Physical properties, engine performance, and exhaust emissions of waste fish oil biodiesel/bioethanol/diesel fuel blends.

In the current study, the physicochemical, engine performance, and exhaust emission of different ternary fuel blends containing waste fish oil (WFO) biodiesel, bioethanol, and petro-diesel have been investigated. WFO Biodiesel was prepared from waste fish oil via transesterification method. Different physiochemical properties including the kinematic viscosity, density, flash point, pour point, cloud point, and heat value have been measured for different fuel blends and compared with the neat petro-diesel. The performance and exhaust emission of engine have been also studied using different fuel blends using a single-cylinder diesel engine in full load condition at 1800 rpm. It was found that the engine torque, engine power, and thermal efficiency of the ternary fuel blends was reduced by 2.45%, 9.25%, 2.35% averagely in comparison with the neat petro-diesel, respectively. The average break specific fuel consumption was also increased by 10.44% compared to the neat petro-diesel. The emission of carbon monoxide (CO), carbon dioxide (CO2), unburned hydrocarbons (UHC), and nitrogen oxides (NOx) was also measured. It was also found that the utilization of ternary fuel blends results in a considerable reduction in CO and UHC emission by 50.55% and 43.87% on average compared to the neat petro-diesel, respectively. The emission of NOx was also increased by 28.25% on average compared to the neat petro-diesel. It was also found that the NOx emission can be adjusted by tuning the WFO biodiesel and bioethanol contents of the ternary fuel blends.

Novel environmentally friendly fuel: The effect of adding graphene quantum dot (GQD) nanoparticles with ethanol-biodiesel blends on the performance and emission characteristics of a diesel engine.

Biodiesel fuel has some disadvantages including increase in NOx, poor atomization and incomplete combustion. Additives and catalysts can be used to reduce the negative effects of biodiesel fuel. In addition, the use of metal oxide and metal nanoparticles causes environmental hazards. However, using biodegradable nanoparticles can significantly reduce such concerns. The present study investigated the effect of adding GQD + E to B10 fuel on the emission and performance characteristics of a diesel engine. B10 was blended with GQD (90 ppm) and bioethanol (E2, E4, E6 and E8% vol). Performance and emission characteristics, including power, torque, SFC, CO, CO2, UHC and NOx emissions were measured at the speeds of 1800, 2100 and 2400 rpm and full load mode. According to the results, the addition of GQD + E to B10 improved torque and power and decreased SFC, CO, UHC and NOx. Finally, the B10 + E6 + GQD90 fuel was the best fuel regarding improved engine performance and reduced exhaust emission. The average of changes in power and torque, SFC, CO, UHC and NOx compared to D100 for B10 + E6 + GQD90 were + 15.69%, +15.39%, -17.58%, -30.30%, -38.91% and -1.54%, respectively.

Prediction of power generation and rotor angular speed of a small wind turbine equipped to a controllable duct using artificial neural network and multiple linear regression.

Wind power is one of the most popular sources of renewable energies with an ideal extractable value that is limited to 0.593 known as the Betz-Joukowsky limit. As the generated power of wind machines is proportional to cubic wind speed, therefore it is logical that a small increment in wind speed will result in significant growth in generated power. Shrouding a wind turbine is an ordinary way to exceed the Betz limit, which accelerates the wind flow through the rotor plane. Several layouts of shrouds are developed by researchers. Recently an innovative controllable duct is developed by the authors of this work that can vary the shrouding angle, so its performance is different in each opening angle. As a wind tunnel investigation is heavily time-consuming and has a high cost, therefore just four different opening angles have been assessed. In this work, the performance of the turbine was predicted using multiple linear regression and an artificial neural network in a wide range of duct opening angles. For the turbine power generation and its rotor angular speed in different wind velocities and duct opening angles, regression and an ANN are suggested. The developed neural network model is found to possess better performance than the regression model for both turbine power curve and rotor speed estimation. This work revealed that in higher ranges of wind velocity, the turbine performance intensively will be a function of shrouding angle. This model can be used as a lookup table in controlling the turbines equipped with the proposed mechanism.

Real diesel engine exhaust emission control: indirect non-thermal plasma and comparison to direct plasma for NOX, THC, CO, and CO2.

Recently, diesel engine exhaust emission control by non-thermal plasma (NTP) technology has been shown to be promising. However, carbon and soot deposition on the inner surface of the NTP reactor for direct plasma processing decreased the efficiency of the plasma process throughout the experiments. In the present work, the feasibility of indirect plasma processing was investigated as an innovative and novel method compared to direct plasma processing. Air was directed through an NTP at an applied voltage of VP-P = 7 kV and a flow rate of 1-4 L/min, and then, it was combined with engine exhaust gas at a flow rate of 5 L/min. In this case, the maximum conversion of NOX was 64.9% at 4 L/min. However, for direct plasma processing at 5 L/min, NO conversion was 58%, which proves that the indirect NTP process can decrease NOX concentration effectively. The maximum conversion for unburned hydrocarbon (UHC), carbon monoxide (CO) and carbon dioxide (CO2) was obtained as 2%, 4% and 0.7% at 4, 2 and 3 L/min in indirect plasma processing; While their remove rate for direct plasma processing was 16.3%, -0.5% and 13.2%, respectively.

Decoupling a novel Trichormus variabilis-Synechocystis sp. interaction to boost phycoremediation.

To conserve freshwater resources, domestic and industrial wastewater is recycled. Algal systems have emerged as an efficient, low-cost option for treatment (phycoremediation) of nutrient-rich wastewater and environmental protection. However, industrial wastewater may contain growth inhibitory compounds precluding algal use in phycoremediation. Therefore, extremophyte strains, which thrive in hostile environments, are sought-after. Here, we isolated such an alga - a strain of Synechocystis sp. we found to be capable of switching from commensal exploitation of the nitrogen-fixing Trichormus variabilis, for survival in nitrogen-deficient environments, to free-living growth in nitrate abundance. In nitrogen depletion, the cells are tethered to polysaccharide capsules of T. variabilis using nanotubular structures, presumably for nitrate acquisition. The composite culture failed to establish in industrial/domestic waste effluent. However, gradual exposure to increasing wastewater strength over time untethered Synechocystis cells and killed off T. variabilis. This switched the culture to a stress-acclimated monoculture of Synechocystis sp., which rapidly grew and flourished in wastewater, with ammonium and phosphate removal efficiencies of 99.4% and 97.5%, respectively. Therefore, this strain of Synechocystis sp. shows great promise for use in phycoremediation, with potential to rapidly generate biomass that can find use as a green feedstock for valuable bio-products in industrial applications.

Optimization of Biodiesel Production over Chicken Eggshell-Derived CaO Catalyst in a Continuous Centrifugal Contactor Separator.

Solid calcium oxide (CaO) catalyst was prepared via the calcination of chicken eggshells as an environmentally friendly waste resource and incorporated in a continuous centrifugal contactor separator (CCCS) for intensified biodiesel synthesis. Biodiesel or fatty acid methyl esters (FAME) were produced via the transesterification of sunflower oil (containing 5 wt % tetrahydrofuran as a cosolvent) with methanol under 60 °C and separated from the glycerol and catalyst phases continuously in the CCCS. The influence of reaction parameters on biodiesel production was well modeled by response surface methodology. At an oil flow rate of 9 mL/min, an alcohol to oil molar ratio of 11:1, and a weight hourly space time (defined as the catalyst weight over the oil mass flow rate) of 0.050 h, an optimized FAME yield of 83.2% with a productivity of 638 kgFAME/(m3 reactor·h) was achieved. CaO catalyst was reused without significant activity loss for at least four cycles.

Experimental investigation of bioethanol liquid phase dehydration using natural clinoptilolite.

An experimental study of bioethanol adsorption on natural Iranian clinoptilolite was carried out. Dynamic breakthrough curves were used to investigate the best adsorption conditions in bioethanol liquid phase. A laboratory setup was designed and fabricated for this purpose. In order to find the best operating conditions, the effect of liquid pressure, temperature and flow rate on breakthrough curves and consequently, maximum ethanol uptake by adsorbent were studied. The effects of different variables on final bioethanol concentration were investigated using Response Surface Methodology (RSM). The results showed that by working at optimum condition, feed with 96% (v/v) initial ethanol concentration could be purified up to 99.9% (v/v). In addition, the process was modeled using Box-Behnken model and optimum operational conditions to reach 99.9% for final ethanol concentration were found equal to 10.7 °C, 4.9 bar and 8 mL/min for liquid temperature, pressure and flow rate, respectively. Therefore, the selected natural Iranian clinoptilolite was found to be a promising adsorbent material for bioethanol dehydration process.

Mathematical modelling of thin layer hot air drying of apricot with combined heat and power dryer.

In this study thermal energy of an engine was used to dry apricot. For this purpose, experiments were conducted on thin layer drying apricot with combined heat and power dryer, in a laboratory dryer. The drying experiments were carried out for four levels of engine output power (25 %, 50 %, 75 % and full load), producing temperatures of 50, 60, 70, and 80 ° C in drying chamber respectively. The air velocity in drying chamber was about 0.5 ± 0.05 m/s. Different mathematical models were evaluated to predict the behavior of apricot drying in a combined heat and power dryer. Conventional statistical equations namely modeling efficiency (EF), Root mean square error (RMSE) and chi-square (χ2) were also used to determine the most suitable model. Assessments indicated that the Logarithmic model considering the values of EF = 0.998746, χ 2 = 0.000120 and RMSE = 0.004772, shows the best treatment of drying apricot with combined heat and power dryer among eleven models were used in this study. The average values of effective diffusivity ranged 1.6260 × 10(-9) to 4.3612 × 10(-9) m2/s for drying apricot at air temperatures between 50 and 80 °C and at the air flow rate of 0.5 ± 0.05 m/s; the values of Deff increased with the increase of drying temperature the effective diffusivities in the second falling rate period were about eight times greater than that in the first falling rate period.