Recent Additions
- Some of the metrics are blocked by yourconsent settings
Publication Vacuum material properties and Cherenkov radiation in logarithmic electrodynamics(Springer Science and Business Media LLC, 2023-02-01)We study some observational signatures of nonlinearities of the electromagnetic field. First to all we show the vital role played by nonlinearities in triggering a material behavior of the vacuum with (ε > 0,μ < 0), which corresponds to a ferrimagnetic material. Secondly, the permittivity and susceptibility induced by nonlinearities are considered in order to obtain the refractive index via the dispersion relation for logarithmic electrodynamics. Finally, we consider the electromagnetic radiation produced by a moving charged particle interacting with a medium characterized by nonlinearities of the electromagnetic field. To this end we consider logarithmic electrodynamics. The result shows that the radiation is driven by the medium through which the particle travels like the one that happens in the Cherenkov effect. - Some of the metrics are blocked by yourconsent settings
Publication Artificial neural network (ANN) modelling to estimate bubble size from macroscopic image and object features(2023-01-01)Bubble size measurements in aerated systems such as froth flotation cells are critical for controlling gas dispersion. Commonly, bubbles are measured by obtaining representative photographs, which are then analyzed using segmentation and identification software tools. Recent developments have focused on enhancing these segmentation tools. However, the main challenges around complex bubble cluster segmentation remain unresolved, while the tools to tackle these challenges have become increasingly complex and computationally expensive. In this work, we propose an alternative solution, circumventing the need for image segmentation and bubble identification. An Artificial Neural Network (ANN) was trained to estimate the Sauter mean bubble size (D<sub>32</sub>) based on macroscopic image features obtained with simple and inexpensive image analysis. The results showed excellent prediction accuracy, with a correlation coefficient, R, over 0.998 in the testing stage, and without bias in its error distribution. This machine learning tool paves the way for robust and fast estimation of bubble size under complex bubble images, without the need of image segmentation. - Some of the metrics are blocked by yourconsent settings
Publication Development and Control of a Real Spherical Robot(MDPI AG, 2023-04-01)This paper presents the design and implementation of a spherical robot with an internal mechanism based on a pendulum. The design is based on significant improvements made, including an electronics upgrade, to a previous robot prototype developed in our laboratory. Such modifications do not significantly impact its corresponding simulation model previously developed in CoppeliaSim, so it can be used with minor modifications. The robot is incorporated into a real test platform designed and built for this purpose. As part of the incorporation of the robot into the platform, software codes are made to detect its position and orientation, using the system SwisTrack, to control its position and speed. This implementation allows successful testing of control algorithms previously developed by the authors for other robots such as Villela, the Integral Proportional Controller, and Reinforcement Learning. - Some of the metrics are blocked by yourconsent settings
Publication Residence Time Distribution Measurements and Modeling in an Industrial-Scale Siemens Flotation Cell(2023-05-01)This short communication presents residence time distribution (RTD) measurements and modeling in a 16 m3 Siemens flotation cell, as the first RTD characterization in an industrial-scale pneumatic cell. The Siemens cell was installed as a pre-rougher machine in a Cu-Mo selective plant. This plant recovered molybdenite as an enriched product, depressing copper-bearing minerals. Irradiated non-floatable solid and Br82 in water solution were employed as solid and liquid tracers, respectively. The tracers were instantly injected into the Siemens cell, and the inlet and outlet concentrations were directly measured by external non-invasive detectors. From the flotation literature, three model structures for the RTDs were evaluated, including perfect mixing, one large perfect mixer and one small perfect mixer in series (LSTS), and N perfectly mixed reactors in series. A transport delay was incorporated for all models. The LSTS representation was more consistent with the experimental data, showing that the Siemens cell RTDs presented significant deviations with respect to perfect mixing and plug-flow regimes. From the industrial measurements, mean residence times of 4.1–5.2 min were estimated. - Some of the metrics are blocked by yourconsent settings
Publication The Role of Stereological Assumptions in Bubble Size Estimations and Their Implications for Assessing Critical Coalescence Concentrations(2023-06-01)Accurate measurement of bubble size is critical for assessing flotation performance. However, the 3D nature of bubbles, in contrast to the 2D nature of photographs obtained using a bubble viewer apparatus, may lead to distortions related to stereological assumptions. This study aimed to quantify the impact of these stereological effects on bubble size measurements in frother characterisations. Our results showed that different assumptions regarding bubble shape and volume resulted in variations in bubble size calculations of up to 10%. Furthermore, these stereological effects were propagated to the calculation of the critical coalescence concentration, leading to uncertainties of up to 14% depending on the type of frother. These findings emphasise the importance of considering stereological effects and selecting an appropriate calculation method when measuring bubble size for flotation and reagent assessments.
Most viewed
- Some of the metrics are blocked by yourconsent settings
Publication - Some of the metrics are blocked by yourconsent settings
Publication Theoretical and numerical comparison of first order algorithms for cocoercive equations and smooth convex optimization(2023-05-01)This paper provides a theoretical and numerical comparison of classical first-order splitting methods for solving smooth convex optimization problems and cocoercive equations. From a theoretical point of view, we compare convergence rates of gradient descent, forward-backward, Peaceman-Rachford, and Douglas-Rachford algorithms for minimizing the sum of two smooth convex functions when one of them is strongly convex. A similar comparison is given in the more general cocoercive setting under the presence of strong monotonicity and we observe that the convergence rates in optimization are strictly better than the corresponding rates for cocoercive equations for some algorithms. We obtain improved rates with respect to the literature in several instances by exploiting the structure of our problems. Moreover, we indicate which algorithm has the smallest convergence rate depending on strong convexity and cocoercive parameters. From a numerical point of view, we verify our theoretical results by implementing and comparing previous algorithms in well established signal and image inverse problems involving sparsity. We replace the widely used ℓ1 norm with the Huber loss and we observe that fully proximal-based strategies have numerical and theoretical advantages with respect to methods using gradient steps. - Some of the metrics are blocked by yourconsent settings
Thesis Arquitectura orientada a eventos para redes de sensores aplicada a control de tráfico(Universidad Técnica Federico Santa María, 2017-01)Las arquitecturas dirigidas por eventos (EDA) comenzaron a desarrollarse a principios de este siglo y tomaron fuerza este último tiempo. En la búsqueda de una nueva propuesta en el ámbito de procesamiento de eventos complejos (CEP), este documento presenta una prueba de escalabilidad entre una arquitectura orientada a eventos y una tradicional utilizando datos sintéticos. Finalmente, se diseñó e implementó un prototipo orientado a eventos utilizando datos reales bajo una simulación trace-driven con el fin de procesar eventos en tiempo real y reconocer patrones complejos generando alarmas ante anomalías detectadas. Del presente estudio, se obtuvo que EDA se comporta de mejor forma que una arquitectura tradicional para sistemas basados en sensores. Además, el prototipo implementado para CEP fue capaz de procesar eventos y detectar anomalías en tiempo real sin acceder a una base de datos históricos. - Some of the metrics are blocked by yourconsent settings
Publication Modeling the influence of COVID-19 protective measures on the mechanics of phonation(2022-05-01)In an effort to mitigate the 2019 novel coronavirus disease pandemic, mask wearing and social distancing have become standard practices. While effective in fighting the spread of the virus, these protective measures have been shown to deteriorate speech perception and sound intensity, which necessitates speaking louder to compensate. The goal of this paper is to investigate via numerical simulations how compensating for mask wearing and social distancing affects measures associated with vocal health. A three-mass body-cover model of the vocal folds (VFs) coupled with the sub- and supraglottal acoustic tracts is modified to incorporate mask and distance dependent acoustic pressure models. The results indicate that sustaining target levels of intelligibility and/or sound intensity while using these protective measures may necessitate increased subglottal pressure, leading to higher VF collision and, thus, potentially inducing a state of vocal hyperfunction, a progenitor to voice pathologies. - Some of the metrics are blocked by yourconsent settings
Thesis On CFTs and conformal techniques in AdS(Universidad Técnica Federico Santa María, 2016-11)Conformal symmetry is a fundamental tool in the study of string theory, critical phenomena, and interacting quantum field theories. This doctoral thesis focuses on conformal methods applied to two main areas: Type IIB superstring theory in an AdS5 x S5 background, and four-dimensional N = 2 supersymmetric field theories. In the case of N = 2 theories, we take an initial step toward computing superconformal blocks for mixed operators. For chiral and real half-BPS operators, these blocks can be constructed using chiral or harmonic superspace techniques. However, no general method exists for more complex multiplets. This work presents a procedure to compute operator product expansions (OPE) involving an N = 2 stress-tensor multiplet, a chiral multiplet, and a flavor current multiplet using superspace techniques. A general bound for the central charge of interacting theories is also derived. On the string theory side, a systematic method is proposed to compute logarithmic divergences of composite operators in the pure spinor formalism of the AdS5 x S5 superstring. These divergences are described in terms of a dilatation operator acting on local operators. The results are verified using key composite operators in the formalism. Finally, the pure spinor AdS string is constructed using supertwistor techniques.
