L1 ⚛ L1-206 ⊙ Testnet

Cryogenic Storage Boiloff — MLI heat-leak estimation

Heat Transfer · Multi-layer insulation heat-leak inverse

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Layer template

⬇ principle.md ⬇ principle.json

Fork L1-206

⬇ L1-206.md ⬇ L1-206.json

Prompt — copy into your LLM

You are helping me submit a MODIFICATION of L1-206 (Cryogenic Storage Boiloff — MLI heat-leak estimation) to the PWM Protocol — a Principle (L1) artifact.

I will paste a Markdown template (or the current L1-206.md).
1. Rewrite the Markdown so the science is correct and clearly explained for my change.
2. Regenerate the sibling L1-206.json so EVERY field matches the Markdown.
3. Keep the schema in the "File Mapping" footer at the bottom of the MD.
4. Keep the parent reference unchanged unless I ask otherwise.
Rules: the Markdown is the source of truth; use SI units; do NOT invent benchmark scores.
Output each file in its own fenced code block tagged with the filename.

Here is my template:
[PASTE THE .md HERE]

⚙ Forward Model

y = ∫_t dt `L.solid_conduction` `L.gas_conduction` `L.radiation_between_layers` x + n,    n ~ 𝒩(0, σ²)

world state x (heat leak W per m2)

→

L · radiation between layers `L.radiation_between_layers`

→

L · gas conduction `L.gas_conduction`

→

L · solid conduction `L.solid_conduction`

→

Temporal integration ∫_t dt

→

observation y (thermal detector)

Noise: additive Gaussian noise

Markdown — human-readable source of truth

⚙ auto-generated

⬇ L1-206.md

# ⚛ L1 Principle — Cryogenic Storage Boiloff — MLI heat-leak estimation **ID:** `L1-206` · **Status:** ⊙ Testnet (genesis catalog) > **🌐 Domain:** Heat Transfer — *Multi-layer insulation heat-leak inverse* > **🎯 Problem class:** linear inverse · **🧮 Solution space:** heat leak W per m2 > **📡 Carrier:** thermal · **🌫 Noise:** gaussian > **⚖ Difficulty (δ):** 3 · **⛓ Block:** 41554035 --- ## 🧠 1. Introduction **Cryogenic Storage Boiloff — MLI heat-leak estimation** is a **linear inverse problem** whose unknown lives in **heat leak W per m2** space, within the **Multi-layer insulation heat-leak inverse** sub-domain of **Heat Transfer**. Measurements consist of thermal radiation / temperature measurements via a **boiloff flowmeter** sensing mechanism. The forward operator applies, in order: L · radiation between layers operator; L · gas conduction operator; L · solid conduction operator; detector accumulates flux over the exposure window. Observations are corrupted by additive Gaussian noise. Conditional stability; mismatch parameters dominate at Omega bounds. ## ⚙ 2. Forward Model Physical chain: **x** → L · radiation between layers → L · gas conduction → L · solid conduction → Temporal integration → **y** (detector). ``` y = ∫_t dt `L.solid_conduction` `L.gas_conduction` `L.radiation_between_layers` x + n, n ~ 𝒩(0, σ²) ``` **Measurement DAG:** | Primitive | What it does | |---|---| | `L.radiation_between_layers` | L · radiation between layers operator | | `L.gas_conduction` | L · gas conduction operator | | `L.solid_conduction` | L · solid conduction operator | | `int.temporal` | Detector accumulates flux over the exposure window | ## 🔬 3. Physics Fingerprint | Property | Value | |---|---| | Domain | Heat Transfer | | Sub domain | Multi-layer insulation heat-leak inverse | | Carrier | thermal | | Problem class | linear_inverse | | Solution space | heat_leak_W_per_m2 | | Noise model | gaussian | | Integration axis | temporal | | Difficulty delta | 3 | | L dag | 3 | ## 📡 4. Measurement Model Conditional stability; mismatch parameters dominate at Omega bounds. | Metric | Value | |---|---| | Metric | PSNR_dB | | Secondary | SSIM | ## 📏 5. Operating Range (Ω) **Center problem class:** `mli_boiloff` · **Forward operator:** `mli_boiloff_forward` **Center point:** | Parameter | Unit | Value | |---|---|---| | T c k | — | 77 | | T h k | — | 300 | | Snr db | dB | 30 | | N layers | — | 20 | | N samples | — | 200 | | Layer spacing error | — | 0 | | Vacuum pressure error | — | 0 | | Layer emissivity error | — | 0 | **Allowed bounds:** | Parameter | Unit | Range | |---|---|---| | T c k | — | 4 – 250 | | T h k | — | 77 – 500 | | Snr db | dB | 0 – 40 | | N layers | — | 1 – 100 | | N samples | — | 10 – 10000 | | Layer spacing error | — | 0.0 – 0.3 | | Vacuum pressure error | — | 0.0 – 0.001 | | Layer emissivity error | — | 0.0 – 0.3 | ## 🎯 6. Tolerance (ε) **Center tolerance:** 24.0 | Metric | Range | |---|---| | Psnr db | 10.0 – 45.0 | ## ⚖ 7. Hardness Function Hardness scales as **`epsilon_fn`** on **PSNR_dB**, with κ = `200` and δ = `3`. ## 💾 8. Reference Dataset - **primary** · weight 1.0 · IPFS _(not pinned yet)_ ## 9. On-chain Registration - **Chain hash:** `0x601eeb79b9b6cd4da18dc611371345fe2e8f6150229ee037df88151a2c19f1df` - **Chain tx hash:** `0x6412fa9dc0b912c7ea35cf766cb4f1287504277a7194bf393aa0a154ac8a9c7d` - **Chain block:** `41554035` --- ## File Mapping This bundle consists of: `L1-206.md`, `L1-206.json`. | File | Role | How to regenerate | |------|------|-------------------| | `L1-206.md` | Source of truth — edit this | Human or LLM | | `L1-206.json` | Structured metadata for the registry | LLM regenerates from the sections above | **Prompt for your LLM after editing this Markdown:** > Read the attached Markdown. Regenerate the sibling `.json` so every field matches. > Preserve the schema documented in the rows above. > Output each file in its own fenced code block tagged with the filename. > Output only the JSON object. _This Markdown was auto-synthesized from the catalog row for `L1-206`._ _Edit it, regenerate the JSON, and submit at [/submit](/submit) to claim the artifact._

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L2-206-001 Cryogenic Storage Boiloff — MLI heat-leak estimation Mismatch-Only Spec

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📋 JSON metadata

{
  "artifact_id": "L1-206",
  "chain_block": 41554035,
  "chain_hash": "0x601eeb79b9b6cd4da18dc611371345fe2e8f6150229ee037df88151a2c19f1df",
  "chain_tx_hash": "0x6412fa9dc0b912c7ea35cf766cb4f1287504277a7194bf393aa0a154ac8a9c7d",
  "domain": "Heat Transfer",
  "hardness_fn": {
    "delta": 3,
    "kappa": 200,
    "metric": "PSNR_dB",
    "type": "epsilon_fn"
  },
  "initiator_dataset": [
    {
      "ipfs_cid": null,
      "license_hash": null,
      "name": "primary",
      "weight": 1.0
    }
  ],
  "layer": "L1",
  "observable_profile": {
    "metric": "PSNR_dB",
    "regime": "Conditional stability; mismatch parameters dominate at Omega bounds.",
    "secondary": "SSIM"
  },
  "physics_fingerprint": {
    "L_DAG": 3.0,
    "carrier": "thermal",
    "difficulty_delta": 3,
    "domain": "Heat Transfer",
    "integration_axis": "temporal",
    "noise_model": "gaussian",
    "primitives": [
      "L.radiation_between_layers",
      "L.gas_conduction",
      "L.solid_conduction",
      "int.temporal"
    ],
    "problem_class": "linear_inverse",
    "sensing_mechanism": "boiloff_flowmeter",
    "solution_space": "heat_leak_W_per_m2",
    "sub_domain": "Multi-layer insulation heat-leak inverse",
    "title": "Cryogenic Storage Boiloff \u2014 MLI heat-leak estimation"
  },
  "size_tiers": {
    "allowed_forward_operators": [
      "mli_boiloff_forward"
    ],
    "allowed_omega_dimensions": [
      "N_layers",
      "T_h_K",
      "T_c_K",
      "N_samples",
      "SNR_dB",
      "layer_emissivity_error",
      "vacuum_pressure_error",
      "layer_spacing_error",
      "layer_emissivity_error",
      "vacuum_pressure_error",
      "layer_spacing_error"
    ],
    "allowed_problem_classes": [
      "mli_boiloff"
    ],
    "center_spec": {
      "epsilon_fn_center": "24.0",
      "forward_operator": "mli_boiloff_forward",
      "input_format": "measurement_only",
      "omega": {
        "N_layers": 20,
        "N_samples": 200,
        "SNR_dB": 30,
        "T_c_K": 77,
        "T_h_K": 300,
        "layer_emissivity_error": 0.0,
        "layer_spacing_error": 0.0,
        "vacuum_pressure_error": 0.0
      },
      "problem_class": "mli_boiloff"
    },
    "epsilon_bounds": {
      "psnr_db": [
        10.0,
        45.0
      ]
    },
    "omega_bounds": {
      "N_layers": [
        1,
        100
      ],
      "N_samples": [
        10,
        10000
      ],
      "SNR_dB": [
        0,
        40
      ],
      "T_c_K": [
        4,
        250
      ],
      "T_h_K": [
        77,
        500
      ],
      "layer_emissivity_error": [
        0.0,
        0.3
      ],
      "layer_spacing_error": [
        0.0,
        0.3
      ],
      "vacuum_pressure_error": [
        0.0,
        0.001
      ]
    }
  },
  "staked_pwm": 0.0,
  "status": "testnet",
  "sub_domain": "Multi-layer insulation heat-leak inverse",
  "title": "Cryogenic Storage Boiloff \u2014 MLI heat-leak estimation"
}

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