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Application of rare earth (RE) salts as a corrosion inhibitor was first proposed by Goldie and McCarrol in 1984. They showed that, with the addition of 0.001 M of Ce(NO₃) or La(NO₃) to 3.5% NaCl solution, the inhibition efficiencies were 91 and 82% for carbon steel, respectively. The aim of this paper is to study the inhibition of a mixture of Ce and La cations on the corrosion prevention of St37 carbon steel in aerated NaCl solutions using weight loss, potentiodynamic polarization, open circuit potential and constant potential measurements.

In this study, St37 steel was used as an experimental sample. The applied inhibitor was a powder mixture of Ce and La oxides with the ratio of Ce/La = 2/1. Each gram of this powder was dissolved in 4 cc acetic acid because of their insolubility in water. Steel samples were polished with 120 to 800 grit SiC polishing papers, deoxidized in 15 per cent HCl, and then ultrasonically cleaned in ethanol. They were degreased in acetone and were dried in a flow of hot air.

It has been shown that a mixture of RE cations (Ce and La) can be used as a corrosion inhibitor for carbon steel in NaCl containing solutions. The optimum inhibitor concentration was found to be 500 ppm with a maximum inhibition efficiency of 76%. An increase in Cl⁻ ion concentration and a rise in temperature from room temperature to 70°C can have an adverse effect on corrosion inhibition efficiency.

The results obtained from various experiments indicated that the mixture of Ce and La cations could be considered as a suitable inhibitor for carbon steel in low to medium chloride‐containing solutions. Owing to their non‐toxic nature, they may be suitable to use in potable water pipelines.

With the advent of AI-federated technologies, it is feasible to perform complex tasks in industrial Internet of Things (IIoT) environment by enhancing throughput of the network and by reducing the latency of transmitted data. The communications in IIoT and Industry 4.0 requires handshaking of multiple technologies for supporting heterogeneous networks and diverse protocols. IIoT applications may gather and analyse sensor data, allowing operators to monitor and manage production systems, resulting in considerable performance gains in automated processes. All IIoT applications are responsible for generating a vast set of data based on diverse characteristics. To obtain an optimum throughput in an IIoT environment requires efficiently processing of IIoT applications over communication channels. Because computing resources in the IIoT are limited, equitable resource allocation with the least amount of delay is the need of the IIoT applications. Although some existing scheduling strategies address delay concerns, faster transmission of data and optimal throughput should also be addressed along with the handling of transmission delay. Hence, this study aims to focus on a fair mechanism to handle throughput, transmission delay and faster transmission of data. The proposed work provides a link-scheduling algorithm termed as delay-aware resource allocation that allocates computing resources to computational-sensitive tasks by reducing overall latency and by increasing the overall throughput of the network. First of all, a multi-hop delay model is developed with multistep delay prediction using AI-federated neural network long–short-term memory (LSTM), which serves as a foundation for future design. Then, link-scheduling algorithm is designed for data routing in an efficient manner. The extensive experimental results reveal that the average end-to-end delay by considering processing, propagation, queueing and transmission delays is minimized with the proposed strategy. Experiments show that advances in machine learning have led to developing a smart, collaborative link scheduling algorithm for fairness-driven resource allocation with minimal delay and optimal throughput. The prediction performance of AI-federated LSTM is compared with the existing approaches and it outperforms over other techniques by achieving 98.2% accuracy.

With an increase of IoT devices, the demand for more IoT gateways has increased, which increases the cost of network infrastructure. As a result, the proposed system uses low-cost intermediate gateways in this study. Each gateway may use a different communication technology for data transmission within an IoT network. As a result, gateways are heterogeneous, with hardware support limited to the technologies associated with the wireless sensor networks. Data communication fairness at each gateway is achieved in an IoT network by considering dynamic IoT traffic and link-scheduling problems to achieve effective resource allocation in an IoT network. The two-phased solution is provided to solve these problems for improved data communication in heterogeneous networks achieving fairness. In the first phase, traffic is predicted using the LSTM network model to predict the dynamic traffic. In the second phase, efficient link selection per technology and link scheduling are achieved based on predicted load, the distance between gateways, link capacity and time required as per different technologies supported such as Bluetooth, Wi-Fi and Zigbee. It enhances data transmission fairness for all gateways, resulting in more data transmission achieving maximum throughput. Our proposed approach outperforms by achieving maximum network throughput, and less packet delay is demonstrated using simulation.

Our proposed approach outperforms by achieving maximum network throughput, and less packet delay is demonstrated using simulation. It also shows that AI- and IoT-federated devices can communicate seamlessly over IoT networks in Industry 4.0.

The concept is a part of the original research work and can be adopted by Industry 4.0 for easy and seamless connectivity of AI and IoT-federated devices.

This paper aims to investigate the experimental behavior and the reliability of concrete columns repaired using fiber-reinforced polymers (FRPs) under axial compression loading. The expression of the ultimate axial resistance was assessed from the experimental data of damaged concrete cylinders repaired by externally bonded double-FRP spiral strips.

The tested columns bearing capacity mainly depends of the elasticity modulus of both damaged and undamaged concrete have been considered in addition to the applied load and the cylinder diameter as random variables in the expression of the failure criterion. The reliability indicators were assessed using first order second moment method.

The emphasized test results, statistically fitted show that the strength has been retrofitted for all repaired specimens whatever the degree of initial damage. However, the gain in axial strength is inversely proportional to the degree of damage.

The efficiency of a new FRP repair procedure using double-spiral strips was studied. This research provides a technical and economical solution for retrofitting existing concrete columns. Finally, the random character of the variables that govern the studied system shows the accuracy and safety of the proposed original design.

The purpose of this study is to improve the corrosion resistance of the transmission towers by Zinc-aluminum-magnesium (Zn-Al-Mg) coatings doped with rare earths lanthanum (La) and cerium (Ce) (denoted as Zn-Al-Mg-Re) in Q345 steel.

The phase structure of Zn-Al-Mg-Re composite coatings has been determined by X-ray diffraction, whereas their surface morphology and cross-sectional microstructure as well as cross-sectional elemental composition have been analyzed by scanning electron microscopy and energy-dispersive spectrometry. Moreover, the corrosion resistance of Zn-Al-Mg-Re composite coatings has been evaluated by acetic acid accelerated salt spray test of copper strip.

Experimental results show that doping with La and Ce favors to tune the composition (along with the generation of new phase, such as LaAl₃ or Al₁₁Ce₃) and refine the microstructure of Zn-Al-Mg galvanizing coatings, thereby significantly improving the corrosion resistance of the coatings. Particularly, Zn-Al-Mg-Re with 0.15% (mass fraction) La exhibits the best corrosion resistance among the tested galvanizing coatings.

Zinc-aluminum-magnesium (Zn-Al-Mg) coatings doped with rare earths lanthanum (La) and cerium (Ce) (denoted as Zn-Al-Mg-Re) have been prepared on Q345 steel substrate by hot-dip galvanizing so as to improve the corrosion resistance of the transmission towers, and to understand the corrosion inhibition of the Zn-Al-Mg-Re coating.

This paper introduces control strategy to enhance the performance of a novel quadrotor unmanned aerial vehicle designed for medical payload delivery. The aim is to achieve precise control and stability when carrying and releasing payloads, which alter the quadrotor’s mass and inertia characteristics.

The equations of motion specific to the payload-carrying quadrotor are derived. A feedforward-proportional-integral-derivative (FF-PID) control strategy is then proposed to address the dynamic changes during payload release. The PID components use propeller speed/orientation information for stability. FF terms based on derivatives of desired position/orientation variables enable adaptation to real-time mass fluctuations.

Extensive simulations, encompassing various fault scenarios, substantiate the effectiveness of the FF-PID approach. Notably, our findings demonstrate superior performance in maintaining altitude precision and stability during critical phases such as takeoff, payload release and landing. Graphical representations of thrust and mass dynamics distinctly illustrate the payload release event. In contrast to the linear quadratic regulator (LQR) and conventional PID control, which encountered difficulties during the payload release process, our approach proves its robustness and reliability.

This study, primarily based on simulations, demands validation through real-world testing in diverse conditions. Uncertainties in dynamic parameters, external factors and the applicability of the proposed approach to other quadrotor configurations require further investigation. Additionally, this research focuses on controlled payload release, leaving unexplored the challenges posed by unforeseen scenarios or disturbances. Hence, adaptability and fault tolerance necessitate further exploration. While our work presents a promising approach, practical implementation, adaptability and resilience to unexpected events are vital considerations for future research in the field of autonomous aerial medical deliveries.

The proposed control strategy promises enhanced efficiency, reliability and adaptability for autonomous aerial medical deliveries in critical scenarios.

The innovative control strategy introduced in this study holds the potential to significantly impact society by enhancing the reliability and adaptability of autonomous aerial medical deliveries. This could lead to faster and more efficient delivery of life-saving supplies to remote or disaster-affected areas, ultimately saving lives and reducing suffering. Moreover, the technology’s adaptability may have broader applications in fields like disaster relief, search and rescue missions, and industrial cargo transport. However, its successful integration into society will require careful regulation, privacy safeguards and ethical considerations to ensure responsible and safe deployment while addressing potential concerns related to noise pollution and privacy intrusion.

While PID control of quadrotors is extensively studied, payload release dynamics have been overlooked. This research studies integration of FF control to enable PID adaptation for a novel payload delivery application.

This study aims to examine the challenges in the implementation of energy management systems in residential buildings to lower the running cost and achieve a better energy-efficient building.

This study adopted a mixed research method. Quantitative data was gathered by issuing a research questionnaire to 20 Delphi experts, while qualitative data was acquired through a Systematic Literature Review. Data received was analyzed using the descriptive analysis method.

The findings revealed that the main barriers to incorporating energy management systems (EMSs) in residential buildings consist of a lack of awareness of energy management systems, lack of management commitment to energy management, lack of knowledge about energy management systems, lack of funds for energy management systems, resistance to energy management technology by the property owners and property managers, distrust and resistance to energy management technology by the property owners, high initial cost of energy management technologies, shortage of technicians for energy management technologies, the nonexistence of local manufacturers of energy management equipment, lack of incentives for efficient energy management and high repair costs of energy management technologies.

The specific focus on residential buildings may limit the applicability of findings to commercial or industrial sectors. Further research is warranted to accommodate other energy-consuming sectors.

People’s perceptions, either wrong or correct, affect their ability to make an informed decision to adopt energy management systems, denying them the opportunity to reap the associated benefits. Therefore, there is an urgent need for the residential industry stakeholders and the government to increase educational opportunities for property owners, managers and property tenants on the importance of energy management systems.

This research presents the potential obstacles and problematic areas that residents may encounter while using these energy management systems. Consequently, they will be able to make a well-informed choice when installing energy management systems. Moreover, the research elucidates the identification of novel perspectives and also unexamined obstacles that impede the widespread use of energy management systems in residential buildings.

The rotorcraft technology is very interesting area since last few decades due to variety of applications. One of the rotorcrafts is the quadrotor unmanned aerial vehicle (QUAV), which contains four rotors mounted on an airframe with an onboard controller. The QUAV is a highly nonlinear system and underactuated. Its controller design is very challenging task, and the need of controller is to make it autonomous based on mission planning. The purpose of this study is to design a controller for quadrotor UAV for attitude stabilization and trajectory tracking problem in presence of external environmental disturbances such as wind gust.

To address this problem, the model predictive control has been designed for attitude control and feedback linearization control for the position control using the linear parameter varying (LPV) approach. The trajectory tracking problem has been addressed using the circular trajectory and helical trajectory.

The simulation results show the efficient performance with good trajectory tracking even in presence of external disturbances in both the scenarios considered, one for circular trajectory tracking and other for helical trajectory tracking.

The novelty of the work came from using the LPV approach in controller design, which increases the robustness of the controller in presence of external disturbances.

Inconel 718 (IN718) is a high-performance nickel-based superalloy with high oxidation-corrosion-temperature resistance, high strength (tensile, fatigue, creep and rupture), durability, toughness, hardness and dimensional stability, which is difficult to machine with traditional fabrication methods. To overcome these difficulties, wire electrical discharge machining (WEDM), one of the modern manufacturing methods, is used.

Main performance criteria in WEDM; material removal rate (MRR), cutting speed, surface roughness, cutting width (kerf) and wire wear rate. In this study, the effect of processing parameters on kerf and MRR because of processing IN718 in WEDM was investigated. Machining parameters, voltage, wire feed rate and dielectric fluid pressure were determined. Deionized water was used as a dielectric fluid and 0.3 mm brass wire was used as wire in the experiments. Gray Relational Analysis (GRA), which is one of the multi-criteria decision-making methods, has been applied for the optimization of the machining parameters in the cutting process with the WEDM. Analysis of variance (ANOVA) was used to determine the effect percentages of the cut-off parameters.

The parameter with the highest effect was determined as tension with a rate of 76.95% for kerf and 91.21% for MRR.

The novel approach uses Taguchi-based GRA optimization as a result of cutting IN718 with WEDM, reducing cost and time consumption.