Sharif University of Technology Sharif Journal of Civil Engineering 2676-4768 42 1 2026 05 22 The Optimal Hybrid Controller Based on Ground Acceleration for a Structure Equipped with MR Dampers The Optimal Hybrid Controller Based on Ground Acceleration for a Structure Equipped with MR Dampers 3 16 24207 10.24200/j30.2025.65523.3381 FA Hosein Ghaffarzadeh Faculty of Civil Engineering of Tabriz University, Tabriz, Iran Samira Safikhanlou Faculty of Civil Engineering of Tabriz University, Tabriz, Iran Alireza Aran Faculty of Civil Engineering of Tabriz University, Tabriz, Iran Journal Article 2024 11 16 Magnetorheological (MR) dampers demonstrate intelligent behavior when subjected to a magnetic field, with their structural response controlled by adjusting the magnetic field's intensity. Various control algorithms and laws have been proposed to implement these control systems. Among the fundamental control laws for semi-active systems, the Skyhook and Groundhook control laws are particularly notable. A hybrid approach combining both of them can be employed to enhance the performance of these control laws. However, determining the optimal contribution of each control law—Skyhook and Groundhook—within the hybrid control law presents a significant challenge. In this study, an eight-story structure equipped with MR dampers is analyzed under the excitation of three earthquakes, Bam, Loma-Prieta, and Northridge, to evaluate the effectiveness of the proposed hybrid control law. The objective is to optimize the hybrid control law using the pattern search algorithm. The hybrid control law for structures with MR dampers can be implemented in two ways: on-off and continuous. In the on-off method, the voltage applied to the MR dampers is restricted to two extreme values, whereas the continuous method allows for voltage adjustment across the entire range between these boundaries. Through an analysis of both on-off and continuous hybrid control laws, it is evident that their performance in reducing the structure's displacement, velocity, and acceleration responses is nearly identical. However, the continuous hybrid control law achieves comparable efficiency with significantly lower control forces. As a result, the continuous optimal hybrid control law emerges as a simple yet highly effective solution. Furthermore, by assuming the same weight of force and displacement in the cost function, it is shown that the participation percentage of the Skyhook control law in the hybrid control law is much higher than that of the Groundhook control law. The optimal participation rate of the Skyhook law is obtained to be approximately 0.95. Magnetorheological (MR) dampers demonstrate intelligent behavior when subjected to a magnetic field, with their structural response controlled by adjusting the magnetic field's intensity. Various control algorithms and laws have been proposed to implement these control systems. Among the fundamental control laws for semi-active systems, the Skyhook and Groundhook control laws are particularly notable. A hybrid approach combining both of them can be employed to enhance the performance of these control laws. However, determining the optimal contribution of each control law—Skyhook and Groundhook—within the hybrid control law presents a significant challenge. In this study, an eight-story structure equipped with MR dampers is analyzed under the excitation of three earthquakes, Bam, Loma-Prieta, and Northridge, to evaluate the effectiveness of the proposed hybrid control law. The objective is to optimize the hybrid control law using the pattern search algorithm. The hybrid control law for structures with MR dampers can be implemented in two ways: on-off and continuous. In the on-off method, the voltage applied to the MR dampers is restricted to two extreme values, whereas the continuous method allows for voltage adjustment across the entire range between these boundaries. Through an analysis of both on-off and continuous hybrid control laws, it is evident that their performance in reducing the structure's displacement, velocity, and acceleration responses is nearly identical. However, the continuous hybrid control law achieves comparable efficiency with significantly lower control forces. As a result, the continuous optimal hybrid control law emerges as a simple yet highly effective solution. Furthermore, by assuming the same weight of force and displacement in the cost function, it is shown that the participation percentage of the Skyhook control law in the hybrid control law is much higher than that of the Groundhook control law. The optimal participation rate of the Skyhook law is obtained to be approximately 0.95.

https://sjce.journals.sharif.edu/article_24207_ef1f649f75e8a22d9c13c9aef6437832.pdf

Sharif University of Technology Sharif Journal of Civil Engineering 2676-4768 42 1 2026 05 22 Investigation of Brine Dispersion of Desalination Plants in the Vicinity of Kish Island Port Using Field Measurements and Numerical Modeling Investigation of Brine Dispersion of Desalination Plants in the Vicinity of Kish Island Port Using Field Measurements and Numerical Modeling 17 30 24223 10.24200/j30.2025.66751.3425 FA Omid Pourabdollah Kish International Campus, University of Tehran, Tehran, Iran. 0000-0002-8158-1729 Reza Ghiassi School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran. 0000-0003-2951-565X Journal Article 2025 05 11 Desalination of seawater is one of the most effective methods, and in some cases, the only possible method for producing drinking water. The combined effect of desalination plants and port structures on the coastal environment can sometimes have specific environmental consequences. The dispersion from the desalination plants, especially the changes in salinity and temperature, has significant effects on coral reefs. In this paper, the effect of the commercial port of Kish Island with regard to the desalination plants was investigated using field measurements and numerical modeling. In 3 stages of field measurement, water quality parameters were measured from 24 different points near the northern coast of Kish Island. The speed and direction of the current were also measured to verify the accuracy of the numerical modeling. The current and dispersion of thermal and salinity pollution were modeled using the MIKE21 two-dimensional model. The computational domain was about 30 square kilometers in size and was discretized into four zones using four different element sizes. Comparison of the numerical modeling results with field measurements indicated acceptable accuracy. The results of the modeling of the salinity diffusion pattern indicate a significant spread in the zone surrounding the outfall of desalination plants and the Kish Island commercial port. Around the outfall, the average temperature and electrical conductivity (EC) increased by 16% and 14%, respectively. This is due to the effect of the west breakwater on current reduction, which resulted in increasing brine concentration. The ultimate point where the ambient temperature has increased by 3 degrees is 170 meters from the outfall. Therefore, considering the impact of temperature changes on coral reefs is critically important. Given the absence of measured data on water quality parameters, current, and velocity direction across various tides at this location, the findings of this study contribute to a better understanding of the environmental status of the area. Desalination of seawater is one of the most effective methods, and in some cases, the only possible method for producing drinking water. The combined effect of desalination plants and port structures on the coastal environment can sometimes have specific environmental consequences. The dispersion from the desalination plants, especially the changes in salinity and temperature, has significant effects on coral reefs. In this paper, the effect of the commercial port of Kish Island with regard to the desalination plants was investigated using field measurements and numerical modeling. In 3 stages of field measurement, water quality parameters were measured from 24 different points near the northern coast of Kish Island. The speed and direction of the current were also measured to verify the accuracy of the numerical modeling. The current and dispersion of thermal and salinity pollution were modeled using the MIKE21 two-dimensional model. The computational domain was about 30 square kilometers in size and was discretized into four zones using four different element sizes. Comparison of the numerical modeling results with field measurements indicated acceptable accuracy. The results of the modeling of the salinity diffusion pattern indicate a significant spread in the zone surrounding the outfall of desalination plants and the Kish Island commercial port. Around the outfall, the average temperature and electrical conductivity (EC) increased by 16% and 14%, respectively. This is due to the effect of the west breakwater on current reduction, which resulted in increasing brine concentration. The ultimate point where the ambient temperature has increased by 3 degrees is 170 meters from the outfall. Therefore, considering the impact of temperature changes on coral reefs is critically important. Given the absence of measured data on water quality parameters, current, and velocity direction across various tides at this location, the findings of this study contribute to a better understanding of the environmental status of the area.

https://sjce.journals.sharif.edu/article_24223_7c4e2c89a4054ce79d83c88031174b3d.pdf

Sharif University of Technology Sharif Journal of Civil Engineering 2676-4768 42 1 2026 05 22 Numerical Study of Cyclic Behavior of Steel Column Base Angle Connections Using Taguchi Experimental Design Numerical Study of Cyclic Behavior of Steel Column Base Angle Connections Using Taguchi Experimental Design 31 43 24222 10.24200/j30.2025.66939.3430 FA Iman Aghaei Department of Civil Engineering, University of Sistan and Baluchestan, Sistan and Baluchestan, Iran. 0009-0005-9102-7798 Mahmoud Miri Department of Civil Engineering, University of Sistan and Baluchestan, Sistan and Baluchestan, Iran. 0000-0001-5009-9887 Hamed Ghohani Arab Department of Civil Engineering, University of Sistan and Baluchestan, Sistan and Baluchestan, Iran. 0000-0001-9808-4596 Journal Article 2025 05 28 This study presents a numerical investigation into the cyclic behavior of steel column base connections equipped with replaceable yielding steel angles under cyclic loading conditions. Utilizing a combined methodology of finite element analysis through ABAQUS and the Taguchi design of experiments (DOE) approach, the research systematically evaluates the influence of three critical parameters: steel angle thickness, applied axial load ratio, and anchor bolt gauge distance from the column edge. The numerical model was rigorously validated against existing experimental results, demonstrating strong agreement and confirming its capability to accurately simulate the nonlinear hysteretic response of the connections. Nine strategically designed parameter combinations based on an L9 orthogonal array enabled an efficient exploration of the parameter space while capturing both individual and interactive effects. Statistical analysis via analysis of variance (ANOVA) identified the thickness of the steel angle as the most significant factor, accounting for approximately 59.43% of the variation in the maximum flexural moment capacity, followed by the gauge distance (24.95%) and axial load ratio (11.92%). The optimal parameter set—comprising a 10 mm angle thickness, 0.2 axial load ratio relative to column capacity, and 40 mm gauge distance—yielded a peak flexural moment capacity of 30.71 kN·m, closely matching the finite element prediction of 30.56 kN·m. Hysteresis curve analyses reveal enhanced energy dissipation capacity, increased initial stiffness, and improved ductility in the optimized configuration, although the connection behavior consistently remains within the pinned range as per ANSI/AISC 360-16 specifications. The concentrated plasticity in the replaceable angle elements effectively localizes damage, promoting easy post-earthquake repair without compromising the main structural components. A regression model derived from the DOE results facilitates reliable predictions of flexural capacity based on the aforementioned parameters, underscoring the practical utility of the Taguchi method in seismic design optimization. These findings provide critical insights into the design of resilient, low-damage steel column base connections capable of sustaining seismic demands while enhancing reparability and lifecycle performance. This study presents a numerical investigation into the cyclic behavior of steel column base connections equipped with replaceable yielding steel angles under cyclic loading conditions. Utilizing a combined methodology of finite element analysis through ABAQUS and the Taguchi design of experiments (DOE) approach, the research systematically evaluates the influence of three critical parameters: steel angle thickness, applied axial load ratio, and anchor bolt gauge distance from the column edge. The numerical model was rigorously validated against existing experimental results, demonstrating strong agreement and confirming its capability to accurately simulate the nonlinear hysteretic response of the connections. Nine strategically designed parameter combinations based on an L9 orthogonal array enabled an efficient exploration of the parameter space while capturing both individual and interactive effects. Statistical analysis via analysis of variance (ANOVA) identified the thickness of the steel angle as the most significant factor, accounting for approximately 59.43% of the variation in the maximum flexural moment capacity, followed by the gauge distance (24.95%) and axial load ratio (11.92%). The optimal parameter set—comprising a 10 mm angle thickness, 0.2 axial load ratio relative to column capacity, and 40 mm gauge distance—yielded a peak flexural moment capacity of 30.71 kN·m, closely matching the finite element prediction of 30.56 kN·m. Hysteresis curve analyses reveal enhanced energy dissipation capacity, increased initial stiffness, and improved ductility in the optimized configuration, although the connection behavior consistently remains within the pinned range as per ANSI/AISC 360-16 specifications. The concentrated plasticity in the replaceable angle elements effectively localizes damage, promoting easy post-earthquake repair without compromising the main structural components. A regression model derived from the DOE results facilitates reliable predictions of flexural capacity based on the aforementioned parameters, underscoring the practical utility of the Taguchi method in seismic design optimization. These findings provide critical insights into the design of resilient, low-damage steel column base connections capable of sustaining seismic demands while enhancing reparability and lifecycle performance.

https://sjce.journals.sharif.edu/article_24222_338ab51c4c2c88328e001aab08fddcd2.pdf

Sharif University of Technology Sharif Journal of Civil Engineering 2676-4768 42 1 2026 05 22 Development of a Hybrid Machine Learning-Based Framework for Monitoring and Predicting Odor Pollution in Urban Surface Water Canals: A Case Study of the Ghiyasvand Canal, Tehran Development of a Hybrid Machine Learning-Based Framework for Monitoring and Predicting Odor Pollution in Urban Surface Water Canals: A Case Study of the Ghiyasvand Canal, Tehran 45 57 24237 10.24200/j30.2025.66941.3433 FA Ammar Safaie Department of Civil Engineering, Sharif University of Technology. 0000-0003-3327-2224 Mohammad Khanjani Department of Civil Engineering, Sharif University of Technology. Zahra Karimi Shavaki Department of Civil Engineering, Sharif University of Technology. Alireza Hadian Department of Civil Engineering, Sharif University of Technology. Amirhossein Haddadi Department of Civil Engineering, Sharif University of Technology. Hediye Rahmani Department of Civil Engineering, Sharif University of Technology. Journal Article 2025 05 24 Unpleasant odors emitted from urban surface‐runoff canals pose a significant environmental and public health challenge in large cities such as Tehran. These odors, primarily caused by anaerobic decomposition of organic matter and the inflow of untreated wastewater, degrade water quality, generate public dissatisfaction, and reduce the environmental health and livability of urban areas. Despite their widespread impact, the spatial distribution and intensity of odor emissions in such canals are rarely monitored systematically. To fill this gap, this study introduces a practical framework for monitoring, quantifying, and predicting odor intensity in urban surface water canals. The proposed framework was implemented and evaluated in a pilot project along the Ghiyasvand Canal in Tehran. Weekly field sampling was carried out at ten critical locations over a ten‐week period, during which key water‐quality parameters (including pH, electrical conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO), and water temperature) and meteorological variables (such as air temperature, wind speed, and relative humidity) were collected. In addition, odor intensity was measured with a portable odor meter. Pearson, Spearman, and Kendall correlation analyses, along with a random forest regression model, were employed to examine and predict the relationships between physicochemical and atmospheric variables and odor intensity. Correlation analyses indicated that water temperature, electrical conductivity, and air temperature were positively correlated with odor intensity, whereas DO showed a negative correlation, indicating its critical role in odor suppression. The developed model performed well in predicting odor intensity, achieving an accuracy of 83% for both training and testing data. This study demonstrates the potential of integrated field monitoring and machine learning approaches to support practical odor management in urban water systems, leading to improved environmental quality and public well-being. While the framework was applied to a specific case in Tehran, the results and approach are broadly applicable to similar urban settings facing odor-related challenges. Unpleasant odors emitted from urban surface‐runoff canals pose a significant environmental and public health challenge in large cities such as Tehran. These odors, primarily caused by anaerobic decomposition of organic matter and the inflow of untreated wastewater, degrade water quality, generate public dissatisfaction, and reduce the environmental health and livability of urban areas. Despite their widespread impact, the spatial distribution and intensity of odor emissions in such canals are rarely monitored systematically. To fill this gap, this study introduces a practical framework for monitoring, quantifying, and predicting odor intensity in urban surface water canals. The proposed framework was implemented and evaluated in a pilot project along the Ghiyasvand Canal in Tehran. Weekly field sampling was carried out at ten critical locations over a ten‐week period, during which key water‐quality parameters (including pH, electrical conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO), and water temperature) and meteorological variables (such as air temperature, wind speed, and relative humidity) were collected. In addition, odor intensity was measured with a portable odor meter. Pearson, Spearman, and Kendall correlation analyses, along with a random forest regression model, were employed to examine and predict the relationships between physicochemical and atmospheric variables and odor intensity. Correlation analyses indicated that water temperature, electrical conductivity, and air temperature were positively correlated with odor intensity, whereas DO showed a negative correlation, indicating its critical role in odor suppression. The developed model performed well in predicting odor intensity, achieving an accuracy of 83% for both training and testing data. This study demonstrates the potential of integrated field monitoring and machine learning approaches to support practical odor management in urban water systems, leading to improved environmental quality and public well-being. While the framework was applied to a specific case in Tehran, the results and approach are broadly applicable to similar urban settings facing odor-related challenges.

https://sjce.journals.sharif.edu/article_24237_680c256fb6e2c27e27a9d268e8379690.pdf

Sharif University of Technology Sharif Journal of Civil Engineering 2676-4768 42 1 2026 05 22 Finite Element Investigation of Novel Semi-Rigid Connection with Controlled Damage Position in CFS Frames Finite Element Investigation of Novel Semi-Rigid Connection with Controlled Damage Position in CFS Frames 59 74 24205 10.24200/j30.2025.67113.3437 FA Mohammad Reza Farajpour Department of Civil Engineering, Ta. C., Islamic Azad University, Tabriz, Iran. 0000-0001-5722-4855 Jamshid Sabouri Department of Civil Engineering, Ta. C., Islamic Azad University, Tabriz, Iran 0000-0001-5512-5220 Yousef Hosseinzadh Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran 0000-0003-4764-5458 Journal Article 2025 07 13 In this study, a novel semi-rigid connection with a Controlled Damage Position (CCDP) is introduced for cold-formed steel (CFS) frames, and its structural performance is thoroughly evaluated through both finite element (FE) modeling and experimental tests. The connection is specifically designed to incorporate a flexural fuse at the beam-to-column joint, thereby effectively relocating damage concentration away from the column and directing it toward a predefined region intended for controlled localized yielding. The proposed connection was fabricated using galvanized steel plates, which were carefully cut and bent to thicknesses of 1-, 2-, and 3-mm. Comparative results between FE simulations and experimental tests demonstrated excellent agreement, with the maximum deviation being less than 9%, confirming the reliability of the FE modeling approach. A detailed parametric investigation was conducted to assess the influence of key geometric parameters, including plate thickness, inclination angle of the connecting components, length of the control segment, and the size of flange stiffeners. The results indicated that increasing plate thickness significantly enhanced both the flexural strength and the initial stiffness of the connection. Furthermore, the parametric analysis revealed that extending the control segment length increased the flexural capacity by up to 18% and the initial stiffness by up to 12%, whereas removal of this segment prevented the proper localization of the plastic hinge. Increasing the inclination angle of the sloped component improved flexural capacity by approximately 13%, while enlarging the flange stiffener length enhanced the flexural resistance by up to 35%, although excessive stiffening could potentially increase the likelihood of local buckling in the beam. Among all the studied configurations, the specimen with 2-mm plates and a 70-mm control segment exhibited the highest moment capacity and initial stiffness. Moreover, the obtained moment–rotation curves confirmed that the CCDP connection provided reliable semi-rigid behavior and effectively controlled buckling within the designated fuse region; in most specimens, no local buckling was observed in either the beam or the column up to a rotation of 0.07 radians. In this study, a novel semi-rigid connection with a Controlled Damage Position (CCDP) is introduced for cold-formed steel (CFS) frames, and its structural performance is thoroughly evaluated through both finite element (FE) modeling and experimental tests. The connection is specifically designed to incorporate a flexural fuse at the beam-to-column joint, thereby effectively relocating damage concentration away from the column and directing it toward a predefined region intended for controlled localized yielding. The proposed connection was fabricated using galvanized steel plates, which were carefully cut and bent to thicknesses of 1-, 2-, and 3-mm. Comparative results between FE simulations and experimental tests demonstrated excellent agreement, with the maximum deviation being less than 9%, confirming the reliability of the FE modeling approach. A detailed parametric investigation was conducted to assess the influence of key geometric parameters, including plate thickness, inclination angle of the connecting components, length of the control segment, and the size of flange stiffeners. The results indicated that increasing plate thickness significantly enhanced both the flexural strength and the initial stiffness of the connection. Furthermore, the parametric analysis revealed that extending the control segment length increased the flexural capacity by up to 18% and the initial stiffness by up to 12%, whereas removal of this segment prevented the proper localization of the plastic hinge. Increasing the inclination angle of the sloped component improved flexural capacity by approximately 13%, while enlarging the flange stiffener length enhanced the flexural resistance by up to 35%, although excessive stiffening could potentially increase the likelihood of local buckling in the beam. Among all the studied configurations, the specimen with 2-mm plates and a 70-mm control segment exhibited the highest moment capacity and initial stiffness. Moreover, the obtained moment–rotation curves confirmed that the CCDP connection provided reliable semi-rigid behavior and effectively controlled buckling within the designated fuse region; in most specimens, no local buckling was observed in either the beam or the column up to a rotation of 0.07 radians.

https://sjce.journals.sharif.edu/article_24205_8b1d4dae4314191be293526cf052e257.pdf

Sharif University of Technology Sharif Journal of Civil Engineering 2676-4768 42 1 2026 06 21 Neural Network Models for Predicting Fracture Energy and Toughness of Asphalt Mixtures Based on Semi-Circular Bending (SCB) Test Results Neural Network Models for Predicting Fracture Energy and Toughness of Asphalt Mixtures Based on Semi-Circular Bending (SCB) Test Results 75 84 24238 10.24200/j30.2025.64904.3353 FA Mohammad Samanipour School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran. Mohammad Zia Alavi School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran. Abbas Babazadeh School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran. 0000-0002-3838-5220 Journal Article 2025 02 05 The measurement of failure characteristics in the semi-circular bending (SCB) test of asphalt mixtures has significantly expanded over the last decade, with laboratory study results being published in numerous studies. The purpose of this article is to develop neural network models to predict the fracture energy and fracture toughness of asphalt mixtures based on data mining principles. For this purpose, 3290 data points from SCB fracture test results of asphalt samples were collected from 102 credible articles. Out of these, 1627 data points are used to predict fracture energy and 1663 data points are used to predict fracture toughness. The input layer of the neural networks includes data collected on fracture mode, loading rate, test temperature, sample thickness, notch dimension, presence of modifier, maximum nominal aggregate size, air void percentage, binder percentage, aging, and binder type of asphalt mixtures. The output layer generates fracture energy and fracture toughness for each assumed input. The results show that the constructed neural network models can predict fracture energy with 75% accuracy and fracture toughness with 70% accuracy. The sensitivity analysis reveals that the loading rate, test temperature, air void percentage, and binder percentage are the most influential characteristics on the prediction models' results. The integration of data mining principles and neural network algorithms enhances the prediction accuracy of asphalt mixture properties, which can aid in designing more durable pavement materials. The accuracy of the models was validated using metrics such as Root Mean Squared Error (RMSE) and Mean Squared Error (MSE), with RMSE values of 0.727 for fracture energy and 0.170 for fracture toughness. The regression analysis between actual and predicted values showed R² values of 0.75 for fracture energy and 0.70 for fracture toughness, indicating robust model performance. In conclusion, the neural network models based on collected SCB test data exhibit acceptable performance in predicting the fracture energy and toughness of asphalt mixtures. The study's findings highlight the importance of considering key input variables such as air void percentage, binder percentage, test temperature, and loading rate in developing reliable predictive models for asphalt mixture behavior. The measurement of failure characteristics in the semi-circular bending (SCB) test of asphalt mixtures has significantly expanded over the last decade, with laboratory study results being published in numerous studies. The purpose of this article is to develop neural network models to predict the fracture energy and fracture toughness of asphalt mixtures based on data mining principles. For this purpose, 3290 data points from SCB fracture test results of asphalt samples were collected from 102 credible articles. Out of these, 1627 data points are used to predict fracture energy and 1663 data points are used to predict fracture toughness. The input layer of the neural networks includes data collected on fracture mode, loading rate, test temperature, sample thickness, notch dimension, presence of modifier, maximum nominal aggregate size, air void percentage, binder percentage, aging, and binder type of asphalt mixtures. The output layer generates fracture energy and fracture toughness for each assumed input. The results show that the constructed neural network models can predict fracture energy with 75% accuracy and fracture toughness with 70% accuracy. The sensitivity analysis reveals that the loading rate, test temperature, air void percentage, and binder percentage are the most influential characteristics on the prediction models' results. The integration of data mining principles and neural network algorithms enhances the prediction accuracy of asphalt mixture properties, which can aid in designing more durable pavement materials. The accuracy of the models was validated using metrics such as Root Mean Squared Error (RMSE) and Mean Squared Error (MSE), with RMSE values of 0.727 for fracture energy and 0.170 for fracture toughness. The regression analysis between actual and predicted values showed R² values of 0.75 for fracture energy and 0.70 for fracture toughness, indicating robust model performance. In conclusion, the neural network models based on collected SCB test data exhibit acceptable performance in predicting the fracture energy and toughness of asphalt mixtures. The study's findings highlight the importance of considering key input variables such as air void percentage, binder percentage, test temperature, and loading rate in developing reliable predictive models for asphalt mixture behavior.

https://sjce.journals.sharif.edu/article_24238_e1e3e4b7d027be780bcfa295e223fa37.pdf

Sharif University of Technology Sharif Journal of Civil Engineering 2676-4768 42 1 2026 05 22 Investigating and Determining Project Success Factors in Iraq: Advice for Exporters of Engineering Services Investigating and Determining Project Success Factors in Iraq: Advice for Exporters of Engineering Services 85 102 24206 10.24200/j30.2025.66077.3400 FA Khaldonn Allousi Department of Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran. Amir Hossein Hosseini Sarcheshmeh Department of Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran. Ali Rahimian School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran. - - Department of Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran. Jafar Bolouri Department of Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran. Journal Article 2025 01 18 Project success in the construction industry refers to the achievement of predetermined goals for the project and the organization within specified time and cost constraints, along with the quality expected by the client. In this context, Iraq, as a developing country, faces numerous challenges regarding project failures. A more detailed examination of the reasons behind these issues could be beneficial for stakeholders in Iran''s construction industry, especially since Iraq is currently one of Iran''s largest trading partners. Understanding the factors contributing to the success of construction projects in Iraq can serve as a valuable guide for those involved in exporting technical services to this country. In this study, the factors influencing the success of construction projects in Iraq were identified through two sources: reputable scientific articles and interviews with 40 expert professionals. After prioritizing these factors, six final elements were identified, including the financial capability of the contracting company, support from senior management, utilization of consulting firms, evaluation and selection of the best contracting company, use of turnkey contracts, and coordination among various project sectors. Among these factors, three, namely the financial capability of the contracting company, support from senior management, and evaluation and selection of the best company, were presented quantitatively, while the other factors were presented qualitatively. In this research, school construction projects in Wasat province were selected as a case study, and 32 projects were analyzed to assess the impact of these six factors. Given that the projects had similar dimensions, construction methods, and costs, time delay was used as a key parameter to determine project success or failure. Based on this criterion, 17 projects were identified as successful and 15 as unsuccessful. Ultimately, a significant relationship was found among all identified success factors in these projects, and recommendations were provided for achieving success in similar projects. Project success in the construction industry refers to the achievement of predetermined goals for the project and the organization within specified time and cost constraints, along with the quality expected by the client. In this context, Iraq, as a developing country, faces numerous challenges regarding project failures. A more detailed examination of the reasons behind these issues could be beneficial for stakeholders in Iran''s construction industry, especially since Iraq is currently one of Iran''s largest trading partners. Understanding the factors contributing to the success of construction projects in Iraq can serve as a valuable guide for those involved in exporting technical services to this country. In this study, the factors influencing the success of construction projects in Iraq were identified through two sources: reputable scientific articles and interviews with 40 expert professionals. After prioritizing these factors, six final elements were identified, including the financial capability of the contracting company, support from senior management, utilization of consulting firms, evaluation and selection of the best contracting company, use of turnkey contracts, and coordination among various project sectors. Among these factors, three, namely the financial capability of the contracting company, support from senior management, and evaluation and selection of the best company, were presented quantitatively, while the other factors were presented qualitatively. In this research, school construction projects in Wasat province were selected as a case study, and 32 projects were analyzed to assess the impact of these six factors. Given that the projects had similar dimensions, construction methods, and costs, time delay was used as a key parameter to determine project success or failure. Based on this criterion, 17 projects were identified as successful and 15 as unsuccessful. Ultimately, a significant relationship was found among all identified success factors in these projects, and recommendations were provided for achieving success in similar projects.

https://sjce.journals.sharif.edu/article_24206_6005fb5ae0d58f2b5c9dd63b6089b92b.pdf

Sharif University of Technology Sharif Journal of Civil Engineering 2676-4768 42 1 2026 05 22 Investigating the Dynamic Stability Index of Steel Structures Investigating the Dynamic Stability Index of Steel Structures 103 115 24219 10.24200/j30.2025.66675.3424 FA Mohammadreza Gholami Department of Civil Engineering, Faculty of Engineering, University of Qom, Qom, Iran 0009-0005-2022-7039 Mohamadreza Shokrzadeh Department of Civil Engineering, Faculty of Engineering, University of Qom, Qom, Iran. 0000-0001-9291-7833 Mahdi Sharifi Department of Civil Engineering, Faculty of Engineering, University of Qom, Qom, Iran. Journal Article 2025 05 03 The stability index, defined as the ratio of moments caused by secondary P-Delta effects to those resulting from design story shear forces, serves as a critical parameter in assessing structural behavior. These P-Delta effects, arising from the interaction between axial loads and lateral displacements, can significantly influence the overall structural response. While current design codes primarily provide static relationships for calculating the stability index - typically developed for lateral loads such as wind - this study adopts an innovative approach by investigating the stability index from both dynamic and nonlinear static perspectives. To obtain reliable results, three reference structures with varying heights (3-, 9-, and 20-story buildings) were analyzed using two advanced analytical methods: Incremental Dynamic Analysis (IDA) and Nonlinear Static Analysis. The research findings reveal that for low-rise buildings, when inelastic deformations are considered, static stability index values closely approximate their dynamic counterparts. However, for medium- and high-rise structures, significant discrepancies emerge between results obtained from the two methods. A key finding demonstrates that the dynamically computed stability index exceeds code-specified threshold values (0.1 and 0.25) for all cases except those with low acceleration levels (below 0.2g). The study further establishes that dynamic stability index values differ substantially from those recommended in current design codes. These results suggest that traditional stability assessment methods may prove non-conservative for tall structures subjected to severe dynamic effects. Significant influence of building height on the relationship between static and dynamic stability indices. Critical importance of considering nonlinear effects in stability calculations for tall structures. Necessity for developing new relationships that properly incorporate dynamic effects in stability index computation. These findings provide a solid foundation for updating structural design codes and developing more precise analytical methods. Future studies should investigate a broader range of structures with various lateral load-resisting systems to establish more comprehensive relationships for stability index calculation. Implementation of height-dependent correction factors in stability evaluation. Development of dynamic amplification coefficients for P-Delta effects. Inclusion of higher-mode effects in stability assessments for tall buildings. Consideration of material nonlinearity and geometric imperfections in analytical models. The study's outcomes emphasize the need for code revisions to address stability concerns in modern tall building designs, particularly in seismic-prone regions. The proposed methodology offers a more realistic assessment of structural stability under extreme loading conditions. The stability index, defined as the ratio of moments caused by secondary P-Delta effects to those resulting from design story shear forces, serves as a critical parameter in assessing structural behavior. These P-Delta effects, arising from the interaction between axial loads and lateral displacements, can significantly influence the overall structural response. While current design codes primarily provide static relationships for calculating the stability index - typically developed for lateral loads such as wind - this study adopts an innovative approach by investigating the stability index from both dynamic and nonlinear static perspectives. To obtain reliable results, three reference structures with varying heights (3-, 9-, and 20-story buildings) were analyzed using two advanced analytical methods: Incremental Dynamic Analysis (IDA) and Nonlinear Static Analysis. The research findings reveal that for low-rise buildings, when inelastic deformations are considered, static stability index values closely approximate their dynamic counterparts. However, for medium- and high-rise structures, significant discrepancies emerge between results obtained from the two methods. A key finding demonstrates that the dynamically computed stability index exceeds code-specified threshold values (0.1 and 0.25) for all cases except those with low acceleration levels (below 0.2g). The study further establishes that dynamic stability index values differ substantially from those recommended in current design codes. These results suggest that traditional stability assessment methods may prove non-conservative for tall structures subjected to severe dynamic effects. Significant influence of building height on the relationship between static and dynamic stability indices. Critical importance of considering nonlinear effects in stability calculations for tall structures. Necessity for developing new relationships that properly incorporate dynamic effects in stability index computation. These findings provide a solid foundation for updating structural design codes and developing more precise analytical methods. Future studies should investigate a broader range of structures with various lateral load-resisting systems to establish more comprehensive relationships for stability index calculation. Implementation of height-dependent correction factors in stability evaluation. Development of dynamic amplification coefficients for P-Delta effects. Inclusion of higher-mode effects in stability assessments for tall buildings. Consideration of material nonlinearity and geometric imperfections in analytical models. The study's outcomes emphasize the need for code revisions to address stability concerns in modern tall building designs, particularly in seismic-prone regions. The proposed methodology offers a more realistic assessment of structural stability under extreme loading conditions.

https://sjce.journals.sharif.edu/article_24219_5b4e256d43c2e28b425581832a4e0a09.pdf

Sharif University of Technology Sharif Journal of Civil Engineering 2676-4768 42 1 2026 06 21 Investigation of Parameters Affecting Bond Strength and Pull-Out Behavior of Polyethylene Terephthalate Ropes in Steel Fiber-Reinforced Cementitious Composites Investigation of Parameters Affecting Bond Strength and Pull-Out Behavior of Polyethylene Terephthalate Ropes in Steel Fiber-Reinforced Cementitious Composites 117 126 24239 10.24200/j30.2025.67085.3436 FA Reza Akbarifar Department of Civil Engineering, Semnan branch, Islamic Azad University, Semnan, Iran 0009-0005-9276-3498 Alireza Mortezaei Department of Civil Engineering, Semnan branch, Islamic Azad University, Semnan, Iran 0000-0001-6802-3661 Ali Babaei Department of Civil Engineering, Semnan branch, Islamic Azad University, Semnan, Iran Journal Article 2025 06 29 This study investigates the bond behavior of braided ropes made from recycled polyethylene terephthalate (PET) as a potential alternative to conventional steel reinforcement in fiber-reinforced cementitious composites (FRCC). Pull-out tests were conducted according to RILEM RC6 standards on FRCC specimens containing different volume fractions of steel fibers, using steel rebars and PET ropes with equal diameters (14 mm). The experimental results revealed that the maximum pull-out force was approximately 30 kN for steel bars and 7.6 kN for PET ropes, indicating a 75% reduction in bond strength for PET compared to steel. However, the displacement corresponding to the peak load was about 23.5 mm for PET ropes and only 0.6 mm for steel bars, representing a 40-fold increase in ductility for PET. In all experiments, PET ropes failed internally without being pulled out from the matrix, while steel bars exhibited bond-slip failure. The inclusion of steel fibers in the matrix significantly enhanced the bond performance, especially in terms of energy absorption and post-peak ductility. For instance, in specimens containing 1% steel fibers, the maximum pull-out load of the PET ropes reached 7.6 KN at a displacement of 9.3 mm, showing a clear improvement over fiberless samples. The experimental observations were further analyzed by comparing the bond–slip responses of PET and steel reinforcements, which demonstrated that PET exhibits a gradual softening after peak load instead of a brittle bond loss. This characteristic suggests a more stable and energy-dissipating interfacial mechanism. In addition, the use of recycled PET not only provides a sustainable and eco-friendly reinforcement option but also contributes to reducing construction waste and CO₂ emissions. Such properties make PET ropes particularly suitable for structures requiring high ductility and seismic resilience. The findings of this study can serve as a reference for future modeling of PET–concrete interface behavior and for developing design guidelines for sustainable fiber-reinforced composites. This study investigates the bond behavior of braided ropes made from recycled polyethylene terephthalate (PET) as a potential alternative to conventional steel reinforcement in fiber-reinforced cementitious composites (FRCC). Pull-out tests were conducted according to RILEM RC6 standards on FRCC specimens containing different volume fractions of steel fibers, using steel rebars and PET ropes with equal diameters (14 mm). The experimental results revealed that the maximum pull-out force was approximately 30 kN for steel bars and 7.6 kN for PET ropes, indicating a 75% reduction in bond strength for PET compared to steel. However, the displacement corresponding to the peak load was about 23.5 mm for PET ropes and only 0.6 mm for steel bars, representing a 40-fold increase in ductility for PET. In all experiments, PET ropes failed internally without being pulled out from the matrix, while steel bars exhibited bond-slip failure. The inclusion of steel fibers in the matrix significantly enhanced the bond performance, especially in terms of energy absorption and post-peak ductility. For instance, in specimens containing 1% steel fibers, the maximum pull-out load of the PET ropes reached 7.6 KN at a displacement of 9.3 mm, showing a clear improvement over fiberless samples. The experimental observations were further analyzed by comparing the bond–slip responses of PET and steel reinforcements, which demonstrated that PET exhibits a gradual softening after peak load instead of a brittle bond loss. This characteristic suggests a more stable and energy-dissipating interfacial mechanism. In addition, the use of recycled PET not only provides a sustainable and eco-friendly reinforcement option but also contributes to reducing construction waste and CO₂ emissions. Such properties make PET ropes particularly suitable for structures requiring high ductility and seismic resilience. The findings of this study can serve as a reference for future modeling of PET–concrete interface behavior and for developing design guidelines for sustainable fiber-reinforced composites.

https://sjce.journals.sharif.edu/article_24239_b83612231364b4cde46b9282b2d4d054.pdf

Sharif University of Technology Sharif Journal of Civil Engineering 2676-4768 42 1 2026 05 22 Study of Unsaturated Behavior of Stabilized Gypsum Sand Soil from Iraq with Cement and CKD Study of Unsaturated Behavior of Stabilized Gypsum Sand Soil from Iraq with Cement and CKD 137 141 24156 10.24200/j30.2026.68033.3473 FA Ahmed Kamil Abraheim Alkinani 1Department of Civil Engineering, Ferdowsi University of Mashhad, Iran. Ali Akhtarpour 1Department of Civil Engineering, Ferdowsi University of Mashhad, Iran. 0000-0003-1654-0194 Mustafa M. Abdalhusein 2Department of Civil Engineering, University of Kufa, Al-Najaf, Iraq. Journal Article 2025 10 20 This research explores the compaction behaviour of Iraqi gypsum-sand soils stabilized with cement and cement kiln dust (CKD) at varying additive percentages (1%, 3%, 5%, and 7%) under different compaction levels (90% and 95%). Laboratory experiments were conducted using a modified oedometer to obtain Soil Water Retention Curves (SWRC) and assess the impact of matric suction on soil compressibility and water retention. The study reveals that both cement (3%) and CKD (5%) significantly improve the water retention capacity of the soil, reduce hysteresis effects, and enhance its resistance to compaction and swelling. These additives positively influence the soil’s water-holding capacity, thereby improving its performance in both saturated and unsaturated conditions. The Van Genuchten model was effectively used to describe the SWRC, demonstrating that cement outperforms CKD in terms of hydraulic behaviour due to the formation of stronger cementitious bonds, which contribute to better soil structure and stability. Additionally, the improvement analysis highlights that stabilization at higher compaction levels (95%) and under conditions of increased matric suction results in greater effectiveness, with cement-treated soils showing the most significant performance improvement. This is particularly critical for applications in environments where soil behaviour under varying moisture content is a key factor. Furthermore, Scanning Electron Microscope (SEM) analysis confirmed the microstructural enhancements caused by cement hydration and the pozzolanic reactions of CKD, which help form a more stable and cohesive structure at the particle level. The results showed that adding 3% cement and 5% CKD reduced hysteresis and improved the SWRC curve, especially at 95% density. Also, at 95% density and 60 kPa suction, cement reached an improvement factor of 83% and CKD reached 33%. The findings underline the importance of both the type of stabilizing agent and the compaction level in improving the hydraulic properties and long-term stability of Iraqi gypsum-rich sandy soils. This research emphasizes the potential of using cement and CKD for soil stabilization, particularly in regions where moisture variability and soil behaviour are significant challenges. These insights contribute to the development of more durable and sustainable soil stabilization techniques in geotechnical engineering. This research explores the compaction behaviour of Iraqi gypsum-sand soils stabilized with cement and cement kiln dust (CKD) at varying additive percentages (1%, 3%, 5%, and 7%) under different compaction levels (90% and 95%). Laboratory experiments were conducted using a modified oedometer to obtain Soil Water Retention Curves (SWRC) and assess the impact of matric suction on soil compressibility and water retention. The study reveals that both cement (3%) and CKD (5%) significantly improve the water retention capacity of the soil, reduce hysteresis effects, and enhance its resistance to compaction and swelling. These additives positively influence the soil’s water-holding capacity, thereby improving its performance in both saturated and unsaturated conditions. The Van Genuchten model was effectively used to describe the SWRC, demonstrating that cement outperforms CKD in terms of hydraulic behaviour due to the formation of stronger cementitious bonds, which contribute to better soil structure and stability. Additionally, the improvement analysis highlights that stabilization at higher compaction levels (95%) and under conditions of increased matric suction results in greater effectiveness, with cement-treated soils showing the most significant performance improvement. This is particularly critical for applications in environments where soil behaviour under varying moisture content is a key factor. Furthermore, Scanning Electron Microscope (SEM) analysis confirmed the microstructural enhancements caused by cement hydration and the pozzolanic reactions of CKD, which help form a more stable and cohesive structure at the particle level. The results showed that adding 3% cement and 5% CKD reduced hysteresis and improved the SWRC curve, especially at 95% density. Also, at 95% density and 60 kPa suction, cement reached an improvement factor of 83% and CKD reached 33%. The findings underline the importance of both the type of stabilizing agent and the compaction level in improving the hydraulic properties and long-term stability of Iraqi gypsum-rich sandy soils. This research emphasizes the potential of using cement and CKD for soil stabilization, particularly in regions where moisture variability and soil behaviour are significant challenges. These insights contribute to the development of more durable and sustainable soil stabilization techniques in geotechnical engineering.

https://sjce.journals.sharif.edu/article_24156_9dc69f4a9d78d28dc1ba5697a159c546.pdf