Metal ALM Process Parameter Optimisation - MALM-PPO
Metal ALM Process Parameter Optimisation - MALM-PPO
批准号:
10039714
负责人:
金额:
$2.29万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2022
资助国家:
英国
项目状态:
已结题
起止时间:
2022 至 --
中文摘要
金属增材制造是在分层过程中构建零件的过程,而不是从初始的均匀块状材料加工它们。通过选择性地调整机器参数,可以在单个部件中包含多种材料特性,从而实现比以前更广泛的优化设计。有一个不断扩大的增材工艺和材料的范围,使全新的执行部件更轻,具有新颖的功能。Additive Flow是领先的多属性优化软件提供商,能够生成具有多属性和多工艺参数的新制造方式。这是英国和国际工程领域的一个新的增长领域。为了释放这种多属性优化的潜力,需要为具有多种材料属性的组件测试和收集数据的新方法。在与国家物理实验室的合作下,将创建一系列多属性组件,然后对其进行测试,并将数据反馈到现有的软件中,从而提高工程性能并节省制造成本。其他好处包括在多尺度和多学科的工程设计空间中降低用户的复杂性,增加可访问性和采用新技术。Additive Flow的优化软件决定了制造速度和成本与最终部件的功能和性能之间的权衡。这可以让更多的新零件更快、更经济地生产出来,从而更好地利用增材制造的优势。然而,许多设计结果导致材料不均匀,缺乏准确的材料性能数据。由于需要足够谨慎以避免零件故障,因此缺乏数据导致了次优优化,随后的认证也很昂贵。该项目将采用测量和评估非均质结构的物理动态材料特性的方法,并使用这些数据来验证数字模拟预测的加工参数。由于表面粗糙度是疲劳的主要影响因素,因此将探索不同的参数,以有目的地显示目标不同的疲劳值,使增材制造在控制疲劳方面迈出重要一步。这有利于英国工业的发展,该解决方案将极大地改善设计优化过程,并具有积极的经济,社会和环境影响,因为材料浪费最小化,避免了过程故障。
英文摘要
Metal additive manufacturing is the process of building up parts in a layerwise process, rather than machining them from initial homogeneous bulk material. By selectively adjusting the machine parameters it is possible to include multiple material properties within a single part, enabling a wider range of more optimised designs than has previously been possible. There is an ever-expanding range of Additive processes and materials, enabling totally new performing parts that are lighter and have novel functions.Additive Flow is the leading software provider for multi-property optimisation and has the capability of generating new ways of manufacturing with multi-properties, and multiple process parameters. This is a fresh new area for growth within engineering in the UK and internationally. In order to unlock the potential of this multi-property optimisation, new ways of testing and gathering data for components that have multiple material properties are needed.In collaboration with the National Physical Laboratory a series of multi-property components will be created which will then be tested and the data will be fed back into the existing software that will improve engineering performance and cost savings for manufacturing. Additional benefits include reducing complexity for users within a multi-scale and multi-disciplinary engineering design space increasing accessibility and adoption of new technologies.Additive Flow's optimisation software determines trade-offs between manufacturing speed and cost against the function and performance of the final part. This can allow more novel parts to be produced quicker and more cost-effectively, enabling greater exploitation of the benefits of AM. However, many of the resulting designs result in inhomogeneous material for which accurate material property data is lacking. The lack of data has resulted in sub-optimal optimisation due to the need to be sufficiently cautious to avoid part failure and subsequently the certification is also expensive.This project will take approaches to measure and evaluate the physical dynamic material properties of heterogeneous structures and use this data to validate processing parameters predicted by the digital simulation. Since surface roughness is a major influencing factor for fatigue, different parameters will be explored to purposely exhibit target varying fatigue values enabling AM to take a major step towards controlling fatigue.This has benefits to the development of the UK industry, where the solution would greatly improve design optimisation processes and have positive economic, social, and environmental implications because material wastage is minimised and process failure is avoided.
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专著(0)
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会议论文
国内基金
海外基金
水稻叶片极性建成控制基因(ALM)的克隆和调控机理研究
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批准号:30770127
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项目类别:面上项目
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资助金额:35.0万元
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批准年份:2007
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负责人:张光恒
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依托单位: