Fatigue life prediction based on a deep learning method for Ti-6Al-4V fabricated by laser powder bed fusion up to very-high-cycle fatigue regime

Application of Deep Neural Network to Predict the High-Cycle Fatigue Life of AISI 1045 Steel Coated by Industrial Coatings

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Fatigue life prediction considering mean stress effect based on random forests and kernel extreme learning machine

(2022) Lei Gan 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

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A fatigue life prediction approach for laser-directed energy deposition titanium alloys by using support vector regression based on pore-induced failures

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Designing against phase and property heterogeneities in additively manufactured titanium alloys

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An experimental investigation of fatigue performance and crack initiation characteristics for an SLMed Ti-6Al-4V under different stress ratios up to very-high-cycle regime

(2022) Rui Fu et al.   INTERNATIONAL JOURNAL OF FATIGUE

Modeling and prediction of surface roughness at the drilling of SLM-Ti6Al4V parts manufactured with pre-hole with optimized ANN and ANFIS

(2022) Hakan Dedeakayoğulları et al.   MEASUREMENT

Comparative analysis of BPNN, SVR, LSTM, Random Forest, and LSTM-SVR for conditional simulation of non-Gaussian measured fluctuating wind pressures

(2022) Jinhua Li et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Modelling fatigue life prediction of additively manufactured Ti-6Al-4V samples using machine learning approach

(2022) Jan Horňas et al.   INTERNATIONAL JOURNAL OF FATIGUE

Fatigue failures from defects in additive manufactured components: A statistical methodology for the analysis of the experimental results

(2021) Andrea Tridello et al.   FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES

Application of DBN and GWO-SVM in analog circuit fault diagnosis

(2021) Xiyuan Su et al.   Scientific Reports

VisEvol: Visual Analytics to Support Hyperparameter Search through Evolutionary Optimization

(2021) A. Chatzimparmpas et al.   COMPUTER GRAPHICS FORUM

Data-driven fatigue life prediction in additive manufactured titanium alloy: A damage mechanics based machine learning framework

(2021) Zhixin Zhan et al.   ENGINEERING FRACTURE MECHANICS

Crack initiation mechanisms under two stress ratios up to very-high-cycle fatigue regime for a selective laser melted Ti-6Al-4V

(2021) Leiming Du et al.   INTERNATIONAL JOURNAL OF FATIGUE

Review of Powder Bed Fusion Additive Manufacturing for Metals

(2021) Leila Ladani et al.   Metals

A New Random Forest Applied to Heavy Metal Risk Assessment

(2021) Ziyan Yu et al.   COMPUTER SYSTEMS SCIENCE AND ENGINEERING

A physics-informed neural network for creep-fatigue life prediction of components at elevated temperatures

(2021) Xiao-Cheng Zhang et al.   ENGINEERING FRACTURE MECHANICS

A novel method of multiaxial fatigue life prediction based on deep learning

(2021) Jingye Yang et al.   INTERNATIONAL JOURNAL OF FATIGUE

Machine Learning Based Predictions of Fatigue Crack Growth Rate of Additively Manufactured Ti6Al4V

(2021) Nithin Konda et al.   Metals

On the use of data-driven machine learning for remaining life estimation of metallic materials based on Ye-Wang damage theory

(2021) Lei Gan et al.   INTERNATIONAL JOURNAL OF FATIGUE

Predicting creep rupture life of Ni-based single crystal superalloys using divide-and-conquer approach based machine learning

(2020) Yue Liu et al.   ACTA MATERIALIA

Very-high-cycle fatigue behavior of Ti-6Al-4V manufactured by selective laser melting: Effect of build orientation

(2020) Guian Qian et al.   INTERNATIONAL JOURNAL OF FATIGUE

A novel effluent quality predicting model based on genetic-deep belief network algorithm for cleaner production in a full-scale paper-making wastewater treatment

(2020) Guoqiang Niu et al.   JOURNAL OF CLEANER PRODUCTION

Analysis of the effect of surface roughness on fatigue performance of powder bed fusion additive manufactured metals

(2020) Niloofar Sanaei et al.   THEORETICAL AND APPLIED FRACTURE MECHANICS

Optimization of selective laser melting process parameters for Ti-6Al-4V alloy manufacturing using deep learning

(2020) Dinh Son Nguyen et al.   Journal of Manufacturing Processes

Influence of processing parameters of selective laser melting on high‐cycle and very‐high‐cycle fatigue behaviour of Ti‐6Al‐4V

(2020) Leiming Du et al.   FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES

A numerical framework to predict the fatigue life of lattice structures built by additive manufacturing

(2020) Alexis Burr et al.   INTERNATIONAL JOURNAL OF FATIGUE

Machine learning based fatigue life prediction with effects of additive manufacturing process parameters for printed SS 316L

(2020) Zhixin Zhan et al.   INTERNATIONAL JOURNAL OF FATIGUE

A machine-learning fatigue life prediction approach of additively manufactured metals

(2020) Hongyixi Bao et al.   ENGINEERING FRACTURE MECHANICS

Hidden unit specialization in layered neural networks: ReLU vs. sigmoidal activation

(2020) Elisa Oostwal et al.   PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

Machine learning of weld joint penetration from weld pool surface using support vector regression

(2019) Rong Liang et al.   Journal of Manufacturing Processes

Micromechanical Gurson-based continuum damage under the context of fretting fatigue: influence of the plastic strain field.

(2019) C.F.B. Sandoval et al.   INTERNATIONAL JOURNAL OF PLASTICITY

Rubber fatigue life prediction using a random forest method and nonlinear cumulative fatigue damage model

(2019) Qiaobin Liu et al.   JOURNAL OF APPLIED POLYMER SCIENCE

The behavior of crack initiation and early growth in high-cycle and very-high-cycle fatigue regimes for a titanium alloy

(2018) Xiangnan Pan et al.   INTERNATIONAL JOURNAL OF FATIGUE

Optimisation of process parameters to address fundamental challenges during selective laser melting of Ti-6Al-4V: A review

(2018) H. Shipley et al.   INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE

Influence of defects, surface roughness and HIP on the fatigue strength of Ti-6Al-4V manufactured by additive manufacturing

(2018) Hiroshige Masuo et al.   INTERNATIONAL JOURNAL OF FATIGUE

Additive manufacturing of Ti6Al4V alloy: A review

(2018) Shunyu Liu et al.   MATERIALS & DESIGN

Fatigue performances of selective laser melted Ti-6Al-4V alloy: Influence of surface finishing, hot isostatic pressing and heat treatments

(2018) Hanchen Yu et al.   INTERNATIONAL JOURNAL OF FATIGUE

A new framework based on continuum damage mechanics and XFEM for high cycle fatigue crack growth simulations

(2018) V.B. Pandey et al.   ENGINEERING FRACTURE MECHANICS

Fatigue life of additively manufactured Ti–6Al–4V in the very high cycle fatigue regime

(2017) J. Günther et al.   INTERNATIONAL JOURNAL OF FATIGUE

The nature and the mechanism of crack initiation and early growth for very-high-cycle fatigue of metallic materials – An overview

(2017) Youshi Hong et al.   THEORETICAL AND APPLIED FRACTURE MECHANICS

Metal Additive Manufacturing: A Review of Mechanical Properties

(2016) John J. Lewandowski et al.   Annual Review of Materials Research

Crack initiation mechanisms of Ti6Al4V in the very high cycle fatigue regime

(2016) S. Heinz et al.   INTERNATIONAL JOURNAL OF FATIGUE

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

Microscopic and nanoscopic observations of metallurgical structures around inclusions at interior crack initiation site for a bearing steel in very high-cycle fatigue

(2015) T. Sakai et al.   FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES

Influence of defects on mechanical properties of Ti–6Al–4V components produced by selective laser melting and electron beam melting

(2015) Haijun Gong et al.   MATERIALS & DESIGN

A study of the microstructural evolution during selective laser melting of Ti–6Al–4V

(2010) Lore Thijs et al.   ACTA MATERIALIA