Modern Compressor Aerodynamic Blading Process Using Multi-Objective Optimization

2006 ◽  
Author(s):  
Akin Keskin ◽  
Amit Kumar Dutta ◽  
Dieter Bestle
Keyword(s):  
High Efficiency ◽  
Axial Compressor ◽  
Design Flow ◽  
Optimization Approach ◽  
Optimization Strategy ◽  
Multi Objective Optimization ◽  
Flow Conditions ◽  
Multi Objective ◽  
Blade Section ◽  
The Individual

Aerodynamic design of an axial compressor is a challenging design task requiring a compromise between contradicting requirements like wide operating range, high efficiency, low number of stages and high surge margin. Therefore, the design process is typically subdivided into a sequence of subproblems where the blading design is a key process. According to flow conditions, which result from throughflow calculations on axis-symmetric stream surfaces, 2-dimensional blade profiles have to be designed, which then may be stacked along a radial stacking line in order to find the 3D-blade geometry. The design of the blade sections is rather time consuming due to many iterations with different programs. Usually a geometry generation tool is used to describe the blade sections which are then evaluated by a blade-to-blade CFD solver. The quality of a single blade section is typically characterized by the overall loss at design flow conditions and the working range determined by an amount of loss increase due to incidence variation. The aerodynamic performance of the final airfoils and thus of the whole compressor depends significantly on the design of the individual blade sections. In this investigation an automated multi-objective optimization strategy is developed to find best blade section geometries with respect to loss and working range. The multi-objective optimization approach provides Pareto-optimal compromise solutions at reasonable computational costs outperforming a given Rolls-Royce datum design which has been ‘optimized’ manually by a human design engineer.

scholarly journals Multi-Objective Multidisciplinary Design Optimization of a Robotic Fish System

2021 ◽  
Vol 9 (5) ◽  
pp. 478
Author(s):  
Hao Chen ◽  
Weikun Li ◽  
Weicheng Cui ◽  
Ping Yang ◽  
Linke Chen
Keyword(s):  
Design Optimization ◽  
Optimization Algorithm ◽  
Multidisciplinary Design Optimization ◽  
Robotic Fish ◽  
Multidisciplinary Design ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cfd Method ◽  
The Individual

Biomimetic robotic fish systems have attracted huge attention due to the advantages of flexibility and adaptability. They are typically complex systems that involve many disciplines. The design of robotic fish is a multi-objective multidisciplinary design optimization problem. However, the research on the design optimization of robotic fish is rare. In this paper, by combining an efficient multidisciplinary design optimization approach and a novel multi-objective optimization algorithm, a multi-objective multidisciplinary design optimization (MMDO) strategy named IDF-DMOEOA is proposed for the conceptual design of a three-joint robotic fish system. In the proposed IDF-DMOEOA strategy, the individual discipline feasible (IDF) approach is adopted. A novel multi-objective optimization algorithm, disruption-based multi-objective equilibrium optimization algorithm (DMOEOA), is utilized as the optimizer. The proposed MMDO strategy is first applied to the design optimization of the robotic fish system, and the robotic fish system is decomposed into four disciplines: hydrodynamics, propulsion, weight and equilibrium, and energy. The computational fluid dynamics (CFD) method is employed to predict the robotic fish’s hydrodynamics characteristics, and the backpropagation neural network is adopted as the surrogate model to reduce the CFD method’s computational expense. The optimization results indicate that the optimized robotic fish shows better performance than the initial design, proving the proposed IDF-DMOEOA strategy’s effectiveness.

scholarly journals Multi-Objective Optimization in Axial Compressor Design Using a Linked CFD-Solver

2008 ◽  
Author(s):  
Kai Becker ◽  
Martin Lawerenz ◽  
Christian Voß ◽  
Reinhard Mo¨nig
Keyword(s):  
Guide Vane ◽  
Axial Compressor ◽  
Navier Stokes ◽  
Inlet Guide Vane ◽  
Optimization Strategy ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Flow Information ◽  
Design Variation

In combination with a multi-objective 3D optimization strategy, a linked CFD-solver is presented in this paper, combining 3D-Reynolds-averaged-Navier-Stokes and an inviscid throughflow method. It enables the adjustment of the 3D boundary conditions for any design variation and contains new options for configuring the objective functions. The link is achieved by matching the flow information between both CFD codes in an iterative procedure. Compared to an individual 3D-CFD calculation, the convergence does not take significantly longer. The potential of the linked CFD-solver is demonstrated in a multi-objective optimization for one blade row to be optimized and one operating point at a 3-stage axial compressor with inlet guide vane. Within the optimization, the objective functions are formulated, so that the performance of the axial compressor is enhanced in addition to the improved efficiency of the 3D-cascade.

Multi-objective optimization of vehicle seat suspension with friction under random excitation

2021 ◽  
pp. 095440702110555
Author(s):  
Rongkang Luo ◽  
Peibao Wu ◽  
Jiabin Luo ◽  
Zhichao Hou ◽  
Le He ◽  
...  
Keyword(s):  
Linear Model ◽  
Human Body ◽  
Random Excitation ◽  
Optimization Approach ◽  
Optimization Strategy ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Seat Suspension ◽  
Model Linearization ◽  
Vehicle Seat

A seat suspension contributes greatly to vehicle ride comfort as a result of direct contact with the human body. Friction in a seat suspension produces strong non-smooth nonlinearity in seat dynamics, which makes the simulation-based optimization on the seat suspension’s performance time-consuming. This study tries to address parameter optimization on a vehicle seat suspension with the friction force in an analytical approach. A two degrees of freedom model is firstly established for the human body-seat system with friction and subjected to bandlimited random excitation. The nonlinear model is converted into an equivalent linear model by using Gaussian linearization. The dynamic responses of the linear model have then derived analytically and validated by Monte Carlo simulations. Based on the analytical solution, a multi-objective optimization strategy is proposed for the seat suspension. The acceleration of the human body and the suspension travel are chosen as the objective indexes to evaluate seat performance. Simulation results show that the proposed optimization strategy is efficient, where a global optimum is guaranteed owing to the analytical expression of the objective function. The optimization approach taking advantage of model linearization can be applied to similar mechanical systems with friction.

Multi-objective optimization of double suction centrifugal pump

2017 ◽  
Vol 232 (6) ◽  
pp. 1108-1117 ◽  
Author(s):  
Ran Tao ◽  
Ruofu Xiao ◽  
Di Zhu ◽  
Fujun Wang
Keyword(s):  
Centrifugal Pump ◽  
High Efficiency ◽  
Design Flow ◽  
Multi Objective Optimization ◽  
Centrifugal Pumps ◽  
Original Design ◽  
Rate Condition ◽  
Multi Objective ◽  
Numerical Studies ◽  
Critical Cavitation

Double suction centrifugal pumps are widely used for water supplying system. In this study, the original design of a double centrifugal pump lacked sufficient head at the design flow rate condition. Therefore, the most important objective was to optimize the design to improve the head. A strategy inspired by “liquid–gas cavitation process” is innovatively used for intelligent global search of better pump designs with both higher head and wider-higher efficiency. This strategy has advantages including flexibility, parallelism, and feasibility on overstepping the local-best. The computational fluid dynamics and artificial neural network are used. It helps this optimization to find unknown points in the non-linear and multi-dimensional searching space, and accelerate the optimization process. Candidates were found after search, and the best one was chosen using Pareto principle. Experimental and numerical studies verify that the optimized impeller meets the requirement of head. The efficiency is also significantly improved with higher best efficiency and wider high efficiency range than original design. The critical cavitation is also improved at design condition. This study provides an effective strategy and a good solution for multi-objective optimization of double suction centrifugal pumps. Moreover, this study provides references for the combination of optimizations with artificial intelligence especially in the pump’s design.

Integrated Design and Multi-Objective Optimization of a Single Stage Heat-Pump Turbocompressor

2013 ◽  
Author(s):  
J. Schiffmann
Keyword(s):  
Design Optimization ◽  
High Efficiency ◽  
Integrated Design ◽  
Heat Pumps ◽  
Small Scale ◽  
Multi Objective Optimization ◽  
Design Constraints ◽  
Multi Objective ◽  
Wide Range ◽  
Standard Design

Small scale turbomachines in domestic heat pumps reach high efficiency and provide oil-free solutions which improve heat-exchanger performance and offer major advantages in the design of advanced thermodynamic cycles. An appropriate turbocompressor for domestic air based heat pumps requires the ability to operate on a wide range of inlet pressure, pressure ratios and mass flows, confronting the designer with the necessity to compromise between range and efficiency. Further the design of small-scale direct driven turbomachines is a complex and interdisciplinary task. Textbook design procedures propose to split such systems into subcomponents and to design and optimize each element individually. This common procedure, however, tends to neglect the interactions between the different components leading to suboptimal solutions. The authors propose an approach based on the integrated philosophy for designing and optimizing gas bearing supported, direct driven turbocompressors for applications with challenging requirements with regards to operation range and efficiency. Using previously validated reduced order models for the different components an integrated model of the compressor is implemented and the optimum system found via multi-objective optimization. It is shown that compared to standard design procedure the integrated approach yields an increase of the seasonal compressor efficiency of more than 12 points. Further a design optimization based sensitivity analysis allows to investigate the influence of design constraints determined prior to optimization such as impeller surface roughness, rotor material and impeller force. A relaxation of these constrains yields additional room for improvement. Reduced impeller force improves efficiency due to a smaller thrust bearing mainly, whereas a lighter rotor material improves rotordynamic performance. A hydraulically smoother impeller surface improves the overall efficiency considerably by reducing aerodynamic losses. A combination of the relaxation of the 3 design constraints yields an additional improvement of 6 points compared to the original optimization process. The integrated design and optimization procedure implemented in the case of a complex design problem thus clearly shows its advantages compared to traditional design methods by allowing a truly exhaustive search for optimum solutions throughout the complete design space. It can be used for both design optimization and for design analysis.

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