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| 1 | Paraxial propagation of partially coherent Hermite-Gauss beams显示文摘 | Qiu Yunli Guo Hong Chen Zhaoxi | 2005 | Opt Commun2005，245，： | 1 |
| 2 | Paraxial propagation of partially coherent Hermite-Gauss beams显示文摘 | Qiu Yunli Guo Hong Chen Zhaoxi | 2005 | Opt Commun2005，245，1： | 1 |
| 3 | Superallowed Fermi transitions in RPA with a relativistic point-coupling energy functional显示文摘The self-consistent random phase approximation (RPA) approach with the residual interaction derived from a relativistic pointcoupling energy functional is applied to evaluate the isospin symmetry-breaking corrections δ c for the 0+ → 0+ superallowed Fermi transitions.With these δ c values,together with the available experimental f t values and the improved radiative corrections,the unitarity of the Cabibbo-Kobayashi-Maskawa (CKM) matrix is examined.Even with the consideration of uncertainty,the sum of squared top-row elements has been shown to deviate from the unitarity condition by 0.1% for all the employed relativistic energy functionals. | LI ZhaoXi YAO JiangMing CHEN Hong | 2011 | Science China(Physics,Mechanics & Astronomy)2011，54，6： | 1 |
| 4 | Paraxial propagation of partially coherent Hermite-Gauss beams显示文摘 | Qiu Yunli Guo Hong Chen Zhaoxi | 2005 | Opt Commun2005，245，16： | 1 |
| 5 | 基于TLBO算法的不确定性条件下复杂产品协同设计的可靠性拓扑优化显示文摘复杂产品的拓扑优化设计可以显著节省材料和节能,有效地降低惯性力和机械振动。本研究以一种大吨位液压机作为典型的复杂产品,用于阐述该优化方法。本文提出了一种基于可靠性与优化解耦模型和基于教学学习的优化(TLBO)算法的可靠性拓扑优化方法。将由板结构形成的支撑物作为拓扑优化对象,重量轻、稳定性好。将不确定性下的可靠性优化和结构拓扑优化协同处理。首先,利用有限差分法将优化问题中的不确定性参数修正为确定性参数。然后,将不确定性可靠性分析和拓扑优化的复杂嵌套解耦。最后,利用TLBO算法求解解耦模型,该算法参数少,求解速度快。TLBO算法采用了自适应教学因子,在初始阶段实现了更快的收敛速度,并在后期进行了更精细的搜索。本文给出了一个液压机基板结构的数值实例,说明了该方法的有效性。 | Zhaoxi Hong Xiangyu Jiang 冯毅雄 Qinyu Tian 谭建荣 | 2023 | Engineering2023，，3： | 1 |
| 6 | Paraxial prop- agation of partially coherent Hermite-Gauss beams显示文摘 | QIU Yunli GUO Hong CHEN Zhaoxi | 2005 | Opt Commun2005，245，16： | 1 |
| 7 | Construction of Human Digital Twin Model Based on Multimodal Data and Its Application in Locomotion Mode Identifcation显示文摘With the increasing attention to the state and role of people in intelligent manufacturing, there is a strong demand for human-cyber-physical systems (HCPS) that focus on human-robot interaction. The existing intelligent manufacturing system cannot satisfy efcient human-robot collaborative work. However, unlike machines equipped with sensors, human characteristic information is difcult to be perceived and digitized instantly. In view of the high complexity and uncertainty of the human body, this paper proposes a framework for building a human digital twin (HDT) model based on multimodal data and expounds on the key technologies. Data acquisition system is built to dynamically acquire and update the body state data and physiological data of the human body and realize the digital expression of multi-source heterogeneous human body information. A bidirectional long short-term memory and convolutional neural network (BiLSTM-CNN) based network is devised to fuse multimodal human data and extract the spatiotemporal features, and the human locomotion mode identifcation is taken as an application case. A series of optimization experiments are carried out to improve the performance of the proposed BiLSTM-CNN-based network model. The proposed model is compared with traditional locomotion mode identifcation models. The experimental results proved the superiority of the HDT framework for human locomotion mode identifcation. | Ruirui Zhong Bingtao Hu Yixiong Feng Hao Zheng Zhaoxi Hong Shanhe Lou Jianrong Tan | 2023 | Chinese Journal of Mechanical Engineering2023，36，5： | 0 |
| 8 | Complicated deformation simulating on temperature-driven 4D printed bilayer structures based on reduced bilayer plate model显示文摘The four-dimensional(4D) printing technology, as a combination of additive manufacturing and smart materials, has attracted increasing research interest in recent years. The bilayer structures printed with smart materials using this technology can realize complicated deformation under some special stimuli due to the material properties.The deformation prediction of bilayer structures can make the design process more rapid and thus is of great importance. However, the previous works on deformation prediction of bilayer structures rarely study the complicated deformations or the influence of the printing process on deformation. Thus, this paper proposes a new method to predict the complicated deformations of temperature-sensitive 4D printed bilayer structures,in particular to the bilayer structures based on temperature-driven shape-memory polymers(SMPs) and fabricated using the fused deposition modeling(FDM) technology. The programming process to the material during printing is revealed and considered in the simulation model. Simulation results are compared with experiments to verify the validity of the method. The advantages of this method are stable convergence and high efficiency,as the three-dimensional(3D) problem is converted to a two-dimensional(2D) problem.The simulation parameters in the model can be further associated with the printing parameters, which shows good application prospect in 4D printed bilayer structure design. | Junjie SONG Yixiong FENG Yong WANG Siyuan ZENG Zhaoxi HONG Hao QIU Jianrong TAN | 2021 | Applied Mathematics and Mechanics(English Edition)2021，42，11： | 0 |
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