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Axle Load Data Analysis And Its Distribution

ABSTRACT

In this project we investigated how distribution of gross weight of the truck among different axle occur as axle load distribution help in pavement design methodologies. First we taken set of axles load data of 371 vehicles and do its analysis by finding frequency distribution of all type of axle which data we had. With help of percentage of load distribution and load spectrum rigid pavement is design according to IRC:58 and according to the actual load distribution among axle and we found that the critical thickness of pavement slab is more in case of actual load distribution.

INTRODUCTION

Traffic data is most critical input for pavement design and it is associated with highest uncertainty. Designing a pavement requires total traffic volume, magnitude of axle load, tire pressure and speed of vehicle. According to IRC: 37-2012 the flexible pavement design guideline for Indian highways demand only two traffic input that is average annual daily traffic (AADT) Data and axle load data.

The axle load of a wheeled vehicle is the total weight bearing on the roadway for all wheels connected to a given axle. Axle load is an important design consideration in the engineering of roadways and railways, as both are designed to tolerate a maximum weight-per-axle (axle load); exceeding the maximum rated axle load will cause damage to the roadway or rail tracks.

In recent years, India has been making strides towards developing a robust mechanistic - empirical pavement design procedure.  Mechanistic Empirical Pavement Design (MEPD) has been developed to use the axle load spectra to represent the vehicle loads in pavement design. These spectra represent the percentage of the total axle applications within each load interval for single, tandem, tridem, and quad axles.

Problem Statement

The commercial vehicles are those carrying gross weight more than 3 tonnes. In general, most of the pavement design methodologies neglect the weight carried by steering axle and considers the load carried by the rear axles only. Further, several assumptions are made with respect to multi-axle trucks in terms load distribution. Hence there is a need to understand the distribution of gross weight of the truck among different set of axles. This will help in giving due considerations for the axle distribution in pavement design methodologies.

Methodology

In order to investigate the axle load distribution, past axle load data from two different  states Uttar Pradesh and Karnataka from India is taken. Data consist of different types of axle such as single, tandem, tridem etc. The frequency distribution is done to see load distribution on different axles and to see how the load is distributed on each axle of tandem, tridem axle.  Then determine the distribution of loads within the tandem and tridem axle and also assess the effect of steering axle weight on the cumulative fatigue damage of concrete pavements.

Comparison between Axle Load Distribution of both State

Distribution of load in all axle- We find relative frequency of axle for different range of load. The size of bin is take 2 tones and frequency distribution table is found which is shown on figure and with help of that bar graph is plotted. We can see from graph that they follow same path maximum number of load occur at 3-5 tones.

Distribution for Single Rear Axle- We find relative frequency of axle for different range of load. The size of bin is take 2 tones and frequency distribution table is found which is shown on Table and with help of that bar graph is plotted. It can be from figure that the trend of variation of percentage axle load is similar in both the states. In other words, the maximum percentage of trucks carry load in the range of 3-5 tones and later this percentage decreases with load.

 Distribution of Tandem Axle- We find relative frequency of axle for different range of load. The size of bin is take 5 tones and frequency distribution table is found which is shown on Table and with help of that bar graph is plotted. It can be seen from Figure that in both the states, the axle load distribution is similar. Further, the first axle of tandem axle carries more load compared to the second axle.

Distribution of Tridem Axle- We find relative frequency of axle for different range of load. The size of bin is take 5 tones and frequency distribution table is found which is shown on Table and with help of that bar graph is plotted. The figure shows that the first axle of tandem axle carries slight lower load compared to second and third axle, which almost carries similar percent of loads. 

Cumulative Fatigue Damage Analysis

For different trial slab thickness cumulative fatigue damage is calculate as per IRC 58 and by analysis load distribution on different axle which is shown in the plot the graph to compare both methods. We found out that critical thickness of slab is 272 mm and 274.9 mm when the rigid pavement is design as IRC 58 and as considering actual load distribution.

Conclusion

Steering axles should be considered in pavement design as most of axle load value is greater than 3 tones in both set of data.

Load Percentage distribution of  2nd axle show peak at 40-50% and 20-30% as there are vehicle with different number of vehicle and the distribution is also occurring according to number of axle similarly for 3rd axle which show peak at 30-40% for data Set-1 (UP) and Load Percentage distribution of 2nd axle show peak at 50-55% and 25-30% as there are vehicle with different number of vehicle and the distribution is also occurring according to number of axle similarly for 3rd axle which show peak at 45-50% and 30-35% for data Set-2 (Karnataka).

The data indicates that the     presence of multi-axle trucks are lower compared to the two axle and three     axle trucks. The two axle or three axle trucks are more damaging compared     to multi-axle trucks.

We     found out that critical thickness of slab is 272 mm and 274.9 mm when the     rigid pavement is design as IRC 58 and as considering actual load     distribution of axle respectively.