A Primer on PDEs: Models, Methods, Simulations (UNITEXT, by Sandro Salsa, Federico M. G. Vegni, Anna Zaretti, Paolo

# A Primer on PDEs: Models, Methods, Simulations (UNITEXT, by Sandro Salsa, Federico M. G. Vegni, Anna Zaretti, Paolo By Sandro Salsa, Federico M. G. Vegni, Anna Zaretti, Paolo Zunino

This e-book is designed as a complicated undergraduate or a first-year graduate direction for college students from quite a few disciplines like utilized arithmetic, physics, engineering. It has advanced whereas instructing classes on partial differential equations over the last decade on the Politecnico of Milan. the most goal of those classes was once twofold: at the one hand, to coach the scholars to understand the interaction among conception and modelling in difficulties coming up within the technologies and however to offer them a fantastic historical past for numerical equipment, corresponding to finite alterations and finite parts.

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Additional info for A Primer on PDEs: Models, Methods, Simulations (UNITEXT, Volume 65)

Example text

Assume that the nonnegative function z (ξ) = −q (g(ξ))g (ξ) attains its positive maximum z (ξ M ) only at the point ξ M ∈ [a, b]. Then ts = min ξ∈[a,b] 1 1 = . 4 The method of characteristics revisited 39 Since xs belongs to the characteristics x = q (g (ξ M )) t + ξ M , we ﬁnd xs = q (g (ξ M )) + ξM . 2. The point (xs , ts ) has an interesting geometrical meaning. 43) admits an envelope and (xs , ts ) is the point on the envelope with minimum time coordinate. 43) with respect to ξ. Clearly, the envelope has not to be confused with the shock curve.

We conclude this minimal introduction to ﬁnite diﬀerence approximation of scalar conservation laws by addressing some considerations about stability, which clarify the behavior of the approximate solution compared to the original model and represent a necessary requirement to make sure that the numerical approximation converges to the exact solution u. We brieﬂy address the CFL condition (from Courant-Friedrichs-Lewy). It requires that the speed at which the scheme propagates the initial state must not be smaller than the characteristic speed of the model, namely |a| for the case ut +aux = 0.

7) we deduce ct = Dcxx − vcx which constitutes our mathematical model. 3 4 Assuming we can take the derivative inside the integral. [q] = [mass] × [time]−1 . 1. Notice that if v and D were non constant, we would get an equation of the form ct = (Dcx )x − (vc)x . 8). We want to determine the evolution of the concentration c, by knowing its initial proﬁle c (x, 0) = g (x) . 9) can be written in the form vcx + ct = ∇c · v =0, pointing out the orthogonality of ∇c and v. But ∇c is orthogonal to the level lines of c, along which c is constant.