Results 51 to 60 of about 14,895 (148)

The homogeneous balance of undetermined coefficients method and its application

Open Mathematics, 2016
The homogeneous balance of undetermined coefficients method is firstly proposed to solve such nonlinear partial differential equations (PDEs), the balance numbers of which are not positive integers.
Wei Yi, He Xin-Dang, Yang Xiao-Feng
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Extended crystal PDE’S stability, II: The extended crystal MHD-PDE’S

Mathematical and Computer Modelling, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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The influence of polydiethylsiloxane (PDES) concentration on the tribolfilm of chlorophenyl silicone oil (CPSO) under high-temperature lubrication

Journal of Materials Research and Technology
As pivotal structural component, steels operating at high temperatures play a vital role in promoting the development of advanced equipment technology.
Yan Meng, Luo Yue, Xiangli Wen, Peng Wei, Xue Zhou, Jie Cheng, Pengpeng Bai, Qian Zhao, Yonggang Meng, Yu Tian   +9 more
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Optimal Combination of EEFs for the Model Reduction of Nonlinear Partial Differential Equations

Journal of Applied Mathematics, 2013
Proper orthogonal decomposition is a popular approach for determining the principal spatial structures from the measured data. Generally, model reduction using empirical eigenfunctions (EEFs) can generate a relatively low-dimensional model among all ...
Jun Shuai, Xuli Han
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Geometry of PDEs. I: Integral bordism groups in PDEs

Journal of Mathematical Analysis and Applications, 2006
Global solutions of formally integrable and completely integrable systems of partial differential equations are characterized by means of integral bordism groups. Unfortunately, a thorough acquintance with the author's articles, namely with \textit{A. Prástaro} [Acta Appl. Math. 51, 243--302 (1998; Zbl 0924.58103) and Acta Appl. Math.
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PDE-DKL: PDE-constrained deep kernel learning in high dimensionality

Many physics-informed machine learning methods for PDE-based problems rely on Gaussian processes (GPs) or neural networks (NNs). However, both face limitations when data are scarce and the dimensionality is high. Although GPs are known for their robust uncertainty quantification in low-dimensional settings, their computational complexity becomes ...
Yan, Weihao, Brune, Christoph, Guo, Mengwu   +2 more
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LE-PDE++: Mamba for accelerating PDEs Simulations

Partial Differential Equations are foundational in modeling science and natural systems such as fluid dynamics and weather forecasting. The Latent Evolution of PDEs method is designed to address the computational intensity of classical and deep learning-based PDE solvers by proposing a scalable and efficient alternative.
Liang, Aoming, Mu, Zhaoyang, liu, Qi, Li, Ruipeng, Ge, Mingming, Fan, Dixia   +5 more
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Numerical PDE solvers outperform neural PDE solvers

We present DeepFDM, a differentiable finite-difference framework for learning spatially varying coefficients in time-dependent partial differential equations (PDEs). By embedding a classical forward-Euler discretization into a convolutional architecture, DeepFDM enforces stability and first-order convergence via CFL-compliant coefficient ...
Chatain, Patrick, Rizvi-Martel, Michael, Rabusseau, Guillaume, Oberman, Adam   +3 more
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Construction of Pickering Double Emulsions Based on Xanthan Gum/Lysozyme Nanoparticles: Structure, Stability, and Co-Encapsulation of Epigallocatechin Gallate and β-Carotene

Foods
The low stability of water-in-oil-in-water (W1/O/W2) double emulsions greatly limits their applications. Therefore, in this study, W1/O/W2 Pickering double emulsions (PDEs) were prepared by a two-step emulsification method using polyglycerol ...
Yongpeng Yin, Denglin Luo, Lala Li, Xingguo Li, Mengyao Kang, Bakht Ramin Shah, Xianling Wei, Wei Xu   +7 more
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Solving nonlinear elliptic partial differential equations in 2D using oscillatory radial basis functions collocation method

Partial Differential Equations in Applied Mathematics
Oscillatory radial basis functions collocation method (ORBF-CM) has been proven to be an effective meshless numerical method for solving various linear elliptic partial differential equations (PDEs). In general, solving nonlinear PDEs is a daunting task.
T. Dangal, A.R. Lamichhane, B. Khatri Ghimire   +2 more
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