Enhanced biogeography-based optimization : A new method for size and shape optimization of truss structures with natural frequency constraints

Peer reviewedPublisher PD

Numerical Analysis of Energy Loss Coefficient in Pipe Contraction Using ANSYS CFX Software

The purpose of this study is the numerical analysis of energy loss coefficient in pipe contraction using ANSYS CFX software. To this end, the effect of the dimensionless parameters of Euler number, Reynolds number, and relative roughness on energy loss coefficient has been investigated and eventually an overall formula to determine the energy loss coefficient in these transitions has been provided. In order to solve the fluid turbulence equations in the pipe, standard K-Epsilon model has been used. For this purpose, first the geometry of pipe transitions was designed in 3-D, using Solid Works software, and then the transitions were meshed by ANSYS MESHING. The initial simulation of transitions including boundary conditions of outlet, inlet and wall, was carried out by a pre-processor called CFX-PRE. Furthermore, to solve the equations governing the fluid flow in the pipes (Navier-Stokes equations) the CFX-SOLVER was used. And finally, the results were extracted using a post-processor called CFD-POST.The results indicated that the energy loss coefficient, contrary to the findings of previous researchers, is not only related to transition geometry, but also is dependent on the Reynolds number, relative roughness of the wall and Euler number. By increasing the Reynolds Number and turbulence of fluid flow in transitions, the energy loss coefficient is reduced. Moreover, by increasing the relative roughness in the transition’s wall the energy loss coefficient is reduced. The increase in pressure fluctuation causes the increase of Euler number which leads to the linear increase of energy loss coefficient

Enhanced Biogeography-based Optimization: A New Method for Size and Shape Optimization of Truss Structures with Natural Frequency Constraints

Abstract The current study presents an enhanced biogeography-based optimization (EBBO) algorithm for size and shape optimization of truss structures with natural frequency constraints. The BBO algorithm is one of the recently developed meta-heuristic algorithms inspired by the mathematical models in biogeography science and is based on the migration behavior of species among the habitats in the nature. In this study, the overall performance of the standard BBO algorithm is enhanced by new migration and mutation operators. The efficiency of the proposed algorithm is demonstrated by utilizing four benchmark truss design examples with frequency constraints. Numerical results show that the proposed EBBO algorithm not only significantly improves the performance of the standard BBO algorithm, but also finds competitive results compared with recently developed optimization methods