Open Access

Im Norden von Serbien erfolgt in Novi Sad der Neubau eines modernen Forschungsgebäudes für das BioSense-Institut mit finanzieller Unterstützung durch die Eu-ropäische Union. Der Gebäudeteil mit Laboren wird zum Schutz und zur Sicherstellung des reibungslosen Betriebs der sensiblen und kapitalintensiven technischen Einbauten mit ei-ner Erdbebenisolierung mit integrierter Körperschallisolation versehen. Zusätzlich wird der entkoppelte Laborteil des For-schungsgebäudes mit einem BIM-basierten Bauwerksmonito-ring versehen, um Änderungen des Gebäudezustands jederzeit abfragen und beurteilen zu können.

A further development of the Added-Mass-Method allows the combined representation of the effects of both soil-structure-interaction and fluid-structure interaction on a liquid-filled-tank in one model. This results in a practical method for describing the dynamic fluid pressure on the tank shell during joint movement. The fluid pressure is calculated on the basis of the tank's eigenform and the earthquake acceleration and represented by additional masses on the shell. The bearing on compliant ground is represented by replacement springs, which are calculated dependent on the local soil composition. The influence of the shear modulus of the compliant soil is clearly visible in the pressure curves and the stress distribution in the shell. The acceleration spectra are also dependent on soil stiffness. According to Eurocode-8 the acceleration spectra are determined for fixed soil-classes, instead of calculating the accelerations for each site in direct dependence on the soil composition. This leads to unrealistic sudden changes in the system's response. Therefore, earthquake spectra are calculated for different soil models in direct dependence of the shear modulus. Thus, both the acceleration spectra and the replacement springs match the soil composition. This enables a reasonable and consistent calculation of the system response for the actual conditions at each site.

Today, the planning and operation of new structures is fully integrated in the digital process chain and supported by Building Information Modelling (BIM), forming the basis of a digital twin. Beside the planning phase, where the digital twin is of great help for not only identifying collisions and having a central place with all structures, systems and components (SSC) and their attributes, the maintenance and Structural Health Monitoring (SHM) have been revolutionized with new generations of sensors and big data processing. Together with sensor data predictive maintenance programs can be developed and enhanced to early identify deviations from normal operation and avoid costly repairs due to damages. The sensor data can easily be integrated and displayed in an augmented or virtual reality environment to support the position identification inside the BIM model and train people. Structural health monitoring by itself is already established and a very useful tool to identify potential damages and visualize the collected data. Thanks to the common standards, the BIM technology is now also accepted and widely used. Nevertheless, the information inside a BIM model is conceived to be a static information and yet, there are no solutions to easily and permanently update the BIM model based on transient sensor data. Furthermore, the data collected by sensors to feed structural health monitoring usually require some post-processing and engineering interpretation to provide a meaningful picture of the SSCs and to draw conclusions by decision makers. Also there needs to be a consistent and structured data management to exploit the data and build a digital twin. The focus of the new approach is mainly on structures, as those are still not monitored on a regular basis and require a calibrated numerical model to reflect the real behavior. But it allows also the continues monitoring of arbitrary non-structural elements with importance for the building operation. All together it allows to study the dynamic performance by building simulation tools for a variety of different boundary conditions and over its lifetime (from design to dismantling). Thus, a novel approach to merge all three disciplines has been developed in order to combine the individual advantages and provide to the end user a highly modular, but still comprehensive dashboard for displaying the real-time behavior of the SSCs and also the quantification of damage indicators. Coupled in the future with artificial intelligence (AI) methods to derive even more robust indicators, taking into account all parameters and their associated uncertainties, opens a large variety of possibilities for utilities/owners and operators to improve reliability. The “intelligent” SHM integrates the dynamic sensor data into BIM models and displays with customizable dashboards the measurement data and evaluation results in a comprehensive manner to the end user. The system, initially designed to provide insights during and after an earthquake, is versatile and can integrate any sensor data, from e.g. temperature (slow incremental change) to accelerations (highly transient and high resolution). The development is based on open-source code and thus, easily adjustable to individual needs and tailor-made for each specific application and environment. The BIM model itself and the platform is located in the cloud or intranet and accessible through a web interface which makes it easily integrable in other environments. Only the sensors are local and transmit their data directly to a central system which can be connected via cables or wireless. The presented iSHM integrates BIM models together with dynamic data provided by sensors to visualize the structural performance of critical infrastructures based on a digital twin of the buildings. While for future structures the implementation is easy and efficient, as their digital twin will be created during the design and operation, for existing buildings it is more challenging to build an adequate twin, as the initial effort is high and sometimes information on the actual in-situ situation is missing. Nevertheless, comparing the benefits of an advanced, intelligent structural health monitoring and the ability to instantaneously derive performance indicators provides a competitive advantage and opens new possibilities. The developed system and its implementation are illustrated for a base-isolated 4-storey reinforced-concrete structure of the BioSense laboratory with highly sensitive equipment in Novi Sad, Serbia.