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http://dx.doi.org/10.5139/JKSAS.2008.36.7.634

Study on the Applications of Automatic Differentiation in Engineering Computation  

Lee, Jae-Hun (한국과학기술원 항공우주공학과 대학원)
Im, Dong-Kyun (한국과학기술원 항공우주공학과 대학원)
Kwon, Jang-Hyuk (한국과학기술원 항공우주공학과)
Publication Information
Journal of the Korean Society for Aeronautical & Space Sciences / v.36, no.7, 2008 , pp. 634-641 More about this Journal
Abstract
Automatic Differentiation(AD) is a tool for generating sensitivities, such as gradient or Jacobian, automatically. AD tools provide mathematically exact sensitivities for the given source code. In this paper applications of automatic differentiation are studied. Derivative codes are generated with AD tools for structural analysis code and flow analysis code. How to apply AD tools is explained and the accuracy of sensitivities is compared with the finite difference. Sensitivities of generated derivative code accord well with finite difference, but the calculation time of derivative code increases. It was found that the calculation time can be decreased by additional modification of derivative code.
Keywords
Automatic Differentiation; Sensitivity; CSM; CFD;
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