東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Modeling Flocculation and Defloccula...

Shen, Xiaoteng.

FindBook

Google Book

Amazon

博客來

Modeling Flocculation and Deflocculation Processes of Cohesive Sediments.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Modeling Flocculation and Deflocculation Processes of Cohesive Sediments./
作者:	Shen, Xiaoteng.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2016,
面頁冊數:	320 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-07(E), Section: B.
Contained By:	Dissertation Abstracts International77-07B(E).
標題:	Physical oceanography. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10031500
ISBN:	9781339531496

Modeling Flocculation and Deflocculation Processes of Cohesive Sediments.
Shen, Xiaoteng.

Modeling Flocculation and Deflocculation Processes of Cohesive Sediments. - Ann Arbor : ProQuest Dissertations & Theses, 2016 - 320 p.

Source: Dissertation Abstracts International, Volume: 77-07(E), Section: B.

Thesis (Ph.D.)--The College of William and Mary, 2016.

The transport and fate of cohesive sediments are responsible for many engineering, environmental, economic and policy issues that relate to, for example, siltation and dredging in navigation channels, water quality, water turbidity, pollutant transports, and biological ecosystem responses. Our current understanding, however, is insufficient to conduct accurate quantitative predictions of these processes. This is because the cohesive particles in natural waters will flocculate, which determines the settling, and thus the deposition behaviors. The simulation of flocculation processes is a primary challenge since the time variation of Floc Size Distribution (FSD) is controlled by a partial differential equation that also contains the integration of FSD itself. Previous models either address less characteristic sizes, which produce biased FSDs, or are incapable of modeling a relative large study domain in order to better express the FSDs with more size groups. In this study, a cohesive sediment flocculation model developed based on the framework of Population Balance Model (PBM) is solved by the Quadrature Method Of Moments (QMOM). This PBM--QMOM flocculation model has reasonably compromised by both the model robustness and model efficiency. The former lies in the capability of describing the time evolution of the FSDs with a maximum of eight size classes, and the latter is reflected in its efficiency to solve PBM with transport terms and the potential to be coupled in a flow-mud estuary model. The model predictions are compared to both the analytical (or trusted class method) results for general PBMs (i.e., beyond the scope of specific research field), and the published experimental results of kaolinite suspension and colloidal montmorillonite. After that, an experimental activity has been carried out to develop a Sony NEX-5R camera system (with extension tubes and close-up) to automatically acquire floc images under various controlled environments, and to use MATLAB software to process the FSDs. This process is validated by the results of two set of sample particles. The validated camera system is first applied in a five liter mixing chamber to investigate the effects of salinity and selected organic matters on kaolinite flocculation. Then, the camera system is improved and assembled in a waterproof house for underwater use to provide data for a conceptual one-dimensional application in a relatively large turbulence tank. The flow field of the tank is measured by an acoustic Doppler velocimetry. The flocculation processes in the mixing chamber or cylindrical tank are modeled by PBM--QMOM and validated by camera statistical FSDs. While chemical and biological effects are not explicitly included in PBM--QMOM (implicitly included in fitting parameters) at this time to address the basic mechanisms of flocculation, these effects can be further extended when the process itself is better understood through other laboratory experiments or field measurements.

ISBN: 9781339531496Subjects--Topical Terms:

3168433
Physical oceanography.

Modeling Flocculation and Deflocculation Processes of Cohesive Sediments.
LDR:04100nmm a2200313 4500 001 2154103
005 20180330130620.5
008 190424s2016 ||||||||||||||||| ||eng d
020 $a 9781339531496
035 $a (MiAaPQ)AAI10031500
035 $a AAI10031500
040 $a MiAaPQ $c MiAaPQ
100 1 $a Shen, Xiaoteng. $3 3341826
245 1 0 $a Modeling Flocculation and Deflocculation Processes of Cohesive Sediments.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2016
300 $a 320 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-07(E), Section: B.
500 $a Adviser: Jerome P.-.Maa.
502 $a Thesis (Ph.D.)--The College of William and Mary, 2016.
520 $a The transport and fate of cohesive sediments are responsible for many engineering, environmental, economic and policy issues that relate to, for example, siltation and dredging in navigation channels, water quality, water turbidity, pollutant transports, and biological ecosystem responses. Our current understanding, however, is insufficient to conduct accurate quantitative predictions of these processes. This is because the cohesive particles in natural waters will flocculate, which determines the settling, and thus the deposition behaviors. The simulation of flocculation processes is a primary challenge since the time variation of Floc Size Distribution (FSD) is controlled by a partial differential equation that also contains the integration of FSD itself. Previous models either address less characteristic sizes, which produce biased FSDs, or are incapable of modeling a relative large study domain in order to better express the FSDs with more size groups. In this study, a cohesive sediment flocculation model developed based on the framework of Population Balance Model (PBM) is solved by the Quadrature Method Of Moments (QMOM). This PBM--QMOM flocculation model has reasonably compromised by both the model robustness and model efficiency. The former lies in the capability of describing the time evolution of the FSDs with a maximum of eight size classes, and the latter is reflected in its efficiency to solve PBM with transport terms and the potential to be coupled in a flow-mud estuary model. The model predictions are compared to both the analytical (or trusted class method) results for general PBMs (i.e., beyond the scope of specific research field), and the published experimental results of kaolinite suspension and colloidal montmorillonite. After that, an experimental activity has been carried out to develop a Sony NEX-5R camera system (with extension tubes and close-up) to automatically acquire floc images under various controlled environments, and to use MATLAB software to process the FSDs. This process is validated by the results of two set of sample particles. The validated camera system is first applied in a five liter mixing chamber to investigate the effects of salinity and selected organic matters on kaolinite flocculation. Then, the camera system is improved and assembled in a waterproof house for underwater use to provide data for a conceptual one-dimensional application in a relatively large turbulence tank. The flow field of the tank is measured by an acoustic Doppler velocimetry. The flocculation processes in the mixing chamber or cylindrical tank are modeled by PBM--QMOM and validated by camera statistical FSDs. While chemical and biological effects are not explicitly included in PBM--QMOM (implicitly included in fitting parameters) at this time to address the basic mechanisms of flocculation, these effects can be further extended when the process itself is better understood through other laboratory experiments or field measurements.
520 $a Key Words: cohesive sediments; floc size distribution; population balance; quadrature method of moments; image acquisition and processing system.
590 $a School code: 0261.
650 4 $a Physical oceanography. $3 3168433
650 4 $a Civil engineering. $3 860360
650 4 $a Environmental engineering. $3 548583
690 $a 0415
690 $a 0543
690 $a 0775
710 2 $a The College of William and Mary. $3 1018629
773 0 $t Dissertation Abstracts International $g 77-07B(E).
790 $a 0261
791 $a Ph.D.
792 $a 2016
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10031500