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Landing gear are exposed to cyclic loads from the ground manoeuvres that aircraft perform in-service. Variability is observed in the loading magnitude associated with ground manoeuvres, along with the per-flight variability in ground manoeuvre occurrence and sequencing. Whilst loading magnitude variability has been widely characterised, significant assumptions are required regarding manoeuvre occurrence and sequencing when constructing landing gear load spectra for fatigue design. These assumptions are required due to the limited availability of data concerning ground manoeuvre occurrence and sequencing relating to aircraft in-service and require validation to facilitate the design of more efficient components. 'Big-Data' approaches, employing Automatic Dependent Surveillance-Broadcast (ADS-B) transponder data, enable aircraft ground tracks to be identified. This paper presents a methodology to characterise the variability in ground manoeuvre occurrence and sequencing using ADS-B data sourced from Flightradar24® for a wide-body aircraft fleet. Using statistics generated for the fleet, it was identified that significant variability exists in the occurrence and sequencing of turning and braking manoeuvres. The statistics also validate existing assumptions, including that the proportional share of left and right turning manoeuvres is equal. Finally, this paper discusses the utility of ADS-B datasets for constructing landing gear load spectra and monitoring of landing gear in-service. [ABSTRACT FROM AUTHOR]

Railway bridges require special attention to provide safe and economical service. To assess the reliability of a structure, all critical parameters need to be specified. Load and resistance are random in nature; hence, the probabilistic approach is the best method for accurate evaluation of the performance of a bridge. In this study, identification of critical parameters was conducted on a typical through-plate girder, riveted, open deck railway bridge. This type of structure is a weakest link system. In such a system, the failure of one component can lead to failure of the entire structural system. This research involved identification of the basic load and resistance parameters and the development of analytical procedures for modelling the structural behaviour. The finite element method (FEM) was used to investigate the structural performance characteristics of the evaluated bridge. A three-dimensional structural model was developed to determine stress distribution in the members and connections. Based on the results of FEM analysis, the reliability indices were calculated for critical components. [ABSTRACT FROM PUBLISHER]

For predicting the fatigue life of the frame and its welds in SF33900 mining dump truck with inwheel motors, a FE model for the frame is established with shell elements. The stress distribution under dynamic loading is obtained by applying software Hypermesh, which is compared with that of the test, validating the correctness of the model, and based on this a multi-body dynamics model is built. According to the actual road condition for dump truck driving with C-grade road spectra as input, the time history of frame dynamic load is gained. Meanwhile, based on the S-N curve of frame material, the fatigue life of frame is got by using Mse, Fatigue, and further, a reliable fatigue life of welds is obtained by using SEAM_weld method, providing reference base for the reliability design and structure optimization of the frame. [ABSTRACT FROM AUTHOR]

In the system of product quality assessments, reliability assessment belongs to the most important ones. One of the reliability criteria is a structural life. In dynamically loaded structures, where it comes to accumulation of fatigue damage, life tests are an important part of new products development. It is inevitable to set effective procedures to verify the machine design even from the point of view of life evaluation. For this purpose, it is necessary to know a load of every structural element in its every kinematic point, as well as service loads in particular working regimes of a building machine. One of the ways to better characterize service load is the determination of load spectrum, i.e. to express cumulative counts and sizes of particular loads. For speeding up a product development stages, it is necessary to develop methods of their testing in such a way that they shorten the time of products testing as much as possible. [ABSTRACT FROM AUTHOR]

• Fabrications of SERS active substrate by Langmuir-Blodgett technique. • SERS efficacy of the substrate has been tested with the probe 4-MPy molecule. • Substrate can act as diagnostic platform to detect normal and cancerous cell lines. • Experimental results are supported by Multivariate data analyses. This paper reports fabrication of efficient and reproducible Surface Enhance Raman Scattering active substrate through integration of self-assembly and Langmuir-Blodgett technique for the detection of normal and cancerous cell lines associated with prostate and breast cancers. Morphology of the substrate has been visualized using FESEM and AFM images. In vitro cytotoxicity test was performed to check the biocompatibility of the substrate. SERS sensing ability of the substrate has been tested with the probe 4-Mercaptopyridine molecule. The as-prepared substrate has been employed for the first time to detect normal and cancerous cell lines linked with prostate and breast cancers. Multivariate statistical approaches like principal component analysis (PCA) and loading spectra were further explored for segregation and identification of the cancer cells from their normal counterparts. Intriguingly, the peak positions of the loading spectra nearly correspond to the difference SERS spectra between the normal and cancerous cell lines of prostate and breast cancers. To our knowledge, such one to one correspondence between the peak positions of loading and differences in the SERS spectra has been noticed for the first time and can act as a diagnostic platform to identify the biomarkers for cancerous cell lines in the molecular scale. [ABSTRACT FROM AUTHOR]