臺灣博碩士論文加值系統

在深床過濾行為的討論中，本論文將以布朗運動模擬方法探討個別膠體粒子在多孔性過濾器的網絡中吸附過濾的動態行為。本研究的模擬條件包含三種不同的網絡模型，分別為改良式正方型、正三角型、和蜂窩型網絡，在相同的初始可穿透度之下，並配合二種不同型態的DLVO能量曲線來進行探討。特徵過濾函數F1(α,σ) 和F2(β,σ)將分別由過濾床出口
的粒子濃度比及壓降曲線在達到穩定時計算而得。模擬結果發現，在相同的網絡架構模型下，在無能障狀態的DLVO能量曲線時，單位收集器體積所吸附的膠體粒子體積值較具有DLVO能障時高。若在相同的能量曲線之下進行三種不同網絡架構的過濾效率比較，結果
發現蜂窩型網絡較為容易過濾膠體粒子，其原因在於在網絡的節點上具有較少的進出管數值，因此其單位收集器體積所能過濾的膠體粒子體積值將會較其他網絡模型為高。在相同的過濾條件下，針對三種網絡模型進行實驗數據的模擬，結果發現正三角型網絡模型對深床過濾的動態行為具有最佳的預測性。

The dynamic behavior of deep bed filtration is investigated in the
present paper by using the Brownian dynamic simulation method to track the individual particles moving through the network structure of porous media in the filter bed. Present simulations include three different network structures of modified square, triangular and honeycomb with the same initial permeability, and two types of DLVO interaction energy curves. The specific filtration functions of F1(α,σ) and F2(β,σ) are determined from the breakthrough curves of effluent concentration and the pressure drop, respectively. It is found that, since the “barrierless” type interaction energy curve favors particle deposition on the pore walls, hence its corresponded specific deposit σ is higher than that of interaction energy curve with energy barrier existed for the same network structure. When comparing the filtration effect of those three different network structures with the same interaction energy curve, the honeycomb network can filter those particles the easiest because of its lowest coordination number, so its corresponded specific deposit σ is the highest. When comparing the available experimental data with those simulation results of three different network structures in the same filter bed, it is found that the triangular network offers the best accuracy on predicting the dynamic behavior of granular filtration.

摘要………………………………………………………………………I
Abstract…………………………………………………………………II
目錄………………………………………………………………………IV
圖表目錄…………………………………………………………………VI
誌謝………………………………………………………………………XIII

一、緒論…………………………………………………………………1
二、文獻回顧與理論分析………………………………………………4
1、深床過濾的現象方程式 ……………………………………………4
2、網絡模型 ……………………………………………………………7
3、楔型管模型 …………………………………………………………10
4、布朗動態模擬法 ……………………………………………………11
5、DLVO理論的能量曲線………………………………………………11
三、模擬方法……………………………………………………………16
四、結果與討論…………………………………………………………20
1、模擬結果探討 ………………………………………………………20
2、與實驗數據之比較 …………………………………………………30
五、結論與展望…………………………………………………………37
六、參考文獻……………………………………………………………42
七、符號說明……………………………………………………………44
八、附錄…………………………………………………………………50
附錄一：楔型管內的流場分佈與軌跡吸附方程式的推導 ………50
附錄二：在模擬流程中，過濾器的可穿透度、壓降及其他參數的
計算 …………………………………………………………………63
附錄三：於本論文研究過程中，已發表的文獻與會議報告 ……65
附錄四：於改良式正方型網絡模型、SCT楔型管的條件，在相同
的DLVO能障曲線下，不同的膠體濃度對於可穿透度與壓降變化
的探討 ………………………………………………………………66
附錄五：膠體粒子大小對於DLVO能障曲線形狀改變影響的探討
…………………………………………………………………………77
附錄六：於不同的網絡模型、DLVO能障、楔型管管型、及有無
布朗運動的模擬條件下，filtration functions F1(α,σ)
(break-through concentration)與F2(β,σ)(pressure
drop)的比較與探討…………………………………………………81
附錄七：以正三角型網絡模型、SCT楔型管的條件下，進行模擬
並與實驗數據比較的探討……………………………………………112
作者簡歷………………………………………………………………116

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