These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

183 related articles for article (PubMed ID: 31083468)

  • 1. Reliability-Based Low Fatigue Life Analysis of Turbine Blisk with Generalized Regression Extreme Neural Network Method.
    Zhang C; Wei J; Jing H; Fei C; Tang W
    Materials (Basel); 2019 May; 12(9):. PubMed ID: 31083468
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Creep-Based Reliability Evaluation of Turbine Blade-Tip Clearance with Novel Neural Network Regression.
    Zhang CY; Wei JS; Wang Z; Yuan ZS; Fei CW; Lu C
    Materials (Basel); 2019 Oct; 12(21):. PubMed ID: 31671898
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Probabilistic Fatigue/Creep Optimization of Turbine Bladed Disk with Fuzzy Multi-Extremum Response Surface Method.
    Zhang CY; Yuan ZS; Wang Z; Fei CW; Lu C
    Materials (Basel); 2019 Oct; 12(20):. PubMed ID: 31618933
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A Combined High and Low Cycle Fatigue Model for Life Prediction of Turbine Blades.
    Zhu SP; Yue P; Yu ZY; Wang Q
    Materials (Basel); 2017 Jun; 10(7):. PubMed ID: 28773064
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Decomposed Collaborative Modeling Approach for Probabilistic Fatigue Life Evaluation of Turbine Rotor.
    Huang Y; Bai GC; Song LK; Wang BW
    Materials (Basel); 2020 Jul; 13(14):. PubMed ID: 32708207
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Fatigue reliability analysis of aeroengine blade-disc systems using physics-informed ensemble learning.
    Li XQ; Song LK; Choy YS; Bai GC
    Philos Trans A Math Phys Eng Sci; 2023 Nov; 381(2260):20220384. PubMed ID: 37742710
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Study on the Elastic-Plastic Correlation of Low-Cycle Fatigue for Variable Asymmetric Loadings.
    Zhang J; Li W; Dai H; Liu N; Lin J
    Materials (Basel); 2020 May; 13(11):. PubMed ID: 32481498
    [TBL] [Abstract][Full Text] [Related]  

  • 8. An optimization study of polishing efficiency of blisk and its technological parameters.
    Huai W; Lin X
    Sci Prog; 2020; 103(3):36850420957850. PubMed ID: 32924782
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Fuzzy Multi-SVR Learning Model for Reliability-Based Design Optimization of Turbine Blades.
    Zhang CY; Wang Z; Fei CW; Yuan ZS; Wei JS; Tang WZ
    Materials (Basel); 2019 Jul; 12(15):. PubMed ID: 31344790
    [TBL] [Abstract][Full Text] [Related]  

  • 10. LCF and HCF of Short Carbon Fibers Reinforced AE42 Mg Alloy.
    Alsaleh NA; Ataya S; Latief FH; Ahmed MMZ; Ataya A; Abdul-Latif A
    Materials (Basel); 2023 May; 16(10):. PubMed ID: 37241313
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Fatigue testing of a NiTi rotary instrument. Part 1: Strain-life relationship.
    Cheung GS; Darvell BW
    Int Endod J; 2007 Aug; 40(8):612-8. PubMed ID: 17532775
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Effects of Machined Surface Integrity on High-Temperature Low-Cycle Fatigue Life and Process Parameters Optimization of Turning Superalloy Inconel 718.
    Ren X; Liu Z; Liang X; Cui P
    Materials (Basel); 2021 May; 14(9):. PubMed ID: 34066982
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Multi-Physics Coupling Modeling and Experimental Investigation of Vibration-Assisted Blisk Channel ECM.
    Zhang J; Song S; Zhang J; Chang W; Yang H; Tang H; Chen S
    Micromachines (Basel); 2021 Dec; 13(1):. PubMed ID: 35056216
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Fatigue Factor Assessment and Life Prediction of Concrete Based on Bayesian Regularized BP Neural Network.
    Chen H; Sun Z; Zhong Z; Huang Y
    Materials (Basel); 2022 Jun; 15(13):. PubMed ID: 35806616
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A New Approach for Fatigue Reliability Analysis of Thin-Walled Structures with DC-ILSSVR.
    Du W; Ma J; Dai C; Yue P; Zu JW
    Materials (Basel); 2021 Jul; 14(14):. PubMed ID: 34300887
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Low-cycle fatigue of NiTi rotary instruments of various cross-sectional shapes.
    Cheung GS; Darvell BW
    Int Endod J; 2007 Aug; 40(8):626-32. PubMed ID: 17459117
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A New Energy-Critical Plane Damage Parameter for Multiaxial Fatigue Life Prediction of Turbine Blades.
    Yu ZY; Zhu SP; Liu Q; Liu Y
    Materials (Basel); 2017 May; 10(5):. PubMed ID: 28772873
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Low-Cycle Fatigue Behavior of the Novel Steel and 30SiMn2MoV Steel at 700 °C.
    Zhao C; Zhang J; Fu J; Lian Y; Zhang Z; Zhang C; Huang J
    Materials (Basel); 2020 Dec; 13(24):. PubMed ID: 33339394
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Application of Instrumented Indentation Procedure in Assessing the Low-Cycle Fatigue Properties of Selected Heat-Treated Steels.
    Hościło B; Molski KL
    Materials (Basel); 2024 May; 17(10):. PubMed ID: 38793441
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Fatigue Life Prediction of a SAE Keyhole Specimen as a Subcase of Certification by Analysis.
    Wu X; Zhang Z; Paraschivoiu D
    Materials (Basel); 2024 Sep; 17(18):. PubMed ID: 39336262
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.