LEADER 06898nam 2200793Ia 450 001 9910824075303321 005 20200520144314.0 010 $a9786613622297 010 $a9781280592461 010 $a128059246X 010 $a9781118315354 010 $a1118315359 010 $a9781118315361 010 $a1118315367 010 $a9781118315330 010 $a1118315332 035 $a(CKB)2670000000177419 035 $a(EBL)837606 035 $a(SSID)ssj0000641999 035 $a(PQKBManifestationID)11393687 035 $a(PQKBTitleCode)TC0000641999 035 $a(PQKBWorkID)10646909 035 $a(PQKB)11599116 035 $a(PQKBManifestationID)16033612 035 $a(PQKB)21357800 035 $a(DLC) 2012003569 035 $a(Au-PeEL)EBL837606 035 $a(CaPaEBR)ebr10560654 035 $a(CaONFJC)MIL362229 035 $a(CaSebORM)9781118014783 035 $a(MiAaPQ)EBC837606 035 $a(OCoLC)795914179 035 $a(PPN)196870054 035 $a(Perlego)1011059 035 $a(EXLCZ)992670000000177419 100 $a20120125d2012 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aTheory of computation /$fGeorge Tourlakis 205 $a1st ed. 210 $aHoboken, N.J. $cWiley$d2012 215 $a1 online resource (410 p.) 300 $aDescription based upon print version of record. 311 08$a9781118014783 311 08$a1118014782 320 $aIncludes bibliographical references and index. 327 $aTheory of Computation; CONTENTS; Preface; 1 Mathematical Foundations; 1.1 Sets and Logic; Nai?vely; 1.1.1 A Detour via Logic; 1.1.2 Sets and their Operations; 1.1.3 Alphabets, Strings and Languages; 1.2 Relations and Functions; 1.3 Big and Small Infinite Sets; Diagonalization; 1.4 Induction from a User's Perspective; 1.4.1 Complete, or Course-of-Values, Induction; 1.4.2 Simple Induction; 1.4.3 The Least Principle; 1.4.4 The Equivalence of Induction and the Least Principle; 1.5 Why Induction Ticks; 1.6 Inductively Defined Sets; 1.7 Recursive Definitions of Functions; 1.8 Additional Exercises 327 $a2 Algorithms, Computable Functions and Computations 2.1 A Theory of Computability; 2.1.1 A Programming Framework for Computable Functions; 2.1.2 Primitive Recursive Functions; 2.1.3 Simultaneous Primitive Recursion; 2.1.4 Pairing Functions; 2.1.5 Iteration; 2.2 A Programming Formalism for the Primitive Recursive Functions; 2.2.1 PR vs. L; 2.2.2 Incompleteness of PR; 2.3 URM Computations and their Arithmetization; 2.4 A Double Recursion that Leads Outside the Primitive Recursive Function Class; 2.4.1 The Ackermann Function; 2.4.2 Properties of the Ackermann Function 327 $a2.4.3 The Ackermann Function Majorizes All the Functions of PR 2.4.4 The Graph of the Ackermann Function is in PR*; 2.5 Semi-computable Relations; Unsolvability; 2.6 The Iteration Theorem of Kleene; 2.7 Diagonalization Revisited; Unsolvability via Reductions; 2.7.1 More Diagonalization; 2.7.2 Reducibility via the S-m-n Theorem; 2.7.3 More Dovetailing; 2.7.4 Recursive Enumerations; 2.8 Productive and Creative Sets; 2.9 The Recursion Theorem; 2.9.1 Applications of the Recursion Theorem; 2.10 Completeness; 2.11 Unprovability from Unsolvability 327 $a3.5 Additional Exercises 4 Adding a Stack to a NFA: Pushdown Automata; 4.1 The PDA; 4.2 PDA Computations; 4.2.1 ES vs AS vs ES+AS; 4.3 The PDA-acceptable Languages are the Context Free Languages; 4.4 Non Context Free Languages; Another Pumping Lemma; 4.5 Additional Exercises; 5 Computational Complexity; 5.1 Adding a Second Stack; Turing Machines; 5.1.1 Turing Machines; 5.1.2 N P-Completeness; 5.1.3 Cook's Theorem; 5.2 Axt, Loop Program, and Grzegorczyk Hierarchies; 5.3 Additional Exercises; Bibliography; Index 330 $a"In the (meta)theory of computing, the fundamental questions of the limitations of computing are addressed. These limitations, which are intrinsic rather than technology dependent, may immediately rule out the existence of algorithmic solutions for some problems while for others they rule out efficient solutions. The author's approach is anchored on the concrete (and assumed) practical knowledge about general computer programming, attained readers in a first year programming course, as well as the knowledge of discrete mathematics at the same level. The book develops the meta-theory of general computing and builds on the reader's prior computing experience. Metatheory via the programming formalism known as Shepherdson-Sturgis Unbounded Register Machines (URM)--a straightforward abstraction of modern high level programming languages--is developed. Restrictions of the URM programming language are also discussed. The author has chosen to focus on the high level language approach of URMs as opposed to the Turing Machine since URMs relate more directly to programming learned in prior experiences. The author presents the topics of automata and languages only after readers become familiar, to some extent, with the (general) computability theory including the special computability theory of more "practical" functions, the primitive recursive functions. Automata are presented as a very restricted programming formalism, and their limitations (in expressivity) and their associated languages are studied. In addition, this book contains tools that, in principle, can search a set of algorithms to see whether a problem is solvable, or more specifically, if it can be solved by an algorithm whose computations are efficient. Chapter coverage includes: Mathematical Background; Algorithms, Computable Functions, and Computations; A Subset of the URM Language: FA and NFA; and Adding a Stack to an NFA: Pushdown Automata"--$cProvided by publisher. 330 $a"The book develops the meta-theory of general computing and builds on the reader's prior computing experience. Metatheory via the programming formalism known as Shepherdson-Sturgis Unbounded Register Machines (URM)--a straightforward abstraction of modern high-level programming languages--is developed. Restrictions of the URM programming language are also discussed. The author has chosen to focus on the high-level language approach of URMs as opposed to the Turing Machine since URMs relate more directly to programming learned in prior experiences"--$cProvided by publisher. 606 $aComputable functions 606 $aFunctional programming languages 615 0$aComputable functions. 615 0$aFunctional programming languages. 676 $a511.3/52 686 $aMAT008000$2bisacsh 700 $aTourlakis$b George J$0149747 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910824075303321 996 $aTheory of computation$94114090 997 $aUNINA LEADER 04318nam 22007935 450 001 9910887808003321 005 20250613004735.0 010 $a9783031677298 010 $a3031677293 024 7 $a10.1007/978-3-031-67729-8 035 $a(MiAaPQ)EBC31690018 035 $a(Au-PeEL)EBL31690018 035 $a(CKB)36193817700041 035 $a(DE-He213)978-3-031-67729-8 035 $a(OCoLC)1460327238 035 $a(EXLCZ)9936193817700041 100 $a20240925d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDiscrete Element Method for Multiphase Flows with Biogenic Particles $eAgriculture Applications /$fby Ling Zhou, Mahmoud A. Elemam, Ramesh K. Agarwal, Weidong Shi 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (183 pages) 225 0 $aEnergy Series 311 08$a9783031677281 311 08$a3031677285 327 $aChapter 1. Introduction -- Chapter 2. Aerodynamic Systems -- Chapter 3. Modeling of Aerodynamic Systems -- Chapter 4. Computational Fluid Dynamic (CFD) -- Chapter 5. Discrete Element Method (DEM) -- Chapter 6. CFD?DEM Coupling -- Chapter 7. CFD?DEM Applications -- Chapter 8. Challenges and Future Outlook. 330 $aThis book presents the advanced theory and application of the combined Computational Fluid Dynamics ? Discrete Element Method (CFD-DEM) to multiphase flow simulations of the gas and bio-particulate matter of non-uniformly shaped biomass. It explores how DEM can simulate the complex behaviour of biomass particles, such as their packing in the multiphase flows that occurs in the agricultural product processing industries. It offers an overview of aerodynamic systems, such as cyclone separators, used in the agricultural processing industry. A detailed description of DEM modeling, including the particle-particle, particle-boundary, and particle-fluid interactions in the context of biomass particles of varying sizes and shapes, is provided. Coverage includes the critical application of CFD-DEM simulation technology in designing and optimizing grain handling and processing equipment and the application of extended DEM to other granular flows of complex particles like sand, powders, and dust from mines where clumping and agglomeration occur. The application of DEM in modeling and simulation of complex multiphase systems can help improve productivity, reduce costs, and increase efficiency in the agricultural industry. Provides state-of-the-art coverage of the discrete element method (DEM) for multiphase flows with biomass particles; Offers computational fluid dynamics (CFD) modeling and turbulence models for turbulent multiphase flows; Describes granular flow and biomass modeling in aerodynamic systems and cyclone separators in the agriculture industry. 606 $aRenewable energy sources 606 $aBiomaterials 606 $aNanoparticles 606 $aFluid mechanics 606 $aBiotechnology 606 $aMathematical physics 606 $aComputer simulation 606 $aRenewable Energy 606 $aBiomaterials 606 $aNanoparticles 606 $aEngineering Fluid Dynamics 606 $aChemical Bioengineering 606 $aComputational Physics and Simulations 615 0$aRenewable energy sources. 615 0$aBiomaterials. 615 0$aNanoparticles. 615 0$aFluid mechanics. 615 0$aBiotechnology. 615 0$aMathematical physics. 615 0$aComputer simulation. 615 14$aRenewable Energy. 615 24$aBiomaterials. 615 24$aNanoparticles. 615 24$aEngineering Fluid Dynamics. 615 24$aChemical Bioengineering. 615 24$aComputational Physics and Simulations. 676 $a621.042 700 $aZhou$b Ling$01770949 701 $aElemam$b Mahmoud A$01770950 701 $aAgarwal$b R. K$g(Ramesh K.)$01354457 701 $aShi$b Weidong$01770951 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910887808003321 996 $aDiscrete Element Method for Multiphase Flows with Biogenic Particles$94521262 997 $aUNINA