Part I deals with the simulation of fluid dynamics using the lattice-Boltzmann method. Microfluidic devices often feature two-dimensional, repetitive arrays. Flows through such devices are pressure-driven and confined by solid walls. We have defined new adaptive generalised periodic boundary conditions to represent the effects of outer solid walls, and are thus able to exploit the periodicity of the array by simulating the flow through one unit cell in lieu of the entire device. The so-calculated fully developed flow describes the flow through the entire array accurately, but with computational requirements that are reduced according to the dimensions of the array. / Part II discusses the problem of separating macromolecules like proteins or DNA coils. The reliable separation of such molecules is a crucial task in molecular biology. The use of Brownian ratchets as mechanisms for the separation of such particles has been proposed and discussed during the last decade. Pressure-driven flows have so far been dismissed as possible driving forces for Brownian ratchets, as they do not generate ratchet asymmetry. We propose a microfluidic design that uses pressure-driven flows to create asymmetry and hence allows particle separation. The dependence of the asymmetry on various factors of the microfluidic geometry is discussed. We further exemplify the feasibility of our approach using Brownian dynamics simulations of particles of different sizes in such a device. The results show that ratchet-based particle separation using flows as the driving force is possible. Simulation results and ratchet theory predictions are in excellent agreement. / Part III deals with the co-evolution of networks and dynamic models. A group of agents occupies the nodes of a network, which defines the relationship between these agents. The evolution of the agents is defined by the rules of the dynamic model and depends on the relationship between agents, i.e., the state of the network. In return, the evolution of the network depends on the state of the dynamic model. The concept is introduced through the adaptive SIS model. We show that the previously used criterion determining the critical infected fraction, i.e., the number of infected agents required to sustain the epidemic, is inappropriate for this model. We introduce a different criterion and show that the critical infected fraction so determined is in good agreement with results obtained by numerical simulations. / This thesis comprises three parts, reporting research results in Fluid Dynamics (Part I), Particle Separation (Part II) and Co-evolving Networks (Part III). / We further discuss the concept of co-evolving dynamics using the Snowdrift Game as a model paradigm. Co-evolution occurs through agents cutting dissatisfied links and rewiring to other agents at random. The effect of co-evolution on the emergence of cooperation is discussed using a mean-field theory and numerical simulations. A transition between a connected and a disconnected, highly cooperative state of the system is observed, and explained using the mean-field model. Quantitative deviations regarding the level of cooperation in the disconnected regime can be fully resolved through an improved mean-field theory that includes the effect of random fluctuations into its model. / Graeser, Oliver = 自主個體為本系統與在流體力學、分子分離、共同演化網絡上的應用 / 顧皓森. / Adviser: Hui Pak-Ming. / Source: Dissertation Abstracts International, Volume: 73-01, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 204-216). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Graeser, Oliver = Zi zhu ge ti wei ben xi tong yu zai liu ti li xue, fen zi fen li, gong tong yan hua wang luo shang de ying yong / Gu Haosen.
Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_344627 |
Date | January 2010 |
Contributors | Graeser, Oliver., Chinese University of Hong Kong Graduate School. Division of Physics. |
Source Sets | The Chinese University of Hong Kong |
Language | English, Chinese |
Detected Language | English |
Type | Text, theses |
Format | electronic resource, microform, microfiche, 1 online resource (xv, 216 leaves : ill.) |
Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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