Quantification of microscale factors for fatigue failure in NiTi shape memory alloys

International audienceFatigue behavior is intrinsically linked to microstructural alterations induced by cyclic loading. However, the quantification of microstructural defects associated with fatigue damage of NiTi shape memory alloys (SMAs) is lacking, which hinders the development of a physically based fatigue criterion. To this end, a multi-scale experimental analysis was conducted on cyclically deformed NiTi SMAs, which evidenced a strong correlation between microstructural inhomogeneity and localized deformation behavior. The microstructural change associated with fatigue was quantified in terms of stored strain–energy, with the highest values observed in the regions where fatigue cracks initiate. Consequently, stored energy is deemed as an effective fatigue indicator, offering valuable insights for future work in the design and optimization of SMAs’ structures against fatigue

On the optimized design of interfacial configurations in a highly thermal conductive graphite flakes/aluminum composite

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Multipath Ghost Suppression Based on Generative Adversarial Nets in Through-Wall Radar Imaging

In this paper, we propose an approach that uses generative adversarial nets (GAN) to eliminate multipath ghosts with respect to through-wall radar imaging (TWRI). The applied GAN is composed of two adversarial networks, namely generator G and discriminator D. Generator G learns the spatial characteristics of an input radar image to construct a mapping from an input to output image with suppressed ghosts. Discriminator D evaluates the difference (namely, the residual multipath ghosts) between the output image and the ground-truth image without multipath ghosts. On the one hand, by training G, the image difference is gradually diminished. In other words, multipath ghosts are increasingly suppressed in the output image of G. On the other hand, D is trained to improve in evaluating the diminishing difference accompanied with multipath ghosts as much as possible. These two networks, G and D, fight with each other until G eliminates the multipath ghosts. The simulation results demonstrate that GAN can effectively eliminate multipath ghosts in TWRI. A comparison of different methods demonstrates the superiority of the proposed method, such as the exemption of prior wall information, no target images with degradation, and robustness for different scenes

Propensity Score Matching Analysis of VATS Lobectomy and Sublobar Resection for Stage I Lung Adenocarcinoma

Background and objective National Comprehensive Cancer Network (NCCN) guidelines recommend video-assisted thoracoscopic surgery (VATS) anatomical lobectomy as the first choice for the treatment of resectable lung cancer. However, sublobar resection offers significantly better functional preservation compared with lobectomy for stage I lung cancer. At present, the inferiority of sublobar resection to lobectomy is still uncertain. Herein, we compared the prognoses of these two types of surgical treatment for stage I lung adenocarcinoma. Methods Retrospective research was conducted on 258 patients with stage I lung adenocarcinomas who underwent VATS lobectomy and sublobar resection at the First Affiliated Hospital of Guangzhou Medical University between January 2009 and December 2011. VATS lobectomy was performed on 222 patients, and VATS sublobe resection was performed on 36 patients. Propensity score matching analyses were conducted on the two groups. Results A total of 70 patients were matched in the two groups. No significant difference was observed between the lobectomy and sublobar resection groups after matching (P=0.137). The disease-free survival (DFS) of the two groups were 49.3 and 42.7 months, and their overall survival (OS) were 50.3 and 49.0 months (P=0.122). Further, stratified analysis showed no significant differences in DFS and OS between the two groups with stage Ia lung adenocarcinoma. Nevertheless, the DFS and OS of the two groups significantly differed in matched patients with stage Ib lung adenocarcinomas. Conclusion Sublobar resection could achieve a similar prognosis to VATS lobectomy for stage Ia lung adenocarcinoma. Lobectomy should still be the first choice for the treatment of stage Ib lung adenocarcinoma

Quantitative study of dislocation densities of friction stir processed in-situ particles reinforced TiB2/AA6063 composites by X-ray line analysis

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HETU: a new high-resolution stress and texture neutron diffractometer at China Mianyang Research Reactor

International audienceHETU is a new high-resolution stress and texture neutron diffractometer installed at the C1 neutron guide at China Mianyang Research Reactor. The diffractometer is designed for precise residual stress and texture analysis of engineering components, as well as in situ investigations under various sample environments for engineering materials. The wavelength range of monochromatic incident neutrons is 1.634–5.800 Å, provided either by a double-focusing perfect single-crystal silicon monochromator in high instrument resolution mode or by a highly oriented pyrolytic graphite monochromator in high neutron flux mode. The intrinsic peak widths of HETU have been measured using a standard silicon powder sample, and residual stress measurements of an aluminium alloy shrink-fit ring and plug have been carried out. These results demonstrate that HETU is a reliable and appropriately designed diffractometer for promoting materials investigation

Processing Laue Microdiffraction Raster Scanning Patterns with Machine Learning Algorithms: A Case Study with a Fatigued Polycrystalline Sample

The massive amount of diffraction images collected in a raster scan of Laue microdiffraction calls for a fast treatment with little if any human intervention. The conventional method that has to index diffraction patterns one-by-one is laborious and can hardly give real-time feedback. In this work, a data mining protocol based on unsupervised machine learning algorithm was proposed to have a fast segmentation of the scanning grid from the diffraction patterns without indexation. The sole parameter that had to be set was the so-called “distance threshold” that determined the number of segments. A statistics-oriented criterion was proposed to set the “distance threshold”. The protocol was applied to the scanning images of a fatigued polycrystalline sample and identified several regions that deserved further study with, for instance, differential aperture X-ray microscopy. The proposed data mining protocol is promising to help economize the limited beamtime

Investigation of the Effect of Graphene Oxide on the Properties and Microstructure of Clay-Cement Composite Grouting Materials

Reductions in bleeding rates and bulk shrinkage of grouting repair materials comprise the key to solving the leakage of earth–rock dams. In this paper, an anti-seepage grouting material for earth–rock dam was developed by introducing mineral admixtures and graphene oxide (GO) nano sheets into low-cost clay–cement grouting materials and by adding polycarboxylate superplasticizers (PCs) to improve slurry viscosity. The experimental results show that the shear stress and viscosity of the slurry increase with the increase in GO concentration, and the slurry has a certain thixotropy. GO can provide a platform to promote the formation of hydration products and fill the pores of clay particles due to its high specific surface area and low volume; in this paper, the microstructure of clay–cement–graphene oxide (CCGO) grouting materials were improved. Therefore, the bleeding rate, bulk shrinkage rate, setting time and unconfined compressive strength (UCS) of the sample were macroscopically improved. In particular, the bleeding rate and bulk shrinkage rate were shown to be 0% when the content of GO reached 1.08 g/kg. Thus, the grouting anti-seepage and reinforcement performance of CCGO grouting materials were improved

Experimental and modelling assessment of ductility in a precipitation hardening AlMgScZr alloy

Precipitation hardening is the most effective strategy to enhance the mechanical properties of metals. Dislocation mechanisms to control strengthening during precipitation have been demonstrated extensively. However, owing to the complexity of different precipitates in alloys, variations in ductility caused by precipitation are complex and have not been clarified so far. In this study, the effects of precipitation on ductility in precipitation hardening aluminium alloys are investigated based on a modified dislocation-based approach and experimental characterisation. The AlMgScZr alloy with spherical Al3(Sc, Zr) precipitates is used as a model alloy system to understand the effects of precipitation on ductility. Via heat treatment, shearable and nonshearable Al3(Sc, Zr) precipitates are introduced in the AlMg matrix. The results show that the ductility of AlMgScZr alloy decreases when shearable precipitates occur, while it increases with shearable precipitates being replaced by nonshearable precipitates. The variation in ductility of AlMgScZr alloy is mainly controlled by the dynamic recovery rate of the dislocations. Finally, by analysing the different precipitate–dislocation interactions and evaluating the dislocation density evolution during deformation, the dislocation mechanisms of ductility during precipitation for AlMgScZr alloy are demonstrated. This study reveals the dislocation mechanism for controlling ductility during precipitation for AlMgScZr alloy which can provide a theoretical foundation for the design of high-performance structural materials