aec90cc8e7
Pump-shutdown deadlock fix split across two submodules: - rotatingMachine@8f9150e: shutdown sequence clears state.delayedMove so the abort-and-return-to-operational path doesn't auto-pickup the queued setpoint and re-engage the pump. - machineGroupControl@ea2857f: turnOffAllMachines clears MGC's _delayedCall and serializes per-pump shutdown so PS's 2 s tick loop can't interrupt an in-flight shutdown. Live verification on pumpingstation-complete-example demo: basin now shuts pumps off at stopLevel cleanly, reverses to fill, completes the hysteresis cycle. Also disable the trends page in the demo flow (build_flow.py + regen flow.json). FlowFuse ui-chart's per-series server-side history buffer (7 charts × ~20 series × 3600-point retention) was saturating the Node-RED event loop at 129% CPU, making the dashboard freeze on every click. Trends remain available — just disabled by default; flip the ui_page_trends "d" key to false to re-enable. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
EVOLV — End-to-End Example Flows
Working with these examples? See
WORKFLOW.md— the canonical guide for editing, switching projects, persistence, and debugging.
Demo flows that show how multiple EVOLV nodes work together in a realistic wastewater-automation scenario. Each example is self-contained: its folder has a flow.json you can import directly into Node-RED plus a README.md that walks through the topology, control modes, and dashboard layout.
These flows complement the per-node example flows under nodes/<name>/examples/ (which exercise a single node in isolation). Use the per-node flows for smoke tests during development; use the flows here when you want to see how a real plant section behaves end-to-end.
Catalogue
| Folder | What it shows |
|---|---|
pumpingstation-complete-example/ |
End-to-end stack: pumpingStation + MGC + 3 pumps + 12 measurement nodes (4 per pump, physics-coupled), operator-driven inflow with scenario buttons (Constant / Sine / Diurnal / Storm), FlowFuse dashboard (realtime + 1h trends), and provisioned Grafana dashboard backed by InfluxDB. |
How it loads
Each subfolder here is a Node-RED project. The Docker stack has Node-RED's Projects feature enabled and bootstraps each examples/<name>/ into /data/projects/<name>/ on first container start.
To run:
docker compose up -dfrom the EVOLV root.- Open Node-RED at
http://localhost:1880. - Menu → Projects → Open Project → pick one.
- Open the FlowFuse dashboard at
http://localhost:1880/dashboard.
The default active project is pumpingstation-complete-example (override via DEFAULT_PROJECT env var on the nodered service). Switching is two clicks; persistence is handled by the evolv_nodered_data named volume — docker compose down && up doesn't lose the active flow.
Each example uses a unique dashboard path so they can coexist if you load multiple in the same runtime.
Adding new examples
When you create a new end-to-end example:
- Make a subfolder under
examples/named<scenario>-<focus>. - Include at least
flow.jsonandREADME.md. Abuild_flow.py(or equivalent generator) is recommended so the JSON stays diff-friendly. docker compose restart nodered— the entrypoint will bootstrap your new folder as a Node-RED project (synthesizespackage.json,git init, initial commit) under/data/projects/<name>/.- Editor → Projects → Open Project → pick your new one.
- Add a row to the catalogue table above.
The bootstrap skips folders that already exist in the volume. To force a refresh of an existing project from the repo source (e.g. after editing build_flow.py), use ./scripts/sync-example.sh <name>.
Wishlist for future examples
These are scenarios worth building when there's a session for it:
- Pump failure + MGC re-routing — kill pump 2 mid-run, watch MGC redistribute to pumps 1 and 3.
- Energy-optimal vs equal-flow control — same demand profile run through
optimalcontrolandprioritycontrolmodes side-by-side, energy comparison chart. - Schedule-driven demand — diurnal flow pattern (low at night, peak at 7 am), MGC auto-tuning over 24 simulated hours.
- Reactor + clarifier loop —
reactorupstream feedingsettler, return sludge controlled by a smallpumpingStation. - Diffuser + DO control — aeration grid driven by a PID controller from a dissolved-oxygen sensor.
- Digital sensor bundle — MQTT-style sensor (BME280, ATAS, etc.) feeding a
measurementnode in digital mode + parent equipment node. - Maintenance window — entermaintenance / exitmaintenance cycle with operator handover dashboard.
- Calibration walk-through — measurement node calibrate cycle with stable / unstable input demonstrations.