A novel approach based on the elastoplastic fatigue damage and machine learning models for life prediction of aerospace alloy parts fabricated by additive manufacturing
出版年份 2020 全文链接
标题
A novel approach based on the elastoplastic fatigue damage and machine learning models for life prediction of aerospace alloy parts fabricated by additive manufacturing
作者
关键词
Elastoplastic fatigue damage, Machine learning, Life prediction, Additive manufacturing, Aerospace alloy parts
出版物
INTERNATIONAL JOURNAL OF FATIGUE
Volume 145, Issue -, Pages 106089
出版商
Elsevier BV
发表日期
2020-12-16
DOI
10.1016/j.ijfatigue.2020.106089
参考文献
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- (2020) E. Samaniego et al. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
- A modified stress field intensity approach for fatigue life prediction of components
- (2020) Peng Zhao et al. MATERIALS & DESIGN
- An efficient computational strategy of cycle-jumps dedicated to fatigue of composite structures
- (2020) O. Sally et al. INTERNATIONAL JOURNAL OF FATIGUE
- A local stress-strain approach for fatigue damage prediction of subsea wellhead system based on semi-decoupled model
- (2020) Jiayi Li et al. APPLIED OCEAN RESEARCH
- Development of a novel fatigue damage model with AM effects for life prediction of commonly-used alloys in aerospace
- (2019) Zhixin Zhan et al. INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
- Evaluation of the mechanical and wear properties of titanium produced by three different additive manufacturing methods for biomedical application
- (2019) H. Attar et al. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
- New hybrid cycle jump approach for predicting low-cycle fatigue behavior by a micromechanical model with the damage induced anisotropy concept
- (2019) A. Abdul-Latif et al. INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
- Fatigue Life Prediction of Aero-engine Compressor Disk based on a New Stress Field Intensity Approach
- (2019) Bingfeng Zhao et al. INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
- Multiaxial fatigue analysis of notched components using combined critical plane and critical distance approach
- (2019) Ding Liao et al. INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
- A new continuum damage mechanics-based two-scale model for high-cycle fatigue life prediction considering the two-segment characteristic in S-N curves
- (2019) Susong Yang et al. FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES
- Energy field intensity approach for notch fatigue analysis
- (2019) Ding Liao et al. INTERNATIONAL JOURNAL OF FATIGUE
- A simplified continuum damage mechanics based modeling strategy for cumulative fatigue damage assessment of metallic bolted joints
- (2019) Ning Liu et al. INTERNATIONAL JOURNAL OF FATIGUE
- Integration of new evolutionary approach with artificial neural network for solving short term load forecast problem
- (2018) Priyanka Singh et al. APPLIED ENERGY
- The influence of laminate stacking sequence on ballistic limit using a combined Experimental/FEM/Artificial Neural Networks (ANN) methodology
- (2018) J.A. Artero-Guerrero et al. COMPOSITE STRUCTURES
- Additive manufacturing (3D printing): A review of materials, methods, applications and challenges
- (2018) Tuan D. Ngo et al. COMPOSITES PART B-ENGINEERING
- Critical distance approach for the fatigue strength assessment of magnesium welded joints in contrast to Neuber's effective stress method
- (2018) Ö. Karakaş et al. INTERNATIONAL JOURNAL OF FATIGUE
- Fatigue life assessment of welded joints by two local stress approaches: The notch stress approach and the peak stress method
- (2018) Leonardo Bertini et al. INTERNATIONAL JOURNAL OF FATIGUE
- A unifying energy approach for high cycle fatigue behavior evaluation
- (2018) Junling Fan et al. MECHANICS OF MATERIALS
- Additive manufacturing of metallic components – Process, structure and properties
- (2018) T. DebRoy et al. PROGRESS IN MATERIALS SCIENCE
- A continuum damage mechanics approach for fretting fatigue under out of phase loading
- (2018) Nadeem Ali Bhatti et al. TRIBOLOGY INTERNATIONAL
- Understanding the mechanical properties of novel UHTCMCs through random forest and regression tree analysis
- (2018) Antonio Vinci et al. MATERIALS & DESIGN
- Using machine learning and a data-driven approach to identify the small fatigue crack driving force in polycrystalline materials
- (2018) Andrea Rovinelli et al. npj Computational Materials
- Continuous fatigue damage prediction of a rubber fibre composite structure using multiaxial energy-based approach
- (2018) Ales Gosar et al. FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES
- A Review on the Fatigue Behavior of Ti-6Al-4V Fabricated by Electron Beam Melting Additive Manufacturing
- (2018) Andrew H. Chern et al. INTERNATIONAL JOURNAL OF FATIGUE
- Fatigue behavior of Ti-6Al-4V cellular structures fabricated by additive manufacturing technique
- (2018) Dechun Ren et al. JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
- Notch fatigue and crack growth resistance of Ti-6Al-4V ELI additively manufactured via selective laser melting: A critical distance approach to defect sensitivity
- (2018) M. Benedetti et al. INTERNATIONAL JOURNAL OF FATIGUE
- Effect of processing conditions on the microstructure, porosity, and mechanical properties of Ti-6Al-4V repair fabricated by directed energy deposition
- (2018) Nathan A. Kistler et al. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
- Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption
- (2017) Muhammad Waseem Ahmad et al. ENERGY AND BUILDINGS
- On the accuracy of nominal, structural, and local stress based approaches in designing aluminium welded joints against fatigue
- (2017) Ibrahim Al Zamzami et al. INTERNATIONAL JOURNAL OF FATIGUE
- Oxides, porosity and fatigue performance of AlSi10Mg parts produced by selective laser melting
- (2017) Ming Tang et al. INTERNATIONAL JOURNAL OF FATIGUE
- Elucidating the Relations Between Monotonic and Fatigue Properties of Laser Powder Bed Fusion Stainless Steel 316L
- (2017) Meng Zhang et al. JOM
- Fatigue and fracture behaviour of laser powder bed fusion stainless steel 316L: Influence of processing parameters
- (2017) Meng Zhang et al. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
- Fatigue of AlSi10Mg specimens fabricated by additive manufacturing selective laser melting (AM-SLM)
- (2017) Naor Elad Uzan et al. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
- Variable selection and prediction of uniaxial compressive strength and modulus of elasticity by random forest
- (2017) S.S. Matin et al. APPLIED SOFT COMPUTING
- Additive manufacturing of metals
- (2016) Dirk Herzog et al. ACTA MATERIALIA
- A Manifold Learning Approach to Data-Driven Computational Elasticity and Inelasticity
- (2016) Rubén Ibañez et al. ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
- An implementation of artificial neural-network potentials for atomistic materials simulations: Performance for TiO 2
- (2016) Nongnuch Artrith et al. COMPUTATIONAL MATERIALS SCIENCE
- Prediction and modeling of mechanical properties in fiber reinforced self-compacting concrete using particle swarm optimization algorithm and artificial neural network
- (2016) Hadi Mashhadban et al. CONSTRUCTION AND BUILDING MATERIALS
- Explaining relationships between coke quality index and coal properties by Random Forest method
- (2016) S. Chehreh Chelgani et al. FUEL
- Critical assessment of the fatigue performance of additively manufactured Ti–6Al–4V and perspective for future research
- (2016) P. Li et al. INTERNATIONAL JOURNAL OF FATIGUE
- A modified energy-based approach for fatigue life prediction of superelastic NiTi in presence of tensile mean strain and stress
- (2016) Mohammad J. Mahtabi et al. INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
- Random forest in remote sensing: A review of applications and future directions
- (2016) Mariana Belgiu et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Mechanical behavior of additive manufactured, powder-bed laser-fused materials
- (2016) Todd M. Mower et al. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
- Modeling of free swelling index based on variable importance measurements of parent coal properties by random forest method
- (2016) S. Chehreh Chelgani et al. MEASUREMENT
- Regression and artificial neural network models for strength properties of engineered cementitious composites
- (2016) Khandaker M. A. Hossain et al. NEURAL COMPUTING & APPLICATIONS
- A machine-learning approach for structural damage detection using least square support vector machine based on a new combinational kernel function
- (2016) Ramin Ghiasi et al. STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
- Fatigue behavior of IN718 microtrusses produced via additive manufacturing
- (2016) Lena Huynh et al. MATERIALS & DESIGN
- Comparison of the microstructures and mechanical properties of Ti–6Al–4V fabricated by selective laser melting and electron beam melting
- (2016) Xiaoli Zhao et al. MATERIALS & DESIGN
- Fatigue performance evaluation of selective laser melted Ti–6Al–4V
- (2014) P. Edwards et al. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
- Finite element implementation of multiaxial continuum damage mechanics for plain and fretting fatigue
- (2012) T. Zhang et al. INTERNATIONAL JOURNAL OF FATIGUE
- Modelling and Pareto optimization of mechanical properties of friction stir welded AA7075/AA5083 butt joints using neural network and particle swarm algorithm
- (2012) Mohammad Hasan Shojaeefard et al. MATERIALS & DESIGN
- Additive manufactured AlSi10Mg samples using Selective Laser Melting (SLM): Microstructure, high cycle fatigue, and fracture behavior
- (2011) Erhard Brandl et al. MATERIALS & DESIGN
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