LTM-Laboratory of Topology Optimization and Multiphysics Analysis - is a research laboratory at the School of Mechanical Engineering of the University of Campinas. Our research focus is in Structural Topology Optimization and Multiphysics-Multiscale Analysis, including studies on new evolutionary methods and bio inspired design strategies. Our team includes engineers and students dedicated to implement and apply specific numerical optimization methods to multiphysics systems. The team works closely with the following problems: static and dynamic structural design, multiscale analysis; design of periodic systems, vibroacoustic analysis, fluid-structure analysis; load dependent problems and fluid actuated systems, nonlinear materials models, metamaterial design.
Thermoelastic structures are structures subjected to thermal and mechanical loads where the properties of the materials, which they are composed, play an important role in its behavior. Due to this, this research focuses on the analysis and the topology optimization of thermoelastic structures considering the macroscale, the microscale and concurrent topology optimization using multiples materials. Lidy Marcela Anaya Jaimes
Macro and Micro Structure Optimization
A metamaterial is an engineering material with properties that are not found in nature. This research focuses on the analysis and topology optimization of metamaterials using inverse homogenization and the BESO method to find the distribution of multiples materials within a cell to obtain a desired property considering a constant thermal load. Lidy Marcela Anaya Jaimes
Micro-Metamaterial and Deformed Structure
Due to its large applicability to the industry, it is interesting to develop and apply techniques to simulate and optmize rotating machineries. Through modifications of the rotor's topology, this research deals with the separation margin of the nominal rotor speed with respect to resonance regions. The algorithm obtains an optmized distribution of the design variables by maximizing or minimizing natural frequencies as well as taking in account damping and gyroscopic effects. Collaborative Project with LaMCoS at INSA de Lyon: Prof. Jarir Mahfoud. Evandro Carobino
Second Mode shape and Shaft Diameter Optimization
Topology optimization of fluid-actuated cellular mechanisms using the Bidirectional Evolutionary Structural Otimization (BESO) method. Inspired by biologic mechanisms of some plants, a class of cellular fluid actuators was described and optimized. By pressuring the fluid inside the actuation cells, the mechanism changes its kinematic configuration and performs a desired movement. Large displacements and deformations are considered: together with the strain tensors nonlinearity, there are nonlinear effects due to hydrostatic loading on moving boundaries. Daniel Cunha
Topology optimization of piezoelectric energy harvesting devices using finite element discretization and the Bidirectional Evolutionary Structural Optimization (BESO) method. This research’s motivation is the increasing demand for cleaner energy and more efficient electric systems. With the advances on 3D printing technology, more sophisticated structures may be manufactured, thus, increasing the viability of producing efficient topologically optimized energy harvesters. The gif shows the evolution of a beam-like periodic harvester along the optimization process. Breno de Almeida
The general aims of this research project is to combine the evolutionary topology optimization techniques with multiphysics problems involving fluid-structure interaction. Different physical problems (e.g., structures and fluids) interacting with each other are considered, especially when the interfaces between each domain is allowed to move during optimization. A discrete optimization method named Bi-directional Evolutionary Structural Optimization (BESO) is used. The discrete design scheme of the BESO allows different physical domains to be modeled straightforwardly with explicitly defined interfaces. William Vicente
Application of the Bidirectional Evolutionary Structural Optimization (BESO) method to solve large 3D problems. This research focuses on the parallel implementation of the BESO method using Multi-CPU or GPU strategies. The figure shows the evolution of a MBB beam problem comprised of 5.184M elements (15,856,203 DOFs) that was solved using a multi-CPU approach. The computational resources were provided by the Center for Computing in Engineering & Sciences at UNICAMP (CCES - UNICAMP). Hugo Idagawa
This research adresses the optimization of a structure's natural frequencies using the Bidirectional Evolutionary Structural Optimization (BESO) method. This includes maximization and minimization of eigenvalues, as well as maximization of the separation of two consecutive ones. In addition to studying and proposing new methods for natural frequency optimization (particularly for high-frequency range), the influence of structural periodicity and the band gap phenomenon are analyzed. Heitor Lopes