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Dr. Zaher Yaseen
Ton Duc Thang University, Ho Chi Minh City, Vietnam

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0 Civil Engineering
0 Climate
0 Water Resources Engineering
0 Hydrology analysis
0 Material Science

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Journal article
Published: 14 August 2021 in Composite Structures
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This paper presents an experimental study on the impact performance of concrete columns confined with large-rupture-strain (LRS, rupture strain≥5%) fiber reinforced polymer (FRP) jackets. A total of 32 concrete specimens were prepared and tested using large-capacity drop-weight equipment. The test variables included four impact height (2, 3, 4 and 5 m), types of FRP, i.e., AFRP, polyethylene naphthalate (PEN) FRP and polyethylene terephthalate (PET) FRP and layers of FRP (1 and 2). The time histories of impact force and FRP rupture strain as well as failure modes were obtained from the test. Compared to the AFRP-confined concrete specimen with similar jacket stiffness, the core concrete of the LRS FRP-confined specimen was less damaged due to the large rupture strain characteristic. The impact force increased and the impact duration decreased with increasing impact height. The impact duration of specimens confined with LRS FRP was longer than that of the AFRP-confined concrete. Results showed that the impact-resistance behaviours of LRS FRP-confined concrete column outperformed its companion column confined with AFRP. Besides, increasing the thickness of FRP jacket can enhance the impact resistance capacity. These findings may facilitate the impact resistance strengthening/retrofitting of RC structures with the application of LRS FRP composites.

ACS Style

Zhi-Wei Yan; Yu-Lei Bai; Togay Ozbakkaloglu; Wan-Yang Gao; Jun-Jie Zeng. Axial impact behavior of Large-Rupture-Strain (LRS) fiber reinforced polymer (FRP)-confined concrete cylinders. Composite Structures 2021, 276, 114563 .

AMA Style

Zhi-Wei Yan, Yu-Lei Bai, Togay Ozbakkaloglu, Wan-Yang Gao, Jun-Jie Zeng. Axial impact behavior of Large-Rupture-Strain (LRS) fiber reinforced polymer (FRP)-confined concrete cylinders. Composite Structures. 2021; 276 ():114563.

Chicago/Turabian Style

Zhi-Wei Yan; Yu-Lei Bai; Togay Ozbakkaloglu; Wan-Yang Gao; Jun-Jie Zeng. 2021. "Axial impact behavior of Large-Rupture-Strain (LRS) fiber reinforced polymer (FRP)-confined concrete cylinders." Composite Structures 276, no. : 114563.

Original article
Published: 13 August 2021 in Neural Computing and Applications
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Relative humidity (RH) is one of the important processes in the hydrology cycle which is highly stochastic. Accurate RH prediction can be highly beneficial for several water resources engineering practices. In this study, extreme gradient boosting (XGBoost) approach “as a selective input parameter” was coupled with support vector regression, random forest (RF), and multivariate adaptive regression spline (MARS) models for simulating the RH process. Meteorological data at two stations (Kut and Mosul), located in Iraq region, were selected as a case study. Numeric and graphic indicators were used for model’s evaluation. In general, all models revealed good prediction performance. In addition, research finding approved the importance of all the meteorological data for the RH simulation. Further, the integration of the XGBoost approach managed to abstract the essential parameters for the RH simulation at both stations and attained good predictability with less input parameters. At Kut station, RF model attained the best prediction results with minimum root mean square error (RMSE = 4.92) and mean absolute error (MAE = 3.89) using maximum air temperature and evaporation parameters. Whereas MARS model reported the best prediction results at Mosul station using all the utilized climate parameters with minimum (RMSE = 3.80 and MAE = 2.86). Overall, the research results evidenced the capability of the proposed coupled machine learning models for modeling the RH at different coordinates within a semi-arid environment.

ACS Style

Hai Tao; Salih Muhammad Awadh; Sinan Q. Salih; Shafik S. Shafik; Zaher Mundher Yaseen. Integration of extreme gradient boosting feature selection approach with machine learning models: application of weather relative humidity prediction. Neural Computing and Applications 2021, 1 -19.

AMA Style

Hai Tao, Salih Muhammad Awadh, Sinan Q. Salih, Shafik S. Shafik, Zaher Mundher Yaseen. Integration of extreme gradient boosting feature selection approach with machine learning models: application of weather relative humidity prediction. Neural Computing and Applications. 2021; ():1-19.

Chicago/Turabian Style

Hai Tao; Salih Muhammad Awadh; Sinan Q. Salih; Shafik S. Shafik; Zaher Mundher Yaseen. 2021. "Integration of extreme gradient boosting feature selection approach with machine learning models: application of weather relative humidity prediction." Neural Computing and Applications , no. : 1-19.

Short communication
Published: 13 August 2021 in Case Studies in Construction Materials
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Glass Fibre Reinforced Polymer (GFRP) composite wrap has become an effective repair system for deteriorated structural columns. It is essential to provide an infill material in the gap between the retrofitted column and the GFRP wrap. So, the properties of the infill material can significantly influence the contribution of these wraps and thus, can affect the overall performance of the retrofitted structure. However, the research on the effect of GFRP confinement on infill materials with various properties is still limited. This study explores the effectiveness of the GFRP wrapping system and its contribution to the axial compression behaviour of concrete, grout and epoxy infill materials. A total of 18 unconfined and GFRP-wrapped cylindrical columns were cast and tested under concentric axial compression loading. A finite element (FE) modelling was implemented using ABAQUS software to analyse the compression behaviour of GFRP-wrapped infill materials. The experimental results demonstrated that the confinement effect of the GFRP wrapping system is highly influenced by the properties of the infill material. The compressive strength and modulus of elasticity significantly increased due to GFRP wrapping by 149% and 77%, respectively for concrete infill, and by 40 % and 72 %, respectively for grout infill whereas negligible confinement efficiency observed in wrapped epoxy infill. The FE analyses showed a good correlation with the experimental results in predicting the overall compressive behaviour of the various infill materials. This study demonstrates valuable insights on the confinement effect of GFRP wraps in the repair of columns involving infill materials which therefore could be employed to better understand the overall behaviour of columns retrofitted with GFRP wrapping systems.

ACS Style

Omar F. Otoom; Weena Lokuge; Warna Karunasena; Allan C. Manalo; Togay Ozbakkaloglu; David Thambiratnam. Experimental and numerical evaluation of the compression behaviour of GFRP-wrapped infill materials. Case Studies in Construction Materials 2021, 15, e00654 .

AMA Style

Omar F. Otoom, Weena Lokuge, Warna Karunasena, Allan C. Manalo, Togay Ozbakkaloglu, David Thambiratnam. Experimental and numerical evaluation of the compression behaviour of GFRP-wrapped infill materials. Case Studies in Construction Materials. 2021; 15 ():e00654.

Chicago/Turabian Style

Omar F. Otoom; Weena Lokuge; Warna Karunasena; Allan C. Manalo; Togay Ozbakkaloglu; David Thambiratnam. 2021. "Experimental and numerical evaluation of the compression behaviour of GFRP-wrapped infill materials." Case Studies in Construction Materials 15, no. : e00654.

Review
Published: 30 July 2021 in Materials
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Development of sustainable concrete as an alternative to conventional concrete helps in reducing carbon dioxide footprint associated with the use of cement and disposal of waste materials in landfill. One way to achieve that is the use of fly ash (FA) as an alternative to ordinary Portland cement (OPC) because FA is a pozzolanic material and has a high amount of alumina and silica content. Because of its excellent mechanical properties, several studies have been conducted to investigate the use of alkali-activated FA-based concrete as an alternative to conventional concrete. FA, as an industrial by-product, occupies land, thereby causing environmental pollution and health problems. FA-based concrete has numerous advantages, such as it has early strength gaining, it uses low natural resources, and it can be configurated into different structural elements. This study initially presents a review of the classifications, sources, chemical composition, curing regimes and clean production of FA. Then, physical, fresh, and mechanical properties of FA-based concretes are studied. This review helps in better understanding of the behavior of FA-based concrete as a sustainable and eco-friendly material used in construction and building industries.

ACS Style

Mugahed Amran; Roman Fediuk; Gunasekaran Murali; Siva Avudaiappan; Togay Ozbakkaloglu; Nikolai Vatin; Maria Karelina; Sergey Klyuev; Aliakbar Gholampour. Fly Ash-Based Eco-Efficient Concretes: A Comprehensive Review of the Short-Term Properties. Materials 2021, 14, 4264 .

AMA Style

Mugahed Amran, Roman Fediuk, Gunasekaran Murali, Siva Avudaiappan, Togay Ozbakkaloglu, Nikolai Vatin, Maria Karelina, Sergey Klyuev, Aliakbar Gholampour. Fly Ash-Based Eco-Efficient Concretes: A Comprehensive Review of the Short-Term Properties. Materials. 2021; 14 (15):4264.

Chicago/Turabian Style

Mugahed Amran; Roman Fediuk; Gunasekaran Murali; Siva Avudaiappan; Togay Ozbakkaloglu; Nikolai Vatin; Maria Karelina; Sergey Klyuev; Aliakbar Gholampour. 2021. "Fly Ash-Based Eco-Efficient Concretes: A Comprehensive Review of the Short-Term Properties." Materials 14, no. 15: 4264.

Research article
Published: 27 July 2021 in Environmental Science and Pollution Research
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The atmospheric particulate matter (PM) with a diameter of 2.5 μm or less (PM2.5) is one of the key indicators of air pollutants. Accurate prediction of PM2.5 concentration is very important for air pollution monitoring and public health management. However, the presence of noise in PM2.5 data series is a major challenge of its accurate prediction. A novel hybrid PM2.5 concentration prediction model is proposed in this study by combining complete ensemble empirical mode decomposition (CEEMD) method, Pearson’s correlation analysis, and a deep long short-term memory (LSTM) method. CEEMD was employed to decompose historical PM2.5 concentration data to different frequencies in order to enhance the timing characteristics of data. Pearson’s correlation was used to screen the different frequency intrinsic-mode functions of decomposed data. Finally, the filtered enhancement data were inputted to a deep LSTM network with multiple hidden layers for training and prediction. The results evidenced the potential of the CEEMD-LSTM hybrid model with a prediction accuracy of approximately 80% and model convergence after 700 training epochs. The secondary screening of Pearson’s correlation test improved the model (CEEMD-Pearson) accuracy up to 87% but model convergence after 800 epochs. The hybrid model combining CEEMD-Pearson with the deep LSTM neural network showed a prediction accuracy of nearly 90% and model convergence after 650 interactions. The results provide a clear indication of higher prediction accuracy of PM2.5 with less computation time through hybridization of CEEMD-Pearson with deep LSTM models and its potential to be employed for air pollution monitoring.

ACS Style

Minglei Fu; Caowei Le; Tingchao Fan; Ryhor Prakapovich; Dmytro Manko; Oleh Dmytrenko; Dmytro Lande; Shamsuddin Shahid; Zaher Mundher Yaseen. Integration of complete ensemble empirical mode decomposition with deep long short-term memory model for particulate matter concentration prediction. Environmental Science and Pollution Research 2021, 1 -12.

AMA Style

Minglei Fu, Caowei Le, Tingchao Fan, Ryhor Prakapovich, Dmytro Manko, Oleh Dmytrenko, Dmytro Lande, Shamsuddin Shahid, Zaher Mundher Yaseen. Integration of complete ensemble empirical mode decomposition with deep long short-term memory model for particulate matter concentration prediction. Environmental Science and Pollution Research. 2021; ():1-12.

Chicago/Turabian Style

Minglei Fu; Caowei Le; Tingchao Fan; Ryhor Prakapovich; Dmytro Manko; Oleh Dmytrenko; Dmytro Lande; Shamsuddin Shahid; Zaher Mundher Yaseen. 2021. "Integration of complete ensemble empirical mode decomposition with deep long short-term memory model for particulate matter concentration prediction." Environmental Science and Pollution Research , no. : 1-12.

Original paper
Published: 25 July 2021 in Natural Resources Research
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This research was conducted on five oilfields in the Mishrif reservoir, southern Iraq, to illustrate the effects of permeability on the damage caused by the injection of river water into the oilfield. Oilfield flooding has dramatically changed the pH and brine chemistry of the reservoir and resulted in the deposition of carbonates and native sulfur. The air permeability test and scanning electron microscope (SEM) analysis revealed how the precipitated minerals and materials (e.g., residual heavy oil, asphaltene, wax, native sulfur and authigenic and diagenetic clay minerals) reduced the permeability by lining the pore necks. The PHREEQC software and saturation index (SI) model revealed several types of pore-lining scales formed in a porous matrix. The SI model indicates that barite, celestite, calcite and pyrite are common scales lining the pore spaces, which precipitated in response to the injection of sulfate- and carbonate-rich river water into an oil well. This research generated useful findings that can be taken into consideration for future oil production worldwide. Additionally, the permeability values were used as evidence for discrimination of sedimentary environment, particularly reef and non-reef facies.

ACS Style

Salih Muhammad Awadh; Heba S. Al-Mimar; Zaher Mundher Yaseen. Effect of Water Flooding on Oil Reservoir Permeability: Saturation Index Prediction Model for Giant Oil Reservoirs, Southern Iraq. Natural Resources Research 2021, 1 -13.

AMA Style

Salih Muhammad Awadh, Heba S. Al-Mimar, Zaher Mundher Yaseen. Effect of Water Flooding on Oil Reservoir Permeability: Saturation Index Prediction Model for Giant Oil Reservoirs, Southern Iraq. Natural Resources Research. 2021; ():1-13.

Chicago/Turabian Style

Salih Muhammad Awadh; Heba S. Al-Mimar; Zaher Mundher Yaseen. 2021. "Effect of Water Flooding on Oil Reservoir Permeability: Saturation Index Prediction Model for Giant Oil Reservoirs, Southern Iraq." Natural Resources Research , no. : 1-13.

Article
Published: 21 July 2021 in Water Resources Management
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This study proposes a new stochastic approach for optimizing diversion system design and its construction schedule by considering different hydrological and hydraulic uncertainties sources. For this purpose, a multi-objective optimization-simulation model was developed to evaluate the failure of a diversion system to flood. Two objective functions, the expected flood damage (EFD) and cost-benefit (CB) index of a diversion system, are optimized in this study using a non-dominated sorting genetic algorithm II (NSGA-II). The approach is tested for four different compositions of uncertainties (Base Case, Case1, Case2, and Case3) to estimate their impacts based on distance index (D) and the boxplot. Finally, finance constraints are evaluated based on the construction period of the project. The Karun-4 dam, located in Iran, is considered as the case study. The obtained results demonstrate that the hydrological uncertainty with \({D}_{case2}^{basecase}=21.335\) and \({IQR}_{basecase}=2.1M\) has the highest effect on the Pareto optimal front and the hydraulic uncertainty of downstream cofferdam with \({D}_{case3}^{basecase}=5.789\) and \({IQR}_{case2}=1.8M\) has the lowest effect on the Pareto optimal front. The best value of the CB index is related to the base case (66.42%) using the pseudo weight factor. The study indicates that the total investment of the water diversion system is lower than the consultant's plan by 20.23%, 18.33%, 17.28%, and 18.81% when the different components of uncertainty are considered. An implementation period of 6-year and 11-year is the best option for no financial constraints and financial constraints, respectively. The stochastic simulation-optimization approach proposed in the present study provides decision-makers reliable insight into planning dam construction.

ACS Style

Ahmad Sharafati; Siyamak Doroudi; Shamsuddin Shahid; Ali Moridi. A Novel Stochastic Approach for Optimization of Diversion System Dimension by Considering Hydrological and Hydraulic Uncertainties. Water Resources Management 2021, 1 -29.

AMA Style

Ahmad Sharafati, Siyamak Doroudi, Shamsuddin Shahid, Ali Moridi. A Novel Stochastic Approach for Optimization of Diversion System Dimension by Considering Hydrological and Hydraulic Uncertainties. Water Resources Management. 2021; ():1-29.

Chicago/Turabian Style

Ahmad Sharafati; Siyamak Doroudi; Shamsuddin Shahid; Ali Moridi. 2021. "A Novel Stochastic Approach for Optimization of Diversion System Dimension by Considering Hydrological and Hydraulic Uncertainties." Water Resources Management , no. : 1-29.

Journal article
Published: 16 July 2021 in Journal of Building Engineering
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To reduce reinforcement congestion in locations of high rebar concentration in a structure, fiber-reinforced polymer (FRP) rebar (replacing steel rebar) can be used in combination with steel fiber (replacing stirrups). Here, an extensive investigation was conducted for the first time in literature on the effect of steel fibers and crumb rubber (CR) aggregate on the shear behavior of high-strength concrete beams reinforced with glass FRP (GFRP) bars. Thirty beam specimens were manufactured and the effect of the key variables including the GFRP reinforcement ratio, shear span-to-depth ratio, CR content, and fiber content in volume on the shear performance of the beams was investigated. Parameters under investigation were the cracking pattern, manner of failure, load-midspan deflection performance, shear capacity, toughness, and post-cracking strength of the beams. The results indicate that when the fiber volume fraction, concrete compressive strength, and GFRP reinforcement ratio increased, the beam shear capacity increased. Conversely, increasing the shear span-to-depth ratio and CR content led to a decrease in the shear capacity. It was also found that the steel fibers were more efficient in improving the beam shear behavior at higher content of CR, such that they changed the cracking type and failure mode from shear to flexural. Finally, the analysis of variance (ANOVA) technique was used to perform statistical analysis of experimental data and calculate the contribution of different parameters to the experimental results.

ACS Style

Mahdi Nematzadeh; Seyyed-Asgar Hosseini; Togay Ozbakkaloglu. The combined effect of crumb rubber aggregates and steel fibers on shear behavior of GFRP bar-reinforced high-strength concrete beams. Journal of Building Engineering 2021, 44, 102981 .

AMA Style

Mahdi Nematzadeh, Seyyed-Asgar Hosseini, Togay Ozbakkaloglu. The combined effect of crumb rubber aggregates and steel fibers on shear behavior of GFRP bar-reinforced high-strength concrete beams. Journal of Building Engineering. 2021; 44 ():102981.

Chicago/Turabian Style

Mahdi Nematzadeh; Seyyed-Asgar Hosseini; Togay Ozbakkaloglu. 2021. "The combined effect of crumb rubber aggregates and steel fibers on shear behavior of GFRP bar-reinforced high-strength concrete beams." Journal of Building Engineering 44, no. : 102981.

Original paper
Published: 10 July 2021 in Stochastic Environmental Research and Risk Assessment
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Among several complex hydrological process elements, Evapotranspiration (ET) is the most complex one. Estimation of ET is very challenging compared to other hydrological variables as it depends on complex interactions of several hydrometeorological variables. In the current research, the estimation of daily ET from maximum and minimum temperature was established. For this purpose, Dynamic Evolving Neural-Fuzzy Inference System (DENFIS) and Multivariate Adaptive Regression Spline (MARS) were hybridized with two advanced metaheuristic optimization algorithms [i.e., Whale Optimization Algorithm (WOA) and Bat Algorithm (BA)]. Daily ET and temperature data estimated at 3 locations in the coastal region of southwest Bangladesh for the period 2005–2016 were used to develop and validate the models. The results showed a good performance of DENFIS-WOA model with minimum values of normalized root mean square error (NRMSE = 0.35–0.54) in estimating ET using only temperature in the complex climatic setup of southwest Bangladesh. DENFIS-BA also showed reasonable performance (NRMSE = 0.43–0.62), while the performance of MARS–WOA (NRMSE = 0.54–0.97) and MARS-BA (0.60–1.13) was found satisfactory in terms of most of the statistical indices. Obtained results were also evaluated using innovative visual presentations of model outputs, which revealed the better capability of only DENFIS-WOA in estimating mean, variability and distribution of ET for all the months and locations. The results indicate the potential of DENFIS-WOA to be used for reliable estimation of daily ET from the temperature in a tropical humid coastal region.

ACS Style

Lu Ye; Musaddak M. Abdul Zahra; Najah Kadhim Al-Bedyry; Zaher Mundher Yaseen. Daily scale evapotranspiration prediction over the coastal region of southwest Bangladesh: new development of artificial intelligence model. Stochastic Environmental Research and Risk Assessment 2021, 1 -21.

AMA Style

Lu Ye, Musaddak M. Abdul Zahra, Najah Kadhim Al-Bedyry, Zaher Mundher Yaseen. Daily scale evapotranspiration prediction over the coastal region of southwest Bangladesh: new development of artificial intelligence model. Stochastic Environmental Research and Risk Assessment. 2021; ():1-21.

Chicago/Turabian Style

Lu Ye; Musaddak M. Abdul Zahra; Najah Kadhim Al-Bedyry; Zaher Mundher Yaseen. 2021. "Daily scale evapotranspiration prediction over the coastal region of southwest Bangladesh: new development of artificial intelligence model." Stochastic Environmental Research and Risk Assessment , no. : 1-21.

Journal article
Published: 06 July 2021 in Environmental Monitoring and Assessment
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The transient storage model (TSM) is a common approach to assess solute transport and pollution modeling in rivers. Several formulas have been developed to estimate TSM parameters. This study develops a new hybrid optimization algorithm consisting of the dragonfly algorithm and simulated annealing (DA-SA) algorithms. This robust method provides accurate formulas for estimating TSM parameters (e.g., kf, T, [Formula: see text]). A dataset gathered by previous scholars from several rivers in the USA was used to assess the proposed formulas based on several error metrics ([Formula: see text] and [Formula: see text]) and visual indicators. According to the results, DA-SA-based formulas adequately estimated the [Formula: see text] ([Formula: see text], [Formula: see text]), [Formula: see text] ([Formula: see text] [Formula: see text]), and [Formula: see text] ([Formula: see text] [Formula: see text]) parameters. Moreover, the DA-SA-1 showed higher accuracy by improving the RMSE and MAE by 98% compared to the DA and DA-SA-1 as alternatives. The formulas developed in this study significantly outperformed the results of previously proposed models by enhancing the NSE up to 70%. The hybrid DA-SA algorithm method proved highly reliable models to estimate the TSM parameters in the water pollution routing problem, which is vital for reactive solute uptake in advective and transient storage zones of stream ecosystems.

ACS Style

Mohammad Ehteram; Ahmad Sharafati; Seyed Babak Haji Seyed Asadollah; Aminreza Neshat. Estimating the transient storage parameters for pollution modeling in small streams: a comparison of newly developed hybrid optimization algorithms. Environmental Monitoring and Assessment 2021, 193, 475 .

AMA Style

Mohammad Ehteram, Ahmad Sharafati, Seyed Babak Haji Seyed Asadollah, Aminreza Neshat. Estimating the transient storage parameters for pollution modeling in small streams: a comparison of newly developed hybrid optimization algorithms. Environmental Monitoring and Assessment. 2021; 193 (8):475.

Chicago/Turabian Style

Mohammad Ehteram; Ahmad Sharafati; Seyed Babak Haji Seyed Asadollah; Aminreza Neshat. 2021. "Estimating the transient storage parameters for pollution modeling in small streams: a comparison of newly developed hybrid optimization algorithms." Environmental Monitoring and Assessment 193, no. 8: 475.

Research article
Published: 28 June 2021 in Frontiers of Structural and Civil Engineering
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The scouring phenomenon is one of the major problems experienced in hydraulic engineering. In this study, an adaptive neuro-fuzzy inference system is hybridized with several evolutionary approaches, including the ant colony optimization, genetic algorithm, teaching-learning-based optimization, biogeographical-based optimization, and invasive weed optimization for estimating the long contraction scour depth. The proposed hybrid models are built using non-dimensional information collected from previous studies. The proposed hybrid intelligent models are evaluated using several statistical performance metrics and graphical presentations. Besides, the uncertainty of models, variables, and data are inspected. Based on the achieved modeling results, adaptive neuro-fuzzy inference system-biogeographic based optimization (ANFIS-BBO) provides superior prediction accuracy compared to others, with a maximum correlation coefficient (Rtest = 0.923) and minimum root mean square error value (RMSEtest = 0.0193). Thus, the proposed ANFIS-BBO is a capable cost-effective method for predicting long contraction scouring, thus, contributing to the base knowledge of hydraulic structure sustainability.

ACS Style

Ahmad Sharafati; Masoud Haghbin; MohammadAmin Torabi; Zaher Mundher Yaseen. Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related uncertainties. Frontiers of Structural and Civil Engineering 2021, 15, 665 -681.

AMA Style

Ahmad Sharafati, Masoud Haghbin, MohammadAmin Torabi, Zaher Mundher Yaseen. Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related uncertainties. Frontiers of Structural and Civil Engineering. 2021; 15 (3):665-681.

Chicago/Turabian Style

Ahmad Sharafati; Masoud Haghbin; MohammadAmin Torabi; Zaher Mundher Yaseen. 2021. "Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related uncertainties." Frontiers of Structural and Civil Engineering 15, no. 3: 665-681.

Article
Published: 21 June 2021 in Hydrological Sciences Journal
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This study evaluated the effectiveness of Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) satellite rainfall data for the development of multi-step ahead streamflow forecasting models. Daily time scale precipitation data of nearly three decades (1986-2012) over the Varahi river basin in Western Ghats of Karnataka, India were used for the analysis. Machine learning (ML) models, namely, the Group Method of Data Handling (GMDH), Chi-square Automatic Interaction Detector (CHAID), and Random Forest (RF) were simulated for one, three and seven days ahead streamflow forecasting. Additionally, the developed forecasting models were improved through the integration with Intrinsic Time-scale decomposition (ITD) (by decomposing the input data into a series of proper rotation components (PRC) and a monotonic trend). The uniqueness of this study lies in coupling ITD with machine learning models to forecast daily streamflow time-series. Concurrently, the precipitation data derived from India Meteorological Department (IMD) gridded rainfall dataset were also employed for developing analogous multistep ahead streamflow forecasting models. The proposed methodology was aimed to have an accurate and a reliable forecasting model that can assist water resources management and operation. Comparative performance evaluation using various statistical indices portrayed the superiority of CHIRPS satellite rainfall data product in forecasting daily streamflows up to a week lead time. The results indicate that, the hybrid ITD-based ML models developed using CHIRPS precipitation data as inputs held a better performance at all lead times.

ACS Style

Maofa Wang; Mohammad Rezaie-Balf; Sujay Raghavendra Naganna; Zaher Mundher Yaseen. Sourcing CHIRPS precipitation data for streamflow forecasting using intrinsic time-scale decomposition based machine learning models. Hydrological Sciences Journal 2021, 1 -20.

AMA Style

Maofa Wang, Mohammad Rezaie-Balf, Sujay Raghavendra Naganna, Zaher Mundher Yaseen. Sourcing CHIRPS precipitation data for streamflow forecasting using intrinsic time-scale decomposition based machine learning models. Hydrological Sciences Journal. 2021; ():1-20.

Chicago/Turabian Style

Maofa Wang; Mohammad Rezaie-Balf; Sujay Raghavendra Naganna; Zaher Mundher Yaseen. 2021. "Sourcing CHIRPS precipitation data for streamflow forecasting using intrinsic time-scale decomposition based machine learning models." Hydrological Sciences Journal , no. : 1-20.

Review
Published: 17 June 2021 in Crystals
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Currently, a number of disadvantages hampers the use of recycled concrete aggregates (RCA). The current review proves that concretes made with complete replacement of natural aggregate with RCA allow the production of high-quality concrete. One of the possibilities for improving concrete properties with RCA is the use of extended curing and pozzolanic materials with varying cement ratios. The potential use of RCA concretes is in the production of high-value materials that increase environmental and financial benefits. RCA have strong potential in the development of a new generation of concrete and stimulate economic activity in many countries in addition to optimizing natural resources. Economic benefits include minimal travel costs; cheaper sources of concrete than newly mined aggregates; reduction of the landfill area required for the placement of concrete waste; the use of RCA minimizes the need for gravel extraction, etc. The proposed strategy could be to sequentially separate demolition waste such as roof finishes, waterproof materials, interior and exterior materials, etc. Closing life cycles is the main approach used for efficient structures for the recycling and reuse of construction and demolition waste in the production and recovery of materials, especially when recycling and reusing materials. In the life cycle, the recycling of recovered materials allows them to be used for new construction purposes, avoiding the use of natural concrete aggregates. Government, design institutes, construction departments and project managers should be involved in the creation and use of RCA. In demolition and construction, the main players are the project owners. Their obligations, expectations and responsibilities must be properly aligned. For the past 20 years, recycled concrete aggregate from demolition and construction waste has been considered as an alternative to pure concrete in structural concrete to minimize the environmental impact of construction waste and demolition waste and the conversion of natural aggregate resources. It is now recognized that the use of RCA for the generations of concrete is a promising and very attractive technology for reducing the environmental impact of the construction sector and conserving natural resources. In the market, the selling price is not an obstacle for market applications of RCA, as there are scenarios in which their cost is lower than the cost of products made from conventional building materials. This is more of an acceptance factor in the market for recycled concrete aggregates. In this sector, the lack of identification, accreditation and uniform quality certification systems and their narrow application cause some marketing problems. With proper RCA preparation, concrete with standard physical and mechanical properties and performance characteristics can be obtained.

ACS Style

Natt Makul; Roman Fediuk; Mugahed Amran; Abdullah Zeyad; Sergey Klyuev; Irina Chulkova; Togay Ozbakkaloglu; Nikolai Vatin; Maria Karelina; Afonso Azevedo. Design Strategy for Recycled Aggregate Concrete: A Review of Status and Future Perspectives. Crystals 2021, 11, 695 .

AMA Style

Natt Makul, Roman Fediuk, Mugahed Amran, Abdullah Zeyad, Sergey Klyuev, Irina Chulkova, Togay Ozbakkaloglu, Nikolai Vatin, Maria Karelina, Afonso Azevedo. Design Strategy for Recycled Aggregate Concrete: A Review of Status and Future Perspectives. Crystals. 2021; 11 (6):695.

Chicago/Turabian Style

Natt Makul; Roman Fediuk; Mugahed Amran; Abdullah Zeyad; Sergey Klyuev; Irina Chulkova; Togay Ozbakkaloglu; Nikolai Vatin; Maria Karelina; Afonso Azevedo. 2021. "Design Strategy for Recycled Aggregate Concrete: A Review of Status and Future Perspectives." Crystals 11, no. 6: 695.

Original paper
Published: 15 June 2021 in Theoretical and Applied Climatology
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Soil moisture (SM) governs the exchange of energy and water between the atmosphere and land surface. In situ measurements of SM are uneven in Iran. This knowledge gap can be filled using satellite- and model-based products. This study assessed the performance of SM products, including Soil Moisture Active Passive (SMAP), Advanced Microwave Scanning Radiometer (AMSR2), and Global Land Data Assimilation System (GLDAS) Catchment Land Surface Model (CLSM) against in situ observations considering the influence of soil texture, climate, and land cover over Lake Urmia Basin, which is the largest salt lake in Iran and the Middle East. In situ SM was measured over Lake Urmia Basin in the morning and afternoon using the time domain reflectometry (TDR) and oven drying and weighing techniques. Five statistical indicators, including correlation (R), absolute correlation (R(abs)), bias, root mean square error (RMSE), and unbiased root mean square error (ubRMSE), were applied. C-band AMSR2 products showed the best performance in grassland and croplands with the highest absolute correlation (0.63) and lowest average bias (−0.01). Among soil textures, SM products performed better in clay soils with the highest absolute correlation between C-band AMSR2 products and in situ observations (0.64) and low average bias and RMSE. Analyzing data based on climate, AMSR2 C1, and GLDAS products with the lowest average RMSE (0.08 m3m−3) and bias (0.01) and AMSR2 C2 with the absolute correlation of 0.6 showed the best performance in both temperate (Csa) and cold (Dsa) climate classes. For all classifications (land cover, soil texture, climate divisions), SMAP products reported the lowest average value of ubRMSE (0.03 m3m−3). The major contribution of the paper is finding the best SM products that can fill the gap in SM measurements data in Lake Urmia. In this analysis, the impacts of land cover, climate, and soil texture on the performance of products were considered.

ACS Style

Mohammad Saeedi; Ahmad Sharafati; Ameneh Tavakol. Evaluation of gridded soil moisture products over varied land covers, climates, and soil textures using in situ measurements: A case study of Lake Urmia Basin. Theoretical and Applied Climatology 2021, 145, 1053 -1074.

AMA Style

Mohammad Saeedi, Ahmad Sharafati, Ameneh Tavakol. Evaluation of gridded soil moisture products over varied land covers, climates, and soil textures using in situ measurements: A case study of Lake Urmia Basin. Theoretical and Applied Climatology. 2021; 145 (3-4):1053-1074.

Chicago/Turabian Style

Mohammad Saeedi; Ahmad Sharafati; Ameneh Tavakol. 2021. "Evaluation of gridded soil moisture products over varied land covers, climates, and soil textures using in situ measurements: A case study of Lake Urmia Basin." Theoretical and Applied Climatology 145, no. 3-4: 1053-1074.

Journal article
Published: 29 May 2021 in Composite Structures
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The polyethylene naphthalene (PEN) and polyethylene terephthalate (PET) fibers have a tensile rupture strain of over 5%, and hence they are referred to as large-rupture-strain (LRS) fiber reinforced polymer (FRP) materials. Their large rupture strain characteristics may contribute to significant improvement of the impact resistance of reinforced concrete (RC) structures. This study investigates the strain rate effect on LRS FRP-confined concrete through Split Hopkinson Pressure Bar (SHPB) test. Results revealed that LRS FRP-confined concrete specimens exhibited superior impact resistance behaviors compared to the counterpart confined with CFRP composites when subjected to a single impact. The critical strain, compressive strength and toughness of the LRS FRP-confined concrete specimen increased with increasing strain rate. Due to the large rupture strain characteristics, the LRS FRP-confined concrete specimen virtually had no visible damage after a single impact. To study the damage evolution mechanism of concrete, the specimens were impacted for multiple times with the same energy until the failure of the specimen. Due to progressive concrete damage, the dynamic compressive strength and toughness experienced a decrease during multiple impacts. These findings might promote the application of LRS FRP materials in the field of impact resistance design of RC structures as a promising external jacketing material.

ACS Style

Zhi-Wei Yan; Yu-Lei Bai; Togay Ozbakkaloglu; Wan-Yang Gao; Jun-Jie Zeng. Rate-Dependent Compressive Behavior of Concrete Confined with Large-Rupture-Strain (LRS) FRP. Composite Structures 2021, 272, 114199 .

AMA Style

Zhi-Wei Yan, Yu-Lei Bai, Togay Ozbakkaloglu, Wan-Yang Gao, Jun-Jie Zeng. Rate-Dependent Compressive Behavior of Concrete Confined with Large-Rupture-Strain (LRS) FRP. Composite Structures. 2021; 272 ():114199.

Chicago/Turabian Style

Zhi-Wei Yan; Yu-Lei Bai; Togay Ozbakkaloglu; Wan-Yang Gao; Jun-Jie Zeng. 2021. "Rate-Dependent Compressive Behavior of Concrete Confined with Large-Rupture-Strain (LRS) FRP." Composite Structures 272, no. : 114199.

Research article atmospheric and space sciences
Published: 28 May 2021 in Acta Geophysica
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In recent years, gridded precipitation products have been widely used in hydrology studies and other fields of water sciences. This study evaluated the potential of several gridded precipitation products, including GPCC, TRMM, CRU, ERA-Interim, and ERA5, in trend analysis of precipitation depth and the number of rainy days in various regions of Iran. Moreover, the observational precipitation data of the daily time series were collected from 68 Iranian synoptic stations. The Mann–Kendall test was conducted to determine gridded and observed precipitation trends in the period of 1997 to 2017. The probability of detection (POD) and false alarm ratio (FAR) indices were utilized to compare gridded and observed precipitation trends. Results showed that the best consistency (POD: 52% ~ 80%, FAR: 60% ~ 88%) was observed between the observed trends of the number of rainy days and those obtained by TRMM product over different regions of Iran. Moreover, ERA-Interim offered a better performance (POD: 50% ~ 100%, FAR: 58% ~ 72%) in the trend analysis of precipitation depth in Iran. The consistency between observational and gridded precipitation trends has never been analyzed in Iran at this level; therefore, this is considered a unique analysis. Besides, the generated maps of precipitation products' performance provide a comprehensive view of better water resources management over different regions of Iran.

ACS Style

Shahin Shobeiri; Ahmad Sharafati; Aminreza Neshat. Evaluation of different gridded precipitation products in trend analysis of precipitation features over Iran. Acta Geophysica 2021, 69, 959 -974.

AMA Style

Shahin Shobeiri, Ahmad Sharafati, Aminreza Neshat. Evaluation of different gridded precipitation products in trend analysis of precipitation features over Iran. Acta Geophysica. 2021; 69 (3):959-974.

Chicago/Turabian Style

Shahin Shobeiri; Ahmad Sharafati; Aminreza Neshat. 2021. "Evaluation of different gridded precipitation products in trend analysis of precipitation features over Iran." Acta Geophysica 69, no. 3: 959-974.

Research article
Published: 27 May 2021 in PLOS ONE
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Groundwater is one of the most important freshwater resources, especially in arid and semi-arid regions where the annual amounts of precipitation are small with frequent drought durations. Information on qualitative parameters of these valuable resources is very crucial as it might affect its applicability from agricultural, drinking, and industrial aspects. Although geo-statistics methods can provide insight about spatial distribution of quality factors, applications of advanced artificial intelligence (AI) models can contribute to produce more accurate results as robust alternative for such a complex geo-science problem. The present research investigates the capacity of several types of AI models for modeling four key water quality variables namely electrical conductivity (EC), sodium adsorption ratio (SAR), total dissolved solid (TDS) and Sulfate (SO4) using dataset obtained from 90 wells in Tabriz Plain, Iran; assessed by k-fold testing. Two different modeling scenarios were established to make simulations using other quality parameters and the geographical information. The obtained results confirmed the capabilities of the AI models for modeling the well groundwater quality variables. Among all the applied AI models, the developed hybrid support vector machine-firefly algorithm (SVM-FFA) model achieved the best predictability performance for both investigated scenarios. The introduced computer aid methodology provided a reliable technology for groundwater monitoring and assessment.

ACS Style

Naser Shiri; Jalal Shiri; Zaher Mundher Yaseen; Sungwon Kim; Il-Moon Chung; Vahid Nourani; Mohammad Zounemat-Kermani. Development of artificial intelligence models for well groundwater quality simulation: Different modeling scenarios. PLOS ONE 2021, 16, e0251510 .

AMA Style

Naser Shiri, Jalal Shiri, Zaher Mundher Yaseen, Sungwon Kim, Il-Moon Chung, Vahid Nourani, Mohammad Zounemat-Kermani. Development of artificial intelligence models for well groundwater quality simulation: Different modeling scenarios. PLOS ONE. 2021; 16 (5):e0251510.

Chicago/Turabian Style

Naser Shiri; Jalal Shiri; Zaher Mundher Yaseen; Sungwon Kim; Il-Moon Chung; Vahid Nourani; Mohammad Zounemat-Kermani. 2021. "Development of artificial intelligence models for well groundwater quality simulation: Different modeling scenarios." PLOS ONE 16, no. 5: e0251510.

Technical paper
Published: 26 May 2021 in Structural Concrete
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The focus of this study is to investigate the effect of using coarse recycled concrete aggregates (RCAs) as an alternative material to natural coarse aggregate on the fresh, mechanical and durability behavior of concrete reinforced with steel fiber. Eighteen unique concrete mixes with RCA content of 0%, 50%, and 100% and steel fiber content of 0%, 1%, and 2% were prepared, and tests were performed to study slump, density, compressive and splitting tensile strengths, flexural behavior, surface hardness, surface abrasion resistance, water absorption, and sorptivity of each mix. It is shown that concrete containing RCA has a lower unit weight, compressive, splitting tensile and flexural strength, flexural toughness, surface hardness, and abrasion resistance, and a higher water absorption and sorptivity in comparison with conventional concrete. An increased compressive, splitting tensile and flexural strength, flexural toughness, surface hardness, and abrasion resistance, and a decreased water absorption and sorptivity of concrete with an increased steel fiber content from 1% to 2% is less significant compared to those from 0% to 1%. The results also show that, at RCA content of 50%, incorporating 1% steel fiber develops a concrete mix with similar or even better properties compared to unreinforced conventional concrete. At 100% RCA content, incorporating 2% steel fiber develops a concrete mix with similar properties to unreinforced conventional concrete having water to cement ratio of 0.3, but inferior properties to unreinforced conventional concrete having water to cement ratio of 0.5. These findings indicate that recycled aggregate concrete with similar or even better properties compared to concrete with natural aggregate can be developed through properly designing mixes, providing a great avenue toward the production of green construction material for structural applications.

ACS Style

Gokhan Kaplan; Oguzhan Yavuz Bayraktar; Aliakbar Gholampour; Osman Gencel; Fuat Koksal; Togay Ozbakkaloglu. Mechanical and durability properties of steel fiber‐reinforced concrete containing coarse recycled concrete aggregate. Structural Concrete 2021, 1 .

AMA Style

Gokhan Kaplan, Oguzhan Yavuz Bayraktar, Aliakbar Gholampour, Osman Gencel, Fuat Koksal, Togay Ozbakkaloglu. Mechanical and durability properties of steel fiber‐reinforced concrete containing coarse recycled concrete aggregate. Structural Concrete. 2021; ():1.

Chicago/Turabian Style

Gokhan Kaplan; Oguzhan Yavuz Bayraktar; Aliakbar Gholampour; Osman Gencel; Fuat Koksal; Togay Ozbakkaloglu. 2021. "Mechanical and durability properties of steel fiber‐reinforced concrete containing coarse recycled concrete aggregate." Structural Concrete , no. : 1.

Original research paper
Published: 20 May 2021 in International Journal of Pavement Research and Technology
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Stockpiles of discarded tires are a global concern. Since tire incinerating results in severe air pollution, reusing tires as tire rubber particles can reduce environmental pollution. A recycled tire, including rubber and recycled steel fiber, can be introduced in cement concrete. This study aimed to investigate the effects of crumb rubber and recycled steel fiber on the conventional concrete pavement's short- and long-term performance. The impact of crumb rubber (Cr) (0–20%) and recycled steel fiber (F) (0–0.5%) on the compressive, splitting, and flexural strength, as well as abrasion and freezing–thawing resistance of concrete, was evaluated through response surface methodology (RSM). The results indicated that fiber's addition to the concrete mix had a remarkable influence on flexural strength in low content and enhanced post-cracking ductility of rubberized concrete. Furthermore, incorporating crumb rubber as fine aggregate led to a reduction in the abrasion resistance and increased sensitivity to freezing–thawing in the presence of saline solution. According to optimization results, the most appropriate way to benefit from the desirable characteristics of rubberized concrete while minimizing the crumb rubber inclusion's adverse effects is through the addition of fibers into the concrete mixtures.

ACS Style

A. Zarei; H. Rooholamini; T. Ozbakkaloglu. Evaluating the Properties of Concrete Pavements Containing Crumb Rubber and Recycled Steel Fibers Using Response Surface Methodology. International Journal of Pavement Research and Technology 2021, 1 -15.

AMA Style

A. Zarei, H. Rooholamini, T. Ozbakkaloglu. Evaluating the Properties of Concrete Pavements Containing Crumb Rubber and Recycled Steel Fibers Using Response Surface Methodology. International Journal of Pavement Research and Technology. 2021; ():1-15.

Chicago/Turabian Style

A. Zarei; H. Rooholamini; T. Ozbakkaloglu. 2021. "Evaluating the Properties of Concrete Pavements Containing Crumb Rubber and Recycled Steel Fibers Using Response Surface Methodology." International Journal of Pavement Research and Technology , no. : 1-15.

Journal article
Published: 13 May 2021 in Ain Shams Engineering Journal
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In the current research, a newly developed ensemble intelligent predictive model called Bagging Regression (BGR) is proposed to predict the compressive strength of a hollow concrete masonry prism (fp). A matrix of input combinations is constructed based on several predictive variables, including mortar compressive strength (fm), concrete block compressive strength (fb), and height to thickness ratio (h/t). Three modeling scenarios based on the different data divisions (i.e., 80–20%, 75–25%, and 70–30%) for training-testing phases are evaluated. The proposed model is validated against classical support vector regression (SVR) and decision tree regression (DTR) models using statistical indicators and graphical presentations. Results indicate the superiority of the BGR over the other models. In quantitative terms, BGR attains minimum root mean square error (RMSE = 1.51 MPa) using the data division scenario of 80–20% in the testing phase, while DTR and standalone SVR models offer RMSE = 2.55 and 2.33 MPa, respectively.

ACS Style

Ahmad Sharafati; Seyed Babak Haji Seyed Asadollah; Nadhir Al-Ansari. Application of bagging ensemble model for predicting compressive strength of hollow concrete masonry prism. Ain Shams Engineering Journal 2021, 1 .

AMA Style

Ahmad Sharafati, Seyed Babak Haji Seyed Asadollah, Nadhir Al-Ansari. Application of bagging ensemble model for predicting compressive strength of hollow concrete masonry prism. Ain Shams Engineering Journal. 2021; ():1.

Chicago/Turabian Style

Ahmad Sharafati; Seyed Babak Haji Seyed Asadollah; Nadhir Al-Ansari. 2021. "Application of bagging ensemble model for predicting compressive strength of hollow concrete masonry prism." Ain Shams Engineering Journal , no. : 1.