基于粒子群算法的劣化桥面铺装多目标组合维护策略优化研究

发展了维护导致的间接维护成本改进模型,基于改进的桥面铺装劣化模型推导了在组合维护策略下其状态指标评估公式,建立了多目标组合维护优化模型.使用自适应粒子群优化算法,根据寿命期内维护成本现值最小化和状态指标最大化的原则,满足性能要求和预算限制约束下,优化出寿命期内成本和性能都满足要求的维护策略.以劣化水泥混凝土桥面铺装为数...     

Continuously Tunable Wettability by Using Surface Patterned Shape Memory Polymers with Giant Deformability

Designing smart surfaces with tunable wettability has drawn much attention in recent years for academic research and practical applications. Most of the previous methods to achieve such surfaces demand some particular materials that inherently have special features or complicated structures which are usually not easy to obtain. A novel strategy to achieve such smart surfaces is proposed by using the surface patterned shape memory polymers of chemically crosslinked polycyclooctene which shows a giant deformability of up to ≈730% strain. The smart surfaces possess the ability to continuously tune the wettability by controlling the recovery temperature and/or time. Coating the modified titanium dioxide nanoparticles onto such surfaces renders the surface superhydrophobicity and expands the tunable range of contact angles (CAs). Theoretical calculations of the CAs at different strains via modified Cassie model well explain the tunable wettability behaviors of such smart surfaces.     

High‐Performance Water Electrolysis System with Double Nanostructured Superaerophobic Electrodes

Catalysts screening and structural optimization are both essential for pursuing a high‐efficient water electrolysis system (WES) with reduced energy supply. This study demonstrates an advanced WES with double superaerophobic electrodes, which are achieved by constructing a nanostructured NiMo alloy and NiFe layered double hydroxide (NiFe‐LDH) films for hydrogen evolution and oxygen evolution reactions, respectively. The superaerophobic property gives rise to significantly reduced adhesion forces to gas bubbles and thereby accelerates the hydrogen and oxygen bubble releasing behaviors. Benefited from these metrics and the high intrinsic activities of catalysts, this WES affords an early onset potential (≈1.5 V) for water splitting and ultrafast catalytic current density increase (≈0.83 mA mV^?1), resulting in ≈2.69 times higher performance compared to the commercial Pt/C and IrO₂/C catalysts based counterpart under 1.9 V. Moreover, enhanced performance at high temperature as well as prominent stability further demonstrate the practical application of this WES.     

基于线性插值的模糊控制

提出一种基于线性插值思想的模糊推理方法 ,该算法很好地解决了传统模糊控制的不足 ,消除了传统模糊控制的继电器特性 ,解决了控制规则数与实时性之间的矛盾。作出了该推理方法的控制曲面 ,并对两种推理方法的控制效果进行了计算机仿真。最后进行了理论解释。     

Constructing Facial Identity Surfaces for Recognition

We present a novel approach to face recognition by constructing facial identity structures across views and over time, referred to as identity surfaces, in a Kernel Discriminant Analysis (KDA) feature space. This approach is aimed at addressing three challenging problems in face recognition: modelling faces across multiple views, extracting non-linear discriminatory features, and recognising faces over time. First, a multi-view face model is designed which can be automatically fitted to face images and sequences to extract the normalised facial texture patterns. This model is capable of dealing with faces with large pose variation. Second, KDA is developed to compute the most significant non-linear basis vectors with the intention of maximising the between-class variance and minimising the within-class variance. We applied KDA to the problem of multi-view face recognition, and a significant improvement has been achieved in reliability and accuracy. Third, identity surfaces are constructed in a pose-parameterised discriminatory feature space. Dynamic face recognition is then performed by matching the object trajectory computed from a video input and model trajectories constructed on the identity surfaces. These two types of trajectories encode the spatio-temporal dynamics of moving faces.     

Quick segmentation for complex curved surface with local geometric feature based on IGES and Open CASCADE

Complex curved surface parts with local geometric feature are usually critical parts in high-end equipments. However, the processing for this kind of parts is usually difficult or inefficient due to the adoption of difficult-to-machine material and special structure. Current approaches cannot satisfy the rapid development of high-end equipments. Due to the existence of the local geometric feature for the parts, processing such parts with constant machining parameters is less applicative, restricting the improvement of machining efficiency. By separating the local geometric feature and generating tool path for the local geometric feature and the remaining processing area separately, the more efficient machining with variable machining parameters will be obtained for the complex curved surface with local geometric feature. In this way, the quick segmentation for the complex curved surface with local geometric feature is of great importance to the NC machining with variable machining parameters for this kind of parts, and a quick segmentation system is developed based on Initial Graphics Exchange Specification (IGES) and Open CASCADE (OCC) platform in this study. The complex curved surface model in IGES format is firstly imported into the system and then trimmed into independent surface patches. After computing the feature size of each surface patch, the segmentation for the complex curved surface is achieved by sorting and classifying the surface patches according to their feature sizes. Taking the whole impeller with small splitter blades for an example, the experimental result shows that the segmentation of small splitter blades from the whole impeller is successful and a serialized processing program could be generated, and then the whole impeller could be machined precisely and efficiently with NC equipment. In the machining experiment, it is proved that the machining with various machining parameters can improve the efficiency by 28.18% in the comparison experiment, 20.14% and 12.33% in the estimation. The research provides an important foundation for the high quality and more efficient machining of the complex curved surface with local geometric feature.     

曲面的自适应三角网格剖分

在传统的映射法基础上 ,采用自适应三角网格加密法能有效地处理带有特征约束条件的任意曲面的三角剖分问题 .在平面三角化算法中对环边统一处理 ,并且采取了一种简单有效的曲率估算方法 ,提高了运行效率 ;并在保持外观的基础上进行了网格质量的优化     

Implementation of a crack propagation constraint within a structural optimization software

A crack propagation constraint related to the stress intensity factor is examined for the minimum-weight design optimization of a composite blade-stiffened panel. A low-fidelity approach uses a closed-form solution for the stress intensity factor, while a high-fidelity approach uses the stress distribution around the crack. Structural optimizations are performed by low- and high-fidelity approaches for a number of panels configured with different values of the load, crack length, and blade height. Response surface (RS) approximations are then constructed for the optimal weight as a function of the three configuration variables. The computational cost, numerical noise, and accuracy for the two approaches are compared. An additional constraint in the low-fidelity solutions is found to be active for some of the configurations, increasing the difference between the low-fidelity and high-fidelity optima. It is shown that outlier analysis helps to identify the configurations with the largest difference.     

基于映射法的曲面自适应网格生成

板壳成形数值模拟过程中用自适应网格不仅可以实现以尽可能少的计算量获得指定精度要求的解,更重要的是可以提高解的精度。而曲面自适应网格自动生成技术国内外都刚开始研究,目前没有很好的方法。本文首次基于映射法在参数区域生成自适应网格,然后映射到空间,用空间曲面的曲率及有限元计算误差估计来控制参数区域中的自适应网格生成。数值例子验证了本算法的正确性及可靠性。