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This study aims to understand how the facesheet size, orientation and core size influence the analytical failure mechanism mode of glass fibre reinforced polymer (GFRP)/polyvinyl chloride (PVC) sandwich structures subjected to three-point bending. The purpose of this study was to develop failure-mode map of GFRP/PVC sandwich structures. Sandwich structures with different facesheet and core thicknesses were used to develop the failure map.

The sandwich structure and facesheet were fabricated using a vacuum-assisted resin infusion method with core sizes of 10, 15 and 20 mm and facesheet thicknesses of 1.5 and 3 mm and were arranged in three different orientations: angle-ply, cross-ply and quasi-isotropic. The key failure modes that occur in sandwich structures were used to predict possible failures in the developed material. Analytical equations were used in MATLAB for each observed failure mode. The probable failure modes, namely, face yielding, core shear and indentation equations, were used to construct the failure maps and were compared with the experimental data.

The boundary of the two failure modes shifts with changes in the facesheet and core thicknesses. The theoretical stiffness of sandwich panels was higher than the experimental stiffness. Based on strength-to-weight ratio, specimens E10-4, A15-8 and E20-8 exhibited the best optimum values owing to their shorter distance to the boundary lines.

In this study, a failure map was used to predict the possible failure modes for different GFRP facesheet orientations and thicknesses and PVC core thickness sandwich structures. Little is known about the prediction of the failure modes of unidirectional GFRP arranged in different orientations and thicknesses and PVC core thicknesses for sandwich structures. Few studies have used failure mode maps with unidirectional GFRP oriented in angle-ply, cross-ply and quasi-isotropic directions as a facesheet for sandwich structures compared to bidirectional mats. This study can serve as a guide for the correct selection of materials during the design process of sandwich structures.

In this experimental investigation, the behavior of strengthened/repaired heat-damaged one-way self-compacted concrete (SCC) slabs with opening utilizing near-surface-mounted-carbon fiber reinforced polymers (NSM-CFRP) strips was explored.

CFRP strip configurations, number of strips and inclination were all investigated in this study. For three hours, slabs were exposed to temperatures of 23°C and 500°C. Four-point load was applied to control slabs, enhanced slabs and repaired slabs.

The results indicate that exposing the slabs to high temperatures reduces their load capability. The number of strips and angle of inclination around the slab opening have a considerable impact on the performance of the strengthened and/or repaired slabs, according to the experimental results. The load capacity, toughness and ductility index of a strengthened and/or repaired slab with opening increase as the number of CFRP strips increases by 143.8–150.5%, 137.3–149.9% and 122.3–124.5%, respectively. The use of NSM strips around the opening with zero inclination showed higher load compared to the NSM strips around the opening with other angles.

It is frequently important to construct openings in the slabs for ventilation, electrical supply, and other purposes. Making openings in slabs might affect the structure’s performance since the concrete and reinforcing would be cut off. SCC is a new type of concrete mixture that can fill in all the voids in the formwork with its own weight without the help of external vibration.  As a result, it is necessary to reinforce the slab under flexure and increase the flexural strength of the SCC slab. Therefore, this work investigates the effect of using NSM-CFRP strip  on the behavior of one way SCC slabs that have been heat-damaged.

The paper aims to introduces an experimental work to investigate the torsional behavior of reinforced concrete (RC) beams strengthened by near-surface mounted (NSM) carbon fiber-reinforced polymer (CFRP) ropes.

In this research, nine rectangular RC beams of 250 mm × 300 mm cross-section and 1,600 mm in length were constructed and tested considering the studied parameters. These parameters include the length of the CFRP rope, the orientation of the CFRP rope, the arrangement of longitudinal and the scheme of NSM-CFRP ropes.

In comparison to control specimens, the results demonstrate a considerable improvement in the torsional response of RC beams strengthened with the CFRP rope. Additionally, specimens strengthened with 90° vertical ropes increase torsional moment capacity more efficiently than specimens strengthened with 45° inclined ropes since the stress concentration leads to premature debonding of the CFRP rope. Whereas RC beams' ability to withstand torsional moments is reduced as the distance between reinforcing CFRP ropes is increased. According to test results, adding CFRP ropes to RC beams' bottoms had a slightly positive impact on torsional response.

This paper fulfills an identified need to study how the using of the CFRP rope is effective in strengthening RC beam subjected to torsion moment.

This study aims to evaluate the failure behavior of glass fiber-reinforced epoxy (GFRE) laminate subjected to cyclic loading conditions. It involves experimental investigation and statistical analysis using Weibull distribution to characterize the failure behavior of the GFRE composite laminate.

Fatigue tests were conducted using a tension–tension loading scheme at a frequency of 2 Hz and a loading ratio (R) of 0.1. The tests were performed at five different stress levels, corresponding to 50%–90% of the ultimate tensile strength (UTS). Failure behavior was assessed through cyclic stress-strain hysteresis plots, dynamic modulus behavior and scanning electron microscopy (SEM) analysis of fracture surfaces.

The study identified common modes of failure, including fiber pullouts, fiber breakage and matrix cracking. At low stress levels, fiber breakage, matrix cracking and fiber pullouts occurred due to high shear stresses at the fiber–matrix interface. Conversely, at high stress levels, fiber breakage and matrix cracking predominated. Higher stress levels led to larger stress-strain hysteresis loops, indicating increased energy dissipation during cyclic loading. High stress levels were associated with a more significant decrease in stiffness over time, implying a shorter fatigue life, while lower stress levels resulted in a gradual decline in stiffness, leading to extended fatigue life.

This study makes a valuable contribution to understanding fatigue behavior under tension–tension loading conditions, coupled with an in-depth analysis of the failure mechanism in GFRE composite laminate at different stress levels. The fatigue behavior is scrutinized through stress-strain hysteresis plots and dynamic modulus versus normalized cycles plots. Furthermore, the characterization of the failure mechanism is enhanced by using SEM imaging of fractured specimens. The Weibull distribution approach is used to obtain a reliable estimate of fatigue life.

Additive lamination manufacturing (ALM), as a novel additive manufacturing technology, builds up the geometry via the lamination of fiber-reinforced polymer (FRP) fabric laterally, rendering it suitable for fabricating large-scale Stay-in-Place concrete formwork. This paper aims to investigate the control parameters and structure performance of ALM and assess its application for the fabrication of large-scale concrete formwork.

Based on previous feasibility studies, this research systematically investigates the control and material parameters that influence horizontal and vertical extrusion speeds, as well as the overall quality of ALM. Once the system parameters are established, a series of prototypes are fabricated and tested to validate the tensile strength of the formwork and its reinforcement capabilities. In addition, this study assesses the potential geometric freedom and implementation constraints of ALM.

This research identifies the essential control parameters for path planning in ALM and examines their impact on fabrication. In addition, this paper evaluates ALM’s strengths and limitations in producing concrete formwork for large-scale concrete structures, comparing these to industry benchmarks.

A critical challenge in additive manufacturing lies in its scalability and compatibility with existing construction processes. In comparison to concrete, FRP offers advantages such as being lighter, easier to handle and providing surface protection and reinforcement. These qualities make FRP superior for formwork and compatible with existing building standards. Despite its advantages and potential, the current path planning and control model in 3D printing do not apply to ALM due to its novel build-up process. Also, the performance of fabricated parts as part of integrated large-scale structures is yet to be studied.

This paper aims to find the effective 3D printing process parameters based on mechanical characteristics such as tensile strength and hardness of poly lactic acid (PLA)/carbon fibre composites (CF-PLA) by implementing intelligent frameworks.

The experiment trials are conducted based on design of experiments (DoE) using Taguchi L9 orthogonal array with three factors (speed, infill % and pattern type) and three levels. The factors have been optimized by solving the regression equation which is obtained from analysis of variance (ANOVA). The contour plots are generated by response surface methodology (RSM). The influencing parameters are found by using Box–Behnken design. The second order response surface model demonstrated the optimal combination of input parameters for higher tensile strength and hardness.

The influencing parameters are found by using Box–Behnken design. The second order response surface model demonstrated the optimal combination of input parameters for higher tensile strength and hardness. The results obtained from RSM are also confirmed by implementing the machine learning classifiers, such as logistic regression, ridge classifier, random forest, K nearest neighbour and support vector classifier (SVC). The results show that the SVC can predict the optimized process parameters with an accuracy of 95.65%.

3D printing parameters which are considered in this work such as pattern types for PLA/CF-PLA composites based on intelligent frameworks has not been attempted previously.

Recently, the repairing of reinforced concrete (RC) structures attracted great research attentions, but the research interests were mainly concentrated on common repairing types. To this end, in this paper, a repairing of pre-loaded RC beams strengthened by aramid reinforcement polymers (AFRP) is presented. Furthermore, the purpose of this paper is to study the behavior of pre-loaded RC Deep beams under sustained load. The AFRP has many advantages such as controlling stresses distribution around the openings, controlling failure modes, and enhancing the structural capacity of pre-cracked RC beams.

Four specimens were experimentally tested: one specimen without strengthening, which is considered as control specimen, one strengthened specimen using AFRP without pre-cracking and two specimens subjected to pre-cracking load before prior to AFRP application. Furthermore, after validation of experimental data by using ANSYS software, a parametric study was conducted to investigate the effect of pre-damage level on shear capacity of RC beams. For pre-cracked beams, loading was first applied until the cracking stage, followed by specimen repairing with epoxy injection, and then the specimens were loaded again until failure point.

The result showed that pre-damage level and AFRP strengthening have great influence on the ultimate strength and failure mode. In addition, the results obtained from experimental tests were compared with those from numerical validation with ANSYS and showed good agreement.

Based on ACI guidelines, an analytical equation for calculating the shear strength of strengthened RC beams with openings subjected to pre-damage was then proposed, and the calculated results were compared with those from the tests, with differences not exceeding 10%.

In this research, the free vibration sensitivity analysis of cracked fiber metal laminated (FML) beams is investigated numerically and experimentally. The effects of single and double cracks on the frequency of the cantilever beams are simulated using the finite element method (FEM) and compared to the experimental results.

In FEM analysis, the crack defect is simulated by the contour integral technique without considering the crack growth. The specimens are fabricated with an aluminum sheet, woven carbon fiber and epoxy resin. The FML specimens are constructed by bonding five layers as [carbon fiber-epoxy/Al/carbon fiber-epoxy/Al/carbon fiber-epoxy]. First, the location and length of cracks are considered input factors for the frequency sensitivity analysis. Then, the design of the experiment is produced in the cases of single and double cracks to compute the frequency of the beams in the first and second modes using the FEM. The mechanical shaker is used to determine the natural frequency of the specimens. In addition, the predicted response values of the frequency for the beam are used to compare with the experimental results.

Consequently, the results of the sensitivity analysis demonstrate that the location and length of the crack have significant effects on the modes.

Effective interaction diagrams are introduced to investigate crack detection for input factors, including the location and length of cracks in the cases of single and double cracks.

This paper reviews and analyses renewable energy options, namely underground thermal, solar, wind and marine wave energy, in seaport cargo terminal operations.

Four renewable energy options that are deployed or tested in different ports around the world are qualitatively examined for their overall implementation potential and characteristics, and their cost and benefits. An application to the port of Singapore is discussed.

Geophysical conditions are key criteria in assessing renewable energy options. In the case of Singapore, solar power is the only suitable renewable energy option.

Being a capital-intensive establishment with high intensities of cargo operations, seaports usually involve a high level of energy consumption. The study of renewable energy options contributes to seaport sustainability.

A key recommendation is to implement a smart energy management system that enables the mixed use of renewable energy to match energy demand and supply optimally and achieve higher energy efficiency.

The use of renewable energy as an eco-friendlier energy source is underway in various ports. However, there is almost no literature that analyses and compares various renewable energy options potentially suitable for cargo terminal operations in ports. This paper narrows the knowledge gaps.

The investigation aims to improve Nd: YAG laser technology for precision cutting of carbon fiber reinforcing polymers (CFRPs), specifically those containing newly created resin (NDR) from the polyethylene and polyurea group, is the goal of the study. The focus is on showing how Nd: YAG lasers may be used to precisely cut CFRP with NDR materials, emphasizing how useful they are for creating intricate and long-lasting components.

The study employs a systematic approach that includes complicated factorial designs, Taguchi L27 orthogonal array trials, Gray relational analysis (GRA) and machine learning predictions. The effects of laser cutting factors on CFRP with NDR geometry are investigated experimentally, with the goal of optimizing the cutting process for greater quality and efficiency. The approach employs data-driven decision-making with GRA, which improves cut quality and manufacturing efficiency while producing high-quality CFRP composites. Integration of machine learning models into the optimization process significantly boosts the precision and cost-effectiveness of laser cutting operations for CFRP materials.

The work uses Taguchi L27 orthogonal array trials for systematically explore the effects of specified parameters on CFRP cutting. The cutting process is then optimized using GRA, which identifies influential elements and determines the ideal parameter combination. In this paper, initially machining parameters are established at level L3P3C3A2, and the optimal machining parameters are determined to be at levels L3P2C3A3 and L3P2C1A2, based on predictions and experimental results. Furthermore, the study uses machine learning prediction models to continuously update and optimize kerf parameters, resulting in high-quality cuts at a lower cost. Overall, the study presents a holistic method to optimize CFRP cutting processes employing sophisticated techniques such as GRA and machine learning, resulting in better quality and efficiency in manufacturing operations.

The novel concept is in precisely measuring the kerf width and deviation in CFRP samples of NDR using sophisticated imaging techniques like SEM, which improves analysis and precision. The newly produced resin from the polyethylene and polyurea group with carbon fiber offers a more precise and comprehensive understanding of the material's behavior under different cutting settings, which makes it novel for kerf width and kerf deviation in their studies. To optimize laser cutting settings in real time while considering laser machining conditions, the study incorporates material insights into machine learning models.