http://www.colloquiam.com/wd/index.php?action=history&feed=atom&title=Margetis_et_al_2022aMargetis et al 2022a - Revision history2026-05-14T19:22:38ZRevision history for this page on the wikiMediaWiki 1.27.0-wmf.10http://www.colloquiam.com/wd/index.php?title=Margetis_et_al_2022a&diff=262840&oldid=prevMove page script: Move page script moved page Margetis et al 1970a to Margetis et al 2022a2022-11-25T15:06:42Z<p>Move page script moved page <a href="/public/Margetis_et_al_1970a" class="mw-redirect" title="Margetis et al 1970a">Margetis et al 1970a</a> to <a href="/public/Margetis_et_al_2022a" title="Margetis et al 2022a">Margetis et al 2022a</a></p>
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</td></tr></table>Move page scripthttp://www.colloquiam.com/wd/index.php?title=Margetis_et_al_2022a&diff=260072&oldid=prevJSanchez: JSanchez moved page Draft Sanchez Pinedo 302374214 to Margetis et al 1970a2022-11-22T13:30:59Z<p>JSanchez moved page <a href="/public/Draft_Sanchez_Pinedo_302374214" class="mw-redirect" title="Draft Sanchez Pinedo 302374214">Draft Sanchez Pinedo 302374214</a> to <a href="/public/Margetis_et_al_1970a" class="mw-redirect" title="Margetis et al 1970a">Margetis et al 1970a</a></p>
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</td></tr></table>JSanchezhttp://www.colloquiam.com/wd/index.php?title=Margetis_et_al_2022a&diff=260071&oldid=prevJSanchez at 13:30, 22 November 20222022-11-22T13:30:53Z<p></p>
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<td colspan='2' style="background-color: white; color:black; text-align: center;">Revision as of 13:30, 22 November 2022</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Abstract ==</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Abstract ==</div></td></tr>
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</table>JSanchezhttp://www.colloquiam.com/wd/index.php?title=Margetis_et_al_2022a&diff=260069&oldid=prevJSanchez at 13:30, 22 November 20222022-11-22T13:30:51Z<p></p>
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<td colspan='2' style="background-color: white; color:black; text-align: center;">Revision as of 13:30, 22 November 2022</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>Gradient-based optimization for large-scale problems governed by unsteady PDEs, in which gradients with respect to the design variables are computed using unsteady adjoint, are characterized by the backward in time integration of the adjoint equations, which require the instantaneous primal/flow fields to be available at each time-step. The most widely used technique to reduce storage requirements, at the expense of a controlled number of recomputations, is binomial check-pointing. Alternatively, one may profit of lossless and lossy compression techniques, such as iPGDZ+, this paper relies upon. iPGDZ+is a hybrid algorithm which consists of (a) an incremental variant of the Proper Generalized Decomposition (iPGD), (b) the ZFP and (c) the Zlib compression algorithms. Two different implementations of iPGDZ+are described: (a) the Compressed Full Storage (CFS ) strategy which stores the whole time-history of the flow solution using iPGDZ+and (b) the Compressed Coarse-grained Check-Pointing (3CP ) technique which combines iPGDZ+with check-pointing. Assessment in aerodynamic shape optimization problems in terms of storage saving, computational cost and representation accuracy are included along with comparisons with binomial check-pointing. The methods presented are implemented within the in-house version of the publicly available adjointOptimisation library of OpenFOAM, for solving the flow and adjoint equations and conducting the optimization.</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>Gradient-based optimization for large-scale problems governed by unsteady PDEs, in which gradients with respect to the design variables are computed using unsteady adjoint, are characterized by the backward in time integration of the adjoint equations, which require the instantaneous primal/flow fields to be available at each time-step. The most widely used technique to reduce storage requirements, at the expense of a controlled number of recomputations, is binomial check-pointing. Alternatively, one may profit of lossless and lossy compression techniques, such as iPGDZ+, this paper relies upon. iPGDZ+is a hybrid algorithm which consists of (a) an incremental variant of the Proper Generalized Decomposition (iPGD), (b) the ZFP and (c) the Zlib compression algorithms. Two different implementations of iPGDZ+are described: (a) the Compressed Full Storage (CFS ) strategy which stores the whole time-history of the flow solution using iPGDZ+and (b) the Compressed Coarse-grained Check-Pointing (3CP ) technique which combines iPGDZ+with check-pointing. Assessment in aerodynamic shape optimization problems in terms of storage saving, computational cost and representation accuracy are included along with comparisons with binomial check-pointing. The methods presented are implemented within the in-house version of the publicly available adjointOptimisation library of OpenFOAM, for solving the flow and adjoint equations and conducting the optimization.</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">== Abstract ==</ins></div></td></tr>
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</table>JSanchezhttp://www.colloquiam.com/wd/index.php?title=Margetis_et_al_2022a&diff=260067&oldid=prevJSanchez at 13:30, 22 November 20222022-11-22T13:30:50Z<p></p>
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<td colspan='2' style="background-color: white; color:black; text-align: center;">Revision as of 13:30, 22 November 2022</td>
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<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">                                </ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">==Summary==</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Gradient-based optimization for large-scale problems governed by unsteady PDEs, in which gradients with respect to the design variables are computed using unsteady adjoint, are characterized by the backward in time integration of the adjoint equations, which require the instantaneous primal/flow fields to be available at each time-step. The most widely used technique to reduce storage requirements, at the expense of a controlled number of recomputations, is binomial check-pointing. Alternatively, one may profit of lossless and lossy compression techniques, such as iPGDZ+, this paper relies upon. iPGDZ+is a hybrid algorithm which consists of (a) an incremental variant of the Proper Generalized Decomposition (iPGD), (b) the ZFP and (c) the Zlib compression algorithms. Two different implementations of iPGDZ+are described: (a) the Compressed Full Storage (CFS ) strategy which stores the whole time-history of the flow solution using iPGDZ+and (b) the Compressed Coarse-grained Check-Pointing (3CP ) technique which combines iPGDZ+with check-pointing. Assessment in aerodynamic shape optimization problems in terms of storage saving, computational cost and representation accuracy are included along with comparisons with binomial check-pointing. The methods presented are implemented within the in-house version of the publicly available adjointOptimisation library of OpenFOAM, for solving the flow and adjoint equations and conducting the optimization.</ins></div></td></tr>
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</table>JSanchezhttp://www.colloquiam.com/wd/index.php?title=Margetis_et_al_2022a&diff=260066&oldid=prevJSanchez: Created blank page2022-11-22T13:30:48Z<p>Created blank page</p>
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