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Ornaghi Heitor L. Almeida José Humberto S. Monticeli Francisco M. Neves Roberta M. Cioffi Maria Odila H. 《Mechanics of Time-Dependent Materials》2021,25(4):601-615
Mechanics of Time-Dependent Materials - The time-temperature creep behavior of advanced composite laminates is herein determined through a comprehensive set of experiments and analytical modeling.... 相似文献
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Neves Roberta Motta Lopes Kirk Silveira Lazzari Lídia Kunz Monticeli Francisco Maciel Zattera Ademir José 《Journal of Porous Materials》2021,28(4):1081-1095
Journal of Porous Materials - Supercritical carbon dioxide (scCO2) has been used as a physical blowing agent to produce polymer expanded materials. Firstly, a statistic study was performed to... 相似文献
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Francisco Maciel Monticeli Dielly Cavalcanti da Silva Monte Vidal Marcos Yutaka Shiino Herman Jacobus Cornelis Voorwald Maria Odila Hilrio Cioffi 《Polymer Engineering and Science》2019,59(6):1215-1222
The mechanical properties of composite structures depend on the preform impregnation and a successful impregnation can be achieved using the permeability relation in the case of an infusion process. The objective of this study is to develop an analytical model to predict the permeability K of carbon and glass fabrics through hybrid laminate using different stacking sequence, applying an average‐permeability model. Preforms permeabilities were evaluated through tortuosity and void‐volume fraction. The model allows the analysis of different stacking sequence combinations (interleaved and in block), measuring the contribution of each material type. As a result, hybrid average‐permeability model was validated through experimental permeability tests, dimensionless permeability, and tortuosity results, besides enabling predictions of the flow front behavior with <10% of deviation. Carbon fiber preforms exhibited higher flow resistance, which is explained via tortuosity concept. A combination of carbon/glass preforms presented an increased permeability, which means a synergy that provides higher value of K. In addition, the use of hybrid preforms, especially Hybrid 2 stacking sequence, reduce the injection time and void formation, ensuring composite impregnation quality. POLYM. ENG. SCI., 59:1215–1222 2019. © 2019 Society of Plastics Engineers 相似文献
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Francisco Maciel Monticeli Sergio Roberto Montoro Herman Jacobus Cornelis Voorwald Maria Odila Hilário Cioffi 《Polymer Engineering and Science》2020,60(4):841-849
In polymer composites, the porosity acts mainly as a stress concentrator, which has detrimental effects depending on the shape and position of the voids. Also, the presence of voids is detrimental to the mechanical properties, which results in the need for an accurate method for their characterization in terms of morphology, position, and volume fraction. The aim of this study was to establish an appropriate procedure for the measurement of voids in a polymer composite using the mercury porosimetry technique. Data were also collected using the Taguchi approach. Subsequently, the feasibility of applying the Hg porosimetry methodology was confirmed through a comparison with standard techniques. Statistical analysis was used to determine the best Hg porosimetry parameters and pressures between 203 and 231 MPa was found to generate reliable results for the maximum porosity measurement, with no dependence on other parameters. Since the Hg porosimetry, acid digestion, and optical microscopy methods provided porosity results with a statistically significant similarity, it can be concluded that all these methods are feasible for the analysis of voids. Finally, potential benefits of the proposed porosity analysis methodology were highlighted through the characterization of the void volume, position, and morphology. POLYM. ENG. SCI., 60:841–849, 2020. © 2020 Society of Plastics Engineers 相似文献
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Lucas Dall Agnol Heitor Luiz Ornaghi Jr Francisco Monticeli Fernanda Trindade Gonzalez Dias Otávio Bianchi 《Polymer Engineering and Science》2021,61(6):1810-1818
The molar mass of the polyurethanes (PUs)' reagents directly influences their thermal response, affecting both the polymerization process and the enthalpy and the degree of reaction. This study reports applying an artificial neural network (ANN), associated with surface response methodology (SRM) models, to predict the calorimetric behavior of certain PU's bulk polymerizations. A noncatalyzed reaction between an aliphatic hexamethylene diisocyanate (HDI) and a polycarbonate diol (PCD) with distinct molar masses (500, 1000, and 2000 g/mol) was proposed. A high level of reliability of the predicted calorimetric curves was obtained due to an excellent agreement between theoretical and modeled results, enabling creating a 3D surface response to predict the reaction kinetics. Also, it was possible to observe that the polymerization kinetics is affected by the OH group's association phenomena. The applied methodology can be extended for other materials or properties of interest. 相似文献
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