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Evaluating FDM Process Parameter Sensitive Mechanical Performance of Elastomers at Various Strain Rates of Loading

机译:评估FDM工艺参数敏感机械性能的各种应变率加载

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摘要

To optimize the mechanical performance of fused deposition modelling (FDM) fabricated parts, it is necessary to evaluate the influence of process parameters on the resulting mechanical performance. The main focus of the study was to characterize the influence of the initial process parameters on the mechanical performance of thermoplastic polyurethane under a quasi-static and high strain rate (~2500 s ). The effects of infill percentage, layer height, and raster orientation on the mechanical properties of an FDM-fabricated part were evaluated. At a quasi-static rate of loading, layer height was found to be the most significant factor (36.5% enhancement in tensile strength). As the layer height of the sample increased from 0.1 to 0.4 mm, the resulting tensile strength sample was decreased by 36.5%. At a high-strain rate of loading, infill percentage was found to be the most critical factor influencing the mechanical strength of the sample (12.4% enhancement of compressive strength at 100% as compared to 80% infill). Furthermore, statistical analysis revealed the presence of significant interactions between the input parameters. Finally, using an artificial neural networking approach, we evaluated a regression model that related the process parameters (input factors) to the resulting strength of the samples.
机译:为了优化融合沉积建模(FDM)制造的部件的机械性能,有必要评估工艺参数对所得的机械性能的影响。该研究的主要重点是在准静态和高应变率下表征初始工艺参数对热塑性聚氨酯机械性能的影响(〜2500秒)。评价填充百分比,层高度和光栅方向对FDM制造部分的机械性能的影响。在准静态的加载速率下,发现层高度是最显着的因素(拉伸强度的增强36.5%)。随着样品的层高度从0.1增加到0.4mm,所得的拉伸强度样品降低36.5%。在高应变率的加载速率下,发现填充百分比是影响样品机械强度的最关键因素(12.4%的抗压强度增强100%,与80%填充相比)。此外,统计分析显示输入参数之间存在显着的相互作用。最后,使用人工神经网络方法,我们评估了与所得样本强度相关的过程参数(输入因子)的回归模型。

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