13 research outputs found
Assessment of CI Engine Performance and Exhaust Air Quality Outfitted with Real-Time Emulsion Fuel Injection System
The main target of the current research work is effectively eliminating fossil fuel dependency and improving the exhaust air quality of conventional Compression Ignition (CI) engines. This research paper demonstrates for the first time that a nanofluid (water without surfactant) stored in separate tanks can be quantified, collected, and immediately emulsified by a high shear mixer before transfer into the combustion chamber of a diesel engine. The experiment was carried out under different load states (25%, 50%, 75% and 100%) with a constant speed of 1500 rpm. Biofuel was extracted from citronella leaves using an energy-intensive process. The 5% water share was used for preparing the biofuel emulsion and nano-biofuel emulsion. A cobalt chromate nanoadditive was used to make the nanofluid. An experimental investigation was performed with prepared test fuels, namely, ultra-low sulphur diesel (ULSD), 100% Citronella (B100), surfactant-free Diesel emulsion (SDE), surfactant-free bioemulsion (SBE), and Surfactant free nano-bioemulsion (SNBE), in a test engine. The properties of the sample test fuels was ensured according to EN and ASTM standards. The observation performance results show that the SNBE blend exhibited lower BTE (by 0.5%) and higher SFC (by 3.4%) than ULSD at peak load. The emission results show that the SNBE blend exhibited lower HC, CO, NOx, and smoke emissions by 23.86%, 31.81%, 2.94%, and 24.63%, respectively, compared to USD at peak load. The CP and HRR results for SNBE were closer to ULSD fuel. Overall, the novel concept of an RTEFI (Real-time emulsion fuel injection) system was proved to be workable and to maintain its benefits of better fuel economy and greener emissions
Enhancing Performance and Emission Characteristics of Biodiesel-Operated Compression Ignition Engines through Low Heat Rejection Mode and Antioxidant Additives: A Review
Prediction of RCCI combustion fueled with CNG and algal biodiesel to sustain efficient diesel engines using machine learning techniques
This study used microalgae biodiesel as a high-reactive fuel directly injected along with various Compressed Natural Gas (CNG) energy shares (10%, 20%, 30%, and 40%) as low-reactive fuel injected into the intake system. The experiments are performed in a single-cylinder, water-cooled, 1500 rpm, 3.5 kW power Compression Ignition (CI) engine under various loading conditions to examine the effects of CNG energy share on performance and emissions in Reactivity Controlled
Compression Ignition (RCCI) combustion mode. The study found that the 30%CNG share decreased Nitrogen oxides (NOx) and smoke by 25% and 31%, as well as an increase in thermal efficiency of 4.35% in comparison to traditional biodiesel combustion. Finally, two machine learning (ML) models, namely the Gradient Boosting Regressor (GBR) and LASSO (Least Absolute Shrinkage and Selection Operator) Regression, were developed for predicting the dependent variables individually from the independent variables. Both the LASSO and GBR models achieved high accuracy with R2 values of 0.98–0.99 and relatively low Root Mean Square
Error (RMSE) values
Challenges and opportunities of Low Viscous Biofuel- a prospective review
Under the roof of solid industrialization and accelerated
intensification of multiple ranges of mobilization, a huge rise in precious fuel consumption and pollution was observed. Based on the recent hardships of fossil fuels, experts are undoubtedly eager in carrying out their research in renewable environment-friendly fuels. There have been many reviews of works considering the parameters and standards of biodiesel, which is only from various vegetable and seed oils. But very little review work was carried out on only plant-based biofuel. Plant-based fuel has a lower viscosity and higher volatility properties. The target of this review was to make a bridge to overcome these research gaps. This review
extensively studies the biological background, production outcome, properties, and reliability of plant-based biofuel and also deeply investigates the feasibility of usage in a diesel engine. From deep investigation, it was identified that most of the low viscous fuel had higher brake thermal efficiency (BTE) (2% to 4%) and NOx emission (5% to 10%) than high viscous biodiesel. The formation of hydrocarbon (HC), CO, and smoke emission was similar to high viscous biodiesel. Overall, the low viscous fuel effectively improves the engine behaviors
Quantitative Analysis of Solar Photovoltaic Panel Performance with Size-Varied Dust Pollutants Deposition Using Different Machine Learning Approaches
In this paper, the impact of dust deposition on solar photovoltaic (PV) panels was examined, using experimental and machine learning (ML) approaches for different sizes of dust pollutants. The experimental investigation was performed using five different sizes of dust pollutants with a deposition density of 33.48 g/m2 on the panel surface. It has been noted that the zero-resistance current of the PV panel is reduced by up to 49.01% due to the presence of small-size particles and 15.68% for large-size (ranging from 600 µ to 850 µ). In addition, a significant reduction of nearly 40% in sunlight penetration into the PV panel surface was observed due to the deposition of a smaller size of dust pollutants compared to the larger size. Subsequently, different ML regression models, namely support vector machine (SVMR), multiple linear (MLR) and Gaussian (GR), were considered and compared to predict the output power of solar PV panels under the varied size of dust deposition. The outcomes of the ML approach showed that the SVMR algorithms provide optimal performance with MAE, MSE and R2 values of 0.1589, 0.0328 and 0.9919, respectively; while GR had the worst performance. The predicted output power values are in good agreement with the experimental values, showing that the proposed ML approaches are suitable for predicting the output power in any harsh and dusty environment
Optimization of performance and emission characteristics of the CI engine fueled with preheated palm oil in blends with diesel fuel
In this analytical investigation, preheated palm oil was used in the direct injection diesel engine with various optimization methods. The main purpose of the optimization was to get better results than the conventional engine. Raw palm oil was heated using the heat exchange process to reduce the density and viscosity. The relationship between the output process and factors response was evaluated in the design of experiment methods. The Taguchi method is an important method for optimization of the output response performance and emission characteristics of a diesel engine. Two important factors—output and input—were calculated. The input factors considered were preheated palm biodiesel blend, torque, injection pressure, compression ratio, and injection timing. The output factors calculated were smoke opacity, carbon monoxide emission, and brake-specific fuel consumption by using the signal-to-noise (S/N) ratio and analysis of variance. Carbon monoxide was most impacted by torque conditions through injection timing and injecting pressure, and opacity of smoke emission. Among them, injection timing had a higher impact. Different biodiesel blends were prepared: B10 (90% diesel + 10% oil), B20 (80% diesel + 20% oil), B30 (70% diesel + 30% oil) and B40 (60% diesel + 40% oil). Silver nanoparticles (50 ppm) were constantly mixed with the various biodiesel blends. The smoke opacity emission for the biodiesel blend B30 + 50 ppm silver nanoparticle showed the lowest S/N ratio and achieved better optimum results compared with the other blends. The blend B30 + 50 ppm silver nanoparticle showed the lowest S/N ratio value of 9.7 compared with the other blends. The smoke opacity, carbon monoxide emission, and brake-specific fuel consumption of all the response optimal factors were found to be 46.77 ppm, 0.32%, and 0.288 kg/kW·h, respectively
Heat Transfer Studies on Solar Parabolic trough Collector Using Corrugated Tube Receiver with Conical Strip Inserts
The heat transfer characteristics of the working fluid passing through the absorber of a solar parabolic trough collector (SPTC) can be enhanced by the creation of a turbulence effect. Therefore, a novel idea was implemented by introducing a corrugated tube (CT) absorber instead of a plain tube absorber in a solar parabolic trough collector. The heat transfer enhancement was improved further through the use of conical strip inserts inside the corrugated tube absorber of the SPTC. A corrugated tube (CT) receiver with a pitch of 8 mm and corrugation height of 2 mm was used with three different pitches of conical strip inserts (pitch pi = 20 mm, 30 mm and 50 mm) for the analysis of the thermal performance of the SPTC. Initially, experiments were conducted in a plain tube and corrugated tube receiver at different mass flow rates. The convective heat transfer rate was increased for all the configurations of the conical strip inserts. The SPTC performance was good for the combination of the corrugated tube (pc = 8 mm and hc = 2 mm) and the conical strip insert I3 (pi= 20 mm). The experimental results showed that the maximum achieved Nu value, friction factor, instantaneous efficiency and thermal efficiency of the CT-I3 were 177%, 38%, 26.92% and 9% compared to the plain tube under the same working conditions
Metal-Free and Regioselective Synthesis of Substituted and Fused Chromenopyrrole Scaffolds via the Divergent Reactivity of Azido Ketones in Water
Compatibility Effects of Waste Cooking Oil Biodiesel Blend on Fuel System Elastomers in Compression Ignition Engines
Performance and Emission Analysis of Biodiesel Blends in a Low Heat Rejection Engine with an Antioxidant Additive: An Experimental Study
The rapid depletion of crude oil and environmental degradation necessitates the search for alternative fuel sources for internal combustion engines. Biodiesel is a promising alternative fuel for compression ignition (CI) engines due to its heat content and combustion properties. Biodiesel blends are used in various vehicles and equipment, such as cars, trucks, buses, off-road vehicles, and oil furnaces. Biodiesel can reduce emissions from CI engines by up to 75% and improve engine durability due to its high lubricity. However, biodiesel has some drawbacks, including reduced performance and increased nitrogen oxide
emissions. Therefore, this study aims to investigate using environmentally available biodiesel in a low-heat rejection engine and an antioxidant additive to enhance performance and reduce nitrogen oxide emissions. India currently
has several biodiesel sources, including mango seed oil, mahua oil, and Pongamia oil, which can be effectively utilized in CI engines by adding L-ascorbic acid. The experimental work involves a single-cylinder 4-stroke water-cooled direct injection CI engine with a power output of 5.2 kW. The
engine’s cylinder head, piston head, and valves are coated with lanthanum oxide using the plasma spray coating technique, with a thickness of 0.5 mm. The coated and uncoated engines are tested with different proportions of mahua oil, mango seed oil, and Pongamia oil. The results show that the engine’s performance is significantly improved compared to the baseline engine at all loads. Additionally, these biodiesels exhibit a notable reduction in nitrogen oxide emissions when combined with L-ascorbic acid