Fabrication Sequence Optimization for Minimizing Distortion in Multi-Axis Additive Manufacturing

Additive manufacturing of metal parts involves phase transformations and high temperature gradients which lead to uneven thermal expansion and contraction, and, consequently, distortion of the fabricated components. The distortion has a great influence on the structural performance and dimensional accuracy, e.g., for assembly. It is therefore of critical importance to model, predict and, ultimately, reduce distortion. In this paper, we present a computational framework for fabrication sequence optimization to minimize distortion in multi-axis additive manufacturing (e.g., robotic wire arc additive manufacturing), in which the fabrication sequence is not limited to planar layers only. We encode the fabrication sequence by a continuous pseudo-time field, and optimize it using gradient-based numerical optimization. To demonstrate this framework, we adopt a computationally tractable yet reasonably accurate model to mimic the material shrinkage in metal additive manufacturing and thus to predict the distortion of the fabricated components. Numerical studies show that optimized curved layers can reduce distortion by orders of magnitude as compared to their planar counterparts

Effect of rotator cuff dysfunction on the initial mechanical stability of cementless glenoid components

The functional outcome of shoulder replacement is related to the condition of the rotator cuff. Rotator cuff disease is a common problem in candidates for total shoulder arthroplasty; this study relates the functional status of the rotator cuff to the initial stability of a cementless glenoid implant. A 3D finite element model of a complete scapula was used to quantify the effect of a dysfunctional rotator cuff in terms of bone-implant interface micromotions when the implant is physiologically loaded shortly after surgery. Four rotator cuff conditions (from fully intact to progressively ruptured rotator cuff tendons) as well as two bone qualities were simulated in a model. Micromotions were significantly larger in the worst modeled cuff dysfunction (i.e. the supraspinatus and infraspinatus tendons were fully dysfunctional). Micromotions were also significantly different between conditions with healthy and poor bone quality. The implant's initial stability was hardly influenced by a dysfunctional supraspinatus alone. However, when the infraspinatus was also affected, the glenohumeral joint force was displaced to the component's rim resulting in larger micromotions and instability of the implant

Rapid and discriminatory diagnosis of scrapie and BSE in retro-pharyngeal lymph nodes of sheep

BACKGROUND: Diagnosis based on prion detection in lymph nodes of sheep and goats can improve active surveillance for scrapie and, if it were circulating, for bovine spongiform encephalopathy (BSE). With sizes that allow repetitive testing and a location that is easily accessible at slaughter, retropharyngeal lymph nodes (RLN) are considered suitable organs for testing. Western blotting (WB) of brain homogenates is, in principle, a technique well suited to both detect and discriminate between scrapie and BSE. In this report, WB is developed for rapid diagnosis in RLN and to study biochemical characteristics of PrP(res). RESULTS: Optimal PrP(res )detection in RLN by WB was achieved by proper tissue processing, antibody choice and inclusion of a step for PrP(res)concentration. The analyses were performed on three different sheep sources. Firstly, in a study with preclinical scrapie cases, WB of RLN from infected sheep of VRQ/VRQ genotype – VRQ represents, respectively, polymorphic PrP amino acids 136, 154, and 171 – allowed a diagnosis 14 mo earlier compared to WB of brain stem. Secondly, samples collected from sheep with confirmed scrapie in the course of passive and active surveillance programmes in the period 2002–2003 yielded positive results depending on genotype: all sheep with genotypes ARH/VRQ, VRQ/VRQ, and ARQ/VRQ scored positive for PrP(res), but ARQ/ARQ and ARR/VRQ were not all positive. Thirdly, in an experimental BSE study, detection of PrP(res )in all 11 ARQ/ARQ sheep, including 7 preclinical cases, was possible. In all instances, WB and IHC were almost as sensitive. Moreover, BSE infection could be discriminated from scrapie infection by faster electrophoretic migration of the PrP(res )bands. Using dual antibody staining with selected monoclonal antibodies like 12B2 and L42, these differences in migration could be employed for an unequivocal differentiation between BSE and scrapie. With respect to glycosylation of PrP(res), BSE cases exhibited a greater diglycosylated fraction than scrapie cases. Furthermore, a slight time dependent increase of diglycosylated PrP(res )was noted between individual sheep, which was remarkable in that it occurred in both scrapie and BSE study. CONCLUSION: The present data indicate that, used in conjunction with testing in brain, WB of RLN can be a sensitive tool for improving surveillance of scrapie and BSE, allowing early detection of BSE and scrapie and thereby ensuring safer sheep and goat products

Prediction of torsional failure in 22 cadaver femora with and without simulated subtrochanteric metastatic defects: a CT scan-based finite element analysis

BACKGROUND: In metastatic bone disease, prophylactic fixation of impending long bone fracture is preferred over surgical treatment of a manifest fracture. There are no reliable guidelines for prediction of pathological fracture risk, however. We aimed to determine whether finite element (FE) models constructed from quantitative CT scans could be used for predicting pathological fracture load and location in a cadaver model of metastatic bone disease. MATERIAL AND METHODS: Subject-specific FE models were constructed from quantitative CT scans of 11 pairs of human femora. To simulate a metastatic defect, a transcortical hole was made in the subtrochanteric region in one femur of each pair. All femora were experimentally loaded in torsion until fracture. FE simulations of the experimental set-up were performed and torsional stiffness and strain energy density (SED) distribution were determined. RESULTS: In 15 of the 22 cases, locations of maximal SED fitted with the actual fracture locations. The calculated torsional stiffness of the entire femur combined with a criterion based on the local SED distribution in the FE model predicted 82% of the variance of the experimental torsional failure load. INTERPRETATION: In the future, CT scan-based FE analysis may provide a useful tool for identification of impending pathological fractures requiring prophylactic stabilization