Computational materials for:
Safe Aggregation in Modular Sustainability Assessment: Process Interfaces, Interface-Aware Pareto Screening, and Contextual Budgets

Author: Juan Jose Segura

Canonical code:
- simulation_master.py

Canonical numerical outputs:
- monte_carlo_lambda_series.csv
- monte_carlo_class_series.csv
- monte_carlo_nk_sensitivity.csv
- benchmark_system_burdens.csv

Master random seed: 20260909
Monte Carlo systems: 160,000 total across the three reported experiments.

Software environment used:
- Python 3.13.5
- NumPy 2.3.5
- pandas 2.2.3
- Matplotlib 3.10.8

The simulations are controlled methodological stress tests. Their random distributions are generic and are not empirical distributions of LCA technologies, impacts, or modeling errors.
