Airport_capacity_intro

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Unformatted text preview: Analysis of Air Transportation Systems Airport Capacity - Introduction Dr. Antonio A. Trani Associate Professor of Civil and Environmental Engineering Virginia Polytechnic Institute and State University Blacksburg, Virginia March 2005 Virginia Tech 1 Methodologies to Assess Airport Capacity The capacity of an airport is a complex issue. Several elements of the airport facility have to be examined. Namely: a) Airside and b) Landside components. Runway Access Road Airside Gates Taxiways Terminal Landside Runway Virginia Tech 2 Airport and Airspace Components The following components of NAS need to be examined: a) Airside - Airspace - Runways - Taxiways b) Landside - Gates - Terminal - Access road Virginia Tech 3 Methodologies to Study Airport Capacity/ Delay • Analytic models - Easier and faster to execute - Good for preliminary airport/airspace planning (when demand function is uncertain) - Results are generally less accurate but appropriate • Simulation-based models - Require more work to execute - Good for detailed assessment of existing facilities - Results are more accurate and microscopic in nature Virginia Tech 4 Methodologies in Use to Study Capacity/ Delay • Analytic models - Time-space analysis - Queueing models (deterministic and stochastic) • Simulation-based models - Monte Carlo Simulation - Continuous simulation models - Discrete-event simulation models Virginia Tech 5 Time-Space Analysis • A solid and simple technique to assess runway and airspace capacity if the headway between aircraft is known • The basic idea is to estimate an expected headway, E(h), and then estimate capacity as the inverse of the expected headway 1 Capacity = ----------E(h) (1) E ( h ) is expressed in time units (e.g., seconds) Virginia Tech 6 Time-Space Analysis Nomenclature δ ij is the minimum separation matrix (nm) T ij is the headway between two successive aircraft (s) δ is the minimum arrival-departure separation (nm) ROT i is the runway occupancy time for aircraft i (s) σ 0 is the standard deviation of the in-trail delivery error (s) V i is the speed of aircraft i (lead aircraft) in knots Virginia Tech 7 Time-Space Analysis Nomenclature V j is the trailing aircraft speed (knots) γ is the common approach length (nm) B ij is the buffer times matrix between successive aircraft (s) q v is the value of the cumulative standard normal at probability of violation p v p v is the probability of violation of the minimum separation criteria between two aircraft Virginia Tech 8 Final Approach and Landing Processes Space Runway ROTi TDi ROTj Tj Ti V i γ Time V j Entry Gate Virginia Tech 9 Possible Outcomes of a Single Runway TimeSpace Diagram Since aircraft approaching a runway arrive in a random pattern we distinguish between two possible scenarios: • Opening Case - Instance when the approach speed of lead aircraft is higher than trailing aircraft ( V i > V j ) • Closing case - Instance when the approach of the lead aircraft is less than that of the trailing aircraft ( V i ≤ V j ) Virginia Tech 10 Opening Case Diagram (Arrivals Only) Space ROTi ROTj Ti Runway Tj V j V i γ 1 1 Time V >V i j δij Entry Gate Virginia Tech 11 Opening Case (Equations) Error free headway, T ij = T j – T i , (no pilot and ATC controller error) assuming control is exercised as the lead aircraft passes the entry gate, 11 δ ij --- – --- T ij = --- + γ - V j V i Vj (2) Position error buffer time (with pilot and ATC controller error) 11 --- – --- B ij = σ o q v – δ ij - V j V i or zero if B ij < 0. Virginia Tech (3) 12 Understanding Position Errors Distribution of Aircraft Position No Buffer 50% 50% δij Real Aircraft Position Runway Distribution of Aircraft Position With Buffer 5% σοqvVj δij Virginia Tech Runway 13 Closing Case Diagram (Arrivals Only) Space ROTi ROTj Ti Runway Tj V i γ Time δij 1 V <V i j V j 1 Entry Gate Virginia Tech 14 Closing Case (Equations) Error free headway, T ij = T j – T i (no pilot and ATC controller error) with the minimum separation enforced when the lead aircraft passes the runway threshold, δ T ij = ---ij Vj (4) Position error buffer time (with pilot and ATC controller error) is, B ij = σ o q v (5) Virginia Tech 15 Mixed Operations Diagram Space Runway TDk ROTi Ti T1 ROTj T2 Tj Time δ V i γ G V j T1 = Ti + RΟΤι T2 = T j - δ / V j Gap (G) exist if T2 - T1 > 0 Entry Gate TDi is the departure runway occupancy time E[Tij + Bij] = E[δ / Vj] + E[ROTi] + (n-1) E(TDk) + Ε(τ) Virginia Tech 16 Mixed Operations Notes • The arriving aircraft leave natural gaps in the time space diagram • When gaps (G) are sufficiently long, ATC controllers can schedule one or more departures in the gap • The size of the gaps depends on: - Runway occupancy time (for lead aircraft) - Runway occupancy time for departing aircraft - Minimum departure-departure headway (seconds) - Minimum arrival-departure separation (δ) Virginia Tech 17 Mixed Operations Notes • In the U.S. the current minimum separation between arrivals and departures (δ) is 2 nautical miles Define: • T 1 as the time when the lead aircraft completes the landing roll (i.e., exits the runway plane) • T 2 as the time when the following arriving aircraft is (δ) from the runway threshold • The gap (G) is the time difference between T 2 and T 1 . G = T2 – T1 (6) Virginia Tech 18 Mixed Operations (Gap Analysis) Mathematically, T 1 = T i + ROT i (7) and δ T 2 = T j – --Vj (8) then δ G = T j – --- – ( T i + ROT i ) Vj Virginia Tech (9) 19 Mixed Operations (Gap Analysis) δ G = ( T j – T i ) – --- – ROT i Vj (10) Note that, ( T j – T i ) is the actual headway between the lead and following aircraft ( T ij + B ij ). This actual headway includes the buffer times since air traffic control will apply those buffers to each successive arrival pair. Our analysis now concentrates in finding suitable gaps between successive aircraft arrivals leaving. Virginia Tech 20 Gap Analysis Assume that we would like to find instances such that the gap is zero. This is the limiting case to schedule one departure between successive arrivals. δ 0 = ( T j – T i ) – --- – ROT i Vj (11) knowing δ 0 = ( T ij + B ij ) – --- – ROT i Vj Virginia Tech (12) 21 Gap Analysis δ ( T ij + B ij ) = --- + ROT i Vj (13) For n departures in gap k the expected value of T ij + B ij has to be longer than: δ ( T ij + B ij ) = --- + ROT i + ( n – 1 ) TD k Vj (14) where TD k is the runway occupancy time of departure k. This expression typically applies under VFR conditions because controllers can dispatch aircraft as Virginia Tech 22 soon as the previous departure clears the runway end (provided that the lead aircraft turns quickly away from runway heading). Under IMC conditions, the runway occupancy time for a departing aircraft TD k is smaller than the minimum headway allowed between departures. This happens because under IMC conditions aircraft are expected to follow a prescribed climb procedure and usually navigate to a departure fix before changing heading. Let ε ij be the minimum departure-departure headway applied by air traffic control. Equation (14) can then be modified to estimate the availability of a gap to release n departures. Virginia Tech 23 Gap Analysis δ ( T ij + B ij ) = --- + ROT i + ( n – 1 ) ε ij Vj (15) One final term usually added to this equation is a pilot reaction time term to account for a possible delay time (departing aircraft) to initiate the takeoff roll. This time is justified because jet engines used in transport aircraft take a few seconds to “spool up” and generate full thrust. Let τ be the time delay (in seconds) for the departing aircraft. Virginia Tech 24 Gap Analysis Adding the time delay term Equation (14) becomes, δ ( T ij + B ij ) = --- + ROT i + ( n – 1 ) ε ij + τ Vj (16) Since ( T ij + B ij ) is calculated as an expected value in the analysis for arrivals only, δ E ( T ij + B ij ) ≥ E --- + E ( ROT i ) + V j (17) ( n – 1 ) E ( ε ij ) + E ( τ ) Virginia Tech 25 Gap Analysis The use of Equation (17) allows us to estimate whether the natural gaps left by successive arrivals (expressed as the expected value of ( T ij + B ij ) ) is large enough to schedule n departures. The practical use of Equation (17) is to compare the actual headways between successive arrivals ( T ij + B ij ) against the sum of all four terms in the right hand side of Equation (17). We do this for various possible departure scenarios that include n departures (typically 1, 2, 3, ... 6 departures). Virginia Tech 26 Practical Values of Arrival-Arrival Separations (δij) Table 1. Typical In-trail Separations (nautical miles) Near Runways at Medium and Small Hub Airports (does not include buffers). Trailing Aircraft Lead Aircraft Heavy Large Small Heavy Large Small 4.00 3.00 3.00 5.00 3.00 3.00 6.00 5.00 3.00 NOTE: always consult with ATC specialist to verify the validity of these minimum separation distances. Virginia Tech 27 Practical Values of Arrival-Arrival Separations (δij) Table 2. Typical In-trail Separations (nautical miles) Near Runways at Large Hub Airports (does not include buffers). Trailing Aircraft Lead Aircraft Heavy Large Small Heavy Large Small 3.00 2.50 2.50 5.00 2.50 2.50 6.00 5.00 2.50 NOTE: always consult with ATC specialist to verify the validity of these minimum separation distances. Virginia Tech 28 Departure-Departure Aircraft Separations Table 3. Typical In-trail Departure Separations Near Runways in seconds. Trailing Aircraft LEAD ACFT. Heavy Large Small Heavy Large Small 120 90 60 120 60 60 120 60 60 NOTE: always consult with ATC specialist to verify the validity of these time. Virginia Tech 29 Example Problem (1) Determine the saturation capacity of an airport serving two groups of aircraft: a) heavy (30% of the population) and b) Small (70% of the population). Assume the common approach length γ to be 7 miles. The aircraft performance characteristics are given in the following table. Table 4. Aircraft Characteristics. Aircraft Group Runway Occupancy Time (seconds) Approach Speed (knots) Heavy 60 150 Small 40 100 Virginia Tech 30 Example Problem (1) Assume radar surveillance is available with 20 seconds for the standard deviation of in-trail delivery accuracy error and a probability of violation of 5%. The airport is a medium hub airport. The arrival-arrival separation matrix is shown in Table 1. The departuredeparture separation matrix is shown in Table 3. Virginia Tech 31 Determine Aircraft Mix and Probabilities The following is a probability matrix establishing the chance that an aircraft of type (i) follows aircraft of type (j). We assume random arrivals. Table 4. Probability Matrix (Pij). Aircraft (i) follows aircraft (j). Trailing Aircraft Lead Aircraft Heavy Small Heavy =(0.3) x (0.3) = 0.09 = (0.3) x (0.7) = 0.21 Small = (0.7) x (0.3) = 0.21 = (0.7) x (0.7) = 0.49 NOTE: verify that ∑P ij = 1.0 i, j Virginia Tech 32 Compute Headways Between Successive Arrivals Closing case: Lead = small, Following = heavy aircraft TS – H 3 δS – H = -------- = -------- = 0.02 hours VH 150 Usually is convenient to express headway in seconds. 3 δS – H T S – H = -------- = -------- 3600 = 72 seconds 150 VH Virginia Tech 33 Closing case (apply this case when speeds are equal): Lead = small, Following = small aircraft TS – S 3 δS – S -------- 3600 = 108 seconds = ------- = 100 VS Lead = heavy, Following = heavy aircraft TH – H 4 δH – H -------- 3600 = 96 seconds = -------- = 150 VH Virginia Tech 34 Opening case: Lead = heavy, Following = small aircraft TH – S 11 δH – S ---- – ---- seconds = -------- + γ V S V H VS 6 1 1 T H – S = -------- 3600 + 7 -------- – -------- 3600 = 300 100 100 150 seconds Virginia Tech 35 Arrival Aircraft Headway Table The following table summarizes the computed headways for all cases when an aircraft of type (i) follows aircraft of type (j). We assume random arrivals. Table 5. Error-Free headways (in seconds) when aircraft (i) follows aircraft (j). Trailing Aircraft Lead Aircraft Heavy Small Heavy 96 300 Small 72 108 Virginia Tech 36 Compute Expected Value of Headway The expected value of the headway is: E ( T ij ) = ∑P T ij ij for all i,j pairs i, j E ( T ij ) = P H – H × T H – H + P S – H × T S – H + P H – S × T H – S + PS – S × TS – S E ( T ij ) = 0.09 ( 96 ) + 0.21 ( 72 ) + 0.21 ( 300 ) + 0.49 ( 108 ) Virginia Tech 37 E ( T ij ) = 0.09 ( 96 ) + 0.21 ( 72 ) + 0.21 ( 300 ) + 0.49 ( 108 ) E ( T ij ) = 139.7 seconds Now compute the buffers between successive arrivals paying close attention to closing and opening equations. Virginia Tech 38 Compute Arrivals-Only Buffers Opening Case: BH – S 11 σ o q v – δ H – S ---- – ---- , 0 = min V S V H 1 1 B H – S = 1.65 ( 20 ) – 6 -------- – -------- 3600 100 150 B H – S = min ( – 39, 0 ) = 0 seconds Virginia Tech 39 Closing Case: B ij = σ o q v B S – S = B H – H = B S – H = σ o q v = 1.65 ( 20 ) = 33 seconds Virginia Tech 40 Arrivals Only Analysis The following table summarizes the computed headways (including the buffer times) for all cases when an aircraft of type (i) follows aircraft of type (j). We assume random arrivals. Table 6. Actual headways (in seconds) when aircraft (i) follows aircraft (j). Trailing Aircraft Lead Aircraft Heavy Small Heavy 96+33 = 129 300 + 0 = 300 Small 72+33 = 105 108+33 = 141 Virginia Tech 41 Expected Value of Headways (Including Buffer Times) The expected value of the actual headways E ( T ij + B ij ) is 165.8 seconds. The arrivals only capacity is, C arrivals 1 = ------------------------- vehicles per second E ( T ij + B ij ) Using more standard units of capacity (aircraft per hour), 3600 C arrivals = ------------------------- arrivals per hour E ( T ij + B ij ) Virginia Tech 42 Arrivals-Only Capacity For the single runway example the arrivals-only capacity is, 3600 C arrivals = ------------ = 21.8 aircraft arrivals per hour 165.8 NOTE: this value is a little low for a busy airport. At busy airports small aircraft are generally handled at a different runway if possible to improve the capacity of a runway operated by heavy aircraft. Virginia Tech 43 Analysis of Runway Gaps Gaps can be studied for all four possible instances studied so far. For example, if a heavy aircraft is followed by a small one, there is a headway of 300 seconds between two successive arrivals. This leaves a large gap that be exploited by air traffic controllers to handle a few departures on the same runway. δ --- + E ( ROT i ) + E ( T ij + B ij ) ≥ E V j ( n – 1 ) E ( ε ij ) + E ( τ ) Virginia Tech 44 Computation of Minimum Gaps E ( T ij + B ij ) ≥ 64.8 + 46 + ( n – 1 ) 78 + 10 seconds E ( T ij + B ij ) ≥ 64.8 + 46 + 10 + 78 n – 78 seconds E ( T ij + B ij ) ≥ 42.8 + 78 n seconds For n = 1 (one departure between arrivals) we need, E ( T ij + B ij ) n = 1 ≥ 120.8 seconds For n = 2 (two departures between arrivals) we need, E ( T ij + B ij ) n = 2 ≥ 198.8 seconds Virginia Tech 45 Computation of Minimum Gaps For n = 3 (three departures between arrivals) we need, E ( T ij + B ij ) n = 3 ≥ 276.8 seconds For n = 4 (four departures between arrivals) we need, E ( T ij + B ij ) n = 4 ≥ 354.8 seconds and so. We need to compare the values stated in Table 6 ( T ij + B ij ) against the gaps needed to schedule n departures per arrival gap instance. Virginia Tech 46 Gap Analysis The following table summarizes the number of departures possible when an aircraft of type (i) follows aircraft of type (j). We assume random arrivals. Table 7. Number of departures per arrival gap when aircraft (i) follows aircraft (j). Trailing Aircraft Lead Aircraft Heavy Small Heavy 1 3 Small 0 1 Virginia Tech 47 Interpretation of Table 7 One departure (on the average) can be scheduled between a heavy aircraft followed by another heavy aircraft. Note that a heavy - heavy arrival sequence implies an average of 129 seconds between successive arrivals. Since 121 seconds are needed to schedule a departure (expected value for all types of operations), we conclude that one departure can occur anytime two heavy aircraft follow each other. Other cells are computed in a similar fashion. Virginia Tech 48 Analysis of Arrival Gaps The final question that needs to be answered is: how many times each gap happens during the period of interest? From our analysis of arrivals only, we determined that on the average hour 21.8 arrivals could be processed at the runway. Since two successive arrivals are needed to form a gap, we can infer that an average of 20.8 gaps are present in one hour. The probability of each one of the four arrival instances is known and has been calculated in Table 4. Thus using Virginia Tech 49 these two pieces of information we estimate the number of times gaps will occur during one hour. Consider the instance of a heavy aircraft leading another heavy aircraft. Nine percent of the time this instance occurs at the airport. Thus for 20.8 gaps per hour this represents an equivalent number of hourly departures per arrival instance ( E D H – H ), ED H – H = TG ( P H – H ) ( DG H – H ) where: TG is the total number of gaps per hour, P H – H is the probability that a heavy aircraft follows another heavy, and DG H – H is the number of departures per gap for each instance (numbers in Table 7). Virginia Tech 50 ED H – H = 20.8 ( 0.09 ) ( 1 ) = 1.87 equivalent departures per hour Similarly, ED H – S = 20.8 ( 0.21 ) ( 3 ) = 13.10 ED S – H = 20.8 ( 0.21 ) ( 0 ) = 0 ED S – S = 20.8 ( 0.49 ) ( 1 ) = 10.19 equivalent departures per hour per instance Virginia Tech 51 Departures with Arrival Priority Table 8 summarizes the number of departures per hour per instance. Table 8. Equivalent departures per hour per arrival instance when aircraft (i) follows aircraft (j). Trailing Aircraft Lead Aircraft Heavy Small Heavy 1.87 13.10 Small 0.00 10.19 Total departures per hour = 25.2 departures per hour Virginia Tech 52 Recapitulation of Results so Far C arrivals 3600 = ------------ = 21.8 arrivals per hour 165.8 C departures = 25.2 departures per hour These results indicate that a single runway can process 21.8 arrivals per hour and during the same period process 25.2 departures per hour using the gaps formed by the arrivals. Total operations = 47 aircraft per hour Virginia Tech 53 Final Note If only departures are processed at this runway (no arrivals), the departures only capacity is the reciprocal of the departure headway (78 seconds), 3600 C dep – NA = ----------- = 46.2 departures per hour 78 Airport engineers use a capacity diagram illustrated in the figure to display all three hourly capacity results in a single diagram. These diagrams represent a Pareto frontier of arrivals and departures. The airport can be operated inside the Pareto boundary. Virginia Tech 54 Arrival-Departure Capacity Diagram B (25.2,21.8) Arrivals per Hour A (0,21.8) 20 10 C (46.2,0) 0 10 20 30 40 Departures per Hour Virginia Tech 55 Review of Runway Capacity Excel Program • The Excel template provided in class attempts to illustrate how the time-space diagram technique can be “programmed” in a standard spreadsheet • You can extend the analysis provided in the basic template to more complex airport configurations • The program, as it stands now, can only estimate the saturation capacity of a single runway. The program provides a simple graphical representation of the arrival -departure saturation diagram (sometimes called capacity Pareto frontier in the literature) • The following pages illustrate the use of the program using the values of the previous runway example. Virginia Tech 56 Excel Template Flowchart 1 Enter runway operation technical parameters - Arrival minimum separation matrix (δij) - Departure-departure separation matrix (εij) - Arrival-departure minimum separation (δ) - Common approach length (γ) - Runway occupancy times (ROTi) - Runway departure times (td) - Aircraft mix (Pi) - Standard deviation of intrail delivery error (so) - Probability of separation violations (Pv) 2 Compute Expected value of ROT times (E(ROT)) - E(ROTi) 3 Estimate the “Error-Free” separation matrix - Tij values using opening and closing cases Compute expected value of the error-free matrix E(Tij) 4 Estimate the “Buffer” separation matrix - Bij values using opening and closing cases Compute expected value of the buffer matrix E(Bij) Virginia Tech 57 Excel Template Flowchart (continuation) 5 Compute augmented separation matrix - Aij = Tij + Bij (error-free + buffer) 6 Compute the probability matrix (i follows j) - Pij 7 Compute expected value of Aij matrix - E(Aij) = E(Tij + Bij) Compute arrivals-only runway saturation capacity Carr 8 Compute expected value of departuredeparture matrix - E(εij) Compute departures-only runway saturation capacity Cdep 9 Compute gaps for n departures (n=1,2,...,5) - E(Gn) 10 Compute feasible departures per arrival gap (implemented as an Excel Macro) Virginia Tech 58 Excel Template Flowchart (continuation) 11 Compute number of departures per gap if arrivals have priority 12 Departure capacity with arrival priority Cdep-arr-priority Draw the arrival-departure diagram using points: Carr Cdep Cdep-arr-priority End Virginia Tech 59 Computer Program Screen 1 1 2 1 Virginia Tech 60 Computer Program (Screen 2) 3 6 4 Virginia Tech 61 Computer Program (Screen 3) 5 1 8 9 Virginia Tech 62 Computer Program (Screen 4) 10 11 Virginia Tech 63 Computer Program (Screen 5) 12 Virginia Tech 64 Estimating Runway Saturation Capacity for Complex Airport Configurations • The methodology explained in the previous handout addresses a simple Time-Space diagram technique to estimate the runway saturation capacity • The time-space approach can also be used to estimate the saturation capacity of more complex runway configurations where interactions occur between runways • Example problems taken from the FAA Airport Capacity benchmark document will be used to illustrate the points made Virginia Tech 65 Methodology • Understand the runway use according to ATC operations • Select a primary runway as the basis for your analysis • Estimate the saturation capacity characteristics of the primary runway using the known time-space method • Examine gaps in the runway operations at the primary runway. These gaps might exist naturally (i.e., large arrival-arrival separations) or might be forced by ATC controllers by imposing large in-trail separations allowing operations at other runways Virginia Tech 66 • If runway operations are independent you can estimate arrival and departure saturation capacities for each runway independently • If the operations on runways are dependent estimate the runway occupancy times (both for arrivals and departures) very carefully and establish a logical order f operations on the runways. Virginia Tech 67 Example 2 - Charlotte-Douglas Intl. Airport Departures Operational Conditions 18R 1) Runways 18R/36L and 18L/36R are used in mixed operations mode 2) Runway 5/23 is inactive 3) Parallel runway separation > 4,3000 ft. 4) ASR-9 airport surveillance radar (scan time 4.8 seconds) 5) Aircraft mix a) Heavy - 20% b) Large - 30% c) Small - 50% 6) Approach speeds a) Heavy - 150 knots b) Large - 140 knots c) Small - 110 knots 7) Runway occupancy times N a) Heavy - 57 s. b) Large - 52 s. c) Small - 49 s. 8) Common approach length - 7 nm 9) In-trail delivery error standard deviation -18 s. 10) Large hub separation criteria (2.5/4/5/6 nm) 11) IMC weather conditions 18L Control Tower 23 Terminal 5 1,00 0 500 Virginia Tech 5 , 0 0 ft 36R 3,000 36L Arrivals 68 Some Intermediate Results Departure-Departure Separation Matrix Virginia Tech 69 Results of CLT Analysis Arrivals (per hour) Single runway analysis - mixed operations 30 25 20 15 10 5 0 0 10 20 30 40 50 Departures (per hour)) Virginia Tech 70 Results of CLT Analysis Arrivals per Hour Two-parallel runway analysis - mixed operations 50% arrivals 50% departures 54 0 95 23 Departures per Hour Virginia Tech 71 Capacity Benchmark Results The FAA capacity benchmarks offer an assessment of the estimated capacity by the FAA Reduced capacity = IMC conditions Virginia Tech 72 FAA Benchmark Results vs. Our Analysis Variations occur because the assumptions made in our example are not necessarily the same as those made by FAA Virginia Tech 73 Example 3 - Charlotte-Douglas Intl. Airport Departures Operational Conditions 18R 1) Runway 18R/36L for departures Runway 18L/36R for arrivals 2) Runway 5/23 is inactive 3) Parallel runway separation > 4,3000 ft. 4) ASR-9 airport surveillance radar (scan time 4.8 seconds) 5) Aircraft mix a) Heavy - 20% b) Large - 30% c) Small - 50% 6) Approach speeds a) Heavy - 150 knots b) Large - 140 knots c) Small - 110 knots 7) Runway occupancy times N a) Heavy - 57 s. b) Large - 52 s. c) Small - 49 s. 8) Common approach length - 7 nm 9) In-trail delivery error standard deviation -18 s. 10) Large hub separation criteria (2.5/4/5/6 nm) 11) IMC weather conditions 18L Control Tower 23 Terminal 5 1,00 0 500 Virginia Tech 5 , 0 0 ft 36R 3,000 36L Arrivals 74 Results of CLT Analysis Two-parallel runway analysis - segregated operations Arrivals per Hour Original Runway Configuration 54 New Runway Configuration 27 0 23 95 47 Departures per Hour Virginia Tech 75 Example 4 - Charlotte-Douglas Intl. Airport Departures Operational Conditions 18R 1) Runways 18R/36L and 18L/36R are used in mixed operations mode 2) Runway 5/23 is inactive 3) Parallel runway separation > 4,3000 ft. 4) ASR-9 airport surveillance radar (scan time 4.8 seconds) 5) Aircraft mix a) Heavy - 20% b) Large - 30% c) Small - 50% 6) Approach speeds a) Heavy - 150 knots b) Large - 140 knots c) Small - 110 knots 7) Runway occupancy times N a) Heavy - 57 s. b) Large - 52 s. c) Small - 49 s. 8) Common approach length - 7 nm 9) In-trail delivery error standard deviation -18 s. 10) Large hub separation criteria (2/3/4/5 nm) 11)VMC weather conditions 18L Control Tower 23 Terminal 5 1,00 0 500 Virginia Tech 5 , 0 0 ft 36R 3,000 36L Arrivals 76 Results for CLT VMC Scenario Arrivals (per hour) Single runway analysis - mixed operations 40 30 20 10 0 0 20 40 60 80 Departures (per hour) ) Virginia Tech 77 Results of CLT VMC Analysis Arrivals per Hour Two-parallel runway analysis - mixed operations 63 54 VMC IMC 0 23 95 26 118 Departures per Hour Virginia Tech 78 Airport Capacity Model (ACM) • Model developed by FAA to expedite computations of runway saturation capacity • Later modified by MITRE to be more user friendly • Inputs and output of the model are similar to those included in the spreadsheet shown in class • Provides 7-9 data points to plot the arrival-capacity saturation capacity envelope (Pareto frontier) Virginia Tech 79 Sample Enhanced ACM Results Virginia Tech 80 Example 5 - Non-towered Aiport Capacity Using Advanced High-Volume Operations Technologies (SATS program) • Existing airports without a control tower have very small runway saturation capacities (4-5 arrivals per hour) • These airports require large headways (10-12 minutes) between aircraft because ATC cannot see the aircraft in radar (ATC applies procedural separations) • NASA is developing technologies to help pilots space themselves at these non-towered airports (using an airport sequence manager and Automated Depedence Surveyance mode B - ADS-B) Virginia Tech 81 HVO Scenario (Uncontrolled Airport) Critical Area of Study Virginia Tech 82 Example 5 - HVO Airport Operational Conditions Departures 1) Single runway used in mixed operations mode 2) HVO technology with Airport Manager and ADSB technology 3) With and without parallel runway 4) No radar 5) Aircraft mix a) TERP A - 60% b) TERP B - 40% c) No TERP C 6) Approach speeds a) TERP A - 90 knots b) TERP B - 110 knots c) No TERP C 7) Runway occupancy times Variable with availability of runway taxiways and parallel taxiway (use REDIM model) 8) Common approach length - 10 nm 9) In-trail delivery error standard deviation -30 s. 10) Arrival-arrival separation criteria (5 nm) 11) IMC weather conditions Key change from procedural seperation Virginia Tech 83 Computer Program Screen 1 1 2 1 Virginia Tech 84 Computer Program (Screen 2) 3 6 4 Virginia Tech 85 Computer Program (Screen 3) 5 1 8 9 Virginia Tech 86 Computer Program (Screen 4) 10 11 Virginia Tech 87 HVO Single Runway Airport Capacity (no parallel taxiway) Virginia Tech 88 HVO Single Runway Airport Capacity (with parallel taxiway) Virginia Tech 89 Validation of Results (using FAA Aairport Capacity Model) Virginia Tech 90 Summary of Results • The saturation capacity of an airport with HVO (ADS-B) technology depends on the safety buffers allowed and the delivery accuracy of pilots/AMM system • The variation in technical parameters such as γ and δ affects the results of saturation capacity • The estimation of departures with 100% arrival priority in our analysis seems consistent with analyses done by TSAA in 2003 (Milsaps, 2003) • The results compare well with those obtained using the FAA Airport Capacity Model • The availability of a parallel taxiway has a large influence in the mixed mode saturation capacities Virginia Tech 91 Recapitulation • The saturation capacity of an airport depends on the runway configuration used • The saturation capacity during VMC conditions is higher than during IMC conditions (due to shorter separation minima) • The variation in technical parameters such as γ and δ affects the results of saturation capacity • The estimation of departures with 100% arrival priority in our analysis seems very conservative • The time-space analysis does not provide with delay results (use deterministic queueing theory or FAA AC 150/5060 to estimate delay) Virginia Tech 92 ...
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