Effects of the allowed axle load increase to the
track structure of forest road network
PÉTER PRIMUSZ
Abstract
In Hungary most of the roads were built before the development of the motorization but later more
and more heavy axle load trucks appear fluently in the forests. The condition of track structure’s
pavement is in close contact with the costs and the phase of decay progress. Increasing axle load,
the costs of carriage decrease but the costs of pavement management rapidly increase. So we can
determine an optimal truck type for every road network – it depends on the road’s conditions. And
this is very important for forest management, because they can plan what kind of trucks should
most be used in delivering.
Keywords: lifetime, bearing capacity, truck, road network, standard axle load, pavement costs
1. INTRODUCTION
Carriage is very important part of every
kind of production progress, which can’t
be imagine without correct road network
and carrying vehicles. However the 8-9
running meter / hectare road density in
Hungarian forest opening up can’t be
said ideal, because it’s enough just for
approaching the forest. In Hungary most
of the roads were built before the
development of the motorization, so they
were made for typical carriage with
horses or trailers. Later with the
development of technique the trucks
become typical in the traffic of forest
roads, these trucks’ broadness and axle
load are bigger than the formers’. The
unbeneficial damaging effects of the
appearing bigger axle load increased the
fact that the wheels displaced towards to
the borders of the road. These borders
were made vertically, so they could be
damage very easily. The increased
impressments
exhaust
the
roads,
Figure 1 The way and tempo of axle load
therefore begun their fast decay [5] [6].
But the general development of increase which is typical in forest road
network
the motorization did not avoid the roads
of forest, more and more heavy axle load trucks appear fluently in the forests.
Public road tests demonstrated that the pressure in the forest road structure
increase rapidly because of the growing axle load. The growing maintenance and
1
pavement management costs limit the vehicles which are good for carrying.
According to the AASHO (American Association of State Highway Officials) road
test it is said that the optimum of resultant of two contrast way impressing
factors is between 80-130 kN. It depends on weather and geology. This is the
comment that here and in most of the countries in Europe the allowed load for
solo axles is 100 kN (1 kN ≈ 0.1 ton) for tandem axles is 140 kN [1].
Till the first of May 2004. when Hungary joined to the EU these were the
allowed values. After joining we had to use the EU law, which regulates the
allowed biggest size and weight and axle load of the vehicles all over EU. This is
the 96/53/EK law. According to the direction the allowed biggest axle load of the
vehicles in the national and international traffic increased, so for solo axle it got
to 115 kN for tandem axle it got to 160 kN. We can see that because of the
direction, we have to count with bigger traffic not only in public roads, but in
forest roads too. That road structure which were made before the modernization
fulfil only partly the new requirements. But in the near future we have to count
that the vehicles in the material delivery will reach or almost catch the highest
limit (Figure 1).
2. VALUATION OF IMPRESSMENT INCREASE
Since the AASHO road tests we know that the impressments of pavement
increase proportionally with the fourth power of axle load. So we can value the
multiplication factors of different axle load vehicles in the traffic in this way:
For solo axle (s):
For tandem axle (t):
 T 
log  ei  = 0.02680  Ti -100    i 
 100 
4
log  ei  = 0.01493  Ti -175
n
EALF =  ei
(2.1)
(2.2)
(2.3)
i=1
where:
EALF = Equivalent Axle Load Factor
ei = equivalent load factor of the axle i. at the given truck
Ti = axle load of the axle i. [kN]
n = number of axles
According to this a 165 kN total weighted two axel truck’s multiplication
factor is this, if on the first axle there’s 65 kN on the back axle there’s 100 kN
load:
2
EALF =  ei =1 + 0.115 =1.115
i=1
On this principal - passing of this truck on the road means 1.115 times
bigger impressments for the structure than a 100 kN vehicle’s. So we can count
how much bigger impressments cause for the pavement these allowed 13-15
percent axle load increase [7].
2
We suppose during the counting, that the transporters will take all
advantage of opportunity because in that way they can decrease their specific
and total costs and they can have bigger benefit than before. The impressments
of pavement and the measure of damage we can examine in two typical case:
1. two axle truck
2. and four axle semi trailer
On the principal of analysis’ result we can say, that compare to the
situation before the direction +110-140 percent traffic growing can be waited for
if the transporters take total advantage of opportunities [6] [7]. (Here we did not
observe that fact, that whit the grown axle loan the same goods quantity needs
less turn with trucks.)
The ratio of vehicles’ own weight and profitable load is more favourable by
heavy trucks than cars (car 2:1, small- and medium trucks 1:1, heavy vehicle
1:1.5), so with total weight growing the part of profitable load is increase [1].
350
Traffic increase t% (%)
300
(a) two axle truck
250
(b) four axle semi trailer
200
150
100
50
0
0
Figure 2 Axle load of an average truck and a
semi trailer
5
10
15
20
Axle load increase (%)
25
30
Figure 3 Traffic increase in function of axle
load increase
Tandem axle
(t)
Case
Driving axle (s)
Not Driving axle (s)
Total (EALF)
(a)b before
100 [kN]
65 [kN]
165 [kN]
eb
1.000
0.115
1.115
(a)a after
115 [kN]
65 [kN]
180 [kN]
ea
2.523
0.115
2.638
(b)b before
100 [kN]
85 [kN]
140 [kN]
325 [kN]
eb
1.000
0.396
0.288
1.6840
(b)a after
115 [kN]
85 [kN]
160 [kN]
360 [kN]
ea
2.523
0.396
0.581
3.500
Increase
+136.6%
+107.8%
b –before new law, a –after new law
Table 1 Bearing force increase in consequence of enabling larger maximum axle load
3
By the (a) type truck we suppose 85 kN own weight and 80 kN full service
load, this is equal with a MAZ type truck. By the (b) type semi trailer we suppose
130 kN own weight and 195 kN full service load. The measure of the traffic we
can count with the next correlation.
Q
qb
Q
 EALFa
qa
Traffic before the axle load grew with 15 percent:
b
F100
 EALFb
(2.4)
Traffic after the axle load grew 15 percent:
a
F100
(2.5)
where:
Q = the weight of deliverable wood capacity during the examined
period a (1 m3 ≈ 10 kN)
EALFb = effect of one turn to the 100 kN standard axle load (before)
EALFa = effect of one turn to the 100 kN standard axle load (after)
qb = full service load (before)
qa = full service load (after)
After reduction and basis on the previous correlation the expectable traffic
growing is the next.
t% =
EALFaq b
EALFbq a
Further we generally suppose that the tonnage changing of all type vehicle
category linear proportionally grows with the ratio of the biggest allowed axle
load. (100/115=0.85)
t % = 0.85
EALFa
EALFb
Accepting reduction above the 15 percent increase of allowed axle load
cause by the (a) type truck 2 times bigger by the (b) type truck 1.75 times bigger
traffic growing.
3. VALUATION OF PLANED SHORTEN LIFETIME
It is known by everyone that the pavement can be damaged in different ways.
From these ways the failure of the bearing capacity is only one opportunity.
Therewith the formation of wheel-track, the inequality of the pavement’s surface,
the road become slimy or the ragged of levels are the facts which need very fast
interference. This damaging ways are in very close contact with the growing axle
load [4].
According to Heukelom and Klomp in case of replicant loads allowable
vertical direction voltage of the soil can be counted in the following way:
4
σz =
0.006  Edin
1 + 0.7  lgN
where:
σ z = allowable vertical direction voltage
Edin = the Young-modulus of the soil
N = the number of the load recurrence
This correlation means, that the allowable voltage of the soil is linear
proportional whit its dynamic modulus and reversed proportional whit the
logarithm of load recurrence [3]. This means that in this case the load is marked
by the number of allowable load recurrence and the incurvation is only an
additional data beside this. So the changing of load can be correlated with the
traffic by the results of AASHO road tests.
In case of the longitudinal wave between the measure of axle load and the
speed of straining we can suppose linear contact – basis on Fi Istán research. The
appearing of maltha mortar on the road’s surface is the main reason of the road’s
sliminess. This effect is because of the trucks which are used in the carriage in
forests. So the increase of axle load is linear proportional with the road’s
sliminess. The waste of pavement – the expectable specific waste value in the
wheel-track – can be in contact with the crossing heavy traffic with a linear
correlation [KÖTUKI]:
 B 
k b = 0.1 + 2.3 10-6  F100  1- r 
 2 
(3.2)
where:
kb = specific waste of pavement in the inboard wheel-track
[mm/year]
F100 = the traffic of the road-section represent in 100 kN standard
axle load
Br = the relative maltha content of the asphalt’s waste level
material
The correlation factor of the consistence is r=0.810. So we can suppose
linear correlation between the waste of pavement and traffic. Summarized we
can tell, that the decrease of load is the fourth power, and the other road
damaging ways are in linear correlation with the crossing vehicle’s axle load [4].
When a new flexible track structure is measured its thickness can be
determined with the traffic and the soil’s load ability. For example the (a) type
truck: if it has to deliver 6000 m3 and the soils load ability is CBR 5%, and the
planed lifetime is 20 years, then the track structure’s thickness is 33.8 ecm. If the
axle loads is increased with 15% to reach the previous impressments it’s enough
less load replicant, which is proportianable with EALFb/EALFa = 0.43, so 43%
less turns are enough for damaging a 33.8 ecm thickness pavement. Decreasing
of planed lifetime can be valued with the following correlation:
5
LTa =
1
 LTb
t%
(3.3)
where:
t % = the expectable traffic increase
LTa = the lifetime after increased traffic
LTb = the expectable lifetime if track structure
The decrease of lifetime depends on for how big traffic the track structure
was measured, and the what kind of trucks the carriage is transacted. The size of
the carriage is the same by both trucks, so the determination of the traffic
depends only on the technical conditions. Two trucks with two different axle load
repartition can be counted in 2 on the fourth power variation.
t%
(a)a
(a)b
(b)a
(b)b
(a)a
1.0
2.0
0.62
1.09
(a)b
0.5
1.0
0.31
0.55
(b)a
1.61
3.22
1.0
1.76
(b)b
0.92
1.82
0.57
1.0
Table 2 Expectable traffic changing t% (%)
Lifetime decreasing (LTa)
1
t%
Planed lifetime (LTb)
25 year
20 year
15 year
10 year
0,85
3.75
3.00
2.25
1.50
0,80
5.00
4.00
3.00
2.00
0,75
6.25
5.00
3.75
2.50
0,70
7.50
6.00
4.50
3.00
0,65
8.75
7.00
5.25
3.50
0,60
10.00
8.00
6.00
4.00
0,55
11.25
9.00
6.75
4.50
0,50
12.50
10.00
7.50
5.00
Table 3 Expectable lifetime decreases
We examine only that variations which cause lifetime decrease. The
decrease of load ability is only one reason for damaging track structure, so the
lower limit of lifetime decrease is 0.85, the upper limit is 0.5. We mustn’t forget,
that this results valid only beside average traffic development, in real life the
deliverable wood quantity splits not consistently. It appears somewhere with
lower somewhere with bigger intensity. This thing is typical in forest delivering,
and it abrogates the measure of lifetime decrease.
6
Wood capacity [m3]
Truck
Passableness
The condition of track structure’s
pavement is in close contact with the costs
and the phase of decay progress. Because
of this aspect of the appraisement jobs it’s
not indifferent what kind of parameters
are chosen to describe the condition of the
road. There’s no way for objective
measuring in every quality of the forest
roads by the track structure parameters
which can be measured difficultly a
subjective measuring number can be used.
This number gives information about
passableness according to the users with
regard to the inequality, getting ribs,
formation of wheel-track, waste of surface,
puddles, burstings and the condition of
pavement’s borders.
The effect of the increasing axle
load can be examined by the following
analyse method (4. figure):
Bearing capacity
4. MAINTENANCE JOBS IN A PAVEMENT MANAGEMENT
SYSTEM
Homogeny s.
Traffic
MATRIX OF DECISION
Optimalization
malizálás
RESULT
Figure 4 Progress of analysis
Analyse steps:
1.
2.
3.
4.
5.
6.
7.
8.
Determine the element of road network (network contact)
Determine the gravitate capacity to the road
Count over the data of wood quantity to the traffic
Measuring the condition of the track structure
a.) Determine the load with Benkelman’s beam
b.) Determine the passableness (subjective appreciation)
Separate the homogeny sections
Make decision about the way of interference
Determine the order of interference way
Optimalization, appraisement of the results
In this test the load and the mark of the pavement’s surface maintain is
important. The load of track structure shows the condition of all stratum and
agriculture. The maintain if pavement shows the quality of the upper stratum.
The two marks can be different from each other. The load is with the future the
passableness is with the present in a very close contact.
The passableness can get marks among 1-5 (1 is the new, 5 is the ruined) It
can be used for further appraisement. The passableness shows how urgent the
interference is. The size of the elastic form changing – which develops because of
the load – can be used for describing the track structure’s load. The urgency and
the time of the interference can be determine with the development of the traffic
7
Urgency of Passableness
and with the load of the roads. The following maintenance and repairing ways
can be chosen by the road manager:
Urgency of Load
Determine urgency
0
1
2
3
0
R(0)
R(0)
O(1)
O(2)
0
Excellent condition, doesn’t need interference
1
U(1)
U(2)
O(2)
O(3)
1
Interference urgency is accidental
2
U(2)
U(3)
O(3)
O(3)
2
Warning territory
3
U(3)
U(3)
O(3)
O(3)
3
Interference is needed immediately
Table 4 Matrix of Decision [5]



Table 5 Determine the urgency without
stative parameters [5]
(R) Repairing: the local damage is mended to prevent their
degeneration.
(U) Upkeep: in a longer road section we would like to get unific
technical condition to slow down the damage.
(O) Overhaul: every parameters of the road must be get as a new
condition. It’s like building something. It has to be done when the main
part of the road is damaged.
The decision can be made with the decision matrix. It consist if the optimal
variations of the profitable interferences which conform to the load and subjective
condition (Table 4). With this analyse system can be made the valuation the
effect of the increasing allowed axle load to the costs.
In the example the length of the road network was 201.1 km we separate
62 homogeny section according to the passbleness. The traffic analysis was done
for 15 years separate for 3 times 5 years. In this time 3.064.587 m3 delivered
wood loaded the network. For each type of trucks the analyse model was done.
The 6th table contains the results. At the half of the road network the increase of
the axle load didn’t do any kind of lifetime decrease. Either the load was good or
the traffic was low. At the (a) truck the lifetime decrease with 15% at the (b)
truck with 100% in the whole network. So the most probable value of the is the
0.85 which is the same with the axle load increase proportion (100/115=0.85). It
depends on the network load and on the traffic resolve.
At the (a) type truck the renewal cost increased with ~15 % at the (b) with
180%. So the tandem axle truck is more sensitive for changing axle load. But the
renewal costs are almost the same but the (b) truck need 3 times more turns to
carry the wood, and the number of the turns is in a very close correlation with
the delivering costs.
8
Timber
[m3]
Type
Distribution of suggested interferences on the network
R(0)
U(1)
U(2)
U(3)
O(1)
O(2)
O(3)
km
db
km
db
km
db
km
db
km
db
km
db
km
db
(a)b Truck
2292912
2,0
1
17,0
7
90,8
29
18,4
7
0,0
0
0,0
0
72,9
18
(a)a Truck
1958831
2,0
1
17,0
7
72,6
21
25,6
12
0,0
0
0,0
0
83,9
21
(b)b Truck
2521084
2,0
1
17,0
7
92,9
31
61,6
17
0,0
0
0,0
0
27,6
6
(b)a Truck
2274286
2,0
1
17,0
7
90,8
29
14,4
6
0,0
0
0,0
0
76,9
19
Table 6 The suggested interferences and the delivered wood quantity which depend on the
applied truck
5. SUMMARY
That truck is the best for carriage, which has the less costs. It means: Every
network has an optimal axle load resolve and axle arrange, and with these
optimal thing the carriage can be solve with minimal costs.
Beside deliberate pavement management the condition of network increase
fluently in a bigger bearing capacity road bigger burden can be delivered so the
cost of carriage decrease and the law of volume proceeds succeed. So we can
determine a optimal truck type for every road network – it depends on the road’s
conditions (Figure 5). And this is very important for forest management, because
they can plan what kind of trucks most be used in delivering.
Figure 5 Synthesis diagram
9
6. REFERENCES
[1]
Ányos András:. Mezőgazdasági utak
Mezőgazdasági Kiadó, Budapest, 1984
építése
és
fenntartása.
[2]
Boromisza
Tibor:
Hajlékony
burkolatok
élettartalma.
Mélyépítéstudományi Szemle, XV. évf. 7. szám. 340-344. old.
[3]
Boromisza Tibor: Aszfaltburkolatú utak teherbírásának vizsgálata
behajlásméréssel. Mélyépítéstudományi Szemle, XXVI. évf. 12. szám.
521-528. old.
[4]
Gáspár László: Útállapot-javítás korlátozott anyagi lehetőségek
mellett. Közlekedéstudományi Szemle, XXXVII. évf. 9. szám. 414-420.
old.
[5]
Kosztka Miklós: Erdei feltáróhálózat építése és fenntartása. Kézirat,
EFE Jegyzetsokszorosító, Sopron, 1990
[6]
Primusz Péter: Tehergépkocsik tengelysúly növekedésének hatása az
erdészeti utak pályaszerkezetére és a pályaszerkezet-gazdálkodására.
Diplomamunka, Sopron, 2006
[7]
Timár András: A megengedett legnagyobb tengelysüly 11,5 tonnára
növelésének hatásai. Közúti és Mélyépítési Szemle, LV. évf. 4. szám.
2-11. old.
Authors address:
Péter Primusz, MSc.
Department of Forest Opening Up and Hydrology,
Institute of Geomatics and Civil Engineering,
University of West Hungary, Bajcsy-Zs. u. 4, Sopron,
H-9400, Hungary
10
E-mail: [email protected]