Predicting Complex Erosion Profiles in Steam Distribution Headers with Convolutional and Recurrent Neural Networks

Yang, Steve D.; Ali, Zulfikhar A.; Kwon, Hyuna; Wong, Bryan M.

doi:10.1021/acs.iecr.1c04712

Predicting Complex Erosion Profiles in Steam Distribution Headers with Convolutional and Recurrent Neural Networks

Journal Article · 05 April 2022 · Industrial and Engineering Chemistry Research

DOI:https://doi.org/10.1021/acs.iecr.1c04712· OSTI ID:1977847

Yang, Steve D. ^[1]; Ali, Zulfikhar A. ^[2]; Kwon, Hyuna ^[3]; ^[4]

Materials Science & Engineering Program, University of California─Riverside, Riverside, California 92521, United States
Department of Physics & Astronomy, University of California─Riverside, Riverside, California 92521, United States
Department of Chemical & Environmental Engineering, University of California─Riverside, Riverside, California 92521, United States
Materials Science & Engineering Program, University of California─Riverside, Riverside, California 92521, United States; Department of Physics & Astronomy, University of California─Riverside, Riverside, California 92521, United States; Department of Chemical & Environmental Engineering, University of California─Riverside, Riverside, California 92521, United States

Not provided.

Research Organization:: Univ. of California, Riverside, CA (United States)

Sponsoring Organization:: USDOE Office of Fossil Energy (FE)

DOE Contract Number:: FE0031746

OSTI ID:: 1977847

Journal Information:: Industrial and Engineering Chemistry Research, Vol. 61, Issue 24; ISSN 0888-5885

Publisher:: American Chemical Society (ACS)

Country of Publication:: United States

Language:: English

References (39)

Solid Particle Erosion Testing of Helicopter Rotor Blade Materials Pepi, Marc; Squillacioti, Richard; Pfledderer, Lynne Journal of Failure Analysis and Prevention, Vol. 12, Issue 1 https://doi.org/10.1007/s11668-011-9531-3	journal	December 2011
Erosion- and corrosion-resistant coatings for aircraft compressor blades Swadźba, L.; Formanek, B.; Gabriel, H. M. Surface and Coatings Technology, Vol. 62, Issue 1-3 https://doi.org/10.1016/0257-8972(93)90288-Y	journal	December 1993
Wear-Resistant Metals and Composites Aramide, B. P.; Popoola, Abimbola Patricia I.; Sadiku, Emmanuel Rotimi Handbook of Nanomaterials and Nanocomposites for Energy and Environmental Applications https://doi.org/10.1007/978-3-030-36268-3_177	book	January 2021
A comprehensive review of solid particle erosion modeling for oil and gas wells and pipelines applications Parsi, Mazdak; Najmi, Kamyar; Najafifard, Fardis Journal of Natural Gas Science and Engineering, Vol. 21 https://doi.org/10.1016/j.jngse.2014.10.001	journal	November 2014
Improvements of Particle Near-Wall Velocity and Erosion Predictions Using a Commercial CFD Code Zhang, Yongli; McLaury, Brenton S.; Shirazi, Siamack A. Journal of Fluids Engineering, Vol. 131, Issue 3 https://doi.org/10.1115/1.3077139	journal	February 2009
Development of mechanistic erosion equation for solid particles Arabnejad, H.; Mansouri, A.; Shirazi, S. A. Wear, Vol. 332-333 https://doi.org/10.1016/j.wear.2015.01.031	journal	May 2015
WearGP: A computationally efficient machine learning framework for local erosive wear predictions via nodal Gaussian processes Tran, Anh; Furlan, John M.; Pagalthivarthi, Krishnan V. Wear, Vol. 422-423 https://doi.org/10.1016/j.wear.2018.12.081	journal	March 2019
A novel approach for solid particle erosion prediction based on Gaussian Process Regression Bahrainian, Seyed Saied; Bakhshesh, Mehdi; Hajidavalloo, Ebrahim Wear, Vol. 466-467 https://doi.org/10.1016/j.wear.2020.203549	journal	February 2021
Developing a dimensionless number for solid particle erosion with gas-liquid-solid flow in standard elbows Bakhshesh, Mehdi; Bahrainian, Seyed Saied; Hajidavalloo, Ebrahim Wear, Vol. 478-479 https://doi.org/10.1016/j.wear.2021.203769	journal	August 2021
A hybrid modeling framework using dimensional analysis for erosion predictions Dai, Wei; Mohammadi, Samira; Cremaschi, Selen Computers & Chemical Engineering, Vol. 156 https://doi.org/10.1016/j.compchemeng.2021.107577	journal	January 2022
An Efficient Deep Learning Technique for the Navier-Stokes Equations: Application to Unsteady Wake Flow Dynamics Miyanawala, Tharindu P.; Jaiman, Rajeev K. arXiv https://doi.org/10.48550/arXiv.1710.09099	preprint	January 2017
Random forest regression prediction of solid particle Erosion in elbows Zahedi, Peyman; Parvandeh, Saeid; Asgharpour, Alireza Powder Technology, Vol. 338 https://doi.org/10.1016/j.powtec.2018.07.055	journal	October 2018
A computational fluid dynamics based artificial neural network model to predict solid particle erosion Pandya, D. A.; Dennis, B. H.; Russell, R. D. Wear, Vol. 378-379 https://doi.org/10.1016/j.wear.2017.02.028	journal	May 2017
Eulerian and Lagrangian predictions of particulate two-phase flows: a numerical study Durst, F.; Miloievic, D.; Schönung, B. Applied Mathematical Modelling, Vol. 8, Issue 2 https://doi.org/10.1016/0307-904X(84)90062-3	journal	April 1984
Heat transfer modelling in Discrete Element Method (DEM)-based simulations of thermal processes: Theory and model development Peng, Zhengbiao; Doroodchi, Elham; Moghtaderi, Behdad Progress in Energy and Combustion Science, Vol. 79 https://doi.org/10.1016/j.pecs.2020.100847	journal	July 2020
Using a coupled CFD – DPM approach to predict particle settling in a horizontal air stream Stone, Luke; Hastie, David; Zigan, Stefan Advanced Powder Technology, Vol. 30, Issue 4 https://doi.org/10.1016/j.apt.2019.02.001	journal	April 2019
CFD-DPM and experimental study of the dynamics of wheat starch powder/pyrolysis gases hybrid mixtures in the 20-L Sphere Pico, Paula; Ratkovich, Nicolás; Muñoz, Felipe Powder Technology, Vol. 372 https://doi.org/10.1016/j.powtec.2020.05.108	journal	July 2020
Assessment of particle-tracking models for dispersed particle-laden flows implemented in OpenFOAM and ANSYS FLUENT Greifzu, Franziska; Kratzsch, Christoph; Forgber, Thomas Engineering Applications of Computational Fluid Mechanics, Vol. 10, Issue 1 https://doi.org/10.1080/19942060.2015.1104266	journal	November 2015
Accurate calculation of Stokes drag for point–particle tracking in two-way coupled flows Horwitz, J. A. K.; Mani, A. Journal of Computational Physics, Vol. 318 https://doi.org/10.1016/j.jcp.2016.04.034	journal	August 2016
2D Materials as Protective Coating against Low and Middle Temperature (100?C - 300?C) Corrosion-Erosion in Waste to Energy Plant: Case of Graphene Qu, Zuopeng; Otshwe, Josué Ngondo Graphene, Vol. 10, Issue 02 https://doi.org/10.4236/graphene.2021.102002	journal	January 2021
Erosion mechanisms due to impact of single angular particles Dhar, S.; Krajac, T.; Ciampini, D. Wear, Vol. 258, Issue 1-4 https://doi.org/10.1016/j.wear.2004.09.016	journal	January 2005
On the velocity dependence of the erosion of ductile metals by solid particles at low angles of incidence Finnie, I.; McFadden, D. H. Wear, Vol. 48, Issue 1 https://doi.org/10.1016/0043-1648(78)90147-3	journal	May 1978
Practical estimation of erosion damage caused by solid particle impact Oka, Y. I.; Okamura, K.; Yoshida, T. Wear, Vol. 259, Issue 1-6 https://doi.org/10.1016/j.wear.2005.01.039	journal	July 2005
Some observations on the erosion of ductile metals Finnie, I. Wear, Vol. 19, Issue 1 https://doi.org/10.1016/0043-1648(72)90444-9	journal	January 1972
A comprehensive phenomenological model for erosion of materials in jet flow Huang, Cunkui; Chiovelli, S.; Minev, P. Powder Technology, Vol. 187, Issue 3 https://doi.org/10.1016/j.powtec.2008.03.003	journal	November 2008
Determination of start-up curves for a boiler with natural circulation based on the analysis of stress distribution in critical pressure components Taler, Jan; Węglowski, Bohdan; Taler, Dawid Energy, Vol. 92 https://doi.org/10.1016/j.energy.2015.03.086	journal	December 2015
Mathematical procedure for predicting tube metal temperature in the second stage reheater of the operating flexibly steam boiler Modliński, Norbert; Szczepanek, Krzysztof; Nabagło, Daniel Applied Thermal Engineering, Vol. 146 https://doi.org/10.1016/j.applthermaleng.2018.10.063	journal	January 2019
A validation of computational fluid dynamics temperature distribution prediction in a pulverized coal boiler with acoustic temperature measurement Modliński, Norbert; Madejski, Pawel; Janda, Tomasz Energy, Vol. 92 https://doi.org/10.1016/j.energy.2015.05.124	journal	December 2015
Analiza cieplno-wytrzymałościowa rozruchu kotła parowego na przykładzie kotła OP-650 Pilarczyk, Marcin; Węglowski, Bohdan Scientific Letters of Rzeszow University of Technology - Mechanics, Vol. 31, Issue 86(1/2013) https://doi.org/10.7862/rm.2014.8	journal	January 2014
CFD Approach for Unburned Carbon Reduction in Pulverized Coal Boilers Li, Jun; Jankowski, Radosław; Kotecki, Michał Energy & Fuels, Vol. 26, Issue 2 https://doi.org/10.1021/ef201700a	journal	January 2012
Long Short-Term Memory Hochreiter, Sepp; Schmidhuber, Jürgen Neural Computation, Vol. 9, Issue 8 https://doi.org/10.1162/neco.1997.9.8.1735	journal	November 1997
Compressed Convolutional LSTM: An Efficient Deep Learning framework to Model High Fidelity 3D Turbulence Mohan, Arvind; Daniel, Don; Chertkov, Michael arXiv https://doi.org/10.48550/arXiv.1903.00033	preprint	January 2019
3D CNN Based Automatic Diagnosis of Attention Deficit Hyperactivity Disorder Using Functional and Structural MRI Zou, Liang; Zheng, Jiannan; Miao, Chunyan IEEE Access, Vol. 5 https://doi.org/10.1109/ACCESS.2017.2762703	journal	January 2017
Image Thresholding Improves 3-Dimensional Convolutional Neural Network Diagnosis of Different Acute Brain Hemorrhages on Computed Tomography Scans Ker, Justin; Singh, Satya P.; Bai, Yeqi Sensors, Vol. 19, Issue 9 https://doi.org/10.3390/s19092167	journal	May 2019
Three-dimensional convolutional neural network (3D-CNN) for heterogeneous material homogenization Rao, Chengping; Liu, Yang Computational Materials Science, Vol. 184 https://doi.org/10.1016/j.commatsci.2020.109850	journal	November 2020
Feature Extraction and Fusion Using Deep Convolutional Neural Networks for Face Detection Lu, Xiaojun; Duan, Xu; Mao, Xiuping Mathematical Problems in Engineering, Vol. 2017 https://doi.org/10.1155/2017/1376726	journal	January 2017
Teeth category classification via seven‐layer deep convolutional neural network with max pooling and global average pooling Li, Zhi; Wang, Shui‐Hua; Fan, Rui‐Rui International Journal of Imaging Systems and Technology, Vol. 29, Issue 4 https://doi.org/10.1002/ima.22337	journal	April 2019
The Relationship Between Variable Selection and Data Agumentation and a Method for Prediction Allen, David M. Technometrics, Vol. 16, Issue 1 https://doi.org/10.1080/00401706.1974.10489157	journal	February 1974
Feature Importance Ranking for Deep Learning Wojtas, Maksymilian; Chen, Ke arXiv https://doi.org/10.48550/arXiv.2010.08973	preprint	January 2020

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