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4. Effect of Microwave Power and Gas Flow Rate on the Combustion Characteristics of the ADN-based Liquid Propellant.

Author

Pan, Sheng, Zhao, Chenghao, Zhang, Dechao, Hou, Yangyang, Su, Gaoshi, Liu, Xuhui, Yu, Yusong, and Shen, Jiannan

Subjects
GAS flow, PROPELLANTS, MICROWAVE plasmas, ELECTRICAL load, COMBUSTION, MICROWAVES
Abstract

As a new type of energy-containing material, Ammonium dinitramide based liquid propellant has the advantages of being green, having low toxicity, good stability, and high safety performance. Traditional catalytic combustion methods require preheating of the catalytic bed and deactivation of the catalytic particles at high temperatures, while microwave ignition methods can effectively solve these problems. To study the combustion characteristics of ADN-based liquid propellants during microwave ignition, the influence of microwave power and gas flow rates on the combustion process are analyzed using experimental methods. A high-speed camera was used to observe the enhanced effects of microwave power and gas flow on plasma and flame. Combined with temperature measurement, the combustion process of ADN-based liquid propellants under the action of plasma was analyzed. The combustion process in the presence of microwaves was observed by comparing parameters such as flame length, flame temperature, and radical intensity. Those results show that, with the increase in microwave power, the luminous burning area of the flame grows significantly. The microwave power is increased by 250 W each, and the flame jet length is increased by nearly 20%. The increase in microwave power also leads to an increase in propellant combustion temperature, however, this increase gradually slows down. At a gas flow rate of 20 L/min, the ADN-based liquid propellant showed the best combustion performance with a maximum jet length of 14.51 cm and an average jet length increase of approximately 85.9% compared to 14 L/min. Too much gas flow rate will hinder the development of the jet, while the high-velocity airflow will have a cooling effect on the flame temperature. The results provide a basis for the specific parameter design of microwave ignition and promote the application of ADN-based liquid propellants in the aerospace field. [ABSTRACT FROM AUTHOR]

Published
2023
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7. Application of image segmentation in inspection of welding : Practical research in MATLAB

Author

Shen, Jiannan

Subjects
Teknik och teknologier, threshold, Engineering and Technology, image segmentation, clustering
Abstract

As one of main methods in modern steel production, welding plays a very important role in our national economy, which has been widely applied in many fields such as aviation, petroleum, chemicals, electricity, railways and so on. The craft of welding can be improved in terms of welding tools, welding technology and welding inspection. However, so far welding inspection has been a very complicated problem. Therefore, it is very important to effectively detect internal welding defects in the welded-structure part and it is worth to furtherly studying and researching.In this paper, the main task is research about the application of image segmentation in welding inspection. It is introduced that the image enhancement techniques and image segmentation techniques including image conversion, noise removal as well as threshold, clustering, edge detection and region extraction. Based on the MATLAB platform, it focuses on the application of image segmentation in ray detection of steeled-structure, found out the application situation of three different image segmentation method such as threshold, clustering and edge detection.Application of image segmentation is more competitive than image enhancement because that:1. Gray-scale based FCM clustering of image segmentation performs well, which can exposure pixels in terms of grey value level so as that it can show hierarchical position of related defects by grey value.2. Canny detection speeds also fast and performs well, that gives enough detail information around edges and defects with smooth lines.3. Image enhancement only could improve image quality including clarity and contrast, which can’t give other helpful information to detect welding defects.This paper comes from the actual needs of the industrial work and it proves to be practical at some extent. Moreover, it also demonstrates the next improvement direction including identification of welding defects based on the neural networks, and improved clustering algorithm based on the genetic ideas. Program: Magisterutbildning i informatik

Published
2012

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