Pipeline thickness estimation using the dispersion of higher-order SH guided waves

Thickness measurement plays an important role in the monitoring of pipeline corrosion damage. However, the requirement for prior knowledge of the shear wave velocity in the pipeline material for popular ultrasonic thickness measurement limits its widespread application. This paper proposes a method that utilizes cylindrical shear horizontal(SH) guided waves to estimate pipeline thickness without prior knowledge of shear wave velocity. The inversion formulas are derived from the dispersion of higher-order modes with the high-frequency approximation. The waveform of the example problems is simulated using the real-axis integral method. The data points on the dispersion curves are processed in the frequency domain using the wave-number method. These extracted data are then substituted into the derived formulas. The results verify that employing higher-order SH guided waves for the evaluation of thickness and shear wave velocity yields less than1% error. This method can be applied to both metallic and non-metallic pipelines, thus opening new possibilities for health monitoring of pipeline structures.

Landslide displacement prediction based on optimized empirical mode decomposition and deep bidirectional long short-term memory network

There are two technical challenges in predicting slope deformation.The first one is the random displacement,which could not be decomposed and predicted by numerically resolving the observed accumulated displacement and time series of a landslide.The second one is the dynamic evolution of a landslide,which could not be feasibly simulated simply by traditional prediction models.In this paper,a dynamic model of displacement prediction is introduced for composite landslides based on a combination of empirical mode decomposition with soft screening stop criteria(SSSC-EMD)and deep bidirectional long short-term memory(DBi-LSTM)neural network.In the proposed model,the time series analysis and SSSC-EMD are used to decompose the observed accumulated displacements of a slope into three components,viz.trend displacement,periodic displacement,and random displacement.Then,by analyzing the evolution pattern of a landslide and its key factors triggering landslides,appropriate influencing factors are selected for each displacement component,and DBi-LSTM neural network to carry out multi-datadriven dynamic prediction for each displacement component.An accumulated displacement prediction has been obtained by a summation of each component.For accuracy verification and engineering practicability of the model,field observations from two known landslides in China,the Xintan landslide and the Bazimen landslide were collected for comparison and evaluation.The case study verified that the model proposed in this paper can better characterize the"stepwise"deformation characteristics of a slope.As compared with long short-term memory(LSTM)neural network,support vector machine(SVM),and autoregressive integrated moving average(ARIMA)model,DBi-LSTM neural network has higher accuracy in predicting the periodic displacement of slope deformation,with the mean absolute percentage error reduced by 3.063%,14.913%,and 13.960%respectively,and the root mean square error reduced by 1.951 mm,8.954 mm and 7.790 mm respectively.Conclusively,this model not only has high prediction accuracy but also is more stable,which can provide new insight for practical landslide prevention and control engineering.

A general method to calculate passive earth pressure on rigid retaining wall for all displacement modes

A general analytical method to calculate the passive rigid retaining wall pressure was deduced considering all displacement modes. First, the general displacement mode function was setup, then the hypotheses were made that the lateral passive pressure is linear to the corresponding horizontal displacement and the soil behind retaining wall is composed of a set of springs and ideal rigid plasticity body, the general analytical method was proposed to calculate the passive rigid retaining wall pressure based on Coulomb theory. The analytical results show that the resultant forces of the passive earth pressure are equal to those of Coulomb＇s theory, but the distribution of the passive pressure and the position of the resultant force depend on the passive displacement mode parameter, and the former is a parabolic function of the soil depth. The analytical results are also in good agreement with the experimental ones.

Separation of closely spaced modes by combining complex envelope displacement analysis with method of generating intrinsic mode functions through filtering algorithm based on wavelet packet decomposition

One of the important issues in the system identification and the spectrum analysis is the frequency resolution, i.e., the capability of distinguishing between two or more closely spaced frequency components. In the modal identification by the empirical mode decomposition （EMD） method, because of the separating capability of the method, it is still a challenge to consistently and reliably identify the parameters of structures of which modes are not well separated. A new method is introduced to generate the intrin- sic mode functions （IMFs） through the filtering algorithm based on the wavelet packet decomposition （GIFWPD）. In this paper, it is demonstrated that the CIFWPD method alone has a good capability of separating close modes, even under the severe condition beyond the critical frequency ratio limit which makes it impossible to separate two closely spaced harmonics by the EMD method. However, the GIFWPD-only based method is impelled to use a very fine sampling frequency with consequent prohibitive computational costs. Therefore, in order to decrease the computational load by reducing the amount of samples and improve the effectiveness of separation by increasing the frequency ratio, the present paper uses a combination of the complex envelope displacement analysis （CEDA） and the GIFWPD method. For the validation, two examples from the previous works are taken to show the results obtained by the GIFWPD-only based method and by combining the CEDA with the GIFWPD method.

Speech-stream detection in short-wave channel based on empirical mode decomposition and higher-order statistics

To capture the presence of speech embedded in nonspeech events and background noise in shortwave non-cooperative communication, an algorithm for speech-stream detection in noisy environments is presented based on Empirical Mode Decomposition （EMD） and statistical properties of higher-order cumulants of speech signals. With the EMD, the noise signals can be decomposed into different numbers of IMFs. Then, the fourth-order cumulant （ FOC ） can be used to extract the desired feature of statistical properties for IMF components. Since the higher-order eumulants are blind for Gaussian signals, the proposed method is especially effective regarding the problem of speech-stream detection, where the speech signal is distorted by Gaussian noise. With the self-adaptive decomposition by EMD, the proposed method can also work well for non-Gaussian noise. The experiments show that the proposed algorithm can suppress different noise types with different SNRs, and the algorithm is robust in real signal tests.

High resolution angular-displacement sensor based on whispering gallery mode resonance in bent optical fibers

A simple fiber sensor to measure angular displacement with high resolution, which is based on whispering gallery mode （WGM） resonance in bent optical fibers,is proposed. The sensor is composed of a single loop formed by loosely tying a knot using single mode fiber. To measure the transmission spectra, a tunable laser and an optic power meter are connected to the two ends of fi- ber loop, respectively. Significant WGM resonances occur over the investigated wavelength range for all the sensors with different bend radius. The angular-displacement sensitivity is studied in the range from -0. 1°to 0. 1°. The detection limit of 1.49 × 10 ^-7 rad can be achieved for the detecting system with the resolution of lpm. The simple loop-structure fiber sensor has potential application prospect in the field of architecture or bridge building with low detection limit and low cost.

Evaluation of stress intensity factors for bi-material interface cracks using displacement jump methods

The aim of the present work is to investigate the numerical modeling of interfacial cracks that may appear at the interface between two isotropic elastic materials. The extended finite element method is employed to analyze brittle and bi-material interfacial fatigue crack growth by computing the mixed mode stress intensity factors(SIF). Three different approaches are introduced to compute the SIFs. In the first one, mixed mode SIF is deduced from the computation of the contour integral as per the classical J-integral method,whereas a displacement method is used to evaluate the SIF by using either one or two displacement jumps located along the crack path in the second and third approaches. The displacement jump method is rather classical for mono-materials,but has to our knowledge not been used up to now for a bimaterial. Hence, use of displacement jump for characterizing bi-material cracks constitutes the main contribution of the present study. Several benchmark tests including parametric studies are performed to show the effectiveness of these computational methodologies for SIF considering static and fatigue problems of bi-material structures. It is found that results based on the displacement jump methods are in a very good agreement with those of exact solutions, such as for the J-integral method, but with a larger domain of applicability and a better numerical efficiency(less time consuming and less spurious boundary effect).

On the accuracy of higher order displacement discontinuity method(HODDM) in the solution of linear elastic fracture mechanics problems

The higher order displacement discontinuity method(HODDM) utilizing special crack tip elements has been used in the solution of linear elastic fracture mechanics(LEFM) problems. The paper has selected several example problems from the fracture mechanics literature(with available analytical solutions) including center slant crack in an infinite and finite body, single and double edge cracks, cracks emanating from a circular hole. The numerical values of Mode Ⅰ and Mode Ⅱ SIFs for these problems using HODDM are in excellent agreement with analytical results(reaching up to 0.001% deviation from their analytical results). The HODDM is also compared with the XFEM and a modified XFEM results. The results show that the HODDM needs a considerably lower computational effort(with less than 400 nodes) than the XFEM and the modified XFEM(which needs more than 10000 nodes) to reach a much higher accuracy. The proposed HODDM offers higher accuracy and lower computation effort for a wide range of problems in LEFM.

Simulation of crack coalescence mechanism underneath single and double disc cutters by higher order displacement discontinuity method

The present research is focused on the numerical crack coalescence analysis of the micro-cracks and cracks produced during the cutting action of TBM disc cutters. The linear elastic fracture mechanics(LEFM) concepts and the maximum tangential stress criterion are used to investigate the micro crack propagation and its direction underneath the excavating discs. A higher order displacement discontinuity method with quadratic displacement discontinuity elements is used to estimate the stress intensity factors near the crack tips. Rock cutting mechanisms under single and double type discs are simulated by the proposed numerical method.The main purposes of the present modeling are to simulate the chip formation process of indented rocks by single and double discs.The effects of specific disc parameters(except speed) on the thrust force Ft, the rolling force Fr, and the specific energy ES are investigated. It has been shown that the specific energy(energy required to cut through a unit volume of rock) of the double disc is less than that of the single disc. Crack propagation in rocks under disc cutters is numerically modeled and the optimum ratio of disc spacing S to penetration depth Pd(i.e. S/Pd ratio) of about 10 is obtained, which is in good agreement with the theoretical and experimental results cited in the literature.

Approximate analysis method for displacement responses of structures with active variable stiffness systems

The performance of structures with active variable stiffness (AVS) systems exhibits strong nonlinearity due to the variety with time of the stiffness of each storey unit,in which the AVS system is installed.Hence,the classical dynamic analysis method for linear structures,such as the mode-superposition method,is not applicable to structures with AVS systems.In this paper,an approximate analysis method is proposed for displacement responses of structures with AVS systems.Firstly,an equivalent relationship between single-degree-of-freedom (SDOF) structures equipped with AVS systems and so-called fictitious linear structures is established.Then,an approximate mode-superposition (AMS) method is presented for multi-degree-of-freedom (MDOF) structures equipped with AVS systems.The accuracy of this method is investigated through extensive parametrical study using different types of earthquake excitations,and some modification is made to the method. Numerical calculation results indicate that the modified AMS method is effective for estimating the maximum displacements relative to the ground and the maximum interstorey drifts of MDOF structures equipped with AVS systems.

砂土中抗拔螺杆桩承载力及变形特性研究

通过基于数字图像相关技术的模型试验和离散元数值模拟方法(PFC),研究了叶片设置、砂土相对密实度、受荷工况等因素对螺杆桩抗拔承载力和变形特性的影响,利用试验结果校准离散元程序的细观参数,模拟结果用于分析螺杆桩的荷载分担特性、螺纹叶片间距对承载力的影响以及桩周土体滑动面特征。结果表明:抗拔工况下桩基荷载位移曲线呈现软化特征,0.05 D破坏准则适用于抗拔桩的极限承载力判定,叶片的设置使得桩承载力提高37%,螺纹段荷载分担比接近70%,直杆段荷载分担比是抗压工况的2倍;上拔承载力随叶片间距增加呈降低趋势,H/D=1.00是此工况下合理参数;砂土相对密实度的提高使得螺杆桩和直杆桩抗拔承载力分别增长19.4%、26%,而对抗拔桩周围土体位移模式影响有限,螺杆桩桩周土体最大影响范围约为4 D,而直杆桩约为2 D。

型钢混凝土T形截面剪力墙基于性能的变形限值研究

为更好地评估T形截面型钢混凝土(steel reinforced concrete,SRC)剪力墙变形性能,采用ABAQUS有限元软件对按照规范设计的324个T形截面SRC剪力墙构件的破坏形态和变形性能进行研究,根据收集的试验数据分析构件的破坏形态,提出T形截面SRC剪力墙的破坏形态划分准则;以构件的各材料应变极限值为准则来判别构件的性能状态,考虑轴压比、剪跨比、弯剪比、腹板暗柱配钢率、暗柱纵筋配筋率及箍筋暗柱特征值对构件变形性能的影响。对不同性能状态变形限值和参数进行线性回归分析,得到不同破坏类型下各性能状态位移角限值计算式;按规范ASCE 41修正各性能状态变形限值的失效概率,得到具有15%、20%、35%失效概率保证的各性能状态变形限值取值表。研究表明:剪跨比、轴压比对构件各性能状态位移角限值影响较大,暗柱腹板配钢率、纵筋配筋率及箍筋特征值对构件位移角限值影响相对较小,但能提高其延性。按规范ASCE 41修正后的位移角限值取值较为合理且有一定的安全储备。为T形截面SRC剪力墙基于性能的抗震设计与性能评估提供参考。

苏北盆地江苏油田CO_(2)驱油技术进展及应用

CCUS(碳捕集、利用与封存)技术对绿色低碳转型、实现“双碳”目标意义重大,而CO_(2)驱油埋存是其重要内容。苏北盆地江苏油田针对复杂断块油藏提高采收率的技术瓶颈开展CO_(2)驱油技术攻关及多种类型矿场试验,形成了以重力稳定驱、驱吐协同等为特点的复杂断块油藏CO_(2)驱油的4种差异化模式,成功开展了花26断块“仿水平井”重力稳定驱等技术先导试验,建成了10×10^(4) t的复杂断块油藏CCUS示范工程。江苏油田累计注入液碳量30.34×10^(4) t,累计增油量9.83×10^(4) t,实现了较好的增产效果及经济效益。技术研究及试验可为其他复杂断块油藏的CO_(2)驱开发提供参考借鉴。

退变及加载方式对于高加载速率下椎间盘力学行为的影响

腰椎间盘退变导致了整个腰椎间盘粘弹性特性的变化,但是对于腰椎间盘退变的确切机制目前仍知之甚少,特别是在加载方式和高加载速率方面。利用胰蛋白酶溶液制备退变牛腰椎间盘模型,应用数字图像相关技术对退变椎间盘进行轴向压缩实验,研究加载方式对于高加载速率下腰椎间盘内部位移分布及弹性模量的综合影响。结果表明:无论退变前后,高加载速率下腰椎间盘的弹性模量均显著高于准静态加载时。退变对于弹性模量的影响及高加载速率下腰椎间盘内部位移分布的影响均与加载方式有关。组织切片染色结果表明,椎间盘的髓核和纤维环组织在注射胰蛋白酶后产生了不同程度的结构破损。

绕墙底转动模式下装配式挡土墙土压力研究

墙背土压力分布及大小是装配式挡土墙设计的关键依据。设计并开展新型装配式混凝土挡土墙现场试验,研究挡土墙在加载条件下的位移模式和土压力分布规律。以现场试验为原型,建立无黏性填土、墙背倾斜且粗糙的挡土墙理论计算模型,同时考虑挡土墙位移模式与大小、土拱效应和土层间剪应力的影响,采用水平层分析法推导了绕墙底转动(RB)模式下挡土墙的土压力计算公式。结果表明:①该装配式挡土墙整体性能良好,绕墙底刚性转动。在RB模式下,墙顶处土体最先达到主动极限状态,土体从上至下逐渐达到极限状态;任意深度处的土体位移S_(c)达到7 mm时将达到极限状态,即S_(c)=0.16%H(H为墙高)。②本文理论解与试验值吻合较好,计算公式可用于求解挡土墙绕墙底转动过程中的土压力分布及大小。③随着挡土墙转动幅度的增大,土压力分布曲线凹向逐渐明显,土压力合力作用点高度呈现先降低后回升的现象;挡土墙转动角度η=0.007 rad为挡土墙达到主动状态的临界值。

基于深度学习的双阶段大坝变形预测模型

为提高大坝位移预测的准确性,提出了一种新颖的基于深度学习的综合预测方法。首先引入了一种基于完全集成经验模态分解(Complete Ensemble Empirical Mode Decomposition with Adaptive Noise,CEEMDAN)和奇异谱分析(Singular Spectrum Analysis,SSA)的多级数据降噪技术。这能有效地消除监测数据中的噪声和异常值,提高数据质量,为后续预测提供更合理的大坝变形数据。随后构建基于卷积神经网络(Convolutional Neural Network,CNN)和门控循环单元(Gated Recurrent Unit,GRU)的深度学习模型。采用CNN从监测数据中提取丰富的特征,利用GRU来捕获和处理时间序列数据中的长期依赖关系。为了增强模型的表现,引入了自注意力机制,以帮助模型更好地处理和识别数据中的复杂模式。通过与其他预测方法的比较,实验结果表明,该方法在大坝位移预测的准确性和稳定性方面相较于其他方法有显著的提升,能够为大坝变形监控领域提供新方法。

基于EEMD-CNN-LSTM的新型综合模型在滑坡位移预测中的应用

滑坡位移预测是滑坡稳定性评价的重要环节。尽管基于深度学习范式的时间序列方法预测滑坡位移取得了一定的成果,但由于滑坡位移数据的非平稳性、周期性和趋势性变化特征,导致当前时间序列模型的滑坡位移的多变量预测容易过拟合。为解决这一问题,针对滑坡位移数据的波动性和由周期项与趋势项位移叠加组成的特性,提出一种基于孤立森林(Isolation Forest,IF)异常检测、集成经验模态分解(Ensemble Empirical Mode Decomposition,EEMD)、卷积神经网络(Convolutional Neural Networks,CNN)和长短期记忆神经网络(Long Short-Term Memory,LSTM)相结合的滑坡位移预测模型。选择三峡库区以降雨为影响因子的阶跃型白家包滑坡为研究对象,引入IF算法对滑坡原始位移数据进行异常检测,使用EEMD方法提取滑坡趋势项和周期项位移,通过CNN捕捉局部周期项和趋势模式,并基于LSTM模型预测总体位移。结果表明,EEMD-CNN-LSTM在预测降雨情况时滑坡总体位移的均方根误差(RMSE)、平均绝对误差(MAE)、评价绝对百分比误差(MAPE)和决定系数(R2)4种指标分别为0.4190、0.3139、0.2379和0.9997,前3种精度评价指标较现有模型分别提升32.3%、25.1%、7.3%。相较于传统的LSTM模型、随机森林方法和EEMD-LSTM方法,EEMD-CNN-LSTM模型在有、无降雨这一外部影响因素下具有显著优势,能够较大地降低过拟合,提高预测的准确性。

露顶式弧形闸门流固耦合数值模拟正反分析

针对表孔局开泄洪诱发露顶式弧形闸门流激振动问题,借助计算流体力学(CFD)软件Fluent和计算结构动力学(CSD)软件Mechanical APDL构建闸门与泄洪水流的流固耦合传递数学模型,计算并分析闸门在泄流时的振动特性,基于模态叠加法原理编制闸门流激振动反分析程序,实现对闸门流激振动的动力响应结果的反分析。以乌江某工程露顶式弧形闸门为例进行正反分析,结果表明:采用大涡模拟(LES)的紊流模型得出闸门面板的脉动压强具有低频、窄带的特性,基本符合正态分布;利用模态坐标和振型向量、应力向量合成计算闸门的结构动力场,反分析得出的动位移场、动应力场与采用完全法正分析得出的结果基本一致,验证了反分析方法的合理性和程序的适用性。

基于多重分形的改进GRU滑坡位移预测模型

门控机制设计难以学习序列变化趋势,导致传统记忆网络模型对滑坡位移非平稳跃变段预测效果较差.基于多重分形改进门控循环单元(GRU),通过量化序列的变化特征来动态更新门控权重,引入循环神经网络单元的状态融合策略以学习数据的长程相关性特征.采用变分模态分解算法将滑坡累积位移分解成趋势项、周期项及随机项,利用改进GRU进行位移分量的训练和预测.选取三峡库区白水河滑坡监测点ZG93、ZG118进行仿真实验.实验结果表明,相比传统预测模型,新模型的滑坡位移形变趋势特征学习能力更强,预测精度更高.

连续性电液伺服系统位移轨迹的滑模跟踪控制

为解决电液伺服系统在零位附近运动时,系统跟踪活塞杆位移轨迹出现抖振问题,提出一种改进连续性电液伺服模型,采用滑模控制方法设计切换超平面和趋近律,在同一大气压下,建立电液伺服系统滑模跟踪控制器,将连续性电液伺服系统和传统的电液伺服系统进行建模仿真,分析电液伺服系统位移轨迹的跟踪控制精度。结果表明,在活塞杆位移跟踪轨迹时,相比传统电液伺服系统,连续性电液伺服系统平滑了2 kHz的抖振现象,且位移跟踪精度提高了5%。