一种改善了非线性和色散性的Boussinesq方程模型

推导了一种在不平底上的新的Boussinesq方程．在不增加方程的最高导数项的阶数的情况下提高了模型方程的非线性．为了提高模型的色散性,引入长波近似,通过调节待定系数来使模型的色散性达到Padé(2,2)．对模型方程进行了非线性、线性色散性和线性浅化性分析,分析表明此模型在非线性、色散性和浅化性上都有所提高．将计算结果与实验数据做了比较,结果显示模型更好的符合了实验数据．     

Construction of kinetic models for metabolic reaction networks: Lessons learned in analysing short-term stimulus response data

Construction of dynamic models of large-scale metabolic networks is one of the central issues in the engineering of living cells. However, construction of such models is often hampered by a number of challenges, for example, data availability, compartmentalization and parameter identification coupled with design of in vivo perturbations. As a solution to the latter, short-term perturbation experiments are proposed and are proven to be a useful experimental method to obtain insights into the in vivo kinetic properties of the metabolic pathways.

The aim of this work is to construct a kinetic model using the available experimental data obtained by short-term perturbation experiments, where the steady state of a glucose-limited anaerobic chemostat culture of Saccharomyces cerevisiae was perturbed. In constructing the model, we first determined the steady-state flux distribution using the data before the glucose pulse and the known stoichiometry. For the rate expressions, we used approximative linlog kinetics, which allows the enzyme–metabolite kinetic interactions to be represented by an elasticity matrix. We performed a priori model reduction based on timescale analysis and parameter identifiability analysis allowing the information content of the experimental data to be assessed. The final values of the elasticities are estimated by fitting the model to the available short-term kinetic response data.

The final model consists of 16 metabolites and 14 reactions. With 25 parameters, the model adequately describes the short-term response of the cells to the glucose perturbation, pointing to the fact that the assumed kinetic interactions in the model are sufficient to account for the observed response.     

A mathematical modelling to extract active ingredients from Oliveria decumbens by supercritical fluid extraction through using ultrasonic process

The experimental feasibility of extracting carvacrol or cymophenol from local and medicinal Oliveria decumbens by supercritical carbon dioxide through using ultrasound waves was investigated in this study. The extraction modelling was carried out in two forms: Internal and external. The internal model was adopted to simulate the concentration distribution of the phytochemicals in the plant particles. In this model, the extracted cell was assumed to be a filled substrate and two mechanisms of molecular permeability and mass transfer had the greatest effect. The comparison of the experimental data obtained from modelling revealed that both the internal and external models are compatible with the experimental data as much as 80%, indicating an acceptable accuracy. Furthermore, the empirical data is completely in line with the model at the final time (40 min), which is the time to reach the equilibrium.     

Revised particle growth model for supported metallocene catalyst co-polymerization

In this paper, a revised version of the particle growth model (PGM) describing olefin co-polymerization with metallocene catalysts is proposed. The model is used to calculate the reaction rate of hexane–propylene co-polymerization under different operating conditions. Results are compared with experimental data obtained by calorimetric technique in order to validate the model. Good agreement between calculated and experimental results is shown.     

A gradient based iterative algorithm for solving model updating problems of gyroscopic systems

Model updating should be correlated with experimental data to ensure that it models the dynamics of the real structure and the updated model predicts the dynamics of a structure more accurately. Considering that the iterative methods for model updating have aroused little public attention, this paper studies an iterative algorithm for quadratic model updating problems which can incorporate the measured modal data into the finite element model to produce an adjusted finite element model on the mass, gyroscopic and stiffness matrices that closely match the experimental modal data. By this method, the best approximation symmetric and skew-symmetric solutions can be obtained by choosing a convergence factor. Numerical example shows that the introduced iterative algorithm is quite efficient.     

A Simple Method for Identification of the Parameters of the Fractional Kelvin-Voight Model

A major difficulty connected with fractional rheological models is the estimation of the model parameters of experimental data. A new method for identification of the parameters of the fractional Kelvin-Voight model is presented. The procedure has been validated using artificial data and then used in estimating parameters from experimental data. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Feed forward neural networks modeling for K–P interactions

Artificial intelligence techniques involving neural networks became vital modeling tools where model dynamics are difficult to track with conventional techniques. The paper make use of the feed forward neural networks (FFNN) to model the charged multiplicity distribution of K–P interactions at high energies. The FFNN was trained using experimental data for the multiplicity distributions at different lab momenta. Results of the FFNN model were compared to that generated using the parton two fireball model and the experimental data. The proposed FFNN model results showed good fitting to the experimental data. The neural network model performance was also tested at non-trained space and was found to be in good agreement with the experimental data.     

The numerical simulation of the noncharring pyrolysis process and fire development within a compartment

A pyrolysis model for noncharring solid fuels is presented in this paper. Model predictions are compared with experimental data for the mass loss rates of polymethylmethacrylate (PMMA) and very good agreement is achieved. Using a three-dimensional CFD environment, the pyrolysis model is then coupled with a gas-phase combustion model and a thermal radiation model to simulate fire development within a small compartment. The numerical predictions produced by this coupled model are found to be in very good agreement with experimental data. Furthermore, numerical predictions of the relationship between the air entrained into the fire compartment and the ventilation factor produce a characteristic post-flashover linear correlation with constant of proportionality 0.38 kg/sm^5/2. The simulation results also suggest that the model is capable of predicting the onset of “flashover” and “post-flashover” type behaviour within the fire compartment.     

Modeling non-Darcian flow and solute transport in porous media with the Caputo–Fabrizio derivative

In this study, the non-Darcian flow and solute transport in porous media are modeled with a revised Caputo derivative called the Caputo–Fabrizio fractional derivative. The fractional Swartzendruber model is proposed for the non-Darcian flow in porous media. Furthermore, the normal diffusion equation is converted into a fractional diffusion equation in order to describe the diffusive transport in porous media. The proposed Caputo–Fabrizio fractional derivative models are addressed analytically by applying the Laplace transform method. Sensitivity analyses were performed for the proposed models according to the fractional derivative order. The fractional Swartzendruber model was validated based on experimental data for water flows in soil–rock mixtures. In addition , the fractional diffusion model was illustrated by fitting experimental data obtained for fluid flows and chloride transport in porous media. Both of the proposed fractional derivative models were highly consistent with the experimental results.     

Experimental,analytical, and numerical studies of composite sandwich panels under low-velocity impact loadings

The objective of this research is to compare the numerical and experimental results with a closed-form solution for the dynamic responses of composite sandwich panels subjected to a low-velocity impact. An equivalent twodegree-of-freedom system is used to predict the response at different boundary conditions. The experimental results were obtained from drop-weight impact tests. Numerical calculations were performed using the LSDYNA software to verify the analytical results. The numerical simulation showed a good agreement with experimental data. Meanwhile, with increasing impact velocity, the analytical model showed some disagreement with experiment. This can be explained by the static analysis and minimization of the potential energy used in the model.     

Deterministic parallel global parameter estimation for a model of the budding yeast cell cycle

Two parallel deterministic direct search algorithms are combined to find improved parameters for a system of differential equations designed to simulate the cell cycle of budding yeast. Comparing the model simulation results to experimental data is difficult because most of the experimental data is qualitative rather than quantitative. An algorithm to convert simulation results to mutant phenotypes is presented. Vectors of the 143 parameters defining the differential equation model are rated by a discontinuous objective function. Parallel results on a 2200 processor supercomputer are presented for a global optimization algorithm, DIRECT, a local optimization algorithm, MADS, and a hybrid of the two.     

From the discrete kinetic theory of vehicular traffic flow to computing the velocity distribution at equilibrium

This paper deals with the identification of the parameters of a model of vehicular traffic flow using experimental data obtained on the highway Padova–Venezia. Subsequently, simulations of the model are developed corresponding to steady uniform flow conditions. These simulations allow us to describe the velocity distribution in the above conditions corresponding to the parameters obtained by identification on the basis of experimental data.     

Sensitivity analysis of experimental data

This paper examines how a number of sensitivity techniques may be adapted to deal with the analysis of real experiments. We show that the fundamental quantities in this context are the partial derivatives of model input parameters with respect to experimental observables. They appear as a consequence of the procedure used to fit the model to the experiment. These so-called experimental elementary sensitivities are then combined with the usual model elementary sensitivities to yield coefficients which relate experimental and model observables. The importance of such coefficients for the planning of experiments is, in particular, discussed. Based on a linear analysis, we also derive simple expressions (containing the experimental elementary sensitivities) for the degree of parameter deviation arising from uncertainties in and discrepancies between model and measured observables. Finally, an overview of the role of sensitivity theory in analyzing experimental data is given.     

Modeling and analysis of the latent period of osteosarcomas induced by incorporated Pu: The role of immune responses

This paper considers the utility of a stochastic model of carcinogenesis, proposed earlier by Yakovlev and Polig, in quantitative analysis of the incidence of radiation-induced osteosarcomas in beagels injected with various amounts of ²³⁹Pu. The original version of the model failed to provide a good fit to our experimental data. The model has been generalized by incorporating a simple mechanism of lesion elimination, which is likely to be mediated by the immune system. Two versions of the model were developed: the first version ( Model 1 ) assumed malignant cells to be a target for the immune attack, while in Model 2 initiated cells were assumed to be such a target. Model 2 was rejected by the likelihood ratio test, thereby indicating that the competing model provides a more plausible explanation of the experimental data. Since in experiments with incorporated radionuclides the dose rate varies with time, dose-rate effects cannot be observed directly, and one must rely on mathematical models. The results of our numerical experiments show that, depending on the time of observation, both the direct and the inverse dose-rate effects may manifest themselves even at a fixed total dose level.     

Numerical study of the primary breakup of a plane liquid sheet with co-flowing air streams

The objective of this study is to model the primary breakup of a plane liquid sheet emerging from an air-blast nozzle. In the present work the interface compression scheme proposed by OpenCFD Ltd. [1] has been used to capture the interface between the liquid and gas. A One-equation subgrid scale (sgs) turbulent energy transport model attributed to Yoshizawa [2] is used for modeling the effects of turbulence. The set up case selected for this study is based on the experiments carried out by Mitra [3]. The 2D simulations performed in this study predict the breakup length of the plane liquid sheet in good agreement with the experimental data. Future work will involve, performing 3D simulations of the plane liquid sheet generated by the air-blast nozzle and performing comparisons of the resulting droplet characteristics with the experimental data. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Simulation of suspension gravity currents with different initial aspect ratio and layout of turbidity fence

A three-dimensional (3D) numerical model, using large eddy simulation (LES), is developed for simulating the motion of suspension gravity currents. The suitable values of model parameters are determined using the existing experimental data of a two-dimensional (2D) suspension (a mixture composed of water and glass bead particles) cloud. The simulated gravity current with different initial aspect ratio (length/breadth) of the suspension is compared with the reported data of 3D laboratory experiments to investigate the effect of initial aspect ratio on the flow characteristics and the diffusion of turbidity under the presence of a turbidity fence. The comparison of simulated results of such main flow characteristics as front height, front propagation velocity and particle deposition with the experimental data reveals that the model is capable of simulating the complex behavior of the 3D suspension gravity currents to a reasonably good accuracy under complex conditions.     

多重改良Logistic模型在磷酸电位滴定的离解平衡常数计算中的应用

基于磷酸电位滴定实验常用切线法、一阶微商法及二阶微商内插法等进行实验数据处理并计算磷酸离解平衡常数的烦琐与不准确性,提出一种与实验数据有高度吻合性的多重改良Logistic模型,应用优化求解得最佳函数表达式,解此函数一阶导数极大值点并计算得磷酸滴定半中和点,结合离解平衡常数校正公式最终得出了磷酸的离解平衡常数的各级pKa值,与文献结果相一致.另外,减少部分实验数据后应用模型处理并计算pKa值,所得结论仍具有一致性,从而提高了实验效率。     

Characterisation of filled rubber with a pronounced non-linear viscoelasticity

This contribution presents the characterisation of an incompressible carbon black-filled elastomer as one characteristical example for highly filled rubber. It shows a strongly pronounced non-linear viscoelastic behaviour and the most important characteristic is the extremely long relaxation time which has to be taken into account. The material model is developed with respect to uniaxial tension data. The basis in the development of a phenomenological model is given by the basic elasticity. For this evaluation the long term relaxation behaviour results in a complex experimental procedure. Therefore, special attention has to be paid according to an optimised experimental process in order to get the necessary reference data in an adequate and reproduceable way [1]. With this model basis further investigations are taken into account concerning the time-dependent viscoelasticity. Therefore, cyclic deformations from zero up to a maximum of deformation are considered for different strain rates. Furthermore, the relaxation behaviour is investigated for multiple strain levels. The phenomena which are observed in the experimental results yield in a purely viscoelastic model, based on a rheological analogous model consisting of an equilibrium spring and several Maxwell-elements which contain nonlinear relations for the relaxation times of the dashpot elements [1,2]. The material model's numerical realisation is accomplished in two ways. Because of its numerical simplicity especially according to the parameter identification the model is restricted only to the simple case of uniaxial tension. A second, alternative implementation is executed providing the benefit that more complex deformation conditions can also be taken into account. Therefore, the general, three-dimensional finite model is implemented in an open-source Finite Element library [3]. (© 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

动力系统实测数据的非线性混沌模型重构

动力系统实测非线性混沌数据的模型重构技术是相空间重构的重要内容。在判定了实测数据的非线性混沌特征,计算了实测数据的分维数,Lyapunov指数,并对其进行了本征值分解和噪声去除及确定其模型阶数以后,提出了一个动力系统实测数据的非线性混沌模型,给出了相应的模型参数辨识方法,并用其确立的混沌模型进行了预测工作,计算结果表明:模型参数辨识方法能迅速地将参数估计值带到多峰目标函数的全局最少值附近,然后再采用优化理论能较准确地求出模型的参数,用得到的混沌模型对系统进行预测工作其预测效果良好,且混沌时序不可能作长期预测。