Good improvements to robustness and adaptive scaling of surface smoothing methods was achieved for CAD-free surface-based methods. Work on RBF volume morphing achieved substantial improvements in computational efficiency. These methods can now be used in routine workflows for design exploration. However, progress with ‘return-to-CAD’ is more limited, this remains a challenging problem. Accepting a loss of generality enables a templating approach which was very successfully demonstrated on the DrivAer mirror case.
Work on CAD-based parametrisation in WP4 was a resounding success with major advances with all approaches that were investigated.
The innovative `implicit’ parametrisation approach NSPCC of QMUL has been applied to a wide range of cases and enhanced with tools for adaptive design space refinement. This approach achieved best results when applied to the S-Bend testcase.
The finite-difference gradient approach of QUB has been very successfully applied to a range of complex industrial cases including constraint handling through generic CAD distance evaluation. Further advances have been demonstrated in adaptive refinement of the CAD feature tree to enrich the design space.
A significant success was the complete differentiation of the open-source CAD kernel Open Cascade Technologies. Both `explicit’ parametrisations, classic engineering approaches that build up the feature tree from points, lines and surfaces, as well as `implicit’ parametrisations that work with the control nets of the NURBS patches forming the Boundary Representation (BRep) have been demonstrated.
Gradient-enabled constraint methodologies were enabled. Most prominent were CAD-based approaches using differentiated distance/collision functionality of the CAD systems, as well as the definition auxiliary constraint functions. The approaches were successfully demonstrated on turbomachinery blades.
IODA also progressed with uncertainty quantification using established polynomial chaos methods, as well as innovative multi-level/multi-fidelity Monte Carlo methods using inexpensive adjoint low-fidelity models. Both approaches are now ready to be exploited in robust engineering design.
All partners have made substantial advances with their in-house capability on adjoint design optimisation. Major routes to impact are:
1. OEM partners (VW, RRD) will use the project developments in their design workflows to develop improved products and hence increase their competitivity in the global maketplace, resulting in employment creation in the EU knowledge economy. The products that can now be designed with much lower environmental impact, in particular CO2 emissions, will make the EU and the world a better place to live.
2. Partners who develop software (Engys, ESI, OCCT) and research institutes (VKI) have significantly increased their capability. The availability of software and services will help smaller and SME companies access this technology, as well as provide employment at the partners. This will have a positive impact on the EU knowledge economy, as well as help to deliver the ambitious environmental targets of the EU.
3. Academic partners (QMUL, NTUA, UPB) have improved their competence and capability, putting them at the forefront of research in the field, and are using this in funding bids.
4. The strong dissemination effort with over 50 open-access papers, as well as the organisation of 3 dedicated minisymposia at leading conferences, makes the developments very accessible to the wider R&D community, supporting strong progress in this field.
5. The very comprehensive training programme has developed a class of 15 researchers with skills to lead in this field.
6. A substantial outreach effort produced a wide range of activities, has delivered a strong contribution to getting school children interested in STEM subjects.
