Risk Assessment Methodology for a Deep Foundation Pit Construction Project in Shanghai, China

Zhou, Hongping; Zhang, Hui

doi:10.1061/(asce)co.1943-7862.0000391

Cited by 50 publications

(30 citation statements)

References 13 publications

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“…As such, most construction safety technology risks can be identified and evaluated at the construction scheme stage. Safety risk evaluation systems of deep foundation construction schemes are therefore decided on the basis of construction schemes before construction starts to allow for a detailed evaluation of safety management issues that can arise during subsequent construction, optimize the allocation of related resources, and improve safety management quality and efficiency (Zhou & Zhang, 2011).…”

Section: Introductionmentioning

confidence: 99%

“…Sun et al (2008) used the Delphi method to identify the safety risks in the construction of Olympic venues and established an AHP model to complete the risk evaluation. Zhou and Zhang (2011) improved a Bayesian network using a fault tree method and established an engineering technology risk deep foundation evaluation model with a fuzzy comprehensive method for evaluating multiple risks. Gao et al (2013) used a fuzzy comprehensive evaluation method to conduct safety risk evaluations of construction worker behavior, from which a preliminary construction safety management system study was conducted.…”

Section: Introductionmentioning

confidence: 99%

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Safety Risk Evaluations of Deep Foundation Construction Schemes Based on Imbalanced Data Sets

Gong

Guo

Huang

et al. 2020

Journal of Civil Engineering and Management

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Safety risk evaluations of deep foundation construction schemes are important to ensure safety. However, the amount of knowledge on these evaluations is large, and the historical data of deep foundation engineering is imbalanced. Some adverse factors influence the quality and efficiency of evaluations using traditional manual evaluation tools. Machine learning guarantees the quality of imbalanced data classifications. In this study, three strategies are proposed to improve the classification accuracy of imbalanced data sets. First, data set information redundancy is reduced using a binary particle swarm optimization algorithm. Then, a classification algorithm is modified using an Adaboost-enhanced support vector machine classifier. Finally, a new classification evaluation standard, namely, the area under the ROC curve, is adopted to ensure the classifier to be impartial to the minority. A transverse comparison experiment using multiple classification algorithms shows that the proposed integrated classification algorithm can overcome difficulties associated with correctly classifying minority samples in imbalanced data sets. The algorithm can also improve construction safety management evaluations, relieve the pressure from the lack of experienced experts accompanying rapid infrastructure construction, and facilitate knowledge reuse in the field of architecture, engineering, and construction.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Safety Risk Evaluations of Deep Foundation Construction Schemes Based on Imbalanced Data Sets

Gong

Guo

Huang

et al. 2020

Journal of Civil Engineering and Management

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“…For example, the 2004's sudden collapse of Singapore's deep braced excavation of Mass Rapid Transit Circle Line project adjacent to Nicoll Highway was reported to result in a disaster in four fatalities, costing approximately $6.7 billion [26]. The Chinese Hangzhou Metro Line 1 project collapse in 2008 was found to take 17 lives and other four missing, with more than ¥50 million loss [27]. Such catastrophic collapses affect the performance of the surrounding infrastructures; similar to the toppling of the 13-floor building in Minhang District of Shanghai, China causing huge social effects [28].…”

Section: Introductionmentioning

confidence: 99%

Deep Foundation Pit Excavations Adjacent to Disconnected Piled Rafts: A Review on Risk Control Practice

Uge¹,

Guo²

2020

OJCE

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Foundation pit excavation engineering is an old subject full of decision making. Yet, it still deserves further research due to the associated high failure cost and the complexity of the geological conditions and/or the surrounding existing infrastructure around it. This article overviews the risk control practice of foundation pit excavation projects in close proximity to existing disconnected piled raft. More focus is given to geotechnical aspects. The review begins with achievements to ensure excavation performance requirements, and follows to discuss the complex soil structure interaction involved among the fundamental components: the retaining wall, mat, piles, cushion, and the soil. After bringing consensus points to practicing engineers and decision makers, it then suggests possible future research directions.

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“…The past decades have witnessed rapid growth in the number and scale of deep foundation pit projects in subway constructions around the world. Once a foundation pit accident (e.g., collapse of retaining structures) occurs, the consequence is often catastrophic, with ripple effects to the safety of adjacent buildings and underground pipelines [1][2][3][4]. In order to prevent such accidents, an important goal in the design and construction of foundation pits is to control the deformation of the soil and the retaining structures.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Deformation Reliability of Retaining Structures in Deep Excavations Considering Measurement Error

Wang

et al. 2019

Applied Sciences

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The deflections of retaining structures during deep excavation should be controlled below a predefined threshold in an attempt to mitigate the deformation-posed damage to the surrounding buildings and infrastructure facilities. In this paper, a new approach is presented to conducting deformation reliability assessments of retaining structures. The method is based on an extension of the classical first-passage reliability problem and is applied on the spatial scale of the retaining structures. With the proposed method, the in situ monitoring data and the associated measurement error can be easily incorporated, which accordingly improves the assessment accuracy. Moreover, the proposed method has a closed-form solution, which is beneficial for the computation efficiency and its practical application. The method was applied to assess the retaining structure reliability in a foundation excavation of a subway station in Fuzhou, China. The accuracy of the analytical results was verified through a comparison with those of Monte Carlo simulation. It was shown that the proposed method can represent well, the deformation-based safety level of retaining structures.

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Risk Assessment Methodology for a Deep Foundation Pit Construction Project in Shanghai, China

Cited by 50 publications

References 13 publications

Safety Risk Evaluations of Deep Foundation Construction Schemes Based on Imbalanced Data Sets

Safety Risk Evaluations of Deep Foundation Construction Schemes Based on Imbalanced Data Sets

Deep Foundation Pit Excavations Adjacent to Disconnected Piled Rafts: A Review on Risk Control Practice

Data-Driven Deformation Reliability of Retaining Structures in Deep Excavations Considering Measurement Error

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