Automation in decision making and design of retrofitting

Civil engineering deals with a variety of tasks. Out of these constructions is the most widely known. Construction of a structure is aimed at two major requirements: Safety and Serviceability. As time progresses constructed structures need aids to maintain them. It may be because the structure loses its initial targeted or the change in requirement. The process of increasing strength, ductility, and stiffness of a structure are called retrofitting. There are two types of retrofitting, global and local retrofitting. The process of retrofitting deals with steps like designing, analysis and decision making. The conventional linear analysis is found to be less accurate; hence the nonlinear pushover analysis is gaining popularity. The design and analysis are generally done by the Finite Element Modelling and Analysis software. This makes the designing of retrofitting a complicated and tedious process. An experienced human intellect is needed. But as the field of automation is flourishing with all leaps and bounds, the field of civil engineering is no exception. The self-intelligent method can help in not only designing retrofit but also in decision making. Self-learning algorithms developed through supervised machine learning (regression model and decision tree) can assist the designing and decision-making process in the field of retrofitting. This can not only reduce the complicacy of the process but will also boost the accuracy and speed. This manner the Artificial Intelligence will Automate the Decision Making and Design of Retrofitting.

SEISMIC EVALUATION AND RETROFIT ON AN EXISTING HOSPITAL BUILDING

The nonlinear pushover analysis was used to evaluate an existing 8-storey reinforced concrete framed hospital building under seismic force and presented in this manuscript. The ‘Guru Teg Bahadur Hospital' is one of the important hospitals at Delhi-India, it was selected for this research. The three-dimensional frame model was used to model the building with a fixed base. The beams and columns were modeled by using three-dimension line frame elements with the centre lines joined at nodes. Diagonal strut elements were used to model the brick masonry infills. The slabs were considered as rigid diaphragms. The plastic hinge rotation capacities as per Federal Emergency Management Agency 356 (FEMA 356) with Performance Levels were adopted in this study, considering the axial force-moment and shear force-moment interactions. The nonlinear pushover analysis of the selected building was done with infills and it was observed that the infills (due to their small number in the considered building) do not make any appreciable effect on the performance level, except their failure at an early stage. The Capacity Spectrum Method (CSM) and Displacement Coefficient Method (DCM) were used to estimate the performance point of the building. The values of various coefficients as per Federal Emergency Management Agency 440 (FEMA 440) were adopted. The DCM was observed to give slightly higher target displacements, as compared to CSM. It was observed in the nonlinear pushover analysis that the unreinforced masonry (URM) infills collapse before the performance point of the building for the Maximum Considered Earthquake (MCE). As the intervention inside the functioning hospital is extremely difficult, it was explored whether it is possible to safeguard the infills by stiffening the building by providing external buttresses. Two cases of retrofitting schemes with 1.2m wide and 3m wide buttresses in transverse direction were used and analysed. It was found that this is not a practicable approach, as the infills collapse even with 3m wide buttresses.

STUDI PERBANDINGAN KINERJA GEDUNG BETON BERTULANG SRPMK 6 LANTAI DENGAN MENGGUNAKAN METODE PUSHOVER DAN NONLINEAR TIME HISTORY ANALYSIS

Indonesia merupakan salah satu negara rawan gempa di dunia. Untuk mengurangi dampak akibat gempa khususnya jatuhnya korban jiwa akibat keruntuhan bangunan, maka dalam perencanaan struktur gedung di daerah rawan gempa, perilaku atau kinerja gedung terhadap gempa merupakan salah satu hal terpenting untuk diperhatikan. Oleh karena itu, perhitungan analisa secara inelastik atau nonlinier harus dilakukan. Beberapa metode untuk perhitungan analisis nonlinier meliputi analisis beban dorong (static nonlinear pushover analysis) dan analisis riwayat waktu (inelastic dynamic time history analysis). Penelitian ini membandingkan hasil kinerja dari analisis beban dorong dan analisis riwayat waktu dengan menggunakan rekaman gempa San Fernando, Morgan Hill dan Kobe untuk gedung beton bertulang SRPMK 6 lantai. Dari hasil analisis beban dorong maupun analisis riwayat waktu, didapatkan tingkat kinerja yang sama yaitu kategori IO ( Immediate Occupancy ) baik untuk arah X dan Y. Target displacement yang didapat dari analisa beban dorong sebesar 0,092 m untuk arah X dan 0,096 m untuk arah Y. Sedangkan displacement maksimum yang didapat dari hasil analisa riwayat waktu adalah sebesar 0,0129 m untuk arah X dan 0,005 m untuk arah Y yang berasal dari rekaman gempa Kobe dan gempa San Fernando.

Seismic Rating of Multistoried Frame System by Non-Linear Pushover Research

This paper compares multistoried frame structures on plain ground and on hilly areas, first under the action of normal commercial loading and thereafter by considering the effect under the action of heavy loads. Behavior of multistoried frame buildings on plains are completely different from buildings which are constructed on hilly slopes. Buildings constructed on plain is simple and symmetrical, whereas the buildings that are constructed on hilly slopes are complex in geometry and asymmetrical in nature. Similarly, the behavior of commercial buildings with normal loading is distinctively different in comparison to special buildings such as Data centre buildings which are heavily loaded under gravity. Four different types of Symmetrical and Asymmetrical analytical Models are generated for five and ten storey buildings using "ETABS". Seismic evaluation of these models is done separately under the effect of normal and heavy loading by performing Nonlinear Pushover analysis