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分子动力学模拟水化硅酸钙的蠕变性能
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作者 李云丽 张学林 吴文平 《硅酸盐通报》 北大核心 2025年第6期2036-2045,共10页
水化硅酸钙(C-S-H)是水泥基材料最主要的水化产物,其内部存在凝胶孔。C-S-H对混凝土的耐久性有着重要影响,为了探究其在微观结构层面的蠕变变形机制,本文基于C-S-H凝胶分子模型,采用分子动力学模拟研究了C-S-H在不同单轴加载方向和含不... 水化硅酸钙(C-S-H)是水泥基材料最主要的水化产物,其内部存在凝胶孔。C-S-H对混凝土的耐久性有着重要影响,为了探究其在微观结构层面的蠕变变形机制,本文基于C-S-H凝胶分子模型,采用分子动力学模拟研究了C-S-H在不同单轴加载方向和含不同尺寸凝胶孔缺陷情况下的蠕变性能。结果表明:C-S-H在钙硅层面上抗蠕变性能更好,而在垂直于钙硅层方向上抗蠕变性能较差;在蠕变过程中,Ca—O离子键和Si—O共价键抗蠕变性能强于氢键网络结构,且C-S-H的抗压缩蠕变性能优于抗拉伸蠕变性能。微结构的分析表明,C-S-H的蠕变主要起源于层间部分,变形主要由层间原子的位移引起,其中水分子对蠕变变形贡献最为显著。此外,凝胶孔缺陷会降低C-S-H的抗蠕变性能,并显著影响初始蠕变阶段的蠕变速率。 展开更多
关键词 水化硅酸钙(C-S-H) 蠕变性能 分子动力学模拟 微观机制 凝胶孔缺陷
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A Novel Framework for IP DiffServ over Optical Burst Switching Networks 被引量:6
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作者 Ke-PingLong yunli +1 位作者 RodneyS.Tucker Chong-GangWang 《Journal of Computer Science & Technology》 SCIE EI CSCD 2004年第6期948-954,共7页
This paper presents a novel framework for IP Differentiated Services (DiffServ) over optical burst switching (OBS), namely, DS-OBS. The network architecture, functional model of edge nodes and core nodes, the control ... This paper presents a novel framework for IP Differentiated Services (DiffServ) over optical burst switching (OBS), namely, DS-OBS. The network architecture, functional model of edge nodes and core nodes, the control packet format, a novel burst assembly scheme at ingress nodes and scheduling algorithm of core nodes are presented. The basic idea is to apply DiffServ capable burst assembly at ingress nodes and perform different per hop behavior (PHB) electronic treatments for control packets of different QoS class services at core nodes. Simulation results show that the proposed schemes can provide the best differentiated service for expedited forwarding (EF), assured forwarding (AF) and best effort (BE) services in terms of end-to-end delay, throughput and IP packet loss probability. Keywords IP quality of service - differentiated service - per hop behavior - optical burst switching NoteThis work is supported by the National Natural Science Foundation of China (Grant No.90304004), the National Hi-Tech Development 863 Program of China (Grant No.2003AA121540), and the research grants by the Ministry of Education of China (Grant No.204125), the Chongqing Education Commission (Grant No.050309) and the Chongqing Science Commission. 展开更多
关键词 IP quality of service differentiated service per hop behavior optical burst switching
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RWBO(pd, w): A Novel Backoff Algorithm for IEEE 802.11 DCF
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作者 yunli Ke-PingLong Feng-RuiYang 《Journal of Computer Science & Technology》 SCIE EI CSCD 2005年第2期276-281,共6页
The Probability Distribution of. Slot Selection (PDoSS) of IEEE 802.11 DCF is extremely uneven, which makes the packet collision probability very high. In this paper, the authors explore how to make the stations selec... The Probability Distribution of. Slot Selection (PDoSS) of IEEE 802.11 DCF is extremely uneven, which makes the packet collision probability very high. In this paper, the authors explore how to make the stations select:the slots uniformly, and give an RWBO(P-d,w) algorithm for 802.11 DCF to make the PDoSS even and decrease the packet collision probability. A Markov model is given to analyze the PDoSS of RWBO(p(d), w). The performance of RWBO(p(d), w) is evaluated, by. simulation in terms of saturation throughput and packet collision probability. The simulation results indicate that RWBO(p(d), w) can decrease the packet contention,probability to a large extent, and utilize the channel more efficiently as compared to the 802.11 DCF. Moreover, the relation between saturation throughput, and walking probability (p(d)),the relation between saturation throughput and contention windows (w), the relation between packet collision probability and walking probability (p(d)), and the relation between packet collision probability and contention windows (w) are analyzed. The analysis indicates that RWBO(p(d), w) has some remarkable features: its saturation throughout keeps high and packet collision probability keeps very low (under 0.1) in a large range of p(d) and w, which allow users to configure p(d) and w more flexibly. 展开更多
关键词 IEEE 802.11 DCF PDoSS random walking BackOff Markov chain model
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