Measuring and Modeling Corrosion in Hydrometallurgical Process Systems

金属腐蚀是一个非常常见且代价高昂的问题，也是化学加工工业（CPI）中导致工厂停工的最常见原因。对于大多数人来说，腐蚀是一种难看的麻烦，但对于CPI来说，它会导致设备故障、泄漏和污染，这些都会导致严重的健康和环境问题。当了解其发生的原因并采取适当的措施时，可以防止大部分这种腐蚀损害。

Corrosion of metals is a very common and costly problem and it is the most frequent cause of plant downtime in the Chemical Processing Industries (CPI). For most people corrosion is an unsightly nuisance but for CPI it causes equipment failure, leaks and contamination, and these can cause significant heath and environmental issues. A great deal of this corrosion damage can be prevented when the reasons its occurrence are understood and appropriate measures are undertaken. Part of CPI is focused on mineral processing, of which Canada is a global leader. Canada has world-class reserves of minerals such as uranium and potash and its economy relies, to a great extent, on the extraction and processing of these materials. Canada is the second largest producer of uranium in the world and the world’s largest mine is located in Saskatchewan. This research project is focused on improving the understanding of and developing mitigation technology for corrosion problems in uranium ore processing systems. The initial stages of processing uranium into usable material involve extraction by using roasting and acid leaching technology. Acids are naturally corrosive and equipment is protected from them by using rubber-like barriers. However, sometimes these barriers becomes damaged leaving the equipment unprotected. This research is focused on determining the mechanisms by which the acidic solutions, used in the leaching process, attack the metal. It will involve carefully performing experiments that mimic the breakdown of the materials as well as creating mathematical models that describe the process. This will allow engineers and scientists to create better ways of protecting the equipment. This five-year project will elucidate the mechanism by which the metal is attacked, determine the rate of corrosion attack and develop predictive models that can be used in “what if” situations during the design of new and retrofit of existing equipment.