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During the construction process of the China Railway Track System (CRTS) I type filling layer, the nonwoven fabric bags have been used as grouting templates for cement asphalt (CA) emulsified mortar. The porous structure of nonwoven fabrics endowed the templates with breathability and water permeability. The standard requires that the volume expansion rate of CA mortar must be controlled within 1%–3%, which can generate expansion pressure to ensure that the cavities under track slabs are filled fully. However, the expansion pressure caused some of the water to seep out from the periphery of the filling bag, and it would affect the actual mix proportion of CA mortar. The differences in physical and mechanical properties between the CA mortar under track slabs and the CA mortar formed in the laboratory were studied in this paper. The relevant results could provide important methods for the research of filling layer materials for CRTS I type and other types of ballastless tracks in China.

During the inspection of filling layer, the samples of CA mortar from different working conditions and raw materials were taken by uncovering the track slabs and drilling cores. The physical and mechanical properties of CA mortar under the filling layer of the slab were systematically analyzed by testing the electrical flux, compressive strength and density of mortar in different parts of the filling layer.

In this paper, the electric flux, the physical properties and mechanical properties of different parts of CA mortar under the track slab were investigated. The results showed that the density, electric flux and compressive strength of CA mortar were affected by the composition of raw materials for dry powders and different parts of the filling layer. In addition, the electrical flux of CA mortar gradually decreased within 90 days’ age. The electrical flux of samples with the thickness of 54 mm was lower than 500 C. Therefore, the impermeability and durability of CA mortar could be improved by increasing the thickness of filling layer. Besides, the results showed that the compressive strength of CA mortar increased, while the density and electric flux decreased gradually, with the prolongation of hardening time.

During 90 days' age, the electrical flux of the CA mortar gradually decreased with the increase of specimen thickness and the electrical flux of the specimens with the thickness of 54 mm was lower than 500 C. The impermeability and durability of the CA mortar could be improved by increasing the thickness of filling layer. The proposed method can provide reference for the further development and improvement of CRTS I and CRTS II type ballastless track in China.

Punching can trigger catastrophic failures in flat slabs because of its sudden nature resulting from exceeding the shear capacity of slabs. Effect of using recycled aggregate, as an environmental-friendly alternative to traditional RC structures, on punching behavior of these slabs was not sufficiently investigated in the literature. Hence, this paper aims to experimentally study the effect of using recycled coarse aggregate (RCA) on the punching shear capacity (PSC) of RC flat slabs. The RCA is produced by crushing of waste of concrete standard cubes obtained from compression tests.

A total of 12 slab-column connection specimens with different slab thicknesses (140, 160 and 200 mm) and different RCA percentages (0%, 30% and 70%) were prepared and tested under a central point load, to test its effect on the behavior of flat slabs. The punching failure loads of the tested specimens were compared with those obtained according to the provisions of different international building codes.

Compared with natural aggregate concrete, mixes with 30% and 70% RCA experienced reductions in the compressive that did not exceed 4% and 21%, while reductions of 4% and 13% were observed for the tensile strength, respectively. The increase in the amount of RCA reduced the PSC by 0%–7%, 0%–4% and 4%–10% for slabs with a thickness of 140, 160 and 200 mm, respectively. For slabs with punching shear reinforcement (PSR), ACI 318 provided the closest estimation for the PSC by 9%, whereas EURO 2 overestimated the PSC by 25% and ECP 203 underestimated the PSC by 41%.

The provided conclusions are obtained from the conducted experimental work where a constant W/C ratio, aggregate type and a maximum aggregate size of 19 mm for the RCA were adopted.

Enhancement in the behavior of flat slabs with various thicknesses and amounts of RCA because of introducing PSR is experimentally evaluated. The failure loads of the tested slabs with recycled and normal coarse aggregates were compared against different code provisions.

This study aims to assess the efficacy of thermal analysis of concrete slabs by including different insulation materials using ANSYS. Regression equations were proposed to predict the thermal conductivity using concrete density. As these simulation and regression analyses are essential tools in designing the thermal insulation concretes with various densities, they sequentially reduce the associated time, effort and cost.

Two grades of concretes were taken for thermal analysis. They were designed by replacing the natural fine aggregates with thermal insulation aggregates: expanded polystyrene, exfoliated vermiculite and light expanded clay. Density, temperature difference, specific heat capacity, thermal conductivity and time were measured by conducting experiments. This data was used to simulate concrete slabs in ANSYS. Regression analysis was performed to obtain the relation between density and thermal conductivity. Finally, the quality of the predicted regression equations was assessed using root mean square error (RMSE), mean absolute error (MAE), integral absolute error (IAE) and normal efficiency (NE).

ANSYS analysis on concrete slabs accurately estimates the thermal behavior of concrete, with lesser error value ranges between 0.19 and 7.92%. Further, the developed regression equations proved accurate with lower values of RMSE (0.013 to 0.089), MAE (0.009 to 0.088); IAE (0.216 to 5.828%) and higher values of NE (94.16 to 99.97%).

The thermal analysis accurately simulates the experimental transfer of heat across the concrete slab. Obtained regression equations proved helpful while designing the thermal insulation concrete.

This research study focuses on investigating the seismic performance of non-straight beams in steel structures and exploring the mechanism by which plastic hinges are formed within these beams. The findings contribute to the understanding of their behaviour under seismic loads and offer insights into their potential for enhancing the lateral resistance of the structure. The abstract of the study highlights the significance of corners in structural plans, where non-coaxial columns, diagonal elements or beams deviating from a straight path are commonly observed. Typically, these non-straight beams are connected to the columns using pinned connections, despite their unknown seismic behaviour. Recognizing the importance of generating plastic hinges in special moment resisting frames and the lack of previous research on the involvement of these non-straight beams, this study aims to address this knowledge gap.

This study examines the seismic behaviour and plastic hinge formation of non-straight beams in steel structures. Non-straight beams are beams that connect non-coaxial columns and diagonal elements, or deviate from a linear path. They are usually pinned to the columns, and their seismic contribution is unknown. A critical case with a 12-m non-straight beam is analysed using Abaqus software. Different models are created with varying cross-section shapes and connection types between the non-straight beams. The models are subjected to lateral monotonic and cyclic loads in one direction. The results show that non-straight beams increase the lateral stiffness, strength and energy dissipation of the models compared to disconnected beams that act as two cantilevers.

The analysis results reveal several key findings. The inclusion of non-straight beams in the models leads to increased lateral stiffness, strength and energy dissipation compared to the scenario where the beams are disconnected and act as two cantilever beams. Plastic hinges are formed at both ends of the non-straight beam when a 3% drift is reached, contributing to energy damping and introducing plasticity into the structure. These results strongly suggest that non-straight beams play a significant role in enhancing the lateral resistance of the system. Based on the seismic analysis results, this study recommends the utilization of non-straight beams in special moment frames due to the formation of plastic hinges within these beams and their effective participation in resisting lateral seismic loads. This research fills a critical gap in understanding the behaviour of non-straight beams and provides valuable insights for structural engineers involved in the design and analysis of steel structures.

The authors believe that this research will greatly contribute to the knowledge and understanding of the seismic performance of non-straight beams in steel structures.

The Government’s investment in infrastructure projects is considerably high, especially in bridge construction projects. Government authorities must establish an initial forecasted budget to have transparency in transactions. Early cost estimating is challenging for Quantity Surveyors due to incomplete project details at the initial stage and the unavailability of standard cost estimating techniques for bridge projects. To mitigate the difficulties in the traditional preliminary cost estimating methods, there is a requirement to develop a new initial cost estimating model which is accurate, user friendly and straightforward. The research was carried out in Sri Lanka, and this paper aims to develop the artificial neural network (ANN) model for an early cost estimate of concrete bridge systems.

The construction cost data of 30 concrete bridge projects which are in Sri Lanka constructed within the past ten years were trained and tested to develop an ANN cost model. Backpropagation technique was used to identify the number of hidden layers, iteration and momentum for optimum neural network architectures.

An ANN cost model was developed, furnishing the best result since it succeeded with around 90% validation accuracy. It created a cost estimation model for the public sector as an accurate, heuristic, flexible and efficient technique.

The research contributes to the current body of knowledge by providing the most accurate early-stage cost estimate for the concrete bridge systems in Sri Lanka. In addition, the research findings would be helpful for stakeholders and policymakers to propose policy recommendations that positively influence the prediction of the most accurate cost estimate for concrete bridge construction projects in Sri Lanka and other developing countries.

The time-varying equivalent linear temperature gradient (ELTG) significantly affects the development of faulting and must therefore be accounted for in pavement design. The same is true for faulting of bonded concrete overlays of asphalt (BCOA) with slabs larger than 3 x 3 m. However, the evaluation of ELTG in Mechanistic-Empirical (ME) BCOA design is highly time-consuming. The use of an effective ELTG (EELTG) is an efficient alternative to calculating ELTG. In this study, a model to quickly evaluate EELTG was developed for faulting in BCOA for panels 3 m or longer in size, whose faulting is sensitive to ELTG.

A database of EELTG responses was generated for 144 BCOAs at 169 locations throughout the continental United States, which was used to develop a series of prediction models. Three methods were evaluated: multiple linear regression (MLR), artificial neural networks (ANNs), and multi-gene genetic programming (MGGP). The performance of each method was compared, considering both accuracy and model complexity.

It was shown that ANNs display the highest accuracy, with an R² of 0.90 on the validation dataset. MLR and MGGP models achieved R² of 0.73 and 0.71, respectively. However, these models consisted of far fewer free parameters as compared to the ANNs. The model comparison performed in this study highlights the need for researchers to consider the complexity of models so that their direct implementation is feasible.

This research produced a rapid EELTG prediction model for BCOAs that can be incorporated into the existing faulting model framework.

The use of recycled coarse aggregate in concrete structures promotes environmental sustainability; however, performance of these structures might be negatively impacted when it is used as a replacement to traditional aggregate. This paper aims to simulate recycled concrete beams strengthened with carbon fiber-reinforced polymer (CFRP), to advance the modeling and use of recycled concrete structures.

To investigate the performance of beams with recycled coarse aggregate concrete (RCAC), finite element models (FEMs) were developed to simulate 12 preloaded RCAC beams, strengthened with two CFRP strengthening schemes. Details of the modeling are provided including the material models, boundary conditions, applied loads, analysis solver, mesh analysis and computational efficiency.

Using FEM, a parametric study was carried out to assess the influence of CFRP thickness on the strengthening efficiency. The FEM provided results in good agreement with those from the experiments with differences and standard deviation not exceeding 11.1% and 3.1%, respectively. It was found that increasing the CFRP laminate thickness improved the load-carrying capacity of the strengthened beams.

The developed models simulate the preloading and loading up to failure with/without CFRP strengthening for the investigated beams. Moreover, the models were validated against the experimental results of 12 beams in terms of crack pattern as well as load, deflection and strain.

This paper covers the development of a novel defect model for concrete highway bridges. The proposed defect model is intended to facilitate the identification of bridge’s condition information (i.e. defects), improve the efficiency and accuracy of bridge inspections by supporting practitioners and even machines with digitalised expert knowledge, and ultimately automate the process.

The research design consists of three major phases so as to (1) categorise common defect with regard to physical entities (i.e. bridge element), (2) establish internal relationships among those defects and (3) relate defects to their properties and potential causes. A mixed-method research approach, which includes a comprehensive literature review, focus groups and case studies, was employed to develop and validate the proposed defect model.

The data collected through the literature and focus groups were analysed and knowledge were extracted to form the novel defect model. The defect model was then validated and further calibrated through case study. Inspection reports of nearly 300 bridges in China were collected and analysed. The study uncovered the relationships between defects and a variety of inspection-related elements and represented in the form of an accessible, digitalised and user-friendly knowledge model.

The contribution of this paper is the development of a defect model that can assist inexperienced practitioners and even machines in the near future to conduct inspection tasks. For one, the proposed defect model can standardise the data collection process of bridge inspection, including the identification of defects and documentation of their vital properties, paving the path for the automation in subsequent stages (e.g. condition evaluation). For another, by retrieving rich experience and expert knowledge which have long been reserved and inherited in the industrial sector, the inspection efficiency and accuracy can be considerably improved.

The purpose of this study is to introduce a new type of sensor which uses microwave metamaterials and direct-coupled split-ring resonators (DC-SRRs) to measure the dielectric properties of solid materials in real time. The sensor uses a transmission line with a bridge-type structure to measure the differential frequency, which can be used to calculate the dielectric constant of the material being tested. The study aims to establish an empirical relationship between the dielectric properties of the material and the frequency measurements obtained from the sensor.

In the proposed design, the opposite arm of the bridge transmission line is loaded by DC-SRRs, and the distance between DC-SRRs is optimized to minimize the mutual coupling between them. The DC-SRRs are loaded with the material under test (MUT) to perform differential permittivity sensing. When identical MUT is placed on both resonators, a single transmission zero (notch) is obtained, but non-identical MUTs exhibit two split notches. For the design of differential sensors and comparators based on symmetry disruption, frequency splitting is highly useful.

The proposed structure is demonstrated using electromagnetic simulation, and a prototype of the proposed sensor is fabricated and experimentally validated to prove the differential sensing principle. Here, the sensor is analyzed for sensitivity by using different MUTs with relative permittivity ranges from 1.006 to 10 and with a fixed dimension of 9 mm × 10 mm ×1.2 mm. It shows a very good average frequency deviation per unit change in permittivity of the MUTs, which is around 743 MHz, and it also exhibits a very high average relative sensitivity and quality factor of around 11.5% and 323, respectively.

The proposed sensor can be used for differential characterization of permittivity and also as a comparator to test the purity of solid dielectric samples. This sensor most importantly strengthens robustness to environmental conditions that cause cross-sensitivity or miscalibration. The accuracy of the measurement is enhanced as compared to conventional single- and double-notch metamaterial-based sensors.

This paper presents the experimental and numerical results of the bending properties of low-height prestressed T-beams. The purpose is to study the bearing capacity, failure state and strain distribution of low-height prestressed T-beams.

First, two 13 m-long full-size test beams were fabricated with different positions of prestressed steel bundles in the span. The load–deflection curves and failure patterns of each test beam were obtained through static load tests. Secondly, the test data were used to validate the finite element model developed to simulate the flexural behavior of low-height prestressed T-beams. Finally, the influence of different parameters (the number of prestressed steel bundles, initial prestress and concrete strength grade) on the flexural performance of the test beams is studied by using a finite element model.

The test results show that when the distance of the prestressed steel beam from the bottom height of the test beam increases from 40 to 120 mm, the cracking load of the test beam decreases from 550.00 to 450.00 kN, reducing by 18.18%, and the ultimate load decreases from 1338.15 to 1227.66 kN, reducing by 8.26%, therefore, the increase of the height of the prestressed steel beam reduces the bearing capacity of the test beam. The numerical simulation results show that when the number of steel bundles increases from 2 to 9, the cracking load increases by 183.60%, the yield load increases by 117.71% and the ultimate load increases by 132.95%. Therefore, the increase in the number of prestressed steel bundles can increase the cracking load, yield load and ultimate load of the test beam. When the initial prestress is from 695 to 1,395 MPa, the cracking load increases by 69.20%, the yield load of the bottom reinforcement increases by 31.61% and the ultimate load increases by 3.97%. Therefore, increasing the initial prestress can increase the cracking load and yield load of the test beam, but it has little effect on the ultimate load. The strength grade of concrete increases from C30 to C80, the cracking load is about 455.00 kN, the yield load is about 850.00 kN and the ultimate load is increased by 4.90%. Therefore, the improvement in concrete strength grade has little influence on the bearing capacity of the test beam.

Based on the experimental study, the bearing capacity of low-height prestressed T-beams with different prestressed steel beam heights is calculated by finite element simulation, and the influence of different parameters on the bearing capacity is discussed. This method not only ensures the accuracy of bearing capacity assessment, but also does not require a large number of samples and has a certain economy. The study of prestressed low-height T-beams is of great significance for understanding the principle and application of prestressed technology. Research on the mechanical behavior and performance of low-height prestressed T beams can provide a scientific basis and technical support for the design and construction of prestressed concrete structures. In addition, the study of prestressed low-height T-beams can also provide a reference for the optimization design and construction of other structural types.