The present investigation uses a blend of Nigella sativa biodiesel, diesel, n-butanol, and graphene oxide nanoparticles to enhance the performance, combustion and symmetric characteristics and to reduce the emissions from the diesel engine of a modified common rail direct injection (CRDI). A symmetric toroidal-type combustion chamber and a six-hole solenoid fuel injector were used in the current investigation. The research aimed to study the effect of two fuel additives, n-butanol and synthesized asymmetric graphene oxide nanoparticles, in improving the fuel properties of Nigella sativa biodiesel (NSME25). The concentration of n-butanol (10%) was kept constant, and asymmetric graphene oxide nano-additive and sodium dodecyl benzene sulphonate (SDBS) surfactant were added to n-butanol and NSME25 in the form of nanofluid in varying proportions. The nanofluids were prepared using a probe sonication process to prevent nanoparticles from agglomerating in the base fluid. The process was repeated for biodiesel, n-butanol and nanofluid, and four different stable and symmetric nanofuel mixtures were prepared by varying the graphene oxide (30, 60, 90 and 120 ppm). The nanofuel blend NSME25B10GO90 displayed an enhancement in the brake thermal efficiency (BTE) and a reduction in brake-specific fuel consumption (BSFC) at maximum load due to high catalytic activity and the enhanced microexplosion phenomenon developed by graphene oxide nanoparticles. The heat release rate (HRR), in-cylinder temperature increased, while exhaust gas temperature (EGT) decreased. Smoke, hydrocarbon (HC), carbon monoxide (CO2) and carbon monoxide (CO) emissions also fell, in a trade-off with marginally increased NOx, for all nanofuel blends, compared with Nigella sativa biodiesel. The results obtained indicates that 90 ppm of graphene oxide nanoparticles and 10% n-butanol in Nigella sativa biodiesel are comparable with diesel fuel.

https://www.mdpi.com/2073-8994/12/6/961/pdf

Effect of nano-graphene oxide and n-butanol fuel additives blended with diesel-Nigella sativa biodiesel fuel emulsion on diesel engine characteristics

Combined effect of oxygenated additives, injection timing and EGR on combustion, performance and emission characteristics of a CRDi diesel engine powered by sapota biodiesel/diesel blends

Performance, emission and combustion characteristics of unmodified diesel engine with titanium dioxide (TiO2) nano particle along with water-in-diesel emulsion fuel

Simultaneous reduction of NOx and smoke emissions with low viscous biofuel in low heat rejection engine using selective catalytic reduction technique

This study is focused on artificial neural network (ANN) modelling of non-modified diesel engine keyed up by the combination of two low viscous biofuels to forecast the parameters of emission and performance. The diesel engine is energised with five different test fuels of the combination of citronella and Cymbopogon flexuous biofuel (C50CF50) with diesel at precise blends of B20, B30, B40, B50 and B100 in which these numbers represent the contents of combination of biofuel and the investigation is carried out from zero to full load condition. The experimental result was found that the B20 blend had improved BTE at all load states compared with the remaining biofuel blends. At 100% load state, BTE (31.5%) and fuel consumption (13.01 g/kW-h) for the B20 blend was closer to diesel. However, the B50 blend had minimal HC (0.04 to 0.157 g/kW-h), CO (0.89 to 2.025 g/kW-h) and smoke (7.8 to 60.09%) emission than other test fuels at low and high load states. The CO2 emission was the penalty for complete combustion. The NOx emission was higher for all the biodiesel blends than diesel by 6.12%, 8%, 11.53%, 14.81% and 3.15% for B20, B30, B40, B50 and B100 respectively at 100% load condition. The reference parameters are identified as blend concentration percentage and brake power values. The trained ANN models exhibit a magnificent value of 97% coefficient of determination and the high R values ranging between 0.9076 and 0.9965 and the low MAPE values ranging between 0.98 and 4.26%. The analytical results also provide supportive evidence for the B20 blend which in turn concludes B20 as an effective alternative fuel for diesel.

Forcasting of an ANN model for predicting behaviour of diesel engine energised by a combination of two low viscous biofuels

A novel study on the effect lemon peel oil as a fuel in CRDI engine at various injection strategies

A comparative assessment on Common Rail Direct Injection (CRDI) engine characteristics using low viscous biofuel blends

Traditional monitoring systems in coal mines are difficult to install, hazardous, and difficult to power. Because of the complexity of the mining environment and the wide range of operations performed in coal mines, it is vital to monitor and maintain the parameters in the background t increase the efficiency and safety of mineworkers. As a result, traditional monitoring methods cannot be relied on to ensure coal workers’ safety. This research represents a ZigBee-based wireless monitoring system using a smart helmet. The presented wireless monitoring system is capable of detecting and transmitting critical parameters in coal mines such as methane gas, high temperature, humidity, and fire. In an emergency, this monitoring system transmits distress signals. A buzzer will sound if emergency conditions are detected, and the monitored variables will be displayed on the user interface machine. Moreover, the Parameters are wirelessly transmitted to the control room, allowing people to determine the safety situation of the mine. This model is easily reprogrammable. Experiments have demonstrated the system’s reliability and stability.

/pdf/coal-mine-safety-monitoring-and-alerting-system-with-smart-22u684tc.pdf

Coal Mine Safety Monitoring and Alerting System with Smart Helmet

Performance of Composite Plate Shear Walls/Concrete Filled (C-PSW/CF) Under Fire Loading: A Numerical Investigation

Every Renewable based energy source requires an additional buffer unit to deliver power to either a standalone system or a grid system. Most of the time unit buffer either provides constant voltage DC-power or AC-power. Higher efficiency in the conversion process can only be achieved if ongoing losses of the buffer system are low. Square sine control approach for Higher-Order Series-Parallel resonant DC-DC Converter is presented in the paper which provides excellent results in both highly and lightly loaded conditions. This control also provides stable bandwidth for input voltage source acceptance which is mostly to be considered as a PV-based source. The strategy also enhances the reliability of the converter by providing a stable and most delightful way of soft switching triggering so as to maintain the output voltage by un-affecting the switching cycle of the Solid-State Semi-conducting Device (SSSD). Selection for the components used in converter design was also studied with a susceptive case study. Further to this control for the entire converter unit is maintained to single variable control so as to reduce the complexity of the system and enhance efficiency. The simulated results of the programmable single variable square sine-wave control is presented for the higher-order resonant converter operating under variable input condition.

Shivam Sharma

Papers

A novel study on the effect lemon peel oil as a fuel in CRDI engine at various injection strategies

A comparative assessment on Common Rail Direct Injection (CRDI) engine characteristics using low viscous biofuel blends

Coal Mine Safety Monitoring and Alerting System with Smart Helmet

Performance of Composite Plate Shear Walls/Concrete Filled (C-PSW/CF) Under Fire Loading: A Numerical Investigation

Designing of Higher-Order Series-Parallel resonant converter with improved ZVS under variable source condition for constant DC-bus System