Analisis Kapasitas Landasan Pacu Sultan Hasanuddin International Airport

Bandar Udara Internasional Sultan Hasanuddin Makassar yang lebih dikenal dengan SHIAM memiliki status sebagai bandara transit utama khususnya untuk penerbangan kawasan Indonesia Timur. Hal tersebut menyebabkan permintaan akan penggunaan pesawat meningkat, terlebih jika memasuki jam-jam puncak atau pada saat masa liburan, jika jumlah pesawat yang beroperasi disuatu bandar udara melebihi kapasitas akan menyebabkan overload pada sistem Air Traffic Management (ATM) yang membuat kualitas pelayanan yang diberikan akan menurun, misalnya terjadi penundaan pelaksanaan operasi penerbangan.Tujuan penelitian untuk mengetahui kapasitas landasan pacu untuk Pesawat Boeing 737-900.ER, mengetahui kapasitas landasan pacu untuk Pesawat Boeing 737-800, dan mengetahui kapasitas landasan pacu untuk Pesawat Airbus A320. Hasil penelitian bahwa Pesawat rencana Boeing 737-900.ER memenuhi panjang runway, pesawat rencana Boeing 737-800 memenuhi panjang runway, dan Runway saat ini masih memenuhi untuk penggunaan pesawat Airbus A320.

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Combined Winds and Turbulence Prediction System for Automated Air-Traffic Management Applications

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-14-0216.1 ◽

2015 ◽

Vol 54 (4) ◽

pp. 766-784 ◽

Cited By ~ 25

Author(s):

Jung-Hoon Kim ◽

William N. Chan ◽

Banavar Sridhar ◽

Robert D. Sharman

Keyword(s):

Los Angeles ◽

Traffic Management ◽

Route Planning ◽

Air Traffic Management ◽

Energy Dissipation Rate ◽

Air Traffic ◽

Weather Patterns ◽

International Airport ◽

Time Lagged ◽

Scale Turbulence

AbstractA time-lagged ensemble of energy dissipation rate (EDR)-scale turbulence metrics is evaluated against in situ EDR observations from commercial aircraft over the contiguous United States and applied to air-traffic management (ATM) route planning. This method uses the Graphic Turbulence Guidance forecast methodology with three modifications. First, it uses the convection-permitting-scale (Δx = 3 km) Advanced Research version of the Weather Research and Forecasting Model (ARW) to capture cloud-resolving-scale weather phenomena. Second, turbulence metrics are computed for multiple ARW forecasts that are combined at the same forecast valid time, resulting in a time-lagged ensemble of multiple turbulence metrics. Third, probabilistic turbulence forecasts are provided on the basis of the ensemble results, which are applied to the ATM route planning. Results show that the ARW forecasts match well with observed weather patterns and the overall performance skill of the ensemble turbulence forecast when compared with the observed data is superior to any single turbulence metric. An example wind-optimal route (WOR) is computed using areas experiencing ≥10% probability of encountering severe-or-greater turbulence. Using these turbulence data, lateral turbulence avoidance routes starting from three different waypoints along the WOR from Los Angeles International Airport to John F. Kennedy International Airport are calculated. The examples illustrate the trade-off between flight time/fuel used and turbulence avoidance maneuvers.

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Safety Culture and Safety-Relevant Behavior in Air Traffic Management

Aviation Psychology and Applied Human Factors ◽

10.1027/2192-0923/a000068 ◽

2015 ◽

Vol 5 (1) ◽

pp. 3-17 ◽

Cited By ~ 5

Author(s):

Michaela Schwarz ◽

K. Wolfgang Kallus

Keyword(s):

Safety Culture ◽

Traffic Management ◽

Service Providers ◽

Five Factor Model ◽

Principal Component ◽

Air Traffic Management ◽

Air Traffic ◽

Psychometric Validation ◽

Safety Attitudes ◽

Culture Development

Since 2010, air navigation service providers have been mandated to implement a positive and proactive safety culture based on shared beliefs, assumptions, and values regarding safety. This mandate raised the need to develop and validate a concept and tools to assess the level of safety culture in organizations. An initial set of 40 safety culture questions based on eight themes underwent psychometric validation. Principal component analysis was applied to data from 282 air traffic management staff, producing a five-factor model of informed culture, reporting and learning culture, just culture, and flexible culture, as well as management’s safety attitudes. This five-factor solution was validated across two different occupational groups and assessment dates (construct validity). Criterion validity was partly achieved by predicting safety-relevant behavior on the job through three out of five safety culture scores. Results indicated a nonlinear relationship with safety culture scales. Overall the proposed concept proved reliable and valid with respect to safety culture development, providing a robust foundation for managers, safety experts, and operational and safety researchers to measure and further improve the level of safety culture within the air traffic management context.

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