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Accelerator-Driven System at Kyoto University Critical Assembly
| Accelerator-Driven System at Kyoto University Critical Assembly |
| Autore | Pyeon Cheol Ho |
| Pubbl/distr/stampa | Springer Nature, 2021 |
| Descrizione fisica | 1 online resource (353 pages) |
| Soggetto topico |
Atomic & molecular physics
Nuclear power & engineering Spectrum analysis, spectrochemistry, mass spectrometry Particle & high-energy physics |
| Soggetto non controllato |
Nuclear Physics, Heavy Ions, Hadrons
Nuclear Energy Nuclear Chemistry Particle Acceleration and Detection, Beam Physics Nuclear Physics Accelerator Physics Open Access Reactor Physics Experiments ADS KUCA Subcriticality Measurement Kinetics Parameter Estimation in Subcritical State Nuclear Transmutation Uncertainty Quantification Atomic & molecular physics Nuclear power & engineering Nuclear chemistry, photochemistry & radiation Particle & high-energy physics |
| ISBN | 981-16-0344-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Contributors -- 1 Introduction -- 1.1 Kyoto University Critical Assembly -- 1.1.1 KUCA Facility -- 1.1.2 Solid-Moderated and Solid-Reflected Cores -- 1.1.3 Light-Water-Moderated and Light-Water-Reflected Core -- 1.1.4 Pulsed-Neutron Generator -- 1.1.5 Fixed-Field Alternating Gradient Accelerator -- 1.2 Accelerator-Driven System -- 1.2.1 Overview of Research and Development -- 1.2.2 Feasibility Study at KUCA -- References -- 2 Subcriticality -- 2.1 Feynman-α and Rossi-α Analyses -- 2.1.1 Experimental Settings -- 2.1.2 Formulae for Data Analyses -- 2.1.3 Results and Discussion -- 2.2 Power Spectral Analyses -- 2.2.1 Experimental Settings -- 2.2.2 Formula for Power Spectral Analyses -- 2.2.3 Results and Discussion -- 2.3 Beam Trip and Restart Methods -- 2.3.1 Experimental Settings -- 2.3.2 Data Analyses Method -- 2.3.3 Results and Discussion -- 2.4 Conclusion -- References -- 3 Reactor Kinetics -- 3.1 α-Fitting Method -- 3.1.1 Experimental Settings -- 3.1.2 Numerical Simulations -- 3.1.3 Results and Discussion -- 3.2 Pulsed-Neutron Source Method -- 3.2.1 Experimental Settings -- 3.2.2 Results and Discussion -- 3.3 Inverse Kinetic Method -- 3.3.1 Theoretical Background -- 3.3.2 Experimental Settings -- 3.3.3 Transient Analyses -- 3.4 Conclusion -- References -- 4 Effective Delayed Neutron Fraction -- 4.1 Dependency of External Neutron Source -- 4.1.1 Experimental Settings -- 4.1.2 Numerical Simulations -- 4.1.3 k-Ratio Method -- 4.2 Measurement -- 4.2.1 Nelson Number Method -- 4.2.2 Experimental Settings -- 4.2.3 Results and Discussion -- 4.3 Evaluation of βeff/Λ -- 4.3.1 Experimental Settings -- 4.3.2 Kinetics Parameters -- 4.3.3 Results and Discussion -- 4.4 Neutron Generation Time -- 4.4.1 Experimental Settings -- 4.4.2 Results and Discussion -- 4.5 Conclusion -- References -- 5 Neutron Spectrum.
5.1 Subcritical Multiplication Factor -- 5.1.1 Theoretical Background -- 5.1.2 Characteristics of the Target -- 5.1.3 Effects of Neutron Spectrum -- 5.2 Threshold Energy Reactions -- 5.2.1 Foil Activation Method -- 5.2.2 Activation Foils -- 5.3 Spectrum Index -- 5.3.1 Cd Ratio -- 5.3.2 In Ratio -- 5.4 Spallation Neutrons -- 5.4.1 Neutron Spectrum Analyses -- 5.4.2 Reaction Rates -- 5.5 Conclusion -- References -- 6 Nuclear Transmutation of Minor Actinide -- 6.1 Integral Experiments at Critical State -- 6.1.1 Critical Irradiation Experiments -- 6.1.2 Experimental Analyses -- 6.1.3 Discussion -- 6.2 ADS Irradiation at Subcritical State -- 6.2.1 Experimental Settings -- 6.2.2 Demonstration of Nuclear Transmutation -- 6.3 Conclusion -- References -- 7 Neutronics of Lead and Bismuth -- 7.1 Sample Reactivity Worth Experiments -- 7.1.1 Core Configuration -- 7.1.2 Experimental Settings -- 7.2 Monte Carlo Analyses -- 7.2.1 Evaluation Method -- 7.2.2 Lead Sample Reactivity Worth -- 7.2.3 Bismuth Sample Reactivity Worth -- 7.3 Sensitivity Coefficients -- 7.3.1 Theoretical Background -- 7.3.2 Lead Isotopes -- 7.3.3 Bismuth Isotope -- 7.4 Uncertainty Quantification -- 7.4.1 Theoretical Background -- 7.4.2 Lead Isotopes -- 7.4.3 Bismuth Isotope -- 7.5 Conclusion -- References -- 8 Sensitivity and Uncertainty of Criticality -- 8.1 Experimental Settings -- 8.1.1 Core Configuration -- 8.1.2 Reactivity Measurements -- 8.2 Criticality -- 8.2.1 Numerical Simulations -- 8.2.2 Sensitivity and Uncertainty -- 8.2.3 Results and Discussion -- 8.3 Benchmarks -- 8.3.1 Experimental Analyses -- 8.3.2 Uncertainty -- 8.4 Conclusion -- References -- Appendix A1: Experimental Benchmarks on ADS at Kyoto University Critical Assembly -- A1.1 Experimental Settings of ADS Benchmarks -- A1.1.1 Core Components -- A1.1.2 Atomic Number Density of Core Elements -- References. Appendix A2: 235U-Fueled and Pb-Bi-Zoned ADS Core -- A2.1 Pb-Bi Target -- A2.1.1 Core Configurations -- A2.1.2 Results of Experiments -- A2.1.2.1 Reaction Rate Distribution -- A2.1.2.2 PNS and Feynman-α Methods -- A2.2 Subcriticality Measurements -- A2.2.1 Core Configurations -- A2.2.2 Results of Experiments -- A2.2.3 PNS and Feynman-α Methods -- A2.3 Reaction Rates -- A2.3.1 Core Configurations -- A2.3.2 Reaction Rate Distributions -- A2.3.3 Reaction Rates of Activation Foils -- References -- Appendix A3: 235U-Fueled and Pb-Zoned ADS Core -- A3.1 Core Configurations -- A3.1.1 ADS with 14 MeV Neutrons -- A3.1.2 ADS with 100 MeV Protons -- A3.2 Kinetics Parameters -- A3.2.1 ADS with 14 MeV Neutrons -- A3.2.1.1 Core Condition at Critical State -- A3.2.1.2 Case D1 (4560 HEU Plates) -- A3.2.1.3 Case D2 (4400 HEU Plates) -- A3.2.1.4 Case D3 (4320 HEU Plates) -- A3.2.1.5 Case D4 (4200 HEU Plates) -- A3.2.1.6 Case D5 (4080 HEU Plates) -- A3.2.1.7 Case D6 (3840 HEU Plates) -- A3.2.2 ADS with 100 MeV Protons -- A3.2.2.1 Core Condition at Critical State -- A3.2.2.2 Case F1 (4560 HEU Plates) -- A3.2.2.3 Case F2 (4440 HEU Plates) -- A3.2.2.4 Case F3 (4320 HEU Plates) -- A3.2.2.5 Case F4 (4200 HEU Plates) -- A3.2.2.6 Case F5 (4080 HEU Plates) -- A3.2.2.7 Case F6 (3960 HEU Plates) -- A3.2.2.8 Case F7 (3840 HEU Plates) -- A3.3 Reaction Rates -- A3.3.1 Core Configurations -- A3.3.2 Reaction Rate Distribution -- References -- Appendix A4: 235U-Fueled ADS Core in Medium-Fast Spectrum -- A4.1 Core Configurations -- A4.1.1 ADS with 14 MeV Neutrons -- A4.1.2 ADS with 100 MeV Protons -- A4.2 Results of Experiments -- A4.2.1 Criticality and Control Rod Worth -- A4.2.2 PNS and Feynman-α Methods -- A4.3 Kinetic Parameters -- A4.3.1 ADS with 14 MeV Neutrons -- A4.3.2 ADS with 100 MeV Protons -- A4.4 Reaction Rates -- A4.4.1 Core Configurations. A4.4.2 Reaction Rate Distributions -- A4.4.3 Reaction Rates of Activation Foils -- References -- Appendix A5: 232Th-Fueled ADS Core -- A5.1 Core Configurations -- A5.2 Results of Experiments -- A5.2.1 Reaction Rate Distributions -- A5.2.2 PNS and Feynman-α Methods -- References. |
| Record Nr. | UNINA-9910473449803321 |
Pyeon Cheol Ho
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| Springer Nature, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Accelerator-Driven System at Kyoto University Critical Assembly
| Accelerator-Driven System at Kyoto University Critical Assembly |
| Autore | Pyeon Cheol Ho |
| Pubbl/distr/stampa | Springer Nature, 2021 |
| Descrizione fisica | 1 online resource (353 pages) |
| Soggetto topico |
Atomic & molecular physics
Nuclear power & engineering Spectrum analysis, spectrochemistry, mass spectrometry Particle & high-energy physics |
| Soggetto non controllato |
Nuclear Physics, Heavy Ions, Hadrons
Nuclear Energy Nuclear Chemistry Particle Acceleration and Detection, Beam Physics Nuclear Physics Accelerator Physics Open Access Reactor Physics Experiments ADS KUCA Subcriticality Measurement Kinetics Parameter Estimation in Subcritical State Nuclear Transmutation Uncertainty Quantification Atomic & molecular physics Nuclear power & engineering Nuclear chemistry, photochemistry & radiation Particle & high-energy physics |
| ISBN | 981-16-0344-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Contributors -- 1 Introduction -- 1.1 Kyoto University Critical Assembly -- 1.1.1 KUCA Facility -- 1.1.2 Solid-Moderated and Solid-Reflected Cores -- 1.1.3 Light-Water-Moderated and Light-Water-Reflected Core -- 1.1.4 Pulsed-Neutron Generator -- 1.1.5 Fixed-Field Alternating Gradient Accelerator -- 1.2 Accelerator-Driven System -- 1.2.1 Overview of Research and Development -- 1.2.2 Feasibility Study at KUCA -- References -- 2 Subcriticality -- 2.1 Feynman-α and Rossi-α Analyses -- 2.1.1 Experimental Settings -- 2.1.2 Formulae for Data Analyses -- 2.1.3 Results and Discussion -- 2.2 Power Spectral Analyses -- 2.2.1 Experimental Settings -- 2.2.2 Formula for Power Spectral Analyses -- 2.2.3 Results and Discussion -- 2.3 Beam Trip and Restart Methods -- 2.3.1 Experimental Settings -- 2.3.2 Data Analyses Method -- 2.3.3 Results and Discussion -- 2.4 Conclusion -- References -- 3 Reactor Kinetics -- 3.1 α-Fitting Method -- 3.1.1 Experimental Settings -- 3.1.2 Numerical Simulations -- 3.1.3 Results and Discussion -- 3.2 Pulsed-Neutron Source Method -- 3.2.1 Experimental Settings -- 3.2.2 Results and Discussion -- 3.3 Inverse Kinetic Method -- 3.3.1 Theoretical Background -- 3.3.2 Experimental Settings -- 3.3.3 Transient Analyses -- 3.4 Conclusion -- References -- 4 Effective Delayed Neutron Fraction -- 4.1 Dependency of External Neutron Source -- 4.1.1 Experimental Settings -- 4.1.2 Numerical Simulations -- 4.1.3 k-Ratio Method -- 4.2 Measurement -- 4.2.1 Nelson Number Method -- 4.2.2 Experimental Settings -- 4.2.3 Results and Discussion -- 4.3 Evaluation of βeff/Λ -- 4.3.1 Experimental Settings -- 4.3.2 Kinetics Parameters -- 4.3.3 Results and Discussion -- 4.4 Neutron Generation Time -- 4.4.1 Experimental Settings -- 4.4.2 Results and Discussion -- 4.5 Conclusion -- References -- 5 Neutron Spectrum.
5.1 Subcritical Multiplication Factor -- 5.1.1 Theoretical Background -- 5.1.2 Characteristics of the Target -- 5.1.3 Effects of Neutron Spectrum -- 5.2 Threshold Energy Reactions -- 5.2.1 Foil Activation Method -- 5.2.2 Activation Foils -- 5.3 Spectrum Index -- 5.3.1 Cd Ratio -- 5.3.2 In Ratio -- 5.4 Spallation Neutrons -- 5.4.1 Neutron Spectrum Analyses -- 5.4.2 Reaction Rates -- 5.5 Conclusion -- References -- 6 Nuclear Transmutation of Minor Actinide -- 6.1 Integral Experiments at Critical State -- 6.1.1 Critical Irradiation Experiments -- 6.1.2 Experimental Analyses -- 6.1.3 Discussion -- 6.2 ADS Irradiation at Subcritical State -- 6.2.1 Experimental Settings -- 6.2.2 Demonstration of Nuclear Transmutation -- 6.3 Conclusion -- References -- 7 Neutronics of Lead and Bismuth -- 7.1 Sample Reactivity Worth Experiments -- 7.1.1 Core Configuration -- 7.1.2 Experimental Settings -- 7.2 Monte Carlo Analyses -- 7.2.1 Evaluation Method -- 7.2.2 Lead Sample Reactivity Worth -- 7.2.3 Bismuth Sample Reactivity Worth -- 7.3 Sensitivity Coefficients -- 7.3.1 Theoretical Background -- 7.3.2 Lead Isotopes -- 7.3.3 Bismuth Isotope -- 7.4 Uncertainty Quantification -- 7.4.1 Theoretical Background -- 7.4.2 Lead Isotopes -- 7.4.3 Bismuth Isotope -- 7.5 Conclusion -- References -- 8 Sensitivity and Uncertainty of Criticality -- 8.1 Experimental Settings -- 8.1.1 Core Configuration -- 8.1.2 Reactivity Measurements -- 8.2 Criticality -- 8.2.1 Numerical Simulations -- 8.2.2 Sensitivity and Uncertainty -- 8.2.3 Results and Discussion -- 8.3 Benchmarks -- 8.3.1 Experimental Analyses -- 8.3.2 Uncertainty -- 8.4 Conclusion -- References -- Appendix A1: Experimental Benchmarks on ADS at Kyoto University Critical Assembly -- A1.1 Experimental Settings of ADS Benchmarks -- A1.1.1 Core Components -- A1.1.2 Atomic Number Density of Core Elements -- References. Appendix A2: 235U-Fueled and Pb-Bi-Zoned ADS Core -- A2.1 Pb-Bi Target -- A2.1.1 Core Configurations -- A2.1.2 Results of Experiments -- A2.1.2.1 Reaction Rate Distribution -- A2.1.2.2 PNS and Feynman-α Methods -- A2.2 Subcriticality Measurements -- A2.2.1 Core Configurations -- A2.2.2 Results of Experiments -- A2.2.3 PNS and Feynman-α Methods -- A2.3 Reaction Rates -- A2.3.1 Core Configurations -- A2.3.2 Reaction Rate Distributions -- A2.3.3 Reaction Rates of Activation Foils -- References -- Appendix A3: 235U-Fueled and Pb-Zoned ADS Core -- A3.1 Core Configurations -- A3.1.1 ADS with 14 MeV Neutrons -- A3.1.2 ADS with 100 MeV Protons -- A3.2 Kinetics Parameters -- A3.2.1 ADS with 14 MeV Neutrons -- A3.2.1.1 Core Condition at Critical State -- A3.2.1.2 Case D1 (4560 HEU Plates) -- A3.2.1.3 Case D2 (4400 HEU Plates) -- A3.2.1.4 Case D3 (4320 HEU Plates) -- A3.2.1.5 Case D4 (4200 HEU Plates) -- A3.2.1.6 Case D5 (4080 HEU Plates) -- A3.2.1.7 Case D6 (3840 HEU Plates) -- A3.2.2 ADS with 100 MeV Protons -- A3.2.2.1 Core Condition at Critical State -- A3.2.2.2 Case F1 (4560 HEU Plates) -- A3.2.2.3 Case F2 (4440 HEU Plates) -- A3.2.2.4 Case F3 (4320 HEU Plates) -- A3.2.2.5 Case F4 (4200 HEU Plates) -- A3.2.2.6 Case F5 (4080 HEU Plates) -- A3.2.2.7 Case F6 (3960 HEU Plates) -- A3.2.2.8 Case F7 (3840 HEU Plates) -- A3.3 Reaction Rates -- A3.3.1 Core Configurations -- A3.3.2 Reaction Rate Distribution -- References -- Appendix A4: 235U-Fueled ADS Core in Medium-Fast Spectrum -- A4.1 Core Configurations -- A4.1.1 ADS with 14 MeV Neutrons -- A4.1.2 ADS with 100 MeV Protons -- A4.2 Results of Experiments -- A4.2.1 Criticality and Control Rod Worth -- A4.2.2 PNS and Feynman-α Methods -- A4.3 Kinetic Parameters -- A4.3.1 ADS with 14 MeV Neutrons -- A4.3.2 ADS with 100 MeV Protons -- A4.4 Reaction Rates -- A4.4.1 Core Configurations. A4.4.2 Reaction Rate Distributions -- A4.4.3 Reaction Rates of Activation Foils -- References -- Appendix A5: 232Th-Fueled ADS Core -- A5.1 Core Configurations -- A5.2 Results of Experiments -- A5.2.1 Reaction Rate Distributions -- A5.2.2 PNS and Feynman-α Methods -- References. |
| Record Nr. | UNISA-996466748203316 |
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Pyeon Cheol Ho
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| Springer Nature, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Advances in Mathematical Sciences : AWM Research Symposium, Houston, TX, April 2019 / Bahar Acu ... [et al.] editors
| Advances in Mathematical Sciences : AWM Research Symposium, Houston, TX, April 2019 / Bahar Acu ... [et al.] editors |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xiii, 369 p. : ill. ; 24 cm |
| Soggetto topico |
13-XX - Commutative algebra [MSC 2020]
35-XX - Partial differential equations [MSC 2020] 65-XX - Numerical analysis [MSC 2020] 05-XX - Combinatorics [MSC 2020] 60-XX - Probability theory and stochastic processes [MSC 2020] 54-XX - General topology [MSC 2020] 00B25 - Proceedings of conferences of miscellaneous specific interest [MSC 2020] 97-XX - Mathematics education [MSC 2020] |
| Soggetto non controllato |
Algebraic Combinatorics
Algebraic biology Braid Groups Combinatorics Data science Education research Ensemble Kalman filter Higher order elliptic problems Math education Noncommutative algebra Parameter Estimation Patricle methods Periodic parameters Professional development Quantum symmetry School and district support Sequential Monte Carlo Student enrichment programs Symplectic and contact topology Uncertainty Quantification |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0248597 |
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Analyticity and Sparsity in Uncertainty Quantification for PDEs with Gaussian Random Field Inputs / Dinh Dũng, ... [et al.]
| Analyticity and Sparsity in Uncertainty Quantification for PDEs with Gaussian Random Field Inputs / Dinh Dũng, ... [et al.] |
| Pubbl/distr/stampa | Cham, : Springer, 2023 |
| Descrizione fisica | xv, 207 p. ; 24 cm |
| Soggetto topico |
33C45 - Orthogonal polynomials and functions of hypergeometric type (Jacobi, Laguerre, Hermite, Askey scheme, etc.) [MSC 2020]
65N30 - Finite elements, Rayleigh-Ritz and Galerkin methods, finite methods for boundary value problems involving PDEs [MSC 2020] 41A25 - Rate of convergence, degree of approximation [MSC 2020] 41A46 - Approximation by arbitrary nonlinear expressions; widths and entropy [MSC 2020] 35J15 - Second order elliptic equations [MSC 2020] 28C20 - Set functions and measures and integrals in infinite-dimensional spaces (Wiener measure, Gaussian measure, etc.) [MSC 2020] 65N15 - Error bounds for boundary value problems involving PDEs [MSC 2020] 35B30 - Dependence of solutions to PDEs on initial and/or boundary data and/or on parameters of PDEs [MSC 2020] 65N21 - Numerical methods for inverse problems for boundary value problems involving PDEs [MSC 2020] 35J57 - Boundary value problems for second-order elliptic systems [MSC 2020] 65D40 - Numerical approximation of high-dimensional functions; sparse grids [MSC 2020] |
| Soggetto non controllato |
Finite element methods
Gaussian measures High-dimensional approximation Parametric and Stochastic PDE Partial differential equations Polynomial chaos Smolyak Quadrature Sparse-Grid Interpolation Uncertainty Quantification |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0269844 |
| Cham, : Springer, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Handbook of Uncertainty Quantification / Roger Ghanem, David Higdon, Houman Owhadi editors
| Handbook of Uncertainty Quantification / Roger Ghanem, David Higdon, Houman Owhadi editors |
| Edizione | [Continuously updated edition] |
| Pubbl/distr/stampa | Cham, : Springer, 2019- |
| Descrizione fisica | pag. varia : ill. ; 24 cm |
| Soggetto topico |
91B05 - Risk models (general) [MSC 2020]
60-XX - Probability theory and stochastic processes [MSC 2020] 60A05 - Axioms; other general questions in probability [MSC 2020] 62-XX - Statistics [MSC 2020] 62Pxx - Applications of statistics [MSC 2020] |
| Soggetto non controllato |
Polynomial chaos
Risk Models Risk analysis Sensitivity analysis Uncertainty Quantification |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0127510 |
| Cham, : Springer, 2019- | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Handbook of uncertainty quantification / Roger Ghanem, David Higdon, Houman Owhadi editors
| Handbook of uncertainty quantification / Roger Ghanem, David Higdon, Houman Owhadi editors |
| Pubbl/distr/stampa | Cham, : Springer, 2017 |
| Descrizione fisica | XXV, 2053 p. : ill. ; 24 cm |
| Soggetto topico |
60-XX - Probability theory and stochastic processes [MSC 2020]
62-XX - Statistics [MSC 2020] 91-XX - Game theory, economics, finance, and other social and behavioral sciences [MSC 2020] |
| Soggetto non controllato |
Polynomial chaos
Risk Models Risk analysis Sensitivity analysis Uncertainty Quantification |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0123377 |
| Cham, : Springer, 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Innovations In Insurance, Risk- And Asset Management - Proceedings Of The Innovations In Insurance, Risk- And Asset Management Conference
| Innovations In Insurance, Risk- And Asset Management - Proceedings Of The Innovations In Insurance, Risk- And Asset Management Conference |
| Autore | Glau Kathrin |
| Pubbl/distr/stampa | World Scientific Publishing Co, 2018 |
| Descrizione fisica | 1 online resource (469 pages) |
| Disciplina | 368 |
| Altri autori (Persone) |
LindersDaniel
MinAleksey SchererMatthias SchneiderLorenz ZagstRudi |
| Soggetto non controllato |
Dynamic Hedging
Uncertainty Quantification Actuarial Science Copula Exchange-Traded Funds Autoregressive Hidden Markov Models Fixed Income Reinsurance Stochastic Processes for Finance Risk Measure Bayesian Finance Insurance Replicating Portfolio Risk Classification Stochastic Dominance |
| ISBN |
981-327-256-2
981-327-255-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Contents -- Foreword -- Preface -- About the Editors -- Part I. Innovations in Risk Management -- 1. Behavioral Value Adjustments for Mortgage Valuation -- 1. Introduction -- 2. Literature review -- 3. A general framework for modeling behavioral risk -- 3.1. Defining behavioral risk -- 3.2. A general framework in parallel with credit risk -- 3.3. Behavioral risk adjustments -- 3.4. A general formula for portfolio valuation -- 4. Mortgage portfolio valuation with BIX model -- 4.1. Heterogeneity and granularity -- 4.2. Market factors -- 4.3. Exogenous factors -- 4.4. Marginal exercise probabilities -- 4.5. Hints for calibration -- 4.6. Survival exercise probabilities -- 4.7. Portfolio pricing -- 4.7.1. Expression for II0(X) -- 4.7.2. Expression for II1(X) -- 4.7.3. Expression for II2(X) -- 4.8. Simulation -- 5. Conclusion -- 6. Appendix -- References -- 2. Wrong-Way Risk Adjusted Exposure: Analytical Approximations for Optionsin Default Intensity Models -- 1. Introduction -- 2. Call and put risk-neutral dynamics -- 3. Expected positive exposures under no WWR -- 4. Expected positive exposures under WWR -- 5. Proxys of ts -- 5.1. Q-expectation -- 5.2. Approximation of QCT -expectation -- 6. Potential future exposures (PFE) -- 7. Numerical experiments -- 8. Conclusion -- References -- 3. Consistent Iterated Simulation of Multivariate Defaults: Markov Indicators, Lack of Memory, Extreme-Value Copulas, and the Marshall- Olkin Distribution -- 1. Introduction -- 1.1. Problem one: "Survival-of-all" events -- 1.2. Problem two: "Mixed default/survival" events -- 1.3. Structure of the paper -- 2. Default-time distributions and survival-indicator processes -- 2.1. Markovian survival indicator-processes -- 2.2. Lack-of-memory properties -- 3. Problem one: Iterating "survival-of-all -- 3.1. Lack-of-memory properties revisited.
3.2. Change in dependence when iterating non-self chaining copulas -- 4. Problem two: "Mixed default/survival" events -- 4.1. The looping default model and the Freund distribution -- 4.2. Marshall-Olkin distributions -- 4.3. Case study: Iteration bias for selected multivariate distributions -- 5. Conclusions -- Appendix A. Alternative construction of Markovian processes -- Acknowledgments -- References -- 4. Examples of Wrong-Way Risk in CVA Induced by Devaluations on Default -- 1. Introduction -- 1.1. Overview of the modeling framework -- 2. A PDE approach for both FX-driven and equity-driven WWR -- 2.1. FX -- 2.1.1. No-arbitrage drift for the market risk-factor (FX) -- 2.1.2. Final conditions - CVA payoff -- 2.2. Equity -- 2.2.1. No-arbitrage drift for the market risk-factor (equity) -- 2.2.2. Final conditions - CVA payoff -- 3. A structural approach for equity/credit WWR -- 3.1. AT1P -- 3.1.1. Credit risk -- 3.1.2. Equity price -- 3.2. Introducing WWR -- 4. Results -- 4.1. Models calibrations -- 4.2. Equity WWR: Correlation impact -- 4.3. Equity WWR: Devaluation impact -- 4.4. FX WWR: FX Vega -- 5. Conclusions -- References -- 5. Implied Distributions from Risk-Reversals and Brexit/Trump Predictions -- 1. Introduction -- 2. Literature Review -- 3. Method -- 4. Results -- 4.1. 2016 Brexit referendum -- 4.2. 2016 US election - Trump -- 4.3. 2017 French elections -- 4.4. 2017 UK general election -- 5. Conclusions -- References -- 6. Data and Uncertainty in Extreme Risks: A Nonlinear Expectations Approach -- 1. Introduction -- 2. DR-expectations -- 2.1. Data-robust risk measures -- 3. Regularization from data -- 4. Heavy tails -- 4.1. Expected shortfall -- 4.2. Value at risk -- 4.3. Probability of loss -- 4.4. Integrated tail and Cramer-Lundberg failure probability -- 4.5. Distortion risk -- Appendix -- Acknowledgments -- References. 7. Intrinsic Risk Measures -- 1. Introduction -- 2. Terminology and preliminaries -- 2.1. Acceptance sets -- 2.2. Traditional risk measures -- 2.2.1. Coherent risk measures -- 2.2.2. Convex risk measures -- 2.2.3. Cash-subadditivity and quasi-convexity of risk measures -- 2.2.4. General monetary risk measures -- 3. Intrinsic risk measures -- 3.1. Fundamental concepts -- 3.2. Representation on conic acceptance sets -- 3.3. Efficiency of the intrinsic approach -- 3.4. Dual representations on convex acceptance sets -- 4. Conclusion -- Bibliography -- 8. Pathwise Construction of Affine Processes -- 1. Introduction -- 2. Preliminaries -- 2.1. Notation -- 2.2. Affine processes -- 2.3. Towards the multivariate Lamperti transform -- 2.4. Affine processes of Heston type -- 3. Existence of the solution of the time-change equation -- 3.1. The setting -- 3.2. The core of the proof -- 3.2.1. Approximation of the vector field -- 3.2.2. The algorithm -- 4. Pathwise construction of affine processes with time-change -- Bibliography -- Part II. Innovations in Insurance and Asset Management -- 9. Fixed-Income Returns from Hedge Funds with Negative Fee Structures: Valuation and Risk Analysis -- 1. Introduction -- 2. Hedge fund fee structures: From traditional fee structures to negative fees -- 2.1. Traditional fee structures -- 2.2. From first-loss to negative first-loss fee structure -- 3. Pricing the payoffs -- 4. Risk analysis of the investor's position as a bond -- 4.1. Impact of the manager's deposit c -- 5. Conclusion -- References -- 10. Static Versus Adapted Optimal Execution Strategies in Two Benchmark Trading Models -- 1. Introduction -- 2. Discrete time trading with information flow -- 2.1. Model formulation with cost based criterion -- 2.2. Permanent market impact: Optimal adapted solution -- 2.3. Permanent market impact: Optimal deterministic solution. 2.4. Permanent market impact: Adapted vs deterministic solution -- 3. Continuous time trading with risk function -- 3.1. Model formulation with cost and risk based criterion -- 3.2. Optimal adapted solution under temporary and permanent impact -- 3.3. Optimal static solution under temporary and permanent impact -- 3.4. Comparison of optimal static and adapted solutions -- 4. Conclusions and further research -- References -- 11. Liability Driven Investments with a Link to Behavioral Finance -- 1. Introduction -- 2. A model for assets and liabilities -- 3. Expected utility framework -- 3.1. The optimization problem -- 4. Extension to cumulative prospect theory -- 4.1. The optimization problem -- 4.2. Probability distortion function -- 5. Comparison -- 5.1. Partial surplus optimization -- 5.2. Connection between CPT optimization, funding ratio optimization and partial surplus optimization -- 6. Conclusion -- Acknowledgment -- Appendix A. Solution of the HJB equation -- Appendix B. Quantile optimization approach -- Appendix C. Probability distortion -- Appendix D. Replicating strategies for selected pay-offs -- Bibliography -- 12. Option Pricing and Hedging for Discrete Time Autoregressive Hidden Markov Model -- 1. Introduction -- 2. Regime-switching autoregressive models -- 2.1. Regime prediction -- 2.1.1. Filtering algorithm -- 2.1.2. Conditional distribution -- 2.1.3. Stationary distribution in the Gaussian case -- 2.2. Estimation of parameters -- 2.3. Goodness-of-fit test and selection of the number of regimes -- 2.4. Application to S& -- P 500 daily returns -- 3. Optimal discrete time hedging -- 3.1. Implementation issues -- 3.1.1. Using regime predictions -- 3.2. Optimal hedging vs delta-hedging -- 3.3. Simulated hedging errors -- 4. Out-of-sample vanilla pricing and hedging -- 4.1. Methodology -- 4.1.1. The underlying asset. 4.1.2. Option dataset -- 4.1.3. Backtesting -- 4.2. Empirical results -- 4.2.1. 2008-2009 Financial Crisis -- 4.2.2. 2013-2015 Bull markets -- 5. Conclusion -- Appendix A. Extension of Baum-Welch algorithm -- Appendix A.1. Estimation of regime-switching models -- Appendix B. Goodness-of-fit test for ARHMM -- Appendix B.1. Rosenblatt's transform -- Appendix B.2. Test statistic -- Appendix B.3. Parametric bootstrap algorithm -- References -- 13. Interest Rate Swap Valuation in the Chinese Market -- 1. Introduction -- 2. Pricing model -- 2.1. Dual curve discounting -- 2.2. Single curve discounting -- 2.3. Valuation difference -- 3. Candidates for the risk-free rate in the Chinese swap market -- 4. Numerical test -- 5. Conclusion -- References -- 14. On Consistency of the Omega Ratio with Stochastic Dominance Rules -- 1. Introduction -- 2. Omega ratios and stochastic dominance -- 3. Omega ratios and combined concave and convex stochastic dominance -- References -- 15. Chance-Risk Classification of Pension Products: Scientific Concepts and Challenges -- 1. Introduction -- 2. Typical private pension products offered in Germany -- 3. Aspects of chance-risk classification concepts -- 4. Capital market model and simulation of important product ingredients -- 5. Scientific challenges and outlook -- References -- 16. Forward versus Spot Price Modeling -- 1. Introduction -- 2. Spot and forward model -- 2.1. Spot model -- 2.2. Forward model -- 2.2.1. Wealth process model -- 3. First example: CEV model -- 4. Second example: JDCEV model -- 5. Implications for modeling -- 6. Conclusion -- Appendix A. Martingale property of driving process -- Appendix B. Density of ST in JDCEV model -- References -- 17. Replication Methods for Financial Indexes -- 1. Introduction -- 2. Replication methods -- 2.1. Factorial approach for strong replication -- 2.2. Weak replication. 2.2.1. Implementation steps. |
| Altri titoli varianti |
Innovations in Insurance, Risk- and Asset Management
Innovations in Insurance, Risk- and Asset Management:Proceedings of the Innovations in Insurance, Risk- and Asset Management Conference Innovations in Insurance, Risk- and Asset Management |
| Record Nr. | UNINA-9910349465003321 |
|
Glau Kathrin
|
||
| World Scientific Publishing Co, 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Introduction to uncertainty quantification / T. J. Sullivan
| Introduction to uncertainty quantification / T. J. Sullivan |
| Autore | Sullivan, Timothy J. |
| Pubbl/distr/stampa | [Cham], : Springer, 2015 |
| Descrizione fisica | XII, 342 p. : ill. ; 24 cm |
| Soggetto topico |
65-XX - Numerical analysis [MSC 2020]
42-XX - Harmonic analysis on Euclidean spaces [MSC 2020] 41-XX - Approximations and expansions [MSC 2020] 62-XX - Statistics [MSC 2020] 60G60 - Random fields [MSC 2020] 65Cxx - Probabilistic methods, stochastic differential equations [MSC 2020] 65J22 - Numerical solution to inverse problems in abstract spaces [MSC 2020] |
| Soggetto non controllato |
Computational probability
Distributional robustness Inverse Problems Model order reduction Sensitivity analysis Spectral expansions Uncertainty Quantification |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0113768 |
|
Sullivan, Timothy J.
|
||
| [Cham], : Springer, 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Mathematical problems in meteorological modelling / András Bátkai ... [et al.] editors
| Mathematical problems in meteorological modelling / András Bátkai ... [et al.] editors |
| Pubbl/distr/stampa | [Cham], : Springer, 2016 |
| Descrizione fisica | XV, 264 p. : ill. ; 24 cm |
| Soggetto topico |
65L06 - Multistep, Runge-Kutta and extrapolation methods for ordinary differential equations [MSC 2020]
62H11 - Directional data; spatial statistics [MSC 2020] 86A10 - Meteorology and atmospheric physics [MSC 2020] |
| Soggetto non controllato |
Data Assimilation
Mathematical modeling Numerical weather prediction Partial differential equations Time discretization Uncertainty Quantification |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0114953 |
| [Cham], : Springer, 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Matrix-exponential distributions in applied probability / Mogens Bladt, Bo Friis Nielsen
| Matrix-exponential distributions in applied probability / Mogens Bladt, Bo Friis Nielsen |
| Autore | Bladt, Mogens |
| Pubbl/distr/stampa | New York, : Springer, 2017 |
| Descrizione fisica | xvii, 736 p. : ill. ; 24 cm |
| Altri autori (Persone) | Nielsen, Bo Friis |
| Soggetto topico |
46-XX - Functional analysis [MSC 2020]
60-XX - Probability theory and stochastic processes [MSC 2020] |
| Soggetto non controllato |
Applied probability
Ladder processes Management Science Markov Processes Matrix exponential distributions Numerical methods Operations Research Phase-type distributions Probability Theory and Stochastic Processes Random Walks Regenerative methods Renewal theory Stochastic modeling Uncertainty Quantification |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0123376 |
|
Bladt, Mogens
|
||
| New York, : Springer, 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
