Data management and GIS in the Center for Disaster Management and Risk Reduction Technology (CEDIM): from integrated spatial data to the mapping of risk

International audienceThe project "Risk Map Germany" of the Center for Disaster Management and Risk Reduction Technology (CEDIM) aims at the examination of existing and the development of new approaches for integrated risk assessment as well as the realisation of risk analyses for selected threats and regions. Hazard, vulnerability and risk maps display the results and provide valuable information for planning, insurances, emergency management, science and the public. This article describes the development of the basic information infrastructure for CEDIM and the "Risk Map Germany" providing components for the networking of participating institutions, for common data management, data dissemination and publication. While a web based project platform offers information and communication facilities for all the project members and also the presentation of CEDIM to the public, an integrated data base is prepared as foundation for cross-discipline but common risk assessment. It is made available by the spatial data service "CEDIM Data Center" which allows the project members to inform themselves about the characteristics of existing data and its applicability for their specific tasks by exploring GIS functionalities. Suitable data can be downloaded and further processed in their own work environment. The components' alignment with the principles of Spatial Data Infrastructures is required to accomplish the suppositions for long-term availability and accessibility of data, information and services

Stochastic method for in-situ damage analysis

Based on the physics of stochastic processes we present a new approach for structural health monitoring. We show that the new method allows for an in-situ analysis of the elastic features of a mechanical structure even for realistic excitations with correlated noise as it appears in real-world situations. In particular an experimental set-up of undamaged and damaged beam structures was exposed to a noisy excitation under turbulent wind conditions. The method of reconstructing stochastic equations from measured data has been extended to realistic noisy excitations like those given here. In our analysis the deterministic part is separated from the stochastic dynamics of the system and we show that the slope of the deterministic part, which is linked to mechanical features of the material, changes sensitively with increasing damage. The results are more significant than corresponding changes in eigenfrequencies, as commonly used for structural health monitoring.Comment: This paper is accepted by European Physical Journal B on November 2. 2012. 5 pages, 5 figures, 1 tabl