Introduction to Mesh Based Generated Lumped Parameter Models for Electromagnetic Problems using Triangular Elements

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.

A modified lumped parameter model of distribution transformer winding

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.

Introduction to Mesh Based Generated Lumped Parameter Models for Electromagnetic Problems

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.

An improved lumped parameter model predicting attenuation of earmuff with air leakage

Since air leakage is inevitable when earmuffs are worn improperly or together with safety glasses in factory or military,it is required to be considered to accurately predict earmuff attenuation.Besides unwanted air leakage,under controlled air leakage is introduced to earmuff to achieve adjustable attenuations in different signal-to-noise ratios(SNRs)and balance between attenuation and speech intelligibility.This work is to develop an improved lumped parameter model(LPM)to predict earmuff attenuation with consideration of air leakage.Air leakage paths are introduced into conventional LPM without air leakage,and air leakage path impedance is analytically described by Maa’s microperforated tube impedance.Earmuff passive attenuation behavior can be analytically described and analyzed with the improved LPM.Finally,the validity of improved LPM is verified experimentally.The results indicate that the improved LPM can predict earmuff attenuation with air leakage,and air leakage deteriorates earmuff attenuation and turns resonance frequency higher.

Evaluation of hepatic fibrosis parameter model and elastic modulus of liver and spleen for the diagnosis of hepatic fibrosis in chronic hepatitis b

Objective Toinvestigate the diagnostic value of hepatic fibrosis parameter model and elastic modulus of liver and spleen in hepatic fibrosis of chronic hepatitis b.Methods 77 patients with hepatic fibrosis of chronic hepatitis in the infection clinic were recruited from July 2016 to December 2018.According to the classification of hepatic fibrosis,23 patients were classified as S1,20 as S2,18 as S3 and 16 as S4.The serum indexes of liver function in all patients were tested,FIB-4,APRI and GPR model indexes were calculated.SWE values of liver and spleen were evaluated,and the correlation between FIB-4,APRI,GPR and SWE was analyzed.Results The SWE values of liver and spleen in the study group were significantly higher than those in the normal group(P<0.01),and the differences in serum GGT,PLT,AST and portal vein velocity between the two groups were statistically significant(P<0.01).GGT and PLT were correlated with SWE values of liver and spleen,which were statistically significant(P<0.01).The model indexes of fib-4,APRI and GPR in the study group were all higher than those in the normal group,with statistically significant differences(P<0.01).Pearson correlation analysis showed that liver SWE value and spleen SWE value were positively correlated with fib-4,APRI and GPR,and the differences were significant(P<0.01),with a higher correlation with GPR.Conclusion GGT,PLT and GPR are positively correlated with SWE of liver and spleen,and combined detection can improve the early diagnosis accuracy of liver fibrosis.

Single Parameter Model for Cosmic Scale Photon Redshift in a Closed Universe

A successful single parameter model has been formulated to match the observations of photons from type 1a supernovae which were previously used to corroborate the standard 𝛬 cold dark matter model. The new single parameter model extrapolates all the way back to the cosmic background radiation (CMB) without requiring a separate model to describe inflation of the space dimensions after the Big Bang. This single parameter model assumes that spacetime forms a finite symmetrical manifold with positive curvature. For the spacetime manifold to be finite, the time dimension must also have positive curvature. This model was formulated to consider whether the curvature of the time dimension may be related to the curvature of the space dimensions. This possibility is not considered in the more complex models previously used to fit the available redshift data. The geometry for the finite spacetime manifold was selected to be compatible with the Friedmann equation with positive curvature. The manifold shape was motivated by an assumption that there exists a matter hemisphere (when considering time together with a single space dimension) and an antimatter hemisphere to give a symmetrical and spherical overall spacetime manifold. Hence, the space dimension expands from a pole to the equator, at a maximum value for the time dimension. This is analogous to the expansion of a circle of latitude on a globe from a pole to the equator. The three space dimensions are identical so that any arbitrary single space direction may be selected. The initial intention was to modify the assumed geometry for the spacetime manifold to account for the presence of matter. It was surprisingly found that, within the error of the reported measurements, no further modification was necessary to fit the data. The Friedmann equation reduces to the Schwarzschild equation at the equator so this can be used to predict the total amount of mass in the Universe. The resulting prediction is of the order of 1051 kg. The corresponding density of matter at the current time is approximately 1.6 × 10-28 kg·m-3.

Implication of community-level ecophysiological parameterization to modelling ecosystem productivity:a case study across nine contrasting forest sites in eastern China

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.

A 3D attention U-Net network and its application in geological model parameterization

To solve the problems of convolutional neural network–principal component analysis(CNN-PCA)in fine description and generalization of complex reservoir geological features,a 3D attention U-Net network was proposed not using a trained C3D video motion analysis model to extract the style of a 3D model,and applied to complement the details of geologic model lost in the dimension reduction of PCA method in this study.The 3D attention U-Net network was applied to a complex river channel sandstone reservoir to test its effects.The results show that compared with CNN-PCA method,the 3D attention U-Net network could better complement the details of geological model lost in the PCA dimension reduction,better reflect the fluid flow features in the original geologic model,and improve history matching results.

INVESTIGATION ON EFFECT OF DRUG DOSING REGIMENTS ON DRUG DELIVERY IN SOLID TUMOR VIA LUMPED PARAMETER MODELING AND ANIMAL EXPERIMENTS

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.

Lumped Parameter Mass Flow Rate and Pressure Control Characteristics Model for High-Speed Pneumatic PWM on/off Valve

Aiming at solving the problem of strong coupling characteristic of the key parameters of high-speed pneumatic pulse width modulation( PWM) on / off valve, a general lumped parameter mathematical model based on the valves time periods was well developed. With this model,the mass flow rate and dynamic pressure characteristics of constant volumes controlled by high-speed pneumatic PWM on /off valves was well described. A variable flow rate coefficient model was proposed to substitute for the constant one used in most of the prior works to investigate PWM on /off valves' dynamical pressure response, and a formula for disclosing the inherent relationship among the PWM command signal,static mass flow rate,and sonic conductance of the valve was newly derived.Finally,an extensive set of analytical experimental comparisons were implemented to verify the validity of the proposed mathematica model. With the proposed model, PWM on /off valves' characteristics,such as mass flow rate,step pressure response of the valve control system,mean pressure and ripple amplitude,not only in the linear range,but also in the nonlinear range can be wel predicted; Good agreement between measured and calculated results was obtained,which proved that the model is helpful for designing a control strategy in a closed loop control system.

Lumped parameter model based surgical planning for CABG

The current 3D CABG model is time consuming,a lumped parameter CABG model may solve this problem.A coronary lumped parameter model without stenosis and graft was constructed.The stenosis resistance was calculated and graft model was constructed.After calculation,the graft flow results of CABG lumped parameter model fit well with 3D CABG model results.

Optimal measurement locations for diagnosis of aortic abnormalities in a lumped-parameter model of the systemic circulation using sensitivity analysis

The basic theme of this work is to identify the optimal measurement locations for pres- sure and flow in the systemic circulation to detect aortic stenoses and aneurysms in early stages of a disease. For this purpose, a linear elastic lumped parameter model of the fluid dynamical simulator, major arterial cardiovascular simulator （MACSim）, is considered and global sensitivity analysis is applied to identify the better measurement locations for pressure and flow in the systemic circulation. The obtained results of sensitivity analysis provide insight that enable the experimentalists to optimize their experimental setups for detecting aortic stenoses and aneurysms using parameter estimation process. From the results, it is observed that the stenosis in the thoracic aorta can be identified from both pressure and flow at the location itself, nearby nodes, aorta ascendens, arcus aorta, arteria subclavia and arteria axillaris. On the other hand, the preferable measurement locations for abdominal aneurysms are locations themselves, nearby nodes and left/right leg of the body.

Is Model Parameter Error Related to a Significant Spring Predictability Barrier for El Nio events? Results from a Theoretical Model

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.

Extraction of temperature dependences of small-signal model parameters in SiGe HBT HICUM model

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.

Model Parameter Transfer for Gear Fault Diagnosis under Varying Working Conditions

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.

Parameter identifications for a rotor system based on its finite element model and with varying speeds

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.

Parameter sensitivity study of the biogeochemical model in the China coastal seas

In order to develop a coupled basin scale model of ocean circulation and biogeochemical cycling,we present a biogeochemical model including 12 components to study the ecosystem in the China coastal seas（CCS）.The formulation of phytoplankton mortality and zooplankton growth are modified according to biological characteristics of CCS.The four sensitivity biological parameters,zooplankton assimilation efficiency rate（ZooAE_N）,zooplankton basal metabolism rate（ZooBM）,maximum specific growth rate of zooplankton（μ_（20）） and maximum chlorophyll to carbon ratio（Chl2C_m） are obtained in sensitivity experiments for the phytoplankton,and experiments about the parameter μ_（20＇）,half-saturation for phytoplankton NO_3 uptake（K_（NO_3）） and remineralization rate of small detritusN（SDeRRN） are conducted.The results demonstrate that the biogeochemical model is quite sensitive to the zooplankton grazing parameter when it ranges from 0.1 to 1.2 d^（-1）.The K_（NO_3） and SDeRRN also play an important role in determining the nitrogen cycle within certain ranges.The sensitive interval of KNO_3 is from 0.1 to 1.5（mmol/m^3）^（-1）,and interval of SEdRRN is from 0.01 and 0.1 d^（-1）.The observational data from September 1998 to July 2000 obtained at SEATS station are used to validate the performance of biological model after parameters optimization.The results show that the modified model has a good capacity to reveal the biological process features,and the sensitivity analysis can save computational resources greatly during the model simulation.

Development and Validation of a Simple Frozen SoilParameterization Scheme Used for Climate Model

A simple frozen soil parameterization scheme is developed based on NCAR LSM and the effects of re-vised scheme are investigated using Former Soviet Union (FSU) 6 stations measurement data. In the revised model, soil ice content and the energy change in phase change process is considered; the original soil thermal conductivity scheme is replaced by Johanson scheme and the soil thermal and hydraulic properties is modi-fied depending on soil ice content. The comparison of original model with revised model results indicates that the frozen soil scheme can reasonably simulate the energy budget in soil column and the variation of thermal and hydraulic properties as the soil ice content changes. Soil moisture in spring is decreased because of the reduction of infiltration and increment of runoff. Consequently, the partition of heat flux and surface temperature changes correspondingly.

Parameterized thermal model of a mixed mantle convection

Simple parameterized models, either whole mantle convection or layered mantleconvection, cannot explain the tectonic characteristics of the Earth's evolution history, therefore a mixed mantle convection model has been carried out in this paper. We introduce a time-dependent parameter F, which denotes the ratio betWeen the mantle material involved in whole mantle convection and the material of the entire mantle, and introduce a local Rayleigh number Raloc as well as two critical numbers Ra1 and Ra2. These parameters are used to describe the stability of the phase boundary between the upper and lower mantle. The result shows that the mixed mantle convection model is able to simulate the episodic tectonic evolution of the Earth.

Introduction of parameterized sea ice drag coefficients into ice free-drift modeling

Many interesting characteristics of sea ice drift depend on the atmospheric drag coefficient （Ca） and oceanic drag coefficient （Cw）. Parameterizations of drag coefficients rather than constant values provide us a way to look insight into the dependence of these characteristics on sea ice conditions. In the present study, the parameterized ice drag coefficients are included into a free-drift sea ice dynamic model, and the wind factor a and the deflection angle θ between sea ice drift and wind velocity as well as the ratio of Ca to Cw are studied to investigate their dependence on the impact factors such as local drag coefficients, floe and ridge geometry. The results reveal that in an idealized steady ocean, Ca/Cw increases obviously with the increasing ice concentration for small ice floes in the marginal ice zone, while it remains at a steady level （0.2-0.25） for large floes in the central ice zone. The wind factor a increases rapidly at first and approaches a steady level of 0.018 when A is greater than 20%. And the deflection angle ~ drops rapidly from an initial value of approximate 80° and decreases slowly as A is greater than 20% without a steady level like a. The values of these parameters agree well with the previously reported observations in Arctic. The ridging intensity is an important parameter to determine the dominant contribution of the ratio of skin friction drag coefficient （Cs＇/Cs） and the ratio of ridge form drag coefficient （Cr＇/Cr） to the value of Ca/Cw, a, and 8, because of the dominance of ridge form drag for large ridging intensity and skin friction for small ridging intensity among the total drag forces. Parameterization of sea ice drag coefficients has the potential to be embedded into ice dynamic models to better account for the variability of sea ice in the transient Arctic Ocean.