Fatigue strength estimation of adhesively bonded tubular joint using genetic algorithm approach

The bonding strength of adhesives is influenced by many factors such as, the surface roughness, bonding clearances, interference fit, temperature, and material of the joining parts, etc. Since all these factors affect the strength of the adhesively joined parts, the effects of these parameters need to be investigated. The present paper describes the use of stochastic search process that is the basis of Genetic Algorithm (GA), in developing fatigue strength estimation of adhesively bonded cylindrical components. Nonlinear estimation models are developed using GA. Developed models are validated with experimental data. Genetic Algorithm Fatigue Strength Estimation Model (GAFSEM) is developed to estimate the fatigue strength of the adhesively bonded tubular joint using several adherent materials, such as steel, bronze and aluminum materials. © 2004 Elsevier Ltd. All rights reserved

Estimation of welded joint strength using genetic algorithm approach

The genetic algorithm approach is extended to the estimation of mechanical properties of the joining of brass materials. The mechanical properties of joint parts can be improved by selecting suitable parameters. The strength of the joint parts is affected by many factors, such as the gap between the parts, the torch angle, the quantity of the shielding gases, the pulse frequencies and the electrode tip angle during welding operations. Since all these factors affect the mechanical properties of the welded joint parts, the effects of these parameters need to be cautiously investigated. The present paper describes the use of the stochastic search process that is the basis of Genetic Algorithms (GA), in developing the strength value of the welded parts. Non-linear estimation models are developed using GAs. Developed models are validated with experimental data. The Genetic Algorithm Welding Strength Estimation Model (GAWSEM) is developed to estimate the mechanical properties of the welded joint for the brass materials. The effects of five welding design parameters on the strength value using the GAWSEM have been examined. The results indicated that the changes of the gap between the joint parts and the torch angle have an important effect on the welded joint strength value and the optimum quantity of the shielding gas and the pulse frequencies exist in the tensile strength of welded joints. © 2005 Elsevier Ltd. All rights reserved

A new approach for calculating the stiffness of bolted connections

The stiffness of bolted joint influences the transfer of initial preload and operating force. The determination of stiffness without the gasket is fairly difficult to obtain, because the compression region spreads out between the bolt head and the nut. Bolted joints including bolts and members act as elastic springs under operating conditions. The affected area is not uniform. The stiffness of the bolted joints can be determined using finite element analysis and soft computing techniques. The prediction of the non-dimensional joint stiffness is developed in this paper by using genetic algorithm methods. The proposed model was in good agreement with the experimental results and previous literature and may be considered as a simple and suitable guideline for the design of bolted joints

Fatigue strength estimation of adhesively bonded tongue and groove joint of thick woven composite sandwich structures using genetic algorithm approach

In the present work, the fatigue behavior of tongue and groove joints bonded by a toughened epoxy adhesive was investigated. Axial cyclic tests were performed by different design configuration conditions and the effects of design parameters were evaluated. The bonding strength of adhesives under fatigue loading is influenced by many factors such as, the length of bondline, adhesive thickness, traverse pre-stress on near the free edges of bond line and material of the joining parts. Since all these factors affect the fatigue strength of the adhesively joined parts, the effects of these parameters need to be investigated. The present paper describes the use of the stochastic search process that is the basis of a Genetic Algorithm, in developing fatigue strength estimation of adhesively bonded thick woven E-glass/vinyl ester laminates. Non-linear estimation models were developed using genetic algorithm. Developed models are validated with experimental data. Genetic Algorithm Fatigue Strength Estimation Model for Tongue and Groove Joints was developed to estimate the fatigue strength of the adhesively bonded joint. The strongest adhesively bonded joints can be achieved by selecting optimum design parameters obtained from the models. The logarithmic number of cycles was increased 2.46 times by selecting aluminum EN AW 5083 insert instead of composite insert materials. The joint fatigue strength was significantly improved by selecting appropriate design parameter values. © 2011 Elsevier Ltd. All rights reserved

Joint strength of friction stir welded AISI 304 austenitic stainless steels

In this study, AISI 304 (X5CrNi18-10) austenitic stainless steels were joined by means of friction stir welding. The welded joint strength of stainless steels was influenced by many factors, such as different tool rotational speeds, traverse speeds, compressive tool forces, and tool angles, etc. There is a strong interrelation among the friction stir welding design parameters. The effects of design parameters on the welded joint were analyzed using a genetic algorithm. Appropriate design parameter configurations led to finegrained microstructures that resulted in higher tensile strength joints compared to the base material. The best design configuration that led to 1.16 times higher strength than the base material was achieved with 47.5 mm min-1 traverse speed, a rotational speed of 1 180 min-1, compressive tool force of 7 kN and tool tilt angle of 2.0°. © Carl Hanser Verlag GmbH & Co. KG

Pre-stressed adhesive strap joints for thick composite sandwich structures

A simple but effective design to improve the strength of thick adhesive composite strap joints is validated with experiment and finite element method. The strap joint under investigation, with a particular application to naval ship structures, consists of two thick woven E-glass/vinyl ester laminates joined together with two steel doublers. Longitudinal tensile loads are applied to the joints, resulting in large concentrated shear and peel stresses near the free edges of bondlines. The new design intends to reduce the adhesive peel stress by application of through-the-thickness compressive pre-stress along the bondline and thus leads to an increase of joint strength. Experiment results show that all the joint failures are delamination of the top layer of the laminated adherends. The test further confirms that joint strength increases significantly by applying the transverse pre-stress. Finite element analysis reveals that the pre-stress can effectively reduce the magnitude even reverse the sign of the peel stress in the adhesive layer and the adherends. Recessing the adhesive leading edge could magnify the pre-stress effect and reduce the adhesive peel stress, but would increase the shear stress. For those composite joints with low transverse interlaminar strength and susceptible to delamination, this simple design/technique can considerably improve their joint strength. © 2005 Elsevier Ltd. All rights reserved

Development of the positive mean stress diagrams using genetic algorithm approach

In this numerical study, a new optimum positive mean stress fatigue failure equation is developed using previous experimental data and genetic algorithm. Two independent curve fitting coefficients are implemented in the equation to supply better correlations with experimental data of the failure strength envelope. In the literature, Gerber, Goodman, Soderberg, Morrow, Bagci, ASME (elliptic line), Clemson, Sekercioglu and so on suggested different equations for estimating fatigue strength envelope under mean stress condition. In these models, the effect of the materials was not considered in details. Some of these mean stress linear expressions are very conservative or have stress area bigger than the yield limit. The yield strength and the effect of materials are considered in the proposed model. The values of the positive mean stress, which correspond to fatigue failure, are obtained, and a minimum average absolute error among the models presented in the literature is remarked. The proposed model, which has less conservative structure, can be effectively used in the mechanical design process. © 2013 Wiley Publishing Ltd

THE EFFECT OF PENTAGONAL AND OCTAGONAL JOINT DESIGN ON THE FATIGUE STRENGTH OF POLYMER-MATRIX COMPOSITE MATERIALS

Joining methods and suitable geometry selection become an important role in the bonding of composites. The fatigue strength of adhesively bonded joint of thick woven type laminated E-glass/ Polymer matrix composites consist of 22 layers with a layer thickness of 0.5 mm was investigated experimentally. Frequency was kept constant at 10 Hz for all experiments, while the load ratio was equal to 0.1, resulting in a tension-tension fatigue loading. Octagonal and pentagonal tongue and groove joint design were used in order to join thick composite materials. Experimental results and SEM analysis of present study indicated that fatigue strength was strongly influenced by the geometry of joint design. Claw length and claw width defined in the design were found to have a significant effect on fatigue strength of adhesively bonded joints. The octagonal design showed almost two times higher fatigue strength than pentagonal joint design

Application of Genetic Algorithm (GA) technique on demand estimation of fossil fuels in Turkey

The main objective of the present study is to investigate Turkey's fossil fuels demand, projection and supplies by giving the structure of the Turkish industry and Turkish economic conditions. This present study develops several scenarios to analyze fossil fuels; such as, coal, oil and natural gas consumption and make future projections based on Genetic Algorithm (GA) notion, and examines the effect of the design parameters on the fossil fuels utilization values. The models developed in the nonlinear form are applied to the coal, oil and natural gas demand of Turkey. Several Genetic Algorithm Demand Estimation Models (GA-DEM) are developed to estimate the future coal, oil and natural gas demand values based on population, Gross National Product (GNP), import, export figures. It may be concluded that the proposed models can be used as an alternative solution and estimation techniques for the future fossil fuel utilization values of any country. Oil is the most important fuel in Turkey, contributing 43% of the Total Primary Energy Supply (TPES), followed by coal (almost 30% of TPES) and natural gas (11.8%). In the study, coil, oil and natural gas consumption of Turkey are projected. Estimation shows that the coal, oil and natural gas consumption values may increase 2.82, 1.73 and 4.83 times from 2000 to 2020. Copyright © 2007 by ASME