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%。     

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。     

我国污染物总量控制制度改革的思考

污染物总量控制制度是我国环境保护制度的重要组成部分。结合污染物总量控制制度的实施现状,分析实施过程中减排基数、核算体系、责任主体等方面存在的问题。提出,改革现行污染物总量控制制度,将总量控制与改革中的排污许可制相融合,落实企业主体责任,将总量指标与环境质量改善挂钩,建立差异化的减排核算体系,并加强日常监管,达到改善环境质量的目标。     

300MW锅炉低NOx燃烧系统改造效果分析

针对日益严重的环境污染、锅炉热效率低等问题，阐述了燃煤锅炉炉内空间分级燃烧技术、煤粉浓淡高效分离技术改造项目和特点，提出了对燃烧器系统、一次风管道、二次风系统和空预器系统等系统进行具体的低氮改造措施。分析了300 MW燃煤锅炉低氮改造后的热经济性和安全性。经试验验证，1号锅炉低氮改造后，锅炉NOx 排放量大幅减少，排放浓度降到了280 mg／m3。     

Optimization of facility location and reallocation in an industrial plant through a multi-annual framework accounting for economic and safety issues

The industrial layout traditionally has been addressed accounting for the facilities distribution and installation since the first day of operation of the plant; this is, without considering future expansions that involve additional facilities in the future operation years. This way, this paper proposes a mathematical programming formulation for the optimal facility sitting and reallocation in an industry accounting for future expansions and involving simultaneously economic and safety objectives. The proposed formulation is based on a multi-annual framework and this corresponds to a multi-objective mixed integer linear programming problem. The proposed optimization approach was applied to a case study for the facility sitting (office buildings and control rooms) in an ethylene oxide plant. The economic objective function involves the minimization of the total annual cost accounting for the value of the money through the time and the safety objective function involves the minimization for the accumulated risk over the operation time. Results show the applicability of the proposed approach.     

What matters for work engagement? A diary study on resources and the benefits of selective optimization with compensation for state work engagement

This diary study addresses the benefits of employees' daily use of selective optimization with compensation (SOC) for state work engagement. We hypothesized that day‐level SOC not only directly fosters work engagement but that SOC also reveals its beneficial effects for work engagement in interaction with both external and internal resources. Specifically, we proposed SOC substitutes for job control, role clarity, and state of being recovered, thus helping employees manage low daily levels of these resources. We tested our hypotheses with a sample of 138 employees who completed two daily surveys over a total of 545 workdays. Results of multilevel analyses revealed that SOC benefits work engagement in both proposed ways. First, day‐level SOC was positively related to state work engagement. Additionally, day‐level role clarity and state of being recovered predicted state work engagement, but day‐level job control did not. Second, SOC benefitted state work engagement by offsetting low levels of role clarity and being recovered, and by boosting job control in their respective relationships with work engagement. The results suggest that by using SOC at work, employees can actively enhance their own work engagement on a given workday. This knowledge provides promising starting points for the development of interventions.     

The accounting method and application of CO2 emissions responsibility by the electricity sector at the provincial level in China

When accounting the CO₂ emissions responsibility of the electricity sector at the provincial level in China,it is of great significance to consider the scope of both producers’ and the consumers’ responsibility,since this will promote fairness in defining emission responsibility and enhance cooperation in emission reduction among provinces.This paper proposes a new method for calculating carbon emissions from the power sector at the provincial level based on the shared responsibility principle and taking into account interregional power exchange.This method can not only be used to account the emission responsibility shared by both the electricity production side and the consumption side,but it is also applicable for calculating the corresponding emission responsibility undertaken by those provinces with net electricity outflow and inflow.This method has been used to account for the carbon emissions responsibilities of the power sector at the provincial level in China since 2011.The empirical results indicate that compared with the production-based accounting method,the carbon emissions of major power-generation provinces in China calculated by the shared responsibility accounting method are reduced by at least 10%,but those of other power-consumption provinces are increased by 20% or more.Secondly,based on the principle of shared responsibility accounting,Inner Mongolia has the highest carbon emissions from the power sector while Hainan has the lowest.Thirdly,four provinces,including Inner Mongolia,Shanxi,Hubei and Anhui,have the highest carbon emissions from net electricity outflow- 14 million t in 2011,accounting for 74.42% of total carbon emissions from net electricity outflow in China.Six provinces,including Hebei,Beijing,Guangdong,Liaoning,Shandong,and Jiangsu,have the highest carbon emissions from net electricity inflow- 11 million t in 2011,accounting for 71.44% of total carbon emissions from net electricity inflow in China.Lastly,this paper has estimated the emission factors of electricity consumption at the provincial level,which can avoid repeated calculations when accounting the emission responsibility of power consumption terminals（e.g.construction,automobile manufacturing and other industries）.In addition,these emission factors can also be used to account the emission responsibilities of provincial power grids.     

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.     

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。     

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。