Abstract

The fouling is a ubiquitous natural process which leads to deterioration of desirable properties of the submerged surfaces. The fouling of mammalian fur is, however, seldomly observed in nature. A mammal's energy reserve is apparently insufficient for active foulant removal, indicating that fur's anti-fouling behavior is an inherent, passive characteristic. Such ability stands in contrast to the currently available methods countering the fouling, which are predominantly active, and thus wasteful. We investigate the dependence of fur fouling on different physico-mechanical properties of the fibers, and the surrounding liquid. Using the bespoke experimental devices, we observe the fur's anti-fouling performance, and collect the data describing the fouling intensity of fibers submerged in moving or near-quiescent liquids. By combining physico-mechanical factors affecting the fouling: fluid mechanics, shape, surface topography, and surface interactions, we develop analytical and computational models to establish the correlations between the anti-fouling performances of different fibers and liquid flow regimes. The parameters such as: liquid velocity, presence of foulants in liquid, surface curvature, topographical pattern, and type of material affect the fouling in a statistically predictable manner. Manipulation of the parameters may, therefore, enable manufacturing of filaments with targeted anti-fouling properties. In addition to the physico-mechanical factors, a wide range of other factors such as: chemical factors, biological factors, stochastic processes, and deterministic phenomena influence the fouling process. Our research offers a foundation for other disciplines to build upon with the research targeting the other factors influencing the fouling, and to improve the understanding of fur's anti-fouling behavior. Passive means of foulants rejection carry tremendous potential benefits in terms of energy and environmental conservation.

Notes

If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu

Graduation Date

2023

Semester

Spring

Advisor

Ghosh, Ranajay

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Mechanical and Aerospace Engineering

Degree Program

Mechanical Engineering

Format

application/pdf

Identifier

CFE0009552; DP0027561

URL

https://purls.library.ucf.edu/go/DP0027561

Language

English

Release Date

May 2028

Length of Campus-only Access

5 years

Access Status

Doctoral Dissertation (Campus-only Access)

Download

Restricted to the UCF community until May 2028; it will then be open access.

Share

COinS