Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/15713
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dc.contributor.authorChamaleen, D.B.D.-
dc.contributor.authorVigneswaran, R.-
dc.date.accessioned2017-01-04T09:02:03Z-
dc.date.available2017-01-04T09:02:03Z-
dc.date.issued2016-
dc.identifier.citationChamaleen, D.B.D. and Vigneswaran, R. 2016. Accelerating the rate of convergence of some efficient schemes for two-stage Gauss method. In Proceedings of the International Research Symposium on Pure and Applied Sciences (IRSPAS 2016), Faculty of Science, University of Kelaniya, Sri Lanka. p 59.en_US
dc.identifier.isbn978-955-704-008-0-
dc.identifier.urihttp://repository.kln.ac.lk/handle/123456789/15713-
dc.description.abstractThe non-linear equations obtaining from the implicit s – stage Runge-Kutta methods have been solved by various iteration schemes. A scheme has been developed, which is computationally more efficient and avoids expensive vector transformations. The rate of convergence of this scheme is examined when it is applied to the scalar test differential equation 􀀒􀀢 = 􀀣􀀒 and the convergence rate depends on the spectral radius 􀀤[􀀘(􀀦)] of the iteration matrix 􀀘(􀀦), where 􀀦 = ℎ􀀣 and ℎ is the step-size. In this scheme, supremum of a lower bound for 􀀤[􀀘(􀀦)] is minimized over the left half 􀀦- plane with the constraints requiring super-linear convergence at 􀀦 = 0 and 􀀦 → ∞ .Two new schemes with parameters are obtained for the two-stage Gauss-method. Numerical experiments are carried out in order to evaluate and compare the efficiency of the new schemes and the original scheme. Consider an initial value problem for stiff system of ordinary differential equations 􀀒􀀢 = 􀀬􀀭􀀒(􀀟)􀀮, 􀀒(􀀯) = 􀀰, 􀀬: ℝ􀀐 → ℝ􀀐. An s-stage implicit Runge-Kutta method computes an approximation 􀀒􀀳􀀴􀀜 to the solution x (􀀟􀀳􀀴􀀜) at discrete point 􀀟􀀳􀀴􀀜 = 􀀟􀀳 + ℎ by 􀀒􀀳􀀴􀀜 = 􀀒􀀳 + ℎ Σ 􀀛􀀶 􀀷 􀀶 􀀸􀀜 􀀬(􀀔􀀶 ), where 􀀔􀀜 ,􀀔􀀙 ,…,􀀔􀀷, satisfy sn equations 􀀔􀀶 􀀸 􀀒􀀳 + ℎ 􀀺 􀀯􀀶􀀻 􀀷 􀀶􀀸􀀜 􀀬􀀭􀀔􀀻􀀮, ), 􀀼 = 1,2, . . . , 􀁀. 􀁁 = 􀁂􀀯􀀶􀀻􀁃 is the real coefficient matrix and 􀀛 = [􀀛􀀜 ,􀀛􀀙 ,…,􀀛􀀷]􀁄 is the column vector of the Runge-Kutta method. Let 􀀔 = 􀀔􀀜 ⊕ 􀀔􀀙 ⊕ … ⊕ 􀀔􀀷 ∈ ℝ􀀷􀀐and 􀁇(􀁈) = 􀀬(􀀔􀀜) ⊕ 􀀬(􀀔􀀙) ⊕ … ⊕ 􀀬(􀀔􀀷) ∈ ℝ􀀷􀀐. Then the above equation in 􀀔􀀜 ,􀀔􀀙 ,…,􀀔􀀷 may be written by 􀁈 = 􀁉 ⊗ 􀀒􀀳 + ℎ(􀁁 ⊗ 􀁋􀀐)􀁇(􀁈), where 􀁉 = (1,1, … ,1)􀁄 and (􀁁 ⊗ 􀁋􀀐) is the tensor product of the matrix 􀁁 with 􀀑 × 􀀑 identity matrix 􀁋􀀐. The efficient scheme, which has been already proposed, is given by [􀁋􀀷 ⊗ (􀁋􀀐 − ℎ􀁌􀁍)]􀁎􀁏 = (􀁐 ⊗ 􀁋􀀐)(􀁉 ⊗ 􀁑􀀳 – 􀁈􀁏) + (􀁓 ⊗ 􀁋􀀐)( 􀁉 ⊗ 􀁑􀀳 – 􀁈􀁏􀁔􀀜) + ℎ(􀁕 ⊗ 􀁋􀀐)􀁇(􀁈􀁏) + ℎ(􀀌 ⊗ 􀁋􀀐)􀁇(􀁈􀁏􀁔􀀜), 􀁖 = 1,2, …, In this scheme, supremum of a lower bound for 􀀤[􀀘(􀀦)] is minimized over ℂ􀁔, where ℂ􀁔 = {􀀦 ∈ 􀁙 /􀀌􀁉 (􀀦) ≤ 0 } with the constraints 􀀤[􀀘(􀀦)] = 0 at 􀀦 = 0 and 􀀤[􀀘(􀀦)] = 0 at 􀀦 → ∞. The parameters for the two-stage Gauss method are obtained and Numerical experiments are carried out.en_US
dc.language.isoenen_US
dc.publisherFaculty of Science, University of Kelaniya, Sri Lankaen_US
dc.subjectImplementationen_US
dc.subjectSuper-linear convergenceen_US
dc.subjectLower bounden_US
dc.titleAccelerating the rate of convergence of some efficient schemes for two-stage Gauss methoden_US
dc.typeArticleen_US
Appears in Collections:IRSPAS 2016

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