2022
DOI: 10.1016/j.addma.2022.102730
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Controlling the mechanical behaviour of stochastic lattice structures: The key role of nodal connectivity

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Cited by 10 publications
(4 citation statements)
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“…It is obtained from combination of Equations ( 4) and (5). It aligns with previous lattice design studies and allows comparison of strength-to-stiffness ratios among different relative density composite TPMS gyroid lattice structures [67][68][69].…”
Section: Gibson-ashby Modelmentioning
confidence: 90%
“…It is obtained from combination of Equations ( 4) and (5). It aligns with previous lattice design studies and allows comparison of strength-to-stiffness ratios among different relative density composite TPMS gyroid lattice structures [67][68][69].…”
Section: Gibson-ashby Modelmentioning
confidence: 90%
“…It is obtained from combination of equations ( 4) and (5). It aligns with previous lattice design studies and allows comparison of strength-to-stiffness ratios among different relative density composite TPMS gyroid lattice structures [49][50][51].…”
Section: Gibson-ashby Modelmentioning
confidence: 94%
“…Recently, computer modeling techniques were used to produce “hybrid” porous structures, where despite porosities being casual in both size and position, they are constrained by boundaries conditions that greatly limit their variability, thus improving reliability [ [135] , [136] , [137] ]. When additive manufacturing technologies are utilized, the topography can be intentionally randomized at the design stage by incorporating stochastic seed generation techniques, meaning that their mechanical response can be modeled by altering the boundary conditions [ 138 ].…”
Section: Stretch-dominated and Bend-dominated Cellular Solidsmentioning
confidence: 99%