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Dimitrios Zarouchas - One of the best experts on this subject based on the ideXlab platform.
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Adapted anisomorphic model for fatigue life prediction of CFRP laminates under Constant Amplitude loading
International Journal of Fatigue, 2019Co-Authors: A.a.r. Broer, Dimitrios ZarouchasAbstract:Abstract A new Constant life diagram (CLD) model is proposed to predict the fatigue life of carbon fibre-reinforced epoxy laminates under Constant Amplitude (CA) loading. The CLD is asymmetric and non-linear, and it is built upon the anisomorphic CLD model. It consists of two sub-models; one sub-model is applicable to laminates with lay-ups characterised by a larger ultimate tensile strength (UTS) than absolute ultimate compressive strength (UCS): UTS ⩾ ∣UCS∣, while the second sub-model can be applied to those exhibiting the opposite tendency: ∣UCS∣ > UTS. Combined, the sub-models can predict the fatigue life of any carbon-epoxy laminate. The CLD can be constructed using only static strength data and fatigue life data related to one stress ratio (R), defined as either R = 0.1 or R = - 1.0 . An experimental campaign was conducted on a carbon-epoxy laminate with a lay-up of [90/0/90]2S to validate the first CLD sub-model. Additionally, a second case study from literature with a lay-up of [45/90/-45/0]2S was employed for validation. The second CLD sub-model was evaluated using two coupon case studies from literature with lay-ups of [±60]3S and [45]16. The predicted and experimentally obtained fatigue lives showed agreements for different R-ratios, and the observed prediction errors were in ranges similar to those of the original anisomorphic CLD model. Hence, the presented CLD model allows for fatigue life predictions in scales similar to experimental results while reducing the required experimental efforts with respect to the anisomorphic CLD model.
B Boashash - One of the best experts on this subject based on the ideXlab platform.
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comments on the cramer rao lower bounds for signals with Constant Amplitude and polynomial phase
IEEE Transactions on Signal Processing, 1998Co-Authors: Branko Ristic, B BoashashAbstract:For original paper see IEEE Trans. Signal Processing, vol.39, p.749-52 (March 1991). Different expressions for the Cramer-Rao lower bounds (CRLBs) of Constant Amplitude polynomial phase signals embedded in white Gaussian noise appear in the literature. The present paper revisits the derivation of the bounds reported by Peleg and Porat (1991) and indicates that the resulting expressions depend on the interval over which the signal is defined. The proper choice of the interval is the one that centers the signal around zero and results in the minimum lower bounds.
B B Verma - One of the best experts on this subject based on the ideXlab platform.
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prediction of fatigue crack growth and residual life using an exponential model part i Constant Amplitude loading
International Journal of Fatigue, 2009Co-Authors: J R Mohanty, B B VermaAbstract:In the present investigation an attempt has been made to introduce a life prediction methodology by adopting an ‘Exponential Model’ that can be used without integration of fatigue crack growth rate curve. The predicted results are compared with experimental crack growth data obtained for 7020-T7 and 2024-T3 aluminum alloy specimens under Constant Amplitude loading. It is observed that the results obtained from this model are in good agreement with experimental data and cover both stage-II and stage-III of fatigue crack growth curve.
A.a.r. Broer - One of the best experts on this subject based on the ideXlab platform.
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Adapted anisomorphic model for fatigue life prediction of CFRP laminates under Constant Amplitude loading
International Journal of Fatigue, 2019Co-Authors: A.a.r. Broer, Dimitrios ZarouchasAbstract:Abstract A new Constant life diagram (CLD) model is proposed to predict the fatigue life of carbon fibre-reinforced epoxy laminates under Constant Amplitude (CA) loading. The CLD is asymmetric and non-linear, and it is built upon the anisomorphic CLD model. It consists of two sub-models; one sub-model is applicable to laminates with lay-ups characterised by a larger ultimate tensile strength (UTS) than absolute ultimate compressive strength (UCS): UTS ⩾ ∣UCS∣, while the second sub-model can be applied to those exhibiting the opposite tendency: ∣UCS∣ > UTS. Combined, the sub-models can predict the fatigue life of any carbon-epoxy laminate. The CLD can be constructed using only static strength data and fatigue life data related to one stress ratio (R), defined as either R = 0.1 or R = - 1.0 . An experimental campaign was conducted on a carbon-epoxy laminate with a lay-up of [90/0/90]2S to validate the first CLD sub-model. Additionally, a second case study from literature with a lay-up of [45/90/-45/0]2S was employed for validation. The second CLD sub-model was evaluated using two coupon case studies from literature with lay-ups of [±60]3S and [45]16. The predicted and experimentally obtained fatigue lives showed agreements for different R-ratios, and the observed prediction errors were in ranges similar to those of the original anisomorphic CLD model. Hence, the presented CLD model allows for fatigue life predictions in scales similar to experimental results while reducing the required experimental efforts with respect to the anisomorphic CLD model.
M Benidir - One of the best experts on this subject based on the ideXlab platform.
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distinction between polynomial phase signals with Constant Amplitude and random Amplitude
International Conference on Acoustics Speech and Signal Processing, 1997Co-Authors: A Ouldali, M BenidirAbstract:In this paper we propose to distinguish between Constant Amplitude polynomial phase signals and the ones having random Amplitude. We study four possibilities for the modulating process. We show that the distinction of this kind of signals is not always possible when using the polynomial phase transform. In fact, in some applications, we show that we cannot estimate the phase of the signal with this transform. In order to solve this problem, we introduce a new transform which allows us to estimate this phase in these particular situations. The obtained transform is referred to as the modified polynomial phase transform.