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To understand patterns of genetic and morphological variability, population structure and dispersal dynamics of the invasive bivalve Pinctada imbricata radiata (Leach, 1814) in Tunisian waters, we ...

Piezoelectric nanogenerator are attracting a lot of attention due to environmental constraints and the ecological considerations of energy collection. A piezoelectric nanocomposite based on Ba 0.85 Ca 0.15 Zr 0.1 Ti 0.9 O 3 (BCZT) nanoparticles and PDMS polymer with excellent output properties for the application of nanogenerators has been developed. The piezoelectric nanogenerator is smart device that offers these required qualities and properties and converts mechanical energy. Here PENG can generate an open circuit voltage of 10 V respectively under the effect of light finger tapping. It reaches an output power of $\mathrm{P}=2.218\ \mu\mathrm{W}$ for a resistance $\mathrm{R}=370\ \mathrm{k}\Omega$ under shaker vibration. This generator is known by its simple and ordinary design as well its high performance after polarization. However, the polarization is long and unsafe. To avoid this problem, a homogeneous distribution of carbon nanotubes (CNTs) on the BCZT/PDMS matrix is the best solution to have self-polarized generator. In this study, piezoelectric nanocomposites were prepared using solution mixing method. A comparative study was performed to investigate the impact of CNTs on the performance of nanogenrators under external mechanical load. The nanogenerator with 15 wt.% BCZT doped with CNTs offers an outstanding output performance with an open circuit voltage of 15 V and an output power $\mathrm{P}=5.68029\ \mu\mathrm{W}$ at a resistance load $\mathrm{R}=350\ \mathrm{k}\Omega$ using the shaker device.

The modeling of mechatronic systems requires the collaboration of several professions such as systems architect, safety expert, mechanical engineer and electronic engineer. Thus, various complex system models using different modeling languages are provided. This paper presents a verification and validation approach that aims to assure the structural consistency between such models. First, the system representations using SysML, AltaRica and Modelica languages for systems engineering, safety analysis and multi-physics respectively, are transformed into labeled and directed multi-graphs. Then, these graphs will be compared for equivalence by using different graph concepts such as isomorphism, subgraph, number of system inputs and outputs, etc. This method allows to synchronize models into one single representation respecting all specifications inherent to each modeling language. Furthermore, inconsistencies are identified when passing from one model to another and feedbacks will be given to each domain expert for validation. A case study from an aeronautical system is used throughout the paper to illustrate our approach.