包含液相扩散方程简化的锂离子电池电化学模型

锂离子电池的电化学模型对于电池特性分析和电池管理具有重要意义,但是准二维(P2D)模型复杂度太高,为了在保证模型精度的基础上尽量降低复杂度,本文提出了一种包含液相简化的P2D (LSP2D)模型,该模型首先基于电化学平均动力学将电池端电压化简成为仅耦合固相Li+浓度c_s和液相Li+浓度c_e的方程,然后进一步对表达c_s和c_e演化规律的偏微分方程进行抛物线近似化简,使得最终的模型由多项式组成.COMSOL仿真表明在放电倍率为1C时该模型与单粒子(SP)模型的估算精度和速度相当,但在放电倍率为3C时,该模型的估算时间比P2D模型减少了99.73%,与SP模型相当,估算精度相比SP模型有大幅度提升.     

A Model of Light from Ancient Blue Emissions

A model is presented to explain the luminar distances and associated red-shifts from ancient supernovae. Light frequencies of supernovae type Ia (SNe Ia) vary smoothly with time, decreasing from singularity to present and intergalactic luminar distances are described as linear combinations of Hubble expansion and smaller components from the time-dependent decrease of emission frequencies. When tested with current cosmic matter densities, SNe Ia distances, red-shifts and the Hubble constant the errors between this model and the vacuum energy model favor this new model, though our model suffers from mathematics about zero. An expression between energy and frequency, derived from the model, reducing to the Planck equation for short observation intervals is also discovered and estimated to within 10% using current SNe Ia data. We also propose a relationship for the deceleration of frequency over time, solve at infinity and discover frequency and time will eventually become uncoupled.     

发光二极管归一化光谱模型的修正

受自吸收等因素的影响,由发光二极管(LED)归一化光谱模型得到的光谱与实测LED光谱之间存在差异。为得到与实测LED光谱相吻合的归一化光谱模型,将由归一化光谱模型得到的理论光谱与实测光谱相减得到近似的自吸收谱。通过分析自吸收谱的峰值强度和半峰全宽与温度之间的关系以及其峰值能量与实测光谱峰值能量之间的定量关系,结合LED光谱的高斯模型和归一化光谱模型给出了自吸收谱的拟合表达式,并作为归一化光谱模型的修正项,对归一化光谱模型进行修正。在不同测试温度下的实验结果表明修正后的平均模型误差小于4%,证明由修正后的归一化光谱模型得到的光谱与实测光谱相吻合。     

Mixing search on complex networks

In this article, we derive the first passage time (FPT) distribution and the mean first passage time (MFPT) of random walks from multiple sources on networks. On the basis of analysis and simulation, we find that the MFPT drops substantially when particle number increases at the first stage, and converges to the shortest distance between the sources and the destination when particle number tends to infinite. Given the fact that a Brownian particle from a high-degree node often needs a large number of steps to reach an expected low-degree node, which is the bottleneck for a single random walk, we propose a mixing search model to improve the efficiency of search processes by using random walks from multiple sources to continue the searches from high-degree nodes to destinations. We compare our model with the mixing navigation model proposed by Zhou on complex networks and find that our model converges much faster with lower hardware cost than Zhou’s model. Moreover, simulations on scale-free networks show that the search efficiency of our model is much higher than that of a single random walk, and comparable to that of multiple random walks which have much higher hardware cost than our model. Finally, we discuss the traffic cost of our model, and propose an absorption strategy for our model to recover the additional walkers in networks. Simulations indicate that this strategy reduces the traffic cost of our model effectively.     

固定床传热参数中的等价关系

本文根据二维拟均相模型与二维非均相模型的等价条件建立了两种模型的传热参数之间的关系,所得结果适用于不存在床高效应的床层。根据本文的结果,只要用径向温度分布法测得床层的温度数据并反向拟合出二维拟均相模型中的传热参数,就可以在此基础上计算得到二维非均相模型中的传热参数,如此则为二维非均相模型的实际应用奠定了基础。     

基于正交信号回归法对中试在线近红外定量模型的模型传递研究

模型传递使在特定条件下建立的模型能够应用于新的样品状态、环境条件或仪器状态。本研究在中药金银花中试在线水提过程中,以水提液中的绿原酸含量为研究对象,建立绿原酸含量的近红外定量模型。针对由金银花来源不同带来的模型失效问题,从光谱背景校正的角度出发,提出以KS算法挑选待传递样本中的代表性样本,结合正交信号回归(OSR)光谱背景校正方法,对不同来源样本的近红外光谱进行光谱背景校正,并深入探讨OSR方法实现近红外定量模型在不同来源中试样本间传递的应用原理。经模型传递后,模型对新批次样本预测的RSEP由14.91%下降到7.11%,RPD由2.95上升到5.36,预测准确度明显提高。实验证明,选择代表性样本的KS算法结合OSR光谱背景校正的模型传递方法不仅能减小不同来源原料药之间的偶然误差,同时消除了中试制剂过程和算法本身的系统误差,因此能够有效地改善因样本来源差异而造成的模型失效现象。该研究充分阐释了OSR模型传递方法的应用原理,以光谱背景校正与挑选代表性样本回归的方法实现了近红外定量模型在不同来源原料药中试样本之间的模型传递,增强了模型应对原料药批次间变动的能力,提高了模型的稳健性,为多来源原料药中试在线制剂过程中有效成分含量的快速实时监测提供了有效方法。     

Disorder structure of free-flow and global jams in the extended BML model

The original BML model is extended by introducing extended sites, which can hold several vehicles at each time-step. Unexpectedly, the flow in the extended model sharply transits from free-flow to global jams, but the transition is not one-order in original BML model. And congestion in the extended model appears more easily. This can ascribe to the mixture of vehicles from different directions in one site, leading to the drop-off of the capacity of the site. Furthermore, the typical configuration of free flowing and global jams in the extended models is disorder, different from the regular structure in the original model.     

Novel model of a AlGaN/GaN high electron mobility transistor based on an artificial neural network

In this paper we present a novel approach to modeling AlGaN/GaN high electron mobility transistor(HEMT) with an artificial neural network(ANN).The AlGaN/GaN HEMT device structure and its fabrication process are described.The circuit-based Neuro-space mapping(neuro-SM) technique is studied in detail.The EEHEMT model is implemented according to the measurement results of the designed device,which serves as a coarse model.An ANN is proposed to model AlGaN/GaN HEMT based on the coarse model.Its optimization is performed.The simulation results from the model are compared with the measurement results.It is shown that the simulation results obtained from the ANN model of AlGaN/GaN HEMT are more accurate than those obtained from the EEHEMT model.     

Statefinder diagnosis for Ricci dark energy

Statefinder diagnostic is a useful method which can differ one dark energy model from each others. In this Letter, we apply this method to a holographic dark energy model from Ricci scalar curvature, called the Ricci dark energy model (RDE). We plot the evolutionary trajectories of this model in the statefinder parameter-planes, and it is found that the parameter of this model plays a significant role from the statefinder viewpoint. In a very special case, the statefinder diagnostic fails to discriminate LCDM and RDE models, thus we apply a new diagnostic called the Om diagnostic proposed recently to this model in this case in Appendix A and it works well.     

Adaptation in a revised inner-hair cell model

A revised computational model of the inner-hair cell (IHC) and auditory-nerve (AN) complex was recently presented [Sumner et al., J. Acoust. Soc. Am. 111, 2178-2188 (2002)]. One key improvement is that the model reproduces the rate-intensity functions of low- (LSR), medium- (MSR), and high-spontaneous rate (HSR) fibers in the guinea-pig. Here we describe the adaptation characteristics of the model, and how they vary with model fiber type. Adaptation of the revised model for a HSR fiber is in line with an earlier version of the model [Meddis and Hewitt, J. Acoust. Soc. Am. 90, 904-917 (1991)]. In guinea-pig, poststimulus time histograms (PSTH) have been found to show less adaptation in LSR fibers. Evidence from chinchilla suggests that this is due to chronic adaptation resulting from short interstimulus intervals, and that fully recovered LSR fibers actually show more adaptation. However, the model is able to account for both variations of PSTH shape when fully recovered from adaptation. Interstimulus interval can also affect recovery in the model. The model is further tested against data previously used to evaluate models of AN adaptation. The tests are (i) recovery from adaptation of spontaneous rate and (ii) the recovery of response to acoustic stimuli ("forward masking"), (iii) the response to stimulus increments and (iv) decrements, and (v) the conservation of transient components. A HSR model fiber performs similarly to the earlier version of the model. However, there is considerable variation in response to increments and decrements between different model fibers.     

A reduced model for nanoparticle coating in non-equilibrium plasma

In this Letter, a reduced model is developed based on the full model presented earlier [Yarin et al., J. Appl. Phys. 99 (6) (2006) 064310] for the deposition of amorphous hydrogenated carbon onto particles in a methane–hydrogen plasma. The reduced model is developed based on the assumption that, under certain conditions, chemistry may be decoupled from transport. The results from the reduced model are compared to the results from the full model for particle charge and growth rate of the deposited layer. It is shown that the two models are in good agreement for submicron particles that are of interest in nanoparticle coating in low-pressure plasma reactors. The reduced model is computationally far less expensive as compared to the full model and can be implemented for simulation of a large number of nanoparticles in plasma reactors.     

Density viscous continuum traffic flow model

A new traffic flow model called density viscous continuum model is developed to describe traffic more reasonably. The two delay time scales are taken into consideration, differing from the model proposed by Xue and Dai [Phys. Rev. E 68 (2003) 066123]. Moreover the relative density is added to the motion equation from which the viscous term can be derived, so we obtain the macroscopic continuum model from microscopic car following model successfully. The condition for stable traffic flow is derived. Nonlinear analysis shows that the density fluctuation in traffic flow induces density waves. Near the onset of instability, a small disturbance could lead to solitons determined by the Korteweg-de-Vries (KdV) equation, and the soliton solution is derived. The results show that local cluster effects can be obtained from the new model and are consistent with the diverse nonlinear dynamical phenomena observed in the freeway traffic.     

Modified model of gate leakage currents in AlGaN/GaN HEMTs

It has been reported that the gate leakage currents are described by the Frenkel-Poole emission(FPE) model,at temperatures higher than 250 K.However,the gate leakage currents of our passivated devices do not accord with the FPE model.Therefore,a modified FPE model is developed in which an additional leakage current,besides the gate(Ⅰ_Ⅱ),is added.Based on the samples with different passivations,the Ⅰ_Ⅱ caused by a large number of surface traps is separated from total gate currents,and is found to be linear with respect to(φ_B-V_g)~(0.5).Compared with these from the FPE model,the calculated results from the modified model agree well with the I_g-V_g measurements at temperatures ranging from 295 K to 475 K.     

地基消光测量确定大气气溶胶模型

 分别取大陆型、海洋型、城市型和Junge谱分布气溶胶模型，用6S辐射传输算法计算出对应于太阳光度计测量时的各波段大气气溶胶光学厚度。将模式计算值与测量值进行比较，确定测量地区的大气气溶胶模型。将该方法用于2004年在北京地区测量的太阳光度计数据，结果显示该地区当日实际大气在几种气溶胶模型中较为符合城市型气溶胶模型。     

金属和合金纳米固体的电阻特性

我们针对金属和合金纳米固体提出了简化的电阻模型，并据此得到了纳米固体总电阻与纳米粒子电阻的关系。依据这一模型，我们对纳米固体电阻特性的尺寸效应、温度效应和压力效应及其与常规多晶材料的差别等进行了有效的物理解释。     

Cosmology with a variable Chaplygin gas

We consider a new generalized Chaplygin gas model that includes the original Chaplygin gas model as a special case. In such a model the generalized Chaplygin gas evolves as from dust to quiescence or phantom. We show that the background evolution for the model is equivalent to that for a coupled dark energy model with dark matter. The constraints from the current type Ia supernova data favour a phantom-like Chaplygin gas model.     

The parameter conversion from the Kedem-Katchalsky model into the two-parameter model

Cryopreservation is an important process for preserving cells and tissues. The process itself can, however, cause damage to cells and tissues. During addition and removal of a cryoprotective agent (CPA), cells are subjected to imbalanced osmotic pressures between the intracellular and extracellular solutions. Cells can be injured if these shrinkage and swelling events are beyond their tolerable limits. The characteristics of the cell volume changes during these processes depend on the types of CPA, the methods of adding and removing of the CPA and the permeability of cells to CPA and water. The typical models of this transportation are the two-parameter (2-p) model and the Kedem-Katchalsky (K-K) model. The K-K model is more general than the 2-p model. However, there is evidence that in many cases water and CPAs do not permeate through common pathways, hence the use of the reflection coefficient in the K-K model may be unnecessary and in some cases it may create conceptual errors. Therefore, the 2-p model is more suitable for use as a transport model than the K-K model. The aim of this study is to use the values of the K-K model parameters from data in the literature to calculate the corresponding parameters for the 2-p model. The results from these simulations demonstrate that the cell volume changes during CPA addition and removal from the K-K model can be closely estimated by the 2-p model.     

A numerical model for ultrasonic measurements of swelling and mechanical properties of a swollen PVA hydrogel

This paper presents a numerical model for the evaluation of mechanical properties of a relatively thin hydrogel. The model utilizes a system identification method to evaluate the acoustical parameters from ultrasonic measurement data. The model involves the calculation of the forward model based on an ultrasonic wave propagation incorporating diffraction effect. Ultrasonic measurements of a hydrogel are also performed in a reflection mode. A Nonlinear Least Square (NLS) algorithm is employed to minimize difference between the results from the model and the experimental data. The acoustical parameters associated with the model are effectively modified to achieve the minimum error. As a result, the parameters of PVA hydrogels namely thickness, density, an ultrasonic attenuation coefficient and dispersion velocity are effectively determined. In order to validate the model, the conventional density measurements of hydrogels were also performed.     

Subgrid-scale scalar flux modelling based on optimal estimation theory and machine-learning procedures

New procedures are explored for the development of models in the context of large eddy simulation (LES) of a passive scalar. They rely on the combination of the optimal estimator theory with machine-learning algorithms. The concept of optimal estimator allows to identify the most accurate set of parameters to be used when deriving a model. The model itself can then be defined by training an artificial neural network (ANN) on a database derived from the filtering of direct numerical simulation (DNS) results. This procedure leads to a subgrid scale model displaying good structural performance, which allows to perform LESs very close to the filtered DNS results. However, this first procedure does not control the functional performance so that the model can fail when the flow configuration differs from the training database. Another procedure is then proposed, where the model functional form is imposed and the ANN used only to define the model coefficients. The training step is a bi-objective optimisation in order to control both structural and functional performances. The model derived from this second procedure proves to be more robust. It also provides stable LESs for a turbulent plane jet flow configuration very far from the training database but over-estimates the mixing process in that case.