System reliability optimization problem of multi-source multi-sink flow network is defined by searching the optimal components that maximize the reliability and minimize the total assignment cost. Therefore, a genetic...System reliability optimization problem of multi-source multi-sink flow network is defined by searching the optimal components that maximize the reliability and minimize the total assignment cost. Therefore, a genetic-based approach is proposed to solve the components assignment problem under budget constraint. The mathematical model of the optimization problem is presented and solved by the proposed genetic-based approach. The proposed approach is based on determining the optimal set of lower boundary points that maximize the system reliability such that the total assignment cost does not exceed the specified budget. Finally, to evaluate our approach, we applied it to various network examples with different numbers of available components;two-source two-sink network and three-source two-sink network.展开更多
In wireless sensor networks(WSNs) with single sink,the nodes close to the sink consume their energy too fast due to transferring a large number of data packages,resulting in the "energy hole" problem.Deployi...In wireless sensor networks(WSNs) with single sink,the nodes close to the sink consume their energy too fast due to transferring a large number of data packages,resulting in the "energy hole" problem.Deploying multiple sink nodes in WSNs is an effective strategy to solve this problem.A multi-sink deployment strategy based on improved particle swarm clustering optimization(IPSCO) algorithm for WSNs is proposed in this paper.The IPSCO algorithm is a combination of the improved particle swarm optimization(PSO) algorithm and K-means clustering algorithm.According to the sink nodes number K,the IPSCO algorithm divides the sensor nodes in the whole network area into K clusters based on the distance between them,making the total within-class scatter to minimum,and outputs the center of each cluster.Then,multiple sink nodes in the center of each cluster can be deployed,to achieve the effects of partition network reasonably and deploy multi-sink nodes optimally.The simulation results show that the deployment strategy can prolong the network lifetime.展开更多
【目的】为保护并优化高度城镇化地区的碳汇空间,有必要系统研究其时空演变特征及规律。【方法】本研究聚焦苏南地区“城镇尺度”的碳汇空间,在研究其时空演变特征的基础上,结合斑块生成土地利用变化模拟(patch-generating land use sim...【目的】为保护并优化高度城镇化地区的碳汇空间,有必要系统研究其时空演变特征及规律。【方法】本研究聚焦苏南地区“城镇尺度”的碳汇空间,在研究其时空演变特征的基础上,结合斑块生成土地利用变化模拟(patch-generating land use simulation,PLUS)模型和聚类分析法研判不同城镇综合响应状态,并提出差异化的碳汇空间管控策略。【结果】1)2000—2020年苏南地区碳汇空间面积大幅减少,减少区域高度集中于高价值碳汇空间。碳汇空间格局在城镇尺度上未因城镇化而全面瓦解,表现出较强的稳定性。2)通过对自然增长情景、碳汇保护情景、碳汇强化情景3种情景的模拟,发现加大碳汇空间保护力度能够实现高质量碳汇空间扩张,但需要警惕生态功能单一化风险,避免盲目追求“高碳汇系数”。3)在3种模拟情景下,大部分城镇碳汇空间结构较稳定,建议通过存量挖潜与功能置换等方式优化碳汇空间;而部分敏感型城镇则呈现差异化演变路径,需根据其具体风险类型,实施更具针对性的管控策略。【结论】快速城镇化地区碳汇空间面积虽然呈现缩减趋势,但在城镇尺度表现出稳定性与敏感性共存的特征。这一特性可通过多情景模拟研判,从而为制定差异化的城镇碳汇空间管控策略提供科学依据。展开更多
大跨桥梁多模态涡激振动控制受限于传统线性吸振器的窄频特性。非线性能量阱惯容器(nonlinear energy sink inerter,NESI)结合宽频吸振与质量放大效应,具备多模态控制潜力,但其性能易受自质量、装配误差等附加位移影响。针对桥梁风致多...大跨桥梁多模态涡激振动控制受限于传统线性吸振器的窄频特性。非线性能量阱惯容器(nonlinear energy sink inerter,NESI)结合宽频吸振与质量放大效应,具备多模态控制潜力,但其性能易受自质量、装配误差等附加位移影响。针对桥梁风致多模态涡激振动控制,提出基于NESI的控制方法。通过理论分析与数值模拟,研究了附加位移效应对NESI控制性能的影响。研究表明,附加位移导致NESI刚度与阻尼的有效参数范围偏移,引发1∶2次频率比共振,涡激振动抑制效率降低53.7%。此外,相较于阻尼比,NESI的控制性能对桥梁模态频率和初始激励幅值更为敏感。当存在附加位移时,NESI控制性能对频率比和激励幅值变化均表现出显著退化,尤其在频率比小于1区域内性能波动剧烈。进一步研究表明,适当提高质量比与惯质比虽可在一定程度上缓解附加位移带来的性能损失,但在频率比小于1的条件下仍难以实现稳定控制。展开更多
非线性能量汇(nonlinear energy sink, NES)在被动控制中有着广阔的应用前景,然而这一领域的研究主要集中在单向吸振器上,这限制了其在实际应用中对多向振动的适用性。设计了一种多向NES,利用相互正交的两组钢丝绳结构,实现了单振子空...非线性能量汇(nonlinear energy sink, NES)在被动控制中有着广阔的应用前景,然而这一领域的研究主要集中在单向吸振器上,这限制了其在实际应用中对多向振动的适用性。设计了一种多向NES,利用相互正交的两组钢丝绳结构,实现了单振子空间任意方向自适应吸振。基于拉格朗日方程建立了系统多向振动控制方程,采用了谐波平衡法对稳态响应进行近似解析分析,并利用四阶龙格-库塔法进行数值验证,其后研究了多向NES的减振效果。结果表明,多向单振子NES能够有效地抑制多向振动,对任意单向激励也同样有效。该研究为NES在多向振动控制中的应用及设计提供了参考。展开更多
文摘System reliability optimization problem of multi-source multi-sink flow network is defined by searching the optimal components that maximize the reliability and minimize the total assignment cost. Therefore, a genetic-based approach is proposed to solve the components assignment problem under budget constraint. The mathematical model of the optimization problem is presented and solved by the proposed genetic-based approach. The proposed approach is based on determining the optimal set of lower boundary points that maximize the system reliability such that the total assignment cost does not exceed the specified budget. Finally, to evaluate our approach, we applied it to various network examples with different numbers of available components;two-source two-sink network and three-source two-sink network.
基金the Key Project of the National Natural Science Foundation of China(No.61134009)National Natural Science Foundations of China(Nos.61473077,61473078)+4 种基金Program for Changjiang Scholars from the Ministry of Education,ChinaSpecialized Research Fund for Shanghai Leading Talents,ChinaProject of the Shanghai Committee of Science and Technology,China(No.13JC1407500)Innovation Program of Shanghai Municipal Education Commission,China(No.14ZZ067)the Fundamental Research Funds for the Central Universities,China(No.15D110423)
文摘In wireless sensor networks(WSNs) with single sink,the nodes close to the sink consume their energy too fast due to transferring a large number of data packages,resulting in the "energy hole" problem.Deploying multiple sink nodes in WSNs is an effective strategy to solve this problem.A multi-sink deployment strategy based on improved particle swarm clustering optimization(IPSCO) algorithm for WSNs is proposed in this paper.The IPSCO algorithm is a combination of the improved particle swarm optimization(PSO) algorithm and K-means clustering algorithm.According to the sink nodes number K,the IPSCO algorithm divides the sensor nodes in the whole network area into K clusters based on the distance between them,making the total within-class scatter to minimum,and outputs the center of each cluster.Then,multiple sink nodes in the center of each cluster can be deployed,to achieve the effects of partition network reasonably and deploy multi-sink nodes optimally.The simulation results show that the deployment strategy can prolong the network lifetime.
文摘【目的】为保护并优化高度城镇化地区的碳汇空间,有必要系统研究其时空演变特征及规律。【方法】本研究聚焦苏南地区“城镇尺度”的碳汇空间,在研究其时空演变特征的基础上,结合斑块生成土地利用变化模拟(patch-generating land use simulation,PLUS)模型和聚类分析法研判不同城镇综合响应状态,并提出差异化的碳汇空间管控策略。【结果】1)2000—2020年苏南地区碳汇空间面积大幅减少,减少区域高度集中于高价值碳汇空间。碳汇空间格局在城镇尺度上未因城镇化而全面瓦解,表现出较强的稳定性。2)通过对自然增长情景、碳汇保护情景、碳汇强化情景3种情景的模拟,发现加大碳汇空间保护力度能够实现高质量碳汇空间扩张,但需要警惕生态功能单一化风险,避免盲目追求“高碳汇系数”。3)在3种模拟情景下,大部分城镇碳汇空间结构较稳定,建议通过存量挖潜与功能置换等方式优化碳汇空间;而部分敏感型城镇则呈现差异化演变路径,需根据其具体风险类型,实施更具针对性的管控策略。【结论】快速城镇化地区碳汇空间面积虽然呈现缩减趋势,但在城镇尺度表现出稳定性与敏感性共存的特征。这一特性可通过多情景模拟研判,从而为制定差异化的城镇碳汇空间管控策略提供科学依据。
文摘大跨桥梁多模态涡激振动控制受限于传统线性吸振器的窄频特性。非线性能量阱惯容器(nonlinear energy sink inerter,NESI)结合宽频吸振与质量放大效应,具备多模态控制潜力,但其性能易受自质量、装配误差等附加位移影响。针对桥梁风致多模态涡激振动控制,提出基于NESI的控制方法。通过理论分析与数值模拟,研究了附加位移效应对NESI控制性能的影响。研究表明,附加位移导致NESI刚度与阻尼的有效参数范围偏移,引发1∶2次频率比共振,涡激振动抑制效率降低53.7%。此外,相较于阻尼比,NESI的控制性能对桥梁模态频率和初始激励幅值更为敏感。当存在附加位移时,NESI控制性能对频率比和激励幅值变化均表现出显著退化,尤其在频率比小于1区域内性能波动剧烈。进一步研究表明,适当提高质量比与惯质比虽可在一定程度上缓解附加位移带来的性能损失,但在频率比小于1的条件下仍难以实现稳定控制。
文摘非线性能量汇(nonlinear energy sink, NES)在被动控制中有着广阔的应用前景,然而这一领域的研究主要集中在单向吸振器上,这限制了其在实际应用中对多向振动的适用性。设计了一种多向NES,利用相互正交的两组钢丝绳结构,实现了单振子空间任意方向自适应吸振。基于拉格朗日方程建立了系统多向振动控制方程,采用了谐波平衡法对稳态响应进行近似解析分析,并利用四阶龙格-库塔法进行数值验证,其后研究了多向NES的减振效果。结果表明,多向单振子NES能够有效地抑制多向振动,对任意单向激励也同样有效。该研究为NES在多向振动控制中的应用及设计提供了参考。
