Multi-Hit Ballistic Test Learning Synthesizer

**Description:**
Each transparent-armor ballistic test destroys an expensive panel to produce a handful of data points, and the learning stays locked in test reports. This capability uses Orchestrate agents to synthesize every shot across programs — impact velocity, projectile type, panel construction, crack-propagation imagery, residual transparency — into continuously improving predictive models of multi-hit performance. Before the next test, agents recommend the shot patterns most likely to discriminate between competing designs, maximizing information per destroyed panel. The models also interpolate between tested configurations, reducing the shot count needed to certify variants. Armor developers reach certified multi-hit performance with fewer test articles, ranges deliver more insight per event, and vehicle programs field protection sooner. Over time the models generalize across panel families, compounding the value of every shot.