Nonlinear geometric and material computational technique : higher-order element with refined plastic hinge approach

This paper addresses of the advanced computational technique of steel structures for both simulation capacities simultaneously; specifically, they are the higher-order element formulation with element load effect (geometric nonlinearities) as well as the refined plastic hinge method (material nonlinearities). This advanced computational technique can capture the real behaviour of a whole second-order inelastic structure, which in turn ensures the structural safety and adequacy of the structure. Therefore, the emphasis of this paper is to advocate that the advanced computational technique can replace the traditional empirical design approach. In the meantime, the practitioner should be educated how to make use of the advanced computational technique on the second-order inelastic design of a structure, as this approach is the future structural engineering design. It means the future engineer should understand the computational technique clearly; realize the behaviour of a structure with respect to the numerical analysis thoroughly; justify the numerical result correctly; especially the fool-proof ultimate finite element is yet to come, of which is competent in modelling behaviour, user-friendly in numerical modelling and versatile for all structural forms and various materials. Hence the high-quality engineer is required, who can confidently manipulate the advanced computational technique for the design of a complex structure but not vice versa.

Tuning second order cyclostationarity parameters for the diagnostics of rolling element bearings

Failures on rolling element bearings usually originate from cracks that are detectable even in their early stage of propogation by properly analyzing vibration signals measured in the proximity of the bearing. Due to micro-slipping in the roller-races contact, damage-induced vibration signals belong to the family of quasi-periodic signals with a strong second order cyclostationary component. Cyclic coherence and its integrated form are widely considered as the most suitable tools for bearing fault diagnostics and their theoretical bases have been already consolidated. This paper presents how to correctly set the parameters of the cyclostationary analysis tool to be implemented in an automatable algorithm. In the first part of the paper some general guidelines are provided for the specific application. These considerations are further verified, applying cyclostationary tools to data collected in an experimental campaign on a specific test-rig.

Dispersion of zero valent iron nanoparticles onto bentonites and the decolourization of orange II

Nano Zero valent iron (Fe0) were reported as an effective material for azo dye removal, however, similar to other nano-materials, ultra-fine powder has a strong tendency to agglomerate into larger particles, resulting in an adverse effect on both effective surface area and catalyst performance. Here we report nano sized Fe0 particles dispersed onto the surface of natural bentonites. X-ray diffraction was used to study the sample phases. Scanning electron microscopy and transmission electron microscopy were applied to study the morphology and morphological changes. Spherical individual Fe0 particles were observed after dispersion onto bentonites, and these samples were used for orange II (OII) decolourization with wide working pH range. Higher reactivity is attributed to good dispersion of Fe0 particles on clay minerals’ surface. This study is significant for providing novel modified clay based catalyst materials for the decolourization of azo dye contaminants from wastewater.

Modelling attitudes to climate change : an order effect and a test between alternatives

Quantum-like models can be fruitfully used to model attitude change in a social context. Next steps require data, and higher dimensional models. Here, we discuss an exploratory study that demonstrates an order effect when three question sets about Climate Beliefs, Political Affiliation and Attitudes Towards Science are presented in different orders within a larger study of n=533 subjects. A quantum-like model seems possible, and we propose a new experiment which could be used to test between three possible models for this scenario.

Higher order spectra based support vector machine for arrhythmia classification

Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. HRV analysis is an important tool to observe the heart’s ability to respond to normal regulatory impulses that affect its rhythm. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. A computer-based arrhythmia detection system of cardiac states is very useful in diagnostics and disease management. In this work, we studied the identification of the HRV signals using features derived from HOS. These features were fed to the support vector machine (SVM) for classification. Our proposed system can classify the normal and other four classes of arrhythmia with an average accuracy of more than 85%.