Gradation-Based Framework for Asphalt Mixtures

Licentiate Thesis

Bernardita Lira Miranda

KTH, Royal Institute of Technology

School of Architecture and Built Environment

Department of Transport Science

Division of Highway and Railway Engineering

SE-100 44 Stockholm

April 2012

TRITA-TSC-LIC 12-001

ISBN 978-91-85539-81-9

©Bernardita Lira

2012

i

Abstract

Asphalt mixture microstructure is formed by aggregates, bitumen binder and air voids.

Aggregates make for up to 90% of the mixtures volume and the structure formed by them

will depend mostly on their size distribution and shape. The study presented in this thesis

has as main objective to develop a framework that allows the characterization of asphalt

mixtures based on the aggregates gradation and its impact on pavement performance.

Moreover, the study aims to identify the range of aggregate sizes which form the load

carrying structure, called Primary Structure, and determine its quality.

The method has been developed as a numerical procedure based on packing theory of

spheres. Parameters like porosity, coordination number and disruption factor of the Primary

Structure; and a binder distribution parameter for the different sub-structures have been

used to evaluate the quality of the load carrying structure and predict the impact on several

failure modes. The distribution of bitumen binder has been derived from a geometrical

model which relates porosity of the mixture with film thickness of particles considering the

overlapping reduction as the film grows. The model obtained is a closer approximation to a

physical characteristic of the compacted mixture separated according to different elements

of the structure.

The framework has been evaluated on several field and laboratory mixtures and predictions

have been made about their rutting performance and moisture resistance. The calculated

parameters have compared favourably with the performances reported from the field and

laboratory testing. The developed gradation analysis framework has proven to be a tool to

identify those mixtures with a poor rutting performance based on the gradation of the

aggregates.

The Gradation - Based Framework has satisfactory distinguished between good and bad

performance of asphalt mixtures when related to permanent deformation and moisture

damage. The calculated parameters have allowed identifying and understanding the main

mechanisms and variables involved in permanent deformation and moisture damage of

asphalt mixtures. The developed model can be used as a tool to determine the optimal

gradation to assure good performance for hot mix asphalt pavements.

Keywords: Asphalt, aggregate gradation, packing theory, asphalt microstructure, porosity,

film thickness, rutting, moisture damage.

iii

Acknowledgment

The work presented in this licentiate thesis has been carried out between June 2009 and

February 2012 at the division of Highway and Railway Engineering, School of Architecture

and the Built Environment at the Royal Institute of Technology, KTH.

I would like to express my gratitude to Trafikverket for the financial support to the project.

I would also like to thank my supervisors Professor Björn Birgisson and Dr. Denis Jelagin

for their guidance during this process. I am very grateful to Mr Måns Collin and Dr. Per

Redelius for all the great discussion that helped us understand and develop the final model.

I would like to thank my colleagues at the department which were always there to put a

smile in the difficult times. Also, nothing would have been possible without the invaluable

help of Mrs Agneta Arnius in all the administrative matters.

Finally, I would like to thank my husband Kristian for his support and patience and my

family in Chile that always believed in me.

Bernardita Lira

Stockholm, February 2012

v

List of enclosed papers

I. Lira, B., D. Jelagin, B. Birgisson, Gradation Based Framework for Asphalt Mixtures

Submitted to Journal of Materials and Structures, October 2011

II. Lira, B., D. Jelagin, B. Birgisson, Binder Distribution Model for Asphalt Mixtures

Based on Packing of the Primary Structure

To be submitted to International Journal of Pavement Engineering

vii

TABLE OF CONTENTS

Abstract

Keywords

Acknowledgements

List of enclosed papers

1. Introduction

2. Theoretical Model

3. Results

4. Discussion and Conclusions

5. Bibliography

Paper I. Gradation-Based Framework for Asphalt Mixtures. Lira, B., D. Jelagin, B.

Birgisson

Paper II. Binder Distribution Model for Asphalt Mixtures Based on Packing of the Primary

Structure. Lira, B., D. Jelagin, B. Birgisson

1

1. Introduction

The impact of aggregate gradation on the performance of asphalt mixtures has been

extensively studied through the years. Several studies, e.g. (Kandhal, et al., 1998),

(Nukunya, et al., 2001), (Birgisson, et al., 2004) have shown that there is a relationship

between aggregate particles size distribution and the resistance to cracking, rutting, ageing

and moisture damage. Furthermore, the way that aggregate particles, bitumen binder and air

voids interact with each other will determine how a mixture will respond to different

loading conditions ( (Campen, et al., 1959), (Kumar & Goetz, 1977)). Through studying

and understanding these interactions future design can be optimized by combining the

available materials in the best possible way.

The objective of the present project is to develop a framework to characterize asphalt

mixtures based on their microstructure. Asphalt mixture microstructure is formed mostly by

aggregate particles and the structure that will be formed depends mainly on their size

distribution, shape and concentration. Bitumen binder will then flow around the particles

forming a film around them and binding all the components together. The framework aims

to describe different types of mixtures depending on how the aggregates group, how the

bitumen is distributed among them and the resulting size and location of the air voids. This

configuration will finally determine the type of response that an asphalt mixture will have

during loading.

Experimental studies on granular material (e.g. Cundall, et al. 1982) have shown the

existence of stress-transmitting paths enclosing virtually stress free regions (Jaeger and

Nagel 1992). In particulate materials then, the load is transferred through chains of particles

and other smaller particles play the secondary role of preventing the main chain from

buckling (e. g. Santamarina 2001). Based on the observations mentioned above two sub-

structures within the aggregate particles have been defined: the Primary Structure, range of

sizes which due to their concentration provide the load bearing capacity of the mixture, and

the Secondary Structure, material smaller than the first one which provides stability to the

structure (Lira, et al., 2011). Packing theory for spherical particles has been used to identify

each sub-structure.

Results from field and laboratory mixtures have been used to validate the relationship

between the Primary Structure content and rutting performance. The model also proposes a

distribution system of the bitumen binder around the Primary and Secondary Structure. It is

shown that the thickness of the film around both structures has a great influence on not only

permanent deformation but also on the resistance for moisture damage on asphalt mixtures

(Lira, et al., 2012).

2

2. Theoretical Model

Mineral aggregates used for pavement construction are largely obtained from local

suppliers. A consequence of this is that certain regions will have better quality materials

than others. It is for this reason that is of key importance to understand the way aggregate

particles interact, and in that way give a tool to engineer mixtures to obtain the best

performance possible according to the available materials.

Aggregate´s physical characteristics, such as resistance to abrasion and strength, are

determined primarily by its mineral composition. However, the production process can

significantly improve the quality of the aggregate by elimination of weaker rock layers and

by the effect of crushing on the particle shape and gradation of the aggregate. Aggregate

gradation is the distribution of particle sizes expressed as a per cent of the total weight.

Gradation is determined by sieve analysis and is normally expressed as total per cent

passing various sieve sizes. Aggregate gradation is certainly one of the most important

properties of an HMA (hot mix asphalt) design. It affects almost all the important properties

of an asphalt mixture, including stiffness, stability, durability, permeability, workability,

fatigue resistance, friction, and resistance to moisture damage (Brown, et al., 2009).

Early studies have proposed that the best gradation for HMA is the one that gives the

densest packing, increasing stability through increased interparticle contact (Fuller &

Thompson, 1907) (Goode & Lufsey, 1962). However, there must be sufficient air void

space to allow enough bitumen binder to be incorporated to ensure durability and

workability, while still leaving some air voids in the mixture to avoid bleeding or rutting.

In 2006 a conceptual and theoretical approach to evaluate coarse aggregate structure based

on gradation was developed by (Roque, et al. 2006). The method identifies the load

carrying size range (DASR) in the mixtures and relates the quality of this structure to the

asphalt mixture performance. However, the DASR identification procedure is valid strictly

for gradations composed of discrete particle size with a size ratio 2:1.

Packing theory is a tool that allows the analysis of aggregate gradations based on the

geometrically systematic arrangement of uniform spheres. The term packing is applied to

any manner of arrangement of solid units in which each constituent unit is supported and

held in place in the earth´s gravitational field by tangent contact with its neighbour (Graton

& Fraser, 1935). From a two-dimensional geometric view there are two different types of

layers, a square and a rhombic layer, as shown in Figure 1. When combining those two

different layers in a three-dimensional space, six different arrangements are obtained. It can

be observed in Table 1 that only four are presented as some of the square arrangements are

repeated by the rhombic ones. By observing the values of porosities it can be determined

that the simple cubic packing is the loosest state and the rhombohedral packing is the

densest one.

3

Table 1. Properties of various packing arrangements

Tangent

neighbours

Volume of the

unit cell

Volume of unit

void

Porosity

Simple Cubic 6 8,00 R3

3,81 R3 47,67%

Orthorhombic 8 6,93 R3 2,74 R

3 39,54%

Tetragonal –

sphenoidal

10 6,00 R3 1,81 R

3 30,19%

Rhombohedral 12 5,66 R3 1,47 R

3 25,95%

Figure 1. Types of layer. A) Square layer; B) rhombic layer (Graton & Fraser, 1935)

For an assemblage of equal-sized particles to be in contact with each other then they must

have porosity not higher than the loosest state given by packing theory. In order to transfer

load, stones need to form a continuous network, which means, the concentration of the load

carrying range has to be minimum around 45%. Concentration can be defined as follows:

n

ret

tot

W

W [1]

where nretW represents the weight of aggregate retained at sieve n and totW is the total weight

of aggregates. Based on standard practice is acceptable to assume that such a concentration

is not achieved by only one size material in a gradation. Packing theory can be used to

define the range of material where stone-to-stone contact is assured and a concentration

higher than 45% can be achieved. This analysis is done by checking the interaction between

consecutive sieve sizes and determining if their individual concentrations are enough to

assure contact between particles of both sizes.

For this analysis four initial assumptions are taken:

All particles are considered spherical.

The aggregate particles are uniformly distributed within the total volume.

4

The material retained at a certain sieve size presents a continuous size distribution

characterized by the parameter B. This means that the mean diameter ( nD ) at a sieve

size can be described as presented in[2], where minD is the opening of the sieve and

maxD is the opening of the previous sieve.

min max nD B D D [2]

The maximum concentration of spheres of two different sizes is equivalent to a

rhombohedral packing type (1

max

&0,74

n nD D

).

The following model identifies three different groups within the mineral aggregates: the

Primary Structure, the Secondary Structure and the oversized material as shown in Figure 2.

The Primary Structure (PS) is a range of sizes in the gradation that due to its concentration

provides the load bearing capacity for the mix. The PS acts as a central core where all the

particles are connected with each other, and the more connections there are the stronger the

core is. The Secondary Structure (SS) is formed by the particles with a smaller size than the

PS. The SS fills in the voids between the PS particles and provides stability to the PS.

Finally, there are oversized particles which size is bigger than the PS and which do not

contribute to any load carrying. To determine the PS range the analysis must consider the

tightest and loosest case in which two consecutive sizes can have stone-to-stone contact,

which are represented in Figure 3.

Figure 2. Gradation Analysis Framework

0

10

20

30

40

50

60

70

80

90

100

0.0

75

0.1

50.3

0

0.6

0

1.1

8

2.3

6

4.7

5

9.5

12.

5

19.

0

Sieve size 0.45

[mm]

% P

ass

ing

5

Figure 3. Tightest (a.) and loosest (b.) configurations of the Primary Structure

For two consecutive sieve sizes with diameter 1 and n nD D and concentrations 1 and n n

respectively, the average particle diameter (avgD ) can be calculated as:

1 1

1

n n n navg

n n

D DD [3]

The tightest case is built upon the addition of smaller spheres to one-sized un-compacted

bigger spheres. The bigger spheres will present a simple cubic configuration as shown on

Figure 3 previous the addition of smaller spheres. When these are added the porosity

decreases until a minimum representing a rhombohedral packing, assuring the contact

between the smaller spheres and the surrounding bigger ones. Numerically this can be

expressed as:

1 10,52 0,22

0,703 0,2970,74

n navg n n

D DD D D [4]

In the loosest case the bigger spheres have no contact with each other, allowing the smaller

spheres to be positioned in between them. To assure contact between both sized spheres

then the distance between the bigger spheres must not be bigger than the diameter of the

smaller spheres. This can be calculated by using the separation distance between the

surfaces of two neighbouring elements (Coussot, 2005) as described in[5].

1

3max2 1

h r [5]

6

The solution for two contiguous sieve sizes can be calculated considering 1 nh D ,

/ 2 nr D , max 0,74 and φ as the volume fraction of the spheres belonging to the sieve

size “n”. This will give the following relation[6]:

1

3

1

1

31

0,742 1

2

0,741

nn

n

n

DD

D

D

[6]

Taking into consideration different sieve systems it is possible to notice that the relationship

1 / n nD D moves between γmax=0,77 and γmin=0,47 giving φ=0,13 and φ=0,23

respectively. Contact between particles will then be assured for a minimum concentration

of the biggest sphere of 0,23. This can be expressed as:

1 10,23 0,51

0,311 0,6890,74

n navg n n

D DD D D [7]

Finally, interaction between two contiguous sieve sizes will occur if the average diameter

for the particles is within the following limits, as given by equation[8]. A summary of the

process to determine the Primary Structure is given in Figure 4.

1 10,311 0,689 0,703 0,297 n n avg n nD D D D D [8]

7

Porosity of the Primary Structure

The relation between performance of asphalt mixtures and gradation characteristics is

influenced by several aggregate properties, e.g. stone texture, shape and stiffness. In the

following framework only the influence of the whole structure formed by the stones is

considered, which is characterized by porosity of the assemblage and contact points due to

their contribution to shear resistance. The calculation of the Primary Structure Porosity is

based on the general definition of porosity as a measure of the void spaces in a material,

given as a fraction of the volume of voids over the total volume (VT). The volume of voids

for the Primary Structure is everything in the mixture that is not considered to be part of the

PS, and the total volume of the mixture is all except the volume of particles bigger than the

Primary Structure. In[9] VaSS

is the volume of aggregate belonging to the Secondary

From Gradation: - sieve sizes D1 and D

2

- per cent retained at each sieve φ1 and φ

2

𝐷𝑎𝑣𝑔 =𝐷 1𝜑1 + 𝐷 2𝜑2𝜑1 + 𝜑2

Calculation of the

Average Particle Size

𝑚𝑖𝑛 = 0,311 ∗ 𝐷1 + 0,689 ∗ 𝐷2 𝑚𝑎𝑥 = 0,703 ∗ 𝐷1 + 0,297 ∗ 𝐷2

Calculation of the

Interaction Range Limits

𝑚𝑖𝑛 ≤ 𝐷𝑎𝑣𝑔 ≤ 𝑚𝑎𝑥 Check Interaction

NO YES

D1 and D

2 have not

enough interaction to

belong to the Primary

Structure

D1 and D

2 do interact and the

might belong to the Primary

Structure

Continue the analysis with the next sieve sizes until Dlast

Figure 4. Primary Structure Identification

8

Structure, Vaoversized

is the volume of aggregate bigger than the Primary Structure, Vbtot

is

the total volume of bitumen binder, VbabsPS

is the volume of bitumen binder absorbed by the

Primary Structure, and Vv is the total volume of voids.

SS tot absPS

V a b v bPS oversized

T T a

V V V V V

V V V [9]

Coordination number (m) is the average of contact points per particle and can be calculated

using the relationship in[10], where η is the porosity, based on packing theory:

1,0692,827 m [10]

Disruption Factor

The Disruption Factor (DF) is a parameter developed to evaluate the potential of the

Secondary Structure to disrupt the Primary Structure (Guarin 2009; Guarin, et al. 2011

under revision). The DF is calculated as following:

Volume of potentially disruptive particles

Volume of PS voids

dp

PS

v

dp

dp

sb

VDF

V

WV

G

[11]

The weight of potentially disruptive particles considers the material belonging to the SS

bigger than the average void size of the PS, which depends on the packing arrangement

(porosity) of the PS particles.

Rutting performance is related to the mixtures capacity to resist shear. An adequate amount

of Secondary Structure, specially the potentially disruptive particles, will benefit the

mixture in the load carrying capacity.

Bitumen Distribution Parameter (t)

The developed framework proposes a solution to calculate the coating thickness of

aggregates in a hierarchical order according to particle size and the packing configuration

of the Primary Structure.

In the following model particles with size below the last sieve size (fines) and the bitumen

binder are considered to form a composite material called mastic. This mastic is distributed

around the Secondary Structure with a certain thickness (tSS). If this film is too thin then the

particles of the Secondary Structure will act as a granular material instead of a composite

9

one, leading to a brittle response under loading. The mixture of mastic and Secondary

Structure will then flow around the Primary Structure, coating it with a certain thickness

(tPS). The thickness of this second coating will depend on the packing configuration of the

Primary Structure and the per cent of air voids in the mixture, as the coat will represent the

distance between the air void and the aggregate-binder interface.

The relationship between film thickness and porosity developed by (Cooke & Rowe, 1999)

has been used to determine tSS and tPS. This relationship considers the different packing

arrangements that a set of spherical particles can present, and the change in porosity when

varying the film thickness taking into consideration the overlapping of the film as it grows.

The particles belonging to the Secondary Structure are always considered to be packed in

the densest possible way (φ=0,74), as their porosities are very low as calculated according

to[12]. However, the porosities of the Primary Structure will vary from the tightest case to

very loose; giving a dependency of the film thickness on the packing arrangement.

f tot eff

v a b vSS SS f tot eff

T a a b v

V V V V

V V V V V [12]

Once calculated SS and (the porosity used to determine the PS coating thickness is the

one of the whole mixture and notPS ), the graph presented in Figure 5 is used to estimate a

dimensionless parameter 2 /t pL d which represents the thickness of the film ( tL ) related to

the particles diameter (pd ). The diameter of the particle will be the weighted average size

of the sub-structure used.

Figure 5. Relation between porosity and film thickness as developed by (Cooke & Rowe,

1999)

0 0.1 0.2 0.3 0.4 0.5 0.6 0.70

0.1

0.2

0.3

0.4

0.5

Dimensionless parameter, 2Lt/dp

Po

rosi

ty,

Simple Cubic

Orthorhombic

Tetragonal

Rhombohedral

10

In Figure 5 only the theoretical packing arrangements are defined, but as the coordination

number for different mixtures is the average of contact points per volume, then

interpolation has to be done between the theoretical curves. In the case of having a mixture

with a coordination number less than 6 (simple cubic), then the distance between coated

particles must be taken into account for the final coating thickness. For cases with m

11

to each other producing a brittle response to loading. This reduces significantly the capacity

of a mixture to resist permanent deformation. In the case of the Primary Structure, low

coating thickness affects the durability of the mixture by increasing the possibility of rutting

due to densification from the traffic. However, low thickness around the PS means

interconnected air voids which help the drainage of moisture trapped in the mix. In the

opposite case, when the coating thickness around the PS is too thick there is a risk of losing

the contact points between the PS particles, affecting the general load bearing capacity of

the mixture.

Figure 6. Results for Field Mixtures

Figure 6 presents the results for WesTrack and NCAT mixtures. It is possible to observe

how the framework is capable to identify those mixtures with rutting problems isolating

them to the extremes. High content of material acting as the load bearer structure produces

mixtures that suffer high permanent deformation. This is due to lack of supporting material

providing stability under loading. The Disruption Factor shows this effect as mixtures with

poor rutting performance have a higher potential to have their PS disrupted. Furthermore,

these “bad” mixtures also present low film thickness around both structures. Low thickness

40 50 60 700

5

10

15

20

% of PS over the total mix volume

Ru

t D

ep

th[m

m]

per

mil

lio

n E

SA

Ls

WesTrack

NCAT E

NCAT N

0 1 2 3 4 50

5

10

15

20

Disruption Factor

Ru

t D

ep

th[m

m]

per

mil

lio

n E

SA

Ls

WesTrack

NCAT E

NCAT N

0 0.2 0.4 0.6 0.80

5

10

15

20

tSS

[mm]

Ru

t D

ep

th[m

m]

per

mil

lio

n E

SA

Ls

WesTrack

NCAT E

NCAT N

0.5 1 1.5 20

5

10

15

20

tPS

[mm]

Ru

t D

ep

th[m

m]

per

mil

lio

n E

SA

Ls

WesTrack

NCAT E

NCAT N

12

around the SS shows a lack of bond between the supporting material, and low thickness

around the PS shows lack of supporting material in general.

Figure 7 shows the results for laboratory mixtures tested with the Asphalt Pavement

Analyser (APA). As it can be observed in the left upper plot there is no clear tendency for

the material from (Guarin, et al., 2011), however the limestone mixtures from (Birgisson, et

al., 2004) show that there is a minimum rutting depth for mixtures with a PS content around

45 – 50% and it increases towards the extremes. Once again, it can be observed in the

Disruption Factor results that the rutting depth increases for DF>1.

Figure 7. Results for Laboratory mixtures with APA test

In (Birgisson, et al., 2005) two groups of aggregates were used: oolitic limestone that in the

past has not shown significant stripping potential and crushed Georgia granite that has

shown potential to stripping. All mixtures were made up of four components: coarse

aggregate, fine aggregate, screenings and mineral filler. They were blended together in

different proportions providing six HMA mixtures for each mineral aggregate type which

were volumetrically equivalent to each other. The mixtures were designed according to the

SuperPave volumetric mix design method and all specimens were compacted on the IPC

Servopac SuperPave gyratoric compactor to 7-8% air voids.

20 30 40 50 600

2

4

6

8

10

% of PS over the total mix volume

AP

A R

ut

[mm

]

Granite (G)

Limestone (G)

Limestone (B)

0 0.5 1 1.50

2

4

6

8

10

Disruption Factor

AP

A R

ut

[mm

]

Granite (G)

Limestone (G)

Limestone (B)

0.08 0.1 0.12 0.140

2

4

6

8

10

tSS

[mm]

AP

A R

ut

[mm

]

Granite (G)

Limestone (G)

Limestone (B)

0.5 1 1.5 20

2

4

6

8

10

tPS

[mm]

AP

A R

ut

[mm

]

Granite (G)

Limestone (G)

Limestone (B)

13

Using digital images from X-ray Computed Tomographic imaging the air void size

distribution and number of air voids was determined for each specimen. In Figure 8 the

relation between air void size and thickness of film around the Primary and Secondary

Structures is presented. It can be observed that the higher tSS then the particles are better

“glued” together making the air voids bigger but fewer. The opposite trend is observed with

tPS as the space in between the particles will clearly decrease with thicker film around them.

Figure 8. Correlation between air void size and binder distribution

The granite mixtures were tested with the Hamburg Wheel Tracking Device to determine

their natural resistance too moisture damage. The test specifications determine that the test

is continued until either rut of 12,5 mm depth is measured or the number of loading cycles

reaches 20000. The number of cycles to strip, Ns, is defined as the loading cycle where the

rate of permanent displacement measured during the test markedly increases.

Figure 9. Hamburg wheel Device test results for granite mixtures

0.09 0.1 0.11 0.12 0.13 0.14 0.15

0.8

1

1.2

1.4

1.6

tSS

[mm]

Av

era

ge V

oid

Dia

mete

r [m

m]

Limestone

Granite

0.4 0.6 0.8 1 1.2

0.8

1

1.2

1.4

1.6

tPS

[mm]

Av

era

ge V

oid

Dia

mete

r [m

m]

Limestone

Granite

0.08 0.1 0.12 0.14 0.160.8

1

1.2

1.4

1.6

1.8

2

2.2x 10

4

tSS

[mm]

N

of

cy

cle

s to

str

ip

0.4 0.6 0.8 1 1.2 1.40.8

1

1.2

1.4

1.6

1.8

2

2.2x 10

4

tPS

[mm]

N

of

cy

cle

s to

str

ip

14

The results given in Figure 9 show the number of cycles to strip related to the thickness

around Primary and Secondary Structure. It can be observed that for a low value of tSS

mixtures strip very fast as the stones have no protection against moisture, and for a ticker

coating around the SS the air pockets are smaller but more numerous. In this case the

thickness of the PS is also high and the more air voids there are the bigger the surface are

exposed to water. It is possible to observe that there is an optimum tSS for which the

resistance to stripping is highest. At this level the stones in the SS are protected against

moisture and at the same time they leave enough open channels for the water to drain as tPS

is low.

Figure 10. Moisture analysis for limestone and granite mixtures

Figure 10 presents the energy ratio results of limestone and granite mixtures. Energy ratio is

a parameter that measures the fracture resistance of mixtures based on the dissipated creep

strain energy, forming a basis for a performance-based fracture criterion for flexible

pavements (Birgisson, et al., 2005). Since it is known that the fracture resistance of a

mixture is strongly affected by moisture damage, by evaluating the energy ratio of the

conditioned and the unconditioned samples a measure of the moisture damage is given.

According to the given definition, moisture damage decreases with higher ERc/ERu. The

influence of the film thickness around the PS is very well captured by the limestones, as

lower films means bigger air voids providing a proper drainage for the water trapped in the

structure as well as there is less mixtures exposed to the moisture. It can be noticed in this

type of testing that granite mixtures do not present such a clear response as in the Hamburg

Wheel Tracking Device. This is due to the conditioning of the samples, as for energy ratio

testing the samples are forced into saturation creating conditions which are unreal to certain

types of minerals, like granites, provoking a general failure of the samples.

0.08 0.1 0.12 0.14 0.160.2

0.4

0.6

0.8

1

1.2

tSS

[mm]

ER

c/E

Ru

Limestone

Granite

0.4 0.6 0.8 1 1.2 1.40.2

0.4

0.6

0.8

1

1.2

tPS

[mm]

ER

c/E

Ru

Limestone

Granite

15

4. Discussion and Conclusions

The following thesis presents a framework developed to characterize asphalt mixtures

based on the aggregates gradation and the structure formed by them. The framework

identifies the range of material which forms the Primary Structure and is the main load

bearing assembly. The amount of material belonging to the Primary Structure may

influence the load response of a mixture and can be characterized by its porosity and

coordination number according to packing theory of spheres. Particles that are smaller than

the Primary Structure are called the Secondary Structure and they provide stability to the

main network by keeping it in place, while particles that are bigger than the Primary

Structure are just considered to be floating in the mixture as their concentration is not

enough to influence the load carrying ability of the mixture.

A complete characterization of asphalt’s microstructure is achieved by determining the way

that the bitumen binder is distributed and how this affects the size and distribution of the air

voids. For this purpose a hierarchical distribution system has been developed which

assumes the following sequence: bitumen binder and fines creates mastic which covers the

particles of the Secondary Structure; this composite is then the material that coats the

Primary Structure. Both thicknesses have been calculated using a previous relationship

based on packing of the particles and the overlapping of the film as it grows. This method

has given a geometrical solution to binder distribution for each sub-structure, which

increases the understanding of asphalt mixture microstructure.

The framework has been validated by taking mixtures with known field rutting

performance and laboratory mixtures that have been tested for both rutting and moisture

damage. The range for Primary and Secondary Structure as well as porosity of the Primary

Structure, coordination number and the binder distribution parameter for each structure

have been calculated for each one of the mixtures. Results obtained show a favourable

relation between the per cent of material that the Primary Structure represents of the whole

mixture and the resistance to rutting, suggesting that there might be an optimum of material

that would give a minimum permanent deformation. Film thickness of the Primary

Structure has shown to be a key parameter to prevent moisture damage, as it is directly

related to the size of the air voids and the protection of the aggregate/mastic interface.

The developed framework is a tool to engineer mixtures and optimize the use of available

materials. The advantages of the model is its flexibility for any type of sieve system used

and its ability to include different size distribution within a sieve size, reducing the

limitations from previously developed models. The assumption of having aggregates as

spherical particles has shown, even though a very rough approximation, to give a good co-

relation to performance on asphalt mixtures. It is still desirable to include the influence of

aggregates shape and texture, and the differences on mixture response depending on the

mineral composition of the aggregates. Packing theory has proven that independent of the

16

shape of the particles the concept of contact points and porosity can be used to describe the

structure formed by the aggregates. The biggest potential of the developed framework can

be seen from the simulation side, as it works as a tool to reduce the number of variables in

asphalt microstructure.

The Gradation - Based Framework has satisfactory distinguished between good and bad

performance of asphalt mixtures when related to permanent deformation and moisture

damage. Further work is needed to calibrate the model based on x-ray tomography or

similar tools, to determine the range of validity of the formulations and to identify the

critical ranges for Primary Structure content and coating thickness for optimal performance

and more durable asphalt pavements. The developed model can be used as a tool to

determine the optimal gradation to assure good performance for hot mix asphalt pavements.

17

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