The papers in this volume provide an introduction to well known and established system identification methods for structural health monitoring and to more advanced, state-of-the-art tools, able to tackle the challenges associated with actual implementation. Starting with an overview on fundamental methods, introductory concepts are provided on the general framework of time and frequency domain, parametric and non-parametric methods, input-output or output only techniques. Cutting edge tools are introduced including, nonlinear system identification methods; Bayesian tools; and advanced modal identification techniques (such as the Kalman and particle filters, the fast Bayesian FFT method). Advanced computational tools for uncertainty quantification are discussed to provide a link between monitoring and structural integrity assessment. In addition, full scale applications and field deployments that illustrate the workings and effectiveness of the introduced monitoring schemes are demonstrated.

While the word "automation" may conjure images of robots taking over jobs, the reality is much more nuanced. In construction, for instance, automation is less likely to diminish employment opportunities than it is to increase productivity. Indeed, automation alongside the global need for new and updated infrastructure and better and more affordable housing can help shape the direction of the construction industry. The key will be anticipating and preparing for the shift, in part by developing new skills in the current and future workforce. This book presents all aspects of automation in construction pertaining to the use of information technologies in design, engineering, construction technologies, and maintenance and management of constructed facilities. The broad scope encompasses all stages of the construction life cycle from initial planning and design, through the construction of the facility, its operation, and maintenance, to the eventual dismantling and recycling of buildings and engineering structures. Features: Examines Building Information Management systems, allowing on-site execution of construction more efficient, and for project teams to eliminate mistakes and better coordinate the workforce Presents the latest information on the automation of modular construction, production in factories, including 3-D printing of components such as facades, or even load-bearing and essential components

The papers in this volume provide an introduction to well known and established system identification methods for structural health monitoring and to more advanced, state-of-the-art tools, able to tackle the challenges associated with actual implementation. Starting with an overview on fundamental methods, introductory concepts are provided on the general framework of time and frequency domain, parametric and non-parametric methods, input-output or output only techniques. Cutting edge tools are introduced including, nonlinear system identification methods; Bayesian tools; and advanced modal identification techniques (such as the Kalman and particle filters, the fast Bayesian FFT method). Advanced computational tools for uncertainty quantification are discussed to provide a link between monitoring and structural integrity assessment. In addition, full scale applications and field deployments that illustrate the workings and effectiveness of the introduced monitoring schemes are demonstrated.