A Magneto-Rheological (MR) fluid disc brake is a device that transmits a torque by the shear force of MR fluid. The fluid is inserted between the rotating and fixed discs and a magnetic field is imposed on the fluid. In this paper, a complete test rig for an MR fluid disc brake is introduced. Experiments are conducted to measure the braking torque and speed of shaft during braking process and the results are presented at different voltage input to the brake. Also theoretical analysis for both MR brake and the mechanical system is developed and is solved numerically using finite difference method and Matlab software. Effect of current input to the MR brake, viscosity of fluid and design parameters is taken into consideration. A validation of the theoretical results with CFD model is introduced. The experimental results are performed and both angular velocity and the braking torque are obtained as responses during the braking process. A comparison between braking torques obtained from theoretical and experimental work shows agreement when voltage is 2 V at speed of 150 rpm and also agreement when voltage is 2 and 3 V at speed of 250 rpm

In this paper a MATLAB SIMULINK model of seven Degrees Of Freedom (DOF) full vehicle model is developed. Mathematical equations are obtained using Newtonâs second law and free body diagram concept. Validation of the SIMULINK model is obtained to ensure that the model is suitable for studying the ride comfort. A Genetic algorithm optimization technique is used to find the optimum values of spring stiffness and damping coefficient for front and rear passive suspension system of the seven DOF vehicle model at variable velocities which improve the performance of the suspension system of the vehicle. Also Proportional Integral (PI) controller is implemented to the model to study its effect on ride comfort. Comparison of the results for body acceleration and sprung mass displacement of the optimized data of suspension parameters and model with PI controller are illustrated. The results show that the optimized parameters and PI controller give significant improvements of the vehicle ride performance over the passive suspension system. Keywords: Vehicle dynamics, Full vehicle model, Seven DOF model, Genetic algorithm, PI controlle

Environmental factors, such as climate change, have serious consequences for existing buildings, including increased resource consumption and footprint, adverse health effects, and reduced comfort for the occupants. To promote sustainability and address climate change, architecture must embrace digitalization. Buildings can be built digitally, analyzed in real time, optimized for energy consumption, and utilized to reduce carbon emissions and achieve zero energy consumption using digital twin technology. Currently, Lebanon’s residents are turning to solar power to generate renewable energy as a result of a lack of energy supplied by the government. In this study, a digital twin model was designed using an artificial neural network (ANN) to investigate the energy consumption of residential buildings. The main idea was to assist architects and engineers in forecasting energy consumption for different design materials by selecting the most effective alternate design for materials with building envelope characteristics, such as exterior walls, roof insulation, and windows, to minimize the consumption of energy in a residential building, hence resulting in a green building. The data simulations used in the digital twin model were carried out using Quick Energy Simulation Tool (eQuest) software; 1540 simulation results were used for different thicknesses of insulation material, values of conductivity, and window types. The digital twins were designed using an artificial neural network model. The results of the investigation and the accompanying eQuest output results were found to be precise and very similar.

The concept of a digital twin is increasingly appearing in industrial applications, including the field of predictive maintenance. A digital twin is a virtual representation of a physical system containing all data available on site. This paper presents condition monitoring of ventilation systems through the digital twin approach. A literature review regarding the most popular system faults is covered. The motor current signature analysis is used in this research to detect system faults. The physical system is further described. Then, based on the free body diagram concept and Newton’s second law, the equations of motion are obtained. Matlab/Simulink software is used to build the digital twin. The Concordia method and the Fast Fourier Transform analysis are used to process the current signal, and physical and numerical system current measurements are obtained and compared. In the final step of the modeling, specific frequencies were adjusted in the twin to achieve the best simulation. In addition, a statistical approach is used to create a complete diagnostic protocol.