Ann-Based Modelling of Fly Ash Compaction Curve / Modelowanie Krzywej Zageszczalnosci Popiołu Lotnego Za Pomoca Ssn

Archives of civil engineering

M. J. SulewskaPhD, DSc, Eng, Faculty of Civil and Environmental Engineering, Bialystok University of Technology,EmailOther articles by this author:De Gruyter OnlineGoogle Scholar¹  K. Zabielska-AdamskaPhD, DSc, Eng, Univ. Professor, Faculty of Civil and Environmental Engineering, Bialystok UniversityEmailOther articles by this author:De Gruyter OnlineGoogle Scholar² 

[1] PhD, DSc, Eng, Faculty of Civil and Environmental Engineering, Bialystok University of Technology,;PhD, DSc, Eng, Univ. Professor, Faculty of Civil and Environmental Engineering, Bialystok University

关键词: Keywords: Compaction curve;    fly ash;    fly ash compactibility;    compaction parameters;    geotechnical parameters;    artificial neural networks;    neural modelling;   

DOI  :  10.2478/v.10169-012-0004-1

学科分类：建筑学

来源: Polska Akademia Nauk * Instytut Podstawowych Problemow Techniki / Polish Academy of Sciences, Institute of Fundamental Technological Research

【 摘 要 】

The use of fly ash as a material for earth structures involves its proper compaction. Fly ash compaction tests have to be conducted on separately prepared virgin samples because spherical ash grains are crushed during compaction, so the laboratory compaction procedure is time-consuming and laborious. The aim of the study was to determine the neural models for prediction of fly ash compaction curve shapes. The attempt of applying the artificial neural networks type MLP was made. ANN inputs were new-created variables - principal components dependent on grain-size distribution (as D10-D90 and uniformity and curvature coefficients), compaction method, and fly ash specific density. The output vectors were presented by co-ordinates of generated compaction curve points. Each point (wi, ρdi) was described by two independent ANNs. Using ANN-based modelling method, models which enable establishing the approximate compaction curve shape were obtained.

【 授权许可】

Unknown