Changhe Li

By Min Yang, Changhe Li, Yanbin Zhang, Dongzhou Jia, Runze Li and Wenfeng Ding

Grinding is an indispensable form of machining, in which, a large amount of heat is transferred into workpiece surface, causing surface burn of the workpiece. Flood grinding is easy to cause pollution to the environment while dry grinding and minimum quantity lubrication (MQL) is insufficient of cooling and lubrication effect. The appearance of nanofluid minimum quantity lubrication cooling (NMQLC) technique can effectively solve the problem of heat transfer in grinding zone and also enhance the lubrication characteristics. In this chapter, NMQLC technique, including nanofluid preparation and atomization is summarized first; then a review on the mechanism of grinding thermodynamics under NMQLC condition is presented based on published literatures. Most of the studies, including investigation of grinding forces and temperatures, indicate that NMQLC has realized a lubrication-cooling effect close to that of flood lubrication. According to existing investigations, theoretical models of temperature field are concluded, heat source distribution model, thermal distribution coefficient model, and heat transfer coefficient model under NMQLC condition are developed, and temperature field control equation are determined. This chapter reviews and amasses the current state of the mechanism of grinding thermodynamics and also recommends ways to precision control the grinding temperature field.

Part of the book: Microfluidics and Nanofluidics

By Min Yang, Changhe Li, Liang Luo, Lan Dong, Dongzhou Jia, Runze Li, Mingzheng Liu, Xin Cui, Yali Hou, Yanbin Zhang, Teng Gao, Xiaoming Wang and Yunze Long

Clinical neurosurgeons used micro grinding to remove bone tissues, and drip irrigation-type normal saline (NS) is used with low cooling efficiency. Osteonecrosis and irreversible thermal neural injury caused by excessively high grinding temperature are bottleneck problems in neurosurgery and have severely restricted the application of micro grinding in surgical procedures. Therefore, a nanoparticle jet mist cooling (NJMC) bio-bone micro grinding process is put forward in this chapter. The nanofluid convective heat transfer mechanism in the micro grinding zone is investigated, and heat transfer enhancement mechanism of solid nanoparticles and heat distribution mechanism in the micro grinding zone are revealed. On this basis, a temperature field model of NJMC bio-bone micro grinding is established. An experimental platform of NJMC bio-bone micro grinding is constructed, and bone micro grinding force and temperatures at different measuring points on the bone surface are measured. The results indicated that the model error of temperature field is 6.7%, theoretical analysis basically accorded with experimental results, thus certifying the correctness of the dynamic temperature field in NJMC bio-bone micro grinding.

Part of the book: Advances in Microfluidic Technologies for Energy and Environmental Applications

By Yanbin Zhang, Changhe Li, Yongjun Zhao, Xin Cui, Xiufang Bai, Mingzheng Liu, Yali Hou, Min Yang, Naiqing Zhang, Heju Ji, Xiaoming Wang and Teng Gao

Numerous researchers have developed theoretical and experimental approaches to force prediction in surface grinding under dry conditions. Nevertheless, the combined effect of material removal and plastic stacking on grinding force model has not been investigated. In addition, predominant lubricating conditions, such as flood, minimum quantity lubrication (MQL), and nanofluid minimum quantity lubrication (NMQL), have not been considered in existing force models. In this study, material removal mechanism under different lubricating conditions was researched. An improved theoretical force model that considers material removal and plastic stacking mechanisms was presented. Grain states, including cutting and ploughing, are determined by cutting efficiency (β). The influence of lubricating conditions was also considered in the proposed force model. Simulation was performed to obtain the cutting depth (a g) of each “dynamic active grain.” Parameter β was introduced to represent the plastic stacking rate and determine the force algorithms of each grain. The aggregate force was derived through the synthesis of each single-grain force. Finally, pilot experiments were conducted to test the theoretical model. Findings show that the model’s predictions were consistent with the experimental results, with average errors of 4.19% and 4.31% for the normal and tangential force components, respectively.

Part of the book: Advances in Microfluidic Technologies for Energy and Environmental Applications