New support roller profile design for railway wheel re-profiling process by under-floor lathes with a single cutting tool

The wheel re-profiling is an important part of railway wheelset maintenance. Researchers and railway operators have been very concerned about how to minimize the loss of time during wheel re-profiling without decreasing safety. Avoiding wheelset disassembly means considerable time savings, while reducing wheel damage during operation. Underfloor wheel lathes are the most appropriate tool to achieve this double objective, and therefore the most used nowadays. Multi-cut tool lathes have the disadvantage of being extremely expensive. On the other hand, with single tool lathes, re-profiling is not smooth or safe enough when current convex profile support rollers are used. It is well known by the companies that during reprofiling the wheel suffers impacts/damaged. In this article, a methodology to optimize the profile of the support rollers used in underfloor single tool lathes for railway wheel re-profiling is proposed. This novel profile design will minimize damage and increase the safety of such lathes, since it proposes a greater smoothness in the process. Simulations of re-profiling process have been carried out by the finite element method showing that the designed roller profile reduces drastically the impact/damage during the operation. The impact generated between the re-profiling wheel and the rollers is avoided. Profile-optimized support rollers have been used in a real underfloor wheel lathe, showing good results.

Non-Destructive Detection of Damaged Strawberries after Impact Based on Analyzing Volatile Organic Compounds

Strawberries are susceptible to mechanical damage. The detection of damaged strawberries by their volatile organic compounds (VOCs) can avoid the deficiencies of manual observation and spectral imaging technologies that cannot detect packaged fruits. In the present study, the detection of strawberries with impact damage is investigated using electronic nose (e-nose) technology. The results show that the e-nose technology can be used to detect strawberries that have suffered impact damage. The best model for detecting the extent of impact damage had a residual predictive deviation (RPD) value of 2.730, and the correct rate of the best model for identifying the damaged strawberries was 97.5%. However, the accuracy of the prediction of the occurrence time of impact was poor, and the RPD value of the best model was only 1.969. In addition, the gas chromatography–mass spectrophotometry analysis further shows that the VOCs of the strawberries changed after suffering impact damage, which was the reason why the e-nose technology could detect the damaged fruit. The above results show that the mechanical force of impact caused changes in the VOCs of strawberries and that it is possible to detect strawberries that have suffered impact damage using e-nose technology.

Ударное разрушение кристаллического, аморфизованного имплантацией Ar-=SUP=-+-=/SUP=- и аморфного диоксида кремния

The mechanical fracture of silicon dioxide initiates the mechanoluminescence (ML) lighting due to multiple breakage of interatomic bonds with producing non-bridged oxygen groups of [Si–O–]. The detected ML signals consisted of series of pulses, the energy of which is proportional to the number of photons irradiated from the broken bonds. The comparative analysis of the energy distributions in ML series induced by the impact damage of the surface of crystalline and vitreous SiO2 before and after the Ar+-ion implantation was conducted. The interplay between random and correlated accumulation of broken bonds under the impact loading was found and discussed.

Effect of Fibre Orientation on Impact Damage Resistance of S2/FM94 Glass Fibre Composites for Aerospace Applications: An Experimental Evaluation and Numerical Validation

This study aims to investigate the influence of fibre orientation and varied incident energy levels on the impact-induced damage of S2/FM94, a kind of aerospace glass fibre epoxy/composite regularly used in aircraft components and often subjected to low-velocity impact loadings. Effects of varying parameters on the impact resistance behaviour and damage modes are evaluated experimentally and numerically. Laminates fabricated with four different fibre orientations 0/90/+45/−458s, 0/90/90/08s, +45/−4516s, and 032 were impacted using three energy levels. Experimental results showed that plates with unidirectional fibre orientation failed due to shear stresses, while no penetration occurred for the 0/90/90/08s and +45/−4516s plates due to the energy transfer back to the plate at the point of maximum displacement. The impact energy and resulting damage were modelled using Abaqus/Explicit. The Finite Element (FE) results could accurately predict the maximum impact load on the plates with an accuracy of 0.52% to 13%. The FE model was also able to predict the onset of damage initiation, evolution, and the subsequent reduction of the strength of the impacted laminates. The results obtained on the relationship of fibre geometry and varying incident impact energy on the impact damage modes can provide design guidance of S2/FM94 glass composites for aerospace applications where impact toughness is critical.

Structural Health Monitoring in Composite Structures: A Comprehensive Review

This study presents a comprehensive review of the history of research and development of different damage-detection methods in the realm of composite structures. Different fields of engineering, such as mechanical, architectural, civil, and aerospace engineering, benefit excellent mechanical properties of composite materials. Due to their heterogeneous nature, composite materials can suffer from several complex nonlinear damage modes, including impact damage, delamination, matrix crack, fiber breakage, and voids. Therefore, early damage detection of composite structures can help avoid catastrophic events and tragic consequences, such as airplane crashes, further demanding the development of robust structural health monitoring (SHM) algorithms. This study first reviews different non-destructive damage testing techniques, then investigates vibration-based damage-detection methods along with their respective pros and cons, and concludes with a thorough discussion of a nonlinear hybrid method termed the Vibro-Acoustic Modulation technique. Advanced signal processing, machine learning, and deep learning have been widely employed for solving damage-detection problems of composite structures. Therefore, all of these methods have been fully studied. Considering the wide use of a new generation of smart composites in different applications, a section is dedicated to these materials. At the end of this paper, some final remarks and suggestions for future work are presented.

Multiple Impact Damage in GLARE Laminates: Experiments and Simulations

Experiments and finite element simulations for multiple impact were performed on GLARE 5-2/1 and aluminum 2024-T3. Experiments were conducted on aluminum 2024-T3 and GLARE 5-2/1 at diverse impact energies to produce BVID (barely visible impact damage) and CVID (clearly visible impact damage). The finite element model was developed for multiple impact analysis using ABAQUS software and was confirmed by comparing the finite element analysis outcomes with experimental results. The two- and three-dimensional failure criteria model was applied to predict multiple impact behavior such as load-time history, maximum deflection-impact energy history, and damage progression. In addition, a user subroutine VUMAT was created to represent a three-dimensional progressive failure and was linked with ABAQUS. FEM results showed good agreement with experimental data.