Computer Simulation of Polyethylene Terephthalate Carbonated Beverage Bottle Bottom Structure Based on Manual–Automatic Double-Adjustment Optimization

Abstract

PET bottlesare often used as airtight containers for filling carbonated drinks. Because carbonated drinks contain large volumes of CO2 gas, the container needs to bear a tremendous pressure from the inside of the bottle.If the stress exceeds the bearing limit, the material will show the phenomenon of local cracking and liquid overflow.For the structural design, the method of manual adjustment before automatic adjustment was adopted. First, through manual optimization, the initial optimal parameter combination was as follows:the inner diameter of the bottle bottom was 17 mm, the dip angle of the valley bottom was 81°, the deepest part of the valley bottom was 25 mm, and the outer diameter was 27 mm. Comsol software was used for automatic optimization. Compared with the original bottle bottom, the total maximum principal stress and total elastic strain energy in the bottle bottom after manual–automatic double optimization decreased by 69.4% and 40.0%, respectively, and the displacement caused by deformation decreased by 0.60 mm (74.1%). The extremely high reduction ratio was caused by manual–automatic double optimization.

Advances in Polyethylene Terephthalate Beverage Bottle Optimization: A Mini Review

“…Manual adjustment of the inherent parameters one by one is the earliest method used [101]. Common adjustable parameters include bottle bottom inner diameter, valley bottom inclination, valley bottom deepest, outer diameter and claw number (Figure 3).…”

“…In order to solve the shortcomings of the above single manual/automatic optimization, Ge-Zhang et al [101] used a brand-new manual-automatic double optimization, that is, first manually control variables for preliminary comparison and optimization, and then automatically optimize on the premise of keeping the quality of consumable materials unchanged. The total maximum principal stress and total elastic strain energy of the bottle bottom decreased by 69.4% and 40.0%, respectively, and the displacement caused by deformation decreased by 74.1%.…”

“…It can be seen from the comparison in Table 2 that the reduction ratio of maximum principal stress of manual-automatic double optimization and single automatic optimization is much better than that of single manual optimization. The number of iterations indicates that manual-automatic double optimization can achieve convergence with less computation, which also means that optimizing the same bottle will cost less time [101]. In fact, we think that when the goal is to design a new type of bottle, the advantages of manual-automatic double optimization can be more reflected: manually testing and optimizing the macro appearance, and automatically optimizing the details.…”