P-graphs for Process Systems Engineering

263 Pages·2022·7.365 MB·English

by  Ferenc Friedler, Ákos Orosz, Jean Pimentel Losada

Ferenc Friedler · Ákos Orosz
Jean Pimentel Losada
P-graphs for
Process Systems
Engineering
Mathematical Models
and Algorithms
P-graphs for Process Systems Engineering
(cid:129)
Ferenc Friedler Ákos Orosz
Jean Pimentel Losada
P-graphs for Process Systems
Engineering
Mathematical Models and Algorithms
FerencFriedler ÁkosOrosz
SzéchenyiIstvánUniversity UniversityofPannonia
Győr,Hungary Veszprém,Hungary
JeanPimentelLosada
BudapestUniversityofTechnologyandEconomics
Budapest,Hungary
ISBN978-3-030-92215-3 ISBN978-3-030-92216-0 (eBook)
https://doi.org/10.1007/978-3-030-92216-0
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In memory of Dr. L.T. Fan
Preface
As a consequence of our ever-increasing need for higher efficiency and better
sustainability, the world is going through rapid and significant changes. Naturally,
thegoalsconcerningefficiencyandsustainabilitydefineproperambitionandtarget
for both short and long term. Going in this direction is progressive; however, it
requires a higher level of exploitation and better use of the potential resources
available locally or globally. This can, however, be realized with additional inter-
connectionsamongthealreadycomplexnetworkofsubsystems,i.e.,withahigher-
levelintegration.Becauseofthat,thedifficultiesofourtimeverymuchdifferfrom
those ofdecadesago.The graduallybetterquality oflife afforded byrecent devel-
opmentscomestogetherwithamajorinfluenceonoureverydayroutine.Intheold
days, a local catastrophe occurring to an independent system had essentially no
directinfluenceonits surroundings.Incontrast, alocalcatastrophenowadays may
becomeregional,orinsomecasesglobal,duetothehighintegrationofsystems.For
instance, an accidental cut-off in an electric transmission network may induce a
continental-levelcatastrophe.Itis,therefore,crucialthatfurtherimprovementofthe
already highly interconnected systems be made by considering their resilience,
controllability, andoperabilityinadditiontothegeneralrequirementsofefficiency
and sustainability. To do so, however, the appropriate knowledge of complex
systemsisneeded.
Currently,mainresearcheffortsareaimedatunderstandingthebehavioroftwo
types of complex networks; the difference between them relates to the types of
mathematical models for describing the individual nodes of the networks. In one
typeofcomplexnetworks,simplemathematicalmodelsdescribethenodes,e.g.,the
Internet. In the other type, complex mathematical models represent the network’s
nodes.Thescopeofourworkbelongstothesecondtypeofcomplexnetworkswhich
is closely related to a variety of engineering systems, including the chemical
industry, production systems, and supply chains. The difficulty in examining this
typeofsystemsliesinboththesizeofthenetwork,intermsofthenumberofnodes,
and the complex mathematical models of the nodes. Because of the fundamental
differencebetweenthetwotypesofcomplexnetworks,theresearchachievementsof
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viii Preface
oneofthemcanhardlybebeneficialtotheothertype.Theexaminationofthesecond
typeofcomplexnetworksbelongstotheareaofprocesssystemsengineering(PSE)
where the complex systems are called complex processing systems, or simply,
processingsystems.Thelatterterminologywillbeusedhere.
The need for the systematic design and operation of processing systems origi-
natedinthepetroleumindustrybackinthe1970s.Thattimesawthebeginningofthe
creationofsimulationprogramsforanalyzingtheexpectedbehaviorofaprocessing
system prior to its construction. These simulation programs have become highly
sophisticated,andbynow,theyarecapableofoptimizinglargeprocessingsystems
of a given network structure; nevertheless, they are incapable of systematically
optimizingthenetworkconnections.Becauseofthat,thequestionofhowtoconnect
the systems elements to each other, i.e., what the best network of the individual
elementsis,cannotbeansweredbysuchtools.Inotherwords,theyareincapableof
thesystematicsynthesisofcomplexengineeringnetworks.
Other types of approaches for the synthesis of processing systems are based on
theoptimization ofamathematicalmodel.The keypoint indeveloping themathe-
matical model of processing systems’ synthesis, however, is to establish an exact
relationshipbetweentherealproblemanditsmathematicalmodel.Thisisextremely
crucial,andalsodifficult,becausethemathematicalmodelofasynthesisproblemis
not the description of a real object, it is an artificial entity. Therefore, this model’s
behaviorcannotbecomparedwithanyrealobjectforverification.Thephilosophical
andpracticalconsequencesofthisissuewillbeoneofthemainfocusesofthebook.
It has to be emphasized that process design based on simulation programs and
process synthesis based on mathematical optimization have major contributions to
the development of industry, but still, fundamental questions must be answered to
satisfyfutureneeds.
With this work, our purpose is to provide a theory of systems by focusing on
processingsystems,i.e.,networks,whosenodes arerepresentedbycomplex math-
ematical models. This theory has been constructed on a unique reformulation of
networksynthesisthatcansimplybereferredtoasinside-outmodelingofsystems.
Asetofaxiomsofprocessstructuresisthebasisofthetheory,wheretheaxiomsare
the expressions of the fundamental structural knowledge embedded into feasible
networks.Thisaxiomaticsetupservesboththerigorandthelong-termdevelopment
ofthetheory.Aframeworkformulatedonthistheory,calledtheP-graphframework,
provides new methods for synthesizing complex systems by taking into account
recently identified requirements on resilience, reliability, and controllability. The
frameworkwasoriginallydevelopedforprocessingsystemsinthechemicalindus-
try; however, its application area now spans a wide range of engineering systems
fromreactionengineeringtosupplychainmanagement.
Thethree mainpartsofthisbookcover thetheoreticalfoundationandthebasic
algorithmsoftheframework(PartI),theframework’sapplications(PartII),andthe
proofs of thealgorithms (Part III). The book gives rigorous mathematical formula-
tionsofthemethodstogetherwithillustrationsofthetheoryforsatisfyingtheneeds
ofresearchers,systemsengineers,andresearchstudents.Demonstrationsoftwareis
Preface ix
also available for readers for better understanding of the theory and to collect
experienceinsynthesizingnetworkstructureswithvariousproperties.
Finally, a paradigm shift is defined as "an important change that happens when
the usual way of thinking about or doing something is replaced by a new and
different way” (Merriam-Webster). In this regard, a natural question can be asked:
Does the proposed framework represent a paradigm shift in process systems engi-
neering,especially,inprocesssynthesis?Wewillletthereaderanswerthisquestion.
Győr,Hungary FerencFriedler
Veszprém,Hungary ÁkosOrosz
Budapest,Hungary JeanPimentelLosada
November2021
Acknowledgments
TheauthorsexpresstheirutmostgratitudetothelateProf.L.T.Fan,theco-founder
oftheP-graphframework.
TheauthorsaregratefultolateBalázsImreh,BotondBertók,lateCsanádImreh,
Zoltán Kovács, István Heckl, Csaba Holló, Zoltán Blázsik, and Andres Argoti for
their contribution to the development of the framework. All P-graph figures in the
bookhavebeendrawnbythefreelyavailablesoftwareP-GraphStudio,whichisalso
acknowledged.
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Contents
PartI FoundationoftheP-graphFramework
1 BasicConceptsofAutomaticProcessDesign. . . . . . . . . . . . . . . . . . 3
2 RepresentationofProcessStructuresinProcessNetwork
Synthesis:P-graphs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3 StructuralModelofProcessNetworkSynthesis. . . . . . . . . . . . . . . 19
4 AlgorithmicGenerationoftheMaximalStructure. . . . . . . . . . . . . 37
5 AlgorithmicGenerationofallSolution-Structures. . . . . . . . . . . . . . 51
6 AcceleratedBranch-and-BoundAlgorithmofProcess
NetworkSynthesis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
PartII ApplicationsoftheP-graphFramework
7 LiteratureReviewonResearchandApplications. . . . . . . . . . . . . . 85
8 CaseStudy:SynthesisofaProductionProcess
forAdipicAcid. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
9 Enumeration-BasedPropertiesofProcessingSystems:
ReliabilityandResilience. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
PartIII TheoryandFormalProofs
10 FormalProofofAlgorithmMSG. . . . . . . . . . . . . . . . . . . . . . . . . . 145
11 SimplificationoftheMaximalStructure. . . . . . . . . . . . . . . . . . . . . 151
12 FormalProofofAlgorithmSSG. . . . . . . . . . . . . . . . . . . . . . . . . . . 159
13 FormalProofofAlgorithmABB. . . . . . . . . . . . . . . . . . . . . . . . . . . 171
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