Dynamic Axle Loads Research Articles

Mitigation of Railway-Induced Ground Vibration by Soft Support Elements and a Higher Bending Stiffness of the Track

The mitigation of train-induced ground vibrations by track solutions is investigated by calculations and measurements. The calculation by a wavenumber domain method includes the correct vehicle–track interaction and the correct track–soil interaction. Some theoretical results for elastic elements and an increased bending stiffness of the track are presented where the force transfer of the track and the vehicle–track interaction are calculated for the high-frequency dynamic mitigation, and the force distribution along the track is calculated for the low-frequency mitigation which is due to the smoother impulses from the passing static loads. Measurement results for the ground vibration near isolated and un-isolated tracks are given for several under-sleeper pads, for under-ballast mats, and for several under-ballast plates and ballast troughs. The elastic elements yield a resonance frequency of the vehicle–track–soil system and a high-frequency reduction of the dynamic axle loads which depends mainly on the softness of the pads or mats and which can be improved by a higher sleeper mass. In addition, all troughs and most of the soft elements show a low-frequency reduction which is attributed to the scattered impulses of the static axle loads. Besides this main contribution of the article, the problem of a soft reference section on a different soil is discussed and recommendations for better ground vibration measurements of mitigation effects are given.

Dynamic Axle Load Effects on High-speed Railway Embankment: Pore Pressure and Deformation in Varied Subsoils

Dynamic Axle Load Effects on High-speed Railway Embankment: Pore Pressure and Deformation in Varied Subsoils

Dynamic Response Analysis of JPCP with Different Roughness Levels under Moving Axle Load Using a Numerical Methodology

In-service Portland cement concrete (PCC) pavements are subject to repeated dynamic loads from moving vehicles; thus, the actual stress generated in a PCC pavement may significantly differ from the static stress, which is normally used in the design and evaluation of pavement performance. Calculating the stress in PCC pavements under moving vehicle loads is of importance to assess their actual service condition, particularly for pavements with different surface roughness levels as the deteriorated roughness might cause large stress in PCC pavement subject to dynamic loads. In this paper, a method is proposed to compute the dynamic response in terms of loads and stresses generated in jointed plain concrete pavements (JPCPs) under a moving axle load, considering the effects of the pavement surface roughness, the vehicle parameters (including vehicle speeds and axle weights), and the pavement structure parameters (including thickness and elastic modulus of different layers and the existence of dowel bars). The dynamic axle load is firstly generated based on the quarter-car model, running through three successive slabs of which the surface roughness is determined by the power spectral density method, and the critical locations in slabs where the largest tensile stresses occur are identified. The combined effects of various pavement surface roughness levels, vehicle speeds, axle weights, and pavement structure parameters are evaluated in terms of the stress and the dynamic factor defined as the ratio of the tensile stress under dynamic load to the tensile stress under static load. For the roughness level D, the tensile stress can reach a maximum value of 3.13 MPa, and the dynamic factor can reach a maximum value of 2.46, which is much larger than the dynamic factor of 1.15 or 1.2 currently used in design guidebooks. Increasing the thicknesses of pavement slab or the subbase layer is an effective way to reduce the tensile stress in JPCP, while increasing the thickness of base layer is not effective. The results of this study can benefit future pavement design and pavement performance evaluation by providing the actual stress and the useful dynamic factor values for various conditions of field pavements. Moreover, preventive maintenance, particularly the improvement of pavement surface roughness, can be planned by referring to the results of this study, to avoid large tensile stress generated in JPCPs.

Analysis of Dynamic Load Characteristics of Accelerated Pavement Testing Equipment Based on Virtual Prototype Model

The purpose of this paper is to study the actual dynamic load characteristics of a full-scale Accelerated Pavement Test (APT) device called Natural Environment-Automatically Loaded Track (NE-ALT) during its operation. The NEALT uses hydraulic and support reaction forces to apply axle loads, which are somewhat different from real trucks. Therefore, in order to ensure the accuracy of the loading parameters of the device, it is necessary to analyze the dynamic load characteristics of the device during operation. In this paper, a virtual prototype model of the device was established, and the important parameters, including vehicle speed and axle load, were set. The dynamic axle load, dynamic load coefficient, and influential factors of the NE-ALT were analyzed using the model at different speeds, hydraulic pressures, and road roughness. The results have shown that the dynamic axle load accuracy was most affected by speed, followed by road roughness, and then hydraulic cylinder pressure. Compared with the real truck, its dynamic load stability was better than the real truck due to the restriction of the guide rail in the acceleration loading system and the method of hydraulic loading, and the larger the load, the more stable the load, which was different from the real truck. Therefore, in the design of accelerated pavement loading experiments, the dynamic axle load characteristics of equipment need to be considered. The results of this study can provide guidance for the further improvement and application of the NE-ALT.

The influence of model assumptions in a hybrid prediction tool for railway induced vibration

Within the SILVARSTAR project, a user-friendly frequency-based hybrid prediction tool is developed to assess the environmental impact of railway induced vibration. This will be implemented in the existing noise mapping software IMMI. The vibration level in a building in each frequency band is expressed as the product of source, propagation and receiver terms. A hybrid approach is used that combines experimental data with numerical predictions, providing increased flexibility and applicability. The train and track properties can be selected from a database or as numerical values. The user can select soil impedance and transfer functions from a database, pre-computed for a wide range of parameters with the MOTIV and TRAFFIC models. An experimental database of force densities, transfer functions, free field vibration and input parameters is also integrated into the new tool. The building response is estimated by means of empirical correction factors. Assumptions within the modelling approach can influence the prediction accuracy and the present paper aims to quantify these. We focus on the influence of train speed and soil properties on the compliance of the track-soil system, the dynamic axle loads, and the free field response, as well as on the load transfer between track and soil.

Mechanistic–Empirical Analysis of Pavement Performance Considering Dynamic Axle Load Spectra Due to Longitudinal Unevenness

Pavement distresses are induced by mechanistic responses in pavement structure subjected to dynamic loads of moving vehicles. Pavement surface evenness deteriorates as pavement distresses propagate, which results in dynamic axle loads and faster pavement deterioration. It is vital to consider the dynamic axle load spectra to predict pavement deterioration using traffic-monitoring data. This study aimed to evaluate the effect of dynamic loads and overweight traffic on asphalt pavement overlay performance using mechanistic–empirical (M–E) pavement analysis. The relationship between dynamic load coefficients (DLCs), axle loads, and international roughness index (IRI) was obtained for accurate quantification of dynamic axle loads. Then the dynamic axle load spectra were derived by shifting the static axle load spectra in weigh-in-motion (WIM) data, given the DLC value. AASHTOWare Pavement ME software was used to analyze pavement performance with static and dynamic axle load spectra, and the impact of overweight traffic on asphalt pavement overlay performance. The impact of dynamic loads on reflective fatigue cracking was distinguished at an early stage of the service period and eliminated after the 10-year analysis period, when the propagation of reflective cracking reached a specific level. On the other hand, the consideration of dynamic axle loads increased the impact of overweight truck traffic on pavement distresses, and pavement structures of major highways tend to be more sensitive to overweight traffic because of greater DLC excitement at higher operational speeds.

Hydrodynamics analysis and coordinated control method of anti-lock brake based on dynamic axle load

Hydrodynamics analysis and coordinated control method of anti-lock brake based on dynamic axle load

Prediction of Specific Fuel Consumption of 60 HP 2WD Tractor Using Artificial Neural Networks

In this study, specific fuel consumption was determined at different axle load, tire pressure and drawbar force for a 60 HP tractor. In addition, the results were also estimated with the help of Artificial Neural Networks (ANN), which is one of the machine learning methods. The testings were carried out on the Tractor Draft Test Track. In the study; three different drive tire inner pressures (P) (160 kPa, 120 kPa and 80 kPa), four different dynamic axle loads (W) (1796 daN, 2076 daN, 2276 daN, 2476 daN) and four different traction forces (500 daN,1000 daN, 1500 daN, 2000 daN) were tested. Specific fuel consump-tion values varied between 290.7-542.1 g/kWh depending on the draft force in the testings Despite the 38% increase in the axle load, a 3.5% decrease occurred in the specific fuel consumption values. Specific fuel consumption values in-creased when increased tire inner pressure. Specific fuel consumption in-creased by 1.03% when a 100% increase in tire pressure. In ANN, the most suc-cessful model was determined by trying different training algorithms, transfer functions and the number of neurons in the hidden layer. In the most successful network model, MAE, RMSE values for the prediction of specific fuel consump-tion were found to be 0.005331, 0.007551 respectively.

Railway crossing vertical vibration response prediction using a data-driven neuro-fuzzy model – Influence of train factors

This paper provides a data-driven model of the vibration response of a railway crossing during vehicle passages. Many of the features of trains passing through instrumented crossing are extracted from measured data. Based on the feature selection process, speed, dynamic axle load and the number of wagons are found proper inputs in the prediction model. Train-crossing interaction response at a crossing due to passing trains is modeled from a data-driven Neuro-Fuzzy soft computing approach. Locally Linear Model Tree (LOLIMOT) is applied to predict the crossing nose acceleration. The model comparison against measurements shows that the ability to predict the extrapolation cases at off-range speeds has satisfactory compatibility. The monitored passing trains are ranked based on the LOLIMOT input space dimension cuts and extrapolation of the model up to higher train speeds. The influence of train factors (i.e. speed, dynamic axle load, number of wagons) on crossing response is demonstrated. Also, based on the analysis results, it is concluded that with a steady increase in train speeds, some trains show a greater amplification in vibration response than others. The results can be applied in data processing in the crossing vibration monitoring and detection of trains with crossing impact sensitive to speed increasing that can lead to proper operation policies to reduce damages and maintenance costs.

Sensor Data Fusion in Multi-Sensor Weigh-In-Motion Systems.

In this paper, we present the results of a comparison of two estimators of the gross vehicle weight (GVW) and the static load of individual axles of vehicles. The estimators were used to process measurement data derived from Multi-Sensor Weigh-In-Motion systems (MS-WIM). The term estimator is understood as an algorithm according to which the dynamic axle load measurement results are processed in order to determine the static load. The result obtained is called static load estimate. As a measure of measurement uncertainty, we adopted the standard deviation of the static load estimate. The mean value and the maximum likelihood estimators were compared. Studies were conducted using simulation methods based on synthetic data and experimental data obtained from a WIM system equipped with 16 lines of polymer axle load sensors. We have shown a substantially lower uncertainty of estimates determined using the maximum likelihood estimator. The results obtained have considerable practical significance, particularly during long-term usage of multi-sensor WIM systems.

Numerical investigation of the fatigue performance of elastic rail clips considering rail corrugation and dynamic axle load

To analyze the reasons for rail clip fracture, the characteristics of rail corrugation were first measured using a rail corrugation meter. The vibration acceleration of the fastener clips at the sections with/without rail corrugation was measured, and the effects of rail corrugation on the clip vibration were analyzed. After this, a vehicle--track coupling dynamic model and a refined model for the fastener system were established in order to study the effects of rail corrugation on the vibration acceleration and stress on critical points. Finally, the rail grinding limits were determined based on the fatigue analysis method and the damage accumulation theory from the aspect of the fatigue life of the clip. The results of the study showed that the main wavelength of rail corrugation at the rail clip fracture section was approximately 40 mm. The vibration acceleration of the clip caused by rail corrugation was too large. Under normal installation conditions, the maximum clip stress was 1490 MPa at the small circular arc on the rear arch, which was identical to the on-site fracture location. The intrinsic frequency of the clip was approximately 810 Hz. Rail corrugation excited and triggered the forced vibration of the clip, and induced resonance at a speed of 120 km/h and a wavelength of 40 mm. The large cyclic stress amplitude of the clip with rail corrugation increased from 44 MPa to 68 MPa when compared with the clip without rail corrugation. Rail clip fracture was caused by the naturally occurring resonance fatigue arising from rail corrugation. For metro lines designed with a maximum speed of 120 km/h, it was suggested to control the rail corrugation amplitudes with a wavelength of 40 mm, 50 mm, 30 mm, 120 mm and 160 mm to below 0.04, 0.08, 0.16, 0.19 and 0.2 mm, respectively, taking into account the fatigue life of the clip.

The influence of the cargo weight and its position on the braking characteristics of light commercial vehicles

AbstractThe influence of the cargo weight loaded on the vehicle and the total gross mass of the vehicle on the braking characteristics is often researched from the road safety reason. However, there is not enough knowledge about the influence of weight and load distribution on the loading area of small trucks or vans on their braking characteristics. This article presents the results of measurements of braking decelerations of the van of N1 category and the braking characteristics of a vehicle loaded with different cargo mass with different cargo locations on the loading area. The impact of the longitudinal cargo position on the loading area on the load of the individual axles and thus on the braking deceleration of the vehicle was investigated. The influence of the height of the center of gravity on the dynamic axle load during braking was also determined. Method of direct vehicle deceleration measurement was used by a decelerometer. There were calculated cargo weight and cargo position influences on the dynamic axle load during braking according to the vehicle deceleration.

Brake force distributions optimised with regard to energy recovery for electric vehicles with single front‐wheel drive or rear‐wheel drive

Energy recovery by means of braking with the electric machine helps to extend the cruising range of electric vehicles. By optimising the recuperation system, the total energy efficiency is increased. In general, using a usual brake force distribution the capability for recuperation is not equal for every type of drive train. Usually, four-wheel drives are advantageous in comparison to drive trains with only one driven axle. Regarding the single drives, generally, a front-wheel drive provides a higher capability for recuperation than a rear-wheel drive. This is mainly due to the dynamic axle load shift, which occurs during decelerations. In order to increase the energy recovery of electric vehicles with single drive, an adaptive brake force distribution is presented and compared with other brake force distributions in this study. It uses the knowledge of the currently available adhesion coefficient between tyre and road. The positive effect on the recuperation without impairing the braking performance on a straight road is demonstrated based on simulations. In curves, the lateral forces additionally need to be considered to guarantee the stability of the vehicle, especially relating to electric vehicles having a rear-wheel drive.

Consideration of dynamic loads in the determination of axle load spectra for pavement design

Axle load spectra constitute a crucial part of the data for pavement design and pavement distress analysis. Typically, axle load spectra represent static load from vehicles and do not include dynamic loads generated by vehicles in motion. While dynamic loads can significantly contribute to faster pavement distress, this fact is mostly omitted in pavement design methods. The paper presents a methodology for consideration of dynamic loads in axle load spectra for mechanistic-empirical pavement design. Calculations of dynamic axle load spectra for pavements of various evenness (expressed by IRI) and various vehicle speeds were performed and discussed. The effect of dynamic axle load spectra on pavement performance was analysed. M-EPDG calculations performed for three selected flexible pavements show that dynamic loads have a minor effect on pavement performance if the pavement is smooth and IRI is close to 1.0 mm/m. The detrimental effects of dynamic axle loads increase rapidly with the pavement evenness deterioration, resulting in faster (up to 25%) development of pavement distresses for IRI = 4.0 mm/m and a vehicle speed of 60 km/h. The analysis proved that thinner pavement structures are more sensitive to dynamic loads than thicker pavement structures. The investigation of vehicle speed impact on vehicle dynamic loads and pavement performance showed that at low vehicle speed (30 km/h) dynamic loads have a minor effect and pavement distress results mostly from a decrease in stiffness modulus of asphalt mixture and increase in permanent deformations, while for vehicle speeds higher than 90 km/h dynamic loads significantly contribute to pavement distress and adverse dynamic effects are not compensated by an increase in stiffness modulus of asphalt mixtures. The results also emphasise the significance of proper pavement evenness maintenance, especially on high speed motorways.

A Mathematical Model to Evaluate the Impact of the Maintenance Strategy on the Service Life of Flexible Pavements

The structural failure of a flexible pavement occurs when the accumulated fatigue damage produced by all the vehicles that have passed over each section exceeds a certain threshold. For this reason, the service life of pavement can be predicted in terms of the damage caused by the passage of a single standard axle and the expected evolution of traffic intensity (measured in equivalent standard axles) over time. In turn, the damage caused by the passage of an axle depends on the vertical load exerted by the wheels on the pavement surface, as given by the technical standard in application, and the depths and mechanical characteristics of the layers that compose the pavement section. In all standards currently in application, the unevenness of the road surface is disregarded. Therefore, no dynamic effects are taken into consideration and the vertical load is simply given in terms of the static weight carried by the standard axle. However, it is obvious that the road profile deteriorates over time, and it has been shown that the increase in the pavement roughness, when considered, gives rise to important dynamic effects that may lead to a dramatic fall in the expected structural service life. In this paper, we present a mathematical formulation for the fatigue analysis of flexible pavements that includes the effects of dynamic axle loading. A pavement deterioration model simulates the sustained growth of the IRI (International Roughness Index) over time. Time is discretized in successive time steps. For each time step, a road surface generation model provides a profile that renders the adequate value of the IRI. A QHV (Quarter Heavy Vehicle) model provides the dynamic amplification function for the loads exerted on the road surface along a virtual ride. This function is conveniently averaged, what gives the value of the so-called effective dynamic load amplification factor (DLA); this is the ratio between the effective dynamic loading and the static loading at each time step. Finally, the damage caused by the passage of the standard axle can be evaluated in terms of the dynamic loading. The product of this damage times the number of equivalent standard axles gives the total fatigue damage produced in the time step. The accumulated fatigue damage at each moment is easily computed by just adding up the damage produced in all the previous time steps. The formulation has been implemented in the software DMSA (Dynamic & Maintenance Simulation App). This tool has been specifically developed for the evaluation of projects in applications for financing submitted to the European Investment Bank (EIB). DMSA allows for quantifying the expected structural service life of the pavement taking into account both the rise of the dynamic axle loads exerted by the traffic as the road profile deteriorates over time and the different preventive maintenance strategies to be taken into consideration.

Determination of dynamic axle load using suspension deflection method for the load distribution optimisation of multi-axle vehicles

Identification of dynamic axle loads in multiple axle vehicles requires complex calculation methods because of its hyper static solving necessity. In this study, suspension deflection method is proposed to determine the dynamic axle loads for optimisation of load distribution of a multi-axle vehicle having more than two axles. The determination of the dynamic axle loads is performed for driving conditions with a climbing angle and a longitudinal acceleration to optimise the loads at the axles of the vehicle using suspension deflection method. General equations and calculation methodology are presented for a multi-axle vehicle and a numerical example is implemented using the suspension deflection method for a four-axle vehicle as a case study. Finally, it is shown that the suspension deflection method is more simple and useful than other approaches to define the dynamic axle loads for an optimisation study of the vehicles which have multiple axles.

Determination of dynamic axle load using suspension deflection method for the load distribution optimisation of multi-axle vehicles

Identification of dynamic axle loads in multiple axle vehicles requires complex calculation methods because of its hyper static solving necessity. In this study, suspension deflection method is proposed to determine the dynamic axle loads for optimisation of load distribution of a multi-axle vehicle having more than two axles. The determination of the dynamic axle loads is performed for driving conditions with a climbing angle and a longitudinal acceleration to optimise the loads at the axles of the vehicle using suspension deflection method. General equations and calculation methodology are presented for a multi-axle vehicle and a numerical example is implemented using the suspension deflection method for a four-axle vehicle as a case study. Finally, it is shown that the suspension deflection method is more simple and useful than other approaches to define the dynamic axle loads for an optimisation study of the vehicles which have multiple axles.

A Parametric Study of Jointed Plain Concrete Pavement Using Finite Element Modeling

Concrete pavements face various types of distresses such as longitudinal, transverse, and joint cracking due to traffic loading and thermal stresses. The objective of this investigation was to develop Three-Dimensional Finite-Element Models (3D-FEM) to assess the performance of dowel in Jointed Plain Concrete Pavement (JPCP).Finite-element modeling is a powerful tool that can be used for the simulation of the structural response of pavements under the effects of different loading condition. Most of the previous studies ignored important factors, including the combined effect of dynamic axle loads and thermal gradient. Overcoming the shortcomings of the previous studies, this study investigated the pavement response under the effect of some model parameters. The result of the study was verified by a comparison with field measurements. Results also showed that the combined negative gradient and axle loads located at the transverse joint subject the top of mid-slab, to high tensile stress that may explain the initiation of top-down cracks. These stresses increase under corner loading when the slab length is increased. In general, the study presented that the developed 3D-FEM is suitable for identifying the effect of different design features including pavement geometry, material properties, thermal gradients, and axle load and configuration on the structural response of rigid pavements.

A study of modelling simplifications in ground vibration predictions for railway traffic at grade

Accurate computational models are required to predict ground-borne vibration due to railway traffic. Such models generally require a substantial computational effort. Therefore, much research has focused on developing computationally efficient methods, by either exploiting the regularity of the problem geometry in the direction along the track or assuming a simplified track structure. This paper investigates the modelling errors caused by commonly made simplifications of the track geometry. A case study is presented investigating a ballasted track in an excavation. The soil underneath the ballast is stiffened by a lime treatment. First, periodic track models with different cross sections are analyzed, revealing that a prediction of the rail receptance only requires an accurate representation of the soil layering directly underneath the ballast. A much more detailed representation of the cross sectional geometry is required, however, to calculate vibration transfer from track to free field. Second, simplifications in the longitudinal track direction are investigated by comparing 2.5D and periodic track models. This comparison shows that the 2.5D model slightly overestimates the track stiffness, while the transfer functions between track and free field are well predicted. Using a 2.5D model to predict the response during a train passage leads to an overestimation of both train-track interaction forces and free field vibrations. A combined periodic/2.5D approach is therefore proposed in this paper. First, the dynamic axle loads are computed by solving the train-track interaction problem with a periodic model. Next, the vibration transfer to the free field is computed with a 2.5D model. This combined periodic/2.5D approach only introduces small modelling errors compared to an approach in which a periodic model is used in both steps, while significantly reducing the computational cost.

Effects of Some Properties of Drive Tires Used in Horticultural Tractors on Tractive Performance

Many studies on tractive performance of tractor tires have been carried out to solve soil-wheel interaction problems in the last decades. The purpose of this study is to experimentally determine effects on tractive performance of radial and bias-ply drive tires at three different tire lug heights, axle loads and inflation pressures. The experiments were carried out in stubble field conditions. To obtain sufficient performance data, a new single wheel tester was designed and manufactured. Travel reduction, net traction ratio and tractive efficiency varied from 3.3% to 34.1%, 0.24 to 0.93 and from 0.27 to 0.78 respectively depending on drawbar pull. The effects of tire type, lug height, dynamic axle load and inflation pressure on tractive efficiency were found significant (P<0.01) by the performed variance analysis and LSD tests. Radial tires provide better tractive performance compared with bias-ply tires. The tractive efficiency increased especially with increasing dynamic axle load and decreased with increasing tire inflation pressure. Tire dynamic axle load was the major contributory factor on tractive performance as compared with other independent variables. For a given drawbar pull, it was observed that tractive efficiency of radial tire can be maximized by selecting appropriate levels of lug height, dynamic axle load and inflation pressure.