MATEC Web Conf.
Volume 264, 20192nd International Conference on Composite Material, Polymer Science and Engineering (CMPSE2018)
|Number of page(s)||5|
|Section||Thermal Properties (Thermal Stability and Thermo-Plasticity)|
|Published online||30 January 2019|
The cubic regression model of thermal estimation in the flammability test of the fibrous compound used in bus bodies
Universidad Técnica de Ambato, Facultad de Ingeniería Civíl y Mecánica, Research group in materials and production,
Av. Los Chasquis and Río Payamino,
a Corresponding author: email@example.com
The fire behavior of fiber compounds is a serious concern in automotive applications. The objective of the proposed work is to predict thermal behavior during flammability testing of the composite material of polymer matrix reinforced with fiberglass used in the interior lining of bodies. Different regression models were performed to determine the best fit. This regression analysis determines the existing correlation between the acquired parameters of burn time and temperature versus two types of fibers used for the interior decorative lining. Different regression coefficients were determined and used for the prediction. Through the best fit regression model, thermal behavior of burning during the flammability test is predicted under ISO standard 3795: 1989 and FMVSS 302. The prediction was made for two types of composites, Roof Fiber, FT, and Fiber for laterals, FL. The cubic regression model showed the best prediction fit with a Rq of 0.79 for FT and 0.81 for FL.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.