Aether Prime Elite: Systems Architecture and Monte Carlo Evaluation of a Modular Interplanetary Freight Transportation Network
Authors/Creators
Description
Aether Prime Elite is a conceptual modular interplanetary freight transportation architecture evaluated through large-scale Monte Carlo systems modeling.
The architecture separates long-lived orbital transport infrastructure from planetary landing systems through a reusable orbital Mule tug, Shuttle cargo landers, and modular cargo pods. The objective is to investigate whether a modular freight-network approach can improve expected-value logistics performance relative to tanker-dependent interplanetary transportation architectures.
This archive contains:
• Monte Carlo simulation results
• Systems architecture documentation
• Methodology documentation
• Assumptions and parameter ranges
• Reproducibility notes
• Source-code files
• Metadata records
• Validation studies
• Results summaries
Computational workflows, validation sweeps, and optimization studies were executed using Python-based Monte Carlo models in Google Colab and standard Python environments.
Key validation outputs from the Maximum Elite Upgrade configuration include:
• Elite Win Rate: 97.61%
• Overall Win Rate: 100.00%
• Mean Cycle Success: 96.32%
• Mean Delivered Cargo: 115.59 tonnes per cycle
• Median Cost: $1,734 per kilogram
• Probability Cost ≤ $3,000/kg: 97.74%
• Probability ΔV ≥ 5.2 km/s: 100.00%
• Median 50-Cycle Cost: $10.06B
This work represents a conceptual systems-model evaluation and should not be interpreted as experimental validation, certified aerospace engineering, or proof of real-world feasibility.
The archive is intended for research discussion, reproducibility, systems engineering analysis, and long-term scholarly preservation.
Methods
Research Scope and Reproducibility
This archive presents Aether Prime Elite, a conceptual modular interplanetary freight transportation architecture evaluated through large-scale Monte Carlo systems modeling. The study investigates reusable orbital infrastructure, modular cargo delivery systems, lifecycle economics, reliability optimization, and expected-value logistics performance across long-duration Mars transportation scenarios.
Simulation workflows, validation sweeps, and optimization studies were developed in Python and executed using Google Colab and standard Python environments. The archive includes source code, simulation outputs, methodology documentation, parameter assumptions, architecture descriptions, validation studies, and reproducibility notes to support independent verification and future extension of the work.
The reported results are derived from computational modeling and should be interpreted as systems-level analytical outcomes rather than experimental validation, certified aerospace engineering, or proof of operational feasibility. The archive is intended for research discussion, reproducibility, systems engineering analysis, and long-term scholarly preservation.
Copyright © 2026 Abraham Joseph Heald. All rights reserved.
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Additional details
Software
- Development Status
- Active