یک الگوریتم انطباقی جدید برای توزیع بهینه مراکز محاسباتی در روش بدون شبکه چندربعی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانش‌آموخته کارشناسی‌ارشد گروه مهندسی عمران، دانشکده فنی و مهندسی، دانشگاه قم، قم، ایران.

2 دانش‌آموخته دکتری گروه مهندسی عمران، دانشکده فنی و مهندسی، دانشگاه قم، قم، ایران.

3 گروه مهندسی عمران، دانشکده فنی و مهندسی، دانشگاه قم، قم، ایران

چکیده

مراکز محاسباتی در روش توابع پایه شعاعی بدون شبکه چندربعی به علت عدم ارتباط هندسی و فیزیکی با یکدیگر دارای قابلیت انطباق‌پذیری بالا و لذا مناسب برای اعمال توزیع‌های انطباقی هستند. در این پژوهش، برای اولین بار یک الگوریتم انطباقی جدید بر مبنای تغییرات (گرادیان) متغیرهای فیزیکی مسئله با هدف ایجاد یک توزیع بهینه پیشنهاد شده است. توزیع انطباقی این الگوریتم، دقت و سرعت روش چندربعی را نسبت به توزیع یکنواخت در مسائل ناپایا به میزان قابل توجهی بهبود می‌بخشد. در این رویکرد نواحی با تغییرات فیزیکی کم و زیاد در گام زمانی معلوم شناسایی می‌شوند و تعداد مراکز محاسباتی به ترتیب در آن‌ها کاهش و افزایش می‌یابد. بنابراین نیاز به یک توزیع فشرده یکنواخت در سراسر میدان به منظور کاهش خطا در نواحی با تغییرات فیزیکی زیاد از بین می‌رود. در مواجهه با دیگر چالش مهم روش چندربعی یعنی تعیین متغیر شکل بهینه نیز یک روش ساده و کارآمد به‌گونه‌ای معرفی می‌شود که به بهینه‌سازی متغیر شکل در هر گام زمانی نیاز نباشد و هزینه‌های محاسباتی کنترل گردد. در پایان، کارایی روش پیشنهادی با ارائه مثال‌هایی از معادلات پخش، جابجایی و پخش-جابجایی برای مقایسه با توزیع‌های یکنواخت و سنجش میزان سرعت و دقت آن‌ها با حل دقیق نشان داده می‌شود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

A New Adaptive Algorithm for the Optimal Distribution of Computational Centers in the Meshless Multiquadric Method

نویسندگان [English]

  • Samira MohammadAlian 1
  • Reza Babaee 2
  • Ehsan Jabbari 3
1 Department of Civil Engineering, Faculty of Engineering, University of Qom, Qom, Iran.
2 Department of Civil Engineering, Faculty of Engineering, University of Qom, Qom, Iran.
3 Department of Civil Engineering, Faculty of Engineering, University of Qom, Qom, Iran
چکیده [English]

The computational centers in the multiquadric radial basis functions meshless method have high adaptability considering the lack of geometric and physical connection between the centers. In this research, a new adaptive algorithm is proposed based on the gradients of the physical variables of the problem with the aim of creating an optimal distribution. The resulted adaptive distribution generated by this algorithm improves significantly the accuracy and speed of the multiquadric method compared to the uniform distribution in steady and unsteady problems. In this approach, firstly, the domains with low and high physical variations are identified in a known time step, then the number of computational centers decreases and increases in these areas, respectively. Thus, the centers will be distributed more compact where needed and will be eliminated where not. Facing another important challenge of the multiquadric method, i.e. determining the optimal shape parameter, a simple and efficient method is introduced in such a way that there is no need to optimize the shape parameter at each time step and the computational costs are controlled. Finally, the effectiveness of the proposed method is shown by solving examples of diffusion, convection and convection-diffusion equations. The results are compared to their uniform distributions by measuring their efficiency and to the exact solution by evaluating the accuracy.

کلیدواژه‌ها [English]

  • Meshless Method
  • Radial Basis Functions
  • Multiquadric -Method
  • Adaptive Algorithm
  • Gradient
[1] Kansa, E. J. (1990). Multiquadrics- A scattered data approximation scheme with applications to computational fluid-dynamics—I surface approximations and partial derivative estimates. Computers & Mathematics with applications, 19(8-9), 127-145. doi: 10.1016/0898-1221(90)90270-T
[2] Kindelan, M., Bernal, F., González-Rodríguez, P., & Moscoso, M. (2010). Application of the RBF meshless method to the solution of the radiative transport equation. Journal of Computational Physics, 229(5), 1897-1908. doi: 10.1016/j.jcp.2009.11.014
[3] Kansa, E. J., & Geiser, J. (2013). Numerical solution to time-dependent 4D inviscid Burgers' equations. Engineering Analysis with Boundary Elements, 37(3), 637-645.‏ doi: 10.1016/j.enganabound.2013.01.003
[4] Patel, S., & Rastogi, A. K. (2017). Meshfree multiquadric solution for real field large heterogeneous aquifer system. Water Resources Management, 31(9), 2869-2884. doi: 10.1007/s11269-017-1668-8
[5] Babaee, R., Jabbari, E., & Eskandari-Ghadi, M. (2019). Application of Multiquadric Radial Basis Function method for Helmholtz equation in seismic wave analysis for reservoir of rigid dams. Amirkabir Journal of Civil Engineering, 52(12), 3015-3030. doi: 10.22060/ceej.2019.16443.6230 [In Persian]
[6] Koushki, M., Jabbari, E., & Ahmadinia, M. (2020). Evaluating RBF methods for solving PDEs using Padua points distribution. Alexandria Engineering Journal, 59(5), 2999-3018. doi: 10.1016/j.aej.2020.04.047
[7] Mirabi, M. H., Jabbari, E., & Rajaee, T. (2022). Numerical Solution of Steady Incompressible Turbulent Navier–Stokes Equations using Multiquadric Radial Basis Function (MQ-RBF) Method. Amirkabir Journal of Civil Engineering, 53(12), 5325-5356. doi: 10.22060/ceej.2021.18788.6964 [In Persian]
[8] Fornberg, B., & Wright, G. (2004). Stable computation of multiquadric interpolants for all values of the shape parameter. Computers & Mathematics with Applications, 48(5-6), 853-867. doi: 10.1016/j.camwa.2003.08.010
[9] Xiang, S., Wang, K. M., Ai, Y. T., Sha, Y. D., & Shi, H. (2012). Trigonometric variable shape parameter and exponent strategy for generalized multiquadric radial basis function approximation. Applied Mathematical Modelling, 36(5), 1931-1938.‏ doi: 10.1016/j.apm.2011.07.076
[10] Esmaeilbeigi, M., & Hosseini, M. M. (2014). A new approach based on the genetic algorithm for finding a good shape parameter in solving partial differential equations by Kansa’s method. Applied Mathematics and Computation, 249, 419-428.‏ doi: 10.1016/j.amc.2014.10.012
[11] Biazar, J., & Hosami, M. (2016). Selection of an interval for variable shape parameter in approximation by radial basis functions. Advances in Numerical Analysis, 2016. doi: 10.1155/2016/1397849
[12] Azarboni, H. R., Keyanpour, M., & Yaghouti, M. (2019). Leave-Two-Out Cross Validation to optimal shape parameter in radial basis functions. Engineering Analysis with Boundary Elements, 100, 204-210. doi: 10.1016/j.enganabound.2018.06.011
[13] Fallah, A., Jabbari, E., & Babaee, R. (2019). Development of the Kansa method for solving seepage problems using a new algorithm for the shape parameter optimization, Computers & Mathematics with Applications, 77(3), 815-829. doi: 10.1016/j.camwa.2018.10.021
[14] Koushki, M., Babaee, R. & Jabbari, E. (2020). Application of RBF Multiquadric method for solving seepage problems using a new algorithm for Optimization of the shape parameter. Amirkabir Journal of Civil Engineering, 52(4), 1009-1024. doi: 10.22060/ceej.2019.15155.5840 [In Persian]
[15] Berger, M. J., & Jameson, A. (1985). Automatic adaptive grid refinement for the Euler equations. AIAA journal, 23(4), 561-568. doi: 10.2514/3.8951
[16] Sarra, S. A. (2005). Adaptive radial basis function methods for time dependent partial differential equations. Applied Numerical Mathematics, 54(1), 79-94. doi: 10.1016/j.apnum.2004.07.004
[17] Libre, N. A., Emdadi, A., Kansa, E. J., Shekarchi, M., & Rahimian, M. (2009). A multiresolution prewavelet-based adaptive refinement scheme for RBF approximations of nearly singular problems. Engineering analysis with boundary elements, 33(7), 901-914. doi: 10.1016/j.enganabound.2009.02.007
[18] Biazar, J., & Hosami, M. (2015). An adaptive meshless method of line based on radial basis functions. Iranian Journal of Numerical Analysis and Optimization, 5(2), 45-58. doi: 10.22067/ijnao.v5i2.35815 
[19] Kaennakham, S., & Chuathong, N. (2019). An automatic node-adaptive scheme applied with a RBF-collocation meshless method. Applied Mathematics and Computation, 348, 102-125. doi: 10.1016/j.amc.2018.11.066
[20] Cavoretto, R., & De Rossi, A. (2020). An adaptive LOOCV-based refinement scheme for RBF collocation methods over irregular domains. Applied Mathematics Letters, 103, 106178. doi: 10.1016/j.aml.2019.106178
[21] Cavoretto, R., & De Rossi, A. (2020). A two-stage adaptive scheme based on RBF collocation for solving elliptic PDEs. Computers & Mathematics with Applications, 79(11), 3206-3222. doi: 10.1016/j.camwa.2020.01.018
[22] Kolbe, N., & Sfakianakis, N. (2022). An adaptive rectangular mesh administration and refinement technique with application in cancer invasion models. Journal of Computational and Applied Mathematics, 416, 114442. doi: 10.1016/j.cam.2022.114442
[23] Cavoretto, R., De Rossi, A., Sommariva, A., & Vianello, M. (2022). RBFCUB: A numerical package for near-optimal meshless cubature on general polygons. Applied Mathematics Letters, 125, 107704. doi: 10.1016/j.aml.2021.107704
[24] Wei, C., Hu, Q., Li, S., & Shi, X. (2023). Hydrodynamic interactions and wake dynamics of fish schooling in rectangle and diamond formations. Ocean Engineering, 267, 113258. doi: 10.1016/j.oceaneng.2022.113258
[25] Loubère, R., Turpault, R., & Bourriaud, A. (2023). A MOOD-like compact high order finite volume scheme with adaptive mesh refinement. Applied Mathematics and Computation, 443, 127792. doi: 10.1016/j.amc.2022.127792
[26] Sankaranarayanan, S., Shankar, N. J., & Cheong, H. F. (1998). Three-dimensional finite difference model for transport of conservative pollutants. Ocean Engineering, 25(6), 425-442. doi: 10.1016/S0029-8018(97)00008-5
[27] Mohammadalian, S. (2022). Evaluation of the performance of adaptive point distribution algorithms in Multiquadric radial basis functions meshfree methods in solving 1-D and 2-D problems. MSc. Thesis, Department of Civil Engineering, Faculty of Engineering, University of Qom, Qom, Iran. [In Persian]
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