Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

2019

Chemical Engineering

Missouri University of Science and Technology

Artificial neural networks

Articles 1 - 2 of 2

Full-Text Articles in Engineering

Application Of Artificial Neural Networks In The Drilling Processes: Can Equivalent Circulation Density Be Estimated Prior To Drilling?, Husam Hasan Alkinani, Abo Taleb Al-Hameedi, Shari Dunn-Norman, David Lian Dec 2019

Application Of Artificial Neural Networks In The Drilling Processes: Can Equivalent Circulation Density Be Estimated Prior To Drilling?, Husam Hasan Alkinani, Abo Taleb Al-Hameedi, Shari Dunn-Norman, David Lian

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

As the drilling environment became more challenging nowadays, managing equivalent circulating density (ECD) is a key factor to minimize non-productive time (NPT) due to many drilling obstacles such as stuck pipe, formation fracturing, and lost circulation. The goal of this work was to predict ECD prior to drilling by using artificial neural network (ANN). Once ECD is recognized, the crucial drilling variables impact ECD can be modified to control ECD within the acceptable ranges. Data from over 2000 wells collected worldwide were used in this study to create an ANN to predict ECD prior to drilling. Into training, validation, and …


Techno-Economic Optimization And Environmental Life Cycle Assessment Of Microgrids Using Genetic Algorithm And Artificial Neural Networks, Prashant Nagapurkar Jan 2019

Techno-Economic Optimization And Environmental Life Cycle Assessment Of Microgrids Using Genetic Algorithm And Artificial Neural Networks, Prashant Nagapurkar

Doctoral Dissertations

"This dissertation focuses primarily on techno-economic optimization and environmental life cycle assessment (LCA) of sustainable energy generation technologies. This work is divided into five papers. The first paper discusses the techno-economic optimization and environmental life cycle assessment of microgrids located in the USA using genetic algorithm. In this paper, a methodology was developed that assessed the techno-economic and environmental performance of a small scale microgrid located in US cities of Tucson, Lubbock and Dickinson. Providing uninterrupted power the microgrid was composed of seven components -- solar photovoltaics, wind-turbines, lead acid batteries, biodiesel generators, fuel cells, electrolyzers and H2 tanks. …