{"id":28479,"date":"2025-12-08T10:11:34","date_gmt":"2025-12-08T09:11:34","guid":{"rendered":"https:\/\/www.dica.polimi.it\/dottorato\/phd-graduate\/"},"modified":"2026-02-25T01:22:46","modified_gmt":"2026-02-25T00:22:46","slug":"phd-graduate","status":"publish","type":"page","link":"https:\/\/www.dica.polimi.it\/en\/dottorato\/phd-graduate\/","title":{"rendered":"PhD Graduate"},"content":{"rendered":"
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On the Use of Textile Waste Fibres for Sustainable Solutions in Earth Embankments Repair<\/h4>\t\t\t\t<\/div>\n\t\t\t\t
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The use of soil mixed with fibres from textile waste in embankment improvement has been investigated with the twofold purpose to identify an effective engineering practice and to provide a strategy for the circular economy of textiles. Laboratory tests have been conducted to define the appropriate mixture proportions and to compare physical properties and hydromechanical behaviour of natural soil and soil treated with linen and viscose fibres. The results indicate that with appropriate fibre content, manageable and homogeneous mixtures can be achieved, making this solution suitable for practical applications; however, ensuring applicability at the site scale requires the use of appropriately sized equipment. The presence of the selected textile fibres significantly impacts the hydromechanical behaviour of the soil and the effect of fibres depends on their geometry, properties, and the sample preparation procedure. As the results demonstrate that the geotechnical properties of the treated soil can be engineered to meet specific site requirements, the proposed approach seems a promising solution for earth works and ground improvement, such as embankment repair and restoration.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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Road Safety on Italian State Roads through Predictive Approach: Transferability of Existing Models and Development of New Models<\/h4>\t\t\t\t<\/div>\n\t\t\t\t
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Every year, over one million people lose their lives in road crashes worldwide. These alarming figures led to the ambitious international goal of halving road fatalities by 2030 and completely eliminating them by 2050, in line with the so-called \u201cVision Zero.\u201d This is the framework in which my PhD thesis was developed. Traditionally, road safety was addressed through a reactive approach, which involved interventions only after crashes occurred. However, the real challenge for road engineers is to wonder if it is possible to prevent crashes from happening in the first place. This question lies at the core of the predictive approach, based on regression models to estimate crash risk of various sites based on road geometry, traffic conditions, and other external factors. My research was focused on adapting and evaluating the transferability of existing models to the Italian context, and developing new alternative models. The ultimate goal is to provide a practical tool to support road managers in safety analysis, planning of interventions, and decision-making process.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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A PFEM numerical framework for simulating 3D printing of advanced materials<\/h4>\t\t\t\t<\/div>\n\t\t\t\t
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This research introduces a Particle Finite Element Method (PFEM) framework for simulating 3D printing processes involving advanced materials. Leveraging the Lagrangian formulation of PFEM, the approach enables precise tracking of free surfaces and accommodates large deformations through an efficient re-meshing strategy. To capture the complex behaviour of modern printing materials, the framework integrates a range of viscoplastic, viscoelastic, and elasto-viscoplastic constitutive models, accounting for key phenomena such as elastic memory, phase transitions, and thixotropy. Specialized techniques are also developed to simulate extrusion and layer-by-layer deposition, incorporating nozzle motion, inter-layer and substrate contact, as well as strategies for reducing computational cost. The model is validated against experimental data, demonstrating high accuracy in predicting filament geometry and offering insight into the influence of material and process parameters. Finally, an optimized implicit finite element solver is implemented in a Fortran environment, enabling efficient, long-duration simulations of complex printed structures, including detailed infill patterns and parameterized geometries.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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From the fault rupture to city seismic response: 3D multi-scale physics-based scenarios of earthquake effects<\/h4>\t\t\t\t<\/div>\n\t\t\t\t
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Earthquakes can be devastating, especially in densely populated urban areas. With urban populations projected to grow, improving seismic hazard and risk evaluation at a site-specific level is essential. While 3D physics-based earthquake simulations (PBS) are reliable for estimating the site-specific ground motion (GM), they are computationally expensive and rarely used for fully coupled earthquake fault-to-structure simulations. In this work, addressing these issues, we validated the accuracy of our open-source code, SPEED<\/a>, for simulating site-specific broadband ground motion. Then, to perform fully coupled simulations without computational overhead, we developed new tools in SPEED to:<\/p>

  1. perform large-scale 3D nonlinear simulations to account for soil response.<\/li>
  2. couple building response with ground motion at an urban scale.<\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t
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    Development of Models for the Simulation of the Mechanical Behavior of Cords Used in Tires<\/h4>\t\t\t\t<\/div>\n\t\t\t\t
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    This study presents a new macroscopic numerical model to simulate the mechanical behavior of polymeric reinforcements used in tires. An extensive experimental campaign on rayon yarns and cords under different loading conditions provided information about material and geometrical nonlinearities. The reinforcement is represented as an equivalent three-dimensional continuum with an anisotropic constitutive model, incorporating viscosity and plasticity components. Local material directions are determined analytically based on twisting and cord construction. The model is calibrated and validated against experimental data, including tensile and bending tests. The proposed approach accurately predicts reinforcement behavior, offering insights for optimizing cord design in tire applications.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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    Sediment transport: from averages to fluctuations<\/h4>\t\t\t\t<\/div>\n\t\t\t\t
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    This thesis explores bedload transport in rivers, focusing on defining, measuring, and modelling solid flowrate. It can be expressed in three ways: as sediment volume crossing a line per unit width and time, as the product of particle activity and velocity, or as the product of entrainment rate and hop length. I show that these definitions are different time\/space averages of the same equation describing flux. I then focus on the second definition, highlighting unresolved issues in measuring flowrate, concentration, and velocity. Distinguishing between movement and stillness is key, so I propose three states: stillness, transport, and non-transport. Particles in transport state clearly move downstream, while non-transport involves isotropic jiggling and doesn\u2019t contribute to bedload but affects other transport metrics. Finally, I examine turbulence\u2019s effect on sediment transport using flume experiments with varying turbulence levels. Measuring fluid velocity, shear stress, and sediment motion reveals that increased fluctuations enhance flowrate, concentration, and velocity, with turbulence having a stronger effect on concentration than velocity.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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    Data-Driven Modeling of Nonlinear Dynamical Systems<\/h4>\t\t\t\t<\/div>\n\t\t\t\t
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    The simulation of complex physical phenomena has traditionally relied on solving computationally expensive models derived from first principles. However, the growing availability of rich data enables a new paradigm: discovering governing equations directly from measurements. This approach enhances flexibility and computational efficiency while preserving physical consistency. By combining machine learning with dimensionality reduction, a new generation of reduced-order models has been developed. These methods identify key variables and governing dynamics from high-dimensional data, enabling accurate predictions and efficient simulations. Applications span from structural mechanics to computational biology, demonstrating the versatility and potential of these techniques. This research lays the groundwork for an AI-driven revolution in scientific discovery, accelerating our ability to understand and control physical systems across scales.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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    Stochastic characterization of reactive processes in porous media<\/h4>\t\t\t\t<\/div>\n\t\t\t\t
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    My research is focused on exploring critical elements of the nature of flow and transport processes taking place across porous geomaterials and their interactions with the host solid matrix. In this broad context, dissolution is a key process driving mineral transformations. These transformations, in turn, drive weathering of mineral surfaces, interact with spreading of pollutants in groundwater systems, and favor carbon capture through mineralization. The key research questions tackled in my PhD thesis are related to:<\/p>