This paper describes the development, implementation and evolution of applied research by the Iowa DOT to better understand how SHM may be used to more effectively manage their bridges. Bridge management is a critical responsibility for highway agencies. Fortunately, advances in technology have allowed for the development and deployment of many types of monitoring schemes. Selected case studies are presented to help describe how the Iowa DOT effectively integrated SHM in their current responsibilities. SHM has been used on wide range of bridge applications in Iowa such as capacity evaluation of deficient or damaged structures, construction phase monitoring, in-service assessment of vulnerable details, security and many others. Working with researchers at Iowa State University (ISU), initial efforts utilized existing technologies for short term monitoring and then advanced into the development of the state of art systems for long term monitoring using fiber optic (strain-based). The SHM system autonomously records, processes and evaluates strain data, and assesses damage in essentially real-time. More recent research has focused on development of broader based monitoring systems that assess both structural and non-structural conditions.

An important challenge for widespread application of structural health monitoring (SHM) in civil engineering is the creation and implementation of algorithms for automatic and reliable detection of unusual structural behavior. Branko, the lead role and the second author of this paper has been in charge of data analysis of a 19-storey tall building. Observation of the data from the instrumentation has over the years, convinced Branko that there is an ongoing differential settlement of one of the base columns, in apparent contrast with his initial expectations. This conclusion matured gradually not only as a consequence of the monitoring results, but also based on verbal information received from a design engineer. Thus, besides the quantitative data provided by the monitoring system, including in the data analysis algorithms the engineer’s knowledge and experience has also been of value. In this study we propose an approach based on Bayesian logic as an effective tool to allow such a blend of field knowledge and SHM results. We show how the whole cognitive process followed by Branko can be suitably reproduced using Bayesian logic. In particular, we discuss to what extent the prior knowledge and potential evidence from inspection, can alter a perception of building behavior based on SHM data alone.

The current publication focuses on Integral Life Cycle Analysis merging major components of structural assessment (Visual Inspection, Design Code Considerations and Structural Health Monitoring). The paper represents the authors contribution to the US Long-Term Bridge Performance Program based on an individual case study (reference bridge NEW JERSEY) in 2010. The developed methodology for the management of infrastructure is based on 20 years of experience in structural assessment – linking research and consulting purposes by means of a constant and synergetic approach. The following major aspects are covered: • The determination/estimation of the DESIGN LIFE OF THE INVESTIGATED structures • The determination/estimation of the RESIDUAL LIFE OF THE INVESTIGATED structures • Assessment criteria whether the REAL DEGRADATION PROCESS corresponds with the assumed and applied life cycle model in order to take corrective measures in cases of accelerated ageing • MAINTENANCE INSTRUCTIONS to guarantee the original design life and operability The elaborated approach delivers all necessary measures to guarantee the functional capability of structures during the overall design life, considering even individual characteristics of each structural member. The chosen categorisation reflects the common composition of available inspection reports making it coherent with civil engineering practice all over the world.

This paper presents an autonomous SHM system that was developed to detect and identify overload occurrence, and changes in structural behavior for bridges primarily on the secondary road system. SHM has gained much attention over the past 10 years. However, for the most part the primary focus has been on deployments on Interstate and other primary highway bridges. It is possible, however, for local systems engineers to reap similar benefits as long as cost, scope, and required staff technical abilities fit within local systems restraints. The SHM system utilizes a new approach to identifying and extracting useful information from large data files. By reducing the large data files into smaller packets of the most relevant information, data processing is greatly relieved, reliable analytical results are quickly achieved, and the long-term structural performance of secondary road system bridges can be presented to owners in a clear format that is more easily understood and utilized. Appropriate data processing and evaluation procedures allows the amount of saved data to be significantly reduced to less than 0.1% of collected data and for the data to be “comfortable” to use by local systems engineers. In addition, this system showcases application and testing of traditional strain gage sensors, installation of the system components, and wireless communication from the bridge site to the owner for monitoring updates. The installation of the strain gages and cabling required no training or special equipment other than safety and normal access equipment. Excluding the communication and power equipment and research and development costs, the system can be implemented at the cost of $10,000 to $15,000 depending on the number of sensors used.

Distributed fiber optic technology offers the capability to measure strain and deformation at thousands of points along a single fiber up to tens of kilometers. This is of particular interest for the monitoring in geotechnical structures where it allows the detection and localization of ground movements. Fiber optic sensing system offers the ability to detect and localize deformation induced by geological assessments, allowing the monitoring of kilometers with a single instrument and localization of the event with a precision better than 1 meter. To improve and optimize the thermal, mechanical and water transport properties of the sensing cable, the optical fiber sensor can be integrated in different types of geotextiles. Geotextile may, for example, be used to increase the strain-transfer surface, to route leaking water to the sensing cable or to protect the cable from damage. Another civil engineering application of textiles is in the reinforcement of structures with composites. In this case the textile is used to reinforce ageing structures, such as masonry walls in seismic regions, corroded concrete columns and beams or other structural elements that require an increase in load-bearing capacity. However, the retrofitting by means of composites covers the original structure and therefore restricts the possibility to visually inspect it. Furthermore, the bonding between the composites and the original structure plays a major role in the effectiveness of such repairs and it must be guaranteed over time. To address such uncertainties, optical fiber sensors are embedded in the textile and become integral part of the composite material when the resin cures. Once in place, those sensors provide information about the strain and deformation of the composite and of the underlying structure. This paper presents several designs of smart textiles and their field applications.