During the past decade, monitoring concepts for structural systems have been subjected to a rapid development process. They have become more and more important in the intervention planning (e.g., maintenance, repair, rehabilitation, replacement) on new and existing structures. Nevertheless, there is still a strong need for the efficient use of structural monitoring data in the reliability assessment and prediction models. Updating prediction models, based on monitoring data, affect the intervention strategies. Since these strategies involve costs, monitoring systems assist the efficient spending of available budgets. Therefore, the demand for the efficient use of monitoring data is not only related to structural reliability, but also to cost aspects. In an extended sense, structural monitoring can be considered similar to quality assurance and acceptance sampling, since it is not practically possible to continuously monitor all performance indicators in all critical sections of an entire structural system...

The implementation of reliability methods for designing new structures and assessing the safety and evaluating the performance of existing structures and infrastructure systems has gained widespread acceptance. Consequently, reliability-based design specifications in the form of load and resistance factor design (LRFD) methods have dominated the development of current codes and standards. This paper reviews the reliability-based performance criteria used to calibrate design and evaluation codes and standards for assessing the strength, serviceability, and fatigue resistance of structural components. The review shows that large differences exist in the target reliability levels adopted for evaluating the strength of various types of structural members and materials. These differences result from many factors, including (1) intended structure design and service life; (2) expected member modes of failure (e.g., ductile or brittle); (3) importance of the individual member to overall system integrity (...

In most state-of-the-art Bridge Management Systems, structural condition is predicted by a homogeneous Markov chain model that uses condition ratings assigned during visual inspections. Although generally accepted, such an approach exhibits certain shortcomings, one of which is not considering the nature of actual physical phenomena that cause deterioration. To overcome this shortcoming, this article presents a framework that combines both information on condition ratings through the semi-Markov process and knowledge of bridge properties using analytical deterioration models. In this manner, and contrary to current practice, not only are the results of visual inspection taken into account, but also information such as environmental loading, as well as material and structural properties. The presented framework was implemented in the case study bridge, in which the deterioration caused by carbonation-induced corrosion was studied. Along with the implementation in the case study, the article contained a detailed overview of the subject of carbonation-induced corrosion and emphasized issues that require additional research in order to develop the framework into a comprehensive and fully applicable tool for condition prediction. Accounting for its adaptability to other material types and deterioration processes and its consideration of the historic deterioration path, the framework presents a suitable alternative to frameworks presently implemented for condition prediction.

A complex interdisciplinary approach to the reliability assessment of reinforced concrete structures is introduced and demonstrated on a real existing bridge structure. The reliability index of the structure decreases during its life cycle due to material degradation. A retrofitting to the desired reliability level should be performed. This procedure is modeled by advanced life-cycle computer simulation. The main feature of the presented approach is the nonlinear finite-element analysis of the structure employed for the realistic assessment of structural behavior. A suitable technique of statistical sampling, which allows a relatively small number of simulations, is used in this context. Analytical deterioration models combined with in situ monitoring are used to launch the degradation process. The presented methodology for advanced life-cycle analysis is integrated in the innovative decision-making tool that supports maintenance planning of engineering structures.

The paper presents a review of testing methods and a classification of strategies and tools in terms of technologies and techniques applied to the monitoring of tunnels. In particular, the topic is contextualized through a brief introduction in Chapter 1, followed by defect taxonomy and degradation mechanisms in Chapters 2 and 3, respectively. Chapters 4 and 5 are related to monitoring strategies and technologies. The former consists of purpose‐based categorization of monitoring policies, while the latter consists of classification of monitoring methods including nondestructive and semidestructive techniques as well as of classification of various types of sensors also based on the physical or chemical quantity measured. General rules of implementation and operation of tunnel monitoring systems are presented taking into account international expert knowledge as well as contemporary practical experience in Austria. Considered issues are related to the fib Model Code 2020 (MC2020) focused on evaluation of structural performance assisted by monitoring and testing. Chapter 6 presents challenges related to the monitoring implementation and operation. Chapter 7 discusses about monitoring characteristics in new tunnel, including data acquisition‐transmission and specific monitoring techniques. Chapter 8 instead treats a particular topic related to considerations related to monitoring characteristics of existing tunnel under investigation. Concluding remarks and references finally close the paper.