Page 13: Research news on AI in built environment

AI in the built environment encompasses data-driven and physics-informed methods to model, predict, and optimize the performance and resilience of buildings and infrastructure. Machine learning and advanced simulation are applied to building energy use, HVAC control, and solar and wind power forecasting, as well as to hazard-related phenomena such as subsidence, floods, fire, and seismic events. The field also integrates retrofitting strategies, climate-smart housing design, and regulatory considerations to enhance energy efficiency, comfort, and disaster resilience in urban systems.

Energy & Green Tech

Tool predicts impact of wildfire smoke on solar power generation

From habitats to property to livelihoods, wildfires destroy everything in their path. But there is another, less-acknowledged, casualty: sunlight and the electrical grid that depends on it. Smoke from wildfires can cover ...

Engineering

Physics reveals the optimal roof ratios for energy efficiency

While serving as a visiting professor in Benevento, outside Naples, Italy, Adrian Bejan noticed something about the local architecture: All the roofs looked the same. With what seemed like too-shallow peaks on smaller, older ...

Engineering

US earthquake safety relies on federal employees' expertise

Earthquakes and the damage they cause are apolitical. Collectively, we either prepare for future earthquakes or the population eventually pays the price. The earthquakes that struck Myanmar on March 28, 2025, collapsing buildings ...

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