Extraction and imaging of indicator elements for non-destructive,in-situ,fast identification of adverse geology in tunnels

The lag in quantitative methods and detection techniques for geologic information has resulted in time-consuming and human-experienced geologic analysis in tunnels.Geochemical indicators of rocks can be used to identify adverse geology and to explain the intrinsic causes of damage to normal rocks.This study proposes a method to identify adverse geology by extracting and imaging the indicator elements.The mapping relationship between rock components and geologic bodies is quickly determined by indicator element extraction based on factor analysis,and then the data are gridded for image output.The location and size of the target adverse geology are visually identified through the distribution images of the indicator elements,thus reducing data dimensions and analysis time.A non-destructive,in-situ and fast element detection technique in tunnels was adopted to speed up the process of geology identification.The accuracy of the detection was validated by comparing field and laboratory test results.This study further confirms and refines the previous research,and the results provide references for geological,mining and underground projects.

Automatic identification of rock discontinuity and stability analysis of tunnel rock blocks using terrestrial laser scanning

Local geometric information and discontinuity features are key aspects of the analysis of the evolution and failure mechanisms of unstable rock blocks in rock tunnels.This study demonstrates the integration of terrestrial laser scanning(TLS)with distinct element method for rock mass characterization and stability analysis in tunnels.TLS records detailed geometric information of the surrounding rock mass by scanning and collecting the positions of millions of rock surface points without contact.By conducting a fuzzy K-means method,a discontinuity automatic identification algorithm was developed,and a method for obtaining the geometric parameters of discontinuities was proposed.This method permits the user to visually identify each discontinuity and acquire its spatial distribution features(e.g.occurrences,spac-ings,trace lengths)in great detail.Compared with hand mapping in conventional geotechnical surveys,the geometric information of discontinuities obtained by this approach is more accurate and the iden-tification is more efficient.Then,a discrete fracture network with the same statistical characteristics as the actual discontinuities was generated with the distinct element method,and a representative nu-merical model of the jointed surrounding rock mass was established.By means of numerical simulation,potential unstable rock blocks were assessed,and failure mechanisms were analyzed.This method was applied to detection and assessment of unstable rock blocks in the spillway and sand flushing tunnel of the Hongshiyan hydropower project after a collapse.The results show that the noncontact detection of blocks was more labor-saving with lower safety risks compared with manual surveys,and the stability assessment was more reliable since the numerical model built by this method was more consistent with the distribution characteristics of actual joints.This study can provide a reference for geological survey and unstable rock block hazard mitigation in tunnels subjected to complex geology and active rockfalls.

Parameter identifications for a rotor system based on its finite element model and with varying speeds

In order to achieve prediction for vibration of rotating machinery, an accurate finite element （FE） model and an efficient parameter identification method of the rotor system are required. In this research, a test rig is used as a prototype of a rotor system to validate a novel parameter identification technique based on an FE model. Rotor shaft vibration at varying operating speeds is measured and correlated with the FE results. Firstly, the theories of the FE modelling and identification technique are introduced. Then disk unbalance parameter, stiffness and damping coefficients of the bearing supports on the test rig are identified. The calculated responses of the FE model with identified parameters are studied in comparison with the experimental results.

Vehicle-Bridge Interaction Simulation and Damage Identification of a Bridge Using Responses Measured in a Passing Vehicle by Empirical Mode Decomposition Method

To prevent early bridge failures, effective Structural Health Monitoring (SHM) is vital. Vibration-based damage assessment is a powerful tool in this regard, as it relies on changes in a structure’s dynamic characteristics as it degrades. By measuring the vibration response of a bridge due to passing vehicles, this approach can identify potential structural damage. This dissertation introduces a novel technique grounded in Vehicle-Bridge Interaction (VBI) to evaluate bridge health. It aims to detect damage by analyzing the response of passing vehicles, taking into account VBI. The theoretical foundation of this method begins with representing the bridge’s superstructure using a Finite Element Model and employing a half-car dynamic model to simulate the vehicle with suspension. Two sets of motion equations, one for the bridge and one for the vehicle are generated using the Finite Element Method, mode superposition, and D’Alembert’s principle. The combined dynamics are solved using the Newmark-beta method, accounting for road surface roughness. A new approach for damage identification based on the response of passing vehicles is proposed. The response is theoretically composed of vehicle frequency, bridge natural frequency, and a pseudo-frequency component related to vehicle speed. The Empirical Mode Decomposition (EMD) method is applied to decompose the signal into its constituent parts, and damage detection relies on the Intrinsic Mode Functions (IMFs) corresponding to the vehicle speed component. This technique effectively identifies various damage scenarios considered in the study.

Changes in Sediment Sources in the Southern Muddy Area of Weihai,China,Since the Late Pleistocene:A Record from Rare Earth Elements

The small muddy areas developed in the southern Shandong Peninsula have attracted increasing attention from researchers because of complex changes in sediment sources driven by sea-level fluctuations and land-sea interactions since the late Pleistocene.This study investigates the evolution of sediment sources and their responses to environmental changes since the late Pleistocene,using core WHZK01 collected from the nearshore muddy area in southern Weihai for rare earth element(REE)analysis.In doing so,this work highlights the changing patterns of material sources and the primary control factors.The results reveal that the sedimentary deposits in core WHZK01 exhibit distinct terrestrial characteristics.Discriminant function analysis(F_(D))and source discrimination dia-grams both suggest that the primary sources of these deposits are the Yellow River and adjacent small and medium-sized rivers,although the sources vary among different sedimentary units.Furthermore,the DU3 layer(17.82-25.10 m)displays typical riverine sedimentation,dominated by terrestrial detrital input,primarily from the local rivers,namely the Huanglei and Muzhu Rivers.The material in the DU2 layer(14.91-17.82 m)is mainly influenced by a mixture of the Qinglong and Yellow Rivers.The DU1 layer(0-14.91 m)is influenced by sea-level changes during the Holocene,with the Yellow River being the primary source,although there is also some input from local rivers.The changes in sea level during the Holocene and the input of Yellow River material carried by the coastal currents of the Yellow Sea are identified as the main controlling factors for the changes in material sources in the study area since the late Pleistocene,with small and mediumsized rivers also exerting some influence on the material sources.The above mentioned findings not only contribute to a better understanding of the source-sink systems of the Yellow River and adjacent small and mediumsized rivers but also deepen our understanding of the late Quaternary land-sea interactions in the Shandong Peninsula.

Trace elements spatial distribution characteristics,risk assessment and potential source identification in surface water from Honghu Lake,China

Five trace elements including Zn, Cu, Cd, Cr and As were investigated in surface water from ten typical sampling sites in Honghu Lake. The consequence indicated that all of the detected trace element levels were within the allowed standard of China’s safe water guideline. The hazard quotients （HQ） and the hazard index （HI） value levels of all the five heavy metals in all sampling sites did not exceed the acceptable risk limits of non-carcinogenic value through the selected assessment method. Pearson’s correlation analysis and principal component analysis （PCA） indicated that Zn and Cu mainly originated from the natural alluviation and non-point agricultural sources, whereas Cr and As were mainly derived from industrial effluents. Moreover, Cd mainly originated from both non-point agricultural and industrial pollution sources. In addition, cluster analysis （CA） implied that cluster 1 （including S3, S5, S6 and S10） was considered the set of high pollution sites and cluster 2 （including S4 and S9） was identified as the set of moderate pollution sites.

MATERIAL SURFACE THERMAL PROPERTY IDENTIFICATION USING HEAT FLUX TACTILE SENSOR

Eased on the mechanism of temperature tactile sensing of human finger,a heat flux tactile sensor com- posed of a thermostat module and a heat flux sensor is designed to identify material thermal properties. The ther- mostat module maintains the sensor temperature invariable, and the heat flux sensor（Peltier device） detects the heat flux temperature difference between the thermostat module and the object surface. Two different modes of the heat flux tactile sensor are proposed, and they are simulated and experimented for different material objects. The results indicate that the heat flux tactile sensor can effectively identify different thermal properties.

Intelligent identification of underground powerhouse of pumped-storage power plant

The damping coefficient and dynamical load characteristics are sensitive to the dynamic response of the underground powerhouse. In this paper, based on results of dynamic identification of the underground powerhouse of a pumped-storage power plant previously made, the immune algorithm is used together with the ANSYS Code and the high-frequency water pressure pulsation during a routine operation and the damping ratio are identified and studied with observed data. This will be useful for generating a precise numerical model and studying the hydropower station.

Log identification method in complex sand reservoirs

In order to obtain effective parameters for complex sand reservoirs,a log evaluation method for relevant reservoir parameters is established based on an analysis in the gas-bearing sandstone with high porosity and low permeability,low porosity and permeability and on various characteristics of log responses to reservoir lithologies and physical properties in the Neopleozoic sand reservoir of the Ordos basin.This log evaluation method covers the Cook method that is used to evaluate the porosity and oiliness in high porosity and low permeability reservoirs and another method in which the mineral content,derived from geochemical logs,is used to identify formation lithologies.Some areas have high calcium and low silt content,not uniformly distributed,the results of which show up in the complex formation lithologies and conventional log responses with great deviation.The reliability of the method is verified by comparison with conventional log data and core analyses.The calculation results coincide with the core analytical data and gas tests,which indicate that this log evaluation method is available,provides novel ideas for study of similar complex reservoir lithologies and has some reference value.

Predicting the martensite transformation start-temperature of low alloy steel based on fuzzy identification

A method of fuzzy identification based on T-S fuzzy model was proposed for predicting temperature Ms from chemical composition, austenitizing temperature and time for low alloy steel. The degree of membership of each sample was calculated with fuzzy clustering algorithm. Kalman filtering was used to identify the consequent parameters. Compared with the results obtained by empirical models based on the same data, the results by the fuzzy method showed good precision. The accuracy of the fuzzy model is almost 6 times higher than that of the best empirical model. The influence of alloying elements, austenitizing temperature and time on Ms was analyzed quantitatively by using the fuzzy model. It is shown that there exists a nonlinear relationship between the contents of alloying elements in steels and their Ms, and the effects of austenitizing temperature and time on Ms temperature cannot be neglected.

Numerical-Experimental Updating Identification of Elastic Behavior of a Composite Plate Using New Multi-Objective Optimization Procedure

This work focuses on the updating-based identification of the three-dimensional orthotropic elastic behavior of a thin carbon fiber reinforced plastic multilayer composite plate. This consists in identifying the engineering constants that minimize the relative deviations between the first eight experimental and three-dimensional finite element frequencies of the vibrating free plate. For this purpose, a multi-objective optimization procedure is applied;it exploits a Particle Swarm Optimizer algorithm (PSO) that is coupled to a metamodeling by the new response surfaces method procedure (NRSMP);the latter is based on numerical design experiments. The conducted sensitivity analyses indicate that the four engineering constants of the two-dimensional elasticity are the most influent.

Rapid identification of spinal ventral and dorsal roots using a quartz crystal microbalance

The fast and accurate identification of nerve tracts is critical for successful nerve anastomosis. Taking advantage of differences in acetylcholinesterase content between the spinal ventral and dorsal roots, we developed a novel quartz crystal microbalance method to distinguish between these nerves based on acetylcholinesterase antibody reactivity. The acetylcholinesterase antibody was immobilized on the electrode surface of a quartz crystal microbalance and reacted with the acetylcholinesterase in sample solution. The formed antigen and antibody complexes added to the mass of the electrode inducing a change in frequency of the electrode. The spinal ventral and dorsal roots were distinguished by the change in frequency. The ventral and dorsal roots were cut into 1 to 2-mm long segments and then soaked in 250 pL PBS. Acetylcholinesterase antibody was immobilized on the quartz crystal microbalance gold electrode surface. The results revealed that in 10 minutes, both spinal ventral and dorsal roots induced a frequency change; however, the frequency change induced by the ventral roots was notably higher than that induced by the dorsal roots. No change was induced by bovine serum albumin or PBS. These results clearly demonstrate that a quartz crystal microbalance sensor can be used as a rapid, highly sensitive and accurate detection tool for the quick identification of spinal nerve roots intraoperatively.

Genetic algorithms and aquifer parameter identification

In order to identify aquifer parameter,authors develops an improved combinatorial method called best chromosome clone plus younger generation chromosome prepotency genetic algorithm (BCC-YGCP-GA), based on a decimal system simple genetic algorithm (SGA). The paper takes unsteady state flows in a two dimensional, inhomogeneous, confined aquifer for a ideal model, and utilizes SGA and BCC-YGCP-GA coupled to finite element method for identifying aquifer hydraulic conductivity K 1 ,K 2 ,K 3 and storage S 1 ,S 2 ,S 3 , respectively. It is shown from the result that GSA does not reach convergence with 100 generations, whereas convergence rate of BCC-YGCD-GA is very fast. Objective function value calculated by BCC-YGCD-GA is 0 001 29 with 100 generations, and hydraulic conductivity and storage of three zones are almost equal to the "true" values of ideal model.

Characteristics of Implicit Customer Needs in Product Design and Methods for Their Identification

The identification of customer needs is one of the important first⁃step works for product design.Contrary to explicit ones,the implicit customer needs are less obvious,thus relying on the designers to discover.Up till now,there still lacks a rational or systematic method on the identification of implicit customer needs.Designers have to rely on their own intuition and personal experience to do the work,hindering the product design and development further on.Therefore,it is necessary to study the implicit customer needs and their identification methods.To this end,this paper first studies the characteristics of implicit needs,and clarifies the relationship between implicit needs and explicit needs.Based on this,the concept of customer needs life cycle is put forward.After that,two methods for the identification of implicit needs are proposed,including an active approach and a passive approach.For the active approach,it is suggested to exploit the functional characteristics of the product and the products in the same series or categories,for which a direct acquisition method and an evaluation data mining method are proposed,and a treadmill design case is studied.For the passive approach,it is suggested to exploit the scenario elements of product usage,for which a scenario elements questionnaire method and a scenario adaptation problem method are proposed,and a spinning bike design case is studied.The two design cases have demonstrated the process of customer needs identification and also verified the applicability of the proposed methods.

Inverse Problems for an Euler-Bernoulli Beam: Identification of Bending Rigidity and External Loads

We present a method for identifying the flexural rigidity and external loads acting on a beam using the finite-element method. We used mixed beam elements possessing transverse deflection and the bending moment as the primary degrees of freedom. The first step is to determine the bending moment from the transverse deflection and boundary conditions. The second step is to substitute the bending moment into the final equations with respect to the unknown parameters (flexural rigidity or external load). The final step solves the resulting system of equations. We apply this method to some inverse beam problems and provide an accurate estimation. Several numerical examples are performed and show that present method gives excellent results for identifying bending stiffness and distributed load of beam.

数据要素价值释放研究进展

数字经济时代,数据成为重要生产要素,透过开放共享与市场化配置释放其价值。文章基于文献内容,详细探讨数据作为生产要素的特征,并深入阐述数据要素价值释放理论、路径与问题,分析目前数据要素确权、定价机制及价值释放过程,探讨政府数据、企业数据及个人数据等不同主体数据要素价值释放模式与路径,指出未来数据要素价值释放研究方向。

基于1D-CNN的无砟轨道CA砂浆脱空识别

为解决水泥乳化沥青砂浆(CA砂浆)脱空位置识别的难题,提出考虑CA砂浆脱空的无砟轨道模型建模与计算方案。首先,基于CRTS I型板式无砟轨道“梁-板-板”建模理论,使用非线性弹簧模拟CA砂浆脱空病害,输入扣件支点反力作为模型的激励,得到监测点位的垂向加速度数据集。其次,通过对数据集缩放、添加噪声的方式进行数据增强,增强数据集的差异,以增强识别模型的泛化性,获得更加准确的识别结果。最后,建立脱空病害的识别方法,搭建一维卷积神经网络(1D-CNN)进行CA砂浆的脱空位置识别,构建准确率、查准率和查全率等评价指标评估识别结果,使用t-SNE降维算法对结果进行可视化。对比其他3种神经网络的表现,探讨1D-CNN应用于CA砂浆脱空位置识别的优势。研究结果表明:“梁-板-板”模型反映了无砟轨道的力学本征,用于CA砂浆脱空问题的仿真模拟是可行的;通过对数据集信号缩放、添加噪声的方式进行数据增强可提高深度学习模型的性能;从深度学习的角度来看,CA砂浆脱空发生在板中造成的危害较小,应重点关注板端CA砂浆脱空的养护与维修问题;1D-CNN相比其他3种模型运算时间短,在CA砂浆脱空位置识别数据集上优势更大,识别准确率可达95%以上。研究结果为进一步提高无砟轨道结构监测的自动化和智能化水平提供参考。

数据驱动的半无限介质裂纹识别模型研究

缺陷识别是结构健康监测的重要研究内容,对评估工程结构的安全性具有重要的指导意义,然而,准确确定结构缺陷的尺寸十分困难.论文提出了一种创新的数据驱动算法,将比例边界有限元法(scaled boundary finite element methods,SBFEM)与自编码器(autoencoder,AE)、因果膨胀卷积神经网络(causal dilated convolutional neural network,CDCNN)相结合用于半无限介质中的裂纹识别.在该模型中,SBFEM用于模拟波在含不同裂纹状缺陷半无限介质中的传播过程,对于不同的裂纹状缺陷,仅需改变裂纹尖端的比例中心和裂纹开口处节点的位置,避免了复杂的重网格过程,可高效地生成足够的训练数据.模拟波在半无限介质中传播时,建立了基于瑞利阻尼的吸收边界模型,避免了对结构全域模型进行计算.搭建了CDCNN,确保了时序数据的有序性,并获得更大的感受野而不增加神经网络的复杂性,可捕捉更多的历史信息,AE具有较强的非线性特征提取能力,可将高维的原始输入特征向量空间映射到低维潜在特征向量空间,以获得低维潜在特征用于网络模型训练,有效提升了网络模型的学习效率.数值算例表明:提出的模型能够高效且准确地识别半无限介质中裂纹的量化信息,且AE-CDCNN模型的识别效率较单CDCNN模型提高了约2.7倍.

基于正交切削逆识别井下管柱的Johnson-Cook本构模型

在有限元仿真金属切削过程中,本构模型是仿真的基础,目前井下生产管柱J55油管材料的本构模型参数尚不明确,为此,提出一种基于正交切削理论逆识别油管材料Johnson-Cook(J-C)本构模型参数的方法。首先,通过准静态拉伸试验得到油管材料的应力-应变曲线,根据曲线拟合确定J55油管的初始屈服强度A、应变硬化系数B和应变硬化因子n;其次,通过正交切削试验获得切削力以及进给力,根据正交切削试验和平行剪切区模型,计算正交切削过程主剪切区中的流动应力、应变、应变率以及切削温度,并将这些参数与计算出的A、B、n代入J-C模型中,得到多组应变率敏感性参数C以及热软化效应参数m,从而确定其约束范围;第三,采用自适应权重粒子群算法在约束范围中搜索出参数C和m的最优值,进而确定J55油管材料本构模型参数;最后,使用逆识别法得出的J-C本构模型进行有限元仿真,将仿真结果与试验结果进行了对比。研究结果表明:与试验相比,有限元仿真的切削力和进给力最大相对误差分别为14.4%和13.64%,有限元仿真模拟温度与实际测量温度的最大相对误差为10.57%,仿真模型和实际切削过程在切屑形态上表现出了一致规律,验证了逆识别方法可行性和本构模型的可靠性。

桑树NAC基因家族鉴定与生根粉处理下表达模式分析

【目的】探究桑树NAC基因家族的生物信息学特征,并研究1000 mg·L^(-1)生根粉(ABT)处理对该基因产生的影响,为深入研究桑树NAC转录因子的功能提供依据。【方法】利用生物信息学方法对川桑NAC基因家族进行基因鉴定,并分析其理化性质、保守基序、顺式作用元件、系统进化树、蛋白三级结构及互作关系,并选用‘果桑大十’作为试验材料,经ABT处理后,分析其4个时期(10、20、30、40 d)NAC基因家族的表达模式。【结果】桑树NAC基因家族共有92个成员,分为22个亚家族,亚家族成员广泛分布于细胞核,且具有相似的保守结构。顺式作用元件分析表明,桑树NAC基因家族对激素具有较强的响应能力。蛋白三级结构显示同一亚家族的蛋白空间结构相似,且功能相同,这可能与其进化同源性有关。ABT处理后,NAC基因家族的表达水平整体呈上升趋势,而MnNAC91、MnNAC67、MnNAC28在对照组(CK)中呈现较高的表达水平。【结论】NAC基因家族功能相对稳定,在整个进化过程中无明显变化;ABT可促进NAC基因家族表达,尤其是MnNAC75、MnNAC104、MnNAC7、MnNAC30、MnNAC101、MnNAC83、MnNAC102具有较高的同源性,并与拟南芥的结构功能相似,推测对抗干旱胁迫有一定作用。