2017
DOI: 10.1016/j.camwa.2017.03.033
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Iterative differential quadrature solutions for Bratu problem

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Cited by 22 publications
(13 citation statements)
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“…To ensure the validity of proposed scheme, the obtained results are compared with previous ones for cracked and un-cracked Euler-Bernoulli and Timoshenko problems. A quadrature numerical scheme is designed to solve cracked Euler-Bernoulli beam problems, equations (22)(23)(24)(25)(26)(27)(28)(29). For each sub-beam, N is to be varied from 5-50 to determine N leading to accurate convergent results.…”
Section: Numerical Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…To ensure the validity of proposed scheme, the obtained results are compared with previous ones for cracked and un-cracked Euler-Bernoulli and Timoshenko problems. A quadrature numerical scheme is designed to solve cracked Euler-Bernoulli beam problems, equations (22)(23)(24)(25)(26)(27)(28)(29). For each sub-beam, N is to be varied from 5-50 to determine N leading to accurate convergent results.…”
Section: Numerical Resultsmentioning
confidence: 99%
“…Recently, differential quadrature method is introduced as promising numerical technique. This method leads to very accurate results by using small number of nodal points [23][24][25][26]. Rotational spring model is employed to simulate the crack existence.…”
Section: Introductionmentioning
confidence: 99%
“…Then, using the iterative quadrature technique (Ragb et al, 2017) to obtain linear an Eigen-value problem as: 1-Firstly, solving the eqs. (35-38) as linear system ( )…”
Section: Discrete Singular Convolution Differential Quadrature Methodmentioning
confidence: 99%
“…In this segment, we exhibit the computational technique employed to solve the nonlinear system of PDEs (14)- (15) with boundary conditions (16). Newton's linearization method (NLM) was utilized to linearize the non-linear system (14)- (16), which was subsequently solved using the differential quadrature method (DQM) [27][28][29][30][31][32][33][34][35][36][37][38][39] and two-point backward finite difference method. Applying NLM on (14)- (16) gives:…”
Section: Hybrid Linearization-differential Quadrature Methods (Hldqm)mentioning
confidence: 99%