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Discrete adjoint returns almost zero sensitivities with inverse design objective |
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March 12, 2018, 14:35
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Discrete adjoint returns almost zero sensitivities with inverse design objective
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Member
Zeno
Join Date: Sep 2013
Location: Delft, The Netherlands
Posts: 63
Rep Power: 12  |
Hello,
I downloaded the test case 'steady_inverse_adjoint' from the GitHub page of SU2 and I tried to run a shape optimization with a discrete adjoint method. The optimization terminates after one single function and adjoint evaluation since the sensitivities are O(1e-11). On the other hand, when running the optimization with a continuous adjoint technique, everything works fine and a minimum is reached after 28 function and 11 gradient evaluations. Any idea why this happens? Thank for the help, Z |
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| discrete adjoints, inverse design, shape optimization |
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