Joint Damage Effects on Axial Capacity of Cold-Formed Steel Uprights: Experimental, Numerical, and Machine Learning Study


Taranu G., Yazici C., ÖZKAL F. M.

Advances in Civil Engineering, cilt.2026, sa.1, 2026 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 2026 Sayı: 1
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1155/adce/4354889
  • Dergi Adı: Advances in Civil Engineering
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, INSPEC, Directory of Open Access Journals
  • Anahtar Kelimeler: axial load capacity, cold-formed steel, finite-element analysis, joint degradation, machine learning, storage rack systems
  • Atatürk Üniversitesi Adresli: Evet

Özet

This study quantifies how beam-to-column joint damage alters the axial resistance and failure modes of cold-formed steel (CFS) uprights used in industrial storage rack systems. Current design-oriented assessments typically neglect the reduction of joint rotational stiffness and moment resistance caused by prior cyclic joint deterioration, which can compromise subsequent compression performance. To address this gap, six commercial perforated upright sections are tested under axial compression in intact and joint-damaged conditions. A unified framework combines experiments, nonlinear finite element analysis (FEA; ANSYS), and machine learning (ML) prediction using geometric descriptors (thickness, area, second moments of area, and radii of gyration) together with experimentally derived joint properties (rotational stiffness and ultimate joint moment). Among the evaluated regressors, the gradient boosting model provides the best predictive performance (cross-validated R2 and lowest root mean square error [RMSE]/mean absolute error [MAE]), showing close agreement with experimental outcomes and numerical trends. Results indicate axial capacity reductions of up to ~30% after joint degradation and a tendency toward coupled distortional and torsional–flexural (TF) instability. The findings highlight the engineering need to account for joint stiffness degradation in residual capacity checks and support rapid, data-informed decisions for inspection and retrofit of rack uprights. The study provides a practical predictive framework for postdamage capacity evaluation in industrial rack systems.