Proceedings of the 16th International Modal Analysis Conference PDF Download

Author: Alfred L. Wicks
Publisher:
ISBN:
Category : Modal analysis
Languages : en
Pages : 836

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Author: Society for Experimental Mechanics (U.S.)
Publisher:
ISBN:
Category : Modal analysis
Languages : en
Pages : 1054

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Author: Zhi-Fang Fu
Publisher: Elsevier
ISBN: 0080511783
Category : Technology & Engineering
Languages : en
Pages : 305

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Modal Analysis provides a detailed overview of the theory of analytical and experimental modal analysis and its applications. Modal Analysis is the processes of determining the inherent dynamic characteristics of any system and using them to formulate a mathematical model of the dynamic behavior of the system. In the past two decades it has become a major technological tool in the quest for determining, improving and optimizing dynamic characteristics of engineering structures. Its main application is in mechanical and aeronautical engineering, but it is also gaining widespread use in civil and structural engineering, biomechanical problems, space structures, acoustic instruments and nuclear engineering. - The only book to focus on the theory of modal analysis before discussing applications - A relatively new technique being utilized more and more in recent years which is now filtering through to undergraduate courses - Leading expert in the field

Author: Zu-Qing Qu
Publisher: Springer Science & Business Media
ISBN: 1447138279
Category : Mathematics
Languages : en
Pages : 379

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Despite the continued rapid advance in computing speed and memory the increase in the complexity of models used by engineers persists in outpacing them. Even where there is access to the latest hardware, simulations are often extremely computationally intensive and time-consuming when full-blown models are under consideration. The need to reduce the computational cost involved when dealing with high-order/many-degree-of-freedom models can be offset by adroit computation. In this light, model-reduction methods have become a major goal of simulation and modeling research. Model reduction can also ameliorate problems in the correlation of widely used finite-element analyses and test analysis models produced by excessive system complexity. Model Order Reduction Techniques explains and compares such methods focusing mainly on recent work in dynamic condensation techniques: - Compares the effectiveness of static, exact, dynamic, SEREP and iterative-dynamic condensation techniques in producing valid reduced-order models; - Shows how frequency shifting and the number of degrees of freedom affect the desirability and accuracy of using dynamic condensation; - Answers the challenges involved in dealing with undamped and non-classically damped models; - Requires little more than first-engineering-degree mathematics and highlights important points with instructive examples. Academics working in research on structural dynamics, MEMS, vibration, finite elements and other computational methods in mechanical, aerospace and structural engineering will find Model Order Reduction Techniques of great interest while it is also an excellent resource for researchers working on commercial finite-element-related software such as ANSYS and Nastran.

Author: Mathias Weske
Publisher: Springer
ISBN: 3319986481
Category : Computers
Languages : en
Pages : 526

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This book constitutes the proceedings of the 16th International Conference on Business Process Management, BPM 2018, held in Sydney, Australia, in September 2018. The 27 papers presented in this volume were carefully reviewed and selected from 140 submissions. They were organized in topical sections named: reflections on BPM; concepts and methods in business process modeling and analysis; foundations of process discovery; alignments and conformance checking; process model analysis and machine learning; digital process innovation; and method analysis and selection.

Author: Alfred L. Wicks
Publisher:
ISBN:
Category : Modal analysis
Languages : en
Pages : 1136

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Author: G.R Tomlinson
Publisher: CRC Press
ISBN: 9780750305471
Category : Technology & Engineering
Languages : en
Pages : 858

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Significant changes have occurred in materials science, including increasing demands on life extensions, and the reliability and exploitability of components, materials, and structures. These changes provide smart technologies with excellent application opportunities in aerospace, civil and electrical engineering, transportation, manufacturing, communications, defense, and medicine. Smart Materials and Structures presents an overview of current developments in the characterization and applications of materials and actuators, issues surrounding their control, and the integration of smart systems and technologies. This compendium provides a valuable synopsis of this rapidly expanding and topical research field for engineers, program managers, technologists, physicists, materials scientists, and mathematicians working to advance smart materials, research methods, their applications, and robotic technologies.

Author: Tshilidzi Marwala
Publisher: John Wiley & Sons
ISBN: 1119153018
Category : Technology & Engineering
Languages : en
Pages : 248

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Probabilistic Finite Element Model Updating Using Bayesian Statistics: Applications to Aeronautical and Mechanical Engineering Tshilidzi Marwala and Ilyes Boulkaibet, University of Johannesburg, South Africa Sondipon Adhikari, Swansea University, UK Covers the probabilistic finite element model based on Bayesian statistics with applications to aeronautical and mechanical engineering Finite element models are used widely to model the dynamic behaviour of many systems including in electrical, aerospace and mechanical engineering. The book covers probabilistic finite element model updating, achieved using Bayesian statistics. The Bayesian framework is employed to estimate the probabilistic finite element models which take into account of the uncertainties in the measurements and the modelling procedure. The Bayesian formulation achieves this by formulating the finite element model as the posterior distribution of the model given the measured data within the context of computational statistics and applies these in aeronautical and mechanical engineering. Probabilistic Finite Element Model Updating Using Bayesian Statistics contains simple explanations of computational statistical techniques such as Metropolis-Hastings Algorithm, Slice sampling, Markov Chain Monte Carlo method, hybrid Monte Carlo as well as Shadow Hybrid Monte Carlo and their relevance in engineering. Key features: Contains several contributions in the area of model updating using Bayesian techniques which are useful for graduate students. Explains in detail the use of Bayesian techniques to quantify uncertainties in mechanical structures as well as the use of Markov Chain Monte Carlo techniques to evaluate the Bayesian formulations. The book is essential reading for researchers, practitioners and students in mechanical and aerospace engineering.

Author: Ka-Veng Yuen
Publisher: John Wiley & Sons
ISBN: 9780470824559
Category : Mathematics
Languages : en
Pages : 320

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Book Description
Bayesian methods are a powerful tool in many areas of science and engineering, especially statistical physics, medical sciences, electrical engineering, and information sciences. They are also ideal for civil engineering applications, given the numerous types of modeling and parametric uncertainty in civil engineering problems. For example, earthquake ground motion cannot be predetermined at the structural design stage. Complete wind pressure profiles are difficult to measure under operating conditions. Material properties can be difficult to determine to a very precise level – especially concrete, rock, and soil. For air quality prediction, it is difficult to measure the hourly/daily pollutants generated by cars and factories within the area of concern. It is also difficult to obtain the updated air quality information of the surrounding cities. Furthermore, the meteorological conditions of the day for prediction are also uncertain. These are just some of the civil engineering examples to which Bayesian probabilistic methods are applicable. Familiarizes readers with the latest developments in the field Includes identification problems for both dynamic and static systems Addresses challenging civil engineering problems such as modal/model updating Presents methods applicable to mechanical and aerospace engineering Gives engineers and engineering students a concrete sense of implementation Covers real-world case studies in civil engineering and beyond, such as: structural health monitoring seismic attenuation finite-element model updating hydraulic jump artificial neural network for damage detection air quality prediction Includes other insightful daily-life examples Companion website with MATLAB code downloads for independent practice Written by a leading expert in the use of Bayesian methods for civil engineering problems This book is ideal for researchers and graduate students in civil and mechanical engineering or applied probability and statistics. Practicing engineers interested in the application of statistical methods to solve engineering problems will also find this to be a valuable text. MATLAB code and lecture materials for instructors available at http://www.wiley.com/go/yuen

Author: Gaetan Kerschen
Publisher: Springer
ISBN: 3319297392
Category : Technology & Engineering
Languages : en
Pages : 414

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Nonlinear Dynamics, Volume 1. Proceedings of the 34th IMAC, A Conference and Exposition on Dynamics of Multiphysical Systems: From Active Materials to Vibroacoustics, 2016, the fi rst volume of ten from the Conference, brings together contributions to this important area of research and engineering. Th e collection presents early fi ndings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: • Nonlinear Oscillations • Nonlinear Modal Analysis • Nonlinear System Identifi cation • Nonlinear Modeling & Simulation • Nonlinearity in Practice • Nonlinearity in Multi-Physics Systems • Nonlinear Modes and Modal Interactions