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LunCo / Platform / Mission operations simulation
For mission designers and operators

Turn a CONOPS into an executable mission study.

A mission concept is more useful when its sequences, handoffs, failure responses, and vehicle behavior can run against the same world. LunCoSim connects scenario policy to live simulation state through events, tasks, and an API.

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Rhai hot-reloadable policyEvents explicit handoffsHTTP/MCP automation
From CONOPS to executable mission Mission intent is authored as scenario policy, executed by the simulation, and observed through events and API state. CONOPS → RUN → EVIDENCE Mission intentsequencehandofffailure responseobjective Rhai scenariotask treeevent handlersqueries / commandshot reload Live missionphysics statetelemetry eventsAPI observationsauthored verdict observe → adjust → rerun
Policy stays separate from physics. Rhai decides what the mission does; Modelica and the runtime carry continuous dynamics and scheduling.

Make the operational logic testable.

The gap between a CONOPS document and a working simulation is an explicit, repeatable connection between intent, state, and response.

01 / AUTHOR

Write mission policy without recompiling the engine.

Rhai scenarios attach to entities and provide task trees, objectives, lifecycle hooks, and event reactions. Edit a scenario, run it again, and inspect its compile/runtime state through the same control surface.

02 / REACT

Use events for handoffs and failure modes.

Touchdown, low fuel, arrival, and other authored signals can become explicit telemetry events. Mission logic reacts to a fact instead of hiding a second threshold or state owner in a polling loop.

03 / OBSERVE

Drive the run from code, UI, or an agent.

The HTTP API, MCP path, UI, and scripts share the command/query boundary. Start a scenario, read ports, inspect entities, and collect the state needed to explain why the run reached its outcome.

04 / ITERATE

Change the plan while the mechanism stays stable.

Mission policy belongs in authored scenario assets. Continuous control math remains in Modelica or the engine kernels, so a new sequence changes the plan while the underlying simulation mechanism stays reusable.

Use cases with an observable outcome

Choose a mission question that can be answered by the run, not merely shown in a demo.

Landing sequence

Release the rover only after touchdown is real.

Connect the powered-descent model, landing events, and post-landing mission handoff in one authored scenario.

Lander simulation → Surface operations

Test whether the route survives the vehicle state.

Run waypoint behavior against terrain and vehicle dynamics, then identify where the traverse stops being viable.

Rover simulation →
Automation

Repeat the same mission question.

Use the API and authored observers to compare runs in CI or in an external engineering workflow.

Repeatable studies

Make the result useful to the team.

A mission run becomes an engineering result when its objective, assumptions, observations, and outcome stay together.

Name the objective
State what the mission must accomplish and what counts as success, failure, or a safe handoff.
Record the conditions
Keep the vehicle, environment, initial state, scenario policy, and assumptions that shaped the run with the result.
Compare the evidence
Use events, named ports, telemetry, and authored observers to explain what changed between one run and the next.

Make the next mission decision executable.

The companion article explains the workflow in plain language: From CONOPS to an executable mission.

Download LunCoSimRead the mission tutorials