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。     

基于等级全息建模的输油泵机组风险根源辨识*

为“挖掘”输油泵机组风险根源,降低设备预知性维护难度,结合输油泵多准则风险评价,提出1种基于等级全息建模的输油泵机组风险根源辨识方法,运用等级全息建模方法将输油泵系统分解为泵体结构、管理因素、环境因素、操作因素、技术因素、运行因素、设备安装7个子系统进行定性和定量分析。结果表明:相比危险与可操作性分析（HAZOP）、事故树分析（FTA）等传统风险辨识方法,等级全息建模（HHM）对轴承等关键部件以及压力等运行参数的监测更为深入,能够有效辨识输油泵机组高风险情景,提升输油泵的风险辨识效率。     

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。     

缝洞型管道瓦斯爆炸特性数值模拟研究

为探究采空区遗煤、松散破碎岩块对瓦斯爆炸的影响,建立缝洞型管道模型,采用数值模拟与理论分析结合方法研究采空区内缝洞型管道内瓦斯爆炸的传播规律及管道长径比对瓦斯爆炸过程中速度与冲击波的影响。研究结果表明:在缝洞型结构内,随着火焰沿管道向前传播,各监测点速度逐渐变大、压力先增加后降低,而压力上升速率则表现出不规则的变化;缝洞结构加剧了火焰燃烧的剧烈程度,提高了管道内各监测点的温度峰值;在缝洞型管道内随长径比r增加,各监测点最大压力峰值以及速度大小依次降低。     

Spatiotemporal Variability of Modeled Watershed Scale Surface‐Depression Storage and Runoff for the Conterminous United States

This study explores the viability of using simulated monthly runoff as a proxy for landscape‐scale surface‐depression storage processes simulated by the United States Geological Survey’s National Hydrologic Model (NHM) infrastructure across the conterminous United States (CONUS). Two different temporal resolution model codes (daily and monthly) were run in the NHM with the same spatial discretization. Simulated values of daily surface‐depression storage (treated as a decimal fraction of maximum volume) as computed by the daily Precipitation‐Runoff Modeling System (NHM‐PRMS) and normalized runoff (0 to 1) as computed by the Monthly Water Balance Model (NHM‐MWBM) were aggregated to monthly and annual values for each hydrologic response unit (HRU) in the CONUS geospatial fabric (HRU; n = 109,951) and analyzed using Spearman’s rank correlation test. Correlations between simulated runoff and surface‐depression storage aggregated to monthly and annual values were compared to identify where which time scale had relatively higher correlation values across the CONUS. Results show Spearman’s rank values >0.75 (highly correlated) for the monthly time scale in 28,279 HRUs (53.35%) compared to the annual time scale in 41,655 HRUs (78.58%). The geographic distribution of HRUs with highly correlated monthly values show areas where surface‐depression storage features are known to be common (e.g., Prairie Pothole Region, Florida).     

Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter‐elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network‐Daily (GHCN‐D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN‐D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN‐D based SWAT‐simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge‐based measurements can improve hydrologic model performance, especially for extreme events.     

Estimating Potential Climate Change Effects on the Upper Neuse Watershed Water Balance Using the SWAT Model

Climate change poses water resource challenges for many already water stressed watersheds throughout the world. One such watershed is the Upper Neuse Watershed in North Carolina, which serves as a water source for the large and growing Research Triangle Park region. The aim of this study was to quantify possible changes in the watershed’s water balance due to climate change. To do this, we used the Soil and Water Assessment Tool (SWAT) model forced with different climate scenarios for baseline, mid‐century, and end‐century time periods using five different downscaled General Circulation Models. Before running these scenarios, the SWAT model was calibrated and validated using daily streamflow records within the watershed. The study results suggest that, even under a mitigation scenario, precipitation will increase by 7.7% from the baseline to mid‐century time period and by 9.8% between the baseline and end‐century time period. Over the same periods, evapotranspiration (ET) would decrease by 5.5 and 7.6%, water yield would increase by 25.1% and 33.2%, and soil water would increase by 1.4% and 1.9%. Perhaps most importantly, the model results show, under a high emission scenario, large seasonal differences with ET estimated to decrease by up to 42% and water yield to increase by up to 157% in late summer and fall. Planning for the wetter predicted future and corresponding seasonal changes will be critical for mitigating the impacts of climate change on water resources.     

An application of a modified theory of planned behavior model to investigate adolescents’ job safety knowledge,norms, attitude and intention to enact workplace safety and health skills

Introduction: For many reasons, including a lack of adequate safety training and education, U.S. adolescents experience a higher rate of job-related injury compared to adult workers. Widely used social-psychological theories in public health research and practice, such as the theory of planned behavior, may provide guidance for developing and evaluating school-based interventions to prepare adolescents for workplace hazards and risks. Method: Using a structural equation modeling approach, the current study explores whether a modified theory of planned behavior model provides insight on 1,748 eighth graders’ occupational safety and health (OSH) attitude, subjective norm, self-efficacy and behavioral intention, before and after receiving instruction on a free, national young worker safety and health curriculum. Reliability estimates for the measures were produced and direct and indirect associations between knowledge and other model constructs assessed. Results: Overall, the findings align with the theory of planned behavior. The structural equation model adequately fit the data; most path coefficients are statistically significant and knowledge has indirect effects on behavioral intention. Confirmatory factor analyses suggest that the knowledge, attitude, self-efficacy, and behavioral intention measures each reflect a unique dimension (reliability estimates ≥0.86), while the subjective norm measure did not perform adequately. Conclusion: The findings presented provide support for using behavioral theory (specifically a modified theory of planned behavior) to investigate adolescents’ knowledge, perceptions, and behavioral intention to engage in safe and healthful activities at work, an understanding of which may contribute to reducing the downstream burden of injury on this vulnerable population—the future workforce. Practical application: Health behavior theories, commonly used in the social and behavioral sciences, have utility and provide guidance for developing and evaluating OSH interventions, including those aimed at preventing injuries and promoting the health and safety of adolescent workers in the U.S., who are injured at higher rates than are adults.     

System safety assessment using safety entropy

Safety assessment has a primary role in hazardous operations. Most studies on safety assessment focus on risk and accident modeling, in which safety is absent. These top-down methods are highly dependent on the occurred accidents to establish accidental scenarios, which may make the assessment approach lagging behind the evolving modern systems. Moreover, this “special to general” logic is scientifically suspect in safety assessment. There is a call for the development of safety assessment methods in the presence of system safety to complement risk-focused safety analysis. These methods should provide a framework based on a bottom-up approach to examine system safety from the operational perspective. This paper has attempted to provide a potential solution. In particular, a novel concept of safety entropy is proposed to integrate with The Functional Resonance Analysis Method (FRAM), which is used to form the qualitative understanding of a system. A formula consisted of safety entropy, functional conformability, and system complexity has been established to determine the spontaneity of the safety state-changing process. The proposed method is applied to the safety assessment of a propane feed-control system. The results show the applicability of the method. Nevertheless, the model still needs to be further improved to fulfill better support for safety-related decision problems.     

Recent application of Computational Fluid Dynamics (CFD) in process safety and loss prevention: A review

In recent years, significant progress has been made to ensure that process industries are among the safest workplaces in the world. However, with the increasing complexity of existing technologies and new problems brought about by emerging technologies, a strong need still exists to study the fundamentals of process safety and predict possible scenarios. This is attained by conducting the corresponding consequence modeling and risk assessments. As a result of the continuous advancement of Computational Fluid Dynamics (CFD) tools and exponentially increased computation capabilities along with better understandings of the underlying physics, CFD simulations have been applied widely in the areas of process safety and loss prevention to gain new insights, improve existing models, and assess new hazardous scenarios. In this review, 126 papers from 2010 to 2020 have been included in order to systematically categorize and summarize recent applications of CFD for fires, explosions, dispersions of flammable and toxic materials from accidental releases, incident investigations and reconstructions, and other areas of process safety. The advantages of CFD modeling are discussed and the future of CFD applications in this research area is outlined.