PhD Proposal by Joshua Daniel Brooks

Event Details
  • Date/Time:
    • Wednesday May 20, 2020
      2:00 pm - 4:00 pm
  • Location: Remote
  • Phone:
  • URL: BlueJeans
  • Email:
  • Fee(s):
    N/A
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Summaries

Summary Sentence: A Methodology for Selecting Multi-attribute Optimal Renewable Energy Driven Hybrid Desalination Architectures

Full Summary: No summary paragraph submitted.

Joshua Daniel Brooks

(Advisor: Prof. Mavris]

will propose a doctoral thesis entitled

 

A Methodology for Selecting Multi-attribute Optimal Renewable Energy Driven Hybrid Desalination Architectures

 

On Wednesday, May 20 at 2:00 p.m.

Blue Jeans (https://bluejeans.com/254507071)

 

Abstract

Increases in global water demand relative to variable and changing water supplies has necessitated a re-evaluation of water management strategies for handling this situation. Desalination in particular is well suited to augment water supplies while remaining relatively insensitive to the changing climate. However, desalination plants face criticism due to their cost, energy inefficiency, carbon emissions, and water inefficiency. This work aims to assist in removing these obstacles to desalination’s widespread adoption through the more expansive exploration of desalination architectures and through the quantification of their multi-attribute performance. The methodology proposed in this work, will be the first of its kind to be made publicly available amongst the literature. The method will follow the IPPD framework for the design of complex systems. Desalination architectures will first be valuated by mapping the core barriers to their adoption to quantifiable performance attributes. The exploration of both the desalination and the energy subsystem design space will be performed and an evaluation environment for considering optionally optimal desalination subsystems with optimal energy subsystems will be developed. This desalination architecture evaluation environment will be situated within an optimization structure, which will subsequently be used to construct Pareto frontier characterizations of the desalination architecture performance space. This performance space will be used as the basis of a multi-attribute decision making exercise, both completing and exemplifying the optimal desalination architecture design and selection methodology. It is expected that the proposed methodology will identify desalination architectures which were previously undiscoverable, and which quantifiably outperform previous “optima”. The rigorous consideration of desalination and energy subsystem integration on the basis of energy form, as well as exploration within an appropriately expanded breadth of the design space is expected to enable these outcomes. Trends between different desalination technologies and specific performance attributes, as well as technology specific modeling fidelities and their impacts to computational expense are expected to be brought to light. Identifying desalination architectures which are cheaper, more efficient, and better for the environment is an imperative next step in the advancement of desalination technology. This study, and others like this will be critical in positioning desalination technology as an appropriate contribution to the global water resource solution.

 

Committee

•Prof. Dimitri Mavris – School of Aerospace Engineering (advisor)

•Prof. Devesh Ranjan – School of Mechanical Engineering

•Dr. Scott Duncan – School of Aerospace Engineering

•Dr. Richard Simmons – Strategic Energy Institute

Additional Information

In Campus Calendar
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Groups

Graduate Studies

Invited Audience
Faculty/Staff, Public, Graduate students, Undergraduate students
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Other/Miscellaneous
Keywords
Phd proposal
Status
  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: May 7, 2020 - 11:38am
  • Last Updated: May 7, 2020 - 11:38am