This paper introduces a numerical methodology for classifying and identifying types of bio-based materials through experimental thermal characterization. In contrast to prevailing approaches that primarily focus on thermal conductivity, our characterization methodology encompasses several thermal parameters. In this paper, the physical characteristics of seven types of bio-based concrete were analyzed, focusing on the thermal properties of palm- and esparto-fiber-reinforced concrete. The proposed method uses artificial intelligence techniques, specifically the k-means clustering approach, to segregate data into homogeneous groups with shared thermal characteristics. This enables the elucidation of insights and recommendations regarding the utilization of bio-based insulation in building applications. The results show that the k-means algorithm is able to efficiently classify the reference concrete (RC) with a performance of up to 71%. Additionally, the technique is more accurate when retaining only six centroids, which, among other things, allows all the characteristics associated with each type of concrete to be grouped and identified. Indeed, whether for k clusters k = 7 or k = 5, the technique was not able to predict the typical characteristics of 2% or 3% esparto concrete (EC).

The objective of this work lies in the three-dimensional study of the thermo mechanical behavior of a blade of a centrifugal compressor. Numerical modeling is performed on the computational code "ABAQUS" based on the finite element method. The aim is to study the impact of the change of types of blades, which are defined as a function of wheel output angle β ₂ , on the stress fields and displacements coupled with the variation of the temperature. This coupling defines in a realistic way the thermo mechanical behavior of the blade where one can note the important concentrations of stresses and displacements in the different zones of its complex form as well as the effects at the edges. It will then be possible to prevent damage and cracks in the blades of the centrifugal compressor leading to its failure which can be caused by the thermal or mechanical fatigue of the material with which the wheel is manufactured.

This work defined the development of a model for thin-film drying of tomatoes using an indi-rect solar dryer. Drying experiments were carried out and the drying model was approximated by a simplified model determined by the measurements collected during the experiments, in particular, the measurement of the relative humidity of the tomato during two days of drying coupled with the thermal behaviour of the drying device in free convection. The results show that with good measurements, it is possible to approximate the drying characteristic curve by a linear model with very high statistical performance indicators. The experiments also show that depending on the drying process adopted, the water behaviour of the tomato can change. In addition, the thin-film drying model adopted made it possible to assess the solar drying kinetics of the tomato variety studied. The results obtained finally show that the dryness of the tomato is reached after about 14 hours of drying. The drying temperature reaches an average of 80°C, and the final product water content after the optimal drying time is about 0.40 kg.water/kg.ms on a dry basis. At the end of this study, we concluded that the drying air temperature represents the most important parameter affecting the drying kinetics. The very good agreement between the experimental and numerical results obtained shows that the theoretical model and assumptions used are acceptable, and that our calculation model is reliable.

Evaluating the structural, optoelectronic, and photovoltaic performance of the Cu₂SnS₃ compound is essential for the development of materials for solar energy. This ternary chalcogenide semiconductor stands out for its strong potential in photovoltaic applications, thanks to its broad light-absorbing range and chemical stability. In this paper, we have examined the structural and optoelectronic properties of copper-based ternary semiconductors, specifically those in the Cu₂SnS₃ compound, and their effectiveness in photovoltaic applications. Since there is significant variation in previous studies on the band gap values (0.65-1.35 eV), an attempt was made to find an appropriate approximation for studying this type of compound. The structural properties were investigated using both the Perdew-Burke-Ernzerhof (PBE) form of the generalized gradient approximation (GGA) and the local density approximation (LDA), allowing a comparative assessment of the effects of different exchange-correlation functionals on the material’s structure. Given the important influence that Cu delectrons play in determining their electronic properties, as shown by the results obtained when using different exchange correlation energy functionals. The combined function of the Becke-Johnson potential, modified by Tran and Blaha, and the Hubbard potential (TB-mBJ+U) was employed to systematically optimize the calculated anion displacement. The calculations yielded the band gap values. The semiconductor quasiparticle is 0.7 eV in the monoclinic structure (m-CTS; SG: Cc), and that of the orthorhombic structure (gold-CTS; SG: Imm2) is 0.73 eV, which is largely consistent with experimental values. The study of optical properties, including the dielectric function, also revealed the reflectance, absorption coefficient, and refractive index of the Cu₂SnS₃ compound in its two phases. The latter is considered a promising candidate in optoelectronic applications. To verify this, we used the SCAPS program, and the results were good. When this compound is used as an absorbent layer in a photovoltaic cell, the current density (Jsc) increases, peaking at a thickness of 800 nm.