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An Adjoint-Sensitivity-Analysis Base...

Tang, Tian.

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An Adjoint-Sensitivity-Analysis Based Mathematical Framework: DNAPL Source Zone Characterization, Uncertainty Quantification, and Sampling Strategy Design.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	An Adjoint-Sensitivity-Analysis Based Mathematical Framework: DNAPL Source Zone Characterization, Uncertainty Quantification, and Sampling Strategy Design./
作者:	Tang, Tian.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	301 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-09, Section: B.
Contained By:	Dissertations Abstracts International80-09B.
標題:	Engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13426142
ISBN:	9781392008263

An Adjoint-Sensitivity-Analysis Based Mathematical Framework: DNAPL Source Zone Characterization, Uncertainty Quantification, and Sampling Strategy Design.
Tang, Tian.

An Adjoint-Sensitivity-Analysis Based Mathematical Framework: DNAPL Source Zone Characterization, Uncertainty Quantification, and Sampling Strategy Design. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 301 p.

Source: Dissertations Abstracts International, Volume: 80-09, Section: B.

Thesis (Ph.D.)--Tufts University, 2019.

This item must not be sold to any third party vendors.

Subsurface contamination by dense non-aqueous phase liquids (DNAPLs) is a continuing societal concern due to the widespread use and improper disposal of these compounds. Due to the heterogeneous nature of geological formations, which leads to a high degree of spatial variability in DNAPL migration and entrapment, delineation of the distribution of source zone mass and the associated downgradient plume presents significant challenges. This research focused on the local estimation of source zone mass distribution metrics from in situ Push-Pull Tracer Tests (PPTTs) and on the optimization of source zone characterization for predictions of future plume persistence and risk to down gradient receptors. An adjoint sensitivity analysis- and inverse theory-based mathematical model is developed and implemented to estimate domain-averaged source zone properties (total mass, average DNAPL saturation, and mass weighted distance from the test well) using PPTT data, accounting for both rate-limited mass transfer and heterogeneity in both the flow field and source zone mass distribution. This model is demonstrated to provide reliable estimates of source zone metrics with accuracy better than 20%. Estimation error of domain-averaged source zone metrics is shown to increase with increased heterogeneity of the permeability field and DNAPL saturation distribution. Comparison of the presented estimation approach with that based upon a local equilibrium partitioning assumption demonstrates the superiority of the new approach, with equilibrium-based estimates resulting in overestimation of the average saturation. In the second portion of this work, an adjoint sensitivity analysis and first-order second-moment based source zone characterization model, honoring borehole observations, is designed and validated for prediction of downgradient flux-averaged concentration (FAC) and its variance at distinct times. Adjoint state theory is applied to quantify the importance of local system properties (e.g., permeability field, initial contaminant mass in aqueous, sorbed, and DNAPL phases) on FAC. By considering the process coupling of DNAPL dissolution, sorption, dispersion, and mass transport, results reveal that local permeability has the greatest impact on FAC predictions. Data worth analyses are performed to guide optimal sampling strategy to provide more accurate FAC predictions and to maximize uncertainty reduction. It is demonstrated that areas of low permeability and high DNAPL saturation have the largest utility for uncertainty reduction and that optimal borehole observation locations vary with the prediction time window. The FOSM-based optimal sampling patterns are demonstrated to outperform alternative sampling approaches for most of the prediction goals, yielding more precise estimates and better confidence intervals.

ISBN: 9781392008263Subjects--Topical Terms:

586835
Engineering.

An Adjoint-Sensitivity-Analysis Based Mathematical Framework: DNAPL Source Zone Characterization, Uncertainty Quantification, and Sampling Strategy Design.
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245 1 3 $a An Adjoint-Sensitivity-Analysis Based Mathematical Framework: DNAPL Source Zone Characterization, Uncertainty Quantification, and Sampling Strategy Design.
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300 $a 301 p.
500 $a Source: Dissertations Abstracts International, Volume: 80-09, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
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506 $a This item must not be sold to any third party vendors.
520 $a Subsurface contamination by dense non-aqueous phase liquids (DNAPLs) is a continuing societal concern due to the widespread use and improper disposal of these compounds. Due to the heterogeneous nature of geological formations, which leads to a high degree of spatial variability in DNAPL migration and entrapment, delineation of the distribution of source zone mass and the associated downgradient plume presents significant challenges. This research focused on the local estimation of source zone mass distribution metrics from in situ Push-Pull Tracer Tests (PPTTs) and on the optimization of source zone characterization for predictions of future plume persistence and risk to down gradient receptors. An adjoint sensitivity analysis- and inverse theory-based mathematical model is developed and implemented to estimate domain-averaged source zone properties (total mass, average DNAPL saturation, and mass weighted distance from the test well) using PPTT data, accounting for both rate-limited mass transfer and heterogeneity in both the flow field and source zone mass distribution. This model is demonstrated to provide reliable estimates of source zone metrics with accuracy better than 20%. Estimation error of domain-averaged source zone metrics is shown to increase with increased heterogeneity of the permeability field and DNAPL saturation distribution. Comparison of the presented estimation approach with that based upon a local equilibrium partitioning assumption demonstrates the superiority of the new approach, with equilibrium-based estimates resulting in overestimation of the average saturation. In the second portion of this work, an adjoint sensitivity analysis and first-order second-moment based source zone characterization model, honoring borehole observations, is designed and validated for prediction of downgradient flux-averaged concentration (FAC) and its variance at distinct times. Adjoint state theory is applied to quantify the importance of local system properties (e.g., permeability field, initial contaminant mass in aqueous, sorbed, and DNAPL phases) on FAC. By considering the process coupling of DNAPL dissolution, sorption, dispersion, and mass transport, results reveal that local permeability has the greatest impact on FAC predictions. Data worth analyses are performed to guide optimal sampling strategy to provide more accurate FAC predictions and to maximize uncertainty reduction. It is demonstrated that areas of low permeability and high DNAPL saturation have the largest utility for uncertainty reduction and that optimal borehole observation locations vary with the prediction time window. The FOSM-based optimal sampling patterns are demonstrated to outperform alternative sampling approaches for most of the prediction goals, yielding more precise estimates and better confidence intervals.
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