Papers citing Machine learning of mechanical properties of steels
Material Property Prediction by Integrating Literature-mining and Crossed Feature Selection
International Conference on Information Systems Engineering (ICISE) · 2023-06-23
Rui Zhang, Jiawang Zhang, Yuexing Han, Qiaochuan Chen
Read original paper ↗ ·High strength steel weld metal properties: metallurgical criteria and computational tools
Welding in the World · 2023-07-10
Krishnaswamy Sampath, Ravikumar Varadarajan
Read original paper ↗ ·Prediction of fracture behavior of Al2O3-Cr2O3 ceramics in different Cr2O3 ratios under flexure load using machine learning methods
Computational Materials Science · 2023-07-12
Ramazan Katırcı, Betül Kafkaslıoğlu Yıldız
Read original paper ↗ ·Data-driven machine learning for alloy research: Recent applications and prospects
Materials Today Communications · 2023-07-19
Xueyun Gao, Haiyan Wang, Huijie Tan, Lei Xing, Zhiyu Hu
Read original paper ↗ ·CNN sensor based motion capture system application in basketball training and injury prevention
Preventive Medicine · 2023-07-20
Zhihao Chen, Guoqing Zhang
Read original paper ↗ ·Steels classification by machine learning and Calphad methods
Calphad · 2023-07-21
Pavel Yu. Korotaev, Alexey V. Yanilkin
Read original paper ↗ ·Optimal design of thermal cycles for experimental processing of advanced TRIP-assisted galvanized steels using support vector regression and kernel-based gradient evolution method
The International Journal of Advanced Manufacturing Technology · 2023-07-26
Carlos O. Flor-Sánchez, Edgar O. Reséndiz‐Flores, Gerardo Altamirano-Guerrero
Read original paper ↗ ·Multi-objective gradient-based intelligent optimization of ultra-high-strength galvanized TRIP steels
The International Journal of Advanced Manufacturing Technology · 2023-07-29
Carlos O. Flor-Sánchez, Edgar O. Reséndiz‐Flores, Gerardo Altamirano-Guerrero, Armando Salinas‐Rodríguez
Read original paper ↗ ·A literature-mining method of integrating text and table extraction for materials science publications
Computational Materials Science · 2023-08-31
Rui Zhang, Jiawang Zhang, Qiaochuan Chen, Bing Wang, Yi Liu, Quan Qian, Deng Pan, Jinhua Xia, Yinggang Wang, Yuexing Han
Read original paper ↗ ·Data‐driven and artificial intelligence accelerated steel material research and intelligent manufacturing technology
Materials Genome Engineering Advances · 2023-09-01
Xiaoxiao Geng, Feiyang Wang, Hong‐Hui Wu, Shuize Wang, Guilin Wu, Junheng Gao, Haitao Zhao, Chaolei Zhang, Xinping Mao
Read original paper ↗ ·Identifying intrinsic factors for ductile-to-brittle transition temperatures in Fe–Al intermetallics via machine learning
Journal of Materials Research and Technology · 2023-09-01
Dexin Zhu, Kunming Pan, Hong‐Hui Wu, Yuan Wu, Jie Xiong, Xusheng Yang, Yongpeng Ren, Hua Yu, Shizhong Wei, Turab Lookman
Read original paper ↗ ·Reduction of testing effort for fatigue tests: Application of Bayesian optimal experimental design
Fatigue & Fracture of Engineering Materials & Structures · 2023-09-29
Christian Frie, Anton Kolyshkin, Sven Mordeja, Ali Riza Durmaz, Christoph Eberl
Read original paper ↗ ·Divide and conquer: Machine learning accelerated design of lead-free solder alloys with high strength and high ductility
npj Computational Materials · 2023-10-23
Qinghua Wei, Bin Cao, Hao Yuan, Youyang Chen, Kangdong You, Shuting Yu, Tixin Yang, Ziqiang Dong, Tong‐Yi Zhang
Read original paper ↗ ·Computation of flow rates in rarefied gas flow through circular tubes via machine learning techniques
Microfluidics and Nanofluidics · 2023-10-27
Filippos D. Sofos, Chris D. Dritselis, Serafeim Misdanitis, Theodoros E. Karakasidis, Dimitris Valougeorgis
Read original paper ↗ ·The Influence of Heatmap Correlation-based Feature Selection on Predictive Modeling of Low Alloy Steel Mechanical Properties Using Artificial Neural Network (ANN) Algorithm
Journal of Energy Material and Instrumentation Technology · 2023-11-15
Desmarita Leni
Read original paper ↗ ·Insights from symmetry: Improving machine-learned models for grain boundary segregation
Computational Materials Science · 2023-11-21
Y. Borges, Liam Huber, H. Zapolsky, Renaud Patte, Gilles Demange
Read original paper ↗ ·Optimizing Parameters of the Pack Carburizing Process with Natural Energizers to Improve the Impact and Hardness Properties of Low-Carbon Steel Using NSGA-II-Based Artificial Intelligence
Journal of Materials Engineering and Performance · 2023-11-21
Attasit Wiangkham, Prasert Aengchuan, Kanchala Sudtachat, Atthaphon Ariyarit, Saksit Srisuk, Narongsak Thammachot
Read original paper ↗ ·Data driven performance prediction of titanium-based matrix composites
Alexandria Engineering Journal · 2023-11-22
Xiaoling Wu, Yunfeng Zhou, Jinxian Zhang, Jiahao Liang
Read original paper ↗ ·Aerodynamic optimization of hypersonic blunted waveriders based on symbolic regression
Aerospace Science and Technology · 2023-12-02
Shuai-Qi Guo, Liu Wen, Chen-An Zhang, Yang Liu, Famin Wang
Read original paper ↗ ·Is a high-throughput experimental dataset large enough to accurately estimate a statistic?
Journal of the Mechanics and Physics of Solids · 2023-12-12
Yifan Zhou, Sirui Lin, Xuhui Zhang, Hou Wu, José Blanchet, Zhigang Suo, Tongqing Lu
Read original paper ↗ ·Analysis of data‐driven models for predicting fatigue strength of steel components with uncertainty quantification
Fatigue & Fracture of Engineering Materials & Structures · 2023-12-18
Christian Frie, Anton Kolyshkin, Christoph Eberl
Read original paper ↗ ·Application of Random Forest and Support Vector Machine for Investigation of Pressure Filtration Performance, a Zinc Plant Filter Cake Modelling
International Journal of Mineral Processing and Extractive Metallurgy · 2023-12-26
Masoume Kazemi, Davood Moradkhani, Alireza Abbas Alipour
Read original paper ↗ ·AI-driven inorganic materials by design
Unknown journal · 2024-01-01
Ruiming Zhu
Read original paper ↗ ·Green buildings: Requirements, features, life cycle, and relevant intelligent technologies
Internet of Things and Cyber-Physical Systems · 2024-01-01
Siyi Yin, Jinsong Wu, Junhui Zhao, Michele Nogueira, Jaime Lloret
Read original paper ↗ ·Material Properties Predictions Using Data-Driven Technology
Lecture notes in mechanical engineering · 2024-01-01
Meenakshi Gautham, Deepak Kumar
Read original paper ↗ ·Machine learning-assisted composition design of W-free Co-based superalloys with high γ′-solvus temperature and low density
Journal of Materials Research and Technology · 2024-01-18
Linlin Sun, Bin Cao, Qingshuang Ma, Qiuzhi Gao, Jiahao Luo, Minglong Gong, Jing Bai, Huijun Li
Read original paper ↗ ·MLMD: a programming-free AI platform to predict and design materials
npj Computational Materials · 2024-03-21
Jiaxuan Ma, Bin Cao, Shuya Dong, Yuan Tian, Menghuan Wang, Jie Xiong, Sheng Sun
Read original paper ↗ ·Material informatics and impact of multicollinearity on regression model for fatigue strength of steel
International Journal of Fracture · 2024-03-29
Mrinal Kumar Adhikary, Archana Bora
Read original paper ↗ ·Highly effective design of high GFA alloys with different metal-based and various components by machine learning
Science China Technological Sciences · 2024-04-23
Yichuan Tang, Yifan He, ZhuoQun Fan, Zhongqi Wang, Chengying Tang
Read original paper ↗ ·Prediction and Feature Analysis of Entrapped Slag Defect on Casting Slab Based on Optimized XGBoost Model
Metallurgical and Materials Transactions B · 2024-05-03
Yi Ji, Wanlin Wang, Lejun Zhou, Xiaocan Zhong, Xianzheng Si
Read original paper ↗ ·Exploration of materials fatigue influence factors using interpretable machine learning
Fatigue & Fracture of Engineering Materials & Structures · 2024-05-13
Christian Frie, Ali Riza Durmaz, Christoph Eberl
Read original paper ↗ ·Assessing the efficacy of machine learning models in hydroxyapatite nano-powder assisted electro discharge machining of Ti-6Al-4 V Grade-5 alloy
International Journal on Interactive Design and Manufacturing (IJIDeM) · 2024-05-15
Prince Jain, Ayanesh Y. Joshi, Anand Y. Joshi, Anand Y. Joshi, Anand Y. Joshi
Read original paper ↗ ·Prediction of martensite start temperature of steel combined with expert experience and machine learning
Science and Technology of Advanced Materials · 2024-05-17
Chengcheng Liu, Hang Su
Read original paper ↗ ·Exploring the mathematic equations behind the materials science data using interpretable symbolic regression
Interdisciplinary materials · 2024-05-29
Guanjie Wang, Erpeng Wang, Zefeng Li, Jian Xin Zhou, Zhimei Sun
Read original paper ↗ ·Development of anti-corrosive layer on steel alloy using novel synthesized 8-hydroxyquinoline-based inhibitors: Experimental and theoretical approach
Inorganic Chemistry Communications · 2024-06-05
Said Yaqouti, Nordine Errahmany, Mohamed Rbaa, El Hassan El Kafssaoui, Rachid Fakhreddine, R. Touir, Elyor Tukhliyevich Berdimurodov, Maryam Chafiq, Abdelkarim Chaouiki, Young Gun Ko, Hayat Larhzil
Read original paper ↗ ·Prediction and Rational Design of Stacking Fault Energy of Austenitic Alloys Based on Interpretable Machine Learning and Chemical Composition
steel research international · 2024-06-05
Chengcheng Liu, Hang Su
Read original paper ↗ ·AISI 1040 Çeliğinin Mikroyapı Resimlerinden Mekanik Özelliklerinin Derin Öğrenme ile Tahmini
Gazi Üniversitesi Fen Bilimleri Dergisi Part C Tasarım ve Teknoloji · 2024-06-13
Ridvan SERT, Ömer Şahin, Volkan Kılıçlı, Fecir Duran
Read original paper ↗ ·Machine learning and experimental study on a novel Cr–Mo–V–Ti high manganese steel: Microstructure, mechanical properties and abrasive wear behavior
Journal of Materials Research and Technology · 2024-06-24
Tao Xu, Binguo Fu, Yanfei Jiang, Jinghui Wang, Guolu Li
Read original paper ↗ ·Reservoir Computing neural networks for estimating mechanical properties of hot steel strips
Unknown journal · 2024-06-30
Francesca Motta, Claudio Gallicchio
Read original paper ↗ ·Testing and evaluation of mechanical properties of C45 steel with bainitic structure
Journal of Achievements of Materials and Manufacturing Engineering · 2024-08-01
Michał Sąsiadek, W. Woźniak, Martin Melichar
Read original paper ↗ ·Predicting the compression properties of Phyllostachys edulis based on the volume of its fiber sheaths
Industrial Crops and Products · 2024-09-06
Kangjian Zhang, Linpeng Yu, Fukuan Dai, Yuxuan Chen, Youhong Wang, Zehui Jiang, Genlin Tian
Read original paper ↗ ·Novel ML Modeling Approach for Fatigue Failure of Hydrogen-Transporting Pipelines
SPE Annual Technical Conference and Exhibition · 2024-09-20
Nayem Ahmed, Ramadan Mohammed Ahmed, Cătălin Teodoriu, Michael Gyaabeng
Read original paper ↗ ·Machine learning assisted crystallographic reconstruction from atom probe tomographic images
Journal of Physics Condensed Matter · 2024-09-30
Jie-Ming Pu, Shuai Chen, Tong‐Yi Zhang
Read original paper ↗ ·Empowering the Sustainable Development of High‐End Alloys via Interpretive Machine Learning
Advanced Materials · 2024-10-14
Hongtao Zhang, Huadong Fu, Weidong Li, Lei Jiang, Wei Yong, Jingtai Sun, Long‐Qing Chen, Jianxin Xie
Read original paper ↗ ·Prediction of Mechanical Properties of Hot-Rolled Strip Steel Based on XGBoost and Metallurgical Mechanism
The Physics of Metals and Metallography · 2024-10-20
Ming Li, Guiqin Li, Li Xihang, Lu Lixin, Peter Mitrouchev
Read original paper ↗ ·Application of Combined Machine Learning Methods in Metallurgy FOR Analysis, Selection of Materials and Prediction of Properties
International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA) · 2024-11-13
Vladislav Yurov, Sergei Kuzenkov, Игорь Анатольевич Цыганов
Read original paper ↗ ·Extreme high accuracy prediction and design of Fe-C-Cr-Mn-Si steel using machine learning
Materials & Design · 2024-11-21
Hao Wu, Jianyuan Zhang, Jintao Zhang, Chengjie Ge, Lu Ren, Xinkun Suo
Read original paper ↗ ·Machine learning-assisted creep life prediction and empirical formula generation for 9-12% Cr steel
Scripta Materialia · 2024-11-30
Yifan Wu, Jingzi Zhang, Chengquan Zhong, Jiakai Liu, Kailong Hu, Xi Lin
Read original paper ↗ ·Identifying determinants of γ’ phase coarsening behavior in Co/CoNi-based superalloys with explainable artificial intelligence (XAI)
Journal of Materials Informatics · 2024-12-25
Linlin Sun, Qingshuang Ma, Jingwen Zhang, Liming Yu, Jie Xiong, Huijun Li, Qiuzhi Gao
Read original paper ↗ ·Bayesian Inference for Fatigue Strength Estimation
Cognitive technologies · 2025-01-01
Dorina Weichert, Elena Haedecke, G. Ernis, Sebastian Houben, Alexander Kister, Stefan Wrobel
Read original paper ↗ ·