Benoît Hilloulin

Assistant Professor

Ecole centrale de Nantes

France

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Research Interests

Solid Mechanics

40%

Rock Mechanics

40%

Concrete Technology

60%

Porosity Analysis

50%

Poroelasticity

30%

Fracture Mechanics

30%

Construction Materials Engineering

20%

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Articles19

Machine learning in concrete durability: challenges and pathways identified by RILEM TC 315-DCS towards enhanced predictive models

Year:

2025

Methods for Defining Climate Change Mitigation Strategies at Organisational Level Review and Outlook

Year:

2025

Microstructural effect of a new combined thermal and CO2 curing protocol for low-carbon cementitious materials

Year:

2025

Combined nanoindentation and SEM imaging for phase quantification and creep prediction of cementitious materials

Year:

2025

Investigation of the creep properties of blended cement pastes using combined nanoindentation and SEM imaging

Year:

2025

Experimental Investigation on the Effects of Mineral Water Composition on the Leaching of Cement-Based Materials

Year:

2024

Machine learning-aided prediction of shrinkage in modern concrete: Focus on mix proportions and SCMs

Year:

2024

Interpretable machine learning model for autogenous shrinkage prediction of low-carbon cementitious materials

Year:

2023

Imaging concrete cracks using Nonlinear Coda Wave Interferometry (INCWI)

Year:

2023

Multiscale investigation of cement pastes with low and high-grade calcined clays and slag at early and advanced ages

Year:

2023

Creep analysis of cementitious materials in seawater using a poro-chemo-mechanical model

Year:

2023

Towards quantifying the effect of pump wave amplitude on cracks in the Nonlinear Coda Wave Interferometry method

Year:

2023

Interpretable ensemble machine learning for the prediction of the expansion of cementitious materials under external sulfate attack

Year:

2023

Coupled effects of simultaneous autogenous self-healing and sustained flexural loading in cementitious materials

Year:

2023

Modular deep learning segmentation algorithm for concrete microscopic images

Year:

2022

Open‐source deep learning‐based air‐void detection algorithm for concrete microscopic images

Year:

2022

ε–greedy automated indentation of cementitious materials for phase mechanical properties determination

Year:

2022

e-greedy automated indentation of cementitious materials for phase mechanical properties determination

Year:

2022

Using machine learning techniques for predicting autogenous shrinkage of concrete incorporating superabsorbent polymers and supplementary cementitious materials

Year:

2022

Collaborators7

Muhammad Usman Hanif

Korea National University of Transportation

SOUTH KOREA

Emmanuel Roziere

Université de Nantes

FRANCE

Woubishet Taffese

Arcada University of Applied Sciences

FINLAND

Jacqueline SALIBA

Associate professor

University of Bordeaux

FRANCE

Alexis Laurent

Technical University of Denmark

DENMARK

Sandra Nunes

Delft University of Technology

NETHERLANDS

Frederic Grondin

Université de Nantes

FRANCE

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