A Modeling Framework to Estimate Airport Runway Capacity. in the National Airspace System. Yueh-Ting Chen. Master of Science

Please download to get full document.

View again

of 36
All materials on our website are shared by users. If you have any questions about copyright issues, please report us to resolve them. We are always happy to assist you.
Information Report
Category:

Advertisement

Published:

Views: 0 | Pages: 36

Extension: PDF | Download: 0

Share
Related documents
Description
A Modeling Framework to Estimate Airport Runway Capacity in the National Airspace System Yueh-Ting Chen Thesis submitted to the faculty of the Virginia Polytechnic Institute and State University in partial
Transcript
A Modeling Framework to Estimate Airport Runway Capacity in the National Airspace System Yueh-Ting Chen Thesis submitted to the faculty of the Virginia Polytechnic Institute and State University in partial fulfillment of the requirements for the degree of Master of Science In Civil and Environmental Engineering Committee Members: Dr. Antonio Trani Dr. Hojong Baik Dr. Hesham Rakha December 12, 2006 Blacksburg, VA Keywords: airport runway capacity, Airfield Capacity Model Copyright 2006, Yueh-Ting Chen A Modeling Framework to Estimate Airport Runway Capacity in the National Airspace System Yueh-Ting Chen Abstract The objective of this study is to estimate the airport capacity in the National Airspace System (NAS). Previous studies have focused on the airport capacity of large commercial airports. This research study estimates the runway capacity for more than two thousand airports in the NAS in order to understand future tradeoffs between air transportation demand and supply. The study presented in this report includes capacity estimates for general aviation and commercial airports. To estimate airport runway capacity, the Federal Aviation Administration (FAA) Airfield Capacity Model (ACM) is used to assess the capacity at all candidate airports in a target airport set. This set includes all airports with potential Very Light Jet (VLJ) operations. The result of the study provides a broad view about the airport capacity in the future air transportation system, and could help decision makers with a modeling framework to identify congestion patterns in the system. Moreover, airport capacity is an important limiting factor in the growth of air transportation demand. The main motivation in our analyis is to include airport capacity constraints in forecasts of air transportation demand. The framework described in this report has been integrated into the Transportation Systems Analysis Model (TSAM). TSAM is a comprehensive intercity and multimode transportation planning tool to predict future air transportation demand. Acknowledgements I would like to thank Dr.Trani for the opportunity to work with him in the Air Transportation Systems Laboratory. His wisdom and patience guide me throughout this study, and the past two years are definitely one of the most invaluable learning experiences that I have ever had. I would also like to thank Dr.Baik, Dr.Rakha, Mr.Swingle and Nick for all of their advices and help throughout this research project, especially the great work of TSAM integration by Nick. Besides, I am really glad to have Senanu, Anand, Sohn, Jeff, Yue, and Nola as my colleagues. Fang-Yi, Chu-Yun, Chih- Yang, and Wen-Chun, I would like to thank all your encouragements. Last but not least, I have to thank the support from my parents and brother throughout my study in the Virginia Tech. Thank your all! Table of Contents Chapter 1 Introduction... 1 Section 1.1 Objectives... 2 Section 1.2 Scope of Study... 2 Section 1.3 Characteristics of Airport Capacity... 3 Section 1.4 Summary... 5 Chapter 2 Literature Review... 6 Section 2.1 Airport Capacity Analysis Methodologies... 6 Section 2.2 Review of Airport Capacity Models... 7 Section 2.3 Review of Other Airport Capacity Research Section 2.4 Summary Chapter 3 Methodology Section 3.1 Introduction Section 3.2 Methodology to Create Target Airport Set Section Overview and Scope of Target Airport Set Section Overview and Scope of FAA Airport Master Record Section Procedure to Create Target Airport Set Section 3.3 Methodology to Estimate Aircraft Mix Section Overview of Aircraft Mix Section Overview and Scope of Aircraft Mix Data Sources Section Overview and Scope of BTS T-100 Data Section Procedure to Calculate Commercial Operations Using BTS T-100 Air Carrier Statistics Section Overview and Scope of Based Aircraft Data Section Procedure to Estimate General Aviation Operations Using Based Aircraft Data Section Procedure to Calculate Aircraft Mix Section 3.4 Airfield Capacity Model Analysis Section Overview and Scope of ACM Section Assumptions about various ACM Parameters Section Procedure to Run ACM and Output Section Applying ACM to Other Airports in the Target Airport Set Section 3.5 Supplementary Runway Capacity Analysis Data Chapter 4 Results and Verification Section 4.1 Composition of the Target Airport Set Section 4.2 Operations and Aircraft Mix at the Target Airport Set Section 4.3 Airport Capacity Section 4.4 Application of Future Scenarios Section 4.5 Verification Chapter 5 Conclusion Section 5.1 Summary of Objectives Section 5.2 Summary of Results i Section 5.3 Recommendations and Future Research References Appendix A Acronyms Appendix B Runway Surface Types and Conditions Accepted Appendix C T-100 Segment Data Fields List and Description Appendix D Airfield Capacity Model Output File Example Appendix E-1 Matlab Program File for Single Runway Airport Appendix E-2 Matlab Program File for Multi-Runway Airport-Runway Classification Appendix E-3 Matlab Program File for Multi-Runway Airport-Parser Appendix E-4 Matlab Program File for Multi-Runway Airport-Result Collection Appendix E-5 Matlab Program File for Multi-Runway Airport-Result Comparison Appendix F List of the Target Airports Appendix G Aircraft Type and Weight Class List ii List of Figures Figure 1: Problem Situation... 9 Figure 2: Final Approach and Landing Processes; Arrival-Only Scenario; Vi Vj Figure 3: Final Approach and Landing Processes; Arrival-Only Scenario; Vi Vj Figure 4: Final Approach and Landing Processes, Mix Operation Scenario Figure 5: Flowchart of the Airport Runway Capacity Study Figure 6: Screen Capture of FAA Airport Master Record Used in the Study Figure 7: Database Structure for Filtering BTS T-100 Data Figure 8: Screen Capture of the FAA Aircraft Characteristics Database Figure 9: Flowchart of Calculating Commercial Operation at Target Airports Figure 10: Flowchart to Estimate the Number of General Aviation Operation Figure 11: Flowchart of Calculating Aircraft Mix Figure 12: Layout of ACM Runway Configuration Models Figure 13: Sample Departure-Arrival Capacity Diagram (e.g., pareto frontier) Figure 14: Map of the Target Airport Set Figure 15: Airport Composition by Operation Type Figure 16: Airport Composition by Number of Runways Figure 17: Airport Composition by Availability of Air Traffic Control Tower Figure 18: Aerial Photo of Chadron Municipal Airport Figure 19: Screen Capture of TSAM Runway Capacity Display Information Figure 20: Maximum Runway Capacity under Upper-Boundary Operational Strategy at Towered Airports Figure 21: Maximum Runway Capacity under Upper-Boundary Operational Strategy at Non- Towered Airports Figure 22: Maximum Runway Capacity under Lower-Boundary Operational Strategy at Towered Airports Figure 23: Maximum Runway Capacity under Lower-Boundary Operational Strategy at Non- Towered Airports Figure 24: Maximum Runway Capacity Comparison between Upper and Lower Boundary Operational Strategies for VMC Condition at Towered Airports Figure 25: Maximum Runway Capacity Comparison between Upper and Lower Boundary Operational Strategies for VMC Condition at Non-Towered Airports Figure 26: Maximum Runway Capacity Comparison between Upper and Lower Boundary Operational Strategies for MMC Condition at Towered Airports Figure 27: Maximum Runway Capacity Comparison between Upper and Lower Boundary Operational Strategies for MMC Condition at Non-Towered Airports Figure 28: Maximum Runway Capacity Comparison between Upper and Lower Boundary Operational Strategies for IMC Condition at Towered Airports Figure 29: Maximum Runway Capacity Comparison between Upper and Lower Boundary Operational Strategies for IMC Condition at Non-Towered Airports Figure 30: VMC Airport Capacity under Upper-boundary Strategy Figure 31: VMC Airport Capacity under Lower-boundary Strategy Figure 32: MMC Airport Capacity under Upper-boundary Strategy Figure 33: MMC Airport Capacity under Lower-boundary Strategy iii Figure 34: IMC Airport Capacity under Upper-boundary Strategy Figure 35: IMC Airport Capacity under Lower-boundary Strategy Figure 36: Aerial Photo of San Diego International-Lindbergh Field Airport Figure 37: Aerial Photo of New York La Guardia Airport Figure 38: Aerial Photo of Los Angeles International Airport Figure 39: Aerial Photo of Phoenix Sky Harbor International Airport Figure 40: Aerial Photo of Atlanta Hartsfield-Jackson International Airport iv List of Tables Table 1: Factors Influencing Airport Capacity Table 2: Runway Capacity Influencing Factors... 4 Table 3: Comparison of Analytic and Simulation Models Table 4: Description of Aircraft Weight Classes Table 5: Comparison of Aviation Industry Databases for Aircraft Mix Calculation Table 6: General Aviation Aircraft Activity and Utilization Table 7: List of the ACM Runway Configuration Models Table 8: VFR Departure-Departure Separations for Tower and Non-Towered Airports Table 9: IFR Departure-Departure Separations for Tower and Non-Towered Airports Table 10: VFR Arrival-Arrival Separations for Tower and Non-Towered Airports Table 11: IFR Arrival-Arrival Separations for Tower and Non-Towered Airports Table 12: Runway Capacity Results for CDR under VMC Condition Table 13: Runway Capacity Results for CDR under MMC Condition Table 14: Runway Capacity Results for CDR under IMC Condition Table 15: Comparison of Runway Capacity of Edward F Knapp State Airport under Current Operation Rules and a Future Scenario Table 16: Comparison of Runway Capacities at SAN between Different Data Sources Table 17: Comparison of Runway Capacities at LGA between Different Data Sources Table 18: Comparison of Runway Capacities at LAX between Different Data Sources Table 19: Comparison of Runway Capacities at PHX between Different Data Sources Table 20: Comparison of Runway Capacities at ATL between Different Data Sources v CHAPTER 1 INTRODUCTION The air transportation system has been an important mode of transportation for medium and long haul trips. According to the Federal Aviation Administration (FAA) Aerospace Forecast [FAA, 2006], U.S. and foreign flag carriers carry million passengers between the U.S. and the rest of the world. The total number of enplanements of U.S. commercial air carriers for fiscal year 2005 was million, a 6% increase compared to the previous year. In addition to commercial flights, general aviation plays an important role in the National Airspace System (NAS). The FAA Aerospace Forecast indicates that non-commercial aircraft activity at FAA and contract towers reached 37 million instrument flight operations in Of these 26.1 million were commercial flights. This implies that 10.9 million operations in the NAS are attributed to general aviation activity. The economic influence of the air transportation system is substantial. The report entitled The Economic & Social Benefits of Air Transport [Air Transport Action Group, 2005] indicates that the air transport industry in North America contributes nearly US$ 410 billion to the gross domestic product (GDP). In the future it is important to maintain an efficient and congestion-free air transportation system. Congestion, which affects the efficiency of the air transport network, is always one of the most critical issues in the development of any air transportion system. The problem that air operations cannot depart/arrive on-time not only disrupts the travel experience of passengers, but also disrupts the airlines operating efficiency and thus affects the national economy. Review of year 2000 data shows that 27 percent of the scheduled flights in the U.S. were delayed more than fifteen minutes or canceled [U.S. Senate, 2001]. To help develop a better, more efficient air transportation system, it is important to understand the capacity constraints of the system. This research effort attempts to predict the airport runway capacity of many airports comprising the NAS. Although there have been several studies addressing the capacity of large commercial airports, there have been few efforts to study the capacity of large numbers of airports in the NAS. With this study and demand forecast models, aviation planners and the Federal Government could identify airport capacity shortcomings in the current system and evaluate possible approaches to improve the 1 air transportion system in the future. This research effort supports the development of the Next Generation Air Transportation System (NGATS) currently under study by National Aeronautics and Space Administration (NASA) and the FAA. Section 1.1 Objectives The objectives of this study are: a) To estimate airport runway capacity for a large number of airports in the NAS. These airports will be candidates to receive very light jet aircraft (VLJ) operations in the future. b) To identify future airport capacity shortcomings as the demand for air transportation increases in the future. Section 1.2 Scope of Study Previous capacity studies have been mostly limited to Large Hub commercial airports. According to the definition in the United States Code, Title 49, Chapter 471 [49 U.S.C. Chapter 471, 2006], a large hub airport is defined as an airport carrying one percent or more of all annual passenger boardings in the NAS. Our study includes all public airports in the continental U.S. capable of handling VLJ traffic in the future. The analysis includes the operational characteristics, geographical specifications, and related capacity of public airports with an effective runway length greater or equal to 915 meters (3,000 feet). The emergence of Very Light Jets (VLJ) is one of the most important challenges in the future of NAS operations. The National Business Aviation Association defines a VLJ as a jet aircraft weighing 10,000 pounds or less maximum certificated takeoff weight and certificated for single pilot operations [NBAA, 2005]. The Virginia Tech Air Transportation Systems Laboratory (ATSL), NASA Langley Research Center and Swales Aerospace have conducted a series of studies to estimate the demand and impact of VLJ traffic in the United States. At the centerpiece of this analysis is the Transportation Systems Analysis Model (TSAM). TSAM is a large-scale, multimode intercity demand generation model [A.A. Trani et al., 2003]. These studies indicate that up to 4,100 VLJ aircraft could be flying in the NAS by 2017 [A.A. Trani et al., 2006]. Although the first VLJ in operation is expected in early 2 2007, it will take several years for the market to develop. Some media reports have stated possible congestion brought by VLJ to already congested airports and airspace [The Wall Street Journal, 2006]. One obvious research question is whether or not the airports in the NAS will have the capacity to handle these emerging flights. To fill in the gap of previous studies and to help decision makers to understand the nationwide impacts of future air transportation demand, this research effort would assess airport capacity for thousands of airports that, in general, are ignored in NAS-wide studies. Section 1.3 Characteristics of Airport Capacity Airport capacity is the number of operations, either takeoffs or landings that can be performed in a unit of time, usually an hour, without violating aircraft safety regulations. If an airport cannot meet the demand function with its existing capacity, a degradation in the perceived level of service (as viewed by airlines and passengers) develops. This results in either a permanent adjustment to the schedule or flight delays. Airport capacity can be discussed from two viewpoints: airside capacity and landside capacity. The airside capacity includes components like the runway, taxiway system, and adjacent airspace to the airport. Landside capacity includes the terminal, gate, and access roads. Table 1 lists the factors that influence airport capacity. Table 1: Factors Influencing Airport Capacity. Factor Air Traffic Control Runway System Taxiway System Apron/Gate Facilities Terminal Facilities Ground Transportation System Description Navigation aids, air traffic control rules and procedures Layout and number of runways Configuration of taxiways Capability to accommodate aircraft in apron/gate area Landside facilities that passenger move through from curb to the loading bridge, like passenger waiting area, ticket counters, security screening points, customs and immigration etc. Landside access system for travelers such as access roads, parking facilities, and public transit. 3 Operating Restrictions Meteorological Conditions Regulations and rules to prevent the airport from operating at full capacity; such as curfews, special departure/arrival procedures, activities in the adjacent airspace Winds, visibility, ceiling, and precipitation [A.T. Wells, 2000] Traditionally, the runway system is one of the most critical components driving airport capacity. This is the focus of this research. Factors influencing airport runway capacity are listed in Table 2. Table 2: Runway Capacity Influencing Factors. Factor Number of Runways and Configuration Runway Operating Strategy Runway Occupancy Time (ROT) Aircraft Mix and Operating Sequence Common Approach Path Length Weather Separation Requirements Approach Speed Air Traffic Control Related Description The layout and number of runway(s) The way runways are used. For example, runway for arrival only/departure only or mix operations The time an aircraft occupies the runway. For arrivals it starts when aircraft passes runway threshold and ends when aircraft exit the runway. For departure it starts when aircraft enters the runway and ends when the aircraft passes the departure end of the runway The percentage of operations among all aircraft weight classes and their arrival/departure sequence The distance aircraft fly in-trail during the approach stage Visibility and ceiling The required minimum distance/time between leading and trailing aircraft The speed when aircraft passes through arrival end of runway Availability of tower, radar coverage This analysis employs data available from various aviation databases to: 4 a) identify aircraft operating at each airport, and b) to derive existing operational conditions at each airport. A detailed process and methodology to estimate runway capacity is described in Chapter 3 of this report. Section 1.4 Summary Airport runway capacity estimation procedures have been developed for major commercial airports. Whereas some of these procedures can be used at towered airports, there are thousands of airports where such procedures do not provide realistic runway saturation capacity estimates. To address this problem, this study integrates several aviation databases and basic runway capacity estimation methods to estimate the capacity for a large number of airports in the NAS. The results could provide Federal State and local authorities with a powerful tool to allocate and optimize limited funding resources throughout the NAS. This in turn will benefit air transportation system users. Morevover, knowledge of airport capacity is a requirement to understand the balance between air transportaton demand and supply in the future NAS. 5 CHAPTER 2 LITERATURE REVIEW This chapter reviews previous studies on the subject of airport capacity analysis. The review of the existing literature helps us to understand various perspectives and approaches to estimate airport runway capacity. The chapter discusses various methodologies to estimate airport runway capacity analysis, including the merits and drawbacks of each method. This review process can help define the scope and focus of this research. The last section of the chapter concentrates on past studies on the subject matter with emphasis on runway capacityrelated factors. Section 2.1 Airport Capacity Analysis Methodologies There are two broad categories of airport capacity estimation models: a) analytic models, and b) simulation-based models Analytic models consist of a series of close-form equations that compute
Recommended
View more...
We Need Your Support
Thank you for visiting our website and your interest in our free products and services. We are nonprofit website to share and download documents. To the running of this website, we need your help to support us.

Thanks to everyone for your continued support.

No, Thanks