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Johor Bahru, Malaysia

Saud S.N.,University of Technology Malaysia | Hamzah E.,University of Technology Malaysia | Abubakar T.,University of Technology Malaysia | Raheleh Hosseinian S.,1310 UTM Johor Bahru
Jurnal Teknologi (Sciences and Engineering) | Year: 2013

Cu-Al-Ni shape memory alloys (SMAs) have been developed for high temperatures engineering components such as sensor and actuators, due to their ability to work at temperatures near 200°C, rather than NiTi and Cu-Zn-Al alloys whose maximum working temperatures around 100°C. These alloys are widely used because they are much cheaper than NiTi/Cu-Zn-Al and do not require any complicated processing during their manufacturing as do for other shape memory alloys. In addition, these alloys have a small hysteresis and high transformation temperatures compared with other alloys. Despite all these advantages, these alloys have their limitations such as brittleness and low phase recovery strains and stress. The present review describes the role of alloying elements on the properties of Cu-Al-Ni shape memory alloys. It has been found that the additions of alloying elements have a significant effect on the formation, morphology, and structure of the obtained martensite, therefore, the properties of these alloys varied in accordance of these effects. © 2013 Penerbit UTM Press. All rights reserved. Source

Yusof F.,1310 UTM Johor Bahru | Kane I.L.,1310 UTM Johor Bahru | Kane I.L.,Umaru Musa YarAdua University | Yusop Z.,University of Technology Malaysia
Jurnal Teknologi (Sciences and Engineering) | Year: 2013

The dependence structure of rainfall is usually very complex both in time and space. It is shown in this paper that the daily rainfall series of Ipoh and Alorsetar are affected by nonlinear characteristics of the variance often referred to as variance clustering or volatility, where large changes tend to follow large changes and small changes tend to follow small changes. In most empirical modeling of hydrological time series, the focus was on modeling and predicting the mean behavior of the time series through conventional methods of an Autoregressive Moving Average (ARMA) modeling proposed by the Box Jenkins methodology. The conventional models operate under the assumption that the series is stationary that is: constant mean and either constant variance or season-dependent variances, however, does not take into account the second order moment or conditional variance, but they form a good starting point for time series analysis. The residuals from preliminary ARIMA models derived from the daily rainfall time series were tested for ARCH behavior. The autocorrelation structure of the residuals and the squared residuals were inspected, the residuals are uncorrelated but the squared residuals show autocorrelation, the Ljung-Box test confirmed the results. McLeod-Li test and a test based on the Lagrange multiplier (LM) principle were applied to the squared residuals from ARIMA models. The results of these auxiliary tests show clear evidence to reject the null hypothesis of no ARCH effect. Hence indicates that GARCH modeling is necessary. Therefore the composite ARIMA-GARCH model captures the dynamics of the daily rainfall series in study areas more precisely. On the other hand, Seasonal ARIMA model became a suitable model for the monthly average rainfall series of the same locations treated. © 2013 Penerbit UTM Press. All rights reserved. Source

Tan W.L.,1310 UTM Johor Bahru | Yusof F.,1310 UTM Johor Bahru | Yusop Z.,Institute of Environmental and Water Resource Management IPASA
Jurnal Teknologi (Sciences and Engineering) | Year: 2013

The non-homogeneous hidden Markov model (NHMM) generates the rainfall observation depends on few weather states which serve as a link between the large scale atmospheric measures. The daily rainfall at 20 stations from Peninsular Malaysia for 33 years sequences is analyzed using NHMM during the northeast monsoon season. A NHMM with six hidden states are identified. The atmospheric variable was obtained from NCEP Reanalysis Data as predictor. The gridded atmospheric fields are summarized through the principle component analysis (PCA) technique. PCA is applied to sea level pressure (SLP) to identify their principal spatial patterns co-varying with rainfall. The NHMM can accurately simulate the observed daily mean rainfall, correlations between stations for daily rainfall amounts and the quantile- quantile plots. It can be concluded that the NHMM is a useful method to simulate the daily rainfall amounts that may be used to prepare strategies and planning for the unpredicted disaster such as flood and drought. © 2013 Penerbit UTM Press. All rights reserved. Source

Suhaila J.,1310 UTM Johor Bahru | Ching-Yee K.,1310 UTM Johor Bahru | Yusof F.,1310 UTM Johor Bahru | Hui-Mean F.,1310 UTM Johor Bahru
Jurnal Teknologi (Sciences and Engineering) | Year: 2013

Flood is a commonly occurring hazard in Malaysia. The climate change in combination with the sea level rise will affected the frequency of flood events especially in a tropical country like Malaysia. Many researches focused on modeling rainfall data have been carried out in Malaysia. However, most of the rainfall studies did not include the zero values. The importance of these zero measurements should be examined in order to increase the quality of the research. The main purpose of this paper is to study the effect of zero measurement in rainfall analysis by applying a mixed bivariate lognormal distribution. The inter-station correlation coefficient was calculated in three cases of datasets. The first case considered only the positive values at both stations, and the second case included the positive values at either one of the stations, while the third case considered all values including zeroes at both rainfall stations. It was found that only the cases considering the positive measurements are useful and valid for the characterization of rainfall fields in our analysis. © 2013 Penerbit UTM Press. All rights reserved. Source

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