Next generation turbomachinery with two-phase flow (Training42Phase)

能源系统的绿色转型需要一系列基于两相流涡轮机械的新型能源转换技术的实施。然而，目前人们对涡轮机械中两相流的认识和理解水平还很低，迫切需要对科学家进行教育，以支持这类技术的发展。Training42Phase的目标是培养未来两相流涡轮机械领域的顶尖科学家，从而为下一代涡轮机械的发展提供所需的科学和技术基础。项目联盟包括解决这些具有挑战性的任务所需的所有关键合作伙伴，并为我们的10名博士候选人团队提供解决这些挑战的最佳基础-欧洲领先的大学，大型国际公司和中小企业的工业合作伙伴，代表技术供应商和数字化解决方案提供商。Training42phase将在以下领域为10名博士候选人提供首次优秀的培训：1)创新的技术解决方案，使设计具有成本效益和可靠的两相流涡轮机械成为可能。2)与两相流涡轮机械的建模、设计、优化和性能预测相关的所有领域的前沿多学科培训，包括气动热建模和设计、应力和疲劳分析、结构动力学、混合/数据驱动的失效机制模型、先进的优化方法和基于机器学习的数据驱动分析技术。3)两相流涡轮机械在新兴新技术中的应用。4)可转移技能的顶级培训，如研究与数据管理、科学诚信与伦理、知识产权与创业、商业规划、职业规划和拨款提案写作。

The green transition of energy systems requires the implementation of a number of novel emerging energy conversion technologies based on turbomachinery with two-phase flow. However, the current level of knowledge and understanding of two-phase flow in turbomachinery is at a very low level, urgently calling for the need of education of scientists that can support the development of such technologies. The aim of Training42Phase is to educate the future leading scientists within turbomachinery with two-phase flow, thereby providing the scientific and technological basis required for the development of the next generation of turbomachinery. The project consortium includes all the key partners needed to address these challenging tasks and provide our group of 10 doctoral candidates with the best foundation for solving these challenges - leading European universities, and industrial partners from large international companies and SMEs, representing technology suppliers and providers of digitalized solutions. Training42phase will provide a first of its kind excellent training for 10 doctoral candidates within the following fields: 1) Innovative technological solutions that enable the design of cost-effective and reliable turbomachinery with two-phase flow. 2) Cutting-edge multi-disciplinary training in all fields related to the modelling, design, optimization and performance prediction of turbomachinery with two-phase flow, including aero-thermal modelling and design, stress and fatigue analysis, structural dynamics, hybrid/data-driven failure mechanism models, advanced optimization methods and data-driven analytic techniques based on machine learning. 3) Application of turbomachinery with two-phase flow to emerging novel technologies. 4) Top-level training in transferable skills, such as research and data management, scientific integrity and ethics, intellectual property rights and entrepreneurship, business planning, career planning and grant proposal writing.