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.     

An approximate method for evaluating the shear band thickness in saturated soils

A formula for the thickness of a shear band formed in saturated soils under a simple shear or a combined stress state has been proposed. It is shown that the shear band thickness is dependent on the pore pressure properties of the material and the dilatancy rate, but is independent of the details of the combined stress state. This is in accordance with some separate experimental observations. Copyright © 2004 John Wiley & Sons, Ltd.     

The comparison between allozyme and RAPD makers for the population genetic structure analysis of scallop Chlamys farreri

1INTRODUCTION Since the first use in human genetic research in1966,allozyme has become the most popular genetic marker for population genetics studies for almost all groups of animals and plants(Lewontin and Hubby,1966;Murphy et al.,1996).In the past seve…     

Neutrino mass,luminosity variation,and spectrum of SN1987A

In this paper, the neutrino mass has been determined from SN1987a observation in a manner that the simultaneity of neutrino emission is not regarded as the starting point, but is itself defined through the analysis by Monte-Carlo simulation. The result is that the neutrino mass lies in 3–4 eV, possiblym _v 3.6 eV. Neutrino luminosity variation and neutrino spectrum are also obtained. Comparison with theories gives further support to the mass determination, and also predicts the mass of progenitor star of SN1987a to be in the range of 12–25M .The project supported by the National Natural Science Foundation of China.     

Possible chemical structures and biological precursors of different vitrinites in coal measure in Northwest China

Chemical structure of Jurassic vitrinites isolated from the coals in basins in NW China have been checked using solid state ¹³C NMR and flash pyrolysis-GC/MS. Study shows some Jurassic collodetrinites are rich in aliphatic products in pyrolysates, consisting with the high amount of methylene carbon in ¹³C NMR spectra. In contrast, pyrolysates of Jurassic collotelinites are rich in phenols and alkylbenzenes. Also one Pennsylvanian and one Permian vitrinite selected from the Ordos basin, NW China have been checked for comparison. The proportion of aliphatics is low in pyrolysates, and aliphatic carbon peak in ¹³C NMR spectrum of Permian vitrinite is mostly composed of gas-prone carbons compared with collodetrinites in those Jurassic basins. But both pyrolysis and ¹³C NMR data shows the Pennsylvanian vitrinite is not only gas-prone but also oil-prone. Relatively high proportion of long chain aliphatic structure of some Jurassic vitrinite in Junggar, Turpan-Hami basins may be due to the contribution of liptodetrinites, which may be included during the formation of vitrinites. And it seems that suberinite is the most possible precursor of long chain aliphatics in the structure of Jurassic collodetrinite.     

Triassic Nb-enriched basalts, magnesian andesites, and adakites of the Qiangtang terrane (Central Tibet): evidence for metasomatism by slab-derived melts in the mantle wedge

New chronological, geochemical, and isotopic data are reported for Triassic (219–236 Ma) adakite-magnesian andesite-Nb-enriched basaltic rock associations from the Tuotuohe area, central Qiangtang terrane. The adakites and magnesian andesites are characterized by high Sr/Y (25–45), La/Yb (14–42) and Na₂O/K₂O (12–49) ratios, high Al₂O₃ (15.34–18.28 wt%) and moderate to high Sr concentrations (220–498 ppm) and ε_ND (t) (+0.86 to +1.21) values. Low enrichments of Th, Rb relative to Nb, and subequal normalized Nb and La contents, and enrichments of light rare earth elements combine to distinguish a group of Nb-enriched basaltic rocks (NEBs). They have positive ε_ND (t) (+2.57 to +5.16) values. Positive correlations between Th, La and Nb and an absence of negative Nb anomalies on mantle normalized plots indicate the NEBs are products of a mantle source metasomatized by a slab melt rather than by hydrous fluids. A continuous compositional variation between adakites and magnesian andesites confirms slab melt interaction with mantle peridotite. The spatial association of the NEBs with adakites and magnesian andesites define an “adakitic metasomatic volcanic series” recognized in many demonstrably subduction-related environments (e.g., Mindanao arc, Philippines; Kamchatka arc, Russia; and southern Baja California arc, Mexico). The age of the Touhuohe suite, and its correlation with Triassic NEB to the north indicates that volcanism derived from subduction-modified mantle was abundant prior to 220 Ma in the central Qiangtang terrane.     

山东近海牙鲆(Paralichthys olivaceus)自然和养殖群体10个微卫星基因座位的遗传多态性分析

采用微卫星遗传标记技术对山东近海牙鲆自然群体和养殖群体的遗传多样性进行了研究。实验所用牙鲆于2003年5月分别采自山东近海和青岛胶南养鱼场，各20尾，取全血或肌肉组织，以酚-仿抽提方法提取基因组DNA，利用筛选获得的10对微卫星引物进行PCR扩增，反应产物经8％非变性聚丙烯酰胺凝胶电泳分离、EB显色，用ImageMasterl D Elite(Version 3．01)软件分析电泳结果，并计算了相应的遗传学参数。结果表明，在自然和养殖群体中，10个基因座位的等位基因平均数(α)分别为6．7和6．1，每个基因座位有效等位基因数(αe)分别为1．8—6．8和2．5—6．7，群体平均杂合度(H)分别为0．8120和0．7310；两个群体间的遗传相似性系数、遗传距离和基因分化系数为0．8558、0．1557和0．0558；自然群体内每个座位上的多态信息含量(PIC)为0．59—0．84、个体识别率(DP)为0．54—0．86、非父排除率(PPE)为0．41—0．72，其累积个体识别率和非父排除率均达到0．9999，表明所选座位属中高识别力的遗传标记，可以将它们应用于今后牙鲆雌核发育群体的遗传变异分析以及进一步的遗传育种的研究中。     

中太平洋铁锰结壳铅同位素研究

已有研究表明大洋中溶解的铅(Pb)来源于陆源物质，但是，对Pb进入大洋的途径争议很大。为此分析了取自中太平洋两块铁锰结壳样品的Pb同位素组成，获得了整个新生代的中太平洋Pb同位素演化历史。结果表明这两块结壳的Pb同位素随时间的演化曲线与中北太平洋沉积物岩心LL44-GPC3中风成碎屑的Pb同位素演化曲线相似。证实该区深水中的天然溶解铅主要来自风成粉尘，并且50Ma之前中太平洋中溶解Pb同位素组成主要取决于源自美洲的风成粉尘的输入，40Ma之后主要取决于源自亚洲的风成粉尘的输入。     

海洋沉积样品~(14)C测年差异来源及其结果解释

~(14)C测年已为海洋研究工作广泛应用,但由于时有不合理取样或在运用数据时没有充分考虑各种海洋环境和动力因素,因而产生无法使用数据作合理解释的现象。本文试从海洋样品本身和海洋各种营力作用分析各种数据差异的来源,认为海洋环境特别是海岸带环境的复杂性是造成海洋样品~(14)C测年数据差异的主要原因,它可能影响样品的代表性或使数据解释时得出错误结论.并指出在运用年代结果时一定要充分考虑地质地理和各种营力作用因素。