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.

Experimental investigation on utilization of Sesbania grandiflora residues through thermochemical conversion process for the production of value added chemicals and biofuels.

All the countries in the world are now searching for renewable, environmentally friendly alternative fuels due to the shortage and environmental problems related with the usage of conventional fuels. The cultivation of cereal and noncereal crops through agricultural activities produces waste biomasses, which are being evaluated as renewable and viable fossil fuel substitutes. The thermochemical properties and thermal degradation behavior of Sesbania grandiflora residues were investigated for this work. A fluidized bed reactor was used for fast pyrolysis in order to produce pyrolysis oil, char and gas. Investigations were done to analyze the effect of operating parameters such as temperature (350-550 °C), particle size (0.5-2.0 mm), sweeping gas flow rate (1.5-2.25 m3/h). The maximum of pyrolysis oil (44.7 wt%), was obtained at 425 °C for 1.5 mm particle size at the sweep gas flow rate of 2.0 m3/h. Fourier transform infrared spectroscopy and gas chromatography-mass spectrometry methods were used to examine the composition of the pyrolysis oil. The pyrolysis oil is rich with aliphatic, aromatic, phenolic, and some acidic chemicals. The physical characteristics of pyrolysis oil showed higher heating value of 19.76 MJ/kg. The char and gaseous components were also analyzed to find its suitability as a fuel.

Experimental and numerical analysis of the thermal performance of pebble solar thermal collector.

In this work, pebbles of higher specific heat than the conventional absorber materials like aluminium or copper are proposed as a absorber in the solar flat plate collector. The proposed collector are integrated into the building design and constructed with masonry. Tests were conducted by varying the operating parameters which influence its performance, like the flow rate of the heat-absorbing medium, and the tilt of the collector using both coated and uncoated pebbles. The maximum temperature difference that could be measured for a conventional absorber was approximately 8 °C for a flow rate of 0.6 L/min. While for a coated and uncoated absorber, it was 7 °C and 5.5 °C respectively. This difference decreased with an increase in flow rates from 0.6 L/min to 1.2 L/min. For all the flow rates, it was observed that the average difference in efficiency between the coated and the conventional absorber collector is 5.82 %, while the difference between the coated and uncoated absorber collector is 15.68 %. Thus, it is very much evident that by replacing the conventional absorber with the proposed coated pebble absorber, the overall loss in efficiency is just 5.82 %, but the advantages are enormous. Along with the experimental study, numerical analysis was also carried out with CFD modeling. The numerical results agreed well with experimental results with the least error. Therefore, CFD simulation can be further used to optimize the design of the collector.

A comprehensive analysis of the emerging modern trends in research on photovoltaic systems and desalination in the era of artificial intelligence and machine learning.

Integration of photovoltaic (PV) systems, desalination technologies, and Artificial Intelligence (AI) combined with Machine Learning (ML) has introduced a new era of remarkable research and innovation. This review article thoroughly examines the recent advancements in the field, focusing on the interplay between PV systems and water desalination within the framework of AI and ML applications, along with it analyses current research to identify significant patterns, obstacles, and prospects in this interdisciplinary field. Furthermore, review examines the incorporation of AI and ML methods in improving the performance of PV systems. This includes raising their efficiency, implementing predictive maintenance strategies, and enabling real-time monitoring. It also explores the transformative influence of intelligent algorithms on desalination techniques, specifically addressing concerns pertaining to energy usage, scalability, and environmental sustainability. This article provides a thorough analysis of the current literature, identifying areas where research is lacking and suggesting potential future avenues for investigation. These advancements have resulted in increased efficiency, decreased expenses, and improved sustainability of PV system. By utilizing artificial intelligence technologies, freshwater productivity can increase by 10 % and efficiency. This review offers significant and informative perspectives for researchers, engineers, and policymakers involved in renewable energy and water technology. It sheds light on the latest advancements in photovoltaic systems and desalination, which are facilitated by AI and ML. The review aims to guide towards a more sustainable and technologically advanced future.

Steam explosion as sustainable biomass pretreatment technique for biofuel production: Characteristics and challenges.

The biorefining process of lignocellulosic biomass has recently emerged as one of the most profitable biofuel production options. However, pretreatment is required to improve the recalcitrant lignocellulose's enzymatic conversion efficiency. Among biomass pretreatment methods, the steam explosion is an eco-friendly, inexpensive, and effective approach to pretreating biomass, significantly promoting biofuel production efficiency and yield. This review paper critically presents the steam explosion's reaction mechanism and technological characteristics for lignocellulosic biomass pretreatment. Indeed, the principles of steam explosion technology for lignocellulosic biomass pretreatment were scrutinized. Moreover, the impacts of process factors on pretreatment efficiency and sugar recovery for the following biofuel production were also discussed in detail. Finally, the limitations and prospects of steam explosion pretreatment were mentioned. Generally, steam explosion technology applications could bring great potential in pretreating biomass, although deeper studies are needed to deploy this method on industrial scales.

A critical review on renewable battery thermal management system using heat pipes.

The critical review presented here exclusively covers the studies on battery thermal management systems (BTMSs), which utilize heat pipes of different structural designs and operating parameters as a cooling medium. The review paper is divided into five major parts, and each part addresses the role of heat pipes in BTMS categorically. Experimental studies, numerical analyses, combined experimental and numerical investigations, optimum utilization of a phase-change material (PCM) with a heat pipe (HP), oscillating heat pipe (OHP), and micro heat pipes combined with PCM for Li-ion BTMS using heat pipes are presented. The usage of HP's and PCM can keep the temperature of the battery system in the desirable limit for a longer duration compared to other traditional and passive methods. More emphasis is made on how one can achieve a suitable cooling system design and structure, which may tend to enhance the energy density of the batteries, improve thermal performance at maximum and minimum temperature range. Arrangement of battery cells in a pack or module, type of cooling fluid used, heat pipe configuration, type of PCM used, working fluid in a heat pipe, and surrounding environmental conditions are reviewed. According to the study, the battery's effectiveness is significantly influenced by temperature. The usage of flat HPs and heat sink proves to be the best cooling method for keeping the battery working temperature below 50 °C and reduces the heat sink thermal resistance by 30%. With an intake temperature of 25 °C and a discharge rate of 1 L per minute, an HP that uses water as a coolant is also effective at regulating battery cell temperature and maintaining it below the permissible 55 °C range. Using beeswax as a PCM in HPs reduces the temperature of BTMS by up to 26.62 °C, while the usage of RT44 in HPs reduces the temperature of BTMS by 33.42 °C. The use of fins along with copper spreaders drastically decreases the temperature capability of HPTMS by 11 °C. MHPA shows excellent performance in controlling the battery temperature within 40 °C. The effective thermal management can be done by incorporating heat pipe alone or by coupling with liquid cooling or metal plate. However, extensive and extended research is required to improve thermal management to safely and effectively use the battery for day-to-day applications.

Performance analysis of biofuel-ethanol blends in diesel engine and its validation with computational fluid dynamics.

The engine tests aimed to produce comparable data for fuel consumption, exhaust emissions, and thermal efficiency. The computational fluid dynamics (CFD) program FLUENT was used to simulate the combustion parameters of a direct injection diesel engine. In-cylinder turbulence is controlled using the RNG k-model. The model's conclusions are validated when the projected p-curve is compared to the observed p-curve. The thermal efficiency of the 50E50B blend (50% ethanol, 50% biofuel) is higher than the other blends as well as diesel. Diesel has lower brake thermal efficiency among the other fuel blends used. The 10E90B mix (10% ethanol, 90% biofuel) has a lower brake-specific fuel consumption (BSFC) than other blends but is slightly higher than diesel. The temperature of the exhaust gas rises for all mixtures as the brake power is increased. CO emissions from 50E50B are lower than diesel at low loads but slightly greater at heavy loads. According to the emission graphs, the 50E50B blend produces less HC than diesel. NOx emission rises with increasing load in the exhaust parameter for all mixes. A 50E50B biofuel-ethanol combination achieves the highest brake thermal efficiency, 33.59%. The BSFC for diesel is 0.254 kg/kW-hr at maximum load, while the BSFC for the 10E90B mix is 0.269 kg/kW-hr, higher than diesel. In comparison to diesel, BSFC has increased by 5.90%.

Microalgae bio-oil production by pyrolysis and hydrothermal liquefaction: Mechanism and characteristics.

Microalgae have great potential in producing energy-dense and valuable products via thermochemical processes. Therefore, producing alternative bio-oil to fossil fuel from microalgae has rapidly gained popularity due to its environmentally friendly process and elevated productivity. This current work aims to review comprehensively the microalgae bio-oil production using pyrolysis and hydrothermal liquefaction. In addition, core mechanisms of pyrolysis and hydrothermal liquefaction process for microalgae were scrutinized, showing that the presence of lipids and proteins could contribute to forming a large amount of compounds containing O and N elements in bio-oil. However, applying proper catalysts and advanced technologies for the two aforementioned approaches could improve the quality, heating value, and yield of microalgae bio-oil. In general, microalgae bio-oil produced under optimal conditions could have 46 MJ/kg heating value and 60% yield, indicating that microalgae bio-oil could become a promising alternative fuel for transportation and power generation.

A state of art review on estimation of solar radiation with various models.

Solar radiation is free, and very useful input for most sectors such as heat, health, tourism, agriculture, and energy production, and it plays a critical role in the sustainability of biological, and chemical processes in nature. In this framework, the knowledge of solar radiation data or estimating it as accurately as possible is vital to get the maximum benefit from the sun. From this point of view, many sectors have revised their future investments/plans to enhance their profit margins for sustainable development according to the knowledge/estimation of solar radiation. This case has noteworthy attracted the attention of researchers for the estimation of solar radiation with low errors. Accordingly, it is noticed that various types of models have been continuously developed in the literature. The present review paper has mainly centered on the solar radiation works estimated by the empirical models, time series, artificial intelligence algorithms, and hybrid models. In general, these models have needed the atmospheric, geographic, climatic, and historical solar radiation data of a given region for the estimation of solar radiation. It is seen from the literature review that each model has its advantages and disadvantages in the estimation of solar radiation, and a model that gives the best results for one region may give the worst results for the other region. Furthermore, it is noticed that an input parameter that strongly improves the performance success of the models for a region may worsen the performance success of another region. In this direction, the estimation of solar radiation has been separately detailed in terms of empirical models, time series, artificial intelligence algorithms, and hybrid algorithms. Accordingly, the research gaps, challenges, and future directions for the estimation of solar radiation have been drawn in the present study. In the results, it is well-observed that the hybrid models have exhibited more accurate and reliable results in most studies due to their ability to merge between different models for the benefit of the advantages of each model, but the empirical models have come to the fore in terms of ease of use, and low computational costs.

Hydrothermal carbonization of food waste as sustainable energy conversion path.

Every day, a large amount of food waste (FW) is released into the environment, causing financial loss and unpredictable consequences in the world, highlighting the urgency of finding a suitable approach to treating FW. As moisture content makes up 75% of the FW, hydrothermal carbonization (HTC) is a beneficial process for the treatment of FW since it does not require extensive drying. Moreover, the process is considered favorable for carbon sequestration to mitigate climate change in comparison with other processes because the majority of the carbon in FW is integrated into hydrochar. In this work, the reaction mechanism and factors affecting the HTC of FW are scrutinized. Moreover, the physicochemical properties of products after the HTC of FW are critically presented. In general, HTC of FW is considered a promising approach aiming to attain simultaneously-two core benefits on economy and energy in the sustainable development strategy.

Optimization of Thermal and Structural Design in Lithium-Ion Batteries to Obtain Energy Efficient Battery Thermal Management System (BTMS): A Critical Review.

Covid-19 has given one positive perspective to look at our planet earth in terms of reducing the air and noise pollution thus improving the environmental conditions globally. This positive outcome of pandemic has given the indication that the future of energy belong to green energy and one of the emerging source of green energy is Lithium-ion batteries (LIBs). LIBs are the backbone of the electric vehicles but there are some major issues faced by the them like poor thermal performance, thermal runaway, fire hazards and faster rate of discharge under low and high temperature environment,. Therefore to overcome these problems most of the researchers have come up with new methods of controlling and maintaining the overall thermal performance of the LIBs. The present review paper mainly is focused on optimization of thermal and structural design parameters of the LIBs under different BTMSs. The optimized BTMS generally demonstrated in this paper are maximum temperature of battery cell, battery pack or battery module, temperature uniformity, maximum or average temperature difference, inlet temperature of coolant, flow velocity, and pressure drop. Whereas the major structural design optimization parameters highlighted in this paper are type of flow channel, number of channels, length of channel, diameter of channel, cell to cell spacing, inlet and outlet plenum angle and arrangement of channels. These optimized parameters investigated under different BTMS heads such as air, PCM (phase change material), mini-channel, heat pipe, and water cooling are reported profoundly in this review article. The data are categorized and the results of the recent studies are summarized for each method. Critical review on use of various optimization algorithms (like ant colony, genetic, particle swarm, response surface, NSGA-II, etc.) for design parameter optimization are presented and categorized for different BTMS to boost their objectives. The single objective optimization techniques helps in obtaining the optimal value of important design parameters related to the thermal performance of battery cooling systems. Finally, multi-objective optimization technique is also discussed to get an idea of how to get the trade-off between the various conflicting parameters of interest such as energy, cost, pressure drop, size, arrangement, etc. which is related to minimization and thermal efficiency/performance of the battery system related to maximization. This review will be very helpful for researchers working with an objective of improving the thermal performance and life span of the LIBs.