Comparison of thermal conductivity data for partially stabilized zirconia with values derived from thermal diffusivity results

1988 ◽  
Vol 9 (4) ◽  
pp. 587-598 ◽  
Author(s):  
R. K. Williams ◽  
J. B. Bates ◽  
R. S. Graves ◽  
D. L. McElroy ◽  
F. J. Weaver
Keyword(s):  
Thermal Conductivity ◽  
Thermal Diffusivity ◽  
Conductivity Data ◽  
Stabilized Zirconia ◽  
Partially Stabilized Zirconia ◽  
Thermal Conductivity Data

Thermal diffusivity, heat capacity and thermal conductivity of porous partially stabilized zirconia

1986 ◽  
Vol 5 (8) ◽  
pp. 799-802 ◽  
Author(s):  
M. V. Swain ◽  
L. F. Johnson ◽  
R. Syed ◽  
D. P. H. Hasselman
Keyword(s):  
Thermal Conductivity ◽  
Heat Capacity ◽  
Thermal Diffusivity ◽  
Stabilized Zirconia ◽  
Partially Stabilized Zirconia

Estimating thermal diffusivity and specific heat from needle probe thermal conductivity data

2006 ◽  
Vol 77 (4) ◽  
pp. 044904 ◽  
Author(s):  
William F. Waite ◽  
Lauren Y. Gilbert ◽  
William J. Winters ◽  
David H. Mason
Keyword(s):  
Thermal Conductivity ◽  
Thermal Diffusivity ◽  
Specific Heat ◽  
Conductivity Data ◽  
Thermal Conductivity Data ◽  
Needle Probe

Thermal conductivity data for refrigerant mixtures containing R1234yf and R1234ze(E)

2019 ◽  
Vol 133 ◽  
pp. 135-142 ◽  
Author(s):  
Sofia K. Mylona ◽  
Thomas J. Hughes ◽  
Amina A. Saeed ◽  
Darren Rowland ◽  
Juwoon Park ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Conductivity Data ◽  
Thermal Conductivity Data ◽  
Refrigerant Mixtures

A Review of Thermal Conductivity Data, Mechanisms and Models for Nanofluids

2010 ◽  
Vol 1 (4) ◽  
pp. 269-322 ◽  
Author(s):  
Ji-Hwan Lee ◽  
Seung-Hyun Lee ◽  
Chul Choi ◽  
Seok Jang ◽  
Stephen Choi
Keyword(s):  
Thermal Conductivity ◽  
Conductivity Data ◽  
Thermal Conductivity Data

Specific models for estimation of locally oriented laboratory thermal conductivity of tertiary sediments in the Niger Delta using wire line logs

2012 ◽  
Vol 4 (3) ◽  
Author(s):  
Akpabio Thompson ◽  
George Jimmy ◽  
Udofia Michael
Keyword(s):  
Thermal Conductivity ◽  
Niger Delta ◽  
Empirical Models ◽  
High Fidelity ◽  
Conductivity Data ◽  
Formation Factor ◽  
Model Based ◽  
Thermal Conductivity Data ◽  
Bed Thickness ◽  
Cementation Factor

AbstractIn this study, specific development of empirical models for estimation of laboratory thermal conductivities from wire line log thermal conductivity within the ambience of locally oriented wells located in the Niger Delta have been established. The laboratory thermal conductivity is characterised with high fidelity compared to wire line log thermal conductivity whose values vary as the dependence of lithology of the subsurface geomaterials, well effects, as well as the effects of the limited bed thickness of the adjacent lithological units of the Niger Delta where the study was stationed. The generalised equation kleff = 0.709 kweff + 0.188 is an empirically estimated model based on site variables (porosity, permeability and temperature) and constants (cementation factor, formation factor and tortuosity) of the locally oriented wells in the Niger Delta. It can be used to set bounds on the unstable wire line log thermal conductivity values within the 1-2.5 km depths where the oil-rich geomaterials in the Niger Delta are usually found. Equations have been established which show inter-convertibility between laboratory and wire line log thermal conductivity. These equations are considered useful in converting the available wire line log thermal conductivity data of nearby wells in the area to the usually desired and stable laboratory thermal conductivity. Various diagrams in 2-D and 3-D have been established to show the distribution of the parameters considered, and this could help the operating companies in the zone to predict the density of oil.

scholarly journals The Classical Nature of Thermal Conduction in Nanofluids

2010 ◽  
Vol 132 (10) ◽  
Author(s):  
Jacob Eapen ◽  
Roberto Rusconi ◽  
Roberto Piazza ◽  
Sidney Yip
Keyword(s):  
Experimental Data ◽  
Thermal Conductivity ◽  
Strong Evidence ◽  
Thermal Conduction ◽  
Base Fluid ◽  
Liquid Mixtures ◽  
Large Set ◽  
Conductivity Data ◽  
Homogeneous Systems ◽  
Thermal Conductivity Data

We show that a large set of nanofluid thermal conductivity data falls within the upper and lower Maxwell bounds for homogeneous systems. This indicates that the thermal conductivity of nanofluids is largely dependent on whether the nanoparticles stay dispersed in the base fluid, form large aggregates, or assume a percolating fractal configuration. The experimental data, which are strikingly analogous to those in most solid composites and liquid mixtures, provide strong evidence for the classical nature of thermal conduction in nanofluids.

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