Multi-Objective Shape Optimization of Convective Wavy Channels

2005 ◽  
Author(s):  
Enrico Nobile ◽  
Francesco Pinto ◽  
Gino Rizzetto
Keyword(s):  
Shape Optimization ◽  
Three Dimensional ◽  
Temperature Fields ◽  
Two Dimensional ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Design Variables ◽  
Wavy Channels ◽  
Steady Laminar ◽  
Objective Shape

In this paper we describe a procedure for the multi-objective shape optimization of periodic wavy channels, representative of the repeating module of an ample variety of heat exchangers. The two objectives considered are the maximization of heat transfer rate and minimization of friction factor. Since there is no a single optimum to be found, we use a Multi-Objective Genetic Algorithm and the so-called Pareto’s dominance concept. The optimization of the periodic channel is obtained, by means of an unstructured Finite Element solver, for a fluid of Prandtl number Pr = 0.7, assuming fully developed velocity and temperature fields, and steady laminar conditions. For the two-dimensional case, the geometry is parameterized either by means of linear-piecewise profiles, or NURBS, and their control points represent the design variables. The three-dimensional channels are obtained by simple extrusion of the two-dimensional geometries. The results obtained are very encouraging, and the procedure described can be applied, in principle, to even more complex problems.

scholarly journals Multi-Point Shape Optimization of a Horizontal Axis Tidal Stream Turbine

Eng ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 340-355
Author(s):  
Hassan el Sheshtawy ◽  
Ould el Moctar ◽  
Satish Natarajan
Keyword(s):  
Genetic Algorithm ◽  
Shape Optimization ◽  
Pressure Coefficient ◽  
Three Dimensional ◽  
Panel Method ◽  
Two Dimensional ◽  
Nsga Ii ◽  
Multi Objective Genetic Algorithm ◽  
Tidal Stream ◽  
Tidal Stream Turbine

A method was developed to perform shape optimization of a tidal stream turbine hydrofoil using a multi-objective genetic algorithm. A bezier curve parameterized the reference hydrofoil profile NACA 63815. Shape optimization of this hydrofoil maximized its lift-to-drag ratio and minimized its pressure coefficient, thereby increasing the turbines power output power and improving its cavitation characteristics. The Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) was employed to perform the shape optimization. A comparative study of two- and three-dimensional optimizations was carried out. The effect of varying the angle of attack on the quality of optimized results was also studied. Predictions based on two-dimensional panel method results were also studied. Predictions based on a two-dimensional panel method and on a computational fluid dynamics code were compared to experimental measurements.

scholarly journals Multi-Point Shape Optimization of a Horizontal Axis Tidal Stream Turbine

2021 ◽  
Author(s):  
Hassan El Sheshtawy ◽  
Ould el Moctar ◽  
Satish Natarajan
Keyword(s):  
Genetic Algorithm ◽  
Shape Optimization ◽  
Pressure Coefficient ◽  
Three Dimensional ◽  
Panel Method ◽  
Two Dimensional ◽  
Nsga Ii ◽  
Multi Objective Genetic Algorithm ◽  
Tidal Stream ◽  
Tidal Stream Turbine

A method was developed to perform shape optimization of a tidal stream turbine hydrofoil using a multi-objective genetic algorithm. A bezier curve parameterized the refrence hydrofoil profoil NACA 63815. Shape optimization of this hydrofoil maximized its lift-to-darg ratio and minimized its pressure coefficient, thereby increasing the turbines power output power and improving its cavitation characteristics. The Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) was employed to perform the shape optimization. A comparative study of two-and three-dimensional optimizations was carried out. The effect of varing the angle of attack on the quality of optimized results was also studied. predictions based on two-dimensional panel method results was also studied. Preditions based on a two-dimensional panel method and on a computational fluid dynamics code were compared to experimental measurments.

scholarly journals A Three-Dimensional Numerical and Multi-Objective Optimal Design of Wavy Plate-Fins Heat Exchangers

Processes ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 9
Author(s):  
Chao Yu ◽  
Xiangyao Xue ◽  
Kui Shi ◽  
Mingzhen Shao
Keyword(s):  
Heat Exchangers ◽  
Cfd Simulation ◽  
Three Dimensional ◽  
Basis Functions ◽  
Approximation Model ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Colburn Factor ◽  
Heat Exchange Efficiency

This paper presents a method for optimizing wavy plate-fin heat exchangers accurately and efficiently. It combines CFD simulation, Radical Basis Functions (RBF) with multi-objective optimization to improve the performance. The optimization of the Colburn factor j and the friction coefficient f is regarded as a multi-objective optimization problem, due to the existence of two contradictory goals. The approximation model was obtained by Radical Basis Functions, and the shape of the heat exchanger was optimized by multi-objective genetic algorithm (MOGA). The optimization results showed that j increased by 17.62% and f decreased by 20.76%, indicating that the heat exchange efficiency was significantly enhanced and the fluid structure resistance reduced. Then, from the aspects of field synergy and tubulence energy, the performance advantage of the optimized structure was further confirmed.

scholarly journals Multi-objective parametrization of interatomic potentials for large deformation pathways and fracture of two-dimensional materials

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Xu Zhang ◽  
Hoang Nguyen ◽  
Jeffrey T. Paci ◽  
Subramanian K. R. S. Sankaranarayanan ◽  
Jose L. Mendoza-Cortes ◽  
...  
Keyword(s):  
Large Deformation ◽  
Functional Form ◽  
Principal Component ◽  
Interatomic Potentials ◽  
Two Dimensional ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Two Dimensional Materials ◽  
Definition Of

AbstractThis investigation presents a generally applicable framework for parameterizing interatomic potentials to accurately capture large deformation pathways. It incorporates a multi-objective genetic algorithm, training and screening property sets, and correlation and principal component analyses. The framework enables iterative definition of properties in the training and screening sets, guided by correlation relationships between properties, aiming to achieve optimal parametrizations for properties of interest. Specifically, the performance of increasingly complex potentials, Buckingham, Stillinger-Weber, Tersoff, and modified reactive empirical bond-order potentials are compared. Using MoSe2 as a case study, we demonstrate good reproducibility of training/screening properties and superior transferability. For MoSe2, the best performance is achieved using the Tersoff potential, which is ascribed to its apparent higher flexibility embedded in its functional form. These results should facilitate the selection and parametrization of interatomic potentials for exploring mechanical and phononic properties of a large library of two-dimensional and bulk materials.

Multi-objective shape optimization of a tube bundle in cross-flow

2014 ◽  
Vol 68 ◽  
pp. 585-598 ◽  
Author(s):  
Paola Ranut ◽  
Gábor Janiga ◽  
Enrico Nobile ◽  
Dominique Thévenin
Keyword(s):  
Shape Optimization ◽  
Tube Bundle ◽  
Cross Flow ◽  
Multi Objective ◽  
Objective Shape
Sign in / Sign up

Export Citation Format

Share Document