A finite element/modal technique for nonlinear plate and stiffened panel response prediction

2001 ◽  
Author(s):  
M. McEwan ◽  
J. Wright ◽  
J. Cooper ◽  
A. Leung
Keyword(s):  
Finite Element ◽  
Response Prediction ◽  
Stiffened Panel ◽  
Nonlinear Plate

scholarly journals The Prediction of Buckling Load of Laminated Composite Hat-Stiffened Panels Under Compressive Loading by Using of Neural Networks

2018 ◽  
Vol 12 (1) ◽  
pp. 468-480 ◽  
Author(s):  
Shashi Kumar ◽  
Rajesh Kumar ◽  
Sasankasekhar Mandal ◽  
Atul K. Rahul
Keyword(s):  
Neural Network ◽  
Finite Element ◽  
Network Architecture ◽  
Laminated Composite ◽  
Buckling Load ◽  
Stiffened Panel ◽  
Stiffness Ratio ◽  
Data Set ◽  
Stiffened Panels ◽  
Structural Problems

Background:Stiffened panels are being used as a lightweight structure in aerospace, marine engineering and retrofitting of building and bridge structure. In this paper, two efficient analytical computational tools, namely, Finite Element Analysis (FEA) and Artificial Neural Network (ANN) are used to analyze and compare the results of the laminated composite 750-hat-stiffened panels.Objective:Finite Element (FE) is an efficient and versatile method for the analysis of a complex problem. FE models have been used to generate data set of four different parameters. The four parameters are extensional stiffness ratio of skin in the longitudinal direction to the transverse direction, orthotropy ratio of the panel, the ratio of twisting stiffness to transverse flexural stiffness and smeared extensional stiffness ratio of stiffeners to that of the plate.Results and Conclusion:For training of ANN, multilayer feedforward back-propagation has been used as a network function with two-hidden layers in the neural network. The good network architecture is achieved after several iterations to predict the buckling load of the stiffened panel. ANN prediction for unknown new data set is in good agreement with FEA results of different cases, which show that ANN tool can be used for the design of complex structural problems in civil engineering and optimization of the laminated composite stiffened panel.

Finite Element Analysis of Top-Hat–Stiffened Panels of Fiber-Reinforced–Plastic Boat Structures

2007 ◽  
Vol 44 (01) ◽  
pp. 16-26
Author(s):  
Ömer Eksik ◽  
R. Ajit Shenoi ◽  
Stuart S. J. Moy ◽  
Han Koo Jeong
Keyword(s):  
Finite Element ◽  
Lateral Pressure ◽  
Three Dimensional ◽  
Element Model ◽  
Stiffened Panel ◽  
Element Analysis ◽  
Stiffened Panels ◽  
Fiber Reinforced Plastic ◽  
Reinforced Plastic ◽  
Experimental Findings

This paper describes the development of a finite element model in order to assess the static response of a top-hat-stiffened panel under uniform lateral pressure. Systematic calculations were performed for deflection, strain, and stress using the developed model based on the ANSYS three-dimensional solid element (SOLID45). The numerical modeling results were compared to the experimental findings for validation and to further understand an internal stress pattern within the different constituents of the panel for explaining the likely causes of the panel failure. Good correlation between experimental and numerical strains and displacements was achieved.

FFS Assessment of Pressurized Equipment Utilizing a Thickness Mapping Tool

2016 ◽  
Author(s):  
Benjamin Hantz ◽  
Venkata M. K. Akula ◽  
John Leroux
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Response Prediction ◽  
Accurate Estimate ◽  
Pressure Vessels ◽  
The Finite Element Method ◽  
Element Analysis ◽  
Level 3 ◽  
Level 1 ◽  
Element Method

For pressure vessels, loss of thickness detected during scheduled maintenance utilizing UT scans can be assessed based on Level 1 or 2 analyses as per API 579 guidelines. However, Level 1 and 2 analyses can point to excessively conservative assessments. Level – 3 assessments utilizing the finite element method can be performed for a more accurate estimate of the load carrying capacity of the corroded structure. However, for a high fidelity structural response prediction using the finite element method, the characteristics of the model must be accurately represented. Although the three nonlinearities, namely, the geometric, material, and contact nonlinearities can be adequately included in a finite element analysis, procedures to accurately include the thickness measurements are not readily available. In this paper, a tool to map thicknesses obtained from UT scans onto a shell based finite element models, to perform Level – 3 analyses is discussed. The tool works in conjunction with Abaqus/CAE and is illustrated for two different structures following the elastic-plastic analysis procedure outlined in the API 579 document. The tool is intended only as a means to reduce the modeling time associated with mapping thicknesses. The results of the analyses and insights gained are presented.

Optimization Methodology for Composite Stiffened Panel Based on Genetic Algorithm

2014 ◽  
Vol 952 ◽  
pp. 34-37
Author(s):  
Da Feng Jin ◽  
Zhe Liu ◽  
Zhi Rui Fan
Keyword(s):  
Genetic Algorithm ◽  
Finite Element Method ◽  
Finite Element ◽  
Design Space ◽  
Design Guidelines ◽  
Stiffened Panel ◽  
Stacking Sequence ◽  
Design Variables ◽  
Composite Stiffened Panel ◽  
Optimization Methodology

A novel optimization methodology for stiffened panel is proposed in this paper. The purpose of the optimization methodology is to improve the first buckling load of the panel which is obtained by finite element method. The stacking sequence of the stiffeners is taken as design variables. In order to ensure the manufacturability of design, the design guidelines of stacking sequence are taken into account. A DOE based on Halton Sequence makes the initial points of genetic algorithm spread more evenly in the design space of laminate parameters and consequently accelerates the search to convergence. The numerical example verifies the efficiency of this method.

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