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Record W4389540781 · doi:10.17118/11143/21080

Experimental characterization and phenomenological modeling of strainrate-dependent compressive mechanical responses of PVC foams up to 500s-1

2023· article· en· W4389540781 on OpenAlexaff
Foad Rahimidehgolan, Pouya Mohammadkhani, William Altenhof, John Magliaro

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCellular and Composite Structures
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsMaterials scienceStrain (injury)Strain ratePhenomenological modelCharacterization (materials science)Composite materialPhysicsNanotechnologyCondensed matter physicsMedicine

Abstract

fetched live from OpenAlex

Abstract: Polymeric foams have a ubiquitous presence in modern industrial design due to their unique combination of crucial advantages, including high strength-to-weight ratio, corrosion resistance and significant energy absorbing capacity. Proper understanding and characterization of the dynamic mechanical response of polymeric foams are crucial for safe and optimized engineering design. Therefore, significant research efforts have investigated the rate sensitivity of polymeric foams utilizing various experimental and simulation techniques. The Split Hopkinson Pressure Bar (SHPB) is the most frequently employed apparatus in the dynamic testing of polymeric foams. It is important to note that the SHPBs technique was originally developed for evaluating the mechanical properties of metallic materials with high impedance levels. However, applying this technique for testing soft materials presents a considerable challenge that requires further research and development to overcome. Furthermore, specimens with smaller dimensions (especially when comprised of testing soft materials) are more desirable for SHPB testing. The minimum specimen geometry in accordance with ASTM D1621, the standard test method for compressive properties of rigid cellular plastics, is typically not attainable when utilizing SHPBs. Therefore, in most previous experimental investigations, the specimen geometry requirements by ASTM D1621 were not fulfilled. Technical challenges associated with utilizing SHPBs (and other dynamic testing machines) in testing polymeric foams have resulted in a lack of reliable dynamic material characterization data at strain rates ranging from 50 s-1 to 500 s-1. In this research work, the strain rate sensitivity of PVC foams with nominal densities of 45 kg/m3 and 250 kg/m3 was experimentally investigated utilizing a pneumatic high strain rate testing machine in combination with a novel sacrificial energy absorber. The pneumatic machine was equipped with a bullet, having a mass of 11.5 kg, being massive compared to other pneumatic testing apparatuses considered by other research investigations. Therefore, testing larger foam specimens, enabling conformance to ASTM D1621 requirements at near-constant strain rates, was achieved by employing the described testing machine. The remaining amount of the bullet’s kinetic energy was dissipated by the novel energy absorber to prevent damaging the machine’s structure and the load transducers after foam compaction was achieved. Strain rates up to 500 s-1 were successfully achieved by using this apparatus. A phenomenological model based on the work of Avalle and a modified version of Nagy’s model was proposed to characterize the PVC foams’ rate-sensitive stress/strain response. The model accurately predicted the complete stress/strain response with an average accumulative error of 6.85%.

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.

How this classification was reachedexpand

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.336

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 head0.025
GPT teacher head0.249
Teacher spread0.224 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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