Abstract

Lubricating greases are special lubricants with a wide range of application. The tribologically stressed grease is used as tribological system and finally modeled as an open thermodynamic system. This study investigated the phenomenon of self-optimization and applied to the process of shearing a grease. The conditions for self-optimization and the consequences of created dissipative structures are investigated according to the interpreted literature.

Highlights

  • Friction and wear are irreversible processes and characterized by energy dissipation with a continuous production of entropy

  • Similar to the solid rubbing bodies of a tribo-system, a lubricating grease undergoes irreversible changes caused by friction

  • Abdel-Aal [1] creates an open thermodynamic system to observe the energetic situation of a solid-solid contact during a tribo-process

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Summary

Introduction

Friction and wear are irreversible processes and characterized by energy dissipation with a continuous production of entropy. Abdel-Aal [1] creates an open thermodynamic system to observe the energetic situation of a solid-solid contact during a tribo-process He described an entropy balance and correlated the wear (as loss of material) with the entropy production. Paszkowski and Olsztynska-Janus [4] investigated the degradation process of Li-soap lubricating greases They reported that the change of structural viscosity during a shear process is caused by destruction of hydrogen bonds (OH-groups) between Li-soap-fibres. That means that the system follows the natural effort to come into a stable situation after working in instability with the help of self-optimized parameters (roughness height, roughness distribution, tribo-film thickness or spatial and temporary patterns) It is assumed, that these phenomena occur in the stressed lubricating grease and lead to an optimized dissipative grease structure. One aim of the current paper is an analytical investigation of this assumption

Process Stability
Conclusion
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Period of self optimization ation
Period of Self-Optimization
Conclusions
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