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Context Engineering Example | Flocode Newsletter

The text below is an example of a context engineering document for use with AI assisted engineering and design. You may choose to include 'fixed' geometry in this document or you may prefer to design with iterative inputs hardcoded into your design pipeline. Both are possible.

PROJECT REQUIREMENTS: INDUSTRIAL PORTAL FRAME STRUCTURAL DESIGN TOOL

NOTE: This document has been scrubbed of identifying information for use as a general example.

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# ---- FULL CONSOLIDATED SCRIPT FROM FLOCODE NEWSLETTER #068 - Structuring Engineering Calculations in Python | 01 - The Basics
# https://flocode.substack.com/

import math # Provides math constants (pi) and functions (sqrt)

# ---- FUNDAMENTAL INPUT PARAMETERS & ASSUMPTIONS ----
# Basic geometry, material properties, loads, factors per ACI 318-19

# Anchor Properties
da = 0.75           # Anchor diameter (in)

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"""
Flocode Newsletter #062 - Machine Learning for Engineers: When and How Should We Use it?

This script demonstrates a simple application of machine learning (ML) to a
structural engineering problem: predicting the required depth of a steel beam
based on its span and applied uniformly distributed load (UDL). It compares
three ML models (linear, non-linear, and deep non-linear neural networks)
with a traditional calculation based on the bending moment formula.

The key concept is that the ML models are trained on data *derived* from the

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# This code supports #052 - Python Dictionaries for Engineers
# It demonstrates the use of dictionaries, Pandas, and Polars for engineering data handling

import pandas as pd
import polars as pl
from datetime import datetime, timedelta
import random

# Dictionary storing material attributes
steel = {

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import json
import os
import shutil
import subprocess
import sys

from cookiecutter.main import cookiecutter

# Template Directory Structure
template = {

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import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from scipy.stats import norm

# Set the background color to black
plt.style.use('dark_background')

# Step 1: Define the prior distribution for the remaining fatigue life (in years)
prior_mean = 20  # Prior mean fatigue life in years

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# -----------------------------------------------------------------------------
# #027 - Data Structures for Civil/Structural Engineers: Pandas 101
# -----------------------------------------------------------------------------

'''
Hi everybody from the flocode newsletter 👋

This is all the code from article #027 - Data Structures for Civil/Structural Engineers:
Pandas 101

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# ==========================================================
# Prepare Pseudocode for Calculating Concrete Volume
# ==========================================================

FUNCTION calculate_concrete_volume(length, width, depth)

  # Calculate the area of the floor slab
  area = length * width

  # Calculate the volume of concrete required

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import numpy as np

# Constants
M = 140  # Moment at the cross-section (kN.m)
I = 102_000_000  # Moment of inertia in mm^4
y = np.array([-150, -100, -50, 0, 50, 100, 150])  # Distance from the neutral axis in mm

# Bending stress calculation
sigma = ((M * 1e6) * y) / I  # Convert M from kN.m to N.mm

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import numpy as np
import matplotlib.pyplot as plt

def plot_beam_diagrams(length, w):
    """
    Plot the shear force and bending moment diagrams for a simply supported beam.

    Parameters:
    - length: Length of the beam (m)
    - w: Magnitude of the uniformly distributed load (kN/m)