Article
Construction & Building Technology
Panagiotis G. Asteris, Paulo B. Lourenco, Panayiotis C. Roussis, Chryssi Elpida Adami, Danial J. Armaghani, Liborio Cavaleri, Constantin E. Chalioris, Mohsen Hajihassani, Minas E. Lemonis, Ahmed S. Mohammed, Kypros Pilakoutas
Summary: A model for estimating the compressive strength of concretes incorporating metakaolin was developed and evaluated using soft computing techniques. The model took into account six parameters as input data and was able to accurately estimate the compressive strength, considering the usage of metakaolin. The study highlighted the nonlinear influence of mix components on the resulting concrete compressive strength.
CONSTRUCTION AND BUILDING MATERIALS
(2022)
Article
Construction & Building Technology
Ngoc-Tra-My Lam, Duy-Liem Nguyen, Duc-Hien Le
Summary: This study presents analytical models (including multiple regression analysis, artificial neural networks, and fuzzy logic) to predict the compressive strength of roller-compacted concrete pavement (RCCP) containing steel slag aggregate and fly ash. The performance of the fuzzy logic model is as good as the artificial neural networks model in predicting the compressive strength.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2022)
Article
Construction & Building Technology
Mohammed Abdul Qader, Ahmed Ibrahim, Al-Badr Alaidaros, Abdul Kareem Abdulkareem, Abdullah Alwuayl, Abdullah Alsaluli, Mamdooh Alwetaishi, Mishal Alsehli, Saleh Alghamdi
Summary: This paper develops algorithms to design and compare concrete mixes, improving efficiency, accuracy, and user-friendliness. Comparisons show that different design methods suggest similar mix proportions for a given compressive strength, with ACI method being more costly. These comparisons are crucial for engineers' decision-making.
ADVANCES IN CIVIL ENGINEERING
(2022)
Article
Chemistry, Multidisciplinary
David Suescum-Morales, Lorenzo Salas-Morera, Jose Ramon Jimenez, Laura Garcia-Hernandez
Summary: This article introduces a novel method using artificial neural network model to predict the compressive strength of recycled aggregate concrete, demonstrating its efficiency in dealing with heterogeneous and noisy data through different training methods and a large dataset of concrete mixes.
APPLIED SCIENCES-BASEL
(2021)
Retraction
Computer Science, Artificial Intelligence
Gholamreza Khalaj, Hossein Yoozbashizadeh, Alireza Khodabandeh, Ali Nazari
Summary: The article was retracted by the Editor-in-Chief due to significant overlap with other articles, including those under consideration at the same time and previously published ones.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Chemistry, Multidisciplinary
Chia-Ju Lin, Nan-Jing Wu
Summary: An artificial neural network model for predicting the compressive strength of concrete was established, validated using experimental data, and a prediction formula was provided.
APPLIED SCIENCES-BASEL
(2021)
Article
Chemistry, Multidisciplinary
Sina Rezvan, Mohammad Javad Moradi, Hamed Dabiri, Kambiz Daneshvar, Moses Karakouzian, Visar Farhangi
Summary: One practical solution to address the environmental impacts of plastic bottle waste is to incorporate them into concrete, a commonly used material in construction industry. Studies have shown that using polyethylene terephthalate (PET) fiber as reinforcement in concrete can significantly enhance its compressive strength. This research utilized a machine learning approach to investigate the benefits of PET fiber in concrete, providing guidance for engineers and stakeholders to utilize these recycled materials.
APPLIED SCIENCES-BASEL
(2023)
Article
Mathematics, Interdisciplinary Applications
Ghodrat Rahchamani, Seyed Mojtaba Movahedifar, Amin Honarbakhsh
Summary: This paper proposes an automated approach based on machine learning strategies to predict the compressive strength of concrete. By analyzing experimental data, the proposed method accurately predicts the quality of concrete and the amount of raw materials used and achieves the best quality concrete with an error rate of less than 5%.
Article
Nuclear Science & Technology
Mohamed A. Saafan, Zeinab A. Etman, Abdelrahman S. Jaballah, Mohamed A. Abdelati
Summary: This study evaluates the performance of heavyweight concrete for nuclear shielding applications through experimental work and theoretical analysis. Different coarse aggregates, including crushed dolomite, magnetite, and steel, were used to prepare heavyweight concrete mixes. The compressive strength and workability of fresh concrete were evaluated, and the attenuation coefficient was determined using gamma-ray spectrometry. The results showed that concrete mixes containing steel achieved the most desirable performance in terms of density and gamma-attenuation, while the mixes incorporating magnetite had the highest compressive strength.
PROGRESS IN NUCLEAR ENERGY
(2023)
Article
Construction & Building Technology
Yousef el Asri, Mouhcine Benaicha, Mounir Zaher, Adil Hafidi Alaoui
Summary: This article summarizes the use of artificial neural networks to model the compressive strength of self-compacting concrete (SCC) based on rheological parameters and viscosity values. After training multiple models, the optimal model architecture is determined to be 5-50-50-1 with a high correlation coefficient.
STRUCTURAL CONCRETE
(2022)
Review
Chemistry, Physical
Zhanzhao Li, Jinyoung Yoon, Rui Zhang, Farshad Rajabipour, Wil V. Srubar, Ismaila Dabo, Aleksandra Radlinska
Summary: Concrete science has made progress, but concrete formulation remains challenging. Machine learning has transformative potential and has been widely used in concrete research. It is necessary to understand methodological limitations and formulate best practices to fully exploit the capabilities of machine learning models.
NPJ COMPUTATIONAL MATERIALS
(2022)
Article
Construction & Building Technology
Amir Ali Shahmansouri, Maziar Yazdani, Mehdi Hosseini, Habib Akbarzadeh Bengar, Hamid Farrokh Ghatte
Summary: The study demonstrates the potential of using artificial neural networks to predict the compressive strength and electrical resistivity of natural zeolitic concrete, significantly speeding up the process and improving accuracy. Experimental results from 324 different designs of natural zeolitic concrete specimens validate the accuracy and reliability of the model. This has important implications for cost reduction and time saving.
CONSTRUCTION AND BUILDING MATERIALS
(2022)
Article
Construction & Building Technology
Nzar Shakr Piro, Ahmed Salih Mohammed, Samir M. Hamad
Summary: This study establishes mathematical models for predicting the compressive strength and electrical resistivity of concrete with steel slag aggregate substitution by collecting and analyzing a large amount of literature data. The artificial neural network model performs the best in predicting both properties, with high coefficients of determination and small root mean square errors.
CONSTRUCTION AND BUILDING MATERIALS
(2022)
Article
Engineering, Civil
Pan Hu, Zohre Moradi, H. Elhosiny Ali, Loke Kok Foong
Summary: This study evaluates the efficiency of three metaheuristic algorithms for optimizing the performance of a multi-layer perceptron system and finds that these algorithms can significantly improve training and prediction accuracy. The proposed models are capable of providing early, inexpensive, and reliable predictions of the compressive strength of concrete.
SMART STRUCTURES AND SYSTEMS
(2022)
Article
Construction & Building Technology
Panagiotis G. Asteris, Athanasia D. Skentou, Abidhan Bardhan, Pijush Samui, Paulo B. Lourenco
Summary: This study compared conventional soft computing techniques in estimating concrete compressive strength using non-destructive tests, finding that the BPNN model provided the most accurate predictions based on ultrasonic pulse velocity and rebound number values, thus assisting engineers in improving the accuracy of predicting concrete compressive strength during the design phase of civil engineering projects.
CONSTRUCTION AND BUILDING MATERIALS
(2021)
Article
Chemistry, Analytical
Alper Ozseven, Iskender Akkurt
Summary: This study investigated the natural radioactivity level of Egirdir Lake surface water in Isparta province of Turkey and found that the gross-alpha and gross-beta activity concentrations were lower than the suggested limits of WHO screening procedure, indicating that the lake water is suitable for drinking as well as other purposes.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL ANALYTICAL CHEMISTRY
(2022)
Article
Mechanics
Semsettin Kilincarslan, Yasemin Simsek Turker
Summary: Glulam columns and beams are structural wood engineering products formed by gluing timbers together, commonly using steel, aluminum, or wood at joints. Recent emphasis has been on non-metallic fasteners due to corrosion and heat resistance issues. This study focuses on strengthening glulam column-beam joints with carbon fiber reinforced polymer, showing increased strength and durability in the connection area.
COMPOSITE STRUCTURES
(2021)
Article
Materials Science, Ceramics
Recep Kurtulus, Taner Kavas, Iskender Akkurt, Kadir Gunoglu
Summary: The study investigated the gamma-rays shielding characteristics of waste soda-lime glass containing lanthanum oxide and gadolinium oxide. It was found that the addition of these substances increased the linear attenuation coefficient, with good agreement between experimental measurements and theoretical calculations.
CERAMICS INTERNATIONAL
(2021)
Article
Engineering, Electrical & Electronic
Y. S. Rammah, I. O. Olarinoye, F. I. El-Agawany, Iskender Akkurt, E. Yousef
Summary: The study investigated the photon and neutron absorbing capacity of titanate-doped borate glasses coded as G1-G7, with results showing that higher titanate doping concentrations led to better shielding capacities compared to traditional materials like concrete and water. The glasses showed superior shielding efficacy and are recommended for use as ionizing radiation shields.
JOURNAL OF MATERIALS SCIENCE-MATERIALS IN ELECTRONICS
(2021)
Article
Materials Science, Multidisciplinary
Aljawhara H. Almuqrin, M. Sayyed, Ashok Kumar, B. O. El-bashir, I Akkurt
Summary: The fabrication of TePbMgX glass system was done using the standard melt quenching method. Increasing the PbO content in the glasses resulted in a decrease in moduli values and band gap energies. The study showed that the glass system has highly effective attenuation performance for low energy radiation and becomes worse attenuators for high energy radiation.
Article
Physics, Multidisciplinary
Iskender Akkurt, Roya Boodaghi Malidarre, Taner Kavas
Summary: Monte Carlo simulation is an important tool for obtaining material parameters when experiments are not possible, and the study of radiation shielding is crucial for various fields. Research on the radiation shielding properties of materials like glass is a popular subject, and simulations can be compared with calculation results to analyze their effectiveness.
EUROPEAN PHYSICAL JOURNAL PLUS
(2021)
Article
Engineering, Electrical & Electronic
Roya Boodaghi Malidarre, Iskender Akkurt
Summary: The present study investigates the neutron-gamma attenuation characteristics of TeO2-Bi2O-PbO-MgO-B2O3 glasses using MCNPX simulation and theoretical calculations. The glass sample TePbMg5 exhibits superior shielding ability compared to other materials. Various attenuation parameters and gamma spectrum for shielding materials were analyzed to evaluate the performance of the glasses in shielding neutron and gamma radiation.
JOURNAL OF MATERIALS SCIENCE-MATERIALS IN ELECTRONICS
(2021)
Article
Engineering, Electrical & Electronic
Recep Kurtulus, Taner Kavas, Iskender Akkurt, Kadir Gunoglu, H. O. Tekin, Cansu Kurtulus
Summary: The study investigated a novel glass system in terms of physical properties and radiation shielding competencies. Increasing the amount of Bi2O3 in substitution for SiO2 increased the glass density, while XRD patterns showed non-crystallinity in the ABS series. The glass with the highest Bi2O3 content (ABS4) exhibited the highest mass attenuation coefficient (MAC).
JOURNAL OF MATERIALS SCIENCE-MATERIALS IN ELECTRONICS
(2021)
Article
Materials Science, Ceramics
Recep Kurtulus, Taner Kavas, K. A. Mahmoud, Iskender Akkurt, Kadir Gunoglu, M. I. Sayyed
Summary: This study examined the potential use of waste soda-lime-silica (SLS) glass with varying MoO3 content in radiation shielding applications. The glass samples were found to have an amorphous structure and transparent appearance, with density and refractive index values increasing with higher MoO3 content. Experimental evaluation of the gamma-ray shielding ability showed an increase in linear attenuation coefficient (LAC) with increasing MoO3 ratio, confirming good agreement between experimental and theoretical calculations.
JOURNAL OF NON-CRYSTALLINE SOLIDS
(2021)
Article
Thermodynamics
M. Davraz, M. Koru, A. E. Akdag, S. Kilincarslan, Y. E. Delikanli, M. Cabuk
Summary: The study investigated the production potential of foam glass with a low apparent density using waste glass powder and foaming agents. By testing different types of waste glass and additives, the optimal production parameters for ultra-light foam glass were determined, resulting in foam glass samples with desired properties.
JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY
(2022)
Article
Materials Science, Multidisciplinary
Y. S. Rammah, I. O. Olarinoye, F. El-Agawany, K. A. Mahmoud, Iskender Akkurt, ElSayed Yousef
Summary: The study on the effects of antimony trioxide on ternary tellurite-vanadium-antimonite glasses revealed that increasing the Sb2O3 insertion ratio significantly enhances the shielding capacity of the glasses, making them good candidates for various nuclear protection applications.
Article
Polymer Science
Roya Boodaghi Malidarre, Iskender Akkurt
Summary: This study investigated the neutron-gamma photon efficiency of two vinyl ester composites using MCNPX Monte Carlo Simulation Code, analytical calculations, and newly developed software. Results showed different characteristics in neutron-gamma photon spectra and fast neutron shielding capacity between colemanite and barite vinyl ester series.
Article
Environmental Sciences
Iskender Akkurt, Parisa Boodaghi Malidarreh, Roya Boodaghi Malidarre
Summary: This study examines the shielding qualities of non-lead ceramic materials using FLUKA code and artificial neural network algorithm. The results show that increasing the concentration of a certain component in the material improves its density and neutron attenuation parameter, thereby enhancing its shielding ability.
ENVIRONMENTAL TECHNOLOGY
(2023)
Article
Environmental Sciences
Mucize Sarihan, Roya Boodaghi Malidarre, Iskender Akkurt
Summary: The present study investigates the shielding performance of charged-uncharged particles with the addition of a mixed type of cathode ray tube (CRT) in a glass system. The results show that CG1 glass sample has the best neutron attenuation and increasing the density of the glass leads to a higher linear attenuation coefficient. Additionally, CG1 glass structure demonstrates better capacity in stopping proton and alpha particles compared to other glass structures.
ENVIRONMENTAL TECHNOLOGY
(2023)
Article
Physics, Multidisciplinary
Iskender Akkurt, Faez Waheed, Hakan Akyildirim, Kadir Gunoglu
Summary: Radiation measurement is crucial in radiation physics to assess its potential impact on human health. The NaI(Tl) crystal is commonly used due to its cost-effectiveness and resistance to thermal effects. The performance of a detector system is important in determining absolute radiation values, with parameters measured using radioactive sources like Na-22, Cs-137, and Co-60 in this study.
INDIAN JOURNAL OF PHYSICS
(2022)
