Md. Tasyrif bin Abdul Rahman
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Preferred name
Md. Tasyrif bin Abdul Rahman
Official Name
Md. Tasyrif, Abdul Rahman
Alternative Name
Abdul Rahman, Md Tasyrif
Rahman, M. D.Tasyrif Abdul
Main Affiliation
Scopus Author ID
36656452500
Researcher ID
FSF-6142-2022

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Fatigue life investigation of UIC 54 rail profile for high speed rail

2017-10-29 , Gurubaran Panerselvan , Mohd Afendi Rojan , Nur Fareisha M. A. , Mohd Shukry Abdul Majid , Haftirman I. , Md. Tasyrif bin Abdul Rahman

This study is to investigate the fatigue life of high speed rail in Malaysia. This paper describes about the experimental and simulation analysis investigation on fatigue life of rail profile UIC 54 using bulk specimen according to ASTM E 466-15 standard. The Fatigue life testing was performed in the fatigue testing machine (Instron 8800) 100 kN. Meanwhile, the fatigue life analysis was performed in ANSYS Workbench 14.5. Furthermore, the stress levels for experimental testing were applied as 16.7%, 25%, 35%, 50%, 58.3%, 66.77% and 75% with machine frequency of 20 Hz. Apart from that, the total fatigue life cycles for rail profile UIC 54 were acquired from both experimental and simulation. The fatigue life S-N curves were plotted and validated with the results of the simulation analysis with experimental results.

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A comparative study on interior acoustic comfort level of compact cars using data mining approach

2020-01-01 , Azuddin K.A. , Ahmad Kadri Junoh , Mohamed Z. , Md. Tasyrif bin Abdul Rahman

Vehicle acoustic comfort is one of the ergonomic measurement criteria that are essential for car occupants. Furthermore, interior cabin noise of a car may affect the driver's concentration when driving. This study is to investigate the noise comfort level of car interior on several compact cars. The objective is to measure interior cabin noise for all three cars and then to compare their acoustic comfort level using subfield data mining approach. A deduction was made to rate the best car among the three in term of acoustic comfort. The interior cabin noise was obtained for the cases where engine speed is varied while the cars are in stationary and moving condition. The noise was assessed according to pre-determined subjective and objective criteria. The sound quality parameters was assessed by regression analysis. In subjective assessment, the recorded noise was evaluated based on jury assessment. Then, the data mining approach was implemented to illustrate the noise level. The collected noise data were divided into five clusters through hierarchical clustering method. To assess the accuracy of noise data clusters, the method of k-nearest neighbours was performed and the results show a high accuracy rate (> 95%). Finally, the interior noise of the three cars was compared by using the analysis of variation. The vehicle acoustic comfort index was produced for the three cars tested in this study. In addition, the acoustic quality among the three cars is presented using anova. Annoyance index of the three cars was generated using data mining method. From the results, Axia car model has the best acoustic comfort compared to the other two cars by objective evaluation. By subjective evaluation, Axia car model recorded the lowest level of annoyance.

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Design optimization of rear uprights for UniMAP Automotive Racing Team Formula SAE racing car

2017-10-29 , Azmeer M. , Mohd Hafif Basha Mohamad Jamel Basha , Hamid M.F. , Md. Tasyrif bin Abdul Rahman , Mohd Sani Mohamad Hashim

In an automobile, the rear upright are used to provide a physical mounting and links the suspension arms to the hub and wheel assembly. In this work, static structural and shape optimization analysis for rear upright for UniMAP's Formula SAE racing car had been done using ANSYS software with the objective to reduce weight while maintaining the structural strength of the vehicle upright. During the shape optimization process, the component undergoes 25%, 50% and 75 % weight reduction in order to find the best optimal shape of the upright. The final design of the upright is developed considering the weight reduction, structural integrity and the manufacturability. The final design achieved 21 % weight reduction and is able to withstand several loads.

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Influence of multi-walled carbon nanotubes on thermal behaviour and mechanical properties of pineapple leaf fibre-based natural rubber composites

2024-05-01 , Yi Xuan Y. , Mohd Ridzuan Mohd Jamir , Mohd Shukry Abdul Majid , Md. Tasyrif bin Abdul Rahman , Yudhanto F. , Azduwin Khasri , Mohd Shihabudin Ismail

Replacing synthetic fibres with natural fibres as reinforcement fillers in natural rubber (NR) tends to yield eco-friendly bio-composites. This study investigated the tensile and hardness properties, and the thermal behaviour of pineapple leaf fibre (PALF)-reinforced NR composites with and without the addition of multi-walled carbon nanotubes (MWCNT). The fibre content was varied at 0, 10, 20, and 30 parts per hundred rubber (phr) and the MWCNT content was fixed at 10 phr. The surface morphology of the tensile-fractured specimens was examined using scanning electron microscopy (SEM) to identify the rubber-matrix adhesion and tear mechanisms of the fibres in the NR matrix. The results revealed that including the PALF and MWCNT allowed the NR composites to exhibit excellent stretching stress at low elongations. Additionally, the composites displayed enhanced stiffness, further increasing the hardness of the composite, ranging from 46.8 to 62.8 Shore A. However, PALF reduces the thermal stability of the composite, where the initial degradation temperature increases. From the thermogravimetric analysis, the residues remaining in the NR composites ranged from 6 to 13% at various fibre loadings. Therefore, this study provides valuable insights into the tensile and hardness properties and the thermal behaviour of PALF-reinforced NR composites to improve end-use properties.

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Effect of elevated temperatures on wear and frictional performance of Pineapple leaf fiber‐reinforced natural rubber composites with the addition of multi‐walled carbon nanotubes

2025-10 , Yeo Yi Xuan , Mohd Ridzuan Mohd Nor , Noraini Marsi , Md. Tasyrif bin Abdul Rahman , Mohd Shukry Abdul Majid , Mohd Hafis Sulaiman

Rubber composites are often used at high temperatures, particularly in practical applications, such as autoclave components, gaskets, and seals. This study investigated the effect of elevated temperatures on the friction and wear properties of pineapple leaf fiber (PALF)-reinforced natural rubber (NR) composites with the addition of multi-walled carbon nanotubes (MWCNTs). Commercial NR composites were prepared using a two-roll mill mixing method, followed by molding. The PALF and MWCNTs contents were fixed at 30 and 10 parts per hundred rubber (phr), respectively. The frictional force, coefficient of friction (COF), and specific wear rate (SWR) were studied in the temperature ranges from room temperature (RT) to 80°C under various applied loads (5, 10, and 15 N). A significant improvement in the wear properties of the composites was achieved with increasing temperature. The results showed that the inclusion of MWCNTs effectively enhanced the wear performance of the composites at elevated temperatures. Overall, this study provides valuable insights into the friction and wear characteristics of PALF-reinforced NR composites with the addition of MWCNTs, enhancing their end-use properties for high-temperature applications. Highlights: Improved wear and frictional properties of NR/30PALF composites with MWCNTs. MWCNTs enhance heat dissipation, reducing softening at elevated temperatures. Frictional force and COF decreased with increasing temperature and load. NR/30PALF/MWCNT composites showed smoother surfaces and lower wear rates. Thermal stability and wear resistance of the composites were enhanced.

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Thermal and Static Properties Investigation of Different Intake Manifold Materials to Lower Air Intake Temperature for Improved Engine Performance

2023-04-01 , Halim S.S. , Md. Tasyrif bin Abdul Rahman , Abdul Hamid Adom , Mohd Al-Hafiz Mohd Nawi , Mohd Ridzuan Mohd Jamir , Suhaimi Illias

Formula SAE competition is targeted at students who are interested in designing and developing a Formula-type race car. Rules were imposed to restrict the car’s performance for safety besides encouraging problem-solving skills. One such rule is the requirement of a 20mm restrictor inserted between the carburettor and intake manifold to reduce the air intake. With a constricted airflow creating a bottleneck effect, less air will be provided to the engine for combustion, consequently reducing engine efficiency. The purpose of this project is to overcome this problem despite the restriction imposed by the rules. This is done by choosing an intake manifold material that provides a low air temperature while withstanding the stress and vibrations from the engine. Computational Fluid Dynamics (CFD) software was used to conduct the static, thermal and modal analysis of Aluminium Alloy 6063, Gray Cast Iron, Fibreglass Epoxy and Carbon Fibre Epoxy to choose the material that produces lower intake air temperature while maintaining high strength. Carbon fibre epoxy was found to provide the best durability against static stress while maintaining a lower intake air temperature compared to the other materials tested.

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Investigation of The Dynamic Deflection of Conveyor Belts Via Simulation Modelling Methods on Idler Factor

2022-01-01 , Munir H.A. , Ammar Zakaria , Ponniran A. , Md. Tasyrif bin Abdul Rahman , Marimuthu T.

Belt conveyor is today's very important mechanism in material handling industries and is most commonly used to transport bulk materials such as grain, salt, coal and sand. Belt deflection indicates belt is loosening. It occurs between the idler roll sets due to the self-weight of the belt and the forces from the bulk material. This paper includes detailed analysis of the conveyor belt deflection under pragmatic load conditions. The aim of the project is to develop a Finite Element Method (FEM) simulation model for the deflection analysis of a conveyor belt using load data for bulk material calculated by a coupled Discrete Element Method (DEM) simulation. The scope of this project is on idler roll aspects. Two types of three-trough idlers were used in this project which were made of steel and plastic respectively. A variety of idler spacing were used to determine the most efficient configuration for the belt. This paper will explain the FEM procedures for the modelling of the belt behavior and the working principle of a coupled FEM-DEM analysis. Experimental results were presented and compared based on parameters. Comparisons showed plastic idler-rollers with smaller gap is better than the rest and it could be optimized to improve the performance and efficiency.

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Study of intake manifold for Universiti Malaysia Perlis automotive racing team formula student race car

2017-10-29 , Norizan A. , Md. Tasyrif bin Abdul Rahman , Nasrul Amri Mohd Amin , Mohd Hafif Basha Mohamad Jamel Basha , Ismail M.H.N. , Azarul Fahmin Ab Hamid

This paper describes the design differences between the intake manifold and restrictor used in racing cars that participate in the Formula Student (FSAE) competition. To fulfil the criteria of rules and regulation of the race, each race car must have a restriction device that has a maximum diameter of 20 mm installed between the throttle body and intake manifold. To overcome these problems, a restrictor has been designed and analysed using the steady state analysis, to reduce the loss of pressure in the restrictor. Design of the restrictor has a fixed parameter of the maximum diameter of 20mm. There are some differences that have been taken to make the comparison between the design of the restrictor, the diameter of the inlet and outlet, the curvature of the surface, convergence and divergence angle and length of the restrictor. Intake manifold was designed based on the design of the chassis, which shall not exceed the envelope defined by the FSAE competition. A good intake manifold design will affect the performance of the engine. Each design have made an analysis designed to ensure that each cylinder engine gets its air evenly. To verify the design, steady state analysis was made for a total mass flow rate and the velocity of air leaving a runner in each engine. Data such as the engine MAP reading was recorded by using Haltech ECU Management Software as reference purposes.

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Connected car: Engines diagnostic via Internet of Things (IoT)

2017-10-29 , Azrul Fahmi A.Hamid , Md. Tasyrif bin Abdul Rahman , Shah Fenner Khan Mohamad Khan , Abdul Hamid Adom , Muhajir Ab. Rahim , Norasmadi Abdul Rahim , Ismail M.H.N. , Norizan A.

This paper is about an experiment for performing engines diagnostic using wireless sensing Internet of Thing (IoT). The study is to overcome problem of current standard On Board Diagnosis (OBD-II) data acquisition method that only can be perform in offline or wired method. From this paper it show a method to determined how the data from engines can be collected, make the data can be easily understand by human and sending data over the wireless internet connection via platform of IOT. This study is separate into three stages that is CAN-bus data collection, CAN data conversion and send data to cloud storage. Every stage is experimented with a two different method and consist five data parameter that is Revolution per Minute (RPM), Manifold Air Pressure (MAP), load-fuel, barometric pressure and engine temperature. The experiment use Arduino Uno as microcontroller, CAN-bus converter and ESP8266 wifi board as transfer medium for data to internet.

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Supervised segmentation on fusarium macroconidia spore in microscopic images via analytical approaches

2024-04-01 , Azuddin K.A. , Ahmad Kadri Junoh , Ammar Zakaria , Md. Tasyrif bin Abdul Rahman , Nor N.M.I.M. , Nishizaki H. , Latiffah Z. , Azuddin N.F. , Abdullah M.Z. , Terna T.P.

Fungi are one of the major causes that contributed to plant diseases. There are lots of fungi species but it is estimated that only 10% have been described. There are two major approaches to identifying fungi species, morphological identification, and molecular test which need cautious clarification to make good interpretations and are time-consuming. In this paper, we propose a Machine Learning approach that involves the use of the K-Means clustering technique, and Decision Tree to highlight the observed fungi spore images taken under the microscopic view and discard background pixels to produce digital images database which later can be used for Deep Learning.

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