UFSCar has an enrollment of approximately 16,000 students and 1,000 professors and researchers. Its researchers are Brazil’s the fourth most productive in terms of articles published in indexed international journals of science. It is highlighted by the high qualifications of its teaching staff: 99.9% are PhDs or Masters.
UFSCar offers 57 undergraduate degrees and 57 graduate degrees. According to the last CAPES evaluation of the Brazilian Graduate System, more than half of all of UFSCar’s Graduate Programs were considered nationally or internationally excellent. Among those programs are special education, physiotherapy, psychology and sociology.
The University has three campuses. The main campus, in São Carlos, is located 234 kilometers (145 mi) from the capital, and occupies 645 hectares (1,590 acres). Approximately 94 kilometers (58 mi) from São Carlos is the 230 hectares (570 acres) Araras campus, containing the agricultural engineer centre, with research in the Biotechnology area. In 2005, the Sorocaba campus opened and offers 14 undergrad 5 graduate courses. In November, 2010, the University Council approved the creation of the rural campus Lagoa do Sino in a 643 hectares (1,590 acres) farm donated by writer Raduan Nassar. It will be a campus focused on courses about food security, family agriculture, and sustainable development.
The university hosts more than 321 laboratories, a community library, 2 theaters, 3 amphitheaters, 3 auditoriums, a sports gym, a sport park with 8 courts and 2 pools, 2 university restaurants, 5 snack bars and 129 classrooms.
The 33 academic departments are divided in four centers: Biological Sciences and Health Center (Centro de Ciências Biológicas e da Saúde, CCBS), Exact Sciences and Technology Center (Centro de Ciências Exatas e de Tecnologia, CCET), Education and Humans Sciences Center (Centro de Educação e Ciências Humanas, CECH) and Agrarian Sciences Center (Centro de Ciências Agrárias, CCA)
A research group of the UPV/EHU-University of the Basque Country has made progress in obtaining bio-oils and raw materials from biomass using its patented reactor
The UPV/EHU’s Catalytic Processes for Waste Valorisation research group is working on various lines of research relating to renewable energies, one of which corresponds to the obtaining of bio-oils or synthetic petroleum using biomass. In a paper recently published in the scientific journal Fuel, the researchers have proposed using artificial neural networks to determine the heating power of each type of biomass using its composition as it is a highly irregular material.
Biomass is one of the main sources of energy and heat in the field of renewable energy production: it is any type of non-fossil organic matter, such as living plants, timber, agricultural and livestock waste, wastewater, solid urban organic waste, etc. The three most developed technologies for obtaining energy from biomass are as follows: pyrolysis (decomposition by heating in the absence of oxygen), gasification (reaction with air, oxygen or a blend of both and conversion into gas) and combustion (decomposition through heating with oxygen). The effectiveness and emission levels of these three processes change depending on the composition of the biomass as well as its properties, the experimental conditions and equipment used.
In collaboration with researchers at the University of Sao Carlos in Brazil and within the framework of a European project, members of the UPV/EHU’s Catalytic Processes for Waste Valorisation research group analysed the process to set up a refinery to obtain bio-oils or synthetic petroleum using biomass. Since “afterwards, using the bio-oil produced it is possible to obtain the same products that are obtained from petroleum; hydrogen as well as any other compound,” explained Martin Olazar, project leader and professor of the Department of Chemical Engineering. The reactor developed and patented by this research group, the conical spouted bed reactor, is highly suited to this process because it is suitable for handling irregular, sticky materials —biomass is a highly irregular material and difficult to handle using conventional technologies—.
Artificial neural networks to determine gross calorific value
In the design of the process to obtain bio-oils using biomass, certain variables need to be determined: the temperature that needs to be achieved, how this temperature is to be achieved, how much fuel (in this case how much biomass) needs to be burnt, etc. The gross calorific value is a key parameter in determining all these data: it is the heat (energy) that is released when a certain quantity of fuel is completely burnt. This parameter is essential in the analysis, design and improvement in biomass pyrolysis, gasification and combustion systems. The correlations existing in the literature give highly variable results depending on each type of biomass and its properties. So the researchers in the group are proposing that artificial neural networks be used to calculate this; they have proven empirically that the system gives very good results and they have reported on them in a paper recently published in the scientific journal Fuel.