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Hi, need to submit a 1750 words paper on the topic Design of the New Nose for Open-Wheel Climb Race Car.
Hi, need to submit a 1750 words paper on the topic Design of the New Nose for Open-Wheel Climb Race Car. The optimization test parameters length setting from 500mm to 700mm and height from 102.8mm to 142.8mm.
The MATLAB codes (Kriging Surrogate Model) were used to help in the optimization of the nose. First, running 10 simulations in different length and height as the database and the maximum downforce predicted with the corresponding length and height noted. Figure 2 shows the optimization of the data as distributed in different positions. The parameters included the maximum down force and the position of the maximum down force.
The nosecone is not the primary producer of down force component. From table 1, the total car absolute largest CL change was about 0.57%, while the least change was of CL was 0.006%. It was found that simulation no.20 has the largest CL which increased the optimization result to about 0.458%. But from the result is hard to find the regulation by simply changing nose length and height may be more simulations needed to show the regulation. Using nose length of 700m and 525m, it was observed that the change in CL is greater when a nose length of 700m is used than for 500m this resulted in an efficiency of 1.149%. The more the simulations, the better the optimization results are realized. Table 2 below, shows each component (nose, front wing, and undertray) CL change in different optimization tests.
From table 2, the results of down force change regulation between the front wing and undertray are shown. From the analysis of the lower nose, the front wing CL increases which has the potential of decreasing the undertray CL. At the higher nose of the nosecone, undertray CL increase but front wings CL decrease. This operation of the machine makes it possible for any change in ride height, the body of full car CL will change. At the same time, when the front wing CL increases, the undertray CL decreases. Quantitatively, from the optimization results, the difference between maximum front wing CL and minimum CL reached was about 4.5% and the difference between .under tray CL and minimum CL reached 6.7%.
