In this work, an ultrasound experimental setup was designed to investigate the feasibility of using low-frequency ultrasonic waves as a substitute to reduce the consumption of chemical demulsifiers in the pretreatment of crude oil. The experiments were planned to study the effects of irradiation time, ultrasonic field intensity and initial water content on the efficiency of separation. The results of experiments showed that by selecting a proper irradiation time and field intensity, it is possible to decrease the usage of demulsifiers by 50%. Moreover, a population balance model was proposed to explicate the experimental data. A hybrid coalescence model was developed to determine the frequency of aggregation. The parameters of the model were estimated by linear regression. The parameter estimation was performed using a parallel execution of the particle swarm optimization algorithm. The results of the model showed a decent agreement with the experimental data.
Magnetorheological dampers have been used in automotive industry and civil engineering applications for shock and vibration control for some time. While such devices are known to provide reliable shock and vibration suppression, there exist emerging applications in which the magnetorheological dampers have to be optimized in terms of power consumption and overall weight (e.g. energy-efficient electric vehicles). Utilizing traditional optimal design approaches to tackle those issues can sometimes lead to convergence problems such as getting trapped in a local extremum and failing to converge to the global optimum. Furthermore, manufacturing limitations are usually not taken into account in the optimization process which may hamper achieving an optimal design. In this article, we present a method for optimal design of magnetorheological dampers by utilizing mathematical optimization and finite element analysis. The proposed method avoids infeasible solutions by considering physical constraints such as fabrication limitations and tolerances. This approach takes every single feasible solution into account so that the final solution would be the global extremum of the optimization cost function. The proposed approach is applied to optimize a complex magnetorheological damper structure with different types of materials such as steel and AlNiCo. In particular, we present the design of a valve-mode magnetorheological damper with AlNiCo integrated as its core. A magnetorheological damper prototype is manufactured based on the proposed optimization method and tested experimentally.
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