A machine learning based approach with an augmented dataset for fatigue life prediction of additively manufactured Ti-6Al-4V samples
出版年份 2023 全文链接
标题
A machine learning based approach with an augmented dataset for fatigue life prediction of additively manufactured Ti-6Al-4V samples
作者
关键词
-
出版物
ENGINEERING FRACTURE MECHANICS
Volume -, Issue -, Pages 109709
出版商
Elsevier BV
发表日期
2023-11-04
DOI
10.1016/j.engfracmech.2023.109709
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Machine learning based very-high-cycle fatigue life prediction of AlSi10Mg alloy fabricated by selective laser melting
- (2023) Tao Shi et al. INTERNATIONAL JOURNAL OF FATIGUE
- A physics-informed machine learning approach for notch fatigue evaluation of alloys used in aerospace
- (2023) W.Q. Hao et al. INTERNATIONAL JOURNAL OF FATIGUE
- Low cycle fatigue life prediction of titanium alloy using genetic algorithm-optimized BP artificial neural network
- (2023) Yanju Wang et al. International Journal of Fatigue
- Machine learning based very-high-cycle fatigue life prediction of Ti-6Al-4V alloy fabricated by selective laser melting
- (2022) Jun Li et al. INTERNATIONAL JOURNAL OF FATIGUE
- The potency of defects on fatigue of additively manufactured metals
- (2022) Xin Peng et al. INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
- A virtual sample generation algorithm supporting machine learning with a small-sample dataset: A case study for rubber materials
- (2022) Lijun Shen et al. COMPUTATIONAL MATERIALS SCIENCE
- Estimating urban PM2.5 concentration: An analysis on the nonlinear effects of explanatory variables based on gradient boosted regression tree
- (2022) Xiatong Hao et al. Urban Climate
- Optimization of fatigue life of pearlitic Grade 900A steel based on the combination of genetic algorithm and artificial neural network
- (2022) Reza Masoudi Nejad et al. INTERNATIONAL JOURNAL OF FATIGUE
- Artificial intelligence modeling of ultrasonic fatigue test to predict the temperature increase
- (2022) M.C. Teixeira et al. INTERNATIONAL JOURNAL OF FATIGUE
- Application of tabular data synthesis using generative adversarial networks on machine learning-based multiaxial fatigue life prediction
- (2022) GaoYuan He et al. INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
- A defect-based physics-informed machine learning framework for fatigue finite life prediction in additive manufacturing
- (2022) Enrico Salvati et al. MATERIALS & DESIGN
- A physics-informed neural network approach to fatigue life prediction using small quantity of samples
- (2022) Dong Chen et al. INTERNATIONAL JOURNAL OF FATIGUE
- Modelling fatigue life prediction of additively manufactured Ti-6Al-4V samples using machine learning approach
- (2022) Jan Horňas et al. INTERNATIONAL JOURNAL OF FATIGUE
- Defect-Based Fatigue Life Prediction of L-PBF Additive Manufactured Metals
- (2021) Niloofar Sanaei et al. ENGINEERING FRACTURE MECHANICS
- On the tight constant in the multivariate Dvoretzky-Kiefer-Wolfowitz inequality
- (2021) Michael Naaman STATISTICS & PROBABILITY LETTERS
- Artificial intelligence assisted fatigue failure prediction
- (2021) W. Schneller et al. INTERNATIONAL JOURNAL OF FATIGUE
- SciPy 1.0: fundamental algorithms for scientific computing in Python
- (2020) Pauli Virtanen et al. NATURE METHODS
- High cycle fatigue in selective laser melted Ti-6Al-4V
- (2020) Punit Kumar et al. ACTA MATERIALIA
- Additive manufacturing and non-destructive testing of topology-optimised aluminium components
- (2020) Sascha Senck et al. Nondestructive Testing and Evaluation
- The effect of manufacturing defects on the fatigue life of selective laser melted Ti-6Al-4V structures
- (2020) Y.N. Hu et al. MATERIALS & DESIGN
- Influence of the position and size of various deterministic defects on the high cycle fatigue resistance of a 316L steel manufactured by laser powder bed fusion
- (2020) Olivier Andreau et al. INTERNATIONAL JOURNAL OF FATIGUE
- Array programming with NumPy
- (2020) Charles R. Harris et al. NATURE
- A machine-learning fatigue life prediction approach of additively manufactured metals
- (2020) Hongyixi Bao et al. ENGINEERING FRACTURE MECHANICS
- Fatigue behaviour of additive manufactured materials: An overview of some recent experimental studies on Ti-6Al-4V considering various processing and loading direction effects
- (2019) Ali Fatemi et al. FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES
- A competition between the contour and hatching zones on the high cycle fatigue behaviour of a 316L stainless steel: Analyzed using X-ray computed tomography
- (2019) Olivier Andreau et al. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
- Effects of defects on mechanical properties in metal additive manufacturing: A review focusing on X-ray tomography insights
- (2019) Anton du Plessis et al. MATERIALS & DESIGN
- Forecasting day-ahead electricity prices in Europe: The importance of considering market integration
- (2018) Jesus Lago et al. APPLIED ENERGY
- Fatigue properties of AlSi10Mg obtained by additive manufacturing: Defect-based modelling and prediction of fatigue strength
- (2018) S. Romano et al. ENGINEERING FRACTURE MECHANICS
- Effect of building direction on porosity and fatigue life of selective laser melted AlSi12Mg alloy
- (2018) Junwen Zhao et al. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
- Investigation of new volumetric non-destructive techniques to characterise additive manufacturing parts
- (2018) A-F. Obaton et al. Welding in the World
- A convolutional neural network with feature fusion for real-time hand posture recognition
- (2018) Sérgio F. Chevtchenko et al. APPLIED SOFT COMPUTING
- Synchrotron-Based X-ray Microtomography Characterization of the Effect of Processing Variables on Porosity Formation in Laser Power-Bed Additive Manufacturing of Ti-6Al-4V
- (2017) Ross Cunningham et al. JOM
- The Influence of Porosity on Fatigue Crack Initiation in Additively Manufactured Titanium Components
- (2017) S. Tammas-Williams et al. Scientific Reports
- Qualification of AM parts: Extreme value statistics applied to tomographic measurements
- (2017) S. Romano et al. MATERIALS & DESIGN
- Linking process, structure, property, and performance for metal-based additive manufacturing: computational approaches with experimental support
- (2016) Jacob Smith et al. COMPUTATIONAL MECHANICS
- Correlation between porosity and processing parameters in TiAl6V4 produced by selective laser melting
- (2016) Galina Kasperovich et al. MATERIALS & DESIGN
- An adaptive algorithm for clustering cumulative probability distribution functions using the Kolmogorov–Smirnov two-sample test
- (2015) Llanos Mora-López et al. EXPERT SYSTEMS WITH APPLICATIONS
- XCT analysis of the influence of melt strategies on defect population in Ti–6Al–4V components manufactured by Selective Electron Beam Melting
- (2015) S. Tammas-Williams et al. MATERIALS CHARACTERIZATION
- 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
- Adaptive network-based fuzzy inference system with leave-one-out cross-validation approach for prediction of surface roughness
- (2010) Minggang Dong et al. APPLIED MATHEMATICAL MODELLING
- X-ray microtomography
- (2010) Eric N. Landis et al. MATERIALS CHARACTERIZATION
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