In this paper, recommended spiral passive micromixer was designed and simulated. spiral design has the potential to create and strengthen the centrifugal force and the secondary flow. A series of simulations were carried out to evaluate the effects of channel width, channel depth, the gap between loops, and flowrate on the micromixer performance. These features impact the contact area of the two fluids and ultimately lead to an increment in the quality of the mixture. In this study, for the flow rate of 25 μl/min and molecular diffusion coefficient of 1×10-10 m2/s, mixing efficiency of more than 90% is achieved after 30 (approximately one-third of the total channel length). Finally, the optimized design fabricated using proposed 3D printing method.

Application of the network equivalent concept for external system representation for power system transient analysis is well known. However, the challenge to utilize an equivalent network, approximated by a rational function, is to guarantee the passivity of the corresponding model. In this regard, special techniques are required to enforce the passivity of the equivalent model through a post processing approach that minimizes its impact on the original model characteristics. In this paper, the passivity is enforced by expressing the problem in terms of a convex Optimization problem that guarantees the global optimal solution. The convex Optimization problem is efficiently solved by recently developed numerical interior–point methods. This passivity enforcement is also global which indicates that the passivity enforcement in one region does not lead to passivity violation in other regions.

Topology Optimization has emerged as a critical tool in engineering design, enabling the creation of highly efficient and innovative structures across various industries. This review provides a comprehensive synthesis of the current state of topology Optimization, focusing on its Computational methods and practical applications in engineering design. The article discusses the foundational role of the Finite Element Method (FEM) in topology Optimization and explores the distinctions between gradient-based and gradient-free Optimization methods. It also delves into recent advancements in multi-scale and multi-physics topology Optimization, which represent the cutting edge of research in this field. The practical applications of topology Optimization are examined in detail, with specific focus on its impact in aerospace, automotive, civil, and biomedical engineering, as well as in the energy sector. The review highlights how topology Optimization has revolutionized design practices by reducing material usage, enhancing structural performance, and enabling the development of innovative solutions across diverse engineering challenges. Finally, the article identifies key areas for future research, including the integration of topology Optimization with emerging manufacturing technologies and the development of more efficient Computational methods. This review serves as a valuable resource for researchers and practitioners, providing insights into both the current applications and the future potential of topology Optimization in engineering design.

In this paper, one-dimensional numerical Optimization of lead-acid battery with finite-volume method is performed using the governing equations of battery dynamics. For validation, the present results are compared with previous studies which show good agreement. The demand for batteries with high energy and power has increased due to their use in hybrid vehicles. The major shortcoming of lead-acid batteries in industry is low energy and high weight; therefore, a cell with higher energy and lower thickness is designed by using particle swarm Optimization based on developed simulation code, which is less time consuming and much faster than experimental method. The results of Optimization show that an optimal battery that has 85 percent higher energy can be made with the same cell length. The results also show that an optimum cell battery can be obtained with a 25 percent decrease in weight and 23 percent in dimensions while keeping the energy content constant.

In the present study, the Large Eddy Simulation (LES) turbulence closure is applied for the fi rst time, to the best of our knowledge, to investigate the viability of air conditioning systems in a large space. The results of LESs were validated against experimental measurements and the model was used to study the effect of different design variables including Air Changes per Hour (ACH), supply temperature, and return air vent height on design objectives such as local and global thermal comfort indexes and energysaving parameter by using a systematic multi-objective Optimization approach. Sensitivity analysis showed that global and local thermal comfort indexes were highly sensitive to the air supply temperature, while energy saving was sensitive to ACH and the supply temperature to the same extent. In addition, it was found that height of the return air vent affected energy saving more than other factors. Finally, an energy saving rate of 22. 9% along with thermal comfort indexes within the allowable range is achievable by using the best design through the multi-objective Optimization.

This paper attempts to improve the Computational efficiency of the well known particle swarm Optimization (PSO) algorithm for tackling discrete sizing Optimization problems of steel frame structures. It is generally known that, in structural design Optimization applications, PSO entails enormously time-consuming structural analyses to locate an optimum solution. Hence, in the present study it is attempted to lessen the Computational effort of the algorithm, using the so called upper bound strategy (UBS), which is a recently proposed strategy for reducing the total number of structural analyses involved in the course of design Optimization. In the UBS, the key issue is to identify those candidate solutions which have no chance to improve the search during the optimum design process. After identifying those non-improving solutions, they are directly excluded from the structural analysis stage, diminishing the total Computational cost. The performance of the UBS integrated PSO algorithm (UPSO) is evaluated in discrete sizing Optimization of a real scale steel frame to AISC-LRFD specifications. The numerical results demonstrate that the UPSO outperforms the original PSO algorithm in terms of the Computational efficiency.