The corrosion behavior of mild sleet in saturated aerated and de-aerated Ca(OH)2 solution was investigated using electrochemical measurements. The work was carried out with small coupons immersed in solutions containing different quantities of NaCl in presence of various NaN02 concentrations as corrosion inhibitors. It has been found thal:(1 ) In presence of NaCl, the time required to reach O2 evolution potential in de-aerated Ca(OH)2 polarized at 10μA/cm 2 is function of inhibitor concentration and it becomes lass as NaN02 increases compared with zero presence indicating the effectiveness of NaN02 as anodic corrosion inhibitor. (2) In absence of NaCl, the Lime required to reach O2 evolution potential in de-aerated solutions is less that in aerated solutions when inhibitor increases from 0 to 0.3 wt. %. (3) In presence of sufficient chloride in de-aerated Ca(OH)i solution, the passive film may broken down locally.
Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform wit
... Show More
