In Situ Characterization of Coal Ash Thermal Conductivity Under Oxidizing and Reducing Conditions

2011 ◽  
Author(s):  
D. Cundick ◽  
D. Maynes ◽  
T. Moore ◽  
D. R. Tree ◽  
M. R. Jones ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Flow Reactor ◽  
Coal Ash ◽  
In Situ Measurements ◽  
Powder River Basin ◽  
Reducing Conditions ◽  
Bituminous Coals ◽  
Thermal Conductivities

This work presents in situ measurements of the effective thermal conductivity in particulate coal ash deposits under both reducing and oxidizing environments. Laboratory experiments generated deposits on an instrumented deposition probe of loosely-bound particulate ash from three coals generated in a down-fired flow reactor with optical access. An approach is presented for making in situ measurements of the temperature difference across the ash deposits, the thickness of the deposits, and the total heat transfer rate through the ash deposits. Using this approach, the effective thermal conductivity was determined for coal ash deposits formed under oxidizing and reducing conditions. Three coals were tested under oxidizing conditions: two bituminous coals derived from the Illinois #6 basin and a subbituminous Powder River Basin coal. The subbituminous coal exhibited the lowest range of effective thermal conductivities (0.05–0.18 W/m· K) while the Illinois #6 coals showed higher effective thermal conductivities (0.2–0.5 W/m· K). One of the bituminous coals and the subbituminous coal were also tested under reducing conditions. A comparison of the ash deposits from these two coals showed no discernible difference in the effective thermal conductivity based on stoichiometry. All experiments indicated an increase in effective thermal conductivity with deposit thickness, probably associated with deposit sintering.

In Situ Characterization of Ash Thermal Conductivity for Three Coal Types Formed Under Oxidizing and Reducing Conditions in a Laboratory Furnace

2012 ◽  
Vol 4 (4) ◽  
Author(s):  
D. Cundick ◽  
D. Maynes ◽  
T. Moore ◽  
D. R. Tree ◽  
M. R. Jones ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Flow Reactor ◽  
Coal Ash ◽  
In Situ Measurements ◽  
Powder River Basin ◽  
Reducing Conditions ◽  
Bituminous Coals ◽  
Thermal Conductivities

This work presents in situ measurements of the effective thermal conductivity in particulate coal ash deposits under both reducing and oxidizing environments. Laboratory experiments generated deposits on an instrumented deposition probe of loosely bound particulate ash from three coals generated in a down-fired flow reactor with optical access. An approach is presented for making in situ measurements of the temperature difference across the ash deposits, the thickness of the deposits, and the total heat transfer rate through the ash deposits. Using this approach, the effective thermal conductivity was determined for coal ash deposits formed under oxidizing and reducing conditions. Three coals were tested under oxidizing conditions: two bituminous coals derived from the Illinois #6 basin and a subbituminous Powder River Basin coal. The subbituminous coal exhibited the lowest range of effective thermal conductivities (0.05–0.18 W/m K) while the Illinois #6 coals showed higher effective thermal conductivities (0.2–0.5 W/m K). One of the bituminous coals and the subbituminous coal were also tested under reducing conditions. A comparison of the ash deposits from these two coals showed no discernible difference in the effective thermal conductivity based on stoichiometry. All experiments indicated an increase in effective thermal conductivity with deposit thickness, probably associated with deposit sintering.

Significantly enhanced and precisely modeled thermal conductivity in polyimide nanocomposites with chemically modified graphene via in situ polymerization and electrospinning-hot press technology

2018 ◽  
Vol 6 (12) ◽  
pp. 3004-3015 ◽  
Author(s):  
Yongqiang Guo ◽  
Genjiu Xu ◽  
Xutong Yang ◽  
Kunpeng Ruan ◽  
Tengbo Ma ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
In Situ Polymerization ◽  
Hot Press ◽  
Conductivity Model ◽  
Chemically Modified ◽  
Thermal Conductivity Model ◽  
Modified Graphene ◽  
Thermal Conductivities

Significantly improved thermal conductivities and a more accurate thermal conductivity model were achieved.

Effective thermal conductivity in a packed-bed radial-flow reactor

AIChE Journal ◽  
1987 ◽  
Vol 33 (10) ◽  
pp. 1747-1750 ◽  
Author(s):  
A. L. López de Ramos ◽  
F. F. Pironti
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Radial Flow ◽  
Flow Reactor ◽  
Packed Bed ◽  
Radial Flow Reactor

scholarly journals Laboratory and In-Situ Measurements for Thermal and Acoustic Performance of Straw Bales

2019 ◽  
Vol 11 (20) ◽  
pp. 5592 ◽  
Author(s):  
Stefano Cascone ◽  
Gianpiero Evola ◽  
Antonio Gagliano ◽  
Gaetano Sciuto ◽  
Chiara Baroetto Parisi
Keyword(s):  
Thermal Conductivity ◽  
Phase Shift ◽  
In Situ Measurements ◽  
Sound Insulation ◽  
Initial Water Content ◽  
Acoustic Performance ◽  
Thermal Transmittance ◽  
Straw Bale Walls ◽  
Straw Bale

This paper investigates the performance of timber-framed walls insulated with straw bales, and compares them with similar walls containing expanded polystyrene (EPS) instead of straw bales. First, thermal conductivity, initial water content, and density of the straw bales were experimentally measured in a laboratory set-up, and the dependence of the thermal conductivity of the dry material on temperature was described. Then, the two insulation solutions were compared by looking at their steady and periodic thermal transmittance, decrement factor, phase shift, internal areal heat capacity and surface mass. Finally, the acoustic performance of both wall typologies was analyzed by means of in situ measurements in two-story buildings built in Southern Italy. The weighted apparent sound reduction index for the partition wall between two houses and the weighted standardized level difference for the façades were assessed based on ISO Standard 16283. The results indicate that the dry straw bales have an average thermal conductivity of k = 0.0573 W/(m·K), and their density is around 80 kg/m3. In addition, straw bale walls have good steady thermal performance, but they still lack sufficient thermal inertia, as witnessed by the low phase shift and the high periodic thermal transmittance. Finally, according to the on-site measurements, the results underline that the acoustic performance of the straw bale walls is far better than the walls adopting traditional EPS insulation. Overall, the straw bales investigated are a promising natural and sustainable solution for thermal and sound insulation of buildings.

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>

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