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Production and Characterization of Bio Oil from Bamboo
Igbagara Princewill Woyinbrakemi,
Akpa Jackson Gunorubon,
Adeloye Olalekan Michael
Issue:
Volume 9, Issue 6, November 2021
Pages:
134-140
Received:
20 August 2021
Accepted:
4 October 2021
Published:
10 November 2021
Abstract: The quest for renewable energy sources have been the major concerns worldwide due to depletion of fossil fuel and ozone layer as a result of fossil fuel combustion. Bio oil or fuel production from different natural plants have been researched over the years in different regions of the world. Thus, this research study focused on production and characterization of bio oil from Nigerian bamboo plant (Ogoni bamboo), which involved fresh bamboo preparation and its pyrolysis and characterization. The fresh bamboo plant was used since it’s not edible unlike other studies that applied edible fruits as source of bio diesel production. The prepared fresh bamboo plant was pyrolysed at a temperature range of 300°C to 600°C and the gaseous products condensed to temperature of 25°C. The applied temperature range was used to evaluate the effect of fast, intermediate and slow pyrolysis, while high yield of bio oil was deduced at 450°C. The produced bio oil was characterized by investigating its density, specific gravity, viscosity with gas chromatography and ASTM distillation D86 analysis carried out on the produced bio oil. The pyrolysis result yielded 59.5wt% of bio oil at reactor bed temperature of 450°C, which is heavy in nature, highly viscous with calorific valuer. Thus, bio oil can be produced from Nigeria bamboo plant as an alternate energy source with further product upgrading process required for effective and commercial use of the produced bamboo bio oil.
Abstract: The quest for renewable energy sources have been the major concerns worldwide due to depletion of fossil fuel and ozone layer as a result of fossil fuel combustion. Bio oil or fuel production from different natural plants have been researched over the years in different regions of the world. Thus, this research study focused on production and chara...
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The Application of Temperature-Pressure-Adsorption Equation in the Adsorption Thermodynamic of Coal Seam
Li Dong,
Zhang Xuemei,
Hao Jingyuan,
Ma Qinghua
Issue:
Volume 9, Issue 6, November 2021
Pages:
141-146
Received:
28 October 2021
Accepted:
15 November 2021
Published:
23 November 2021
Abstract: In order to study the adsorption thermodynamics of coal seam, a series of isothermal adsorption experimental data, in 30°C to 100°C temperature range, 0.0MPa to 32.0MPa pressure range, 0.0 cm3/g to 35 cm3/g adsorbed amounts range, of long flame coal, fat coal, lean coal and meager coal are transformed into the isosteric adsorption data through a temperature-Pressure-Adsorption equation. Both the small percentage values of the relative average error and the agreement between the measured points and the TPAE surfaces have proved the TPAE can accurately represent the series of isothermal adsorption experiments. The enthalpy of the gas adsorption process is calculated by the indefinite integral of Clausius-Clapeyron equation. The concept and calculation method of unit isosteric adsorption enthalpy (IAE) is presented. The adsorption process of the coal is an exothermic process because the lnP vs 1/T plot is a straight line with a negative slope. The phenomenon of unit IAE being decreased with the increasing of adsorption amount indicates that the energy in-homogeneity on the coal surface. Since the adsorption process of the coal is an exothermic process, adsorption always occurs first at higher energy and more active positions in order to release more energy and to make the system more stable. The higher rank coal has a larger unit IAE, and there must be a larger adsorption capacity.
Abstract: In order to study the adsorption thermodynamics of coal seam, a series of isothermal adsorption experimental data, in 30°C to 100°C temperature range, 0.0MPa to 32.0MPa pressure range, 0.0 cm3/g to 35 cm3/g adsorbed amounts range, of long flame coal, fat coal, lean coal and meager coal are transformed into the isosteric adsorption data through a te...
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Improving Operational Efficiency Through Alarm Management in Water Treatment Processes Using Artificial Intelligence
Kaushik Ghosh,
Gokula Krishnan Sivaprakasam
Issue:
Volume 9, Issue 6, November 2021
Pages:
147-153
Received:
11 October 2021
Accepted:
10 November 2021
Published:
7 December 2021
Abstract: Water Treatment Plants are controlled by modern industrial process control systems like SCADA or DCS. This facilitates to monitor, control, and troubleshoot water treatment processes and helps in maintaining continuous supply of water with adequate quality. At times and in contrary, these systems hamper process control by generating far too many alarms than needed. Many of the alarms are nuisance in nature and do not indicate any real abnormality. The true alarms which require prompt operator actions to normalize the process are often buried in the pool of nuisance alarms causing significant challenge for operator to take appropriate corrective actions in a timely manner. Many of the past major incidents occurring in the major process industries were attributed to operators’ inability to identify true alarms and take necessary actions. In this paper, we propose an Artificial Intelligence (AI) based pattern mining and advisory system to improve operational efficiency in alarm management. The identified alarm patterns bring out actionable insights in data by (i) identifying nuisance, chattering, redundant alarms, and (ii) Alarm response Pattern. A novel technique for sequential pattern mining in industrial Alarm & Event log data was developed based on State-of-the-art AI based association rule and pattern mining. The efficacy of the proposed method for systematically improving alarm management system in an actual plant environment is currently being studied in a water treatment plant in Singapore.
Abstract: Water Treatment Plants are controlled by modern industrial process control systems like SCADA or DCS. This facilitates to monitor, control, and troubleshoot water treatment processes and helps in maintaining continuous supply of water with adequate quality. At times and in contrary, these systems hamper process control by generating far too many al...
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Modelling COD Removal from Slaughterhouse Wastewater by Electrocoagulation Using Response Surface Methodology
Kouakou Eric Adou,
Bi Gouessé Henri Briton,
Ahissan Donatien Ehouman,
Kopoin Adouby,
Patrick Drogui
Issue:
Volume 9, Issue 6, November 2021
Pages:
154-161
Received:
22 October 2021
Accepted:
30 November 2021
Published:
9 December 2021
Abstract: Modeling is an indispensable tool for a better wastewater treatment strategy. However, the modelling of slaughterhouse wastewater treatment by electrocoagulation can be difficult to achieve because of the various physico-chemical mechanisms involved. It is in this context that the objective of this study was to model and optimize COD removal and electrical energy consumption by response surface methodology (RSM) during the treatment of slaughterhouse wastewater by electrocoagulation (EC). For this purpose, a full factorial design (FD) was first used to observe the effect of experimental parameters (stirring speed, pH, time and current intensity) on COD removal and energy consumption. Then, a central composite design (CCD) was performed to optimize COD removal and electrical energy consumption. The optimum conditions are obtained at the stirring speed of 871 rpm, pH = 6.83; time of 80 min and current intensity of 1.85 A. By applying these optimal conditions for the treatment, reductions of 84 ± 1.08% of COD; 93.86 ± 0.91% of BOD; 97.80 ± 0.86% of turbidity and 99.62 ± 0.12% of PO43- and an energy consumption of 9 KWh.m-3 were obtained. Thus, this study reveals that RSM is an effective tool for the modeling and optimization of electrocoagulation.
Abstract: Modeling is an indispensable tool for a better wastewater treatment strategy. However, the modelling of slaughterhouse wastewater treatment by electrocoagulation can be difficult to achieve because of the various physico-chemical mechanisms involved. It is in this context that the objective of this study was to model and optimize COD removal and el...
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