Study on the response of circular thin plate under low velocity impact

Proceedings of the Institution of Mechanical Engineers, Part E:

Mostofi

Armoudli

2016

Self Cite

This paper studies the dynamic plastic response of thin quadrangular mild steel plates subjected to uniform and localized impulsive loading. For this, two new dimensionless numbers based on dimensionless governing equation of plates have been suggested. Four different effective parameters such as plate geometry, inertia of applied load, mechanical properties of material and strain rate sensitivity have been considered in suggested dimensionless numbers. The unknown coefficients of these numbers have been calculated by using singular value decomposition method. In order to illustrate the ability of empirical constitutive equations for predicting the maximum deflection, these equations are compared with different sets of experimental results that have been performed by various researchers. The comparison between the results of present empirical equations and the other theoretical and experimental ones shows that these models are more accurate than the other ones and are suitable to use for predicting the maximum deflection of all quadrangular mild steel plates subjected to uniform and localized loading.

Section: Introductionmentioning

confidence: 99%

On dimensionless numbers for the dynamic plastic response of quadrangular mild steel plates subjected to localized and uniform impulsive loading

Proceedings of the Institution of Mechanical Engineers, Part E:

Mostofi

Armoudli

2016

Self Cite

“…One can find that equation (10) can be easily recasts in a matrix form for given M input-output data pairs (X i , y i ), ði ¼ 1, 2, . .…”

Section: Modelling Using Anfismentioning

confidence: 99%

“…Statistical index to determine the accuracy of designed models by ANFIS is RMSE. Also, for better comparison, the RMSE of closed-form mathematical equations obtained by SVD approach in Babaei et al 10 is calculated in Table 3. These models are presented in equations (17) and (18…”

Section: Multi-objective Ga/svd-anfis Modelling Of Experimental Datamentioning

confidence: 99%

“…There are different forming processes, like gas detonation forming, 3 explosive forming, [4][5][6] electromagnetic forming, 7,8 electro-hydraulic forming, 9 and hydrodynamic impact forming. 10 However, these methods have defects and advantages but these processes are found to be attractive by the manufacturers. Moreover, low velocity hydroforming using drop hammer system is a novel method to form the structures with low cost, less wrinkles, and more safety.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multi-objective optimum design of ANFIS for modelling and prediction of deformation of thin plates subjected to hydrodynamic impact loading

Jamali

Proceedings of the Institution of Mechanical Engineers, Part L:

Nariman-Zadeh

et al. 2016

Drop hammer impact experiments have been carried out to assess the dynamic plastic response of fully clamped circular and rectangular plates made of aluminum and steel subjected to hydrodynamic impact loading at various energy levels. Also, the effective parameters in forming process are proposed in non-dimensional forms for modeling and prediction of the central deflection of plates using adaptive neuro-fuzzy inference system in conjunction with genetic algorithm and singular value decomposition method. Genetic algorithm is used for optimal scheme of Gaussian membership function’s variables and multi-objective Pareto optimal design of adaptive neuro-fuzzy inference system model. Also, the singular value decomposition method is applied to compute the linear parameters of the adaptive neuro-fuzzy inference system method. The important conflicting objectives of developed adaptive neuro-fuzzy inference system, namely, training error and prediction error, are obtained by dividing date sets into two parts. Hence, various optimal choices of adaptive neuro-fuzzy inference system model are provided which are non-dominated states from each other. Moreover, optimal Pareto front of such model leads to trade-off between the conflicting pair of considered objectives for two series of experiments. The results of this work indicate that multi-objective Pareto optimal design of adaptive neuro-fuzzy inference system predicts central deflection of plates with a good accuracy. In addition, the comparison between the adaptive neuro-fuzzy inference system model and exiting one demonstrates superior performance of the present approach in simulating central deflection of plates.

“…There are numerous analytical and numerical techniques used by many researchers to define and predict the behavior of complex materials under various types of loading. [16][17][18] According to the rules and theories of modeling, it is necessary to develop a mathematical relationship between input data and the output results, which, obviously requires knowledge of different techniques. [19][20][21][22] Generally it is well known that in cyclic loading fatigue is the main cause of failure in materials used in many structures.…”

Section: Introductionmentioning

confidence: 99%

Modeling and prediction of fatigue life in composite materials by using singular value decomposition method

Proceedings of the Institution of Mechanical Engineers, Part L:

Mostofi

2016

Self Cite

Proposing a comprehensive model to predict the fatigue life of composite structures under dynamic loading has always been a challenging problem. In this study, an attempt has been made to develop a polynomial model by utilization of experimental data together with singular value decomposition technique to estimate the fatigue life of composite materials. The model is based on a nonlinear mathematical function with effective parameters related to fatigue phenomenon in a nondimensional form. For this, four effective parameters such as cyclic stress amplitude, static strength, stress ratio, and fiber angle have been considered in modeling process. To evaluate the capability of this model a comparison has been made with some available experimental results where a good agreement is achieved. So, the obtained results demonstrate that despite system complexity and inability to extract an analytical model for estimating the fatigue life of composite materials, singular value decomposition method could be known as a useful and powerful tool for modeling.