Work package 3

Lifecycle-Driven Design and Optimization of Prefabricated Structures

Starting Month: 4/40

Lead Beneficiary : POLITO

Objectives: To develop advanced computational algorithms for structural optimization that incorporate multi-criteria optimization techniques, data-driven methodologies, and consider the use of recycled materials to promote sustainable design practices. Additionally, this WP aims to integrate DfD principles into BIM tools and conduct LCAs for construction materials to enhance the sustainability and environmental impact of construction projects.

Description of Work: The needs of WP3 will be carried out through the following parts that are composed by various tasks:

Task 3.1.  Development of Computational Algorithms for Structural Optimization (Leader: NAPSLAB, PM=24.0M): This task focuses on devising algorithms that incorporate multi-criteria optimization techniques, allowing for the evaluation of various design parameters such as material usage, cost, environmental impact, and structural performance. Integration of data-driven methodologies into the optimization process will enhance the algorithms' ability to adapt to complex construction scenarios and diverse material properties, including those of recycled and repurposed materials. Genetic Algorithms (GAs), Topology Optimization, Agent-Based Models (ABMs), ML Techniques, and FEA will be used. The goal is to achieve designs that not only meet structural and economic requirements but also contribute to the CE by optimizing the use of recycled materials and minimizing waste. Role of Participants: NAPSLAB: Will develop the core optimization framework, integrating GAs, gradient-based methods, and topology optimization techniques. NTUA: Could apply ML algorithms to analyze and predict the performance of structures based on historical data. POLITO: Could specialize in the application of ABMs to model the interaction between different materials within a structure. UOA: Might focus on incorporating FEA into the optimization process, simulating physical responses of structures to various load conditions 

Task 3.2. Integration of DfD principles into BIM (Leader: POLITO, PM=23.0M): This task involves development of custom software plugins or extensions for existing BIM applications, enabling the integration of DfD criteria directly into the design process, neural networks to process complex design data and predict the ease of disassembly, NLP to interpret design notes and integrate DfD principles from textual descriptions into the BIM models, parametric modelling, and Database Management Systems (DBMS) to store DfD-related data, which BIM tools can query to assist in making informed design decisions. Role of Participants: POLITO: Will spearhead the development of BIM methodologies and tools, ensuring the integration of DfD principles aligns with industry standards and practices. INFERSENCE: Could focus on AI-driven analysis tools, developing algorithms to provide feedback on design modifications. USTUTT: Concentrate on the development of parametric modeling tools within the BIM framework to allow flexible design changes.

Task 3.3. LCA for construction materials (Leader: UCY, PM=20.0M): This task involves inventory analysis models with the collection and analysis of data related to the production, use, and end-of-life phases of construction materials, aiming to identify opportunities for reducing carbon footprints and enhancing sustainability in the construction sector, utilization of established LCA software tools such as SimaPro or GaBi to assess the environmental impacts associated with each stage of a material's life cycle, applying normalization and weighting techniques to interpret LCA results within a broader environmental context, enabling the comparison of impacts across different categories like global warming potential, ozone depletion, and resource depletion, as well as aligning LCA findings with structural performance analysis to ensure that eco-friendly choices also satisfy safety and durability requirements. Tools like SAP2000 or ETABS could be used for structural simulations that incorporate material sustainability profiles. Statistical methods and ML algorithms will predict the environmental performance of new materials or novel uses of existing materials. Role of Participants: UCY: Coordinates the LCA methodology and aligns it with structural performance requirements. Develops frameworks for incorporating LCA results into design decisions. INS: Contributes to data collection and management, ensuring the accuracy and completeness of the inventory analysis. JUST: Focuses on the environmental impact assessment using LCA software, interpreting results to guide sustainable material choices. NTUA: Provides expertise in structural engineering, integrating LCA data with structural performance simulations.