Lower Bound HPMVs
Analysis of Pavement Impacts
Lower Bound HPMVs
Analysis of Pavement Impacts
Prepared By
Adele Jones
Asset Manager - Infrastructure
Reviewed By
William Gray
Service Excellence Leader - Central Region
Approved for
Release By
Trent Downing
Work Group Manager - Information
Management
© Opus International Consultants Ltd 2012
Opus International Consultants Ltd
Napier Office
Opus House, 6 Ossian Street
Private Bag 6019, Hawkes Bay Mail Centre,
Napier 4142
New Zealand
Telephone:
Facsimile:
+64 6 833 5100
+64 6 835 0881
Date:
Reference:
Status:
29 April 2013
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Lower Bound HPMVs – Analysis of Pavement Impacts
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
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
Axle Gp
1
Average Weight (tonnes)
Axle Gp Axle Gp Axle Gp
2
3
4
ESA
GCW
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
R11
20
R11
21
R11T1
Vehicle
Configurations
Veh
Class
Drury
Tokoroa
Te Puke
Waipara
Eskdale
MCV
73556
10475
15018
19322
4767
MCV
320439
68368
110396
70583
29178
30
o-o (wb 2.0-3.2m, gw
>= 2.5t)
o--o (wb >3.2m, gw
>= 2.5t)
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
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
A111 T12
622
o--o--oo--o-o
HCV2
24
13
9
19
0
A223
713
oo-oo--ooo
HCV2
11925
2741
1945
1443
819
A133
R12 T22 or
B1222
747
HCV2
275
60
38
54
2
HCV2
101289
26611
44643
15274
10244
771
o--ooo---ooo
o-oo--oo--oo B-train
or T&T
oo--o--oo--oo
HCV2
2
31
11
24
2
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
A124
751
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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Lower Bound HPMVs – Analysis of Pavement Impacts
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” takeup 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
WiM Site
Drury
Tokoroa
Te Puke
Eskdale
Waipara
Nominal 50t LB HPMV
17% take- 52% take- 66% takeup
up
up
-5.2%
-7.9%
-6.4%
-7.7%
-7.7%
-1.0%
-1.6%
-1.4%
-1.6%
-1.5%
0.7%
0.9%
0.7%
0.8%
1.1%
6% Overloaded LB HPMV
17% take- 52% take- 66% takeup
up
up
-4.1%
-6.1%
-5.0%
-6.0%
-5.9%
2.6%
3.8%
3.0%
3.6%
4.2%
5.3%
7.8%
6.2%
7.5%
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:
4
•
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
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
Auckland Area*
Yes
5499
93%
Central Hawke’s
Bay DC
South Waikato
DC
Wairoa DC
Yes
1263
68%
56%
Yes
528
98%
20%
Yes
904
30%
18%
Western Bay of
Plenty DC
Yes
1027
78%
Ashburton DC
Gore DC
Mackenzie DC
Marlborough DC
No
No
No
Yes
2630
894
711
1519
56%
40%
27%
57%
0%
0%
0%
11%
Southland DC
Yes
4966
39%
11%
Typical
AADT
Basis of SNP
Data†
50020,000+
Representative
value for each
treatment length
Individual FWD
test points
Individual FWD
test points
Individual FWD
test points
Individual FWD
test points
North Island
100-2,000
100-1,000
100-4,000
South Island
100-4,000
100-2,000
100-1,000
100-5,000
N/A
N/A
N/A
Individual FWD
test points
100-2,000 Representative
value for each
treatment length
100-8,000 N/A
100-1,000 N/A
CC, Papakura CC, and Waitakere
Timaru DC
No
1718
55%
0%
Waitaki DC
No
1832
41%
0%
*Auckland Area includes Auckland CC, Franklin DC, Manukau
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 2830% 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 viscoelastic 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.
Original VDM Methodology
•
6.3
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
Planned
maintenance
Reactive
maintenance
Pavement and
surfacing design
changes
Governing
Loading Impact
• Rutting in
subgrade (ESA
increase = 0)
• Shear failure
• Surface damage
• Rutting in
subgrade (ESA
increase = 0)
• Shear failure
• Surface damage
• Rutting in
subgrade (ESA
increase = 0)
Areas of Impact
Assessed
Pavement
Impact
• 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.
• 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.
• Even in an increased loading situation
pavement design changes can be
minimal. Austroads 2004 Figure 8.4
Possible minimal
increase
2-S4908.00.001NI
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28
Nil to small some resurfacing
may need to be
Lower Bound HPMVs – Analysis of Pavement Impacts
Pavement
Impact Factor
Vulnerable Areas
6.4
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.
• 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
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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Lower Bound HPMVs – Analysis of Pavement Impacts
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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Lower Bound HPMVs – Analysis of Pavement Impacts
Table 7 – Truck and Trailer Existing and LB HPMV Configurations
Vehicle
Configuration
Load
State
Axle
Gp 1
Axle
Gp 2
Average Weight (tonnes)
Truck
Axle
Axle
Trailer
Gp 3
Gp 4
R22T22
R12T22
R22T23 (LB)
ESA
Laden
9.34
13.54
22.88
10.71
11.16
21.88
44.76
2.81
Laden
5.67
14.45
20.12
11.73
12.73
24.46
44.58
3.68
Laden
9.84
14.04
23.88
12.21
14.66
26.88
50.76
3.42
GCW
Table 8 – B-Train Existing and LB HPMV Configurations
Vehicle
Configuration
Load
State
Axle Gp 1
Average Weight (tonnes)
Axle Gp 2 Axle Gp 3 Axle Gp 4
ESA
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
GCW
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
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Lower Bound HPMVs – Analysis of Pavement Impacts
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 NZdTIMS, 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.
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Lower Bound HPMVs – Analysis of Pavement Impacts
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.
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Lower Bound HPMVs – Analysis of Pavement Impacts
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.
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Lower Bound HPMVs – Analysis of Pavement Impacts
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.
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Lower Bound HPMVs – Analysis of Pavement Impacts
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.
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Lower Bound HPMVs – Analysis of Pavement Impacts
Appendix A – ESA Calculation Spreadsheets for WiM sites (n=4)
LB HPMVs 50tonne, 52% “Base Case” take-up scenario
DRURY WiM SITE
Existing Traffic Fleet
Vehicles
converted
to LB
HPMV
Numb.
Passes for 1 week
or more Sum ESAs
New traffic Fleet (including 50t LB HPMVs)
Average
ESA per
Vehicle*
No.
Vehicles
Changed
to LB
HPMV
R11
21
R11T1
30
Vehicle
Configurations
o-o (wb 2.0-3.2m,
gw >= 2.5t)
o--o (wb >3.2m, gw
>= 2.5t)
o-o--o
R12
R21
R11 T11
A112
R12 T1
R21 T1
R22
R13
31
34
40
41
42
44
45
47
o--oo
oo--o
o--o-o--o
o-o--oo
o-oo--o
oo-o--o
oo--oo
o--ooo
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
50
52
53
57
61
62
63
o-o-o-o-o
o--oo-o--o
o-oo--oo
o--o-----ooo
o-o--o-o--oo
o--oo--o-o-o
o--oo-o--oo
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
65
66
68
69
74
77
78
oo--o-o--oo
oo--oo-o--o
oo--oo--oo
o-oo--ooo
o-oo--oo-o--o
oo--oo-o--oo
o--ooo-o--oo
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
85
89
300
301
401
402
503
o-oo--oo-o--oo
o-oo--ooo-o--o
o--o--o
o--oo
o--o--oo
o--oo---o
o--oo--oo
HCV2
HCV2
MCV
HCV1
MCV
HCV1
HCV2
A223
A121 T12
A133
511
621
622
713
731
747
HCV1
HCV2
HCV2
HCV2
HCV2
HCV2
R12 T22 or B1222
751
A122 T2
A224
A134
752
771
791
811
826
847
oo--ooo
o-oo--o-o--o
o--o--oo--o-o
oo-oo--ooo
o-oo--o-o--oo
o--ooo---ooo
o-oo--oo--oo B-train
or T&T
o--oo-oo--oo
oo--o--oo--oo
o-oo-oooo
o--oo--oo--ooo
oo-oo--oooo
o--ooo---oooo
B1232
851 o-oo--ooo--oo
HCV2
LB HMPV
1639
2771
1.69
469
R22 T22
B2232
891 oo--oo-oo--oo
914 oo-oo--ooo-oo
HCV2
HCV2
LB HMPV
4833
34
55
570
9135
51
1.89
1.53
1382
0
53
0
0
96
957
56
0
0
1.75
1.68
1.04
0
0
0
0
0
27312
34346
Type
R11
R12 T11
A122
A111 T12
R12 T12
R21 T12
R22 T11
R22 T2
A123
A122 T11
R22 T12
A123 T11
A121 T11
A124
R22 T23
B1233
B2233
B1234
B2234
WIM
20
915
951
1020
1032
1133
oo-oo--oo-ooo
o-oo-ooo-ooo
oo-oo-ooo-ooo
o-oo-ooo-oooo
oo-oo-ooo-oooo
% 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)
MCV
1415
54
0.04
0
0%
0%
0.0
0
54
MCV
6162
1528
0.25
0
0%
0%
0.0
0
1528
HCV1
66
2612
9
18
0.27
0
0%
0.0
0
18
2957
4
0
110
10
0
1471
1
1.13
0.45
0.63
0.45
0.76
0.00
1.06
1.83
0
0
0
0
0
0
0
0
0%
0%
0%
0%
0%
0%
0%
0%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0
0
2957
4
0
110
10
0
1471
1
1
124
562
35
0
70
366
1.50
1.17
1.53
1.50
2.94
2.90
2.09
0
0
0
0
0
0
0
0%
0%
0%
0%
0%
0%
0%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0
1
124
562
35
0
70
366
0
19
379
4179
0
550
0
0.00
1.24
1.38
1.75
0.00
2.37
0.00
0
0
0
0
0
0
0
0%
0%
0%
0%
0%
0%
0%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0
0
19
379
4179
0
550
0
0
0
102
45
84
63
8
0.00
0.00
0.50
1.00
0.50
1.00
1.50
0
0
0
0
0
0
0
0%
0%
0%
0%
0%
0%
0%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0
0
0
102
45
84
63
8
17
0
1
578
0
12
1.50
0.00
2.90
2.52
0.00
2.21
0
0
0
0
0
0
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
17
0
1
578
0
12
4714
2.42
0
0%
0%
0.0
0
4714
738
26
1149
26
0
0
1529
68
1577
45
0.00
1.70
2.07
2.65
1.37
1.75
0
0
0
0
0
0
0%
0%
0%
0%
0%
0%
52%
52%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0
0
1529
68
1577
45
29%
13.6
2.85
391
2824
29%
0%
13.6
0.0
3.22
1160
0
8739
51
0%
0%
0%
0%
0%
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
96
957
56
0
0
0
244
13
0
1381
1
1
106
366
23
0
24
175
0
16
276
2388
0
232
0
0
0
204
45
169
63
5
11
0
0
229
0
5
HCV2
1948
0
0
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
Total
1851
1551
% ESA Loading increase:
*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
2-S4908.00.001NI
April 2013
37
34004
-1.00
Lower Bound HPMVs – Analysis of Pavement Impacts
Tokoroa WiM SITE
Existing Traffic Fleet
Type
R11
R11
R11T1
R12
R21
R11 T11
A112
R12 T1
R21 T1
R22
R13
WIM
20
21
A223
A121 T12
A133
30
31
34
40
41
42
44
45
47
50
52
53
57
61
62
63
65
66
68
69
74
77
78
85
89
300
301
401
402
503
511
621
622
713
731
747
R12 T22 or B1222
751
A122 T2
752
771
791
811
826
847
R12 T11
A122
A111 T12
R12 T12
R21 T12
R22 T11
R22 T2
A123
A122 T11
R22 T12
A123 T11
A121 T11
A124
A224
A134
B1232
R22 T22
B2232
R22 T23
B1233
B2233
B1234
B2234
851
891
914
915
951
1020
1032
1133
New traffic Fleet (including 50t LB HPMVs)
% Uptake
to HMPV
% of the
heaviest
vehicles
changed
(55%
loaded)
% Weight
Increase
applied
0
0%
0%
0.25
0
0%
0.27
1.13
0.45
0.63
0.45
0.76
0.00
1.06
1.83
1.50
1.17
1.53
1.50
2.94
2.90
2.09
0.00
1.24
1.38
1.75
0.00
2.37
0.00
0.00
0.00
0.50
1.00
0.50
1.00
1.50
1.50
0.00
2.90
2.52
0.00
2.21
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
1238
2.42
0
0
1
456
23
591
9
0.00
1.70
2.07
2.65
1.37
1.75
0
0
0
0
0
0
Veh
Number of
converted Passes for 1 week
to LB
HPMV
or more Sum ESAs
Average
ESA per
Veh*
No.
Vehicles
Changed
MCV
201
8
0.04
MCV
1315
326
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
MCV
HCV1
MCV
HCV1
HCV2
HCV1
HCV2
HCV2
HCV2
HCV2
HCV2
15
589
6
0
75
1
1
613
0
1
15
72
4
0
13
69
0
6
130
450
0
108
0
0
0
54
8
55
20
2
1
0
0
53
0
1
4
667
3
0
34
1
0
652
1
1
17
110
6
0
38
144
0
7
179
788
0
256
0
0
0
27
8
28
20
3
2
0
1
133
0
3
Vehicle
Configurations
o-o (wb 2.0-3.2m,
gw >= 2.5t)
o--o (wb >3.2m, gw
>= 2.5t)
o-o--o
o--oo
oo--o
o--o-o--o
o-o--oo
o-oo--o
oo-o--o
oo--oo
o--ooo
o-o-o-o-o
o--oo-o--o
o-oo--oo
o--o-----ooo
o-o--o-o--oo
o--oo--o-o-o
o--oo-o--oo
oo--o-o--oo
oo--oo-o--o
oo--oo--oo
o-oo--ooo
o-oo--oo-o--o
oo--oo-o--oo
o--ooo-o--oo
o-oo--oo-o--oo
o-oo--ooo-o--o
o--o--o
o--oo
o--o--oo
o--oo---o
o--oo--oo
oo--ooo
o-oo--o-o--o
o--o--oo--o-o
oo-oo--ooo
o-oo--o-o--oo
o--ooo---ooo
o-oo--oo--oo B-train
or T&T
o--oo-oo--oo
oo--o--oo--oo
o-oo-oooo
o--oo--oo--ooo
oo-oo--oooo
o--ooo---oooo
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
o-oo--ooo--oo
oo--oo-oo--oo
oo-oo--ooo-oo
oo-oo--oo-ooo
o-oo-ooo-ooo
oo-oo-ooo-ooo
o-oo-ooo-oooo
oo-oo-ooo-oooo
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
Total
512
0
1
220
9
430
5
LB HMPV
807
LB HMPV
2952
14
41
416
7
0
0
1364
5579
22
71
699
7
0
0
1.69
1.89
1.53
1.75
1.68
1.04
231
844
0
0
0
0
0
0
9291
13525
62
1075.1
SUM
Number of
vehicles
needed to
cart same
load
Sum ESAs
(all
vehicles
includes
those not
changed)
0.0
0
8
0%
0.0
0
326
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4
667
3
0
34
1
0
652
1
1
17
110
6
0
38
144
0
7
179
788
0
256
0
0
0
27
8
28
20
3
2
0
1
133
0
3
0%
0%
0.0
0
1238
0%
0%
0%
0%
0%
0%
52%
52%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0
1
456
23
591
9
29%
29%
0%
0%
0%
0%
0%
0%
13.6
13.6
0.0
0.0
0.0
0.0
0.0
0.0
193
708
0
0
0
0
0
0
1391
5337
22
71
699
7
0
0
0.57
New ESA
for the
heavy
vehicles
changed
2.85
3.22
901
% ESA Loading increase:
*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
2-S4908.00.001NI
April 2013
38
13310
-1.59
Lower Bound HPMVs – Analysis of Pavement Impacts
TE PUKE WiM SITE
Existing Traffic Fleet
Type
WIM
R11
20
R11
21
R11T1
R12
R21
R11 T11
A112
R12 T1
R21 T1
R22
R13
A223
A121 T12
A133
30
31
34
40
41
42
44
45
47
50
52
53
57
61
62
63
65
66
68
69
74
77
78
85
89
300
301
401
402
503
511
621
622
713
731
747
R12 T22 or B1222
751
A122 T2
752
771
791
811
826
847
R12 T11
A122
A111 T12
R12 T12
R21 T12
R22 T11
R22 T2
A123
A122 T11
R22 T12
A123 T11
A121 T11
A124
A224
A134
B1232
R22 T22
B2232
R22 T23
B1233
B2233
B1234
B2234
851
891
914
915
951
1020
1032
1133
New traffic Fleet (including 50t LB HPMVs)
% Uptake
to HMPV
% of the
heaviest
vehicles
changed
(55%
loaded)
% Weight
Increase
applied
0
0%
0%
0.0
0
11
0
0%
0%
0.0
0
526
0.27
1.13
0.45
0.63
0.45
0.76
0.00
1.06
1.83
1.50
1.17
1.53
1.50
2.94
2.90
2.09
0.00
1.24
1.38
1.75
0.00
2.37
0.00
0.00
0.00
0.50
1.00
0.50
1.00
1.50
1.50
0.00
2.90
2.52
0.00
2.21
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
952
2
0
24
0
0
1177
1
0
18
84
5
0
27
228
0
9
31
1274
0
284
0
0
0
29
27
27
18
6
2
0
1
94
0
2
2078
2.42
0
0%
0%
0.0
0
2078
0
0
284
1
536
53
0.00
1.70
2.07
2.65
1.37
1.75
0
0
0
0
0
0
0%
0%
0%
0%
0%
0%
52%
52%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0
0
284
1
536
53
29%
29%
0%
0%
0%
0%
0%
0%
13.6
13.6
0.0
0.0
0.0
0.0
0.0
0.0
124
580
0
0
0
0
0
0
894
4366
21
4
60
1
0
0
Veh
Number of
converted Passes for 1 week
to LB
HPMV
or more Sum ESAs
Average
ESA per
Veh*
No.
Vehicles
Changed
MCV
289
11
0.04
MCV
2123
526
0.25
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
MCV
HCV1
MCV
HCV1
HCV2
HCV1
HCV2
HCV2
HCV2
HCV2
HCV2
7
841
4
0
52
0
0
1105
0
0
16
55
3
0
9
109
0
7
22
728
0
120
0
0
0
57
27
53
18
4
1
0
0
37
0
1
2
952
2
0
24
0
0
1177
1
0
18
84
5
0
27
228
0
9
31
1274
0
284
0
0
0
29
27
27
18
6
2
0
1
94
0
2
Vehicle
Configurations
o-o (wb 2.0-3.2m,
gw >= 2.5t)
o--o (wb >3.2m, gw
>= 2.5t)
o-o--o
o--oo
oo--o
o--o-o--o
o-o--oo
o-oo--o
oo-o--o
oo--oo
o--ooo
o-o-o-o-o
o--oo-o--o
o-oo--oo
o--o-----ooo
o-o--o-o--oo
o--oo--o-o-o
o--oo-o--oo
oo--o-o--oo
oo--oo-o--o
oo--oo--oo
o-oo--ooo
o-oo--oo-o--o
oo--oo-o--oo
o--ooo-o--oo
o-oo--oo-o--oo
o-oo--ooo-o--o
o--o--o
o--oo
o--o--oo
o--oo---o
o--oo--oo
oo--ooo
o-oo--o-o--o
o--o--oo--o-o
oo-oo--ooo
o-oo--o-o--oo
o--ooo---ooo
o-oo--oo--oo B-train
or T&T
o--oo-oo--oo
oo--o--oo--oo
o-oo-oooo
o--oo--oo--ooo
oo-oo--oooo
o--ooo---oooo
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
o-oo--ooo--oo
oo--oo-oo--oo
oo-oo--ooo-oo
oo-oo--oo-ooo
o-oo-ooo-ooo
oo-oo-ooo-ooo
o-oo-ooo-oooo
oo-oo-ooo-oooo
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
Total
859
0
0
137
0
390
30
LB HMPV
519
LB HMPV
2415
14
2
36
1
0
0
877
4564
21
4
60
1
0
0
1.69
1.89
1.53
1.75
1.68
1.04
148
691
0
0
0
0
0
0
10093
13337
62
839.1
SUM
0.57
New ESA
for the
heavy
vehicles
changed
2.85
3.22
Number of
vehicles
needed to
cart same
load
703
% ESA Loading increase:
*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
2-S4908.00.001NI
April 2013
39
Sum ESAs
(all
vehicles
includes
those not
changed)
13157
-1.36
Lower Bound HPMVs – Analysis of Pavement Impacts
ESKDALE WiM SITE
Existing Traffic Fleet
Type
R11
R11
R11T1
R12
R21
R11 T11
A112
R12 T1
R21 T1
R22
R13
WIM
20
21
A223
A121 T12
A133
30
31
34
40
41
42
44
45
47
50
52
53
57
61
62
63
65
66
68
69
74
77
78
85
89
300
301
401
402
503
511
621
622
713
731
747
R12 T22 or B1222
751
A122 T2
752
771
791
811
826
847
R12 T11
A122
A111 T12
R12 T12
R21 T12
R22 T11
R22 T2
A123
A122 T11
R22 T12
A123 T11
A121 T11
A124
A224
A134
B1232
R22 T22
B2232
R22 T23
B1233
B2233
B1234
B2234
851
891
914
915
951
1020
1032
1133
New traffic Fleet (including 50t LB HPMVs)
Veh
Number of
converted Passes to LB
for 1 week
HPMV
or more Sum ESAs
Average
ESA per
Vehicle*
No.
Vehicles
Changed
% Uptake
to HMPV
% of the
heaviest
vehicles
changed
(55%
loaded)
MCV
92
4
0.04
0
0%
0%
0.0
0
4
MCV
561
139
0.25
0
0%
0%
0.0
0
139
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
MCV
HCV1
MCV
HCV1
HCV2
HCV1
HCV2
HCV2
HCV2
HCV2
HCV2
5
206
3
0
28
1
0
597
0
0
9
37
3
0
13
13
0
1
18
134
0
76
0
0
0
22
4
29
7
1
0
0
0
16
0
0
1
233
1
0
13
0
0
635
1
0
10
56
4
0
38
28
0
1
25
235
0
181
0
0
0
11
4
14
7
1
0
0
0
40
0
0
0.27
1.13
0.45
0.63
0.45
0.76
0.00
1.06
1.83
1.50
1.17
1.53
1.50
2.94
2.90
2.09
0.00
1.24
1.38
1.75
0.00
2.37
0.00
0.00
0.00
0.50
1.00
0.50
1.00
1.50
1.50
0.00
2.90
2.52
0.00
2.21
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
233
1
0
13
0
0
635
1
0
10
56
4
0
38
28
0
1
25
235
0
181
0
0
0
11
4
14
7
1
0
0
0
40
0
0
477
2.42
0
0%
0%
0.0
0
477
0
0
86
13
212
1
0.00
1.70
2.07
2.65
1.37
1.75
0
0
0
0
0
0
0%
0%
0%
0%
0%
0%
52%
52%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0
0
86
13
212
1
29%
29%
0%
0%
0%
0%
0%
0%
13.6
13.6
0.0
0.0
0.0
0.0
0.0
0.0
57
265
0
0
0
0
0
0
409
1997
13
5
105
2
0
0
Vehicle
Configurations
o-o (wb 2.0-3.2m,
gw >= 2.5t)
o--o (wb >3.2m, gw
>= 2.5t)
o-o--o
o--oo
oo--o
o--o-o--o
o-o--oo
o-oo--o
oo-o--o
oo--oo
o--ooo
o-o-o-o-o
o--oo-o--o
o-oo--oo
o--o-----ooo
o-o--o-o--oo
o--oo--o-o-o
o--oo-o--oo
oo--o-o--oo
oo--oo-o--o
oo--oo--oo
o-oo--ooo
o-oo--oo-o--o
oo--oo-o--oo
o--ooo-o--oo
o-oo--oo-o--oo
o-oo--ooo-o--o
o--o--o
o--oo
o--o--oo
o--oo---o
o--oo--oo
oo--ooo
o-oo--o-o--o
o--o--oo--o-o
oo-oo--ooo
o-oo--o-o--oo
o--ooo---ooo
o-oo--oo--oo B-train
or T&T
o--oo-oo--oo
oo--o--oo--oo
o-oo-oooo
o--oo--oo--ooo
oo-oo--oooo
o--ooo---oooo
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
o-oo--ooo--oo
oo--oo-oo--oo
oo-oo--ooo-oo
oo-oo--oo-ooo
o-oo-ooo-ooo
oo-oo-ooo-ooo
o-oo-ooo-oooo
oo-oo-ooo-oooo
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
Total
197
0
0
42
5
154
1
LB HMPV
237
LB HMPV
1104
8
3
63
2
0
0
401
2087
13
5
105
2
0
0
1.69
1.89
1.53
1.75
1.68
1.04
68
316
0
0
0
0
0
0
3691
5085
62
383.7
SUM
0.57
% Weight
Increase
applied
New ESA
for the
heavy
vehicles
changed
2.85
3.22
Number of
vehicles
needed to
cart same
load
Sum ESAs
(all
vehicles
includes
those not
changed)
322
% ESA Loading increase:
*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
2-S4908.00.001NI
April 2013
40
5002
-1.63
Lower Bound HPMVs – Analysis of Pavement Impacts
Waipara WiM SITE
Existing Traffic Fleet
Type
R11
R11
R11T1
R12
R21
R11 T11
A112
R12 T1
R21 T1
R22
R13
WIM
20
21
A223
A121 T12
A133
30
31
34
40
41
42
44
45
47
50
52
53
57
61
62
63
65
66
68
69
74
77
78
85
89
300
301
401
402
503
511
621
622
713
731
747
R12 T22 or B1222
751
A122 T2
752
771
791
811
826
847
R12 T11
A122
A111 T12
R12 T12
R21 T12
R22 T11
R22 T2
A123
A122 T11
R22 T12
A123 T11
A121 T11
A124
A224
A134
B1232
R22 T22
B2232
R22 T23
B1233
B2233
B1234
B2234
851
891
914
915
951
1020
1032
1133
New traffic Fleet (including 50t LB HPMVs)
% Uptake
to HMPV
% of the
heaviest
vehicles
changed
(55%
loaded)
% Weight
Increase
applied
0
0%
0%
0.25
0
0%
0.27
1.13
0.45
0.63
0.45
0.76
0.00
1.06
1.83
1.50
1.17
1.53
1.50
2.94
2.90
2.09
0.00
1.24
1.38
1.75
0.00
2.37
0.00
0.00
0.00
0.50
1.00
0.50
1.00
1.50
1.50
0.00
2.90
2.52
0.00
2.21
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
711
2.42
0
0
1
437
2
283
4
0.00
1.70
2.07
2.65
1.37
1.75
0
0
0
0
0
0
Veh
Number of
converted Passes for 1 week
to LB
HPMV
or more Sum ESAs
Average
ESA per
Veh*
No.
Vehicles
Changed
MCV
372
14
0.04
MCV
1357
337
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV1
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
MCV
HCV1
MCV
HCV1
HCV2
HCV1
HCV2
HCV2
HCV2
HCV2
HCV2
15
399
2
0
57
1
0
379
3
0
12
60
4
0
11
41
0
4
77
283
0
124
0
0
0
71
16
76
21
8
1
0
0
28
0
1
4
452
1
0
25
1
0
403
6
0
14
93
6
0
32
85
0
5
105
494
0
293
0
0
0
36
16
38
21
12
1
0
1
70
0
2
Vehicle
Configurations
o-o (wb 2.0-3.2m,
gw >= 2.5t)
o--o (wb >3.2m, gw
>= 2.5t)
o-o--o
o--oo
oo--o
o--o-o--o
o-o--oo
o-oo--o
oo-o--o
oo--oo
o--ooo
o-o-o-o-o
o--oo-o--o
o-oo--oo
o--o-----ooo
o-o--o-o--oo
o--oo--o-o-o
o--oo-o--oo
oo--o-o--oo
oo--oo-o--o
oo--oo--oo
o-oo--ooo
o-oo--oo-o--o
oo--oo-o--oo
o--ooo-o--oo
o-oo--oo-o--oo
o-oo--ooo-o--o
o--o--o
o--oo
o--o--oo
o--oo---o
o--oo--oo
oo--ooo
o-oo--o-o--o
o--o--oo--o-o
oo-oo--ooo
o-oo--o-o--oo
o--ooo---ooo
o-oo--oo--oo B-train
or T&T
o--oo-oo--oo
oo--o--oo--oo
o-oo-oooo
o--oo--oo--ooo
oo-oo--oooo
o--ooo---oooo
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
o-oo--ooo--oo
oo--oo-oo--oo
oo-oo--ooo-oo
oo-oo--oo-ooo
o-oo-ooo-ooo
oo-oo-ooo-ooo
o-oo-ooo-oooo
oo-oo-ooo-oooo
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
HCV2
Total
294
0
0
211
1
206
2
LB HMPV
698
LB HMPV
1920
13
32
251
2
0
0
1179
3628
20
57
421
2
0
0
1.69
1.89
1.53
1.75
1.68
1.04
200
549
0
0
0
0
0
0
7051
9311
62
748.5
SUM
Number of
vehicles
needed to
cart same
load
Sum ESAs
(all
vehicles
includes
those not
changed)
0.0
0
14
0%
0.0
0
337
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4
452
1
0
25
1
0
403
6
0
14
93
6
0
32
85
0
5
105
494
0
293
0
0
0
36
16
38
21
12
1
0
1
70
0
2
0%
0%
0.0
0
711
0%
0%
0%
0%
0%
0%
52%
52%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0
1
437
2
283
4
29%
29%
0%
0%
0%
0%
0%
0%
13.6
13.6
0.0
0.0
0.0
0.0
0.0
0.0
167
461
0
0
0
0
0
0
1202
3470
20
57
421
2
0
0
0.57
New ESA
for the
heavy
vehicles
changed
2.85
3.22
627
% ESA Loading increase:
*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
2-S4908.00.001NI
April 2013
41
9176
-1.45
Lower Bound HPMVs – Analysis of Pavement Impacts
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):
n
ESA =
Axle load
(1)
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.
2-S4908.00.001NI
April 2013
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Lower Bound HPMVs – Analysis of Pavement Impacts
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
(2)
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.
4.00
New Eqn
3.50
n = 51.62SNP-2.8832
R2 = 0.9695
Damage Exponent, n
3.00
2.50
Old Eqn from CAPTIF
y = 5.8104x -1.34
R2 = 0.9697
2.00
1.50
1.00
0.50
0.00
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
SNP
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.
2-S4908.00.001NI
April 2013
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Lower Bound HPMVs – Analysis of Pavement Impacts
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
3
4
5
7
10
15
1.00E+7
1.00E+7
1.00E+7
1.00E+7
1.00E+7
1.00E+7
1.00E+7
1.10E+7
1.10E+7
1.10E+7
1.10E+7
1.10E+7
1.10E+7
1.10E+7
791
647
556
491
404
325
251
798
653
561
495
407
328
253
7
6
5
4
3
3
2
2-S4908.00.001NI
April 2013
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