name: thermodynamic-economics description: | Thermodynamic foundations for distributed systems design. Use when analyzing energy flows, EROEI calculations, autopoietic closure, or validating economic models against physical constraints. Triggers: energy economics, thermodynamic analysis, EROEI, autopoiesis, Energy Seneca, heterotroph/autotroph analysis, network energy costs, Fourth Transition concepts.

Thermodynamic Economics

Purpose

This skill provides the thermodynamic foundations required to validate any distributed economic system against physical reality. It addresses the critique that metaphorical frameworks (mycelial networks, Dunbar limits) often lack thermodynamic grounding.

Core Principles

The Heterotroph Problem

Any distributed network must answer: Where does the energy come from and how does it flow?

AUTOTROPH (Primary Producer)     HETEROTROPH (Consumer)
─────────────────────────────    ─────────────────────────
Captures external energy         Consumes already-captured energy
Examples: Plants, solar PV       Examples: Fungi, animals, most tech
Creates energy gradient          Dissipates energy gradient
Can be autopoietic alone         Cannot be autopoietic alone

Key insight: A mycelial/fungal network metaphor describes distribution topology, not energy generation. Fungi decompose dead organic matter (stored solar energy). Any "mycelial economics" must specify its autotrophic energy source.

Energy Return on Energy Invested (EROEI/EROIp)

EROIp = Energy Delivered to Society / Energy Required for Extraction

Historical fossil fuel EROIp:    | Current status:
1930s oil: ~100:1                | Conventional oil: 10-20:1
1970s oil: ~30:1                 | Tight oil/fracking: 5-10:1  
Peak conventional: ~35:1         | Solar PV: 10-20:1
                                 | Wind: 15-25:1
                                 | Biofuels: 1-3:1

Minimum societal viability: ~7-10:1 (supports industrial complexity)
Below 5:1: Cannot maintain current infrastructure
At 1:1: Thermodynamic equilibrium (dead state)

The Three Thermodynamic Laws Applied

First Law (Conservation): Energy cannot be created or destroyed
- Implication: Total energy in = Total energy out + storage changes
- For any network: Map all energy inputs, outputs, and stocks
Second Law (Entropy): Entropy always increases in isolated systems
- Implication: Every energy transformation has losses
- For any network: Calculate waste heat at each transformation step
Third Law (Absolute Zero): Perfect efficiency is impossible
- Implication: No process achieves 100% conversion
- For any network: Budget for irreversible losses

Autopoiesis Defined

An autopoietic system produces and maintains itself by creating its own components.

Autopoietic requirements:
1. Self-production of components
2. Boundary/membrane maintenance  
3. Operational closure (processes produce processes)
4. Thermodynamic openness (energy/matter exchange with environment)
5. Positive net energy after self-maintenance

Dr. Arnoux's claim: Humankind ceased being autopoietic between 2010-2020
Meaning: Our civilization can no longer reproduce its operational basis 
         from currently accessible energy flows

Analysis Framework

Step 1: Map Energy Sources (Autotrophic Base)

For any proposed system, identify:

| Source Type | Capture Method | Location | Capacity (W) | EROEI |
|-------------|---------------|----------|--------------|-------|
| Solar       | PV panels     | ...      | ...          | 10-20 |
| Wind        | Turbines      | ...      | ...          | 15-25 |
| Hydro       | Turbines      | ...      | ...          | 40-60 |
| Geothermal  | Heat exchange | ...      | ...          | 5-15  |
| Fossil      | Extraction    | ...      | ...          | 5-20  |

Step 2: Map Energy Flows (Transformation Chain)

Source → Capture → Storage → Distribution → End Use → Waste
   ↓         ↓        ↓           ↓            ↓        ↓
100%      20-40%   70-90%      85-95%       20-80%   Heat

Calculate cumulative efficiency: E_net = E_source × η₁ × η₂ × η₃ × η₄

Step 3: Calculate Network Energy Costs

For distributed systems, include:

# Network maintenance energy
E_network = (
    E_node_operation +      # Computation, storage per node
    E_communication +       # Data transmission between nodes
    E_consensus +           # Distributed consensus overhead
    E_redundancy +          # Fault tolerance copies
    E_infrastructure        # Physical infrastructure maintenance
)

# Net available for productive work
E_available = E_captured - E_network - E_losses

# System viability condition
VIABLE = E_available > 0 AND EROEI_system > 7

Step 4: Autopoietic Closure Check

# Can the system reproduce itself from available energy?
reproduction_energy = (
    E_replace_components +   # Physical replacement of worn parts
    E_train_operators +      # Knowledge transfer to new operators  
    E_maintain_supply_chain +# Energy to maintain material inputs
    E_adapt_to_changes       # Energy for system evolution
)

AUTOPOIETIC = E_available > reproduction_energy

Integration with Univrs.io

The Hyphal Network Critique

Current state: The Hyphal Network describes a distribution topology based on:

Small-world network properties (Watts-Strogatz)
Dunbar-limited local clustering
Market-based "Kiers model" coordination

Missing: Explicit energy source and flow specification

Required Integration

Proposed Architecture:
                                    
┌─────────────────────────────────────────────────────────┐
│                  AUTOTROPHIC LAYER                       │
│  Solar/Wind/Hydro → Energy Capture → Primary Storage    │
└────────────────────────────┬────────────────────────────┘
                             │ Energy Flow
                             ▼
┌─────────────────────────────────────────────────────────┐
│                  DISTRIBUTION LAYER                      │
│  Hyphal Network Topology (Small-World + Dunbar)         │
│  Spirit Packages (.dol → .spirit) for coordination      │
│  VUDO VM Runtime for execution                          │
└────────────────────────────┬────────────────────────────┘
                             │ Net Energy
                             ▼
┌─────────────────────────────────────────────────────────┐
│                  HETEROTROPHIC LAYER                     │
│  Productive work, value creation, ecosystem services    │
│  (Constrained by available net energy)                  │
└─────────────────────────────────────────────────────────┘

Small Worlds Mathematics

See references/small-worlds-math.md for complete Watts-Strogatz formalism.

Key metrics for any proposed network:

Clustering coefficient C(p)
Characteristic path length L(p)
Small-world coefficient σ = (C/C_random) / (L/L_random)
Scaling behavior: L ∝ log(N)/log(k) for small-world

Scripts

scripts/eroei_calculator.py — Calculate EROEI for energy systems
scripts/energy_flow_analyzer.py — Map energy flows through network
scripts/small_world_metrics.py — Calculate Watts-Strogatz metrics

References

references/small-worlds-math.md — Complete Watts-Strogatz formalism
references/eroei-database.md — EROEI values for energy sources
references/arnoux-framework.md — Fourth Transition concepts
references/autopoiesis-checklist.md — Maturana-Varela framework applied

Learning Path

Thermodynamics primer: Entropy, exergy, dissipative structures
EROEI deep dive: Hall, Murphy, Cleveland's work
Autopoiesis: Maturana & Varela's original formulation
Small worlds: Watts & Strogatz 1998 paper
Fourth Transition: Dr. Arnoux's Medium series and FTI work
Integration: Apply to Univrs.io architecture

Validation Checklist

Before claiming any system is "sustainable" or "viable":

Energy sources explicitly identified (autotrophic base)
EROEI calculated for each energy source
Energy flow chain mapped with efficiency at each step
Network energy costs calculated (computation, communication, consensus)
Net energy positive after all losses
Autopoietic closure demonstrated (can reproduce operational basis)
Small-world metrics calculated if claiming network benefits
Dunbar limits applied correctly (cognitive, not just numerical)

thermodynamic-economics

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