Lower Bound HPMV s Analysis of Pavement Impacts · Analysis of Pavement Impacts Prepared By Opus International Consultants Ltd Adele Jones Napier Office Asset Manager - Infrastructure

Lower Bound HPMVs

Analysis of Pavement Impacts

Lower Bound HPMVs

Analysis of Pavement Impacts

Prepared By Opus International Consultants Ltd

Adele Jones Napier Office

Asset Manager - Infrastructure Opus House, 6 Ossian Street

Private Bag 6019, Hawkes Bay Mail Centre,

Napier 4142

New Zealand

Reviewed By Telephone: +64 6 833 5100

William Gray Facsimile: +64 6 835 0881

Service Excellence Leader - Central Region

Date: 29 April 2013

Reference: 2-S4908.00.001NI

Status: FINAL (Version 5)

Approved for

Release By

Trent Downing

Work Group Manager - Information

Management

© Opus International Consultants Ltd 2012

Lower Bound HPMVs – Analysis of Pavement Impacts

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December 2012 i

Contents

1 Executive Summary ............................................................................................................. 1

2 Introduction .......................................................................................................................... 3

3 Methodology ........................................................................................................................ 3

3.1 Inputs Required from Other Work Streams ................................................................... 3

3.2 Methodology ................................................................................................................. 4

4 Loading Impact Assessment............................................................................................... 6

4.1 TERNZ LB HPMV Pro-forma Design Inputs .................................................................. 6

4.2 WiM Data Inputs ........................................................................................................... 8

4.3 ESA Calculation Spreadsheet Assumptions ................................................................ 11

4.4 Loading Impact Summary ........................................................................................... 12

5 Review of NZ Pavement Strengths ................................................................................... 14

5.1 Measure of Pavement Strength .................................................................................. 14

5.2 CAPTIF Research of ESA and Pavement Strength Relationship ................................ 15

5.3 State Highways Pavement Strength ............................................................................ 15

5.4 Local Authority (LA) Roads Pavement Strength .......................................................... 18

5.5 Pavement Strength Summary ..................................................................................... 26

6 Pavement Effects ............................................................................................................... 27

6.1 Loading Impact on Pavements .................................................................................... 27

6.2 Loading and Pavement Assumptions .......................................................................... 27

6.3 Original VDM Methodology ......................................................................................... 28

6.4 Literature Review of Pavement Effects ....................................................................... 29

6.5 Pavement Effects Summary........................................................................................ 32

7 Conclusions and Recommendations ............................................................................... 33

7.1 Loading Impact ........................................................................................................... 33

7.2 Pavement Strength Analysis ....................................................................................... 34

7.3 Pavement Effects ........................................................................................................ 34

7.4 General Recommendations ........................................................................................ 34

8 References ......................................................................................................................... 35

9 Acknowledgements ........................................................................................................... 36

Appendix A – ESA Calculation Spreadsheets for WiM sites (n=4) .......................................... 37

Appendix B – CAPTIF Research of Equivalent Standard Axles and Pavement Strength

Relationship ................................................................................................................................ 42


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Appendix C – Loading Effects on Pavement Design ................................................................ 44


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1 Executive Summary

The NZ Transport Agency (NZTA) has introduced the concept of a Lower Bound High

Productivity Motor Vehicles (LB HPMV), which will result in increased freight productivity

while having minor or no impact on roading infrastructure in terms of load limits on

structures and impact on pavements. The base assumption is that because the LB HPMVs

will be carting the same overall freight task, the overall number of trips will reduce,

potentially resulting in less heavy vehicles on the road.

The purpose of this report is to review the new LB HPMV proforma vehicles and assess

whether the loading impact on the pavement is neutral when compared with the existing

heavy vehicle traffic fleet. It also provides an assessment of the pavement effects based on

the loading impact outcomes.

The impact of the addition of LB HPMVs has been assessed using the Equivalent Standard

Axle (ESA) “4th power law”, which associates pavement wear with distress caused by

vertical loads. The latest Weigh in Motion (WiM) data from five sites on state highways

around New Zealand was used as the base traffic fleet mix and compared with a fleet mix

including LB HPMVs. Using this approach, findings show that there is a slight reduction in

overall ESA loading for the 50 tonne LB HPMV, based on assessed industry “Base Case”

take-up. This confirms that the addition of LB HPMVs to the existing fleet mix produces a

neutral impact in terms of pavement loading, using this approach.

Overloading above 50 tonnes (up to 53 tonnes) was also reviewed using the same method

and findings show there is a small loading increase, based on assessed industry “Base

Case” take-up. However, due to the strict penalties imposed on HPMV permit holders there

is unlikely to be any significant overloading by LB HPMV operators.

It is important to note that the use of a blanket percentage change in ESA loading based on

WiM site traffic data is not necessarily the best way to represent the loading impact across

all roads. It is unlikely that all roads will get the same change in loading. The take-up

forecast shows that most of the take-up will be on urban and line haul routes (75% take-up),

with only approximately 20% take-up likely on rural local roads. Therefore, the loading

impact assessment included in this report could be considered the upper bound of impact

for many local authority roads.

An assessment of pavement strengths (SNP) across New Zealand showed that pavement

strengths for roads with higher traffic volumes (Average Daily Traffic > 4,000 vehicles per

day) are generally higher, indicating that these roads are less likely to be impacted by

changes in loading than lower trafficked roads. The local soils and geology also affect the

ability of pavements to carry traffic loading. Based on SNP, approximately 20% of state

highway pavements and 30% of LA road pavements are characterised as weaker (SNP <

2.4) and more vulnerable to any increase in pavement loading.

The overall risk of increased pavement deterioration as a result of LB HPMVs is assessed

to be low. As the impact of the LB HPMVs was confirmed to be neutral using the “4th power

law” approach and assessed “Base Case” take-up, theoretically there will be no resulting

pavement impact in terms of rutting in the subgrade. Dynamic loading impacts resulting in


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shear failure and pavement surface damage have not been quantified but are unlikely to be

significant. Indications are that the areas where take-up of LB HPMVs is most likely are

urban and line haul routes. These generally encompass the more highly trafficked stronger

pavements (i.e. state highways), which are less susceptible to changes in loading.

However, both state highway and LA road impacts will be more dependent on localised

conditions. There are parts of all networks that are vulnerable to the any loading change

due to soft subgrades, poor quality pavement materials and road alignment.

If the take-up significantly increases from that assessed, it is possible that weaker

pavements (SNP < 2.4) may be more susceptible to the LB HPMV loading. The risk of the

take-up being higher than assessed is low. The impacts of any change in take-up would

need to be assessed against the productivity gains.

It is recommended that a further review be completed on the outcomes of a number of

applicable NZTA and Austroads research projects that are currently being completed, to

determine any applicable outcome in terms of LB HPMVs impact on pavements and

surfacings.


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2 Introduction

The Land Transport Rule: Vehicle Dimensions and Mass Amendment 2010 (VDM Rule

Amendment), allows for High Productivity Motor Vehicles (HPMVs) to operate under permit

at weights and lengths greater than previously allowed, on approved roads within New

Zealand. The purpose of this change was to improve freight efficiency across the country

by achieving fewer trips to move the existing freight task, potentially resulting in less heavy

vehicles on the road. Although a significant number of vehicles are now operating under

such permits, only limited routes have been opened up for HPMV use due to capacity

issues with weak structures and pavements. Therefore, the NZ Transport Agency (NZTA)

has introduced the concept of a Lower Bound HPMV (LB HPMV), which will result in

increased freight productivity while having minor or no impact on roading infrastructure in

terms of load limits on structures and impact on pavements.

The NZTA has proposed that LB HPMVs can be achieved with modifications to the existing

fleet and the introduction of a new proforma design for vehicle mass and length. It is also

proposed that these vehicles will be allowed general rather than restricted access across

the network. However, initially these vehicles would be “Permitted” and a review of any

impacts completed at a later time (maybe up to five years) prior to any change in

regulations.

The new LB HPMV proforma vehicle designs must comply with a revised bridge formula

which is an extrapolation of the existing Class 1 bridge formula for weights above 44 tonnes

and they must not generate any more pavement wear than the existing standard vehicles

that they will replace, for the same freight task (i.e. individual HPMVs may have higher

impact per vehicle but fewer trips will be needed to carry the same freight).

The purpose of this report is to review the new LB HPMV proforma vehicles and assess

whether the loading impact on the pavement is neutral when compared with the existing

heavy vehicle traffic fleet, carrying the same total freight task. It also provides an

assessment of the pavement effects based on the loading impact outcomes.

3 Methodology

This methodology covers the requirements of Work Stream 2 Analysis of Pavements included in the scoping document NZTA’s Preparation for the Introduction of Lower Bound

HPMV.

3.1 Inputs Required from Other Work Streams

Transport Engineering Research New Zealand Limited (TERNZ) was commissioned by the

NZTA to complete Work Stream 3 to develop a new proforma design for a LB HPMV that

will conform to the requirements set out the VDM Rule Amendment. The outcomes from

TERNZ’s review provide a significant input into this work stream. The objective for the new

LB HPMV configurations was to produce an Equivalent Standard Axle (ESA) per tonne of


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payload the same or less than the current vehicle fleet at their maximum loading allowance

when using the “4th power rule”, thus producing a neutral impact on pavements.

Stimpson & Co have been commissioned by the NZTA to complete Work Stream 4 to

complete an economic analysis including determining the level of take-up by the road

transport industry. The outcomes from this assessment provide an input into the loading

impact assessment completed as part of Work Stream 2.

3.2 Methodology

The original Work Stream 2 methodology submitted to and approved by the NZTA, was

based around the methodology for assessing additional pavement costs (VDM

Methodology)1 resulting from Opus International Consultants’ 2010 report VDM Rule

Amendment Impact on State Highway Pavements. This was to provide consistency in

reviewing the pavement impacts of LB HPMV against previous analysis completed on full

HPMV pavement impacts. However, during the completion of this project, this methodology

has been modified in agreement with NZTA and the final methodology used is outlined

below.

Confirming loading impact

Using the latest Weigh in Motion (WiM) data from the five WiM sites in New Zealand and

the ESA calculator spreadsheet, confirm that the loading impact is neutral in the “4th power

law” case. This has been considered for both a nominal 50 tonne LB HPMV and an

overloaded (up to 6% above nominal 50 tonne) LB HPMV scenario. This has been

completed for three industry take-up scenario outcomes from Work Stream 4.

Data Requirements: NZTA to supply national WiM data

Output: ESA calculator spreadsheets for each of the five WIM sites.

Review of NZ pavements strengths

A review of New Zealand pavement strengths is to be completed in order to make an

assessment of the weaker pavements that may be more susceptible to any increase in

loading. For the purpose of assessing the strengths of pavements across New Zealand, this

report uses the Adjusted Structural Number (SNP).

Information on NZ State Highways is held within NZTA’s State Highway RAMM database.

From this information a review of the pavement strength characteristics (based on SNP) of

the state highway pavements is completed. From this we can assess the length of highway

which may be impacted by loading changes due to weak pavements.

For many local authority roads there is no pavement strength data held in RAMM therefore,

the pavement strength for LA roads has been reviewed using two methods:

1 Hunter, E & Patrick, J (May 2010). Vehicle Dimension and Mass Amendment 2012 – Methodology for

Assessing Additional Pavement Costs from HPMV Loading on an Approved Route. Opus International

Consultants Ltd, Napier.


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• Using data collected at the LA Long Term Pavement Performance (LTPP) sites

monitored by NZTA. There are 84 sites across 21 LAs. This provides a sample of the

full local road network across the country, for which data is consistently collected and

recorded.

• Pavement strength data from RAMM has been obtained from a number of LAs for

which Opus has access to RAMM databases. The LAs included in this review provide

a reasonably representative cross section of LAs throughout New Zealand, with a

variety of different traffic volume and geological characteristics.

These methods have been used to determine the pavement strength characteristics across

the LA road network and to assess the percentage of LA pavements which may be

impacted by loading changes due to weak pavements.

Data Requirements: NZTA to supply access to NZTA State Highway RAMM database and

local authority LTPP site data for pavement strength

Output: An assessment of the pavement strengths of state highway and local authority

roads.

What are the pavement effects?

From the VDM methodology, there are a number of pavement and surfacing factors which

may be impacted by increased HPMV loadings. These include:

• Planned maintenance • Reactive maintenance • Pavement and surfacing design changes • Vulnerable areas – high risk curves and intersections

All of the above factors are mostly dependent on the axle loadings. If we can show that LB

HPMVs have a neutral loading impact for the pavement, then for the “4th power law” it is

likely that these vehicles will only impact the pavement and surfacing in vulnerable areas.

The impact on vulnerable areas will be dependent on the location of the additional axle on

each Lower Bound HPMV. Feedback from the consultants completing Work Stream 3 will

be required to indicate the best configurations for minimising the impact on vulnerable

areas. It should be noted that the vulnerable areas impact assessment from the original

methodology is based on practitioners’ knowledge and is very dependent on individual

vulnerable area site conditions. Therefore, a literature review of dynamic loading effects of

changed loading and configurations that contribute to shear failure and pavement surface

damage has also been carried out. In particular, this looks at the impact of changing a

tandem axle to a tridem axle in the LB HPMV proforma designs.

Output: Confirmation that axle loading impacts are neutral or otherwise for Lower Bound

HPMV.


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4 Loading Impact Assessment

4.1 TERNZ LB HPMV Pro-forma Design Inputs

Transport Engineering Research New Zealand Limited (TERNZ) has been commissioned

by the NZTA to complete Work stream 3 to develop a new proforma design for a LB HPMV

that will conform to the requirements set out the VDM Rule Amendment.

The TERNZ draft report2 concludes that there are only two vehicle configurations that have

the axle group weight capacity to allow additional gross weight. These are the truck and

trailer and the B-train. The LB HPMV pro-forma designs developed in TERNZ’s report are

based on the existing pro-forma HPMV designs. For both the truck-trailer and the B-train it

is possible to increase the Gross Combination Weight (GCW) to 50 tonne using a longer

vehicle (approx. 22.3m), without increasing pavement wear using the R22T23 and B1233

combinations. It was assumed that the pattern of overloading for the LB HPMVs will be

similar to that for existing vehicles. Thus the R22T23 vehicle is assumed to have a GCW of

50.76 tonnes and the B1233 is assumed to have a GCW of 50.54 tonne.

The current pro-forma design for the truck and trailer (R22T22) is shown in Figure 1. To

make it a valid LB HPMV requires the following in addition:

• The rear axle group on the trailer must be a tridem group (making it an R22T23). Other

axle groups may be tridem group but this is not a requirement.

• For 50t GCW, the distance from the first-to-last axle must be a minimum of 20m, for 49t

it must be a minimum of 19.375m, for 48t a minimum of 18.75m, for 47t a minimum of

18.125m and for 46t a minimum of 17.5m.

• All other axle combinations must be checked for compliance with the bridge formulae

and axle group weight limits must be specified such that it is not possible to exceed the

bridge formula while complying with the axle group limits.

Figure 1 – Current 22.3m pro-forma truck and trailer (R22T22)

2 de Pont, J. (June 2012). Lower Bound HPMVs – Vehicle Configurations (draft report). TERNZ Ltd.


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There are current three pro-forma B-train (B1233 and B1232) designs as shown in Figure 2

- Figure 4. The LB HPMV pro-forma could use the dimensional envelopes of any of these

three designs with the following additional conditions:

• The trailer axle groups must be tridems

• For 50t GCW, the distance from the first-to-last axle must be a minimum of 20m, for 49t

it must be a minimum of 19.375m, for 48t a minimum of 18.75m, for 47t a minimum of

18.125m and for 46t a minimum of 17.5m.

• All other axle combinations must be checked for compliance with the bridge and axle

group weight limits must be specified such that it is not possible to exceed the bridge

formula while complying with the axle group limits.

Figure 2 – 22m pro-forma B-train (B1233)

Figure 3 – 22.3m pro-forma B-train with 5.68m tractor (B1232)


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Figure 4 – 22.3m pro-forma B-train with 5.70m tractor (B1232)

The outcomes from the TERNZ draft report that have been used in this review of loading

impact are summarised in Table 1.

Table 1 – Profroma LB HPMV ESAs

Vehicle

Configuration

Load

State

Average Weight (tonnes) ESA

Axle Gp

1

Axle Gp

2

Axle Gp

3

Axle Gp

4

GCW

R22T23 Laden 9.84 14.04 12.21 14.66 50.76 3.42

R22T23 Tare 6.89 5.06 2.99 3.99 18.93 0.34

B1233 Laden 5.51 12.54 16.7 15.79 50.54 2.98

B1233 Tare 4.75 5.85 4.84 4.3 19.74 0.64

If we limit the laden weight to a maximum of 50 tonnes, the laden ESA for the R22T23

becomes 3.22 and the laden ESA for the B1233 becomes 2.85.

4.2 WiM Data Inputs

There are six WiM sites in New Zealand collecting axle loading data for use nationally in

traffic monitoring. These are all located on State Highways as follows:

• State Highway 1 at Drury near Auckland

• State Highway 2 at Te Puke in the Bay of Plenty

• State Highway 1 at Tokoroa in South Waikato

• State Highway 35 near Gisborne

• State Highway 5 at Eskdale in the Hawke’s Bay

• State Highway 1 at Waipara in Canterbury

The Hamamanaua WiM site on SH35 in the Gisborne region is the latest WiM site to be

introduced, data collection started in November 2011. The collected data was not included

in the most recent WiM report published in April 2012. The WiM data used for this loading


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impact review is the annual data provided for the 2011 year; therefore it excludes the SH35

WiM site in Gisborne.

All sites are continuously collecting individual vehicle records, and statistics normally

downloaded weekly.

The loading impact review was completed using the full fleet mix included in the WiM data

and has been completed as a separate review for each of the five WiM sites included. This

permits the impact of any varying loading effects across the country to be assessed.

It should be noted that there are a number of limitations in using the WiM data. These are

as follows:

• The data is from sites which are all on generally higher trafficked rural State Highways

and may not necessarily be representative of the traffic mix across all New Zealand

roads.

• The data provided has an accuracy tolerance of ±10% for gross loads and ±15% for

axle group loads.

• The data does not separately identify permitted overweight vehicles. This means that

information on existing HPMVs will be contained within the WiM data. It should also be

noted that the 2011 WiM data contained significant portions of the heavy vehicle fleet

that were overweight (i.e. total gross weight greater than 44 tonne).

• The data cannot distinguish between single and dual tyres. It is assumed that steer

axles are single tyred and all others are dual tyred. Therefore, any subsequent

calculation of ESAs will be based on assumed axle group types.

The classification used by NZTA in their 2011 summary report and the count data for each

of the five sites included in this review is summarised in Table 2.

Table 2 – Summary of 2011 WiM Data

Annual Traffic Counts

Type Pat

Class

Vehicle

Configurations

Veh

Class

Drury Tokoroa Te Puke Waipara Eskdale

R11 20 o-o (wb 2.0-3.2m, gw

>= 2.5t) MCV 73556 10475 15018 19322 4767

R11 21 o--o (wb >3.2m, gw

>= 2.5t) MCV 320439 68368 110396 70583 29178

R11T1 30 o-o--o HCV1 3438 777 360 775 256

R12 31 o--oo HCV1 135817 30649 43723 20752 10719

R21 34 oo--o HCV1 444 295 226 121 131

A112 41 o-o--oo HCV1 12668 3901 2725 2940 1448

R12 T1 42 o-oo--o HCV1 690 51 19 41 29

R21 T1 44 oo-o--o HCV1 20 38 9 10 10

R22 45 oo--oo HCV1 71824 31855 57448 19702 31025


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Annual Traffic Counts

Type Pat

Class

Vehicle

Configurations

Veh

Class

Drury Tokoroa Te Puke Waipara Eskdale

R13 47 o--ooo HCV1 41 15 15 179 18

50 o-o-o-o-o HCV2 43 27 1 12 7

R12 T11 52 o--oo-o--o HCV2 5510 766 818 633 444

A122 53 o-oo--oo HCV2 19043 3725 2862 3137 1902

57 o--o-----ooo HCV2 1202 199 170 201 154

A111 T12 61 o-o--o-o--oo HCV2 3 1 1 2 0

62 o--oo--o-o-o HCV2 1253 685 488 569 676

R12 T12 63 o--oo-o--oo HCV2 9094 3588 5682 2113 694

R21 T12 65 oo--o-o--oo HCV2 0 2 0 4 0

R22 T11 66 oo--oo-o--o HCV2 815 286 387 204 48

R22 T2 68 oo--oo--oo HCV2 14345 6762 1164 3985 948

A123 69 o-oo--ooo HCV2 124160 23424 37844 14691 6978

A122 T11 74 o-oo--oo-o--o HCV2 7 9 0 0 1

R22 T12 77 oo--oo-o--oo HCV2 12060 5612 6228 6431 3963

300 o--o--o MCV 10615 2792 2977 3702 1161

301 o--oo HCV1 2351 426 1384 839 211

401 o--o--oo MCV 8762 2869 2771 3957 1492

402 o--oo---o HCV1 3295 1040 911 1096 342

503 o--oo--oo HCV2 273 90 212 408 48

511 oo--ooo HCV1 576 64 59 26 13

622 o--o--oo--o-o HCV2 24 13 9 19 0

A223 713 oo-oo--ooo HCV2 11925 2741 1945 1443 819

A133 747 o--ooo---ooo HCV2 275 60 38 54 2

R12 T22 or

B1222 751

o-oo--oo--oo B-train

or T&T HCV2 101289 26611 44643 15274 10244

771 oo--o--oo--oo HCV2 2 31 11 24 2

A124 791 o-oo-oooo HCV2 38386 11452 7136 10956 2160

811 o--oo--oo--ooo HCV2 1327 450 20 32 251

A224 826 oo-oo--oooo HCV2 59761 22381 20299 10725 8033

A134 847 o--ooo---oooo HCV2 1327 266 1561 107 28

B1232 851 o-oo--ooo--oo HCV2 85249 41974 26981 36277 12331

R22 T22 891 oo--oo-oo--oo HCV2 251332 153503 125574 99815 57433

B2232 914 oo-oo--ooo-oo HCV2 1745 742 722 695 435

R22 T23 915 oo-oo--oo-ooo HCV2 2855 2106 126 1689 140

B1233 951 o-oo-ooo-ooo HCV2 29622 21638 1852 13029 3262

B2233 1020 oo-oo-ooo-ooo HCV2 2775 371 32 79 111

B1234 1032 o-oo-ooo-oooo HCV2 1 1 0 7 0

Total 1420239 483131 524847 366660 191914


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4.3 ESA Calculation Spreadsheet Assumptions

An ESA calculation spreadsheet from the original VDM Methodology has been produced for

each of the five WiM sites using the traffic counts included in Table 2. The average ESA for

each vehicle type is aggregated up to a total ESA for the existing fleet. This loading is then

compared with a revised vehicle fleet mix which includes the new LB HPMV Proforma

vehicles. The same ESA calculation process is completed and the two ESA loading impact

outcomes are compared to confirm whether the revised traffic fleet mix has any increase in

overall loading impact. The spreadsheet allows calculation of this impact for the “4th power

law” case.

This spreadsheet incorporates a number of assumptions as outlined below.

Efficiency gain – Each of the LB HPMV vehicles can carry more freight due to increased

weight limits and thus to transport the same amount of freight, the overall number of trips

will reduce, potentially resulting in less heavy vehicles on the road. This assumption has

been incorporated into the spreadsheet.

Traffic mix – The main state highways carry a full range of commodities most of which will

not change as a result of the new LB HPMV loads. Therefore, NZTA’s WIM data

summarised in Table 2 was used to determine the existing traffic mix, including vehicle

types and their weights.

Existing Fleet ESA/Vehicle – The average ESA per vehicle configuration has been based

on those included in the original ESA calculation spreadsheet (calculated from previous

WiM data) and provided in the TERNZ report. There are a number of new vehicle

configurations included in the 2011 WiM data which were not included in the original ESA

calculation spreadsheet. The average ESA/vehicle for these configurations has been

estimated based on other similar configurations/vehicle classes. Changes to these

estimated values had minimal impact on the overall change in loading calculated in the

spreadsheet, as they stay the same for both the existing and new fleet mixes.

The spreadsheet used to calculate the increase in ESA is based on WIM data where the

existing traffic loading in ESA takes into account unloaded, partially loaded, and fully loaded

truck travel to determine an existing average ESA per heavy vehicle. Calculating the new

total ESA for the road network incorporating the new LB HMPV vehicles is detailed in the

formula below:

New Total ESA = (current average ESA per vehicle)*(number of vehicles that have not

changed to the new LB HMPV plus the number of unloaded trips of the LB HMPV) + (new

fully loaded ESA per LB HMPV)*(number of fully loaded LB HMPV vehicles)

The “current average ESA per vehicle” in the equation above has been reduced in value to

take account of the reduction in number of fully loaded vehicles in the existing fleet that

have not changed to LB HPMV.

Percentage take-up – The percentage take-up to the new LB HPMV loading has a direct

impact on the increase in pavement loading. The overall percentage take-up for all LB

HPMVs (R22T23 and B1233) has been based on the outcomes of the Stimpson Business


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Case, November 20123. This presents three loading take-up scenarios: “Base Case” take-

up is 52%, “Pessimistic Case” is 17% and “Optimistic Case” is 66%. The total take-up is

estimated to be over five years, however for the purposes of this loading impact review the

total take-up for each case has been used. The take-up forecasts show that most of the

take-up will be by non-rural and line haul vehicles (75% take-up for the “Base Case”), with

only limited take-up likely on rural local roads (20% take-up for the “Base Case”). Including

all three take-up scenarios allows for review of the sensitivity of loading change based on a

change in take-up.

New maximum allowable weights – The ESA calculation spreadsheet assumes that

those existing vehicles that are near their maximum weight will choose to adopt the new

HPMV limits. The first loading scenario used a maximum allowable weight for LB HPMV’s

of 50 tonnes. A second scenario was calculated where the LB HPMVs were assumed to be

approximately 6% heavier than the new mass limits.

4.4 Loading Impact Summary

Table 3 summarises the loading impact outputs from the ESA calculation spreadsheets for

each of the five WiM sites reviewed for the three industry take-up scenarios (“Pessimistic

Case” 17%, “Base Case” 52% and “Optimistic Case” 66%). It also shows the impact of the

LB HPMV nominal gross weight of 50 tonne as well as the overloaded scenario increased

by 6% as discussed above. The spreadsheets for each WiM site (50t, 52% “Base Case”

take-up scenario) are included in Appendix A.

Table 3 – Summary of ESA Calculation Spreadsheets for WiM Sites

Nominal 50t LB HPMV 6% Overloaded LB HPMV

WiM Site 17% take-

up

52% take-

up

66% take-

up

17% take-

up

52% take-

up

66% take-

up

Drury -5.2% -1.0% 0.7% -4.1% 2.6% 5.3%

Tokoroa -7.9% -1.6% 0.9% -6.1% 3.8% 7.8%

Te Puke -6.4% -1.4% 0.7% -5.0% 3.0% 6.2%

Eskdale -7.7% -1.6% 0.8% -6.0% 3.6% 7.5%

Waipara -7.7% -1.5% 1.1% -5.9% 4.2% 8.2%

Table 3 shows that for the 52% “Base Case” take-up there is actually a slight reduction in

loading across all WiM sites for the 50t LB HPMV. There is a very minor increase in

loading for the 66% “Optimistic Case”. This confirms that the addition of LB HPMVs to the

existing fleet mix produces a neutral impact in terms of pavement loading, based on the “4th

power law” approach.

For the overloaded case, there is a small loading increase for 52% take-up, and a further

increase for the 66% take-up scenario, which demonstrates a potential impact if operators

do not conform to the new proforma LB HPMV weight limits under higher take-up scenarios.

3 Appendix Two - Stimpson, D. (27 November 2012). Business Case for Lower Bound High Productivity

Motor Vehicles. Stimpson & Co, Wellington.


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It is worth noting at this point that more rigorous overloading implications exist for HPMVs

than for regular Class 1 vehicles operating at 44 tonnes or less. In terms of the Land

Transport (Offences and Penalties) Regulations 1999, there is a tolerance of up to 1.5

tonnes for any weight recorded or calculated where the legal maximum weight exceeds 33

tonnes but does not exceed 60 tonnes. Overloading above this tolerance results in an

infringement fine (a maximum of $10,000 for up to 13,000kg exceedence). A higher mass

HPMV will have the administrative concessionary enforcement tolerance applied, which is

300kg on a front axle, 500kg on any other axle, axle group or gross. If any of these

concessionary tolerances are exceeded, the permit is voided and standard vehicle

enforcement practices will apply, including infringement fees. This supports better control

of overloading for the LB HPMV case, and therefore it is probable that there will be minimal

impacts from overloading.


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5 Review of NZ Pavement Strengths

5.1 Measure of Pavement Strength

With reference to Cenek et al (2011), the pavement is a semi-infinite continuum comprising

layers of materials with often greatly differing properties and behaviour under load. Also,

light loads have a shallower influence than heavy loads. Therefore, a uniform basis is

required for representing pavement strength. For the purpose of assessing the strengths of

pavements across New Zealand, this report uses the Adjusted Structural Number (SNP).

The SNP of a section of pavement is a single parameter used to provide a representation of

the load-bearing ability of that pavement. The bigger the SNP number the greater the load

bearing capacity of the pavement. SNP can be used as an approximate indicator for the

capacity or structural life of pavements, provided that:

(i) rutting is the governing distress mechanism;

(ii) the majority of the rutting occurs in the subgrade rather than the overlying layers;

(iii) the treatment length4 is correctly defined and relates to a uniform sub-section; and,

(iv) the appropriate percentile (rather than average) SNP is determined that corresponds to

the percentage of road in a terminal condition which would trigger rehabilitation.

In reality pavements are subjected to many other distress modes and therefore there are

limitations with this method of assessing pavement structural capacity. However, SNP has

been used for this review as data is relatively available and it provides a simple method of

analysis that can be widely applied. It is also the currently adopted parameter for

deterioration modelling in New Zealand and was used as part of the original methodology

for assessing the impact of HPMVs on pavements.

Other limitations in the approach of using SNP including:

• SNP had its origin in the AASHO Road Test in the late 1950’s before the advent of

analytical methods. Research reported by Stevens et al (2009), showed that the

number of ESA to a terminal rutting condition using the Austroads subgrade strain

criterion apparently ranges over two or three orders of magnitude for a given SNP

value.

• There are several methods for evaluating structural strength, including SNP and two

methods for modified structural number (SNC). Cenek et al (2011) have shown that the

variation in structural number with displacement is very similar for all three methods,

although SNP appears to give lower values on weak (low structural number)

pavements.

• In New Zealand SNP is typically derived from falling weight deflectometer (FWD)

surveys. There is variability and possibly a lack of consistency in terms of timing of

4 A treatment length is a discreet length of pavement with the same condition and age characteristics


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FWD testing from year to year. This may result in seasonal variations of pavement

strength data. The data also provides a snapshot in time of the pavement in one

particular condition (i.e. wet, dry etc).

5.2 CAPTIF Research of ESA and Pavement Strength Relationship

An accelerated loading test was undertaken in 2002 at the Canterbury Accelerated

pavement Testing Indoor Facility (CAPTIF) to compare the wear generated by different

levels of loading (Arnold et al 2005). The pavement consisted of five different segments

that were subjected to 1,000,000 load cycles in two parallel wheel paths. The axle load on

one wheel path was 8.2 tonnes while the load on the other was 12 tonnes. Key findings

from this study can be summarised as follows:

• The relationships between SNP and pavement life are best when using the lower 10th

percentile value of SNP for the road section of interest.

• There is a relationship between SNP and the damage law exponent, n, the lower the

value of SNP, the higher the damage exponent as shown in Appendix B. This

relationship indicates that pavements with an SNP less than 2.4 will have a damage

exponent higher than n=4 and where axles are overloaded this will have greater impact.

It is understood that new research5 is currently being completed to further review this

relationship for axle loads less than the standard axle. This should be reviewed at some

stage in future for applicability to the LB HPMV case. However, for the purposes of this

report it is assumed that an SNP less than 2.4 indicates that there will be more impact of

increased loading on these pavements.

It is also worth noting that based on measured SNP values research by Cenek et al (2011)

indicates a lower limit 10th percentile SNP value with a limiting SNP of 1.8. In terms of FWD

derived SNP, an SNP of less than 2 is associated with central deflections greater than

3mm. For NZ pavements with non-volcanic subgrades, deflections greater than 3mm

would be uncommon and thus a lower limit SNP value of 1.8 appears reasonable.

5.3 State Highways Pavement Strength

There are 10,894km of state highways across New Zealand, which make up approximately

12% of New Zealand’s roads but account for around half of the 36 billion kilometres

travelled each year.

In order to review the strength of these state highway pavements, we have reviewed the

SNP data from the State Highway RAMM database. This SNP data is generally back

calculated from Falling Weight Deflectometer (FWD) data collected during on-site testing.

The data analysed includes the latest data for all treatment lengths across the state

highway network, where this is available. Approximately 144,000 data results were used in

this review.

5 The relationship between vehicle axle loadings and pavement wear on local roads. 2012 NZTA Current

Research Project RRT6.


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Figure 5 shows the location of SNP data across the state highway network, based on the

year the data was collected and recorded in RAMM. This shows that some of the data

included in this analysis dates back to 1998, but the majority of data is from the last 10

years. It provides a snapshot of the pavement condition at the time of testing, however the

pavement may have since deteriorated or been rehabilitated. Because of this, there may be

some discrepancy between the results of this analysis and the actual strength of existing

state highway pavements at the present time.

Figure 5 – State Highway SNP data by year recorded

A comparison of the SNP data across a variety of different traffic volume scenarios has

been achieved by reviewing the data against the old National State Highway Strategy

(NSHS) Hierarchy categories which are currently available in RAMM. Although there is

now a new classification system for State Highways, the old hierarchy allows us to group

the strength of pavements by different traffic volume groups around the country. Table 4

shows the hierarchy as defined in the State Highway National Pavement Condition Report

2009. The R2, R3 and R4 roads make up a total of 85% of the network length.


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Table 4 – NSHS Hierarchy Classification

Figures 6 and 7 illustrate the breakdown of these results by NSHS hierarchy. Figure 6

indicates that R2, R3 and R4 roads have the highest frequency of SNP data. For all

hierarchies the results are generally well distributed, although the data for motorways is

skewed towards the higher end of the SNP scale. This indicates good pavement strength,

which is to be expected.

Figure 6 – Frequency of SNP by NSHS Hierarchy

Figure 7 – SNP Distribution by NSHS Hierarchy


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As an indication of likely weaker pavements, approximately 20% of all state highway SNP

results have a value of less than 2.4 so will potentially be more susceptible to loading

impact. Figures 8 and 9 show the location of SNP results that are less than or equal to 2.4

compared with SNP results of 2.4 or greater. There is a reasonable spread of results across

the state highway network for both cases, although the south island and northland appear

to have generally higher SNPs.

Figure 8 – SNP results ≤ 2.4 Figure 9 – SNP results > 2.4

As an indication of the lower limit of pavement strength for all state highways, the 10th

percentile SNP value is 1.89. Individual road hierarchies show that R3 and R4 highways

have the weakest pavements with 10th percentile SNPs of 1.77 and 1.74 respectively, which

is to be expected. This compares well with the lower limit SNP values determined in

research by Cenek et al (2011).

5.4 Local Authority (LA) Roads Pavement Strength

There are 83,200km of LA roads across New Zealand, which make up approximately 78%

of New Zealand’s roads and are administered by 78 councils.

There has been significantly more difficulty in obtaining pavement strength data for LA

pavements for a number of reasons including:


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• Limited access to LA RAMM databases due to sensitivities around obtaining this

without having to seek direct approval from LAs

• SNP data is not collected and/or recorded by all LAs

• There is a large component of the LA network that is unsealed (38% of the 83,200km

nationally) which is generally not tested for pavement strength and is more likely to

have pavement strength variation over time.

5.4.1 Long Term Pavement Performance (LTPP) data

There are 84 Long Term Pavement Performance (LTPP) sites across 21 LAs, which are

monitored by NZTA. These LTPP sites were chosen to ensure they provided good

representation across a range of environments, traffic classes, pavement types/strengths,

pavement age/condition, urban/rural and maintenance regime (with or without

maintenance). Although the LTPP data provides a limited sample in relation to all LA roads,

it has the advantage of providing data which is consistently collected and recorded.

An assessment of pavement strengths for the LTPP sites has been completed based on the

NSHS road hierarchies (i.e. using the same traffic volume bands) to enable ready

comparison with state highway results. Using this information and extrapolating it across

the national length of LA roads can give an indication of the pavement strengths across all

LA roads.

The SNP provided in the LTPP dataset is a representative SNP value for each site and has

been derived from back analysis of FWD testing completed on all sites in 2006. Individual

SNP data readings were not provided in NZTA’s LTPP database. The data included in this

analysis provides a snapshot of the pavement condition at the time of testing, however the

pavement may have since deteriorated or been rehabilitated. Because of this, there may be

some discrepancy between the results of this analysis and the actual strength of existing

state highway pavements at the present time.

The SNP data from the 84 LA LTPP sites is shown in Figure 10. SNP values are lowest for

those roads with traffic volumes of less than 1,000 vehicles per day. 30% of these sites

have pavement strengths below the indicative SNP of 2.4 which equates to n=4 damage

exponent. SNP values for roads with higher traffic volumes are all substantially higher and

improve with increasing traffic volume, indicating that roads with higher traffic volumes have

more robust design and construction requirements. As an indication of the lower limit of

pavement strength for roads with an AADT less than 1,000 vehicles a day, the 10th

percentile SNP value is 1.72.


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Figure 10 – SNP Distribution by Traffic Volume for LTPP Sites

A straight extrapolation of this data across the national local road length indicates that lower

trafficked local roads are most at risk of increased loading impact.

5.4.2 Individual LA RAMM Data

A subset of New Zealand LAs for which we could access RAMM has been reviewed for

SNP data. Table 5 shows the LAs included in the review. A number of these did not have

any SNP data recorded in their current RAMM database.

Limitations of this individual LA data review include:

• The SNP results have not all been calculated using the same methodology. Some of

the methods for calculating SNP in RAMM can give poor approximations. The best

method available is the RAMM FWD – Pavement Strength method, which is based on

Tonkin & Taylor’s methodology. This methodology recommends adjusting SNP results

based on geology.

• The SNP data has not been adjusted for subgrade variation factors.

• Some of the SNP data is based on FWD test points and is relatively detailed, while

other data is provided in the format of a representative SNP value per treatment length.

• Testing has been completed at different times and using different test suppliers.

• Some LAs complete FWD testing on sites prior to rehabilitation, which may skew

results to a lower limit as these are generally weaker pavements so will likely have

lower SNP values. It is uncertain whether this is the case for the LAs represented in

this review.

• Most LAs only have SNP results for a limited sample of their network. This is partially

because many LAs have a significant portion of unsealed roads, which are generally

not tested.


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Table 5 – Local Authorities RAMM Data

Local

Authority

SNP

Data in

RAMM

Total

Network

length

(km)

Percentage

of Network

Sealed

Network

Length

Represented

by SNP data

Typical

AADT

Basis of SNP

Data†

North Island

Auckland Area* Yes 5499 93% 500-

20,000+

Representative

value for each

treatment length

Central Hawke’s

Bay DC

Yes 1263 68% 56% 100-2,000 Individual FWD

test points

South Waikato

DC

Yes 528 98% 20% Individual FWD

test points

Wairoa DC Yes 904 30% 18% 100-1,000 Individual FWD

test points

Western Bay of

Plenty DC

Yes 1027 78% 100-4,000 Individual FWD

test points

South Island

Ashburton DC No 2630 56% 0% 100-4,000 N/A

Gore DC No 894 40% 0% 100-2,000 N/A

Mackenzie DC No 711 27% 0% 100-1,000 N/A

Marlborough DC Yes 1519 57% 11% 100-5,000 Individual FWD

test points

Southland DC Yes 4966 39% 11% 100-2,000 Representative

value for each

treatment length

Timaru DC No 1718 55% 0% 100-8,000 N/A

Waitaki DC No 1832 41% 0% 100-1,000 N/A

*Auckland Area includes Auckland CC, Franklin DC, Manukau CC, Papakura CC, and Waitakere

DC. These councils are now amalgamated.

†SNP data is either based on a representative value for each treatment length or based on individual

FWD test points (i.e. a number of values per treatment length)

Figure 11 shows the LA roading network areas included in Table 5, where SNP data has

been recorded in RAMM. The map identifies the SNP data points, showing geographically

the extent of SNP data. As also indicated in Table 5, some networks have limited coverage

of SNP data across their network. Note that the Southland network GIS mapping was not

available for inclusion at the time of release of this report, therefore the area (Northern

Southland) of SNP data included has been indicated in red hatching against the full

Southland district in black hatching.


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Figure 11 – Location of LA SNP data

Results from the analysis of these LAs are shown in Figures 12 and 13. These figures show

substantially more variability in SNP results across the LAs reviewed than within the LTPP

data, as would be expected. This is both in terms of the amount of data obtained and the

overall strength of pavements.


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Figure 12 – Frequency of SNP data for Individual LAs

Figure 13 – SNP Distribution for Individual LAs

Western Bay of Plenty (WBOP), South Waikato and Wairoa have 87%, 75% and 59% of

SNP results less than 2.4 respectively and lower limit 10th percentile values of 1.19, 1.50

and 0.43 respectively. In particular, the distributions for WBOP and South Waikato are

heavily weighted to lower SNP values due to the soil types in the region (volcanic ash

subgrades giving higher FWD deflections), and the raw SNP data is normally adjusted

(increased) for predictive modelling and other analysis purposes. For example, in WBOP

for predictive modelling the SNP values typically increase by 1-1.5 due to the soil type.

Figures 14 and 15 provide a review of the data from all councils grouped together into traffic

volume bands. Because of the impact of the volcanic soils in WBOP and South Waikato,

this same analysis has been completed with the data from these regions excluded. This is

included in Figures 16 and 17.


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Figure 14 – Frequency of SNP data for all

LAs by Traffic Volume

Figure 15 – SNP Distribution for all LAs by

Traffic Volume

Figure 16 – Frequency of SNP data for all

LAs by Traffic Volume (excluding volcanic

Subgrades)

Figure 17 – SNP Distribution for all LAs by

Traffic Volume (excluding volcanic

Subgrades)

Again the SNP values for roads with higher traffic volumes are substantially higher and

improve with increasing traffic volume, indicating that roads with higher traffic volumes have

more robust design and construction requirements than higher trafficked roads have. What

is interesting is that the lowest trafficked roads (ADT < 100 vehicles a day) have better

strength than the mid-traffic volume bands (ADT 100-4,000 vehicles per day). This is

perhaps because many of these lower trafficked roads are in fact urban streets that have

been also been well constructed with longer pavement design lives.

With the SNP values from regions with volcanic ash subgrade (Western Bay of Plenty and

South Waikato) excluded, the distributions for roads with ADT 100 to 4,000 show a higher

pavement strength and a similar overall distribution to other traffic volumes. This

comparison emphasises the need to ensure that the SNP data being reviewed is a good

overall representation of the pavement strength. In taking the RAMM data at face value, the

results are skewed towards lower strength pavements.


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For all LA approximately 45% of all SNP results are less than 2.4 and the lower limit 10th

percentile is 1.24. For the LAs excluding those with volcanic ash subgrade 28% of all SNP

values are less than 2.4 and the lower limit 10th percentile value is 1.32. This correlates

with the LTPP data review which shows that 30% of pavements have SNP values less than

2.4.

Overall, this review of a selection of LAs reflects the fact that local soils and geology can

play a significant part in the ability of pavements to carry loading. It also confirms the

variability of results and the limited ability to create a “one size fits all” solution for increased

pavement loading, based on such a limited dataset. However, it does indicate that higher

trafficked local roads are stronger than lower trafficked roads, and the roads most at risk of

loading impact are those with an ADT 100 to 4,000 vehicles a day.

This does not directly correlate with the outcomes of the LA LTPP data review. Both

analyses show that higher volume roads are unlikely to be affected by increased loading,

but there is some disparity in the conclusions drawn over the rest of the traffic volume

spectrum.

5.5 Pavement Strength Summary

The State Highway RAMM database included SNP data across the SH network. Although

some of the data dated back to 1998 and may not wholly reflect the current pavement

strength, it provides a reasonable indication of the strength of existing SH pavements. The

data analysed by road hierarchies shows generally well distributed results and good

pavement strength. However, results indicate that up to 20% of state highway pavements

may be more susceptible to any increased loading, based on approximately 21% of all state

highway SNP results having a value of less than 2.4. The weakest pavements are on lower

trafficked R3 and R4 roads.

Pavement strength data for Local Authority (LA) roads was more difficult to obtain and

results were variable. However, indications are that higher trafficked roads are generally

significantly stronger than the lower trafficked roads. Results indicate that up to 30% of LA

pavements may be more susceptible to any increased loading, based on approximately 28-

30% of all LA SNP results (excluding volcanic subgrades) having a value of less than 2.4.


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6 Pavement Effects

6.1 Loading Impact on Pavements

The loading impact assessment completed in Section 4 has used the traditional approach

to pavement design in New Zealand, which is based on the number of Equivalent Standard

Axles (ESA) using the “4th power law”. The key assumption is that any axle group that

causes the same maximum surface deflection as a Standard Axle causes the same

damage as the Standard Axle. Therefore, this loading impact only associates pavement

wear with distress caused by vertical loads.

This method of assessing pavement impact does not take account the following:

• Dynamic loading effects (i.e. surface deflection measurements are static). The visco-

elastic nature of some pavement materials, as well as the development of pore

pressures within granular and natural soil layers would be expected to be affected by

the loading and unloading speed.

• The changing performance of the material layers in the pavement (i.e. it treats the

pavement as a single entity) under loading.

Therefore, the impact of the LB HPMVs on pavements should be assessed based on a

number of pavement and surfacing deterioration factors as outlined below:

(i) Rutting of the Subgrade – resulting from increased vertical loading, assessed based

on ESA loading.

(ii) Shear Failure – occurring in the near surface layers of the pavement, which is

impacted by dynamic loading.

(iii) Pavement Surface Damage – mainly caused by tyre scuffing forces. This may

contribute to shear failure where water proofing of the pavement is reduced by

scuffing of the surfacing.

6.2 Loading and Pavement Assumptions

Based on the analysis completed in Sections 4 and 5, the following assumptions are used

in this pavement impact review:

• The significant change for existing vehicle configurations to become proforma LB

HPMV configurations is the rear tandem axle set changing to a tridem axle set (i.e.

B1232 becomes B1233 and R22T22 becomes and R22T23).

• Based on assessed “Base Case” take-up and the assumption of no change to the total

freight task, there is no increase in ESA loading on pavements for the new vehicle fleet

including 50t LB HPMVs.

• Because the loading impact based on the “4th power law” is neutral based on assessed

“Base Case” take-up, this indicates that rutting of the subgrade will not be impacted.


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Therefore, the assessment of pavement impacts below is more focussed on shear

failure and pavement surface damage.

• The majority of pavements in New Zealand are granular pavements with thin

bituminous surfacing, with the exception of highly trafficked pavements (e.g.

motorways) which tend to be structural asphaltic concrete.

• Based on findings from Section 5 (snapshot of SNPs around NZ), approximately 20%

of state highway pavements and 30% of LA road pavements are characterised as

weaker and would be more vulnerable to any potential increase in pavement loading.

6.3 Original VDM Methodology

The original VDM Methodology includes a number of pavement and surfacing factors which

may be impacted by increased HPMV loadings as follows:

• Planned maintenance • Reactive maintenance • Pavement and surfacing design changes • Vulnerable areas – high risk curves and intersections

For maintenance activities associated with rutting, there is no expected pavement effect as

a result of LB HPMVs. However, for some factors such as reactive maintenance and

vulnerable areas there may also be an impact in terms of shear failure and pavement

surface damage.

A summary of the assessed pavement impact of LB HPMVs, based on this methodology, is

included in Table 6.

Table 6 – Summary of Pavement Impacts using Original VDM Methodology

Pavement

Impact Factor

Governing

Loading Impact

Areas of Impact Assessed

Pavement

Impact

Planned

maintenance

• Rutting in

subgrade (ESA

increase = 0)

• Shear failure

• Surface damage

• Chip seal surfacings may have

shortened lives in areas of higher stress

(see vulnerable areas below).

Nil to small -

some resurfacing

may need to be

advanced.

Reactive

maintenance

• Rutting in

subgrade (ESA

increase = 0)

• Shear failure

• Surface damage

• Weaker pavements (SNP < 2.4) may be

more susceptible to shear failure. Based

on findings from Section 5 (snapshot of

SNPs around NZ) 20% of SHs and 30% of

LA roads may have increased reactive

maintenance.

• Increase in edge break resulting from

longer vehicles cutting corners on

curvilinear alignments.

Possible minimal

increase

Pavement and

surfacing design

changes

• Rutting in

subgrade (ESA

increase = 0)

• Even in an increased loading situation

pavement design changes can be

minimal. Austroads 2004 Figure 8.4

Nil to small -

some resurfacing

may need to be


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Pavement

Impact Factor

Governing

Loading Impact

Areas of Impact Assessed

Pavement

Impact

• Shear failure

• Surface damage

design chart, shows a 10% increase in

ESA loading results in a maximum of

7mm increase of in design pavement

depth for granular pavements with thin

bituminous surfacings as detailed

further in Appendix C. This is negligible

when compared to existing design and

construction tolerances.

• Resurfacing options for new pavements

may need to be reviewed in areas of

higher stress (e.g. intersections).

changed to more

robust solutions.

Vulnerable Areas • Shear failure

• Surface damage

• High stress & high speed curves may

have increased planned and reactive

maintenance – approx 12% of SH

network (4434 high risk curves in SH

database), no information obtained for

LA roads.

• Intersections with sharp/low speed

turning movements may have

increased scuffing damage, and

increased risk of pavement shear.

Possible minimal

increase

6.4 Literature Review of Pavement Effects

A number of research projects have been completed in recent years, focusing on the

impact of changed loading in terms of traditional vertical loading, dynamic loading and

scuffing force effects on pavements. The outcomes of some of the more significant

research reports applicable to this review of the possible impact of LB HPMVs are

discussed below.

6.4.1 Influence of Multiple Axle Loads on Pavement Performance

Austroads Publication No. AP–T184/11 outlines interim findings of research that examines

the effects of axle group type on pavement performance, focussing on Australasian flexible

pavement types. One of the reasons for this research is to assist industry (vehicle

designers and operators) in the development of more efficient heavy vehicles which will

maximise payload without increasing the wear to established road infrastructure.

In general terms, the objective of this research study was to investigate improved methods

for assessing the pavement damage caused by different multiple axle group loads, and to

develop a framework that can be used to quantify this pavement damage for use in the

Austroads flexible pavement design processes.

Of particular applicability to the LB HPMV case, was the testing completed on unbound

pavements, which sought to assess the deformation performance of a typical unbound


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granular pavement and subgrade structure under full-scale accelerated loading. Single

(40kN), tandem (60KN and 80kN) and tridem axles (90kN) were run over the pavement.

Although the overall deformation was slightly less for the tandem axle (80kN) than tridem

axle, no definitive conclusions can be drawn to relate this to the LB HPMV case.

Insufficient performance data was collected during the research project to allow the

development of new design methods. Austroads have established an additional research

project, TT1614 Pavement wear effects of heavy vehicle axle groups, to expand the data

collected, and to undertake the analysis required to develop the design framework. This is

yet to be reported on and should be reviewed for applicability in New Zealand once

published.

One question that this research does not appear to address yet is whether the dynamic

effects of the LB HPMV caused by an increasing number of tyres per vehicle could

generate enhanced pore pressure effects in the near surface basecourse materials. Such

effects could shorten the life of pavements, particularly where lower quality basecourse

materials are present in the pavement.

6.4.2 Pavement Surface Damage Caused by Tyre Scuffing Forces

Land Transport NZ research report 347 (completed by TERNZ) investigated pavement

surface damage resulting from tyre scuffing in locations with tight alignments which require

heavy vehicles to complete low-speed turns. This study showed that the amount of scuffing

force depends on the axle weight, axle group spread, road curvature (increasing turn

radius), the tyre configuration, inflation pressure, the use of self-steering axles, and on the

type of vehicle. The pertinent conclusions from this report that particularly impact on LB

HPMV outcomes are:

• Scuffing forces increase with increasing axle weight

• Scuffing forces increase with increasing axle group spread.

• When laden to the maximum legal weight limits, tridem axle groups produce higher

scuffing forces than tandem axle groups even though the tridem axle groups have less

weight per axle.

In terms of the LB HPMV configuration changes, the changes from current configurations

are shown in Tables 7 and 8. These show that the new LB HPMV configurations (R22T23

and B1233) have heavier axle weights on nearly all axles. Also the rear axle is changed

from a tandem axle to a tridem axle.


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Table 7 – Truck and Trailer Existing and LB HPMV Configurations

Vehicle

Configuration

Load

State

Average Weight (tonnes) ESA

Axle

Gp 1

Axle

Gp 2

Truck Axle

Gp 3

Axle

Gp 4

Trailer GCW

R22T22 Laden 9.34 13.54 22.88 10.71 11.16 21.88 44.76 2.81

R12T22 Laden 5.67 14.45 20.12 11.73 12.73 24.46 44.58 3.68

R22T23 (LB) Laden 9.84 14.04 23.88 12.21 14.66 26.88 50.76 3.42

Table 8 – B-Train Existing and LB HPMV Configurations

Vehicle

Configuration

Load

State

Average Weight (tonnes)

ESA

Axle Gp 1 Axle Gp 2 Axle Gp 3 Axle Gp 4 GCW

B1222 Laden 5.82 14.22 11.74 12.80 44.58 3.76

B1232 Laden 5.26 12.40 16.94 9.99 44.59 2.54

B1233 Laden 5.50 11.54 15.70 11.79 44.53 2.26

B1233 (LB) Laden 5.51 12.54 16.7 15.79 50.54 2.98

Research Report 347 concludes that for the same vehicle configuration scuffing forces are

proportional to load. So for the truck-trailers, the trucks are the same configuration but with

higher weight so the scuffing forces on the drive axles will increase.

For the rear trailers (truck trailers and B-trains) there are two competing effects. The tridem

axle group generate more scuffing than the tandem but the axle loads are less which

produces less pavement wear. The R22T23 combination was not investigated because

none existed at that stage, however a comparison of the B1233 and the B1232 was

made. For smaller turn angles, the B1233 actually generated lower peak scuffing forces

than the B1232. The crossover point was at about 90 degrees.

The indications from this research are that the changes made to LB HPMVs are likely to be

relatively neutral in terms of scuffing compared with the existing HCV configurations they

will replace. However, depending on how the configurations are actually loaded there may

be a small impact on scuffing.

6.4.3 Relationship Between Vehicle Axle Loadings and Pavement Wear on Local

Roads

NZTA research is currently being completed to provide reliable evidence on the wear

characteristics of New Zealand local road pavements from accelerated pavement loading

studies at CAPTIF and validated with field data from the nationwide LTTP sites.

The objective of this research is to provide a comprehensive picture of the load – wear

relationships for New Zealand roads. Previous research here and in Australia has only

considered loads above the current legal limit on State Highways. However, that research

has indicated that there may be a significantly different relationship on local roads and

below the legal limit. This research will fill in the gaps below the legal limit and on local

roads. The research outputs will be a Power Law model that has been tested across the full


2-S4908.00.001NI

April 2013 32

range of New Zealand roads and a full range of loads used. The results will be published

as NZTA research report.

At this stage there have been no published findings from this research, however it will have

direct applicability to the LB HPMV case and should be reviewed in this context when

published.

6.4.4 Modelling Extreme Traffic Loading Effects

NZTA research (Cenek et al, 2011) on modelling extreme traffic loading effects is currently

being finalised. The draft report presents findings of a study aimed at establishing whether

the pavement deterioration and pavement distress models for roughness, rutting and

cracking progression incorporated into pavement management systems, such as NZ-

dTIMS, could be modified so they reliability predict the condition of a pavement after it has

been exposed to sudden extreme traffic loading. Although there is some relevance of this

research to the review of impacts from LB HPMVs, it is important to note that the impact for

the LB HPMV loading scenario is apparently neutral, based on the “4th power law”, so

modelling outcomes should be unchanged. However, it may be worth reviewing the

outcomes of the final NZTA research report for applicability to the LB HPMV loading

scenario.

6.5 Pavement Effects Summary

The loading impact assessment using the “4th power law” has provided the basis for the

pavement impact in terms of rutting in the subgrade. As the impact of the LB HPMV

vehicles was confirmed to be neutral using this approach for the assessed “Base Case”

take-up, theoretically there will be no resulting pavement damage.

If the take-up significantly increases, it is possible that weaker pavements (SNP < 2.4) may

be more susceptible to the LB HPMV loading. The risk of the take-up being higher than

assessed is considered to be low. The impacts of any change in take-up would need to be

assessed against the productivity gains.

In terms of the impacts of dynamic loading resulting in shear failure and pavement surface

damage, there is no conclusive pavement impact. There are parts of all networks that are

likely to be more vulnerable to the change due to soft subgrades, poor quality pavement

materials and road alignment. High stress curves and intersections may also be impacted

due to the change in axle configuration from tandem to tridem resulting in a change in

scuffing forces. However, research indicates that the changes made to LB HPMVs are

likely to be relatively neutral in terms of scuffing compared with the existing HCV

configurations they will replace. This is dependent on the way axles are loaded and the

turning angles.


2-S4908.00.001NI

April 2013 33

7 Conclusions and Recommendations

7.1 Loading Impact

7.1.1 ESA Calculation Spreadsheet Outcomes

The ESA calculation spreadsheet used in this analysis provides a simplified approach to

determining the loading impact of the addition of LB HPMVs to the existing traffic fleet.

There are a number of assumptions built into the spreadsheet which could be further

reviewed to provide a more accurate calculation of the loading impact.

It is recommended that if the ESA calculation spreadsheet is going to be used for further

HPMV loading impact assessments in future, it should be reviewed and updated.

7.1.2 Industry Take-up

The overall assessed industry “Base Case” take-up (based on Stimpson Business Case,

November 2012) has been incorporated into the loading impact calculations. This take-up

forecast shows that most of the take-up will be on urban and line haul routes (75% take-up),

with only approximately 20% take-up likely on rural local roads. Because of this, it is

possible that the loading impact on most local authority roads will be less than assessed

based on WiM site traffic data. Therefore, the loading impact assessment included in this

report could be considered the upper bound of impact for many local authority roads.

7.1.3 Percentage Change in Loading

As indicated in 7.1.2 above, the use of a blanket percentage change in ESA loading based

on WiM site traffic data is not necessarily the best way to represent the loading impact

across all roads. It is unlikely that all roads will get the same change in loading. Some

roads may not have any vehicles change to LB HPMV (e.g. low volume LA roads), while

other routes (most likely urban and line haul) may have substantial take-up. A further

review at a more detailed regional or network level would provide a more accurate reflection

of the actual loading impact on road pavements.

7.1.4 LB HPMV versus Demand Based Loading Increases

It is worth pointing out that the LB HPMV will result in a net change in trafficking based on a

change to vehicle configurations. It is assumed that LB HPMVs will be carting the same

overall freight task, and therefore overall trips will reduce. They will be replacing existing

heavy vehicles and travelling on the same routes. Therefore, the effect of LB HPMVs

cannot be compared to the effects of demand based loading changes, which potentially

present a far greater loading increase and impact on the pavement. Weaker pavements are

very susceptible to increased loading resulting from a change in traffic use characteristics,

such as resulting from land use changes (e.g. dairy conversions, forestry harvesting). It is

understood that this is a significant issue for many local authorities who are currently

experiencing pavement deterioration due to demand based changes.


2-S4908.00.001NI

April 2013 34

7.2 Pavement Strength Analysis

The pavement strength analysis completed in this report was based on a desk top study of

existing data in RAMM databases maintained by NZTA and various LAs as well as LTPP

site data. As detailed in Section 5, there were a number of limitations with this approach

and the outcomes of this analysis provide an indication only of New Zealand pavement

strengths. In particular, the review of LA roads has covered only a small portion of the LA

roads across the country and further review and testing of pavement strength at a network

level would be required to confirm pavement strengths.

Further, as SNP represents vertical loading outcomes (i.e. SNP represents rutting in the

subgrade), this review does not necessarily take into account other pavement strength

parameters such as individual pavement layer strength.

7.3 Pavement Effects

The overall risk of increased pavement deterioration as a result of LB HPMVs is assessed

to be low. As the impact of the LB HPMVs was confirmed to be neutral using the “4th power

law” approach and assessed “Base Case” take-up, theoretically there will be no resulting

pavement impact in terms of rutting in the subgrade. Dynamic loading impacts resulting in

shear failure and pavement surface damage have not been quantified but are unlikely to be

significant. Indications are that the areas where take-up of LB HPMVs is most likely are

urban and line haul routes. These generally encompass the more highly trafficked stronger

pavements (i.e. state highways), which are less susceptible to changes in loading.

However, both state highway and LA road impacts will be more dependent on localised

conditions. There are parts of all networks that are vulnerable to the any loading change

due to soft subgrades, poor quality pavement materials and road alignment.

7.4 General Recommendations

Although indications are that LB HPMVs will have a neutral impact on pavements at

assessed “Base Case” take-up, it would be prudent to complete monitoring of reactive

maintenance post LB HPMV take-up. NZTA already has a monitoring regime in place since

the introduction of HPMVs, which reviews impacts on the LTPP sites across the country, on

both State Highway and LA roads. This monitoring would be appropriate to assess the

impacts of the LB HPMVs also, including any change in shallow shear pavement repair

quantities, increased edge break repairs on curves and scuffing of surfacing in low speed

turning environments. This will be particularly important in areas where pavement strength

is lower as these areas are most likely to be impacted.

It is also recommended that a further review be completed on the outcomes of a number of

applicable NZTA and Austroads research projects that are currently being completed as

discussed in this report, to determine any applicable outcome in terms of LB HPMVs impact

on pavements and surfacings.


2-S4908.00.001NI

April 2013 35

8 References

Arnold,G., Steven,B., Alabaster,D., Fussell,A. (2005): Effect on Pavement Wear of an

Increase in Mass Limits for Heavy Vehicles – Stage 3, Land Transport New Zealand

Research Report 279, Wellington, New Zealand.

Arnold, G.,Steven, B., Alabaster, D., Fussell, A. (2005). Effect on pavement wear of

increased mass limits for heavy vehicles – concluding report. Land Transport New Zealand

Research Report 281.

Austroads Ltd. (2011).The Influence of Multiple Axle Loads on Pavement Performance:

Interim Findings. Austroads Publication No. AP–T184/11.

Austroads (2004). Pavement Design - A Guide to the Structural Design of Road

Pavements. Austroads, Sydney.

Cenek, PD, Henderson, R., McIver, I., Patrick, J. (2011) Modelling of Extreme Traffic

Loading Effects. DRAFT NZ Transport Agency research report.

de Pont, J. (June 2012). Lower Bound HPMVs – Vehicle Configurations (draft report).

TERNZ Ltd.

Hunter, E & Patrick, J (April 2010). VDM Rule Amendment Impact on State Highway

Pavements and Addendum 2 – VDM Rule Amendment Impact on State Highway

Pavements. Opus International Consultants Ltd, Napier.

Hunter, E & Patrick, J (May 2010). Vehicle Dimension and Mass Amendment 2012 –

Methodology for Assessing Additional Pavement Costs from HPMV Loading on an

Approved Route. Opus International Consultants Ltd, Napier.

NZ Government. (March 2012). Land Transport (Offences and Penalties) Regulations 1999.

NZ Transport Agency (April 2012). Annual Weight-in-Motion (WiM) Report 2011.

Salt G.; Henning T.F.P.; Stevens D.; and Roux D.C. (2010) Rationalisation of the structural

capacity definition and quantification of roads based on falling weight deflectometer tests.

NZ Transport Agency Research Report no.401.

Stevens D.; Salt G.; Henning T.F.P. & Roux D.C. (November 2009). Pavement

Performance Prediction: A Comprehensive New Approach to Defining Structural Capacity

(SNP). Paper for TRANSIT NZIHT 10th ANNUAL CONFERENCE, Rotorua.

Stimpson, D. (27 November 2012). Business Case for Lower Bound High Productivity

Motor Vehicles. Stimpson & Co, Wellington.

Taramoeroa, N., de Pont, J. (2008). Characterising pavement surface damage caused by

tyre scuffing forces. Land Transport New Zealand Research Report 374.


2-S4908.00.001NI

April 2013 36

9 Acknowledgements

We wish to acknowledge the contribution of Dr Greg Arnold (Technical Manager

Pavements, Road Science), in reviewing loading impact analysis, including the ESA

calculation spreadsheet outputs, and providing confirmation that new research is currently

being completed to review the relationship between vehicle axle loadings (including axle

loads less than the standard axle) and pavement wear on local roads.


2-S4908.00.001NI

April 2013 37

Appendix A – ESA Calculation Spreadsheets for WiM sites (n=4)

LB HPMVs 50tonne, 52% “Base Case” take-up scenario

DRURY WiM SITE

Type WIM

Vehicle

Configurations

Vehicles

converted

to LB

HPMV

Numb.

Passes -

for 1 week

or more Sum ESAs

Average

ESA per

Vehicle*

No.

Vehicles

Changed

to LB

HPMV

% Uptake

to HMPV

% of the

heaviest

vehicles

changed

(55%

loaded)

% Weight

Increase

applied

New ESA

for the

heavy

vehicles

changed

Number of

vehicles

needed to

cart same

load

Sum ESAs

(all

vehicles

includes

those not

changed)

R11 20o-o (wb 2.0-3.2m,

gw >= 2.5t)MCV 1415 54 0.04 0 0% 0% 0.0 0 54

R11 21o--o (wb >3.2m, gw

>= 2.5t)MCV 6162 1528 0.25 0 0% 0% 0.0 0 1528

R11T1 30 o-o--o HCV1 66 18 0.27 0 0% 0% 0.0 0 18

R12 31 o--oo HCV1 2612 2957 1.13 0 0% 0% 0.0 0 2957

R21 34 oo--o HCV1 9 4 0.45 0 0% 0% 0.0 0 4

R11 T11 40 o--o-o--o HCV1 0 0 0.63 0 0% 0% 0.0 0 0

A112 41 o-o--oo HCV1 244 110 0.45 0 0% 0% 0.0 0 110

R12 T1 42 o-oo--o HCV1 13 10 0.76 0 0% 0% 0.0 0 10

R21 T1 44 oo-o--o HCV1 0 0 0.00 0 0% 0% 0.0 0 0

R22 45 oo--oo HCV1 1381 1471 1.06 0 0% 0% 0.0 0 1471

R13 47 o--ooo HCV1 1 1 1.83 0 0% 0% 0.0 0 1

50 o-o-o-o-o HCV2 1 1 1.50 0 0% 0% 0.0 0 1

R12 T11 52 o--oo-o--o HCV2 106 124 1.17 0 0% 0% 0.0 0 124

A122 53 o-oo--oo HCV2 366 562 1.53 0 0% 0% 0.0 0 562

57 o--o-----ooo HCV2 23 35 1.50 0 0% 0% 0.0 0 35

A111 T12 61 o-o--o-o--oo HCV2 0 0 2.94 0 0% 0% 0.0 0 0

62 o--oo--o-o-o HCV2 24 70 2.90 0 0% 0% 0.0 0 70

R12 T12 63 o--oo-o--oo HCV2 175 366 2.09 0 0% 0% 0.0 0 366

R21 T12 65 oo--o-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

R22 T11 66 oo--oo-o--o HCV2 16 19 1.24 0 0% 0% 0.0 0 19

R22 T2 68 oo--oo--oo HCV2 276 379 1.38 0 0% 0% 0.0 0 379

A123 69 o-oo--ooo HCV2 2388 4179 1.75 0 0% 0% 0.0 0 4179

A122 T11 74 o-oo--oo-o--o HCV2 0 0 0.00 0 0% 0% 0.0 0 0

R22 T12 77 oo--oo-o--oo HCV2 232 550 2.37 0 0% 0% 0.0 0 550

78 o--ooo-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

85 o-oo--oo-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

A123 T11 89 o-oo--ooo-o--o HCV2 0 0 0.00 0 0% 0% 0.0 0 0

300 o--o--o MCV 204 102 0.50 0 0% 0% 0.0 0 102

301 o--oo HCV1 45 45 1.00 0 0% 0% 0.0 0 45

401 o--o--oo MCV 169 84 0.50 0 0% 0% 0.0 0 84

402 o--oo---o HCV1 63 63 1.00 0 0% 0% 0.0 0 63

503 o--oo--oo HCV2 5 8 1.50 0 0% 0% 0.0 0 8

511 oo--ooo HCV1 11 17 1.50 0 0% 0% 0.0 0 17

A121 T11 621 o-oo--o-o--o HCV2 0 0 0.00 0 0% 0% 0.0 0 0

622 o--o--oo--o-o HCV2 0 1 2.90 0 0% 0% 0.0 0 1

A223 713 oo-oo--ooo HCV2 229 578 2.52 0 0% 0% 0.0 0 578

A121 T12 731 o-oo--o-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

A133 747 o--ooo---ooo HCV2 5 12 2.21 0 0% 0% 0.0 0 12

R12 T22 or B1222 751o-oo--oo--oo B-train

or T&THCV2

19484714 2.42 0 0% 0% 0.0 0 4714

A122 T2 752 o--oo-oo--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

771 oo--o--oo--oo HCV2 0 0 1.70 0 0% 0% 0.0 0 0

A124 791 o-oo-oooo HCV2 738 1529 2.07 0 0% 0% 0.0 0 1529

811 o--oo--oo--ooo HCV2 26 68 2.65 0 0% 0% 0.0 0 68

A224 826 oo-oo--oooo HCV2 1149 1577 1.37 0 0% 0% 0.0 0 1577

A134 847 o--ooo---oooo HCV2 26 45 1.75 0 0% 0% 0.0 0 45

B1232 851 o-oo--ooo--oo HCV2 LB HMPV 1639 2771 1.69 469 52% 29% 13.6 2.85 391 2824

R22 T22 891 oo--oo-oo--oo HCV2 LB HMPV 4833 9135 1.89 1382 52% 29% 13.6 3.22 1160 8739

B2232 914 oo-oo--ooo-oo HCV2 34 51 1.53 0 0% 0% 0.0 0 51

R22 T23 915 oo-oo--oo-ooo HCV2 55 96 1.75 0 0% 0% 0.0 0 96

B1233 951 o-oo-ooo-ooo HCV2 570 957 1.68 0 0% 0% 0.0 0 957

B2233 1020 oo-oo-ooo-ooo HCV2 53 56 1.04 0 0% 0% 0.0 0 56

B1234 1032 o-oo-ooo-oooo HCV2 0 0 0 0% 0% 0.0 0 0

B2234 1133 oo-oo-ooo-oooo HCV2 0 0 0 0% 0% 0.0 0 0

Total 27312 34346 1851 1551 34004

-1.00

*Values in bold itallics are assumed based on similar weight class/configuration vehicles. Changes to these ESA/veh have limited impact on the overall %ESA increase due to low vehicle

numbers in these classes

% ESA Loading increase:

Existing Traffic Fleet New traffic Fleet (including 50t LB HPMVs)


2-S4908.00.001NI

April 2013 38

Tokoroa WiM SITE

Type WIM

Vehicle

Configurations

Veh

converted

to LB

HPMV

Number of

Passes -

for 1 week

or more Sum ESAs

Average

ESA per

Veh*

No.

Vehicles

Changed

% Uptake

to HMPV

% of the

heaviest

vehicles

changed

(55%

loaded)

% Weight

Increase

applied

New ESA

for the

heavy

vehicles

changed

Number of

vehicles

needed to

cart same

load

Sum ESAs

(all

vehicles

includes

those not

changed)

R11 20o-o (wb 2.0-3.2m,

gw >= 2.5t)MCV 201 8 0.04 0 0% 0% 0.0 0 8

R11 21o--o (wb >3.2m, gw

>= 2.5t)MCV 1315 326 0.25 0 0% 0% 0.0 0 326

R11T1 30 o-o--o HCV1 15 4 0.27 0 0% 0% 0.0 0 4

R12 31 o--oo HCV1 589 667 1.13 0 0% 0% 0.0 0 667

R21 34 oo--o HCV1 6 3 0.45 0 0% 0% 0.0 0 3

R11 T11 40 o--o-o--o HCV1 0 0 0.63 0 0% 0% 0.0 0 0

A112 41 o-o--oo HCV1 75 34 0.45 0 0% 0% 0.0 0 34

R12 T1 42 o-oo--o HCV1 1 1 0.76 0 0% 0% 0.0 0 1

R21 T1 44 oo-o--o HCV1 1 0 0.00 0 0% 0% 0.0 0 0

R22 45 oo--oo HCV1 613 652 1.06 0 0% 0% 0.0 0 652

R13 47 o--ooo HCV1 0 1 1.83 0 0% 0% 0.0 0 1

50 o-o-o-o-o HCV2 1 1 1.50 0 0% 0% 0.0 0 1

R12 T11 52 o--oo-o--o HCV2 15 17 1.17 0 0% 0% 0.0 0 17

A122 53 o-oo--oo HCV2 72 110 1.53 0 0% 0% 0.0 0 110

57 o--o-----ooo HCV2 4 6 1.50 0 0% 0% 0.0 0 6

A111 T12 61 o-o--o-o--oo HCV2 0 0 2.94 0 0% 0% 0.0 0 0

62 o--oo--o-o-o HCV2 13 38 2.90 0 0% 0% 0.0 0 38

R12 T12 63 o--oo-o--oo HCV2 69 144 2.09 0 0% 0% 0.0 0 144

R21 T12 65 oo--o-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

R22 T11 66 oo--oo-o--o HCV2 6 7 1.24 0 0% 0% 0.0 0 7

R22 T2 68 oo--oo--oo HCV2 130 179 1.38 0 0% 0% 0.0 0 179

A123 69 o-oo--ooo HCV2 450 788 1.75 0 0% 0% 0.0 0 788

A122 T11 74 o-oo--oo-o--o HCV2 0 0 0.00 0 0% 0% 0.0 0 0

R22 T12 77 oo--oo-o--oo HCV2 108 256 2.37 0 0% 0% 0.0 0 256

78 o--ooo-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

85 o-oo--oo-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

A123 T11 89 o-oo--ooo-o--o HCV2 0 0 0.00 0 0% 0% 0.0 0 0

300 o--o--o MCV 54 27 0.50 0 0% 0% 0.0 0 27

301 o--oo HCV1 8 8 1.00 0 0% 0% 0.0 0 8

401 o--o--oo MCV 55 28 0.50 0 0% 0% 0.0 0 28

402 o--oo---o HCV1 20 20 1.00 0 0% 0% 0.0 0 20

503 o--oo--oo HCV2 2 3 1.50 0 0% 0% 0.0 0 3

511 oo--ooo HCV1 1 2 1.50 0 0% 0% 0.0 0 2

A121 T11 621 o-oo--o-o--o HCV2 0 0 0.00 0 0% 0% 0.0 0 0

622 o--o--oo--o-o HCV2 0 1 2.90 0 0% 0% 0.0 0 1

A223 713 oo-oo--ooo HCV2 53 133 2.52 0 0% 0% 0.0 0 133

A121 T12 731 o-oo--o-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

A133 747 o--ooo---ooo HCV2 1 3 2.21 0 0% 0% 0.0 0 3


or T&THCV2

5121238 2.42 0 0% 0% 0.0 0 1238

A122 T2 752 o--oo-oo--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

771 oo--o--oo--oo HCV2 1 1 1.70 0 0% 0% 0.0 0 1

A124 791 o-oo-oooo HCV2 220 456 2.07 0 0% 0% 0.0 0 456

811 o--oo--oo--ooo HCV2 9 23 2.65 0 0% 0% 0.0 0 23

A224 826 oo-oo--oooo HCV2 430 591 1.37 0 0% 0% 0.0 0 591

A134 847 o--ooo---oooo HCV2 5 9 1.75 0 0% 0% 0.0 0 9



B2232 914 oo-oo--ooo-oo HCV2 14 22 1.53 0 0% 0% 0.0 0 22

R22 T23 915 oo-oo--oo-ooo HCV2 41 71 1.75 0 0% 0% 0.0 0 71

B1233 951 o-oo-ooo-ooo HCV2 416 699 1.68 0 0% 0% 0.0 0 699

B2233 1020 oo-oo-ooo-ooo HCV2 7 7 1.04 0 0% 0% 0.0 0 7

B1234 1032 o-oo-ooo-oooo HCV2 0 0 0 0% 0% 0.0 0 0


Total SUM 9291 13525 62 1075.1 0.57 901 13310

-1.59






2-S4908.00.001NI

April 2013 39

TE PUKE WiM SITE

Type WIM

Vehicle

Configurations

Veh

converted

to LB

HPMV

Number of

Passes -

for 1 week

or more Sum ESAs

Average

ESA per

Veh*

No.

Vehicles

Changed

% Uptake

to HMPV

% of the

heaviest

vehicles

changed

(55%

loaded)

% Weight

Increase

applied

New ESA

for the

heavy

vehicles

changed

Number of

vehicles

needed to

cart same

load

Sum ESAs

(all

vehicles

includes

those not

changed)

R11 20o-o (wb 2.0-3.2m,

gw >= 2.5t)MCV 289 11 0.04 0 0% 0% 0.0 0 11

R11 21o--o (wb >3.2m, gw

>= 2.5t)MCV 2123 526 0.25 0 0% 0% 0.0 0 526

R11T1 30 o-o--o HCV1 7 2 0.27 0 0% 0% 0.0 0 2

R12 31 o--oo HCV1 841 952 1.13 0 0% 0% 0.0 0 952

R21 34 oo--o HCV1 4 2 0.45 0 0% 0% 0.0 0 2

R11 T11 40 o--o-o--o HCV1 0 0 0.63 0 0% 0% 0.0 0 0

A112 41 o-o--oo HCV1 52 24 0.45 0 0% 0% 0.0 0 24

R12 T1 42 o-oo--o HCV1 0 0 0.76 0 0% 0% 0.0 0 0

R21 T1 44 oo-o--o HCV1 0 0 0.00 0 0% 0% 0.0 0 0

R22 45 oo--oo HCV1 1105 1177 1.06 0 0% 0% 0.0 0 1177

R13 47 o--ooo HCV1 0 1 1.83 0 0% 0% 0.0 0 1

50 o-o-o-o-o HCV2 0 0 1.50 0 0% 0% 0.0 0 0

R12 T11 52 o--oo-o--o HCV2 16 18 1.17 0 0% 0% 0.0 0 18

A122 53 o-oo--oo HCV2 55 84 1.53 0 0% 0% 0.0 0 84

57 o--o-----ooo HCV2 3 5 1.50 0 0% 0% 0.0 0 5

A111 T12 61 o-o--o-o--oo HCV2 0 0 2.94 0 0% 0% 0.0 0 0

62 o--oo--o-o-o HCV2 9 27 2.90 0 0% 0% 0.0 0 27

R12 T12 63 o--oo-o--oo HCV2 109 228 2.09 0 0% 0% 0.0 0 228

R21 T12 65 oo--o-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

R22 T11 66 oo--oo-o--o HCV2 7 9 1.24 0 0% 0% 0.0 0 9

R22 T2 68 oo--oo--oo HCV2 22 31 1.38 0 0% 0% 0.0 0 31

A123 69 o-oo--ooo HCV2 728 1274 1.75 0 0% 0% 0.0 0 1274

A122 T11 74 o-oo--oo-o--o HCV2 0 0 0.00 0 0% 0% 0.0 0 0

R22 T12 77 oo--oo-o--oo HCV2 120 284 2.37 0 0% 0% 0.0 0 284

78 o--ooo-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

85 o-oo--oo-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

A123 T11 89 o-oo--ooo-o--o HCV2 0 0 0.00 0 0% 0% 0.0 0 0

300 o--o--o MCV 57 29 0.50 0 0% 0% 0.0 0 29

301 o--oo HCV1 27 27 1.00 0 0% 0% 0.0 0 27

401 o--o--oo MCV 53 27 0.50 0 0% 0% 0.0 0 27

402 o--oo---o HCV1 18 18 1.00 0 0% 0% 0.0 0 18

503 o--oo--oo HCV2 4 6 1.50 0 0% 0% 0.0 0 6

511 oo--ooo HCV1 1 2 1.50 0 0% 0% 0.0 0 2

A121 T11 621 o-oo--o-o--o HCV2 0 0 0.00 0 0% 0% 0.0 0 0

622 o--o--oo--o-o HCV2 0 1 2.90 0 0% 0% 0.0 0 1

A223 713 oo-oo--ooo HCV2 37 94 2.52 0 0% 0% 0.0 0 94

A121 T12 731 o-oo--o-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

A133 747 o--ooo---ooo HCV2 1 2 2.21 0 0% 0% 0.0 0 2


or T&THCV2

8592078 2.42 0 0% 0% 0.0 0 2078

A122 T2 752 o--oo-oo--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

771 oo--o--oo--oo HCV2 0 0 1.70 0 0% 0% 0.0 0 0

A124 791 o-oo-oooo HCV2 137 284 2.07 0 0% 0% 0.0 0 284

811 o--oo--oo--ooo HCV2 0 1 2.65 0 0% 0% 0.0 0 1

A224 826 oo-oo--oooo HCV2 390 536 1.37 0 0% 0% 0.0 0 536

A134 847 o--ooo---oooo HCV2 30 53 1.75 0 0% 0% 0.0 0 53



B2232 914 oo-oo--ooo-oo HCV2 14 21 1.53 0 0% 0% 0.0 0 21

R22 T23 915 oo-oo--oo-ooo HCV2 2 4 1.75 0 0% 0% 0.0 0 4

B1233 951 o-oo-ooo-ooo HCV2 36 60 1.68 0 0% 0% 0.0 0 60

B2233 1020 oo-oo-ooo-ooo HCV2 1 1 1.04 0 0% 0% 0.0 0 1

B1234 1032 o-oo-ooo-oooo HCV2 0 0 0 0% 0% 0.0 0 0


Total SUM 10093 13337 62 839.1 0.57 703 13157

-1.36






2-S4908.00.001NI

April 2013 40

ESKDALE WiM SITE

Type WIM

Vehicle

Configurations

Veh

converted

to LB

HPMV

Number of

Passes -

for 1 week

or more Sum ESAs

Average

ESA per

Vehicle*

No.

Vehicles

Changed

% Uptake

to HMPV

% of the

heaviest

vehicles

changed

(55%

loaded)

% Weight

Increase

applied

New ESA

for the

heavy

vehicles

changed

Number of

vehicles

needed to

cart same

load

Sum ESAs

(all

vehicles

includes

those not

changed)

R11 20o-o (wb 2.0-3.2m,

gw >= 2.5t)MCV 92 4 0.04 0 0% 0% 0.0 0 4

R11 21o--o (wb >3.2m, gw

>= 2.5t)MCV 561 139 0.25 0 0% 0% 0.0 0 139

R11T1 30 o-o--o HCV1 5 1 0.27 0 0% 0% 0.0 0 1

R12 31 o--oo HCV1 206 233 1.13 0 0% 0% 0.0 0 233

R21 34 oo--o HCV1 3 1 0.45 0 0% 0% 0.0 0 1

R11 T11 40 o--o-o--o HCV1 0 0 0.63 0 0% 0% 0.0 0 0

A112 41 o-o--oo HCV1 28 13 0.45 0 0% 0% 0.0 0 13

R12 T1 42 o-oo--o HCV1 1 0 0.76 0 0% 0% 0.0 0 0

R21 T1 44 oo-o--o HCV1 0 0 0.00 0 0% 0% 0.0 0 0

R22 45 oo--oo HCV1 597 635 1.06 0 0% 0% 0.0 0 635

R13 47 o--ooo HCV1 0 1 1.83 0 0% 0% 0.0 0 1

50 o-o-o-o-o HCV2 0 0 1.50 0 0% 0% 0.0 0 0

R12 T11 52 o--oo-o--o HCV2 9 10 1.17 0 0% 0% 0.0 0 10

A122 53 o-oo--oo HCV2 37 56 1.53 0 0% 0% 0.0 0 56

57 o--o-----ooo HCV2 3 4 1.50 0 0% 0% 0.0 0 4

A111 T12 61 o-o--o-o--oo HCV2 0 0 2.94 0 0% 0% 0.0 0 0

62 o--oo--o-o-o HCV2 13 38 2.90 0 0% 0% 0.0 0 38

R12 T12 63 o--oo-o--oo HCV2 13 28 2.09 0 0% 0% 0.0 0 28

R21 T12 65 oo--o-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

R22 T11 66 oo--oo-o--o HCV2 1 1 1.24 0 0% 0% 0.0 0 1

R22 T2 68 oo--oo--oo HCV2 18 25 1.38 0 0% 0% 0.0 0 25

A123 69 o-oo--ooo HCV2 134 235 1.75 0 0% 0% 0.0 0 235

A122 T11 74 o-oo--oo-o--o HCV2 0 0 0.00 0 0% 0% 0.0 0 0

R22 T12 77 oo--oo-o--oo HCV2 76 181 2.37 0 0% 0% 0.0 0 181

78 o--ooo-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

85 o-oo--oo-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

A123 T11 89 o-oo--ooo-o--o HCV2 0 0 0.00 0 0% 0% 0.0 0 0

300 o--o--o MCV 22 11 0.50 0 0% 0% 0.0 0 11

301 o--oo HCV1 4 4 1.00 0 0% 0% 0.0 0 4

401 o--o--oo MCV 29 14 0.50 0 0% 0% 0.0 0 14

402 o--oo---o HCV1 7 7 1.00 0 0% 0% 0.0 0 7

503 o--oo--oo HCV2 1 1 1.50 0 0% 0% 0.0 0 1

511 oo--ooo HCV1 0 0 1.50 0 0% 0% 0.0 0 0

A121 T11 621 o-oo--o-o--o HCV2 0 0 0.00 0 0% 0% 0.0 0 0

622 o--o--oo--o-o HCV2 0 0 2.90 0 0% 0% 0.0 0 0

A223 713 oo-oo--ooo HCV2 16 40 2.52 0 0% 0% 0.0 0 40

A121 T12 731 o-oo--o-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

A133 747 o--ooo---ooo HCV2 0 0 2.21 0 0% 0% 0.0 0 0


or T&THCV2

197477 2.42 0 0% 0% 0.0 0 477

A122 T2 752 o--oo-oo--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

771 oo--o--oo--oo HCV2 0 0 1.70 0 0% 0% 0.0 0 0

A124 791 o-oo-oooo HCV2 42 86 2.07 0 0% 0% 0.0 0 86

811 o--oo--oo--ooo HCV2 5 13 2.65 0 0% 0% 0.0 0 13

A224 826 oo-oo--oooo HCV2 154 212 1.37 0 0% 0% 0.0 0 212

A134 847 o--ooo---oooo HCV2 1 1 1.75 0 0% 0% 0.0 0 1



B2232 914 oo-oo--ooo-oo HCV2 8 13 1.53 0 0% 0% 0.0 0 13

R22 T23 915 oo-oo--oo-ooo HCV2 3 5 1.75 0 0% 0% 0.0 0 5

B1233 951 o-oo-ooo-ooo HCV2 63 105 1.68 0 0% 0% 0.0 0 105

B2233 1020 oo-oo-ooo-ooo HCV2 2 2 1.04 0 0% 0% 0.0 0 2

B1234 1032 o-oo-ooo-oooo HCV2 0 0 0 0% 0% 0.0 0 0


Total SUM 3691 5085 62 383.7 0.57 322 5002

-1.63






2-S4908.00.001NI

April 2013 41

Waipara WiM SITE

Type WIM

Vehicle

Configurations

Veh

converted

to LB

HPMV

Number of

Passes -

for 1 week

or more Sum ESAs

Average

ESA per

Veh*

No.

Vehicles

Changed

% Uptake

to HMPV

% of the

heaviest

vehicles

changed

(55%

loaded)

% Weight

Increase

applied

New ESA

for the

heavy

vehicles

changed

Number of

vehicles

needed to

cart same

load

Sum ESAs

(all

vehicles

includes

those not

changed)

R11 20o-o (wb 2.0-3.2m,

gw >= 2.5t)MCV 372 14 0.04 0 0% 0% 0.0 0 14

R11 21o--o (wb >3.2m, gw

>= 2.5t)MCV 1357 337 0.25 0 0% 0% 0.0 0 337

R11T1 30 o-o--o HCV1 15 4 0.27 0 0% 0% 0.0 0 4

R12 31 o--oo HCV1 399 452 1.13 0 0% 0% 0.0 0 452

R21 34 oo--o HCV1 2 1 0.45 0 0% 0% 0.0 0 1

R11 T11 40 o--o-o--o HCV1 0 0 0.63 0 0% 0% 0.0 0 0

A112 41 o-o--oo HCV1 57 25 0.45 0 0% 0% 0.0 0 25

R12 T1 42 o-oo--o HCV1 1 1 0.76 0 0% 0% 0.0 0 1

R21 T1 44 oo-o--o HCV1 0 0 0.00 0 0% 0% 0.0 0 0

R22 45 oo--oo HCV1 379 403 1.06 0 0% 0% 0.0 0 403

R13 47 o--ooo HCV1 3 6 1.83 0 0% 0% 0.0 0 6

50 o-o-o-o-o HCV2 0 0 1.50 0 0% 0% 0.0 0 0

R12 T11 52 o--oo-o--o HCV2 12 14 1.17 0 0% 0% 0.0 0 14

A122 53 o-oo--oo HCV2 60 93 1.53 0 0% 0% 0.0 0 93

57 o--o-----ooo HCV2 4 6 1.50 0 0% 0% 0.0 0 6

A111 T12 61 o-o--o-o--oo HCV2 0 0 2.94 0 0% 0% 0.0 0 0

62 o--oo--o-o-o HCV2 11 32 2.90 0 0% 0% 0.0 0 32

R12 T12 63 o--oo-o--oo HCV2 41 85 2.09 0 0% 0% 0.0 0 85

R21 T12 65 oo--o-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

R22 T11 66 oo--oo-o--o HCV2 4 5 1.24 0 0% 0% 0.0 0 5

R22 T2 68 oo--oo--oo HCV2 77 105 1.38 0 0% 0% 0.0 0 105

A123 69 o-oo--ooo HCV2 283 494 1.75 0 0% 0% 0.0 0 494

A122 T11 74 o-oo--oo-o--o HCV2 0 0 0.00 0 0% 0% 0.0 0 0

R22 T12 77 oo--oo-o--oo HCV2 124 293 2.37 0 0% 0% 0.0 0 293

78 o--ooo-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

85 o-oo--oo-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

A123 T11 89 o-oo--ooo-o--o HCV2 0 0 0.00 0 0% 0% 0.0 0 0

300 o--o--o MCV 71 36 0.50 0 0% 0% 0.0 0 36

301 o--oo HCV1 16 16 1.00 0 0% 0% 0.0 0 16

401 o--o--oo MCV 76 38 0.50 0 0% 0% 0.0 0 38

402 o--oo---o HCV1 21 21 1.00 0 0% 0% 0.0 0 21

503 o--oo--oo HCV2 8 12 1.50 0 0% 0% 0.0 0 12

511 oo--ooo HCV1 1 1 1.50 0 0% 0% 0.0 0 1

A121 T11 621 o-oo--o-o--o HCV2 0 0 0.00 0 0% 0% 0.0 0 0

622 o--o--oo--o-o HCV2 0 1 2.90 0 0% 0% 0.0 0 1

A223 713 oo-oo--ooo HCV2 28 70 2.52 0 0% 0% 0.0 0 70

A121 T12 731 o-oo--o-o--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

A133 747 o--ooo---ooo HCV2 1 2 2.21 0 0% 0% 0.0 0 2


or T&THCV2

294711 2.42 0 0% 0% 0.0 0 711

A122 T2 752 o--oo-oo--oo HCV2 0 0 0.00 0 0% 0% 0.0 0 0

771 oo--o--oo--oo HCV2 0 1 1.70 0 0% 0% 0.0 0 1

A124 791 o-oo-oooo HCV2 211 437 2.07 0 0% 0% 0.0 0 437

811 o--oo--oo--ooo HCV2 1 2 2.65 0 0% 0% 0.0 0 2

A224 826 oo-oo--oooo HCV2 206 283 1.37 0 0% 0% 0.0 0 283

A134 847 o--ooo---oooo HCV2 2 4 1.75 0 0% 0% 0.0 0 4



B2232 914 oo-oo--ooo-oo HCV2 13 20 1.53 0 0% 0% 0.0 0 20

R22 T23 915 oo-oo--oo-ooo HCV2 32 57 1.75 0 0% 0% 0.0 0 57

B1233 951 o-oo-ooo-ooo HCV2 251 421 1.68 0 0% 0% 0.0 0 421

B2233 1020 oo-oo-ooo-ooo HCV2 2 2 1.04 0 0% 0% 0.0 0 2

B1234 1032 o-oo-ooo-oooo HCV2 0 0 0 0% 0% 0.0 0 0


Total SUM 7051 9311 62 748.5 0.57 627 9176

-1.45






2-S4908.00.001NI

April 2013 42

Appendix B – CAPTIF Research of Equivalent Standard Axles and

Pavement Strength Relationship

Road traffic consists of a range of vehicle types, wheels and loads. A method intrinsic in

pavement design and deterioration modelling is to combine all traffic into one type. This one

type of traffic is commonly referred to as an Equivalent Standard Axle (ESA). The standard

axle is defined as a single axle with dual wheels that carries a load of 8.2 tonnes (40kN half

dual tyred axle as tested at NZTAs Pavement Test Facility CAPTIF).

To calculate the number of ESA for any given traffic distribution, equation (1) is used as

given in the Austroads Pavement Design Guide (Austroads, 2004):

ESA = Axle load

Axle load reference

where,

ESAs = number of standard axles needed to cause the same damage as one pass

of the actual axle load (Axle load, Equation 1).

Axle load = actual axle load in kN (or total axle group weight).

Axle load reference = reference load depending on the axle load group below.

Axle Group Type Load (kN) Load (kg)

Single axle with single tyres (SAST) 53 5400

Single axle with dual tyres (SADT) 80 8160

Tandem axle with dual tyres (TADT) 135 13770

Triaxial with dual tyres (TRDT) 181 18460

Quad-axle with dual tyres (QADT) 221 22540

n = damage law exponent (commonly = 4, although different exponents are used

depending on pavement strength, SNP).

Research at CAPTIF on the effects of Mass Limits found that the fourth power relationship

is not valid for all pavement types. A range of relationships were determined between SNP

(determined by two different FWD methods) and the damage law exponent, n. Results

showed that the exponent is nearly 1.0 for strong well built pavements (high SNP) and as

high as 8.0 for weak pavements (low SNP) indicating their brittle nature (i.e. weak

pavements fail quickly if their shear strength is exceeded). Practitioners would agree with

this trend as local roads that are weak would fail quickly with the introduction of new

vehicles with increased mass limits. Further, the expected trend is that the strong

pavements (high SNP) on the busiest state highways would feel little structural impact with

the introduction of increased mass limits.

n

(1)


2-S4908.00.001NI

April 2013 43

Two methods were used at CAPTIF to calculate the SNP. One method involved a

regression equation using FWD deflection data. The regression equation has since

changed and therefore the CAPTIF data was revisited to determine SNP using the new

equation (2):

SNP = 112(D0)-0.5 +47(D0-D900)

-0.5 -56(D0-D1500)-0.5 -0.4

Where deflections are in microns, after standardising to 40 kN plate load and subscripts are

offsets in mm from the plate centre.

The end of life for the CAPTIF pavements was a rut depth/vertical surface deformation of

15 mm. Based on this criteria and the new equation for calculating SNP a relationship

between damage exponent, n and SNP was determined as detailed in Figure 56.

Although the CAPTIF results match expectations they are from a very limited number of

pavement types and should be used cautiously.

Figure 5 – SNP versus damage exponent (n)

For the ESA damage exponent of 4 the correlating SNP is 2.4, based on the new equation

from CAPTIF. This indicates that those pavements with a SNP lower than 2.4, may

potentially be more susceptible to loading impact than those with an SNP of 2.4 or more.

6 Opus International Consultants Ltd. VDM Rule Amendment Impact on State Highway Pavements. April

2010, pp 21-22, Figure 4.2.1a.

n = 51.62SNP-2.8832

R2 = 0.9695

y = 5.8104x-1.34

R2 = 0.9697

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00

SNP

Da

ma

ge

Exp

on

en

t, n

New Eqn

Old Eqn from CAPTIF

(2)


2-S4908.00.001NI

April 2013 44

Appendix C – Loading Effects on Pavement Design

Granular Overlay Depth Change

The common method of determining the granular overlay depth is to assume a design of a

new pavement where the:

Granular Overlay Depth = Depth of New Pavement minus the Depth of the Old/Existing

Pavement.

Table D-1 below shows a worst case scenario for the increase in thickness due to a 10%

increase in ESA based on the design chart from Austroads as shown above. As the

percentage increase in ESAs is the same only the subgrade CBR affects the increase in

depth required.

Subgrade

CBR

Existing ESA New LB HPMV

ESA

Depth Required

(Existing)

(mm)

Depth Required

(LB HPMV)

(mm)

Increase in

Depth

(mm)

2 1.00E+7 1.10E+7 791 798 7

3 1.00E+7 1.10E+7 647 653 6

4 1.00E+7 1.10E+7 556 561 5

5 1.00E+7 1.10E+7 491 495 4

7 1.00E+7 1.10E+7 404 407 3

10 1.00E+7 1.10E+7 325 328 3

15 1.00E+7 1.10E+7 251 253 2

Documents

Lower Bound HPMV s Analysis of Pavement Impacts · Analysis of Pavement Impacts Prepared By Opus International Consultants Ltd Adele Jones Napier Office Asset Manager - Infrastructure