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Research Article

A non-probabilistic convex modelling framework for uncertainty quantification of laser powder bed fusion fabricated structures based on limited data

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Article: e2324429 | Received 01 Sep 2023, Accepted 19 Feb 2024, Published online: 06 Mar 2024

References

  • Liu J, Chen T, Zhang Y, et al. On sound insulation of pyramidal lattice sandwich structure. Compos Struct. 2019a;208:385–394. doi:10.1016/j.compstruct.2018.10.013.
  • Liu J, Ou H, Zeng R, et al. Fabrication, dynamic properties and multi-objective optimization of a metal origami tube with Miura sheets. Thin-Walled Struct. 2019b;144:106352, doi:10.1016/j.tws.2019.106352.
  • Zhang Y, Xu X, Fang J, et al. Load characteristics of triangular honeycomb structures with self-similar hierarchical features. Eng Struct. 2022;257:114114, doi:10.1016/j.engstruct.2022.114114.
  • Liu H, Gu D, Qi J, et al. Dimensional effect and mechanical performance of node-strengthened hybrid lattice structure fabricated by laser powder bed fusion. Virtual Phys Prototyp. 2023;18(1), doi:10.1080/17452759.2023.2240306.
  • Yin S, Chen H, Wu Y, et al. Introducing composite lattice core sandwich structure as an alternative proposal for engine hood. Compos Struct. 2018;201:131–140. doi:10.1016/j.compstruct.2018.06.038.
  • Sha W, Xiao M, Zhang J, et al. Robustly printable freeform thermal metamaterials. Nat Commun. 2021;12(1):7228, doi:10.1038/s41467-021-27543-7.
  • Chen B, Chen L, Du B, et al. Novel multifunctional negative stiffness mechanical metamaterial structure: tailored functions of multi-stable and compressive mono-stable. Composites Part B: Engineering. 2021;204:108501, doi:10.1016/j.compositesb.2020.108501.
  • Blakey-Milner B, Gradl P, Snedden G, et al. Metal additive manufacturing in aerospace: a review. Mater Des. 2021;209:110008, doi:10.1016/j.matdes.2021.110008.
  • Liu G, Zhang X, Chen X, et al. Additive manufacturing of structural materials. Materials Science and Engineering: R: Reports. 2021;145:100596.
  • Kumar SP, Elangovan S, Mohanraj R, et al. Review on the evolution and technology of State-of-the-Art metal additive manufacturing processes. Mater Today Proc. 2021;46:7907–7920. doi:10.1016/j.matpr.2021.02.567.
  • Yap CY, Chua CK, Dong ZL, et al. Review of selective laser melting: materials and applications. Appl Phys Rev. 2015;2(4):041101, doi:10.1063/1.4935926.
  • Nagarajan B, Hu Z, Song X, et al. Development of micro selective laser melting: the state of the art and future perspectives. Engineering. 2019;5(4):702–720. doi:10.1016/j.eng.2019.07.002.
  • Nagesha BK, Dhinakaran V, Varsha Shree M, et al. Review on characterization and impacts of the lattice structure in additive manufacturing. Mater Today Proc. 2020;21:916–919. doi:10.1016/j.matpr.2019.08.158.
  • Gu D, Shi X, Poprawe R, et al. Material-structure-performance integrated laser-metal additive manufacturing. Science. 2021;372(6545):eabg1487, doi:10.1126/science.abg1487.
  • Delcuse L, Bahi S, Gunputh U, et al. Effect of powder bed fusion laser melting process parameters, build orientation and strut thickness on porosity, accuracy and tensile properties of an auxetic structure in IN718 alloy. Addit Manuf. 2020;36:101339, doi:10.1016/j.addma.2020.101339.
  • Meng L, Lan X, Zhao J, et al. Failure analysis of bio-inspired corrugated sandwich structures fabricated by laser powder bed fusion under three-point bending. Compos Struct. 2021;263:113724, doi:10.1016/j.compstruct.2021.113724.
  • Zhong T, He K, Li H, et al. Mechanical properties of lightweight 316L stainless steel lattice structures fabricated by selective laser melting. Mater Des. 2019;181:108076, doi:10.1016/j.matdes.2019.108076.
  • Dzugan J, Seifi M, Rzepa S, et al. Mechanical properties characterisation of metallic components produced by additive manufacturing using miniaturised specimens. Virtual Phys Prototyp. 2023;18(1):2161400, doi:10.1080/17452759.2022.2161400.
  • Mukalay TA, Trimble JA, Mpofu K, et al. A systematic review of process uncertainty in Ti6Al4V-selective laser melting. CIRP J Manuf Sci Technol. 2022;36:185–212. doi:10.1016/j.cirpj.2021.12.005.
  • Zocca A, Wilbig J, Waske A, et al. Challenges in the technology development for additive manufacturing in space. Chin J Mech Eng: Addit Manuf Front. 2022;1(1):100018, doi:10.1016/j.cjmeam.2022.100018.
  • Moser D, Cullinan M, Murthy J. Multi-scale computational modeling of residual stress in selective laser melting with uncertainty quantification. Addit Manuf. 2019;29:100770, doi:10.1016/j.addma.2019.06.021.
  • Chen Z, Han C, Gao M, et al. A review on qualification and certification for metal additive manufacturing. Virtual Phys Prototyp. 2022;17(2):382–405. doi:10.1080/17452759.2021.2018938.
  • Lin Q, Hu J, Zhou Q, et al. Multi-output Gaussian process prediction for computationally expensive problems with multiple levels of fidelity. Knowl Based Syst. 2021;227:107151, doi:10.1016/j.knosys.2021.107151.
  • Cao L, Liu J, Xie L, et al. Non-probabilistic polygonal convex set model for structural uncertainty quantification. Appl Math Model. 2021;89:504–518. doi:10.1016/j.apm.2020.07.025.
  • Wang L, Liu Y, Li M. Time-dependent reliability-based optimization for structural-topological configuration design under convex-bounded uncertain modeling. Reliab Eng Syst Saf. 2022;221:108361, doi:10.1016/j.ress.2022.108361.
  • Kang Z, Zhang W. Construction and application of an ellipsoidal convex model using a semi-definite programming formulation from measured data. Comput Methods Appl Mech Eng. 2016;300:461–489. doi:10.1016/j.cma.2015.11.025.
  • Zhao MY, Yan WJ, Veng Yuen K, et al. Non-probabilistic uncertainty quantification for dynamic characterization functions using complex ratio interval arithmetic operation of multidimensional parallelepiped model. Mech Syst Signal Process. 2021;156:107559, doi:10.1016/j.ymssp.2020.107559.
  • Jiang C, Han X, Lu GY, et al. Correlation analysis of non-probabilistic convex model and corresponding structural reliability technique. Comput Methods Appl Mech Eng. 2011;200(33-36):2528–2546. doi:10.1016/j.cma.2011.04.007.
  • Xu M, Du J, Wang C, et al. A dual-layer dimension-wise fuzzy finite element method for structural analysis with epistemic uncertainties. Fuzzy Sets Syst. 2019;367:68–81. doi:10.1016/j.fss.2018.08.010.
  • Luo Y, Zhan J, Xing J, et al. Non-probabilistic uncertainty quantification and response analysis of structures with a bounded field model. Comput Methods Appl Mech Eng. 2019;347:663–678. doi:10.1016/j.cma.2018.12.043.
  • Zhao G, Liu J, Wen G, et al. Non-probabilistic convex model theory to obtain failure shear stress of simulated lunar soil under interval uncertainties. Probab Eng Mech. 2018;53:87–94. doi:10.1016/j.probengmech.2018.06.002.
  • Zhao G, Wen G, Liu J. A novel analysis method for vibration systems under time-varying uncertainties based on interval process model. Probab Eng Mech. 2022;70:103363, doi:10.1016/j.probengmech.2022.103363.
  • Gorguluarslan RM, Choi S-K, Saldana CJ. Uncertainty quantification and validation of 3D lattice scaffolds for computer-aided biomedical applications. J Mech Behav Biomed Mater. 2017;71:428–440. doi:10.1016/j.jmbbm.2017.04.011.
  • Li F, Wang R, Zheng Z, et al. A time-variant reliability analysis framework for selective laser melting fabricated lattice structures with probability and convex hybrid models. Virtual Phys Prototyp. 2022;17(4):841–853. doi:10.1080/17452759.2022.2074196.
  • Lozanovski B, Downing D, Tran P, et al. A Monte Carlo simulation-based approach to realistic modelling of additively manufactured lattice structures. Addit Manuf. 2020;32:101092, doi:10.1016/j.addma.2020.101092.
  • Snider-Simon B, Frantziskonis G. Reliability of metal additive manufactured materials from modeling the microstructure at different length scales. Addit Manuf. 2022;51:102629, doi:10.1016/j.addma.2022.102629.
  • Zhao G, Liu J, Wen G, et al. A novel method for non-probabilistic convex modelling based on data from practical engineering. Appl Math Model. 2020;80:516–530. doi:10.1016/j.apm.2019.12.002.
  • Cui Y, Geng Z, Zhu Q, et al. Review: multi-objective optimization methods and application in energy saving. Energy. 2017;125:681–704. doi:10.1016/j.energy.2017.02.174.
  • Ni BY, Jiang C, Huang ZL. Discussions on non-probabilistic convex modelling for uncertain problems. Appl Math Model. 2018;59:54–85. doi:10.1016/j.apm.2018.01.026.
  • Shen C, Bao X, Tan J, et al. Two noise-robust axial scanning multi-image phase retrieval algorithms based on Pauta criterion and smoothness constraint. Opt Express. 2017;25(14):16235–16249. doi:10.1364/OE.25.016235.
  • Jiang C, Bi RG, Lu GY, et al. Structural reliability analysis using non-probabilistic convex model. Comput Methods Appl Mech Eng. 2013;254:83–98. doi:10.1016/j.cma.2012.10.020.