• Journal of Electrochemical Science and Technology
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• v.13 no.2
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• pp.199-207
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• 2022

Lithium-sulfur batteries (LSBs) have emerged as a promising alternative to lithium-ion batteries (LIBs) owing to their high energy density and economic viability. In addition, all-solid-state LSBs, which use solid-state electrolytes, have been proposed to overcome the polysulfide shuttle effect while improving safety. However, the high interfacial resistance and poor ionic conductivity exhibited by the electrode and solid-state electrolytes, respectively, are significant challenges in the development of these LSBs. Herein, we apply a poly (ethylene oxide) (PEO)-based composite solid-state electrolyte with oxide Li₇La₃Zr₂O₁₂ (LLZO) solid-state electrolyte in an all-solid-state LSB to overcome these challenges. We use an electrochemical method to evaluate the degradation of the all-solid-state LSB in accordance with the carbon content and loading weight within the cathode. The all-solid-state LSB, with sulfur-carbon content in a ratio of 3:3, exhibited a high initial discharge capacity (1386 mAh g^-1), poor C-rate performance, and capacity retention of less than 50%. The all-solid-state LSB with a high loading weight exhibited a poor overall electrochemical performance. The factors influencing the electrochemical performance degradation were revealed through systematic analysis.

• Journal of Environmental Health Sciences
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• v.48 no.3
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• pp.167-175
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• 2022

Background: Disinfection is essential to provide drinking water from a water source. The disinfection process mainly consists of the use of chlorine and ozone, but when chlorine is used as a disinfectant, the problem of disinfection by-products arises. In order to resolve the issue of disinfection by-products, electro-chlorination technology that produces chlorine-based disinfectants from salt water through electrochemical principles should be applied. Objectives: This study surveys the possibility of optimally producing active chlorine from synthetic NaCl solutions using an electro-chlorination system through RSM. Methods: Response surface methodology (RSM) has been used for modeling and optimizing a variety of water and wastewater treatment processes. This study surveys the possibility of optimally producing active chlorine from synthetic saline solutions using electrolysis through RSM. Various operating parameters, such as distance of electrodes, sodium chloride concentration, electrical potential, and electrolysis time were evaluated. Results: Various operating parameters, such as distance of electrodes, sodium chloride concentration, electrical potential, and electrolysis time were evaluated. A central composite design (CCD) was applied to determine the optimal experimental factors for chlorine production. Conclusions: The concentration of the synthetic NaCl solution and the distance between electrodes had the greatest influence on the generation of hypochlorite disinfectant. The closer the distance between the electrodes and the higher the concentration of the synthetic NaCl solution, the more hypochlorous acid disinfectant was produced.

• Structural Engineering and Mechanics
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• v.85 no.5
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• pp.635-644
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• 2023

The design of honeycomb sandwich structures is often challenging because these structures can be tailored from a variety of possible cores and face sheets configurations, therefore, the design of sandwich structures is characterized as a time-consuming and complex task. A data-driven computational approach that integrates the analytical method and Artificial Neural Network (ANN) is developed by the authors to rapidly predict the design of sandwich structures for a targeted maximum structural deflection. The elaborated ANN reverse design approach is applied to obtain the thickness of the sandwich core, the thickness of the laminated face sheets, and safety factors for composite sandwich structure. The required data for building ANN model were obtained using the governing equations of sandwich components in conjunction with the Monte Carlo Method. Then, the functional relationship between the input and output features was created using the neural network Backpropagation (BP) algorithm. The input variables were the dimensions of the sandwich structure, the applied load, the core density, and the maximum deflection, which was the reverse input given by the designer. The outstanding performance of reverse ANN model revealed through a low value of mean square error (MSE) together with the coefficient of determination (R2) close to the unity. Furthermore, the output of the model was in good agreement with the analytical solution with a maximum error 4.7%. The combination of reverse concept and ANN may provide a potentially novel approach in designing of sandwich structures. The main added value of this study is the elaboration of a reverse ANN model, which provides a low computational technique as well as savestime in the design or redesign of sandwich structures compared to analytical and finite element approaches.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.233-239
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• 2022

The injection molding process is a process in which thermoplastic resin is heated and made into a fluid state, injected under pressure into the cavity of a mold, and then cooled in the mold to produce a product identical to the shape of the cavity of the mold. It is a process that enables mass production and complex shapes, and various factors such as resin temperature, mold temperature, injection speed, and pressure affect product quality. In the data collected at the manufacturing site, there is a lot of data related to good products, but there is little data related to defective products, resulting in serious data imbalance. In order to efficiently solve this data imbalance, undersampling, oversampling, and composite sampling are usally applied. In this study, oversampling techniques such as random oversampling (ROS), minority class oversampling (SMOTE), ADASYN(Adaptive Synthetic Sampling), etc., which amplify data of the minority class by the majority class, and complex sampling using both undersampling and oversampling, are applied. For composite sampling, SMOTE+ENN and SMOTE+Tomek were used. Artificial neural network techniques is used to predict product quality. Especially, MLP and RNN are applied as artificial neural network techniques, and optimization of various parameters for MLP and RNN is required. In this study, we proposed an SA technique that optimizes the choice of the sampling method, the ratio of minority classes for sampling method, the batch size and the number of hidden layer units for parameters of MLP and RNN. The existing sampling methods and the proposed SA method were compared using accuracy, precision, recall, and F1 Score to prove the superiority of the proposed method.

• Journal of Microbiology and Biotechnology
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• v.33 no.2
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• pp.260-267
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• 2023

In this study, we sought to improve lutein and zeaxanthin production in Mychonastes sp. 247 and investigated the effect of environmental factors on lutein and zeaxanthin productivity in Mychonastes sp. The basic medium selection and N:P ratio were adjusted to maximize cell growth in one-stage culture, and lutein and zeaxanthin production conditions were optimized using a central composite design for two-stage culture. The maximum lutein production was observed at a light intensity of 60 μE/m²/s and salinity of 0.49%, and the maximum zeaxanthin production was observed at a light intensity of 532 μE/m²/s and salinity of 0.78%. Lutein and zeaxanthin production in the optimized medium increased by up to 2 and 2.6 folds, respectively, compared to that in the basic medium. Based on these results, we concluded that the optimal conditions for lutein and zeaxanthin production are different and that optimization of light intensity and culture salinity conditions may help increase carotenoid production. This study presents a useful and potential strategy for optimizing microalgal culture conditions to improve the productivity of lutein and zeaxanthin, which has applications in the functional food field.

• Steel and Composite Structures
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• v.42 no.5
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• pp.633-647
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• 2022

This paper presents the results from reliability analyses of the current Eurocode 4 (EN 1994-1-1) and AISC 360-16 design models for predicting the resistance of headed stud shear connectors within profiled steel sheeting, when the ribs are oriented transverse to the supporting beam. For comparison purposes, the performance of the alternative "Luxembourg" and "Stuttgart" model were also considered. From an initial database of 611 push-out tests, 269 cases were included in the study, which ensured that the results were valid over a wide range of geometrical and material properties. It was found that the current EN 1994-1-1 design rules deliver a corrected partial safety factor γ_M^* of around 2.0, which is significantly higher than the target value 1.25. Moreover, 179 tests fell within the domain of the concrete-related failure design equation. Notwithstanding this, the EN 1994-1-1 equations provide satisfactory results for re-entrant profiled sheeting. The AISC 360-16 design equation for steel failure covers 263 of the tests in the database and delivers 𝛾_M^*≈2.0. Conversely, whilst the alternative "Stuttgart" model provides an improvement over the current codes, only a corrected partial safety factor of 𝛾_M^*=1.47 is achieved. Finally, the alternative "Luxembourg" design model was found to deliver the required target value, with a corrected partial safety factor 𝛾_M^* between 1.21 and 1.28. Given the fact that the Luxembourg design model is the only model that achieved the target values required by EN 1990, it is recommended as a potential candidate for inclusion within the second generation of Eurocodes.

• Steel and Composite Structures
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• v.47 no.6
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• pp.743-757
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• 2023

In this paper, the dynamic response of a simply-supported composite sandwich plate with a viscoelastic core based on the Golla-Hughes-McTavish (GHM) viscoelastic model is investigated analytically. The formulation is developed using the three-layered sandwich panel theory. Hamilton's principle has been employed to derive the equations of motion. Since classical models, like kelvin-voigt and Maxwell models, cannot express a comprehensive description of the dynamic behavior of viscoelastic material, the GHM method is used to model the viscoelastic core of the plate in this research. The main advantage of the GHM model in comparison with classical models is the consideration of the frequency-dependent characteristic of viscoelastic material. Identification of the material parameters of GHM mini-oscillator terms is an essential procedure in applying the GHM model. In this study, the focus of viscoelastic modeling is on the development of GHM parameters identification. For this purpose, a new method is proposed to find these constants which express frequency-dependent behavior characterization of viscoelastic material. Natural frequencies and loss factors of the sandwich panel based on ESL and three-layered theories in different geometrics are described at 30℃ and 90℃; also, the comparisons show that obtained natural frequencies are grossly overestimated by ESL theory. The argumentations of differences in natural frequencies are also illustrated in detail. The obtained results show that the GHM model presents a more accurate description of the plate's dynamic response by considering the frequency dependency behavior of the viscoelastic core.

• Steel and Composite Structures
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• v.46 no.3
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• pp.367-383
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• 2023

In this investigation, an improved integral trigonometric shear deformation theory is employed to examine the vibrational behavior of the functionally graded (FG) sandwich plates resting on visco-Pasternak foundations. The studied structure is modelled with only four unknowns' variables displacements functions. The simplicity of the developed model being in the reduced number of variables which was made with the help of the use of the indeterminate integral in the formulation. The current kinematic takes into consideration the shear deformation effect and does not require any shear correction factors as used in the first shear deformation theory. The equations of motion are determined from Hamilton's principle with including the effect of the reaction of the visco-Pasternak's foundation. A Galerkin technique is proposed to solve the differentials governing equations, which enables one to obtain the semi-analytical solutions of natural frequencies for various clamped and simply supported FG sandwich plates resting on visco-Pasternak foundations. The validity of proposed model is checked with others solutions found in the literature. Parametric studies are performed to illustrate the impact of various parameters as plate dimension, layer thickness ratio, inhomogeneity index, damping coefficient, vibrational mode and elastic foundation on the vibrational behavior of the FG sandwich plates.

• Journal of Aerospace System Engineering
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• v.17 no.2
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• pp.62-70
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• 2023

We proposed a technique for predicting Stress-Life (S-N) curve or fatigue life using geometric features of a ply-overlap joint structure in which plies of two composite materials are partially or wholly laminated and bonded. Geometric features that could affect fatigue properties of a structure were selected as variables. By analyzing relationships between geometric variables and material constants of the Epaarachchi-Clausen model, a fatigue model for composites, relational expressions of these two factors were proposed. To verify the prediction accuracy of the proposed method, fatigue life of a CFRP/GFRP ply-overlap joint was predicted. Predicted life and life obtained by test data-based model were compared to actual life. High prediction accuracy was confirmed by calculating the coefficient of determination of the predicted S-N curve.

• Computers and Concrete
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• v.32 no.1
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• pp.75-85
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• 2023

This work utilizes simplified higher-order shear deformation beam theory (HSDBT) to investigate the vibration response for functionally graded carbon nanotube-reinforced composite (CNTRC) beam. Novel to this work, single-walled carbon nanotubes (SWCNTs) are distributed and aligned in a matrix of polymer throughout the beam, resting on a viscoelastic foundation. Four un-similar patterns of reinforcement distribution functions are investigated for the CNTRC beam. Porosity is another consideration taken into account due to its significant effect on functionally graded materials (FGMs) properties. Three types of uneven porosity distributions are studied in this study. The damping coefficient and Winkler's and Pasternak's parameters are considered in investigating the viscosity effect on the foundation. Moreover, the impact of different parameters on the vibration of the CNTRC beam supported by a viscoelastic foundation is discussed. A comparison to other works is made to validate numerical results in addition to analytical discussions. The findings indicate that incorporating a damping coefficient can improve the vibration performance, especially when the spring constant factors are raised. Additionally, it has been noted that the fundamental frequency of a beam increases as the porosity coefficient increases, indicating that porosity may have a significant impact on the vibrational characteristics of beams.