Sami Barmada

Dr. Sami Barmada

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Academic Career Length

27Years (2000-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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5 July 2006 in IEEE Journal on Selected Areas in Communications
Verified
Journal Article
Closed access
SBSami Barmada
Sami Barmada
AMAntonino Musolino
Antonino Musolino
MRMARCO RAUGI
MARCO RAUGI
This work presents a channel model for the broadband characterization of power lines in presence of time variation of the loads. The model is characterized by taking into account both measured and geometrical channel characteristics and can easily be used to take into account also the presence of noise. The channel is described by a two-port equivalent described by a scattering matrix determined from a wavelet-based expansion of the input and output quantities. Upper and lower bounds for the response of the channel in presence of time-varying loads are determined in a fast and efficient way avoiding time consuming Monte Carlo simulations. The bounds determination allows the estimate of noteworthy quantities for the tuning of currently used modulation schemes for power lines communications such as orthogonal frequency-division multiplexing.
13 January 2020 in IEEE Transactions on Magnetics
Verified
Journal Article
Closed access
SBSami Barmada
Sami Barmada
NFNunzia Fontana
Nunzia Fontana
Luca SaniLuca Sani
Luca Sani
DTDimitri Thomopulos
Dimitri Thomopulos
MTMauro Tucci
Mauro Tucci
The computational cost of topology optimization based on binary particle swarm optimization is greatly reduced by the use of Deep Neural Networks (DNN). A first Convolutional Neural Network (CNN) is trained with data coming from Finite Element Analysis (FEA) with the aim of correctly estimating the output quantity (a motor torque in the proposed case study). A second CNN is trained to give as output the boundary conditions (BC, expressed in terms of fields or potentials) to be used as BC of a reduced Finite Element Method (FEM) model, created in order to still be able to give the correct value of the output quantity. In the optimization phase, the torque properties are evaluated by the trained CNN, and only a reduced percentage of cases are re-evaluated by either the full FEM model or the reduced FEM model. The overall computational time of the optimization procedure is significantly reduced.
1 June 2014 in IET Electrical Systems in Transportation
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Journal Article
Open access
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SBSami Barmada
Sami Barmada
MRMARCO RAUGI
MARCO RAUGI
MTMauro Tucci
Mauro Tucci
FRFrancesco Romano
Francesco Romano
Predictive Maintenance, Prognostics and Reliability Centered Maintenance approach are becoming more and more important in the railway sector to reduce costs of operation and to increase reliability and safety. In fact, these are fundamental to optimize the maintenance process, to define new measures and algorithms which locate faults, to monitor health conditions of subsystems and to estimate residual life of components. In some cases it's possible to use existing sensors and existing processing hardware to extract new information from the existing available data. It's clear that this is usually the best option because the benefit can be achieved with little or no cost at all. This paper describes the result of a study performed with the aim of detecting arcing events without the need of additional equipment mounted on board the train. A set of data relative to voltage and current collected on high speed trains along with a set of measurements coming from photosensors are available. The data are processed by the use of an advanced classification technique, Support Vector Machines, with the aim of extracting important information such as the time coordinate related to anomalies in the overhead contact line and the status of the pantograph contact strip.
21 November 2023 in Applied Soft Computing
Verified
Journal Article
Closed access
SRShaowei Rao
Shaowei Rao
GZGuoping Zou
Guoping Zou
SYShiyou Yang
Shiyou Yang
SBSami Barmada
Sami Barmada
14 June 2010 in IEEE Transactions on Vehicular Technology
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Journal Article
Closed access
SBSami Barmada
Sami Barmada
LBLisa Bellanti
Lisa Bellanti
MRMARCO RAUGI
MARCO RAUGI
MTMauro Tucci
Mauro Tucci
This paper presents a theoretical and experimental analysis on the application of power-line communication (PLC) on a cruise ship. The authors have developed an accurate model of the power grid of a ship when it is used as a PLC channel. The model is developed based on a theoretical approach and validated by a thorough measurement campaign. The accuracy of the model is addressed by a comparison between simulation results and measured data, and its use gives an insight into the performance of the power network to be used as PLC channel.
2 March 2021 in IEEE Transactions on Magnetics
Verified
Journal Article
Closed access
SBSami Barmada
Sami Barmada
NFNunzia Fontana
Nunzia Fontana
Alessandro FormisanoAlessandro Formisano
Alessandro Formisano
DTDimitri Thomopulos
Dimitri Thomopulos
MTMauro Tucci
Mauro Tucci
In this work a topology optimization procedure is proposed and applied to the TEAM 25 problem, i.e. a model of a die press with electromagnet for orientation of magnetic powder. The shape of the press is described as a free discretized profile, and its relation to the flux density in the cavity is simulated by Finite Element Analysis (FEA) and learned by a Deep Neural Network (DNN) model. The DNN is used as a surrogate model for optimization, aiming to obtain a desired flux density distribution in the cavity. Results are promising, as better accuracy is obtained with respect to full FEA-based optimization approach with reduced time cost. Once trained, surrogate model can be used to efficiently solve a whole family of problems where a different target field distribution is defined.