Computational optimization of hempcrete integration

Computational optimization of hempcrete integration: Improving energy performance and minimizing embodied energy in a variety of building types and climates

Mountaki, Dimitra (TU Delft Architecture and the Built Environment)

Turrin, M. (mentor)
Tenpierik, M.J. (mentor)

Delft University of Technology

Architecture, Urbanism and Building Sciences | Building Technology | Sustainable Design

2024-06-18

The growing threat of climate change highlights the necessity for long-term solutions in the construction industry. Buildings account for a large share of worldwide energy consumption and carbon dioxide emissions, so there is an urgent need for creative techniques to improve energy efficiency and reduce their ecological footprint. This thesis focuses on this by creating a computational optimization workflow for incorporating hempcrete, a low-carbon construction material, into high-performance structures during the initial stages of design. This approach uses a multi-objective optimization process to offer optimal solutions adapted to various climates and building types, optimizing energy efficiency and daylight while limiting global warming potential. Architects and engineers can get greater performance and sustainability results by experimenting with different layout options and design parameters using parametric modelling, energy analysis, and optimization algorithms. The suggested workflow provides a systematic technique to facilitate decision-making during the key design steps, promoting hempcrete implementation and accelerating the shift to performance-driven architectural design in response to climate change problems.

hempcrete
Computational Optimization
energy performance
life cycle assessment (LCA)
Energy and comfort
BREEAM
Future Climate Scenarios
energy
Daylight analysis
global warming potential
Embodied energy
climate responsive design
climate change adapation

http://resolver.tudelft.nl/uuid:1f36006f-9273-40a8-a36b-a152b68f0f25

30.033333,31.233334

Student theses

master thesis

© 2024 Dimitra Mountaki