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How do you know what works and what doesn't? This book contains
case studies highlighting the power of polytope projects for
complex problem solving. Any sort of combinational problem
characterized by a large variety of possibly complex constructions
and deconstructions based on simple building blocks can be studied
in a similar way. Although the majority of case studies are related
to chemistry, the method is general and equally applicable to other
fields for engineering or science.
This book is useful to engineers, researchers, entrepreneurs, and
students in different branches of production, engineering, and
systems sciences. The polytopic roadmaps are the guidelines
inspired by the development stages of cognitive-intelligent
systems, and expected to become powerful instruments releasing an
abundance of new capabilities and structures for complex
engineering systems implementation. The 4D approach developed in
previous monographs and correlated with industry 4.0and Fourth
Industrial Revolution is continued here toward higher dimensions
approaches correlated with polytopic operations, equipment,
technologies, industries, and societies. Methodology emphasizes the
role of doubling, iteration, dimensionality, and cyclicality around
the center, of periodic tables and of conservative and exploratory
strategies. Partitions, permutations, classifications, and
complexification, as polytopic chemistry, are the elementary
operations analyzed. Multi-scale transfer, cyclic operations,
conveyors, and assembly lines are the practical examples of
operations and equipment. Polytopic flow sheets, online analytical
processing, polytopic engineering designs, and reality-inspired
engineering are presented. Innovative concepts such as Industry
5.0, polytopic industry, Society 5.0, polytopic society, cyber
physical social systems, industrial Internet, and digital twins
have been discussed. The general polytopic roadmaps, (GPTR), are
proposed as universal guidelines and as common methodologies to
synthesize the systemic thinking and capabilities for growing
complexity projects implementation.
This book is useful to engineers, researchers, entrepreneurs, and
students in different branches of production, engineering, and
systems sciences. The polytopic roadmaps are the guidelines
inspired by the development stages of cognitive-intelligent
systems, and expected to become powerful instruments releasing an
abundance of new capabilities and structures for complex
engineering systems implementation. The 4D approach developed in
previous monographs and correlated with industry 4.0and Fourth
Industrial Revolution is continued here toward higher dimensions
approaches correlated with polytopic operations, equipment,
technologies, industries, and societies. Methodology emphasizes the
role of doubling, iteration, dimensionality, and cyclicality around
the center, of periodic tables and of conservative and exploratory
strategies. Partitions, permutations, classifications, and
complexification, as polytopic chemistry, are the elementary
operations analyzed. Multi-scale transfer, cyclic operations,
conveyors, and assembly lines are the practical examples of
operations and equipment. Polytopic flow sheets, online analytical
processing, polytopic engineering designs, and reality-inspired
engineering are presented. Innovative concepts such as Industry
5.0, polytopic industry, Society 5.0, polytopic society, cyber
physical social systems, industrial Internet, and digital twins
have been discussed. The general polytopic roadmaps, (GPTR), are
proposed as universal guidelines and as common methodologies to
synthesize the systemic thinking and capabilities for growing
complexity projects implementation.
This book presents a domain of extreme industrial and scientific
interest: the study of smart systems and structures. It presents
polytope projects as comprehensive physical and cognitive
architectures that support the investigation, fabrication and
implementation of smart systems and structures. These systems
feature multifunctional components that can perform sensing,
control, and actuation. In light of the fact that devices, tools,
methodologies and organizations based on electronics and
information technology for automation, specific to the third
industrial revolution, are increasingly reaching their limits, it
is essential that smart systems be implemented in industry.
Polytope projects facilitate the utilization of smart systems and
structures as key elements of the fourth industrial revolution. The
book begins by presenting polytope projects as a reference
architecture for cyber-physical systems and smart systems, before
addressing industrial process synthesis in Chapter 2. Flow-sheet
trees, cyclic separations and smart configurations for
multi-component separations are discussed here. In turn, Chapter 3
highlights periodic features for drug delivery systems and networks
of chemical reactions, while Chapter 4 applies conditioned random
walks to polymers and smart materials structures. Chapter 5
examines self-assembly and self-reconfiguration at different scales
from molecular to micro systems. Smart devices and technologies are
the focus of chapter 6. Modular micro reactor systems and timed
automata are examined in selected case studies. Chapter 7 focuses
on inferential engineering designs, concept-knowledge, relational
concept analysis and model driven architecture, while Chapter 8
puts the spotlight on smart manufacturing, industry 4.0, reference
architectures and models for new product development and testing.
Lastly, Chapter 9 highlights the polytope projects methodology and
the prospects for smart systems and structures. Focusing on process
engineering and mathematical modeling for the fourth industrial
revolution, the book offers a unique resource for engineers,
scientists and entrepreneurs working in chemical, biochemical,
pharmaceutical, materials science or systems chemistry, students in
various domains of production and engineering, and applied
mathematicians.
This book presents a domain of extreme industrial and scientific
interest: the study of smart systems and structures. It presents
polytope projects as comprehensive physical and cognitive
architectures that support the investigation, fabrication and
implementation of smart systems and structures. These systems
feature multifunctional components that can perform sensing,
control, and actuation. In light of the fact that devices, tools,
methodologies and organizations based on electronics and
information technology for automation, specific to the third
industrial revolution, are increasingly reaching their limits, it
is essential that smart systems be implemented in industry.
Polytope projects facilitate the utilization of smart systems and
structures as key elements of the fourth industrial revolution. The
book begins by presenting polytope projects as a reference
architecture for cyber-physical systems and smart systems, before
addressing industrial process synthesis in Chapter 2. Flow-sheet
trees, cyclic separations and smart configurations for
multi-component separations are discussed here. In turn, Chapter 3
highlights periodic features for drug delivery systems and networks
of chemical reactions, while Chapter 4 applies conditioned random
walks to polymers and smart materials structures. Chapter 5
examines self-assembly and self-reconfiguration at different scales
from molecular to micro systems. Smart devices and technologies are
the focus of chapter 6. Modular micro reactor systems and timed
automata are examined in selected case studies. Chapter 7 focuses
on inferential engineering designs, concept-knowledge, relational
concept analysis and model driven architecture, while Chapter 8
puts the spotlight on smart manufacturing, industry 4.0, reference
architectures and models for new product development and testing.
Lastly, Chapter 9 highlights the polytope projects methodology and
the prospects for smart systems and structures. Focusing on process
engineering and mathematical modeling for the fourth industrial
revolution, the book offers a unique resource for engineers,
scientists and entrepreneurs working in chemical, biochemical,
pharmaceutical, materials science or systems chemistry, students in
various domains of production and engineering, and applied
mathematicians.
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.
This monograph presents key method to successfully manage the
growing complexity of systems where conventional engineering and
scientific methodologies and technologies based on learning and
adaptability come to their limits and new ways are nowadays
required. The transition from adaptable to evolvable and finally to
self-evolvable systems is highlighted, self-properties such as
self-organization, self-configuration, and self-repairing are
introduced and challenges and limitations of the self-evolvable
engineering systems are evaluated.
This monograph presents key method to successfully manage the
growing complexity of systems where conventional engineering and
scientific methodologies and technologies based on learning and
adaptability come to their limits and new ways are nowadays
required. The transition from adaptable to evolvable and finally to
self-evolvable systems is highlighted, self-properties such as
self-organization, self-configuration, and self-repairing are
introduced and challenges and limitations of the self-evolvable
engineering systems are evaluated."
This book is devoted to a domain of highest industrial and
scienti?c interest, the complexity. The complexity understanding
and management will be a main source of e?ciency and prosperity for
the next decades. Complex systems areassembliesof multiple
subsystemsand arecharact- ized by emergent behavior that results by
nonlinear interactions among the subsystems at multiple levels of
organization. Evolvability that is the ability to evolve is the
method to confront and surpass the successive boundaries of
complexity. Evolvability is not biological but should be considered
here in the sense that the corresponding systems have, at di?erent
levels, charact- istics that are naturally associated to the living
systems. The signi?cance of the complexity and the phenomena of
emergence are highlighted in the ?rst chapterofthe
book.Theimplicationofconcepts aslevelofreality, circularity and
closure for evolvable systems is evaluated. The second chapter of
the book exposes the methodology to analyze and manage complex
systems. The polystochastic models, PSMs, are the cons- ered
mathematical tools. PSMs characterize systems emerging when several
stochastic processes occurring at di?erent conditioning levels, are
capable to interact with each other, resulting in qualitatively new
processes and s- tems. Innovative are the higher categories
approach and the introduction of apartialdi?erentialmodelfor
multiple levelsmodeling.This imposes making use of appropriate
notions of time, space, probabilities and entropy.
Categorytheoryistheformalismcapabletooutlinethegeneralframework,
shared by the functional organization of biological organisms, of
cognitive systems, by the operational structure of evolvable
technologies and devices and after all by the scienti?c and
engineering methods
This book is devoted to a domain of highest industrial and
scienti?c interest, the complexity. The complexity understanding
and management will be a main source of e?ciency and prosperity for
the next decades. Complex systems areassembliesof multiple
subsystemsand arecharact- ized by emergent behavior that results by
nonlinear interactions among the subsystems at multiple levels of
organization. Evolvability that is the ability to evolve is the
method to confront and surpass the successive boundaries of
complexity. Evolvability is not biological but should be considered
here in the sense that the corresponding systems have, at di?erent
levels, charact- istics that are naturally associated to the living
systems. The signi?cance of the complexity and the phenomena of
emergence are highlighted in the ?rst chapterofthe
book.Theimplicationofconcepts aslevelofreality, circularity and
closure for evolvable systems is evaluated. The second chapter of
the book exposes the methodology to analyze and manage complex
systems. The polystochastic models, PSMs, are the cons- ered
mathematical tools. PSMs characterize systems emerging when several
stochastic processes occurring at di?erent conditioning levels, are
capable to interact with each other, resulting in qualitatively new
processes and s- tems. Innovative are the higher categories
approach and the introduction of apartialdi?erentialmodelfor
multiple levelsmodeling.This imposes making use of appropriate
notions of time, space, probabilities and entropy.
Categorytheoryistheformalismcapabletooutlinethegeneralframework,
shared by the functional organization of biological organisms, of
cognitive systems, by the operational structure of evolvable
technologies and devices and after all by the scienti?c and
engineering methods
This book focuses on new developments in polytopic projects,
particularly on implementation domains and case studies, as well as
high-dimensional methodology. Polytopic projects are based on a
general reference architecture inspired and shared by the
functional organization of organisms and enterprises as
informational and cognitive systems, the scientific and engineering
methodology and the operational structure of existing
self-evolvable and self-sustainable systems.
This book focuses on new developments in polytopic projects,
particularly on implementation domains and case studies, as well as
high-dimensional methodology. Polytopic projects are based on a
general reference architecture inspired and shared by the
functional organization of organisms and enterprises as
informational and cognitive systems, the scientific and engineering
methodology and the operational structure of existing
self-evolvable and self-sustainable systems.
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.
High dimensional reference architectures presented here allows
confronting and prevailing over the growing complexity of polytopic
projects implementations. Such projects should be envisaged giving
that conventional systems operations, equipments, methodologies or
organizations will reach their limits for self-evolvability in high
complexity conditions. Self-evolvable high complexity systems are
based on high dimensional polytopic reference architectures.
Polytope is the general term of the sequence: point, line, polygon,
polyhedron and so on.The polytopic projects are targeting the
artificiality, not only for materials where it is well known and
applied, but also for biological, cognitive, intelligent and
mathematical systems. The book highlights the polytopic projects
basic similarity despite the noticeable difference as domains of
application. The roads to follow and the algebra of changing roads
are emphasized. The book is divided in 9 chapters. Chapter 1
introduces the Polytopic Roadmap to 4D and beyond. The role for the
dialogue of processes in duality of the non-Aristotelian Logic of
Contradiction and of Included Middle is emphasized for different
domains. Chapter 2 refers to chemical systems. Supramolecular
chemistry, metal organic frameworks, MOF, and reaction networks,
are the examples considered in the frame of polytopic chemistry.
Chapter 3 refers to biological systems. Biological dynamical
hierarchies and quasi-species are the considered case studies.
Technological and scientific projects targeting artificiality for
cells and viruses are considered. Chapter 4 refers to cognitive
systems. Developmental stages, formal and relational concepts
analysis, and neural coding are considered here. The roles of the
4D systems of systems of systems and of conceptual 4D-cube are
emphasized. Artificiality for cognitive systems is the object of
study. Chapter 5 refers to mathematical systems. Modeling levels
and the 4D digital twins are discussed. Hopf monoids as tools for
the study of combinations and separations, dual graded graphs and
V-models are informally presented. Chapter 6 refers to application
of formal concept analysis, FCA, for high dimensional separations,
nesting and drug delivery. Chapter 7 refers to polytopic
engineering systems as multiscale transfer,
distributors-collectors, cyclic operations, middle vessel columns,
mixing, assembly and designs. Equipments have been characterized
using Polytopic Roadmaps and classified by Periodic Tables. Chapter
8 introduces polytopic industry, economy, society and
sustainability. Chapter 9 outlines new domains of interest as arts
and architecture, transdisciplinarity, complex systems and unity of
sciences and engineering. Polytopic Roadmaps are proposed as Method
for experts from various fields to synthesize their thinking and
capabilities into new projects implementation to face and surpass
high complexity. A repetitive finding of this book is that
self-evolvability observed in physical systems is based on the same
directed sequence of reference architectures as the
self-evolvability of concepts in our mind. Continuing to develop
the field of self-evolvable systems and presenting the polytopic
roadmaps for 4D and beyond advances in ever growing complexity
domains, the book will be useful to engineers, researchers,
entrepreneurs and students in different branches of production,
complex systems sciences and engineering, ecology and applied
mathematics.
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