A hybrid model for human factor analysis in process accidents: FBN-HFACS

Human factors are the largest contributing factors to unsafe operation of the chemical process systems. Conventional methods of human factor assessment are often static, unable to deal with data and model uncertainty, and to consider independencies among failure modes. To overcome the above limitations, this paper presents a hybrid dynamic human factor model considering Human Factor Analysis and Classification System (HFACS), intuitionistic fuzzy set theory, and Bayesian network. The model is tested on accident scenarios which have occurred in a hot tapping operation of a natural gas pipeline. The results demonstrate that poor occupational safety training, failure to implement risk management principles, and ignoring reporting unsafe conditions were the factors that contributed most failures causing accident. The potential risk-based safety measures for preventing similar accidents are discussed. The application of the model confirms its robustness in estimating impact rate (degree) of human factor induced failures, consideration of the conditional dependency, and a dynamic and flexible modelling structure.     

Modeling of a sequencing batch reactor treating municipal wastewater using multi-layer perceptron and radial basis function artificial neural networks

A sequencing batch reactor was modeled using multi-layer perceptron and radial basis function artificial neural networks (MLPANN and RBFANN). Then, the effects of influent concentration (IC), filling time (FT), reaction time (RT), aeration intensity (AI), SRT and MLVSS concentration were examined on the effluent concentrations of TSS, TP, COD and NH₄⁺-N. The results showed that the optimal removal efficiencies would be obtained at FT of 1 h, RT of 6 h, aeration intensity of 0.88 m³/min and SRT of 30 days. In addition, COD and TSS removal efficiencies decreased and TP and NH₄⁺-N removal efficiencies did not change significantly with increases of influent concentration. The TSS, TP, COD and NH₄⁺-N removal efficiencies were 86%, 79%, 94% and 93%, respectively. The training procedures of all contaminants were highly collaborated for both RBFANN and MLPANN models. The results of training and testing data sets showed an almost perfect match between the experimental and the simulated effluent of TSS, TP, COD and NH₄⁺-N. The results indicated that with low experimental values of input data to train ANNs the MLPANN models compared to RBFANN models are more precise due to their higher coefficient of determination (R²) and lower root mean squared errors (RMSE) values.     

长江三峡区间数字流域水系的构建

基于全球陆地一公里基础高程GLOBE数据 ,采用Martz和Garbrecht研制的数字高程流域水系模型自动提取长江三峡万县～宜昌区间的河网水系、各子流域分水线、河网与子流域编码及河网结构拓扑关系 ,从而构成该区域的数字流域和数字水系。结果表明该模型生成的水系是可以接受的 ,与 1:10万地形图上长江三峡万县～宜昌区间的水系一致 ,这为空间分布式模型的建立提供了必备的空间信息数据。最后 ,探讨了数字流域水系在流域生态学中的应用前景 ,构建的数字水系可为中尺度以上流域水体和水生生物的资源保护与合理利用提供决策平台 ,服务于社会经济的可持续发展。     

Modeling Parent and Metabolite Fate and Transport in Subsurface Drained Fields With Directly Connected Macropores1

Abstract: Few studies exist that evaluate or apply pesticide transport models based on measured parent and metabolite concentrations in fields with subsurface drainage. Furthermore, recent research suggests pesticide transport through exceedingly efficient direct connections, which occur when macropores are hydrologically connected to subsurface drains, but this connectivity has been simulated at only one field site in Allen County, Indiana. This research evaluates the Root Zone Water Quality Model (RZWQM) in simulating the transport of a parent compound and its metabolite at two subsurface drained field sites. Previous research used one of the field sites to test the original modification of the RZWQM to simulate directly connected macropores for bromide and the parent compound, but not for the metabolite. This research will evaluate RZWQM for parent/metabolite transformation and transport at this first field site, along with evaluating the model at an additional field site to evaluate whether the parameters for direct connectivity are transferable and whether model performance is consistent for the two field sites with unique soil, hydrologic, and environmental conditions. Isoxaflutole, the active ingredient in BALANCE^® herbicide, was applied to both fields. Isoxaflutole rapidly degrades into a metabolite (RPA 202248). This research used calibrated RZWQM models for each field based on observed subsurface drain flow and/or edge of field conservative tracer concentrations in subsurface flow. The calibrated models for both field sites required a portion (approximately 2% but this fraction may require calibration) of the available water and chemical in macropore flow to be routed directly into the subsurface drains to simulate peak concentrations in edge of field subsurface drain flow shortly after chemical applications. Confirming the results from the first field site, the existing modification for directly connected macropores continually failed to predict pesticide concentrations on the recession limbs of drainage hydrographs, suggesting that the current strategy only partially accounts for direct connectivity. Thirty‐year distributions of annual mass (drainage) loss of parent and metabolite in terms of percent of isoxaflutole applied suggested annual simulated percent losses of parent and metabolite (3.04 and 1.31%) no greater in drainage than losses in runoff on nondrained fields as reported in the literature.     

人口流动规律及其政策含义

人口流动是人力资源配轩优化的根本创新路径,人口流动的一般规律是:如果流动人口为理性行为选择者,在社会制度安排许可的发展环境下,当不同区域和不同产业间形成比较收益差异,存在着流动收益大于流动成本的潜在和现实的各种获利机会时,就必定驱使人们由低收益领域向高必益领域流动,而且比较收益差异量与流动人口的流速、流量正相关,并必然导致产生收益率及人口分布走向平均化的趋势,社会发展也将获得最优化的人力资源配置结果.其相关政策含义:一是人口流动是流动人口的理性选择;二是切实保障公民的自由流动权利;三是利用比较利益差别促进人口流动;四是降低各种不必要的流动成本和流动风险;五是建构人口流动的有效率社会发展框架.     

Phosphate recovery with granular acid-activated neutralized red mud: Fixed-bed column performance and breakthrough curve modelling

Granular acid-activated neutralized red mud (AaN-RM) has been successfully prepared with good chemical stability and physical strength. However, its potential for industrial application remains unknown. Therefore, the performance of granular AaN-RM for phosphate recovery in a fixed-bed column was investigated. The results demonstrated that the phosphate adsorption performance of granular AaN-RM in a fixed-bed column was affected by various operational parameters, such as the bed depth, flow rate, initial solution pH and initial phosphate concentration. With the optimal empty-bed contact time (EBCT) of 24.27 min, the number of processed bed volumes and the phosphate adsorption capacity reached 496.95 and 84.80 mg/g, respectively. Then, the saturated fixed-bed column could be effectively regenerated with a 0.5 mol/L HCl solution. The desorption efficiency remained as high as 83.45% with a low weight loss of 3.57% in the fifth regeneration cycle. In addition, breakthrough curve modelling showed that a 5-9-1 feed-forward artificial neural network (ANN) could be effectively applied for the optimization of the fixed-bed adsorption system; the coefficient of determination (R²) and the root mean square error (RMSE) evaluated on the validation-testing data were 0.9987 and 0.0183, respectively. Therefore, granular AaN-RM fixed-bed adsorption exhibits promising potential for phosphate removal and recovery from polluted water.     

Performance of different macrophytes in the decontamination of and electricity generation from swine wastewater via an integrated constructed wetland-microbial fuel cell process

Plants constitute a major element of constructed wetlands(CWs).In this study,a coupled system comprising an integrated vertical flow CW(IVCW) and a microbial fuel cell(MFC) for swine wastewater tre atment was developed to research the effects of macrophytes commonly employed in CWs,Canna indica,Acorus calamus,and Ipomoea aquatica,on decontamination and electricity production in the system.Because of the different root types and amounts of oxygen released by the roots,the rates of chemical oxygen demand(COD) and ammonium nitrogen(NH_4~+-N) removal from the swine wastewater differed as well.In the unplanted,Canna indica,Acorus calamus,and Ipomoea aquatica systems,the COD removal rates were 80.20%,88.07%,84.70%,and 82.20%,respectively,and the NH_4~+-N removal rates were 49.96%,75.02%,70.25%,and 68.47%,respectively.The decontamination capability of the Canna indica system was better than those of the other systems.The average output voltages were 520±42,715±20,660±27,and 752±26 mV for the unplanted,Canna indica,Acorus calamus,and Ipomoea aquatica systems,respectively,and the maximum power densities were 0.2230,0.4136,0.3614,and0.4964 W/m~3,respectively.Ipomoea aquatica had the largest effect on bioelectricity generation promotion.In addition,electrochemically active bacteria,Geobacter and Desulfuromonas,were detected in the anodic biofilm by high-throughput sequencing analysis,and Comamonas(Proteobacteria),which is widely found in MFCs,was also detected in the anodic biofilm.These results confirmed the important role of plants in IVCW-MFCs.     

驾驶舱空气动力源致振动响应分析研究

目的分析驾驶舱外形上多处凸起对驾驶舱内若干重要部位的振动响应的影响。方法首先采用大涡模拟方法,计算多种飞行工况下分离气流产生的作用于机身前段外表面的非定常脉动压力载荷,然后将所得载荷作用于前机身详细有限元模型上,获得所关心的驾驶舱内部分站位的加速度响应。结果通过对加速度响应结果的分析处理及与试飞测试数据对比,可知驾驶舱外形上多处凸起对驾驶舱内的振动量值影响比较大,气流分离对驾驶舱舱内振动贡献,峰值位置处达到了25%左右。结论相关计算结果可用于驾驶舱工效性评估和驾驶舱外形优化。     

汶川地震重灾区泥石流灾损土地利用及生态修复模式——以北川县都坝河小流域为例

汶川地震诱发了大量泥石流灾害,灾损土地利用和生态修复是灾区产业重建面临的重要课题。以北川县都坝河小流域为研究对象,通过调查灾损土地禀赋、灾害特征、土地需求,采取多因素耦合和关键因子限制分析法,探讨灾害胁迫条件下的经济活动与生态修复之间的互馈作用,结果表明：（1）流域新增土地供给源主要为泥石流灾损土地,土地资源化利用受灾害、聚落和产业结构控制;（2）灾损土地根据成因划分为沟口堆积型、沟道冲淤型以及岸坡侵蚀型,三者的肥力、安全性及交通条件等特征具有显著差异;（3）基于“因灾分区、耕地优先、产业共建、美居造景”的原则,建立了灾损土地的利用方式和生态修复模式,并选取杨家沟进行验证,沟域灾损土地利用方式为生态林地、产业林地及优质耕地,分别占比28.5%、56.3%、15.2%,生态修复措施主要为提高土地安全度、提升植被覆盖率和增强水保功能。该研究建立的震区土地利用和生态修复模式可有力协调人地矛盾、发展绿色经济和提升人居环境。