We present a prototype of the flood early warning system (EWS) developed within the UrbanFlood FP7 project. The system monitors sensor networks installed in flood defenses (dikes, dams, embankments, etc.), detects sensor signal abnormalities, calculates dike failure probability, and simulates possible scenarios of dike breaching and flood propagation. All the relevant information and simulation results are fed into an interactive decision support system that helps dike managers and city authorities to make informed decisions in case of emergency and in routine dike quality assessment. In addition to that, a Virtual Dike computational module has been developed for advanced research into dike stability and failure mechanisms, and for training the artificial intelligence module on signal parameters induced by dike instabilities. This paper describes the UrbanFlood EWS generic design and functionality, the computational workflow, the individual modules, their integration via the Common Information Space middleware, and the first results of EWS monitoring and performance benchmarks.
We present a decision support system for flood early warning and disaster management. It includes the models for datadriven meteorological predictions, for simulation of atmospheric pressure, wind, long sea waves and seiches; a module for optimization of flood barrier gates operation; models for stability assessment of levees and embankments, for simulation of city inundation dynamics and citizens evacuation scenarios. The novelty of this paper is a coupled distributed simulation of surface and subsurface flows that can predict inundation of low-lying inland zones far from the submerged waterfront areas, as observed in St. Petersburg city during the floods. All the models are wrapped as software services in the CLAVIRE platform for urgent computing, which provides workflow management and resource orchestration.
This discussion paper introduces the concept of the Virtual Artery as a multiscale model for arterial physiology and pathologies at the physics–chemistry–biology (PCB) interface. The cellular level is identified as the mesoscopic level, and we argue that by coupling cell-based models with other relevant models on the macro- and microscale, a versatile model of arterial health and disease can be composed. We review the necessary ingredients, both models of arteries at many different scales, as well as generic methods to compose multiscale models. Next, we discuss how this can be combined into the virtual artery. Finally, we argue that the concept of models at the PCB interface could or perhaps should become a powerful paradigm, not only as in our case for studying physiology, but also for many other systems that have such PCB interfaces.This article is part of the themed issue ‘Multiscale modelling at the physics–chemistry–biology interface’.
A three-dimensional cell-based mechanical model of coronary artery tunica media is proposed. The model is composed of spherical cells forming a hexagonal close-packed lattice. Tissue anisotropy is taken into account by varying interaction forces with the direction of intercellular connection. Several cell-centre interaction potentials for repulsion and attraction are considered, including the Hertz contact model and its neo-Hookean extension, the Johnson-Kendall-Roberts model of adhesive contact, and a wormlike chain model. The model is validated against data from uni-axial tension tests performed on dissected strips of tunica media. The wormlike chain potential in combination with the neo-Hookean Hertz contact model produces stress-stretch curves which represent the experimental data very well.
The paper analyses the experimental slope failure of a full-scale earthen dyke (levee) in Booneschans (Groningen, the Netherlands). The goals of the experiment were to develop efficient dyke-monitoring systems predicting various modes of failure well in advance of onset and to test the ability of numerical geotechnical models to predict the mode of failure and the time of collapse. Prior to the experiments, a special competition for the best prediction for all three planned tests had been announced. Several commercial corporations and scientific research organisations modelling dykes participated in the competition; the authors of this paper provided the best prediction for the macro-instability experiment, according to the decision of jury. The IJkDijk macro-instability test prediction has become the ultimate validation of the Virtual Dike simulation module, which is a functional part of the UrbanFlood early warning system for flood protection. Regarding sensor recordings, tilt measurements offered the simplest method of detecting the onset of slope failure. The early signs of progressing local instabilities in the dyke were registered by tilt sensors more than 4 d before the global collapse – a time that is sufficient for the dyke maintenance service to take necessary steps to reinforce the slope.
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