• 한국도로학회:학술대회논문집
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• 2009.11a
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• pp.373-379
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• 2009

• 한국도로학회:학술대회논문집
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• 2009.11a
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• pp.689-696
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• 2009

• International Journal of Highway Engineering
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• v.10 no.1
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• pp.135-144
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• 2008

The dynamic loads imposed by moving vehicles have variations in the magnitude due to the surface roughness of the pavement systems and the larger dynamic loads than the design loads may affect the pavement performance. This paper presents variations of the moving dynamic vehicle loads due to the pavement surface roughness. This study was performed as a basic study to apply the pay factor to the surface roughness for the improvement of pavement quality and performance. The profile data was obtained from the old and new pavements and the analysis was performed to investigate the dynamic loads when vehicles move on the pavements having those profiles. The artificial profiles were also developed to find the effects of the vehicle speed, wavelength and amplitude of the surface roughness on the dynamic vehicle loads. The increase in the load magnitude due to the surface roughness affects the stresses and strains of pavements and finally reduces the pavement life. The methodology to obtain the relationship between the surface roughness and the pavement performance was proposed in this study.

• Structural Monitoring and Maintenance
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• v.6 no.4
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• pp.317-346
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• 2019

Performance assessment of pavements proves useful, in terms of handling the ride quality, controlling the travel time of vehicles and adequate maintenance of pavements. Roughness profiles provide a good measure of the deteriorating condition of the pavement. For the accurate estimates of pavement roughness from dynamic vehicle responses, vehicle parameters should be known accurately. Information on vehicle parameters is uncertain, due to the wear and tear over time. Hence, condition monitoring of pavement requires the identification of pavement roughness along with vehicle parameters. The present study proposes a scheme which estimates the roughness profile of the pavement with the use of accurate estimates of vehicle parameters computed in parallel. Pavement model used in this study is a two-layer Euler-Bernoulli beam resting on a nonlinear Pasternak foundation. The asphalt topping of the pavement in the top layer is modeled as viscoelastic, and the base course bottom layer is modeled as elastic. The viscoelastic response of the top layer is modeled with the help of the Burgers model. The vehicle model considered in this study is a half car model, fitted with accelerometers at specified points. The identification of the coupled system of vehicle-pavement interaction employs a coupled scheme of an unbiased minimum variance estimator and an optimization scheme. The partitioning of observed noisy quantities to be used in the two schemes is investigated in detail before the analysis. The unbiased minimum variance estimator (MVE) make use of a linear state-space formulation including roughness, to overcome the linearization difficulties as in conventional nonlinear filters. MVE gives estimates for the unknown input and fed into the optimization scheme to yield estimates of vehicle parameters. The issue of ill-posedness of the problem is dealt with by introducing a regularization equivalent term in the objective function, specifically where a large number of parameters are to be estimated. Effect of different objective functions is also studied. The outcome of this research is an overall measure of pavement condition.

• Smart Structures and Systems
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• v.31 no.2
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• pp.155-169
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• 2023

The quasi-static component of the moving vehicle-induced dynamic response is promising in damage detection as it is sensitive to bridge damage but insensitive to environmental changes. However, accurate extraction of quasi-static component from the dynamic response is challenging especially when the vehicle velocity is high. This paper proposes an adaptive quasi-static component extraction method based on the modified variational mode decomposition (VMD) algorithm. Firstly the analytical solutions of the frequency components caused by road surface roughness, high-frequency dynamic components controlled by bridge natural frequency and quasi-static components in the vehicle-induced bridge response are derived. Then a modified VMD algorithm based on particle swarm algorithm (PSO) and mutual information entropy (MIE) criterion is proposed to adaptively extract the quasi-static components from the vehicle-induced bridge dynamic response. Numerical simulations and real bridge tests are conducted to demonstrate the feasibility of the proposed extraction method. The results indicate that the improved VMD algorithm could extract the quasi-static component of the vehicle-induced bridge dynamic response with high accuracy in the presence of the road surface roughness and measurement noise.

• International Journal of Highway Engineering
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• v.19 no.5
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• pp.89-96
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• 2017

PURPOSES: This study aims to develop a rational procedure for estimating the pavement roughness index considering vehicle wandering. METHODS : The location analysis of the passing vehicle in the lane was performed by approximately 1.2 million vehicles for verification of the wandering distribution. According to verification result, the distribution follows the normal distribution pattern. The probability density function was estimated using each lane's wandering distribution model. Then the procedure for applying a weighted value into the lane profile was conducted using this function. RESULTS : The modified index, MRIw, with consideration towards applying the wandering weighted value application was computed then compared with MRI. It was found that the Coefficient of Variation for distribution of lateral roughness index in the lane was high in the case of a large difference between each index (i.e., MRIw and MRI) observed. CONCLUSIONS : This result confirms that the new procedure with consideration of the weight factor can successfully improve the lane representative characteristics of the roughness index.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.4
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• pp.105-110
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• 2014

This paper presents the hysteresis friction of a sliding elastomer on various types of surfaces. The hysteresis friction is calculated by means of an analytical model which considers the energy spent by the local deformation of the rubber due to surface asperities. By establishing the fractal character of the surfaces, the contribution to rubber friction of roughness at different length scales is accounted for. High resolution surface profilometer is used in order to calculate the main three surface descriptors and the minimal length scale that can contribute to hysteresis friction. The results show that this friction prediction can be used in order to characterize in an elegant manner the surface morphology of various surfaces and to quantify the friction coefficient of sliding rubber as a function of surface roughness, load and speed.

• International Journal of Automotive Technology
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• v.5 no.4
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• pp.257-268
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• 2004

The wavelet analysis method is introduced in this paper to study the nonstationary vibration of vehicles. A new road model, a so-called time domain correlated four-wheel road roughness, which considers the coherence relationships between the four wheels of a vehicle, has been newly developed. Based on a vehicle model with eight degrees of freedom, the analysis of nonstationary random vibration responses was carried out in a time domain on a computer. Verification of the simulation results show that the proposed road model is more accurate than previous ones and that the simulated responses are credible enough when compared with some references. Furthermore, by taking wavelet analysis on simulated signals, some substantial rules of vehicle nonstationary vibration, such as the relationship between each vibration level, and how the vibration energy flows on a time-frequency map, beyond those from conventional spectral analysis, were revealed, and these will be of much benefit to vehicle design.

• Journal of Korean Society of Steel Construction
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• v.23 no.2
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• pp.199-210
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• 2011

The cables in cable-stayed bridges are under high stress and are very sensitive to vibration due to their small section areas compared with other members. Therefore, it is reasonable to evaluate the cable impact factor by taking into account the dynamic effect due to moving-vehicle motion. In this study, the cable impact factors were evaluated via moving-vehicle-load analysis, considering the design parameters, i.e., vehicle weight, cable model, road surface roughness, vehicle speed, longitudinal distance between vehicles. For this purpose, two steel composite cable-stayed bridges with 230- and 540-m main spans were selected. The results of the analysis were then compared with those of the influence line method that is currently being used in design practice. The road surface roughness was randomly generated based on ISO 8608, and the convergence of impact factors according to the number of generated road surfaces was evaluated to improve the reliability of the results. A9-d.o.f. tractor-trailer vehicle was used, and the vehicle motion was derived from Lagrange's equation. 3D finite element models for the selected cable-stayed bridges were constructed with truss elements having equivalent moduli for the cables, and with beam elements for the girders and the pylons. The direct integration method was used for the analysis of the bridge-vehicle interaction, and the analysis was conducted iteratively until the displacement error rate of the bridge was within the specified tolerance. It was acknowledged that the influence line method, which cannot consider the dynamic effect due to moving-vehicle motion, could underestimate the impact factors of the end-cables at the side spans, unlike moving-vehicle-load analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3A
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• pp.305-313
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• 2008

A reliability based calibration of dynamic load allowance (DLA) of highway bridge is performed by numerical dynamic analysis of various types of bridges taking into account of the road surface roughness and bridge-vehicle interaction. A total of 10 simply supported bridges with three girder types in the form of prestressed concrete girder, steel plate girder, and steel box girder is analyzed. The cross sections recommended in "The Standardized Design of Highway Bridge Superstructure" by the Korean Ministry of Construction are used for the prestressed concrete girder bridges and steel plate girder bridges while the box girder bridges are designed by the LRFD method. Ten sets of road surface roughness for each bridge are generated from power spectral density (PSD) function by assuming the roadway as "Average Road". A three dimensionally modeled 5-axle tractor-trailer with its gross weight the same as that of DB-24 design truck is used in the dynamic analysis. For the finite element modeling of superstructure, beam elements for the main girder, shell elements for concrete deck, and rigid links between main girder and concrete deck are used. The statistical mean and coefficient of variation of DLA are obtained from a total of 100 DLA results for 10 different bridges with each having 10 sets of road surface roughness. Applying the DLA statistics obtained, the DLA is finally calibrated in a reliability based LRFD format by using the formula developed in the calibration of OHBDC code.