This paper deals with the failure risk of masonry constructions under the effect of floods. It is developed within a probabilistic framework, with loads and resistances considered as random variables. Two complementary approaches have been investigated for this purpose: – a global approach based on combined effects of several governing parameters with individual weighted contribution (material quality and geometry, presence and distance between columns, beams, openings, resistance of the soil and its slope. . .), – and a reliability method using the failure mechanism of masonry walls standing out-plane pressure. The evolution of the probability of failure of masonry constructions according to the flood water level is analysed. The analysis of different failure probability scenarios for masonry walls is conducted to calibrate the influence of each "vulnerability governing parameter" in the global approach that is widely used in risk assessment at the urban or regional scale. The global methodology is implemented in a GIS that provides the spatial distribution of damage risk for different flood scenarios. A real case is considered for the simulations, i.e. Cheffes sur Sarthe (France), for which the observed river discharge, the hydraulic load according to the Digital Terrain Model, and the structural resistance are considered as random variables. The damage probability values provided by both approaches are compared. Discussions are also developed about reduction and mitigation of the flood disaster at various scales (set of structures, city, region) as well as resilience.

The paper presents an integrated framework which deals with natural hazards (tsunamis), physical vulnerability modelling, risk of failure for industrial structures (metal structures) and structural resilience provided by plastic adaptation. Simplified models are proposed to describe the run-up and wave height attenuation in case of tsunamis. The results are calibrated in the case of important tsunamis having taken place in Asian region. The mechanical vulnerability of cylindrical metal tanks erected near the shoreline is also investigated. The fragility curves are then developed in order to describe the multimodal failure: overturning, rupture of anchorages and sliding, buoyancy, excessive bending effects or buckling. Corresponding fragility curves are developed under various conditions: height of tsunami waves, filling ratios and service conditions of the tanks, friction tank/ground as well as dimensions effects. Probabilistic description of the natural hazard and the fragility curves are presented. Sensitivity analysis is also performed in order to investigate the effect of various governing parameters. Furthermore, resilience concepts and metrics are proposed. Theoretical description of the damages and post-disaster recovery functions are discussed: plastic adaptation as well as elastic and plastic attractors.

This paper presents two complementary methods: an approach to compute a network data-set for indoor space of a building by using its two-dimensional (2D) floor plans and limited semantic information, combined with an optimal crowd evacuation method. The approach includes three steps: (1) generate critical points in the space, (2) connect neighbour points to build up the network, and then (3) run the optimal algorithm for optimal crowd evacuation from a room to the exit gates of the building. Triangulated Irregular Network (TIN) is used in the first two steps. The optimal evacuation crowd is not based on the nearest evacuation gate for a person but relies on optimal sorting of the waiting lists at each gate of the room to be evacuated. As an example case, a rectangular room with 52 persons with two gates is evacuated in 102 elementary interval times (one interval corresponds to the time for one step for normal velocity walking), whereas it would have been evacuated in not less than 167 elementary steps. The procedure for generating the customized network involves the use of 2D floor plans of a building and some common Geographic Information System (GIS) functions. This method combined with the optimal sorting lists will be helpful for guiding crowd evacuation during any emergency.

This study uses interferometric synthetic aperture radar (SAR) techniques to identify and track earthquake-induced landslides as well as lands prone to landslides, by detecting deformations in areas struck by earthquakes. The pilot study area investigates the Mila region in Algeria, which suffered significant landslides and structural damage (earthquake: M_w 5, 7 August 2020). DInSAR analysis shows normal interferograms with small fringes. The coherence change detection (CCD) and DInSAR analysis were able to identify many landslides and ground deformations also confirmed by Sentinel-2 optical images and field inspection. The most important displacement (2.5 m), located in the Kherba neighborhood, caused severe damage to dwellings. It is worth notice that CCD and DInSAR are very useful since they were also able to identify ground cracks surrounding a large zone (3.94 km² area) in Grarem City, whereas the Sentinel-2 optical images could not detect them. Although displacement time-series analysis of 224 interferograms (April 2015 to September 2020) performed using LiCSBAS did not detect any pre-event geotechnical precursors, the post-event analysis shows a 110 mm yr⁻¹ subsidence velocity in the back hillside of Kherba.