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The textile industry now produces thousands of tons of waste worldwide, and the total amount of discarded material waste increases yearly. Hygrothermal aging of cotton/E-glass (hybrid) fiber reinforced with various proportions of graphene oxide (0%, 1%, 3%, 5%, 7%, and 9%) was performed. Epoxy and vinyl ester (50:50) have been chosen because of the Interpenetrating Polymer Networks (IPNs) concept. Laminates were subjected to 50, 60, and 70°C temperatures for 180 days. Further, Tg and the degree of cross-linking have been determined by using differential scanning calorimetry (DSC). DSC analysis proves that a hot water bath enhances the cross-linking of the polymer. IPN laminates were also intermittently weighed for water uptake, and their consecutive mechanical properties like tensile, flexural, and impact strength were obtained. From this work, it was observed that the addition of 5 w.t% graphene oxide in cotton/E glass fiber vinyl ester/epoxy resin hybrid IPN composites showed a tensile strength of 375.61 MPa, flexural strength of 393.54 MPa, Interlaminar shear strength (ILSS) of 49 MPa and the impact strength of 22.54 MPa. Moreover, the lowest inclusion of particulate addition exhibits better mechanical properties than (up to 5% of GO) the highest particulate loading into the matrix. SEM study was conducted on the broken specimens to know the impact of diffusion characteristics on the physical properties of the IPN composites. Highlights • Natural and synthetic fibers are used as reinforcements. • Waste cotton/E glass fiber vinyl epoxy composites are fabricated. • Laminates were subjected to diverse temperatures for 180 days. • The moisture diffusion coefficient is proportional to water temperature. • Bathtub temperature affects the tensile strength of the laminate. [ABSTRACT FROM AUTHOR]

The increased durability and performance features of polymer concrete panels have led to their widespread application in construction. The manufacturing of precise and effective techniques for identifying forms and flaws is vital to guarantee the high quality of these panels. To increase the accuracy of structure and defect-recognition in polymer concrete panels, this study presents a new Stochastic raven roosting optimization enhanced artificial neural network (SRRO-EANN) forecasting technique. The data sample used to assess the completed model fits the training dataset is referred to the test dataset. The Gaussian filter (GF) is a tool used in the pre-processing and Principal Component Analysis (PCA) feature extraction, leading to more effective utilization and understanding the defect capturing. The findings of the research indicate the effectiveness for the future development of forecasting technologies in the realm of quality control and building material inspection. [ABSTRACT FROM AUTHOR]

This study is aimed at reducing NOx, Smoke, HC, CO emissions from single-cylinder, four-stroke, and water cooled diesel engine. The research engine is fueled with diesel and two blends of butanol and diesel at atmospheric conditions. Neat diesel is termed as D100, 10%, and 20% Volume of butanol dispersed in D100 is termed as D90B10 and D80B20 respectively. The chemical and physical properties of D100, D90B10 and D80B20 fall within the limits of ASTM standards. Results revealed that enhanced chemical properties and higher latent heat of vaporization of butanol lowered the CO, HC, smoke, and NOX emissions of diesel fueled research diesel engine. [ABSTRACT FROM AUTHOR]