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Research On Realistic Simulation Method Of Burning Phenomenon In Virtual Surgery

Posted on:2018-12-18Degree:MasterType:Thesis
Country:ChinaCandidate:N Q FuFull Text:PDF
GTID:2404330542990009Subject:Electronic and communication engineering
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Virtual surgery system is an important application of virtual reality technology in medical field,it provides a three-dimensional display environment and an interactive platform for doctors to achieve a true simulation of clinical surgery.The common minimally invasive surgery through the electrical surgical equipment,laser and other tools can achieve cutting,coagulation,etc.The smoke produced during the operation has great harm to the operation and health of the operating personnel.Therefore,it is of great significance to simulate the burning smoke.In this paper,the traditional smoke simulation method has many problems such as the limitation of the number of particles,low computational efficiency and the lack of small scales of the smoke turbulence.On the basis of SPH fluid simulation,a hybrid algorithm of smoke improvement is proposed to improve the realistic and real-time performance of smoke simulation,the following works have been carried out:(1)Study on the physicochemical properties of surgical smoke.Combining the characteristics of the actual operation and analysing the relevant methods of smoke simulation in graphics in order to simulate the burning smoke.In the Lagrange perspective of Navier-Stokes Equation,the smoothed particle hydrodynamics(SPH)method is used to model the smoke.In this paper,we study the important steps such as the discretization,numerical solution of the model correlation equation and the smoke visualization.Comparing with the traditional particle system and texture method,the smoke realism has been greatly improved with high stability.(2)Use SPH to solve the fluid equation and improve the algorithm.Based on the basic framework of smoke model,several key problems which affect the simulation accuracy and computational efficiency are analyzed and improved.In order to solve the problem of uneven distribution of fluid density caused by the difference of the number of neighboring particles in the traditional SPH method,a boundary condition for a double layer adaptive particle is proposed.The boundary particle mass weight function is given to realize the stability simulation of incompressible flow with complex boundary,which improves the stability of the model.In order to improve the efficiency of program operation,the use of spatial mesh particle search reduces the number of particles in the problem area and the computation involved.The smoothing kernel function is modified to avoid the extra traversal operation,which can save computation cost and memory usage.(3)In order to keep the defects of the SPH method in the simulation of a series of gaseous phenomena such as turbulence and vortex,a new method based on SPH turbulence is proposed.We construct a high precision moving mesh around the smoke.By using FLIP to complete the calculation of the organ surface coarse particles flow,then we sample the vortex and use the vortex grid carrying SPH particles in the global flow to keep this scroll.Combined with the SPH turbulence model,it can effectively capture the generation and maintenance of the smoke vortex at a small scale.In this way the method can improve the details of the simulation.In this paper,we design and develop a prototype system of virtual surgery firing phenomenon which integrated module algorithm.According to experimental results:the simulation method of the smoke simulation based on grid and SPH particle mixture model has a good sense of reality,and the smoke details perform better.It meets the real-time requirement of virtual surgery system and enhances the sense of reality and immersion of virtual surgery system.The realistic simulation of the burning smoke enhances the accuracy of the training,which is helpful to improve the training effect of the virtual surgery system.
Keywords/Search Tags:virtual surgery, smoke, SPH, moving mesh, hybrid SPH vortex particle model
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