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Record W4390841455 · doi:10.1177/07316844241226834

Crashworthiness investigations for 3D printed multi-layer multi-topology carbon fiber nylon lattice materials

2024· article· en· W4390841455 on OpenAlex
Autumn R. Bernard, Muhammet Muaz Yalçın, Mostafa S. A. ElSayed

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

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

Bibliographic record

VenueJournal of Reinforced Plastics and Composites · 2024
Typearticle
Languageen
FieldEngineering
TopicCellular and Composite Structures
Canadian institutionsCarleton University
FundersMitacs
KeywordsOctetMaterials scienceCrashworthinessLattice (music)Topology (electrical circuits)Composite materialComposite numberStructural engineeringFinite element methodPhysicsAcousticsMathematics

Abstract

fetched live from OpenAlex

Cellular solids have superior energy absorption capabilities as compared to monolithic materials. Within this category of materials, lattice materials are of particular interest since their periodicity offers repeatable – and thus predictable – behavior. In combination with the advancements in additive manufacturing technologies, these lattice materials can be highly customized for a desired response. In this paper, the crashworthiness of unique multi-layer, multi-topology (MLMT) lattices is investigated. First, the nylon-carbon fiber composite material properties within a developed numerical model were tuned based on strut orientation. Then, the response of single-layer and three-layer cubic and octet lattices was investigated, where all lattices were designed with a relative density of 30%. Following the characterization of single-topology lattices, the response of MLMT lattices were investigated. Stress-strain, efficiency-strain, and multiple crashworthiness parameter data was collected for all lattices to facilitate in the comparison of those lattices. It was found that, experimentally, the unique MLMT lattices did not absorb more energy than their constituent layers combined, though modifications to the interface between layers could increase the energy absorption capability; the prediction of energy absorption of the MLMT lattices based on constituent layers was similar to actual numerical results. As all lattices were designed at the same relative density, the mass-specific energy absorption of the cubic-octet-cubic MLMT lattice (1.56 x10 3 J/kg) outperforms the single-topology octet lattice by 19% to 36% (1.15–1.31 x10 3 J/kg). While the octet-cubic-octet MLMT lattice (0.71 x10 3 J/kg) is outperformed by the single-topology cubic lattices (1.69–3.76 x10 3 J/kg), they see an increase of 59% to 77% in plateau stress (5.1–9.2 MPa) as compared to the MLMT lattice (2.1 MPa).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.707
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.014
GPT teacher head0.241
Teacher spread0.227 · 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