Incorporating heavy vehicles into seal designs

Incorporating heavy vehicles into seal designs Kym Neaylon Opus Research, Opus International Consultants

Abstract—The foremost challenge facing spray seal designers and practitioners is the performance of sprayed seals under the increasing numbers of large heavy vehicles on major transportation routes connecting capital cities and in rural areas, particularly in Australia.

axle? If not, should the increase in multiple axles influence the way that heavy vehicles are accounted for in the seal design process?

The objective of this paper is twofold. Firstly, the loadings permitted on single, tandem and triaxle groupings have been calculated such that the multiple axles cause the same damage as the more lightly loaded single axles. This is based on pavement theory. However, do these axle groupings and loadings that cause the same damage to a pavement, cause different damage to a sprayed seal? Would one triaxle cause the same spray seal wear as a single axle? If not, should the increase in multiple axles influence the way that heavy vehicles are accounted for in the seal design process? The paper investigates these questions by analysing data obtained under the Australian Accelerated Loading Facility. Secondly, it would be simple for seal designers if the pavement design concept of ESAs could be input into heavyvehicle seal design. The concept of ESAs is interconnected with the 4th power law, which has been variously derived with definitions of pavement damage such as vertical elastic deformation (Benkelman beam), plastic deformation (rutting) and a pavement serviceability index (roughness). Vertical elastic deflection, rutting and roughness are not typical failure modes for sprayed seals or chip seals.

Fig. 1. changing

The proportion of multiple axles to single axles is

Does a load damage exponent of 4 apply to sprayed seal wear? Should it be 3.1 or 2.0? This paper suggests that the load damage exponent is closer to 1. Keywords — Chip seal; sprayed seal; seal design; heavy vehicles; multiple axles; load damage exponent; thin flexible surfacing

I. INTRODUCTION The foremost challenge facing many spray seal designers and practitioners is the performance of sprayed seals under the increasing numbers of large heavy vehicles on major transportation routes, particularly connecting capital cities and in rural areas of Australia. Firstly, there is a changing proportion of single axles to multiple axles in the transport fleet [1] as a result of freight efficiency (Fig. 1). The allowable loadings permitted on single, tandem and triaxle groupings (Fig. 2) have been calculated such that the multiple axles cause the same damage as the more lightly loaded single axles [2]. This is based on pavement theory. However, do these axle groupings and loadings that cause the same damage to a pavement, cause different damage to a sprayed seal? Would one of the triaxles shown in Figure 1 cause the same spray seal wear as a single

Fig. 2. Example of a multiple axle groups

This paper focusses on determining whether a) the concept of heavy vehicle ESAs as developed for pavement designers is applicable for sprayed seal design, which then leads to a seal damage model; and b) the determination of a load damage exponent applicable for a sprayed seal on a typical Australian rural granular pavement.

II. CURRENT PRACTICE HEAVY VEHICLE SEAL DESIGN Sprayed seal design methods have evolved over the years, mostly building upon Frederick Melrose Hanson’s landmark work in 1935 [3], [4].

Australian approach of a traffic adjustment for heavy vehicles was recommended, and included the Australian definitions and allowances for heavy vehicles, large heavy vehicles and equivalent heavy vehicles.

An overview of global practice shows diverging approaches to the handling of heavy vehicles in sprayed seal design, as shown in Table I. Of particular interest is the conversion of raw data into a variety of design inputs.

The Project 14-7 report was then endorsed and rebadged by the American Association of State Highway and Transportation Officials in 2012 [12]. However, this progression does not appear to have been widely adopted in any recent State DoT publications and manuals at the time of this paper.

TABLE I.

SUMMARY OF HEAVY VEHICLE SEAL DESIGN TRAFFIC INPUTS Reference

Large heavy vehicles

Raw data converted for design input into units of:

Commercial vehicles

Raw data used Average annual daily traffic

Country

UK influenced tropics and subtropics Republic of South Africa New Zealand – simple designs New Zealand – complex designs United Kingdom

Yes

No

No

Total vehicles/lane/day

Overseas road note 3 [5].

Yes

Yes

No

Equivalent light vehicles/lane/day

TRH3 [6].

Yes

Yes

No

Equivalent light vehicles/lane/day

Chipsealing in NZ [7].

Yes

Yes

No

Chipsealing in NZ [7].

No

Yes

No

North America

Yes

No

No

Equivalent light vehicles/lane/first 100 days accumulated Commercial vehicles only/lane/day Total vehicles/lane/day

Australia – simple designs Australia – complex designs

Yes

Yes

No

Yes

Yes

Yes

Total vehicles and % commercial vehicles/lane/day Total vehicles and % equivalent heavy vehicles/lane/day

2007

Road Note 39 [8]. NCHRP Synthesis 342 [9]. AP-T68/06 [10]. AP-T68/06 [10].

The design inputs vary considerably. In one extreme, heavy vehicles can be part of the average daily traffic count, and ignored. In the other extreme, traffic can be classified solely as the number of medium and heavy vehicles per day, and the light vehicles, or passenger cars, are ignored. Then there are countries where the medium and heavy vehicles are converted back into light vehicles, or passenger car equivalents. Australia converts medium and heavy vehicles into heavy vehicle equivalents (EHVs), and yet utilises the overall average daily traffic count as well. A seal design method based on the Australian Austroads AP-T68/06, Update of the Austroads Sprayed Seal Design Method [10] has been recommended for use in the US. This resulted from NCHRP Project 14-7, which was set up to provide a rational method for the design of chip seals over hot mix asphalt pavements. In this project report [11] the

III. METHOD Full scale accelerated pavement testing (APT) is used by pavement engineers around the world to improve understanding of pavement behavior and to evaluate new pavement materials, additives and alternative materials processing, and new construction techniques [13]. It also provides the ability to validate and calibrate new pavement models with minimal risk and a lower cost than full length construction. The opportunity as taken to investigate a chip seal behavior under APT Many potential variables (as detailed below) are likely to have interacted with the response being measured if they were not held as constant as possible. For this reason it has not been logical to use data gathered from field sites around Australia. For example, an early consideration was to completely use field testing, and to vary the traffic loading by varying the location study, for example one local road site, one State highway site, and one national highway site, with accurate traffic classification counts for each site. However, this would have added significant ‘noise’ to the data set, such as • different pavement materials and different construction quality (leading to different aggregate embedment into the base courses) • different seal ages (leading to a variety of binder viscosities to resist aggregate reorientation) • different rainfalls (leading to variable softening of basecourse near the shoulders, or to variable binder rise caused by water vapour) • different pavement temperatures (aggregate reorientation will occur faster at higher temperatures because of lower binder viscosities), and • unknown extraneous vehicles such as overweight vehicles (one outlier load could swamp the damage effect of the average daily traffic count). Accelerated pavement testing provides an opportunity to eliminate these variables. In 2006, Austroads initiated a research project titled The influence of multiple axle loads on pavement performance, to improve the understanding of the relationship between different multiple axle group loads (single, tandem, triaxles, as shown in Figure 2) on Australian flexible pavement types and road pavement performance [14]. The pavement chosen for the experiment was an unbound granular pavement with a thin bituminous surfacing. The

pavement was designed such that the materials and thickness were representative of a typical (i.e. not heavy duty) Australian state road. Full details of the pavement material and design are published in [15], [16], and [17]. The sprayed seal was designed using the Austroads design method [10] and is summarized in Table II. TABLE II. Application Prime First application Second application

TABLE III. Single axle dual tyre 40 kN load

Tandem axle dual tyre 60 kN Load

Tandem axle dual tyre 80 kN Load

Triaxle dual tyre 90 kN load

40 kN

60 kN

80 kN

90 kN

TABLE IV.

ALF TRIAL REGIMES

Experiment 3511

Total cycles 298,400

3507 3510

342,500 75,000

Date commenced 23 May 2010 20 Sep 2010 23 Jun 2011

3500

365,680

3 Aug 2011

60

3508 3503

278,232 322,600

80

3505

291,000

3506 3512

370,000 22,000

7 Dec 2009 22 Nov 2010 15 Mar 2010 19 Feb 2011 7 Feb 2012

3514

234,500

3502 3504

210,000 310,413

3501 3509

390,000

SEAL DESIGN SUMMARY

Material Bitumen emulsion SBR 3% latex emulsion binder 14 mm aggregate SBR 3% latex emulsion binder 7 mm aggregate

ALF EXPERIMENTAL LOADING REGIMES

Application rate 1.0 L/m2 1.2 L/m2 residual 100 m2/m3 0.5 L/m2 residual 340 m2/m3

The accelerated pavement tester uses was the Australian accelerated loading facility (ALF), as shown in Fig 3. The axle configuration could be changed from single axle (Fig 3) to tandem axle to triaxle (Fig 4).

Axle Single

Tandem

Load (kN) 40

Fig. 3. ALF operating indoors near Melbourne

Fig. 4. ALF with triaxle assembly fitted

The pavement was then loaded with a number of cycles of the axle assembly configurations as shown in Figure 4.23, until the testing program (shown in Table 4.8) was completed. The ALF assembly was fitted with driving wheels and limited steering, and was repositioned to a new pavement location for each experimental location.

Tri

90

Nil

Nil

3513

19 Mar 2012 15 Oct 2009 13 July 2010 18 Apr 2011 Rejected

Not proposed

Date completed 7 July 2010 16 Nov 2010 17 July 2011 Abandoned due to hydraulic oil spill 7 Oct 2011 Discard all data from site Ch 0 – 4 m 6 Feb 2010 10 Jan 2011 10 May 2010 12 Apr 2011 2 Mar 2012 Abandoned due to hydraulic oil spill 9 Jul 2012 19 Nov 2009 13 Sep 2010 14 Jun 2011 Test pavement failed to meet screening criteria of the falling weight deflectometer End of funding

All ALF experiments underwent a preconditioning (bedding-in) of 10,000 passes of a tandem axle loaded at 60 kN. After bedding-in the appropriate axle grouping and loading were fitted and ALF was then operated at full speed (approx. 22 km/h) with programmed transverse movements every 50 cycles, to mimic traffic wander. In addition to logging the

number of cycles, at each transverse move the following data was logged: air-spring pressures; hydraulic oil pressure and temperature; ambient air temperature; pavement temperature at depth; and seal surface temperature. Also during the operation of each experiment, the loading cycles were regularly paused and manual sand patch texture measurements and laser texture cross-sections were taken at specified chainages along each of the 12 m experimental sections. IV.

DATA ANALYSIS

This paper contains a summary of the data analysis. For the interested reader, a more detailed account will be found at [18] and the full statistical analysis at [19]. Fig. 6. Individual Weibull model fits

A statistical analysis of these models, as shown in Table V has found them to be statistically significant.

Fig. 5. Normalisede surface texture decay (Power curve fits)

A. Determining individual models Power curve fits such as y=axb using Microsoft Excel are statistically of limited use in resolving more complex research questions, and more detailed and powerful models were sought. Weibull models [20] are used widely in medicine, biology and engineering. A Weibull model of the form  


=1- 



(1)

was then applied to each loading regime using IBM SPSS statistics version 21, with the results being illustrated in Figure 6.

Triaxl e 90 kN

0.81

0.68

Standard error (SE)

Coefficient value 628,43 2

130,545

21%

β

-0.324

0.037

11%

α

406,18 0

59,588

15%

β

-0.292

0.028

9%

α

325,68 2

38,800

12%

β

-0.284

0.025

9%

α

711,02 7

216,267

30%

β

-0.276

0.042

15%

p value

Tande m axle 80 kN

0.80

α

t test value

Tande m axle 60 kN

0.69

ALF TRIAL REGIMES Degree of freedom

Single axle 40 kN

Regression coefficient

R2

Curve

TABLE V.

SE as a % of estimate

To deal with construction variability, the surface texture measurements were expressed in terms of reduction in sand patch texture depth from the initial starting value. An overview of the resulting data is shown in Fig. 5

572=55 572=55 412=39 412=39 452=43 452=43 342=32 342=32

4.8