屏蔽服冷却系统对人体表面温度影响的研究*

为科学有效地论证多种方式组合的冷却屏蔽服在不同环境条件下对人体表面温度控制的效果,需要对冷却系统及人体敏感部位发热量进行客观评估。通过对5名健康男性的高温测试,探究人体在不同环境温度下体表温度的变化,得出胸部、背部及额头为热量最高部位,并构建以“人体-降温屏蔽服-外界环境”为主体的冷却系统数值模型,对不同环境中的屏蔽服冷却效果展开研究,分析穿戴冷却屏蔽服时人体躯干部分的温度分布及影响。结果表明:在屏蔽服中靠近胸部、背部部位引入相变材料和风扇,均可帮助人体降低体温,提高舒适度。     

环境风作用下弧形立面机场航站楼自然排烟效果的数值模拟研究

机场航站楼公共区域多采用自然排烟方式,而环境风和排烟窗控制模式会影响排烟效果,尤其在弧形立面航站楼中影响效果显著。以某弧形立面航站楼为研究对象,选取候机指廊弧形区域的自然排烟窗分3段控制启闭,进而确定6种控制模式,采用 FDS火灾动力学模拟软件研究了不同模式下的排烟效果,获得了环境风和发烟量对危险到达时间的影响规律, 提出了排烟窗控制模式流程。结果表明:对于弧形立面航站楼而言,排烟窗分段控制模式下的排烟效果优于不分段控制模式,可以有效降低环境风对自然排烟的影响。当环境风速超过10 m/s时,须关闭迎风向排烟窗,避免烟气倒灌。在法向环境风作用的不利条件下,当发烟量在0. 05~0. 20之间时,危险到达时间的最大值tmax与发烟量x满足一次函数关系式:tmax=-3018x+1030.5。     

基于疲劳累积破坏机制的储罐结构动力可靠度分析

针对随机风载荷作用下储罐结构动力可靠性问题,以300 m3的中小型立式低温储罐为研究对象,利用AR模型进行数值模拟得到风载荷的脉动风速时程与脉动功率谱密度函数。采用ANSYS建立储罐三维有限元模型,并对储罐进行动力学分析,计算出储罐结构的随机响应,进而求出随机风载荷作用下储罐结构动力可靠性所需全部数字特征,最后利用疲劳累积损伤机制计算得到储罐的动力可靠度。结果表明:假设结构强度不随时间退化,前5 a动力可靠度基本保持不变,随着使用年限的延长,动力可靠度下降速度明显增大。研究方法可为储罐的动力可靠性及寿命预测提供一定的理论依据。     

矿井巷道火灾烟流逆退数值模拟及临界风速研究

为了研究矿井发生火灾后高温烟流的蔓延规律及影响因素,利用COMSOL软件对火区进行数值模拟,建立巷道三维模型,得到火区风流速度与温度分布。通过改变边界条件,分析火风压作用下,火区烟气在不同控制风速、巷道条件作用下蔓延规律,得出不同因素与临界风速的关系,为选取合理的火灾控制风速提供理论依据。研究结果表明:火源温度一定时,巷道入口风速越低,火源下风侧高温烟流越靠近巷道顶部,随着风速增大,向巷道下部蔓延;风速较低时,在火区火风压的作用下,会产生烟流逆退现象,随着风速的增大,逆流层长度和厚度随之减小;巷道入口通风条件不变时,火区温度越高越容易产生烟流的逆退,影响范围越大;巷道高度越高、上行风坡度越小,越易发生逆退现象;不同影响因素与巷道平均温度不成正比关系,其中下行风坡度5~15°时巷道平均温度较高且易于发生烟流滚退现象,影响范围较大;火源温度、巷道条件与临界风速的数据拟合结果对预测巷道的临界风速有较好的参考价值。     

开放源对环境空气质量影响的评估技术与实例

开放源排放的颗粒物已经成为城市环境大气颗粒物的主要来源之一,介绍了其对环境空气质量影响的评估技术,采用开放源的动力学经验公式测算S市粉煤灰场、原煤堆场、土堆、沙石料堆4类开放源不同粒径颗粒物的起动风速及扩散距离,并利用箱模型(A值)和源解析(化学质量平衡法,CMB)模型测算开放源的区域年均起尘量及其对环境空气中颗粒物的贡献值.结果表明:开放源排放的颗粒物易升腾而且影响面积很大;S市区开放源类排放的小于100 μm的颗粒物约22.2×104 t/a,小于10 μm的颗粒物约15.8×104 t/a;开放源对环境空气中TSP的贡献值约370 μg/m3,质量浓度分担率达60%,对PM₁₀的贡献值约263 μg/m3,分担率达64%.      

街道峡谷内汽车排放污染物浓度分布的观测与数值模拟

在上海某典型街道峡谷内按一定的空间布点,在一定时段内同时对各布点进行采样并做一氧化碳浓度分析,同时记录车辆种类、车流量、气象条件等,分析街道峡谷内污染物浓度的分布.运用风向频率加权(WDFW)方法,结合大气流动和污染物扩散的CFD模型进行数值模拟计算.结果表明,数值模拟结果和现场观测结果较吻合,建筑物低的一侧污染物浓度远高于建筑物高的一侧污染物浓度,两侧的污染物浓度随着高度的增加而降低.     

基于回归分析的火灾发生气象因子的研究

利用二元回归分析法,对火灾发生次数、空气湿度、风速进行回归分析并检验,得出了火灾发生次数、空气湿度、风速三者之间的显著线性关系。     

Performance improvement of airfoils for wind blade with the groove

This study was a basic one to explore how much the aerodynamic characteristics of wind blade improve. The extent of improvement according to the shapes of groove placed on the surface of airfoil (NACA0015) was analyzed through computational analysis. A commercial computational fluid dynamics (CFD) code, the ANSYS Fluent 13, was used in this study. In this study, regarding with the positions and shapes of groove, the end of groove was placed at a certain distance (length, l) from both the front and back of separation starting point, the depth and the width were designated as h and d respectively. Analysis was conducted at the 7° angle of attack under the following conditions; the thickness (δ) of boundary layer to the depth (h) of groove ratio (h/δ) 0.6–1.0, the depth (h) of groove to the width (d) of groove ratio (h/d) 0.1–1.4, and the length (l) between the end of groove and separation point to the thickness (δ) of boundary layer ratio (l/δ) ?0.5–0.5. Among these conditions, the best improvement of lift to drag ratio, standing at 15.3%, was under h/δ = 1.0, h/d = 0.12, and l/δ = –0.5 (7° AOA, Re = 360k). In addition, throughout the range of angle of attack, 2–14°, lift to drag ratio improved by 0.8%, 5.1%, 3.2%, and 1.8% each when Reynolds numbers were 280k, 360k, 450k, and 530k. It is also confirmed that the shape of groove contributed to recovering velocity around airfoil wall and the lift to drag ratio improvements by groove were maintained at the given range of Reynolds number and around the angle of attack, 7°.     

The Relative Importance of Landscape Amenity and Health Impacts in the Wind Farm Debate in Australia

In recent years, Australia has experienced public debate around the growth in wind farms as part of government and community strategies to move from fossil fuels to renewable energy. Many of the arguments put forward by opponents and supporters are similar to those that have been evident in North America and Western Europe, including possible environmental impacts on wildlife, noise levels and, perhaps most prominently adverse changes in ‘landscape amenity’. A concern of increasing prominence is that of adverse human health impacts from proximity to operating turbines. Using analysis of submissions to public inquiries and a small number of detailed interviews, we consider the increased focus in Australia on the health impacts of wind farms. We note that health impacts, as elsewhere in the world, are often part of a suite of objections to wind farm developments but conclude that for some people near such developments, these are the main concern and not a cover or proxy for other concerns, such as changes in landscape amenity and aesthetics.     

Suitable error evaluation criteria selection in the wind energy assessment via the K-means clustering algorithm

In this paper, wind energy potential of four locations in Xinjiang region is assessed. The Weibull distribution as well as the Logistic and the Lognormal distributions are applied to describe the distributions of the wind speed at different heights. In determining the parameters in the Weibull distribution, four intelligent parameter optimization approaches including the differential evolutionary, the particle swarm optimization, and two other approaches derived from these two algorithms and combined advantages of these two approaches are employed. Then the optimal distribution is chosen through the Chi-square error (CSE), the Kolmogorov–Smirnov test error (KSE), and the root mean square error (RMSE) criteria. However, it is found that the variation range of some criteria is quite large, thus these criteria are analyzed and evaluated both from the anomalous values and by the K-means clustering method. Anomaly observation results have shown that the CSE is the first one should be considered to be eliminated from the consequent optimal distribution function selection. This idea is further confirmed by the K-means clustering algorithm, by which the CSE is clustered into a different group with KSE and RMSE. Therefore, only the reserved two error evaluation criteria are utilized to evaluate the wind power potential.