Publications related to Thermoviscoelastic anisotropic analysis of process induced residual stresses and dimensional stability in real polymer matrix composite components

Related publications (31)

A Comparative Analysis of Tools & Task Types for Measuring Computational Problem-Solving

Richard Lee Davis, Engin Walter Bumbacher, Jérôme Guillaume Brender

How to measure students' Computational Problem-Solving (CPS) competencies is an ongoing research topic. Prevalent approaches vary by measurement tools (e.g., interactive programming, multiple-choice tests, or programming-independent tests) and task types ( ...

Association for Computing Machinery2024

Flash Melting Amorphous Ice

Marcel Drabbels, Ulrich Lorenz, Gabriele Bongiovanni, Constantin Richard Krüger, Nathan Junior Mowry

Water can be vitrified if it is cooled at high rates, which makes it possible to outrun crystallization in so-called no man’s land, a range of deeply supercooled temperatures where water crystallizes rapidly. Here, we study the reverse process in pure wate ...

2024

Two-dimensional quasi-static delamination in composite laminates under Mode-I and Mode-II conditions

Congzhe Wang

Fiber-polymer composites consist of a polymer matrix and reinforcing fibers made of various materials. These composites exhibit exceptional properties, such as a high strength-to-weight ratio and excellent corrosion resistance, which has led to their incre ...

EPFL2024

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Evann Pierre Guy Courdier

Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power. Simultaneously, a critical pain point arises as several computer vision applications are deploye ...

EPFL2024

Proposed residual stress model for hot‐rolled wide flange steel cross sections

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

Residual stresses in hot-rolled wide flange steel cross sections may lead to premature yielding, accelerated corrosion and brittle fracture of steel members. The above phenomena lead to a loss of a steel member's stiffness and resistance under mechanical l ...

Ernst & Sohn2023

Database of Residual Stress Measurements on Hot-rolled Wide Flange Steel Cross Sections

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

Data_info.csv: Database of 'Residual Stress Measurements on Hot-rolled Wide Flange Steel Cross Sections' including cross-sectional and material characteristics as well as information relevant to ploting the residual stress distributions. Distributions.zip: ...

Zenodo2023

Advancing efficiency and reliability in thermal analysis of laser powder-bed fusion

Christian Leinenbach

In laser based powder-bed fusion of metals (PBF-LB/M), parts are fabricated by melting layers of powder using a high-intensity laser beam. During this process, the material is exposed to rapid cooling rates and intense thermal gradients, which are the unde ...

2023

Nanomechanical Modeling of the Bending Response of Silicon Nanowires

Yusuf Leblebici, Zuhal Tasdemir

Understanding the mechanical behavior of silicon nanowiresis essentialfor the implementation of advanced nanoscale devices. Although bendingtests are predominantly used for this purpose, their findings shouldbe properly interpreted through modeling. Variou ...

AMER CHEMICAL SOC2023

Geometric tolerances of welded connections with inelastic panel zones

Ce Wen, Dimitrios Lignos, Andronikos Skiadopoulos

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

The Societal and Scientific Importance of Inclusivity, Diversity, and Equity in Machine Learning for Chemistry

Daniel Probst

While the introduction of practical deep learning has driven progress across scientific fields, recent research highlighted that the requirement of deep learning for ever-increasing computational resources and data has potential negative impacts on the sci ...

2023

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

Tailor-made Piezoelectric Elastomer Materials

Francis Owusu

Recent advancements in miniature devices with higher computational capabilities and ultralow power consumption have accelerated the development of wearable sensors, actuators, and energy harvesters everywhere. The ultimate aim of such a technological revol ...

EPFL2023

Learning With Your PETS

Drazen Dujic, Andrea Cervone, Renan Pillon Barcelos, Jules Christian Georges Macé, Max Dupont

Recently, we published an article [1] presenting how the Power Electronics course at the bachelor level is organized by the Power Electronics Laboratory and taught at Ecole Polytechnique Fédérale de Lausanne, EPFL, Switzerland. For those avid readers who m ...

2023

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

Expectation consistency for calibration of neural networks

Lenka Zdeborová, Florent Gérard Krzakala, Bruno Loureiro, Lucas Andry Clarte

Despite their incredible performance, it is well reported that deep neural networks tend to be overoptimistic about their prediction confidence. Finding effective and efficient calibration methods for neural networks is therefore an important endeavour tow ...

2023

Microscopic Digital Image Correlation Analysis of Strain Distributions in Stainless Steel 316L Induced by Multiaxial Cyclic Loading

Elif Cansu Kursun

Fatigue damage in materials results in localized strain at the microstructural level. In many engineering components of the cooling circuits of nuclear power plants, where austenitic steels are used, the material experiences multiaxial cyclic loading, eith ...

EPFL2023

Numerical and experimental investigation of spiral-grooved gas journal bearings

Elia Iseli

Small-scale turbomachinery is increasingly used in carbon-free energy conversion systems, such as commercial or domestic scale heat pumps, fuels cells for transportation and waste heat recovery. The usage of aerodynamic bearings allows the design of compac ...

EPFL2022

FEM of stress partition during compression of WC-10 wt.% Co with realistic 3D morphology

Daniele Mari, Lucas Eric Jacques Degeneve

A Finite Element Model is developed to represent the mechanical behavior of WC-10 wt.% Co in compression tests. In this research, realistic three-dimensional model is obtained by slicing a sample by Focused Ion Beam and reconstituting it, resulting in two ...

ELSEVIER SCI LTD2022

Democratizing Machine Learning

Nirupam Gupta, Rafaël Benjamin Pinot, Alexandre David Olivier Maurer

The increasing prevalence of personal devices motivates the design of algorithms that can leverage their computing power, together with the data they generate, in order to build privacy-preserving and effective machine learning models. However, traditional ...

IEEE2022

Towards coupling conventional with high-fidelity fuel behavior analysis tools

Andreas Pautz, Carlo Fiorina, Alessandro Scolaro, Edoardo Luciano Brunetto

Multi-dimensional fuel performance codes have the potential to enhance the understanding of complex phenomena affecting fuel integrity, but their application is often limited by the high computational cost. Recognizing that many multi-dimensional aspects s ...

PERGAMON-ELSEVIER SCIENCE LTD2022