Showing papers by "Katrin Beyer published in 2023"
TL;DR: In this paper , a blind prediction was organized with participants from academia and industry to test modelling approaches and assumptions and to learn about the extent of uncertainty in modelling for such masonry aggregates.
Abstract: Abstract City centres of Europe are often composed of unreinforced masonry structural aggregates, whose seismic response is challenging to predict. To advance the state of the art on the seismic response of these aggregates, the Adjacent Interacting Masonry Structures (AIMS) subproject from Horizon 2020 project Seismology and Earthquake Engineering Research Infrastructure Alliance for Europe (SERA) provides shake-table test data of a two-unit, double-leaf stone masonry aggregate subjected to two horizontal components of dynamic excitation. A blind prediction was organized with participants from academia and industry to test modelling approaches and assumptions and to learn about the extent of uncertainty in modelling for such masonry aggregates. The participants were provided with the full set of material and geometrical data, construction details and original seismic input and asked to predict prior to the test the expected seismic response in terms of damage mechanisms, base-shear forces, and roof displacements. The modelling approaches used differ significantly in the level of detail and the modelling assumptions. This paper provides an overview of the adopted modelling approaches and their subsequent predictions. It further discusses the range of assumptions made when modelling masonry walls, floors and connections, and aims at discovering how the common solutions regarding modelling masonry in general, and masonry aggregates in particular, affect the results. The results are evaluated both in terms of damage mechanisms, base shear forces, displacements and interface openings in both directions, and then compared with the experimental results. The modelling approaches featuring Discrete Element Method (DEM) led to the best predictions in terms of displacements, while a submission using rigid block limit analysis led to the best prediction in terms of damage mechanisms. Large coefficients of variation of predicted displacements and general underestimation of displacements in comparison with experimental results, except for DEM models, highlight the need for further consensus building on suitable modelling assumptions for such masonry aggregates.
3 citations
TL;DR: In this paper , an image-based end-to-end pipeline that automatically generates finite element meshes for solid-element and equivalent-frame models of the outer walls of free-standing historical masonry buildings is presented.
Abstract: Abstract To predict the response of masonry buildings to various types of loads, engineers use finite element models, specifically solid-element and macro-element models. For predicting masonry responses to seismic events in particular, equivalent frame models—a subcategory of macro-element models—are a common choice because of their low computational cost. However, an existing bottleneck in modeling pipelines is generating the geometry of the model, which is currently a slow and laborious process that is done manually using computer-aided design tools. In this paper, we address this by automating the modelling process using recent advancements in computer vision and machine learning. We present an image-based end-to-end pipeline that automatically generates finite element meshes for solid-element and equivalent-frame models of the outer walls of free-standing historical masonry buildings. As the input, our framework requires RGB images of the buildings that are processed using structure-from-motion algorithms, which create 3D geometries, and convolutional neural networks, which segment the openings and their corners. These layers are then combined to generate level of detail models. We tested our pipeline on structures with irregular surface geometries and opening layouts. While generating the solid element mesh from the level of detail model is straightforward, generating equivalent frame models required algorithms for segmenting the façade and the meshing. Experts in the field analyzed the generated equivalent frame models and determined them to be useful for numerical modeling. These finite element geometries will be invaluable for future predictions of the seismic response of damaged and undamaged buildings. The codes and dataset are publicly available for future studies and benchmarking ( https://github.com/eesd-epfl/FEM_buildings and https://doi.org/10.5281/zenodo.8094306 ).
24 Mar 2023
TL;DR: In this article , the effect of FRP reinforcement on the behavior of masonry walls is modeled as linear elastic in tension up to the failure with a zero compressive strength, and the authors use a recently developed macro-element to capture both in-plane and out-of-plane failure modes.
Abstract: Fibre-reinforced polymers (FRP) strengthening can be applied to decrease the seismic vulnerability of existing masonry buildings, both with regard to in-plane and out-of-plane failure mechanisms. Experimentally, the impact of strengthening solutions has been thoroughly studied. There are, however, few efficient and reliable numerical modeling approaches that can accurately capture the effect of such strengthening on the seismic response of the masonry building. Therefore, we herein develop and validate a modeling approach to capture the effect of FRP strengthening on the behaviour of masonry walls. To model this effect, we use a recently developed macro-element, which can capture both in-plane and out-of-plane failure modes. In the macro-element, the intervention is modelled by adding fibres representing the longitudinal FRP strips to the section model. These fibres were modelled as linear elastic in tension up to the failure with a zero compressive strength. Transversal FRP strips effect the shear strength, and in the macro-element, this is accounted for by increasing the cohesion in the equation for the shear strength. To validate the model, we also compare the numerical simulations with existing experimental results obtained from the literature. Overall, the proposed modeling approach accurately predicts the in-plane and out-of-plane response, implying that equivalent frame models can predict the response of masonry buildings with FRP-strengthened walls. To conclude, the models described in this paper can be used for a time-efficient assessment. Moreover, it can help in selecting the optimal strengthening approach for future retrofitting. This aspect is especially important for the cultural heritage structures, where excessive retrofitting should be avoided.