Browsing by Subject "CONCRETE"

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    An investigation on the use of tincal ore waste, fly ash, and coal bottom ash as Portland cement replacement materials
    (PERGAMON-ELSEVIER SCIENCE LTD) Kula, I; Olgun, A; Sevinc, V; Erdogan, Y
    The possibility of using tineal ore waste (TW), coal bottom ash (BA), and fly ash (FA) as partial replacement in concrete was examined through a number of tests. The properties examined include setting time, compressive strength, mortar expansion, water consistency of mortar, and microstructure. The results showed that compressive strength of all specimens containing I wt.% of TW was higher than that of the control at the 28th day of curing. At 90 days, the contribution to strength by BA + TW and FA + TW was higher than in the concrete-prepared equivalent TW beyond 3 wt.% of Portland cement (PC) replacement. With the replacement of 3-5 wt.% of PC by TW, the compressive strength of the concrete decreased compared to control concrete. However, the values obtained are within the limit of Turkish Standards (TS). Adding BA or FA with TW improved the performance relative to TW replacement only. Increasing replacement of TW gives rise to a higher setting time. As a result. TW, BA, and FA samples may be used as cementitious materials. (C) 2002 Elsevier Science Ltd. All rights reserved.
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    A Novel Hierarchical Extreme Machine-Learning-Based Approach for Linear Attenuation Coefficient Forecasting
    (MDPI) Varone, G; Ieracitano, C; Çiftçioglu, A; Hussain, T; Gogate, M; Dashtipour, K; Al-Tamimi, BN; Almoamari, H; Akkurt, I; Hussain, A
    The development of reinforced polymer composite materials has had a significant influence on the challenging problem of shielding against high-energy photons, particularly X-rays and gamma-rays in industrial and healthcare facilities. Heavy materials' shielding characteristics hold a lot of potential for bolstering concrete chunks. The mass attenuation coefficient is the main physical factor that is utilized to measure the narrow beam gamma-ray attenuation of various combinations of magnetite and mineral powders with concrete. Data-driven machine learning approaches can be investigated to assess the gamma-ray shielding behavior of composites as an alternative to theoretical calculations, which are often time- and resource-intensive during workbench testing. We developed a dataset using magnetite and seventeen mineral powder combinations at different densities and water/cement ratios, exposed to photon energy ranging from 1 to 1006 kiloelectronvolt (KeV). The National Institute of Standards and Technology (NIST) photon cross-section database and software methodology (XCOM) was used to compute the concrete's gamma-ray shielding characteristics (LAC). The XCOM-calculated LACs and seventeen mineral powders were exploited using a range of machine learning (ML) regressors. The goal was to investigate whether the available dataset and XCOM-simulated LAC can be replicated using ML techniques in a data-driven approach. The minimum absolute error (MAE), root mean square error (RMSE), and R2score were employed to assess the performance of our proposed ML models, specifically a support vector machine (SVM), 1d-convolutional neural network (CNN), multi-Layer perceptrons (MLP), linear regressor, decision tree, hierarchical extreme machine learning (HELM), extreme learning machine (ELM), and random forest networks. Comparative results showed that our proposed HELM architecture outperformed state-of-the-art SVM, decision tree, polynomial regressor, random forest, MLP, CNN, and conventional ELM models. Stepwise regression and correlation analysis were further used to evaluate the forecasting capability of ML techniques compared to the benchmark XCOM approach. According to the statistical analysis, the HELM model showed strong consistency between XCOM and predicted LAC values. Additionally, the HELM model performed better in terms of accuracy than the other models used in this study, yielding the highest R2score and the lowest MAE and RMSE.
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    A STUDY OF SOME DURABILITY PROPERTIES OF MORTARS WITH WHITE CEMENT AND PORTLAND CEMENT
    (SERBAN SOLACOLU FOUNDATION) Öztürk, AU; Kaplan, G
    Workability, strength and durability are among the most important properties when working with concrete. Increased compressive strength of concrete has favorable impact on durability along with on its several other features. To ensure a high degree of durability, it is essential that clean, sound materials and the lowest possible water content are used in the concrete, together with thorough mixing. Good consolidation during placement of the concrete is important, as are proper curing and protection of the concrete during the early hardening period, which assure favorable conditions of temperature and moisture. Cure concrete properly for a minimum of three days in order to develop good durability. In this study mortars with white cement and Portland cement and different w/c ratios were produced and investigated. The mortars produced were then tested for the impacts of alkali silica reaction (ASR), high temperatures, abrasion and acid effect. Results show that less expansion was measured on the mortars using portland cement while the white cement gave the largest expansions (approximate 0.60%).However, there was no significant difference between cements in terms of their acid resistance. The impact of higher temperatures on mortars produced using white cement was less in comparison with normal Portland cement. Durability tests showed that w/c ratio plays an important role.
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    Investigation of gamma-ray attenuation parameters of some materials used in dental applications
    (ELSEVIER) Abbasova, N; Yüksel, Z; Abbasov, E; Gülbiçim, H; Tufan, MÇ
    Radiological parameters of composite filler, zirconium and acrylic coating materials used in dental treatment are determined. Mass attenuation coefficients (mu(m)) of these materials have been experimentally determined for 9 different gamma energies emitting from Ra-226 and Eu-152 radioactive sources by using gamma spectrometry system with (3 '' x 3 '') NaI(Tl) detector. Effective atomic and electron numbers (Z(eff), N-eff), atomic and electronic cross sections (sigma(t,a) and sigma(t,el)) have been also obtained for these materials. The obtained results were compared with the NIST database and EGSnrc Monte Carlo (MC) code. It is found that general trends of these parameters are consistent with the literature. The maximum attenuation occurs at 122 keV and it has been found for 1 mm thick samples that 21%, 10% and 2% of the incident radiation have been absorbed by the zirconium, composite and acrylic samples, respectively.
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    Enhancing thermal efficiency and durability of sintered clay bricks through incorporation of polymeric waste materials
    (ELSEVIER SCI LTD) Erdogmus, E; Sutcu, M; Gencel, O; Kazmi, SMS; Munir, MJ; Velasco, PM; Ozbakkaloglu, T
    This pioneering study investigates the use of expanded polystyrene (EPS) and waste rubber tyre powder (WRTP) in sintered clay bricks for eco-friendly and cleaner buildings. Different ratios of EPS and WRTP were mixed with clay and sintered at 1000 degrees C. Advanced material characterization techniques were used to evaluate the materials, and physical, mechanical, and durability tests were performed on the bricks. The findings show that higher doses of EPS and WRTP increased the bricks' thermal efficiency and reduced their weight. Brick specimens with 0.5% EPS dosage met the weathering resistance requirements, and those with 0.5% EPS dosage and 5% WRTP dosage met the minimum compressive strength standards. The study offers valuable insights into the potential appli-cations of EPS and WRTP in producing clean and sustainable polymer waste bricks to improve brick performance and efficient waste management in the construction industry.
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    INFLUENCE OF THE AIR-ENTRAINING ADMIXTURE WITH DIFFERENT SUPERPLASTICIZERS ON THE FREEZE-THAW RESISTANCE OF CEMENT MORTARS
    (SERBAN SOLACOLU FOUNDATION) Ozturk, AU; Erdem, RT
    Compatibility of different based superplasticizers with air-entraining admixture has been investigated. Physical and mechanical properties such as flow, setting time and compressive strength of cement mortars incorporating an air-entraining admixture (HS) with naphthalene sulfonate (SPNS) and modified polymer (SPMP) based admixtures have been determined. Also, the effects of their combinations on the freeze-thaw resistance of cement mortars have been determined. All admixtures are used with three different ratios and one of them is for overdosage effect. Results indicate that cement mortars having lowest early strength values are mortars incorporating 1.5% SPMP and 2.0% SPNS by mass of cement. The most effective series for the ultimate highest strength values were series with 0.05 % HS and 0.8 % SPMP. The freeze-thaw resistances of cement mortars were investigated for 50, 100, 150 and 200 freeze-thaw cycles. Indeed, the most effective series for freeze-thaw resistance were series with 0.05 % HS and 0.8 % SPMP.
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    Evaluation of blends tincal waste, volcanic tuff, bentonite and fly ash for use as a cement admixture
    (ELSEVIER) Abali, Y; Bayca, SU; Targan, S
    The evaluation of blends tincal waste (TW), fly ash (FA), bentonite (BE), volcanic tuff (VT) for use as a cement admixture was investigated. The properties examined include setting time, expansion, water requirement, specific surface and compressive strength of cement mixtures. The results revealed that the early compressive strength decrease with increasing tincal waste, due to tincal waste increasing initial setting time of the cement. The tincal waste and volcanic tuff of cement mixtures increased and there was reduction in compressive strength. The more the tincal waste increased the greater retardation there was initial setting time this may be attributed to containing high amount B2O3 and MgO content. The tincal waste and fly ash increased with expansion increased. Water requirement increased as the Blaine fineness of the cement mixtures increased. The results obtained were compared with standards and five batches were advised as suitable for the standard. (c) 2005 Published by Elsevier B.V.
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    EVALUATION AND OPTIMIZATION OF PVA REINFORCED CEMENTITIOUS COMPOSITE CONTAINING METAKAOLIN AND FLY ASH
    (SERBAN SOLACOLU FOUNDATION) Calis, G; Akpinar, ME; Yildizel, SA; Çögürcü, MT
    Due to high consumption of natural sources in the production of cement, scholars have been studying alternative materials that can replace cement in the concrete. Metakaolin and fly ash are used by scholars for their chemical properties and filler effect as pozzolanic material. In this study effect of PVA fiber, metakaolin and fly ash in concrete samples are investigated. The number of experiments to be carried out was reduced to 25 with the Taguchi optimization method, in this research. In addition, the recommended mixing ratios were obtained by this preliminary optimization study. Taguchi optimization were applied according to the experimental test results. F-value comparison of each ingredients were analyzed via ANOVA to list the most effective factors on the strengths based on the Taguchi optimization results. Later Response Surface Design was applied to the output parameters of the ANOVA and Taguchi methods to obtain better and detailed clarifications of relations between the input parameters and the strengths.
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    Influence of colemanite admixture on Portland cement durability
    (ICE PUBLISHING) Erdogmus, E; Targan, S; Erdogan, Y; Avciata, U; Gencel, O
    In this study, the compressive strength of mortar prepared by Portland cement (PC) and different proportions of blast furnace slag, fly ash and colemanite concentrator waste was examined at the end of the 2nd, 7th, 28th, 60th and 90th days. Moreover, some mortars were kept in 50 g/l sodium sulfate (Na2SO4) solution according to ASTM C1012 for 6 months to determine their sulfate resistance. The first length of some mortars made with alkali reactive sand together with additives mentioned above or PC according to ASTM C1260 was measured to detect their alkali-aggregate reaction resistance and then their final lengths were measured after being kept in 1 M sodium hydroxide (NaOH) solution at a temperature of 80 degrees C for 14 days. The results were compared both among themselves and with Portland cement. In addition, the microstructures of some samples scanned by scanning electron microscopy were photographed. It was found that all the additives had positive effects on sulfate and ASR resistance.
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    RAGN-L: A stacked ensemble learning technique for classification of Fire-Resistant columns
    (PERGAMON-ELSEVIER SCIENCE LTD) Çiftçioglu, AÖ
    One of the main challenges in using reinforced concrete materials in structures is to comprehend their fire resistance. The assessment of fire resistance can be performed in a laboratory environment using fire. However, such tests are time-consuming and expensive, and they may not provide a complete assessment of all relevant properties of a particular tested specimen. To that end, the implementation of machine learning (ML) in the investigation of fire-resistant structural performance would be beneficial, as it would also contribute to the reduction of time and cost problems related to traditional techniques. Here, this research proposes a novel ensemble ML approach to classify columns according to their fire resistance characteristics, supporting the application of ML techniques by fire engineers and scientists. The proposed model, named RAGN-L, combines Random Forest, Adaptive Boosting, and Gradient Naive Bayes, and is stacked using the Logistic Regression approach. RAGN-L is evaluated on real-world databases of reinforced concrete columns and concrete-filled steel tube columns, as well as a synthetic database generated by the TVAE deep learning model. The performance of the proposed solution is compared with ten different ML classifiers based on common statistical metrics, accu-racy, precision, recall, and f1-score, and validated using the k-fold cross-validation approach. The developed algorithm outperforms ten different classifiers in all databases, with classification accuracies of 86.6%, and 99.6% for the real-world and synthetic databases of reinforced concrete columns, respectively, and 88.1% for the real-world database of concrete-filled steel tube columns.