Analytical Model for Assessing Collapse Risk During Mountain Tunnel Construction Guo-Hua Zhang, Yu-Yong Jiao, Li-Biao Chen, Hao Wang, and Shu-Cai Li
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326 ARTICLE Analytical model for assessing collapse risk during mountain tunnel construction Guo-Hua Zhang, Yu-Yong Jiao, Li-Biao Chen, Hao Wang, and Shu-Cai Li Abstract: Risk management for safety in mountain tunnel construction is of great significance. However, existing research lags behind engineering applications. In this paper, the risk of mountain tunnel collapse is used as an example to illustrate a new assessment method based on case-based reasoning, advanced geological prediction, and rough set theory. First, the risk sur- roundings and risk factors involved in tunnel collapse are integrated and summarized, and a risk assessment index system is established for tunnel collapse. At the same time, because the dynamic response parameters obtained by the advanced geological prediction usually indicate a typical geological structure, sensitive response parameters are introduced in the assessment index system. Advanced risk assessment can be performed for tunnel sections at a certain distance ahead of the tunnel face. Second, the major risk surroundings and the advanced geological prediction results are analyzed for the tunnel under assessment. Cases with similar attribute characteristics are selected via comparison with previous cases. Attribute reduction and calculation of weights are subsequently performed for the risk surroundings and risk factors of similar cases based on the attribute signifi- cance theory of rough sets. Finally, index screening and objective weights are applied in the fuzzy comprehensive assessment model. The results of this paper can be used to improve the theoretical level and reliability of risk assessment in tunnel safety and serve as a reference for tunnel construction. Key words: mountain tunnel, case-based reasoning, advanced geological prediction, rough set, risk assessment. Résumé : La gestion des risques visant a` garantir la sécurité des chantiers de construction des tunnels de montagne revêt une grande importance. Cependant, la recherche accuse un retard important par rapport l’ingénierie liée a` ce domaine. Dans le présent article, le risque d’effondrement des tunnels de montagne est utilisé comme exemple d’application d’une nouvelle méthode d’évaluation axée sur le raisonnement par cas, sur la prévision avancée des risques géologiques sur la théorie des ensembles approximatifs. Dans un premier temps, les risques et facteurs de risque associés a` l’effondrement d’un tunnel sont rassemblés et synthétisés et un système d’indices d’évaluation de ces risques est créé. Parallèlement, étant donné que les paramètres de la réponse dynamique obtenus par prévision avancée des risques géologiques sont généralement associés a` une structure géologique typique, les paramètres de la réponse sensible sont incorporés au système d’indices d’évaluation. Il est For personal use only. possible de réaliser une évaluation poussée des risques d’effondrement dans des segments de tunnel situés a` l’avant du front de taille du tunnel, a` l’avant de ce dernier. Dans un deuxième temps, les risques majeurs associés et les résultats de la prévision avancée des risques géologiques sont analysés dans le cas du tunnel évalué. On sélectionne des cas d’étude présentant des caractéristiques similaires, en les comparant a` d’autres exemples passés. On procède ensuite a` une réduction des attributs et au calcul des poids dans le cas des risques associés et des facteurs de risques de cas similaires, a` l’aide de la théorie des ensembles approximatifs basée sur l’importance des attributs. Enfin, on applique le filtrage des indices et les poids objectifs au modèle flou d’évaluation exhaustive. Les résultats de la présente étude peuvent servir a` améliorer le niveau théorique et la fiabilité du processus d’évaluation des risques visant a` garantir la sécurité des tunnels et servir d’outil de référence pour la construction de tunnels. [Traduit par la Rédaction] Mots-clés : tunnel de montagne, raisonnement par cas, prévision avancée des risques géologiques, ensemble approximatif, évaluation des risques. Introduction (mud gushing, water inrush), and other hazards frequently occur. Complex geological conditions, intensive tectonic movements, During construction of mountain tunnels, risk accidents such as sophisticated construction technology, and unforeseeable risks collapses and gushing not only result in construction delays, dam- are usually encountered during construction of mountain tun- age to equipment, and increased investment, but also pose a great nels. The construction technology and management level can threat to the safety of construction workers. Therefore, many hardly catch up with the rapid development of large-scale moun- studies have been conducted on the mechanisms of tunnel collapse tain tunnels. In addition, due to the nonobjective evaluation of and gushing and the countermeasures to control the risk level the risks during underground engineering construction, nonsci- within an acceptable range via risk assessment and management. entific risk management, and insufficient investment in risk man- Einstein et al. (1978) and Einstein (1996) proposed risk analysis Can. Geotech. J. Downloaded from www.nrcresearchpress.com by "Wuhan Institute of Rock and Soil Mechanics, CAS" on 02/03/16 agement, tunnel collapses (including large deformation), gushing for tunnel engineering and initiated an upsurge in studies on risk Received 10 February 2015. Accepted 24 July 2015. G.-H. Zhang, Y.-Y. Jiao, and H. Wang. State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, P.R. China. L.-B. Chen. Fujian Provincial Expressway Construction Directorate, Fuzhou, Fujian 350001, China. S.-C. Li. Geotechnical & Structural Engineering Research Centre, Shandong University, Jinan 250061, P.R. China. Corresponding author: Yu-Yong Jiao (e-mail: [email protected]). Can. Geotech. J. 53: 326–342 (2016) dx.doi.org/10.1139/cgj-2015-0064 Published at www.nrcresearchpress.com/cgj on 17 August 2015. Zhang et al. 327 assessment for underground engineering. In the early days, Sturk Algorithm of attribute reduction et al. (1996), Bielecki (1998), Stille et al. (1998), Isaksson et al. (1999), Rough set (RS) theory can be viewed as a mathematical tool that Reilly (2000), and Choi et al. (2004) conducted a large number of enables approximate reasoning that involves uncertainty and studies on risk assessment for road tunnels, undersea tunnels, vagueness in decision-making processes (Pawlak 1982). Due to its and subway tunnels, and proposed some concepts and methods advantages, which include the elimination of the need for addi- for tunneling risk assessment. These studies established the the- tional information about data and the ability to extract rules di- oretical and practical bases for tunneling risk assessment. In 2004, rectly from data itself, this theory has been used in more and the International Tunnel Association released the “Guidelines for more domains. The fundamental knowledge about RS theory is Tunneling Risk Management”, which provides a reference and introduced in Appendix A. method for tunneling risk management (Eskesen et al. 2004). At It is well known that when the condition attributes for any the same time, the Monte Carlo (Chung et al. 2006; Ruwanpura decision-making information system are used in classifications, and Ariaratnam 2007; Min et al. 2008), Bayesian networks (Shin the significance of each attribute is different. Certain attributes et al. 2009; Sousa and Einstein 2012), and artificial neural net- play dominant roles, others are less important, and other attri- works (Benardos and Kaliampakos 2004) methods have been used butes might be redundant. Attribute reduction is a process used to in tunnel risk assessment. These models are able to describe in obtain a concise decision-making information system by remov- detail the uncertainties involved in the prediction of geotechnical ing those redundant or insignificant attributes while the classifi- conditions and the common variations of performance rates or cation remains unchanged. For the discretized decision-making unit costs, but in general, they fail to consider the impact of other information system, the information entropy theory of rough sets factors, including extraordinary events (e.g., collapse, deforma- is applied for attribute reduction and weight calculation accord- tion, water inrush) as well as construction and organizational ing to the following procedures: factors. In particular, the latter ones lead to a significant increase Step 1 in the uncertainty of the project cost and duration, and should be For the discretized information system S =<U, C ഫ D, V, f >, included in a realistic model (Sousa and Einstein 2012). equivalence partitioning is performed. The indiscernible relation- Various research software packages for risk analysis during tun- ships U|IND͑D͒ and U|IND͑C͒ are calculated for the decision attri- nel construction have been developed over recent years, and the bute D and the condition attribute C, respectively. U is a finite set most important one is Decision Aids for Tunneling (DAT). The DAT of objects, V is a domain of attributes, and f is an information approach is based on an interactive program that uses probabilis- function. tic modeling of the construction processes to analyze the effects of geotechnical uncertainties and construction uncertainties on Step 2 the construction costs and duration (Einstein 2002). However, the Calculation of the condition information