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Record W3205923293 · doi:10.1080/15440478.2021.1944429

Optimization and Modeling of Sound-Absorption Properties of Natural Fibers for Acoustical Application

2021· article· en· W3205923293 on OpenAlex

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.

Bibliographic record

VenueJournal of Natural Fibers · 2021
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsToronto Metropolitan University
FundersIran National Science Foundation
KeywordsKenafMaterials scienceComposite materialNoise reduction coefficientUltimate tensile strengthPorosityScanning electron microscopeAbsorption (acoustics)FiberDurability

Abstract

fetched live from OpenAlex

Kenaf fibers have long been utilized because of their remarkable properties, such as availability, durability, and strength. Recently, they have also been used as sound-absorbing composites for noise control purposes. This paper investigates the possibility of improving the tensile strength of kenaf fibers through optimizing the alkaline treatment process. It also considers the effects of such optimization on the acoustic absorption coefficients of the samples fabricated from these treated kenaf fibers as well as the applicability of the numerical model to predict the acoustic absorption. Having employed the response surface methodology (RSM) to optimize the alkaline treatment process and achieve optimal conditions for the kenaf fibers, the scanning electron microscopy (SEM) and tensile test were used to study and compare the morphological and tensile properties of raw fibers (nonoptimal) and the fibers treated in optimal conditions. Several cylindrical samples with constant thickness and density (30 mm and 200 kg/m3) were then made of fibers treated in optimal conditions. The sound absorption coefficient, porosity, and airflow resistivity of these samples were measured based using ISO 10534–2 (impedance tube system), SEM and ASTM C423-09A, respectively. The results demonstrated that the tensile strength of optimally treated fibers increased by 182.39%. The acoustic absorption coefficients of the samples fabricated from these fibers were also higher at all frequencies (low-, mid-, and high-frequency range) compared with samples made of untreated fibers in a way that the Sound Absorption Average value of the former increased by 17.97%. Moreover, it was found that inverted Dunn and Davern model via Nelder-Mead simplex method well follows the sound absorption pattern from the experimental results in the overall frequency range. The use of multifaceted improvement approaches for natural materials such as kenaf fibers increases the usability of these materials as sustainable and eco-friendly alternatives in the engineering process of manufacturing sound-absorbing materials.

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 score0.309
Threshold uncertainty score0.465

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 communication0.0000.001
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 head0.019
GPT teacher head0.257
Teacher spread0.238 · 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