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A principal component analysis in concrete design

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Over the last 200 years, ordinary concrete has evolved from four basic ingredient materials (gravel, sand, cement, and water) to multicomponent complex composites. The number and variety of the additives, admixtures, non-conventional aggregates, fillers, and fibres currently used for concrete production have continued to grow rapidly. Regrettably, the methods for de-signing concrete mixes have not evolved at a similarly fast pace. Keeping the above facts in mind, the authors utilised a principal component analysis (PCA) to design modern concrete mixes. As an initial approach, 550 cast and tested concrete mixes were analysed. The main aim of the presented study was to prove the usefulness of the PCA methodology for the fast classification of concrete mix compositions. The acquired knowledge should be useful for the effective design of multicomponent modern concrete mixes.
Rocznik
Tom
Strony
203--219
Opis fizyczny
Bibliogr. 34 poz., rys., tab.
Twórcy
  • University of Warmia and Mazury in Olsztyn, Poland
autor
  • University of Warmia and Mazury in Olsztyn, Poland
Bibliografia
  • 1.Abdul-Razzaq, K.S. (2017) Proposing a new type of structural slurry infiltrated concrete (SSICON). Journal of Building Engineering, 13, 254-265.
  • 2.Alves, M.F., Cremonini, R.A. & Dal Molin, D.C.C. (2004) A comparison of mix proportioning methods for high-strength concrete. Cement and Concrete Composites, 26(6), 613-621.
  • 3.Atiş, C.D. & Karahan, O. (2009) Properties of steel fiber reinforced fly ash concrete. Construction and Building Materials.
  • 4.Aygün, B., Şakar, E., Agar, O., Sayyed, M.I., Karabulut, A. & Singh, V.P. (2021) Development of new heavy concretes containing chrome-ore for nuclear radiation shielding applications. Progress in Nuclear Energy, 133.
  • 5.Benaicha, M., Belcaid, A., Alaoui, A.H., Jalbaud, O. & Burtschell, Y. (2019) Rheological characterization of self-compacting concrete: New recommendation. Structural Concrete, 20(5), 1695-1701.
  • 6.Bolomey, J. (1927) Determination of the compressive strength of mortars and concretes. Bulletin Technique de La Suisse Romande, 16, 22-24.
  • 7.de Brito, J., Kurda, R. & da Silva, P.R. (2018) Can we truly predict the compressive strength of concrete without knowing the properties of aggregates? Applied Sciences (Switzerland), 8(7).
  • 8.BS EN 12350-5 (2009) Testing Fresh Concrete - Part 5: Flow Table Test. British Standard.
  • 9.BS EN 12390-8:2009 (2009) Testing Hardened Concrete - Part 8: Depth of Penetration of Water under Pressure. British Standard.
  • 10.Concrete. Specification, Performance, Production and Conformity (2013), European Committee for Standardization (CEN)).
  • 11.Gheibi, M., Karrabi, M., Shakerian, M. & Mirahmadi, M. (2018) Life cycle assessment of concrete production with a focus on air pollutants and the desired risk parameters using genetic algorithm. Journal of Environmental Health Science and Engineering, 16(1), 89-98.
  • 12.Halbiniak, J., Katzer, J., Major, M. & Major, I. (2020) A proposition of an in situ production of a blended cement. Materials, 13(10), 2289.
  • 13.Hornakova, M., Katzer, J., Kobaka, J. & Konecny, P. (2019) Lightweight SFRC benefitting from a presoaking and internal curing process. Materials, 12(24).
  • 14.Johnson, P.E., Smith, M.O. & Adams, J.B. (1985) Quantitative analysis of planetary reflectance spectra with principal components analysis. Journal of Geophysical Research.
  • 15.Kansal, C.M. & Goyal, R. (2021) Analysing mechanical properties of concrete with nano silica, silica fume and steel slag. Materials Today: Proceedings available from https://linkinghub.elsevier.com/retrieve/pii/S2214785320407503.
  • 16.Kassambara, A. (2017) Practical guide to principal component methods in R: PCA, M (CA), FAMD, MFA, HCPC, Factoextra. STHDA 2, 1-155.
  • 17.Katzer, J., Kobaka, J. & Ponikiewski, T. (2020) Influence of crimped steel fibre on properties of concrete based on an aggregate mix of waste and natural aggregates. Materials, 13(8).
  • 18.Kobaka, J. (2021) Principal component analysis as a statistical tool for concrete mix design. Materials, 14(10), 2668.
  • 19.Kobaka, J., Katzer, J. & Zarzycki, P.K. (2019) Pilbara craton soil as a possible lunar soil simulant for civil engineering applications. Materials, 12(23), 1-11.
  • 20.Kumar, D.C. (2013) Genetic algorithm based optimum design of prestressed concrete beam. International Journal for Computational Civil and Structural Engineering, 3(3), 644-654.
  • 21.Mehta, P.K. & Aietcin, P.C.C. (1990) Principles underlying production of high-performance concrete. Cement, Concrete and Aggregates, 12(2), 70-78.
  • 22.Pieters, C. (2002) Statistical analysis of the links among lunar mare soil mineralogy, chemistry, and reflectance spectra. Icarus, 155(2), 285-298.
  • 23.Rossi, P. (1997) Strain rate effects in concrete structures: The LCPC experience. Materials and Structures/Materiaux et Constructions.
  • 24.Salem, M.A.A. & Pandey, R.K. (2015) Effect of cement-water ratio on compressive strengthand density of concrete. International Journal of Engineering Research and Technology (IJERT), 4(2).
  • 25.Shen, W., Li, F. & Lu, C. (2011) Study on improving overall calculation method of mix design method for fly ash Hpc. Advanced Materials Research, 163-167, 1414-1418.
  • 26.Singh, S.B., Munjal, P. & Thammishetti, N. (2015) Role of water/cement ratio on strength development of cement mortar. Journal of Building Engineering [online], 4, 94-100.
  • 27.To Joseph Aspdin, of Leeds, in the County of York, Bricklayer, for His New Invented Improvement in the Mode of Producing an Artificial Stone (1826). Journal of the Franklin Institute, 1(3), 146-149.
  • 28.Xie, X. (2012) The design of mix proportion of high-performance concrete for passenger dedicated railway based on overall calculation method. Applied Mechanics and Materials, 193-194, 814-821
  • 29.Xuan, D., Zhan, B. & Poon, C.S. (2016) Development of a new generation of eco-friendly concrete blocks by accelerated mineral carbonation. Journal of Cleaner Production, 133, 1235-1241.
  • 30.Zarzycki, P.K. (2017) Application of multivariate statistical techniques in chromatographic and spectroscopic fingerprinting of complex food and environmental samples. Journal of AOAC International.
  • 31.Zarzycki, P.K. & Katzer, J. (2018) Assessment of lunar soil simulants based on multivariate statistics. Earth and Space 2018: Engineering for Extreme Environments - Proceedings of the 16th Biennial International Conference on Engineering, Science, Construction, and Operations in Challenging Environments.
  • 32.Zarzycki, P.K., Katzer, J. & Domski, J. (2017) Fast classification of fibres for concretebased on multivariate statistics. Computers and Concrete, 20(1).
  • 33.Zhang, H., Zou, K., Ji, X., Zhang, C., Tang, F. & Wu, X. (2015) Mixture design methods for high performance concrete a review. Proceedings of the 2015 International Conference on Advanced Engineering Materials and Technology. Paris, Atlantis Press.
  • 34.Zhang, J., Huang, Y., Ma, G. & Nener, B. (2021) Mixture optimization for environmental, economical and mechanical objectives in silica fume concrete: A novel frame-work based on machine learning and a new meta-heuristic algorithm. Resources, Conservation and Recycling, 167, 105395.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f5051322-b1db-41c4-b0cd-25ea5f524951
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