CASE STUDY · GN&C SYSTEMS
6-DOF Simulation, Digital Twins, and Monte Carlo Automation
Building simulation and DevOps infrastructure to evaluate dynamic-system performance, detect defects earlier, and automate repeatable release analysis.
Problem
Complex dynamic systems need simulation infrastructure that does more than generate trajectories. Engineers need repeatability, automated regression evidence, configurable Monte Carlo campaigns, and a credible way to connect software changes to system-level performance.
Constraints
The simulation environment had to support system-performance evaluation, software releases, verification activity, and large sets of uncertainty-driven runs without turning every new build into a manual analysis exercise.
Approach
I developed software applications for six-degree-of-freedom missile simulation, a digital twin used for performance evaluation, strengthened continuous integration with additional tests, and automated Monte Carlo generation whenever new software builds were released.
This creates a useful feedback loop:
software change → automated build → regression checks → Monte Carlo campaign → performance evidence → engineering decision
Results
The work improved the team’s ability to detect defects earlier, evaluate new builds consistently, and use simulation as an integrated engineering tool rather than a detached analysis activity.
Engineering notes
Simulation becomes far more valuable when it is treated as executable system knowledge. A digital twin tied into CI can act as a continuously exercised hypothesis about system behavior, making model assumptions and software regressions visible much earlier in the engineering cycle.