Re-Gen, coordinated by ROD-IS, is funded through the CEDR Transnational Road Research Programme Call 2013 “Ageing Infrastructure”. The project commenced in April 2014 and is due for completion in March 2016. The aim of the project is to provide road owners/managers with best practice risk management and decision tools for the risk assessment of ageing critical infrastructure elements, such as bridges, retaining structures and steep embankments. To achieve this, a network-wide probabilistic risk based approach to optimise lifecycle performance of the infrastructure, within the context of evolving traffic demands and climate change effects, is being developed. The proposed framework will consider the different types of risk faced by national road administrations such as safety risk, financial risk, operational risk, commercial risk and reputational risk. It is expected that these tools will be employed by infrastructure owners/managers to optimise the lifecycle performance of (i) their already built infrastructure and (ii) future construction. 

In order to develop the set of risk management and decision tools, work streams are focusing on the areas of; Prediction of Deterioration Considering Climate change; Traffic Effect Forecasting and Risk profiling (i.e. investigating the probabilities of road infrastructure failure and the consequences.)

Due to our significant expertise and knowledge of Weigh- in- Motion (WIM) and load modelling ROD-IS, in addition to acting a project coordinator, is responsible for the activity related to Traffic Growth Forecasting. 
As part of this work, we provided a comprehensive overview of existing guidelines for collecting WIM data, recommended a procedure for quality assurance of WIM data and for cleaning of erroneous data and provided examples of good practice of using WIM data for bridge applications. 


Subsequently we assessed the implications of Traffic Growth on the Eurocode alpha-factors used in Site-Specific Bridge Assessment. These alpha factors are used to scale down the notional loads from the Eurocode load model for new bridges to undertake assessments of existing bridges. Using complex statistical processes and a sophisticated analysis, long run simulations were carried out for a range of load effects, spans and rates of growth to determine the extent to which growth in traffic influences the -factor. 

It is important to note that for design or routine assessment of small bridges, a load model such as the Eurocode LM1, sometimes scaled using -factors, is generally sufficient. However, for larger or strategically located bridges, a reliability Analysis may be required to obtain a more accurate measure of its true safety to account for uncertainties inherent in, for example, material properties, workmanship, element dimensions, traffic load, environmental conditions and the deterioration process. Consequently the effects of traffic growth were then included in a probabilistic framework, which considered reliability, from which we provided guidelines for probabilistic modelling of resistance and load modelling, considering traffic growth.

Further information can be found at www.re-gen.net