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Titlebook: An Introduction to Scientific Computing; Fifteen Computationa Ionut Danaila,Pascal Joly,Marie Postel Textbook 2023Latest edition The Editor

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樓主: Monomania
11#
發(fā)表于 2025-3-23 10:34:10 | 只看該作者
Offene Fragen und weitere Forschungsans?tzee step to compute accurately the solution since it is necessary to capture rapid time scales. In this chapter, we consider a 1D advection-diffusion equation with a solution varying abruptly near one endpoint, making difficult to compute the solution in a reasonable time. We show how a finite-element stabilization method overcomes this difficulty.
12#
發(fā)表于 2025-3-23 14:15:52 | 只看該作者
13#
發(fā)表于 2025-3-23 21:17:26 | 只看該作者
14#
發(fā)表于 2025-3-23 23:10:36 | 只看該作者
15#
發(fā)表于 2025-3-24 02:40:18 | 只看該作者
16#
發(fā)表于 2025-3-24 10:26:20 | 只看該作者
Nonlinear Differential Equations: Application to Chemical Kinetics,, etc.). The numerical solution of this type of system is a domain of study in itself with flourishing literature. This chapter presents two seminal examples of such problems along with their numerical treatment.
17#
發(fā)表于 2025-3-24 14:34:37 | 只看該作者
,Solving an Advection–Diffusion Equation by a Finite Element Method,e step to compute accurately the solution since it is necessary to capture rapid time scales. In this chapter, we consider a 1D advection-diffusion equation with a solution varying abruptly near one endpoint, making difficult to compute the solution in a reasonable time. We show how a finite-element stabilization method overcomes this difficulty.
18#
發(fā)表于 2025-3-24 18:40:24 | 只看該作者
19#
發(fā)表于 2025-3-24 19:42:28 | 只看該作者
Gas Dynamics: The Riemann Problem and Discontinuous Solutions: Application to the Shock Tube Probleerived and compared with numerical solutions obtained using first- and second-order schemes (Lax-Wendroff and MacCormack). Upwind schemes (Godunov, Roe) specifically designed for hyperbolic equations are also presented.
20#
發(fā)表于 2025-3-25 00:37:17 | 只看該作者
Optimization Applied to Model Fitting,lexity in the most varied scientific fields. In this chapter, we recall some theoretical results concerning unconstrained optimization and we illustrate them on the problem of identifying parameters by adjustment to the data, for a simple epidemic model.
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