Date of Award

Fall 2021

Document Type

Open Access Thesis

Department

Mechanical Engineering

First Advisor

Abdel-Moez E. Bayoumi

Abstract

Fresh water shortage threatens the development and prosperity of many countries including several areas in the United States. Sea and ground water reverse osmosis desalination is rapidly becoming a dominant technology for overcoming water shortage threats by providing cost-effective freshwater production. Digital transformation can be used to help facilitate and advance water treatment technologies by reducing costs and minimizing downtime. Digital transformation is a process that encapsulates digital tools and technologies such as cloud computing, machine learning, artificial intelligence, the internet of things, and virtual/augmented reality. It is a process where objects in the physical world are given virtual replicas established via collected real-time data that is exchanged from sensors attached to the physical system to create a virtual digital twin. These virtual replicates represent the same behaviors that govern the physical object throughout its life development and operation.

Utilizing digital transformation technology in the water desalination industry is essential for multiple benefits such as optimization, control, fault detection, health monitoring, reducing capital and operation costs by reducing maintenance operations and downtime, and improving the design and manufacturing process.

This thesis develops a proof of concept for utilizing digital transformation in water desalination by building digital twins for two components within a water desalination system. A three-piston high-pressure pump energy recovery device (HPP - ERD) along with a three-stage reverse osmosis digital membrane model have been built and integrated into a digital twin that can be used to evaluate the system's behaviors under normal and abnormal conditions, predict future failures, and improve the overall system design. The developed digital twin was validated with real-time data collected from a physical water desalination system. This digital transformation proof of concept, including all algorithms, models, and techniques developed in this thesis, can be expanded to the remaining components and subsystems of a water desalination plant for further optimization.

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