[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123486-en":3,"doc-seo-123486-105":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":4,"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},123486,687197207919,"Theodora","https://ap-avatar.wpscdn.com/avatar/a000253d6f5f7c60be?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779446848396160552",8,"Research & Report","Strength Characterisation of Fly Ash Blended 3D Printed Concrete Enhanced with Explainable Machine Learning","This study evaluates the performance of 3D printed concrete using fly ash as a partial cement replacement and builds a machine learning framework to predict mechanical properties. Twenty-eight mixtures are prepared by varying fly ash content, water-to-binder ratios, and superplasticiser dosage, and seven mixes satisfy printability criteria covering flowability, extrudability, and buildability. Mechanical and transport tests measure compressive strength, flexural strength, water absorption, and sorptivity. Results indicate improved strength and durability at 5%–7.5% fly ash, while higher replacement levels reduce early-age performance. Microstructure observations support pore refinement and densification, and a TPE-optimised XGBoost model with SHAP-based interpretability achieves R² > 0.997 for strength prediction.","Journal Pre-proof  \nStrength Characterisation of Fly Ash Blended 3D Printed Concrete Enhanced with Explainable Machine Learning  \nImtiaz Iqbal, Waleed Bin Inqiad, Tala Kasim, Svetlana Besklubova, Melak Mohammad Adil, Mujib Rahman  \nPII: S2214-5095(25)01480-9  \nDOI: [https://doi.org/10.1016/j.cscm.2025.e05682](https://doi.org/10.1016/j.cscm.2025.e05682)  \nReference: CSCM5682  \nTo appear in: Case Studies in Construction Materials  \nReceived date: 25 September 2025  \nRevised date: 7 November 2025  \nAccepted date: 9 December 2025  \nPlease cite this article as: Imtiaz Iqbal, Waleed Bin Inqiad, Tala Kasim, Svetlana Besklubova, Melak Mohammad Adil and Mujib Rahman, Strength Characterisation of Fly Ash Blended 3D Printed Concrete Enhanced with Explainable Machine Learning, Case Studies in Construction Materials, (2025) doi:[https://doi.org/10.1016/j.cscm.2025.e05682](https://doi.org/10.1016/j.cscm.2025.e05682)  \nThis is a PDF of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability. This version will undergo additional copyediting, typesetting and review before it is published in its final form. As such, this version is no longer the Accepted Manuscript, but it is not yet the definitive Version of Record; we are providing this early version to give early visibility of the article. Please note that Elsevier’s sharing policy for the Published Journal Article applies to this version, see:  \n[https://www.elsevier.com/about/policies-and-standards/sharing\\#4-published](https://www.elsevier.com/about/policies-and-standards/sharing#4-published)journal-article. Please also note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.  \nStrength Characterisation of Fly Ash Blended 3D Printed Concrete Enhanced with Explainable Machine Learning  \nImtiaz Iqbal 1, Waleed Bin Inqiad 1, Tala Kasim1*, Svetlana Besklubova2*, Melak Mohammad Adil1, Mujib Rahman 1  \n1. Department of Civil Engineering, Aston University, Birmingham, B4 7ET, United Kingdom; [220425973@aston.ac.uk](220425973@aston.ac.uk) (I.I), [w.bininqiad@aston.ac.uk](w.bininqiad@aston.ac.uk) (W.B.I), [t.kasim@aston.ac.uk](t.kasim@aston.ac.uk) (T.K), [210115066@aston.ac.uk](210115066@aston.ac.uk) (M.M.A), [m.rahman19@aston.ac.uk](m.rahman19@aston.ac.uk) (M.R)  \n2. Department of Engineering, University of Cambridge, 7a JJ Thomson Avenue, Cambridge CB 0FA, UK; [sb2837@cam.ac.uk](sb2837@cam.ac.uk)  \n* Correspondence: [t.kasim@aston.ac.uk](t.kasim@aston.ac.uk) (T.K), [sb2837@cam.ac.uk](sb2837@cam.ac.uk) (SB)  \nAbstract  \nThis study investigates the performance of 3D printed concrete incorporating fly ash as a partial cement replacement and develops a machine learning model to predict its mechanical properties. A total of 28 mixtures were prepared with varying fly ash contents (5–15%), water-to-binder ratios, and superplasticiser dosages. Of these, seven mixes met the requirements for printability in terms offlowability, extrudability, and buildability. Experimental tests were conducted to evaluate compressive strength, flexural strength, water absorption, and sorptivity. Results showed that mixes with 5% and 7.5% fly ash achieved improved strength and durability, whereas higher fly ash levels reduced earlyage performance due to clinker dilution and slower pozzolanic activity. Microstructural analyses confirmed the presence of C–S–H, portlandite, and ettringite, with fly ash contributing to pore refinement and matrix densification. To enhance predictive capability, a TPE-optimised Extreme Gradient Boosting (TPE-XGB) model was developed using data obtained from laboratory testing. The model achieved excellent accuracy (R² > 0.997) in predicting compressive and flexural strength. A graphical user interface integrating SHAP visualisation was created to provide transparent predictions, supporting practical implement","cbCaimGnPBArHGjX","https://ap.wps.com/l/cbCaimGnPBArHGjX","pdf",2205143,1,31,"English","en",105,"# Abstract\n# Keywords\n# Introduction","[{\"question\":\"What variables were changed in the 3D printed concrete mixtures?\",\"answer\":\"The study prepared 28 mixtures by varying fly ash content (5–15%), water-to-binder ratios, and superplasticiser dosages.\"},{\"question\":\"Which fly ash dosages improved strength and durability?\",\"answer\":\"Mixtures with 5% and 7.5% fly ash showed improved strength and durability, while higher fly ash levels lowered early-age performance.\"},{\"question\":\"How was explainable machine learning used in the work?\",\"answer\":\"A TPE-optimised Extreme Gradient Boosting model was trained on laboratory data, and a graphical interface with SHAP visualisation was built to provide transparent predictions.\"}]","Strength Characterisation of Fly Ash Blended 3D Printed Concrete Enhanced with Explainable Machine Learning | PDF",1785816793,78,{"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},"strength-characterisation-of-fly-ash-blended-3d-printed-concrete-enhanced-with-explainable-machine-learning","",{"@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/strength-characterisation-of-fly-ash-blended-3d-printed-concrete-enhanced-with-explainable-machine-learning/123486/",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","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What variables were changed in the 3D printed concrete mixtures?","Question",{"text":75,"@type":76},"The study prepared 28 mixtures by varying fly ash content (5–15%), water-to-binder ratios, and superplasticiser dosages.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which fly ash dosages improved strength and durability?",{"text":80,"@type":76},"Mixtures with 5% and 7.5% fly ash showed improved strength and durability, while higher fly ash levels lowered early-age performance.",{"name":82,"@type":73,"acceptedAnswer":83},"How was explainable machine learning used in the work?",{"text":84,"@type":76},"A TPE-optimised Extreme Gradient Boosting model was trained on laboratory data, and a graphical interface with SHAP visualisation was built to provide transparent predictions.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]