Abstract
Wave minimal surfaces (WMSs) are mathematically defined structures that are commonly observed in nature. Their unique properties have allowed researchers to harness their potential for engineering applications. Since WMSs can be represented by mathematical equations, the geometry can be parametrized and studied using computational fluid dynamics (CFD) for particle separation. Low energy particle separation in water treatment can yield low-carbon footprint technology approaches such as biochar water treatment where removal and recovery of adsorbed N and P on biochar can address water pollution, climate change and food security. The objective of this work was to demonstrate the capability of WMS as a crossflow filtration system to remove particulates in water. For this purpose we used CFD to optimize WMS geometry and studied the performance of the 3D-Printed (3DP) optimized WMS using experimental fluid dynamics (EFD) in a water tunnel. CFD studies quantified planar vorticity, fluid filtrate flux, and particle behavior of WMS. For inflow velocities of 0.2–0.4 m/s, CFD results showed that a reverse wave filter design with convex shape leading-edge, angle of incidence of 90 o , and maximum width of n = 1.0 captured 15–25% of upstream velocity at the filter port. CFD analysis showed more than 95% separation efficiency at velocities and pressures of 0.2–0.32 m/s and 5–35 kPa, respectively. Particle Image Velocimetry (PIV) was used for EFD fluid flow measurements with an optimized wave minimal surface (OMWS). Comparison of OMWS CFD and PIV velocity fields showed good agreement with a root-mean-square error of less than 10%. Particle size analysis showed that the 3DP OMWS could filter particle sizes ranging from 1–30 μm with at least 50% particle count reduction in the filtrate. Thus, we successfully demonstrated a novel framework for analyzing a crossflow water filtration system from conceptual design to initial benchtop experiments using iterative CFD, 3DP, and EFD.