Improving the Purity of Multicrystalline Silicon by Using Directional Solidification Method

Large temperature gradient was introduced to improve the removal rate of metal impurity in silicon ingot during direction solidification. The concentration of metal impurities in the silicon ingot with a large temperature gradient is 0.96 ppmw. The solidification time is reduced by 20% due to the fast speed of crystal growth improved; meanwhile the purity is increased by 64%.

Numerical Simulation of Temperature Distribution in a Containment Vessel of an Operating PWR Plant

The structural integrity of the containment vessel (CV) for a pressurized water reactor (PWR) plant under a loss-of-coolant accident is evaluated by a safety analysis code that uses the average temperature of gas phase in the CV during reactor operation as an initial condition. Since the estimation of the average temperature by measurement is difficult, this paper addressed the numerical simulation for the temperature distribution in the CV of an operating PWR plant. The simulation considered heat generation of the equipment, the ventilation and air conditioning systems (VAC), heat transfer to the structure, and heat release to the CV exterior based on the design values of the PWR plant. The temperature increased with a rise in height within the CV and the flow field transformed from forced convection to natural convection. Compared with the measured temperature data in the actual PWR plant, predicted temperatures in the lower regions agreed well with the measured values. The temperature differences became larger above the fourth floor, and the temperature inside the steam generator (SG) loop chamber on the fourth floor was most strongly underestimated, −16.2 K due to the large temperature gradient around the heat release equipment. Nevertheless, the predicted temperature distribution represented a qualitative tendency, low at the bottom of the CV and increases with a rise in height within the CV. The total volume-averaged temperature was nearly equal to the average gas phase temperature. To improve the predictive performance, parameter studies regarding heat from the equipment and the reconsideration of the numerical model that can be applicable to large temperature gradient around the equipment are needed.