Urban populations and mega-cities are on the rise and so is the amount of wastewater pouring into treatment facilities that cannot adequately handle the load.<\/p>\n
What if you had a tool that could tell whether a large wastewater treatment plant was capable of reliably meeting the demand?<\/p>\n
\u201cIt could avert a public health disaster caused by harmful water quality,\u201d said 51ÁÔÆæ electrical engineer Lingfeng Wang, who has devised such a software tool.<\/p>\n
\u201cFor most public systems, there is no quantitative way to know whether operations are working until the output is insufficient,\u201d said Wang, an associate professor of electrical engineering.<\/p>\n
Instead of real-time monitoring of the equipment conditions, Wang\u2019s software is based on the historical data on equipment reliability to decide if the existing plant facilities are able to meet the safety requirement on wastewater treatment.<\/p>\n
His tool is unique because it rates the reliability of a treatment plant holistically, incorporating a swath of dynamic uncertainties including mechanical malfunctions, software and sensor failure, or an interrupted electric power supply.<\/p>\n
It defines water-quality risk metrics and offers a long-term profile of the water released after treatment, assessing individual pollutants separately. Three main conditions are considered for each pollutant: the treatment process failure, the facility monitoring system failure and the effluent quality sensor failure.<\/p>\n
The software can even determine a plant\u2019s resilience in the face of adverse events such as a cyberattack.<\/p>\n
\u201cThe tool is very timely for deciding how to invest on our crumbling wastewater infrastructure,\u201d Wangsaid, \u201cwhich receives the grade of D+ in the most recent report card by the American Society of Civil Engineers.\u201d<\/p>\n
The software was developed with support from the Industry\/University Collaborative Research Center on Water Equipment & Policy. Established by the National Science Foundation, the center brings industry together with researchers at UW-Milwaukee and Marquette University.<\/p>\n","protected":false},"excerpt":{"rendered":"
Urban populations and mega-cities are on the rise and so is the amount of wastewater pouring into treatment facilities that cannot adequately handle the load. What if you had a tool that could tell whether a large wastewater treatment plant was capable of reliably meeting the demand? \u201cIt could avert a public health disaster caused […]<\/p>\n","protected":false},"author":836,"featured_media":59577,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","uwm_wg_additional_authors":[]},"categories":[174,200,175],"tags":[],"section":[],"display_categories":[],"related-coverage":[],"uwmnews-feed":[149],"class_list":["post-59576","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","category-news-in-brief","category-research","uwmnews-feed-engineering-applied-science"],"yoast_head":"\n