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Energy Plus in Colab
Run EnergyPlus building energy simulations in Google Colab — no local install needed. What it does One script sets everything up inside a Colab runtime:
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CityGML Browser
A lightweight web browser for interacting with and exploring CityGML datasets.
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SBE Viewer
The GIS Viewer Application is a React-based project designed to load, view, and filter GIS files. It provides a user-friendly interface for visualising geographic data and supports various file formats. Features
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Python for AEC Researchers
This repository contains the source for the Python for AEC Researchers book.It is designed for BT researchers, research assistants, and supervisors who want to use Python for data analysis, automation, and reproducible research. Run interactively:Many chapters and exercises are Jupyter notebooks. You can launch them in Google Colab or run locally with AnacondaThe book can be read online (here).
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ACE MR Studio Demo
An interactive mixed-reality urban visualisation platform built for the ACE MR Studio at Chalmers University of Technology. The application provides multiple data visualisation layers for urban planning, environmental analysis, and stakeholder engagement.
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Early-stage Building Energy Dataset
This repository contains materials for my Xinyue Wang’s research on creating machine learning models to predict residential building energy demand from early-stage architectural design variables. Research focus The PhD project investigates how simple architectural design variables (shape, orientation, glazing ratio, building compactness, etc.) influence annual energy demand. The goal is to produce fast, accurate surrogate…
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Meet the Student Assistants at the SBE Research Area
Student assistants are an integral part of the Sustainable Built Environments research area. Currently completing their Master’s degrees, Johan Blomsterberg, Djamila Mamedova, and Arvid Hall support our research in energy-efficient building renovation, data management, and spatial data visualisation. We sat down to talk to Johan, Djamila and Arvid about their backgrounds and the specific projects…
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Interview with Jieming
This week, we sat down with Jieming Yan, SBE’s most recent PhD candidate. Jieming’s research explores how mixed reality can support better communication of building performance simulation results to inform sustainable decision-making. Jieming is supervised by Alexander Hollberg and Sanjay Somanath with funding from the Digital Twin Cities Centre. First of all, congratulations on your…
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From Architecture to Machine Learning: Xinyue Wang on Making Early-Stage Energy Optimisation Practical
What if predicting building energy demand did not require long simulation runs, heavy workflows, or massive datasets? Xinyue Wang recently defended her PhD, “Leveraging Machine Learning to Improve Early-stage Building Energy Optimization.” Originally trained as an architect, her research sits at the intersection of building energy simulation and machine learning. Her work focuses on making…