How Pall is delivering cutting-edge filtration solutions that drive global decarbonization efforts.
In the quest for decarbonization to achieve net-zero 2050 goals, the ability to produce filtration systems tailored to customers’ needs is key. Pall Corporation works with organizations in nearly every industry to create solutions that fit their requirements and optimize operations. The company continues to strengthen the filter design value chain, from material and element design, to housing configuration and filter testing. A crucial part of the process is the initial research and development phase. Filter Mesh Belt
Meeting the stringent requirements of filter efficiency, durability, and sustainability requires fundamental insights into how fluids interact with media materials, flow through filter elements, and distribute across entire filtration systems. Traditional analytical methods, which often focus on upstream/downstream sampling, fall short of capturing the real-world fluid dynamics within filters.
Advanced flow imaging techniques, including tools based on computed tomography (CT) and nuclear magnetic resonance (NMR), bridge this gap by providing real-time visualization of fluid behaviors within filters, through non-invasive experimental approaches. These techniques enable detailed analysis and targeted refinement across every stage of the design value chain. The following sections explore their applications in three key areas: multi-phase fluid detection, versatility in material and media formats, and fluid field across the whole filter. Through these innovations, Pall continues to deliver cutting-edge filtration solutions that drive global decarbonization efforts.
Multi-phase fluid systems – such as gas-liquid or immiscible liquid-liquid systems – are central to many decarbonization processes. Applications like carbon capture, hydrogen purification, and biofuel production often involve separation of immiscible fluid phases. For example, Pall coalescers achieve high performance by coalescing droplets to ease removal of the immiscible fluid phase. However, detecting multi-phase behaviors, such as droplet coalescence and phase boundaries within filtration systems, is inherently challenging, thus adding complexity to filter design and optimization.
Advanced flow imaging brings their unique capabilities to analyze multiphase systems. For instance, NMR-based techniques can detect and differentiate two-phase flows through packed beds [1], offering clear distinguishment between the gas phase and the aqueous phase, with detailed spatial resolution down to hundreds of microns. This capability adds critical insights into flow behavior to direct filter design and optimization of operating conditions, to ensure effective phase separation in decarbonization processes.
Versatility in material and media formats
Advanced flow imaging serves as a robust foundation for filter design, as it can adapt to a variety of media materials and formats. For fibrous media widely used in decarbonization processes, these imaging techniques enable detailed analyses of fluid behaviors, such as liquid distribution and contaminant saturation across fibers. As an example, imaging technique based on magnetic resonance has been applied to track flows and study hydrodynamics in hollow fiber modules [2]. The analysis was able to resolve cross-sectional velocity maps, to evaluate filtration performance of different module designs.
In addition to fibrous media, flat-sheet media, often arranged in pleated configurations, can be analyzed in detail using CT scans. CT scans are powerful for capturing physical geometry of pleats, revealing real-life manufacturing outcomes. When paired with contrasting agents like BaSO4, CT scans can also illuminate flow paths, as BaSO4 particles carried by flows deposit and appear as bright patterns in the images. In Figure 2.1, CT scan provided a detailed view of pleat arrangements, with demonstration of flow paths highlighted by BaSO4 particles between the pleats. By integrating the geometric and flow data of pleat designs, critical insights can be obtained to optimize pleat designs, ensuring filter elements are precisely tailored to the specific demands of decarbonization applications.
Fluid field across the whole filter
Beyond fluid phase interactions and media properties, advanced flow imaging techniques can offer a comprehensive view of fluid distribution across an entire filter at the macro scale. This holistic perspective is crucial for identifying areas of stagnation, turbulence, or uneven flow that may compromise filtration efficiency.
Figure 2.2(a) shows a representative image of a Pall filter. Using advanced flow imaging and data analytics, the flow field across the entire filter can be visualized and constructed. Figure 2.2(b) provides a conceptual representation of a flow field, with quantitative information depicted through color codes. Specifically, this flow field is illustrated with rainbow color codes, where red indicates regions of high flow, and blue indicates regions of no or stagnant flow.
By reconstructing the entire flow field, bottlenecks or bypass zones that hinder filter efficiency can be precisely located. This detailed understanding enables optimization of filter geometry and hardware designs to ensure uniform flow and minimal energy loss.
Overall, by delivering system-wide insights into fluid behaviors, advanced imaging techniques are vital for next-generation filter design and optimization. Their versatility and precision enable evaluation of diverse materials, medias, and filter configurations, driving innovative solutions for decarbonization efforts.
Wen Liu is a Scientist II in the Filtration Technology team at Pall Corporation. She received her PhD in Chemical Engineering from University of Texas at Austin, where her research focused on nanomaterials and renewable energy applications. At Pall Corporation, Wen leverages her expertise in computational fluid dynamics and flow visualization testing to develop innovative filtration solutions that enhance performance and advance sustainability efforts.
[1] MH Sankey, DJ Holland, AJ Sederman and LF Gladden, "Magnetic resonance velocity imaging of liquid and gas two-phase flow in packed beds," Journal of Magnetic Resonance, no. 196, pp. 142-148, 2009.
[2] X Yang, EO Fridjonsson, ML Johns, R Wang and AG Fane, "A non-invasive study of flow dynamics in membrane distillation hollow fiber modules using low-field nuclear magnetic resonance imaging (MRI)," Journal of Membrane Science, no. 451, pp. 46-54, 2014.
[3] Ansys Inc, Ansys CFD-post Release 2024 R2.03, Cannonsburg, PA.
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