MODELLING OF MINING DRAGLINE JOINT: A SENSITIVITY ANALYSIS WITH SOBOL’S VARIANCE-BASED METHOD
DOI:
https://doi.org/10.11113/jt.v78.8480Keywords:
Sensitivity analysis, mining dragline joint, mechanical response, variance-based methodAbstract
A sensitivity analysis is performed to determine the key uncertain geometric parameters that influence the mechanical response of a mining dragline joint subjected to large dynamic loading. An alternative design is modeled where the welded of the lacing members are attached on the sleeve structure rather than welded to the main chord directly using ABAQUS. Based on the simulated values, the Sobol's variance-based method which consists of first-order and total-effect sensitivity indices is presented. The sensitivity of four uncertain geometric parameters on the mechanical responses are investigated; i.e. thickness of sleeve, thickness of bracing members, weld fillet and eccentricity. To conclude, it is observed that the thickness of sleeve is the most dominant uncertain geometric parameter with respect to the specified mechanical responses.  Â
References
Hartman. 2014. Retrieve on 22 September 2014. Introduction to Mining, http://www.cienciaviva.pt.
Winstanley, G., Usher, K., Corke, P., Dunbabin, M., and Roberts, J. 2007. Dragline Automation—A Decade of Development. IEEE Robotics & Automation Magazine. 57-64.
Mashiri, F. R., Joshi, S., Pang, N. L., Dayawansa, D. P., Zhao, X. L., Chitty, G., Jiao, H., and Price, J. W. H. 2011. Service Loads in Dragline Tubular Structures: A Case Study of Cluster A5. Structural Control and Health Monitoring.
Pang, N. L., Zhao, X. L., Mashiri, F. R., and Dayawansa, P. 2009. Full-size Testing to Determine Stress Concentration Factors of Dragline Tubular Joints. Engineering Structures. 31: 43-56.
Barsoum, Z. 2008. Residual Stress Analysis and Fatigue of Multi-Pass Welded Tubular Structures. Engineering Failure Analysis. 15: 863-874.
Joshi, S. and Price, J. W. H. 2009. A Comparative Study on Application of Design Codes for Prediction of Fatigue Life of a Mining Dragline Cluster. Engineering Failure Analysis. 16: 1562-1569.
Joshi, S., Price, J. W. H., and Dayawansa, D. P. 2010. Influence of Variations in Geometric Parameters and Alternative Design for Improved Fatigue Life of A Mining Dragline Joint. Engineering Structures. 32: 1333-1340.
Joshi, S., Mashiri, F. R., Dayawansa, D. P., Zhao, X. L., and Price, J. W. H. 2010. Structural Health Monitoring of A Dragline Cluster Using The Hot Spot Stress Method. Structural Health Monitoring. 10(2): 173-187.
Anderson, T. L. 2006. Fracture Mechanics-Fundamentals and Applications. Edition 3. London.
Dayawansa, P., Chitty, G., Kerezsi, B., Bartosiewicz, H., and Price, J. W. H. 2006. Fracture Mechanics of Mining Dragline Booms. Engineering Failure Analysis. 13: 716-725.
Saltelli, A., Chan, K., and Scott, E. M. 2000. Sensitivity Analysis. Series in Probability and Statistics. West Sussex: Wiley.
Wei, P., Lu, Z., and Song, J. 2013. A New Variance-based Global Sensitivity Analysis Technique. Computer Physics Communications. 184: 2540-2551.
Homma, T., and Saltelli, A. 1996. Importance Measures in Global Sensitivity Analysis of Nonlinear Models. Reliability Engineering and System Safety. 52: 1-17.
Quaglietta, E., and Punzo, Vincenzo. 2013. Supporting the Design of Railway Systems By Means of A Sobol Variance-Based Sensitivity Analysis. Transportation Research Part C. 34: 38-54.
Nossent, J., Elsen, P., and Bauwens, W. 2011. Sobol’ Sensitivity Analysis of a Complex Environmental Model. Environmental Modelling & Software. 26: 1515-1525.
Iman, R. L., and Helton J. C. 1985. A Comparison of Uncertainty and Sensitivity Analysis Techniques for Computer Models. Sandia Report SAND. 84-87.
Sobol, I. M. 1993. Sensitivity Analysis for Nonlinear Mathematical Models. Mathematical Modeling & Computational Experiment. 1: 407-414.
Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M. and Tarantola, S. 2007. Variance-Based Methods, in Global Sensitivity Analysis. The Primer, John Wiley & Sons, Chichester.
Beer, F. P., and Johnston E. R. 1992. Mechanics of Materials. (Vol2). McGraw-Hil. Bilal, N. (2014, July 14-17). Implementation Of Sobol’s Method Of Global Sensitivity Analysis To A Compressor Simulation Model. 22nd International Compressor Engineering Conference at Purdue.
Ilyani Akmar, A. B., Lahmer, T., Bordas, S. P. A., Beex, L. A. A., and Rabczuk, T. 2014. Uncertainty Quantification of Dry Woven Fabrics: A Sensitivity Analysis on Material Properties. Composite Structures. 116: 1-17.
Goh, E. G., and Noborio K. 2014. Sensitivity Analysis Using Sobol ‘Variance-Based Method on the Haverkamp Constitutive Functions Implemented in Richards’ Water Flow Equation. Malaysian Journal of Soil Science. 18: 19-33.
ASME/ANSI B36.19, Stainless Steel Pipe.
Abaqus 6. 2013. 13 SIMULIA Documentation.
Helton, J. C., and Davis, F. J. 2003. Latin hypercube Sampling and the Propagation of Uncertainty in Analyses of Complex Systems. Reliability Engineering and System Safety. 18: 23-69.
Downloads
Published
Issue
Section
License
Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.
