2 "Thermodynamics" Posts

The Wreck of the Edmund Fitzgerald: Modeling Decomposition in Extreme Environments

How cold, pressure, and buoyancy explain why Lake Superior may never give up her dead

Nov 30, 2025 • Category: Applied Modeling and Simulation • Tags: #biology · #physics · #Python · #thermodynamics

What You'll Learn

Why bodies normally resurface after a drowning
How cold water dramatically slows decomposition
How water pressure compresses decomposition gases at depth
How temperature, pressure, and buoyancy interact in Lake Superior
How Python can model whether a body will ever surface
Why the Edmund Fitzgerald’s depth creates an extreme preservation environment

Modeling Heat Capacity and Evaporation with Python: Why Water Warms Slowly but Cools Fast

Using thermodynamics and Python to explain why pools resist daytime warming but lose heat rapidly at night

Oct 12, 2025 • Category: Applied Modeling and Simulation • Tags: #energy balance · #Python · #thermodynamics

What You'll Learn

Why water’s high specific heat makes a swimming pool warm much more slowly than the surrounding air
Why evaporation can remove heat from water faster than sunlight replaces it
How convection, radiation, solar absorption, and evaporation combine in a surface energy balance
How to translate conservation of energy into a Python model of water temperature
Why covering a pool can dramatically reduce nighttime heat loss
How simulation can reveal the effects of weather, geometry, and surface conditions on water temperature

Behind the Code

My focus is the engineering beneath modern AI systems. After several years of building applications with AI through APIs, my interests have moved below that abstraction layer: understanding how models are architected, trained, evaluated, and served, why they’re designed the way they are, and the engineering tradeoffs behind those decisions.

That direction follows a pattern across my forty-year career as a software developer. I’ve primarily built applications, but I’ve repeatedly found myself pushing beyond the application itself and building the systems, abstractions, and tooling behind it: metaprogramming layers, dynamic runtimes, configuration-driven engines, and automation platforms designed to outlive the original feature request.

The pattern shows across my career: Forms Express at AT&T, a four-layer dynamic runtime shipped for under $500K against a $2M consulting bid; VeriSign’s first-ever customer self-service mobile activation system, which won the 2003 SUPERQuest Award; and TAG at Microsoft, a production LLM orchestration platform that shipped nearly 100 Terraform articles by parsing XML templates, routing prompts to Azure OpenAI, and composing results with browser-driven Azure portal capture. Along the way: C++ MVP, nine technology books, 100+ articles for .NET Programming Tips & Techniques, and helping run CodeGuru, the largest Windows developer community of its era.

After 21 years at Microsoft, I’m now full-time on what’s next: completing my Master’s in Computer Science and publishing at Signal & Syntax, where I research and write about the mathematics and engineering underneath modern AI. I use mathematical models, experiments, and small implementations to explore everything from gradient descent and attention to inference-time behavior and training infrastructure; not just how to use these systems through an API, but how the machinery beneath that API actually works.

Connect with me on LinkedIn .