This research work explores the thermal and mass transport phenomena for a time-dependent Maxwell fluid flow in the presence of Cattaneo–Christov concept. The Maxwell fluid flow is analyzed through a stretching cylinder and sheet. Brownian motion, non-uniform heat source/sink, thermophoresis, and variable thermal conductivity are operated in this study. A theoretical analysis of the modeled system of equations is explored with the help of HAM. Impacts of fixed constraints on velocity, thermal, and concentration functions are offered graphically. It is concluded that the velocity profile heightens quickly for Newtonian fluid equated to non-Newtonian fluid (Maxwell) via curvature parameter while the temperature and concentration distributions increase quickly for non-Newtonian fluid as equated to the Newtonian fluid via curvature parameter. The presence of Maxwell and magnetic parameters increases the size of the trapping bolus.

Permutation flow-shop scheduling is the strategy that ensures the processing of jobs on each subsequent machine in the exact same order while optimizing an objective, which generally is the minimization of makespan. Because of its NP-Complete nature, a substantial portion of the literature has mainly focused on computational efficiency and the development of different AI-based hybrid techniques. Particle Swarm Optimization (PSO) has also been frequently used for this purpose in the recent past. Following the trend and to further explore the optimizing capabilities of PSO, first, a standard PSO was developed during this research, then the same PSO was hybridized with Variable Neighborhood Search (PSO-VNS) and later on with Simulated Annealing (PSO-VNS-SA) to handle Permutation Flow-Shop Scheduling Problems (PFSP). The effect of hybridization was validated through an internal comparison based on the results of 120 different instances devised by Taillard with variable problem sizes. Moreover, further comparison with other reported hybrid metaheuristics has proved that the hybrid PSO (HPSO) developed during this research performed exceedingly well. A smaller value of 0.48 of ARPD (Average Relative Performance Difference) for the algorithm is evidence of its robust nature and significantly improved performance in optimizing the makespan as compared to other algorithms.

This paper proposes a multi-scale analysis technique based on the micromechanics of failure (MMF) to predict and investigate the damage progression and ultimate strength at failure of laminated composites. A lamina’s representative volume element (RVE) is developed to predict and calculate constituent stresses. Damages that occurred in the constituents are calculated using separate failure criteria for both fiber and matrix. Subsequently, the volume-based damage homogenization technique is utilized to prevent the localization of damage throughout the total matrix zone. The proposed multiscale analysis procedure is then used to investigate the notched and unnotched behavior of three multi-directional composite layups, [30, 60, 90, −60, 30]_2S, [0, 45, 90, −45]_2S, and [60, 0, −60]_3S, subjected to static tension and compression loading. The specimen is fabricated from unidirectionally reinforced composite (IM7/977-3). The prediction of ultimate strength at failure and equivalent stiffness are then benchmarked against the experimental test data. The comparative analysis with various failure models is also carried out to validate the proposed model. MMF demonstrated the capability to correctly predict the ultimate strength at failure for a range of multidirectional composites laminates under tensile and compressive load. The numerically predicted findings revealed a good agreement with the experimental test data. Out of the three investigated composite layups, the simulated results for the quasi-isotropic [0, 45, 90, −45]_2S layup agreed extremely well with the experimental results with all the percentage errors within 10% of the measured failure loads.