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Reduced Order Methods for Modeling and Computational Reduction

This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized;

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Model Reduction of Complex Dynamical Systems

order reduction software packages and benchmarks. This volume will be an ideal resource for graduate students and researchers in all areas;

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Reduced-Order Modeling (ROM) for Simulation and Optimization

order reduction (MOR) for simulation, optimization and control. The topical scope includes, but is not limited to, new out-of-the-box;

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Model Order Reduction Techniques with Applications in Finite Element Analysis

by excessive system complexity. Model Order Reduction Techniques explains and compares such methods focusing mainly on recent work;

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Model Order Reduction Techniques with Applications in Finite Element Analysis

, vibration, finite elements and other computational methods in mechanical, aerospace and structural engineering will find Model Order Reduction;

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Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics

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Computational Materials Engineering

evaluating possible methods for improving computational accuracy and efficiency. Beginning with a discussion of conventional fast models;

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Interpolatory Methods for Model Reduction

methods are among the most widely used model reduction techniques, and Interpolatory Methods for Model Reduction is the first comprehensive;

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Advanced Computational Fluid and Aerodynamics

optimization, multiphysics problems, reduced order models, and large scale computations and the future of CFD. Advanced Computational Fluid and;

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Cardiovascular and Respiratory Bioengineering

Cardiovascular and Respiratory Bioengineering focuses on computational tools and modeling techniques in cardiovascular and respiratory;

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Scientific Computing in Electrical Engineering

devices, electromagnetic fields, and coupled problems. The focus in methodology was on model order reduction and uncertainty quantification;

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Sub-structure Coupling for Dynamic Analysis

This book combines a model reduction technique with an efficient parametrization scheme for the purpose of solving a class of complex and;

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Sub-structure Coupling for Dynamic Analysis

This book combines a model reduction technique with an efficient parametrization scheme for the purpose of solving a class of complex and;

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Proper Orthogonal Decomposition Methods for Partial Differential Equations

Proper Orthogonal Decomposition Methods for Partial Differential Equations evaluates the potential applications of POD reduced-order;

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Computational Modeling of Inorganic Nanomaterials

materials. This book shows how computational modeling is critical for understanding inorganic nanomaterials and their future development.;

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A Modern Course in Aeroelasticity

aerodynamic flows using the methods of computational fluid dynamics and reduced order modeling techniques. New chapters on aeroelasticity;

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Computational Modeling of Inorganic Nanomaterials

materials. This book shows how computational modeling is critical for understanding inorganic nanomaterials and their future development.;

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Computational Mathematics

Computational Mathematics depicts a real-life system, which is always challenging for scientists and engineers. Concerned with the design;

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Multigrid Finite Element Methods for Electromagnetic Field Modeling

element-based modal analysis of electromagnetic waveguides and cavities Application of Krylov subspace-based methodologies for reduced-order;

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Scientific Computing in Electrical Engineering

and Simulation, Circuit Simulation, Mathematical and Computational Methods, Model Order Reduction. Each part starts with a general;

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Computational Modeling of Biological Systems

Computational modeling is emerging as a powerful new approach to study and manipulate biological systems. Multiple methods have been;

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Essential Computational Modeling for the Human Body

Analysis: Computational Modeling for the Human Body Vol. 12 (2005). Computational (Mathematical) Modeling is used by scientists and;

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System Reduction for Nanoscale IC Design

cycles in the microelectronics industry, and proposes methods of model reduction which facilitate circuit and device simulation for specific;

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System Reduction for Nanoscale IC Design

cycles in the microelectronics industry, and proposes methods of model reduction which facilitate circuit and device simulation for specific;

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Computational Nanotoxicology

degree of complexity and multifunctionality of ENMs, computational methods originally developed for regular chemicals cannot always be applied;

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Finite Element Modeling of Elastohydrodynamic Lubrication Problems

Modeling; Advanced FEM Modeling, including Model Order Reduction techniques; and Applications, including Pressure, Film Thickness and Friction;

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Computational Methods for Inverse Problems in Imaging

aspects and applications. The formulation of inverse problems in imaging requires accurate mathematical modeling in order to preserve the;

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