Abstract
Nowadays, the production of large pieces made of thermoplastic composites is an industrial challenging issue as there are yet several difficulties associated to their processing. The laser-assisted tape placement (LATP) process is an automated manufacturing technique to produce long-fiber reinforced thermoplastic matrix composites. In this process, a tape is placed and progressively welded on the substrate. The main aim of the present work is to solve an almost state of the art thermal model by using an efficient numerical technique, the so-called Proper Generalized Decomposition (PGD) that considers parameters (geometrical and material) as model extra-coordinates. Within the PGD rationale the parametric temperature field is expressed in a separated form, as a finite sum of functional products, where each term depends on a single coordinate (space, time or each one of the parameters considered as extra-coordinates). Such a separated representation allows the explicit expression of the sensitivity fields, from the temperature derivative with respect to each parameter. These sensitivity fields represent a very valuable methodology to analyze and establish the influence of the critical input parameters on the thermal response, and therefore, for performing process optimization and control, as well as for evaluating the effect of parameters variability on the thermal response.
Highlights
The context of this study is the laserassisted tape placement (LATP) process, that consists in an automated filament winding process designed to produce composite parts with a thermoplastic matrix
We study the influence of material parameters variability into the thermal behaviour during the LATP process from the data reported in [20]
The Proper Generalized Decomposition (PGD) [29, 30] is an “a priori” model order reduction technique based on the use of separated representations in order to ensure that the complexity scales linearly with the model dimensionality
Summary
The context of this study is the LATP process, that consists in an automated filament winding process designed to produce composite parts with a thermoplastic matrix. These sensitivity fields represent a very valuable methodology to analyze and establish the influence of the critical input parameters on the thermal response, and for performing process optimization and control Having such a parametric solution allows quantifying the effects of materials and/or process parameters variability, because as highlighted latter, real properties are statistically distributed. The present work does not propose neither models nor simulation tools, it considers state of the art models, applies an advanced simulation tool, the Proper Generalized Decomposition (PGD) for calculating a parametric temperature, and it proposes a new methodology for providing an exhaustive analysis on the critical parameters influencing the process (sensitivity analysis) as well as a very efficient uncertainty propagator, able to address material and process variability, and evaluating their impact on the process. The third part analyses the influence of the input material parameters on the thermal response and perform a statistical analysis related to the material and process variability
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