Multi-objective structural optimization of a HAWT composite blade based on ultimate limit state analysis

2012 ◽  
Vol 26 (1) ◽  
pp. 129-135 ◽  
Author(s):  
Weifei Hu ◽  
Insik Han ◽  
Sang-Chul Park ◽  
Dong-Hoon Choi
Keyword(s):  
Structural Optimization ◽  
Limit State ◽  
Ultimate Limit State ◽  
Multi Objective ◽  
Composite Blade ◽  
Limit State Analysis ◽  
Ultimate Limit ◽  
State Analysis

scholarly journals Ultimate limit state analysis of a double-hull tanker subjected to biaxial bending in intact and collision-damaged conditions

2020 ◽  
Vol 209 ◽  
pp. 107519 ◽  
Author(s):  
Artjoms Kuznecovs ◽  
Jonas W. Ringsberg ◽  
Erland Johnson ◽  
Yasuhira Yamada
Keyword(s):  
Limit State ◽  
Ultimate Limit State ◽  
Biaxial Bending ◽  
Limit State Analysis ◽  
Double Hull ◽  
Ultimate Limit ◽  
State Analysis

scholarly journals Ultimate Limit State Analysis of Ship Structures

2019 ◽  
Author(s):  
S Sathish Kumar
Keyword(s):  
Ultimate Load ◽  
Progressive Collapse ◽  
Limit State ◽  
Structural Response ◽  
Load Factor ◽  
Ultimate Limit State ◽  
Ship Structures ◽  
Limit State Analysis ◽  
Ultimate Limit ◽  
State Analysis

Subjective and objective uncertainties are imposed on ship structures due to the random nature of the loading environment, inadequate knowledge of physical phenomena associated with loads or deviations in material properties which make reliable predictions of structural response a difficult task. Strength criteria for ships can be established by ultimate strength studies of progressive collapse analysis of finite element models under different boundary conditions with combined geometric and material nonlinearities. Load-Displacement and/or Moment-Curvature curves can be generated and the ultimate load causing failure identified as a multiple of the design load. Ultimate limit state analysis can be carried out for various combinations of parameters to identify the ultimate load factor in each case.

Applications of Vector Evaluated Genetic Algorithms (VEGA) in Ultimate Limit State Based Ship Structural Design

2014 ◽  
Author(s):  
Owen Hughes ◽  
Ming Ma ◽  
Jeom Kee Paik
Keyword(s):  
Genetic Algorithms ◽  
Structural Design ◽  
Limit State ◽  
Structural Safety ◽  
Wall Structure ◽  
Ultimate Limit State ◽  
Thin Wall ◽  
Limit States ◽  
Multi Objective ◽  
Ultimate Limit

Ship structural design often deals with multiple objectives such as weight, safety, and cost. These objectives usually conflict with each other, and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other objectives. A reasonable solution to a multi-objective problem is to investigate a set of solutions, each of which satisfies the objectives at an acceptable level without being dominated by any other solution. Genetic algorithms have been demonstrated to be particularly effective to determine excellent solutions to these problems. In this paper a multi-objective GA, called Vector Evaluated Genetic Algorithm (VEGA) is formulated and used to optimize a large and complex thin-wall structure (a complete cargo hold of a 200,000 ton oil tanker) on the basis of weight, safety and cost. The structure weight and cost and all of the stresses are calculated using a realistic finite element model. The structure adequacy is then evaluated using the ALPS/ULSAP computer program (Paik and Thayamballi, 2003) which can efficiently evaluate all six ultimate limit states for stiffened panels and grillages. This example was chosen because the initial design is severely inadequate. The results show that the proposed method can perform ultimate strength based structural optimization with multi-objectives, namely minimization of the structural weight and cost and maximization of structural safety, and also that the method is very robust.

Ultimate Limit State Based Ship Structural Design Using Multi-Objective Discrete Particle Swarm Optimization

2015 ◽  
Author(s):  
Ming Ma ◽  
Owen Hughes ◽  
Tobin McNatt
Keyword(s):  
Finite Element ◽  
Particle Swarm Optimization ◽  
Limit State ◽  
Particle Swarm ◽  
Structural Safety ◽  
Ultimate Limit State ◽  
Discrete Particle Swarm Optimization ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Ultimate Limit

Multi-objective optimization problems consist of several objectives that must be handled simultaneously. These objectives usually conflict with each other, and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other objectives. A reasonable solution to a multi-objective problem is to investigate a set of solutions, each of which satisfies the objectives at an acceptable level without being dominated by any other solution. Genetic or evolution algorithms have been demonstrated to be particularly effective to determine excellent solutions to these problems. Among many algorithms, the particle swarm optimization (PSO) has been found to be faster with less computational overhead. In this paper a multi-objective discrete particle swarm optimization is formulated and used to optimize a large and complex thin-wall structure on the basis of weight, safety and cost. The structure weight and cost are calculated using realistic finite element models. The design process has two stages: (1) the actual stresses are obtained by finite element analysis of the full ship, (2) for a midship segment of the ship (referred to as a “control cluster”) the structural safety is evaluated using the ALPS/ULSAP set of ultimate limit state criteria, and then the segment is optimized using any suitable optimization method (in this paper, the PSO method). Both stages involve iteration, but the process is arranged so as to keep the number of full ship finite element analyses to a minimum. The complete design process is illustrated for a 200,000 ton oil tanker. The numerical results show that the PSO method is very useful to perform ultimate strength based ship structural optimization with multi-objectives, namely minimization of the structural weight and cost and maximization of structural safety. The example also demonstrates that the proper definition of boundary conditions and design load cases is of paramount importance for design optimization.

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