A greater need to enhance comfort characteristics during vehicle design process has recently forced the manufacturers to develop simulation-based approaches. In this study, a simulation-based model of a full-car suspension system is proposed to predict the ride comfort. A simulation model was created for calculating ride comfort effectively. This simulation uses seat-back, seat-surface, and feet acceleration values collected from four different road vehicles which were run on six different roads. Parameters which effect ride comfort were also investigated. Using these parameters, a simulation-based model of a full-car suspension system including engine and seat is created for predicting the ride comfort. The correlation between the results of physical tests and the simulation is very promising. It was found that the effect of an engine has a substantial influence on the ride comfort. To find the optimum values of each parameter, an optimization process was executed properly and added in the model. Using this model, the best ride comfort values were computed without the need of physical prototypes. The developed algorithm can be very helpful as an assistant tool for engineers during vehicle design and manufacturing process.
Due to their applications in many branches of science, topological graph
indices are becoming more popular every day. Especially as one can model
chemical molecules by graphs to obtain valuable information about the
molecules using solely mathematical calculations on the graph. The inverse
problem for topological graph indices is a recent problem proposed by Gutman
and is about the existence of a graph having its index value equal to a
given non-negative integer. In this paper, the inverse problem for Bell
index which is one of the irregularity indices is solved. Also a recently
defined graph invariant called omega invariant is used to obtain several
properties related to the Bell index.
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