Optimal Shape for Elliptic Problems with Random Perturbations
classification
🧮 math.OC
math.AP
keywords
omegaarrayformhboxoptimalperturbationrandomshape
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In this paper we analyze the relaxed form of a shape optimization problem with state equation $\{{array}{ll} -div \big(a(x)Du\big)=f\qquad\hbox{in}D \hbox{boundary conditions on}\partial D. {array}.$ The new fact is that the term $f$ is only known up to a random perturbation $\xi(x,\omega)$. The goal is to find an optimal coefficient $a(x)$, fulfilling the usual constraints $\alpha\le a\le\beta$ and $\displaystyle\int_D a(x) dx\le m$, which minimizes a cost function of the form $$\int_\Omega\int_Dj\big(x,\omega,u_a(x,\omega)\big) dx dP(\omega).$$ Some numerical examples are shown in the last section, to stress the difference with respect to the case with no perturbation.
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