Finite element models are increasingly being utilized in composite materials design; thus, an increase in the accuracy of the model analysis and a decrease in computational cost are of paramount importance. This study investigates the effects of a particular add-on, Helius:MCT (Firehole Technologies, Inc.), onto the Abaqus (Dassault Systèmes) software package. Unlike the stand-alone Abaqus software, Helius:MCT embodies a solver, which analyzes the composite structure by separating the fiber and matrix into constituent parts. Treating the fiber and matrix as separate, yet linked entities, allows for a more accurate depiction of the formations of stress and strain within the composite. Furthermore, Helius:MCT utilizes a method called Intelligent Discrete Softening (IDS), a feature not present within Abaqus, to increase solver robustness and convergence probability. An Abaqus finite element (FE) model of a notched, carbon-fiber panel loaded in bending was used in this study. Six different laminate combinations were tested with six variations of the Abaqus model. Three of the variations used Helius:MCT with Abaqus and three the stand-alone Abaqus package. The combinations were composed of either 20 or 40 plies with 10, 30, or 50 percent all zero ply orientations. All the FE analysis results were compared to experimental values for a plate of the exact configuration as that of the model. The most accurate results were obtained using Helius:MCT. The configuration with the greatest accuracy utilizes Helius:MCT and deviates an average of 1.7 percent from experimental values for maximum flexural strength. A single run takes an average of 7 hours to complete. Conversely, the most accurate configuration obtained without the use of Helius:MCT deviates an average of 10 percent from the experimental values and takes over 80 hours to run. Helius: MCT increases the accuracy and decreases the computational costs of the analyses of composite models in Abaqus. The improvements in analyses while using Helius: MCT may allow for a substantial savings in experimental costs and in valuable time.

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