Modeling and Optimization of Chemical Processes Lab

The Modeling and Optimization of Chemical Process Laboratory is located at Federal University of Uberlândia, Santa Mônica Campus, Bloco 5K.

Tel: +55 34 3239-4561

Coordinador: Luís Cláudio Oliveira Lopes

Dryer Modeling and Simulation

Modeling and simulation of different dryers configuration: fixed bed, sliding bed, concurrent and countercurrent flow, and cross-flow.

Modeling and Simulation of Fermentation Process with Immobilized Cells

Fermenters development and analysis for both free and immobilized cells operation have a great potential to increase the bioprocess activities. This project aims to offer technological alternatives for bioprocess evaluating efficiency, operational stability, and tests based on conceptual and identified models such as strategic control and optimization.

Modeling and simulation of Fruits, Grains, and Fertilizers Drying Process in Different Dryers

This line of research considers the modeling and simulation of fruits, grains, and fertilizers drying process in fixed-bed dryer; sliding bed dryer; concurrent, countercurrent, and cross-flow modes, hybrid configuration, and rotary dryer. Phenomenological mathematical models are used to represent the moisture content and temperature distribution in the gas-solid phases as well as the Computational Fluid Dynamics. The projects concern the drying kinetics determination; constitutive equations to determine physical-chemical and thermo-physical properties and shrinkage factor; parametric sensibility analysis; and product quality analysis.

Current Members: Luís Cláudio Oliveira Lopes, Marcos Antônio de Souza Barrozo, Valéria Viana Murata e Vivian Consuelo Reolon Schmidt.

Modelagem, Controle e Otimização de Processos

Solids Control in Oil and Gas Well Drilling and Fluid Flow in Reservoir Rock

Coordinator: Carlos Henrique Ataíde

Current Members: Aristeu da Silveira Neto, Cláudio Roberto, Curt Max de Ávila Panisset, Elie Luis Martínez Padilla, Fábio de Oliveira Arouca, Fran Sergio Lobato, Irineu Petri Júnior, Isabele Cristina Bicalho, João Jorge Ribeiro Damasceno, Luís Cláudio Oliveira Lopes, Luiz Gustavo Martins Vieira, Marcos A. S. Barrozo, Marina Seixas Pereira, Rubens Gedraite, Sergio Mauro da S. Neiro, Valéria Viana Murata, Matheus Miguel Rodrigues Pena, Karen Cristina Cardoso Silva.

The project is funding by Petrobras S/A.

Fault-tolerant Control Systems Development

Fault detection or abnormal behavior diagnosis is an important role in efficient industrial operation. For a fault-tolerant system is important to implement automatic monitoring techniques able to provide accurate information about the process state and to be the basis for system recovery. This monitoring structure acts as the main information source for supervision systems responsible for corrective actions to adjust the fault effects. For instance, the petrochemical industry loses around 60 billion Brazilian real per year due to abnormal behavior in industrial operation. Fault detection and diagnosis techniques are based on process knowledge. This knowledge derives from process modeling or operational data and the industries have given attention to fault detection and diagnosis using operational data. In this way, the current project aims to develop algorithms and techniques to implement fault-tolerant control systems with structural reconfiguration using control allocation and virtual sensors based on artificial intelligence (fuzzy, support vector machines), trained neural networks, identified models, and phenomenological models.

Predictive Control Systems Development (hybrid approach, stable control systems, economic model, and cooperative distributed control system)

The project aims to develop predictive control structures including a hybrid approach inherent stable mode, and a cooperative distributed model. The hybrid control systems demand consistent response with interaction among discrete and continuous events, which leads to specific control strategies developed for these scenarios. This project also investigates the production scheduling, supply chain, and process control integration to optimize the production stages using the control strategy within each stage. Thus, it has a great impact allowing real industry scenarios application such as energy, pharmaceutical, food, and supplies distribution.

Modeling and Simulation using Computational Fluid Dynamics for Particles Dispersion from Vehicular Emissions

Particles dispersion by vehicular emission in large cities generate severe impacts on environmental and human health. Buildings, wind direction and velocity, air moisture, traffic signal timing, vehicle type and age, streets configuration, among others influence this dispersion. This line of research considers algorithms and open-sources software to estimate the particle concentration in places with high traffic flow and people movement. The Eulerian approach and the turbulence effect are considered. The model results are validated by comparison with the experimental data obtained from the monitoring station in the city center located at Central Station in Uberlância (MG).

Optimization of Solid-Liquid Separation Process in Oil and Gas Well Drilling and Modeling and Numerical Simulation for Fluid Flow in Annular Sections

Coordinator: Carlos Henrique Ataíde

Current Members: Aristeu da Silveira Neto, Cláudio Roberto, Curt Max de Ávila Panisset, Elie Luis Martínez Padilla, Fábio de Oliveira Arouca, Fran Sergio Lobato, João Jorge Ribeiro Damasceno, Luís Cláudio Oliveira Lopes, Luiz Gustavo Martins Vieira, Marcos A. S. Barrozo, Marina Seixas Pereira, Rubens Gedraite, Valéria Viana Murata.

The project is funding by Petrobras S/A.

Dynamic Optimization through Direct Methods, Indirect Methods, Hybrid Methods, and Evolutionary Computation

Numerical solution of dynamic optimization problems is a challenge since the inequality constraints activation and deactivation modifies the differential index of the differential equations systems. This project aims to extend the algebraic-differential approach to the Differential Algebraic Optimal Control Problems – DAOCP. Indirect methods based on Pontryagin’s Principle are considered under the computational implementation perspective. The solution algorithms using direct methods are also investigated. From these classical approach performances, it is proposed a solution using hybrids methods and evolutionary computation.

Production Planning and Scheduling

This line of research investigates optimization techniques feasibility for planning and scheduling of petroleum supply chain, blending, and products distribution applying specific Brazilian refinery operational conditions. The studies focus on overlapping and non-overlapping unloading process, pipeline distribution with an interface between products, decomposition strategies applied to mathematical solutions, flexible time horizon, among others. The objective functions consider material, pumping operation, inventory, and transition costs.

Current Members: Sérgio Mauro da Silva Neiro e Valéria Viana Murata.

Computer-Aided Industrial Process Project

This project evaluates industrial processes development using process simulation. The studies are comprised of the following steps: thermodynamic validation; choosing the appropriate unit operations; industrial plant optimization. It will be underlined sustainable development according to the national reality.

Solids Control Technologies in Oil and Gas Well Drilling: Optimization, alternative solid-liquid separation process, and instrumentation

This Cooperation Agreement aims to boost the technological development of the drill cuttings cleaning operation, which includes several units such as sieves, centrifuges, settlers, and hydrocyclones.

Current Members: Carlos Henrique Ataíde (coordinador); João Jorge Ribeiro Damasceno; Claudio Roberto Duarte; Luiz Gustavo Martins Vieira; Fábio de Oliveira Arouca; Valéria Viana Murata; Rubens Gedraite; Marcos Antonio de Souza Barrozo; Marina Seixas Pereira.

The project is funding by Petrobras S/A.