An Experimental Study of Effective Thermal Conductivity of High Temperature Insulations

2008 ◽  
Vol 130 (3) ◽  
Author(s):  
Bo-ming Zhang ◽  
Wei-hua Xie ◽  
Shan-yi Du ◽  
Shu-yuan Zhao
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Maximum Temperature ◽  
Environmental Pressures ◽  
Average Temperature ◽  
Experimental Apparatus ◽  
History Of ◽  
Temperature And Pressure ◽  
Transfer Mechanisms ◽  
Thermal Conductivities

An experimental apparatus was designed and fabricated to measure the effective thermal conductivities and simulate the temperature and pressure history of reentry of a launch vehicle into a planetary atmosphere with a maximum temperature of 1600°C. An improved testing method was used to test the thermal conductivities of an alumina fibrous insulation at environmental pressures from 0.03Pato105Pa with the average temperature of the sample increased to 864°C and its density being 128kg∕m3. A method based on temperature difference is used to compute the in-plane effective thermal conductivity, and the result shows that the in-plane thermal conductivity along the y axis is 1.47 times that along the x axis. The influences of temperature and pressure on the contribution of three heat transfer mechanisms to the effective thermal conductivities were compared.

Temperature and Pressure Dependences of the Effective Thermal Conductivity of Granites

2020 ◽  
Vol 84 (9) ◽  
pp. 1144-1146
Author(s):  
S. N. Emirov ◽  
A. A. Aliverdiev ◽  
V. D. Beybalaev ◽  
A. A. Amirova ◽  
R. M. Aliev ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Temperature And Pressure

Experimental and Theoretical Modeling of the Effective Thermal Conductivity of Rough Steel Spheroid Packed Beds

2003 ◽  
Vol 125 (4) ◽  
pp. 693-702 ◽  
Author(s):  
G. Buonanno ◽  
A. Carotenuto ◽  
G. Giovinco ◽  
N. Massarotti
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Solid Mechanics ◽  
Packed Bed ◽  
Elementary Cell ◽  
Upper And Lower Bounds ◽  
Packed Beds ◽  
The Finite Element Method ◽  
Two Phase ◽  
Experimental Apparatus

The upper and lower bounds of the effective thermal conductivity of packed beds of rough spheres are evaluated using the theoretical approach of the elementary cell for two-phase systems. The solid mechanics and thermal problems are solved and the effects of roughness and packed bed structures are also examined. The numerical solution of the thermal conduction problem through the periodic regular arrangement of steel spheroids in air is determined using the Finite Element Method. The numerical results are compared with those obtained from an experimental apparatus designed and built for this purpose.

scholarly journals Investigation of Effective Thermal Conductivity for Ordered and Randomly Packed Bed with Thermal Resistance Network Method

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1666 ◽  
Author(s):  
Jian Yang ◽  
Yingxue Hu ◽  
Qiuwang Wang
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Thermal Resistance ◽  
Effective Thermal Conductivity ◽  
Packed Bed ◽  
Random Packing ◽  
Packing Factor ◽  
Resistance Network ◽  
Network Method ◽  
Thermal Conductivities

In the present paper, the effective thermal conductivities of Li4SiO4-packed beds with both ordered and random packing structures were investigated using thermal resistance network methods based on both an Ohm’s law model and a Kirchhoff’s law model. The calculation results were also validated and compared with the numerical and experimental results. Firstly, it is proved that the thermal resistance network method based on the Kirchhoff’s law model proposed in the present study is reliable and accurate for prediction of effective thermal conductivities in a Li4SiO4-packed bed, while the results calculated with the Ohm’s law model underestimate both ordered and random packings. Therefore, when establishing a thermal resistance network, the thermal resistances should be connected along the main heat transfer direction and other heat transfer directions as well in the packing unit. Otherwise, both the total heat flux and effective thermal conductivity in the packing unit will be underestimated. Secondly, it is found that the effect of the packing factor is remarkable. The effective thermal conductivity of a packed bed would increase as the packing factor increases. Compared with random packing at similar packing factor, the effective thermal conductivity of packed bed would be further improved with an ordered packing method.

Numerical determination of pressure-dependent effective thermal conductivity in Berea sandstone

2021 ◽  
Author(s):  
Mirko Siegert ◽  
Marcel Gurris ◽  
Erik Hans Saenger
Keyword(s):  
Experimental Data ◽  
Thermal Conductivity ◽  
Numerical Model ◽  
Effective Thermal Conductivity ◽  
Rock Sample ◽  
Rock Physics ◽  
Contact Phase ◽  
Data Set ◽  
Computed Tomography Images ◽  
Thermal Conductivities

<p>Within the scope of the present work, the pressure-dependent effective thermal conductivity of rock samples is simulated. Our workflow can be assigned to the field of digital rock physics. In a first step, a 3D micro-CT scan of a rock sample is taken. Subsequently, the resulting greyscale images are analysed and segmented depending on the occurring phases. Based on this data set, a computational mesh is created and the corresponding thermal conductivities are assigned to each phase. Finally the numerical simulations can be carried out.<br>For the representation of the pressure dependency we use the approach proposed by Saenger [1]. By making use of the watershed algorithm, boundaries between the individual grains of the rock sample are detected and assigned to an artificial contact phase. In the course of several simulations, the thermal conductivity of the contact phase is continuously increased. Starting with the thermal conductivity of the pore phase and ending with the thermal conductivity of the grain phase. A linear correlation is used to match the thermal conductivity of the contact phase with the pressure of a given experimental data set. This enables a direct comparison between simulation and measurement.<br>In a further step, the numerical model is calibrated to optimise the agreement between experimental data and simulation results. In particular, starting from two calibration points of the experimental data set, an adjustment of the thermal conductivities in the numerical model is carried out. While the thermal conductivity of the pore phase is held constant during the whole calibration process, thermal conductivities of the grain and contact phase are adjusted.</p><p>References<br>[1] Saenger et al. 2016. Analysis of high-resolution X-ray computed tomography images of Bentheim sandstone under elevated confining pressures. Geophysical Prospecting, 64(4), 848–859.</p><p> </p>

The study on effective thermal conductivity of carbon foam based on fractal theory

e-Polymers ◽  
2007 ◽  
Vol 7 (1) ◽  
Author(s):  
Wang Yong ◽  
An Qingqing ◽  
Cao Lingling ◽  
Si Xiaojuan ◽  
Liu Donghui ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Theoretical Basis ◽  
Fractal Theory ◽  
Carbon Foam ◽  
Conducting Property ◽  
Thermal Conductivity Model ◽  
Thermal Conducting ◽  
Temperature And Pressure ◽  
The Relationship

AbstractNovel carbon foam with high thermal conductivity is prepared by thermal treating of mesophase pitch under certain temperature and pressure condition. With fractal theory, the thermal conducting property of this novel porous material is discussed. Then we deduce the area fractal dimension of carbon foam. A thermal conductivity model of carbon foam is proposed. The relationship formula of effective thermal conductivity is presented by using thermal resistance method. Through computation, the effective thermal conductivity of carbon foam is acquired. The value of model forecast is consistent with that of the actual observed for carbon foam. This method has provided the theoretical basis for better using its fine heat conduction performance.

Measurements of the Intrinsic Thermal Conductivity of Individual Multi-Wall Carbon Nanotubes

2011 ◽  
Author(s):  
Juekuan Yang ◽  
Scott W. Waltermire ◽  
Yang Yang ◽  
Deyu Li ◽  
Yunfei Chen
Keyword(s):  
Thermal Conductivity ◽  
Carbon Nanotubes ◽  
Heat Source ◽  
Thermal Resistance ◽  
Effective Thermal Conductivity ◽  
Experimental Studies ◽  
Contact Thermal Resistance ◽  
Multi Wall Carbon Nanotubes ◽  
The Past ◽  
Thermal Conductivities

Thermal transport through carbon nanotubes (CNTs) attracted a lot of attention over the past decade. Several experimental studies have been carried out to determine the thermal conductivities of CNTs [1–3]. However, the measurements are based on an individual CNT sample between two suspended membranes and the results actually include both the intrinsic thermal resistance of the CNT and the contact thermal resistance between the CNT and the two suspended membranes that serve as a heat source and a heat sink. Hence, the effective thermal conductivity extracted from these measurements should be lower than the intrinsic thermal conductivities of the CNTs measured. To minimize the contact thermal resistance, electron beam induce deposition (EBID) of different metals has been used to increase the contact area between the CNT and the heat source and sink [3,4]. However, it is still not clear how effective this treatment is and to what level the effective thermal conductivity obtained after the EBID treatment reflects the intrinsic one.

Curvature Effect on the Thermal Conductivity of Nanowires

2008 ◽  
Author(s):  
Liang-Chun Liu ◽  
Mei-Jiau Huang ◽  
Ronggui Yang
Keyword(s):  
Thermal Conductivity ◽  
Monte Carlo ◽  
Effective Thermal Conductivity ◽  
Silicon Nanowires ◽  
Phonon Transport ◽  
Curvature Effect ◽  
Transport Efficiency ◽  
Directional Preference ◽  
Monte Carlo Simulator ◽  
Thermal Conductivities

Directional preference of the ballistic phonon transport plays an important role in the effective thermal conductivity of nanostructures. Curved nanowires can have very different thermal conductivities from straight ones. In this work, a Monte-Carlo simulator is developed and used to investigate the curvature effect on the phonon transport in silicon nanowires. The results show that the curvature of geometry does not alter the phonon transport efficiency in large wires but decreases the effective thermal conductivity in their nano-sized counterparts.

An Experimental Evaluation of the Effective Thermal Conductivities of Packed Beds at High Temperatures

1994 ◽  
Vol 116 (4) ◽  
pp. 829-837 ◽  
Author(s):  
K. Nasr ◽  
R. Viskanta ◽  
S. Ramadhyani
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
High Temperatures ◽  
Radiation Heat Transfer ◽  
Particle Diameter ◽  
Spherical Particles ◽  
Packed Beds ◽  
Packing Materials ◽  
Bed Temperature ◽  
Thermal Conductivities

Combined conduction and radiation heat transfer in packed beds of spherical particles was investigated. Three different packing materials (alumina, aluminum, and glass) of various particle diameters (2.5 to 13.5 mm) were tested. Internal bed temperature profiles and corresponding effective thermal conductivities were measured under steady-state conditions for a temperature range between 350 K and 1300 K. The effects of particle diameter and local bed temperature were examined. It was found that higher effective thermal conductivities were obtained with larger particles and higher thermal conductivity packing materials. The measured values for the effective thermal conductivity were compared against the predictions of two commonly used models, the Kunii–Smith and the Zehner–Bauer–Schlu¨nder models. Both models performed well at high temperatures but were found to overpredict the effective thermal conductivity at low temperatures. An attempt was made to quantify the relative contributions of conduction and radiation. Applying the diffusion approximation, the radiative conductivity was formulated, normalized, and compared with the findings of other investigators.

Thermal Conductivities of Porous Rocks Filled with Stagnant Fluid

1961 ◽  
Vol 1 (01) ◽  
pp. 37-42 ◽  
Author(s):  
D. Kunii ◽  
J.M. Smith
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Water Solution ◽  
Pure Water ◽  
General System ◽  
Practical Significance ◽  
Glycerol Water ◽  
Starting Point ◽  
Thermal Conductivities ◽  
Stagnant Fluid

Abstract Effective thermal conductivities of sandstones filled with stagnant fluids were measured using a steady-state technique. Data were obtained for seven sandstone samples, taken from four different locations and ranging in permeability from 18 to 590 md. The measurements with gases (helium, nitrogen, air and carbon dioxide) covered a pressure range from 0.039 psia to 400 psig. Data were taken for four liquids - n-heptane, methyl alcohol, 79.8 weight per cent glycerol-water solution and pure water at atmospheric pressure. The experimental results were used to evaluate the theoretical equations for predicting stagnant conductivities developed earlier. The low-pressure measurements permitted evaluation of the consolidation parameter hpDp/ks (necessary to utilize the theory) for the various types of sandstones. Using these characteristic values, the theoretical equations correlated well with the experimental conductivity data for the several fluids and rock samples. Introduction An aspect of heat transfer in solid-fluid systems of considerable current interest is the effective thermal conductivity of porous media. The stimulus for study of the subject arises from the need for sound procedures for designing thermal methods of petroleum production. The general system occurs when there exists a flow of fluid through the pores of the solid material. However, a logical starting point in developing a theory for predicting the effective thermal conductivity in the general system is to attack the special case when the porous solid is filled with stagnant fluid. Since the flow rates anticipated in thermal production processes are very low, such stagnant conductivities k are also of practical significance.

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