PSI - Issue 78

Mauro Mazzei et al. / Procedia Structural Integrity 78 (2026) 1649–1656

1656

structures, together with the numerical modelling carried out, have made it possible to identify initial verification criteria. In particular, due to these characteristics, even complex geometries can be obtained with spatial lattice structures with a lower structural weight than any other type of solution. Taking into account the resistant mechanism of the lattice structure, it is possible to reduce the number of members to the strict minimum necessary and to arrange them in simple triangulations with similar sides and angles to ensure a regular distribution of stresses. It is also evident from using new-generation structural analysis software that the design of lattice structures is mostly stressed by normal compressive or tensile stress. It was very interesting to design a lattice structure module that could be easily replicated and that supports a geometric spatial figure that is also very interesting from a mathematical point of view References Letov N., Zhao Y.F.. GEOMETRIC MODELLING OF HETEROGENEOUS LATTICE STRUCTURES THROUGH FUNCTION REPRESENTATION WITH LATTICEQUERY, (2023) Proceedings of the Design Society, 3, pp. 2045 - 2054, DOI: 10.1017/pds.2023.205 Pasko A., Adzhiev V., Sourin A., Savchenko V., Function representation in geometric modeling: concepts, implementation and applications, (1995) The Visual Computer, 11 (8), pp. 429 - 446, Cited 421 times. DOI: 10.1007/BF02464333 Mathur A., Pirron M., Zufferey D., Interactive Programming for Parametric CAD (2020) Computer Graphics Forum, 39 (6), pp. 408 - 425, DOI: 10.1111/cgf.14046 Harris C.R., Millman K.J., van der Walt S.J., Gommers R., Virtanen P., Cournapeau D., Wieser E., Taylor J., Berg S., Smith N.J., Kern R., Picus M., Hoyer S., van Kerkwijk M.H., Brett M., Haldane A., del Río J.F., Wiebe M., Peterson P., Gérard-Marchant P., Sheppard K., Reddy T., Weckesser W., Abbasi H., Gohlke C., Oliphant T.E. Array programming with NumPy, (2020) Nature, 585 (7825), pp. 357 - 362, DOI: 10.1038/s41586-020-2649-2 Letov N., Zhao Y.F., A geometric modelling framework to support the design of heterogeneous lattice structures with non-linearly varying geometry, (2022) Journal of Computational Design and Engineering, 9 (5), pp. 1565 - 1584, DOI: 10.1093/jcde/qwac076 Junk S., Kuen C., Review of Open Source and Freeware CAD Systems for Use with 3D-Printing (2016) Procedia CIRP, 50, pp. 430 - 435, DOI: 10.1016/j.procir.2016.04.174 Liu Y., Zheng G., Letov N., Zhao Y.F., A Survey of Modeling and Optimization Methods for Multi-Scale Heterogeneous Lattice Structures, (2021) Journal of Mechanical Design, 143 (4), art. no. 040803, DOI: 10.1115/1.4047917 Gopsill J.A., Shindler J., Hicks B.J., Using finite element analysis to influence the infill design of fused deposition modelled parts, (2018) Progress in Additive Manufacturing, 3 (3), pp. 145 - 163, DOI: 10.1007/s40964-017-0034-y Savio G., Meneghello R., Concheri G., Geometric modeling of lattice structures for additive manufacturing, (2018) Rapid Prototyping Journal, 24 (2), pp. 351 - 360, DOI: 10.1108/RPJ-07-2016-0122 Qi L., Li Z., Pan H., Xie Z., Li L., Huang X., Study on mechanical properties of double-layer hex-tri timber reciprocal frame of mortise-tenon connections, (2022) Journal of Building Structures, 43 (11), pp. 151 - 157, DOI: 10.14006/j.jzjgxb.2021.0131 Guo J., Li M., Augmented Sphere Tracing for Real-time Editing Mega-scale Periodic Shell-lattice Structures, (2025) CAD Computer Aided Design, 184, art. no. 103876, Cited 0 times., DOI: 10.1016/j.cad.2025.103876 Kwon Y., Minck M., Multiscale and Failure Analysis of Periodic Lattice Structures, (2025) Applied Sciences (Switzerland), 15 (12), art. no. 6701, Cited 0 times., DOI: 10.3390/app15126701 McKenna F., OpenSees: A framework for earthquake engineering simulation,(2011) Computing in Science and Engineering, 13 (4), art. no. 5931487, pp. 58 - 66, DOI: 10.1109/MCSE.2011.66 Virtanen P., Gommers R., Oliphant T.E., Haberland M., Reddy T., Cournapeau D., Burovski E., Peterson P., Weckesser W., Bright J., et. al., SciPy 1.0: fundamental algorithms for scientific computing in Python, (2020) Nature Methods, 17 (3), pp. 261 - 272, Cited 24678 times., DOI: 10.1038/s41592-019-0686-2 Zhu M., McKenna F., Scott M.H., OpenSeesPy: Python library for the OpenSees finite element framework (2018) SoftwareX, 7, pp. 6 - 11, DOI: 10.1016/j.softx.2017.10.009 Guo J., Ye A., Wang X., Guan Z., OpenSeesPyView: Python programming-based visualization and post-processing tool for OpenSeesPy, (2023) SoftwareX, 21, art. no. 101278, DOI: 10.1016/j.softx.2022.101278 Psyrras N.K., Sextos A.G., Build-X: Expert system for seismic analysis and assessment of 3D buildings using OpenSees, (2018) Advances in Engineering Software, 116, pp. 23 - 35, DOI: 10.1016/j.advengsoft.2017.11.007 Arroyo O., Feliciano D., Novoa D., Valcárcel J., A Python library to streamline OpenSeesPy workflows (2024) SoftwareX, 27, art. no. 101832, DOI: 10.1016/j.softx.2024.101832 Rahman M.M., Nahar T.T., Kim D., FeView: Finite element model (FEM) visualization and post-processing tool for OpenSees, (2021) SoftwareX, 15, art. no. 100751, DOI: 10.1016/j.softx.2021.100751

Made with FlippingBook Digital Proposal Maker