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BREAKING NEWS: Trump issues executive orders to overhaul nuclear industry
The Trump administration issued four executive orders today aimed at boosting domestic nuclear deployment ahead of significant growth in projected energy demand in the coming decades.
During a live signing in the Oval Office, President Donald Trump called nuclear “a hot industry,” adding, “It’s a brilliant industry. [But] you’ve got to do it right. It’s become very safe and environmental.”
Uuganbayar Otgonbaatar, Emilio Baglietto, Neil Todreas
Nuclear Science and Engineering | Volume 184 | Number 3 | November 2016 | Pages 430-440
Technical Paper | doi.org/10.13182/NSE16-9
Articles are hosted by Taylor and Francis Online.
The measurement of the steam generator feedwater mass flow rate is a dominant source of uncertainty in the nominal thermal power calculation of a plant. In this paper, mass flow rate measurement by means of an orifice plate is considered. Reynolds-averaged Navier-Stokes (RANS) simulation was performed using the computational fluid dynamics code STAR-CCM+ to quantify the representativeness uncertainty of mass flow rate measured in a dedicated experimental configuration. The representativeness uncertainty arises from applying the tolerance values prescribed by the International Organization for Standardization (ISO) standard in non-straight piping geometries. The simulation results were compared with the test results and the uncertainty bounds prescribed by the ISO standard, demonstrating the feasibility of applying RANS in an industrial setting for sub-1% uncertainty applications. The RANS results were also used to identify the variability in the measurement result with respect to the angular location of the pressure tap used in the flow rate measurement. Second, a large eddy simulation (LES) was performed on a straight piping configuration to simulate unsteady coherent flow shedding at the orifice plate. The spectral results of LES were compared with data from a test. The time-averaged LES results are within 0.1% of the value prescribed by the ISO standard. Direct comparison of the temporal spectrum of the LES result to the test data is not possible due to the measurement technique. This work is a part of a wider effort to develop a methodology to characterize, assess, and quantify representativeness uncertainty in performance indicator measurements of plants. Spatial, temporal, and modeling representativeness uncertainties are presented in this current work.