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North American construction is back—smaller and faster—at OPG’s Darlington
“The nuclear renaissance is real here,” said Ontario Power Generation’s Subo Sinnathamby on May 8, one year to the day after OPG secured a final investment decision to build the first of four planned BWRX-300 reactors at its Darlington nuclear power plant, and shortly after the new reactor’s foundation was lifted into place. “We got our license to construct in April and our [final investment decision] in May, and we’ve been off to the races since.”
Sin Kim, Goon-Cherl Park
Nuclear Technology | Volume 117 | Number 3 | March 1997 | Pages 340-352
Technical Paper | Heat Transfer and Fluid Flow | doi.org/10.13182/NT97-A35348
Articles are hosted by Taylor and Francis Online.
The anisotropic turbulent diffusion and the turbulent mixing phenomena in rod bundle flow fields are studied. The former is a distinguishing feature of the flow through rod bundles, and the latter is essential to the subchannel thermal-hydraulic analysis. On the basis of the flow pulsation, which is suggested as a main process of turbulent mixing, scale relations for principal parameters such as the anisotropic factor and mixing rate are derived. To obtain a scale relation for the anisotropic factor, eddy viscosities are classified into isotropic and flow pulsation parts. Scales of each part are estimated using the scale analysis method. For the purpose of determining the length and velocity scales of the pul sating flow, a hypothetical circulating flow with a period corresponding to the frequency of the pulsation is assumed. The scale relation is compared with the experimental data and shows good agreement both with respect to trend and magnitude for various geometries. Thus, it is concluded that the flow pulsation is a significant contributor to the strong anisotropy in the rod bundle flow field. Also, the mixing rate is predicted by estimating the effective mixing velocity. The estimated mixing rate is transformed into well-known dimensionless numbers, which are compared with the experimental data and with correlations to verify the predictability.