Research Interests

Dr Sarah Kamaludin B.Eng., M.Sc. (USM), Ph.D. (UKM) (email: This email address is being protected from spambots. You need JavaScript enabled to view it.)

• Finite Element Method (FEM): Development and application of FEM for complex material and structural analysis.
• Computational Mechanics: Exploring advanced computational techniques for modeling mechanical behavior of materials.
• Continuum Damage Mechanics (CDM): Investigating damage evolution and failure in materials using continuum mechanics principles.
• Simulation of Advanced material: applying computational methods to solve problems or predict mechanical responses of advanced material, e.g. fiber-reinforced composites and additive-manufactured structures.
• Micromechanical Models: Modeling material behavior at the microscopic level to understand the macroscopic properties.
• Machine Learning & Deep Learning: Integrating AI and machine learning techniques with traditional engineering models to enhance predictive capabilities and automation in mechanical analysis.
• Programming: writing codes for ABAQUS subroutine (Fortran) and Python

Background

Sarah Kamaludin holds a B.Sc. in Mechanical Engineering from the School of Mechanical Engineering, USM, completed in 2011. She continued her studies at USM, earning an M.Sc. (2012–2015) with a focus on mesh-adaptive finite element methods for Multiphysics problems, specifically thermoelectric systems. Her doctoral research, completed in 2021 at UKM, was in Computational Mechanics that is developing a non-local damage criterion for viscoelastic solids.

Her current research focuses on advanced computational techniques, emphasizing the finite element method (FEM) and continuum damage mechanics to investigate material failure and damage evolution, particularly in advanced materials such as composites and 3D-printed structures. She is also interested in micromechanical models and machine learning algorithms to predict macroscopic material properties from micromechanical modeling.

Through this interdisciplinary approach, she aims to advance the understanding and prediction of material behavior, contributing to more reliable and efficient engineering designs.

Publications

1. Sarah, K. & Thamburaja (2023), P. Efficient Neighbor Search Algorithm for Nonlocal-based Simulations: Application to Failure Mechanics. Journal of Failure Analysis and Prevention, 23, 540–547 (2023).

2. Qianrui, Du, Sarah Kamaludin, and Norwahida Yusoff (2022). Frequency-Driven Crack Propagation in Ultrasonically-Assisted Bone Cutting. International Journal of Integrated Engineering 14.8: 112-117.

3. Thamburaja, P., Sarah, K., Srinivasa, A., & Reddy, J. N. (2021). Fracture modelling of plain concrete using non-local fracture mechanics and a graph-based computational framework. Proceedings of the Royal Society A, 477(2252), 20210398.

4. Sarah, K., Thamburaja, P., Srinivasa, A., & Reddy, J. N. (2020). Numerical simulations of damage and fracture in viscoelastic solids using a nonlocal fracture criterion. Mechanics of Advanced Materials and Structures, 27(13), 1085–1097.

5. Thamburaja, P., Sarah, K., Srinivasa, A., & Reddy, J. N. (2019). Fracture of viscoelastic materials: FEM implementation of a non-local & rate form-based finite-deformation constitutive theory. Computer Methods in Applied Mechanics and Engineering, 354, 871–903.

6. Siti Sarah K., Thamburaja, P., & Ariffin, A. K. (2018) Atomistic Simulations of Twist Grain Boundary Structures in Aluminum-Magnesium Alloys. International Journal of Engineering & Technology, 7, 180–182.

7. Kamaludin, S. S., & Abdul-Rahman, R. (2014) Fully automatic adaptive finite element procedure for multiphysics problems in three dimensions. In AIP Conference Proceedings (Vol. 1605, No. 1, pp. 535-539). American Institute of Physics.

Networking and Linkages

Funding Agencies:

• Ministry of Higher Education (MOHE) Malaysia
• Universiti Sains Malaysia

Research Links:

• Department of Mechanical and Manufacturing. Faculty of Engineering and Built Environment, UKM