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OPG, Microsoft to work toward net-zero future for Ontario
Ontario Power Generation and Microsoft Canada have formed a partnership aimed at combatting climate change and driving sustainable growth across the province of Ontario, the Canadian utility announced this week.
Under the partnership, Microsoft will procure clean energy credits (CECs) sourced from OPG’s nuclear and hydro assets in Ontario on an hourly basis. (OPG’s nuclear assets include the four-unit Darlington plant and six-unit Pickering facility.) According to the announcement, this will enable Microsoft to advance toward its 100/100/0 by 2030 goal, which commits the software firm to powering its data centers globally with zero-carbon energy, 24/7.
Liangxing Li, Shengjie Gong, Weimin Ma
Nuclear Technology | Volume 177 | Number 1 | January 2012 | Pages 107-118
Technical Paper | Thermal Hydraulics | dx.doi.org/10.13182/NT12-A13331
Articles are hosted by Taylor and Francis Online.
This paper documents an experimental study on two-phase flow regimes and frictional pressure drop characteristics in a particulate (porous) bed packed with multidiameter (1.5-, 3-, and 6-mm) glass spheres. The experimental results provide new data to validate/develop hydrodynamic models for coolability analysis of debris beds formed in fuel-coolant interactions during a postulated severe accident. The POMECO-FL test facility is employed to perform the experiment, with the spheres packed in a test section of 90 mm diameter and 635 mm height. The pressure drops are measured for air/water two-phase flow through the packed bed, and flow patterns are obtained by means of visual observations. Meanwhile, local void fraction in the center of the bed is measured by a microconductive probe.The experimental results show that the frictional pressure drop of single-phase flow through the bed can be predicted by the Ergun equation, if the area mean diameter of the particles is chosen in the calculation. Given the so-determined effective particle diameter, the estimation of the Reed model for two-phase flow pressure gradient in the bed has a good agreement with the experimental data. The characteristics of the local void fraction can be used to predict flow pattern and mean void fraction. It is observed that slug flow prevails when the mean void fraction is <0.5, whereas annular flow dominates after the mean void fraction is >0.7. If the effective particle diameter is further used as an influential parameter in flow pattern identification, the observed flow regimes of two-phase flow in porous media are well predicted by the existing flow pattern map.