Study on the Seismic Behavior of a Steel Plate–Concrete Composite Shear Wall with a Fishplate Connection

The steel plate–concrete composite shear wall (SPCSW), having been widely applied to several super high-rise buildings, is currently regarded as a new type of lateral load-resisting structure. The SPCSW design does not consider the connection to the surrounding structure, normally envisaged as a buttweld connection, while the fishplate lap connection tends to be applied in construction. To explore the fishplate lap connection to achieve the performance standard of SPCSW, in this paper, an SPCSW with a fishplate connection is modeled using ABAQUS to investigate the hysteretic behavior under constant axial force and horizontal cyclic loads. Through the hysteresis curve and a load–displacement skeleton curve, the effects of fishplate thickness and lap length on its hysteretic behavior are studied. The results show that increasing the fishplate thickness contributes to a slight increase in the bearing capacity and energy dissipation and has little influence on stiffness degradation. When the fishplate thickness is more than half the steel plate thickness, the strength and energy dissipation of an SPCSW with a fishplate connection can reach the level of an SPCSW without a fishplate connection. The bearing capacity and stiffness of the SPCSW increase with the increase in lap length. When the lap length is greater than 50 mm, the strength, stiffness and energy dissipation capacity of an SPCSW with a fishplate connection are superior to those without fishplate connections. Finally, engineering suggestions on fishplate connections are put forward

Study on the Seismic Behavior of a Steel Plate–Concrete Composite Shear Wall with a Fishplate Connection

The steel plate–concrete composite shear wall (SPCSW), having been widely applied to several super high-rise buildings, is currently regarded as a new type of lateral load-resisting structure. The SPCSW design does not consider the connection to the surrounding structure, normally envisaged as a buttweld connection, while the fishplate lap connection tends to be applied in construction. To explore the fishplate lap connection to achieve the performance standard of SPCSW, in this paper, an SPCSW with a fishplate connection is modeled using ABAQUS to investigate the hysteretic behavior under constant axial force and horizontal cyclic loads. Through the hysteresis curve and a load–displacement skeleton curve, the effects of fishplate thickness and lap length on its hysteretic behavior are studied. The results show that increasing the fishplate thickness contributes to a slight increase in the bearing capacity and energy dissipation and has little influence on stiffness degradation. When the fishplate thickness is more than half the steel plate thickness, the strength and energy dissipation of an SPCSW with a fishplate connection can reach the level of an SPCSW without a fishplate connection. The bearing capacity and stiffness of the SPCSW increase with the increase in lap length. When the lap length is greater than 50 mm, the strength, stiffness and energy dissipation capacity of an SPCSW with a fishplate connection are superior to those without fishplate connections. Finally, engineering suggestions on fishplate connections are put forward

Photogrammetric UAV Mapping of Terrain under Dense Coastal Vegetation: An Object-Oriented Classification Ensemble Algorithm for Classification and Terrain Correction

Photogrammetric UAV sees a surge in use for high-resolution mapping, but its use to map terrain under dense vegetation cover remains challenging due to a lack of exposed ground surfaces. This paper presents a novel object-oriented classification ensemble algorithm to leverage height, texture and contextual information of UAV data to improve landscape classification and terrain estimation. Its implementation incorporates multiple heuristics, such as multi-input machine learning-based classification, object-oriented ensemble, and integration of UAV and GPS surveys for terrain correction. Experiments based on a densely vegetated wetland restoration site showed classification improvement from 83.98% to 96.12% in overall accuracy and from 0.7806 to 0.947 in kappa value. Use of standard and existing UAV terrain mapping algorithms and software produced reliable digital terrain model only over exposed bare grounds (mean error = −0.019 m and RMSE = 0.035 m) but severely overestimated the terrain by ~80% of mean vegetation height in vegetated areas. The terrain correction method successfully reduced the mean error from 0.302 m to −0.002 m (RMSE from 0.342 m to 0.177 m) in low vegetation and from 1.305 m to 0.057 m (RMSE from 1.399 m to 0.550 m) in tall vegetation. Overall, this research validated a feasible solution to integrate UAV and RTK GPS for terrain mapping in densely vegetated environments

Photogrammetric UAV Mapping of Terrain under Dense Coastal Vegetation: An Object-Oriented Classification Ensemble Algorithm for Classification and Terrain Correction

Photogrammetric UAV sees a surge in use for high-resolution mapping, but its use to map terrain under dense vegetation cover remains challenging due to a lack of exposed ground surfaces. This paper presents a novel object-oriented classification ensemble algorithm to leverage height, texture and contextual information of UAV data to improve landscape classification and terrain estimation. Its implementation incorporates multiple heuristics, such as multi-input machine learning-based classification, object-oriented ensemble, and integration of UAV and GPS surveys for terrain correction. Experiments based on a densely vegetated wetland restoration site showed classification improvement from 83.98% to 96.12% in overall accuracy and from 0.7806 to 0.947 in kappa value. Use of standard and existing UAV terrain mapping algorithms and software produced reliable digital terrain model only over exposed bare grounds (mean error = −0.019 m and RMSE = 0.035 m) but severely overestimated the terrain by ~80% of mean vegetation height in vegetated areas. The terrain correction method successfully reduced the mean error from 0.302 m to −0.002 m (RMSE from 0.342 m to 0.177 m) in low vegetation and from 1.305 m to 0.057 m (RMSE from 1.399 m to 0.550 m) in tall vegetation. Overall, this research validated a feasible solution to integrate UAV and RTK GPS for terrain mapping in densely vegetated environments

Analysis of progressive collapse of a super-long span latticed steel arch structure

The progressive collapse of a space grid structure which has a large number of members and a large span is the focus of current research. Before the progressive collapse of the structure, there is a problem of instability of the members. In this paper, dynamic nonlinear analysis of a super-long span latticed steel arch structure is carried out to study its progressive collapse process using a Kinematic Hardening Plasticity constitutive model compiled by Vumat material subprogram in Abaqus, which takes into account instability of the members. Differences in the dynamic response process of the structure at the collapse moment and the failure sequence of the members using the member stability model and the material failure constitutive model are compared. Compared with the material failure constitutive model, when the member stability constitutive model is used, the proportion of compressive buckling members in the structural failure is higher, and the bearing capacity of the structure is lower when the initial failure occurs. The structure suffers from localized member compressive failure rather than material yielding, which leads to the progressive collapse of the structure