Publications

Energetic transition in automotive industry leads to production of new parts such as battery trays. These parts present machining challenges linked to their vibration. It was shown that dynamic model accuracy is highly conditioned by fixture modeling. In the present work a clamping modeling approach for machining simulation is presented. Updating methodology of fixture stiffness and damping, based on dynamic reduction, is detailed. It allows to assess the influence of fixture on part dynamic behaviour in machining. Numerical predictions of ma chined surface geometry are compared to experiments on a battery tray part.

Background Measuring passive hip flexion range of motion (ROM) is challenging due to compensatory movements. Despite the interest in using functional lateral radiographs for assessing hip mobility, the relationship with passive hip flexion ROM remains unclear. This study aims to elucidate this relationship and clarify spinopelvic parameters and mobility factors influencing variations in passive and radiographic hip flexion ROM. Methods A retrospective cross-sectional study was conducted on 154 preoperative patients undergoing primary total hip arthroplasty. Passive and radiographic hip flexion ROM were assessed to clarify these relationships, and these differences were classified into 3 groups (O, A and U). Spinopelvic and hip parameters were assessed in standing, relaxed-seated and flexed-seated positions, as well as lumbar, pelvis, and hip mobility between each position to identify factors influencing differences. Results There was a moderate correlation between passive and radiographic hip flexion ROM (R2 = 0.48, P < .01). A significant difference was found in pelvic and hip alignment in the flexed-seated position between all groups. In postural changes, the O group, which had more patients with relatively low hip mobility, showed greater lumbar spine and pelvic movement, while the U group, which had more patients with relatively high hip mobility, showed less lumbar spine and pelvic movement. Conclusions This study confirmed that passive hip flexion ROM and radiographic hip flexion ROM correlate and that spinopelvic and hip alignment and mobility influence these differences. This result suggests that clinicians should consider lumbar and pelvic alignment and mobility in clinical practice to improve the accuracy of passive hip flexion ROM measurements.

Study Design. Retrospective study of a multicentric prospective database. Objective. This study aimed at describing the relative contribution of vertebral bodies versus discs to lumbar lordosis, and its variation with age and pelvic incidence. Summary of Background Data. While studies sought to determine the physiological magnitude and distribution of lumbar lordosis, data regarding its anatomical composition is lacking. Methods. This study included healthy volunteers with full-body stereoradiographs in free-standing position, without lumbosacral transitional vertebra or age under 18. The following parameters were analyzed: age, sex, pelvic incidence (PI), lumbar lordosis (LL). Posterior heights and sagittal Cobb angles between upper and lower endplate for each lumbar disc and each vertebral body were measured from L1 to S1. Ratios of contribution to LL were calculated for each disc and vertebral body. The cohort was divided into four age groups and four PI groups. Results. 645 subjects were included, mean age was 37.6±16.3, 51% of females. There was a significant decrease in total lumbar disc lordosis with age (−48.9±9.7° to −42.9±10.2°), occurring in lower LL. Vertebral bodies were significantly more kyphotic in Seniors than Youngs (−8.9±8.4° vs. −5.0±9.4°, P=0.03), driven by a significant increase in kyphosis of L1 and L2 bodies. Vertebral body contribution to LL significantly increased between groups as PI increased, from a median of 8.0% to 20.5% (P&lt;0.001). This decrease in disc contribution in favor of vertebral bodies mainly took place in lower LL. Conclusion. This study highlights the importance of vertebral contribution to lumbar lordosis, ranging from 8 to 21% among PI groups. Lumbar lordosis decreased with aging through decreased disc lordosis in the lower lumbar spine and increased body kyphosis in the upper lumbar spine. These results may help surgeons in the assessment of sagittal alignment and the selection of operative technique to achieve surgical correction.

This paper proposes a model for predicting the complex inelastic mechanical response of polyamide 66. Polyamide 66 is a semi-crystalline pressure-sensitive polymer that exhibits asymmetric yielding behavior, in which the yield strength is slightly higher in compression. With this in mind, an �� 1 -�� 2 yield function considering the asymmetric behavior and the hydrostatic pressure effect is presented and integrated into a phenomenological viscoelastic–viscoplastic model accounting for ductile damage. The corresponding thermodynamic framework and constitutive laws are discussed. Then, an experimental approach is presented to identify the model parameters through mechanical tests with different loading paths to capture the active mechanisms. The experimental findings obtained from uni-axial and multi-axial (tension-torsion) mechanical tests and the numerical model are used in an optimization algorithm to identify the model parameters. A parametric analysis is performed to study the effect of the asymmetric behavior on the state variables under different loading conditions using the identified parameters. The present model responses are in good agreement with the experimental data, and the combination of the experimental and numerical results demonstrates and statesthe asymmetric behavior of polyamide at relative humidity (RH) of 50%, which is captured by the suggested model. It is also worth pointing out that the parametric study conducted on a notched plate using finite element simulations showcases the structural computation capabilities of the proposed model.

This contribution presents a new physics-informed deep homogenization neural network model for identifying local displacement and stress fields, as well as homogenized moduli, of nanocomposites with periodic arrays of porosities under general loading conditions. Notably, it accounts for the surface elasticity effect, utilizing the Gurtin-Murdoch interface theory. First of all, a fully connected neural network model is established that maps the spatial coordinates, passing first through several sinusoidal functions, to the microscopic displacements. The loss function is formulated as the weighted sum of residuals of Navier-Cauchy equations in the bulk domains and the Young-Laplace equations on the energetic surfaces, evaluated on separate sets of collocation points. To more effectively predict stress concentrations inside the microstructures, we introduce fully trainable weights to each collocation point. The capacity and effectiveness of the new homogenization technique for capturing the size-dependent local and global response of nanocomposites with distinct pore sizes and shapes are verified upon extensive comparisons with the finite-element benchmark results, under various loading conditions. New results showcase the proposed theory’s ability to model random distributions of nano-porosities with a high degree of accuracy, a task not easily achievable with alternative techniques except for the specialized finite-element method.

In this work, a new class of iron-based high entropy shape memory alloys (HE-SMAs) have been designed, characterized, and optimized. These FeCu-NiMnV alloys (FeMn-like) with damping properties at low and high temperatures are developed; a methodology is proposed to demonstrate how to preserve this effect from the memory loss observed on conventional damping alloys. The developed alloys are analyzed using X-ray diffraction, scanning electron microscopy and differential scanning calorimetry. Their damping capacity is investigated using a drop weight test device instrumented with a digital image correlation system for the displacement measurement. It is compared with one of FeMnV, NiTi, CuAlNi, and 1050A alloys at different temperatures. The results show that the damping capacity is interesting over a wide range of operating temperatures. It has been established that the cocktail effect obtained by mixing Cu, Fe, Ni, Mn, and V elements allows for optimizing the damping capacity of the HE-SMAs. In addition, the sluggish diffusion may allow these HE-SMAs to prevent the premature aging that leads to a degradation of the damping behavior notably at high temperature. The variation of the composition of the Cu x-Fe y Ni z Mn 20 V 11 alloys enables the adjustment of the alloying element content by favoring the appearance of the non-thermally activated martensite keeping hence a stable damping behavior from - 40 to 200 C.

We present a novel elasticity-inspired data-driven Fourier homogenization network (FHN) theory for periodic heterogeneous microstructures with square or hexagonal arrays of cylindrical fibers. Towards this end, two custom-tailored networks are harnessed to construct microscopic displacement functions in each phase of composite materials, based on the exact Fourier series solutions of Navier’s displacement differential equations. The fiber and matrix networks are seamlessly connected through a common loss function by enforcing the continuity conditions, in conjunction with periodicity boundary conditions, of both tractions and displacements. These conditions are evaluated on a set of weighted collocation points located on the fiber/matrix interface and the exterior faces of the unit cell, respectively. The partial derivatives of displacements are computed effortlessly through the automatic differentiation functionality. During the training of the FHN model, the total loss function is minimized with respect to the Fourier series parameters using gradient descent and concurrently maximized with respect to the adaptive weights using gradient ascent. The transfer learning technique is employed to speed up the training of new geometries by leveraging a pre-trained model. Comparison with finite-element/volume-based unit cell solutions under various loading scenarios showcases the computational capability of the proposed method. The utility of the proposed technique is further demonstrated by capturing the interfacial debonding in unidirectional composites via a cohesive interface model.

This paper presents a topology optimization framework to achieve volume minimization with Crossland fatigue constraints under proportional loading using the Constrained Natural Element Method. The local minimization problem is solved by means of the augmented Lagrangian method to deal with a large number of evaluation points. To suppress the numerical instabilities, a neighbor-based filter is proposed and compared to the widely used density filter. Furthermore, to circumvent the problem of stress singularity, several different relaxations of the constraints are also investigated. Compared with the topology optimization procedure based on the finite element method, the proposed method has the advantage of showing greater flexibility and convenience in discretization of complex design domains and the ability to maintain stable output under various discretization conditions.

The effect of increased productivity in L-PBF manufacturing on the metal dusting resistance of Inconel 625 was studied at 610 ◦C. Two sets of processing parameters were tested: the standard parameters given by the machine manufacturer and degraded parameters with increased scan speed and hatching distance. The materials obtained with degraded parameters presented numerous lacks of fusion at the surface and exhibited significantly shorter incubation times before corrosion. Carburisation was preferentially localised around the defects where the oxide scale was less protective and where the confinement of the atmosphere could result in an increase of the local carbon activity.

The Proper Generalized Decomposition (PGD) is a Model Order Reduction framework that has been proposed to be able to do parametric analysis of physical problems. These parameters may include material properties, boundary conditions, etc. With this framework most of the computation may done in an off-line stage allowing to perform real time simulation in a variety of situations. Nevertheless, this scheme may lose its efficiency where the domain itself is also considered as “a parameter”. Optimal transport techniques, on the other hand, have demonstrated exceptional performance in interpolating different types of fields described over geometrical domains with varying shapes. Hence trying allying both techniques is quite natural. The core idea is that PGD handles the parametric solution, while the optimal transport-based methodology transports the solution for a family of domains defined by geometrical parameters such as lengths, radii, thicknesses, etc. In this first attempt the associated methodology is proposed and apply in simple 1D and 2D cases showing interesting performances.