The Fuzzy Reliability Optimum Design of Offshore Jacket Platforms

2002 ◽  
Author(s):  
Gangjun Zhai ◽  
Haigui Kang ◽  
Facong Xu
Keyword(s):  
Optimum Design ◽  
Structural Reliability ◽  
Fuzzy Optimization ◽  
Optimization Method ◽  
Optimum Level ◽  
Design Variables ◽  
Fuzzy Constraint ◽  
Cut Set ◽  
Optimum Model ◽  
Optimum Solution

In consideration of the fuzzy constraint boundary and through analysis of structural reliability, a model of structural fuzzy optimum design is established based on reliability for offshore jacket platforms. According to the characteristics of offshore jacket platforms, the tolerance coefficient of the constraint boundary is determined with the fuzzy optimization method. The optimum level cut set λ*, which is the intersection of the fuzzy constraint set and fuzzy objective set, is determined with the bound search method, and then the fuzzy optimum solution of fuzzy optimization problem is obtained. The center offshore platform SZ36-1 is designed with the fuzzy optimum model based on reliability above; the results are compared with those from deterministic optimum design and fuzzy optimum design. The tendency of design variables and its reasons in the above three methods are analyzed. The results of an example show that the fuzzy optimum design based on reliability is stable and reliable.

Description and Optimum Design of Fuzzy Mechanical Systems

1987 ◽  
Vol 109 (1) ◽  
pp. 126-132 ◽  
Author(s):  
S. S. Rao
Keyword(s):  
Optimum Design ◽  
Fuzzy Set ◽  
Mechanical Systems ◽  
Fuzzy Optimization ◽  
Optimization Techniques ◽  
Fuzzy Constraints ◽  
Constraint Set ◽  
Fuzzy Constraint ◽  
Optimum Solution ◽  
Set Of Points

Much of the decision-making in the real world takes place in an environment in which the goals, the constraints and the consequences of possible actions are not known precisely. To deal quantitatively with imprecision, the tools of fuzzy set theory can be used. This paper deals with the description and optimization of mechanical systems containing fuzzy information. The fuzzy constraints define a fuzzy feasible domain in the design space and hence the fuzzy optimum solution will be defined by a fuzzy set of points. In this work, two methods are presented for solving a fuzzy optimization problem using ordinary optimization techniques. The optimum design of a four-bar function generating mechanism with fuzzy objective function and fuzzy constraint set is considered to illustrate the procedures.

A Study on Optimum Design Using Fuzzy Numbers As Design Variables

1995 ◽  
Author(s):  
Masao Arakawa ◽  
Hiroshi Yamakawa
Keyword(s):  
Fuzzy Sets ◽  
Optimum Design ◽  
Fuzzy Numbers ◽  
Fuzzy Optimization ◽  
Design Parameters ◽  
Numerical Examples ◽  
Design Variables ◽  
Conventional Methods

Abstract In this study, we summerize the method of fuzzy optimization using fuzzy numbers as design variables. In order to detect flaw in fuzzy calculation, we use LR-fuzzy numbers, which is known as its simplicity in calculation. We also use simple fuzzy numbers’ operations, which was proposed in the previous papers. The proposed method has unique characteristics that we can obtain fuzzy sets in design variables (results of the design) directly from single numerical optimizing process. Which takes a large number of numerical optimizing processes when we try to obtain similar results in the conventional methods. In the numerical examples, we compare the proposed method with several other methods taking imprecision in design parameters into account, and demonstrate the effectiveness of the proposed method.

Fuzzy Optimization Design on Stranded Wire Helical Spring of High-Frequency Vibration Sieve

2010 ◽  
Vol 97-101 ◽  
pp. 4066-4070 ◽  
Author(s):  
Xiao Xin Gong ◽  
Yan Nian Rui ◽  
Ying Ping He
Keyword(s):  
High Frequency ◽  
Optimization Design ◽  
Fuzzy Theory ◽  
Fuzzy Optimization ◽  
Helical Spring ◽  
High Frequency Vibration ◽  
Vibration Resistance ◽  
Design Variables ◽  
The Common ◽  
Optimum Solution

When the common cylindrical helical spring is used in high-frequency vibration sieve for slime dewatering, there are many problems such as poor vibration resistance, easy happening fatigue fracture, etc. In order to solve these problems, this paper uses the stranded wire helical spring as a support instead, and applies fuzzy theory method to get the optimization design. By selecting the design variables correlated with spring and determining the objective function together with the constraint conditions, the fuzzy optimization mathematical model is built and the optimum solution is obtained so as to achieve the perfect results of optimization.

An approach to weight optimization of a spur gear

2016 ◽  
Vol 231 (2) ◽  
pp. 189-202 ◽  
Author(s):  
S Panda ◽  
BB Biswal ◽  
SD Jena ◽  
D Mishra
Keyword(s):  
Optimum Design ◽  
Failure Modes ◽  
Differential Evolution Algorithm ◽  
Spur Gear ◽  
Weight Optimization ◽  
Element Analysis ◽  
Design Variables ◽  
Stress Region ◽  
Objective Function Values ◽  
Optimum Solution

Lightweight is one of the most important criterion in the optimum design of gear set for motorsport and aerospace application. A tradeoff between optimum weight and failure modes of gear is a subject of interest for researchers and the industry. In the present work weight of a single-stage spur gear set is optimized. This nonlinear constrained optimization formulation has been solved by using differential evolution algorithm. A total of six design variables corresponding to gear geometry and material property are considered. The results obtained are compared with those of published heuristics like genetic algorithm, simulated annealing, and particle swarm optimization algorithm, respectively. The optimization is performed in such a way that the design variables satisfy all constraints at optimum solution. Apart from this, several constraints related to scoring are included in the optimization. The constraint violation study is performed to prioritize the constraints. The sensitivity analysis is carried out to see the effect of manufacturing tolerances of design variables on weight of the gear set. The optimality of the solution has been ensured through the convergence study. The optimization reveals that the reported results are also encouraging in terms of objective function values and CPU time. In addition, the optimum design variables obtained through the weight optimization of spur gear set are used for preparation of a CAD model. Then the stress analysis using finite element analysis is performed on the gear set to identify the critical stress region in the optimized gear set.

Optimization Design of Cantilever Supporting Structure

2013 ◽  
Vol 357-360 ◽  
pp. 2410-2413
Author(s):  
Wei Xu ◽  
Jian Sheng Feng ◽  
Fei Fei Feng
Keyword(s):  
Genetic Algorithm ◽  
Optimization Design ◽  
Design Method ◽  
Optimal Solution ◽  
Optimization Method ◽  
Original Design ◽  
Supporting Structure ◽  
Primary Object ◽  
Design Variables ◽  
Optimum Solution

The primary object of this fundamental research is to reveal the application of genetic algorithm improved on the optimization design of cantilever supporting structure. In order to meet the strength of pile body and pile top displacement as well as design variables subjected to constraint, an algorithm is carried on to seek the optimum solution and relevant examples by means of comprehensively considering the effects on center-to-center spacing between piles,pile diameter and quantity of distributed steel, which is taken the lowest engineering cost as objective function. Through the comparison of the optimized scheme and original design, this fruitful work provides explanation to the effectiveness of genetic algorithm in optimization design. These findings of the research lead to the conclusion that the shortcomings of traditional design method is easy to fall into local optimal solution. The new optimization method can overcome this drawback.

scholarly journals Antioptimisation of Trusses Using Two-Level Population-Based Incremental Learning

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Phinit Tontragunrat ◽  
Sujin Bureerat
Keyword(s):  
Optimum Design ◽  
Incremental Learning ◽  
Population Based ◽  
Numerical Results ◽  
Level Population ◽  
Case Scenario ◽  
Worst Case ◽  
Worst Case Scenario ◽  
Design Variables ◽  
Optimum Solution

Practical optimum design of structures often involves parameters with uncertainties. There have been several ways to deal with such optimisation problems, and one of the approaches is an antioptimisation process. The task is to find the optimum solution of common design variables while simultaneously searching for the worst case scenario of those parameters with uncertainties. This paper proposed a metaheuristic based on population-based incremental learning (PBIL) for solving antioptimisation of trusses. The new algorithm is called two-level PBIL which consists of outer and inner loops. Five antioptimisation problems are posed to test the optimiser performance. The numerical results show that the concept of using PBIL probability vectors for handling the antioptimisation of truss is powerful and effective. The two-level PBIL can be considered a powerful optimiser for antioptimisation of trusses.

Optimum Design of Interior Permanent Magnet Motor for Automotive Cooling Device

2012 ◽  
Vol 260-261 ◽  
pp. 581-586 ◽  
Author(s):  
Ju Seong Yu ◽  
Han Wook Cho
Keyword(s):  
Permanent Magnet ◽  
Optimum Design ◽  
Optimization Method ◽  
Permanent Magnet Motor ◽  
Order Model ◽  
Cooling Device ◽  
Brushless Motor ◽  
Design Variables ◽  
Interior Permanent Magnet ◽  
Interior Permanent Magnet Motor

In this paper, we developed stator and rotor shapes of interior permanent magnet type brushless motor for automotive cooling device in order to obtain better performance than the prototype. Response surface methodology (RSM) is employed in this paper as an optimization method. Finite element computations have been used for numerical experiments on geometrical design variables in order to determine the coefficients of a second order model for the RSM. The optimum design results confirm that desirable improvements in cogging torque, back-EMF and THD are achieved.

scholarly journals Enumeration search method for optimisation of stacking sequence of laminated composite plates subjected to buckling

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Joko Sedyono ◽  
Homayoun Hadavinia ◽  
Demetrios Venetsanos ◽  
Denis R. Marchant
Keyword(s):  
Uniaxial Compression ◽  
Optimum Design ◽  
Plate Theory ◽  
Composite Plates ◽  
Global Optimum ◽  
Search Method ◽  
Laminated Plate ◽  
Compression Load ◽  
Design Variables ◽  
Optimum Solution

AbstractEnumeration search method (ESM) checks all possible combinations of design variables in a bottom-up approach until it finds the global optimum solution for the design conditions. In this paper an optimum design of a multilayered laminated plate made of unidirectional fibre reinforced polymer (FRP) composite subject to uniaxial compression is sought.ESMtogether with classical laminated plate theory (CLPT) has been used to find the lightest laminate for maximizing the buckling load capable of providing structural stability for a set target uniaxial compression load. The choice of the design variables is limited to 4 possible fibres orientation angles (0,90,-45,+45) and the sequence of the laminate, making the problem an integer programming. Experimental and finite element analyses were used to verify the optimum solution. It has been shown that the exhaustive enumeration search method is a powerful tool for finding the global optimum design.

Development of Global Optimization Method for Design of Turbine Stages

2005 ◽  
Author(s):  
Hiroyuki Kawagishi ◽  
Kazuhiko Kudo
Keyword(s):  
Genetic Algorithm ◽  
Global Optimization ◽  
Simulated Annealing ◽  
Optimum Design ◽  
Optimization Method ◽  
Global Optimum ◽  
Global Optimization Method ◽  
Optimum Solution ◽  
Global Optimum Solution ◽  
Number Of Iterations

A new optimization method which can search for the global optimum solution and decrease the number of iterations was developed. The performance of the new method was found to be effective in finding the optimum solution for single- and multi-peaked functions for which the global optimum solution was known in advance. According to the application of the method to the optimum design of turbine stages, it was shown that the method can search the global optimum solution at approximately one seventh of the iterations of GA (Genetic Algorithm) or SA (Simulated Annealing).

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