Polytechnic University of Catalonia

About: Polytechnic University of Catalonia is a education organization based out in Barcelona, Spain. It is known for research contribution in the topics: Finite element method & Population. The organization has 16006 authors who have published 45325 publications receiving 949306 citations. The organization is also known as: UPC - BarcelonaTECH & Technical University of Catalonia.

Monte Carlo convolution for learning on non-uniformly sampled point clouds

Abstract: Deep learning systems extensively use convolution operations to process input data. Though convolution is clearly defined for structured data such as 2D images or 3D volumes, this is not true for other data types such as sparse point clouds. Previous techniques have developed approximations to convolutions for restricted conditions. Unfortunately, their applicability is limited and cannot be used for general point clouds. We propose an efficient and effective method to learn convolutions for non-uniformly sampled point clouds, as they are obtained with modern acquisition techniques. Learning is enabled by four key novelties: first, representing the convolution kernel itself as a multilayer perceptron; second, phrasing convolution as a Monte Carlo integration problem, third, using this notion to combine information from multiple samplings at different levels; and fourth using Poisson disk sampling as a scalable means of hierarchical point cloud learning. The key idea across all these contributions is to guarantee adequate consideration of the underlying non-uniform sample distribution function from a Monte Carlo perspective. To make the proposed concepts applicable to real-world tasks, we furthermore propose an efficient implementation which significantly reduces the GPU memory required during the training process. By employing our method in hierarchical network architectures we can outperform most of the state-of-the-art networks on established point cloud segmentation, classification and normal estimation benchmarks. Furthermore, in contrast to most existing approaches, we also demonstrate the robustness of our method with respect to sampling variations, even when training with uniformly sampled data only. To support the direct application of these concepts, we provide a ready-to-use TensorFlow implementation of these layers at https://github.com/viscom-ulm/MCCNN.

Comparison of dose calculation algorithms in phantoms with lung equivalent heterogeneities under conditions of lateral electronic disequilibrium.

Abstract: An extensive set of benchmark measurement of PDDs and beam profiles was performed in a heterogeneous layer phantom, including a lung equivalent heterogeneity, by means of several detectors and compared against the predicted dose values by different calculation algorithms in two treatment planning systems. PDDs were measured with TLDs, plane parallel and cylindrical ionization chambers and beam profiles with films. Additionally, Monte Carlo simulations by means of the PENELOPE code were performed. Four different field sizes (10 x 10, 5 x 5, 2 x 2, and 1 x 1 cm2) and two lung equivalent materials (CIRS, p(w)e=0.195 and St. Bartholomew Hospital, London, p(w)e=0.244-0.322) were studied. The performance of four correction-based algorithms and one based on convolution-superposition was analyzed. The correction-based algorithms were the Batho, the Modified Batho, and the Equivalent TAR implemented in the Cadplan (Varian) treatment planning system and the TMS Pencil Beam from the Helax-TMS (Nucletron) treatment planning system. The convolution-superposition algorithm was the Collapsed Cone implemented in the Helax-TMS. The only studied calculation methods that correlated successfully with the measured values with a 2% average inside all media were the Collapsed Cone and the Monte Carlo simulation. The biggest difference between the predicted and the delivered dose in the beam axis was found for the EqTAR algorithm inside the CIRS lung equivalent material in a 2 x 2 cm2 18 MV x-ray beam. In these conditions, average and maximum difference against the TLD measurements were 32% and 39%, respectively. In the water equivalent part of the phantom every algorithm correctly predicted the dose (within 2%) everywhere except very close to the interfaces where differences up to 24% were found for 2 x 2 cm2 18 MV photon beams. Consistent values were found between the reference detector (ionization chamber in water and TLD in lung) and Monte Carlo simulations, yielding minimal differences (0.4%+/-1.2%). The penumbra broadening effect in low density media was not predicted by any of the correction-based algorithms, and the only one that matched the experimental values and the Monte Carlo simulations within the estimated uncertainties was the Collapsed Cone Algorithm.

Micromechanical analysis of quasi-brittle materials using fracture-based interface elements

Abstract: A microstructural model for the mechanical behaviour of quasi-brittle materials is developed and verified for concrete and bone specimens. The model is based on interface elements equipped with a constitutive law representing non-linear fracture, while continuum elements remain linear elastic. The interface constitutive model is implemented with a sub-stepping scheme. Non-linear geometric effects due to large displacements are included in the model by means of an incremental Lagrangian formulation, although strains in the continuum and relative displacements in the interfaces are assumed to remain small. An arc-length procedure is used to ensure convergence during the highly non-linear behaviour in the post-peak regime. Concrete and bone specimens are idealized as two-phase particle composites and are discretized into finite elements, including interface elements along the main potential crack paths. The numerical results in tension and compression are described and compared with experimental observations. The need of considering non-linear geometric effects in this type of calculations is also discussed. Copyright © 2001 John Wiley & Sons, Ltd.