Multi-objective design optimization of planar Yagi antenna using surrogate models

2013 ◽  
Author(s):  
Slawomir Koziel ◽  
Stanislav Ogurtsov
Keyword(s):  
Design Optimization ◽  
Surrogate Models ◽  
Multi Objective ◽  
Yagi Antenna

Robust Design Optimization Applied to a High Pressure Turbine Blade Based on Surrogate Modelling Techniques

2015 ◽  
Author(s):  
Frank Wagner ◽  
Arnold Kühhorn ◽  
Roland Parchem
Keyword(s):  
High Pressure ◽  
Design Optimization ◽  
Turbine Blade ◽  
Robust Design ◽  
Turbine Blades ◽  
Surrogate Models ◽  
Robust Design Optimization ◽  
High Pressure Turbine ◽  
Surrogate Modelling ◽  
Multi Objective

To achieve reverse objectives in engine design, advanced modelling and analysis methods are among the key research technologies. In the presented work, a robust design optimization of a first stage high pressure turbine blade has been carried out. This blade derives from a current production of a Rolls-Royce aero engine. The motivation of this work is to show that the methodology of robust design optimization can be applied to high pressure turbine blades. A fully automated workflow, which encapsulated the integral blade design and analysis process, has been used. The main workflow objective is a representative life value of the external surface of the blade. In addition, the workflow enables the engineering uses to consider sub objectives like mass, efficiency and life at critical locations of the blade. These can also be taken into account in the multi-objective robust design optimization. This research also focuses on the use of surrogate models, with attention to the delivery of a physically correct result. For this purpose, the validation of the applied methods has a huge significance and a toolbox was created to generate and evaluate the quality of the surrogate models. In the present case sixteen geometry parameters were considered. In order to show that this methodology is not limited to geometry variation, parameters for material specification and for boundary conditions were varied in addition. The surrogate model was trained by the workflow generated DoE-data and could be used for different kinds of optimization. As a conclusion, it has been demonstrated that the methodology can be used for the engineering design process of turbine blades, while delivering physically correct results. The different techniques for surrogate modelling were examined and compared. With the help of these surrogate models, an optimization of life, mass and efficiency with 22.5 million evaluations was possible. Finally, an overview of the methodology for the case of a real world turbine blade could be given, and an improved blade in the sense of multi-objective robust design was found.

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.

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.

Application of Multi-Objective Genetic Algorithm (MOGA) for Design Optimization of Valve Timing at Various Engine Speeds

2011 ◽  
Vol 264-265 ◽  
pp. 1719-1724 ◽  
Author(s):  
A.K.M. Mohiuddin ◽  
Md. Ataur Rahman ◽  
Yap Haw Shin
Keyword(s):  
Genetic Algorithm ◽  
Design Optimization ◽  
Robust Design Optimization ◽  
Primary Concern ◽  
Variable Valve Timing ◽  
Valve Timing ◽  
Engine Valve ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Variable Valve

This paper aims to demonstrate the effectiveness of Multi-Objective Genetic Algorithm Optimization and its practical application on the automobile engine valve timing where the variation of performance parameters required for finest tuning to obtain the optimal engine performances. The primary concern is to acquire the clear picture of the implementation of Multi-Objective Genetic Algorithm and the essential of variable valve timing effects on the engine performances in various engine speeds. Majority of the research works in this project were in CAE software environment and method to implement optimization to 1D engine simulation. The paper conducts robust design optimization of CAMPRO 1.6L (S4PH) engine valve timing at various engine speeds using multiobjective genetic algorithm (MOGA) for the future variable valve timing (VVT) system research and development. This paper involves engine modelling in 1D software simulation environment, GT-Power. The GT-Power model is run simultaneously with mode Frontier to perform multiobjective optimization.

Artificial Bee Colony (ABC) for multi-objective design optimization of composite structures

2011 ◽  
Vol 11 (1) ◽  
pp. 489-499 ◽  
Author(s):  
S.N. Omkar ◽  
J. Senthilnath ◽  
Rahul Khandelwal ◽  
G. Narayana Naik ◽  
S. Gopalakrishnan
Keyword(s):  
Design Optimization ◽  
Composite Structures ◽  
Artificial Bee Colony ◽  
Multi Objective ◽  
Bee Colony
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