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مقاله انگلیسی رایگان در مورد بازسازی زیرساخت بحرانی: تخمین ریسک بر اساس منطق فازی – الزویر ۲۰۱۷

 

مشخصات مقاله
انتشار مقاله سال ۲۰۱۷
تعداد صفحات مقاله انگلیسی ۱۹ صفحه
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منتشر شده در نشریه الزویر
نوع مقاله ISI
عنوان انگلیسی مقاله Critical Infrastructure Renewal: A Framework for Fuzzy Logic Based Risk Assessment and Microscopic Traffic Simulation Modelling
ترجمه عنوان مقاله بازسازی زیرساخت بحرانی: تخمین ریسک بر اساس منطق فازی و مدل سازی ترافیک
فرمت مقاله انگلیسی  PDF
رشته های مرتبط مهندسی عمران
گرایش های مرتبط برنامه ریزی حمل و نقل، راه و ترابری، سازه
مجله کنفرانس جهانی تحقیقات حمل و نقل – World Conference on Transport Research
دانشگاه Civil and Resource Engineering – Dalhousie University – Canada
کلمات کلیدی دوباره پوشیدن، منطق فازی، احتمال تاخیر، شبیه سازی میکرو، اثرات ترافیکی
کد محصول E5846
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بخشی از متن مقاله:
۱٫ Introduction

Risk is inherent in large construction projects and refers to the potential complications in achieving the project goals. Risk has greatly plagued the construction industries which necessitates the risk assessment for the large scale construction projects. Especially, risk assessment is critical for new construction or renewal of ‘Critical Infrastructure (CI)’, such as bridges as they are the vital links for a transport network. Gradually increasing complexity in road construction and constant exposure to environmental conditions increase the vulnerability of large Critical Infrastructure construction projects to the unexpected hazardous events. Literature offers a plenty of evidence of the schedule slippage and thereby failures to attain the objectives of construction projects. Many factors such as weather, labor skill, and incidents are liable for construction delays and cost overruns of the projects (Baldwin et al., 1984; Ayyub and Halder, 1984; Smith and Hancher, 1989). Among many, the most weather- susceptible road construction activities might include earthwork, road paving, and structural work, including bridge re-decking and activities involving the use of heavy crane machinery (Apipattanavis et al., 2010). These risk factors and events have made the road construction delay a likely circumstance, often having significant impacts on project duration and traffic flows on surrounding road network. Although the delay of road construction projects cannot be avoided, the associated impacts on road network can be assessed and mitigated prior to commencing construction. Recently, Halifax Harbour Bridge (HHB) Commission has begun a re-decking project known as the “Big Lift” (۲۰۱۵-۲۰۱۷) in order to replace the suspended spans of the Macdonald Bridge, a 1.3 km long Critical Infrastructure (CI) in Halifax, Canada. After the Lions’ Gate Bridge re-decking in Vancouver (2000-2001), this is the second time in history a suspension bridge is being replaced while maintaining traffic during day-time. The project will last for almost 18 months. The associated risk and potential impacts could be significant as up to 48,000 vehicles, 700 cyclists, and 750 pedestrians cross the bridge every day, yet the consequences of disruption to the Macdonald Bridge have never been studied (Quigley, 2015). Therefore, this paper presents a fuzzy logic approach to estimate the construction-related bridge opening delay, and develops a micro simulation model to assess the traffic impacts due to unexpected bridge opening delay during the “Big Lift” project. The re-decking has been started in October, 2015. Construction commences from 7:00 pm, with the bridge becoming operational again at 5:30 am the following morning. The main objectives of this study is (i) to develop a framework to estimate the construction related bridge opening delay in the morning, and (ii) to assess the traffic impacts due to bridge opening delay utilizing a micro simulation model. The delay risk analysis feeds the simulation process with the delay information required to test the possible case scenarios in AM peak period. The scenarios include (i) Base case scenario (no delayed opening) (ii) 1 hour delay (iii) 2 hour delay, and (iv) 3 hour delay in bridge opening to traffic in the morning. The impacts are evaluated based on specific Measures of Effectiveness (MOEs) such as average queue length, average travel time, average delay, average speed, and traffic flow indicators.

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