Lithium ion battery has typical character of distributed parameter system, and can be described precisely by partial differential equations and multi-physics theory because lithium ion battery is a complicated electro...Lithium ion battery has typical character of distributed parameter system, and can be described precisely by partial differential equations and multi-physics theory because lithium ion battery is a complicated electrochemical energy storage system. A novel failure prediction modeling method of lithium ion battery based on distributed parameter estimation and single particle model is proposed in this work. Lithium ion concentration in the anode of lithium ion battery is an unmeasurable distributed variable. Failure prediction system can estimate lithium ion concentration online, track the failure residual which is the difference between the estimated value and the ideal value. The precaution signal will be triggered when the failure residual is beyond the predefined failure precaution threshold, and the failure countdown prediction module will be activated. The remaining time of the severe failure threshold can be estimated by the failure countdown prediction module according to the changing rate of the failure residual. A simulation example verifies that lithium ion concentration in the anode of lithium ion battery can be estimated exactly and effectively by the failure prediction model. The precaution signal can be triggered reliably, and the remaining time of the severe failure can be forecasted accurately by the failure countdown prediction module.展开更多
This work aims to investigate the effects of dosing regiments on drug delivery in solid tumors and to validate them with experiments on rats. The lumped parameter models of pharmacokinetics and of drug delivery in tum...This work aims to investigate the effects of dosing regiments on drug delivery in solid tumors and to validate them with experiments on rats. The lumped parameter models of pharmacokinetics and of drug delivery in tumor were developed to simulate time courses of average drug concentration （Ct） of tumor interstitium in two types of dosing regiments （i.e., single-shot and triple-shot ones）. The two regiments were performed via antitumor drug, hydroxycamptothecin （HCPT）, on rats, to measure the drug concentration in the tumor. The simulations of the drug concentration in the tumor of the two dosing regiments were conducted and compared with the experimental data on rats. The coefficients in the models were investigated. It is concluded that the triple-shot method is more effective than that of single-shot injection. The present lumped-parameter model is quantitatively competent for drug delivery in solid tumor.展开更多
The constitutive model is essential for predicting the deformation and stability of rocksoil mass.The estimation of constitutive model parameters is a necessary and important task for the reliable characterization of ...The constitutive model is essential for predicting the deformation and stability of rocksoil mass.The estimation of constitutive model parameters is a necessary and important task for the reliable characterization of mechanical behaviors.However,constitutive model parameters cannot be evaluated accurately with a limited amount of test data,resulting in uncertainty in the prediction of stress-strain curves.This paper proposes a Bayesian analysis framework to address this issue.It combines the Bayesian updating with the structural reliability and adaptive conditional sampling methods to assess the equation parameter of constitutive models.Based on the triaxial and ring shear tests on shear zone soils from the Huangtupo landslide,a statistical damage constitutive model and a critical state hypoplastic constitutive model were used to demonstrate the effectiveness of the proposed framework.Moreover,the parameter uncertainty effects of the damage constitutive model on landslide stability were investigated.Results show that reasonable assessments of the constitutive model parameter can be well realized.The variability of stress-strain curves is strongly related to the model prediction performance.The estimation uncertainty of constitutive model parameters should not be ignored for the landslide stability calculation.Our study provides a reference for uncertainty analysis and parameter assessment of the constitutive model.展开更多
This paper is an introduction to mesh based generated reluctance network modeling.An overview of scientific works which led to the development of this approach is first presented.Basic concepts of the approach are the...This paper is an introduction to mesh based generated reluctance network modeling.An overview of scientific works which led to the development of this approach is first presented.Basic concepts of the approach are then presented in the case of electromagnetic devices.A step-by-step procedure for coding the approach in the case of a flat linear permanent magnet machine is presented.Codes developed under MATLAB and Scilab environments are also included.展开更多
This paper is an introduction to mesh based generated reluctance network modeling using triangular elements.Many contributions on mesh based generated reluctance networks using rectangular shaped elements have been pu...This paper is an introduction to mesh based generated reluctance network modeling using triangular elements.Many contributions on mesh based generated reluctance networks using rectangular shaped elements have been published,but very few on those generated from a mesh using triangular elements.The use of triangular elements is aimed at extending the application of the approach to any shape of modeled devices.Basic concepts of the approach are presented in the case of electromagnetic devices.The procedure for coding the approach in the case of a flat linear permanent magnet machine is presented.Codes developed under MATLAB environment are also included.展开更多
Three degrees of freedom (3-DOF) Helmholtz resonator which consists of three cylindrical necks and cavities connected in series (neck-cavity-neck-cavity-neck-cavity) is suitable to reduce flow pulsation in hydraulic s...Three degrees of freedom (3-DOF) Helmholtz resonator which consists of three cylindrical necks and cavities connected in series (neck-cavity-neck-cavity-neck-cavity) is suitable to reduce flow pulsation in hydraulic system. A novel lumped parameter model (LPM) of 3-DOF Helmholtz resonator in hydraulic system is developed which considers the viscous friction loss of hy- draulic fluid in the necks. Applying the Newton's second law of motion to the equivalent mechanical model of the resonator, closed-form expression of transmission loss and resonance frequency is presented. Based on the LPM, an optimal design method which employs rotate vector optimization method (RVOM) is proposed. The purpose of the optimal design is to search the reso- nator's unknown parameters so that its resonance frequencies can coincide with the pump-induced flow pulsation harmonics respectively. The optimal design method is realized to design 3-DOF Helmholtz resonator for a certain type of aviation piston pump hydraulic system. The optimization result shows the feasibility of this method, and the simulation under optimum parame- ters reveals that the LPM can get the same precision as transfer matrix method (TMM).展开更多
Within a theoretical ENSO model, the authors investigated whether or not the errors superimposed on model parameters could cause a significant ＂spring predictability barrier＂ （SPB） for El Nio events. First, sensit...Within a theoretical ENSO model, the authors investigated whether or not the errors superimposed on model parameters could cause a significant ＂spring predictability barrier＂ （SPB） for El Nio events. First, sensitivity experiments were respectively performed to the air-sea coupling parameter, α and the thermocline effect coefficient μ. The results showed that the uncertainties superimposed on each of the two parameters did not exhibit an obvious season-dependent evolution; furthermore, the uncertainties caused a very small prediction error and consequently failed to yield a significant SPB. Subsequently, the conditional nonlinear optimal perturbation （CNOP） approach was used to study the effect of the optimal mode （CNOP-P） of the uncertainties of the two parameters on the SPB and to demonstrate that the CNOP-P errors neither presented a unified season-dependent evolution for different El Nio events nor caused a large prediction error, and therefore did not cause a significant SPB. The parameter errors played only a trivial role in yielding a significant SPB. To further validate this conclusion, the authors investigated the effect of the optimal combined mode （i.e. CNOP error） of initial and model errors on SPB. The results illustrated that the CNOP errors tended to have a significant season-dependent evolution, with the largest error growth rate in the spring, and yielded a large prediction error, inducing a significant SPB. The inference, therefore, is that initial errors, rather than model parameter errors, may be the dominant source of uncertainties that cause a significant SPB for El Nio events. These results indicate that the ability to forecast ENSO could be greatly increased by improving the initialization of the forecast model.展开更多
By analyzing the optical spectra and electron paramagnetic resonance parameter D, the local structure distortion of （NiF6）4- clusters in AMF3 （A=K, Rb; M=Zn, Cd, Ca） and K2ZnF4 series are studied using the complet...By analyzing the optical spectra and electron paramagnetic resonance parameter D, the local structure distortion of （NiF6）4- clusters in AMF3 （A=K, Rb; M=Zn, Cd, Ca） and K2ZnF4 series are studied using the complete energy matrix based on the double spin-orbit coupling parameter model for configuration ions in a tetragonal ligand field. The results indicate that the contribution of ligand to spin-orbit coupling interaction should be considered for our studied systems. Moreover, the relationships between D and the spin-obit coupling coefficients as well as the average parameter and the divergent parameter are discussed.展开更多
Firstly, the research progress of grey model GM （1,1） is summarized, which is divided into three development stages： assimilation, alienation and melting stages. Then, the matrix analysis theory is used to study th...Firstly, the research progress of grey model GM （1,1） is summarized, which is divided into three development stages： assimilation, alienation and melting stages. Then, the matrix analysis theory is used to study the modeling mechanism of GM （1,1）, which decomposes the modeling data matrix into raw data transformation matrix, accumulated generating operation matrix and background value selection matrix. The changes of these three matrices are the essential reasons affecting the modeling and the accuracy of GM （1,1）. Finally, the paper proposes a generalization grey model GGM （1,1）, which is a extended form of GM （1,1） and also a unified form of model GM （1,1）, model GM （1,1,α）, stage grey model, hopping grey model, generalized accumulated model, strengthening operator model, weakening operator model and unequal interval model. And the theory and practical significance of the extended model is analyzed.展开更多
In this work, temperature dependences of small-signal model parameters in the SiGe HBT HICUM model are presented. Electrical elements in the small-signal equivalent circuit are first extracted at each temperature, the...In this work, temperature dependences of small-signal model parameters in the SiGe HBT HICUM model are presented. Electrical elements in the small-signal equivalent circuit are first extracted at each temperature, then the temperature dependences are determined by the series of extracted temperature coefficients, based on the established temperature for- mulas for corresponding model parameters. The proposed method is validated by a 1x 0.2 x 16 μm2 SiGe HBT over a wide temperature range （from 218 K to 473 K）, and good matching is obtained between the extracted and modeled resuits. Therefore, we believe that the proposed extraction flow of model parameter temperature dependence is reliable for characterizing the transistor performance and guiding the circuit design over a wide temperature range.展开更多
The modelling of the distribution transformer winding is the starting point and serves as important basis for the transformer characteristics analysis and the lightning pulse response prediction.A distributed paramete...The modelling of the distribution transformer winding is the starting point and serves as important basis for the transformer characteristics analysis and the lightning pulse response prediction.A distributed parameters model can depict the winding characteristics accurately,but it requires complex calculations.Lumped parameter model requires less calculations,but its applicable frequency range is not wide.This paper studies the amplitude-frequency characteristics of the lightning wave,compares the transformer modelling methods and finally proposes a modified lumped parameter model,based on the above comparison.The proposed model minimizes the errors provoked by the lumped parameter approximation,and the hyperbolic functions of the distributed parameter model.By this modification it becomes possible to accurately describe the winding characteristics and rapidly obtain the node voltage response.The proposed model can provide theoretical and experimental support to lightning protection of the distribution transformer.展开更多
Gear fault diagnosis technologies have received rapid development and been effectively implemented in many engineering applications.However,the various working conditions would degrade the diagnostic performance and m...Gear fault diagnosis technologies have received rapid development and been effectively implemented in many engineering applications.However,the various working conditions would degrade the diagnostic performance and make gear fault diagnosis(GFD)more and more challenging.In this paper,a novel model parameter transfer(NMPT)is proposed to boost the performance of GFD under varying working conditions.Based on the previous transfer strategy that controls empirical risk of source domain,this method further integrates the superiorities of multi-task learning with the idea of transfer learning(TL)to acquire transferable knowledge by minimizing the discrepancies of separating hyperplanes between one specific working condition(target domain)and another(source domain),and then transferring both commonality and specialty parameters over tasks to make use of source domain samples to assist target GFD task when sufficient labeled samples from target domain are unavailable.For NMPT implementation,insufficient target domain features and abundant source domain features with supervised information are fed into NMPT model to train a robust classifier for target GFD task.Related experiments prove that NMPT is expected to be a valuable technology to boost practical GFD performance under various working conditions.The proposed methods provides a transfer learning-based framework to handle the problem of insufficient training samples in target task caused by variable operation conditions.展开更多
Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations...Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations often arise from inappropriate model parameterization.Here we compared five methods for defining community-level specific leaf area(SLA)and leaf C:N across nine contrasting forest sites along the North-South Transect of Eastern China,including biomass-weighted average for the entire plant community(AP_BW)and four simplified selective sampling(biomass-weighted average over five dominant tree species[5DT_BW],basal area weighted average over five dominant tree species[5DT_AW],biomass-weighted average over all tree species[AT_BW]and basal area weighted average over all tree species[AT_AW]).We found that the default values for SLA and leaf C:N embedded in the Biome-BGC v4.2 were higher than the five computational methods produced across the nine sites,with deviations ranging from 28.0 to 73.3%.In addition,there were only slight deviations(<10%)between the whole plant community sampling(AP_BW)predicted NPP and the four simplified selective sampling methods,and no significant difference between the predictions of AT_BW and AP_BW except the Shennongjia site.The findings in this study highlights the critical importance of computational strategies for community-level parameterization in ecosystem process modelling,and will support the choice of parameterization methods.展开更多
Aircraft wake turbulence is an inherent outcome of aircraft flight,presenting a substan-tial challenge to air traffic control,aviation safety and operational efficiency.Building upon data obtained from coherent Dopple...Aircraft wake turbulence is an inherent outcome of aircraft flight,presenting a substan-tial challenge to air traffic control,aviation safety and operational efficiency.Building upon data obtained from coherent Doppler Lidar detection,and combining Dynamic Bayesian Networks(DBN)with Genetic Algorithm-optimized Backpropagation Neural Networks(GA-BPNN),this paper proposes a model for the inversion of wake vortex parameters.During the wake vortex flow field simulation analysis,the wind and turbulent environment were initially superimposed onto the simulated wake velocity field.Subsequently,Lidar-detected echoes of the velocity field are simulated to obtain a data set similar to the actual situation for model training.In the case study validation,real measured data underwent preprocessing and were then input into the established model.This allowed us to construct the wake vortex characteristic parameter inversion model.The final results demonstrated that our model achieved parameter inversion with only minor errors.In a practical example,our model in this paper significantly reduced the mean square error of the inverted velocity field when compared to the traditional algorithm.This study holds significant promise for real-time monitoring of wake vortices at airports,and is proved a crucial step in developing wake vortex interval standards.展开更多
The estimation of model parameters is an important subject in engineering.In this area of work,the prevailing approach is to estimate or calculate these as deterministic parameters.In this study,we consider the model ...The estimation of model parameters is an important subject in engineering.In this area of work,the prevailing approach is to estimate or calculate these as deterministic parameters.In this study,we consider the model parameters from the perspective of random variables and describe the general form of the parameter distribution inference problem.Under this framework,we propose an ensemble Bayesian method by introducing Bayesian inference and the Markov chain Monte Carlo(MCMC)method.Experiments on a finite cylindrical reactor and a 2D IAEA benchmark problem show that the proposed method converges quickly and can estimate parameters effectively,even for several correlated parameters simultaneously.Our experiments include cases of engineering software calls,demonstrating that the method can be applied to engineering,such as nuclear reactor engineering.展开更多
Chemical processes are usually nonlinear singular systems.In this study,a soft sensor using nonlinear singular state observer is established for unknown inputs and uncertain model parameters in chemical processes,whic...Chemical processes are usually nonlinear singular systems.In this study,a soft sensor using nonlinear singular state observer is established for unknown inputs and uncertain model parameters in chemical processes,which are augmented as state variables.Based on the observability of the singular system,this paper presents a simplified observability criterion under certain conditions for unknown inputs and uncertain model parameters.When the observability is satisfied,the unknown inputs and the uncertain model parameters are estimated online by the soft sensor using augmented nonlinear singular state observer.The riser reactor of fluid catalytic cracking unit is used as an example for analysis and simulation.With the catalyst circulation rate as the only unknown input without model error,one temperature sensor at the riser reactor outlet will ensure the correct estimation for the catalyst circulation rate.However,when uncertain model parameters also exist,additional temperature sensors must be used to ensure correct estimation for unknown inputs and uncertain model parameters of chemical processes.展开更多
To investigate the dynamic characteristics and damping theory of the passive hydraulic engine mount （PHEM）, numerical prediction is performed through lumped parameter model. System parameters, including volume compl...To investigate the dynamic characteristics and damping theory of the passive hydraulic engine mount （PHEM）, numerical prediction is performed through lumped parameter model. System parameters, including volume compliance of the decoupler chamber, effective piston area, fluid inertia and resistance of inertia track and direct-decoupler, are identified by means of experiments and finite element method （FEM）. Dynamic behaviors are tested with elastomer test system for purpose of validating PHEM. With incorporation of inertia track and direct-decoupler, PHEM behaves effective and efficient vibration isolation in range of both low and high frequencies. The comparison of the numerical results with the experimental observations shows that the present PHEM achieves fairly good performance for the engine vibration isolation.展开更多
This paper describes a flood routing method applied in an ungauged basin, utilizing the Muskingum model with variable parameters of wave travel time K and weight coefficient of discharge x based on the physical charac...This paper describes a flood routing method applied in an ungauged basin, utilizing the Muskingum model with variable parameters of wave travel time K and weight coefficient of discharge x based on the physical characteristics of the river reach and flood, including the reach slope, length, width, and flood discharge. Three formulas for estimating parameters of wide rectangular, triangular, and parabolic cross sections are proposed. The influence of the flood on channel flow routing parameters is taken into account. The HEC-HMS hydrological model and the geospatial hydrologic analysis module HEC-GeoHMS were used to extract channel or watershed characteristics and to divide sub-basins. In addition, the initial and constant-rate method, user synthetic unit hydrograph method, and exponential recession method were used to estimate runoff volumes, the direct runoff hydrograph, and the baseflow hydrograph, respectively. The Muskingum model with variable parameters was then applied in the Louzigou Basin in Henan Province of China, and of the results, the percentages of flood events with a relative error of peak discharge less than 20% and runoff volume less than 10% are both 100%. They also show that the percentages of flood events with coefficients of determination greater than 0.8 are 83.33%, 91.67%, and 87.5%, respectively, for rectangular, triangular, and parabolic cross sections in 24 flood events. Therefore, this method is applicable to ungauged basins.展开更多
In order to achieve prediction for vibration of rotating machinery, an accurate finite element （FE） model and an efficient parameter identification method of the rotor system are required. In this research, a test r...In order to achieve prediction for vibration of rotating machinery, an accurate finite element （FE） model and an efficient parameter identification method of the rotor system are required. In this research, a test rig is used as a prototype of a rotor system to validate a novel parameter identification technique based on an FE model. Rotor shaft vibration at varying operating speeds is measured and correlated with the FE results. Firstly, the theories of the FE modelling and identification technique are introduced. Then disk unbalance parameter, stiffness and damping coefficients of the bearing supports on the test rig are identified. The calculated responses of the FE model with identified parameters are studied in comparison with the experimental results.展开更多
基金This work was supported by the Fundamental Research Funds for the Central Universities （No.2017JBM003）, the National Natural Science Foundation of China （No.61575053, No.61504008）, and the Specialized Research Fund for the Doctoral Program of Higher Education of China （No.20130009120042）.
文摘Lithium ion battery has typical character of distributed parameter system, and can be described precisely by partial differential equations and multi-physics theory because lithium ion battery is a complicated electrochemical energy storage system. A novel failure prediction modeling method of lithium ion battery based on distributed parameter estimation and single particle model is proposed in this work. Lithium ion concentration in the anode of lithium ion battery is an unmeasurable distributed variable. Failure prediction system can estimate lithium ion concentration online, track the failure residual which is the difference between the estimated value and the ideal value. The precaution signal will be triggered when the failure residual is beyond the predefined failure precaution threshold, and the failure countdown prediction module will be activated. The remaining time of the severe failure threshold can be estimated by the failure countdown prediction module according to the changing rate of the failure residual. A simulation example verifies that lithium ion concentration in the anode of lithium ion battery can be estimated exactly and effectively by the failure prediction model. The precaution signal can be triggered reliably, and the remaining time of the severe failure can be forecasted accurately by the failure countdown prediction module.
基金Project suppoted by the National Natural Science Foundation of China (Grant No10372026)the Shanghai Leading Academic Discipline Project (Grant NoB112)
文摘This work aims to investigate the effects of dosing regiments on drug delivery in solid tumors and to validate them with experiments on rats. The lumped parameter models of pharmacokinetics and of drug delivery in tumor were developed to simulate time courses of average drug concentration （Ct） of tumor interstitium in two types of dosing regiments （i.e., single-shot and triple-shot ones）. The two regiments were performed via antitumor drug, hydroxycamptothecin （HCPT）, on rats, to measure the drug concentration in the tumor. The simulations of the drug concentration in the tumor of the two dosing regiments were conducted and compared with the experimental data on rats. The coefficients in the models were investigated. It is concluded that the triple-shot method is more effective than that of single-shot injection. The present lumped-parameter model is quantitatively competent for drug delivery in solid tumor.
基金supported by the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(No.GLAB 2024ZR03)the National Natural Science Foundation of China(No.42407248)+2 种基金the Guizhou Provincial Basic Research Program(Natural Science)(No.QKHJC-[2023]-YB066)the Key Laboratory of Smart Earth(No.KF2023YB04-02)the Fundamental Research Funds for the Central Universities。
文摘The constitutive model is essential for predicting the deformation and stability of rocksoil mass.The estimation of constitutive model parameters is a necessary and important task for the reliable characterization of mechanical behaviors.However,constitutive model parameters cannot be evaluated accurately with a limited amount of test data,resulting in uncertainty in the prediction of stress-strain curves.This paper proposes a Bayesian analysis framework to address this issue.It combines the Bayesian updating with the structural reliability and adaptive conditional sampling methods to assess the equation parameter of constitutive models.Based on the triaxial and ring shear tests on shear zone soils from the Huangtupo landslide,a statistical damage constitutive model and a critical state hypoplastic constitutive model were used to demonstrate the effectiveness of the proposed framework.Moreover,the parameter uncertainty effects of the damage constitutive model on landslide stability were investigated.Results show that reasonable assessments of the constitutive model parameter can be well realized.The variability of stress-strain curves is strongly related to the model prediction performance.The estimation uncertainty of constitutive model parameters should not be ignored for the landslide stability calculation.Our study provides a reference for uncertainty analysis and parameter assessment of the constitutive model.
文摘This paper is an introduction to mesh based generated reluctance network modeling.An overview of scientific works which led to the development of this approach is first presented.Basic concepts of the approach are then presented in the case of electromagnetic devices.A step-by-step procedure for coding the approach in the case of a flat linear permanent magnet machine is presented.Codes developed under MATLAB and Scilab environments are also included.
文摘This paper is an introduction to mesh based generated reluctance network modeling using triangular elements.Many contributions on mesh based generated reluctance networks using rectangular shaped elements have been published,but very few on those generated from a mesh using triangular elements.The use of triangular elements is aimed at extending the application of the approach to any shape of modeled devices.Basic concepts of the approach are presented in the case of electromagnetic devices.The procedure for coding the approach in the case of a flat linear permanent magnet machine is presented.Codes developed under MATLAB environment are also included.
基金National Science Fund for Distinguished Young Scholars (50825502)
文摘Three degrees of freedom (3-DOF) Helmholtz resonator which consists of three cylindrical necks and cavities connected in series (neck-cavity-neck-cavity-neck-cavity) is suitable to reduce flow pulsation in hydraulic system. A novel lumped parameter model (LPM) of 3-DOF Helmholtz resonator in hydraulic system is developed which considers the viscous friction loss of hy- draulic fluid in the necks. Applying the Newton's second law of motion to the equivalent mechanical model of the resonator, closed-form expression of transmission loss and resonance frequency is presented. Based on the LPM, an optimal design method which employs rotate vector optimization method (RVOM) is proposed. The purpose of the optimal design is to search the reso- nator's unknown parameters so that its resonance frequencies can coincide with the pump-induced flow pulsation harmonics respectively. The optimal design method is realized to design 3-DOF Helmholtz resonator for a certain type of aviation piston pump hydraulic system. The optimization result shows the feasibility of this method, and the simulation under optimum parame- ters reveals that the LPM can get the same precision as transfer matrix method (TMM).
基金sponsored by the Knowl-edge Innovation Program of the Chinese Academy of Sciences (No. KZCX2-YW-QN203)the National Basic Re-search Program of China (No. 2007CB411800)the GYHY200906009 of the China Meteorological Administra-tion
文摘Within a theoretical ENSO model, the authors investigated whether or not the errors superimposed on model parameters could cause a significant ＂spring predictability barrier＂ （SPB） for El Nio events. First, sensitivity experiments were respectively performed to the air-sea coupling parameter, α and the thermocline effect coefficient μ. The results showed that the uncertainties superimposed on each of the two parameters did not exhibit an obvious season-dependent evolution; furthermore, the uncertainties caused a very small prediction error and consequently failed to yield a significant SPB. Subsequently, the conditional nonlinear optimal perturbation （CNOP） approach was used to study the effect of the optimal mode （CNOP-P） of the uncertainties of the two parameters on the SPB and to demonstrate that the CNOP-P errors neither presented a unified season-dependent evolution for different El Nio events nor caused a large prediction error, and therefore did not cause a significant SPB. The parameter errors played only a trivial role in yielding a significant SPB. To further validate this conclusion, the authors investigated the effect of the optimal combined mode （i.e. CNOP error） of initial and model errors on SPB. The results illustrated that the CNOP errors tended to have a significant season-dependent evolution, with the largest error growth rate in the spring, and yielded a large prediction error, inducing a significant SPB. The inference, therefore, is that initial errors, rather than model parameter errors, may be the dominant source of uncertainties that cause a significant SPB for El Nio events. These results indicate that the ability to forecast ENSO could be greatly increased by improving the initialization of the forecast model.
文摘By analyzing the optical spectra and electron paramagnetic resonance parameter D, the local structure distortion of （NiF6）4- clusters in AMF3 （A=K, Rb; M=Zn, Cd, Ca） and K2ZnF4 series are studied using the complete energy matrix based on the double spin-orbit coupling parameter model for configuration ions in a tetragonal ligand field. The results indicate that the contribution of ligand to spin-orbit coupling interaction should be considered for our studied systems. Moreover, the relationships between D and the spin-obit coupling coefficients as well as the average parameter and the divergent parameter are discussed.
基金supported by the National Natural Science Foundation of China(70971103)the Specialized Research Fund for the Doctora Program of Higher Education(20120143110001)
文摘Firstly, the research progress of grey model GM （1,1） is summarized, which is divided into three development stages： assimilation, alienation and melting stages. Then, the matrix analysis theory is used to study the modeling mechanism of GM （1,1）, which decomposes the modeling data matrix into raw data transformation matrix, accumulated generating operation matrix and background value selection matrix. The changes of these three matrices are the essential reasons affecting the modeling and the accuracy of GM （1,1）. Finally, the paper proposes a generalization grey model GGM （1,1）, which is a extended form of GM （1,1） and also a unified form of model GM （1,1）, model GM （1,1,α）, stage grey model, hopping grey model, generalized accumulated model, strengthening operator model, weakening operator model and unequal interval model. And the theory and practical significance of the extended model is analyzed.
基金supported partially by the Important National Science&Technology Specific Projects,China(Grant No.2013ZX02503003)
文摘In this work, temperature dependences of small-signal model parameters in the SiGe HBT HICUM model are presented. Electrical elements in the small-signal equivalent circuit are first extracted at each temperature, then the temperature dependences are determined by the series of extracted temperature coefficients, based on the established temperature for- mulas for corresponding model parameters. The proposed method is validated by a 1x 0.2 x 16 μm2 SiGe HBT over a wide temperature range （from 218 K to 473 K）, and good matching is obtained between the extracted and modeled resuits. Therefore, we believe that the proposed extraction flow of model parameter temperature dependence is reliable for characterizing the transistor performance and guiding the circuit design over a wide temperature range.
基金supported by the National Key Research and Development Plan of China under Grant(2016YFB0900600XXX)
文摘The modelling of the distribution transformer winding is the starting point and serves as important basis for the transformer characteristics analysis and the lightning pulse response prediction.A distributed parameters model can depict the winding characteristics accurately,but it requires complex calculations.Lumped parameter model requires less calculations,but its applicable frequency range is not wide.This paper studies the amplitude-frequency characteristics of the lightning wave,compares the transformer modelling methods and finally proposes a modified lumped parameter model,based on the above comparison.The proposed model minimizes the errors provoked by the lumped parameter approximation,and the hyperbolic functions of the distributed parameter model.By this modification it becomes possible to accurately describe the winding characteristics and rapidly obtain the node voltage response.The proposed model can provide theoretical and experimental support to lightning protection of the distribution transformer.
基金Supported by National Natural Science Foundation of China(Grant No.51835009).
文摘Gear fault diagnosis technologies have received rapid development and been effectively implemented in many engineering applications.However,the various working conditions would degrade the diagnostic performance and make gear fault diagnosis(GFD)more and more challenging.In this paper,a novel model parameter transfer(NMPT)is proposed to boost the performance of GFD under varying working conditions.Based on the previous transfer strategy that controls empirical risk of source domain,this method further integrates the superiorities of multi-task learning with the idea of transfer learning(TL)to acquire transferable knowledge by minimizing the discrepancies of separating hyperplanes between one specific working condition(target domain)and another(source domain),and then transferring both commonality and specialty parameters over tasks to make use of source domain samples to assist target GFD task when sufficient labeled samples from target domain are unavailable.For NMPT implementation,insufficient target domain features and abundant source domain features with supervised information are fed into NMPT model to train a robust classifier for target GFD task.Related experiments prove that NMPT is expected to be a valuable technology to boost practical GFD performance under various working conditions.The proposed methods provides a transfer learning-based framework to handle the problem of insufficient training samples in target task caused by variable operation conditions.
基金This research was funded by the National Natural Science Foundation of China(Grant Nos.31870426).
文摘Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations often arise from inappropriate model parameterization.Here we compared five methods for defining community-level specific leaf area(SLA)and leaf C:N across nine contrasting forest sites along the North-South Transect of Eastern China,including biomass-weighted average for the entire plant community(AP_BW)and four simplified selective sampling(biomass-weighted average over five dominant tree species[5DT_BW],basal area weighted average over five dominant tree species[5DT_AW],biomass-weighted average over all tree species[AT_BW]and basal area weighted average over all tree species[AT_AW]).We found that the default values for SLA and leaf C:N embedded in the Biome-BGC v4.2 were higher than the five computational methods produced across the nine sites,with deviations ranging from 28.0 to 73.3%.In addition,there were only slight deviations(<10%)between the whole plant community sampling(AP_BW)predicted NPP and the four simplified selective sampling methods,and no significant difference between the predictions of AT_BW and AP_BW except the Shennongjia site.The findings in this study highlights the critical importance of computational strategies for community-level parameterization in ecosystem process modelling,and will support the choice of parameterization methods.
基金supported by the National Natural Science Foundation of China (No.U2133210).
文摘Aircraft wake turbulence is an inherent outcome of aircraft flight,presenting a substan-tial challenge to air traffic control,aviation safety and operational efficiency.Building upon data obtained from coherent Doppler Lidar detection,and combining Dynamic Bayesian Networks(DBN)with Genetic Algorithm-optimized Backpropagation Neural Networks(GA-BPNN),this paper proposes a model for the inversion of wake vortex parameters.During the wake vortex flow field simulation analysis,the wind and turbulent environment were initially superimposed onto the simulated wake velocity field.Subsequently,Lidar-detected echoes of the velocity field are simulated to obtain a data set similar to the actual situation for model training.In the case study validation,real measured data underwent preprocessing and were then input into the established model.This allowed us to construct the wake vortex characteristic parameter inversion model.The final results demonstrated that our model achieved parameter inversion with only minor errors.In a practical example,our model in this paper significantly reduced the mean square error of the inverted velocity field when compared to the traditional algorithm.This study holds significant promise for real-time monitoring of wake vortices at airports,and is proved a crucial step in developing wake vortex interval standards.
基金partially sponsored by the Natural Science Foundation of Shanghai(No.23ZR1429300)the Innovation Fund of CNNC(Lingchuang Fund)。
文摘The estimation of model parameters is an important subject in engineering.In this area of work,the prevailing approach is to estimate or calculate these as deterministic parameters.In this study,we consider the model parameters from the perspective of random variables and describe the general form of the parameter distribution inference problem.Under this framework,we propose an ensemble Bayesian method by introducing Bayesian inference and the Markov chain Monte Carlo(MCMC)method.Experiments on a finite cylindrical reactor and a 2D IAEA benchmark problem show that the proposed method converges quickly and can estimate parameters effectively,even for several correlated parameters simultaneously.Our experiments include cases of engineering software calls,demonstrating that the method can be applied to engineering,such as nuclear reactor engineering.
基金Supported by the National Natural Science Foundation of China （21006127）, the National Basic Research Program of China （2012CB720500） and the Science Foundation of China University of Petroleum, Beijing （KYJJ2012-05-28）.
文摘Chemical processes are usually nonlinear singular systems.In this study,a soft sensor using nonlinear singular state observer is established for unknown inputs and uncertain model parameters in chemical processes,which are augmented as state variables.Based on the observability of the singular system,this paper presents a simplified observability criterion under certain conditions for unknown inputs and uncertain model parameters.When the observability is satisfied,the unknown inputs and the uncertain model parameters are estimated online by the soft sensor using augmented nonlinear singular state observer.The riser reactor of fluid catalytic cracking unit is used as an example for analysis and simulation.With the catalyst circulation rate as the only unknown input without model error,one temperature sensor at the riser reactor outlet will ensure the correct estimation for the catalyst circulation rate.However,when uncertain model parameters also exist,additional temperature sensors must be used to ensure correct estimation for unknown inputs and uncertain model parameters of chemical processes.
基金National Hi-tech Research Development Program of China(863 Program,No.2001AA505000-11)
文摘To investigate the dynamic characteristics and damping theory of the passive hydraulic engine mount （PHEM）, numerical prediction is performed through lumped parameter model. System parameters, including volume compliance of the decoupler chamber, effective piston area, fluid inertia and resistance of inertia track and direct-decoupler, are identified by means of experiments and finite element method （FEM）. Dynamic behaviors are tested with elastomer test system for purpose of validating PHEM. With incorporation of inertia track and direct-decoupler, PHEM behaves effective and efficient vibration isolation in range of both low and high frequencies. The comparison of the numerical results with the experimental observations shows that the present PHEM achieves fairly good performance for the engine vibration isolation.
基金supported by the Technological Fund Item of China University of Mining and Technology (Grant No. OF4533)the Key Research Project of the Water Resources Department of Henan Province
文摘This paper describes a flood routing method applied in an ungauged basin, utilizing the Muskingum model with variable parameters of wave travel time K and weight coefficient of discharge x based on the physical characteristics of the river reach and flood, including the reach slope, length, width, and flood discharge. Three formulas for estimating parameters of wide rectangular, triangular, and parabolic cross sections are proposed. The influence of the flood on channel flow routing parameters is taken into account. The HEC-HMS hydrological model and the geospatial hydrologic analysis module HEC-GeoHMS were used to extract channel or watershed characteristics and to divide sub-basins. In addition, the initial and constant-rate method, user synthetic unit hydrograph method, and exponential recession method were used to estimate runoff volumes, the direct runoff hydrograph, and the baseflow hydrograph, respectively. The Muskingum model with variable parameters was then applied in the Louzigou Basin in Henan Province of China, and of the results, the percentages of flood events with a relative error of peak discharge less than 20% and runoff volume less than 10% are both 100%. They also show that the percentages of flood events with coefficients of determination greater than 0.8 are 83.33%, 91.67%, and 87.5%, respectively, for rectangular, triangular, and parabolic cross sections in 24 flood events. Therefore, this method is applicable to ungauged basins.
基金supported by the National Natural Science Foundation of China(50775028)the Ministry of Science and Technology of China for the 863 High-Tech Scheme(2007AA04Z418)
文摘In order to achieve prediction for vibration of rotating machinery, an accurate finite element （FE） model and an efficient parameter identification method of the rotor system are required. In this research, a test rig is used as a prototype of a rotor system to validate a novel parameter identification technique based on an FE model. Rotor shaft vibration at varying operating speeds is measured and correlated with the FE results. Firstly, the theories of the FE modelling and identification technique are introduced. Then disk unbalance parameter, stiffness and damping coefficients of the bearing supports on the test rig are identified. The calculated responses of the FE model with identified parameters are studied in comparison with the experimental results.
