Reproducibility archive for "Risk-averse optimization of Internet of Things sensor placement in semiconductor wastewater networks: A mass-balanced simulation and Monte Carlo framework"

This record contains the complete anonymized reproducibility archive for the manuscript “Risk-averse optimization of Internet of Things sensor placement in semiconductor wastewater networks: A mass-balanced simulation and Monte Carlo framework.” The archive includes three reconstructed wastewater-network definitions, versioned configurations, mass-balanced simulation and event-generation code, exact sensor-placement enumeration, independent Monte Carlo evaluation, controller-aligned robustness analyses, time-step convergence checks, objective-form sensitivity analyses, machine-readable results, and a SHA-256 checksum manifest. Design selection uses 2,500 simulated training years, and assessment uses 50,000 independently generated annual Monte Carlo draws. The networks and results are computational benchmarks and do not represent proprietary factory layouts, private incident records, or external plant validation.