Technology for a sustainable Canadian metals extraction industry

在金属和材料加工领域，技术成本、物理和数学建模科学与生命周期分析科学之间缺乏定量联系。如今，人们越来越重视气候变化的驱动因素，特别是能源消耗和伴随而来的温室气体排放。金属资源行业是最大的能源消耗者之一，历史上主要由经济驱动，因此需要在流程绩效和可持续性指标之间建立量化联系。换言之，金属和材料加工行业需要密切审查和扩展对其工业生态的分析。通过发展这里提出的数学关系(链接)，可以基于技术-成本、物理和数学模型来开发预测性可持续性影响模型。由此产生的可持续性模型不仅可以从经济角度，而且从环境和社会影响角度来优化现有技术。这些可持续性模型还可以通过确定否则会被企业忽视的可能性来帮助确定新的材料加工机会。为了发展这些定量联系，有必要利用应用数学的工具，特别是离散事件动力学和矩阵因式分解的方法，再加上社会学和经济学模型。将需要实验室实验研究来获取数据，以完善关系，并测试和验证由此产生的模型。这种交叉同源方法将从申请者目前在有色金属火法冶金方面的专业开始，然后扩展到先进材料加工等新的应用。在毕业和就业后，学习这一领域的学生将能够为他们的雇主规划未来的最佳路线，从而为改善加拿大的经济、环境和社会可持续性做出贡献。

There exists poor quantitative linkage between the science of technical-cost, physical and mathematical modeling and of life-cycle-analysis in the field of metals and materials processing. Nowadays, there is increasing emphasis on the drivers of climate change, notably energy consumption and concomitant greenhouse gas emissions. The metals resource industry, one of the largest consumers of energy and historically primarily driven by economics alone, needs to develop quantitative linkages between process performance and sustainability metrics.  In other words, the metals and materials processing industries need to closely examine and extend the analysis of their industrial ecology. By developing the mathematical relationships (linkages) that are proposed here, predictive sustainability impact models can be developed based on technical-cost, physical and mathematical models.  The resulting sustainability models may then be used to optimize existing technology not only from an economic point of view, but also from an environmental and social impact point of view.  Such sustainability models may also assist in identifying new materials processing opportunities by identifying possibilities that would be otherwise overlooked by business. To develop these quantitative linkages, it is necessary to exploit the tools of applied mathematics, in particular, the methods of discrete event dynamics and matrix factorization, coupled with sociological and economic models.  The resulting computational methodologies are intended to be applied to metals and materials processing operations and technologies. Laboratory experimental studies will be required to acquire data to refine the relationships and to test and validate the resulting models.  This cross-cognate approach will start from the applicant's current specialization in non-ferrous pyrometallurgy and then extend to novel applications such as advanced materials processing. Upon graduation and employment, students studying in this area will be able to contribute to improving Canada's economic, environmental and social sustainability by being able to chart optimum courses forward for their employers.