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Input parameter and thermal load representation uncertainties effects on the buckling and dynamic characteristics of cylindrical tubes. (English) Zbl 1502.74053

Summary: This research considers different methods in sensitivity analysis and uncertainty quantification applied to cylindrical tubes subject to three types of thermal load representation, namely, uniform, linear, and nonlinear in the radial direction. Sensitivity analysis techniques are used to quantify and rank the parameters that are most influential in altering the critical buckling temperatures, the post-buckled configuration amplitudes, and the natural frequencies in the pre- and post-buckling regimes. The uncertainty quantification and sensitivity analysis strategies show a great potential and usefulness in terms of determining the most influential input parameters for cylindrical tubes subject to thermal loads. Based on the set of nominal parameters in this study, it is shown that the length is the most sensitive parameter in altering the critical thermal buckling load. Additionally, it is demonstrated how uncertainty in the thermal load representation can lead to over or underestimation in both sensitivity analysis and uncertainty quantification findings. The outcome of this analysis can be utilized by other researchers in the design and optimization of cylindrical tubes in thermal environment.

MSC:

74H55 Stability of dynamical problems in solid mechanics
74H45 Vibrations in dynamical problems in solid mechanics
74K10 Rods (beams, columns, shafts, arches, rings, etc.)
74F05 Thermal effects in solid mechanics

Software:

VARS-TOOL
Full Text: DOI

References:

[1] Abdelkefi, A.; Yan, Z.; Hajj, M., Modeling and nonlinear analysis of piezoelectric energy harvesting from transverse galloping, Smart Mater. Struct., 22, Article 025016 pp. (2013)
[2] Benesty, J.; Chen, J.; Huang, Y.; Cohen, I., Pearson correlation coefficient, (Noise Reduction in Speech Processing (2009), Springer topics in signal processing: Springer topics in signal processing Berlin, Heidelberg: Springer)
[3] Campolongo, F.; Cariboni, J.; Saltelli, A., An effective screening design for sensitivity analysis of large models, Environ. Model. Software, 22, 1509-1518 (2007)
[4] Campolongo, F.; Saltelli, A.; Cariboni, J., From screening to quantitative sensitivity analysis. A unified approach, Comput. Phys. Commun., 182, 978-988 (2011) · Zbl 1219.93120
[5] Ceballes, S.; Abdelkefi, A., Observations on the general nonlocal theory applied to axially loaded nanobeams, Microsyst. Technol., 27, 739-761 (2021)
[6] Ceballes, S.; Abdelkefi, A., Application of sensitivity analysis and uncertainty quantification methods on the dynamic response of general nonlocal beams, Appl. Math. Model., 97, 322-343 (2021) · Zbl 1481.74430
[7] Ghaffari, S.; Ceballes, S.; Abdelkefi, A., Role and significance of thermal loading on the performance of carbon nanotube-based mass sensors, Mater. Des., 160, 229-250 (2018)
[8] Ghaffari, S.; Ceballes, S.; Abelkefi, A., Effects of thermal loads representations on the dynamics and characteristics of carbon nanotubes-based mass sensors, Smart Mater. Struct., 28, Article 074003 pp. (2019)
[9] Huang, H.; Han, Q., Nonlinear dynamic buckling of functionally graded cylindrical shells subjected to time-dependent axial load, Compos. Struct., 92, 593-598 (2010)
[10] Jones, N., A theoretical study of the dynamic plastic behavior of beams and plates with finite-deflections, Int. J. Solid Struct., 7, 1007-1029 (1971) · Zbl 0241.73045
[11] Kadhim, D.; Jobair, H.; Abdullah, O., Analytical evaluation of temperature dependent thermal conductivity for solid and hollow cylinders subjected to a uniform heat generation, Int. J. Mech. Eng. Technol., 9, 1095-1106 (2018)
[12] Kong, S.; Zhou, S.; Nie, Z.; Wang, K., Static and dynamic analyssi of microbeams based on strain gradient elesticity theory, Int. J. Eng. Sci., 47, 487-498 (2009) · Zbl 1213.74190
[13] Kristensen, M. H.; Peterson, S., Choosing the appropriate sensitivity analysis for building energy model-based investigations, Energy Build., 130, 166-176 (2016)
[14] Larkin, K.; Hunter, A.; Abdelkefi, A., Comparative investigations of multi-fidelity modeling on performance of electrostatically-actuated cracked microbeams, Int. J. Mech. Sci., 192, Article 106139 pp. (2021)
[15] Latif, U.; Uddin, E.; Younis, M.; Aslam, J.; Ali, Z. S.M.; Abdelkefi, A., Experimental electro-hydrodynamic investigation of flag-based energy harvesting in the wake of inverted C-shape cylinder, Energy, 215, Article 119195 pp. (2021)
[16] Li, C.; Mahadevan, S., Sensitivity analysis of a Bayesian network, ASME J. Risk Uncertain. Eng. Syst., Part B, 4, Article 011003 pp. (2018)
[17] Li, K.; He, S.; Liu, H.; Mao, X.; Li, B.; Lou, B., Bayesian uncertainty quantification and propogation for prediction of milling stability lobe, Mech. Syst. Signal Process., 138, 106-532 (2020)
[18] Liu, Y.; Wang, L.; Qiu, Z.; Chen, X., A dynamic force reconstruction method based on modified Kalman filter using acceleration responses under multi-source uncertain samples, Mech. Syst. Signal Process., 159, Article 107761 pp. (2021)
[19] Menberg, K.; Heo, Y.; Choudhary, R., Sensitivity analysis methods for building energy models: comparing computational costs and extractable information, Energy Build., 133, 433-445 (2016)
[20] Morris, M., Factorial sampling plans for preliminary computational experiments, Technometrics, 33, 161-174 (1991)
[21] Morris, M., Factorial sampling plans for preliminary computational experiments, Technometrics, 33, 161-174 (1991)
[22] Morris, M.; Mitchell, T., Exploratory designs for computational experiments, J. Stat. Plann. Inference, 43, 381-402 (1995) · Zbl 0813.62065
[23] Morris, M.; Mitchell, T., Exploratory designs for computational experiments, J. Stat. Plann. Inference, 43, 381-402 (1995) · Zbl 0813.62065
[24] Nayfeh, A. H.; Emam, S. A., Exact solution and stability of postbuckling configurations of beams, Nonlinear Dynam., 54, 395-408 (2008) · Zbl 1173.74019
[25] Razavi, S.; Sheikholeslami, R.; Gupta, H.; Haghnegahdar, A., VARS-TOOL: a toolbox for comprehensice, efficient, and robust sensitivity and uncertainty analysis, Environ. Model. Software, 112, 95-107 (2019)
[26] Renuart, E.; Fitzgerald, A.; Kenny, T.; Dauskardt, R., Fatigue crack growth in micro-machined single-crystal silicone, J. Mater. Res., 19, 2635-2640 (2004)
[27] Saltelli, A., Making best use of model evaluations to compute sensitivity indices, Comput. Phys. Commun., 145, 280-297 (2002) · Zbl 0998.65065
[28] Shaker, F., Effect of Axial Load on Mode Shapes and Frequencies of Beams (1975), National Aeronautics and Space Administration: National Aeronautics and Space Administration Cleveland, OH
[29] Siranosian, A.; Schembri, P.; Miller, N., The Benchmark Extensible Tractable Testbed Engineering Resource (BETTER) (No. LA-UR-16-23838) (2016), Los Alamos National Laboratory: Los Alamos National Laboratory Los Alamos, NM (USA)
[30] Sobol, I., Global sensitivity indices for nonlinear mathematical models and their Monte Carlo simulations, Math. Comput. Simulat., 55, 271-280 (2001) · Zbl 1005.65004
[31] Umair, M.; Latif, U.; Uddin, E.; Abdelkefi, A., Experimental hydrodynamic investigations on the effectiveness of inverted flag-based piezoelectric energy harvester in the wake of bluff body, Ocean Eng., 245, Article 110454 pp. (2022)
[32] Wang, L.; Liu, Y.; Liu, Y., An inverse method for distributed dynamic load identification of structures with interval uncertainties, Adv. Eng. Software, 131, 77-89 (2019)
[33] Xiao, S.; Lu, Z.; Wang, P., Multivariate global sensitivity analysis for dynamic modelsl based on wavelet analysis, Reliab. Eng. Syst. Saf., 170, 20-30 (2018)
[34] Xiong, C.; Wang, L.; Liu, G.; Shi, Q., An iterative dimension-by-dimension method for structural interval response prediction with multidimensional uncertain variables, Aero. Sci. Technol., 86, 572-581 (2019)
[35] Xu, J.; Yuan, X.; Zhang, H.; Zhao, Z.; Zhao, W., Combined effects of axial load and temperature on finite deformation of incompressible thermo-hyperelastic cylinder, Appl. Math. Mech., 40, 499-514 (2019) · Zbl 1416.74019
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