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| 1 | 考虑多因素的页岩气吸附模型——以川东南五峰组—龙马溪组页岩为例显示文摘甲烷在页岩中的吸附同时受页岩本体物理性质和外部储存条件的综合影响,为了建立考虑多种因素影响的页岩气吸附模型,以川东南五峰组—龙马溪组页岩为例,开展了不同总有机碳含量(TOC含量)的页岩在多个不同温度、不同含水率下对甲烷的吸附实验,采用Langmuir吸附模型对吸附数据进行了拟合,分析了饱和吸附量及Langmuir压力分别与温度、TOC含量及含水率的定量关系,最终建立了考虑温度、压力、TOC含量及含水率综合影响的多因素页岩气吸附模型,并通过与实测吸附数据对比验证了该模型的准确性。结果表明:Langmuir模型能很好的拟合五峰组—龙马溪组页岩在不同特定条件下的吸附数据,拟合精度较高,决定系数R^(2)介于0.9728~0.9982。饱和吸附量与TOC含量呈正线性相关,与温度及含水率呈线性负相关。Langmuir压力与TOC含量呈线性负相关,与温度及含水率呈线性正相关。30℃下TOC含量为4.17%的页岩干样吸附量比TOC含量为2.95%的页岩干样吸附量高约39%。当温度由30℃增至80℃时,TOC含量为4.17%的页岩干样其饱和吸附量降低约30.6%。对于TOC含量为3.66%的含水页岩,当含水率由0增至4.2%时,30℃和60℃下页岩气的饱和吸附量分别降低了23.1%和11.4%。基于Langmuir模型建立的考虑多因素的吸附模型能准确的计算不同TOC含量、不同温度及不同含水情况下的页岩气吸附量。经与2组实测吸附数据对比验证,整个实验压力范围内的相对误差均小于6%,平均误差分别为3.67%和2.48%。经采用其他文献中不同物性的页岩吸附数据验证,表明多因素吸附模型对不同页岩有很好的适用性。 | 李爱芬 韩文成 孙海 ASADULLAH Memon | 2021 | 煤炭学报2021，46，3： | 6 |
| 2 | 含水煤岩超临界等温吸附模型的对比分析显示文摘甲烷在煤层中的吸附多为含水条件下的超临界吸附。为了对比分析含水和超临界条件下经典吸附模型的适用性和准确性,开展了不同温度和不同含水率下煤层气的吸附实验,并分别采用Langmuir模型、Dubinin-Radushkevich(D-R)模型、Dubinin-Astakhov(D-A)模型,以及考虑了煤层气溶解及煤岩膨胀的改进Langmuir+k模型、Dubinin-Radushkevich+k(D-R+k)模型、Dubinin-Astakhov+k(D-A+k)模型对含水煤岩的吸附数据进行了拟合及对比分析,并讨论了水分和温度对煤岩超临界吸附的综合影响。结果表明:Langmuir模型、D-R模型和D-A模型在中压和高压下与实测结果偏差较大,均方根误差介于0.01~0.06。而考虑溶解气及煤岩膨胀等因素的改进吸附模型具有更高的拟合精度,其中D-A+k模型最适用于描述含水煤岩的超临界吸附,拟合误差最小,拟合精度最高,其均方根误差介于0.002~0.009。不同温度下含水煤岩的饱和吸附量均随含水率的增加出现不同程度的降低,当含水率增加至某一值后甲烷吸附量趋于稳定。在30和60℃下当煤岩含水率由0增至6%时,甲烷饱和吸附量分别降低7.92%和2.49%。不同含水率的煤岩其饱和吸附量随温度的增加出现不同程度的降低,当温度由30℃升高至60℃时,干煤样的饱和吸附量降低9.05%,而含水率为2.5%的湿煤样其饱和吸附量降低4.61%,含水率为6.0%的湿煤样其饱和吸附量降低3.68%。可见甲烷在煤岩中的吸附受水分和温度的综合影响,含水煤岩的饱和吸附量随温度和含水率的升高而降低,温度越高时煤岩的饱和吸附量受水分的影响越小,含水率越高的煤岩其饱和吸附量受温度影响越小。 | 韩文成 李爱芬 方齐 ASADULLAH Memon | 2020 | 煤炭学报2020，45，12： | 1 |
| 3 | Time and Quantity Based Hybrid Consolidation Algorithms for Reduced Cost Products Delivery显示文摘In today’s competitive business environment,the cost of a product is one of the most important considerations for its sale.Businesses are heavily involved in research strategies to minimize the cost of elements that can impact on the final price of the product.Logistics is one such factor.Numerous products arrive from diverse locations to consumers in today’s digital era of online businesses.Clearly,the logistics sector faces several dilemmas from order attributes to environmental changes in this regard.This has specially been noted during the ongoing Covid-19 pandemic where the demands on online businesses have increased several fold.Consequently,the methodology to optimise delivery cost and its impact on environmental focus by reducing CO_(2) emissions has gained relevance.The resultant strategy of Shipment Consolidation that has evolved is an approach that combines one or more transport orders in the same vehicle for delivery.Shipment Consolidation has been categorized in three order scheduling approaches:Time based consolidation,Quantity based consolidation,and a Hybrid(Time-Quantity)based consolidation.In this paper,a new Hybrid Consolidation approach is presented.Using the Hybrid approach,it has been shown that order delivery can be facilitated by taking into account not only the order pick up time,but also the total order quantity.These results have shown that if a time window is available in respect of the order delivery time,then the order can be delayed from pickup to consolidate it with other orders for cost optimization.This hybrid approach is based on four consolidation principles,two of which work on fixed departure and two,on demand departure.Three of these rules have been implemented and tested here with an application case study.Statistical analysis of the results is illustrated with different planning evaluation indicators.The Result analyses indicate that consolidation of orders is increased with each implemented rule hence motivating us towards the implementation of the fourth rule.Testing with bigger data sets is required. | Muhammad Ali Memon Asadullah Shaikh Adel Sulaiman Abdullah Alghamdi Mesfer Alrizq Bernard Archimède | 2021 | Computers, Materials & Continua2021，，10： | 0 |
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