Chady Ghnatios

On the use of model order reduction for simulating automated fibre placement processes

Automated fibre placement (AFP) is an incipient manufacturing process for composite structures. Despite its conceptual simplicity it involves many complexities related to the necessity of melting the thermoplastic at the interface tape-substrate, ensuring the consolidation that needs the diffusion of molecules and control the residual stresses installation responsible of the residual deformations of the formed parts. The optimisation of the process and the determination of the process window requires a plethora of simulations because there are many parameters involved in the characterization of the material and the process. The exploration of the design space cannot be envisaged by using standard simulation techniques. In this paper we propose the off-line calculation of rich parametric solutions that can be then explored on-line in real time in order to perform inverse analysis, process optimisation or on-line simulation-based control. In particular, in the present work, and in continuity with our former works, we consider two main extra-parameters, the first related to the line acceleration and the second to the number of plies laid-up.

Improving Computational Efficiency in LCM by Using Computational Geometry and Model Reduction Techniques

LCM simulation is computationally expensive because it needs an accurate solution of flowequations during the mold filling process. When simulating large computing times are not compatiblewith standard optimization techniques (for example for locating optimally the injection nozzles)or with process control that in general requires fast decision-makings. In this work, inspired by theconcept of medial axis, we propose a numerical technique that computes numerically approximatedistance fields by invoking computational geometry concepts that can be used for the optimal locationof injection nozzles in infusion processes. On the other hand we also analyze the possibilities thatmodel order reduction offers to fast and accurate solutions of flow models in mold filling processes.

A Simulation App based on reduced order modeling for manufacturing optimization of composite outlet guide vanes

Composites manufacturing processes usually involve multiscale models in both space and time, highly non-linear and anisotropic behaviors, strongly coupled multiphysics and complex geometries. In this framework, the use of simulation for real-time decision making directly in the manufacturing facility is still precluded nowadays, in spite of the impressive progresses reached in numerical analysis and computer science during the last decade. In this paper, a process-specific simulation tool based on reduced order modeling is introduced, the Simulation App. This concept is presented through a practical case involving a multi-physics and coupled problem describing the manufacturing process of a composite outlet guide vane. We show that several manufacturing settings can be simulated in few seconds with the Simulation App, thus enabling fast process optimization. Finally, the advantages over general-purpose simulation software, in the context of process simulation, are discussed.

Optimizing Composites Forming Processes by Applying the Proper Generalized Decomposition

Different computational methods are nowadays active research topics in computational mechanics. Different strategies have been proposed, the main challenge being always the computing cost induced by complex problems exhibiting multiple degrees of freedom. In this paper we present the Proper Generalized Decompositions or PGD, a way of addressing an efficient solution for multidimensional problems [1]. Moreover, we will apply this technique on the design of dies. The optimal choice of the design parameters, in our case the temperatures prescribed on different regions of the die wall, is a difficult task. In general some values are chosen for the thermal simulations performed. Then a cost function is evaluated and the temperatures are modified in order to reduce such function. Obviously, for each choice of the temperatures prescribed on the different regions of the die walls, a thermal problem must be solved. Thus, optimization becomes too expensive from the computation time point of view. The PGD allows solving only once a thermal model for any temperature prescribed on the different regions of the die wall. Optimizations as well as inverse identification become an easy matter.

Processing of a carbon fiber reinforced polymer (CFRP) laminate part by microwaves

Microwave (MW) technology relies on volumetric heating. Thermal energy is transferred through electromagnetic fields to materials that can absorb it at specific frequencies. The principal objective of this work is to model and simulate the interactions of the MW field with a composite laminated part, consisting of a stack of layers of different orientations, each layer made of resin matrix and carbon fibers.

Simulation of microwave heating of a composite part in an oven cavity

Microwave (MW) technology relies on volumetric heating. Thermal energy is transferred to the material that can absorb it at specific frequencies. In this paper, a coupled thermic and electromagnetic model is proposed in order to simulate the emerging process of microwave heating for composite materials. Solving the problem in a laminated composite material requires a high degree of discretization in the thickness direction which is made possible by introducing the in-plane-out-of-plane decomposition approach using the Proper Generalized Decomposition (PGD).Microwave (MW) technology relies on volumetric heating. Thermal energy is transferred to the material that can absorb it at specific frequencies. In this paper, a coupled thermic and electromagnetic model is proposed in order to simulate the emerging process of microwave heating for composite materials. Solving the problem in a laminated composite material requires a high degree of discretization in the thickness direction which is made possible by introducing the in-plane-out-of-plane decomposition approach using the Proper Generalized Decomposition (PGD).

Optimization of composite forming processes using nonlinear thermal models and the proper generalized decomposition

The potential of reduced order models to improve computational efficiency without any loss of behavioral fidelity, is attracting many researchers. Indeed, the reduced order models appear to be efficient for linear models. However, the challenge isnt won yet facing the nonlinear models. The Proper Generalized Decomposition (PGD) is one of the popular reduced order models techniques. In fact, it reduces the computation time by separating the space dimensions and therefore reducing the dimensionality of the problem. Moreover, the PGD treats nonlinearity by a linearization step, using iterations for example. However, the aim of using reduced order models is the computation time reduction. Using iterative linearization techniques, computation time reduction becomes irrelevant and therefore new techniques should be proposed. In this work we propose a new linearization method by combining the PGD and the POD (Proper Orthogonal Decomposition). The treated problem rises from thermoset materials curing where a coupling between the nonlinear heat equation and the nonlinear curing kinetics exists.

Poroelastic properties identification through micro indentation modeled by using the proper generalized decomposition

Recently, articular cartilage are being intensively studied to be able to understand their properties and mechanical behavior, in order to be able to create effective replacements. However, these structures are complex and their behavior is not effectively modeled yet. In fact cartilage is a biphasic structure and its interstitial fluid pressurization is the main load bearing phenomenon as well as the main lubricant of the structure. Hertzian rate-controlled micro indentation is one of the common experiments that can be used to identify material properties by comparing to the simulated models. In this work we propose to simulate the micro indentation of cartilage by using a simplified mechanical model combined with the use of the proper generalized decomposition to compute the fluid pressure inside the cartilage calcium tissues.

3D modeling of squeeze flow of unidirectionally thermoplastic composite inserts

Thermoplastic composites are attractive because they can be recycled and exhibit superior mechanical properties. The ability of thermoplastic resin to melt and solidify allows for fast and cost-effective manufacturing processes, which is a crucial property for high volume production. Thermoplastic composite parts are usually obtained by stacking several prepreg plies to create a laminate with a particular orientation sequence to meet design requirements. During the consolidation and forming process, the thermoplastic laminate is subjected to complex deformation which can include intraply and/or interply shear, ply reorientation and squeeze flow. In the case of unidirectional prepregs, the ply constitutive equation, when elastic effects are neglected, can be modeled as a transversally isotropic fluid, that must satisfy the fiber inextensibility as well as the fluid incompressibility. The high-fidelity solution of the squeeze flow in laminates composed of unidirectional prepregs was addressed in our former ...

3D modelling of squeeze flow of unidirectional and fabric composite inserts

The enhanced design flexibility provided to the thermo-forming of thermoplastic materials arises from the use of both continuous and discontinuous thermoplastic prepregs. Discontinuous prepregs are patches used to locally strengthen the part. In this paper, we propose a new modelling approach for suspensions involving composite patches that uses theoretical concepts related to discontinuous fibres suspensions, transversally isotropic fluids and extended dumbbell models.