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نتیجه جستجو - Construction risk

تعداد مقالات یافته شده: 5
ردیف عنوان نوع
1 Risk assessment of the UPIoT construction in China using combined dynamic weighting method under IFGDM environment
ارزیابی ریسک ساخت و ساز UPIoT در چین با استفاده از روش توزین وزن ترکیبی در محیط IFGDM-2020
Large-scale integration of renewable energy systems poses challenges to the ubiquitous power Internet of things (UPIoT) construction in China. This paper aims to study beyond these challenges from a risk assessment per- spective, using the combined dynamic weighting evidence fusion (CDWEF) method under the intuitionistic fuzzy group decision-making (IFGDM) environment. The UPIoT construction risk is identified and characterized by a 17-indicator system which is scored by intuitionistic fuzzy relations (IFRs) from experts. The IFRs are corrected by the dynamic expert weight determined from both the intuitionistic fuzzy entropy and conflicts among IFRs. The IF-AHP-DEMATEL method is adopted to determine the combined indicator weight for correcting the risk mass functions, which are obtained from the IFRs with the evidence fusion theory. The proposed risk assessment method is validated in a case study, indicating that the UPIoT construction risk in China is high in communication networks and business innovation.
Keywords: The ubiquitous power Internet of things (UPIoT) | intuitionistic fuzzy group decision-making | combined dynamic weighting | intuitionistic fuzzy AHP-DEMATEL | risk assessment
مقاله انگلیسی
2 Risk assessment and management via multi-source information fusion for undersea tunnel construction
ارزیابی و مدیریت ریسک از طریق تلفیق اطلاعات چند منبع برای ساخت تونل زیر زمینی -2020
The construction of undersea tunnels is an extremely risky endeavor that is vulnerable to water seepage and gushing due to the high water pressure, complex geological conditions, and pore water trapped in unstable rocks. This risk can lead to the collapse of tunnels under construction and disastrous consequences of fatalities and injuries as well as project delays and financial losses. The current risk management practices for tunnel construction projects in China are static and rely on the subjective judgement of experts and practitioners and do not incorporate real-time monitoring data during the construction process at this time. This paper presents a new method and system to assess and manage the risks during the construction process by coupling the risk management system and the quality management system and integrating jobsite monitoring data, design data, and environmental data. In this new method and system, the risk factors are categorized into (hu)man, material, machine, method, and environment, or 4M1E, and are quantitatively measured. The Dempster-Shaffer (D-S) theory was adopted in this method to both fuse the 4M1E data and to compute the aggregate risk index. This new method and system was tested during the Xiamen Metro Line No. 3 project when a shield machine cutter accident occurred. The results show that, before the accident, the individual risk measures in all five dimensions (4M1E) and the aggregate risk index were extremely high, which clearly illustrated the feasibility and capability of the newly developed method and system.
Keywords: Undersea tunnel construction | Multi-source information fusion | Construction risk | D-S evidence theory | Fuzzy matter element
مقاله انگلیسی
3 Predicting seismic-based risk of lost circulation using machine learning
پیش بینی خطر مبتنی بر لرزه نگاری از دست رفته گردش خون با استفاده از یادگیری ماشین-2019
Lost circulation during well drilling and completion wastes productive time, and even kills the well in severe cases. Timely identifying lost circulation events and taking countermeasures has been the focus of related study. However, a real prediction of lost circulation risk before drilling would be an active response to the challenge. In this paper, a technical solution is proposed to evaluate geological lost-circulation risk in the field using 3D seismic data attributes and machine learning technique. First, four seismic attributes (variance, attenuation, sweetness, RMS amplitude) that are the most correlated with lost circulation incidents are recommended. Then a prediction model is built by conducting supervised learning that involves a majority voting algorithm. The performance of the model is illustrated by six unseen drilled wells and shows the ability and potential to forecast lost circulation probability both along well trajectory and in the region far away from the drilled wells. The prediction resolution in the lateral and vertical direction is about 25m and 6m (2 ms), respectively, which are distinct advantages over the traditional description of geological structures using seismic data. It shows that the lost circulation risk can be hardly recognized by interpreting one specific seismic attribute, which is a common practice. Finally, the challenges in predicting lost circulation risk using seismic data are summarized. Overall, the study suggests that machine learning would be a practical solution to predict various construction risks that are related to seismic-based geological issues. Knowing in advance the risks, people could avoid or at least minimize the losses by optimizing well deployment in the field and taking preventive measures.
Keywords: Machine learning | Lost circulation | Seismic attribute | Mud loss | Seismic interpretation
مقاله انگلیسی
4 Towards integrating construction risk management and stakeholder management: A systematic literature review and future research agendas
به سوی یکپارچه سازی مدیریت خطر در ساخت و مدیریت ذی نفع: یک مرور سیستماتیک روی منابع و حوزه های تحقیقاتی آتی-2018
We propose that integrated management of construction risk and stakeholder is feasible and can promote the effectiveness of both risk management (RM) and stakeholder management (SM). A systematic literature review is conducted on the current construction literature involving both RM and SM, through which we identify four linkage modes between risk and stakeholder management. We further suggest future directions that enable integrating risk and stakeholder management to benefit the management process and/or management outcome of RM and SM. These linkages and directions shed light on enhancing the effectiveness of RM and SM through new ways of thinking about, analyzing, and then managing risks and stakeholders in a holistic and integrated way, but not the traditional endeavor in individual areas. Integrating risk and stakeholder management is challenging, but can be a novel way for improving project performance for which this research conceptually justifies its feasibility and benefits, which merits further study.
keywords: Integrated management |Risk management |Stakeholder management |Construction project |Literature review
مقاله انگلیسی
5 Improving the risk quantification under behavioural tendencies: A tale of construction projects
بهبود کمّی سازی خطر تحت گرایشات رفتاری: یک حکایتی از پرژوه های ساخت-2018
Complex construction projects are risky owing to several features and factors. Their management involves risk assessment which is subjected to various behavioural tendencies and the existing body of knowledge lacks appropriate methods to quantify these effects. The prevalent standard model of Expected Utility Theory does not differentiate between threat and opportunity, resulting into an identical estimation for both facets of risk. This limitation was addressed by Prospect Theory which better captures risk preferences. However, construction industry still relies upon conventional methods of risk assessment. The current study introduces a weighting function to better quantify the cognitive errors in construction risk assessment by adjusting the over- and under-estimation. In doing so, detailed scenario-based, semi-structured interviews are conducted engaging senior professionals. It is found that, typically, opportunities are underestimated by 7.5% and threats are overestimated by 8%. Integrating these findings into risk response strategies results into a realistic and effective resource allocation.
keywords: Risk assessment |Risk quantification |Construction projects |Risk behaviour |Cognitive bias
مقاله انگلیسی
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