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  • Open Access

    ARTICLE

    Solving the BBMB Equation in Shallow Water Waves via Space-Time MQ-RBF Collocation

    Hongwei Ma1, Yingqian Tian2,*, Fuzhang Wang3,*, Quanfu Lou4, Lijuan Yu4

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3419-3432, 2025, DOI:10.32604/cmes.2025.070791 - 30 September 2025

    Abstract This study introduces a novel single-layer meshless method, the space-time collocation method based on multiquadric-radial basis functions (MQ-RBF), for solving the Benjamin-Bona-Mahony-Burgers (BBMB) equation. By reconstructing the time variable as a space variable, this method establishes a combined space-time structure that can eliminate the two-step computational process required in traditional grid methods. By introducing shape parameter-optimized MQ-RBF, high-precision discretization of the nonlinear, dispersive, and dissipative terms in the BBMB equation is achieved. The numerical experiment section validates the effectiveness of the proposed method through three benchmark examples. This method shows significant advantages in computational efficiency, More >

  • Open Access

    ARTICLE

    Hybrid Wavelet Methods for Nonlinear Multi-Term Caputo Variable-Order Partial Differential Equations

    Junseo Lee1, Bongsoo Jang1, Umer Saeed1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2165-2189, 2025, DOI:10.32604/cmes.2025.069023 - 31 August 2025

    Abstract In recent years, variable-order fractional partial differential equations have attracted growing interest due to their enhanced ability to model complex physical phenomena with memory and spatial heterogeneity. However, existing numerical methods often struggle with the computational challenges posed by such equations, especially in nonlinear, multi-term formulations. This study introduces two hybrid numerical methods—the Linear-Sine and Cosine (L1-CAS) and fast-CAS schemes—for solving linear and nonlinear multi-term Caputo variable-order (CVO) fractional partial differential equations. These methods combine CAS wavelet-based spatial discretization with L1 and fast algorithms in the time domain. A key feature of the approach is More >

  • Open Access

    ARTICLE

    Wave Propagation and Chaotic Behavior in Conservative and Dissipative Sawada–Kotera Models

    Nikolai A. Magnitskii*

    FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.7, pp. 1529-1544, 2025, DOI:10.32604/fdmp.2025.067021 - 31 July 2025

    Abstract This paper presents both analytical and numerical studies of the conservative Sawada–Kotera equation and its dissipative generalization, equations known for their soliton solutions and rich chaotic dynamics. These models offer valuable insights into nonlinear wave propagation, with applications in fluid dynamics and materials science, including systems such as liquid crystals and ferrofluids. It is shown that the conservative Sawada–Kotera equation supports traveling wave solutions corresponding to elliptic limit cycles, as well as two- and three-dimensional invariant tori surrounding these cycles in the associated ordinary differential equation (ODE) system. For the dissipative generalized Sawada–Kotera equation, chaotic More >

  • Open Access

    ARTICLE

    Numerical Analysis of Entropy Generation in Joule Heated Radiative Viscous Fluid Flow over a Permeable Radially Stretching Disk

    Tahir Naseem1, Fateh Mebarek-Oudina2,3,*, Hanumesh Vaidya4, Nagina Bibi5, Katta Ramesh6,7, Sami Ullah Khan8

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 351-371, 2025, DOI:10.32604/cmes.2025.063196 - 11 April 2025

    Abstract Maximizing the efficiency of thermal engineering equipment involves minimizing entropy generation, which arises from irreversible processes. This study examines thermal transport and entropy generation in viscous flow over a radially stretching disk, incorporating the effects of magnetohydrodynamics (MHD), viscous dissipation, Joule heating, and radiation. Similarity transformations are used to obtain dimensionless nonlinear ordinary differential equations (ODEs) from the governing coupled partial differential equations (PDEs). The converted equations are then solved by using the BVP4C solver in MATLAB. To validate the findings, the results are compared with previously published studies under fixed parameter conditions, demonstrating strong… More >

  • Open Access

    PROCEEDINGS

    Analysis of High-Order Partial Differential Equations by Using the Generalized Finite Difference Method

    Tsung-Han Li1,*, Chia-Ming Fan1, Po-Wei Li2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.012120

    Abstract The generalized finite difference method (GFDM), which cooperated with the fictitious-nodes technique, is proposed in this study to accurately analyze three-dimensional boundary value problems, governed by high-order partial differential equations. Some physical applications can be mathematically described by boundary value problems governed by high-order partial differential equations, but it is non-trivial to analyze the high-order partial differential equations by adopting conventional mesh-based numerical schemes, such as finite difference method, the finite element method, etc. In this study, the GFDM, a localized meshless method, is proposed to accurately and efficiently solve boundary value problems governed by… More >

  • Open Access

    ARTICLE

    Incorporating Lasso Regression to Physics-Informed Neural Network for Inverse PDE Problem

    Meng Ma1,2,*, Liu Fu1,2, Xu Guo3, Zhi Zhai1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 385-399, 2024, DOI:10.32604/cmes.2024.052585 - 20 August 2024

    Abstract Partial Differential Equation (PDE) is among the most fundamental tools employed to model dynamic systems. Existing PDE modeling methods are typically derived from established knowledge and known phenomena, which are time-consuming and labor-intensive. Recently, discovering governing PDEs from collected actual data via Physics Informed Neural Networks (PINNs) provides a more efficient way to analyze fresh dynamic systems and establish PED models. This study proposes Sequentially Threshold Least Squares-Lasso (STLasso), a module constructed by incorporating Lasso regression into the Sequentially Threshold Least Squares (STLS) algorithm, which can complete sparse regression of PDE coefficients with the constraints More >

  • Open Access

    ARTICLE

    Results Involving Partial Differential Equations and Their Solution by Certain Integral Transform

    Rania Saadah1, Mohammed Amleh1, Ahmad Qazza1, Shrideh Al-Omari2,*, Ahmet Ocak Akdemir3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1593-1616, 2024, DOI:10.32604/cmes.2023.029180 - 17 November 2023

    Abstract In this study, we aim to investigate certain triple integral transform and its application to a class of partial differential equations. We discuss various properties of the new transform including inversion, linearity, existence, scaling and shifting, etc. Then, we derive several results enfolding partial derivatives and establish a multi-convolution theorem. Further, we apply the aforementioned transform to some classical functions and many types of partial differential equations involving heat equations, wave equations, Laplace equations, and Poisson equations as well. Moreover, we draw some figures to illustrate 3-D contour plots for exact solutions of some selected More >

  • Open Access

    ARTICLE

    On Time Fractional Partial Differential Equations and Their Solution by Certain Formable Transform Decomposition Method

    Rania Saadeh1, Ahmad Qazza1, Aliaa Burqan1, Shrideh Al-Omari2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3121-3139, 2023, DOI:10.32604/cmes.2023.026313 - 09 March 2023

    Abstract This paper aims to investigate a new efficient method for solving time fractional partial differential equations. In this orientation, a reliable formable transform decomposition method has been designed and developed, which is a novel combination of the formable integral transform and the decomposition method. Basically, certain accurate solutions for time-fractional partial differential equations have been presented. The method under concern demands more simple calculations and fewer efforts compared to the existing methods. Besides, the posed formable transform decomposition method has been utilized to yield a series solution for given fractional partial differential equations. Moreover, several More >

  • Open Access

    ARTICLE

    The Fractional Investigation of Some Nonlinear Partial Differential Equations by Using an Efficient Procedure

    Fairouz Tchier1, Hassan Khan2,3,*, Shahbaz Khan2, Poom Kumam4,5, Ioannis Dassios6

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2137-2153, 2023, DOI:10.32604/cmes.2023.022855 - 23 November 2022

    Abstract The nonlinearity in many problems occurs because of the complexity of the given physical phenomena. The present paper investigates the non-linear fractional partial differential equations’ solutions using the Caputo operator with Laplace residual power series method. It is found that the present technique has a direct and simple implementation to solve the targeted problems. The comparison of the obtained solutions has been done with actual solutions to the problems. The fractional-order solutions are presented and considered to be the focal point of this research article. The results of the proposed technique are highly accurate and More >

  • Open Access

    ARTICLE

    A Weighted Average Finite Difference Scheme for the Numerical Solution of Stochastic Parabolic Partial Differential Equations

    Dumitru Baleanu1,2,3, Mehran Namjoo4, Ali Mohebbian4, Amin Jajarmi5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1147-1163, 2023, DOI:10.32604/cmes.2022.022403 - 27 October 2022

    Abstract In the present paper, the numerical solution of Itô type stochastic parabolic equation with a time white noise process is imparted based on a stochastic finite difference scheme. At the beginning, an implicit stochastic finite difference scheme is presented for this equation. Some mathematical analyses of the scheme are then discussed. Lastly, to ascertain the efficacy and accuracy of the suggested technique, the numerical results are discussed and compared with the exact solution. More >

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