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Eccentric Loading01:16

Eccentric Loading

319
Eccentric loading is a crucial concept in the study of structural engineering and mechanics, particularly when analyzing the stability and stress distribution in columns. Unlike centric loading, where the force is applied along the centroidal axis, causing uniform compression, eccentric loading occurs when a force is applied off-center. This off-center application introduces not only direct compressive stress but also bending stress, significantly influencing the column's behavior under...
319
Design of Columns under an Eccentric Load01:21

Design of Columns under an Eccentric Load

434
Designing columns to withstand eccentric loads is a critical aspect of structural engineering, ensuring structures can support off-center loads without failure. This design process must account for the additional normal stresses introduced by eccentric loading, which can significantly influence a column's stress distribution and overall stability. An eccentric load applied to a column induces normal stresses that can be conceptualized as a combination of stresses due to an equivalent...
434
Design of Columns under a Centric Load01:17

Design of Columns under a Centric Load

104
The design of columns under centric load is a fundamental aspect of structural engineering and is critical for ensuring the stability and integrity of structures. Euler's and Secant's formulas are central to understanding and calculating the critical load and deformation behaviors of columns, providing a basis for safe and effective structural design.
Euler's formula is applicable under the assumption that the column is a perfect, straight, homogenous prism, and it is operating...
104
Euler's Formula for Pin-Ended Columns01:21

Euler's Formula for Pin-Ended Columns

288
In structural engineering, the stability of columns under compressive axial loads is a critical consideration, described as buckling. A typical example involves a column PQ, which is pin-connected at both ends and subjected to a centric axial load F applied at one end, with a reaction force of F' = -F at the other end. Here, it is crucial to understand that when an applied load exceeds the critical load, buckling occurs as the system becomes unstable.
To calculate the critical load,...
288
Euler's Formula to Columns with Other End Conditions01:15

Euler's Formula to Columns with Other End Conditions

461
Euler's formula is very important in the field of structural engineering, providing a foundation for understanding the critical loading conditions of pin-ended columns. This formula links the modulus of elasticity, the moment of inertia of the cross-section, and the column's length, offering a precise calculation of the critical load at which a column is prone to buckling.
461
Eccentric Axial Loading in a Plane of Symmetry01:16

Eccentric Axial Loading in a Plane of Symmetry

161
Eccentric axial loading occurs when an axial load is applied away from the centroidal axis of a structural member. This scenario is common in engineering, where structural elements may not be directly aligned due to various design or functional requirements.
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Strength prediction of ECC-CES columns under eccentric compression using adaptive sampling and ML techniques.

Khaled Megahed1

  • 1Department of Structural Engineering, Mansoura University, PO BOX 35516, Mansoura, Egypt. k.megahed@mans.edu.eg.

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|January 8, 2025
PubMed
Summary

Engineered Cementitious Composites (ECC) confined concrete-encased steel (CES) columns show improved performance. Machine learning models accurately predict their eccentric compressive capacity, outperforming current design standards.

Keywords:
Adaptive samplingCatBoost modelEccentric compressionEngineered cementitious compositesFinite element modelingMachine learning

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Area of Science:

  • Civil Engineering
  • Materials Science
  • Computational Mechanics

Background:

  • Conventional concrete-encased steel (CES) columns have limitations in ductility and toughness.
  • Engineered Cementitious Composites (ECC) offer enhanced material properties for structural applications.
  • ECC-confined CES (ECC-CES) columns present a novel composite with superior performance characteristics.

Purpose of the Study:

  • To develop an innovative method for predicting the eccentric compressive capacity of ECC-CES columns.
  • To utilize adaptive sampling and machine learning (ML) for accurate capacity prediction.
  • To compare ML model performance against established design codes.

Main Methods:

  • Development and validation of a finite element (FE) model for ECC-CES columns, including material and geometric nonlinearities.
  • Application of adaptive sampling via Bayesian Optimization (BO) to generate a comprehensive FE database (2,908 models).
  • Training and evaluation of six ML models (GPR, CatBoost, LGBM, etc.) to predict eccentric compressive capacity.

Main Results:

  • FE model validation demonstrated strong predictive accuracy against experimental data.
  • ML models achieved high prediction accuracy, with GPR, CatBoost, and LGBM showing over 97% of samples within a 10% error range.
  • ML models significantly outperformed EC4 and AISC360 design standards in predicting eccentric compressive capacity.

Conclusions:

  • Machine learning, particularly GPR, CatBoost, and LGBM, offers a highly accurate method for predicting ECC-CES column capacity.
  • The integration of adaptive sampling with ML effectively generates robust training data for complex structural analysis.
  • While ML models excel in accuracy, their interpretability requires further research for direct design application, prompting the proposal of a new design approach.