# Quantitative Analysis of Drag Reduction Methods for Blunt Shaped Automobiles
## 3 Quantitative Analysis
One of them had larger value in Figure 7a,b. For high drag vehicle SJF, for low drag vehicle, Fairings is more advised. Data that were presented in Figures 5-7 can be seen in a tabulated version, in Tables 1-3, divided according to the three main categories. For active systems, the largest DR was 29% (85 Count) and the largest Count was 147 (DR = 15%). As previously mentioned, the maximum DR was achieved by a high flowrate at the rear slant [15], while the lowest was an active mechanism [58]. As for Count, the highest was attained with an SJA system. From the 6 SJA method, neither DR nor Count values had connection with the St values. From St 0.1 [47] 12.1 [10], it had low and high reductions, which made it difficult to establish general connection to the actuation frequency, though it supports [PERSON] et al. [14]'s findings. The active methods mostly relied on experimental measurements from the 12 presented papers, out of which 11 were using wind tunnel measurements; in addition, 7 applied PIV, and only [PERSON] et al. 2018 [58] used CFD software. Moreover, 10 papers that discussed drag reduction by shape optimization used CFD in 5 cases; and wind tunnel measurements were presented 9 times. The reason for the larger amount of CFD applications is that, with numerically it is faster to examine different geometry, while it is crucial to have a validated model, as previously mentioned. From Table 2, it can be seen that the most effective drag reduction was achieved when side skirt was used on a high drag vehicle. Both DR and Count (26.50% and 184) had a maximum in the work by [PERSON] et al. [69]. Between DR or Count and C\({}_{\text{Dinitial}}\), or year of publication, no correlations were found. The mean value was 14.91% \(\pm\) 8% (97.38 \(\pm\) 63). It can be attributed that the standard deviation was relatively large compared to the mean value, yet the difference between mean and median was relatively small (12%). This main category had the highest minimum value, which shows its effectiveness of the methods. For topology modifications, the methods had a longer list. Between 2010 and 2020, 13 relevant research papers were found that discussed DR on cars. From these papers, significant change could be seen where purely numerical evaluations were made. From the mentioned articles, only two ([PERSON] et al. [92] and [PERSON] et al. [79]) compared their results with wind tunnel measurements. The rest had only validated the CFD models. It is also worth noting that RANS was used for modelling, and with one exception ([PERSON] et al. [19]), effect was not examined with DES or LES methods. Six papers had experimental results to compare the topology modification effects. In Section 2.3.3, it was mentioned that a small wing is a VG type; it was solely applied in ref. [91]. This method was an adjustable height VG. It could have been categorized to winglet due to the height width ratio and to flap due to the surface orientation. Since it was adjustable, it could have even been added to active systems, since it can work adaptively. Flap and Winglet type DR (and Count) mean values were 9.73% \(\pm\) 5.44% (38.72 \(\pm\) 16.00) and 21.31% \(\pm\) 38.52% (209 \(\pm\) 436), respectively. Winglets showed more potential over Flaps. Due to peaking values, subcategories had large standard deviations, though median values had similar for Flap and Winglet, 8.86% (36) and 4.35% (15), respectively. Purely spoiler application did not show notable DR (2.02% [79] and 3.10% [19]). Difference between the upward (DR = 15.64% \(\pm\) 5.68%; Count = 45.17 \(\pm\) 25.87 [91; 96; 97; 99]) and downward (DR = 7.31% \(\pm\) 2.27%; Count = 47.33 \(\pm\) 14.64 [78]) facing flaps, the DR value was almost 50%, while in Count, it was less than 2, which leads to a conclusion that upward facing flaps are more