# ASSESSING MOTORCYCLE CRASH-RELATED HEAD INJURIES USING FINITE ELEMENT SIMULATIONS

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4 Figure 4: Motorcycle-car impact configuration. Figure 5: The position of the dummy in contact with the car. 4. INJURY ASSESSMENT It is common practice, in the injury assessment procedure, to evaluate the level of injuries using only the part of the body which is to be affected by the impact. The interest here is focused on the short time period of the impact only and the influence of the remaining mass is already incorporated into the impact speed extracted from the simulation using the full dummy model. Therefore, no added mass or inertia is included. Similarly, only the part of the car in contact with the head is considered during the next step of the procedure. The boundary conditions for the window are obvious; the points on its boundaries are fixed in all directions, as though the glass is fixed in the surrounding structure of the car. The HICs for the simulations in cases of the head with and without the helmet are 732 and 12958, respectively. A value of 1000 corresponds to 18 % probability of a severe head injury, a 55 % probability of a serious injury and a 90 % probability of a moderate head injury to the average adult [20]. Fig. 6 shows both the models with and without the helmet and the distribution of the energy transmitted during the impact at the same time instant after the fist contact occurs. As expected, the figure shows that the skull and brain absorb less energy with the helmet protection on, as most of it is absorbed by the helmet itself. Figure 6: Specific energy in the models with and without the helmet, respectively. 146

5 5. DESIGN OF EXPERIMENTS The survival of a motorcyclist can depend on the choice of materials in the helmet and/or the window. Therefore, the question arises about the effect of the used materials on the object of interest, i.e. for the present study the HIC and the maximum value of the internal energy within the brain. Design of Experiments (DoE) can be performed in order to evaluate the factors that control the HIC or other objectives. A set of control tests is conducted, and these are analysed, in order to determine the relationship between the materials affecting the process and the output of that process. Three variables are chosen to perform the DoE, namely the scale factors for yield curves of two of the foams surrounding the head and the Young s modulus of the window. In other words, all these variables determine the stiffness of the chosen materials. Since the impact is to the frontal bone of the skull, the third foam, protecting the cheeks, is not considered for the DoE. Table I: Variables determining the stiffness of the chosen materials and the corresponding HICs. Run Foam Liner 1 Foam Liner 2 Window (MPa) HIC Energy in Brain (mj) Figure 7: Interpolated response surface. The values for all the materials are summarized in Table I, where foam liner 1 represents the largest liner surrounding most of the skull and foam liner 2 represents the smaller one on top of the head, see Fig.1. Each of the variables has two different values and altogether they complete eight different combinations, i.e. full factorial DoE measuring the response of every possible combination of factors. Thus, eight simulations of these combinations are computed using RADIOSS solver and analysed using HyperStudyDSS. The solutions are summarized in 147

6 the last two columns of Table I. The values of corresponding HICs vary substantially around the mean value of 832. Therefore, naturally, the values of stiffness of the chosen materials could predetermine the survival of the motorcycle rider in the given scenario. Fig. 7 depicts the effect of the stiffnesses of both of the liner components on the HIC. The higher the stiffness of liner 2, the higher the HIC. However, it is not as clear with the stiffness of liner 1. In case of high stiffness of liner 2, the increasing stiffness of liner 1 decreases the chance of head injury. In case of low stiffness of liner 2, the increasing stiffness of liner 1 has only a small influence on the HIC. An explanation of this combined effect is not really straightforward. Possibly due to the geometry of both of the liners, having liner 2 stiffer than liner 1 causes an additional movement inside the helmet which influences the global deceleration of the head during impact. Fig. 8 shows the effects and the combined effects of all three stiffnesses on the HIC. Every graph has three horizontal dot-dashed lines. The central one represents the mean value, 832. The three graphs on the diagonal show the individual effects of all three variables separately. The stiffness of the foam liner 2 has the greatest variation around the mean value. Similarly as observed from Fig. 7, with an increasing value of the stiffness of foam liner 2, the HIC increases. It is the opposite in the case of foam liner 1, with a smaller effect on the HIC. The stiffness of the window has only a minimal effect on the HIC. The other graphs show the combined effects. The +1 (-1) in those graphs means that the corresponding dashed line in the graph represents the effect of the stiffness of the material stated at bottom of the figure when the material stated at the left has its maximum (minimum) value. For example, the first graph in the second row shows that with increasing stiffness of foam liner 1, and maximum value of the stiffness of liner 2, the HIC decreases; while in case of a minimum value of the stiffness for liner 2 the HIC increases only slightly, as also previously concluded from Fig. 7. Figure 8: The effects and combined effects on HIC. Similarly, since a detailed head model is used, other objectives concerning the head model can be evaluated within the scope of a DoE. Fig. 9 shows the individual and combined effects of the variables on the maximum value of the internal energy absorbed by the brain during the 148

7 impact. The combined effects are linear, and it is therefore rather straightforward to analyse the outcome. The foam liner 1 has the highest effect on the energy absorbed within the brain, and, considering the point of impact, the foam liner 2 has the smallest effect. The stiffness of the window, in comparison to the stiffness of the foam liner 1, influences the internal energy of the brain only slightly. Essentially, there are two levels of the internal energy, lower level for lower stiffness of the foam liner 1 and higher level for the higher stiffness. Interestingly, the run number 5, see Table I, gives the smallest HIC, but, at the same time, a higher level of the internal energy. Although there are no documented threshold values for the HUMOS2 head model to correlate the energy absorbed by the brain and the level of head injuries, the fact that higher levels of the internal energy can occur together with a low value of HIC suggests that the HIC alone, at least in cases of direct impact to the head protected by a more detailed helmet, might not be enough to accurately predict the level of head injuries. Figure 9: The effects and combined effects on internal energy in the brain. 6. CONCLUSION The entire process of the computational modelling of an accident scenario from the first impact between the PTW vehicle and the other vehicle up to the contact of the PTW rider with the other vehicle, including the consequent injury assessment, is presented. Thus, the injury assessment procedure can be summarized in three steps. Firstly the kinematic run is executed with the impact conditions between the two vehicles; secondly the impact conditions between the PTW rider and the other vehicle are extracted at the point of their impact, namely the impact speed and the direction of impact of the relevant body part with respect to the car, and thirdly another run is executed involving the relevant body and car parts with the appropriate boundary and impact conditions. The difference between protected and unprotected head impacts is shown. The DoE analysis is performed on the complex helmet model coupled with a detailed human head model. As the development of the protection evolves, the protective equipments are becoming more complex. It is concluded that the DoE can be very useful in analysing the combined effects of various parts of the protective 149

9 France [17] Chawla, A.; Mukherjee, S.; Mohan, D.; Bose, D.; Rawat, P.; Sakurai, M.; Nakatani, T. (2004). FE simulations of motorcycle-car frontal crashes, validation and observations, JARI Research Journal, Vol. 26, No. 10: [18] Deguchi, M. (2005). Simulation of motorcycle-car collision, 19 th International Technical Conference on the Enhanced Safety of Vehicles, Washington D.C. [19] Mukherjee, S.; Chawla, A.; Mohan, D.; Singh, M.; Sakurai, M.; Tamura, Y. (2001). Motorcyclecar side impact simulation, IRCOBI Proceedings, [20] Mackay, M. (2007). The increasing importance of the biomechanics of impact trauma, Sadhana, Vol. 32, No. 4,

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