James T. P. Yao

Health Monitoring and Structural Reliability as a Value Chain

A value chain is defined as an end-to-end solution to a problem, with the beneficiary constituting one end of the chain and the enabling technologies (or parties) making up the rest of the chain. In this context, enabling technologies such as health monitoring, damage detection, and reliability are viewed as sequential components in a chain, with each continuing the chain while adding value to it, so that the aggregate value of the chain can be delivered to the ownership. This holistic view is taken to expose a current imbalance in technology development, and the weak link corresponds to a lack of information that relates technology-investment costs to financial benefits for the owner. Structural reliability, useful life expectancy, and other information of this genre are seen to be keeping the full value of the chain from being realized and appreciated by the ownership. An example of what the desired linkage may be comes from aerospace and mechanical engineering. In the form of so-called symptom-based reliability technology, reliability is quantified for existing structures based on actual usage instead of natural age and measured symptoms instead of idealized model prediction. Hence it is also compatible with current health-monitoring and damage-detection developments (enabling technologies of the value chain). Since the value of the chain is only as (in)effective as its weakest link, it is argued that future research effort should stress balanced development throughout the chain.

Mathematical modelling of structural behaviour during earthquakes

Abstract The dynamical behaviour of structures can be modelled and simulated satisfactorily in the linear and slightly nonlinear ranges using finite elements and other analytical models in conjunction with modern computers. However, the highly nonlinear behaviour of structures remains to be studied further. The nonlinear response of complex structures which have been damaged by strong-motion earthquakes lies in this area. It is extremely difficult to collect sufficient field or laboratory data for the construction of accurate mathematical models of such structures for practical applications. This is partly due to the fact that the failure behaviour of a given structure is highly load-history dependent. In the absence of reliable analytical tools, system identification techniques may occasionally be applied to verify and/or update the mathematical model of a structure. The development of mathematical models useful for analysis of structural behaviour to earthquake excitation is an area too large to be covered in detail by a single review. In this paper, an attempt is made to critically review available mathematical models in the random earthquake response analysis of structures. By random, we refer to the excitation, to the properties of the structure itself, or to both. We are especially interested in those models dealing with slightly to highly nonlinear behaviour. Some recent work which utilizes these analytical techniques is highlighted. Also included is a review of system identification techniques as applied to structures. The concept of damage accumulation is mentioned, and a damage index is discussed which may be used in conjunction with an analytical model. A selective bibliography is also given for a more complete introduction into the areas discussed herein.

Suggested Topics for a Civil Engineering Curriculum in Infrastructure Management

Public works and infrastructure management have always been the primary domain of civil engineers. In recent decades, however, the role of the civil engineer in this field seems to have been decreasing in importance, with increasing emphasis being placed on administrative skills, management experience, and political savvy over technical expertise. If civil engineers want to regain a prominent position in the planning and management of public works, a new curriculum must be developed and implemented. This curriculum should provide students with a basic knowledge and understanding of (a) mathematics and basic science; (b) engineering science; (c) technical aspects of infrastructure systems; (d) decision analysis in the face of uncertainty; (e) management and business principles; (f) societal needs, ethics, public policy, and political science; and (g) communication skills. Furthermore, faculty members need to be exposed to practical problems so that they can bring back that experience into the classroom. A broad-based undergraduate degree should be followed with a more specialized master’s-level degree for civil engineering practice at a professional level.

Structural Health Monitoring and Symptom-Based Reliability

An international workshop on structural health monitoring was held at Stanford University in September of 1999. Results of this workshop are summarized in a subjective manner in this paper. The authors believe that future efforts should be concentrated on the analysis and interpretation of collected data. Because many professional engineers are capable of assessing the damage of existing structures, attempts have been made to build expert systems in the subject area of condition evaluation of existing structures. Moreover, fuzzy sets have been applied in civil engineering research that include damage assessments. Recently, efforts are being made to develop and apply symptom-based reliability in order to evaluate the safety of existing structures. Potentially, symptom-based reliability can be used to monitor the structural condition of existing structures. Previous research also advocated a holistic approach to structural health monitoring in the form of a “value chain” that achieves the value of the stakeholder, and these works are summarized and discussed in this paper.