Carbon nanotubes and glucose oxidase bionanocomposite bridged by ionic liquid-like unit: Preparation and electrochemical properties

For their biocompatibility and potential bionanoelectronic applications, integration of carbon nanotubes (CNTs) with biomolecules such as redox enzyme is highly anticipated. Therein, CNTs are expected to act not only as an electron transfer promoter, but also as immobilizing substrate for biomolecules. In this report, a novel method for immobilization of biomolecules on CNTs was proposed based on ionic interaction, which is of universality and widespread use in biological system. As illustrated, glucose oxidase (GOD) and single-walled carbon nanotubes (SWNTs) were integrated into a unitary bionanocomposite by means of ionic liquid-like unit on functionalized SWNTs. The resulted bionanocomposite illustrated better redox response of immobilized GOD in comparison of that prepared by weak physical absorption without ionic interaction. As a potential application of concept, the electrochemical detection of glucose was exemplified based on this novel bionanocomposite.

基于网络化虚拟仪器的机器人传感器实验平台

设计了基于网络化虚拟仪器的多节点机器人传感器实验平台系统,利用COM、软件插件等技术开发了虚拟控件和信号处理软件模块,用户可通过PPL创建自定义的信号处理模块,为进行面向智能机器人控制的传感器测试、标定、组网等奠定了基础。

基于整车配送的多仓库开路VRPTW问题的研究与实现

以整车销售物流为背景,探讨多仓库带时窗约束的车辆路线安排问题的解决方法.提出了更为复杂的基于现实的细节性要求的多配送中心开路VRPTW问题模型,并将遗传算法产生部分解和评估完整解的优化解决方法和涌现交叉算子MX1引入到带时窗的多仓库VRP问题优化中,实现了快速全局优化.提出的开路混合配送方法有利于提高车辆满载率,降低回程空载率.同时实现了运输资源的优化配置,提高车辆利用率.计算机仿真实验证明了算法的可行性.

基于精细结构描述及数值试验的断续节理岩体力学参数智能选取

Evaluating the mechanical properties of rock masses is the base of rock engineering design and construction. It has great influence on the safety and cost of rock project. The recognition is inevitable consequence of new engineering activities in rock, including high-rise building, super bridge, complex underground installations, hydraulic project and etc. During the constructions, lots of engineering accidents happened, which bring great damage to people. According to the investigation, many failures are due to choosing improper mechanical properties. ‘Can’t give the proper properties’ becomes one of big problems for theoretic analysis and numerical simulation. Selecting the properties reasonably and effectively is very significant for the planning, design and construction of rock engineering works. A multiple method based on site investigation, theoretic analysis, model test, numerical test and back analysis by artificial neural network is conducted to determine and optimize the mechanical properties for engineering design. The following outcomes are obtained: (1) Mapping of the rock mass structure Detailed geological investigation is the soul of the fine structure description. Based on statistical window，geological sketch and digital photography，a new method for rock mass fine structure in-situ mapping is developed. It has already been taken into practice and received good comments in Baihetan Hydropower Station. (2) Theoretic analysis of rock mass containing intermittent joints The shear strength mechanisms of joint and rock bridge are analyzed respectively. And the multiple modes of failure on different stress condition are summarized and supplied. Then, through introducing deformation compatibility equation in normal direction, the direct shear strength formulation and compression shear strength formulation for coplanar intermittent joints, as well as compression shear strength formulation for ladderlike intermittent joints are deducted respectively. In order to apply the deducted formulation conveniently in the real projects, a relationship between these formulations and Mohr-Coulomb hypothesis is built up. (3) Model test of rock mass containing intermittent joints Model tests are adopted to study the mechanical mechanism of joints to rock masses. The failure modes of rock mass containing intermittent joints are summarized from the model test. Six typical failure modes are found in the test, and brittle failures are the main failure mode. The evolvement processes of shear stress, shear displacement, normal stress and normal displacement are monitored by using rigid servo test machine. And the deformation and failure character during the loading process is analyzed. According to the model test, the failure modes quite depend on the joint distribution, connectivity and stress states. According to the contrastive analysis of complete stress strain curve, different failure developing stages are found in the intact rock, across jointed rock mass and intermittent jointed rock mass. There are four typical stages in the stress strain curve of intact rock, namely shear contraction stage, linear elastic stage, failure stage and residual strength stage. There are three typical stages in the across jointed rock mass, namely linear elastic stage, transition zone and sliding failure stage. Correspondingly, five typical stages are found in the intermittent jointed rock mass, namely linear elastic stage, sliding of joint, steady growth of post-crack, joint coalescence failure, and residual strength. According to strength analysis, the failure envelopes of intact rock and across jointed rock mass are the upper bound and lower bound separately. The strength of intermittent jointed rock mass can be evaluated by reducing the bandwidth of the failure envelope with geo-mechanics analysis. (4) Numerical test of rock mass Two sets of methods, i.e. the distinct element method (DEC) based on in-situ geology mapping and the realistic failure process analysis (RFPA) based on high-definition digital imaging, are developed and introduced. The operation process and analysis results are demonstrated detailedly from the research on parameters of rock mass based on numerical test in the Jinping First Stage Hydropower Station and Baihetan Hydropower Station. By comparison，the advantages and disadvantages are discussed. Then the applicable fields are figured out respectively. (5) Intelligent evaluation based on artificial neural network (ANN) The characters of both ANN and parameter evaluation of rock mass are discussed and summarized. According to the investigations, ANN has a bright application future in the field of parameter evaluation of rock mass. Intelligent evaluation of mechanical parameters in the Jinping First Stage Hydropower Station is taken as an example to demonstrate the analysis process. The problems in five aspects, i. e. sample selection, network design, initial value selection, learning rate and expected error, are discussed detailedly.

锦屏电站地下厂房卸荷岩体参数研究

It is a basic work to ascertain the parameters of rock mass for evaluation about stability of the engineering. Anisotropism、inhomogeneity and discontinuity characters of the rock mass arise from the existing of the structural plane. Subjected to water、weathering effect、off-loading, mechanical characters of the rock mass are greatly different from rock itself, Determining mechanical parameters of the rock mass becomes so difficult because of structure effect、dimension effect、rheological character, ‘Can’t give a proper parameter’ becomes one of big problems for theoretic analysis and numerical simulation. With the increment of project scale, appraising the project rock mass and ascertaining the parameters of rock mass becomes more and more important and strict. Consequently, researching the parameters of rock mass has important theoretical significance and actual meaning. The Jin-ping hydroelectric station is the first highest hyperbolic arch dam in the world under construction, the height of the dam is about 305m, it is the biggest hydroelectric station at lower reaches of Yalong river. The length of underground factory building is 204.52m, the total height of it is 68.83m, the maximum of span clearance is 28.90m. Large-scale excavation in the underground factory of Jin-ping hydroelectric station has brought many kinds of destructive phenomenon, such as relaxation、spilling, providing a precious chance for study of unloading parameter about rock mass. As we all know, Southwest is the most important hydroelectric power base in China, the construction of the hydroelectric station mostly concentrate at high mountain and gorge area, basically and importantly, we must be familiar with the physical and mechanical character of the rock mass to guarantee to exploit safely、efficiently、quickly, in other words, we must understand the strength and deformation character of the rock mass. Based on enough fieldwork of geological investigation, we study the parameter of unloading rock mass on condition that we obtain abundant information, which is not only important for the construction of Jin-ping hydroelectric station, but also for the construction of other big hydroelectric station similar with Jin-ping. This paper adopt geological analysis、test data analysis、experience analysis、theory research and Artificial Neural Networks （ANN） brainpower analysis to evaluate the mechanical parameter, the major production is as follows: (1)Through the excavation of upper 5-layer of the underground powerhouse and the statistical classification of the main joints fractures exposed, We believe that there are three sets of joints, the first group is lay fracture, the second group and the fourth group are steep fracture. These provide a strong foundation for the following calculation of and analysis; (2)According to the in-situ measurement about sound wave velocity、displacement and anchor stress, we analyses the effects of rock unloading effect，the results show a obvious time-related character and localization features of rock deformation. We determine the depth of excavation unloading of underground factory wall based on this. Determining the rock mass parameters according to the measurement about sound wave velocity with characters of low- disturbing、dynamic on the spot, the result can really reflect the original state, this chapter approximately the mechanical parameters about rock mass at each unloading area; (3)Based on Hoek-Brown experienced formula with geological strength index GSI and RMR method to evaluate the mechanical parameters of different degree weathering and unloading rock mass about underground factory, Both of evaluation result are more satisfied; (4)From the perspective of far-field stress, based on the stress field distribution ideas of two-crack at any load conditions proposed by Fazil Erdogan (1962)，using the strain energy density factor criterion (S criterion) proposed by Xue changming(1972)，we establish the corresponding relationship between far-field stress and crack tip stress field, derive the integrated intensity criterion formula under the conditions of pure tensile stress among two line coplanar intermittent jointed rock，and establish the corresponding intensity criterion for the exploratory attempt; (5)With artificial neural network, the paper focuses on the mechanical parameters of rock mass that we concerned about and the whole process of prediction of deformation parameters, discusses the prospect of applying in assessment about the parameters of rock mass，and rely on the catalog information of underground powerhouse of Jinping I Hydropower Station, identifying the rock mechanics parameters intellectually，discusses the sample selection, network design, values of basic parameters and error analysis comprehensively. There is a certain significance for us to set up a set of parameters evaluation system，which is in construction of large-scale hydropower among a group of marble mass.

The design algorithm of an associative memory neural network

A design algorithm of an associative memory neural network is proposed. The benefit of this design algorithm is to make the designed associative memory model can implement the hoped situation. On the one hand, the designed model has realized the nonlinear association of infinite value pattern from n dimension space to m dimension space. The result has improved the ones of some old associative memory neural network. On the other hand, the memory samples are in the centers of the fault-tolerant. In average significance the radius of the memory sample fault-tolerant field is maximum.