Effect Of Road Surface Roughness Research Articles

Drive-By Identification of Joint Bridge Damage and Surface Roughness Based on Sensitivity Analysis of Residual Contact Point Deflections

Drive-by inspection of bridge damage using a passing vehicle’s dynamic response has great potential in bridge damage identification. Among the current drive-by methodologies, the methods based on bridge modeling have been proposed for the quantitative identification of bridge damage and bridge surface roughness. However, the coupling of bridge damage and unknown surface roughness increases the difficulty of the identification problem and most previous studies conduct the identification task of bridge damage or bridge surface roughness separately. In this paper, a novel method is proposed for the identification of joint bridge damage and bridge surface roughness based on the residual bridge deflections from the front and rear wheels contact points of an instrumented passing vehicle. The vehicle–bridge interaction is analyzed using a half-car model of a four degrees of freedom (4-DOF) with front and rear vehicle wheels. First, the vehicle–bridge unknown forces and displacement of the vehicle axles are identified by the generalized Kalman filter under unknown input (GKF-UI) proposed by the authors. The sensors can be installed conveniently on the vehicle body due to GKF-UI. Then, the residual bridge deflections from the front and rear vehicle wheels contact points are utilized to eliminate the effect of road surface roughness. Afterward, bridge structural damage is identified based on the sensitivity analysis of residual bridge deflections from the front and rear contact points with [Formula: see text]1-norm regularization. Finally, bridge road surface roughness is estimated based on the identified unknown forces and updated bridge model with damage. The results of numerical identification examples demonstrate the effectiveness of the proposed method for the identification of joint bridge damage and surface roughness.

Human-bus-road coupled vibration considering effect of braking forces

The ride comfort of vehicles traveling on the road has always been a concern. In addition, the braking force of vehicles will aggravate the damage to road structures and reduce the comfort of drivers and passengers. In the present study, the dynamic response of pavement, road friendliness, and human comfort are investigated by setting up the human-bus-road coupled vibration system considering the braking forces. Firstly, the three-dimensional finite element model of asphalt pavement with interlayer contact and the human-bus model with multiple degrees of freedom (2n + 7) were established to analyze the dynamic responses of asphalt pavement, human body, and bus under different braking conditions. Then, the dynamic load coefficients of wheels under different combined conditions were investigated to evaluate the road friendliness and the human annoyance rate was adopted to evaluate the human comfort. The results show that for the asphalt pavement, the shear stress of the pavement is larger than the normal stress due to the bus braking, and the combined effect of road surface roughness and braking force on the road friendliness is the largest. For the human comfort, the pitch acceleration of human body increases more than the roll acceleration due to bus braking, resulting in the decreased human comfort and increased annoyance rate.

An autonomous and heuristic approach for extracting bridge frequencies from passing vehicles

The Federal Highway Administration (FHWA) recognizes a need for cost-effective and practical structural health monitoring (SHM) techniques to manage the bridge network. System identification (SI) techniques are the first step in developing SHM frameworks to extract bridge dynamic properties (natural frequencies, damping ratios, and mode shapes). One promising indirect SI technique uses accelerometer-instrumented vehicles to measure the dynamic properties of bridges, such that a few instrumented vehicles could economically monitor a large network of bridges. This study proposes an autonomous framework called autonomous peak picking variational mode decomposition (APPVMD), which leverages an ensemble of signal processing techniques and heuristic models to autonomously extract bridge frequencies from instrumented vehicles. The proposed framework does not require prior information or model-informed training. The framework is tested on four vehicles and 39 unique bridge classes using finite element (FE) models to assess the feasibility of deploying it into practice. The results of this study indicate that the algorithm can make successful bridge frequency extractions in more than 69.2% of the bridge cases using any vehicle and a maximum value of 97.4% using an SUV, while considering the effects of road surface roughness. The influence of bridge stiffness, mass, and span length on the algorithm’s success rate is discussed. It is concluded that flexural rigidity and span length play a significant role in the accuracy of APPVMD. The combined effects of bridge inertia and damping cause heavier bridges to have a higher amplitude signal for a longer duration, increasing the algorithm’s successful detection rate of bridge frequency. Next, the authors examine the effect of reducing the tire stiffness in the truck model on the success of the APPVMD algorithm. The customized truck outperformed the original truck and the SUV by successfully extracting the bridge frequencies of 97.4% of the bridge cases and by having more bridge frequencies predicted in a higher confidence region than the SUV. In addition, the customized truck model is used to verify the APPVMD’s robustness to large levels of sensor noise. Even at significant levels of white noise (1% SNR), as the success rate for bridge frequency extraction using the customized truck only drops to 84.6%. Finally, the influence of vehicle speed on the APPVMD algorithm’s effectiveness is studied. Generally, slower speeds resulted in more successful predictions of bridge frequency, but minor improvements in the accuracy of the frequency predictions were observed at slightly increased velocities, 13.4 m/s (30 mph) and 17.9 m/s (40 mph), but a reduction in accuracy was observed at higher velocities, 22.3 m/s (50 mph).

Indirect Approach to Identify Girder Bridge Element Stiffness Based on Blind Source Separation

The indirect method of using a passing vehicle to identify modal properties of a girder bridge has become attractive recently. Compared to the direct method, which requires a lot of sensors installed directly on the bridge itself, the indirect method only requires a single sensor installed on the vehicle to indirectly measure the response of the bridge. However, it is difficult to eliminate the adverse effect of road surface roughness. An indirect approach based on blind source separation is proposed for the first time in this study to identify the bridge element stiffness where two movable vehicles are used. Two identical vehicles stay at rest at the designated measurement points and their vertical accelerations are collected. After one measurement, the two vehicles move to other designated measurement points and the accelerations are collected again. The same procedure is repeated until the two vehicles have moved over all the designated measurement points. Then the blind source separation technique is employed to extract the fundamental mode shape of the bridge and the improved direct stiffness method is adopted to estimate the bridge element stiffness based on the collected data, which are used to monitor the health of the bridge structure and to maintain structure safety and natural symmetry. The proposed method only requires the output response of the vehicle due to the involvement of the blind separation technique. In addition, the proposed method can overcome the adverse effect of road surface roughness because the vehicles only move between two measurements and they stay at rest during one measurement. Numerical simulation was conducted to validate the proposed method, and the effect of various factors such as bridge damping ratio and measurement noise was investigated. Field measurement on Min-Xie bridge in Chongqing city was also carried out to further investigate the feasibility of the proposed method and showed that it can perform well in extracting the fundamental mode shape and evaluating bridge element stiffness.

Enhanced drive‐by bridge modal identification via dual Kalman filter and singular spectrum analysis

The drive-by bridge health monitoring is to assess the bridge condition using the acceleration responses measured on the body or axle of instrumented vehicles. The vehicle responses are greatly affected by the road surface roughness that makes the bridge dynamic information blurred. Instead of direct using vehicle responses for the bridge monitoring, the dynamic response of contact point (CP) between the vehicle and bridge is further explored to enhance the drive-by bridge modal identification. A novel three-step framework is proposed to extract the components related to the bridge vibration from vehicle responses. The first step is to identify the input forces of two successive vehicles by solving the combined state-input estimation problem using dual Kalman filter. The CP responses of two contact points are calculated using the input forces and vehicle parameters. In the second step, the subtraction technique is applied to the identified CP responses of the two instrumented vehicles and the effect of the road surface roughness can be significantly reduced. Finally, an automatic singular spectrum analysis technique (auto SSA) is incorporated to decompose the response residual. Then the mono-component modes related to the bridge response are extracted from the response residual for drive-by bridge modal identification and/or the nonstationary characteristic identification of vehicle–bridge interaction (VBI) system. Results of numerical and experimental study demonstrate that the method can significantly suppress the vehicle response component and reduce the effect of road surface roughness to enhance the bridge modal identification.

Fundamental mode shape estimation and element stiffness evaluation of girder bridges by using passing tractor-trailers

A comprehensive indirect method is proposed in this study to estimate the dynamic characteristics of the fundamental mode and evaluate the element stiffness of a girder bridge using a passing tractor with two identical trailers. The novelty of this study is the use of the dynamic interaction between the two identical trailers and the bridge rather than that between the truck and the bridge. One of the advantages of this is that the dynamic characteristics of trailers are easier to model and analyse. Under the proposed method, the residual acceleration of the two trailers is first used to eliminate the adverse effects of road surface roughness. The fundamental natural frequency of the bridge is obtained from the Fourier transform of the resulting signal. Next, the component corresponding to this fundamental frequency was extracted using bandpass filtering. The corresponding damping ratio and mode shape can be reconstructed through a short-time Fourier transform (STFT) under the assumption that the fundamental mode shape amplitude peak is located at the midspan. Finally, the element stiffness of the bridge was evaluated using the reconstructed fundamental mode shape. In this study, the proposed method is investigated via numerical examples and performs well in different scenarios, for example, in the presence of high-level measurement noise and low-level road surface roughness. Furthermore, the method was validated through field testing on the Li-Zi-Wan bridge in Chongqing. The extracted fundamental mode shape agrees well with that obtained using the stochastic subspace identification (SSI) method. The evaluated element stiffness matches very well with both the original design and the static deflection test results.

Fatigue damage prognosis of steel bridges under traffic loading using a time-based crack growth method

Traditionally, the fatigue damage assessment of steel bridges is conducted using cycle-based methods. Cycle-based methods require stress time history be transformed to cycle history first before fatigue analysis can be performed. However, well-defined cycle history does not exist for the traffic-induced stress time history of bridges as it contains numerous large and small cycles with random stress ranges embedded together. To address this inherent difficulty, a time-based fatigue crack growth (FCG) model is proposed for fatigue damage prognosis of steel bridges under traffic loading. The time-based FCG method describes the crack growth in the time domain through a crack growth kinetics function derived based on the physical mechanism of fatigue crack propagation. To demonstrate the proposed method, numerical simulations are first performed using full-scale coupled vehicle-bridge interaction framework to generate stress time histories of a typical steel bridge under traffic loading. Then, FCG analysis is performed using the time-based method and the effects of road surface roughness and vehicle weight on the FCG are studied. Finally, a case study on the I-10 Twin Span Bridge is presented to demonstrate the time-based FCG method for fatigue damage prognosis using in situ monitoring data. The results show that the proposed method can be used to directly predict the FCG of steel bridges in the time domain using stress time histories obtained either from stress analysis or in situ monitoring.

The Effect of Road Surface Roughness to Recommended Speed of Vehicles

Road safety is one of the major concerns of the transportation system planners and managers in any nation. The principle goal of road safety is to reduce the frequency and severity of traffic accidents. The design and manufacturing of high-quality road directly play an important role in achieving better road safety. This research presents the model describing the relationship between road surface roughness with the vehicle’s recommended safe velocity. The result shows that the road surface roughness measured by the International Roughness Index (henceforth IRI) is indirectly proportional to the vehicle’s recommended safe velocity. In particular, if the recommended safe velocity is 100 km/h, the surface roughness IRI should not exceed 1.9 m/km. An implication of this is the possibility that using the simulation on MATLAB Simulink software should have the appropriate IRI concerning the designed speed.

Study on Passenger Comfort Based on Human–Bus–Road Coupled Vibration

Nowadays, the comfort of drivers and passengers is drawing more and more attention. The interaction between vehicles and the asphalt road can cause coupled vibration and reduce the comfort of passengers. Therefore, the research on human–vehicle–road coupled vibration and the comfort of passengers is of great importance. In this paper, the three-dimensional human–bus–road coupled vibration system is established, including the bus model, the parallel biomechanical human model with 2 degrees-of-freedom (DOF), and road surface roughness condition. The proposed coupled model was then used to study the dynamic response of the system and the comfort evaluation of the human body. In the comfort evaluation, the annoyance rate based method was proposed to consider the randomness of passenger vibration, the difference of the psychosensory vibration, and the fuzziness of evaluation indicators. Compared to the fuzzy evaluation based on the ISO 2631 standard, the proposed annoyance rate based method gives a quantitative evaluation of human comfort. Not only the degree of comfort can be evaluated, but the percentage of people feeling uncomfortable can also be obtained. Finally, parametric studies were conducted to investigate the effects of road surface roughness, interlayer bonding condition, bus weight, bus speed, and sitting position. It is found that the road surface roughness has the most significant effect on human comfort.

Feasibility Study of Tractor-Test Vehicle Technique for Practical Structural Condition Assessment of Beam-Like Bridge Deck

The tractor-test vehicle technique of non-destructive testing for indirect measurement of the modal properties of a bridge deck is revisited in this paper with several improvements for possible practical application to the structural condition assessment of a beam-like bridge deck. The effect of damping of the vehicle-bridge system is considered and the modal properties from only the first vibration mode of the structure will be used for a quick and simple assessment. The two test vehicles are designed to have the same modal frequency and damping ratio but with parameters in the follower No.2 test vehicle proportional to those in the follower No.1 test vehicle. This effectively removes the effect of road surface roughness in the response of an equivalent vehicle such that the error in the subsequent condition assessment is reduced. Through data collected on-sitetransmitted to theremote computer platform, a simple technique based on the moment-curvature relationship acceptable to practical engineers is adopted for the condition assessment with improvements in the estimation of the element bending stiffness of the deck. Scenarios with different damping, vehicle speed, road surface roughness, and local damages in the bridge structure are studied with or without temperature effect in the measurement. Through numerical simulations and field tests, the tractor-test vehicle technique of non-destructive testing with the proposed modifications and improvements has been demonstrated to give consistently accurate estimates of the element bending stiffness of the bridge deck but with a small error close to the end of the deck.

Development of Dynamic Impact Factor Expressions for Skewed Composite Concrete‐Steel Slab‐On‐Girder Bridges

In order to take into account the dynamic effects of moving vehicles, bridges are designed to carry static loads that are increased by dynamic impact (IFs) factors (or dynamic amplification factors) that are a function of either the span or the first flexural natural frequency of the bridge. However, this approach tends to produce very conservative designs as the IFs are calculated based on a relatively few general parameters, ignoring many significant bridge and truck dynamic characteristics. This paper presents a method for determining more realistic dynamic impact factors for skewed composite slab‐on‐girder bridges under AASHTO LRFD truck loading. An extensive parametric study of over 125 bridge prototypes examined key parameters, namely, the number of girders, number of lanes, skew angle, and span length. Based on the data generated by this analysis, appropriate expressions for dynamic impact factors for the longitudinal moment and deflection are proposed. In order to reduce the complexity of proposed expressions, the effects of road surface roughness on dynamic responses of bridge‐vehicle interaction are considered in bridge modeling. The findings of this study are expected to help bridge engineers to design composite slab‐on‐girder bridges more reliably and economically and can also be used to reassess the safe live‐load capacity of existing structures, potentially preventing the unnecessary posting or closing of busy highway bridges.

A Damage Detection Algorithm Utilizing Dynamic Displacement of Bridge under Moving Vehicle

A damage detection method is proposed, which utilizes dynamic displacement of bridge structures under moving vehicle. The problem is first elaborated with closed-form solution of dynamic displacement, which is decomposed into quasi-static component and dynamic component. Dynamic curvature is defined as second derivative of the dynamic displacement for detecting damage location and estimating damage extent. Damage is modeled by local reduction of stiffness in this paper. Numerical study was conducted on a simply supported beam to verify the proposed method. Vehicle model is analyzed with Newmark’s method using Matlab to obtain the contact force acting on the bridge. Beam model is established in commercial finite element software ABAQUS. The effects of road surface roughness and vehicle-bridge interaction are both considered in the analysis. In order to identify damage location and extent, dynamic curvature was calculated with midspan displacement. Parametric study on measurement noise level, damage location, damage extent, and multiple damage cases is performed, and the analysis results show both reliability and efficacy of this method in damage detection of bridge structures. At last, conclusions are drawn for its application to bridges in engineering practice.

Assessment of Prestress Force in Bridges Using Structural Dynamic Responses under Moving Vehicles

This study carries out numerical simulations to identify the magnitude of prestress force in a highway bridge by making use of the dynamic responses from moving vehicular loads. The prestressed bridges are modeled using four-node isoparametric flat shell element taking into account the transverse shearing deformation in the finite element model. The vehicle is modeled as a multiple degrees-of-freedom system. An approach based on dynamic response sensitivity-based finite element model updating is proposed to identify the elemental prestress force. The identified results are obtained iteratively with the penalty function method with regularization from the measured structural dynamic responses. A single-span prestressed Tee beam and two-span prestressed box-girder bridge are studied as two numerical examples. The effects of road surface roughness, measurement noise, and speed of moving vehicle on the identification results are investigated. Studies indicate that the proposed method is efficient and robust for prestress force identification. Good identified results can be obtained from several measured acceleration responses.

Effect of road surface roughness on the response of a moving vehicle for identification of bridge frequencies

Measuring the bridge frequencies indirectly from an instrumented test vehicle is a potentially powerful technique for its mobility and economy, compared with the conventional direct technique that requires vibration sensors to be installed on the bridge. However, road surface roughness may pollute the vehicle spectrum and render the bridge frequencies unidentifiable. The objective of this paper is to study such an effect. First, a numerical simulation is conducted using the vehicle-bridge interaction element to demonstrate how the surface roughness affects the vehicle response. Then, an approximate theory in closed form is presented, for physically interpreting the role and range of influence of surface roughness on the identification of bridge frequencies. The latter is then expanded to include the action of an accompanying vehicle. Finally, measures are proposed for reducing the roughness effect, while enhancing the identifiability of bridge frequencies from the passing vehicle response.

Using two connected vehicles to measure the frequencies of bridges with rough surface: a theoretical study

Measuring the bridge frequencies indirectly from a test vehicle is a potentially powerful technique for its advantage of efficiency and economy. However, the existence of road surface roughness may excite the vehicle-related frequencies to a higher level of amplitude than the bridge-related ones, making it difficult to identify the bridge frequencies. In order to overcome this drawback, this paper proposes the use of two connected vehicles to remove or reduce the blurring effect of road surface roughness, so as to ensure the successful identification of bridge frequencies. Underlaid by this idea, a Fourier-based algorithm for extracting the bridge frequencies is presented. Numerical studies are conducted for several different combinations of vehicle masses and stiffnesses, as well as for vehicle spacing. Through such a study, the feasibility of using two connected vehicles to extract the bridge frequencies is confirmed.

Prediction of vehicle-induced local responses and application to a skewed girder bridge

This paper proposes an innovative and flexible simulation method that predicts the dynamic responses of bridges induced by passing vehicles. The decoupled equations of motion of the vehicle–bridge system are derived from Lagrange equations and include the effect of road surface roughness, while the interaction forces between the two systems are calculated step by step, using Newmark’s method. This algorithm does not require a special finite element (FE) code and can be implemented with standard FE software and general numerical software such as ABAQUS and MATLAB, respectively. In order to illustrate the practicability of the method, an extensive case study is then presented in which some aspects of the dynamic behaviour of a skewed bridge monitored under vehicle-induced loads are investigated. After adjustment of the boundary conditions and the spectral roughness coefficient, good agreement is obtained between the bridge vibrations predicted by the numerical model and the field measurements. The validated model is further used to analyse the distinctive dynamic effects caused by the skewness. For that purpose, a reference non-skewed bridge model is prepared according to the same design as the original skewed bridge. The obtuse corner of the skewed bridge located near the loading path is found to be a critical region where the slab-negative moments, the girder stress near the sole plate and the bearing force are significantly greater than those in the reference bridge.

Effect of road surface roughness on indirect approach for measuring bridge frequencies from a passing vehicle

The indirect approach for measuring the bridge frequencies from the dynamic responses of a passing vehicle is a highly potential method. In this study, the effect of road surface roughness on such an approach is studied through finite element simulations. A two-dimensional mathematical model with the vehicle simulated as a moving sprung mass and the bridge as a simply-supported beam is adopted. The dynamic responses of the passing vehicle are solved by the finite element method along with the Newmark <TEX>${\beta}$</TEX> method. Through the numerical examples studied, it is shown that the presence of surface roughness may have negative consequence on the extraction of bridge frequencies from the test vehicle. However, such a shortcoming can be overcome either by introducing multiple moving vehicles on the bridge, besides the test vehicle, or by raising the moving speed of the accompanying vehicles.

Discussion of “Impact Factors for Horizontally Curved Composite Box Girder Bridges” by Khaled M. Sennah, Xuesheng Zhang, and John B. Kennedy

A discussion of an article with the aforementioned title, published in this journal (Vol. 9, No. 6, November/December 2004), is presented. The discusser comments on the complexity of vibration behavior of bridges due to moving vehicles, and seeks further information on the vehicle model and assumptions used in the original study. In the original study, the moving vehicle is treated as a pair of constant concentrated loads, and the effect of road surface roughness and the interaction between vehicle and bridge is not addressed. For straight box girder bridges, the authors suggest an impact factor of 0.6 for support reaction. The discusser questions the origin of such a high impact factor when the bridge deck is assumed to be smooth and the vehicle is simulated as a pair of constant concentrated forces.

Influence of road surface roughness on dynamic impact factor of bridge by full-scale dynamic testing

Effects of road surface roughness on the dynamic impact factor of bridge are investigated through full-scale field loading tests under controlled traffic conditions. The dynamic time histories of displacements are obtained for twenty-five bridges on Korean highways. The impact factors of the bridges are evaluated by using the measured displacements. The road surface profiles of the twenty-five bridges are also measured at every 10 to 30 cm interval in the span direction. By using the measured road surface profiles, the international roughness index (IRI) and the roughness coefficients of the bridges are evaluated. The linear regression and correlation analyses are performed to obtain the coherences between the IRI and the roughness coefficient and between the IRI and the impact factor. The sample correlation coefficients between the impact factor and the IRI and between the impact factor and the roughness coefficient are calculated to be 0.61 and 0.62, respectively, showing a strong coherence between the road surface roughness and the impact factor.Key words: bridge, impact factor, road surface roughness, international roughness index, roughness coefficient.

Dynamic behaviour of high-sided road vehicles subject to a sudden crosswind gust

High-sided road vehicles are susceptible to a sharp-edged crosswind gust, which may cause vehicle accidents such as overturning, excessive sideslip, or exaggerated rotation. This paper thus investigates the dynamic behaviour and possible accidents of high-sided road vehicles entering a sharp-edged crosswind gust with road surface roughness and vehicle suspension included. The high-sided road vehicle is modelled as a combination of several rigid bodies connected by a series of springs and dampers in both vertical and lateral directions. The random roughness of road surface is generated from power spectral density functions for various road conditions. The empirical formulae derived from wind tunnel test results are employed to determine aerodynamic forces and moments acting on the vehicle. After the governing equations of motion are established, an extensive computation work is performed to examine the effects of road surface roughness and vehicle suspension on the dynamic behaviour and vehicle accidents. It is demonstrated that for the high-sided road vehicle and wind forces specified in the computation, the accident vehicle speed of the road vehicle running on the road of average condition is relatively smaller than that running on the road of very good condition for a given crosswind gust. The vehicle suspension system should be taken into consideration, and the accident vehicle speed becomes smaller if the vehicle suspension system has softer springs and lighter dampers.