Title: Uncertainty Quantification and Propagation of Heat Transfer Coefficients in Thermal Management for Composites Manufacturing using Bayesian Inference

Authors: Arghyanil Bhattacharjee, Kamyar Gordnian, Anmol Bhatia, Gavin Tao, Reza Vaziri, Trevor Campbell, Anoush Poursartip

DOI: 10.33599/nasampe/c.24.0280

Abstract: The development of thermal management models using physics-based process simulation for composites manufacturing has become well established in recent years. However, the determination of the boundary conditions in the form of heat transfer coefficients (HTCs) at the air-part and air-tool interfaces during convective heat transfer-based curing processes (such as autoclaves, ovens) remains a challenge and a major source of uncertainty in the modeling of such processes. Typically, physics-based approaches such as simplified 1D through-thickness models or computationally intensive 3D Computational Fluid Dynamics (CFD) simulations have been used to estimate the HTCs. However, such deterministic methods are not able to capture the effect of uncertainties involved in estimating HTC values and their consequent effects in predicting the corresponding thermal histories of curing parts in process simulations models. In this work, the applicability of statistical inference-based models to calculate HTC distributions and quantify the associated uncertainties are demonstrated using experimental datasets generated from the cooling of a heated tool under a controlled airflow setup. The uncertainty in the inferred HTC distributions is then integrated into a process simulation model to investigate the effect of uncertainty propagation on the thermal response of the tool by comparing the predicted thermal histories to experimental measurements.

References: [1] F. P. Incropera and D. P. DeWitt, Fundamentals of heat and mass transfer, 4th ed. New York: Wiley, 1996. [2] A. A. Johnston, “An integrated model of the development of process-induced deformation in autoclave processing of composite structures,” PhD Thesis, The University of British Columbia, Vancouver, 1997. [3] T. A. Bogetti and J. W. Gillespie Jr, “Two-dimensional cure simulation of thick thermosetting composites,” J Compos Mater, vol. 25, no. 3, pp. 239–273, 1991. [4] A. Johnston, P. Hubert, G. Fernlund, R. Vaziri, and A. Poursartip, “Process Modeling of Composite Structures Employing a Virtual Autoclave Concept,” Science and Engineering of Composite Materials, vol. 5, Jan. 1996, doi: 10.1515/SECM.1996.5.3-4.235. [5] R. A. Kline and M. C. Altan, “Curing of composite materials using extended heat transfer models,” US5453226A, Sep. 1995 Accessed: Nov. 30, 2023. [Online]. Available: https://patents.google.com/patent/US5453226A/en [6] N. A. Slesinger, “Thermal Modeling Validation Techniques for Thermoset Polymer Matrix Composites,” Masters Thesis, The University of British Columbia, Vancouver, 2010. [7] T. A. Weber, J. C. Arent, L. Münch, M. Duhovic, and J. M. Balvers, “A fast method for the generation of boundary conditions for thermal autoclave simulation,” Compos Part A Appl Sci Manuf, vol. 88, pp. 216–225, Sep. 2016, doi: 10.1016/j.compositesa.2016.05.036. [8] K. M. Nelson, T. Wu, and C.-H. Lin, “Airflow in autoclaves,” US 20160348976A1, Dec. 01, 2016 Accessed: Feb. 01, 2024. [Online]. Available: https://patents.google.com/patent/US20160348976A1/en [9] A. I. Khan, M. M. Billah, C. Ying, J. Liu, and P. Dutta, “Bayesian Method for Parameter Estimation in Transient Heat Transfer Problem,” Int J Heat Mass Transf, vol. 166, p. 120746, Feb. 2021, doi: 10.1016/j.ijheatmasstransfer.2020.120746. [10] N. Gnanasekaran and C. Balaji, “A Bayesian approach for the simultaneous estimation of surface heat transfer coefficient and thermal conductivity from steady state experiments on fins,” Int J Heat Mass Transf, vol. 54, no. 13–14, pp. 3060–3068, Jun. 2011, doi: 10.1016/j.ijheatmasstransfer.2011.01.028. [11] J. Berger and C. Legros, “Surface Transfer Coefficients Estimation for Heat Conduction Problem Using the Bayesian Framework,” Heat Transfer Engineering, vol. 44, no. 5, pp. 391–410, Mar. 2023, doi: 10.1080/01457632.2022.2068217. [12] P. S. Jakkareddy and C. Balaji, “Estimation of spatially varying heat transfer coefficient from a flat plate with flush mounted heat sources using Bayesian inference,” J Phys Conf Ser, vol. 745, p. 032094, Sep. 2016, doi: 10.1088/1742-6596/745/3/032094. [13] M. Iglesias, Z. Sawlan, M. Scavino, R. Tempone, and C. Wood, “Bayesian inferences of the thermal properties of a wall using temperature and heat flux measurements,” Int J Heat Mass Transf, vol. 116, pp. 417–431, Jan. 2018, doi: 10.1016/j.ijheatmasstransfer.2017.09.022. [14] K. Gordnian, A. Bhattacharjee, A. Poursartip, R. Vaziri, and T. Campbell, “Estimation of Boundary Conditions, Along with Quantification and Propagation of Uncertainty, in Curing Processes of Composites: A Bayesian Framework,” Unpublished work.

Conference: CAMX 2024 | San Diego CA

Publication Date: 2024/9/9

SKU: TP24-0000000280

Pages: 10

Price: $20.00