Research On Fractal Diffusion Aggregation Of Colloidal Particles | Posted on:2024-01-05 | Degree:Master | Type:Thesis | Country:China | Candidate:Y Wu | Full Text:PDF | GTID:2530306917488154 | Subject:Electronic information | Abstract/Summary: | PDF Full Text Request | Water is an essential and important resource for human beings.Improving the treatment process of water and wastewater has important economic value and practical significance.Flocculation is one of the important unit operations of water treatment.Its main function is to make colloidal particles form flocs with suitable structure,particle size and compactness,which are easy to settle.Therefore,the flocculation operation has a crucial influence on the subsequent water treatment process and the final effluent water quality.In recent years,scientists have found through sophisticated equipment such as electron microscopes that the diffusion and coagulation of colloidal particles in water treatment is an obvious nonlinear behavior,and the final floc structure has obvious fractal characteristics.Therefore,using the fractal growth theory to carry out simulation research on the diffusion and aggregation of colloidal particles is of great significance for exploring the mechanism of diffusion and aggregation of colloidal particles and improving flocculation technology.According to the characteristics of colloidal particle diffusion and agglomeration in the process of water and wastewater treatment,random network,uniform isotropic turbulence,fragmentation-re-growth,fractal growth models,etc.are used to carry out related simulation experiments on the fractal diffusion and agglomeration of colloidal particles.The main research content of this thesis is as follows.(1)Research on the establishment of fractal diffusion and aggregation model of colloidal particlesFirstly,based on the classic diffusion limited aggregation(DLA)model,combined with the long-distance jump phenomenon that exists in the diffusion and aggregation process of colloidal particles or small particles in actual flocculation processes,the DLA model is optimized and improved to establish a colloidal particle fractal diffusion and aggregation control model with long-distance jump phenomenon.Considering the influence of microturbulence in the diffusion and aggregation of colloidal particles,the phenomenon of collision and aggregation of colloidal particles under the influence of turbulence is studied,and the model of diffusion and collision aggregation of colloidal particles under the influence of turbulence is established.(2)Fractal diffusion and aggregation control of colloidal particles based on random networksThe random network degree distribution is close to the Poisson distribution,the network shape is uniform,and it has the properties of short average path length and small clustering coefficient.In this thesis,a fractal diffusion and aggregation control model for colloidal particles based on random networks is established,and the long-distance hopping phenomenon of particles is realized by using random network pathways.The control of floc shape is realized by changing the channel connection probability and channel range,and the channel connection probability and channel range are quantitatively analyzed.The impact on flocs,and then realize the fractal diffusion and aggregation control of colloidal particles.Subsequently,this thesis uses the multifractal growth theory to compare and analyze the structural indicators of flocs under different control conditions,and uses BP neural network to compare the relationship between random network control parameters and multifractal parameters and the impact on floc morphology analyze.The simulation results show that the spectral difference Δf in the multifractal spectrum can now better characterize the influence of network range parameters on flocs,and the right spectral width αmax can better characterize the influence of network node connection probability parameters on flocs,which further explained the fractal diffusion growth mechanism of colloidal particles in water and wastewater treatment.In order to further understand the fractal growth mechanism of flocs,a simulation experiment of the crushing-regrowth process was carried out on the generated flocs.Different crushing intensities were used to crush the flocs,and the broken flocs were used as the initial core of the regrowth.Continue to conduct regrowth simulation studies on pairs under random network control conditions.The results show that the morphology and structural compactness of flocs can be effectively improved under the appropriate crushing parameters and random network control parameters.(3)Study on the control of colloidal particle collision and aggregation under uniform isotropic turbulenceThis thesis considers the influence of hydraulic or microturbulent flow on the flocculation of colloidal particles in a homogeneous and isotropic environment,a colloidal particle collision agglomeration model based on uniform isotropic turbulent flow is established.The diffusion and aggregation control of colloidal particles is realized by controlling the moving step length and offset angle of the colloidal particles.The simulation results show that the flocs formed in a homogeneous isotropic environment have fewer branches,the distribution of branches is uneven,and the overall morphology of the flocs presents a chain-like shape and other characteristics.By analyzing various characteristic indicators such as the radius of gyration,coordination number and Feret diameter of the floc,it is found that as the number of aggregated particles increases,the morphology of the floc gradually tends to be chain-like.In order to explore the mechanism of collision aggregation of colloidal particles,this thesis carried out a simulation experiment of crushing and regrowth of flocs under the condition of uniform isotropic turbulent flow.The experimental results show that when the number of aggregated particles is 5000,proper crushing leads to the minimum porosity and maximum fractal dimension of the regrown flocs. | Keywords/Search Tags: | Random Network, Floc, BP Neural Network, Multifractal, Fractal Growth Control, Uniform Isotropic Turbulent Flow, Fragmentation-regrowth | PDF Full Text Request | Related items |
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