Search

This study aims to investigate the influence of the geographical and climate parameters on the performance of the hybrid solar gas turbine with a pressurized air receiver. A number of sites located in South America (Chile, Bolivia, and Peru) and North Africa (Algeria and Libya) are considered. The geometric design parameters of the solar receiver and the tower are calculated using an in-house code. The layout and the optical performance of the heliostat field are carried out using SolarPILOT software. The simulation of the complete hybrid solar gas turbine is carried out using TRNSYS software. A 50 MWe hybrid solar gas turbine is chosen in this study. Results show that a hybrid solar gas turbine installed in North Africa performs better than that installed in South America. This is mainly due to the optical performance of the heliostat field, which are better in North Africa are than in South America. The highest annual optical efficiency of a solar field is observed at Bechar (Algeria) 56.8% while the lowest annual efficiency is observed at Antofagasta (Chile) 48.1%.The solar-to-electric efficiency at Atacama Desert is lower than in the Sahara Desert. Indeed, in Atacama region the solar-to-electric efficiency varies from 17% at Antofagasta to about 18% in Arequipa while it is above 19% at Sabha and Bechar.

The mining industry is looking at the use of solar energy to address issues related to highly variable energy prices, falling ore grades, and increasing concern about the industry’s carbon footprint. The pressure oxidation of ore sulfides is an economic alternative to the smelting process because it has the potential to reduce energy consumption and treat low-grade ores. In the pressure oxidation of ore sulfides, the purity and utilization of oxygen are key factors. Indeed, oxygen production and consumption constitute the major operating cost of the pressure oxidation process. Solar thermo-chemical looping processes have been identified as one of the most efficient pathways for the production and storage of oxygen. This study investigates the integration of a solar thermo-chemical looping process with a pressure oxidation process to treat ore sulfide and produce electricity. The analysis shows that the temperature of the cold storage tank has a strong influence on the performance of the complete system. The increase in the cold tank temperature results in a sharp decrease in the size of the receiver. This reduce the investment costs for both the solar receiver and the heliostat field. For the considered case, the useful heat of the solar receiver is 3.7 MWth when the cold tank temperature is set at 100°C. If the cold tank temperature is set at 400°C, the required useful solar heat is about 3.1 MWth and the nominal output of the gas turbine is 0.56 MWe. The analysis showed that about 80% of the useful solar heat can be used to generate oxygen when the temperature of the cold tank is as high as that of the reduction reaction

El presente artículo hace referencia a toda la investigación que tiene como objetivo diseñar e implementar un prototipo clasificador de cacao usando Visión Artificial y Machine Learning. El paso inicial fue entrenar una neurona mediante Teachable Machine (Plataforma de Google) para lograr identificar acorde a las características del grano del cacao su nivel de fermentación y asimismo ignorar otros elementos inherentes al target a analizar, una vez ya entrenada la neurona se procedía al análisis en tiempo real para después llegar a la clasificación. La idea base de implementar estos tipos de conceptos en este tipo de actividades es demostrar que tan maleables pueden ser al momento de utilizarlos en áreas que aparentemente no estarían correlacionadas de manera directa con este nivel de tecnología. En cuanto al sistema será una amalgama de herramientas tanto lógicas como físicas, ya que de manera estructural estará formado por motores servos, una cinta transportadora, una cámara, un sistema de led, un sensor infrarrojo y demás; en cuanto a los recursos lógicos se usará Python como lenguaje base y se emplearán librerías como Tkinter, Numpy, Tensorflow, entre otros. The objective of this degree project is to design and implement a cocoa classifier prototype using Artificial Vision and Machine Learning using open sources resources and technologies. The initial step was to train a neuron using Teachable Machine to identify its fermentation level according to the characteristics of the cocoa bean and also ignore other elements inherent to the target to be analyzed, once the neuron was trained, the analysis was carried out in real time to then get to the classification The basic idea of implementing these types of concepts in these types of activities is to demonstrate how malleable they can be when used in areas that apparently would not be directly correlated with this level of technology. As for the system, it will be an amalgam of both logical and physical tools, since in a structural way it will be made up of servo motors, a conveyor belt, a camera, a LED system, an infrared sensor and others; in terms of logic, Python will be used as the base language and libraries such as Tkinter, Numpy, Tensorflow, among others, will be used.