Uncertainties in predictive models for concrete structures performance can influence adversely the timing of management activities. A methodology has been developed that uses data obtained through proactive health monitoring to increase the confidence in predicted performance by reducing the associated uncertainties. Due to temporal and spatial variations associated with climatic changes, exposure conditions, workmanship, and concrete quality, the actual performance could vary at different locations of the member. In this respect, the use of multiple sensors may be beneficial, notwithstanding cost and other constraints. Two distinct cases are identified for which an updating methodology based on data from multiple sensors needs to be developed. In the first case the interest lies in improving the performance prediction for an entire member (or a structure) incorporating spatial and temporal effects. For this purpose, the member is divided into small zones with the assumption that a sensor can be located in each zone. In the second case, the objective is to minimise uncertainties in performance prediction, or to increase the redundancy of health monitoring systems, at critical locations. The development of updating methodologies for the above-mentioned scenarios is described in this paper. Its implications on the management activities, for example, establishing the timing of principal inspections, are evaluated and discussed. 1. Introduction In the UK, the Highways Agency is administering over 9,000 trunk road and motorway bridges that are valued at over ￡20 billion. More than 65% of those are either reinforced or prestressed concrete bridges [1]. These structures represent 2% of the national network length but 30% of its total asset value. The effective maintenance management of these high value assets is of increasing importance and significant research is directed towards this area. In the UK, 50% of the total bridge and large culvert stock were constructed between 1960 and 1980 [2]. In most developed countries with already established, but aging, infrastructure, the investment on maintenance of these structures is either approaching, or has already exceeded, the capital spent for new construction. For example, the UK’s Highways Agency supports a maintenance program of ￡7 billion from 2001 to 2010 for their administered transport network [3]. Visual inspections are widely used to aid maintenance management of almost all deterioration prone systems. Despite obvious benefits (e.g., simplicity, cost, and access to 100% of the visible surface), they are
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