Energi

To build this simulation, Python served as the analytical engine, utilizing libraries like pandas and numpy to process complex datasets and model the energy output and carbon footprint of various power plants. This "digital twin" logic calculated the environmental consequences of every player decision, translating infrastructure choices into data-driven impacts like $CO_2$ fluctuations or resource depletion. These backend computations were then bridged to a web interface where HTML, CSS, and JavaScript turned raw data into an interactive dashboard. We combined and parsed through data to create this comprehensive simulation. This setup allowed for real-time visualization, where JavaScript-driven charts reflected the shifting environmental trends based on the Python-processed models, creating a seamless loop between structural engineering concepts and data science applications.