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RESEARCH PAPER · Journal of Nuclear Materials · 2019

Predicting the onset of void swelling in irradiated metals with machine learning

Miaomiao Jin, Penghui Cao, Michael Philip Short

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42 direct citing works

Predicting the onset of void swelling in irradiated metals with machine learningOriginalDesign of comprehensive mechanical properties by machine learning and high-throughput optimization algorithm in RAFM steels30Deep neural network based prediction of burst parameters for Zircaloy-4 fuel cladding during loss-of-coolant accident17Level 3 Milestone Report: April 20200Machine learning guided methods in building chemical composition-hardenability model for wear-resistant steel24Artificial intelligence in nuclear industry: Chimera or solution?75On the use of non-destructive, gigahertz ultrasonics to rapidly screen irradiated steels for swelling resistance7Machine learning-based predictions of fatigue life and fatigue limit for steels173Boosting algorithms in energy research: a systematic review88Composition optimization of radiation resistance ODS alloy with high strength and ductility for advanced reactor based on machine learning8Nuclear Power Plant Burst Parameters Prediction During a Loss-of-Coolant Accident Using an Artificial Neural Network1Application of machine learning in understanding the irradiation damage mechanism of high-entropy materials38Machine learning in nuclear materials research125Predicting the Irradiation Swelling of Austenitic and Ferritic/Martensitic Steels, Based on the Coupled Model of Machine Learning and Rate Theory12Integrated High‐Throughput and Machine Learning Methods to Accelerate Discovery of Molten Salt Corrosion‐Resistant Alloys56Nobility vs Mobility: Unlocking New Insights Into Molten Salt Corrosion Mechanisms of High Entropy Alloys with High-Throughput Experiments and Machine Learning-Enabled Analysis0Covariate Dependent Sparse Functional Data Analysis2Multiscale modelling of irradiation damage behavior in high entropy alloys35Influence analysis of alloy elements on irradiation embrittlement of RPV steel based on deep neural network13Machine learning-based predictions of yield strength for neutron-irradiated ferritic/martensitic steels16Predicting the particle-agglomeration effect on the equivalent mechanical properties of dispersion nuclear fuel by machine learning16Machine Learning–Based Prediction of Irradiation-Induced Swelling from Synergistic Effects of Helium and Hydrogen1Irradiated mechanical properties predicted by a machine learning method with the Fourier-transform-based feature extension0Neural Networks for Prediction of Swelling in Austenitic Steels Irradiated by Fast Neurons0Neural Networks for Prediction of Swelling in Austenitic Steels Irradiated by Fast Neurons0Shallow Learning vs. Deep Learning in Engineering Applications13Prediction of the energetics of stable self-interstitial atoms at tungsten grain boundaries via machine learning7Forecasting of Nuclear Power Plant Burst Factors using Radial Basis Neural Network throughout Loss of Coolant Accident0Nobility vs. mobility: Insights into molten salt corrosion mechanisms of high-entropy alloys via high-throughput experiments and machine learning23Prediction of the swelling rate of irradiated type 316 stainless steels via machine learning methods11Degradation modeling using Bayesian hierarchical piecewise linear models: A case study to predict void swelling in irradiated materials3Establishing machine-learning approach for predicting outer-diametral strains in ferritic/martensitic (F/M) steel tubes during in-reactor neutron-irradiation creep experiments2Neural networks for prediction of swelling in austenitic steels irradiated by fast neutrons5Machine learning - assisted prediction of yield strength in irradiated type 316 stainless steels8Progress in radiation tolerant materials: Current insights from the perspective of grain size and environmental temperature10Machine learning-based prediction of alloying element effects on irradiation swelling in austenitic steels0In-pile heat conduction model of the dispersion nuclear fuel plate with particle agglomeration. Part II: Predicting the effective thermal conductivity under the in-pile thermal transfer pattern based on a deep neural network2Insights into irradiation creep coefficient in nuclear graphite from machine learning5Hybrid machine learning model with optimization algorithm for predicting the incubation dose of void swelling in irradiated metals5Enhanced vacancy-interstitial annihilation via sliding, rotation and emission of the interstitial in tungsten0Physics-informed transformer model for multiaxial ratchetting-fatigue life prediction of SUS301L stainless steel butt-welded joint11Predicting swelling in austenitic steels under PWR environments using machine learning0Automated machine learning with data augmentation for predicting void swelling onset dose in irradiated metals2Machine learning-based surrogate modeling for fast prediction of porosity evolution in U3Si2 nuclear fuel under irradiation0Thermal and Radiation Resistance Properties of High-Entropy Alloys0Physics-guided neural network for predicting fatigue life of unirradiated and irradiated austenitic and ferritic/martensitic steels under reactor-relevant conditions2Multi-head attention network for prediction of irradiation embrittlement in reactor pressure vessel steels0Transforming the modelling of nuclear structural materials: A critical review of machine learning approaches0Explainable ensemble learning for predicting the incubation dose of void swelling in irradiated metals0Quantifying uncertainty in void swelling prediction: A conformal prediction framework for reactor safety margins0

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  2. Deep neural network based prediction of burst parameters for Zircaloy-4 fuel cladding during loss-of-coolant accident

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  5. Artificial intelligence in nuclear industry: Chimera or solution?

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  6. On the use of non-destructive, gigahertz ultrasonics to rapidly screen irradiated steels for swelling resistance

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  15. Nobility vs Mobility: Unlocking New Insights Into Molten Salt Corrosion Mechanisms of High Entropy Alloys with High-Throughput Experiments and Machine Learning-Enabled Analysis

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  16. Covariate Dependent Sparse Functional Data Analysis

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  17. Multiscale modelling of irradiation damage behavior in high entropy alloys

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  18. Influence analysis of alloy elements on irradiation embrittlement of RPV steel based on deep neural network

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  19. Machine learning-based predictions of yield strength for neutron-irradiated ferritic/martensitic steels

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  20. Predicting the particle-agglomeration effect on the equivalent mechanical properties of dispersion nuclear fuel by machine learning

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  21. Machine Learning–Based Prediction of Irradiation-Induced Swelling from Synergistic Effects of Helium and Hydrogen

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  22. Irradiated mechanical properties predicted by a machine learning method with the Fourier-transform-based feature extension

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  23. Neural Networks for Prediction of Swelling in Austenitic Steels Irradiated by Fast Neurons

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