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Proefschrift

ter verkrijging van de graad van doctor aan de Technische Universiteit Delft,

RSJH]DJYDQGH5HFWRU0DJQLILFXV3URILU.&K$0/X\EHQ voorzitter van het College voor Promoties,

in het openbaar te verdedigen op maandag 7 december, 2015 om 10:00 uur

Door

Mirella Maria VILLANI

INGEGNERE CIVILE

Composition of the doctoral committee:

Rector Magnificus Technische Universiteit Delft, chairman

Prof. dr. A. Scarpas Technische Universiteit Delft, promoter

Independent members:

Prof. dr. Ir. S.M.J.G. Erkens Technische Universiteit Delft

Prof. dr. E. Masad Texas A&M University at Qatar

Prof. dr. A. Loizos National Technical University of Athens

Prof. dr. A. D’Andrea Sapienza, University of Rome

Dr. D. Woodward University of Ulster

Prof. dr. ir. H.E.J.G. Schlangen Technische Universiteit Delft, reserve lid

Published and distributed by: Section of Pavement Engineering

Faculty of Civil Engineering & Geosciences Delft University of Technology

P.O. Box 5048, 2600 GA Delft, The Netherlands

m.m.villani@tudelft.nl, mirella.villani@gmail.com.

© 2015 by Mirella Maria Villani Printed by CPI Koninklijke Wohrmann ISBN 978-94-6203-955-1

All rights reserved. No part of this material protected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system, without written consent from the publisher.











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‘Twenty years from now you will be more disappointed by the things you didn't do than by the ones you did do. So throw off the bowlines. Sail away from the safe harbor. Catch the trade winds in your sails. Explore. Dream. Discover.’ – Mark Twain

Fresh from the AAPT scholarship, I was asked to give an inspirational talk to new PhD candidates. I started thinking back at my experience and I realized, inspired by the quote above, that the easier way to explain what is doing a PhD is to compare it with a long sailing trip. My point is that a PhD is not an activity that you can do alone and for a definite amount of time but more a long term goal to which you have to put all your time, all your effort and all your passion. Currents can be strong, certainties comes and go, research is very difficult to handle, so in order to get through your trip you need to stay focus and to rely on a strong and a multidisciplinary Crew. Now that this trip got to an end, it is finally time to thanks all the Captains and Sailors that have been helping me in reaching my destination.

I would like to thanks Prof. A. Scarpas. He has been a captain, a mentor and a friend. It was with his support that I have left the ‘safe harbor’ with the SKIDSAFE catamaran. I caught the first wind under his control and he helped me in finding the right wind. We stopped together in several harbors to communicate and share ideas with other travelers and we have done together research, management and dissemination for several projects we were involved.

I have learned so much about Tensors and Programming from our interaction. Dr. Arian de Bondt and Radjan Khedoe from OOMS Civiel have been working with me in the design, validation and use of the the new device and for the asphalt testing campaign. Our discussions over the constructions and protocols details have always been very productive. I am very thankful for their constant help and daily technical and moral support. Regarding the OOMS crew, I would also like to thanks all the members particularly Peter Bijkerk, Dave Long and Fred Spieard for their technical and moral support.

Important Boats have been sailing with the TUDelft and OOMS Civiel Crew during this PhD and I am thankful to their Captains and to their Crew for their support: Dr. I. Artamendi from Aggregate Industries, Dr. M. Kane from IFSTTAR and Prof. A Loizos from NTUA. I would like to mention another big Crew to which I owe immense gratitude for ackwnowledging my research by awarding it with a very prestigious and generous award: the Association of Asphalt Paving Technologists.

I would like to thank also Prof. A. D’Andrea for introducing me on the asphalt world and for his ‘asphalt and soil lessons’. By calling me a ‘force of nature’ during my MSc defence, he reminds me that I can fight also against the strongest sea. I would also like to thanks Prof. Erkens, Prof. Masad and Dr. Woodward for our inspiring discussions and finally all the colleagues and friends at TU Delft. I would like also to thank all the friends that have been supporting me in these years when the see was calm but also when it was very rough. Thanks Federica, Giovanna, Loredana, Maureen, Michele, Niki, and Sasa.

Finally, I would like to thanks my family and my husband Richard. Their infinite and unconditional support, their ideas, suggestions, also at a technical level, had a radical impact on my work and on my life. Their love, through the difficult storms we went through in these years, guided me to the graduation harbor. They well known that I could never have reached it without them.











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Skid resistance in asphalt concrete mixes (AC) is recognized as a major societal issue since it is of essence for road safety. Loss of skid resistance can have dramatic material and loss of life consequences.

Given the awareness of the problem and the lack of fundamental knowledge on its causes and solutions, this thesis examines, at a more fundamental level, the processes taking place at the interface between the pavement surface and the rubber treads in order to identify and investigate the controlling parameters influencing skid resistance of Asphalt Concrete mixes.

Starting from the component level, bitumen and aggregate characteristics are presented. The various bitumen properties are reported and the results of a mineralogical and mechanical aggregate characterization are discussed. Due to the fundamental role of the bulk behavior of the AC and the rubber types, an extensive laboratory testing campaign was performed on three different mixes (Porous Asphalt, Stone Mastic Asphalt and Dense Graded Mix). Uniaxial monotonic tests, relaxation and creep tests have been performed, in tension and in compression, for various strain rates, displacement and load levels at the temperatures of

elastic component acting in series with a stress dependent viscous component. A novel computational scheme has been developed for the solution of the coupled system of equations expressing the interdependent response of these two in-series components. An explicit, mechanistic parameter determination procedure is presented for the laboratory determination of all necessary model parameters. Examples of model parameter determination and utilization for prediction of the response of a recycled asphalt mix and a stone mastic asphalt mix are presented.

In order to identify the controlling parameters at the interface, an innovative Skid Resistance Interface Testing Device (SR-ITD®) was designed, validated and utilized. By means of this device, various combinations of slip velocity, pressure, AC mix types and rubber types have been considered, providing a better understanding of the frictional response of AC mixes and allowing identifying the paramount role of temperature. The AC surface characteristics and the variation of the AC surface due to the progressive polishing action of the wheels has been monitored by translating the data from a non-contact laser profilometer into fractal plots. Finally, on the basis of laboratory evidence and computational studies, Finite Element Analyses show the influence of the different parameters in pavement strains.











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Stroefheid in asfaltbetonmengsels (AC) wordt erkend als een belangrijke maatschappelijke kwestie, omdat het van essentieel belang is voor de verkeersveiligheid. Verlies van stroefheid kan dramatisch materiaal verlies en het verlies van het levens tot gevolg hebben.

Gezien de bewustwording over het probleem en het ontbreken van fundamentele kennis over de oorzaken en oplossingen, onderzoekt dit proefschrift, op een meer fundamenteel niveau, de processen die plaatsvinden in de interface tussen het wegdek en het rubberen bandloopvlak om zo de controlerende parameters, die de stroefheid van asfalt beton mixen beïnvloeden, te identificeren en te kwantificeren.

Bitumen- en aggregaatkenmerken worden gepresenteerd, te beginnen vanaf component niveau. De verschillende bitumeneigenschappen worden beschreven en de resultaten van een mineralogische en mechanische aggregaatkarakterisatie worden besproken. Vanwege de fundamentele rol van het bulkgedrag van het AC en de rubber types, is een uitgebreide laboratoriumtestcampagne uitgevoerd op drie verschillende mixen (ZOAB, Steen mastiekasfalt en AC10). Uniaxiale monotone testen, relaxatie- en kruiptesten zijn uitgevoerd

lineaire visco-elastische component in serie met een spanningsafhankelijke visceuze component. Een nieuwe rekenkundige methodiek is ontwikkeld voor het oplossen van het gekoppelde systeem van vergelijkingen, die het onderling afhankelijke gedrag van deze twee in serie gekoppelde componenten beschrijven.

Een expliciete, mechanistische parameterbepalingsprocedure wordt gepresenteerd voor de bepaling van alle noodzakelijke modelparameters in het laboratorium. Voorbeelden van modelparameterbepaling en het gebruik voor het voorspellen van de respons van een gerecyclede asfaltmix en een Steen mastiekasfalt asfaltmix worden gepresenteerd. Om de controlerende parameters te identificeren in de interface, werd een innovatief Stroefheid Interface Testing Device (SR-ITD®) ontwikkeld, gevalideerd en gebruikt. Met dit apparaat zijn verschillende combinaties van glijsnelheid, druk, AC mix types en rubbersoorten bekeken, wat een beter begrip van de wrijvingsrespons van AC mixen opleverde en een betere identificatie van de dominante rol van de temperatuur.

De AC oppervlakte-eigenschappen en de variatie van het AC oppervlak door de geleidelijke polijstende werking van de wielen wordt gecontroleerd door het vertalen van de gegevens van een non-contact laser profilometer in fractal plots.

Tot slot, op basis van zowel het laboratoriumbewijs als de computerstudies, laten de eindige-elementenberekeningen de invloed zien van de verschillende parameters op de vervorming van een asfaltlaag.









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‘Great things are done by a series of small things brought together’ - Vincent Van Gogh



1. Introduction ... 1

1.1 Road Safety and skid resistance ... 1

1.2 Aim of this research ... 2

1.3 Research methodology ... 3

1.4 Content overview ... 4

2. Literature review ... 7

2.2.3 Constitutive models for AC mixes ... 10

2.3 Rubber characteristics and constitutive models ... 12

2.4 Basic concept of friction ... 13

2.5 Skid resistance: relevant factors ... 14

2.5.1 Pavement surface characteristics ... 15

2.5.2 Tire properties ... 19

2.5.3 Vehicle Operating Factors ... 20

2.5.4 Environmental conditions ... 21

2.6 Evaluation of friction ... 21

2.6.1 Friction and polishing characteristics evaluation in a laboratory environment 22 2.6.2 Evaluation of Skid resistance in situ ... 27

2.7 Available friction models ... 27

2.8 Lessons learnt from the literature review ... 29

3. AC experimental testing campaign ... 31

3.2.1 Mix design ... 32

3.3 Characterization of aggregates ... 34

3.3.1 Mineralogy ... 34

3.3.2 Physical and mechanical aggregate tests ... 36

3.4 AC mixes mechanical characterization ... 38

3.4.1 Specimen preparation procedure ... 39

3.4.2 Test Set-Up ... 41

3.4.3 Uniaxial monotonic tests ... 41

3.4.4 Relaxation tests ... 43

3.4.5 Creep tests ... 46

4. AC Constitutive Model and Mechanistic Parameter Determination Procedure ... 51

4.1 Introduction ... 51

4.2 Laboratory tests on AC mixes containing recycled asphalt material ... 52

4.2.1 Sample characteristics and test protocol ... 52

4.3 Energy based 3D constitutive model for asphaltic materials ... 53

4.3.1 Preliminaries ... 53

4.4.1 Preliminaries ... 60

4.4.2 Parameter determination for the HE’component ... 61

4.4.3 Parameter determination for the HEe component ... 63

4.4.4 Parameter determination for the V_ηcomponent ... 65

4.4.5 Parameter determination for the VΓcomponent ... 71

4.5 RAC model application ... 73

4.5.1 Test I: Comparison between different load frequencies ... 75

4.5.2 Test II: Comparison between confined and unconfined specimens ... 75

4.5.3 Test III: Comparison between different rest periods ... 76

4.6 SMA mix simulation via the RAC model ... 77

5. Rubber characterization ... 81

5.1 Introduction ... 81

5.2 Rubber characterization ... 81

5.2.1 Viscoelastic theory ... 82

5.3 Evaluation of the rubber parameters on the basis of DSR tests ... 87

6. Skid Resistance Interface Testing Device ... 89

6.1 Introduction ... 89

6.2 Design choices behind the new device ... 90

6.3 Design of the new device ... 91

6.3.1 Loading frame ... 91

6.3.2 Rotating pan ... 94

6.4 Development of a testing protocol ... 96

6.4.1 Influence of temperature development on constant velocity tests ... 98

6.4.2 Braking test protocol ... 100

6.5 Stone braking tests ... 100

6.5.1 Influence of rubber type for stone braking test ... 103

6.6 AC mixes braking tests ... 106

6.6.1 Influence of rubber type for AC mixes for the braking test ... 108

6.7 AC mixes polishing tests ... 111

7. Fractal method and finite element analyses ... 115

7.2.3 Application of the fractal approach for the study of the evolution of surface

damage ... 122

7.2.4 Application of the fractal approach for the study of the influence of the aggregate type and grading on friction and surface damage ... 124

7.3 Hysteretic friction ... 125

7.4 Zener model ... 129

7.5 Friction model ... 130

7.6 Pavement modelling: introduction ... 130

7.7 Geometry and boundary conditions ... 131

7.8 Material properties ... 132

7.9 Load application ... 132

7.10 Results ... 134

8. Conclusions ... 137

8.1 General conclusions ... 137

8.2 Back to the research questions ... 137

9. Appendix A Asphalt testing ... 141

A.1 Database description ... 141

A.2 Monotonic displacement controlled compression tests (20 oC) ... 148

A.3 Monotonic displacement controlled compression tests (40 oC) ... 150

A.4 Monotonic displacement controlled tension tests (20 oC) ... 153

A.5 Monotonic displacement controlled tension tests (40 oC) ... 156

A.6 Displacement controlled relaxation compression tests (20 oC) ... 159

A.7 Displacement controlled relaxation compression tests (40 oC) ... 162

A.8 Displacement controlled relaxation tension tests (20 oC) ... 165

A.9 Displacement controlled relaxation tension tests (40 oC) ... 168

A.10 Creep tests in compression (20 oC) ... 169

A.11Creep tests in compression (40 oC) ... 171

A.12 Creep tests in tension (20 oC) ... 173

A.13 Creep tests in tension (40 oC) ... 175

Appendix B Clausius Plank local dissipation inequality ... 177

 Appendix C First P. K. component in principal stretches ... 181

Appendix F Braking protocol ... 187

F.1 Pre-test checks ... 187

F.2 Braking test procedure ... 188

Appendix G Polishing protocol ... 189

G.1 Pre-test checks ... 189 G.2 Polishing procedure ... 189  References ... 191 Curriculum Vitae ... 201 List of pubblications ... 203









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“Whatever you can do or dream you can, begin it. Action has genius, power and magic in it.” - Goethe

1.1 Road Safety and skid resistance

Road Safety is recognized as a major societal issue. In 2012, more than 28,000 people died on the roads of the European Union, i.e. the equivalent of a medium town [EU commission, 2013]. It is also estimated that for every death on Europe's roads there are 10 serious injuries and 40 more slightly injured. Considering that vehicle accidents, where the state of the road surface plays an important role, are known to account for at least 25% of all European road fatalities [Research Framework 2007-2015, 2006], it becomes clear that a strong effort at road management and at research level is still needed.

Road conditions with low friction have been identified as a frequent cause of traffic accidents. Low friction between the road surface and the car tire can lead to vehicle skidding. A direct consequence of skidding is a dramatic loss of breaking power and steering capability of the vehicle which might lead to accidents and consequently to human casualties.

Skid resistance describes the contribution of the road surface to the development of friction at the tire-road interface. Friction originates primarily from the interaction of the asperities of the road surface with the morphological characteristics of tires. Unfortunately, due to the polishing effect of traffic combined with environmental factors, the frictional characteristics of the road surface decrease and, as a consequence, skid resistance of the road drops and can reach unsafe levels.

In order to ensure that unsafe levels are not reached in the road network, road authorities perform skid resistance tests by means of available friction devices. Since there are several devices available nowadays, the result obtained is only an indication and is impossible to compare with the results of other equipment.

The pavement engineering community, the material suppliers, the road authorities and the society at large could benefit from a better understanding of the frictional phenomenon as well as a more systematic way of characterizing Asphalt Concrete (AC) frictional performance.

1.2 Aim of this research

As mentioned in the previous section, skid resistance is recognized by the asphalt community and the road authorities as a major concern. Given the awareness of the problem and the lack of quantified fundamental knowledge on its causes and solutions, this thesis examines, at a more fundamental level, the processes taking place at the interface between the pavement surface and the rubber treads towards the identification and investigation of the various parameters influencing the skid resistance of Asphalt Concrete mixes.

Decomposing the topic into three levels (asphalt, rubber and interaction levels), the main research questions of this study are:

At asphalt concrete level:

• How can we use laboratory tests to provide us with an insight into Asphalt Concrete mechanical characteristics?

Introduction

• How we can link laboratory tests to finite element analyses in order to understand the response of asphaltic mixes for a more extensive range of states of stress?

• How can we compare different asphalt concrete surfaces in relation to their texture? How can we monitor the evolution of asphalt concrete surfaces with time/progressive wheel passes?

At rubber level:

• How can we use laboratory tests to provide us with an insight into rubber mechanical characteristics?

At asphalt concrete-rubber interaction level:

• Which are the most important parameters influencing asphalt concrete mixes – rubber interaction?

In the course of this thesis, answers to the above questions are provided. In the following section, the research methodology that is used in order to provide answers to those questions is described.

1.3 Research methodology

An integral approach has been used in this thesis. The study of the interaction between Asphalt Concrete and rubber comes, for this reason, after a detailed study of the two interacting materials.

Because of the complex structure of AC, an upscaling approach has been considered for this material. Its properties were evaluated by means of the study of the mix components (aggregates and bitumen) and further by means of its mix design.

With the goal of developing a constitutive model capable of simulating its inelastic response, a focused testing protocol was developed for asphalt specimens.

On the basis of these tests, a constitutive model has been selected for the AC material. Consequently, mechanically based parameter determination procedures were developed on the basis of the creep test results.

At the same time, because of the temperature-sensitive response of rubber materials, the rheological characteristics of the rubber types utilized in this project have been studied by means of DSR tests and a constitutive model has been calibrated.

In a follow up level, on the basis of the material characteristics, the interaction between the two materials was object of study.

In order to reduce the amount of parameters influencing skid resistance, in this work, a controlled laboratory environment has been considered. After a detailed analysis of all the parameters influencing rubber-AC mixes friction, the following parameters were considered important for the defined problem: pressure, speed, slip velocity and asphalt and rubber characteristics.

Since no available laboratory devices can analyse all these factors, in order to study their influence on friction, an innovative Skid Resistance Interface Testing Device (SR-ITD®) has been designed, validated and utilized for this study. For a defined set of pressures and speeds, the frictional characteristics have been investigated and the temperature has been monitored during the test.

Finally, Finite Element Analyses show the influence of the different parameters in pavement strains.

1.4 Content overview

On the basis of the research methodology presented in the previous Chapter, an overview of the thesis outlines is given in Fig. 1.1. Chapter 2 presents a literature review of the state of art on AC and rubber models and on friction. Chapter 3 describes a detailed material characterization for AC mixes. Chapter 4 presents a mechanistic procedure for parameter

Introduction

campaign and a parameter determination procedure for rubber. Moving to the interaction between the two materials, the characteristics of the innovative Skid Resistance–Interface Testing Device and the results obtained are presented in Chapter 6. In Chapter 7, analytical models for the study of the interaction are discussed as well as simulations of a tire load on a pavement surface. Finally, in Chapter 8 conclusions and recommendations are presented.

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“Once we accept our limits, we go beyond them ” - Einstein

Equation Section 2

2.1 Introduction

Following the integral approach discussed in the previous Chapter, a literature survey on earlier attempts to investigate the tire pavement interaction phenomenon is presented in this Chapter.

The first part of this Chapter focuses on each material underlining previous laboratory material characterization studies and modelling attempts.

In a second part, all the aspects related to the interaction between the two materials are investigated. After a general discussion about friction and skid resistance, the influencing factors are discussed: pavement surface characteristics, tire properties, vehicle operating factors and finally environmental conditions. Subsequently, the state of the art regarding friction and polishing devices and skid resistance devices is reported. Finally, available friction constitutive models are listed and their limitations are discussed.

2.2 Asphalt concrete characteristics and constitutive models

Asphalt concrete is one of the most popular materials for the construction of highway pavements, streets, airport runways, parking lots and other travelled areas. It is a composite material consisting typically of stone aggregates of various sizes bonded together by a bituminous matrix known as mastic. In addition to bitumen, mastic includes varying amounts of sand and other minerals known as “fillers” and can also include polymer or rubber particles. Depending on its design characteristics, a mix may have up to 20% of air-voids. After mixing, it is laid down and compacted to the desired air voids level. Because of the presence of bitumen, the response of asphalt concrete is sensitive to strain rate and temperature and exhibits strong elasto-visco-plastic characteristics even at small strains.

2.2.1 Mix design

Asphalt concrete pavement design started with mix design. In the 1920’s, due to the development of petroleum asphalt, the road engineering research produced the first test on AC. This test, called Hubbard-Field test, was meant to provide info regarding the stability of a mix on the basis of a punching-shear test.

Ten years after the first test, the first mix design procedure was developed by Francis Hveem. The procedure of Hveen is in disuse but the procedure developed by Bruce Marshall in 1960’s is still used in several countries in order to find the best binder content for a specific aggregate gradation. However, the link between the Marshall mix design procedure and the performance of AC pavement is purely based on experience. This means that in case laboratory tests results are compared with real pavement performances, the conclusions obtained are only valid on similar construction, climate, traffic conditions, etc.

2.2.2 Pavement design

Literature review

number of passes of a standard load) and construction geometry (e.g. thickness and stiffness for the other road foundation materials). The output of the calculation is the thickness of the asphalt layer based on multi-layer (ML) analyses associated to a series of empirical correction factors.

In 1993, the AASHTO design procedure was published based on empirical equations derived from the AASHO Road Test conducted in the late 1950’s in a test track in Ottawa, Illinois. Due to the changes in materials and due to the increase in traffic volumes, the AASHTO guide was soon replaced by the Mechanical Empirical Pavement Design Guide. This guide contains a wide database on American climatic data and more mechanical-empirical relations for pavement design and rehabilitation. The software developed, that can be run through internet, uses models based on the ML elastic program JULEA and the 2-D Finite Element (FE) program DSC2D. The latter can be used only in order to characterize the non-linear moduli response of unbound layer materials and it is suggested to be used only for research porpoises.

The step of the MEPDG to move from ML analysis to 2D FE analyses shows that there is a new trend trying to gradually replace ML analyses with more accurate Finite Element Analyses. This is due to the following several drawbacks of the ML analyses:

• Fixed geometry: ML can model horizontal infinite layers. For this reason, it cannot take into account joints, cracks and other discontinuities that may be present in an asphalt layer. Furthermore, it cannot model asphalt concrete specimens.

• Changes in mechanical response or in conditions (such as temperature or strain rate) within a layer cannot be taken into account.

It is also important to underline that, in order to evaluate pavement performances (e. g. damage, distress and smoothness), empirical performance models are considered. These empirical models are based on laboratory tests and empirical correction factors (to account for factors such as aging and healing). The addition of these factors seriously limit their applicability to any type of pavement having different characteristics or subjected to different loading or environmental conditions from those where the relations were obtained. Also, due

predict the response of these mixes and, this can lead to several problems. The US Department of Transportation, in a recent memorandum, is warning the Directors of Field Services regarding a high number of highway agencies reporting pre-mature cracking in relatively new asphalt pavements containing high content of recycled asphalt binder.

This means that more mechanically driven FE simulations of mixes and/of pavement response should be performed and that the availability of these type of tools would certainly help the asphalt industries in designing better products and the road authorities in limiting maintenance operations.

Current limitations to a fully mechanistic approach are related to the need of sophisticate constitutive models and powerful computational tools so research is at the moment focused on these two aspects. An overview of the state of the art on constitutive models is reported in the next section.

2.2.3 Constitutive models for AC mixes

The difficulties in finding a model able to simulate the various states of stress that the asphalt concrete encounter during its lifetime are related to the sensitivity of AC mixes to strain rate and temperature and due to its strong elasto-visco-plastic characteristics even at small strains.

Studies assuming asphalt to be visco-elastic have used spring-dashpot analogs like Burgers’ model, Monismith & Secor [1962], or generalized Maxwell and/or Kelvin models, Lytton et. al [1993], Lee [1996] and Nillson et al. [2002] with varying degrees of success. More recently, the Huet-Sayegh model has been utilized by Olard & di Benedetto [2003], Oeser et al. [2008] and Xu & Solaimanian [2009]. In the context of linear visco-elasticity it was shown that the model can describe the response of the material using a smaller number of parameters.

Levenberg & Uzan [2004], Uzan & Levenberg [2007], Scarpas [2004], Erkens et al. [2002] and Erkens [2002] focused on aspects of the three dimensional elasto-visco-plastic response of the material and their implementation in finite element software for actual finite element analyses of pavements.

Literature review

Models have also been proposed based on the “correspondence principle” proposed by Schapery [1984] to generate non-linear visco-elastic models from non-linear elastic models, Park et al. [1996], Kim & Little [1990]. Uniaxial versions of these and their ad hoc extension to three dimensions are currently used extensively for investigation of various aspects of the inelastic response of asphalt, Christensen & Bonaquist [2005], Kutay et al. [2008], Underwood et al. [2010] and references therein. Unfortunately, despite their popularity and wide use, it has been shown by Rajagopal and Srinivasa [2005] that models generated by appealing to the correspondence principle do not satisfy the balance of angular momentum principle which constitutes one of the fundamental principles in mechanics that ensures the symmetry of a three dimensional stress tensor.

Finite strain constitutive models originating from the concept of multiplicative decomposition of the total deformation gradient into elastic and inelastic components as proposed earlier by Lee and Liu [1967] and Lee [1969] admit the existence of local unstressed intermediate configurations that evolve with the development of inelastic deformations. Murali Krishnan and Rajagopal [2003, 2004] and Murali Krishnan and Rajagopal [2005] have coined the term “natural configurations” for the set of evolving intermediate configurations. On the basis of standard thermodynamic arguments, they were able to derive expressions for the evolution of the stress tensor and the inelastic deformation gradient of an incompressible visco-elastic constitutive model for asphalt mixes. For the case of asphalt mixes, this is a rather limiting postulate since the available experimental evidence indicates the development of large volumetric strains with loading, Erkens [2002].

An elasto-visco-plastic material model for asphaltic mixes that is not bound by the limitation of incompressibility has been proposed by Scarpas [2004] and Kringos et al. [2007]. By exploiting the Clausius–Duhem local energy dissipation inequality, constitutive equations have been developed for a material model consisting of an elasto-plastic and visco-elastic components acting in parallel.

When Asphalt Concrete is subjected to repeated creep and recovery tests, some of the models described above are unable to capture secondary region behavior and long rest periods. For

tests and cyclic tests. Levenberg & Uzan [2004] proposed a viscoelastic-viscoplastic model able to simulate the response of uniaxial creep and recovery cycles but this theory is limited to small strains.

2.3 Rubber characteristics and constitutive models

A piece of rubber, if deformed, shows elastic deformation up to large strain values (often well over 100%). For this reason, rubber is often studied as an elastic material.

The basic features of the hyperelastic stress-strain behavior of rubber have been well modeled by:

• statistical treatment of rubber elasticity (Treloar, [1975] and Arruda-Boyce [1993]) LQYROYLQJSK\VLFDOO\PRWLYDWHGPRGHOV

• stretch invariant based continuum models (Rivlin [1948], Mooney [1940] and Rivlin [1948] and Yeoh [1993])

• phenomenological models or hybrids of phenomenological and mechanistic models (Gent [1996]).

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Fig. 2.1 Stress-strain curve for rubber for: (a) various temperatures and (b) various load application speed.

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surface roughness and rubber characteristics. In this type of interaction, according to Moore [1972], the two main friction forces are adhesion and hysteresis, Fig. 2.3.

Fig. 2.3 Schematic representation of the rubber friction main mechanism [NCHRP, 2009].

The adhesion component arises from molecular interactions between the rubber and the AC surface while hysteresis is related to energy loss due to the tire deformation.

Upscaling the interaction phenomenon to a tire that is braking/rolling on an asphalt concrete pavement, the influence of factors such as road condition (presence of water, snow, sludge, etc.) and tire geometry should also be taken into account in the evaluation of the two mechanisms described above.

2.5 Skid resistance: relevant factors

In papers and publications, the words ‘skid resistance’ and ‘friction’ are often used as synonyms. In this thesis, the word ‘friction’ is related to the rubber - asphalt surface interaction while the words ‘skid resistance’ or ‘wet pavement friction’ are considered as a ‘measure of the force generated when the tire slides on a wet pavement surface’, according to the definition in the NCHRP Synthesis 291, [2000].

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The Permanent International Association of Road Congress (PIARC) has classified the texture wavelengths that have an impact on pavement surface performance (wet friction, rolling resistance, noise, etc.) [PIARC, 1995].

As it is shown in Fig. 2.4, in case of wet pavement friction, microtexture and macrotexture are the texture wavelengths that deserve more attention, Kummer and Meyer, [1963].

The microtextural wavelengths, ranging from 0.1 to 0.5 mm, are related mainly to the aggregate properties while, macrotextural wavelengths, ranging from 0.5 to 50 mm, are related to aggregate gradation and size.

On the basis of extensive studies from Noyce et al. [2005], a qualitative information regarding the influence of the microtextural and macrotextural characteristics on the frictional response was obtained.

Fig. 2.5 Microtexture and macrotexture effect on friction [Noyce et al., 2005].

As it can be seen in Fig. 2.5, where the sliding coefficient of friction is studied with respect to sliding velocity, the microtexture defines the magnitude of skid resistance, while the

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study has been concluded that macrotexture influences strongly the skid resistance at high speed, while, at low speed, microtexture is therefore the main component of friction.

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Several models for the prediction of the friction decay are available [Rezaei, 2009], and usually are statistical-empirical, based on laboratory data (British Pendulum Value, Los Angeles, mineralogical characteristics of aggregate, voids, etc.) and in-field data (Annual Average Daily Traffic, road type, Mean Penetration Depth, etc.). Since statistical analysis are conducted, similarly to what has been underlined in the asphalt concrete characterization literature review, the prediction of those models, could lead to errors in case the type differs significantly from those the model is calibrated for.

2.5.1.1 Surface texture characterization techniques

The oldest but often still in use way to evaluate the surface texture characteristic is via volumetric techniques. The most commonly utilized is the sand patch method in which a known volume of material (usually sand) is spread into the pavement surface. Via this method, the Mean Texture Depth is evaluated by dividing the area by the volume of material. Another method based on the same technique is the Outflow Meter Test [Henry and Hegmon, 1975].

Nowadays, the interest is moving towards the use of optical or laser devices because of their accuracy. The Mean Penetration Depth (MPD) and the Root Mean Square (RMS) are the most popular parameters to characterize the macrotextural properties of AC profiles. Regarding this method, some concerns are raised [EN 13473-1] regarding the use of the MPD in case of Porous Asphalt mixes.

Fewer studies are available on the microtextural properties [Do et al., 2000, Masad et al., 2010] and are conducted on a single aggregate scale using microscope and/or digital image processing techniques.

All the methods described above, define the parameters only on selected wavelengths but as discussed earlier in this section, the frictional problem is due to the interaction with the surface texture at several wavelengths, therefore the same method should be used for evaluating the parameters at the various scales. A more comprehensive multiscale approach based on the fractal properties of the AC mixes [Heinrich and Kluppel, 2000] is certainly more beneficial in order to characterize surface texture and, therefore, is discussed in Chapter 7.

Literature review

2.5.2 Tire properties

It is well known that the characteristics of the tire and particularly the inflation pressure, the carcass structure and its flexibility and the tire compounds can strongly influence the frictional response. The main components of the tire carcass are shown in Fig. 2.7.

Fig. 2.7 Tire carcass structure.

Among those components, according to Grosch, [1996], the most important is the tread. The tire properties and the tread properties are strongly related because:

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speed or direction, an increase of friction can be measured. As the breaking force increases, the friction tends to increase until the slip ratio reaches values around 18% - 30%. After this value, lower values of friction are obtained until, in correspondence of a locked wheel, the friction stabilizes.

Other factors that may influence skid resistance are related to the road geometry (uphill, downhill, corner. etc.) but they are not taken into account in this thesis.

2.5.4 Environmental conditions

In real pavements, sinusoidal fluctuations in skid resistance due to the environmental conditions (difference in temperature, wind, rain) are usually observed >)OLQWVFK HW DO  Wilson and Dunn, 2005].

This variation is related to the fact that, during summer, loss of skid resistance occurs because of oil dripping and grease on the surface and because of an accelerated polishing due to particles accumulation. On the contrary, during winter, the rainwater flushes out dust and oil dripping and the skid resistance increases [Wilson and Dunn, 2005]. On top of seasonal variations also day-to-day fluctuations can occur because of extreme changes in weather conditions [Davis et al., 2002].

2.6 Evaluation of friction

Before the performance based contract, Road Authorities were setting tests to be performed and limits to be satisfied in order to make sure that Asphalt Concrete (AC) mixes were characterized by adequate friction and resistance to polishing action.

With the current moving towards performance based contracts, contractors have to guarantee optimal pavement performances for several years. In this type of context, past tests on aggregate do not always provide a clear answer regarding which aggregate performs the best, so a more accurate approach needs to be considered.

Using friction devices and polishing devices on the entire asphalt concrete structure is a more proactive approach, at mix design level, in order to study the performance of various mixes and to compare them. Also, monitoring the in situ skid resistance can help in identifying premature severe loss of skid-resistance.

In the next sections, tests on aggregates, friction and polishing devices for AC mixes will be presented. Also, a brief overview of the available skid resistance devices is reported.

2.6.1 Friction and polishing characteristics evaluation in a laboratory

environment

2.6.1.1 Pre-evaluation of aggregates for use in Asphalt Mixes

Historically, the toughness of aggregates has been determined using the Los Angeles test. In the last years, more tests have been developed and used in order to evaluate the aggregate characteristics. A list of tests currently in use follows.

• The Los Angeles (LA) test [EN 1097-2] is a measure of the resistance of coarse aggregates to fragmentation resulting from a combination of actions including abrasion or attrition, impact and grinding. In this test, a portion of 10/14 mm aggregate is rolled in a steel drum together with steel balls. The LA coefficient is determined by the percentage of the test portion passing the 1.6 mm sieve at the end of the test, Fig. 2.10 (a).

• The Micro Deval (MD) test [EN 1097-1] is meant for measuring the wear produced by friction between aggregates and an abrasive charge in a rotating drum in dry or wet conditions, Fig. 2.10 (b).

• The aggregate abrasion value (AAV) test [EN 1097-8], Fig. 2.11 gives a measure of the resistance of an aggregate to surface wear by abrasion. In this case, the stone mosaics are pressed against the surface of a steel disc rotating in a horizontal plane and sand is used as abrasive material. Unlike the LA Abrasion test, for this test, there are no

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• WKH:HKQHU6FKXO]H:6PDFKLQH>'RHWDO@KDVRQHrotary head for polishing applied on top of the specimen, )LJ  E 7KUHH VPDOO KDUG FRQHV URWDWH RQ WKH VXUIDFHZLWKDVSHHGRINPK7KHIULFWLRQURWDU\KHDGLVWKHQXVHGWRGHWHUPLQHE\ PHDQVRIWKHYDULDWLRQLQIULFWLRQGXHWRSROLVKWKHYDULDWLRQLQVXUIDFHFKDUDFWHULVWLFV In order to test aggregates, PSV, AAV and WS tests are performed on a mosaic of stones. Several researchers [Fwa et al., 2003, :RRGZDUGDQGVillani et al. 2012] underlined that tKH IULFWLRQDO UHVSRQVH RI PRVDLF VDPSOHV LV LQIOXHQFHG E\ WKH ZD\ WKH VDPSOHV DUH FUHDWHG (e.g. size and number of gaps between aggregates, the arrangement of aggregate particles in the specimen for heterogeneous materials such as gravel), therefore all the above mentioned tests should be only be considered as indicators.

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• the Dynamic Friction Tester (DFT) [Saito et al., 1996], small pads rotate on a surface with a tangential speed varying from 0 up to 90 km/h. For this device, the pressure (0.2 MPa) cannot be varied and it is quite low in comparison with current traffic pressure levels.

• the Wehner Schulze (WS) machine consists of two rotary heads, one for friction measurement of specimens and one for polishing. In the friction measurement part, Fig. 2.14 (c), three small pads rotate on the surface with a tangential speed varying from 0 up to respectively 100 km/h with a pressure of 0.3 MPa. The friction measured at 60 km/h is the output of the test.

• the LAT 100, currently used in the rubber industry, utilizes instead of the real asphalt or stone surfaces, Alumina or Silicon carbide [Grosch, 1963, Heinz and Grosch, 2007 and Grosch, 2007] surfaces. The main focus of this test is on the study of the frictional response of rubber in relation to its various compounds and/or to the addition of fillers or oil.

While the first two devices are portable and therefore they can be also used in situ, the last two can be used only in a lab environment.

2.6.1.3 Polishing devices for AC mixes

Several devices are also available in order to study the evolution of surface texture with polishing passes for laboratory size specimens. Some of these devices utilize real tires (e.g. Michigan Indoor Wear Track), some pneumatic tires characterized by a smaller size (e.g. NCAT Three-Wheel Polishing Device), some hard rubber cones (WS machine, Fig. 2.14 (b)) and some rubber pads (Penn state polishing machine). In case an evaluation of friction is required, these devices are used in conjunction with one of the friction devices described in the previous subsection.

Literature review

2.6.2 Evaluation of Skid resistance in situ

Different skid resistance measuring devices have been developed over the years. According to the way they measure skid resistance, four groups can be distinguished:

• A slider apparatus derives the skid resistance of the road by means of the rate of deceleration needed. The British Friction Tester, already discussed in the previous subsection, belongs to this group.

• Longitudinal Friction Coefficient (LFC) measurement uses an instrumented measuring wheel mounted in line with the travelling direction. A fixed gear, or braking system, forces the wheel to rotate more slowly than the speed of the vehicle or to be locked. The ratio between vertical and drag force is calculated.

• Sideway Force Coefficient (SFC) measurement measures the force on an instrumented rotating wheel set at an angle to the direction of travel of the vehicle.

• Decelerometers mounted on commercial cars.

2.7 Available friction models

In the road industry, the commonly adopted model is the exponential PIARC model. This friction model has been calibrated on fixed wheel slip devices and varying measuring speed.

The PIARC model or Penn State University model [Leu and Henry, 1978] is characterized by the following formula:

0

v/v 0e−

μ = μ (2.2)

A similar model, calibrated on fixed measuring speed and different slip speed is called the Rado model. The Rado formulation [Rado, 1994] complements the PIARC model in terms of the modeling of the maximum friction μ_max and speed s_max. It takes the following form:

( )

2 max s ln s c max s e § · ¨ ¸ © ¹ − μ = μ  (2.3)

where ˆc is the shape factor.

Both the PIARC and the Rado models don’t take into account the pressure applied and the temperature of the rubber. Experimental models available from the tire industry take this aspect into account. Among those models, the Rieger model [1968] shows the interrelation between friction, rubber temperature θ and sliding velocity obtained on the basis of experimental tests by using the formula:

( )

( )

0 a ln ln b s

μ = μ + θ θ − (2.4)

Another relevant model is the Wriggers model [Wriggers, 2002], in which the friction evolution is defined as a function of the normal pressurep , the maximum friction coefficient _N

max

μ and the corresponding speed v_max as follows: max N 2 2 max max c 2 v v (v , p ) v v § · μ =¨_¨ ¸_¸ μ + © ¹ (2.5)

The parameters a, b, c and d describe the hysteretic damping. They can be calculated on the basis of the following equations:

max N v =a p (2.6) max N N b arctan(d p ) p μ = (2.7)

Nackenhorst [2004], aware of the importance of temperature in the frictional phenomenon, presents a model function of speed and pressure valid only when the temperature variation can be neglected, such as when small sliding velocities occur (10-3 to 10 m/s):

T T T 0 N 1 2 1 2 v v (v ) (p ) c ln c ln v v μ = μ + − (2.8)

Literature review N 0 N 1 0 p (p ) p α ª º μ = μ « » ¬ ¼ (2.9)

This model needs seven parameters that can be deduced from experiments.

Dorsch et al. [2002], on the basis of the results of an experimental campaign using LAT 100, obtains an expression consisting of pressure, speed and temperature that it is used for FE simulations, but parameters and complete expression are not declared in their paper.

Comparing the various models described in terms of numbers of parameters that needs to be determined, Table 2.1 is obtained.

Table 2.1 Overview of friction models described and number of required parameters.

Function of Number of parameters

PIARC Speed 2

Rado Speed 3

Rieger Speed, temperature 3

Wriggers Speed, pressure 4

Nackenhorst Speed, pressure 7

2.8 Lessons learnt from the literature review

From the literature review, the following points are underlined regarding material characterization:

• There is currently a trend towards new design procedures for material characterization and simulations based on mechanical approaches rather than empirical. Despite that, researchers have not yet converged towards a unique testing procedure or a constitutive model able to characterize AC performances.

• Laboratory tests should be designed and performed with the goal of understanding the mechanical response of mixes at various levels of stress and strains and not with the unique interest on mixes performance indicators ranking. For this reason, the state of stress to which the material is subjected during testing should be clear and should lead to easy-to-determine parameters.

• From the obtained parameters, finite element simulations should lead to characterization of the asphalt concrete response for several states of stress.

Regarding the interaction between asphalt mixes and rubber, a list of relevant factors has been reported. At first, the influence of pavement texture wavelengths on the tire-pavement interaction and the importance of a multiscale approach are underlined. Also, the importance of the tread properties was underlined during the description of the tire properties and, finally, the importance of speed and rolling/braking conditions was documented.

Regarding the evaluation of the interaction between asphalt mixes and rubber, it is clear that, also in this case, the predominant factor is experience. Current available friction/polishing devices do not provide user control of the actual test conditions imposed by the equipment on the material(s). For this reason, the obtained response is only valid under the specific test conditions and cannot be generalized to other situations. The same conclusions can be drawn regarding correlations between laboratory results and field results, where the results are also only valid for the specific mix/device/tire so they cannot be generalized.

Finally, the friction models literature review underlines that speed, temperature, pressure, surface characteristics and rubber characteristics are all important factors but at the moment, no experimental tests can be carried out by controlling all these factors, so a clear relation between friction and all these parameters is not yet available.









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Equation Section 3

3.1 Introduction

In the literature review presented in Chapter 2, the fundamental role of the asphalt characteristics on skid resistance was underlined. For this reason, this Chapter focuses on the laboratory characterization of three asphalt concrete mixes studied during the SKIDSAFE project.

Starting from the component level, bitumen and aggregate characteristics are presented. The various bitumen properties are reported and the results of a mineralogical and mechanical aggregate characterization are discussed.

In the second part of this Chapter, an extensive laboratory experimental program for the mechanical characterization of AC mixes is presented. The results of these tests will be utilized for constitutive model calibration in Chapter 4.

3.2 AC mixes components characterization

3.2.1 Mix design

The asphalt mix composition was designed, during the project SKIDSAFE, by the laboratory of Aggregate Industries (AGI). Three AC mixes, representative of typical asphalt concrete available in Europe were utilized for this work: Porous Asphalt (PA), Stone Mastic Asphalt (SMA) and Dense Graded Mix (AC10). Table 3.1 indicates the type of aggregate, filler and bitumen selected for each mix and their percentage by weight. The gradation curve for the three mixes is reported in Fig. 3.1.

Table 3.1 Mix design of the AC mixes object of study.

PA Composition (%) 4/10 mm Greywacke 54.9 2/6.3 mm Greywacke 16.8 0/4 mm Greywacke 19.2 Limestone Filler 3.8 Binder (40/60) 5.3 AC10 Composition (%) 4/10 mm Granite 17.9 2/6.3 mm Granite 33.9 0/4 mm Granite 37.7 Limestone Filler 4.7 Binder (100 PMB) 5.8 SMA Composition (%) 4/10 mm Granite 55.2 2/6.3 mm Granite 14.8 0/4 mm Granite 15.9 Limestone Filler 8.4 Binder (100 PMB) 6.4

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3.3 Characterization of aggregates

As already discussed in Section 3.2, three types of aggregates, commonly available in Europe, were selected during this study: granite, greywacke and limestone.

The first two are commonly utilized in pavement wearing courses. The last one, due to its low resistance to polishing, is used only on binder and base layer and on wearing courses of secondary roads.

An extensive mechanical, mineralogical and chemical characterization performed on the aggregates is described in the next two sections.

3.3.1 Mineralogy

According to Tourenq and Fourmaintraux [1971], a direct relation exists between the polishing propensity of aggregates and the minerals hardness.

Using their approach, aggregates can be selected after comparing the composing minerals with Mohs scale or Vickers hardness values, Table 3.3. The table underlines that quartz and feldspars grains are relatively hard with typical hardness values of 7 and 6, respectively. Chlorite, biotite and calcite grains are, on the other hand, much softer with hardness values between 2 and 3. In the following the characteristics of the different minerals for each aggregate and their interrelation with friction and polishing are discussed.

Table 3.3 Hardness values of minerals.

Mineral Mohs scale (1-10) Vickers (kg/mm2)

Quartz 7 1280 Feldspars 6 720 Amphibole 6 730 Chlorite 2 – 2.5 Biotite 2.5 – 3 90 Calcite 3 110

AC experimental testing campaign

Greywacke is a type of sedimentary rock belonging to the sandstone group. Petrographic examination presented in SKIDSAFE Report R1.1 [Artamendi, 2012] showed that greywacke aggregates comprised of several mineral grains namely quartz, feldspars, chlorite and biotite. Quartz and feldspars grains are angular and relatively coarse with grain sizes ranging from 100 to 300 ȝm. Chlorite and biotite mineral grains, on the other hand, are elongated and smaller in size. Moreover, in the greywacke, coarse angular quartz and feldspar grains are cemented by the much finer matrix of chlorite and biotite minerals. The chemistry of the greywacke indicates relatively high silica content (66 %). The silica combines with the main oxides (Iron, Magnesia, Calcium, Sodium and Potassium oxide) to form the silicates. In the greywacke, silicates comprise of quartz, feldspars, chlorite and biotite. Quartz is composed of pure silica. Feldspars are aluminosilicates containing potassium, sodium and calcium. Chlorite and biotite are phyllosilicate minerals, i.e. with a tendency to split along defined crystallographic structural planes, rich in iron and magnesium. The frictional performance for this aggregate is expected to be high due to the angular shape of the coarse quartz and feldspars grains. The sorting of the different mineral grains and differences in size and shape between them create an irregular and fairly harsh rock surface microtexture which provides high friction and high polishing resistance.

Granites are intrusive igneous rocks composed of interlocking crystals. They are usually coarse grained, often with similar sized individual crystals which are generally randomly arranged. Petrographic examination of the granite used in this study showed that the rock comprised mainly of quartz, feldspars (orthoclase), amphibole and biotite. Feldspars and amphibole grains are angular with coarse grains with grain sizes ranging from 100 to 2000 ȝm. These minerals have well developed crystal faces (euhedral). Quartz grains are finer (50 – 200 ȝm) and rounded with no crystal faces (anhedral). Biotite grains, on the other hand, are elongated and smaller than the feldspars.

The chemistry of granite indicates relatively high silica content of 64 %. Silicates in this granite comprise of quartz, feldspars, amphibole and biotite. Quartz is composed of pure silica. Orthoclase feldspars are aluminosilicates containing potassium and are the main component in the granite (46 %). Amphibole is an inosilicate or chain silicate containing iron

and magnesium in its structure. It might also contain sodium and calcium. Biotite is a phyllosilicate (sheet silicate) mineral rich in iron and magnesium.

Regarding frictional performance, it is expected to be good due to the angular shape of the coarse interlocking feldspars and amphibole grains. The crystalline structure of these minerals and the random distribution of the crystals creates a rough surface microtexture which provides high friction and therefore good skid resistance. For this stone, high concentration of feldspars grains (> 40 %) plus the contribution of the amphibole and quartz gives the rock good resistance to polishing.

Limestones are sedimentary rocks formed in a marine environment from the precipitation of calcium carbonate and compressed to form a solid rock. They are composed primarily of calcium carbonate (CaCO3) in the form of calcite. Petrographic examination of the limestone used in the study showed an almost single mineral phase nature of the aggregate. There was evidence of different types of limestone, namely, sparite, ooid and micrite. Sparite calcite showed angular rhomboid-like grains between 100 microns and 1.1 mm in size. Oolithic limestone showed rounded ooids with a diameter of 300 microns. Micrite, on the other hand, was composed of very small crystals (< 5 ȝm).

The frictional performance of this stone is expected to be rather low due to the small size of the micrites, which creates a uniform smooth matrix and the irregular and rounded shape of the sparite and ooid calcite grains. Regarding polishing, the single nature of the mineral grains and their low hardness, typically around 3 in Mohs scale, make this type of rock very susceptible to polishing.

3.3.2 Physical and mechanical aggregate tests

In order to determine the physical properties of the aggregates, apparent particle density (ȡa), oven-dried particle density (ȡrd), saturated and surface-dried particle density (ȡssd) and water absorption after immersion for 24 h (WA24) have been determined according to the Standard CEN method [EN 1097-6, 2000] and are presented in Table 3.4.

AC experimental testing campaign

Table 3.4 Particle density and water absorption values.

Aggregate type ȡrd (Mg/m3) ȡa (Mg/m3) ȡssd (Mg/m3) WA24 (%)

Greywacke 2.76 2.78 2.81 0.6

Granite 2.56 2.61 2.69 1.8

Limestone 2.66 2.68 2.78 0.8

It is common practice to select the aggregate with a better polishing, abrasion and wear resistance by means of four easy to perform tests: Los Angeles (LA) [EN 1097-2, 2010], Micro-Deval (MD) [EN 1097-1, 2010], Aggregate Abrasion Value (AAV) and the Polishing Stone Value (PSV) tests. Details about these tests can be found in Section 2.6.1.1.

The Los Angeles (LA) test shows that the greywacke is the strongest material in terms of resistance to fragmentation, crushing and impact. Micro-Deval (MD) test and Aggregate Abrasion Value (AAV) test are, on the other hand, related to the abrasion and wear characteristics of the aggregates. The results, shown in Table 3.5, indicate that the greywacke and granite aggregates have similar resistance to abrasion and wear. PSV values indicate that the greywacke and granite aggregates have both good polishing resistance characteristics. Limestone, on the other hand, has low resistance to polishing and abrasion.

Table 3.5 Standard aggregate tests results.

Aggregate type LA MD AAV PSV

Greywacke 12 10 3.2 60

Granite 28 9 4 58

Limestone 31 17 9.4 32

From Table 3.5, the observation can be made that aggregate ranking between the various tests differs significantly. On the basis of these tests and on their mineralogical characterization,