Highway Structures Research Articles

Flexural Fatigue Properties of Ultra-High Performance Engineered Cementitious Composites (UHP-ECC) Reinforced by Polymer Fibers.

In recent years, the application of engineered cementitious composites (ECCs) in structures subjected to cyclic fatigue loading, such as highway bridges, has gained widespread attention. However, most existing ECCs do not have sufficient strength and ductility, which limits their applications, especially in highway bridge structures under high-stress. In this work, an ultra-high performance engineered cementitious composite (UHP-ECC) was configured, which had a compressive strength of approximately 120 MPa, a tensile strength of up to 12 MPa, and a tensile strain capacity of more than 8%. This paper presents a study of the fatigue performance of UHP-ECC at four different fatigue stress levels through the four-point bending test. The mid-span deflection of the specimen was monitored along with the crack opening displacement (COD) of the pure bending section at the bottom of the specimen, and the crack width. In addition, the dissipated energy was calculated at various stress levels. The progressive formation of cracks under static loading was monitored using the digital image correlation (DIC) technique. The fibers at the fractured surface of the specimens were observed and analyzed by environmental scanning electron microscopy, and the morphology of the fibers was obtained at different fatigue stress levels. Eventually, the fatigue life under different stress levels was obtained, and the relationship between the fatigue life and the stress level was established.

Innovative method for recognizing subgrade defects based on a convolutional neural network

Subgrade defects originate below the base of an asphalt pavement and they contribute significantly to pavement damage. The detection of subgrade defects is considered challenging because the recognition of defects is difficult. Therefore, the utilization of ground penetrating radar (GPR) to detect subgrade defects has attracted significant interest in recent years. However, the use of manually processed GPR images for classifying defects is inefficient and inaccurate. Thus, in this study, we applied convolutional neural networks (CNNs) to GPR images for automatically classifying subgrade defects (e.g., uneven settlement, sinkholes, and subgrade cracks). Two CNNs called multi-stage CNN and cascade CNN with different structures were established to accomplish the tasks automatically. The main difference between the two CNNs is that the cascade CNN is a classifier 2, which is for recognition and trained only using hard samples. Each CNN was developed in training, validation, and testing processes. Based on the training and testing results, sensitivity analysis was performed to verify the stability of the CNNs. We compared state-of-the-art methods for defect detection and the CNN-based method in order to verify the superior performance of the CNNs. Finally, we tested an application of the CNN-based method to show that it is transferrable to other asphalt pavements. The training results indicated that the cascade CNN classified subgrade defects with 97.35% accuracy during training and 96.80% in validation, while the multi-stage CNN classified subgrade defects with 91.35% accuracy during training and 90.45% in validation. The sensitivity analysis results showed that the cascade CNN exhibited the expected stability in terms of the transmitting frequency, i.e., the frequency of a high-frequency electromagnet wave from the transmitting antenna of the GPR, and different highway structures, whereas the multi-stage CNN did not. In addition, compared with Sobel edge detection and K-value clustering analysis, the CNN-based method obtained more robust performance at subgrade defect detection under various conditions using raw images. These results indicate that the CNN-based method performs well and it can classify subgrade defects in realistic situations.

An Electromagnetism-like Algorithm to Solve Three-dimensional Highway Alignment Problem

Road alignment design is an important determinant of the development cost of road networks. On the one side, it affects road construction and maintenance costs, which constitute a significant part of country-wide infrastructure development, management and operation budget each year. On the other side, it affects road user-related costs of travel time and vehicle use, which comprise a significant portion of the total transportation cost. This study adapts the existing Electromagnetism-like meta-heuristic algorithm to solve a three-dimensional highway alignment problem, which explores and finds a good route between two given points on a terrain. It detects the potentials of the given initial routes, which are enhanced and shaped toward better positions by the help of the local and global search. The final good solution is, then, fine-tuned for a better alignment. Several example problems are designed to show the behavior of the algorithm. The results show that the algorithm satisfactorily maneuvers to by-pass obstacles, and build highway structures where necessary. The set of the example problems in this paper may also serve to found a basis for evaluation of the performance of alternative algorithms

Highway Construction of Soft Soil Foundation Processing Analysis

Highway is an important channel to connect regional economic development, and is an indispensable part of modern transportation system. In view of the extensive nature of highway cover space and the existence of diversified construction environment, climate and geological influence in highway construction, soft soil foundation is one of the more typical geological forms. With wide distribution in our country, seen as a big difficulty, highway construction technology and directly affect the quality of highway construction, cost, if not properly handled, will cause the soft soil foundation highway engineering structure is not stable, prone to accidents in use. In this paper, we study the treatment of soft soil foundation in highway construction, and put forward some reasonable Suggestions.

Particle Swarm Optimization for Active Structural Control of Highway Bridges Subjected to Impact Loading

The application of active structural control technology to highway bridge structures subjected to high‐impact loadings is investigated. The effects of high‐impact loads on infrastructure, like heavy vehicle collisions with bridge piers, have not been studied as much as seismic load effects on structures. Due to this lack of research regarding impact loads and structural control, a focused study on the application of active control devices to infrastructure after impact events can provide valuable results and conclusions. This research applies active structural control to an idealized two‐span, continuous girder, concrete highway bridge structure. The idealization of a highway bridge structure as a two degree‐of‐freedom structural system is used to investigate the effectiveness of control devices installed between the bridge pier and deck, the two degrees of freedom. The control devices are fixed to bracing between the bridge pier and girders and controlled by the proportional‐integral‐derivative (PID) control. The PID control gains are optimized by both the Ziegler–Nichols ultimate sensitivity method (USM) and a new method for this impact load application called particle swarm optimization (PSO). The controlled time‐domain responses are compared to the uncontrolled responses, and the effectiveness of PID control, USM optimization, and PSO is compared for this control device configuration. The results of this investigation show PID control to be effective for minimizing both superstructure and substructure responses of highway bridges after high‐impact loads. Deck response reductions of greater than 19% and 37% were seen for displacement and acceleration responses, respectively, regardless of the performance index used to analyze them. PSO was much more effective than USM optimization for tuning PID control gains.

Short-Term Traffic Flow Prediction of Highway Network Based on Network-Constrained Lasso and NN

Accurate and timely traffic flow prediction is important for the successful deployment of intelligent transportation systems. Most of existing methods have not made good use of information from adjacent sections to analyse the trends of the object section. A new method for traffic flow prediction of highway network, namely network-constrained Lasso (Least absolute shrinkage and selection operator) and Neural Networks, was proposed. Unlike existing methods, our approach incorporated all the spatial and temporal information available in a highway network to carry our short-term traffic flow prediction for the objective section. To capture the spatial correlation of traffic network, the Laplacian matrix was introduced to describe the highway network structure. Subsequently, a network-constrained Lasso method was applied for sparse variable selection. With the extracted historic and real-time data, the back propagation neural networks were implemented to predict traffic flow at different time intervals in future. The experimental results verified that the proposed method could achieve above 90% average accuracy in the 30-minutes speed predictions for 78 road sections.

PROBABILITY MODEL AND RELIABILITY ANALYSIS OF CABLE STRESS FOR CABLE-STAYED BRIDGE

The aim of this paper is to investigate the time-varying effect of stay cable of long-span cable-stayed bridges subject to vehicle load. The analysis has been carried out on the Su-Tong cable-stayed bridge in Jiangsu, China that has the second-longest span among the completed composite-deck cable-stayed bridges in the world currently. Probability models of vehicle load in each lane (fast lane, middle lane and slow lane) and cable stress under random vehicle load were developed based on the stochastic process theory. The results show the gross vehicle weight follows lognormal distribution or multi-peak distribution, and the time-interval of the vehicle follows a lognormal distribution. Then, the probability function of maximum cable stress was determined using up-crossing theory. Finally, the reliability of stay cable under random vehicle load was analysed. The reliability index ranges from 9.59 to 10.82 that satisfies the target reliability index of highway bridge structure of finished dead state.

CHARACTERISTICS OF GLASS FIBRE REINFORCED ASPHALT CONCRETE FOR HIGHWAY PAVEMENT DURABILITY

Fibres have been reported to improve the performance of asphalt against some pavement distresses and have the potential to improve the cohesive and tensile strength of asphalt. Laboratory investiga-tion of the characteristics and properties of glass fibre reinforced asphalt was conducted. Specimens were produced and tested for Stability using Marshall Test. The optimum bitumen content for the con-trol was also determined. Glass fibre of 12 mm length in the range of 0.2 – 0.8% by weight were added to the mix, volumetric parameters were examined using Asphalt Institute specification. Voids in Total Mix was used to determine if there is significant difference in the mean using one-way ANOVA at 5% probability level. The result showed that the penetration of the modified bitumen are lower and there is increase in the optimum bitumen content when compared with the control. Voids in mineral aggregate decreases by 2.72, 1.60, 5.92 and 6.98% when 0.2, 0.4, 0.6 and 0.8% fibre respectively were added. Voids in total mix for both the control and modified asphalt showed no significant difference. The volu-metric parameters falls within the specification. The modified glass fibre would greatly enhance the durability and longevity of highway pavement structures.

Lessons learnt from the December 2015 flood event in Cumbria, UK

The December 2015 floods in Cumbria, north-west England, UK, were preceded by 3 weeks of extremely wet weather, which prompted the highway bridge management team of Cumbria County Council to review their response procedures. The events of 4–6 December proved that the council’s procedures were up to the task of protecting the public from the risks of road flooding and bridge collapse, but that their resources were overstretched by the scale of the damage and the need to assess accurately the condition of closed bridges before they could be returned to service. After a year of inspections and damage reviews, measures have been identified to improve the resilience of the bridge stock, but potential areas for improvement exist in the methodology currently mandated for the assessment of risk to highway structures. It is hoped that this paper will act as a prompt to review these methods and give the guidance needed to identify the more significant factors that contribute to the overall safety of bridge structures, so that maintaining authorities can focus their efforts, and limited resources, more effectively.

ROADKILL IN THE BRAZILIAN CERRADO SAVANNA: COMPARING FIVE HIGHWAYS IN SOUTHWESTERN GOIÁS

This study described and analyzed the roadkill of native vertebrates in the southwest of the Brazilian State of Goias, evaluating the influence of the seasonal variation in climate and the influence of highway structure (e.g., two lane/one lane routes, road conditions). In this context, we collected samples each month over a one-year period on five of the region's highways, all of which originate in the town of Jatai, linking it to the neighboring towns of Acreuna, Apore, Itaja, Doverlândia and Portelândia. We recorded 1113 individuals (0.115 individuals/km/year), including nine amphibians, 55 reptiles, 223 birds,and 826 mammals. The two-lane highway had the highest species richness and abundance, and was significantly different from the other roads. We also found significant seasonal differences in overall abundance, and the species richness and abundance of the herpetofauna, with a greater number of collisions occurring during the rainy season. Over the long term, programs of environmental education - especially during the rainy season - may help to raise the awareness of drivers.

Model for practical prediction of natural carbonation in reinforced concrete: Part 1-formulation

A model is proposed for prediction of natural carbonation in reinforced concrete (RC) structures, and is potentially applicable to existing and new RC structures. The major components of the model comprise mathematical functions applied to predict the influence of concrete composition, and environmental factors on natural carbonation.This paper introduces the model concept and explains its structure including derivation, optimization and calibration. Over 163 data sets taken from a 10-year carbonation study were used in the model development and calibration. Only the experimental data that were based on outdoor natural exposure environment were employed in this research. Also in this study, the proposed model is compared with fib-Model Code 2010 using carbonation predictions generated from 346 data sets involving real world, highway structures. It is shown that the proposed model is comparably accurate and involves mainly basic tests with no major anticipated costs.

Effect of post weld heat treatment on steel plate deck with trough rib by portable heat source

A lot of cases have been reported that fatigue cracks occur from welded parts between steel deck plates and trough ribs of highway bridge structures. In order to improve fatigue life of this kind of welded parts, welding residual stress release by post weld heat treatment is examined. A general heat treatment method by a heating furnace is not available because steel plate deck structures are so large. Therefore, applicability of a sheet-type ceramic heater as a portable heat source is investigated. A heat treatment experiment was carried out on test specimens modeling a steel plate deck with a trough rib. The effect of tensile stress release was elucidated by measuring welding residual stress and stress distribution after the heat treatment. On the other hand, the experiment was simulated by a thermal elastic plastic analysis for proposing an analysis model for simulation of heat treatment process by the sheet-type ceramic heater. Based on the experimental and analytical results, a residual stress release method for the welded parts between the deck plate and the trough rib by the portable heater was examined. Furthermore, the effect of fatigue life improvement by the stress release due to heat treatment on the specimens was investigated.

Statistical Modeling of the Default Mode Brain Network Reveals a Segregated Highway Structure

We investigate the functional organization of the Default Mode Network (DMN) – an important subnetwork within the brain associated with a wide range of higher-order cognitive functions. While past work has shown the whole-brain network of functional connectivity follows small-world organizational principles, subnetwork structure is less well understood. Current statistical tools, however, are not suited to quantifying the operating characteristics of functional networks as they often require threshold censoring of information and do not allow for inferential testing of the role that local processes play in determining network structure. Here, we develop the correlation Generalized Exponential Random Graph Model (cGERGM) – a statistical network model that uses local processes to capture the emergent structural properties of correlation networks without loss of information. Examining the DMN with the cGERGM, we show that, rather than demonstrating small-world properties, the DMN appears to be organized according to principles of a segregated highway – suggesting it is optimized for function-specific coordination between brain regions as opposed to information integration across the DMN. We further validate our findings through assessing the power and accuracy of the cGERGM on a testbed of simulated networks representing various commonly observed brain architectures.

Reduced partial factors in UK standards for assessment of bridges and structures

Structural engineering design standards are based on a range of input variables for resistance, action and modelling. The distribution type and parameters for each determine the partial factors appropriate to achieve a defined reliability level over a specified reference period. For the assessment of existing bridges and structures, a reduced reliability level may be accepted due to the greater cost of providing reliability through strengthening when compared with the cost of providing it at design. This would allow the use of lower partial factors, although they are still limited by the need to provide a minimum level for human safety. Adoption of this approach for assessment would have significant benefits for an ageing UK infrastructure by reducing the need to carry out costly strengthening and retrofitting schemes while still ensuring appropriate structural reliability levels are maintained. This paper presents a study investigating appropriate reduced partial factors to be applied through UK highway structure assessment standards, the sensitivity of these values to input distribution model assumptions and how they could be implemented in industry.

Passive Vibration Mitigation for Highway Sign Trusses Susceptible to Wind-Induced Vibrations

AbstractStockbridge-type tuned-mass dampers are commonly used in highway sign and traffic signal support structures throughout the U.S. to reduce wind-induced and truck gust–induced vibrations. Eff...

Monitoring and evaluating techniques of highway subgrade safety in the operation period

Operation safety of highway subgrade structure has become the most concerned issue which needs to be solved. Depending on the operational connotation requirements of the subgrade safety, a lot of investigations, and indoor and outdoor experimental and theoretical analyses are carried out. Based on the subgrade overall stability and pavement performance, the embankment safety monitoring technology and the early warning system are established, as well as the subgrade structure safety evaluation index and standard under typical working conditions. Highway subgrade cracking displacement acquisition device with a function of real-time monitor and wireless transmission is researched and developed independently, and acquisition subgrade cracking displacement method is proposed. Integrating the project research results, the subgrade structural safety monitoring and maintenance management system with subgrade monitoring data analysis and forecasting, safety hazards identification, safety assessment and early warning, conservation decision-making functions are developed. Project research achievements have been used in highway subgrade stability of longevity and continuity of safety monitoring. They provide a scientific basis for formulating appropriate maintenance decisions.

Vibration of infinite Timoshenko beam on Pasternak foundation under vehicular load

The vibration of beams on foundations under a vehicular load has attracted wide attention for decades. The problem has numerous applications in several fields such as highway structures. However, most of analytical or semi-analytical studies simplify the vehicular load as a concentrated point or distributed line load with the constant or harmonically varying amplitude, and neglect the presence of the vehicle and the road irregularity. This article carries out an analytical study of vibration on an infinite Pasternak-supported Timoshenko beam under vehicular load which is generated by the passage of a quarter car on a road with harmonic surface irregularity. The governing equations of motion are derived based on Hamilton’s principle and Timoshenko beam theory and then are solved in the frequency–wavenumber domain with a moving coordinate system. The analytical solutions are expressed in a general form of Cauchy’s residue theorem. The results are validated by the case of an Euler–Bernoulli beam on a Winkler foundation, which is a special case of the current system and has an explicit form of solution. Finally, a numerical example is employed to investigate the influence of properties of the beam (the radius of gyration and the shear rigidity) and the foundation (the shear viscosity, rocking, and normal stiffness) on the deflected shape, maximum displacement, critical frequency, and critical velocity of the system.

Parametric seismic evaluation of highway overpass bridges in moderate seismic areas

Prior to modern seismic provisions, several bridges were not designed for seismic actions in moderate seismic areas. Precast multi-girder and slab bridges are typical highway overpass structures; they have a significant contribution to national bridge stocks. Since the seismic behavior is questionable, a preliminary parametric study is conducted to determine critical configurations and components. The results indicate that the behavior of the abutments, backfill soil, superstructure and foundation is normally satisfactory; however, the superstructure-abutment joints are critical for both single- and multi-span bridges, while the piers are also critical for longer multi-span configurations. The parametric results provide a solid basis both for detailed seismic assessment and development of design concepts of newly built structures in moderate seismic zones.

Autonomous image localization for visual inspection of civil infrastructure

Low-cost, high-performance vision sensors in conjunction with aerial sensing platforms are providing new possibilities for achieving autonomous visual inspection in civil engineering structures. A large volume of images of a given structure can readily be collected for use in visual inspection, overcoming spatial and temporal limitations associated with human-based inspection. Although researchers have explored several algorithms and techniques for vision-based inspection in recent decades, a major challenge in past implementations lies in dealing with a high volume of images while only a small fraction of them are important for actual inspection. Because processing irrelevant images can generate a significant number of false-positives, automated visual inspection techniques should be used in coordination with methods to localize relevant regions on the images. When combined, automated visual inspection will be able to meet the objectives and quality of human visual inspection. To enable this technology, we develop and validate a novel automated image localization technique to extract regions of interest (ROIs) on each of the images before utilizing vision-based damage detection techniques. ROIs are the portions of an image that contain the physical region of the structure that is targeted for visual interrogation, denoted as the targeted region of interest (TRI). ROIs are computed based on the geometric relationship between the collected images and the TRIs. Analysis of such highly relevant and localized images would enable efficient and reliable visual inspection. We successfully demonstrate the capability of the technique to extract the ROIs using a full-scale highway sign structure in the case where weld connections serve as the TRIs.

Experimental Study on Geosynthetic Reinforced Soil Dynamic Characteristics under Cyclic Loading

The technology of geosynthetic reinforced soil has been widely used in the structural strengthening of highway subgrade. Under the action of long-term vehicle cyclic loading, geosynthetic reinforced soil can effectively improve the bearing and deformation resistance capacity of the subgrade, improve the long-term stability of the highway structure and prolong the service period of the road. At present, the quasi-static method to design the geosynthetic reinforced subgrade under the action of traffic load is not perfect enough, the research on dynamic property, design theory and parameters still lags far behind engineering practice and technology development. In this paper, we investigated the dynamic triaxial tests in laboratory with different kinds of soils (clay and silt), different confining pressures (50 Kpa, 100 Kpa and 150 Kpa), and different reinforcement layers (0 layer, 1 layer and 2 layers) to show the changes and influencing factors of dynamic elastic modulus and damping ratio. The experimental results will provide the basis for the parameter choice of geosynthetic reinforced subgrade with the influence of traffic load.