Machine learning for the prediction of the local skin friction factors and Nusselt numbers in turbulent flows past rough surfaces

Turbulent flows past rough surfaces can create substantial energy losses in engineering equipment. During the last decades, developing accurate correlations to predict the thermal and hydrodynamic behavior of rough surfaces has proven to be a difficult challenge. In this work, we investigate the applicability of convolutional neural networks...

Machine learning for the prediction of the local drag forces and heat transfer rates in turbulent flows past rough surfaces

Turbulent flows past rough surfaces can create substantial energy losses in engineering equipment. During the last decades, developing accurate correlations to predict the thermal and hydrodynamic behavior of rough surfaces has proven to be a difficult challenge. In this work, we develop a convolutional neural network architecture to perform...

The influence of inter-laminar thermal contact resistance on the cooling of material during laser assisted fiber placement

The effect of thermal contact resistance (TCR) correlated to the degree of intimate contact (DIC) between the incoming tape and the substrate on the temperature history during laser-assisted fiber placement (LAFP) was investigated. A novel experimental methodology was designed to understand the effect with a non-contact method which did not...

The influence of thermal contact resistance on the thermal history in laser-assisted fiber placement

The temperature history during the laser assisted fiber placement (LAFP) process is very important since it significantly influences the final quality of the structure. Air pockets between subsequent plies, caused by the lack of intimate contact, act as insulators and reduce the through-thickness heat transfer. This phenomenon is commonly...