Waleed Fekry Faris

Enhancing the efficiency of polymerase chain reaction using graphene nanoflakes

The effect of the recently developed graphene nanoflakes (GNFs) on the polymerase chain reaction (PCR) has been investigated in this paper. The rationale behind the use of GNFs is their unique physical and thermal properties. Experiments show that GNFs can enhance the thermal conductivity of base fluids and results also revealed that GNFs are a potential enhancer of PCR efficiency; moreover, the PCR enhancements are strongly dependent on GNF concentration. It was found that GNFs yield DNA product equivalent to positive control with up to 65% reduction in the PCR cycles. It was also observed that the PCR yield is dependent on the GNF size, wherein the surface area increases and augments thermal conductivity. Computational fluid dynamics (CFD) simulations were performed to analyze the heat transfer through the PCR tube model in the presence and absence of GNFs. The results suggest that the superior thermal conductivity effect of GNFs may be the main cause of the PCR enhancement.

Vehicle Fuel Consumption and Emission Modelling: An In-Depth Literature Review

Modelling of vehicle fuel consumption and emissions has emerged as an effective tool to help develop and assess vehicle technologies and to help predict vehicle fuel consumption and emissions. A review to identify the current state-of-the-art on vehicle fuel consumption and emissions modelling is elucidated. This review categorises vehicle fuel consumption and emissions models into five classifications. The relevant main models to each of these classifications are presented. These models are then compared with regard to assumptions, limitations, merits, drawbacks, characteristic parameters, data collection techniques, accuracy, and relevance to road traffic. The study demonstrates that the trends of vehicle fuel consumption and emissions provided by current models generally do satisfactorily replicate field data trends. In addition, the paper demonstrates that mesoscopic models, empirical models, mean value-based models, and quasi dimensional models strike a balance between accuracy and simplicity and thus are very suitable for transportation and control applications. The study shows as well that no one model as yet fully meets the needs of transportation applications.

Simple Vehicle Powertrain Model for Modeling Intelligent Vehicle Applications

This research develops a simple vehicle powertrain model that can be incorporated within microscopic traffic simulation software for the modeling of intelligent vehicle applications. This simple model can be calibrated using vehicle parameters that are publically available without the need for field data collection. The model uses the driver throttle level input to compute the engine speed and, subsequently, the engine torque and power to finally compute the vehicle acceleration, speed, and position. The model is tested using field measurements and is demonstrated to produce vehicle power, fuel consumption, acceleration, speed, and position estimates that are consistent with field observations.

Design of robust H ∞ , fuzzy and LQR controller for active suspension of a quarter car model

In this paper design of active suspension in a quarter car model is presented. The idea of suspension is to improve the ride quality while maintaining good handling characteristics to different road disturbance. The purpose of designing the active controller for vehicle suspension systems is to decrease the traditional design between ride and handling by directly controlling the suspension forces to suit the road and driving conditions. The presented approach uses linear controller that does not require physical model of shock absorber or the car which is time consuming to derive and implement. Performance of active suspensions like robust H∞ controller, LQR controller and Fuzzy control are compared with existing passive suspension. Simulation result shows that the active controllers are better than passive in terms of settling time.

Dynamic Modal Analysis of Vertical Machining Centre Components

The paper presents a systematic procedure and details of the use of experimental and analytical modal analysis technique for structural dynamic evaluation processes of a vertical machining centre. The main results deal with assessment of the mode shape of the different components of the vertical machining centre. The simplified experimental modal analysis of different components of milling machine was carried out. This model of the different machine tools structure is made by design software and analyzed by finite element simulation using ABAQUS software to extract the different theoretical mode shape of the components. The model is evaluated and corrected with experimental results by modal testing of the machine components in which the natural frequencies and the shape of vibration modes are analyzed. The analysis resulted in determination of the direction of the maximal compliance of a particular machine component.

Dynamics and control policies analysis of semi-active suspension systems using a full-car model

Several control policies of semi-active systems, namely skyhook, groundhook and hybrid controls, are presented. Their ride comfort, suspension displacement and road-holding performances are analysed and compared with passive systems. The analysis covers both transient and steady-state responses in the time domain and transmissibility response in the frequency domain. The results show that the hybrid control policy yields better comfort than a passive suspension, without reducing the road-holding quality or increasing the suspension displacement for typical passenger cars. The hybrid control policy is also shown to be a better compromise between comfort, roadholding and suspension displacement than the skyhook and groundhook control policies.

A comparative ride performance and dynamic analysis of passive and semi-active suspension systems based on different vehicle models

Vehicle models used to evaluate performance and dynamic behaviour are either discrete models, which includes quarter, half, and full car models, or continuous models using finite element modelling. In this work our focus will be on discrete models, which have more popularity with ground vehicle analysts owing to their shorter computational time and lower cost compared with continuous models. In this paper, ride comfort, suspension displacement and road-holding performances are compared for three different models – quarter (Q), half (H) and full (F) car models. In each model, semi-active system controls, namely skyhook, groundhook and hybrid controls, are used along with the conventional passive system. The analysis covers both transient and steady-state responses in the time domain and transmissibility response in the frequency domain. Results show that while the responses give generally the same trend, the simpler model gives significantly higher responses.

Analysis of control policies and dynamic response of a Q-car 2-DOF semi active system

Several control policies of Q-car 2-DOF semiactive system, namely skyhook, groundhook and hybrid controls are presented. Their ride comfort, suspension displacement and road-holding performances are analyzed and compared with passive system. The analysis covers both transient and steady state responses in time domain and transmissibility response in frequency domain. The results show that the hybrid control policy yields better comfort than a passive suspension, without reducing the road-holding quality or increasing the suspension displacement for typical passenger cars. The hybrid control policy is also shown to be a better compromise between comfort, road-holding and suspension displacement than the skyhook and groundhook control policies.

Ride Comfort Performance of a Vehicle Using Active Suspension System with Active Disturbance Rejection Control

Active disturbance rejection control (ADRC) for a quarter-car active suspension system is proposed. The performance of ADRC is compared with benchmark (LQR control) from current literature. A simulation experiment is performed to investigate the performance of ADRC in comparison with passive system and the LQR control, as well as to test the ability of ADRC to cope with varying process. Results show that ADRC performs better than the benchmark control and is able to cope with varying process commonly seen in active suspension system.

Active engine mounting control algorithm using neural network

This paper proposes the application of neural network as a controller to isolate engine vibration in an active engine mounting system. It has been shown that the NARMA-L2 neurocontroller has the ability to reject disturbances from a plant. The disturbance is assumed to be both impulse and sinusoidal disturbances that are induced by the engine. The performance of the neural network controller is compared with conventional PD and PID controllers tuned using Ziegler-Nichols. From the result simulated the neural network controller has shown better ability to isolate the engine vibration than the conventional controllers.