Microencapsulação de oleoresina de cúrcuma (curcuma longa l.) em misturas de goma arábica, maltodextrina e amido modificado

Pós-graduação em Engenharia e Ciência de Alimentos - IBILCE

A influência do processo de cura nas propriedades do compósito estrutural carbono/epóxi fabricado via VARTM: processamento e caracterização

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Desenvolvimento e caracterização de compósito processados por RTM para aplicação aeroespacial

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Quantificação do ácido lático na fermentação etanólica como parâmetro de monitoramento do processo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Caracterização estrutural e propriedades óticas e mecânicas do diglime polimerizado a plasma

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudo do processo de implantação iônica por imersão em plasma com campo magnético externo usando técnicas numéricas e experimentais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Espumas cerâmicas produzidas pela conjugação dos processos sol-gel, aeração e emulsificação

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Aplicação de redes NeuroFuzzy ao processamento de peças automotivas por meio de injeção de polímeros

The injection molding of automotive parts is a complex process due to the many non-linear and multivariable phenomena that occur simultaneously. Commercial software applications exist for modeling the parameters of polymer injection but can be prohibitively expensive. It is possible to identify these parameters analytically, but applying classical theories of transport phenomena requires accurate information about the injection machine, product geometry, and process parameters. However, neurofuzzy networks, which achieve a synergy by combining the learning capabilities of an artificial neural network with a fuzzy set's inference mechanism, have shown success in this field. The purpose of this paper was to use a multilayer perceptron artificial neural network and a radial basis function artificial neural network combined with fuzzy sets to produce an inference mechanism that could predict injection mold cycle times. The results confirmed neurofuzzy networks as an effective alternative to solving such problems.

Effects of processing on physical properties of extruded snacks with blends of sour cassava starch and flaxseed flour

The opportunity to supplement common cassava biscuits with a product of higher nutritional value meets consumer expectations. In this work it was studied the effects of process parameters and flaxseed addition on physical properties of expanded snacks. Extrusion process was carried out using a single screw extruder in a factorial central composite rotatable design with four factors: flaxseed flour percentage (0-20%), moisture (12-20%), extrusion temperature (90-130 °C) and screw speed (190-270). The effect of extrusion variables was investigated in terms of expansion index, specific volume, water absorption index, water solubility index, color parameters (L*, a* ,b*) and hardness. The data analysis showed that variable parameters of the extrusion process and flaxseed flour affected physical properties of puffed snacks. Among the experimental conditions used in the present study, expanded snack products with good physical properties can be obtained under the conditions of 10% flaxseed flour, 230 rpm screw speed, temperature of 90 °C and moisture of 12%.

Experimental RTM manufacturing analysis of carbon/epoxy composites for aerospace application

The success of manufacturing composite parts by liquid composite molding processes with RTM depends on tool designs, efficient heat system, a controlled injection pressure, a stabilized vacuum system, besides of a suitable study of the preform lay-up and the resin system choice. This paper reports how to assemble a RTM system in a laboratory scale by specifying heat, injection and vacuum system. The design and mold material were outlined by pointing out its advantages and disadvantages. Four different carbon fiber fabrics were used for testing the RTM system. The injection pressure was analyzed regarding fiber volume content, preform compression and permeability, showing how these factors can affect the process parameters. The glass transition temperature (Tg) around 203 ºC matched with the aimed temperature of the mold which ensured good distribution of the heat throughout the upper and lower mold length. The void volume fraction in a range of 2% confirmed the appropriate RTM system and parameters choice.

Síntese, caracterização estrutural e análise do potencial catalítico do SrTiO3 e das Perovskitas duplas de Sr1-xKxTiCux/2O3, onde x = 0,2; 0,3 e 0,5, na preparação de biodiesel

Pós-graduação em Química - IBILCE

Extrusion of blends of cassava leaves and cassava flour: physical characteristics of extrudates

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Usinabilidade do aço DIN C45 trefilado de alta resistência

Pós-graduação em Engenharia Mecânica - FEG

Obtenção e caracterização de nanoestruturas puras e dopadas a base de 'TI''O'IND.2' para a aplicação em fotocatálise

Pós-graduação em Química - IQ

Desidratação de polpa de manga em leito de espuma com e sem intermitência térmica

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)