Other Engineering Science and Materials Commons^™

Degumming Of Hemp Fibers Using Combined Microwave Energy And Deep Eutectic Solvent, Bulbul Ahmed

LSU Master's Theses

Hemp is considered as one of the sustainable agricultural fiber materials. Degumming or surface modification of hemp bast is needed to produce single fibers for ensuing textile and industrial applications. The traditional degumming process necessitates a high amount of alkali, which causes detrimental environmental pollution. This study offers a new method to degum hemp fibers with reduced use of harmful alkali and precious water resources. In this work, hemp bast fibers were degummed by using combined microwave energy and deep eutectic solvent (DES). The properties of hemp fibers manufactured by this method were investigated and compared with the traditional alkali …

Development Of Reduced Order Models Using Reservoir Simulation And Physics Informed Machine Learning Techniques, Mark V. Behl Jr

LSU Master's Theses

Reservoir simulation is the industry standard for prediction and characterization of processes in the subsurface. However, simulation is computationally expensive and time consuming. This study explores reduced order models (ROMs) as an appropriate alternative. ROMs that use neural networks effectively capture nonlinear dependencies, and only require available operational data as inputs. Neural networks are a black box and difficult to interpret, however. Physics informed neural networks (PINNs) provide a potential solution to these shortcomings, but have not yet been applied extensively in petroleum engineering.

A mature black-oil simulation model from Volve public data release was used to generate training data …

A Modelling Study For Smart Pigging Technique For Pipeline Leak Detection, Caitlyn Judith Thiberville

LSU Master's Theses

Although leak incidents continue, a pipeline remains the most reliable mode of transportation within the oil and gas industry. It becomes even more important today because the projection for new pipelines is expected to increase by 1 billion BOE through 2035. In addition, increasing number and length of subsea tiebacks face new challenges in term of data acquisition, monitoring, analysis, and remedial actions. Passive leak-detection methods commonly used in the industry have been successful with some limitations in that they often cannot detect small leaks and seeps. In addition to a thorough review of related topics, this study investigates how …

Artificial Intelligence Based Wrist Fracture Classification, Dineep Thomas

LSU Master's Theses

The problem of predicting wrist fractures from X-rays using Artificial Intelligence (AI) methods is addressed. Wrist fractures are the most commonly misdiagnosed fractures because of the complex anatomical structure of the wrist bone which includes several different bones. This research provides a predictive solution to automate the process of wrist fracture classifications and outlines a visualization technique to identify the probable location of the fractured region on the X-rays. This thesis describes a deep learning based approach for wrist fracture classification. Deep convolutional neural network (CNN) based models have been used for wrist fracture classification by combining different optimization techniques. …