Browsing by Subject "topology"

Now showing 1 - 3 of 3
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    Alternative Breed of Three-Phase Four-Wire Shunt Compensators based on Cascaded Transformer with Single Dc-link
    (IEEE, 2017-03) de Almeida Carlos, Gregory A.; Jacobina, Cursino B.; dos Santos Jr., Euzeli C.; Electrical and Computer Engineering, School of Engineering and Technology
    This paper introduces a new breed of four-wire (4W) multilevel shunt compensator to deal with either harmonic or reactive power compensation. The converter configurations are generalized for K-stages and the main benefits of proposed topologies lie on i) multilevel waveforms generation, ii) single dc-link unit and iii) modular characteristic. The configurations are based on cascaded transformers along with three-phase-bridge (TPB) converters. These converters are directly connected to the transformer primary side. A suitable PWM strategy combined with an appropriate transformer turns ratio guarantees the desirable multilevel output waveforms. The modularity feature provides simple maintenance and makes the proposed shunt active power filters (SAPFs) an attractive solution in comparison with conventional configurations. The configuration model and overall control are addressed, as well. Simulation and experimental results are presented for theoretical validation.
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    Multiphase Thermomechanical Topology Optimization of Functionally Graded Lattice Injection Molds
    (ASME, 2016-08) Wu, Tong; Liu, Kai; Tovar, Andres; Department of Mechanical Engineering, School of Engineering and Technology
    This work presents a design methodology of lightweight, thermally efficient injection molds with functionally graded lattice structure using multiphase thermomechanical topology optimization. The aim of this methodology is to increase or maintain thermal and mechanical performance as well as to lower the cost of thermomechanical components such as injection molds when these are fabricated using additive manufacturing technologies. The proposed design approach makes use of thermal and mechanical finite element analyses to evaluate the components stiffness and heat conduction in two length scales: mesoscale and macroscale. The mesoscale contains the structural features of the lattice unit cell. Mesoscale homogenized properties are implemented in the macroscale model, which contains the components boundary conditions including the external mechanical loads as well as the heat sources and heat sinks. The macroscale design problem addressed in this work is to find the optimal distribution of given number of lattice unit cell phases within the component so its mass is minimized, while satisfying stiffness and heat conduction constraints of the overall component and the specific regions. This problem is solved through two steps: conceptual design generation and multiphase material distribution. In the first step, the mass is minimized subject to constraints of mechanical compliance and thermal cost function. In the second step, a given number of lattice material are optimally distributed subjected to nonlinear thermal and mechanical constraints, e.g., maximum nodal temperature, maximum nodal displacement. The proposed design approach is demonstrated through 2D and 3D examples including the optimal design of the core of an injection mold. The results demonstrate that a small reduction in mechanical and thermal performance allows for significant mass savings: the second example shows that 3.5% heat conduction reduction and 8.7% stiffness reduction results in 30.3% mass reduction.
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    Multiscale Topology Optimization With Gaussian Process Regression Models
    (American Society of Mechanical Engineers, 2021-08-17) Najmon, Joel C.; Valladares, Homero; Tovar, Andres; Mechanical Engineering, School of Engineering and Technology
    Multiscale topology optimization (MSTO) is a numerical design approach to optimally distribute material within coupled design domains at multiple length scales. Due to the substantial computational cost of performing topology optimization at multiple scales, MSTO methods often feature subroutines such as homogenization of parameterized unit cells and inverse homogenization of periodic microstructures. Parameterized unit cells are of great practical use, but limit the design to a pre-selected cell shape. On the other hand, inverse homogenization provide a physical representation of an optimal periodic microstructure at every discrete location, but do not necessarily embody a manufacturable structure. To address these limitations, this paper introduces a Gaussian process regression model-assisted MSTO method that features the optimal distribution of material at the macroscale and topology optimization of a manufacturable microscale structure. In the proposed approach, a macroscale optimization problem is solved using a gradient-based optimizer The design variables are defined as the homogenized stiffness tensors of the microscale topologies. As such, analytical sensitivity is not possible so the sensitivity coefficients are approximated using finite differences after each microscale topology is optimized. The computational cost of optimizing each microstructure is dramatically reduced by using Gaussian process regression models to approximate the homogenized stiffness tensor. The capability of the proposed MSTO method is demonstrated with two three-dimensional numerical examples. The correlation of the Gaussian process regression models are presented along with the final multiscale topologies for the two examples: a cantilever beam and a 3-point bending beam.