Inverse analysis for geomaterial parameter identification using Pareto multiobjective optimization

An inverse analysis method that combines the back propagation neural network (BPNN) and vector evaluated genetic algorithm (VEGA) was proposed to identify mechanical geomaterial parameters for a more accurate prediction of deformation. The BPNN is used to replace the time‐consuming numerical calculations, thus enhancing the efficiency of the inverse analysis. The VEGA is used to find the Pareto‐optimal solutions to multiobjective functions. Unlike traditional back‐analysis methods which are based on only 1 type of field measurement and a single objective function, this proposed method can consider multiple field observations simultaneously. The proposed method was applied to the Shapingba foundation pit excavation located in Chongqing city, China. Two types of measurements are considered in the method simultaneously: the displacements in the x‐direction (north orientation) and those in the y‐direction (east orientation). Five deformation modulus parameters for artificial backfill soil, silty clay, siltstone, sandstone, and mudstone were selected as the inversion parameters. Compared with the weighted sum approach, the proposed method was demonstrated as an efficient multi‐objective optimization tool for back calculating undetermined parameters. After performing a forward‐calculation using the optimized parameters obtained by the inverse analysis, the predicted results were well consistent with the practical deformation in magnitude and trend.     

Optimized neural network using beetle antennae search for predicting the unconfined compressive strength of jet grouting coalcretes

This investigation studied the coalcrete, a new supporting material produced by jet grouting (JG) for supporting surrounding coal seams. For support design, the unconfined compressive strength (UCS) of the coalcrete is an essential parameter to evaluate the jet grouting effect in coal mines. In this study, an intelligent technique was proposed for predicting the UCS of the coalcrete by combining back propagation neural network (BPNN) and beetle antennae search (BAS). The architecture of BPNN was first tuned by BAS, and then, the optimized BPNN-BAS model was subsequently used for nonlinear relationship modeling. Several crucial influencing variables including water-cement ratio, coal-grout ratio, and curing time were selected as the inputs. By combining these variables, 360 coalcrete samples were prepared in a controlled laboratory environment and tested for establishing the dataset. The results demonstrate that BAS can tune the BPNN architecture more efficiently compared with random selection. Moreover, in comparison with multiple regression (MLR) and logistic regression (LR), and support vector machine (SVM), the optimized BPNN-BAS model is more reliable and accurate for predicting coalcrete strength. Sensitivity analysis (SA) was used to obtain the variable importance, and the results demonstrate that curing time affects the UCS of the coalcrete most strongly, followed by water-cement ratio and coal-grout ratio. The success of this study provides an accurate and brief approach to coalcrete strength prediction.     

考虑实际投影成像平面位置的扇束滤波反投影(FFBP)算法

扇束滤波反投影(Fan-beam Filtered Back Projection- FFBP)算法理论公式中,投影成像平面位于旋转中心;而实际CT扫描系统中,投影成像平面与旋转中心都存在一定距离.考虑到实际投影成像平面位置,本文推导了它的FFBP算法(即IFFBP-Improved Fan-beam Filtered Back Projection算法),比较了此两种情况下(即忽略成像平面与旋转中心距离)FFBP、IFFBP算法重建质量.计算机模拟和实验结果证明了IFFBP算法的正确性.     

滑坡勘察中滑带土强度指标确定方法的探讨

滑坡防治工程设计中确定滑带土强度是滑坡防治工程设计是否安全的基本出发点,其确定取决于滑坡发育、发展及稳定状况,以及不同部位的差异性。本文结合工程实例,除采用模拟滑坡变形状态反算确定滑带土强度的新方法外,采用不同方法对滑带土强度确定方法进行了的探讨。     

基于软土结构性对路基沉降的反分析研究

从软土的结构性出发,对软土较高的孔隙比、较强的透水性以及其压缩曲线的特点等进行分析总结,对公路路基沉降计算方法作进一步探讨。反分析方法在路基沉降方面的应用已经成为预测工后沉降的一种行之有效的途径。该方法是在空域和时域内对工程进行反馈分析的方法,是动态设计的最基本也是最重要的组成部分。它不仅包括在常规设计期间内进行的各种静态分析,而且包括随施工过程,根据工程现场实测的变形及其它可观测信息进行一系列反馈处理,它将设计与施工过程密切联系起来。为了较好地预测工后沉降,从沉降固结计算的角度对模型参数进行反分析,并反演设定参数,预测了沉降趋势,并与实际观测数据及理论计算数值进行比较,对实际工程做出评价,对工后沉降做出合理地预测。     

Vertical gradational variability of fines deposited in a gravel framework

Vertical gradational structures develop as sand infiltrates into static gravel beds. Understanding the vertical distribution of interstitial sand deposits will improve predictions of ecological suitability and hyporheic hydrodynamics. A series of flume experiments was performed to investigate fine infiltration processes. Four sand distributions were introduced into flows over gravel beds. After each experiment, bed cores were extracted and analysed in vertical layers to examine the gradational trends with depth. Vertical trends of fine content were highly sensitive to the relative grain‐size distributions of the gravel bed and the introduced sand. For experiments with d_15gravel/d_85sand ratios 15·4 and larger unimpeded static percolation was observed, where sand filled the voids relatively uniformly from the bottom of the gravel layer to the top. Experiments with ratios 10·6 and smaller bridged. Sand clogged a thin layer of gravel pores near the bed surface, precluding subsequent infiltration. Interstitial sand deposits fined with depth of penetration for all experiments which was the result of three distinct but overlapping processes. (i) Granular sorting: As particles fell through the substrate, smaller material preferentially passed through the voids deeper into the gravel. (ii) Bed‐load sorting: Size segregation occurs in the wake of the leading bed form as smaller particles saltate further and settle first. (iii) Hydraulic sorting: Smaller sand was transported preferentially as suspended load filling the deep voids of the furthest flume positions downstream. Finally, when the experiments that formed a bridge layer were replicated with higher bed shear stresses, less interstitial sand deposition was observed. Higher shear stresses transported coarse particles downstream more efficiently causing bridge layers to form earlier and allowing less time for suspended load to settle into the deeper substrate pores before the pathways were closed.     

Major and trace elements in plants and soils in Horton Plains National Park,Sri Lanka: an approach to explain forest die back

Forest die back has been observed from 1980s in the montane moist forest of Horton Plains in the Central Sri Lanka for which the aetiology appears to be uncertain. The concentration levels of Na, K, Ca, Mg, Fe, Mn, Cu, Ni, Zn and Pb in canopy leaves, bark and roots, which were collected from dying and healthy plants of three different endemic species, Calophyllum walkeri, Syzygium rotundifolium and Cinnamomum ovalifolium, from three different die back sites were studied. Soils underlying the plants were also analyzed for their extractable trace metals and total contents of major oxides. Analysis of dead and healthy plants does not show any remarkable differences in the concentrations of studied trace elements. The results show that there is a low status of pollution based on the concentrations of chemical elements of environmental concern. Extractable and total trace element analysis indicates a low content of Ca in soils due to high soil acidity that probably leads to Mg and Al toxicity to certain plants. Relatively high Al levels in the soil would affect the root system and hamper the uptake and transport of essential cations to the plant. It therefore seems that the forest declining appears to be a natural phenomenon, which occurs due to the imbalance of macro and micronutrients in the natural forest due to excessive weathering and the continuous leaching of essential elements.     

Dynamics of sedimentary environments in the accelerated siltation of a reservoir: the case of Alhama de Granada,southern Spain

An analysis has been made of sedimentary systems involved in the rapid silting of a reservoir constructed in 1974 in Alhama de Granada (S. Spain); in only 30 years the storage capacity of the reservoir has shrunk by 80% and its perimeter has decreased by 64%. A study of sediment lithofacies identified in a series of shallow trenches and of georadar facies identified in a series of almost 900 m lines of ground penetrating radar (GPR) images, together with a survey of surface geology, has identified 3 alluvial systems (2 transversal systems and a longitudinal system) whose deltas have filled in the reservoir. Thus, there are three phases in the evolution of the reservoir siltation: (1) an initial stage (1974–1977) typified by northward progradation of the longitudinal river delta of about 100 m year⁻¹ and an eastward progradation of the transversal system delta of about 20 m year⁻¹; (2) an intermediate stage (1977–1984) in which the longitudinal river delta progradation slowed to 25 m year⁻¹ and the axial drainage became obstructed due to the considerable eastward progradation of the transversal delta; and (3) a final phase (1984–present) in which there have been few changes in the areal distribution of the deltas apart from a southeastward expansion of the transversal delta. Generally, aggradational growth patterns (vertical accretion) have dominated in this final phase. The lithology of the source area, the slope and precipitation distribution has a significant effect not only on the sediment supply, but also indirectly on the creation of accommodation space and on the evolution of stratal growth patterns.     

基于BP神经网络的SAR影像水面舰船检测

分析了水面舰船的SAR成像能力和探测优势。在总结已有的舰船检测方法的基础之上,根据舰船目标在SAR图像中的成像特点,提出了利用BP神经网络实现SAR水面舰船目标识别实验。进一步利用形态学方法对检测结果进行修整,结合已知的SAR图像的像元大小,提取舰船的长度和宽度信息,同时利用原始图像的经纬度内插实现舰船目标中心的定位。结果表明,BP神经网络具有很强的自适应性,在低信噪比的情况下,也能够取得良好的效果。     

A paired metamorphic belt in a subduction‐to‐collision orogen: An example from the South Qilian–North Qaidam orogenic belt,NW China

The early Palaeozoic South Qilian–North Qaidam orogenic belt in northwestern China records a nearly complete history of early‐stage long‐lived oceanic subduction–accretion followed by late‐stage continental collision. Most previous studies have focused on low dT/dP metamorphism (HP–UHP) in this belt whereas the paired high dT/dP belt in the hinterland has received little attention. In this contribution, phase equilibrium modelling is combined with zircon petrochronology to determine the P–T–t evolution of granulites in the North Wulan gneiss complex in the high dT/dP hinterland of the South Qilian–North Qaidam orogen. Granulites record a clockwise P–T path with near‐peak temperatures of ~800–900°C at 5.5–7 kbar. Peak metamorphism was followed by high‐T decompression. Zircon petrochronology reveals protracted zircon growth from c. 474 to 446 Ma during the high‐T portion of the P–T path. High dT/dP metamorphism in the North Wulan gneiss complex was likely the result of heat transfer from the underlying hot asthenosphere and minor coeval magmatism in an arc–back‐arc system during slab retreat and roll‐back of the South Qilian oceanic plate. Broadly contemporaneous but slightly younger HP–UHP metamorphism in the foreland of the South Qilian–North Qaidam orogenic belt indicates that the region records an early Palaeozoic paired metamorphic belt. This early Palaeozoic paired metamorphic belt provides a detailed example of dual thermal regimes in a modern‐style orogenic system that can be applied to understanding the time‐scales and P–T conditions of high dT/dP metamorphism that accompany subduction in Phanerozoic and Precambrian orogenic belts.