Publications associées à Cyclic demand at the shell-bottom connection of unanchored steel tanks

Shear and steel-fibre reinforcement for the punching resistance of flat slabs at internal and edge columns

Reinforced concrete flat slabs consist of a continuous, thin concrete plate that rests on a grid of columns. The supporting surface of the columns is very small compared to the floor plan dimensions, leading to concentrations of shear forces near the colum ...

EPFL2024

CONTROL OF HYPERBOLIC AND PARABOLIC EQUATIONS ON NETWORKS AND SINGULAR LIMITS

Nicola De Nitti

vanishing viscosity, networks. This work has received funding from the Alexander von Humboldt-Professorship program, the Transregio 154 Project "Mathematical Modelling, Simulation and Optimization Using the Example of Gas Networks" of the DFG, the grant PI ...

Amer Inst Mathematical Sciences-Aims2024

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

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

Fault roughness controls injection-induced seismicity

Lei Wang, Simon Guérin-Marthe

Surface roughness ubiquitously prevails in natural faults across various length scales. Despite extensive studies highlighting the important role of fault geometry in the dynamics of tectonic earthquakes, whether and how fault roughness affects fluid-induc ...

National Academy of Sciences2024

A Softening Constitutive Law and Gradient-Inelastic Fiber-Based Element for 3-Dimensional Frame Simulations Under Seismic Excitations

Diego Isidoro Heredia Rosa

Steel frame structures are essential components of modern infrastructure. Understanding their behavior under seismic loading is critical for ensuring public safety and minimizing damage that occurs during earthquakes. To accurately predict the response of ...

EPFL2024

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Alireza Modirshanechi

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

EPFL2024

Experimental Investigation on Size-Effect of Rubble Stone Masonry Walls Under In-Plane Horizontal Loading: Overview and Preliminary Results

Katrin Beyer, Savvas Saloustros

Rubble stone masonry is a common construction typology of historical city centres and vernacular architecture. While past earthquakes have shown that it is one of the most vulnerable masonry construction typologies, there are few experimental campaigns giv ...

2024

Geometric Learning: Leveraging differential geometry for learning and control

Bernardo Fichera

In this thesis, we concentrate on advancing high-level behavioral control policies for robotic systems within the framework of Dynamical Systems (DS). Throughout the course of this research, a unifying thread weaving through diverse fields emerges, and tha ...

EPFL2024

How roughness emerges on natural and engineered surfaces

Jean-François Molinari, Ramin Aghababaei

Roughness, defined as unevenness of material surfaces, plays an important role in determining how engineering components or natural objects interact with other bodies and their environment. The emergence of fractal roughness on natural and engineered surfa ...

SPRINGER HEIDELBERG2023

Equivalent Frame Models for FRP-Strengthened Masonry Buildings

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 be ...

Proceedings of the 2nd Croatian Conference on Earthquake Eng2023

The use of ductile steel fuses for the seismic protection of acceleration sensitive non- structural components: Numerical and Experimental verification

Dimitrios Lignos, Ahmed Mohamed Ahmed Elkady

Recent seismic events have showcased the vulnerability of non-structural components to even low- or moderate-intensity earthquakes that occur far more frequently than design-basis ones. Thus, community-critical buildings, such as hospitals, telecommunicati ...

EEME2023

Geometric tolerances of welded connections with inelastic panel zones

Dimitrios Lignos, Andronikos Skiadopoulos, Ce Wen

Prequalified beam-to-column connections in steel moment resisting frames usually concentrate inelastic deformations in the steel beam ends. As such, nonlinear geo-metric instabilities (i.e., local buckling) may occur in these regions at modest lateral drif ...

Ernst & Sohn2023

Full-Scale Experiments of Cyclically Loaded Welded Moment Connections with Highly Dissipative Panel Zones and Simplified Weld Details

Dimitrios Lignos, Andronikos Skiadopoulos

This paper presents the experimental results of two welded unreinforced flange-welded web (WUF-W) beam-to-column connections that defy the current design paradigm of prequalified welded connections. The proposed WUF-W connections feature customized beveled ...

2023

Surrogate modelling for seismic collapse risk assessment of steel moment resisting frames

Dimitrios Lignos, Andronikos Skiadopoulos, Nenad Bijelic

With the overall goal of reducing the numerical burden of uncertainty quantification involved in seismic risk assessments, this paper examines opportunities for assessment of seismic collapse capacity and risk using data-driven surrogates as a complement t ...

2023

Caching and Neutrality

Aikaterini Argyraki, Pavlos Nikolopoulos, Muhammad Abdullah

We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users’ quality of experience (QoE). Most content today is accessed through edge caches, ...

ACM Association for Computing Machinery2023

Full Scale Experiments of a Composite Steel Moment Resisting Frame: Behavioral Insights and Implications on Seismic Design

Dimitrios Lignos, Hammad El Jisr

This paper discusses the cyclic performance of a heavily instrumented 2-bay full-scale composite-steel moment resisting frame (CMRF) sub-system from the onset of structural damage up until incipient collapse. The CMRF featured stiffened end plate bolted co ...

EEME2023

Energy dissipation in fiber-polymer composites adhesive joints under cyclic loading

Ghazaleh Eslami

Sustainable development has emerged as a paramount consideration in various fields of industry, including construction, to preserve the environment and its finite resources. Lightweight structures, such as fiber-polymer composite structures, address both s ...

EPFL2023

Reliability analysis and partial safety format calibration considering the characteristics of the resistance of reinforced concrete structures

Qianhui Yu

Every engineering calculation is an approximation of reality, with inevitable uncertainties involved. This fact implies that a reliability verification accounting for the uncertainties is a necessary step in the design and assessment of structures. Nowaday ...

EPFL2023

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

Colin Neil Jones, Melanie Nicole Zeilinger, Xuan Truong Nghiem, Roland Schwan

Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to ...

IEEE2023