Session: K10-02: Heat transfer equipment

Paper Number: 183903

183903 - An Enhanced Predictive Model for a Prototype Atmospheric Water Generator 

Abstract: 

The paper builds upon previous research with a prototype atmospheric water generator (AWG) to improve the accuracy of a predictive analytical model built in the Engineering Equation Solver (EES) software that estimates rates of atmospheric water collection by the device. The predictions, based on data inputs of inlet air temperature, relative humidity, and circulating water temperature, were assessed for accuracy through a percent error analysis comparing the predicted amount to the actual amount of water collected at the test site. Previous testing of the prototype AWG investigated utilizing geothermal energy for cooling water circulating through the heat exchanger as air passed through the device condensing vapor into water. The objective of the new phase of testing is to continue collecting data from the prototype and to improve the accuracy of the estimates produced in the predictive analytical model in EES. The previous research of predicting the atmospheric water outputs in international locations was continued in this phase of testing utilizing the same cities. Due to the previous testing location being outdoors, the research and subsequent results were subject to variability from climate conditions impacting the results. This new phase of research took place indoors to control the testing environment for the prototype AWG system to attempt collecting data for a better understanding of the full capabilities of the device. The geothermal energy aspect from the previous phase was not reproduced. To simulate a humid environment, modifications were made to the device at the new testing location in Harrisonburg, Virginia, where more extensive experimentation was performed. These modifications include incorporating a gas mixing chamber to the front of the device attached to the fan inlet where hoses for steam generators were also installed to produce vapor. Additionally, slight adjustments were made to the analytical simulation model including fixing unit errors, implementing a more specific atmospheric pressure value, and fixing other minor coding errors. The refined predictive model was recalibrated with collected data from the recent experiment trials. At the testing location in Virginia, the AWG’s fan operated at an average of 135 cubic feet per minute (cfm) and the average water volumetric flow rate circulating through the heat exchanger was 4.48 gallons per minute (gpm). The initial results recorded from the experimentation trials were an average water collection rate of 1.35 liters/hour at an average inlet air temperature of  51.2 ℃, relative humidity of 37.1 %, and circulating water temperature of 17.7 ℃. The international locations tested were the same as those tested in the previous phase and include the cities of  Houston, Texas, United States; Cape Town, South Africa; Basrah, Iraq; Puntarenas, Costa Rica; and Valletta, Malta. The international results tested in the new adjusted predictive analytical model estimates peak atmospheric water collection rates for the cities include 0.75 liters/hour, 0.00006 liters/hour, 2.35 liters/hour, 1.21 liters/hour, and 0.53 liters/hour, respectively.

Presenting Author: Karim Altaii James Madison University

Presenting Author Biography: Dr. Altaii holds a Ph.D. in mechanical engineering, and received his doctorate from The City University
of New York. He is a professor in the College of Integrated Science and Engineering (CISE) at
James Madison University. He is a registered Professional Engineer and holds five patents in solar energy
applications and irrigation system. He is the director of CISE Energy and Environmental Projects- an
international summer program in Costa Rica.
His primary interests are in renewable energy applications, fluid-thermal sciences, and international
education.

Authors:

Karim Altaii James Madison University
Jackson Lambert James Madison University
Lorelai Lamoureux James Madsion University
Leonard Manwarren James Madison University
Jacob Miller James Madison University
Zach Morse James Madison University
Justin Tagert James Madison University