Prediction of the logarithmic of partition coefficients (log P) of some organic compounds by least square-support vector machine (LS-SVM)

A new method least square-support vector machine (LS-SVM) was used to develop quantitative structure–property relationship (QSPR) models for predicting the logarithmic of n-octanol/water partition coefficient (log P) of some derivatives phenolic compounds. The calibration and predictive ability of LS-SVM were investigated and compared with those of three other methods; multiple linear regression (MLR), support vector linear regression (SVR) and artificial neural network (ANN). The results showed that the log P values calculated by LS-SVM were in good agreement with experimental values, and the performances of the LS-SVM models were comparable or superior to those of MLR, SVR and ANN methods. The root-mean-square errors of the training set and the predicting set for the LS-SVM model were 0.0855, 0.0746 and the squares of the correlation coefficients were 0.9960 and 0.9728, respectively. These values and other statistical parameters obtained for the LS-SVM model show the reliability of this model. LS-SVM is a new and effective method for predicting log P of some organic compounds, and can be used as a powerful chemometrics tool for QSPR studies.     

Calculation of the detonation velocity of porous water-containing RDX-based charges

A nomographic method for predicting the detonation velocity of a porous explosive mixture prepared from RDX powder and water is proposed. It is shown that, in contrast to the existing calculation methods for predicting the detonation velocity, the use of the proposed nomogram greatly simplifies the procedure and requires knowledge of only two parameters: the mass fraction of RDX and the density of the mixture in the charge. At the same time, the nomogram is a coordinate system that enables to place and to compare on one field experimental data obtained at different parameters of the charge. It is shown that RDX powder-water hand-prepared charges can have a detonation velocity of 6–8 km/s. The detonation velocity of cylindrical water-containing charges 10–36 mm in diameter and 120–1000 mm in length with RDX mass fractions of 0.6–1.0 is measured.     

Numerical prediction of oblique detonation wave structures using detailed and reduced reaction mechanisms

Modelling of the structure and the limiting flow turning angles of an oblique detonation wave, established by a two-dimensional wedge, requires the implementation of detailed chemical kinetic models involving a large number of chemical species. In this paper, a method of reducing the computational effort involved in simulating such high-speed reacting flows by implementing a systematically reduced reaction mechanism is presented. For a hydrogen - air mixture, starting with an elementary mechanism having eight species in 12 reactions, three alternate four-step reduced reaction mechanisms are developed by introducing the steady-state approximation for the reaction intermediates HO2, O and OH, respectively. Additional reduction of the computational effort is achieved by introducing simplifications to the thermochemical data evaluations. The influence of the numerical grid used in predicting the induction process behind the shock is also investigated. Comparisons of the induction zone predicted by two-dimensional oblique detonation wave calculations with that of a static reactor model (with initial conditions of the gas mixture specified by those behind the nonreactive oblique shock wave) are also presented. The reasonably good agreement between the three four-step reduced mechanism predictions and the starting mechanism predictions indicates that further reduction to a two-step mechanism is feasible for the physical flow time scales (corresponding to inflow Mach numbers of 8 - 10) considered here, and needs to be pursued in the future.     

Predicting the contents of polysaccharides and its monosugars in Dendrobium huoshanense by partial least squares regression model using attenuated total reflectance Fourier transform infrared spectroscopy

An attenuated total reflectance Fourier transform infrared spectroscopy method combined with partial least square regression was established to rapidly quantify the total polysaccharide and its major monosugars in Dendrobium huoshanense. The results showed that the optimal predictive methods were the models established by the infrared spectroscopy files pretreated by standard normal transformation combined with the second derivative; the accuracy of the models selecting wavelength regions based on the assignments of Fourier transform infrared spectroscopy signals of polysaccharide was obviously higher than the models selecting wavelength regions suggested by Thermofisher Quantity Analyst software and other possible wavelength region selecting modes. The external validation and the complete external validation confirmed the robustness and reliability of the developed attenuated total reflectance Fourier transform infrared model. Our study might provide an efficient technique tool for the rapid, green, low-cost, and nondestructive quantification of the total polysaccharide and the main monosaccharides in Dendrobium huoshanense and other rich-in-polysaccharide plant food or medicines.     

The SURF model and the curvature effect for PBX 9502

SURF is a high explosive burn model based on the ignition & growth concept of hot-spot reaction. For the TATB based explosive PBX 9502, the model has been calibrated to shock-to-detonation transition experiments. To apply the SURF model for propagating detonation waves, the rate has to be extended to a higher pressure regime than is sampled by shock initiation experiments. The experimentally measured curvature effect – detonation speed as a function of front curvature or D _n(κ) – provides the appropriate data for calibrating the propagation regime. The calibration to the curvature effect is based on the ODEs for the reaction zone profile of a detonation wave in conjunction with a shooting algorithm to determine the rate model parameters, for a given κ, needed to obtain a specified detonation speed. A complication for calibrating PBX 9502 rate models arises from the kink in the experimentally measured D _n(κ) curve. This results from the fast and slow reactions that TATB exhibits. To account for this, we use an extension of the SURF model that utilises a sequence of two reactions. The first, with a fast rate, is due to molecular decomposition and is described by the original SURF formulation. The second, with a slow rate, is due to carbon clustering and is used to contribute additional energy from the formation of carbon bonds. The wave profile equations are generalised to the SURF-plus model. Model parameters are then determined for the propagation regime to fit the curvature effect data. The extended model is applicable to both the shock initiation regime and the propagating detonation wave regime.     

低温下JB-9014钝感炸药DSD参数研究

 爆轰冲击波动力学（Detonation Shock Dynamics,DSD）是目前研究爆轰波非理想传播的有效途径。利用DSD的广义几何光学模型,研究了大长径比药柱中爆轰波非理想传播现象,根据-30 ℃下直径为10～30 mm药柱的直径效应实验数据,利用遗传算法确定了低温下JB-9014钝感炸药的DSD参数。由DSD参数计算得到了JB-9014药柱中的定态波形和爆速,计算结果与实验结果符合。     

Using near-infrared reflectance spectroscopy to predict physical parameters of beef

The objective of this study was to develop near-infrared reflectance spectroscopy models for predicting the physical parameters of beef from commercial cuts. Four hundred and forty-two minced beef samples from various commercial cuts of two cattle breeds were used for the modeling process and randomly divided into two subsets: a calibration set and an independent prediction set (75 vs. 25%). Reflectance spectra (1000–1800?nm) were collected from both subsets of samples, and calibration models were built using partial least square regression on the calibration set of samples. Different mathematical pretreatments were tested and mean centering or multiplicative scatter correction combined with first-derivative preprocessing gave the best calibration models on all the beef physical traits. Based on the selected calibration equations, the coefficients of determination in calibration and prediction for Warner-Bratzler shear force, pH, color L*, and a* were higher than 0.60, which means models in the calibration were acceptable. However, the ratio performance deviation for all parameters was less than 2.0, indicating that the prediction abilities on independent validation set were not adequate for routine analysis. Further studies are required to establish more robust models for practical application of using near-infrared reflectance spectroscopy to predict physical traits of beef.     

Analyzing the performance of statistical models for estimating leaf nitrogen concentration of Phragmites australis based on leaf spectral reflectance

Abstract

Nitrogen is an essential nutrient for plant growth and development. Rapid and nondestructive monitoring of nitrogen nutrition in plants using hyperspectral remote sensing is important for accurate diagnosis and quality evaluation of plant growth status. The sensitive bands of leaf nitrogen concentration varied in different plants. However, most of the current studies are concentrated on crops, and only a few studies focused on wetland plants. This study investigated the accuracy of the most common univariate, stepwise multiple linear regression, and partial least squares regression models for predicting leaf nitrogen content in a wetland plant reed (Phragmites australis) by testing the accuracy of all the models through leave-one-out cross validation coefficient of determination, root mean square error and relative error. It found that: (i) sensitive bands responding to leaf nitrogen concentration were concentrated in the green and red regions of visible light; (ii) for univariate regression models, the quadratic polynomial model based on the difference spectral index composed of 665?nm and 680?nm had the highest predictive accuracy (the validation coefficient of determination was 0.7535); (iii) for multivariate regression models, the stepwise multiple linear regression models had superior predictive accuracy to the partial least squares regression models, and the stepwise multiple linear regression model with first derivative reflectance was optimal for predicting leaf nitrogen concentration (the validation coefficient of determination was 0.7746, the validation root mean square error was 0.2925, and the validation relative error was 0.0804). The findings provide a scientific basis for rapid estimation and monitoring of leaf nitrogen concentration in P. australis in a nondestructive manner.     

强爆轰参数的理论估算

用两相的排平物态方程对硝基甲烷的强爆轰参数进行了理论估算 ,理论值与拟稳态强爆轰的实验值(爆速、爆压和爆温 )符合得很好 .这既检验了这种理论估算方法 ,也再次检验了爆轰的ZND理论和两相的排平物态方程 ,也是对实验方法的一种支持 .常k形物态方程的强爆轰参数理论估算方法也得到了有条件的肯定     

常温下JB-9014钝感炸药的DSD参数研究

 爆轰冲击波动力学（DSD）是目前研究爆轰波非理想传播的有效途径。利用爆轰冲击波动力学的广义几何光学模型,研究了大长径比药柱中爆轰波非理想传播现象,根据常温下Ф10~30 mm药柱的直径效应实验数据,通过非线性优化方法——遗传算法,确定了一套JB-9014钝感炸药的DSD参数。这套DSD参数对JB-9014药柱中定态波形和爆速的计算与实验结果符合。     

Methods and computer codes for nuclear systems calculations

Some numerical methods for reactor cell, sub-critical systems and 3D models of nuclear reactors are presented. The methods are developed for steady states and space-time calculations. Computer code TRIFON solves space-energy problem in (X, Y) systems of finite height and calculates heterogeneous few-group matrix parameters of reactor cells. These parameters are used as input data in the computer code SHERHAN solving the 3D heterogeneous reactor equation for steady states and 3D space-time neutron processes simulation. Modification of TRIFON was developed for the simulation of space-time processes in sub-critical systems with external sources. An option of SHERHAN code for the system with external sources is under development.      

钝感炸药爆轰驱动研究

 对两种典型的钝感炸药（IHE）的爆轰驱动模型进行了实验研究。一种是点爆散心波驱动，另一种是滑移爆轰驱动。并在同一条件下做了非钝感炸药（HE）的爆轰驱动实验，以比较IHE和HE驱动规律的异同。对实验模型用二维数值模拟及拟合公式进行了计算，最后给出了在本实验条件下两种炸药驱动规律差异，也对计算偏差范围作了估计。     

Calibration of the Pseudo-Reaction-Zone model for detonation wave propagation

An approach for the calibration of an advanced programmed burn (PB) model for detonation performance calculations in high explosive systems is detailed. Programmed burn methods split the detonation performance calculation into two components: timing and energy release. For the timing, the PB model uses a Detonation Shock Dynamics (DSD) surface propagation model, where the normal surface speed is a function of local surface curvature. For the energy release calculation and subsequent hydrodynamic flow evolution, a Pseudo-Reaction-Zone (PRZ) model is used. The PRZ model is similar to a reactive burn model in that it converts reactants into products at a finite rate, but it has a reaction rate dependent on the normal surface speed derived from the DSD calculation. The PRZ reaction rate parameters must be calibrated in such a way that the rate of energy release due to reaction in multi-dimensional geometries is consistent with the timing calculation provided by the DSD model. Our strategy for achieving this is to run the PRZ model in a detonation shock-attached frame in a compliant 2D planar slab geometry in an equivalent way to a reactive burn model, from which we can generate detonation front shapes and detonation phase speed variations with slab thickness. In this case, the D _n field used by the PRZ model is then simply the normal detonation shock speed rather than the DSD surface normal speed. The PRZ rate parameters are then iterated on to match the equivalent surface front shapes and surface phase speed variations with slab thickness derived from the target DSD model. For the purposes of this paper, the target DSD model is fitted to the performance properties of an idealised condensed-phase reactive burn model, which allows us to compare the detonation structure of the calibrated PRZ model to that of the originating idealised-condensed phase model.     

An experimental investigation of the onset of detonation

An experimental configuration is devised in the present investigation whereby the condition at the final phase of the deflagration to detonation transition (DDT) process can be generated reproducibly by reflecting a CJ detonation from a perforated plate. The detonation products are transmitted downstream through the plate, generating a turbulent reaction front that mixes with the unburned mixture and that drives a precursor shock ahead of it at a strength of about M = 3. The gasdynamic condition that is generated downstream of the perforated plate closely corresponds to that just prior to the onset of detonation in the DDT process. The turbulence parameters can be controlled by varying the geometry of the perforated plate; thus, the condition leading to the onset of detonation can be experimentally investigated. A one-dimensional theoretical analysis of the steady wave processes was first performed, and the experimental results show good agreement, indicating that the present experimental condition can be theoretically described. Two different detonation tube geometries (one with a square cross-section of 300 mm by 300 mm and the other with a circular cross-section of 150 mm) are used to demonstrate the independence of the tube diameter at the critical condition for DDT. Perforated plates with different hole diameters (d = 8, 15, and 25 mm) were tested, and the hole spacing to hole diameter ratio was maintained at 0.5. Different hydrogen–air mixtures were tested at normal temperature and pressure. For the plate with 8 mm holes, the onset of detonation is never observed. For the plate with 15 mm holes, successful initiation of a detonation is achieved for 0.8 < < 1.75 in both detonation tubes. For the plate with 25 mm holes, detonation initiation is observed for 0.7 < < 2.1 in the square detonation tube and for 0.8 < < 1.6 in the smaller circular detonation tube.     

A comparison in a back-bead prediction of gas metal arc welding using multiple regression analysis and artificial neural network

This research was done on the basis of prediction that there is a relationship between welding parameters and geometry of the back-bead in arc welding which is a gap. Multiple regression analysis and artificial neural network were used as methods for predicting the geometry of the back-bead. The multiple regression analysis and the artificial neural network were formed, and the analysis data or verification data which were used in the formation process of the multiple regression, and the training data or test data which were used in the formation process of the artificial neural network, were used to perform the prediction of the back-bead. Through this research, it was found that the error rate predicted by the artificial neural network was smaller than that predicted by the multiple regression analysis, in terms of the width and depth of the back-bead. It was also found that between the two predictions, the prediction of the width of the back-bead was superior to the prediction of the depth in both methods.     

苯的硝基和叠氮基衍生物热力学性质的构效关系

苯的硝基和叠氮基衍生物是一类重要的含能材料,为了揭示其热力学性质与分子结构之间的关系,采用第一性原理进行了计算研究.通过计算平衡电负性连接指数,结合分子结构描述符,对苯的硝基和叠氮基衍生物的热力学性质建立了构效关系模型.模型检验结果表明,构建的模型具有良好的稳健性和预测能力,所得模型为苯的硝基和叠氮基衍生物的爆轰参数计算和分解机理研究提供了一种快速的热力学性质预测方法 .