Jing Yuen Tey - Academia.edu (original) (raw)

Papers by Jing Yuen Tey

60 Years of the Loeb-Sourirajan Membrane

Journal of Manufacturing Processes

Lecture Notes in Electrical Engineering, 2012

ABSTRACT

Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2019

A new method based on constraint multi-objective optimization using evolutionary algorithms is pr... more A new method based on constraint multi-objective optimization using evolutionary algorithms is proposed to optimize the powertrain design of a battery electric formula vehicle with an all-wheel independent motor drive. The electric formula vehicle has a maximum combined motor power of 80 kW, which is a constraint for delivering maximum vehicle performance with minimal energy consumption. The performance of the vehicle will be simulated and measured against different driving events, that is, acceleration event, autocross event, and endurance event. Each event demands a different aspect of performance to be delivered by the motor. The respective event lap time or energy rating will be measured for performance assessment. In this study, a non-dominated sorting genetic algorithm II and constrained multi-objective evolutionary algorithm based on decomposition by using differential evolution are employed to optimize the motor transmission ratio, motor torque scaling, and downforce scale o...

Applied Acoustics, 2020

Water leakage control emerges as a prime concern among researchers and water utility companies du... more Water leakage control emerges as a prime concern among researchers and water utility companies due to ever-increasing water loss level. Acoustic leak detection technique is a promising and widely used approach. Unfavorably, the deficiency of this method is that acoustic waves are interfered by undesirable noise and presence of multi-modal dispersive wave. The conventional correlation-based method assumes leak noise propagates as a single non-dispersive wave and this leads to unreliable detection method. This paper concerns on noise reduction through an improved de-noising method and leak localization by considering wave dispersion. Wavelet de-noising is a common de-noising method used in past leak detection works. But it has shortcomings of frequency aliasing and shift-variant due to DWT decomposition. Therefore, a shift-invariant Dual Tree Complex Wavelet Transform (DTCWT) is introduced here to substitute DWT for wavelet de-noising. DTCWT will decompose the signal into several band...

Journal of Renewable Materials, 2020

Polylactic acid (PLA) bioplastic is a common material used in Fused Deposition Modeling (FDM) 3D ... more Polylactic acid (PLA) bioplastic is a common material used in Fused Deposition Modeling (FDM) 3D printing. It is biodegradable and environmentally friendly biopolymer which made out of corn. However, it exhibits weak mechanical properties which reduced its usability as a functional prototype in a real-world application. In the present study, two PLA composites are created through coextruded with 3K carbon fibres and twisted Kevlar string (as core fibre) to form a fibre reinforced parts (FRP). The mechanical strength of printed parts was examined using ASTM D638 standard with a strain rate of 1 mm/min. It has been demonstrated that the FRPs coextruded with 3K carbon fibres had achieved significant improvement in Young's modulus (+180.6%, 9.205 GPa), ultimate tensile strength (+175.3%, 103 MPa) and maximum tensile strain (+21.6%, 1.833%). Although the Young's modulus of Kevlar FRP was found to be similar to as compared to unreinforced PLA (~3.29 GPa), it has gained significant increment in terms of maximum tensile strain (+179.7%, 104.64 MPa), and maximum tensile strain (+257%, 5.384%). Thus, this study revealed two unique composite materials, in which the 3K carbon FRP can offer stiff and high strength structure while Kevlar FRP offers similar strength but at a higher elasticity.

Materials Today: Proceedings

IOP Conference Series: Earth and Environmental Science, Jul 2, 2019

Water leakage is one of the important agendas across the globe thus several effectual systems for... more Water leakage is one of the important agendas across the globe thus several effectual systems for leakage detection had been developed with the aim to improve sustainable use of water. Among the methods, acoustic leak detection technique had been proven as a promising approach to detect and localize leaks in water or gas pipeline. However, existence of noise in acoustic signals complicated the leak detection practices. Traditional de-noising methods like filtering and wavelet de-noising are not suitable for non-stationary and broadband acoustic signals. Therefore, Dual Tree Complex Wavelet Transform (DTCWT) is applied in this paper to reduce acoustic noise and decompose signals into several frequency bands. DTCWT decomposition is intended to resolve the problem encountered by the typical correlation-based leak localization method. Due to dispersive and frequency-dependent nature of wave propagation, correlation-based method normally assumes constant wave velocity which results in inaccurate leak source localization. In this paper, signal will be de-noised and decomposed by employing DTCWT. Wave velocity is evaluated based on the dominant frequency and dispersion curve. Then, time delay can be estimated via comparison study among cross correlation, CWT localization and convolution. CWT localization and convolution are proposed as new time-delay estimation method attributable to enhance localization accuracy. Experimental results validated that the proposed method, DTCWT-correlation outperforms other methods with a localization error of 4.67 %. Both CWT localization and convolution are also capable to pinpoint the location of leaks. Besides, leaking and non-leaking condition can be differentiated after multilevel decomposition of DTCWT.

Formula 1 is considered an important motorsport event that has driven the development of cutting-... more Formula 1 is considered an important motorsport event that has driven the development of cutting-edge automotive technology. Similarly, virtual formula competition is introduced at the university level to harness technological advances for automotive development among universities. Performance and fuel efficiency have always been two conflicting objectives in determining the optimal powertrain design. In this paper, state-of-the-art multi-objective evolutionary algorithms (MOEAs) are employed to optimize the vehicle powertrain design based on competing event and the ontrack performance through software in-the-loop optimization approach. Unlike conventional powertrain optimization approach where the powertrain design is optimized again standard urban driving profiles to achieve optimum driving performance and fuel consumption which is not suitable to be employed to optimize race car powertrain design. The powertrain design is optimized and benchmarked in multiple dynamic test events i.e. Acceleration, Autocross and Endurance. Each event measures different performance parameters (i.e. lap time and fuel consumption) A total of nine design parameters are optimized in this study. Three design parameters (employed to formulate the progressive gear calculation of six gear ratios), five gear shifting rpm (revolutions per minute) and an aerodynamic downforce scale value (for front and rear downforce). Two stages of optimization solution are proposed to handle such complicated design requirement. NSGA-II was identified as the most efficient algorithms among the MOEAs employed in this study; especially in terms of computational time, Pareto distribution and Pareto design. Overall, the optimized powertrain design showed significant improvement in all events i.e. energy efficiency was increased by 13.7% for the endurance event while lap time was reduced by 0.7 and 1.2% in the acceleration and autocross events, respectively.

Vehicle System Dynamics

A method based on constraint multi-objective evolutionary algorithms approach is proposed to opti... more A method based on constraint multi-objective evolutionary algorithms approach is proposed to optimise the handling performance of a race car dynamic. This involves a software-in-the-loop optimisation (SiLO) between a high-fidelity model of a formula vehicle modelled in VI-Grade and MATLAB for hosting the optimisation algorithms. The optimisation process involves the tuning of the suspension design variables, i.e. spring stiffness, anti-roll bar stiffness, damper coefficient, toe angle, and camber angle for both front and rear suspensions against eight objectives functions, i.e. sideslip overshoot, yaw rate overshoot, linear understeer gradient, limit understeer gradient, maximum lateral acceleration, yaw rate phase delay and lateral acceleration phase delay. A custom constraint function was introduced to improve the convergence speed of the optimisation process. The optimised result showed a promising increase in handling performances, i.e. the maximum achievable lateral acceleration has increased by 8.9% whilst maintaining the stability of the vehicle close to neutral steer behaviour. The sideslip angle was well controlled under 1 deg at 95% of maximum lateral acceleration, and slip angle overshoot has improved by 1.65% in step steer manoeuvre. Additionally, the skid-pad events and autocross event laps time were reduced by 5.19% and 1.71%, respectively.

IOP Conference Series: Earth and Environmental Science

3D printing employed in additive manufacturing, converts digital data based on a computer-aided d... more 3D printing employed in additive manufacturing, converts digital data based on a computer-aided design (CAD) model into an object by adding material layer by layer. Unlike subtractive manufacturing, complex geometries can be printed with minimal wastage. The additive manufacturing process for 3D printers features several types of technology ranging from fused deposition modelling (FDM), laser sintering, stereolithography and laser melting to binder jetting and others. However, these technologies are limited to process one material at a time, which poses a challenge to print functionally graded material (FGM). This difficulty can be overcome by offering a unique solution which is proposed in this paper - by applying FDM customized with an extrusion screw to incorporate mixing and blending of the polymer matrix and filler as a continuous process during printing. The intent of this technique is to ease the production of FGMs (which vary in mechanical, electrical and texture gradually o...

International Journal of Metalcasting

The high-pressure die casting process is meant for high volume production rate mainly used in the... more The high-pressure die casting process is meant for high volume production rate mainly used in the automotive industry. An efficient method to separate the die-cast components from the main sprue and runner system is crucial to improving the productivity of the manufacturing processes. Conventionally casting components are often separated with the use of a grinding wheel machine, trimming machine or pneumatic hammer. Often these techniques require customized machine design in trimming the cast part as each die casting gate design might be different from one another, especially when there is a change in production cast model. This may incur higher set-up cost and additional configuration time. It is unfavourable in the manufacturing production line that handles small batch high variation of casting model in the small/medium casting industry. Thus, this paper introduced an alternative degating technique with the use of a shaker machine to match the resonance of the casting component natural frequency to separate the die-cast component from the casting tree. The proposed method can overcome the drawback of the conventional method by eliminating the additional configuration time required when there is a change in different casting part design. Die casting parts employed in this study were constructed by AlSi10Cu2Fe aluminium alloy. Experimental modal analysis was performed to verify the natural frequency calculated through finite element analysis. The correlated finite element model was then employed for harmonic response analysis to compute the frequency response of input excitation location against output stress response at the gate. The results from the analysis showed that the first natural frequency mode could induce a bending mode at the gate and created the highest stress concentration at the location. Next, an experiment was carried out by exciting the first natural frequency to the casting part using a shaker machine. In the experiment, the die-cast components were able to break away within 0.31 s at its first natural frequency. This observation was found to be in agreement with the simulation results, whereby the degating time of 0.27 s was obtained. Therefore, the present study has shown that an efficient degating of casting components process can be achieved via introducing a correct mode of vibration excitation.

Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering

The conventional approach in vehicle suspension optimization based on the ride comfort and the ha... more The conventional approach in vehicle suspension optimization based on the ride comfort and the handling performance requires decomposition of the multi-performance targets, followed by lengthy iteration processes. Suspension tuning is a time-consuming process, which often requires the benchmarking of competitors’ vehicles to define the performance targets of the desired vehicle by experimental techniques. Optimum targets are difficult to derive from benchmark vehicles as each vehicle has its own unique vehicle set-up. A new method is proposed to simplify this process and to reduce significantly the development process. These design objectives are formulated into a multi-objective optimization problem together with the suspension packaging dimensions as the design constraints. This is in order to produce a Pareto front of an optimized vehicle at the early stages of design. These objectives are minimized using a multi-objective optimization workflow, which involves a sampling technique, and a regularity-model-based multi-objective estimation of the distribution algorithm to solve greater than 100-dimensional spaces of the design parameters by the software-in-the-loop optimization process. The methodology showed promising results in optimizing a full-vehicle suspension design based on the ride comfort and the handling performance, in comparison with the conventional approach.

Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2014

In this paper an alternative method is proposed for defining the suspension performance targets t... more In this paper an alternative method is proposed for defining the suspension performance targets through the use of full-vehicle modelling consisting of a ride model and a handling model. These models are derived with the use of a non-linear damper, suspension kinematic characteristics and basic vehicle dimensions. The vehicle performances can be explored using the design-of-experiments method. The non-sorting method is then employed to sort for non-dominated solutions, where these samples represent the Pareto front of the vehicle performances in ride comfort and handling. The k-means clustering method is used to classify further the solution into different unique optimum characteristics. The expectation–maximization algorithm is developed to compute the allowable variance of design parameters required to achieve the specific optimum design targets. This method can be a very useful tool in the earliest design stages where vehicle data are inadequate. This methodology potentially redu...

ABSTRACT In an effort to reduce cost involving repetitive prototype build–test cycles, it is inev... more ABSTRACT In an effort to reduce cost involving repetitive prototype build–test cycles, it is inevitable that simulation on full vehicle will be carried out during the product development stage. Desired suspension kinematic profiles of a given vehicle parameter are often unknown at the initial design stage. This paper demonstrates a simple methodology to obtain optimized kinematic characteristics against quality of handling performance using this model as predictive model in earliest design stage. A full vehicle model that is inclusive of suspension kinematic profiles and nonlinear damper profiles has been derived to enable the engineer to study the characteristics of the nonlinear elements against the vehicle performance when only limited vehicle data are available in the initial stage. Results suggest that the handling characteristics of a vehicle are sensitive to the changes in suspension kinematic profile. Additionally, the proposed vehicle model is able to provide satisfactory handling objective when measured in transient handling and frequency response compared to other vehicle models. A robust prediction model of the vehicle responses in frequency domain is proposed. It is coupled with the vehicle model employed as predictive model to optimize front toe angle profile against vehicle quality of handling performance measured in frequency domain.