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When the reinforced concrete beams are reinforced by bonding steel plates to the bottom, excessive use of steel plates will make the reinforced concrete beams become super-reinforced beams, and there are security risks in the actual use of super-reinforced beams. In order to avoid the occurrence of this situation, the purpose of this paper is to study the calculation method of the maximum number of bonded steel plates to reinforce reinforced concrete beams.

First of all, when establishing the limit failure state of the reinforced member, this paper comprehensively considers the role of the tensile steel bar and steel plate and takes the load effect before reinforcement as the negative contribution of the maximum number of bonded steel plates that can be used for reinforcement. Through the definition of the equivalent tensile strength, equivalent elastic modulus and equivalent yield strain of the tensile steel bar and steel plate, a method to determine the relative limit compression zone height of the reinforced member is obtained. Second, based on the maximum ratio of (reinforcement + steel plate), the relative limit compression zone height and the equivalent tensile strength of the tensile steel bar and steel plate of the reinforced member, the calculation method of the maximum number of bonded steel plates is derived. Then, the static load test of the test beam is carried out and the corresponding numerical model is established, and the reliability of the numerical model is verified by comparison. Finally, the accuracy of the calculation method of the maximum number of bonded steel plates is proved by the numerical model.

The numerical simulation results show that when the steel plate width is 800 mm and the thickness is 1–4 mm, the reinforced concrete beam has a delayed yield platform when it reaches the limit state, and the failure mode conforms to the basic stress characteristics of the balanced-reinforced beam. When the steel plate thickness is 5–8 mm, the sudden failure occurs without obvious warning when the reinforced concrete beam reaches the limit state. The failure mode conforms to the basic mechanical characteristics of the super-reinforced beam failure, and the bending moment of the beam failure depends only on the compressive strength of the concrete. The results of the calculation and analysis show that the maximum number of bonded steel plates for reinforced concrete beams in this experiment is 3,487 mm². When the width of the steel plate is 800 mm, the maximum thickness of the steel plate can be 4.36 mm. That is, when the thickness of the steel plate, the reinforced concrete beam is still the balanced-reinforced beam. When the thickness of the steel plate, the reinforced concrete beam will become a super-reinforced beam after reinforcement. The calculation results are in good agreement with the numerical simulation results, which proves the accuracy of the calculation method.

This paper presents a method for calculating the maximum number of steel plates attached to the bottom of reinforced concrete beams. First, based on the experimental research, the failure mode of reinforced concrete beams with different number of steel plates is simulated by the numerical model, and then the result of the calculation method is compared with the result of the numerical simulation to ensure the accuracy of the calculation method of the maximum number of bonded steel plates. And the study does not require a large number of experimental samples, which has a certain economy. The research result can be used to control the number of steel plates in similar reinforcement designs.

This paper aims to study the influence of different reinforcement methods on crack monitoring characteristics of eddy current array sensors, and the sensors with two different reinforcement methods, SUS304 reinforcement and permalloy reinforcement, are proposed.

First, the finite element model of the sensor is established to analyze the influence of the reinforcement plate’s electromagnetic parameters on the crack identification sensitivity. Then, the crack monitoring accuracy test of sensors with two reinforcement methods is carried out. Finally, the fatigue crack monitoring experiments with bolt tightening torques of 45 and 63 N · m are carried out, respectively.

In this study, it is found that the crack identification sensitivity of the sensor can be improved by increasing the relative permeability of the reinforcement plate. The crack monitoring accuracy of the sensors with two different reinforcement methods is about 1 mm. And the crack identification sensitivity of the sensor reinforced by permalloy reinforcement plate is significantly higher than that of the sensor reinforced by SUS304 reinforcement plate.

The sensor reinforced by reinforcement plate can work normally under the squeezing action of the bolt, and the crack monitoring sensitivity of the sensor can be significantly improved by using the reinforcement plate with high relative permeability.

This paper aim to solve the problem of low assembly success rate for 3c assembly lines designed based on classical control algorithms due to inevitable random disturbances and other factors,by incorporating intelligent algorithms into the assembly line, the assembly process can be extended to uncertain assembly scenarios.

This work proposes a reinforcement learning framework based on digital twins. First, the authors used Unity3D to build a simulation environment that matches the real scene and achieved data synchronization between the real environment and the simulation environment through the robot operating system. Then, the authors trained the reinforcement learning model in the simulation environment. Finally, by creating a digital twin environment, the authors transferred the skill learned from the simulation to the real environment and achieved stable algorithm deployment in real-world scenarios.

In this work, the authors have completed the transfer of skill-learning algorithms from virtual to real environments by establishing a digital twin environment. On the one hand, the experiment proves the progressiveness of the algorithm and the feasibility of the application of digital twins in reinforcement learning transfer. On the other hand, the experimental results also provide reference for the application of digital twins in 3C assembly scenarios.

In this work, the authors designed a new encoder structure in the simulation environment to encode image information, which improved the model’s perception of the environment. At the same time, the authors used the fixed strategy combined with the reinforcement learning strategy to learn skills, which improved the rate of convergence and stability of skills learning. Finally, the authors transferred the learned skills to the physical platform through digital twin technology and realized the safe operation of the flexible printed circuit assembly task.

In the analysis of structures in a fire situation by simplified and analytical methods, one assumption is that the fire resistance time is greater than or equal to the required fire resistance time. Among the methodologies involving the fire resistance time, the most used is the tabular method, which associates fire resistance time values to structural elements based on minimum dimensions of the cross section. The tabular method is widely accepted by the technical-scientific community due to the fact that it is safe and practical. However, its main criticism is that it results in lower fire resistance times than advanced thermal and thermostructural analysis methods. The objective of this study was to evaluate the fire resistance time of reinforced concrete beams and compare it with the required fire resistance time recommended by the tabular method of NBR 15200 (ABNT, 2012).

The fire resistance time and required fire resistance time of reinforced concrete beams were evaluated using, respectively, numerical models developed based on the finite element method and the tabular method of NBR 15200 (ABNT, 2012). The influence of the following parameters was investigated: longitudinal reinforcement cover, characteristic compressive strength of concrete, beam height, longitudinal reinforcement area and arrangement of steel bars.

Among the evaluated parameters, the covering of the longitudinal reinforcement proved to be more relevant for the fire resistance time, justifying that the tabular method of NBR 15200 (ABNT, 2012) being strongly and directly influenced by this parameter. In turn, more resistant concretes, higher beams and higher steel grades have lower fire resistance time values. This is because beams in these conditions have greater resistance capacity at room temperature and, consequently, are subject to external stresses of greater magnitude. In some cases, the fire resistance time was even lower than the required fire resistance time prescribed by NBR 15200 (ABNT, 2012). Both the fire resistance time and the required fire resistance time were not influenced by the arrangement of the longitudinal reinforcements.

The present paper innovates by demonstrating the influence of other important design variables on the required fire resistance time of the NBR 15200 (ABNT, 2012). Among several conclusions, it was found that the load level to which the structural elements are subjected considerably affects their fire resistance time. For this reason, it was recommended that the methods for calculating the required fire resistance time consider the load level. In addition, the article quantifies the security degree of the tabular method and exposes some situations for which the tabular method proved to be unsafe. Moreover, in all the models analyzed, the relationship between the span and the vertical deflection associated with the failure of the beams in a fire situation was determined. With this, a span over average deflection relationship was presented in which beams in fire situations fail.

The ultimate capacity and ductility behavior of a reinforced concrete (RC) beam generally depends on its constituent material properties. This study aims to use ANSYS to accentuate the nonlinear parametric finite element (FE) simulations of RC sections under monotonic loading.

The concrete matrix and steel reinforcement are the primary constituent materials of RC beams. The material properties such as tensile reinforcement area, tensile bars yield strength, concrete compressive strength and strain rate in tensile reinforcement at nominal strength have significantly influenced the ultimate response of RC beams. Therefore, these intensive parameters are considered in this study to ascertain their effect on the RC beam's ultimate behavior. The nonlinear response up to the ultimate load capacity and the crack evolutions of RC beams are predicted efficiently.

The parametric study reveals that increasing the tensile steel reinforcements (from Ast = 213–857 mm2) significantly improves the ultimate load capacity by 229% and yield deflections by 20%. However, it declines the ultimate deflection by 47% and ductility by 56% substantially. Varying the strain limit (?tn = 0.010–0.0015) of tensile reinforcement has proficiently increased the ultimate load-resisting capacity by 20%, whereas the ductility declined by 62%. When the concrete strength increases (from fck = 25–65 MPa), the cracking load increases profoundly by 51%, whereas the ultimate capacity has found an insignificant effect.

The load-deflection response plots extracted from the proposed numerical model exhibit satisfactory accuracy (less than 9% deviation) against the experimental curves available in the literature, which emphasizes the proficiency of the proposed FE model.

This paper aims to describe carbon fiber reinforced plastics (CFRP) bars as a way to strengthen a 40-year-old stone arch bridge. To investigate effectiveness of the strengthening method, fielding-load tests were carried out before and after strengthening.

High-strength CFRP bars with minor radius, high tensile strain and good corrosion resistance were used in this reinforcement. The construction process for strengthening with CFRP bars – including CFRP bars cutting, crack grouting, original structural surface treatment, implant drilling, CFRP bars installation and pouring mortar – was described. Ultimate bearing capacity of the bridge after strengthening was discussed.

The results of concrete stress and deflection show that the strength and stiffness of the strengthened bridge are improved. The strengthened way with CFRP bars is feasible and effective.

This paper describes CFRP bars as a way to strengthen a 40-year-old stone arch bridge.

This research outlines the development and characterization of advanced composite materials and their potential applications in the aerospace industry for interior applications. Advanced composites, such as carbon-fiber-reinforced polymers and ceramic matrix composites, offer significant advantages over traditional metallic materials in terms of weight reduction, stiffness and strength. These materials have been used in various aerospace applications, including aircraft, engines and thermal protection systems.

The development of design of experiment–based hybrid aluminum composites using the stir-casting technique has further enhanced the performance and cost-effectiveness of these materials. The design of the experiment was followed to fabricate hybrid composites with nano cerium oxide (nCeO₂) and graphene nanoplatelets (GNPs) as reinforcements in the Al-6061 matrix.

The Al6061 + 3% nCeO2 + 3% GNPs exhibited a high hardness of 119.6 VHN. The ultimate tensile strength and yield strength are 113.666 MPa and 73.08 MPa, respectively. A uniform distribution of reinforcement particulates was achieved with 3 Wt.% of each reinforcement in the matrix material, which is analyzed using scanning electron microscopy. Fractography revealed that brittle and ductile fractures caused the failure of the fractured specimens in the tensile test.

The manufactured aluminum composite can be applied in a range of exterior and interior structural parts like wings, wing boxes, motors, gears, engines, antennas, floor beams, etc. The fan case material of the GEnx engine (currently using carbon-fiber reinforcement plastic) for the Boeing 7E7 can be another replacement with manufactured hybrid aluminum composite, which predicts weight savings per engine of close to 120 kg.

The development of hybrid reinforcements, where two or more types of reinforcements are used in combination, is also a novel approach to improving the properties of these composites. Advanced composite materials are known for their high strength-to-weight ratio. If the newly developed composite material demonstrates superior properties, it can potentially be used to replace traditional materials in aircraft manufacturing. By reducing the weight of aircraft structures, fuel efficiency can be improved, leading to reduced operating costs and environmental impact. This allows for a more customized solution for specific application requirements and can lead to further advancements in materials science and technology.

The global food waste and food scarcity paradox is steadfastly increasing. This study aims to examine the effects of digital nudging as forms of positive and negative reinforcement to change food waste behavior and found that nudging positive reinforcement modifies this habit.

A field experiment was conducted on 628 diners randomly split into experiment (n = 412) and control group (n = 216) in two separate dining locations over four weeks. Out of these, 412 diners were randomly subjected to tent cards with positive (n = 228) and negative (n = 184) reinforcement nudging and completed a questionnaire to ascertain if nudging affects their consumption behavior. Consumption waste per unit revenue was calculated from all 628 diners individually to analyze the financial impact between control and experiment groups.

SEM analysis reveals that positive reinforcement mediates between external motivators (social media and restaurant service) and reduction of food waste behavior. Further analysis also reveals that nudging has a higher three times effect on reducing food waste as compared with no nudging (control).

Positive messaging encourages behavior change more effectively as compared to negative ones. Gentle reminders of how everyone can personally be a “warrior” or “hero” in the fight against global food waste increases the likelihood of altruistic motivation in tackling these issues.

This study demonstrates how positive reinforcement in the form of nudges acts as key mediator to support reduction of consumer food waste on site, ultimately helping to reduce financial costs compared to those without nudges.

The purpose of this paper is to study Al-based green composite. To make composite samples of aluminium alloy (AA3105) with different weight percentages of rice husk ash (RHA) and eggshell (ES) particles as reinforcement, stir casting method was used.

Several other aspects, including the weight percent of reinforcing agent particles, the applied stress and the sliding speed, were taken into consideration. During the course of the wear test, the sliding distance that was recorded varied from a minimum of 1,000 m all the way up to a maximum of 3,135 m (10, 15, 20, 25 and 30 min). The typical range for normal loads is 8–24 N, and their speed is 1.58 m/s.

With the AA/ES/RHA composite, the wear rates decreases when the grain size of the reinforcing particles enhanced. Scanning electron microscopy images of worn surfaces show that at low speeds, delaminating and ploughing are the main causes of wear. At high speeds, ploughing is major cause of wear. Composites with better wear-resistant properties can be used in wide range of tribological applications, especially in the automotive industry. It was found that hardness increases at the same time as the weight of the reinforcement increases. Tensile and hardness were maximized at 10% reinforcement mix in Al3105.

In this work, ES and RHA has been used to develop green metal matrix composite to support green revolution as promoted/suggested by United Nations thus reducing the environmental pollution.

At present, teaching methods based on 2D drawings are still commonly used for educating students on the location of steel reinforcement bars in concrete. However, traditional teaching methods have limitations as students can find it difficult to understand 2D drawings. This study aims to develop an interactive and collaborative augmented reality environment (ICARE) using augmented reality (AR) technology to improve students' engagement in learning.

This study develops an ICARE prototype, which is organized into two stages: (1) The augmented teaching environment comprising of models and interactive components; (2) The AR collaborative application which uses Photon Unity Networking (PUN) plugin and Azure spatial anchors cloud service. The AR-based teaching environment runs with Universal Windows Platform (UWP) to enable development in the HoloLens 2 through Microsoft Visual Studio.

An experimental study was conducted, where 60 students were divided into three groups employing Drawings-based, building information modeling (BIM)-based and AR-based methods for teaching. After the test, the three groups of students were requested to complete a questionnaire. According to the analysis of the experimental results, the ICARE can improve students' comprehension, memory of learned materials and their ability to read and understand steel reinforcement drawings improving the quality of teaching, especially interactivity and engagement.

As illustrated in the experiments, the developed ICARE has outstanding performance over conventional approaches in civil engineering courses that can improve students' comprehension and memory of knowledge and their ability to read and understand steel bar drawings. This study provides empirical evidence that AR is a promising technology that can be integrated with traditional classroom instruction and can improve students' comprehension and memory of knowledge and their ability to read and understand steel bar drawings.