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    Wyświetlanie 1-3 z 3
    Tytuł:
    Buckling and bending properties of aluminium plate with multiple cracks
    Autorzy:
    Mohmmed, J. H.
    Mahmood, N. Y.
    Ali, M.
    Zainulabdeen, A. A.
    Powiązania:
    https://bibliotekanauki.pl/articles/1818485.pdf
    Data publikacji:
    2020
    Wydawca:
    Stowarzyszenie Komputerowej Nauki o Materiałach i Inżynierii Powierzchni w Gliwicach
    Tematy:
    buckling stability
    bending strength
    crack
    aluminium plate
    ANSYS package
    stabilność wyboczeniowa
    wytrzymałość na zginanie
    pęknięcie
    płyta aluminiowa
    pakiet ANSYS
    Opis:
    Purpose: In this paper, the bending strength and buckling stability of (AA 7075-T6) aluminium plate weakened by many transverse cracks, which located at different positions, subjected to concentrated loads applied at the ends were analysed. Design/methodology/approach: Numerical modelling and calculation by the finite element method (ANSYS Package), for the critical load of bending and compression panel were estimated. Findings: It found that the variation of the critical stress in bending and buckling is proportional to the crack conditions (no. of crack and location). In general, the critical load in bending and buckling decreases with increasing the crack number in structure. Research limitations/implications: For both bending and buckling, two transverse cracks on one face of plate is more stable than two transverse cracks on opposite faces. Practical implications: In addition, many experimental tests were carried out by using an INSTRON test machine to obtain the buckling critical loads, where the experimental results were compared with the ones of the finite element method. Furthermore, bending strength was calculated theoretically for the cracked panel. Originality/value: Comparison between the experimental and numerical (FE based model) data and between the theoretical and nu-merical (FE based model) data for buckling and bending strength respectively indicate the precise and the simplicity of the developed models to determine the critical loads in such cases.
    Źródło:
    Archives of Materials Science and Engineering; 2020, 106, 2; 49--58
    1897-2764
    Pojawia się w:
    Archives of Materials Science and Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Mechanical properties and microstructure of alkali activated mortar containing unexpanded clay
    Autorzy:
    Nasser, I.F.
    Ali, M.A.
    Kadhim, M.J.
    Powiązania:
    https://bibliotekanauki.pl/articles/2201132.pdf
    Data publikacji:
    2022
    Wydawca:
    Stowarzyszenie Komputerowej Nauki o Materiałach i Inżynierii Powierzchni w Gliwicach
    Tematy:
    alkali-activated mortar
    pozzolan
    unexpanded clay
    flexural toughness
    scanning electron microscope
    thermal insulation
    pucolana
    glina nie spulchniona
    wytrzymałość na zginanie
    skaningowy mikroskop elektronowy
    izolacja termiczna
    Opis:
    Purpose: In building constructions, due to the decrease of local raw materials and for sustainability purpose, beside the need of light pieces to be used in roofing and false ceiling; an alkali-activated mortar is the new development where pozzolanic material is used instead of cement and activated by an alkaline solution. Therefore, in this research, alkali-activated mortar containing unexpanded clay as a fine aggregate with a dry density of 1652 kg/m3, compressive strength of 3.2 MPa, and thermal conductivity of 0.4 (W/m.K) was produced ,also boards were performed in a dimension of 305×152×12 mm as to use them in false ceiling, and reinforced with 0.25 and 0.5% steel fibre to improve their toughness by 370.8% and 1146.1% compared with reference boards, which made them good choice to used them in roofing and secondary ceiling. Design/methodology/approach: For preparation of alkali-activated mortar, low calcium fly ash (FA) was used as a source binder material. In addition, super-plasticizer and unexpanded clay as a fine aggregate (produce from the crushed artificial aggregate) in the ratio of 1:2.75 fly ash/fine aggregate. The paste was prepared by mixing fly ash with an alkali silicate solution, in a solid-to-liquid ratio of 0.4. Alkali silicate activator was prepared by mixing the NaOH and Na2SiO3 solutions at the mass ratios of 2.5. The concentrations of the NaOH was the same molarity of (14M).To improve the mechanical properties of the reference mortar mixture ,steel fibre with 0.25 and 0.5% content were added to the mix .The specimens were tested for water absorption, dry density, compressive strength, flexural strengths, flexural toughness, and thermal conductivity, in addition to the Scanning Electron Microscope test (SEM) for all mortar mixes. Alkali-activated mortar boards with (305×152×12 mm) were prepared and tested for flexural strength and toughness. Findings: The results indicated that the modulus of rupture for mortar boards reinforced with 0.25 and 0.5% steel fibre exhibits an increase of (3.68-12.10)%. In comparison, the toughness is increased by about 370.8% and 1146.1%, respectively, as compared with the reference mortar (without fibre) which made them resistance to accident, in addition to use them in roofing due to their thermal insulation. Research limitations/implications: Further research is needed to make a similar board using another sustainable material. We can examine the thermal insulation that we can get from these board, especially in the building in Iraq which the weather faces high temperatures. Practical implications: There is a by-product that we could get from the electricity station in Iraq. We must study how we get rid of it. Originality/value: This paper investigate how to produce a new light board using artificial aggregate made from unexpanded clay, which has many benefits in building insulation roofing.
    Źródło:
    Archives of Materials Science and Engineering; 2022, 113, 2; 56--68
    1897-2764
    Pojawia się w:
    Archives of Materials Science and Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Prediction of flexural strength of FRC pavements by soft computing techniques
    Autorzy:
    Kimteta, A.
    Thakur, M.S.
    Sihag, P.
    Upadhya, A.
    Sharma, N.
    Powiązania:
    https://bibliotekanauki.pl/articles/24200582.pdf
    Data publikacji:
    2022
    Wydawca:
    Stowarzyszenie Komputerowej Nauki o Materiałach i Inżynierii Powierzchni w Gliwicach
    Tematy:
    flexural strength
    fibre reinforced concrete
    artificial neural network
    random forest
    random tree
    M5P based model
    wytrzymałość na zginanie
    beton zbrojony włóknami
    sztuczna sieć neuronowa
    las losowy
    drzewo losowe
    model oparty na M5P
    Opis:
    Purpose: The mechanical characteristics of concrete used in rigid pavements can be improved by using fibre-reinforced concrete. The purpose of the study was to predict the flexural strength of the fibre-reinforced concrete for ten input variables i.e., cement, fine aggregate, coarse aggregate, water, superplasticizer/high range water reducer, glass fibre, polypropylene fibre, steel fibres, length and diameter of fibre and further to perform the sensitivity analysis to determine the most sensitive input variable which affects the flexural strength of the said fibre-reinforced concrete. Design/methodology/approach: The data used in the study was acquired from the published literature to create the soft computing modes. Four soft computing techniques i.e., Artificial neural networks (ANN), Random forests (RF), Random trees RT), and M5P, were applied to predict the flexural strength of fibre-reinforced concrete for rigid pavement using ten significant input variables as stated in the ‘purpose’. The most performing algorithm was determined after evaluating the applied models on the threshold of five statistical indices, i.e., the coefficient of correlation, mean absolute error, root mean square error, relative absolute error, and root relative squared error. The sensitivity analysis for most sensitive input variable was performed with out-performing model, i.e., ANN. Findings: The testing stage findings show that the Artificial neural networks model outperformed other applicable models, having the highest coefficient of correlation (0.9408), the lowest mean absolute error (0.8292), and the lowest root mean squared error (1.1285). Furthermore, the sensitivity analysis was performed using the artificial neural networks model. The results demonstrate that polypropylene fibre-reinforced concrete significantly influences the prediction of the flexural strength of fibre-reinforced concrete. Research limitations/implications: Large datasets may enhance machine learning technique performance. Originality/value: The article's novelty is that the most suitable model amongst the four applied techniques has been identified, which gives far better accuracy in predicting flexural strength.
    Źródło:
    Archives of Materials Science and Engineering; 2022, 117, 1; 13--24
    1897-2764
    Pojawia się w:
    Archives of Materials Science and Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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