Explicit Dynamics May 2026

It is computationally expensive. It requires meticulous mesh quality. But when you watch a simulation of a crumple zone absorbing kinetic energy or a turbine blade surviving a bird strike, you realize the power of moving beyond the steady state.

That’s where takes center stage.

The secret lies in and the CFL condition (Courant-Friedrichs-Lewy). The stable time step is dictated by the smallest element in your mesh: Δt = L_e / C_d (element length divided by the speed of sound in the material). explicit dynamics

That tiny step isn't a bug; it's the physics. You are literally simulating the propagation of a stress wave across your model. For a steel beam being hit by a projectile, that wave moves fast. To capture it, you must move faster. You should reach for an explicit solver when the event happens faster than the natural frequency of the structure. Specifically: 1. Automotive Crashworthiness The classic use case. When a car hits a barrier at 40 mph, the front crumples, the engine dips, and the airbag deploys—all within 150 milliseconds. Explicit codes (like LS-DYNA or Radioss) are the industry standard here. 2. Drop Testing Will your smartphone survive a 1.5m drop onto concrete? Explicit dynamics models the micro-second of impact, the propagation of the shockwave through the glass, and the resulting fracture. 3. High-Speed Machining & Drilling When a carbide tool cuts through Inconel at 10,000 RPM, the chips fly, the heat spikes locally, and the material shears. Explicit solvers handle the element erosion (removing failed elements) required for chip formation. 4. Blast & Ballistics From a bullet hitting a ceramic plate to a shockwave hitting a reinforced bunker—these events involve extreme deformation rates. Only explicit methods can handle the equation of state (EOS) required for explosives. The Hidden Danger: Dynamic Damping & Inertia Here is the most common mistake engineers make: using explicit dynamics for a quasi-static problem (like a slow press-fit or a rubber seal compression).

If Implicit methods are the marathon runners—steady, calculated, and efficient for long, slow loads—Explicit Dynamics are the sprinters. They thrive on chaos, micro-second time steps, and highly non-linear events. It is computationally expensive

The real world isn't static. It explodes, crashes, and drops. It’s time your simulations did the same. Have you struggled with convergence issues in implicit codes for high-speed events? Or are you just getting started with explicit analysis? Let me know in the comments below.

In the world of engineering simulation, we often spend our time looking for balance. We seek steady-state temperatures, static stress distributions, and converging flow patterns. But what happens when the story isn’t about equilibrium? What happens when it’s about the crash, the drop, the blast, or the milliseconds following a high-speed impact? That’s where takes center stage

Because explicit solvers introduce artificial inertia to stabilize the small time step, you risk —where the model is so "heavy" in the simulation that it takes a different deformation path than reality.