automatic shape optimization of structural components with manufacturing constraints

Abstract Among optimization procedures, mesh morphing gained a relevant position: it proved to be a suitable tool in obtaining weight and stress concentration reduction, without the need to iterate the numerical model generation. Shape modification through mesh morphing can be performed in an automatic fashion adopting two approaches: defining parameters which will describe the modified shape or exploiting results coming from numerical analyses. With this second approach, it is possible to achieve a very high automation grade: stress values retrieved on component surfaces can be successfully employed to drive the shape modification of the component itself. This 'driven-by-numerical-results' automatic approach can lead to complex optimized shapes, which can be easily achieved with modern additive manufacturing processes, but not adopting traditional manufacturing processes. In the present work a method to include manufacturing constraints in a shape optimization workflow is presented and applied to different structural optimization cases, in order to demonstrate how even manufacturing based on traditional processes can take advantage of automatic shape optimization of structural components

Fast interactive CFD evaluation of hemodynamics assisted by RBF mesh morphing and reduced order models: the case of aTAA modelling

AbstractThe medical digital twin is emerging as a viable opportunity to provide patient-specific information useful for treatment, prevention and surgical planning. A bottleneck toward its effective use when computational fluid dynamics (CFD) techniques and tools are adopted for the high fidelity prediction of blood flow, is the significant computing cost required. Reduced order models (ROM) looks to be a promising solution for facing the aforementioned limit. In fact, once ROM data processing is accomplished, the consumption stage can be performed outside the computer-aided engineering software adopted for simulation and, in addition, it could be also implemented on interactive software visualization interfaces that are commonly employed in the medical context. In this paper we demonstrate the soundness of such a concept by numerically investigating the effect of the bulge shape for the ascending thoracic aorta aneurysm case. Radial basis functions (RBF) based mesh morphing enables the implementation of a parametric shape, which is used to build up the ROM framework and data. The final result is an inspection tool capable to visualize, interactively and almost in real-time, the effect of shape parameters on the entire flow field. The approach is first verified considering a morphing action representing the progression from an average healthy patient to an average aneurismatic one (Capellini et al. in Proceedings VII Meeting Italian Chapter of the European Society of Biomechanics (ESB-ITA 2017), 2017; Capellini et al. in J. Biomech. Eng. 140(11):111007-1–111007-10, 2018). Then, a set of shape parameters, suitable to consistently represent a widespread number of possible bulge configurations, are defined and accordingly generated. The concept is showcased taking into account the steady flow field at systolic peak conditions, using ANSYS®Fluent®and its ROM environment for CFD and ROM calculations respectively, and the RBF MorphTM software for shape parametrization

cae update of cae models on actual manufactured shapes

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Machine learning and reduced order modelling for the simulation of braided stent deployment

Endoluminal reconstruction using flow diverters represents a novel paradigm for the minimally invasive treatment of intracranial aneurysms. The configuration assumed by these very dense braided stents once deployed within the parent vessel is not easily predictable and medical volumetric images alone may be insufficient to plan the treatment satisfactorily. Therefore, here we propose a fast and accurate machine learning and reduced order modelling framework, based on finite element simulations, to assist practitioners in the planning and interventional stages. It consists of a first classification step to determine a priori whether a simulation will be successful (good conformity between stent and vessel) or not from a clinical perspective, followed by a regression step that provides an approximated solution of the deployed stent configuration. The latter is achieved using a non-intrusive reduced order modelling scheme that combines the proper orthogonal decomposition algorithm and Gaussian process regression. The workflow was validated on an idealised intracranial artery with a saccular aneurysm and the effect of six geometrical and surgical parameters on the outcome of stent deployment was studied. The two-step workflow allows the classification of deployment conditions with up to 95% accuracy and real-time prediction of the stent deployed configuration with an average prediction error never greater than the spatial resolution of 3D rotational angiography (0.15 mm). These results are promising as they demonstrate the ability of these techniques to achieve simulations within a few milliseconds while retaining the mechanical realism and predictability of the stent deployed configuration

Crack Propagation Analysis of Near-Surface Defects with Radial Basis Functions Mesh Morphing

Abstract Fracture mechanics analysis is nowadays adopted in several industrial fields to assess the capability of components to withstand fatigue loads. Finite Element Method (FEM) is a well-established tool for the evaluation of flaw Stress Intensity Factors (SIF) and for the survey of its propagation. Nevertheless the study of the growth of near-surface circular and elliptical cracks is still an arduous task to be faced with FEM. In fact, the interaction of the flaw with free surfaces leads the crack front to assume complex shapes, whose simulation cannot be easily accomplished. A possible answer to deal with such a problem is to use the mesh morphing technique, a nodal relocation methodology, that allows to cover different problems. In fact, with mesh morphing, it is possible to fit the baseline flaw front with the desired shape (generic shape) and to automatically simulate its evolution at a certain number of cycles. In the proposed work this approach is demonstrated exploiting ANSYS Mechanical as FEM tool and RBF Morph ACT Extension as mesh-morpher. The results of the proposed workflow are compared with those available in literature

structural assessment of tf superconducting magnet of the dtt device

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Optimal airfoil’s shapes by high fidelity CFD

Purpose – There is an increasing interest in airfoils that modify their shape to adapt at the flow conditions. The study aims at the evaluation of the optimal 4-digit NACA airfoil that maximizes the lift-over-drag ratio for a constant lift coefficient of 0.6, from Re = 104 to 3 x 106. Design/methodology/approach – The authors consider a y - Re t transition model and a k – v shear stress transport turbulence model with a covariance matrix adaptation evolutionary optimization algorithm. The shape is adapted by radial basis functions mesh morphing using four parameters (angle of attack, thickness, camber and maximum camber position). The objective of the optimization is to find the airfoil that enables a maximum lift-over-drag ratio for a target lift coefficient of 0.6. Findings – The computation of the optimal airfoils confirmed the expected increase with Re of the lift-over-drag ratio. However, although the observation of efficient biological fliers suggests that the thickness increases monotonically with Re, the authors find that it is constant but for a 1.5 per cent step increase at Re = 3 x 10 exposant5. Practical implications – The authors propose and validate an efficient high-fidelity method for the shape optimization of airfoils that can be adopted to define robust and reliable industrial design procedures. Originality/value – It is shown that the difference in the numerical error between two-dimensional and three-dimensional simulations is negligible, and that the numerical uncertainty of the two-dimensional simulations is sufficiently small to confidently predict the aerodynamic forces across the investigated range of Re