WearGP: A computationally efficient machine learning framework for local erosive wear predictions via nodal Gaussian processes

[1]  Selen Cremaschi,et al.  Uncertainty quantification in erosion predictions using data mining methods , 2018, Wear.

[2]  D. Pandya,et al.  A computational fluid dynamics based artificial neural network model to predict solid particle erosion , 2017 .

[3]  N. Thürey,et al.  Data-driven synthesis of smoke flows with CNN-based feature descriptors , 2017, ACM Trans. Graph..

[4]  Wei Li,et al.  Convolutional Neural Networks for Steady Flow Approximation , 2016, KDD.

[5]  Shahaboddin Shamshirband,et al.  Performance investigation of micro- and nano-sized particle erosion in a 90° elbow using an ANFIS model , 2015 .

[6]  R. Visintainer,et al.  Finite Element Prediction of Multi-Size Particulate Flow through Three-Dimensional Channel: Code Validation , 2013 .

[7]  Iain Murray,et al.  A framework for evaluating approximation methods for Gaussian process regression , 2012, J. Mach. Learn. Res..

[8]  Ming J. Zuo,et al.  Support vector machine based data processing algorithm for wear degree classification of slurry pump systems , 2010 .

[9]  M. K. Ghosh,et al.  Solid particle erosion studies on polyphenylene sulfide composites and prediction on erosion data using artificial neural networks , 2009 .

[10]  Mark D. Hill,et al.  Amdahl's Law in the Multicore Era , 2008, Computer.

[11]  J. Weston,et al.  Approximation Methods for Gaussian Process Regression , 2007 .

[12]  Krishnan V. Pagalthivarthi,et al.  Determination of wear coefficients for erosive wear prediction through Coriolis wear testing , 2005 .

[13]  S. Danaher,et al.  Erosion modelling using Bayesian regulated artificial neural networks , 2004 .

[14]  J. Karger‐Kocsis,et al.  Artificial neural network predictions on erosive wear of polymers , 2003 .

[15]  Olaf Schenk,et al.  Solving unsymmetric sparse systems of linear equations with PARDISO , 2002, Future Gener. Comput. Syst..

[16]  Kai Velten,et al.  Wear volume prediction with artificial neural networks , 2000 .

[17]  P. Spalart.  A One-Equation Turbulence Model for Aerodynamic Flows , 1992 .

[18]  T. Hughes,et al.  Streamline upwind/Petrov-Galerkin formulations for convection dominated flows with particular emphasis on the incompressible Navier-Stokes equations , 1990 .

[19]  T. Hughes,et al.  A theoretical framework for Petrov-Galerkin methods with discontinuous weighting functions: application to the streamline-upwind procedure. , 1982 .

[20]  Nando de Freitas,et al.  Taking the Human Out of the Loop: A Review of Bayesian Optimization , 2016, Proceedings of the IEEE.

[21]  R. Visintainer,et al.  Development of A-scan ultrasound technique for measuring local particle concentration in slurry flows , 2012 .

[22]  Krishnan V. Pagalthivarthi,et al.  Solid-Liquid Flow-Induced Erosion Prediction in Three-Dimensional Pump Casing , 2009 .

[23]  Carl Edward.  Gaussian Processes in Machine Learning , 2004 .

[24]  F. White.  Viscous Fluid Flow , 1974 .