The conference is intended to provide a major forum for the exchange of ideas and discussion of recent developments in all mechanics, probabilistic-methods and materials research fields. The technical sessions and symposia on fundamentals, tools and applications serve to highlight and promote educational needs, emerging thrusts, novel techniques, and innovative applications in areas that span across many engineering disciplines relevant to engineering mechanics and probabilistic mechanics and structural reliability. Special sessions should be submitted directly to the conference chairs to


EMI Topics

For the Engineering Mechanics Conference topics include, but are not limited to:
  • Solid Mechanics
  • Fluid Mechanics
  • Computational Mechanics
  • Computational Fluid Dynamics
  • Mechanics of Composites
  • Elasticity and Elastodynamics
  • Wave Propagation
  • Nonlinear Mechanics
  • Linear/Nonlinear Dynamics, Chaos
  • Biomechanics
  • System Identification and Control
  • Non-destructive Evaluation, Structural Health Monitoring
  • High Performance Materials, Smart Materials
  • Smart Structures
  • Fracture, Fatigue, Crack Propagation, Damage Mechanics
  • Mechanics and Dynamics of Space Structures
  • Offshore Dynamics and Mechanics
  • Fluid-Structure Interaction
  • Soil Mechanics and Dynamics
  • Micromechanics
  • Probabilistic Mechanics
  • Reliability Methods
  • Turbulence
  • Signal Processing, Sensors
  • Experimental Analysis
  • Large-Scale Computational Simulation
  • Hybrid Simulation
  • Parallel and Distributed Simulations

PMC Topics

For the Probabilistic Mechanics and Structural Reliability Conference, topics include, but are not limited to:
    • Stochastic Vibrations
    • Stochastic Mechanics
    • Reliability Assessment
    • Reliability-Based Design Optimization
    • Monte Carlo Methods and Stochastic Simulation
    • Uncertainty Quantification
    • Bayesian Identification and Model Updating
    • Bayesian networks
    • Robust Design Optimization
    • Parallel Computations for Probabilistic Applications
    • Life-cycle assessment and design
    • Stochastic Optimization