This paper presents the optimization of an inductive displacement transducer or linear variable differential transformer (LVDT). The method integrates design software (SolidWorks 2023), simulation tools (COMSOL Multiphysics), and MATLAB. The optimization phase utilizes the non-dominated sorting genetic algorithm (NSGA)-II and -III to fine-tune the geometry configuration by adjusting six inner parameters corresponding to the dimension of the interior components of the LVDT, thus aiming to improve the overall performance of the device. The outcomes of this study reveal a significant achievement in LVDT enhancement. By employing the proposed methodology, the operational range of the LVDT was effectively doubled, extending it from its initial 8 (mm) to 16 (mm). This expansion in the operational range was achieved without compromising measurement accuracy, as all error values for the working range of 0–16 (mm) (NSGA-II with a maximum final relative error of 2.22% and NSGA-III with 2.44%) remained below the imposed 3% limit. This research introduces a new concept in LVDT optimization, capitalizing on the combined power of NSGA-II and NSGA-III algorithms. The integration of these advanced algorithms, along with the interconnection between design, simulation, and programming tools, distinguishes this work from conventional approaches. This study fulfilled its initial objectives and generated quantifiable results. It introduced novel internal configurations that substantially improved the LVDT’s performance. These achievements underscore the validity and potential of the proposed methodology in advancing LVDT technology, with promising implications for a wide range of engineering applications.

Understanding the effect of different electric potentials upon the preferential formation of biofilms inside microfluidic devices could represent a step forward in comprehending the mechanisms that govern biofilm formation and growth. 3D printed microfluidic devices were used to investigate the influence of the dielectrophoretic forces on the formation and growth of Staphylococcus aureus ATCC 25923 biofilms. Bacterial suspensions of 2.5 McF were pushed through microfluidic channels while simultaneously applying various potential differences between 10 and 60 V. The overall electric field distribution within the channel was simulated using the COMOSL software. The effect of the electric potential variation on the preferential biofilm formation was determined using an adjusted microtiter plate technique, as well as a qualitative method, Scanning Electron Microscopy (SEM). SEM images were used to describe the morphology of the biofilm surface. The conclusions show that the dielectrophoretic forces, resulting due to inhomogeneity of the electric field, have more visible effects upon the cells up to 40 V. Above this magnitude, due to a more homogenous distribution of the electric field, the formation and growth of the biofilm become more uniform. At around 60 V, the distance between the high electric gradient regions decreases, leading to an almost uniform distribution of the electric field and, therefore, to a shift from dielectrophoretic to electrophoretic forces acting upon the bacterial cells.

This paper presents two optimization methods of an interior permanent magnetic motor (IPM). The first method is based on the non-dominated sorting genetic algorithm II (NSGA-II), while the second one is based on the NSGA-III algorithm. The focus is on the reduction of the cogging torque (CT), which acts upon the rotor when the IPM is not powered, and the current that flows through the three windings is 0. The influence of the CT over the motor operation is a negative one, inducing vibrations that are not desired. The limitation of these influences is the desired way for improvement. The optimizations applied entailed the change of the geometrical configuration of the stator whilst maintaining the exterior dimensions unaltered. Through this simple but robust approach, the performance of the IPM proposed was improved.