Regression Model based Method for Stiffness Design of Laminated Glasses

There has been a growing interest in laminated sidelites (or door glasses) in automotive for the benefits of both security and comfort. Current standard products are a 2.1/0.76/2.1 mm construction with soda-lime glass symmetrically distributed on each side of a PVB layer. Due to low shear stiffness of PVB, the standard laminate has a significantly reduced flexural rigidity in comparison to a monolith with the same total thickness. A novel lightweight laminate concept with ultrathin chemically strengthened glass was developed by Corning [1]. This concept considered asymmetrical designs with thinner (0.5 – 1.1 mm) chemically strengthened Corning® Gorilla® Glass laminated to relatively thick outer ply of conventional soda-lime glass and was found to provide enhanced stiffness over standard symmetrical laminate designs of same total thickness. It is known that flexural rigidity of laminated glass depends on multiple variables, such as shape, load distribution and boundary constraining conditions. Theoretical enhanced effective thickness method [2] has been a useful tool for the first-pass analysis but is limited from predicting industry standard testing conditions, such as the unique loading profile of a sidelite. This paper presented a new regression model-based method for accurate predictions of flexural rigidity of different laminate constructions with a consistent 3-point bending test setup. Numerical FEA models have been developed and validated with experimental data, then used to provide training data required for the statistical model. The multi-variable regression method considered six input variables of total glass thickness, thickness ratio of glass plies as well as high-order terms. As a result, the flexural rigidity of the laminate and the improvement percentage over the standard symmetrical design can be predicted with high precision.