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Modeling of the Hydroentanglement Process

Profile image of Abdelfattah SeyamAbdelfattah Seyam

Journal of Engineered Fibers and Fabrics

https://doi.org/10.1177/155892500600100201
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15 pages

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Abstract

Mechanical performance of hydroentangled nonwovens is determined by the degree of the fiber entanglement, which depends on parameters of the fibers, fiberweb, forming surface, water jet and the process speed. This paper develops a computational fluid dynamics model of the hydroentanglement process. Extensive comparison with experimental data showed that the degree of fiber entanglement is linearly related to flow vorticity in the fiberweb, which is induced by impinging water jets. The fiberweb is modeled as a porous material of uniform porosity and the actual geometry of forming wires is accounted for in the model. Simulation results are compared with experimental data for a Perfojet ® sleeve and four woven forming surfaces. Additionally, the model is used to predict the effect of fiberweb thickness on the degree of fiber entanglement for different forming surfaces.

FAQs

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What explains the relationship between vorticity and fiber entanglement efficiency?add

The study finds that fiber entanglement is linearly correlated with average vorticity, achieving R coefficients of 0.99407 and 0.97641 in machine and cross-machine directions, respectively.

How does water jet pressure affect fiber entanglement in the model?add

The model predicts that average vorticity, hence fiber entanglement, increases with water jet pressure, confirming a strong correlation across different forming surfaces.

What parameters were found to limit fiber entanglement effectiveness?add

The research indicates that fiberweb thickness has a critical threshold, approximately 1.5 mm, beyond which additional thickness results in diminished entanglement due to energy dissipation.

Why are fine mesh woven surfaces more effective in fiber entanglement?add

The findings show that finer mesh forming surfaces yield higher average vorticities, leading to improved fiber entanglement efficiency compared to coarser mesh surfaces.

How was the hydroentanglement model validated against experimental data?add

Model simulations were compared to experimental data using Perfojet® and various woven forming surfaces, achieving linear correlations for tensile strength and vorticity metrics.

Figures (17)
Figure la: Schematic diagram of the problem and the computational domain In the hydroentanglement process, the impinging jets induce vortices within the fluid region, the fiberweb, and the interstices between the forming wires. The water vortices in the fiberweb cause the interaction between the impinging water and fibers in the fiberweb, involve fibers in vortices, align them along the water flow streamlines, and swirl them with the vortices. The rotational effect of fluid flow on a solid particle or a fiber is determined by flow vorticity. Shahcheraghi and Dwyer [7], for example, evaluated the rotation rate of a sphere in a flow field by one-half of the local flow vorticity at the sphere-center position. It is the rotational force on a fiber imposed by the water flow that causes the fiber to swirl and entangle with nearby fibers. It is therefore assumed that the degree of fiber entanglement is proportional to the average vorticity in the fiberweb region.
Figure la: Schematic diagram of the problem and the computational domain In the hydroentanglement process, the impinging jets induce vortices within the fluid region, the fiberweb, and the interstices between the forming wires. The water vortices in the fiberweb cause the interaction between the impinging water and fibers in the fiberweb, involve fibers in vortices, align them along the water flow streamlines, and swirl them with the vortices. The rotational effect of fluid flow on a solid particle or a fiber is determined by flow vorticity. Shahcheraghi and Dwyer [7], for example, evaluated the rotation rate of a sphere in a flow field by one-half of the local flow vorticity at the sphere-center position. It is the rotational force on a fiber imposed by the water flow that causes the fiber to swirl and entangle with nearby fibers. It is therefore assumed that the degree of fiber entanglement is proportional to the average vorticity in the fiberweb region.
Figure 1b: Projection of forming wires on the MD-CD plane
Figure 1b: Projection of forming wires on the MD-CD plane
Figure 2: Computational domain for 3D simulations Since the impinging jet velocity is very high, the flow in the fluid layer, porous fiberweb layer, and in the interstices between the forming wires (see Figure Ja) is turbulent. A turbulent flow model is used to simulate 3D flow in all three layers. The geometry of the computational domain for 3D simulations is shown in Figure 2, in which only two water jets are included. This is because all water jets in one manifold are identical and a manifold can be separated into many unit cells shown in Figure 2, in which the water flow field is similar and fiber entanglement simply accumulates when moving from one unit cell to the next.
Figure 2: Computational domain for 3D simulations Since the impinging jet velocity is very high, the flow in the fluid layer, porous fiberweb layer, and in the interstices between the forming wires (see Figure Ja) is turbulent. A turbulent flow model is used to simulate 3D flow in all three layers. The geometry of the computational domain for 3D simulations is shown in Figure 2, in which only two water jets are included. This is because all water jets in one manifold are identical and a manifold can be separated into many unit cells shown in Figure 2, in which the water flow field is similar and fiber entanglement simply accumulates when moving from one unit cell to the next.
To compare with experimental results, simulations are performed to model experimental conditions as closely as possible. Since the Perfojet® sleeve is micro-perforated with a small open area (8%), in simulations it could be shown that 95% of the impinging water is reflected back by the sleeve. This is because it is assumed that the micro-perforated holes in the sleeve have cylindrical geometry with discharge coefficient of Cz = 0.62. It is also assumed that the water velocity does not change from the inlet to the exit of the holes in the sleeve. Table 1: Parameters of the fiberweb processed using the Perfojet ® sleeve
To compare with experimental results, simulations are performed to model experimental conditions as closely as possible. Since the Perfojet® sleeve is micro-perforated with a small open area (8%), in simulations it could be shown that 95% of the impinging water is reflected back by the sleeve. This is because it is assumed that the micro-perforated holes in the sleeve have cylindrical geometry with discharge coefficient of Cz = 0.62. It is also assumed that the water velocity does not change from the inlet to the exit of the holes in the sleeve. Table 1: Parameters of the fiberweb processed using the Perfojet ® sleeve
Woven forming wires: The straight lines in Figure 3 are the linear fit lines between the simulated and experimental results. The correlation coefficient, R, of the linear fit line for the results in the MD is 0.99407, while that for the results in the CD is 0.97641, which means that the correlation coefficients in both the machine and cross-machine directions are very close to unity. This indicated that there is a linear correlation between the fabric tensile strength and the average vorticity in the fiberweb. Since the fabric tensile strength is proportional to the degree of fiber entanglement, it is evident that the degree of fiber entanglement is linearly correlated to the average vorticity in the fiberweb, which validates the major assumption of this research.
Woven forming wires: The straight lines in Figure 3 are the linear fit lines between the simulated and experimental results. The correlation coefficient, R, of the linear fit line for the results in the MD is 0.99407, while that for the results in the CD is 0.97641, which means that the correlation coefficients in both the machine and cross-machine directions are very close to unity. This indicated that there is a linear correlation between the fabric tensile strength and the average vorticity in the fiberweb. Since the fabric tensile strength is proportional to the degree of fiber entanglement, it is evident that the degree of fiber entanglement is linearly correlated to the average vorticity in the fiberweb, which validates the major assumption of this research.
Simulations are performed exactly for the same conditions as experiments. The measured thicknesses of the four woven forming surfaces are given in Table 2. For the woven forming surface, since it has a structure of interconnected wires and empty spaces between the wires, some of the inlet water is reflected back by the wires and the rest of water is evacuated through he interstices between the wires. Based on industry observations [10], it is assumed that 16% of he water that impinges on the wires is reflected back by the forming wires. Thus, the reflected portion of the water brought into the fiberweb by the jets is calculated as Ri =0.16x(1-9), where @ is the open area of the forming wires, which depends on geometry of the forming wires see Table 2). In the present study, the migration of fibers into the interstices between the forming wires is neglected. Table 2: Geometrical parameters of woven forming wires
Simulations are performed exactly for the same conditions as experiments. The measured thicknesses of the four woven forming surfaces are given in Table 2. For the woven forming surface, since it has a structure of interconnected wires and empty spaces between the wires, some of the inlet water is reflected back by the wires and the rest of water is evacuated through he interstices between the wires. Based on industry observations [10], it is assumed that 16% of he water that impinges on the wires is reflected back by the forming wires. Thus, the reflected portion of the water brought into the fiberweb by the jets is calculated as Ri =0.16x(1-9), where @ is the open area of the forming wires, which depends on geometry of the forming wires see Table 2). In the present study, the migration of fibers into the interstices between the forming wires is neglected. Table 2: Geometrical parameters of woven forming wires
Figure 5: Comparison with experimental data for the “36 mesh” woven forming surface
Figure 5: Comparison with experimental data for the “36 mesh” woven forming surface
Comparing the correlation results in Figures 5-7 with those in Figure 4, it is evident that the correlation coefficients for the “36 mesh,” “14 mesh,” and “10 mesh” forming surfaces are smaller than that for the “100 mesh” surface. This indicates that this model is more accurate for a fine mesh woven forming surface than a coarse one.
Comparing the correlation results in Figures 5-7 with those in Figure 4, it is evident that the correlation coefficients for the “36 mesh,” “14 mesh,” and “10 mesh” forming surfaces are smaller than that for the “100 mesh” surface. This indicates that this model is more accurate for a fine mesh woven forming surface than a coarse one.
dissipates as water filters through the fiberweb. For the fiberweb of a large thickness, the kinetic energy completely dissipates in the upper portion of the fiberweb causing almost no entanglement in its lower portion. This means the process is only efficient for fiberwebs with a critical thickness (about 1.5 mm) in a single manifold. Figure 8: Effect of fiberweb thickness on the average vorticity in the fiberweb for the “100 mesh” woven forming surface Figure 9: Effect of fiberweb thickness on the average vorticity in the fiberweb for the “36 mesh” woven forming surface
dissipates as water filters through the fiberweb. For the fiberweb of a large thickness, the kinetic energy completely dissipates in the upper portion of the fiberweb causing almost no entanglement in its lower portion. This means the process is only efficient for fiberwebs with a critical thickness (about 1.5 mm) in a single manifold. Figure 8: Effect of fiberweb thickness on the average vorticity in the fiberweb for the “100 mesh” woven forming surface Figure 9: Effect of fiberweb thickness on the average vorticity in the fiberweb for the “36 mesh” woven forming surface
Figure 11: Effect of fiberweb thickness on the average vorticity in the fiberweb for the “10 mesh” woven forming surface
Figure 11: Effect of fiberweb thickness on the average vorticity in the fiberweb for the “10 mesh” woven forming surface

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References (11)

  1. Pourdeyhimi, B., Mintion A., Putnam, M. and Kim, H.S.; Structure-process-property relationships in hydroentangled nonwoven -Part 1: preliminary experimental observations, International Nonwoven Journal; vol. 13, no. 4, pp. 15-21, 2004
  2. Berkalp, O.B., Pourdeyhimi, B. and Seyam, A.; Texture evolution in hydroentangled nonwovens, International Nonwoven Journal; vol. 12, pp. 28-35, 2003
  3. Ghassemieh E., Acar M. and Versteeg H. K.; Microstructural analysis of non-woven fabrics using scanning electron microscopy and image processing. Part 2: application to hydroentangled fabrics, Proceedings of the Institution Mechanical Engineers, Part L, Journal of Materials: Design and Applications; vol. 216, No. 4, pp. 211-218, 2002
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  5. Seyam, A. M., Shiffler D. A. and Zheng H.; An examination of the hydroentangling process variables, International Nonwoven Journal; vol. 14, no. 1, pp. 25-33, 2005
  6. Xiang P., Kuznetsov A.V. and Seyam, A.; Simulation of fiber entanglement by modeling vorticity in water flow field, Textile Research Journal; 2006, In Press
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  10. Holmes, R.; Private communication, 2006 AUTHORS ADDRESSES Abdelfattah Mohamed Seyam, Ph.D., Ping Xiang, M.S North Carolina State University College of Textiles 2401 Research Drive Raleigh, North Carolina 27695-8301 USA
  11. Andrey V. Kuznetsov, Ph,D. North Carolina State University Department of Mechanical and Aerospace Engineering 2401 Research Drive Raleigh, North Carolina 27695-8301 USA

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