Theses and Dissertations

Fall 2010

Hong, Sahyun

, nonlinear relations and different qualities. Previous approaches rely on a strong Gaussian assumption or the combination of the source-specific probabilities that are individually calibrated from each data source. This dissertation develops different approaches to integrate diverse earth science data

. First approach is based on combining probability. Each of diverse data is calibrated to generate individual conditional probabilities, and they are combined by a combination model. Some existing models are reviewed and a combination model is proposed with a new weighting scheme. Weakness of the

probability combination schemes (PCS) is addressed. Alternative to the PCS, this dissertation develops a multivariate analysis technique. The method models the multivariate distributions without a parametric distribution assumption and without ad-hoc probability combination procedures. The method accounts

Spring 2022

Nwabia, Francis N

(DFN) model offers a viable alternative for explicit representation of multiple fractures in the domain, where the comprising fracture properties are defined in accordance with specific probability distributions. However, even with the successful modelling of a DFN, the relationship between a set of

) interpretations, which are useful for inferring the prior probability distributions of relevant fracture parameters. A pilot point scheme and sequential indicator simulation are employed to update the distributions of fracture intensities which represent the abundance of secondary fractures (NFs) in the entire

), transmissivity of the secondary induced fracture (Tsf) and secondary fracture intensity (Psf32L), secondary fracture aperture (re), length and height (L and H), in a multifractured shale gas well in the Horn River Basin. An initial realization of the DFN model is sampled from the prior probability distributions

Spring 2015

nejadi, siavash

Gaussian variables, but it often fails to honor the reference probability distribution of the model parameters where the distribution of model parameters are non-Gaussian and the system dynamics are strongly nonlinear. In this thesis, novel sampling procedures are proposed to honor geologic information in

certain number of assimilation steps, the updated ensemble is used to generate a new ensemble that is conditional to both the geological information and the early production data. Probability field simulation and a novel probability weighted re-sampling scheme are introduce to re-sample a new ensemble

. After the re-sampling step, iterative EnKF is again applied on the ensemble members to assimilate the remaining production history. A new automated dynamic data integration workflow is implemented for characterization and uncertainty assessment of fracture reservoir models. This new methodology includes

Spring 2015

Sadeghi, Naimeh

. Stochastic uncertainty is a system property and represents the uncertainty associated with variation of a variable. Stochastic uncertainty can be represented by a probability distribution. On the other hand, subjective uncertainty represents the lack of knowledge of the system modeller regarding the actual

DES is only able to consider stochastic uncertainty using probability distributions; and cannot handle subjective uncertainty. Fuzzy set theory provides a methodology for mathematical modelling of subjective uncertainty. Recently, fuzzy discrete event simulation (FDES) has been proposed for

considering subjective uncertainty in construction simulation models. However, the fundamental differences between fuzzy numbers and probability distributions introduce new challenges to FDES frameworks. Furthermore, subjective and stochastic uncertainties may simultaneously exist in a simulation model

Fall 2023

Sanchez Villar, Sebastian

bivariate distribution and shows novel equations for the calculation of probabilities of the internal bivariate distribution. Additionally, it proposes a workflow to use the equations as a tool to aid the indicator variogram modeling process. Third, it proposes a new methodology of MIK that uses the RBF

Quantifying uncertainty is a critical task of resource delineation in the mining industry. Uncertainty is used to assess risk in economic evaluation and for classification in resource reporting. The inference of local distributions from conditioning data is key to quantifying uncertainty. Multiple

indicator Kriging (MIK) is a well-established non-parametric local distribution inference technique that does not assume a prior distribution. The local conditional cumulative distribution functions (CCDF) are estimated directly from indicators defined from thresholds. MIK is flexible since allows the

Fall 2013

Macciotta, Renato

through a Monte Carlo simulation technique, and the outcome of the analysis is a probability distribution of the estimated risk. This methodology shows the potential for evaluating the uncertainties related to risk estimations. The full potential of the risk management framework is best met with the

carried out for two case histories, where population of the analyses input parameters is done as probability distributions rather than fixed values. The probability distributions of the input parameters cover the range of values believed realistic for each input parameter. The risk is then estimated

establishment of risk evaluation criteria. The other objective of this work focuses on the development of risk evaluation criteria. It is not the intention of this work to develop case specific criteria, as this responsibility should lie with owners and regulators, but to propose a framework for developing the

Fall 2019

Rajabpour Ashkiki, Alireza

of particle size distribution and composition, on trommel’s screening performance during full-scale operation throughout the year. Also investigated was the impact of clogging of screen apertures on screening of material. The second set of objectives were defined to characterize the operation

performance of the waste processing system, with a primary focus on the trommel, using system analysis methods including system availability, maintainability and throughput. A two-stage trommel, respectively, with 5 cm and 23 cm screens was evaluated in this study. The trommel design capacity was 55 tonnes

compositional analyses. Separation efficiency and recovery results verified that the performance of the first stage varied seasonally, primarily due to changes in the particle size distribution of the feedstock; secondly, because of a greater feed rate. The seasonal variation in the compostable fraction of the

Fall 2016

Kang, Chao

well with that from the numerical experiments. In order to use the new entrainment model into debris flow runout calculation, the new entrainment model has been incorporated in a runout model based on an energy approach. Entrainment calculation governed by a second order partial differential equation

failure mechanism. A new analytical model is proposed to calculate entrainment in debris flow analysis by considering both rolling and shearing motion. Newton’s Law of Motion is used to calculate accelerations, velocities, and displacements of granular particles. To study the entrainment process inside

granular flow and to verify the new entrainment model, numerical experiments have been carried out using the Discrete Element Method (DEM). Velocities, including translational velocity, rotational velocity and average velocity, total volume, shear stresses are monitored using measurement circles in the

Spring 2019

Prybysh, Robert

to establish a cumulative distribution function of the direct comparison of long-term costs between two systems. This allows the evaluator to not only establish the probability that one system will have a lower life cycle cost over another system, but also the degree of savings.

residential buildings of various sizes. Although the technique has been utilized for many years, the performance and efficiency, the effects of using potable water as a hydronic medium on water quality, and the long-term operational cost implications have yet to be explored through dedicated research. This

building. This involves establishing the building efficiency as steady state efficiency and a standby loss, a methodology previously presented for individual appliances, but not explored for both the heating and cooling performances of complete building systems. The impact on the palatability of the water

Fall 2009

Hosseini, Amir Hossein

uncertainty band that meets the requirements of unbiasedness and fairness of the calibrated probabilities. The second development in this thesis is related to a probabilistic model for characterization of uncertainty in the 3D localized distribution of residual NAPL in a real site. A categorical variable is

source geometry and hydraulic conductivity distribution. The central idea in this thesis is to develop a flexible modeling approach for characterization of uncertainty in residual NAPL dissolution rate and first-order biodegradation rate by tailoring the estimation of these parameters to distributions of

defined based on the available CPT-UVIF data, while secondary data based on soil texture and groundwater table elevation are also incorporated into the model. A cross-validation study shows the importance of incorporation of secondary data in improving the prediction of contaminated and uncontaminated