Statistical prediction of fracture parameters of concrete and implications for choice of testing standard

This article shows how the fracture energy of concrete, as well as other fracture parameters such as the effective length of the fracture process zone, critical crack-tip opening displacement and the fracture toughness, can be approximately predicted from the standard compression strength, maximum aggregate size, water-cement ratio, and aggregate type (river or crushed). A database, consisting of 238 test data, is extracted from the literature and tabulated, and approximate mean prediction formulae calibrated by this very large data set are developed. A distinction is made between (a) the fracture energy, G_f, corresponding to the area under the initial tangent of the softening stress-separation curve of cohesive crack model, which governs the maximum loads of structures and is obtained by the size effect method (SEM) or related methods (Jenq-Shah two-parameter method and Karihaloo's effective crack model, ECM) and (b) the fracture energy, G_F, corresponding to the area under the complete stress-separation curve, which governs large postpeak deflections of structures and is obtained by the work-of-fracture method (WFM) proposed for concrete by Hillerborg. The coefficients of variation of the errors in the prediction formulae compared to the test data are calculated; they are 17.8% for G_f and 29.9% for G_F, the latter being 1.67 times higher than the former. Although the errors of the prediction formulae taking into account the differences among different concretes doubtless contribute significantly to the high values of these coefficients of variation, there is no reason for a bias of the statistics in favor of G_f or G_F. Thus, the statistics indicate that the fracture energy based on the measurements in the maximum load region is much less uncertain than that based on the measurement of the tail of the postpeak load-deflection curve. While both G_f and G_F are needed for accurate structural analysis, it follows that if the testing standard should measure, for the sake of simplicity, only one of these two fracture energies, then G_f is preferable.     

基于GM（1，1）和线性回归模型在印刷包衬压缩变形中的数据预测研究

运用线性回归对预测数据进行分析,剔除异常数据,用GM（1,1）模型进行预测,有效降低了数据相对误差,提高了预测数据的精度。选用印刷包衬压缩变形的压缩变形量值,用线性回归进行数据分析并剔除异常数据后用GM（1,1）进行预测,使得预测数据具有更高的准确性和适应性。实验及仿真结果表明,经过前期数据分析整理后的灰色预测模型,其预测期望值远优于单纯的回归模型和GM（1,1）模型。     

Groundwater as a source and pathway for road salt contamination of surface water in the Lake Ontario Basin: A review

In Ontario, there is limited comprehensive research regarding the contribution of chloride in groundwater to surface water systems. The delivery of chloride via groundwater can contribute to the degradation of the Great Lakes and their tributaries. Thus, this review intends to fill or identify knowledge gaps regarding assessing groundwater as a potential source of road salt, the single largest use of salt in urban cold region environments, contamination to surface water by synthesizing existing groundwater chloride research in the Lake Ontario Basin. Knowledge regarding source characterization, properties, pathways, and impacts of chloride in the environment is essential to evaluate the contribution of chloride via groundwater. Past groundwater chloride research in the basin is primarily concentrated in highly urbanized areas and has identified localized trends of increasing groundwater chloride concentrations in these regions; however, few investigations have been conducted in varying land uses (e.g., rural or less urbanized watersheds) or at sufficient temporal and/or spatial scales. Significant chloride accumulation is occurring in watersheds and aquifers within the basin. Concentrations are expected to increase until equilibrium is obtained, thus resulting in sustained yearlong elevated concentrations in tributaries. Recently, chloride loading to Lake Ontario has increased significantly, with groundwater inputs having the potential to support long-term increases in chloride concentrations in the lake. However, few studies have evaluated the explicit contribution via groundwater to Lake Ontario, and therefore a knowledge gap continues to exist. We provide a synthesis of additional research priorities to better understand the magnitude of groundwater chloride issues in the basin.     

Prediction model of compressive strength development of fly-ash concrete

Based on experimental results concerning the compressive strength development of concrete containing fly ash, the authors derived an estimation equation for compressive strength development. The equation can express coefficient , which indicates the activity of fly ash as a binder, in the form of a function of age, fly-ash content, and Blaine specific surface area of fly ash.

This equation is capable of explaining the increases in the early strength due to fly ash in place of part of fine aggregate, the decreases in the early strength due to fly ash in place of part of cement, the increases in the long-term strength due to pozzolanic reaction, the relationship between the fly-ash replacement ratio and the ratio of strength increase/decrease, and the effect of fly ash's Blaine specific surface area on the strength.     

Effect of changing groundwater levels caused by land-use changes on greenhouse gas fluxes from tropical peat lands

Monthly measurements of carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) fluxes in peat soils were carried out and compared with groundwater level over a year at four sites (drained forest, upland cassava,upland and lowland paddy fields) located in Jambi province, Indonesia. Fluxes from swamp forest soils were also measured once per year as the native state of this investigated area. Land-use change from drained forest to lowland paddy field significantly decreased the CO₂ (from 266 to 30 mg C m^–2 h^–1) and N₂O fluxes (from 25.4 to 3.8 g N m^–2 h^–1), but increased the CH₄ flux (from 0.1 to 4.2 mg C m^–2 h^–1) in the soils. Change from drained forest to cassava field significantly increased N₂O flux (from 25.4 to 62.2 g N m^–2 h^–1), but had no significant influence on CO₂ (from 266 to 200 mg C m^–2 h^–1) and CH₄ fluxes (from 0.1 to 0.3 mg C m^–2 h^–1) in the soils. Averaged CO₂ fluxes in the swamp forests (94 mg C m^–2 h^–1) were estimated to be one-third of that in the drained forest. Groundwater levels of drained forest and upland crop fields had been lowered by drainage ditches while swamp forest and lowland paddy field were flooded, although groundwater levels were also affected by precipitation. Groundwater levels were negatively related to CO₂ flux but positively related to CH₄ flux at all investigation sites. The peak of the N₂O flux was observed at –20 cm of groundwater level. Lowering the groundwater level by 10 cm from the soil surface resulted in a 50 increase in CO₂ emission (from 109.1 to 162.4 mg C m^–2 h^–1) and a 25% decrease in CH₄ emission (from 0.440 to 0.325 mg C m^–2 h^–1) in this study. These results suggest that lowering of groundwater level by the drainage ditches in the peat lands contributes to global warming and devastation of fields. Swamp forest was probably the best land-use management in peat lands to suppress the carbon loss and greenhouse gas emission. Lowland paddy field was a better agricultural system in the peat lands in terms of C sequestration and greenhouse gas emission. Carbon loss from lowland paddy field was one-eighth of that of the other upland crop systems, although the Global Warming Potential was almost the same level as that of the other upland crop systems because of CH₄ emission through rice plants.     

网络信息安全风险态势预测分析方法探讨

本文主要研究了在复杂网络环境下的信息安全风险预测问题。它提出了一种较为实用并且具有一定广泛意义的网络风险态势预测方法;通过实验表明,本方法可以满足因网络结构复杂、资产价值不一而造成的风险态势评估误报问题,有实际应用意义。     

Movement characteristics of Karst water in a deep mining area

In order to study the movement characteristics of groundwater in a deep mining area and solve the dispute of the distri-bution rule of hydro-chemical zoning which is contradicted by lixiviation water zoning in a horizontal direction, we directed our attention to the source of deep groundwater, its seepage and hydro-chemical characteristics in a typical mining area. We used a neotectonic water-control theory, chemical and isotope methods, as well as a method for analyzing dynamic groundwater conditions. The results indicate that 1) Karst water in the deep and medium parts of this mining area is recharged by vertical leakage through neotectonic fractures rather than seepage along strata from subcrop parts or surrounding flows; 2) from surface to deep leakage paths, the variation in the types of chemical groundwater agrees with the normal lixiviation water distribution rule and the age of mixed groundwater increases; 3) the water-rich zones along neotectonic fractures correspond with water-diluted zones in a hori-zontal direction; 4) the leakage coefficient and water capacity of aquifers increases during the flow process of Kant water along the antidip direction (from west to east) and 5) Karst water in shallow mining areas forms a strong runoff belt along strikes and quickly dilutes the water from deep and medium mining areas. Overall, chemical and dynamic water characteristics actually agree with in terms of the entire consideration for differences in vertical leakage and abnormalities in the zone of water chemical distribution, along a horizontal runoff direction.     

基于并行预测控制的Turbo码译码结构

提出一种基于并行预测控制的Turbo码译码结构. 通过建立预测控制模块(PCA)来预测分量译码器第n+1次的译码外部信息值. 相比于传统的并行译码方案,基于PCA模块的PPC-Turbo结构可以降低译码算法的复杂度,并减少译码时延. 通过对单次外部信息值预测（6～9次）及复次外部信息值预测（6+8、7+9次）,对比了外部信息预测的变化趋势及不同帧长（1?024、512、256、128、64帧）情况下的译码时延,验证了译码时延的减少. 在帧长为1?024、信噪比为0～2?dB时,对译码器2第6～8次的外部信息进行了单次预测,比较了PPC-Turbo与Turbo的误比特率(BER)性能,结果表明,两者的BER非常接近,预测控制模块可以代替分量译码器的一次译码迭代.     

优化SVR的加权马尔可夫链用电量预测

研究电力系统中用电量的准确预测问题.由于影响用电量的因素众多,并且用电量数据与相关因素之间呈现高度的非线性关系,传统的预测方法很难捕捉用电量的变化趋势,预测精度较低.为了提高预测的精度,提出了一种马尔可夫链优化的SVR模型.上述模型根据支持向量回归机原理,以网络搜索交叉验证的思想优化模型参数,通过加权马尔可夫链原理优化预测结果,将原来的数值预测转化为概率区间上的预测.同时,在利用加权马尔可夫链的预测信息之后,也提高了预测的精度.最后,将改进模型应用于江苏省全社会用电量的预测分析,实验结果表明优化的支持向量模型优于其它对比模型,有较高的泛化能力和预测精度.     

Fitts＇定律实验的设计与实现

首先,介绍了Fitts＇定律,然后,设计了验证Fitts＇定律的实验,最后,使用Matlab7.0.1对数据进行了统计和分析.实验结果有效地验证了Fitts＇定律,并且Fitts＇ Law（错误率为4％）得到的预测模型精度高于通过“effective width”Fitts＇ Law得到的预测模型.