U. Meenu Krishnan

Mathematical approach to find optimal material layouts under fracture constraints and manufacturing considerations. Targets lightweight, high-strength structures for real-world aerospace and civil applications. Integrated with 3D printing for fabrication of complex geometries.

Large Scale Topology Optimization — phase field coupled result

Optimization convergence

Performance curves

A continuous-field framework for simulating crack propagation in materials without explicit crack tracking algorithms. Enhanced with mesh adaptivity and automatic time-stepping for large-scale problems. Scales efficiently on HPC clusters using MPI-parallel FEniCS/PETSc.

Displacement field — fracture simulation

Phase field crack pattern

Using Evolutionary Deep Neural Networks (EDNN) to solve multi-physics problems in solid mechanics — coupled fracture, heat conduction, and wave propagation. Bridges physics-based modeling and machine learning to create efficient, generalizable solvers without the need for labeled training data.

Engineering materials with tailored mechanical, acoustic, and photonic properties via topology optimization and additive manufacturing. Designed microstructures achieve extreme stiffness-to-weight ratios, wave-guiding behavior, and auxetic responses.

Parallel algorithms for massive computational loads in structural simulation, deployed on distributed HPC clusters for aerospace, automotive, and civil infrastructure domains.

MeshX — mesh generation tool