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Characterization of reactive solute ...

Williams, Rachael.

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Characterization of reactive solute transport in laboratory column experiments using temporal moments.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Characterization of reactive solute transport in laboratory column experiments using temporal moments./
作者:	Williams, Rachael.
面頁冊數:	108 p.
附註:	Source: Dissertation Abstracts International, Volume: 65-03, Section: B, page: 1223.
Contained By:	Dissertation Abstracts International65-03B.
標題:	Environmental Sciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3125487
ISBN:	0496727761

Characterization of reactive solute transport in laboratory column experiments using temporal moments.
Williams, Rachael.

Characterization of reactive solute transport in laboratory column experiments using temporal moments. - 108 p.

Source: Dissertation Abstracts International, Volume: 65-03, Section: B, page: 1223.

Thesis (Ph.D.)--Clemson University, 2004.

A method is presented for the analysis of contaminant breakthrough curves from laboratory column experiments using temporal moments. The temporal moments were used (1) to determine if an experimental breakthrough curve can be predicted by one of three linear advection/dispersion/sorption models and (2) to estimate the corresponding transport and sorption parameters. The technique was developed for both known and unknown Peclet number. It was first tested for ideal breakthrough curves (error-free data with small time increments) and was generally successful in identifying if one of the three linear models was consistent with a given breakthrough curve and providing accurate estimates of transport parameters.

ISBN: 0496727761Subjects--Topical Terms:

676987
Environmental Sciences.

Characterization of reactive solute transport in laboratory column experiments using temporal moments.
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245 1 0 $a Characterization of reactive solute transport in laboratory column experiments using temporal moments.
300 $a 108 p.
500 $a Source: Dissertation Abstracts International, Volume: 65-03, Section: B, page: 1223.
500 $a Adviser: Robert Fjeld.
502 $a Thesis (Ph.D.)--Clemson University, 2004.
520 $a A method is presented for the analysis of contaminant breakthrough curves from laboratory column experiments using temporal moments. The temporal moments were used (1) to determine if an experimental breakthrough curve can be predicted by one of three linear advection/dispersion/sorption models and (2) to estimate the corresponding transport and sorption parameters. The technique was developed for both known and unknown Peclet number. It was first tested for ideal breakthrough curves (error-free data with small time increments) and was generally successful in identifying if one of the three linear models was consistent with a given breakthrough curve and providing accurate estimates of transport parameters.
520 $a To test the robustness of the technique, it was then applied to simulated breakthrough curves more representative of those that might be obtained experimentally. These curves were produced by introducing random error into the concentration data and increasing the time increment between data points. When data error and time increment were considered simultaneously, it was found that relative errors greater than about 10-4 or 10-3 could not be tolerated, hence raising questions about the practical applicability of the moments method. However, in the analysis of some real breakthrough data the results using the moments technique were consistent with those from curve fitting, while inconclusive for other data sets.
520 $a The two practical implications of this research are (1) the importance of minimizing data error as much as possible in the conduct of column experiments and (2) the identification of a hybrid approach for analyzing breakthrough curves which involves both curve fitting and higher order moments. This hybrid approach overcomes the limitation of pure curve fitting, i.e. the inability to distinguish between models which are consistent with the data and those which are not, and the limitation of the moments technique, which is significant uncertainty in parameter estimation due to data error.
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