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An object-oriented framework for solving model problems using the sequential function approximation algorithm.

机译:使用顺序函数逼近算法解决模型问题的面向对象框架。

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This dissertation describes and tests an Object-Oriented framework, written in Fortran 90, for the Sequential Function Approximation (SFA) algorithm. The SFA algorithm is a meshless method which places its basis functions in the domain sequentially, using optimization techniques. The framework described herein allows the user to define the domain, boundary conditions, and governing equations of 1-D and 2-D problems with minimal user coding, and to solve them using the SFA method.; This work advances the state of knowledge in the fields of meshless methods in general and of the SFA method in particular. Unsteady transport problems are solved for the first time with the SFA method: diffusive, convective-diffusive, and purely convective problems are solved using a semi-discrete approach and stabilized with the Streamline-Upwind Petrov-Galerkin (SUPG) technique.; Additionally, some light is shed on the role of consistency. SFA is placed within the broader context of meshless methods, and made consistent by transforming it into a sequentially solved Partition of Unity (POU) method. Consistency is experimentally found to improve the convergence behavior of all model problems solved. The improvement is most notable in problems with convection phenomena, although some improvement is seen even in purely diffusive problems. Other hypotheses regarding the SFA method are investigated as well.
机译:本文描述并测试了用Fortran 90编写的面向对象的框架,用于顺序函数逼近(SFA)算法。 SFA算法是一种无网格方法,它使用优化技术将其基础函数依次放在域中。此处描述的框架允许用户以最少的用户编码来定义一维和二维问题的域,边界条件和控制方程,并使用SFA方法求解它们。这项工作总体上提高了无网格方法领域的知识水平,特别是SFA方法。不稳定的运输问题首次使用SFA方法解决:扩散,对流-扩散和纯对流问题使用半离散方法解决,并通过Streamline-Upwind Petrov-Galerkin(SUPG)技术得以稳定。此外,对一致性的作用也有一些了解。 SFA置于更广泛的无网格方法环境中,并且通过将其转换为顺序解决的Unity分区(POU)方法而保持一致。实验上发现一致性可以改善所有已解决模型问题的收敛性。尽管对流现象的问题甚至在纯扩散问题中也有所改善,但对流现象的问题最明显。还研究了有关SFA方法的其他假设。

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