Mathematische Modellsimulation und Parameteridentifizierung zur Transportprognose

Drittmittelfinanzierte Gruppenförderung - Teilprojekt

Details zum übergeordneten Gesamtprojekt

Titel des Gesamtprojektes: BMBF Förderschwerpunkt Sickerwasserprognose

Details zum Projekt

Prof. Dr. Peter Knabner

Dr. Alexander Prechtel

Beteiligte FAU-Organisationseinheiten:
Lehrstuhl für Angewandte Mathematik (Modellierung und Numerik)

Mittelgeber: Bundesministerium für Bildung und Forschung (BMBF)
Projektstart: 01.01.2001
Projektende: 31.12.2003
Laufzeitverlängerung bis: 31.12.2004


Multicomponent reactive transport in natural porous media
Lehrstuhl für Angewandte Mathematik (Modellierung und Numerik)

Abstract (fachliche Beschreibung):

Mathematical simulation tools allow the quantitative integration of
competing transport and transformation processes which are relevant for a
seepage water risk prognosis. Therefore model simulations have to
contain a comprehensive process description, while they can serve for
parameter identification by inverse modelling of suitable column or
batch experiments, and allow to quantify the dependence of a key
variable on parameters through a simultaneous sensitivity analysis. The
software platform RICHY1D has been extended and is already intensively
and successfully used in universities, institutes and by consultants for
the 1D simulation of complex reactive transport and for parameter
identification. It stands out by the application of efficient and highly
accurate mathematical solution strategies for the resulting systems of
partial differential equations (e.g. locally mass conserving mixed
hybrid finite element discretisations, modified Newton’s method).
Besides the formerly existing modules for coupled surfactant-water
transport, multiphase flow, saturated-unsaturated flow or carrier
facilitated transport, the extensions contain in particular source terms
(boundary conditions, distributed sources, arbitrarily time dependent,
nonlinear and multiple (de-)sorption kinetics, mobilisation from a
residual NAPL phase), preferential flow with solute transport, and heat
transport in soils with coupling to reaction parameters of the
contaminant transport like Monod degradation parameters, e.g.. The
parameter identification is possible for the model extensions as well,
which allows the identification of multiple complex parametrizations
from suitable experiments (for example for source terms or microbially
mediated degradation, sorption characteristics and hydraulic
parameters). There is no need to impose a certain functional shape of
these nonlinearities, the so-called form-free identification is also
feasible, and furthermore a closed-flow experiment design can be
accounted for. The sensitivity analysis is provided separately for the
evaluation of the dependence of a key variable like the concentration of
arbitrary model parameters, what represents a powerful tool in a
transport simulation to identify controlling factors and evaluate
uncertainties of the data.


Bitterlich, S., & Knabner, P. (2003). Experimental design for outflow experiments based on a multi-level identification method for material laws. Inverse Problems, 19(5), 1011-1030.

Zuletzt aktualisiert 2019-09-04 um 11:15