Implementation of a coupled plastic damage distinct lattice spring model for dynamic crack propagation in geomaterials

This paper studies dynamic crack propagation by employing the distinct lattice spring model (DLSM) and 3‐dimensional (3D) printing technique. A damage‐plasticity model was developed and implemented in a 2D DLSM. Applicability of the damage‐plasticity DLSM was verified against analytical elastic solutions and experimental results for crack propagation. As a physical analogy, dynamic fracturing tests were conducted on 3D printed specimens using the split Hopkinson pressure bar. The dynamic stress intensity factors were recorded, and crack paths were captured by a high‐speed camera. A parametric study was conducted to find the influences of the parameters on cracking behaviors, including initial and peak fracture toughness, crack speed, and crack patterns. Finally, selection of parameters for the damage‐plasticity model was determined through the comparison of numerical predictions and the experimentally observed cracking features.     

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.     

A critical state model for sands dependent on stress and density

An elastoplastic model for sands is presented in this paper, which can describe stress–strain behaviour dependent on mean effective stress level and void ratio. The main features of the proposed model are: (a) a new state parameter, which is dependent on the initial void ratio and initial mean stress, is proposed and applied to the yield function in order to predict the plastic deformation for very loose sands; and (b) another new state parameter, which is used to determine the peak strength and describe the critical state behaviour of sands during shearing, is proposed in order to predict simply negative/positive dilatancy and the hardening/softening behaviour of medium or dense sands. In addition, the proposed model can also predict the stress–strain behaviour of sands under three-dimensional stress conditions by using a transformed stress tensor instead of ordinary stress tensor. Copyright © 2004 John Wiley & Sons, Ltd.     

江汉盆地钻孔测井资料确定地应力最大水平主压应力方向

利用钻孔测井资料并运用地层倾角测量信息分析法，给出了江汉盆地地应力最大水平主压应力方向为ＮＥ６０～６５°     

A neural network approach to ship track-keeping control

This paper presents an on-line trained neural net work controller for ship track-keeping problems. Following a brief review of the ship track-keeping control development since the 1980's, an analysis of various existing backpropagation-based neural controllers is provided. We then propose a single-input multioutput (SIMO) neural control strategy for situations where the exact mathematical dynamics of the ship are not available. The aim of this study is to build an autonomous neural controller which uses rudder to regulate both the tracking error and heading error. During the whole control process, the proposed SIMO neural controller adapts itself on-line from a direct evaluation of the control accuracy, and hence the need for a “teacher” or an off-line training process can be removed. With a relatively modest amount of quantitative knowledge of the ship behavior, the design philosophy enables real time control of a nonlinear ship model under random wind disturbances and measurement noise. Three different track-keeping tasks have been simulated to demonstrate the effectiveness of the training method and the robust performance of the proposed neural control strategy     

Silicon limitation on primary production and its destiny in Jiaozhou Bay, China——Ⅳ：Study on cross-bay transect from estuary to ocean

The authors analyzed the data collected in the Ecological Station Jiaozhou Bay from May 1991 to November 1994, including 12 seasonal investigations, to determine the characteristics, dynamic cycles and variation trends of the silicate in the bay. The results indicated that the rivers around Jiaozhou Bay provided abundant supply of silicate to the bay. The silicate concentration there depended on river flow variation. The horizontal variation of silicate concentration on the transect showed that the silicate concentration decreased with distance from shorelines. The vertical variation of it showed that silicate sank and deposited on the sea bottom by phytoplankton uptake and death, and zooplankton excretion. In this way, silicon would endlessly be transferred from terrestrial sources to the sea bottom. The silicon took up by phytoplankton and by other biogeochemical processes led to insufficient silicon supply for phytoplankton growth. In this paper, a 2D dynamic model of river flow versus silicate concentration was established by which silicate concentrations of 0.028–0.062 μmol/L in seawater was yielded by inputting certain seasonal unit river flows (m³/s), or in other words, the silicate supply rate; and when the unit river flow was set to zero, meaning no river input, the silicate concentrations were between 0.05–0.69 μmol/L in the bay. In terms of the silicate supply rate, Jiaozhou Bay was divided into three parts. The division shows a given river flow could generate several different silicon levels in corresponding regions, so as to the silicon-limitation levels to the phytoplankton in these regions. Another dynamic model of river flow versus primary production was set up by which the phytoplankton primary production of 5.21–15.55 (mgC/m²·d)/(m³/s) were obtained in our case at unit river flow values via silicate concentration or primary production conversion rate. Similarly, the values of primary production of 121.98–195.33 (mgC/m²·d) were achieved at zero unit river flow condition. A primary production conversion rate reflects the sensitivity to silicon depletion so as to different phytoplankton primary production and silicon requirements by different phytoplankton assemblages in different marine areas. In addition, the authors differentiated two equations (Eqs. 1 and 2) in the models to obtain the river flow variation that determines the silicate concentration variation, and in turn, the variation of primary production. These results proved further that nutrient silicon is a limiting factor for phytoplankton growth. This study was funded by NSFC (No. 40036010), and the Director's Fund of the Beihai Sea Monitoring Center, the State Oceanic Administration.     

运输系统的区域效应研究

运输系统改进—运距缩短—产业布局调整这一空间过程对不同的区域可能具有完全不同的意义。本文通过对一个两区域—两部门经济模型的研究得出结论:当较落后的资源产区与经济中心之间的距离由于运输系统的改进而缩短时,资源产区的经济结构向单一化转变,初级产品的生产和输出在经济建设中逐渐占主导地位,加工工业逐渐萎缩,地方经济发展受到阻碍,而且这种变化是在距离的某一特定值处突然出现的,带有跃变的性质。这一研究结果表明,对区域运输系统的任何改进措施都应该慎而行之,以免造成与本来目标相悖的区域效应。     

COORDINATING DEVELOPMENT OF AGRICULTURAL RESOURCES AND ENVIRONMENT OF THE TROPIC REGION IN YUNNAN PROVINCE

（姚建衢）（杨焕宗）ＣＯＯＲＤＩＮＡＴＩＮＧＤＥＶＥＬＯＰＭＥＮＴＯＦＡＧＲＩＣＵＬＴＵＲＡＬＲＥＳＯＵＲＣＥＳＡＮＤＥＮＶＩＲＯＮＭＥＮＴＯＦＴＨＥＴＲＯＰＩＣＲＥＧＩＯＮＩＮＹＵＮＮＡＮＰＲＯＶＩＮＣＥ￥ＹａｏＪｉａｎｑｕ（Ｉｎｓｔｉｔｕｔｅｏｆ...     

THE CONSTRUCTION AND ITS DEVELOPMENT OFTHE OVERSEAS TRANSPORT SYSTEM IN NORTHEAST CHINA

ＴＨＥＣＯＮＳＴＲＵＣＴＩＯＮＡＮＤＩＴＳＤＥＶＥＬＯＰＭＥＮＴＯＦＴＨＥＯＶＥＲＳＥＡＳＴＲＡＮＳＰＯＲＴＳＹＳＴＥＭＩＮＮＯＲＴＨＥＡＳＴＣＨＩＮＡＧａｏＳｈａｌｉ（高莎丽）（ＤｅｐａｒｔｍｅｎｔｏｆＧｅｏｇｒａｐｈｙ，ＮｏｒｔｈｅａｓｔＮｏｒｍ...     

Development and Extension of Seawater Desalination by Reverse Osmosis

Seawater desalination has been people‘s fond dream since ancient times,the dream is now becoming a reality.This paper presents a brief development history of reverse osmosis.Much attention was paid to innovative development in mebranes,modules.equipments and applied technology,including asymmetric and composite membranes,spiral-wound element and hollow fiber module,energy recovery equipments and different technological processes.The extension of reverse osmosis,such as desalination,pre-concentration,integrated processes and nanofiltration,is also briefly mentioned.