The porosity of the CFF samples was calculated using Equation (8), and the average values for the different Grades/PPI numbers are summarized in and the results for each of the individual CFF samples can be found in , , and . As can be seen from the table, the high-Grade/PPI number CFFs (65 and 80) from suppliers A and B showed slightly lower porosity than the low-Grade/PPI number CFFs (30). However, this trend was not observed for the CFFs from supplier C. The reason for this is believed to be directly linked to the uneven cylindrical shape of the samples secured from the 50 PPI and 60 PPI CFF blocks from supplier C which later also gave an increased uncertainty in measuring the sample dimensions. Nevertheless, the obtained result clearly indicated that the porosity of the different CFF samples was somewhat similar.
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The true particle density of the CFF samples and their average are summarized in . As can be seen from the table, the average true particle density for the CFFs from suppliers A and B were relatively similar and slightly higher than those of the CFFs from supplier C.
To better understand the differences between the CFF samples in view of their physical morphologies, the mean Feret diameter of the Cells and Windows of each Grade/PPI number was calculated and presented together with the pooled standard deviations and the number of counts (sample population) within each Grade/PPI number, see (the mean Feret diameter of the Cells and Windows of each of the individual CFF samples can be found in , , , , , , and ). As can be seen from the table, the deviations between the measured Feret diameter of the Windows proved to be less than in the case of the Cells. This is believed to be due to how they were measured, i.e., the circumferences of the Windows were identified through thresholding with a higher degree of precision than in the case of the Cells. It can also be seen from the that CFF samples of corresponding Grade/PPI number clearly have different values for the Feret diameter of the Cells and Windows. In some cases, the values are significantly different, e.g., the average CFF Window diameter of Grade 30 from supplier A was 27% less than that of the 30 PPI from supplier C. It should be noted that in the grading system, the Cell Feret diameter defines the range of each CFF Grade. However, as the Windows Feret diameter can be measured with more precision, it is believed that it can substitute the Cell size in the grading system.
An identical statistical analysis was performed to identify the corresponding CFF from suppliers B and supplier C to CFF from supplier A. A summary of the results is shown in correlating the identical CFF using colored boxes. The results in are valid for statistical analysis of both permeability and the Feret diameter of the Window and confirm/highlight the lack of a systematic way of sorting CFFs as there are two different classification systems. No correlation can even be identified between the CFFs classified using the same system, as in the case of suppliers B and supplier C.
The permeability or morphological characteristics of the samples investigated in the present study, i.e., of the CFFs within each Grade/PPI, were defined using the statistical two-sample t-test with a 95% confidence interval. Before executing the t-test, the equality of the variances between the two datasets was tested to identify what assumption, i.e., equal, or unequal variances, should be practiced for the unpaired t-test. The test was accomplished by performing a two-sample F-test with a 95% confidence interval and by assuming equal variances for each pair of the dataset, i.e., the Null hypothesis. In , the results from the statistical analysis in view of identifying the variations in the mean sample permeability of CFFs Grade 30 from supplier A and 30 PPI from supplier B are presented. As can be seen from the table, the Null hypothesis could not be rejected, concluding that the variation of the mean permeability of CFFs Grade 30 from supplier A and CFFs 30 PPI from supplier B was not statistically significant.
As can be seen from , the permeability of CFF 30 PPI and CFF 50 PPI from supplier C is significantly higher than the corresponding CFFs from suppliers A and B, i.e., Grade 30 and Grade 50 from supplier A, as well as 30 PPI and 50 PPI from supplier B, which, as previously mentioned, is believed to be linked to the disparity of their structural morphologies, see . This observation indicates that the permeability of the CFFs of a specific class can be relatively different in view of their structural morphologies and fluid flow properties when originating from different suppliers.
The CFF sample permeability was measured based on pressure drop experiments performed at the velocity range ≤ 10 mm·s −1 . In the calculated mean permeability of all the investigated CFFs is presented. The permeability of each of the individual CFF samples within each Grade/PPI number can be found in , , and .
The velocity at which the laminar flow is transferred to transient flow and eventually turbulent flow can be identified using graphs correlating the dimensionless Fanning friction factor to Rei number, where the mean Window Feret diameter of CFF samples is used as the characteristic length scale for the estimation of Rei number. In the relation of the Fanning friction factor as a function of Rei number for CFF grade 30–80 from supplier A is presented. As can be seen from the Figure, the graph becomes almost horizontal at the onset of the turbulent flow regime, where the Fanning factor approaches zero.
The obtained laminar, transition, and turbulent flow regimes can be recognized by analogy with the three flow regions presented in . The linear section of the diagram showing the laminar flow regime and the onset of the transitional flow regime can be defined by drawing a tangent line from the linear section of the graph to the interception with the “x” axis. In the laminar flow region, the friction factor of CFFs Grade 80 is one order of magnitude higher than the CFFs Grade 30, indicating that the wall shear stresses are higher for the CFFs with smaller pore sizes. As previously mentioned, the transitional flow region is reached a point where the drag forces are dominant, and the inertial forces are comparable to viscous forces. After that, the graph starts to decay until the velocity graph flattens horizontally.
The flow regimes in the CFFs from suppliers B and supplier C were also evaluated, and the results indicated that a laminar flow was achieved through CFFs of Grades/PPI numbers 30–80 at Rei ≤ 1, which corresponds to a superficial fluid velocity of ≤2 mm·s−1. This velocity is lower than the normally applied Al filtration velocities in the DC casting process, i.e., the velocity is in the superficial velocity range at which the flow in the channels is transient or turbulent. The presently obtained results are contrary to the assumption made by Bao et al. [8], where the laminar (creeping) flow was considered in a model of particle removal in CFFs during Al filtration. In view of this, a higher filtration efficiency was obtained in the derived model compared to the experimental work as the influence of the inertia as lifting forces on the collected particles partly resulted in particle re-entrainment.
In the present study, the obtained pressure drop variations in the investigated CFFs can be analyzed through the model equations derived from graphs of Fanning friction factor (f) versus Rei number and their correlation to the Forchheimer equation (Equation (5)). In correlation to a characteristic length scale of CFFs, the model is identical to the Ergun equation (Equation (6)) that can derive the constants a and b in Equation (4) for CFFs of a specific Grade/PPI number. However, deriving global constants is, for straightforwardness, of more interest. Accordingly, the calculated Fanning friction factor (f) of all the investigated CFFs in the present study was plotted against the corresponding Rei number, and a model equation was derived using regression analysis, see .
As can be seen from the figure, a nonlinear trend line at 95% confidence interval was fitted through the data points using regression analysis, and a polynomial inverse first-order equation was derived. The resulting function was later modified by substituting Equation (3) for the Fanning friction factor (f), and correlating the pressure drop of the CFFs to their characteristic length scale, i.e., to the Window Feret diameter (dw), see Equation (13):
ΔPL=18.612μudw2+0.388ρu2dw
(13)
Equation (13), together with a previously published equation by Kennedy et al. [19] (Equation (9)), were then plotted against the experimental pressure drop values obtained for CFF samples from suppliers A, B, and C to find the model that could describes better the experimental work, see . The Cell Feret diameter and Window Feret diameter of the samples were used, respectively, for dc and dw in Equations (9) and (13), see , , , and for the measured data of dc, dw, and porosity of all the samples.
In Equation (9), the Cell Feret diameter (dc) was substituted for the equivalent particle size (dp) in the Ergun equation (Equation (6)) using Equation (14) which allowed to obtain an equivalent particle size (dp) for CFFs based on their porosity (Ø) and mean Cell Feret diameter (dc) [19]:
dp=1.5(1−∅)∅dc
(14)
In , the presently measured experimental and calculated pressure drops values are shown by respective symbols and regression lines. As can be seen from the figure, there is an increased agreement between the obtained results based on the presently derived equation, i.e., Equation (13), and the experimental values when compared with the calculated pressure drop values based on the equation proposed by Kennedy et al. [10], i.e., Equation (9). It should, however, be noted that Kennedy et al. [10] used a similar experimental setup as in the present study but used a maximum velocity of 800 mm·s−1. In contrast, in the present case, the velocity used was set to simulate industrial casting conditions, i.e., ≤ 10 mm·s−1.
In the filtration of Al using CFFs, the filters are placed inside a filter box and preheated to a temperature of about 993 K (720 °C) to prevent solidification of the molten Al metal when it initially meets the filter at the start of the filtration step [29]. As a result, a metallostatic head is formed on the surface of the CFF, and the pressure from the metal head breaks the oxides layer that has formed on the interface between the CFF surface and the molten Al, thereby primes the filter, i.e., infiltrates the CFFs with molten Al [16]. From that point, the filtration process is initiated, and the molten Al flows through the CFF [16]. Equations (9) and (13) can both be used to evaluate the required metallostatic head needed to prime the CFF, and a metal head of 21.3 cm and 8.9 cm were presently obtained. In view of this result, it is clear that pressure drop experiments must be performed at velocities close to industrial casting conditions for Al to be able to accurately study and evaluate the hydraulic properties of CFF during the Al filtration.
Alumina Foam Ceramic filter for Alumina or Aluminium alloy casting
Alumina Ceramic Foam Filters mainly for filtration of aluminium and aluminium alloys in foundries and cast houses. With their excellent resistance to attack and corrosion from molten aluminum, they can effectively remove inclusions, reduce trapped gas and provide laminar flow, and then the filtered metal is significantly cleaner. Cleaner metal results in higher-quality castings, less scrap, and fewer inclusion defects, all of which contribute to bottom-line profit.
Alumina Ceramic Foam Filters(CFF-AL) Common Size:
CFF-AL is available in all common sizes: 7", 9", 12", 15", 17", 20", and 23". We offers the whole range of porosities from PPI 10 up to PPI 60 (PPI = pores per inch). Custom-made cut-to-size filters are also possible.
Alumina Ceramic Foam Filters (CFF-AL) Gasketing:
For more Ceramic Foam Filter for Aluminum Castinginformation, please contact us. We will provide professional answers.
CFF-AL is equipped with a gasket on the edges. The gasket assures the proper and tight position of the filter within the filter box. There are different types of gasket available, eg. Ceramic fibre gasket etc. Also you can choose CFF-AL without gasket.
Physical Properties for Alumina Ceramic Foam Filters (CFF-AL):
Working
≤1200°C
Porosity
80~90%
Compression Strength (Room Temperature)
≥1.0Mpa
Volume Density
≤0.5g/cm3
Thermal Shock Resistance
800°C---room temperature 5 times
Application
non-ferrous and alumina alloys,
high temperature gasfilter,
chemical fillings and catalysis carrier etc.
Chemical Composition for Alumina Ceramic Foam Filters (CFF-AL):
Al2O3
SiC
SiO2
ZrO2
Others
80~82%
---
5~6%
---
12~15%
For more information, please visit Alloy Supplier.