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When a nuclear plant closes
Theresa Knickerbocker, the mayor of the village of Buchanan, N.Y., where the Indian Point nuclear power plant is located, is not happy. What has gotten Ms. Knickerbocker’s ire up is the fact that Indian Point’s Unit 2 was closed on April 30, and Unit 3 is scheduled to close in 2021. The village, population 2,300, is about 1.3 square miles total, with the Indian Point site comprising 240 acres along the Hudson River, 30 miles upstream of Manhattan. Unit 2 was a 1,028-MWe pressurized water reactor; Unit 3 is a 1,041-MWe PWR.
The nuclear plant provides the revenue for half of Buchanan’s annual $6-million budget, Knickerbocker told Nuclear News. That’s $3 million in tax revenues each year that eventually will go away. How will that revenue be replaced? Where will the replacement power come from?
Dan G. Cacuci, Ruixian Fang
Nuclear Technology | Volume 198 | Number 2 | May 2017 | Pages 85-131
Technical Paper | dx.doi.org/10.1080/00295450.2017.1294429
Articles are hosted by Taylor and Francis Online.
For counter-flow mechanical draft cooling towers, the air in the fill can reach the point of saturation before leaving the fill section. The heat and mass transfer to the saturated air by evaporative cooling inside the fill are modeled with some assumptions and with over 50 parameters for boundary conditions, cooling tower geometries, heat and mass transfer correlations, water and air thermal properties, etc. Because of the parameter uncertainties and modeling assumptions, the accuracy and reliability of the cooling tower model need to be evaluated by quantifying the uncertainties associated with the model output. First, sensitivities of the model output with respect to all the model parameters need to be analyzed. Based on the cooling tower model, this work developed adjoint sensitivity models for the saturated case to compute efficiently and exactly the sensitivities of the model responses to all model parameters by applying the general adjoint sensitivity analysis methodology for nonlinear systems. The solution of the adjoint sensitivity models are independently verified. With the sensitivities known, the model parameters can be ranked in their importance for contributing to response uncertainties. The propagation of the uncertainties in the model parameters to the uncertainties in the model outputs can be evaluated. By further applying the predictive modeling for coupled multiphysics systems methodology, the cooling tower model for the saturated case can be improved by reducing the model prediction uncertainties through assimilation of experimental measurements and calibration of model parameters.