超声波燃气表矩形流道的雷诺修正系数仿真研究

在超声波流量计测量技术中, 雷诺修正系数相关的研究对于提高计量精度有重要作用. 为研究矩形流道的雷诺修正系数与雷诺数的关系, 对矩形流道在常温常压流量较小情况下进行仿真, 结果发现: 矩形流道层流状态下的雷诺修正系数与雷诺数呈线性相关. 保持压强、体积流量不变, 在不同温度下进行仿真及拟合, 结果表明: 在不同温度下雷诺修正系数与雷诺数的线性关系依然满足. 在上述实验基础上, 对矩形流道湍流状态下的雷诺修正系数与雷诺数关系进行研究, 通过改变温度、压强和体积流量进行仿真及拟合发现, 矩形流道湍流状态下雷诺修正系数与雷诺数呈非线性相关.     

Comparison study of exchange-correlation functionals on prediction of ground states and structural properties

Despite significant advances in first-principles calculation methods, there is no single exchange-correlation functional which predicts the ground state of materials without an error yet. We investigated how accurately ground states of binary semiconductors are described using 16 exchange-correlation functionals (with or without van der Waals corrections). LDA, PBEsol, SCAN (with or without rVV10 correction), and PBE with D3 van der Waals correction (zero or Becke-Johnson damping) show good predicting power. The lattice constants of stable phases were slightly better described by SCAN, PBEsol, PBE+D3 (Becke-Johnson damping), and MS2. We also propose a set of functionals to double-check the stability of new materials based on the majority vote.     

Optimization of heterogeneous Catalyst-assisted fatty acid methyl esters biodiesel production from Soybean oil with different Machine learning methods

There is a growing attention to the bio and renewable energies due to fast depletion of fossil fuels as well as the global warming problem. Here, we developed a modeling and simulation method by means of artificial intelligence (AI) for prediction of the bioenergy production from vegetable bean oil. AI methods are well known for prediction of complex and nonlinear process. Three distinct Adaptive Boosted models including Huber regression, LASSO, and Support Vector Regression (SVR) as well as artificial neural network (ANN) were applied in this study to predict actual yield of Fatty acid methyl esters (FAME) production. All boosted utilizing the Adaptive boosting algorithm. The important influencing parameters on the biodiesel production such as the catalyst loading (CAO/Ag, wt%) and methanol to oil (Soybean oil) molar ratio were selected as the input variables of models while the yield of FAME production was selected as output. Model hyper-parameters were tuned to maintain generality while improving prediction accuracy. The models were evaluated using three distinct metrics Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R². Error rates of 8.16780E-01, 4.43895E-01, 2.06692E + 00, and 3.92713 E-01 were obtained with the MAE metric for boosted Huber, SVR, LASSO and ANN models. On the other hand, the RMSE error of these models were about 1.092E-02, 1.015E-02, 2.669E-02, and 1.01174E-02, respectively. Finally, the R-square score were calculated for boosted Huber, boosted SVR, and boosted LASSO as 0.976, 0.990, 0.872, and 0.99702, respectively. Therefore, it can be concluded that although the boosted SVR and ANN models were better models for prediction of process efficiency in terms of error, but all algorithms had high accuracy. The optimum yield of 83.77% and 81.60% for biodiesel production were observed at optimum operating values from boosted SVR and ANN models, respectively.     

On the complexity of extending the convergence ball of Wang’s method for finding a zero of a derivative

Ball convergence results are very important, since they demonstrate the complexity in choosing initial points for iterative methods. One of the most important problems in the study of iterative methods is to determine the convergence ball. This ball is small in general restricting the choice of initial points. We address this problem in the case of Wang’s method utilized to determine a zero of a derivative. Finding such a zero has many applications in computational fields, especially in function optimization. In particular, we find the convergence ball of Wang’s method using hypotheses up to the second derivative in contrast to earlier studies using hypotheses up to the fourth derivative. This way, we also extend the applicability of Wang’s method. Numerical experiments used to test the convergence criteria complete this study.     

电感耦合等离子体质谱(ICP-MS)法测定地质样品中Cu和Zn的干扰研究

电感耦合等离子体质谱法（ICP-MS）标准模式测定地质样品中Cu和Zn时,样品溶液中Ti在高温下易形成TiO+和 TiOH+离子产生重叠干扰,使测定值偏离真值而影响测定结果。采用氢氟酸-高氯酸-硝酸消解、王水复溶样品,通过多级在线校正46Ti16O+,消除TiO+和 TiOH+离子重叠干扰,研究了单质Ti与46Ti16O+、质荷比63、64、65、66离子间存在的关系,建立了一种电感耦合等离子体质谱(ICP-MS)法测定地质样品中Cu和Zn的分析方法。实验结果表明：单质Ti对Cu和Zn产生的干扰值与其质量浓度呈非简单的正相关性,TiO+产生的干扰离子质荷比65离子强度比63高,质荷比64离子强度比66 高; 46Ti16O+对质荷比63、66离子干扰增量值与单质Ti质量浓度变化无关;62Ni对46Ti16O+产生同量异位素重叠干扰,测定值须校正来自62Ni的贡献。ICP-MS测定地质样品中Cu和Zn时应选择测量同位素63Cu和66Zn,其检出限（n=7）分别为0.35 μg/g和0.63 μg/g。经有证标准物质验证,测定值与认定值吻合,准确度（RE）<8.6%,精密度（RSD,n=6）<5%。本方法适用于ICP-MS测定地质样品中Cu和Zn的质谱干扰消除,满足地质分析要求。     

Calibration transfer employing univariate correction and robust regression

This paper proposes a new method for calibration transfer, which was specifically designed to work with isolated variables, rather than the full spectrum or spectral windows. For this purpose, a univariate procedure is initially employed to correct the spectral measurements of the secondary instrument, given a set of transfer samples. A robust regression technique is then used to obtain a model with low sensitivity with respect to the univariate correction residuals. The proposed method is employed in two case studies involving near infrared spectrometric determination of specific mass, research octane number and naphthenes in gasoline, and moisture and oil in corn. In both cases, better calibration transfer results were obtained in comparison with piecewise direct standardization (PDS). The proposed method should be of a particular value for use with application-targeted instruments that monitor only a small set of spectral variables.     

Numerical approximation of a viscoelastic frictional contact problemApproximation numérique d'un problème viscoélastique de contact avec frottement

We consider a fully discrete scheme for a quasistatic frictional contact problem between a viscoelastic body and an obstacle. The contact is bilateral, the friction is modeled with Tresca's law and the behavior of the material is described with a viscoelastic constitutive law with long memory. We state an existence and uniqueness result for the discrete solution, followed by error estimate results. Then, we present numerical simulations in the study of a two-dimensional test example. To cite this article: Á. Rodríguez-Arós et al., C. R. Mecanique 334 (2006).     

Nouvelle approche pour la discrétisation de flux diffusifs en volumes finis à forte obliquité

We propose a new approach for the discretization of diffusive flux on a non orthogonal mesh based on the Deferred correction introduced by Peric. This new method is applied successfully to the solution of a Poisson problem in quadrangular domains meshed with very distorted control volumes. The interest of this approach lies in the fact that the precision of the used schemes is conserved despite meshes distortion level. The comparative study of the value of the spectral radius of iteration matrix enables us to explain why our Deferred correction approach is better than that of Peric, which diverges on highly skewed meshes. To cite this article: Y.M. Ahipo, Ph. Traore, C. R. Mecanique 334 (2006).     

完整系统的多刚体系统离散时间传递矩阵法研究

基于多刚体系统离散时间传递矩阵法，采用提高计算精度的方法，研究具有大运动、非线性特征的完整系统在平面、空间中的动力学响应。提出了对部分变量重新赋值的违约修正方法，计算机仿真表明了其有效性。多刚体系统离散时间传递矩阵法不须进行违约修正，体现了该方法建模灵活性较强、程式化程度较高的优点。