In design under uncertainty, random distributions are often determined by expensive sampling tests. A key question is whether to invest in more samples or live with a reduced performance by fewer samples due to large uncertainty. The question is particularly difficult to answer when the type of distribution is unknown. This paper investigates the tradeoff between performance and conservativeness in estimating B-basis allowables, using experiments on composite plates with holes. Two approaches that do not require a distribution type are examined: (1) bootstrap confidence intervals and (2) Hanson-Koopmans non-parametric method. Based on the study, it is found that the Hanson-Koopmans method was more conservative than the bootstrap method because the latter penalized allowables for small-size samples. For a small number of samples (less than 29), conservative estimations are preferred over accuracy to account for the large uncertainty. Based on this observation, the bootstrap-assisted Hanson-Koopmans method is proposed to enhance the conservativeness. For the tested cases, the performance penalty using the bootstrap-assisted Hanson-Koopmans method for a small number of samples is found to be substantial.
The term additive manufacturing (AM) is used to describe processes of joining materials to make parts from a three-dimensional model data, as opposed to subtractive manufacturing. Although AM technology offers potential cost savings, production efficiencies, and distinct design features that cannot be easily achieved through traditional manufacturing, it is known that the performance of a product that is additively manufactured can be sensitive to the raw materials and the process parameters used. This often means that performance can vary across a product that is additively manufactured depending on build orientation, location within the processing equipment, and the combination of process parameters utilized in fabrication. In addition, the manufacturing variations that are inherent in the AM process from build to build, machine to machine, or batch to batch can have a significant effect on the final mechanical performance of a product that is additively manufactured. The task of characterizing mechanical properties at the coupon level to represent product that is additively manufactured not only is essential in design and analysis for the desired application but also is crucial in material, process, and machine qualification efforts. In choosing a test method or coupon design, the test volume should be sufficient to properly represent the part of interest. This paper provides experiences with using current industry-accepted ASTM tensile coupon test methods on products that are additively manufactured.
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