Prioritizing Building Envelope Retrofits Through Data-Driven Heat Flux Prediction

This repository contains the code, data, and documentation for our workflow to predict surface‑level heat flux in existing buildings and rank envelope components for targeted retrofit. It implements two machine‑learning surrogates (XGBoost and Deep MLP) trained on EnergyPlus simulation outputs of Danish building archetypes, and validates the method on an independent office model.