Design of brushless doubly-fed machines based: On magnetic circuit modeling

This paper proposes a magnetic circuit model (MCM) for the design of a brushless doubly-fed machine (BDFM). The BDFM possesses advantages in terms of high reliability and reduced gearbox stages, and it requires a fractionally-rated power converter. This makes it suitable for utilization in offshore wind turbines. It is difficult for conventional design methods to calculate the flux in the stator because the two sets of stator windings, which have different pole number, form a complex flux pattern which is not easily determined using common analytical approaches. However, it is advantageous to predict the flux density in the teeth and air-gap at the initial design stage for sizing purposes without recourse finite element analysis. Therefore a magnetic circuit model is developed in this paper to calculate the flux density. A BDFM is used as a case study with FEA validation. © 1965-2012 IEEE.

The effect of inclined soil layers on surface vibration from underground railways using a semi-analytical approach

Ground vibration due to underground railways is a significant source of disturbance for people living or working near the subways. The numerical models used to predict vibration levels have inherent uncertainty which must be understood to give confidence in the predictions. A semi-analytical approach is developed herein to investigate the effect of soil layering on the surface vibration of a halfspace where both soil properties and layer inclination angles are varied. The study suggests that both material properties and inclination angle of the layers have significant effect ( ± 10dB) on the surface vibration response. © 2009 IOP Publishing Ltd.

Quantitative approaches for characterising fibrillar protein nanostructures

Polypeptide sequences have an inherent tendency to self-assemble into filamentous nanostructures commonly known as amyloid fibrils. Such self-assembly is used in nature to generate a variety of functional materials ranging from protective coatings in bacteria to catalytic scaffolds in mammals. The aberrant self-assembly of misfolded peptides and proteins is also, however, implicated in a range of disease states including neurodegenerative conditions such as Alzheimer's and Parkinson's diseases. It is increasingly evident that the intrinsic material properties of these structures are crucial for understanding the thermodynamics and kinetics of the pathological deposition of proteins, particularly as the mechanical fragmentation of aggregates enhances the rate of protein deposition by exposing new fibril ends which can promote further growth. We discuss here recent advances in physical techniques that are able to characterise the hierarchical self-assembly of misfolded protein molecnles and define their properties. © 2010 Materials Research Society.

A general design method for electric machines using magnetic circuit model considering the flux saturation problem

This paper proposes an analytical approach that is generalized for the design of various types of electric machines based on a physical magnetic circuit model. Conventional approaches have been used to predict the behavior of electric machines but have limitations in accurate flux saturation analysis and hence machine dimensioning at the initial design stage. In particular, magnetic saturation is generally ignored or compensated by correction factors in simplified models since it is difficult to determine the flux in each stator tooth for machines with any slot-pole combinations. In this paper, the flux produced by stator winding currents can be calculated accurately and rapidly for each stator tooth using the developed model, taking saturation into account. This aids machine dimensioning without the need for a computationally expensive finite element analysis (FEA). A 48-slot machine operated in induction and doubly-fed modes is used to demonstrate the proposed model. FEA is employed for verification.

A constitutive description of the inelastic response of ceramics

The objective of the article is to present a unified model for the dynamic mechanical response of ceramics under compressive stress states. The model incorporates three principal deformation mechanisms: (i) lattice plasticity due to dislocation glide or twinning; (ii) microcrack extension; and (iii) granular flow of densely packed comminuted particles. In addition to analytical descriptions of each mechanism, prescriptions are provided for their implementation into a finite element code as well as schemes for mechanism transitions. The utility of the code in addressing issues pertaining to deep penetration is demonstrated through a series of calculations of dynamic cavity expansion in an infinite medium. The results reveal two limiting behavioral regimes, dictated largely by the ratio of the cavity pressure p to the material yield strength σY. At low values of p/σY, cavity expansion occurs by lattice plasticity and hence its rate diminishes with increasing σY. In contrast, at high values, expansion occurs by microcracking followed by granular plasticity and is therefore independent of σY. In the intermediate regime, the cavity expansion rate is governed by the interplay between microcracking and lattice plasticity. That is, when lattice plasticity is activated ahead of the expanding cavity, the stress triaxiality decreases (toward more negative values) which, in turn, reduces the propensity for microcracking and the rate of granular flow. The implications for penetration resistance to high-velocity projectiles are discussed. Finally, the constitutive model is used to simulate the quasi-static and dynamic indentation response of a typical engineering ceramic (alumina) and the results compared to experimental measurements. Some of the pertinent observations are shown to be captured by the present model whereas others require alternative approaches (such as those based on fracture mechanics) for complete characterization. © 2011 The American Ceramic Society.

Monte Carlo approaches to nonlinear optimal control

This paper explores the use of Monte Carlo techniques in deterministic nonlinear optimal control. Inter-dimensional population Markov Chain Monte Carlo (MCMC) techniques are proposed to solve the nonlinear optimal control problem. The linear quadratic and Acrobot problems are studied to demonstrate the successful application of the relevant techniques.