Abstract: Multivariate and progressive uncertainty is the main factor of accuracy in simulation systems. It can be a critical issue for systems that forecast and prevent extreme events and related risks. To deal with this problem, computational uncertainty management strategies should be used. This paper aims to demonstrate an adaptation of the computational uncertainty management strategy in the framework of a system for prediction and prevention of such natural disasters as coastal floods. The main goal of the chosen strategy is to highlight the most significant ways of uncertainty propagation and to collocate blocks of action with procedures for reduction or evaluation of uncertainty in a way that catches the major part of model error. Blocks of action involve several procedures: calibration of models, data assimilation, ensemble forecasts, and various techniques for residual uncertainty evaluation (including risk evaluation). The strategy described in this paper was tested and proved based on a case study of the coastal flood prevention system in St. Petersburg.

Abstract: Surge floods in Saint-Petersburg are related to extreme natural phenomena of rare repeatability. A lot of works were devoted to the problems appeared during maintenance of the flood prevention facility complex in Saint-Petersburg. However a lot of investigation issues connected with similar extreme events in Baltic Sea are remained opened. In this work, for surge flood of rare repeatability reconstruction need combination of two approaches based on the statistical multidimensional extremum analysis and on the synthetic surge floods was made. Synthetic storm model, taking multidimensional probability distributions from Reanalysis was developed and synthetic cyclone generation for its implementation was proposed.

Abstract: Urban areas are characterised by high population densities and the resulting complex social dynamics. For urban planners to evaluate, analyse, and predict complex urban dynamics, a lot of scenarios and a large parameter space must be explored. In urban disasters, complex situations must be assessed in short notice. We propose the concept of an assisted decision support system to aid in these situations. The system interactively runs a scenario exploration, which evaluates scenarios and optimize for desired properties. We introduce the SIM-CITY architecture to run such interactive scenario explorations and highlight a use case for the architecture, an urban fire emergency response simulation in Bangalore.

Abstract: Numerical simulations of urgent events, e.g. tsunamis, storms and flash floods, must be completed within a stipulated deadline. The simulation results are needed by relevant authorities in making timely educated decisions to mitigate financial losses, manage affected areas and reduce casualties. The existing definition of urgent computing is too usage context specific and thus restricts the identification of urgent use cases and the general application of urgent computing. We aim to extend and refine the existing definition and provide a comprehensive general definition of urgent computing. This general definition will aid in the identification of urgent computing's unique challenges and thus demonstrates the need for innovative multi-disciplinary solutions to address these challenges.

Abstract: We developed a robust approach for real-time levee condition monitoring based on combination of data-driven methods (one-side classification) and finite element analysis. It was implemented within a flood early warning system and validated on a series of full-scale levee failure experiments organised by the IJkdijk consortium in August-September 2012 in the Netherlands. Our approach has detected anomalies and predicted levee failures several days before the actual collapse. This approach was used in the UrbanFlood decision support system for routine levee quality assessment and for critical situations of a potential levee breach and inundation. In case of emergency, the system generates an alarm, warns dike managers and city authorities, and launches advanced urgent simulations of levee stability and flood dynamics, thus helping to make informed decisions on preventive measures, to evaluate the risks and to alleviate adverse effects of a flood.

Abstract: Nowadays the importance of data collection, processing, and analyzing is growing tremendously. BigData technologies are in high demand in different areas, including bio-informatics, hydrometeorology, high energy physics, etc. One of the most popular computation paradigms that is used in large data processing frameworks is the MapReduce programming model. Today integrated optimization mechanisms that take into account only load balance and execution fast simplicity are not enough for advanced computations and more efficient complex approaches are needed. In this paper, we suggest an improved algorithm based on categorization for data reorganization in MapReduce frameworks using replication and network aspects. Moreover, for urgent computations that require a specific approach, the prioritization customization is introduced.

Abstract: Complex phenomena are increasingly attracting the interest of researchers from various branches of computational science. So far, this interest have conditioned the demand not only for more sophisticated autonomous models, but also for mechanisms that would associate them. This paper presents a multiscale agent-based modelling and simulation technique based on the incorporation of multiple modules. Two key principles are presented as guiding such an integration: common abstract space as a space, where entities of different models interact and commonly controlled agents – abstract actors operating in a common space, which can be handled by different agent-based models. Proposed approach is evaluated through series of experiments on simulating the emergency evacuation from the cinema building to the city streets, where building and street levels are reproduced in heterogeneous models.

Abstract: We present a resource provisioning and execution management solution for a flood decision support system. The system developed within the ISMOP project, features an urgent computing scenario in which flood threat assessment for large sections of levees is requested within a specified deadline. Unlike typical decision support systems which utilize heavyweight simulations in order to predict the possible course of an emergency, in ISMOP we employ an alternative approach based on the `scenario identification' method. We show that this approach is a particularly good fit for the resource provisioning model of IaaS Clouds. We describe the architecture of the ISMOP decision support system, focusing on the urgent computing scenario and its formal resource provisioning model. Preliminary results of experiments performed in order to calibrate and validate the model indicate that the model fits experimental data.

Abstract: This paper presents the concept of holistic approach to urgent computing which extends resources management in situation of emergency from computational resources to Data Acquisition and Preprocessing System. The layered structure of this system is presented in detail and its rearrangement in case of emergency is proposed. This process is harmonised with large scale computation using Urgent Service Profile. The proposed approach was validated by practical work performed under ISMOP project. Concrete examples of Urgent Service Profile definition have been discussed. Results of preliminary experiments related to energy management and data transmission optimization in case of emergency have been presented.

Abstract: The paper describes a software system to simulate the ship motions in a crisis situation. The scenario consists of the damaged ship subjected to wave excitation forces generated by a random sea base on real wave spectrum. The simulation is displayed in an interactive Virtual Environment allowing the visualization of the ship motions. The numerical simulation of the sea surface and ship motions requires intensive computation to maintain the real-time or even the fast-forward simulations, which are the only ones of interest for these situations. Dedicated tools to analyse the ship behaviour in time are also described. The system can be useful to evaluate the responses of the ship to the current sea state, namely the amplitude, variations and tendencies of ship motions, and help the planning and coordination of rescue operations.