Examinando por Autor "Sanz, Antonio"

Mostrando 1 - 3 de 3

Monitoring Volcanic and Tectonic Sandbox Analogue Models Using the Kinect v2 sensor
(Earth and Space Science, 2022-06-01) Rincón, Marta; Marquez, A; Herrera, R; Galland, O; Sanchez-Oro, Jesús; Concha, David; Sanz, Antonio
The measurement of surface deformation in analogue models of volcanic and tectonic processes is an area in continuous development. Properly quantifying topography change in analogue models is key for a useful comparison between experiment results and nature. The aim of this work is to evaluate the capabilities of the simple and cheap Microsoft® Kinect v2 sensor for monitoring analogue models made of granular materials. Microsoft® Kinect v2 is a video-gaming RedGreenBlue-Depth device combining an optical camera and an infrared distance measurement sensor. The precision of the device for model topography measurements has been quantified using 64 experiments, with variable granular materials materials and distance to the model. Additionally, we tested the capabilities of averaging several distance images to increase the precision. We have developed a specific software to facilitate the acquisition and processing of the Kinect v2 data in experiment monitoring. Our results show that measurement precision is material dependent: with clear-colored and fine-grained materials, a precision ∼1.0 mm for digital elevation models with a 1.6 mm pixel size can be obtained. We show that by averaging ≥5 consecutive images the distance precision can reach values as low as 0.5 mm. To show the Kinect v2 capabilities, we present monitoring results from case study experiments modeling tectonics and volcano deformation. The Kinect v2 achieves lower spatial resolutions and precision than more sophisticated techniques such as photogrammetry. However, Kinect v2 provides a cheap, straightforward and powerful tool for monitoring the topography changes in sandbox analogue models.
Optimization and parallelization of the discrete ordinate method for radiation transport simulation in OpenFOAM: Hierarchical combination of shared and distributed memory approaches
(Open Research Europe, 2021-01-01) Marugán, J; Moreno-Sansegundo, José Ángel; Casado, Cintia; Concha, David; Sanz, Antonio
This paper describes the reduction in memory and computational time for the simulation of complex radiation transport problems with the discrete ordinate method (DOM) model in the open-source computational fluid dynamics platform OpenFOAM. Finite volume models require storage of vector variables in each spatial cell; DOM introduces two additional discretizations, in direction and wavelength, making memory a limiting factor. Using specific classes for radiation sources data, changing the store of fluxes and other minor changes allowed a reduction of 75% in memory requirements. Besides, a hierarchical parallelization was developed, where each node of the standard parallelization uses several computing threads, allowing higher speed and scalability of the problem. This architecture, combined with optimization of some parts of the code, allowed a global speedup of x15. This relevant reduction in time and memory of radiation transport opens a new horizon of applications previously unaffordable.
Performance evaluation of a 3D multi-view-based particle filter for visual object tracking using GPUs and multicore CPUs
(Journal of Real-Time Image Processing, 2018-08-01) Concha, David; Cabido, Raúl; Pantrigo, Juan José; Sanz, Antonio
This paper presents a deep and extensive performance analysis of the particle filter (PF) algorithm for a very compute intensive 3D multi-view visual tracking problem. We compare different implementations and parameter settings of the PF algorithm in a CPU platform taking advantage of the multithreading capabilities of the modern processors and a graphics processing unit (GPU) platform using NVIDIA CUDA computing environment as developing framework. We extend our experimental study to each individual stage of the PF algorithm, and evaluate the quality versus performance trade-off among different ways to design these stages. We have observed that the GPU platform performs better than the multithreaded CPU platform when handling a large number of particles, but we also demonstrate that hybrid CPU/GPU implementations can run almost as fast as only GPU solutions.