Main research questions:

RQ5.1: How to enhance design optimization by integrating multi-scale and process-coupled methods in FAST Virtual Lab?

RQ5.2: How to incorporate PCS effects in structural designs by coupling microstructure models with advanced finite element analysis?

RQ5.3: How to design a holistic multi-criteria decision support model incorporating techno-economic and sustainability parameters as trade-offs and sensitivities in guiding the circularity transition?

Approach and methodology:

Workflow and plug-in integration for design optimization based on inputs from WP1-WP5, assembled into FAST Virtual Lab. The latter will be based on commercial software combined with application-specific units, using semantic documentation and interoperability to standardise data representation, interfaces and user-oriented design. FAST Virtual Lab will be validated, T5.2-T5-4, at TRL4, by comparing PCS vs primary based aluminium products, for use-cases across the three value-chains.

Research tasks:

T5.1: Develop FAST Virtual Lab, a digital framework allowing seamless workflows of modules/plug-ins from each WP, as stand-alone modules or coupled multiscale systems. A standardised and common data representation to all plug-ins is thus required and will be developed using semantic documentation, common interface and ontologies.

T5.2: Validation use-case Automotive. Studies of crash management systems (CMS) by exploiting FAST Virtual Lab and insights from WP3 and WP4 into a structural optimization framework. FE models will be developed to predict aluminium part performance under large deformations and fracture, accounting for impurity content and enabling optimal design of high-PCS components.

T5.3: Validation use-case Cables & conductors. The goal is to understand how PCS affects conductivity while maintaining strength, creep, and fatigue resistance. This involves analysing nano-/micro-structure relationships using experiments and FAST Virtual Lab to optimise PCS alloy design.

T5.4: Validation use-case Large structures. Effects of local post-weld heat treatment and mechanical deformation on hardness, grain refinement, microstructure, and residual stress will be investigated, considering weld type, material grade, and industrial feasibility. Fatigue life improvements for various aluminium joint configurations will be studied, with predictive fatigue models developed from experimental data.

T5.5: This task will develop decision support models to quantify trade-offs, and sensitivity, of value creation and environmental impacts of the materials, processes and technologies developed in FAST.

Sub-tasks: 1) define scope and system boundaries, collect data on material/energy flows and techno-economic and environmental key parameters, production throughputs and efficiencies, embodied energy, resource and byproducts;

2) building on existing optimization-based frameworks, a multi-criteria optimization model will be developed to identify trade-offs between economic and environmental performance; 3) perform sensitivity analyses and calibrate and validate model based on variabilities and projections.

Main expected outcomes:

OU5.1: FAST Virtual Lab - a digital framework for connecting workflows, material- and microstructure models, structural design, manufacturing processes and product and structure lifecycle performance models, for multi-criteria optimization.

OU5.2: Validations of FAST Virtual Lab at lab-scale (TRL4) for products and structures across all three value chains.

OU5.3: Holistic multi-criteria optimization tool integrating social, economic and sustainability parameters for guiding lifecycle performance of PCS-based structural designs.

OU5.4: 2 PhDs and one Postdoc are connected to WP5.