Evaluation of climatic factors based on the mechanistic-empirical pavement design guide/Klimato veiksniu vertinimas pagal mechanini-empirini keliu dangu projektavimo vadova/Klimatisko faktoru ietekmes izvertejums mehaniski empiriskas segu projektesanas rokasgranata/Klimaatiliste tegurite hindamine lahtudes mehhanistlik-empiirilisest katendite projekteerimise juhendist.
Zilioniene, Daiva ; De Luca, Mario ; Dell'Acqua, Gianluca 等
1. Introduction and literature reviews
Pavements are an example of a complex engineering system requiring
probabilistic modelling due to the uncertain nature of most of the
pavement performance model parameters. Due to the large number of
parameters involved, such as the thickness of layers, material
properties and climatic conditions affecting pavement performance, it is
usually not feasible to determine optimal design using a trial and error
approach (Gaurav et al. 2011). The deterministic pavement performance
models vary from simplistic empirical relationships to complex
mechanistic-empirical computational algorithms (Wojtkiewicz et al.
2011). In this context, the overall objective of the
Mechanistic-Empirical Pavement Design Guide (MEPDG) is to provide the
highway community with a state-of-the-practice tool for the design of
pavement structures, based on mechanistic-empirical principles according
to the Guide for Mechanistic-Empirical Design of New and Rehabilitated
Pavement Structures of 2004. The Mechanistic-Empirical format of the
Design Guide provides a framework for future continuous improvement to
keep up with changes in trucking, materials, construction, design
concepts, computers, and particularly in climate modelling. As a support
for implementing the new MEPDG, a sensitivity study was undertaken to
assess the comparative effect of design input parameters pertaining to
material properties, traffic and climate on the performance of two
existing flexible pavements in Iowa with relatively thick asphalt
concrete (AC) layers (Kim et al. 2007). Some of the required data either
are not available or are stored in locations not familiar to designers.
A recent study examined the adequacy of using conventional traffic data
and national default values in the absence of weigh-in-motion (WIM) data
for pavement design. A comparative study was conducted on 14 unique
sections in Arizona, where WIM data are available through the Long-Term
Pavement Performance Program (Ahn et al. 2011). The study consists of
two parts: 1) comparisons of input traffic data and 2) comparisons of
pavement distresses predicted by the MEPDG. The MEPDG distress
prediction equations were used to predict the mixture performance as a
function of density (Mogawer et al. 2011). The testing analysis and
MEPDG predictions indicated that higher density specimens yielded
improved fatigue and rutting performance. Moreover, tests were performed
on asphalt rubber binder and asphalt rubber asphalt concrete (ARAC) mix
in order to verify whether the new MEPDG can be used effectively for
asphalt rubber (AR) materials (Pasquini et al. 2011).
2. The Italian CNR road pavement design catalogue
The Italian CNR road pavement design catalogue Catalogo delle
pavimentazioni stradali C.N.R.-B.U.-178,1995provides a set of solutions
for the design and testing of pavements. The following types of pavement
are considered: flexible, semi-rigid and rigid. For each pavement, the
catalogue provides a series of solutions in relation to the bearing
capacity of the substrate and the traffic conditions. In the catalogue
there are 32 cards for each type of road (as prescribed under Italian
law). Details regarding the assumptions on traffic, subgrade, material
characteristics and climatic conditions are presented in to the
C.N.R.-B.U.-178,1995.
3. Mechanistic-Empirical Pavement Design Guide
The testing procedure and design guidance contained in the MEPDG is
divided into three phases as follows. During the first phase, a
characterization of the parameters constituting the pavement materials
and those of the traffic is established. Moreover, a climate model is
used to study changes in temperature and humidity within each layer of
the pavement. The model takes into account climate data from weather
stations (temperature, precipitation, solar radiation, cloud cover, wind
speed) allocated in the area where the road is developed. The
predictions of temperature and humidity for the layers of the pavement
are calculated from the model each hour for the entire life of the
pavement. The model uses this information to determine the modulus of
the different materials used at different depths. The second phase of
the process refers to the structural design and the analysis of the
performance. The approach consists of an iterative process: starting
from an initial design hypothesis conceived by the designer (or obtained
from a catalogue) that describes the thickness of the pavement layers
and material properties. The analysis is carried out using fatigue
models (which provide the output deformation), the combined damage, and
the evolution of pavement surface characteristics over time. If the
hypothesis does not meet the criteria of efficiency, changes are made
and new analyses are carried out via a feedback process until the reach
of satisfactory result. In the third phase of the process, through a
series of procedures, the design alternatives are compared from the
point of view of technical terms and cost.
4. Proposals to adapt the Italian CNR road pavement design
catalogue through the Mechanistic-Empirical Pavement Design Guide
Both the catalogue that the MEPDG guide for the design and the road
pavement tests are based on the concept of reliability. Moreover, to
identify the performance of the pavement, the catalogue only refers to
the Pavement Serviceability Index (PSI), and the MEPDG refers to
International Roughness Index (IRI, in/mi). The MEPDG also makes it
possible to estimate the following parameters: bottom-up cracking (%),
total permanent deformation, permanent deformation AC (in), surface
cracking down (ft/mi) and thermal fracture (ft) for flexible pavements,
transverse cracking (%) and mean joint fault (in) for rigid pavements.
For a comparison of the results it was necessary to standardize the
results by referring to a single parameter. In this regard, reference
was made to the report (Paterson 1986):
IRI = (5-PSI)100, (1)
where IRI--International Roughness Index, m/km; PSI--Pavement
Serviceability Index, in particular is a concept derived during the
AASHO Road Test. This concept is related to the primary function of a
pavement structure: to provide the travelling public with a smooth,
comfortable, and safe ride. A scale ranging from 0 to 5 is used to
evaluate PSI; pavement with a rating of 0 is impossible and with a
rating of 5.0 would be perfectly smooth.
To apply the MEPDG to the Italian reality the information contained
in C.N.R.-B.U.-178, 1995 was taken into account. Using the MEPDG, the
solutions proposed in the catalogue were tested for the freeways (about
100 km) and highways (about 100 km). In particular, before starting the
simulation, it was necessary to organize the data in the form required
by the MEPDG.
The data included in the MEPDG support software were organized into
the following three groups: characteristics of the materials, traffic
characteristics and climatic conditions.
4.1. Characteristics of materials
For the material properties and thickness of the layers, reference
was made to the variables (and their values for the upper limit) given
in C.N.R.-B.U.-178, 1995. In particular for the dynamic modulus,
reference is made to a maximum value of 150 N/[mm.sup.2].
4.2. Traffic characteristics
For traffic, reference was made to the following variables:
--average annual daily traffic (AADT, vpd)--provided by the
administrators of the road analyzed on a five-years basis;
--percent of heavy vehicles ([P.sub.t], %)--provided by the
management of the roads analyzed on a five-years basis;
--operating speed, estimated using predictive models for the
operating speed.
It was also necessary to refer to the following calibration factors
regarding traffic volume:
--factors of monthly adjustment ([MFA.sub.i]);
--distributions of the classes of vehicles;
--distribution of vehicles per hour;
--factors of increase of traffic.
For [MAF.sub.i], it was assumed that during summer the movement of
heavy vehicles is less. In this regard the distribution was as follows:
[MAF.sub.1-6,10-12] = 1.08 and [MAF.sub.7-9] = 0.76.
For the distribution of vehicle classes, given the difference
between USA vehicles and Italian vehicles, it was necessary to make
adjustments in "terms of equivalence" (Table 1). For the
hourly distribution factor (HDF), i.e. the percentage of the average
daily traffic at all hours of the day, it is referred to the standard
distribution prescribed by the MEPDG also taking into account particular
kind of traffic surveys carried out on particular roads in the Italian
territory.
4.3. Factors of increased traffic
The MEPDG provides options for three different laws regarding an
increase in traffic, and in this study, the one providing the most
serious condition was assumed. In particular, in the simulations,
reference was made to the maximum value indicated in the catalogue.
[FIGURE 1 OMITTED]
4.4. Climate data
To take into account the climatic conditions, a series of data
collected through the surveys conducted in the survey stations indicated
in Table 2 and Fig. 1 were used. It was necessary to resort to other
sources for some specified variables. The data was collected using the
instrumentation of weather stations indicated in Table 2. These stations
are constituted by a series of sensors connected to a data logger.
The instrumentation present in each station is:
--anemometer for measuring wind speed;
--thermometer to measure temperature;
--hygrometer to measure humidity;
--pyranometer to measure solar radiation;
--rain gauge for the determination of the intensity of rain.
These data, recorded by the logger, were organized in accordance
with the procedures indicated by the MEPDG. Two different files were
generated to insert the information contained in Fig. 2 into the MEPDG.
The first file (*.hcd) contained information on the survey station and
the second file (*.icm) contained the information/instructions needed to
setup the Enhanced Integrated Climatic Model (EICM). In particular the
data introduced into the EICM were organized into four groups.
Group I contains the time interval for which the meteorological
data are available--data for 24 months were taken into consideration.
Group II contains the following information:
--geographical coordinates--latitude and longitude;
--elevation above sea level (ft);
--depth of water table (ft);
--annual average temperature in ([degrees] F);
--freezing degree days ([degrees] F)--an index of freezing FDD:
FDD = 32 - [T.sub.a], (2)
where FDD--an index of freezing; [T.sub.a]--function of the average
daily temperature.
--height of average annual rainfall (in);
--average monthly relative humidity (%).
Group III contains:
--date as month/day/year;
--time of sunrise and sunset, derived from the geographical
coordinates of the survey station;
--daily maximum value of solar radiation. This data is taken
directly from the instruments present in the different stations that
provide it in W/[m.sup.2]. However given that for this variable the EICM
does not provide the units, reference was made to the "potential
maximum daily radiation". This variable to which the MEPDG refers
was obtained according to the following procedure.
The daytime period (time between sunrise and sunset) is:
[N.sub.i] = [cos.sup.-1](-tg[phi]tg[delta]), (3)
where [N.sub.i]--the period between the point where the sun rises
and the highest point of the sun, t; [phi]--the latitude, rad. [phi] and
[delta] take a conventionally positive value with respect to the North.
The declination of the sun, i.e. the apparent distance of the orbit
of the sun daily from the earth's equator:
[delta] = arcsen{0.39785sen [4.869 + 0.0172i + 0.03345sen (6.224 +
0.0172i)]|, (4)
where [delta]--declination of the sun, rad, i--days of the year,
number of day.
Fig. 2. Layout of data entered into the MEPDG
ICM Files (*.icm)
StartDate (YYYYMMDD)--EndDate (YYYMMDD): The period for which this
file contains data for. 19960701-20011231
Longitude, Latitude, ELEVATION, Annual Water Table Depth (-1 if
using seasonal), spring water table depth, summer water table, fall
water table, winter water table, MEAN ANNUAL TEMPERATURE, FREEZING
DEGREE DAYS, ANNUAL RAINFALL, monthly average humidity (12
total-start January) -86.23,32.18,227,-1,10,20,19,10,64.8035,12.8717,
44.1237,72.3031,69.6847,65.7183,70.4444,70.5253,75.7314,75.2074,74.
7333,74.5993,72.8259,74.0491,75.2558
Month, Day, Year, Sunrise time (decimal-24 hour), sunset, daily
solar radiation maximum. Sunrise/Sunset calculated from Lat/Long.
Solar radiation data from rad.datfile, correct for Lat/Long. 7 1
1996 4.95899 19.041 3730.48
Hour, temperature, precipitation, wind speed, percent sunshine,
hourly ground water depth.
0 72 0 0 100 20
1 71.1 0 0 100 20
2 70 0 3 100 20
3 70 0 0 100 20
Height of the sun, defined as the angle between the position of the
sun and the horizon:
h = 90[degrees]-[absolute value of [phi]-[delta]], (5)
where h--height of the sun, rad.
Max height of the sun, measured at the passage on the upper
meridian:
senh = sen[phi]sen[delta] + cos[phi]cos[delta]cosP. (6)
A factor of earth-sun distance correction that allows us to
evaluate the potential radiation:
[E.sub.0] = 1 + 0.0334cos(0.0172i - 0.0552), (7)
where [E.sub.0]--factor of earth-sun distance, (MJ [m.sup.-2]).
The potential maximum daily radiation ([R.sub.a], MJ [m.sup.-2])
for each location indicated in the Table 1 was obtained as:
[R.sub.a] = 117.5 [E.sub.0]([N.sub.i]sen[phi] sen[delta] +
cos[phi]cos[delta] sen[N.sub.i]/[pi]). (8)
Group IV containing information:
--time (0-24 format);
--temperature, [degrees] F;
--rainfall intensity, in/h;
--wind speed, mph;
--cloud cover, %,--this information was derived from Meteorological
Aerodrome Report bulletins. In particular, using this information it was
possible to determine cloud cover according to the following
classification: CLR (clear), FEW (few clouds 1/8-2/8), SCT (scattered
clouds 3/8-4/8), BKN (broken 5/8-7/8), OVC (overcast 8/8).
5. Numerical simulations with MEPDG
Nine different scenarios were simulated. They are obtained from the
combination of 3 different latitude values (North, Central, South) with
3 altitude conditions (high, medium, low). Through these simulations it
was possible to study in 9 different configurations the performance
offered by 6 different solutions proposed by the C.N.R.B.U.-178, 1995.
Figs 3-11 report the results obtained for the 54 combinations simulated.
In particular, by analyzing the results concerning the flexible
pavement, the tests carried out using the MEPDG on the solutions
suggested by the catalogue, in reference to the IRI index, are positive
(Dell'Acqua et al. 2011).
[FIGURE 3 OMITTED]
[FIGURE 4 OMITTED]
[FIGURE 5 OMITTED]
[FIGURE 6 OMITTED]
[FIGURE 7 OMITTED]
[FIGURE 8 OMITTED]
[FIGURE 9 OMITTED]
[FIGURE 10 OMITTED]
[FIGURE 11 OMITTED]
For alligator cracking on highways the tests are positive, while
for the freeway the proposed solution is not acceptable. For the
permanent strain (asphalt layer), it is observed that the checks are
almost always satisfied for both (freeway and highway). For total
permanent strain, for both freeway and highway, checks are satisfied for
about half of the scenarios simulated. Finally, the PSI is always
satisfied for the freeway, while for highways, it only fails to be
satisfied in three scenarios.
For the semi-rigid pavement, the solutions suggested by the
C.N.R.-B.U.-178, 1995, in reference to IRI and alligator cracking, are
satisfied for both types of roads (freeway and highway).
For the permanent strain (asphalt layer) checks are almost never
satisfied on the highway. They are almost always satisfied on the
freeway. For the total permanent strain, checks have never been
satisfied on the highway and only in some cases are satisfied on the
freeway. Finally, the verification of the PSI is satisfied on the
highway. On the freeway, it is not satisfied for about half of the
simulated scenarios. For the rigid pavement in almost all scenarios, the
simulated checks are not satisfied. IRI testing is never satisfied on
both types of roads analyzed.
On freeways no test concerning transverse carking and joint
faulting is satisfied. Only in a few cases, (on highways) these two
tests (transverse carking and joint faulting) are satisfied. Finally,
the verification of the PSI is never satisfied for both types of roads
analyzed (freeway and highway). For the permanent strain (asphalt layer)
checks are almost never satisfied in the highway. They are almost always
satisfied on the freeway. For the total permanent strain, checks have
never been satisfied in the Highway and only in some cases are satisfied
in the freeway. Finally, the verification of the PSI is satisfied on the
highway. On the freeway, it is not satisfied for about half of the
simulated scenarios.
For the rigid pavement in almost all scenarios, the simulated
checks are not satisfied. IRI testing is never satisfied in both the
types of roads analyzed. On freeways no test concerning transverse
carking and joint faulting is satisfied. Only in a few cases, (on
highways) these two tests (transverse carking and joint faulting) are
satisfied. Finally, the verification of the PSI is never satisfied for
both types of roads analyzed (freeway and highway).
6. Conclusions
The comparison between the proposed solutions from the catalogue
and the results of simulations carried out using MEPDG showed that many
proposed solutions from the catalogue are very approximate. As
extensively discussed and illustrated for all types of pavements
examined, in many cases the checks are not satisfied. It is clear that
the assumptions introduced in the Italian CNR road pavement design
catalogue and specifically the assumptions adopted for the
characterization of climatic conditions should be modified. Therefore it
is necessary to revise the tool design and verification of the pavement,
through more sophisticated tools such as the MEPDG. The scenarios that
have not passed the tests, compared with the total examined, are
significant in number. It is believed on the basis of the information
obtained in this study that this approach (i.e. to revise the proposed
solutions of the catalogue with ME-PDG) is a good strategy to revise and
upgrade the Italian CNR road pavement design catalogue Catalogo delle
pavimentazioni stradali C.N.R.-B.U.-178, 1995.
Caption: Fig. 1. Map of the survey stations
Caption: Fig. 3. Simulation PSI decay: a--PSI decay highway one
carriageways--flexible pavement; b--PSI decay--freeway two
carriageways--fexible pavement
Caption: Fig. 4. Decay of the pavement--freeway/flexible pavement
after 20 years
Caption: Fig. 5. Decay of the pavement--highway/flexible pavement
after 20 years
Caption: Fig. 6. Simulation PSI decay: a--PSI decay freeway two
carriageways--semi-rigid pavement; b--PSI decay highway one
carriageways--semi-rigid pavement
Caption: Fig. 7. Decay of the pavement--freeway/semi-rigid pavement
after 20 years
Caption: Fig. 8. Decay of the pavement--highway/semi-rigid pavement
after 20 years
Caption: Fig. 9. Simulation PSI decay: a--highway rigid pavement;
b--freeway rigid pavement
Caption: Fig. 10. Decay of the pavement--freeway/rigid pavement
after 20 years
Caption: Fig. 11. Decay of the pavement--highway/rigid pavement
after 20 years
doi: 10.3846/bjrbe.2013.20
References
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Received 10 October 2012; accepted 5 March 2013
Daiva Zilioniene (1), Mario De Luca (2) [mail], Gianluca
Dell'Acqua (3)
(1) Dept of Roads, Vilnius Gediminas Technical University,
Saul?tekio al. 11, 10223 Vilnius, Lithuania
(2,3) Dept of Civil, Construction and Environmental Engineering,
University of Napoli Federico II, Via Claudio 21, 80125 Napoli, Italy
E-mails: (1)
[email protected]; (2)
[email protected];
(3)
[email protected]
Table 1. Equivalent classes in USA and Italy
USA Italy
According to the MEPDG According to the C.N.R.-B.U.
Guide 178, 1995
of the Federal Highway of the Italian National
Administration Research Council
Class Characteristic Class Characteristic
4 Buses 3 axis 14 Buses 2 axis
15 Buses 2 axis
16 Buses 2 axis
5 Truck 2 axis 1 Van 2 axis
2 Truck 2 axis
3 Truck 2 axis
4 Truck 2 axis
6 Truck 3 axis 5 Truck 3 axis
6 Truck 3 axis
9 Truck 5 axis 9 Truck 4 axis
10 Truck 4 axis
10 Truck 6 axis 11 Truck 5 axis
12 Truck 5 axis
13 Truck 5 axis
11 Trailer Truck 7 Trailer truck 4 axis
5 axis 8 Trailer Truck 5 axis
Table 2. Survey stations
Station Height Area/Town Scenarios
Survey
Station
Mezzoldo (BG) 1682 m Bergamo High Altitude--North
Edolo (BS) 720 m Brescia Middle Altitude--North
Lambrate (MI) 120 m Milano Lower Altitude--North
Pizzotrevescovi (MC) 1670 m Macerata High Altitude--Centre
Camerino (MC) 780 m Macerata Middle Altitude--Centre
Cerbara (PG) 288 m Perugia Lower Altitude--Centre
Montescuro (CS) 1671 m Cosenza High Altitude--South
Acri (CS) 750m 750 m Cosenza Middle Altitude--South
Martirano (CZ) 281 m Catanzaro Lower Altitude--South