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Conference Spotlight
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.
Yang Liu, Nam Dinh, Xiaodong Sun, Rui Hu
Nuclear Technology | Volume 209 | Number 12 | December 2023 | Pages 2002-2015
Research Article | doi.org/10.1080/00295450.2022.2162792
Articles are hosted by Taylor and Francis Online.
Multiphase Computational Fluid Dynamics (MCFD) based on the two-fluid model is considered a promising tool to model complex two-phase flow systems. MCFD simulation can predict local flow features without resolving interfacial information. As a result, the MCFD solver relies on closure relations to describe the interaction between the two phases. Those empirical or semi-mechanistic closure relations constitute a major source of uncertainty for MCFD predictions.
In this paper, we leverage a physics-informed uncertainty quantification (UQ) approach to inversely quantify the closure relations’ model form uncertainty in a physically consistent manner. This proposed approach considers the model form uncertainty terms as stochastic fields that are additive to the closure relation outputs. Combining dimensionality reduction and Gaussian processes, the posterior distribution of the stochastic fields can be effectively quantified within the Bayesian framework with the support of experimental measurements. As this UQ approach is fully integrated into the MCFD solving process, the physical constraints of the system can be naturally preserved in the UQ results. In a case study of adiabatic bubbly flow, we demonstrate that this UQ approach can quantify the model form uncertainty of the MCFD interfacial force closure relations, thus effectively improving the simulation results with relatively sparse data support.