Effect of surface temperature rise on friction characteristics for sliding speed under unlubricated condition

Author(s):  
T Nakahara ◽  
S Momozono ◽  
A O-Rui
Author(s):  
E. M. Evans ◽  
J. Whittle

This paper is intended to demonstrate that designers of wet clutches for power transmission can obtain the optimum friction characteristics for specific applications by considering the interaction between friction materials and lubricants. A friction clutch plate rig is described and the friction results obtained are presented. It is shown that a wide variation of coefficients of friction and frictional characteristics in wet friction clutches can be obtained by changing the oils and friction materials. In particular the coefficient of friction is dependent upon (1) the oil, (2) the materials of the sliding surfaces, (3) sliding speed, and (4) temperature. It is also shown that the coefficient of friction is affected by ( a) refining treatment given to the oil, ( b) different base oils, and ( c) additives.


2021 ◽  
Vol 926 (1) ◽  
pp. 012005
Author(s):  
G S H Arimufti ◽  
W Sunanda ◽  
R F Gusa

Abstract The floating photovoltaic panel is increasingly being used. This is one of the ways to reduce temperature rise in photovoltaic panel. The floating photovoltaic panel is used for lighting at the fish pond. A unit of 8-watt lamp for lighting supplied by 1 unit of 50 Wp photovoltaic panel and 1 unit of 12 V/3.5 Ah battery. The heatsink attached to the bottom of the floating photovoltaic panel transfers heat from the panel to the fish pond water. Sensors are connected to Arduino to measure photovoltaic panel output voltage and current, solar irradiance, photovoltaic panel temperature and fish pond water temperature. From the measurement, the voltage generated from the floating photovoltaic panel is 12.71 – 14.71 V and the current is 0.15 - 1.17 A. While the solar irradiance value is 71 W/m2 to 396 W/m2, the surface temperature of photovoltaic panel is 26.9°C - 32.4°C and fish pond water temperature is 27.1°C - 30.2°C.


2018 ◽  
Vol 883 ◽  
pp. 53-62 ◽  
Author(s):  
Shin Yuh Chern ◽  
Jeng Haur Horng ◽  
Cheng Han Tsai ◽  
Hung Jung Tsai

The surface micro-temperature of sliding, rough bodies is an important factor affecting contact properties, such as chemical reactions of automatic injectors for medicine and chemical processes and surface failure of micro-and macro-devices. In this work, the Finite Element Method is used to analyze the micro-temperature of the peaks and valleys of multiplying asperity sliding contact surfaces. The affecting parameters include pressure, roughness, sliding speed, Peclet number, and thermal conductivity of rough surfaces. Analysis results showed that the effects of the studied parameters are different to those of peak and valley temperatures. While pressure increased, the increasing rate of the temperature rise parameter of valleys was larger than those of peaks. The temperature rise of peaks increased as roughness increased. On the contrary, the temperature rise of valleys decreased as roughness increased. Sliding speed and thermal conductivity played the most important roles in affecting the maximum micro-temperature rise. The temperature rise difference between peaks and valleys was almost proportional to thermal conductivity, and was inversely proportional to sliding speed for all cases. This transient thermal analysis enables precision control of interface micro-temperature for micro-moving devices.


2018 ◽  
Vol 4 (1/2) ◽  
pp. 19-36 ◽  
Author(s):  
Alex G. Libardoni ◽  
Chris E. Forest ◽  
Andrei P. Sokolov ◽  
Erwan Monier

Abstract. Historical time series of surface temperature and ocean heat content changes are commonly used metrics to diagnose climate change and estimate properties of the climate system. We show that recent trends, namely the slowing of surface temperature rise at the beginning of the 21st century and the acceleration of heat stored in the deep ocean, have a substantial impact on these estimates. Using the Massachusetts Institute of Technology Earth System Model (MESM), we vary three model parameters that influence the behavior of the climate system: effective climate sensitivity (ECS), the effective ocean diffusivity of heat anomalies by all mixing processes (Kv), and the net anthropogenic aerosol forcing scaling factor. Each model run is compared to observed changes in decadal mean surface temperature anomalies and the trend in global mean ocean heat content change to derive a joint probability distribution function for the model parameters. Marginal distributions for individual parameters are found by integrating over the other two parameters. To investigate how the inclusion of recent temperature changes affects our estimates, we systematically include additional data by choosing periods that end in 1990, 2000, and 2010. We find that estimates of ECS increase in response to rising global surface temperatures when data beyond 1990 are included, but due to the slowdown of surface temperature rise in the early 21st century, estimates when using data up to 2000 are greater than when data up to 2010 are used. We also show that estimates of Kv increase in response to the acceleration of heat stored in the ocean as data beyond 1990 are included. Further, we highlight how including spatial patterns of surface temperature change modifies the estimates. We show that including latitudinal structure in the climate change signal impacts properties with spatial dependence, namely the aerosol forcing pattern, more than properties defined for the global mean, climate sensitivity, and ocean diffusivity.


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