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Submodule bumps land the deadlock fix (state.js residue unpark + MGC optimalControl dispatch reorder) and pumpingStation stopLevel hysteresis. - Renames examples/pumpingstation-3pumps-dashboard → pumpingstation-complete-example with regenerated flow.json. New dashboard groups, demand-broadcast wiring, S88 placement rule applied, ui-chart trend-split and link-channel naming follow .claude/rules/node-red-flow-layout.md. - New cross-node test harness under test/: end-to-end-pumpingstation drives PS + MGC + 3 pumps + physics simulator end-to-end and verifies the ~5/15 min cycle. - Adds Grafana provisioning dashboards (pumping-station.json) and a helper sync-example.sh script for export/import to live Node-RED. - Docker entrypoint + settings + compose tweaks for the persistent user dir layout used by the demo. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
54 lines
3.8 KiB
Markdown
54 lines
3.8 KiB
Markdown
# EVOLV — End-to-End Example Flows
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> **Working with these examples?** See [`WORKFLOW.md`](WORKFLOW.md) — the canonical guide for editing, switching projects, persistence, and debugging.
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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.
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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.
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## Catalogue
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| Folder | What it shows |
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| [`pumpingstation-complete-example/`](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. |
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## How it loads
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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.
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To run:
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1. `docker compose up -d` from the EVOLV root.
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2. Open Node-RED at `http://localhost:1880`.
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3. Menu → **Projects** → **Open Project** → pick one.
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4. Open the FlowFuse dashboard at `http://localhost:1880/dashboard`.
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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.
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Each example uses a unique dashboard `path` so they can coexist if you load multiple in the same runtime.
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## Adding new examples
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When you create a new end-to-end example:
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1. Make a subfolder under `examples/` named `<scenario>-<focus>`.
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2. Include at least `flow.json` and `README.md`. A `build_flow.py` (or equivalent generator) is recommended so the JSON stays diff-friendly.
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3. `docker compose restart nodered` — the entrypoint will bootstrap your new folder as a Node-RED project (synthesizes `package.json`, `git init`, initial commit) under `/data/projects/<name>/`.
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4. Editor → Projects → Open Project → pick your new one.
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5. Add a row to the catalogue table above.
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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>`.
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## Wishlist for future examples
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These are scenarios worth building when there's a session for it:
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- **Pump failure + MGC re-routing** — kill pump 2 mid-run, watch MGC redistribute to pumps 1 and 3.
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- **Energy-optimal vs equal-flow control** — same demand profile run through `optimalcontrol` and `prioritycontrol` modes side-by-side, energy comparison chart.
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- **Schedule-driven demand** — diurnal flow pattern (low at night, peak at 7 am), MGC auto-tuning over 24 simulated hours.
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- **Reactor + clarifier loop** — `reactor` upstream feeding `settler`, return sludge controlled by a small `pumpingStation`.
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- **Diffuser + DO control** — aeration grid driven by a PID controller from a dissolved-oxygen sensor.
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- **Digital sensor bundle** — MQTT-style sensor (BME280, ATAS, etc.) feeding a `measurement` node in digital mode + parent equipment node.
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- **Maintenance window** — entermaintenance / exitmaintenance cycle with operator handover dashboard.
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- **Calibration walk-through** — measurement node calibrate cycle with stable / unstable input demonstrations.
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