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.     

Zircon U–Pb age, trace element and Hf isotope composition of Kongling terrane in the Yangtze Craton: refining the timing of Palaeoproterozoic high-grade metamorphism

U–Pb age, trace element and Hf isotope compositions of zircon were analysed for a metasedimentary rock and two amphibolites from the Kongling terrane in the northern part of the Yangtze Craton. The zircon shows distinct morphological and chemical characteristics. Most zircon in an amphibolite shows oscillatory zoning, high Th/U and ¹⁷⁶Lu/¹⁷⁷Hf ratios, high formation temperature, high trace element contents, clear negative Eu anomaly, as well as HREE-enriched patterns, suggesting that it is igneous. The zircon yields a weighted mean ²⁰⁷Pb/²⁰⁶Pb age of 2857 ± 8 Ma, representing the age of the magmatic protolith. The zircon in the other two samples is metamorphic. It has low Th/U ratios, low trace element concentrations, variable HREE contents (33.8 ≥ Lu_N≥2213; 14.7 ≤ Lu_N/Sm_N ≤ 354) and ¹⁷⁶Lu/¹⁷⁷Hf ratios (0.000030–0.001168). The data indicate that the zircon formed in the presence of garnet and under upper amphibolite facies conditions. The metamorphic zircon yields a weighted mean ²⁰⁷Pb/²⁰⁶Pb age of 2010 ± 13 Ma. These results combined with previously obtained Palaeoproterozoic metamorphic ages suggest a c. 2.0 Ga Palaeoproterozoic collisional event in the Yangtze Craton, which may result from the assembly of the supercontinent Columbia. The zircon in two samples yields weighted mean two-stage Hf model ( T _DM2) ages of 3217 ± 110 and 2943 ± 50 Ma, respectively, indicating that their protoliths were mainly derived from Archean crust.     

ANALYSIS OF DRIVING FORCES ON THE CHANGE OF HISTORICAL FARMLAND USE IN SHANDONG PROVINCE DURING THE QING DYNASTY (1644-1911)

1INTRODUCTIONTheIGBP-IHDP(InternationalGeosphere-BiosphereProgramme,andInternationalHumanDimensionPro-gramme)jointproject—LUCC(landuse/coverchange)isaninterdisciplinaryprogramdesignedtoimprovetheunderstandingofthedynamicsofland-useandland-coverchangeasinputstoandconsequencesofglobalenvironmentalchangeandsustainabledevelopment(CHARLOTTE,2002).Inparticularthedifferentbio-geochemicalmodeling(e.g.theglobalcarboncycle)ac-tivitiesandcomparativestudies,suchasthoseconduct-edbyIGBP-G…     

CPLD技术及其在现代时统中的应用

对CPLD(复杂可编程逻辑器件)技术的基本特征和发展趋势作了简要介绍,揭示了该技术在现代数字系统中的重要地位及作用.利用CPLD对时统设备IRIG-B码产生器进行集成,其实验结果表明,集成了的B码产生器不但简单、可靠,而且便于调试,克服了以往硬件电路复杂的缺点.     

概率赋范空间的S-凸和K-凸

文献[1][2]认为M－PN空间是局部凸的。通过定理说明这个结论对t-模T（a,b)≥min(a,b)时成立。又通过反例表明，当t-模型T（a,b)=max(a b-1,0）时无论邻域Nθ（ε，λ）概率有界还是概率半有界结论均不成立。还讨论了Takahashi凸性并对S－凸和K－凸作了比较。     

A Simulating Experiment in the Process of Soil Erosion on Bare Land in Mt. Tanakami

In order to understand the process of surface erosion and acquire basic data of conditions on hillslope without vege tation, a sprinkling experiment is conducted on a bare slope in Mt. Tanakami in the central part of Japan. Based on the mea surements of runoff, mean soil erosion depth, and sediment yield, etc. , the results suggest the following characteristics in the process of surface erosion in the experimental area. (1) The occurrence of sediment discharge is interrupted; (2) Surface runoff is a saturated overland flow; (3) The mean soil erosion depth is thick compared with other areas in Mt. Tanakami;(4) Sediment discharge process is detachment- limited.     

关于网络用户经济效益评测模型的研究

着重讨论了网络用户经济效益的内涵以及用户的投入量和产出量，并提出了评价网络用户经济效益的指标体系，包括成本降低率，成本利润增长率、产品开发时间约率、市场占有增长率等系列指标。     

Optical Flash of GRB 990123: Constraints on the Physical Parameters of the Reverse Shock

The optical flash accompanying GRB 990123 is believed to be powered by the reverse shock of a thin shell. With the best-fit physical parameters for GRB 990123 and the assumption that the parameters in the optical flash are the same as in the afterglow, we show that: 1) the shell is thick rather than thin, and we have provided the light curve for the thick shell case which coincides with the observation; 2) the theoretical peak flux of the optical flash accounts for only 3×10~-4 of the observed. In order to remove this discrepancy, the physical parameters, the electron energy and magnetic ratios, εe and εB, should be 0.61 and 0.39, which are very different from their values for the late afterglow.     

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.