This work analyse the movements and the muscular activity during motocross sessions and how a neck brace influence both. These movements are measured in terms of angles using two Biometrics (R) angular sensors (one for bi-planar flexion and one for torsion); the muscle activity is registered using four pairs of electrodes (muscle selected: Sterno-Cleido-Mastoid left and right, Trapezium left and right). From the results obtained, we can conclude that the pilot wants to focus the attention to the next jump or obstacle while accelerations of different nature are acting on the neck, therefore isometric contractions are predominant. The fact that the brace did not reduce the rotational range of motion is a positive result because the pilot field of view is not modified which is a safety requirement. According to the evidence of a fatigue effect, the brace is useful not only to protect the pilot during accidents but also as a supporting device during driving sessions

In this work, a journal bearing optimization process has been developed and is divided into two stages. Each one has a set of decision variables and custom objectives aggregating performances with a weighting strategy. The performance functions used are an artificial neural network, trained with Reynolds equation solutions, and a CFD simulation of the bearings carried out with commercial software. The results show the capabilities of the algorithm to design and optimize journal bearings by reducing both power loss and mass flow with respect to ones designed with traditional methods, as well as by minimizing the maximum and average temperature.

The scope of this work is to mathematically optimize the choice of geometrical parameters of a hydrodynamic journal bearing to maximize its performance. Despite the fact that several works have investigated methods to predict the optimal shape of this family of sliding bearings, significant opportunities remain to improve the efficiency of the algorithm through the use of validated computational fluid dynamics and intelligent stochastic algorithms to find the function's maximum and minimum. This work presents a set of experiments carried out to validate simulations of fluid film bearings. These virtual models are used to determine the temperatures inside the bearing film. A series of objective functions were built and minimized in order to maximize the performance of the bearing and obtain the optimal combination of geometrical parameters for the design. The paper shows the capabilities of the algorithm to improve an existing journal bearing design as well as the validation data of the CFD simulations.