arXiv subjects
Publications and source records attributed to Marco Lauricella.
We outline the main ideas behind the numerical modelling of soft-flowing crystals, with special attention to their application to microfluidic devices for the design of novel mesoscale porous materials.
The problem of estimating the parameters of induction motor models is considered, using the data measured by a circuit breaker equipped with industrial sensors. The measured data pertain to direct-on-line motor startups, during which the breaker acquires three-phase stator voltage and current derivative. This setup is novel with respect to previous contributions in the literature, where voltage and current (and possibly also rotor speed) are considered. The collected data are used to formulate a parameter identification problem, where the cost function penalizes the discrepancy between simulated and measured derivatives of the stator currents. The resulting nonlinear program is solved via numerical optimization, and a number of algorithmic improvements with respect to the literature are proposed. In order to evaluate the goodness of the obtained results, an experimental rig has been built, where the motor's voltages and currents are simultaneously acquired also by accurate sensors, and the corresponding identification results are compared with those obtained with the circuit breaker. The presented experimental results indicate that the considered industrial circuit breaker is able to provide data with high-enough quality to carry out model-based nonlinear identification of induction machines. The identified models can then be used for several further applications within a smart grid scenario.
We present a regularized version of the color gradient lattice Boltzmann (LB) scheme for the simulation of droplet formation in microfluidic devices of experimental relevance. The regularized version is shown to provide computationally efficient access to Capillary number regimes relevant to droplet generation via microfluidic devices, such as flow-focusers and the more recent microfluidic step emulsifier devices.
We investigate the effects of nanoparticles on the onset of varicose and whipping instabilities in the dynamics of electrified jets. In particular, we show that the non-linear interplay between the mass of the nanoparticles and electrostatic instabilities, gives rise to qualitative changes of the dynamic morphology of the jet, which in turn, drastically affect the final deposition pattern in electrospinning experiments. It is also shown that even a tiny amount of excess mass, of the order of a few percent, may more than double the radius of the electrospun fiber, with substantial implications for the design of experiments involving electrified jets as well as spun organic fibers.
Electrospinning is a nanotechnology process whereby an external electric field is used to accelerate and stretch a charged polymer jet, so as to produce fibers with nanoscale diameters. In quest of a further reduction in the cross section of electrified jets hence of a better control on the morphology of the resulting electrospun fibers, we explore the effects of an external rotating electric field orthogonal to the jet direction. Through extensive particle simulations, it is shown that by a proper tuning of the electric field amplitude and frequency, a reduction of up to a $30 \%$ in the aforementioned radius can be obtained, thereby opening new perspectives in the design of future ultra-thin electrospun fibres. Applications can be envisaged in the fields of nanophotonic components as well as for designing new and improved filtration materials.
We propose a mathematical model for computing drug release from multi-layer capsules. The diffusion problem in such heterogeneous layer-by-layer composite medium is described by a system of coupled partial differential equations, which we solve analytically using separation of variables. In addition to the conventional interlayer continuous mass transfer boundary conditions, we consider also the case of finite mass transfer resistance, which corresponds to the case of a coated capsule. The drug concentration in the core and through all layers, as well as in the external release medium, is then given in terms of a Fourier series that we compute numerically to characterize the drug release mechanism.
We present a multi-layer mathematical model to describe the the transdermal drug release from an iontophoretic system. The Nernst-Planck equation describe the basic convection-diffusion process, with the electric potential obtained by Laplace equation. These equations are complemented with suitable interface and boundary conditions in a multi-domain. The stability of the mathematical problem is discussed in different scenarios and a finite-difference method is used to solve the coupled system. Numerical experiments are included to illustrate the drug dynamics under different conditions.
Nowadays, several models of unidimensional fluid jets exploit discrete element methods. In some cases, as for models aiming at describing the electrospinning nanofabrication process of polymer fibers, discrete element methods suffer a non constant resolution of the jet representation. We develop a dynamic mesh-refinement method for the numerical study of the electro-hydrodynamic behavior of charged jets using discrete element methods. To this purpose, we import ideas and techniques from the string method originally developed in the framework of free-energy landscape simulations. The mesh-refined discrete element method is demonstrated for the case of electrospinning applications.
We study the effects of a controlled gas flow on the dynamics of electrified jets in the electrospinning process. The main idea is to model the air drag effects of the gas flow by using a non-linear Langevin-like approach. The model is employed to investigate the dynamics of electrified polymer jets at different conditions of air drag force, showing that a controlled gas counterflow can lead to a decrease of the average diameter of electrospun fibers, and potentially to an improvement of the quality of electrospun products. We probe the influence of air drag effects on the bending instabilities of the jet and on its angular fluctuations during the process. The insights provided by this study might prove useful for the design of future electrospinning experiments and polymer nanofiber materials.
We present the open-source computer program JETSPIN, specifically designed to simulate the electrospinning process of nanofibers. Its capabilities are shown with proper reference to the underlying model, as well as a description of the relevant input variables and associated test-case simulations. The various interactions included in the electrospinning model implemented in JETSPIN are discussed in detail. The code is designed to exploit different computational architectures, from single to parallel processor workstations. This paper provides an overview of JETSPIN, focusing primarily on its structure, parallel implementations, functionality, performance, and availability.
JETSPIN is an open-source computer program specifically designed to simulate the electrospinning process of nanofibers. This manual provides an overview of JETSPIN, focusing primarily on its structure, parallel implementations, functionality, performance, and availability. The code is designed to exploit different computational architectures, from single to parallel processor workstations.
We investigate the effects of dissipative air drag on the dynamics of electrified jets in the initial stage of the electrospinning process. The main idea is to use a Brownian noise to model air drag effects on the uniaxial elongation of the jets. The developed numerical model is used to probe the dynamics of electrified polymer jets at different conditions of air drag force, showing that the dynamics of the charged jet is strongly biased by the presence of air drag forces. This study provides prospective beneficial implications for improving forthcoming electrospinning experiments.
Electrospun polymer jets are imaged for the first time at an ultra-high rate of 10,000 frames per second, investigating the process dynamics, and the instability propagation velocity and displacement in space. The polymer concentration, applied voltage bias and needle-collector distance are systematically varied, and their influence on the instability propagation velocity and on the jet angular fluctuations analyzed. This allows us to unveil the instability formation and cycling behavior, and its exponential growth at the onset, exhibiting radial growth rates of the order of 10^3 s^-1. Allowing the conformation and evolution of polymeric solutions to be studied in depth, high-speed imaging at sub-ms scale shows a significant potential for improving the fundamental knowledge of electrified jets, leading to obtain finely controllable bending and solution stretching in electrospinning, and consequently better designed nanofibers morphologies and structures.
We present a non-linear Langevin model to investigate the early-stage dynamics of electrified polymer jets in electrospinning experiments. In particular, we study the effects of air drag force on the uniaxial elongation of the charged jet, right after ejection from the nozzle. Numerical simulations show that the elongation of the jet filament close to the injection point is significantly affected by the non-linear drag exerted by the surrounding air. These result provide useful insights for the optimal design of current and future electrospinning experiments.