Thermal Analysis and Design of Self-Heating Molds Using Large-Scale Additive Manufacturing for Out-of-Autoclave Applications

Abstract

Autoclave processing is a commonly used state-of-the-art fiber-reinforced composite manufacturing technology, albeit with high capital cost, long cycle times and high energy consumption. Alternatively, out-of-autoclave processing reduces the initial and operating costs while producing composite structures with similar quality as that of autoclave parts. Additive Manufacturing (AM) the scaled-up molds for out-of-autoclave process using carbon fiber (CF) reinforced composite offers design flexibility, enhanced mechanical, and thermal properties in addition to reduction in weight and cost. However, heating of these molds using an oven is still expensive and necessitates an energy-efficient heating process. In this study, resistive heating through heating elements embedded within fiber reinforced composite molds is used as an efficient heating mechanism. The goal is to design wire embeddings and determine the optimal heat flux density to achieve a target uniform temperature of 80°C across the mold surface. To this end, numerical analyses were performed to evaluate the temperature distribution across the composite mold surface for a given wire placement and mold configuration. Constant thermal properties of the 20 wt.% short CF reinforced acrylonitrile butadiene styrene (ABS) were used in the thermal analysis. Time taken to reach the steady state temperature was also estimated. Design guidelines for wire embeddings were included to enable efficient manufacturing of fiber-reinforced composites through out-of-autoclave molds.

Compression and energy absorption characteristics of short fiber‐reinforced 2D composite lattices made by material extrusion

“…However, differences in the manufacturing process itself could lead to different mechanical properties of lattice structures at mid‐scale and large‐scale AM, affecting their compression performance. In large‐scale AM, the process parameters such as layer time and bead dimensions could affect the geometric stability, porosity, warping, and distortion of these structures, resulting in distinct compression characteristics or even failure during printing 28,55–59 . However, detailed investigations into the effect of process parameters of large‐scale AM on mechanical response of lattice structures is out of the scope of the current study.…”

“…In large-scale AM, the process parameters such as layer time and bead dimensions could affect the geometric stability, porosity, warping, and distortion of these structures, resulting in distinct compression characteristics or even failure during printing. 28,[55][56][57][58][59] However, detailed investigations into the effect of process parameters of large-scale AM on mechanical response of lattice structures is out of the scope of the current study.…”

Numerical Modelling of the Heat Source and the Thermal Response of an Additively Manufactured Composite during an Active Thermographic Inspection

“…Thermal analysis is carried out while the part is being manufactured, layer by layer. This method is widely used to optimise printing parameters or in machine learning [6,7]. Concurrently, IRT has also gained increasing interest in the context of the detection of porosity inside components made of composite materials [8].…”