5 research outputs found

    Optimizing IC engine efficiency: A comprehensive review on biodiesel, nanofluid, and the role of artificial intelligence and machine learning

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    Transportation and power generation have historically relied upon Internal Combustion Engines (ICEs). However, because of environmental impact and inefficiency, considerable research has been devoted to improving their performance. Alternative fuels are necessary because of environmental concerns and the depletion of non-renewable fuel stocks. Biodiesel has the potential to reduce emissions and improve sustainability when compared to diesel fuel. Several researchers have examined using nanofluids to increase biodiesel performance in internal combustion engines. Due to their thermal and physical properties, nanoparticles in a host fluid improve engine combustion and efficiency. This comprehensive review examines three key areas for improving ICE efficiency: biodiesel as an alternative fuel, application of nanofluids, and artificial intelligence (AI)/machine learning (ML) integration. The integration of AI/ML in nanoparticle-infused biodiesel offers exciting possibilities for optimizing production processes, enhancing fuel properties, and improving engine performance. This article first discusses, the benefits of biodiesel concerning the environment and various difficulties associated with its usage. The review then explores the effects and characteristics of nanofluids in IC engines, aiming to know their impact on engine emissions and performance. After that, this review discusses the utilization of AI/ML techniques in enhancing the biodiesel-nanofluid combustion process. This article sheds light on the ongoing efforts to make ICE technology more environmentally friendly and energy-efficient by examining current research and emerging patterns in these fields. Finally, the review presents the challenges and future perspectives of the field, paving the way for future research and improvement

    Quality and degree of pollution of groundwater, using PIG from a rural part of Telangana State, India

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    Abstract Impacts of geogenic and anthropogenic sources change seriously quality of groundwater. Inferior groundwater quality directly affects the human health, agricultural output and industrial sector. The aim of the present study is to evaluate the groundwater quality for drinking purpose and also to identify the pollutants responsible for variation of chemical quality of groundwater, using pollution index of groundwater (PIG). Groundwater samples collected from a rural part of Telangana State, India, were analyzed for pH, total dissolved solids (TDS), calcium (Ca2+), magnesium (Mg2+), sodium (Na+), potassium (K+), bicarbonate (HCO3− {\text{HCO}}_{3}^{ - } HCO3- ), chloride (Cl− {\text{Cl}}^{ - } Cl- ), sulfate (SO42− {\text{SO}}_{4}^{2 - } SO42- ), nitrate (NO3− {\text{NO}}_{3}^{ - } NO3- ) and fluoride (F− {\text{F}}^{ - } F- ). The groundwater is characterized by Na+ and HCO3− {\text{HCO}}_{3}^{ - } HCO3- ions. The values of TDS, Mg2+, Na+, K+, HCO3− {\text{HCO}}_{3}^{ - } HCO3- , Cl− {\text{Cl}}^{ - } Cl- , SO42− {\text{SO}}_{4}^{2 - } SO42- , NO3− {\text{NO}}_{3}^{ - } NO3- and F− {\text{F}}^{ - } F- are more than their threshold limits prescribed for drinking purpose in a few groundwater samples. The computed values of PIG varied from 0.69 to 1.37, which classify the 80% of the present study area into the insignificant pollution zone (PIG: < 1.0) caused by geogenic origin associated with rock-weathering, mineral dissolution, ion exchange and evaporation processes, and the rest (20%) into the low pollution zone (PIG: 1.0 to 1.5) due to influence of anthropogenic source (waste waters and agricultural activities) on the groundwater system, which are proved by ANOVA test. The diagrams (Ca2+ + Mg2+) versus (HCO3− {\text{HCO}}_{3}^{ - } HCO3-  + SO42− {\text{SO}}_{4}^{2 - } SO42- ), Na+ versus (Ca2+ + Mg2+), Na+ versus Cl− {\text{Cl}}^{ - } Cl- , Ca2+ versus SO42− {\text{SO}}_{4}^{2 - } SO42- and Ca2+ versus Mg2+ support the geogenic origin, whereas the diagram TDS with (NO3− {\text{NO}}_{3}^{ - } NO3-  + Cl− {\text{Cl}}^{ - } Cl- )/HCO3− {\text{HCO}}_{3}^{ - } HCO3- confirms the impact of anthropogenic activities on the aquifer chemistry, which substantially proved the explanation of PIG. The characterization of geochemical evolution of groundwater, using trilinear diagram, also further supports the assessment of PIG in the variation of groundwater quality. From this study, the TDS, Mg2+, Na+, Cl− {\text{Cl}}^{ - } Cl- , SO42− {\text{SO}}_{4}^{2 - } SO42- and NO3− {\text{NO}}_{3}^{ - } NO3- are considered as indicators in assessing the groundwater pollution sources
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