Journal of Engineering Research最新文献

The present study focuses on the influence of the strengthening grinding process (SGP) on the corrosion resistance of CSS-42 L alloy. To this end, the surface and cross-sectional characteristics of samples before and after SGP treatment were examined. In this regard, the surface morphology, roughness, microstructure, and phase content were analyzed. The results demonstrate a dense surface layer and a high surface roughness in SGP-treated samples. Through electrochemical and salt spray tests, it is confirmed that SGP treatment for 3 and 6 min improves the corrosion resistance of samples. It was found that the highest corrosion resistance can be achieved after SGP treatment for 6 min. The enhanced corrosion resistance of the SGP-treated samples originates from the synergistic effects of various factors, including surface roughness, dislocation density, the presence of compressive residual stress, the precipitation of Cr-phases, and the deformation of a dense surface layer.

The accurate design of the shell-and-tube heat exchanger (STHE) model is crucially important for industries such as process industries, oil refining, thermic devices, and power plants. However, determining its parameters is a challenging task due to the multimodality and nonlinearity of the cost function. Due to such nature, performing algorithms face the challenges of sluggish convergence speed and the proneness to local optima, making it difficult to reach satisfactory solutions. In line with the above challenges, this paper aims to contribute by developing an improved optimization algorithm that can effectively deal with such optimization issues. The proposed algorithm, named Levy-Opposition- Equilibrium Optimizer (LOEO), combines the Equilibrium Optimizer (EO) and the strategies of opposition learning (OL) and Levy flight learning (LFL) to overcome the dilemma of early convergence and getting trapped in local optima. It does this by employing the OL and LFL strategies after performing the EO phase to explore the search space in opposite directions and exploit the search space by means of the Levy distribution pattern, respectively. The proposed LOEO approach aims to enhance the algorithm's ability (provides enhanced exploration capability, effective search space exploitation, and enhanced convergence speed) and reach higher quality solutions to optimization problems. To assess the performance of the suggested LOEO, three stages of analysis are carried out. In the first stage, the performance of the proposed algorithm is investigated on some benchmark problems, including CEC 2005 and CEC 2020, using statistical verifications, convergence behavior, and the boxplot paradigm. The second stage involves the non-parametric Friedman test to assess the significance of results, where the results indicate that the LOEO outperforms the best existing one (equilibrium whale optimization algorithm (EWOA)) by an average rank of the Friedman test greater than 28% for CEC 2005 benchmark functions while outperforming enhanced EO (EEO) by 24% for CEC 2020. Finally, the LOEO's applicability is realized through determining the optimal design structure of the STHE model. The reported results indicate that the LOEO algorithm offers accurate performance compared to competing algorithms as it saves the cost of the device by 39.81% compared to the best existing results, and thus, it is commended to adopt for new applications.

Mechanical and microstructure properties of weld joint between mild steel plates before and after heat treatment process have been studied. In this study, electric arc welding was used as a welding method as it is the most common welding method. Then heat treatment of the samples were done in the furnace. Firstly, in the heat treatment process, stress annealing was done as stress generated at different places in the welding zone and after that full annealing was done using furnace cooling for cooling purpose. Tensile strength was measured using ASTM A370 standard specimen and Brinell hardness test was done at different surfaces of the welding zone. The microstructures were observed by cutting the specimen in a certain shape, and mirror surfaces were generated to observe in electron microscope. From the results, it was observed that PWHT causes a 4.1 % increase in tensile strength, a 13.84 % gain in yield strength, and a 4.96 % rise in percentage elongation. However, the value of hardness decreased 19.19 % after heat treatment as heat treatment increased the ductility of the specimen. At the place of the Electric Arc Welding joint, a smaller grain size, a lower gap between the grains, and comparatively few voids were identified.

Public and private sector organizations continually seek to optimize strategies for sustained competitiveness by reallocating resources efficiently among various institutions. This research introduces a non-radial resource reallocation model employing network data envelopment analysis to address this need. The study introduces an approach to redistributing resources in a dynamic network setting over multiple periods. It takes into account indicators of both negative outcomes, aiming to improve the overall effectiveness and efficiency of companies within a holding structure. The research outlines a methodology, including data collection, modeling assumptions, decision variables, and constraints for implementing this reallocation model. By focusing on resource allocation in network systems over periods, this study provides a solid foundation for enhancing resource allocation efficiency in organizations. Additionally, it addresses the complexities associated with resource allocation compared to settings. The proposed dynamic network DEA model considers both temporal aspects in evaluations. Demonstrates its potential for resource allocation in multi-stage processes through applications within the banking industry. One key finding is the importance of recognizing shared constraints among Decision Making Units (DMUs). Considering the impact of restrictions, like government regulations, on decision-making processes and overall efficiency. The created dynamic network DEA model introduces an inventive method to redistribute resources in intricate organizational setups. It offers perspectives for decision-making procedures. Moreover, it sets the stage for further exploration into different indicators and the impact of diverse government interventions on resource allocation effectiveness.