The Use of Average Least Dimension in Surface Dressing Design

The Use of Average Least Dimension in Surface Dressing Design

RE-PAV-00001

April 2021

Prepared by PMS Pavement Management Services Ltd.

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TII Publication Title The Use of Average Least Dimension in Surface Dressing Design

TII Publication Number RE-PAV-00001

Activity Research (RE) Document Set Technical

Stream Pavement (PAV) Publication Date April 2021

Document Number

00001 Historical Reference

N/A

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TRANSPORT INFRASTRUCTURE IRELAND (TII) PUBLICATIONS

Page i

TII Publications

Activity: Research (RE)

Stream: Pavement (PAV)

TII Publication Title: The Use of Average Least Dimension in Surface Dressing Design

TII Publication Number: RE-PAV-00001

Publication Date: April 2021

Set: Technical

Contents

1. Introduction ................................................................................................................. 2

2. Background ................................................................................................................. 3

3. Methods Used for Average Least Dimension ........................................................... 5

4. Sampling and Testing of Surface Dressing Chips ................................................... 8

5. Analysis of Results ................................................................................................... 10

6. Conclusions ............................................................................................................... 16

7. References ................................................................................................................. 17

....................................................................................................................... 18

Particle Size Distributions .................................................................................................... 18

TII Publications RE-PAV-00001 The Use of Average Least Dimension in Surface Dressing Design April 2021

Page ii

Contents Table

1. Introduction ................................................................................................................. 2

2. Background ................................................................................................................. 3

3. Methods Used for Average Least Dimension ........................................................... 5

3.1 Direct Measurement Methods ............................................................................. 5

3.2 Computational Methods ...................................................................................... 5

4. Sampling and Testing of Surface Dressing Chips ................................................... 8

4.1 Sampling ............................................................................................................. 8

4.2 Sample Reduction .............................................................................................. 8

4.3 Laboratory Testing .............................................................................................. 9

5. Analysis of Results ................................................................................................... 10

5.1 Median Size and Flakiness Index Results ........................................................ 10

5.2 Comparison of Machine ALD and Manual ALD ................................................ 11

5.3 Analysis of ALD Results ................................................................................... 11

5.4 Comparison of Nomograph ALD and Nomograph Equation ALD ..................... 12

5.5 Comparison of Nomograph Equation ALD and Dumas Equation ALD with Automated Machine ALD .................................................................................. 13

6. Conclusions ............................................................................................................... 16

7. References ................................................................................................................. 17

....................................................................................................................... 18

Particle Size Distributions .................................................................................................... 18


Page 1

Executive Summary

Surface dressing is the application of a thin layer of bituminous binder and single-sized aggregate chippings to the surface of a road, in one or more layers. The technique has been widely used on Irish roads for many years to improve skid resistance, seal the road surface and to arrest deterioration. The procedure has become increasingly important since the introduction of standards for skidding resistance on National roads by Transport Infrastructure Ireland (TII). TII have developed a new analytical design approach for surface dressing on National roads.

Based on best practice in other countries, an essential parameter used in the analytical design of surface dressing is the Average Least Dimension (ALD) of the aggregates used. The ALD is used to determine the optimum rates of spray of binder and rates of spread of chippings for surface dressing. The purpose of this research study carried out in 2015 was to determine the most appropriate way of calculating the ALD using surface dressing aggregates from Irish quarry sources. A total of five different methods were examined, two direct measurement methods and three computational methods. The direct measurement methods used included the use of a new device developed in South Africa to automatically measure ALD. The data for the study was collected by sampling and testing four different aggregate sizes from eight quarry sources nationwide. The testing included the determination of particle size distribution and flakiness index for each sample, in addition to determining the ALD by each of the five methods.

This report outlines the findings of the research study undertaken including an analysis of the range of ALD values obtained for Irish quarry sources, and a comparison of the three computational methods of estimating ALD against the direct measurement methods. In addition, the report recommends a method for calculating the ALD of Irish aggregates to be used in surface dressing.

KEY WORDS: Surface Dressing; Average Least Dimension; Irish Aggregates; Analytical Design Procedure, National Roads.


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1. Introduction

Surface dressing has been used extensively in Ireland for many years for the upkeep and maintenance of road pavements including national routes. In addition, expenditure on surface dressing represents a significant proportion of the road maintenance budget each year. It is therefore essential that surface dressings are properly designed to ensure they are durable for their expected life, provide value for money and maximise the return on investment.

A surface dressing consists of the uniform application of a thin layer of bituminous binder and single-sized aggregate chippings to the surface of a road, in one or more layers. The technique has been widely used on Irish roads to improve skid resistance, seal the road surface and to arrest deterioration. The procedure has become increasingly important since the introduction of the HD28/11 “Management of Skid Resistance” standard for skidding resistance on National roads published by Transport Infrastructure Ireland (TII), formerly the National Roads Authority (NRA) in 2011 [1]. In this regard, TII have developed a new analytical design approach for surface dressing on National roads. The approach was incorporated in a revision of TII Publication DN-PAV-03074 “Design of Bituminous Mixtures, Surface Treatments, and Miscellaneous Products and Processes” in June 2017 [2].

Based on research and best practice in other countries, an essential parameter used in the analytical design of surface dressing is the Average Least Dimension (ALD) of the aggregates used. The ALD is used to determine the optimum rates of spread of binder and chippings for surface dressing.

PMS Pavement Management Services Ltd. (PMS) was commissioned by TII to undertake a research study to determine the most appropriate method of calculating the ALD for surface dressing aggregates from Irish quarry sources. A total of five different methods were examined, two direct measurement methods and three computational methods. The objectives of the research were to assess the range of ALD values for Irish quarry sources, to compare the three computational methods of estimating ALD against the direct measurement methods, and to recommend a computational method for calculating ALD. The data for the study was collected by sampling and testing 4 different aggregate sizes from 8 quarry sources nationwide. The testing included the determination of particle size distribution and flakiness index for each sample, in addition to determining the ALD by each of the five methods.

The report outlines the findings of the research study undertaken including an analysis of the range of ALD values obtained for Irish quarry sources, and a comparison of the three computational methods of estimating ALD against the direct measurement methods. In addition, the report recommends a method for calculating the ALD of Irish aggregates to be used in surface dressing.

The findings of the research were used to carry out surface dressing trials at 12 sites in six local authorities. The outcomes of these trials were subsequently used to finalise the Surface Dressing Analytical Design procedure which was incorporated in a revision of DN-PAV-03074 in June 2017 [2].


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2. Background

Following an extensive literature review and study of best practice in other countries, it became clear that a key parameter used in the analytical design of surface dressing is the Average Least Dimension (ALD) [3, 4, 5, 6].

The surface dressing design methods used in Australia and New Zealand are based on work originally conducted by Hanson (1935) who developed an engineering approach to the selection of optimum rates of spread of binder and chippings for surface dressing [3, 4]. The procedure considered the volume of voids between the chippings after spreading and rolling, and the orientation the chippings adopt after trafficking. Hanson found that after construction and trafficking compaction, chippings will orient to the flattest direction and thereby adopt a position whereby their least dimension is vertical, hence giving rise to the concept of Average Least Dimension (ALD) as shown in Figure 1. To ensure that the aggregate chips are not submerged in binder during service, the average least dimension of the aggregates is used to determine an appropriate rate of spread of aggregate and binder [4].

Figure 1 Orientation of Chippings After Trafficking [7].

Figure 2 shows the states of embedment of surface dressing chippings. As shown in Figure 2, Hanson’s main observations were that:

1. Chippings when initially placed loose on the binder had a percentage voids of approximately 50%, which reduced to around 30% after construction rolling, and further reduced to about 20% under traffic compaction. This resulted in a single layer of chippings that bedded in with shoulder-to-shoulder contact after trafficking.

2. The amount of binder to be used is related to the volume of voids in the covering aggregate. Sufficient binder should be added so that between 65 to 70% of the voids are filled with binder when the aggregate is fully compacted under traffic.

3. The average depth of the aggregate layer after construction and traffic compaction is approximately equal to the ALD of the aggregate chippings used.

The least dimension of an aggregate particle is the smallest perpendicular distance between two parallel plates through which the particle will just pass. The average least dimension is the arithmetic mean of all the measured least dimensions of the aggregate particles measured [5]. There is significant overlap with the flakiness index, used for many years as an aggregate characteristic in surface dressing design in Ireland, but international practice has shown that the flakiness index alone does not fully capture the shape properties required.

Accordingly, it was decided to conduct research to determine the most appropriate way of calculating the ALD using surface dressing aggregates from Irish quarry sources.


Page 4

Figure 2 States of Embedment of Surface Dressing Chippings [2, 4].


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3. Methods Used for Average Least Dimension

A total of five different methods were examined, two direct measurement methods and three computational methods.

3.1 Direct Measurement Methods

In the two direct measurement methods, the ALD of an aggregate sample was determined by measuring the least dimension of every particle in a 200 chip representative sample of the overall sample, and dividing the total of the least dimensions by the number of particles measured. The direct measurement method was carried out in accordance with the test standard TMH1 Method B18(a) [5].

The first direct measurement method consisted of physical measurement whereby the least dimension of each of the 200 representative chippings was physically measured using a Vernier calipers. This method is extremely slow, tedious and time-consuming, and in reality provides a baseline with which other faster methods of ALD computation can be compared.

The second direct measurement method is a variation on the first, and consisted of machine measurement using a device developed in South Africa to automatically take dimension measurements of the 200 representative chippings as shown in Figure 3. The machine is operated using a computer, software and a control unit with the ALD value automatically calculated. This machine method is significantly faster than the Vernier calipers measurement, and effectively provides a more efficient method of generating a baseline ALD for comparison with the computational methods, but it is still considered to be much too time-consuming for routine measurement of ALD.

Figure 3 ALD Machine from South Africa.

3.2 Computational Methods

Three computational methods of estimating ALD were examined, and compared to the results obtained from the manual and mechanical measurements of ALD.

The first computational method uses a Nomograph as shown in Figure 4 [6, 7].

The Nomograph uses two key input parameters determined from routine laboratory testing, the median particle size and the flakiness index of aggregate in the sample.


Page 6

The median particle size is defined as the sieve size that 50% of the sample will pass through, and is determined by interpolation from a grading analysis using a full set of sieves.

Figure 4 Shell Nomograph [6, 7].

A second computational approach investigated the use of an equation developed to replicate the results obtained from the Nomograph [3]. The key input parameters are again flakiness index and median particle size. The equation is

ALD = (Me)/(1.139285 + (0.011506 x FI))

where:

Me = Median Particle Size (mm)

FI = Flakiness Index

Finally, a new and more complex computational approach developed by Dumas in South Africa was investigated [8]. In the cases of the Nomograph and Nomograph equation methods, the median particle size is the only variable which describes the particle size distribution of the aggregates. The underlying principle of the Dumas method is that the median on its own cannot fully reflect the characteristics of the particle size distribution. Hence, more information is required in addition to the median.

The approach taken in essence is to characterise the particle size distribution based on percentage passing and percentage retained on five sieves, rather than the single interpolated sieve used to define median particle size.

The Dumas approach is based on examination of the percentage retained (PR) from the gradation analysis for five different PR values, 10%, 25%, 50%, 75% and 90%. The PR values are used to determine the degree of peakiness (K-value) and degree of symmetry (S-value) which are used together with the median value (Me), flakiness index (Fi) and fraction not measured (Fr) to calculate the ALD [8, 9].


Page 7

The calculation process described by Dumas is quite complex, but has been developed in this research through a Microsoft Excel spreadsheet, with the calculated ALD values derived directly from the full gradation analysis results and the flakiness index. The full Dumas equation and values required for this computational method are outlined in the test standard TMH1 Method B18(b)T [9].


Page 8

4. Sampling and Testing of Surface Dressing Chips

4.1 Sampling

PMS Pavement Management Services Ltd. (PMS) was commissioned by TII to carry out sampling and laboratory testing of 6mm, 10mm, 14mm and 20mm nominal size chippings from eight quarry sources nationwide. The sampling was carried out from stockpiles in each quarry in accordance with IS EN 932 Part 1 [10]. The eight quarry sources are labelled A to H. The sources selected typically provide chippings of high polished stone value (PSV) for surface dressing on National routes. The samples were taken from stockpiles at each quarry in March 2015, with 29 quarry source/aggregate size samples taken in total. The samples were taken in 20kg sample size bags. Table 1 shows a summary of the number of 20kg samples by size taken at each quarry.

Table 1 Summary of Quantity Sampled.

4.2 Sample Reduction

The bulk samples taken in the quarries for each nominal size of aggregate were reduced down to a workable quantity and to obtain a representative sample of chippings for the laboratory testing using a riffle box procedure in accordance with IS EN 933 Part 2 [11]. The various sizes of aggregate chippings were split down into the following approximate test sample quantities for each test:

Grading and Flakiness Index:

• 5.0kg samples for 20mm aggregate




Source 20mm 14mm 10mm 6mm

Quarry A 2 2 2 1

Quarry B 2 2 2 1

Quarry C N/A 2 N/A 1

Quarry D 2 2 2 1

Quarry E 2 2 2 1

Quarry F 2 2 2 1

Quarry G N/A 2 2 1

Quarry H 2 2 2 1

Total 12 16 14 8

Number of Samples (20kg) Taken by Size

N/A = Not Avai lable


Page 9

Average Least Dimension (ALD):

• 10kg of each aggregate size

4.3 Laboratory Testing

The grading analysis and flakiness index were carried out on the 6mm, 10mm, 14mm and 20mm aggregate samples from each quarry source. The grading analysis was carried out in accordance with IS EN 933 Part 1, and the flakiness index was determined in accordance with IS EN 933 Part 3 [12, 13].

The ALD was determined for the 10mm, 14mm and 20mm aggregate samples from each quarry source in accordance with the direct measurement method specified in TMH1 Method B18(a) [5]. The ALD was assessed by measuring the least dimension of every particle in a representative sample and dividing the total of the least dimensions by the number of particles measured. The measurements were recorded using the automated ALD machine shown in Figure 3 for all of the 10mm, 14mm and 20mm aggregate samples.

To obtain a representative sample of chippings for the ALD test, the test samples of aggregate were washed using a 2mm sieve and dried off. The test samples were then further split down using a riffler to such a size as to give at least 200 aggregate particles in each representative sample. The sample was then sieved through a sieve of aperture size that is half the nominal size of the aggregate to be tested and the particles passing through the sieve were discarded. Using the ALD device, the smallest dimension of each particle retained on that sieve is measured to the nearest 0.1mm and the measurements and number of particles measured is recorded.

The ALD is calculated to the nearest 0.01mm as follows

Average least dimension (mm) = A/B

where:

A = sum of the smallest dimension of all the particles (mm)

B = number of particles

The ALD value is reported to the first decimal place. The average least dimension was also determined by manual measurement, whereby the least dimension of each of the 200 representative chippings was physically measured using a Vernier calipers on four randomly selected test samples of aggregate for comparison with the ALD device results.


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5. Analysis of Results

5.1 Median Size and Flakiness Index Results

The median particle size (Me) and flakiness index (FI) results for each aggregate sample are given in Table 2. The Me and FI values were used to compute the ALD values for each sample using the Nomograph and the Nomograph equation. The Me and FI values were also used together with the calculated percentage retained (PR) values to compute the ALD using the more complex Dumas equation [8, 9].

Table 2 Median Particle Size and Flakiness Index Values.

QuarryNominal

Size (mm)

Median Size

(mm)

Flakiness

Index (%)

20 15.8 14.2%

14 11.6 8.6%

10 8.0 11.0%

6 4.8 13.0%

20 15.2 11.7%

14 12.1 17.5%

10 7.8 23.0%

6 4.3 21.9%

14 11.7 11.6%

6 5.0 27.5%

20 15.8 9.9%

14 11.7 11.1%

10 7.8 13.2%

6 3.9 15.7%

20 17.4 6.6%

14 11.2 12.9%

10 8.3 18.1%

6 5.0 20.7%

20 16.7 8.9%

14 12.0 13.4%

10 7.6 20.7%

6 5.1 16.7%

14 11.5 13.6%

10 8.4 15.6%

6 4.6 31.3%

20 16.0 15.6%

14 11.4 16.4%

10 7.8 14.5%

6 4.7 32.4%

Quarry H

Quarry B

Quarry A

Quarry C

Quarry D

Quarry E

Quarry G

Quarry F


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5.2 Comparison of Machine ALD and Manual ALD

The ALD values obtained for the four sets of measurements made using the automated ALD machine and the Vernier calipers are shown in Table 3.

The results of the manual measurements compare very well with the results from the ALD machine. The marginal differences between the two sets are well within the typical variability in ALD measurement encountered in practice. As outlined earlier, the automated ALD approach is considerably faster than the manual measurement and accordingly, the automated measurement approach was used for the remainder of the baseline measurements.

Table 3 Machine versus Manual ALD measurements.

5.3 Analysis of ALD Results

The compiled results for the ALD direct measurement and computational methods undertaken as part of this research are given in Table 4. The ALD values obtained for the eight Irish quarry sources ranged from 5 mm to 14 mm. This range of values are in the range covered by the Nomograph shown in Figure 4, and are similar to values calculated and used in other countries including Australia, New Zealand and South Africa.

Linear regression was used to perform the statistical analysis of the data from the study [14]. The regression and statistical data analysis was carried out using Microsoft Excel, and MINITAB, a widely used statistical package.

QuarryNominal

Size (mm)

Machine ALD

(mm)

Manual ALD

(mm)

Quarry B 20 11.7 12.2

Quarry D 20 12.0 12.2

Quarry E 14 7.9 8.2

Quarry G 10 5.7 5.9


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Table 4 Summary of ALD Results.

5.4 Comparison of Nomograph ALD and Nomograph Equation ALD

The ALD data calculated from median particle size and flakiness index results for each sample using the Nomograph and the Nomograph equation are plotted in Figure 5. There was very good agreement between the ALD values from both methods with a very high R2 of 99.7%. The regression equation without an intercept is given by:

Nomograph Equation ALD = 1.0097 x Nomograph ALD

These results indicate that the Nomograph equation gives effectively identical results to the Nomograph. It is much quicker and more efficient to use the equation rather than the Nomograph, and hence it is recommended that the Nomograph equation be adopted for use in preference to the Nomograph.

QuarryNominal Size

(mm)

Automated

ALD (mm)

Nomograph

ALD (mm)

Nomograph

Equation ALD

(mm)

Dumas

Equation ALD

(mm)

20 11.9 11.9 12.1 11.5

14 8.8 9.4 9.4 8.9

10 5.6 6.4 6.3 6.0

20 11.7 11.6 11.9 11.6

14 7.8 9.0 9.0 8.6

10 5.4 5.6 5.5 5.3

Quarry C 14 8.7 9.2 9.2 8.8

20 12.0 12.4 12.6 11.9

14 8.5 9.4 9.2 8.5

10 5.6 6.2 6.1 5.4

20 12.5 N/A 14.3 13.4

14 7.9 8.7 8.7 8.2

10 5.4 6.2 6.1 5.9

20 12.9 13.0 13.5 12.6

14 9.3 9.2 9.3 8.9

10 5.1 5.5 5.5 5.3

14 8.1 8.9 8.9 8.4

10 5.7 6.5 6.4 5.9

20 11.2 11.8 12.1 11.7

14 8.4 8.5 8.6 8.1

10 5.0 6.0 6.0 5.3

Quarry H

Quarry A

Quarry B

Quarry D

Quarry E

Quarry F

Quarry G


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Figure 5 Plot of Nomograph ALD Versus Nomograph Equation ALD.

5.5 Comparison of Nomograph Equation ALD and Dumas Equation ALD with Automated Machine ALD

The main purpose of the research was to determine the most appropriate method of computation of ALD for Irish aggregates. The ALD values obtained using the automated ALD machine was used as the baseline data. Figure 6 shows a plot of the Automated ALD (X-axis) versus the ALD computed using the Nomograph equation and the Dumas equation. As can be seen, there is a strong linear relationship with both computed ALD values.

The Dumas approach yields a slightly higher R2 at 98.3% versus 98.0% for the Nomograph equation. The two computational methods do give different results, with a clear separation in the trend lines visible in Figure 6.

Figure 7 shows the same data as Figure 6, but this time with a “forced” regression having a zero intercept. It is clear from Figure 7 that the Dumas computed ALD yields an almost exact 1:1 relationship with the automated ALD. The slope of the regression line is 1.011, with a very high R2 of 98.1%. The slope of the regression line between the Nomograph equation ALD and the automated ALD is significantly higher, at 1.069, and has a slightly lower R2 value of 97.7%. There is still a very good correlation between the two sets of ALD results, but the Dumas relationship is preferable.


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Figure 6 Plot of Machine ALD Versus Nomograph Equation and Dumas Equation ALD.

Figure 7 Plot of Machine ALD Versus Nomograph Equation and Dumas Equation ALD (no intercept).


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The residual errors between the observed and the fitted values for the regression analysis of Machine ALD versus Dumas equation ALD are shown in Figure 8 with almost all of the residuals between –0.5mm and +0.5mm.

Figure 8 Residual Plots for Regression Analysis of Machine ALD Versus Dumas Equation ALD.


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6. Conclusions

TII have developed a new analytical design approach for surface dressing on National roads which was incorporated in a revision of DN-PAV-03074 in June 2017. The Average Least Dimension (ALD) of the chippings used is an essential parameter in the analytical design procedure.

A large scale research project was undertaken to investigate the use of the ALD parameter in analytical Surface Dressing design in Ireland and to determine the most appropriate way of calculating the ALD for Irish aggregates. A total of five different methods were examined, two direct measurement methods and three computational methods. The objectives of the research were to assess the range of ALD values for Irish quarry sources, to compare the three computational methods against the direct measurement methods, and to recommend a computational method for calculating ALD.

Testing was carried out on 10 mm, 14 mm and 20 mm aggregates sourced from eight Irish quarries that supply large volumes of aggregate to surface dressing operations. A new device developed in South Africa to automatically measure ALD was used in the study to provide the baseline data for comparison with the computational methods. The computed ALD values were obtained from the gradation and flakiness index results using a direct Nomograph approach, an equation approach based on the Nomograph, and a more complex computational approach developed by Dumas in South Africa.

The ALD values obtained for the eight quarry sources ranged from 5 mm to 14 mm which were in the range covered by the Shell Nomograph, and are similar to values seen in other countries including New Zealand, Australia and South Africa.

The analysis of the Irish results showed that the Nomograph equation gave virtually identical results to the direct Nomograph results. Accordingly, it is recommended that the equation should be adopted in preference to the Nomograph as it is quicker to use and less subject to variation.

The Nomograph equation ALD and the Dumas equation ALD both showed good agreement with the machine measured ALD, with the Dumas equation showing a better overall relationship. Based on examination of regression results, it is recommended that the Dumas approach should be used to determine the computed ALD as it more fully reflects the characteristics of the particle size distribution of the aggregates, and it gives a better relationship to the actual measured ALD. Using the Dumas method, the ALD can be accurately calculated using results from standard gradation and flakiness index laboratory testing for surfacing dressing aggregates.

The findings of the research have been used to carry out surface dressing trials in 2015 at 12 sites in six local authorities. The outcomes of these trials were subsequently used to finalise the Surface Dressing Analytical Design procedure which was incorporated in a revision of DN-PAV-03074 in June 2017 [2].


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7. References

[1] TII Publications (Standards), Management of Skid Resistance, AM-PAV-06045-01 (HD28/11), Transport Infrastructure Ireland, November 2011.

[2] TII Publications (Standards), Design of Bituminous Mixtures, Surface Treatments, and Miscellaneous Products and Processes, DN-PAV-03074-02, Transport Infrastructure Ireland, June 2017.

[3] National Cooperative Highway Research Program (NCHRP) Report 680, Manual for Emulsion-Based Chip Seals for Pavement Preservation, Transportation Research Board, Washington DC, 2011.

[4] Transit NZ, RCA, Roading NZ, Chipsealing in New Zealand, Transit New Zealand, Road Controlling Authorities, Roading New Zealand, Wellington, New Zealand, 2005.

[5] TMH1 Method B18(a), The Determination of the Average Least Dimension of Aggregates by Direct Measurement, Standard Test Methods, Technical Methods for Highways, Pretoria, South Africa, 1986.

[6] Jackson G. P., Surface Dressing. Bitumen Division, Shell International Petroleum Co. Ltd., London, 1963.

[7] The Shell Bitumen Handbook (5th Ed.), D. Whiteoak, Shell Bitumen UK, July 1990, 281-292.

[8] Dumas, B., Determination of the Average Least Dimension of Surfacing Aggregates by Computation, Proceedings of the 8th Conference on Asphalt Pavements for Southern Africa (CAPSA’04), Sun City, South Africa. September 2004.

[9] TMH1 Method B18(b)T, Computational Method for the Determination of the Average Least Dimension of Surfacing Aggregates, Technical Methods for Highways, Pretoria, South Africa, 2001/03.

[10] IS EN 932 Part 1: 1997; Test for General Properties of Aggregates – Part 1: Methods for Sampling, National Standards Authority of Ireland, 1997.

[11] IS EN 932 Part 2: 1999; Test for General Properties of Aggregates – Part 2: Methods for Reducing Laboratory Samples, National Standards Authority of Ireland, 1999.

[12] IS EN 933 Part 1: 2012; Test for Geometrical Properties of Aggregates – Part 1: Determination of Particle Size Distribution – Sieving Method, National Standards Authority of Ireland, 2012.

[13] IS EN 933 Part 3: 2012; Test for Geometrical Properties of Aggregates – Part 3: Determination of Particle Shape - Flakiness Index, National Standards Authority of Ireland, 2012.

[14] Applied Linear Statistical Models, Michael H. Kutner, John Neter, Christopher J. Nachtsheim, William Li, McGraw-Hill College, 5th Edition, November 2004.


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Particle Size Distributions


Page 19

Sample Size: 20 mm

Quarry Source Quarry A Quarry D Quarry E Quarry F Quarry H Quarry B

Sample Reference No. NRA15006/1.8 NRA15012/1.7 NRA15011/1.7 NRA15010/1.7 NRA15009/1.7 NRA15013/1.7

EN Sieve Size % Passing % Passing % Passing % Passing % Passing % Passing

25 mm 100 100 100 100 100 100

20 mm 97.5 96.9 86.8 87.0 93.2 98.9

16 mm 54.1 54.0 31.2 41.9 50.6 68.1

14 mm 20.3 20.0 11.1 18.2 20.8 23.9

12.5 mm 6.5 7.9 2.8 9.0 6.0 5.3

10 mm 3.7 3.5 1.2 3.6 2.1 1.8

8 mm 3.3 2.5 1.0 2.0 1.5 1.2

6.3 mm 3.2 2.2 1.0 1.2 1.4 0.9

5 mm 3.2 1.9 1.0 0.7 1.3 0.8

4 mm 3.2 1.7 1.0 0.6 1.3 0.7

2 mm 3.1 1.3 0.9 0.5 1.1 0.6

1 mm 3.0 1.2 0.9 0.5 1.0 0.6

500 µm 2.9 1.2 0.9 0.4 1.0 0.5

425 µm 2.9 1.2 0.9 0.4 1.0 0.5

250 µm 2.7 1.2 0.9 0.4 0.9 0.5

150 µm 2.3 1.1 0.8 0.4 0.9 0.5

125 µm 2.1 1.1 0.8 0.3 0.9 0.4

63 µm 1.6 0.9 0.7 0.3 0.7 0.4


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Sample Size: 14 mm

Quarry Source Quarry A Quarry D Quarry E Quarry G Quarry F Quarry H Quarry B Quarry C

Sample Reference No. NRA15006/3.8 NRA15012/3.7 NRA15011/3.7 NRA15008/1.5 NRA15010/3.7 NRA15009/3.7 NRA15013/3.7 NRA15007/1.5

EN Sieve Size % Passing % Passing % Passing % Passing % Passing % Passing % Passing % Passing

25 mm 100 100 100 100 100 100 100 100

20 mm 100 100 100 100 100 100 100 100

16 mm 100 100 100 99.0 97.8 99.6 100 99.8

14 mm 97.7 91.2 98.0 93.2 84.6 88.8 93.7 95

12.5 mm 71.3 64.6 78.8 69.3 58.4 71.0 58.2 68.1

10 mm 11.7 19.9 22.7 21.1 12.7 22.9 5.3 10

8 mm 0.9 6.0 3.5 4.0 2.7 6.1 1.6 2

6.3 mm 0.7 3.1 0.9 1.5 1.6 3.3 1.3 1.6

5 mm 0.7 2.4 0.3 1.0 1.2 2.6 1.1 1.5

4 mm 0.7 2.1 0.3 0.9 1.1 2.4 1 1.4

2 mm 0.7 2.0 0.2 0.8 0.9 2.2 0.9 1.3

1 mm 0.7 1.9 0.2 0.8 0.8 2.1 0.8 1.2

500 µm 0.6 1.8 0.2 0.7 0.7 2.0 0.8 1.1

425 µm 0.6 1.8 0.2 0.7 0.7 1.9 0.8 1.1

250 µm 0.6 1.8 0.2 0.7 0.6 1.7 0.8 1.1

150 µm 0.6 1.7 0.2 0.7 0.6 1.3 0.7 1

125 µm 0.6 1.7 0.2 0.7 0.6 1.2 0.7 0.9

63 µm 0.5 1.3 0.1 0.6 0.5 0.7 0.7 0.8


Page 21

Sample Size: 10 mm

Quarry Source Quarry A Quarry D Quarry E Quarry G Quarry F Quarry H Quarry B

Sample Reference No. NRA15006/6.8 NRA15012/5.7 NRA15011/5.7 NRA15008/3.5 NRA15010/5.7 NRA15009/5.7 NRA15013/5.7

EN Sieve Size % Passing % Passing % Passing % Passing % Passing % Passing % Passing

25 mm 100 100 100 100 100 100 100

20 mm 100 100 100 100 100 100 100

16 mm 100 100 100 100 100 100 100

14 mm 100 100 100 100 100 100 100

12.5 mm 100 100 100 100 100 100 100

10 mm 94.7 88.0 91.8 85.5 95.5 98.3 91.9

8 mm 51.1 53.0 44.0 40.2 59.8 54.2 54.7

6.3 mm 11.6 24.3 7.1 14.7 19.8 20.3 20.2

5 mm 1.1 11.1 1.0 6.5 3.0 9.6 3.1

4 mm 1.0 6.5 0.7 5.0 1.1 5.6 1.4

2 mm 0.9 3.5 0.6 3.3 0.4 2.6 1

1 mm 0.9 3.2 0.5 2.6 0.3 2.2 0.8

500 µm 0.9 3.1 0.5 2.3 0.3 2.1 0.7

425 µm 0.9 3.0 0.5 2.2 0.2 2.1 0.7

250 µm 0.8 3.0 0.5 2.0 0.2 2.1 0.6

150 µm 0.8 2.8 0.4 1.8 0.2 2.0 0.6

125 µm 0.8 2.8 0.4 1.7 0.2 1.9 0.6

63 µm 0.7 2.0 0.3 1.4 0.1 1.6 0.6


Page 22

Sample Size: 6 mm

Quarry Source Quarry A Quarry D Quarry E Quarry G Quarry F Quarry H Quarry B Quarry C

Sample Reference No. NRA15006/8.8 NRA15012/7.7 NRA15011/7.7 NRA15008/5.5 NRA15010/7.7 NRA15009/7.7 NRA15013/7.7 NRA15007/5.5

EN Sieve Size % Passing % Passing % Passing % Passing % Passing % Passing % Passing % Passing

25 mm 100 100 100 100 100 100 100 100

20 mm 100 100 100 100 100 100 100 100

16 mm 100 100 100 100 100 100 100 100

14 mm 100 100 100 100 100 100 100 100

12.5 mm 100 100 100 100 100 100 100 100

10 mm 100 99.5 99.8 100 100 100.0 100 100

8 mm 100 99.3 99.1 100 99.5 99.7 100 99.7

6.3 mm 98.9 95.4 85.3 95.5 90.8 93.5 97.5 91.1

5 mm 56.7 76.9 50.2 61.9 45.4 55.2 72.1 51.4

4 mm 13.8 51.2 22.9 31.5 14.4 38.7 38.8 20.4

2 mm 2.7 12.6 1.8 7.5 1.8 3.2 5.3 2.9

1 mm 2.3 8.6 0.4 3.6 0.9 2.2 3.2 2

500 µm 2.0 7.7 0.3 2.8 0.7 2.0 2.9 1.9

425 µm 1.9 7.6 0.3 2.8 0.7 1.9 2.8 1.9

250 µm 1.9 7.2 0.3 2.5 0.6 1.7 2.5 1.8

150 µm 1.7 6.6 0.3 2.3 0.6 1.6 2.4 1.7

125 µm 1.7 6.4 0.3 2.2 0.5 1.6 2.3 1.6

63 µm 1.5 4.6 0.3 2.0 0.5 1.4 2.1 1.4


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The Use of Average Least Dimension in Surface Dressing Design