📖 ABSTRACT/OVERVIEW
Structural reliability analysis of reinforced concrete frames designed and built under Nigerian practice conditions requires probabilistic treatment of material property variability, workmanship quality variation, and loading uncertainty specific to the Nigerian context, yet no such analysis has been published for Nigerian construction conditions. This study conducted an original probabilistic structural reliability analysis of reinforced concrete frame buildings representative of Nigerian building practice in Lagos State, North Central Nigeria, and Kano State, representing different climate and construction practice contexts. In-situ concrete compressive strength data were collected from 60 completed residential and commercial reinforced concrete frame buildings (1,240 core samples), characterising the statistical distribution of actual in-situ strength relative to specified design strength. Reinforcement yield strength was measured from 420 bar samples collected from construction sites. Loading statistics for Nigerian occupancy conditions were established from a nationwide survey of 200 buildings. Monte Carlo simulation was used to conduct reliability analysis of representative column, beam, and slab elements, calculating probability of failure and reliability index under combined dead, live, and wind loading. Results showed that in-situ concrete compressive strength averaged only 78% of specified characteristic strength, with a coefficient of variation of 32%, significantly exceeding the 15% assumed in design codes. Reliability indices for standard columns designed to BS 8110 were below the target value of 3.8 in 38% of simulated cases. The study provides the first empirical probabilistic reliability assessment of Nigerian RC frame construction, revealing a systematic strength shortfall that creates latent structural vulnerability, and recommends updated material factor specifications in Nigerian structural design standards.
Keywords: structural reliability, reinforced concrete, probabilistic analysis, Nigerian construction, Monte Carlo simulation
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