常规线性回归方法用于建立选厂生产经验模型时的不足及其修正方法

由于受现有测量技术的限制，选厂生产经验模型中有影响十分显著的因素无法给予考虑，线性回归的剩余方差较大．常规线性回归方法，由于其优化目标存在缺陷，不适于剩余方差较大的场合，因而需要给予修正．     

全站仪在矿区三维监测中的应用研究

针对矿区变形监测的特点，应用计算机模拟分析和试验研究相结合的手段，分析研究了用全站仪进行矿区三维变形监测的特点，使用范围和测量精度。三维变形精度比二维的精度高，而且较均匀。     

Wavelet neural networks for modelling high pressure inactivation kinetics of Listeria monocytogenes in UHT whole milk

The aim of the present work was to investigate the applicability of a Wavelet Neural Network to describe the inactivation pattern of Listeria monocytogenes by high hydrostatic pressure in ultra high temperature (UHT) whole milk, and evaluate its performance against models used in predictive microbiology such as the re-parameterized Gompertz and modified Weibull equations. A comparative study with linear partial least squares regression (PLS-R) as well as neural network (NN) models demonstrated on the same dataset has been also considered. Milk was artificially inoculated with an initial population of the pathogen of ca. 10⁷ CFU/ml and exposed to a range of high pressures (350, 450, 550, 600 MPa) for up to 40 min at ambient temperature (ca. 25 °C). Typical survival curves were obtained including a shoulder, a log-linear and a tailing phase. Increasing the magnitude of the applied pressure resulted in increasing levels of inactivation. Modelling approaches provided good fit to experimental training data as inferred by the low values of the root mean squared error (RMSE) and the high values of regression coefficient (R²). Models were validated at 400 and 500 MPa with independent experimental data. First or second order polynomial models were employed to relate the inactivation parameters to pressure, whereas the wavelet network as well as the PLS and NN models were utilised as a one-step modelling approach. The prediction performance of the proposed learning-based network was better at both validation pressures. The development of accurate models to describe the survival curves of micro-organisms in high pressure treatment would be very important to the food industry for process optimisation, food safety and would eventually expand the applicability of this non-thermal process.     

Experimental analysis and finite element modelling of nano-scratch test applied on 40-120 nm SiCN thin films deposited on Cu/Si substrate

In this work, the nano-scratch test is used to characterize the interfacial adhesion of amorphous SiCN thin films deposited by plasma enhanced chemical vapour deposition on Cu/Si substrates. The experimental results show that the critical load F_c is directly related to the rupture of the SiCN/Cu interface. A strong linear dependence of F_c to the SiCN thickness independently to the adhesion is also put in evidence. A three-dimensional finite element model of the test is then built. The results show a clear relation between the stresses into the coating and the cracking and buckling of the film observed experimentally. We then discuss how the interfacial tensile stresses can explain the increase of F_c with the film thickness.     

麦克斯韦的尾模型方程的守恒律

研究麦克斯韦的尾模型方程的守恒律.运用直接方法以及解空间上的变分方法讨论方程的守恒律.给出了麦克斯韦尾模型方程形如(T1(x,t,u,ux,ut),T2(x,t,u,ux,ut))的守恒向量.利用2种方法得到了麦克斯韦的尾模型方程的3个守恒律.     

Characterising the release of flavour compounds from chewing gum through HS-SPME analysis and mathematical modelling

The headspace solid-phase microextraction (HS-SPME) technique combined with GC–MS was evaluated to study 33 selected flavour compounds released from chewing gum. The operating conditions of SPME were optimised, including different fibres (PDMS, DVB/CAR/PDMS, PA and PDMS/DVB), sample size, extraction time and temperature. The results indicated that while HS-SPME was a rapid and valuable technique, poor reproducibility occurred under all conditions. It was found that this deficiency could be alleviated by utilising mathematical modelling techniques, an approach which had not been previously used in the analysis of flavour compounds in chewing gum by HS-SPME. Compared to the instrumental analysis data themselves, the models provided more insights to the release behaviour of flavour compounds from chewing gum and the more reproducible kinetic rate constants might be used for comparing the release of different compounds or the same compound under different conditions.     

Experimental study on drying of pear slices in a convective dryer

The experiments were conducted on pear slices with thickness of 5 mm at temperatures of 50, 57, 64 and 71 °C with an air velocity of 2.0 m s^?1. Prior to drying, pear slices were pretreated with citric acid solution (0.5% w/w, 1 min, 20 °C) or blanched in hot water (1 min, 85 °C). Also, the untreated samples were dried as control. The shortest drying time of pear slices was obtained with pretreatment with citric acid solution. It was observed that whole drying process of pear slices took place in a falling rate period. Four mathematical models were tested to fit drying data of pear slices. According to the statistical criteria (R², χ² and RMSE), the Midilli et al. model was found to be the best model to describe the drying behaviour of pear slices. The effective diffusivity of moisture transfer during drying process varied between 8.56 × 10^?11 and 2.25 × 10^?10 m² s^?1, while the activation energy of moisture diffusion in pear slices was found to be 34.95–41.00 kJ mol^?1.     

Energy modelling of fabrics wrinkle recovery behaviour

Wrinkle recovery behaviour is an important property of fabrics for apparel applications. Fifty fabrics of a variety of constructions have been objectively evaluated in order to study the wrinkle recovery after a deformation. The wrinkle recovery behaviour was studied based on energy modelling. To study their wrinkle recovery properties, fabrics are modelled with the energy method. It is shown that the more the energy dissipation is low, the more fabric is able to recover to its initial state and then the more residual deformation is low. Thus, the energy dissipation can be used to estimate the ability of the fabric to recover to its initial state. In this paper, we also studied the effect of the fatigue test after the repeated wrinkling. Further, the increase of the fatigue cycle number after repeated wrinkling resulted in an increase of the residual deformation and permanent deformation. This method allows us for better approximation of the real behaviour of multidirectional wrinkling of clothing during wearing.     

Impact properties of thermoplastic composites

The excellent properties exhibited by thermoplastic composites at much reduced weight have attracted attention in the development of products in different sectors. Thermoplastic (TP) composites, because of their distinctive properties as well as ease of manufacturing, have emerged as a competitor against the conventional thermoset resin-based composites. Depending on the application, these composites may undergo impact events at various velocities and often fail in many complex modes. Hence, the development of TP composites having high energy-dissipation at (the desired) much-reduced weight has become a challenging task, but it is a problem which may be alleviated through the appropriate selection of materials and fabrication processes. Furthermore, fibre surface modification has been shown to increase fibre-matrix interfacial adhesion, which can lead to improved impact resistance. Textile preforms are helpful in acting as a structural backbone in the composites since they offer a relatively free hand to the composite designer to tailor its properties to suit a specific application. Additionally, hybrid textile composite structures may help in achieving the desired properties at much lower weight.

Simulation software can play a significant role in the evaluation of composites without damaging physical samples. Once the simulation result has been validated with actual experimental results, it should be possible to predict the test outcomes for different composites, with different characteristics, at different energy levels without conducting further physical tests. Various numerical models have been developed which have to be incorporated into these software tools for better prediction of the result.

In the current issue of Textile Progress, the effects of various materials and test parameters on impact behaviour are critically analyzed. The effect of incorporating high-performance fibres and natural fibres or their hybrid combination on the impact properties of TP composites are also discussed and the essential properties of TP polymers are briefly explained. The effects of fibre and matrix hybridization, environmental factors, various textile preform structures and fibre surface modification treatments on the impact properties of thermoplastic composites are examined in detail. Various numerical models used for impact analysis are discussed and the potential applications of TP composites in automobile, aerospace and medical sectors are highlighted.