Traffic Load Effects Research Articles

Steady-State Data Baseline Model for Nonstationary Monitoring Data of Urban Girder Bridges

In bridge structural health monitoring systems, an accurate baseline model is particularly important for identifying subsequent structural damage. Environmental and operational loads cause nonstationarity in the strain monitoring data of urban girder bridges. Such nonstationary monitoring data can mask damage and reduce the accuracy of the established baseline model. To address this problem, a steady-state data baseline model for bridges is proposed. First, for observable effects such as ambient temperature, a directional projection decoupling method for strain monitoring data is proposed, which can reduce the nonstationary effect of ambient temperature, and the effectiveness of this method is proven using equations. Second, for unobservable effects such as traffic load, a k-means clustering method for steady state of traffic loads is proposed; using this method, which can divide the steady and nonsteady states of traffic loads and reduce the nonstationary effect of traffic loads on strain monitoring data, a steady-state baseline model is established. Finally, the effectiveness of the steady-state baseline model is verified using an actual bridge. The results show that the proposed baseline model can reduce the error caused by nonstationary effects, improve the modelling accuracy, and provide useful information for subsequent damage identification.

On the load-carrying capacity produced by different load models for road bridges

The evaluation of existing bridges is an important process and source of information within the bridge management system. Except for the load-carrying capacity represents the basic evaluation parameter, it moreover expresses a relevant and decisive parameter for the transition of actual road traffic. The paper presents the continuation of an already published analytical study aimed at comparing the effects of traffic load produced by different load models on road bridges. There are presented calculated load-carrying capacities for model cases of bridges with an upper deck with eight alternative spans and six different cross-sectional arrangements. On each of them, multiple load models simulating the effects of traffic were considered, while a certain predefined part of the considered load represented the required weight of the vehicle defining the load-carrying capacity of the respective bridge. The discussion is mainly focused on the pitfalls and possibilities of correctly defining the dependence of the weight of the vehicle representing the load-carrying capacity from the traffic load consideration schemes themselves, which are mostly defined by design codes.

Effects of Traffic Loading on Seasonal Temperature Change-Induced Problems for Integral Bridge Approaches and Mitigation with Geosynthetic Reinforcement

Effects of Traffic Loading on Seasonal Temperature Change-Induced Problems for Integral Bridge Approaches and Mitigation with Geosynthetic Reinforcement

An improved micro model for stochastic traffic load simulation with consideration of axle load and microscopic behavior

Simulating the stochastic traffic load has been an important issue for bridge condition evaluation. This paper proposes an improved cellular automaton for stochastic traffic load simulation with consideration of axle load and microscopic interaction. The cells, neighbors, transition rules and boundary conditions in the improved model are all redefined. The cell length can be manually defined with any value. The vehicle load can be precisely simulated using axle load if the cell length is set small or using concentrated load when a large cell length is defined. Acceleration based transition rules are proposed, and different acceleration for each vehicle can be computed to more reasonably simulate the microscopic behavior. The feasibility of the proposed model is validated through comparisons on traffic flow simulation and load effect quantification with in-field weigh in motion data and other models. The results indicate that the proposed model improves the existing models both in vehicle load simulation and traffic flow simulation and can be used for stochastic traffic load simulation for bridges with any length.

Discussion and analysis on the improvement of the widening technology of cement concrete pavement of rural highway

ABSTRACT In order to improve the widening technology of cement concrete pavement of rural highway, this paper further studies the blockage simulation process of permeable concrete pavement. Moreover, this paper separately studies various external conditions such as sediment gradation, horizontal runoff velocity, seepage velocity, porosity, etc., and reveals the mechanism of pore blockage in permeable pavement. After decades of self-gravity consolidation and the effect of traffic load on the subgrade of the rural old road, the consolidation of the old road has been basically completed. At the same time, after the new road is built, due to its own load and vehicle load, it gradually generates its own settlement, resulting in differential settlement of the old and new subgrade. In addition, this paper explores this difference through digital simulation, and puts forward several suggestions in combination with the simulation model. Finally, on this basis, this paper verifies the method proposed in this paper through experimental research. The research results show that the improvement strategy proposed in this paper is suitable for the widening construction of cement concrete pavement of rural highway.

An extreme value prediction method based on clustering algorithm

Extreme value prediction has been widely applied in many safety-critical scenarios. Due to the influence of mixed types of events, the random variables oftentimes do not comply with the independence and identical distributions. Neglecting the mixed distribution characteristics of these variables may lead to inaccurate extreme value prediction. To solve this problem, this study proposes a novel clustering algorithm based on the generalized extreme value mixture model (GEVMM). The algorithm adaptively classifies the block maximum data into different clusters and synthesizes the clusters according to their weights in the population, thus forming a GEVMM that can predict the maximum values in a given return period. The elbow method combined with root mean squared error (RMSE) and coefficient of determination (R-squared) is used to select the optimal number of clusters to prevent over- and under-fitting the model. Through theoretical examples, the proposed method shows strong applicability to promote the accurate extrapolation of extreme values regardless of overlap among the original mixture components. To demonstrate the practical application of the proposed approach, traffic load effects on bridges based on weight-in-motion data are used to extrapolate extreme values during a specific return period. The process and results show that the developed approach is more reliable for estimating extreme values with mixed probability distribution as compared with existing methods. It also provides a powerful tool for extreme value analysis of mixed distribution data in other fields.

Study on the Skid Resistance Deterioration Behavior of the SMA Pavement

The skid resistance of asphalt pavement is of great importance to the driving safety, but deterioration of pavement skid resistance is inevitable owing to the coupling effect of traffic loading and climate conditions. The existing prediction models of skid resistance were mainly established based on the laboratory accelerated polishing tests (for instance Polished Stone Value, PSV), and these models can only consider the influence of a single factor; they fail to reflect the coupling effect of different factors under the real service condition. For the purpose of investigating the influences of seasonal variation, and aggregate type on the skid resistance of asphalt pavement, the skid resistance of three test tracks were continuously measured for 48 months through five different test methods. The results show that different test methods exhibit significant inconsistency. The aggregate type is the internal factor that determines the long-term skid resistance performance of pavement. The skid resistances of the selected test tracks were ranked as greywacke pavement > diabase pavement > rhyolite pavement. This is in well agreement with the ranking of aggregate polishing resistance obtained from the laboratory Wehner/Schulze (W/S) test. This indicates that the W/S test is effective in distinguishing the aggregates that used in pavement construction. It is also found that the skid resistance of asphalt pavement shows significant fluctuation with respect to seasonal variation. The skid resistance is generally high in autumn and low in summer. Therefore, it is suggested to use the low measurement value of skid resistance in summer as the lower limit for the evaluation and prediction of the skid resistance performance of asphalt pavement.

Development of pavement roughness models using Artificial Neural Network (ANN)

ABSTRACT Pavement roughness in terms of the International Roughness Index (IRI) plays an important role in determining the riding quality of road networks. Moreover, it is considered as a pavement performance measure and a determinant of the optimal time for pavement Maintenance and Rehabilitation (M & R). Due to the high cost of evaluating pavement roughness using automated devices, it is crucial to find a suitable alternative method with low cost and high accuracy, especially in developing countries. The main objective of this research was to develop pavement roughness models using the Artificial Neural Network (ANN) based on smartphone measurements. The effects of pavement age, traffic loading, and traffic volume on the IRI values were investigated. The results of ANN model development showed that ANN is promising to predict the future IRI with a relatively low average error of less than 10%. M & R alternatives were also suggested based on the present and predicted IRI values. The predicted alternatives using ANN showed a relatively low average error (less than 15%) compared to the actual M & R alternatives. The comparison result between regression and ANN models showed that developed ANN models were more accurate in IRI prediction than the regression models.

An analytical solution to traffic loads on long span bridges

The paper deals with the prediction of extreme values of traffic loads and load effects of long span bridges. The traffic states are idealized a series of spatially stationary stochastic fields, which correspond to free, congested and full stop traffic states. For each traffic state, the Poisson point field is invoked to model the spatial distribution of vehicles. The vehicle density is then determined initially by the empirical formula based on microsimulation and modified further by a Poisson point model with a limited minimum space lag. With the modified vehicle density and influence functions of the bridge response, the expressions of the mean values and variances of the traffic loads or load effects are derived based on Poisson model, which are very simple compared with Ditlevsen’ formulas. Because the bridge loads are the sum of a large number of independent vehicle weights, the normal distribution is a reasonable model for loads and load effects. Correspondingly, the long term characteristic values and distribution functions of traffic loads and load effects are estimated easily with the derived mean and variance . The numerical analyses show that all results calculated are very close to those by the popular microsimulation methods. Hence, an analytical method is developed for predicting the traffic loads and load effects, which can be easily used to develop a design code for a long span bridge. Moreover, the analytical method based on Poisson models incorporated with the normal distribution of loads or load effects would make it more easily combine the traffic loads with wave and wind loadings for a floating bridge.

Fatigue damage evaluation of steel bridges considering thermal effect

With the change of external environmental factors, thermal loads are changing and causing fluctuating thermal stresses in critical fatigue details of steel bridges, which contribute to fatigue damage cumulation significantly. This paper proposed two fatigue evaluation methods considering the coupling effects of traffic load and thermal load: (1) Evaluation based on vehicular fatigue load model (VFLM) and thermal fatigue load model (TFLM). (2) Evaluation based on measurements of thermal load and traffic load. The analytical approach for obtaining the thermal fatigue load model was introduced, and the concept of the coupling stress model of ‘wave-surfer model’ was set up according to the mechanism of fatigue damage cumulation. Taking a steel box girder bridge as a case study, the collections of temperature data and traffic information were carried out. The two evaluation methods based on different load information were applied to two typical fatigue details, and the corresponding fatigue damage was calculated, which demonstrates that thermal effects should be taken into account for fatigue evaluation.

Investigation of multiple-presence factor for traffic loads on road-rail bridges based on a novel extreme value analysis approach

Multiple-presence factor (MPF) is an efficient measure for calculating traffic load effects on bridges with multiple lanes. It takes into account the probability of multiple heavy vehicles that simultaneously present in adjacent lanes. Though road-rail bridges carrying both road and rail traffic are common in modern cities, no sophisticated method is available to obtain the MPFs for the combined traffic loads. This study presents a novel extreme value analysis approach to predict the extreme load effects on road-rail bridges and investigate the corresponding MPFs. The core of the new approach is an unsupervised clustering algorithm based on a generalized extreme value mixture model (GEVMM), which can fit data with mixed distribution characteristics and can predict extreme values. The road-vehicle flow is represented by vehicle parameters and traffic parameters. The train flow is generated based on the distribution of passenger volume and train schedule. The 1000-day load effects on road-rail bridges with various spans are simulated and then used to predict the maximum load effects in 100 years based on the proposed method and the conventional generalized extreme value (GEV) approach, respectively. The comparison among the predicted maximum load effects and those obtained from the simulated 100-year road-rail traffic flow shows that the proposed approach is more reliable than the conventional GEV approach. Then the MPF values of the road-rail bridges are calculated from the predicted maximum load effects during a specified return period of 2000 years. The proposed method provides a valuable reference for the design and evaluation of road-rail bridges with various spans.

The Effect of Temperature, Rest Periods and Ageing on the Response of Bituminous Materials in Fatigue Tests: Considerations and Proposals on Analytical Dimensioning Models.

One of the basic assumptions of analytical dimensioning models of asphalt pavements is failure due to fatigue cracking of the bituminous layers. Furthermore, it is considered that the damaging effects of different traffic loads are linear and cumulative, per Miner’s law. However, the analysis carried out on the effect of temperature, rest periods, and ageing of the bituminous materials questions considering fatigue failure as the only and main assumption for the calculation of the pavement life. Ageing of the pavement asphalt layers results in stiffening and transverse cracking. Consequently, these asphalt layers are no longer of infinite extent in the horizontal direction and their response resembles that of a slab. The application of this last calculation assumption provides pavement sections more in line with those used in Spain in the Catalogue of Structural Sections, which is based on experience gained from the real behavior of those sections. The calculation based on the fatigue laws results in undersized structures. This paper shows the results of a strain sweep test implemented at the UPC Roads Laboratory, which was used to analyse all the aforementioned effects and to propose a calculation procedure for heavy traffic pavements considering transverse cracking of the asphalt layers.

Analysis of the Coupling Effect of Thermal and Traffic Loads on Cement Concrete Pavement with Voids Repaired with Polymer Grout

Under the repeated action of traffic and thermal loads, a cement concrete pavement slab may partially lose contact with its base course, and voids may develop underneath the slab. Such distress will greatly impact the pavement performance. To fill the voids and restore the base support to the slab, the technology of polymer grouting has been increasingly adopted in recent years due to its advantages of quick application and high efficiency. There is, however, a lack of research on the mechanistic responses and performance of such a repaired rigid pavement under coupled influences of thermal and traffic loads. Existing literature has mainly focused on normal cement concrete pavement structures (i.e., without polymer grouted voids). This study intends to fill the research gap by investigating the time-domain characteristics of thermal stress response of a cement concrete pavement with underlying voids filled with polymer grout, along with design traffic loads. The finite element method was adopted with a 3-dimensional nonlinear temperature field within the pavement. A program module was developed in the Abaqus FEA software environment for temperature effect analysis. It was found that under the coupling action of thermal and traffic loads, thermal stress had a greater influence on the critical slab stress at the slab corner than those at other slab locations. Through the comparative analysis before and after polymer grouting repair, the critical tensile stress at the slab corner under the vehicle and thermal loads can be effectively reduced. The polymer performance is stable after three years.

Time-Dependent Reliability Assessment and Updating of Post-tensioned Concrete Box Girder Bridges Considering Traffic Environment and Corrosion

AbstractIn the reliability assessment of a bridge in operation with regards to its ultimate limit state, it should be noted that the strengths of members and effects of traffic load vary continuous...

PENGARUH BEBAN LALU LINTAS TERHADAP KERUSAKAN LENTUR DI JALAN TOL BERDASARKAN METODE PAVEMENT CONDITION INDEX (Studi Kasus Ruas Lingkar Luar Jakarta (JORR) W2 Utara Jalur A dan B)

Jorr toll road function as a network of roads that serves to break down the traffic that currently accumulates in the city of Jakarta, so that this toll road will facilitate the flow of traffic from bogor / Jagorawi towards Tangerang / Merak, and vice versa. With the perfect JORR, it will be one of the alternatives to Soekarno-Hatta International Airport. Jakarta W2 Utara Outer Ring Road is often crowded with traffic during certain hours. So in the field there are many locations of pavement damage where as large in the lane of heavy-laden and overloaded vehicles. Differences in traffic load can cause different levels of road damage between lanes. The extent of road damage can be evaluated by using the PCI method. The purpose of this study is to evaluate the effect of traffic load on flexible damage based on PCI method with the level and type of damage in each lane can be identified.

Temporal global sensitivity analysis of concrete sewer pipes under compounding corrosion and heavy traffic loads

During their lifetime, sewer networks face risks of infiltration or exfiltration, restriction of flow capacity, and loss of structural integrity. These factors individually or combined can impact the public health and the environment. This study is aimed at analyzing uncertainties contributing to the service life performance of sewer pipes under compounding effects of corrosion deterioration and traffic loads using a global sensitivity analysis (GSA). The specific goals are to identify significant sources of uncertainty, and to quantify and rank their time-varying significance for extended time horizons. The study considers a comprehensive set of uncertain environmental, structural, and geotechnical variables. Results indicate that among all the material properties, tensile and compressive strength of concrete are the most influential parameters over the entire service life of sewer pipes. According to the results, the significance of environmental variables varies considerably with time. Dissolved sulfide concentration and pH-dependent factor for the proportion of in wastewater significantly affect infiltration/exfiltration for pipes that are older than 30 years. Variables contributing to truckload including the truck weight and multiple presence factor are also found to be significant.

Predicting method on settlement of soft subgrade soil caused by traffic loading involving principal stress rotation and loading frequency

Since the alarming settlement of transport infrastructures on soft subgrade caused by long-term traffic loading, a method for predicting settlement is of considerable significance in the engineering design. In this study, we proposed a practical and simple predicting method on the settlement of soft subgrade considering traffic loading effects. The model used in this method involves the principal stress rotation and loading frequency, which needs only four parameters with clear meaning obtained by several cyclic triaxial tests. The applicability of the model has been verified by previous results from other researchers. Moreover, the engineering practicality of this method was validated by the field data of a highway. The settlements under low-frequency and high-frequency are the upper limit and lower limit of the traffic load-induced settlements, respectively. With the increasing embankment thickness, the settlements decrease because the cyclic stress ratio decreases and the detrimental effect of the principal stress rotation on the settlement reduces. The vehicle load is a more influential factor in the settlement than the traffic volume.

Effects of poly-sulfide regenerant on the rejuvenated performance of SBS modified asphalt-binder

ABSTRACT Styrene-butadiene-styrene (SBS) block copolymer modified asphalt-binder (SBSMA) is one of the commonly used asphalt-binders in the upper layers of asphalt pavements. Continuous environmental exposure along with the combined effects of traffic loading during the pavement’s service life means high susceptibility to aging and degradation over time. Exploration of innovative methods to enhance the resilience of SBSMAs and improve the overall performance of asphalt pavements is thus inevitable. This study investigated the rejuvenation effects of poly-sulfide on aged SBSMA using molecular dynamic simulations and laboratory experimentation including the dynamic shear rheometer (DSR) and Fourier-transform infrared spectroscopy (FTIR) tests for evaluating the rheological properties and chemical compositions, respectively. In the study, the following parametric properties were determined and quantified, namely the diffusion coefficient, viscosity, solubility, and rutting factor of SBSMA. The corresponding results exhibited higher diffusion coefficient for the rejuvenated SBSMA over SBS and the asphalt-binder components. Overall, the study findings indicated that poly-sulfide, at dosages less than 8.0wt%, can potentially rejuvenate aged SBSMA and enhance its rheological properties. Additionally, the simulated results were found to be comparable to the laboratory test results.

Bayesian Updates for an Extreme Value Distribution Model of Bridge Traffic Load Effect Based on SHM Data

As the distribution function of traffic load effect on bridge structures has always been unknown or very complicated, a probability model of extreme traffic load effect during service periods has not yet been perfectly predicted by the traditional extreme value theory. Here, we focus on this problem and introduce a novel method based on the bridge structural health monitoring data. The method was based on the fact that the tails of the probability distribution governed the behavior of extreme values. The generalized Pareto distribution was applied to model the tail distribution of traffic load effect using the peak-over-threshold method, while the filtered Poisson process was used to model the traffic load effect stochastic process. The parameters of the extreme value distribution of traffic load effect during a service period could be determined by theoretical derivation if the parameters of tail distribution were estimated. Moreover, Bayes’ theorem was applied to update the distribution model to reduce the statistical uncertainty. Finally, the rationality of the proposed method was applied to analyze the monitoring data of concrete-filled steel tube arch bridge suspenders. The results proved that the approach was convenient and found that the extreme value distribution type III might be more suitable as the traffic load effect probability model.

The effects of aural and visual factors on appropriateness ratings of residential spaces in an urban city.

This study investigates the aural and visual factors that influence appropriateness perception in soundscape evaluations in residential spaces, where people may spend most of their time in. Appropriateness in soundscape is derived from the expectation of sound sources in a specific environment, place or function heard by a listener. Appropriateness of soundscapes in 30 locations in an urban residential environment is investigated with varying landscape, visual and aural elements through a questionnaire. Participants experienced the soundscape in-situ and were asked to evaluate the appropriateness of soundscape as well as the dominance of specific sound sources such as traffic, human activities and birdsongs in the residential space. The effect of type of traffic on appropriateness is also investigated. A strong relationship is found between appropriateness and affective soundscape qualities such as pleasantness, highlighting the importance of considering appropriateness in soundscape research. In audio-visual combination of specific elements and the partial correlation with appropriateness, specific aural sound sources are found to correlate uniquely to appropriateness while controlling for relevant visual elements, whereas visual elements became redundant in its partial correlation to appropriateness. Residents' perception of appropriateness is found to likely be more dependent on the individual visual elements rather than the overall landscape. This study investigates the factors that influences appropriateness perceptual in soundscape evaluations in residential spaces, where people may spend most of their time in. Appropriateness in soundscape is derived from the expectation of sound sources in a specific environment, place or function and heard by a listener. The appropriateness of soundscapes of 30 locations in an urban residential environment is investigated with varying visual (greenery, building, waterbody) and aural elements through a questionnaire approach. Participants experienced the soundscape in-situ and were asked to evaluate the appropriateness of soundscape as well as the dominance of specific sound sources such as traffic, human activities and birdsongs in a residential space. The type of traffic is also investigated to explore the effect of traffic load on appropriateness.