3 research outputs found
In Situ Defect Detection Using Three Color Spectroscopy in Laser Powder Bed Additive Manufacturing
Additive Manufacturing (AM) provides a way to create parts that would be extremely difficult or impossible with conventional manufacturing processes. However, AM also introduces defects, which are detrimental to the mechanical performance. These defects are potentially unknown until post-processing inspection and testing, wasting time and resources on an unusable part or initiating unexpected failure. Historically, spectroscopy has successfully been used for in situ monitoring of laser welding, using changing parameters in the generated plume to predict defects. In situ monitoring using a visible spectrometer for fabrication of Alloy 718 on a test bed laser powder bed fusion system is performed. AM defects, such as keyhole porosity and unfused powder, are detected in the sensor output and a physics-based modeling approach is used to predict defect occurrence. Spectroscopy can provide near real-time monitoring, allowing defects to be predicted, and potentially corrected before the completion of the part, saving time and resources
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Individual and joint trajectories of change in bone, lean mass and physical performance in older men.
BackgroundDeclines in bone, muscle and physical performance are associated with adverse health outcomes in older adults. However, few studies have described concurrent age-related patterns of change in these factors. The purpose of this study was to characterize change in four properties of muscle, physical performance, and bone in a prospective cohort study of older men.MethodsUsing repeated longitudinal data from up to four visits across 6.9 years from up to 4681 men (mean age at baseline 72.7 yrs. ±5.3) participating in the Osteoporotic Fractures in Men (MrOS) Study, we used group-based trajectory models (PROC TRAJ in SAS) to identify age-related patterns of change in four properties of muscle, physical performance, and bone: total hip bone mineral (BMD) density (g/m2) and appendicular lean mass/ht2 (kg/m2), by DXA; grip strength (kg), by hand dynamometry; and walking speed (m/s), by usual walking pace over 6 m. We also described joint trajectories in all pair-wise combinations of these measures. Mean posterior probabilities of placement in each trajectory (or joint membership in latent groups) were used to assess internal reliability of the model. The number of trajectories for each individual factor was limited to three, to ensure that the pair-wise determination of joint trajectories would yield a tractable number of groups as well as model fit considerations.ResultsThe patterns of change identified were generally similar for all measures, with three district groups declining over time at roughly similar rates; joint trajectories revealed similar patterns with no cross-over or convergence between groups. Mean posterior probabilities for all trajectories were similar and consistently above 0.8 indicating reasonable model fit to the data.ConclusionsOur description of trajectories of change with age in bone mineral density, grip strength, walking speed and appendicular lean mass found that groups identified by these methods appeared to have little crossover or convergence of change with age, even when considering joint trajectories of change in these factors