• Smart Structures and Systems
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• v.23 no.4
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• pp.329-335
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• 2019

Structural fuses are made up from oriented steel plates to be used to resist seismic force with shear loading resistance capabilities. The damage and excessive inelastic deformations are concentrated in structural fuses to avoid any issues for the rest of the surrounding elements. Recently developed fuse plates are designed with engineered cutouts leaving flexural or shear links with controlled yielding features. A promising type of link is proposed to align better bending strength along the length of the link with the demand moment diagram is a butterfly-shaped link. Previously, the design methodologies are purely based on the flexural stresses, or shear stresses only, which overestimate the dampers capability for resisting against the applied loadings. This study is specifically focused on the optimized design methodologies for commonly used butterfly-shaped dampers. Numerous studies have shown that the stresses are not uniformly distributed along the length of the dampers; hence, the design methodology and the effective implementation of the steel need revisions and improvements. In this study, the effect of shear and flexural stresses on the behavior of butterfly-shaped links are computationally investigated. The mathematical models based on von-Mises yielding criteria are initially developed and the optimized design methodology is proposed based on the yielding criterion. The optimized design is refined and investigated with the aid of computational investigations in the next step. The proposed design methodology meets the needs of optimized design concepts for butterfly-shaped dampers considering the uniform stress distribution and efficient use of steel.

• Steel and Composite Structures
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• v.42 no.4
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• pp.539-552
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• 2022

Concentrically braced frames (CBFs) possess high stiffness and strength against lateral loads; however, they suffer from low energy absorption capacity against seismic loads due to the susceptibility of CBF diagonal elements to bucking under compression loading. To address this problem, in this study, an innovative damper was proposed and investigated experimentally and numerically. The proposed damper comprises main plates and includes a flange plate angled at θ and a trapezius-shaped web plate surrounded by the plate at the top and bottom sections. To investigate the damper behaviour, dampers with θ = 0°, 30°, 45°, 60°, and 90° were evaluated with different flange plate thicknesses of 10, 15, 20, 25 and 30 mm. Dampers with θ = 0° and 90° create rectangular-shaped and I-shaped shear links, respectively. The results indicate that the damper with θ = 30° exhibits better performance in terms of ultimate strength, stiffness, overstrength, and distribution stress over the damper as compared to dampers with other angles. The hysteresis curves of the dampers confirm that the proposed damper acts as a ductile fuse. Furthermore, the web and flange plates contribute to the shear resistance, with the flange carrying approximately 80% and 10% of the shear force for dampers with θ = 30° and 90°, respectively. Moreover, dampers that have a larger flange-plate shear strength than the shear strength of the web exhibit behaviours in linear and nonlinear zones. In addition, the over-strength obtained for the damper was greater than 1.5 (proposed by AISC for shear links). Relevant relationships are determined to predict and design the damper and the elements outside it.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.980-998
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• 2023

In Low Earth Orbit (LEO) satellite networks, satellites operate fast and the inter-satellite link change period is short. In order to sense the spectrum state in LEO satellite networks in real-time, a space-based satellite network intelligent spectrum sensing algorithm based on artificial neural network (ANN) is proposed, while Geosynchronous Earth Orbit (GEO) satellites are introduced to make fast and effective judgments on the spectrum state of LEO satellites by using their stronger arithmetic power. Firstly, the visibility constraints between LEO satellites and GEO satellites are analyzed to derive the inter-satellite link building matrix and complete the inter-satellite link situational awareness. Secondly, an ANN-based energy detection (ANN-ED) algorithm is proposed based on the traditional energy detection algorithm and artificial neural network. The ANN module is used to determine the spectrum state and optimize the traditional energy detection algorithm. GEO satellites are used to fuse the information sensed by LEO satellites and then give the spectrum decision, thereby realizing the inter-satellite spectrum state sensing. Finally, the sensing quality is evaluated by the analysis of sensing delay and sensing energy consumption. The simulation results show that our proposed algorithm has lower complexity, the sensing delay and sensing energy consumption compared with the traditional energy detection method.

• Earthquakes and Structures
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• v.15 no.6
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• pp.667-685
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• 2018

In eccentrically braced steel frames (EBFs), the links are fuse members which enter inelastic phase before other structure members and dissipate the seismic energy. Based on the force-based seismic design method, damages and plastic deformations are limited to the links, and the main structure members are required tremendous sizes to ensure elastic with limited or no damage. Force-based seismic design method is very common and is found in most design codes, it is unable to determine the inelastic response of the structure and the damages of the members. Nowadays, methods of seismic design are emphasizing more on performance-based seismic design concept to have a more realistic assessment of the inelastic response of the structure. Links use ordinary steel Q345 (the nominal yielding strength $f_y{\geq}345MPa$) while other members use high strength steel (Q460 $f_y{\geq}460MPa$ or Q690 $f_y{\geq}690MPa$) in eccentrically braced frames with high strength steel combination (HSS-EBFs). The application of high strength steels brings out many advantages, including higher safety ensured by higher strength in elastic state, better economy which results from the smaller member size and structural weight as well as the corresponding welding work, and most importantly, the application of high strength steel in seismic fortification zone, which is helpful to popularize the extensive use of high strength steel. In order to comparison seismic behavior between HSS-EBFs and ordinary EBFs, on the basis of experimental study, four structures with 5, 10, 15 and 20 stories were designed by PBSD method for HSS-EBFs and ordinary EBFs. Nonlinear static and dynamic analysis is applied to all designs. The loading capacity, lateral stiffness, ductility and story drifts and failure mode under rare earthquake of the designs are compared. Analyses results indicated that HSS-EBFs have similar loading capacity with ordinary EBFs while the lateral stiffness and ductility of HSS-EBFs is lower than that of EBFs. HSS-EBFs and ordinary EBFs designed by PBSD method have the similar failure mode and story drift distribution under rare earthquake, the steel weight of HSS-EBFs is 10%-15% lower than ordinary EBFs resulting in good economic efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4892-4911
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• 2015

Trust as one of important social relations has attracted much attention from researchers in the field of social network-based recommender systems. In trust network-based recommender systems, there exist normally two roles for users, truster and trustee. Most of trust-based methods generally utilize explicit links between truster and trustee to find similar neighbors for recommendation. However, there possibly exist implicit correlations between users, especially for users with the same role (truster or trustee). In this paper, we propose a novel Collaborative Filtering method called CF-TC, which exploits Trust Context to discover implicit correlation between users with the same role for recommendation. In this method, each user is first represented by the same-role users who are co-occurring with the user. Then, similarities between users with the same role are measured based on obtained user representation. Finally, two variants of our method are proposed to fuse these computed similarities into traditional collaborative filtering for rating prediction. Using two publicly available real-world Epinions and Ciao datasets, we conduct comprehensive experiments to compare the performance of our proposed method with some existing benchmark methods. The results show that CF-TC outperforms other baseline methods in terms of RMSE, MAE, and recall.