Introduction
Noise pollution is one of the most important problems associated with the aviation industry. It can lead to health problems as well as negative social and economic impacts. Examples of negative impacts of noise pollution include sleep disturbance, community annoyance, cardiovascular diseases, and mental health problems.
Noise pollution refers to the presence of excessive or harmful levels of sound in the environment that disrupts the natural acoustic balance and negatively affects human health and well-being. The expanding transportation network and the use of new energy sources other than fossil fuels have transformed society over the centuries. With the increasing demand due to population growth in modern society, regulations related to environmental pollution have been continuously developed and are becoming more stringent in terms of fuel consumption and noise pollution. Noise pollution is a particular concern for communities living near airports and wind turbine farms. The noise from aircraft during take-off and landing is a major concern.
The allocation of new coastal sites for wind turbines has become a serious problem, mainly due to the aerodynamic noise generated by wind turbines.
One of the most important causes of noise pollution is noise pollution from aerodynamic surfaces such as aircraft wings and wind turbine blades. The origin of this noise pollution is the flow separated on the wing. Today, with the help of relationships and methods such as numerical analysis relationships, in addition to identifying the location and intensity of separation, airfoils used in wind turbine wings and blades can be optimized with the help of methods such as postponing the separation point and controlling the flow separated from the desired surface by changing the airfoil shape in order to reduce noise pollution.
The research project Development of Design Tools for Wind Turbines with Reduced Aerodynamic Noise Pollution considers the actual shape of the airfoil(s) used in wind turbine blades, with the aim of developing acoustic prediction codes, which is done by a combination of analytical and numerical work. Another aspect of this work is the use of advanced CFD (Computational Fluid Dynamics) codes to generate accurate information from the airfoil boundary layers. In addition, an extensive set of wind tunnel measurements is carried out with the aim of validating each stage of the development of the prediction codes.
This research investigates the factors of noise pollution caused by airfoils (aircraft, wind turbines, etc.) on the environment and human health and the solution to reduce it.
 
Methodology
In this study, first, the factors causing noise pollution in various airfoils are studied, as well as the introduction of general relations and numerical analysis to predict the amount of noise pollution. These equations are derived from more basic equations such as RANS equations and simplified according to boundary layer changes in different conditions. Then, several practical and tested methods are introduced for better flow control and delaying the separation point in airfoils used in various fields. The methods introduced have been obtained experimentally and have been tested in industries such as wind turbines.
 
Conclusion
By identifying the factors affecting the production of noise pollution, such as flow separation, and making changes to the airfoil, such as adding geometric elements to the airfoil, with the help of existing methods such as using numerical analysis relations to predict and calculate these factors, it is possible to manufacture airfoils with lower noise pollution levels, which will reduce environmental damage caused by factors such as airplanes and wind turbine farms.
Significant advances have been made in recent years, contributing to a better understanding of flow physics, the development of more accurate and efficient aerodynamic models, the emergence of innovative simulation technologies, and the emergence of multidisciplinary engineering applications. Despite the comprehensive nature of this review, specific topics are not covered, in particular the applications of artificial intelligence and machine learning in experimental studies.
According to the World Health Organization, noise pollution can cause social discomfort and sleep deprivation in the short term, and cardiovascular disease and mental health problems in the long term. Technological advances are helping to reduce noise pollution, but the growing demand for air traffic means that more effort must be made by all stakeholders involved to reduce noise levels around airports using modern computational methods. People living in the vicinity of
airports are most affected by aircraft noise.
Today, with the emergence of solutions such as artificial intelligence algorithms, it is possible to create a system for producing optimal airfoils to reduce noise pollution at a lower cost and in less time, without the need to use numerical analysis relationships, and in a more accurate manner, which is not the purpose of this article and will be examined in future research.