Theses and Dissertations

Spring 2017

Fallah Nafari, Saeideh

framework was also developed to estimate the probability distributions of maximum tensile and compressive bending stresses in the rail head and base, which are necessary for calculating the rail reliability under applied loading. The accuracy of the proposed equations was first verified using a numerical

method was developed which allowed the simulation of a stochastically varying track modulus along the track. Track models with different track modulus distributions were developed and the resulting VTD and rail bending stresses under moving wheel loads were calculated. The mathematical correlations

between the inputted track modulus, modelled VTD and rail bending stresses were quantified using statistical approaches. Based on the results, equations were proposed to estimate the statistical properties of track modulus and rail bending stresses over track windows using the VTD measurements. A

Fall 2015

Lajevardi, Saina

. Notable features of this thesis are (1) addressing information loss in facies upscaling process through a proposed measure which captures variability on non-major facies; (2) proposing a novel inverse modeling approach to estimate shale continuity in the form of a probability distribution function; (3

Spring 2010

Alshehri, Naeem S.

technical analysis considering all available data. Current methods of estimating resource uncertainty use spreadsheets or Monte Carlo simulation software with specified probability distributions for each variable. 3-D models may be constructed, but they rarely consider uncertainty in all variables. This

. The CFD approach produced more realistic uncertainty in distributions of the HIIP than those obtained from the BS or SBS approaches. 0-D modeling was used for estimating uncertainty in HIIP with different source of thickness. 2-D is based on geological mapping and can be presented in 2-D maps and

A reliable estimate of the amount of oil or gas in a reservoir is required for development decisions. Uncertainty in reserve estimates affects resource/reserve classification, investment decisions, and development decisions. There is a need to make the best decisions with an appropriate level of

Spring 2024

Valdivia Paucar, Myzael J.

parameter of a material as a random variable with a specific probability distribution. The outcomes of such analyses are evaluated through design acceptance criteria (DAC) that incorporate uncertainty in terms of design reliability – also known as Reliability-Based Design Acceptance Criteria (RBDAC

on a modified open pit slope, inspired by the geotechnical, geological, and hydrological characteristics of an implemented pit slope located in British Columbia, Canada. The outcomes of this research yield significant insights for forthcoming probabilistic open pit slope stability analyses. The

to higher coefficients of variation and thus an elevated probability of failure. These results can be the defining factor between designs deemed acceptable or not, as per the RBDAC criteria. Based on these outcomes, it is suggested that practitioners consider, depending on the necessity of the design

Spring 2024

Mirhadi, Seyed Nima

short-term temperature fluctuations play a significant role in landslide occurrences at the C018 site, and their effect can be quantified from a probabilistic approach. A clear weather signature has been identified for landslides occurring in the winter months. Moreover, statistical analyses on

landslides occurring in spring and summer showed that if there is more than 20 mm of rainfall in 14 days, there is a 6% probability of a landslide, with a 0.1% probability of a landslide if there is less than 20 mm of rainfall in the preceding 14 days. This probabilistic approach provides a means to identify

. The results show that a linear relationship can be approximated between the annual precipitation and the annual volume of landslides. This relationship is then used to estimate the annual volume of landslides by considering the projected annual precipitation based on the climate change models for the

Spring 2021

Mancell, Steven, A.

Mineral exploration and mining are capital intensive and carry significant environmental and societal considerations. The feasibility of prospective mining operations hinges on a series of engineering decisions. The mineral resource estimation of the quality and quantity of resources greatly

generates a single model output and does not carry a measure of uncertainty. Stochastic approaches to boundary modeling capture short scale variability of the geology; however, imparting geological knowledge on the model is difficult. This thesis develops a new implicit methodology for boundary modeling

that provides globally unbiased models with uncertainty. The indicator approach maps a field of probabilities and applies a threshold that results in an extracted boundary. Uncertainty assessment by varying the indicator thresholds provides eroded and dilated boundaries and a zone of uncertainty

Fall 2024

Al Hasan, Iyad

pairwise comparison matrices and utilizes probability distributions to establish objective weights for each criterion. The developed evaluation model incorporates a Linear Additive Utility Model (LAUM) to calculate a Performance Index (PI) that quantifies subcontractor performance across various levels

The management of the contractor-subcontractor relationship is a pivotal component of supply chain management in the construction industry, significantly impacting project success. This thesis explores approaches to assess performance of subcontractor, select the best subcontractor and the critical

role of subcontractors in construction projects. Traditionally, process of subcontractor assessment performance and selection have been influenced by subjective assessments, often leading to biased decision-making processes. To address this, the research develops a comprehensive framework that links

Fall 2022

Mehranfar, Mahyar

longitudinal direction. The second objective was to test the performance of the new technique on a variety of pipeline dents. The developed method is based on the three-dimensional mathematical model proposed by Okoloekwe et al. In the original model proposed by Okoloekwe et al, it was assumed that the

the pipeline can cause lower pressure capacity. Analytical and numerical models, such as the finite element method (FEA), can predict this issue. The traditional way for recognizing the seriousness of the dent is to test the dent depth. But unfortunately, this method cannot predict the probability of

failure accurately. Based on previous research, there are two ways to assess the seriousness of the dents. The first method is to model the pipe by finite element method. While very accurate, the finite element method is very computationally demanding and time consuming. The second method utilizes the

Spring 2018

Ma, Zhiwei

these trained models are shown to be both reliable and satisfactory. Next, a series of synthetic SAGD models based on typical Athabasca oil reservoir properties and operating conditions is constructed. Heterogeneities are modeled by randomly sampling distribution, volume, and orientation of shale

barriers and lean zones from several probability distributions inferred from field data, and are superposed to the base homogenous models. Many parameterization schemes are investigated to extract input and output parameters from production time-series data and heterogeneous configurations, respectively

is of great interest to propose a feasible SAGD analysis alternative that is capable of utilizing these field data for production analysis and heterogeneities characterization. Data-driven modeling techniques, which involve data analytics and implementation of artificial intelligence (AI) methods for

Spring 2019

Gallardo Vizcaino, Enrique

. This requires transferring the geological uncertainty to probability distributions of a response variable suitable for decision-making and use of a decision criterion that considers the reservoir manager’s preferences toward the project’s return-risk trade-off. This is challenging in petroleum

transfer concepts and ideas from discrete simulation. It works on homogeneous and heterogeneous reservoirs and is computationally efficient enough to be applied over multiple geostatistical realizations. A case study performed with a realistic multi-realization geological model validates the predictive

making under geological uncertainty. MVC-SDR does not rely on a specific utility function and leads to decisions that are considered rational to risk-averse reservoir managers. The shortcoming is a reduced ability to rank projects with very similar value. Two examples illustrate the use of MVC-SDR, the