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Stiffness design method of Gyroid-based functionally graded lattice structures with variable porosity controlled by load path

2025· article· en· W4415985948 on OpenAlex

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affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueComposite Structures · 2025
Typearticle
Languageen
FieldEngineering
TopicComposite Structure Analysis and Optimization
Canadian institutionsUniversity of Manitoba
FundersMitacsNational Natural Science Foundation of China
KeywordsPorosityStiffnessCantileverLattice (music)SubdivisionBeam (structure)Material propertiesBending stiffnessPorous medium

Abstract

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The design of functionally graded lattice structure (FGLS) with triply period minimal surface can better improve the specific stiffness, strength, and energy-absorption capacity. However, how to design the porosity distribution and accurately control structural stiffness is a challenging task. This paper presents a stiffness design method of Gyroid-based FGLS based on variable porosity controlled by load paths. The continuous space iterative subdivision search method is established to calculate the minimum distance from central coordinate point of the cell to the main load paths. Then the mapping relationship between minimum distance and cell porosity is established. The influence of the dispersion range of cell porosity on mechanical properties is further analyzed. It was found that the mechanical properties increase with the increase of dispersion range. Next, cantilever beam and three-point bending beam are taken as the research object, and the FGLSs of the two models with bidirectional gradient are redesigned. The simulation and experimental results show that the stiffness of bidirectional gradient FGLSs is better than uniform density lattice structure under the same volume fraction. This method can accurately and explicitly controls the porosity of each cell by load path, thereby improving the overall structural stiffness.

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.756
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.220
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it