Suchergebnisse

Landslides are considered to be one of the main natural geohazards causing relevant economic damages and social effects worldwide. Italy is one of the countries worldwide most affected by landslides; in the Region of Tuscany alone, more than 100,000 phenomena are known and mapped. The possibility to recognize, investigate, and monitor these phenomena play a key role to avoid further occurrences and consequences. The number of applications of Advanced Differential Interferometric Synthetic Aperture Radar (A-DInSAR) analysis for landslides monitoring and mapping greatly increased in the last decades thanks to the technological advances and the development of advanced processing algorithms. In this work, landslide-induced damage on structures recognized and classified by field survey and velocity of displacement re-projected along the steepest slope were combined in order to extract fragility curves for the hamlets of Patigno and Coloretta, in the Zeri municipality (Tuscany, northern Italy). Images using ERS1/2, ENVISAT, COSMO-SkyMed (CSK) and Sentinel-1 SAR (Synthetic Aperture Radar) were employed to investigate an approximate 25 years of deformation affecting both hamlets. Three field surveys were conducted for recognizing, identifying, and classifying the landslide-induced damage on structures and infrastructures. At the end, the damage probability maps were designed by means of the use of the fragility curves between Sentinel-1 velocities and recorded levels of damage. The results were conceived to be useful for the local authorities and civil protection authorities to improve the land managing and, more generally, for planning mitigation strategies. ; This work has been carried out within the project founded and supported by the Regional government of Tuscany, under the agreement "Monitoring ground deformation in the Tuscany Region with satellite radar data". Roberto Tomás was supported by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO), the State Agency of Research (AEI) and European Funds for Regional Development (FEDER), under projects TEC2017-85244-C2-1-P and PRX17/00439.

DR 2002/08 Departament d'EIO - Research Supported by PRIME European Project ; Real-time models for estimating incident probabilities (EIP models) are innovative methods for predicting the potential occurrence of incidents and improving the effectiveness of incident management policies devoted to increasing road safety. EIP models imbedded in traffic management systems can lead to the development of control strategies for reducing the likelihood of incidents before they occur. This paper presents and discusses the design, implementation and off-line testing of an EIP model in the PRIME (Prediction of Congestion and Incidents in Real Time for Intelligent Incident Management and Emergency Traffic Management) Project of the "Information Societies Technology Programme" of the EU. A statistically-oriented approach based on Generalized Linear Regression models with polytomous responses is developed: geometry, traffic and weather conditions are taken as explanatory variables at a road section level and a binary variable related to incident occurrence or otherwise for the prevailing conditions is taken as a response variable on the first level of decision. Once the probability of a generic incident has been predicted, the lower level models in the selected hierarchical approach will predict the probabilities of incidents in a set of categories defined at a design level. The EIP model has been incorporated in the AIMSUN microscopic simulation environment (developed by TSS ). AIMSUN is able to emulate a traffic management system, since it simulates traffic evolution including the replication of observed incidents and incorporates different modules of incident and traffic management in such a way that the impact of traffic management strategies can be evaluated by simulation. A test site in Barcelona, located in a 15-km portion of the Ronda de Dalt ring road provided the data for calibrating and testing the EIP module. The selected site is equipped with 12 CCTV cameras for traffic monitoring, 18 local controllers, 12 detection stations, 10 variable message panels and 13 variable speed signals. Detection stations provide measures of different traffic variables in lane detail every minute. ; Preprint

DR 2002/08 Departament d'EIO - Research Supported by PRIME European Project ; Real-time models for estimating incident probabilities (EIP models) are innovative methods for predicting the potential occurrence of incidents and improving the effectiveness of incident management policies devoted to increasing road safety. EIP models imbedded in traffic management systems can lead to the development of control strategies for reducing the likelihood of incidents before they occur. This paper presents and discusses the design, implementation and off-line testing of an EIP model in the PRIME (Prediction of Congestion and Incidents in Real Time for Intelligent Incident Management and Emergency Traffic Management) Project of the "Information Societies Technology Programme" of the EU. A statistically-oriented approach based on Generalized Linear Regression models with polytomous responses is developed: geometry, traffic and weather conditions are taken as explanatory variables at a road section level and a binary variable related to incident occurrence or otherwise for the prevailing conditions is taken as a response variable on the first level of decision. Once the probability of a generic incident has been predicted, the lower level models in the selected hierarchical approach will predict the probabilities of incidents in a set of categories defined at a design level. The EIP model has been incorporated in the AIMSUN microscopic simulation environment (developed by TSS ). AIMSUN is able to emulate a traffic management system, since it simulates traffic evolution including the replication of observed incidents and incorporates different modules of incident and traffic management in such a way that the impact of traffic management strategies can be evaluated by simulation. A test site in Barcelona, located in a 15-km portion of the Ronda de Dalt ring road provided the data for calibrating and testing the EIP module. The selected site is equipped with 12 CCTV cameras for traffic monitoring, 18 local controllers, 12 detection stations, 10 variable message panels and 13 variable speed signals. Detection stations provide measures of different traffic variables in lane detail every minute. ; Preprint

Efforts to perform the deterministic and probabilistic analysis and to improve the safety of the Ignalina NPP are continuously being increased in Lithuania. Probabilistic safety estimation at the Ignalina NPP shows that it is necessary to keep on performing risk analysis and to continue improving safety. Technical experiments and calculations in different countries allow an unambiguous conclusion that the main building constructions of the Ignalina NPP would withstand the falling of light planes and can be destroyed by heavy transport or military planes. Crash of a light plane on the Ignalina NPP may damage separate systems important for the safety of the plant (for example, to break off the lines of the external electric system) and cause other accidents. Thus, the modelling of aircraft crash occurrence and its impact on the Ignalina NPP is significant in order to evaluate risk and prevent potential failure of the systems important to safety. In this work, we improve the aircraft crash probability estimation model in order to analyze the importance of the used parameters for the results. The aircraft crash probability on the territory of the NPP with the radius r may be expressed by the derived formula. This formula is used to calculate the aircraft crash probability using the most recent statistical data. As part of the initial conditions and parameters of aircraft crash models are not well-known or have different values for different types of planes, the uncertainty analysis was performed for a new model. The sensitivity analysis determines the parameters that have the greatest influence on the model results. Conclusions about the importance of the parameters and sensitivity of the results are obtained using a linear approximation of the model under analysis.

Efforts to perform the deterministic and probabilistic analysis and to improve the safety of the Ignalina NPP are continuously being increased in Lithuania. Probabilistic safety estimation at the Ignalina NPP shows that it is necessary to keep on performing risk analysis and to continue improving safety. Technical experiments and calculations in different countries allow an unambiguous conclusion that the main building constructions of the Ignalina NPP would withstand the falling of light planes and can be destroyed by heavy transport or military planes. Crash of a light plane on the Ignalina NPP may damage separate systems important for the safety of the plant (for example, to break off the lines of the external electric system) and cause other accidents. Thus, the modelling of aircraft crash occurrence and its impact on the Ignalina NPP is significant in order to evaluate risk and prevent potential failure of the systems important to safety. In this work, we improve the aircraft crash probability estimation model in order to analyze the importance of the used parameters for the results. The aircraft crash probability on the territory of the NPP with the radius r may be expressed by the derived formula. This formula is used to calculate the aircraft crash probability using the most recent statistical data. As part of the initial conditions and parameters of aircraft crash models are not well-known or have different values for different types of planes, the uncertainty analysis was performed for a new model. The sensitivity analysis determines the parameters that have the greatest influence on the model results. Conclusions about the importance of the parameters and sensitivity of the results are obtained using a linear approximation of the model under analysis.