白云岩单轴压缩试验声发射特性研究

在单轴压缩条件下,进行白云岩破坏全过程的声发射试验研究,得到应力、声发射特性与时间的关系,并研究了岩体的Kaiser效应。结果表明:（1）岩石单轴压缩破坏过程中并不是所有试验岩样有具有典型的声发射特征阶段,部分岩样AE曲线中可以找到Kaiser效应特征点,但是多数岩样的Kaiser效应特征点不明显;（2）岩样的AE现象在应力达到峰值前会经过一个平静期,而在岩石发生破坏直至彻底破坏阶段,AE现象明显增加,这个先平静后剧增的过程可以作为预报岩爆发生的一种警示信号;（3）大多数岩样都在AE能量达到最大时发生彻底破坏。     

桥式起重机安全评估指标体系研究和系统设计

在对桥式起重机的设计、结构组成和常见事故故障资料进行调查研究的基础上,分析了桥式起重机在工程应用中遇到的不安全因素,建立了较完善的安全评估指标体系。设计了一种基于模糊神经网络的桥式起重机安全评估系统并对系统的软件功能设计进行了初步探讨。建立了模糊神经网络评估数学模型,利用MATLAB工具对模型进行了仿真验证,结果表明此模型是可行的。通过研究,为进一步针对桥式起重机展开定性、定量评估及安全管理与决策提供了有益参考     

惠州西湖浮游植物磷脂脂肪酸特征研究

对富营养化水体常见浮游植物进行了分离和培养,测定了其磷脂脂肪酸（PLFA）。同时,检测了惠州西湖浮游植物的磷脂脂肪酸;结合惠州西湖浮游植物群落组成数据,分析了浮游植物磷脂脂肪酸特征及其与浮游植物群落结构的关系。结果表明：结合PLFA与细胞丰度和生物量的分析,α-亚麻酸（18：3ω3）的质量浓度与蓝藻（除湖丝藻外）呈正相关;二十碳四烯酸ARA（20：4ω6）和二十二碳六烯酸DHA（22：6ω3）的质量浓度与硅藻呈正相关;二十碳五烯酸EPA（20：5ω3）和16：3ω3的质量浓度与绿藻呈正相关等,其中16：3ω3为绿藻门独有的脂肪酸。这些均与室内实验得到的结果相符合。本研究表明,磷脂脂肪酸可以作为生物标志物来分析浮游植物组成,它将是一种可行的研究浮游植物群落结构的新方法。     

基于蚁群神经网络的煤矿瓦斯预测模型

为了提高煤矿瓦斯涌出量的预测精度和预测速度,用蚁群算法和神经网络相结合的方法进行预测模型设计。选择瓦斯涌出的重要影响因素,建立其神经网络的预测模型。以网络的均方误差为目标函数,通过蚁群算法的迭代运算,实现BP网络的权值优化,并用优化好的BP网络进行瓦斯涌出预测。仿真结果表明,该方法具有较高的拟合预测精度。     

基于BP神经网络的煤与瓦斯突出预测系统开发

煤与瓦斯突出影响因素多,难以为其建立合适的多指标非线性预测模型,为提高突出预测的准确性和增强预测预报方法的实用性,采用改进的BP算法建立煤与瓦斯突出预测数学模型。通过研究不同算法的突出预测效果,对已建模型的泛化能力进行检验,利用Matlab GUI和神经网络工具箱设计开发煤与瓦斯突出预测系统,通过向系统输入已知的突出样本数据,经过学习、训练,实现对未知参数的预测。仿真结果表明:网络在训练300次后,误差训练曲线的均方差(MSE)可以达到10-15,实际预测误差也小于0.1,系统得到的5组数据预测结果与实际情况相符。     

基于CREAM方法的人因失效概率预测模型研究

认知可靠性与差错分析方法(CREAM)是第二代人因可靠性分析方法中的代表方法之一,通过对任务环境进行分析从而直接确定人为差错发生概率。本文分析了该方法及其后续研究在人因可靠度评估时存在的主要问题,并以CREAM方法为基础建立新的人因失效概率预测模型。模型首先要求有针对性的对具体任务环境确定通用性能影响因子(CPC)权重,然后通过对CPC进行打分对任务环境进行量化,通过加权求和的方式分别计算出CPC的改进总分值G和降低总分值J,最后运用新建的预测模型计算出人因失效概率。新模型提出了三点改进:第一将任务环境设定为连续的空间;第二提出了不同的工作环境(任务环境)应该有其对应的CPC因子权重;第三考虑正影响CPC因子和负影响CPC因子的双重影响,建立双变量预测模型,预测结果更加合理。     

淮安市砂土地震液化势的综合评估

建立了BP神经网络模型LM算法的砂土地震液化判别方法,采用LVQ模式分类网络对数据进行分类,选取唐山地震时76个场地、320组现场液化勘察资料为研究对象,训练和检验网络模型的数据各160组,结果表明,该方法的砂土液化预测准确度为96.8%。根据淮安市典型场地土的钻孔资料,采用《建筑抗震设计规范法》液化判别法(规范法)、美国国家地震研究中心建议的液化判别简化方法(NCEER法)和谢君斐-陈国兴液化判别方法(谢-陈法)等3种液化判别方法及本文提出的BP神经网络模型液化判别方法对22个钻孔、120标贯点进行了液化判别,结果表明:14种地震液化判别方法的计算结果基本一致;2NCEER法比谢-陈法的计算结果要保守;3谢-陈法与规范法的计算结果很吻合,预测正确率相差不大;4规范法相对BP神经网络模型法的计算结果要保守;5BP神经网络模型法比其他3种方法的预测结果更符合实际的液化规律。最后,综合4种方法的液化判别结果给出了该地区地震液化势的评估结果,并给出了部分典型地质剖面土层地震液化势分布图。     

Comparing network analysis methodologies for consumer–resource relations at species and ecosystems scales

This research compares two existing methodologies, mixed trophic impact analysis and utility analysis, which use network analysis to evaluate the direct, pair-wise, and indirect, holistic, ecological relations between ecosystem compartments. The two approaches have many similarities, but differ in some key assumptions which affect both the final results and interpretations. Here, we briefly introduce both methodologies through a series of two simple examples; a 3-compartment competition model and a 3-compartment food chain model, and then apply the methodologies to a 15-compartment ecosystem model of the Chesapeake Bay. This example demonstrates how implementing the various conceptual and methodological assumptions lead to differing results. Notably, the overall number of positive relations is greatly affected by the treatment of the self-interactions and the handling of detritus compartments lead to a distinction between ecological or trophic relations. We recommend slight changes to both methodologies, not necessarily in order to bring them completely together, but because each has some points which are stronger and better defensible.     

Comparative network analysis toward characterization of systemic organization for human–environmental sustainability

A preliminary study in comparative ecological network analysis was conducted to identify key assumptions and methodological challenges, test initial hypotheses and explore systemic and network structural characteristics for environmentally sustainable ecosystems. A nitrogen network for the U.S. beef supply chain – a small sub-network of the industrial food system analyzed as a pilot study – was constructed and compared to four non-human carbon and nitrogen trophic networks for the Chesapeake Bay and the Florida Everglades. These non-human food webs served as sustainable reference systems. Contrary to the main original hypothesis, the “window of vitality” and the number of network roles did not clearly differentiate between a human sub-network and the more complete non-human networks. The effective trophic level of humans (a partial estimate of trophic level based on the single food source of beef) was much higher (8.1) than any non-human species (maximum of 4.88). Network connectance, entropy, total dependency coefficients, trophic efficiencies and the ascendency to capacity ratio also indicated differences that serve as hypotheses for future tests on more comprehensive human food webs. The study elucidated important issues related to (1) the steady state assumption, which is more problematic for industrial human systems, (2) the absence or dearth of data on contributions of dead humans and human wastes to feed other species in an integrated food web, (3) the ambiguity of defining some industrial compartments as living versus non-living, and (4) challenges with constructing compartments and trophic transfers in industrial versus non-human food webs. The two main novel results are (1) the progress made toward adapting ecological network analysis (ENA) methodology for analysis of human food networks in industrial cultures and (2) characterizing the critical aspects of comparative ENA for understanding potential causes of the problems, and providing avenues for solutions, for environmental sustainability. Based on this work, construction and comparative network analysis of a more comprehensive industrial human food network seems warranted and likely to provide valuable insights for modifying structures of industrial food networks to be more like natural networks and more sustainable.     

Young-boy networks without kin clusters in a lek-mating manakin

I use 10 years of data from a long-term study of lek-mating long-tailed manakins to relate the social network among males to their spatial and genetic structure. Previously, I showed that the network connectivity of young males predicts their future success. Here, I ask whether kinship might shape the organization of this “young-boy network”. Not surprisingly, males that were more socially distant (linked by longer network paths) were affiliated with perch zones (lek arenas) that were further apart. Relatedness (r) among males within the network decreased as social distance increased, as might be expected under kin selection. Nevertheless, any role for indirect inclusive fitness benefits is refuted by the slightly negative mean relatedness among males at all social distances within the network (overall mean r = −0.06). That is, relatedness ranged from slightly negative (−0.04) to more negative (−0.2). In contrast, relatedness in dyads for which at least one of the males was outside the social network (involving at least one blood-sampled male not documented to have interacted with other banded males) was slightly above the random expectation (mean r = 0.05). The slight variations around r = 0 among males of different categories likely reflect dispersal dynamics, rather than any influence of kinship on social organization. Relatedness did not covary with the age difference between males. These results, together with previous results for lack of relatedness between alpha and beta male partners, refute any role for kin selection in the evolution of cooperative display in this lek-mating system. This contribution is part of the special issue “Social Networks: new perspectives” (Guest Editors: J. Krause, D. Lusseau, and R. James).