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Hydraulic fracturing drilling technology can cause a high risk of surface spill accidents and thus water contamination. Climate change together with the high water demand and rapid increase in industrial and agricultural activities are valued reasons why we should all care about the availability of water resources and protect them from contamination. Hence, the purpose of this study is to estimate the risk associated with a site contaminated with benzene from oil spillage and its potential impact on groundwater. This study focused on investigating the impact of soil variability and water table depth on groundwater contamination. Temperature-dependent parameters, such as soil water content and the diffusion of pollutants, were considered as key input factors for the HYDRUS 1D numerical model to simulate benzene migration through three types of soil (loamy, sandy clay loam, and silt loam) and evaluate its concentration in the water aquifer. The results indicated that an anticipated increase in earth’s average surface temperature by 4 °C due to climate change could lead to a rise in the level of groundwater pollution in the study area by 0.017 mg/L in loamy soil, 0.00046 mg/L in sandy clay loam soil, and 0.00023 mg/L in silt loam soil. It was found that climate change can reduce the amount of benzene absorbed from 10 to 0.07% in loamy soil, 14 to 0.07% in sandy clay loam soil, and 60 to 53% in silt loam soil. The results showed that the soil properties and solute characteristics that depend on the temperature have a major and important role in determining the level of groundwater pollutants.

The idea of shipping container house is no longer a revolutionized to western country but in Asia country particularly in Malaysia it is relatively new. The idea of container house is relatively new and there is no clear sign of how far does Malaysian citizen can accept this idea. There is no indicator of what are the expectations from Malaysian citizen about the container house. This research serves as basic references for both government and private sector to the future property industry development of shipping container house as well as shipping container non-residential building in Malaysia to pursue Malaysia’s unity, economic and national integration. The purpose of this study is to test the feasibility of using ISO shipping container to build low cost house. Four set of questionnaires are prepared to assess the opinion of respondents about the acceptance of shipping container house. The result obtained is that the acceptance level of the idea to live inside a container house is only 45% but the acceptance level of using shipping container as means of storage, office, and business development is highly acceptable by Malaysian citizen.

Thermochemical reactions viz. combustion and pyrolysis are important processes in the conversion of biomass from agricultural wastes into functional materials activated carbon fibre (ACF). Acid treatment during combustion and pyrolysis leaves a major impact which affects quality and properties of the resulting ACF such as pore size control and surface area enlargement. In this study, carbonisation and activation of empty fruit bunch (EFB) fibre into ACF was carried out using acid treatment assisted combustion and pyrolysis followed by CO2 gas flow. The effects of acid treatment on the physicochemical properties and pore characteristics was studied by applying sulphuric acid and switching the sequence of acid treatment before and after combustion and pyrolysis. Intercalation of sulphuric acid and exfoliation reactions on the acid-treated EFB fibre resulted in a higher thermal degradation rate compared to raw EFB fibre without acid treatment. Higher BET surface area and total pore volume were obtained for ACF samples treated with acid. The higher pore volume is due to the intercalated sulphuric compound which facilitated the removal of volatile matter and generated more pores for adsorption. However, severe acid oxidation could also lead to pore blocking with excess oxygen complexes and creation of limited porosity. The results show that properties of the ACF can be affected by the sequence of the acid treatment depending on the thermochemical process applied.

Owing to the growing interest of bioconvection flow of nanomaterials, many investigations on this topic have been performed, especially in this decade. The bioconvection flow of nanofluid includes some novel significance in era of biotechnology and bio-engineering like bio-fuels, microbial enhanced oil recovery, enzymes, pharmaceutical applications, petroleum engineering, etc. The current analysis aims to explore the various thermal properties of Sutterby nanofluid over rotating and stretchable disks with external consequences of variable thermal conductivity, heat absorption/generation consequences, activation energy and thermal radiation. The considered flow problem is changed into dimensionless form with convenient variables. The numerical structure for the obtained non-dimensional equations is numerically accessed with built-in shooting technique. The consequences of various physical parameters are observed for enhancement of velocity, temperature, concentration and motile microorganism. It is noted that both axial and tangential velocity components decrease with Reynolds number and buoyancy ratio parameter. The nanofluid concentration improves with activation energy and concentration Biot number. Moreover, an improved microorganisms profile is noticed with microorganism Biot number and bioconvection Rayleigh number.

Abstract The variation of properties with temperature have many practical applications in the area of chemical engineering and metallurgy, in the process of extrusion, the materials moving between a feed roll and on carrier belt. Here our intention is to explore the consequences of temperature dependent viscosity and variable thermal conductivity on flow of nanoliquid in a rotating system. Fluid between parallel plates is taken. Energy expression incorporates the exponential heat source. This analysis also explores the attributes of modified Arrhenius energy function with chemical reaction. Boundary layer problems have been computed via NDSolve approach. The obtained solutions are sketched for various estimations of embedded variables of interest. Results pointed out that both axial and transverse velocities show decaying behavior for higher rotation parameter. Thermal field boosts up with an enhancement of thermophoretic and space dependent heat source variables. Moreover the rate of mass transport decays through dimensionless activation energy.

Industrial grade ferrotitanium (Fe–Ti) was used for the first time as the raw material to synthesize TiC. Mixtures of Fe–Ti and graphite were milled in a planetary ball mill for varying durations between 10 h and 40 h. The milled mixtures were subsequently heat treated at 1000°C for 15 min. The powder mixtures were characterized by using XRD and SEM-EDAX. In an attempt to purify the TiC, the milled and heat treated powder products were leached with dilute HCl. The XRD patterns of as milled heat treated powders indicated formation of crystalline TiC. SEM images also indicated grain refinement even though agglomeration to some extent was noticed. The mechanochemical route coupled with leaching thus offers a successful way to synthesize TiC from a cheap source that has not been attempted before.

Air conditioning system is a complex system and consumes the most energy in a building. Any fault in the system operation such as cooling tower fan faulty, compressor failure, damper stuck, etc. could lead to energy wastage and reduction in the system’s coefficient of performance (COP). Due to the complexity of the air conditioning system, detecting those faults is hard as it requires exhaustive inspections. This paper consists of two parts; i) to investigate the impact of different faults related to the air conditioning system on COP and ii) to analyse the performances of machine learning algorithms to classify those faults. Three supervised learning classifier models were developed, which were deep learning, support vector machine (SVM) and multi-layer perceptron (MLP). The performances of each classifier were investigated in terms of six different classes of faults. Results showed that different faults give different negative impacts on the COP. Also, the three supervised learning classifier models able to classify all faults for more than 94%, and MLP produced the highest accuracy and precision among all.