We study the forecast of the electrical energy demand of the N'Djamena city, Chad, by 2032 using the statistical model based on the linear regression technic. A series of data of the maximum power demand (PMA) for the past years from 2005 to 2017 are obtained from the dispatching center of the company national electricity board of N'Djamena, which allow us to make energy projection from 2018 to 2032. Then these data are analyzed by the statistical method of linear regression forecast. The results obtained by the linear regression are closed to that provided by the Excel trend curve and they have a strong linear correlation coefficient of 0.963 between the maximum powers estimated and the given years. In addition, the predicted power peak needed by electricity consumers by 2032 is 175 MW compared to 90 MW in 2017, meaning that in 15 years, the consumption of electrical energy will pass from simple to double.

The effects of masonry wall parameters on the water’s migration are deeply explored via the experimental laboratory simulation method. At this end, an experimental device consisting of a water tank in which a masonry block wall has a contact of around one centimeter with the water at its base is designed. The variation of the compactness of masonry blocks is obtained by compacting the concrete blocks with a hydraulic block press. The investigations consist of the monitoring of moisture front and moisture rate as a function of porosity, obtained by varying the compactness of the masonry wall, and the granular class of sand constituting the masonry. The determination of the granular sand classes was made from the NF P 18-101 standard. Three granular classes of sand were obtained using sand from the Logbadjeck quarry: 0/0.315 mm, 0.63/1.25 mm, and 2.5/5 mm. The obtained results show that the device is a good tool for the experimental analysis of the behavior of different masonry walls under water migration, which are in agreement with existing models in the literature.

Our study is being carried out in the Wouri Estuary more precisely in the Nylon area, Douala. This area is influenced by abundant rainfall which promotes the phenomenon of rain erosion. This erosion contributes to the degradation of structures and soils. To better understand and predict this phenomenon of rainfall erosion, we set out to establish a mathematical model that takes into account precipitation and topography. To this end, the data collected in the field and in the laboratory made it possible. First, we graphically modeled the variation of the potential as a function of the intensity of rainfall and the slope of the ground. Next, we identified a mathematical model from cubic spline surface interpolation. Finally, we obtained the mathematical model which makes it possible to evaluate and predict the erosion potential. The results obtained allowed to have an erosion potential of 153.67 t/ha/year with field data and 153.94 t/ha/year with laboratory data. We compared the results obtained with those existing in the literature on the same study site. This comparison made it possible to validate the established mathematical model. This mathematical model is a decision support tool and can predict problems related to water, erosion and the environment.