Funded by the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 958161.

ASHVIN aims at enabling the European construction industry to significantly improve its productivity, while reducing cost and ensuring absolutely safe work conditions, by providing a proposal for a European wide digital twin standard, an open source digital twin platform integrating IoT and image technologies, and a set of tools and demonstrated procedures to apply the platform and the standard proven to guarantee specified productivity, cost, and safety improvements. The envisioned platform will provide a digital representation of the construction product at hand and allow to collect real-time digital data before, during, and after production of the product to continuously monitor changes in the environment and within the production process. Based on the platform, ASHVIN will develop and demonstrate applications that use the digital twin data.

One of the highest risk activities in construction relates to unknown or unanticipated soil conditions. Current design methods deal with uncertainty by assuming conservative estimates of soil properties and calculating the response of the geotechnical structure to some unlikely set of extreme loads. In certain analyses involving soil-structure interaction problems (e.g. soil retaining structures) the loads experienced by structural elements (such as piles, anchors, walls etc.) are directly related to the displacements (strains) experienced. Therefore, only a model that uses the most-likely soil and structure properties at any given point in the life-cycle of a structure to accurately predict the displacement can allow the real safety level (resistance to additional loading) of a structure to be determined. InGEO are responsible for identifying geo-monitoring techniques that can measure the response of a geo-structure in real-time. The data are from a case study site where comprehensive monitoring data are available are implemented in an numerical modelling environment to track the response of all element of a deep excavation in real-time. Model updating is performed to validate model predictions. What-if scenarios can be implemented with confidence to determine the impact of changes in the construction sequence, time etc. on the risk-level throughout the process.