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Finite element head (FE) models are important numerical tools to study head injuries and develop protection systems. The generation of anatomically accurate and subject-specific head models with conforming hexahedral meshes remains a significant challenge. The focus of this study is to present two developmental works: first, an anatomically detailed FE head model with conforming hexahedral meshes that has smooth interfaces between the brain and the cerebrospinal fluid, embedded with white matter (WM) fiber tracts; second, a morphing approach for subject-specific head model generation via a new hierarchical image registration pipeline integrating Demons and Dramms deformable registration algorithms. The performance of the head model is evaluated by comparing model predictions with experimental data of brain–skull relative motion, brain strain, and intracranial pressure. To demonstrate the applicability of the head model and the pipeline, six subject-specific head models of largely varying intracranial volume and shape are generated, incorporated with subject-specific WM fiber tracts. DICE similarity coefficients for cranial, brain mask, local brain regions, and lateral ventricles are calculated to evaluate personalization accuracy, demonstrating the efficiency of the pipeline in generating detailed subject-specific head models achieving satisfactory element quality without further mesh repairing. The six head models are then subjected to the same concussive loading to study the sensitivity of brain strain to inter-subject variability of the brain and WM fiber morphology. The simulation results show significant differences in maximum principal strain and axonal strain in local brain regions (one-way ANOVA test, p

In Industry 4.0 era, rapid changes to the global landscape of manufacturing are transforming industrial plants in increasingly more complex digital systems. One of the most impactful innovations generated in this context is the “Digital Twin”, a digital copy of a physical asset, which is used to perform simulations, health predictions and life cycle management through the use of a synchronized data flow in the manufacturing plant. In this paper, an innovative approach is proposed in order to contribute to the current collection of applications of Digital Twin in manufacturing: a Digital Shadow cloud-based application to enhance quality control in the manufacturing process. In particular, the proposal comprises a Digital Shadow updated on high performance computing cloud infrastructure in order to recompute the performance prediction adopting a variation of the computer-aided engineering model shaped like the actual manufactured part. Thus, this methodology could make possible the qualification of even not compliant parts, and so shift the focus from the compliance to tolerance requirements to the compliance to usage requirements. The process is demonstrated adopting two examples: the structural assessment of the geometry of a shaft and the one of a simplified turbine blade. Moreover, the paper presents a discussion about the implications of the use of such a technology in the manufacturing context in terms of real-time implementation in a manufacturing line and lifecycle management.

Principal components analysis is a powerful technique which can be used to reduce data dimensionality. With reference to three-dimensional bone shape models, it can be used to generate an unlimited number of models, defined by thousands of nodes, from a limited (less than twenty) number of scalars. The full procedure has been here described in detail and tested. Two databases were used as input data: the first database comprised 40 mandibles, while the second one comprised 98 proximal femurs. The “average shape” and principal components that were required to cover at least 90% of the whole variance were identified for both bones, as well as the statistical distributions of the respective principal components weights. Fifteen principal components sufficed to describe the mandibular shape, while nine components sufficed to describe the proximal femur morphology. A routine has been set up to generate any number of mandible or proximal femur geometries, according to the actual statistical shape distributions. The set-up procedure can be generalized to any bone shape given a sufficiently large database of the respective 3D shapes.

Numerical simulations to evaluate thoracic aortic hemodynamics include a computational fluid dynamic (CFD) approach or fluid-structure interaction (FSI) approach. While CFD neglects the arterial deformation along the cardiac cycle by applying a rigid wall simplification, on the other side the FSI simulation requires a lot of assumptions for the material properties definition and high computational costs. The aim of this study is to investigate the feasibility of a new strategy, based on Radial Basis Functions (RBF) mesh morphing technique and transient simulations, able to introduce the patient-specific changes in aortic geometry during the cardiac cycle. Starting from medical images, aorta models at different phases of cardiac cycle were reconstructed and a transient shape deformation was obtained by proper activating incremental RBF solutions during the simulation process. The results, in terms of main hemodynamic parameters, were compared with two performed CFD simulations for the aortic model at minimum and maximum volume. Our implemented strategy copes the actual arterial variation during cardiac cycle with high accuracy, capturing the impact of geometrical variations on fluid dynamics, overcoming the complexity of a standard FSI approach.

Radial basis functions (RBF) mesh morphing is a well established approach to quickly update an existing finite element analysis (FEA) mesh so that new shapes can be adapted and related performances explored. The RBF in fact allow to adapt the volume mesh maintaining a good quality even for substantial changes of the shape. New shapes imposed at FEA domain borders can be controlled by direct parameters (mesh based or CAD based) or by deformation fields resulting from the physics. In this paper we explore how the last approach can be exploited according to two different strategies: the biological growth method (BGM), which consists in adding/removing material according to the local stress at surface, the adjoint method, which consists in moving inward outward the surface according to the surface sensitivities. The FEA solver ANSYS® MechanicalTM in combination with the mesh morphing software RBF MorphTM was adopted for this purpose. The BGM implementation is the one implemented in RBF Morph, the adjoint solver is the one implemented in the topological optimisation tool by ANSYS. Automatic shape sculpting applications are demonstrated on a simple geometry, a thick plate with simple load conditions, and on an industrial part.

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.

This paper discusses a strategy for speeding up the mesh deformation process in the design-by-optimization of high-frequency components involving electromagnetic field simulations using the 3D finite element method (FEM). The mesh deformation is assumed to be described by a linear elasticity model of a rigid body; therefore, each time the shape of the device is changed, an auxiliary elasticity finite-element problem must be solved. In order to accomplish this in a very short time numerical integration and the solution of the resulting system of equations are performed using a graphics processing unit (GPU). The performance of the proposed algorithm is illustrated are verified using a complex example involving 3D FEM analysis of a dielectric-resonator filter.

The aim of this paper is to compare and validate two computational methods to study typical aircrafts aeroelastic problems. The first one is the very well-established 2-way coupling approach, which envisages the use of a mesh morphing tool to update the CFD mesh according to the computed displacements in combination with a mapping algorithm to transfer the loads onto the FEM mesh. The second one is based on the embedding of structural modes, computed in advance by a FEM solver, directly into the CFD solver. It requires a morphing tool to deform the CFD mesh according to FEA computed modal shapes and a surface integration algorithm that allows to evaluate the modal forces acting on the CFD mesh. Modes embedding makes the CFD model intrinsically aeroelastic and thus capable to self-adapt its shape in the respect of the actual deformation, removing all the complexities related to the data exchange between solvers. Both methods were validated against a literature benchmark test case consisting in the prediction of the static aeroelastic equilibrium of the HIRENASD model using two of the meshes available in the “NASA First Aeroelasticity Workshop” database. The fidelity of both methods has been successfully validated, achieving a satisfactory agreement with experimental data.

We present a new numerical simulation framework for prediction of flow patterns in the human left ventricle model. In this study, a radial basis function (RBF) mesh morphing method is developed and applied within the finite-volume computational fluid dynamics (CFD) approach. The numerical simulations are designed to closely mimic details of recent tomographic particle image velocimetry (TomoPIV) experiments. The numerically simulated dynamic motions of the left ventricle and tri-leaflet biological mitral valve are emulated through the RBF morphing method. The arbitrary Lagrangian-Eulerian (ALE) based CFD is performed with the RBF-defined deforming wall boundaries. The results obtained show a good agreement with experiments, confirming the reliability and accuracy of the developed simulation framework.

Positive displacement machines (e.g. scroll, twin screw, reciprocating, etc.) are proven to be suitable as expanders for organic Rankine cycle (ORC) applications, especially in the medium to low power range. However, in order to increase their performance, detailed simulation models are required to optimize the design and reduce the internal losses. In recent years, computational fluid dynamics (CFD) has been applied for the design and analysis of positive displacement machines (both compressors and expanders) with numerous challenges due to the dynamics of the expansion (or compression) process and deforming working chambers. The majority of the studies reported in literature focused on scroll, twin screw and reciprocating machines. Furthermore, the limitation of such methodologies to be applied directly to complex multi-rotor machines has been highlighted in literature. In this paper, a single screw expander (SSE) is used as benchmark to evaluate the applicability of different grid generation methodologies (dynamic remeshing and Chimera strategy overlapping grid), in terms of computational resources required, accuracy of the results and limitations. Although, the low-order models have been applied to single screw machines, there is still a lack of CFD analyses due to the particular complexity of the machine geometry and of its working principle. The calculations have been performed with air to reduce the complexity of the problem. to the main results are two folds: (i) the assessment of a numerical strategy with respect to the most critical parameters of a dynamic mesh-based simulation and (ii) the comparison of the pressure field and internal flow features obtained by using different numerical approaches.

Micro-ORC systems are usually equipped with positive displacement machines such as expanders and pumps. The pumping system has to guarantee the mass flow rate and allows a pressure rise from the condensation to the evaporation pressure values. In addition, the pumping system supplies the organic fluid, characterized by pressure and temperature very close to the saturation. In this work, a CFD approach is developed to analyze from a novel point of view the behavior of the pumping system of a regenerative lab-scale micro-ORC system. In fact, starting from the liquid receiver, the entire flow path, up to the inlet section of the evaporator, has been numerically simulated (including the Coriolis flow meter installed between the receiver and the gear pump). A fluid dynamic analysis has been carried out by means of a transient simulation with a mesh morphing strategy in order to analyze the transient phenomena and the effects of pump operation. The analysis has shown how the accuracy of the mass flow rate measurement could be affected by the pump operation being installed in the same circuit branch. In addition, the results have shown how the cavitation phenomenon affects the pump and the ORC system operation compared to control system actions.

Purpose Numerical simulation of icing has become a standard. Once the iced shape is known, however, the analyst needs to update the computational fluid dynamics (CFD) grid. This paper aims to propose a method to update the numerical mesh with ice profiles. Design/methodology/approach The present paper concerns a novel and fast radial basis functions (RBF) mesh morphing technique to efficiently and accurately perform ice accretion simulations on industrial models in the aviation sector. This method can be linked to CFD analyses to dynamically reproduce the ice growth. Findings To verify the consistency of the proposed approach, one of the most challenging ice profile selected in the LEWICE manual was replicated and simulated through CFD. To showcase the effectiveness of this technique, predefined ice profiles were automatically applied on two-dimensional (2D) and three-dimensional (3D) cases using both commercial and open-source CFD solvers. Practical implications If ice accreted shapes are available, the meshless characteristic of the proposed approach enables its coupling with the CFD solvers currently supported by the RBF4AERO platform including OpenFOAM, SU2 and ANSYS Fluent. The advantages provided by the use of RBF are the high performance and reliability, due to the fast application of mesh smoothing and the accuracy in controlling surface mesh nodes. Originality/value As far as authors’ knowledge is concerned, this is the first time in scientific literature that RBF are proposed to handle icing simulations. Due to the meshless characteristic of the RBF mesh morphing, the proposed approach is cross solver and can be used for both 2D and 3D geometries.

On the route to a spatio-temporal geoscience information system, an appropriate data model for geo-objects in space and time has been developed. In this model, geo-objects are represented as sequences of geometries and properties with continuous evolution in each time interval. Because geomodeling software systems usually model objects at specific time instances, we want to interpolate the geometry and properties from two models of an object with only geometrical constraints (no physical or mechanical constraints). This process is called spatio-temporal data construction or morphological interpolation of intermediate geometries. This paper is strictly related to shape morphing, shape deformation, cross-parameterization and compatible remeshing and is only concerned with geological surfaces. In this study, two main sub-solutions construct compatible meshes and find trajectories in which vertices of the mesh evolve. This research aims to find an algorithm to construct spatio-temporal data with some constraints from the geosciences, such as cutting surfaces by faulting or fracturing phenomena and evolving boundaries attached to other surfaces. Another goal of this research is the implementation of the algorithm in a software product, namely a gOcad plug-in. The four main procedures of the algorithm are cutting the surfaces, setting up constraints, partitioning and calculating the parameterizations and trajectories. The software has been tested to construct data for a salt dome and other surfaces in regard to the geological processes of faulting, deposition and erosion. The result of this research is an algorithm and software for the construction of spatio-temporal data.

This paper presents the RBF4AERO benchmark technology platform, developed in the framework of the EU-funded RBF4AERO project. The platform enables the so-called Benchmark Management System (BMS) used for benchmark submission and results reporting. The BMS is deployed using three modules, namely the Graphical User Interface (GUI), the Workflow Manager (WM) and the Benchmarking Database System (BDS) which cooperate during the whole optimization benchmark life-cycle. The GUI is the only component which interacts with the end-user. It enables the optimization benchmark submission, along with the progress, results and computational platform resources monitoring. The configuration of the Optimization (OT) and the Morpher Tool (MT) is a pre-requisite for the optimization benchmark submission. In an optimization scenario the WM, which is practically the controller of the system, queries the OT in order to get a table of samples and gives back the results of the simulator (for instance a CFD tool). The evaluated individuals serve as training patterns of a Response Surface Model (RSM) which is, then, used for an Evolutionary Algorithms based optimization. The resulting 'optimal' solution(s) are delivered back to the WM for re-evaluation on the CFD tool. For each evaluation on the CFD tool, when a new geometrical shape is required, the computational grid is morphed using the MT based on radial basis functions.

This work is focused on a parametric numerical study of the barrier\'s bar inclination shelter effect in crosswind scenario. The parametric study combines mesh morphing and design of experiments in automated manner. Radial Basis Functions (RBF) method is used for mesh morphing and Ansys Workbench is used as an automation platform. Wind barrier consists of five bars where each bar angle is parameterized. Design points are defined using the design of experiments (DOE) technique to accurately represent the entire design space. Three-dimensional RANS numerical simulation was utilized with commercial software Ansys Fluent 14.5. In addition to the numerical study, experimental measurement of the aerodynamic forces acting on a vehicle is performed in order to define the critical wind disturbance scenario. The wind barrier optimization method combines morphing, an advanced CFD solver, high performance computing, and process automaters. The goal is to present a parametric aerodynamic simulation methodology for the wind barrier shelter that integrates accuracy and an extended design space in an automated manner. In addition, goal driven optimization is conducted for the most influential parameters for the wind barrier shelter.

The study is focused on the use of mesh morphing to explore different trims of yachts sails. In particular, four trims of the fore and aft sail of a model-scale sailing yacht were modelled leading to 16 configurations in total. Sail pressure distributions were validated with wind-tunnel measurements for all the 16 configurations, and full verification and validation was performed for one of these conditions. The 16 configurations were modelled with two different approaches: generating a new mesh for each trim condition (standard method) and using a morphed version of the baseline condition. This second novel method, based on the use of radial basis functions to morph the mesh, allows the computational time of exploring different geometries with computational fluid dynamics to be significantly decreased. Good agreement is observed between the pressure distributions computed with new meshes and morphed meshes. In order to show an example of trim optimisation, a metamodel approach is defined for the estimation of the response surface using radial basis function interpolation in the parameter space. Thanks to the continuum nature of morphing approach, the optimal trim angles for the given flow condition could be verified using new full computational fluid dynamic simulations. The original full factorial map of 16 points was replaced with a new map of 9 points with an optimal space filling approach to understand the faithfulness of a reduced metamodel. In both cases optimal point is evaluated using a fine design of experiment table built using the metamodel (41 levels for each parameter). The maximum thrust is achieved at the same trim for both metamodels. Proposed method can be easily extended to a wide number of parameters. Such flexibility is demonstrated in the present paper showing the sensitivity of results with respect to apparent wind angle and heeling angle.

Fast passing trains induce aerodynamic forces which can be dangerous for trackside objects and for passengers on station platforms. To develop theoretical and numerical approaches for optimizing the shape of train heads with the objective of minimizing the amplitude of the induced pressure wave and the resulting forces on trackside objects is the aim of the present work. In the first part, we consider shape optimization of a potential train head modeled by superposing monopole sources to a uniform flow. To demonstrate the reliability of the potential flow model, we determine the aerodynamic loads on a sphere induced by the head pressure pulse of a passing train and compare them with results measured in a moving model rig, the so-called “Tunnel Simulation Facility” (TSG). Since good agreement is obtained , we conclude that the potential flow model is suitable to predict the pressure induced forces on track side objects. Then, the validated simplified potential model is used to select the shape of a train head which minimizes the sucking force on a cylindrical object passing the train at a specified lateral distance. In the second part, we apply the continous adjoint optimization approach, first on the potential train body and then on a more detailed shape of a train performing Reynolds-averaged Navier-Stokes (RANS) simulations. The focus of this ongoing research is to develop a process chain using the continous adjoint-based shape optimization approach in conjunction with a potential flow on the one hand and with RANS simulations, filtered gradients and CAD-free mesh morphing based on radial basis function interpolation on the other hand. In the RANS study, shape optimization is performed with the objective of minimizing the amplitude of the generated pressure wave. This part of the paper includes new results of the work started in Jakubek et al..

The operating conditions of modern high-speed trains require efficient aerodynamic shape optimization methods. Many of the interesting aerodynamic features can be determined by means of RANS simulations. The objective of the study, presented in this paper, is to determine how far a shape optimization procedure using adjoint-based methods with continuous approach in conjunction with filtered gradients and CAD free mesh morphing based on radial basis function interpolation is capable of meeting the requirements of modern train development. First applications of the developed process chain consider shape optimization with regard to the generated pressure wave.