AIRCRAFT MODULATION ANALYSIS USING PARTICLE SWARM OPTIMIZATION METHODE FOR RUNWAY PAVEMENT THICKNESS DESIGN CASE STUDY: JENDERAL AHMAD YANI AIRPORT. - Imawan, Januar
This study aims to analyze runway thickness planning using Particle Swarm Optimization (PSO) as a method to develop an optimal runway pavement thickness design, the design must be in accordance with the operational needs of the planned aircraft on the planned year. The research utilizes secondary data, including annual airport passenger statistics, soil CBR data, planned aircraft data, and existing aircraft traffic data. The analysis of the planned aircraft modulation using PSO optimization obtained the maximum number of passengers that could be accommodated by a combination of aircraft of 0.042% more than the aircraft modulation using the aircraft traffic selection method. The next step involves comparing the pavement thickness results between the two modulation methods using the mechanistic approach through FAARFIELD software. Once the thickness for each method is determined, further analysis evaluates the pavement layer structure, focusing on the potential for fatigue failure. The results indicate that the runway pavement thickness using PSO modulation consist a 29,68 inch subbase, a 6,5 inch base course, and a 4 inch surface. Meanwhile runway pavement thickness using aircraft traffic selection modulation consist a 24,79 inch subbase, a 6.5 inch base course, and a 4 inch surface. The difference of pavement thickness is due to the aircraft modulation configuration. The methods that conclude more proportion of wide body aircraft in the combination will result a thicker runway pavement requirements.