UHPC-PINN-parallel micro element system for the local bond stress–slip model subjected to monotonic loading

Pishro, Ahad Amini; Zhang, Zhengrui; Pishro, Mojdeh Amini; Feng, Xinliang; Zhang, Lili; Yang, Qihong; Matlan, Siti Jahara

doi:10.1016/j.istruc.2022.10.053

Cited by 12 publications

(4 citation statements)

References 29 publications

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“…The application of finite element analysis in structural engineering, with special attention to its application in reinforced concrete and steel structures, is exemplified in various studies. For example, Ahad investigated the parallel micro-element system (PMES) on the local bond stress-slip (LBSS) relationship at the steel bar-UHPC interface subjected to monotonic loading [5]. Amini Pishro A. et al adopted the multiple linear regression (MLR) method to give the LBS equation of reinforced UHPC structural members [6].…”

Section: Project Overviewmentioning

confidence: 99%

Comparison and Selection of Multiple Construction Schemes for the Large-Span and Heavy-Load Transfer Truss

Lan,

Xing,

Qin

et al. 2023

Buildings

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The main building of Zone II of Zhanjiang Bay Laboratory R&D Building adopts a steel frame–core tube shear wall structure system, with a 53.4 m large-span and heavy-load-transfer truss on the fourth floor. In order to propose the optimal construction and installation scheme for the large-span and heavy-load-transfer truss, the simplified model, single model, and 3D model are utilized to compare Scheme 1 with rigid connection and Scheme 2 with elastic connection and rigid connection. After completing the construction of the underground layer and towers on both sides, in Scheme 1, the fourth-floor transfer truss is directly connected to the towers on both sides in a rigid manner. Subsequently, the support at the bottom of the transfer truss is removed, allowing for layer-by-layer construction. The transfer truss remains rigidly connected to both side towers throughout. On the other hand, in Scheme 2, initially, the transfer truss is connected to both side towers through upper chords and diagonal bars before being constructed upwards until reaching the sixth floor. Once formed as a whole with two floors above using large diagonal tie rods, lower chords of the large-span and heavy-load-transfer truss are then connected with another diagonal bar to establish a rigid connection between the transfer truss and towers; thereafter, upward construction continues. Following completion of constructing a seven-story large diagonal tie rod, whereupon removal of support at the bottom of the conversion truss occurs, subsequent layer-by-layer construction takes place accordingly. It has been observed that employing Scheme 2 can enhance stress distribution within core barrel shear walls as well as transfer trusses while ensuring deflection and stress levels meet requirements for the large-span and heavy-load-transfer truss, thereby rendering structural stress more rationalized, leading to significantly improved overall safety.

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Section: Project Overviewmentioning

confidence: 99%

Comparison and Selection of Multiple Construction Schemes for the Large-Span and Heavy-Load Transfer Truss

Lan,

Xing,

Qin

et al. 2023

Buildings

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“…Amini et al [20] stated that the addition of nano-silica to UHPC increased its compressive strength. Amini et al [20,24] also experimentally and numerically studied the local bond stress between UHPC and steel rebars and concluded that the addition of micro-silica increased the local bond stress. The UHPC flexural tensile strength can reach 45 MPa according to Walraven [25], and its post-cracking tension strength varies from 5.6 to 9.0 MPa for fiber volumes between 0.8% and 1.6%, respectively [25].…”

Section: Introductionmentioning

confidence: 99%

Design Recommendations for Columns Made of Ultra-High-Performance Concrete and NiTi SMA Bars

et al. 2023

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The use of new materials in construction endows structures with better mechanical characteristics. The combination of ultra-high-performance concrete (UHPC) and nickel and titanium (NiTi) shape memory alloy (SMA) improves the behavior of building structures by increasing both their ductility and dissipation energy due to the low-damage and self-centering properties of NiTi SMA. Since UHPC and NiTi SMA are expensive materials and still scarce in distribution channels, this article tries to offer design recommendations to reduce the length of the column-beam connection in which these new materials should be introduced, leaving the rest of the column with conventional materials. To achieve this, a nonlinear static pushover analysis of columns using finite element software, SeismoStruct, was performed. This model was calibrated using experimental results. Next, a parametric analysis was carried out to propose the design recommendations. Results indicated that an adequate design for the column–beam connection, considering both economy and performance, should include a main zone with UHPC and SMA reinforcements, a transition zone with UHPC and steel reinforcements, and another zone with conventional reinforced concrete. The transition zone improved the hybrid column’s performance without excessively raising the cost. The main zone length, the transition zone length, and the strength of the concrete in the rest of the column must be determined to ensure that the critical section of the column was in the main zone to develop the maximum strength and ductility. The length of the main zone depended on the compressive strength of the conventional concrete, the relative axial load of the column, and the required ductility.

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“…These developments include a wide range of civil engineering domains such as geotechnical [4,5] and water [6,7] analysis. Focusing on the structural aspects of this field, engineers have benefitted from various technologies and simulation tools for analyzing the behavior of structures (and their particular elements) [8][9][10] under different loading conditions [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Estimating the Concrete Ultimate Strength Using a Hybridized Neural Machine Learning

Zhang

2023

Buildings

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Concrete is a highly regarded construction material due to many advantages such as versatility, durability, fire resistance, and strength. Hence, having a prediction of the compressive strength of concrete (CSC) can be highly beneficial. The new generation of machine learning models has provided capable solutions to concrete-related simulations. This paper deals with predicting the CSC using a novel metaheuristic search scheme, namely the slime mold algorithm (SMA). The SMA retrofits an artificial neural network (ANN) to predict the CSC by incorporating the effect of mixture ingredients and curing age. The optimal configuration of the algorithm trained the ANN by taking the information of 824 specimens. The measured root mean square error (RMSE = 7.3831) and the Pearson correlation coefficient (R = 0.8937) indicated the excellent capability of the SMA in the assigned task. The same accuracy indicators (i.e., the RMSE of 8.1321 and R = 0.8902) revealed the competency of the developed SMA-ANN in predicting the CSC for 206 stranger specimens. In addition, the used method outperformed two benchmark algorithms of Henry gas solubility optimization (HGSO) and Harris hawks optimization (HHO) in both training and testing phases. The findings of this research pointed out the applicability of the SMA-ANN as a new substitute to burdensome laboratory tests for CSC estimation. Moreover, the provided solution is compared to some previous studies, and it is shown that the SMA-ANN enjoys higher accuracy. Therefore, an explicit mathematical formula is developed from this model to provide a convenient CSC predictive formula.

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UHPC-PINN-parallel micro element system for the local bond stress–slip model subjected to monotonic loading

Cited by 12 publications

References 29 publications

Comparison and Selection of Multiple Construction Schemes for the Large-Span and Heavy-Load Transfer Truss

Comparison and Selection of Multiple Construction Schemes for the Large-Span and Heavy-Load Transfer Truss

Design Recommendations for Columns Made of Ultra-High-Performance Concrete and NiTi SMA Bars

Estimating the Concrete Ultimate Strength Using a Hybridized Neural Machine Learning

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