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Öğe Comparative analysis to reduce greenhouse gas (GHG) emission in CI engine fuelled with sweet almond oil using ammonia/after treatment system(Elsevier, 2024) Sonthalia, Ankit; Varuvel, Edwin Geo; Subramanian, Thiyagarajan; Josephin, Femilda J. S.; Alahmadi, Tahani Awad; Pugazhendhi, ArivalagaThe present study analyses the various techniques to reduce CO 2 emission, a major contributor to GHG emissions. Diesel was replaced with prunus amygdalus dulcis (sweet almond oil) -fuelled single -cylinder compression ignition (CI) engine. Due to the high viscosity of sweet almond oil, a transesterification procedure was used to convert it to biodiesel. In this experiment, the diesel fuel was entirely substituted with biodiesel (B100) in order to evaluate the emissions, combustion characteristics, and performance of the CI engine operating at a consistent 1500 revolutions per minute under varying loads. In comparison to diesel, tailpipe CO 2 emissions were greater when biodiesel was utilized due to its higher carbon content in the molecular structure. However, plantations absorbs CO 2 emissions from atmosphere causing 'net negative CO 2 emission '. No carbon fuel ammonia was introduced into the intake air using sweet almond oil biodiesel as the base fuel in order to reduce exhaust CO 2 emissions. Under various load conditions, ammonia was introduced at varying flow rates ranging from 10 to 30 LPM. It is observed that increase in ammonia flow rate led to reduction in CO 2 emission. CO 2 emission was reduced from 11.2 % for biodiesel to 6.9 % with 30 LPM ammonia. An after -treatment system was designed with calcite/ activated carbon and retrofitted in exhaust pipe and tested with B100 as fuel. The results indicate that calcite reduces CO 2 more effectively than CO 2 capture systems based on activated carbon. CO 2 emission with calcite is 9.6 % and with activated carbon it is 10.2 % at maximum load condition. The utilization of a calcite -based CO 2 capture system in conjunction with biofuel is believed to effectively mitigate the adverse effects of global warming by generating a net negative CO 2 effect and reducing engine out emissions. Based on the experimental results, compared to after treatment system, ammonia addition with biodiesel is more effective in reducing CO 2 emission without much affecting the other parameters.Öğe Influence of hydrogen-assisted combustion in compression ignition engines fueled with fuel blends of pine oil and waste cooking oil biodiesel using toroidal combustion chamber(Pergamon-elsevier science LTD, 2024) Thiagarajan, S.; Damodaran, Ajith; Seetharaman, Sathyanarayanan; Varuvel, Edwin GeoIn this research study, fuel blends of pine oil and waste cooking oil biodiesel (P/WCO) were examined for combustion analysis, engine performance, and emission characteristics tests. Improved combustion and engine performance were achieved using a toroidal re-entrant combustion chamber (TCC) and hydrogen supply as a dual fuel. The combustion behavior of fuel blends and hydrogen fuel was examined by varying the engine load at a constant speed. The results revealed that significant reduction in the specific fuel consumption for rich pine oil. Thus, a slightly lesser energy share from the fuel blends and a higher energy share from the hydrogen fuel was required for the engine to maintain the same brake power. Lower viscosity, higher flash point, and presence of oxygen in the pine oil enhance the combustion rate and brake thermal efficiency. Furthermore, hydrogen induction in the engine improves the flame velocity. A lesser crevice volume in the TCC can trap the unburnt fuel which can further increase the combustion efficiency. Thus, rich pine oil with the support of hydrogen induction in TCC causes advanced ignition, improved combustion, and more heat release during the combustion. The investigation results revealed that hydrogen induction increases the heat release rate and peak pressure by 7.4% and 2.67%, respectively. Similarly, the maximum of 24.55% increase in BTE and 18.22% reduction in BSFC was observed due to a constant 10 lpm hydrogen induction. Furthermore, hydrogen fuel significantly reduces the emissions such as CO, HC, CO2, and smoke. However, more NOx was generated due to more heat release rate during combustion. Thus, pine oil and waste cooking oil biodiesel blends with the support of hydrogen induction in TCC improve the engine performance and mitigate the toxic pollutants and can be a suitable alternative to diesel fuel.Öğe Assessing the impact of sargassum algae biodiesel blends on energy conversion in a modified single-cylinder diesel engine with a silica-incorporated diamond-like coated piston(Taylor & Francis, 2024) Jayaraman, Kamalakannan; Veeraraghavan, Sakthimurugan; Sundaram, Madhu; Varuvel, Edwin GeoAs coal and oil reserves deplete, the world is shifting to alternative fuels and renewable energy. Researchers are exploring a cleaner alternative to fossil fuels for powering automobiles. In this investigation, biodiesel was synthesized from brown marine algae (Sargassum algae) using transesterification process. Silica-incorporated diamond-like coating (DLC) was done on the engine piston by using the chemical vapor deposition (CVD) process with flow rate of 7sccm of C2H2. Three different coating thicknesses, such as 50,100, and 150 mu m, were employed on the CI engine piston. Mechanical properties such as hardness, wear, and microstructure analysis were investigated. Analysis of mechanical characteristics reveals that pistons with a 100 mu m coating have enhanced characteristics compared to those with other pistons. Using a 100 mu m silicon coated piston on a single-cylinder Kirloskar engine, four blends (B10, B20, B30, and B40) were compared to neat diesel. At maximum engine load conditions, the B40 blends produced 42 ppm of HC whereas neat diesel with 19 ppm which is 57% higher than diesel and CO emission concentration increased by 4.9% than diesel. Similarly, brake-specific fuel consumption was observed at maximum load conditions for diesel with 0.18 kg/kWh and 0.20 kg/kWh for B10D90 which is 9.54% higher than diesel. As a result, it is critical to recognize the importance of sargassum's potential for producing sustainable energy toward green globalization.Öğe Recent advances and research progress on the role of carbon-based biomass in ultra-capacitors: a systematic review(Wiley, 2024) Balasubramanian, Dhinesh; Varadharajan, Hariharan; Papla Venugopal, Inbanaathan; Varuvel, Edwin GeoBiomass-derived carbon material has drawn significant attention recently due to its wide availability, environmentally free, and effective performance of the resulting porous carbons for supercapacitor (SC) applications. Carbon electrode material derived from biomass is used for energy storage (ES) because it has distinct qualities in porosity, a large specific surface area, and excellent conductivity. Furthermore, these materials' homogeneous, flawless biological structures can be used as models to create electrode materials with accurate geometries. The ES devices, known as SCs, also known as ultra-capacitors, serve as a link between a capacitor and a battery. Due to their charge storage, SCs can produce a much higher density than batteries. Several factors, including the electrode's potential window, the electrode materials characteristics, and the electrolyte choice, have a major effect on SC performance. Therefore, all efforts have been made to develop SC electrode materials. This paper explains the different types of SCs and how they work. The various available biomass resources, as well as the methods for producing them, are outlined. In addition, the different types of electrode materials, activation methods, heteroatom functionalization, and electrolyte types are all thoroughly examined. The application and research advancement of biomass-derived carbon used in SCs over the past 3 years are highlighted. Furthermore, this research outlines the benefits of SCs for the environment and the economy, as well as present challenges and future recommendations for advancing biomass-derived carbon applications. This article aims to give an in-depth knowledge of carbon-based biomass materials that are used in SCs. Biomass-derived carbon material for supercapacitors. imageÖğe Evaluating the potential performance of methane in lean conditions and examining the variations in combustion in a gasoline direct injection engine(Pergamon elsevier science LTD, 2024) Stanley, M. Jerome; Varuvel, Edwin Geo; Martin, M. Leenus JesuThe present work investigates the effect of methane addition on a direct injection spark-ignition engine's performance, combustion, cycle-to-cycle variation, coefficient of variation, and emission characteristics. Equivalence ratio of the engine is varied from lambda = 1.0, 1.02, 1.08, 1.15, and 1.22. Methane addition for the equivalence ratios (lambda = 1.0, 1.02, and 1.08) close to the stoichiometric condition does not support the methane addition. Decrease in peak pressure is seen in minimum to the maximum methane addition of 19.5 %. Adding the gaseous fuel to the intake manifold causes charge displacement, as the fuel is inducted at the suction top dead center. This effect is consistent with the increase in flame initiation and combustion durations. The same methane addition fraction for the equivalence ratios of lambda = 1.15 and 1.22 provides better combustion stability and efficiency. The peak pressure attainment for lambda = 1.22 is a 25 % increment with the maximum methane addition. Emission formation of carbon monoxide and unburnt hydrocarbons drops as the fuel is leaner towards lambda = 1.22, even with the addition of methane. The oxides of nitrogen emissions decrease initially for the equivalence ratio close to the stoichiometric condition but increase for the leaner equivalence ratio with the methane addition fraction.Öğe Dual-Channel Fuzzy Interaction Information Fused Feature Selection With Fuzzy Sparse and Shared Granularities(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 14.11.2024) Ju, Hengrong; Fan, Xiaoxue; Ding, Weiping; Huang, Jiashuang; Xu, Suping; Yang, Xibei; Pedrycz, WitoldFuzzy information granularity is an effective granular computation approach for feature evaluation and selection. However, most existing methods rely on a single granulation channel, neglecting different granularity representations. In this article, a novel dual-channel fuzzy interaction information fused feature selection with fuzzy sparse and shared granularities is proposed. It mainly comprises the following three parts. First, a dual-channel framework is introduced to construct the fuzzy information granularity from two different strategies. One channel employs sparse mutual strategy to form the sparse representation-based fuzzy information granularity, while the other constructs the fuzzy shared information granularity with a novel fuzzy semi-ball. Second, in each channel, the criteria of maximum relevancy, minimum redundancy, and maximum interaction is adopted to access feature correlation and perform feature ranking. Third, the two feature sequences derived from the dual-channel are fused to form a final feature sequence based on the within-class and between-class mechanism. To validate the efficacy of the proposed method, experimental validations on 15 datasets and schizophrenia data are conducted. The results show that the proposed method outperforms other algorithms in classification accuracy and statistical analysis. Moreover, its superiority regarding accuracy can be demonstrated in the experiments of schizophrenia detection, where it performs well in recognizing schizophrenia through visual interpretation.Öğe Experimental investigation of ammonia gas as hydrogen carrier in prunus amygdalus dulcis oil fueled compression ignition engine(Elsevier Ltd, 2024) Sonthalia, Ankit; Geo Varuvel, Edwin; Subramanian, Thiyagarajan; Josephin JS, Femilda; Almoallim, Hesham S.; Pugazhendhi, ArivalaganThe present study aims to utilize ammonia gas as a hydrogen carrier with prunus amygdalus dulcis (sweet almond oil)-fueled single-cylinder compression ignition (CI) engine. Due to the high viscosity of sweet almond oil, a transesterification procedure was used to convert it to biodiesel. The diesel fuel was completely replaced with biodiesel to assess the performance, emission, and combustion characteristics of the CI engine running at a constant speed of 1500 rpm under different load conditions. Poor performance and combustion were exhibited with biodiesel in comparison to diesel. Lower brake thermal efficiency with higher fuel consumption and lower nitrous oxides (NOx) emissions were observed with biodiesel in comparison to diesel. While hydrocarbon (HC), carbon monoxide (CO), and smoke emissions were higher with biodiesel, to further improve the performance, hydrogen gas was introduced at different flow rates (10–30 LPM). Hydrogen improved the brake thermal efficiency with reduced carbon emissions. At maximum load condition, with 30 LPM hydrogen brake thermal efficiency is improved by 15 %. However, NOx emissions were higher with hydrogen induction compared to base fuels at all load conditions. NOx emissions were increased from 1274 ppm with biodiesel to 1451 ppm with 30 LPM hydrogen addition at maximum load. Although hydrogen is one of the most promising techniques to improve the performance of biodiesel, its higher NOx emissions and safety aspects make its practical application questionable. Hence, ammonia gas was used as a hydrogen carrier, and tests were conducted in dual fuel mode with biodiesel at different flow rates. It is observed that performance parameters in ammonia dual fuel mode are on par with those of biodiesel with reduced carbon and NOx emissions. Hence, ammonia can be considered a viable option to replace hydrogen as its carrier to meet global energy demands and also for its safer use. © 2024 Elsevier LtdÖğe Crafting high-performance polymer-integrated solid electrolyte for solid state sodium ion batteries(Wiley, 2024) Kannadasan, Mahalakshmi; Sathiasivan, Kiruthika; Balakrishnan, Muthukumaran; Subramanian, Balaji; Varuvel, Edwin GeoThe development of modern solid-state batteries with high energy density has provided the reliable and durable solution needed for over-the-air network connectivity devices. In this study, a NASICON-type Na3Zr2Si2PO12 (NZSP) ceramic filler was prepared using the sol-gel method and then a polymer-integrated solid electrolyte consisting of polyethylene oxide (PEO), NZSP, and sodium perborate (SPB) was prepared by Stokes' solution casting process. Through physico-chemical and electrochemical characterization techniques, the morphology, electrochemical, and thermal properties of the prepared solid electrolyte sample were carefully studied. The PEO/NZSP/SPB electrolyte developed for all-solid-state sodium-ion batteries (ASSSBs) exhibited a strong ionic conductivity, a large window for electrochemical stability, and was effective in controlling the growth of sodium dendrites. Furthermore, the polymer-integrated solid electrolyte showed impressive rate capability, high discharge capacity (73.2 mAh g-1) at 0.1 mA cm-2, and good faradaic efficiency (98%) even after 100 cycles. These results reveal that the PEO/NZSP/SPB electrolyte is a potential and inevitable candidate for the evolution of high-performance rechargeable ASSSBs.Öğe Bending, free vibration and buckling finite element analysis of porous functionally graded plates with various porosity distributions using an improved FSDT(Taylor & francis, 2024) Belarbi, Mohamed-Ouejdi; Karamanlı, Armağan; Benounas, Soufiane; Daikh, Ahmed AmineFunctionally graded materials (FGMs) are advanced composite materials with spatially varying properties, and their porosity distribution further enhances their complexity. The distribution pattern of porosity within a porous material plays a crucial role in determining the mechanical response of these structures. Therefore, the main objective of this study is to analyze the bending, free vibration, and buckling characteristics of porous FG plates by considering different porosity distributions and their effects on the overall behavior. To achieve this goal, a new finite element model is developed in the framework of an improved first-order shear deformation theory (IFSDT). In contrast to the conventional Mindlin-Reissner theory, the present IFSDT incorporates an improved mathematical formulation and provides a more realistic parabolic depiction of shear strain throughout the plate's thickness without using any shear correction factors. In the present study, five types of porosity distribution functions are considered for the analysis. The material characteristics of the FGM porous plate change gradually in the thickness direction based on a power-law function. The governing equations are derived here using Hamilton's principle, and a finite element method is employed for numerical analysis. Comparative analyses with previously published literature underscore the precision and simplicity of our developed finite element model. Moreover, the effects of various types of loads, porosity parameters, power-law index, side-to-thickness ratio, aspect ratio, porosity distributions and boundary conditions on the deflections, natural frequencies, and critical buckling loads are thoroughly analyzed in detail. Finally, the findings of this research contribute to the understanding of the mechanical behavior of FGMs and pave the way for designing and optimizing novel porous functionally graded structures.Öğe On the bending, buckling and free vibration analysis of bio-inspired helicoidal laminated composite shear and normal deformable beams(Elsevier ltd, 2025) Karamanlı, Armağan; Vo, Thuc P.; Belarbi, Mohamed-Ouejdi; Lee, SeunghyeThe mechanical behaviours of bio-inspired helicoidal symmetric laminated composite (BIHLC) beams are investigated via the Ritz method. By exploiting the variational formulation, equations of motion along with element stiffness, geometrical stiffness, and mass matrices are derived. The study conducts a thorough examination, covering bending, buckling stability, and free vibration analyses of BIHLC beams with various lamination schemes. The developed model is verified against existing literature on conventional composite laminated and BIHLC beams. The study also examines the mechanical response of BIHLCs, considering boundary conditions, lamination schemes, orthotropy ratios, and aspect ratios. Notably, deflections, critical buckling loads, and fundamental frequencies demonstrate variations dependent on the specific lamination scheme, boundary condition, and aspect ratio. Novel findings, presented for the first time, offer valuable insights for future studies in this area.Öğe A deep learning multi-feature based fusion model for predicting the state of health of lithium-ion batteries(Elsevier ltd, 2025) Sonthalia, Ankit; Bai, Femilda Josephin Joseph Shobana; Varuvel, Edwin Geo; Chinnathambi, Arunachalam; Subramanian, Thiyagarajan; Kiani, FarzadLithium-ion batteries have become the preferred energy storage method with applications ranging from consumer electronics to electric vehicles. Utilization of the battery will eventually lead to degradation and capacity fade. Accurately predicting the state of health (SOH) of the cells holds significant importance in terms of reliability and safety of the cell during its operation. The battery degradation mechanism is strongly non-linear and the physics-based model have their inherent disadvantages. The machine learning method has become popular for estimating SOH due to its superior non-linear mapping, adaptive, and self-learning capabilities, made possible by advances in deep learning technologies. In this study parallel hybrid neural network is formulated for predicting the state of health of lithium-ion cell. Firstly, the factors that have an effect on the cell state were analysed. These factors are cell voltage, charging & discharging time and incremental capacity curve. The features were then processed for use as input to the model. Spearman correlation coefficient analysis shows that all the factors had a positive correlation with SOH. While charging time has a negative correlation with the other features. Next the deep learning models namely convolution neural network (CNN), temporal convolution network (TCN), long-short-term memory (LSTM) and bi-directional LSTM were used to make fusion models. The number of layers in CNN and TCN were also varied. The hyperparameters used in the models were optimized using Bayesian optimization algorithm. The models were validated through comparative experiments on the University of Maryland battery degradation dataset. The prediction accuracy with CNN 3-layer LSTM was found to be the best for the training and the test dataset. The overall R2 value, root mean squared error (RMSE) and mean absolute percentage error (MAPE) with the model was found to be 0.999646, 0.003807 and 0.3, respectively. The impact of the features on the model was also analysed by removing one feature and retraining the model with the other features. The effect of discharging time and the peak of the discharge incremental capacity curve was maximum. The analysis also reveals that either charging voltage or discharging voltage can be used. Further, the proposed model was also compared with the other studies. The comparison shows that the R2, RMSE and MAPE values of the proposed model was better.Öğe Impact of hydrogen-assisted combustion in a toroidal re-entrant combustion chamber powered by rapeseed oil/waste cooking oil biodiesel(Elsevier ltd, 2025) Thiagarajan, S.; Seetharaman, Sathyanarayanan; Lokesh, R.; Prasanth, G.; Karthick, B.; Bai, Femilda Josephin Joseph Shobana; Ali Alharbi, Sulaiman; Pugazhendhi, Arivalagan; Varuvel, Edwin GeoThis study investigates the performance and emission characteristics of biodiesel blends of rapeseed oil and waste cooking oil in a toroidal re-entrant combustion chamber (TCC) compression ignition engine. Hydrogen was allowed into the engine in dual fuel mode to enhance the engine performance. The presence of oxygen in the biodiesel and hydrogen induction increased the peak pressure and heat release rate significantly for all the engine loads. At a peak load of 4.88 kW, the maximum brake thermal efficiency (BTE) of 31.77% was recorded for the D70R20W10 (diesel 70%, rapeseed oil 20%, waste cooking oil 10%) biodiesel blend. Furthermore, hydrogen induction enhanced the BTE by around 3%. The biodiesel blending substantially lowered the emissions of unburnt hydrocarbons, carbon monoxide, and smoke opacity. Additionally, hydrogen supplementation facilitated 5-10% carbon monoxide reduction over biodiesel blends by enabling more complete oxidation. However, higher temperatures generated due to complete combustion resulted in more NOx formation. Thus, the authors propose that biodiesel blends of rapeseed oil, waste cooking oil, and diesel with hydrogen induction improve engine performance and reduce regulated emissions.Öğe Battery fault diagnosis methods for electric vehicle lithium-ion batteries: Correlating codes and battery management system(Institution of chemical engineers, 2025) Naresh, G.; Praveenkumar, T.; Madheswaran, Dinesh Kumar; Varuvel, Edwin Geo; Pugazhendhi, Arivalagan; Thangamuthu, Mohanraj; Muthiya, S. JenorisLithium-ion batteries are the heart of modern electric vehicle technology. Operational stresses such as temperature changes, mechanical impacts, and electrochemical aging often subject them to faults, necessitating accurate fault diagnosis that adheres to international safety standards. Consequently, this review examines state-ofthe-art fault diagnosis methodologies, emphasizing their integration with global safety frameworks such as the International Organization for Standardization, International Electrotechnical Commission, Society of Automotive Engineers, etc. A thorough analysis of artificial fault induction techniques-such as overcharging and overheating-is presented to assess their effectiveness in validating diagnostic algorithms. Additionally, the role of machine learning in battery management systems is reviewed, where the Feature Fusion and Expert Knowledge Integration network emerged effective, achieving an anomaly detection rate of 98.5 %, outperforming conventional methods in accuracy and speed. Hybrid diagnostic frameworks integrating model-based and machine-learning techniques are also highlighted for their scalability and precision in addressing sub-extreme fault scenarios. Looking ahead, this study emphasizes the importance of interdisciplinary research to enhance fault detection, focusing on adaptive machine learning algorithms and real-world testing to ensure the long-term viability of contemporary battery technologies.Öğe A comparative analysis of advanced machine learning models for the prediction of combustion, emission and performance characteristics using endoscopic combustion flame image of a pine oil–gasoline fuelled spark ignition engine(Elsevier Ltd., 2024) Godwin, D. Jesu; Varuvel, Edwin Geo; Jesu Martin, M. Leenus; Jasmine R, Anita; Josephin JS, FemildaThis research focuses on using machine learning to predict the spark ignition engine's combustion, performance, and emission parameters with bio-fuel blends such as pine oil blend, which significantly diminishes the environmental impact of traditional fuels, reduces the limitations of repeated engine experimentation and addresses the nonlinearities in engine test results contributing to sustainable cleaner fuel and energy solutions. The models used were Ensemble Decision Tree Bagging, Ensemble Least Squares Boosting, Gaussian Process Regression and Support Vector Machine Regression, with good generalization ability. Brake Specific Fuel Consumption data from the test engine trials and endoscopic image flame area data after spark timing at different crank angles (320, 400, 480, 560, and 640 after Spark Timing) were fed into the machine-learning models as predictors. The response variables were Brake thermal efficiency, Unburnt Hydrocarbons, Carbon monoxide, Carbon dioxide, Oxides of nitrogen, maximum In-cylinder pressure, and maximum heat release rate. The bootstrap technique was used to generate numerous datasets from the experimental data for data-driven model training and tested using both interpolative and extrapolative data. The experimental and predicted values for all these algorithms were subjected to repeated hyperparameter optimization trials and the best machine learning method was identified using the performance and error metrics. The Ensemble Least Squares Boost model showed the overall best correlation (R2) in the range of 0.97–0.99 for gasoline and pine oil PN20 blend for the predicted versus experimental engine parameters. The root-mean-squared error (RMSE) at maximum load ranged between 0.0086 and 0.3044 for gasoline and 0.0049–0.2046 for the Pine oil PN20 fuel blend respectively. Therefore, employing an Ensemble Least Squares Boosting machine learning framework can effectively predict the characteristics of gasoline engines using pine oil and blends. This approach serves as a virtual engine model, efficiently overcoming the limitations and complexities inherent in conventional engine experiments. © 2024 Elsevier LtdÖğe On the Effect of Interphase Boundary Energy Anisotropy on Morphologies: A New Type of Eutectic Grain Observed in a Three-Phase Eutectic System(Springer, 2024) Mohagheghi, S.; Şerefoğlu, M.Eutectic microstructures are dramatically affected by the anisotropy in interphase boundary energy. Depending on this anisotropy function, different eutectic grains may grow simultaneously at the same experimental conditions. In all reported quasi-isotropic and anisotropic two-phase and three-phase eutectic grains in thin samples, lamellar morphology is observed and the microstructure is essentially two dimensional (2D), since the interphase boundaries are perpendicular to the sample walls. Using the ?(In)–In2Bi–?(Sn) system and real-time solidification experiments in thin samples, we introduce a unique and new type of anisotropic three-phase eutectic grain, entitled here as “Laminated Matrix with Rods (LMR).” In this grain, due to the anisotropy in In2Bi/?(Sn) interphase boundary, the evolving phases, and hence, the microstructures observed through the two glass plates of the thin sample are completely different, despite the strong confinement effect. During rotating directional solidification (RDS) experiments, the morphology or the aspect ratio of all phases changes periodically and drastically. Specifically, In2Bi, ?(In), and ?(Sn) phases evolve from all being lamellar perpendicular to the sample walls to the matrix, elongated/trapezoidal rods, and a lamella parallel to the sample walls, respectively. Our experimental results show that these morphological transitions are due to change in the interphase boundary orientation with respect to the growth direction. Graphical abstract: (Figure presented.) © The Author(s) 2024.Öğe NOx emission reduction in low viscous low cetane (LVLC) fuel using additives in CI engine: an experimental study(Springer Science and Business Media Deutschland GmbH, 2024) Sonthalia, A.; Varuvel, E.G.; Subramanian, T.; Kumar, N.This study examines the combustion properties of pine oil (PO), which is classified as a low viscosity, low cetane (LVLC) fuel. It highlights the superior performance of pine oil in comparison to diesel fuel, but acknowledges that its low cetane index causes a delay in combustion initiation, which consequently results in elevated NOx emissions. Fuel atomization, evaporation, and air/fuel mixing are enhanced by the reduced viscosity and boiling point of PO in comparison to diesel. Nevertheless, the low cetane index of PO restricts its applicability as a diesel fuel substitute in CI engines. Due to significant heat release after an extended ignition delay, NOx emissions tend to rise with less viscous and low cetane (LVLC) fuels. A range of cetane improvers, such as diethyl ether (DEE), benzyl alcohol (Bn), diglyme (DGE), and methyl tert-butyl ether (MTBE), have demonstrated effectiveness in mitigating nitrogen oxide (NOx) emissions upon introduction into pine oil. All the cetane improvers were added 5% and 10% by volume with pine oil. A twin-cylinder tractor engine operating at a constant speed of 1500 revolutions per minute was utilized in this testing. In order to achieve a warm-up condition that would enable the smooth operation of PO, the engine was initially operated on diesel fuel. At maximum load condition, NOx emission of PO was higher by 8% in comparison to diesel. NOx emission was significantly reduced with addition of cetane improvers. Maximum reduction of 7% was observed with PO + MTBE 10% in comparison to PO which is in par with diesel. An increase in HC and CO emission was observed with all cetane improver addition with PO. Graphical abstract: (Figure presented.). © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.Öğe An innovative transient simulation of a solar energy system with a thermochemical hydrogen production cycle for zero-energy buildings(Elsevier Ltd, 2024) Mohammadi, Z.; Ahmadi, P.; Ashjaee, M.This research investigates the incorporation of solar power systems into buildings to meet the energy needs of near-zero-energy buildings. The study focuses on a complex buildings in Shiraz City, Iran. The primary objective of this case study is to integrate an innovative method of hydrogen production known as thermochemical hydrogen production methods to fulfill the building's energy demands. Solar energy is utilized to generate heat by parabolic trough collectors, which is the sole energy source required for the V–Cl thermochemical cycle. Consequently, hydrogen is produced and stored during the day for use at night when there is no solar radiation. To address this, a novel component has been developed for the vanadium chlorine cycle (V–Cl) within the TRNSYS software. The energy system was simulated using the TRNSYS software, a powerful transient simulation tool. Despite the numerous advantages offered by TRNSYS's energy system simulation, it lacks optimization capabilities. The use of a neural network-genetic algorithm optimization approach allows for the calculation of an optimized area for collectors and the power output of fuel cells for the building complex. The optimum configuration results in minimum installation cost, lowest CO2 emissions, and the highest power supply renewable (PSR). The results reveal that the installation of collectors with a surface area of 70 m2 and the utilization of fuel cells with a power output of 345 kW lead to a total carbon dioxide (CO2) generation of 10.31 tons per year, a PSR of 1.21, and a cost of $4.915 per hour. © 2024 Hydrogen Energy Publications LLCÖğe A Quasi-3D theory for bending, vibration and buckling analysis of FG-CNTRC and GPLRC curved beams(Elsevier Ltd, 2024) Pham, S.D.; Karamanli, A.; Wattanasakulpong, N.; Vo, T.P.This paper proposes a finite element model based on Quasi-3D theory, which includes both normal and shear effects, to study the bending, vibration, and buckling responses of FG-CNTRC and GPLRC curved beams. A two-node beam element satisfying C1 continuity requirement is utilized to compute displacements, critical buckling loads, and natural frequencies for beams with various boundary conditions. To evaluate the precision of the suggested model, various numerical examples are conducted. Next, a comprehensive parameter study is carried out to study the effects of distribution patterns and fractional volume of reinforced materials, open angles, aspect ratios, and boundary conditions. Numerous numerical results can serve as benchmarks for subsequent investigations. © 2024 The AuthorsÖğe Impact of hydrogen addition on diesel engine performance, emissions, combustion, and vibration characteristics using a Prosopis Juliflora methyl ester-decanol blend as pilot fuel(Elsevier Ltd, 2024) Duraisamy, B.; Varuvel, E.G.; Palanichamy, S.; Subramanian, B.; Jerome, Stanley, M.; Madheswaran, D.K.The research primarily focuses on investigating the impact of hydrogen induction on parameters of a compression ignition (CI) engine utilizing biodiesel blended with decanol, up to knock limit. The utilization of non-edible oil, exemplified by Prosopis Juliflora seed oil (JFO), presents inherent challenges due to its elevated viscosity, limited atomization, and suboptimal combustion attributes. However, the conversion of JFO into Prosopis Juliflora methyl ester (JFME) biodiesel substantially ameliorates its fuel characteristics, although it still exhibits relatively lower performance in comparison to conventional diesel fuel. To enhance the attributes of JFME blends, decanol is mixed with 20 % on volumetric basis (referred to as D20). Furthermore, the introduction of hydrogen into the engine's intake manifold is employed to bolster performance and curtail emissions. Different hydrogen flow rates, spanning from 2.5 to 10 litres per minute (lpm), are assessed in conjunction with the D20 biodiesel blend. The inclusion of hydrogen into D20 blends yields an enhancement in brake thermal efficiency (BTE), coupled with reductions in hydrocarbon (HC), carbon monoxide (CO), and smoke emissions. However, it should be noted that hydrogen's notable flame velocity and higher calorific value engender escalated combustion temperatures and an associated rise in Nitric oxide (NO) emission. The research also encompasses an evaluation of engine vibration during dual-fuel operation, revealing a proportional increase in engine vibration with heightened rates of hydrogen induction. In summation, the utilization of D20 in conjunction with hydrogen at a rate of 10 lpm emerges as a viable approach for operating diesel engines in a dual-fuel mode. © 2023 Hydrogen Energy Publications LLCÖğe Influence of hydrogen injection timing and duration on the combustion and emission characteristics of a diesel engine operating on dual fuel mode using biodiesel of dairy scum oil and producer gas(Elsevier Ltd, 2023) Lalsangi, Sadashiva; Yaliwal V.S.; Banapurmath N.R.; Soudagar, Manzoore Elahi M.; Balasubramanian, Dhinesh; Sonthalia, Ankit; Varuvel, Edwin Geo; Wae-Hayee, MakatarThe main aim of the present work is to investigate the influence of hydrogen injection timing and injection duration on the combustion and emissions of a CI engine functioning on dual fuel (DF) mode by employing diesel/dairy scum oil methyl ester (DiSOME)/Waste frying oil methyl ester (WFOME) - producer gas (PG) combination. Hydrogen flow rate was maintained constant (8 lpm) and injected in air-producer gas (PG) mixture an inlet manifold using a gas injector. In this current work, injection timing was varied from TDC to 15 deg., aTDC in steps of 5. Similarly, injection duration was adopted from 30 deg., CA to 90 deg., CA and differed in steps of 30. From the outcome of work, it is noticed that the best possible injection timing and injection duration were found to be 10 deg., aTDC and 60 deg., CA respectively. Results showed that, at optimum injection parameters, diesel-PG combination with hydrogen resulted in augmented BTE by 6.7% and 12.4%, decreased smoke by 26.04% and 36.4%, decreased HC by 16.6% and 22.4%, decreased CO by 23.5% and 29.6% and increased NOx by 12.4% and 22.1%, compared to DiSOME and WFOME supported DF operation. Investigation with DiSOME-hydrogen enriched PG combustion showed satisfactory operation. © 2022 Hydrogen Energy Publications LLC
