AMPEL360-BWB-Q/ampel360-config.yaml at main · AmedeoPelliccia/AMPEL360-BWB-Q · GitHub

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# AMPEL360 H₂-BWB-Q Enterprise Framework Configuration
# Main configuration for the complete enterprise framework

meta:
  version: "1.0"
  framework: "AMPEL360-H2-BWB-Q"
  last_updated: "2025-08-26"
  status: "P2-Approved-Pending-QNNN"

# Organizational Configuration
organizational:
  governance:
    program_board:
      chair: "Chief Architect (DT)"
      members: ["CSE Office", "Cert Lead", "H2 Infrastructure Lead", "Safety of AI Officer"]

    committees:
      ARB: "Architecture Review Board"
      SRB: "Safety Review Board"
      CWG: "Configuration Working Group"
      HCC: "Hard Constraints Committee"
      DSC: "Digital Systems Committee"

  financial:
    budget_allocation:
      r_and_d: 0.40
      infrastructure: 0.25
      certification: 0.20
      manufacturing: 0.15

    funding_sources:
      - government_grants
      - private_investment
      - defense_contracts
      - commercial_partnerships

# Procedural Configuration
procedural:
  phase_gates:
    P1: "Conservative Configuration"
    P2: "Introduce BWB"
    P3: "Full Optimal Configuration"

  current_phase: "P2"

  processes:
    design_review: "quarterly"
    change_control: "gated"
    risk_management: "continuous"
    certification: "phased"

# Technological Configuration
technological:
  architecture_domains:
    - A-ARCHITECTURE
    - M-MECHANICAL
    - E-ENVIRONMENTAL
    - D-DIGITAL
    - E2-ENERGY
    - O-OPERATING_SYSTEMS
    - P-PROPULSION
    - E3-ELECTRONICS
    - L-LOGISTICS
    - L2-LINKS
    - I-INFRASTRUCTURES
    - C-CONTROL
    - C2-CRYOGENICS

  hydrogen_systems:
    storage_type: "LH2"
    distribution: "integrated"
    safety_level: "aerospace_grade"

# Machine Learning Configuration
machine_learning:
  algorithms:
    - QAOA
    - quantum_neural_networks
    - classical_ml_ensemble

  simulation:
    models: ["CFD", "FEA", "systems_integration"]
    digital_twin: true
    real_time_capable: true

# Integration Points
integration:
  existing_config: "ampel360_config.json"
  constraints: "constraints/hard_constraints.yaml"
  candidates: "OPTIM-FRAMEWORK/I-INTELLIGENT/data/candidates.yaml"
  optimization_engine: "OPTIM-FRAMEWORK/I-INTELLIGENT/scripts/qaoa_over_F.py"

# Performance Metrics
metrics:
  trl_target: 6
  certification_readiness: 0.85
  feasible_set_size: 1000
  optimization_convergence: 0.95