Date of Award

3-2025

Document Type

Thesis

Degree Name

Master of Science in Engineering Management

Department

Department of Systems Engineering and Management

First Advisor

Willie F. Harper, Jr., PhD

Abstract

This research investigated the performance of a Tsunami T50 Vapor Compression Cycle styled Atmospheric Water Generation (AWG) machine operated under ambient conditions in Dayton, Ohio. Water yield from the device was measured volumetrically and these values are paired with respective weather data, collected from a local monitoring station, to build an Artificial Neural Network in MATLAB and JMP software. Water yield varied over the course of this study but averaged 1.2L and maxed at 5L for 4-hour operating periods. This work is part of a 3-year project; future data is needed to enhance both training and validation of the model presented in this thesis. Weather data was used to with the preliminary model to forecast water yield predictions. To this author’s knowledge, this study is the first to #1) collect AWG water yield data in a "humid continental" climate in the continental US with distinct seasons and variable weather patterns and to #2) report assembly of ANNs for the purpose of predicting water yield for a vapor compression-based AWG.

AFIT Designator

AFIT-ENV-MS-25-M-081

Comments

An embargo was observed for posting this thesis on AFIT Scholar.

This work is marked as Distribution A - Approved for public release. Distribution Unlimited. PA clearance case number on file.

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