Investigation on diesel spray flame evolution and its conceptual model for large nozzle and high-density of ambient gas

Liu, Long; Fu, Shiyi; Han, Changfu

doi:10.1016/j.fuel.2022.127357

Cited by 19 publications

(6 citation statements)

References 19 publications

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“…In Figure 10(b) the deep green region shows the higher value of 0.25em Q i with respect to the speed and fuel blend. It can be seen that, at lower value of fuel blend and speed the 0.25em Q i value increases (Liu et al, 2023; Muhammad et al, 2022; Wu et al, 2023).…”

Section: Resultsmentioning

confidence: 99%

Developing a model for waste plastic biofuels in CRDi diesel engines using FTIR, GCMS, and WASPAS synchronisations for engine analysis

Kanchan,

Pradhan,

Kumar

et al. 2023

Energy Exploration & Exploitation

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The excessive use of single-use plastic products in modern life has caused severe environmental, social, economic, and health consequences globally. Mostly all plastics manufactured are one-time-use materials that end up in landfills or as unmanageable garbage. This situation has led to the production of around 400 million tonnes of plastic waste per year, and if this trend continues, global production will reach up to 1100 million tonnes by 2050. India alone produced over 34.7 lakh tonnes per annum (TPA) of plastic waste, with only half of it being recycled or co-processed. As such, there is an urgent need to develop ways to reduce plastic waste. One possible solution is the use of waste plastic biofuel in engines, which has been shown to have promising results. The study aimed to analyse waste plastic oil using (Gas Chromatography Mass Spectrometry) GC-MS and (Fourier Transform Infrared Spectroscopy) FTIR analysis to identify its chemical composition. The findings of the study revealed the presence of various chemical compounds, such as alcohol, hydroperoxide, carbonyl acid groups, ester, carboxylic acid, ketones, aldehyde groups, and others. FTIR analysis confirmed the presence of alcohol, hydroperoxide, carbonyl acid groups, methyl and methylene groups, ester, carboxylic acid, ketones, aldehyde group, symmetric and asymmetric C-H bending, C-O stretch for ethers, carboxylic acids, and esters, and=C-H bending out for alkenes. The study further explains that primary plastic consumption and packaging lifetime have a significant impact on plastic waste generation. The research indicates the need to explore alternative ways to recycle and dispose of single-use plastics to mitigate its negative impact on the environment. Furthermore, this study analyses the statistical optimisation method to develop a model fit for engine behaviour using waste plastic biofuel on a single-cylinder (common rail direct injection engine) CRDi diesel engine using the (weighted aggregated sum product assessment) WASPAS approach. Additionally, the objective is to develop a model that can optimise the engine's performance while using waste plastic biofuel. The uncertainty analysis demonstrated that the experiment was carried out with a high degree of accuracy and the results were reliable. The study employed the WASPAS methodology to evaluate the performance of different (waste plastic oil) WPO samples, and the results showed that the optimal parametric setting to obtain the desired responses can be achieved with a fuel blend of 5%, load of 21 bar, and speed of 2000 RPM. However, the results demonstrate that the use of waste plastic biofuel can significantly improve engine performance, and the proposed optimisation model can accurately predict the engine's behaviour. The regression equation that was formulated showed a reasonable degree of agreement between the actual experimental results and the predicted values, thereby indicating the reliability of the experiment. Significant effects were observed from fuel blend, and speed, whereas load did not make a substantial contribution. The findings regarding the effect of parameters suggest that a reduction in fuel blend, and engine speed resulted in a decline in the performance index, while variations in load had little impact. The relationship between load and speed demonstrates that a rise in load and a reduction in speed contributed to enhanced combustion and a higher performance index. The interaction among fuel blend and speed, with a particular emphasis on the significance of reduced fuel blend and speed values in order to optimise the performance index. The findings of the analysis underlined the vitality of process parameters, specifically fuel blend and speed, wherein speed exhibited a significant impact on the outcomes. The study concludes that the use of waste plastic biofuel in engines can be an effective way to reduce plastic waste while improving engine performance. This study's findings can be applied to various engines to improve their performance while reducing plastic waste. All in all, the outcomes of the study make a substantial contribution to the advancement of scientific information regarding the properties of waste plastic oil as well as its combustion characteristics. This expands the potential for advanced breakthrough innovations in sustainable energy solutions and the conservation of the environment.

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Section: Resultsmentioning

confidence: 99%

Developing a model for waste plastic biofuels in CRDi diesel engines using FTIR, GCMS, and WASPAS synchronisations for engine analysis

Kanchan,

Pradhan,

Kumar

et al. 2023

Energy Exploration & Exploitation

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“…Next, in Fig 6 (b), we show a relationship between the number of trees in the model and the depth of each tree. We created a grid of 9 different n estimators' values (100 to 500) and 6 different max depth values (2,4,6,8,10,12), and each combination was evaluated using 10-fold cross-validation. A total of 9 × 6 × 10 or 540 models were trained and evaluated.…”

Section: Hyperparameter Resultsmentioning

confidence: 99%

“…The data preprocessing module removes outliers using the deep autoencoder (DAE) reconstruction error (RE) [6] and normalizes the data using OrdinalEncoder (OE) transformation techniques. The data labeling module selects only natural gas (NG) CH4 [7,8] data from the preprocessed data, divides it into groups using the k-means clustering algorithm, and classifies the data according to that group. Afterward, the predictive analysis module builds a model that predicts gas loss using machine learning algorithms on the available data.…”

Section: Introductionmentioning

confidence: 99%

NDAMA: A Novel Deep Autoencoder and Multivariate Analysis Approach for IoT-Based Methane Gas Leakage Detection

Dashdondov,

Kim,

2023

IEEE Access

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Natural gas is widely used for domestic and industrial purposes, and whether it is being leaked into the air cannot be directly known. The current problem is that gas leakage is not only economically harmful but also detrimental to health. Therefore, much research has been done on gas damage and leakage risks, but research on predicting gas leakages is just beginning. In this study, we propose a method based on deep learning to predict gas leakage from environmental data. Our proposed method has successfully improved the performance of machine learning classification algorithms by efficiently preparing training data using a deep autoencoder model. The proposed method was evaluated on an open dataset containing natural gas and environmental information and compared with extreme gradient boost (XGBoost), K-nearest neighbors (KNN), decision tree (DT), random forest (RF), and naive Bayes (NB) algorithms. The proposed method is evaluated using accuracy, F1-score, mean square error (MSE), mean intersection over union (mIoU), and area under the ROC curve (AUC). The presented method in this study outperformed all compared methods. Moreover, the deep autoencoder and ordinal encoder-based XGBoost (DA-MA-XGBoost) showed the best performance by giving 99.51% accuracy, an F1-score of 99.53%, an MSE of 0.003, mIoU of 99.40 and an AUC of 99.62%.INDEX TERMS Deep autoencoder, multivariate analysis, methane gas, risk detection, XGBoost.

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“…Meanwhile, the density-based algorithm is chosen because of the high-pressure gradient in our model 47 – 50 . More facts regarding the governing equations have been presented in fuel details in published articles 51 – 53 . Theoretical methods have extensively used for optimization and improvement of the mechanical systems 54 – 57 .…”

Section: Governing Equations and Simulation Methodologymentioning

confidence: 99%

Fuel mixing enhancement of transverse coaxial air and fuel jet by upstream shock wave on in scramjet engines: numerical study

Abdollahi,

Jafari,

Aminian

et al. 2023

Sci Rep

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In this study, computational fluid dynamics (CFD) is used to disclose the impacts of upstream shock waves on fuel mixing of cross coaxial air and fuel jet at a scramjet engine. This study has tried to investigate the impact of three different lobe injectors (2-lobe, 3-lobe, and 4-lobe nozzle) on the fuel penetrations along the scramjet combustor. The supersonic air stream is M = 4 while cross hydrogen and air jet are released in sonic velocity. This study uses CFD simulations to analyze the effects of upstream shock waves on fuel mixing in the transverse coaxial jet and assess their potential for improving combustion efficiency. The results demonstrate that the usage of upstream shock waves significantly increases shock interactions and augments the vortex region downstream of the jet. Our results show that the impacts of shock waves on the penetration of fuel jet released from the coaxial lobe nozzle are substantial.

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Investigation on diesel spray flame evolution and its conceptual model for large nozzle and high-density of ambient gas

Cited by 19 publications

References 19 publications

Developing a model for waste plastic biofuels in CRDi diesel engines using FTIR, GCMS, and WASPAS synchronisations for engine analysis

Developing a model for waste plastic biofuels in CRDi diesel engines using FTIR, GCMS, and WASPAS synchronisations for engine analysis

NDAMA: A Novel Deep Autoencoder and Multivariate Analysis Approach for IoT-Based Methane Gas Leakage Detection

Fuel mixing enhancement of transverse coaxial air and fuel jet by upstream shock wave on in scramjet engines: numerical study

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