Zhong Zhang, Bo Cui, Pengxu Chen, Liming Zhou, Yue Wu
{"title":"Hygro-thermo-mechanical-electro coupling inhomogeneous isogeometric analysis of functionally graded piezoelectric structures under hygrothermal environment","authors":"Zhong Zhang, Bo Cui, Pengxu Chen, Liming Zhou, Yue Wu","doi":"10.1016/j.camwa.2025.12.002","DOIUrl":"10.1016/j.camwa.2025.12.002","url":null,"abstract":"<div><div>The functionally graded piezoelectric structure (FGPS) is one of the core structures for the design and development of new intelligent components, and has excellent piezoelectric effect and gradient distribution characteristics. Since FGPS has a complex structure and often operates in complex environments, it is essential to propose an efficient algorithm for solving the multi-physics coupling problem of FGPS. Based on the structural characteristics of FGPS, this study introduces NURBS basis functions, proposes hygro-thermo-mechanical-electro coupling inhomogeneous isogeometric analysis (HTMEI-IGA) combining the constitutive equations and boundary conditions of FGPS, and derives the control equations and motion equations of HTMEI-IGA. The free vibration, transient response and harmonic response of FGPS in the hygrothermal field are solved using the subspace iteration method and the Newmark method. The convergence and accuracy of HTMEI-IGA are verified through multiple numerical examples. The influence of exponential factors, moisture and thermal on the FGPS structure is also studied, providing a new means for design and development of FGPS.</div></div>","PeriodicalId":55218,"journal":{"name":"Computers & Mathematics with Applications","volume":"204 ","pages":"Pages 71-96"},"PeriodicalIF":2.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145813853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Nonconforming finite element method and reduced order algorithm for poroelasticity problem","authors":"Xue Wang , Hongxing Rui , Xiaozhe Hu","doi":"10.1016/j.camwa.2025.12.022","DOIUrl":"10.1016/j.camwa.2025.12.022","url":null,"abstract":"<div><div>In this work, we develop a nonconforming finite element method for the three-field Biot model, where the variables are displacement, Darcy velocity, and pore pressure. The discretization employs the lowest-order Crouzeix-Raviart (CR) element for both displacement and Darcy velocity, and piecewise constant element for pressure. We establish the well-posedness of the discrete problem with respect to a carefully chosen weighted norm, ensuring robustness with respect to both discretization and physical parameters. Furthermore, we prove optimal convergence of the proposed scheme. To improve computational efficiency, we introduce a reduced-order CR method based on the proper orthogonal decomposition (POD) technique. Numerical experiments are provided to verify the theoretical convergence rates and to demonstrate the effectiveness of the reduced-order approach.</div></div>","PeriodicalId":55218,"journal":{"name":"Computers & Mathematics with Applications","volume":"204 ","pages":"Pages 216-230"},"PeriodicalIF":2.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Unconditionally energy-stable and accurate schemes based on hyperbolic tangent scalar auxiliary variable approach for gradient flows","authors":"Haihong Zhou , Huan Zhang , Xiaomin Pan","doi":"10.1016/j.camwa.2025.12.031","DOIUrl":"10.1016/j.camwa.2025.12.031","url":null,"abstract":"<div><div>In this paper, we extend the selection of auxiliary variables by proposing a hyperbolic tangent scalar auxiliary variable (tanh-SAV) approach for solving gradient flows. The proposed tanh-SAV schemes introduce an auxiliary variable based on the hyperbolic tangent function, providing a well-defined formulation that enables the construction of decoupled, linear, and efficient numerical schemes. We demonstrate the construction of first-order, second-order, and higher-order unconditionally energy-stable schemes, utilizing either the Crank–Nicolson method or a <em>k</em>-step backward differentiation formula for time discretization. Only one constant-coefficient equation needs to be solved per time step, and we prove that all resulting tanh-SAV schemes are uniquely solvable at each time level. Furthermore, the theoretical analysis demonstrates the discrete energy stability of the proposed numerical schemes and proves the positivity property of the auxiliary variable. For the tanh-SAV/BDF<em>k</em> schemes (<span><math><mrow><mi>k</mi><mo>=</mo><mn>2</mn><mo>,</mo><mn>3</mn><mo>,</mo><mn>4</mn></mrow></math></span>) combined with a Fourier pseudo-spectral spatial discretization, we further establish fully discrete optimal-order error estimates. In addition, we provide numerical simulations of one- and two-dimensional Cahn–Hilliard, Allen–Cahn, and phase-field crystal models. The results demonstrate that, consistent with the theoretical analysis, the proposed schemes preserve the positivity of the auxiliary variable, maintain excellent stability, and achieve the desired temporal accuracy.</div></div>","PeriodicalId":55218,"journal":{"name":"Computers & Mathematics with Applications","volume":"204 ","pages":"Pages 263-282"},"PeriodicalIF":2.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Image restoration strategy stimulated level set model for segmenting images with strongly disturbance information","authors":"Yanjun Ren , Dong Li , Liming Tang","doi":"10.1016/j.camwa.2025.11.023","DOIUrl":"10.1016/j.camwa.2025.11.023","url":null,"abstract":"<div><div>In order to solve the problems of pixel misclassification, boundary leakage and unstable segmentation model encountered by the traditional level set method when dealing with images with strong disturbance information, this paper introduces a new energy functional based on a global-like global fitting term and a variational denoising term into variational level set framework, which not only significantly improves the segmentation of severe intensity inhomogeneous images and effectively realizes the denoising and deblurring process of images. Specifically, we utilize fitting term constructed with global and global-like information to reduce the sensitivity of the traditional level set method to intensity inhomogeneity. At the same time, we introduce a bounded Hessian variational restoration term to effectively suppressing the undesirable effects of strong noise, staircase artifacts, and blurring on segmentation. Moreover, a new edge indicator function was designed to enhance the model’s robustness to weak boundaries of the images. Experimental results on classical datasets demonstrate that our model exhibits significant advantages in noise suppression and edge preservation compared to existing state-of-the-art level set methods. The robustness and scalability of the model make it suitable for a wide range of image segmentation scenarios.</div></div>","PeriodicalId":55218,"journal":{"name":"Computers & Mathematics with Applications","volume":"204 ","pages":"Pages 123-139"},"PeriodicalIF":2.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145822950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Brian Choi, Jie Xu, Trevor Norton, Mark Kon, Julio E. Castrillón-Candás
{"title":"Analytic regularity of strong solutions for the complexified stochastic nonlinear Poisson-Boltzmann equation","authors":"Brian Choi, Jie Xu, Trevor Norton, Mark Kon, Julio E. Castrillón-Candás","doi":"10.1016/j.camwa.2025.12.003","DOIUrl":"10.1016/j.camwa.2025.12.003","url":null,"abstract":"<div><div>The nonlinear Poisson-Boltzmann equation (nPBE) is a fundamental partial differential equation (PDE) in electrostatics, widely used in computational biology and chemistry to model potential fields in solvents or plasmas. In this paper, we consider the problem of quantifying the statistical uncertainty of the stochastic nPBE solution under random variations in its coefficients. We establish the existence and uniqueness of solutions of the complexified nPBE using a contraction mapping argument, as conventional convex optimization techniques for the real-valued nPBE do not naturally extend to the complex setting. Using the existence and uniqueness result, we demonstrate that the solutions admit analytic extensions over a well-defined region in the complex hyperplane The analyticity makes the computation for statistics of real-valued quantities of interest amenable to numerical techniques such as sparse grids. Sparse grids are applied to uniformly approximate analytic functions with algebraic to sub-exponential error with respect to the number of knots, thus allowing for efficient approximations of high-dimensional integrals. Our numerical experiments confirm the predicted error behavior.</div></div>","PeriodicalId":55218,"journal":{"name":"Computers & Mathematics with Applications","volume":"204 ","pages":"Pages 97-122"},"PeriodicalIF":2.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145822955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A linear, unconditionally stable, second order decoupled method for the Ericksen-Leslie model with SAV approach","authors":"Ruonan Cao , Nianyu Yi","doi":"10.1016/j.camwa.2025.11.018","DOIUrl":"10.1016/j.camwa.2025.11.018","url":null,"abstract":"<div><div>In this paper, we present a second order, linear, fully decoupled, and unconditionally energy stable scheme for solving the Erickson-Leslie model. This approach integrates the pressure correction method with a scalar auxiliary variable technique. We rigorously demonstrate the unconditional energy stability of the proposed scheme. Furthermore, we present several numerical experiments to validate its convergence order, stability, and computational efficiency.</div></div>","PeriodicalId":55218,"journal":{"name":"Computers & Mathematics with Applications","volume":"204 ","pages":"Pages 52-70"},"PeriodicalIF":2.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Nonlocal multiplicative denoising method based on variational approach and topological shape optimization","authors":"El Hadji S. Diop","doi":"10.1016/j.camwa.2025.11.024","DOIUrl":"10.1016/j.camwa.2025.11.024","url":null,"abstract":"<div><div>In this work we propose multiplicative image denoising methods that are based on variational methods and topological shape optimization techniques. First, we extend a total variation-based multiplicative denoising approach to the W<sup>1,<em>p</em></sup> Sobolev space using the p-Dirichlet integral as a regularizer. We then formulate the new denoising problem as a topological shape optimization problem, which is solved using a generalized adjoint method. We propose a nonlocal denoising method that works on patch-by-patch basis thanks to the useful information given by the topological sensitivity, which is explicitly provided. Obtained numerical experiments on speckled and SAR images show neat qualitative and quantitative improvements of the proposed methods, especially in very noisy environments. Results show that the nonlocal method performs better than other denoising approaches in comparison.</div></div>","PeriodicalId":55218,"journal":{"name":"Computers & Mathematics with Applications","volume":"204 ","pages":"Pages 1-23"},"PeriodicalIF":2.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145753834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhixian Lv , Jiahao Huang , Chengyang Yue , Junseok Kim , Yibao Li
{"title":"Efficient prediction of phase-field crystal dynamics via β-variational autoencoders and time-series transformers on coupled physical fields","authors":"Zhixian Lv , Jiahao Huang , Chengyang Yue , Junseok Kim , Yibao Li","doi":"10.1016/j.camwa.2025.12.024","DOIUrl":"10.1016/j.camwa.2025.12.024","url":null,"abstract":"<div><div>Dendritic crystal growth is a complex phenomenon that has traditionally required high-fidelity simulations, which are computationally expensive. This study introduces a data-driven reduced-order modeling framework for efficient prediction of dendritic crystal growth. A <em>β</em>-variational autoencoder is utilized to compress coupled physical fields into a compact latent space. We systematically evaluate the impact of the regularization parameter and latent dimensionality on reconstruction accuracy. The trained encoder-decoder pair is integrated into an end-to-end time-series forecasting framework, where multiple representative models are employed to predict future latent dynamics. We investigate the influence of input sequence length and prediction horizon on forecasting accuracy, as well as the inference efficiency of the different models. Numerical experiments on a phase-field crystal growth dataset demonstrate that the proposed approach achieves high reconstruction fidelity, robust predictive performance, and significant reduction in computational cost. This offers a practical solution for fast modeling and multi-scale dynamics prediction in complex physical systems.</div></div>","PeriodicalId":55218,"journal":{"name":"Computers & Mathematics with Applications","volume":"204 ","pages":"Pages 198-215"},"PeriodicalIF":2.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"New highly efficient and accurate numerical scheme for the Cahn-Hilliard-Brinkman system","authors":"Dawei Chen, Qinzhen Ren, Minghui Li","doi":"10.1016/j.camwa.2025.12.016","DOIUrl":"10.1016/j.camwa.2025.12.016","url":null,"abstract":"<div><div>In this paper, based on a generalized scalar auxiliary variable approach with relaxation (R-GSAV), we construct a class of high-order backward differentiation formula (BDF) schemes with variable time steps for the Cahn-Hilliard-Brinkman(CHB) system. In theory, it is strictly proved that the designed schemes are unconditionally energy-stable. With the delicate treatment of adaptive strategies, we propose several adaptive time-stepping algorithms to enhance the robustness of the schemes. More importantly, a novel hybrid-order adaptive time steps algorithm performs outstanding for the coupled system. The hybrid-order algorithm inherits the advantages of some traditional high-order BDF adaptive strategies. A comprehensive comparison with some adaptive time-stepping algorithms is given, and the advantages of the new adaptive time-stepping algorithms are emphasized. Finally, the effectiveness and accuracy of the new methods are validated through a series of numerical experiments.</div></div>","PeriodicalId":55218,"journal":{"name":"Computers & Mathematics with Applications","volume":"204 ","pages":"Pages 182-197"},"PeriodicalIF":2.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An efficient hybrid Fourier KAN-SepONet solver for the high-frequency Helmholtz equation and convergence analysis","authors":"Rui Zhang , Yu Gao","doi":"10.1016/j.camwa.2025.12.006","DOIUrl":"10.1016/j.camwa.2025.12.006","url":null,"abstract":"<div><div>The high-frequency Helmholtz equations are extensively emerging in many fields, such as seismic wave detection, medicine, and the military. Deep neural networks have shown promise in solving differential equations, yet remain challenged by the ill-conditioning of high-frequency Helmholtz operators. To address this, we propose a Hybrid Fourier KAN-SepONet solver for high-frequency Helmholtz equations. Our approach transforms the problem into a well conditioned integral operator equation using potential theory, approximates the integral operator efficiently via SepONet, and solves it with a physics-informed Fourier KAN. We prove the reformulated equation is a second-kind Fredholm system and analyze convergence through the condition number of the training matrix. Numerical results confirm the solver’s efficiency.</div></div>","PeriodicalId":55218,"journal":{"name":"Computers & Mathematics with Applications","volume":"204 ","pages":"Pages 162-181"},"PeriodicalIF":2.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}