Hydroconversion of coal tar to produce aromatic hydrocarbons(BTX)represents a crucial strategy for the highvalue hierarchical utilization of coal.This study focused on the hydrocracking of hydrorefined products derive...Hydroconversion of coal tar to produce aromatic hydrocarbons(BTX)represents a crucial strategy for the highvalue hierarchical utilization of coal.This study focused on the hydrocracking of hydrorefined products derived from coal tar to enhance the production of benzene,toluene,and xylene(BTX).Various reaction conditions,including reaction temperature,hydrogen pressure,space velocity,and hydrogen-to-oil volume ratio,were systematically explored to optimize BTX yields while also considering the process’s economic feasibility.The results indicate that increasing the reaction temperature from 360℃ to 390℃ significantly favors the production of BTX,with yields increasing from 21.42%to 41.14%.Similarly,an increase in hydrogen pressure from 4 MPa to 6 MPa boosts BTX production,with yields rising from 36.31%to 41.14%.Reducing the space velocity from 2 h^(-1) to 0.5 h^(-1) also favors the BTX production process,with yields increasing from 37.96%to 45.13%.Furthermore,raising the hydrogen-to-oil volume ratio from 750 to 1500 improves BTX yields from 41.61%to 45.44%.Through economic analysis,the optimal conditions for BTX production were identified as a reaction temperature of 390℃,hydrogen pressure of 5-6 MPa,space velocity of 1 h^(-1),and hydrogen-to-oil volume ratio of 1000,achieving a BTX yield of 43.73%.This investigation highlights the importance of a holistic evaluation of hydrocracking conditions to optimize BTX production.Furthermore,the findings offer valuable insights for the design and operation of industrial hydrocracking processes aimed at efficiently converting coal tar-derived hydrorefined feedstock into BTX.展开更多
Ethane steam cracking process in an industrial reactor was investigated.An one-demsional(1D)steady-state model was developed firstly by using an improved molecular reaction scheme and was then simulated in Aspen Plus....Ethane steam cracking process in an industrial reactor was investigated.An one-demsional(1D)steady-state model was developed firstly by using an improved molecular reaction scheme and was then simulated in Aspen Plus.A comparison of model results with industrial data and previously reported results showed that the model can predict the process kinetics more accurately.In addition,the validated model was used to study the effects of different process variables,including coil outlet temperature(COT),steam-to-ethane ratio and residence time on ethane conversion,ethylene selectivity,products yields,and coking rate.Finally,steady-state optimization was conducted to the operation of industrial reactor.The COT and steam-to-ethane ratio were taken as decision variables to maximize the annual operational profit.展开更多
In this paper, based on the principle of heat transfer and thermal elastic-plastic theory, the heat treatment process optimization scheme for face gears is proposed according to the structural characteristics of the f...In this paper, based on the principle of heat transfer and thermal elastic-plastic theory, the heat treatment process optimization scheme for face gears is proposed according to the structural characteristics of the face gear and material properties of 12Cr2Ni4 steel. To simulate the effect of carburizing and quenching process on tooth deformation and residual stress distribution, a heat treatment analysis model of face gears is established, and the microstructure, stress and deformation of face gear teeth changing with time are analyzed. The simulation results show that face gear tooth hardness increases, tooth surface residual compressive stress increases and tooth deformation decreases after heat treatment process optimization. It is beneficial to improving the fatigue strength and performance of face gears.展开更多
The RTS technology can produce ultra-low sulfur diesel at lower costs using available hydrogenation catalyst and device.However,with the increase of the mixing proportion of secondary processed diesel fuel in the feed...The RTS technology can produce ultra-low sulfur diesel at lower costs using available hydrogenation catalyst and device.However,with the increase of the mixing proportion of secondary processed diesel fuel in the feed,the content of nitrogen compounds and polycyclic aromatic hydrocarbons in the feed increased,leading to the acceleration of the deactivation rate of the primary catalyst and the shortening of the service cycle.In order to fully understand the reason of catalyst deactivation,the effect of mixing secondary processed diesel fuel oil on the operating stability of the catalyst in the first reactor was investigated in a medium-sized fixed-bed hydrogenation unit.The results showed that the nitrogen compounds mainly affected the initial activity of the catalyst,but had little effect on the stability of the catalyst.The PAHs had little effect on the initial activity of the catalyst,but could significantly accelerate the deactivation of the catalyst.Combined with the analysis of the reason of catalyst deactivation and the study of RTS technology,the direction of RTS technology process optimization was put forward,and the stability of catalyst was improved obviously after process optimization.展开更多
Because there is neither waste rock nor mill tailings in the gypsum mine, and the buildings on the goaf of gypsum mine are needed to be protected, the research proposed the scheme of the clay filling technology. Gypsu...Because there is neither waste rock nor mill tailings in the gypsum mine, and the buildings on the goaf of gypsum mine are needed to be protected, the research proposed the scheme of the clay filling technology. Gypsum, cement, lime and water glass were used as adhesive, and the strength of different material ratios were investigated in this study. The influence factors of clay strength were obtained in the order of cement, gypsum, water glass and lime. The results show that the cement content is the determinant influence factor, and gypsum has positive effects, while the water glass can enhance both clay strength and the fluidity of the filing slurry. Furthermore, combining chaotic optimization method with neural network, the optimal ratio of composite cementing agent was obtained. The results show that the optimal ratio of water glass, cement, lime and clay (in quality) is 1.17:6.74:4.17:87.92 in the process of bottom self-flow filling, while the optimal ratio is 1.78:9.58:4.71:83.93 for roof-contacted filling. A novel filling process to fill in gypsum mine goaf with clay is established. The engineering practice shows that the filling cost is low, thus, notable economic benefit is achieved.展开更多
Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biolo...Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biological unit in response to pulsatile inputs, and its spontaneous excitation rate due to noise perturbation. Then we analytically calculate the mutual information, energy cost, and energy efficiency of an array of these bistable units. We find that the optimal number of units could maximize this array＇s energy efficiency in encoding pulse inputs, which depends on the fixed energy cost. We conclude that demand for energy efficiency in biological systems may strongly influence the size of these systems under the pressure of natural selection.展开更多
This study investigates the dry reformation of methane(DRM)over Ni/Al_(2)O_(3)catalysts in a dielectric barrier discharge(DBD)non-thermal plasma reactor.A novel hybrid machine learning(ML)model is developed to optimiz...This study investigates the dry reformation of methane(DRM)over Ni/Al_(2)O_(3)catalysts in a dielectric barrier discharge(DBD)non-thermal plasma reactor.A novel hybrid machine learning(ML)model is developed to optimize the plasma-catalytic DRM reaction with limited experimental data.To address the non-linear and complex nature of the plasma-catalytic DRM process,the hybrid ML model integrates three well-established algorithms:regression trees,support vector regression,and artificial neural networks.A genetic algorithm(GA)is then used to optimize the hyperparameters of each algorithm within the hybrid ML model.The ML model achieved excellent agreement with the experimental data,demonstrating its efficacy in accurately predicting and optimizing the DRM process.The model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM performance.We found that the optimal discharge power(20 W),CO_(2)/CH_(4)molar ratio(1.5),and Ni loading(7.8 wt%)resulted in the maximum energy yield at a total flow rate of∼51 mL/min.Furthermore,we investigated the relative significance of each operating parameter on the performance of the plasma-catalytic DRM process.The results show that the total flow rate had the greatest influence on the conversion,with a significance exceeding 35%for each output,while the Ni loading had the least impact on the overall reaction performance.This hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets,enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes.展开更多
Corn as one of the world's major food crops,its by-product corn cob is also rich in resources.However,the unreasonable utilization of corn cob often causes the environmental pollution,waste of resources and other ...Corn as one of the world's major food crops,its by-product corn cob is also rich in resources.However,the unreasonable utilization of corn cob often causes the environmental pollution,waste of resources and other problems.As one of the most abundant polymers in nature,xylan is widely used in food,medicine,materials and other fields.Corn cob is rich in xylan,which is an ideal raw material for extracting xylan.However,the intractable lignin is covalently linked to xylan,which increases the difficulty of xylan extraction.It has been reported that the deep eutectic solvent(DES)could preferentially dissolve lignin in biomass,thereby dissolving the xylan.Then,the xylan in the extract was separated by ethanol precipitation method.The xylan precipitate was obtained after centrifugation,while the supernatant was retained.The components of the supernatant after ethanol precipitation were separated by the rotary evaporator.The ethanol,water and DES were collected for the subsequent extraction of corn cob xylan.In this study,a novel way was provided for the green production of corn cob xylan.The DES was used to extract xylan from corn cob which was used as the raw material.The effects of solid-liquid ratio,reaction time,reaction temperature and water content of DES on the extraction rate of corn cob xylan were investigated by the single factor test.Furthermore,the orthogonal test was designed to optimize the xylan extraction process.The structure of corn cob xylan was analyzed and verified.The results showed that the optimum extraction conditions of corn cob xylan were as follows:the ratio of corn cob to DES was 1:15(g:mL),the extraction time was 3 h,the extraction temperature was 60℃,and the water content of DES was 70%.Under these conditions,the extraction rate of xylan was 16.46%.The extracted corn cob xylan was distinctive triple helix of polysaccharide,which was similar to the structure of commercially available xylan.Xylan was effectively and workably extracted from corn cob by the DES method.This study provided a new approach for high value conversion of corn cob and the clean production of xylan.展开更多
We discuss the symmetric quantum discord （SQD） for an arbitrary two-qubit state consisting of subsystems A and B and give the analysis formula of the symmetric quantum discord for the arbitrary two-qubit state. We a...We discuss the symmetric quantum discord （SQD） for an arbitrary two-qubit state consisting of subsystems A and B and give the analysis formula of the symmetric quantum discord for the arbitrary two-qubit state. We also give the optimization process of the symmetric quantum discord for some states and obtain the symmetric quantum discord. We compare the quantum discord （QD） with the symmetric quantum discord, and find that the symmetric quantum discord is greater than the quantum discord. We also find that the symmetric quantum discord can be unequal to the quantum discord when the right quantum discord （measure on subsystem B） is equal to the left quantum discord （measure on subsystem A）.展开更多
文摘Hydroconversion of coal tar to produce aromatic hydrocarbons(BTX)represents a crucial strategy for the highvalue hierarchical utilization of coal.This study focused on the hydrocracking of hydrorefined products derived from coal tar to enhance the production of benzene,toluene,and xylene(BTX).Various reaction conditions,including reaction temperature,hydrogen pressure,space velocity,and hydrogen-to-oil volume ratio,were systematically explored to optimize BTX yields while also considering the process’s economic feasibility.The results indicate that increasing the reaction temperature from 360℃ to 390℃ significantly favors the production of BTX,with yields increasing from 21.42%to 41.14%.Similarly,an increase in hydrogen pressure from 4 MPa to 6 MPa boosts BTX production,with yields rising from 36.31%to 41.14%.Reducing the space velocity from 2 h^(-1) to 0.5 h^(-1) also favors the BTX production process,with yields increasing from 37.96%to 45.13%.Furthermore,raising the hydrogen-to-oil volume ratio from 750 to 1500 improves BTX yields from 41.61%to 45.44%.Through economic analysis,the optimal conditions for BTX production were identified as a reaction temperature of 390℃,hydrogen pressure of 5-6 MPa,space velocity of 1 h^(-1),and hydrogen-to-oil volume ratio of 1000,achieving a BTX yield of 43.73%.This investigation highlights the importance of a holistic evaluation of hydrocracking conditions to optimize BTX production.Furthermore,the findings offer valuable insights for the design and operation of industrial hydrocracking processes aimed at efficiently converting coal tar-derived hydrorefined feedstock into BTX.
基金The financial support provided by the Project of National Natural Science Foundation of China(21822809&21978256)the Fundamental Research Funds for the Central Universitiesthe Foundation of State Key Laboratory of High-efficiency Utilization of Coal and Green Chemical Engineering(Grant No.2018-K23)are gratefully acknowledged.
文摘Ethane steam cracking process in an industrial reactor was investigated.An one-demsional(1D)steady-state model was developed firstly by using an improved molecular reaction scheme and was then simulated in Aspen Plus.A comparison of model results with industrial data and previously reported results showed that the model can predict the process kinetics more accurately.In addition,the validated model was used to study the effects of different process variables,including coil outlet temperature(COT),steam-to-ethane ratio and residence time on ethane conversion,ethylene selectivity,products yields,and coking rate.Finally,steady-state optimization was conducted to the operation of industrial reactor.The COT and steam-to-ethane ratio were taken as decision variables to maximize the annual operational profit.
基金Funded by Key Project of Advanced Research Foundation(No.9140A18020113xx)Advanced Research Foundation Project(No.9140A18020212xx)Advanced Research Projects(Nos.5131802xx and 5131812xx)
文摘In this paper, based on the principle of heat transfer and thermal elastic-plastic theory, the heat treatment process optimization scheme for face gears is proposed according to the structural characteristics of the face gear and material properties of 12Cr2Ni4 steel. To simulate the effect of carburizing and quenching process on tooth deformation and residual stress distribution, a heat treatment analysis model of face gears is established, and the microstructure, stress and deformation of face gear teeth changing with time are analyzed. The simulation results show that face gear tooth hardness increases, tooth surface residual compressive stress increases and tooth deformation decreases after heat treatment process optimization. It is beneficial to improving the fatigue strength and performance of face gears.
基金This work was financially supported by the Technology Development Project of SINOPEC(121025)All of the staff in our laboratory had provided a lot of support in the analysis of oil samples and catalyst characterization.
文摘The RTS technology can produce ultra-low sulfur diesel at lower costs using available hydrogenation catalyst and device.However,with the increase of the mixing proportion of secondary processed diesel fuel in the feed,the content of nitrogen compounds and polycyclic aromatic hydrocarbons in the feed increased,leading to the acceleration of the deactivation rate of the primary catalyst and the shortening of the service cycle.In order to fully understand the reason of catalyst deactivation,the effect of mixing secondary processed diesel fuel oil on the operating stability of the catalyst in the first reactor was investigated in a medium-sized fixed-bed hydrogenation unit.The results showed that the nitrogen compounds mainly affected the initial activity of the catalyst,but had little effect on the stability of the catalyst.The PAHs had little effect on the initial activity of the catalyst,but could significantly accelerate the deactivation of the catalyst.Combined with the analysis of the reason of catalyst deactivation and the study of RTS technology,the direction of RTS technology process optimization was put forward,and the stability of catalyst was improved obviously after process optimization.
基金supported by the National Basic Research and Development Program of China (No. 2010CB732004)the joint funding of the National Natural Science Foundation and Shanghai Baosteel Group Corporation of China (No. 51074177)
文摘Because there is neither waste rock nor mill tailings in the gypsum mine, and the buildings on the goaf of gypsum mine are needed to be protected, the research proposed the scheme of the clay filling technology. Gypsum, cement, lime and water glass were used as adhesive, and the strength of different material ratios were investigated in this study. The influence factors of clay strength were obtained in the order of cement, gypsum, water glass and lime. The results show that the cement content is the determinant influence factor, and gypsum has positive effects, while the water glass can enhance both clay strength and the fluidity of the filing slurry. Furthermore, combining chaotic optimization method with neural network, the optimal ratio of composite cementing agent was obtained. The results show that the optimal ratio of water glass, cement, lime and clay (in quality) is 1.17:6.74:4.17:87.92 in the process of bottom self-flow filling, while the optimal ratio is 1.78:9.58:4.71:83.93 for roof-contacted filling. A novel filling process to fill in gypsum mine goaf with clay is established. The engineering practice shows that the filling cost is low, thus, notable economic benefit is achieved.
基金Supported by the National Natural Science Foundation of China under Grant Nos 11105062 and 11265014the Fundamental Research Funds for the Central Universities under Grant Nos LZUJBKY-2011-57 and LZUJBKY-2015-119
文摘Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biological unit in response to pulsatile inputs, and its spontaneous excitation rate due to noise perturbation. Then we analytically calculate the mutual information, energy cost, and energy efficiency of an array of these bistable units. We find that the optimal number of units could maximize this array＇s energy efficiency in encoding pulse inputs, which depends on the fixed energy cost. We conclude that demand for energy efficiency in biological systems may strongly influence the size of these systems under the pressure of natural selection.
基金This project received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 813393the funding from the National Natural Science Foundation of China (No. 52177149)
文摘This study investigates the dry reformation of methane(DRM)over Ni/Al_(2)O_(3)catalysts in a dielectric barrier discharge(DBD)non-thermal plasma reactor.A novel hybrid machine learning(ML)model is developed to optimize the plasma-catalytic DRM reaction with limited experimental data.To address the non-linear and complex nature of the plasma-catalytic DRM process,the hybrid ML model integrates three well-established algorithms:regression trees,support vector regression,and artificial neural networks.A genetic algorithm(GA)is then used to optimize the hyperparameters of each algorithm within the hybrid ML model.The ML model achieved excellent agreement with the experimental data,demonstrating its efficacy in accurately predicting and optimizing the DRM process.The model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM performance.We found that the optimal discharge power(20 W),CO_(2)/CH_(4)molar ratio(1.5),and Ni loading(7.8 wt%)resulted in the maximum energy yield at a total flow rate of∼51 mL/min.Furthermore,we investigated the relative significance of each operating parameter on the performance of the plasma-catalytic DRM process.The results show that the total flow rate had the greatest influence on the conversion,with a significance exceeding 35%for each output,while the Ni loading had the least impact on the overall reaction performance.This hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets,enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes.
基金This work was supported by the National Natural Science Foundation of China[21978070]Natural Science Foundation of Henan[212300410032,232103810065]+2 种基金Key Research and Development Projects of Henan Province[221111320500]Program for Science&Technology Innovation Talents in Universities of Henan Province[20HASTIT034]Henan Province“Double First-Class”Project-Food Science and Technology.
文摘Corn as one of the world's major food crops,its by-product corn cob is also rich in resources.However,the unreasonable utilization of corn cob often causes the environmental pollution,waste of resources and other problems.As one of the most abundant polymers in nature,xylan is widely used in food,medicine,materials and other fields.Corn cob is rich in xylan,which is an ideal raw material for extracting xylan.However,the intractable lignin is covalently linked to xylan,which increases the difficulty of xylan extraction.It has been reported that the deep eutectic solvent(DES)could preferentially dissolve lignin in biomass,thereby dissolving the xylan.Then,the xylan in the extract was separated by ethanol precipitation method.The xylan precipitate was obtained after centrifugation,while the supernatant was retained.The components of the supernatant after ethanol precipitation were separated by the rotary evaporator.The ethanol,water and DES were collected for the subsequent extraction of corn cob xylan.In this study,a novel way was provided for the green production of corn cob xylan.The DES was used to extract xylan from corn cob which was used as the raw material.The effects of solid-liquid ratio,reaction time,reaction temperature and water content of DES on the extraction rate of corn cob xylan were investigated by the single factor test.Furthermore,the orthogonal test was designed to optimize the xylan extraction process.The structure of corn cob xylan was analyzed and verified.The results showed that the optimum extraction conditions of corn cob xylan were as follows:the ratio of corn cob to DES was 1:15(g:mL),the extraction time was 3 h,the extraction temperature was 60℃,and the water content of DES was 70%.Under these conditions,the extraction rate of xylan was 16.46%.The extracted corn cob xylan was distinctive triple helix of polysaccharide,which was similar to the structure of commercially available xylan.Xylan was effectively and workably extracted from corn cob by the DES method.This study provided a new approach for high value conversion of corn cob and the clean production of xylan.
基金supported by the National Natural Science Foundation of China(Grant No.11174028)the Fundamental Research Funds for the Central Universities,China(Grant No.2011JBZ013)
文摘We discuss the symmetric quantum discord （SQD） for an arbitrary two-qubit state consisting of subsystems A and B and give the analysis formula of the symmetric quantum discord for the arbitrary two-qubit state. We also give the optimization process of the symmetric quantum discord for some states and obtain the symmetric quantum discord. We compare the quantum discord （QD） with the symmetric quantum discord, and find that the symmetric quantum discord is greater than the quantum discord. We also find that the symmetric quantum discord can be unequal to the quantum discord when the right quantum discord （measure on subsystem B） is equal to the left quantum discord （measure on subsystem A）.
