Meelad Ranaiefar, P. Honarmandi, Lei Xue, Chen Zhang, A. Elwany, I. Karaman, E. Schwalbach, R. Arróyave
{"title":"A Differential Evaporation Model to Predict Chemistry Change of Additively Manufactured Metals","authors":"Meelad Ranaiefar, P. Honarmandi, Lei Xue, Chen Zhang, A. Elwany, I. Karaman, E. Schwalbach, R. Arróyave","doi":"10.2139/ssrn.3813432","DOIUrl":null,"url":null,"abstract":"The desire for increased performance and functionality has introduced additional complexities to the design and fabrication of additively manufactured (AM) parts. However, addressing these needs would require improved control over local properties during the fabrication process. In this regard, differential evaporation is an inherent characteristic in metal AM processes, directly influencing local chemistry, material properties, functionality, and performance. In the present work, a differential evaporation model (DEM) is presented for laser powder bed fusion (LPBF) AM to predict and control the effect of evaporation on chemistry and properties on local and part-wide scales. The DEM model is coupled with an analytical thermal model that is calibrated against 51.2 Ni [at.%] nickel titanium SMA single-track experiments and a multi-layer model that accounts for the AM part’s multi-layer design and the inherent melt pool overlap and chemistry propagation. The combined hierarchical model, consisting of the thermal, evaporation, and multi-layer components, is used to predict location-specific chemistry for LBPF AM fabrication of 50.8 Ni [at.%] nickel titanium shape memory alloys(NiTi SMAs). Model predictions are validated with values obtained from multi-layer experiments on a commercial LPBF system, resulting in a root mean square error (RMSE) of 0.25 Ni [at.%] for predicted Ni content. Additionally, martensitic transformation temperature, Ms, is calculated and compared with empirical data, resulting in an RMSE of 18.6 K. A practical account of the cumulative and propagative thermal-induced evaporation effect on location-specific chemistry is made through this linkage of models. Fundamentally, this model chain has also provided a solution to the forward modeling problem, enabling steps to be taken towards resolving the inverse design problem of deter-mining processing parameters based on desired location-specific properties.","PeriodicalId":18255,"journal":{"name":"MatSciRN: Process & Device Modeling (Topic)","volume":"151 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"MatSciRN: Process & Device Modeling (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3813432","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The desire for increased performance and functionality has introduced additional complexities to the design and fabrication of additively manufactured (AM) parts. However, addressing these needs would require improved control over local properties during the fabrication process. In this regard, differential evaporation is an inherent characteristic in metal AM processes, directly influencing local chemistry, material properties, functionality, and performance. In the present work, a differential evaporation model (DEM) is presented for laser powder bed fusion (LPBF) AM to predict and control the effect of evaporation on chemistry and properties on local and part-wide scales. The DEM model is coupled with an analytical thermal model that is calibrated against 51.2 Ni [at.%] nickel titanium SMA single-track experiments and a multi-layer model that accounts for the AM part’s multi-layer design and the inherent melt pool overlap and chemistry propagation. The combined hierarchical model, consisting of the thermal, evaporation, and multi-layer components, is used to predict location-specific chemistry for LBPF AM fabrication of 50.8 Ni [at.%] nickel titanium shape memory alloys(NiTi SMAs). Model predictions are validated with values obtained from multi-layer experiments on a commercial LPBF system, resulting in a root mean square error (RMSE) of 0.25 Ni [at.%] for predicted Ni content. Additionally, martensitic transformation temperature, Ms, is calculated and compared with empirical data, resulting in an RMSE of 18.6 K. A practical account of the cumulative and propagative thermal-induced evaporation effect on location-specific chemistry is made through this linkage of models. Fundamentally, this model chain has also provided a solution to the forward modeling problem, enabling steps to be taken towards resolving the inverse design problem of deter-mining processing parameters based on desired location-specific properties.
对提高性能和功能的渴望为增材制造(AM)零件的设计和制造带来了额外的复杂性。然而,要满足这些需求,就需要在制造过程中改进对当地特性的控制。在这方面,微分蒸发是金属增材制造工艺的固有特性,直接影响到局部化学、材料特性、功能和性能。本文提出了激光粉末床熔合AM的微分蒸发模型(DEM),以预测和控制蒸发对局部和局部范围内化学和性能的影响。DEM模型与51.2 Ni [at校准的解析热模型相结合。%]镍钛SMA单轨实验和多层模型,该模型解释了增材制造部件的多层设计以及固有的熔池重叠和化学传播。该组合分层模型由热、蒸发和多层组件组成,用于预测LBPF AM制造50.8 Ni [at的特定位置化学。镍钛形状记忆合金(NiTi sma)。通过商用LPBF系统的多层实验验证了模型预测值,得出均方根误差(RMSE)为0.25 Ni [at]。%]表示预测的Ni含量。此外,计算了马氏体相变温度Ms,并与经验数据进行了比较,得出RMSE为18.6 K。通过这种模式的联系,对累积和传播的热诱导蒸发对特定地点化学的影响进行了实际的说明。从根本上说,该模型链还为正演建模问题提供了解决方案,从而可以采取步骤解决基于所需位置特定属性确定加工参数的反设计问题。