超大型钢壳混凝土沉管安装多线形联合锁网贯通测量方法设计及应用

以深中通道沉管隧道为例,针对沉管隧道最终接头横向贯通精度极高的要求,充分利用施工现场地形条件和隧道内部空间结构,对隧道洞内外平面控制网进行优化设计和横向贯通误差模拟计算,在左、右行车道和中廊道分别布设一套导线网,并相互连接,形成隧道多线形联合锁网贯通测量方法,实现了沉管隧道最终接头的精准合龙贯通。

光缆在农村通信网中应用的思考

一、农村光通信网路组织目前,在农村通信网中,光缆一般应用于县局(C4)至农村端局(C5)以及端局至模块局之间的中继传输.常见的网路组织方案基本上可以分为线形网和星形网两种结构,如图1、图2所示:

Possible contribution of artificial neural networks and linear discriminant analysis in recognition of patients with suspected atrophic body gastritis

AIM: To investigate whether ANNs and LDA could recognize patients with ABG in a database, containing only clinical and biochemical variables, of a pool of patients with and without ABG, by selecting the most predictive variables and by reducing input data to the minimum.METHODS: Data was collected from 350 consecutive outpatients (263 with ABG, 87 with non-atrophic gastritis and/or celiac disease [controls]). Structured questionnaires with 22 items (anagraphic, anamnestic, clinical, and biochemical data) were filled out for each patient. All patients underwent gastroscopy with biopsies. ANNs and LDA were applied to recognize patients with ABG.Experiment 1: random selection on 37 variables, experiment 2: optimization process on 30 variables, experiment 3:input data reduction on 8 variables, experiment 4: use of only clinical input data on 5 variables, and experiment 5:use of only serological variables.RESULTS: In experiment 1, overall accuracies of ANNs and LDA were 96.6% and 94.6%, respectively, for predicting patients with ABG. In experiment 2, ANNs and LDA reached an overall accuracy of 98.8% and 96.8%,respectively. In experiment 3, overall accuracy of ANNs was 98.4%. In experiment 4, overall accuracies of ANNs and LDA were, respectively, 91.3% and 88.6%. In experiment 5, overall accuracies of ANNs and LDA were,respectively, 97.7% and 94.5%.CONCLUSION: This preliminary study suggests that advanced statistical methods, not only ANNs, but also LDA,may contribute to better address bioptic sampling during gastroscopy in a subset of patients in whom ABG may be suspected on the basis of aspecific gastrointestinal symptoms or non-digestive disorders.

Design for CNN Templates with Performance of Global Connectivity Detection

The cellular neural/nonlinear network (CNN) is a powerful tool for image and video signal processing,robotic and biological visions. This paper discusses a general method for designing template of the global connectivitydetection (GCD) CNN, which provides parameter inequalities for determining parameter intervals for implementing thecorresponding functions. The GCD CNN has stronger ability and faster rate for determining global connectivity in binarypatterns than the GCD CNN proposed by Zarandy. An example for detecting the connectivity in complex patterns isgiven.

Strategic games on a hierarchical network model

Among complex network models,the hierarchical network model is the one most close to such real networks as world trade web,metabolic network,WWW,actor network,and so on.It has not only the property of power-law degree distribution,but also the scaling clustering coefficient property which Barabási-Albert(BA)model does not have.BA model is a model of network growth based on growth and preferential attachment,showing the scale-free degree distribution property.In this paper,we study the evolution of cooperation on a hierarchical network model,adopting the prisoner's dilemma(PD)game and snowdrift game(SG)as metaphors of the interplay between connected nodes.BA model provides a unifying framework for the emergence of cooperation.But interestingly,we found that on hierarchical model,there is no sign of cooperation for PD game,while the fre-quency of cooperation decreases as the common benefit decreases for SG.By comparing the scaling clustering coefficient prop-erties of the hierarchical network model with that of BA model,we found that the former amplifies the effect of hubs.Considering different performances of PD game and SG on complex network,we also found that common benefit leads to cooperation in the evolution.Thus our study may shed light on the emergence of cooperation in both natural and social environments.

Numerical simulation of the effect of coupling support of bolt-mesh-anchor in deep tunnel

The mechanical effects of bolt-mesh-anchor coupling support in deep tunnels were studied by using a numerical method, based on deep tunnel coupling supporting techniques and non-linear deformation mechanical theory of rock mass at great depths.It is shown that the potential of a rigid bolt support can be efficiently activated through the coupling effect between a bolt-net support and the surrounding rock.It is found that the accumulated plastic energy in the surrounding rock can be sufficiently transformed by the coupling effect of a bolt-mesh-tray support.The strength of the surrounding rock mass can be mobilized to control the deforma-tion of the surrounding rock by a pre-stress and time-space effect of the anchor support.The high stress transformation effect can be realized by the mechanical coupling effect of the bolt-mesh-anchor support, whereby the force of the support and deformation of the surrounding rock tends to become uniform, leading to a sustained stability of the tunnel.

南汽试车跑道精密施工测量

介绍采用微型短边线形三角控制网、强制归心技术、独立前方交会成功的、高质量、高精度、高效益完成南汽试车跑道精密施工测量,希望能为类似工程测量提供一定的参考。(修改)

Exponential synchronization of general chaotic delayed neural networks via hybrid feedback

This paper investigates the exponential synchronization problem of some chaotic delayed neural networks based on the proposed general neural network model,which is the interconnection of a linear delayed dynamic system and a bounded static nonlinear operator,and covers several well-known neural networks,such as Hopfield neural networks,cellular neural networks(CNNs),bidirectional associative memory(BAM)networks,recurrent multilayer perceptrons(RMLPs).By virtue of Lyapunov-Krasovskii stability theory and linear matrix inequality(LMI)technique,some exponential synchronization criteria are derived.Using the drive-response concept,hybrid feedback controllers are designed to synchronize two identical chaotic neural networks based on those synchronization criteria.Finally,detailed comparisons with existing results are made and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.

Pore-scale simulation of gas-water flow in low permeability gas reservoirs

A novel method was developed to establish a realistic three dimensional(3D) network model representing pore space in low permeability sandstone.Digital core of rock sample was established by the combination of micro-CT scanning and image processing,then 3D pore-throat network model was extracted from the digital core through analyzing pore space topology,calculating pore-throat parameters and simplifying the shapes of pores and throats.The good agreements between predicted and measured porosity and absolute permeability verified the validity of this new network model.Gas-water flow mechanism was studied by using pore-scale simulations,and the influence of pore structure parameters,including coordination number,aspect ratio and shape factor,on gas-water flow,was investigated.The present simulation results show that with the increment of coordination number,gas flow ability in network improves and the effect of invading water on blocking gas flow weakens.The smaller the aspect ratio is,the stronger the anisotropy of the network is,resulting in the increase of seepage resistance.It is found that the shape factor mainly affects the end points in relative permeability curves,and for a highly irregular pore or throat with a small shape factor,the irreducible water saturation(Swi) and residual gas saturation(Sgr) are relatively high.

COLORED NOISE PREDICTION BASED ON NEURAL NETWORK

A method for predicting colored noise by introducing prediction of nonlinear time series is presented. By adopting three kinds of neural networks prediction models, the colored noise prediction is studied through changing the filter bandwidth for stochastic noise and the sampling rate for colored noise. The results show that colored noise can be predicted. The prediction error decreases with the increasing of the sampling rate or the narrowing of the filter bandwidth. If the parameters are selected properly, the prediction precision can meet the requirement of engineering implementation. The results offer a new reference way for increasing the ability for detecting weak signal in signal processing system.

3DT-PP:localization and path planning of mobile anchors over complex 3D terrains

Mobile anchors are widely used for localization in WSNs.However,special properties over 3D terrains limit the implementation of them.In this paper,a novel 3D localization algorithm is proposed,called 3 DT-PP,which utilizes path planning of mobile anchors over complex 3 D terrains,and simulations based upon the model of mountain surface network are conducted.The simulation results show that the algorithm decreases the position error by about 91%,8.7%and lowers calculation overhead by about 75%,1.3%,than the typical state-of-the-art localization algorithm(i.e.,'MDS-MAP','Landscape-3D').Thus,our algorithm is more potential in practical WSNs which are the characteristic of limited energy and 3D deployment.

Expected density of progress for wireless ad hoc networks with Nakagami-m fading

This paper presents the closed-form expression to the expected density of progress for wireless ad hoc networks with Nakagami-m fading. The expected density of progress is defined as the expectation of a product between the number of simultaneous successful transmission per unit area and the distance towards the destination. Numerical results show that the expected density of progress is determined by two factors, terminal density and the probability that a terminal attempts to transmit.

港珠澳大桥沉管隧道施工控制网布设研究

针对港珠澳大桥沉管隧道特殊的测量环境和超高的贯通精度要求,对其施工平面控制问题进行了研究。依据测量误差分配理论,研究了长距离沉管隧道贯通误差的合理分配方案;采用贯通误差严密估算方法,分析了沉管隧道内外控制网横向贯通误差影响规律。提出了一种适宜沉管隧道结构的双线形联合锁网布测方法,通过陆地上1∶1模拟试验和工程实际应用验证了双线形联合锁网的精度和可靠性。与全导线网相比,其平面控制精度提高15%～30%,平均多余观测分量提高约4%,能够满足外海超长沉管隧道的贯通精度要求,有效保障了工程的精准贯通。

Active structures integrated with wireless sensor and actuator networks： a bio-inspired control framework

One of the main problems in controlling the shape of active structures （AS） is to determine the actuations that drive the structure from the current state to the target state. Model-based methods such as stochastic search require a known type of load and relatively long computational time, which limits the practical use of AS in civil engineering. Moreover, additive errors may be produced because of the discrepancy between analytic models and real structures. To overcome these limitations, this paper presents a compound system called WAS, which combines AS with a wireless sensor and actuator network （WSAN）. A bio-inspired control framework imitating the activity of the nervous systems of animals is proposed for WAS. A typical example is tested for verification. In the example, a triangular tensegrity prism that aims to maintain its original height is integrated with a WSAN that consists of a central controller, three actuators, and three sensors. The result demonstrates the feasibility of the proposed concept and control framework in cases of unknown loads that include different types, distributions, magnitudes, and directions. The proposed control framework can also act as a supplementary means to improve the efficiency and accuracy of control frameworks based on a common stochastic search.

An engineering approach to improve the accuracy of one-step simulation for vehicle forming-to-crashworthiness integrated evaluation

To improve the accuracy of the vehicle crashworthiness simulation, it is necessary as well as important to integrate the valid forming effects of key parts. It has been agreed by many that one-step simulation results should be used only as a qualitative trend of the part but not as an engineering result for further structural analysis, especially for a relatively complex part. The study shows that it is inaccurate to analyze the forming effects with one-step simulation based on the geometry of the final part through comparison with the incremental simulation and verification with the actual part, whether in thickness or in plastic strain. However, incremental simulation is very time consuming and infeasible in the early stage of vehicle design due to lack- ing of forming tools and process parameters. An engineering approach is proposed to meet the requirement of accuracy as well as the time efficiency, where one-step simulation is conducted based on the geometry of the transformed part instead of the fi- nN part. The geometry of the transformed part is generated by simple die design engineering and proves to offer much more accuracy than the one-step simulation based on the final part geometry.

Numerical manifold method based on isogeometric analysis

In this study, numerical manifold method(NMM) coupled with non-uniform rational B-splines(NURBS) and T-splines in the context of isogeometric analysis is proposed to allow for the treatments of complex geometries and local refinement. Computational formula for a 9-node NMM based on quadratic B-splines is derived. In order to exactly represent some common free-form shapes such as circles, arcs, and ellipsoids, quadratic non-uniform rational B-splines(NURBS) are introduced into NMM. The coordinate transformation based on the basis function of NURBS is established to enable exact integration for the manifold elements containing those shapes. For the case of crack propagation problems where singular fields around crack tips exist, local refinement technique by the application of T-spline discretizations is incorporated into NMM, which facilitates a truly local refinement without extending the entire row of control points. A local refinement strategy for the 4-node mathematical cover mesh based on T-splines and Lagrange interpolation polynomial is proposed. Results from numerical examples show that the 9-node NMM based on NURBS has higher accuracies. The coordinate transformation based on the NURBS basis function improves the accuracy of NMM by exact integration. The local mesh refinement using T-splines reduces the number of degrees of freedom while maintaining calculation accuracy at the same time.

Design of chirped fiber gratings for optical beamforming networks

The properties of the linear chirped fiber grating （CFG） which is used in the true time delay unit of the optical beamforming networks （OBFNs） are studied intensively through theoretical analyses and numerical calculations. It is concluded that the dispersion of the CFG is equal to 1/（3Gc）, where G is the chirp coefficient of CFG and c is the light speed. Based on this relationship, a simplified designing process of a CFG which satisfies the requirements of the O13 FN is given. The simula- tion results are coincident with the theoretical conclusions.