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The present interdisciplinary
SNF funded research project (4 professors from 5 research groups at D-BAUG) is
concerned about the development of a generic decision theoretical framework for
the consistent and rational management of earthquake risks in three situations,
namely, before, during and after an earthquake, see Figure 1. The decision
support framework is being designed for decision makers responsible for the
safety of personnel, environment and assets of a larger area such as e.g. a
region or a city. The system which is based on the Bayesian Decision Theory and
utilizes Bayesian Probabilistic Networks (BPN) is generic in the sense that it
is formulated in terms of characteristic descriptors (indicators) which can be
observed, see Figure 2. It can thus easily be adapted to the
characteristics of a specific region or city. The main emphasis will be on the
risks due to potential failures and collapses of building structures as well as
infrastructure systems such as bridges and tunnels. An important feature of the
decision framework is that it provides cost efficient decision support on how
to optimize investments into risk reducing measures.
The elaboration of the relevant condition indicators for the BPNs requires an interdisciplinary research group. At an integral level the
· decision theoretical framework and the uncertainty modelling of the indicators are studied at the Institute of Structural Engineering, Group Risk and Safety (IBK, Prof. Faber, Dr. Ulfkjaer, Dipl.-Ing. Bayraktarli).
The development of the indicators at a process oriented level are pursued in the relevant disciplines; Indicators concerning the
·
soil behaviour at the Institute for Geotechnical Engineering (IGT, Dr. Laue, Dipl.-Ing.).
·
structural behaviour at the Institute of Structural Engineering (IBK, Prof. Dazio, M.Sc. Yazgan).
·
measurement of damages at the Institute of Photogrammetry and Remote Sensing (IGP, Prof. Grün, M.Sc
Rezaeian).
·
consequence assessment at the Institute for Construction Engineering and Management (IBB, Prof. Schalcher, M.Sc
Faizian).
Figure 1: Decision situations
Figure 2: Bayesian Probabilistic Network
