Shamsul Anuar Shamsudin

Prediction on Power Produced from Power Turbine as a Waste Heat Recovery Mechanism on Naturally Aspirated Spark Ignition Engine Using Artificial Neural Network

The waste heat from exhaust gases represents a significant amount of thermal energy, which has conventionally been used for combined heating and power applications. This paper explores the performance of a naturally aspirated spark ignition engine equipped with waste heat recovery mechanism WHRM in a sedan car. The amount of heat energy from exhaust is presented and the experimental test results suggest that the concept is thermodynamically feasible and could significantly enhance the system performance depending on the load applied to the engine. However, the existence of WHRM affects the performance of engine by slightly reducing the power. The simulation method is created using an artificial neural network ANN which predicts the power produced from the WHRM.

Prediction of generated power from steam turbine waste heat recovery mechanism system on naturally aspirated spark ignition engine using artificial neural network

The waste heat from exhaust gases represents a significant amount of thermal energy, which has conventionally been used for combined heating and power applications. This paper proposes a prediction model on the performance of a naturally aspirated spark ignition engine equipped with a waste heat recovery mechanism (WHRM) using steam turbine mechanism. The simulation method is created using an artificial neural network (ANN) to predict the power produced from this WHRM. The automated neural network was employed to run the simulation, where the ANN analysis used multilayer perceptrons as the network architecture, which is a feed-forward neural network architecture with uni-directional full connections between successive layers and applied Broyden–Fletcher–Goldfarb–Shanno algorithm iterative techniques to train the data. By using ANN, power generated from this WHRM could be predicted with good accuracy of 0.007, 0.011, and 0.016% error on training, test and validation data, respectively.

Facing the Autonomous Underwater Vehicle Competition Challenge: The TUAH AUV Experience

This paper describes the experience of UTeM AUV team during an autonomous underwater vehicle international competition. The competition provides the participants with the opportunity to experience the engineering challenges during the development of the autonomous underwater vehicle (AUV) systems. The competition focuses on underwater vehicle technology development that emphasizes on the autonomous operations of the vehicle in a swimming pool.

The Development of PANTHER AUV for Autonomous Underwater Vehicle Competition Challenge 2017/2018

This paper describes the development of an autonomous underwater vehicle for a competition that gives participants the opportunity to experience the engineering challenges of autonomous underwater vehicle (AUV) systems and develop skills in underwater technology. The competition focuses on the autonomous operations in the pool, with four tasks to be completed. The inertial measurement unit, depth sensor and Pixy (CMUcam5) camera are used in AUV navigation, while Arduino Uno is used for the overall controls. Field test has been conducted during the Malaysian Autonomous Underwater Vehicle Challenge (MAUVC) during the IEEE 7th International Conference on Underwater System Technology USYS in Kuala Lumpur. The outcome of the test will be studied for the preparation of the next Autonomous Underwater Vehicle Challenge, which will be held in Singapore.

Design Efficiency Analysis Towards Product Improvement for Eco-Friendly Using DFMA Method

This paper presents the comparative study of design efficiency of two different brands of products, performing the same function using the Design for Manufacturing and Assembly (DFMA) method. The study aims to compare the products on the relative design efficiency. The DFMA method was used as it is a well-established technique for improving the efficiency of the product leading to minimizing production costs. It also shortens product development time by reducing the number of components in a product. The study used two different brands of dry iron as a case study. The result shows that the percentage of the design efficiency of dry iron A is 8.82%, whereas it is 10.34% of dry iron B. Thus, the dry iron B is much better as compared to A in term of its assembly operation and design efficiency. Therefore, the dry iron B is greener than dry iron A. Furthermore, a redesign of dry iron B was proposed and analyzed for the internal validation. The DFMA analysis result shows that the percentage of design efficiency of a new conceptual design of dry iron B increased to 18.08%. The application of the DFMA method to enhance the eco-friendliness of a product has been proven to be highly useful in design work.

A study on tracking peformance of the pneumatic system with enhanced NPID controller

An investigation on the performance of enhanced Nonlinear Proportional Integral Derivative (ENPID) controller is presented in this paper. The study is focused on the potential of the controller to perform well in tracking set point of pneumatic actuator system. Two control strategies of the ENPID are considered in this paper, namely Multi-rate NPID (MN-PID) and Self-regulation NPID (SN-PID). These control strategies are tested against NPID and conventional PID controller. Also, the dead-zone compensation (DZC) is applied to the system to overcome the dead-band of the valve. Feed forward path is also included to improve the tracking performance. Two different input signals i.e. sinusoidal and S-curve waveforms are used to evaluate the performance of the techniques. To further examine the controller performance, the frequency and amplitude of the sinusoidal test signal are varied. The effectiveness of the proposed controllers is verified through simulation and experimental studies.

Analysis Opacity and Size of Soot Particles in Fuel of Diesel Engine

In a diesel engine the soot was produced due to the result of incomplete fuel combustion in the combustion chamber. Some of this soot moves down slowly to piston where the lubricant oil is located. This soot causes the lubricant oil to become contaminated thus increases its viscosity. As a result, frequent changing of lubricant oil is required in order to keep up the engine performance. This soot also has solid particles (Particulate Matter: PM) and nitrogen oxide (NOx) that are very harmful to the environment. The purpose of this study is to compare the opacity value of B20 (Jatropha) oil, Palm oil and diesel oil by using diesel engine. Besides that, this project also aims to compare the average of soot agglomeration size produces by using Jatropha oil, Palm oil and diesel oil in diesel engine. In this experiment, Jatropha and Palm oil was mixed with Diesel oil before being tested to diesel engine. A smoke tester was used to collect soot that came out from the exhaust of the diesel engine. The soot was observed by inverted microscope in order to investigate the soot agglomeration size. Result from this studies show that the value of opacity value of biodiesel Jatropha and Palm oil is lower compared to Diesel oil. Besides that, Diesel oil has the biggest soot agglomeration size compared to biodiesel.