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PhD Candidate of Civil Engineering

Northwestern University


ACI convention Fall 2018 (from left to right) Professor Gianluca Cusatis, Professor Zdeněk Bažant, Professor Luigi Cedolin, and myself.


I am a fifth-year PhD candidate of Civil Engineering within the Mechanics, Materials, and Structures Group at Northwestern University. I obtained a Bachelor and a Master's Degree in structural engineering from Ecole Spéciale des Travaux Publics, du Bâtiment et de l'Industrie (France) and a Master of Science in mechanics of materials and solids from Northwestern University. Prior to joining Northwestern University, I worked in the field of asphalt testing and modeling, in the research and development departments of LafargeHolcim and Eiffage Travaux Publics (France). My current research interests lie in formulating and validating multi-scale and multi-physics models for the characterization of concrete behavior, based on both experimental studies and computational mechanics. In particular, I study concrete deterioration due to alkali-silica reaction, hydration and aging process, and model calibration and inverse/optimization problems. I also work on random fields models for concrete, modeling fiber-reinforced concrete and concrete shear walls, and scratch test on quasi-brittle materials. In parallel, I was involved in undergraduate and graduate courses as a teaching assistant and grader in the subjects of Engineering Analysis, Mechanics of Materials, Theory of Elasticity and Inelastic Analysis of Structures.  

Current Research

Experimental and Modeling Study of Concrete/Mortar Deterioration Due to Alkali Silica Reaction and Aging Process

  1. The mechanical behavior of mortar was evaluated and monitored, under normal and accelerated environmental conditions. Properties such as fracture energy, compressive strength and tensile strength were measuredA multi-physics computational framework, based on the Lattice Discrete Particle Model (LDPM) was proposed and numerical simulations were performed.
    For more information:


  2. Similar experimental and computational work was conducted for regular concrete, and additional aspects such as long-term behavior, creep and shrinkage were explored. 

  3. Structural longitudinally reinforced beam elements, with or without shear reinforcements, were tested under four point bending, along with strain gage measurement on rebars and DIC (Digital Image Correlation) during testings. Ongoing work focuses on simulating the different failure mechanisms and the decrease in flexural strength and stiffness using LDPM.

  4. The model parameters being already calibrated, ongoing work focuses on predicting available data in the literature. In particular, the aim is to predict the behavior of ASR-affected concrete subjected to triaxial confinement.  

Multiscale Modeling of Cement Hydration in Concrete

  1. In the absence of additional (curing) water, cement hydration is accompanied by self-desiccation and autogeneous shrinkage, which may induce early-age cracking. The traditional approach in predicting self-desiccation is to simulate hygro-thermo-mechanics directly at the macroscale and provide hydration-related inputs via empirical constitutive models. 

    The original contribution of this work, instead, is to obtain inputs to such constitutive relations from direct simulations of cement hydration at the microscale, using the state-of-the-art simulator for Cement Hydration in Three Dimensions (CEMHYD3D). The advantages of this two-scales approach are twofold: (i) the simulations at the macroscale do not need to be calibrated by fitting any of the experiments that they aim to predict, viz. the parametrization of constitutive laws is purely bottom-up from the microscale simulations; (ii) the microscale simulations provide the full range of parameters that are needed for the macroscale model, in contrast with experiment-based model calibrations that often suffer from incomplete datasets. 
    For more information:

Model Calibration and Inverse/Optimization Problems

  1. Model predictions depend largely on the quality and robustness of the model itself. The formulations of the physics-based or semi-empirical equations and the well-posedness of the investigated problem are crucial.

    In order to provide a reliable numerical tool for researchers and engineers, a systematic optimization approach is developed to identify the model parameters based on experimental data. The code uses the so-called NLOPT, an open-source/free library, well-known for its capabilities in non-linear optimization. This algorithm was successfully implemented in C++ as an external program and is applied to perform the inverse analysis of concrete fracturing behavior using LDPM.


Discrete Modeling of Scratch Test

  1. The idea of the scratch test is simple: cutting at different depths with a scratch device the surface of a weaker material, and relate the scratch resistance to the mechanical properties of the tested material. 

    The focus of this study is the modeling of scratch tests on granular materials using the LDPM framework as a discrete formulation. The interest is to analyze the failure mechanisms underlying this complex test by means of analytical formulations and numerical simulations, i.e. LDPM and Linear Elastic Fracture Mechanics (LEFM) based models. 

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