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In this study, data analysis was performed using an artificial neural network (ANN) approach to investigate the effect of the chemical composition of welds on their mechanical properties (yield strength, tensile strength, and impact toughness). Based on the data collected from previously performed experiments, correlations between related variables and results were analyzed and predictive models were developed. Sufficient datasets were prepared using data augmentation techniques to solve problems caused by insufficient data and to make better predictions. Finally, closed-form equations were developed based on the predictive models to evaluate the mechanical properties according to the chemical composition.

The LNG cargo containment system used in membrane-type LNG cargo tanks must have sufficient dynamic strength to withstand the impact of sloshing loads. However, performing direct dynamic nonlinear transient finite element assessments against design sloshing impact loads with different design specifications can be complicated and time-consuming. To address this, it is effective to use linear superposition methods, such as the triangular impulse response function (TIRF) method, to conduct dynamic transient FE assessments of LNG cargo containment systems. However, as LNG cargo containment systems have a high level of nonlinearities in terms of geometry, material, and boundary effects, it is necessary to evaluate the applicability of the TIRF method in advance. This study investigates the dynamic responses of an LNG cargo containment system using the TIRF method and compares the ultimate value of the structural responses and impulses with that obtained using direct dynamic nonlinear transient assessments. Based on a comparison of a series of FE analyses, the study proposes a design for the partial safety factors for calculating the ultimate bending and shear capacities of an LNG cargo containment system, taking into consideration the dynamic impact of sloshing loads using the TIRF method. Finally, the ultimate shear and bending capacities are calculated using the proposed method and compared with those obtained through direct dynamic nonlinear transient assessments. The results show that the proposed method provides conservative estimates against direct nonlinear finite element simulations, with a difference of around 10% for the mean minus two standard deviations. This approach can be practically applied for early basic design purposes in the shipbuilding industry.

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: Volatile organic compounds (VOC) free adhesives have been interested by many scientists and engineers due to environmental regulations and the safety of industrial workers. In this work, a series of composites composed with bisphenol A epoxy resin used as solvent, dicyandiamide, and promoter were prepared to investigate the most appropriate molar ratio for steel-steel adhesion. The cured test specimen of each composite were measured with universal testing machine (UTM) to figure out mechanical properties such as tensile strength, Young's modulus, and elongation. Furthermore, the lap shear strength of the specimen was tested with UTM while impact resistance was measured with Izod impact tester. The composite whose molar ratio of epoxy resin to curing agent is 1 : 0.9 (sample 3), showed better tensile strength, coefficient of elastic modulus, elongation, and impact strength than other composites did. The highest tanδ from dynamic mechanical analysis (DMA) was observed from sample 2 (epoxy resin: dicy = 1 : 0.7) while sample 3 showed slightly lower tanδ than that of 2. The morphology of the fracture surface of the cured composites from SEM showed that the number of subtle lines on the surface caused by impact increase as the contents of amine curing agent accrete. Furthermore, the viscosity change of sample 5 (epoxy resin: dicy = 1 : 1.3) was observed to confirm its storage stability.