Publications associées à Influence of the constant life diagram formulation on the fatigue life prediction of composite materials

Publications associées (34)

Adaptive Recursive Query Optimization

Anastasia Ailamaki, Martin Odersky, Guillaume André Fradji Martres, Anna Patricia Herlihy

Performance-critical industrial applications, including large-scale program, network, and distributed system analyses, are increasingly reliant on recursive queries for data analysis. Yet traditional relational algebra-based query optimization techniques d ...

IEEE2024

Dimensionality reduction of time-series data, and systems and devices that use the resultant embeddings

Mackenzie Mathis, Steffen Schneider

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for dimensionality reduction of time-series using contrastive learning. A method can include receiving multidimensional input time series data that includes ...

2023

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

An empirical model to calculate snow depth from daily snow water equivalent: SWE2HS 1.0

Adrien Michel

Many methods exist to model snow densification in order to calculate the depth of a single snow layer or the depth of the total snow cover from its mass. Most of these densification models need to be tightly integrated with an accumulation and melt model a ...

COPERNICUS GESELLSCHAFT MBH2023

A Geometric Transformer for Structural Biology: Development and Applications of the Protein Structure Transformer

Lucien Fabrice Krapp

Proteins, the central building blocks of life, play pivotal roles in nearly every biological function. To do so, these macromolecular structures interact with their surrounding environment in complex ways, leading to diverse functional behaviors. The predi ...

EPFL2023

Predictive Analysis of Errors During Robot-Mediated Gamified Training

Pierre Dillenbourg, Arzu Güneysu Özgür

This paper presents our approach to predicting future error-related events in a robot-mediated gamified phys- ical training activity for stroke patients. The ability to predict future error under such conditions suggests the existence of distinguishable fe ...

IEEE2022

Wigner Formulation of Thermal Transport in Solids

Nicola Marzari, Michele Simoncelli

Two different heat-transport mechanisms are discussed in solids. In crystals, heat carriers propagate and scatter particlelike as described by Peierls's formulation of the Boltzmann transport equation for phonon wave packets. In glasses, instead, carriers ...

American Physical Society2022

Lightweight HI source finding for next generation radio surveys

Jean-Paul Richard Kneib, Frédéric Courbin, Aymeric Alexandre Galan, Austin Chandler Peel, Emma Elizabeth Tolley, Mark Thomas Sargent

Future deep HI surveys will be essential for understanding the nature of galaxies and the content of the Universe. However, the large volume of these data will require distributed and automated processing techniques. We introduce LiSA, a set of python modu ...

ELSEVIER2022

Auto-tuning ensemble models for estimating shear resistance of headed studs in concrete

Xianlin Wang

The shear resistance of headed studs is of paramount importance for the design of steel-concrete composite structures and an accurate predictive model is highly needed. Ensemble learning is expected to be a powerful solution while it relies on laborious se ...

2022

A Novel Method to Quantify Self-Healing Capabilities of Fiber-Reinforced Polymers

Cecilia Scazzoli, Véronique Michaud, Amaël Maximilien Cohades, Robin Samuel Trigueira

The present work investigates a novel and practical method to evaluate the healing efficiency of carbon-reinforced polymer composites. The method should be representative of damage occurring during the lifetime of a composite part, should tend to damage th ...

FRONTIERS MEDIA SA2022

Reviewing Challenges of Predicting Protein Melting Temperature Change Upon Mutation Through the Full Analysis of a Highly Detailed Dataset with High-Resolution Structures

Luciano Andres Abriata

Predicting the effects of mutations on protein stability is a key problem in fundamental and applied biology, still unsolved even for the relatively simple case of small, soluble, globular, monomeric, two-state-folder proteins. Many articles discuss the li ...

2021

A data-driven perspective on the colours of metal-organic frameworks

Berend Smit, Luc Patiny, Mehrdad Asgari, Seyedmohamad Moosavi, Kevin Maik Jablonka, Christopher Patrick Ireland

Colour is at the core of chemistry and has been fascinating humans since ancient times. It is also a key descriptor of optoelectronic properties of materials and is often used to assess the success of a synthesis. However, predicting the colour of a materi ...

2021

Predictors and predictands of linear response in spatially extended systems

Umberto Maria Tomasini

The goal of response theory, in each of its many statistical mechanical formulations, is to predict the perturbed response of a system from the knowledge of the unperturbed state and of the applied perturbation. A new recent angle on the problem focuses on ...

SPRINGER HEIDELBERG2021

Surface energy contributions to the work of infiltration in metal matrix composite processing

Andreas Mortensen, Gionata Schneider

The work needed to mechanically drive molten metal into a porous solid preform when producing a composite material by infiltration can significantly exceed the energy change required for thermodynamically reversible infiltration. We measure, by quantitativ ...

2021

Worldwide performance evaluation of ground surface reflectance models

Christophe Ballif, Arttu Matias Tuomiranta

To improve the accuracy of bifacial gain estimation, recent radiative models of solar energy systems have abandoned the traditional assumption of isotropic ground-reflected radiance. However, surface reflectance itself is still commonly considered as a con ...

2021

On The Relationship Between Speech-Based Breathing Signal Prediction Evaluation Measures And Breathing Parameters Estimation

Mathew Magimai Doss, Zohreh Mostaani

The respiratory system is one of the major components of the speech production system. Any alteration in breathing can result in changes in speech. Specific breathing characteristics, such as breathing rate and tidal volume, can indicate a person's patholo ...

IEEE2021

Optimal Adversarial Policies in the Multiplicative Learning System With a Malicious Expert

Negar Kiyavash, Seyed Jalal Etesami

We consider a learning system based on the conventional multiplicative weight ( MW) rule that combines experts' advice to predict a sequence of true outcomes. It is assumed that one of the experts is malicious and aims to impose the maximum loss on the sys ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Load history effects in fibre-reinforced polymer composite materials

Abdolvahid Movahedirad

Today, it is widely accepted that fatigue is one of the most common failure mechanisms in structural components, and pure static failure is rarely observed. Engineering structures are subjected to complex mechanical fatigue loading histories, which cause d ...

EPFL2019

A machine learning approach based on generative topographic mapping for disruption prevention and avoidance at JET

Alessandro Pau

The need for predictive capabilities greater than 95% with very limited false alarms are demanding requirements for reliable disruption prediction systems in tokamaks such as JET or, in the near future, ITER. The prediction of an upcoming disruption must b ...

IOP Publishing Ltd2019

Predicting involuntary hospitalization in psychiatry: A machine learning investigation

Mehdi Gholam

Background Coercion in psychiatry is a controversial issue. Identifying its predictors and their interaction using traditional statistical methods is difficult, given the large number of variables involved. The purpose of this study was to use machine-lear ...

CAMBRIDGE UNIV PRESS2021