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            <title xml:lang="en">DIRECT COMPUTATION OF ABSORBING BOUNDARY CONDITIONS AT THE DISCRETE LEVEL</title>
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            <idno type="halRefHtml">&lt;i&gt;13th World Congress on Computational Mechanics (WCCM XIII)&lt;/i&gt;, Jul 2018, New York, United States</idno>
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            <idno type="stamp" n="UNIV-EIFFEL">Université Gustave Eiffel</idno>
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                <title xml:lang="en">DIRECT COMPUTATION OF ABSORBING BOUNDARY CONDITIONS AT THE DISCRETE LEVEL</title>
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                <term xml:lang="en">discrete method</term>
                <term xml:lang="en">Helmholtz equation</term>
                <term xml:lang="en">wave</term>
                <term xml:lang="en">absorbing boundary</term>
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              <p>The calculation of wave radiation in exterior domains by finite element methods can lead to large computations. A large part of the exterior domain is meshed and this computational domain is truncated at some distance where local or global boundary conditions are imposed at this artificial boundary. These conditions at finite distance must simulate as closely as possible the exact radiation condition at infinity and are generally obtained by discretizing an operator on the boundary. Here, we propose a different approach, still based on the finite element method. Instead of finding an absorbing operator and then discretizing it, we will estimate the absorbing operator directly at the discrete level and build a sparse matrix approximating the absorbing condition. This discrete absorbing matrix is added to the dynamic stiffness matrix of the problem which is then solved in a classical way. The problem is considered for acoustics in the frequency domain and is described by the Helmholtz equation. The coefficients of the absorbing matrix are found from the solutions of small size linear systems for each node on the radiating boundary. This is done using a set of radiating functions for which a boundary condition is written. The precision of the method is estimated from the number of functions in the test set and from the number of coefficients allowed in the sparse matrix. Finally, some examples are computed to validate the method.</p>
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