AirPAD ® Project Airport Pavement Analysis and Design SySCOM Consulting UK version, all rights reserved @2009 Pavement Management Middle East 2009 29-30

AirPAD® ProjectAirport Pavement Analysis and Design

SySCOM Consulting

UK version, all rights reserved @2009

Pavement Management Middle East 200929-30 march 2009, Dubai UAE

Kteg Engineering ltd

Department of Civil Engineering

University of Rome “Tor Vergata” Italy

Why the need of a reliable prediction model ?

Aviation Industry Evolution

Latest generation of large civil aircraft is not just heavy, achieving TOW loads up to 750.000kg, but even having

complex, multiple-wheel, multiple truck landing gear systems. The latest Boeing B-777-ER version has only two six-

wheel landing main landing gears to support a gross weight of up to 350.000kg. The Airbus A380, over 500.000kg,

which entered commercial service in 2006, has two six-wheel body gears in addition to two four wheel wing gears, for a

total of 20 wheels in the main gear assembly. The complex gear loads applied to airport pavements, runways as well as

taxiways and aprons, by these new aircraft types are quite different from the loads applied by the older generation of

commercial airplanes.

Complex landing gear layouts and wheel load interactions within airport pavement layersintroduced the risk of premature failure of pavement layers

AirPAD - Airport Pavement Analysis and Design

How to predict the real residual life of a runway originally designed for a limited trafficand actually performing over it’s designed capability?

Airports and Traffic Growth

In the last few years most European regional airports have been experiencing a dramatic traffic growth, pushed by the

low-cost airlines phenomenon. Many low-cost airline bases are former NATO airports turned to perform as international

“low-cost hubs”; hence the over-use of former pavements designed for a limited traffic.

Beside the low-cost airlines, European hubs report a remarkable traffic growth as well. Runways and taxiways have

been designed for a different traffic rate and smaller aircrafts. How to predict pavements durability, then? The ability

to understand how any airport pavement would sustain the growth of air traffic is very important in terms of

maintenance planning and reliability forecast. Not least the commercial agreements with airlines and operators.


How to predict the real residual life of a runway originallydesigned for a limited traffic and actually performing

over it’s designed capability?

Why the need of a reliable prediction model

The AirPAD is a Performance-Based Prediction model to forecast

when and to what extent an airport pavement section will suffer

fatigue cracking distress.

The AirPAD performs as a decision support tool; it could be

integrated in a set of Life Cycle Cost Analysis tools or used to

reverse-engineer and verify pavement sections design at project level.


• Is possible to calculate the stress and damage contribution affecting the pavement section by each aircraft type, according to the effective payload configuration operating the airfield.

• The algorithm is sensitive to the real climatic condition (temperature, wind, pressure) of the airfield environment along the whole day

• Aircrafts wandering distribution is calculated by deviation and spread according by the section path type (runway, taxiway, apron)

• As the structure design is fully customisable, is possible to define the mechanical specification and performances of each construction material, referring to local available materials instead of standard laboratory materials


AirPAD main features

The input variables set could be tailored around the real background and performance condition

Realistic >> Accurate >> Statistically Reliable


Basic hypothesis of multi layered elasticity theory

• Pavement cross section is represented by overlapped

layers set over an elastic half-space

• Each layer is assumed as homogenous, isotropic and

defined by viscoelastic parameters dependent on loads,

time (loading cycle) and temperature

• The cumulative damage of the section is calculated by

the stress applied on section layers

• Traffic loads are assumed to be vertical and directly

applied by the landing gears

• The affecting strain is the combined contribution of each

wheel strain

AirPAD Algorithm, basic workflow


Input data set



AirPAD – Traffic and Operations Definition - NEW PAVEMENT SECTION

average daily operations are distributed along time slots of 3 hours as pavement performances change along daytime temperature gradient

multiple and independent operations definition on different pavement sections

up to three different payload configuration for each aircraft

individual landing gear assembly, including tires pressure, for each aircraft type

no restriction on landing gear assembly layout.

virtually unlimited aircraft repository as the same aircraft could have different layouts according to operating carrier


AirPAD – Traffic and Operations Definition - CURRENT PAVEMENT SECTION

Pavement sections already in use can record a complex operations history as old aircraft models can have been discontinued operations in former times and/or latest models could operate since a short time only.

Most of pavement design software refer to a “static picture” of airport operations, at least requiring a static traffic growth factor. We know that a “living airport” can experience dramatic changes along its operational life.


pavement lifespan is sorted into six 4-years time frames

is possible to specify the operations related to each aircraft along the whole pavement operational life

traffic growth is now implicit in the operations/year data.

is possible to input the traffic interchange among aircrafts upgrades/dismissing (i.e. B747-400 >>> A380-800)

AirPAD – Traffic and Operations Definition - CURRENT PAVEMENT SECTION


AirPAD – Landing gear layout

individual landing gear assembly layout design, fully customizable, including tires pressure, for each aircraft type

virtually unlimited aircraft repository as the same aircraft could have different layouts according to operating carrier


AirPAD – Climate definition

Climate is defined on seasonal basis by main parameters related to the stress-matrix by the E-modulus: solar radiation, wind speed at ground level, air temperature, … (refer to list below)

Daily temperature field is calculated over the average temperature on each 3 hours interval, because asphalt concrete behaviour and performances change significantly with temperature variation. The most realistic E-modulus calculated by background conditions improves significantly the model results accuracy and reliability

temperature distribution along the layers under different climate conditions is calculated by Barber’s theory of the nonlinear unstable pavement temperature fields of two-dimension layered system.

AirPAD – Section Layers Definition


• The pavement cross section is segmented into 20cm wide stripes to calculate the local stress path along the layers, stripe by stripe;

• Normal stress, shear and strain are calculated with the multi-layered elasticity model implemented;

• The engineer is free to design all the coated and un-coated courses of the pavement cross-section;

• Each layer could be defined by an enhanced set of parameters and variables that fully describe the mechanical performances of asphalt concrete, cement treated aggregates and unbound aggregates;

• Bitumen performances can be set for each coated layer (wearing, binder and base), This feature allows to define specific performances introduced by bitumen compounds with chemical additives;

• Aggregates domain could be described by detailed Jigs and sieves passing rates.

Algorithm cycles


Algorithm cycle: Thermodynamic layout characterization

• calculated on seasonal base and/or 8x3-hours time slots on daily base over seasonal average.

• temperature at every layer depth is calculated by the validated Barber formula

A) Thermodynamic layout defined by daily average temperature >> 1 value Tm per each temperature wave

B) Thermodynamic layout defined by segmentation of Barber temperature wave into 8x3h time slots >> 8 values Ti / wave

Tpav(z,t) = Tag + R + (Ag/2 + 3*R) * F * exp(-C*z) * sin [0.262*t – C*z – arctg(C/(H+C))]

15

20

25

30

35

40

0 3 6 9 12 15 18 21 24

time [hours]

Pav

emen

t Te

mp

erat

ure

s [°

C]

3 ho

urs

perio

d

3 ho

urs

perio

d

3 ho

urs

perio

d

3 ho

urs

perio

d

3 ho

urs

perio

d

3 ho

urs

perio

d


Algorithm cycle: Dynamic Loads Calculation

Dynamic loads are calculated by:

• load distribution on wheels

• test point assignment (differential depth)

• gears footprint area and pressure

• load frequency

• residual deformation on tandem assembly


Algorithm cycle: Bitumen performances definition

• mechanical behaviour as elastic-plastic-viscous

• |E*| complex elasticity modulus

• Poisson |*| complex ratio

• performances are related to temperature, load and frequency

Complex Modulus |E*|

• French SHELL method

• ASPHALT method

|E*| Elasticity modulus is calculated by the French SHELL method and Asphalt method, over the input of parameters:

• temperature and climate parameters;

• dynamic load by landing gears assembly load distribution and traffic frequency by deviation;

• aggregate domain distribution (Asphalt)

• asphalt concrete composition and voids % (Shell)

• layers friction (within layers)

• bitumen performances (additives)


Algorithm cycle: Unbound Granular Materials (MG)

• Hypothesis of non-linear mechanical behaviour

• Resilient Modulus MR defines the behaviour of unbound granular

materials (MG) as a local Elasticity modulus under load stress

Stress tensor deviator of the reversible strain when load is removed

The Algorithm assumes the UZAN implementation model

MR is related to the stress path verified and calculated on load points, at a specific thermodynamic layout.

k1 value range 0 – 3

k 2 value range 0 – 1,5

k 3 value range 0 – -7


Algorithm cycle: Friction factor within layers

Hypothesis

Adherence between layers is not perfect

Stress tensor not constant

Friction factor at layers interface is related to:

• sealant and adhesive layer spread (usually bitumen and additives)

• aggregates penetration grade

• vertical stress (in competition with shear stress)

• section temperature (as is influencing bitumen performances)

• dynamic loads

uK

Horizontal reaction module at interface

= shear stress at interfaceu = horizontal strain at interface


Hypothesis

• aircraft direction is not constant

• The pavement cross section is segmented into 20cm wide stripes to calculate the local stress path along the layers, stripe by stripe

• cross distribution of trajectories is assumed Normal

• the effective position of each wheel from the centre of the gear assembly and aircraft axis is approximated to 20cm

Assumptions

• standard deviation of 14m-18m on runways take-off area

• standard deviation of 18m-22m on runways landing area

• standard deviation up to 20m-26m on fast exit taxiways


Algorithm cycle: Aircraft wandering distribution

The Miner criteria is adopted to calculate the cumulative damage

Asphalt Concrete (surface)

Unbound Granular Materials (MG) (base and subgrade)

i

i

N

n ni = load cycles on stress state - i

Ni = total number of load cycles on stress state –i at fractured stage

Nmax is related to construction materials used and is assumed the FAA formula:

EA = elastic modulus asphalt concrete

h = horizontal strain at lower bound

Esub = Resilient modulus Mr subgrade

v = vertical strain at subgrade layer upper bound

Stabilised Granular Materials (MC) (base)

1

10 5780011.9

N

N

= specific horizontal traction strain at stabilised layer lower bound ( 0.0001576).

0001576.0

0001576.0


Algorithm cycle: Cumulative damage calculation

AirPAD model calibration

Unbound Granular Materials (MG) Regression parameters calibration k1, k2, k3 used to calculate MR

Base layer k1 = 2,410; k2 = 0,360; k3 = - 0,400

Subgrade k1 = 0,946; k2 = 0,163; k3 = - 0,419

Average MR would be comparable with the value result of laboratory test, at

same stress condition.


Equivalence factor for cement bounded granular layers

The FAA protocol introduces an equivalence factor [coef.eq.FAA]

from the MG base layer to the MC base layer, by range [1,6-2,3]

The AirPAD is introducing instead the modulus fcp to measure the

compression strength of the base layer cement bounded granular

materials when calculating the resilient Mr of fractured layers:

The calibration is required to find a correlation between the

strenght of the fractured cement bounded granular layers, modulus

fcp, and the value of the [coef.eq.FAA]

A comprehensive set of test sessions were performed with values

[coef.eq.FAA] as 1,6-1,9-2,3 . Each series was performing a further

3-steps test with progressive values of modulus fcp

Cumulative damage (D) vs modulus fcp, with coef.eq.FAA = 1,6

A regression analysis found a convergent mean value of modulus

fcp (at D-stress=0) with the correspondent coef.eq.FAA assumed, at

different operations/year rates.



Equivalence factor for cement stabilised granular layers (MC)

By regression analysis is found a functional correlation between

the FAA equivalent factor, the FCP modulus and the load on

landing gears, sorted by aircraft type.

Generic multi-regression analysis equation:

as z = modulus fcp (coeff.eq.FAA) ; x = coef.eq.FAA ; y = (load on gear).

Values must comply with the following equations:

The multi-regression analysis sorted the following correlation:



K-parameter of friction factor within layers

The FAA protocol still ignores a critical friction factor within layers

A comparative test session with FAA standard results (sum of

squares of residuals mean of miner curves up to 20 years

lifespan ) is performed to investigate results variation and

accuracy with assigned K-values

Convergent results are reached with friction factor multiplier

k = 6. Higher values reduce results stability and accuracy

Sum of squares (residuals) at friction factor variation

Cumulative damage vs effective friction factor



AirPAD – Algorithm results

• verify the most affected cross section stripe by dynamic loads and traffic

• stress-strain matrix at all layers

• cumulative damage on base and subbase layers, sorted by year and aircraft type contribution

• pavement section lifetime forecast according to operations planned


cumulative damage (Miner) contribution on cross section by B747-400 operations on runway (take off area)

Comparison with other methods/softwares

It’s interesting to compare features and flexibility with the upcoming APSDS-5 platform, the closest to the

AirPAD:

The AirPAD is sorting the cross section into 20cm wide control stripes in order to gain a complete and

accurate stress-strain matrix along the cross section and layers.

The stress-deformation matrix is calculated at each stripe, on each layer (1/3h) resolving the stress-strain

tensor of the multi layered elasticity equations to a convergence. This implies more calculation cycles to

minimise the residual error.

The APSDS doesn't take count of temperature (as the FAA as well) and it's variation along days and seasons.

The traffic is not sorted by the day (different time slots mean operations at different temperature).

The speed (load frequency) is not considered as variable with the traffic and the section position.

The AirPAD refers to the formulation from Asphalt Institute ( ref. to AASHTO 2000) and SHELL in every point

of the cross section, at different layers depth.

The APSDS ignores the residual strain of a tandem gear assembly between the 1-wheel unload and 2-wheel

dynamic load, when calculating (if even does it) the stress tensor.

Friction factor between the layers: the APSDS assumes the adherence as perfect. Instead, the AirPAD

introduces different values according to the real behaviour.

Any other algorithm allow to define exactly the materials specifications and performances


AirPAD integration and improvement

The AirPAD Algorithm is structured as a set of interrelated modules linked by a functional "backbone"

Modules could be updated or calibrated as needed to be closer to airports/operations’ requirements

Modules could be re-engineered or according to the latest scientific improvements

Modules could be added and integrated with other APMS platforms


Case Study at FCO Airport

Aim of the simulation (year 2006) is the investigation of the potential pavement damage and durability reduction consequent to the future replacement of most B747-400 actually operating in the FCO International Airport of Roma (Italy) by the wider and heavier Airbus A380

The section investigated is the mid-section of the Runway 25, actually operating the 91% of all takeoff traffic in the airport. Section layers structure and materials have been recovered by original plans and on-site surveys.



Actual scenario on Runway 25

Actual traffic distribution on Runway 25




Cumulative Damage (average Temperature on seasonal base) – Base Layer




Cumulative damage (8x3hours time slot temperature) – Base Layer


The simulated scenario introduces the A380 replacing the 60% of the traffic operated by the B747-300/400, total of

4026 takeoff/year, and the B747-300/400 replacing the 30% of traffic operated by the B767-300, total of 3389

takeoff/year.

The traffic operated by the B767-300 is then reduced to 4937 takeoff/year.

The residual traffic distribution is assumed as steady for the following years (this latest unrealistic hypothesis is

necessary to separate the effect of potentially different traffic contributions)



Simulated scenario on Runway 25

Performing the AirPAD algorithm and analysing the results, there is no evidence of a significant difference

between the two scenarios. This result means that the introduction of the new A380 in the traffic distribution

doesn't affect significantly the runway cross section examined.



Results

Comments

Forecast airport pavement sections effective lifetime is a powerful decision support tool, allowing

the airport management to prevent unexpected failures, improve safety, plan effectively future

maintenance works, analyse the economic impact of a different traffic layout.

One for all: which is the real benefit balance operating a new carrier or aircraft model in your

airport?

Most algorithms/software deliver a quick response, introducing allowances and shortcuts that pay

a great price in terms of statistical reliability and results accuracy.

Common approach is to refer to “standard materials” and “standard climate condition” as well as

“standard dynamic loads”, then simplified calculation models. But, how far is YOUR airport from

standards? Materials could be different according to local availability, climate is the most variable

issue (and even ignored by the most), dynamic loads can change by location and traffic condition

as well.

Introducing too many allowance sources, the consequent statistical error is far higher, not just as

linear yet exponential.

About prediction models, statistic reliability is a primary concern as a lack of reliability

downgrades the utility of a model to the same statistical relevance of a coin as a prediction

tool … that’s not predicting yet gambling!


AirPAD® ProjectAirport Pavement Analysis and Design

SySCOM Consulting

Thank you

w w w . a i r p a d . o r g

Documents

AirPAD ® Project Airport Pavement Analysis and Design SySCOM Consulting UK version, all rights reserved @2009 Pavement Management Middle East 2009 29-30