Resistance Optimization of Fishing Boat Based on Parametric Modeling Method and Sensitivity Analysis

2021 ◽  
Vol 55 (6) ◽  
pp. 117-128
Author(s):  
Guan Guan ◽  
Shuai Zhou ◽  
Zhengmao Zhuang ◽  
Qu Yang
Keyword(s):  
Sensitivity Analysis ◽  
Shape Optimization ◽  
Parametric Modeling ◽  
Modeling Method ◽  
Orthogonal Experimental Design ◽  
Range Analysis ◽  
Fishing Boat ◽  
Design Variables ◽  
Minimum Resistance ◽  
Selection Of

Abstract In the conventional process of parametric ship optimization, the selection of design variables mostly relies on design experience. The lack of a clear and quantitative method of parameter selection leads to a certain degree of blindness and inefficiency. In this article, a parametric hull modeling method is proposed. The sensitivity analysis based on orthogonal experimental design is performed to select the design variables of optimization. Through variance and range analysis, the parameters that have a significant influence on the optimization objective are selected as the design variables. A combination of Sobol and tangent search method is applied during the optimization. The shape optimization of a fishing boat with minimum resistance is taken as an example. The optimization result proves the efficiency of the proposed parametric modeling method and the sensitivity analysis, which are significant for the shape optimization of a fishing boat.

An Algorithm for Automated Design Variable Selection in Structural Shape Optimization With Intrinsically Defined Geometry

1995 ◽  
Author(s):  
James M. Widmann ◽  
Sheri D. Sheppard
Keyword(s):  
Shape Optimization ◽  
Optimization Problems ◽  
Analysis Model ◽  
Structural Shape ◽  
Structural Shape Optimization ◽  
Design Variables ◽  
Sufficient Set ◽  
Compatibility Constraint ◽  
Selection Of

Abstract A major difficulty encountered in the shape optimization of structural components is the selection of an adequate set of shape design variables. The quality of the solution and the value of the optimal objective function depend on the chosen set of design variables. This paper presents an algorithm for the automated selection of intrinsically defined design variables to solve two-dimensional structural shape optimization problems. The algorithm arrives at a sufficient set of design variables by solving a series of optimization problems. Using the results of intermediate solutions, the algorithm adaptively refines the set of design variables until the solution converges. The algorithm specifies the addition and deletion of design variables and makes use of a model compatibility constraint to determine whether the analysis model must be updated. Two examples are presented which illustrate the effectiveness of the algorithm.

Implementation of Design Sensitivity Analysis with Existing Finite Element Codes

1987 ◽  
Vol 109 (3) ◽  
pp. 385-391 ◽  
Author(s):  
K. K. Choi ◽  
J. L. T. Santos ◽  
M. C. Frederick
Keyword(s):  
Sensitivity Analysis ◽  
Finite Element ◽  
Design Sensitivity ◽  
Design Sensitivity Analysis ◽  
Cross Sectional ◽  
Design Variables ◽  
Accurate Design ◽  
Analysis Theory ◽  
Problem Design ◽  
Selection Of

A numerical method is presented to implement structural design sensitivity analysis theory, using the versatility and convenience of existing finite element structural analysis programs. Design variables such as thickness and cross-sectional areas of components of individual members and built-up structures are considered. Structural performance functionals considered include displacement and stress. The method is also applicable for eigenvalue problem design sensitivity analysis. It is shown that calculations can be carried out outside existing finite element codes, using postprocessing data only. Thus design sensitivity analysis software does not have to be imbedded in an existing finite element code. Feasibility of the method is shown through analysis of several problems, including a built-up structure. Accurate design sensitivity results are obtained without the uncertainty of numerical accuracy associated with selection of finite difference perturbations.

Application of a Decomposition Technique for Treating a Shape Optimization Problem

1989 ◽  
Author(s):  
M. Bremicker ◽  
H. Eschenauer
Keyword(s):  
Sensitivity Analysis ◽  
Shape Optimization ◽  
Optimization Problem ◽  
Optimization Methods ◽  
Objective Functions ◽  
Shape Optimization Problem ◽  
Boundary State ◽  
Design Variables ◽  
Dimensional Shape ◽  
Suitable Approximation

Abstract The range of application of structural optimization methods can be considerably enlarged by using decomposition techniques. In this paper a novel procedure is introduced to deal with such problems more efficiently. The mechanical structure resp. system is divided into several subsystems splitting up the design variables, objective functions, and constraints accordingly. The boundary state quantities of the subsystems and the global (i.e. subsystem overlapping) functions are approximated by a sensitivity analysis of the entire system using suitable approximation concepts. It is thus possible to optimize the subsystems independently. Variables, objective functions and constraints can be chosen arbitrarily; all coupling information is obtained from the sensitivity analysis by means of global information. The application of this technique is demonstrated by a two-dimensional shape optimization problem.

Application of Orthogonal Experimental Design on Reliability and Sensitivity Analysis

2011 ◽  
Vol 211-212 ◽  
pp. 651-655 ◽  
Author(s):  
Qin Shu He ◽  
Xi Nen Liu ◽  
Shi Fu Xiao
Keyword(s):  
Sensitivity Analysis ◽  
Experimental Design ◽  
Structural Parameters ◽  
Orthogonal Experimental Design ◽  
Random Input ◽  
Range Analysis ◽  
First Order ◽  
Reliability Method ◽  
Structural Responses ◽  
Input Variables

In the present paper, the effects of four structural parameters at three levels on the reliability and sensitivity of structure are investigated. Sensitivity of parameters is achieved by the range analysis and the significance of parameters is achieved by the variance analysis. A response surface based on orthogonal experimental design and finite element calculations is elaborated so that the relation between the random input variables and structural responses could be established. The First-Order Reliability Method (FORM) as an approximated method is used here to assess the reliability. Comparing with the results of Monte Carlo simulations by ANSYS for a numerical example, the effect of sensitivity analysis has been proved, while the precision of the reliability and sensitivity should be improved in the future.

Sensitivity Analysis in Shape Optimization Design for Pressure Vessel

1992 ◽  
Vol 114 (4) ◽  
pp. 428-432 ◽  
Author(s):  
L. Younsheng ◽  
L. Ji
Keyword(s):  
Sensitivity Analysis ◽  
Finite Element ◽  
Shape Optimization ◽  
Pressure Vessel ◽  
Optimization Design ◽  
Element Model ◽  
Element Analysis ◽  
Design Variables ◽  
The Finite Element Analysis ◽  
Derivatives Of

In this paper, sensitivity analysis for a finite element model during shape optimization design for a pressure vessel is discussed. The derivation is emphatically carried out for the derivatives of stiffness matrix and various load ranks with respect to design variables. Because the information resulting from the finite element analysis is fully utilized in this method, the programs are greatly simplified so that it becomes possible to carry out the shape optimization with comparatively more versatility. The conclusion is illustrated by an example.

Sensitivity Analysis and Selection of Check Index of Signal Intersection Simulation Model Based on VISSIM

2019 ◽  
Vol 2 (5) ◽  
Author(s):  
Mengda Zhang ◽  
Chenjing Zhou ◽  
Tian-tian Zhang ◽  
Yan Han
Keyword(s):  
Sensitivity Analysis ◽  
Simulation Model ◽  
Optimal Process ◽  
Parameter Calibration ◽  
Index Set ◽  
The Core ◽  
Core Module ◽  
Simulation Parameter ◽  
Simulation Parameters ◽  
Selection Of

Selecting check index quantitatively is the core of the calibration of micro traffic simulation parameters at signal intersection. Five indexes in the node (intersection) module of VISSIM were selected as the check index set. Twelve simulation parameters in the core module were selected as the simulation parameters set. Optimal process of parameter calibration was proposed and model of the intersection of Huangcun west street and Xinghua street in Beijing was built in VISSIM to verify it. The sensitivity analysis between each check index and simulation parameter in their own set was conducted respectively. Sensitive parameter sets of different check indices were obtained and compared. The results show that different indexes have different size of set, and average vehicle delay's is maximum, so it's necessary to select index quantitatively. The results can provide references for scientific selection of the check indexes and improve the study efficiency of parameter calibration.

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