T. T. Soong – författare

This comprehensive handbook is designed to provide the reader with the knowledge needed to successfully implement an active, hybrid or semi-active control system to a structure, safeguarding it against environmental forces such as wind or earthquakes. Written by leading experts in structural control, this book: Emphasises fail-safe techniques and validates their implementation through simulations.Examines the implicit issues between theoretical development and actual implementation of systems.Identifies important hardware and software safety features.Describes a PC-based system simulator, which simulates the real-time response of structure and control hardware.Active, Hybrid and Semi-active Structural Control is a must have reference for researchers, practitioners and design engineers working in civil, aerospace, automotive and mechanical engineering. It is undoubtedly the key resource for all postgraduate students in this rapidly growing area of research interest and development.

This textbook differs from others in the field in that it has been prepared very much with students and their needs in mind, having been classroom tested over many years.  It is a true “learner’s book” made for students who require a deeper understanding of probability and statistics. It presents the fundamentals of the subject along with concepts of probabilistic modelling, and the process of model selection, verification and analysis.  Furthermore, the inclusion of more than 100 examples and 200 exercises (carefully selected from a wide range of topics), along with a solutions manual for instructors, means that this text is of real value to students and lecturers across a range of engineering disciplines. Key features: Presents the fundamentals in probability and statistics along with relevant applications.Explains the concept of probabilistic modelling and the process of model selection, verification and analysis.Definitions and theorems are carefully stated and topics rigorously treated.Includes a chapter on regression analysis.Covers design of experiments.Demonstrates practical problem solving throughout the book with numerous examples and exercises purposely selected from a variety of engineering fields.Includes an accompanying online Solutions Manual for instructors containing complete step-by-step solutions to all problems.

This textbook differs from others in the field in that it has been prepared very much with students and their needs in mind, having been classroom tested over many years.  It is a true “learner’s book” made for students who require a deeper understanding of probability and statistics. It presents the fundamentals of the subject along with concepts of probabilistic modelling, and the process of model selection, verification and analysis.  Furthermore, the inclusion of more than 100 examples and 200 exercises (carefully selected from a wide range of topics), along with a solutions manual for instructors, means that this text is of real value to students and lecturers across a range of engineering disciplines. Key features: Presents the fundamentals in probability and statistics along with relevant applications.Explains the concept of probabilistic modelling and the process of model selection, verification and analysis.Definitions and theorems are carefully stated and topics rigorously treated.Includes a chapter on regression analysis.Covers design of experiments.Demonstrates practical problem solving throughout the book with numerous examples and exercises purposely selected from a variety of engineering fields.Includes an accompanying online Solutions Manual for instructors containing complete step-by-step solutions to all problems.

This textbook differs from others in the field in that it has been prepared very much with students and their needs in mind, having been classroom tested over many years.  It is a true “learner’s book” made for students who require a deeper understanding of probability and statistics. It presents the fundamentals of the subject along with concepts of probabilistic modelling, and the process of model selection, verification and analysis.  Furthermore, the inclusion of more than 100 examples and 200 exercises (carefully selected from a wide range of topics), along with a solutions manual for instructors, means that this text is of real value to students and lecturers across a range of engineering disciplines.

Key features:

Presents the fundamentals in probability and statistics along with relevant applications. Explains the concept of probabilistic modelling and the process of model selection, verification and analysis. Definitions and theorems are carefully stated and topics rigorously treated. Includes a chapter on regression analysis. Covers design of experiments. Demonstrates practical problem solving throughout the book with numerous examples and exercises purposely selected from a variety of engineering fields. Includes an accompanying online Solutions Manual for instructors containing complete step-by-step solutions to all problems.