Performance-based seismic vulnerability evaluation of existing buildings in old sectors of Quebec

To perform a seismic vulnerability evaluation for the existing buildings in old sectors of Quebec, two major tools at two different levels are missing: first, in the context of the seismic vulnerability assessment of a group of buildings, an updated rapid visual screening method which complies with the Uniform Hazard Spectra presented in the 2005 version of the National Building Code of Canada (NBCC) does not exist; and second, in the context of loss estimation studies, capacity and fragility curves which are developed based on the specific building typologies present in those sectors are required. In this research work, in the first place, a building classification for the existing buildings in old sectors of Quebec considering the masonry as the main construction material is proposed. Later, an updated rapid visual screening method—in the form of vulnerability indices for different typologies and cities in Quebec—which is adapted to the Uniform Hazard Spectra in NBCC 2005 is proposed. The structural vulnerability indices (SVI) are calculated through the application of the improved nonlinear static analysis procedure in FEMA 440 Improvement of nonlinear static seismic analysis procedures for three levels of seismic hazard. A set of index modifiers are also presented for the building height, irregularities, and the design and construction year. To deal with the second problem, on the other hand, a performance-based seismic vulnerability evaluation method is applied to examine the structural performance of two buildings—a 6-storey industrial masonry building and a 5-storey concrete frame with masonry infill walls, as two of the building classes constructed vastly in old sectors in Quebec—at multiple seismic demand levels. The results of such an assessment are used to develop dynamic capacity and fragility curves for the target buildings. The Applied Element Method is used here as an alternative to FE-based methods to conduct a thorough 4-step performance-based seismic vulnerability evaluation. To this end, the Incremental Dynamic Analyses (IDA) for the buildings are carried out using various sets of synthetic and real ground motions representing three M and R categories. Consequently, the fragility curves are developed for the three structural performance levels—Immediate Occupancy, Life Safety, and Collapse Prevention. Finally, the mean annual frequencies of exceeding those performance levels are calculated by combining the data from the calculated fragility curves and those from the region’s hazard curves. The proposed method is shown to be useful to conduct seismic vulnerability evaluations in regions for which little observed damage data exists

Fragility Analysis of Existing Unreinforced Masonry Buildings through a Numerical-based Methodology

As an approach to the problem of seismic vulnerability evaluation of existing buildings using the predicted vulnerability method, numerical models can be applied to define fragility curves of typical buildings which represent building classes. These curves can be then combined with the seismic hazard to calculate the seismic risk for a building class (or individual buildings). For some buildings types, mainly the unreinforced masonry structures, such fragility analysis is complicated and time consuming if a Finite Element-based method is used. The FEM model has to represent the structural geometry and relationships between different structural elements through element connectivity. Moreover, the FEM can face major challenges to represent large displacements and separations for progressive collapse simulations. Therefore, the Applied Element Method which combines the advantages of FEM with that of the Discrete Element Method in terms of accurately modelling a deformable continuum of discrete materials is used in this paper to perform the fragility analysis for unreinforced masonry buildings. To this end, a series of nonlinear dynamic analyses using the AEM has been per-formed for two unreinforced masonry buildings (a 6-storey stone masonry and a 4-storey brick masonry) using more than 50 ground motion records. Both in-plane and out-of-plane failure have been considered in the damage analysis. The distribution of the structural responses and inter-storey drifts are used to develop spectral-based fragility curves for the five European Macroseismic Scale damage grades

A binary particle swarm optimization algorithm for ship routing and scheduling of liquefied natural gas transportation

With the increasing global demands for energy, fuel supply management is a challenging task of today’s industries in order to decrease the cost of energy and diminish its adverse environmental impacts. To have a more environmentally friendly fuel supply network, Liquefied Natural Gas (LNG) is suggested as one of the best choices for manufacturers. As the consumption rate of LNG is increasing dramatically in the world, many companies try to carry this product all around the world by themselves or outsource it to third-party companies. However, the challenge is that the transportation of LNG requires specific vessels and there are many clauses in related LNG transportation contracts which may reduce the revenue of these companies, it seems essential to find the best option for them. The aim of this paper is to propose a meta-heuristic Binary Particle Swarm Optimization (BPSO) algorithm to come with an optimized solution for ship routing and scheduling of LNG transportation. The application demonstrates what sellers need to do to reduce their costs and increase their profits by considering or removing some obligations

Damage prediction for regular reinforced concrete buildings using the decision tree algorithm

To overcome the problem of outlier data in the regression analysis for numerical-based damage spectra, the C4.5 decision tree learning algorithm is used to predict damage in reinforced concrete buildings in future earthquake scenarios. Reinforced concrete buildings are modelled as single-degree-of-freedom systems and various time-history nonlinear analyses are performed to create a dataset of damage indices. Subsequently, two decision trees are trained using the qualitative interpretations of those indices. The first decision tree determines whether damage occurs in an RC building. Consequently, the second decision tree predicts the severity of damage as repairable, beyond repair, or collapse

An integrated grey-based multi-criteria decision-making approach for supplier evaluation and selection in the oil and gas industry

Purpose The oil and gas industry is a crucial economic sector for both developed and developing economies. Delays in extraction and refining of these resources would adversely affect industrial players, including that of the host countries. Supplier selection is one of the most important decisions taken by managers of this industry that affect their supply chain operations. However, determining suitable suppliers to work with has become a phenomenon faced by these managers and their organizations. Furthermore, identifying relevant, critical and important criteria needed to guide these managers and their organizations for supplier selection decisions has become even more complicated due to various criteria that need to be taken into consideration. With limited works in the current literature of supplier selection in the oil and gas industry having major methodological drawbacks, the purpose of this paper is to develop an integrated approach for supplier selection in the oil and gas industry. Design/methodology/approach To address this problem, this paper proposes a new uncertain decision framework. A grey-Delphi approach is first applied to aid in the evaluation and refinement of these various available criteria to obtain the most important and relevant criteria for the oil and gas industry. The grey systems theoretic concept is adopted to address the subjectivity and uncertainty in human judgments. The grey-Shannon entropy approach is used to determine the criteria weights, and finally, the grey-EDAS (evaluation based on distance from average solution) method is utilized for determining the ranking of the suppliers. Findings To exemplify the applicability and robustness of the proposed approach, this study uses the oil and gas industry of Iran as a case in point. From the literature review, 21 criteria were established and using the grey-Delphi approach, 16 were finally considered. The four top-ranked criteria, using grey-Shannon entropy, include warranty level and experience time, relationship closeness, supplier’s technical level and risks which are considered as the most critical and influential criteria for supplier evaluation in the Iranian oil and gas industry. The ranking of the suppliers is obtained, and the best and worst suppliers are also identified. Sensitivity analysis indicates that the results using the proposed methodology are robust. Research limitations/implications The proposed approach would assist supply chain practicing managers, including purchasing managers, procurement managers and supply chain managers in the oil and gas and other industries, to effectively select suitable suppliers for cooperation. It can also be used for other multi-criteria decision-making (MCDM) applications. Future works on applying other MCDM methods and comparing them with the results of this study can be addressed. Finally, broader and more empirical works are required in the oil and gas industry. Originality/value This study is among the first few studies of supplier selection in the oil and gas industry from an emerging economy perspective and sets the stage for future research. The proposed integrated grey-based MCDM approach provides robust results in supplier evaluation and can be used for future domain applications