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Using the Variational Approach and Adjoint Equations Method Under the Identification of the Input Parameter of the Passive Admixture Transport Model

  • Sergey Germanovich Demyshev
  • Vladimir Sergeevich Kochergin
  • Sergey Vladimirovich Kochergin
Conference paper
Part of the Springer Geology book series (SPRINGERGEOL)

Abstract

Method of the adjoint equations, estimation method and variational algorithm of the input parameters identification of the passive admixture transport model is considered in that work. Modification of the variational algorithm of the measurements data assimilation, allows saving the calculation resources under the algorithms numerical realization considerably. Problem of the contamination point source power estimation on the base of the evaluation method and working out the obtained estimations is solved. The numerical experiments for estimation the concentration fields according to the initial data and solving the corresponding adjoint problem are conducted. Variation algorithm of the initial pollution spot identification is realized. Possibility to use assimilation variational methods and measurements data filtration for the wide range of problems connected with investigated basin ecological state was shown in the present work. Modified scheme for realization of the variational algorithm identification of the model input parameters is suggested. Conditions, under which the suggested algorithm has advantages over the standard approach, were obtained. The conducted numerical experiments have shown the proven work of the identification algorithm of the contamination source parameters applying the passive admixture transport model in the Azov Sea. Good converging of the iteration process and accuracy of the concentration field initial distribution determination was obtained for the variational algorithm of the passive contaminant concentration initial field identification.

Keywords

Transport model Passive admixture Variational algorithm Adjoint problem Identification Azov sea 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Marine Hydrophysical Institute RASSevastopolRussian Federation

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