[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119950-en":3,"doc-seo-119950-105":30,"detail-sidebar-cat-0-en-105":91},{"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":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},119950,4398048949847,"Eliana","https://ap-avatar.wpscdn.com/avatar/400002536579ef2da7f?_k=1778318612642679267",8,"Research & Report","Machine Learning in Combustion - Optimization of Fuel Combustion of Rockets","Machine learning techniques are increasingly used to improve rocket propulsion by modeling and optimizing combustion behavior. This paper reviews how ML connects with combustion science and then focuses on rocket fuel combustion optimization. It surveys combustion fundamentals, links them to supervised, unsupervised, and semi-supervised learning approaches, and describes key rocket engine types (solid, liquid, hybrid) by performance characteristics. The study culminates in results and discussion drawn from rocket fuel combustion optimization research.","Machine Learning in Combustion: Optimization of Fuel  \nCombustion of Rockets  \nNobendu Sen*  \n ORCID: 0009-0004-9262-9638  \nJanardhan Kamath S†  \n ORCID: 0009-0002-5610-5111  \nGautham M Nair‡  \n ORCID: 0009-0007-0285-7285  \nA Immanuel Selvakumart§  \n ORCID: 0000-0003-2637-4441  \nKarunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India  \nAbstract: The application of Machine Learning (ML) techniques in research has seen a drastic increase in the past few years. The primary focus in rocket propulsion is to understand the combustion process and to find various methods to optimize it. This paper provides an overview of the relationship between machine learning and combustion, with a specific focus on optimizing rocket fuel combustion. The introduction presents an overview of combustion and the various ways in which ML is associated with it. Subsequently, the paper discusses various ML algorithms, extending its discussions to supervised, unsupervised, and semi-supervised learning techniques, along with some of their types. An overview of different types of rocket engines is presented to understand the characteristics, advantages, and disadvantages of commonly used rocket engines such as solid, liquid, and hybrid propellant ones. Focusing on rocket fuel combustion, the discussion extends to various methods of optimizing the combustion process. Finally, the paper presents comprehensive results and discussions derived from the studies conducted on rocket fuel combustion optimization.  \nContents  \n1. Introduction ......................................................................................................................................................... 2  \n2. Overview of ML Algorithm ................................................................................................................................ 2  \n3. Rocket Fuel Combustion ..................................................................................................................................... 6  \n4. Optimization of Rocket Fuel Combustion .......................................................................................................... 7  \n5. Results, Discussion, and Conclusion .................................................................................................................. 9  \n6. References ........................................................................................................................................................... 9  \n7. Team Biography................................................................................................................................................ 10  \n8. Acknowledgement ............................................................................................................................................ 10  \n9. Conflict of Interest ............................................................................................................................................ 10  \n10. Funding ...................................................................................................................................................... 10  \n*PG Research Scholar, Division of Aerospace engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, 641114, [India.](India. Contact: nobendusen@karunya.edu.in)[ Contact: nobendusen@karunya.edu.in](India. Contact: nobendusen@karunya.edu.in).  \n† PG Research Scholar, Division of Aerospace engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, 641114, India. Corresponding Author: [janardhankamath@karunya.edu.in](janardhankamath@karunya.edu.in).  \n‡ PG Research Scholar, Division of Aerospace engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, 641114, India. Contact: [gautham22@karunya.edu.in](gautham22@karunya.edu.in).  \n§ Professor 7 Head, Division of Electrical and Electronics Engineering, Karunya Institute of Technology","cbCaiuSj3JiLQHjF","https://ap.wps.com/l/cbCaiuSj3JiLQHjF","pdf",628700,1,10,"English","en",105,"# Contents\n## Introduction\n## Overview of ML Algorithm\n## Rocket Fuel Combustion\n## Optimization of Rocket Fuel Combustion\n## Results, Discussion, and Conclusion\n## References\n## Team Biography\n## Acknowledgement\n## Conflict of Interest\n## Funding","[{\"question\":\"How does machine learning help optimize rocket fuel combustion?\",\"answer\":\"ML uncovers patterns in combustion-related data and builds data-driven models to forecast combustion behavior. It supports optimization methods aimed at improving combustion efficiency for rocket propulsion.\"},{\"question\":\"Which machine learning learning settings are discussed in the paper?\",\"answer\":\"The paper covers supervised, unsupervised, and semi-supervised learning, including typical types within these categories.\"},{\"question\":\"What rocket engine categories are considered when analyzing combustion characteristics?\",\"answer\":\"The discussion includes solid, liquid, and hybrid propellant rocket engines, comparing their advantages and disadvantages to support combustion optimization.\"}]","Machine Learning in Combustion - Optimization of Fuel Combustion of Rockets | PDF",1785727146,25,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-in-combustion-optimization-of-fuel-combustion-of-rockets","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-in-combustion-optimization-of-fuel-combustion-of-rockets/119950/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"How does machine learning help optimize rocket fuel combustion?","Question",{"text":75,"@type":76},"ML uncovers patterns in combustion-related data and builds data-driven models to forecast combustion behavior. 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