A critical challenge of any blast simulation facility is in producing the widest possible pressure-impulse range for matching against equivalent high-explosive events.Shock tubes and blast simulators are often constra...A critical challenge of any blast simulation facility is in producing the widest possible pressure-impulse range for matching against equivalent high-explosive events.Shock tubes and blast simulators are often constrained with the lack of effective ways to control blast wave profiles and as a result have a limited performance range.Some wave shaping techniques employed in some facilities are reviewed but often necessitate extensive geometric modifications,inadvertently cause flow anomalies,and/or are only applicable under very specific configurations.This paper investigates controlled venting as an expedient way for waveforms to be tuned without requiring extensive modifications to the driver or existing geometry and could be widely applied by existing and future blast simulation and shock tube facilities.The use of controlled venting is demonstrated experimentally using the Advanced Blast Simulator(shock tube)at the Australian National Facility of Physical Blast Simulation and via numerical flow simulations with Computational Fluid Dynamics.Controlled venting is determined as an effective method for mitigating the impact of re-reflected waves within the blast simulator.This control method also allows for the adjustment of parameters such as tuning the peak overpressure,the positive phase duration,and modifying the magnitude of the negative phase and the secondary shock of the blast waves.This paper is concluded with an illustration of the potential expanded performance range of the Australian blast simulation facility when controlled venting for blast waveform tailoring as presented in this paper is applied.展开更多
To investigate the in vitro digestion and fermentation properties of soybean oligosaccharides(SBOS)extracted from defatted soybean meal,the changes in monosaccharide composition and molecular mass were analyzed.Subseq...To investigate the in vitro digestion and fermentation properties of soybean oligosaccharides(SBOS)extracted from defatted soybean meal,the changes in monosaccharide composition and molecular mass were analyzed.Subsequently,the effect of SBOS on microbial community structure and metabolites was studied by 16S rRNA gene sequencing and untargeted metabolomics based on liquid chromatography-mass spectrometry.Results showed that SBOS was not easily enzymolyzed during simulated digestion and could reach the large intestine through the digestive system.The significant decrease in the molecular mass of SBOS after in vitro fermentation indicated its utilization by the gut microbiota,which increased the contents of short-chain fatty acids and lactic acid,thereby reducing the pH of the fermentation broth.Moreover,the core community was found to consist of Blautia,Lactobacillaceae,and Pediococcus.SBOS up-regulated beneficial differential metabolites such as myo-inositol,lactose,and glucose,which were closely related to galactose,amino sugar,and nucleotide sugar metabolism.This study will provide a reference for exploring the relationship between the gut microbiota and the metabolites of SBOS,and provide a basis for the development and application of SBOS as an ingredient for functional products.展开更多
The graded density impactor(GDI)dynamic loading technique is crucial for acquiring the dynamic physical property parameters of materials used in weapons.The accuracy and timeliness of GDI structural design are key to ...The graded density impactor(GDI)dynamic loading technique is crucial for acquiring the dynamic physical property parameters of materials used in weapons.The accuracy and timeliness of GDI structural design are key to achieving controllable stress-strain rate loading.In this study,we have,for the first time,combined one-dimensional fluid computational software with machine learning methods.We first elucidated the mechanisms by which GDI structures control stress and strain rates.Subsequently,we constructed a machine learning model to create a structure-property response surface.The results show that altering the loading velocity and interlayer thickness has a pronounced regulatory effect on stress and strain rates.In contrast,the impedance distribution index and target thickness have less significant effects on stress regulation,although there is a matching relationship between target thickness and interlayer thickness.Compared with traditional design methods,the machine learning approach offers a10^(4)—10^(5)times increase in efficiency and the potential to achieve a global optimum,holding promise for guiding the design of GDI.展开更多
The microstructures and thermodynamic properties of mixed systems comprising pyridinium ionic liquid[HPy][BF_(4)]and acetonitrile at different mole fractions were studied using molecular dynamics simulation in this wo...The microstructures and thermodynamic properties of mixed systems comprising pyridinium ionic liquid[HPy][BF_(4)]and acetonitrile at different mole fractions were studied using molecular dynamics simulation in this work.The following properties were determined:density,self-diffusion coefficient,excess molar volume,and radial distribution function.The results show that with an increase in the mole fraction of[HPy][BF_(4)],the self-diffusion coefficient decreases.Additionally,the excess molar volume initially decreases,reaches a minimum,and then increases.The rules of radial distribution functions(RDFs)of characteristic atoms are different.With increasing the mole fraction of[HPy][BF_(4)],the first peak of the RDFs of HA1-F decreases,while that of CT6-CT6 rises at first and then decreases.This indicates that the solvent molecules affect the polar and non-polar regions of[HPy][BF_(4)]differently.展开更多
The performance of a material is directly affected by its microstructural development during the solidification phase. Discrete cellular automaton (CA) models are widelyused in materials science to simulate and predic...The performance of a material is directly affected by its microstructural development during the solidification phase. Discrete cellular automaton (CA) models are widelyused in materials science to simulate and predict microstructural growth. This review comprehensively explains the developments and applications of CA in solidification structure simulation, including the theoretical underpinnings, computational procedures, software development, and recent advances. Summarizes the potential and limitations of cellular automata in understanding microstructure evolution during solidification, explores the evolution of microstructures during solidification, and adds to our existing knowledge of cellular automaton theory. Finally, the research trend in simulating the evolution of the solidification microstructure using cellular automaton theory is explored.展开更多
Chloride ions(Cl^(-))have been shown to impact the long-lasting nature of reinforced concrete.However,Cl^(-)that are already bound inside the concrete will not lead to the deterioration of the concrete’s characterist...Chloride ions(Cl^(-))have been shown to impact the long-lasting nature of reinforced concrete.However,Cl^(-)that are already bound inside the concrete will not lead to the deterioration of the concrete’s characteristics.The composition of the cement-based material,including the type of cement and auxiliary materials,greatly influences the ability of the material to bind Cl^(-),and varied components result in varying binding beha-vior of the Cl^(-).Simultaneously,the Cl^(-)binding process in concrete is influenced by both the internal and exterior surroundings,as well as the curing practices.These factors impact the hydration process of the cement and the internal pore structure of the concrete.Currently,mathematical theories and molecular dynamics simulations have increasingly been employed as the prevalent methods for examining the binding behaviors of Cl^(-)in concrete.These techniques are extensively utilized for predicting the lifespan and conducting microscopic studies of reinforced concrete in Cl^(-)settings.This work proposes recommendations for future research based on a summary of experimental and simulation investigations on Cl^(-)binding.Which will offer theoretical guidance for studying the binding of Cl^(-)in cement-based materials.展开更多
To address the limitations of existing coupling methods in aero-engine system simulation,which fail to adaptively adjust iterative parameters and coupling relationships,which can result in low efficiency and in⁃stabil...To address the limitations of existing coupling methods in aero-engine system simulation,which fail to adaptively adjust iterative parameters and coupling relationships,which can result in low efficiency and in⁃stability,this study introduces a‘Dynamic Event-Driven Co-Simulation’algorithm integrated with decision tree algorithms.This algorithm separates the overall coupling relationships and the main solver from the primary mod⁃el,utilizing a dynamic event monitoring module to adaptively adjust simulation strategies,including iteration pa⁃rameters,coupling relationships,and convergence criteria.This facilitates efficient adaptive simulations of dy⁃namic events while balancing solution accuracy and computational efficiency.The research focuses on a twinshaft turbofan engine,establishing six system-level models that encompass overall performance and various sub⁃systems based on three coupling methods,along with a multidisciplinary multi-fidelity simulation framework in⁃corporating a 3D CFD nozzle model.The study tests both model exchange and coupled simulation methods under a 14 s transient acceleration and deceleration scenario.In a 100%throttle condition,a high-fidelity nozzle model is used to analyze the sensitivity of different convergence criteria on computational efficiency and accuracy.Re⁃sults indicate that the accuracy and efficiency achieved with this method are comparable to those of PROOSIS soft⁃ware(18 s and 35 s,respectively),while being 71%more efficient than Simulink software(62 s and 120 s,re⁃spectively).Furthermore,appropriately relaxing the convergence criteria for the 0D model(from 10-6 to 10-4)while enhancing those for the 3D model(from 3000 steps to 6000 steps)can effectively balance computational accuracy and efficiency.展开更多
This study focuses on the thermal management of 4680-type cylindrical lithium-ion battery packs utilizing NCM811 chemistry.It establishes coupled multi-physics models for both immersion and serpentine cold plate cooli...This study focuses on the thermal management of 4680-type cylindrical lithium-ion battery packs utilizing NCM811 chemistry.It establishes coupled multi-physics models for both immersion and serpentine cold plate cooling systems.Through a combination of numerical simulation and experimental validation,the technical advantages and mechanisms of immersion cooling are systematically explored.Simulation results indicate that under a 3C fast-charging condition(inlet temperature 20℃,flow rate 36 L/min),the immersion cooling structure 3demonstrates a triple enhancement in thermal performance compared to the cold plate structure 1:a 13.06%reduction in peak temperature,a 31.67%decrease in overall maximum temperature difference,and a 47.62%decrease in single-cell temperature deviation,while also reducing flow resistance by 33.61%.Furthermore,based on the immersion cooling model,a small battery module comprising seven cylindrical cells was designed for thermal runaway testing via nail penetration.The results show that the peak temperature of the triggered cell was limited to 437.6℃,with a controllable temperature rise gradient of only 3.35℃/s and a rapid cooling rate of 0.6℃/s.The maximum temperature rise of adjacent cells was just 64.8℃,effectively inhibiting thermal propagation.Post-test disassembly revealed that the non-triggered cells retained>99.2%of their original voltage and>99%structural integrity,confirming the module’s ability to achieve“localized failure with global stability.”展开更多
[Objective]This study aims to develop a thermodynamically consistent phase-field framework for modeling the initiation and evolution of discontinuous structures in geomaterials.[Methods]Our model introduces crack driv...[Objective]This study aims to develop a thermodynamically consistent phase-field framework for modeling the initiation and evolution of discontinuous structures in geomaterials.[Methods]Our model introduces crack driving forces derived from the volumetric-deviatoric strain decomposition strategy,incorporating distinct tension,compression,and shear degradation mechanisms.Inertia effects capture compaction-band formation driven by wave-like disturbances,grain crushing,and frictional rearrangement.A monolithic algorithm ensures numerical stability and rapid convergence.[Results]The framework reproduces tensile,shear,mixed tensile-shear,and compressive-shear failures using the Benzeggagh-Kenane criterion.Validation against benchmark simulations-including uniaxial compression of rock-like and triaxial compression of V-notched sandstone specimens-demonstrates accurate predictions of crack initiation stress,localization orientation,and energy dissipation.[Conclusions]The framework provides a unified and robust numerical tool for analyzing the spatiotemporal evolution of strain localization and fracture in geomaterials.[Significance]By linking microscale fracture dynamics with macroscale failure within a thermodynamically consistent scheme,this study advances predictive modeling of rock stability,slope failure,and subsurface energy systems,contributing to safer and more sustainable geotechnical practice.展开更多
The PICOSEC Micromegas(MM)is a precise timing gaseous detector based on a Cherenkov radiator coupled with a semi-transparent photocathode and an MM amplifying structure.It features a two-stage amplification process th...The PICOSEC Micromegas(MM)is a precise timing gaseous detector based on a Cherenkov radiator coupled with a semi-transparent photocathode and an MM amplifying structure.It features a two-stage amplification process that leads to a significant deterioration of non-uniformity when scaling up to larger areas.Since the performance of gaseous detectors is highly dependent on the choice of working gas,optimizing the gas mixture offers a promising solution to improve the uniformity performance.This paper addresses these challenges through a combined approach of simulation based on Garfield++and experimental studies.The simulation investigates the properties of different mixing fractions of gas mixtures and their impact on detector performance,including gain uniformity and time resolution.To verify the simulation results,experimental tests were conducted using a multi-channel PICOSEC MM prototype with different gas mixtures.The experimental results are consistent with the findings of the simulation,indicating that a higher concentration of neon significantly improves the detector’s gain uniformity.Furthermore,the influence of gas mixtures on time resolution was explored as a critical performance indicator.The study presented in this paper offers valuable insights for improving uniformity in large-area PICOSEC MM detectors and optimizing overall performance.展开更多
The finite volume method was applied to numerically simulate the bottom pressure field induced by regular waves,vehicles in calm water and vehicles in regular waves.The solution of Navier-Stokes(N-S)equations in the v...The finite volume method was applied to numerically simulate the bottom pressure field induced by regular waves,vehicles in calm water and vehicles in regular waves.The solution of Navier-Stokes(N-S)equations in the vicinity of numerical wave tank's boundary was forced towards the wave theoretical solution by incorporating momentum source terms,thereby reducing adverse effects such as wave reflection.Simulations utilizing laminar flow,turbulent flow,and ideal fluid models were all found capable of effectively capturing the waveform and bottom pressure of regular waves,agreeing well with experimental data.In predicting the bottom pressure field of the submerged vehicle,turbulent simulations considering fluid viscosity and boundary layer development provided more accurate predictions for the stern region than inviscid simulations.Due to sphere's diffractive effect,the sphere's bottom pressure field in waves is not a linear superposition of the wave's and the sphere's bottom pressure field.However,a slender submerged vehicle exhibits a weaker diffractive effect on waves,thus the submerged vehicle's bottom pressure field in waves can be approximated as a linear superposition of the wave's and the submerged vehicle's bottom pressure field,which simplifies computation and analysis.展开更多
Al-Cu-Mg-Ag alloys have become a research hotspot because of its good heat resistance.Its excellent mechanical properties are inseparable from the regulation of the structure by researchers.The method of material stru...Al-Cu-Mg-Ag alloys have become a research hotspot because of its good heat resistance.Its excellent mechanical properties are inseparable from the regulation of the structure by researchers.The method of material structure simulation has become more and more perfect.This study employs numerical simulation to investigate the microstructure evolution of Al-Cu-Mg-Ag alloys during solidification with the aim of controlling its structure.The size distribution of Ti-containing particles in an Al-Ti-B master alloy was characterized via microstructure observation,serving as a basis for optimizing the nucleation density parameters for particles of varying radii in the phase field model.The addition of refiner inhibited the growth of dendrites and no longer produced coarse dendrites.With the increase of refiner,the grains gradually tended to form cellular morphology.The refined grains were about 100μm in size.Experimental validation of the simulated as-cast grain morphology was conducted.The samples were observed by metallographic microscope and scanning electron microscope.The addition of refiner had a significant effect on the refinement of the alloy,and the average grain size after refinement was also about 100μm.At the same time,the XRD phase identification of the alloy was carried out.The observation of the microstructure morphology under the scanning electron microscope showed that the precipitated phase was mainly concentrated on the grain boundary.The Al_(2)Cu accounted for about 5%,and the matrix phase FCC accounted for about 95%,which also corresponded well with the simulation results.展开更多
For space-borne gravitational wave detection missions based on the heterodyne interferometry principle,tilt-to-length(TTL)coupling noise is an important optical noise source,significantly influencing the accuracy of t...For space-borne gravitational wave detection missions based on the heterodyne interferometry principle,tilt-to-length(TTL)coupling noise is an important optical noise source,significantly influencing the accuracy of the measurement system.We present a method for analyzing TTL coupling noise under the joint influence of multiple factors.An equivalent simulated optical bench for the test mass interferometer was designed,and Gaussian beam tracing was adopted to simulate beam propagation.By simulating the interference signal,it can analyze the impact of various factors on the TTL coupling noise,including positional,beam parameters,detector parameters,and signal definition factors.On this basis,a random parameter space composed of multiple influential factors was constructed within a range satisfying the analysis requirement,and the corresponding simulation results from random sampling were evaluated via variance-based global sensitivity analysis.The calculated results of the main and total effect indexes show that the test mass rotation angle and the piston effect(lateral)significantly influence the TTL coupling noise in the test mass interferometer.The analysis provides a qualitative reference for designing and optimizing space-borne laser interferometry systems.展开更多
Objective Traditional Chinese medicine(TCM)constitutes a valuable cultural heritage and an important source of antitumor compounds.Poria(Poria cocos(Schw.)Wolf),the dried sclerotium of a polyporaceae fungus,was first ...Objective Traditional Chinese medicine(TCM)constitutes a valuable cultural heritage and an important source of antitumor compounds.Poria(Poria cocos(Schw.)Wolf),the dried sclerotium of a polyporaceae fungus,was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia.Traditionally recognized for its diuretic,spleen-tonifying,and sedative properties,modern pharmacological studies confirm that Poria exhibits antioxidant,anti-inflammatory,antibacterial,and antitumor activities.Pachymic acid(PA;a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid),isolated from Poria,is a principal bioactive constituent.Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms,though these remain incompletely characterized.Neuroblastoma(NB),a highly malignant pediatric extracranial solid tumor accounting for 15%of childhood cancer deaths,urgently requires safer therapeutics due to the limitations of current treatments.Although PA shows multi-mechanistic antitumor potential,its efficacy against NB remains uncharacterized.This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking,dynamic simulations,and in vitro assays,aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays.Methods This study employed network pharmacology to identify potential targets of PA in NB,followed by validation using molecular docking,molecular dynamics(MD)simulations,MM/PBSA free energy analysis,RT-qPCR and Western blot experiments.Network pharmacology analysis included target screening via TCMSP,GeneCards,DisGeNET,SwissTargetPrediction,SuperPred,and PharmMapper.Subsequently,potential targets were predicted by intersecting the results from these databases via Venn analysis.Following target prediction,topological analysis was performed to identify key targets using Cytoscape software.Molecular docking was conducted using AutoDock Vina,with the binding pocket defined based on crystal structures.MD simulations were performed for 100 ns using GROMACS,and RMSD,RMSF,SASA,and hydrogen bonding dynamics were analyzed.MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex.In vitro validation included RT-qPCR and Western blot,with GAPDH used as an internal control.Results The CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability.GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress,vesicle lumen,and protein tyrosine kinase activity.KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT,MAPK,and Ras signaling pathways.Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1,EGFR,SRC,and HSP90AA1.RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1,EGFR,and SRC while increasing the HSP90AA1 mRNA and protein levels.Conclusion It was suggested that PA may exert its anti-NB effects by inhibiting AKT1,EGFR,and SRC expression,potentially modulating the PI3K/AKT signaling pathway.These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.展开更多
基金funded partially by the Australian Government through the Australian Research Council’s Linkage Infrastructure,Equipment and Facilities (LIEF)funding scheme (LE130100133)。
文摘A critical challenge of any blast simulation facility is in producing the widest possible pressure-impulse range for matching against equivalent high-explosive events.Shock tubes and blast simulators are often constrained with the lack of effective ways to control blast wave profiles and as a result have a limited performance range.Some wave shaping techniques employed in some facilities are reviewed but often necessitate extensive geometric modifications,inadvertently cause flow anomalies,and/or are only applicable under very specific configurations.This paper investigates controlled venting as an expedient way for waveforms to be tuned without requiring extensive modifications to the driver or existing geometry and could be widely applied by existing and future blast simulation and shock tube facilities.The use of controlled venting is demonstrated experimentally using the Advanced Blast Simulator(shock tube)at the Australian National Facility of Physical Blast Simulation and via numerical flow simulations with Computational Fluid Dynamics.Controlled venting is determined as an effective method for mitigating the impact of re-reflected waves within the blast simulator.This control method also allows for the adjustment of parameters such as tuning the peak overpressure,the positive phase duration,and modifying the magnitude of the negative phase and the secondary shock of the blast waves.This paper is concluded with an illustration of the potential expanded performance range of the Australian blast simulation facility when controlled venting for blast waveform tailoring as presented in this paper is applied.
文摘To investigate the in vitro digestion and fermentation properties of soybean oligosaccharides(SBOS)extracted from defatted soybean meal,the changes in monosaccharide composition and molecular mass were analyzed.Subsequently,the effect of SBOS on microbial community structure and metabolites was studied by 16S rRNA gene sequencing and untargeted metabolomics based on liquid chromatography-mass spectrometry.Results showed that SBOS was not easily enzymolyzed during simulated digestion and could reach the large intestine through the digestive system.The significant decrease in the molecular mass of SBOS after in vitro fermentation indicated its utilization by the gut microbiota,which increased the contents of short-chain fatty acids and lactic acid,thereby reducing the pH of the fermentation broth.Moreover,the core community was found to consist of Blautia,Lactobacillaceae,and Pediococcus.SBOS up-regulated beneficial differential metabolites such as myo-inositol,lactose,and glucose,which were closely related to galactose,amino sugar,and nucleotide sugar metabolism.This study will provide a reference for exploring the relationship between the gut microbiota and the metabolites of SBOS,and provide a basis for the development and application of SBOS as an ingredient for functional products.
基金supported by the Guangdong Major Project of Basic and Applied Basic Research(Grant No.2021B0301030001)the National Key Research and Development Program of China(Grant No.2021YFB3802300)the Foundation of National Key Laboratory of Shock Wave and Detonation Physics(Grant No.JCKYS2022212004)。
文摘The graded density impactor(GDI)dynamic loading technique is crucial for acquiring the dynamic physical property parameters of materials used in weapons.The accuracy and timeliness of GDI structural design are key to achieving controllable stress-strain rate loading.In this study,we have,for the first time,combined one-dimensional fluid computational software with machine learning methods.We first elucidated the mechanisms by which GDI structures control stress and strain rates.Subsequently,we constructed a machine learning model to create a structure-property response surface.The results show that altering the loading velocity and interlayer thickness has a pronounced regulatory effect on stress and strain rates.In contrast,the impedance distribution index and target thickness have less significant effects on stress regulation,although there is a matching relationship between target thickness and interlayer thickness.Compared with traditional design methods,the machine learning approach offers a10^(4)—10^(5)times increase in efficiency and the potential to achieve a global optimum,holding promise for guiding the design of GDI.
文摘The microstructures and thermodynamic properties of mixed systems comprising pyridinium ionic liquid[HPy][BF_(4)]and acetonitrile at different mole fractions were studied using molecular dynamics simulation in this work.The following properties were determined:density,self-diffusion coefficient,excess molar volume,and radial distribution function.The results show that with an increase in the mole fraction of[HPy][BF_(4)],the self-diffusion coefficient decreases.Additionally,the excess molar volume initially decreases,reaches a minimum,and then increases.The rules of radial distribution functions(RDFs)of characteristic atoms are different.With increasing the mole fraction of[HPy][BF_(4)],the first peak of the RDFs of HA1-F decreases,while that of CT6-CT6 rises at first and then decreases.This indicates that the solvent molecules affect the polar and non-polar regions of[HPy][BF_(4)]differently.
文摘The performance of a material is directly affected by its microstructural development during the solidification phase. Discrete cellular automaton (CA) models are widelyused in materials science to simulate and predict microstructural growth. This review comprehensively explains the developments and applications of CA in solidification structure simulation, including the theoretical underpinnings, computational procedures, software development, and recent advances. Summarizes the potential and limitations of cellular automata in understanding microstructure evolution during solidification, explores the evolution of microstructures during solidification, and adds to our existing knowledge of cellular automaton theory. Finally, the research trend in simulating the evolution of the solidification microstructure using cellular automaton theory is explored.
文摘Chloride ions(Cl^(-))have been shown to impact the long-lasting nature of reinforced concrete.However,Cl^(-)that are already bound inside the concrete will not lead to the deterioration of the concrete’s characteristics.The composition of the cement-based material,including the type of cement and auxiliary materials,greatly influences the ability of the material to bind Cl^(-),and varied components result in varying binding beha-vior of the Cl^(-).Simultaneously,the Cl^(-)binding process in concrete is influenced by both the internal and exterior surroundings,as well as the curing practices.These factors impact the hydration process of the cement and the internal pore structure of the concrete.Currently,mathematical theories and molecular dynamics simulations have increasingly been employed as the prevalent methods for examining the binding behaviors of Cl^(-)in concrete.These techniques are extensively utilized for predicting the lifespan and conducting microscopic studies of reinforced concrete in Cl^(-)settings.This work proposes recommendations for future research based on a summary of experimental and simulation investigations on Cl^(-)binding.Which will offer theoretical guidance for studying the binding of Cl^(-)in cement-based materials.
文摘To address the limitations of existing coupling methods in aero-engine system simulation,which fail to adaptively adjust iterative parameters and coupling relationships,which can result in low efficiency and in⁃stability,this study introduces a‘Dynamic Event-Driven Co-Simulation’algorithm integrated with decision tree algorithms.This algorithm separates the overall coupling relationships and the main solver from the primary mod⁃el,utilizing a dynamic event monitoring module to adaptively adjust simulation strategies,including iteration pa⁃rameters,coupling relationships,and convergence criteria.This facilitates efficient adaptive simulations of dy⁃namic events while balancing solution accuracy and computational efficiency.The research focuses on a twinshaft turbofan engine,establishing six system-level models that encompass overall performance and various sub⁃systems based on three coupling methods,along with a multidisciplinary multi-fidelity simulation framework in⁃corporating a 3D CFD nozzle model.The study tests both model exchange and coupled simulation methods under a 14 s transient acceleration and deceleration scenario.In a 100%throttle condition,a high-fidelity nozzle model is used to analyze the sensitivity of different convergence criteria on computational efficiency and accuracy.Re⁃sults indicate that the accuracy and efficiency achieved with this method are comparable to those of PROOSIS soft⁃ware(18 s and 35 s,respectively),while being 71%more efficient than Simulink software(62 s and 120 s,re⁃spectively).Furthermore,appropriately relaxing the convergence criteria for the 0D model(from 10-6 to 10-4)while enhancing those for the 3D model(from 3000 steps to 6000 steps)can effectively balance computational accuracy and efficiency.
文摘This study focuses on the thermal management of 4680-type cylindrical lithium-ion battery packs utilizing NCM811 chemistry.It establishes coupled multi-physics models for both immersion and serpentine cold plate cooling systems.Through a combination of numerical simulation and experimental validation,the technical advantages and mechanisms of immersion cooling are systematically explored.Simulation results indicate that under a 3C fast-charging condition(inlet temperature 20℃,flow rate 36 L/min),the immersion cooling structure 3demonstrates a triple enhancement in thermal performance compared to the cold plate structure 1:a 13.06%reduction in peak temperature,a 31.67%decrease in overall maximum temperature difference,and a 47.62%decrease in single-cell temperature deviation,while also reducing flow resistance by 33.61%.Furthermore,based on the immersion cooling model,a small battery module comprising seven cylindrical cells was designed for thermal runaway testing via nail penetration.The results show that the peak temperature of the triggered cell was limited to 437.6℃,with a controllable temperature rise gradient of only 3.35℃/s and a rapid cooling rate of 0.6℃/s.The maximum temperature rise of adjacent cells was just 64.8℃,effectively inhibiting thermal propagation.Post-test disassembly revealed that the non-triggered cells retained>99.2%of their original voltage and>99%structural integrity,confirming the module’s ability to achieve“localized failure with global stability.”
文摘[Objective]This study aims to develop a thermodynamically consistent phase-field framework for modeling the initiation and evolution of discontinuous structures in geomaterials.[Methods]Our model introduces crack driving forces derived from the volumetric-deviatoric strain decomposition strategy,incorporating distinct tension,compression,and shear degradation mechanisms.Inertia effects capture compaction-band formation driven by wave-like disturbances,grain crushing,and frictional rearrangement.A monolithic algorithm ensures numerical stability and rapid convergence.[Results]The framework reproduces tensile,shear,mixed tensile-shear,and compressive-shear failures using the Benzeggagh-Kenane criterion.Validation against benchmark simulations-including uniaxial compression of rock-like and triaxial compression of V-notched sandstone specimens-demonstrates accurate predictions of crack initiation stress,localization orientation,and energy dissipation.[Conclusions]The framework provides a unified and robust numerical tool for analyzing the spatiotemporal evolution of strain localization and fracture in geomaterials.[Significance]By linking microscale fracture dynamics with macroscale failure within a thermodynamically consistent scheme,this study advances predictive modeling of rock stability,slope failure,and subsurface energy systems,contributing to safer and more sustainable geotechnical practice.
基金supported by the National Natural Science Foundation of China(12125505).
文摘The PICOSEC Micromegas(MM)is a precise timing gaseous detector based on a Cherenkov radiator coupled with a semi-transparent photocathode and an MM amplifying structure.It features a two-stage amplification process that leads to a significant deterioration of non-uniformity when scaling up to larger areas.Since the performance of gaseous detectors is highly dependent on the choice of working gas,optimizing the gas mixture offers a promising solution to improve the uniformity performance.This paper addresses these challenges through a combined approach of simulation based on Garfield++and experimental studies.The simulation investigates the properties of different mixing fractions of gas mixtures and their impact on detector performance,including gain uniformity and time resolution.To verify the simulation results,experimental tests were conducted using a multi-channel PICOSEC MM prototype with different gas mixtures.The experimental results are consistent with the findings of the simulation,indicating that a higher concentration of neon significantly improves the detector’s gain uniformity.Furthermore,the influence of gas mixtures on time resolution was explored as a critical performance indicator.The study presented in this paper offers valuable insights for improving uniformity in large-area PICOSEC MM detectors and optimizing overall performance.
文摘The finite volume method was applied to numerically simulate the bottom pressure field induced by regular waves,vehicles in calm water and vehicles in regular waves.The solution of Navier-Stokes(N-S)equations in the vicinity of numerical wave tank's boundary was forced towards the wave theoretical solution by incorporating momentum source terms,thereby reducing adverse effects such as wave reflection.Simulations utilizing laminar flow,turbulent flow,and ideal fluid models were all found capable of effectively capturing the waveform and bottom pressure of regular waves,agreeing well with experimental data.In predicting the bottom pressure field of the submerged vehicle,turbulent simulations considering fluid viscosity and boundary layer development provided more accurate predictions for the stern region than inviscid simulations.Due to sphere's diffractive effect,the sphere's bottom pressure field in waves is not a linear superposition of the wave's and the sphere's bottom pressure field.However,a slender submerged vehicle exhibits a weaker diffractive effect on waves,thus the submerged vehicle's bottom pressure field in waves can be approximated as a linear superposition of the wave's and the submerged vehicle's bottom pressure field,which simplifies computation and analysis.
文摘Al-Cu-Mg-Ag alloys have become a research hotspot because of its good heat resistance.Its excellent mechanical properties are inseparable from the regulation of the structure by researchers.The method of material structure simulation has become more and more perfect.This study employs numerical simulation to investigate the microstructure evolution of Al-Cu-Mg-Ag alloys during solidification with the aim of controlling its structure.The size distribution of Ti-containing particles in an Al-Ti-B master alloy was characterized via microstructure observation,serving as a basis for optimizing the nucleation density parameters for particles of varying radii in the phase field model.The addition of refiner inhibited the growth of dendrites and no longer produced coarse dendrites.With the increase of refiner,the grains gradually tended to form cellular morphology.The refined grains were about 100μm in size.Experimental validation of the simulated as-cast grain morphology was conducted.The samples were observed by metallographic microscope and scanning electron microscope.The addition of refiner had a significant effect on the refinement of the alloy,and the average grain size after refinement was also about 100μm.At the same time,the XRD phase identification of the alloy was carried out.The observation of the microstructure morphology under the scanning electron microscope showed that the precipitated phase was mainly concentrated on the grain boundary.The Al_(2)Cu accounted for about 5%,and the matrix phase FCC accounted for about 95%,which also corresponded well with the simulation results.
文摘For space-borne gravitational wave detection missions based on the heterodyne interferometry principle,tilt-to-length(TTL)coupling noise is an important optical noise source,significantly influencing the accuracy of the measurement system.We present a method for analyzing TTL coupling noise under the joint influence of multiple factors.An equivalent simulated optical bench for the test mass interferometer was designed,and Gaussian beam tracing was adopted to simulate beam propagation.By simulating the interference signal,it can analyze the impact of various factors on the TTL coupling noise,including positional,beam parameters,detector parameters,and signal definition factors.On this basis,a random parameter space composed of multiple influential factors was constructed within a range satisfying the analysis requirement,and the corresponding simulation results from random sampling were evaluated via variance-based global sensitivity analysis.The calculated results of the main and total effect indexes show that the test mass rotation angle and the piston effect(lateral)significantly influence the TTL coupling noise in the test mass interferometer.The analysis provides a qualitative reference for designing and optimizing space-borne laser interferometry systems.
文摘Objective Traditional Chinese medicine(TCM)constitutes a valuable cultural heritage and an important source of antitumor compounds.Poria(Poria cocos(Schw.)Wolf),the dried sclerotium of a polyporaceae fungus,was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia.Traditionally recognized for its diuretic,spleen-tonifying,and sedative properties,modern pharmacological studies confirm that Poria exhibits antioxidant,anti-inflammatory,antibacterial,and antitumor activities.Pachymic acid(PA;a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid),isolated from Poria,is a principal bioactive constituent.Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms,though these remain incompletely characterized.Neuroblastoma(NB),a highly malignant pediatric extracranial solid tumor accounting for 15%of childhood cancer deaths,urgently requires safer therapeutics due to the limitations of current treatments.Although PA shows multi-mechanistic antitumor potential,its efficacy against NB remains uncharacterized.This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking,dynamic simulations,and in vitro assays,aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays.Methods This study employed network pharmacology to identify potential targets of PA in NB,followed by validation using molecular docking,molecular dynamics(MD)simulations,MM/PBSA free energy analysis,RT-qPCR and Western blot experiments.Network pharmacology analysis included target screening via TCMSP,GeneCards,DisGeNET,SwissTargetPrediction,SuperPred,and PharmMapper.Subsequently,potential targets were predicted by intersecting the results from these databases via Venn analysis.Following target prediction,topological analysis was performed to identify key targets using Cytoscape software.Molecular docking was conducted using AutoDock Vina,with the binding pocket defined based on crystal structures.MD simulations were performed for 100 ns using GROMACS,and RMSD,RMSF,SASA,and hydrogen bonding dynamics were analyzed.MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex.In vitro validation included RT-qPCR and Western blot,with GAPDH used as an internal control.Results The CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability.GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress,vesicle lumen,and protein tyrosine kinase activity.KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT,MAPK,and Ras signaling pathways.Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1,EGFR,SRC,and HSP90AA1.RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1,EGFR,and SRC while increasing the HSP90AA1 mRNA and protein levels.Conclusion It was suggested that PA may exert its anti-NB effects by inhibiting AKT1,EGFR,and SRC expression,potentially modulating the PI3K/AKT signaling pathway.These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.
