Build a Desalination Multi-Train Chemical Pre-Treatment Dosing and Energy Balancer

Evaluate coagulant and antiscalant consumption across seawater reverse osmosis pre-treatment trains. Compare operational dosing regimes against power consumption to formulate cost-effective treatment schedules.

Water Treatment Process Chemist

Ingest raw seawater intake telemetry including turbidity, temperature, and total dissolved solids.

Model pre-treatment chemical consumption and high-pressure reverse osmosis flux using WaterTAP principles.

Calculate chemical dosage costs alongside hourly grid electrical tariff rates.

Synthesize operational setpoint recommendations for plant chemical dosing controllers.

Multi-train process dashboard displaying intake water quality trends, dosing setpoints, and unit production cost charts.

Utilize WaterTAP RO flowsheet example parameters parameterized with seasonal Arabian Gulf seawater salinity profiles. Starter examples below are synthetic. They are not downloaded records.

WaterTAP treatment modeling Implements WaterTAP unit model relationships for reverse osmosis pressure drops and pre-treatment chemical consumption scaling.

ray-serve, watertap, numpy. Ray Serve efficiently distributes concurrent parameter evaluation across multiple parallel desalination treatment trains. Local or hosted LLM with strong technical explanation and chemical process parameter formatting.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

Parses intake water quality parameters and maps them to membrane fouling indices.

Computes optimal antiscalant dosage (mg/L) using WaterTAP scaling equations.

Determines total operating expense per cubic meter including electrical and chemical costs.

Outputs an operator-ready dosing schedule with high-turbidity alarm flags.

```json [ { "input": { "train_id": "TRAIN-B", "intake_turbidity_ntu": 4.8, "intake_tds_ppm": 42000, "intake_temp_c": 31, "permeate_flow_m3h": 400, "antiscalant_unit_cost_usd_kg": 3.2, "electricity_cost_usd_kwh": 0.08 }, "expected_output": { "recommended_setpoints": { "antiscalant_dose_ppm": 2.4, "coagulant_dose_ppm": 1.1, "feed_pressure_bar": 64.2, "chemical_cost_per_m3_usd": 0.011, "total_unit_cost_usd_m3": 0.385 }, "membrane_scaling_risk": "NOMINAL", "requires_chemist_signoff": true } }, { "input": { "train_id": "TRAIN-C", "intake_turbidity_ntu": 25, "intake_tds_ppm": 42000, "intake_temp_c": 31, "permeate_flow_m3h": 400, "antiscalant_unit_cost_usd_kg": 3.2, "electricity_cost_usd_kwh": 0.08 }, "expected_output": { "recommended_setpoints": {}, "alarm": "HIGH_TURBIDITY_EXCEEDS_DAF_CAPACITY", "membrane_scaling_risk": "CRITICAL", "requires_chemist_signoff": true } } ] ```

Simulation and recommendation only; chemical metering pumps remain governed by hard-coded safety PLCs. Use mock external writes. Require human review before any real deployment.