This paper simulates and predicts the laminar flow inside the 3D aneurysm geometry, since the hemodynamic situation in the blood vessels is difficult to determine and visualize using standard imaging techniques, for example, magnetic resonance imaging (MRI). Three different types of Lattice Boltzmann (LB) models are computed, namely, single relaxation time (SRT), multiple relaxation time (MRT), and regularized BGK models. The results obtained using these different versions of the LB-based code will then be validated with ANSYS FLUENT, a commercially available finite volume- (FV-) based CFD solver. The simulated flow profiles that include velocity, pressure, and wall shear stress (WSS) are then compared between the two solvers. The predicted outcomes show that all the LB models are comparable and in good agreement with the FVM solver for complex blood flow simulation. The findings also show minor differences in their WSS profiles. The performance of the parallel implementation for each solver is also included and discussed in this paper. In terms of parallelization, it was shown that LBM-based code performed better in terms of the computation time required.
Traumatic brain injury (TBI) is one of the injuries that can bring serious consequences if medical attention has been delayed. Commonly, analysis of computed tomography (CT) or magnetic resonance imaging (MRI) is required to determine the severity of a moderate TBI patient. However, due to the rising number of TBI patients these days, employing the CT scan or MRI scan to every potential patient is not only expensive, but also time consuming. Therefore, in this paper, we investigate the possibility of using electroencephalography (EEG) with computational intelligence as an alternative approach to detect the severity of moderate TBI patients. EEG procedure is much cheaper than CT or MRI. Although EEG does not have high spatial resolutions as compared with CT and MRI, it has high temporal resolutions. The analysis and prediction of moderate TBI from EEG using conventional computational intelligence approaches are tedious as they normally involve complex preprocessing, feature extraction, or feature selection of the signal. Thus, we propose an approach that uses convolutional neural network (CNN) to automatically classify healthy subjects and moderate TBI patients. The input to this computational intelligence system is the resting-state eye-closed EEG, without undergoing preprocessing and feature selection. The EEG dataset used includes 15 healthy volunteers and 15 moderate TBI patients, which is acquired at the Hospital Universiti Sains Malaysia, Kelantan, Malaysia. The performance of the proposed method has been compared with four other existing methods. With the average classification accuracy of 72.46%, the proposed method outperforms the other four methods. This result indicates that the proposed method has the potential to be used as a preliminary screening for moderate TBI, for selection of the patients for further diagnosis and treatment planning.
Microbial fuel cell (MFC) would be a standalone solution for clean, sustainable energy and rural electrification. It can be used in addition to wastewater treatment for bioelectricity generation. Materials chosen for the membrane and electrodes are of low cost with suitable conducting ions and electrical properties. The prime objective of the present work is to enhance redox reactions by using novel and low-cost cathode catalysts synthesized from waste castor oil. Synthesized graphene has been used as an anode, castor oil-emitted carbon powder serves as a cathode, and clay material acts as a membrane. Three single-chambered MFC modules developed were used in the current study, and continuous readings were recorded. The maximum voltage achieved was 0.36 V for a 100 mL mixture of domestic wastewater and cow dung for an anodic chamber of 200 mL. The maximum power density obtained was 7280 mW/m2. In addition, a performance test was evaluated for another MFC with inoculums slurry, and a maximum voltage of 0.78 V and power density of 34.4093 mW/m2 with an anodic chamber of 50 mL was reported. The present study's findings show that such cathode catalysts can be a suitable option for practical applications of microbial fuel cells.
In this work, the piezoresistive effects of defective graphene used on a flexible pressure sensor are demonstrated. The graphene used was deposited at substrate temperatures of 750, 850 and 1000 °C using the hot-filament thermal chemical vapor deposition method in which the resultant graphene had different defect densities. Incorporation of the graphene as the sensing materials in sensor device showed that a linear variation in the resistance change with the applied gas pressure was obtained in the range of 0 to 50 kPa. The deposition temperature of the graphene deposited on copper foil using this technique was shown to be capable of tuning the sensitivity of the flexible graphene-based pressure sensor. We found that the sensor performance is strongly dominated by the defect density in the graphene, where graphene with the highest defect density deposited at 750 °C exhibited an almost four-fold sensitivity as compared to that deposited at 1000 °C. This effect is believed to have been contributed by the scattering of charge carriers in the graphene networks through various forms such as from the defects in the graphene lattice itself, tunneling between graphene islands, and tunneling between defect-like structures.
Sand production remains a huge obstacle in many oil and gas fields around the world, but the hazards of contaminants riding on the produced sand are often not emphasised. Improper disposal of the sand could see the toxic leaching into the environment including the food chain, endangering all living organisms. The impending sand production from an oilfield offshore Sabah also suffers from the lack of hazards identification; hence, this study was conducted to assess the contaminant on the produced sand. Sand samples were collected from multiple wells in the area, with the contaminants extracted using n-hexane and subjected to chemical and thermal analyses. FTIR and GC-MS detected traces of harmful pollutants like naphthalene, amine substances, cyclohexanol, and short-chain alkanes. It was discovered that the volatile fraction of the contaminants was able to evaporate at 33 °C, while high energy was needed to remove 100% of the contaminants from the sand. Overall, the produced sand from the oilfield was unsafe and required treatment before it could be dumped or used.
The generation of power and fuel sustainability that contributes to a cleaner output of exhaust gases is one of the most important objectives the world seeks. In this paper, oxyhydrogen gas is used to retrofit into a two-stroke engine. The water was electrolysed and generated a mixture of oxygen (O2) and hydrogen (H2) or known as oxyhydrogen (HHO) gas via an electrolytic dry cell generator. The HHO was retrofitted experimentally to investigate the engine emissions and exhaust gas temperature from a 1.5 kW gasoline engine. The engine was tested with different power ratings (84-720 W) to investigate the performance and emissions of the engine using gasoline followed by the addition of HHO. The emissions of CO and NOx were measured with different amounts of HHO added. The exhaust temperature was calculated as one of the variables to be considered in relation to pollution. The air-fuel ratios are varied from 12 to 20% in the experiment. The most appropriate air-fuel ratio needed to start the generator with the most environmentally friendly gas emission was analysed. The results showed that the addition of HHO to the engine is successful in reducing fuel consumption up to 8.9%. A higher percentage of HHO added also has improved the emissions and reduced exhaust gas temperature. In this study, the highest quantity of HHO added at 0.15% of the volume fraction reduced CO gas emission by up to 9.41%, NOx gas up to 4.31%, and exhaust gas temperature by up to 2.02%. Generally, adding oxyhydrogen gas has significantly reduced the emissions, and exhaust temperature and provided an eco-friendly environment.