The outbreak of infectious diseases is the result of a combination of various factors,including season,the movement of individuals,non-pharmaceutical interventions(NPIs)and the effectiveness and availability of vaccin...The outbreak of infectious diseases is the result of a combination of various factors,including season,the movement of individuals,non-pharmaceutical interventions(NPIs)and the effectiveness and availability of vaccines.Taking these key elements into consideration,an almost periodic SVEIR warning model in the patch environment is here proposed.First,in terms of reproduction numbers,our results imply that if the effective reproduction numbers are R_(e)<1,then the disease dies out;if R_(e)>1,then the disease spreads and leads to local outbreaks.Second,the relationships between R_(e)and C_(s1),C_(a1)(see Section 2)are given by numerical simulations.The numerical results show that even if all people are vaccinated,NPIs are still needed because of the potentially low efficacy of vaccines.Furthermore,the numerical results suggest that NPIs and the strengthening of the effective rate of vaccination are essential in order to achieve herd immunity.Theories involving this model effectively explain the transmission mechanism of most infectious diseases,and provide a valuable theoretical basis for analyzing new infectious diseases in the future.Moreover,this model is helpful for the prevention and control of infectious diseases and the formulation of public health safety policies.展开更多
To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework ba...To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.展开更多
The current research of large eddy simulation （LES） of turbulent flow in pumps mainly concentrates in applying conventional subgrid-scale （SGS） model to simulate turbulent flow, which aims at obtaining the flow fi...The current research of large eddy simulation （LES） of turbulent flow in pumps mainly concentrates in applying conventional subgrid-scale （SGS） model to simulate turbulent flow, which aims at obtaining the flow field in pump. The selection of SGS model is usually not considered seriously, so the accuracy and efficiency of the simulation cannot be ensured. Three SGS models including Smagorinsky-Lilly model, dynamic Smagorinsky model and dynamic mixed model are comparably studied by using the commercial CFD code Fluent combined with its user define function. The simulations are performed for the turbulent flow in a centrifugal pump impeller. The simulation results indicate that the mean flows predicted by the three SGS models agree well with the experimental data obtained from the test that detailed measurements of the flow inside the rotating passages of a six-bladed shrouded centrifugal pump impeller performed using particle image velocimetry （PIV） and laser Doppler velocimetry （LDV）. The comparable results show that dynamic mixed model gives the most accurate results for mean flow in the centrifugal pump impeller. The SGS stress of dynamic mixed model is decompose into the scale similar part and the eddy viscous part. The scale similar part of SGS stress plays a significant role in high curvature regions, such as the leading edge and training edge of pump blade. It is also found that the dynamic mixed model is more adaptive to compute turbulence in the pump impeller. The research results presented is useful to improve the computational accuracy and efficiency of LES for centrifugal pumps, and provide important reference for carrying out simulation in similar fluid machineries.展开更多
This paper investigates the capabilities of large language models(LLMs)to leverage,learn and create knowledge in solving computational fluid dynamics(CFD)problems through three categories of baseline problems.These ca...This paper investigates the capabilities of large language models(LLMs)to leverage,learn and create knowledge in solving computational fluid dynamics(CFD)problems through three categories of baseline problems.These categories include(1)conventional CFD problems that can be solved using existing numerical methods in LLMs,such as lid-driven cavity flow and the Sod shock tube problem;(2)problems that require new numerical methods beyond those available in LLMs,such as the recently developed Chien-physics-informed neural networks for singularly perturbed convection-diffusion equations;and(3)problems that cannot be solved using existing numerical methods in LLMs,such as the ill-conditioned Hilbert linear algebraic systems.The evaluations indicate that reasoning LLMs overall outperform non-reasoning models in four test cases.Reasoning LLMs show excellent performance for CFD problems according to the tailored prompts,but their current capability in autonomous knowledge exploration and creation needs to be enhanced.展开更多
The measurement of the pairing gap is crucial for investigating the physical properties of superconductors or superfluids.We propose a strategy to measure the pairing gap through the dynamical excitations.With the ran...The measurement of the pairing gap is crucial for investigating the physical properties of superconductors or superfluids.We propose a strategy to measure the pairing gap through the dynamical excitations.With the random phase approximation(RPA),we study the dynamical excitations of a two-dimensional attractive Fermi-Hubbard model by calculating its dynamical structure factor.Two distinct collective modes emerge:a Goldstone phonon mode at transferred momentum q=[0,0]and a roton mode at q=[p,p].The roton mode exhibits a sharp molecular peak in the low-energy regime.Notably,the area under the roton molecular peak scales with the square of the pairing gap,which holds even in three-dimensional and spin-orbit coupled(SOC)optical lattices.This finding suggests an experimental approach to measure the pairing gap in lattice systems by analyzing the dynamical structure factor at q=[p,p].展开更多
This work reviews models and methods for determining the dynamic response of pavements to moving vehicle loads in the framework of continuum-based three dimensional models and linear theories.This review emphasizes th...This work reviews models and methods for determining the dynamic response of pavements to moving vehicle loads in the framework of continuum-based three dimensional models and linear theories.This review emphasizes the most representative models and methods of analysis in the existing literature and illustrates all of them by numerical examples.Thus,13 such examples are presented here in some detail.Both flexible and rigid(concrete)pavement models involving simple and elaborate cases with respect to geometry and material behavior are considered.Thus,homogeneous or layered half-spaces with isotropic or cross-anisotropic and elastic,viscoelastic or poroelastic properties are considered.The vehicles are modeled as simple point or distributed loads or discrete spring-mass-dashpot system moving with constant or variable velocity.The dynamic response of the above pavement-vehicle systems is obtained by analytical/numerical or purely numerical methods of solution.Analytical/numerical methods have mainly to do with Fourier transforms or complex Fourier series with respect to both space and time.Purely numerical methods involve the finite element method(FEM)and the boundary element method(BEM)working in time or frequency domain.Critical discussions on the advantages and disadvantages of the various pavement-vehicle models and their methods of analysis are provided and the effects of the main parameters on the pavement response are determined through parametric studies and presented in the examples.Finally,conclusions are provided and suggestions for future research are made.展开更多
Under the paradigm of Industry 5.0,intelligent manufacturing transcends mere efficiency enhancement by emphasizing human-machine collaboration,where human expertise plays a central role in assembly processes.Despite a...Under the paradigm of Industry 5.0,intelligent manufacturing transcends mere efficiency enhancement by emphasizing human-machine collaboration,where human expertise plays a central role in assembly processes.Despite advancements in intelligent and digital technologies,assembly process design still heavily relies on manual knowledge reuse,and inefficiencies and inconsistent quality in process documentation are caused.To address the aforementioned issues,this paper proposes a knowledge push method of complex product assembly process design based on distillation model-based dynamically enhanced graph and Bayesian network.First,an initial knowledge graph is constructed using a BERT-BiLSTM-CRF model trained with integrated human expertise and a fine-tuned large language model.Then,a confidence-based dynamic weighted fusion strategy is employed to achieve dynamic incremental construction of the knowledge graph with low resource consumption.Subsequently,a Bayesian network model is constructed based on the relationships between assembly components,assembly features,and operations.Bayesian network reasoning is used to push assembly process knowledge under different design requirements.Finally,the feasibility of the Bayesian network construction method and the effectiveness of Bayesian network reasoning are verified through a specific example,significantly improving the utilization of assembly process knowledge and the efficiency of assembly process design.展开更多
A second-order dynamic model based on the general relation between the subgrid-scale stress and the velocity gradient tensors was proposed. A priori test of the second-order model was made using moderate resolution di...A second-order dynamic model based on the general relation between the subgrid-scale stress and the velocity gradient tensors was proposed. A priori test of the second-order model was made using moderate resolution direct numerical simulation date at high Reynolds number ( Taylor microscale Reynolds number R-lambda = 102 similar to 216) for homogeneous, isotropic forced flow, decaying flow, and homogeneous rotating flow. Numerical testing shows that the second-order dynamic model significantly improves the correlation coefficient when compared to the first-order dynamic models.展开更多
The subgrid-scale(SGS)kinetic energy has been used to predict the SGS stress in compressible flow and it was resolved through the SGS kinetic energy transport equation in past studies.In this paper,a new SGS eddy-visc...The subgrid-scale(SGS)kinetic energy has been used to predict the SGS stress in compressible flow and it was resolved through the SGS kinetic energy transport equation in past studies.In this paper,a new SGS eddy-viscosity model is proposed using artificial neural network to obtain the SGS kinetic energy precisely,instead of using the SGS kinetic energy equation.Using the infinite series expansion and reserving the first term of the expanded term,we obtain an approximated SGS kinetic energy,which has a high correlation with the real SGS kinetic energy.Then,the coefficient of the modelled SGS kinetic energy is resolved by the artificial neural network and the modelled SGS kinetic energy is more accurate through this method compared to the SGS kinetic energy obtained from the SGS kinetic energy equation.The coefficients of the SGS stress and SGS heat flux terms are determined by the dynamic procedure.The new model is tested in the compressible turbulent channel flow.From the a posterior tests,we know that the new model can precisely predict the mean velocity,the Reynolds stress,the mean temperature and turbulence intensities,etc.展开更多
A sufficient condition for the asymptotic stability of the equilibrium point of a system, which appears as a model for couple of the love affair with time delay, is obtained by applying the technique of linearized met...A sufficient condition for the asymptotic stability of the equilibrium point of a system, which appears as a model for couple of the love affair with time delay, is obtained by applying the technique of linearized method and Hopf- bifurcation.展开更多
Industry foundation classes(IFC)is an open and neutral data format specification for building information modeling(BIM)that plays a crucial role in facilitating interoperability.With increases in web-based BIM applica...Industry foundation classes(IFC)is an open and neutral data format specification for building information modeling(BIM)that plays a crucial role in facilitating interoperability.With increases in web-based BIM applications,there is an urgent need for fast loading large IFC models on a web browser.However,the task of fully loading large IFC models typically consumes a large amount of memory of a web browser or even crashes the browser,and this significantly limits further BIM applications.In order to address the issue,a method is proposed for dynamically loading IFC models based on spatial semantic partitioning(SSP).First,the spatial semantic structure of an input IFC model is partitioned via the extraction of story information and establishing a component space index table on the server.Subsequently,based on user interaction,only the model data that a user is interested in is transmitted,loaded,and displayed on the client.The presented method is implemented via Web Graphics Library,and this enables large IFC models to be fast loaded on the web browser without requiring any plug-ins.When compared with conventional methods that load all IFC model data for display purposes,the proposed method significantly reduces memory consumption in a web browser,thereby allowing the loading of large IFC models.When compared with the existing method of spatial partitioning for 3D data,the proposed SSP entirely uses semantic information in the IFC file itself,and thereby provides a better interactive experience for users.展开更多
As the largest pool of terrestrial organic carbon, soils interact strongly with atmosphere composition, climate, and land change. Soil organic carbon dynamics in ecosystem plays a great role in global carbon cycle and...As the largest pool of terrestrial organic carbon, soils interact strongly with atmosphere composition, climate, and land change. Soil organic carbon dynamics in ecosystem plays a great role in global carbon cycle and global change. With development of mathematical models that simulate changes in soil organic carbon, there have been considerable advances in understanding soil organic carbon dynamics. This paper mainly reviewed the composition of soil organic matter and its influenced factors, and recommended some soil organic matter models worldwide. Based on the analyses of the developed results at home and abroad, it is suggested that future soil organic matter models should be developed toward based-process models, and not always empirical ones. The models are able to reveal their interaction between soil carbon systems, climate and land cover by technique and methods of GIS (Geographical Information System) and RS (Remote Sensing). These models should be developed at a global scale, in dynamically describing the spatial and temporal changes of soil organic matter cycle. Meanwhile, the further researches on models should be strengthen for providing theory basis and foundation in making policy of green house gas emission in China.展开更多
Mathematical models of tire-longitudinal road adhesion for use in the study of road vehicle dynamics are set up so as to express the relations of longitudinal adhesion coefficients with the slip ratio. They perfect th...Mathematical models of tire-longitudinal road adhesion for use in the study of road vehicle dynamics are set up so as to express the relations of longitudinal adhesion coefficients with the slip ratio. They perfect the Pacejka's models in practical use by taking into account the influences of all essential parameters such as road surface condition. vehicle velocity. slip angle. vertical load and slip ratio on the longitudinal adhesion coefficients. The new models are more comprehensive more concise. simpler and more convenient in application in all kinds of simulations of car dynamics in various sorts of braking modes.展开更多
The cause-effect relationship is not always possible to trace in GCMs because of the simultaneous inclusion of several highly complex physical processes. Furthermore, the inter-GCM differences are large and there is n...The cause-effect relationship is not always possible to trace in GCMs because of the simultaneous inclusion of several highly complex physical processes. Furthermore, the inter-GCM differences are large and there is no simple way to reconcile them. So, simple climate models, like statistical-dynamical models (SDMs), appear to be useful in this context. This kind of models is essentially mechanistic, being directed towards understanding the dependence of a particular mechanism on the other parameters of the problem. In this paper, the utility of SDMs for studies of climate change is discussed in some detail. We show that these models are an indispensable part of hierarchy of climate models.展开更多
Mathematical models of tire-lateral mad adhesion for use in mad vehicle dynamics studies are set up to express the relations of adhesion coefficients with slip ratio in lateral direction.The models of tire-lateral mad...Mathematical models of tire-lateral mad adhesion for use in mad vehicle dynamics studies are set up to express the relations of adhesion coefficients with slip ratio in lateral direction.The models of tire-lateral mad adhesion revolutionize the Pacejka's model in concept and therefore make it possible for applications in vehicle dynamics studies by the expression of lateral adhesion coefficient as a function of wheel slip ratio,instead of the wheel slip angle,taking into account in the mean time the influences of mad surface condition, vehicle velocity,vertical load,tire slip angle,and wheel camber angle.展开更多
A variable-fidelity method can remarkably improve the efficiency of a design optimization based on a high-fidelity and expensive numerical simulation,with assistance of lower-fidelity and cheaper simulation(s).However...A variable-fidelity method can remarkably improve the efficiency of a design optimization based on a high-fidelity and expensive numerical simulation,with assistance of lower-fidelity and cheaper simulation(s).However,most existing works only incorporate‘‘two"levels of fidelity,and thus efficiency improvement is very limited.In order to reduce the number of high-fidelity simulations as many as possible,there is a strong need to extend it to three or more fidelities.This article proposes a novel variable-fidelity optimization approach with application to aerodynamic design.Its key ingredient is the theory and algorithm of a Multi-level Hierarchical Kriging(MHK),which is referred to as a surrogate model that can incorporate simulation data with arbitrary levels of fidelity.The high-fidelity model is defined as a CFD simulation using a fine grid and the lower-fidelity models are defined as the same CFD model but with coarser grids,which are determined through a grid convergence study.First,sampling shapes are selected for each level of fidelity via technique of Design of Experiments(DoE).Then,CFD simulations are conducted and the output data of varying fidelity is used to build initial MHK models for objective(e.g.C_D)and constraint(e.g.C_L,C_m)functions.Next,new samples are selected through infillsampling criteria and the surrogate models are repetitively updated until a global optimum is found.The proposed method is validated by analytical test cases and applied to aerodynamic shape optimization of a NACA0012 airfoil and an ONERA M6 wing in transonic flows.The results confirm that the proposed method can significantly improve the optimization efficiency and apparently outperforms the existing single-fidelity or two-level-fidelity method.展开更多
In previous attempts of rational subgrid-scale (SGS) modeling by employing the Kolmogorov equation of filtered (KEF) quantities, it was necessary to assume that the resolved-scale second-order structure function is st...In previous attempts of rational subgrid-scale (SGS) modeling by employing the Kolmogorov equation of filtered (KEF) quantities, it was necessary to assume that the resolved-scale second-order structure function is stationary. Forced isotropic turbulence is often used as a framework for establishing and validating such SGS models based on stationary restrictions, for it generates statistical stationary samples. However, traditional forcing method at low wavenumbers cannot provide an analytic form of forcing term for a complete KEF in physical space, which has been illustrated to be essential in the modeling of such SGS models. Thus, an alternative forcing method giving an analytic forcing term in physical space is needed for rational SGS modeling. Giving an analytic linear driving term in physical space, linearly forced isotropic turbulence should be considered an ideal theoretical framework for rational SGS modeling. In this paper, we demonstrate the feasibility of establishing a rational SGS model with stationary restriction based on linearly forced isotropic turbulence. The performance of this rational SGS model is validated. We, therefore, propose the use of linearly forced isotropic turbulence as a complement to free-decaying isotropic turbulence and low-wavenumber forced isotropic turbulence for SGS model validations.展开更多
In this paper, we study the higher dimensional nonlinear Rossby waves under the generalized beta effect.Using methods of the multiple scales and weak nonlinear perturbation expansions [Q. S. Liu, et al., Phys. Lett. A...In this paper, we study the higher dimensional nonlinear Rossby waves under the generalized beta effect.Using methods of the multiple scales and weak nonlinear perturbation expansions [Q. S. Liu, et al., Phys. Lett. A383(2019) 514], we derive a new(2 + 1)-dimensional generalized Boussinesq equation from the barotropic potential vorticity equation. Based on bifurcation theory of planar dynamical systems and the qualitative theory of ordinary differential equations, the dynamical analysis and exact traveling wave solutions of the new generalized Boussinesq equation are obtained. Moreover, we provide the numerical simulations of these exact solutions under some conditions of all parameters. The numerical results show that these traveling wave solutions are all the Rossby solitary waves.展开更多
The dynamical framework of the nine-level version of the IAP AGCM is presented in this paper. The emphasis of the model's description is put on the following two aspects:(1) A model's standard atmosphere, whic...The dynamical framework of the nine-level version of the IAP AGCM is presented in this paper. The emphasis of the model's description is put on the following two aspects:(1) A model's standard atmosphere, which is a satisfactory approximation to the observed troposphere and lower stratosphere standard atmosphere, is introduced into the equations of the model to permit a more accurate calculation of the vertical transport terms, especially near the tropopause; (2) The vertical levels of the model are carefully selected to guarantee a smooth dependence of layer thickness upon pressure in order to reduce the truncation error involved in the unequal interval vertical finite-differencing. For testing the model, two kinds of linear baroclinic Rossby-Haurwitz waves, one of which has a dynamically stable vertical structure and the other has a relatively unstable one, are constructed to provide initial conditions for numerical experiments. The two waves have been integrated for more than 300 days and 100 days respectively by using the model and both of them are propagating westward with almost identical phase-speed during the time period of the integrations. No obvious change of the wave patterns is found at the levels in the model's troposphere. The amplitudes of both two waves at the uppermost level, however, exhibit rather significant oscillation with time, of which the periods are exactly 20 days and 25 days espectively.The explanation of this interesting phenomena is still under investigation.展开更多
The field experiments were carried out to investigate the dynamics and models of N, P and K absorption for the cotton plants with a lint of 3 000 kg ha-1 in Xinjiang. The main results were as follows: The contents of ...The field experiments were carried out to investigate the dynamics and models of N, P and K absorption for the cotton plants with a lint of 3 000 kg ha-1 in Xinjiang. The main results were as follows: The contents of N, P2O5, K2O in cotton leaves, stems, squares and bolls decreased obviously with the time over the whole growth duration and the falling extent was greater in high-yield cotton than in CK. Contents of N in leaves, squares and bolls, in particular in the leaves of fruit-bearing shoot was higher in high-yield cotton than in CK. Contents of P2O5 in squares and bolls and that of K2O in stems were higher in high-yield cotton than in CK during the whole growing period. The accumulations of N, P2O5 and K2O in the cotton plants could be described with a logistic curve equation. There was the fastest nutrient uptake at about 90 d for N, 92 d for P2O5 and 85 d for K2O after emergence, respectively. Total nutrient accumulation of N, P2O5 and K2O was 385.8, 244. 7 and 340.3 kg ha-1, respectively. Approximately 12. 5 kg N, 8. 0 kg P2O5 and 11.1 kg K2O were needed for producing 100 kg lint with the leaves and stems under the super high yield condition of 3 000 kg ha-1 in Xinjiang.展开更多
基金supported by the NSFC(11501269)and the Natural Science Foundation of Gansu Province(23JRRA1041).
文摘The outbreak of infectious diseases is the result of a combination of various factors,including season,the movement of individuals,non-pharmaceutical interventions(NPIs)and the effectiveness and availability of vaccines.Taking these key elements into consideration,an almost periodic SVEIR warning model in the patch environment is here proposed.First,in terms of reproduction numbers,our results imply that if the effective reproduction numbers are R_(e)<1,then the disease dies out;if R_(e)>1,then the disease spreads and leads to local outbreaks.Second,the relationships between R_(e)and C_(s1),C_(a1)(see Section 2)are given by numerical simulations.The numerical results show that even if all people are vaccinated,NPIs are still needed because of the potentially low efficacy of vaccines.Furthermore,the numerical results suggest that NPIs and the strengthening of the effective rate of vaccination are essential in order to achieve herd immunity.Theories involving this model effectively explain the transmission mechanism of most infectious diseases,and provide a valuable theoretical basis for analyzing new infectious diseases in the future.Moreover,this model is helpful for the prevention and control of infectious diseases and the formulation of public health safety policies.
基金supported by the confidential research grant No.a8317。
文摘To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.
基金supported by National Natural Science Foundation of China (Grant Nos. 51139007, 51079151, 51079152)Research Fundfor the Doctoral Program of Higher Education of China (Grant No. 0100008110012)
文摘The current research of large eddy simulation （LES） of turbulent flow in pumps mainly concentrates in applying conventional subgrid-scale （SGS） model to simulate turbulent flow, which aims at obtaining the flow field in pump. The selection of SGS model is usually not considered seriously, so the accuracy and efficiency of the simulation cannot be ensured. Three SGS models including Smagorinsky-Lilly model, dynamic Smagorinsky model and dynamic mixed model are comparably studied by using the commercial CFD code Fluent combined with its user define function. The simulations are performed for the turbulent flow in a centrifugal pump impeller. The simulation results indicate that the mean flows predicted by the three SGS models agree well with the experimental data obtained from the test that detailed measurements of the flow inside the rotating passages of a six-bladed shrouded centrifugal pump impeller performed using particle image velocimetry （PIV） and laser Doppler velocimetry （LDV）. The comparable results show that dynamic mixed model gives the most accurate results for mean flow in the centrifugal pump impeller. The SGS stress of dynamic mixed model is decompose into the scale similar part and the eddy viscous part. The scale similar part of SGS stress plays a significant role in high curvature regions, such as the leading edge and training edge of pump blade. It is also found that the dynamic mixed model is more adaptive to compute turbulence in the pump impeller. The research results presented is useful to improve the computational accuracy and efficiency of LES for centrifugal pumps, and provide important reference for carrying out simulation in similar fluid machineries.
基金supported by the National Natural Science Foundation of China Basic Science Center Program for“Multiscale Problems in Nonlinear Mechanics”(Grant No.11988102)the National Natural Science Foundation of China(Grant No.12202451).
文摘This paper investigates the capabilities of large language models(LLMs)to leverage,learn and create knowledge in solving computational fluid dynamics(CFD)problems through three categories of baseline problems.These categories include(1)conventional CFD problems that can be solved using existing numerical methods in LLMs,such as lid-driven cavity flow and the Sod shock tube problem;(2)problems that require new numerical methods beyond those available in LLMs,such as the recently developed Chien-physics-informed neural networks for singularly perturbed convection-diffusion equations;and(3)problems that cannot be solved using existing numerical methods in LLMs,such as the ill-conditioned Hilbert linear algebraic systems.The evaluations indicate that reasoning LLMs overall outperform non-reasoning models in four test cases.Reasoning LLMs show excellent performance for CFD problems according to the tailored prompts,but their current capability in autonomous knowledge exploration and creation needs to be enhanced.
基金supported by the National Natural Science Foundation of China[Grant Nos.U23A2073(P.Z.)and 11547034(H.Z.)].
文摘The measurement of the pairing gap is crucial for investigating the physical properties of superconductors or superfluids.We propose a strategy to measure the pairing gap through the dynamical excitations.With the random phase approximation(RPA),we study the dynamical excitations of a two-dimensional attractive Fermi-Hubbard model by calculating its dynamical structure factor.Two distinct collective modes emerge:a Goldstone phonon mode at transferred momentum q=[0,0]and a roton mode at q=[p,p].The roton mode exhibits a sharp molecular peak in the low-energy regime.Notably,the area under the roton molecular peak scales with the square of the pairing gap,which holds even in three-dimensional and spin-orbit coupled(SOC)optical lattices.This finding suggests an experimental approach to measure the pairing gap in lattice systems by analyzing the dynamical structure factor at q=[p,p].
文摘This work reviews models and methods for determining the dynamic response of pavements to moving vehicle loads in the framework of continuum-based three dimensional models and linear theories.This review emphasizes the most representative models and methods of analysis in the existing literature and illustrates all of them by numerical examples.Thus,13 such examples are presented here in some detail.Both flexible and rigid(concrete)pavement models involving simple and elaborate cases with respect to geometry and material behavior are considered.Thus,homogeneous or layered half-spaces with isotropic or cross-anisotropic and elastic,viscoelastic or poroelastic properties are considered.The vehicles are modeled as simple point or distributed loads or discrete spring-mass-dashpot system moving with constant or variable velocity.The dynamic response of the above pavement-vehicle systems is obtained by analytical/numerical or purely numerical methods of solution.Analytical/numerical methods have mainly to do with Fourier transforms or complex Fourier series with respect to both space and time.Purely numerical methods involve the finite element method(FEM)and the boundary element method(BEM)working in time or frequency domain.Critical discussions on the advantages and disadvantages of the various pavement-vehicle models and their methods of analysis are provided and the effects of the main parameters on the pavement response are determined through parametric studies and presented in the examples.Finally,conclusions are provided and suggestions for future research are made.
基金Supported by National Key Research and Development Program(Grant No.2024YFB3312700)National Natural Science Foundation of China(Grant No.52405541)the Changzhou Municipal Sci&Tech Program(Grant No.CJ20241131)。
文摘Under the paradigm of Industry 5.0,intelligent manufacturing transcends mere efficiency enhancement by emphasizing human-machine collaboration,where human expertise plays a central role in assembly processes.Despite advancements in intelligent and digital technologies,assembly process design still heavily relies on manual knowledge reuse,and inefficiencies and inconsistent quality in process documentation are caused.To address the aforementioned issues,this paper proposes a knowledge push method of complex product assembly process design based on distillation model-based dynamically enhanced graph and Bayesian network.First,an initial knowledge graph is constructed using a BERT-BiLSTM-CRF model trained with integrated human expertise and a fine-tuned large language model.Then,a confidence-based dynamic weighted fusion strategy is employed to achieve dynamic incremental construction of the knowledge graph with low resource consumption.Subsequently,a Bayesian network model is constructed based on the relationships between assembly components,assembly features,and operations.Bayesian network reasoning is used to push assembly process knowledge under different design requirements.Finally,the feasibility of the Bayesian network construction method and the effectiveness of Bayesian network reasoning are verified through a specific example,significantly improving the utilization of assembly process knowledge and the efficiency of assembly process design.
文摘A second-order dynamic model based on the general relation between the subgrid-scale stress and the velocity gradient tensors was proposed. A priori test of the second-order model was made using moderate resolution direct numerical simulation date at high Reynolds number ( Taylor microscale Reynolds number R-lambda = 102 similar to 216) for homogeneous, isotropic forced flow, decaying flow, and homogeneous rotating flow. Numerical testing shows that the second-order dynamic model significantly improves the correlation coefficient when compared to the first-order dynamic models.
基金supported by the National Key Research and Development Program of China(Grant Nos.2020YFA0711800,2019YFA0405302)NSFC Projects(Grant Nos.12072349,91852203)+1 种基金National Numerical Windtunnel Project,Science Challenge Project(Grant No.TZ2016001)Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDC01000000).
文摘The subgrid-scale(SGS)kinetic energy has been used to predict the SGS stress in compressible flow and it was resolved through the SGS kinetic energy transport equation in past studies.In this paper,a new SGS eddy-viscosity model is proposed using artificial neural network to obtain the SGS kinetic energy precisely,instead of using the SGS kinetic energy equation.Using the infinite series expansion and reserving the first term of the expanded term,we obtain an approximated SGS kinetic energy,which has a high correlation with the real SGS kinetic energy.Then,the coefficient of the modelled SGS kinetic energy is resolved by the artificial neural network and the modelled SGS kinetic energy is more accurate through this method compared to the SGS kinetic energy obtained from the SGS kinetic energy equation.The coefficients of the SGS stress and SGS heat flux terms are determined by the dynamic procedure.The new model is tested in the compressible turbulent channel flow.From the a posterior tests,we know that the new model can precisely predict the mean velocity,the Reynolds stress,the mean temperature and turbulence intensities,etc.
文摘A sufficient condition for the asymptotic stability of the equilibrium point of a system, which appears as a model for couple of the love affair with time delay, is obtained by applying the technique of linearized method and Hopf- bifurcation.
基金The study was supported by the National Key R&D Program of China(No.2018YFB0505400)the National Natural Science Foundation of China(No.61472202)+1 种基金the Special Scientific Research Fund of China Railway Corporation(No.J2017X010)the Research on Key Technologies of Virtual Engineering of Railway Engineering Unit Based on BIM Technology(No.K2018G055).
文摘Industry foundation classes(IFC)is an open and neutral data format specification for building information modeling(BIM)that plays a crucial role in facilitating interoperability.With increases in web-based BIM applications,there is an urgent need for fast loading large IFC models on a web browser.However,the task of fully loading large IFC models typically consumes a large amount of memory of a web browser or even crashes the browser,and this significantly limits further BIM applications.In order to address the issue,a method is proposed for dynamically loading IFC models based on spatial semantic partitioning(SSP).First,the spatial semantic structure of an input IFC model is partitioned via the extraction of story information and establishing a component space index table on the server.Subsequently,based on user interaction,only the model data that a user is interested in is transmitted,loaded,and displayed on the client.The presented method is implemented via Web Graphics Library,and this enables large IFC models to be fast loaded on the web browser without requiring any plug-ins.When compared with conventional methods that load all IFC model data for display purposes,the proposed method significantly reduces memory consumption in a web browser,thereby allowing the loading of large IFC models.When compared with the existing method of spatial partitioning for 3D data,the proposed SSP entirely uses semantic information in the IFC file itself,and thereby provides a better interactive experience for users.
基金The research is funded by National Natural Science Foundation (40231016) and Canadian International Development Agency (CIDA).
文摘As the largest pool of terrestrial organic carbon, soils interact strongly with atmosphere composition, climate, and land change. Soil organic carbon dynamics in ecosystem plays a great role in global carbon cycle and global change. With development of mathematical models that simulate changes in soil organic carbon, there have been considerable advances in understanding soil organic carbon dynamics. This paper mainly reviewed the composition of soil organic matter and its influenced factors, and recommended some soil organic matter models worldwide. Based on the analyses of the developed results at home and abroad, it is suggested that future soil organic matter models should be developed toward based-process models, and not always empirical ones. The models are able to reveal their interaction between soil carbon systems, climate and land cover by technique and methods of GIS (Geographical Information System) and RS (Remote Sensing). These models should be developed at a global scale, in dynamically describing the spatial and temporal changes of soil organic matter cycle. Meanwhile, the further researches on models should be strengthen for providing theory basis and foundation in making policy of green house gas emission in China.
文摘Mathematical models of tire-longitudinal road adhesion for use in the study of road vehicle dynamics are set up so as to express the relations of longitudinal adhesion coefficients with the slip ratio. They perfect the Pacejka's models in practical use by taking into account the influences of all essential parameters such as road surface condition. vehicle velocity. slip angle. vertical load and slip ratio on the longitudinal adhesion coefficients. The new models are more comprehensive more concise. simpler and more convenient in application in all kinds of simulations of car dynamics in various sorts of braking modes.
文摘The cause-effect relationship is not always possible to trace in GCMs because of the simultaneous inclusion of several highly complex physical processes. Furthermore, the inter-GCM differences are large and there is no simple way to reconcile them. So, simple climate models, like statistical-dynamical models (SDMs), appear to be useful in this context. This kind of models is essentially mechanistic, being directed towards understanding the dependence of a particular mechanism on the other parameters of the problem. In this paper, the utility of SDMs for studies of climate change is discussed in some detail. We show that these models are an indispensable part of hierarchy of climate models.
文摘Mathematical models of tire-lateral mad adhesion for use in mad vehicle dynamics studies are set up to express the relations of adhesion coefficients with slip ratio in lateral direction.The models of tire-lateral mad adhesion revolutionize the Pacejka's model in concept and therefore make it possible for applications in vehicle dynamics studies by the expression of lateral adhesion coefficient as a function of wheel slip ratio,instead of the wheel slip angle,taking into account in the mean time the influences of mad surface condition, vehicle velocity,vertical load,tire slip angle,and wheel camber angle.
基金sponsored by the National Natural Science Foundation of China(Nos.11772261 and 11972305)Aeronautical Science Foundation of China(No.2016ZA53011)Foundation of National Key Laboratory(No.JCKYS2019607005).
文摘A variable-fidelity method can remarkably improve the efficiency of a design optimization based on a high-fidelity and expensive numerical simulation,with assistance of lower-fidelity and cheaper simulation(s).However,most existing works only incorporate‘‘two"levels of fidelity,and thus efficiency improvement is very limited.In order to reduce the number of high-fidelity simulations as many as possible,there is a strong need to extend it to three or more fidelities.This article proposes a novel variable-fidelity optimization approach with application to aerodynamic design.Its key ingredient is the theory and algorithm of a Multi-level Hierarchical Kriging(MHK),which is referred to as a surrogate model that can incorporate simulation data with arbitrary levels of fidelity.The high-fidelity model is defined as a CFD simulation using a fine grid and the lower-fidelity models are defined as the same CFD model but with coarser grids,which are determined through a grid convergence study.First,sampling shapes are selected for each level of fidelity via technique of Design of Experiments(DoE).Then,CFD simulations are conducted and the output data of varying fidelity is used to build initial MHK models for objective(e.g.C_D)and constraint(e.g.C_L,C_m)functions.Next,new samples are selected through infillsampling criteria and the surrogate models are repetitively updated until a global optimum is found.The proposed method is validated by analytical test cases and applied to aerodynamic shape optimization of a NACA0012 airfoil and an ONERA M6 wing in transonic flows.The results confirm that the proposed method can significantly improve the optimization efficiency and apparently outperforms the existing single-fidelity or two-level-fidelity method.
基金the National Natural Science Foundation of China (Grant 11772128)the Fundamental Research Funds for the Central Universities (Grants 2017MS022 and 2018ZD09).
文摘In previous attempts of rational subgrid-scale (SGS) modeling by employing the Kolmogorov equation of filtered (KEF) quantities, it was necessary to assume that the resolved-scale second-order structure function is stationary. Forced isotropic turbulence is often used as a framework for establishing and validating such SGS models based on stationary restrictions, for it generates statistical stationary samples. However, traditional forcing method at low wavenumbers cannot provide an analytic form of forcing term for a complete KEF in physical space, which has been illustrated to be essential in the modeling of such SGS models. Thus, an alternative forcing method giving an analytic forcing term in physical space is needed for rational SGS modeling. Giving an analytic linear driving term in physical space, linearly forced isotropic turbulence should be considered an ideal theoretical framework for rational SGS modeling. In this paper, we demonstrate the feasibility of establishing a rational SGS model with stationary restriction based on linearly forced isotropic turbulence. The performance of this rational SGS model is validated. We, therefore, propose the use of linearly forced isotropic turbulence as a complement to free-decaying isotropic turbulence and low-wavenumber forced isotropic turbulence for SGS model validations.
基金Supported by the National Natural Science Foundation of China under Grant Nos.11562014,11762011,11671101,71471020,51839002the Natural Science Foundation of Inner Mongolia under Grant No.2017MS0108+4 种基金Hunan Provincial Natural Science Foundation of China under Grant No.2016JJ2061the Scientific Research Fund of Hunan Provincial Education Department under Grant No.18A325the Construct Program of the Key Discipline in Hunan Province under Grant No.201176the Aid Program for Science and Technology Innovative Research Team in Higher Educational Instituions of Hunan Province under Grant No.2014207Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering of Changsha University of Science and Technology under Grant No.018MMAEZD191
文摘In this paper, we study the higher dimensional nonlinear Rossby waves under the generalized beta effect.Using methods of the multiple scales and weak nonlinear perturbation expansions [Q. S. Liu, et al., Phys. Lett. A383(2019) 514], we derive a new(2 + 1)-dimensional generalized Boussinesq equation from the barotropic potential vorticity equation. Based on bifurcation theory of planar dynamical systems and the qualitative theory of ordinary differential equations, the dynamical analysis and exact traveling wave solutions of the new generalized Boussinesq equation are obtained. Moreover, we provide the numerical simulations of these exact solutions under some conditions of all parameters. The numerical results show that these traveling wave solutions are all the Rossby solitary waves.
文摘The dynamical framework of the nine-level version of the IAP AGCM is presented in this paper. The emphasis of the model's description is put on the following two aspects:(1) A model's standard atmosphere, which is a satisfactory approximation to the observed troposphere and lower stratosphere standard atmosphere, is introduced into the equations of the model to permit a more accurate calculation of the vertical transport terms, especially near the tropopause; (2) The vertical levels of the model are carefully selected to guarantee a smooth dependence of layer thickness upon pressure in order to reduce the truncation error involved in the unequal interval vertical finite-differencing. For testing the model, two kinds of linear baroclinic Rossby-Haurwitz waves, one of which has a dynamically stable vertical structure and the other has a relatively unstable one, are constructed to provide initial conditions for numerical experiments. The two waves have been integrated for more than 300 days and 100 days respectively by using the model and both of them are propagating westward with almost identical phase-speed during the time period of the integrations. No obvious change of the wave patterns is found at the levels in the model's troposphere. The amplitudes of both two waves at the uppermost level, however, exhibit rather significant oscillation with time, of which the periods are exactly 20 days and 25 days espectively.The explanation of this interesting phenomena is still under investigation.
基金supported by the National Key Technologies R&D Program in 10th Five-year Plan of China(2001BA507A)the National Natural Sicence Foundation of China(39760040).
文摘The field experiments were carried out to investigate the dynamics and models of N, P and K absorption for the cotton plants with a lint of 3 000 kg ha-1 in Xinjiang. The main results were as follows: The contents of N, P2O5, K2O in cotton leaves, stems, squares and bolls decreased obviously with the time over the whole growth duration and the falling extent was greater in high-yield cotton than in CK. Contents of N in leaves, squares and bolls, in particular in the leaves of fruit-bearing shoot was higher in high-yield cotton than in CK. Contents of P2O5 in squares and bolls and that of K2O in stems were higher in high-yield cotton than in CK during the whole growing period. The accumulations of N, P2O5 and K2O in the cotton plants could be described with a logistic curve equation. There was the fastest nutrient uptake at about 90 d for N, 92 d for P2O5 and 85 d for K2O after emergence, respectively. Total nutrient accumulation of N, P2O5 and K2O was 385.8, 244. 7 and 340.3 kg ha-1, respectively. Approximately 12. 5 kg N, 8. 0 kg P2O5 and 11.1 kg K2O were needed for producing 100 kg lint with the leaves and stems under the super high yield condition of 3 000 kg ha-1 in Xinjiang.
