Abubakar, Auwal BalaDeepho, JitsupaMalik, MaulanaArgyros, Ioannis K....
16页
查看更多>>摘要：In this work, a new hybrid conjugate gradient (CG) algorithm is developed for finding solutions to unconstrained optimization problems. The search direction of the algorithm consists of a combination of conjugate descent (CD) and Dai-Yuan (DY) CG parameters. The search direction is also close to the direction of the memoryless Broyden-Fletcher- Goldfarb-Shanno (BFGS) quasi-Newton algorithm. Moreover, the search direction is bounded and satisfies the descent condition independent of the line search. The global convergence of the algorithm under the Wolfe-type is proved with the help of some proper assumptions. Numerical experiments on some benchmark test problems are reported to show the efficiency of the new algorithm compared with other existing schemes. Finally, application of the algorithm in risk optimization completes the work. (c) 2021 Elsevier B.V. All rights reserved.
Crawshaw, Jessica R.Flegg, Jennifer A.Osborne, James M.
14页
查看更多>>摘要：In this paper we present and validate a simple adaptive surface remeshing technique to transfer history dependent variables from an old distorting mesh to a new mesh during finite element simulations of elastic surface deformation. This technique allows us to reduce the error arising from excessive mesh distortion whilst preserving information about the initial configuration of the mesh and the history dependent variables. The transfer technique presented here constructs the initial configuration of the new mesh by considering the distortion incurred by the elements of the old mesh and projecting backwards in time. Using this new initial configuration, the stress and strain over the new mesh can be easily calculated. After presenting the necessary steps to reconstruct the initial configuration, we show that this relatively simple transfer technique adds stability to finite element simulations and reduces the spatial error and the strain error across the domain. The novel transfer technique presented in this paper is easy to implement, released under an open source licence, and provides a simple strategy to add stability to simulations undergoing large deformations. (c) 2021 Elsevier B.V. All rights reserved.
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Elsevier