scholarly journals Aerodynamic Shape Multi-Objective Optimization for SAE Aero Design Competition Aircraft

2021 ◽  
Author(s):  
Ruben Fernandez ◽  
Hernando Lugo ◽  
Georfe Dulikravich
Keyword(s):  
Aerodynamic Drag ◽  
Pitching Moment ◽  
Multi Objective Optimization ◽  
Cfd Simulations ◽  
Ansys Fluent ◽  
Multi Objective ◽  
Regular Class ◽  
Design Variables ◽  
Design Competition ◽  
Aerodynamic Lift

The SAE Regular Class Aero Design Competition requires students to design a radio-controlled aircraft with limits to the aircraft power consumption, take-off distance, and wingspan, while maximizing the amount of payload it can carry. As a result, the aircraft should be designed subject to these simultaneous and contradicting objectives: 1) minimize the aerodynamic drag force, 2) minimize the aerodynamic pitching moment, and 3) maximize the aerodynamic lift force. In this study, we optimized the geometric design variables of a biplane configuration using 3D aerodynamic analysis using the ANSYS Fluent. Coefficients of lift, drag, and pitching moment were determined from the completed 3D CFD simulations. Extracted coefficients were used in modeFRONTIER multi-objective optimization software to find a set of non-dominated (Pareto-optimal or best trade-off) optimized 3D aircraft shapes from which the winner was selected based to the desired plane performance.

The Finite Element Analysis and the Multi-Objective Optimization Design of Spindle Systems of CNC Gantry Machine Tools

2016 ◽  
Vol 693 ◽  
pp. 243-250
Author(s):  
Zhi Zhong Guo ◽  
Yun Shun Zhang ◽  
Shi Hao Liu
Keyword(s):  
Machine Tools ◽  
Optimization Design ◽  
Multi Objective Optimization ◽  
Element Analysis ◽  
Multi Objective ◽  
Vibration Resistance ◽  
Design Variables ◽  
Force Coupling ◽  
The Finite Element Analysis ◽  
Spindle Structure

It is discovered that the vibration resistance of spindle systems needs to be improved based on the statics analysis, modal analysis and heating-force coupling analysis of spindle systems of CNC gantry machine tools. The design variables of optimization are set according to sensitivity analysis, multi-objective and dynamic optimization design is realized and its designing scheme is gained for spindle structure. The research results show that vibration resistance can be improved without change of the quality and static property of spindle systems of CNC gantry machine tools.

Multi-objective optimization of a sports car suspension system using simplified quarter-car models

2020 ◽  
Vol 21 (4) ◽  
pp. 412
Author(s):  
Salman Ebrahimi-Nejad ◽  
Majid Kheybari ◽  
Seyed Vahid Nourbakhsh Borujerd
Keyword(s):  
Numerical Solutions ◽  
Suspension System ◽  
Mode Shapes ◽  
Ride Quality ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Characteristic Roots ◽  
Design Variables ◽  
Stiffness Matrices ◽  
Quarter Car

In this paper, first, the vibrational governing equations for the suspension system of a selected sports car were derived using Lagrange's Equations. Then, numerical solutions of the equations were obtained to find the characteristic roots of the oscillating system, and the natural frequencies, mode shapes, and mass and stiffness matrices were obtained and verified. Next, the responses to unit step and unit impulse inputs were obtained. The paper compares the effects of various values of the damping coefficient and spring stiffness in order to identify which combination causes better suspension system performance. In this regard, we obtained and compared the time histories and the overshoot values of vehicle unsprung and sprung mass velocities, unsprung mass displacement, and suspension travel for various values of suspension stiffness (KS ) and damping (CS ) in a quarter-car model. Results indicate that the impulse imparted to the wheel is not affected by the values of CS and KS . Increasing KS will increase the maximum values of unsprung and sprung mass velocities and displacements, and increasing the value of CS slightly reduces the maximum values. By increasing both KS and CS we will have a smaller maximum suspension travel value. Although lower values of CS provide better ride quality, very low values are not effective. On the other hand, high values of CS and KS result in a stiffer suspension and the suspension will provide better handling and agility; the suspension should be designed with the best combination of design variables and operation parameters to provide optimum vibration performance. Finally, multi-objective optimization has been performed with the approach of choosing the best value for CS and KS and decreasing the maximum accelerations and displacements of unsprung and sprung masses, according to the TOPSIS method. Based on optimization results, the optimum range of KS is between 130 000–170 000, and the most favorable is 150, and 500 is the optimal mode for CS .

Approximate Multi-Objective Optimization of Medical Foot Support: Case of 3D Shape Optimization

2009 ◽  
Author(s):  
Shin-ichiro Miyake ◽  
Suguru Nakao ◽  
Masao Arakawa
Keyword(s):  
Physical Therapists ◽  
Daily Life ◽  
Radial Basis Function Network ◽  
Medical Doctors ◽  
Multi Objective Optimization ◽  
3D Shape ◽  
Multi Objective ◽  
Maximum Reduction ◽  
Design Variables ◽  
Function Network

Splayfoot seems not serious diseases. However, it cause fatigue in the daily life. In that sense, if we can solve these problems it might support daily life much comfortable especially for elder people. To support splayfoot, there are some commercial ones. But they just add small amount of support and not made up for each person. Besides, when the height of support is not suitable for patients, it sometimes makes situation worse. We have tried it and measured by using myoelectric potential measurements, and see differences of three patients. Even if we use the same commercial support its effectiveness differs to each other and sometimes it makes worse. Physical therapists make foot support for each patient but they make them owing to their experience. There are studies on the positions of bone of foot and its portrait of the desired positions has been reported by medical doctors. One of them is called Mizuno standard [1]. In the previous study, we tried to design foot support aiming to make portrait of this standard in vertical space. For that purpose, we used approximate multi-objective optimization using Radial Basis Function network. For validation, we used electromyography again. As a result the foot support by the proposed method showed the maximum reduction in integral of myoelectric. However, in the previous study [2], we only used two design variables, and we have only designed vertical phase. Therefore, we have not completely designed the support. In this study, we use 3D spline expression to make support, and try to design 3D shape of support. In validation, the results of approximate multi-objective optimization show the best reduction in integral of myoelectric, and show the effectiveness of the proposed method.

Robustness Against Large Variations in Multi-Objective Optimization Problems

2013 ◽  
Author(s):  
Weijun Wang ◽  
Stéphane Caro ◽  
Fouad Bennis
Keyword(s):  
Optimization Problems ◽  
Optimal Solutions ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Design Environment ◽  
Multi Objective ◽  
Uncertainty Sources ◽  
Design Variables ◽  
Robustness Index ◽  
Environment Parameters

In the presence of multiple optimal solutions in multi-modal optimization problems and in multi-objective optimization problems, the designer may be interested in the robustness of those solutions to make a decision. Here, the robustness is related to the sensitivity of the performance functions to uncertainties. The uncertainty sources include the uncertainties in the design variables, in the design environment parameters, in the model of objective functions and in the designer’s preference. There exist many robustness indices in the literature that deal with small variations in the design variables and design environment parameters, but few robustness indices consider large variations. In this paper, a new robustness index is introduced to deal with large variations in the design environment parameters. The proposed index is bounded between zero and one, and measures the probability of a solution to be optimal with respect to the values of the design environment parameters. The larger the robustness index, the more robust the solution with regard to large variations in the design environment parameters. Finally, two illustrative examples are given to highlight the contributions of this paper.

Multi-Objective Optimization of a Segmented Lunar Wheel Concept

2011 ◽  
Author(s):  
Michele Faragalli ◽  
Damiano Pasini ◽  
Peter Radzizsewski
Keyword(s):  
Optimization Problem ◽  
Element Model ◽  
Multi Objective Optimization ◽  
Stress Concentrations ◽  
Multi Objective ◽  
Optimization Framework ◽  
Multi Objective Genetic Algorithm ◽  
Design Variables ◽  
Rider Comfort ◽  
Original Concept

The goal of this work is to develop a systematic method for optimizing the structural design of a segmented wheel concept to improve its operating performance. In this study, a wheel concept is parameterized into a set of size and shape design variables, and a finite element model of the wheel component is created. A multi-objective optimization problem is formulated to optimize its directional compliance and reduce stress concentrations, which has a direct affect on the efficiency, traction, rider comfort, maneuverability, and reliability of the wheel. To solve the optimization problem, a Matlab-FE simulation loop is built and a multi-objective genetic algorithm is used to find the Pareto front of optimal solutions. A trade-off design is selected which demonstrates an improvement from the original concept. Finally, recommendations will be made to apply the structural optimization framework to alternative wheel conceptual designs.

Shaft Shape Multi Objective Optimization Based on Bacterial Chemotaxis

2010 ◽  
Author(s):  
Maria Alejandra Guzma´n Pardo ◽  
Rodrigo Nicoletti ◽  
Jonas de Carvalho
Keyword(s):  
Bacterial Chemotaxis ◽  
Optimization Methods ◽  
Multi Objective Optimization ◽  
Safety Factors ◽  
Design Constraints ◽  
Multi Objective ◽  
Chemical Gradients ◽  
Design Variables ◽  
Final Weight ◽  
Living Organisms

Chemotaxis is the biased movement developed by certain living organisms as a response to chemical gradients present in their environment. Thanks to advances in the computing field, bacterial chemotactical strategies and its excellent ability in searching can be modeled, simulated and emulated, thus developing bio-inspired optimization methods alternatively to classical methods. In this work, a multi objective optimization algorithm based on bacterial chemotaxis is proposed and applied to the shape optimization of shafts. Design variables are the diameters along shaft’s length and different constraints are tested, such as variable torques, critical velocities, and position of elements. The design results are obtained in terms of final weight and design safety factors at specific points of the shaft, thus leading to a front of optimum solutions, i.e. to the different possible design solutions that satisfy design constraints, where the engineer can find the best compromise solution for his application.

Aerodynamic optimization to tandem stators by using sweep and dihedral

2020 ◽  
Vol 234 (6) ◽  
pp. 1225-1236
Author(s):  
Jinouwen Zhang ◽  
Haowan Zhuang ◽  
Jinfang Teng ◽  
Mingmin Zhu ◽  
Xiaoqing Qiang
Keyword(s):  
Gaussian Process ◽  
Surrogate Model ◽  
Aerodynamic Performance ◽  
High Dimensional ◽  
Two Dimensional ◽  
Multi Objective Optimization ◽  
Optimization Scheme ◽  
Multi Objective ◽  
Design Variables ◽  
Dimensional Optimization

In the modern aerodynamic design of turbomachinery blades, the geometries of blades often need to be reshaped to achieve better aerodynamic performance by introducing extra parametric design variables. A higher variable dimension will lead to a larger sampling range as well as a sparser sample distribution, which challenges the effectiveness and stability of optimization schemes based on surrogate model by making the model prediction quality even poorer. In this paper, a multi-objective optimization based on Gaussian process model was carried out for a high dimensional design space. Based on the previous two-dimensional optimization, tandem stators of a modern compressor were optimized by the design of sweep and dihedral. The purpose of the study is to improve the aerodynamic performance of the compressor tandem stators as well as to provide an effective optimization scheme for high dimensional multi-objective optimization problems. The design of sweep and dihedral for reshaping the tandem stators consists of a total of 18 design variables. An improvement in total pressure recovery coefficient of at least 0.7% at positive incidence and at least 0.3% at negative incidence was obtained, much larger than that in the previous two-dimensional optimization. The optimization process shows that, by using Gaussian process as the surrogate model and a special sampling strategy, this optimization scheme is effective and efficient to handle this high dimensional space. The aerodynamic influences of design parameters of tandem blades were analyzed in detail and the superiority of sweep and dihedral in reducing aerodynamic loss was confirmed.

scholarly journals Multi-Objective Optimization of Off-Grid Hybrid Renewable Energy Systems in Buildings with Prior Design-Variable Screening

Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 3026 ◽  
Author(s):  
Paolo Conti ◽  
Giovanni Lutzemberger ◽  
Eva Schito ◽  
Davide Poli ◽  
Daniele Testi
Keyword(s):  
Renewable Energy ◽  
Design Problem ◽  
Net Present Value ◽  
Renewable Energy Sources ◽  
Optimization Strategy ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Specific Investment ◽  
Design Variables ◽  
Electrochemical Storage

This work presents an optimization strategy and the cost-optimal design of an off-grid building served by an energy system involving solar technologies, thermal and electrochemical storages. Independently from the multi-objective method (e.g., utility function) and algorithm used (e.g., genetic algorithms), the optimization of this kind of systems is typically characterized by a high-dimensional variables space, computational effort and results uncertainty (e.g., local minimum solutions). Instead of focusing on advanced optimization tools to handle the design problem, the dimension of the full problem has been reduced, only considering the design variables with a high “effect” on the objective functions. An off-grid accommodation building is presented as test case: the original six-variable design problem consisting of about 300,000 possible configurations is reduced to a two-variable problem, after the analysis of 870 Monte Carlo simulations. The new problem includes only 220 possible design alternatives with a clear benefit for the multi-objective optimization algorithm. The energy-economy Pareto frontiers obtained by the original and the reduced problems overlap, showing the validity of the proposed methodology. The No-RES (no renewable energy sources) primary energy consumption can be reduced up to almost 0 kWh/(m2yr) and the net present value (NPV) after 20 years can reach 70 k€ depending on the number of photovoltaic panels and electrochemical storage size. The reduction of the problem also allows for a plain analysis of the results and the drawing of handy decision charts to help the investor/designer in finding the best design according to the specific investment availability and target performances. The configurations on the Pareto frontier are characterized by a notable electrical overproduction and a ratio between the two main design variables that goes from 4 to 8 h. A sensitivity analysis to the unitary price of the electrochemical storage reveals the robustness of the sizing criterion.

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