Search results

As an important part of steel bridge deck pavement, if waterproof adhesive layer performance does not meet requirements, numerous kinds of bridge deck pavement distress may be encountered. To study the adhesive behavior of rubber asphalt waterproof adhesive layers in steel bridge gussasphalt pavement, the pull-off and direct-shear tests have been used in the study to mechanically simulate steel bridge deck pavement under vehicles loading.

Several potentially influential factors associated with the adhesive strength of rubber asphalt are investigated including temperature, spraying quantity and environmental conditions.

Results indicate that rubber asphalt was associated with good performance with respect to its use as a waterproof adhesive layer; simulated performance was negatively correlated with increasing temperatures. A necessary spraying quantity of 0.4 Lm^-2 is required for appropriate adhesive strength of the composite structure, with a decrease in adhesive strength noted when spraying quantity is significantly greater or less than this.

The current paper presents an examination of the adhesive performance of a rubber asphalt adhesive layer on steel bridge deck pouring construction, while additionally examining potentially influential factors and conditions via use of both pull-off and shear tests.

Polyurethane concrete (PUC), as a new type of steel bridge deck paving material, the bond-slip pattern at the interface with the steel plate is not yet clear. In this study, the mechanical properties of the PUC and steel plate interface under the coupled action of temperature, normal force and tangential force were explored through shear tests and numerical simulations. An analytical model for bond-slip at the PUC/steel plate interface and a predictive model for the shear strength of the PUC/steel plate interface were developed.

The new shear test device designed in this paper overcomes the defect that the traditional oblique shear test cannot test the interface shear performance under the condition of fixed normal force. The universal testing machine (UTM) test machine was used to adjust the test temperature conditions. Combined with the results of the bond-slip test, the finite element simulation of the interface is completed by using the COHENSIVE unit to analyze the local stress distribution characteristics of the interface. The use of variance-based uncertainty analysis guaranteed the validity of the simulation.

The shear strength (τ_f) at the PUC-plate interface was negatively correlated with temperature while it was positively correlated with normal stress. The effect of temperature on the shear properties was more significant than that of normal stress. The slip corresponding to the maximum shear (D₁) positively correlates with both temperature and normal stress. The interfacial shear ductility improves with increasing temperature.

Based on the PUC bond-slip measured curves, the relationship between bond stress and slip at different stages was analyzed, and the bond-slip analytical model at different stages was established; the model was defined by key parameters such as elastic ultimate shear stress τ₀, peak stress τ_f and interface fracture energy G_f.

The application of ultra-high performance concrete (UHPC) in anchorage zones can significantly improve the local compression performance of structures. However, the high cost and complex preparation of UHPC make UHPC difficult to be widely used in practice. This study proposes a method to strengthen the local compression zone of structures built by normal strength concrete (NSC) by incorporating UHPC cores.

In this study, a Finite Element Model (FEM) of local compression specimens was established by ABAQUS, and the accuracy of FEM was verified by comparing the FEM calculation results with experimental results. The verified FEM was adapted to the research on the influences of affecting factors on local compression performance of structures, including NSC strength, UHPC strength, spiral steel bar strength, and UHPC core diameter.

The results show that the peak load of the strengthened specimen SC1-U + N increases by 210.2% compared to that of the SC1-NSC. Furthermore, compared to SC1, the strengthened specimen SC1-U + N can save 64.7% amount of UHPC while the peak load decreases by only 34.4%. The peak load of the strengthened specimens increases with the axial compressive strength and the diameter of UHPC cores increasing, crack load increases with increasing the compressive strength of NSC, the spiral steel bar with high strength can prevent the sharp drop of load-deflection curve and the residual bearing capacity increases accordingly. All findings indicate that increasing the diameter of UHPC cores can improve the overall performance of the specimens. Under loading, all specimens fail by following a similar pattern. The effectiveness of this new strengthen method is also verified by FEM analytical calculations.

Based on the experimental study, this study extrapolates the influence of different parameters on the local bearing capacity of the strengthened specimens by finite element simulation. This method not only ensures the accuracy of bearing capacity assessment, but also does not require many samples, which ensures the economy of the reinforcement process. The research results provide a reference for the reinforcement design of anchorage zone.

The purpose of this paper is to try to understand the relationship between price and quality in public procurement by using data on the quality of civil engineering works and prices in tenders. By doing so, it tries to conduct a comprehensive examination of the quality of construction works, which has been difficult to recognize and evaluate.

The methodology of this analysis is to collect data on the quality of construction works from the rankings of construction performance evaluations revealed by public procurement authorities. In addition, the prices of bids of the providers in public procurement are also collected from the available data and analyzed. The relationship between the two was statistically analyzed in an objective and verifiable way.

What the study found was that the price of the work measured by the bid rate had a positive and significant relationship with the quality of the work measured by the construction performance rating. Furthermore, the panel data were analyzed using panel data for 51 firms that all appeared in the construction performance evaluation for 12 years and participated in at least three bids in each year, and the first-order term of the bid rate was negative and the second-order term was positive and was 10% significant, which is a U-shaped relationship.

This study is one of the investigations focused on public procurement construction work. One of the limitations of this study is that it is a study of one industry in the Asian region. However, this study focuses on the incentives of business operators. As such, the analysis is applicable to all situations faced by those running businesses.

The managerial implications of this study include the following: although, improving the quality of construction results is costly, competitive firms are also steadily improving their quality as it is a factor of competition. However, there will come a point where their efforts come to a halt at a certain level. It is necessary to operate the business with this situation in mind. In addition to the company's efforts, it is necessary to lobby the government.

As a policy implication for this analysis, it was possible to evaluate that steady improvement in construction results was confirmed, but the correlation between the relaxation of the competition and the increase in the bid rate was correlated with the decrease in the total amount of public works. This highlights the problem of having to think about measures for the efficient use of the. In addition to this, the fact that the competition situation has been eased can be considered as a problem that it will adversely affect the innovation stimulation of operators, and that it will become necessary to pay more attention to competition limiting acts.

The uniqueness of this paper is firstly that unique data representing the quality of public procurement, which had been difficult to analyze, were collected, organized and used in the study. In addition, not only did we find a positive relationship between quality and price but we also found a U-shaped relationship between them using panel data.

Reinforcement of reinforced concrete (RC) beams in-service have always been an important research field, anchoring steel plate in the bottom of the beams is a kind of common reinforcement methods. In actual engineering, the contribution of pavement layer to the bearing capacity of RC beams is often ignored, which underestimates the bearing capacity and stiffness of RC beams to a certain extent. The purpose of this paper is to study the effect of pavement layer on the RC beams before and after reinforcement.

First, static load experiments are carried out on three in-service RC hollow slab beams, meanwhile, nonlinear finite element models are built to study the bearing capacity of them. The nonlinear material and shear slip effect of studs are considered in the models. Second, the finite element models are verified, and the numerical simulation results are in good agreement with the experimental results. Last, the finite element models are adopted to carry out the research on the influence of different steel plate thicknesses on the flexural bearing capacity and ductility.

The experimental results showed that pavement layers increase the flexural capacity of hollow slab beams by 16.7%, and contribute to increasing stiffness. Ductility ratio of SPRCB3 and PRCB2 was 30% and 24% lower than that of RCB1, respectively. The results showed that when the steel plate thickness was 1 mm–6 mm, the bearing capacity of the hollow slab beam increased gradually from 2158.0 kN.m to 2656.6 kN.m. As the steel plate thickness continuously increased to 8 mm, the ultimate bearing capacity increased to 2681.0 kN.m. The increased thickness did not cause difference to the bearing capacity, because of concrete crushing at the upper edge.

In this paper, based on the experimental study, the bearing capacity of hollow beam strengthened by steel plate with different thickness is extrapolated by finite element simulation, and its influence on ductility is discussed. This method not only guarantees the accuracy of the bearing capacity evaluation, but also does not require a large number of samples, and has certain economy. The research results provide a basis for the reinforcement design of similar bridges.

This paper aims to provide an integrated framework of life cycle assessment (LCA) and life cycle cost analysis (LCCA) for assessing alternative technologies, processes, and/or activities, with focus on concrete pavements.

LCA and LCCA are used to evaluate environmental and economic impacts of substituting different percentages of fly ash and slag into continuously reinforced concrete pavement (CRCP) and jointed plane concrete pavement (JPCP). Impacts are determined over different life cycle phases.

An LCA of the extraction phase indicated that JPCP pavement had 33‐62 percent less emissions than CRCP pavements, when only steel consumption was considered. When cement was considered, JPCP pavement had almost 40 percent greater emissions then CRCP for all mix types. An LCCA showed that over the entire life cycle phases studied, CRCP pavements had about 46 percent more costs than JPCP. However, when only maintenance costs were considered, CRCP pavement cost 80 percent less to maintain than JPCP over the studied period of 35 years.

The study is a step towards using an integrated framework to evaluate the performance of different materials and technology. The same framework could be conducted for different kinds of asphalt pavements and concrete pavements, as well as other infrastructure that makes up the built environment, with the goal of making decisions that take into account design considerations, environmental impacts, and cost effectiveness.

In order to understand the status of the bridge reinforcement process, the construction process monitoring of the reinforced bridge is carried out. The T-beam bridge was tested using the truck loading test. The displacements and concrete strains of the bridge at mid-span were measured during the test.

This paper describes an innovative technique, external prestressing, used to strengthen a 36-year-old prestressed T-beam bridge. This paper introduces the construction process of the prestressed reinforcement method, and makes a theoretical analysis of the reinforced bridge through the establishment of the reinforcement model.

This study showed that the structural capacity and performance of the bridge were enhanced with externally prestressed steel strand strengthening.

The innovative reinforcement method of prestressed T-shaped bridge is put forward, which has guiding significance for similar bridge reinforcement and maintenance.

The massive number of pavements and buildings coupled with the limited inspection resources, both monetary and human, to detect distresses and recommend maintenance actions lead to rapid deterioration, decreased service life, lower level of service and increased community disruption. Therefore, this paper aims at providing a state-of-the-art review of the literature with respect to deep learning techniques for detecting distress in both pavements and buildings; research advancements per asset/structure type; and future recommendations in deep learning applications for distress detection.

A critical analysis was conducted on 181 papers of deep learning-based cracks detection. A structured analysis was adopted so that major articles were analyzed according to their focus of study, used methods, findings and limitations.

The utilization of deep learning to detect pavement cracks is advanced compared to assess and evaluate the structural health of buildings. There is a need for studies that compare different convolutional neural network models to foster the development of an integrated solution that considers the data collection method. Further research is required to examine the setup, implementation and running costs, frequency of capturing data and deep learning tool. In conclusion, the future of applying deep learning algorithms in lieu of manual inspection for detecting distresses has shown promising results.

The availability of previous research and the required improvements in the proposed computational tools and models (e.g. artificial intelligence, deep learning, etc.) are triggering researchers and practitioners to enhance the distresses’ inspection process and make better use of their limited resources.

A critical and structured analysis of deep learning-based crack detection for pavement and buildings is conducted for the first time to enable novice researchers to highlight the knowledge gap in each article, as well as building a knowledge base from the findings of other research to support developing future workable solutions.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

This paper aims to present a novel robotic system for airport pavement inspection tasks.

The cloud-edge-terminal-based distributed architecture is designed for the proposed robotic system. Then, the following three major parts are designed and deployed, respectively: Terminal: the wheeled-robot-based data collection system. Edge: remote monitoring and data analysis system. Cloud: shared database center of the inspection data and knowledge.

Validation and application results show that the proposed system satisfies the demands of automated airport pavement inspection tasks and saves the cost of manpower and time.

The proposed system provides a novel solution for the full process of airport pavement inspection. Compared with the traditional manual method, the robotic system can guarantee complete coverage and provide high-precision pavement inspection results with less time and labor costs.