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August 17, 2025Journal of Physics Conference Series1 citationsOpen Access

Finite Element Analysis of Static Linear Euler-Bernoulli Microbeams Based on the Modified Strain Gradient Theory

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OKOssama M KamalHEHesham A. ElkaranshawyAEAhmed A. H. Elerian

Key Points

  • Microbeams reveal pronounced size effects, showing increased stiffness as dimensions approach material length scale parameters.
  • The finite element framework derives governing equations that integrate modified strain gradient theory and material length scale parameters.
  • Comparison with classical theory illustrates that MSGT-based formulations align better with microscale behaviour in MEMS applications.
  • Results suggest that gradient-enhanced models are essential for achieving precision in micro-engineering applications.

Abstract

Abstract This paper develops a finite element formulation (FEF) for static linear Euler-Bernoulli microbeams using the modified strain gradient theory (MSGT). Remarkably, classical models often fail to predict microscale behaviour, e.g. micro-electromechanical systems (MEMS), by neglecting material length scale parameters (MLSPs). Thus, MSGT integrates into the beam formulation to address this. Subsequently, a finite element framework derives governing equations extending classical theory via MSGT and incorporating MLSPs into the stiffness matrix. For validation, a cantilever microbeam, a simple microbeams and a fixed-fixed microbeam are analysed, comparing results with classical theory and published analytical results, which reveals pronounced size effects e.g. increased stiffness, as beam dimensions approach MLSPs. The findings demonstrate that classical models inaccurately predict deflections and stresses, whereas MSGT-based FEF consistently aligns with microscale phenomena. Overall, this work establishes the formulation as a robust tool for MEMS design, emphasizing the necessity of gradient-enhanced models for precision in micro-engineering applications.

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Cite This Study

Kamal et al. (2025) studied this question.

synapsesocial.com/papers/68a36a360a429f797332e2f5https://doi.org/10.1088/1742-6596/3075/1/012009
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