Computational modelling of process-structure-property-performance relationships in metal additive manufacturing: a review

被引:77
|
作者
Hashemi, Seyed Mahdi [1 ]
Parvizi, Soroush [2 ]
Baghbanijavid, Haniyeh [2 ]
Tan, Alvin T. L. [3 ]
Nematollahi, Mohammadreza [1 ]
Ramazani, Ali [4 ]
Fang, Nicholas X. [4 ]
Elahinia, Mohammad [1 ]
机构
[1] Univ Toledo, Mech Ind & Mfg Engn Dept, Dynam & Smart Syst Lab, 2801 W Bancroft St,MS 312, Toledo, OH 43606 USA
[2] Shahid Rajaee Teacher Training Univ SRTTU, Mat Engn Dept, Tehran, Iran
[3] MIT, Dept Mat Sci & Engn, Cambridge, MA 02139 USA
[4] MIT, Dept Mech Engn, Cambridge, MA 02139 USA
关键词
Metal additive manufacturing; real data; data-driven modelling; multi-scale multi-physics model/simulation; process-structure-property-performance relations; POWDER-BED FUSION; FINITE-ELEMENT-ANALYSIS; PHASE-FIELD SIMULATION; MELT POOL GEOMETRY; RESIDUAL-STRESS; EXPERIMENTAL VALIDATION; PROCESS PARAMETERS; INCONEL; 718; MICROSTRUCTURE EVOLUTION; MECHANICAL-PROPERTIES;
D O I
10.1080/09506608.2020.1868889
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In the current review, an exceptional view on the multi-scale integrated computational modelling and data-driven methods in the Additive manufacturing (AM) of metallic materials in the framework of integrated computational materials engineering (ICME) is discussed. In the first part of the review, process simulation (P-S linkage), structure modelling (S-P linkage), property simulation (S-P linkage), and integrated modelling (PSP and PSPP linkages) are elaborated considering different physical phenomena (multi-physics) in AM and at micro/meso/macro scales (multi-scale modelling). The second part provides an extensive discussion of a data-driven framework, which involves extracting existing data from databases and texts, data pre-processing, high throughput screening, and, therefore, database construction. A data-driven workflow that integrates statistical methods, including ML, artificial intelligence (AI), and neural network (NN) models, has great potential for completing PSPP linkages. This review paper provides an insight for both academic and industrial researchers, working on the AM of metallic materials.
引用
收藏
页码:1 / 46
页数:46
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