Aerodynamic preliminary design optimization of a centrifugal compressor turbocharger based on one-dimensional mean-line model

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lakhdar Bourabia ◽  
Cheikh Brahim Abed ◽  
Mahfoudh Cerdoun ◽  
Smail Khalfallah ◽  
Michaël Deligant ◽  
...  
Keyword(s):  
Design Optimization ◽  
Centrifugal Compressor ◽  
Optimization Design ◽  
Optimization Techniques ◽  
Solution Phase ◽  
Geometrical Parameters ◽  
Preliminary Design ◽  
Line Model ◽  
Content Type ◽  
One Dimensional

Purpose The purpose of this paper is the development of a new turbocharger compressor is a challenging task particularly when both wider operating range and higher efficiency are required. However, the cumbersome design effort and the inherent calculus burden can be significantly reduced by using appropriate design optimization approaches as an alternative to conventional design techniques. Design/methodology/approach This paper presents an optimization-based preliminary-design (OPD) approach based on a judicious coupling between evolutionary optimization techniques and a modified one-dimensional mean-line model. Two optimization strategies are considered. The first one is mono-objective and is solved using genetic algorithms. The second one is multi-objective and it is handled using the non-dominated sorting genetic algorithm-II. The proposed approach constitutes an automatic search process to select the geometrical parameters of the compressor, ensuring the most common requirements of the preliminary-design phase, with a minimum involvement of the designer. Findings The obtained numerical results demonstrate that the proposed tool can rapidly produce nearly optimal designs as an excellent basis for further refinement in the phase by using more complex analysis methods such as computational fluid dynamics and meta-modeling. Originality/value This paper outlines a new fast OBPD approach for centrifugal compressor turbochargers. The proposal adopts an inverse design method and consists of two main phases: a formulation phase and a solution phase. The complexity of the formulated problem is reduced by using a sensitivity analysis. The solution phase requires to link, in an automatic way, three processes, namely, optimization, design and analysis.

On the Coupling of Direct Design and Optimization Techniques for Mitigating the Turbomachinery Performance Test Risk

2013 ◽  
Author(s):  
Keiji Tajiri ◽  
Jinhui Zhao ◽  
William C. Hohlweg ◽  
Haijie Zhang
Keyword(s):  
New Product Development ◽  
Centrifugal Compressor ◽  
Optimization Techniques ◽  
Design System ◽  
Design Modification ◽  
One Dimensional ◽  
Multi Objective ◽  
Direct Design ◽  
Multistage Compressor ◽  
The Impact

Automatic optimization techniques have been used in recent years to facilitate more rapid analyses of different design options with multiple performance objectives. Typically, this process has been used during new product development. In this paper, a design system is presented, which enables the multipoint, multi-objective optimization of the centrifugal compressor stage aerodynamic components. Moreover, it is applied to a design modification of a multistage compressor, during the manufacturing cycle, for risk mitigation. The system is based on the application of the Isight code for coupling of one dimensional direct design and analysis with multi-objective genetic algorithms, design of experiment, and response surface method. The design system was applied to a redesign of the diffuser, crossover, and return channel of two stages in a multistage compressor. The geometry parameterization is performed by a one dimensional analysis method where the diffuser width, crossover inlet and exit width and associated inner and outer radii, are used to describe the meridional flow path while holding the return vane geometry unchanged. Centrifugal compressor performance parameters, such as polytropic head and efficiency at the client rated point, head rise to surge, and choke flow capacity are evaluated during the optimization process. The example confirmed the validity of the system to perform the optimization of turbomachine components in a time efficient manner to meet production schedule. The system also allowed for a sensitivity analysis of the impact of geometry parameters on the aerodynamic performance, contributing to the development of guidelines for manufacturers to design new products and mitigate the performance risk on test floor.

Variable-fidelity shape optimization of dual-rotor wind turbines

2018 ◽  
Vol 35 (7) ◽  
pp. 2514-2542
Author(s):  
Andrew Thelen ◽  
Leifur Leifsson ◽  
Anupam Sharma ◽  
Slawomir Koziel
Keyword(s):  
Design Optimization ◽  
Wind Turbines ◽  
Computational Cost ◽  
Optimization Techniques ◽  
Fast Variable ◽  
Efficient Design ◽  
Content Type ◽  
Optimization Framework ◽  
Derivative Free ◽  
Variable Fidelity

Purpose Dual-rotor wind turbines (DRWTs) are a novel type of wind turbines that can capture more power than their single-rotor counterparts. Because their surrounding flow fields are complex, evaluating a DRWT design requires accurate predictive simulations, which incur high computational costs. Currently, there does not exist a design optimization framework for DRWTs. Since the design optimization of DRWTs requires numerous model evaluations, the purpose of this paper is to identify computationally efficient design approaches. Design/methodology/approach Several algorithms are compared for the design optimization of DRWTs. The algorithms vary widely in approaches and include a direct derivative-free method, as well as three surrogate-based optimization methods, two approximation-based approaches and one variable-fidelity approach with coarse discretization low-fidelity models. Findings The proposed variable-fidelity method required significantly lower computational cost than the derivative-free and approximation-based methods. Large computational savings come from using the time-consuming high-fidelity simulations sparingly and performing the majority of the design space search using the fast variable-fidelity models. Originality/value Due the complex simulations and the large number of designable parameters, the design of DRWTs require the use of numerical optimization algorithms. This work presents a novel and efficient design optimization framework for DRWTs using computationally intensive simulations and variable-fidelity optimization techniques.

High-speed functionality optimization of five-phase PM machine using third harmonic current

2014 ◽  
Vol 33 (3) ◽  
pp. 879-893 ◽  
Author(s):  
Jinlin Gong ◽  
Bassel Aslan ◽  
Frédéric Gillon ◽  
Eric Semail
Keyword(s):  
Control Strategy ◽  
High Speed ◽  
Design Methodology ◽  
Computation Time ◽  
Complex Model ◽  
Optimization Techniques ◽  
Geometrical Parameters ◽  
Content Type ◽  
Third Harmonic ◽  
Remarkable Effect

Purpose – The purpose of this paper is to apply some surrogate-assisted optimization techniques in order to improve the performances of a five-phase permanent magnet machine in the context of a complex model requiring computation time. Design/methodology/approach – An optimal control of four independent currents is proposed in order to minimize the total losses with the respect of functioning constraints. Moreover, some geometrical parameters are added to the optimization process allowing a co-design between control and dimensioning. Findings – The optimization results prove the remarkable effect of using the freedom degree offered by a five-phase structure on iron and magnets losses. The performances of the five-phase machine with concentrated windings are notably improved at high speed (16,000 rpm). Originality/value – The effectiveness of the method allows solving the challenge which consists in taking into account inside the control strategy the eddy-current losses in magnets and iron. In fact, magnet losses are a critical point to protect the machine from demagnetization in flux-weakening region.

Design Optimization of a Centrifugal Compressor Impeller Using Radial Basis Neural Network Method

2009 ◽  
Author(s):  
Jin-Hyuk Kim ◽  
Jae-Ho Choi ◽  
Kwang-Yong Kim
Keyword(s):  
Neural Network ◽  
Design Optimization ◽  
Centrifugal Compressor ◽  
Optimization Techniques ◽  
Design Flow ◽  
Radial Basis Neural Network ◽  
Neural Network Method ◽  
Network Method ◽  
Radial Basis ◽  
Isentropic Efficiency

This paper presents a procedure for design optimization of a centrifugal compressor. The centrifugal compressor consists of a centrifugal impeller, vaneless diffuser and volute. And, optimization techniques based on radial basis neural network method are used to optimize the impeller of the centrifugal compressor. Latin hypercube sampling of design of experiments is used to generate thirty design points within design spaces. Three-dimensional Reynolds-averaged Navier-Stokes equations with shear stress transport turbulence model are discretized by using finite volume approximations and solved on hexahedral grids to evaluate the objective function of an isentropic efficiency. Four variables defining impeller hub and shroud contours are selected as design variables in this optimization. The results of optimization show that the isentropic efficiency of the optimized shape at the design flow coefficient is enhanced by 1.0% and the efficiencies at the off-design points are also improved significantly by the design optimization.

Multi-Objective Optimization of Inclined Discrete Cavities in a Centrifugal Compressor Using Hybrid Optimization Techniques

2018 ◽  
Author(s):  
Sang-Bum Ma ◽  
Kwang-Yong Kim
Keyword(s):  
Centrifugal Compressor ◽  
Parametric Study ◽  
Stokes Equations ◽  
Three Dimensional ◽  
Leading Edge ◽  
Latin Hypercube Sampling ◽  
Global Optimum ◽  
Optimization Techniques ◽  
Geometrical Parameters ◽  
Objective Functions

In order to extend the operating range of a centrifugal compressor, inclined discrete cavities located upstream of the impeller leading edge were optimized in this work. Aerodynamic performance analysis was performed using three-dimensional Reynolds-averaged Navier-Stokes equations with the shear stress transport turbulence model. A parametric study on aerodynamic performances of the centrifugal compressor with the inclined discrete cavities was conducted with six geometrical parameters. Through the parametric study, three geometric parameters were selected as design variables for optimization. Peak adiabatic efficiency and stall margin were selected as objective functions. The Latin hypercube sampling method was used to select the design points, and the radial basis neural network was used to construct surrogate models of the objective functions. A hybrid method combining the particle swarm optimization showed better overall performance in finding global optimum than the genetic algorithm. Pareto-optimal solutions provided the designs which enhance considerably both the performance parameters compared to the reference design.

Optimum Design of Turbomachinery Components: A System Based Design

2000 ◽  
Author(s):  
Somanath Nagendra
Keyword(s):  
Shape Optimization ◽  
Design Optimization ◽  
Numerical Models ◽  
Turbine Blades ◽  
Optimization Procedure ◽  
Response Surfaces ◽  
Optimization Techniques ◽  
Geometric Constraints ◽  
Preliminary Design ◽  
Design Cycle

Abstract The advent of incredibly fast, increased memory computational systems enable a very systematic design integration of complex engineering modules using an integrated system based approach. Rapid turn-around time for investigating new design concepts is a primary force driving design productivity initiatives across industry. A system based integration focusing on tools for rapid design automation and preliminary design, (e.g. Closed Form Solutions, Response Surfaces, Approximate Numerical Models etc), finite element analysis coupled with optimization methods are needed. Numerical design algorithms (e.g. Sensitivity analysis methods, Feasible Direction methods, Genetic Algorithms, Simulated Annealing, Gradient based Algorithms etc.) at the preliminary and detailed design stages, would ensure higher quality designs from the beginning of the product design cycle. Resulting reliable, robust optimum designs from the preliminary design phase would enable to reduce the overall design cycle time. Large-scale engineering systems (like the gas turbine See Figure. 1) often involve many disciplines which are either loosely or tightly coupled to each other due to the multidisciplinary nature of the interactions. Designers have long recognized the need to decompose such systems into a set of smaller more tractable disciplines. This decomposition is usually based either on engineering disciplines or mathematical models governing the system. Narayan et al. [1] developed a multi-disciplinary design optimization procedure for the design of the aerodynamic shape of turbine blades for enhanced performance using shape optimization techniques. A multidisciplinary design optimization procedure for thin-walled high temperature components has been developed and demonstrated on different components Aerodynamic, heat transfer, structural and modal design objectives are integrated along with various constraint on the blade geometry for multidisciplinary shape optimization. The average blade temperature, maximum blade temperature and the blade weight are minimized with aerodynamic, structural, modal and geometric constraints. A methodology for performing mechanical design of turbine blade components is developed and tested.

RANS-based design optimization of dual-rotor wind turbines

2018 ◽  
Vol 35 (1) ◽  
pp. 35-52 ◽  
Author(s):  
Andrew Thelen ◽  
Leifur Leifsson ◽  
Anupam Sharma ◽  
Slawomir Koziel
Keyword(s):  
Design Optimization ◽  
Wind Turbines ◽  
Optimization Algorithms ◽  
Computational Cost ◽  
Pattern Search ◽  
Optimization Techniques ◽  
Optimal Designs ◽  
Kriging Interpolation ◽  
Direct Optimization ◽  
Content Type

Purpose An improvement in the energy efficiency of wind turbines can be achieved using dual rotors. Because of complex flow physics, the design of dual-rotor wind turbines (DRWTs) requires repetitive evaluations of computationally expensive partial differential equation (PDE) simulation models. Approaches for solving design optimization of DRWTs constrained by PDE simulations are investigated. The purpose of this study is to determine design optimization algorithms which can find optimal designs at a low computational cost. Design/methodology/approach Several optimization approaches and algorithms are compared and contrasted for the design of DRWTs. More specifically, parametric sweeps, direct optimization using pattern search, surrogate-based optimization (SBO) using approximation-based models and SBO using kriging interpolation models with infill criteria are investigated for the DRWT design problem. Findings The approaches are applied to two example design cases where the DRWT fluid flow is simulated using the Reynolds-averaged Navier−Stokes (RANS) equations with a two-equation turbulence model on an axisymmetric computational grid. The main rotor geometry is kept fixed and the secondary rotor characteristics, using up to three variables, are optimized. The results show that the automated numerical optimization techniques were able to accurately find the optimal designs at a low cost. In particular, SBO algorithm with infill criteria configured for design space exploitation required the least computational cost. The widely adopted parametric sweep approach required more model evaluations than the optimization algorithms, as well as not being able to accurately find the optimal designs. Originality/value For low-dimensional PDE-constrained design of DRWTs, automated optimization algorithms are essential to find accurately and efficiently the optimal designs. More specifically, surrogate-based approaches seem to offer a computationally efficient way of solving such problems.

scholarly journals A Two-Round Optimization Design Method for Aerostatic Spindles Considering the Fluid–Structure Interaction Effect

2021 ◽  
Vol 11 (7) ◽  
pp. 3017
Author(s):  
Qiang Gao ◽  
Siyu Gao ◽  
Lihua Lu ◽  
Min Zhu ◽  
Feihu Zhang
Keyword(s):  
Optimal Design ◽  
Optimization Design ◽  
Design Method ◽  
Fluid Structure Interaction ◽  
Design Procedure ◽  
Design Parameters ◽  
Geometrical Parameters ◽  
Fluid Structure ◽  
Structure Interaction ◽  
Aerostatic Spindle

The fluid–structure interaction (FSI) effect has a significant impact on the static and dynamic performance of aerostatic spindles, which should be fully considered when developing a new product. To enhance the overall performance of aerostatic spindles, a two-round optimization design method for aerostatic spindles considering the FSI effect is proposed in this article. An aerostatic spindle is optimized to elaborate the design procedure of the proposed method. In the first-round design, the geometrical parameters of the aerostatic bearing were optimized to improve its stiffness. Then, the key structural dimension of the aerostatic spindle is optimized in the second-round design to improve the natural frequency of the spindle. Finally, optimal design parameters are acquired and experimentally verified. This research guides the optimal design of aerostatic spindles considering the FSI effect.

scholarly journals Special Finite Elements with Adaptive Strain Field on the Example of One-Dimensional Elements

2021 ◽  
Vol 11 (2) ◽  
pp. 609
Author(s):  
Tadeusz Chyży ◽  
Monika Mackiewicz
Keyword(s):  
Finite Elements ◽  
Strain Field ◽  
Main Idea ◽  
Deformation Field ◽  
Geometrical Parameters ◽  
Single Element ◽  
One Dimensional ◽  
New Type ◽  
Self Adaptation ◽  
Adaptation Method

The conception of special finite elements called multi-area elements for the analysis of structures with different stiffness areas has been presented in the paper. A new type of finite element has been determined in order to perform analyses and calculations of heterogeneous, multi-coherent, and layered structures using fewer finite elements and it provides proper accuracy of the results. The main advantage of the presented special multi-area elements is the possibility that areas of the structure with different stiffness and geometrical parameters can be described by single element integrated in subdivisions (sub-areas). The formulation of such elements has been presented with the example of one-dimensional elements. The main idea of developed elements is the assumption that the deformation field inside the element is dependent on its geometry and stiffness distribution. The deformation field can be changed and adjusted during the calculation process that is why such elements can be treated as self-adaptive. The application of the self-adaptation method on strain field should simplify the analysis of complex non-linear problems and increase their accuracy. In order to confirm the correctness of the established assumptions, comparative analyses have been carried out and potential areas of application have been indicated.

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