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½²×ùÖ÷Ì⣺One-parameter spectral Galerkin methods for Timoshenko beam system with delay boundary feedback

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This talk deals with Timoshenko beam (TB) system with delay boundary feedback (DBF). For external-force-free TB system with DBF, an energy stability criterion is established. For solving general TB system with DBF, a class of one-parameter spectral Galerkin (OPSG) methods are suggested. It is proved under the appropriate conditions that OPSG methods can preserve the energy stability in the discrete sense. Based on a new projection operator and some analytical techniques, an L2-error estimate of the methods is derived. Finally, by performing several numerical experiments, the obtained theoretical results and the computational accuracy of the methods are further illustrated.

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½²×ùÖ÷Ì⣺An efficient sequential quadratic programming methods with finite element for American and swing option pricing

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In this talk, we present the recent work on the sequential quadratic programming method (SQPM) for American option pricing based on the variational inequality formulation. The variational inequality is discretized using the theta method in time and the finite element method in space. The resulting system of algebraic inequalities at each time step is solved through a sequence of box-constrained quadratic programming problems, with the latter being solved by a globally and quadratically convergent, large-scale suitable reflective Newton method. It is proved that the sequence of quadratic programming problems converges with a constant rate under a mild conditionon the time step size. The method is general in solving the variational inequalities for the option pricing with many styles of optimal stopping and complex underlying asset models. In particular, swing options and stochastic volatility and jump diffusion models are studied. Numerical examples are presented to confirm the effectiveness of the method. (This is joint work with Weizhang Huang and Jinye Shen.)

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½²×ùÖ÷Ì⣺High order structure-preserving arbitrary Lagrangian-Eulerian discontinuous Galerkin methods for the Euler equations under gravitational fields

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In this work, we present high-order arbitrary Lagrangian-Eulerian discontinuous Galerkin (ALE-DG) methods for the Euler equations under gravitational fields on the moving mesh. The goal of this paper is to demonstrate that, through careful design of the scheme, the ALE-DG methods can also achieve the structure-preserving properties of DG methods, such as high order accuracy, well-balanced property, positivity-preserving property, for the Euler equations with arbitrary moving meshes. We propose two well-balanced and positivity-preserving ALE-DG schemes which can preserve the explicitly given equilibrium state on arbitrary moving grids, and also carry out rigorous positivity-preserving analyses for both schemes. Our schemes are established both in one dimension and in two dimensions on unstructured triangular meshes. The most challenging component in designing such ALE-DG schemes on the moving mesh is to maintain the equilibrium state and the mass conservation at the same time, since temporal discretization of the ALE method may destroy the well-balanced property, and inappropriate adjustment of the numerical flux could lead to the loss of the mass conservation property on the moving meshes. A novel approximation of the desired equilibrium state based on ALE-DG methods on the moving mesh has been introduced to overcome such difficulty.Numerical experiments in different circumstances are provided to illustrate the well-balanced property, positivity-preserving property and high order accuracy. We also compare the schemes on the moving mesh and on the static mesh to demonstrate the advantage of ALE-DG methods for discontinuous solutions.

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½²×ùÖ÷Ì⣺A general collocation analysis for weakly singular Volterra integral equations with variable exponent

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Piecewise polynomial collocation of weakly singular Volterra integral equations (VIEs) of the second kind has been extensively studied in the literature, where integral kernels of the form (t-s)^{-\alpha} for some constant \alpha\in (0,1) are considered. Variable-order fractional-derivative differential equations currently attract much research interest, and in Zheng and Wang SIAM J. Numer. Anal. 2020 such a problem is transformed to a weakly singular VIE whose kernel has the above form with variable $\alpha = \alpha(t)$, then solved numerically by piecewise linear collocation, but it is unclear whether this analysis could be extended to more general problems or to polynomials of higher degree. In the present paper the general theory (existence, uniqueness, regularity of solutions) of variable-exponent weakly singular VIEs is developed, then used to underpin an analysis of collocation methods where piecewise polynomials of any degree can be used. The sharpness of the theoretical error bounds obtained for the collocation methods is demonstrated by numerical examples.

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½²×ùÖ÷Ì⣺Multi-output physics-informed neural network forPDE models

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In thistalk, a physics-informed neural network based on the time difference methodis developed tosome PDEmodels. Selecting the hyperbolic tangent function as the activation function, we construct a multi-outputneural network to obtain the numerical solution, which is constrained by the time discrete formulaand boundary conditions. Automatic differentiation technology is developed to calculate the spatialpartial derivatives. Numerical results are provided to confirm the effectiveness and feasibility of theproposed method and illustrate that compared with the single output neural network, using the multi-output neural network can effectively improve the accuracy of the predicted solution and save a lot ofcomputing time.

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½²×ùÖ÷Ì⣺Maximum-Norm Error Estimates of Fourth-Order Compact and ADI Compact Difference Methods for Nonlinear Bacterial Systems

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By introducing two temporal derivative-dependent auxiliary variables, a linearized and decoupled fourth-order compact finite difference method is developed and analyzed for the nonlinear coupled bacterial systems. The temporal-spatial error splitting technique and discrete energy method are employed to prove the unconditional stability and convergence of the method in discrete maximum-norm. Furthermore, to improve the computational efficiency, an ADI compact difference algorithm is proposed, and the unconditional stability and optimal-order maximum-norm error estimate are also strictly established. Finally, several numerical experiments are conducted to validate the theoretical convergence and to simulate the phenomena of bacterial extinction as well as the formation of endemic diseases. In particular, an adaptive time-stepping algorithm is developed and tested for long-term stable simulations.

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½²×ùÖ÷Ì⣺Astabilizer-free weak Galerkin finite element method for the Darcy-Stokes equations

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In this talk, we will introduce a new method for the Darcy-Stokes equations based on the stabilizer-free weak Galerkin ?nite element method. In the proposed method, we remove thestabilizer term by increasing the degree of polynomial approximation space of the weak gradient operator. We show that the new algorithm not only has a simpler formula, but also reduces the computational complexity. Some numerical tests are carried out to confirm the theoretical analysis.

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In the first part, the numerical solution of nonlocal problem with integrable kernels is considered. The structure of the true solution to the problem is analyzed first. The analysis leads naturally to a new kind of discontinuous Galerkin method that can more efficiently solve the problem numerically. Moreover, it has optimal convergence rate for any dimensional case under mild assumptions. Some applications, such as sub-diffusion equations are also given. In the second part, we show the convergence analysis of nonlocal solutions by polygonal approximations to the local limit of the original nonlocal solutions. Our finding reveals that the new nonlocal solution does not converge to the correct local limit when the number of sides of polygons is uniformly bounded. On the other hand, if the number of sides tends to infinity, the desired convergence can be shown. These results may be used to guide computational studies of nonlocal problems, such as Peridynamics.

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½²×ùÖ÷Ì⣺Bayesian parameter inference in partial differential equations using persistence diagram data

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In complex physical systems, parameter inference problems are frequently encountered. These problems arise when we attempt to estimate or infer the values of unknown parameters in mathematical models that describe the behavior or properties of physical systems. Parameter inference plays a crucial role in understanding and analyzing physical systems, as it allows us to fit model predictions to experimental data and gain insights into the underlying mechanisms. The Bayesian approach is a powerful tool for tackling such parameter inference problems. In this framework, it provides a formal and coherent way to combine prior knowledge or beliefs about the parameters with experimental data to estimate the posterior probability distributions. In this paper, we explore the posterior distribution when the observation is collected as persistence diagrams of the solutions to partial differential equations. The well-posedness of the posterior distribution is analyzed. Some numerical tests are given to verify the effectiveness of the proposed method.

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