Prediction of boundary shear stress in circular and trapezoidal channels with entropy concept

Relying on the power law to develop new relationships, the present study developed the Shannon entropy concept to predict shear stress distribution. The presented method was evaluated and compared with valid laboratory results and the shear stress distribution surveyed through this concept in circular, circular with flat bed and trapezoidal channels. By increasing the flow depth in circular channels, the model presented herein gives an improved prediction of shear stress distribution, while in circular channels with flat bed it is better in predicting shear stress both at lower flow depth and subcritical flow conditions. In comparison, in trapezoidal channels the model is much better in predicting the shear stress distribution at lower flow depths. Accordingly, with a mean error percentage of 1.99% in circular channels, 3.69% in circular channels with flat bed and 4.1% in trapezoidal channels, this novel model shows good ability in predicting shear stress distribution.     

New developments in predicting stage–discharge curves, velocity and boundary shear stress distributions in open channel flow

The stage–discharge curve, depth-averaged velocity and boundary shear stress distributions are required to be determined for flood alleviation schemes. These parameters are hard to predict because of the three-dimensional (3-D) aspects of flow in open channels. This paper proposes a new approach for modelling open channel flow based on the Shiono and Knight Method (SKM), which is a depth-averaged model based on the governing Navier–Stokes equations. The modelling philosophy is applied to natural rivers and artificial channels both in inbank and overbank flow conditions. Accurate results are obtained when compared with field data and experimental measurements. Modelling philosophies are presented for the three calibration coefficients of the SKM. These coefficients represent the most important features of the 3-D flow mechanism.     

Efficient shear stress distribution detection in circular channels using Extreme Learning Machines and the M5 model tree algorithm

With the aid of 174 laboratory data sets, Extreme Learning Machine (ELM) and decision tree (M5) models were investigated in predicting the shear stress distribution in circular channels. To evaluate the sensitivity of the input variables, 15 different input combinations were applied to each model. The calculation results show that the Re and y/P parameter values greatly affect ELM method performance, while y/P and h/D are sensitive to shear stress distribution modeling with M5. The best models among ELM and M5 were compared with an equation based on the Shannon entropy. According to the comparison results, the two proposed models outperform the Shannon entropy equation. Moreover, the ELM method’s function is superior in estimating the shear stress distribution and more adapted to experimental data with average Root Mean Square Error (RMSE) of 0.0236 compared to the M5 method with RMSE of 0.0364.     

Prediction of pullout interaction coefficient of geogrids by extreme gradient boosting model

Geogrids embedded in fill materials are checked against pullout failure through standard pullout testing methodology. The test determines the pullout interaction coefficient which is critical in fixing the embedment length of geogrids in mechanically stabilized earth walls. This paper proposes prediction of pullout interaction coefficient using data driven machine learning regression algorithms. The study primarily focusses on using extreme gradient boosting (XGBoost) method for prediction. A data set containing 220 test results from the literature has been used for training and testing. Predicted results of XGBoost have been compared with the results of random forest (RF) ensemble learning based algorithm. The predictions of XGBoost model indicates 85% accuracy and that of RF model shows 77% accuracy, indicating significantly superior and robust prediction through XGBoost above RF model. The importance analysis indicates that normal stress is the most significant factor that influences the pullout interaction coefficients. Subsequently pullout tests have been performed on geogrid embedded in four different fill materials at three normal stresses. The proposed XGBoost model gives 90% accuracy in prediction of pullout interaction coefficient compared to laboratory test results. Finally, an open-source graphical user interface based on the XGBoost model has been created for preliminary estimation of the pullout interaction coefficient of geogrid at different test conditions.     

Bed shear stress evaluation in combined sewers

Experiments have been undertaken on two sewer trunk lines in order to identify an accurate and practical technique for estimating bed shear stresses in combined sewers. Various methods were tested to determine both local bed shear stress values (one based on the logarithmic velocity profile and the other on the Reynolds shear stress distribution) and mean bed shear stress values (using a method based on the energy slope). Velocity measurements were performed using a micropropeller and an Acoustic Doppler Velocimeter (ADV) under dry weather flow conditions. In sewers without sediments, both the wall law and Reynolds shear stress distribution methods lead to the same bed shear stress estimation. A method based on the logarithmic velocity profile obtained by micropropeller is proposed herein to evaluate local shear stress in combined sewers. Calculations based on channel slope lead to an over-estimation of bed shear stress due to the inaccuracy of bed slope data. If the energy slope S _c , as calculated from the Darcy-Weisbach or Manning formula, is used to calculate the mean shear stress in sewer sections without sediments, results are consistent with the local shear stress measurements.     

基于RF-GOA-RVM的海底管道腐蚀速率预测

针对油气管道腐蚀预测模型参数确定困难及预测精度不高等问题,提出一种基于RF-GOA-RVM的腐蚀速率预测新方法。运用随机森林（RF）筛选海底管道腐蚀影响因素,确定腐蚀主要因素;用蝗虫算法（GOA）优化相关向量机（RVM）参数,预测管道腐蚀速率。仿真实验表明：与粒子群算法-相关向量机（PSO-RVM）和RVM相比,RF-GOA-RVM模型稳定性更好,预测精度更高,可为海底管道腐蚀失效预测提供决策依据。     

锚固段侧阻力分布的一维滑移-软化半数值分析

工程实际表明，预应力锚索（拉力型）锚固段侧阻力的沿程分布多呈单峰上凸曲线，而较多解析推导及半数值分析采用锚固体与孔壁界面的严格全程黏结假设，其计算结果难以解释这一现象。对此，以岩土介质的半无限弹性体假设为基础建立一维力学模型，利用半无限体Mindlin问题的位移解析解，以半数值法求得岩土体与锚固体的孔壁界面位移差值。通过引入侧阻力与位移差值的滑移-软化模型关系，对锚索锚固段的侧阻力分布进行半数值求解探索和算例讨论。相对于锚固段严格全程黏结假设，考虑孔壁界面侧阻力滑移-软化特性更符合实际情况，在张拉力作用下，锚固段始端一定范围的滑移使该区段侧阻力降低，应力向深处转移调整，从而形成侧阻力分布的单峰曲线。     

Estimating moment capacity of ferrocement members using self-evolving network

In this paper, an empirical model based on self-evolving neural network is proposed for predicting the flexural behavior of ferrocement elements. The model is meant to serve as a simple but reliable tool for estimating the moment capacity of ferrocement members. The proposed model is trained and validated using experimental data obtained from the literature. The data consists of information regarding flexural tests on ferrocement specimens which include moment capacity and cross-sectional dimensions of specimens, concrete cube compressive strength, tensile strength and volume fraction of wire mesh. Comparisons of predictions of the proposed models with experimental data indicated that the models are capable of accurately estimating the moment capacity of ferrocement members. The proposed models also make better predictions compared to methods such as the plastic analysis method and the mechanism approach. Further comparisons with other data mining techniques including the back-propagation network, the adaptive spline, and the Kriging regression models indicated that the proposed models are superior in terms prediction accuracy despite being much simpler models. The performance of the proposed models was also found to be comparable to the GEP-based surrogate model.     

Shear strength estimation of reinforced concrete beam–column sub‐assemblages using multiple soft computing techniques

The aim of the present study is to propose innovative predictive models for shear capacity of reinforced concrete (RC) exterior joints in terms of multiple soft computing techniques. Existing models were evaluated and by a preliminary sensitivity analysis, seven parameters including compressive strength of concrete, product of the yield stress and the reinforcement ratio of the joint stirrups, the effective width of the joint panel, cross‐sectional column width, beam tensile longitudinal reinforcement ratio, beam compressive longitudinal reinforcement ratio, and column longitudinal reinforcement ratio were considered. Then, a large data set having the details of experimental programs on shear capacity of exterior RC beam–column joints was provided. The experimental data were utilized in developing the proposed models. After verification of the new models against available database, their efficiency compared with existing models was confirmed. Finally, a sensitivity analysis was performed in order to find the relative importance of each input parameter on the shear strength of RC joints. The results indicated that the beam reinforcement is the most important factor in shear capacity estimation of exterior RC beam–column connections.     

Slope stability prediction using ensemble learning techniques: A case study in Yunyang County,Chongqing, China

Slope stability prediction plays a significant role in landslide disaster prevention and mitigation. This study develops an ensemble learning-based method to predict the slope stability by introducing the random forest(RF) and extreme gradient boosting(XGBoost). As an illustration, the proposed approach is applied to the stability prediction of 786 landslide cases in Yunyang County, Chongqing, China. For comparison, the predictive performance of RF, XGBoost, support vector machine(SVM), and logi...     

Three-Dimensional Modeling of Tailings Beach Shape

Abstract: Tailings (mining waste) disposal is a significant consideration for the mining industry, with the majority of the ore processed in most mining operations ending up as tailings. This creates large volumes of tailings, which must be handled and stored responsibly to avoid potential environmental catastrophes. The most common form of tailings storage facility is the impoundment, where tailings are contained within a basin, with beaches forming around the perimeter of the impoundment and a pond standing in the middle. A relatively new method of tailings storage is to create a “stack,” whereby the tailings solids form a large heap, with the discharge of tailings slurry from the apex of the heap. This method of tailings storage is finding greater popularity as the industry seeks to reduce the amount of water discharged with the tailings, and usually features the discharge of non‐segregating tailings slurry that flows turbulently in its own self‐formed channel down the tailings beach. It is of significant interest for mine operators and tailings engineers to be able to predict the shape of the beach that forms in either of these disposal scenarios. The key to being able to do this relies on a method of prediction of the beach slope. In this article two new beach shape models are presented for the three‐dimensional (3‐D) geometric modeling of the beach surface of a tailings stack that has been formed through the variable discharge of a non‐segregating slurry that periodically changes in its composition, whereby the overall discharge output is defined as a sequence of smaller finite periods of steady uniform discharge, each having its own resulting beach slope. A beach slope model previously presented by the authors has been used here to predict the applicable beach slope for each finite discharge regime. The shape models presented here present two different methods for the compounding of the individual tailings deposits that are generated by each of these finite discharge regimes. Historic tailings discharge data is run through both models, and the shapes predicted by the models are compared with aerial survey data of real tailings stacks. This work not only presents a method of tailings stack shape prediction, but also a plausible theory for explaining the concavity of tailings beaches. The models also have the potential to be developed further for the 3‐D modeling of tailings beaches formed in other types of storage facilities, such as impoundments or valleys.     

Numerical investigation of longitudinally stiffened web channels predominantly in shear

In practice, there is a wide variety of commercially available channel sections with complex shapes where the web is stiffened by adding longitudinal intermediate stiffeners. These stiffeners may improve the shear capacity of the channels. Recently, the Direct Strength Method (DSM) of design of cold-formed sections has been extended in the North American Specification for Cold-Formed Steel Structural Members (NAS S100:2012) to include shear based on research by the authors. The prequalified sections include flat webs and webs with small intermediate longitudinal stiffeners. To extend the range to larger intermediate stiffeners as occurs in practice, a series of predominantly shear tests of lipped channel sections with one web stiffener of different shapes and various sizes has been performed at the University of Sydney. Six different types of stiffened web channel sections were tested along with an additional reference plain section. All tests were conducted with straps screwed on the top flanges adjacent to the loading points. These straps provide torsion/distortion restraints which may enhance the shear capacities of the sections. The test failures were observed mainly in the combined bending and shear modes. Numerical simulations based on the Finite Element Method (FEM) using the software package ABAQUS/Standard are also performed to compare with and calibrate against the tests. The accurate results from the FEM models allow extension of the test data. Based on the reliable FEM models, a series of FEM modelling of predominantly shear tests for stiffened web channels has been performed without straps attached to the top flanges adjacent to loading points. The test and FEM results are subsequently plotted against the DSM interaction curves between bending and shear where the interaction is found to be significant. An extended range of DSM prequalified sections with longitudinally stiffened web channels in shear is proposed in this paper.     

Prediction of the backwater level due to bridge constriction in waterways

This article proposes a mathematical method to calculate the backwater level at bridge constrictions for compound channels. Such a model is necessary, as many of the previously developed simple formulas yield inaccurate results. Parametric studies on a single‐opening semicircular arch, single‐opening semielliptical arch and single‐opening straight deck bridge were also conducted using the commercial software HEC‐RAS to investigate the influences of different factors on backwater level. The results indicated that the Froude number, opening ratio, discharge and roughness coefficient impact the backwater level considerably. Hence, a simple mathematical method was developed based on these parameters and validated using experimental data in a symmetrical two‐stage channel with different roughness coefficients for different types of bridge models. The results obtained using the proposed formula corresponded well with the experimental data and the results obtained using the energy method, which is accurate and the most commonly used method to calculate backwater level.     

基于地应力现场实测与开采扰动能量积聚理论的岩爆预测研究

高地应力诱发的岩爆灾害是目前深部地下工程经常遇到的工程地质问题。现场地应力测量是岩爆预测的重要前提,根据三山岛金矿深部测量和岩体赋存状况的特点,优化应力解除测量技术并在矿区深部进行现场实测。提出采场岩爆发生的2个必要条件,即岩石具备储备高应变能的特性和采场具备高应变能积聚的应力环境。基于地应力实测与岩石力学室内试验结果,采用多准则判据对矿区深部发生岩爆的倾向性做出定性分析与评价。FLAC3D数值模拟分析揭示深部开采引起的采场围岩能量积聚、分布状况及变化规律。首次采用地震学的知识,对三山岛金矿未来深部开采过程中可能诱发岩爆的地点和级别做出预测。研究成果为深部地下工程岩爆的预测、预报提供新的思路和途径。     

考虑剪胀性和应变软化的油砂非线性弹性模型

油砂力学模型是石油工程设计与开发的基础。为了更精确地描述油砂的剪胀和应变软化特征,本文提出了一种四参数形式的轴应变-偏应力、轴应变-体应变模型,对比分析了四参数模型、南水模型和修正的成都科大模型对风城油砂轴应变-偏应力、轴应变-体应变测试数据的拟合效果,最后对剪胀扩容诱导的绝对渗透率和水的有效渗透率增量进行了预测。研究表明,四参数模型比南水模型、修正的成都科大模型更能合理描述油砂的应变软化、剪胀效应以及体应变演化。根据四参数模型能够更精确地预测剪胀诱导的绝对渗透率以及水的有效渗透率增量,其预测误差比修正的成都科大模型小50%以上。本文提出的四参数模型可以为油砂钻完井及热采数值模拟分析提供关键依据。     

断层倾角对断层活化及底板突水的影响研究

 针对含断层缺陷底板的受力特征,建立相应的简化力学模型,分析得到断层面上的剪切应力和法向应力表达式,并研究断层倾角对断层面上剪切应力、法向应力及断层活化的影响规律。同时运用RFPA2D-Flow软件,模拟不同倾角的正断层在采动影响下底板的裂隙分布、渗流分布及采空区底板涌水量变化特征。模拟结果在一定程度上揭示含断层构造底板突水通道的形成机制及断层倾角对底板突水的影响规律。研究表明,断层倾角越大,断层越容易活化与突水。研究结果对采场底板含断层缺陷时防水煤柱的留设具有重要的参考价值。     

煤矿井下地质构造对地应力分布的影响

采用小孔径水压致裂地应力测量装置,在典型的急倾斜、特厚煤层矿区——甘肃华亭矿区的大型向斜构造附近进行14个测站地应力测量,以分析向斜构造不同部位的地应力变化。实测数据表明:华亭煤矿、砚北煤矿井下构造应力占绝对优势;在向斜翼部,水平应力较小;在向斜轴部,水平应力急剧增加,增加幅度远大于垂直应力;向斜构造对矿区地应力分布产生严重影响。基于山西晋城矿区的地应力实测数据,分析断层对地应力值与方向的影响。断层附近某些区域水平应力有所减小,大型断层会引起最大水平主应力方向的扭转。在实测数据基础上,采用FLAC3D数值计算软件,分析华亭矿区大型向斜构造周围地应力场分布,并与地应力实测数据进行对比。将地应力实测与数值模拟有机结合,是全面了解煤矿井下地应力场分布特征的有效途径。     

直接强度法计算冷弯薄壁斜卷边槽钢轴压柱的承载力

通过计算得到了适合各种弯起角度的斜卷边槽形截面特性计算公式,方便了手算求解构件的屈曲应力。采用直接强度计算法对斜卷边槽钢轴压固支柱的稳定承载力及破坏模式进行了分析,并与已有的试验资料进行了对比。结果表明:直接强度法可以有效地预测斜卷边槽钢轴压固支构件的稳定承载力,从而说明了建立在简支试验结果基础上,经回归得到的直接强度法同样适用于固支柱稳定承载力的计算。     

潮间带原位剪切波速特性探讨及应用分析

探讨适用于近海及潮间带场区的剪切波速原位测试方法,针对黄海小洋口潮间带,进行剪切波速的原位测试,分析剪切波速的变化规律及其与土体参数的统计关系,并建立复合关系进行剪切波速预测分析,同时基于剪切波速测试成果进行应用分析。研究结果如下：通过经适性对比,近海及潮间带剪切波速测试采用单孔悬挂式方法较为适宜;剪切波速与测点深度呈相关性较好幂函数关系,按土层的统计关系分析,幂函数及其误差包络线基本反映了规律性;与土体物理力学参数的统计关系呈相关性较好幂函数或线性关系;基于测试资料,建立剪切波速 、孔隙比e、密度 及有效自重应力 的复合关系,通过计算对比分析,按此方法可以取得良好的剪切波速预测结果,亦可进行相关指标的预测分析;通过原位测试资料,进行场地土类划分对比、动参数规律性分析及地震液化判定分析,可为工程勘测、设计人员提供参考。     

半刚性框架-屈曲约束钢板剪力墙结构弹塑性层剪力分布研究

为研究弹塑性状态下半刚性框架-屈曲约束钢板剪力墙结构(BR-SPSW)的层剪力分布,设计了具有理想屈服模式的5层、10层、15层和20层的BR-SPSW结构等效拉杆简化模型。综合考虑结构层数、构件截面、近场地震速度脉冲效应及远场地震加速度循环累积效应对结构的影响,采用弹塑性时程分析方法获得了BR-SPSW结构在两类地震作用下的层剪力分布平均值,提出了BR-SPSW结构弹塑性状态的层剪力分布模式,并基于已有层剪力分布模式及GB 50011—2010《建筑抗震设计规范》的底部剪力法提出的层剪力分布模式进行对比。结果表明,近场地震波的速度脉冲效应和远场地震波的加速度循环效应对半刚性框架 屈曲约束钢板墙的层剪力分布影响较大,层剪力分布应综合考虑二者的影响。建议的层剪力分布模式在计算精度上优于其他层剪力分布模式,可为屈曲约束钢板墙结构基于性能的设计方法提供参考。