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

optimisation of industrial parts by mesh morphing enabled automatic shape sculpting

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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

multiphysics numerical investigation on the aeroelastic stability of a le mans prototype car

Abstract In the analysis and design of racing competition cars, numerical tools allow to investigate a wide range of solutions in short time and with high confidence in results. The great available computational power permits to combine simulation software so that different physics involved can be tackled at the same time. An important class of multi-physics simulations for motor sport addresses the fluid-structure interactions happening between the aerodynamic components of the car and the surrounding flow: this interaction can induce structural deformations and vibrations which, in turn, can influence the surrounding fluxes. In this paper, the flutter analysis of the front wing splitter mounted on the 2001 Le Mans Prototype car by Dallara (LMP1) is presented. The study was set up adopting high fidelity CAE models: a 400k shell elements FEM represents the full front wing assembly including the mounting frame, a 240M cells CFD represents the full car immersed in a box shaped wind tunnel. FEM extracted structural modal shapes are mapped onto the CFD mesh adopting Radial Basis Functions (RBF) mesh morphing so that the surfaces of the CFD model can be deformed according to retained modes. Such deformation is then propagated so that the volume mesh is adapted accordingly. The elastic CFD model with modes embedded was then loaded by applying a transient signal individually to each retained mode with a smoothed step function. A Reduced Order Model (ROM) for the aerodynamics of the coupled system was then extracted combining the results of the individual transient run. The critical speed experimentally observed to be in the operating range of the car was captured by the model quite well. The same workflow was then adopted to investigate a different design in which a stiffener has been introduced to increase the first mode natural frequency from 40Hz to 49.4Hz. Flutter speed was increased and moved outside the vehicle range. The car equipped with the improved part proved to perform on the track without previously detected instabilities

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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Fast strain mapping in abdominal aortic aneurysm wall reveals heterogeneous patterns

Abdominal aortic aneurysm patients are regularly monitored to assess aneurysm development and risk of rupture. A preventive surgical procedure is recommended when the maximum aortic antero-posterior diameter, periodically assessed on two-dimensional abdominal ultrasound scans, reaches 5.5 mm. Although the maximum diameter criterion has limited ability to predict aneurysm rupture, no clinically relevant tool that could complement the current guidelines has emerged so far. In vivo cyclic strains in the aneurysm wall are related to the wall response to blood pressure pulse, and therefore, they can be linked to wall mechanical properties, which in turn contribute to determining the risk of rupture. This work aimed to enable biomechanical estimations in the aneurysm wall by providing a fast and semi-automatic method to post-process dynamic clinical ultrasound sequences and by mapping the cross-sectional strains on the B-mode image. Specifically, the Sparse Demons algorithm was employed to track the wall motion throughout multiple cardiac cycles. Then, the cyclic strains were mapped by means of radial basis function interpolation and differentiation. We applied our method to two-dimensional sequences from eight patients. The automatic part of the analysis took under 1.5 min per cardiac cycle. The tracking method was validated against simulated ultrasound sequences, and a maximum root mean square error of 0.22 mm was found. The strain was calculated both with our method and with the established finite-element method, and a very good agreement was found, with mean differences of one order of magnitude smaller than the image spatial resolution. Most patients exhibited a strain pattern that suggests interaction with the spine. To conclude, our method is a promising tool for investigating abdominal aortic aneurysm wall biomechanics as it can provide a fast and accurate measurement of the cyclic wall strains from clinical ultrasound sequences