Flat slab system is becoming widely popular for multistory buildings due to its several advantages. However, the performance of flat slab buildings under earthquake loading is unsatisfactory due to their vulnerability...Flat slab system is becoming widely popular for multistory buildings due to its several advantages. However, the performance of flat slab buildings under earthquake loading is unsatisfactory due to their vulnerability to punching shear failure. Several national design codes provide guidelines for designing flat slab system under gravity load only. Nevertheless, flat slab buildings are also being constructed in high seismicity regions. In this paper, performance of flat slab buildings of various heights, designed for gravity load alone according to code, is evaluated under earthquake loading as per ASCE/SEI 41 methodology. Continuity of slab bottom reinforcement through column cage improves the performance of flat slab buildings to some extent, but it is observed that these flat slab systems are not adequate in high seismicity areas and need additional primary lateral load resisting systems such as shear walls. A displacement-based method is proposed to proportion shear walls as primary lateral load resisting elements to ensure satisfactory performance. The methodology is validated using design examples of flat slab buildings with various heights.展开更多
Classification systems such as Slope Mass Rating(SMR) are currently being used to undertake slope stability analysis. In SMR classification system, data is allocated to certain classes based on linguistic and experien...Classification systems such as Slope Mass Rating(SMR) are currently being used to undertake slope stability analysis. In SMR classification system, data is allocated to certain classes based on linguistic and experience-based criteria. In order to eliminate linguistic criteria resulted from experience-based judgments and account for uncertainties in determining class boundaries developed by SMR system,the system classification results were corrected using two clustering algorithms, namely K-means and fuzzy c-means(FCM), for the ratings obtained via continuous and discrete functions. By applying clustering algorithms in SMR classification system, no in-advance experience-based judgment was made on the number of extracted classes in this system, and it was only after all steps of the clustering algorithms were accomplished that new classification scheme was proposed for SMR system under different failure modes based on the ratings obtained via continuous and discrete functions. The results of this study showed that, engineers can achieve more reliable and objective evaluations over slope stability by using SMR system based on the ratings calculated via continuous and discrete functions.展开更多
文摘Flat slab system is becoming widely popular for multistory buildings due to its several advantages. However, the performance of flat slab buildings under earthquake loading is unsatisfactory due to their vulnerability to punching shear failure. Several national design codes provide guidelines for designing flat slab system under gravity load only. Nevertheless, flat slab buildings are also being constructed in high seismicity regions. In this paper, performance of flat slab buildings of various heights, designed for gravity load alone according to code, is evaluated under earthquake loading as per ASCE/SEI 41 methodology. Continuity of slab bottom reinforcement through column cage improves the performance of flat slab buildings to some extent, but it is observed that these flat slab systems are not adequate in high seismicity areas and need additional primary lateral load resisting systems such as shear walls. A displacement-based method is proposed to proportion shear walls as primary lateral load resisting elements to ensure satisfactory performance. The methodology is validated using design examples of flat slab buildings with various heights.
文摘Classification systems such as Slope Mass Rating(SMR) are currently being used to undertake slope stability analysis. In SMR classification system, data is allocated to certain classes based on linguistic and experience-based criteria. In order to eliminate linguistic criteria resulted from experience-based judgments and account for uncertainties in determining class boundaries developed by SMR system,the system classification results were corrected using two clustering algorithms, namely K-means and fuzzy c-means(FCM), for the ratings obtained via continuous and discrete functions. By applying clustering algorithms in SMR classification system, no in-advance experience-based judgment was made on the number of extracted classes in this system, and it was only after all steps of the clustering algorithms were accomplished that new classification scheme was proposed for SMR system under different failure modes based on the ratings obtained via continuous and discrete functions. The results of this study showed that, engineers can achieve more reliable and objective evaluations over slope stability by using SMR system based on the ratings calculated via continuous and discrete functions.