This book presents the latest scientific research and application practice findings in the engineering field of maintenance and safety of aging infrastructure . The selected invited contributions will provide an overview of the use of advanced computational and/or experimental techniques in damage and vulnerability assessment as well as maintenance and retrofitting of aging structures and infrastructures (buildings, bridges, lifelines, etc) for minimization of losses and life-cycle-cost. Cost-competent maintenance and management of civil infrastructure requires balanced consideration of both the structure performance and the total cost accrued over the entire life-cycle. Another major problem is that the structure performance is usually reduced during its functioning due to environmental and other factors. Thus, current structural condition state is usually assessed by visual inspection or more advanced automatic structural health monitoring techniques. Furthermore, maintenance managers often require a list of prioritized maintenance interventions for civil infrastructure on an annual and/or long-term basis. Various unavoidable uncertainties associated with both randomness (i.e., aleatory uncertainty) and imperfect knowledge (i.e., epistemic uncertainty) also play a crucial role in management and maintenance of engineering systems. Taking into account the aforementioned issues, this volume aims to present the recent developments of life-cycle maintenance and management planning for deteriorating civil infrastructure considering simultaneously multiple and often competing criteria in terms of condition, safety and life-cycle cost."

The enormous advances in computational hardware and software resources over the last fifteen years resulted in the development of non-conventional data processing and simulation methods. Among these methods artificial intelligence (AI) has been mentioned as one of the most eminent approaches to the so-called intelligent methods of information processing that present a great potential for engineering applications. ""Intelligent Computational Paradigms in Earthquake Engineering"" contains contributions that cover a wide spectrum of very important real-world engineering problems, and explore the implementation of neural networks for the representation of structural responses in earthquake engineering. This book assesses the efficiency of seismic design procedures and describes the latest findings in intelligent optimal control systems and their applications in structural engineering. ""Intelligent Computational Paradigms in Earthquake Engineering"" presents the application of learning machines, artificial neural networks and support vector machines as highly-efficient pattern recognition tools for structural damage detection. It includes an AI-based evaluation of bridge structures using life-cycle cost principles that considers seismic risk, and emphasizes the use of AI methodologies in a geotechnical earthquake engineering application.