Publications related to Experimental characterization and stochastic models for time-dependent rupture of thin-ply composite laminates

Related publications (30)

biogrowleR: Enhancing Longitudinal Data Analysis

Cathrin Brisken, Giovanna Ambrosini, Andrea Agnoletto, Carlos Henrique Venturi Ronchi, Daria Matvienko, Hazel Margaret Quinn

Time course measurements are used for many applications in biomedical research, ranging from growth curves to drug efficacy testing and high-throughput screening. Statistical methods used to analyze the resulting longitudinal data, such as t-tests or repea ...

Springer Science and Business Media LLC2025

A multigrid method for PDE-constrained optimization with uncertain inputs

Fabio Nobile, Tommaso Vanzan

In this manuscript, we present a collective multigrid algorithm to solve efficiently the large saddle-point systems of equations that typically arise in PDE-constrained optimization under uncertainty, and develop a novel convergence analysis of collective ...

Springer Science and Business Media LLC2024

Process development of pre-impregnated hybrid thin-ply composites

Alexios Argyropoulos

Thin-ply composites, obtained with recently developed fiber spreading techniques, rapidly gained industrial interest because they offer a large composite design freedom, and lead to a composite tensile strength that is close to that of the individual fiber ...

EPFL2023

Robust optimization of control parameters for WEC arrays using stochastic methods

Tommaso Vanzan

This work presents a new computational optimization framework for the robust control of parks of Wave Energy Converters (WEC) in irregular waves. The power of WEC parks is maximized with respect to the individual control damping and stiffness coefficients ...

Journal of Computational Physics2023

Multi-scale characterization and modeling of notched strength and translaminar fracture in hybrid thin-ply composites based on different carbon fiber grades

Guillaume Clément Broggi

Owing to their high specific stiffness and strength, Carbon Fiber Reinforced Composites (CFRP) are ideal candidates for the development of lightweight high-performance structures. Within this family, thin-ply composites allow for wider design freedom and p ...

EPFL2023

A multiscale consolidation model for press molding of hybrid textiles into complex geometries

Véronique Michaud

Modeling the consolidation of fiber-reinforced thermoplastic composites at the part level presents a formidable computational challenge due to the multi-scale nature of the process. In this article, a method to bypass the multi-scale problem by homogenizin ...

Wiley2024

Technosignatures Longevity and Lindy's Law

Claudio Grimaldi

The probability of detecting technosignatures (i.e., evidence of technological activity beyond Earth) increases with their longevity, or the time interval over which they manifest. Therefore, the assumed distribution of longevities has some bearing on the ...

Iop Publishing Ltd2024

We Need Subject Matter Expertise to Choose and Identify Causal Estimands: Comment on "Estimands for Recurrent Event Endpoints in the Presence of a Terminal Event"

Mats Julius Stensrud, Matias Janvin

We summarize what we consider to be the two main limitations of the "Estimands for Recurrent Event Endpoints in the Presence of a Terminal Event" (Schmidli et al. 2022). First, the authors did not give detailed guidance on how to choose an appropriate esti ...

TAYLOR & FRANCIS INC2023

Robot Learning using Tensor Networks

Suhan Narayana Shetty

In various robotics applications, the selection of function approximation methods greatly influences the feasibility and computational efficiency of algorithms. Tensor Networks (TNs), also referred to as tensor decomposition techniques, present a versatile ...

EPFL2024

Mean value theorems for collections of lattices with a prescribed group of symmetries

Nihar Prakash Gargava

Euclidean lattices are mathematical objects of increasing interest in the fields of cryptography and error-correcting codes. This doctoral thesis is a study on high-dimensional lattices with the motivation to understand how efficient they are in terms of b ...

EPFL2024

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Soumaya Elkantassi

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. ...

EPFL2023

Efficient and insightful descriptors for representing molecular and material space

Alexander Jan Goscinski

Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

EPFL2024

Experiments and proposed model for residual stresses in hot-rolled wide flange shapes

Dimitrios Lignos, Albano António De Abreu E Presa De Castro E Sousa, Andronikos Skiadopoulos

This paper proposes a new residual stress model for hot-rolled wide flange steel cross sections. For this purpose, a dataset of 85 residual stress measurements is first assembled. The dataset is comprised of prior measurements available in the literature t ...

2023

Numerical investigation of two-dimensional Mode-II delamination in composite laminates

Thomas Keller, Anastasios Vassilopoulos, Congzhe Wang

Existing standards for delamination tests on composite materials typically employ one-dimensional (1D) beam specimens. However, such specimens may not represent real delamination scenarios in composite structures, where cracks tend to propagate in two dime ...

Elsevier Sci Ltd2024

Personalized Privacy-Preserving Distributed Learning on Heterogeneous Data

Michael Christoph Gastpar, Aditya Pradeep

One major challenge in distributed learning is to efficiently learn for each client when the data across clients is heterogeneous or non iid (not independent or identically distributed). This provides a significant challenge as the data of the other client ...

2023

Influence of model uncertainty and long term deformations in action effects calculation in reinforced concrete structures

Xhemsi Malja

Most codes of practice adopt a semi probabilistic design approach for the dimensioning and assessment of structures. Accordingly, structural safety is ensured by performing limit state verifications using design values determined with adequately calibrated ...

EPFL2024

An Unbiased Method of Measuring the Ratio of Two Data Sets

Jean-Paul Richard Kneib, Huanyuan Shan

In certain cases of astronomical data analysis, the meaningful physical quantity to extract is the ratio R between two data sets. Examples include the lensing ratio, the interloper rate in spectroscopic redshift samples, and the decay rate of gravitational ...

IOP Publishing Ltd2023

A comprehensive review of digital twin-part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives

Olga Fink

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision- and policy-making, and more, by comprehensively m ...

SPRINGER2023

Full-Scale Tests to Characterize the Effect of Framing Action and Slab Continuity on the Collapse Capacity of Composite Frames Under Cyclic Loading

Dimitrios Lignos, Hammad El Jisr

This paper presents an experimental study that examined the role of the slab continuity and framing action on the overall hysteretic behavior of a composite-steel moment resisting frame (MRF) up until incipient collapse using advanced instrumentation. The ...

2024

Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024