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Background: Settlements induced by tunneling in inner urban areas can easily damage above ground structures. This already has to be considered in early planning of tunneling routes. Assessing the risk of damages to structures on hypothetical tunneling routes inflicted by such settlements beforehand enables routes' comparability. Hereby, it facilitates the choice of the optimal tunneling route in terms of potential damages and of suitable countermeasures. Risk analyses of structures establishing the assessment obtain relevant data from various sources. Some data even has to be gathered manually. Virtual building models could ease this process and facilitate analyses for entire districts as they combine several required information in a single data set. Commonly, these are yet modelled very coarse. Relevant details like facade openings, which highly affect a structures stiffness, are not included. Methods: In this paper, we propose a system which detects windows in facade images. This is used to subsequently enrich existing virtual building models allowing for a precise risk assessment. For this, we apply a sliding window detector which employs a cascaded classifier to obtain windows in images patches. Results: Our system yields sufficient results on facade images of several countries showing its general applicability despite regional and architectural variation in the facades' and windows' appearance. In an ensuing case study, we assess the risk of damages to structures based on detections of our system using different analysis methods. Conclusions: We contrast these results to assessments using manually gathered data. Hereby, we show that the detection rate of our proposed system is sufficient for a reliable estimation of a structure's damage class.

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Currently, in mechanized tunneling, the steering of tunnel boring machines (TBM) in practice is mainly decided based on engineering expert knowledge and recorded monitoring data. In this chapter, a new concept of exploiting the advantages of simulation models to support the steering phase is presented, which allows optimizing the construction process. With the aim to support the steering decision during tunnel construction by means of real-time simulations, predictive simulation models are established in the initial planning phase of a tunnel project. The models are then capable of being continuously updated with monitoring data during the construction. The chapter focuses on explaining models for real-time predictions of logistics processes and tunneling induced settlements as well as the risk of building damage in more details. Additionally, application examples, which are practical-oriented, are also presented to illustrate the applicability of the proposed concept.