03852nam 22007095 450 99646650550331620200702174710.03-540-44971-X10.1007/BFb0104102(CKB)1000000000437273(SSID)ssj0000325480(PQKBManifestationID)12069573(PQKBTitleCode)TC0000325480(PQKBWorkID)10323991(PQKB)11660567(DE-He213)978-3-540-44971-3(MiAaPQ)EBC6297073(MiAaPQ)EBC5591224(Au-PeEL)EBL5591224(OCoLC)1066188018(PPN)155164457(EXLCZ)99100000000043727320121227d2000 u| 0engurnn|008mamaatxtccrOscillatory Integrals and Phenomena Beyond all Algebraic Orders[electronic resource] with Applications to Homoclinic Orbits in Reversible Systems /by Eric Lombardi1st ed. 2000.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2000.1 online resource (XVIII, 418 p.) Lecture Notes in Mathematics,0075-8434 ;1741Bibliographic Level Mode of Issuance: Monograph3-540-67785-2 Includes bibliographical references (pages [405]-410) and index."Exponential tools" for evaluating oscillatory integrals -- Resonances of reversible vector fields -- Analytic description of periodic orbits bifurcating from a pair of simple purely imaginary eigenvalues -- Constructive floquet theory for periodic matrices near a constant one -- Inversion of affine equations around reversible homoclinic connections -- The 02+i? resonance -- The 02+i? resonance in infinite dimensions. Application to water waves -- The (i?0)2i?1 resonance.During the last two decades, in several branches of science (water waves, crystal growth, travelling waves in one dimensional lattices, splitting of separatrices,...) different problems appeared in which the key point is the computation of exponentially small terms. This self-contained monograph gives new and rigorous mathematical tools which enable a systematic study of such problems. Starting with elementary illuminating examples, the book contains (i) new asymptotical tools for obtaining exponentially small equivalents of oscillatory integrals involving solutions of nonlinear differential equations; (ii) implementation of these tools for solving old open problems of bifurcation theory such as existence of homoclinic connections near resonances in reversible systems.Lecture Notes in Mathematics,0075-8434 ;1741Mathematical analysisAnalysis (Mathematics)Statistical physicsDynamical systemsAnalysishttps://scigraph.springernature.com/ontologies/product-market-codes/M12007Complex Systemshttps://scigraph.springernature.com/ontologies/product-market-codes/P33000Statistical Physics and Dynamical Systemshttps://scigraph.springernature.com/ontologies/product-market-codes/P19090Mathematical analysis.Analysis (Mathematics).Statistical physics.Dynamical systems.Analysis.Complex Systems.Statistical Physics and Dynamical Systems.515.35Lombardi Ericauthttp://id.loc.gov/vocabulary/relators/aut63016MiAaPQMiAaPQMiAaPQBOOK996466505503316Oscillatory integrals and phenomena beyond all algebraic orders78810UNISA05544nam 2200673 a 450 991083085480332120170815115039.00-470-77073-21-281-84099-897866118409900-470-77074-0(CKB)1000000000556207(EBL)366872(OCoLC)437234453(SSID)ssj0000263926(PQKBManifestationID)11217805(PQKBTitleCode)TC0000263926(PQKBWorkID)10283146(PQKB)11279627(MiAaPQ)EBC366872(PPN)204738563(EXLCZ)99100000000055620720080229d2008 uy 0engur|n|---|||||txtccrUncertainty in industrial practice[electronic resource] a guide to quantitative uncertainty management /edited by Etienne de Rocquigny, Nicolas Devictor, Stefano TarantolaChichester, England ;Hoboken, NJ J. Wileyc20081 online resource (365 p.)Description based upon print version of record.0-470-99447-9 Includes bibliographical references and index.Uncertainty in Industrial Practice; Contents; Preface; Contributors and Acknowledgements; Introduction; Notation - Acronyms and abbreviations; Part I Common Methodological Framework; 1 Introducing the common methodological framework; 1.1 Quantitative uncertainty assessment in industrial practice: a wide variety of contexts; 1.2 Key generic features, notation and concepts; 1.2.1 Pre-existing model, variables of interest and uncertain/fixed inputs; 1.2.2 Main goals of the uncertainty assessment; 1.2.3 Measures of uncertainty and quantities of interest; 1.2.4 Feedback process1.2.5 Uncertainty modelling1.2.6 Propagation and sensitivity analysis processes; 1.3 The common conceptual framework; 1.4 Using probabilistic frameworks in uncertainty quantification - preliminary comments; 1.4.1 Standard probabilistic setting and interpretations; 1.4.2 More elaborate level-2 settings and interpretations; 1.5 Concluding remarks; References; 2 Positioning of the case studies; 2.1 Main study characteristics to be specified in line with the common framework; 2.2 Introducing the panel of case studies; 2.3 Case study abstracts; Part II Case Studies3 CO2 emissions: estimating uncertainties in practice for power plants3.1 Introduction and study context; 3.2 The study model and methodology; 3.2.1 Three metrological options: common features in the pre-existing models; 3.2.2 Differentiating elements of the fuel consumption models; 3.3 Underlying framework of the uncertainty study; 3.3.1 Specification of the uncertainty study; 3.3.2 Description and modelling of the sources of uncertainty; 3.3.3 Uncertainty propagation and sensitivity analysis; 3.3.4 Feedback process; 3.4 Practical implementation and results; 3.5 Conclusions; References4 Hydrocarbon exploration: decision-support through uncertainty treatment4.1 Introduction and study context; 4.2 The study model and methodology; 4.2.1 Basin and petroleum system modelling; 4.3 Underlying framework of the uncertainty study; 4.3.1 Specification of the uncertainty study; 4.3.2 Description and modelling of the sources of uncertainty; 4.3.3 Uncertainty propagation and sensitivity analysis; 4.3.4 Feedback process; 4.4 Practical implementation and results; 4.4.1 Uncertainty analysis; 4.4.2 Sensitivity analysis; 4.5 Conclusions; References5 Determination of the risk due to personal electronic devices (PEDs) carried out on radio-navigation systems aboard aircraft5.1 Introduction and study context; 5.2 The study model and methodology; 5.2.1 Electromagnetic compatibility modelling and analysis; 5.2.2 Setting the EMC problem; 5.2.3 A model-based approach; 5.2.4 Regulatory and industrial stakes; 5.3 Underlying framework of the uncertainty study; 5.3.1 Specification of the uncertainty study; 5.3.2 Description and modelling of the sources of uncertainty; 5.3.3 Uncertainty propagation and sensitivity analysis; 5.3.4 Feedback process5.4 Practical implementation and resultsManaging uncertainties in industrial systems is a daily challenge to ensure improved design, robust operation, accountable performance and responsive risk control. Authored by a leading European network of experts representing a cross section of industries, Uncertainty in Industrial Practice aims to provide a reference for the dissemination of uncertainty treatment in any type of industry. It is concerned with the quantification of uncertainties in the presence of data, model(s) and knowledge about the system, and offers a technical contribution to decision-making processes whilst acknowledginIndustrial managementMathematical modelsUncertaintyMathematical modelsRisk managementIndustrial managementMathematical models.UncertaintyMathematical models.Risk management.658658.001Rocquigny Etienne de522144Devictor Nicolas1641991Tarantola Stefano1641992MiAaPQMiAaPQMiAaPQBOOK9910830854803321Uncertainty in industrial practice3986465UNINA