Enhancing property prediction in building materials through data-augmented neural networks

Identificador:  TDX:4466

Handle: https://hdl.handle.net/20.500.11797/TDX4466

Autors:  Souza Rosa, Ana Carolina

Resum:
Energy-efficient construction practices are essential in modern urban planning, aiming to reduce energy consumption, improve thermal comfort, promote sustainability, and lower long-term costs. The demand far energy-efficient buildings drives advancements in materials, techniques, and smart technologies, leading to sustainable and cost-effective structures that benefit both the environment and the economy. Researchers focus on building materials far the building envelope, crucial far maintaining stable interna! temperatures. The careful selection of materials during design can significantly reduce energy consumption, enhance durability, and lower costs. Concrete remains a versatile material, valued far its mechanical strength and adaptability. lt can be tailored with different compositions and additives to meet specific project requirements, supporting energy efficiency and long-term resilience.