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On the random wave equation within the mean square context

  • * Corresponding author: Juan Carlos Cortés

    * Corresponding author: Juan Carlos Cortés 
Abstract / Introduction Full Text(HTML) Figure(4) Related Papers Cited by
  • This paper deals with the random wave equation on a bounded domain with Dirichlet boundary conditions. Randomness arises from the velocity wave, which is a positive random variable, and the two initial conditions, which are regular stochastic processes. The aleatory nature of the inputs is mainly justified from data errors when modeling the motion of a vibrating string. Uncertainty is propagated from these inputs to the output, so that the solution becomes a smooth random field. We focus on the mean square contextualization of the problem. Existence and uniqueness of the exact series solution, based upon the classical method of separation of variables, are rigorously established. Exact series for the mean and the variance of the solution process are obtained, which converge at polynomial rate. Some numerical examples illustrate these facts.

    Mathematics Subject Classification: Primary: 35C05, 35C10, 35R60.


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  • Figure 1.  Expectation and variance of the solution $ u(x,t) $ to (1), for different space-time points and orders of truncation $ N $ of the series (2). This figure corresponds to Example 1.

    Figure 2.  Rate of convergence of $ \mathbb{E}[u_N(0.5,2)] $ and $ \mathbb{V}[u_N(0.5,2)] $ with $ N $, where $ u_N(x,t) $ is the truncation (11) of $ u(x,t) $ (2). This figure corresponds to Example 1.

    Figure 3.  Expectation and variance of the solution $ u(x,t) $ to (1), for different space-time points and orders of truncation $ N $ of the series (2). This figure corresponds to Example 2.

    Figure 4.  Rate of convergence of $ \mathbb{E}[u_N(0.5,2)] $ and $ \mathbb{V}[u_N(0.5,2)] $ with $ N $, where $ u_N(x,t) $ is the truncation (11) of $ u(x,t) $ (2). This figure corresponds to Example 2.

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