Typhoon risk and climate-change impact assessment for cultural heritage asset roofs

Recent catastrophic events in Southeast Asia have emphasized that roofs made of wood/steel frames and lightweight metal roofing sheets are the most vulnerable component in the building envelope when subjected to typhoon-induced wind uplift. This also applies to aging cultural heritage (CH) assets, which deserve special consideration because of their intangible value for local communities, and their essential role for inclusive and sustainable socio-economic development through cultural tourism. This paper introduces a simulation-based framework for fragility analysis and typhoon risk assessment of CH-asset roofs. Fastener pullout and roof-panel pullover are explicitly considered in the proposed framework to model the progressive failure of the roof system. A simplified roof geometry is assumed, requiring limited information about the structure under investigation and low computational resources. Such a low computational burden allows modeling wind-induced demands and component capacities probabilistically as well as considering the effects of load redistributions due to fastener failure and fastener/roof-panel corrosion. Variance-based sensitivity analysis (i.e., Sobol’ indices) based on polynomial chaos expansions of the limit state function is also performed, highlighting the parameters most affecting typhoon-fragility variance and then requiring special attention during data collection. Climate-change impact on the typhoon risk estimates is finally investigated through the use of various scenarios and a time-dependent function modifying the wind hazard profile of the site where the assets of interest are located. The proposed framework is applied to 25 CH assets in Iloilo City, Philippines. The required input data was collected through rapid visual surveying combined with new technologies, such as drones. It is shown that the proposed framework can be adopted in practice for both risk prioritization at a building-portfolio level and simplified risk assessment at a building-specific level

Typhoon fragility analysis and climate change impact assessment of Filipino cultural heritage asset roofs

Cultural Heritage (CH) assets are especially vulnerable to natural hazards (e.g., earthquake-induced ground shaking, typhoon-induced strong wind, and flooding) due to the lack of hazard-resistant features and to aging-induced extensive structural degradation. These considerations, together with their high historical/cultural value, justify the prioritization/implementation of disaster risk reduction (DRR) and resilience-enhancing strategies for the preservation of such assets. This paper proposes a probabilistic, simulation-based framework for the derivation of wind fragility relationships for CH roofs. Roof-panel pullout and pullover failure modes are used to model the progressive failure of the roof system, thus enabling the integration of fastener corrosion effects and load redistribution into the proposed fragility model. Monte-Carlo sampling is used to propagate the uncertainties related to wind-induced demands and roof component (i.e., fasteners and panels) capacities. Climate projections are used to assess the impact of climate change on wind hazard variations, and ultimately on the asset wind risk profile over time. An illustrative application of the proposed procedure is presented with reference to 25 heritage buildings in Iloilo City, Philippines

Dynamic structural health monitoring for concrete gravity dams based on the Bayesian inference

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

A multi-fidelity Bayesian framework for robust seismic fragility analysis

Fragility analysis of structures via numerical methods involves a complex trade-off between the desired accuracy, the explicit consideration of uncertainties (both epistemic and aleatory) related to the numerical structural model and the available computational performance. This paper introduces a framework for deriving numerical fragility relationships based on multi-fidelity non-linear models of the structure under investigation and response-analysis types. The proposed framework aims to reduce the computational burden while achieving a desired accuracy of the fragility estimates without neglecting aleatory and epistemic uncertainties. The proposed approach is an extension of the well-known robust fragility (RF) analysis framework. Different model classes, each characterised by increasing refinement, are used to define multi-fidelity polynomial expansions of the fragility model parameters. Each analysis result is then considered as a ‘new observation’ in a Bayesian framework and used to update the coefficients of the polynomial expansions. An adaptive sampling algorithm is also proposed to futher improve the performance of the multi-fidelity framework. Specifically, such an adaptive sampling algorithm relies on partitioning the sample space and the Kullback–Leibler divergence to find the optimal sampling path. The sample space partitioning allows an analyst to specify different criteria and parameters of the algorithm for different regions, thus further improving the performance of the procedure. The proposed approach is illustrated for an archetype reinforced concrete (RC) frame for which two model classes are developed/analysed: the simple lateral mechanism analysis (SLaMA), coupled with the capacity spectrum method, and non-linear dynamic analysis. Both model classes involve a cloud-based approach employing unscaled real (i.e. recorded) ground motions. The fragility relationships derived with the proposed procedure are finally compared to those calculated by using only the most advanced/high-fidelity (HF) model class, thus quantifying the performance of the proposed approach and highlighting further research needs

Seismic screening and structural investigation of heritage buildings for adaptive reuse: a survey study at Iloilo City, Philippines

Building adaptive reuse has been a popular strategy for cultural heritage conservation of structures for it serves two basic objectives of preserving heritage structures and promoting cultural heritage and tourism. Adaptive reuse is the adaptation of an old structure to allow the introduction of a modern function into the old structure. Old buildings are not demolished but recycled into modern uses. This strategy, however, needs a careful and thorough assessment of these existing heritage buildings to assure their resilience and sustainability to future hazards. Heritage buildings for adaptive reuse due to age and structural deterioration are highly vulnerable to hazards like earthquakes. Moreover, these buildings when used for commercial purposes may be subjected to additional loads due to changes in function. Considering the age of the structure, conformity to new design codes, additional loads imposed by unit modification, and the new function brought about by adaptive reuse of these structures, there is a need to assess these buildings to assure their safety and continuous use. Promoting adaptive reuse of heritage buildings and tourism is most appropriate in heritage zones like Calle Real in Iloilo City, the site for the case study. This paper presents a rapid seismic screening of buildings to prioritize a population of heritage buildings in a heritage zone for further detailed inspection. A site survey of the buildings was conducted at the heritage zone of Calle Real, Iloilo City in terms of their current use, and current condition to determine potential structural, maintenance, and functional issues related to resilience and to recommend future improvements in the implementation of adaptive reuse of heritage structures in cities and towns to assure their sustainability

Model parameter estimation using Bayesian and deterministic approaches: the case study of the Maddalena Bridge

Finite element modeling has become common practice for assessing the structural health of historic constructions. However, because of the uncertainties typically affecting our knowledge of the geometrical dimensions, material properties and boundary conditions, numerical models can fail to predict the static and dynamic behavior of such structures. In order to achieve more reliable predictions, important information can be obtained measuring the structural response under ambient vibrations. This wholly non-destructive technique allows obtaining very accurate information on the structure’s dynamic properties (Brincker and Ventura (2015)). Moreover, when experimental data is coupled with a finite element model, an estimate of the boundary conditions and the mechanical properties of the constituent materials can also be obtained via model updating procedures. This work presents two different model updating procedures. The first relies on construction of local parametric reduced-order models embedded in a trust region scheme to minimize the distance between the natural frequencies experimentally determined and the corresponding numerically evaluated ones (Girardi et al. (2018)). The second has been developed within a Bayesian statistical framework and uses both frequencies and mode shapes (Yuen (2015)). Both algorithms are used in conjunction with the NOSA-ITACA code for calculation of the eigenfrequencies and eigenvectors. These procedures are illustrated in the case study of the medieval Maddalena Bridge in Borgo a Mozzano (Italy). Experimental data, frequencies and mode shapes, acquired in 2015 (Azzara et al. (2017)) have enabled calibration of the bridge’s constituent materials and boundary condition

Construction phases analysis of unreinforced masonry buildings through equivalent frame model

Structural analysis of masonry buildings is affected by many uncertainties and characterized by issues related to the very nature of the material. In this scenario, refined analysis methodologies are confined to the research environment, while professional applications need simpler methodologies, which allow for a better understanding of the analysis results: the equivalent frame model is one of these methodologies. However, the method is affected by some issues, which, if not adequately addressed, may lead to unrealistic stress distributions. In this work, we propose a procedure that increases the reliability of the analysis results. It consists in the modification of the model depending on the nature of the acting loads in relation to the different construction phases of the structure. In addition, an extension of the method for the analysis of buildings constructed in different periods is introduced. Finally, the results of the analysis performed for a case study are presented in order to validate the proposed methods

Acoustic Fluid-Structure Interaction Modeling of Gravity Dams in the Frequency Domain

The assessment of the seismic safety of gravity dams is a topic of great importance in civil engineering. In this paper, fluid structure interaction modeling of gravity dams during earthquakes is investigated. In particular, this work aims to provide physical significance of a plan numerical model simulating the dam and the infinite length reservoir when a horizontal ground motion acts at the dam foundation. After a preliminary calibration of the model with analytical solutions, the dynamic properties of the numerical model are investigated via modal and frequency response analyses. The fully coupled mechanical-acoustic model is also compared to the widespread “added mass” model [1] adopted in most national codes

Hierarchical Bayesian framework for uncertainty reduction in the seismic fragility analysis of concrete gravity dams

Concrete gravity dams are critical infrastructures for communities to meet the basic human needs as well as rising standards of living. Most of the existing concrete gravity dams in Italy were built before the introduction of seismic regulations. Although no concrete gravity dams have as yet suffered a catastrophic collapse during or after a seismic event, their preservation remains a key aspect for communities, also in view of that older dams may have deteriorated to a critical level. For these reasons, researchers and practitioners in dam engineering are working to improve seismic fragility, and ultimately seismic risk, assessment procedures. Since no case histories are available, numerical modelling plays an important role, even though many uncertainties can affect the models and then the estimation of the seismic fragility. This paper presents a robust hierarchical Bayesian framework for the calibration of dynamic parameters of dam numerical models based on ambient vibrations, which allows an analyst to reduce uncertainties in the seismic fragility derivation. A probabilistic predictive model of the dam modal behaviour based on the general Polynomial Chaos Expansion is adopted in order to reduce the computational burden and a numerical algorithm for the solution of the inverse problem based on Markov Chain Monte Carlo is also presented. The proposed approach is applied to an existing large concrete gravity dam in Italy, and the effect of epistemic uncertainty reduction is finally evaluated in terms of fragility curves

A multi-hazard risk prioritisation framework for cultural heritage assets

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