B5 Fuels Research Articles

Evaluation of performance and emission characteristics of a CI engine using functional multi-walled carbon nanotubes (MWCNTs-COOH) additives in biodiesel-diesel blends

The present study investigated the effect of adding functional multi-walled carbon nanotubes (MWCNTs-COOH) to diesel-biodiesel fuel on the engine performance and emission characteristics of a diesel engine. The MWCNTs-COOH nanoparticles were mixed with B5 biodiesel blend. The MWCNTs-COOH nanoparticles, at concentrations of 30, 60, and 90 ppm, were dispersed into B5 by ultra-sonication. Engine testing was performed at various speeds of 1800, 2100 and 2400 rpm and full load. Performance and emission characteristics, including power, torque, specific fuel consumption (SFC), CO, CO2, unburned-hydrocarbon (UHC), and NOx emissions, were investigated. The results showed that adding MWCNTs-COOH to B5 increased power by 13.01% and 16.57% compared to D100 and B5. The average torque also increased by 17.61% and 18.03% compared to the D100 and B5, respectively. SFC decreased by 9.48% and 10.21%, respectively, compared to D100 and B5 fuels. Despite MWCNTs-COOH in the fuel, CO emissions decreased by an average of 10.26% and 7.26% compared to the D100 and B5, respectively. Also, UHC emissions decreased by 16.33% and 10.64% compared to the D100 and B5 fuels, respectively.

Detection and classification of diesel-biodiesel blends by LDA, QDA and SVM approaches using an electronic nose

This study addressed the detection and classification of biodiesel from different sources using electronic nose through application of statistical training-based methods and mathematical optimization techniques. Biodiesel fuels obtained from canola oil with methanol (MK), corn oil with methanol (MZ), canola oil with ethanol (EK) and corn oil with ethanol (EZ) as well as a combined fuel (EK&MZ) were mixed with different volume percentages (2, 5, 10, 20, 80 and 100) of the petroleum diesel. Data collection was performed by application of an electronic nose equipped with 8 metal oxide semiconductor (MOS) sensors. Data analysis was conducted using different methods including linear and quadratic discriminant analysis (LDA and DDA) as well as the support vector machine (SVM). Based on the results, SVM, QDA and LDA had classification precisions of 94.8%, 94.1% and 87.1%, respectively. Moreover, the discrimination and classification precision of SVM was higher (about 95.4%) for the two groups of pure and impure fuels (various mixtures of diesel and biodiesel). For QDA and LDA methods, this precision value was 84.4% and 75.5%, respectively. Classification of B5 fuels was better in all the methods when compared with B2 and B20 fuels. Detection and classification precision of B5 biodiesels was 100%, 97.6% and 96.1% for LDA, QDA and SVM methods, respectively. Application of the overall desirability function showed that QDA method had better performance when compared to LDA and SVM as it had higher discrimination and classification ability. The performance parameters of this model were 0.941, 0.941, 0.975 and 0.850 for mean precision, sensitivity, specificity and final desirability, respectively.

EFFECT OF METALLOID COMPOUND AND BIO-SOLUTION ADDITIVES ON BIODIESEL ENGINE PERFORMANCE AND EXHAUST EMISSIONS

The purpose of this study is to perform comparative analysis of the effect of the different fuel addit ives as polymer based-bio-solution, natural organic based-b io-solution and nano-titanium metalloid (TiO 2) compound on the performance parameters and exhuast emissions of a pickup Diesel engine, operating on commercial Diesel fuel (D) and B5 palm biodiesel (95% D+5% palm oil). The basic properties of the fuel blended wi th TiO 2 metalloid compound and bio-solution based additives were measured according to ASTM standard. Engine performance of a pickup diesel engine was investigated by testing on a chassis dynamometer with the simulation of road load condition. It was found tha t TiO 2 based-additive is more effective for improving engine power than pure Diesel and B5 fuels by 7.78% and 1.36%, respectively. Meanwhile, with using TiO 2 additive, the maximum engine torque on average increased by 1.01% and 1.53% in the wide range between 1,700 and 3,000 rpm as compared with Diesel and B5 fuels, respectively. The TiO 2 and natural organic additives is significantly effective on Diesel fuel for reduc ing brake specific fuel consumption reached by 13.2 2% and 10.01%, respectively as compared with pure Diesel. Moreover, the exhuast emissions (NO x, CO and CO 2) decreased from the engine using the TiO 2 additive in Diesel fuel and natural organic additi ve in Diesel fuel.

Analyzing the Changes in Dynamic Viscosities of Hazelnut Oil and Hazelnut Oil Methyl Ester with Respect to Temperature

In this study, dynamic viscosities of fuels of raw hazelnut oil and raw hazelnut oil methyl ester are measured in the interval of 0–100°C with 10°C intervals using a Brookfield Engineering Co., USA DV-II+ Pro rotary viscosity-meter. The experiments are conducted under 20°C ambient temperature. Viscosity measurements are performed at 50 rpm constant speed by using a RVII spindle. Data are recorded in 5 sec intervals using Brookfield Engineering Co., Wingather software. Dynamic viscosities of fuels of raw hazelnut and raw hazelnut methyl ester have obtained a decrease by increasing temperature and diesel concentration. Using the dynamic viscosities of raw hazelnut oil methyl ester and diesel fuel, dynamic viscosities of B50, B20, and B5 fuels with respect to temperature are estimated by using Arrhenius mixture equation. In addition to this, using a modified Andrade equation, regression analyses are conducted in MATLAB® software and R2, absolute error, and error percentages are determined in the interval of 0–100°C with 10°C intervals.