On December 6, 2019, Dr. Yu xiaochuan, from the university of New Orleans, gave a lecture entitled "predicting the trajectory of a cylinder with Unscented Transformation method" to teachers and students in lecture hall 109 of haiyang building.
The lecture mainly proposed that when the offshore facilities such as offshore platforms, ships and wharf hoisting operations may be affected by human error or natural factors (such as wind, waves, etc.), resulting in the lifting of cargo (such as oil exploration pipes, pipelines, torpedoes, etc.) fall into the water accidents occur. Objects entering the water may cause direct damage to the hoisting cargo, while objects falling into the water may also damage submarine cables, various oil and gas pipelines, etc., resulting in more serious secondary accidents. In order to avoid the occurrence of the above situation and timely stop loss, the position of the falling object and the movement path in the water should be located in the minimum time. However, commercial software on the market that can be used to calculate the motion trajectory of falling objects has some problems, such as large deviation between simulated motion trajectory and experimental motion trajectory, low accuracy of calculation, and long calculation time. Therefore, Dr. Yu xiaochuan proposed the Unscented Transformation method to predict the trajectory of a cylinder in water.
Since the number of objects falling into water accidents is relatively small, the method of mathematical probability combined with experiment is adopted, which first considers the trajectory in the two-dimensional state and then extends to the three-dimensional state (adding the influence of wave water flow). The experiment shows that the behavior of the object is random when there is a small disturbance at the initial moment when the object falls into the water. There are various trajectories that can be derived from experience. In addition, the numerical results also show that small changes in the initial state, such as drop Angle, rolling frequency, and the selection of drag coefficient, will affect the shape of the falling trajectory. If the initial state obeys the gaussian distribution, it can be regarded as a nonlinear prediction problem. The Unscented Transform (UT) method is a deterministic sampling method used to predict motion trajectories. Firstly, the system expression of three degrees of freedom as the model of state space is given. Secondly, the interval estimation method is adopted to solve this prediction problem through UT method. Finally, the predicted trajectory is compared with the experimental data. Based on two parameters, an evaluation method for predicting the accuracy of the object's entry trajectory is proposed. On December 6, 2019, Dr. Yu xiaochuan, from the university of New Orleans, gave a lecture entitled "predicting the trajectory of a cylinder with Unscented Transformation method" to teachers and students in lecture hall 109 of haiyang building.
The lecture mainly proposed that when the offshore facilities such as offshore platforms, ships and wharf hoisting operations may be affected by human error or natural factors (such as wind, waves, etc.), resulting in the lifting of cargo (such as oil exploration pipes, pipelines, torpedoes, etc.) fall into the water accidents occur. Objects entering the water may cause direct damage to the hoisting cargo, while objects falling into the water may also damage submarine cables, various oil and gas pipelines, etc., resulting in more serious secondary accidents. In order to avoid the occurrence of the above situation and timely stop loss, the position of the falling object and the movement path in the water should be located in the minimum time. However, commercial software on the market that can be used to calculate the motion trajectory of falling objects has some problems, such as large deviation between simulated motion trajectory and experimental motion trajectory, low accuracy of calculation, and long calculation time. Therefore, Dr. Yu xiaochuan proposed the Unscented Transformation method to predict the trajectory of a cylinder in water.
Since the number of objects falling into water accidents is relatively small, the method of mathematical probability combined with experiment is adopted, which first considers the trajectory in the two-dimensional state and then extends to the three-dimensional state (adding the influence of wave water flow). The experiment shows that the behavior of the object is random when there is a small disturbance at the initial moment when the object falls into the water. There are various trajectories that can be derived from experience. In addition, the numerical results also show that small changes in the initial state, such as drop Angle, rolling frequency, and the selection of drag coefficient, will affect the shape of the falling trajectory. If the initial state obeys the gaussian distribution, it can be regarded as a nonlinear prediction problem. The Unscented Transform (UT) method is a deterministic sampling method used to predict motion trajectories. Firstly, the system expression of three degrees of freedom as the model of state space is given. Secondly, the interval estimation method is adopted to solve this prediction problem through UT method. Finally, the predicted trajectory is compared with the experimental data. Based on two parameters, an evaluation method for predicting the accuracy of the object's entry trajectory is proposed. These two parameters can be directly applied to the salvage and recovery of air-dropped objects on the sea. In addition, the numerical results show that the UT method is an effective method to predict the trajectory of the cylindrical free-fall.
It is believed that in the future, UT method can have higher accuracy, less computation time, and be applied to predict the trajectory of water entering objects of other shapes. In the accident prevention, timely stop loss play a greater role.
In the report, Dr. Yu xiaochuan patiently answered the students' questions, and also guided some of the students' research directions, effectively expanding the students' horizons.
