Evidence on the value of information towards decision-makers

Currently, there is a need to enhance the basis for decisions in the management of Civil Engineering infrastructure, explained by the evolution of social paradigms, such as the prioritization of green and sustainable policies. At the same time, the increased availability of data, collected by Structural Health Monitoring (SHM) systems, load testing or non-destructive testing, is enhancing our knowledge about the real condition and structural capacity of such infrastructure.

Taking advantage of such momentum, this special issue aims to demonstrate the practical feasibility of the Value of Information (VoI) concept applied towards effective and sustainable infrastructure management. Nine full-scale case studies, including bridges, buildings, and dikes, set the bottom line for this objective. Despite a strong mathematical background is beneficial for full comprehension, all contributions have been carefully tailored to guarantee, as much as possible, effective communication with those who may not be experts in the subject, but can potentially utilize the insights in future decision-making.

The first step, for those not familiarized with the VoI concept, is to have suitable guidelines where the mathematical background is translated to a sequence of steps with adequate vocabulary and understanding for those non-experts in the subject. Procedures for practicing engineers are outlined by Sykora, Diamantidis Müller and Sousa based on a rational and objective framework – the quantification of the Value of SHM (Cost Action TU1402 2014). A historic masonry wall, part of the church from the 17th century, located in Cerny Dul, Czechia, is used to show the application of these procedures. Focussing on the reliability of the structure, the number of surveys is optimized based on non-destructive tests calibrated by destructive tests. The outlined procedures and case study have been carefully prepared, so that the reader can easily understand the feasibility of the VoI concept in real applications.

Nowadays, the amount of available data brings the challenge associated with its effective use. Hence, the question ‘How beneficial is the available data’ should be properly addressed first. Skokandić and Mandić Ivankovic address this by outlining the value of existing traffic data, collected with both the traffic counters and the Weigh-in-Motion (WIM) methods in a reinforced concrete slab bridge in Croatia. Considering all related costs, the benefits of employing traffic load monitoring data, in structural assessment and subsequent decision-making process in service life management of bridges, are throughout debated. It is shown that the investment in WIM measurements can benefit, on a relative basis, the bridge owner by 91% when considering owner costs, although it can go up to 96% when both owner and user costs are considered together.

The continuous collection of data can be seen as a sequence of data sets. Thus, ‘How does knowledge, about the condition/performance of a structure, enhance when a new data set becomes available, given that a previous data set has been taken?’ is a pertinent question to the decision-maker when deciding on the monitoring sequence and period. Larsson Ivanov, Björnsson, Honfi and Leander illustrate how: (i) a point-in-time decision model (i.e., using only one slot of data) and (ii) a sequential updating decision model (i.e., more than one slot of data is used) improve the decision-making process related to maintenance. Using a concrete bridge in Sweden, where the edge beams may have to be replaced, it is demonstrated that the sequential model provides a higher VoI.

Conversely, if data are temporarily acquired, the question by the decision-maker may be reformulated to: ‘How much time should a monitoring campaign last and how many campaigns should be considered to optimize investment?’. Long, Farreras Alcover and Thöns address this aspect, mainly the optimization of the duration of SHM campaigns based on a utility-based solution to posteriorly determine: (i) optimal monitoring durations and (ii) the extension of the service life of the welds on a steel bridge deck. The approach is illustrated focusing on the remaining fatigue life estimation of the welds on the orthotropic steel deck of the Great Belt Bridge, in Denmark. The results show that the decision on short-term monitoring is systematically the most valued SHM strategy.

Looking into more detail to the meaning of ‘data’, this can range from in-situ inspections to remote sensing. When different possible sources of data are considered, decision-makers need clarification on whether uncertainty reduction is worth investing (i.e., type of data). van der Krogt, Klerk, Kanning, Schweckendiek and Kok address this aspect by presenting a framework to assess the VoI of two uncertainty reduction methods: (i) proof loading and (ii) pore pressure monitoring, used in the case of a typical river dike, located in the Netherlands, with an insufficiently stable inner slope. All results show a positive VoI, with an optimal result for the strategy of proof loading and monitoring. In this case, a reduction of the total cost of 25% is observed, if compared to a conventional dike reinforcement.

Such data can also be very useful allied to specific further analysis and assessments (e.g., consultancy) envisaging optimal decisions on a cost-benefit basis. A novel VoI framework incorporating successive tiers of measurement, analysis, and assessment, common in engineering practice, is presented by Khan, Caprani Ghosh and Ghosh. A reinforced concrete bridge pier crosshead, subjected to high shear, is used to demonstrate the potential benefit of SHM. The benefit is particularly high when high risks are involved or when slight changes in structural assessment could trigger different intervention actions. Interestingly, this study also identifies the significant role that low-cost low-accuracy SHM strategies can play in decision guidance.

In scenarios involving hazard events, the consequences usually affect more than one structure. The decision-maker is faced with the difficult decision of which structures should be kept operating and closed. SHM data might be valuable to better assess the structures’ performance and therefore, better decisions are taken. Giordano and Limongelli provides a methodology to compute the VoI of SHM for seismic emergency management of roadway bridges, which can be used by decision-makers before installation. Applied to a case study in Sicily, Italy (a medium-high seismic area), the results show high VoI when the expected costs of the decision alternatives evaluated without the SHM information are comparable. In this condition, the SHM information can provide the maximum support to decision-making.

In addition, there are contexts where data is scarce, or even inexistent, due to the nature of the problem under analysis. This is the case of damage detection, where advanced Finite Element (FE) modelling of the structure is the most reliable approach. Sousa and Courage introduce a formulation for the quantification of the Value of Information of a pro-active SHM tool devoted to early damage detection. Supported by a comprehensive case study, the Lezíria Bridge in Portugal, the structural behaviour and sensors’ measurements are anticipated via the FE model, for a set of likely damages. From a pedagogical perspective and attempting to address the decision-makers' perspective, the results show that the VoI can go up to approximately +13.1%.

Nevertheless, there might be cases where no value is added by the data collected. This means that the decision-maker does not get any return from the investment made (negative VoI). ‘In which scenarios this may happen?’ becomes of interest. This is discussed in the contribution from Verzobio, Bolognani, Quigley and Zonta, in which a formulation is proposed allowing to assess when and under which specific conditions the VoI becomes negative. The Streicker Bridge, a pedestrian bridge on the Princeton University campus in the USA, equipped with a fibre optic sensing system, is used. The results show that the predominant factor for a negative VoI is the different risk appetite between different decision-makers, e.g., the owner and the manager.

The guest editors aim that, ultimately, this special issue on ‘Evidence on the value of information towards decision-makers’ may strengthen the communication between academics and decision-makers. In their opinion, this is one of the best approaches –improving communication– to build win-win partnerships between both audiences. Finally, but not least, authors’ knowledge and efforts reflected in their contributions, as well as the support of all reviewers involved in the peer-review process are sincerely acknowledged.