Number Of Axles Research Articles

Identification of external load information using distributed optical fiber sensors embedded in an existing road pavement

This paper describes field applications of distributed optical fiber sensors (DOFS) for monitoring the traffic load on an existing road. To investigate the optimal embedment depth for DOFS for pavement monitoring, a series of field tests was conducted by considering three embedment depths (10, 30, and 40 mm) and three moving loads (pedestrian, car and truck). The main objectives were to examine the performance of DOFS embedded in the pavement and investigate its suitability and sensitivity for obtaining information about moving loads at various depths from the road surface. Among the existing backscattering light technology, Rayleigh scattering-based Optical Frequency Domain Reflectometry (OFDR) was chosen in order to achieve a measurement of high-speed, high range, and good repeatability with a very high spatial resolution of 2.56 mm, all of which are necessary for monitoring dynamic responses due to moving loads. In addition, a data-processing method was developed based on a combination of a Hampel identifier and a low-pass filter, which proved to be effective in removing outliers and high-frequency noise from the raw measurement data, respectively. The results showed that it is not only possible to detect a moving load on a road, but that a wide range of information can also be obtained from the strains measured by DOFS, including the type of load, its speed, its weight, the number of axles, the axle spacings (in the case of a vehicle) and the traffic flow. With low maintenance costs, DOFS based on Rayleigh scattering OFDR could be used for collection of accurate and reliable traffic data when embedded in a pavement.

Dynamic response and parameter analysis on the vehicle–bridge coupling of cable-stayed bridge under over-limit transportation

PurposeOver-limit transportation has the characteristics of large axle load, large number of axles and lateral distribution width. Under the action of over-limit load, the coupling vibration effect of vehicle–bridge is more obvious, and the deformation of bridge components is large. Thus, research and analysis of the vehicle–bridge coupling dynamic response of long-span bridges under over-limit transportation has practical engineering significance.Design/methodology/approachBased on the principle of invariable elastic potential energy, this paper derives dynamic model of over-limit transportation n-axis flat vehicle. The numerical simulation method is used to model and calculate a cable-stayed bridge, and the static effect of the cable-stayed bridge and the dynamic response of vehicle–bridge coupling under different parameters are compared and analyzed.FindingsThe focus is on the influence of vehicle load and vehicle velocity parameters on the stress and amplitude of different cables under over-limit transportation, and the corresponding variation law is obtained.Originality/valueThe research on the coupled dynamic response of cable-stayed bridges has attracted the attention of many scholars, but there are relatively few studies on the coupled vibration of out-limit vehicles and bridges. In this paper, based on finite element software, a vehicle–bridge coupling model under bulk transportation is established.

Dynamics of long multi-trailer heavy vehicles crossing short to medium span length bridges

Around the world, many countries experience an increase in the demand for freight to be transported by road. One solution is to introduce larger heavy vehicles, which have the capability of transporting more freight. These vehicles have more trailers, more axles and are longer and heavier than existing heavy vehicle traffic. All these factors have an important influence on the dynamic amplification between the vehicle and bridge. This contribution presents the findings of the dynamic behaviour of long, multi-trailer vehicles, specifically the B-Double vehicles when crossing short to medium span bridges. The dynamic behaviour of these larger vehicles is compared to the well-known single articulated vehicles which are currently operating in many countries around the world. The effect of axle groups and their spacing on dynamic amplification is explored in depth to support the finding that the time of entry of axle groups on an excited bridge is key to the explanation of dynamic response. The relationship between midspan accelerations and dynamic amplification is introduced and explored extensively for further validation of the presented findings. There is an indication, that the commonly accepted inverse relationship between the high static load and observed low dynamic amplification is not generally true. Number of axles, along with inter-axle spacing matching with the natural frequency of the bridge are of substantial relevance to the dynamic response, yielding in some cases higher dynamic amplification of high static loads.

Axle Configuration and Weight Sensing for Moving Vehicles on Bridges Based on the Clustering and Gradient Method

Traffic information, including vehicle weight and axle spacing, is vital for bridge safety. The bridge weigh-in-motion (BWIM) system remotely estimates the axle weights of moving vehicles using the response measured from instrumented bridges. It has been proved more accurate and durable than the traditional pavement-based method. However, the main drawback of conventional BWIM algorithms is that they can only identify the axle weight and the information of axle configuration (the number of axles and axle spacing) is required to be determined using an extra device in advance of the weight identification procedure. Namely, dedicated sensors (pressure-sensitive sensors placed on the deck surface or under the soffit of a bridge) in addition to weighing sensors must be adopted for identifying the axle configuration, which significantly decreases the utility, feasibility, and economic efficiency of BWIM technology. In this study, a new iterative procedure simultaneously identifying axle spacing as well as axle weights and gross weights of vehicles is proposed. The novel method is based on k-means clustering and the gradient descent method. In this method, both the axle weight and the axle location are obtained by using the same global response of bridges; thus the axle detectors are no longer required, which makes it economical and easier to be implemented. Furthermore, the proposed optimization method has good computational efficiency and thus is practical for real-time application. Comprehensive numerical simulations and laboratory experiments based on scaled vehicle and bridge models were conducted to verify the proposed method. The identification results show that the proposed method has good accuracy and high computational efficiency in axle spacing and axle weight identification.

A bridge weigh-in-motion method of motorway bridges considering random traffic flow based on long-gauge fibre Bragg grating sensors

Accurate traffic conditions and their development regularity can help in the management of future traffic demand and bridge design. This study proposes a bridge weigh-in-motion method for identifying the vehicle parameters of motorway bridges considering random traffic flow and capitalizes on the advantages of long-gauge fibre Bragg grating sensors. A bridge-vehicle coupling system is numerically simulated, a 1:10 indoor experiment is used to verify the proposed method, and the vehicle parameters (e.g., traffic lane, vehicle spacing, vehicle axle weight, and speed) are identified with high accuracy. The effects of the road surface conditions, vehicle numbers, lateral positions and accelerations on the proposed method are investigated, and only find that the lateral positions are obviously related while and others have almost no influence on the method. In addition, the accuracy in axle number and weight identification is not high when the gauge length is smaller than vehicle wheelbases.

Automatic generation of fine‐grained traffic load spectrum via fusion of weigh‐in‐motion and vehicle spatial–temporal information

AbstractObtaining accurate traffic loads is crucial for the assessment of bridges. The traffic load obtained by the current method is insufficient for the refined analysis of bridge structures. Herein, a fusion method is proposed to generate fine‐grained traffic load spectra using weigh‐in‐motion data, video‐based vehicle spatial–temporal information, and knowledge‐based information of historical passing vehicles. Its effectiveness is tested on an interchange viaduct in Shaanxi, China. The average biases of the longitudinal and transverse locations of driving vehicles, which were identified using the proposed method, are 1.31 and 0.14 m, respectively. The identification accuracy in these two directions improved by 19% and 56%, respectively, compared with that of a pure deep learning‐based video identification method. Meanwhile, the accuracy of identifying the axle number is 99.87%. Additionally, a fine‐grained traffic load spectrum automatically generated with high accuracy is demonstrated. This method can be extended to other scenarios to further analyze and predict vehicle‐related bridge performance.

Polynomial approximation of dynamic signals of single platform railway scales

Purpose. Obtaining an approximating function (or a system of approximating equations), which, with a minimum error, will make approximations to the available data on a train of railway objects through 1 platform scales. Methodology. To solve this problem, numerical methods are used, namely, the approximation by polynomial functions of the nth order. The experimental data on the basis of which the experiments were carried out were obtained from the weighing and identification system of wagon in motion on a single platform scale. The approximation process is automated using a program written in the Python programming language in which the polyPit and polyid functions of the numPy library are used to obtain the polynomial coefficients. Findings. Due to the use of polynomial approximation in data processing from tensometric railroad weighing systems, it was possible to obtain a system of linear equations that, with minimal error, restored the experimental data that were obtained from the existing system of the Severny GOK: Metinvest enterprise. When normalizing the readings of the sensors from conventional units, obtained from the summing box to the range of values [0; 1] it became possible, in percentage terms, to describe a railway object. This makes it possible to avoid the dependence of the final results on the travel speed of the carriage or locomotive, which leads to an increase in the accuracy of the identification of cars in the rolling stock due to the use of the percentage of the axles staying on the weighing platform (approach / exit). It became possible to determine the type of carriage with the same number of axles, but different characteristics of the center space and the base of the rolling stock. Originality. The novelty is to obtain a general method of approximation of experimental data of the passage of wagons through a single-platform scales, which can be used to train intelligent systems and generate close to real data of the passage of a car (due to the imposition of noise, etc.). Practical value. Improving the accuracy and speed of the carriage identification as a whole, which reduces the plant downtime, contributes to an increase in the number of weighed and identified moving objects, as well as the ability to identify the type of carriage with the same number of axles in the train. The methods presented in the work can be used both for identification and for tasks, the end result of which is the classification of input data (neural networks, etc.).

An Empirical Tire-Wear Model for Heavy-Goods Vehicles

ABSTRACT Tire selection has an important impact on the operational costs of heavy-goods vehicles (HGVs). HGV tires are designed on a tradeoff between wear resistance, rolling resistance, and adhesion (skid resistance). High wear resistance tires (high mileage) are replaced less often but use more fuel during operation, and vice versa for low rolling resistance tires. Presently, finding the optimal tire to minimize replacement costs and fuel consumption (greenhouse gas emissions) is challenging due to the difficulty in predicting tire wear for a given operation, since its rate varies with different vehicle configurations (e.g., load, vehicle length, number of axles, type of axle, etc.) and road types (e.g., motorways/highways, minor roads, urban roads, etc.). This article presents a novel empirical tire-wear model that can be used to predict the wear for multi-axle vehicles based on route data and a vehicle model. The first part of the article presents the analytical and experimental development of the model. The second part presents the experimental validation of the model based on 10 months of in-service data totaling 37,000 km of operation. The model predicts tire tread depth within 8% (average error of 2%).

The Effect of Vehicle and Road Conditions on Rollover of Commercial Heavy Vehicles during Cornering: A Simulation Approach

Heavy vehicles make up a relatively small percentage of traffic volume on Malaysian roads compared to other vehicle types. However, heavy vehicles have been reported to be involved in 30,000–40,000 accidents yearly and caused significantly more fatalities. Rollover accidents may also incur cargo damages and cause environmental or human disasters for vehicles that carry hazardous cargos if these contents are spilled. Thus, in this paper, a comprehensive study was conducted to investigate the effects of vehicle and road conditions on rollover of commercial heavy vehicles during cornering at curved road sections. Vehicle conditions include the heavy vehicle class (based on the axle number and vehicle type), speed and gross vehicle weight, while road conditions include the cornering radius and coefficient of friction values. In order to reduce the risks involved in usage of actual heavy vehicles in crash experiments, a simulation approach using a multi-body vehicle dynamic software was applied in this study, where the verified virtual heavy vehicle model was simulated and the output results were extracted and analyzed. The results showed that a maximum of 40% and a minimum of 23% from the total number of simulations resulted in an unsafe condition (indicated as failed) during the simulations. From the unsafe conditions, two types of rollover accidents could be identified, which were un-tripped and tripped rollovers. The heavy vehicle speed was also found to have a strong correlation to the lateral acceleration (to cause a rollover), followed by gross vehicle weight, coefficient of friction and cornering radius, respectively.

Transportation-Mission-Based Optimization of Heterogeneous Heavy-Vehicle Fleet Including Electrified Propulsion

Commercial-vehicle manufacturers design vehicles to operate over a wide range of transportation tasks and driving cycles. However, certain possibilities of reducing emissions, manufacturing and operational costs from end vehicles are neglected if the target range of transportation tasks is narrow and known in advance, especially in case of electrified propulsion. Apart from real-time energy optimization, vehicle hardware can be meticulously tailored to best fit a known transportation task. As proposed in this study, a heterogeneous fleet of heavy-vehicles can be designed in a more cost- and energy-efficient manner, if the coupling between vehicle hardware, transportation mission, and infrastructure is considered during initial conceptual-design stages. To this end, a rather large optimization problem was defined and solved to minimize the total cost of fleet ownership in an integrated manner for a real-world case study. In the said case-study, design variables of optimization problem included mission, recharging infrastructure, loading–unloading scheme, number of vehicles of each type, number of trips, vehicle-loading capacity, selection between conventional, fully electric, and hybrid powertrains, size of internal-combustion engines and electric motors, number of axles being powered, and type and size of battery packs. This study demonstrated that by means of integrated fleet customization, battery-electric heavy-vehicles could strongly compete against their conventional combustion-powered counterparts. The primary focus has been put on optimizing vehicle propulsion, transport mission, infrastructure and fleet size rather than routing.

FEATURES OF ADAPTIVE BRAKE CONTROL OF THE SECONDARY BRAKE SYSTEM OF A MULTI-AXLE VEHICLE

Problem. A malfunction of the service braking system of a wheeled vehicle (CTS) significantly affects road safety, especially when operating multi-axle vehicles with large masses. One of the ways to increase the level of road safety of multi-axle vehicles, when braking them using a spare (emergency) braking system, is the introduction of automated adaptive braking systems into the design of the brake drive of vehicles. The definition of the limits of the use of the adaptive braking system on vehicles with many axles is almost not disclosed in the scientific and technical literature, therefore, the issue of using such a system on vehicles with a large number of axles requires additional research. Purpose. The purpose of this work is to develop a simulation model for adaptive control of the braking process of a multi-axle vehicle using a spare (emergency) braking system, taking into account the simulation of the dynamics of the drive and the variability of the adhesion properties between the tire of the vehicle wheel and the road surface. Methodology. To achieve this goal, it is necessary to develop a simulation model of the brake drive in an adaptive mode, implement a model of the interaction of the tire with the road surface, and implement a model of the braking dynamics of a multi-axle vehicle in the event of a malfunction of its service brake system. Originality. The proposed key criterion (Kr) for changing the throttle section in electro-pneumatic pressure modulators, which provide adaptive air inlet or outlet from the corresponding brake chambers of the drive, during simulation, made it possible to simulate the operation of the drive circuits in the adaptive mode. It has been established that, depending on the potential for the realization of the adhesion between the tires of automobile wheels and the road surface, the pressure in the electro-pneumatic brake drive with its adaptive regulation can be increased by no more than 0.04 MPa.

Bridge influence surface identification method considering the spatial effect of vehicle load

Bridge influence surface is an important tool to study the bridge responses under the moving loads, which contains tremendous structural information. The structural deterioration during the service life would induce the variation of the bridge influence surface, which makes it essential to identify the influence surface exactly from the field measured data under moving vehicle loads. This paper firstly summarizes current development of bridge influence surface identification methods and classifies the methods in which the vehicle is respectively equivalent to line loads and concentrated loads. After that, the actual spatial distribution of the vehicle load is considered, based on which a new identification method is presented to solve the boundary problem of current influence surface identification methods. Then a numerical slab model with two fixed ends is illustrated to prove the validity of the method, and the accuracy and identifiable region of different methods in this condition are compared with the other methods. Influence factors of identification accuracy including noise level, axle number of vehicle and loading point are analyzed. Finally, laboratory verification using the same slab model is prepared to verify the effectiveness of the proposed identification method. Results of this study provide an effective identification method of bridge influence surface with very high identification accuracy, which can be used to full bridge influence surface test.

Impact analysis of traffic loading on pavement performance using support vector regression model

ABSTRACT This study aims to use traditional regression model and machine learning method to analyse the impact of traffic loading on pavement performance. Pavement condition data were obtained from pavement management systems (PMS) and axle loads of truck traffic were collected at weigh-in-motion (WIM) stations. Support vector regression (SVR) method was selected for modelling pavement performance since it provides the flexibility to find the appropriate hyperplane in higher dimensions to fit the data and customise control errors in an acceptable range. Compared to traditional nonlinear regression model, the accuracy of pavement performance prediction was significantly increased by utilising the SVR method. The model accuracy was further improved by considering the number of axles and fitted Gaussian distribution of axle load spectra in the performance model. The derived SVR models were further used to investigate the impact of overweight truck on pavement life reduction considering characteristics of axle load distributions. The proposed pavement performance model can be further used in determining pavement damage caused by overweight trucks for pavement rehabilitation strategy and fee analysis is permitted.

The Model of Degressive Taxation of Trucks: Case of the Czech Republic

Abstract The article examines issues related to the design of road tax as an instrument supporting the operation of trucks that are more environment-friendly to the transport infrastructure. The Introduction presents analyses of road taxation in the European Union Member States, whose aim was to identify features supporting trucks that are eco-friendly with regard to the infrastructure. The principal part of the contribution is the formulation of a regression model of road tax rates, which is subjected to statistical, econometric and economic verification in order to confirm or disprove degressivity of road tax rates for trucks. The economic verification is based on typical examples of vehicles defined in Annex 2 to the text. The Conclusion presents the results achieved, which verify the degressive nature of road tax in the Czech Republic. The tax rates are degressive in relation to the number of truck axles; therefore, a proposal for the elimination of degressivity in the system of tax rates for trucks was designed based on the principle of fair taxation, which is also discussed in the contribution.

Damage investigation of thin flexible pavements to Longer Heavier Vehicle loading through instrumented road sections and numerical calculations

Longer Heavier Vehicles provide an improvement in energy efficiency and environmental performance compared to traditional Heavy-Duty Vehicles. In Sweden, the maximum permissible vehicle gross weight has been increased from ∼64 to ∼74 tonnes without increasing the axle load limits. The consequence of this is investigated in this study. Response from two instrumented thin flexible pavements subjected to loading from three types of heavy vehicles (∼64, ∼68 and ∼74 tonnes) has been measured and the recordings were compared with numerical calculations based on 2D multilayer elastic calculations. Pavement damage contribution by the three vehicles was thereafter investigated. As long as the number of axles is increased to compensate for the increased vehicle loading and dual wheels are used, ∼74 tonnes vehicle are not more aggressive to the two thin pavement structures compared to the lighter vehicles with fewer axles but higher average axle loads and tyre pressure.

Traffic intensity calculation criteria for freight vehicles

To choose the road pavement, it is necessary to determine the traffic intensity and composition of the traffic flow on highways. The existing methods are used depending on the number of axles or carrying capacity of trucks. The purpose of this study is to compare the methods for determining the traffic intensity of vehicles and analyze the values of the minimum total modulus of elasticity. The article presents the results of calculation of the modulus of elasticity based on the traffic flow, the number of axles and carrying capacity of the vehicle. As part of the analysis, tables were compiled, the total estimated number of applications of the design load to a surface point was determined, and the minimum total modulus of elasticity of the road structure was calculated. The result of the research is recommendations for choosing a method for recording traffic intensity depending on the road category and traffic flow composition.

Interferometric optical fiber sensor for monitoring of dynamic railway traffic

The optical fiber sensor based on a Fabry-Pérot interferometer was developed and experimentally verified. As a sensing element a conventional optical fiber was used. The prepared optical sensor was placed at the rail and tested in normal operation for 24 h. Practical tests have shown that from the measured signals of the prepared sensor it is possible to determine the time dependence of the elongation of the sensing optical fiber. From this it is possible to determine the speed of the train set, the number of axles, the load of individual wheels and identified a possible flat wheels of train set. The results document that the sensor can be used as a sensitive detector for monitoring of dynamic railway traffic. The main advantages, in addition to sensitivity and a wide range of monitored parameters, include easy implementation and no expensive equipment.

The influence of the parameters of the running systems of wheeled vehicles on the change in soil density

The movement of wheeled vehicles on soils and grounds leads to a change in their density. The research includes the influence of mass and its distribution along the axes of the wheels on the change in the density of soils and grounds. The substantiation of analytical dependencies for determining the density of compacted and flowing soils and soils from repeated impacts of wheels under various loads is given. The dependence for determining the density of the soil in the general case, including compressed and fluid components of the state of the soil and soil mass, was substantiated.
 The experimental laboratory studies were carried out on the effect of wheels on the soil and the effect of wheel load on soil compaction. The dependences were obtained to determine the compaction of soil with different physical and mechanical properties under different loading modes of the running systems. It was found that the distribution of the mass of a wheeled vehicle along the axles of the wheels affects the depth of the track and the compaction of the soil. The obtained dependences for describing the process of soil compaction are consistent with the results of experiments. It was found that with an increase in the number of axles of the running system, soil compaction decreases. The minimum track depth and soil compaction are observed when the mass of the wheeled vehicle is evenly distributed along the axes of the chassis. With an increase in the number of axles, the influence of the ratio of the pressure of the first wheel to the average pressure on soil compaction decreases due to a decrease in the differential pressure of the wheels that occurs in multi-axle wheel systems. With slight deviations from the unit of the ratio of the front wheel load to the average value of the pressure, the increase in soil density is not perceptible. As the front-to-middle load ratio increases, soil compaction increases significantly compared to an even weight distribution along the axles.

A Theoretical Model with Which to Safely Optimize the Configuration of Hydraulic Suspension of Modular Trailers in Special Road Transport

The dimensions and weight of machines, structures, and components that need to be transported safely by road are growing constantly. One of the safest and most widely used transport systems on the road today due to their versatility and configuration are modular trailers. These trailers have hydraulic pendulum axles that are that are attached in pairs to the rigid platform above. In turn, these modular trailers are subject to limitations on the load that each axle carries, the tipping angle, and the oil pressure of the suspension system in order to guarantee safe transport by road. Optimizing the configuration of these modular trailers accurately and safely is a complex task. Factors to be considered include the load’s characteristics, the trailer’s mechanical properties, and road route conditions including the road’s slope and camber, precipitation and direction, and force of the wind. This paper presents a theoretical model that can be used for the optimal configuration of hydraulic cylinder suspension of special transport by road using modular trailers. It considers the previously mentioned factors and guarantees the safe stability of road transport. The proposed model was validated experimentally by placing a nacelle wind turbine at different points within a modular trailer. The weight of the wind turbine was 42,500 kg and its dimensions were 5133 × 2650 × 2975 mm. Once the proposed model was validated, an optimization algorithm was employed to find the optimal center of gravity for load, number of trailers, number of axles, oil pressures, and hydraulic configuration. The optimization algorithm was based on the iterative and automatic testing of the proposed model for different positions on the trailer and different hydraulic configurations. The optimization algorithm was tested with a cylindrical tank that weighed 108,500 kg and had dimensions of 19,500 × 3200 × 2500 mm. The results showed that the proposed model and optimization algorithm could safely optimize the configuration of the hydraulic suspension of modular trailers in special road transport, increase the accuracy and reliability of the calculation of the load configuration, save time, simplify the calculation process, and be easily implemented.

The effect of different loading patterns on the resistance to shear flow of hot mix asphalt

The aim of this study was to evaluate the performance of hot mix asphalt against shear deformations. Loading axles (single, tandem and tridem) as well as vehicle speed were considered as research variables. The combination of research variables creates different loading scenarios with different loading pulse times. Using theoretical principles, loading scenarios similar to the field mode were simulated. Then, using the repeated load uniaxial test (RLUT), a quantitative analysis was performed on the mentioned variables. Flow number (FN) and tertiary flow (TF) were used as quantitative output parameters to analyze the test results. In addition, the regression coefficients of the power-law model represent the effect of initial densification and shear flow. It was observed that at higher speeds and in the mode of multiple axles, the initial densification had more effect on the permanent strain compared to the effects of the shear flow. On the other hand, in the single axle, the shear flow was the dominant factor at all speeds. At the middle speed (60 km⁄h), the shear flow (the slope) was the dominant parameter for the tridem axle. Low pulse times, high speeds and proximity of the load impact peaks can cause higher initial densifications in multiple axles. It was also indicated that by increasing the number of axles, values of the FN and the TF, and the value of the interval between these two parameters reduced. This reduction became more tangible by increasing the number of axles from single to other axle modes. In all axle modes, by increasing the speed, the FN and the TF increased. The rate of these increases was higher when transitioning from low speed (20 km⁄h) to middle speed (60 km⁄h) was more intense. Therefore, low speeds had more destructive effects. Thus, higher speeds reduced the destruction effects of multiple axles loads and increased the service life of the mixtures, and improved their performance against shear deformations.