Experimental determination of relaxation modulus of linear viscoelastic materials, in principle, requires the application of an ideal step strain to the specimen. This could not be achieved in practice, however, and is replaced by a ramp-constant strain history. The material response to the ramp-constant strain deviates from its ideal step response and should be corrected. Different correction methods have been proposed for the full-range modulus extraction from ramp-constant strain experiments, and among them the three methods of Zapas–Phillips, Lee–Knauss, and Sorvari–Malinen are distinguishable. Few comparative studies have been performed on these methods, all of which have been based on the simulated response of a hypothetic material rather than on the real experimental data. Furthermore, the simulations have been performed assuming specific material models not essentially appropriate for the material parameter extraction purposes, leading to undesirable errors in the simulation results. In this paper, the above-mentioned methods are compared based on both simulation and experimental approaches. The simulation results show that all methods effectively improve the range of modulus extraction compared to the well-known “ten-times rule”, and the Lee–Knauss method provides the best predictions, in contrast to some of the previously published results. Considering the experimental results, however, it is observed that all the modulus extraction methods lose their performance if a sufficiently small sampling rate is not provided by the experimental data acquisition system. It has been discussed that the conclusion of some authors regarding the invalidity of ten-times-rule stems from a misinterpretation of their simulation results and is faultful.
Gas metal arc welding is a fusion welding process which has got wide applications in industry. In order to obtain a good quality weld, it is therefore, necessary to control the input welding parameters. In other words proper selection of input welding parameters in this process contribute to weld productivity. One of the important welding output parameters in this process is weld dilution affecting the quality and productivity of weldment. In this research paper using Taguchi method of design of experiments a mathematical model was developed using parameters such as, wire feed rate (W), welding voltage (V), nozzle-to-plate distance (N), welding speed (S) and gas flow rate (G) on weld dilution. After collecting data, signal-to-noise ratios (S/N) were calculated and used in order to obtain the optimum levels for every input parameter. Subsequently, using analysis of variance the significant coefficients for each input factor on the weld dilution were determined and validated. Finally a mathematical model based on regression analysis for predicting the weld dilution was obtained. Results show that wire feed rate (W),arc voltage (V) have increasing effect while Nozzle-to-plate distance (N) and welding speed (S) have decreasing effect on the dilution whereas gas Flow rate alone has almost no effect on dilution but its interaction with other parameters makes it quite significant in increasing the weld dilution
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