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You searched for +publisher:"University of Southern California" +contributor:("De Barros, Felipe"). Showing records 1 – 3 of 3 total matches.

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University of Southern California

1. Haddad Zadegan, Hamed. Data worth analysis in geostatistics and spatial prediction.

Degree: PhD, Civil Engineering, 2015, University of Southern California

A main challenge in decision making on soil remediation is risk management through acquisition of knowledge using more informative models and data. To demonstrate the approach to this problem, value of information should be considered and computed. To improve the quality of prediction of contamination we need to have more data or samples. When we add new samples to our model, we get new probability distribution function for the quantity of interest. Then we need to compare the old (prior) and new (posterior) predictions and quantify the difference and improvement from one prediction to another one and measure information content of predictions. Also, to find the best design for location of new samples, we should find the samples that provide maximum information compared to other samples. Samples with maximum information will be the optimal design for location of new data. The optimal design minimizes the cost of sampling because it provides the most possible information with minimum number of samples. ❧ In this research we try to identify the best locations for new samples. To address this problem, Kullback-Leibler divergence which is a measure in probability theory is used. The Kullback-Leibler divergence represents the difference between two probability distribution functions. Under the assumption of Multi-variate normal distribution for log-transformed concentration data, the Kullback-Leibler divergence can be considered as a tool to measure the information content of new samples. Computation of information content of new samples helps us to optimize the location of new samples. Advisors/Committee Members: Ghanem, Roger G. (Committee Chair), Masri, Sami F. (Committee Member), De Barros, Felipe (Committee Member), Meshkati, Najmedin (Committee Member), Sahimi, Muhammad (Committee Member).

Subjects/Keywords: geostatistics; Kullback-Leibler divergence; sampling design; soil remediation; value of information

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Haddad Zadegan, H. (2015). Data worth analysis in geostatistics and spatial prediction. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/280600/rec/1769

Chicago Manual of Style (16th Edition):

Haddad Zadegan, Hamed. “Data worth analysis in geostatistics and spatial prediction.” 2015. Doctoral Dissertation, University of Southern California. Accessed November 21, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/280600/rec/1769.

MLA Handbook (7th Edition):

Haddad Zadegan, Hamed. “Data worth analysis in geostatistics and spatial prediction.” 2015. Web. 21 Nov 2019.

Vancouver:

Haddad Zadegan H. Data worth analysis in geostatistics and spatial prediction. [Internet] [Doctoral dissertation]. University of Southern California; 2015. [cited 2019 Nov 21]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/280600/rec/1769.

Council of Science Editors:

Haddad Zadegan H. Data worth analysis in geostatistics and spatial prediction. [Doctoral Dissertation]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/280600/rec/1769


University of Southern California

2. Li, Weixuan. Inverse modeling and uncertainty quantification of nonlinear flow in porous media models.

Degree: PhD, Civil Engineering, 2014, University of Southern California

When using computer models to predict flow in porous media, it is necessary to set parameter values that correctly characterize the geological properties like permeability and porosity. Besides direct measurements of these geological properties, which may be expensive and difficult, parameter values could be obtained from inverse modeling which calibrates the model to any available observations on flow behaviors such as pressure, saturation and well production rates. A typical inverse problem has non‐unique solutions because the information contained in the observations is usually insufficient to identify all uncertain parameters. Finding a single solution to the inverse problem that well matches all observations does not guarantee the correct representation of the real geological system. In order to capture multiple solutions and quantify remaining uncertainty we solve an inverse problem from a probabilistic point of view: seek the posterior distribution of parameters given the observations using Bayes' theorem. In the situation where the model is nonlinear, which is often the case of subsurface flow problems, the posterior distribution cannot be analytically derived. Instead we implement numerical algorithms to find approximate results. The key to running an inversion algorithm is to understand how the model input (parameters) and model output (simulation results) are related to each other. For complex models where direct derivation is difficult this task can be done by running a large number of trial simulations with different parameter values. These algorithms work well for simple small scale models but are prohibitively expensive to apply to subsurface flow models since each single run may take a long time and we do not have unlimited time and resource to run the trial simulations. ❧ The main contribution of this research is the development and test of two approaches—the "adaptive ANOVA‐based probabilistic collocation Kalman filter (PCKF)" and "adaptive sampling via Gaussian process (GP)‐based surrogates"—for inverse modeling of nonlinear flow in porous media models. Both approaches fall into the category of probabilistic inversion and have the capability to quantify remaining uncertainty. This study focuses on computational efficiency, which is often the bottleneck of implementing inverse modeling and uncertainty quantification (UQ) algorithms for nonlinear models. The selection of proper inversion approach to be used is problem dependent. The "adaptive ANOVA‐based PCKF", is a nonlinear variant of the classic Kalman filter approach, which estimates the first two statistical moments, i.e., mean and covariance, of the posterior distribution. It applies to the problems where the nonlinearity is mild and the posterior distribution is approximately Gaussian. The main idea is to represent and propagate uncertainty with a proper polynomial chaos expansion (PCE) that is adaptively selected for the specific problem. The second method is more general and deals with stronger nonlinearity and non-Gaussian, even… Advisors/Committee Members: Zhang, Dongxiao (Committee Chair), Jafarpour, Behnam (Committee Member), De Barros, Felipe (Committee Member), Ghanem, Roger G. (Committee Member).

Subjects/Keywords: flow in porous media; uncertainty quantification; nonlinear and probabilistic inverse modeling

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Li, W. (2014). Inverse modeling and uncertainty quantification of nonlinear flow in porous media models. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/366536/rec/3613

Chicago Manual of Style (16th Edition):

Li, Weixuan. “Inverse modeling and uncertainty quantification of nonlinear flow in porous media models.” 2014. Doctoral Dissertation, University of Southern California. Accessed November 21, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/366536/rec/3613.

MLA Handbook (7th Edition):

Li, Weixuan. “Inverse modeling and uncertainty quantification of nonlinear flow in porous media models.” 2014. Web. 21 Nov 2019.

Vancouver:

Li W. Inverse modeling and uncertainty quantification of nonlinear flow in porous media models. [Internet] [Doctoral dissertation]. University of Southern California; 2014. [cited 2019 Nov 21]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/366536/rec/3613.

Council of Science Editors:

Li W. Inverse modeling and uncertainty quantification of nonlinear flow in porous media models. [Doctoral Dissertation]. University of Southern California; 2014. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/366536/rec/3613


University of Southern California

3. Ghadiri, Maryam. Feasibility of using a lined portion of the Los Angeles River for artificial recharge.

Degree: PhD, Civil Engineering (Environmental Engineering), 2015, University of Southern California

This dissertation investigates the feasibility of using artificial recharge derived from surface water in a portion of the Los Angeles River north of the city of Los Angeles in Southern California. Currently, the river channel in this area is concrete lined with no percolation capability. The purpose of this study is to determine the technical and economic feasibility of removing a portion of the lined channel to allow infiltration into aquifers of the Central Basin of Los Angeles County (specifically, the forebay area). Water artificially recharged through a breach in the lined channel will be banked for later use in dry seasons or when otherwise needed to supplement water supply. The study includes removing a portion of the lined channel by removing a portion of the concrete pavement and estimating the amount of artificial recharge that could occur under various infiltration rates for different soils. In addition, the net benefit of replenishing groundwater basin over a ten year study period will be evaluated. If the study period is chosen too short, the project may not be economically feasible. Also, if the study period is chosen too long, then the uncertainty in the parameters that were used for this study will be large. This study is presented in stages with the first stage estimating the amount of surface water that could be recharged into the aquifers using a distributed parameter ground water flow model. The second stage would be an economic feasibility of proposed alternatives developed by enumerating costs associated with the optimal execution of the project as well as potential benefits. In conjunction with this, an optimization pumping plan was formalized. Specifically, well discharge rates were optimized in order to achieve maximum ground water storage within the relevant geohydrological and land use constraints. Based on the optimal pumping rates, pumping costs and value of extracted water was estimated which together, along with construction costs, were analyzed in a comprehensive cost-benefit analysis. Advisors/Committee Members: Lee, Jiin-Jen (Committee Chair), Williams, Dennis (Committee Member), Wellford, L., Carter (Committee Member), Moore, James Elliott, II (Committee Member), De Barros, Felipe (Committee Member).

Subjects/Keywords: Los Angeles River; artificial recharge; conjunctive use; optimization; economic study; groundwater

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ghadiri, M. (2015). Feasibility of using a lined portion of the Los Angeles River for artificial recharge. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/605672/rec/2784

Chicago Manual of Style (16th Edition):

Ghadiri, Maryam. “Feasibility of using a lined portion of the Los Angeles River for artificial recharge.” 2015. Doctoral Dissertation, University of Southern California. Accessed November 21, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/605672/rec/2784.

MLA Handbook (7th Edition):

Ghadiri, Maryam. “Feasibility of using a lined portion of the Los Angeles River for artificial recharge.” 2015. Web. 21 Nov 2019.

Vancouver:

Ghadiri M. Feasibility of using a lined portion of the Los Angeles River for artificial recharge. [Internet] [Doctoral dissertation]. University of Southern California; 2015. [cited 2019 Nov 21]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/605672/rec/2784.

Council of Science Editors:

Ghadiri M. Feasibility of using a lined portion of the Los Angeles River for artificial recharge. [Doctoral Dissertation]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/605672/rec/2784

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