Amanda Rempel da Silva, Gean Carlos França, J. C. Ordonez, Crístofer H. Marques
The International Maritime Organization has expressed its concern about the pollution caused by ships by putting in place regulations to decrease greenhouse gas emissions. As a result, ships must evermore be fitted with efficient and environmentally friendly engines, and one of the most essential selection parameters to consider is the specific fuel consumption. This parameter can be obtained by means of simulation models with various levels of sophistication, which can be either coded in basic programming languages or run in dedicated packages. The aim of the present study is to conceive a facilitated model to calculate the specific fuel consumption of low-speed dual-fuel engines with low-pressure gas injection driving either fixed or controllable pitch propellers. Clear specific fuel consumption trends were revealed when a normalization process was employed and then polynomials were obtained by numerical regression. This model requires very limited input data to predict the specific fuel consumption of an engine at any contractual maximum continuous rating, including part load operation. Results showed very close qualitative behavior and the highest deviations occurred for the brake-specific pilot consumption, peaking at about 5%. At last, the developed approach was concluded to be an easy-to-implement and fast-to-run model with promising usage for optimization studies.
{"title":"FUEL CONSUMPTION PREDICTION IN DUAL-FUEL LOW-SPEED MARINE ENGINES WITH LOW-PRESSURE GAS INJECTION","authors":"Amanda Rempel da Silva, Gean Carlos França, J. C. Ordonez, Crístofer H. Marques","doi":"10.1115/1.4066058","DOIUrl":"https://doi.org/10.1115/1.4066058","url":null,"abstract":"\u0000 The International Maritime Organization has expressed its concern about the pollution caused by ships by putting in place regulations to decrease greenhouse gas emissions. As a result, ships must evermore be fitted with efficient and environmentally friendly engines, and one of the most essential selection parameters to consider is the specific fuel consumption. This parameter can be obtained by means of simulation models with various levels of sophistication, which can be either coded in basic programming languages or run in dedicated packages. The aim of the present study is to conceive a facilitated model to calculate the specific fuel consumption of low-speed dual-fuel engines with low-pressure gas injection driving either fixed or controllable pitch propellers. Clear specific fuel consumption trends were revealed when a normalization process was employed and then polynomials were obtained by numerical regression. This model requires very limited input data to predict the specific fuel consumption of an engine at any contractual maximum continuous rating, including part load operation. Results showed very close qualitative behavior and the highest deviations occurred for the brake-specific pilot consumption, peaking at about 5%. At last, the developed approach was concluded to be an easy-to-implement and fast-to-run model with promising usage for optimization studies.","PeriodicalId":509700,"journal":{"name":"Journal of Energy Resources Technology","volume":"119 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141801913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thomas Russell, Cuong Nguyen, Grace Loi, S. R. Mohd Shafian, N. N. Zulkifli, A. Zeinijahromi, P. Bedrikovetsky
Formation damage due to fines migration after water breakthrough during oil and gas production results in significant well productivity decline. A recent study derived an analytical model for fines migration during commingled water-oil production in homogeneous reservoirs. Yet, reservoir heterogeneity highly affects well productivity. This paper develops an analytical model for layer-cake reservoirs. We develop a novel methodology of characterising productivity decline by the function of impedance versus water-cut, two quantities that are commonly measured throughout the production life of the well. The methodology is based on a new analytical model for inflow performance in layer-cake reservoirs under fines migration. The new model integrates pseudo phase-permeability functions for water-oil flow with equations for fines release and induced permeability damage. The analytical model reveals linear well impedance growth versus water-cut increase, where the slope is determined by a modified form of the mobility ratio which includes the extent of formation damage. This linear form is shown to arise when the formation damage factor is constant, regardless of the reservoir permeability distribution. The model is validated by comparison with production histories of five wells from three fields, which exhibit good agreement with the linear trend predicted by the new model. The explicit formulae allow for prediction of productivity at abandonment, determining the optimal well stimulation time, as well as reconstructing skin values during the early stages of production to better estimate the influences of other formation damage factors, like those induced during drilling and completion.
{"title":"Effects of fines migration and reservoir heterogeneity on well productivity: analytical model and field cases","authors":"Thomas Russell, Cuong Nguyen, Grace Loi, S. R. Mohd Shafian, N. N. Zulkifli, A. Zeinijahromi, P. Bedrikovetsky","doi":"10.1115/1.4066057","DOIUrl":"https://doi.org/10.1115/1.4066057","url":null,"abstract":"\u0000 Formation damage due to fines migration after water breakthrough during oil and gas production results in significant well productivity decline. A recent study derived an analytical model for fines migration during commingled water-oil production in homogeneous reservoirs. Yet, reservoir heterogeneity highly affects well productivity. This paper develops an analytical model for layer-cake reservoirs. We develop a novel methodology of characterising productivity decline by the function of impedance versus water-cut, two quantities that are commonly measured throughout the production life of the well. The methodology is based on a new analytical model for inflow performance in layer-cake reservoirs under fines migration. The new model integrates pseudo phase-permeability functions for water-oil flow with equations for fines release and induced permeability damage. The analytical model reveals linear well impedance growth versus water-cut increase, where the slope is determined by a modified form of the mobility ratio which includes the extent of formation damage. This linear form is shown to arise when the formation damage factor is constant, regardless of the reservoir permeability distribution. The model is validated by comparison with production histories of five wells from three fields, which exhibit good agreement with the linear trend predicted by the new model. The explicit formulae allow for prediction of productivity at abandonment, determining the optimal well stimulation time, as well as reconstructing skin values during the early stages of production to better estimate the influences of other formation damage factors, like those induced during drilling and completion.","PeriodicalId":509700,"journal":{"name":"Journal of Energy Resources Technology","volume":"30 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141799395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Artificial intelligence (AI) can help improve many areas of waste management and biogas generation. The world has reached a state where waste generation is increasing daily, while an effective waste management system is essential for the sustainable development of a country. AI could be of great use in optimizing the waste management scheme by technical differentiation of all sorts and recycling techniques. AI can contribute to the improvement of waste segmentation, recycling, and disposal. Thus, by assessing availability and composition, AI can easily contribute to the selection of the most suitable feedstock for biogas generation. This paper will discuss the optimization of gasifier design, an important part of biogas production, to enhance gasification efficiency for more efficient syngas production. Several gains accrue from AI applications, and among them is the selection of feedstocks and gasifiers optimal for more efficient and sustainable waste management and use in the production of biogas systems. This review paper identifies the potential application areas in either waste management practices or biogas production and puts forward ways in which AI can be used in these areas.
{"title":"Downdraft Gasification for Biogas Production: The Role of Artificial Intelligence","authors":"Vandana Sharma, Kamal Upreti, Arul Kumar Natarajan, Nishi Jain, Sanjay Kumar, Anant Rajee Bara, Sushma Kumari","doi":"10.1115/1.4066059","DOIUrl":"https://doi.org/10.1115/1.4066059","url":null,"abstract":"\u0000 Artificial intelligence (AI) can help improve many areas of waste management and biogas generation. The world has reached a state where waste generation is increasing daily, while an effective waste management system is essential for the sustainable development of a country. AI could be of great use in optimizing the waste management scheme by technical differentiation of all sorts and recycling techniques. AI can contribute to the improvement of waste segmentation, recycling, and disposal. Thus, by assessing availability and composition, AI can easily contribute to the selection of the most suitable feedstock for biogas generation. This paper will discuss the optimization of gasifier design, an important part of biogas production, to enhance gasification efficiency for more efficient syngas production. Several gains accrue from AI applications, and among them is the selection of feedstocks and gasifiers optimal for more efficient and sustainable waste management and use in the production of biogas systems. This review paper identifies the potential application areas in either waste management practices or biogas production and puts forward ways in which AI can be used in these areas.","PeriodicalId":509700,"journal":{"name":"Journal of Energy Resources Technology","volume":"45 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141800034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Juncheng Pan, Qi Zhang, Lang Ding, Dongmei Huang, Le Wu, Mingjing Lu
To ensure the economic feasibility of shale oil and gas exploitation, large-scale hydraulic fracturing is essential for increasing recovery volumes by creating more efficient conductivity channels. However, China's continental shale reservoirs present complex geological conditions, making optimization through traditional hydraulic fracturing challenging. Thus, substituting CO2 for water in fracturing fluids to enhance shale reservoirs has garnered significant interest. An orthogonal experimental design was implemented to identify the optimal parameters for CO2 composite fracturing. Analysis of single-factor experiments led to the selection of four key variables: slickwater volume, slickwater displacement, preflush liquid CO2 volume, and proppant addition volume, resulting in 16 experimental configurations. Using numerical simulation of tight oil shale reservoirs, the effective stimulated reservoir volume for each parameter combination was calculated. Variance analysis revealed that increased slickwater volume significantly enhances fracture initiation and propagation. While variations in slickwater displacement and preflush liquid CO2 volume influence fracture network morphology and complexity, they have a lesser effect on the stimulated volume compared to slickwater volume. Proppant quantity primarily affects fracture conductivity with minimal impact on stimulated volume. This research underpins the optimization of Constructional parameters for CO2 composite fracturing.
{"title":"Construction Parameters Optimization of CO2 Composite Fracturing for Horizontal Shale Wells","authors":"Juncheng Pan, Qi Zhang, Lang Ding, Dongmei Huang, Le Wu, Mingjing Lu","doi":"10.1115/1.4066016","DOIUrl":"https://doi.org/10.1115/1.4066016","url":null,"abstract":"\u0000 To ensure the economic feasibility of shale oil and gas exploitation, large-scale hydraulic fracturing is essential for increasing recovery volumes by creating more efficient conductivity channels. However, China's continental shale reservoirs present complex geological conditions, making optimization through traditional hydraulic fracturing challenging. Thus, substituting CO2 for water in fracturing fluids to enhance shale reservoirs has garnered significant interest. An orthogonal experimental design was implemented to identify the optimal parameters for CO2 composite fracturing. Analysis of single-factor experiments led to the selection of four key variables: slickwater volume, slickwater displacement, preflush liquid CO2 volume, and proppant addition volume, resulting in 16 experimental configurations. Using numerical simulation of tight oil shale reservoirs, the effective stimulated reservoir volume for each parameter combination was calculated. Variance analysis revealed that increased slickwater volume significantly enhances fracture initiation and propagation. While variations in slickwater displacement and preflush liquid CO2 volume influence fracture network morphology and complexity, they have a lesser effect on the stimulated volume compared to slickwater volume. Proppant quantity primarily affects fracture conductivity with minimal impact on stimulated volume. This research underpins the optimization of Constructional parameters for CO2 composite fracturing.","PeriodicalId":509700,"journal":{"name":"Journal of Energy Resources Technology","volume":" July","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141823886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The rate of penetration (ROP) is crucial for efficient and cost-effective oil well drilling. This study introduces a novel prediction method for rate of penetration that pioneers the use of different types of drill bits and lithologies with traditional drilling parameters. Utilizing a comprehensive dataset from 12 diverse wells, it employs advanced machine learning techniques including an adaptive moment estimation based artificial neural network for developing the algorithm. By integrating various controllable and uncontrollable drilling parameters, the random forest, decision tree and K-nearest neighbor models demonstrated superior performance. These models achieved a coefficient of determination of approximately 98% and a mean absolute percentage error of only 3.30%, outperforming traditional models such as Maurer and Bingham, as well as other machine learning models. Using 500 testing and 2,000 training data points from real-time measurements reduced the risk of overfitting and enhanced model effectiveness in different drilling environments. The predictions of the developed model can modify the input parameters to increase rate of penetration through various formations. This study highlights the importance of lithology and utilizes feature ablation analysis to transition from black-to-white box model. Additionally, based on the predictions of this work, post-drilling analysis can reduce costs and time by only requiring surface-measured parameters and eliminates the need for extensive study on geological, laboratory and drilling data prior to drilling activities. This integrated approach sets new standards for machine learning in drilling, representing a robust and adaptive strategy to enhance operational efficiency.
{"title":"Transforming Oil Well Drilling: Prediction of Real-Time Rate of Penetration with Novel Machine Learning Approach in Varied Lithological Formations","authors":"Raunak Gupta, Uttam K. Bhui","doi":"10.1115/1.4066015","DOIUrl":"https://doi.org/10.1115/1.4066015","url":null,"abstract":"\u0000 The rate of penetration (ROP) is crucial for efficient and cost-effective oil well drilling. This study introduces a novel prediction method for rate of penetration that pioneers the use of different types of drill bits and lithologies with traditional drilling parameters. Utilizing a comprehensive dataset from 12 diverse wells, it employs advanced machine learning techniques including an adaptive moment estimation based artificial neural network for developing the algorithm. By integrating various controllable and uncontrollable drilling parameters, the random forest, decision tree and K-nearest neighbor models demonstrated superior performance. These models achieved a coefficient of determination of approximately 98% and a mean absolute percentage error of only 3.30%, outperforming traditional models such as Maurer and Bingham, as well as other machine learning models. Using 500 testing and 2,000 training data points from real-time measurements reduced the risk of overfitting and enhanced model effectiveness in different drilling environments. The predictions of the developed model can modify the input parameters to increase rate of penetration through various formations. This study highlights the importance of lithology and utilizes feature ablation analysis to transition from black-to-white box model. Additionally, based on the predictions of this work, post-drilling analysis can reduce costs and time by only requiring surface-measured parameters and eliminates the need for extensive study on geological, laboratory and drilling data prior to drilling activities. This integrated approach sets new standards for machine learning in drilling, representing a robust and adaptive strategy to enhance operational efficiency.","PeriodicalId":509700,"journal":{"name":"Journal of Energy Resources Technology","volume":" 1137","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141823155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohamed Maache, Cheikh Kada, Ryoichi S. Amano, Hiroyuki Kumano, Osama M. Selim, Kada Kada
Horse manure is one of the highest potential biowastes for heat and power generation. This paper investigates the experimental and mathematical modeling of thermochemical conversion for horse manure. As one type of thermochemical conversions, the pyrolysis process was carried out at eight different heating rates on horse manure using three parameters: The extent of reaction, the rate change of the extent of reaction and Differential Thermal Analysis (DTA), all used to determine kinetic data that will be validated with a mathematical model. Slow pyrolysis: below 15 °C/min showed optimistic results of obtaining exothermic reaction over a wide range of temperature which makes it self-sustainable with steady heat generation. Also, low heating rates allowed a quasi-equilibrium state through slow heating with a minimum delay in response for any transient error that could be generated from Differential Thermogravimetry (DTG) device.
{"title":"Experimental and Mathematical Investigation of Thermochemical Conversion for Horse Manure","authors":"Mohamed Maache, Cheikh Kada, Ryoichi S. Amano, Hiroyuki Kumano, Osama M. Selim, Kada Kada","doi":"10.1115/1.4065956","DOIUrl":"https://doi.org/10.1115/1.4065956","url":null,"abstract":"\u0000 Horse manure is one of the highest potential biowastes for heat and power generation. This paper investigates the experimental and mathematical modeling of thermochemical conversion for horse manure. As one type of thermochemical conversions, the pyrolysis process was carried out at eight different heating rates on horse manure using three parameters: The extent of reaction, the rate change of the extent of reaction and Differential Thermal Analysis (DTA), all used to determine kinetic data that will be validated with a mathematical model. Slow pyrolysis: below 15 °C/min showed optimistic results of obtaining exothermic reaction over a wide range of temperature which makes it self-sustainable with steady heat generation. Also, low heating rates allowed a quasi-equilibrium state through slow heating with a minimum delay in response for any transient error that could be generated from Differential Thermogravimetry (DTG) device.","PeriodicalId":509700,"journal":{"name":"Journal of Energy Resources Technology","volume":"3 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141646447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohamed Abousabae, Areej Khalil, Saif Al Hamad, Ryoichi S. Amano
Despite the aluminized propellants offering a high specific impulse, the challenge of nozzle erosion adversely impacts the rocket's performance and its potential for reusability. This study presents a numerical model aiming to predict the mechanical erosion of the propulsion chamber nozzle. The model employs an Eulerian/Lagrangian approach to simulate the complexity of the flow field within the rocket combustion chamber and the interactions between the continuous phase and particles. The model also includes a simplified representation of the aluminum particle combustion process, besides the consideration of secondary breakup phenomena in liquid droplets. Experimental and numerical data from the literature were used to validate the numerical model. Subsequently, the model was utilized to explore the impacts of increasing propellant aluminum content and varying particles' injection velocities on the nozzle mechanical erosion. The outcomes indicated that higher aluminum content leads to a 4-10% increase in nozzle erosion compared to the 15% content case. Furthermore, the aluminum particles tend not to fully burn within the combustion chamber and contribute to nozzle erosion. Lastly, particles with higher initial velocity at the inlet of the combustion chamber increase the nozzle mechanical erosion despite the observed decrease in incident mass flux.
{"title":"Influence of Aluminum Content and Agglomerates Initial Velocity on Erosion in Solid Rocket Motor","authors":"Mohamed Abousabae, Areej Khalil, Saif Al Hamad, Ryoichi S. Amano","doi":"10.1115/1.4065955","DOIUrl":"https://doi.org/10.1115/1.4065955","url":null,"abstract":"\u0000 Despite the aluminized propellants offering a high specific impulse, the challenge of nozzle erosion adversely impacts the rocket's performance and its potential for reusability. This study presents a numerical model aiming to predict the mechanical erosion of the propulsion chamber nozzle. The model employs an Eulerian/Lagrangian approach to simulate the complexity of the flow field within the rocket combustion chamber and the interactions between the continuous phase and particles. The model also includes a simplified representation of the aluminum particle combustion process, besides the consideration of secondary breakup phenomena in liquid droplets. Experimental and numerical data from the literature were used to validate the numerical model. Subsequently, the model was utilized to explore the impacts of increasing propellant aluminum content and varying particles' injection velocities on the nozzle mechanical erosion. The outcomes indicated that higher aluminum content leads to a 4-10% increase in nozzle erosion compared to the 15% content case. Furthermore, the aluminum particles tend not to fully burn within the combustion chamber and contribute to nozzle erosion. Lastly, particles with higher initial velocity at the inlet of the combustion chamber increase the nozzle mechanical erosion despite the observed decrease in incident mass flux.","PeriodicalId":509700,"journal":{"name":"Journal of Energy Resources Technology","volume":"17 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141649452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The vertical-axis Savonius wind rotor is known for its design simplicity, better starting qualities, and direction independency despite its inferior efficiency when measured against certain other types of vertical-axis wind rotors. Despite a plethora of research work on Savonius rotors, an in-depth analysis of Reynolds number (Re) on aerodynamic and power coefficients of the Savonius rotors is scarce. This paper aims at understanding the influence of Re on the performance of a novel parabolic blade profile through unsteady two-dimensional (2D) computation. The Reynolds-averaged Navier Stokes (RANS) equations are modelled using the ANSYS-Fluent by adopting shear stress transport (SST) k-ω turbulence model. The computational results of the novel blade profile are then compared and analysed with an established semicircular blade profile to draw some meaningful insights into the aerodynamic performance. In the tested range of Re = 5.3 × 104 − 10.6 × 104, the novel parabolic blade profile outperformed the semicircular blade profile in terms of aerodynamic and performance coefficients.
{"title":"Influence of Reynolds Number on Aerodynamic and Performance Coefficients of a Novel Parabolic-Bladed Savonius Wind Rotor","authors":"Man Mohan, Parag K Talukdar, U. Saha","doi":"10.1115/1.4065954","DOIUrl":"https://doi.org/10.1115/1.4065954","url":null,"abstract":"\u0000 The vertical-axis Savonius wind rotor is known for its design simplicity, better starting qualities, and direction independency despite its inferior efficiency when measured against certain other types of vertical-axis wind rotors. Despite a plethora of research work on Savonius rotors, an in-depth analysis of Reynolds number (Re) on aerodynamic and power coefficients of the Savonius rotors is scarce. This paper aims at understanding the influence of Re on the performance of a novel parabolic blade profile through unsteady two-dimensional (2D) computation. The Reynolds-averaged Navier Stokes (RANS) equations are modelled using the ANSYS-Fluent by adopting shear stress transport (SST) k-ω turbulence model. The computational results of the novel blade profile are then compared and analysed with an established semicircular blade profile to draw some meaningful insights into the aerodynamic performance. In the tested range of Re = 5.3 × 104 − 10.6 × 104, the novel parabolic blade profile outperformed the semicircular blade profile in terms of aerodynamic and performance coefficients.","PeriodicalId":509700,"journal":{"name":"Journal of Energy Resources Technology","volume":"38 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141644909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shuo Zhang, Xinghan Suo, Leilei Liu, Lin Wang, Hongqing Feng, Changhui Wang
In this paper, the detailed mechanism of isopentanol was simplified by DRGEP, generation rate analysis, reaction path optimisation and sensitivity analysis, and a comprehensive simplified mechanism of isopentanol/gasoline alternative fuels was obtained. isopentanol/gasoline characterised fuels with different blending ratios were investigated, and the results showed that blending of isopentanol promoted the autoignition of gasoline. It was found that blending isopentanol does not significantly affect the low-temperature reaction path of alkanes, but increases the reaction path flux from toluene to benzene. During combustion of isopentanol/gasoline alternative fuels, the isopentanol component exhibits a unique two-stage combustion phenomenon.
{"title":"Study on Chemical Kinetic Mechanism and Autoignition Characteristics of Isopentanol/Gasoline Surrogate Fuel","authors":"Shuo Zhang, Xinghan Suo, Leilei Liu, Lin Wang, Hongqing Feng, Changhui Wang","doi":"10.1115/1.4065950","DOIUrl":"https://doi.org/10.1115/1.4065950","url":null,"abstract":"\u0000 In this paper, the detailed mechanism of isopentanol was simplified by DRGEP, generation rate analysis, reaction path optimisation and sensitivity analysis, and a comprehensive simplified mechanism of isopentanol/gasoline alternative fuels was obtained. isopentanol/gasoline characterised fuels with different blending ratios were investigated, and the results showed that blending of isopentanol promoted the autoignition of gasoline. It was found that blending isopentanol does not significantly affect the low-temperature reaction path of alkanes, but increases the reaction path flux from toluene to benzene. During combustion of isopentanol/gasoline alternative fuels, the isopentanol component exhibits a unique two-stage combustion phenomenon.","PeriodicalId":509700,"journal":{"name":"Journal of Energy Resources Technology","volume":"10 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141648391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhizhen Zhang, Xin Zheng, Haiming Yang, Xuan Chen, Peng Chen
The transformer is the key oil-filled equipment in the power system, and its fire behavior seriously affects the safe operation of the power grid. In this paper, in order to analyze the fire development process and combustion behavior of oil-filled equipment, a mesoscale model of transformer equipment was constructed, and fire simulation experiments of transformer equipment under the action of external ignition sources were conducted. The flame temperature, flame height, heat release rate, oil temperature, and pressure were measured. The experimental results show that the oil-filled equipment fire presents the characteristics of nonlinear development. The fire can be divided into three stages: ignition stage, stable growth stage, and combustion mutation stage. The transformer oil near the wall is pyrolyzed by the external heat source, and the combustible gas and transformer oil form a gas-liquid two-phase flow, which is the main reason for the nonlinear development of oil-filled equipment fire. The experimental results are of great significance for the safe operation and fire control of power system oil-filled equipment.
{"title":"Experimental study on nonlinear development process of oil-filled equipment fire under external fire source","authors":"Zhizhen Zhang, Xin Zheng, Haiming Yang, Xuan Chen, Peng Chen","doi":"10.1115/1.4065949","DOIUrl":"https://doi.org/10.1115/1.4065949","url":null,"abstract":"\u0000 The transformer is the key oil-filled equipment in the power system, and its fire behavior seriously affects the safe operation of the power grid. In this paper, in order to analyze the fire development process and combustion behavior of oil-filled equipment, a mesoscale model of transformer equipment was constructed, and fire simulation experiments of transformer equipment under the action of external ignition sources were conducted. The flame temperature, flame height, heat release rate, oil temperature, and pressure were measured. The experimental results show that the oil-filled equipment fire presents the characteristics of nonlinear development. The fire can be divided into three stages: ignition stage, stable growth stage, and combustion mutation stage. The transformer oil near the wall is pyrolyzed by the external heat source, and the combustible gas and transformer oil form a gas-liquid two-phase flow, which is the main reason for the nonlinear development of oil-filled equipment fire. The experimental results are of great significance for the safe operation and fire control of power system oil-filled equipment.","PeriodicalId":509700,"journal":{"name":"Journal of Energy Resources Technology","volume":"5 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141648717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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