Optimization of wear behavior of heat-treated Ti-6Al-7Nb biomedical alloy by response surface methodology.

Titanium-based metals are used most often in biomedical implant studies because they have good qualities like being biocompatible, not being poisonous, Osseo-integration, high specific properties, wear resistance, etc. The main goal of this work is to improve the wear resistance of Ti-6Al-7Nb biomedical metal by using a mix of Taguchi, ANOVA, and Grey Relational Analysis. The effect of changeable control process factors like applied load, spinning speed, and time on wear reaction measures like wear rate (WR), coefficient of friction (COF), and frictional force. The optimal combinations of wear rate, COF, and frictional force minimise wear characteristics. The L9 Taguchi orthogonal array was used to plan the experiments, which were done on a pin-on-disc set-up according to ASTM G99. To find the best set of control factors, Taguchi, ANOVA, and Grey relationship analysis were used. The results show that a load of 30 N, a speed of 700 rpm, and a time of 10 min are the best control settings.

Experimental study of diesel engine performance and emissions from microalgae fuel blends with SiO2 nanoadditives: RSM and Taguchi optimization.

In this investigation, the effects of blending microalgae biodiesel with silicon dioxide (SiO2) nanoparticles in a diesel engine are evaluated. For the study, test fuels (diesel, B20, B20n25, B20n50, B20n75, and B20n100) were prepared by blending pure diesel with microalgae biodiesel with the addition of SiO2 nanoparticles having particle sizes ranging from 25 to 100 ppm. A liquid-cooled, two-cylinder, four-stroke, compression ignition engine having a load range between 2 and 12 kW, fuel injection timing of 23° bTDC, and 16.5:1 compression ratio was chosen for this study. The results demonstrated that the test fuels enhanced the engine performance and declined emissions. Performance parameters such as brake thermal efficiency (BTE) and brake-specific fuel consumption (BSFC) were all improved by 1.6-4.8% and 8.55-15.33%, respectively, by the biodiesel containing SiO2 nanoparticles. At full engine load, emissions such as carbon dioxide (CO2), smoke opacity (BSN), and NOx declined by 1.8-9%, 6.2-21.4%, and 19-34% respectively. The study backs the use of SiO2 nanoadditives for better performance and lower emissions in diesel engines. Test results were analyzed by Taguchi and RSM method to find optimized conditions.

Predict the characteristics of the DI engine with various injection timings by Glycine max oil biofuel using artificial neural networks.

Glycine max oil biofuel (GMOB) is a product of the transesterification of soybean oil. It contains a substantial amount of thermal energy. In this study, the result of varying fuel injection timings on the performance, ignition, and exhaust parameters of a research engine with single-cylinder, four-stroke with direct injection (DI) diesel was experimentally investigated and optimised using artificial neural networks (ANN). The results demonstrated that a 20% fuel blend with 24.5° before top dead centre (b TDC) decreased brake thermal efficiency (BTE), NOx emissions, and exhaust cylinder temperature but improved fuel consumption, carbon dioxide emissions (CDE), and smoke emissions. With 26.5° b TDC, the BTE was found to be approximately 5.0% higher while the fuel consumption was approximately 2.0% lower than with the original injection timing of 24.5° b TDC. At 26.5° b TDC, the NOx emission was approximately 8.6% higher, and the smoke emission was approximately 4.07% lower than at the original injection timing (24.5° b TDC).

Production and testing of mahua oil-based biodiesel synthesized through heterogeneous catalyst using experimental and numerical method.

A two-step treatment  of mahua oil was conducted to synthesize mahua biodiesel using heterogeneous biomass-based catalyst derived from mahua shell. Mahua oil having higher free fatty acid (FFA) content (about 19%) was esterified to reduce the FFA content up to 1%. The esterification process was carried out using 200 mL mahua oil, 5:1 molar ratio (methanol:oil), and 2.25 weight% of H2SO4 at a temperature of 60 °C for 3 h. Post esterification, a set of 16 experiments were created using a Box-Behnken design (BBD)-based response surface methodology (RSM) approach to conduct the transesterification of the esterified oil. Molar ratio, catalyst loading, reaction temperature, and reaction time were the four input variables chosen for the design of experiments. The optimized conditions for maximum biodiesel yield (87.7%) were found to be 14.88 molar ratio, 3.578% catalyst loading, 69.7 °C reaction temperature, and 81.9 min reaction time. The Diesel RK engine simulation tool which was experimentally validated for baseline diesel fuel was used for numerical simulation of mahua biodiesel. The performance, combustion, and emission behavior of mahua biodiesel analyzed using numerical simulation presented the sustainability of mahua biodiesel as an alternate fuel.

Enhancing diesel engine performance and emission reduction through hydrogen enrichment in algal biodiesel blends.

The introduction of hydrogen into the engine could enhance its combustion efficiency and emission characteristics. The current study examines the attributes of compression ignition (CI) engines by introducing hydrogen into a biodiesel blend derived from algae. The improved thermal properties of hydrogen, when combined with algae biodiesel, significantly affect the performance, combustion, and emissions of dual-fuel engines. A study was conducted to evaluate the impact of hydrogen enrichment levels of 5%, 10%, 15%, and 20% of the nozzle volume on a biodiesel blend fuel. In comparison to diesel, algal biodiesel reduces emissions of unburned hydrocarbons (HC), carbon monoxide (CO), and oxygen (O2) by 5.19%, 3.61%, and 2.83%, respectively, while increasing nitrogen oxide (NO) emissions by 4.73%. In contrast to biodiesel, diesel demonstrated superior brake thermal efficiency (BTE) and lower specific energy consumption (SEC). Injecting hydrogen into A20 blend fuel at volumes of 5%, 10%, 15%, and 20% results in a respective increase in brake thermal efficiency of 2.65%, 2.97%, 3.50%, and 4.15%. The addition of hydrogen gas to biodiesel blends further enhances their combustion qualities, leading to elevated peak cylinder pressure, temperature, and heat release rate. The results indicate that A20H5, A20H10, A20H15, and A20H20 fuel reduced CO emissions by 3.75%, 8.75%, 12.5%, and 16.25%, respectively, compared to the A20 blend. In the same vein, HC emissions decreased by 5.76%, 10.29%, 15.52%, and 18.98%, respectively, as compared to A20 fuel. However, NO emissions rose by 5.36%, 10.20%, 15.28%, and 23.23%, respectively, for A20H5, A20H10, A20H15, and A20H20 test fuels. Ultimately, the utilization of algal biodiesel and hydrogen enrichment in diesel engines was proven to substantially reduce pollutants while increasing efficiency. This study contributes valuable insights into the intersection of renewable fuels, hydrogen enrichment, and engine technology, with the potential to drive significant advancements in sustainable transportation and environmental conservation.

Optimizing soybean biofuel blends for sustainable urban medium-duty commercial vehicles in India: an AI-driven approach.

This article presents the outcomes of a research study focused on optimizing the performance of soybean biofuel blends derived from soybean seeds specifically for urban medium-duty commercial vehicles. The study took into consideration elements such as production capacity, economics and assumed engine characteristics. For the purpose of predicting performance, combustion and emission characteristics, an artificial intelligence approach that has been trained using experimental data is used. At full load, the brake thermal efficiency (BTE) dropped as engine speed increased for biofuel and diesel fuel mixes, but brake-specific fuel consumption (BSFC) increased. The BSFC increased by 11.9% when diesel compared to using biofuel with diesel blends. The mixes cut both maximum cylinder pressure and NO x emissions. The biofuel-diesel fuel proved more successful, with maximum reduction of 9.8% and 22.2 at rpm, respectively. The biofuel and diesel blend significantly improved carbon dioxide ( CO 2 ) and smoke emissions. The biofuel blends offer significant advantages by decreeing exhaust pollutants and enhancing engine performance.

Exergy-energy, sustainability, and emissions assessment of Guizotia abyssinica (L.) fuel blends with metallic nano additives.

This study extensively examined the impact of aluminium oxide (Al2O3) and titanium dioxide (TiO2) nanoparticles addition in the biodiesel fuel derived from Guizotia abyssinica (L.) oil. The assessment of fuel blends, which were created by combining nanoparticles and biodiesel was conducted using energy, exergy, and sustainability indices. The highest recorded power output of 2.81 kW was observed for the GAB20A engine operating at 1800 rpm. The experimental results revealed that the GAB20A exhibited the lowest fuel consumption, with a recorded value of 203 g/kWh, when operated at 1600 rpm among all the tested blend fuels. The blend GAB20A exhibited the highest level of energy efficiency at 1600 rpm of 29.5%, as determined by the study. Simultaneously, it was observed that GAB20 exhibited the lowest energy efficiency at 1200 rpm among all the blend fuels at 25%. The emission levels of nitrogen oxides (NOx) and carbon monoxide (CO) were observed to be quite low, although a little rise in carbon dioxide (CO2) was detected. For validation of results the artificial neural network (ANN) was used and an average of 1.703% difference in energy efficiency, 2.246% decrease in exergy efficiency, and 1.416% difference in sustainability index was found.

Optimization of performance characteristics in diesel engine utilizing Chlorella vulgaris fuel-a green approach towards sustainable development.

Sustainable renewable energy fuel is used to reduce fossil fuel consumption and mitigate global warming pollution. The effect of diesel and biodiesel blends on engine combustion, performance, and emissions were studied at various engine loads, compression ratios, and engine speed. Chlorella vulgaris biodiesel is derived through a transesterification process and diesel and biodiesel blends are prepared at 20% incremental volume up to CVB100. The performance such as brake thermal efficiency reduced by 1.49%, specific fuel consumption increased by 2.78%, and exhaust gas temperature increased by 0.43% for CVB20 as compared to diesel. Similarly, emissions were reduced such as smoke, particulate matters. CVB20 shows close performance and lower emission than diesel at a 15.5 compression ratio and 1500 rpm engine speed. The increasing compression ratio has a positive impact on engine performance and emission except for NOx. Similarly, increasing engine speed has a positive impact on engine performance and emission except for exhaust gas temperature. The performance of a diesel engine fueled with a blend of diesel and Chlorella vulgaris biodiesel is optimized by varying compression ratio, engine speed, load, and blend. It was found that at 8 compression ratio, 1835 rpm speed, 88% engine load, and 20% biodiesel blend the maximum BTE obtained 34% while minimum SFC 0.158 kg/kWh is obtained employing research surface methodology tool.

Effects of different biofuels and their mixtures with diesel fuel on diesel engine performance and exhausts.

In this study, a compression ignition engine that ran on recycled used cooking oil (RUCO), Jatropha curcas (JC), Pongamia Pinnata (PP), and petroleum diesel fuel (PDF) was investigated for its energy, performance, and exhaust emissions. The 20 % by volume RUCO, JC, and PP biofuel mix with PDF is taken. According to the American Society for Testing and Material (ASTM) standard, the blend qualities are evaluated. Viscosity, density, flash point, and heating value have all been tested for the 20 % blend. The outcome indicated that for a 20 % mix, the viscosity, density and flash point were all greater than in the PDF but heat value lower. Because studies have demonstrated that diesel engines can operate on 20 % replacement without any modifications, this study focused on 20 % blend. The engine was tested with loads (Ls) ranging from 0 % to 100 % of its entire capacity while the compression ratios (CRs) was varied. The experimental result demonstrated that the thermal efficiency, as measured by the PDF, was much greater than that of the DRUCO20, DJC20, and DPP20 blends. After the addition of RUCO, JC, and PP to PDF, the temperature of the exhaust gases reduced, and the engine used more gasoline as a result. It was discovered that an engine emissions of hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx) were lower than those of PDF. Even though it produced a greater amount of carbon dioxide (CO2) emissions, the DRUCO20 was superior to both the DCJ20 and the DPP20.

Experimental and empirical investigation of a CI engine fuelled with blends of diesel and roselle biodiesel.

The continuous rise in demand, combined with the depletion of the world's fossil fuel reserves, has forced the search for alternative fuels. The biodiesel produced from Roselle is one such indigenous biodiesel with tremendous promise, and its technical ability to operate with compression ignition engines is studied in this work. To characterize the fuel blends, researchers used experimental and empirical approaches while operating at engine loads of 25, 50, 75, and 100%, and with fuel injection timings of 19°, 21°, 23°, 25°, and 27° before top dead center. Results indicate that for 20% blend with the change of injection timing from 19° bTDC to 27° bTDC at full load, brake specific fuel consumption and exhaust gas temperature was increased by 15.84% and 4.60% respectively, while brake thermal efficiency decreases by 4.4%. Also, an 18.89% reduction in smoke, 5.26% increase in CO2, and 12.94% increase in NOx were observed. In addition, an empirical model for full range characterization was created. With an r-squared value of 0.9980 ± 0.0011, the artificial neural network model constructed to characterize all 10 variables was able to predict satisfactorily. Furthermore, substantial correlation among specific variables suggested that empirically reduced models were realistic.

Algae as green energy reserve: Technological outlook on biofuel production.

Depletion of fossil fuel sources and their emissions have triggered a vigorous research in finding alternative and renewable energy sources. In this regard, algae are being exploited as a third generation feedstock for the production of biofuels such as bioethanol, biodiesel, biogas, and biohydrogen. However, algal based biofuel does not reach successful peak due to the higher cost issues in cultivation, harvesting and extraction steps. Therefore, this review presents an extensive detail of deriving biofuels from algal biomass starting from various algae cultivation systems like raceway pond and photobioreactors and its bottlenecks. Evolution of biofuel feedstocks from edible oils to algae have been addressed in the initial section of the manuscript to provide insights on the different generation of biofuel. Different configuration of photobioreactor systems used to reduce contamination risk and improve biomass productivity were extensively discussed. Photobioreactor performance greatly relies on the conditions under which it is operated. Hence, the importance of such conditions alike temperature, light intensity, inoculum size, CO2, nutrient concentration, and mixing in bioreactor performance have been described. As the lipid is the main component in biodiesel production, several pretreatment methods such as physical, chemical and biological for disrupting cell membrane to extract lipid were comprehensively reviewed and presented. This review article had put forth the recent advancement in the pretreatment methods like hydrothermal processing of algal biomasses using acid or alkali. Eventually, challenges and future dimensions in algal cultivation and pretreatment process were discussed in detail for making an economically viable algal biofuel.

Study of Particle Dispersion on One Bed Hospital using Computational Fluid Dynamics.

Increasing concerns about the spread of airborne disease in hospital such as severe acute respiratory syndrome (SARS), chickenpox, measles, tuberculosis and novel swine-origin influenza A (H1N1) have attracted public attention. A present study was carried out to look for the source of contamination (patient itself) and examine the route of contaminant transfer in the hospital. This article provides recommendation for future work to improve the yield and save the energy consumption simultaneously. The risk of airborne infection can be minimized in hospital wards by using a high air change rate. The Local mean age of air will decrease with an increasing flow rate because the source must be considered to be constant. The location of the outlet openings plays an important role for the transfer of the contaminant particle in the hospital.