Ice-going ships play a crucial role in polar transportation and resource extraction.Different from the existing modeling approach which assumes that ships remain stationary,dynamic overset grid technology and DFBI(Dyn...Ice-going ships play a crucial role in polar transportation and resource extraction.Different from the existing modeling approach which assumes that ships remain stationary,dynamic overset grid technology and DFBI(Dynamic Fluid-Body Interaction)method are employed in this paper to enable the free-running motion of the ship in modeling.A numerical model capable of simulating a ship navigating through pack ice area is proposed,which uses Computational Fluid Dynamics(CFD)method to solve the flow field and applies the Discrete Element Method(DEM)to simulate ship-ice and ice-ice interactions.Besides,the proposed high-precision method for generating pack ice area can be used in conjunction with the proposed numerical model.By comparing the numerical results with the available model test data and experimental observations,the effectiveness of the numerical model is validated,demonstrating its strong capability of predicting resistance and simulating ship navigation in pack ice,as well as its significant potential and applicability for further studies.展开更多
To improve the compactness and properties of C/C-SiC-ZrC composites produced by precursor infiltration and pyrolysis(PIP)method,the low-temperature reactive melt infiltration(RMI)process was used to seal the composite...To improve the compactness and properties of C/C-SiC-ZrC composites produced by precursor infiltration and pyrolysis(PIP)method,the low-temperature reactive melt infiltration(RMI)process was used to seal the composites using Zr_(2)Cu as the filler.The microstructure,mechanical properties,and ablation properties of the Zr_(2)Cu packed composites were analyzed.Results show that during Zr_(2)Cu impregnation,the melt efficiently fills the large pores of the composites and is converted to ZrCu due to a partial reaction of zirconium with carbon.This results in an increase in composite density from 1.91 g/cm^(3)to 2.24 g/cm^(3)and a reduction in open porosity by 27.35%.Additionally,the flexural strength of Zr_(2)Cu packed C/C-SiC-ZrC composites is improved from 122.78±8.09 MPa to 135.53±5.40 MPa.After plasma ablation for 20 s,the modified composites demonstrate superior ablative resistance compared to PIP C/C-SiC-ZrC,with mass ablation and linear ablation rates of 2.77×10^(−3)g/s and 2.60×10^(−3)mm/s,respectively.The“selftranspiration”effect of the low-melting point copper-containing phase absorbs the heat of the plasma flame,further reducing the ablation temperature and promoting the formation of refined ZrO_(2)particles within the SiO_(2)melting layer.This provides more stable erosion protection for Zr_(2)Cu packed C/C-SiC-ZrC composites.展开更多
With the rapid development of the new energy automotive industry,the enhancement of lithium battery performance and production efficiency has become critical.This article explores the application of artificial intelli...With the rapid development of the new energy automotive industry,the enhancement of lithium battery performance and production efficiency has become critical.This article explores the application of artificial intelligence technology in the lithium battery module PACK line,analyzing how it optimizes the production process and improves production efficiency,and predicts future development trends.The PACK line is an important link in battery manufacturing,involving complex processes such as cell sorting,welding,assembly and testing.The application of AI technology in image recognition,data analysis and predictive maintenance provides new solutions for the intelligent upgrading of the PACK line.This article describes the process of the PACK line in detail,analyzes the challenges under current technological levels,and reviews the application cases of AI technology in the manufacturing industry.The study aims to provide theoretical and practical guidance for the intelligent development of lithium battery module PACK lines,discussing the integration of AI technology,its actual performance,technical challenges,and solutions.It is expected that AI technology will play a greater role in the PACK line,and future research will focus on improving the adaptability of models,developing efficient algorithms,and further integrating into the production line.展开更多
The large molecular weight and high hydrophilicity of chloramphenicol(CAP) residuals in wastewater led to severe degradation difficulty,which propelled the development of new wastewater degradation processes and react...The large molecular weight and high hydrophilicity of chloramphenicol(CAP) residuals in wastewater led to severe degradation difficulty,which propelled the development of new wastewater degradation processes and reactors based on process intensification.This study enhanced the CAP degradation by ozone/peroxydisulfate(PDS) advanced oxidation process in a submerged rotating packed bed(SRPB)reactor.Compared the usage of different oxidants,it was indicated that the combination of O_(3) and PDS exhibited a higher degradation efficiency than ozone and PDS alone.The more desired degradation efficiency could be achieved at the operating conditions of ascending PDS concentration,SRPB rotational speed,ozone concentration,reduced initial CAP concentration,and the water qualities of ascended pH,lower Cl^(-)and initial CO_(3)^(2-) concentrations.Under the optimized conditions of C_(CAP)=20 mg·L^(-1),C_(O3)=30 mg·L^(-1),C_(PDS)=100 mg·L^(-1),and N=400 r·min^(-1),and water qualities of pH=10,the maximum chloramphenicol degradation efficiency of 97% and kinetic constant of 0.23 min^(-1) were achieved after treating 16 min.A comparison of the results with previously reported advanced oxidation processes of CAP indicated that the enhanced O^(3)/PDS advanced oxidation system using the SRPB can significantly improve the degradation efficiency of CAP.展开更多
AIM:To assess the variations in photoreceptor cell packing density(PCPD)across the retina among young healthy individuals with emmetropia,low and moderate myopia.METHODS:High-resolution adaptive optics scanning laser ...AIM:To assess the variations in photoreceptor cell packing density(PCPD)across the retina among young healthy individuals with emmetropia,low and moderate myopia.METHODS:High-resolution adaptive optics scanning laser ophthalmoscopy(AOSLO)systems were utilized for retinal imaging with a large sampling window of 700μm×700μm.The study cohort included 14 emmetropic[spherical equivalent(SE)ranged+0.5 to-0.5 D],15 low myopic(SE ranged-0.5 to-3 D)and 21 moderate myopic(SE ranged-3 to-6 D)healthy young adults.Photoreceptors at 3°temporal,6°superior and inferior 6°were captured.Statistical analysis was then performed to obtain PCPD and cell spacing.RESULTS:The average age of participants was 22.54±2.86(ranged 20–30y)with no difference among 3 groups.At 3°temporal,the emmetropic group exhibited the highest PCPD of 15186.16±2050.54 cells/mm^(2),while the low and moderate myopic groups had PCPD of 14009.15±1073.01 and 13466.92±1121.71 cells/mm2,respectively.At 3°temporal,the emmetropic group also had the smallest cell spacing at 6.66±0.26 mm,compared to 6.85±0.26 and 6.91±0.28 mm for the low and moderate myopic groups,respectively.Compared to the emmetropic group,at 3°temporal,the myopic groups showed significantly reduced PCPD(low myopia:P=0.032;moderate myopia:P=0.001).At 6°inferior,the moderate myopic group exhibited a significant decrease in PCPD(P=0.013),while at 6°superior,there were no significant statistical differences in PCPD for the low and moderate myopic groups(P>0.05).In comparison to the emmetropic group,only the moderate myopic group showed significantly increased cell spacing at all three positions(temporal 3°:P=0.011,superior 6°:P=0.046,inferior 6°:P=0.013).Correlation analysis revealed a positive correlation between PCPD and axial length changes(P<0.05).CONCLUSION:Reduced PCPD and increased cell spacing strongly correlated with refractive error in mild to moderate myopic eyes,especially at 6°inferior to the fovea and the decreased PCPD in the macular region of myopic patients may be associated with increased axial lengthinduced retinal stretching.展开更多
This paper introduces a kind of substitute bench testing method for vehicle application development and testing method of the test requirements,including battery fast conversion cycle test equipment,enter type incubat...This paper introduces a kind of substitute bench testing method for vehicle application development and testing method of the test requirements,including battery fast conversion cycle test equipment,enter type incubator,liquid-cooled machine and ancillary equipment composed of a set of test system,through the walk-in constant temperature box to simulate the new energy vehicles under different environmental conditions of the test requirements,Liquid-cooled machine and auxiliary parts to complete the battery thermal management system need cooling fluid conditions,the battery conversion cycle test equipment to simulate the dc fast charging way of filling pile,complete battery thermal management system test,shorten the filling fast charging time and improve battery fast charge security,for troubleshooting and data collection and analysis,Improve work efficiency,save costs,and eliminate customer anxiety about battery life and charging time.展开更多
Two-dimensional energetic materials(2DEMs),characterized by their exceptional interlayer sliding properties,are recognized as exemplar of low-sensitivity energetic materials.However,the diversity of available 2DEMs is...Two-dimensional energetic materials(2DEMs),characterized by their exceptional interlayer sliding properties,are recognized as exemplar of low-sensitivity energetic materials.However,the diversity of available 2DEMs is severely constrained by the absence of efficient methods for rapidly predicting crystal packing modes from molecular structures,impeding the high-throughput rational design of such materials.In this study,we employed quantified indicators,such as hydrogen bond dimension and maximum planar separation,to quickly screen 172DEM and 16 non-2DEM crystal structures from a crystal database.They were subsequently compared and analyzed,focusing on hydrogen bond donor-acceptor combinations,skeleton features,and intermolecular interactions.Our findings suggest that theπ-πpacking interaction energy is a key determinant in the formation of layered packing modes by planar energetic molecules,with its magnitude primarily influenced by the strongest dimericπ-πinteraction(π-π2max).Consequently,we have delineated a critical threshold forπ-π2max to discern layered packing modes and formulated a theoretical model for predictingπ-π2max,grounded in molecular electrostatic potential and dipole moment analysis.The predictive efficacy of this model was substantiated through external validation on a test set comprising 31 planar energetic molecular crystals,achieving an accuracy of 84%and a recall of 75%.Furthermore,the proposed model shows superior classification predictive performance compared to typical machine learning methods,such as random forest,on the external validation samples.This contribution introduces a novel methodology for the identification of crystal packing modes in 2DEMs,potentially accelerating the design and synthesis of high-energy,low-sensitivity 2DEMs.展开更多
Modern chromatography is increasingly focused on miniaturization and integration. Compared to conventional liquid chromatography, microfluidic chip liquid chromatography(microchip-LC) has the potential due to its zero...Modern chromatography is increasingly focused on miniaturization and integration. Compared to conventional liquid chromatography, microfluidic chip liquid chromatography(microchip-LC) has the potential due to its zero-dead volume connection and ease of integration. Nano-sized packings have the potential to significantly enhance separation performance in microchip-LC. However, their application has been hindered by packing difficulties. This study presents a method for packing nano-sized silica particles into a microchannel as the stationary phase. The microchip-LC packed column was prepared by combining the weir and the porous silica single-particle as frit to retain the packing particles. A surface tensionbased single-particle picking technique was established to insert porous single-particle frit into glass microchannels. Additionally, we developed a slurry packing method that utilizes air pressure to inject nano-sized packing into the microchannel. Pressure-driven chromatographic separation was performed using this nano-packed column integrated into a glass microchip. The mixture of four PAHs was successfully separated within just 8 min using a 5 mm separation channel length, achieving high theoretical plates(10~6plates/m). Overall, these findings demonstrate the potential of utilizing nano-sized packings for enhancing chromatographic performance in microchip systems.展开更多
For graphs G and H,an embedding of G into H is an injection ϕ:V(G)→V(H)such that ϕ(a)ϕ(b)∈E(H)whenever ab∈E(G).A packing of p graphs G_(1),G_(2),…,G_(p) into H is a p-tupleΦ=(ϕ_(1),ϕ_(2),…,ϕ_(p))such that,for i=...For graphs G and H,an embedding of G into H is an injection ϕ:V(G)→V(H)such that ϕ(a)ϕ(b)∈E(H)whenever ab∈E(G).A packing of p graphs G_(1),G_(2),…,G_(p) into H is a p-tupleΦ=(ϕ_(1),ϕ_(2),…,ϕ_(p))such that,for i=1,2,…,p,ϕ_(i) is an embedding of Gi into H and the p sets ϕ_(i)(E(G_(i)))are mutually disjoint.Motivated by the"Tree Packing Conjecture"made by Gyar fas and Lehel,Wang Hong conjectured that for each k-partite tree,there is a packing of two copies of T(X)into a complete k-partite graph B_(n+m)(Y),where m=■k/2」..In this paper,we confirm this conjecture for k=4.展开更多
The precipitation of topologically close-packed(TCP)phases is the result of microstructure instabilities of Ni-based superalloys.This review seeks to comprehensively collate all the available information on TCP phases...The precipitation of topologically close-packed(TCP)phases is the result of microstructure instabilities of Ni-based superalloys.This review seeks to comprehensively collate all the available information on TCP phases in SX superalloys based on the latest findings.First,the thermodynamics and kinetics of the TCP phase precipitation are introduced.Meanwhile,the morphology,composition and orientation of TCP phases and their sequential transformation are summarized in detail.Further,the factors affecting the precipitation of these phases are sorted out.Besides,the proposed damage mechanisms of TCP phases are listed.Finally,several control and prediction methods of the TCP phase precipitation are reviewed,so the alloy designer can better balance the relationship between microstructure stabilities and properties of the superalloy.展开更多
Accurate capacity estimation is of great importance for the reliable state monitoring,timely maintenance,and second-life utilization of lithium-ion batteries.Despite numerous works on battery capacity estimation using...Accurate capacity estimation is of great importance for the reliable state monitoring,timely maintenance,and second-life utilization of lithium-ion batteries.Despite numerous works on battery capacity estimation using laboratory datasets,most of them are applied to battery cells and lack satisfactory fidelity when extended to real-world electric vehicle(EV)battery packs.The challenges intensify for large-sized EV battery packs,where unpredictable operating profiles and low-quality data acquisition hinder precise capacity estimation.To fill the gap,this study introduces a novel data-driven battery pack capacity estimation method grounded in field data.The proposed approach begins by determining labeled capacity through an innovative combination of the inverse ampere-hour integral,open circuit voltage-based,and resistance-based correction methods.Then,multiple health features are extracted from incremental capacity curves,voltage curves,equivalent circuit model parameters,and operating temperature to thoroughly characterize battery aging behavior.A feature selection procedure is performed to determine the optimal feature set based on the Pearson correlation coefficient.Moreover,a convolutional neural network and bidirectional gated recurrent unit,enhanced by an attention mechanism,are employed to estimate the battery pack capacity in real-world EV applications.Finally,the proposed method is validated with a field dataset from two EVs,covering approximately 35,000 kilometers.The results demonstrate that the proposed method exhibits better estimation performance with an error of less than 1.1%compared to existing methods.This work shows great potential for accurate large-sized EV battery pack capacity estimation based on field data,which provides significant insights into reliable labeled capacity calculation,effective features extraction,and machine learning-enabled health diagnosis.展开更多
The liquid-cooled battery energy sto rage system(LCBESS) has gained significant attention due to its superior thermal management capacity.However,liquid-cooled battery pack(LCBP) usually has a high sealing level above...The liquid-cooled battery energy sto rage system(LCBESS) has gained significant attention due to its superior thermal management capacity.However,liquid-cooled battery pack(LCBP) usually has a high sealing level above IP65,which can trap flammable and explosive gases from battery thermal runaway and cause explosions.This poses serious safety risks and challenges for LCBESS.In this study,we tested overcharged battery inside a commercial LCBP and found that the conventionally mechanical pressure relief valve(PRV) on the LCBP had a delayed response and low-pressure relief efficiency.A realistic 20-foot model of an energy storage cabin was constructed using the Flacs finite element simulation software.Comparative studies were conducted to evaluate the pressure relief efficiency and the influence on neighboring battery packs in case of internal explosions,considering different sizes and installation positions of the PRV.Here,a newly developed electric-controlled PRV integrated with battery fault detection is introduced,capable of starting within 50 ms of the battery safety valve opening.Furthermore,the PRV was integrated with the battery management system and changed the battery charging and discharging strategy after the PRV was opened.Experimental tests confirmed the efficacy of this method in preventing explosions.This paper addresses the safety concerns associated with LCBPs and proposes an effective solution for explosion relief.展开更多
In this study,the fluid flow and mixing process in an impinging stream-rotating packed bed(IS-RPB)is simulated by using a new three-dimensional computational fluid dynamics model.Specifically,the gaseliquid flow is si...In this study,the fluid flow and mixing process in an impinging stream-rotating packed bed(IS-RPB)is simulated by using a new three-dimensional computational fluid dynamics model.Specifically,the gaseliquid flow is simulated by the Euler-Euler model,the hydrodynamics of the reactor is predicted by the RNG k-εmethod,and the high-gravity environment is simulated by the sliding mesh model.The turbulent mass transfer process is characterized by the concentration variance c^(2) and its dissipation rateεc formulations,and therefore the turbulent mass diffusivity can be directly obtained.The simulated segregation index Xs is in agreement with our previous experimental results.The simulated results reveal that the fringe effect of IS can be offset by the end effect at the inner radius of RPB,so the investigation of the coupling mechanism between IS and RPB is critical to intensify the mixing process in IS-RPB.展开更多
Cell-to-cell variations(CtCV) compromise the electrochemical performance of battery packs, yet the evolutional mechanism and quantitative impacts of CtCV on the pack's fast-charging performance remain unexplored. ...Cell-to-cell variations(CtCV) compromise the electrochemical performance of battery packs, yet the evolutional mechanism and quantitative impacts of CtCV on the pack's fast-charging performance remain unexplored. This knowledge gap is vital for the proliferation of electric vehicles. This study underlies the relationship between CtCV and charging performance by assessing the pack's charge speed, final electric quantity, and temperature consistency. Cell variations and pack status are depicted using 2D parameter diagrams, and an m PnS configured pack model is built upon a decomposed electrode cell model.Variations in three single electric parameters, i.e., capacity(Q), electric quantity(E), and internal resistance(R), and their dual interactions, i.e., E-Q and R-Q, are analyzed carefully. The results indicate that Q variations predominantly affect the final electric quantity of the pack, while R variations impact the charge speed most. With incremental variances in cell parameters, the pack's fast-charging capability first declines linearly and then deteriorates sharply as variations intensify. This research elucidates the correlations between pack charging capabilities and cell variations, providing essential insights for optimizing cell sorting and assembly, battery management design, and charging protocol development for battery packs.展开更多
Battery pack capacity estimation under real-world operating conditions is important for battery performance optimization and health management,contributing to the reliability and longevity of batterypowered systems.Ho...Battery pack capacity estimation under real-world operating conditions is important for battery performance optimization and health management,contributing to the reliability and longevity of batterypowered systems.However,complex operating conditions,coupling cell-to-cell inconsistency,and limited labeled data pose great challenges to accurate and robust battery pack capacity estimation.To address these issues,this paper proposes a hierarchical data-driven framework aimed at enhancing the training of machine learning models with fewer labeled data.Unlike traditional data-driven methods that lack interpretability,the hierarchical data-driven framework unveils the“mechanism”of the black box inside the data-driven framework by splitting the final estimation target into cell-level and pack-level intermediate targets.A generalized feature matrix is devised without requiring all cell voltages,significantly reducing the computational cost and memory resources.The generated intermediate target labels and the corresponding features are hierarchically employed to enhance the training of two machine learning models,effectively alleviating the difficulty of learning the relationship from all features due to fewer labeled data and addressing the dilemma of requiring extensive labeled data for accurate estimation.Using only 10%of degradation data,the proposed framework outperforms the state-of-the-art battery pack capacity estimation methods,achieving mean absolute percentage errors of 0.608%,0.601%,and 1.128%for three battery packs whose degradation load profiles represent real-world operating conditions.Its high accuracy,adaptability,and robustness indicate the potential in different application scenarios,which is promising for reducing laborious and expensive aging experiments at the pack level and facilitating the development of battery technology.展开更多
文摘Ice-going ships play a crucial role in polar transportation and resource extraction.Different from the existing modeling approach which assumes that ships remain stationary,dynamic overset grid technology and DFBI(Dynamic Fluid-Body Interaction)method are employed in this paper to enable the free-running motion of the ship in modeling.A numerical model capable of simulating a ship navigating through pack ice area is proposed,which uses Computational Fluid Dynamics(CFD)method to solve the flow field and applies the Discrete Element Method(DEM)to simulate ship-ice and ice-ice interactions.Besides,the proposed high-precision method for generating pack ice area can be used in conjunction with the proposed numerical model.By comparing the numerical results with the available model test data and experimental observations,the effectiveness of the numerical model is validated,demonstrating its strong capability of predicting resistance and simulating ship navigation in pack ice,as well as its significant potential and applicability for further studies.
基金Open Fund of Zhijian Laboratory,Rocket Force University of Engineering(2024-ZJSYS-KF02-09)National Natural Science Foundation of China(51902028,52272034)+1 种基金Key Research and Development Program of Shaanxi(2023JBGS-15)Fundamental Research Funds for the Central Universities(Changan University,300102313202,300102312406)。
文摘To improve the compactness and properties of C/C-SiC-ZrC composites produced by precursor infiltration and pyrolysis(PIP)method,the low-temperature reactive melt infiltration(RMI)process was used to seal the composites using Zr_(2)Cu as the filler.The microstructure,mechanical properties,and ablation properties of the Zr_(2)Cu packed composites were analyzed.Results show that during Zr_(2)Cu impregnation,the melt efficiently fills the large pores of the composites and is converted to ZrCu due to a partial reaction of zirconium with carbon.This results in an increase in composite density from 1.91 g/cm^(3)to 2.24 g/cm^(3)and a reduction in open porosity by 27.35%.Additionally,the flexural strength of Zr_(2)Cu packed C/C-SiC-ZrC composites is improved from 122.78±8.09 MPa to 135.53±5.40 MPa.After plasma ablation for 20 s,the modified composites demonstrate superior ablative resistance compared to PIP C/C-SiC-ZrC,with mass ablation and linear ablation rates of 2.77×10^(−3)g/s and 2.60×10^(−3)mm/s,respectively.The“selftranspiration”effect of the low-melting point copper-containing phase absorbs the heat of the plasma flame,further reducing the ablation temperature and promoting the formation of refined ZrO_(2)particles within the SiO_(2)melting layer.This provides more stable erosion protection for Zr_(2)Cu packed C/C-SiC-ZrC composites.
文摘With the rapid development of the new energy automotive industry,the enhancement of lithium battery performance and production efficiency has become critical.This article explores the application of artificial intelligence technology in the lithium battery module PACK line,analyzing how it optimizes the production process and improves production efficiency,and predicts future development trends.The PACK line is an important link in battery manufacturing,involving complex processes such as cell sorting,welding,assembly and testing.The application of AI technology in image recognition,data analysis and predictive maintenance provides new solutions for the intelligent upgrading of the PACK line.This article describes the process of the PACK line in detail,analyzes the challenges under current technological levels,and reviews the application cases of AI technology in the manufacturing industry.The study aims to provide theoretical and practical guidance for the intelligent development of lithium battery module PACK lines,discussing the integration of AI technology,its actual performance,technical challenges,and solutions.It is expected that AI technology will play a greater role in the PACK line,and future research will focus on improving the adaptability of models,developing efficient algorithms,and further integrating into the production line.
基金supported by the National Natural Science Foundation of China(22288102)。
文摘The large molecular weight and high hydrophilicity of chloramphenicol(CAP) residuals in wastewater led to severe degradation difficulty,which propelled the development of new wastewater degradation processes and reactors based on process intensification.This study enhanced the CAP degradation by ozone/peroxydisulfate(PDS) advanced oxidation process in a submerged rotating packed bed(SRPB)reactor.Compared the usage of different oxidants,it was indicated that the combination of O_(3) and PDS exhibited a higher degradation efficiency than ozone and PDS alone.The more desired degradation efficiency could be achieved at the operating conditions of ascending PDS concentration,SRPB rotational speed,ozone concentration,reduced initial CAP concentration,and the water qualities of ascended pH,lower Cl^(-)and initial CO_(3)^(2-) concentrations.Under the optimized conditions of C_(CAP)=20 mg·L^(-1),C_(O3)=30 mg·L^(-1),C_(PDS)=100 mg·L^(-1),and N=400 r·min^(-1),and water qualities of pH=10,the maximum chloramphenicol degradation efficiency of 97% and kinetic constant of 0.23 min^(-1) were achieved after treating 16 min.A comparison of the results with previously reported advanced oxidation processes of CAP indicated that the enhanced O^(3)/PDS advanced oxidation system using the SRPB can significantly improve the degradation efficiency of CAP.
基金Supported by National Natural Science Foundation of China(No.82271107).
文摘AIM:To assess the variations in photoreceptor cell packing density(PCPD)across the retina among young healthy individuals with emmetropia,low and moderate myopia.METHODS:High-resolution adaptive optics scanning laser ophthalmoscopy(AOSLO)systems were utilized for retinal imaging with a large sampling window of 700μm×700μm.The study cohort included 14 emmetropic[spherical equivalent(SE)ranged+0.5 to-0.5 D],15 low myopic(SE ranged-0.5 to-3 D)and 21 moderate myopic(SE ranged-3 to-6 D)healthy young adults.Photoreceptors at 3°temporal,6°superior and inferior 6°were captured.Statistical analysis was then performed to obtain PCPD and cell spacing.RESULTS:The average age of participants was 22.54±2.86(ranged 20–30y)with no difference among 3 groups.At 3°temporal,the emmetropic group exhibited the highest PCPD of 15186.16±2050.54 cells/mm^(2),while the low and moderate myopic groups had PCPD of 14009.15±1073.01 and 13466.92±1121.71 cells/mm2,respectively.At 3°temporal,the emmetropic group also had the smallest cell spacing at 6.66±0.26 mm,compared to 6.85±0.26 and 6.91±0.28 mm for the low and moderate myopic groups,respectively.Compared to the emmetropic group,at 3°temporal,the myopic groups showed significantly reduced PCPD(low myopia:P=0.032;moderate myopia:P=0.001).At 6°inferior,the moderate myopic group exhibited a significant decrease in PCPD(P=0.013),while at 6°superior,there were no significant statistical differences in PCPD for the low and moderate myopic groups(P>0.05).In comparison to the emmetropic group,only the moderate myopic group showed significantly increased cell spacing at all three positions(temporal 3°:P=0.011,superior 6°:P=0.046,inferior 6°:P=0.013).Correlation analysis revealed a positive correlation between PCPD and axial length changes(P<0.05).CONCLUSION:Reduced PCPD and increased cell spacing strongly correlated with refractive error in mild to moderate myopic eyes,especially at 6°inferior to the fovea and the decreased PCPD in the macular region of myopic patients may be associated with increased axial lengthinduced retinal stretching.
文摘This paper introduces a kind of substitute bench testing method for vehicle application development and testing method of the test requirements,including battery fast conversion cycle test equipment,enter type incubator,liquid-cooled machine and ancillary equipment composed of a set of test system,through the walk-in constant temperature box to simulate the new energy vehicles under different environmental conditions of the test requirements,Liquid-cooled machine and auxiliary parts to complete the battery thermal management system need cooling fluid conditions,the battery conversion cycle test equipment to simulate the dc fast charging way of filling pile,complete battery thermal management system test,shorten the filling fast charging time and improve battery fast charge security,for troubleshooting and data collection and analysis,Improve work efficiency,save costs,and eliminate customer anxiety about battery life and charging time.
基金support from National Natural Science Foundation of China(Grant Nos.22275145,22305189and 21875184)Natural Science Foundation of Shaanxi Province(Grant Nos.2022JC-10 and 2024JC-YBQN-0112).
文摘Two-dimensional energetic materials(2DEMs),characterized by their exceptional interlayer sliding properties,are recognized as exemplar of low-sensitivity energetic materials.However,the diversity of available 2DEMs is severely constrained by the absence of efficient methods for rapidly predicting crystal packing modes from molecular structures,impeding the high-throughput rational design of such materials.In this study,we employed quantified indicators,such as hydrogen bond dimension and maximum planar separation,to quickly screen 172DEM and 16 non-2DEM crystal structures from a crystal database.They were subsequently compared and analyzed,focusing on hydrogen bond donor-acceptor combinations,skeleton features,and intermolecular interactions.Our findings suggest that theπ-πpacking interaction energy is a key determinant in the formation of layered packing modes by planar energetic molecules,with its magnitude primarily influenced by the strongest dimericπ-πinteraction(π-π2max).Consequently,we have delineated a critical threshold forπ-π2max to discern layered packing modes and formulated a theoretical model for predictingπ-π2max,grounded in molecular electrostatic potential and dipole moment analysis.The predictive efficacy of this model was substantiated through external validation on a test set comprising 31 planar energetic molecular crystals,achieving an accuracy of 84%and a recall of 75%.Furthermore,the proposed model shows superior classification predictive performance compared to typical machine learning methods,such as random forest,on the external validation samples.This contribution introduces a novel methodology for the identification of crystal packing modes in 2DEMs,potentially accelerating the design and synthesis of high-energy,low-sensitivity 2DEMs.
基金supported by the National Natural Science Foundation of China (No.21936001)the Beijing Outstanding Young Scientist Program (No.BJJWZYJH01201910005017)。
文摘Modern chromatography is increasingly focused on miniaturization and integration. Compared to conventional liquid chromatography, microfluidic chip liquid chromatography(microchip-LC) has the potential due to its zero-dead volume connection and ease of integration. Nano-sized packings have the potential to significantly enhance separation performance in microchip-LC. However, their application has been hindered by packing difficulties. This study presents a method for packing nano-sized silica particles into a microchannel as the stationary phase. The microchip-LC packed column was prepared by combining the weir and the porous silica single-particle as frit to retain the packing particles. A surface tensionbased single-particle picking technique was established to insert porous single-particle frit into glass microchannels. Additionally, we developed a slurry packing method that utilizes air pressure to inject nano-sized packing into the microchannel. Pressure-driven chromatographic separation was performed using this nano-packed column integrated into a glass microchip. The mixture of four PAHs was successfully separated within just 8 min using a 5 mm separation channel length, achieving high theoretical plates(10~6plates/m). Overall, these findings demonstrate the potential of utilizing nano-sized packings for enhancing chromatographic performance in microchip systems.
基金Supported by the National Natural Science Foundation of China(12071334)。
文摘For graphs G and H,an embedding of G into H is an injection ϕ:V(G)→V(H)such that ϕ(a)ϕ(b)∈E(H)whenever ab∈E(G).A packing of p graphs G_(1),G_(2),…,G_(p) into H is a p-tupleΦ=(ϕ_(1),ϕ_(2),…,ϕ_(p))such that,for i=1,2,…,p,ϕ_(i) is an embedding of Gi into H and the p sets ϕ_(i)(E(G_(i)))are mutually disjoint.Motivated by the"Tree Packing Conjecture"made by Gyar fas and Lehel,Wang Hong conjectured that for each k-partite tree,there is a packing of two copies of T(X)into a complete k-partite graph B_(n+m)(Y),where m=■k/2」..In this paper,we confirm this conjecture for k=4.
基金financially supported by the National Science and Technology Major Project(No.2019-VII-0019-0161)Science Center for Gas Turbine Project(No.P2021-A-Ⅳ-001-002)+1 种基金National Key Research and Development Program of China under Grant(No.2017YFA0700704)National Natural Science Foundation of China(No.51971214).
文摘The precipitation of topologically close-packed(TCP)phases is the result of microstructure instabilities of Ni-based superalloys.This review seeks to comprehensively collate all the available information on TCP phases in SX superalloys based on the latest findings.First,the thermodynamics and kinetics of the TCP phase precipitation are introduced.Meanwhile,the morphology,composition and orientation of TCP phases and their sequential transformation are summarized in detail.Further,the factors affecting the precipitation of these phases are sorted out.Besides,the proposed damage mechanisms of TCP phases are listed.Finally,several control and prediction methods of the TCP phase precipitation are reviewed,so the alloy designer can better balance the relationship between microstructure stabilities and properties of the superalloy.
基金supported in part by the National Key Research and Development Program of China(No.2022YFB3305403)Project of basic research funds for central universities(2022CDJDX006)+1 种基金Talent Plan Project of Chongqing(No.cstc2021ycjhbgzxm0295)National Natural Science Foundation of China(No.52111530194)。
文摘Accurate capacity estimation is of great importance for the reliable state monitoring,timely maintenance,and second-life utilization of lithium-ion batteries.Despite numerous works on battery capacity estimation using laboratory datasets,most of them are applied to battery cells and lack satisfactory fidelity when extended to real-world electric vehicle(EV)battery packs.The challenges intensify for large-sized EV battery packs,where unpredictable operating profiles and low-quality data acquisition hinder precise capacity estimation.To fill the gap,this study introduces a novel data-driven battery pack capacity estimation method grounded in field data.The proposed approach begins by determining labeled capacity through an innovative combination of the inverse ampere-hour integral,open circuit voltage-based,and resistance-based correction methods.Then,multiple health features are extracted from incremental capacity curves,voltage curves,equivalent circuit model parameters,and operating temperature to thoroughly characterize battery aging behavior.A feature selection procedure is performed to determine the optimal feature set based on the Pearson correlation coefficient.Moreover,a convolutional neural network and bidirectional gated recurrent unit,enhanced by an attention mechanism,are employed to estimate the battery pack capacity in real-world EV applications.Finally,the proposed method is validated with a field dataset from two EVs,covering approximately 35,000 kilometers.The results demonstrate that the proposed method exhibits better estimation performance with an error of less than 1.1%compared to existing methods.This work shows great potential for accurate large-sized EV battery pack capacity estimation based on field data,which provides significant insights into reliable labeled capacity calculation,effective features extraction,and machine learning-enabled health diagnosis.
基金sponsored by the Science and Technology Program of State Grid Corporation of China(4000-202355090A-1-1ZN)。
文摘The liquid-cooled battery energy sto rage system(LCBESS) has gained significant attention due to its superior thermal management capacity.However,liquid-cooled battery pack(LCBP) usually has a high sealing level above IP65,which can trap flammable and explosive gases from battery thermal runaway and cause explosions.This poses serious safety risks and challenges for LCBESS.In this study,we tested overcharged battery inside a commercial LCBP and found that the conventionally mechanical pressure relief valve(PRV) on the LCBP had a delayed response and low-pressure relief efficiency.A realistic 20-foot model of an energy storage cabin was constructed using the Flacs finite element simulation software.Comparative studies were conducted to evaluate the pressure relief efficiency and the influence on neighboring battery packs in case of internal explosions,considering different sizes and installation positions of the PRV.Here,a newly developed electric-controlled PRV integrated with battery fault detection is introduced,capable of starting within 50 ms of the battery safety valve opening.Furthermore,the PRV was integrated with the battery management system and changed the battery charging and discharging strategy after the PRV was opened.Experimental tests confirmed the efficacy of this method in preventing explosions.This paper addresses the safety concerns associated with LCBPs and proposes an effective solution for explosion relief.
基金supported by the National Natural Science Foundation of China (22208328, 22378370 and 22108261)Fundamental Research Program of Shanxi Province(20210302124618)
文摘In this study,the fluid flow and mixing process in an impinging stream-rotating packed bed(IS-RPB)is simulated by using a new three-dimensional computational fluid dynamics model.Specifically,the gaseliquid flow is simulated by the Euler-Euler model,the hydrodynamics of the reactor is predicted by the RNG k-εmethod,and the high-gravity environment is simulated by the sliding mesh model.The turbulent mass transfer process is characterized by the concentration variance c^(2) and its dissipation rateεc formulations,and therefore the turbulent mass diffusivity can be directly obtained.The simulated segregation index Xs is in agreement with our previous experimental results.The simulated results reveal that the fringe effect of IS can be offset by the end effect at the inner radius of RPB,so the investigation of the coupling mechanism between IS and RPB is critical to intensify the mixing process in IS-RPB.
基金supported by the National Natural Science Foundation of China under No. 52177217the Postdoctoral Innovative Talents Support Program under No. BX20240232。
文摘Cell-to-cell variations(CtCV) compromise the electrochemical performance of battery packs, yet the evolutional mechanism and quantitative impacts of CtCV on the pack's fast-charging performance remain unexplored. This knowledge gap is vital for the proliferation of electric vehicles. This study underlies the relationship between CtCV and charging performance by assessing the pack's charge speed, final electric quantity, and temperature consistency. Cell variations and pack status are depicted using 2D parameter diagrams, and an m PnS configured pack model is built upon a decomposed electrode cell model.Variations in three single electric parameters, i.e., capacity(Q), electric quantity(E), and internal resistance(R), and their dual interactions, i.e., E-Q and R-Q, are analyzed carefully. The results indicate that Q variations predominantly affect the final electric quantity of the pack, while R variations impact the charge speed most. With incremental variances in cell parameters, the pack's fast-charging capability first declines linearly and then deteriorates sharply as variations intensify. This research elucidates the correlations between pack charging capabilities and cell variations, providing essential insights for optimizing cell sorting and assembly, battery management design, and charging protocol development for battery packs.
基金supported by the National Outstanding Youth Science Fund Project of National Natural Science Foundation of China[Grant No.52222708]the Natural Science Foundation of Beijing Municipality[Grant No.3212033]。
文摘Battery pack capacity estimation under real-world operating conditions is important for battery performance optimization and health management,contributing to the reliability and longevity of batterypowered systems.However,complex operating conditions,coupling cell-to-cell inconsistency,and limited labeled data pose great challenges to accurate and robust battery pack capacity estimation.To address these issues,this paper proposes a hierarchical data-driven framework aimed at enhancing the training of machine learning models with fewer labeled data.Unlike traditional data-driven methods that lack interpretability,the hierarchical data-driven framework unveils the“mechanism”of the black box inside the data-driven framework by splitting the final estimation target into cell-level and pack-level intermediate targets.A generalized feature matrix is devised without requiring all cell voltages,significantly reducing the computational cost and memory resources.The generated intermediate target labels and the corresponding features are hierarchically employed to enhance the training of two machine learning models,effectively alleviating the difficulty of learning the relationship from all features due to fewer labeled data and addressing the dilemma of requiring extensive labeled data for accurate estimation.Using only 10%of degradation data,the proposed framework outperforms the state-of-the-art battery pack capacity estimation methods,achieving mean absolute percentage errors of 0.608%,0.601%,and 1.128%for three battery packs whose degradation load profiles represent real-world operating conditions.Its high accuracy,adaptability,and robustness indicate the potential in different application scenarios,which is promising for reducing laborious and expensive aging experiments at the pack level and facilitating the development of battery technology.
