https://jtie.semnan.ac.ir/ Journal of Transportation Infrastructure Engineering en daily 1 Fri, 22 May 2026 00:00:00 +0330 Fri, 22 May 2026 00:00:00 +0330 https://jtie.semnan.ac.ir/article_10599.html Steel slag, as one of the most favorable recycled industrial by-products, is widely used in green asphalt mixtures as a sustainable alternative to a portion of natural mineral aggregates. In this study, the effect of adding steel slag powder as a filler on Mode I fracture toughness of Hot Mix Asphalt (HMA) was investigated. circular bending specimens with a straight-through notch (ENDB) were utilized to perform the fracture tests. Different HMA mixtures containing 0%, 3%, and 5% steel slag powder by weight of total filler were prepared using the Superpave Gyratory Compactor at a target air void content of 7%. Mode I fracture experiments were conducted under symmetric loading at an intermediate temperature of +25°C and a low temperature of −12°C. Two key fracture parameters, fracture energy and fracture toughness, were calculated and analyzed to evaluate the cracking resistance of the asphalt mixtures. The results indicated that the addition of steel slag powder and the increase in its percentage significantly improved both fracture toughness and fracture energy at both test temperatures. The highest values of fracture energy and fracture toughness were observed in the mixture containing 5% steel slag powder. Furthermore, increasing the test temperature resulted in a decrease in fracture toughness and an increase in fracture energy. https://jtie.semnan.ac.ir/article_10600.html The increasing use of concrete in concrete pavements is accompanied by serious environmental, economic and technical challenges. The high consumption of Portland cement and natural aggregates leads to the destruction of natural resources, greenhouse gas emissions and waste management problems caused by construction waste. The use of recycled concrete aggregates (RCA)1 as a partial replacement for natural aggregates is considered a sustainable solution, but due to high water absorption (5-10% higher than natural aggregate), higher porosity and weak interfacial transition zone (ITZ)2, it reduces the compressive strength of concrete by 10-20% and weakens its durability against environmental factors. The present study investigated the effect of simultaneous use of recycled concrete aggregates (with 25 and 50 percent replacement levels), Class F fly ash as a cement supplement (with 25 and 50 percent levels), and polypropylene macrosynthetic fibers (with 0.4 and 0.6 percent volume percentages) on the mechanical properties and durability of pavement concrete. Ten mix designs including a control sample were designed and manufactured. Fresh concrete slump tests, compressive strength at 7 and 28 days, tensile strength, elastic modulus, and water absorption were performed on cubic and cylindrical samples. The results showed that RCA replacement alone reduced compressive strength and increased water absorption, but the simultaneous addition of fly ash and macrosynthetic fibers significantly compensated for this performance loss. The optimal design combination (T8) (25 percent RCA + 25 percent fly ash + 0.4 percent macrosynthetic fibers) provided the best results; So that the 28-day compressive strength reached 31.48 MPa (8.5% higher than the control sample), tensile strength reached 2.81 MPa, and water absorption reached 1.41%. This combination, by creating a synergistic effect in improving the microstructure of the cement paste, strengthening the interfacial transition zone, and reducing porosity, provides a sustainable, economical, and resistant pavement concrete suitable for Iran's climatic https://jtie.semnan.ac.ir/article_10005.html Hot Mix Asphalt (HMA), although widely used in pavement construction due to its favorable mechanical properties, is highly affected by environmental and chemical conditions of surface runoff. The aim of this study is to investigate the effect of runoff pH variations (4, 7, and 9) on the adhesion between bitumen and aggregates and the mechanical failure parameters of asphalt mixtures. To this end, a series of laboratory tests, including Indirect Tensile Strength and moisture sensitivity (ITS/TSR), Semi-Circular Bending (SCB) at low temperature, Indirect Tensile Fatigue Test (ITFT), and contact angle measurements for Surface Free Energy (SFE) analysis were performed. The results indicated that acidification of the environment (pH = 4) significantly increased the contact angle and reduced the total surface free energy of bitumen from about 46.14 to 52.12 (ergs/cm²), reflecting a decline in wettability and adhesion. TSR values decreased markedly under acidic conditions, while a relative improvement was observed in alkaline conditions. In addition, the Indirect Tensile Strength and SCB indices (peak load and fracture energy) were considerably reduced in the acidic environment; for example, the maximum load of the samples dropped by more than 20% compared to the neutral condition. Fatigue tests showed that fatigue life decreased sharply in acidic conditions, whereas alkaline conditions provided a relative improvement compared to neutral conditions, although still lower than that of the dry state. Overall, the findings demonstrate that acidic runoff has the most detrimental effect on the adhesion and mechanical durability of HMA, while alkaline conditions may partially compensate for moisture-induced damage. These results highlight the importance of considering environmental chemical conditions in the design and maintenance of pavements, particularly in urban and industrial areas with a high probability of acidic runoff https://jtie.semnan.ac.ir/article_10585.html Cracking is one of the main failure mechanisms in asphalt pavements, leading to reduced service life and increased maintenance costs. The objective of this research is to comprehensively evaluate the fracture behavior of basalt fiber-reinforced asphalt mixtures using the Semi-Circular Bending (SCB) test. The main innovation of this study lies in the simultaneous analysis of fracture mechanics parameters in different modes and the determination of the optimal range of basalt fiber content to improve fracture behavior. Asphalt samples with different percentages of basalt fibers (0.2, 0.3, 0.4, and 0.5% by weight) were prepared, and key fracture parameters including critical load (Pcr), fracture energy (Gf), fracture toughness (KIC), and Crack Resistance Index (CRI) were analyzed at low temperatures (-10 and 0°C) and intermediate temperature (10°C). The results showed that basalt fibers, by creating a reinforcing network in the mixture, prolong the crack propagation path and increase energy absorption capacity. At low temperatures, the most positive effect of fibers was observed in tensile mode (Mode I), while shear mode (Mode II) showed less sensitivity to increasing fiber content. Fracture energy and fracture toughness increased with increasing fiber content up to an optimal range (0.3-0.4%) and stabilized or slightly decreased beyond that. The CRI index at 10°C reflected the combined effect of critical load and fracture energy and showed a significant improvement with increasing fiber content. The results of analyzing different fracture modes indicated that basalt fibers play an effective role in reducing stress concentration and increasing the structural stability of asphalt mixtures. https://jtie.semnan.ac.ir/article_10611.html Marl soils are problematic soils with widespread distribution in Iran and other parts of the world. These soils exhibit good bearing capacity and strength in dry conditions; however, their strength and bearing capacity significantly decrease in the presence of moisture, which emphasizes the necessity of stabilizing marl soil. In the present study, lime, as a traditional stabilizer, and xanthan gum, an eco-friendly biopolymer, were used for stabilizing marl soil. The mechanical behavior of marl soil stabilized with 3%, 4%, and 5% lime by dry soil weight, and xanthan gum at 0.5%, 1%, and 1.5% by dry soil weight, has been discussed and compared. These evaluations were conducted using compaction, unconfined compressive strength (UCS), direct shear, and California Bearing Ratio (CBR) tests. According to the results, increasing the lime content to 4% and xanthan gum to 1% led to a dry density increase of 1.12 and 1.14 times, respectively. The UCS test showed an increase of 4.33 times for lime and 7.66 times for xanthan gum. Additionally, the direct shear test revealed that the cohesion of soil increased by 1.44 times with 5% lime and by 2.52 times with 1.5% xanthan gum. Regarding the internal friction angle, a 1.33-fold increase was observed for 4% lime and approximately 1.5-fold for 1.5% xanthan gum. The CBR value increased by 2.11 times for 4% lime and 2.22 times for 1.5% xanthan gum. https://jtie.semnan.ac.ir/article_10675.html In recent years, Ultra‑High‑Performance Concrete (UHPC) has gained considerable attention as a suitable material for producing precast components such as manhole covers, owing to its very high mechanical strength, excellent durability, and enhanced post‑cracking behavior. In this study, the effects of different types of fibers and nanosilica on the microstructure and mechanical performance of UHPC‑based concrete manhole covers are investigated. First, the performance of three types of fibers—steel, glass, and polypropylene—each at a volume fraction of 1%, was evaluated in UHPC to determine the most suitable fiber for concrete manhole cover applications. Compressive strength, load-bearing capacity, and freeze–thaw resistance tests were conducted on the specimens in accordance with the Iranian National Standard. The results showed that the incorporation of fibers improved the compressive strength and load‑bearing capacity of the covers, with steel fibers exhibiting the greatest enhancement, increasing the compressive strength by 19% to about 180 MPa and increasing load capacity from 6 tons to 12.5 tons. In the next stage, 1% nanosilica was added to the mixture containing steel fibers. The presence of nanosilica increased the compressive strength to about 200 MPa and the load‑bearing capacity to 14 tons. Specimens containing steel fibers and nanosilica exhibited a lower reduction in strength after freeze–thaw cycling. Microstructural analyses using Scanning Electron Microscopy (SEM) and X‑ray Diffraction (XRD) revealed that nanosilica, through nucleation effects, pozzolanic reactions, and filler action, reduced porosity, increased matrix density, and improved the interfacial transition zone (ITZ) between fibers and matrix. The findings indicate that the combined use of steel fibers and nanosilica in UHPC enhances mechanical properties and durability, providing a sustainable and economically viable solution for concrete manhole covers from a life-cycle perspective. https://jtie.semnan.ac.ir/article_10590.html In this study, the performance of modular flowerbox systems as semi-structural and bio-sustainable stabilizing elements was evaluated for improving the geotechnical behavior and stability of urban trenches in arid climates. To this end, six representative urban trenches were selected and subjected to field monitoring. Geotechnical data including natural moisture content, wet density, Standard Penetration Test (SPT) results, internal friction angle, effective cohesion, and recorded settlements over a six-month period were collected and analyzed. Stability analysis was conducted using finite element modeling in PLAXIS. In addition, data-driven approaches including XGBoost, Random Forest, and Multilayer Perceptron (MLP) neural networks were employed to predict settlement and analyze soil behavior. Model input parameters were calibrated based on laboratory results and instrumentation data, and model performance was evaluated using 10-fold cross-validation. Numerical modeling results indicated that the installation of modular flowerboxes reduced surface settlement by 38% (from an average of 12.5 mm to 7.75 mm) and increased the factor of safety by 37% (from 1.15 to 1.57). Due to the shallow trench geometry, the influence of surface structural elements was clearly reflected in stress redistribution and displacement patterns. A reduction in horizontal stress ranging from 9 to 13 kPa, along with decreased lateral wall displacement, was also observed. In the data-driven analysis, the XGBoost algorithm achieved the highest predictive accuracy, with an RMSE of 1.87 mm and a coefficient of determination (R²) of 0.94, demonstrating strong agreement with field instrumentation data. The findings suggest that integrating bio-sustainable surface systems with numerical modeling and intelligent data-driven techniques provides an efficient, cost-effective, and reliable approach for enhancing the stability of urban trenches, particularly in sandy–silty soils of arid regions. https://jtie.semnan.ac.ir/article_10536.html Considering the various uses of different types of asphalt mixtures in the world, the evaluation of the different behaviors of this mixture is significant in terms of performance and safety. Despite extensive research on the self-healing properties of asphalt mixtures, the specific impact of carbon nanotube (CNT)-modified Gilsonite asphalt binder on self-healing performance has not been thoroughly investigated. This study fills this gap by exploring the synergistic effects of CNT and Gilsonite on the self-healing behavior of asphalt mixtures, providing new insights into enhancing pavement properties. The goal of this study was to examine the self-healing behavior of asphalt mixtures containing asphalt binders modified with CNT. For this purpose, 7 wt% of Gilsonite-modified asphalt binder, as well as 0.05, 0.1, 0.2, and 0.3 wt% of CNT-modified asphalt binder, were added to the virgin binder with penetration grade 60/70 and mixed by a high-shear mixer. Then, the four-point bending test was conducted on the modified asphalt binder samples and examined under the constant strain test conditions at 500 and 800 microstrain levels. The results indicated that the addition of CNT to Gilsonite-modified asphalt binder had a remarkable impact on increasing the self-healing characteristics of asphalt samples. Moreover, results showed that the healed samples recovered the stiffness from a minimum of 69% to a maximum of 99% compared to the base samples. Also, the self-healing rate was considerably different between the base asphalt sample and mixtures modified with Gilsonite and CNT under constant strains. The findings suggest that incorporating CNT into Gilsonite-modified asphalt binder significantly enhances self-healing properties, with potential applications in extending the lifespan of pavements and reducing maintenance costs, and as a result, the economic efficiency and sustainability of transportation infrastructure increase. https://jtie.semnan.ac.ir/article_10715.html Accurate prediction of soil CBR (California Bearing Ratio) is of great importance in pavement design, but traditional CBR testing is time-consuming, expensive, and requires laboratory equipment. In this study, a hybrid approach based on Artificial Neural Network (ANN) and the Copula method is presented for estimating soil CBR. For this purpose, a database consisting of 1011 real samples of geotechnical parameters (including sand percentage, fine content, plastic limit, plasticity index, maximum dry density, and optimum moisture content) was collected and preprocessed. Then, a Multilayer Perceptron (MLP) neural network was designed and implemented using the Python programming language. Initial results showed that the base model achieved coefficient of determination (R²) values of 0.630 and 0.606 for training and testing data, respectively. In the following, to improve model performance, synthetic data were generated using the Copula method. Kolmogorov-Smirnov (KS) and Anderson-Darling (AD) statistical tests, along with comparison of probability density function (PDF) curves, demonstrated that the generated synthetic data had very high statistical similarity to the real data. After adding 50,000 synthetic data points to the training set, the neural network was retrained. The results indicated a significant improvement in model performance; the coefficient of determination (R²) for test data increased from 0.606 to 0.672, representing an approximately 11% improvement. The Mean Absolute Percentage Error (MAPE) decreased from 7.08% to 6.38%. Other evaluation metrics including MAE, RMSE, IOA, and IOS also showed meaningful improvements. The findings of this study confirm that the Copula method can serve as an effective strategy for synthetic data augmentation of geotechnical data and enhancing the accuracy of machine learning models. The proposed approach also offers significant economic and environmental benefits, including cost reduction, time savings, and decreased natural resource waste. https://jtie.semnan.ac.ir/article_10694.html In recent years, the use of machine learning methods for predicting the mechanical properties of concrete has received significant attention. Among these, accurate prediction of concrete compressive strength is considered one of the most important design parameters in concrete pavements. However, the limitation of experimental data is one of the main challenges in developing accurate machine learning models. In this study, a hybrid approach based on the Gaussian copula model and artificial neural networks (Copula-ANN) is proposed to augment the training data and improve the accuracy of compressive strength prediction of concrete. The dataset used in this research was extracted from the standard Yeh dataset and includes concrete mix design variables and compressive strength. The performance of the proposed model was compared with a conventional neural network and linear regression. The results showed that the use of the copula method significantly improved the performance of the neural network, increasing the coefficient of determination (R²) from 0.914 to 0.976. To evaluate the generalization capability of the model, external validation was performed using experimental data of high-strength concrete reported in reliable studies. The results of this validation indicated a good agreement between the predicted values and the experimental data, confirming the accuracy and reliability of the proposed model .Finally, the results demonstrate the ability of the proposed model to improve the accuracy of concrete compressive strength prediction and enhance the generalization capability of machine learning models in concrete engineering problems. https://jtie.semnan.ac.ir/article_10716.html Differences between the client (employer) and contractor in road construction projects, as a significant problem, can substantially impact project efficiency, scheduling, and quality. This research aims to identify, prioritize, and provide practical solutions for managing and reducing these differences. Initially, twenty of the most important factors contributing to disputes were extracted through literature review and interviews with road construction experts. These factors were evaluated and ranked using fuzzy hierarchical analysis, considering criteria such as probability of occurrence, impact on time and cost, repeatability, and complexity of resolution. The findings revealed that delays in completion due to general factors (weight 0.087), unrealistic schedules and inaccurate estimates (weight 0.073), and disputes arising from changes in work and overtime (weight 0.063) ranked first to third. Finally, based on the results obtained, practical and tailored solutions are provided for each of the prioritized conflicts, aiming to focus on the main factors and enhance collaboration and success in road construction projects . https://jtie.semnan.ac.ir/article_10717.html In recent years, the increase in traffic volume within urban freeway networks has led to intensified merging and weaving interactions in the areas of on-ramps and off-ramps. This phenomenon has had a significant impact on traffic performance, including increased delay, reduced speed, and higher traffic density. The objective of this study is to investigate the effects of geometric improvement of on-ramps and off-ramps on traffic flow performance in the Hemmat Highway in Tehran. In this research, the microscopic traffic simulation software AIMSUN Next 22 was used for modeling and analyzing traffic conditions. Field data, including traffic volume, speed, and ramp geometric characteristics, were collected. After model calibration, five selected ramps were evaluated under two scenarios: the “existing condition” and the “geometric improvement based on AASHTO standards.” Performance evaluation criteria included delay time, average traffic speed, traffic density, and CO emissions. Simulation results indicated that the implementation of geometric improvements led to a significant enhancement in traffic performance across all ramps. Specifically, the average delay time decreased by approximately 40% to 75%, traffic speed increased by 2 to 3 times, and traffic density experienced a noticeable reduction. In addition, CO emissions also decreased in the improved scenarios. Finally, the results demonstrate that improving ramp geometry can play an effective role in reducing traffic weaving and enhancing the overall performance of the highway network. Furthermore, the developed simulation model is capable of being applied to analyze similar scenarios in other urban roadways. It should be noted that the observed improvements are solely based on traffic performance indicators, and a direct safety assessment (based on accident data) was not conducted in this study. https://jtie.semnan.ac.ir/article_10779.html GB5 high-modulus asphalt mixtures are considered promising materials for high-performance pavements because of their favorable aggregate structure and desirable mechanical properties. However, high modulus values are commonly achieved using hard binders with low penetration grades, which increase mixture stiffness but also increase susceptibility to low-temperature thermal cracking. Therefore, improving low-temperature performance while maintaining adequate stiffness and modulus remains a significant challenge in pavement engineering. This study experimentally investigated the performance of GB5 asphalt mixtures containing 60/70 penetration grade bitumen modified with zinc oxide nanoparticles (Nano-ZnO) and styrene–butadiene–styrene (SBS) polymer, with particular emphasis on low-temperature behavior. The rheological properties of the binders were evaluated using the Bending Beam Rheometer (BBR) test. In addition, the corresponding asphalt mixtures were assessed in terms of dynamic modulus, low-temperature cracking resistance using the Semi-Circular Bending (SCB) test, and moisture susceptibility through the Indirect Tensile Strength (ITS) test. The results demonstrated that Nano-ZnO improved the low-temperature performance of the binder and enhanced the resistance of asphalt mixtures to thermal cracking. Furthermore, SBS improved the viscoelastic behavior of the binder, resulting in enhanced fatigue resistance and mechanical stability. The combined use of Nano-ZnO and SBS produced a synergistic effect and provided the best overall performance in terms of cracking resistance, moisture durability, and fatigue behavior. The BBR results indicated that the optimum combination of 4.2% Nano-ZnO and 3.7% SBS reduced flexural creep stiffness by 80% and increased the m-value by 31%. The T12 mixture (4.9% Nano-ZnO and 4.2% SBS) exhibited a dynamic modulus exceeding 16 GPa. Moreover, the SCB test showed more than a 70% improvement in fracture resistance at −5°C, while the ITS results indicated at least a 10% increase in moisture resistance. Overall, Nano-ZnO/SBS-modified 60/70 bitumen can effectively replace hard low-penetration binders in the production of high-modulus asphalt mixtures. https://jtie.semnan.ac.ir/article_10808.html In recent years, the use of bio-based additives and recycled materials in asphalt pavements has attracted considerable attention due to their potential to improve mechanical performance while reducing environmental impacts. This study investigated the individual and combined effects of lignin and cellulose nanofiber on the mechanical properties and microstructural characteristics of hot mix asphalt. In addition, the behavior of mixtures containing 50%reclaimed asphalt pavement was comparatively evaluated. For this purpose, lignin contents of 10%, 15%, and20% by weight of binder and CNF contents of 0.5%, 0.75%,and 1.0% by weight of binder were incorporated into the mixtures. The mechanical performance of the mixtures was evaluated using indirect tensile strength, dynamic creep, four-point bending beam fatigue, and low-temperature fracture resistance tests. The results indicated that lignin increased mixture stiffness and enhanced resistance to permanent deformation, whereas CNF exhibited a more pronounced effect on improving fatigue performance and low-temperature fracture resistance. The simultaneous use of lignin and CNF provided a more balanced combination of stiffness and flexibility in the asphalt mixtures. Fracture resistance results showed that increasing CNF content enhanced fracture energy and reduced mixture brittleness, while higher lignin contents reduced fracture toughness. Comparative evaluation of RAP-containing mixtures revealed that the presence of aged binder slightly improved rutting resistance but reduced fatigue and low-temperature cracking resistance. Microstructural analyses further demonstrated that increasing the dosage of either additive reduced binder homogeneity and increased the tendency for particle agglomeration. Based on the overall performance evaluation, the mixture containing approximately 10%lignin and 0.5–0.75%CNF exhibited the most favorable balance among the investigated performance indicators under different temperature conditions. The findings suggest that the controlled combined use of lignin and CNF can effectively balance rutting resistance, fatigue performance, and low-temperature cracking resistance, thereby providing a promising approach for the development of sustainable asphalt mixtures incorporating recycled materials. https://jtie.semnan.ac.ir/article_10809.html The increasing consumption of cement and the growing generation of metallic waste have highlighted the urgent need for developing sustainable concrete incorporating recycled materials. Although numerous studies have independently investigated the effects of microsilica or waste iron shavings on concrete properties, limited research has examined their combined influence on both the mechanical performance and durability characteristics of concrete. Consequently, a significant research gap remains regarding the synergistic behavior of these two materials. Therefore, the present study aimed to experimentally investigate the combined effects of microsilica and waste iron shavings on concrete performance and to identify the optimum mixture exhibiting the best overall performance within the investigated range. To this end, concrete mixtures containing 4% and 8% microsilica as partial replacements for cement and 3%, 5%, and 7% waste iron shavings as partial replacements for fine aggregate were prepared. Compressive strength, splitting tensile strength, flexural strength, water absorption, density, and electrical resistivity were evaluated at curing ages of 7, 28, and 90 days. The results indicated that replacing cement with 8% microsilica increased the 90-day compressive strength by approximately 29% compared with the control mixture. Furthermore, incorporating 3% waste iron shavings enhanced the compressive strength by approximately 22%, whereas increasing the iron shaving content to 7% resulted in a reduction in strength and an increase in water absorption. However, considering the overall performance in terms of mechanical properties and durability indicators, the mixture incorporating 8% microsilica and 3% waste iron shavings exhibited the most balanced and favorable performance. Overall, the findings demonstrate that the controlled incorporation of waste iron shavings in the presence of microsilica can simultaneously enhance the strength and durability of concrete through a synergistic effect, providing an effective approach for producing sustainable concrete with improved engineering performance. https://jtie.semnan.ac.ir/article_10870.html یکی از روش‌های نوین در زمینه بهبود عملکرد حرارتی روسازی، استفاده از روش گرمایش با امواج مایکروویو است. مخلوط‌های آسفالتی به دلیل ماهیت عایق سنگدانه‌ها و قیر، ضریب هدایت حرارتی پایینی دارند. این ویژگی در هنگام گرمایش با امواج مایکروویو منجر به ایجاد گرادیان دمایی شدید میان سطح و عمق لایه‌ی آسفالت می‌شود. برای غلبه بر این محدودیت، استفاده از افزودنی‌های مختلف جهت ایجاد یک شبکه انتقال حرارت یکنواخت مورد توجه محققین بسیاری قرار گرفته است. هدف اصلی این تحقیق بررسی تأثیر استایرن-بوتادین-استایرن (SBS) و الیاف کربن (CF) بر نرخ گرمایش و توزیع دمایی نمونه‌های آسفالتی تحت تابش امواج مایکروویو است. به منظور بررسی فرایند گرمایش، نمونه‌های آسفالتی در مدت زمان‌های 30، 60، 90 ،120و 150 ثانیه، در داخل دستگاه مایکروویو قرار گرفتند و سپس دمای ایجاد شده در سطح و داخل نمونه‌ها، مورد بررسی قرار گرفت. نتایج نشان داد که الیاف کربن باعث افزایش نرخ گرمایش و توزیع یکنواخت‌تر دمای نمونه‌ها نسبت به نمونه‌های شاهد می‌گردد. همچنین SBS دمای متوسط سطح و داخل نمونه‌های آسفالتی را کاهش داد و یکنواختی توزیع دما را ضعیف‌تر کرد. علاوه بر این، به منظور ارزیابی و مقایسه تأثیر این افزودنی‌ها بر خواص مکانیکی مخلوط آسفالتی از آزمایش خمش سه نقطه‌ای استفاده گردید. نتایج نشان داد که SBS منجر به افزایش 180 درصدی مقاومت نمونه‌ها نسبت به نمونه‌های شاهد می‌گردد. همچنین الیاف کربن مقاومت نمونه‏های آسفالتی را تقریباً 21 درصد نسبت به نمونه‌های شاهد کاهش داد. به‏طورکلی می‌توان نتیجه گرفت که نمونه‌های ساخته شده با ترکیب دو افزودنی SBS و CF، دارای عملکرد بهتری نسبت به سایر نمونه‌های آسفالتی می‌باشند؛ به‌طوری که دارای مقاومتی حدود 164 درصد مقاومت نمونه‌های شاهد بوده و همچنین دارای توزیع دمایی یکنواخت‌تر و نرخ گرمایش بیشتری نسبت به نمونه‌های شاهد می‌باشند. https://jtie.semnan.ac.ir/article_10871.html Aging-induced embrittlement, fatigue cracking, and moisture damage are among the primary factors limiting the long-term performance of asphalt pavements. This study investigated the effects of heavy-oil-containing capsules and Nano Zycosoil surface treatment on the mechanical performance, moisture susceptibility, and fatigue behavior of asphalt mixtures. Five mixture groups were prepared: a control mixture, a mixture containing untreated capsules, a mixture containing Nano Zycosoil-treated capsules, a mixture containing treated aggregates and untreated capsules, and a mixture containing both treated aggregates and treated capsules. The optimum asphalt content of each group was independently determined using the Marshall method. The mixtures were evaluated through Marshall stability, indirect tensile strength, tensile strength ratio (TSR), indirect tensile fatigue, and boiling-water tests. In addition, the thermal stability and structural characteristics of the capsules were examined using thermogravimetric analysis (TGA), computed tomography (CT), and scanning electron microscopy (SEM). Short-term aging decreased binder penetration from 48 to 35 dmm and ductility from 135 to 107 cm, while increasing the softening point from 51.5 to 54 °C. The incorporation of untreated capsules alone reduced indirect tensile strength and fatigue life relative to the control mixture; however, surface treatment of the capsules recovered a substantial portion of this reduction. The mixture containing both Nano Zycosoil-treated aggregates and treated capsules exhibited the best overall performance, achieving a Marshall stability of 1400 kg, dry and moisture-conditioned indirect tensile strengths of 1.884 and 1.815 MPa, respectively, a TSR of 96.34%, and a fatigue life of 112,827 cycles. Its fatigue life was 39.64% higher than that of the control mixture. Furthermore, the estimated retained asphalt coating in the boiling-water test increased from 43% for untreated aggregates to 95% for treated aggregates. Overall, the simultaneous surface treatment of aggregates and capsules provided the most effective improvement in mechanical performance, moisture resistance, and fatigue durability.