The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jan. 17, 2017
Filed:
Aug. 29, 2012
Ernest R Blatchley, Iii, West Lafayette, IN (US);
Eric Gentil Mbonimpa, Las Vegas, NV (US);
Bruce Applegate, West Lafayette, IN (US);
Bryan Vadheim, Miles City, MT (US);
Ernest R Blatchley, III, West Lafayette, IN (US);
Eric Gentil Mbonimpa, Las Vegas, NV (US);
Bruce Applegate, West Lafayette, IN (US);
Bryan Vadheim, Miles City, MT (US);
Purdue Research Foundation, West Lafayette, IN (US);
Abstract
Potable drinking water is a scarce resource in many parts of developing countries, especially rural areas. Due to limited financial means of these countries, low cost point-of-use systems are thought to be appropriate technology to treat water. Systems using solar ultraviolet (UV) radiation could be successful since many vulnerable countries are located where solar radiation is intense and abundant throughout the year. The goal of this disclosure is to develop a simple and low cost point-of-use solar UV reactor to disinfect water. In this disclosure wavelength-dependent microbial dose-response behavior was investigated using surrogates to pathogenic microbes. A solar radiation prediction method based on the SMARTS model was used to predict solar UV intensity as function of geographic location and time. A numerical modeling procedure using the discrete ordinate (DO) model and CFD software (FLUENT) was used to simulate UV dose (distribution) delivery to microorganisms. Then, the dose distribution was combined with the dose response behavior using a segregated flow model to predict microbial inactivation by the reactor. A prototype was produced and tested to validate the numerical modeling procedure. The inactivation results from the prototype were in agreement with numerical inactivation prediction. The modeling procedure permits parameters such as reactor dimensions and material properties to be varied to meet a treatment goal.