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With the advancement of technology and the increasing integration of aircraft into daily life, there is a growing demand for enhanced wing optimization. In response, this study provides a summary and discussion of common research directions and achievements in airfoil optimization, with the aim of identifying optimal solutions. Based on a review of the literature and an examination of core airfoil theory, four key research directions are identified: data measurement, airfoil structure, functional diversity, and environmental adaptability. Recent advancements in artificial intelligence (AI) have been extensively integrated into data measurement processes, particularly through the application of AI models for simulating experiments across diverse scenarios. This integration has significantly enhanced data accuracy while reducing experimental costs. The study concludes that the primary challenge remains achieving high-precision measurement of airfoil data, while functional innovation represents a prominent and actively pursued research focus. With the increasing range of applications for aircraft wings, there has been a growing demand for airfoil profiles that can perform effectively across diverse and demanding scenarios. Examples include hovering technologies and the adaptability of wing materials to extreme environmental conditions.
Published in: Academic Journal of Science and Technology
Volume 20, Issue 2, pp. 254-263
DOI: 10.54097/kp2y4985