Artificial Intelligence Predictive Liquid Quality System for High-Performance Computing (HPC) Data Center Cooling Loops (AIPWQ)

Method claim

• A method for predictive liquid quality management in a high-performance computing cooling loop comprising the steps of:
• periodically extracting coolant samples from the loop;
• performing assays on the samples to detect contaminants and chemical properties;
• measuring operational parameters including pressure, flow rate, and temperature of the coolant loop;
• transmitting analytical and sensor data to a data processing unit;
• applying artificial intelligence algorithms trained on historical coolant chemistry, workload telemetry, pressure data, temperature data and flow data to forecast deterioration events;
• and
• generating alerts and corrective action recommendations without direct chemical dosing.

Computer-Readable Medium Claim

• A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause the processor to:
• receive analytical data from coolant assays and sensor measurements including pressure, flow rate, and temperature;
• process the data locally or transmit the data to a remote server for centralized analysis;
• apply artificial intelligence algorithms trained on historical coolant chemistry, workload telemetry, pressure data, and flow data to forecast deterioration events;
• and
• generate alerts and corrective action recommendations without direct chemical dosing.