Performance investigation of integrated model of quarter car semi-active seat suspension with human model

In this paper, an integrated model of a semi-active seat suspension with a human model over a quarter is presented. The proposed eight-degrees of freedom (8-DOF) integrated model consists of 2-DOF for the quarter car model, 2-DOF for the semi-active seat suspension and 4-DOF for the human model. A magneto-rheological (MR) damper is implemented for the seat suspension. The fuzzy logic-based self-tuning (FLST) proportional–integral–derivative (PID) controller allows to regulate the controlled force on the basis of sprung mass velocity error and its derivative as input. The controlled force is tracked by the Heaviside step function which determines the supply voltage for the MR damper. The performance of the proposed integrated model is analysed, in-terms of human head accelerations, for several road profiles and at different speeds. The performance of the semi-active seat suspension is compared with the traditional passive seat suspension to validate the effectiveness of the proposed integrated model with a semi-active seat suspension. The simulation results show that the semi-active seat suspension improves the ride comfort significantly by reducing the head acceleration effectively compared to the passive seat suspension

Response surface methodology and artificial neural network-based models for predicting performance of wire electrical discharge machining of inconel 718 alloy

This paper deals with the development and comparison of prediction models established using response surface methodology (RSM) and artificial neural network (ANN) for a wire electrical discharge machining (WEDM) process. The WEDM experiments were designed using central composite design (CCD) for machining of Inconel 718 superalloy. During experimentation, the pulse-on-time (TON), pulse-off-time (TOFF), servo-voltage (SV), peak current (IP), and wire tension (WT) were chosen as control factors, whereas, the kerf width (Kf), surface roughness (Ra), and materials removal rate (MRR) were selected as performance attributes. The analysis of variance tests was performed to identify the control factors that significantly affect the performance attributes. The double hidden layer ANN model was developed using a back-propagation ANN algorithm, trained by the experimental results. The prediction accuracy of the established ANN model was found to be superior to the RSM model. Finally, the Non-Dominated Sorting Genetic Algorithm-II (NSGA- II) was implemented to determine the optimum WEDM conditions from multiple objectives

Evaluation of copper-based alloy (C93200) composites reinforced with marble dust developed by stir casting under vacuum environment

Copper-based alloy (C93200) composites reinforced with a different weight percentage of marble dust particles (1.5, 3, 4.5, and 6 wt.%) were developed by stir casting method under vacuum environment. By using this type of reinforcement, it was possible to detect a suitable material for bearing applications. The manufactured material was characterized for its mechanical properties using a micro-hardness tester. A universal INSTRON-5967 machine was used to detect the yield and tensile strength. Further the hardness features were measured using a Walter Uhl model machine, whereby the wear characteristics were simulated under the pin-on-disc tribometer under different working conditions in ambient temperature (23 °C). Next, the preference selection index (PSI) technique that considers multi-criteria decision-making was proposed to validate which material was the best candidate. For the selection of material criteria, some specific material intrinsic properties—such as, density, void fraction, hardness resistance along with tensile, compressive, and flexural strength—were proposed and the surface characteristics linked to friction coefficients along wear properties. It was found that the novel composite material containing 4.5 wt.% of marble dust provided the best combination of properties and is a suitable candidate material for bearing applications

Role of homogeneous distribution of SiC reinforcement on the characteristics of stir casted Al–SiC composites

Stir casting process is very popular for the fabrication of particle reinforced metal matrix composites. However, achieving a homogenous distribution of the reinforcement particles is very challenging, which directly affect the final mechanical performances. In this research, a detailed investigation was conducted to obtain a superior synthesis of Al–SiC composite materials and to detect the effect of SiC particles distribution on the mechanical characteristic of the stir casted Al matrix composites using glycerol–water based model. The glycerol– water based model study displays the impacts of viscosity of Al melt (1.04-1.24 mPa.s), impeller position (10-50%), stirring speed (100-300 rpm) and blade angle (0-90º) on the vortex height, dispersion time, settling time and clustering of particles. The results of the experiments using glycerol–water based model, 45 º blade angles, impeller position of 40% from the base, stirring speed of 250 rpm showed the best uniform distribution of reinforcement particles. Confirmation experiments were carried out by fabricating Al-SiC PRMMC based on three different viscosities (1.04, 1.13, and 1.24 mPa.s) of Al melt and considering other parameters as constant. Fabricated Al-SiC samples were analysed by Scanning Electron Microscope (SEM) and mechanical testing such as tensile, hardness and wear tests. Based on the confirmation results, the viscosity of 1.13 mPa.s for Al melt (at 750 ºC) resulted in uniform distribution of SiC particles, which enhanced the tensile strength by 4%, wear resistance by 21%, and led to a uniform hardness value of 47 VHN throughout the composites

Characterization of Fracture Toughness Properties of Aluminium Alloy for Pipelines

Continuous critical loading of pressure equipments can affect the structural stability of these plants. The structural stability and mechanical resistance under pressure loads can also be affected by defects. Fracture mechanics assumptions were applied to aluminium alloys to study their effect on its mechanical behaviours. A 3-point bending standard test was employed and the critical Stress Intensity Factor, K (SIF) in mode I was determined in order to provide a quantitative/qualitative evaluation of the performance. Additional experiments were carried out to validate the numerical results gained from the Finite Element Method (FEM) and the Extended Finite Element Method (X-FEM). The crack propagation process is discussed in this study focussing on the effect of crack tip radius