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Ab initio Quantum Monte Carlo Tutorial : Going beyond DFT / / by Ryo Maezono
| Ab initio Quantum Monte Carlo Tutorial : Going beyond DFT / / by Ryo Maezono |
| Autore | Maezono Ryo |
| Edizione | [1st ed. 2026.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2026 |
| Descrizione fisica | 1 online resource (486 pages) |
| Disciplina | 620.100285 |
| Collana | Chemistry and Materials Science Series |
| Soggetto topico |
Materials science - Data processing
Chemistry - Data processing Quantum chemistry Materials Chemistry Computer simulation Computational Materials Science Computational Chemistry Quantum Chemistry Computational Design Of Materials |
| ISBN | 981-9541-34-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Introduction -- 2. Running a calculation first -- 3. Diffusion Monte Carlo method -- 4. Variational optimization of many-body wavefunctions -- 5. Generating trial nodes with a DFT package -- 6. Review of procedures and molecular system calculations -- 7. Theory of diffusion Monte Carlo method -- 8. Further topics on underlying theory -- 9. Practical topics -- 10. Essence of many-body electronic correlation theory -- 11. Appendix A: Terminal Setting (For Macintosh) -- 12. Appendix B: Terminal Environment Setup (Windows Version) -- 13. Appendix C: Derivation of the diffusion equation from random walk -- 14. Appendix D: Supplementary remarks on mathematical topics -- 15. Appendix E: Supplementary notes on electronic structure theory.-16. Appendix F: Notes on density functional theory -- 17. Appendix G: Tools used in many-body perturbation theory -- 18. Appendix H: Overview of many-body perturbation theory.-Index. |
| Record Nr. | UNINA-9911061733803321 |
Maezono Ryo
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2026 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Computerized symbolic manipulation in mechanics / edited by E. Kreuzer
| Computerized symbolic manipulation in mechanics / edited by E. Kreuzer |
| Pubbl/distr/stampa | Wien [etc.] : Springer, copyr. 1994 |
| Descrizione fisica | 262 p. : ill. ; 24 cm |
| Disciplina | 620.100285 |
| Collana | Courses and lectures / International centre for mechanical sciences |
| Soggetto topico |
Meccanica applicata - Modelli matematici
Sistemi meccanici - Analisi - Impiego degli elaboratori elettronici |
| ISBN | 3-211-82616-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-990000361710203316 |
| Wien [etc.] : Springer, copyr. 1994 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Current Trends and Open Problems in Computational Mechanics / / edited by Fadi Aldakheel, Blaž Hudobivnik, Meisam Soleimani, Henning Wessels, Christian Weißenfels, Michele Marino
| Current Trends and Open Problems in Computational Mechanics / / edited by Fadi Aldakheel, Blaž Hudobivnik, Meisam Soleimani, Henning Wessels, Christian Weißenfels, Michele Marino |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (587 pages) |
| Disciplina |
620.10015118
620.100285 |
| Collana | Engineering Series |
| Soggetto topico |
Mechanics, Applied
Solids Mathematics - Data processing Solid Mechanics Computational Science and Engineering |
| ISBN | 3-030-87312-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1: Multiphysics computation of thermomechanical fatigue in electronics under electrical loading -- Chapter 2: Phase-field modeling of fatigue crack propagation in brittle materials -- Chapter 3: A non-intrusive global/local cycle-jumping techniques: application to visco-plastic structures -- Chapter 4: VEM approach for homogenization of fibre-reinforced composites with curvilinear inclusions -- Chapter 5: Free Bloch wave propagation in periodic Cauchy materials: analytical and computational strategies -- Chapter 6: Divergence free VEM for the Stokes problem with no internal degrees of freedom -- Chapter 7: Strategy for Preventing Membrane Locking through Reparametrization -- Chapter 8: Model-free fracture mechanics and fatigue -- Chapter 9: Node based non-invasive form finding revisited - the challenge of remeshing -- Chapter 10: Micropolar modelling of periodic Cauchy materials based on asymptotic homogenization -- Chapter 11: Experimental and numerical investigation of granules as crash-absorber in ship building -- Chapter 12: On Hydraulic Fracturing in Fully and Partially Saturated Brittle Porous Material -- Chapter13: Efficient two-scale modeling of porous media using numerical model reduction with fully computable error bounds -- Chapter 14: Perspectives on the master-master contact formulation -- Chapter 15: Remarks on the History of Glacier Research and the Flow Law of Ice -- Chapter 16: Anisotropic Failure Criteria in Relation to Crack Phase-Field Modeling at Finite Strains. |
| Record Nr. | UNINA-9910552732303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Materials Informatics and Catalysts Informatics : An Introduction / / by Keisuke Takahashi, Lauren Takahashi
| Materials Informatics and Catalysts Informatics : An Introduction / / by Keisuke Takahashi, Lauren Takahashi |
| Autore | Takahashi Keisuke |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (301 pages) |
| Disciplina | 620.100285 |
| Altri autori (Persone) | TakahashiLauren |
| Soggetto topico |
Materials science - Data processing
Cheminformatics Catalysis Chemistry - Data processing Graph theory Computational Materials Science Computational Chemistry Graph Theory |
| ISBN | 981-9702-17-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. An Introduction to Materials Informatics and Catalysts Informatics -- Chapter 2. Developing an Informatics Work Environment -- Chapter 3. Programming -- Chapter 4. Programming and Python -- Chapter 5. Data and Materials and Catalysts Informatics -- Chapter 6. Data Visualization -- Chapter 7. Machine Learning -- Chapter 8. Supervised Machine Learning -- Chapter 9. Unsupervised Machine Learning and Beyond Machine Learning. |
| Record Nr. | UNINA-9910847088503321 |
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Takahashi Keisuke
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Multidisciplinary design optimization in computational mechanics [[electronic resource] /] / edited by Piotr Breitkopf, Rajan Filomeno Coelho
| Multidisciplinary design optimization in computational mechanics [[electronic resource] /] / edited by Piotr Breitkopf, Rajan Filomeno Coelho |
| Pubbl/distr/stampa | London, : ISTE |
| Descrizione fisica | 1 online resource (573 p.) |
| Disciplina | 620.100285 |
| Altri autori (Persone) |
BreitkopfPiotr
CoelhoRajan Filomeno |
| Collana | ISTE |
| Soggetto topico |
Engineering design
Engineering mathematics |
| ISBN |
1-118-60015-0
1-118-60002-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Multidisciplinary Design Optimization in Computational Mechanics; Title Page; Copyright Page; Table of Contents; Foreword; Notes for Instructors; Acknowledgements; Chapter 1. Multilevel Multidisciplinary Optimization in Airplane Design; 1.1. Introduction; 1.2. Overview of the traditional airplane design process and expected MDO contributions; 1.3. First step toward MDO: local dimensioning by mathematical optimization; 1.4. Second step toward MDO: multilevel multidisciplinary dimensioning; 1.5. Elements of an MDO process; 1.6. Choice of optimizers; 1.6.1. Deterministic algorithms
1.6.2. Stochastic algorithms1.7. Coupling between levels; 1.7.1. Reduction of mathematical models; 1.7.2. Simplified physical models; 1.8. Post-processing; 1.8.1. Lagrange multipliers; 1.8.2. Pareto fronts; 1.8.3. Self-organizing maps; 1.9. Conclusion; Chapter 2. Response Surface Methodology and Reduced Order Models; 2.1. Introduction; 2.2. Introducing some more notations; 2.3. Linear regression; 2.3.1. Introduction to linear regression; 2.3.2. Leverage; 2.3.3. Generalized linear regression; 2.3.4. An implicit reduced order model: moving least-squares (MLS) method 2.3.5. Bias-variance trade-off2.4. Non-linear regression; 2.4.1. Neural networks as an example of non-linear models; 2.4.2. Another example of a non-linear model: parametrized RBFs; 2.4.3. Gradient algorithms; 2.4.4. Second-order methods; 2.5. Kriging interpolation; 2.5.1. Recall on Gaussian regression; 2.5.2. Basic principles of kriging algorithms; 2.5.3. Trend estimation; 2.5.4. Covariance estimation; 2.6. Non-parametric regression and kernel-based methods; 2.6.1. Introduction to non-parametric methods; 2.6.2. Parzen window regression; 2.6.3. Radial basis functions (RBFs) 2.6.4. EM estimation of a mixture2.6.5. How RBFs are used in this book; 2.7. Support vector regression; 2.7.1. Variational formulation of SVR; 2.7.2. Dual formulation of SVR; 2.7.3. Computation of SVR models; 2.7.4. Self-reproducing Hilbert space; 2.7.5. Regularizing properties of the kernel; 2.7.6. Margin selection and ν-regression; 2.7.7. Large databases and recursive learning; 2.8. Model selection; 2.8.1. Estimating generalization error; 2.8.2. Cross-validation methods; 2.8.3. Leverage methods; 2.9. Introduction to design of computer experiments (DoCE); 2.9.1. Classical techniques 2.9.2. Input space sampling2.9.3. Adaptive learning and sequential design; 2.10. Bibliography; Chapter 3. PDE Metamodeling using Principal Component Analysis; 3.1. Principal component analysis (PCA); 3.2. Truncation rank and projector error; 3.3. Application: POD reduction of velocity fields in an engine combustion chamber; 3.4. Reduced-basis methods, numerical analysis; 3.4.1. POD-Galerkin projection method; 3.4.2. Dual approach POD-Petrov-Galerkin; 3.5. Intrusive/non-intrusive aspects; 3.6. Double reduction in both space and parameter dimensions; 3.7. The weighted residual method 3.8. Non-linear problems |
| Record Nr. | UNINA-9910141601803321 |
| London, : ISTE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Multidisciplinary design optimization in computational mechanics [[electronic resource] /] / edited by Piotr Breitkopf, Rajan Filomeno Coelho
| Multidisciplinary design optimization in computational mechanics [[electronic resource] /] / edited by Piotr Breitkopf, Rajan Filomeno Coelho |
| Pubbl/distr/stampa | London, : ISTE |
| Descrizione fisica | 1 online resource (573 p.) |
| Disciplina | 620.100285 |
| Altri autori (Persone) |
BreitkopfPiotr
CoelhoRajan Filomeno |
| Collana | ISTE |
| Soggetto topico |
Engineering design
Engineering mathematics |
| ISBN |
1-118-60015-0
1-118-60002-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Multidisciplinary Design Optimization in Computational Mechanics; Title Page; Copyright Page; Table of Contents; Foreword; Notes for Instructors; Acknowledgements; Chapter 1. Multilevel Multidisciplinary Optimization in Airplane Design; 1.1. Introduction; 1.2. Overview of the traditional airplane design process and expected MDO contributions; 1.3. First step toward MDO: local dimensioning by mathematical optimization; 1.4. Second step toward MDO: multilevel multidisciplinary dimensioning; 1.5. Elements of an MDO process; 1.6. Choice of optimizers; 1.6.1. Deterministic algorithms
1.6.2. Stochastic algorithms1.7. Coupling between levels; 1.7.1. Reduction of mathematical models; 1.7.2. Simplified physical models; 1.8. Post-processing; 1.8.1. Lagrange multipliers; 1.8.2. Pareto fronts; 1.8.3. Self-organizing maps; 1.9. Conclusion; Chapter 2. Response Surface Methodology and Reduced Order Models; 2.1. Introduction; 2.2. Introducing some more notations; 2.3. Linear regression; 2.3.1. Introduction to linear regression; 2.3.2. Leverage; 2.3.3. Generalized linear regression; 2.3.4. An implicit reduced order model: moving least-squares (MLS) method 2.3.5. Bias-variance trade-off2.4. Non-linear regression; 2.4.1. Neural networks as an example of non-linear models; 2.4.2. Another example of a non-linear model: parametrized RBFs; 2.4.3. Gradient algorithms; 2.4.4. Second-order methods; 2.5. Kriging interpolation; 2.5.1. Recall on Gaussian regression; 2.5.2. Basic principles of kriging algorithms; 2.5.3. Trend estimation; 2.5.4. Covariance estimation; 2.6. Non-parametric regression and kernel-based methods; 2.6.1. Introduction to non-parametric methods; 2.6.2. Parzen window regression; 2.6.3. Radial basis functions (RBFs) 2.6.4. EM estimation of a mixture2.6.5. How RBFs are used in this book; 2.7. Support vector regression; 2.7.1. Variational formulation of SVR; 2.7.2. Dual formulation of SVR; 2.7.3. Computation of SVR models; 2.7.4. Self-reproducing Hilbert space; 2.7.5. Regularizing properties of the kernel; 2.7.6. Margin selection and ν-regression; 2.7.7. Large databases and recursive learning; 2.8. Model selection; 2.8.1. Estimating generalization error; 2.8.2. Cross-validation methods; 2.8.3. Leverage methods; 2.9. Introduction to design of computer experiments (DoCE); 2.9.1. Classical techniques 2.9.2. Input space sampling2.9.3. Adaptive learning and sequential design; 2.10. Bibliography; Chapter 3. PDE Metamodeling using Principal Component Analysis; 3.1. Principal component analysis (PCA); 3.2. Truncation rank and projector error; 3.3. Application: POD reduction of velocity fields in an engine combustion chamber; 3.4. Reduced-basis methods, numerical analysis; 3.4.1. POD-Galerkin projection method; 3.4.2. Dual approach POD-Petrov-Galerkin; 3.5. Intrusive/non-intrusive aspects; 3.6. Double reduction in both space and parameter dimensions; 3.7. The weighted residual method 3.8. Non-linear problems |
| Record Nr. | UNINA-9910830099103321 |
| London, : ISTE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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A Numerical Approach to the Classical Laminate Theory of Composite Materials : The Composite Laminate Analysis Tool—CLAT v2.0 / / by Andreas Öchsner, Resam Makvandi
| A Numerical Approach to the Classical Laminate Theory of Composite Materials : The Composite Laminate Analysis Tool—CLAT v2.0 / / by Andreas Öchsner, Resam Makvandi |
| Autore | Öchsner Andreas |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (181 pages) |
| Disciplina | 620.100285 |
| Altri autori (Persone) | MakvandiResam |
| Collana | Advanced Structured Materials |
| Soggetto topico |
Materials science - Data processing
Continuum mechanics Composite materials Computational Materials Science Continuum Mechanics Composites |
| ISBN |
9783031329753
3031329759 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Introduction -- 2. Classical Laminate Theory -- 3. Composite Laminate Analysis Tool - CLAT -- 4. Application Examples -- 5. Source Codes. |
| Record Nr. | UNINA-9910734849003321 |
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Öchsner Andreas
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Phase Field Theory in Materials Physics : The Hodograph Equation / / by Peter Galenko
| Phase Field Theory in Materials Physics : The Hodograph Equation / / by Peter Galenko |
| Autore | Galenko Peter |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (240 pages) |
| Disciplina | 620.100285 |
| Soggetto topico |
Materials science - Data processing
Condensed matter Metals Thermodynamics Mathematical physics Computational Materials Science Structure of Condensed Matter Metals and Alloys Phase Transitions and Multiphase Systems Mathematical Methods in Physics |
| ISBN |
9783031492785
3031492781 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Phase Interfaces -- Phase Field -- Gibbs Free Energy: Equilibrium and Dynamics -- Approach to Fast Transformations -- The Hodograph Equation -- Velocity-Dependent Herring Equation. |
| Record Nr. | UNINA-9910835061003321 |
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Galenko Peter
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Smart Materials Engineering : Data-Driven Approaches and Multiscale Modelling / / edited by Ali Ahmadian, Sambhrant Srivastava, Ashok Kumar Yadav, Vijay Kumar, Pramod Kumar Srivastava
| Smart Materials Engineering : Data-Driven Approaches and Multiscale Modelling / / edited by Ali Ahmadian, Sambhrant Srivastava, Ashok Kumar Yadav, Vijay Kumar, Pramod Kumar Srivastava |
| Autore | Ahmadian Ali |
| Edizione | [1st ed. 2026.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026 |
| Descrizione fisica | 1 online resource (301 pages) |
| Disciplina | 620.100285 |
| Altri autori (Persone) | Ahmadian |
| Collana | Physics and Astronomy Series |
| Soggetto topico |
Materials science - Data processing
Artificial intelligence Nanotechnology Materials Bionics Sustainability Computational Materials Science Artificial Intelligence Bioinspired Materials |
| ISBN | 3-032-09540-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine Learning’s Emergence in Predictive and Prescriptive Materials Design Modeling -- Recent Advances in Nano-Hybrid Composite Systems: Toward Smart and Sustainable Functional Materials -- Smart Material Design: Integrating Data-Driven Optimization and Complexity Analysis for Next-Generation Materials -- Eco-Innovative Fiber Composites: Utilization of Industrial and Agricultural Waste for Sustainable Structures -- Green Revolution in Composites: A Review on Bio-Based and Agricultural Waste-Derived Composite Materials -- Fuzzy Logic-based Energy-Efficient Trust Evaluation Scheme in Sensor Assisted Industry 4.0 -- AI-Driven Terrain Segmentation and Material Interaction Modeling for Extraterrestrial Landings -- Experimental Trial-and-Error Optimization of Microwave-Assisted Fabrication Parameters for Hybrid Laminates: Development and Characterization for Smart Structural Applications -- Recent Research Challenges while Applying Machine Learning in Materials Science -- Emerging Challenges and Future Directions in Multiscale Modelling for Integration of Biology and Materials Design -- Machine Learning in Materials Science: Current Challenges and Future Outlook. |
| Record Nr. | UNINA-9911049105403321 |
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Ahmadian Ali
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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