Mixed mode fatigue crack growth predictions

This work is aimed at developing a predictive capability for the quantitative assessment of crack growth under fatigue loadings. The crack growth rate relation, $\text{Δa}\text{ΔN}$, may involve all three stress intensity factors k₁-k₃ such that the direction of crack growth may not be known in advance and must be predicted from a preassumed criterion. In principle, both the stress amplitude and the mean stress level should be included in the original expression for $\text{Δa}\text{ΔN}$.The strain energy density factor range, ΔS, is found to be a convenient parameter for predicting fatigue crack growth and can be applied expediently to examine the combined influence of crack geometry, complex loadings and material properties. Assumed is the accumulation of energy, $\text{ΔW}\text{ΔV}$, stored in an element ahead of the crack which triggers subcritical crack growth upon reaching a number of loading cycle, say ΔN. The proposed $\text{δa}\text{ΔN}$ relationship includes both the stress amplitude and mean stress effects.     

Phase transformations in highly disperse powders during their rapid heating and cooling

Phase transformations in particles of ultrafine powders of graphite, hexagonal boron nitride, and quartz during rapid heating and cooling by passage through a laser beam were investigated. A continuous infrared laser with a wavelength of 10.6 μm was used as a heat source through which the powders were recycled several times. Methods of concentrating the product phases are described. Particles of diamond, carbides, cubic boron nitride, koesite and stishovite were obtained in the mixed products.     

Bounds on the number of samples needed for neural learning.

The relationship between the number of hidden nodes in a neural network, the complexity of a multiclass discrimination problem, and the number of samples needed for effect learning are discussed. Bounds for the number of samples needed for effect learning are given. It is shown that Omega(min (d,n) M) boundary samples are required for successful classification of M clusters of samples using a two-hidden-layer neural network with d-dimensional inputs and n nodes in the first hidden layer.     

Intelligent identification and control for autonomous guided vehicles using adaptive fuzzy-based algorithms

Fuzzy logic was first suggested as the mechanism by which humans drive cars. This paper addresses the use of fuzzy logic and algorithms towards the intelligent autonomous motion control of land vehicles. To cope with vehicle complexities, internal parametric changes, and with unpredictable environmental effects, the controllers that are presented, whilst heuristic in nature, are self-organizing or self-learning in that they generate automatically by observation an experiential rule base that models the vehicle, and via an appropriate performance index an optimal control rule base that is robust to large parametric changes. The methodology presented is applicable to any complex process which is too difficult to model or control using conventional methods, or which has relied on the experience of a human operator. An overview of fuzzy logic and static fuzzy logic control (akin to expert systems) is provided, together with illustrative examples.     

Comparing VVR-M reactor fuel assembly heat technological capabilities

Translated from Atomnaya Énergiya, Vol. 67, No. 2, pp. 97–100, August, 1989.     

Theoretical analysis of control properties for the brushless doubly fed reluctance machine

The brushless doubly fed induction machine (BDFIM) has been extensively researched for approximately 30 years, but a related machine [the brushless doubly fed reluctance machine (BDFRM)], has not. This was mainly due to the fact that reluctance rotor designs were not capable of generating saliency ratios large enough to make the BDFRM competitive with other machines. However, recent developments in reluctance rotors, spurred on by research into synchronous reluctance machines, has resulted in high saliency ratio rotors that are economic to build. This, together with the promise of higher efficiency and simpler control compared to the BDFIM, means that further investigation of the BDFRM is warranted. A relatively limited amount of work to date has been published on the BDFRM. This paper attempts to fill this void by presenting a theoretical analysis of some of the important control properties of the ideal BDFRM.     

Macroscopic and crystallographic density of solid-state extruded polyethylene

Summary The influence of draw ratio on macroscopic and crystallographic density of polyethylene with different initial morphologies, has been investigated by solid-state extrusion. An initial drop followed by an increase in macroscopic density as a function of draw ratio has been observed. Since precision X-ray measurements of unit cell parameters showed no variation of crystallographic density, it was concluded that plastic deformation of polyethylene upon drawing proceeds with a decrease of the degree of crystallinity. This was confirmed by differential scanning calorimetry.