L1 ⚛ L1-188 ⊙ Testnet

Darcy Flow — low-Re porous-medium flow

Fluid Dynamics · Linear Darcy's law in porous media

⬇ Download bundle 🚀 Submit to mainnet — earn 100 PWM + 5% royalty

Markdown — human-readable source of truth

⚙ auto-generated

⬇ L1-188.md

# ⚛ L1 Principle — Darcy Flow — low-Re porous-medium flow **ID:** `L1-188` · **Status:** ⊙ Testnet (genesis catalog) > **🌐 Domain:** Fluid Dynamics — *Linear Darcy's law in porous media* > **🎯 Problem class:** linear inverse · **🧮 Solution space:** pressure velocity in porous > **📡 Carrier:** mechanical · **🌫 Noise:** gaussian > **⚖ Difficulty (δ):** 3 · **⛓ Block:** 41553977 --- ## 🧠 1. Introduction **Darcy Flow — low-Re porous-medium flow** is a **linear inverse problem** whose unknown lives in **pressure velocity in porous** space, within the **Linear Darcy's law in porous media** sub-domain of **Fluid Dynamics**. Measurements consist of mechanical vibrations or strain signals via a **piezometers tracer** sensing mechanism. The forward operator applies, in order: L · darcy linear operator; L · mass conservation operator; L · bc operator; pixel-level spatial averaging on the detector. Observations are corrupted by additive Gaussian noise. Conditional stability; mismatch parameters dominate at Omega bounds. ## ⚙ 2. Forward Model Physical chain: **x** → L · darcy linear → L · mass conservation → L · bc → Spatial integration → **y** (detector). ``` y = ∫_A dA `L.bc` `L.mass_conservation` `L.darcy_linear` x + n, n ~ 𝒩(0, σ²) ``` **Measurement DAG:** | Primitive | What it does | |---|---| | `L.darcy_linear` | L · darcy linear operator | | `L.mass_conservation` | L · mass conservation operator | | `L.bc` | L · bc operator | | `int.spatial` | Pixel-level spatial averaging on the detector | ## 🔬 3. Physics Fingerprint | Property | Value | |---|---| | Domain | Fluid Dynamics | | Sub domain | Linear Darcy's law in porous media | | Carrier | mechanical | | Problem class | linear_inverse | | Solution space | pressure_velocity_in_porous | | Noise model | gaussian | | Integration axis | spatial | | Difficulty delta | 3 | | L dag | 2.8 | ## 📡 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:** `darcy` · **Forward operator:** `darcy_forward` **Center point:** | Parameter | Unit | Value | |---|---|---| | H | px | 128 | | W | px | 128 | | Z | — | 32 | | Snr db | dB | 30 | | Bc error | — | 0 | | Viscosity error | — | 0 | | Permeability error | — | 0 | **Allowed bounds:** | Parameter | Unit | Range | |---|---|---| | H | px | 16 – 1024 | | W | px | 16 – 1024 | | Z | — | 8 – 512 | | Snr db | dB | 0 – 40 | | Bc error | — | 0.0 – 0.2 | | Viscosity error | — | 0.0 – 0.1 | | Permeability error | — | 0.0 – 0.3 | ## 🎯 6. Tolerance (ε) **Center tolerance:** 26.0 | 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:** `0x32fed19be36cc2c5ae115920fc3d4ccd17d55f6e3a9c5135006586191ce5b8aa` - **Chain tx hash:** `0x8306ffe18a481beb6d6bd02c9afb6a7e714305e098805c3ab04b95fc403e3053` - **Chain block:** `41553977` --- ## File Mapping This bundle consists of: `L1-188.md`, `L1-188.json`. | File | Role | How to regenerate | |------|------|-------------------| | `L1-188.md` | Source of truth — edit this | Human or LLM | | `L1-188.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 `L1-188`._ _Edit it, regenerate the JSON, and submit at [/submit](/submit) to claim the artifact._

📝 Polish this artifact in your LLM

Download the files on the right.
Paste the Markdown into ChatGPT / Claude / Gemini and edit freely.
Send your edited Markdown back with the prompt below.
Save the regenerated JSON, then submit via /submit.

Prompt to give your LLM

Read the attached Markdown (L1-188.md).
Regenerate L1-188.json so every field matches the Markdown.
Preserve the schema documented in the File Mapping footer at the bottom of the MD.
Output each file in its own fenced code block tagged with the filename.

⌥ Hierarchy

Upstream lineage and downstream children

↓ L2 Spec 1 child ▾

L2-188-001 Darcy Flow — low-Re porous-medium flow Mismatch-Only Spec

⬇ Download bundle

2 files · click to download

📋 JSON metadata

{
  "artifact_id": "L1-188",
  "chain_block": 41553977,
  "chain_hash": "0x32fed19be36cc2c5ae115920fc3d4ccd17d55f6e3a9c5135006586191ce5b8aa",
  "chain_tx_hash": "0x8306ffe18a481beb6d6bd02c9afb6a7e714305e098805c3ab04b95fc403e3053",
  "domain": "Fluid Dynamics",
  "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": 2.8,
    "carrier": "mechanical",
    "difficulty_delta": 3,
    "domain": "Fluid Dynamics",
    "integration_axis": "spatial",
    "noise_model": "gaussian",
    "primitives": [
      "L.darcy_linear",
      "L.mass_conservation",
      "L.bc",
      "int.spatial"
    ],
    "problem_class": "linear_inverse",
    "sensing_mechanism": "piezometers_tracer",
    "solution_space": "pressure_velocity_in_porous",
    "sub_domain": "Linear Darcy\u0027s law in porous media",
    "title": "Darcy Flow \u2014 low-Re porous-medium flow"
  },
  "size_tiers": {
    "allowed_forward_operators": [
      "darcy_forward"
    ],
    "allowed_omega_dimensions": [
      "H",
      "W",
      "Z",
      "SNR_dB",
      "permeability_error",
      "viscosity_error",
      "bc_error",
      "permeability_error",
      "viscosity_error",
      "bc_error"
    ],
    "allowed_problem_classes": [
      "darcy"
    ],
    "center_spec": {
      "epsilon_fn_center": "26.0",
      "forward_operator": "darcy_forward",
      "input_format": "measurement_only",
      "omega": {
        "H": 128,
        "SNR_dB": 30,
        "W": 128,
        "Z": 32,
        "bc_error": 0.0,
        "permeability_error": 0.0,
        "viscosity_error": 0.0
      },
      "problem_class": "darcy"
    },
    "epsilon_bounds": {
      "psnr_db": [
        10.0,
        45.0
      ]
    },
    "omega_bounds": {
      "H": [
        16,
        1024
      ],
      "SNR_dB": [
        0,
        40
      ],
      "W": [
        16,
        1024
      ],
      "Z": [
        8,
        512
      ],
      "bc_error": [
        0.0,
        0.2
      ],
      "permeability_error": [
        0.0,
        0.3
      ],
      "viscosity_error": [
        0.0,
        0.1
      ]
    }
  },
  "staked_pwm": 0.0,
  "status": "testnet",
  "sub_domain": "Linear Darcy\u0027s law in porous media",
  "title": "Darcy Flow \u2014 low-Re porous-medium flow"
}

🎁

Earn PWM by promoting this to mainnet

• 100 PWM one-time grant on mainnet promotion
• 5% upstream royalty on every downstream L4 mining event, forever
• Your wallet is enrolled the moment the founder accepts

🚀 Submit to mainnet →

How: Download the bundle above → polish the Markdown in ChatGPT / Claude / Gemini → submit your version → founder reviews → mainnet.