Pub Date : 2025-03-26DOI: 10.1016/j.fuel.2025.135196
Xinlong Zhang , Huiqing Guo , An Yan , Tong Shi , Yanqiu Lei , Fenrong Liu
In this study, the mechanisms of thiophenes decomposition catalyzed by the perfect and defective surfaces of CaO were mainly investigated by density functional theory (DFT) calculations. By XPS analysis, thiophenes of YQ coal significantly decreases after adding CaO, meanwhile CaS obviously appears in XPS spectra, suggesting CaO possesses the strong desulfurization effect on thiophenes. DFT calculation results show that the direct C2-S bond breakage of TH all difficultly occur on these three CaO surfaces, especially for the Cavac surface as of its highest energy barrier. Similar, its C3-C4 bond breakage is more difficult to occur on these three surfaces. However, the direct CH3C2-S bond breakage of 2-methylthiophene (2-MT) all easily happen on these three CaO surfaces, especially for the Ovac surface as of its lowest energy barrier and negative reaction energy. In addition, the sulfur atom of 2-MT finally combines with the Ca to form CaS on these surfaces, further discovering the reasons about the appearance and increase of CaS in XPS spectra. These DFT calculations can provide some theoretical basis for the catalyzed desulfurization mechanisms of thiophenes.
{"title":"Discovering the desulfurization mechanisms of thiophenes catalyzed by CaO (001) different surfaces","authors":"Xinlong Zhang , Huiqing Guo , An Yan , Tong Shi , Yanqiu Lei , Fenrong Liu","doi":"10.1016/j.fuel.2025.135196","DOIUrl":"10.1016/j.fuel.2025.135196","url":null,"abstract":"<div><div>In this study, the mechanisms of thiophenes decomposition catalyzed by the perfect and defective surfaces of CaO were mainly investigated by density functional theory (DFT) calculations. By XPS analysis, thiophenes of YQ coal significantly decreases after adding CaO, meanwhile CaS obviously appears in XPS spectra, suggesting CaO possesses the strong desulfurization effect on thiophenes. DFT calculation results show that the direct C<sub>2</sub>-S bond breakage of TH all difficultly occur on these three CaO surfaces, especially for the Ca<sub>vac</sub> surface as of its highest energy barrier. Similar, its C<sub>3</sub>-C<sub>4</sub> bond breakage is more difficult to occur on these three surfaces. However, the direct CH<sub>3</sub>C<sub>2</sub>-S bond breakage of 2-methylthiophene (2-MT) all easily happen on these three CaO surfaces, especially for the O<sub>vac</sub> surface as of its lowest energy barrier and negative reaction energy. In addition, the sulfur atom of 2-MT finally combines with the Ca to form CaS on these surfaces, further discovering the reasons about the appearance and increase of CaS in XPS spectra. These DFT calculations can provide some theoretical basis for the catalyzed desulfurization mechanisms of thiophenes.</div></div>","PeriodicalId":325,"journal":{"name":"Fuel","volume":"395 ","pages":"Article 135196"},"PeriodicalIF":6.7,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The escalating interest in utilizing non-competitive feedstocks for biodiesel production suggests waste cooking oil as a cost-effective resource being explored. The present work highlights the bioconversion of waste cooking oil catalyzed by heterogeneous ZnO nano-catalyst derived from Aloe vera. The performance of DI-CI engine was analyzed for the biodiesel blends of B20 & B20GS50 with externally cooled electronically controlled EGR. The green synthesized zinc oxide nano particle acts as a dual performer including transesterification catalyst and fuel additive. The results revealed that nano catalyzed biodiesel potential of waste cooking oil was 92 ± 0.24 %. The kinetic modelling demonstrated first order reaction kinetics with k = 0.015 min−1 and thermodynamic analysis evidenced endothermic nature of transesterification with ΔH = 39.74 kJ/mol. UV–Vis spectra confirm the presence of zinc oxide nanoparticles at 564 cm−1. FTIR analysis exhibited peaks at 2928, 1442, 3428 and 1750 cm−1 indicate alkane (CH2), C=O, hydroxyl and amino functional moieties respectively. The sharp peak indicates good crystallinity of the nanoparticles in XRD analysis. Machine learning tools such as RSM and ANN demonstrated lesser RMSE and R2 values of 0.1555, 0.2276, 20.33 and 83.54 for BTE and NOx respectively. The higher R2 value of RSM such as 0.9891 and 0.9999 corresponding to BTE and NOx indicates the reliability of the model towards performance optimization. RSM predicted optimized parameters are 100 % load, 81.564 % biodiesel and 20 % EGR resulted with 31.259 % BTE and 169.2 ppm NOx. The predictive ability of RSM was higher than ANN. Therefore, the study recommended RSM for performance optimization of DI-CI engine.
{"title":"Hybrid optimization of engine performance and emission using RSM-ANN-GA framework to explore valorization potential of waste cooking oil with green synthesized heterogenous ZnO nanocatalyst","authors":"Prakash Rajavel , Murugesan Arthanarisamy , Subbaiya Ramasamy","doi":"10.1016/j.fuel.2025.135092","DOIUrl":"10.1016/j.fuel.2025.135092","url":null,"abstract":"<div><div>The escalating interest in utilizing non-competitive feedstocks for biodiesel production suggests waste cooking oil as a cost-effective resource being explored. The present work highlights the bioconversion of waste cooking oil catalyzed by heterogeneous ZnO nano-catalyst derived from Aloe vera. The performance of DI-CI engine was analyzed for the biodiesel blends of B20 & B20GS50 with externally cooled electronically controlled EGR. The green synthesized zinc oxide nano particle acts as a dual performer including transesterification catalyst and fuel additive. The results revealed that nano catalyzed biodiesel potential of waste cooking oil was 92 ± 0.24 %. The kinetic modelling demonstrated first order reaction kinetics with k = 0.015 min<sup>−1</sup> and thermodynamic analysis evidenced endothermic nature of transesterification with ΔH = 39.74 kJ/mol. UV–Vis spectra confirm the presence of zinc oxide nanoparticles at 564 cm<sup>−1</sup>. FTIR analysis exhibited peaks at 2928, 1442, 3428 and 1750 cm<sup>−1</sup> indicate alkane (CH<sub>2</sub>), C=O, hydroxyl and amino functional moieties respectively. The sharp peak indicates good crystallinity of the nanoparticles in XRD analysis. Machine learning tools such as RSM and ANN demonstrated lesser RMSE and R<sup>2</sup> values of 0.1555, 0.2276, 20.33 and 83.54 for BTE and NO<sub>x</sub> respectively. The higher R<sup>2</sup> value of RSM such as 0.9891 and 0.9999 corresponding to BTE and NO<sub>x</sub> indicates the reliability of the model towards performance optimization. RSM predicted optimized parameters are 100 % load, 81.564 % biodiesel and 20 % EGR resulted with 31.259 % BTE and 169.2 ppm NO<sub>x</sub>. The predictive ability of RSM was higher than ANN. Therefore, the study recommended RSM for performance optimization of DI-CI engine.</div></div>","PeriodicalId":325,"journal":{"name":"Fuel","volume":"395 ","pages":"Article 135092"},"PeriodicalIF":6.7,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-26DOI: 10.1016/j.fuel.2025.135029
Zhi Zhang , Anning Zhou , Zhiwei Shi , Huaiqing Zhang , Xinfu He , Yongjuan Wang , Zhuangwei Bai , Dong Xi
Elucidating the relationship between the structure of tar-rich coal and its pyrolysis products, as well as developing an accurate predictive model for these products, can effectively establish a correspondence between tar-rich coal and high-value utilization pathways. Therefore, this study systematically investigates the structural characteristics of tar-rich coals through proximate analysis, ultimate analysis, and 13C NMR, and establishes the correlation between coal structure and pyrolysis products using Pearson correlation analysis. Subsequently, ridge regression is applied to construct a predictive model for pyrolysis products using the structural characteristics of tar-rich coals. The results indicate that there is a significant correlation between the pyrolysis yield, product distribution, and the functional groups of tar-rich coal structure. Specifically, tar yield is highly correlated with Vdaf, terminal methyl groups, methyl groups on rings, and oxygen-attached aromatic carbon. The formation of tar components, including light oil, phenolic oil, and naphthalene oil, is influenced by aliphatic carbon, methylene, aromatic methyl, and methoxy. Additionally, the correlations between Mad, O/C ratio, methyl group on rings (Ar-CH3), and fixed carbon (FCd) are closely related to the yields of pyrolysis gas and semi-coke. Based on these correlations, a pyrolysis yield prediction model was constructed, with the R2 value exceeding 0.87 and the prediction accuracy greater than 88.06%. This study provides valuable theoretical insights into the directional transformation of oils and gases during pyrolysis.
{"title":"Explaining relationships between chemical structure and tar-rich coal pyrolysis products yield based on Pearson correlation coefficient","authors":"Zhi Zhang , Anning Zhou , Zhiwei Shi , Huaiqing Zhang , Xinfu He , Yongjuan Wang , Zhuangwei Bai , Dong Xi","doi":"10.1016/j.fuel.2025.135029","DOIUrl":"10.1016/j.fuel.2025.135029","url":null,"abstract":"<div><div>Elucidating the relationship between the structure of tar-rich coal and its pyrolysis products, as well as developing an accurate predictive model for these products, can effectively establish a correspondence between tar-rich coal and high-value utilization pathways. Therefore, this study systematically investigates the structural characteristics of tar-rich coals through proximate analysis, ultimate analysis, and <sup>13</sup>C NMR, and establishes the correlation between coal structure and pyrolysis products using Pearson correlation analysis. Subsequently, ridge regression is applied to construct a predictive model for pyrolysis products using the structural characteristics of tar-rich coals. The results indicate that there is a significant correlation between the pyrolysis yield, product distribution, and the functional groups of tar-rich coal structure. Specifically, tar yield is highly correlated with <em>V</em><sub>daf</sub>, terminal methyl groups, methyl groups on rings, and oxygen-attached aromatic carbon. The formation of tar components, including light oil, phenolic oil, and naphthalene oil, is influenced by aliphatic carbon, methylene, aromatic methyl, and methoxy. Additionally, the correlations between <em>M</em><sub>ad</sub>, <em>O/C</em> ratio, methyl group on rings (Ar-CH<sub>3</sub>), and fixed carbon (<em>FC</em><sub>d</sub>) are closely related to the yields of pyrolysis gas and semi-coke. Based on these correlations, a pyrolysis yield prediction model was constructed, with the R<sup>2</sup> value exceeding 0.87 and the prediction accuracy greater than 88.06%. This study provides valuable theoretical insights into the directional transformation of oils and gases during pyrolysis.</div></div>","PeriodicalId":325,"journal":{"name":"Fuel","volume":"395 ","pages":"Article 135029"},"PeriodicalIF":6.7,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-26DOI: 10.1016/j.fuel.2025.135106
Songtao Wu , Modi Guan , Xiaohan Wang , Jing Zhang , Yuhang Zhou , Xiu Huang , Bin Pan
Wettability is a pivotal parameter to determine hydrocarbon reserves and production in shale reservoirs, typically characterized quantitatively by shale-oil-brine contact angles. This parameter is a complex function of shale composition, fluid properties, temperature etc. and is therefore very difficult for conventional theoretical methods to predict accurately and efficiently.
Therefore, herein machine learning methods [eXtreme gradient boosting (XGBoost) and the Shapley additive explanations (SHAP)] were integrated to predict this parameter and analyze its sensitivity. To make up the shortage of available data in literature (only 162 data points), another 100 data points about shale/mineral-alkane-water contact angles were measured under in-situ reservoir conditions using the sessile droplet method, thus totally 262 data points were used for machine learning.
Experimental results showed that shale, quartz, mica and albite became more hydrophilic with increasing temperature from 25 ℃ to 70 ℃, while K-feldspar and dolomite demonstrated the opposite trend; shale-alkane-water contact angle increased from 60° to 149° (thus wettability shifted from water-wet to oil-wet) with increasing TOC content from 1.9 wt% to 10 wt%. The XGBoost model demonstrated superior predictive accuracy than the gradient boosting regressor and support vector machine models (e.g. R2 is 0.913, 0.876 and 0.623, respectively). The SHAP sensitivity analysis revealed that brine ionic strength, TOC content, calcite content and quartz content were the four most influential factors affecting wettability.
This work presents an efficient artificial intelligence method for shale wettability prediction, which is beneficial for hydrocarbon reserves estimation and production in shale reservoirs.
{"title":"Machine learning − based shale-alkane-brine contact angle prediction at in-situ reservoir conditions","authors":"Songtao Wu , Modi Guan , Xiaohan Wang , Jing Zhang , Yuhang Zhou , Xiu Huang , Bin Pan","doi":"10.1016/j.fuel.2025.135106","DOIUrl":"10.1016/j.fuel.2025.135106","url":null,"abstract":"<div><div>Wettability is a pivotal parameter to determine hydrocarbon reserves and production in shale reservoirs, typically characterized quantitatively by shale-oil-brine contact angles. This parameter is a complex function of shale composition, fluid properties, temperature etc. and is therefore very difficult for conventional theoretical methods to predict accurately and efficiently.</div><div>Therefore, herein machine learning methods [eXtreme gradient boosting (XGBoost) and the Shapley additive explanations (SHAP)] were integrated to predict this parameter and analyze its sensitivity. To make up the shortage of available data in literature (only 162 data points), another 100 data points about shale/mineral-alkane-water contact angles were measured under <em>in-situ</em> reservoir conditions using the sessile droplet method, thus totally 262 data points were used for machine learning.</div><div>Experimental results showed that shale, quartz, mica and albite became more hydrophilic with increasing temperature from 25 ℃ to 70 ℃, while K-feldspar and dolomite demonstrated the opposite trend; shale-alkane-water contact angle increased from 60° to 149° (thus wettability shifted from water-wet to oil-wet) with increasing TOC content from 1.9 wt% to 10 wt%. The XGBoost model demonstrated superior predictive accuracy than the gradient boosting regressor and support vector machine models (e.g. <em>R</em><sup>2</sup> is 0.913, 0.876 and 0.623, respectively). The SHAP sensitivity analysis revealed that brine ionic strength, TOC content, calcite content and quartz content were the four most influential factors affecting wettability.</div><div>This work presents an efficient artificial intelligence method for shale wettability prediction, which is beneficial for hydrocarbon reserves estimation and production in shale reservoirs.</div></div>","PeriodicalId":325,"journal":{"name":"Fuel","volume":"395 ","pages":"Article 135106"},"PeriodicalIF":6.7,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-26DOI: 10.1016/j.fuel.2025.135202
Junjian Tian , Yue Ma , Weiwei Song , Zhanshi Ni , Xiang Liu , Peng Hu , Kesheng Meng , Qizhao Lin
This study investigates the effects of various diluents and their proportions on methane-based Moderate or Intense Low-oxygen Dilution (MILD) combustion in a swirl combustion chamber. The experimental analysis focuses on the modulation of the diluent effect by equivalence ratio and thermal power. Key parameters, including temperature distribution, temperature fluctuation rates, and CO and NO emissions, are systematically examined under different operating conditions. The findings demonstrate that CO2 dilution significantly lowers the combustion temperature, enhances temperature uniformity, and minimizes NO emissions (up to 70%), but increases CO emissions. However, N2 dilution slightly increases the temperature and reduces CO emissions, with comparatively less effect on NO emissions. Furthermore, variations in equivalence ratio and thermal power have marked effects on temperature and emissions behavior. Appropriate adjustments of these parameters can optimize temperature uniformity and emissions control. This work confirms that optimized MILD combustion can be achieved in a swirl combustion chamber by using CO2 and N2 to dilute CH4, which is a critical insight for advancing the practical application of MILD combustion technology.
{"title":"Influence of N2 and CO2 dilution on methane MILD combustion: Insights into temperature distribution and emission optimization","authors":"Junjian Tian , Yue Ma , Weiwei Song , Zhanshi Ni , Xiang Liu , Peng Hu , Kesheng Meng , Qizhao Lin","doi":"10.1016/j.fuel.2025.135202","DOIUrl":"10.1016/j.fuel.2025.135202","url":null,"abstract":"<div><div>This study investigates the effects of various diluents and their proportions on methane-based Moderate or Intense Low-oxygen Dilution (MILD) combustion in a swirl combustion chamber. The experimental analysis focuses on the modulation of the diluent effect by equivalence ratio and thermal power. Key parameters, including temperature distribution, temperature fluctuation rates, and CO and NO emissions, are systematically examined under different operating conditions. The findings demonstrate that CO<sub>2</sub> dilution significantly lowers the combustion temperature, enhances temperature uniformity, and minimizes NO emissions (up to 70%), but increases CO emissions. However, N<sub>2</sub> dilution slightly increases the temperature and reduces CO emissions, with comparatively less effect on NO emissions. Furthermore, variations in equivalence ratio and thermal power have marked effects on temperature and emissions behavior. Appropriate adjustments of these parameters can optimize temperature uniformity and emissions control. This work confirms that optimized MILD combustion can be achieved in a swirl combustion chamber by using CO<sub>2</sub> and N<sub>2</sub> to dilute CH<sub>4</sub>, which is a critical insight for advancing the practical application of MILD combustion technology.</div></div>","PeriodicalId":325,"journal":{"name":"Fuel","volume":"395 ","pages":"Article 135202"},"PeriodicalIF":6.7,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-26DOI: 10.1016/j.fuel.2025.135189
Ting Wang , Chuan-Feng Yue , Jing-Bo Wang
Compared with conventional hydrocarbon fuels, hydrocarbon fuels with added energetic particles have higher calorific value and are hold potential applications in high-speed aircraft. In the present work, the ignition and combustion process of CH4 with the addition of aluminum particles are investigated using a density functional theory calculation and kinetic simulation. The geometric configuration and the energy of intermediates involved in the decomposition of methane on the Al(111) surface are analyzed and the dissociation potential energy profiles are drawn to find the optimal reaction path. Three reactions including direct dehydrogenation, O* and OH* assisted dehydrogenation are considered for CHx (x = 1–4) dehydrogenation. Stating from the initial reactants of CH4 and O2, the most preferable path for CO formation is CH4 → CH3* → CH2* → CH* → C* → CO* at 1500 K, in which C* is generated from CH* by the OH* assisted dehydrogenation. The favorable pathways for CO2 and H2O formation are CO* → COH* → OCOHcis* → CO2* and O2 → O* → OH* → H2O*. In these reaction paths, the rate-determining step is C* → CO* with the Gibbs energy barrier of 2.73 eV. The surface reaction of CH4 is seriously affected by the presence of O2 and N2 in the initial atmosphere. Based on DFT energies at 0 K, for the dissociative adsorption of O2 molecule on Al(111) surface, there is no activation energy and releases heat of 9.16 eV. The dissociative adsorption of N2 needs to overcome the energy barrier of 3.50 eV accompanied by the exothermic energy of 2.91 eV. A detailed kinetic mechanism on the methane oxidation in the presence of aluminum particle is developed accounting for surface reactions and gas interactions. Through kinetic simulation of the developed mechanism, the Al surface demonstrates the combustion-enhancing effect on CH4 combustion and this effect decreases with increasing temperature and pressure. Analyzing the gas and surface species concentrations, the dissociative reaction of O2 on Al surface is identified as the key reaction to promote CH4 ignition due to its large heat release.
{"title":"Theoretical study of the combustion kinetics and mechanism of methane on Al(111) surface","authors":"Ting Wang , Chuan-Feng Yue , Jing-Bo Wang","doi":"10.1016/j.fuel.2025.135189","DOIUrl":"10.1016/j.fuel.2025.135189","url":null,"abstract":"<div><div>Compared with conventional hydrocarbon fuels, hydrocarbon fuels with added energetic particles have higher calorific value and are hold potential applications in high-speed aircraft. In the present work, the ignition and combustion process of CH<sub>4</sub> with the addition of aluminum particles are investigated using a density functional theory calculation and kinetic simulation. The geometric configuration and the energy of intermediates involved in the decomposition of methane on the Al(111) surface are analyzed and the dissociation potential energy profiles are drawn to find the optimal reaction path. Three reactions including direct dehydrogenation, O* and OH* assisted dehydrogenation are considered for CH<em><sub>x</sub></em> (<em>x</em> = 1–4) dehydrogenation. Stating from the initial reactants of CH<sub>4</sub> and O<sub>2</sub>, the most preferable path for CO formation is CH<sub>4</sub> → CH<sub>3</sub>* → CH<sub>2</sub>* → CH* → C* → CO* at 1500 K, in which C* is generated from CH* by the OH* assisted dehydrogenation. The favorable pathways for CO<sub>2</sub> and H<sub>2</sub>O formation are CO* → COH* → OCOH<sub>cis</sub>* → CO<sub>2</sub>* and O<sub>2</sub> → O* → OH* → H<sub>2</sub>O*. In these reaction paths, the rate-determining step is C* → CO* with the Gibbs energy barrier of 2.73 eV. The surface reaction of CH<sub>4</sub> is seriously affected by the presence of O<sub>2</sub> and N<sub>2</sub> in the initial atmosphere. Based on DFT energies at 0 K, for the dissociative adsorption of O<sub>2</sub> molecule on Al(111) surface, there is no activation energy and releases heat of 9.16 eV. The dissociative adsorption of N<sub>2</sub> needs to overcome the energy barrier of 3.50 eV accompanied by the exothermic energy of 2.91 eV. A detailed kinetic mechanism on the methane oxidation in the presence of aluminum particle is developed accounting for surface reactions and gas interactions. Through kinetic simulation of the developed mechanism, the Al surface demonstrates the combustion-enhancing effect on CH<sub>4</sub> combustion and this effect decreases with increasing temperature and pressure. Analyzing the gas and surface species concentrations, the dissociative reaction of O<sub>2</sub> on Al surface is identified as the key reaction to promote CH<sub>4</sub> ignition due to its large heat release.</div></div>","PeriodicalId":325,"journal":{"name":"Fuel","volume":"395 ","pages":"Article 135189"},"PeriodicalIF":6.7,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-26DOI: 10.1016/j.fuel.2025.135167
Patrick Frisinghelli , Angelika Zachl , Markus Buchmayr , Johann Gruber , Andrés Anca–Couce , Robert Scharler , Christoph Hochenauer
Small-scale gasification of biomass combined with a gas engine and a generator (combined heat and power CHP) is an important technology, as it is one of the best ways to replace fossil fuels in electricity and heat generation. Small-scale gasification plants generally have strict fuel property requirements, which makes them economically unattractive.
In particular, the water content of the fuel is crucially important, as commercial plants usually only allow a water content of up to 15 m%. In this study, a simple approach was taken to extend the operational limit of a stratified downdraft gasifier by extending the reactor height. In turn, this extends the permissible range of fuel water content. In the experimental part of this study, the reactor with and without a reactor extension was fed with fuel with different water contents (8–24 m%). During operation, the bed temperatures are measured as a function of the reactor height. In addition, permanent gases (CO, CO2, H2, CH4) were measured, and an online tar measurement was ensured. An optimal temperature profile in the gasifier and extremely low tar values in the product gas were determined for all fuel water contents investigated.
By taking this simple approach, the operating limits for the permissible water content of the fuel could be extended from 15 m% to 22 m%, allowing cheaper fuel to be used without significantly reducing the gas quality. These results will help to make small-scale biomass gasification more attractive and economical.
{"title":"Extending the operational limit for fuel water content in a stratified downdraft gasifier from 15 to 22 m% by increasing the reactor height","authors":"Patrick Frisinghelli , Angelika Zachl , Markus Buchmayr , Johann Gruber , Andrés Anca–Couce , Robert Scharler , Christoph Hochenauer","doi":"10.1016/j.fuel.2025.135167","DOIUrl":"10.1016/j.fuel.2025.135167","url":null,"abstract":"<div><div>Small-scale gasification of biomass combined with a gas engine and a generator (combined heat and power CHP) is an important technology, as it is one of the best ways to replace fossil fuels in electricity and heat generation. Small-scale gasification plants generally have strict fuel property requirements, which makes them economically unattractive.</div><div>In particular, the water content of the fuel is crucially important, as commercial plants usually only allow a water content of up to 15 m%. In this study, a simple approach was taken to extend the operational limit of a stratified downdraft gasifier by extending the reactor height. In turn, this extends the permissible range of fuel water content. In the experimental part of this study, the reactor with and without a reactor extension was fed with fuel with different water contents (8–24 m%). During operation, the bed temperatures are measured as a function of the reactor height. In addition, permanent gases (CO, CO<sub>2</sub>, H<sub>2</sub>, CH<sub>4</sub>) were measured, and an online tar measurement was ensured. An optimal temperature profile in the gasifier and extremely low tar values in the product gas were determined for all fuel water contents investigated.</div><div>By taking this simple approach, the operating limits for the permissible water content of the fuel could be extended from 15 m% to 22 m%, allowing cheaper fuel to be used without significantly reducing the gas quality. These results will help to make small-scale biomass gasification more attractive and economical.</div></div>","PeriodicalId":325,"journal":{"name":"Fuel","volume":"395 ","pages":"Article 135167"},"PeriodicalIF":6.7,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143698040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-26DOI: 10.1016/j.fuel.2025.134853
Wendell de Queiróz Lamas
Algae have gained significant attention as a sustainable bio-mass source for bio-fuel production due to their rapid growth rate and high lipid content. The increasing demand for renewable energy sources highlights the need for accurate predictive models to optimise bio-fuel production. This study hypothesises that artificial neural networks (ANNs) outperform multiple linear regression (MLR) in predicting the lower heating value (LHV) and gas yields of algae bio-mass. The methodology integrates elemental analysis with statistical and machine learning models to estimate LHV and gas yields, comparing the performance of ANN and MLR. Results indicate that ANN models provide higher predictive accuracy, capturing complex non-linear relationships, with an LHV prediction of 20.31 MJ/kg compared to 19.55 MJ/kg from MLR. These findings suggest that ANN models offer greater reliability in energy prediction, though at a higher computational cost. It is concluded that while ANN provides superior accuracy, MLR remains useful for simpler applications due to its efficiency and interpretability.
{"title":"Algae’s potential as a bio-mass source for bio-fuel production: MLR vs. ANN models analyses","authors":"Wendell de Queiróz Lamas","doi":"10.1016/j.fuel.2025.134853","DOIUrl":"10.1016/j.fuel.2025.134853","url":null,"abstract":"<div><div>Algae have gained significant attention as a sustainable bio-mass source for bio-fuel production due to their rapid growth rate and high lipid content. The increasing demand for renewable energy sources highlights the need for accurate predictive models to optimise bio-fuel production. This study hypothesises that artificial neural networks (ANNs) outperform multiple linear regression (MLR) in predicting the lower heating value (LHV) and gas yields of algae bio-mass. The methodology integrates elemental analysis with statistical and machine learning models to estimate LHV and gas yields, comparing the performance of ANN and MLR. Results indicate that ANN models provide higher predictive accuracy, capturing complex non-linear relationships, with an LHV prediction of 20.31 MJ/kg compared to 19.55 MJ/kg from MLR. These findings suggest that ANN models offer greater reliability in energy prediction, though at a higher computational cost. It is concluded that while ANN provides superior accuracy, MLR remains useful for simpler applications due to its efficiency and interpretability.</div></div>","PeriodicalId":325,"journal":{"name":"Fuel","volume":"395 ","pages":"Article 134853"},"PeriodicalIF":6.7,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-26DOI: 10.1016/j.fuel.2025.135197
Peitao Shi , Jixiong Zhang , Baiyi Li , Hao Yan , Yuyang Xia
Carbon sequestration in deep, unexploitable coal seams is an effective method for carbon emission reduction. However, the impact of CO2 on coal’s mechanical properties is critical for the stability of coal bed carbon sequestration. This study examines the effects of moisture content, saturation medium, saturation pressure, and saturation time on the mechanical properties of coal through saturation experiments. The mechanisms by which the coal matrix is weakened by CO2 and water are revealed. Furthermore, to assess the impact of high-dimensional factors on mechanical properties, an ensemble perturbation model (EP-SVR) is developed to evaluate the mechanical properties of coal after carbon sequestration. The study also investigates the impact of iterations and perturbation level on the performance of EP-SVR. The model systematically evaluated the effects of eight factors, including coal rank, sample size, moisture content, saturation medium, saturation time, saturation pressure, saturation temperature, and test loading rate, on the mechanical performance. The results indicate that CO2 saturation in multiple phases weakens the mechanical properties of coal. The weakening mechanisms include the expansion of the coal matrix, erosion of organic and mineral components, an increase in porosity, and the formation of micro-cracks. This model can adaptively assess the changes in the mechanical properties of CO2-saturated coal at different stages. Compared with other models, the EP-SVR has the advantage of higher tolerance to adversarial data by dynamically training a new adaptive decision function through an iterative process, thus enhancing the model’s robustness to diverse data. This study provides insights into the safety prediction of coal carbon sequestration.
{"title":"Mechanical property weakening mechanisms and ensemble assessment during coalbed carbon sequestration","authors":"Peitao Shi , Jixiong Zhang , Baiyi Li , Hao Yan , Yuyang Xia","doi":"10.1016/j.fuel.2025.135197","DOIUrl":"10.1016/j.fuel.2025.135197","url":null,"abstract":"<div><div>Carbon sequestration in deep, unexploitable coal seams is an effective method for carbon emission reduction. However, the impact of CO<sub>2</sub> on coal’s mechanical properties is critical for the stability of coal bed carbon sequestration. This study examines the effects of moisture content, saturation medium, saturation pressure, and saturation time on the mechanical properties of coal through saturation experiments. The mechanisms by which the coal matrix is weakened by CO<sub>2</sub> and water are revealed. Furthermore, to assess the impact of high-dimensional factors on mechanical properties, an ensemble perturbation model (EP-SVR) is developed to evaluate the mechanical properties of coal after carbon sequestration. The study also investigates the impact of iterations and perturbation level on the performance of EP-SVR. The model systematically evaluated the effects of eight factors, including coal rank, sample size, moisture content, saturation medium, saturation time, saturation pressure, saturation temperature, and test loading rate, on the mechanical performance. The results indicate that CO<sub>2</sub> saturation in multiple phases weakens the mechanical properties of coal. The weakening mechanisms include the expansion of the coal matrix, erosion of organic and mineral components, an increase in porosity, and the formation of micro-cracks. This model can adaptively assess the changes in the mechanical properties of CO<sub>2</sub>-saturated coal at different stages. Compared with other models, the EP-SVR has the advantage of higher tolerance to adversarial data by dynamically training a new adaptive decision function through an iterative process, thus enhancing the model’s robustness to diverse data. This study provides insights into the safety prediction of coal carbon sequestration.</div></div>","PeriodicalId":325,"journal":{"name":"Fuel","volume":"395 ","pages":"Article 135197"},"PeriodicalIF":6.7,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Low emissions and fuel flexibility are two important criteria required for gas turbine combustors to facilitate the energy transition to low-carbon fuels for propulsion and power applications. A jet-stabilized combustor, having both these characteristics, was operated with CH4–H2 fuel mixtures with H2 varying from 0 to 100 % and with varying equivalence ratios (). Comprehensive measurements were carried out of the velocity field using Particle Image Velocimetry (PIV), temperature and gas composition by traversing probes in the chamber, and flame topology using chemiluminescence imaging. The flow field in this combustor consists of a jet that undergoes recirculation, generating Central and Peripheral Recirculation Zones (CRZ and PRZ). The recirculation ratio in the PRZ is found to be twice that of the CRZ. Increasing H2 % for the same leads to higher NOx. Ultra-low flames could be stabilized only at H50 %, which in turn leads to low NOx due to low adiabatic flame temperatures. The combination of temperature, gas composition (CO/NO), and chemiluminescence images is used to identify the extent and location of the reaction zone. Distributed reaction zones, stabilizing at around 30 % of the length of the chamber, are achieved at lean conditions, whereas an increase in H2 % makes the reaction zone more compact and shifts upstream towards the burner head. Flame kernels are extracted from the instantaneous chemiluminescence images, and probability distribution functions for their aspect ratio and axial location are constructed. It is seen that reducing leads to low aspect ratio kernels that tend to occur further downstream, whereas increasing H2 % leads to higher aspect ratio kernels, stabilizing upstream. These flame kernel statistics are also used to identify ignition modes (autoignition/flame propagation) for varying fuel H2 % and inlet based on a hypothesis of flame stabilization mechanisms.
{"title":"Stabilization and emissions characteristics of CH4–H2 blends in a premixed jet stabilized combustor","authors":"Rishikesh Sampat, Niek Goselink, Kaushal Dave, Ferry Schrijer, Arvind Gangoli Rao","doi":"10.1016/j.fuel.2025.135059","DOIUrl":"10.1016/j.fuel.2025.135059","url":null,"abstract":"<div><div>Low emissions and fuel flexibility are two important criteria required for gas turbine combustors to facilitate the energy transition to low-carbon fuels for propulsion and power applications. A jet-stabilized combustor, having both these characteristics, was operated with CH<sub>4</sub>–H<sub>2</sub> fuel mixtures with H<sub>2</sub> varying from 0 to 100 % and with varying equivalence ratios (<span><math><mi>ϕ</mi></math></span>). Comprehensive measurements were carried out of the velocity field using Particle Image Velocimetry (PIV), temperature and gas composition by traversing probes in the chamber, and flame topology using chemiluminescence imaging. The flow field in this combustor consists of a jet that undergoes recirculation, generating Central and Peripheral Recirculation Zones (CRZ and PRZ). The recirculation ratio in the PRZ is found to be twice that of the CRZ. Increasing H<sub>2</sub> % for the same <span><math><mi>ϕ</mi></math></span> leads to higher NO<sub><em>x</em></sub>. Ultra-low <span><math><mi>ϕ</mi></math></span> flames could be stabilized only at H<span><math><msub><mspace></mspace><mn>2</mn></msub><mo>≥</mo></math></span>50 %, which in turn leads to low NO<sub><em>x</em></sub> due to low adiabatic flame temperatures. The combination of temperature, gas composition (CO/NO), and chemiluminescence images is used to identify the extent and location of the reaction zone. Distributed reaction zones, stabilizing at around 30 % of the length of the chamber, are achieved at lean conditions, whereas an increase in H<sub>2</sub> % makes the reaction zone more compact and shifts upstream towards the burner head. Flame kernels are extracted from the instantaneous chemiluminescence images, and probability distribution functions for their aspect ratio and axial location are constructed. It is seen that reducing <span><math><mi>ϕ</mi></math></span> leads to low aspect ratio kernels that tend to occur further downstream, whereas increasing H<sub>2</sub> % leads to higher aspect ratio kernels, stabilizing upstream. These flame kernel statistics are also used to identify ignition modes (autoignition/flame propagation) for varying fuel H<sub>2</sub> % and inlet <span><math><mi>ϕ</mi></math></span> based on a hypothesis of flame stabilization mechanisms.</div></div>","PeriodicalId":325,"journal":{"name":"Fuel","volume":"395 ","pages":"Article 135059"},"PeriodicalIF":6.7,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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