Delineation of hydrocarbon-bearing sands and the extent of accumulation using seismic data is a reoccurring challenge for many fields.This study addressed the existing challenges of delineating a known hydrocarbon reg...Delineation of hydrocarbon-bearing sands and the extent of accumulation using seismic data is a reoccurring challenge for many fields.This study addressed the existing challenges of delineating a known hydrocarbon region for a thin-pay reservoir using conventional attributes extraction methods.The efficacy of applying iso-frequency extraction and spectral frequency blending in identifying thin-pay and thick-pay reservoirs on seismic was tested by utilizing 3D seismic data and well logs data of Terra field in the Western Niger Delta Basin.Well tops of all the reservoirs in the field were picked and two reservoirs that correspond to thin-and thick-pay reservoirs,namely A and F were identified respectively.The gross pay thickness of reservoir A is 18 ft while that of reservoir F is 96 ft.Conventional attribute extraction such as RMS amplitude,minimum amplitude,and average energy can be used to identify the hydrocarbon-bearing region in reservoir F but was not applicable for identifying the thin-pay reservoir A.This prompted the interest of using iso-frequency extractions and spectral frequency blending of three iso-frequency cubes of 12 Hz,30 Hz,and 70 Hz to get a spectral frequency RGB cube.The 12 Hz isofrequency can be used to partially identify hydrocarbon-bearing region in reservoir A while the 30Hz iso-frequency can be used to partially identify hydrocarbon-bearing region in reservoir F.The results show that time slices from the spectral frequency blended cube were able to delineate both the thin-pay and thick-pay hydrocarbon-bearing regions as high amplitude.The extractions also conformed to the structure of the two reservoirs.However,there seems to be a color difference in the amplitude display for both reservoirs.The thick-pay reservoir showed a red color on the time slice while the thin-pay reservoir showed a green color.This study has shown that spectral frequency blending is a more effective tool than conventional attributes extractions in identifying hydrocarbon-bearing region using seismic data.The methodology utilized in this study can be applied to other fields with similar challenges and for identifying prospective hydrocarbon bearing areas.展开更多
Wet flue gas desulfurization(WFGD)could effectively reduce sulfur dioxide emission.However,magnesium sulfite(MgSO_(3)),a by-product of desulfurization,was easy to result in secondary pollution.In this study,the solid ...Wet flue gas desulfurization(WFGD)could effectively reduce sulfur dioxide emission.However,magnesium sulfite(MgSO_(3)),a by-product of desulfurization,was easy to result in secondary pollution.In this study,the solid catalyst Co-Bent(bentonite supported cobalt)was prepared by blending method for MgSO_(3) oxidation with bentonite as the carrier and cobalt as the active component.At the calcination temperature of 550℃ and the Co loading level of 3 wt.%,the catalyst showed excellent catalytic performance for the oxidation of high concentration MgSO_(3) slurry,and the oxidation rate of MgSO_(3) was 0.13 mol/(L·h).The research indicated that the active component was uniformly distributed within porous structure of the catalyst as Co_(3)O_(4),which facilitated the oxidation of SO_(3)^(2-) catalyzed by Co_(3)O_(4).Kinetic researches indicated the oxidation rate of MgSO_(3) was influenced by the catalyst dosage,the reaction temperature,the solution pH,the airflow rate,and the SO_(3)^(2-) concentration.Additionally,after recycling experiments,the regenerated catalyst retained its high catalytic performance for the MgSO_(3) oxidation.The reaction mechanism for the catalytic oxidation of MgSO_(3) by Co-Bent catalyst was also proposed.The generation of active free radicals(OH·,SO_(4)^(-)·,SO_(3)^(-)·,SO_(5)^(-)·)accelerated the MgSO_(3) oxidation.These results provide theoretical support for the treatment of MgSO_(3) and the development of durable catalyst.展开更多
China has abundant resources of high-alumina coal(HAC).However,its application as a raw gasification material is limited owing to high ash-fusion characteristics.For overcoming the limitation,this study employed Xinji...China has abundant resources of high-alumina coal(HAC).However,its application as a raw gasification material is limited owing to high ash-fusion characteristics.For overcoming the limitation,this study employed Xinjiang coal(XJ),having a low ash fusion temperature,to improve the ash fusibility and viscosity of high-alumina Jungar coal(JG).The evolution of Al-containing phases and structures during mixed ash melting were investigated based on XRD,XPS,27Al NMR,high-temperature stage microscopy(HTSM),and thermodynamic simulations.An increase in the XJ mass ratio resulted in the transformation of gehlenite to anorthite and mullite,producing more amorphous materials at high temperature.These phenomena were manifested at a microscopic imaging as an increase in the number of reaction/melting sites and their area expansion rate,as well as a decrease in ash area shrinkage and melting temperature.Moreover,the introduction of XJ altered the alumina-oxygen network,reducing the binding to the silicaoxygen network and converting some[AlO_(6)]^(9-)to[AlO_(4)]^(5-)as the relative concentration of O_(2)-and O-increases.Consequently,the decrease in the stability of the aluminate structure improves the AFT and viscosity.Based on these results,a mechanism to improve the ash fusion characteristics of HAC based on coal blending is proposed.展开更多
The use of hot recycled asphalt mixture(HRAM)allows for a reduction in the depletion of non-renewable resources and presents environmental benefits.However,concerns arise regarding the performance of HRAM due to the l...The use of hot recycled asphalt mixture(HRAM)allows for a reduction in the depletion of non-renewable resources and presents environmental benefits.However,concerns arise regarding the performance of HRAM due to the lower degree of blending(DOB)of virgin and aged asphalt(V&A asphalt).This paper aims to provide an up-to-date review on the DOB of V&A asphalt in HRAM.Initially,the paper introduces the DOB of V&A asphalt,followed by an analysis of the blending theory,evaluation methods,and influencing factors of DOB.Subsequently,the effect of DOB on the performance of HRAM is investigated,and molecular dynamic simulation is utilized to analyze the blend of V&A asphalt.Finally,methods for improving DOB are summarized.It was found that the use of high-resolution microscopy with tracer methods such as SEM/EDS was an effective way to characterize DOB.Furthermore,the chemical composition and colloid structure between virgin and aged asphalt are crucial to DOB.Additionally,improving DOB by utilizing the coupling effect of time and temperature during transportation,paving,and compaction stages is promising.Future research should focus on standardizing test methods,refining field simulation models,and developing intelligent construction technologies to achieve more efficient and durable blending.This review provides theoretical guidance and practical references for improving the DOB of V&A asphalt and promoting sustainable pavement construction.展开更多
Current mix design practices typically assume total blending and use the white curve of reclaimed asphalt pavement(RAP)to determine the gradation and optimum asphalt content(OAC)of recycled hot mix asphalt(HMA),often ...Current mix design practices typically assume total blending and use the white curve of reclaimed asphalt pavement(RAP)to determine the gradation and optimum asphalt content(OAC)of recycled hot mix asphalt(HMA),often overlooking the effects of RAP agglomeration and partial blending.This oversight can result in unsatisfactory performance,particularly when higher RAP content is used.Therefore,this paper reviews and discusses strategies for adjusting the mix design of recycled HMA to enhance its in-service performance.The discussion begins with RAP particle agglomeration,a significant phenomenon that significantly impacts the aggregate gradation of recycled HMA.Subsequently,detection methods to clarify the blending between virgin and RAP binders are described.Partial blending between RAP and virgin binders is common,and various indexes have been proposed to quantify the blending degree.Finally,the adjusted mix design method of recycled HMA is presented,emphasizing gradation optimization and corrected OAC.Gradation optimization should account for RAP agglomeration,while the corrected OAC should consider particle blending.Recycled HMA using the adjusted mix design exhibits improved crack resistance and fatigue life without substantially impairing rutting performance.This review aims to help both academics and highway agencies maximize the utilization of RAP materials within sustainable pavement frameworks.展开更多
Quantitative Precipitation Forecast(QPF)is a challenging issue in seamless prediction.QPF faces the following difficulties:(i)single rather than multiple model products are still used;(ii)most QPF methods require long...Quantitative Precipitation Forecast(QPF)is a challenging issue in seamless prediction.QPF faces the following difficulties:(i)single rather than multiple model products are still used;(ii)most QPF methods require long-term training samples not easily available,and(iii)local features are insufficiently reflected.In this work,a multi-model blending(MMB)algorithm with supplemental grid points(SGPs)is experimented to overcome these shortcomings.The MMB algorithm includes three steps:(1)single-model bias-correction,(2)dynamic weight MMB,and(3)light-precipitation elimination.In step 1,quantile mapping(QM)is used and SGPs are configured to expand the sample size.The SGPs are chosen based on similarity of topography,spatial distance,and climatic characteristics of local precipitation.In step 2,the dynamic weight MMB uses the idea of ensemble forecasting:a precipitation process can be forecast if more than 40% of the models predict such a case;moreover,threat score(TS)is used to update the weights of ensemble members.Finally,in step 3,the number of false alarms of light precipitation is reduced,thus alleviating unreasonable expansion of the precipitation area caused by the blending of multiple models.Verification results show that using the MMB algorithm has effectively improved the TS and bias score(BS)for blended 6-h QPF.The rate of increase in TS for heavy rainfall(25-mm threshold)reaches 20%-40%;in particular,the improvement has reached 47.6% for forecast lead time of 24 h,compared with the ECMWF model.Meanwhile,the BS is closer to 1,which is better than any single-model forecast.In sum,the QPF using MMB with SGPs shows great potential to further improve the present operational QPF in China.展开更多
The gasoline inline blending process has widely used real-time optimization techniques to achieve optimization objectives,such as minimizing the cost of production.However,the effectiveness of real-time optimization i...The gasoline inline blending process has widely used real-time optimization techniques to achieve optimization objectives,such as minimizing the cost of production.However,the effectiveness of real-time optimization in gasoline blending relies on accurate blending models and is challenged by stochastic disturbances.Thus,we propose a real-time optimization algorithm based on the soft actor-critic(SAC)deep reinforcement learning strategy to optimize gasoline blending without relying on a single blending model and to be robust against disturbances.Our approach constructs the environment using nonlinear blending models and feedstocks with disturbances.The algorithm incorporates the Lagrange multiplier and path constraints in reward design to manage sparse product constraints.Carefully abstracted states facilitate algorithm convergence,and the normalized action vector in each optimization period allows the agent to generalize to some extent across different target production scenarios.Through these well-designed components,the algorithm based on the SAC outperforms real-time optimization methods based on either nonlinear or linear programming.It even demonstrates comparable performance with the time-horizon based real-time optimization method,which requires knowledge of uncertainty models,confirming its capability to handle uncertainty without accurate models.Our simulation illustrates a promising approach to free real-time optimization of the gasoline blending process from uncertainty models that are difficult to acquire in practice.展开更多
Fuel design is a complex multi-objective optimization problem in which facile and robust methods are urgently demanded.Herein,a complete workflow for designing a fuel blending scheme is presented,which is theoreticall...Fuel design is a complex multi-objective optimization problem in which facile and robust methods are urgently demanded.Herein,a complete workflow for designing a fuel blending scheme is presented,which is theoretically supported,efficient,and reliable.Based on the data distribution of the composition and properties of the blending fuels,a model of polynomial regression with appropriate hypothesis space was established.The parameters of the model were further optimized by different intelligence algorithms to achieve high-precision regression.Then,the design of a blending fuel was described as a multi-objective optimization problem,which was solved using a Nelder–Mead algorithm based on the concept of Pareto domination.Finally,the design of a target fuel was fully validated by experiments.This study provides new avenues for designing various blending fuels to meet the needs of next-generation engines.展开更多
Controlled-release urea(CRU)releases nitrogen(N)at the same pace that rice takes it up,which can effectively improve N use efficiency,increase rice yield and improve rice quality.However,few studies have described the...Controlled-release urea(CRU)releases nitrogen(N)at the same pace that rice takes it up,which can effectively improve N use efficiency,increase rice yield and improve rice quality.However,few studies have described the effects of CRU application on the photosynthetic rate and endogenous enzyme activities of rice.Accordingly,a twoyear field trial was conducted with a total of seven treatments:CK,no N fertilizer;BBF,regular blended fertilizer;RBBF,20%N-reduced regular blended fertilizer;CRF1,70%CRU+30%regular urea one-time base application;CRF2,60%CRU+40%regular urea one-time base application;RCRF1,CRF1 treatment with 20%N reduction;and RCRF2,CRF2 treatment with 20%N reduction.Each treatment was conducted in triplicate.The results showed that the N recovery efficiency(NRE)of the controlled-release bulk blending fertilizer(CRBBF)treatments was significantly greater over the two years.There were significant yield increases of 4.1–5.9%under the CRF1treatment and 5.6–7.6%under the CRF2 treatment compared to the BBF treatment,but the differences between the reduced-N treatments RBBF and RCRF2 were not significant.Photosynthetic rates under the CRF1 and CRF2treatments were significantly higher than under the other treatments,and they had significantly greater RuBPCase,RuBisCO,glutamate synthase(GOGAT)and glutamine synthetase(GS)enzyme activities.Additionally,the soil NH_(4)^(+)-N and NO_(3)^(–)-N contents under the CRBBF treatments were significantly higher at the late growth stage of rice,which was more in-line with the fertilizer requirements of rice throughout the reproductive period.CRBBF also led to some improvement in rice quality.Compared with the BBF and RBBF treatments,the protein contents under the CRBBF treatments were reduced but the milling,appearance,eating and cooking qualities of the rice were improved.These results showed that the application of CRBBF can improve the NRE,photosynthetic rate and endogenous enzyme activities of rice,ensuring sufficient N nutrition and photosynthetic material production during rice growth and thereby achieving improved rice yield and quality.展开更多
High-entropy polymer blends composed of polypropylene(PP),polystyrene(PS),polyamide 6(PA6),poly(lactic acid)(PLA),and styrene-ethylene-butylene-styrene(SEBS)were successfully fabricated using maleic anhydride-grafted ...High-entropy polymer blends composed of polypropylene(PP),polystyrene(PS),polyamide 6(PA6),poly(lactic acid)(PLA),and styrene-ethylene-butylene-styrene(SEBS)were successfully fabricated using maleic anhydride-grafted SEBS(SEBS-g-MAH)as a compatibilizer.Dynamic mechanical analysis(DMA),differential scanning calorimetry(DSC),scanning electron microscopy(SEM),and mechanical testing demonstrated that SEBS-g-MAH significantly enhanced the compatibility between the polar(PA6,PLA)and nonpolar(PP,PS,SEBS)components.The compatibilizer effectively refined the microstructure,substantially reduced the domain sizes,and blurred the phase boundaries,indicating enhanced interfacial interactions among all the components.The optimal compatibilizer content(15 wt%)notably increased tensile ductility(elongation at break from 5.0%to 23.7%)while maintaining balanced crystallization behavior,despite slightly decreasing modulus.This work not only demonstrates the broad applicability of high-entropy polymer blends as a sustainable strategy for converting complex,unsorted plastic waste into high-performance value-added materials that significantly contribute to plastic upcycling efforts,but also highlights intriguing physical phenomena emerging from such complex polymer systems.展开更多
This article explores in-class practice of blended teaching of Chinese-English(C-E)translation for English as a Foreign Language(EFL)majors in the era of artificial intelligence(AI).It examines the opportunities and c...This article explores in-class practice of blended teaching of Chinese-English(C-E)translation for English as a Foreign Language(EFL)majors in the era of artificial intelligence(AI).It examines the opportunities and challenges AI presents in enhancing translation education,particularly in fostering student engagement,improving teaching efficiency,and promoting self-motivated learning.Case study suggests that AI can enhance the flexibility of teaching and motivate students,yet challenges such as over-reliance on AI and diminished critical thinking need to be addressed.While acknowledging the indispensability of human translators,the article concludes that effective blended teaching requires purposeful curriculum design,proper integration of AI,and a collaborative effort of teachers and students to maximize the potential of AI while ensuring high-quality,independent learning outcomes.展开更多
Fuel injection properties,including the injection rate(temporal aspects)and spray behavior(spatial aspects),play a crucial role in the combustion efficiency and emissions of diesel engines.This study investigates the ...Fuel injection properties,including the injection rate(temporal aspects)and spray behavior(spatial aspects),play a crucial role in the combustion efficiency and emissions of diesel engines.This study investigates the effects of different ethanol-biodiesel-diesel(EBD)blends on the injection performance in diesel engines.Experimental tests are conducted to examine key injection parameters,such as spray penetration distance,spray cone angle,and droplet size,alongside an analysis of coupling leakage.The main findings are as follows:(1)The injection behavior of ethanol and diesel differs significantly.The addition of ethanol reduces the density,viscosity,and modulus of elasticity of the fuel mixture.While the injection advance angle,penetration distance,and Sauter mean diameter show minimal changes,the spray cone angle and coupling leakage increase notably.These alterations may disrupt the“fuelair-chamber”matching characteristics of the original engine,potentially affecting performance.(2)In contrast,the injection performance of biodiesel ismore similar to that of diesel.As biodiesel content increases,the density,viscosity,and modulus of elasticity of the blended fuel also grow.Though changes in injection timing,penetration distance,and spray cone angle remain minimal,the Sauter mean diameter experiences a slight increase.The“air-fuel chamber”compatibility of the original engine is largely unaffected,though fuel atomization slightly deteriorates.Blending up to 20%biodiesel and 30%ethanol with diesel effectively compensates for the shortcomings of using single fuels,maintaining favorable injection dynamics while enhancing lubrication and sealing performance of engine components.展开更多
College students’safety education is an important part of the fundamental task of fostering virtue through education in colleges and universities.A questionnaire survey at J University shows that the popularization d...College students’safety education is an important part of the fundamental task of fostering virtue through education in colleges and universities.A questionnaire survey at J University shows that the popularization degree and teaching satisfaction of college students’safety education are relatively high,but the teaching content and teaching forms still need improvement.With the rapid development of artificial intelligence technology and considering the char-acteristics of college students’online learning in the new era,carrying out the SPOC+PBL blended teaching reform not only helps to enhance the effectiveness of theoretical and practical teaching but also contributes to optimizing the teach-ing evaluation and feedback mechanism and strengthening students’problem-solving abilities.Therefore,we should adhere to the goal orientation,meticulously design the teaching plan,highlight the student-centered approach,focus on integrating teaching resources,strengthen process management,promptly provide feedback and guidance,empower with data,and continuously improve teaching evaluation.Thus,a student-centered SPOC+PBL blended teaching sys-tem can be constructed to empower the transformation and innovation of talent cultivation in higher education.展开更多
Objective:To construct a blended teaching model for surgical nursing based on the OBE(Outcome-Based Education)concept and explore its application effect in nursing education.Methods:A total of 220 undergraduate nursin...Objective:To construct a blended teaching model for surgical nursing based on the OBE(Outcome-Based Education)concept and explore its application effect in nursing education.Methods:A total of 220 undergraduate nursing students in the class of 2023 were selected as the main research subjects.The experimental group(110 students)adopted the OBE-based blended teaching model,while the control group(110 students)used conventional teaching methods.The learning effects,skill mastery,and clinical practice performance of the two groups were compared.Results:The experimental group significantly outperformed the control group in theoretical scores,practical skills,clinical application ability,and learning satisfaction,with statistically significant differences(P<0.05).Conclusion:The OBE-based blended teaching model has significant teaching advantages,which can effectively improve the comprehensive quality of undergraduate nursing students,enhance their clinical adaptability and innovative thinking,and is worthy of widespread promotion.展开更多
In this study,we conducted an experiment to construct multi-model ensemble(MME)predictions for the El Niño-Southern Oscillation(ENSO)using a neural network,based on hindcast data released from five coupled oceana...In this study,we conducted an experiment to construct multi-model ensemble(MME)predictions for the El Niño-Southern Oscillation(ENSO)using a neural network,based on hindcast data released from five coupled oceanatmosphere models,which exhibit varying levels of complexity.This nonlinear approach demonstrated extraordinary superiority and effectiveness in constructing ENSO MME.Subsequently,we employed the leave-one-out crossvalidation and the moving base methods to further validate the robustness of the neural network model in the formulation of ENSO MME.In conclusion,the neural network algorithm outperforms the conventional approach of assigning a uniform weight to all models.This is evidenced by an enhancement in correlation coefficients and reduction in prediction errors,which have the potential to provide a more accurate ENSO forecast.展开更多
文摘Delineation of hydrocarbon-bearing sands and the extent of accumulation using seismic data is a reoccurring challenge for many fields.This study addressed the existing challenges of delineating a known hydrocarbon region for a thin-pay reservoir using conventional attributes extraction methods.The efficacy of applying iso-frequency extraction and spectral frequency blending in identifying thin-pay and thick-pay reservoirs on seismic was tested by utilizing 3D seismic data and well logs data of Terra field in the Western Niger Delta Basin.Well tops of all the reservoirs in the field were picked and two reservoirs that correspond to thin-and thick-pay reservoirs,namely A and F were identified respectively.The gross pay thickness of reservoir A is 18 ft while that of reservoir F is 96 ft.Conventional attribute extraction such as RMS amplitude,minimum amplitude,and average energy can be used to identify the hydrocarbon-bearing region in reservoir F but was not applicable for identifying the thin-pay reservoir A.This prompted the interest of using iso-frequency extractions and spectral frequency blending of three iso-frequency cubes of 12 Hz,30 Hz,and 70 Hz to get a spectral frequency RGB cube.The 12 Hz isofrequency can be used to partially identify hydrocarbon-bearing region in reservoir A while the 30Hz iso-frequency can be used to partially identify hydrocarbon-bearing region in reservoir F.The results show that time slices from the spectral frequency blended cube were able to delineate both the thin-pay and thick-pay hydrocarbon-bearing regions as high amplitude.The extractions also conformed to the structure of the two reservoirs.However,there seems to be a color difference in the amplitude display for both reservoirs.The thick-pay reservoir showed a red color on the time slice while the thin-pay reservoir showed a green color.This study has shown that spectral frequency blending is a more effective tool than conventional attributes extractions in identifying hydrocarbon-bearing region using seismic data.The methodology utilized in this study can be applied to other fields with similar challenges and for identifying prospective hydrocarbon bearing areas.
基金supported by the State Key Laboratory of Urban Water Resource and Environment,Harbin Institute of Technology (No. 2022TS10)the Taishan Industrial Experts Programthe Natural Science Foundation of Shandong Province of China (No. ZR2023ME212).
文摘Wet flue gas desulfurization(WFGD)could effectively reduce sulfur dioxide emission.However,magnesium sulfite(MgSO_(3)),a by-product of desulfurization,was easy to result in secondary pollution.In this study,the solid catalyst Co-Bent(bentonite supported cobalt)was prepared by blending method for MgSO_(3) oxidation with bentonite as the carrier and cobalt as the active component.At the calcination temperature of 550℃ and the Co loading level of 3 wt.%,the catalyst showed excellent catalytic performance for the oxidation of high concentration MgSO_(3) slurry,and the oxidation rate of MgSO_(3) was 0.13 mol/(L·h).The research indicated that the active component was uniformly distributed within porous structure of the catalyst as Co_(3)O_(4),which facilitated the oxidation of SO_(3)^(2-) catalyzed by Co_(3)O_(4).Kinetic researches indicated the oxidation rate of MgSO_(3) was influenced by the catalyst dosage,the reaction temperature,the solution pH,the airflow rate,and the SO_(3)^(2-) concentration.Additionally,after recycling experiments,the regenerated catalyst retained its high catalytic performance for the MgSO_(3) oxidation.The reaction mechanism for the catalytic oxidation of MgSO_(3) by Co-Bent catalyst was also proposed.The generation of active free radicals(OH·,SO_(4)^(-)·,SO_(3)^(-)·,SO_(5)^(-)·)accelerated the MgSO_(3) oxidation.These results provide theoretical support for the treatment of MgSO_(3) and the development of durable catalyst.
基金support from the National Natural Science Foundation of China(22408004)the Scientific Research Foundation for the Introduction of Talent,Anhui University of Science and Technology(2023yjrc90)+1 种基金the Fundamental Research Funds of the AUST(2024JBQN0015)the Open Research Fund Program of Anhui Provincial Institute of Modern Coal Processing Technology,Anhui University of Science and Technology(MTY202302).
文摘China has abundant resources of high-alumina coal(HAC).However,its application as a raw gasification material is limited owing to high ash-fusion characteristics.For overcoming the limitation,this study employed Xinjiang coal(XJ),having a low ash fusion temperature,to improve the ash fusibility and viscosity of high-alumina Jungar coal(JG).The evolution of Al-containing phases and structures during mixed ash melting were investigated based on XRD,XPS,27Al NMR,high-temperature stage microscopy(HTSM),and thermodynamic simulations.An increase in the XJ mass ratio resulted in the transformation of gehlenite to anorthite and mullite,producing more amorphous materials at high temperature.These phenomena were manifested at a microscopic imaging as an increase in the number of reaction/melting sites and their area expansion rate,as well as a decrease in ash area shrinkage and melting temperature.Moreover,the introduction of XJ altered the alumina-oxygen network,reducing the binding to the silicaoxygen network and converting some[AlO_(6)]^(9-)to[AlO_(4)]^(5-)as the relative concentration of O_(2)-and O-increases.Consequently,the decrease in the stability of the aluminate structure improves the AFT and viscosity.Based on these results,a mechanism to improve the ash fusion characteristics of HAC based on coal blending is proposed.
基金supported in part by the key project supported by the Joint Funds of the National Natural Science Foundation of China(grant No.U2433210)Shaanxi Province Postdoctoral Science Foundation(2024BSHSDZZ225)+1 种基金Natural Science Basic Research Program of Shaanxi Province(2025JC-YBQN-595)the Fundamental Research Funds for the Central Universities,CHD(300102215102).
文摘The use of hot recycled asphalt mixture(HRAM)allows for a reduction in the depletion of non-renewable resources and presents environmental benefits.However,concerns arise regarding the performance of HRAM due to the lower degree of blending(DOB)of virgin and aged asphalt(V&A asphalt).This paper aims to provide an up-to-date review on the DOB of V&A asphalt in HRAM.Initially,the paper introduces the DOB of V&A asphalt,followed by an analysis of the blending theory,evaluation methods,and influencing factors of DOB.Subsequently,the effect of DOB on the performance of HRAM is investigated,and molecular dynamic simulation is utilized to analyze the blend of V&A asphalt.Finally,methods for improving DOB are summarized.It was found that the use of high-resolution microscopy with tracer methods such as SEM/EDS was an effective way to characterize DOB.Furthermore,the chemical composition and colloid structure between virgin and aged asphalt are crucial to DOB.Additionally,improving DOB by utilizing the coupling effect of time and temperature during transportation,paving,and compaction stages is promising.Future research should focus on standardizing test methods,refining field simulation models,and developing intelligent construction technologies to achieve more efficient and durable blending.This review provides theoretical guidance and practical references for improving the DOB of V&A asphalt and promoting sustainable pavement construction.
基金sponsored by the National Natural Science Foundation of China(52178420,52408476)Special subsidy from Heilongjiang Provincial People's Government(HITTY-20190028)+1 种基金Postdoctoral Fellowship Program of CPSF(GZC20242207)the Fundamental Research Funds for the Central Universities(HIT.DZJJ.2023086).
文摘Current mix design practices typically assume total blending and use the white curve of reclaimed asphalt pavement(RAP)to determine the gradation and optimum asphalt content(OAC)of recycled hot mix asphalt(HMA),often overlooking the effects of RAP agglomeration and partial blending.This oversight can result in unsatisfactory performance,particularly when higher RAP content is used.Therefore,this paper reviews and discusses strategies for adjusting the mix design of recycled HMA to enhance its in-service performance.The discussion begins with RAP particle agglomeration,a significant phenomenon that significantly impacts the aggregate gradation of recycled HMA.Subsequently,detection methods to clarify the blending between virgin and RAP binders are described.Partial blending between RAP and virgin binders is common,and various indexes have been proposed to quantify the blending degree.Finally,the adjusted mix design method of recycled HMA is presented,emphasizing gradation optimization and corrected OAC.Gradation optimization should account for RAP agglomeration,while the corrected OAC should consider particle blending.Recycled HMA using the adjusted mix design exhibits improved crack resistance and fatigue life without substantially impairing rutting performance.This review aims to help both academics and highway agencies maximize the utilization of RAP materials within sustainable pavement frameworks.
基金Supported by the National Key Research and Development Program of China(2017YFC1502004)Special Project for Forecasters of China Meteorological Administration(CMAYBY2020-162)Special Project for Forecasters of National Meteorological Center(Y202135)。
文摘Quantitative Precipitation Forecast(QPF)is a challenging issue in seamless prediction.QPF faces the following difficulties:(i)single rather than multiple model products are still used;(ii)most QPF methods require long-term training samples not easily available,and(iii)local features are insufficiently reflected.In this work,a multi-model blending(MMB)algorithm with supplemental grid points(SGPs)is experimented to overcome these shortcomings.The MMB algorithm includes three steps:(1)single-model bias-correction,(2)dynamic weight MMB,and(3)light-precipitation elimination.In step 1,quantile mapping(QM)is used and SGPs are configured to expand the sample size.The SGPs are chosen based on similarity of topography,spatial distance,and climatic characteristics of local precipitation.In step 2,the dynamic weight MMB uses the idea of ensemble forecasting:a precipitation process can be forecast if more than 40% of the models predict such a case;moreover,threat score(TS)is used to update the weights of ensemble members.Finally,in step 3,the number of false alarms of light precipitation is reduced,thus alleviating unreasonable expansion of the precipitation area caused by the blending of multiple models.Verification results show that using the MMB algorithm has effectively improved the TS and bias score(BS)for blended 6-h QPF.The rate of increase in TS for heavy rainfall(25-mm threshold)reaches 20%-40%;in particular,the improvement has reached 47.6% for forecast lead time of 24 h,compared with the ECMWF model.Meanwhile,the BS is closer to 1,which is better than any single-model forecast.In sum,the QPF using MMB with SGPs shows great potential to further improve the present operational QPF in China.
基金supported by National Key Research & Development Program-Intergovernmental International Science and Technology Innovation Cooperation Project (2021YFE0112800)National Natural Science Foundation of China (Key Program: 62136003)+2 种基金National Natural Science Foundation of China (62073142)Fundamental Research Funds for the Central Universities (222202417006)Shanghai Al Lab
文摘The gasoline inline blending process has widely used real-time optimization techniques to achieve optimization objectives,such as minimizing the cost of production.However,the effectiveness of real-time optimization in gasoline blending relies on accurate blending models and is challenged by stochastic disturbances.Thus,we propose a real-time optimization algorithm based on the soft actor-critic(SAC)deep reinforcement learning strategy to optimize gasoline blending without relying on a single blending model and to be robust against disturbances.Our approach constructs the environment using nonlinear blending models and feedstocks with disturbances.The algorithm incorporates the Lagrange multiplier and path constraints in reward design to manage sparse product constraints.Carefully abstracted states facilitate algorithm convergence,and the normalized action vector in each optimization period allows the agent to generalize to some extent across different target production scenarios.Through these well-designed components,the algorithm based on the SAC outperforms real-time optimization methods based on either nonlinear or linear programming.It even demonstrates comparable performance with the time-horizon based real-time optimization method,which requires knowledge of uncertainty models,confirming its capability to handle uncertainty without accurate models.Our simulation illustrates a promising approach to free real-time optimization of the gasoline blending process from uncertainty models that are difficult to acquire in practice.
基金the support from the National Key R&D Program of China(No.2021YFC2103701)the National Natural Science Foundation of China(No.22178248)the Haihe Laboratory of Sustainable Chemical Transformations。
文摘Fuel design is a complex multi-objective optimization problem in which facile and robust methods are urgently demanded.Herein,a complete workflow for designing a fuel blending scheme is presented,which is theoretically supported,efficient,and reliable.Based on the data distribution of the composition and properties of the blending fuels,a model of polynomial regression with appropriate hypothesis space was established.The parameters of the model were further optimized by different intelligence algorithms to achieve high-precision regression.Then,the design of a blending fuel was described as a multi-objective optimization problem,which was solved using a Nelder–Mead algorithm based on the concept of Pareto domination.Finally,the design of a target fuel was fully validated by experiments.This study provides new avenues for designing various blending fuels to meet the needs of next-generation engines.
基金supported by the Natural Science Foundation of Jiangsu Province,China(BK20220563)the Key R&D Program of Jiangsu Province,China(BE2022338)the Colleges and Universities in Jiangsu Province Natural Science Foundation of China(19KJB210014)。
文摘Controlled-release urea(CRU)releases nitrogen(N)at the same pace that rice takes it up,which can effectively improve N use efficiency,increase rice yield and improve rice quality.However,few studies have described the effects of CRU application on the photosynthetic rate and endogenous enzyme activities of rice.Accordingly,a twoyear field trial was conducted with a total of seven treatments:CK,no N fertilizer;BBF,regular blended fertilizer;RBBF,20%N-reduced regular blended fertilizer;CRF1,70%CRU+30%regular urea one-time base application;CRF2,60%CRU+40%regular urea one-time base application;RCRF1,CRF1 treatment with 20%N reduction;and RCRF2,CRF2 treatment with 20%N reduction.Each treatment was conducted in triplicate.The results showed that the N recovery efficiency(NRE)of the controlled-release bulk blending fertilizer(CRBBF)treatments was significantly greater over the two years.There were significant yield increases of 4.1–5.9%under the CRF1treatment and 5.6–7.6%under the CRF2 treatment compared to the BBF treatment,but the differences between the reduced-N treatments RBBF and RCRF2 were not significant.Photosynthetic rates under the CRF1 and CRF2treatments were significantly higher than under the other treatments,and they had significantly greater RuBPCase,RuBisCO,glutamate synthase(GOGAT)and glutamine synthetase(GS)enzyme activities.Additionally,the soil NH_(4)^(+)-N and NO_(3)^(–)-N contents under the CRBBF treatments were significantly higher at the late growth stage of rice,which was more in-line with the fertilizer requirements of rice throughout the reproductive period.CRBBF also led to some improvement in rice quality.Compared with the BBF and RBBF treatments,the protein contents under the CRBBF treatments were reduced but the milling,appearance,eating and cooking qualities of the rice were improved.These results showed that the application of CRBBF can improve the NRE,photosynthetic rate and endogenous enzyme activities of rice,ensuring sufficient N nutrition and photosynthetic material production during rice growth and thereby achieving improved rice yield and quality.
基金supported by the National Natural Science Foundation of China(No.52173017)the Project of Introducing Urgently Needed and Scarce Talents in Key Supported Regions of Shandong Province in 2024.
文摘High-entropy polymer blends composed of polypropylene(PP),polystyrene(PS),polyamide 6(PA6),poly(lactic acid)(PLA),and styrene-ethylene-butylene-styrene(SEBS)were successfully fabricated using maleic anhydride-grafted SEBS(SEBS-g-MAH)as a compatibilizer.Dynamic mechanical analysis(DMA),differential scanning calorimetry(DSC),scanning electron microscopy(SEM),and mechanical testing demonstrated that SEBS-g-MAH significantly enhanced the compatibility between the polar(PA6,PLA)and nonpolar(PP,PS,SEBS)components.The compatibilizer effectively refined the microstructure,substantially reduced the domain sizes,and blurred the phase boundaries,indicating enhanced interfacial interactions among all the components.The optimal compatibilizer content(15 wt%)notably increased tensile ductility(elongation at break from 5.0%to 23.7%)while maintaining balanced crystallization behavior,despite slightly decreasing modulus.This work not only demonstrates the broad applicability of high-entropy polymer blends as a sustainable strategy for converting complex,unsorted plastic waste into high-performance value-added materials that significantly contribute to plastic upcycling efforts,but also highlights intriguing physical phenomena emerging from such complex polymer systems.
基金supported by the Industry-Academia Collaboration Project of the Ministry of Education:A Study on the Blended Teaching Model of Chinese-English Translation in the Era of Artificial Intelligence(Project Fund No.231001363084506).
文摘This article explores in-class practice of blended teaching of Chinese-English(C-E)translation for English as a Foreign Language(EFL)majors in the era of artificial intelligence(AI).It examines the opportunities and challenges AI presents in enhancing translation education,particularly in fostering student engagement,improving teaching efficiency,and promoting self-motivated learning.Case study suggests that AI can enhance the flexibility of teaching and motivate students,yet challenges such as over-reliance on AI and diminished critical thinking need to be addressed.While acknowledging the indispensability of human translators,the article concludes that effective blended teaching requires purposeful curriculum design,proper integration of AI,and a collaborative effort of teachers and students to maximize the potential of AI while ensuring high-quality,independent learning outcomes.
基金supported by Innovation Research Project for the training of high-level scientific and technological talents(Technical expert talents)of the Armed Police Force ZZKY20222415“13th Five-Year Plan”military key colleges and key disciplines-Equipment Engineering(Power)-17.
文摘Fuel injection properties,including the injection rate(temporal aspects)and spray behavior(spatial aspects),play a crucial role in the combustion efficiency and emissions of diesel engines.This study investigates the effects of different ethanol-biodiesel-diesel(EBD)blends on the injection performance in diesel engines.Experimental tests are conducted to examine key injection parameters,such as spray penetration distance,spray cone angle,and droplet size,alongside an analysis of coupling leakage.The main findings are as follows:(1)The injection behavior of ethanol and diesel differs significantly.The addition of ethanol reduces the density,viscosity,and modulus of elasticity of the fuel mixture.While the injection advance angle,penetration distance,and Sauter mean diameter show minimal changes,the spray cone angle and coupling leakage increase notably.These alterations may disrupt the“fuelair-chamber”matching characteristics of the original engine,potentially affecting performance.(2)In contrast,the injection performance of biodiesel ismore similar to that of diesel.As biodiesel content increases,the density,viscosity,and modulus of elasticity of the blended fuel also grow.Though changes in injection timing,penetration distance,and spray cone angle remain minimal,the Sauter mean diameter experiences a slight increase.The“air-fuel chamber”compatibility of the original engine is largely unaffected,though fuel atomization slightly deteriorates.Blending up to 20%biodiesel and 30%ethanol with diesel effectively compensates for the shortcomings of using single fuels,maintaining favorable injection dynamics while enhancing lubrication and sealing performance of engine components.
基金“Research on Mental Health Education of Poor College Students-Based on the Perspective of‘New Campus’”Philosophy and Social Science Research Project of Universities in Jiangsu Province(2019SJB912)“Research on Mental Health Education of Poor College Students-Based on the Perspective of‘New Campus’”Special Topic of Ideological and Political Education for College Students in 2018(JDXGXB201801)“Research on College English Teaching Strategies from the Perspective of the Theory of Multiple Intelligences”Jiangsu Provincial University Philosophy and Social Sciences Research Project(2023SJYB2216)。
文摘College students’safety education is an important part of the fundamental task of fostering virtue through education in colleges and universities.A questionnaire survey at J University shows that the popularization degree and teaching satisfaction of college students’safety education are relatively high,but the teaching content and teaching forms still need improvement.With the rapid development of artificial intelligence technology and considering the char-acteristics of college students’online learning in the new era,carrying out the SPOC+PBL blended teaching reform not only helps to enhance the effectiveness of theoretical and practical teaching but also contributes to optimizing the teach-ing evaluation and feedback mechanism and strengthening students’problem-solving abilities.Therefore,we should adhere to the goal orientation,meticulously design the teaching plan,highlight the student-centered approach,focus on integrating teaching resources,strengthen process management,promptly provide feedback and guidance,empower with data,and continuously improve teaching evaluation.Thus,a student-centered SPOC+PBL blended teaching sys-tem can be constructed to empower the transformation and innovation of talent cultivation in higher education.
文摘Objective:To construct a blended teaching model for surgical nursing based on the OBE(Outcome-Based Education)concept and explore its application effect in nursing education.Methods:A total of 220 undergraduate nursing students in the class of 2023 were selected as the main research subjects.The experimental group(110 students)adopted the OBE-based blended teaching model,while the control group(110 students)used conventional teaching methods.The learning effects,skill mastery,and clinical practice performance of the two groups were compared.Results:The experimental group significantly outperformed the control group in theoretical scores,practical skills,clinical application ability,and learning satisfaction,with statistically significant differences(P<0.05).Conclusion:The OBE-based blended teaching model has significant teaching advantages,which can effectively improve the comprehensive quality of undergraduate nursing students,enhance their clinical adaptability and innovative thinking,and is worthy of widespread promotion.
基金The fund from Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)under contract No.SML2021SP310the National Natural Science Foundation of China under contract Nos 42227901 and 42475061the Key R&D Program of Zhejiang Province under contract No.2024C03257.
文摘In this study,we conducted an experiment to construct multi-model ensemble(MME)predictions for the El Niño-Southern Oscillation(ENSO)using a neural network,based on hindcast data released from five coupled oceanatmosphere models,which exhibit varying levels of complexity.This nonlinear approach demonstrated extraordinary superiority and effectiveness in constructing ENSO MME.Subsequently,we employed the leave-one-out crossvalidation and the moving base methods to further validate the robustness of the neural network model in the formulation of ENSO MME.In conclusion,the neural network algorithm outperforms the conventional approach of assigning a uniform weight to all models.This is evidenced by an enhancement in correlation coefficients and reduction in prediction errors,which have the potential to provide a more accurate ENSO forecast.
