Structural Optimization of Fir-Tree Root and Groove for Turbine Blade With Superellipse and P-Norm Aggregation Function

2019 ◽  
Author(s):  
Deqi Yu ◽  
Xiaojuan Zhang ◽  
Jiandao Yang ◽  
Kai Cheng ◽  
Ming Li
Keyword(s):  
Stress Concentration ◽  
Design Optimization ◽  
Finite Size ◽  
Large Family ◽  
Peak Stress ◽  
Aggregation Function ◽  
Optimization Approach ◽  
Optimization Constraints ◽  
Design Variables ◽  
Family Of Curves

Abstract Due to its finite size and the large centrifugal load, the fir-tree root is highly stressed, which leads to the possible early failure of the gas turbine and steam turbine. To find an optimized fir-tree root is an important issue for the design of the turbine structures. In this paper, a superellipse-based design optimization approach is proposed for the fir-tree root. Rather than the straight line and arc used in literature, the combination of the superellipse curve and line are employed to characterize the fir-tree root since the superellipse curve represents a large family of curves with limited parameters, which makes the design optimization easy and economic. For the design optimization, the objective function is to minimize the peak stress, which is a typical min-max problem with possible severe iterative oscillation and subsequent convergence difficulty. To avoid this problem, a P-norm aggregation function is proposed. The superellipse parameters are defined as design variables, while the stress concentration factor and the stress at root neck are specified as optimization constraints. With the P-series fir-tree root design as example, it is proved that our approach is effective to find the optimized configuration with better stress distribution and lower stress concentration.

Reliability-based design optimization of electromagnetic shielding structure using neural networks and real-coded genetic algorithm

2014 ◽  
Vol 228 (18) ◽  
pp. 3471-3481 ◽  
Author(s):  
Heeralal Gargama ◽  
Sanjay K Chaturvedi ◽  
Awalendra K Thakur
Keyword(s):  
Genetic Algorithm ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Design Optimization ◽  
Electromagnetic Shielding ◽  
Optimization Approach ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design ◽  
Design Variables ◽  
Real Coded Genetic Algorithm

The conventional approaches for electromagnetic shielding structures’ design, lack the incorporation of uncertainty in the design variables/parameters. In this paper, a reliability-based design optimization approach for designing electromagnetic shielding structure is proposed. The uncertainties/variability in the design variables/parameters are dealt with using the probabilistic sufficiency factor, which is a factor of safety relative to a target probability of failure. Estimation of probabilistic sufficiency factor requires performance function evaluation at every design point, which is extremely computationally intensive. The computational burden is reduced greatly by evaluating design responses only at the selected design points from the whole design space and employing artificial neural networks to approximate probabilistic sufficiency factor as a function of design variables. Subsequently, the trained artificial neural networks are used for the probabilistic sufficiency factor evaluation in the reliability-based design optimization, where optimization part is processed with the real-coded genetic algorithm. The proposed reliability-based design optimization approach is applied to design a three-layered shielding structure for a shielding effectiveness requirement of ∼40 dB, used in many industrial/commercial applications, and for ∼80 dB used in the military applications.

Multidisciplinary Design Optimization of Small Canister-Launched Space Launch Vehicle Using Genetic Algorithm

2013 ◽  
Vol 302 ◽  
pp. 583-588 ◽  
Author(s):  
Fredy M. Villanueva ◽  
Lin Shu He ◽  
Da Jun Xu
Keyword(s):  
Genetic Algorithm ◽  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Optimal Solution ◽  
Optimization Method ◽  
Launch Vehicle ◽  
Low Earth Orbit ◽  
Multidisciplinary Design ◽  
Optimization Approach ◽  
Design Variables

A multidisciplinary design optimization approach of a three stage solid propellant canister-launched launch vehicle is considered. A genetic algorithm (GA) optimization method has been used. The optimized launch vehicle (LV) is capable of delivering a microsatellite of 60 kg. to a low earth orbit (LEO) of 600 km. altitude. The LV design variables and the trajectory profile variables were optimized simultaneously, while a depleted shutdown condition was considered for every stage, avoiding the necessity of a thrust termination device, resulting in reduced gross launch mass of the LV. The results show that the proposed optimization approach was able to find the convergence of the optimal solution with highly acceptable value for conceptual design phase.

Structural Optimization of Fir-Tree Root and Groove for Turbine Blade With Splines and Genetic Algorithm

2016 ◽  
Author(s):  
Deqi Yu ◽  
Fengwei Li ◽  
Jiandao Yang ◽  
Kai Cheng ◽  
Weilin Shu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Optimization Technique ◽  
Peak Stress ◽  
Optimization Approach ◽  
Stress Concentrations ◽  
Spline Curves ◽  
Design Variables ◽  
Straight Line ◽  
Feature Based ◽  
Profile Optimization

The wide use of fir-tree root and groove in turbine structures prompts the expectation to find optimum configurations, which ensure that stresses are in the safe limits to avoid mechanical failure. To perform the optimization, the reasonable characterization of root configuration is required. The existing researches characterized the fir-tree root with straight line, arc or even elliptic fillet, then the parameters of these features were defined as design variables to perform root profile optimization. However, this feature-based optimization technique yields configuration which is only optimal under the feature assumption, the question why choose these feature and whether there is a better feature modeling technique is difficult to answer. In this work, instead of the feature-based method, spline curves technique is involved to characterize the root and groove configuration, and the horizontal coordinates of the control points are selected as design variables, which are modified in the vicinity of their initial values during optimization process. The objective function is to minimize the peak stress in the root and groove regions. With the Multi-island genetic algorithm, the optimal fir-tree root configuration can be obtained with better stress distributions and low stress concentrations. The proposed spline-based optimization approach may shed lights on the conceptual design of blade root and can be easily extended to other industrial equipment design.

scholarly journals Automatic Strain Gauge Balance Design Optimization Approach and Implementation Based on Integration of Software

2020 ◽  
Vol 20 (1) ◽  
pp. 22-34
Author(s):  
Guangwei Xiang ◽  
Peng Mi ◽  
Guoqing Yi ◽  
Chao Wang ◽  
Wei Liu
Keyword(s):  
Design Optimization ◽  
Design Process ◽  
Network Architecture ◽  
High Performance ◽  
Lightweight Design ◽  
Optimization Approach ◽  
Optimization Strategy ◽  
Balance Design ◽  
Design Variables ◽  
Tunnel Strain

AbstractThe traditional wind tunnel strain balance design cycle is a manual iterative process. With the experience and intuition of the designer, one solution that meets the design requirements can be selected among a small number of design solutions. This paper introduces a novel software integration-based automatic balance design optimization system (ABDOS) and its implementation by integrating professional design knowledge and experience, stepwise optimization strategy, CAD-CAE software, self-developed scripts and tools. The proposed two-step optimization strategy includes the analytical design process (ADP) and the finite element method design process (FEDP). The built-in optimization algorithm drives the design variables change and searches for the optimal structure combination meeting the design objectives. The client-server based network architecture enables local lightweight design input, task management, and result output. The high-performance server combines all design resources to perform all the solution calculations. The development of more than 10 balances that have been completed and a case study show that this method and platform significantly reduce the time for design evaluation and design-analysis-redesign cycles, assisting designers to comprehensively evaluate and improve the performance of the balance.

Multidisciplinary Design Optimization Approach for a Small Solid Propellant Launch Vehicle Conceptual Design Using Hybrid Simulated Annealing

2011 ◽  
Vol 110-116 ◽  
pp. 4765-4771 ◽  
Author(s):  
Masoud Ebrahimi ◽  
Jafar Roshanian ◽  
Farnaz Barzinpour
Keyword(s):  
Simulated Annealing ◽  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Solid Propellant ◽  
Launch Vehicle ◽  
Multidisciplinary Design ◽  
Optimization Approach ◽  
Design Variables ◽  
Base Method ◽  
Hybrid Simulated Annealing

Multidisciplinary Design Optimization (MDO) of a two-stage Small Solid Propellant Launch Vehicle (SSPLV) by simulated annealing (SA) Method is investigated. Propulsion, weight, aerodynamic (geometry) and 3degree of freedom (3DOF) trajectory simulation disciplines are used in an appropriate combination. Suitable design variables, technological-functional constraints and minimum launch weight objective function are considered. To handle constraints augmentation of constraints to cost using penalty coefficients are used. Results are compared with gradient-base method that shows the ability of SA to escape local optimums.

A New Approach to Design of a Lightweight Anthropomorphic Arm for Service Applications

2015 ◽  
Vol 7 (3) ◽  
Author(s):  
Lelai Zhou ◽  
Shaoping Bai
Keyword(s):  
Design Optimization ◽  
Integrated Design ◽  
Robot Kinematics ◽  
Strength Analysis ◽  
Optimization Approach ◽  
Element Analysis ◽  
New Approach ◽  
Design Variables ◽  
Kinematic Performance ◽  
Service Application

This paper describes a new approach to the design of a lightweight robotic arm for service applications. A major design objective is to achieve a lightweight robot with desired kinematic performance and compliance. This is accomplished by an integrated design optimization approach, where robot kinematics, dynamics, drive-train design and strength analysis by means of finite element analysis (FEA) are generally considered. In this approach, kinematic dimensions, structural dimensions, and the motors and the gearboxes are parameterized as design variables. Constraints are formulated on the basis of kinematic performance, dynamic requirements and structural strength limitations, whereas the main objective is to minimize the weight. The design optimization of a five degree-of-freedom (dof) lightweight arm is demonstrated and the robot development for service application is also presented.

Constrained Design Optimization of Rotor-Tilting Pad Bearing Systems

2010 ◽  
Vol 132 (12) ◽  
Author(s):  
Costin D. Untaroiu ◽  
Alexandrina Untaroiu
Keyword(s):  
Design Optimization ◽  
Power Loss ◽  
Optimization Design ◽  
Optimization Approach ◽  
Design Variables ◽  
Tilting Pad ◽  
Rotor Bearing ◽  
Automatic Optimization ◽  
Tilting Pad Bearings ◽  
Bearing System

Design of a rotor-bearing system is a challenging task due to various conflicting design requirements, which should be fulfilled. This study considers an automatic optimization approach for the design of a rotor supported on tilting-pad bearings. A numerical example of a rotor-bearing system is employed to demonstrate the merits of the proposed design approach. The finite element method is used to model the rotor-bearing system, and the dynamic speed-dependent coefficients of the bearing are calculated using a bulk flow code. A number of geometrical characteristics of the rotor simultaneously with the parameters defining the configuration of tilting pad bearings are considered as design variables into the automatic optimization process. The power loss in bearings, stability criteria, and unbalance responses are defined as a set of objective functions and constraints. The complex design optimization problem is solved using heuristic optimization algorithms, such as genetic, and particle-swarm optimization. Whereas both algorithms found better design solutions than the initial design, the genetic algorithms exhibited the fastest convergence. A statistical approach was used to identify the influence of the design variables on the objective function and constraint measures. The bearing clearances, preloads and lengths showed to have the highest influence on the power loss in the chosen design space. The high performance of the best solution obtained in the optimization design suggests that the proposed approach has good potential for improving design of rotor-bearing systems encountered in industrial applications.

scholarly journals Hybrid Seven-bar Press Mechanism

2018 ◽  
Vol 12 (3) ◽  
pp. 181-187
Author(s):  
M. Erkan Kütük ◽  
L. Canan Dülger
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Design Optimization ◽  
Hybrid System ◽  
Degrees Of Freedom ◽  
Dimensional Synthesis ◽  
Design Variables ◽  
Optimization Study ◽  
Metal Stamping

An optimization study with kinetostatic analysis is performed on hybrid seven-bar press mechanism. This study is based on previous studies performed on planar hybrid seven-bar linkage. Dimensional synthesis is performed, and optimum link lengths for the mechanism are found. Optimization study is performed by using genetic algorithm (GA). Genetic Algorithm Toolbox is used with Optimization Toolbox in MATLAB®. The design variables and the constraints are used during design optimization. The objective function is determined and eight precision points are used. A seven-bar linkage system with two degrees of freedom is chosen as an example. Metal stamping operation with a dwell is taken as the case study. Having completed optimization, the kinetostatic analysis is performed. All forces on the links and the crank torques are calculated on the hybrid system with the optimized link lengths

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.

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