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Browsing by Author "Sabri, Khier"

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    Analysis of a Directionally Solidified (DS) GTD-111 Turbine Blade Failure
    (Springer, 2020) Sabri, Khier; Gaceb, Mohamed; Si-Chaib, Mohamed Ouali
    The purpose of this paper is to clarify the impact of pitting corrosion and erosion on the directionally solidified (DS) GTD-111 turbine blade behavior. Moreover, the pitting corrosion and oxidation phenomena engendered inside cooling channels of the turbine blade are utterly highlighted. Other features such as the η (Ni3, Ti) platelets nucleation, needle σ-phase precipitation at the interface NiPtAl/(DS) GTD-111 substrate are exhibited as well. Finally, the different microstructural changes in (NiPtAl) coating strata against hot corrosion, oxidation and interaction with (DS) GTD-111 substrate are revealed and argued.
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    Assessment of the degraded high-pressure blades in a land-based gas turbine
    (Springer, 2021) Sabri, Khier; Si-Chaib, Mohamed Ouali; Gaceb, Mohamed
    The purpose of this paper is to evaluate high-pressure turbine blades after a long-term thermal exposure in a land-based gas turbine. Emphasis is placed upon structure and composition of the various layers evolving, on the one hand, due to hot oxidation/corrosion attacks and, on the other hand, because of interdiffusion phenomena between the substrates and their protective coatings. This work therefore discusses the influence of γ′-Ni3 (Al, Ti) precipitates coarsening, needle σ-phase nucleation, and M23C6-Carbides formation on the hardness properties of blades. In addition, this assessment attempts to evaluate the influence of γ′-Ni3 (Al, Ti) orientation changes and crystallites size growth on the intrinsic degradation of GTD-111 and IN738LC substrates
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    Effect of Rejuvenation Heat Treatment on the Degraded Turbine Blades
    (Springer, 2020) Sabri, Khier; Si-Chaib, Mohamed Ouali; Gaceb, Mohamed
    This paper presents a novel approach to estimate the extended lifetime of first-stage turbine blades made of directionally solidified GTD-111 nickel-based superalloys. These turbine blades were removed from land-based industrial gas turbines for power generation. In addition, this new way to evaluate the lifetime extension of degraded turbine blades after rejuvenation heat treatment is based on knowledge of newly introduced degradation index (Di) evolution. The rejuvenation heat treatment (RHT) process offers an extension of 36% in blades lifetime. Effect of the RHT on the aged γ-γ’ microstructures is presented and discussed.
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    Etude et prediction de la duree de vie residuelle moyenne des aubes de turbine a gaz
    (Universite de Boumerdes : Faculté des hydrocarbures et de la chimie, 2021) Sabri, Khier; Si-Chaib, Mohammed Ouali(Directeur de thèse)
    Le potentiel pour l fextension de la duree de vie des aubes de turbine a gaz haute pression base sur le traitement thermique de rajeunissement presente un interet economique notable aux operateurs. Les superalliages a base de nickel IN738LC (CC), GTD-111 (CC), et GTD-111 (DS) sont adaptes a une application de turbine a gaz terrestre dans un environnement hautement corrosif. La microstructure de ces superalliages est constituee d'une matrice austenitique ƒÁ riche en nickel renforcee par une fraction volumique elevee de precipites ordonnes ƒÁ'-Ni3Al. La coherence et la fraction volumique elevee des precipites ƒÁ' apportent a ces superalliages leur resistance exceptionnelle au fluage a haute temperature. La degradation des superalliages induite en service comprend principalement la croissance et la coalescence des precipites ƒÁ', la precipitation de la phase aciculaire ƒÐ et de lamelles ƒÅ (Ni3, Ti), et la formation de carbures M23C6 riches en Cr. Par consequent, le traitement de rajeunissement des aubes de turbine pourrait restaurer la taille et la forme initiales des precipites ƒÁ', et homogeneiser les microstructures ƒÁ + ƒÁ' en dissolvant les phases topologiquement compactes (TCP). Dans la presente etude, la structure et la composition des differentes strates d'aubes de turbine (IN738LC/NiPtAl, GTD-111/NiPtAl, et GTD-111/VPS) apres une exposition thermique a long terme dans des turbines a gaz terrestres ont ete evaluees. Une aube en GTD-111 (DS) erodee/corrodee dans la region du bord de fuite a ete aussi evaluee. De plus, un traitement thermique de rajeunissement (RHT) specifique a ete applique pour restaurer la microstructure d'origine du GTD-111, et donc prolonger la duree de vie des aubes. Les traitements thermiques de mise en solution et de maintien ont permis d'homogeneiser avec succes la microstructure du (DS) GTD-111 et de precipiter les particules ƒÁ' de taille, de morphologie et de distribution appropriees. En vue d'evaluer la taille moyenne de ƒÁ', plusieurs micrographies ont ete prises des differentes aubes vieillies avant et apres le RHT. La microstructure du pied de sapin a ete examinee pour mesurer la taille des precipites de ƒÁ' dans leur etat d'origine. Une nouvelle approche a ete proposee pour estimer la duree de vie prolongee (LTE) des aubes apres le traitement de rajeunissement en utilisant l'indice de degradation (Di) nouvellement introduit. L festimation de l fextension de la duree de vie des aubes sur la base de l'indice de microdurete nouvellement propose, confirme la bonne correlation avec la prevision precedente basee sur la taille des precipites ƒÁ'. Des tests de microdurete plus faciles, peu couteux a realiser et non destructifs peuvent nous epargner les examens microscopiques pour la determination de la taille des particules ƒÁ'. Les valeurs de l'indice d fextension de la duree de vie propose suggerent que la realisation du RHT a 48 000 heures est le moment approprie pour la recuperation partielle (~30 %) de la microstructure originale de ƒÁ + ƒÁ'
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    Lifetime extension prediction of the rejuvenated first stage gas turbine blades
    (Taylor & Francis, 2019) Sabri, Khier; Ouali Si-Chaib, Mohamed; Gaceb, Mohamed
    This paper presents a novel method for the first stage gas turbine blades lifetime extension based on degraded GTD-111 substrates hardness evolution after the rejuvenation heat treatments (RHTs) process. Moreover, the RHT impact on directionally solidified (DS) GTD-111 nickel-based suparalloys homogenisation and blades hardness properties were revealed and discussed. The measured hardness values indicate that turbine blades hardness progress is closely related to the nucleation of topologically close packed (TCP) phases, irregular γ’ (Ni3, Al) precipitates growth, and Cr-rich M23C6 Coarsening at grain boundaries. Aspects like γ′/γ eutectic regions rafting, cooling holes oxidation attacks, and formation of cavities within γ-matrix were also identified and analysed.
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    Smart casting: vision-driven defect detection for high-precision manufacturing
    (Springer Science and Business Media, 2025) Sabri, Khier; Gaceb, Mohamed
    This study introduces a vision-driven defect detection system leveraging advanced deep learning architectures to enhance quality control in metal manufacturing. The system integrates four models: the VGG-19 Network, an Attention-Augmented Convolutional Neural Network (CNN), a Vision Transformer (ViT), and a Convolutional Autoencoder. These models were trained and evaluated on a dataset of annotated high-resolution images of impellers acquired under controlled industrial conditions. Among the classifiers, the VGG-19 Network achieved an overall classification accuracy of 100% on this dataset, with F1-scores of 100% for defective samples and 99% for acceptable ones. Grad-CAM visualizations were used to highlight the critical regions influencing the VGG-19 network’s classification decisions. The Attention-Augmented CNN achieved an accuracy of 98.17%. The ViT model yielded F1-scores of 99.42% on the training set and 100% on the validation set, with a 0% false positive rate and a 1.54% false negative rate. The Convolutional Autoencoder enabled unsupervised segmentation by detecting pixel-wise reconstruction errors that indicate anomalies. Each of the four models exhibits an acceptable level of performance with respect to both computational efficiency and deployment feasibility for real-time anomaly detection in manufacture processes

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