects. Different numerical codes were used. Overall there is good agreement between the results of both models. Features shown by both models include (1) the sinking of the plume below the lake, (2) the raising of the water table in the fresh water adjacent to the lake in response to the increased pressure from the dense plume, and (3) the formation of a second sinking plume in an area where evapotranspiration exceeded infiltration, thus increasing the solute concentrations above the source (i.e., lake) values
A global food demand model for the assessment of complex human-earth systems
Energy Technology Data Exchange (ETDEWEB)
EDMONDS, JAMES A. [Pacific Northwest National Laboratory’s, Joint Global Change Research Institute, 5825 University Research Court, Suite 3500, College Park, MD 20740, USA; LINK, ROBERT [Pacific Northwest National Laboratory’s, Joint Global Change Research Institute, 5825 University Research Court, Suite 3500, College Park, MD 20740, USA; WALDHOFF, STEPHANIE T. [Pacific Northwest National Laboratory’s, Joint Global Change Research Institute, 5825 University Research Court, Suite 3500, College Park, MD 20740, USA; CUI, RYNA [Pacific Northwest National Laboratory’s, Joint Global Change Research Institute, 5825 University Research Court, Suite 3500, College Park, MD 20740, USA
2017-11-01
Demand for agricultural products is an important problem in climate change economics. Food consumption will shape and shaped by climate change and emissions mitigation policies through interactions with bioenergy and afforestation, two critical issues in meeting international climate goals such as two-degrees. We develop a model of food demand for staple and nonstaple commodities that evolves with changing incomes and prices. The model addresses a long-standing issue in estimating food demands, the evolution of demand relationships across large changes in income and prices. We discuss the model, some of its properties and limitations. We estimate parameter values using pooled cross-sectional-time-series observations and the Metropolis Monte Carlo method and cross-validate the model by estimating parameters using a subset of the observations and test its ability to project into the unused observations. Finally, we apply bias correction techniques borrowed from the climate-modeling community and report results.
International Nuclear Information System (INIS)
Hassane-Mamadou-Maina, Fadji-Zaouna
2016-01-01
Groundwater is the main available water resource for many countries; they are mainly replenished by water from precipitation, called groundwater recharge. Due to its great importance, management of groundwater resources is more essential than ever, and is achieved through mathematical models which offer us a better understanding of physical phenomena as well as their prediction. Hydrogeological Systems are generally complex thus characterized by a highly variable dynamic over time and space. These complexities have attracted the attention of many hydro geologists and many sophisticated models that can handle these issues and describe these Systems accurately were developed. Unfortunately, modeling groundwater recharge is still a challenge in groundwater resource management. Generally, groundwater models are used to simulate aquifers flow without a good estimation of recharge and its spatial-temporal distribution. as groundwater recharge rates show spatial-temporal variability due to climatic conditions, land use, and hydrogeological heterogeneity, these methods have limitations in dealing with these characteristics. To overcome these limitations, a coupled model which simulates flow in the unsaturated zone and recharge as well as groundwater flow was developed. The flow in the unsaturated zone is solved either with resolution of Richards equation or with empirical models while the diffusivity equation governs flow in the saturated zone. Robust numerical methods were used to solve these equations: we apply nonconforming finite element to solve the diffusivity equation and we used an accurate and efficient method for solving the Richards equation. In the natural environments, parameters that control these hydrological mechanisms aren't accurately known or even unknowns, only variations of piezometric heads are commonly available. Hence, ail parameters related to unsaturated and saturated flows will be identified by using only these piezometric data
International Nuclear Information System (INIS)
Chang, Y.H.J.; Mosleh, A.
2007-01-01
This is the last in a series of five papers that discuss the Information Decision and Action in Crew (IDAC) context for human reliability analysis (HRA) and example application. The model is developed to probabilistically predict the responses of the control room operating crew in nuclear power plants during an accident, for use in probabilistic risk assessments (PRA). The operator response spectrum includes cognitive, emotional, and physical activities during the course of an accident. This paper describes a dynamic PRA computer simulation program, accident dynamics simulator (ADS), developed in part to implement the IDAC model. This paper also provides a detailed example of implementing a simpler version of IDAC, compared with the IDAC model discussed in the first four papers of this series, to demonstrate the practicality of integrating a detailed cognitive HRA model within a dynamic PRA framework
DEFF Research Database (Denmark)
Butts, Michael; Drews, Martin; Larsen, Morten Andreas Dahl
2014-01-01
the atmosphere and the groundwater via the land surface and can represent the lateral movement of water in both the surface and subsurface and their interactions, not normally accounted for in climate models. Meso-scale processes are important for climate in general and rainfall in particular. Hydrological......To improve our understanding of the impacts of feedback between the atmosphere and the terrestrial water cycle including groundwater and to improve the integration of water resource management modelling for climate adaption we have developed a dynamically coupled climate–hydrological modelling...... impacts are assessed at the catchment scale, the most important scale for water management. Feedback between groundwater, the land surface and the atmosphere occurs across a range of scales. Recognising this, the coupling was developed to allow dynamic exchange of water and energy at the catchment scale...
Economic Disadvantage in Complex Family Systems: Expansion of Family Stress Models
Barnett, Melissa A.
2008-01-01
Economic disadvantage is associated with multiple risks to early socioemotional development. This article reviews research regarding family stress frameworks to model the pathways from economic disadvantage to negative child outcomes via family processes. Future research in this area should expand definitions of family and household to incorporate…
International Nuclear Information System (INIS)
Chang, Y.H.J.; Mosleh, A.
2007-01-01
This is the third in a series of five papers describing the IDAC (Information, Decision, and Action in Crew context) model for human reliability analysis. An example application of this modeling technique is also discussed in this series. The model is developed to probabilistically predict the responses of the nuclear power plant control room operating crew in accident conditions. The operator response spectrum includes cognitive, emotional, and physical activities during the course of an accident. This paper discusses the modeling components and their process rules. An operator's problem-solving process is divided into three types: information pre-processing (I), diagnosis and decision-making (D), and action execution (A). Explicit and context-dependent behavior rules for each type of operator are developed in the form of tables, and logical or mathematical relations. These regulate the process and activities of each of the three types of response. The behavior rules are developed for three generic types of operator: Decision Maker, Action Taker, and Consultant. This paper also provides a simple approach to calculating normalized probabilities of alternative behaviors given a context
Management of complex dynamical systems
MacKay, R. S.
2018-02-01
Complex dynamical systems are systems with many interdependent components which evolve in time. One might wish to control their trajectories, but a more practical alternative is to control just their statistical behaviour. In many contexts this would be both sufficient and a more realistic goal, e.g. climate and socio-economic systems. I refer to it as ‘management’ of complex dynamical systems. In this paper, some mathematics for management of complex dynamical systems is developed in the weakly dependent regime, and questions are posed for the strongly dependent regime.
Large scale hydrogeological modelling of a low-lying complex coastal aquifer system
DEFF Research Database (Denmark)
Meyer, Rena
2018-01-01
intrusion. In this thesis a new methodological approach was developed to combine 3D numerical groundwater modelling with a detailed geological description and hydrological, geochemical and geophysical data. It was applied to a regional scale saltwater intrusion in order to analyse and quantify...... the groundwater flow dynamics, identify the driving mechanisms that formed the saltwater intrusion to its present extent and to predict its progression in the future. The study area is located in the transboundary region between Southern Denmark and Northern Germany, adjacent to the Wadden Sea. Here, a large-scale...... parametrization schemes that accommodate hydrogeological heterogeneities. Subsequently, density-dependent flow and transport modelling of multiple salt sources was successfully applied to simulate the formation of the saltwater intrusion during the last 4200 years, accounting for historic changes in the hydraulic...
Robust Modeling of Complex Systems with Heavy Tails and Long Memory
2014-07-16
cluster model, Scandinavian Actuarial Journal , (09 2011): 0. doi: Gennady Samorodnitsky, Sami Umut Can, Thomas Mikosch. Weak convergence of the...further studies in science , mathematics, engineering or technology fields: Student Metrics This section only applies to graduating undergraduates...0.00 0.00 0.00 0.00 The number of undergraduates funded by this agreement who graduated during this period with a degree in science , mathematics
The evolution of ecosystem ascendency in a complex systems based model.
Brinck, Katharina; Jensen, Henrik Jeldtoft
2017-09-07
General patterns in ecosystem development can shed light on driving forces behind ecosystem formation and recovery and have been of long interest. In recent years, the need for integrative and process oriented approaches to capture ecosystem growth, development and organisation, as well as the scope of information theory as a descriptive tool has been addressed from various sides. However data collection of ecological network flows is difficult and tedious and comprehensive models are lacking. We use a hierarchical version of the Tangled Nature Model of evolutionary ecology to study the relationship between structure, flow and organisation in model ecosystems, their development over evolutionary time scales and their relation to ecosystem stability. Our findings support the validity of ecosystem ascendency as a meaningful measure of ecosystem organisation, which increases over evolutionary time scales and significantly drops during periods of disturbance. The results suggest a general trend towards both higher integrity and increased stability driven by functional and structural ecosystem coadaptation. Copyright © 2017 Elsevier Ltd. All rights reserved.
A model for predicting the potential diffusion of solar energy systems in complex urban environments
International Nuclear Information System (INIS)
La Gennusa, Maria; Lascari, Giovanni; Rizzo, Gianfranco; Scaccianoce, Gianluca; Sorrentino, Giancarlo
2011-01-01
The necessity to reduce greenhouse gases emission produced by energy building consumptions and to cut the energy bill (mainly due to the use of fossil sources) leads to the employment of renewable energy sources in new planned scenarios. In particular, more and more often municipal energy and environmental plans pay great attention to the possibilities of employment of the solar technologies at urban scale. Solar thermal and photovoltaic (PV) systems are, by far, the most suitable tools to be utilized in urban areas. Obviously, the proper adoption of such systems in buildings does call for the availability of calculation methods suitable to provide the actual level of exploitation of solar energy in urban layouts. In this work, a procedure for evaluating the geographical energy potential of building roofs in urban areas is proposed; in particular, the amount of surface on the roof that could be used for the installation of systems able to capture solar radiation for the energy production is investigated. The proposed procedure is based on the use of the GIS technology and 3D cartography. The effectiveness of the proposed method is assessed by means of an application to the town of Palermo (Italy). - Highlights: → The GIS techniques allow to analyze various future scenarios about urban planning. → We propose a procedure for assessing the extension of superficial urban areas useable for the installation of solar systems. → This procedure allow to compile a scale of priority of intervention. → The cost for financing such interventions is compared to the penalty to pay for not achieving the Kyoto goals.
The Reliasep method used for the functional modeling of complex systems
International Nuclear Information System (INIS)
Dubiez, P.; Gaufreteau, P.; Pitton, J.P.
1997-07-01
The RELIASEP R method and its support tool have been recommended to carry out the functional analysis of large systems within the framework of the design of new power units. Let us first recall the principles of the method based on the breakdown of functions into tree(s). These functions are characterised by their performance and constraints. Then the main modifications made under EDF requirement and in particular the 'viewpoints' analyses are presented. The knowledge obtained from the first studies carried out are discussed. (author)
The Reliasep method used for the functional modeling of complex systems
Energy Technology Data Exchange (ETDEWEB)
Dubiez, P.; Gaufreteau, P.; Pitton, J.P
1997-07-01
The RELIASEP{sup R} method and its support tool have been recommended to carry out the functional analysis of large systems within the framework of the design of new power units. Let us first recall the principles of the method based on the breakdown of functions into tree(s). These functions are characterised by their performance and constraints. Then the main modifications made under EDF requirement and in particular the `viewpoints` analyses are presented. The knowledge obtained from the first studies carried out are discussed. (author)
DEFF Research Database (Denmark)
Vester, Steen
2015-01-01
We study the complexity of the model-checking problem for the branching-time logic CTL ∗ and the alternating-time temporal logics ATL/ATL ∗ in one-counter processes and one-counter games respectively. The complexity is determined for all three logics when integer weights are input in unary (non...
Odille, Fabrice G J; Jónsson, Stefán; Stjernqvist, Susann; Rydén, Tobias; Wärnmark, Kenneth
2007-01-01
A general mathematical model for the characterization of the dynamic (kinetically labile) association of supramolecular assemblies in solution is presented. It is an extension of the equal K (EK) model by the stringent use of linear algebra to allow for the simultaneous presence of an unlimited number of different units in the resulting assemblies. It allows for the analysis of highly complex dynamic equilibrium systems in solution, including both supramolecular homo- and copolymers without the recourse to extensive approximations, in a field in which other analytical methods are difficult. The derived mathematical methodology makes it possible to analyze dynamic systems such as supramolecular copolymers regarding for instance the degree of polymerization, the distribution of a given monomer in different copolymers as well as its position in an aggregate. It is to date the only general means to characterize weak supramolecular systems. The model was fitted to NMR dilution titration data by using the program Matlab, and a detailed algorithm for the optimization of the different parameters has been developed. The methodology is applied to a case study, a hydrogen-bonded supramolecular system, salen 4+porphyrin 5. The system is formally a two-component system but in reality a three-component system. This results in a complex dynamic system in which all monomers are associated to each other by hydrogen bonding with different association constants, resulting in homo- and copolymers 4n5m as well as cyclic structures 6 and 7, in addition to free 4 and 5. The system was analyzed by extensive NMR dilution titrations at variable temperatures. All chemical shifts observed at different temperatures were used in the fitting to obtain the DeltaH degrees and DeltaS degrees values producing the best global fit. From the derived general mathematical expressions, system 4+5 could be characterized with respect to above-mentioned parameters.
Measuring Complexity of SAP Systems
Directory of Open Access Journals (Sweden)
Ilja Holub
2016-10-01
Full Text Available The paper discusses the reasons of complexity rise in ERP system SAP R/3. It proposes a method for measuring complexity of SAP. Based on this method, the computer program in ABAP for measuring complexity of particular SAP implementation is proposed as a tool for keeping ERP complexity under control. The main principle of the measurement method is counting the number of items or relations in the system. The proposed computer program is based on counting of records in organization tables in SAP.
A new decision sciences for complex systems
Lempert, Robert J.
2002-01-01
Models of complex systems can capture much useful information but can be difficult to apply to real-world decision-making because the type of information they contain is often inconsistent with that required for traditional decision analysis. New approaches, which use inductive reasoning over large ensembles of computational experiments, now make possible systematic comparison of alternative policy options using models of complex systems. This article describes Computer-Assisted Reasoning, an...
Directory of Open Access Journals (Sweden)
N. Bender
2013-03-01
Full Text Available Cubic equations of state combined with excess Gibbs energy predictive models (like UNIFAC and equations of state based on applied statistical mechanics are among the main alternatives for phase equilibria prediction involving polar substances in wide temperature and pressure ranges. In this work, the predictive performances of the PC-SAFT with association contribution and Peng-Robinson (PR combined with UNIFAC (Do through mixing rules are compared. Binary and multi-component systems involving polar and non-polar substances were analyzed. Results were also compared to experimental data available in the literature. Results show a similar predictive performance for PC-SAFT with association and cubic equations combined with UNIFAC (Do through mixing rules. Although PC-SAFT with association requires less parameters, it is more complex and requires more computation time.
Mitchell, Christine M.
1993-01-01
This chapter examines a class of human-computer interaction applications, specifically the design of human-computer interaction for the operators of complex systems. Such systems include space systems (e.g., manned systems such as the Shuttle or space station, and unmanned systems such as NASA scientific satellites), aviation systems (e.g., the flight deck of 'glass cockpit' airplanes or air traffic control) and industrial systems (e.g., power plants, telephone networks, and sophisticated, e.g., 'lights out,' manufacturing facilities). The main body of human-computer interaction (HCI) research complements but does not directly address the primary issues involved in human-computer interaction design for operators of complex systems. Interfaces to complex systems are somewhat special. The 'user' in such systems - i.e., the human operator responsible for safe and effective system operation - is highly skilled, someone who in human-machine systems engineering is sometimes characterized as 'well trained, well motivated'. The 'job' or task context is paramount and, thus, human-computer interaction is subordinate to human job interaction. The design of human interaction with complex systems, i.e., the design of human job interaction, is sometimes called cognitive engineering.
Third International Conference on Complex Systems
Minai, Ali A; Unifying Themes in Complex Systems
2006-01-01
In recent years, scientists have applied the principles of complex systems science to increasingly diverse fields. The results have been nothing short of remarkable: their novel approaches have provided answers to long-standing questions in biology, ecology, physics, engineering, computer science, economics, psychology and sociology. The Third International Conference on Complex Systems attracted over 400 researchers from around the world. The conference aimed to encourage cross-fertilization between the many disciplines represented and to deepen our understanding of the properties common to all complex systems. This volume contains over 35 papers selected from those presented at the conference on topics including: self-organization in biology, ecological systems, language, economic modeling, ecological systems, artificial life, robotics, and complexity and art. ALI MINAI is an Affiliate of the New England Complex Systems Institute and an Associate Professor in the Department of Electrical and Computer Engine...
A novel neural-wavelet approach for process diagnostics and complex system modeling
Gao, Rong
Neural networks have been effective in several engineering applications because of their learning abilities and robustness. However certain shortcomings, such as slow convergence and local minima, are always associated with neural networks, especially neural networks applied to highly nonlinear and non-stationary problems. These problems can be effectively alleviated by integrating a new powerful tool, wavelets, into conventional neural networks. The multi-resolution analysis and feature localization capabilities of the wavelet transform offer neural networks new possibilities for learning. A neural wavelet network approach developed in this thesis enjoys fast convergence rate with little possibility to be caught at a local minimum. It combines the localization properties of wavelets with the learning abilities of neural networks. Two different testbeds are used for testing the efficiency of the new approach. The first is magnetic flowmeter-based process diagnostics: here we extend previous work, which has demonstrated that wavelet groups contain process information, to more general process diagnostics. A loop at Applied Intelligent Systems Lab (AISL) is used for collecting and analyzing data through the neural-wavelet approach. The research is important for thermal-hydraulic processes in nuclear and other engineering fields. The neural-wavelet approach developed is also tested with data from the electric power grid. More specifically, the neural-wavelet approach is used for performing short-term and mid-term prediction of power load demand. In addition, the feasibility of determining the type of load using the proposed neural wavelet approach is also examined. The notion of cross scale product has been developed as an expedient yet reliable discriminator of loads. Theoretical issues involved in the integration of wavelets and neural networks are discussed and future work outlined.
Computational Modeling of Complex Protein Activity Networks
Schivo, Stefano; Leijten, Jeroen; Karperien, Marcel; Post, Janine N.; Prignet, Claude
2017-01-01
Because of the numerous entities interacting, the complexity of the networks that regulate cell fate makes it impossible to analyze and understand them using the human brain alone. Computational modeling is a powerful method to unravel complex systems. We recently described the development of a
European Conference on Complex Systems
Pellegrini, Francesco; Caldarelli, Guido; Merelli, Emanuela
2016-01-01
This work contains a stringent selection of extended contributions presented at the meeting of 2014 and its satellite meetings, reflecting scope, diversity and richness of research areas in the field, both fundamental and applied. The ECCS meeting, held under the patronage of the Complex Systems Society, is an annual event that has become the leading European conference devoted to complexity science. It offers cutting edge research and unique opportunities to study novel scientific approaches in a multitude of application areas. ECCS'14, its eleventh occurrence, took place in Lucca, Italy. It gathered some 650 scholars representing a wide range of topics relating to complex systems research, with emphasis on interdisciplinary approaches. The editors are among the best specialists in the area. The book is of great interest to scientists, researchers and graduate students in complexity, complex systems and networks.
Anomaly Detection for Complex Systems
National Aeronautics and Space Administration — In performance maintenance in large, complex systems, sensor information from sub-components tends to be readily available, and can be used to make predictions about...
Chifflard, Peter; Tilch, Nils
2010-05-01
Introduction Hydrological or geomorphological processes in nature are often very diverse and complex. This is partly due to the regional characteristics which vary over time and space, as well as changeable process-initiating and -controlling factors. Despite being aware of this complexity, such aspects are usually neglected in the modelling of hazard-related maps due to several reasons. But particularly when it comes to creating more realistic maps, this would be an essential component to consider. The first important step towards solving this problem would be to collect data relating to regional conditions which vary over time and geographical location, along with indicators of complex processes. Data should be acquired promptly during and after events, and subsequently digitally combined and analysed. Study area In June 2009, considerable damage occurred in the residential area of Klingfurth (Lower Austria) as a result of great pre-event wetness and repeatedly heavy rainfall, leading to flooding, debris flow deposit and gravitational mass movement. One of the causes is the fact that the meso-scale watershed (16 km²) of the Klingfurth stream is characterised by adverse geological and hydrological conditions. Additionally, the river system network with its discharge concentration within the residential zone contributes considerably to flooding, particularly during excessive rainfall across the entire region, as the flood peaks from different parts of the catchment area are superposed. First results of mapping Hydro(geo)logical surveys across the entire catchment area have shown that - over 600 gravitational mass movements of various type and stage have occurred. 516 of those have acted as a bed load source, while 325 mass movements had not reached the final stage yet and could thus supply bed load in the future. It should be noted that large mass movements in the initial or intermediate stage were predominately found in clayey-silty areas and weathered material
Multilevel Complex Networks and Systems
Caldarelli, Guido
2014-03-01
Network theory has been a powerful tool to model isolated complex systems. However, the classical approach does not take into account the interactions often present among different systems. Hence, the scientific community is nowadays concentrating the efforts on the foundations of new mathematical tools for understanding what happens when multiple networks interact. The case of economic and financial networks represents a paramount example of multilevel networks. In the case of trade, trade among countries the different levels can be described by the different granularity of the trading relations. Indeed, we have now data from the scale of consumers to that of the country level. In the case of financial institutions, we have a variety of levels at the same scale. For example one bank can appear in the interbank networks, ownership network and cds networks in which the same institution can take place. In both cases the systemically important vertices need to be determined by different procedures of centrality definition and community detection. In this talk I will present some specific cases of study related to these topics and present the regularities found. Acknowledged support from EU FET Project ``Multiplex'' 317532.
Energy Technology Data Exchange (ETDEWEB)
Vizcaino, Miren [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); University of California, Department of Geography, Berkeley, CA (United States); Mikolajewicz, Uwe; Maier-Reimer, Ernst [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Groeger, Matthias [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); IFM-GEOMAR, Kiel (Germany); Schurgers, Guy [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Lund University, Department of Physical Geography and Ecosystems Analysis, Lund (Sweden); Winguth, Arne M.E. [Center for Climatic Research, Department of Atmospheric and Oceanic Sciences, Madison (United States)
2008-11-15
Several multi-century and multi-millennia simulations have been performed with a complex Earth System Model (ESM) for different anthropogenic climate change scenarios in order to study the long-term evolution of sea level and the impact of ice sheet changes on the climate system. The core of the ESM is a coupled coarse-resolution Atmosphere-Ocean General Circulation Model (AOGCM). Ocean biogeochemistry, land vegetation and ice sheets are included as components of the ESM. The Greenland Ice Sheet (GrIS) decays in all simulations, while the Antarctic ice sheet contributes negatively to sea level rise, due to enhanced storage of water caused by larger snowfall rates. Freshwater flux increases from Greenland are one order of magnitude smaller than total freshwater flux increases into the North Atlantic basin (the sum of the contribution from changes in precipitation, evaporation, run-off and Greenland meltwater) and do not play an important role in changes in the strength of the North Atlantic Meridional Overturning Circulation (NAMOC). The regional climate change associated with weakening/collapse of the NAMOC drastically reduces the decay rate of the GrIS. The dynamical changes due to GrIS topography modification driven by mass balance changes act first as a negative feedback for the decay of the ice sheet, but accelerate the decay at a later stage. The increase of surface temperature due to reduced topographic heights causes a strong acceleration of the decay of the ice sheet in the long term. Other feedbacks between ice sheet and atmosphere are not important for the mass balance of the GrIS until it is reduced to 3/4 of the original size. From then, the reduction in the albedo of Greenland strongly accelerates the decay of the ice sheet. (orig.)
Language Networks as Complex Systems
Lee, Max Kueiming; Ou, Sheue-Jen
2008-01-01
Starting in the late eighties, with a growing discontent with analytical methods in science and the growing power of computers, researchers began to study complex systems such as living organisms, evolution of genes, biological systems, brain neural networks, epidemics, ecology, economy, social networks, etc. In the early nineties, the research…
Complexity, Modeling, and Natural Resource Management
Directory of Open Access Journals (Sweden)
Paul Cilliers
2013-09-01
Full Text Available This paper contends that natural resource management (NRM issues are, by their very nature, complex and that both scientists and managers in this broad field will benefit from a theoretical understanding of complex systems. It starts off by presenting the core features of a view of complexity that not only deals with the limits to our understanding, but also points toward a responsible and motivating position. Everything we do involves explicit or implicit modeling, and as we can never have comprehensive access to any complex system, we need to be aware both of what we leave out as we model and of the implications of the choice of our modeling framework. One vantage point is never sufficient, as complexity necessarily implies that multiple (independent conceptualizations are needed to engage the system adequately. We use two South African cases as examples of complex systems - restricting the case narratives mainly to the biophysical domain associated with NRM issues - that make the point that even the behavior of the biophysical subsystems themselves are already complex. From the insights into complex systems discussed in the first part of the paper and the lessons emerging from the way these cases have been dealt with in reality, we extract five interrelated generic principles for practicing science and management in complex NRM environments. These principles are then further elucidated using four further South African case studies - organized as two contrasting pairs - and now focusing on the more difficult organizational and social side, comparing the human organizational endeavors in managing such systems.
Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Riera-Fernández, Pablo; López-Díaz, Antonio; Pazos, Alejandro; González-Díaz, Humberto
2014-01-27
The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein interactions, or metabolic networks. However, the applications are not restricted to the world of molecules and can be extended to the study of macroscopic nonliving systems, organisms, or even legal or social networks. On the other hand, the development of the field of Artificial Intelligence has led to the formulation of computational algorithms whose design is based on the structure and functioning of networks of biological neurons. These algorithms, called Artificial Neural Networks (ANNs), can be useful for the study of complex networks, since the numerical parameters that encode information of the network (for example centralities/node descriptors) can be used as inputs for the ANNs. The Wiener index (W) is a graph invariant widely used in chemoinformatics to quantify the molecular structure of drugs and to study complex networks. In this work, we explore for the first time the possibility of using Markov chains to calculate analogues of node distance numbers/W to describe complex networks from the point of view of their nodes. These parameters are called Markov-Wiener node descriptors of order k(th) (W(k)). Please, note that these descriptors are not related to Markov-Wiener stochastic processes. Here, we calculated the W(k)(i) values for a very high number of nodes (>100,000) in more than 100 different complex networks using the software MI-NODES. These networks were grouped according to the field of application. Molecular networks include the Metabolic Reaction Networks (MRNs) of 40 different organisms. In addition, we analyzed other biological and legal and social networks. These include the Interaction Web Database Biological Networks (IWDBNs), with 75 food webs or ecological systems and the Spanish Financial Law Network (SFLN). The calculated W
Directory of Open Access Journals (Sweden)
T. Friedrich
2010-08-01
Full Text Available The mechanism triggering centennial-to-millennial-scale variability of the Atlantic Meridional Overturning Circulation (AMOC in the earth system model of intermediate complexity LOVECLIM is investigated. It is found that for several climate boundary conditions such as low obliquity values (~22.1° or LGM-albedo, internally generated centennial-to-millennial-scale variability occurs in the North Atlantic region. Stochastic excitations of the density-driven overturning circulation in the Nordic Seas can create regional sea-ice anomalies and a subsequent reorganization of the atmospheric circulation. The resulting remote atmospheric anomalies over the Hudson Bay can release freshwater pulses into the Labrador Sea and significantly increase snow fall in this region leading to a subsequent reduction of convective activity. The millennial-scale AMOC oscillations disappear if LGM bathymetry (with closed Hudson Bay is prescribed or if freshwater pulses are suppressed artificially. Furthermore, our study documents the process of the AMOC recovery as well as the global marine and terrestrial carbon cycle response to centennial-to-millennial-scale AMOC variability.
Directory of Open Access Journals (Sweden)
JuanM. Medina
2012-08-01
Full Text Available This paper proposes a parameterized definition for fuzzy comparators on complex fuzzy datatypes like fuzzy collections with conjunctive semantics and fuzzy objects. This definition and its implementation on a Fuzzy Object-Relational Database Management System (FORDBMS provides the designer with a powerful tool to adapt the behavior of these operators to the semantics of the considered application.
From System Complexity to Emergent Properties
Aziz-Alaoui, M. A
2009-01-01
Emergence and complexity refer to the appearance of higher-level properties and behaviours of a system that obviously comes from the collective dynamics of that system's components. These properties are not directly deductable from the lower-level motion of that system. Emergent properties are properties of the "whole'' that are not possessed by any of the individual parts making up that whole. Such phenomena exist in various domains and can be described, using complexity concepts and thematic knowledges. This book highlights complexity modelling through dynamical or behavioral systems. The pluridisciplinary purposes, developped along the chapters, are enable to design links between a wide-range of fundamental and applicative Sciences. Developing such links - instead of focusing on specific and narrow researches - is characteristic of the Science of Complexity that we try to promote by this contribution.
Multidimensional approach to complex system resilience analysis
International Nuclear Information System (INIS)
Gama Dessavre, Dante; Ramirez-Marquez, Jose E.; Barker, Kash
2016-01-01
Recent works have attempted to formally define a general metric for quantifying resilience for complex systems as a relationship of performance of the systems against time. The technical content in the proposed work introduces a new model that allows, for the first time, to compare the system resilience among systems (or different modifications to a system), by introducing a new dimension to system resilience models, called stress, to mimic the definition of resilience in material science. The applicability and usefulness of the model is shown with a new heat map visualization proposed in this work, and it is applied to a simulated network resilience case to exemplify its potential benefits. - Highlights: • We analyzed two of the main current metrics of resilience. • We create a new model that relates events with the effects they have. • We develop a novel heat map visualization to compare system resilience. • We showed the model and visualization usefulness in a simulated case.
Zunz, Violette; Goosse, Hugues; Dubinkina, Svetlana
2013-04-01
The sea ice extent in the Southern Ocean has increased since 1979 but the causes of this expansion have not been firmly identified. In particular, the contribution of internal variability and external forcing to this positive trend has not been fully established. In this region, the lack of observations and the overestimation of internal variability of the sea ice by contemporary General Circulation Models (GCMs) make it difficult to understand the behaviour of the sea ice. Nevertheless, if its evolution is governed by the internal variability of the system and if this internal variability is in some way predictable, a suitable initialization method should lead to simulations results that better fit the reality. Current GCMs decadal predictions are generally initialized through a nudging towards some observed fields. This relatively simple method does not seem to be appropriated to the initialization of sea ice in the Southern Ocean. The present study aims at identifying an initialization method that could improve the quality of the predictions of Southern Ocean sea ice at decadal timescales. We use LOVECLIM, an Earth-system Model of Intermediate Complexity that allows us to perform, within a reasonable computational time, the large amount of simulations required to test systematically different initialization procedures. These involve three data assimilation methods: a nudging, a particle filter and an efficient particle filter. In a first step, simulations are performed in an idealized framework, i.e. data from a reference simulation of LOVECLIM are used instead of observations, herein after called pseudo-observations. In this configuration, the internal variability of the model obviously agrees with the one of the pseudo-observations. This allows us to get rid of the issues related to the overestimation of the internal variability by models compared to the observed one. This way, we can work out a suitable methodology to assess the efficiency of the
Multifaceted Modelling of Complex Business Enterprises.
Chakraborty, Subrata; Mengersen, Kerrie; Fidge, Colin; Ma, Lin; Lassen, David
2015-01-01
We formalise and present a new generic multifaceted complex system approach for modelling complex business enterprises. Our method has a strong focus on integrating the various data types available in an enterprise which represent the diverse perspectives of various stakeholders. We explain the challenges faced and define a novel approach to converting diverse data types into usable Bayesian probability forms. The data types that can be integrated include historic data, survey data, and management planning data, expert knowledge and incomplete data. The structural complexities of the complex system modelling process, based on various decision contexts, are also explained along with a solution. This new application of complex system models as a management tool for decision making is demonstrated using a railway transport case study. The case study demonstrates how the new approach can be utilised to develop a customised decision support model for a specific enterprise. Various decision scenarios are also provided to illustrate the versatility of the decision model at different phases of enterprise operations such as planning and control.
Multifaceted Modelling of Complex Business Enterprises
2015-01-01
We formalise and present a new generic multifaceted complex system approach for modelling complex business enterprises. Our method has a strong focus on integrating the various data types available in an enterprise which represent the diverse perspectives of various stakeholders. We explain the challenges faced and define a novel approach to converting diverse data types into usable Bayesian probability forms. The data types that can be integrated include historic data, survey data, and management planning data, expert knowledge and incomplete data. The structural complexities of the complex system modelling process, based on various decision contexts, are also explained along with a solution. This new application of complex system models as a management tool for decision making is demonstrated using a railway transport case study. The case study demonstrates how the new approach can be utilised to develop a customised decision support model for a specific enterprise. Various decision scenarios are also provided to illustrate the versatility of the decision model at different phases of enterprise operations such as planning and control. PMID:26247591
Physical approach to complex systems
Kwapień, Jarosław; Drożdż, Stanisław
2012-06-01
Typically, complex systems are natural or social systems which consist of a large number of nonlinearly interacting elements. These systems are open, they interchange information or mass with environment and constantly modify their internal structure and patterns of activity in the process of self-organization. As a result, they are flexible and easily adapt to variable external conditions. However, the most striking property of such systems is the existence of emergent phenomena which cannot be simply derived or predicted solely from the knowledge of the systems’ structure and the interactions among their individual elements. This property points to the holistic approaches which require giving parallel descriptions of the same system on different levels of its organization. There is strong evidence-consolidated also in the present review-that different, even apparently disparate complex systems can have astonishingly similar characteristics both in their structure and in their behaviour. One can thus expect the existence of some common, universal laws that govern their properties. Physics methodology proves helpful in addressing many of the related issues. In this review, we advocate some of the computational methods which in our opinion are especially fruitful in extracting information on selected-but at the same time most representative-complex systems like human brain, financial markets and natural language, from the time series representing the observables associated with these systems. The properties we focus on comprise the collective effects and their coexistence with noise, long-range interactions, the interplay between determinism and flexibility in evolution, scale invariance, criticality, multifractality and hierarchical structure. The methods described either originate from “hard” physics-like the random matrix theory-and then were transmitted to other fields of science via the field of complex systems research, or they originated elsewhere but
Sutherland models for complex reflection groups
International Nuclear Information System (INIS)
Crampe, N.; Young, C.A.S.
2008-01-01
There are known to be integrable Sutherland models associated to every real root system, or, which is almost equivalent, to every real reflection group. Real reflection groups are special cases of complex reflection groups. In this paper we associate certain integrable Sutherland models to the classical family of complex reflection groups. Internal degrees of freedom are introduced, defining dynamical spin chains, and the freezing limit taken to obtain static chains of Haldane-Shastry type. By considering the relation of these models to the usual BC N case, we are led to systems with both real and complex reflection groups as symmetries. We demonstrate their integrability by means of new Dunkl operators, associated to wreath products of dihedral groups
Complexity-aware simple modeling.
Gómez-Schiavon, Mariana; El-Samad, Hana
2018-02-26
Mathematical models continue to be essential for deepening our understanding of biology. On one extreme, simple or small-scale models help delineate general biological principles. However, the parsimony of detail in these models as well as their assumption of modularity and insulation make them inaccurate for describing quantitative features. On the other extreme, large-scale and detailed models can quantitatively recapitulate a phenotype of interest, but have to rely on many unknown parameters, making them often difficult to parse mechanistically and to use for extracting general principles. We discuss some examples of a new approach-complexity-aware simple modeling-that can bridge the gap between the small-scale and large-scale approaches. Copyright © 2018 Elsevier Ltd. All rights reserved.
Collectives and the design of complex systems
Wolpert, David
2004-01-01
Increasingly powerful computers are making possible distributed systems comprised of many adaptive and self-motivated computational agents. Such systems, when distinguished by system-level performance criteria, are known as "collectives." Collectives and the Design of Complex Systems lays the foundation for a science of collectives and describes how to design them for optimal performance. An introductory survey chapter is followed by descriptions of information-processing problems that can only be solved by the joint actions of large communities of computers, each running its own complex, decentralized machine-learning algorithm. Subsequent chapters analyze the dynamics and structures of collectives, as well as address economic, model-free, and control-theory approaches to designing complex systems. The work assumes a modest understanding of basic statistics and calculus. Topics and Features: Introduces the burgeoning science of collectives and its practical applications in a single useful volume Combines ap...
1989 lectures in complex systems
International Nuclear Information System (INIS)
Jen, E.
1990-01-01
This report contains papers on the following topics: Lectures on a Theory of Computation and Complexity over the Reals; Algorithmic Information Content, Church-Turing Thesis, Physical Entroph, and Maxwell's Demon; Physical Measures of Complexity; An Introduction to Chaos and Prediction; Hamiltonian Chaos in Nonlinear Polarized Optical Beam; Chemical Oscillators and Nonlinear Chemical Dynamics; Isotropic Navier-Stokes Turbulence. I. Qualitative Features and Basic Equations; Isotropic Navier-Stokes Turbulence. II. Statistical Approximation Methods; Lattice Gases; Data-Parallel Computation and the Connection Machine; Preimages and Forecasting for Cellular Automata; Lattice-Gas Models for Multiphase Flows and Magnetohydrodynamics; Probabilistic Cellular Automata: Some Statistical Mechanical Considerations; Complexity Due to Disorder and Frustration; Self-Organization by Simulated Evolution; Theoretical Immunology; Morphogenesis by Cell Intercalation; and Theoretical Physics Meets Experimental Neurobiology
Discontinuity and complexity in nonlinear physical systems
Baleanu, Dumitru; Luo, Albert
2014-01-01
This unique book explores recent developments in experimental research in this broad field, organized in four distinct sections. Part I introduces the reader to the fractional dynamics and Lie group analysis for nonlinear partial differential equations. Part II covers chaos and complexity in nonlinear Hamiltonian systems, important to understand the resonance interactions in nonlinear dynamical systems, such as Tsunami waves and wildfire propagations; as well as Lev flights in chaotic trajectories, dynamical system synchronization and DNA information complexity analysis. Part III examines chaos and periodic motions in discontinuous dynamical systems, extensively present in a range of systems, including piecewise linear systems, vibro-impact systems and drilling systems in engineering. And in Part IV, engineering and financial nonlinearity are discussed. The mechanism of shock wave with saddle-node bifurcation and rotating disk stability will be presented, and the financial nonlinear models will be discussed....
Extraction of quantifiable information from complex systems
Dahmen, Wolfgang; Griebel, Michael; Hackbusch, Wolfgang; Ritter, Klaus; Schneider, Reinhold; Schwab, Christoph; Yserentant, Harry
2014-01-01
In April 2007, the Deutsche Forschungsgemeinschaft (DFG) approved the Priority Program 1324 “Mathematical Methods for Extracting Quantifiable Information from Complex Systems.” This volume presents a comprehensive overview of the most important results obtained over the course of the program. Mathematical models of complex systems provide the foundation for further technological developments in science, engineering and computational finance. Motivated by the trend toward steadily increasing computer power, ever more realistic models have been developed in recent years. These models have also become increasingly complex, and their numerical treatment poses serious challenges. Recent developments in mathematics suggest that, in the long run, much more powerful numerical solution strategies could be derived if the interconnections between the different fields of research were systematically exploited at a conceptual level. Accordingly, a deeper understanding of the mathematical foundations as w...
A new decision sciences for complex systems.
Lempert, Robert J
2002-05-14
Models of complex systems can capture much useful information but can be difficult to apply to real-world decision-making because the type of information they contain is often inconsistent with that required for traditional decision analysis. New approaches, which use inductive reasoning over large ensembles of computational experiments, now make possible systematic comparison of alternative policy options using models of complex systems. This article describes Computer-Assisted Reasoning, an approach to decision-making under conditions of deep uncertainty that is ideally suited to applying complex systems to policy analysis. The article demonstrates the approach on the policy problem of global climate change, with a particular focus on the role of technology policies in a robust, adaptive strategy for greenhouse gas abatement.
El-Sawah, Sondoss; Guillaume, Joseph H.A.; Filatova, Tatiana; Rook, Josefine; Jakeman, Anthony J.
2015-01-01
This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation
Complex fluids modeling and algorithms
Saramito, Pierre
2016-01-01
This book presents a comprehensive overview of the modeling of complex fluids, including many common substances, such as toothpaste, hair gel, mayonnaise, liquid foam, cement and blood, which cannot be described by Navier-Stokes equations. It also offers an up-to-date mathematical and numerical analysis of the corresponding equations, as well as several practical numerical algorithms and software solutions for the approximation of the solutions. It discusses industrial (molten plastics, forming process), geophysical (mud flows, volcanic lava, glaciers and snow avalanches), and biological (blood flows, tissues) modeling applications. This book is a valuable resource for undergraduate students and researchers in applied mathematics, mechanical engineering and physics.
The Kuramoto model in complex networks
Rodrigues, Francisco A.; Peron, Thomas K. DM.; Ji, Peng; Kurths, Jürgen
2016-01-01
Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from social and physical to biological and technological systems. The most successful approach to describe how coherent behavior emerges in these complex systems is given by the paradigmatic Kuramoto model. This model has been traditionally studied in complete graphs. However, besides being intrinsically dynamical, complex systems present very heterogeneous structure, which can be represented as complex networks. This report is dedicated to review main contributions in the field of synchronization in networks of Kuramoto oscillators. In particular, we provide an overview of the impact of network patterns on the local and global dynamics of coupled phase oscillators. We cover many relevant topics, which encompass a description of the most used analytical approaches and the analysis of several numerical results. Furthermore, we discuss recent developments on variations of the Kuramoto model in networks, including the presence of noise and inertia. The rich potential for applications is discussed for special fields in engineering, neuroscience, physics and Earth science. Finally, we conclude by discussing problems that remain open after the last decade of intensive research on the Kuramoto model and point out some promising directions for future research.
System crash as dynamics of complex networks.
Yu, Yi; Xiao, Gaoxi; Zhou, Jie; Wang, Yubo; Wang, Zhen; Kurths, Jürgen; Schellnhuber, Hans Joachim
2016-10-18
Complex systems, from animal herds to human nations, sometimes crash drastically. Although the growth and evolution of systems have been extensively studied, our understanding of how systems crash is still limited. It remains rather puzzling why some systems, appearing to be doomed to fail, manage to survive for a long time whereas some other systems, which seem to be too big or too strong to fail, crash rapidly. In this contribution, we propose a network-based system dynamics model, where individual actions based on the local information accessible in their respective system structures may lead to the "peculiar" dynamics of system crash mentioned above. Extensive simulations are carried out on synthetic and real-life networks, which further reveal the interesting system evolution leading to the final crash. Applications and possible extensions of the proposed model are discussed.
Designing complex systems - a structured activity
van der Veer, Gerrit C.; van Vliet, Johannes C.; Lenting, Bert; Olson, Gary M.; Schuon, Sue
1995-01-01
This paper concerns the development of complex systems from the point of view of design as a structure of activities, related both to the clients and the users. Several modeling approaches will be adopted for different aspects of design, and several views on design will be integrated. The proposed
Pulido-Velazquez, Manuel; Lopez-Nicolas, Antonio; Harou, Julien J.; Andreu, Joaquin
2013-04-01
Hydrologic-economic models allow integrated analysis of water supply, demand and infrastructure management at the river basin scale. These models simultaneously analyze engineering, hydrology and economic aspects of water resources management. Two new tools have been designed to develop models within this approach: a simulation tool (SIM_GAMS), for models in which water is allocated each month based on supply priorities to competing uses and system operating rules, and an optimization tool (OPT_GAMS), in which water resources are allocated optimally following economic criteria. The characterization of the water resource network system requires a connectivity matrix representing the topology of the elements, generated using HydroPlatform. HydroPlatform, an open-source software platform for network (node-link) models, allows to store, display and export all information needed to characterize the system. Two generic non-linear models have been programmed in GAMS to use the inputs from HydroPlatform in simulation and optimization models. The simulation model allocates water resources on a monthly basis, according to different targets (demands, storage, environmental flows, hydropower production, etc.), priorities and other system operating rules (such as reservoir operating rules). The optimization model's objective function is designed so that the system meets operational targets (ranked according to priorities) each month while following system operating rules. This function is analogous to the one used in the simulation module of the DSS AQUATOOL. Each element of the system has its own contribution to the objective function through unit cost coefficients that preserve the relative priority rank and the system operating rules. The model incorporates groundwater and stream-aquifer interaction (allowing conjunctive use simulation) with a wide range of modeling options, from lumped and analytical approaches to parameter-distributed models (eigenvalue approach). Such
Combinations of complex dynamical systems
Pilgrim, Kevin M
2003-01-01
This work is a research-level monograph whose goal is to develop a general combination, decomposition, and structure theory for branched coverings of the two-sphere to itself, regarded as the combinatorial and topological objects which arise in the classification of certain holomorphic dynamical systems on the Riemann sphere. It is intended for researchers interested in the classification of those complex one-dimensional dynamical systems which are in some loose sense tame. The program is motivated by the dictionary between the theories of iterated rational maps and Kleinian groups.
Semiotics of constructed complex systems
Energy Technology Data Exchange (ETDEWEB)
Landauer, C.; Bellman, K.L.
1996-12-31
The scope of this paper is limited to software and other constructed complex systems mediated or integrated by software. Our research program studies foundational issues that we believe will help us develop a theoretically sound approach to constructing complex systems. There have really been only two theoretical approaches that have helped us understand and develop computational systems: mathematics and linguistics. We show how semiotics can also play a role, whether we think of it as part of these other theories or as subsuming one or both of them. We describe our notion of {open_quotes}computational semiotics{close_quotes}, which we define to be the study of computational methods of dealing with symbols, show how such a theory might be formed, and describe what we might get from it in terms of more interesting use of symbols by computing systems. This research was supported in part by the Federal Highway Administration`s Office of Advanced Research and by the Advanced Research Projects Agency`s Software and Intelligent Systems Technology Office.
Complex Adaptive Systems of Systems (CASOS) engineering environment.
Energy Technology Data Exchange (ETDEWEB)
Detry, Richard Joseph; Linebarger, John Michael; Finley, Patrick D.; Maffitt, S. Louise; Glass, Robert John, Jr.; Beyeler, Walter Eugene; Ames, Arlo Leroy
2012-02-01
Complex Adaptive Systems of Systems, or CASoS, are vastly complex physical-socio-technical systems which we must understand to design a secure future for the nation. The Phoenix initiative implements CASoS Engineering principles combining the bottom up Complex Systems and Complex Adaptive Systems view with the top down Systems Engineering and System-of-Systems view. CASoS Engineering theory and practice must be conducted together to develop a discipline that is grounded in reality, extends our understanding of how CASoS behave and allows us to better control the outcomes. The pull of applications (real world problems) is critical to this effort, as is the articulation of a CASoS Engineering Framework that grounds an engineering approach in the theory of complex adaptive systems of systems. Successful application of the CASoS Engineering Framework requires modeling, simulation and analysis (MS and A) capabilities and the cultivation of a CASoS Engineering Community of Practice through knowledge sharing and facilitation. The CASoS Engineering Environment, itself a complex adaptive system of systems, constitutes the two platforms that provide these capabilities.
Energy Technology Data Exchange (ETDEWEB)
Marzouk, Youssef [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
2016-08-31
Predictive simulation of complex physical systems increasingly rests on the interplay of experimental observations with computational models. Key inputs, parameters, or structural aspects of models may be incomplete or unknown, and must be developed from indirect and limited observations. At the same time, quantified uncertainties are needed to qualify computational predictions in the support of design and decision-making. In this context, Bayesian statistics provides a foundation for inference from noisy and limited data, but at prohibitive computional expense. This project intends to make rigorous predictive modeling *feasible* in complex physical systems, via accelerated and scalable tools for uncertainty quantification, Bayesian inference, and experimental design. Specific objectives are as follows: 1. Develop adaptive posterior approximations and dimensionality reduction approaches for Bayesian inference in high-dimensional nonlinear systems. 2. Extend accelerated Bayesian methodologies to large-scale {\\em sequential} data assimilation, fully treating nonlinear models and non-Gaussian state and parameter distributions. 3. Devise efficient surrogate-based methods for Bayesian model selection and the learning of model structure. 4. Develop scalable simulation/optimization approaches to nonlinear Bayesian experimental design, for both parameter inference and model selection. 5. Demonstrate these inferential tools on chemical kinetic models in reacting flow, constructing and refining thermochemical and electrochemical models from limited data. Demonstrate Bayesian filtering on canonical stochastic PDEs and in the dynamic estimation of inhomogeneous subsurface properties and flow fields.
5th International Conference on Complex Systems
Braha, Dan; Bar-Yam, Yaneer
2011-01-01
The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore common themes and applications of complex system science. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex system science.
7th International Conference on Complex Systems
Braha, Dan; Bar-Yam, Yaneer
2012-01-01
The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore common themes and applications of complex system science. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex system science.
Directory of Open Access Journals (Sweden)
Rocha Reginaldo C.
2001-01-01
Full Text Available Iron and ruthenium complexes of the type [M-LH]n (where M = RuII,III(NH35(2+,3+, RuII,III(edta2-,- [edta = ethylenedinitrilotetraacetate], or FeII,III(CN5(3-,2- and LH = benzotriazole or benzimidazole were prepared and characterized in aqueous solutions by means of electrochemical and spectroelectrochemical methods. Special emphasis was given to the pH-dependent redox processes, exhibited by all the investigated complexes. From their related Pourbaix diagrams, which displayed a typically Nernstian behavior, the pKa and formal reduction potential values were extracted. In addition, these E1/2 versus pH curves were also used to illustrate the partitioning relationship concerning the redox and acid-base species, and their interconversion equilibria. The active area in which the dependence of the M III/M II couple on the pH takes place, as delimited by pKaIII and pKaII, was taken into account in order to evaluate the usefulness of such simple complexes as models for proton-coupled electron transfer (PCET. The results were interpreted in terms of the acceptor/donor electronic character of the ligands and sigma,pi-metal-ligand interactions in both redox states of the metal ion.
Bosikov, I. I.; Klyuev, R. V.; Revazov, V. Ch; Pilieva, D. E.
2018-03-01
The article describes research and analysis of hazardous processes occurring in the natural-industrial system and effectiveness assessment of its functioning using mathematical models. Studies of the functioning regularities of the natural and industrial system are becoming increasingly relevant in connection with the formulation of the task of modernizing production and the economy of Russia as a whole. In connection with a significant amount of poorly structured data, it is complicated by regulations for the effective functioning of production processes, social and natural complexes, under which a sustainable development of the natural-industrial system of the mining and processing complex would be ensured. Therefore, the scientific and applied problems, the solution of which allows one to formalize the hidden structural functioning patterns of the natural-industrial system and to make managerial decisions of organizational and technological nature to improve the efficiency of the system, are very relevant.
Model complexity control for hydrologic prediction
Schoups, G.; Van de Giesen, N.C.; Savenije, H.H.G.
2008-01-01
A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore
Distributed redundancy and robustness in complex systems
Randles, Martin
2011-03-01
The uptake and increasing prevalence of Web 2.0 applications, promoting new large-scale and complex systems such as Cloud computing and the emerging Internet of Services/Things, requires tools and techniques to analyse and model methods to ensure the robustness of these new systems. This paper reports on assessing and improving complex system resilience using distributed redundancy, termed degeneracy in biological systems, to endow large-scale complicated computer systems with the same robustness that emerges in complex biological and natural systems. However, in order to promote an evolutionary approach, through emergent self-organisation, it is necessary to specify the systems in an \\'open-ended\\' manner where not all states of the system are prescribed at design-time. In particular an observer system is used to select robust topologies, within system components, based on a measurement of the first non-zero Eigen value in the Laplacian spectrum of the components\\' network graphs; also known as the algebraic connectivity. It is shown, through experimentation on a simulation, that increasing the average algebraic connectivity across the components, in a network, leads to an increase in the variety of individual components termed distributed redundancy; the capacity for structurally distinct components to perform an identical function in a particular context. The results are applied to a specific application where active clustering of like services is used to aid load balancing in a highly distributed network. Using the described procedure is shown to improve performance and distribute redundancy. © 2010 Elsevier Inc.
Lee, Peter; Calvo, Conrado J.; Alfonso-Almazán, José M.; Quintanilla, Jorge G.; Chorro, Francisco J.; Yan, Ping; Loew, Leslie M.; Filgueiras-Rama, David; Millet, José
2017-02-01
Panoramic optical mapping is the primary method for imaging electrophysiological activity from the entire outer surface of Langendorff-perfused hearts. To date, it is the only method of simultaneously measuring multiple key electrophysiological parameters, such as transmembrane voltage and intracellular free calcium, at high spatial and temporal resolution. Despite the impact it has already had on the fields of cardiac arrhythmias and whole-heart computational modeling, present-day system designs precludes its adoption by the broader cardiovascular research community because of their high costs. Taking advantage of recent technological advances, we developed and validated low-cost optical mapping systems for panoramic imaging using Langendorff-perfused pig hearts, a clinically-relevant model in basic research and bioengineering. By significantly lowering financial thresholds, this powerful cardiac electrophysiology imaging modality may gain wider use in research and, even, teaching laboratories, which we substantiated using the lower-cost Langendorff-perfused rabbit heart model.
Elsawah, Sondoss; Guillaume, Joseph H A; Filatova, Tatiana; Rook, Josefine; Jakeman, Anthony J
2015-03-15
This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation models (quantitative) with the ultimate goal of improving understanding and communication about decision making in complex socio-ecological systems. The methodology integrates cognitive mapping and agent based modelling. It cascades through a sequence of qualitative/soft and numerical methods comprising: (1) Interviews to elicit mental models; (2) Cognitive maps to represent and analyse individual and group mental models; (3) Time-sequence diagrams to chronologically structure the decision making process; (4) All-encompassing conceptual model of decision making, and (5) computational (in this case agent-based) Model. We apply the proposed methodology (labelled ICTAM) in a case study of viticulture irrigation in South Australia. Finally, we use strengths-weakness-opportunities-threats (SWOT) analysis to reflect on the methodology. Results show that the methodology leverages the use of cognitive mapping to capture the richness of decision making and mental models, and provides a combination of divergent and convergent analysis methods leading to the construction of an Agent Based Model. Copyright © 2014 Elsevier Ltd. All rights reserved.
Modelling the complex dynamics of vegetation, livestock and rainfall ...
African Journals Online (AJOL)
Open Access DOWNLOAD FULL TEXT ... In this paper, we present mathematical models that incorporate ideas from complex systems theory to integrate several strands of rangeland theory in a hierarchical framework. ... Keywords: catastrophe theory; complexity theory; disequilibrium; hysteresis; moving attractors
Hadaeghi, Fatemeh; Hashemi Golpayegani, Mohammad Reza; Jafari, Sajad; Murray, Greg
2016-08-01
In the absence of a comprehensive neural model to explain the underlying mechanisms of disturbed circadian function in bipolar disorder, mathematical modeling is a helpful tool. Here, circadian activity as a response to exogenous daily cycles is proposed to be the product of interactions between neuronal networks in cortical (cognitive processing) and subcortical (pacemaker) areas of the brain. To investigate the dynamical aspects of the link between disturbed circadian activity rhythms and abnormalities of neurotransmitter functioning in frontal areas of the brain, we developed a novel mathematical model of a chaotic system which represents fluctuations in circadian activity in bipolar disorder as changes in the model's parameters. A novel map-based chaotic system was developed to capture disturbances in circadian activity across the two extreme mood states of bipolar disorder. The model uses chaos theory to characterize interplay between neurotransmitter functions and rhythm generation; it aims to illuminate key activity phenomenology in bipolar disorder, including prolonged sleep intervals, decreased total activity and attenuated amplitude of the diurnal activity rhythm. To test our new cortical-circadian mathematical model of bipolar disorder, we utilized previously collected locomotor activity data recorded from normal subjects and bipolar patients by wrist-worn actigraphs. All control parameters in the proposed model have an important role in replicating the different aspects of circadian activity rhythm generation in the brain. The model can successfully replicate deviations in sleep/wake time intervals corresponding to manic and depressive episodes of bipolar disorder, in which one of the excitatory or inhibitory pathways is abnormally dominant. Although neuroimaging research has strongly implicated a reciprocal interaction between cortical and subcortical regions as pathogenic in bipolar disorder, this is the first model to mathematically represent this
Energy Technology Data Exchange (ETDEWEB)
Burgwinkel, Paul; Vreydal, Daniel; Eltaliawi, Gamil; Vijayakumar, Nandhakumar [RWTH Aachen (DE). Inst. fuer Maschinentechnik der Rohstoffindustrie (IMR)
2010-09-15
For the first time the Co-simulation method was successfully used for full representation of a large belt conveyor for an open cast mine in a simulation model at the Institute for Mechanical Engineering in the Raw Materials Industry at Rhineland-Westphalia Technological University in Aachen. The aim of this project was the development of an electro-mechanical simulation model, which represents all components of a large belt conveyor from the drive motor to the conveyor belt in one simulation model and thus makes the interactions between the individual assemblies verifiable by calculations. With the aid of the developed model it was possible to determine critical operating speeds of the represented large belt conveyor and derive suitable measures to combat undesirable resonance states in the drive assembly. Furthermore it was possible to clarify the advantage of the full numerical representation of an electromechanical drive system. (orig.)
International Nuclear Information System (INIS)
Han, Yongming; Zhu, Qunxiong; Geng, Zhiqiang; Xu, Yuan
2017-01-01
Highlights: • The ELM integrated ISM (ISM-ELM) method is proposed. • The proposed method is more efficient and accurate than the ELM through the UCI data set. • Energy and carbon emissions analysis and prediction of petrochemical industries based ISM-ELM is obtained. • The proposed method is valid in improving energy efficiency and reducing carbon emissions of ethylene plants. - Abstract: Energy saving and carbon emissions reduction of the petrochemical industry are affected by many factors. Thus, it is difficult to analyze and optimize the energy of complex petrochemical systems accurately. This paper proposes an energy and carbon emissions analysis and prediction approach based on an improved extreme learning machine (ELM) integrated interpretative structural model (ISM) (ISM-ELM). ISM based the partial correlation coefficient is utilized to analyze key parameters that affect the energy and carbon emissions of the complex petrochemical system, and can denoise and reduce dimensions of data to decrease the training time and errors of the ELM prediction model. Meanwhile, in terms of the model accuracy and the training time, the robustness and effectiveness of the ISM-ELM model are better than the ELM through standard data sets from the University of California Irvine (UCI) repository. Moreover, a multi-inputs and single-output (MISO) model of energy and carbon emissions of complex ethylene systems is established based on the ISM-ELM. Finally, detailed analyses and simulations using the real ethylene plant data demonstrate the effectiveness of the ISM-ELM and can guide the improvement direction of energy saving and carbon emissions reduction in complex petrochemical systems.
Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.
2015-12-01
Our work focuses on development of a multi-agent, hydroeconomic model for purposes of water policy evaluation in Jordan. The model adopts a modular approach, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the groundwater model, we adopt a response matrix method approach in which a 3-dimensional MODFLOW model of a complex regional groundwater system is converted into a linear simulator of groundwater response by pre-processing drawdown results from several hundred numerical simulation runs. Surface water models for each major surface water basin in the country are developed in SWAT and similarly translated into simple rainfall-runoff functions for integration with the multi-agent model. The approach balances physically-based, spatially-explicit representation of hydrologic systems with the efficiency required for integration into a complex multi-agent model that is computationally amenable to robust scenario analysis. For the multi-agent model, we explicitly represent human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. The agents' decision making models incorporate both rule-based heuristics as well as economic optimization. The model is programmed in Python using Pynsim, a generalizable, open-source object-oriented code framework for modeling network-based water resource systems. The Jordan model is one of the first applications of Pynsim to a real-world water management case study. Preliminary results from a tanker market scenario run through year 2050 are presented in which several salient features of the water system are investigated: competition between urban and
Interdisciplinary Symposium on Complex Systems
Zelinka, Ivan; Rössler, Otto
2014-01-01
The book you hold in your hands is the outcome of the "ISCS 2013: Interdisciplinary Symposium on Complex Systems" held at the historical capital of Bohemia as a continuation of our series of symposia in the science of complex systems. Prague, one of the most beautiful European cities, has its own beautiful genius loci. Here, a great number of important discoveries were made and many important scientists spent fruitful and creative years to leave unforgettable traces. The perhaps most significant period was the time of Rudolf II who was a great supporter of the art and the science and attracted a great number of prominent minds to Prague. This trend would continue. Tycho Brahe, Niels Henrik Abel, Johannes Kepler, Bernard Bolzano, August Cauchy Christian Doppler, Ernst Mach, Albert Einstein and many others followed developing fundamental mathematical and physical theories or expanding them. Thus in the beginning of the 17th century, Kepler formulated here the first two of his three laws of planetary motion on ...
Complex scaling in the cluster model
International Nuclear Information System (INIS)
Kruppa, A.T.; Lovas, R.G.; Gyarmati, B.
1987-01-01
To find the positions and widths of resonances, a complex scaling of the intercluster relative coordinate is introduced into the resonating-group model. In the generator-coordinate technique used to solve the resonating-group equation the complex scaling requires minor changes in the formulae and code. The finding of the resonances does not need any preliminary guess or explicit reference to any asymptotic prescription. The procedure is applied to the resonances in the relative motion of two ground-state α clusters in 8 Be, but is appropriate for any systems consisting of two clusters. (author) 23 refs.; 5 figs
Engineering education as a complex system
Gattie, David K.; Kellam, Nadia N.; Schramski, John R.; Walther, Joachim
2011-12-01
This paper presents a theoretical basis for cultivating engineering education as a complex system that will prepare students to think critically and make decisions with regard to poorly understood, ill-structured issues. Integral to this theoretical basis is a solution space construct developed and presented as a benchmark for evaluating problem-solving orientations that emerge within students' thinking as they progress through an engineering curriculum. It is proposed that the traditional engineering education model, while analytically rigorous, is characterised by properties that, although necessary, are insufficient for preparing students to address complex issues of the twenty-first century. A Synthesis and Design Studio model for engineering education is proposed, which maintains the necessary rigor of analysis within a uniquely complex yet sufficiently structured learning environment.
Mathis, Moritz; Elizalde, Alberto; Mikolajewicz, Uwe
2018-04-01
Climate change impact studies for the Northwest European Shelf (NWES) make use of various dynamical downscaling strategies in the experimental setup of regional ocean circulation models. Projected change signals from coupled and uncoupled downscalings with different domain sizes and forcing global and regional models show substantial uncertainty. In this paper, we investigate influences of the downscaling strategy on projected changes in the physical and biogeochemical conditions of the NWES. Our results indicate that uncertainties due to different downscaling strategies are similar to uncertainties due to the choice of the parent global model and the downscaling regional model. Downscaled change signals reveal to depend stronger on the downscaling strategy than on the model skills in simulating present-day conditions. Uncoupled downscalings of sea surface temperature (SST) changes are found to be tightly constrained by the atmospheric forcing. The incorporation of coupled air-sea interaction, by contrast, allows the regional model system to develop independently. Changes in salinity show a higher sensitivity to open lateral boundary conditions and river runoff than to coupled or uncoupled atmospheric forcings. Dependencies on the downscaling strategy for changes in SST, salinity, stratification and circulation collectively affect changes in nutrient import and biological primary production.
Morphogenetic Engineering Toward Programmable Complex Systems
Sayama, Hiroki; Michel, Olivier
2012-01-01
Generally, spontaneous pattern formation phenomena are random and repetitive, whereas elaborate devices are the deterministic product of human design. Yet, biological organisms and collective insect constructions are exceptional examples of complex systems that are both self-organized and architectural. This book is the first initiative of its kind toward establishing a new field of research, Morphogenetic Engineering, to explore the modeling and implementation of “self-architecturing” systems. Particular emphasis is placed on the programmability and computational abilities of self-organization, properties that are often underappreciated in complex systems science—while, conversely, the benefits of self-organization are often underappreciated in engineering methodologies. Altogether, the aim of this work is to provide a framework for and examples of a larger class of “self-architecturing” systems, while addressing fundamental questions such as > How do biological organisms carry out morphog...
Complexity in electronic negotiation support systems.
Griessmair, Michele; Strunk, Guido; Vetschera, Rudolf; Koeszegi, Sabine T
2011-10-01
It is generally acknowledged that the medium influences the way we communicate and negotiation research directs considerable attention to the impact of different electronic communication modes on the negotiation process and outcomes. Complexity theories offer models and methods that allow the investigation of how pattern and temporal sequences unfold over time in negotiation interactions. By focusing on the dynamic and interactive quality of negotiations as well as the information, choice, and uncertainty contained in the negotiation process, the complexity perspective addresses several issues of central interest in classical negotiation research. In the present study we compare the complexity of the negotiation communication process among synchronous and asynchronous negotiations (IM vs. e-mail) as well as an electronic negotiation support system including a decision support system (DSS). For this purpose, transcripts of 145 negotiations have been coded and analyzed with the Shannon entropy and the grammar complexity. Our results show that negotiating asynchronically via e-mail as well as including a DSS significantly reduces the complexity of the negotiation process. Furthermore, a reduction of the complexity increases the probability of reaching an agreement.
International Nuclear Information System (INIS)
Andersen, V.; Andersen, H.B.; Axel, E.; Petersen, T.
1990-01-01
A short introduction will be given to the European (ESPRIT II) project, ''IT Support for Emergency Management - ISEM''. The project is aimed at the development of an integrated information system capable of supporting the complex, dynamic, distributed decision making in the management of emergencies. The basic models developed to describe and construct emergency management organisations and their preparedness have been illustrated, and it has been stated that similarities may be found even in emergency situations that originally are of quite different nature. (author)
Unified Computational Intelligence for Complex Systems
Seiffertt, John
2010-01-01
Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to e
Automatic Emergence Detection in Complex Systems
Directory of Open Access Journals (Sweden)
Eugene Santos
2017-01-01
Full Text Available Complex systems consist of multiple interacting subsystems, whose nonlinear interactions can result in unanticipated (emergent system events. Extant systems analysis approaches fail to detect such emergent properties, since they analyze each subsystem separately and arrive at decisions typically through linear aggregations of individual analysis results. In this paper, we propose a quantitative definition of emergence for complex systems. We also propose a framework to detect emergent properties given observations of its subsystems. This framework, based on a probabilistic graphical model called Bayesian Knowledge Bases (BKBs, learns individual subsystem dynamics from data, probabilistically and structurally fuses said dynamics into a single complex system dynamics, and detects emergent properties. Fusion is the central element of our approach to account for situations when a common variable may have different probabilistic distributions in different subsystems. We evaluate our detection performance against a baseline approach (Bayesian Network ensemble on synthetic testbeds from UCI datasets. To do so, we also introduce a method to simulate and a metric to measure discrepancies that occur with shared/common variables. Experiments demonstrate that our framework outperforms the baseline. In addition, we demonstrate that this framework has uniform polynomial time complexity across all three learning, fusion, and reasoning procedures.
Alexandridis, Konstantinos T.
This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land
Metric for Calculation of System Complexity based on its Connections
Directory of Open Access Journals (Sweden)
João Ricardo Braga de Paiva
2017-02-01
Full Text Available This paper proposes a methodology based on system connections to calculate its complexity. Two study cases are proposed: the dining Chinese philosophers’ problem and the distribution center. Both studies are modeled using the theory of Discrete Event Systems and simulations in different contexts were performed in order to measure their complexities. The obtained results present i the static complexity as a limiting factor for the dynamic complexity, ii the lowest cost in terms of complexity for each unit of measure of the system performance and iii the output sensitivity to the input parameters. The associated complexity and performance measures aggregate knowledge about the system.
Complex Physical, Biophysical and Econophysical Systems
Dewar, Robert L.; Detering, Frank
1. Introduction to complex and econophysics systems: a navigation map / T. Aste and T. Di Matteo -- 2. An introduction to fractional diffusion / B. I. Henry, T.A.M. Langlands and P. Straka -- 3. Space plasmas and fusion plasmas as complex systems / R. O. Dendy -- 4. Bayesian data analysis / M. S. Wheatland -- 5. Inverse problems and complexity in earth system science / I. G. Enting -- 6. Applied fluid chaos: designing advection with periodically reoriented flows for micro to geophysical mixing and transport enhancement / G. Metcalfe -- 7. Approaches to modelling the dynamical activity of brain function based on the electroencephalogram / D. T. J. Liley and F. Frascoli -- 8. Jaynes' maximum entropy principle, Riemannian metrics and generalised least action bound / R. K. Niven and B. Andresen -- 9. Complexity, post-genomic biology and gene expression programs / R. B. H. Williams and O. J.-H. Luo -- 10. Tutorials on agent-based modelling with NetLogo and network analysis with Pajek / M. J. Berryman and S. D. Angus.
Dependability problems of complex information systems
Zamojski, Wojciech
2014-01-01
This monograph presents original research results on selected problems of dependability in contemporary Complex Information Systems (CIS). The ten chapters are concentrated around the following three aspects: methods for modelling of the system and its components, tasks ? or in more generic and more adequate interpretation, functionalities ? accomplished by the system and conditions for their correct realization in the dynamic operational environment. While the main focus is on theoretical advances and roadmaps for implementations of new technologies, a?much needed forum for sharing of the bes
Infinite Particle Systems: Complex Systems III
Directory of Open Access Journals (Sweden)
Editorial Board
2008-06-01
Full Text Available In the years 2002-2005, a group of German and Polish mathematicians worked under a DFG research project No 436 POL 113/98/0-1 entitled "Methods of stochastic analysis in the theory of collective phenomena: Gibbs states and statistical hydrodynamics". The results of their study were summarized at the German-Polish conference, which took place in Poland in October 2005. The venue of the conference was Kazimierz Dolny upon Vistula - a lovely town and a popular place for various cultural, scientific, and even political events of an international significance. The conference was also attended by scientists from France, Italy, Portugal, UK, Ukraine, and USA, which predetermined its international character. Since that time, the conference, entitled "Infinite Particle Systems: Complex Systems" has become an annual international event, attended by leading scientists from Germany, Poland and many other countries. The present volume of the "Condensed Matter Physics" contains proceedings of the conference "Infinite Particle Systems: Complex Systems III", which took place in June 2007.
Nonparametric Bayesian Modeling of Complex Networks
DEFF Research Database (Denmark)
Schmidt, Mikkel Nørgaard; Mørup, Morten
2013-01-01
an infinite mixture model as running example, we go through the steps of deriving the model as an infinite limit of a finite parametric model, inferring the model parameters by Markov chain Monte Carlo, and checking the model?s fit and predictive performance. We explain how advanced nonparametric models......Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...
Bilinear effect in complex systems
Lam, Lui; Bellavia, David C.; Han, Xiao-Pu; Alston Liu, Chih-Hui; Shu, Chang-Qing; Wei, Zhengjin; Zhou, Tao; Zhu, Jichen
2010-09-01
The distribution of the lifetime of Chinese dynasties (as well as that of the British Isles and Japan) in a linear Zipf plot is found to consist of two straight lines intersecting at a transition point. This two-section piecewise-linear distribution is different from the power law or the stretched exponent distribution, and is called the Bilinear Effect for short. With assumptions mimicking the organization of ancient Chinese regimes, a 3-layer network model is constructed. Numerical results of this model show the bilinear effect, providing a plausible explanation of the historical data. The bilinear effect in two other social systems is presented, indicating that such a piecewise-linear effect is widespread in social systems.
From complex to simple: interdisciplinary stochastic models
International Nuclear Information System (INIS)
Mazilu, D A; Zamora, G; Mazilu, I
2012-01-01
We present two simple, one-dimensional, stochastic models that lead to a qualitative understanding of very complex systems from biology, nanoscience and social sciences. The first model explains the complicated dynamics of microtubules, stochastic cellular highways. Using the theory of random walks in one dimension, we find analytical expressions for certain physical quantities, such as the time dependence of the length of the microtubules, and diffusion coefficients. The second one is a stochastic adsorption model with applications in surface deposition, epidemics and voter systems. We introduce the ‘empty interval method’ and show sample calculations for the time-dependent particle density. These models can serve as an introduction to the field of non-equilibrium statistical physics, and can also be used as a pedagogical tool to exemplify standard statistical physics concepts, such as random walks or the kinetic approach of the master equation. (paper)
Transition Manifolds of Complex Metastable Systems
Bittracher, Andreas; Koltai, Péter; Klus, Stefan; Banisch, Ralf; Dellnitz, Michael; Schütte, Christof
2018-04-01
We consider complex dynamical systems showing metastable behavior, but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics.
Dependency visualization for complex system understanding
Energy Technology Data Exchange (ETDEWEB)
Smart, J. Allison Cory [Univ. of California, Davis, CA (United States)
1994-09-01
With the volume of software in production use dramatically increasing, the importance of software maintenance has become strikingly apparent. Techniques now sought and developed for reverse engineering and design extraction and recovery. At present, numerous commercial products and research tools exist which are capable of visualizing a variety of programming languages and software constructs. The list of new tools and services continues to grow rapidly. Although the scope of the existing commercial and academic product set is quite broad, these tools still share a common underlying problem. The ability of each tool to visually organize object representations is increasingly impaired as the number of components and component dependencies within systems increases. Regardless of how objects are defined, complex ``spaghetti`` networks result in nearly all large system cases. While this problem is immediately apparent in modem systems analysis involving large software implementations, it is not new. As will be discussed in Chapter 2, related problems involving the theory of graphs were identified long ago. This important theoretical foundation provides a useful vehicle for representing and analyzing complex system structures. While the utility of directed graph based concepts in software tool design has been demonstrated in literature, these tools still lack the capabilities necessary for large system comprehension. This foundation must therefore be expanded with new organizational and visualization constructs necessary to meet this challenge. This dissertation addresses this need by constructing a conceptual model and a set of methods for interactively exploring, organizing, and understanding the structure of complex software systems.
Application of Complex Adaptive Systems in Portfolio Management
Su, Zheyuan
2017-01-01
Simulation-based methods are becoming a promising research tool in financial markets. A general Complex Adaptive System can be tailored to different application scenarios. Based on the current research, we built two models that would benefit portfolio management by utilizing Complex Adaptive Systems (CAS) in Agent-based Modeling (ABM) approach.…
Dynamics of complex quantum systems
Akulin, Vladimir M
2014-01-01
This book gathers together a range of similar problems that can be encountered in different fields of modern quantum physics and that have common features with regard to multilevel quantum systems. The main motivation was to examine from a uniform standpoint various models and approaches that have been developed in atomic, molecular, condensed matter, chemical, laser and nuclear physics in various contexts. The book should help senior-level undergraduate, graduate students and researchers putting particular problems in these fields into a broader scientific context and thereby taking advantage of well-established techniques used in adjacent fields. This second edition has been expanded to include substantial new material (e.g. new sections on Dynamic Localization and on Euclidean Random Matrices and new chapters on Entanglement, Open Quantum Systems, and Coherence Protection). It is based on the author’s lectures at the Moscow Institute of Physics and Technology, at the CNRS Aimé Cotton Laboratory, and on ...
Metasynthetic computing and engineering of complex systems
Cao, Longbing
2015-01-01
Provides a comprehensive overview and introduction to the concepts, methodologies, analysis, design and applications of metasynthetic computing and engineering. The author: Presents an overview of complex systems, especially open complex giant systems such as the Internet, complex behavioural and social problems, and actionable knowledge discovery and delivery in the big data era. Discusses ubiquitous intelligence in complex systems, including human intelligence, domain intelligence, social intelligence, network intelligence, data intelligence and machine intelligence, and their synergy thro
Propagating wave correlations in complex systems
International Nuclear Information System (INIS)
Creagh, Stephen C; Gradoni, Gabriele; Hartmann, Timo; Tanner, Gregor
2017-01-01
We describe a novel approach for computing wave correlation functions inside finite spatial domains driven by complex and statistical sources. By exploiting semiclassical approximations, we provide explicit algorithms to calculate the local mean of these correlation functions in terms of the underlying classical dynamics. By defining appropriate ensemble averages, we show that fluctuations about the mean can be characterised in terms of classical correlations. We give in particular an explicit expression relating fluctuations of diagonal contributions to those of the full wave correlation function. The methods have a wide range of applications both in quantum mechanics and for classical wave problems such as in vibro-acoustics and electromagnetism. We apply the methods here to simple quantum systems, so-called quantum maps, which model the behaviour of generic problems on Poincaré sections. Although low-dimensional, these models exhibit a chaotic classical limit and share common characteristics with wave propagation in complex structures. (paper)
Directory of Open Access Journals (Sweden)
Weiwei Mo
2018-06-01
Full Text Available A modeling framework was conceptualized for capturing the complexities in resilience and sustainability associated with integration of centralized and decentralized water and energy systems under future demographic, climate, and technology scenarios. This framework integrates survey instruments for characterizing individual preferences (utility functions related to decentralization of water and energy infrastructure systems. It also includes a spatial agent-based model to develop spatially explicit adoption trajectories and patterns in accordance with utility functions and characteristics of the major metropolitan case study locations as well as a system dynamics model that considers interactions among infrastructure systems, characterizes measures of resilience and sustainability, and feeds these back to the agent-based model. A cross-scale spatial optimization model for understanding and characterizing the possible best case outcomes and for informing the design of policies and incentive/disincentive programs is also included. This framework is able to provide a robust capacity for considering the ways in which future development of energy and water resources can be assessed.
Relaxation and Diffusion in Complex Systems
Ngai, K L
2011-01-01
Relaxation and Diffusion in Complex Systems comprehensively presents a variety of experimental evidences of universal relaxation and diffusion properties in complex materials and systems. The materials discussed include liquids, glasses, colloids, polymers, rubbers, plastic crystals and aqueous mixtures, as well as carbohydrates, biomolecules, bioprotectants and pharmaceuticals. Due to the abundance of experimental data, emphasis is placed on glass-formers and the glass transition problem, a still unsolved problem in condensed matter physics and chemistry. The evidence for universal properties of relaxation and diffusion dynamics suggests that a fundamental physical law is at work. The origin of the universal properties is traced to the many-body effects of the interaction, rigorous theory of which does not exist at the present time. However, using solutions of simplified models as guides, key quantities have been identified and predictions of the universal properties generated. These predictions from Ngai’...
Symmetry analysis in parametrisation of complex systems
International Nuclear Information System (INIS)
Sikora, W; Malinowski, J
2010-01-01
The symmetry analysis method based on the theory of group representations is used for description of complex systems and their behavior in this work. The first trial of using the symmetry analysis in modeling of behavior of complex social system is presented. The evacuation of large building scenarios are discussed as transition from chaotic to ordered states, described as movements of individuals according to fields of displacements, calculated correspondingly to given scenario. The symmetry of the evacuation space is taken into account in calculation of displacements field - the displacements related to every point of this space are presented in the coordinate frame in the best way adapted to given symmetry space group, which is the set of basic vectors of irreducible representation of given symmetry group. The results got with using the symmetry consideration are compared with corresponding results calculated under assumption of shortest way to exits (Voronoi assumption).
Symmetry analysis in parametrisation of complex systems
Energy Technology Data Exchange (ETDEWEB)
Sikora, W; Malinowski, J, E-mail: sikora@novell.ftj.agh.edu.p [Faculty of Physics and Applied Computer Science, AGH - University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow (Poland)
2010-03-01
The symmetry analysis method based on the theory of group representations is used for description of complex systems and their behavior in this work. The first trial of using the symmetry analysis in modeling of behavior of complex social system is presented. The evacuation of large building scenarios are discussed as transition from chaotic to ordered states, described as movements of individuals according to fields of displacements, calculated correspondingly to given scenario. The symmetry of the evacuation space is taken into account in calculation of displacements field - the displacements related to every point of this space are presented in the coordinate frame in the best way adapted to given symmetry space group, which is the set of basic vectors of irreducible representation of given symmetry group. The results got with using the symmetry consideration are compared with corresponding results calculated under assumption of shortest way to exits (Voronoi assumption).
SUPERCOMPUTER SIMULATION OF CRITICAL PHENOMENA IN COMPLEX SOCIAL SYSTEMS
Directory of Open Access Journals (Sweden)
Petrus M.A. Sloot
2014-09-01
Full Text Available The paper describes a problem of computer simulation of critical phenomena in complex social systems on a petascale computing systems in frames of complex networks approach. The three-layer system of nested models of complex networks is proposed including aggregated analytical model to identify critical phenomena, detailed model of individualized network dynamics and model to adjust a topological structure of a complex network. The scalable parallel algorithm covering all layers of complex networks simulation is proposed. Performance of the algorithm is studied on different supercomputing systems. The issues of software and information infrastructure of complex networks simulation are discussed including organization of distributed calculations, crawling the data in social networks and results visualization. The applications of developed methods and technologies are considered including simulation of criminal networks disruption, fast rumors spreading in social networks, evolution of financial networks and epidemics spreading.
Simulating Complex Window Systems using BSDF Data
Energy Technology Data Exchange (ETDEWEB)
Konstantoglou, Maria; Jonsson, Jacob; Lee, Eleanor
2009-06-22
Nowadays, virtual models are commonly used to evaluate the performance of conventional window systems. Complex fenestration systems can be difficult to simulate accurately not only because of their geometry but also because of their optical properties that scatter light in an unpredictable manner. Bi-directional Scattering Distribution Functions (BSDF) have recently been developed based on a mixture of measurements and modelling to characterize the optics of such systems. This paper describes the workflow needed to create then use these BSDF datasets in the Radiance lighting simulation software. Limited comparisons are made between visualizations produced using the standard ray-tracing method, the BSDF method, and that taken in a full-scale outdoor mockup.
Quantum mechanics in complex systems
Hoehn, Ross Douglas
This document should be considered in its separation; there are three distinct topics contained within and three distinct chapters within the body of works. In a similar fashion, this abstract should be considered in three parts. Firstly, we explored the existence of multiply-charged atomic ions by having developed a new set of dimensional scaling equations as well as a series of relativistic augmentations to the standard dimensional scaling procedure and to the self-consistent field calculations. Secondly, we propose a novel method of predicting drug efficacy in hopes to facilitate the discovery of new small molecule therapeutics by modeling the agonist-protein system as being similar to the process of Inelastic Electron Tunneling Spectroscopy. Finally, we facilitate the instruction in basic quantum mechanical topics through the use of quantum games; this method of approach allows for the generation of exercises with the intent of conveying the fundamental concepts within a first year quantum mechanics classroom. Furthermore, no to be mentioned within the body of the text, yet presented in appendix form, certain works modeling the proliferation of cells types within the confines of man-made lattices for the purpose of facilitating artificial vascular transplants. In Chapter 2, we present a theoretical framework which describes multiply-charged atomic ions, their stability within super-intense laser fields, also lay corrections to the systems due to relativistic effects. Dimensional scaling calculations with relativistic corrections for systems: H, H-, H 2-, He, He-, He2-, He3- within super-intense laser fields were completed. Also completed were three-dimensional self consistent field calculations to verify the dimensionally scaled quantities. With the aforementioned methods the system's ability to stably bind 'additional' electrons through the development of multiple isolated regions of high potential energy leading to nodes of high electron density is shown
Reduction of Subjective and Objective System Complexity
Watson, Michael D.
2015-01-01
Occam's razor is often used in science to define the minimum criteria to establish a physical or philosophical idea or relationship. Albert Einstein is attributed the saying "everything should be made as simple as possible, but not simpler". These heuristic ideas are based on a belief that there is a minimum state or set of states for a given system or phenomena. In looking at system complexity, these heuristics point us to an idea that complexity can be reduced to a minimum. How then, do we approach a reduction in complexity? Complexity has been described as a subjective concept and an objective measure of a system. Subjective complexity is based on human cognitive comprehension of the functions and inter relationships of a system. Subjective complexity is defined by the ability to fully comprehend the system. Simplifying complexity, in a subjective sense, is thus gaining a deeper understanding of the system. As Apple's Jonathon Ive has stated," It's not just minimalism or the absence of clutter. It involves digging through the depth of complexity. To be truly simple, you have to go really deep". Simplicity is not the absence of complexity but a deeper understanding of complexity. Subjective complexity, based on this human comprehension, cannot then be discerned from the sociological concept of ignorance. The inability to comprehend a system can be either a lack of knowledge, an inability to understand the intricacies of a system, or both. Reduction in this sense is based purely on a cognitive ability to understand the system and no system then may be truly complex. From this view, education and experience seem to be the keys to reduction or eliminating complexity. Objective complexity, is the measure of the systems functions and interrelationships which exist independent of human comprehension. Jonathon Ive's statement does not say that complexity is removed, only that the complexity is understood. From this standpoint, reduction of complexity can be approached
Automated design of complex dynamic systems.
Directory of Open Access Journals (Sweden)
Michiel Hermans
Full Text Available Several fields of study are concerned with uniting the concept of computation with that of the design of physical systems. For example, a recent trend in robotics is to design robots in such a way that they require a minimal control effort. Another example is found in the domain of photonics, where recent efforts try to benefit directly from the complex nonlinear dynamics to achieve more efficient signal processing. The underlying goal of these and similar research efforts is to internalize a large part of the necessary computations within the physical system itself by exploiting its inherent non-linear dynamics. This, however, often requires the optimization of large numbers of system parameters, related to both the system's structure as well as its material properties. In addition, many of these parameters are subject to fabrication variability or to variations through time. In this paper we apply a machine learning algorithm to optimize physical dynamic systems. We show that such algorithms, which are normally applied on abstract computational entities, can be extended to the field of differential equations and used to optimize an associated set of parameters which determine their behavior. We show that machine learning training methodologies are highly useful in designing robust systems, and we provide a set of both simple and complex examples using models of physical dynamical systems. Interestingly, the derived optimization method is intimately related to direct collocation a method known in the field of optimal control. Our work suggests that the application domains of both machine learning and optimal control have a largely unexplored overlapping area which envelopes a novel design methodology of smart and highly complex physical systems.
ter Maat, G. W.; Pastore, Z.; Michels, A.; Church, N. S.; McEnroe, S. A.; Larsen, R. B.
2017-12-01
The Reinfjord Ultramafic Complex is part of the 5000 km2 Seiland Igneous Province (SIP) in Northern Norway. The SIP is argued to be the deep-seated conduit system of a Large Igneous Province and was emplaced at 25-35 km depth in less than 10 Ma (570-560 Ma). The Reinfjord Ultramafic Complex was emplaced during three major successive events at 22-28km depth at pressures of 6-8kb, with associated temperatures 1450-1500°C (Roberts, 2006). The rocks are divided into three formations: the central series (CS) consisting of mainly dunites, upper layered series (ULS) consisting of dunites and wehrlites, a lower layered series (LLS) containing most pyroxene-rich rocks and a marginal zone (MZ) which formed where the ultramafic melts intruded the gabbro-norite and metasedimentary gneisses. Deep exposures such as the Reinfjord Ultramafic Complex are rare, therefore this study gives a unique insight in the rock magnetic properties of a deep ultramafic system. Localised serpentinised zones provide an opportunity to observe the effect of this alteration process on the magnetic properties of deep-seated rocks. Here, we present the results from the rock magnetic properties, a paleomagnetic study and combined potential-fields modeling. The study of the rock magnetic properties provides insight in primary processes associated with the intrusion, and later serpentinization. The paleomagnetic data yields two distinct directions. One direction corresponds to a Laurentia pole at ≈ 532 Ma while the other, though younger, is not yet fully understood. Rock magnetic properties were measured on > 700 specimens and used to constrain the modelling of gravity, high-resolution helicopter, and ground magnetic data. The intrusion is modelled as a cylindrically shaped complex with a dunite core surrounded by wehrlite and gabbro. The ultramafic part of the complex dips to the NE and its maximum vertical extent is modelled to 1400m. Furthermore, modelling allows estimation of relative volumes of
Encyclopedia of Complexity and Systems Science
Meyers, Robert A
2009-01-01
Encyclopedia of Complexity and Systems Science provides an authoritative single source for understanding and applying the concepts of complexity theory together with the tools and measures for analyzing complex systems in all fields of science and engineering. The science and tools of complexity and systems science include theories of self-organization, complex systems, synergetics, dynamical systems, turbulence, catastrophes, instabilities, nonlinearity, stochastic processes, chaos, neural networks, cellular automata, adaptive systems, and genetic algorithms. Examples of near-term problems and major unknowns that can be approached through complexity and systems science include: The structure, history and future of the universe; the biological basis of consciousness; the integration of genomics, proteomics and bioinformatics as systems biology; human longevity limits; the limits of computing; sustainability of life on earth; predictability, dynamics and extent of earthquakes, hurricanes, tsunamis, and other n...
International Nuclear Information System (INIS)
Derr, E.D.; Harper, J.R.; Zygmunt, S.J.; Taggart, D.P.; Betts, S.E.
1997-01-01
Los Alamos National Laboratory has implemented mobile and portable characterization and repackaging systems to characterize TRU waste in storage for ultimate shipment and disposal at the Waste Isolation Pilot Plant (WIPP) near Carlsbad, NM. These mobile systems are being used to characterize and repackage waste to meet the full requirements of the WIPP Waste Acceptance Criteria (WAC) and the WIPP Characterization Quality Assurance Program Plan (QAPP). Mobile and portable characterization and repackaging systems are being used to supplement the capabilities and throughputs of existing facilities. Utilization of mobile systems is a key factor that is enabling LANL to: (1) reduce its TRU waste work-off schedule from 36 years to 8.5 years; (2) eliminate the need to construct a $70M+ TRU waste characterization facility; (3) have waste certified for shipment to WIPP when WIPP opens; (4) continue to ship TRU waste to WIPP at the rate of 5000 drums per year; and, (5) reduce overall costs by more than $200M. Aggressive implementation of mobile and portable systems throughout the DOE complex through a centralized-distributed services model will result in similar advantages complex-wide
International Nuclear Information System (INIS)
Derr, E.D.; Harper, J.R.; Zygmunt, S.J.; Taggart, D.P.; Betts, S.E.
1997-01-01
Los Alamos National Laboratory (LANL) has implemented mobile and portable characterization and repackaging systems to characterize transuranic (TRU) waste in storage for ultimate shipment and disposal at the Waste Isolation Pilot Plant (WIPP) near Carlsbad, NM. These mobile systems are being used to characterize and repackage waste to meet the full requirements of the WIPP Waste Acceptance Criteria (WAC) and the WIPP Characterization Quality Assurance Program Plan (QAPP). Mobile and portable characterization and repackaging systems are being used to supplement the capabilities and throughputs of existing facilities. Utilization of mobile systems is a key factor that is enabling LANL to (1) reduce its TRU waste work-off schedule from 36 years to 8.5 years; (2) eliminate the need to construct a $70M+ TRU waste characterization facility; (3) have waste certified for shipment to WIPP when WIPP opens; (4) continue to ship TRU waste to WIPP at the rate of 5000 drums per year; and (5) reduce overall costs by more than $200M. Aggressive implementation of mobile and portable systems throughout the Department of Energy complex through a centralized-distributed services model will result in similar advantages complex-wide
Energy Technology Data Exchange (ETDEWEB)
Kevrekidis, Ioannis G. [Princeton Univ., NJ (United States)
2017-02-01
The work explored the linking of modern developing machine learning techniques (manifold learning and in particular diffusion maps) with traditional PDE modeling/discretization/scientific computation techniques via the equation-free methodology developed by the PI. The result (in addition to several PhD degrees, two of them by CSGF Fellows) was a sequence of strong developments - in part on the algorithmic side, linking data mining with scientific computing, and in part on applications, ranging from PDE discretizations to molecular dynamics and complex network dynamics.
European Conference on Complex Systems 2012
Kirkilionis, Markus; Nicolis, Gregoire
2013-01-01
The European Conference on Complex Systems, held under the patronage of the Complex Systems Society, is an annual event that has become the leading European conference devoted to complexity science. ECCS'12, its ninth edition, took place in Brussels, during the first week of September 2012. It gathered about 650 scholars representing a wide range of topics relating to complex systems research, with emphasis on interdisciplinary approaches. More specifically, the following tracks were covered: 1. Foundations of Complex Systems 2. Complexity, Information and Computation 3. Prediction, Policy and Planning, Environment 4. Biological Complexity 5. Interacting Populations, Collective Behavior 6. Social Systems, Economics and Finance This book contains a selection of the contributions presented at the conference and its satellite meetings. Its contents reflect the extent, diversity and richness of research areas in the field, both fundamental and applied.
Systemic Resilience of Complex Urban Systems
Directory of Open Access Journals (Sweden)
Serge Salat
2012-07-01
Full Text Available Two key paradigms emerge out of the variety of urban forms: certain cities resemble trees, others leaves. The structural difference between a tree and a leaf is huge: one is open, the other closed. Trees are entirely disconnected on a given scale: even if two twigs are spatially close, if they do not belong to the same branch, to go from one to the other implies moving down and then up all the hierarchy of branches. Leaves on the contrary are entirely connected on intermediary scales. The veins of a leaf are disconnected on the two larger scales but entirely connected on the two or three following intermediary scales before presenting tiny tree-like structures on the finest capillary scales. Deltas are leaves not trees. Neither galaxies nor whirlpools are trees. We will see in this paper that historical cities, like leaves, deltas, galaxies, lungs, brains and vein systems are all fractal structures, multiply connected and complex on all scales. These structures display the same degree of complexity and connectivity, regardless of the magnification scale on which we observe them. We say that these structures are scale free. Mathematical fractal forms are often generated recursively by applying again and again the same generator to an initiator. The iteration creates an arborescence. But scale free structure is not synonymous with a recursive tree-like structure. The fractal structure of the leaf is much more complex than that of the tree by its multiconnectivity on three or more intermediary levels. In contrast, trees in the virgin forest, even when they seem to be entangled, horizontal, and rhizomic, have branches that are not interconnected to form a lattice. As we will see, the history of urban planning has evolved from leaf-like to tree-like patterns, with a consequent loss of efficiency and resilience. Indeed, in a closed foliar path structure, the formation of cycles enables internal complexification and flow fluctuations due to the
Automated Diagnosis and Control of Complex Systems
Kurien, James; Plaunt, Christian; Cannon, Howard; Shirley, Mark; Taylor, Will; Nayak, P.; Hudson, Benoit; Bachmann, Andrew; Brownston, Lee; Hayden, Sandra;
2007-01-01
Livingstone2 is a reusable, artificial intelligence (AI) software system designed to assist spacecraft, life support systems, chemical plants, or other complex systems by operating with minimal human supervision, even in the face of hardware failures or unexpected events. The software diagnoses the current state of the spacecraft or other system, and recommends commands or repair actions that will allow the system to continue operation. Livingstone2 is an enhancement of the Livingstone diagnosis system that was flight-tested onboard the Deep Space One spacecraft in 1999. This version tracks multiple diagnostic hypotheses, rather than just a single hypothesis as in the previous version. It is also able to revise diagnostic decisions made in the past when additional observations become available. In such cases, Livingstone might arrive at an incorrect hypothesis. Re-architecting and re-implementing the system in C++ has increased performance. Usability has been improved by creating a set of development tools that is closely integrated with the Livingstone2 engine. In addition to the core diagnosis engine, Livingstone2 includes a compiler that translates diagnostic models written in a Java-like language into Livingstone2's language, and a broad set of graphical tools for model development.
Computer control system synthesis for nuclear power plants through simplification and partitioning of the complex system model into a set of simple subsystems
International Nuclear Information System (INIS)
Zobor, E.
1978-12-01
The approach chosen is based on the hierarchical control systems theory, however, the fundamentals of other approaches such as the systems simplification and systems partitioning are briefly summarized for introducing the problems associated with the control of large scale systems. The concept of a hierarchical control system acting in broad variety of operating conditions is developed and some practical extensions to the hierarchical control system approach e.g. subsystems measured and controlled with different rates, control of the partial state vector, coordination for autoregressive models etc. are given. Throughout the work the WWR-SM research reactor of the Institute has been taken as a guiding example and simple methods for the identification of the model parameters from a reactor start-up are discussed. Using the PROHYS digital simulation program elaborated in the course of the present research, detailed simulation studies were carried out for investigating the performance of a control system based on the concept and algorithms developed. In order to give a real application evidence, a short description is finally given about the closed-loop computer control system installed - in the framework of a project supported by the Hungarian State Office for Technical Development - at the WWR-SM research reactor where the results obtained in the present IAEA Research Contract were successfully applied and furnished the expected high performance
Simulating Complex Systems by Cellular Automata
Kroc, Jiri; Hoekstra, Alfons G
2010-01-01
Deeply rooted in fundamental research in Mathematics and Computer Science, Cellular Automata (CA) are recognized as an intuitive modeling paradigm for Complex Systems. Already very basic CA, with extremely simple micro dynamics such as the Game of Life, show an almost endless display of complex emergent behavior. Conversely, CA can also be designed to produce a desired emergent behavior, using either theoretical methodologies or evolutionary techniques. Meanwhile, beyond the original realm of applications - Physics, Computer Science, and Mathematics – CA have also become work horses in very different disciplines such as epidemiology, immunology, sociology, and finance. In this context of fast and impressive progress, spurred further by the enormous attraction these topics have on students, this book emerges as a welcome overview of the field for its practitioners, as well as a good starting point for detailed study on the graduate and post-graduate level. The book contains three parts, two major parts on th...
Abstraction in artificial intelligence and complex systems
Saitta, Lorenza
2013-01-01
Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences. After discussing the characterizing properties of abstraction, a formal model, the K
Synchronization and emergence in complex systems
Indian Academy of Sciences (India)
... complex systems. Fatihcan M Atay. Synchronization, Coupled Systems and Networks Volume 77 Issue 5 November 2011 pp 855-863 ... We show how novel behaviour can emerge in complex systems at the global level through synchronization of the activities of their constituent units. Two mechanisms are suggested for ...
Meyer, Sven Erik; Passchier, Cees; Abu-Alam, Tamer; Stüwe, Kurt
2014-05-01
Metamorphic core complexes usually develop as extensional features during continental crustal thinning, such as the Basin and Range and the Aegean Terrane. The Najd fault system in Saudi Arabia is a 2000 km-long and 400 km-wide complex network of crustal-scale strike-slip shear zones in a Neoproterozoic collision zone. Locally, the anastomosing shear zones lead to exhumation of lower crustal segments and represent a new kinematic model for the development of core complexes. We report on two such structures: the Qazaz complex in Saudi Arabia and the Hafafit complex in Egypt. The 15 km-wide Qazaz complex is a triangular dome of gently dipping mylonitic foliations within the 140 km-long sinistral strike-slip Qazaz mylonite zone. The gneissic dome consists of high-grade rocks, surrounded by low-grade metasediments and metavolcanics. The main SE-trending strike-slip Qazaz shear zone splits southwards into two branches around the gneiss dome: the western branch is continuous with the shallow dipping mylonites of the dome core, without overprinting, and changes by more than 90 degrees from a NS-trending strike-slip zone to an EW-trending 40 degree south-dipping detachment that bounds the gneiss dome to the south. The eastern SE-trending sinistral strike-slip shear zone branch is slightly younger and transects the central dome fabrics. The gneiss dome appears to have formed along a jog in the strike-slip shear zone during 40 km of horizontal strike-slip motion, which caused local exhumation of lower crustal rocks by 25 km along the detachment. The eastern shear zone branch formed later during exhumation, transacted the gneiss dome and offset the two parts by another 70 km. The Hafafit core complex in Egypt is of similar shape and size to the Qazaz structure, but forms the northern termination of a sinistral strike-slip zone that is at least 100 km in length. This zone may continue into Saudi Arabia as the Ajjaj shear zone for another 100 km. The NW trending strike slip
Supervisory control for a complex robotic system
International Nuclear Information System (INIS)
Miller, D.J.
1988-01-01
The Robotic Radiation Survey and Analysis System investigates the use of advanced robotic technology for performing remote radiation surveys on nuclear waste shipping casks. Robotic systems have the potential for reducing personnel exposure to radiation and providing fast reliable throughput at future repository sites. A primary technology issue is the integrated control of distributed specialized hardware through a modular supervisory software system. Automated programming of robot trajectories based upon mathematical models of the cask and robot coupled with sensory feedback enables flexible operation of a commercial gantry robot with the reliability needed to perform autonomous operations in a hazardous environment. Complexity is managed using structured software engineering techniques resulting in the generation of reusable command primitives which contribute to a software parts catalog for a generalized robot programming language
Statistical Physics of Complex Substitutive Systems
Jin, Qing
Diffusion processes are central to human interactions. Despite extensive studies that span multiple disciplines, our knowledge is limited to spreading processes in non-substitutive systems. Yet, a considerable number of ideas, products, and behaviors spread by substitution; to adopt a new one, agents must give up an existing one. This captures the spread of scientific constructs--forcing scientists to choose, for example, a deterministic or probabilistic worldview, as well as the adoption of durable items, such as mobile phones, cars, or homes. In this dissertation, I develop a statistical physics framework to describe, quantify, and understand substitutive systems. By empirically exploring three collected high-resolution datasets pertaining to such systems, I build a mechanistic model describing substitutions, which not only analytically predicts the universal macroscopic phenomenon discovered in the collected datasets, but also accurately captures the trajectories of individual items in a complex substitutive system, demonstrating a high degree of regularity and universality in substitutive systems. I also discuss the origins and insights of the parameters in the substitution model and possible generalization form of the mathematical framework. The systematical study of substitutive systems presented in this dissertation could potentially guide the understanding and prediction of all spreading phenomena driven by substitutions, from electric cars to scientific paradigms, and from renewable energy to new healthy habits.
Large-scale Complex IT Systems
Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard
2011-01-01
This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that identifies the major challen...
Large-scale complex IT systems
Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard
2012-01-01
12 pages, 2 figures This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that ident...
Directory of Open Access Journals (Sweden)
Michael Graf
2013-07-01
Full Text Available The spectral wave model SWAN (Simulating Waves Nearshore was applied to Lake Zurich, a narrow pre-Alpine lake in Switzerland. The aim of the study is to investigate whether the model system consisting of SWAN and the numerical weather prediction model COSMO-2 is a suitable tool for wave forecasts for the pre-Alpine Lake Zurich. SWAN is able to simulate short-crested wind-generated surface waves. The model was forced with a time varying wind field taken from COSMO-2 with hourly outputs. Model simulations were compared with measured wave data at one near-shore site during a frontal passage associated with strong on-shore winds. The overall course of the measured wave height is well captured in the SWAN simulation: the wave amplitude significantly increases during the frontal passage followed by a transient drop in amplitude. The wave pattern on Lake Zurich is quite complex. It strongly depends on the inherent variability of the wind field and on the external forcing due to the surrounding complex topography. The influence of the temporal wind resolution is further studied with two sensitivity experiments. The first one considers a low-pass filtered wind field, based on a 2-h running mean of COSMO-2 output, and the second experiment uses simple synthetic gusts, which are implemented into the SWAN model and take into account short-term fluctuations of wind speed at 1-sec resolution. The wave field significantly differs for the 1-h and 2-h simulations, but is only negligibly affected by the gusts.
Extending Life Concepts to Complex Systems
Directory of Open Access Journals (Sweden)
Jean Le Fur
2013-01-01
Full Text Available There is still no consensus definition of complex systems. This article explores, as a heuristic approach, the possibility of using notions associated with life as transversal concepts for defining complex systems. This approach is developed within a general classification of systems, with complex systems considered as a general ‘living things’ category and living organisms as a specialised class within this category. Concepts associated with life are first explored in the context of complex systems: birth, death and lifetime, adaptation, ontogeny and growth, reproduction. Thereafter, a refutation approach is used to test the proposed classification against a set of diverse systems, including a reference case, edge cases and immaterial complex systems. The summary of this analysis is then used to generate a definition of complex systems, based on the proposal, and within the background of cybernetics, complex adaptive systems and biology. Using notions such as ‘birth’ or ‘lifespan’ as transversal concepts may be of heuristic value for the generic characterization of complex systems, opening up new lines of research for improving their definition.
Warscher, M; Strasser, U; Kraller, G; Marke, T; Franz, H; Kunstmann, H
2013-05-01
[1] Runoff generation in Alpine regions is typically affected by snow processes. Snow accumulation, storage, redistribution, and ablation control the availability of water. In this study, several robust parameterizations describing snow processes in Alpine environments were implemented in a fully distributed, physically based hydrological model. Snow cover development is simulated using different methods from a simple temperature index approach, followed by an energy balance scheme, to additionally accounting for gravitational and wind-driven lateral snow redistribution. Test site for the study is the Berchtesgaden National Park (Bavarian Alps, Germany) which is characterized by extreme topography and climate conditions. The performance of the model system in reproducing snow cover dynamics and resulting discharge generation is analyzed and validated via measurements of snow water equivalent and snow depth, satellite-based remote sensing data, and runoff gauge data. Model efficiency (the Nash-Sutcliffe coefficient) for simulated runoff increases from 0.57 to 0.68 in a high Alpine headwater catchment and from 0.62 to 0.64 in total with increasing snow model complexity. In particular, the results show that the introduction of the energy balance scheme reproduces daily fluctuations in the snowmelt rates that trace down to the channel stream. These daily cycles measured in snowmelt and resulting runoff rates could not be reproduced by using the temperature index approach. In addition, accounting for lateral snow transport changes the seasonal distribution of modeled snowmelt amounts, which leads to a higher accuracy in modeling runoff characteristics.
Osteosarcoma models : understanding complex disease
Mohseny, Alexander Behzad
2012-01-01
A mesenchymal stem cell (MSC) based osteosarcoma model was established. The model provided evidence for a MSC origin of osteosarcoma. Normal MSCs transformed spontaneously to osteosarcoma-like cells which was always accompanied by genomic instability and loss of the Cdkn2a locus. Accordingly loss of
Lüder, Arndt; Gerhard, Detlef
2017-01-01
This book discusses challenges and solutions for the required information processing and management within the context of multi-disciplinary engineering of production systems. The authors consider methods, architectures, and technologies applicable in use cases according to the viewpoints of product engineering and production system engineering, and regarding the triangle of (1) product to be produced by a (2) production process executed on (3) a production system resource. With this book industrial production systems engineering researchers will get a better understanding of the challenges and requirements of multi-disciplinary engineering that will guide them in future research and development activities. Engineers and managers from engineering domains will be able to get a better understanding of the benefits and limitations of applicable methods, architectures, and technologies for selected use cases. IT researchers will be enabled to identify research issues related to the development of new methods, arc...
Khan, Sobia; Vandermorris, Ashley; Shepherd, John; Begun, James W; Lanham, Holly Jordan; Uhl-Bien, Mary; Berta, Whitney
2018-03-21
Complexity thinking is increasingly being embraced in healthcare, which is often described as a complex adaptive system (CAS). Applying CAS to healthcare as an explanatory model for understanding the nature of the system, and to stimulate changes and transformations within the system, is valuable. A seminar series on systems and complexity thinking hosted at the University of Toronto in 2016 offered a number of insights on applications of CAS perspectives to healthcare that we explore here. We synthesized topics from this series into a set of six insights on how complexity thinking fosters a deeper understanding of accepted ideas in healthcare, applications of CAS to actors within the system, and paradoxes in applications of complexity thinking that may require further debate: 1) a complexity lens helps us better understand the nebulous term "context"; 2) concepts of CAS may be applied differently when actors are cognizant of the system in which they operate; 3) actor responses to uncertainty within a CAS is a mechanism for emergent and intentional adaptation; 4) acknowledging complexity supports patient-centred intersectional approaches to patient care; 5) complexity perspectives can support ways that leaders manage change (and transformation) in healthcare; and 6) complexity demands different ways of implementing ideas and assessing the system. To enhance our exploration of key insights, we augmented the knowledge gleaned from the series with key articles on complexity in the literature. Ultimately, complexity thinking acknowledges the "messiness" that we seek to control in healthcare and encourages us to embrace it. This means seeing challenges as opportunities for adaptation, stimulating innovative solutions to ensure positive adaptation, leveraging the social system to enable ideas to emerge and spread across the system, and even more important, acknowledging that these adaptive actions are part of system behaviour just as much as periods of stability are. By
Energy Technology Data Exchange (ETDEWEB)
Belmonte, Fabien, E-mail: fabien.belmonte@transport.alstom.co [Alstom Transport, 48 rue Albert Dhalenne, 93482 Saint-Ouen cedex (France); Schoen, Walter [Universite de Technologie de Compiegne, Laboratoire Heudiasyc, Centre de Recherches de Royallieu, BP20529, 60205 Compiegne cedex (France); Heurley, Laurent [Universite de Picardie Jules Verne, Equipe Cognition, Langage, Emotion et Acquisition (CLEA), EA 4296, UFR de Philosophie, Sciences Humaines et Sociales, Chemin du Thil, 80025 Amiens, Cedex 1 (France); Capel, Robert [Alstom Transport, 48 rue Albert Dhalenne, 93482 Saint-Ouen cedex (France)
2011-02-15
This paper presents an application of functional resonance accident models (FRAM) for the safety analysis of complex socio-technological systems, i.e. systems which include not only technological, but also human and organizational components. The supervision of certain industrial domains provides a good example of such systems, because although more and more actions for piloting installations are now automatized, there always remains a decision level (at least in the management of degraded modes) involving human behavior and organizations. The field of application of the study presented here is railway traffic supervision, using modern automatic train supervision (ATS) systems. Examples taken from railway traffic supervision illustrate the principal advantage of FRAM in comparison to classical safety analysis models, i.e. their ability to take into account technical as well as human and organizational aspects within a single model, thus allowing a true multidisciplinary cooperation between specialists from the different domains involved. A FRAM analysis is used to interpret experimental results obtained from a real ATS system linked to a railway simulator that places operators (experimental subjects) in simulated situations involving incidents. The first results show a significant dispersion in performances among different operators when detecting incidents. Some subsequent work in progress aims to make these 'performance conditions' more homogeneous, mainly by ergonomic modifications. It is clear that the current human-machine interface (HMI) in ATS systems (a legacy of past technologies that used LED displays) has reached its limits and needs to be improved, for example, by highlighting the most pertinent information for a given situation (and, conversely, by removing irrelevant information likely to distract operators).
International Nuclear Information System (INIS)
Belmonte, Fabien; Schoen, Walter; Heurley, Laurent; Capel, Robert
2011-01-01
This paper presents an application of functional resonance accident models (FRAM) for the safety analysis of complex socio-technological systems, i.e. systems which include not only technological, but also human and organizational components. The supervision of certain industrial domains provides a good example of such systems, because although more and more actions for piloting installations are now automatized, there always remains a decision level (at least in the management of degraded modes) involving human behavior and organizations. The field of application of the study presented here is railway traffic supervision, using modern automatic train supervision (ATS) systems. Examples taken from railway traffic supervision illustrate the principal advantage of FRAM in comparison to classical safety analysis models, i.e. their ability to take into account technical as well as human and organizational aspects within a single model, thus allowing a true multidisciplinary cooperation between specialists from the different domains involved. A FRAM analysis is used to interpret experimental results obtained from a real ATS system linked to a railway simulator that places operators (experimental subjects) in simulated situations involving incidents. The first results show a significant dispersion in performances among different operators when detecting incidents. Some subsequent work in progress aims to make these 'performance conditions' more homogeneous, mainly by ergonomic modifications. It is clear that the current human-machine interface (HMI) in ATS systems (a legacy of past technologies that used LED displays) has reached its limits and needs to be improved, for example, by highlighting the most pertinent information for a given situation (and, conversely, by removing irrelevant information likely to distract operators).
Al-abadleh, H. A.; Tofan-Lazar, J.; Situm, A.; Ruffolo, J.; Slikboer, S.
2013-12-01
Surface water plays a crucial role in facilitating or inhibiting surface reactions in atmospheric aerosols. Little is known about the role of surface water in the complexation of organic molecules to transition metals in multicomponent aerosol systems. We will show results from real time diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) experiments for the in situ complexation of catechol to Fe(III) and its photosensitized degradation under dry and humid conditions. Catechol was chosen as a simple model for humic-like substances (HULIS) in aerosols and aged polyaromatic hydrocarbons (PAH). It has also been detected in secondary organic aerosols (SOA) formed from the reaction of hydroxyl radicals with benzene. Given the importance of the iron content in aerosols and its biogeochemistry, our studies were conducted using FeCl3. For comparison, these surface-sensitive studies were complemented with bulk aqueous ATR-FTIR, UV-vis, and HPLC measurements for structural, quantitative and qualitative information about complexes in the bulk, and potential degradation products. The implications of our studies on understanding interfacial and condensed phase chemistry relevant to multicomponent aerosols, water thin islands on buildings, and ocean surfaces containing transition metals will be discussed.
Empirical and theoretical analysis of complex systems
Zhao, Guannan
This thesis is an interdisciplinary work under the heading of complexity science which focuses on an arguably common "hard" problem across physics, finance and biology [1], to quantify and mimic the macroscopic "emergent phenomenon" in large-scale systems consisting of many interacting "particles" governed by microscopic rules. In contrast to traditional statistical physics, we are interested in systems whose dynamics are subject to feedback, evolution, adaption, openness, etc. Global financial markets, like the stock market and currency market, are ideal candidate systems for such a complexity study: there exists a vast amount of accurate data, which is the aggregate output of many autonomous agents continuously competing with each other. We started by examining the ultrafast "mini flash crash (MFC)" events in the US stock market. An abrupt system-wide composition transition from a mixed human machine phase to a new all-machine phase is uncovered, and a novel theory developed to explain this observation. Then in the study of FX market, we found an unexpected variation in the synchronicity of price changes in different market subsections as a function of the overall trading activity. Several survival models have been tested in analyzing the distribution of waiting times to the next price change. In the region of long waiting-times, the distribution for each currency pair exhibits a power law with exponent in the vicinity of 3.5. By contrast, for short waiting times only, the market activity can be mimicked by the fluctuations emerging from a finite resource competition model containing multiple agents with limited rationality (so called El Farol Model). Switching to the biomedical domain, we present a minimal mathematical model built around a co-evolving resource network and cell population, yielding good agreement with primary tumors in mice experiment and with clinical metastasis data. In the quest to understand contagion phenomena in systems where social group
Narotam, Pradeep K; Morrison, John F; Schmidt, Michael D; Nathoo, Narendra
2014-04-01
Predictive modeling of emergent behavior, inherent to complex physiological systems, requires the analysis of large complex clinical data streams currently being generated in the intensive care unit. Brain tissue oxygen protocols have yielded outcome benefits in traumatic brain injury (TBI), but the critical physiological thresholds for low brain oxygen have not been established for a dynamical patho-physiological system. High frequency, multi-modal clinical data sets from 29 patients with severe TBI who underwent multi-modality neuro-clinical care monitoring and treatment with a brain oxygen protocol were analyzed. The inter-relationship between acute physiological parameters was determined using symbolic regression (SR) as the computational framework. The mean patient age was 44.4±15 with a mean admission GCS of 6.6±3.9. Sixty-three percent sustained motor vehicle accidents and the most common pathology was intra-cerebral hemorrhage (50%). Hospital discharge mortality was 21%, poor outcome occurred in 24% of patients, and good outcome occurred in 56% of patients. Criticality for low brain oxygen was intracranial pressure (ICP) ≥22.8 mm Hg, for mortality at ICP≥37.1 mm Hg. The upper therapeutic threshold for cerebral perfusion pressure (CPP) was 75 mm Hg. Eubaric hyperoxia significantly impacted partial pressure of oxygen in brain tissue (PbtO2) at all ICP levels. Optimal brain temperature (Tbr) was 34-35°C, with an adverse effect when Tbr≥38°C. Survivors clustered at [Formula: see text] Hg vs. non-survivors [Formula: see text] 18 mm Hg. There were two mortality clusters for ICP: High ICP/low PbtO2 and low ICP/low PbtO2. Survivors maintained PbtO2 at all ranges of mean arterial pressure in contrast to non-survivors. The final SR equation for cerebral oxygenation is: [Formula: see text]. The SR-model of acute TBI advances new physiological thresholds or boundary conditions for acute TBI management: PbtO2≥25 mmHg; ICP≤22 mmHg; CPP≈60-75
Modular interdependency in complex dynamical systems.
Watson, Richard A; Pollack, Jordan B
2005-01-01
Herbert A. Simon's characterization of modularity in dynamical systems describes subsystems as having dynamics that are approximately independent of those of other subsystems (in the short term). This fits with the general intuition that modules must, by definition, be approximately independent. In the evolution of complex systems, such modularity may enable subsystems to be modified and adapted independently of other subsystems, whereas in a nonmodular system, modifications to one part of the system may result in deleterious side effects elsewhere in the system. But this notion of modularity and its effect on evolvability is not well quantified and is rather simplistic. In particular, modularity need not imply that intermodule dependences are weak or unimportant. In dynamical systems this is acknowledged by Simon's suggestion that, in the long term, the dynamical behaviors of subsystems do interact with one another, albeit in an "aggregate" manner--but this kind of intermodule interaction is omitted in models of modularity for evolvability. In this brief discussion we seek to unify notions of modularity in dynamical systems with notions of how modularity affects evolvability. This leads to a quantifiable measure of modularity and a different understanding of its effect on evolvability.
Reliability of large and complex systems
Kolowrocki, Krzysztof
2014-01-01
Reliability of Large and Complex Systems, previously titled Reliability of Large Systems, is an innovative guide to the current state and reliability of large and complex systems. In addition to revised and updated content on the complexity and safety of large and complex mechanisms, this new edition looks at the reliability of nanosystems, a key research topic in nanotechnology science. The author discusses the importance of safety investigation of critical infrastructures that have aged or have been exposed to varying operational conditions. This reference provides an asympt
Directory of Open Access Journals (Sweden)
Christopher D Hudson
Full Text Available The ever-growing volume of data routinely collected and stored in everyday life presents researchers with a number of opportunities to gain insight and make predictions. This study aimed to demonstrate the usefulness in a specific clinical context of a simulation-based technique called probabilistic sensitivity analysis (PSA in interpreting the results of a discrete time survival model based on a large dataset of routinely collected dairy herd management data. Data from 12,515 dairy cows (from 39 herds were used to construct a multilevel discrete time survival model in which the outcome was the probability of a cow becoming pregnant during a given two day period of risk, and presence or absence of a recorded lameness event during various time frames relative to the risk period amongst the potential explanatory variables. A separate simulation model was then constructed to evaluate the wider clinical implications of the model results (i.e. the potential for a herd's incidence rate of lameness to influence its overall reproductive performance using PSA. Although the discrete time survival analysis revealed some relatively large associations between lameness events and risk of pregnancy (for example, occurrence of a lameness case within 14 days of a risk period was associated with a 25% reduction in the risk of the cow becoming pregnant during that risk period, PSA revealed that, when viewed in the context of a realistic clinical situation, a herd's lameness incidence rate is highly unlikely to influence its overall reproductive performance to a meaningful extent in the vast majority of situations. Construction of a simulation model within a PSA framework proved to be a very useful additional step to aid contextualisation of the results from a discrete time survival model, especially where the research is designed to guide on-farm management decisions at population (i.e. herd rather than individual level.
Imura, Jun-ichi; Ueta, Tetsushi
2015-01-01
This book is the first to report on theoretical breakthroughs on control of complex dynamical systems developed by collaborative researchers in the two fields of dynamical systems theory and control theory. As well, its basic point of view is of three kinds of complexity: bifurcation phenomena subject to model uncertainty, complex behavior including periodic/quasi-periodic orbits as well as chaotic orbits, and network complexity emerging from dynamical interactions between subsystems. Analysis and Control of Complex Dynamical Systems offers a valuable resource for mathematicians, physicists, and biophysicists, as well as for researchers in nonlinear science and control engineering, allowing them to develop a better fundamental understanding of the analysis and control synthesis of such complex systems.
DEFF Research Database (Denmark)
Tsivintzelis, Ioannis; Economou, Ioannis; Kontogeorgis, Georgios
2009-01-01
simpler molecules of similar chemical structure and/or are fitted to Hansen's partial solubility parameters. The methodology is applied to modeling the solubility of three pharmaceuticals, namely acetanilide, phenacetin, and paracetamol, using the nonrandom hydrogen bonding (NRHB) EoS. In all cases...
Mining sensor data from complex systems
Vespier, Ugo
2015-01-01
Today, virtually everything, from natural phenomena to complex artificial and physical systems, can be measured and the resulting information collected, stored and analyzed in order to gain new insight. This thesis shows how complex systems often exhibit diverse behavior at different temporal
Exergy Analysis of Complex Ship Energy Systems
Directory of Open Access Journals (Sweden)
Pierre Marty
2016-04-01
Full Text Available With multiple primary and secondary energy converters (diesel engines, steam turbines, waste heat recovery (WHR and oil-fired boilers, etc. and extensive energy networks (steam, cooling water, exhaust gases, etc., ships may be considered as complex energy systems. Understanding and optimizing such systems requires advanced holistic energy modeling. This modeling can be done in two ways: The simpler approach focuses on energy flows, and has already been tested, approved and presented; a new, more complicated approach, focusing on energy quality, i.e., exergy, is presented in this paper. Exergy analysis has rarely been applied to ships, and, as a general rule, the shipping industry is not familiar with this tool. This paper tries to fill this gap. We start by giving a short reminder of what exergy is and describe the principles of exergy modeling to explain what kind of results should be expected from such an analysis. We then apply these principles to the analysis of a large two-stroke diesel engine with its cooling and exhaust systems. Simulation results are then presented along with the exergy analysis. Finally, we propose solutions for energy and exergy saving which could be applied to marine engines and ships in general.
Directory of Open Access Journals (Sweden)
Simone S. Nascimento
2014-12-01
Full Text Available O. basilicum leaves produce essential oils (LEO rich in monoterpenes. The short half-life and water insolubility are limitations for LEO medical uses. β-Cyclodextrin (β-CD has been employed to improve the pharmacological properties of LEO. We assessed the antihyperalgesic profile of LEO, isolated or complexed in β-CD (LEO/β-CD, on an animal model for fibromyalgia. Behavioral tests: mice were treated every day with either LEO/β-CD (25, 50 or 100 mg/kg, p.o., LEO (25 mg/kg, p.o., tramadol (TRM 4 mg/kg, i.p. or vehicle (saline, and 60 min after treatment behavioral parameters were assessed. Therefore, mice were evaluated for mechanical hyperalgesia (von Frey, motor coordination (Rota-rod and muscle strength (Grip Strength Metter in a mice fibromyalgia model. After 27 days, we evaluated the central nervous system (CNS pathways involved in the effect induced by experimental drugs through immunofluorescence protocol to Fos protein. The differential scanning analysis (DSC, thermogravimetry/derivate thermogravimetry (TG/DTG and infrared absorption spectroscopy (FTIR curves indicated that the products prepared were able to incorporate the LEO efficiently. Oral treatment with LEO or LEO-βCD, at all doses tested, produced a significant reduction of mechanical hyperalgesia and we were able to significantly increase Fos protein expression. Together, our results provide evidence that LEO, isolated or complexed with β-CD, produces analgesic effects on chronic non-inflammatory pain as fibromyalgia.
Directory of Open Access Journals (Sweden)
L. V. Savkin
2015-01-01
Full Text Available One of the problems in implementation of the multipurpose complete systems based on the reconfigurable computing fields (RCF is the problem of optimum redistribution of logicalarithmetic resources in growing scope of functional tasks. Irrespective of complexity, all of them are transformed into an orgraph, which functional and topological structure is appropriately imposed on the RCF based, as a rule, on the field programmable gate array (FPGA.Due to limitation of the hardware configurations and functions realized by means of the switched logical blocks (SLB, the abovementioned problem becomes even more critical when there is a need, within the strictly allocated RCF fragment, to realize even more complex challenge in comparison with the problem which was solved during the previous computing step. In such cases it is possible to speak about graphs of big dimensions with respect to allocated RCF fragment.The article considers this problem through development of diagnostic algorithms to implement diagnostics and control of an onboard control complex of the spacecraft using RCF. It gives examples of big graphs arising with respect to allocated RCF fragment when forming the hardware levels of a diagnostic model, which, in this case, is any hardware-based algorithm of diagnostics in RCF.The article reviews examples of arising big graphs when forming the complicated diagnostic models due to drastic difference in formation of hardware levels on closely located RCF fragments. It also pays attention to big graphs emerging when the multichannel diagnostic models are formed.Three main ways to solve the problem of big graphs with respect to allocated RCF fragment are given. These are: splitting the graph into fragments, use of pop-up windows with relocating and memorizing intermediate values of functions of high hardware levels of diagnostic models, and deep adaptive update of diagnostic model.It is shown that the last of three ways is the most efficient
Role models for complex networks
Reichardt, J.; White, D. R.
2007-11-01
We present a framework for automatically decomposing (“block-modeling”) the functional classes of agents within a complex network. These classes are represented by the nodes of an image graph (“block model”) depicting the main patterns of connectivity and thus functional roles in the network. Using a first principles approach, we derive a measure for the fit of a network to any given image graph allowing objective hypothesis testing. From the properties of an optimal fit, we derive how to find the best fitting image graph directly from the network and present a criterion to avoid overfitting. The method can handle both two-mode and one-mode data, directed and undirected as well as weighted networks and allows for different types of links to be dealt with simultaneously. It is non-parametric and computationally efficient. The concepts of structural equivalence and modularity are found as special cases of our approach. We apply our method to the world trade network and analyze the roles individual countries play in the global economy.
Complex biological and bio-inspired systems
Energy Technology Data Exchange (ETDEWEB)
Ecke, Robert E [Los Alamos National Laboratory
2009-01-01
The understanding and characterization ofthe fundamental processes of the function of biological systems underpins many of the important challenges facing American society, from the pathology of infectious disease and the efficacy ofvaccines, to the development of materials that mimic biological functionality and deliver exceptional and novel structural and dynamic properties. These problems are fundamentally complex, involving many interacting components and poorly understood bio-chemical kinetics. We use the basic science of statistical physics, kinetic theory, cellular bio-chemistry, soft-matter physics, and information science to develop cell level models and explore the use ofbiomimetic materials. This project seeks to determine how cell level processes, such as response to mechanical stresses, chemical constituents and related gradients, and other cell signaling mechanisms, integrate and combine to create a functioning organism. The research focuses on the basic physical processes that take place at different levels ofthe biological organism: the basic role of molecular and chemical interactions are investigated, the dynamics of the DNA-molecule and its phylogenetic role are examined and the regulatory networks of complex biochemical processes are modeled. These efforts may lead to early warning algorithms ofpathogen outbreaks, new bio-sensors to detect hazards from pathomic viruses to chemical contaminants. Other potential applications include the development of efficient bio-fuel alternative-energy processes and the exploration ofnovel materials for energy usages. Finally, we use the notion of 'coarse-graining,' which is a method for averaging over less important degrees of freedom to develop computational models to predict cell function and systems-level response to disease, chemical stress, or biological pathomic agents. This project supports Energy Security, Threat Reduction, and the missions of the DOE Office of Science through its efforts to
Czech Academy of Sciences Publication Activity Database
Vlach, Marek
2015-01-01
Roč. 42, č. 1 (2015), s. 741-748 ISSN 0323-9535. [International Congress of Roman Frontier Studies /22./. Ruse, 06.09.2012-11.09.2012] R&D Projects: GA ČR GA404/09/1054 Grant - others:Rada Programu interní podpory projektů mezinárodní spolupráce AV ČR(CZ) M300011201 Program:M Institutional support: RVO:68081758 Keywords : Roman period * Middle Danube region * Germanic settlement structure * Agent Based Modeling * archaeological demography Subject RIV: AC - Archeology, Anthropology, Ethnology
International Nuclear Information System (INIS)
Vasseur, D.; Eid, M.
1996-01-01
One of EDF's current priorities is the optimisation of the preventive maintenance in all French nuclear power stations. This optimisation involves a rationalization of the choice of equipments to be maintained and maintenance tasks to be carried out, as well as a judicious choice of intervals between these tasks. This work is being carried out in cooperation between EDF and the CEA (Atomic Energy Commission), and suggests a procedure to provide assistance in optimising intervals between maintenance tasks respecting a global unavailability target. This work is based on the differential model for equivalent parameters (DMEP). (authors)
Modelling the structure of complex networks
DEFF Research Database (Denmark)
Herlau, Tue
networks has been independently studied as mathematical objects in their own right. As such, there has been both an increased demand for statistical methods for complex networks as well as a quickly growing mathematical literature on the subject. In this dissertation we explore aspects of modelling complex....... The next chapters will treat some of the various symmetries, representer theorems and probabilistic structures often deployed in the modelling complex networks, the construction of sampling methods and various network models. The introductory chapters will serve to provide context for the included written...
Interval stability for complex systems
Klinshov, Vladimir V.; Kirillov, Sergey; Kurths, Jürgen; Nekorkin, Vladimir I.
2018-04-01
Stability of dynamical systems against strong perturbations is an important problem of nonlinear dynamics relevant to many applications in various areas. Here, we develop a novel concept of interval stability, referring to the behavior of the perturbed system during a finite time interval. Based on this concept, we suggest new measures of stability, namely interval basin stability (IBS) and interval stability threshold (IST). IBS characterizes the likelihood that the perturbed system returns to the stable regime (attractor) in a given time. IST provides the minimal magnitude of the perturbation capable to disrupt the stable regime for a given interval of time. The suggested measures provide important information about the system susceptibility to external perturbations which may be useful for practical applications. Moreover, from a theoretical viewpoint the interval stability measures are shown to bridge the gap between linear and asymptotic stability. We also suggest numerical algorithms for quantification of the interval stability characteristics and demonstrate their potential for several dynamical systems of various nature, such as power grids and neural networks.
Challenges in the analysis of complex systems: introduction and overview
Hastings, Harold M.; Davidsen, Jörn; Leung, Henry
2017-12-01
One of the main challenges of modern physics is to provide a systematic understanding of systems far from equilibrium exhibiting emergent behavior. Prominent examples of such complex systems include, but are not limited to the cardiac electrical system, the brain, the power grid, social systems, material failure and earthquakes, and the climate system. Due to the technological advances over the last decade, the amount of observations and data available to characterize complex systems and their dynamics, as well as the capability to process that data, has increased substantially. The present issue discusses a cross section of the current research on complex systems, with a focus on novel experimental and data-driven approaches to complex systems that provide the necessary platform to model the behavior of such systems.
Systems Biology and Health Systems Complexity in;
Donald Combs, C.; Barham, S.R.; Sloot, P.M.A.
2016-01-01
Systems biology addresses interactions in biological systems at different scales of biological organization, from the molecular to the cellular, organ, organism, societal, and ecosystem levels. This chapter expands on the concept of systems biology, explores its implications for individual patients
Fourth International Conference on Complex Systems
Minai, Ali A; Unifying Themes in Complex Systems IV
2008-01-01
In June of 2002, over 500 professors, students and researchers met in Boston, Massachusetts for the Fourth International Conference on Complex Systems. The attendees represented a remarkably diverse collection of fields: biology, ecology, physics, engineering, computer science, economics, psychology and sociology, The goal of the conference was to encourage cross-fertilization between the many disciplines represented and to deepen understanding of the properties common to all complex systems. This volume contains 43 papers selected from the more than 200 presented at the conference. Topics include: cellular automata, neurology, evolution, computer science, network dynamics, and urban planning. About NECSI: For over 10 years, The New England Complex Systems Institute (NECSI) has been instrumental in the development of complex systems science and its applications. NECSI conducts research, education, knowledge dissemination, and community development around the world for the promotion of the study of complex sys...
Sixth International Conference on Complex Systems
Minai, Ali; Bar-Yam, Yaneer; Unifying Themes in Complex Systems
2008-01-01
The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore the common themes and applications of complex systems science. In June 2006, 500 participants convened in Boston for the sixth ICCS, exploring an array of topics, including networks, systems biology, evolution and ecology, nonlinear dynamics and pattern formation, as well as neural, psychological, psycho-social, socio-economic, and global systems. This volume selects 77 papers from over 300 presented at the conference. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex systems science.
Quantum transport in complex system
International Nuclear Information System (INIS)
Kusnezov, D.; Bulgac, A.; DoDang, G.
1998-01-01
We derive the influence function and the effective dynamics of a quantum systems coupled to a chaotic environment, using very general parametric and banded random matrices to describe the quantum properties of a chaotic bath. We find that only in certain limits the thermalization can result from the environment. We study the general transport problems including escape, fusion and tunneling (fission). (author)
Lectures in Complex Systems (1991)
1992-08-05
of Development and Aging of the Nervous System, edited by J. M. Lauder , 217-225. New York: Plenum Press, 1990. 88. Keller, E. F. A Feeling for the...not every player wins an infinite amount of money just because the expected winning is infinite. The perception of this paradox in the 1700s was to cast
Complex System Governance for Acquisition
2016-04-30
are not the privilege, or curse, of any particular field or sector (energy, utilities, healthcare, transportation , commerce, defense, security...2005; Whitney et al., 2015) and Management Cybernetics ( Beer , 1972, 1979, 1985) and the field has been built upon their philosophical, theoretical, and...et al., 2015), while Management Cybernetics has been identified as the science of effective (system) organization ( Beer , 1972). Following from the
A System for Complex Robotic Welding
DEFF Research Database (Denmark)
Madsen, Ole; Sørensen, Carsten Bro; Olsen, Birger
2002-01-01
This paper presents the architecture of a system for robotic welding of complex tasks. The system integrates off-line programming, control of redundant robots, collision-free motion planning and sensor-based control. An implementation for pipe structure welding made at Odense Steel Shipyard Ltd......., Denmark, demonstrates the system can be used for automatic welding of complex products in one-of-a-kind production....
Workshop on Nonlinear Phenomena in Complex Systems
1989-01-01
This book contains a thorough treatment of neural networks, cellular-automata and synergetics, in an attempt to provide three different approaches to nonlinear phenomena in complex systems. These topics are of major interest to physicists active in the fields of statistical mechanics and dynamical systems. They have been developed with a high degree of sophistication and include the refinements necessary to work with the complexity of real systems as well as the more recent research developments in these areas.
Hale, Mark A.; Craig, James I.; Mistree, Farrokh; Schrage, Daniel P.
1995-01-01
Computing architectures are being assembled that extend concurrent engineering practices by providing more efficient execution and collaboration on distributed, heterogeneous computing networks. Built on the successes of initial architectures, requirements for a next-generation design computing infrastructure can be developed. These requirements concentrate on those needed by a designer in decision-making processes from product conception to recycling and can be categorized in two areas: design process and design information management. A designer both designs and executes design processes throughout design time to achieve better product and process capabilities while expanding fewer resources. In order to accomplish this, information, or more appropriately design knowledge, needs to be adequately managed during product and process decomposition as well as recomposition. A foundation has been laid that captures these requirements in a design architecture called DREAMS (Developing Robust Engineering Analysis Models and Specifications). In addition, a computing infrastructure, called IMAGE (Intelligent Multidisciplinary Aircraft Generation Environment), is being developed that satisfies design requirements defined in DREAMS and incorporates enabling computational technologies.
González-Díaz, Humberto; Arrasate, Sonia; Gómez-SanJuan, Asier; Sotomayor, Nuria; Lete, Esther; Besada-Porto, Lina; Ruso, Juan M
2013-01-01
In general perturbation methods starts with a known exact solution of a problem and add "small" variation terms in order to approach to a solution for a related problem without known exact solution. Perturbation theory has been widely used in almost all areas of science. Bhor's quantum model, Heisenberg's matrix mechanincs, Feyman diagrams, and Poincare's chaos model or "butterfly effect" in complex systems are examples of perturbation theories. On the other hand, the study of Quantitative Structure-Property Relationships (QSPR) in molecular complex systems is an ideal area for the application of perturbation theory. There are several problems with exact experimental solutions (new chemical reactions, physicochemical properties, drug activity and distribution, metabolic networks, etc.) in public databases like CHEMBL. However, in all these cases, we have an even larger list of related problems without known solutions. We need to know the change in all these properties after a perturbation of initial boundary conditions. It means, when we test large sets of similar, but different, compounds and/or chemical reactions under the slightly different conditions (temperature, time, solvents, enzymes, assays, protein targets, tissues, partition systems, organisms, etc.). However, to the best of our knowledge, there is no QSPR general-purpose perturbation theory to solve this problem. In this work, firstly we review general aspects and applications of both perturbation theory and QSPR models. Secondly, we formulate a general-purpose perturbation theory for multiple-boundary QSPR problems. Last, we develop three new QSPR-Perturbation theory models. The first model classify correctly >100,000 pairs of intra-molecular carbolithiations with 75-95% of Accuracy (Ac), Sensitivity (Sn), and Specificity (Sp). The model predicts probabilities of variations in the yield and enantiomeric excess of reactions due to at least one perturbation in boundary conditions (solvent, temperature
Theories and simulations of complex social systems
Mago, Vijay
2014-01-01
Research into social systems is challenging due to their complex nature. Traditional methods of analysis are often difficult to apply effectively as theories evolve over time. This can be due to a lack of appropriate data, or too much uncertainty. It can also be the result of problems which are not yet understood well enough in the general sense so that they can be classified, and an appropriate solution quickly identified. Simulation is one tool that deals well with these challenges, fits in well with the deductive process, and is useful for testing theory. This field is still relatively new, and much of the work is necessarily innovative, although it builds upon a rich and varied foundation. There are a number of existing modelling paradigms being applied to complex social systems research. Additionally, new methods and measures are being devised through the process of conducting research. We expect that readers will enjoy the collection of high quality research works from new and accomplished researchers. ...
Systems Approach to Tourism: A Methodology for Defining Complex Tourism System
Directory of Open Access Journals (Sweden)
Jere Jakulin Tadeja
2017-08-01
Full Text Available Background and Purpose: The complexity of the tourism system, as well as modelling in a frame of system dynamics, will be discussed in this paper. The phaenomenon of tourism, which possesses the typical properties of global and local organisations, will be presented as an open complex system with all its elements, and an optimal methodology to explain the relations among them. The approach we want to present is due to its transparency an excellent tool for searching systems solutions and serves also as a strategic decision-making assessment. We will present systems complexity and develop three models of a complex tourism system: the first one will present tourism as an open complex system with its elements, which operate inside of a tourism market area. The elements of this system present subsystems, which relations and interdependencies will be explained with two models: causal-loop diagram and a simulation model in frame of systems dynamics.
Complex energy system management using optimization techniques
Energy Technology Data Exchange (ETDEWEB)
Bridgeman, Stuart; Hurdowar-Castro, Diana; Allen, Rick; Olason, Tryggvi; Welt, Francois
2010-09-15
Modern energy systems are often very complex with respect to the mix of generation sources, energy storage, transmission, and avenues to market. Historically, power was provided by government organizations to load centers, and pricing was provided in a regulatory manner. In recent years, this process has been displaced by the independent system operator (ISO). This complexity makes the operation of these systems very difficult, since the components of the system are interdependent. Consequently, computer-based large-scale simulation and optimization methods like Decision Support Systems are now being used. This paper discusses the application of a DSS to operations and planning systems.
Agile Integration of Complex Systems
2010-04-28
intervention in using SOA can be reduced Page 5 SOA in DoD DoD has mandated that all systems support the Network - Centric Environment and SOA is fundamental to...it and dropping it on an orchestrate icon (slide 22) Di i lifi d d d i l Page 13 scovery s mp e an ma e v sua SOAF Messaging Service Transport
Membrane tethering complexes in the endosomal system
Directory of Open Access Journals (Sweden)
Anne eSpang
2016-05-01
Full Text Available Vesicles that are generated by endocytic events at the plasma membrane are destined to early endosomes. A prerequisite for proper fusion is the tethering of two membrane entities. Tethering of vesicles to early endosomes is mediated by the CORVET complex, while fusion of late endosomes with lysosomes depends on the HOPS complex. Recycling through the TGN and to the plasma membrane is facilitated by the GARP and EARP complexes, respectively. However, there are other tethering functions in the endosomal system as there are multiple pathways through which proteins can be delivered from endosomes to either the TGN or the plasma membrane. Furthermore, complexes that may be part of novel tethering complexes have been recently identified. Thus it is likely that more tethering factors exist. In this review, I will provide an overview of different tethering complexes of the endosomal system and discuss how they may provide specificity in membrane traffic.
Advances in complex societal, environmental and engineered systems
Essaaidi, Mohammad
2017-01-01
This book addresses recent technological progress that has led to an increased complexity in many natural and artificial systems. The resulting complexity research due to the emergence of new properties and spatio-temporal interactions among a large number of system elements - and between the system and its environment - is the primary focus of this text. This volume is divided into three parts: Part one focuses on societal and ecological systems, Part two deals with approaches for understanding, modeling, predicting and mastering socio-technical systems, and Part three includes real-life examples. Each chapter has its own special features; it is a self-contained contribution of distinguished experts working on different fields of science and technology relevant to the study of complex systems. Advances in Complex Systems of Contemporary Reality: Societal, Environmental and Engineered Systems will provide postgraduate students, researchers and managers with qualitative and quantitative methods for handling th...
Complex motions and chaos in nonlinear systems
Machado, José; Zhang, Jiazhong
2016-01-01
This book brings together 10 chapters on a new stream of research examining complex phenomena in nonlinear systems—including engineering, physics, and social science. Complex Motions and Chaos in Nonlinear Systems provides readers a particular vantage of the nature and nonlinear phenomena in nonlinear dynamics that can develop the corresponding mathematical theory and apply nonlinear design to practical engineering as well as the study of other complex phenomena including those investigated within social science.
Generative complexity of Gray-Scott model
Adamatzky, Andrew
2018-03-01
In the Gray-Scott reaction-diffusion system one reactant is constantly fed in the system, another reactant is reproduced by consuming the supplied reactant and also converted to an inert product. The rate of feeding one reactant in the system and the rate of removing another reactant from the system determine configurations of concentration profiles: stripes, spots, waves. We calculate the generative complexity-a morphological complexity of concentration profiles grown from a point-wise perturbation of the medium-of the Gray-Scott system for a range of the feeding and removal rates. The morphological complexity is evaluated using Shannon entropy, Simpson diversity, approximation of Lempel-Ziv complexity, and expressivity (Shannon entropy divided by space-filling). We analyse behaviour of the systems with highest values of the generative morphological complexity and show that the Gray-Scott systems expressing highest levels of the complexity are composed of the wave-fragments (similar to wave-fragments in sub-excitable media) and travelling localisations (similar to quasi-dissipative solitons and gliders in Conway's Game of Life).
Integrated Visualisation and Description of Complex Systems
National Research Council Canada - National Science Library
Goodburn, D
1999-01-01
... on system topographies and feature overlays. System information from the domain's information space is filtered and integrated into a Composite Systems Model that provides a basis for consistency and integration between all system views...
Pulinets, S. A.; Ouzounov, D. P.; Karelin, A. V.; Davidenko, D. V.
2015-07-01
This paper describes the current understanding of the interaction between geospheres from a complex set of physical and chemical processes under the influence of ionization. The sources of ionization involve the Earth's natural radioactivity and its intensification before earthquakes in seismically active regions, anthropogenic radioactivity caused by nuclear weapon testing and accidents in nuclear power plants and radioactive waste storage, the impact of galactic and solar cosmic rays, and active geophysical experiments using artificial ionization equipment. This approach treats the environment as an open complex system with dissipation, where inherent processes can be considered in the framework of the synergistic approach. We demonstrate the synergy between the evolution of thermal and electromagnetic anomalies in the Earth's atmosphere, ionosphere, and magnetosphere. This makes it possible to determine the direction of the interaction process, which is especially important in applications related to short-term earthquake prediction. That is why the emphasis in this study is on the processes proceeding the final stage of earthquake preparation; the effects of other ionization sources are used to demonstrate that the model is versatile and broadly applicable in geophysics.
Complex engineering systems science meets technology
Minai, Ali A; Bar-Yam, Yaneer
2006-01-01
Every time that we take money out of an ATM, surf the internet or simply turn on a light switch, we enjoy the benefits of complex engineered systems. Systems like power grids and global communication networks are so ubiquitous in our daily lives that we usually take them for granted, only noticing them when they break down. But how do such amazing technologies and infrastructures come to be what they are? How are these systems designed? How do distributed networks work? How are they made to respond rapidly in 'real time'? And as the demands that we place on these systems become increasingly complex, are traditional systems-engineering practices still relevant? This volume examines the difficulties that arise in creating highly complex engineered systems and new approaches that are being adopted. Topics addressed range from the formal representation and classification of distributed networked systems to revolutionary engineering practices inspired by biological evolution. By bringing together the latest resear...
Seekhao, Nuttiiya; Shung, Caroline; JaJa, Joseph; Mongeau, Luc; Li-Jessen, Nicole Y K
2016-05-01
We present an efficient and scalable scheme for implementing agent-based modeling (ABM) simulation with In Situ visualization of large complex systems on heterogeneous computing platforms. The scheme is designed to make optimal use of the resources available on a heterogeneous platform consisting of a multicore CPU and a GPU, resulting in minimal to no resource idle time. Furthermore, the scheme was implemented under a client-server paradigm that enables remote users to visualize and analyze simulation data as it is being generated at each time step of the model. Performance of a simulation case study of vocal fold inflammation and wound healing with 3.8 million agents shows 35× and 7× speedup in execution time over single-core and multi-core CPU respectively. Each iteration of the model took less than 200 ms to simulate, visualize and send the results to the client. This enables users to monitor the simulation in real-time and modify its course as needed.
The Self as a Complex Dynamic System
Mercer, Sarah
2011-01-01
This article explores the potential offered by complexity theories for understanding language learners' sense of self and attempts to show how the self might usefully be conceived of as a complex dynamic system. Rather than presenting empirical findings, the article discusses existent research on the self and aims at outlining a conceptual…
Strategies of complexity leadership in governance systems
Nooteboom, S.G.; Termeer, C.J.A.M.
2013-01-01
In complex governance systems, innovations may emerge, not controlled by a single leader, but enabled by many. We discuss how these leaders are embedded in networks and which strategies they use. The theoretical framework is based on Complexity Leadership Theory. We conducted participatory
Controller Design of Complex System Based on Nonlinear Strength
Directory of Open Access Journals (Sweden)
Rongjun Mu
2015-01-01
Full Text Available This paper presents a new idea of controller design for complex systems. The nonlinearity index method was first developed for error propagation of nonlinear system. The nonlinearity indices access the boundary between the strong and the weak nonlinearities of the system model. The algorithm of nonlinearity index according to engineering application is first proposed in this paper. Applying this method on nonlinear systems is an effective way to measure the nonlinear strength of dynamics model over the full flight envelope. The nonlinearity indices access the boundary between the strong and the weak nonlinearities of system model. According to the different nonlinear strength of dynamical model, the control system is designed. The simulation time of dynamical complex system is selected by the maximum value of dynamic nonlinearity indices. Take a missile as example; dynamical system and control characteristic of missile are simulated. The simulation results show that the method is correct and appropriate.
Optimal sensor configuration for complex systems
DEFF Research Database (Denmark)
Sadegh, Payman; Spall, J. C.
1998-01-01
. The procedure for sensor configuration is based on the simultaneous perturbation stochastic approximation (SPSA) algorithm. SPSA avoids the need for detailed modeling of the sensor response by simply relying on the observed responses obtained by limited experimentation with test sensor configurations. We......The paper considers the problem of sensor configuration for complex systems with the aim of maximizing the useful information about certain quantities of interest. Our approach involves: 1) definition of an appropriate optimality criterion or performance measure; and 2) description of an efficient...... and practical algorithm for achieving the optimality objective. The criterion for optimal sensor configuration is based on maximizing the overall sensor response while minimizing the correlation among the sensor outputs, so as to minimize the redundant information being provided by the multiple sensors...
Optimal sensor configuration for complex systems
DEFF Research Database (Denmark)
Sadegh, Payman; Spall, J. C.
1998-01-01
configuration is based on maximizing the overall sensor response while minimizing the correlation among the sensor outputs. The procedure for sensor configuration is based on simultaneous perturbation stochastic approximation (SPSA). SPSA avoids the need for detailed modeling of the sensor response by simply......Considers the problem of sensor configuration for complex systems. Our approach involves definition of an appropriate optimality criterion or performance measure, and description of an efficient and practical algorithm for achieving the optimality objective. The criterion for optimal sensor...... relying on observed responses as obtained by limited experimentation with test sensor configurations. We illustrate the approach with the optimal placement of acoustic sensors for signal detection in structures. This includes both a computer simulation study for an aluminum plate, and real...
Visualizing complex (hydrological) systems with correlation matrices
Haas, J. C.
2016-12-01
When trying to understand or visualize the connections of different aspects of a complex system, this often requires deeper understanding to start with, or - in the case of geo data - complicated GIS software. To our knowledge, correlation matrices have rarely been used in hydrology (e.g. Stoll et al., 2011; van Loon and Laaha, 2015), yet they do provide an interesting option for data visualization and analysis. We present a simple, python based way - using a river catchment as an example - to visualize correlations and similarities in an easy and colorful way. We apply existing and easy to use python packages from various disciplines not necessarily linked to the Earth sciences and can thus quickly show how different aquifers work or react, and identify outliers, enabling this system to also be used for quality control of large datasets. Going beyond earlier work, we add a temporal and spatial element, enabling us to visualize how a system reacts to local phenomena such as for example a river, or changes over time, by visualizing the passing of time in an animated movie. References: van Loon, A.F., Laaha, G.: Hydrological drought severity explained by climate and catchment characteristics, Journal of Hydrology 526, 3-14, 2015, Drought processes, modeling, and mitigation Stoll, S., Hendricks Franssen, H. J., Barthel, R., Kinzelbach, W.: What can we learn from long-term groundwater data to improve climate change impact studies?, Hydrology and Earth System Sciences 15(12), 3861-3875, 2011
Geographical National Condition and Complex System
Directory of Open Access Journals (Sweden)
WANG Jiayao
2016-01-01
Full Text Available The significance of studying the complex system of geographical national conditions lies in rationally expressing the complex relationships of the “resources-environment-ecology-economy-society” system. Aiming to the problems faced by the statistical analysis of geographical national conditions, including the disunity of research contents, the inconsistency of range, the uncertainty of goals, etc.the present paper conducted a range of discussions from the perspectives of concept, theory and method, and designed some solutions based on the complex system theory and coordination degree analysis methods.By analyzing the concepts of geographical national conditions, geographical national conditions survey and geographical national conditions statistical analysis, as well as investigating the relationships between theirs, the statistical contents and the analytical range of geographical national conditions are clarified and defined. This investigation also clarifies the goals of the statistical analysis by analyzing the basic characteristics of the geographical national conditions and the complex system, and the consistency between the analysis of the degree of coordination and statistical analyses. It outlines their goals, proposes a concept for the complex system of geographical national conditions, and it describes the concept. The complex system theory provides new theoretical guidance for the statistical analysis of geographical national conditions. The degree of coordination offers new approaches on how to undertake the analysis based on the measurement method and decision-making analysis scheme upon which the complex system of geographical national conditions is based. It analyzes the overall trend via the degree of coordination of the complex system on a macro level, and it determines the direction of remediation on a micro level based on the degree of coordination among various subsystems and of single systems. These results establish
Baianu, I C
2004-01-01
Quantitative Biology, abstract q-bio.OT/0406045 From: I.C. Baianu Dr. [view email] Date (v1): Thu, 24 Jun 2004 02:45:13 GMT (164kb) Date (revised v2): Fri, 2 Jul 2004 00:58:06 GMT (160kb) Complex Systems Analysis of Cell Cycling Models in Carcinogenesis: II. Authors: I.C. Baianu Comments: 23 pages, 1 Figure Report-no: CC04 Subj-class: Other Carcinogenesis is a complex process that involves dynamically inter-connected modular sub-networks that evolve under the influence of micro-environmentally induced perturbations, in non-random, pseudo-Markov chain processes. An appropriate n-stage model of carcinogenesis involves therefore n-valued Logic treatments of nonlinear dynamic transformations of complex functional genomes and cell interactomes. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous, Boolean or "fuzzy", logic models of genetic activities in vivo....
Stephen Jay Kline on systems, or physics, complex systems, and the gap between.
Energy Technology Data Exchange (ETDEWEB)
Campbell, Philip LaRoche
2011-06-01
At the end of his life, Stephen Jay Kline, longtime professor of mechanical engineering at Stanford University, completed a book on how to address complex systems. The title of the book is 'Conceptual Foundations of Multi-Disciplinary Thinking' (1995), but the topic of the book is systems. Kline first establishes certain limits that are characteristic of our conscious minds. Kline then establishes a complexity measure for systems and uses that complexity measure to develop a hierarchy of systems. Kline then argues that our minds, due to their characteristic limitations, are unable to model the complex systems in that hierarchy. Computers are of no help to us here. Our attempts at modeling these complex systems are based on the way we successfully model some simple systems, in particular, 'inert, naturally-occurring' objects and processes, such as what is the focus of physics. But complex systems overwhelm such attempts. As a result, the best we can do in working with these complex systems is to use a heuristic, what Kline calls the 'Guideline for Complex Systems.' Kline documents the problems that have developed due to 'oversimple' system models and from the inappropriate application of a system model from one domain to another. One prominent such problem is the Procrustean attempt to make the disciplines that deal with complex systems be 'physics-like.' Physics deals with simple systems, not complex ones, using Kline's complexity measure. The models that physics has developed are inappropriate for complex systems. Kline documents a number of the wasteful and dangerous fallacies of this type.
Modeling Musical Complexity: Commentary on Eerola (2016
Directory of Open Access Journals (Sweden)
Joshua Albrecht
2016-07-01
Full Text Available In his paper, "Expectancy violation and information-theoretic models of melodic complexity," Eerola compares a number of models that correlate musical features of monophonic melodies with participant ratings of perceived melodic complexity. He finds that fairly strong results can be achieved using several different approaches to modeling perceived melodic complexity. The data used in this study are gathered from several previously published studies that use widely different types of melodies, including isochronous folk melodies, isochronous 12-tone rows, and rhythmically complex African folk melodies. This commentary first briefly reviews the article's method and main findings, then suggests a rethinking of the theoretical framework of the study. Finally, some of the methodological issues of the study are discussed.
Coordination Approaches for Complex Software Systems
Bosse, T.; Hoogendoorn, M.; Treur, J.
2006-01-01
This document presents the results of a collaboration between the Vrije Universiteit Amsterdam, Department of Artificial Intelligence and Force Vision to investigate coordination approaches for complex software systems. The project was funded by Force Vision.
Platform strategy for complex products and systems
Alblas, A.A.
2011-01-01
The thesis of Alex Alblas presents a design reuse strategy for firms producing complex products and systems (CoPS). Examples of CoPS include industrial machinery, oil-rigs, electrical power distribution systems, integrated mail processing systems and printing press machinery. CoPS firms are
Distributed redundancy and robustness in complex systems
Randles, Martin; Lamb, David J.; Odat, Enas M.; Taleb-Bendiab, Azzelarabe
2011-01-01
that emerges in complex biological and natural systems. However, in order to promote an evolutionary approach, through emergent self-organisation, it is necessary to specify the systems in an 'open-ended' manner where not all states of the system are prescribed
Modeling Complex Nonlinear Optical Systems
2006-07-01
L .k cycycyT kzk kzkkVxV kzkxTzVzTxVV ω β ββ κ 3 trapping cases (GS: ω(v=0) ≈ 0.96) |),,0(| tzxE =+ 2. Trapping into one defect...sech1 2 1 ),(sech2 where ),1)((tanh1 ),5;()()5;()( 22 222 2 22 1 22 21 . ., ., ., .- .k cycycyT kzk kzkkVxV kzkxTzVzTxVV L
Complex fluids in biological systems experiment, theory, and computation
2015-01-01
This book serves as an introduction to the continuum mechanics and mathematical modeling of complex fluids in living systems. The form and function of living systems are intimately tied to the nature of surrounding fluid environments, which commonly exhibit nonlinear and history dependent responses to forces and displacements. With ever-increasing capabilities in the visualization and manipulation of biological systems, research on the fundamental phenomena, models, measurements, and analysis of complex fluids has taken a number of exciting directions. In this book, many of the world’s foremost experts explore key topics such as: Macro- and micro-rheological techniques for measuring the material properties of complex biofluids and the subtleties of data interpretation Experimental observations and rheology of complex biological materials, including mucus, cell membranes, the cytoskeleton, and blood The motility of microorganisms in complex fluids and the dynamics of active suspensions Challenges and solut...
Project risk management in complex petrochemical system
Directory of Open Access Journals (Sweden)
Kirin Snežana
2012-01-01
Full Text Available Investigation of risk in complex industrial systems, as well as evaluation of main factors influencing decision making and implementation process using large petrochemical company as an example, has proved the importance of successful project risk management. This is even more emphasized when analyzing systems with complex structure, i.e. with several organizational units. It has been shown that successful risk management requires modern methods, based on adequate application of statistical analysis methods.
The deconvolution of complex spectra by artificial immune system
Galiakhmetova, D. I.; Sibgatullin, M. E.; Galimullin, D. Z.; Kamalova, D. I.
2017-11-01
An application of the artificial immune system method for decomposition of complex spectra is presented. The results of decomposition of the model contour consisting of three components, Gaussian contours, are demonstrated. The method of artificial immune system is an optimization method, which is based on the behaviour of the immune system and refers to modern methods of search for the engine optimization.
The sleeping brain as a complex system.
Olbrich, Eckehard; Achermann, Peter; Wennekers, Thomas
2011-10-13
'Complexity science' is a rapidly developing research direction with applications in a multitude of fields that study complex systems consisting of a number of nonlinear elements with interesting dynamics and mutual interactions. This Theme Issue 'The complexity of sleep' aims at fostering the application of complexity science to sleep research, because the brain in its different sleep stages adopts different global states that express distinct activity patterns in large and complex networks of neural circuits. This introduction discusses the contributions collected in the present Theme Issue. We highlight the potential and challenges of a complex systems approach to develop an understanding of the brain in general and the sleeping brain in particular. Basically, we focus on two topics: the complex networks approach to understand the changes in the functional connectivity of the brain during sleep, and the complex dynamics of sleep, including sleep regulation. We hope that this Theme Issue will stimulate and intensify the interdisciplinary communication to advance our understanding of the complex dynamics of the brain that underlies sleep and consciousness.
Linking Complexity and Sustainability Theories: Implications for Modeling Sustainability Transitions
Directory of Open Access Journals (Sweden)
Camaren Peter
2014-03-01
Full Text Available In this paper, we deploy a complexity theory as the foundation for integration of different theoretical approaches to sustainability and develop a rationale for a complexity-based framework for modeling transitions to sustainability. We propose a framework based on a comparison of complex systems’ properties that characterize the different theories that deal with transitions to sustainability. We argue that adopting a complexity theory based approach for modeling transitions requires going beyond deterministic frameworks; by adopting a probabilistic, integrative, inclusive and adaptive approach that can support transitions. We also illustrate how this complexity-based modeling framework can be implemented; i.e., how it can be used to select modeling techniques that address particular properties of complex systems that we need to understand in order to model transitions to sustainability. In doing so, we establish a complexity-based approach towards modeling sustainability transitions that caters for the broad range of complex systems’ properties that are required to model transitions to sustainability.
Sell, K. S.; Heather, M. R.; Herbert, B. E.
2004-12-01
Exposing earth system science (ESS) concepts into introductory geoscience courses may present new and unique cognitive learning issues for students including understanding the role of positive and negative feedbacks in system responses to perturbations, spatial heterogeneity, and temporal dynamics, especially when systems exhibit complex behavior. Implicit learning goals of typical introductory undergraduate geoscience courses are more focused on building skill-sets and didactic knowledge in learners than developing a deeper understanding of the dynamics and processes of complex earth systems through authentic inquiry. Didactic teaching coupled with summative assessment of factual knowledge tends to limit student¡¦s understanding of the nature of science, their belief in the relevancy of science to their lives, and encourages memorization and regurgitation; this is especially true among the non-science majors who compose the majority of students in introductory courses within the large university setting. Students organize scientific knowledge and reason about earth systems by manipulating internally constructed mental models. This pilot study focuses on characterizing the impact of inquiry-based learning with multiple representations to foster critical thinking and mental model development about authentic environmental issues of coastal systems in an introductory geoscience course. The research was conducted in nine introductory physical geology laboratory sections (N ˜ 150) at Texas A&M University as part of research connected with the Information Technology in Science (ITS) Center. Participants were randomly placed into experimental and control groups. Experimental groups were exposed to multiple representations including both web-based learning materials (i.e. technology-supported visualizations and analysis of multiple datasets) and physical models, whereas control groups were provided with the traditional ¡workbook style¡" laboratory assignments
Bistacchi, A.; Pisterna, R.; Romano, V.; Rust, D.; Tibaldi, A.
2009-04-01
The plumbing system that connects a sub-volcanic magma reservoir to the surface has been the object of field characterization and mechanical modelling efforts since the pioneering work by Anderson (1936), who produced a detailed account of the spectacular Cullin Cone-sheet Complex (Isle of Skye, UK) and a geometrical and mechanical model aimed at defining the depth to the magma chamber. Since this work, the definition of the stress state in the half space comprised between the magma reservoir and the surface (modelled either as a flat surface or a surface comprising a volcanic edifice) was considered the key point in reconstructing dike propagation paths from the magma chamber. In fact, this process is generally seen as the propagation in an elastic media of purely tensional joints (mode I or opening mode propagation), which follow trajectories perpendicular to the least compressive principal stress axis. Later works generally used different continuum mechanics methodologies (analytic, BEM, FEM) to solve the problem of a pressure source (the magma chamber, either a point source or a finite volume) in an elastic (in some cases heterogeneous) half space (bounded by a flat topography or topped by a "volcano"). All these models (with a few limited exceptions) disregard the effect of the regional stress field, which is caused by tectonic boundary forces and gravitational body load, and consider only the pressure source represented by the magma chamber (review in Gudmundsson, 2006). However, this is only a (sometimes subordinate) component of the total stress field. Grosfils (2007) first introduced the gravitational load (but not tectonic stresses) in an elastic model solved with FEM in a 2D axisymmetric half-space, showing that "failure to incorporate gravitational loading correctly" affect the calculated stress pattern and many of the predictions that can be drawn from the models. In this contribution we report on modelling results that include: 2D axisymmetric or true
Fatigue modeling of materials with complex microstructures
DEFF Research Database (Denmark)
Qing, Hai; Mishnaevsky, Leon
2011-01-01
with the phenomenological model of fatigue damage growth. As a result, the fatigue lifetime of materials with complex structures can be determined as a function of the parameters of their structures. As an example, the fatigue lifetimes of wood modeled as a cellular material with multilayered, fiber reinforced walls were...
What Is a Complex Innovation System?
Katz, J. Sylvan
2016-01-01
Innovation systems are sometimes referred to as complex systems, something that is intuitively understood but poorly defined. A complex system dynamically evolves in non-linear ways giving it unique properties that distinguish it from other systems. In particular, a common signature of complex systems is scale-invariant emergent properties. A scale-invariant property can be identified because it is solely described by a power law function, f(x) = kxα, where the exponent, α, is a measure of scale-invariance. The focus of this paper is to describe and illustrate that innovation systems have properties of a complex adaptive system. In particular scale-invariant emergent properties indicative of their complex nature that can be quantified and used to inform public policy. The global research system is an example of an innovation system. Peer-reviewed publications containing knowledge are a characteristic output. Citations or references to these articles are an indirect measure of the impact the knowledge has on the research community. Peer-reviewed papers indexed in Scopus and in the Web of Science were used as data sources to produce measures of sizes and impact. These measures are used to illustrate how scale-invariant properties can be identified and quantified. It is demonstrated that the distribution of impact has a reasonable likelihood of being scale-invariant with scaling exponents that tended toward a value of less than 3.0 with the passage of time and decreasing group sizes. Scale-invariant correlations are shown between the evolution of impact and size with time and between field impact and sizes at points in time. The recursive or self-similar nature of scale-invariance suggests that any smaller innovation system within the global research system is likely to be complex with scale-invariant properties too. PMID:27258040
What Is a Complex Innovation System?
Directory of Open Access Journals (Sweden)
J Sylvan Katz
Full Text Available Innovation systems are sometimes referred to as complex systems, something that is intuitively understood but poorly defined. A complex system dynamically evolves in non-linear ways giving it unique properties that distinguish it from other systems. In particular, a common signature of complex systems is scale-invariant emergent properties. A scale-invariant property can be identified because it is solely described by a power law function, f(x = kxα, where the exponent, α, is a measure of scale-invariance. The focus of this paper is to describe and illustrate that innovation systems have properties of a complex adaptive system. In particular scale-invariant emergent properties indicative of their complex nature that can be quantified and used to inform public policy. The global research system is an example of an innovation system. Peer-reviewed publications containing knowledge are a characteristic output. Citations or references to these articles are an indirect measure of the impact the knowledge has on the research community. Peer-reviewed papers indexed in Scopus and in the Web of Science were used as data sources to produce measures of sizes and impact. These measures are used to illustrate how scale-invariant properties can be identified and quantified. It is demonstrated that the distribution of impact has a reasonable likelihood of being scale-invariant with scaling exponents that tended toward a value of less than 3.0 with the passage of time and decreasing group sizes. Scale-invariant correlations are shown between the evolution of impact and size with time and between field impact and sizes at points in time. The recursive or self-similar nature of scale-invariance suggests that any smaller innovation system within the global research system is likely to be complex with scale-invariant properties too.
Signs, Systems and Complexity of Transmedia Storytelling
Directory of Open Access Journals (Sweden)
Renira Rampazzo Gambarato
2012-12-01
Full Text Available This article addresses key concepts such as sign, system and complexity in order to approach transmedia storytelling and better understand its intricate nature. The theoretical framework chosen to investigate transmedia storytelling meanders is Semiotics by Charles Sanders Peirce (1839-1914 and General Systems Theory by Mario Bunge (1919-. The complexity of transmedia storytelling is not simply the one of the signs of the works included in a transmedia franchise. It also includes the complexity of the dispositions of users/consumers/players as interpreters of semiotic elements (e.g. characters, themes, environments, events and outcomes presented by transmedia products. It extends further to the complexity of social, cultural, economical and political constructs. The German transmedia narrative The Ultimate SuperHero-Blog by Stefan Gieren and Soﬁa’s Diary, a Portuguese multiplatform production by BeActive, are presented as examples of closed and open system transmedia storytelling respectively.
Vibrations and stability of complex beam systems
Stojanović, Vladimir
2015-01-01
This book reports on solved problems concerning vibrations and stability of complex beam systems. The complexity of a system is considered from two points of view: the complexity originating from the nature of the structure, in the case of two or more elastically connected beams; and the complexity derived from the dynamic behavior of the system, in the case of a damaged single beam, resulting from the harm done to its simple structure. Furthermore, the book describes the analytical derivation of equations of two or more elastically connected beams, using four different theories (Euler, Rayleigh, Timoshenko and Reddy-Bickford). It also reports on a new, improved p-version of the finite element method for geometrically nonlinear vibrations. The new method provides more accurate approximations of solutions, while also allowing us to analyze geometrically nonlinear vibrations. The book describes the appearance of longitudinal vibrations of damaged clamped-clamped beams as a result of discontinuity (damage). It...
Complex and adaptive dynamical systems a primer
Gros, Claudius
2007-01-01
We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...
Complex and Adaptive Dynamical Systems A Primer
Gros, Claudius
2011-01-01
We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...
Complex and adaptive dynamical systems a primer
Gros, Claudius
2013-01-01
Complex system theory is rapidly developing and gaining importance, providing tools and concepts central to our modern understanding of emergent phenomena. This primer offers an introduction to this area together with detailed coverage of the mathematics involved. All calculations are presented step by step and are straightforward to follow. This new third edition comes with new material, figures and exercises. Network theory, dynamical systems and information theory, the core of modern complex system sciences, are developed in the first three chapters, covering basic concepts and phenomena like small-world networks, bifurcation theory and information entropy. Further chapters use a modular approach to address the most important concepts in complex system sciences, with the emergence and self-organization playing a central role. Prominent examples are self-organized criticality in adaptive systems, life at the edge of chaos, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase...
Updating the debate on model complexity
Simmons, Craig T.; Hunt, Randall J.
2012-01-01
As scientists who are trying to understand a complex natural world that cannot be fully characterized in the field, how can we best inform the society in which we live? This founding context was addressed in a special session, “Complexity in Modeling: How Much is Too Much?” convened at the 2011 Geological Society of America Annual Meeting. The session had a variety of thought-provoking presentations—ranging from philosophy to cost-benefit analyses—and provided some areas of broad agreement that were not evident in discussions of the topic in 1998 (Hunt and Zheng, 1999). The session began with a short introduction during which model complexity was framed borrowing from an economic concept, the Law of Diminishing Returns, and an example of enjoyment derived by eating ice cream. Initially, there is increasing satisfaction gained from eating more ice cream, to a point where the gain in satisfaction starts to decrease, ending at a point when the eater sees no value in eating more ice cream. A traditional view of model complexity is similar—understanding gained from modeling can actually decrease if models become unnecessarily complex. However, oversimplified models—those that omit important aspects of the problem needed to make a good prediction—can also limit and confound our understanding. Thus, the goal of all modeling is to find the “sweet spot” of model sophistication—regardless of whether complexity was added sequentially to an overly simple model or collapsed from an initial highly parameterized framework that uses mathematics and statistics to attain an optimum (e.g., Hunt et al., 2007). Thus, holistic parsimony is attained, incorporating “as simple as possible,” as well as the equally important corollary “but no simpler.”
Complex systems and networks dynamics, controls and applications
Yu, Xinghuo; Chen, Guanrong; Yu, Wenwu
2016-01-01
This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of ...
Directory of Open Access Journals (Sweden)
Kyung Ah Koo
2015-04-01
Full Text Available Alpine, subalpine and boreal tree species, of low genetic diversity and adapted to low optimal temperatures, are vulnerable to the warming effects of global climate change. The accurate prediction of these species’ distributions in response to climate change is critical for effective planning and management. The goal of this research is to predict climate change effects on the distribution of red spruce (Picea rubens Sarg. in the Great Smoky Mountains National Park (GSMNP, eastern USA. Climate change is, however, conflated with other environmental factors, making its assessment a complex systems problem in which indirect effects are significant in causality. Predictions were made by linking a tree growth simulation model, red spruce growth model (ARIM.SIM, to a GIS spatial model, red spruce habitat model (ARIM.HAB. ARIM.SIM quantifies direct and indirect interactions between red spruce and its growth factors, revealing the latter to be dominant. ARIM.HAB spatially distributes the ARIM.SIM simulations under the assumption that greater growth reflects higher probabilities of presence. ARIM.HAB predicts the future habitat suitability of red spruce based on growth predictions of ARIM.SIM under climate change and three air pollution scenarios: 10% increase, no change and 10% decrease. Results show that suitable habitats shrink most when air pollution increases. Higher temperatures cause losses of most low-elevation habitats. Increased precipitation and air pollution produce acid rain, which causes loss of both low- and high-elevation habitats. The general prediction is that climate change will cause contraction of red spruce habitats at both lower and higher elevations in GSMNP, and the effects will be exacerbated by increased air pollution. These predictions provide valuable information for understanding potential impacts of global climate change on the spatiotemporal distribution of red spruce habitats in GSMNP.
Synchronization coupled systems to complex networks
Boccaletti, Stefano; del Genio, Charo I; Amann, Andreas
2018-01-01
A modern introduction to synchronization phenomena, this text presents recent discoveries and the current state of research in the field, from low-dimensional systems to complex networks. The book describes some of the main mechanisms of collective behaviour in dynamical systems, including simple coupled systems, chaotic systems, and systems of infinite-dimension. After introducing the reader to the basic concepts of nonlinear dynamics, the book explores the main synchronized states of coupled systems and describes the influence of noise and the occurrence of synchronous motion in multistable and spatially-extended systems. Finally, the authors discuss the underlying principles of collective dynamics on complex networks, providing an understanding of how networked systems are able to function as a whole in order to process information, perform coordinated tasks, and respond collectively to external perturbations. The demonstrations, numerous illustrations and application examples will help advanced graduate s...
Large-scale computing techniques for complex system simulations
Dubitzky, Werner; Schott, Bernard
2012-01-01
Complex systems modeling and simulation approaches are being adopted in a growing number of sectors, including finance, economics, biology, astronomy, and many more. Technologies ranging from distributed computing to specialized hardware are explored and developed to address the computational requirements arising in complex systems simulations. The aim of this book is to present a representative overview of contemporary large-scale computing technologies in the context of complex systems simulations applications. The intention is to identify new research directions in this field and
Modeling OPC complexity for design for manufacturability
Gupta, Puneet; Kahng, Andrew B.; Muddu, Swamy; Nakagawa, Sam; Park, Chul-Hong
2005-11-01
Increasing design complexity in sub-90nm designs results in increased mask complexity and cost. Resolution enhancement techniques (RET) such as assist feature addition, phase shifting (attenuated PSM) and aggressive optical proximity correction (OPC) help in preserving feature fidelity in silicon but increase mask complexity and cost. Data volume increase with rise in mask complexity is becoming prohibitive for manufacturing. Mask cost is determined by mask write time and mask inspection time, which are directly related to the complexity of features printed on the mask. Aggressive RET increase complexity by adding assist features and by modifying existing features. Passing design intent to OPC has been identified as a solution for reducing mask complexity and cost in several recent works. The goal of design-aware OPC is to relax OPC tolerances of layout features to minimize mask cost, without sacrificing parametric yield. To convey optimal OPC tolerances for manufacturing, design optimization should drive OPC tolerance optimization using models of mask cost for devices and wires. Design optimization should be aware of impact of OPC correction levels on mask cost and performance of the design. This work introduces mask cost characterization (MCC) that quantifies OPC complexity, measured in terms of fracture count of the mask, for different OPC tolerances. MCC with different OPC tolerances is a critical step in linking design and manufacturing. In this paper, we present a MCC methodology that provides models of fracture count of standard cells and wire patterns for use in design optimization. MCC cannot be performed by designers as they do not have access to foundry OPC recipes and RET tools. To build a fracture count model, we perform OPC and fracturing on a limited set of standard cells and wire configurations with all tolerance combinations. Separately, we identify the characteristics of the layout that impact fracture count. Based on the fracture count (FC) data
Summer School Mathematical Foundations of Complex Networked Information Systems
Fosson, Sophie; Ravazzi, Chiara
2015-01-01
Introducing the reader to the mathematics beyond complex networked systems, these lecture notes investigate graph theory, graphical models, and methods from statistical physics. Complex networked systems play a fundamental role in our society, both in everyday life and in scientific research, with applications ranging from physics and biology to economics and finance. The book is self-contained, and requires only an undergraduate mathematical background.
Documentation Driven Development for Complex Real-Time Systems
2004-12-01
This paper presents a novel approach for development of complex real - time systems , called the documentation-driven development (DDD) approach. This... time systems . DDD will also support automated software generation based on a computational model and some relevant techniques. DDD includes two main...stakeholders to be easily involved in development processes and, therefore, significantly improve the agility of software development for complex real
Recording information on protein complexes in an information management system.
Savitsky, Marc; Diprose, Jonathan M; Morris, Chris; Griffiths, Susanne L; Daniel, Edward; Lin, Bill; Daenke, Susan; Bishop, Benjamin; Siebold, Christian; Wilson, Keith S; Blake, Richard; Stuart, David I; Esnouf, Robert M
2011-08-01
The Protein Information Management System (PiMS) is a laboratory information management system (LIMS) designed for use with the production of proteins in a research environment. The software is distributed under the CCP4 licence, and so is available free of charge to academic laboratories. Like most LIMS, the underlying PiMS data model originally had no support for protein-protein complexes. To support the SPINE2-Complexes project the developers have extended PiMS to meet these requirements. The modifications to PiMS, described here, include data model changes, additional protocols, some user interface changes and functionality to detect when an experiment may have formed a complex. Example data are shown for the production of a crystal of a protein complex. Integration with SPINE2-Complexes Target Tracker application is also described. Copyright © 2011 Elsevier Inc. All rights reserved.
Design tools for complex dynamic security systems.
Energy Technology Data Exchange (ETDEWEB)
Byrne, Raymond Harry; Rigdon, James Brian; Rohrer, Brandon Robinson; Laguna, Glenn A.; Robinett, Rush D. III (.; ); Groom, Kenneth Neal; Wilson, David Gerald; Bickerstaff, Robert J.; Harrington, John J.
2007-01-01
The development of tools for complex dynamic security systems is not a straight forward engineering task but, rather, a scientific task where discovery of new scientific principles and math is necessary. For years, scientists have observed complex behavior but have had difficulty understanding it. Prominent examples include: insect colony organization, the stock market, molecular interactions, fractals, and emergent behavior. Engineering such systems will be an even greater challenge. This report explores four tools for engineered complex dynamic security systems: Partially Observable Markov Decision Process, Percolation Theory, Graph Theory, and Exergy/Entropy Theory. Additionally, enabling hardware technology for next generation security systems are described: a 100 node wireless sensor network, unmanned ground vehicle and unmanned aerial vehicle.
7th International Conference on Complex Systems Design & Management
Goubault, Eric; Krob, Daniel; Stephan, François
2017-01-01
This book contains all refereed papers that were accepted to the seventh edition of the international conference « Complex Systems Design & Management Paris» (CSD&M Paris 2016) which took place in Paris (France) on the December 13-14, 2016 These proceedings cover the most recent trends in the emerging field of complex systems sciences & practices from an industrial and academic perspective, including the main industrial domains (aeronautic & aerospace, defense & security, electronics & robotics, energy & environment, healthcare & welfare services, software & e-services, transportation), scientific & technical topics (systems fundamentals, systems architecture & engineering, systems metrics & quality, system is modeling tools) and system types (artificial ecosystems, embedded systems, software & information systems, systems of systems, transportation systems). The CSD&M Paris 2016 conference is organized under the guidance of the CESAMES non-profit orga...
6th International Conference on Complex Systems Design & Management
Bocquet, Jean-Claude; Bonjour, Eric; Krob, Daniel
2016-01-01
This book contains all refereed papers that were accepted to the sixth edition of the « Complex Systems Design & Management Paris » (CSD&M Paris 2015) international conference which took place in Paris (France) on November 23-25, 2015. These proceedings cover the most recent trends in the emerging field of complex systems sciences & practices from an industrial and academic perspective, including the main industrial domains (aeronautics & aerospace, defense & security, electronics & robotics, energy & environment, health & welfare, software & e-services, transportation), scientific & technical topics (systems fundamentals, systems architecture & engineering, systems metrics & quality, systems modeling tools) and systems types (artificial ecosystems, embedded systems, software & information systems, systems of systems, transportation systems). The CSD&M Paris 2015 conference is organized under the guidance of the CESAMES non-profit organization, address...
Atomic switch networks as complex adaptive systems
Scharnhorst, Kelsey S.; Carbajal, Juan P.; Aguilera, Renato C.; Sandouk, Eric J.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.
2018-03-01
Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.
What is complex in the complex world? Niklas Luhmann and the theory of social systems
Directory of Open Access Journals (Sweden)
Clarissa Eckert Baeta Neves
Full Text Available This paper discusses Niklas Luhmann's understanding of complexity, its function in the theory and the different ways of its use. It starts with the paradigmatic change that occurred in the field of general Science, with the rupture of the Newtonian model. In the 20th century, the paradigm of order, symmetry, regularity, regulation of the intellect to things, collapses.Based on new formulations of Physics, Chemistry, etc., a new universe is built on bases radically opposed to those of modern Science.Chaos, the procedural irreversibility, indeterminism, the observer and the complexity are rehabilitated.This new conceptual context served as substratum to Niklas Luhmann's theoretical reflection.With his Theory of Social Systems, he proposes the reduction of the world's complexity.Social systems have the function of reducing complexity because of their difference in relation to the environment.On the other hand, the reduction of complexity also creates its own complexity. Luhmann defines complexity as the moment when it is not possible anymore for each element to relate at any moment with all the others. Complexity forces the selection, what means contingency and risk. Luhmann expands the concept of complexity when he introduces the figure of the observer and the distinction of complexity as a unit of a multiplicity. He also deals with the limit of relations in connection, the time factor, the self-reference of operations and the representation of complexity in the form of sense. To conclude, the paper discusses the complexity in the system of science, the way it reduces internal and external complexity, in accordance in its own operative basis.
Minimum-complexity helicopter simulation math model
Heffley, Robert K.; Mnich, Marc A.
1988-01-01
An example of a minimal complexity simulation helicopter math model is presented. Motivating factors are the computational delays, cost, and inflexibility of the very sophisticated math models now in common use. A helicopter model form is given which addresses each of these factors and provides better engineering understanding of the specific handling qualities features which are apparent to the simulator pilot. The technical approach begins with specification of features which are to be modeled, followed by a build up of individual vehicle components and definition of equations. Model matching and estimation procedures are given which enable the modeling of specific helicopters from basic data sources such as flight manuals. Checkout procedures are given which provide for total model validation. A number of possible model extensions and refinement are discussed. Math model computer programs are defined and listed.
Radwaste treatment complex. DRAWMACS planned maintenance system
International Nuclear Information System (INIS)
Keel, A.J.
1992-07-01
This document describes the operation of the Planned Maintenance System for the Radwaste Treatment Complex. The Planned Maintenance System forms part of the Decommissioning and Radwaste Management Computer System (DRAWMACS). Further detailed information about the data structure of the system is contained in Database Design for the DRAWMACS Planned Maintenance System (AEA-D and R-0285, 2nd issue, 25th February 1992). Information for other components of DRAWMACS is contained in Basic User Guide for the Radwaste Treatment Plant Computer System (AEA-D and R-0019, July 1990). (author)
The self as a complex dynamic system
Directory of Open Access Journals (Sweden)
Sarah Mercer
2011-04-01
Full Text Available This article explores the potential offered by complexity theories for understanding language learners’ sense of self and attempts to show how the self might usefully be conceived of as a complex dynamic system. Rather than presenting empirical findings, the article discusses existent research on the self and aims at outlining a conceptual perspective that may inform future studies into the self and possibly other individual learner differences. The article concludes by critically considering the merits of a complexity perspective but also reflecting on the challenges it poses for research.
Modeling and estimating system availability
International Nuclear Information System (INIS)
Gaver, D.P.; Chu, B.B.
1976-11-01
Mathematical models to infer the availability of various types of more or less complicated systems are described. The analyses presented are probabilistic in nature and consist of three parts: a presentation of various analytic models for availability; a means of deriving approximate probability limits on system availability; and a means of statistical inference of system availability from sparse data, using a jackknife procedure. Various low-order redundant systems are used as examples, but extension to more complex systems is not difficult
On spin and matrix models in the complex plane
International Nuclear Information System (INIS)
Damgaard, P.H.; Heller, U.M.
1993-01-01
We describe various aspects of statistical mechanics defined in the complex temperature or coupling-constant plane. Using exactly solvable models, we analyse such aspects as renormalization group flows in the complex plane, the distribution of partition function zeros, and the question of new coupling-constant symmetries of complex-plane spin models. The double-scaling form of matrix models is shown to be exactly equivalent to finite-size scaling of two-dimensional spin systems. This is used to show that the string susceptibility exponents derived from matrix models can be obtained numerically with very high accuracy from the scaling of finite-N partition function zeros in the complex plane. (orig.)
Third International Conference on Complex Systems
Minai, Ali A; Unifying Themes in Complex Systems
2006-01-01
In recent years, scientists have applied the principles of complex systems science to increasingly diverse fields. The results have been nothing short of remarkable: their novel approaches have provided answers to long-standing questions in biology, ecology, physics, engineering, computer science, economics, psychology and sociology. The Third International Conference on Complex Systems attracted over 400 researchers from around the world. The conference aimed to encourage cross-fertilization between the many disciplines represented and to deepen our understanding of the properties common to all complex systems. This volume contains selected transcripts from presentations given at the conference. Speakers include: Chris Adami, Kenneth Arrow, Michel Baranger, Dan Braha, Timothy Buchman, Michael Caramanis, Kathleen Carley, Greg Chaitin, David Clark, Jack Cohen, Jim Collins, George Cowan, Clay Easterly, Steven Eppinger, Irving Epstein, Dan Frey, Ary Goldberger, Helen Harte, Leroy Hood, Don Ingber, Atlee Jackson,...
Systems thinking and complexity: considerations for health promoting schools.
Rosas, Scott R
2017-04-01
The health promoting schools concept reflects a comprehensive and integrated philosophy to improving student and personnel health and well-being. Conceptualized as a configuration of interacting, interdependent parts connected through a web of relationships that form a whole greater than the sum of its parts, school health promotion initiatives often target several levels (e.g. individual, professional, procedural and policy) simultaneously. Health promoting initiatives, such as those operationalized under the whole school approach, include several interconnected components that are coordinated to improve health outcomes in complex settings. These complex systems interventions are embedded in intricate arrangements of physical, biological, ecological, social, political and organizational relationships. Systems thinking and characteristics of complex adaptive systems are introduced in this article to provide a perspective that emphasizes the patterns of inter-relationships associated with the nonlinear, dynamic and adaptive nature of complex hierarchical systems. Four systems thinking areas: knowledge, networks, models and organizing are explored as a means to further manage the complex nature of the development and sustainability of health promoting schools. Applying systems thinking and insights about complex adaptive systems can illuminate how to address challenges found in settings with both complicated (i.e. multi-level and multisite) and complex aspects (i.e. synergistic processes and emergent outcomes). © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Reliability assessment of complex electromechanical systems under epistemic uncertainty
International Nuclear Information System (INIS)
Mi, Jinhua; Li, Yan-Feng; Yang, Yuan-Jian; Peng, Weiwen; Huang, Hong-Zhong
2016-01-01
The appearance of macro-engineering and mega-project have led to the increasing complexity of modern electromechanical systems (EMSs). The complexity of the system structure and failure mechanism makes it more difficult for reliability assessment of these systems. Uncertainty, dynamic and nonlinearity characteristics always exist in engineering systems due to the complexity introduced by the changing environments, lack of data and random interference. This paper presents a comprehensive study on the reliability assessment of complex systems. In view of the dynamic characteristics within the system, it makes use of the advantages of the dynamic fault tree (DFT) for characterizing system behaviors. The lifetime of system units can be expressed as bounded closed intervals by incorporating field failures, test data and design expertize. Then the coefficient of variation (COV) method is employed to estimate the parameters of life distributions. An extended probability-box (P-Box) is proposed to convey the present of epistemic uncertainty induced by the incomplete information about the data. By mapping the DFT into an equivalent Bayesian network (BN), relevant reliability parameters and indexes have been calculated. Furthermore, the Monte Carlo (MC) simulation method is utilized to compute the DFT model with consideration of system replacement policy. The results show that this integrated approach is more flexible and effective for assessing the reliability of complex dynamic systems. - Highlights: • A comprehensive study on the reliability assessment of complex system is presented. • An extended probability-box is proposed to convey the present of epistemic uncertainty. • The dynamic fault tree model is built. • Bayesian network and Monte Carlo simulation methods are used. • The reliability assessment of a complex electromechanical system is performed.
Application of functional derivatives to analysis of complex systems
Czech Academy of Sciences Publication Activity Database
Beran, Zdeněk; Čelikovský, Sergej
2013-01-01
Roč. 350, č. 10 (2013), s. 2982-2993 ISSN 0016-0032 R&D Projects: GA ČR GA13-20433S Institutional support: RVO:67985556 Keywords : complex systems * linear equation * modeling Subject RIV: BC - Control Systems Theory Impact factor: 2.260, year: 2013 http://library.utia.cas.cz/separaty/2013/TR/beran-0398123.pdf
Directory of Open Access Journals (Sweden)
Tammy E Foster
Full Text Available Society needs information about how vegetation communities in coastal regions will be impacted by hydrologic changes associated with climate change, particularly sea level rise. Due to anthropogenic influences which have significantly decreased natural coastal vegetation communities, it is important for us to understand how remaining natural communities will respond to sea level rise. The Cape Canaveral Barrier Island complex (CCBIC on the east central coast of Florida is within one of the most biologically diverse estuarine systems in North America and has the largest number of threatened and endangered species on federal property in the contiguous United States. The high level of biodiversity is susceptible to sea level rise. Our objective was to model how vegetation communities along a gradient ranging from hydric to upland xeric on CCBIC will respond to three sea level rise scenarios (0.2 m, 0.4 m, and 1.2 m. We used a probabilistic model of the current relationship between elevation and vegetation community to determine the impact sea level rise would have on these communities. Our model correctly predicted the current proportions of vegetation communities on CCBIC based on elevation. Under all sea level rise scenarios the model predicted decreases in mesic and xeric communities, with the greatest losses occurring in the most xeric communities. Increases in total area of salt marsh were predicted with a 0.2 and 0.4 m rise in sea level. With a 1.2 m rise in sea level approximately half of CCBIC's land area was predicted to transition to open water. On the remaining land, the proportions of most of the vegetation communities were predicted to remain similar to that of current proportions, but there was a decrease in proportion of the most xeric community (oak scrub and an increase in the most hydric community (salt marsh. Our approach provides a first approximation of the impacts of sea level rise on terrestrial vegetation communities
Foster, Tammy E; Stolen, Eric D; Hall, Carlton R; Schaub, Ronald; Duncan, Brean W; Hunt, Danny K; Drese, John H
2017-01-01
Society needs information about how vegetation communities in coastal regions will be impacted by hydrologic changes associated with climate change, particularly sea level rise. Due to anthropogenic influences which have significantly decreased natural coastal vegetation communities, it is important for us to understand how remaining natural communities will respond to sea level rise. The Cape Canaveral Barrier Island complex (CCBIC) on the east central coast of Florida is within one of the most biologically diverse estuarine systems in North America and has the largest number of threatened and endangered species on federal property in the contiguous United States. The high level of biodiversity is susceptible to sea level rise. Our objective was to model how vegetation communities along a gradient ranging from hydric to upland xeric on CCBIC will respond to three sea level rise scenarios (0.2 m, 0.4 m, and 1.2 m). We used a probabilistic model of the current relationship between elevation and vegetation community to determine the impact sea level rise would have on these communities. Our model correctly predicted the current proportions of vegetation communities on CCBIC based on elevation. Under all sea level rise scenarios the model predicted decreases in mesic and xeric communities, with the greatest losses occurring in the most xeric communities. Increases in total area of salt marsh were predicted with a 0.2 and 0.4 m rise in sea level. With a 1.2 m rise in sea level approximately half of CCBIC's land area was predicted to transition to open water. On the remaining land, the proportions of most of the vegetation communities were predicted to remain similar to that of current proportions, but there was a decrease in proportion of the most xeric community (oak scrub) and an increase in the most hydric community (salt marsh). Our approach provides a first approximation of the impacts of sea level rise on terrestrial vegetation communities, including important
Modeling Sustainable Food Systems.
Allen, Thomas; Prosperi, Paolo
2016-05-01
The processes underlying environmental, economic, and social unsustainability derive in part from the food system. Building sustainable food systems has become a predominating endeavor aiming to redirect our food systems and policies towards better-adjusted goals and improved societal welfare. Food systems are complex social-ecological systems involving multiple interactions between human and natural components. Policy needs to encourage public perception of humanity and nature as interdependent and interacting. The systemic nature of these interdependencies and interactions calls for systems approaches and integrated assessment tools. Identifying and modeling the intrinsic properties of the food system that will ensure its essential outcomes are maintained or enhanced over time and across generations, will help organizations and governmental institutions to track progress towards sustainability, and set policies that encourage positive transformations. This paper proposes a conceptual model that articulates crucial vulnerability and resilience factors to global environmental and socio-economic changes, postulating specific food and nutrition security issues as priority outcomes of food systems. By acknowledging the systemic nature of sustainability, this approach allows consideration of causal factor dynamics. In a stepwise approach, a logical application is schematized for three Mediterranean countries, namely Spain, France, and Italy.
Geometric Modelling with a-Complexes
Gerritsen, B.H.M.; Werff, K. van der; Veltkamp, R.C.
2001-01-01
The shape of real objects can be so complicated, that only a sampling data point set can accurately represent them. Analytic descriptions are too complicated or impossible. Natural objects, for example, can be vague and rough with many holes. For this kind of modelling, a-complexes offer advantages
A cognitive model for software architecture complexity
Bouwers, E.; Lilienthal, C.; Visser, J.; Van Deursen, A.
2010-01-01
Evaluating the complexity of the architecture of a softwaresystem is a difficult task. Many aspects have to be considered to come to a balanced assessment. Several architecture evaluation methods have been proposed, but very few define a quality model to be used during the evaluation process. In
Understanding Complex Construction Systems Through Modularity
DEFF Research Database (Denmark)
Jensen, Tor Clarke; Bekdik, Baris; Thuesen, Christian
2014-01-01
This paper develops a framework for understanding complexity in construction projects by combining theories of complexity management and modularization. The framework incorporates three dimensions of product, process, and organizational modularity with the case of gypsum wall elements. The analysis...... system, rather than a modular, although the industry forces modular organizational structures. This creates a high complexity degree caused by the non-alignment of building parts and organizations and the frequent swapping of modules....... finds that the main driver of complexity is the fragmentation of the design and production, which causes the production modules to construct and install new product types and variants for each project as the designers are swapped for every project. The many interfaces are characteristics of an integral...
Methodology for Measuring the Complexity of Enterprise Information Systems
Directory of Open Access Journals (Sweden)
Ilja Holub
2016-07-01
Full Text Available The complexity of enterprise information systems is currently a challenge faced not only by IT professionals and project managers, but also by the users of such systems. Current methodologies and frameworks used to design and implement information systems do not specifically deal with the issue of their complexity and, apart from few exceptions, do not at all attempt to simplify the complexity. This article presents the author's own methodology for managing complexity, which can be used to complement any other methodology and which helps limit the growth of complexity. It introduces its own definition and metric of complexity, which it defines as the sum of entities of the individual UML models of the given system, which are selected according to the MMDIS methodology so as to consistently describe all relevant content dimensions of the system. The main objective is to propose a methodology to manage information system complexity and to verify it in practice on a real-life SAP implementation project.
Statistical physics of complex systems a concise introduction
Bertin, Eric
2016-01-01
This course-tested primer provides graduate students and non-specialists with a basic understanding of the concepts and methods of statistical physics and demonstrates their wide range of applications to interdisciplinary topics in the field of complex system sciences, including selected aspects of theoretical modeling in biology and the social sciences. Generally speaking, the goals of statistical physics may be summarized as follows: on the one hand to study systems composed of a large number of interacting units, and on the other to predict the macroscopic, collective behavior of the system considered from the perspective of the microscopic laws governing the dynamics of the individual entities. These two goals are essentially also shared by what is now called 'complex systems science', and as such, systems studied in the framework of statistical physics may be considered to be among the simplest examples of complex systems – while also offering a rather well developed mathematical treatment. The second ...
Comparing flood loss models of different complexity
Schröter, Kai; Kreibich, Heidi; Vogel, Kristin; Riggelsen, Carsten; Scherbaum, Frank; Merz, Bruno
2013-04-01
Any deliberation on flood risk requires the consideration of potential flood losses. In particular, reliable flood loss models are needed to evaluate cost-effectiveness of mitigation measures, to assess vulnerability, for comparative risk analysis and financial appraisal during and after floods. In recent years, considerable improvements have been made both concerning the data basis and the methodological approaches used for the development of flood loss models. Despite of that, flood loss models remain an important source of uncertainty. Likewise the temporal and spatial transferability of flood loss models is still limited. This contribution investigates the predictive capability of different flood loss models in a split sample cross regional validation approach. For this purpose, flood loss models of different complexity, i.e. based on different numbers of explaining variables, are learned from a set of damage records that was obtained from a survey after the Elbe flood in 2002. The validation of model predictions is carried out for different flood events in the Elbe and Danube river basins in 2002, 2005 and 2006 for which damage records are available from surveys after the flood events. The models investigated are a stage-damage model, the rule based model FLEMOps+r as well as novel model approaches which are derived using data mining techniques of regression trees and Bayesian networks. The Bayesian network approach to flood loss modelling provides attractive additional information concerning the probability distribution of both model predictions and explaining variables.
Complex and adaptive dynamical systems a primer
Gros, Claudius
2015-01-01
This primer offers readers an introduction to the central concepts that form our modern understanding of complex and emergent behavior, together with detailed coverage of accompanying mathematical methods. All calculations are presented step by step and are easy to follow. This new fourth edition has been fully reorganized and includes new chapters, figures and exercises. The core aspects of modern complex system sciences are presented in the first chapters, covering network theory, dynamical systems, bifurcation and catastrophe theory, chaos and adaptive processes, together with the principle of self-organization in reaction-diffusion systems and social animals. Modern information theoretical principles are treated in further chapters, together with the concept of self-organized criticality, gene regulation networks, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase transitions and the cognitive system approach to the brain. Technical course prerequisites are the standard ...
Managing interoperability and complexity in health systems.
Bouamrane, M-M; Tao, C; Sarkar, I N
2015-01-01
In recent years, we have witnessed substantial progress in the use of clinical informatics systems to support clinicians during episodes of care, manage specialised domain knowledge, perform complex clinical data analysis and improve the management of health organisations' resources. However, the vision of fully integrated health information eco-systems, which provide relevant information and useful knowledge at the point-of-care, remains elusive. This journal Focus Theme reviews some of the enduring challenges of interoperability and complexity in clinical informatics systems. Furthermore, a range of approaches are proposed in order to address, harness and resolve some of the many remaining issues towards a greater integration of health information systems and extraction of useful or new knowledge from heterogeneous electronic data repositories.
Energy Technology Data Exchange (ETDEWEB)
Chang, Y.H.J. [Center for Risk and Reliability, University of Maryland, College Park, MD 20742 (United States) and Paul Scherrer Institute, 5232 Villigen PSI (Switzerland)]. E-mail: yhc@umd.edu; Mosleh, A. [Center for Risk and Reliability, University of Maryland, College Park, MD 20742 (United States)
2007-08-15
This is the fourth in a series of five papers describing the Information, Decision, and Action in Crew context (IDAC) operator response model for human reliability analysis. An example application of this modeling technique is also discussed in this series. The model has been developed to probabilistically predicts the responses of a nuclear power plant control room operating crew in accident conditions. The operator response spectrum includes cognitive, emotional, and physical activities during the course of an accident. This paper assesses the effects of the performance-influencing factors (PIFs) affecting the operators' problem-solving responses including information pre-processing (I), diagnosis and decision making (D), and action execution (A). Literature support and justifications are provided for the assessment on the influences of PIFs.
International Nuclear Information System (INIS)
Chang, Y.H.J.; Mosleh, A.
2007-01-01
This is the fourth in a series of five papers describing the Information, Decision, and Action in Crew context (IDAC) operator response model for human reliability analysis. An example application of this modeling technique is also discussed in this series. The model has been developed to probabilistically predicts the responses of a nuclear power plant control room operating crew in accident conditions. The operator response spectrum includes cognitive, emotional, and physical activities during the course of an accident. This paper assesses the effects of the performance-influencing factors (PIFs) affecting the operators' problem-solving responses including information pre-processing (I), diagnosis and decision making (D), and action execution (A). Literature support and justifications are provided for the assessment on the influences of PIFs
On complex adaptive systems and terrorism
International Nuclear Information System (INIS)
Ahmed, E.; Elgazzar, A.S.; Hegazi, A.S.
2005-01-01
Complex adaptive systems (CAS) are ubiquitous in nature. They are basic in social sciences. An overview of CAS is given with emphasize on the occurrence of bad side effects to seemingly 'wise' decisions. Hence application to terrorism is given. Some conclusions on how to deal with this phenomena are proposed
Engineering Education as a Complex System
Gattie, David K.; Kellam, Nadia N.; Schramski, John R.; Walther, Joachim
2011-01-01
This paper presents a theoretical basis for cultivating engineering education as a complex system that will prepare students to think critically and make decisions with regard to poorly understood, ill-structured issues. Integral to this theoretical basis is a solution space construct developed and presented as a benchmark for evaluating…
Ensemble annealing of complex physical systems
Habeck, Michael
2015-01-01
Algorithms for simulating complex physical systems or solving difficult optimization problems often resort to an annealing process. Rather than simulating the system at the temperature of interest, an annealing algorithm starts at a temperature that is high enough to ensure ergodicity and gradually decreases it until the destination temperature is reached. This idea is used in popular algorithms such as parallel tempering and simulated annealing. A general problem with annealing methods is th...
Modeling of anaerobic digestion of complex substrates
International Nuclear Information System (INIS)
Keshtkar, A. R.; Abolhamd, G.; Meyssami, B.; Ghaforian, H.
2003-01-01
A structured mathematical model of anaerobic conversion of complex organic materials in non-ideally cyclic-batch reactors for biogas production has been developed. The model is based on multiple-reaction stoichiometry (enzymatic hydrolysis, acidogenesis, aceto genesis and methano genesis), microbial growth kinetics, conventional material balances in the liquid and gas phases for a cyclic-batch reactor, liquid-gas interactions, liquid-phase equilibrium reactions and a simple mixing model which considers the reactor volume in two separate sections: the flow-through and the retention regions. The dynamic model describes the effects of reactant's distribution resulting from the mixing conditions, time interval of feeding, hydraulic retention time and mixing parameters on the process performance. The model is applied in the simulation of anaerobic digestion of cattle manure under different operating conditions. The model is compared with experimental data and good correlations are obtained
International Nuclear Information System (INIS)
Chang, Y.H.J.; Mosleh, A.
2007-01-01
This is the second in a series of five papers describing the information, decision, and action in crew context (IDAC) model for human reliability analysis. An example application of this modeling technique is also discussed in this series. The model is developed to probabilistically predict the responses of the nuclear power plant control room operating crew in accident conditions. The operator response spectrum includes cognitive, psychological, and physical activities during the course of an accident. This paper identifies the IDAC set of performance influencing factors (PIFs), providing their definitions and causal organization in the form of a modular influence diagram. Fifty PIFs are identified to support the IDAC model to be implemented in a computer simulation environment. They are classified into eleven hierarchically structured groups. The PIFs within each group are independent to each other; however, dependencies may exist between PIFs within different groups. The supporting evidence for the selection and organization of the influence paths based on psychological literature, observations, and various human reliability analysis methodologies is also indicated
Complex adaptative systems and computational simulation in Archaeology
Directory of Open Access Journals (Sweden)
Salvador Pardo-Gordó
2017-07-01
Full Text Available Traditionally the concept of ‘complexity’ is used as a synonym for ‘complex society’, i.e., human groups with characteristics such as urbanism, inequalities, and hierarchy. The introduction of Nonlinear Systems and Complex Adaptive Systems to the discipline of archaeology has nuanced this concept. This theoretical turn has led to the rise of modelling as a method of analysis of historical processes. This work has a twofold objective: to present the theoretical current characterized by generative thinking in archaeology and to present a concrete application of agent-based modelling to an archaeological problem: the dispersal of the first ceramic production in the western Mediterranean.
DEFF Research Database (Denmark)
Fernández, Elena; Vårdal, Linda; Vidal, Lorena
2017-01-01
Complexation-mediated electromembrane extraction (EME) of highly polar basic drugs (log P ... as complexation reagent, and selectively formed boronate esters by reversible covalent binding with the model analytes at the sample/SLM interface. This enhanced the mass transfer of the highly polar model analytes across the SLM, and EME of basic drugs with log P in the range -1 to -2 was shown for the first...... chromatography coupled to tandem mass spectrometry and evaluated for quantification of epinephrine and dopamine. Standard addition calibration was applied to a pooled human urine sample. Calibration curves using standards between 25 and 125 μg L-1 gave a high level of linearity with a correlation coefficient...
A Multifaceted Mathematical Approach for Complex Systems
Energy Technology Data Exchange (ETDEWEB)
Alexander, F.; Anitescu, M.; Bell, J.; Brown, D.; Ferris, M.; Luskin, M.; Mehrotra, S.; Moser, B.; Pinar, A.; Tartakovsky, A.; Willcox, K.; Wright, S.; Zavala, V.
2012-03-07
Applied mathematics has an important role to play in developing the tools needed for the analysis, simulation, and optimization of complex problems. These efforts require the development of the mathematical foundations for scientific discovery, engineering design, and risk analysis based on a sound integrated approach for the understanding of complex systems. However, maximizing the impact of applied mathematics on these challenges requires a novel perspective on approaching the mathematical enterprise. Previous reports that have surveyed the DOE's research needs in applied mathematics have played a key role in defining research directions with the community. Although these reports have had significant impact, accurately assessing current research needs requires an evaluation of today's challenges against the backdrop of recent advances in applied mathematics and computing. To address these needs, the DOE Applied Mathematics Program sponsored a Workshop for Mathematics for the Analysis, Simulation and Optimization of Complex Systems on September 13-14, 2011. The workshop had approximately 50 participants from both the national labs and academia. The goal of the workshop was to identify new research areas in applied mathematics that will complement and enhance the existing DOE ASCR Applied Mathematics Program efforts that are needed to address problems associated with complex systems. This report describes recommendations from the workshop and subsequent analysis of the workshop findings by the organizing committee.
A Practical Philosophy of Complex Climate Modelling
Schmidt, Gavin A.; Sherwood, Steven
2014-01-01
We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project (CMIP).We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naive predictions. The framework we use for making inferences about reality using simulations is naturally Bayesian (in an informal sense), and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work.
Complexity, Analysis and Control of Singular Biological Systems
Zhang, Qingling; Zhang, Xue
2012-01-01
Complexity, Analysis and Control of Singular Biological Systems follows the control of real-world biological systems at both ecological and phyisological levels concentrating on the application of now-extensively-investigated singular system theory. Much effort has recently been dedicated to the modelling and analysis of developing bioeconomic systems and the text establishes singular examples of these, showing how proper control can help to maintain sustainable economic development of biological resources. The book begins from the essentials of singular systems theory and bifurcations before tackling the use of various forms of control in singular biological systems using examples including predator-prey relationships and viral vaccination and quarantine control. Researchers and graduate students studying the control of complex biological systems are shown how a variety of methods can be brought to bear and practitioners working with the economics of biological systems and their control will also find the ...
Different Epidemic Models on Complex Networks
International Nuclear Information System (INIS)
Zhang Haifeng; Small, Michael; Fu Xinchu
2009-01-01
Models for diseases spreading are not just limited to SIS or SIR. For instance, for the spreading of AIDS/HIV, the susceptible individuals can be classified into different cases according to their immunity, and similarly, the infected individuals can be sorted into different classes according to their infectivity. Moreover, some diseases may develop through several stages. Many authors have shown that the individuals' relation can be viewed as a complex network. So in this paper, in order to better explain the dynamical behavior of epidemics, we consider different epidemic models on complex networks, and obtain the epidemic threshold for each case. Finally, we present numerical simulations for each case to verify our results.
Complex Constructivism: A Theoretical Model of Complexity and Cognition
Doolittle, Peter E.
2014-01-01
Education has long been driven by its metaphors for teaching and learning. These metaphors have influenced both educational research and educational practice. Complexity and constructivism are two theories that provide functional and robust metaphors. Complexity provides a metaphor for the structure of myriad phenomena, while constructivism…
Cosmic Ray Neutron Sensing in Complex Systems
Piussi, L. M.; Tomelleri, E.; Tonon, G.; Bertoldi, G.; Mejia Aguilar, A.; Monsorno, R.; Zebisch, M.
2017-12-01
Soil moisture is a key variable in environmental monitoring and modelling: being located at the soil-atmosphere boundary, it is a driving force for water, energy and carbon fluxes. Nevertheless its importance, soil moisture observations lack of long time-series at high acquisition frequency in spatial meso-scale resolutions: traditional measurements deliver either long time series with high measurement frequency at spatial point scale or large scale and low frequency acquisitions. The Cosmic Ray Neutron Sensing (CRNS) technique fills this gap because it supplies information from a footprint of 240m of diameter and 15 to 83 cm of depth at a temporal resolution varying between 15 minutes and 24 hours. In addition, being a passive sensing technique, it is non-invasive. For these reasons, CRNS is gaining more and more attention from the scientific community. Nevertheless, the application of this technique in complex systems is still an open issue: where different Hydrogen pools are present and where their distributions vary appreciably with space and time, the traditional calibration method shows some limits. In order to obtain a better understanding of the data and to compare them with remote sensing products and spatially distributed traditional measurements (i.e. Wireless Sensors Network), the complexity of the surrounding environment has to be taken into account. In the current work we assessed the effects of spatial-temporal variability of soil moisture within the footprint, in a steep, heterogeneous mountain grassland area. Measurement were performed with a Cosmic Ray Neutron Probe (CRNP) and a mobile Wireless Sensors Network. We performed an in-deep sensitivity analysis of the effects of varying distributions of soil moisture on the calibration of the CRNP and our preliminary results show how the footprint shape varies depending on these dynamics. The results are then compared with remote sensing data (Sentinel 1 and 2). The current work is an assessment of
Caseau, Yves; Krob, Daniel; Rauzy, Antoine
2013-01-01
This book contains all refereed papers that were accepted to the third edition of the « Complex Systems Design & Management » (CSD&M 2012) international conference that took place in Paris (France) from December 12-14, 2012. (Website: http://www.csdm2012.csdm.fr) These proceedings cover the most recent trends in the emerging field of complex systems sciences & practices from an industrial and academic perspective, including the main industrial domains (transport, defense & security, electronics, energy & environment, e-services), scientific & technical topics (systems fundamentals, systems architecture& engineering, systems metrics & quality, systemic tools) and system types (transportation systems, embedded systems, software & information systems, systems of systems, artificial ecosystems). The CSD&M 2012 conference is organized under the guidance of the CESAMES non-profit organization (http://www.cesames.net).
Controlling Complex Systems and Developing Dynamic Technology
Avizienis, Audrius Victor
In complex systems, control and understanding become intertwined. Following Ilya Prigogine, we define complex systems as having control parameters which mediate transitions between distinct modes of dynamical behavior. From this perspective, determining the nature of control parameters and demonstrating the associated dynamical phase transitions are practically equivalent and fundamental to engaging with complexity. In the first part of this work, a control parameter is determined for a non-equilibrium electrochemical system by studying a transition in the morphology of structures produced by an electroless deposition reaction. Specifically, changing the size of copper posts used as the substrate for growing metallic silver structures by the reduction of Ag+ from solution under diffusion-limited reaction conditions causes a dynamical phase transition in the crystal growth process. For Cu posts with edge lengths on the order of one micron, local forces promoting anisotropic growth predominate, and the reaction produces interconnected networks of Ag nanowires. As the post size is increased above 10 microns, the local interfacial growth reaction dynamics couple with the macroscopic diffusion field, leading to spatially propagating instabilities in the electrochemical potential which induce periodic branching during crystal growth, producing dendritic deposits. This result is interesting both as an example of control and understanding in a complex system, and as a useful combination of top-down lithography with bottom-up electrochemical self-assembly. The second part of this work focuses on the technological development of devices fabricated using this non-equilibrium electrochemical process, towards a goal of integrating a complex network as a dynamic functional component in a neuromorphic computing device. Self-assembled networks of silver nanowires were reacted with sulfur to produce interfacial "atomic switches": silver-silver sulfide junctions, which exhibit
Complex networks under dynamic repair model
Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao
2018-01-01
Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.
Dynamics of a Simple Quantum System in a Complex Environment
Bulgac, A; Kusnezov, D; Bulgac, Aurel; Dang, Gui Do; Kusnezov, Dimitri
1998-01-01
We present a theory for the dynamical evolution of a quantum system coupled to a complex many-body intrinsic system/environment. By modelling the intrinsic many-body system with parametric random matrices, we study the types of effective stochastic models which emerge from random matrix theory. Using the Feynman-Vernon path integral formalism, we derive the influence functional and obtain either analytical or numerical solutions for the time evolution of the entire quantum system. We discuss thoroughly the structure of the solutions for some representative cases and make connections to well known limiting results, particularly to Brownian motion, Kramers classical limit and the Caldeira-Leggett approach.
Modelling and simulating in-stent restenosis with complex automata
Hoekstra, A.G.; Lawford, P.; Hose, R.
2010-01-01
In-stent restenosis, the maladaptive response of a blood vessel to injury caused by the deployment of a stent, is a multiscale system involving a large number of biological and physical processes. We describe a Complex Automata Model for in-stent restenosis, coupling bulk flow, drug diffusion, and
The dynamic complexity of a three species food chain model
International Nuclear Information System (INIS)
Lv Songjuan; Zhao Min
2008-01-01
In this paper, a three-species food chain model is analytically investigated on theories of ecology and using numerical simulation. Bifurcation diagrams are obtained for biologically feasible parameters. The results show that the system exhibits rich complexity features such as stable, periodic and chaotic dynamics
Information, complexity and efficiency: The automobile model
Energy Technology Data Exchange (ETDEWEB)
Allenby, B. [Lucent Technologies (United States)]|[Lawrence Livermore National Lab., CA (United States)
1996-08-08
The new, rapidly evolving field of industrial ecology - the objective, multidisciplinary study of industrial and economic systems and their linkages with fundamental natural systems - provides strong ground for believing that a more environmentally and economically efficient economy will be more information intensive and complex. Information and intellectual capital will be substituted for the more traditional inputs of materials and energy in producing a desirable, yet sustainable, quality of life. While at this point this remains a strong hypothesis, the evolution of the automobile industry can be used to illustrate how such substitution may, in fact, already be occurring in an environmentally and economically critical sector.
A marketing mix model for a complex and turbulent environment
Directory of Open Access Journals (Sweden)
R. B. Mason
2007-12-01
Full Text Available Purpose: This paper is based on the proposition that the choice of marketing tactics is determined, or at least significantly influenced, by the nature of the companys external environment. It aims to illustrate the type of marketing mix tactics that are suggested for a complex and turbulent environment when marketing and the environment are viewed through a chaos and complexity theory lens. Design/Methodology/Approach: Since chaos and complexity theories are proposed as a good means of understanding the dynamics of complex and turbulent markets, a comprehensive review and analysis of literature on the marketing mix and marketing tactics from a chaos and complexity viewpoint was conducted. From this literature review, a marketing mix model was conceptualised. Findings: A marketing mix model considered appropriate for success in complex and turbulent environments was developed. In such environments, the literature suggests destabilising marketing activities are more effective, whereas stabilising type activities are more effective in simple, stable environments. Therefore the model proposes predominantly destabilising type tactics as appropriate for a complex and turbulent environment such as is currently being experienced in South Africa. Implications: This paper is of benefit to marketers by emphasising a new way to consider the future marketing activities of their companies. How this model can assist marketers and suggestions for research to develop and apply this model are provided. It is hoped that the model suggested will form the basis of empirical research to test its applicability in the turbulent South African environment. Originality/Value: Since businesses and markets are complex adaptive systems, using complexity theory to understand how to cope in complex, turbulent environments is necessary, but has not been widely researched. In fact, most chaos and complexity theory work in marketing has concentrated on marketing strategy, with
Morphodynamics: Ergodic theory of complex systems
International Nuclear Information System (INIS)
Fivaz, R.
1993-01-01
Morphodynamics is a general theory of stationary complex systems, such as living systems, or mental and social systems; it is based on the thermodynamics of physical systems and built on the same lines. By means of the ergodic hypothesis, thermodynamics is known to connect the particle dynamics to the emergence of order parameters in the equations of state. In the same way, morphodynamics connects order parameters to the emergence of higher level variables; through recurrent applications of the ergodic hypothesis, a hierarchy of equations of state is established which describes a series of successive levels of organization. The equations support a cognitivist interpretation that leads to general principles of evolution; the principles determine the spontaneous and irreversible complexification of systems living in their natural environment. 19 refs
Analysis of complex systems using neural networks
International Nuclear Information System (INIS)
Uhrig, R.E.
1992-01-01
The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms), to some of the problems of complex engineering systems has the potential to enhance the safety, reliability, and operability of these systems. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network (e.g., a fast Fourier transformation of the time-series data to produce a spectral plot of the data). Specific applications described include: (1) Diagnostics: State of the Plant (2) Hybrid System for Transient Identification, (3) Sensor Validation, (4) Plant-Wide Monitoring, (5) Monitoring of Performance and Efficiency, and (6) Analysis of Vibrations. Although specific examples described deal with nuclear power plants or their subsystems, the techniques described can be applied to a wide variety of complex engineering systems
Verification and Examination Management of Complex Systems
Directory of Open Access Journals (Sweden)
Stian Ruud
2014-10-01
Full Text Available As ship systems become more complex, with an increasing number of safety-critical functions, many interconnected subsystems, tight integration to other systems, and a large amount of potential failure modes, several industry parties have identified the need for improved methods for managing the verification and examination efforts of such complex systems. Such needs are even more prominent now that the marine and offshore industries are targeting more activities and operations in the Arctic environment. In this paper, a set of requirements and a method for verification and examination management are proposed for allocating examination efforts to selected subsystems. The method is based on a definition of a verification risk function for a given system topology and given requirements. The marginal verification risks for the subsystems may then be evaluated, so that examination efforts for the subsystem can be allocated. Two cases of requirements and systems are used to demonstrate the proposed method. The method establishes a systematic relationship between the verification loss, the logic system topology, verification method performance, examination stop criterion, the required examination effort, and a proposed sequence of examinations to reach the examination stop criterion.
A Concise Introduction to the Statistical Physics of Complex Systems
Bertin, Eric
2012-01-01
This concise primer (based on lectures given at summer schools on complex systems and on a masters degree course in complex systems modeling) will provide graduate students and newcomers to the field with the basic knowledge of the concepts and methods of statistical physics and its potential for application to interdisciplinary topics. Indeed, in recent years, statistical physics has begun to attract the interest of a broad community of researchers in the field of complex system sciences, ranging from biology to the social sciences, economics and computer science. More generally, a growing number of graduate students and researchers feel the need to learn some basic concepts and questions originating in other disciplines without necessarily having to master all of the corresponding technicalities and jargon. Generally speaking, the goals of statistical physics may be summarized as follows: on the one hand to study systems composed of a large number of interacting ‘entities’, and on the other to predict...
Complex Time-Delay Systems Theory and Applications
Atay, Fatihcan M
2010-01-01
Time delays in dynamical systems arise as an inevitable consequence of finite speeds of information transmission. Realistic models increasingly demand the inclusion of delays in order to properly understand, analyze, design, and control real-life systems. The goal of this book is to present the state-of-the-art in research on time-delay dynamics in the framework of complex systems and networks. While the mathematical theory of delay equations is quite mature, its application to the particular problems of complex systems and complexity is a newly emerging field, and the present volume aims to play a pioneering role in this perspective. The chapters in this volume are authored by renowned experts and cover both theory and applications in a wide range of fields, with examples extending from neuroscience and biology to laser physics and vehicle traffic. Furthermore, all chapters include sufficient introductory material and extensive bibliographies, making the book a self-contained reference for both students and ...
Synchronization in node of complex networks consist of complex chaotic system
Energy Technology Data Exchange (ETDEWEB)
Wei, Qiang, E-mail: qiangweibeihua@163.com [Beihua University computer and technology College, BeiHua University, Jilin, 132021, Jilin (China); Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024 (China); Xie, Cheng-jun [Beihua University computer and technology College, BeiHua University, Jilin, 132021, Jilin (China); Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin (China); Liu, Hong-jun [School of Information Engineering, Weifang Vocational College, Weifang, 261041 (China); Li, Yan-hui [The Library, Weifang Vocational College, Weifang, 261041 (China)
2014-07-15
A new synchronization method is investigated for node of complex networks consists of complex chaotic system. When complex networks realize synchronization, different component of complex state variable synchronize up to different scaling complex function by a designed complex feedback controller. This paper change synchronization scaling function from real field to complex field for synchronization in node of complex networks with complex chaotic system. Synchronization in constant delay and time-varying coupling delay complex networks are investigated, respectively. Numerical simulations are provided to show the effectiveness of the proposed method.
Speciation of Zinc Mixed Ligand Complexes in Salt Water Systems ...
African Journals Online (AJOL)
Speciation of Zinc Mixed Ligand Complexes in Salt Water Systems. ... method has been used to study heavy metal interaction in model lake water in KNO3 ... is of no consequential effect because in its normal state, the [OH-] of the lake water is ...
A SIMULATION MODEL OF THE GAS COMPLEX
Directory of Open Access Journals (Sweden)
Sokolova G. E.
2016-06-01
Full Text Available The article considers the dynamics of gas production in Russia, the structure of sales in the different market segments, as well as comparative dynamics of selling prices on these segments. Problems of approach to the creation of the gas complex using a simulation model, allowing to estimate efficiency of the project and determine the stability region of the obtained solutions. In the presented model takes into account the unit repayment of the loan, allowing with the first year of simulation to determine the possibility of repayment of the loan. The model object is a group of gas fields, which is determined by the minimum flow rate above which the project is cost-effective. In determining the minimum source flow rate for the norm of discount is taken as a generalized weighted average percentage on debt and equity taking into account risk premiums. He also serves as the lower barrier to internal rate of return below which the project is rejected as ineffective. Analysis of the dynamics and methods of expert evaluation allow to determine the intervals of variation of the simulated parameters, such as the price of gas and the exit gas complex at projected capacity. Calculated using the Monte Carlo method, for each random realization of the model simulated values of parameters allow to obtain a set of optimal for each realization of values minimum yield of wells, and also allows to determine the stability region of the solution.
Complex Engineered Systems: A New Paradigm
Mina, Ali A.; Braha, Dan; Bar-Yam, Yaneer
Human history is often seen as an inexorable march towards greater complexity — in ideas, artifacts, social, political and economic systems, technology, and in the structure of life itself. While we do not have detailed knowledge of ancient times, it is reasonable to conclude that the average resident of New York City today faces a world of much greater complexity than the average denizen of Carthage or Tikal. A careful consideration of this change, however, suggests that most of it has occurred recently, and has been driven primarily by the emergence of technology as a force in human life. In the 4000 years separating the Indus Valley Civilization from 18th century Europe, human transportation evolved from the bullock cart to the hansom, and the methods of communication used by George Washington did not differ significantly from those used by Alexander or Rameses. The world has moved radically towards greater complexity in the last two centuries. We have moved from buggies and letter couriers to airplanes and the Internet — an increase in capacity, and through its diversity also in complexity, orders of magnitude greater than that accumulated through the rest of human history. In addition to creating iconic artifacts — the airplane, the car, the computer, the television, etc. — this change has had a profound effect on the scope of experience by creating massive, connected and multiultra- level systems — traffic networks, power grids, markets, multinational corporations — that defy analytical understanding and seem to have a life of their own. This is where complexity truly enters our lives.
Synchronization Experiments With A Global Coupled Model of Intermediate Complexity
Selten, Frank; Hiemstra, Paul; Shen, Mao-Lin
2013-04-01
In the super modeling approach an ensemble of imperfect models are connected through nudging terms that nudge the solution of each model to the solution of all other models in the ensemble. The goal is to obtain a synchronized state through a proper choice of connection strengths that closely tracks the trajectory of the true system. For the super modeling approach to be successful, the connections should be dense and strong enough for synchronization to occur. In this study we analyze the behavior of an ensemble of connected global atmosphere-ocean models of intermediate complexity. All atmosphere models are connected to the same ocean model through the surface fluxes of heat, water and momentum, the ocean is integrated using weighted averaged surface fluxes. In particular we analyze the degree of synchronization between the atmosphere models and the characteristics of the ensemble mean solution. The results are interpreted using a low order atmosphere-ocean toy model.
Life: An Introduction to Complex Systems Biology
Kaneko, Kunihiko
2006-01-01
What is life? Has molecular biology given us a satisfactory answer to this question? And if not, why, and how to carry on from there? This book examines life not from the reductionist point of view, but rather asks the question: what are the universal properties of living systems and how can one construct from there a phenomenological theory of life that leads naturally to complex processes such as reproductive cellular systems, evolution and differentiation? The presentation has been deliberately kept fairly non-technical so as to address a broad spectrum of students and researchers from the natural sciences and informatics.
Describing joint air defence within operations other than war context as a complex system
CSIR Research Space (South Africa)
Oosthuizen, R
2009-10-01
Full Text Available . This paper will firstly investigate the theory of complexity and identify the main characteristics. This will be applied to Systems Engineering and modelling techniques, to propose a method of implementation in the real world. The application... of complexity in warfare is discussed to form a foundation for the discussion of JAD. Finally, the sources of complexity in JAD are identified and an approach to address these proposed. 2 Complex Systems 2.1 Definition of Complex Systems The theory...
Observation-Driven Configuration of Complex Software Systems
Sage, Aled
2010-06-01
The ever-increasing complexity of software systems makes them hard to comprehend, predict and tune due to emergent properties and non-deterministic behaviour. Complexity arises from the size of software systems and the wide variety of possible operating environments: the increasing choice of platforms and communication policies leads to ever more complex performance characteristics. In addition, software systems exhibit different behaviour under different workloads. Many software systems are designed to be configurable so that policies can be chosen to meet the needs of various stakeholders. For complex software systems it can be difficult to accurately predict the effects of a change and to know which configuration is most appropriate. This thesis demonstrates that it is useful to run automated experiments that measure a selection of system configurations. Experiments can find configurations that meet the stakeholders' needs, find interesting behavioural characteristics, and help produce predictive models of the system's behaviour. The design and use of ACT (Automated Configuration Tool) for running such experiments is described, in combination a number of search strategies for deciding on the configurations to measure. Design Of Experiments (DOE) is discussed, with emphasis on Taguchi Methods. These statistical methods have been used extensively in manufacturing, but have not previously been used for configuring software systems. The novel contribution here is an industrial case study, applying the combination of ACT and Taguchi Methods to DC-Directory, a product from Data Connection Ltd (DCL). The case study investigated the applicability of Taguchi Methods for configuring complex software systems. Taguchi Methods were found to be useful for modelling and configuring DC- Directory, making them a valuable addition to the techniques available to system administrators and developers.