神经外科颅骨磨削温度场预测新模型

基于恒定热流密度的温度场理论计算值与实际温度值的误差较大，是当前磨削温度场理论研究的瓶颈。建立了不同冷却条件下的对流换热系数及材料内部的热传导模型，通过实时采集动态磨削力，利用高次高斯函数拟合建立了动态热流密度模型，并以此为基础建立了神经外科骨磨削温度场预测新模型。在干式磨削、喷雾式及纳米粒子射流喷雾式冷却条件下对骨磨削温度场进行了数值分析，并采用与人体颅骨力学性能最相近的新鲜牛股骨密质骨，采用羟基磷灰石纳米粒子及生理盐水进行了试验验证。结果表明，与试验测得温度值相比，采用基于恒定热流密度的温度场模型计算的温度值误差为18.8%，而采用新模型计算的温度值误差为6.6%，理论分析与试验结果吻合，即骨磨削温度场预测新模型更符合实际工况。

A New Model for Predicting Neurosurgery Skull Bone Grinding Temperature Field

The temperature field theory based on the steady heat flux density has a large error between the calculated value and the actual temperature value, which is the bottleneck of the theoretical study of the grinding temperature field. The convective heat transfer coefficient and thermal conductivity model in materials is established firstly in this paper, and the dynamic heat flux model is established by using the high order Gauss function fitting to acquire the dynamic grinding force in real-time, on the basis of which, a new prediction model of neurosurgery bone grinding temperature field is established. The numerical analysis of the grinding temperature field is carried out under dry grinding, mist and nanoparticle jet mist cooling. The mechanical property of fresh bovine femur is closest to the human skull bone, and then the verification grinding experiments of fresh bovine femurs are carried out using hydroxyapatite nanoparticles and normal saline. The results show that, compared with the experimentally measured temperature, model error loading steady heat flux is 18.8%, and model error using the new model is 6.6%. The theoretical analysis of the new model is consistent with the experimental results, that is, the new prediction model of the bone grinding temperature field is more in line with the actual conditions.