A method for improving the simulation efficiency of trawl based on simulation stability criterion. (1st May 2016)

• Record Type: Journal Article
• Authors: Yao, Yeming; Chen, Yinglong; Zhou, Hua; Yang, Huayong
• Is Part Of: Ocean engineering. Volume 117(2016)
• Page Start: 63
• Page End: 77
• Publication Date: 2016-05-01
• Subjects: Trawl -- Numerical simulation -- Physical parameter optimize -- Step size -- Calculation efficiency -- Lumped-mass method; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2016.03.031
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: The lumped-mass method is one of the most fundamental methods to simulate the dynamic behavior of submerged flexible nets. However, the low calculation efficiency limits its applications. In order to improve the calculation efficiency, the numerical stability of lumped-mass method based on explicated Euler integral algorithm was investigated. The simulation stability criterion was derived as a function of simulation step size and the physical parameters of netting materials. A physical parameter optimization (PPO) method was put forward to calculate the desired values of the lumped-mass model's physical parameters based on stability criterion; length compensation was implemented to compensate the extra deformation of mesh bars caused by the changes of their stiffness. The PPO method can ensure the stability of the lumped-mass model with a desired simulation step size while minimizing the change to the physical parameters. A lumped-mass model of trawl gear was established with the PPO method, the simulation results were compared with those of the conventional lumped-mass method (without PPO) to validate the improvements. By using the PPO method, the calculation efficiency can be accelerated by 40 times while only inducing less than 2% error to the simulation results. Highlights: We derived the simulation stability criterion of lumped-mass method. The stability criterion is a function of step size and net material parameters. We developed a physical parameter optimization method to accelerate simulation. After optimization, the simulation efficiency can be accelerated by 40 times. After optimization, the error in the simulation results is less than 2%.