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Urban Mining vs Space Mining: Hybrid Simulation Code

Authors: Matos, Anderson Adelson de; Vieira Neto, Ernesto; PERRELLA BALESTIERI, JOSE ANTONIO;

Urban Mining vs Space Mining: Hybrid Simulation Code

Abstract

Python implementation of a hybrid simulation model to analyze technological competition between urban mining (e-waste recycling) and space mining (asteroid resources) for future gold supply. This code accompanies the paper "Urban Mining vs. Space Mining: A Prospective Analysis of Technological Competition by Hybrid Simulation" submitted to Acta Astronautica. The model integrates three methodologies:- Ordinary Differential Equations (ODE) for technological growth modeling- Lotka-Volterra competition dynamics for market interaction simulation- Monte Carlo simulation for uncertainty quantification Features:- Static model with constant parameters (baseline analysis)- Dynamic model with time-evolving parameters (realistic scenarios)- Comprehensive sensitivity analysis tools- 8 predefined scenarios covering validation extremes to realistic projections- Automated figure generation and detailed reports Requirements: Python 3.8+, NumPy, Pandas, Matplotlib, SciPy, Seaborn See README.md for installation instructions and usage examples.

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Keywords

space mining, technological competition, urban mining, hybrid simulation, Lotka-Volterra, Monte Carlo, Python

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average