Corrosion Books: Werkstoffkunde. By: H.‐J. Bargel, H.Hilbrans, K.‐H. Hübner, O. Krüger, G. Schulze

Fischer, Josef

doi:10.1002/maco.200690087

Cited by 2 publications

(2 citation statements)

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“…To prevent fatigue failure, it is important to understand fatigue failure mechanisms. Many researchers have provided insightful information regarding fatigue in NCI from the experiments like Murakami [2], Fischer et al [3], Cavallini et al [4], Greno et al [5], Asi [6], Xue et al [7], Komotori et al [8] to name a few. The small defects, matrix, and microshrinkages have major influence on the fatigue strength of NCI [9].…”

Section: Introductionmentioning

confidence: 99%

Characterising Fatigue Behaviour of Nodular Cast Iron Using Micromechanical Simulations

2019

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Elastic-plastic porous materials experience an increase in the mean void volume fraction when they are subjected to cyclic loading. This behavior is known both from the experiments and simulations in the literature. The authors have first time used this mechanism for the evaluation of the fatigue life in nodular cast iron. In this contribution, the stress-life approach is presented for the characterization of fatigue failure. For this purpose, micromechanical finiteelement simulations are carried out using the axisymmetric cell model. The cell model having isotropic/non-linear kinematic hardening behavior is subjected to fully reversed cyclic stress controlled loading. The finite element simulations are carried out cycle by cycle until the final failure of the cell model. The numbers of cycles to failure are extracted from the simulations. The stress-life curves are shown for spherical and elliptical graphite particle cell models. The results of the micromechanical simulations are in qualitative agreement with the typical experimental stress-life curves. *

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Section: Introductionmentioning

confidence: 99%

Characterising Fatigue Behaviour of Nodular Cast Iron Using Micromechanical Simulations

2019

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“…The study confirms that HTTP and P2P are currently the most dominant applications on the Internet. They have progressively replaced other protocols and applications, such as File Transfer Protocol (FTP) and e-mail, that carried a large part of the Internet traffic at the beginning of the nineties[46].Ipoque has released three of the most extensive Internet traffic studies existing so far, which cover years 2006[122], 2007[120] and 2008-2009 [121]. While the 2006 and 2007 editions of the study highlighted P2P as the most dominant application on the Internet in terms of traffic volume, the 2008-2009 study reported a clear growth of HTTP traffic compared to P2P, which was mostly attributed to file sharing over HTTP.…”

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confidence: 99%

Efficient algorithms for passive network measurement

Sanjuàs Cuxart

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Network monitoring has become a necessity to aid in the management and operation of large networks. Passive network monitoring consists of extracting metrics (or any information of interest) by analyzing the traffic that traverses one or more network links. Extracting information from a high-speed network link is challenging, given the great data volumes and short packet inter-arrival times. These difficulties can be alleviated by using extremely efficient algorithms or by sampling the incoming traffic. This work improves the state of the art in both these approaches. For one-way packet delay measurement, we propose a series of improvements over a recently appeared technique called Lossy Difference Aggregator. A main limitation of this technique is that it does not provide per-flow measurements. We propose a data structure called Lossy Difference Sketch that is capable of providing such per-flow delay measurements, and, unlike recent related works, does not rely on any model of packet delays. In the problem of collecting measurements under the sliding window model, we focus on the estimation of the number of active flows and in traffic filtering. Using a common approach, we propose one algorithm for each problem that obtains great accuracy with significant resource savings. In the traffic sampling area, the selection of the sampling rate is a crucial aspect. The most sensible approach involves dynamically adjusting sampling rates according to network traffic conditions, which is known as adaptive sampling. We propose an algorithm called Cuckoo Sampling that can operate with a fixed memory budget and perform adaptive flow-wise packet sampling. It is based on a very simple data structure and is computationally extremely lightweight. The techniques presented in this work are thoroughly evaluated through a combination of theoretical and experimental analysis.

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Corrosion Books: Werkstoffkunde. By: H.‐J. Bargel, H.Hilbrans, K.‐H. Hübner, O. Krüger, G. Schulze

Cited by 2 publications

References 0 publications

Characterising Fatigue Behaviour of Nodular Cast Iron Using Micromechanical Simulations

Characterising Fatigue Behaviour of Nodular Cast Iron Using Micromechanical Simulations

Efficient algorithms for passive network measurement

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