偏滤器高热负荷材料研究

Research of High Heat Flux for Divertor Materials

用热等静压焊接的方法对两种性能差异很大的金属材料钨和铜进行了成功的焊接。用SEM对断口和焊接界面在各种不同条件下焊接的性能作了对比分析。给出了两种样品的断裂特征和焊接过程中元素的扩散特点。钨和铜合金的结合主要是物理结合 ,是在高温高压下 ,材料表面微观的凹凸不平而产生的犬齿交合结合在一起的 ,扩散结合只占很少的部分。偏滤器靶板的寿命主要决定于靶板材料的热疲劳性能。在真空室中用大功率电子束作为热源进行了热疲劳试验。电子束的功率密度选为 9MW/m2 ,循环周期为 4 0s,冷却水流量为 80mL/s。用直径为 0 .3mm的NiCr NiSi热电偶测量了下材料表面的温度分布。结果发现 ,在冷却充分的情况下 ,表面最高温度约 4 0 0℃ ,钨铜焊缝处的平均最高温度约1 5 0℃。经过 1 0 0 0次的循环加热后 ,没有发现靶板材料出现破坏现象。对试验条件下的材料表面温度分布进行了计算机模拟计算。计算结果和试验测得的结果是相吻合的 。

The HIP(hot isostatic press)technology was used to weld two kinds metal materials involving tungsten and copper which have a great difference in physic properties. The welding properties were discussed under different conditions. The fracture surface of the elements during the welding process were showed in this paper. It was found that the binding of tungsten and copper was mainly physical binding, they were linked by high temperature and high pressure because of the material surface under micro dimension. The diffusion was almost not found. The welding interface of copper and staintess steel has a good diffusion because of the incorperation of nickel. Thermal fatigue of the divertor plate is one of the key factors governing the lifetime of the divertor plate. The thermal cycling test of divertor target plate was carried out in the vacuum; a high heat flux electron gun was used as a thermal source. A cyclic heat flux of 9 MW/m 2 was loaded onto the target plate and a pulse duration of 20 s selected, with the cooling water flow rate of 80 ml/s. NiCr-NiSi thermocouples with diameter of 0.3 mm are used to test the temperature distribution of the specimen under 9 MW/m 2 power density in the vacuum. It is found that the highest temperature of the surface is 400℃. The highest temperature at the welding seam of tungsten and copper is 150℃. After 1 000 cycles, the surface and the W/Cu joint of the target plate did not show any damage during the fatigue test. The calculation data comform with the testing result. It is conducted that the testing data are reliable.