scholarly journals Empirical seismic fragility models for Nepalese school buildings

2020 ◽  
Vol 105 (1) ◽  
pp. 339-362 ◽  
Author(s):  
Nicola Giordano ◽  
Flavia De Luca ◽  
Anastasios Sextos ◽  
Fernando Ramirez Cortes ◽  
Carina Fonseca Ferreira ◽  
...  
Keyword(s):  
Structural Integrity ◽  
Structural Characteristics ◽  
Fragility Curves ◽  
School Buildings ◽  
Data Sets ◽  
Loss Assessment ◽  
Building Stock ◽  
Urban Settlements ◽  
Damage Data ◽  
The Impact

AbstractEmpirical vulnerability models are fundamental tools to assess the impact of future earthquakes on urban settlements and communities. Generally, they consist of sets of fragility curves that are derived from georeferenced post-earthquake damage data. Following the 2015 Nepal earthquake sequence, the World Bank, through the Global Program for Safer Schools, conducted a Structural Integrity and Damage Assessment (SIDA) of about 18,000 school buildings in the earthquake-affected area. In this work, the database is utilized to identify the main structural characteristics of the Nepalese school building stock. For the first time, extended SIDA school damage data is processed to derive fragility curves for the main structural typologies. Data sets for each structural typology are used for a Bayesian updating of existing fragilities to obtain regional models for Nepalese schools. These fragility estimates can be adopted to assess potential seismic losses of the school infrastructure in Nepal. Additionally, they can be used for calibrating loss assessment studies in the wider Himalayan region where the structural typologies are similar.

Empirical Fragility Functions based on Remote Sensing and Field Data after the 12 January 2010 Haiti Earthquake

2013 ◽  
Vol 29 (4) ◽  
pp. 1275-1310 ◽  
Author(s):  
Ufuk Hancilar ◽  
Fabio Taucer ◽  
Christina Corbane
Keyword(s):  
Remote Sensing ◽  
Damage Assessment ◽  
Aerial Images ◽  
Data Sets ◽  
Fragility Functions ◽  
Haiti Earthquake ◽  
Building Stock ◽  
The World Bank ◽  
Damage Grades ◽  
Damage Data

In the immediate aftermath of the Haiti earthquake of 12 January 2010, a joint study for the estimation of damage to the building stock based on aerial images was carried out by UNITAR-UNOSAT, the EC-JRC, and the World Bank/ImageCAT in support of the PDNA. A targeted field campaign was led to the areas affected by the disaster in collaboration with the CNIGS with the purpose of validating the remote sensing based damage assessment. These two methodologies for collecting data resulted in two data sets of the damaged buildings categorized according to the EMS-98 damage grades. In the present study, fragility functions for different urban zones of Haiti, that is, low-, medium-, and high-density built-up and shanty zones, are developed from the remote sensing damage assessment data. Structural fragilities for buildings grouped with respect to material type and number of stories are derived on the basis of field damage data.

Detailed assessment of structural characteristics of Turkish RC building stock for loss assessment models

2008 ◽  
Vol 28 (10-11) ◽  
pp. 914-932 ◽  
Author(s):  
İ. Engin Bal ◽  
Helen Crowley ◽  
Rui Pinho ◽  
F. Gülten Gülay
Keyword(s):  
Structural Characteristics ◽  
Loss Assessment ◽  
Building Stock ◽  
Rc Building ◽  
Detailed Assessment

A Statistical Study on Structural Characteristics of RC Building Stock of Dhaka City for Seismic Loss Assessment Application

2013 ◽  
Vol 330 ◽  
pp. 884-888 ◽  
Author(s):  
Mohammd Shafiqual Alam ◽  
M. Rafi Sajjad ◽  
Zeeshan Yasir ◽  
Fuad M. Moinul Haque
Keyword(s):  
Goodness Of Fit ◽  
Seismic Vulnerability ◽  
Structural Characteristics ◽  
Risk Index ◽  
Dual Frame ◽  
Loss Assessment ◽  
Statistical Parameters ◽  
Building Stock ◽  
Mean Values ◽  
Seismic Loss Assessment

Dhaka is one of the most seismically hazardous cities in the world and several studies indicate Dhaka to have one of the highest values of earthquake disaster risk index (EDRI) mainly due to its inherent vulnerability of building infrastructure, high population density, and poor emergency response and recovery capability. Assessment of the seismic vulnerability of the building stock of Dhaka is of growing importance since such information is needed for reliable estimation of the losses that possible future earthquakes are likely to induce. The principal aim of this paper is to provide statistical information on geometrical, functional and material properties of the Dhaka building stock for use in risk and loss assessment models, and other types of statistic-or probability-based studies. To achieve this goal, the existing reinforced concrete (RC) stock has been classified as dual (frame-wall) or frame structures. In addition to the statistical parameters such as mean values, standard deviations, etc., probability density functions and their goodness-of-fit have also been investigated for all types of parameters. Concrete properties of existing and recently constructed buildings and characteristics of 40 ksi and 60 ksi types of steel commonly used in constructions have been also documented.

Statistical Analysis of Bridge Damage Data from the 1994 Northridge, CA, Earthquake

1999 ◽  
Vol 15 (1) ◽  
pp. 25-54 ◽  
Author(s):  
Nesrin I. Basöz ◽  
Anne S. Kiremidjian ◽  
Stephanie A. King ◽  
Kincho H. Law
Keyword(s):  
Los Angeles ◽  
Ground Motion ◽  
Structural Characteristics ◽  
Fragility Curves ◽  
Cost Ratio ◽  
Repair Cost ◽  
Ground Acceleration ◽  
Damage Data ◽  
Bridge Damage ◽  
Observed Damage

This paper presents the significant findings from a study on damage to bridges during the January 17, 1994 Northridge, CA earthquake. The damage and repair cost data were compiled in a database for bridges in the Greater Los Angeles area. Observed damage data for all bridges were discriminated by structural characteristics. The analyses of data on bridge damage showed that concrete structures designed and built with older design standards were more prone to damage under seismic loading. Repair and/or reconstruction of collapsed structures formed seventy five percent of the total estimated repair cost. Peak ground acceleration values were also estimated at all bridge locations as part of this study. Empirical relationships between ground motion and bridge damage, and repair cost ratio were developed in the form of fragility curves and damage probability matrices, respectively. A comparison of the empirical and available ground motion-damage relationships demonstrated that the relationships that are currently in use do not correlate well to the observed damage.

scholarly journals Seismic Vulnerability Assessment of School Buildings in Seismic Zone 4 of Pakistan

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Muhammad Zain ◽  
Muhammad Usman ◽  
Syed Hassan Farooq ◽  
Tahir Mehmood
Keyword(s):  
Vulnerability Assessment ◽  
Seismic Vulnerability ◽  
Fragility Curves ◽  
Assessment Process ◽  
School Buildings ◽  
Seismic Zone ◽  
Building Stock ◽  
Kashmir Earthquake ◽  
Building Type ◽  
Structural Configurations

Thick population density and its escalation propensity in seismically active regions of Pakistan has raised sincere concerns about the performance of building stock whose suboptimal performance and complete collapses led to a colossal number of casualties during the past earthquakes. The current research is inspired by the Kashmir earthquake of 2005 which consumed more than 80,000 lives, out of which, approximately 19,000 were children due to wide spread collapse of school buildings. A new database for existing reinforced concrete (RC) school buildings in seismic zone 4 of Pakistan has been developed using the surveyed information and presented briefly. The paper presents the statistics of the data collected through field surveys and professional interviews. It was found that the infrastructural authorities in the considered region developed some specific designs for school buildings, with varying architectural and structural configurations, which were eventually replicated throughout the area. In the current study, almost 2500 schools were surveyed for identifying versatile architectural and structural configurations, and subsequently, 19 different types had been identified, which were eventually used as representative stock for the schools in seismic zone 4 of Pakistan, Muzaffarabad district. The results of the study yield the brief of the collected data from the field and a consolidated methodology for establishing the analytical fragility relationships for one of the 19 structural configurations of the school buildings. A sample building from the collected data has been selected by considering the maximum number of students, and afterwards, the vulnerability is assessed by employing incremental dynamic analysis (IDA) which constitutes the presented methodology. Finally, the fragility curves are developed and presented for the said building type. The derived analytical fragility curves for the considered building type indicate its structural vulnerability and as a whole represent its satisfactory behavior. The vulnerability assessment process and the fragility development are described in an easy manner so that the domestic practicing engineers can readily become able to extend the application towards other school buildings in the region. The developed relationships can be employed for rational decision making so that essential disaster preparedness can be carried out by identifying any need for structural strengthening and interventions.

BIM-BASED APPROACH FOR SEISMIC RISK ANALYSIS

2018 ◽  
Vol 5 (2) ◽  
Author(s):  
Valentina Villa ◽  
Marco Domaneschi ◽  
Gian Paolo Cimellaro ◽  
Carlo Caldera
Keyword(s):  
Risk Analysis ◽  
Seismic Risk ◽  
Seismic Analysis ◽  
Structural Characteristics ◽  
National Standard ◽  
School Buildings ◽  
Destructive Testing ◽  
Seismic Risk Analysis ◽  
Building Stock ◽  
Existing Building

The Italian school buildings asset consists of over 40,000 units. The most (more than 60%) were built before the introduction of the national standard on school buildings and constructions in seismic areas. The present research aims to implement a methodology that consists in an informative modelling for seismic risk analysis. The objective of the activity is to provide the policy makers of a useful tool for screening the existing building stock, in order to define the priorities of intervention. The research is divided into several parts. First of all, the most recurrent building technologies have to be defined with respect to the year of construction and the structural characteristics. Furthermore, to assess the seismic risk, the seismic hazard has also to be analyzed. Next, a multiphase process of increasing complexity has to be defined, in which two approaches of seismic analysis are tested. The first one is related to "simple" construction technologies (e.g. frame structures) where information can be collected through visual screening during inspections and through the study of the existing documentation. The second one is a more refined approach that includes non-destructive testing on site and structural analysis. Both procedures lead to the definition of BIM models.

scholarly journals The Structural Characteristics of Collagen in Swim Bladders with 25-Year Sequence Aging: The Impact of Age

2021 ◽  
Vol 11 (10) ◽  
pp. 4578
Author(s):  
Xiaofeng He ◽  
Liling Xie ◽  
Xiaoshan Zhang ◽  
Fan Lin ◽  
Xiaobo Wen ◽  
...  
Keyword(s):  
Triple Helix ◽  
Structural Integrity ◽  
Structural Characteristics ◽  
Fiber Bundles ◽  
Attenuated Total Reflectance ◽  
X Ray Diffraction ◽  
Scanning Calorimetry ◽  
Force Microscopy ◽  
Atomic Force ◽  
The Impact

Aged swim bladders from the yellow drum (Protonibea diacanthus) are considered collagen-based functional food with extremely high market value. The structural integrity of collagen may be crucial for its biological functions. In the current study, swim bladders with 25-year-old sequences were collected and found to be basically composed of collagen. Then, thermogravimetry (TG), differential scanning calorimetry (DSC), X-ray diffraction (XRD), and attenuated total reflectance–Fourier transform infrared spectroscopy (ATR–FTIR) were conducted to evaluate the integrity of the peptide chain and triple helix in the collagen. The structures of microfibers and fiber bundles were revealed with atomic force microscopy (AFM), scanning electrical microscopy (SEM), and optical spectroscopy. The collagens in the aged swim bladders were found to have similar thermal properties to those of fresh ones, but the relative content of the triple helixes was found to be negatively correlated with aging. The secondary structure of the remaining triple helix showed highly retained characteristics as in fresh swim bladders, and the microfibrils also showed a similar D-period to that of the fresh one. However, the fiber bundles displayed more compact and thick characteristics after years of storage. These results indicate that despite 25 years of aging, the collagen in the swim bladders was still partially retained with structures.

scholarly journals Potential and limitations of finite element modelling in assessing structural integrity of coralline algae under future global change

2015 ◽  
Vol 12 (19) ◽  
pp. 5871-5883 ◽  
Author(s):  
L. A. Melbourne ◽  
J. Griffin ◽  
D. N. Schmidt ◽  
E. J. Rayfield
Keyword(s):  
Climate Change ◽  
Finite Element ◽  
Structural Integrity ◽  
Geometric Model ◽  
Algal Growth ◽  
Coralline Algae ◽  
Rocky Shores ◽  
Element Analysis ◽  
Scan Data ◽  
The Impact

Abstract. Coralline algae are important habitat formers found on all rocky shores. While the impact of future ocean acidification on the physiological performance of the species has been well studied, little research has focused on potential changes in structural integrity in response to climate change. A previous study using 2-D Finite Element Analysis (FEA) suggested increased vulnerability to fracture (by wave action or boring) in algae grown under high CO2 conditions. To assess how realistically 2-D simplified models represent structural performance, a series of increasingly biologically accurate 3-D FE models that represent different aspects of coralline algal growth were developed. Simplified geometric 3-D models of the genus Lithothamnion were compared to models created from computed tomography (CT) scan data of the same genus. The biologically accurate model and the simplified geometric model representing individual cells had similar average stresses and stress distributions, emphasising the importance of the cell walls in dissipating the stress throughout the structure. In contrast models without the accurate representation of the cell geometry resulted in larger stress and strain results. Our more complex 3-D model reiterated the potential of climate change to diminish the structural integrity of the organism. This suggests that under future environmental conditions the weakening of the coralline algal skeleton along with increased external pressures (wave and bioerosion) may negatively influence the ability for coralline algae to maintain a habitat able to sustain high levels of biodiversity.

scholarly journals Investigating the impact of pre-processing techniques and pre-trained word embeddings in detecting Arabic health information on social media

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yahya Albalawi ◽  
Jim Buckley ◽  
Nikola S. Nikolov
Keyword(s):  
Social Media ◽  
Deep Learning ◽  
Comprehensive Evaluation ◽  
Classification Problem ◽  
Data Sets ◽  
Word Embeddings ◽  
Data Set ◽  
Lower Accuracy ◽  
Health Related ◽  
The Impact

AbstractThis paper presents a comprehensive evaluation of data pre-processing and word embedding techniques in the context of Arabic document classification in the domain of health-related communication on social media. We evaluate 26 text pre-processings applied to Arabic tweets within the process of training a classifier to identify health-related tweets. For this task we use the (traditional) machine learning classifiers KNN, SVM, Multinomial NB and Logistic Regression. Furthermore, we report experimental results with the deep learning architectures BLSTM and CNN for the same text classification problem. Since word embeddings are more typically used as the input layer in deep networks, in the deep learning experiments we evaluate several state-of-the-art pre-trained word embeddings with the same text pre-processing applied. To achieve these goals, we use two data sets: one for both training and testing, and another for testing the generality of our models only. Our results point to the conclusion that only four out of the 26 pre-processings improve the classification accuracy significantly. For the first data set of Arabic tweets, we found that Mazajak CBOW pre-trained word embeddings as the input to a BLSTM deep network led to the most accurate classifier with F1 score of 89.7%. For the second data set, Mazajak Skip-Gram pre-trained word embeddings as the input to BLSTM led to the most accurate model with F1 score of 75.2% and accuracy of 90.7% compared to F1 score of 90.8% achieved by Mazajak CBOW for the same architecture but with lower accuracy of 70.89%. Our results also show that the performance of the best of the traditional classifier we trained is comparable to the deep learning methods on the first dataset, but significantly worse on the second dataset.

scholarly journals Building stock market resilience through digital transformation: using Google trends to analyze the impact of COVID-19 pandemic

2020 ◽  
Vol 14 (1) ◽  
Author(s):  
Ding Ding ◽  
Chong Guan ◽  
Calvin M. L. Chan ◽  
Wenting Liu
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Digital Transformation ◽  
Google Trends ◽  
Building Stock ◽  
Market Sentiment ◽  
Price Performance ◽  
Novel Coronavirus ◽  
The Impact

Abstract As the 2019 novel coronavirus disease (COVID-19) pandemic rages globally, its impact has been felt in the stock markets around the world. Amidst the gloomy economic outlook, certain sectors seem to have survived better than others. This paper aims to investigate the sectors that have performed better even as market sentiment is affected by the pandemic. The daily closing stock prices of a total usable sample of 1,567 firms from 37 sectors are first analyzed using a combination of hierarchical clustering and shape-based distance (SBD) measures. Market sentiment is modeled from Google Trends on the COVID-19 pandemic. This is then analyzed against the time series of daily closing stock prices using augmented vector autoregression (VAR). The empirical results indicate that market sentiment towards the pandemic has significant effects on the stock prices of the sectors. Particularly, the stock price performance across sectors is differentiated by the level of the digital transformation of sectors, with those that are most digitally transformed, showing resilience towards negative market sentiment on the pandemic. This study contributes to the existing literature by incorporating search trends to analyze market sentiment, and by showing that digital transformation moderated the stock market resilience of firms against concern over the COVID-19 outbreak.

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