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.     

Research based on double coverage rate and reliability of gas detector layout optimization

The gas detector layout should be highly attuned to combustible gas leakage and attain a good reliability in avoiding detector malfunction, which is an important guarantee for the normal production of the chemical industry and other related enterprises. Herein, a gas detector layout optimization method based on double coverage and reliability is proposed. The key gas leakage monitoring area is determined through layout scene field investigation. To improve the detection probability and detection system reliability, the dual coverage target and voting mechanism are set, and the gas detector layout is determined with the ray-casting algorithm according to the coverage target. Combined with FLACS software to simulate a variety of typical leakage conditions under different layout scenarios, the relationship between the leaked gas concentration detected by gas detectors in each layout scheme and time is obtained, and the gas leakage detection probability in each layout scheme, number of detectors that can trigger the alarm, shortest time to trigger the alarm and reliability are comprehensively evaluated. The decision-maker selects the final gas detector layout plan according to the evaluation results and actual site needs. The study shows that the detection probability of each layout scheme set according to the double coverage is high, and multiple detectors can trigger the alarm (up to 100%), which ensures that the alarm can be triggered within 10 s under all applicable conditions. According to the evaluation results, the decision-maker can obtain a layout scheme that not only agrees with the actual site conditions but also attains a high detection probability, short detection time and strong reliability.     

AHP与GA-SVM耦合模型在滑坡预警中的应用*

为了减少滑坡造成的损失,提高滑坡预测的准确性,通过搭建灾害模拟平台获得滑坡的实验数据,在获得多组模拟实验数据后,分析各变量的特性。首先,通过层次分析(Analytic Hierarchy Process,AHP)算法,对滑坡进行危险度划分;然后,通过支持向量机(Support Vector Machine,SVM)建立模型,遗传算法(Genetic Algorithm,GA)再优化SVM参数,提出1种层次分析法与GA-SVM相耦合的模型。研究结果表明:AHP方法划分后的数据,通过GA与SVM结合建立的模型精度较好,实验预测结果与实际结果较为吻合,与单一SVM相比,精度更高,结果更好,更加适用于多变量的复杂非线性滑坡预警。     

提高GPS定位精度的群调度滤波算法*

为解决现行安全生产科技领域中全球定位系统（GPS）/惯性导航系统（INS）融合系统容易产生较大时变误差的关键问题,满足GPS定位信号的精度和信号数据处理时间的要求,提出1种群调度滤波算法,通过实验仿真,分别与模糊算法、机器学习算法及卡尔曼滤波网络算法进行比较研究。结果表明:群调度滤波算法兼顾了定位精度与数据处理时间,具有较大优势,可在航空安全、船舶安全、应急监测、灾后抢险等安全科技领域广泛应用。     

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。     

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。     

维修时间不确定性下配电网灾后维修队安排的鲁棒恢复研究*

为最小化灾后配电网损失量,准确描述完整维修队工作时间（分为路途时间与具体维修时间）,依据台风路径对维修队所需路途时间进行分类,并利用期望概率描述具体维修时间的不确定性。建立2阶段分布式鲁棒优化模型,采用CCG算法分析国内某地区配电网算例发现:考虑维修时间不确定性可以有效减少配电网损失量。     

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.