Universiti Teknologi Petronas

About: Universiti Teknologi Petronas is a education organization based out in Ipoh, Malaysia. It is known for research contribution in the topics: Adsorption & Ionic liquid. The organization has 6127 authors who have published 11284 publications receiving 119400 citations.

Natural fiber reinforced poly(vinyl chloride) composites : a review.

Abstract: Materials from renewable resources – also called biomaterials or ‘green’ materials – are presently gaining in importance worldwide. In these times of continuous increases in the price of crude oil ...

What make consumer sign up to PHEVs? Predicting Malaysian consumer behavior in adoption of PHEVs

Abstract: Malaysia is amongst the major energy intense countries and is under an excessive burden to advance its energy efficiency and to also work towards the reduction of its carbon emission. Plug-in Hybrid Electric Vehicles (PHEVs) have the potential to lessen the carbon emission and gasoline consumption in order to alleviate environmental problems. Consequently, attempts are being initiated to popularise the use of PHEVs as the main mode of transportation. The diffusion of PHEV adoption is a positive initiative. A sample of 403 respondents has been collected from Malaysia in order to forecast the customer’s intention to adopt PHEVs by using the extended theory of planned behaviour. The empirical outcome using the PLS investigation exposed that all four constructs, subjective norm, personal moral norm, perceived behavioural control, and attitude ominously shows an indirect effect which has inclined towards the Malaysian consumers’ intention to adopt PHEVs. All these four major constructs were significantly predetermined by their respective environmental concern. Whereas, hyperbolic discounting moderated the relationship between intention and adoption. The fostering result verifies that the relevance of the extended TPB had a good explanatory power in the line of predicting the Malaysian consumers’ intention to adopt PHEVs. For future study, grounded by the observed outcome, authors explain the implication aimed at promoting the PHEV adoption.

Using artificial neural networks to estimate solar radiation in Kuwait

Abstract: It is an aim of the Kuwaiti government to achieve more penetration levels of renewable energy sources into the national electric grid. Among the various available renewable energy alternatives, solar power generation imposes itself as the most feasible and reasonable solution for a greener Kuwait. In Kuwait, hours of sunshine range between 7 h per day in December and 11 per day in August. On average, there are about 3347 sunshine hours per year, which make it an ideal place for massive solar energy generation. This massive potential for solar energy will reduce Kuwait's dependency on oil and other fossil fuels and lead to a more secure power supply, a modernized Kuwaiti electric network, more job vacancies, and a dramatically cleaner environment. It is essential to quantify the amounts of solar radiation recorded during the past few years and to make projections for the future. In this paper, a model forecaster for the daily average solar radiation in Kuwait has been developed. The forecasting model is based on artificial neural networks that are able to cope with nonlinear data. Actual data from five different Kuwaiti sites were used as training/testing data while developing the model. The developed forecaster is intended to help country officials, prospective investors, and power system engineers choose locations for solar installation and assess the techno-economic merits of large-scale solar energy integration.