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The modern approach of Virtual Engineering allows one to detect with some accuracy the residual life of components especially free of cracks. The life estimation becomes cumbersome when the components contain a crack. A straightforward formulation requires a parameter that considers geometrical constraints and materials properties. The magnitude of the stress singularity developed by the tip of a crack, needs to be expressed by the Stress Intensity Factors (SIF). In order to prove the validity of the results, calibration by experimental and/or analytical technique is required. To have a better understanding of this parameter, in the first part of this paper an analytical model to compute the SIF connected to crack propagation into Mode I has been implemented. The case study displays a pipeline component with a crack defect submitted to internal pressure. Therefore, an appropriate correlation between the analytical approach and numerical simulation has been established embedded.

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Photovoltaic (PV) solar energy enables direct production of electricity. The photovoltaic effect produced in the solar cells converts light energy from the sun's rays into electricity. Some of the solar radiation absorbed by a PV module is not converted into electricity but takes the form of an increase in the temperature of the module, reducing its electrical efficiency. The operating temperature of PV modules generally affects the performance of the PV system; performance also depends on numerous variables such as ambient temperature, wind speed, wind direction, total irradiance, dust accumulating on the PV module face and relative humidity. In this study different models for predicting the operating temperature of PV modules have been investigated. The models' relevance to PV module technology and climatic conditions in Errachidia city (coordinates: 31 55 0 55 00 north, 4 25 0 28 00 west) in the Drâa Tafilalet region was examined. The models that factor in wind data predict PV cell temperature better than the standard approach which does not include wind data. The models' accuracy was estimated based on R 2 and RMSE values. A model is more accurate the higher the R 2 is and the lower the RMSE is. In addition, we noticed that the models investigated are more accurate for a short time period during the day.

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