Development of An Exposure Model for Bridge Structures in Northern Algeria

2018 ◽  
Author(s):  
Andrés Abarca ◽  
Ricardo Monteiro
Keyword(s):  
Risk Assessment ◽  
Large Scale ◽  
Risk Mitigation ◽  
Regional Scale ◽  
Mitigation Measures ◽  
Exposure Model ◽  
Building Stock ◽  
Earthquake Scenarios ◽  
Northern Algeria ◽  
Bridge Structures

In recent years, the use of large scale seismic risk assessment has become increasingly popular to evaluate the fragility of a specific region to an earthquake event, through the convolution of hazard, exposure and vulnerability. These studies tend to focus on the building stock of the region and sometimes neglect the evaluation of the infrastructure, which has great importance when determining the ability of a social group to attend to a disaster and to eventually resume normal activities. This study, developed within the scope of the EU-funded project ITERATE (Improved Tools for Disaster Risk Mitigation in Algeria), focuses on the proposal of an exposure model for bridge structures in Northern Algeria. The proposed model was developed using existing national data surveys, as well as satellite information and field observations. As a result, the location and detailed characterization of a significant share of the Algeria roadway bridge inventory was developed, as well as the definition of a taxonomy that is able to classify the most common structural systems used in Algerian bridge construction. The outcome of this study serves as input to estimate the fragility of the bridge infrastructure inventory and, furthermore, to the overall risk assessment of the Northern Algerian region. Such fragility model will, in turn, enable the evaluation of earthquake scenarios at a regional scale and provide valuable information to decision makers for the implementation of risk mitigation measures.

Credit Risk Management of Commercial Banks in Nepal

2019 ◽  
Vol 4 (1) ◽  
pp. 27-37
Author(s):  
Shreya Pradhan ◽  
Ajay K. Shah
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Credit Risk ◽  
Commercial Banks ◽  
Management Practices ◽  
Risk Mitigation ◽  
Mitigation Measures ◽  
Credit Risk Management ◽  
Loan Repayment ◽  
Credit Risk Assessment

The study is primarily focused on credit risk assessment practices in commercial banks on the basis of their internal efficiency, assessment of assets and borrower. The model of the study is based on the analysis of relationship between credit risk management practices, credit risk mitigation measures and obstacles and loan repayment. Based on a descriptive research approach the study has used survey-based primary data and performed a correlation analysis on them. It discovered that credit risk management practices and credit risk mitigation measures have a positive relationship with loan repayment, while obstacles faced by borrowers have no significant relationship with loan repayment. The study findings can provide good insights to commercial bank managers in analysing their model of credit risk management system, policies and practices, and in establishing a profitable and sustainable model for credit risk assessment, by setting a risk tolerance level and managing credit risks vis-a-vis the prevailing market competition.

Modeling the Residential Building Inventory in South America for Seismic Risk Assessment

2017 ◽  
Vol 33 (1) ◽  
pp. 299-322 ◽  
Author(s):  
Catalina Yepes-Estrada ◽  
Vitor Silva ◽  
Jairo Valcárcel ◽  
Ana Beatriz Acevedo ◽  
Nicola Tarque ◽  
...  
Keyword(s):  
Risk Assessment ◽  
South America ◽  
Structural Characteristics ◽  
Construction Materials ◽  
Residential Building ◽  
Exposure Model ◽  
Earthquake Risk ◽  
Building Stock ◽  
Building Inventory ◽  
Andean Countries

This study presents an open and transparent exposure model for the residential building stock in South America. This model captures the geographical distribution, structural characteristics (including information about construction materials, lateral load resisting system, range of number of stories), average built-up area, replacement cost, expected number of occupants, and number of dwellings and buildings. The methodology utilized to develop this model was based on national population and housing statistics and expert judgment from dozens of local researchers and practitioners. This model has been developed as part of the South America Risk Assessment (SARA) project led by the Global Earthquake Model (GEM), and it can be used to perform earthquake risk analyses. It is available at different geographical scales for seven Andean countries: Argentina, Bolivia, Chile, Colombia, Ecuador, Peru, and Venezuela (DOI: 10.13117/GEM. DATASET.EXP.ANDEAN-v1.0).

Arc flash: a risk assessment and mitigation strategy

2011 ◽  
Vol 51 (2) ◽  
pp. 737
Author(s):  
Danny Norton ◽  
Dale Wright
Keyword(s):  
Risk Assessment ◽  
Oil And Gas ◽  
Capital Expenditure ◽  
Risk Mitigation ◽  
Cumulative Effect ◽  
Mitigation Strategy ◽  
Assessment Process ◽  
Mitigation Measures ◽  
Safe Work ◽  
Arc Flash

Oil and gas facility managers are well aware that attention to detail saves lives and supports business continuity and reputation. Those tasked with stewardship of electrical assets will be aware of the need to protect their employees from the hazard of electrical arc flash and that it should be at the forefront of safety thinking. Complacency and lack of duty of care with this real and possibly un-quantified hazard can lead to fatalities. The primary solution to arc flash consequences in older installations has been the implementation of safe work procedures and personal protective equipment. While still valid, these solutions are the least effective options in the hierarchy of controls. SKM have developed a practical risk mitigation strategy that considers the hazards of prospective arc flash energy together with the cumulative effect of switchboard age, design, capability and condition. The strategy also considers the range of potential mitigation controls available through the mechanism of substitution and engineering design that focuses on reducing: The likelihood of an arc flash incident occurring; The likelihood of personnel exposure; and, The energy released should an incident occur. A structured arc flash risk assessment process can provide the asset owner the opportunity to rank individual switchboards for likelihood, consequence and risk, and thus provide direction for engineered remediation and capital expenditure. SKM proposes the way in which arc flash risk can be assessed, how appropriate layered mitigation measures might be selected, and how an asset owner may approach the issue of arc flash hazard mitigation to economically and reliably protect its employees.

scholarly journals EXPLUME v1.0: a model for personal exposure to ambient O<sub>3</sub> and PM<sub>2.5</sub>

2020 ◽  
Vol 13 (3) ◽  
pp. 1075-1094 ◽  
Author(s):  
Myrto Valari ◽  
Konstandinos Markakis ◽  
Emilie Powaga ◽  
Bernard Collignan ◽  
Olivier Perrussel
Keyword(s):  
Regional Scale ◽  
Personal Exposure ◽  
Exposure Model ◽  
Population Exposure ◽  
Population Mobility ◽  
Building Stock ◽  
Annual Average ◽  
Time Activity ◽  
Road Tunnels ◽  
Pm2.5 Exposure

Abstract. This paper presents the first version of the regional-scale personal exposure model EXPLUME (EXposure to atmospheric PolLUtion ModEling). The model uses simulated gridded data of outdoor O3 and PM2.5 concentrations and several population and building-related datasets to simulate (1) space–time activity event sequences, (2) the infiltration of atmospheric contaminants indoors, and (3) daily aggregated personal exposure. The model is applied over the greater Paris region at 2 km×2 km resolution for the entire year of 2017. Annual averaged population exposure is discussed. We show that population mobility within the region, disregarding pollutant concentrations indoors, has only a small effect on average daily exposure. By contrast, considering the infiltration of PM2.5 in buildings decreases annual average exposure by 11 % (population average). Moreover, accounting for PM2.5 exposure during transportation (in vehicle, while waiting on subway platforms, and while crossing on-road tunnels) increases average population exposure by 5 %. We show that the spatial distribution of PM2.5 and O3 exposure is similar to the concentration maps over the region, but the exposure scale is very different when accounting for indoor exposure. We model large intra-population variability in PM2.5 exposure as a function of the transportation mode, especially for the upper percentiles of the distribution. Overall, 20 % of the population using bicycles or motorcycles is exposed to annual average PM2.5 concentrations above the EU target value (25 µg m−3), compared to 0 % for people travelling by car. Finally, we develop a 2050 horizon projection of the building stock to study how changes in the buildings' characteristics to comply with the thermal regulations will affect personal exposure. We show that exposure to ozone will decrease by as much as 14 % as a result of this projection, whereas there is no significant impact on exposure to PM2.5.

scholarly journals A Behavioral Probabilistic Risk Assessment Framework for Managing Autonomous Underwater Vehicle Deployments

2012 ◽  
Vol 29 (11) ◽  
pp. 1689-1703 ◽  
Author(s):  
Mario Brito ◽  
Gwyn Griffiths ◽  
James Ferguson ◽  
David Hopkin ◽  
Richard Mills ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Autonomous Underwater Vehicle ◽  
Risk Mitigation ◽  
Operational Risk ◽  
Maximum Error ◽  
Underwater Vehicle ◽  
Behavioral Approach ◽  
Mitigation Measures ◽  
The Arctic ◽  
Deep Diving

Abstract The deployment of a deep-diving long-range autonomous underwater vehicle (AUV) is a complex operation that requires the use of a risk-informed decision-making process. Operational risk assessment is heavily dependent on expert subjective judgment. Expert judgments can be elicited either mathematically or behaviorally. During mathematical elicitation experts are kept separate and provide their assessment individually. These are then mathematically combined to create a judgment that represents the group view. The limitation with this approach is that experts do not have the opportunity to discuss different views and thus remove bias from their assessment. In this paper, a Bayesian behavioral approach to estimate and manage AUV operational risk is proposed. At an initial workshop, behavioral aggregation, that is, reaching agreement on the distributions of risks for faults or incidents, is followed by an agreed upon initial estimate of the likelihood of success of the proposed risk mitigation methods. Postexpedition, a second workshop assesses the new data and compares observed to predicted risk, thus updating the prior estimate using Bayes’ rule. This feedback further educates the experts and assesses the actual effectiveness of the mitigation measures. Applying this approach to an AUV campaign in ice-covered waters in the Arctic showed that the maximum error between the predicted and the actual risk was 9% and that the experts’ assessments of the effectiveness of risk mitigation led to a maximum of 24% in risk reduction.

scholarly journals Regional based exposure models to account for local building typologies

2021 ◽  
Author(s):  
G. Tocchi ◽  
M. Polese ◽  
M. Di Ludovico ◽  
A. Prota
Keyword(s):  
Seismic Risk ◽  
Large Scale ◽  
Census Data ◽  
Construction Material ◽  
Regional Scale ◽  
Exposure Model ◽  
Masonry Building ◽  
Building Inventory ◽  
Exposure Models ◽  
Regional Vulnerability

AbstractThe development of building inventory is a fundamental step for the evaluation of the seismic risk at territorial scale. Census data are usually employed for building inventory in large scale application and their use requires suitable rules to assign buildings typologies to vulnerability classes, that is an exposure model specific for the considered vulnerability model. Several exposure models are developed proposing class assignment rules that are calibrated on building typological data available from post-earthquake survey data. However, this approach has the drawback of being based on data from specific geographic areas that have been hit by damaging earthquakes. Indeed, the distribution of building typologies can vary greatly for different areas of a country and the diffusion of one building’s typology rather than another one may depend on the availability of construction material in the area, the evolution of construction techniques and the codes in force at the time of construction. This paper aims to improve the exposure modelling at regional scale, investigating the variability of masonry building typologies distribution. It proposes a methodology to recalibrate the exposure models at regional scale and evaluates the influence of the improved characterization of regional vulnerability on damage and risk assessment. The study shows that the analysis of local building typologies may strongly impact on the evaluation of the seismic risk at territorial scale.

PREDICTORS AND THEIR DOMAIN FOR STATISTICAL DOWNSCALING OF CLIMATE IN BANGLADESH

2016 ◽  
Vol 78 (6-12) ◽  
Author(s):  
Mahiuddin Alamgir ◽  
Sahar Hadi Pour ◽  
Morteza Mohsenipour ◽  
M. Mehedi Hasan ◽  
Tarmizi Ismail
Keyword(s):  
Statistical Downscaling ◽  
General Circulation ◽  
Large Scale ◽  
Regional Scale ◽  
Circulation Model ◽  
Local Scale ◽  
Mitigation Measures ◽  
Grid Points ◽  
Hydrological Services ◽  
Atmospheric Variables

Reliable projection of future rainfall in Bangladesh is very important for the assessment of possible impacts of climate change and implementation of necessary adaptation and mitigation measures. Statistical downscaling methods are widely used for downscaling coarse resolution general circulation model (GCM) output at local scale. Selection of predictors and their spatial domain is very important to facilitate downscaling future climate projected by GCMs. The present paper reports the finding of the study conducted to identify the GCM predictors and demarcate their climatic domain for statistical downscaling in Bangladesh at local or regional scale. Twenty-six large scale atmospheric variables which are widely simulated GCM predictors from 45 grid points around the country were analysed using various statistical methods for this purpose. The study reveals that large-scale atmospheric variables at the grid points located in the central-west part of Bangladesh have the highest influence on rainfall.  It is expected that the finding of the study will help different meteorological and agricultural organizations of Bangladesh to project rainfall and temperature at local scale in order to provide various agricultural or hydrological services.

Challenges With Oil Spill Risk Assessment in Arctic Regions: Shipping Along the Northern Sea Route

2014 ◽  
Author(s):  
Alexei Bambulyak ◽  
Rudiger U. Franz von Bock und Polach ◽  
Sören Ehlers ◽  
Are Sydnes
Keyword(s):  
Risk Assessment ◽  
Oil Spill ◽  
Industrial Development ◽  
Oil Spills ◽  
Risk Mitigation ◽  
Geographic Area ◽  
Mitigation Measures ◽  
Political Agenda ◽  
Arctic Regions ◽  
Northern Sea Route

Arctic regions, and thus ice-covered waters, are continuously getting higher in the national and international political agenda. The world demand in energy resources and the need in development of new transportation routes are pushing industrial activities up North where we see prospects and expectations on one side, and gaps and challenges on the other. Industrial development of the new geographic area is complex, and the priority in transportation is given to marine shipping. For the recent years, transit cargo shipping through the North Eastern Passage or the Northern Sea Route (NSR) increased more than 10 times from 0.11 million tons (4 passages) in 2010 to 1.36 million tons (71 passages) in 2013. Although, the numbers are small compared to global cargo shipping, the sensitive Arctic environment requires the establishment of a oil spill recovery system as well as risk mitigation measures. This, in turn, requires the preceding development of a risk assessment methodology for oil spills in ice-covered waters. Therefore, this paper presents the challenges involved in Arctic shipping along the NSR and identifies the knowledge gaps with respect to environmental risk assessment of accidental oil spill.

scholarly journals NODE: a large‐scale seismic risk prioritization tool for Italy based on nominal structural performance

2021 ◽  
Author(s):  
Fabio Petruzzelli ◽  
Iunio Iervolino
Keyword(s):  
Seismic Risk ◽  
Large Scale ◽  
Seismic Vulnerability ◽  
Risk Mitigation ◽  
Risk Measure ◽  
Computational Effort ◽  
Specific Reference ◽  
Stock Management ◽  
Building Stock ◽  
Italian Case

AbstractPrioritization of seismic risk mitigation at a large scale requires rough-input methodologies able to provide an expedited, yet conventional, assessment of the seismic risk corresponding to the portfolio of interest. In fact, an evaluation of seismic vulnerability at regional level by means of mechanics-based methods is generally only feasible for a fraction of the portfolio, selected according to prioritization criteria, due to the sheer volume of information and computational effort required. Therefore, conventional assessment of seismic risk via simple indices has been proposed in literature and in some guidelines, mainly based on the comparison of code requirements at the time of design and current seismic demand. These indices represent an attempt to define a relative seismic risk measure for a rapid ranking to identify the part of the portfolio that deserves further investigation. Although these risk metrics are based on strong assumptions, they have the advantage of only requiring easy-to-retrieve data, such as design year and location as the bare minimum, making them suitable for applications within the risk analysis industry. Moreover, they can take both hazard and vulnerability into account, albeit conventionally, and can be manipulated in order to account for exposure in terms of individual or societal risks. In the present study, the main assumptions, limitations, and possible evolutions of existing prioritization approaches to nominal risk are reviewed, with specific reference to the Italian case. Furthermore, this article presents the software NODE (available to interested readers), which enables the computation of location-specific code-based seismic performance demands, according to the Italian code and the evolution of seismic classification since 1909. Finally, this study intends to contribute to the ongoing debate on strategies for large-scale seismic assessment for building stock management purposes.

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