# ⚛  L1 Principle — Euler-Bernoulli Beam — thin-beam bending

**ID:** `L1-208` · **Status:** ⊙ Testnet (genesis catalog)

> **🌐 Domain:** Structural Mechanics — *Classical thin-beam bending PDE*
> **🎯 Problem class:** linear inverse · **🧮 Solution space:** beam deflection 1D
> **📡 Carrier:** mechanical · **🌫 Noise:** gaussian
> **⚖ Difficulty (δ):** 3 · **⛓ Block:** 41554009

---

## 🧠 1. Introduction

**Euler-Bernoulli Beam — thin-beam bending** is a **linear inverse problem** whose unknown lives in **beam deflection 1D** space, within the **Classical thin-beam bending PDE** sub-domain of **Structural Mechanics**.

Measurements consist of mechanical vibrations or strain signals via a **strain gauges lvdt** sensing mechanism.

The forward operator applies, in order: L · bending stiffness operator; L · 4th order pde 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 · bending stiffness → L · 4th order pde → L · bc → Spatial integration → **y** (detector).

```
y = ∫_A dA `L.bc` `L.4th_order_pde` `L.bending_stiffness` x + n,    n ~ 𝒩(0, σ²)
```

**Measurement DAG:**

| Primitive | What it does |
|---|---|
| `L.bending_stiffness` | L · bending stiffness operator |
| `L.4th_order_pde` | L · 4th order pde operator |
| `L.bc` | L · bc operator |
| `int.spatial` | Pixel-level spatial averaging on the detector |

## 🔬 3. Physics Fingerprint

| Property | Value |
|---|---|
| Domain | Structural Mechanics |
| Sub domain | Classical thin-beam bending PDE |
| Carrier | mechanical |
| Problem class | linear_inverse |
| Solution space | beam_deflection_1D |
| 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:** `euler_bernoulli` · **Forward operator:** `euler_bernoulli_forward`

**Center point:**

| Parameter | Unit | Value |
|---|---|---|
| Snr db | dB | 30 |
| Ei error | — | 0 |
| Bc error | — | 0 |
| N sensors | — | 16 |
| N elements | — | 50 |
| Load error | — | 0 |

**Allowed bounds:**

| Parameter | Unit | Range |
|---|---|---|
| Snr db | dB | 0 – 40 |
| Ei error | — | 0.0 – 0.1 |
| Bc error | — | 0.0 – 0.2 |
| N sensors | — | 2 – 256 |
| N elements | — | 5 – 10000 |
| Load error | — | 0.0 – 0.1 |

## 🎯 6. Tolerance (ε)

**Center tolerance:** 28.0

| Metric | Range |
|---|---|
| Psnr db | 10.0 – 45.0 |

## ⚖ 7. Hardness Function

Hardness scales as **`epsilon_fn`** on **PSNR_dB**, with κ = `160` and δ = `3`.

## 💾 8. Reference Dataset

- **primary** · weight 1.0 · IPFS _(not pinned yet)_

## 9. On-chain Registration

- **Chain hash:** `0x946253cecb9371ebe20c0e79c8ccd11787742c2ebe2a5a9ae0e77cfd59a33a12`
- **Chain tx hash:** `0x2841ff2f212ab6e9e6f2820303f308c09e00427cf07d87adbe9b7b7c60d323d6`
- **Chain block:** `41554009`

---

## File Mapping

This bundle consists of: `L1-208.md`, `L1-208.json`.

| File | Role | How to regenerate |
|------|------|-------------------|
| `L1-208.md` | Source of truth — edit this | Human or LLM |
| `L1-208.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 `L1-208`._
_Edit it, regenerate the JSON, and submit at [/submit](/submit) to claim the artifact._