Modeling is a very useful method for the performance prediction of concrete. Most of the models available in literature are related to the compressive strength because it is a major mechanical property used in concrete design. Many attempts were taken to develop suitable mathematical models for the prediction of compressive strength of different concretes, but not for self-consolidating high-strength concrete (SCHSC) containing palm oil fuel ash (POFA). The present study has used artificial neural networks (ANN) to predict the compressive strength of SCHSC incorporating POFA. The ANN model has been developed and validated in this research using the mix proportioning and experimental strength data of 20 different SCHSC mixes. Seventy percent (70%) of the data were used to carry out the training of the ANN model. The remaining 30% of the data were used for testing the model. The training of the ANN model was stopped when the root mean square error (RMSE) and the percentage of good patterns was 0.001 and ≈100%, respectively. The predicted compressive strength values obtained from the trained ANN model were much closer to the experimental values of compressive strength. The coefficient of determination (R²) for the relationship between the predicted and experimental compressive strengths was 0.9486, which shows the higher degree of accuracy of the network pattern. Furthermore, the predicted compressive strength was found very close to the experimental compressive strength during the testing process of the ANN model. The absolute and percentage relative errors in the testing process were significantly low with a mean value of 1.74 MPa and 3.13%, respectively, which indicated that the compressive strength of SCHSC including POFA can be efficiently predicted by the ANN.
The contribution of palm oil fuel ash (POFA), an agricultural waste as a low cost adsorbent for the removal of arsenite (As(III)) and arsenate (As(V)) was explored. Investigation on the adsorbency characteristics of POFA suspension revealed that the surface area, particle size, composition, and crystallinity of the SiO2 rich mullite structure were the crucial factors in ensuring a high adsorption capacity of the ions. Maximum adsorption capacities of As(III) and As(V) at 91.2 and 99.4 mg g-1, respectively, were obtained when POFA of 30 μm particle size was employed at pH 3 with the highest calcination temperature at 1150 °C. An optimum dosage of 1.0 g of dried POFA powder successfully removed 48.7% and 50.2% of As(III) and As(V), respectively. Molecular modeling using the density functional theory consequently identified the energy for the proposed reaction routes between the SiO- and As+ species. The high stability of the POFA suspension in water in conjunction with good adsorption capacity of As(III) and As(V) seen in this study, thus envisages its feasibility as a potential alternative absorbent for the remediation of water polluted with heavy metals.
The carbonation rate of reinforced concrete is influenced by three parameters, namely temperature, relative humidity, and concentration of carbon dioxide (CO₂) in the surroundings. As knowledge of the service lifespan of reinforced concrete is crucial in terms of corrosion, the carbonation process is important to study, and high-performance durable reinforced concretes can be produced to prolong the effects of corrosion. To examine carbonation resistance, accelerated carbonation testing was conducted in accordance with the standards of BS 1881-210:2013. In this study, 10⁻30% of micro palm oil fuel ash (mPOFA) and 0.5⁻1.5% of nano-POFA (nPOFA) were incorporated into concrete mixtures to determine the optimum amount for achieving the highest carbonation resistance after 28 days water curing and accelerated CO₂ conditions up to 70 days of exposure. The effect of carbonation on concrete specimens with the inclusion of mPOFA and nPOFA was investigated. The carbonation depth was identified by phenolphthalein solution. The highest carbonation resistance of concrete was found after the inclusion of 10% mPOFA and 0.5% nPOFA, while the lowest carbonation resistance was found after the inclusion of 30% mPOFA and 1.5% nPOFA.
This study involves the use of quality engineering in oil spill classification based on oil spill fingerprinting from GC-FID and GC-MS employing the six-sigma approach. The oil spills are recovered from various water areas of Peninsular Malaysia and Sabah (East Malaysia). The study approach used six sigma methodologies that effectively serve as the problem solving in oil classification extracted from the complex mixtures of oil spilled dataset. The analysis of six sigma link with the quality engineering improved the organizational performance to achieve its objectivity of the environmental forensics. The study reveals that oil spills are discriminated into four groups' viz. diesel, hydrocarbon fuel oil (HFO), mixture oil lubricant and fuel oil (MOLFO) and waste oil (WO) according to the similarity of the intrinsic chemical properties. Through the validation, it confirmed that four discriminant component, diesel, hydrocarbon fuel oil (HFO), mixture oil lubricant and fuel oil (MOLFO) and waste oil (WO) dominate the oil types with a total variance of 99.51% with ANOVA giving Fstat>Fcritical at 95% confidence level and a Chi Square goodness test of 74.87. Results obtained from this study reveals that by employing six-sigma approach in a data-driven problem such as in the case of oil spill classification, good decision making can be expedited.
This paper presents novel research on the development of a generic intelligent oil fraction sensor based on Electrical Capacitance Tomography (ECT) data. An artificial Neural Network (ANN) has been employed as the intelligent system to sense and estimate oil fractions from the cross-sections of two-component flows comprising oil and gas in a pipeline. Previous works only focused on estimating the oil fraction in the pipeline based on fixed ECT sensor parameters. With fixed ECT design sensors, an oil fraction neural sensor can be trained to deal with ECT data based on the particular sensor parameters, hence the neural sensor is not generic. This work focuses on development of a generic neural oil fraction sensor based on training a Multi-Layer Perceptron (MLP) ANN with various ECT sensor parameters. On average, the proposed oil fraction neural sensor has shown to be able to give a mean absolute error of 3.05% for various ECT sensor sizes.
Extended use of GC-FID and GC-MS in oil spill fingerprinting and matching is significantly important for oil classification from the oil spill sources collected from various areas of Peninsular Malaysia and Sabah (East Malaysia). Oil spill fingerprinting from GC-FID and GC-MS coupled with chemometric techniques (discriminant analysis and principal component analysis) is used as a diagnostic tool to classify the types of oil polluting the water. Clustering and discrimination of oil spill compounds in the water from the actual site of oil spill events are divided into four groups viz. diesel, Heavy Fuel Oil (HFO), Mixture Oil containing Light Fuel Oil (MOLFO) and Waste Oil (WO) according to the similarity of their intrinsic chemical properties. Principal component analysis (PCA) demonstrates that diesel, HFO, MOLFO and WO are types of oil or oil products from complex oil mixtures with a total variance of 85.34% and are identified with various anthropogenic activities related to either intentional releasing of oil or accidental discharge of oil into the environment. Our results show that the use of chemometric techniques is significant in providing independent validation for classifying the types of spilled oil in the investigation of oil spill pollution in Malaysia. This, in consequence would result in cost and time saving in identification of the oil spill sources.
Domestic wastewater has been generated massively along with rapid growth of population and economic. Biological treatment using sequencing batch reactor (SBR) augmented with palm oil fuel ash (POFA) was investigated for the first time. The performance of POFA in enhancing biological treatment of wastewater has not been tested. The porosity property of POFA can improve SBR efficiency by promoting growth of mixed liquor suspended solids (MLSS) and formation of larger flocs for settling and facilitating attachment of microorganisms and pollutants onto POFA surfaces. The properties of POFA were tested to identify morphological properties, particle size, surface area, chemical compositions. Four SBRs, namely SBR1, SBR2, SBR3 and SBR4 were provided with aeration rate of 1, 2, 3 and 4 L/min, respectively. Each reactor was augmented with different dosages of POFA. Optimum aeration rate and POFA concentration were identified by the performance of SBRs in removing chemical oxygen demand (COD), ammoniacal nitrogen (NH3-N) and colour from domestic wastewater. The results showed the most efficient COD (97.8%), NH3-N (99.4%) and colour (98.8%) removals were achieved at optimum POFA concentration of 4 g/L in SBR and aeration rate of 1 L/min. The study also found that higher aeration rate would contribute to the smaller specific size of flocs and decrease the pollutant removal efficiency.
Recently, the graphite based materials have gained interest as excellent platforms to remove aqueous pollutants via adsorption routes. This is given that such materials possess large specific surface area and low density. In the present work, a comparative study of two facile and effective approaches is conventional thermal heating and microwave irradiation methods to fabricate expanded graphite from available flake graphite sources of Vietnam for oil-contaminated water purification. The as-prepared expanded graphite was characterized by using FT-IR, SEM, XRD and BET analysis. The results exhibited that expanded graphite has multilevel pore structures and the surface area of expanded graphite obtained from microwave irradiation and conventional heating was 147.5 (m²/g) and 100.97 (m²/g) under optimal processing conditions. The as-synthesized expanded graphite from the microwave irradiation method was found to have higher adsorption capacities for diesel oil, crude oil, and fuel oil compared to conventional heating method.
Energy has a significant influence on Malaysia's industry. It is used in electricity generation, refineries, gas processing plants and end-user applications such as transportation, residential, agriculture and fishing. These burning fossil fuel activities produce greenhouse gases (GHG) emissions. This article presents the emissions data of fuel used in power plants in Malaysia during the year of 1990 until 2017. The fuel used in power plants is coal and coke, natural gas, diesel oil and residual fuel oil. The energy data used in power plants were gathered from the Malaysia Energy Information Hub, published by the Malaysian Energy Commission. The GHG emissions data were calculated using the emission factors method. The climate impact of different GHGs in terms of CO2-equivalent (CO2-e) was also calculated using global warming potentials. The article also presents population data in Malaysia during the year. A correlation between the fuels, GHG emission and the population is also investigated using statistical analysis. The data presented here may facilitate the Malaysian government to identify the source of the pollutants and undertake a climate change mitigation plan.
Recently, as a supplement of cement, the utilization of pozzolanic materials in cement and concrete manufacturing has increased significantly. This study investigates the scope to use pozzolanic wastes (slag, palm oil fuel ash and rice husk ash) as an alkali activated binder (AAB) that can be used as an alternative to cement. To activate these materials, sodium hydroxide solution was used at 1.0, 2.5 and 5.0 molar concentration added into the mortar, separately. The required solution was used to maintain the flow of mortar at 110% ± 5%. The consistency and setting time of the AAB-paste were determined. Mortar was tested for its flow, compressive strength, porosity, water absorption and thermal resistance (heating at 700 °C) and investigated by scanning electron microscopy. The experimental results reveal that AAB-mortar exhibits less flow than that of ordinary Portland cement (OPC). Surprisingly, AAB-mortars (with 2.5 molar solution) achieved a compressive strength of 34.3 MPa at 28 days, while OPC shows that of 43.9 MPa under the same conditions. Although water absorption and porosity of the AAB-mortar are slightly high, it shows excellent thermal resistance compared to OPC. Therefore, based on the test results, it can be concluded that in the presence of a chemical activator, the aforementioned pozzolans can be used as an alternative material for cement.
The production of cement contributes to 10% of global carbon dioxide (CO2) pollution and 74 to 81% towards the total CO2 pollution by concrete. In addition to that, its low strength-to-weight ratio, high density and thermal conductivity are among the few limitations of heavy weight concrete. Therefore, this study was carried out to provide a solution to these limitations by developing innovative eco-friendly lightweight foamed concrete (LFC) of 1800 kg/m3 density incorporating 20-25% palm oil fuel ash (POFA) and 5-15% eggshell powder (ESP) by weight of total binder as supplementary cementitious material (SCM). The influence of combined utilization of POFA and ESP on the fresh state properties of eco-friendly LFC was determined using the J-ring test. To determine the mechanical properties, a total of 48 cubes and 24 cylinders were prepared for compressive strength, splitting tensile strength and modulus of elasticity each. A total of 24 panels were prepared to determine the thermal properties in terms of surface temperature and thermal conductivity. Furthermore, to assess the environmental impact and eco-friendliness of the developed LFC, the embodied carbon and eco-strength efficiency was calculated. It was determined that the utilization of POFA and ESP reduced the workability slightly but enhanced the mechanical properties of LFC (17.05 to 22.60 MPa compressive strength and 1.43 to 2.61 MPa tensile strength), thus satisfies the ACI213R requirements for structural lightweight concrete and that it can be used for structural applications. Additionally, the thermal conductivity reduced ranging from 0.55 to 0.63 W/mK compared to 0.82 W/mK achieved by control sample. Furthermore, the developed LFC showed a 16.96 to 33.55% reduction in embodied carbon and exhibited higher eco-strength efficiency between 47.82 and 76.97%. Overall, the combined utilization of POFA and ESP as SCMs not only enhanced the thermo-mechanical performance, makes the sustainable LFC as structural lightweight concrete, but also has reduced the environmental impacts caused by the disposal of POFA and ESP in landfills as well as reducing the total CO2 emissions during the production of eco-friendly LFC.
The characteristics and water/oil sorption effectiveness ofkapok fibre, sugarcane bagasse and rice husks have been compared. The three biomass types were subjected to field emission scanning electron microscopy-energy dispersive X-ray spectroscopy and surface tension analyses for liquid-air and oil-water systems were conducted. Both kapok fibre and sugarcane bagasse exhibit excellent oil sorption capabilities for diesel, crude, new engine and used engine oils as their oil sorption capacities all exceed 10 g/g. The synthetic sorbent exhibits oil sorption capacities comparable with sugarcane bagasse, while rice husks exhibit the lowest oil sorption capacities among all the sorbents. Kapok fibre shows overwhelmingly high oil-to-water sorption (O/W) ratios ranging from 19.35 to 201.53 while sugarcane bagasse, rice husks and synthetic sorbent have significantly lower O/W ratios (0.76-2.69). This suggests that kapok fibre is a highly effective oil sorbent even in well-mixed oil-water media. An oil sorbent suitability matrix is proposed to aid stakeholders in evaluating customized oil removal usage of the natural sorbents.
A sustainable super-hydrophobic coating composed of silica from palm oil fuel ash (POFA) and polydimethylsiloxane (PDMS) was synthesised using isopropanol as a solvent and coated on a glass substrate. FESEM and AFM analyses were conducted to study the surface morphology of the coating. The super-hydrophobicity of the material was validated through goniometry, which showed a water contact angle of 151°. Cytotoxicity studies were conducted by assessing the cell viability and cell morphology of mouse fibroblast cell line (L929) and hamster lung fibroblast cell line (V79) via tetrazolium salt 3-(4-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and microscopic methods, respectively. The clonogenic assay was performed on cell line V79 and the cell proliferation assay was performed on cell line L929. Both results validate that the toxicity of PDMS: SS coatings is dependent on the concentration of the super-hydrophobic coating. The results also indicate that concentrations above 12.5 mg/mL invariably leads to cell toxicity. These results conclusively support the possible utilisation of the synthesised super-hydrophobic coating for biomedical applications.
Palm oil fuel ash (POFA) is an agricultural waste which was employed in this study to produce novel adsorptive ceramic hollow fibre membranes. The membranes were fabricated using phase inversion-based extrusion technique and sintered at 1150 °C. The membranes were then evaluated on their ability to adsorb cadmium (Cd(II)). These membranes were characterised using (nitrogen) N2 adsorption-desorption analysis, field emission scanning electron microscopy-energy-dispersive X-ray spectroscopy (FESEM-EDX) mapping, X-ray fluorescence (XRF), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR) analyses while adsorptivity activity was examined by batch adsorption studies. The adsorption test results show that the quantity of hollow fibre used and water pH level significantly affected the adsorption performance with the 3-fibre membrane yielding 96.4% Cd(II) removal in 30 min equilibrium time at pH 7. These results are comparable to those reported by other studies, and hence demonstrate a promising alternative of low-cost hollow fibre adsorbent membrane. Graphical abstract Figure of FESEM image of the hollow fibre, proposed mechanism and the graph of percentage removal of Cd(II) using POFA.