Mechanization and Import Substitution in Zimbabwean Farmers' Equipment: A Case Study of the Revitalization of an Abandoned Tractor Trailer
Drill String Vibrational Analysis and Parametric Optimization for a Portable Water Well Rig Development
An Efficient Deep Neural Network with Amplifying Sine Unit for Nonlinear Oscillatory Systems
The Occupational Directness of Nanorobots in Medical Surgeries
Recent Trends in Solar Thermal Cooling Technologies
Design of Oil-Ammonia Separator for Refrigeration Systems
A Review on Mechanical and Tribological Characteristics of Hybrid Composites
Design and Experimental Investigation of a Natural Draft Improved Biomass Cookstove
Progressive Development of Various Production and Refining Process of Biodiesel
Optimization of Wire-ED Turning Process Parameters by Taguchi-Grey Relational Analysis
Evaluation Of Mechanical Behavior Of Al-Alloy/SiC Metal Matrix Composites With Respect To Their Constituents Using Taguchi Techniques
Multistage Extractive Desulfurization of Liquid Fuel by Ionic Liquids
Isomorphism Identification of Compound Kinematic Chain and Their Mechanism
Development of Electroplating Setup for Plating Abs Plastics
A Comprehensive Review of Biodiesel Application in IDI Engines with Property Improving Additives
Environmental issues and increased fuel prices are driving automotive manufacturers to develop more fuel-efficient vehicles with lower emissions. Due to the limitations of conventional wind tunnel experiments and rapid developments in computer hardware, considerable efforts have been invested to study vehicle aerodynamics computationally. The ANSYS computer software package is employed, and 3D computer model cars are designed by the SolidWorks software. The Fluent subpackage is used to evaluate the aerodynamic behavior. This paper concentrates on the prediction of lift and drag for the car body using Computational Fluid Dynamics (CFD) on three different models of vehicles for simulation without any devices, with a rear wing or spoiler, and with vortex generators. Turbulence modeling was done with the realizable k-ε model using standard wall functions. The computational results for the three models are provided. The drag and lift coefficients that we have found are 0.4142 and 0.4338, respectively; compared with model 2, they are 0.4585 and 0.0387, and for model 3, they are 0.3971 and 0.3858, respectively. Model 2 has shown that the aerodynamic drag has increased from 0.4142 to 0.4585, which is a 10.69% drag increment. In addition, it showed an increase in negative lift by reducing the lift coefficient from 0.4338 to -0.0387, which is a 91.07% lift reduction by comparing with model 1. Similarly, model 3 has shown that the aerodynamic drag is reduced from 0.4142 to 0.3971, which is a 4.12% drag reduction, and it also showed an increase in negative lift by decreasing the lift coefficient from 0.4338 to 0.3858, which is a 11.06% lift reduction.
This paper aims at characterizing the role of preload, friction and mass on the dynamic response of the linear motion stage used in the laser marking machine for black granite. A single-axis linear motion stage model was realized in Creo Parametric® CAE software. The mechanism design option was used to create a virtual mechanism with simulation entities for stiffness, friction, mass, damping, and motors. The experimental design was accomplished using Minitab® software to create the Taguchi orthogonal array. The simulation experiments with different values of preload, friction, and mass were conducted. The results show that increasing the linear bearing preload reduced the settling time. Increased elastic deformation increased bearing rigidity, which ultimately helped reduce vibrations and hence settling time. Furthermore, lower levels of friction reduced sticking and slipping, which led to reduced vibration levels and therefore a lower settling time.
As the utilization of roadways increases, the probability of accidents happening also increases. So to overcome this, Uturn paths were created in place of signals. So, waiting on the signal was totally avoided, eliminating pollution in traffic signal areas. The design and development of manual and voice-assisted U-turn indicators for automobiles are discussed in this paper. The design of this system requires the development of a new circuit to accommodate the voice control system for the indicators using Google Nest Mini and the button operated, which is controlled by a MQTT app in a tab with Wi-Fi connectivity. These devices are connected to the power supply unit to charge them through USB connectors, and the NodeMCU is used for the controlling of the whole system and responsible for the displaying of the indicator signs on the 16x16 LED wall placed on the vehicle. There are conventional indicators also present in the vehicle, along with the newly developed voice-controlled and button operated MQTT app, which will control the left and right turn indicators and the left and right U-turn indicators when a specific voice command is given to the microcontroller through Google Nest Mini. By using this technology, people can reduce the lack of communication during the U-turn and control the indicator, which is a hands-free operation. Placing this technology on the vehicle will increase the safety of the automobile and reduce the risk of accidents. This system allows people to control the voice-assisted control system and an integrated dashboard control system to control the U-turn indicators and the normal indicators with ease.
This paper provides a comprehensive and cost-effective solution for automotive health maintenance and diagnostics. The software performs checks and analyses of key vehicle parameters through the use of the OBD-II (On-Board Diagnostics-II) port on the car. The port has to be physically connected to an interface called the ELM327 Bluetooth or Wi-Fi module that connects to the Android device running the software through Bluetooth or Wi-Fi. On a successful connection, the user can use the software to check the status of electronic control units (ECUs) throughout the vehicle to point out malfunctioning components and change the configurations of some of these electronic control units. The vehicle reports back a log with Diagnostics Trouble Codes (DTCs) that indicates the number of problems that have been found, if there are any.
This paper explores the various factors that influence the dynamic response of a linear translation stage. The dynamic behavior of a linear translation stage is dominated by various factors such as friction, stiffness and resonant frequency. Friction behavior hinges on the preload level, while vibration behavior is dominated by the resonant frequency of the stage. Dynamic stiffness depends on the bearing preload and the mechanical properties of the linear motion stage. Damping is influenced by the linear bearing preload, friction, and the lubricant film. The preload applied to the rolling element bearings plays a key role in the dynamic response of the system since it influences friction, damping, resonant frequency, and stiffness of the linear translation stage.
