Gebrail Bekdaş & Sinan Melih Nigdeli 
Optimization of Tuned Mass Dampers [PDF ebook] 
Using Active and Passive Control

Підтримка


This book is a timely book to summarize the latest developments in the optimization of tuned mass dampers covering all classical approaches and new trends including metaheuristic algorithms. Also, artificial intelligence and machine learning methods are included to predict optimum results by skipping long optimization processes. Another difference and advantage of the book are to provide chapters about several types of control types including passive tuned mass dampers, active tuned mass dampers, tuned liquid dampers, tuned liquid column dampers and inerter dampers. 


Tuned mass dampers (TMDs) are vibration absorber devices used in all types of mechanic systems. The key factor in the design is an effective tuning of TMDs for the desired performance. In practice, several high-rise structures and bridges were designed by including TMDs. Also, TMDs were installed after the construction of the structures after several negative experiences resulting from the disturbing sway of the structures. In optimum design, several closed-form expressions have been proposed for optimum frequency and damping ratio of TMDs, but the exact optimization requires iterative optimization approaches. The current trend is to use evolutionary algorithms and metaheuristic optimization methods to reach the goal. 

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Зміст

Introduction and Overview: Structural Control and Tuned Mass Dampers.- Robust design of different tuned mass damper techniques to mitigate wind-induced vibrations under uncertain conditions.- Machine Learning-Based Model for Optimum Design of TMDs by Using Artificial Neural Networks.

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Мова Англійська ● Формат PDF ● Сторінки 187 ● ISBN 9783030983437 ● Розмір файлу 7.6 MB ● Редактор Gebrail Bekdaş & Sinan Melih Nigdeli ● Видавець Springer International Publishing ● Місто Cham ● Країна CH ● Опубліковано 2022 ● Завантажувані 24 місяців ● Валюта EUR ● Посвідчення особи 8361961 ● Захист від копіювання Соціальний DRM

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