[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-128016-en":3,"doc-seo-128016-105":31,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},128016,962084928904,"Asher","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","A MACHINE LEARNING STUDY TO PREDICT WIND-DRIVEN WATER RUNBACK CHARACTERISTICS PERTINENT TO AIRCRAFT ICING PHENOMENA - Chapter 2 - dissertation contents","A dissertation develops machine learning methods to predict wind-driven water runback characteristics relevant to aircraft icing phenomena. The research integrates learning models with detailed datasets and evaluates performance using multiple error metrics. It presents training and prediction procedures, including forecasting evolution of the front contact point and the film thickness distribution. Comparisons among LightGBM, MLP, and a ConvLSTM-autoencoder architecture support discussion of results and conclusions for improved icing-related flow prediction.","A machine learning study of wind-driven runback/flow-off multiphase flows pertinent to aircraft  \nicing phenomena  \nby  \nJincheng Wang  \nA dissertation submitted to the graduate faculty  \nin partial fulfillment of the requirements for the degree of  \nDOCTOR OF PHILOSOPHY  \nMajor: Aerospace Engineering  \nProgram of Study Committee:  \nHui Hu, Co-major Professor  \nPing He, Co-major Professor  \nAnupam Sharma  \nJue Yan  \nZhengyuan Zhu  \nThe student author, whose presentation of the scholarship herein was approved by the program of study committee, is solely responsible for the content of this dissertation. The Graduate College will ensure this dissertation is globally accessible and will not permit alterations after a  \ndegree is conferred.  \nIowa State University  \nAmes, Iowa  \n2024  \nCopyright © Jincheng Wang, 2024. All rights reserved.  \nDEDICATION  \nThis dissertation is dedicated to my beloved wife, Liujing, and my parents, who have been an unwavering source of support and encouragement throughout this journey.  \nNobody ever figures out what life is all about, and it doesn't matter. Explore the world. Nearly everything is really interesting if you go into it deeply enough.  \nFrom Richard P. Feynman  \nTABLE OF CONTENTS  \nPage  \nLIST OF FIGURES ...................................................................................................................... vii  \nLIST OF TABLES ......................................................................................................................... xi  \nACKNOWLEDGMENTS ............................................................................................................ xii  \nABSTRACT................................................................................................................................. xiii  \nCHAPTER 1. GENERAL INTRODUCTION........................................................................... 1  \n1.1 Aircraft Icing................................................................................................................... 1  \n1.1.1 Icing Physics ............................................................................................................... 1  \n1.1.2 Environmental Parameters for Aircraft Icing ............................................................. 3  \n1.1.3 Icing Effect on Aerodynamic Performance of Aircraft .............................................. 5  \n1.1.4 Icing Effect on Different Phases of Flight .................................................................. 6  \n1.1.5 Wind-driven Runback Water Transport and Film Dynamics ..................................... 8  \n1.1.6 Predictions on Aircraft Icing..................................................................................... 10  \n1.1.7 Aircraft Ground Icing and Ground Deicing Technique ............................................ 10  \n1.2 Machine Learning in Fluid Mechanics ......................................................................... 13  \n1.2.1 Machine Learning Fundamentals.............................................................................. 13  \n1.2.2 Machine Learning Applications in Aircraft Icing..................................................... 17  \n1.3 Motivation for Current Research .................................................................................. 19  \n1.4 Outline of the Dissertation ............................................................................................ 21  \nReferences ................................................................................................................................. 22  \nCHAPTER 2. A MACHINE LEARNING STUDY TO PREDICT WIND-DRIVEN WATER RUNBACK CHARACTERISTICS PERTINENT TO AIRCRAFT ICING PHENOMENA ..... 31  \nAbstract ..................................................................................................................................... 31  \n2.1 Introduction .............................................................................","cbCaivuTUbFM8aAI","https://ap.wps.com/l/cbCaivuTUbFM8aAI","pdf",12365212,2,1,147,"English","en",105,"# Chapter 1. General Introduction\n## Aircraft Icing\n## Machine Learning in Fluid Mechanics\n## Motivation and Dissertation Outline\n# Chapter 2. A Machine Learning Study to Predict Wind-Driven Water Runback Characteristics Pertinent to Aircraft Icing Phenomena\n## Introduction\n## Machine Learning Methods and Datasets\n## Results and Discussions\n## Conclusions\n# Chapter 3. A Physics-Guided Fourier Neural Operator for the Prediction of Water Film Flow for Aircraft Icing Applications","[{\"question\":\"What problem does the dissertation address?\",\"answer\":\"It addresses predicting wind-driven water runback/flow-off multiphase behavior that is pertinent to aircraft icing phenomena, with emphasis on measurable flow characteristics.\"},{\"question\":\"Which machine learning models are investigated?\",\"answer\":\"The work includes LightGBM, an MLP model, and a ConvLSTM-autoencoder architecture, trained and validated using experimental datasets.\"},{\"question\":\"What key outputs are forecasted in the study?\",\"answer\":\"The dissertation forecasts the evolution of the front contact point and the film thickness distribution associated with the icing-relevant water film dynamics.\"}]","A MACHINE LEARNING STUDY TO PREDICT WIND-DRIVEN WATER RUNBACK CHARACTERISTICS PERTINENT TO AIRCRAFT ICING PHENOMENA - Chapter 2 - dissertation contents | PDF",1785943933,370,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"a-machine-learning-study-to-predict-wind-driven-water-runback-characteristics-pertinent-to-aircraft-icing-phenomena-chapter-2-dissertation-contents","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,48,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":20},"https://docshare.wps.com/document/","Document",{"item":49,"name":12,"@type":44,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/a-machine-learning-study-to-predict-wind-driven-water-runback-characteristics-pertinent-to-aircraft-icing-phenomena-chapter-2-dissertation-contents/128016/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-28","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What problem does the dissertation address?","Question",{"text":76,"@type":77},"It addresses predicting wind-driven water runback/flow-off multiphase behavior that is pertinent to aircraft icing phenomena, with emphasis on measurable flow characteristics.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Which machine learning models are investigated?",{"text":81,"@type":77},"The work includes LightGBM, an MLP model, and a ConvLSTM-autoencoder architecture, trained and validated using experimental datasets.",{"name":83,"@type":74,"acceptedAnswer":84},"What key outputs are forecasted in the study?",{"text":85,"@type":77},"The dissertation forecasts the evolution of the front contact point and the film thickness distribution associated with the icing-relevant water film dynamics.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":47,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]