Analysis of a metallic pedestrian bridge under dynamic human loads in pre and post reinforcement phases

The purpose of this work is to study the dynamic behavior of a pedestrian bridge in Alicante, Spain. It is a very slender footbridge with vertical and horizontal vibration problems during the passage of pedestrians. Accelerations have been recorded by accelerometers installed at various locations of the bridge. Two scenarios, in free vibration (after the passage of a certain number of pedestrians on the bridge) and forced vibration produced by a fixed number of pedestrians walking on the bridge at a certain speed and frequency. In each test, the effect on the comfort of the pedestrians, the natural frequencies of vibration, the mode shapes and damping factors have been estimated. It has been found that the acceleration levels are much higher than the allowable by the Spanish standards and this should be considered in the restoration of the footbridge.

A parallel method for impulsive image noise removal on hybrid CPU/GPU systems

A parallel algorithm for image noise removal is proposed. The algorithm is based on peer group concept and uses a fuzzy metric. An optimization study on the use of the CUDA platform to remove impulsive noise using this algorithm is presented. Moreover, an implementation of the algorithm on multi-core platforms using OpenMP is presented. Performance is evaluated in terms of execution time and a comparison of the implementation parallelised in multi-core, GPUs and the combination of both is conducted. A performance analysis with large images is conducted in order to identify the amount of pixels to allocate in the CPU and GPU. The observed time shows that both devices must have work to do, leaving the most to the GPU. Results show that parallel implementations of denoising filters on GPUs and multi-cores are very advisable, and they open the door to use such algorithms for real-time processing.