The structural control of concrete gravity dams is of primary importance. In this context, numerical models play a fundamental role both to assess the vulnerability of gravity dams and to control their behaviour during normal operativity and after extreme events. In this regard, data monitoring represents an important source of information for numerical model calibrations. This study proposes a novel probabilistic procedure, defined in the Bayesian framework, to calibrate the parameters of finite elements models of dams. To this aim, monitoring data and the results of material tests are used as reference information. The computational burden is reduced by using a new hybridpredictive model of the dam displacements. An application on an Italian dam shows the feasibility of the proposed procedure.

Abstract. Multi-hazard risk assessment of building portfolios is of primary importance in natural-hazard-prone regions, particularly for the prioritisation of disaster risk reduction and resilience-enhancing strategies. In this context, cultural heritage assets require special consideration because of their high vulnerability to natural hazards – due to ageing and types of construction – and their strong links with communities from both an economic and a historical–sociocultural perspective. This paper introduces a multi-hazard risk prioritisation framework specifically developed for cultural heritage assets. The proposed framework relies on a multilevel rapid-visual-survey (RVS) form for the multi-hazard exposure data collection and risk prioritisation of case-study assets. Because of the multilevel architecture of the proposed RVS form, based on three levels of refinement and information, an increasing degree of accuracy can be achieved in the estimation of structural vulnerability and, ultimately, structural risk of the considered assets. At the lowest level of refinement, the collected data are used for the computation of seismic-risk and wind-risk prioritisation indices, specifically calibrated in this study for cultural heritage assets with various structural and non-structural features. The resulting indices are then combined into a unique multi-hazard risk prioritisation index in which the intangible value of cultural heritage assets is also considered. This is achieved by defining a score expressing the cultural significance of the asset. The analytic hierarchy process is extensively used throughout the study to reduce the subjectivity involved in the framework, thus obtaining a simplified yet robust approach which can be adapted to different building typologies. The proposed framework is applied to 25 heritage buildings in Iloilo City, Philippines, for which innovative, non-invasive techniques and tools for improved surveying have also been tested. Thermal and omnidirectional cameras have helped in the collection of structural data, together with drones for the inspection of roofs. Results of the study are presented and critically discussed, highlighting advantages and drawbacks of the use of new technologies in this field.

The preservation of concrete dams is a key issue for researchers and practitioners in dam engineering because of the important role played by these infrastructures in the sustainability of our society. Since most of existing concrete dams were designed without considering their dynamic behaviour, monitoring their structural health is fundamental in achieving proper safety levels. Structural Health Monitoring systems based on ambient vibrations are thus crucial. However, the high computational burden related to numerical models and the numerous uncertainties affecting the results have so far prevented structural health monitoring systems for concrete dams from being developed. This study presents a framework for the dynamic structural health monitoring of concrete gravity dams in the Bayesian setting. The proposed approach has a relatively low computational burden, and detects damage and reduces uncertainties in predicting the structural behaviour of dams, thus improving the reliability of the structural health monitoring system itself. The application of the proposed procedure to an Italian concrete gravity dam demonstrates its feasibility in real cases.

Abstract. Multi-hazard risk assessment of building portfolios is of primary importance in natural-hazard-prone areas, particularly for the prioritization of disaster risk reduction and resilience-enhancing strategies. In this context, cultural heritage assets require special consideration because of their high vulnerability to natural hazards – due to ageing and the type of constructions – and their strong links with communities from both an economic and a historical/sociocultural perspective. As part of the Cultural Heritage Resilience & Sustainability to multiple Hazards (CHeRiSH) project, funded by the UK Newton Fund, this paper introduces a multi-hazard risk prioritisation framework specifically developed for cultural heritage assets. The proposed framework relies on a multi-level rapid-visual-survey (RVS) form for the multi-hazard data collection and risk prioritization of case-study assets. Because of the multi-level architecture of the proposed RVS form, based on three levels of refinement/information, an increasing degree of accuracy can be achieved in the estimation of structural vulnerability and, ultimately structural risk of the considered assets. At the lowest level of refinement, the collected data are used for the computation of seismic and wind risk prioritization indices, specifically calibrated in this study for cultural heritage assets with various structural/non-structural features. The resulting indices are then combined into a unique multi-hazard risk prioritization index in which the intangible value of cultural heritage assets is also considered. This is achieved by defining a score expressing the cultural significance of the asset. The analytic hierarchy process is extensively used throughout the study to reduce the subjectivity involved in the framework, thus obtaining a simplified, yet robust, approach which can be adapted to different building typologies. The proposed framework is applied to 25 heritage buildings in Iloilo City, Philippines, for which innovative, non-invasive techniques and tools for improved surveying have also been tested. Thermal and omnidirectional cameras have helped in the collection of structural data, together with drones for the inspection of roofs. Results of the study are presented and critically discussed, highlighting advantages and drawbacks of the use of new technologies in this field.

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