Based on Gauss’ law for the electric field, new formulas were deduced, that enable for the first time the writing of an analytical formula of the built-in potential of implanted and diffused semiconductor junctions. Consequently, in this work is devised a measurement technique for the built-in potential of such junctions. Such measurement is useful because new semiconductor materials besides silicon are more and more used today, like silicon-carbide (SiC) and gallium-nitride (GaN), which have larger bandgap and junction built-in potential. Finding the built-in potential helps adjusting the computer assisted design (CAD) tools and validates the simulation of such wide-bandgap devices.
In this work, we present a new fuzzy second-order sliding mode controller (FSOSMC) for wind power transformation system based on a doubly-fed induction generator (DFIG) using intelligent space vector pulse width modulation (SVPWM). The proposed command strategy combines a fuzzy logic and a second order sliding mode control (SOSMC) for the DFIG command. This strategy presents attractive features such as chattering-free, compared to the conventional first and second order sliding mode techniques. The use of this method provides very satisfactory performance for the DFIG command. The effectiveness of this command strategy is proven through the simulation results.
To establish an exercise in open muscular chain rehabilitation (OMC), it is necessary to choose the type of kinematic chain of the mechanical / biomechanical system that constitutes the lower limbs in interaction with the robotic device. Indeed, it’s accepted in biomechanics that a rehabilitation exercise in OMC of the lower limb is performed with a fixed hip and a free foot. Based on these findings, a kinematic structure of a new machine, named Reeduc-Knee, is proposed, and a mechanical design is carried out. The contribution of this work is not limited to the mechanical design of the Reeduc-Knee system. Indeed, to define the minimum parameterizing defining the configuration of the device relative to an absolute reference, a geometric and kinematic study is presented.
This work is about the validation of a Common Rail (CR) injector model. The model describes injector internal behavior in a detailed way, validation is done using dosage measurements and needle lift traces.
The model contains fluid dynamic, mechanic and electro-magnetic parts describing all important internal processes. To compare the modelling results against measurement data, three test cases were chosen on a medium duty test engine to represent a wide range of operation points. Dosage measurements were done by averaging the injected mass of 1500 injections, each measurement repeated three times. Needle displacement was measured using an injector equipped with a needle lift sensor in the same operating points. The results of the simulated injector and the measured values showed good conformity both in needle displacement and injected fuel mass, so the model can be a basis for further injector and combustion analyses.
Automation of industrial activities aims to improve the efficiency of the productive processes while reducing costs and increasing safety. In industrial laundries, detergent management is a key factor that can lead to severe economic and environmental impacts if left uncontrolled. This paper documents the solution devised for an integrated detergent control and supervision system based on Internet-of Things paradigms. This solution follows from a problem put forward by the laundry services of Santa Casa da Misericórdia de Bragança, located in Portugal, to the Polytechnic Institute of Bragança. In order to keep track of the detergent in a centralised dispensing system, a Wi-Fi based measurement system was developed which enables real-time monitoring of the chemicals level. In order to facilitate the physical installation of the developed hardware, a custom-made enclosure was designed and 3D printed. The acquired data is then sent to a database connected to a data processing web-based platform which is responsible for the analytics.
Development of increasingly efficient production methods is a competiveness driving factor for any company. Today, many of these improvements include the integration of technology-based solutions into processes traditionally operated by humans. In this context, the present work aims to report the controller performance of a prototype developed for semi-automatic sewing stations. This project was fostered by “Factory Play”, a Portuguese company that produces inflatable structures, under the technical supervision of the Polytechnic Institute of Bragança. At the present time, the sewing station travel speed is regulated by an embedded PID controller that has been previously tuned using classical methods. However, even if the overall performance is currently acceptable, additional experiments were made regarding the use of evolutionary based algorithms to attain a better dynamic response and flexibility. This article present the results obtained using those methods where it is possible to confirm that the use of evolutionary algorithm will simplify the design process while consistently leading to a suitable solution.
Machine-learning techniques allow to extract information from electroencephalographic (EEG) recordings of brain activity. By processing the measurement results of a publicly available EEG dataset, we were able to obtain information that could be used to train a feedforward neural network to classify two types of volunteer activities with high efficiency.
Electrostatic actuators have major role in many MEMS devices, e.g. sensors, actuators. The amount of applied voltage to an electrostatic micro-actuator has a direct impact on the amplitude of deflection throughout the cantilever. This research aims to study the effect of the electrode length and the applied voltage on the amplitude of deflection of the micro-cantilever. Also, the resonant frequency for the cantilever was computed for full length and compared with simulation results. Finite element method, ANSYS was used as a simulation tool.
In this paper, the earlier formulation of the eight-node hexahedral SFR8 element is extended in order to analyze material nonlinearities. This element stems from the so-called Space Fiber Rotation (SFR) concept which considers virtual rotations of a nodal fiber within the element that enhances the displacement vector approximation. The resulting mathematical model of the proposed SFR8 element and the classical associative plasticity model are implemented into a Fortran calculation code to account for small strain elastoplastic problems. The performance of this element is assessed by means of a set of nonlinear benchmark problems in which the development of the plastic zone has been investigated. The accuracy of the obtained results is principally evaluated with some reference solutions.
The paper presents a four-node tetrahedral solid finite element SFR4 with rotational degrees of freedom (DOFs) based on the Space Fiber Rotation (SFR) concept for modeling three-dimensional solid structures. This SFR concept is based on the idea that a 3D virtual fiber, after a spatial rotation, introduces an enhancement of the strain field tensor approximation. Full numerical integration is used to evaluate the element stiffness matrix. To demonstrate the efficiency and accuracy of the developed four-node tetrahedron solid element and to compare its performance with the classical four-node tetrahedral element, extensive numerical studies are presented.