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.

A Memetic Optimization Strategy Based on Dimension Reduction in Decision Space

2015 ◽  
Vol 23 (1) ◽  
pp. 69-100 ◽  
Author(s):  
Handing Wang ◽  
Licheng Jiao ◽  
Ronghua Shang ◽  
Shan He ◽  
Fang Liu
Keyword(s):  
Dimension Reduction ◽  
Optimization Problems ◽  
State Of The Art ◽  
Search Space ◽  
Optimization Strategy ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Decision Space ◽  
Multi Objective ◽  
Decision Variables

There can be a complicated mapping relation between decision variables and objective functions in multi-objective optimization problems (MOPs). It is uncommon that decision variables influence objective functions equally. Decision variables act differently in different objective functions. Hence, often, the mapping relation is unbalanced, which causes some redundancy during the search in a decision space. In response to this scenario, we propose a novel memetic (multi-objective) optimization strategy based on dimension reduction in decision space (DRMOS). DRMOS firstly analyzes the mapping relation between decision variables and objective functions. Then, it reduces the dimension of the search space by dividing the decision space into several subspaces according to the obtained relation. Finally, it improves the population by the memetic local search strategies in these decision subspaces separately. Further, DRMOS has good portability to other multi-objective evolutionary algorithms (MOEAs); that is, it is easily compatible with existing MOEAs. In order to evaluate its performance, we embed DRMOS in several state of the art MOEAs to facilitate our experiments. The results show that DRMOS has the advantage in terms of convergence speed, diversity maintenance, and portability when solving MOPs with an unbalanced mapping relation between decision variables and objective functions.

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 A New Approach to Group Multi-Objective Optimization under Imperfect Information and Its Application to Project Portfolio Optimization

2021 ◽  
Vol 11 (10) ◽  
pp. 4575
Author(s):  
Eduardo Fernández ◽  
Nelson Rangel-Valdez ◽  
Laura Cruz-Reyes ◽  
Claudia Gomez-Santillan
Keyword(s):  
Portfolio Optimization ◽  
Imperfect Information ◽  
Model Parameters ◽  
Final Decision ◽  
Project Portfolio ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
New Approach ◽  
Multi Objective ◽  
Group Member

This paper addresses group multi-objective optimization under a new perspective. For each point in the feasible decision set, satisfaction or dissatisfaction from each group member is determined by a multi-criteria ordinal classification approach, based on comparing solutions with a limiting boundary between classes “unsatisfactory” and “satisfactory”. The whole group satisfaction can be maximized, finding solutions as close as possible to the ideal consensus. The group moderator is in charge of making the final decision, finding the best compromise between the collective satisfaction and dissatisfaction. Imperfect information on values of objective functions, required and available resources, and decision model parameters are handled by using interval numbers. Two different kinds of multi-criteria decision models are considered: (i) an interval outranking approach and (ii) an interval weighted-sum value function. The proposal is more general than other approaches to group multi-objective optimization since (a) some (even all) objective values may be not the same for different DMs; (b) each group member may consider their own set of objective functions and constraints; (c) objective values may be imprecise or uncertain; (d) imperfect information on resources availability and requirements may be handled; (e) each group member may have their own perception about the availability of resources and the requirement of resources per activity. An important application of the new approach is collective multi-objective project portfolio optimization. This is illustrated by solving a real size group many-objective project portfolio optimization problem using evolutionary computation tools.

scholarly journals Braille Block Detection via Multi-Objective Optimization from an Egocentric Viewpoint

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2775
Author(s):  
Tsubasa Takano ◽  
Takumi Nakane ◽  
Takuya Akashi ◽  
Chao Zhang
Keyword(s):  
Optimization Problem ◽  
Line Pair ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Optimization Framework ◽  
Visually Impaired People ◽  
Comprehensive Comparison ◽  
Basic Characteristics ◽  
Support Devices

In this paper, we propose a method to detect Braille blocks from an egocentric viewpoint, which is a key part of many walking support devices for visually impaired people. Our main contribution is to cast this task as a multi-objective optimization problem and exploits both the geometric and the appearance features for detection. Specifically, two objective functions were designed under an evolutionary optimization framework with a line pair modeled as an individual (i.e., solution). Both of the objectives follow the basic characteristics of the Braille blocks, which aim to clarify the boundaries and estimate the likelihood of the Braille block surface. Our proposed method was assessed by an originally collected and annotated dataset under real scenarios. Both quantitative and qualitative experimental results show that the proposed method can detect Braille blocks under various environments. We also provide a comprehensive comparison of the detection performance with respect to different multi-objective optimization algorithms.

Natural Transition Phenomena on an Axial Compressor Blade

2000 ◽  
Author(s):  
J. D. Hughes ◽  
G. J. Walker
Keyword(s):  
Guide Vane ◽  
Axial Compressor ◽  
Inlet Guide Vane ◽  
Instability Wave ◽  
Blade Loading ◽  
Instability Waves ◽  
Transition Prediction ◽  
Tollmien Schlichting ◽  
Vane Clocking ◽  
Hot Film

Data from a surface hot-film array on the outlet stator of a 1.5 stage axial compressor are analyzed to look for direct evidence of natural transition phenomena. An algorithm is developed to identify instability waves within the Tollmien Schlichting (T-S) frequency range. The algorithm is combined with a turbulent intermittency detection routine to produce space∼time diagrams showing the probability of instability wave occurrence prior to regions of turbulent flow. The paper compares these plots for a range of blade loading, with free-stream conditions corresponding to the maximum and minimum inflow disturbance periodicity produced by inlet guide vane clocking. Extensive regions of amplifying instability waves are identified in nearly all cases. The implications for transition prediction in decelerating flow regions on axial turbomachine blades are discussed.

Analyzing the Objective Functions for Multi-Objective Optimization of the Amplifier Adaptive Control of Operating Point

2021 ◽  
Author(s):  
Erick A. Barboza ◽  
Carmelo J. A. Bastos-Filho ◽  
Daniel A. R. Chaves ◽  
Joaquim F. Martins-Filho ◽  
Leonardo D. Coelho ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Operating Point ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective

Accommodation of Multi-Shaft Gas Turbine Switching Control Gain Tuning Problem to IGV Position

2021 ◽  
Author(s):  
Yujia Ma ◽  
Liu Jinfu ◽  
Linhai Zhu ◽  
Qi Li ◽  
Huanpeng Liu ◽  
...  
Keyword(s):  
Gas Turbine ◽  
Guide Vane ◽  
Optimization Procedure ◽  
Switching Control ◽  
Inlet Guide Vane ◽  
Multi Objective ◽  
Control Gain ◽  
Controller Gain ◽  
Compressor Inlet ◽  
Comprehensive Indicator

Abstract This article aims to discuss the influence of compressor Inlet Guide Vane (IGV) position on gas turbine switching control system gain tuning problem. The distinction between IGV and normally reckoned working conditions is differentiated, and an improved double-layer LPV model is proposed to estimate the protected parameters under various IGV positions. Controller gain tuning is conducted with single and multi-objective intellectual optimization algorithms. Simulation results reveal that normally used multi-objective optimization procedure is unnecessary and time-consuming. While with the comprehensive indicator introduced in this paper, the calculation burden can be greatly eased. This improvement is especially advantageous when tuning work is carried out under multiple IGV positions.

Aerothermal Optimization of Fully Cooled Turbine Blade Tips

2019 ◽  
Vol 141 (6) ◽  
Author(s):  
Valeria Andreoli ◽  
James Braun ◽  
Guillermo Paniagua ◽  
Cis De Maesschalck ◽  
Matthew Bloxham ◽  
...  
Keyword(s):  
Turbine Blade ◽  
Heat Load ◽  
Performance Enhancement ◽  
Navier Stokes ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Hexahedral Elements ◽  
Sst Model ◽  
Blade Tip ◽  
Novel Strategy

Optimal turbine blade tip designs have the potential to enhance aerodynamic performance while reducing the thermal loads on one of the most vulnerable parts of the gas turbine. This paper describes a novel strategy to perform a multi-objective optimization of the tip geometry of a cooled turbine blade. The parameterization strategy generates arbitrary rim shapes around the coolant holes on the blade tip. The tip geometry performance is assessed using steady Reynolds-averaged Navier–Stokes simulations with the k–ω shear stress transport (SST) model for the turbulence closure. The fluid domain is discretized with hexahedral elements, and the entire optimization is performed using identical mesh characteristics in all simulations. This is done to ensure an adequate comparison among all investigated designs. Isothermal walls were imposed at engine-representative levels to compute the convective heat flux for each case. The optimization objectives were a reduction in heat load and an increase in turbine row efficiency. The multi-objective optimization is performed using a differential evolution strategy. Improvements were achieved in both the aerodynamic efficiency and heat load reduction, relative to a conventional squealer tip arrangement. Furthermore, this work demonstrates that the inclusion of over-tip coolant flows impacts the over-tip flow field, and that the rim–coolant interaction can be used to create a synergistic performance enhancement.

A New Loss and Deviation Model for Axial Compressor Inlet Guide Vanes

2013 ◽  
Author(s):  
Milan Banjac ◽  
Milan V. Petrovic ◽  
Alexander Wiedermann
Keyword(s):  
Guide Vane ◽  
Thickness Distribution ◽  
Axial Compressor ◽  
Algebraic Model ◽  
Operating Conditions ◽  
Inlet Guide Vane ◽  
Viscous Effects ◽  
Through Flow ◽  
Trailing Vortices ◽  
Compressor Inlet

This paper describes a new universal algebraic model for the estimation of flow deflection and losses in axial compressor inlet guide vane devices. The model deals with nominal flow and far-off-design operating conditions in connection with large stagger angle adjustments. The first part of the model considers deflection and losses in 2D cascades, taking into account the main cascade geometry parameters and operating conditions, such as Mach number and stagger adjustment. The second part of the model deals with additional deviation and losses due to secondary flow caused by the endwall viscous effects and by the trailing vortices. The model is developed for NACA65 airfoils, NACA63-A4K6 airfoils and airfoils having an NACA65 thickness distribution on a circular-arc camber line. It is suitable for application in 1D or 2D through-flow calculations for design and analysis cases. The development of the method is based on systematic CFD flow calculations for various cascade geometries and operating parameters. The comparison of correlation results with experimental data for several test cases shows good agreement.

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