Parameters optimization of a walnut shell-kernel separation device using response surface methodology and ANN coupled genetic algorithm

Authors

  • Hualong Liu 1. College of Mechanical and Electronic Engineering, Tarim University, Alar, Xinjiang 843300, China 2. Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar, Xinjiang 843300, China 3. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Alar, Xinjiang 843300, China
  • Biqi Mao 1. College of Mechanical and Electronic Engineering, Tarim University, Alar, Xinjiang 843300, China 2. Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar, Xinjiang 843300, China 3. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Alar, Xinjiang 843300, China
  • Hong Zhang 1. College of Mechanical and Electronic Engineering, Tarim University, Alar, Xinjiang 843300, China 2. Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar, Xinjiang 843300, China 3. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Alar, Xinjiang 843300, China
  • Peiyu Chen 1. College of Mechanical and Electronic Engineering, Tarim University, Alar, Xinjiang 843300, China 2. Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar, Xinjiang 843300, China 3. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Alar, Xinjiang 843300, China
  • Yurong Tang 1. College of Mechanical and Electronic Engineering, Tarim University, Alar, Xinjiang 843300, China 2. Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar, Xinjiang 843300, China 3. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Alar, Xinjiang 843300, China
  • Xiuwen Fan 1. College of Mechanical and Electronic Engineering, Tarim University, Alar, Xinjiang 843300, China 2. Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar, Xinjiang 843300, China 3. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Alar, Xinjiang 843300, China
  • Yongcheng Zhang 1. College of Mechanical and Electronic Engineering, Tarim University, Alar, Xinjiang 843300, China 2. Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar, Xinjiang 843300, China 3. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Alar, Xinjiang 843300, China
  • Jianping Wang 1. College of Mechanical and Electronic Engineering, Tarim University, Alar, Xinjiang 843300, China 2. Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar, Xinjiang 843300, China 3. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Alar, Xinjiang 843300, China
  • Yong Zeng 1. College of Mechanical and Electronic Engineering, Tarim University, Alar, Xinjiang 843300, China 2. Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar, Xinjiang 843300, China 3. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Alar, Xinjiang 843300, China

DOI:

https://doi.org/10.25165/ijabe.v18i5.9375

Keywords:

walnut, two-stage separation device, multi-objective optimization, response surface methodology, artificial neural network

Abstract

Walnut shell-kernel separation after cracking is crucial for providing raw materials for further processing. However, impurities and losses during separation limit complete separation. To address this, a two-stage tandem separation device was designed and optimized. Computational fluid dynamics (CFD) was used to analyze the effects of four bent duct structures on the flow field. Response surface methodology (RSM) and artificial neural networks (ANN) were employed to predict separation performance under various conditions. Both models accurately predicted performance, with ANN showing superior predictive ability. The optimal design was determined using non-dominated sorting genetic algorithm-II (NSGA-II) and technique for order preference by similarity to an ideal solution (TOPSIS): the inclination of the first stage deflector plate (x1) was 39°,the inclination of the second stage deflector plate (x2) was 36°, the wind speed of the first stage fan (x3) was 21 m/s, and the wind speed of the second stage fan (x4) was 13.5 m/s; impurity rate (y1) was 4.51%, and loss rate (y2) was 6.62%. Compared with traditional single-stage devices, the optimized device reduced impurity rate by 73.98% to 77.55% and loss rate by 9.44% to 53.96%, significantly improving separation efficiency and quality. This study provides theoretical guidance for designing and optimizing shell-kernel separation devices. Keywords: walnut, two-stage separation device, multi-objective optimization, response surface methodology, artificial neural network DOI: 10.25165/j.ijabe.20251805.9375 Citation: Liu H L, Mao B Q, Zhang H, Chen P Y, Tang Y R, Fan X W, et al. Parameters optimization of a walnut shell-kernel separation device using response surface methodology and ANN coupled genetic algorithm. Int J Agric & Biol Eng, 2025; 18(5): 306–316.

Author Biographies

Biqi Mao, 1. College of Mechanical and Electronic Engineering, Tarim University, Alar, Xinjiang 843300, China 2. Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar, Xinjiang 843300, China 3. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Alar, Xinjiang 843300, China

PhD, associate professor

Peiyu Chen, 1. College of Mechanical and Electronic Engineering, Tarim University, Alar, Xinjiang 843300, China 2. Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar, Xinjiang 843300, China 3. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Alar, Xinjiang 843300, China

PhD, associate professor

Xiuwen Fan, 1. College of Mechanical and Electronic Engineering, Tarim University, Alar, Xinjiang 843300, China 2. Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar, Xinjiang 843300, China 3. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Alar, Xinjiang 843300, China

Master, associate professor

Yongcheng Zhang, 1. College of Mechanical and Electronic Engineering, Tarim University, Alar, Xinjiang 843300, China 2. Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar, Xinjiang 843300, China 3. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Alar, Xinjiang 843300, China

Master, associate professor

Jianping Wang, 1. College of Mechanical and Electronic Engineering, Tarim University, Alar, Xinjiang 843300, China 2. Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar, Xinjiang 843300, China 3. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Alar, Xinjiang 843300, China

Master, associate professor

Yong Zeng, 1. College of Mechanical and Electronic Engineering, Tarim University, Alar, Xinjiang 843300, China 2. Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar, Xinjiang 843300, China 3. Key Laboratory of Tarim Oasis Agriculture, Ministry of Education, Alar, Xinjiang 843300, China

PhD, associate professor

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Published

2025-10-27

How to Cite

Liu, H., Mao, B., Zhang, H., Chen, P., Tang, Y., Fan, X., … Zeng, Y. (2025). Parameters optimization of a walnut shell-kernel separation device using response surface methodology and ANN coupled genetic algorithm. International Journal of Agricultural and Biological Engineering, 18(5), 306–316. https://doi.org/10.25165/ijabe.v18i5.9375

Issue

Vol. 18 No. 5 (2025): IJABE

Section

Agro-product and Food Processing Systems

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