Computer simulations of molten salts interactions with metallic materials

熔盐与金属材料相互作用的计算机模拟

• 批准号: 573450-2022
• 负责人: Béland, LaurentKarimLK
• 金额: $ 3.92万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=759785
• 关键词: Computer; simulations; molten; salts; interactions

Small modular reactors have been identified by the Canadian government as a "source of safe, clean, affordable energy [...] for Canada and Canadians." Several of these reactor concepts rely on molten salt heat exchange loops, rather than traditional water-based heat exchangers. A key issue is that molten-salt driven corrosion is much less understood. This is of prime importance for the three main industry partners-the Canadian Nuclear Laboratories, Ontario Power Generation, and Global First Power-which are involved in the design, planning and construction of Canada's small modular reactors. In order to bridge this knowledge gap, we will perform atom-by-atom computer simulations to understand and predict how molten salts interact with metallic structural materials. A challenging aspect of this research is that interatomic interactions are intrinsically quantum in nature. Simulation methods based on quantum mechanics are accurate, but tend to have a prohibitive computational cost. Here, we will use state-of-the-art machine learning algorithms to construct interatomic interaction models with a level of accuracy comparable to that of quantum-mechanics-based methods, but at a tractable computational cost. The research project will involve four industrial internships on the site of the industry partners, helping train the next generation of Canadian nuclear industry scientists.

小型模块化反应堆已被加拿大政府认定为“为加拿大和加拿大人提供安全、清洁、负担得起的能源[...]”。其中一些反应堆概念依赖于熔盐热交换回路，而不是传统的水基热交换器。一个关键问题是，人们对熔盐驱动的腐蚀知之甚少。这对于参与加拿大小型模块化反应堆设计、规划和建设的三个主要行业合作伙伴——加拿大核实验室、安大略发电公司和全球第一电力公司来说至关重要。为了弥补这一知识差距，我们将进行逐个原子的计算机模拟，以了解和预测熔盐如何与金属结构材料相互作用。这项研究的一个具有挑战性的方面是原子间相互作用本质上是量子的。基于量子力学的模拟方法很准确，但计算成本往往过高。在这里，我们将使用最先进的机器学习算法来构建原子间相互作用模型，其精度水平可与基于量子力学的方法相媲美，但计算成本易于处理。该研究项目将涉及在行业合作伙伴现场进行四次工业实习，帮助培训下一代加拿大核工业科学家。