Zhiwei Li, Dingding Li, Yulong Zhou, Haoping Peng, Aijun Xie and Jianhua Wang
This paper aims to contribute to the performance improvement and the broader application of hot-dip galvanized coating.
Abstract
Purpose
This paper aims to contribute to the performance improvement and the broader application of hot-dip galvanized coating.
Design/methodology/approach
First, the ability to provide barrier protection, galvanic protection, and corrosion product protection provided by hot-dip galvanized coating is introduced. Then, according to the varying Fe content, the growth process of each sublayer within the hot-dip galvanized coating, as well as their respective microstructures and physical properties, is presented. Finally, the electrochemical corrosion behaviors of the different sublayers are analyzed.
Findings
The hot-dip galvanized coating is composed of η-Zn sublayer, ζ-FeZn13 sublayer, δ-FeZn10 sublayer, and Γ-Fe3Zn10 sublayer. Among these sublayers, with the increase in Fe content, the corrosion potential moves in a noble direction.
Research limitations/implications
There is a lack of research on the corrosion behavior of each sublayer of hot-dip galvanized coating in different electrolytes.
Practical implications
It provides theoretical guidance for the microstructure control and performance improvement of hot-dip galvanized coatings.
Originality/value
The formation mechanism, coating properties, and corrosion behavior of different sublayers in hot-dip galvanized coating are expounded, which offers novel insights and directions for future research.
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Abstract
Purpose
The promotion of new energy vehicles (EVs) is an effective way to achieve low carbon emission reduction. This paper aims to investigate the optimal pricing of automotive supply chain members in the context of dual policy implementation while considering consumers' low-carbon preferences.
Design/methodology/approach
This article takes manufacturers, retailers and consumers in a main three-level supply chain as the research object. Stackelberg game theory is used as the theoretical guidance. A game model in which the manufacturer is the leader and the retailer is the follower is established. The author also considered the impact of carbon tax policies, subsidy policies and consumer preferences on the results. Furthermore, the author investigates the optimal decision-making problem under the profit maximization model.
Findings
Through model solving, it is found that the pricing of EVs is positively correlated with the unit price of carbon and the amount of subsidies. The following conclusions can be obtained by numerical analysis of each parameter. Changes in carbon prices have a greater impact on conventional gasoline vehicles. Based on the numerical analysis of parameter β, it is also found that when the government subsidizes consumers, supply chain members will increase their prices to obtain partial subsidies. Compared with retailers, low-carbon preferences have a greater impact on manufacturers.
Research limitations/implications
The new energy automobile industry involves many policies, including tax cuts, tax exemptions and subsidies. The policy environment faced by the members of a supply chain is complex and diverse. Therefore, the analysis in this article is based only on partial policies.
Originality/value
The authors innovatively combine the three factors of subsidy policy, carbon tax policy and consumer low-carbon preference, with research on the pricing of EVs. The influence of policy factors and consumer preferences on the pricing of EVs is studied.
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Lina Qiu, Jin Tian, Weiwei Zhang, Aijun Gong and Weiyu Zhao
Sulfate-reducing bacteria (SRB) are recognized by scholars as the most important class of bacteria leading to corrosion of metal materials. It is important to use the properties…
Abstract
Purpose
Sulfate-reducing bacteria (SRB) are recognized by scholars as the most important class of bacteria leading to corrosion of metal materials. It is important to use the properties of microorganisms to inhibit the growth of SRB in the corrosion protection of metal materials and to protect the environment.
Design/methodology/approach
In this work, the behavior of anaerobic Thiobacillus denitrificans (TDN) intracellular enzyme inhibition of SRB corrosion of EH36 steel was investigated with electrochemical impedance spectroscopy, biological detection technology and X-ray photoelectron spectroscopy.
Findings
Results showed that the SRB crude intracellular enzyme affected the corrosion behavior of EH36 steel greatly and the purified TDN intracellular enzyme inhibits SRB intracellular enzyme corrosion to EH36 steel.
Originality/value
A perfect enzyme activity inhibition mechanism will provide theoretical guidance for the selection and application of anticorrosion microorganisms, which is of scientific significance in the field of microbial anticorrosion research.
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Abstract
Purpose
The purpose of this paper is to introduce an improved system identification method for small unmanned helicopters combining adaptive ant colony optimization algorithm and Levy’s method and to solve the problem of low model prediction accuracy caused by low-frequency domain curve fitting in the small unmanned helicopter frequency domain parameter identification method.
Design/methodology/approach
This method uses the Levy method to obtain the initial parameters of the fitting model, uses the global optimization characteristics of the adaptive ant colony algorithm and the advantages of avoiding the “premature” phenomenon to optimize the initial parameters and finally obtains a small unmanned helicopter through computational optimization Kinetic models under lateral channel and longitudinal channel.
Findings
The algorithm is verified by flight test data. The verification results show that the established dynamic model has high identification accuracy and can accurately reflect the dynamic characteristics of small unmanned helicopter flight.
Originality/value
This paper presents a novel and improved frequency domain identification method for small unmanned helicopters. Compared with the conventional method, this method improves the identification accuracy and reduces the identification error.
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Mati Ullah, Chunhui Zhao and Hamid Maqsood
The purpose of this paper is to design a hybrid robust tracking controller based on an improved radial basis function artificial neural network (IRBFANN) and a novel…
Abstract
Purpose
The purpose of this paper is to design a hybrid robust tracking controller based on an improved radial basis function artificial neural network (IRBFANN) and a novel extended-state observer for a quadrotor system with various model and parametric uncertainties and external disturbances to enhance the resiliency of the control system.
Design/methodology/approach
An IRBFANN is introduced as an adaptive compensator tool for model and parametric uncertainties in the control algorithm of non-singular rapid terminal sliding-mode control (NRTSMC). An exact-time extended state observer (ETESO) augmented with NRTSMC is designed to estimate the unknown exogenous disturbances and ensure fast states convergence while overcoming the singularity issue. The novelty of this work lies in the online updating of weight parameters of the RBFANN algorithm by using a new idea of incorporating an exponential sliding-mode effect, which makes a remarkable effort to make the control protocol adaptive to uncertain model parameters. A comparison of the proposed scheme with other conventional schemes shows its much better performance in the presence of parametric uncertainties and exogenous disturbances.
Findings
The investigated control strategy presents a robust adaptive law based on IRBFANN with a fast convergence rate and improved estimation accuracy via a novel ETESO.
Practical implications
To enhance the safety level and ensure stable flight operations by the quadrotor in the presence of high-order complex disturbances and uncertain environments, it is imperative to devise a robust control law.
Originality/value
A new idea of incorporating an exponential sliding-mode effect instead of conventional approaches in the algorithm of the RBFANN is used, which makes the control law resistant to model and parametric uncertainties. The ETESO provides rapid and accurate disturbance estimation results and updates the control law to overcome the performance degradation caused by the disturbances. Simulation results depict the effectiveness of the proposed control strategy.