00000cmm a22000004a 4500 UP-99796217611272855 Buklod 20241028113429.0 m o j cr |n |||auu|a 241028s2011 gw o j eng d 9783642179464 (eBook) (iLib)UPD-00216804761 DMLR rda eng DMLUC QA 273.6 I57 2011eb Iordache, Octavian author. Modeling multi-level systems [electronic resource] Octavian Iordache. Heidelberg, Germany Springer Berlin 2011. 1 online resource (xv, 232 pages) text rdacontent computer rdamedia online resource rdacarrier Understanding complex systems. Springer complexity Introduction -- Methodological Resources -- Conventional PSM frames -- New PSM frames.-Mixing in chemical reactors -- Compartmental systems -- Turbulent mixing -- Entropy -- Formal concept analysis -- Existential graphs -- Evolvable designs of experiments -- Autonomous systems perspective. IP-based subscription, access limited to within on-campus computer network. Access via Electronic Resources of the UPD University Library Website. This book is devoted to modeling of multi-level complex systems, a challenging domain for engineers, researchers and entrepreneurs, confronted with the transition from learning and adaptability to evolvability and autonomy for technologies, devices and problem solving methods. Chapter 1 introduces the multi-scale and multi-level systems and highlights their presence in different domains of science and technology. Methodologies as, random systems, non-Archimedean analysis, category theory and specific techniques as model categorification and integrative closure, are presented in chapter 2. Chapters 3 and 4 describe polystochastic models, PSM, and their developments. Categorical formulation of integrative closure offers the general PSM framework which serves as a flexible guideline for a large variety of multi-level modeling problems. Focusing on chemical engineering, pharmaceutical and environmental case studies, the chapters 5 to 8 analyze mixing, turbulent dispersion and entropy production for multi-scale systems. Taking inspiration from systems sciences, chapters 9 to 11 highlight multi-level modeling potentialities in formal concept analysis, existential graphs and evolvable designs of experiments. Case studies refer to separation flow-sheets, pharmaceutical pipeline, drug design and development, reliability management systems, security and failure analysis. Perspectives and integrative points of view are discussed in chapter 12. Autonomous and viable systems, multi-agents, organic and autonomic computing, multi-level informational systems, are revealed as promising domains for future applications. Written for: engineers, researchers, entrepreneurs and students in chemical, pharmaceutical, environmental and systems sciences engineering, and for applied mathematicians. Electronic reproduction. New York SpringerLink 2011. Available via World Wide Web through SpringerLink. Stochastic models. System theory Mathematical models. Available for UP System via Springer Link. https://doi.org/10.1007/978-3-642-17946-4 FO UPD DMLR QA 273.6 I57 2011eb Electronic Resource