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    Effect of pumice powder and artificial lightweight fine aggregate on self-compacting mortar
    (Techno-Press, 2021) Etli, Serkan; Cemalgil, Selim; Onat, Onur
    An experimental program was conducted to investigate the fresh properties, mechanical properties and durability characteristics of the self-compacting mortars (SCM) produced with pumice powder and Artificial Lightweight Fine Aggregate (aLWFA). aLWFA was produced by using fly ash. A total of 16 different mixtures were designed with a constant water-binder ratio of 0.37, in which natural sands were partially replaced with aLWFA and pumice powder at different volume fractions of 5%, 10% and 15%. The artificial lightweight aggregates used in this study were manufactured through cold bonding pelletisation of 90% of class-F fly ash and 10% of Portland cement in a tilted pan with an ambient temperature and moisture content. Flowability tests were conducted on the fresh mortar mixtures beforehand, to determine the self-compacting characteristics on the basis of EFNARC. To determine the conformity of the fresh mortar characteristics with the standards, mini-slump and mini-V-funnel tests were carried out. Hardened state tests were conducted after 7, 28 and 56 days to determine the flexural strength and axial compressive strength respectively. Durability, sorptivity, permeability and density tests were conducted at the end of 28 days of curing time. The test results showed that the pumice powder replacement improved both the fresh state and the hardened state characteristics of the mortar and the optimum mixture ratio was determined as 15%, considering other studies in the literature. In the aLWFA mixtures used, the mechanical and durability characteristics of the modified compositions were very close to the control mixture. It is concluded in this study that mixtures with pumice powder replacement eliminated the negative effects of the aLWFA in the mortars and made a positive contribution.
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    Effect of waste textile dye adsorbed almond shell on self compacting mortar
    (Elsevier Sci Ltd, 2021) Cemalgil, Selim; Onat, Onur; Tanaydin, Mehmet Kayra; Etli, Serkan
    The aim of the current experimental study is to investigate the effect of waste textile dye absorbed almond shell on fresh and mechanical characteristics of self-compacting mortar (SCMs). In this context, eight SCMs were designed by substituting Violet Dye Solution adsorbed Almond shell (VDSA) at the rate of 0%, 2.5%, 5.0%, 7.5%, 10.0%, 12.5%, 15.0% and 17.5% as a cement on weight basis including the control mix. To measure the rheological properties of SCMs, mini slump and V-Funnel tests were conducted. A total of 72 beams of 40x40x160 mm(3) dimension specimens were casted and immersed in water curing at the end of the 7, 28 and 56 days to determine the mechanical parameters. 48 cubes of 50x50x50 mm(3) dimensions were casted and kept in the curing tank to determine durability characteristics such as porosity, sorptivity and specific gravity. Quantitative analyses are also performed by using Scanning Electron Microscopes (SEM), X-ray Diffraction Analysis (XRD), Energy-Dispersive X-ray Spectroscopy (EDS) and Fourier Transform Infrared (FTIR). The experimental results indicated that as the content of VDSA enchases, a remarkable enhancement in flexural strength at early days age and 28 days age strength. Whereas, increasing the content of VDSA resulted in a considerable decrease in compressive strength higher than 5%. (C) 2021 Elsevier Ltd. All rights reserved.
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    An Estimation Proposal for Engineering Properties of Modified Concrete by using Standalone and Hybrid GRELM
    (Springer Int Publ Ag, 2023) Cemalgil, Selim; Onat, Onur; Aruntas, Hueseyin Yilmaz
    The presented study pertains to an attempt to propose a novel prediction model to predict the flexural and compressive strengths of concrete modulated using steel fiber (SFb) and silica fume (SF). A completed experimental investigation is adopted for the current study, and a research plan is employed. Three different superplasticizers amount (SP), different SF replacement ratios, and a constant amount of SFb were used by the weight of cement to meet the C25 target strength. A sum of 16 distinct mixtures designed by changing SP and SF ratios were developed. Furthermore, SFb was added at a fixed rate of 65 kg/m(3) to all planned concrete mixes. In addition, SFb was used to create a 16-mix design. Finally, a total of 32 distinct mix designs were created. Produced, hardened specimens were exposed to two different curing conditions. This research uses the mechanical characteristics of concrete treated with SF, SP, and SFb to estimate by conducting standalone and hybridized generalized extreme learning machine (GRELM) algorithms based on available experimental data in terms of the metaheuristic aspects of this work. With continuous input data, four separate data sets were constructed. Compressive strength and flexural strength were estimated separately. With the aid of the Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) algorithms, binary and ternary hybrid approaches were developed and tested on the data. Four distinct estimation models were suggested. Two quality metrics were used to evaluate the estimation performance: Root Mean Square Error (RMSE) and correlation of determination (R-2). The estimation results showed that the hybridized GRELM-PSO-GWO estimation model that was built for prediction was relatively successful in all sets.
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    Field reconnaissance and structural assessment of the October 30, 2020, Samos, Aegean Sea earthquake: an example of severe damage due to the basin effect
    (Springer, 2022) Onat, Onur; Yon, Burak; Oncu, Mehmet Emin; Varolgunes, Sadik; Karasin, Abdulhalim; Cemalgil, Selim
    An earthquake with a magnitude ranging from Mw = 6.9 (KOERI) to Mw = 7.0 (USGS) struck Samos Island in the Aegean Sea on October 30, 2020, with an epicentre 70 kms from the Izmir city centre in Turkey. The earthquake took place at 14:51 local time (11:51 UTC). The peak ground acceleration (PGA) of this earthquake was recorded to be 0.179 g at the epicentre of the earthquake. This earthquake occurred at a depth of 17.26 km (AFAD (2020) Izmir Earthquake Report, (In Turkish)) and lasted 16 s. The main shock from the earthquake triggered a tsunami that hit the building stocks built near the coast. During the gradual deregulation of COVID-19 pandemic regulations, various events caused considerable damage to the building stock, particularly in the Izmir Seferihisar and Bayrakli regions and resulted in a massive disruption of daily habits. The main shock caused 117 deaths in both Turkey and Greece, and 1632 people were also injured in Turkey. Moreover, several injuries occurred in Greece. A total of 103 buildings collapsed, 700 were severely damaged, 814 buildings were moderately damaged, and 7889 were slightly damaged. The basic aim of this paper is to briefly present the past and present seismotectonic characteristics of the region, present building stock, and former structural conditions before the earthquake, assess structural performance and classify distinguished earthquake-induced failures and damage due to the basin effect.
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    A novel prediction model for durability properties of concrete modified with steel fiber and Silica Fume by using Hybridized GRELM
    (Elsevier Sci Ltd, 2022) Cemalgil, Selim; Gul, Enes; Onat, Onur; Aruntas, Hilseyin Yilmaz
    The service life performance of conventional and modified concrete subjected to harsh climatic condition environment is directly related to durability properties of concrete like abrasion, freezing and thawing cycles. These properties are critical issues that should be predicted before performing experimental test. On this basis, the basic purpose of this paper is to predict the abrasion loss, freezing and thawing properties of concrete modified with silica fume (SF) and steel fiber (SFb) by using mix design and additional properties. From this point of view, a conducted experimental study was selected as a case study. In the control concrete (CC) mixtures, Portland cement, crushed stone aggregate, and superplasticizer (SP) were used in the selected experimental study. SP in concrete mixtures was used in the amounts of 1.0%, 1.5%, and 2.0% by weight of cement, and so modified concrete was produced with and without SFb according to the target strength of C25. Furthermore, SF and SFb were used in different amounts to modify the concrete. The SF was replaced with cement in the amounts of 7.5%, 10.0%, and 15.0%. In total, 16 different mix designs were prepared with different SP and SF ratios. In addition, SFb was added to all mixtures of designed concrete at a constant amount of 65 kg/m3. Additionally, a 16-mix design was prepared with SFb. Cumulatively, 32 different mix designs were prepared for the experimental study. Tests on the fresh, hardened, and life-cycle performance properties of the concrete were conducted. As for the metaheuristic part of this study, on the basis of the available experimental data, life-cycle performance parameters of the concrete modified with SF and SFb are predicted by using single and hybrid generalized extreme learning machine methods. Eight different data sets were generated with gradually extended input data. Two different outputs were considered: abrasion resistance (AL) and freezing/thawing (FT). Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) algorithms were used to produce binary and ternary hybrid methods. Four different models were proposed as listed: single use of Generalized Extreme Learning Machine (GRELM), binary use of GRELM-PSO, and GRELM-GWO. Finally, PSO and GWO were hybridized and integrated into GRELM. Two quality indicators, namely Root Mean Square Error (RMSE) and correlation of determination (R2), were considered to see the performance of the prediction. The results showed that the proposed ternary prediction model composed of GRELM-PSO-GWO provided more accurate results in all sets from 74% to 91% by extending input parameters, even if complicated parameters are inserted in as an input to the data set.