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The air-supported membrane coal shed is widely used in bulk cargo terminals. It not only effectively protects goods from adverse weather conditions but also helps reduce coal dust and harmful gas emissions, promoting the green and sustainable development of ports. However, in practical engineering, the design parameters of the coal shed are often based on experience, making it difficult to accurately assess the quality of the structural design. The flexibility of the membrane material also makes the structure susceptible to deformation or tearing. This paper mainly focuses on modeling and solving the optimization design issues of air-supported membrane coal shed structures. According to the evaluation criteria for the form of air-supported membrane coal sheds, a multi-objective structural optimization model is established to minimize the maximum stress on the membrane surface, ensure uniform stress distribution, maximize structural stiffness, and minimize costs. The study utilizes a combined optimization approach using ANSYS 19.0 and MATLAB 2016a, incorporating an improved NSGA-II algorithm program developed in MATLAB into ANSYS for structural form analysis and load calculation. The research results indicate that the optimal solution reduces the maximum stress on the loaded membrane surface by 5.36%, shortens the maximum displacement by 30.3%, and saves on economic costs by 9.85%. Compared to traditional empirical design methods, the joint use of MATLAB and ANSYS for optimization design can provide more superior solutions, helping ports to achieve environmental protection and economic efficiency goals. [ABSTRACT FROM AUTHOR]

In the context of global carbon neutrality, ports face significant electricity demand for cargo handling and pressure to reduce carbon emissions. The abundant wind energy resources in port areas make wind power highly promising for port applications. The optimal selection of site and turbine types for wind power systems can effectively reduce emissions in ports, achieving sustainability and improving economic benefits. The practical implementation of wind energy systems considering practical constraints holds significant research significance. Taking Ningbo-Zhoushan Port as an example, this paper analyzes the wind energy resources in the port area and provides an overview of wind power system construction sites. Based on the actual conditions of the port area, this paper comprehensively reviews the site selection of wind turbines from the perspectives of wind resources, specific climates, and noise impacts. With the consideration of engineering preferences, this paper selects performance indicators based on the four mainstream turbine models and proposes a comprehensive weight determination method using the entropy weight method and analytic hierarchy process (AHP) to determine the weights of the indicators. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is then employed to score and compare four turbine plans, enabling the turbine selection process to consider both engineering preferences and objectivity, thereby enhancing the accuracy and reliability of wind turbine planning and achieving significant ecological and economic benefits through benefit analysis. [ABSTRACT FROM AUTHOR]

Greenhouse gas emission and subsequent global warming have attracted more and more attention all over the world. As one of the biggest emission sources, shipping industry is suffering great emission reduction pressure from the public. Although shipping industry can improve the energy efficiency by exploring new strategies to reduce the fuel cost and the emission to air, some deficiencies may be discovered in practice due to lack of a comprehensive consideration of other significant factors, such as safety factors. Therefore, energy efficiency management strategies that consider both safety and economy factors have more practical significance for enhancing the ship energy efficiency. In this article, a power supply model considering economy, emission reduction and safety was established, and a multi-objective optimization problem to keep the system working at a high safety level, a low CO2 emission and a moderate fuel consumption was proposed. Furthermore, the particle swarm optimization algorithm was adopted to solve the multi-objective optimization problem, and the obtained non-inferior solutions could help officers on duty to select the optimum main engine speed by weighing the economy and the safety of the ship. The results show that the proposed method of energy efficiency management could reduce the greenhouse gas emission and the energy efficiency operation index (EEOI) of the ship effectively. The trade-off between ship economy, emission and robustness of the power supply system was studied, which is meaningful to the energy efficiency improvement and the CO2 emission reduction under the safety requirement of power supply. [ABSTRACT FROM AUTHOR]