Lattice Boltzmann simulation of phase change and heat transfer characteristics in the multi-layer deposition

The metal droplets deposition method(MDDM)is a rapid prototyping technology,implemented via metallurgy bonding within droplets.The anisotropy of heat transfer and re-melting is caused by an asymmetric deposition process.A lattice Boltzmann method(LBM)model is established to predict the heat transfer and phase change in the multi-layer deposition.The prediction model is verified by the experimental temperature profiles in existing literature.The monitoring points are set to compare the temperature profiles,and decoupling analyze the heat transfer mechanism in different positions.The negative relationships between the re-molten volume of the temperature difference,as well as the influence of the dispositive position and the relative position of the adjacent component are observed and analyzed under the heat conduction.This work is helpful to choose the appropriate temperature conditions and the optimal dispositive method.     

Simulation of coupled flowing-reaction-deformation with mass transfer in heap leaching processes

Governing equations for a fully coupled flowing-reaction-deformation behavior with mass transfer in heap leaching are developed. The model equations are solved using an explicit finite difference method under the conditions of invariable application rate and constant hydraulic head. The distribution of the degree of the saturation, as well as the distributions of the concentration of the reagent and the solute is given. A cubic relationship between the mineral recovery and the leaching duration is obtained based on the numerical results. The relationship can be used to predict the recovery percentage of the valuable metal.     

Difference inversion model of wave equation

A numerical iterative model was derived from the difference method and a perturbation assumption to calculate the coefficient function of a wave equation. The method was used to solve the disaccord problem of numerical precision between the direct problem model and inverse problem model, and its serial problems using the old method. Numerical simulation calculation shows that the method is feasible and effective.     

Research on the iterative method for model updating based on the frequency response function

Model reduction technique is usually employed in model updating process.In this paper,a new model updating method named as cross-model cross-frequency response function(CMCF) method is proposed and a new iterative method associating the model updating method with the model reduction technique is investigated.The new model updating method utilizes the frequency response function to avoid the modal analysis process and it does not need to pair or scale the measured and the analytical frequency response function,which could greatly increase the number of the equations and the updating parameters.Based on the traditional iterative method,a correction term related to the errors resulting from the replacement of the reduction matrix of the experimental model with that of the finite element model is added in the new iterative method.Comparisons between the traditional iterative method and the proposed iterative method are shown by model updating examples of solar panels,and both of these two iterative methods combine the CMCF method and the succession-level approximate reduction technique.Results show the effectiveness of the CMCF method and the proposed iterative method.     

Comparative numerical study of single and two-phase models of nanofluid heat transfer in wavy channel

The main purpose of this study is to survey numerically comparison of two- phase and single phase of heat transfer and flow field of copper-water nanofluid in a wavy channel. The computational fluid dynamics （CFD） prediction is used for heat transfer and flow prediction of the single phase and three different two-phase models （mixture, volume of fluid （VOF）, and Eulerian）. The heat transfer coefficient, temperature, and velocity distributions are investigated. The results show that the differences between the temperature fie].d in the single phase and two-phase models are greater than those in the hydrodynamic tleld. Also, it is found that the heat transfer coefficient predicted by the single phase model is enhanced by increasing the volume fraction of nanoparticles for all Reynolds numbers; while for the two-phase models, when the Reynolds number is low, increasing the volume fraction of nanoparticles will enhance the heat transfer coefficient in the front and the middle of the wavy channel, but gradually decrease along the wavy channel.     

A PREDICTION TECHNIQUE FOR DYNAMIC ANALYSIS OF FLAT PLATES IN MID-FREQUENCY RANGE

The wave-based method (WBM) has been applied for the prediction of mid-frequency vibrations of flat plates.The scaling factors,Gauss point selection rule and truncation rule are introduced to insure the wave model to converge.Numerical results show that the prediction tech- nique based on WBM is with higher accuracy and smaller computational effort than the one on FEM,which implies that this new technique on WBM can be applied to higher-frequency range.     

一种基于训练数据的迭代改进核函数

To improve performance of a support vector regression, a new method for a modified kernel function is proposed. In this method, information of all samples is included in the kernel function with conformal mapping. Thus the kernel function is data-dependent. With a random initial parameter, the kernel function is modified repeatedly until a satisfactory result is achieved. Compared with the conventional model, the improved approach does not need to select parameters of the kernel function. Sim- ulation is carried out for the one-dimension continuous function and a case of strong earthquakes. The results show that the improved approach has better learning ability and forecasting precision than the traditional model. With the increase of the iteration number, the figure of merit decreases and converges. The speed of convergence depends on the parameters used in the algorithm.     

Experiment and evaluation of wrinkling strain in a corner tensioned square membrane

Prediction of wrinkling characteristics is strongly correlated with the strain perpendicular to wrinkling direc- tion. In this paper, the strain field of wrinkled membrane is tested by VIC-3D system based on the digital image correlation technique. Experimental results are validated by the tension wrinkling simulation. The experimental strain perpendicular to wrinkling direction is analyzed in depth. The wrinkling strain of a square wrinkled membrane under corner tension is extracted from experimental strain perpendicular to wrinkling direction. A quantitative characterization format of the experimental wrinkling strain is proposed. A modified prediction method of wrinkling amplitude is presented based on the experimental wrinkling strain. The re- sults show that the precision of modified prediction model has improved 13.2% compared with the classical prediction model. The results reveal that the modified model can give an accurate prediction of the wrinkling amplitude.     

Recent improvements of actuator line-large-eddy simulation method for wind turbine wakes

In a large wind farm,the wakes of upstream and downstream wind turbines can interfere with each other,affecting the overall power output of the wind farm.To further improve the numerical accuracy of the turbine wake dynamics under atmosphere turbulence,this work proposes some improvements to the actuator line-large-eddy simulation(AL-LES)method.Based on the dynamic k-equation large-eddy simulation(LES),this method uses a precursor method to generate atmospheric inflow turbulence,models the tower and nacelle wakes,and improves the body force projection method based on an anisotropic Gaussian distribution function.For these three improvements,three wind tunnel experiments are used to validate the numerical accuracy of this method.The results show that the numerical results calculated in the far-wake region can reflect the characteristics of typical onshore and offshore wind conditions compared with the experimental results.After modeling the tower and nacelle wakes,the wake velocity distribution is consistent with the experimental result.The radial migration velocity of the tip vortex calculated by the improved blade body force distribution model is 0.32 m/s,which is about 6%different from the experimental value and improves the prediction accuracy of the tip vortex radial movement.The method proposed in this paper is very helpful for wind turbine wake dynamic analysis and wind farm power prediction.     

Flexural-wave-generation using a phononic crystal with a piezoelectric defect

This paper proposes a method to amplify the performance of a flexural-wave-generation system by utilizing the energy-localization characteristics of a phononic crystal(PnC) with a piezoelectric defect and an analytical approach that accelerates the predictions of such wave-generation performance. The proposed analytical model is based on the Euler-Bernoulli beam theory. The proposed analytical approach, inspired by the transfer matrix and S-parameter methods, is used to perform band-structure an...     

加权函数组合预测边坡变形模型的研究

边坡变形监测是边坡监测的主要内容之一,其变形预测问题是边坡工程中主要技术难题之一。考虑边坡位移变形预测模型的局限性,如神经网络预测方法需要大量的实测数据作为学习样本,灰色系统模型要求原始数据序列必须满足指数规律,且数据序列变化速度不能太快等。建立了边坡变形反向传播神经网络预测模型,同时给出了灰色GM(1,1)边坡预测模型。提出边坡的神经网络与灰色系统加权函数组合预测模型,采用动态规划解法,将原模型转化为多阶段决策问题,使组合预测误差的平方和最小,得到组合权重,这样得到的变形预测结果的精度将大大提高,弥补了单一方法的局限性,满足工程预测的需要。通过边坡实例加以验证,加权函数组合预测模型的预测结果精度有一定提高,能够与实际监测数据相吻合,达到准确预测的目的。     

Dynamical randomicity and predictive analysis in cubic chaotic system

The dynamical randomicity and grey prediction in cubic chaotic system will be studied in this paper. These stochastic symbolic sequences bear three features. The distribution of frequency, inter-occurrence times, the first passage time, the rth passage time and the ordinal passage time are discussed separately. By using transfer probability of Markov chain (MC), one obtains analytic expressions of generating functions in three-probabilities stochastic wander model, which can be applied to all three symbolic systems. The visitation density function of cubic map will also be resolved. Especially, after introducing grey system theory, one is mainly using GM(1,1) model to forecast data sequences, and the usual forecast precision is approximately 90%. In the symbolic prediction of cubic chaotic dynamical system, the precision of grey prediction certainly will decrease as the length of symbolic sequence is increasing. But in this place we have found a generating rule that may realize chaotic synchronization at least in short and medium terms, and we can analyze and forecast in this way.     

中心逼近式灰色GM(1,1)模型在滑坡变形预测中的应用

黄龙西村滑坡位于甘肃天水,属黄土高势能滑坡,滑体体积3.9×10⁵m³,基底为花岗闪长岩。为了提高滑坡灰色GM(1,1)模型的预测精度,采用一种改变背景值的方法--中心逼近式灰色GM(1,1)模型。通过黄龙西村滑坡实例验证分析,结果表明中心逼近式灰色GM(1,1)模型的预测值与该滑坡实际监测值十分接近,且其残差平方和及平均误差百分比明显比传统灰色GM(1,1)模型的残差平方和及平均误差百分比小,具有较高的预测精度。同时,可通过调整模型中参数m的取值,使中心逼近式灰色GM(1,1)模型具有更高的预测精度。经计算,当m=6时,中心逼近式灰色GM(1,1)模型的预测精度比传统灰色GM(1,1)模型提高了5.34%。     

Two novel nonlinear multivariate grey models with kernel learning for small-sample time series prediction

For many applications, small-sample time series prediction based on grey forecasting models has become indispensable. Many algorithms have been developed recently to make them effective. Each of these methods has a specialized application depending on the properties of the time series that need to be inferred. In order to develop a generalized nonlinear multivariable grey model with higher compatibility and generalization performance, we realize the nonlinearization of traditional GM(1,N), and we call it NGM(1,N). The unidentified nonlinear function that maps the data into a better representational space is present in both the NGM(1,N) and its response function. The original optimization problem with linear equality constraints is established in terms of parameter estimation for the NGM(1,N), and two different approaches are taken to solve it. The former is the Lagrange multiplier method, which converts the optimization problem into a linear system to be solved; and the latter is the standard dualization method utilizing Lagrange multipliers, that uses a flexible estimation equation for the development coefficient. As the size of the training data increases, the estimation results of the potential development coefficient get richer and the final estimation results using the average value are more reliable. The kernel function expresses the dot product of two unidentified nonlinear functions during the solving process, greatly lowering the computational complexity of nonlinear functions. Three numerical examples show that the LDNGM(1,N) outperforms the other multivariate grey models compared in terms of generalization performance. The duality theory and framework with kernel learning are instructive for further research around multivariate grey models to follow.

     

Modeling of cementitious materials exposed to isothermal calcium leaching,considering process kinetics and advective water flow. Part 1: Theoretical model

Part 1 of the paper presents a new mathematical model of hydro-chemo-mechanical behavior of cementitious materials exposed to contact with the deionized water. For analyzing the calcium leaching process, an equation describing kinetics of the process is proposed instead of an equilibrium curve commonly used in previous models. This allows taking directly into account the characteristic time of calcium leaching which affects the time evolution of the process, especially that with a relatively fast decrease of the concentration of calcium in pore water. Constitutive relationships describing the transport and strength properties of concrete during chemical degradation are discussed. They are expressed in terms of the leaching degree, an internal variable of the model describing the material decalcification. The governing equations of the model and boundary conditions are expressed in terms of the state variables: gas pressure, capillary pressure, calcium concentration and displacement vector. Numerical solution of the model equations with the finite element method, as well as several examples of application of the model for analysis of various problems, are presented in the part 2 paper.     

Hybrid GR-SVM for prediction of surface roughness in abrasive water jet machining

This paper presents a hybridization model of support vector machine (SVM) and grey relational analysis (GRA) in predicting surface roughness value of abrasive water jet (AWJ) machining process. The influential factors of five process parameters in AWJ, namely traverse speed, water jet pressure, standoff distance, abrasive grit size and abrasive flow rate, need to be analyzed using GRA approach. Then, the irrelevance factors of process parameters are eliminated. There is a need of determining the influential factors of process parameters to the surface roughness as to develop a robust prediction model. GRA acts as feature selection method in preprocessing process of hybrid grey relational-support vector machine (GR-SVM) prediction model. Efficiency of the proposed model is demonstrated. GR-SVM presents more accurate result than conventional SVM as it removes the redundant features and irrelevant element from the experimental datasets.     

Migration of salts with the leaching of soils with piecewise-homogeneous salinization

The article discusses the one-dimensional problem of the leaching of a soil with piecewise-homogeneous initial salinization under conditions of a movable wetting front. Depending on the character of the salinization and the water-physical properties of the soil at the moving boundary, there are given either the values of the sought function or of its derivative with respect to the spatial variable. The solution of the problem is represented as the superposition of solutions of an auxiliary process modelling the process of the leaching of a soil with homogeneous salinization with the presence of an upper desalinated layer. A numerical example is given.Translated from Izvestiya Akademii Nauk SSSR, Mekhanika Zhidkosti i Gaza, No. 3, pp. 76–81, May–June, 1977.     

A note of hybrid GR-SVM for prediction of surface roughness in abrasive water jet machining

The paper attempts at reviewing a previous research entitled “Hybrid GR-SVM for prediction of surface roughness in abrasive water jet (AWJ) machining” and some problems were found in its reducing parameters process and prediction model. The authors presented a hybrid of grey relation analysis (GRA) and support vector machine (SVM) to estimate the roughness surface in a certain dataset of AWJ machining. Their proposed method may not work in real case of AWJ machining as it is claimed. This paper gives a counter model in order to illustrate these remarks.     

Modeling of cementitious materials exposed to isothermal calcium leaching,considering process kinetics and advective water flow. Part 2: Numerical solution

The second part of the paper presents numerical solutions of the mathematical model of hydro-chemo-mechanical behavior of cementitious materials exposed to contact with deionized water of part 1. The model defines kinetics of the calcium leaching process instead of a direct application of a curve describing equilibrium between solid calcium in the material skeleton and the calcium dissolved in the pore solution. It further takes into account the advective flux of calcium ions. Both aspects are new as compared to previous models. The weak form of the governing equations of the model is derived first using the Galerkin method. Then, the equations are discretized in space with finite elements and in time domain with finite differences, and finally the procedures used for numerical solution of their discretized form are presented. Three numerical examples are solved to test the numerical solution procedure proposed and demonstrate its robustness for solution of 1D and 2D problems concerning fast and slow leaching of cement-based materials. The effect of various factors on the results concerning chemical degradation of structures made of cementitious materials is analyzed as well.