Publications associées à Pre-bcc: A novel integrated machine learning framework for predicting mechanical and durability properties of blended cement concrete

Publications associées (35)

Pedagogy of an interdisciplinary, hands-on workshop to design and build floor systems with reused materials

Corentin Jean Dominique Fivet, Maléna Bastien Masse, Célia Marine Küpfer, Barbara Ludivine Justine Lambec, Peter Zurbrügg

This paper reflects on the pedagogy used for a series of student workshops on building with reused materials at the Ecole Polytechnique Fédérale de Lausanne (EPFL) and presents the results of its 7 th edition, which focused on floor systems. During these w ...

CRC Press2025

A Novel Uniaxial Penetration Approach to Investigate Sulfate Attack on Cement-Based Materials

Karen Scrivener, Qiao Wang

The sodium sulfate crystallization attack in cementitious materials is addressed in this paper. Portland cement, sulfate-resisting cement, and calcined clay limestone cement were compared by the evolution of expansion, sulfate ingress property, and suscept ...

Springer Science and Business Media B.V.2025

Random matrix methods for high-dimensional machine learning models

Antoine Philippe Michel Bodin

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

EPFL2024

Decarbonization potential of steel fibre-reinforced limestone calcined clay cement concrete one-way slabs

Hisham Tarek Mohamed Hafez, Beatrice Malchiodi

This study deals with a comparison of the environmental performance of one-way slabs utilizing steel fibrereinforced limestone calcined clay cement (LC3) concrete with the control case of Ordinary Portland cement concrete. The experimental program constitu ...

Elsevier Sci Ltd2024

Robust machine learning for neuroscientific inference

Steffen Schneider

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

EPFL2024

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Arnout Jan J Devos

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

EPFL2024

Additively manufactured steel reinforcement for small scale reinforced concrete modeling: Tensile and bond behavior

Christian Leinenbach

Small scale (1:30-1:40) Reinforced Concrete is useful for centrifuge testing. However, manufacturing the reinforcing cages by hand at this scale is practically difficult. This paper suggests that small scale reinforcement can be manufactured using a metal ...

Elsevier Sci Ltd2024

Contradict mechanism of long-term magnesium and sodium sulfate attacks of nano silica-modified cement mortars - Experimental and thermodynamic modeling

Qiao Wang

The mechanisms of external sulfate attack on cement mortars containing nano silica have been studied under full immersion conditions after 3 years. The sulfate degradation processes were compared between sodium sulfate and magnesium sulfate solutions with ...

Elsevier Sci Ltd2024

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Mattia Atzeni

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Jean-Paul Richard Kneib, Emma Elizabeth Tolley, Michele Bianco, Tianyue Chen

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Oxford Univ Press2024

Contributions to rebar-to-concrete interaction and its structural implications for design and monitoring applications

Enrique Corres Sojo

Bond between reinforcing bars and concrete has been the focus of extensive research over the last century. This is well-justified as the functioning of reinforced concrete intimately depends on the interaction between rebar and concrete, as for example cra ...

EPFL2024

CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

David Atienza Alonso, Marina Zapater Sancho, Ali Pahlevan, Darong Huang, Luis Maria Costero Valero

Computing servers have played a key role in developing and processing emerging compute-intensive applications in recent years. Consolidating multiple virtual machines (VMs) inside one server to run various applications introduces severe competence for limi ...

2024

A bio-chemo-hydro-mechanical model of transport, strength and deformation for bio-cementation applications

Lyesse Laloui, Dimitrios Terzis

Bio-cementation through microbially induced calcite precipitation (MICP) has the potential to overcome several technical and environmental limitations of conventional cement-based soil improvement techniques. While a significant amount of research has been ...

Springer Heidelberg2024

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Romain Christophe Rémy Fleury, Janez Rus

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

2024

Engineering novel protein interactions with therapeutic potential using deep learning-guided surface design

Anthony Marchand

Proteins are foundational biomolecules of life playing a crucial role in a myriad of biological processes. Their function often requires interplay with other biomolecules, including proteins themselves. Protein-protein interactions (PPIs) are essential for ...

EPFL2024

FLO:RE – A new floor system made of reused reinforced concrete and steel elements

Corentin Jean Dominique Fivet, Numa Joy Bertola, Maléna Bastien Masse, Célia Marine Küpfer

Carefully extracting reinforced concrete (RC) elements from soon-to-be demolished structures and reusing them as load-bearing components is an emerging circular low-carbon alternative to building new structures. As floor construction typically accounts for ...

IABSE2024

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Olga Fink, Hao Lu

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

2024

Reliable data-driven decision-making through optimal transport

Bahar Taskesen

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

EPFL2024

Incorporating Projective Geometry into Deep Learning

Michal Jan Tyszkiewicz

In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

EPFL2024

Dynamic Voxels Based on Ego-Conditioned Prediction: An Integrated Spatio-Temporal Framework for Motion Planning

Alexandre Massoud Alahi

Prediction is a vital component of motion planning for autonomous vehicles (AVs). By reasoning about the possible behavior of other target agents, the ego vehicle (EV) can navigate safely, efficiently, and politely. However, most of the existing work overl ...

IEEE Institute of Electrical and Electronics Engineers2024