Geometric fidelity of 3D printed products is critical for additive manufacturing (AM) to be a direct manufacturing technology. Shape deviations of AM built products can be attributed to multiple variation sources such as substrate geometry defect, disturbance in process variables, and material phase change. Three strategies have been reported to improve geometric quality in AM: (1) control process variables x based on the observed disturbance of process variables Ax, (2) control process variables x based on the observed product deviation Ay, and (3) control input product geometry y based on the observed product deviation Ay. This study adopts the third strategy which changes the computer-aided design (CAD) design by optimally compensating the product deviations. To accomplish the goal, a predictive model is desirable to forecast the quality of a wide class o f product shapes, particularly considering the vast library of AM built products with complex geometry. Built upon our previous optimal compensation study of cylindrical products, this work aims at a novel statistical predictive modeling and compensation approach to predict and improve the quality of both cylindrical and prismatic parts. Ex perimental investigation and validation of polyhedrons a indicates the promise of predict ing and compensating a wide class of products built through 3D printing technology.

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Fatigue failure of rubber‐like materials has been often previously modeled with classical power‐law approaches, however with the new generation of physics‐based fatigue models, choosing the proper model depends on the material, loading condition and the computational cost users can afford. In view of the high number of validated fatigue models, it is challenging for engineers to choose a reliable fatigue model for a specific application. In service condition, reliability of elastomeric components is influenced by a variety of factors, ranging from environmental service condition to mechanical loads and compound properties. In sensitive applications, assuring the long‐term reliable performance of elastomers subjected to multiaxial variable loading is necessary to ensure the durability of the system. The purpose of this article is to review different stressors that contribute to the fatigue failure of elastomers and the associated modeling approaches used to assess their strengths and weaknesses. Additionally, this article summarizes the effect of thermal oxidation, moisture, hydrolysis, and radiation on long‐term aging of the fatigue properties of rubber, which has been studied over the last 50 years.

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