Multi-Objective Heuristic Optimization-Based Carbon Fiber Reinforced Structure for High-Rise Seismic Resilient and Sustainable Infrastructure Development

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Authors: Deekshith ., I. Ramesha Mithanthaya, Chinnagiri Gowda
Cited by: 0

Abstract

This research proposes a robust multi-objective NSGA-II heuristic optimization framework for CFRP (Carbon Fiber Reinforced Polymer) wrapping to promote seismic-resilient and low-carbon high-rise infrastructure. The method integrates nonlinear time-history analysis with a multi-objective genetic algorithm to determine optimal CFRP application conditions, including whether floors require CFRP wrapping, mortar jacketing, steel jacketing, or combinations thereof. It further optimizes CFRP thickness, orientation, design pattern (unilinear, bidirectional, hybrid), coverage, and anchorage details. Optimization simultaneously minimizes overall cost, torsional irregularity index, Park–Ang damage index, and seismic sensitivity while maintaining structural reliability under seismic loading. Simulation results indicate that proposed CFRP framework reduces torsional impacts by approximately 35%, enhancing seismic resilience. Hybrid CFRP configurations combined with 20–40 MPa mortar and optional 10–40 mm steel jacketing showed improved structural performance. Anchorage of 0–2 per end per face reduced torsional drift to ≤0.5–1.0%. For a 10-storey building, lower floors benefit from CFRP with mortar/steel jacketing up to ±45°, mid-level floors from hybrid (0/±45°) configurations, and upper floors from predominantly ±45° CFRP with occasional 90° bands. CFRP thickness of 0–3 mm (0–6 plies) achieved improved seismic resilience, cost efficiency, and structural reliability, supporting its potential for seismic-resilient infrastructure policy and design.

Fields of Study & Subjects

Seismic Performance and Analysis Structural Behavior of Reinforced Concrete Seismic and Structural Analysis of Tall Buildings

Publication details

Journal / source
Preprints.org
Publication date
12 February 2026
Language
EN
Document type
Preprint