Author
Athanasios Chasalevris
Other affiliations: BorgWarner Inc., National Technical University of Athens, General Electric ...read more
Bio: Athanasios Chasalevris is an academic researcher from Technische Universität Darmstadt. The author has contributed to research in topics: Bearing (mechanical) & Rotor (electric). The author has an hindex of 14, co-authored 36 publications receiving 611 citations. Previous affiliations of Athanasios Chasalevris include BorgWarner Inc. & National Technical University of Athens.
Papers
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TL;DR: In this paper, a local compliance matrix of two degrees of freedom, bending in the horizontal and the vertical planes is used to model the rotating transverse crack in the shaft and is calculated based on the available expressions of the stress intensity factors and the associated expressions for the strain energy release rates.
95 citations
TL;DR: In this article, a closed form expression for the definition of the lubricant pressure is presented using the method of separation of variables in an additive and a multiplicative form, a set of particular solutions of the Reynolds equation is added in the general solution of the homogenous Reynolds equation thus a closed-form expression is presented.
72 citations
TL;DR: In this paper, a model for the coupling effect of bending vibrations on the cracked shaft is first introduced and then used to identify the rotational angle of the crack, which is a significant factor and a prerequisite for the existence of coupling.
67 citations
TL;DR: In this paper, the journal bearing with variable geometry is presented in its final form with the detailed design procedure, and the implementation of the variable geometry bearing in an experimental rotor bearing system is outlined.
55 citations
TL;DR: In this paper, a very recent analysis of the exact analytical solution of the Reynolds equation for the lubrication of the plain journal bearing with finite length is used in order to evaluate the impedance forces of the fluid film and define them in closed form analytical expressions.
51 citations
Cited by
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TL;DR: In this paper, the strain energy release rate (SERR) theory is applied to a rotating crack and gives good results, and different methods of crack identification are presented as well as those for multi-crack identification.
170 citations
TL;DR: In this article, two new breathing functions were identified to represent the actual breathing effect on the cracked element stiffness matrix, which were then used in formulating the time-varying finite element stiffness matrices of a cracked element.
144 citations
TL;DR: In this paper, the authors summarize the different studies on double/multi-cracks and to note the influences, identification methods in vibration structures such as beams, rotors, pipes, etc.
142 citations
TL;DR: In this article, a review of the non-linear effects caused by a closing crack in the most common types of structural elements such as beams, shafts and plates is presented, with the aim being to assess the potential and future prospects of using nonlinear behaviour to detect damage.
137 citations
TL;DR: The comparison of the effectiveness of artificial neural network (ANN) and linear regression (LR) in the prediction of strain in tie section using experimental data from eight high-strength-self-compactconcrete (HSSCC) deep beams are presented here.
Abstract: The comparison of the effectiveness of artificial neural network (ANN) and linear regression (LR) in the prediction of strain in tie section using experimental data from eight high-strength-self-compactconcrete (HSSCC) deep beams are presented here. Prior to the aforementioned, a suitable ANN architecture was identified. The format of the network architecture was ten input parameters, two hidden layers, and one output. The feed forward back propagation neural network of eleven and ten neurons in first and second
TRAINLM training function was highly accurate and generated more precise tie strain diagrams compared to classical LR. The ANN\'s MSE values are 90 times smaller than the LR\'s. The correlation coefficient value from ANN is 0.9995 which is indicative of a high level of confidence.
133 citations