Estimation Of Seismic Risk Research Articles

Seismic risk estimates for reinforced concrete structures with incorporation of corrosion and aftershock

Numerous reinforced concrete (RC) structures are exposed to aggressive environments, such as chloride, mainshock and aftershock. These environmental and extreme loads have the potential to increase the seismic risks during structure's service life. This study introduces a practical probabilistic methodology to estimate the seismic risk of corroded RC frame subjected to mainshock-aftershock sequences. In this methodology, a time-variant modeling strategy is used to simulate the geometrical and mechanical properties of structural degraded materials. The Bayesian updating theorem is employed to calibrate the demand models, which are then used to estimate the fragilities and confidence intervals considering the model uncertainties. A Copula-based approach is conducted to generate joint probability of mainshock and aftershock intensities and the seismic hazard of the mainshock-aftershock scenario. Finally, the seismic risk and associated confidence intervals are estimated by integrating over all mainshock and aftershock intensities levels. A typical corroded RC frame structure is used to illustrate the proposed methodology. The results show that the contribution of corrosion and aftershock would lead a 10 times higher seismic risks compared to scenarios considering only mainshock damage. It is necessary to account for the influence of both corrosion and aftershock in seismic design.

Operational status effect on the seismic risk assessment of oil refineries

The operational status of an oil refinery (type and scale of operations that take place at any time instance) largely determines the amount of fuel produced, circulated within the facility, and stored in tanks. This status is affected by seasonality, periods of peak or low demand, as well as periods of routine maintenance. However, it is an aspect that is typically neglected even though it stands out among the factors that determine the seismic performance of several critical industrial assets, such as the storage tanks, as well as the consequences of any potential failure. An open-source refinery testbed is employed herein to demonstrate the effect of the refinery's operational status on the seismic risk estimates. Alternative realistic operational scenarios are developed following typical industry practices and are arranged over a time period between two refinery major maintenance shutdown events. The most probable damage state is selected for each asset to identify the most vulnerable ones. Based on the type and importance of the impacted assets, the potential consequences are determined at the facility level. Resulting estimates are very different if an earthquake strikes during a regular/high/low-demand period, or a maintenance period. The framework can be utilized to identify the locations within the refinery that may trigger cascading failures and secondary damages, should their assets be damaged by a seismic event. The outcomes can be exploited by stakeholders, risk engineers, and emergency action planners for developing customized and businesslike procedures to enhance the seismic resilience of the facility.

Mapping 1D seismic amplification effects in the range of periods of engineering interest based on geological data

Regional scale seismic hazard assessment including the effect of local seismo-stratigraphical conditions is a basic tool for seismic risk estimates. A novel physically based procedure is proposed for using geological maps to extensively estimate expected seismic amplification effects relative to spectral ordinates of main engineering interest (<0.8 s). Automatic GIS based analysis of geological maps, statistical data relative to the seismic/geotechnical properties of geological units and numerical modelling are combined to determine the probability distribution of expected amplification effects by accounting for uncertainty affecting the relevant parameters. To evaluate the feasibility of the proposed procedure, it has been applied to the Tuscany Region in Central Italy. Unbiasedness of outcomes has been tested by considering detailed microzonation studies available for the considered area. Results of the proposed approach could be easily implemented in extensive seismic risk analyses where detailed seismic microzonation studies are lacking.

Fragility and vulnerability models for poorly-detailed infilled buildings accounting for building-to-building and masonry infill variability

While in poorly-detailed masonry-infilled reinforced concrete (RC) buildings the significance of masonry infills is acknowledged, less attention has been paid to the variability surrounding their mechanical properties and its potential impact on fragility and, consequently, vulnerability models to be used in seismic risk estimation. This study addresses this gap by proposing updated fragility and vulnerability models of existing poorly-detailed masonry infilled and pilotis RC frames that consider the variability in building layout and infill properties. A large building portfolio, representative of those designed according to Italian codes between 1970 and 1980, is selected as case study, incorporating building-to-building variability through various geometrical configurations. Updated modelling uncertainty parameters, specifically derived for existing infilled RC frames, are used, including the variability surrounding the properties of different infill typologies and the occurrence of RC frame shear failure. The portfolio was analysed through multiple-stripe analyses, followed by the development of upgraded fragility models for buildings with different heights and geometrical configurations. Finally, the corresponding vulnerability models were derived using damage-to-loss models calibrated with post-earthquake observation damage data from the 2009 L'Aquila earthquake. The updated fragility and vulnerability curves can be used for more refined seismic risk estimates of large building portfolios, that account for building-to-building and infill-to-infill variability, revised modelling uncertainty estimates and a more robust intensity measure (AvgSa).

Influence of local versus national datasets on seismic loss estimates: A case study for residential buildings in the metropolitan area of Montreal, Canada

Assessing seismic losses requires information on ground shaking levels, a comprehensive inventory of elements at risk and their asset values to evaluate repair/reconstruction costs. The uncertainties associated with these parameters are often significant and the available data are often incomplete. This study aims to assess the value and utility of detailed data in refining seismic risk estimates. Over several years, detailed site conditions and residential exposure datasets were compiled for Greater Montreal. These models were used to estimate building damage and associated losses for various seismic scenarios. Recently, Natural Resources Canada developed a national exposure model to provide a National Earthquake Risk Profile using data derived from existing sources such as topographic maps and census data. This paper compares seismic loss projections for residential buildings using the local dataset as a baseline with those from the national model using OpenQuake and the latest Seismic Hazard Model. The local site model is based on in situ data and site measurements, while the global, proxy-based model relies on USGS correlations between slope topography and site classification. Results show that the global model overestimates seismic hazards, resulting in 30% higher residential losses than the local model. Absolute losses are increased by a factor of 3.6–5.6 depending on the building classification when using the national exposure model compared to the local inventory while relative losses are increased by a factor of 1.1–1.5. These results emphasize the need to develop detailed seismic risk assessment databases for accurate risk assessments, and for selecting appropriate risk reduction measures.

The assessment of probabilistic seismic risk using ground-motion simulations via a Monte Carlo approach

Accurately characterizing ground motions is crucial for estimating probabilistic seismic hazard and risk. The growing number of ground-motion models, and increased use of simulations in hazard and risk assessments, warrants a comparison between the different techniques available to predict ground motions. This research aims at investigating how the use of different ground-motion models can affect seismic hazard and risk estimates. For this purpose, a case study is considered with a circular seismic source zone and two line sources. A stochastic ground-motion model is used within a Monte Carlo analysis to create a benchmark hazard output. This approach allows the generation of many records, helping to capture details of the ground-motion median and variability, which a ground motion prediction equation may fail to properly model. A variety of ground-motion models are fitted to the simulated ground motion data, with fixed and magnitude-dependant standard deviations (sigmas) considered. These include classic ground motion prediction equations (with basic and more complex functional forms), and a model using an artificial neural network. Hazard is estimated from these models and then we extend the approach to a risk assessment for an inelastic single-degree-of-freedom-system. Only the artificial neural network produces accurate hazard results below an annual frequency of exceedance of 1 × 10–3 years−1. This has a direct impact on risk estimates—with ground motions from large, close-to-site events having more influence on results than expected. Finally, an alternative to ground-motion modelling is explored through an observational-based hazard assessment which uses recorded strong-motions to directly quantify hazard.

Seismic risk assessment using integrated MCDM method in West Bengal, India

Earthquakes are one of the natural hazards that threaten human lives and properties. Consequently, seismic risk assessment plays a significant role in disaster mitigation. This study estimates seismic risk in West Bengal, India, by integrating the two multi-criteria decision-making (MCDM) models: analytical hierarchy process (AHP) and Entropy. Integrated AHP-Entropy is used to determine vulnerability, seismic hazard, and coping capacity. The seismic risk was then assessed by integrating the thematic information of vulnerability, seismic hazard, and coping capacity. The results show that about 19% of the total area and 70% of the total population in West Bengal may be at very high seismic risk. The result is validated through a receiver operating characteristic curve, displaying satisfactory performance in seismic risk estimation. The findings of this study may help governmental agencies identify seismic-risk zones and establish seismic hazard plans in advance against any potential threat in the study region.

Seismic Fragility Analysis of Retaining Walls Dependent on Initial Conditions

Fragility curves of retaining walls constitute an efficient tool for the estimation of seismic risk and can be utilized for prevention from potential damage or for immediate decision-making. In this work, fragility curves for cantilever retaining walls of three different heights are proposed, considering cohesionless soil materials. The seismic response of the soil-wall system, in terms of permanent vertical ground displacement of the backfill soil and permanent horizontal displacement of the wall’s base, is estimated by conducting non-linear time history analyses, through the 2D finite element simulation method. Five initial conditions are investigated regarding the value of the global factor of safety (FS) under static conditions. An initial value of FS equal to 1.5 is considered for dry conditions. If the presence of the water table is taken into account, the corresponding FS drops to values ranging from 1.4 to 1.1. Parameters that characterize seismic intensity are evaluated based on criteria, in order to identify the intensity measures that best correlate with the system’s response. Three damage states are adopted, corresponding to minor, moderate, and extensive damage. The approach of combined damage criteria is also investigated. Finally, fragility curves are derived demonstrating the degree of dependency on initial conditions.

Improved seismic intensity measures and regional structural risk estimation models

Seismic intensity measures are essential quantitative parameters for evaluating and predicting engineering structures’ seismic risk and vulnerability. Various regional earthquake analysis and vulnerability models with evaluation and prediction capabilities have been developed using macroseismic and instrumental intensity measures. These results have significant positive implications for evaluating large-scale regional earthquake resilience and predicting earthquake risks. However, the traditional determination of seismic intensity measures is based on given seismic station detection data and macroscopic intensity standards, and the developed seismic risk models are relatively outdated, resulting in relatively low accuracy in assessing the vulnerability of regional structures. This paper proposed an improved instrumental intensity calculation equation and updated the model using 216,000 acceleration records monitored by nine typical seismic stations in China during the Jiuzhaigou earthquake on August 8, 2017. The proposed calculation model was combined with the latest version of China’s macrointensity standard, and undamaged building samples were sufficiently considered. The vulnerability level of 1,499 buildings surveyed in the Jiuzhaigou earthquake was assessed. This paper innovatively proposed a membership index calculation model to estimate the impact relationship between different vulnerability levels. A comparative curve model was generated with the updated vulnerability databases of four typical regional structures, considering different vulnerability membership indices. Using the improved seismic intensity measures and nonlinear regression model, an improved vulnerability fitting model was developed to assess the seismic risk of regional structures. The model was analysed and verified using field survey data from the Jiuzhaigou earthquake.

Bias in the Estimation of Seismic Risk for Municipal Building Stocks Due to Limited Data

This study investigated the effect of the building data knowledge level on seismic risk estimation for municipal building stocks, focusing on identifying the characteristics that influence loss estimation bias. Fifteen municipalities in two Slovenian regions were analysed using twelve building data knowledge levels, defined by combining different knowledge levels about building location and floor area. The knowledge levels ranged from those using data aggregated at the municipality level to those using building-specific data. The bias was quantified as the log residual between the expected annual losses estimated for the given knowledge level and the base-case level, characterised by building-specific data. The results indicate that loss estimation bias is affected by both the building location and floor-area knowledge levels. The data on building density distribution across the municipality and building-class-specific floor areas are sufficient for estimating loss with low bias with respect to the base-case level. The effect of potential data improvement on bias reduction can be assessed using building stock homogeneity and hazard variation indexes determined from readily available data. Further research is needed to explore loss estimation bias for building data knowledge levels not considered in this study and generalise the concepts to other regions and building classifications.

Seismic risk assessment of ageing existing reinforced concrete bridges accounting for uncertainty in bearing properties

A growing challenge in the seismic risk assessment of ageing existing bridge structures is the lack of knowledge of the key features of the structural components. In fact, the mechanical properties could change over time and the recommendations in the literature could be considerably different thus adopted modelling parameters can significantly alter the seismic response and risk estimates,e.g., expected annual losses (EAL) or mean annual frequency of collapse (MAFC). It is therefore crucial to understand the role of critical properties of structural components on seismic risk metrics before allocating further resources to estimate them more accurately.With the above in mind, this study focuses on analysing the importance of the frequently unknown properties of bridge bearings featuring un-reinforced thin elastomeric pads, typically used in bridges built in the ‘60 s and ‘70 s in Italy. For this purpose, a real case study bridge is selected and Latin Hypercube Sampling is performed to generate a large set of bearing parameters, namely the shear modulus and friction coefficient between rubber and concrete surfaces. Component-level seismic loss estimation of the bridge is performed for each bearing properties realisation, considering both the presence and absence of non-sacrificial shear keys at the cap beams. The EAL and MAFC results are scrutinised to analyse the impact of the variation in the bearing properties on such risk metrics. The main observations indicate that the influence of the shear modulus of rubber on these quantities is low, whereas the friction coefficient between concrete and rubber can lead to more impactful changes.

Automatic identification of residential building features using machine learning techniques

Seismic risk assessment represents a major challenge in countries with considerable seismic hazard and vulnerable built heritage, such as Italy. Especially for large-scale analyses, vulnerability evaluation may result in very time-consuming and expensive investigations. In order to tackle this problem, satellite images and street view pictures can be used to automatically collect data about buildings through Convolutional Neural Networks (CNNs).In this way, meaningful parameters that influence seismic vulnerability can be acquired remotely from images, with a significant reduction in time and costs. This can also lead to a better vulnerability assessment, thus to more precise seismic risk estimates.

Modelling site response at regional scale for the 2020 European Seismic Risk Model (ESRM20)

Quantitative estimation of seismic risk over a region requires both an underlying probabilistic seismic hazard model and a means to characterise shallow site response over a large scale. The 2020 European Seismic Risk Model (ESRM20) builds on the 2020 European Seismic Hazard Model (ESHM20), requiring additional information to firstly parameterise the local site condition across all of Europe, and subsequently determine its influence on the prediction of seismic ground motion. Initially, a harmonised digital geological database for Europe is compiled, alongside a model of topographic/bathymetric elevation and a database of 30 m averaged shearwave velocity measurements (V_{S30}), in order to produce separate 30 arc-second maps of inferred V_{S30} based on topography and on geology. We then capitalise on a large database of seismic recording stations in Europe for which site-to-site ground motion residuals (delta S2S_{S}) have been determined with respect to the shallow crustal ground motion model used in the ESHM20. These residuals allow us to incorporate site amplification functions into the European GMM calibrated upon either observed or inferred V_{S30}, or on the European geology and topography models. We present the resulting pan-European seismic site amplification model and assess its impact on seismic hazard and risk compared against other approaches. The new site amplification model fulfils the requirements of the ESRM20 and, providing uncertainty is fully propagated, yields estimates of seismic hazard and risk at a large space scale that may be comparable to other methods often applied at local/urban scale where better-constrained site information is available.

Improving urban seismic risk estimates for Bishkek, Kyrgyzstan, through incorporating recently gained geological knowledge of hazards

Many cities are built on or near active faults, which pose seismic hazard and risk to the urban population. This risk is exacerbated by city expansion, which may obscure signs of active faulting. Here, we estimate the risk to Bishkek city, Kyrgyzstan, due to realistic earthquake scenarios based on historic earthquakes in the region and an improved knowledge of the active fault sources. We use previous literature and fault mapping, combined with new high-resolution digital elevation models to identify and characterise faults that pose a risk to Bishkek. We then estimate the hazard (ground shaking), damage to residential buildings and distribution of losses (economical cost and fatalities) using the Global Earthquake Model OpenQuake engine. We model historical events and hypothetical events on a variety of faults that could plausibly host significant earthquakes. This includes proximal, recognised, faults as well as a fault under folding in the north of the city that we identify using satellite DEMs. We find that potential earthquakes on faults nearest to Bishkek—Issyk Ata, Shamsi Tunduk, Chonkurchak and the northern fault—would cause the most damage to the city. An Mw 7.5 earthquake on the Issyk Ata fault could potentially cause 7900 ± 2600 completely damaged buildings, a further 16,400 ± 2000 damaged buildings and 2400 ± 1500 fatalities. It is vital to properly identify, characterise and model active faults near cities to reduce uncertainty as modelling the northern fault as a Mw 6.5 instead of Mw 6.0 would result in 37% more completely damaged buildings and 48% more fatalities.

Epistemic uncertainty in poorly detailed existing frames accounting for masonry infill variability and RC shear failure

AbstractRobust performance‐based earthquake assessment should consider the effects of both aleatory and epistemic uncertainty on seismic response parameters. While the effects of modelling uncertainty on specific engineering demand parameters and collapse fragility curves have been widely investigated to date on bare frame structural typologies, little attention has been paid to the impact of masonry infill properties variability on the uncertainty estimation in existing infilled RC frames. Previous studies available in the literature are mainly related to seismically designed RC buildings and the suggestions provided in international guidelines cannot be reasonably adopted for poorly detailed RC existing frames. As regards the uncertainty in existing RC frames, the role of masonry infills was often neglected or their interaction with the surrounding frames was not rigorously accounted for in the uncertainty estimation. With such limitations in mind, the aim of this study is to provide more realistic modelling uncertainty quantities to be adopted in seismic assessment of existing infilled RC frames, including, in a thorough manner, the impact of the variability of the masonry infill typologies and the occurrence of RC frame shear failure. Both the aleatory and epistemic uncertainties are estimated, in terms of the overall dispersion on specific engineering demand parameters and collapse fragility curves. Finally, the impact of such uncertainties on seismic risk estimates, quantified through expected annual losses, is also thoroughly investigated. The inclusion of additional random variables, not considered so far, in the uncertainty estimation framework, led to importantly higher modelling uncertainty quantities than those currently available from previous studies.

Direct seismic loss estimation of predominantly plan‐symmetrical frame buildings using simplified nonlinear models

AbstractThe estimation of building seismic risk and loss utilising response history analysis is challenging, especially because the final objective is the seismic loss estimation for building stock. In this paper, this challenge is addressed by developing a simplified nonlinear structural model, which is capable of simulating the seismic response of predominantly plan‐symmetrical reinforced concrete frame buildings subjected to ground motions in both horizontal directions. The simplified structural model is plugged into the direct seismic risk and loss estimation methodology. Its capabilities are then demonstrated by estimating the seismic risk and losses for a four‐storey office building and a five‐storey school building. For the analysed buildings, it is shown that the frequency of collapse, the expected annual loss and the frequency of exceedance of a given loss can be simulated with the same level of accuracy as in the case of the conventional structural model, but with greater numerical robustness and computational efficiency. Research is needed to better define the limitations of the introduced simplified model and extend the capabilities of simplified nonlinear models to more complex structural systems of plan‐asymmetrical buildings.

Seismic probabilistic risk estimation of Japanese railway embankments and risk-based design strength of soil and reinforcement

For the rational seismic design of railway embankments considering seismic risk, high-strength geomaterials and reinforcements should be used in areas with high seismic probability, and low-strength geomaterials and reinforcements should be used in areas with low seismic probability. In this study, a seismic probabilistic risk estimation of Japanese railway embankments was conducted using publicly available information on seismic hazards in Japan and previously estimated seismic-fragility curves for Japanese railway embankments. To determine the required average friction angle of backfill soil and average reinforcement tensile strength for satisfying the prescribed allowable seismic risk, a sensitivity analysis of the railway embankment was conducted by changing the average friction angle of the backfill soil and the average reinforcement tensile strength. Using the sensitivity-analysis results, the required average friction angle of the backfill soil and average reinforcement tensile strength of the railway embankment satisfying the prescribed allowable seismic risk considering the occurrence probability of earthquakes were analytically obtained.

Machine learning network suitable for accurate rapid seismic risk estimation of masonry building stocks

Machine learning network suitable for accurate rapid seismic risk estimation of masonry building stocks

Seismic fragility analysis of traditional himis structures in Turkey

It is extremely important to better understand the behavior of existing buildings against earthquakes, to reduce the damage that may occur in these structures in future earthquakes, and to repair and strengthen them when necessary. Studies on the earthquake behavior of traditional Himis structures, which constitute a large part of the historical urban fabric in Turkey, are not quite enough. So, using existing example types, the purpose of this study is to examine, wooden himis frame Turkish structures according to seismic loads. In this study, the earthquake performance of traditional Turkish himis structures under different earthquake accelerations and the behavior of structures in earthquakes were investigated. Himis structures are also evaluated in terms of their studs types, as well as material details. The buildings were modeled based on the finite element model approach by Sap2000 V22 software, their dynamic characteristics were determined and time history analyses were performed to obtain drift ratio. Furthermore, the seismic demand of the Himis structure types was defined and compared. Finally, to assess seismic risk and damage estimation, a probabilistic assessment was carried out and the fragility curves for each building type were derived.

Earthquake hazard and risk analysis for natural and induced seismicity: towards objective assessments in the face of uncertainty

The fundamental objective of earthquake engineering is to protect lives and livelihoods through the reduction of seismic risk. Directly or indirectly, this generally requires quantification of the risk, for which quantification of the seismic hazard is required as a basic input. Over the last several decades, the practice of seismic hazard analysis has evolved enormously, firstly with the introduction of a rational framework for handling the apparent randomness in earthquake processes, which also enabled risk assessments to consider both the severity and likelihood of earthquake effects. The next major evolutionary step was the identification of epistemic uncertainties related to incomplete knowledge, and the formulation of frameworks for both their quantification and their incorporation into hazard assessments. Despite these advances in the practice of seismic hazard analysis, it is not uncommon for the acceptance of seismic hazard estimates to be hindered by invalid comparisons, resistance to new information that challenges prevailing views, and attachment to previous estimates of the hazard. The challenge of achieving impartial acceptance of seismic hazard and risk estimates becomes even more acute in the case of earthquakes attributed to human activities. A more rational evaluation of seismic hazard and risk due to induced earthquakes may be facilitated by adopting, with appropriate adaptations, the advances in risk quantification and risk mitigation developed for natural seismicity. While such practices may provide an impartial starting point for decision making regarding risk mitigation measures, the most promising avenue to achieve broad societal acceptance of the risks associated with induced earthquakes is through effective regulation, which needs to be transparent, independent, and informed by risk considerations based on both sound seismological science and reliable earthquake engineering.