Blast Induced Pervasive Failure

Rensselaer Polytechnic Institute

Gianluca Cusatis

Problems

Structural failures resulting from blast loads are highly nonlinear processes involving complex material constitutive behavior, post-peak material softening, localization, new surface generation via dynamic crack propagation, and ubiquitous contact. The extent of material fracturing is pervasive in the sense that a multitude of cracks are dynamically active, propagating in arbitrary directions, branching, and coalescing. An additional challenge for modeling blast induced pervasive failure is the two-way coupling between the fluid and the structure. This two-way coupling is essential for accurately simulating confined blasts as well as the flow of structural debris within the blast. Currently, there is a very limited set of computational tools that can accurately and reliably simulate blast induced pervasive failures and none is able to naturally transition between the different physics relevant to the fluid interaction with the entire structure (length scale of several meters) as opposed to structural debris (length scale of millimeters or less).

Approach

We are developing a multiscale multiphysics computational framework by taking into account the various length and time scales characterizing the fluid/solid interaction during pervasive failure. This computational framework is obtained through the development and the seamless integration of three components: (a) a three-dimensional meso-scale model, the Lattice Discrete Particle Model (LDPM), accounting for arbitrary variability of material properties; (b) a three-dimensional macro-scale model for pervasive failure; and (c) a fluid/solid interaction model.

Findings

The fluid-solid interaction method for coupling a computational fluid dynamics framework with the Lattice Discrete Particle Model framework was successfully formulated and validated on the basis of the Immersed Finite Element Method. A statistical method was developed for verifying mesh convergence in a sequence of distributions observed through direct Monte Carlo sampling. The method has been demonstrated using three examples: (1) a logistic map in the chaotic regime, (2) a fragmenting ductile ring, and (3) a fragmenting quasi-brittle ring. A unified formulation of a continuum/discrete computational method for the simulation of fracture and fragmentation was accomplished and applied to the simulation of impact induced spalling.

Impact

This research is laying the foundation for the development of computational technologies that will improve the ability of the engineering community to protect the National infrastructures against manmade and natural hazards. More specifically, the results of this research project will enable the accurate design of necessary standoff distances for strategic civil infrastructures (dams and public buildings) to be guarded against terrorist attacks, the assessment of primary and secondary damage caused by explosions and subsequent debris flow, the accurate simulation of attacks on hard and deeply buried targets.

Core competencies

  • Constitutive modeling of quasi-brittle materials.
  • Discrete modeling of solids.
  • Nonlinear fracture mechanics.
  • Material behavior under high strain rates.
  • Computational analysis of concrete and reinforced concrete structures.

Current research team members

  • Gianluca Cusatis (PI)
  • Edwad Shauffert (Post-Doctoral Associate)
  • Xinwei Zhou (Ph.D. Candidate)
  • Mohammed Al-Naggar (Ph.D. Candidate)
  • Roozbeh Rezakhani (Ph.D. Candidate)
  • Andrea Mencarelli (Ph.D. Candidate)
  • Jovanca Lewis-Smith (M.S. Candidate)
  • Michelle Riedman (Undergraduate)
  • Eric Domonell (Undergraduate)

Recent graduates

  • Edwad Shauffert (Ph.D. 2010)
  • Eric Dahl (M.S. 2009)
  • Daniel Horvath (M.S. 2009)

Current research collaborations

  • Joseph Bishop (Sandia National Labs) Failure and fragmentation of concrete.
  • Lucy Zhang (MANE Department, Rensselaer Polytechnic Institute) Fluid-solid interaction framework for simulating debris dynamics.
  • Daniele Pelessone (ES3, Inc.) Implementation of Lattice Discrete Particle Model based multiscale techniques.