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In order to study the failure mechanism and movement characteristics of overburden induced by coal pillar instability, the first continuously-extraction area of No. 15 coal seam in Zhaowu Mine was taken as a geological model, and theoretical analysis, similar simulation, site measurement and formula calculation were combined to build a systematic model in strip Wongawilli mining, and the coal pillar instability and its effect on overburden failure were analyzed. The results show that in the pillar system of strip Wongawilli mining, some damaged or irregular pillars would become instable under the coupling effect of mining pressure, ground water immersion and other unfavorable factors, correspondingly, relevant pillars would be affected and become instable. Therefore, “Domino effect” occurred and the whole pillar system invalidated. Overburden failure was aggravated by pillars instability, the mining condition transformed insufficient mining stage to sufficient mining stage, which resulted in surface subsidence. [ABSTRACT FROM AUTHOR]

• The statistical analysis of a large number of accidents occurred in tank farm was performed. • The causes of the primary events and the secondary events for domino accidents were separately analyzed. • The C5.0 decision tree algorithm was employed to extract rules that show the possible combinations of causal factors for domino accidents. • The most important factors for the prediction of domino risks were identified. • The patterns of domino effect were identified based on the association rule mining. In recent decades, scarce work was done on risk management of the domino effect by establishing the relationship models between influencing factors and consequences of accidents. In this study, the statistical analysis of the 1144 accidents of tank farms including 100 domino accidents and 1044 non-domino accidents occurred in China from 1960 to 2018 was performed. Unlike the existing statistical analysis literature, the causes of the primary events and the secondary events were separately analyzed to determine the common causes of accident escalation. The C5.0 decision tree algorithm was adopted to extract rules that show the most likely sequences of causal factors for triggering domino accidents. Association rule mining was performed on season factors, units of accidents, operation status and causal factors to predict the causal factors under different process conditions and scenarios. The results showed that inadequate training, inadequate procedure and design deficiency were the most important factors in the C5.0 models on the prediction of domino risks. Six decision rules were learned by C5.0 algorithm and twenty effective rules were learned by the association rule mining, which can jointly provide accurate and reliable prevention strategies and decision support for the risk management of domino accidents. [ABSTRACT FROM AUTHOR]

As China continues to urbanise and both intra- and inter-regional migrants move out from their home villages, local economies adapt and form new ecosystems with linked migrants. As a result, local policies targeting one group of migrants may unintentionally affect the other. To reveal it, this paper explores how households' housing choices shaped by local policies have linked upstream and downstream migrants together and how the policy targeting one group of migrants may disadvantage the other. Using a household survey and in-depth interviews in 108 natural villages in peri-urban Shanghai, the research findings reveal that the local government's earlier efforts to 'urbanise' local farmers attracted these farmers to resettle in nearby urban areas and lease their rural dwellings to interregional migrants attracted by manufacturing development. The landlords use the rentals to finance their new urban dwellings. Thus, the two groups of migrant families are tied together by the housing market. These linkages mean that new policies trying to dislocate migrants in peri-urban Shanghai are likely to affect migrants upstream and downstream. Interregional migrants might find similar informal accommodation elsewhere or return to their home villages, but 'urbanised' farmer families can be trapped and even de-urbanise as a result of their rapidly declining income. This research contributes to the growing international literature on the interdependency of migration and stresses the need for policymakers to consider the externalities of local exclusionary migration policies. [ABSTRACT FROM AUTHOR]