## 5 Conclusions  
In this study, an optimization study with the TIES method was conducted on a PAV from a conceptual design standpoint. By investigating an existing design similar to roadable PAVs in South Korea, target goals were specified. Based on a market analysis, target values for the following design variables were specified: (i) MTOW, (ii) wing span, (iii) wing root chord, (iv) W/S, (v) P/W, and (vi) fuel efficiency. A morphological matrix was employed to define the concept space with the conventional type of system design. For modeling and simulation, JMP software developed by SAS, Microsoft Excel,  
Figure 14: K-factor sensitivity analysis: deviation of design variables 1 for 10% decrease of the k factor.  
Figure 15: K-factor sensitivity analysis: deviation of design variables 2 for 10% increase of the k factor.  
and a PAV sizing tool developed for this study were utilized. To explore the design space, both a screening test and a Pareto front analysis were conducted to determine the design variables that had the greatest influence on the design. As a result, seven design variables were finally chosen, specifically the range, maximum speed, cruise speed, cruise altitude, passengers, takeoff ground roll, and stall speed. A CCD was constructed to sample experimental points with the selected design variables. RSE values were then generated using the sample points. To evaluate the accuracy of the generated RSEs, the coefficient of determination was calculated and evaluated. Consequently, it was found that the metric values are close to 1. Using the generated RSEs, an MCS was performed to propagate the metrics of interest and to explore the design space within the provided design ranges. Based on the results from the MCS, it was observed that a probability of meeting the target value for the MTOW is 26.7%. Similarly, the wing span value was 100%, the wing root chord value was 2.5%, the W/S ratio was 50%, and the P/W ratio was 50%. Moreover, the design range for fuel efficiency was estimated to be from 0.061 hp/lb to 0.089 hp/lb; therefore, it was confirmed that all design variables could be used for the optimization process. The optimized design variables were then acquired using JMP\({}^{\prime}\)s desirability function. However, it was found that the wing root chord design variable could not reach the target value, as expected.  
In the technology identification and evaluation steps, several applicable technologies having significant impacts on the design were explored to determine if the technologies allow the design variables to meet the target values by infusing suitable technologies. Finally, eight technologies were chosen for the wing root chord design variable. In addition, a k-factor sensitivity analysis was performed to assess the technologies quantitatively. As a result, it was observed that the factors of flow circulation flap, leading edge blowing, nanocoating, liquid metal, and advanced composite material had the greatest influence on the target values. Furthermore, the variations in the target values were analyzed as the k factors changed.  
[PERSON] was responsible for all tasks related to the work, from conceptualization, establishing the methodology, to data analysis entirely; [PERSON] was responsible for the writing of the original manuscript; [PERSON] managed the overall project and reviewed it.  
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2019R1F1A1042533).  
The authors declare no conflict of interest.