N
Noreffendy Tamaldin
Researcher at Universiti Teknikal Malaysia Melaka
Publications - 100
Citations - 923
Noreffendy Tamaldin is an academic researcher from Universiti Teknikal Malaysia Melaka. The author has contributed to research in topics: Diesel engine & Tribometer. The author has an hindex of 11, co-authored 90 publications receiving 571 citations. Previous affiliations of Noreffendy Tamaldin include Universitas Nasional & Universiti Malaysia Pahang.
Papers
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Journal ArticleDOI
Impacts of Biodiesel Storage Duration on Fuel Properties and Emissions
TL;DR: In this paper, the effects of storage conditions on properties of biodiesel such as density, kinematics viscosity, acid value, water content and flash point were discussed in detail.
Journal ArticleDOI
Theoretical study and indoor experimental validation of performance of the new photovoltaic thermal solar collector (PVT) based water system
Amira Lateef Abdullah,Suhaimi Misha,Noreffendy Tamaldin,Mohd Afzanizam Mohd Rosli,Fadhil Abdulameer Sachit +4 more
TL;DR: In this paper, a dual oscillating absorber copper pipe flow that was designed based on the water-based hybrid photovoltaic thermal (PVT) system was developed and studied.
Book ChapterDOI
Natural fiber polymer composites: Utilization in aerospace engineering
TL;DR: In this article, the current applications of natural fiber polymer composites (NFPC) for aerospace engineering are discussed. Among the topics covered are the introduction to aerospace materials especially polymer composite such as for aircraft frames, and engine construction, and the advantages offered by the material.
Journal ArticleDOI
Review of artificial neural networks for gasoline, diesel and homogeneous charge compression ignition engine
Ibham Veza,Asif Afzal,M.A. Mujtaba,Anh Tuan Hoang,Dhinesh Balasubramanian,Manigandan Sekar,I.M. Rizwanul Fattah,Manzoore Elahi M. Soudagar,Ahmed I. El-Seesy,D. Wibowo Djamari,Agus Hananto,N.R. Putra,Noreffendy Tamaldin +12 more
TL;DR: In automotive applications, artificial neural network (ANN) is now considered as a favorable prediction tool as mentioned in this paper , since it does not need an understanding of the system or its underlying physics, an ANN model can be beneficial especially when the system is too complicated and it is too costly to model it using a simulation program.
Journal ArticleDOI
Optimization of Tribological Performance of hBN/AL2O3Nanoparticles as Engine Oil Additives☆
Muhammad Ilman Hakimi Chua Abdullah,Mohd Fadzli Bin Abdollah,Hilmi Amiruddin,Noreffendy Tamaldin,Nur Rashid Mat Nuri +4 more
TL;DR: In this article, a low Coefficient of Friction (COF) with hexagonal boron nitride (hBN) and alumina (Al2O3) nanoparticles, dispersed in conventional diesel engine oil (SAE 15W40) was constructed using the Taguchi method.