Article
Engineering, Mechanical
Wanjun Xu, Xiang Wang, Tianhao Huang, Jiangang Yang
Summary: Since the successful application of the Elrod method to the JFO theory, new alternative methods have been presented, including improved cavitation algorithms based on unconstrained optimization and modulus-based methods. This paper reviews and compares these algorithms, providing pseudocodes for implementation. A novel equivalent symmetric matrix equation is proposed to enhance efficiency, and a case study shows the method can save computing time by over 2-5 times.
TRIBOLOGY INTERNATIONAL
(2023)
Article
Mathematics, Applied
Pelin Ciloglu, Hamdullah Yucel
Summary: This study investigates the numerical behavior of a convection diffusion equation with random coefficients by using stochastic Galerkin and discontinuous Galerkin methods. The efficiency and accuracy of the proposed methodology are demonstrated through numerical experiments on benchmark problems.
APPLIED NUMERICAL MATHEMATICS
(2022)
Article
Physics, Mathematical
Jialin Hong, Jialin Ruan, Liying Sun, Lijin Wang
Summary: This study introduces a numerical integration methodology for stochastic Poisson systems (SPSs) with multiple noises and different Hamiltonians in diffusion coefficients. By transforming SPSs into their canonical form and using a generating function approach, the proposed method is able to preserve the Poisson structure and Casimir functions of the systems while efficiently integrating them numerically.
COMMUNICATIONS IN COMPUTATIONAL PHYSICS
(2021)
Article
Mathematics, Applied
Gianluca Frasca-Caccia, Pranav Singh
Summary: In this paper, we present a procedure for identifying optimal methods in parametric families of numerical schemes for initial value problems in partial differential equations. The procedure maximizes accuracy by adaptively computing optimal parameters that minimize a defect-based estimate of the local error at each time step. We propose viable refinements to reduce computational overheads and maintain conservation properties of the original methods. Numerical tests demonstrate the improved efficiency of the new technique compared to existing methods.
JOURNAL OF SCIENTIFIC COMPUTING
(2023)
Article
Mathematics, Applied
Guoguo Yang, Xuliang Li, Xaiohua Ding
Summary: Arbitrary high order quadratic invariants and energy conservation parametric stochastic partitioned Runge-Kutta methods are proposed for stochastic canonical Hamiltonian systems, ensuring good performance and validity through the analysis of order conditions and parameter selection.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2021)
Article
Physics, Multidisciplinary
Jun Ohkubo
Summary: The proposed method in this study, which does not require a dataset and utilizes original system equations to evaluate targeted elements of the Koopman matrix, shows good performance and reliability in dealing with stochastic differential equations and obtaining the Koopman matrix.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2022)
Article
Mathematics, Applied
Kai Liu, Guiding Gu
Summary: In this paper, a family of fully implicit strong Ito-Taylor numerical methods for stochastic differential equations (SDE) is designed. These methods are based on truncating the general stochastic Ito-Taylor expansions to achieve high-order convergence. By selecting parameters, different stability properties can be obtained. The mean-square stability of the second-order case is investigated and numerical results are reported to demonstrate the convergence and stability properties of the methods.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2022)
Article
Mathematics, Interdisciplinary Applications
Xiao Ma, Modesar Shakoor, Dmytro Vasiukov, Stepan V. Lomov, Chung Hae Park
Summary: Numerical artifacts in FFT methods for multiphase elastic problems, caused by irregular discretization of the interface, are addressed in this study. An enhanced composite voxel method using the level-set technique is proposed to alleviate implementation difficulties and is particularly useful for non-parametrized interface representations.
COMPUTATIONAL MECHANICS
(2021)
Article
Physics, Multidisciplinary
Ali Raza, Jan Awrejcewicz, Muhammad Rafiq, Muhammad Mohsin
Summary: The Nipah virus is a zoonotic virus, and the proposed stochastic non-standard finite difference method in the numerical solution focuses on positivity and boundedness. This method explains the stability and convergence of biological problems' features effectively.
Article
Engineering, Civil
Hanbo Zhu, Jinsheng Cheng, Mei-Ling Zhuang, Chuanzhi Sun, Li Gao, Youzhi Wang, Junxiang Shao, Lu Han, Haibo Fang, Lin Zhao
Summary: Reinforced concrete column specimens with the same parameters often exhibit differences in bearing capacity and deformation under the same loading path. Most previous studies attribute these differences to instrumentation errors or randomness in material and bond dimensions. However, the method to improve the accuracy of numerical simulation for reinforced concrete components is still unclear. This research utilizes a weighted least squares estimation (WLS) method to fuse test samples and introduces stochastic parameters into the model through a genetic algorithm. By comparing the numerical seismic performance indexes with test results, it is shown that considering parameter randomness improves the simulation accuracy by 88%.
Article
Physics, Particles & Fields
Daniel Alvestad, Rasmus Larsen, Alexander Rothkopf
Summary: This study explores the potential of modern implicit solvers for stochastic partial differential equations in real-time complex Langevin dynamics simulations. The methods offer asymptotic stability and allow simulation at large Langevin time steps, leading to lower computational cost. The study compares different ways of regularizing path integrals and estimates errors introduced due to finite Langevin time steps, implementing benchmark thermal and non-thermal simulations of the quantum anharmonic oscillator.
JOURNAL OF HIGH ENERGY PHYSICS
(2021)
Article
Mathematics, Applied
Kevin Burrage, Pamela M. Burrage, Grant Lythe
Summary: This paper presents an algorithm for homogeneous diffusive motion on a sphere by considering the equivalent process of a randomly rotating spin vector. By introducing appropriate sets of random variables, families of methods are constructed that effectively preserve the spin modulus for every realization, achieved by exponentiating an antisymmetric matrix.
NUMERICAL ALGORITHMS
(2022)
Article
Meteorology & Atmospheric Sciences
N. Lafon, R. Fablet, P. Naveau
Summary: Data assimilation plays a crucial role in geosciences for reconstructing hidden dynamical processes. However, inferring the state posterior distribution remains a challenge, especially for complex nonlinear processes. This study proposes an end-to-end neural scheme that combines variational Bayes inference and a trainable solver to address data assimilation and uncertainty quantification simultaneously.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2023)
Article
Mathematics, Applied
Yabing Sun, Weidong Zhao
Summary: This paper is devoted to numerical methods for mean-field stochastic differential equations with jumps (MSDEJs). By developing the Ito formula and constructing the Ito-Taylor expansions, the strong order gamma and weak order eta Ito-Taylor schemes for MSDEJs are proposed and theoretically proven for their convergence rates. Numerical tests are conducted to verify the theoretical conclusions.
NUMERICAL ALGORITHMS
(2021)
Article
Mathematics, Applied
Peipei Lu, Andreas Rupp, Guido Kanschat
Summary: This article proves the uniform convergence of geometric multigrid V-cycle for hybridized discontinuous Galerkin methods, under a new set of assumptions on the injection operators. The method involves standard smoothers and local solvers, and the proofs utilize a weak version of elliptic regularity. The new assumptions allow for local injection operators on each coarse grid cell, and examples of admissible injection operators are provided.
SIAM JOURNAL ON NUMERICAL ANALYSIS
(2022)