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Jack Banahene Osei

Civil Engineering

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About

Jack Banahene Osei’s research evolves around performance-based earthquake engineering, reinforced concrete structures and several applications of finite element method in engineering.

Research Summary

(inferred from publications by AI)

The researcher's work is centered on advancing the understanding and application of reinforced concrete structures across various domains. Their focus includes bamboo properties for sustainable construction, which they integrate into self-compacting concrete beams, enhancing durability and resilience in rural areas. Through finite element modeling and machine learning techniques, they analyze the behavior of bamboo-reinforced concrete beams under different loading conditions, such as one-way slabs and beams with 100% recycled coarse aggregate. Their research also delves into the structural integrity of these beams, contributing to sustainable construction practices. Additionally, they employ empirical joint shear strength models to predict structural failure in laterally loaded RC columns. The researcher's work extends beyond concrete structures by incorporating energy-efficient materials like graphite and advanced radiation studies for nuclear technology. Structural health monitoring techniques, including predictive behavior modeling with finite element analysis, are also explored. Their research contributes significantly to both sustainable construction practices and the development of innovative concrete reinforcement materials.

Research Themes

All Papers

Bamboo‐reinforced self‐compacting concrete beams for sustainable construction in rural areas(2017)
Bamboo reinforced self-compacting concrete one-way slabs for sustainable construction in rural areas(2018)
Finite Element Modelling of Bamboo Reinforced Concrete Beams(2018)
Structural Characteristics of Reinforced Palm Kernel Shell Concrete Deep Beams(2018)
Behaviour of Bamboo Reinforced Concrete Beams With 100% Recycled Coarse Aggregate(2019)
A machine learning-based structural load estimation model for shear-critical RC beams and slabs using multifractal analysis(2023)
Structural Failure Mode Prediction in Laterally Loaded Reinforced Concrete Columns Using Machine Learning(2024)
A comparative seismic fragility analysis of a multi and single component beam-column joint models(2018)
Monte Carlo Based Seismic Hazard Model for Southern Ghana(2018)
Nonlinear seismic analysis of a super 13-element reinforced concrete beam-column joint model(2016)
Average spectral acceleration: Ground motion duration evaluation(2018)
Evaluation of Empirical Joint Shear Strength Models for Simulating Dynamic Responses of Reinforced Concrete Structures(2017)
On The Non-Linear Finite Element Modelling of Self-Compacting Concrete Beams(2017)
Strain driven mode-switching analytical framework for estimating flexural strength of RC box girders strengthened by prestressed CFRP plates with experimental validation(2023)
Predictive Behaviour from Finite Element Analysis on PVC-Ducted Reinforced Concrete Column(2024)
Structural Performance of Reused GFRP Bars in Reinforced Concrete Beams: A Sustainable Approach to Concrete Reinforcement(2025)
Bond Characteristics of Coated Reinforcing Steel Bars with Reference to Deformation of Concrete Beams(2025)
Rice Husk Ash as Partial Replacement of Cement in Sustainable Construction(2024)
A Machine Learning-Based Structural Load Estimation Model For Shear-Critical Rc Beams and Slabs Using Multifractal Analysis(2022)
Incorporating joint flexibility in collapse risk assessment(2017)
Assessment of Oil Paints for Corrosion Protection of Reinforcing Steel Bars in Concrete(2024)

Collaboration Network

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About This Profile

This profile is generated from publicly available publication metadata and is intended for research discovery purposes. Themes, summaries, and trajectories are inferred computationally and may not capture the full scope of the lecturer's work. For authoritative information, please refer to the official KNUST profile.