This simulator links a remote receiver to two radio towers that would normally give redundant communication. A shared storm zone can disable both at once, so you can see how a common cause cuts into the benefit of redundancy and what modeled diversity removes.
• A 3D radio tower A, radio tower B, shared exposure zone and remote receiver. • Sliders for mission duration (100-3000 h), component failure rate (0.05-2 per 1000 h) and shared-cause mission probability (0-0.3), switches for an independent fault on each tower, a shared storm and a remove-shared-dependency option. • Four live readouts: independent-pair survival, survival including the shared cause, the shared-cause reliability penalty and whether communication is available. • Two presets: Shared storm (both healthy towers lose service) and Modeled diversity (the shared storm is excluded; independent branch faults still apply).
Each tower branch survives with R_branch = exp(-lambda T), so the independent pair survives with 1 - (1 - R_branch)^2. A shared event with mission probability q_common disables both, which multiplies the result by (1 - q_common): R = (1 - q_common)[1 - (1 - R_branch)^2]. The penalty is the difference between the independent result and this one, and it shows that no amount of added redundancy can push reliability above 1 - q_common.
The shared event is treated as independent of the branch-specific failures and disables both towers when it occurs. Diversity removes only this explicitly modeled cause and does not prove immunity to every common cause. This is not a beta-factor model. Raise the shared-cause probability and watch the survival plateau well below the independent-pair value.
Yes. If a shared cause can disable several components together, branch outcomes are not independent and the independent formula overstates the system reliability.
No. It removes only the explicitly modeled shared dependency in this lab; other common causes may still exist in a real system.
R = (1 - q_common) times [1 - (1 - R_branch)^2]: the shared event multiplies the independent-pair survival by its own survival probability.
It uses one modeled shared event independent of branch failures, not a beta-factor or partial common-cause model, and does not model repair.