Inspired by the high adhesiveness of the electrospun fiber, we propose a method to fabricate multi-scale heterogeneous hump-on-string fiber via the adsorption of nanoparticles, the NPCTi which is the hydrolysate of titanium tetrachloride (TiCl4) and the nanoparticles containing Al (NPCAl) which is produced by the hydrolysis of Trimethylaluminium (TMA, Al(CH3)3). The water collection efficiency of the fibers can be easily controlled via changing not only the size of the beads but also the ratio of the Ti and Al. In addition, we introduce a computational fluid dynamics (CFD) simulation to show the pressure distribution of on the surface of the fibers, which gives another explanation regarding the high water collection efficiency.
Turbulence plays a key role in the aerospace design process. It is common that incompressible and compressible flows coexist in turbulent flows around aerospace vehicles. However, most upwind schemes in compressible solvers were designed to capture shock waves and have been proved to have difficulties in predicting low-speed flow regions. In order to overcome this defect, many all-speed schemes have been proposed. This paper investigates the properties of the all-speed schemes when applying to Reynolds averaged Navier–Stokes simulations with important low-speed features. First, the correctness of our code is validated. Then four test cases are adopted to evaluate the scheme performance, including a Mach 2.85 compression ramp, the NACA 4412 airfoil, a Mach 2.92 ramped cavity and a three-dimensional surface-mounted cube. Grid-converged results from the all-speed schemes show good agreement with the experimental data and remarkable improvement when compared to standard upwind schemes. Moreover, different from the traditional preconditioning methods, the all-speed schemes are simple to realize and free from the cut-off strategy or any problem-dependent parameter. Therefore, they are expected to be widely implemented into compressible solvers and applied to all-speed turbulent flow simulations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.