The COVID-19 pandemic has caused significant disruptions in global air travel demand, presenting new challenges for accurately forecasting passenger volumes. This study analyzes the monthly air passenger demand data from 2010 to 2022 to identify key external factors that influence passenger demand. Our analysis shows that the number of international visitors to Singapore is a critical determinant of passenger demand. Consequently, we propose a SARIMAX (Seasonal AutoRegressive Integrated Moving Average with eXogenous variables) model to forecast monthly air passenger demand at Singapore's Changi Airport, integrating international visitor numbers as an exogenous variable. Through comprehensive model identification and parameter estimation, we select the best SARIMAX configuration. To validate the performance of the model, traditional time series methods such as SARIMA, various exponential smoothing methods, and advanced machine learning methods like LSTM (Long Short-Term Memory) and Prophet were compared for forecasting monthly air passenger demand at Changi Airport in 2023. The results show that the SARIMAX model significantly outperforms all other tested models, achieving the best performance across multiple forecasting metrics, including the Mean Absolute Percentage Error.

This study analyzes the feasibility of operating the E190-E2 aircraft at Ulleung Airport, which has a runway length of 1,200 meters. Using aircraft manufacturer data and PACE LAB under EASA standards, takeoff and landing performance were evaluated under various environmental conditions. Results indicate that with round-trip fuel tankering, the aircraft can carry up to 106 passengers at departure and 89 at arrival under wet runway conditions. If refueling is available at Ulleung Airport, the payload capacity can increase by approximately 10 passengers. A flight test conducted at Pohang Airport supported these findings. The study suggests that minor infrastructure improvements, such as refueling facilities and limited runway extension, would make E190-E2 operations at Ulleung Airport technically feasible.

Baengnyeong Airport is under review for construction to improve transportation accessibility in island regions and has passed the preliminary feasibility study. While airport development significantly enhances transportation convenience for residents, it may also cause aircraft noise issues and lead to conflicts within local communities. Previous studies estimated noise impacts based on ATR-42 and Q300 aircraft. However, this study focuses on a more realistic assessment using ATR-72 and E190-E2 aircraft. By utilizing the FAA’s Aviation Environmental Design Tool (AEDT), a projected noise contour map for Baengnyeong Airport was developed. The analysis shows that considering ATR-72 and E190-E2, which generate higher noise levels, provides a more practical evaluation of noise-affected areas. The results indicate that the noise impact is mostly confined within the runway area; however, potential noise complaints may arise from Baengnyeong Island and nearby regions. Based on these findings, this study suggests the need for optimized flight procedures and urban planning measures to mitigate aircraft noise issues.

Ulsan Airport cannot operate precision instrument approach procedures from the south direction (Runway 18) due to obstacles. Even non-precision instrument approach procedures have higher approach angles and minimum descent altitudes (MDA) compared to other airports, which can pose safety risks for pilots following the flight procedures. Recently, since the introduction of SBAS-based satellite navigation flight procedures in Korea, Ulsan Airport is expected to experience improvements, including reduced offsets and lower minimum descent altitudes in its existing flight procedures. During the design process of new flight procedure routes, a comprehensive analysis of noise differences from existing routes and the noise impact on new areas is necessary. Therefore, this study aims to present the changes in aircraft noise resulting from the implementation of new flight procedures using the Aviation Environmental Design Tool (AEDT)

본 연구는 한국 기상대 데이터를 활용하여 콘크리트 포장의 깊이별 온도를 예측하는 ANN(Artificial Neural Network) 모델을 개발하는 것을 목표로 한다. 기존의 열평형 방정식 기반 모델은 특정 지역의 기상 데이터를 필요로 하기 때문에 일반적인 적용이 어렵다는 한계를 가지고 있다. 이에 본 연구에서는 ANN을 활용하여 기상대 데이터를 기반으로 범용적 인 온도 예측 모델을 개발하고자 한다. 이를 통해 다양한 지역 및 환경 조건에서도 적용 가능한 모델을 구축하는 것이 목적이다. 본 연구에서는 2017년 1월 1일부터 2018년 12월 31일까지의 1시간 단위 기상 및 온도 데이터를 활용하며, 0.05m, 0.15m, 0.25m, 0.35m, 0.45m 깊이별 온도 데이터를 학습 데이터로 사용한다. 입력 변수로는 기온, 풍속, 강수량, 습도, 일 조량, 일사량, 적설량, 적운량, 지면온도를 포함한다. 이러한 다양한 기상 데이터를 활용하여 신경망 모델을 학습하고, 기 존 방식보다 높은 정확도를 확보하는 것이 연구의 핵심 목표이다. 기존 ANN 구조인 O = WI + B에서 확장된 O = W(I + (WI + B)) + B 형태의 비선형 구조를 적용하여 기존 모델이 가지는 비선형 관계 반영의 한계를 극복하고자 한다. 또한, 선형 다중 은닉층 모델과 비선형 다중 은닉층 모델을 각각 개발하여 성능을 비교하고, 비선형 모델의 필요성과 일반화 능력을 평가할 예정이다. 최종적으로 두 모델의 성능을 평균 제곱 오차 및 평균 절대 오차 등과 같은 평가 지표들을 이용하여 비교 분석하고, 가장 적합한 모델을 도출하고자 한다.

Noise is a sound that humans do not want. In this study, noise is measured for C172, the most frequently used general aviation trainer in Korea and abroad. In addition, in this study, noise measurement points are selected for Muan Airport, where most of the domestic training aircraft fly under the supervision of the Ministry of Land, Infrastructure and Transport. Based on this, the measured data is scaled and analyzed. In addition, we intend to analyze what characteristics C172 aircraft have unique through frequency analysis of noise of C172. Through this, it is intended to understand what type of noise training aircraft affect in future studies.

본 연구는 중국의 11개 4F급 공항을 대상으로 변이할당분석을 통해 공항의 경쟁 력을 비교한다. 분석기간은 2001년-2021년으로 설정하고 2001년-2007년, 2008년-201 8년 그리고 2019년-2021년 세 구간을 설정하고 있다. 변이효과를 권역별로 보면 화 북지역의 공항 경쟁력은 감소하고 있으며, 화동지역, 화남지역과 화중지역의 공항 경 쟁력은 모두 상승하고 있다. 반대로 서북지역과 서남지역은 공항 경쟁력이 감소하고 있다. 할당효과를 보면 북경수도국제공항과 상해포동국제공항, 광주백운국제공항, 그 리고 심천보안국제공항의 할당효과가 가장 크다. 그리고 권역별로 절대적 성장치와 할당효과의 분석결과를 종합해 보면 화동지역, 화남지역 그리고 화중지역의 공항 경 쟁력이 상대적으로 높으며, 화북지역과 서북지역 그리고 서남지역의 공항 경쟁력은 상대적으로 낮다고 해석할 수 있다.

PURPOSES : In this study, a method to use magnesium phosphate ceramic (MPC) concrete for the surface maintenance of airport pavements with jointed concrete is developed. METHODS : To investigate the application of a material incorporated with MPC for the surface maintenance of airport pavements with jointed concrete, structures with various cross-sections and thicknesses were constructed. The cross-section of the structure was modeled for the surface maintenance of four types of pavements and typical pavement construction processes, such as cutting, cleaning, production and casting, finishing, hardening, and joint reinstallation. Subsequently, the hours required for each process was determined. RESULTS : The MPC concrete used for the surface maintenance of airport pavements with jointed concrete demonstrate excellent performance. The MPC concrete indicates a compressive strength exceeding 25 MPa for 2 h, and its hydration heat is 52.9 ℃~61.2 ℃. Meanwhile, the crushing and cleaning performed during the production and casting of the MPC require a significant amount of time. Specifically, for a partial repair process, a total of 6 h is sufficient under traffic control, although this duration is inadequate for a complete repair process. CONCLUSIONS : MPC concrete is advantageous for the surface maintenance of airport pavements with jointed concrete. In fact, MPC concrete can be sufficiently constructed using existing concrete maintenance equipment, and partial repair works spanning a cross-sectional area of 11 m2 can be completed in 1 d. In addition, if the crushing and cleaning are performed separately from production and construction, then repair work using MPC concrete can be performed at a larger scale.

PURPOSES : In this study, drone highway route alternatives were evaluated using the analytic hierarchy process (AHP) technique to investigate any difficulties or improvements while designing drone highway routes. METHODS : Based on the literature review and AHP analysis, 39 road and airport experts were surveyed to evaluate two alternate drone highway routes that connect the Seoul train station and Jamsil park near Gangnam business district. RESULTS : The AHP analysis results revealed that the environmental aspect was the most critical factor in designing a drone highway route, followed by social and technological factors. Among the investigated factors, noise and life-environment showed the highest geometric mean value of 0.21. This mean should be considered when developing plans and policies for drone highway design. CONCLUSIONS : Environmental and social agreement is more crucial than the technological and economic aspects when designing drone highway routes. Laws and policies should be updated and followed to support the drone highway system, which is vital in logistics.