48,208 research outputs found
A network-based approach to improving robustness of a high-speed train by structure adjustment
No full textTo enhance the ability of a high-speed train (HST) to provide services under various adverse conditions, this paper studies robustness improvement of the HST by adjusting its structure. We model the HST as an interdependent machine-electricity-communication network (IMECN) composed of a machine network (MN), an electricity network (EN) and a communication network (CN), and propose a robustness metric of the IMECN subject to node failures considering failure propagation. Then, a robustness optimization model is constructed for structure adjustment. A Tabu search algorithm with directed and undirected edge exchange operators is designed to solve this problem. A case study on a practical HST is used to verify the feasibility and effectiveness of the proposed method. The results show that robustness of the IMECN is significantly improved by structure adjustment. Furthermore, most nodes have little effect on robustness, and impact of failures on any node is minimized after optimization. In addition, in terms of topology, nodes with low and high degrees in the MN and CN reconnect with those with a similar degree, their clustering coefficients become larger, and closeness of all nodes in the subnetworks increases. Finally, adjusting the structures leads to a slight difference of loads in the EN and CN
A DYNAMIC MULTI-SOURCE INFORMATION FUSION FRAMEWORK FOR MECHANICAL FAULT DIAGNOSIS
No full textDeep learning methods for fault diagnosis play a critical role in the monitoring and detecting operating conditions of the mechanical equipment. However, the most existing studies are accompanied by single-source sensor and data features, which make them unsuitable for the complex and harsh real-world factory environments. In this paper, we propose a dynamic feature fusion framework based on graph convolutional networks under multi-source information named DF2GCNs. First, we extract multi-source features from raw multi-source signals through the convolutional neural networks. Then, we design a dynamic weighted factor to achieve more effective fusion between the extracted features. After that, the fused features are input to a graph construction module to construct graph topology. Moreover, we utilize the graph convolutional networks to not only extract latent features but also mine the relationships between multiple features to enrich fault-related representations. Finally, Comprehensive experiments on a multi-source test bench demonstrate DF2GCNs outperforms the state-of-the-art (SOTA) methods, striking a good trade-off between diagnostic performance and robustness
A multi-objective optimization model for identifying groups of critical elements in a high-speed train
No full textThis paper proposes a multi-objective optimization-based approach to identify critical elements, including units and interactions within and between systems, in a high-speed train (HST). In the framework, network theory is used to model the HST as an interdependent machine-electricity-communication network (IMECN) composed of a machine network (MN), an electricity network (EN) and a communication network (CN). Cascading failure models for the subnetworks and IMECN, and topological and functional metrics for robustness are developed. We then formulate a multi-objective optimization model for maximizing the impact of the failure of critical elements on the topological and functional robustness of the IMECN and minimizing their number. We use NSGA-II to solve the optimization problem. Considering a practical HST as a case study, we apply the multi-objective optimization framework to search the groups of critical nodes, intra-links and inter-links. The results show that critical nodes, intra-links and inter-links of the IMECN are within the MN and CN. In particular, end nodes of the critical intra-links and inter-links may also be critical, and the critical elements of subnetworks tend to also be critical for the IMECN. In addition, we find that the critical nodes, intra-links and inter-links are not related to their topological importance
Risk assessment of e-waste - Liquid Crystal Monomers re-suspension caused by coastal dredging operations
No full textThe Pearl River Estuary (PRE), one of the primary e-waste recycling centers in the world, has been suffering from the pollution of Liquid Crystal Monomers (LCMs), critical materials with persistent, bio-accumulative, and toxic substances used in electronic devices. It has been detected in seabed sediment with both high frequency and concentration near PRE - Hong Kong (HK) waters. In the same area, dredging operations with in-situ sediment have been frequently used in the last decades for coastal land reclamation projects. Dredging is known to cause a huge amount of sediment re-suspension into water columns, with potential damage to marine ecosystems and biodiversity. In this study, we proposed a new risk assessment strategy to estimate the secondary pollution due to the re-suspension sediment highly contaminated by LCMs. We formulate a robust and reliable probabilistic approach based on unsupervised machine learning and hydrodynamic and sediment transport numerical simulation. New risk indexes were also proposed to better quantify the impact of contaminated sediments. We applied the methodology to assess the potential impact of dredging operations in the PRE and Hong Kong waters on the local marine ecosystem. The results of the analysis showed how the potentially contaminated areas depended on the dredging locations
Sparse Array Design via Integer Linear Programming
No full textIn this paper, a design framework based on integer linear programming is proposed for optimizing sparse array structures. We resort to binary vectors to formulate the design problem for non-redundant arrays (NRA) and minimum-redundant arrays (MRA). The flexibility of the proposed framework allows for dynamic adjustment of constraints to meet various applicative requirements, e.g., to achieve desired array apertures and mitigate mutual coupling effects. The proposed framework is also extended to the design of high-order arrays associated by exploiting high-order cumulants. The effectiveness of the proposed sparse array design framework is investigated through extensive numerical analysis. A comparative analysis with closed-form solutions and integer linear programming-based array design methods confirms the superiority of the proposed design framework in terms of number of degrees of freedom (DOF) and direction of arrival (DOA) estimation accuracy
Synthesis and Design of Quasi-Canonical Planar Filters Comprising Cascaded Frequency-Variant Blocks
No full textThis article discusses the synthesis of a new class of cross-coupled blocks incorporating frequency-variant couplings, that is, the frequency-variant blocks (FVBs), and their planar implementations based on an analytical approach. The proposed FVBs require fewer coupling elements with regard to traditional blocks, while can realize a quasi-canonical characteristic (i.e., realizing k -1 transmission zeros for a block of k th order). Derivation of the FVBs relies on a uniform synthesis process, where each transformation is mathematically simplified as a non-reciprocal matrix. An N th-order quasi-canonical filter (possessing either symmetric or asymmetric TZs) can thereafter be synthesized by properly cascading the FVBs. Moreover, a unique planar technique is introduced to construct the quasi-canonical filters (with TZs above passband) using parallel-coupled microstrips, where a complete design procedure from synthesis to circuit parameters will be given. Validity of this work is eventually demonstrated by three illustrative examples, whose synthesis, simulation, and test results perform desired responses and are well-matched with each other
Advanced Direct Synthesis Approach for High Selectivity In-Line Topology Filters Comprising N - 1 Adjacent Frequency-Variant Couplings
No full textIn this paper, a direct synthesis approach is presented to realize high selectivity in-line topology filters with adjacent frequency-variant couplings (FVCs). By considering the annihilation of frequency-variant elements during admittance matrix transformation for the first time, this paper provides a deterministic mechanism (no optimization is involved) that can generate FVCs between every two cascaded resonators. In consequence, a high selectivity filtering response where N-1 transmission zeros are implemented and independently controllable can be achieved for an Nth-order in-line network. As the foundation, a novel matrix process is detailed to obtain two adjacent FVCs inside of a 4th-order in-line network. The Nth-order prototype is then realized based on the process in an iterative manner. A synthesis example is illustrated in terms of the proposed approach step by step to show validity. Eventually, a 6th-order in-line band-pass filter, which contains adjacent FVCs in two pairs has been designed and fabricated via coaxial cavity structures. The synthesis results, EM simulation results, and tested results are well matched with each other, which reveals the effectiveness of the presented method during physical implementation
Exploring Environmental Collaboration and Greenwashing in Construction Projects: Integrative Governance Framework
No full textEnvironmental collaboration between organizations involved in construction projects enables the efficiency of environmental management to gain environmental sustainability. Yet, in many projects, this collaboration is gamed promoting contractor greenwashing behavior, thereby diminishing the effectiveness of environmental management. What is unclear are the underpinning mechanisms to concurrently increase environmental collaboration and decrease contractor greenwashing behavior in construction projects. We used an integrated theoretical framework based on social exchange theory and transaction cost economics to evaluate the potential linear, curvilinear, and combined influence of interorganizational trust and formal contracts on environmental collaboration and contractor greenwashing behavior. Drawing evidence from questionnaire surveys, we find that two categories of interorganizational trust yield positive impacts on environmental collaboration and different curvilinear impacts on greenwashing behavior. Two categories of formal contracts exert an inverted U-shaped effect on environmental collaboration and heterogeneous effects on greenwashing behavior. We also find that formal contracts negatively moderate the effects of interorganizational trust on environmental collaboration, and interorganizational trust negatively moderates the impact of formal contracts on greenwashing. We provide novel insights into the interorganizational governance mechanisms regarding greenwashing in construction projects relevant for construction managers concerned with the environmental efficiency-effectiveness
High Crystal Quality 2D Manganese Phosphorus Trichalcogenide Nanosheets and their Photocatalytic Activity
No full textTransition metal phosphorus trichalcogenides (MPX3, X = S, Se) are layered materials possessing high chemical diversity and wide range of applications in a broad wave length spectrum. Theoretical studies reveal that auspicious activity of photocatalytic water splitting can be realized from them. However, experimental efforts have so far been challenged with the synthesis bottleneck. Described herein is the general chemical vapor deposition (CVD) growth method and photocatalytic activity of these materials. A novel route to systematically grow MnPX3 nanosheets on flexible carbon fiber substrate is reported. The temperature profile of the CVD process is carefully optimized that confer a facile and successful conversion of oxide precursor to phospho-trichalcogenide with high crystallinity. Moreover, the obtained manganese-based phosphorus trichalcogenide nanosheets demonstrate promising activity in sacrificial agent-free photocatalytic water splitting under simulated solar light (AM 1.5G). This study provides a significant stepping stone in exploring the fascinating world of functional 2D materials and pursuing performance enhancement
Lateral performance of midply wood shear walls with anchor tie-down system: Experimental investigation and numerical simulation
No full textThis paper presents experimental and numerical studies on the lateral performance of midply wood shear walls. A kind of anchor tie-down system (ATS) is introduced into the wood shear wall, and two different wall-foundation connections (i.e., screwed connection and bolted connection) are considered. Reserved cyclic loading tests were conducted to investigate the failure modes, lateral load resisting capacity, stiffness degradation, and energy dissipation of four midply wood shear wall specimens. Test results show that with the installation of ATS, the lateral load resisting capacity, energy dissipation, and lateral stiffness of the specimen increased by 154%, 427%, and 93%, respectively. The pull-out failure of the wall studs was also avoided with the application of ATS. Compared with the midply wood shear wall specimens with bolted wall-foundation connection, the specimens with screwed wall-foundation connection dissipated more energy; however, the fatigue failure of the screws might lead to brittle failure of the shear wall. A nonlinear finite element model of the midply wood shear wall was then developed and verified with the test results. User-defined Q-pinch model was applied to simulate the sheathing-framing connection of the shear wall. The simulation results show that the hysteretic behavior of the specimen with ATS was well predicted. The experimental and numerical studies provide fundamental knowledge for the development and application of midply wood shear walls, especially for the application of such wall system into mid-rise timber structures
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