Composition optimization of PMMA base denture reinforced with different percentages of Nano Hydroxyapatite and alumina particles to obtain highest KIc and KIIc values using hybrid IWO/PSO algorithm

•Hybrid IWO/PSO algorithm for composition optimization of PMMA base denture.•Effect of PMMA-Nano Hydroxyapatite-Nano Alumina contents on modes I and II fracture toughness.•Performing initial guess KIc and KIIc tests on nine-groups of base dentures using symmetric and asymmetric bend beams.•Predictio...

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Published inTheoretical and applied fracture mechanics Vol. 128; p. 104090
Main Authors Wu, Junliang, Wang, Haibo, Mao, Liqing, Aliha, M.R.M.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.12.2023
Subjects
Online AccessGet full text
ISSN0167-8442
1872-7638
DOI10.1016/j.tafmec.2023.104090

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Abstract •Hybrid IWO/PSO algorithm for composition optimization of PMMA base denture.•Effect of PMMA-Nano Hydroxyapatite-Nano Alumina contents on modes I and II fracture toughness.•Performing initial guess KIc and KIIc tests on nine-groups of base dentures using symmetric and asymmetric bend beams.•Prediction of highest KIc and KIIc values for the PMMA/Nanoparticle denture using meta-heuristic approach.•Good agreement of fracture toughness ratio (KIIc/KIc) obtained from the experiments and IWO/PSO prediction. Composition of three-phase dental denture (Polymethyl methacrylate or PMMA + Nano Hydroxyapatite + Nano Alumina) was optimized using hybrid IWO/PSO algorithm to obtain the highest KIc and KIIc. First, initial fracture toughness tests were performed on nine groups of PMMA base dentures with different percentages of ingredients. Symmetric single edge notch beam and asymmetric three-point bend beam with inclined crack were used for KIc and KIIc testing, respectively. The initial design parameters were considered as: {75–100% PMMA, 0–10% Nano Hydroxyapatite and, 0–15% Nano Alumina}. As the initial guess values for starting the hybrid optimization algorithm, B-spline curves (as the cost function) were fitted to the experimental results of both modes I and II. Then the IWO/PSO algorithm was run to find the optimum composition and maximum fracture toughness value of each mode. The best KIc was found for the composition of {78.5% PMMA + 9% Nano Hydroxyapatide + 12.5% Nano Alumina}. Similarly, using the hybrid IWO/PSO algorithm the optimum composition of {83.4% PMMA + 8.7% Nano Hydroxyapatide + 7.9 % Nano Alumina} was obtained to gain the highest KIIc. The experimental fracture toughness values obtained from the proposed compositions via employing the hybrid algorithm were approximately 40% higher than the all tested nine groups of PMMA base dentures under both modes I and II. The fracture toughness ratio KIIc/KIc of the optimum mix-designs predicted by the hybrid algorithm was equal to 0.78 and showed good agreement with the experimental KIIc/KIc ratio. The fracture toughness for any desired mixed mode condition can also be predicted in-terms of the KIc and stress intensity factors and T-stress of the desired mode mixity.
AbstractList •Hybrid IWO/PSO algorithm for composition optimization of PMMA base denture.•Effect of PMMA-Nano Hydroxyapatite-Nano Alumina contents on modes I and II fracture toughness.•Performing initial guess KIc and KIIc tests on nine-groups of base dentures using symmetric and asymmetric bend beams.•Prediction of highest KIc and KIIc values for the PMMA/Nanoparticle denture using meta-heuristic approach.•Good agreement of fracture toughness ratio (KIIc/KIc) obtained from the experiments and IWO/PSO prediction. Composition of three-phase dental denture (Polymethyl methacrylate or PMMA + Nano Hydroxyapatite + Nano Alumina) was optimized using hybrid IWO/PSO algorithm to obtain the highest KIc and KIIc. First, initial fracture toughness tests were performed on nine groups of PMMA base dentures with different percentages of ingredients. Symmetric single edge notch beam and asymmetric three-point bend beam with inclined crack were used for KIc and KIIc testing, respectively. The initial design parameters were considered as: {75–100% PMMA, 0–10% Nano Hydroxyapatite and, 0–15% Nano Alumina}. As the initial guess values for starting the hybrid optimization algorithm, B-spline curves (as the cost function) were fitted to the experimental results of both modes I and II. Then the IWO/PSO algorithm was run to find the optimum composition and maximum fracture toughness value of each mode. The best KIc was found for the composition of {78.5% PMMA + 9% Nano Hydroxyapatide + 12.5% Nano Alumina}. Similarly, using the hybrid IWO/PSO algorithm the optimum composition of {83.4% PMMA + 8.7% Nano Hydroxyapatide + 7.9 % Nano Alumina} was obtained to gain the highest KIIc. The experimental fracture toughness values obtained from the proposed compositions via employing the hybrid algorithm were approximately 40% higher than the all tested nine groups of PMMA base dentures under both modes I and II. The fracture toughness ratio KIIc/KIc of the optimum mix-designs predicted by the hybrid algorithm was equal to 0.78 and showed good agreement with the experimental KIIc/KIc ratio. The fracture toughness for any desired mixed mode condition can also be predicted in-terms of the KIc and stress intensity factors and T-stress of the desired mode mixity.
ArticleNumber 104090
Author Wang, Haibo
Mao, Liqing
Wu, Junliang
Aliha, M.R.M.
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Keywords Nano Alumina
Hybrid IWO/PSO algorithm
Nano Hydroxyapatite
Modes I and II fracture toughness
Mixture optimization
PMMA base denture
Language English
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Snippet •Hybrid IWO/PSO algorithm for composition optimization of PMMA base denture.•Effect of PMMA-Nano Hydroxyapatite-Nano Alumina contents on modes I and II...
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StartPage 104090
SubjectTerms Hybrid IWO/PSO algorithm
Mixture optimization
Modes I and II fracture toughness
Nano Alumina
Nano Hydroxyapatite
PMMA base denture
Title Composition optimization of PMMA base denture reinforced with different percentages of Nano Hydroxyapatite and alumina particles to obtain highest KIc and KIIc values using hybrid IWO/PSO algorithm
URI https://dx.doi.org/10.1016/j.tafmec.2023.104090
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