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Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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From operator to entrepreneur: David Garcia applies outage management lessons
David Garcia
If ComEd’s Zion plant in northern Illinois hadn’t closed in 1998, David Garcia might still be there, where he got his start in nuclear power as an operator at age 24.
But in his ninth year working there, Zion closed, and Garcia moved on to a series of new roles—including at Wisconsin’s Point Beach plant, the corporate offices of Minnesota’s Xcel Energy, and on the supplier side at PaR Nuclear—into an on-the-job education that he augmented with degrees in business and divinity that he sought later in life.
Garcia started his own company—Waymaker Resource Group—in 2014. Recently, Waymaker has been supporting Holtec’s restart project at the Palisades plant with staffing and analysis. Palisades sits almost exactly due east of the fully decommissioned Zion site on the other side of Lake Michigan and is poised to operate again after what amounts to an extended outage of more than three years. Holtec also plans to build more reactors at the same site.
For Garcia, the takeaway is clear: “This industry is not going away. Nuclear power and the adjacent industries that support nuclear power—and clean energy, period—are going to be needed for decades upon decades.”
In July, Garcia talked with Nuclear News staff writer Susan Gallier about his career and what he has learned about running successful outages and other projects.
Jacob A. Farber, Daniel G. Cole, Ahmad Y. Al Rashdan, Vaibhav Yadav
Nuclear Technology | Volume 205 | Number 8 | August 2019 | Pages 1043-1052
Technical Paper – Special section on Big Data for Nuclear Power Plants | doi.org/10.1080/00295450.2018.1534484
Articles are hosted by Taylor and Francis Online.
This paper presents data-driven methods to detect loss-of-coolant accidents (LOCAs) in the primary side of a pressurized water reactor. Process data for a variety of accident scenarios have been generated and collected using a generic pressurized water reactor simulator. The data have been used to train kernel density functions, which estimate nonparametric probability density functions based on training data. These density functions have then been used with Bayesian hypothesis testing and maximum likelihood estimation to detect the onset of the LOCAs and to identify where in the primary side the leaks have occurred. The methods have been able to detect the LOCAs for all scenarios tested with an average detection delay of one-seventh the time for the reactor to trip. Furthermore, the methods have been able to correctly identify the leak locations for 92.3% of the scenarios tested, with higher success rates for larger leaks.