Dr. Eftychia Apostolidi,
Junior Research Group Leader Structural Mechanics
Bridges are so formative that their construction has become a figure of speech for overcoming obstacles. Since ancient times, they have connected shores, people and cultures. Changing loads on these structures require ever new analysis methods and calculation models.
To date, data from monitoring systems on structures (primarily bridges) has been used for the structural assessment and maintenance measures of such structures. In a similar way, sensor systems installed on vehicles are used to monitor vehicle components and the track system. Inherently, however, the respective sensor systems collect data that contain further information: An instrumented train passes over a large number of bridges on its journey and a large number of trains pass over an instrumented bridge.
The objective of the project is to develop, implement and validate a digital tool for the in-situ monitoring of railroad bridge structures in the context of a sensor data-based predictive maintenance concept using a BIM-integrated Digital Twin (Digital Twin), based on Artificial Intelligence. The core objective is to develop a template for a highly automated and improved assessment (resonance hazard, structural safety, remaining service life) of existing railroad bridges.
The status data obtained by dynamic monitoring is taken into account via an automated and continuous update of the actual status of the digital twin. Based on the condition data, an artificial intelligence decides on any necessary adaptation of the structural models (bridge and vehicle) to the existing condition (structure identification, system calibration) by considering the mechanical correlations of the structure
A new load model is needed because current high-speed rail bridge design and evaluation standards do not cover a number of newly developed rail vehicles that have innovative axle arrangements and are faster and heavier than the vehicles under consideration for the development of current load models. For these reasons, a parametric high-speed load model needs to be developed to fill gaps in the current model and to allow future models to adapt to developments in the rail vehicle industry.
Current status and work packages
The first work package, Current Standards in Science and Technology, was completed in January-March 2020. Project partners are currently working on the following work packages:
Conceptualization of a load model upon analysis of previous approaches (April 2020 – April 2022). A general load model will be created that can be used to represent all central factors and that is open to possible adaptations in the future (e.g., longer trains, various wheel set sequences). If it makes sense to use different calculation formulas for different traffic, several approaches can be created. However, the goal must be to have as few individual components as possible to represent the total load from amount of use.
Simplification of the load model for a plausibility check (February 2021 – July 2022). Dynamic calculation models can only be estimated to a limited extent and therefore do not allow intuitive validation of the numerical calculation. Therefore, a method must be created to evaluate the calculation results at least qualitatively and to check them for plausibility. This can be accomplished via a user-friendly simplification of the load models for the plausibility check, and by the development of an additional simplified test procedure, for example.
Design and implementation of a validation process (August 2020 – December 2022). Validation of models and the development of a standardizable concept for the definition of the new dynamic load models will be presented, including detailed and simplified calculation models, as well as their application limits.
- TU Darmstadt (TUDa, Germany)
- KU Leuven (Belgium)
- Austrian Institute of Technology (AIT, Austria)
- REVOTEC (Austria)
- iSEA Tec (Germany)
Motivated by increasingly stringent architectural requirements, there is a current trend in civil engineering to design and build slimmer and lighter structures with larger spans. For structures exposed to human locomotion (e.g., pedestrian bridges), this often results in excessive pedestrian-induced structural vibrations. As a result, humans must adjust their gait to match the vibrations of the underlying structure in order to maintain balance. In turn, changes in gait affect the response of the structure, resulting in a continuous interaction between the human and the structure. However, current biomechanical gait models cannot predict the response of humans walking on a flexible structure because the underlying mechanisms of how humans interact with vibrating structures are still unclear. In addition, current models used in design do not take into account the interaction between humans and structures, which can lead to unsafe structures or to oversized and unaesthetic structures. Therefore, there is a critical need from both scientific fields (biomechanics and civil engineering) for a better understanding of the biomechanical adaptation of humans walking on excitable and vibrating structures.
Aim of the project
The aim of the project is to develop and validate improved biomechanical and structural loading models to describe and investigate the act of humans walking on vibrating structures. This goal will be achieved through an interdisciplinary research project at the TU Darmstadt involving sports biomechanics (Prof. Seyfarth, LL – who has specific knowledge of biomechanical models, and statics (Prof. Schneider, ISMD –who has specific knowledge of structural dynamics.
In this investigation, we will collect and analyze experimental data from human participants walking on vibrating structures and (for comparison) on rigid structures. The experiments will include the collection of both biomechanical and structural responses. Based on the results of the experimental studies, advanced biomechanical models with varying levels of detail for walking on flexible structures will be developed for simulation. Subsequently, the developed gait models will be implemented in the structural analysis. Extensive comparisons will be made between the measurements and simulations. This will allow for the formulation of minimum model requirements for both gait and structural models in terms of level of detail. Finally, we expect to propose a mechanical model for predicting pedestrian-induced vibration that accounts for human-structure interaction and a gait model for accurately simulating human response while walking on vibrating structures. The functionality of the proposed biomechanical model will be demonstrated on a soft active leg orthosis.
Bridge structures must be evaluated at certain intervals with regard to their remaining service life. This depends to a large extent on the stress oscillations in the material caused by traffic and the associated accumulation of damage. Current approaches for determining the remaining service life of existing bridges are based on idealized load models of the past or on certain assumptions about future traffic volumes. However, these assumptions are subject to large uncertainties and therefore usually have a strongly conservative character, which can lead to a premature repair of the structure. Data from axle load measuring points cannot yet be used to determine the remaining service life.
The core objective of this project is the development of a concept for the integration of existing real dynamic vehicle loads into the residual life assessment of railroad infrastructures. For this purpose, data from the axle load measuring points installed in the European railroad network as well as from classical structural monitoring systems will be used. By means of statistical extrapolation methods and data fusion, this data will be incorporated into the line-specific evaluation of the remaining service life of existing bridge structures in Germany. An extension of the remaining service life of existing bridge structures of at least 20% is expected compared to the current conservative approach, resulting in improved availability of bridge structures and a high degree of savings in resources.
A data-based extrapolation method for wheelset loads in the German rail network will be developed based on the analysis of existing data from axle load measuring points, structural monitoring data as well as operational and network data of infrastructure managers in Europe. In addition, a data-based method for the cost-effective determination of wheelset loads of railroad vehicles will be developed and validated. Finally, line-specific load spectra for calculating the (remaining) service life of railroad infrastructure assets will be derived.
||Dr. Eftychia Apostolidi|
+49 6151 16-23019
||Steven Lorenzen M.Sc.|
+49 6151 16-23011
||Antonia Kohl M.Sc.|
+49 6151 16-23032
||Max Fritzsche M.Sc.|
+49 6151 16-23065
||Henrik Riedel M.Sc.|
+49 6151 16-23011
||Maximilian Rupp M.Sc.|
+49 6151 16-23032