Eccentrically braced frames (EBFs) have good elastic stiffness, while semirigid joints can provide greater ductility and make all components easy to fabricate. With application of semirigid connections to EBFs, a seismic structure can be formed. After earthquake, damaged components can be easily replaced, and repair costs and maintenance time can be reduced. In order to study the seismic performance of this type of structure, four single‐story plane specimens were tested under low‐cycle cyclic loads. Also, a total of 7 EBF models were investigated through three‐dimensional, nonlinear finite element analysis. Good agreement is achieved between the simulation and experimental results. The results show that the failure modes of the EBFs with semirigid connections are the fracture at link end plate connection, and no obvious buckling deformation and cracks occur in the other components. The EBFs with semirigid connections exhibit good inelastic rotation ability, and the inelastic rotation of all specimens and models exceeds the limit of 2016 AISC specification. Due to the slip between members, the hysteretic curves of those new structures show different degrees of pinching phenomenon and it becomes more obvious with the increase of the length of links. By analyzing the strain of the bolts, it is found that the bolt strains of the joints of link‐to‐beam are the highest, while the bolt strains of the joints of beam‐to‐column and column‐to‐brace are smaller. This structure system shows higher energy dissipation capacity and good economic benefits.

Transfer learning (TL) has demonstrated effective application in diagnosing bearing faults under varying operating conditions. The current TL methods achieve domain alignment by minimizing the variation in the marginal distribution of data between the source and target domains in the feature space. However, this approach yields incomplete similarity, leading to domain shift and a decrease in diagnostic performance. To overcome this problem, this paper proposes a new distance-guided domain adaptation method that consists of two modules: deep domain adaptive correlation alignment (Deep CORAL) combined with joint maximum mean discrepancy (JMMD) for guided domain adaptation. Deep CORAL employs nonlinear transformations to synchronize second-order statistical correlations across source and target domains, thus ensuring feature-level alignment between these domains. JMMD is utilized to align the joint distribution of input features and output labels within the activation layer in the deep network, thereby bolstering domain alignment. Building on this, we propose a network structure that merges ResNet and bidirectional long short-term memory, powered by wavelet kernels, serving as a feature extractor. This structure is designed to learn domain-invariant features and incorporates attention mechanisms to amplify important information while diminishing the impact of redundant data. An analysis of bearing experiments is used to demonstrate the effectiveness of this method, and the proposed method significantly outperforms several popular methods in diagnostic performance.

This study presents a new GFRP pipe structure fabricated by a combination of continuous and spacing arrangement of filament winding, where the latter was used to form the stiffened part and the former to form the structural part. Results of comparative analysis through a series of flatwise compression tests indicate that, with the same material consumptions, up to 38.7% increase in ring stiffness was achieved by the stiffened outer pipes with diameter of 400 mm, compared with the plain ones. The failure mode of this proposed pipe is ductile fracture during the loading process, and its bearing capacity did not decrease rapidly after fiber failure. The stiffened inner pipes with diameter of 500 mm exhibited an average of 16.7% increase in ring stiffness compared with the plain ones, while both types of specimens showed the same failure mode with delamination occurring between the stiffened layer and outer structural layer. From the experimental investigation, it is concluded that suitable geometric shape can significantly improve the ring stiffness of the specimens, which provides a guidance for structural design of pipelines and their geometric optimization.

Prefabricated steel structure is a type of green building, which conforms to the development process of building industrialization. The hysteretic behavior, bearing capacity, rotational capacity and energy dissipation of semi-rigid joint and eccentric supports of beam and column are being summarized. At present, there are few researches on the aseismic performance and failure mechanism of beam column semi-rigid connection applied to eccentrically support steel frames.

Due to the high corrosion and chemical resistance, the fiber reinforced polymer( FRP) materials are increasingly being used for the tall slender thin-walled structure, such as smoking desulfuration absorber tower. The properties of this slender fiber reinforced polymer absorber tower are: the aspect ratio is 2.5 and the ratio of the wall thickness to its radius is taken to be 0.0038. So the seismic analysis is required and important. Response spectrum theory is one of the primary approaches in structure seismic analysis. ANSYS codes are employed to investigate the tower's dynamic characteristics and seismic responses. The liquid mass in the absorber tower is modelled as lumped masses referred as sloshing mass and rigid mass. The multi-dimensional seismic response of tower is obtained using the modal superposition technique. The results demonstrate that the strength and stiffness of the absorber tower meet the requirements of code for seismic design of tower. The bottom bolts also meet the strength requirements under 9 degree seismic fortification intensity.