基于人工神经网络的气体泄爆最大超压预测研究

为解决传统经验公式在预测气体泄爆中最大超压出现时的较大偏差或过于保守的问题,提出使用人工神经网络预测气体泄爆最大超压。基于124组实验数据,采用BP与RBF神经网络,通过优化算法计算与迭代循环对泄爆样本中的影响因素进行降维与选择,并确定2类神经网络本身在学习与计算气体泄爆样本时的相关参数。结果表明:PCA（主成分分析法）在当前样本条件下的降维效果较差,而通过迭代对比确认气体泄爆样本中的5类特征全部保留时神经网络的训练模拟效果最好;通过对124组实验数据进行随机挑选训练集与测试集的训练模拟结果发现,神经网络对气体泄爆中最大超压的预测效果较好;通过对比Molkov提出的和经Fakandu等改进的NFPA 68经验公式以及2类神经网络的预测结果表明,神经网络相比于传统气体泄爆经验公式具有明显优势。     

瓦斯抽采PC-CAS基封孔材料优化及其膨胀作用分析*

为了研制以硅酸盐/铝酸盐水泥、生石灰、生石膏为主的PC-CAS基封孔材料,采用正交试验优化材料配比、开展膨胀力研究,并用扫描电镜观测料-煤胶结形貌。研究结果表明:材料的最优配比为A2B2C4,其具备优良的流动性、强度及致密性,造浆量达2 100 mL/kg;PC-CAS基材料具有显著的膨胀性,其膨胀力随时间先增大而后趋于稳定,并且该膨胀力随着径向约束的提高而增大;相比于FP材料,PC-CAS基材料产生的膨胀力能够显著降低材料-煤岩界面的空隙并在一定程度上压密煤体内部的裂隙;该材料产生的膨胀力可压密封孔段围岩、提高封孔质量,并为后期“二次注浆”提供保压条件。工业试验结果表明,采用PC-CAS基材料进行封孔可显著改善抽采效果,将原有平均浓度10.11%提升至20.08%。     

基于复合治理理论的基层应急管理模式优化*

为弥补传统基层应急管理模式的短板,解决信息壁垒、协调困难、公众参与不足等问题。从复合性视角出发,阐述复合治理理论内涵,探讨复合治理与应急管理在主体、思维、过程、空间、目标上的契合性,并进一步分析基层应急管理的现实背景和困境,进而构建基于复合治理理论的基层应急管理模式,阐明模式基本结构和工作流程,最终提出理念树立、平台搭建、机制保障、队伍建设、制度安排、文化营造、技术支撑方面的优化路径。结果表明:复合治理理论的应用可以加强基层应急管理能力,促进多元主体协同共治。     

电气柜疲劳强度校核及结构优化

针对多孔闭孔型发泡硅橡胶D型空心密封条的超弹性特性,通过试验找出了密封条回弹力与压缩量之间的关系,提出了密封条满足IP X5的判别方程式,同时对方程式进行了试验验证,最后对密封条进行了阿累尼乌斯图寿命推算,为变流器柜门IP防护设计提供了重要参考。     

Mitigating Impact of Devils Lake Flooding on the Sheyenne River Sulfate Concentration

Devils Lake is a terminal lake located in northeast North Dakota. Because of its glacial origin and accumulated salts from evaporation, the lake has a high concentration of sulfate compared to the surrounding water bodies. From 1993 to 2011, Devils Lake water levels rose by ~10 m, which flooded surrounding communities and increased the chance of an overspill to the Sheyenne River. To control the flooding, the State of North Dakota constructed two outlets to pump the lake water to the river. However, the pumped water has raised concerns about of water quality degradation and potential flooding risk of the Sheyenne River. To investigate these perceived impacts, a Soil and Water Assessment Tool (SWAT) model was developed for the Sheyenne River and it was linked to a coupled SWAT and CE‐QUAL‐W2 model that was developed for Devils Lake in a previous study. While the current outlet schedule has attempted to maintain the total river discharge within the confines of a two‐year flood (36 m³/s), our simulation from 2012 to 2018 revealed that the diversion increased the Sheyenne River sulfate concentration from an average of 125 to >750 mg/L. Furthermore, a conceptual optimization model was developed with a goal of better preserving the water quality of the Sheyenne River while effectively mitigating the flooding of Devils Lake. The optimal solution provides a “win–win” outlet management that maintains the efficiency of the outlets while reducing the Sheyenne River sulfate concentration to ≤600 mg/L.     

Location selection of emergency supplies repositories for emergency logistics management: A variable weighted algorithm

With the development of the city, the number of establishments that are proposed or under construction is increasing year by year, and if they are industries that handle flammable, explosive, toxic, harmful, and dangerous substances, the public safety will face great threats, which will bring great challenges to emergency rescue work. Therefore, providing reasonable solutions to the problem of location selection of emergency supplies repositories are necessary for improving the emergency response efficiency in chemical industrial parks. A mathematical model for location selection of emergency supplies repositories in emergency logistics management are presented considering more actual factors. The optimization objectives of the model are to minimize total transport length and cost. And then a Variable Weighted Algorithm is designed to solve the model, where an auxiliary function was constructed with different methods of building weighting factors based on the theory and method of solving multi-objective optimization problems in operational research. Simulation results show the effectiveness and feasibility of the models and algorithms presented in this paper.     

Scenario-based assessment and multi-objective optimization of urban development plan with carrying capacity of water system

• Impact of urban development on water system is assessed with carrying capacity. • Impacts on both water resource quantity and environmental quality are involved. • Multi-objective optimization revealing system trade-off facilitate the regulation. • Efficiency, scale and structure of urban development are regulated in two stages. • A roadmap approaching more sustainable development is provided for the case city. Environmental impact assessments and subsequent regulation measures of urban development plans are critical to human progress toward sustainability, since these plans set the scale and structure targets of future socioeconomic development. A three-step methodology for assessing and optimizing an urban development plan focusing on its impacts on the water system was developed. The methodology first predicted the pressure on the water system caused by implementation of the plan under distinct scenarios, then compared the pressure with the carrying capacity threshold to verify the system status; finally, a multi-objective optimization method was used to propose regulation solutions. The methodology enabled evaluation of the water system carrying state, taking socioeconomic development uncertainties into account, and multiple sets of improvement measures under different decisionmaker preferences were generated. The methodology was applied in the case of Zhoushan city in South-east China. The assessment results showed that overloading problems occurred in 11 out of the 13 zones in Zhoushan, with the potential pressure varying from 1.1 to 18.3 times the carrying capacity. As a basic regulation measure, an environmental efficiency upgrade could relieve the overloading in 4 zones and reduce 9%‒63% of the pressure. The optimization of industrial development showed that the pressure could be controlled under the carrying capacity threshold if the planned scale was reduced by 24% and the industrial structure was transformed. Various regulation schemes including a more suitable scale and structure with necessary efficiency standards are provided for decisionmakers that can help the case city approach a more sustainable development pattern.     

Diffusive gradients in thin films using molecularly imprinted polymer binding gels for in situ measurements of antibiotics in urban wastewaters

• Selective molecularly imprinted polymer (MIP) binding gel was prepared. • MIP-DGT showed excellent uptake performance for antibiotics. • In situ measurement of antibiotics in wastewaters via MIP-DGT was developed. • The MIP-DGT method was robust, reliable, and highly sensitive. Urban wastewater is one of main sources for the introduction of antibiotics into the environment. Monitoring the concentrations of antibiotics in wastewater is necessary for estimating the amount of antibiotics discharged into the environment through urban wastewater treatment systems. In this study, we report a novel diffusive gradient in thin films (DGT) method based on molecularly imprinted polymers (MIPs) for in situ measurement of two typical antibiotics, fluoroquinolones (FQs) and sulfonamides (SAs) in urban wastewater. MIPs show specific adsorption toward their templates and their structural analogs, resulting in the selective uptake of the two target antibiotics during MIP-DGT deployment. The uptake performance of the MIP-DGTs was evaluated in the laboratory and was relatively independent of solution pH (4.0–9.0), ionic strength (1–750 mmol/L), and dissolved organic matter (DOM, 0–20 mg/L). MIP-DGT samplers were tested in the effluent of an urban wastewater treatment plant for field trials, where three SA (sulfamethoxazole, sulfapyridine, and trimethoprim) and one FQ (ofloxacin) antibiotics were detected, with concentrations ranging from 25.50 to 117.58 ng/L, which are consistent with the results measured by grab sampling. The total removal efficiency of the antibiotics was 80.1% by the treatment plant. This study demonstrates that MIP-DGT is an effective tool for in situ monitoring of trace antibiotics in complex urban wastewaters.     

基于灾害风险评估的山地城市固定避难场所布局优化研究——以东川区为例

研究以各区域灾害风险评估系数作为权重系数,对山地小城市各区域避难场所进行优化布局。首先,通过风险值=危险性*脆弱性/抗灾救灾能力机理表达式构建灾害风险评估指标体系,并以模糊综合评价法得出灾害风险评估数值,在此基础上通过多目标选址优化模型来构建山地城市避难场所的优化模型,其中灾害风险评估系数作为影响布局的权重因素纳入其中。最后,以东川区为研究对象,对其固定避难场所进行优化布局研究,结果表明:东川区城区固定避灾场所数量可在接近最优解的情况下达到效果最优。     

Point Sampling Digital Imagery with ‘Samplepoint’

Measuring percent occurrence of objects from digital images can save time and expense relative to conventional field measurements. However, the accuracy of image analysis had, until now, not reached the level of the best conventional field measurements. Additionally, most image-analysis software programs require advanced user training to successfully analyze images. Here we present a new software program, ‘SamplePoint,’ that provides the user a single-pixel sample point and the ability to view and identify the pixel context. We found SamplePoint to allow accuracy comparable with the most accurate field-methods for ground-cover measurements. Expert use of the program requires minimal training and its ease of use allows rapid measurements from image data. We recommend SamplePoint for calibrating the threshold-detection level of image-analysis software or for making direct measurements of percent occurrence from digital images.