The purpose of this study was to determine the optimal design parameters and to indicate which of the design parameters are statistically significant for obtaining a low coefficient of friction (COF) and low wear rate with waste palm oil blended with SAE 40. The tribology performance was evaluated using a piston-ring-liner contact tester. The design of experiment (DOE) was constructed by using response surface methodology (RSM) to minimize the number of experimental conditions and to develop a mathematical model between the key process parameters such as rotational speeds (200 rpm to 300 rpm), volume concentration (0% to 10% waste oil), and applied loads (2 kg to 9 kg). Analysis of variance (ANOVA) test was also carried out to check the adequacy of the empirical models developed. Scanning electron microscopy (SEM) was used to examine the damage features at the worn surface under lubricant contact conditions.
In this paper the solar radiation forecasting in Pekan located in Pahang is presented. The time series utilized are 10 minute solar radiation data obtained directly from the measurements realized in the sites during about one month. In order to do solar radiation forecasting, quick propagation algorithms Artificial Neural Network (ANN) models were developed. Around 1617 data's are taken to train ANN. The effects of temperature, humidity, wind speed, wind chill, pressure and rain on solar radiation are discussed in this paper. The maximum mean absolute percentage error was found to be less than 7.74% and R-squared (R2) values were found to be about 98.9% for the testing stations. However, these values were found to be 5.398% and 97.9 % for the training stations. The trained and tested ANN models show greater accuracy for evaluating the solar radiation. The predicted solar potential values from the ANN are given in the form of table where included the other variables such as temperature, humidity, wind speed, wind chill, pressure and rain. This table is of prime importance for different working disciplines, like scientists, architects, meteorologists and solar engineers, in Malaysia. The predictions from the ANN models could enable scientists to locate and design solar energy systems in Malaysia and determine the best solar technology
The main objective of this article is to investigate wind and solar potential in Universiti Malaysia Pahang renewable energy resources as response to Malaysian government regarding to green technology. It is a preliminary study mainly focuses on technique of measurement and collecting potential wind and solar data. The first solar panels installation was planned to be inside Universiti Malaysia Pahang with the first wind turbine being installed at the bank of the Sungai Pahang in Pekan, Pahang. The local solar radiation regime was described with on-site measurements and calculations where the former was carried out from the beginning of 2010. The setup of the measurement device is discussed in this paper.
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