矿井热宽温度环境人体热健康分区热调节模型*

为评价矿井热环境中工人职业健康安全状况,提出矿井热宽温度环境人体热健康状态的基本特征与生理要求,分析热宽温度环境人体分区热调节规律与热健康状态的对应关系。基于生物控制论的观点,提出热宽温度范围内不同热应力作用下人体分区热调节机制,建立人体分区热调节模型。结果表明:模型能实现对环境热应力作用下人体物理热平衡状态与生理状态的参数化描述,揭示多因素作用下人体热健康状态的热应力边界与变化规律。分区热调节模型提供了人体热健康状态定量模拟平台,通过参数调整可使模型适应研究需求,模型为井下热环境工人职业健康安全状况分析与评价提供了可参考的思路与方法。     

高应力条件下尾矿破碎特性及坝体稳定性研究*

高应力条件下尾矿破碎特性与坝体稳定性研究是高尾矿坝避免溃坝事故的重要参考。分析尾矿颗粒破碎过程中级配曲线的演化规律,提出采用BET测试颗粒比表面积以定量化表征颗粒破碎指标;在室内高应力三轴试验的基础上,阐述高应力条件下尾矿的力学行为,提出高应力条件下尾矿强度准则,并基于该准则对工程实例进行应用分析。结果表明:相比于常用破碎指标,从能量观点出发的BET法比表面积表征尾矿颗粒破碎更为合理;采用线性Mohr-Coulomb准则计算尾矿在低应力阶段的内摩擦角,采用幂函数Mohr强度准则计算尾矿在高应力阶段的内摩擦角;提出1套考虑高应力条件下尾矿强度折减的坝体稳定性分析方法,以供实际工程参考。     

基于微生物相互作用机理的完全耦合活性污泥模型研究

根据微生物生长机理,推导出微生物的耦合作用机理并在该机理的基础上改进了ASM3 Bio-P模型.假设活性污泥系统中有机物氧化过程、生物硝化过程、生物反硝化过程、生物除磷过程可同时存在,在ASM3 Bio-P模型上添加相关的开关函数,推导出完全耦合活性污泥模型(FCASM).基于计算机程序进行数值模拟,并将FCASM模拟结果与实测值以及ASM3 Bio-P模型模拟值进行对比.结果表明,完全耦合活性污泥模型对氨氮模拟的稳态出水值为1.90 g·m-3,ASM3 Bio-P模型模拟的氨氮稳态出水值为0 g·m-3,而实测的氨氮稳态出水值为1.50 g·m-3,完全耦合活性污泥模型的结果更接近真实值.     

基于熵值法和GM(1,1)模型的重庆城市生态系统健康评价

应用信息熵值反映数据本身的效用值来计算指标权重系数,建立熵权综合评价模型,对重庆城市生态系统健康进行了评价.根据评价结果和灰理论数学建模特点,建立GM(1,1)灰色预测模型,对重庆市生态系统健康进行了动态预测分析.结果表明:2005~2009年期间,重庆城市生态系统健康总体水平良好,其中各要素指数评价大小依次是活力指数、恢复力指数、组织结构指数、服务功能指数、人群生活指数;2010~2015年期间,重庆城市生态系统健康综合评价值将以e0.1268的增速保持良好发展态势.此外,建立以熵权综合评价为基础的GM(1,1)灰色预测模型对城市生态系统健康进行评价,能够得出更客观、更全面的评价结果.     

民用机场消防指挥员决策能力分析

为研究民用机场消防指挥员决策能力,根据专家意见及相关规章、文件的规定,筛选出文化素质、身体素质、心理素质等18项影响机场消防指挥员决策能力的要素,并采用问卷调查的方式进行调研。运用SPSS 21.0对问卷进行信度分析、效度分析及因子分析,确定民用机场消防指挥员决策能力指标体系。根据该指标体系构建民用机场消防指挥员决策能力结构方程模型,运用Amos 17.0计算各变量的路径系数,进而得到各指标的权重,避免了人为打分方法确定权重的主观性。研究结果为分析民用机场消防指挥员决策能力提供更加准确、合理、可信的评价方法。     

军用物资集装箱内部低温环境条件研究

以天津和齐齐哈尔两个低温地区军用物资集装箱运输为背景,分别对两个地区的集装箱内部温度变化及大气温度等数据进行测试并对比分析。对齐齐哈尔地区的数据进行回归分析,建立了集装箱内部温度模型,预测出集装箱内部最恶劣的低温极值范围,为危险军用物资集装箱安全储运提供理论依据,并提出了相应的对策及建议。     

加载条件下原水管道受力特征模型试验研究

为研究堆载大小对原水管道受力变形的影响,采用量纲分析法得出模型试验相似比,并根据相似比进行模型箱的设计、管道材料的选取和重塑土的配制,研究不同工况下管道的受力特征。试验结果表明:整体上管道端部应力大于管中央应力,管轴向应力大于管环向应力。在中心加载下,管端应力值较管中央处大,前者增长速度更快,而后者增长速度较慢。在偏心荷载作用下,靠近荷载的管端应力最大,而管中央应力最小;尤其在偏载6 kPa作用下,管端下表面轴向应力达到595 kPa,而管中央处仅有64 kPa,管端受边界约束作用明显,管道呈弯曲变形。     

Using empirical models of species colonization under multiple threatening processes to identify complementary threat‐mitigation strategies

Approaches to prioritize conservation actions are gaining popularity. However, limited empirical evidence exists on which species might benefit most from threat mitigation and on what combination of threats, if mitigated simultaneously, would result in the best outcomes for biodiversity. We devised a way to prioritize threat mitigation at a regional scale with empirical evidence based on predicted changes to population dynamics—information that is lacking in most threat‐management prioritization frameworks that rely on expert elicitation. We used dynamic occupancy models to investigate the effects of multiple threats (tree cover, grazing, and presence of an hyperaggressive competitor, the Noisy Miner (Manorina melanocephala) on bird‐population dynamics in an endangered woodland community in southeastern Australia. The 3 threatening processes had different effects on different species. We used predicted patch‐colonization probabilities to estimate the benefit to each species of removing one or more threats. We then determined the complementary set of threat‐mitigation strategies that maximized colonization of all species while ensuring that redundant actions with little benefit were avoided. The single action that resulted in the highest colonization was increasing tree cover, which increased patch colonization by 5% and 11% on average across all species and for declining species, respectively. Combining Noisy Miner control with increasing tree cover increased species colonization by 10% and 19% on average for all species and for declining species respectively, and was a higher priority than changing grazing regimes. Guidance for prioritizing threat mitigation is critical in the face of cumulative threatening processes. By incorporating population dynamics in prioritization of threat management, our approach helps ensure funding is not wasted on ineffective management programs that target the wrong threats or species.     

The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake

Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple‐use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders’ willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders’ decisions to engage in management. To test the utility of our best‐supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost‐effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost‐effective for prioritizing management when social data collection costs were low (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost‐efficient and effective manner.     

辽宁省经济发展与环境关系的实证研究

维持经济的持续稳定增长是我国的重要政策目标,然而面对日趋严峻的资源、环境制约,大力推进生态文明建设已刻不容缓。相应地,在理论方面,研究经济增长与环境污染的双向作用机制也非常必要。利用VAR模型,研究了辽宁省经济发展与环境之间的关系,发现两者之间的关系并不是EKC理论中所说的倒u型曲线,而是呈现w型、N型等更加复杂的曲线形状。实验结果也表明辽宁省环境与经济存在双向作用机制,其中,废气与废水对辽宁省经济增长影响最大。