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Jino Mathew
Jino Mathew
在 coventry.ac.uk 的电子邮件经过验证
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引用次数
引用次数
年份
Prediction of welding residual stresses using machine learning: Comparison between neural networks and neuro-fuzzy systems
J Mathew, J Griffin, M Alamaniotis, S Kanarachos, ME Fitzpatrick
Applied Soft Computing 70, 131-146, 2018
882018
Instantaneous vehicle fuel consumption estimation using smartphones and recurrent neural networks
S Kanarachos, J Mathew, ME Fitzpatrick
Expert Systems with Applications 120, 436-447, 2019
692019
Prediction of residual stresses in girth welded pipes using an artificial neural network approach
J Mathew, RJ Moat, S Paddea, ME Fitzpatrick, PJ Bouchard
International Journal of Pressure Vessels and Piping 150, 89-95, 2017
402017
Anomaly detection in time series data using a combination of wavelets, neural networks and Hilbert transform
S Kanarachos, J Mathew, A Chroneos, M Fitzpatrick
2015 6th International Conference on Information, Intelligence, Systems and …, 2015
312015
Reactor pressure vessel embrittlement: Insights from neural network modelling
J Mathew, D Parfitt, K Wilford, N Riddle, M Alamaniotis, A Chroneos, ...
Journal of Nuclear Materials 502, 311-322, 2018
302018
Through-thickness residual stress profiles in austenitic stainless steel welds: A combined experimental and prediction study
J Mathew, RJ Moat, S Paddea, JA Francis, ME Fitzpatrick, PJ Bouchard
Metallurgical and Materials Transactions A 48, 6178-6191, 2017
222017
Validated prediction of weld residual stresses in austenitic steel pipe girth welds before and after thermal ageing, part 1: Mock-up manufacture, residual stress measurements …
MC Smith, O Muránsky, Q Xiong, PJ Bouchard, J Mathew, C Austin
International Journal of Pressure Vessels and Piping 172, 233-250, 2019
192019
Machine learning-based prediction and optimisation system for laser shock peening
J Mathew, R Kshirsagar, S Zabeen, N Smyth, S Kanarachos, K Langer, ...
Applied Sciences 11 (7), 2888, 2021
182021
Probabilistic kernel machines for predictive monitoring of weld residual stress in energy systems
M Alamaniotis, J Mathew, A Chroneos, ME Fitzpatrick, LH Tsoukalas
Engineering Applications of Artificial Intelligence 71, 138-154, 2018
142018
Analysis of surface roughness influence in non-destructive magnetic measurements applied to reactor pressure vessel steels
G Vértesy, A Gasparics, JM Griffin, J Mathew, ME Fitzpatrick, ...
Applied Sciences 10 (24), 8938, 2020
132020
Magnetic Barkhausen Noise Method for Characterisation of Low Alloy Steel
G Kadavath, J Mathew, J Griffin, D Parfitt, ME Fitzpatrick
Pressure Vessels and Piping Conference 58967, V005T10A007, 2019
62019
Validated prediction of weld residual stresses in austenitic steel pipe girth welds before and after thermal ageing, part 2: Modelling and validation
Q Xiong, MC Smith, O Muransky, J Mathew
International Journal of Pressure Vessels and Piping 172, 430-448, 2019
62019
Modelling and measuring residual stresses in pipe girth welds: lessons from the Style Framework 7 project
MC Smith, O Muransky, D Smith, SC Do, PJ Bouchard, J Mathew
Pressure Vessels and Piping Conference 46049, V06BT06A075, 2014
62014
Vacuum plasma etching of 1 wt% La2O3 dispersed tungsten
J Mathew, RM Mohanty, R Sundaresan, V Sivan, K Balasubramanian
Fusion engineering and design 85 (5), 824-827, 2010
62010
Weld Residual Stress Profiles for Structural Integrity Assessment
J Mathew
PQDT-UK & Ireland, 2015
52015
Prediction of pipe girth weld residual stress profiles using artificial neural networks
J Mathew, RJ Moat, PJ Bouchard
Pressure Vessels and Piping Conference 55713, V06BT06A075, 2013
42013
Machine-Learning Approach to Determine Surface Quality on a Reactor Pressure Vessel (RPV) Steel
JM Griffin, J Mathew, A Gasparics, G Vértesy, I Uytdenhouwen, ...
Applied Sciences 12 (8), 3721, 2022
32022
Prediction of welding-induced residual stresses using a neural network approach
J Mathew
Welding and Cutting 15 (4), 232 - 233, 2016
32016
A comparison of machine learning methods to classify radioactive elements using prompt-gamma-ray neutron activation data
J Mathew, R Kshirsagar, DZ Abidin, J Griffin, S Kanarachos, J James, ...
Scientific Reports 13 (9948), 2023
22023
Optimised neural network prediction of residual stress profiles for structural integrity assessment of pipe girth welds
J Mathew, RJ Moat, PJ Bouchard
Pressure Vessels and Piping Conference 46025, V005T11A028, 2014
22014
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