ORCID Profile
0000-0001-5120-1345
Current Organisation
Universiti Putra Malaysia
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Publisher: Springer Science and Business Media LLC
Date: 16-05-2018
Publisher: Elsevier BV
Date: 02-2022
Publisher: Elsevier BV
Date: 02-2023
Publisher: Springer Science and Business Media LLC
Date: 03-10-2013
Publisher: Informa UK Limited
Date: 10-2011
Publisher: Elsevier BV
Date: 10-2019
Publisher: EDP Sciences
Date: 2018
DOI: 10.1051/E3SCONF/20183402007
Abstract: Electric Arc Furnace steel slag (EAFS) is the waste produced in steelmaking industry. Environmental problem such as pollution will occur when dumping the steel slag waste into the landfill. These steel slags have properties that are suitable for various applications such as water treatment and wastewater. The objective of this study is to develop efficient and economical chlorination route for EAFS extraction by using leaching process. Various parameters such as concentration of hydrochloric acid, particle size of steel slag, reaction time and reaction temperature are investigated to determine the optimum conditions. As a result, the dissolution rate can be determined by changing the parameters, such as concentration of hydrochloric acid, particle size of steel slag, reaction time and reaction temperature. The optimum conditions for dissolution rates for the leaching process is at 3.0 M hydrochloric acid, particle size of 1.18 mm, reaction time of 2.5 hour and the temperature of 90°C.
Publisher: Elsevier BV
Date: 2017
Publisher: Wiley
Date: 23-02-2022
DOI: 10.1002/PRS.12346
Abstract: The new Fourth Industrial Revolution (IR 4.0) trend is driven by the concept of automation and artificial intelligence (AI). However, Malaysia is slightly behind Singapore in terms of adopting AI innovation among ASEAN countries. This paper aims to conduct a literature review of machine learning to overcome subjectivity and bias in risk ranking decision‐making. An introduction to machine learning concerning accident risk analysis is presented, and the challenges of its application in Malaysia are discussed. Existing machine learning features were evaluated to identify the feasible application in industrial accident analysis and ensure safety decision‐making consistency. This review observed how the IR 4.0 approaches were used in the risk analysis, especially on supervised machine learning. This study also highlights the finding from the previous works on challenges in utilizing supervised machine learning, which is the need to have publicly accessible large database from industries and agencies such as the Department of Occupational Safety and Health (DOSH) Malaysia for the development of algorithms, which can potentially improve accident risk analysis and safety, especially for Malaysian industries.
Publisher: American Chemical Society (ACS)
Date: 16-12-2012
DOI: 10.1021/JP209512N
Publisher: MDPI AG
Date: 31-03-2023
DOI: 10.3390/EN12010041
Abstract: For a gas-liquid separator sizing, many engineers have neglected the flow pattern of incoming fluids. The impact of inlet slug flow which impeded onto the separator’s liquid phase will cause a separator fails to perform when sloshing happened in the separator. To date, the study on verifying the impact of inlet slug flow in a separator remains limited. In this paper, the impact of inlet momentum and inlet slug flow on the hydrodynamics in a separator for cases without an inlet device were investigated. The experimental and Computational Fluid Dynamics (CFD) results of cavity formation and sloshing occurrence in the separator in this study were compared. A User Defined Function (UDF) was used to describe the inlet slug flow at the separator inlet. Inlet slug flow occurred at inlet momentum from 200 to 1000 Pa, and sloshing occurred in the separator at 1000 Pa. Both experimental and simulated results showed similar phenomena.
Publisher: IOP Publishing
Date: 10-2017
Publisher: Elsevier BV
Date: 07-2012
Publisher: IOP Publishing
Date: 04-2020
DOI: 10.1088/1757-899X/811/1/012006
Abstract: Calculation work is carried out in the present project to study the effect of different parameters on hydrodynamics of gas-liquid flow by using CFD. The steady state and transient, three dimensional simulations are performed of the whole bubble column for various inlet gas and sparger designs. A standard k- ε is used to describe turbulence occurring in the continuous fluid. Results show he asymmetric recirculation stronger with an increase in the number of holes giving better mixing. The gas hold-up increased with superficial gas velocity but independent of the sparger design at high velocity. Comparison of simulation results with the previous experimental work data has provided a successful validation of the model.
Publisher: Springer Science and Business Media LLC
Date: 23-02-2011
Publisher: Elsevier BV
Date: 10-2013
Publisher: Bulletin of Chemical Reaction Engineering and Catalysis
Date: 09-07-2020
DOI: 10.9767/BCREC.15.2.6774.568-578
Abstract: In this study, the dehydrogenation of cyclohexanol to cyclohexanone over nitrogen-doped reduced graphene oxide (N-rGO) Cu catalyst has been reported. The N-rGO support was synthesized by chemical reduction of graphite oxide (GO). The synthesized N-rGO was used as a support to prepare the Cu/N-rGO catalyst via an incipient wet impregnation method. The as-prepared support and the Cu/N-rGO catalyst were characterized by FESEM, EDX, XRD, TEM, TGA, and Raman spectroscopy. The various characterization analysis revealed the suitability of the Cu/N-rGO as a heterogeneous catalyst that can be employed for the dehydrogenation of cyclohexanol to cyclohexanone. The catalytic activity of the Cu/N-rGO catalyst was tested in non-oxidative dehydrogenation of cyclohexanol to cyclohexanone using a stainless-steel fixed bed reactor. The effects of temperature, reactant flow rate, and time-on-stream on the activity of the Cu/N-rGO catalyst were examined. The Cu/N-rGO nanosheets show excellent catalytic activity and selectivity to cyclohexanone. The formation of stable Cu nanoparticles on N-rGO support interaction and segregation of Cu were crucial factors for the catalytic activity. The highest cyclohexanol conversion and selectivity of 93.3% and 82.7%, respectively, were obtained at a reaction temperature of 270 °C and cyclohexanol feed rate of 0.1 ml/min. Copyright © 2020 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (icenses/by-sa/4.0).
Publisher: Elsevier BV
Date: 05-2021
No related grants have been discovered for Musab Abdul Razak.