Modeling and Validation of Thrust Prediction of Underwater Solid Rocket Motor

The solid rocket motor driven system is one of the common ways for submarines to launch underwater missiles. It has significant advantages in improving the missile’s water exit speed, anti-interference capability, and enemy striking power. The prediction of the underwater loading is a preliminary factor for the power system design of the underwater vehicle. This paper presents a rapid prediction method and validated by the experimental study for the underwater thrust of the solid rocket motor. Based on the potential flow assumption of the water field, a model of the bubble and a one-dimensional quasi-steady model of the nozzle are established to directly solve the flow status of the nozzle. The aerodynamic thrust and hydrodynamic thrust have been calculated and analyzed. The calculation results are within 5% error of the experimental results. Moreover, a design platform to predict the underwater thrust of the solid rocket motor has been developed based on Python and the PyQt library, which shows excellent system adaptability and computational efficiency.

Modeling and Prediction for the thrust on EPB TBMs under different geological conditions by considering mechanical decoupling

EPB TBMs(Earth pressure balance Tunneling Boring Machines) are extensively used in tunneling constructions because of its high efficiency and low disturbance on structures above ground. It is critically significant to predict the thrust acting on TBMs under different geological conditions for both the design of power system and the control of tunneling process. The interaction between the cutterhead and the ground is the core of excavation, through which geological conditions determine the thrust re-quirement combined with operating status and structural characteristics. This paper conducted a mechanical decoupling analysis to obtain a basic expression of the cutterhead-ground interactive stress. Then more engineering factors(such as cutterhead topological structure, underground overburden, thrusts on other parts, etc.) were further considered to establish a predicting model for the total thrust acting on a machine during tunneling. Combined with three subway projects under different geological conditions in China, the model was verified and used to analyze how geological, operating and structural parameters influence the acting thrust.

A data-driven approach for modeling and predicting the thrust force of a tunnel boring machine

Thrust prediction of a tunnel boring machine(TBM)is crucial for the life span of disc cutters,cost forecasting,and its design optimization.Many factors affect the thrust of a TBM.The rock pressure on the shield,advance speed,and cutter water pressure will all have a certain impact.In addition,geological conditions and other random factors will also influence the thrust and greatly increase the difficulty of modeling it,seriously affecting the efficiency of tunnel excavation.To overcome these challenges,this paper establishes a thrust prediction model for the TBM based on the combination of on-site quality record data and surrogate model technology.Firstly,the thrust composition and influencing factors are analyzed and the thrust is modeled using a surrogate model based on field data.After main factor screening based on the Morris method,the accuracy of the surrogate model is greatly improved.The Kriging model with the highest accuracy is selected to model the thrust and predict the thrust of the unexcavated section.The results show that the thrust model has better thrust prediction by selecting similar conditions for modeling and reasonably increasing modeling samples.The thrust prediction method of TBM based on the combination of field data and surrogate model can accurately predict the dynamic thrust of the load and can also accurately estimate its statistical characteristics and effectively improve the excavation plan.