01161nam0 2200301 450 00002343020081127120815.020081127d1945----km-y0itaa50------bafreFRJournal intimesuivi de Esquisse d'une autobiographieconsiderations sur le péchéméditationsFranz Kafkaintroduction et traduction par Pierre KlossowskiParisB. Grassetc1945319 p.19 cm.Diari e memorie838.912(21. ed.)Scritti miscellanei tedeschi. 1900-1945Kafka,Franz155661Klossowski,PierreITUniversità della Basilicata - B.I.A.RICAunimarc000023430Suivi de Esquisse d'une autobiographie90977Méditations1528130Journal intime90976Considerations sur le péché1528129UNIBASLETTEREEXT100120081127BAS011208BAS01BAS01BOOKBASA1Polo Storico-UmanisticoFMASFondo MasiniFMas/817/603817/603B817/6032008112704Prestabile Didattica05342nam 2200649Ia 450 991014434270332120170810192838.01-280-72286-X97866107228603-527-60878-83-527-60859-1(CKB)1000000000376188(EBL)481747(OCoLC)78205030(SSID)ssj0000201010(PQKBManifestationID)11184271(PQKBTitleCode)TC0000201010(PQKBWorkID)10232319(PQKB)10805776(MiAaPQ)EBC481747(EXLCZ)99100000000037618820060804d2006 uy 0engur|n|---|||||txtccrMembrane technology in the chemical industry[electronic resource] /edited by Suzana Pereira Nunes and Klaus-Vktor Peinemann2nd Rev. and extended ed.Weinheim Wiley-VCH20061 online resource (356 p.)Previous ed.: 2001.3-527-31316-8 Includes bibliographical references and index.Membrane Technology; Contents; Preface; List of Contributors; Part I Membrane Materials and Membrane Preparation; 1 Introduction; 2 Membrane Market; 3 Membrane Preparation; 3.1 Phase Inversion; 4 Presently Available Membranes for Liquid Separation; 4.1 Membranes for Reverse Osmosis; 4.2 Membranes for Nanofiltration; 4.2.1 Solvent-resistant Membranes for Nanofiltration; 4.2.2 NF Membranes Stable in Extreme pH Conditions; 4.3 Membranes for Ultrafiltration; 4.3.1 Polysulfone and Polyethersulfone; 4.3.2 Poly(vinylidene fluoride); 4.3.3 Polyetherimide; 4.3.4 Polyacrylonitrile; 4.3.5 Cellulose4.3.6 Solvent-resistant Membranes for Ultrafiltration4.4 Membranes for Microfiltration; 4.4.1 Polypropylene and Polyethylene; 4.4.2 Poly(tetrafluorethylene); 4.4.3 Polycarbonate and Poly(ethylene terephthalate); 5 Surface Modification of Membranes; 5.1 Chemical Oxidation; 5.2 Plasma Treatment; 5.3 Classical Organic Reactions; 5.4 Polymer Grafting; 6 Membranes for Fuel Cells; 6.1 Perfluorinated Membranes; 6.2 Nonfluorinated Membranes; 6.3 Polymer Membranes for High Temperatures; 6.4 Organic-Inorganic Membranes for Fuel Cells; 7 Gas Separation with Membranes; 7.1 Introduction7.2 Materials and Transport Mechanisms7.2.1 Organic Polymers; 7.2.2 Background; 7.2.3 Polymers for Commercial Gas-separation Membranes; 7.2.4 Ultrahigh Free Volume Polymers; 7.2.5 Inorganic Materials for Gas-separation Membranes; 7.2.6 Carbon Membranes; 7.2.7 Perovskite-type Oxide Membranes for Air Separation; 7.2.8 Mixed-matrix Membranes; 7.3 Basic Process Design; Acknowledgments; References; Part II Current Application and Perspectives; 1 The Separation of Organic Vapors from Gas Streams by Means of Membranes; Summary; 1.1 Introduction; 1.2 Historical Background1.3 Membranes for Organic Vapor Separation1.3.1 Principles; 1.3.2 Selectivity; 1.3.3 Temperature and Pressure; 1.3.4 Membrane Modules; 1.4 Applications; 1.4.1 Design Criteria; 1.4.2 Off-gas and Process Gas Treatment; 1.4.2.1 Gasoline Vapor Recovery; 1.4.2.2 Polyolefin Production Processes; 1.5 Applications at the Threshold of Commercialization; 1.5.1 Emission Control at Petrol Stations; 1.5.2 Natural Gas Treatment; 1.5.3 Hydrogen/Hydrocarbon Separation; 1.6 Conclusions and Outlook; References; 2 Gas-separation Membrane Applications; 2.1 Introduction; 2.2 Membrane Application Development2.2.1 Membrane Selection2.2.2 Membrane Form; 2.2.3 Membrane Module Geometry; 2.2.4 Compatible Sealing Materials; 2.2.5 Module Manufacture; 2.2.6 Pilot or Field Demonstration; 2.2.7 Process Design; 2.2.8 Membrane System; 2.2.9 Beta Site; 2.2.10 Cost/Performance; 2.3 Commercial Gas-separation Membrane Applications; 2.3.1 Hydrogen Separations; 2.3.2 Helium Separations; 2.3.3 Nitrogen Generation; 2.3.4 Acid Gas-Separations; 2.3.5 Gas Dehydration; 2.4 Developing Membrane Applications; 2.4.1 Oxygen and Oxygen-enriched Air; 2.4.2 Nitrogen Rejection from Natural Gas; 2.4.3 Nitrogen-enriched Air (NEA)ReferencesMembrane Technology - a clean and energy saving alternative to traditional/conventional processes.Developed from a useful laboratory technique to a commercial separation technology, today it has widespread and rapidly expanding use in the chemical industry. It has established applications in areas such as hydrogen separation and recovery of organic vapors from process gas streams, and selective transport of organic solvents, and it is opening new perspectives for catalytic conversion in membrane reactors. Membrane technology provides a unique solution for industrial waste treatment andMembrane filtersMembrane separationElectronic books.Membrane filters.Membrane separation.660.2842660.28424Nunes S. P(Suzana Pereira)855337Peinemann K. V(Klaus-Viktor)855336MiAaPQMiAaPQMiAaPQBOOK9910144342703321Membrane technology in the chemical industry2170868UNINA05616nam 22008655 450 99646573270331620200704064156.01-280-38324-097866135611693-642-03767-410.1007/978-3-642-03767-2(CKB)1000000000772857(SSID)ssj0000316862(PQKBManifestationID)11276959(PQKBTitleCode)TC0000316862(PQKBWorkID)10288386(PQKB)10074023(DE-He213)978-3-642-03767-2(MiAaPQ)EBC3064515(PPN)139955143(EXLCZ)99100000000077285720100301d2009 u| 0engurnn|008mamaatxtccrComputer Analysis of Images and Patterns[electronic resource] 13th International Conference, CAIP 2009, Münster, Germany, September 2-4, 2009, Proceedings /edited by Xiaoyi Jiang, Nicolai Petkov1st ed. 2009.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2009.1 online resource (XLVI, 1251 p.) Image Processing, Computer Vision, Pattern Recognition, and Graphics ;5702Bibliographic Level Mode of Issuance: Monograph3-642-03766-6 Includes bibliographical references and index.Invited Talks -- Biometrics -- Calibration -- Document Analysis -- Features -- Graph Representations -- Image Processing -- Image Registration -- Image and Video Retrieval -- Medical Imaging -- Object and Scene Recognition -- Pattern Recognition -- Shape Recovery -- Segmentation -- Stereo and Video Analysis -- Texture Analysis -- Applications -- Erratum.It was an honor and a pleasure to organizethe 13th International Conference on Computer Analysis of Images and Patterns (CAIP 2009) in Mu ¨nster, Germany. CAIP has been held biennially since 1985: Berlin (1985), Wismar (1987), Leipzig (1989), Dresden (1991), Budapest (1993), Prague (1995), Kiel (1997), Ljubljana (1999), Warsaw (2001), Groningen (2003), Paris (2005), and Vienna (2007). Initially, this conference series served as a forum for getting together s- entistsfromEastandWestEurope.Nowadays,CAIPenjoysahighinternational visibility and attracts participants from all over the world. For CAIP 2009 we received a record number of 405 submissions. All papers were reviewed by two, and in most cases, three reviewers. Finally, 148 papers were selected for presentation at the conference, resulting in an acceptance rate of 36%. All Program Committee members and additional reviewers listed here deserve a great thanks for their timely and competent reviews. The accepted papers were presented either as oral presentations or posters in a single-track program.In addition, wewereveryhappyto haveAljoscha Smolicand David G. Storkasourinvitedspeakerstopresenttheirworkintwofascinatingareas.With this scienti?c program we hope to continue the tradition of CAIP in providing a forum for scienti?c exchange at a high quality level. A successful conference like CAIP 2009 would not be possible without the support of many institutions and people. First of all, we like to thank all the authors of submitted papers and the invited speakers for their contributions. The Steering Committee members were always there when advice was needed.Image Processing, Computer Vision, Pattern Recognition, and Graphics ;5702Pattern recognitionBiometrics (Biology)Data miningOptical data processingNatural language processing (Computer science)Artificial intelligencePattern Recognitionhttps://scigraph.springernature.com/ontologies/product-market-codes/I2203XBiometricshttps://scigraph.springernature.com/ontologies/product-market-codes/I22040Data Mining and Knowledge Discoveryhttps://scigraph.springernature.com/ontologies/product-market-codes/I18030Computer Imaging, Vision, Pattern Recognition and Graphicshttps://scigraph.springernature.com/ontologies/product-market-codes/I22005Natural Language Processing (NLP)https://scigraph.springernature.com/ontologies/product-market-codes/I21040Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Kongress.swdMünster (Westfalen, 2009)swdPattern recognition.Biometrics (Biology).Data mining.Optical data processing.Natural language processing (Computer science).Artificial intelligence.Pattern Recognition.Biometrics.Data Mining and Knowledge Discovery.Computer Imaging, Vision, Pattern Recognition and Graphics.Natural Language Processing (NLP).Artificial Intelligence.006.42DAT 760fstubDAT 770fstubSS 4800rvkJiang Xiaoyiedthttp://id.loc.gov/vocabulary/relators/edtPetkov Nicolaiedthttp://id.loc.gov/vocabulary/relators/edtInternational Conference on Computer Analysis of Images and PatternsBOOK996465732703316Computer Analysis of Images and Patterns772514UNISA04898nam 22005895 450 991033763110332120200701034114.03-030-13543-810.1007/978-3-030-13543-0(CKB)4100000007746674(MiAaPQ)EBC5720256(DE-He213)978-3-030-13543-0(PPN)23500426X(EXLCZ)99410000000774667420190226d2019 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierA New Hypothesis on the Anisotropic Reynolds Stress Tensor for Turbulent Flows Volume I: Theoretical Background and Development of an Anisotropic Hybrid k-omega Shear-Stress Transport/Stochastic Turbulence Model /by László Könözsy1st ed. 2019.Cham :Springer International Publishing :Imprint: Springer,2019.1 online resource (152 pages)Fluid Mechanics and Its Applications,0926-5112 ;1203-030-13542-X 1 Introduction -- 1.1 Historical Background and Literature Review -- 1.2 Governing Equations of Incompressible Turbulent Flows -- 1.3 Summary -- References -- 2 Theoretical Principles and Galilean Invariance -- 2.1 Introduction -- 2.2 Basic Principles of Advanced Turbulence Modelling -- 2.3 Summary -- References -- 3 The k-w Shear-Stress Transport (SST) Turbulence Model -- 3.1 Introduction -- 3.2 Mathematical Derivations -- 3.3 Governing Equations of the k-w SST Turbulence Model -- 3.4 Summary -- References -- 4 Three-Dimensional Anisotropic Similarity Theory of Turbulent Velocity Fluctuations -- 4.1 Introduction -- 4.2 Similarity Theory of Turbulent Oscillatory Motions -- 4.3 Summary -- References -- 5 A New Hypothesis on the Anisotropic Reynolds Stress Tensor -- 5.1 Introduction -- 5.2 The Anisotropic Reynolds Stress Tensor -- 5.3 An Anisotropic Hybrid k-w SST/STM Closure Model for Incompressible Flows -- 5.4 Governing Equations of the Anisotropic Hybrid k-w SST/STM Closure Model -- 5.5 On the Implementation of the Anisotropic Hybrid k-w SST/STM Turbulence Model -- 5.6 Summary -- References -- Appendices: Additional Mathematical Derivations -- A.1 The Unit Base Vectors of the Fluctuating OrthogonalCoordinate System -- A.2 Galilean Invariance of the Unsteady Fluctuating VorticityTransport Equation -- A.3 The Deviatoric Part of the Similarity Tensor.This book gives a mathematical insight--including intermediate derivation steps--into engineering physics and turbulence modeling related to an anisotropic modification to the Boussinesq hypothesis (deformation theory) coupled with the similarity theory of velocity fluctuations. Through mathematical derivations and their explanations, the reader will be able to understand new theoretical concepts quickly, including how to put a new hypothesis on the anisotropic Reynolds stress tensor into engineering practice. The anisotropic modification to the eddy viscosity hypothesis is in the center of research interest, however, the unification of the deformation theory and the anisotropic similarity theory of turbulent velocity fluctuations is still missing from the literature. This book brings a mathematically challenging subject closer to graduate students and researchers who are developing the next generation of anisotropic turbulence models. Indispensable for graduate students, researchers and scientists in fluid mechanics and mechanical engineering.Fluid Mechanics and Its Applications,0926-5112 ;120Fluid mechanicsFluidsComputer scienceMathematicsProbabilitiesEngineering Fluid Dynamicshttps://scigraph.springernature.com/ontologies/product-market-codes/T15044Fluid- and Aerodynamicshttps://scigraph.springernature.com/ontologies/product-market-codes/P21026Computational Science and Engineeringhttps://scigraph.springernature.com/ontologies/product-market-codes/M14026Probability Theory and Stochastic Processeshttps://scigraph.springernature.com/ontologies/product-market-codes/M27004Fluid mechanics.Fluids.Computer scienceMathematics.Probabilities.Engineering Fluid Dynamics.Fluid- and Aerodynamics.Computational Science and Engineering.Probability Theory and Stochastic Processes.532.0527015118532.0527015118Könözsy Lászlóauthttp://id.loc.gov/vocabulary/relators/aut999615BOOK9910337631103321A New Hypothesis on the Anisotropic Reynolds Stress Tensor for Turbulent Flows2294603UNINA