An Approach Integrating Dimensional Analysis and Field Data for Predicting the Load on Tunneling Machine
- 12 Downloads
The forecast of machine performance has been widely discussed in recent years, where accurate predictions with common regularity could reduce costs and achieve time-efficient construction. This study uses the case of predicting the load (including the thrust and torque) acting on tunneling machine. Because most data-mining techniques are black-box models, which rely too much on specific data and cannot reveal the mechanics principle. A new approach is developed to deal with this problem, which combines data analysis with mechanics principle through dimensional analysis. Firstly, power relations between the soil properties, operational, structural parameters and the load are obtained. Then dimensionless model is established, which involves the dominant dimensionless groups representing operating status and geological conditions. At last, to overcome the problem of high correlation between independent variables, ridge estimation is performed. The obtained dimensionless model is in accordance with Krause Empirical Model for the power relationship between the load and the cutterhead diameter. Moreover, the earth pressure in the chamber is proportional to the load, which is consistent with previous experimental results. In addition to its prediction ability, the validation data from two urban subway projects show that, the proposed model can correctly indicating the geological variation during excavation.
Keywordsdimensional analysis tunnel engineering thrust torque ridge estimation prediction
Unable to display preview. Download preview PDF.
This research is supported by National Key R&D Program of China [No.2018YFB1702505], National Natural Science Foundation of China [No. 11872269], and Natural Science Foundation of Tianjin [No.18JCYBJC19600].
- Ates, U., Bilgin, N., and Copur, H. (2014). “Estimating torque, thrust and other design parameters of different type TBMs with some criticism to TBMs used in Turkish tunneling projects.” Tunnelling and Underground Space Technology, vol. 40, pp. 46–63, DOI: https://doi.org/10.1016/j.tust.2013.09.004.CrossRefGoogle Scholar
- Krause, T. (1987). Shield tunneling with fluid and earth-supported face, Message from the Institute of Foundation Engineering and Soil Mechanics, TU Braunschweig, 24 (in German).Google Scholar
- Kumar, S., Sharma, V., Choudhary, A. K. S., Chattopadhyaya, S., and Hloch, S. (2013). “Determination of layer thickness in direct metal deposition using dimensional analysis.” International Journal of Advanced Manufacturing Technology, Vol. 67, Nos. 9–12, pp. 2681–2687, DOI: https://doi.org/10.1007/s00170-012-4683-1.CrossRefGoogle Scholar
- Lin, X. H., Kang, Y. L., Qin, Q. H., and Fu, D. H. (2005). “Identification of interfacial parameters in a particle reinforced metal matrix composite Al6061–10% Al2O3 by hybrid method and genetic algorithm.” Computational Materials Science, vol. 32, no. 1, pp. 47–56, DOI: https://doi.org/10.1016/j.commatsci.2004.04.006.CrossRefGoogle Scholar
- Mahdevari, S., Shahriar, K., Yagiz, S., and Shirazi, M. A. (2014). “A support vector regression model for predicting tunnel boring machine penetration rates.” International Journal of Rock Mechanics and Mining Sciences, vol. 72, pp. 214–229, DOI: https://doi.org/10.1016/j.ijrmms.2014.09.012.CrossRefGoogle Scholar
- Meng, X., Qin, G., and Zou, Z. (2018). “Characterization of molten pool behavior and humping formation tendency in high-speed gas tungsten arc welding.” International Journal of Heat and Mass Transfer, vol. 117, pp. 508–516, DOI: https://doi.org/10.1016/j.ijheatmasstransfer.2017.09.124.CrossRefGoogle Scholar
- Tyng, Y. H., Chao, O. Z., Kong, K. K., Ismail, Z., Rahman, A. G. A., and Chong, W. T. (2017). “Similitude study of an in-service industrial piping system under high flow induced vibration.” Journal of Mechanical Science and Technology, vol. 31, no. 8, pp. 3705–3713, DOI: https://doi.org/10.1007/s12206-017-0713-0.CrossRefGoogle Scholar
- Wang, J., Kang, Y. L., Qin, Q. H., Fu, D. H., and Li, X. Q. (2008). “Identification of time-dependent interfacial mechanical properties of adhesive by hybrid/inverse method.” Computational Materials Science, vol. 43, no. 4, pp. 1160–1164, DOI: https://doi.org/10.1016/j.commatsci.2008.03.007.CrossRefGoogle Scholar
- Wu, X. Q., Wang, X., Wei, Y. P., Song, H. W., and Huang, C. G. (2012). “Parametric study on single shot peening by dimensional analysis method incorporated with finite element method.” Acta Mechanica Sinica, vol. 28, no. 3, pp. 825–837, DOI: https://doi.org/10.1007/s10409-012-0072-0.CrossRefGoogle Scholar