基于滚动摩擦作用下玉米颗粒在模拟筒仓卸料中的力链分析（网络首发、推荐阅读）

针对颗粒滚动摩擦作用对筒仓中玉米颗粒的力链空间分布进行研究，通过EDEM离散元软件建立筒仓模型与仿真玉米颗粒模型进行卸粮仿真模拟，并与筒仓卸料实验作流态对比，验证模型与仿真结果的准确性。通过对模拟仓进行切片观察和数据处理，对比分析了不同摩擦情况下力链的细观参数随时间演化规律。模拟结果表明：颗粒间摩擦系数越大，卸粮完成的最终时间越长；颗粒间滚动摩擦系数越小，颗粒由整体流转变为管状流的时间越早。对于有漏斗的筒仓来说，减小颗粒间摩擦会改变整体流和管状流之间的极限，从而增加产生管状流的面积。标准滚动摩擦系数下玉米颗粒在卸料过程中会出现起拱-塌陷效应；减小滚动摩擦，玉米颗粒卸料较稳定，未出现起拱的应力突增、以及拱塌陷的应力衰减；增大颗粒间滚动摩擦不但会增加拱效应，且出现成拱高度距离漏斗口更高。     

立柱加固型框架大楼的爆破拆除

采用定向控制爆破技术拆除立柱加固型7层框架大楼。为了彻底炸毁加固立柱,确保大楼顺利定向倾倒,通过多次爆破试验确定了炸药单耗、布孔参数和装药结构。为了控制大楼塌落时的触地震动,采取了秒差分区爆破、空中解体、铺垫缓冲层和开挖减震沟等技术措施。爆破过程中进行了震动监测。此外还介绍了起爆顺序、安全防护措施及爆破结果。     

爆破工程费用计算方法探讨

爆破工程具有周期短、自成完整体系、技术管理严格的特点,但在费用管理上需进一步规范与整顿。本文阐述了工程费用的构成、调整及爆破工程费用的计算方法。     

Stochastic free vibration analyses of composite shallow doubly curved shells – A Kriging model approach

This paper presents the Kriging model approach for stochastic free vibration analysis of composite shallow doubly curved shells. The finite element formulation is carried out considering rotary inertia and transverse shear deformation based on Mindlin’s theory. The stochastic natural frequencies are expressed in terms of Kriging surrogate models. The influence of random variation of different input parameters on the output natural frequencies is addressed. The sampling size and computational cost is reduced by employing the present method compared to direct Monte Carlo simulation. The convergence studies and error analysis are carried out to ensure the accuracy of present approach. The stochastic mode shapes and frequency response function are also depicted for a typical laminate configuration. Statistical analysis is presented to illustrate the results using Kriging model and its performance.     

Comparison of xylo-oligosaccharides production by autohydrolysis of fibers separated from ground corn flour and DDGS

Xylo-oligosaccharides (XOS) are known to have beneficial health properties, and are considered to be functional food ingredients. The objective of this study is to compare corn fibers separated from ground corn flour and distillers dried grains with solubles (DDGS) for XOS yield and optimum autohydrolysis conditions. Based on the initial xylan content, the fiber separated from ground corn flour (FC) resulted in higher XOS yield (71.5%) than the fiber separated from DDGS (FD) (54.6%) at the maximum XOS production conditions. XOS produced were mainly xylobiose and xylotriose. Based on total initial material also, FC resulted in higher XOS yield (8.9%) than FD (8.0%), based on total original masses. Thus, fiber separated from ground corn flour would be a better feedstock for production of XOS than fiber separated from DDGS. The conditions for maximum XOS production from FD and FC were 180 °C with 20 min hold-time and 190 °C with 10 min hold-time, respectively.     

Application of higher order spectral features and support vector machines for bearing faults classification

Condition monitoring and fault diagnosis of rolling element bearings timely and accurately are very important to ensure the reliability of rotating machinery. This paper presents a novel pattern classification approach for bearings diagnostics, which combines the higher order spectra analysis features and support vector machine classifier. The use of non-linear features motivated by the higher order spectra has been reported to be a promising approach to analyze the non-linear and non-Gaussian characteristics of the mechanical vibration signals. The vibration bi-spectrum (third order spectrum) patterns are extracted as the feature vectors presenting different bearing faults. The extracted bi-spectrum features are subjected to principal component analysis for dimensionality reduction. These principal components were fed to support vector machine to distinguish four kinds of bearing faults covering different levels of severity for each fault type, which were measured in the experimental test bench running under different working conditions. In order to find the optimal parameters for the multi-class support vector machine model, a grid-search method in combination with 10-fold cross-validation has been used. Based on the correct classification of bearing patterns in the test set, in each fold the performance measures are computed. The average of these performance measures is computed to report the overall performance of the support vector machine classifier. In addition, in fault detection problems, the performance of a detection algorithm usually depends on the trade-off between robustness and sensitivity. The sensitivity and robustness of the proposed method are explored by running a series of experiments. A receiver operating characteristic (ROC) curve made the results more convincing. The results indicated that the proposed method can reliably identify different fault patterns of rolling element bearings based on vibration signals.     

Effect of complexation of oxidised corn starch with mineral elements on physicochemical properties

The objective of this study was to determine the effect of complexation of oxidised starch with mineral elements on its physicochemical properties. Corn starch was oxidised with sodium hypochlorite and, afterwards, modified with ions of potassium, magnesium and iron. Thus, native and modified starches were analysed for: contents of mineral elements, colour parameters (L*a*b*), water binding capacity and solubility in water at temperature of 60 and 80 °C. Thermodynamic characteristics of gelatinisation by DSC, molecular weight distribution by GPC, intrinsic viscosity and pasting properties by RVA were studied. The efficiency of incorporation of metal ions into oxidised corn starch was about 30%, 20% and 20% for potassium, magnesium and iron ions, respectively. The complexation with potassium ions caused the greatest changes in the molecular weight distribution and the intrinsic viscosity of starches and viscosity of starch pastes. Only modification of starch with iron ions affected the colour parameters of the starch. Incorporation of metal ions into starch resulted also in changes in its water binding capacity and solubility in water.     

Comparison of two Analytical Methods (ELISA and LC-MS/MS) for Determination of Aflatoxin B1 in Corn and Aflatoxin M1 in Milk

The aim of this paper is to assess the closeness of agreement between results of ELISA and LC-MS/MS methods for determination of aflatoxin B₁ in corn and aflatoxin M₁ in milk. Samples of corn (n=100) and milk (n=250) were simultaneously analyzed using ELISA and LC-MS/MS methods, after the severe drought that affected Serbia in summer 2012 resulting in occurrence of aflatoxin B1 in corn and aflatoxin M₁ in milk. Regression analysis showed higher level of agreement between aflatoxin B₁ samples (R²=0.994), compared to aflatoxin M₁ samples (R²=0.920). However, both techniques were satisfactory in meeting the requirements for official control purposes.