Publications by Katrin Beyer | EPFL Graph Search

Influence of the Horizontal-to-Vertical Compressive Strength of Hollow Clay Bricks on the In-Plane Drift Capacity of Unreinforced Masonry Walls

The seismic damage of masonry walls is reflected in cracks that tend to start at the head and bed joints and subsequently propagates through the masonry units. In this regard, the horizontal-to-vertical compressive strength ratio of bricks might have the a ...

2025

Topological data analysis-based damage indices for plastered stone masonry walls under cyclic loading

Katrin Beyer

The qualitative aspect of visual inspection of damaged structures can be largely benefited by incorporating quantitative metrics. Moreover, automating this process requires the development of effective computational tools capable of making reliable assessm ...

2025

Code-based ground motion selection and scaling for seismic assessment: Application to two masonry building case studies

Katrin Beyer, Igor Tomic

This paper investigates the applicability and limitations of the guidelines for ground motion selection and scaling provided in the first- and second-generation of Eurocode 8 for the assessment of two unreinforced masonry buildings subjected to bi-directio ...

2025

Geometric planning for masonry wall construction with natural stones using discrete convolution

Katrin Beyer, Qianqing Wang

Using unprocessed materials in construction is a promising approach to reducing energy and material consumption in the building industry. This paper presents a geometric planning algorithm for constructing multi-leaf masonry walls using natural stones. Our ...

2025

Optimal intensity measure and probabilistic seismic demand model for the assessment of historical masonry buildings: application to two case studies

Katrin Beyer, Igor Tomic

This paper presents a probabilistic seismic demand model (PSDM) as a relationship between intensity measures (IMs) and engineering demand parameters (EDPs) for the seismic assessment of two case studies resembling historical masonry buildings. The first on ...

2025

Disk harmonics for analysing curved and flat self-affine rough surfaces and the topological reconstruction of open surfaces

Guillaume Anciaux, Katrin Beyer

When two bodies get into contact, only a small portion of the apparent area is actually involved in producing contact and friction forces because of the surface roughnesses. It is, therefore, crucial to accurately describe the morphology of rough surfaces, ...

2025

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Ian Smith, Katrin Beyer, Bryan German Pantoja Rosero, Mathias Christian Haindl Carvallo

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

Springer2024

On the conjugate symmetry and sparsity of the harmonic decomposition of parametric surfaces with the randomised Kaczmarz method

Katrin Beyer

This limitation is circumvented by using scalable and non–memory–intensive harmonic expansions. In this paper, the projection of parametric surfaces onto disk and spherical harmonics bases is investigated, and three novel computationally efficient algorith ...

2024

Investigation of the bed joint reinforcement effect on the drift capacity of modern unreinforced masonry walls

Katrin Beyer, Savvas Saloustros

Bed joint reinforcement significantly affects the shear capacity of masonry walls due to its effective ability to transfer shear forces through a diagonal crack, but how does this phenomenon impact its drift capacity? This paper presents an experimental st ...

EDP Sciences2024

Using image-based inspection data to improve response predictions of earthquake-damaged unreinforced masonry buildings

Katrin Beyer, Mathias Christian Haindl Carvallo

Explicit representation of uncertainties is essential to improve the reliability of seismic assessments of earthquake-damaged buildings, particularly when dealing with unreinforced masonry buildings. Modern inspection techniques use images for detecting an ...

2024

Experimental and numerical evaluation of a U-shaped thin lightly reinforced concrete wall tested under cyclic loading

Katrin Beyer

Reinforced concrete walls provide effective bracing against seismic lateral loading for buildings worldwide. In Latin America, seismic design provisions commonly adhere to the ACI 318 building code, which is predominantly based on United States constructio ...

2024

Foreword to the special issue "Adjacent Interacting Masonry Structures"

Katrin Beyer

This special issue focuses on the seismic performance of adjacent interacting masonry structures, particularly in historical European city centers. The AIMS project provided unique data on interacting masonry structures through large-scale shake table test ...

SPRINGER2024

Automatic Removal of Non-Architectural Elements in 3D Models of Historic Buildings with Language Embedded Radiance Fields

Frédéric Kaplan, Katrin Beyer, Bryan German Pantoja Rosero

Neural radiance fields have emerged as a dominant paradigm for creating complex 3D environments incorporating synthetic novel views. However, 3D object removal applications utilizing neural radiance fields have lagged behind in effectiveness, particularly ...

MDPI AG2024

Generation of LOD4 models for buildings towards the automated 3D modeling of BIMs and digital twins

Frédéric Kaplan, Katrin Beyer, Bryan German Pantoja Rosero

An image-based methodology is presented for the automatic generation of geometric building models at LOD4, incorporating both interior and exterior geometrical information. Existing approaches often focus on simplified geometries for either exteriors or in ...

Elsevier BV2024

Partial annotations in active learning for semantic segmentation

Radhakrishna Achanta, Katrin Beyer

Semantic segmentation with deep learning plays a crucial role in various fields, including civil engineering, particularly in tasks such as damage assessment and urban planning. This paper addresses the challenge of efficiently training deep learning model ...

2024

Uncertainty quantification for a deep learning models for image-based crack segmentation

Katrin Beyer, Bryan German Pantoja Rosero, Ketson Roberto Maximiano Dos Santos

Recent advancements in deep learning have found compelling applications in the image-based inspection of infrastructure systems. However, the efficacy of these models hinges significantly on the quality and diversity of the input data used for training. In ...

2024

Seismic Testing of Adjacent Interacting Masonry Structures – Analysis of a Blind Prediction

Katrin Beyer, Andrea Penna, Igor Tomic

Masonry aggregates, which emerged as layouts of cities and villages became denser, make up historical centres all over the world. In these aggregates, neighbouring structures may share structural walls that are joined at the interfaces by mortar or interlo ...

Springer2024

Automated construction of multi-leaf walls with natural stones

Katrin Beyer, Qianqing Wang, Ketson Roberto Maximiano Dos Santos

This paper introduces an innovative strategy for the construction of multi-leaf walls utilizing raw stones, a significant step forward in sustainable building practices. Our approach leverages advanced computational algorithms and image processing techniqu ...

EDP Sciences2024

Numerical Modeling of FRP-Strengthened Masonry Structures Using Equivalent Frame Models

Katrin Beyer, Francesco Vanin, Ivana Bozulic

The present study focuses on enhancing the seismic resistance of existing masonry structures. To that aim, the use of fiber-reinforced polymer (FRP) strengthening serves to improve structural behaviour by attaching FRP strips to the masonry walls. Despite ...

Springer2024

Micro modeling of irregular stone masonry walls using mathematical programming

Katrin Beyer, Qianqing Wang, Ketson Roberto Maximiano Dos Santos

While understanding the shear strength of stone masonry structures is important for the design and the mainte- nance, we still lack computational tools for predicting the strength as a function of the stone layout. Here we implement an end-to-end image bas ...

Springer2024