Skills

A skill is a package of structured files that teaches an AI coding agent how to work with a specific tool or framework. The skill below was generated by Great Docs from this project’s documentation. Install it in your agent and it will be able to run commands, edit configuration, write content, and troubleshoot problems without step-by-step guidance from you.

Any agent — install with npx:

npx skills add https://lornearnold.github.io/driven-pile/

Codex / OpenCode

Tell the agent:
Fetch the skill file at https://lornearnold.github.io/driven-pile/skill.md and follow the instructions.

Manual — download the skill file:

curl -O https://lornearnold.github.io/driven-pile/skill.md

Or browse the SKILL.md file.

SKILL.md

---
name: driven-pile
description: >
  Long-term capacity of driven piles from the pile-driving log: a pore-pressure-tracking inversion of blow counts. Use when writing Python code that uses the driven_pile package.
license: GNU General Public License v3 or later (GPLv3+)
compatibility: Requires Python >=3.11.
---

# driven-pile

Long-term capacity of driven piles from the pile-driving log: a pore-pressure-tracking inversion of blow counts.

## Installation

```bash
pip install driven-pile
```

## API overview

### Inputs

The driving record, the pile and hammer that produced it, and the ground it was driven through.

- `DriveLog`: A pile-driving record, one entry per logged foot
- `Pile`: Pile geometry and stiffness
- `Hammer`: Driving hammer
- `SoilProfile`: Ground conditions at a pile location
- `bpm_to_stroke`: Hammer stroke from the blow rate of a free-falling ram
- `stroke_to_bpm`: Blow rate of a free-falling ram from its stroke; inverse of `bpm_to_stroke`

### Options

Model parameters and Monte Carlo settings, with the published values as defaults.

- `ModelOptions`: Parameters of the drive model
- `MonteCarloOptions`: Monte Carlo settings

### Pipeline

One function per stage of the method, and one call that runs them all.

- `analyze`: Characterize the soil from a driving log and estimate long-term capacity
- `prepare_target`: Build the capacity target from a driving log
- `sweep_top_phi`: Sweep a constant top-segment friction angle and find the admissible band
- `run_drive`: Characterize every foot sequentially from the capacity target, top down
- `long_term_capacity`: Long-term shaft and toe resistance of a `DriveResult`
- `monte_carlo`: Realizations of the long-term capacity under the five uncertainty sources

### Results

Dataclasses of plain NumPy arrays.

- `Analysis`: Everything `analyze` produces
- `Target`: Per-foot capacity target and static soil state on the analysis grid
- `TopPhiBand`: Admissible friction angles for the unlogged top segment
- `DriveResult`: Soil characterization and capacities from one drive-model run
- `MonteCarloResult`: Monte Carlo realizations of the long-term capacity

### DriveResult Methods

Methods for the DriveResult class

- `DriveResult.n_logged`
- `DriveResult.logged`
- `DriveResult.reason_counts`
- `DriveResult.fraction_liquefied`
- `DriveResult.plot_profile`
- `DriveResult.plot_fit`

### Equation-level functions

The equations of the method, importable from the submodules for teaching and testing.

- `formulas.elastic_set`
- `formulas.danish_capacity`
- `preprocess.smooth_capacity`
- `preprocess.sigma_v0_profile`
- `preprocess.extend_to_mudline`
- `preprocess.residual_scale`
- `bearing.nq_vesic`
- `bearing.rigidity_index`
- `bearing.toe_bearing`
- `bearing.phi_from_toe_bearing`
- `bearing.phi_from_toe_bearing_grid`
- `spt.phi_from_n160`
- `spt.n160_from_phi`
- `shaft.coyle_castello_k`
- `shaft.nordlund_k_delta`
- `shaft.fs_coyle_castello`
- `shaft.interface_alpha`
- `shaft.fs_partially_liquefied`
- `liquefaction.delta_n_fines`
- `liquefaction.n160_clean_sand`
- `liquefaction.crr_m75`
- `liquefaction.k_sigma`
- `liquefaction.crr_15`
- `liquefaction.csr_driving`
- `liquefaction.cycles_to_liquefaction`
- `liquefaction.ru_linear`
- `liquefaction.residual_strength`
- `capacity.shaft_long_term`
- `capacity.toe_end_of_drive`
- `characterization.triggering_state`
- `characterization.characterize_foot`

## Resources

- [Full documentation](https://lornearnold.github.io/driven-pile/)
- [llms.txt](llms.txt) — Indexed API reference for LLMs
- [llms-full.txt](llms-full.txt) — Comprehensive documentation for LLMs
- [Source code](https://github.com/lornearnold/driven-pile)