Development of Prediction Model for Structural Behavior and Gradation of Porous Asphalt Pavement

doi:10.21203/rs.3.rs-3648294/v1

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Development of Prediction Model for Structural Behavior and Gradation of Porous Asphalt Pavement

https://doi.org/10.21203/rs.3.rs-3648294/v1

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This study is aimed at developing a prediction model for structural behavior of Porous Asphalt Pavement (PAP) using ABAQUS and also developing ANN model to predict void percentages in Porous Asphalt gradation mixes. Data from the past literature was used to analyze various mixing parameters affecting the properties of Porous Asphalt gradation mix. PAP was analyzed using KENPAVE software and the results revealed that lesser number of allowable repetitions to fatigue and rutting failures were observed for lesser Porous Asphalt Concrete (PAC) layer thicknesses. Nature of subgrade material was found to influence the rutting performance of PAP with clayey soils showing 77.74% reduction in design life of pavement as compared to gravelly soil subgrade. Higher contact pressures resulted in higher tensile stresses at the bottom of PAC layer which in turn reduced the fatigue life of PAP. Results from ABAQUS revealed that increase in void percentage in PAC mix resulted in significant increase in horizontal tensile strain at the bottom of PAC layer by 12.3% and increased tensile strain for 28% void in total mix than for 16% voids. Thus, leading to 92.8% reduction in allowable load repetitions to fatigue failure. Also, increased void percentage led to decrease in vertical stress and deflection in PAP but no significant effect on allowable repetitions to rutting failure was found. Asphalt Pavement mixes were also compiled to develop ANN prediction model. The results indicate good conformity between predicted and actual data with mean square error of 0.109 and coefficient of correlation as 0.994.

Porous Asphalt Pavement (PAP)

Rutting Failure

Fatigue Failure

Asphalt Concrete

Subgrade

KENPAVE

Normally asphalt pavements let rainfall and runoff to move through the pavement surface, and drain into neighboring catch basins of roads. In contradiction to this, the basic purpose of a Porous Asphalt Pavement (PAP) is to allow water to seep through the surface of pavement thus allowing a direct drainage to rainfall and runoff. PAP is gaining prominence in the construction industry as a viable solution in locations where drainage is a serious issue. PAP is constructed in the form of an underlying and open graded stone bed which permits drainage for the water. PAP allows surface water to seep into a stone bed reservoir, which is designed to hold water and slowly allowing it to seep into the natural ground below.

Porous Asphalt Pavement has proven to be a promising technique and prove to be effective in enhancing the traffic safety in rainy weather, reducing splash and spray on the roads, having good skid resistance at elevated speeds ^[21]. Also, PAP is getting attention due to remarkable performance in drainage, noise reduction, stormwater management and treatment, mitigation of floods and urban heating island effect.^{[2] [4] [17]}

The performance of Porous Asphalt Concrete (PAC) is not only governed by material properties but also the distribution of constituents of PAC mix and formation of voids. The voids in PAC mix play a vital role in determining the functional performance of PAC. Many researchers have evaluated the relation between air voids and hydrological performance of PAC. Jiang, W. et al (2015) reported that Air void contents not only affected the functional performance of PAC and in turn void features were significantly influenced by NMAS and aggregate gradation. High temperature performance shear and anti-clogging ability was detected for coarse gradation. Also, anti-stripping and noise reduction ability was detected for fine gradations. Also, Król, J.B. et al (2018) linked permeability performance of PAC with pore structure, with high permeability values observed for PAC mix with maximum aggregate size. The fine content in PAC should be low enough to avoid the closure of void spaces and ultimately resulting in low permeability of PAP. The mixture containing high amount of fine aggregates indicated more resistance to deformation but produced a low coefficient of permeability (Ahmad, K.A et al 2018). Chen, M.J. and Wong, Y.D., 2015 established relation between aggregate gradation and permeability performance of PAC pavement, and recommended less than 7% fines in PAC mix for suitability in wet environment. Abdullah, W.S et al. (1998) studied the influence of aggregate type and its gradation on the voids in mineral aggregate and air voids of asphalt concrete paving mixtures. It was concluded that coarser mix resulted in higher rate of increase in the water permeability for the same type of aggregate.

In the current study, Finite Element Modelling of PAP to study its structural behavior is carried out using ABAQUS software. Many researchers have evaluated the structural behavior of flexible pavements using ABAQUS software and determined the structural criteria of pavements. Yassenn, O.M. et al (2015) discussed finite element modelling (FEM) of flexible pavements to evaluate the structural criteria of the pavement. Effect of stress and strains caused by traffic movement on fatigue and rutting damage life can be properly evaluated using linear elastic modelling in case of normal pavements with normal loading. Huang, J et al (2015) carried out FEM analysis to evaluate dynamic behavior of asphalt pavement structure. Analysis of the results reveal when surface layer thickness is increased, pore-water pressure in surface layers increase correspondingly and hence is disadvantageous for resistance of pavement for water-induced damages. Further increase of modulus of the surface layer leads to reduction of the pore-water pressure thus increasing shear stress. Hongchang, W. et al (2011) analyzed double layer porous asphalt pavement for noise reducing property. Results reveal that sound absorption coefficient for porous asphalt is related to acoustic frequency and reabsorption coefficient rises to peak in case of double layer porous asphalt pavement. Gao, L et al (2017) studied cooling effect of porous asphalt pavement using ABAQUS software and derived positive linear correlation between cooling effect and air voids

Despite having so much importance, much research has not been conducted for understanding various aspects of PAP. The structural behavior of PAP under varied loading and environmental conditions has not been conducted yet. Role of different mix proportions of porous asphalt in the stress and strain experienced by various PAP layers is yet to be studied. Relationship between void percentage and structural response of porous asphalt pavements needs to establish. The present study is aimed at developing a prediction model for structural behavior of PAP using ABAQUS and KENPAVE software, and to develop ANN model to predict the void content in Porous Asphalt Mix for varied gradations and mixture properties.

The first part of study includes Collection of gradations of Porous asphalt mix to check the various mix parameters affecting the properties of PAC mix and this gradation data is evaluated to develop ANN prediction model for determining void content of different porous asphalt mixes using NNTOOL Programme. In this part of investigation, a total of seven research studies were selected for extraction of Porous Asphalt gradations. ^{[5] [6] [13] [14] [18] [19] [20]}

Further, in order to predict the structural behavior of PAC pavements, mechanistic analysis of porous asphalt pavement is carried out in KENPAVE software where Porous Asphalt pavement functional performance is evaluated for different thicknesses of PAC layer, axle configurations and different subgrade soils. The PAP test section consists of four layers, including PAC Wearing coarse with thickness ranging from 5-15cm (2”-6”), choker course with thickness ranging from 5-10cm (2"-4"), stone bed recharge of 45 cm (18") thickness and a Sub grade ^[9].Various probable cross-sections that can be used for PAC wearing course and choker course are considered, and by varying thicknesses total of 8 cross sections are obtained as shown in Table 1.The various types of soils and their respective properties considered for the analysis are given in Table 2. Also, to evaluate the effect of different axle configurations and increased tire pressure on pavement responses and pavement design life, data considered for analysis is given in Table 3.

Table 1

Thicknesses of various layers of Porous Asphalt Pavement
Designed cross-sections	Thickness of Porous asphalt layer (in cm)	Thickness of choker course (in cm)	Thickness of Stone bed reservoir (in cm)	Thickness of subgrade
A	5	5	45	∞
B	7.5	5	45	∞
C	10	5	45	∞
D	12.5	5	45	∞
E	15	5	45	∞
F	7.5	7.5	45	∞
G	10	7.5	45	∞
H	10	10	45	∞

Table 2

Properties of Subgrade Soils
Type of subgrade soil	Permeability	Modulus of elasticity in Mpa
Gravelly soil subgrade	Excellent	200 (29000 psi)
Sand, sand gravel mix with little fines	Good	137 (20000 psi)
Silty gravel soil	Fair	62 (9000psi)
Clayey sand soil	Low	26 (3750 psi)
Clayey soil	Very low	15 (2250 psi)

Table 3

Axle configurations with tire pressure and spacing
Axle configuration	Contact pressure in KPa	Contact radius in cm (inches)	Tire spacing (Yw) in cm	Axle spacing (Xw) in cm
Single Axle- Dual Wheel	550 (80 psi)	10.7 (4.23)	33	-
Tandem Axle- Dual Wheel	480 (70 psi)	11.4 (4.52)	34	122
Tandem Axle- Dual Wheel	538 (78 psi)	10.8 (4.25)	34	122
Tandem Axle- Dual Wheel	675 (98 psi)	10.66 (4.20)	34	122
Tandem Axle- Dual Wheel	744 (108 psi)	10.6 (4.18)	34	122
Tandem Axle- Dual Wheel	875 (127 psi)	10.4 (4.09)	34	122
Tridem Axle- Dual Wheel	660 (95.72 psi)	10.3 (4.06)	34	122

Also, to evaluate the structural response of PAP with actual pores, modelling of Porous asphalt pavement with different void contents of PAC mix is executed using ABAQUS software. Pores in asphalt layer are assumed to be square shaped and extending from top to bottom of PAC layer as in^[8] .It is assumed that 40 kN wheel load is equally distributed over the contact surface with tire pressure of 700 kPa. In this part of study PAC layer with various void percentages of 16.4%, 17.7%, 18.9%, 20%, 21%, 22.1%, 24%, 25%, 26%, 28% has been analyzed with constant pore size of 3mm x 3mm. For ease of computation, size of top PAC layer with pores has been limited to 210 x 200 mm so as to accommodated stress area of 198 x 144mm, representing the half wheel load of area ^{[12] [23]}. The size of choker course, stone bed reservoir and subgrade are 1400 x 600mm to show half width of pavement. For proper meshing of pores in PAC layer tetrahedral elements are used.

Development of ANN prediction model:

The data collected provided a fair insight into the parameters affecting the permeability and voids in PAC mix. From the data collected, relation between voids in total mix and permeability coefficient of PAC was established as in (Fig. 1). Artificial Neural Networks (ANN) were successfully implemented to develop a prediction model from data collected for porous asphalt gradations. The application of ANN in this part was mainly focused on prediction of void percentages in a given PAC mix. A three-layered feed forward error-back propagation ANN architecture was used. From regression plots as given in (Fig. 2), 15-10-1 ANN model was selected as better prediction model to predict void percentages in PAC mix with coefficient of correlation as 0.994 and mean square error of 0.106. Further the test data of 15 samples was provided for evaluation of 15-10-1 ANN model and results obtained in (Fig. 3) depict that the predicted and actual void percentages of PAC gradation test data show good agreement as plotted.

This model was further used to evaluate the effect of the mix parameters on PAC mix to produce different void percentages. In this part, effect of Optimum Binder Content (OBC) was analyzed for PAC mix properties. The results obtained indicates that increase in OBC of PAC mix causes decrease in void percentage for that particular mix.

Analysis of Porous Asphalt Pavement in KENPAVE software:

The result outputs of KENPAVE for each of the cross-sections analyzed gives the idea of variation for maximum deflection, maximum vertical stresses, maximum tensile strain and maximum compressive strain at each point along the depth of pavement. To check for rutting analysis, we consider for Fatigue analysis Maximum Horizontal Tensile Strain (ε_t) at the bottom of PAC layer and Maximum Vertical Compressive Strain (ε_z) at the top of sub-grade layer is considered. Then those (ε_z) and (ε_t) values helped in estimating maximum allowable number of load repetitions for preventing rutting failure (N_r) and Fatigue failure (N_f) simultaneously for any cross section ^[16]

It is observed from the graphical analysis that cross-section E is providing maximum allowance for load repetitions in view of fatigue cracking (N_f), that is 2.8^E + 06 cycles of single axle dual wheel load. Also, it can be observed that cross-section E is allowing maximum number of load repetitions in case of rutting failure (N_r), that is 2.7 ^E+08 cycles of single axle dual wheel load and hence the optimum cross-section that is satisfying failure resisting conditions is the cross-section E. So cross section E is considered be the best arrangement of layers in terms of pavement performance. The layer thicknesses of cross-section E are: PAC top layer = 10 cm; Choker course = 5 cm; Stone bed reservoir = 45cm

The result outputs of KENPAVE for cross-section E with different subgrade materials analyzed gives the idea of the damage expected during the service life of pavement along with the damage ratios and expected design life of pavement. The results obtained from the analysis indicate that the design life of pavement with gravelly soil subgrade, which is the most preferred soil for construction of porous asphalt pavement due to its good permeability, is obtained as 15.32 years with least damage ratio of 0.0653. Also, the maximum damage ratio for clay soil is 0.3 and there is 77.74% reduction in design life as compared to the Pavement with gravelly soil subgrade. The allowable number of repetitions for preventing fatigue failure ranges between 7.66 ^E+06 & 5.31^E + 06. The allowable number of repetitions for preventing rutting failure is maximum for gravely soil subgrade i.e., 3.98 ^E+08 and least for clay soil subgrade i.e. 1.7 ^E+06

Effect of different axle configurations as well as tire pressures was successfully evaluated for porous asphalt pavement with the help of KENLAYER. Damage analysis was performed for various configurations and tire pressures to evaluate the performance of PAC pavement. The maximum design life of 15.32 years was obtained for single axle dual wheel assembly with contact pressure of 550 kPa. The least design life of 2.37 years was obtained for tandem axle dual wheel configuration with contact pressure of 875 kPa. There is 84.53% reduction in design life of PAC pavement for tandem axle dual wheel configuration with 875 kPa as compared to single axle dual wheel assembly with 550 kPa contact pressure. In case of tandem axle dual wheel configuration, different contact pressures reveal different result. For tandem axle dual wheel configuration, maximum design life is obtained for 480 kPa contact pressure i.e. 9.6 years and least design life of 2.37 years was obtained for 875 kPa contact pressure.

It can be seen from results that maximum damage ratio obtained for bottom of top PAC layer is more for tridem axle configuration and tandem axle assemble with 875 kPa tire pressure. The value of damage ratio at bottom of PAC layer is maximum, i.e. 1.49^e − 01, for tandem axle configuration with 875kPa tire contact pressure, followed by tridem axle configuration of 660kPa tire contact pressure with damage ratio equal to 1.03^e − 01. In case of damage ratios obtained on top of subgrade, the value obtained is very less than 1. The maximum damage ratio obtained on top of subgrade is equal to 2.03^e − 04, indicating least effect of tire pressure on damage of pavement due to rutting.

Analysis of Porous Asphalt Pavement in ABAQUS software:

Prior to modelling of PAP in ABAQUS, comparative study between KENPAVE and ABAQUS was carried out for evaluation of ABAQUS software to model pavement structure and evaluate the critical responses. Results from the comparative study indicate the suitability of ABAQUS software to model PAP with much comparable results obtained in both computer Programme.

The usefulness of ABAQUS was evaluated by modelling of actual pores in PAC layer, which is not otherwise possible in KENPAVE software. Porous Asphalt Pavement was successfully modeled in ABAQUS software with actual pores modeled in top PAC layer. Results obtained from ABAQUS analysis (Fig. 4) show that, with increase in void percentage in PAC mix, vertical stress dissipated on layers under PAC layer decrease. For a void percentage of 16.4%, vertical stress under PAC layer is 267 kPa, whereas for 28% voids vertical stress dissipated below PAC layer is 243 kPa. Consequently, displacement under PAC decreases with increasing percentage of voids in PAC mix.

It is also observed that with increase in percentage of voids in PAC mix, horizontal tensile strain at bottom of PAC layer increases leading to early fatigue failure of pavement. For the lowest void percentage of 16.4%, horizontal tensile strain at bottom of PAC layer is 2.48^e-04 and for highest void percentage of 28%, horizontal tensile strain at bottom of PAC layer is 5.53^e-04. Similarly number of repetitions for fatigue failure is 7.8^e + 05 for 16.4%voids and for 28% voids, no. Of allowable repetition are 5.6^e + 04. The impact of horizontal stress is mostly in PAC layer and horizontal tensile stresses under the wheel load increase with increase in the percentage of voids. For void percentages in range of 16 to 19% horizontal strain at bottom of PAC layer is less than 3^E-04 and there is not much reduction in allowable number of repetitions to fatigue failure. From (Fig. 5), it is quite evident that void content in PAC layer has more prominent effect on horizontal tensile below PAC layer rather than vertical compressive strains. Since horizontal tensile strain below PAC layer is responsible for fatigue failure in pavement, increasing total void percentage in PAC layer may lead to early deterioration of porous asphalt pavement due to lesser allowable number of repetitions to fatigue failure.

Thickness of PAC layer has a dominant effect on functional and structural performance of pavement with respect to allowable number of repetitions to fatigue and rutting failure. In case of fatigue failure, an increase in the PAC layer thickness increases the maximum allowance for load repetitions to fatigue damage. Decreasing the PAC layer thickness lowers the maximum allowable number of load repetitions to fatigue damage.
Also, for rutting failure, an increase in the PAC layer thickness increases the maximum allowance for load repetitions to rutting failure of PAP. Decreasing the PAC layer decreases the maximum allowable number of load repetitions to rutting failure. So, for better performance of PAP in view of traffic capacity, 150 mm thickness of PAC layer is proposed.
The type of subgrade soil in pavement has notable effect on rutting failure of pavement with respect to allowable load repetitions for preventing the rutting failure, with clayey soil as subgrade showing drastic reduction in design life of PAP. Subgrade soil in pavement has least effect on fatigue failure of pavement and does not have much impact on allowable load repetitions to fatigue failure in pavement.
Further from KENPAVE analysis of PAP for different tire pressure, it was concluded that with increase in tire pressure, stresses increase at the bottom of PAC layer. The value for damage ratio obtained corresponding to PAC top layer and top of subgrade show that maximum damage occurs at bottom of PAC layer, thus causing fatigue failure. This concludes that increased tire pressure has worst effect on porous asphalt layer and thus layer gets deteriorated much earlier than its usual designed period due to high tire pressures.
Increase in tire pressure does not have much effect on allowable number of load repetitions for causing rutting failure.
From the results obtained from ABAQUS software, it was deduced that with increase in void content in PAC layer, there is a slight decrease in vertical compressive stress and vertical displacement along the depth of the pavement.
Also, it has also been observed that as the void percentage is increased, tensile stress generated at the bottom of the PAC layer under the wheel load increases. Since with increase in the void percentage, the number of particles to resist the tensile forces at the bottom layer decreases. This in turn increases the tensile stress and hence the tensile strain at the bottom of the PAC layer as can be seen in results. Hence, it can be concluded that increasing the void percentage in PAC layer increases the chances of fatigue failure in pavements.
The voids in PAC mix vary linearly with the coefficient of permeability.
ANN prediction model was developed to predict void content in different PAC mixes with 10 neurons in hidden network found suitable for the network. The predicted void percentage was compared with actual void percentage using coefficient of correlation (R) which was found to be satisfactory i.e. equal to 0.994. This shows that model is capable of predicting void percentages in any PAC gradation mix with low error rates and in a short span of time.
Effect of optimum binder content was analyzed for a particular gradation. The results indicated that low optimum binder content produces more void content for that PAC gradation mix.
Although versatility of proposed ANN prediction model in this study is limited to the available data set, but this network can easily be improved with addition of more data and can be satisfactorily used to evaluate the effect of other input parameters on void content of PAC mix.

Author Contribution

Note: Competing Interests and Funding Information:• The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.• All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Yateen Lokesh, Dr. Harshad R Parate , Dr. H M Rajashekhar Swamy and Humaira Ali . The first draft of the manuscript was written by Yateen Lokesh and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.• Authors declare that no funding was received for conducting this study.• The authors have no competing interests to declare that are relevant to the content of this article.

Acknowledgement

Authors are thankful to Ramaiah University of Applied Sciences, Bangalore for extending their support with the necessary facilities in conducting the research.

Data Availability Statement (DAS):

The authors declare that the data supporting the findings of this study are available. Upon request the data can be provided by contacting the corresponding author (Mr. Yateen Lokesh).

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No competing interests reported.

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You are reading this latest preprint version

Development of Prediction Model for Structural Behavior and Gradation of Porous Asphalt Pavement

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Version 1

Abstract

Figures

Introduction

Methodology

Result and Discussions

Development of ANN prediction model:

Analysis of Porous Asphalt Pavement in KENPAVE software:

Analysis of Porous Asphalt Pavement in ABAQUS software:

Conclusion

Declarations

Author Contribution

References

Additional Declarations

Status:

Version 1