Tissue spheroids have been proposed as building blocks in 3D biofabrication. Conventional magnetic force-driven 2D patterning of tissue spheroids requires prior cell labeling by magnetic nanoparticles, meanwhile a label-free approach for 3D magnetic levitational assembly has been introduced. Here we present first time report on rapid assembly of 3D tissue construct using scaffold-free, nozzle-free and label-free magnetic levitation of tissue spheroids. Chondrospheres of standard size, shape and capable to fusion have been biofabricated from primary sheep chondrocytes using non-adhesive technology. Label-free magnetic levitation was performed using a prototype device equipped with permanent magnets in presence of gadolinium (Gd ³⁺ ) in culture media, which enables magnetic levitation. Mathematical modeling and computer simulations were used for prediction of magnetic field and kinetics of tissue spheroids assembly into 3D tissue constructs. First, we used polystyrene beads to simulate the assembly of tissue spheroids and to determine the optimal settings for magnetic levitation in presence of Gd ³⁺ . Second, we proved the ability of chondrospheres to assemble rapidly into 3D tissue construct in the permanent magnetic field in the presence of Gd ³⁺ . Thus, scaffold- and label-free magnetic levitation of tissue spheroids is a promising approach for rapid 3D biofabrication and attractive alternative to label-based magnetic force-driven tissue engineering.

Fatigue crack in rails and cyclic-loaded train parts is a contributory factor in multiple railroad accidents. We address the problem of crack detection and measurement at early stages, when total failure has not yet occurred. We propose to combine acoustic emission (AE) testing for prediction of crack growth with digital image correlation (DIC) for its accurate quantitative characterization. In this study, we imitated fatigue crack appearance and growth in samples of railway rail and two train parts by cyclic loading, and applied these two techniques for inspection. Experimental results clearly indicate the efficiency of AE in the early detection of fatigue cracks, and excellent DIC capabilities in terms of geometrical measurements. Combination of these techniques reveals a promising basis for real-time and non-destructive monitoring of rails and train parts.

Estimation of probability of defect detection (POD) is one of the most important problems in acoustic emission (AE) testing. It is caused by the influence of the material microstructure parameters on the diagnostic data, variability of noises, the ambiguous assessment of the materials emissivity, and other factors, which hamper modeling the AE data, as well as the a priori determination of the diagnostic parameters necessary for calculating POD. In this study, we propose an empirical approach based on the generalization of the experimental AE data acquired under mechanical testing of samples to a priori estimation of the AE signals emitted by the defect. We have studied the samples of common industrial steels 09G2S (similar to steel ANSI A 516-55) and 45 (similar to steel 1045) with fatigue cracks grown in laboratory conditions during cyclic testing. Empirical generalization of data using probabilistic models enables estimating the conditional probability of record emissivity and amplitudes of AE signals. This approach allows to eliminate the existing methodological gap and to build a comprehensive method for assessing the probability of fatigue cracks detection by the AE testing.

AE control results for cyclic tests of metal samples with a notch are presented. The main stages of the fatigue crack development and standard AE parameters are matched. A criterial plane which...

The properties of austenitic–martensitic VNS9-Sh (23Kh15N5AM3-Sh) sheet TRIP steel during static and cyclic loading are studied. The specific features of the mechanical behavior of the steel during...