نشریه مهندسی عمران مدرس
سال بیست و چهارم شماره 4 (مهر و آبان 1403)

Today, most of the existing pavements in the country are asphalt pavements. This is due to the abundance of oil in the country and the lack of a suitable alternative for it. Asphalt pavements, despite their popularity and ease of implementation, also have disadvantages.  The low service life of asphalt pavements and the exorbitant costs that are paid for their maintenance, as well as the damages caused in some special areas of the pavement, such as airport runways, require the use of pavements that can have many characteristics. It is better than asphalt paving to meet the needs of these areas. In recent years, the use of concrete pavement compared to asphalt pavement has had a higher economic justification. Also, in some cases, the use of concrete pavement, such as airport runways, which must have high resistance to pressure, impact, and wear, is the only viable option. But concrete pavement also has disadvantages such as low durability against freezing and thawing cycles in cold regions. Therefore, it is necessary to take into account the necessary measures to increase the durability of concrete, compensate for the disadvantages of concrete pavements against destructive factors and increase their service life to a significant amount, so that it is economically justified compared to asphalt procedures. The indigenous concrete mixing plan is a new approach that has been considered as an economic solution for the sustainable development of many civil infrastructures in the world. For this purpose, in this article, a practical and effective method to increase the efficiency and life of concrete pavements of Mashhad Airport by using potential mineral resources and also to minimize maintenance costs has been introduced. In this study, 8 concrete mixing plans were prepared with aggregates from two local quarries, Mehrizi and Rezaei, in relation to Mashhad airport, and then the mechanical properties and durability behavior of all mixtures were carried out to provide the optimal local mixing plan. The results showed that by adding polypropylene fibers to the samples containing microsilica, the bending strength of the concrete samples increased up to 8.7 MPa. Based on the results, concrete samples containing Mehrizi aggregates showed better performance in terms of mechanical behavior and durability compared to concretes made from Rezai mine aggregates. Also, among the mixtures of Mehrizi mine, the mixing design containing polypropylene fibers and 7% replacement of microsilica with cement showed far higher resistance and durability than other samples. In such a way that the rate of improvement in compressive strength, resistance to chlorine ion invasion, melting and ice phenomenon and silica alkali reactions compared to the control sample after the end of each of the aforementioned tests is 22.81%, 418%, 400% respectively. % and 189.31%. Therefore, based on the mentioned results, a local mixing plan using Mahden Mehrizi materials is suggested for use in the apron of Mashhad airport.

Heavy metal pollutants containing lead have consistently been major sources of environmental contamination over the past decades. Human and industrial activities have directly or indirectly led to the introduction of substantial amounts of lead-based pollutants into soil and groundwater. The Solidification/Stabilization (S/S) technique using cement, by significantly reducing the mobility and solubility of lead in soil, serves as an effective tool for remediating lead-contaminated soils. Conversely, the heavy metal pollutant lead significantly affects the setting time of cement, and the setting time directly impacts the efficiency of cementitious compounds. Consequently, understanding the interaction between lead and cement is of paramount importance. In this regard, the present study aims to investigate the influence of the heavy metal lead on the setting time and microstructural interaction of lead and cement. To achieve this, lead nitrate solution with concentrations of 0, 10,25,50, 100, 250 and 500 kg/cmol-solid, was added to cement. The effect of lead on the hydration process and setting time of cement was examined through setting time tests, X-ray diffraction (XRD) analysis, scanning electron microscopy (SEM) images, and leachability analysis (TCLP). According to the research results, the precipitation and chemical complexation of the heavy metal lead in the form of Pb(OH)2 and Pb-C-S-H delayed the cement hydration process, extended the initial and final setting times of cement paste, and immobilized and solidified lead pollution effectively. By adding 25 kg/cmol-solid lead nitrate, the initial setting time of cement increased from 65 minutes to 155 minutes. Microstructural results demonstrated that cement effectively interacted with heavy metal lead up to a concentration of 100 cmol/kg-solid during the Solidification/Stabilization (S/S) process, keeping pollutant levels within permissible limits for soil.

This study seeks to integrate steel shear walls with precast concrete systems into stable and resistant structures against lateral loads. Until now, no laboratory research has been published due to the very limited number of tests performed on the precast concrete system with steel shear wall, ductility factor, additional strength and behavior as well as the energy absorption of this integrated system compared to the precast concrete system without steel shear wall. For this purpose, two steel shear wall samples made of black plate and galvanized plate (energy absorber) have been tested. Also, a sample of precast concrete frame without steel shear wall has been tested to compare the mentioned coefficients. The results of investigations show that steel shear walls significantly increase the stiffness, ultimate strength and behavioral performance of precast concrete buildings.

Structures, including concrete bridges, may be exposed to gradual damage during operation due to environmental conditions such as corrosion, which will reduce their useful life. Knowing the amount of remaining useful life of the structures makes it possible to improve, strengthen or rebuild them at the right time. To determine the remaining useful life of a structure, there are three common methods under the titles of data-driven method, failure physics method and combined method. In this article, the combined method of determining the remaining useful life of structures has been studied. The purpose of this research is to propose a suitable method for predicting the remaining useful life of a bridge structure with a reinforced concrete deck under chloride ion corrosion using a Bayesian network. The remaining useful life of reinforced concrete parts under chloride attack includes two parts of the time related to the initial stage of corrosion and the time related to the release of chlorine ions. To determine the remaining useful life part related to the initial stage, various researches have been done and the American ACI365 committee has proposed a software called Life-365 for this purpose. There is no comprehensive research to determine the second part of the remaining life, which is related to the release stage. Based on the prepared Bayesian network and the formula obtained in this research, the remaining life of the chloride diffusion stage in concrete was estimated to be 9.116 years in the best conditions and 2.73 years in the worst conditions. Meanwhile, the number suggested by the ACI365 committee, in practical work, is usually equal to 6 years for the release stage.  This issue clarifies the need for more research in this regard. In this article, using the data available in past researches and reproducing the data and using the Bayesian network, relationships are presented to determine the useful life of the bridge structure in both the initial and release stages.Based on the proposed method, using the Bayesian network, relationships can be obtained for each of the two parts of the remaining useful life of the structure under chloride corrosion, i.e., the corrosion initiation stage and the chloride release stage, in terms of factors affecting the remaining useful life in a specific project. . In these networks, the effect of various factors can be considered, which is one of the advantages of the proposed method.The remaining useful life has an inverse relationship with temperature. When the average temperature increases by 20 degrees, the remaining useful life decreases by an average of 30%.With the help of the proposed relationships, a parametric study was conducted to investigate the effect of different conditions of using pozzolanic compounds on the remaining life of the structure. In this regard, 17 states of different pozzolanic compounds with different concentrations were considered and the average remaining useful life due to different states was calculated. The average life obtained compared to the case where no pozzolan is used in concrete showed a 38% increase in life. In order to evaluate the results of the proposed relationships, the problem of determining the remaining useful life for a numerical model of a concrete bridge and several marine structures located in the Persian Gulf was investigated. The results of this research show that by using the proposed relationships, it is possible to improve the accuracy of estimating the remaining useful life of bridges with concrete decks exposed to chloride ion penetration, relying on the data obtained from the field inspections of the structure.

Friction angle of soil is a critical parameter in the geotechnical engineering and has a direct impact on the design of various structures, such as retaining walls, slopes, and piles. This parameter plays a crucial role in determining the overall safety and performance of these structures, making it a key player in the geotechnical analysis and design. In recent years, there have been some impressive advancements in the field of artificial neural networks and deep learning models. These advancements have transformed these models into the highly effective tools for predicting the properties and behavior of soil. By using a powerful deep learning model, it is now possible to save a considerable amount of time and money when it comes to estimating and predicting soil properties. In this particular study, a convolutional neural network was developed to predict the peak friction angle of Firuzkuh sand using some soil images and the dry density as the input parameters. The network itself consisted of five consecutive convolutional layers, as well as a pyramid pooling module that utilized four different pooling sizes arranged in parallel. In addition, two fully connected layers were incorporated into the network's design, which enabled it to satisfactorily process the input parameters of the images and the dry densities with respect to the speed and precision. This network converts the soil image into a scalar (number) by using these 5 convolutional layers, the pyramid pooling module and a fully connected layer. Then, this scalar is concatenated with the dry density of the soil, is passed through a fully connected layer, and the peak friction angle of the soil is obtained as an output. For data generation, a total of ten samples of Firuzkuh sand were prepared. These samples had different gradation curves, which are referred to as S1 to S10 specimens. Each soil specimen was compacted at three different dry densities. The peak friction angle associated with the 30 different densities for the 10 different particle size distributions (S1 to S10 specimens) was determined using the direct shear test apparatus. The direct shear test box was 100 ×100 × 25 mm in size. For network training and testing, the soil specimens were spread on a flat surface and 50 photos in different light environments with varying distances of the camera from the soil surface, were taken from each specimen. Since in the network training process, three dry densities were considered for each sample, a total of 1500 images were prepared for the network database. Of these, 1125 photos were used for training and 375 photos were saved for testing the network. The network was trained for 1000 epochs on the training data, and the mean square error after 1000 epochs was reduced to 1.84. The outcome of the assessment conducted on the designed convolutional neural network in this study, using 375 test data, revealed that the network can predict the peak friction angle of Firuzkuh sand by incorporating the image and dry density of the soil as input variables. The total normalized relative error was 3.0%, while the maximum normalized relative error was 10%. This indicates that the network has the ability to quickly predict the peak friction angle of the Firuzkuh sand with a good accuracy.

Dams are structures whose continuous evaluation is of great importance. Due to their large scale, experimental study of concrete dams is difficult and therefore, the numerical simulation is used in the dynamic analysis of such dams more effectively. Despite the widespread use of concrete, our knowledge on its exact properties and physical behavior under different conditions is still limited, and many assumptions and simplifications are made to study the concrete behavior in most studies. This is especially complicated in mass concrete structures such as concrete dams. The presence of joints in most concrete structures is common and inevitable. Lift joints in dams cause different characteristics in vertical and horizontal planes. In fact, this is a special type of anisotropy that follows axial symmetry with respect to any vertical axis, which means that the mechanical behavior is the same in all horizontal planes. The mechanical behavior in all vertical planes passing through the axis of symmetry is also the same, however, it is different from the behavior of horizontal planes. Since the lift joints are usually ignored in the numerical analyzes of concrete dams, in the present paper, taking into account the orthotropic behavior of concrete, the concreting joints that cause weakness in specific positions and directions of the dam body are included. First, non-linear seismic analyzes were performed using FEAP finite element software, then a Fortran program was coded to predict the time history of displacement. The proposed method draws upon evolutionary algorithms inspired by Darwinian biology, which are increasingly utilized as surrogate models for various analyses. This approach relies on data-driven learning, wherein algorithms, based on training or sample data, generate a mathematical model for making predictions.  The Pine Flat dam was modeled and analyzed under the Taft earthquake loading over a 20 second time interval with 0.02 second time steps. After successful training and learning, the model was compared and tested for other anisotropy ratios. The purpose of developing the program was to reduce the time required for analyzes so that by analyzing the initial seconds of seismic loading, by importing training inputs to the program, a proper prediction of the response process for the rest of the loading time could be obtained. In addition, by training the program for the isotropic and orthotropic modes, time history diagrams could be extracted for other orthotropic modes in different anisotropy ratios. According to the obtained results, the program is acceptably able to predict the graphs in a very short time. In addition, an equation for predicting the displacements in the orthotropic mode is presented. The maximum displacement of the orthotropic analysis was more than the isotropic one, and the use of isotropic material and homogeneous modeling of the dam body caused errors in the results. Therefore, considering the orthotropic properties of concrete can lead to more realistic results. The results reveal that time history plots derived from the implemented program closely resemble those from finite element analyses. The output results are remarkable, given the significantly reduced time required for predictions generated by the implemented program.

Labyrinth weirs are of the non-linear weirs whose discharge coefficient is higher than similar linear weirs. These weirs have a simple structure. They are mainly made in rectangular, trapezoidal, triangular and semicircular shapes. Investigating the amount of energy loss in these high-efficiency weirs has become very important for engineers in recent years. The experiments were carried out in a flume with a length of 10 meters, a width of 0.6 meters and a height of 0.8 meters. The flow is fed by a pump with an error of 0.01% by three surface tanks and after passing through the flow relaxers into the flume. In this research, four sinusoidal labyrinth weirs were used to check the amount of energy loss. The first spillway has a crown length of 1.3 meters, the second spillway has a crown length of 1.5 meters, the third spillway has a crown length of 1.55 meters, and the fourth spillway has a crown length of 1.6 meters. Also, the first and second weirs have a height of 0.15 meters and the width ratio of the inlet to the outlet is 6.86, and the third and fourth weirs have a height of 0.18 meters and the width ratio of the inlet to the outlet is 7.67. The flow depth in the upstream and downstream of the weir was taken by a point gauge with an error of 1 mm. Weirs are installed at a distance of 5.5 meters from the beginning of the channel. The downstream depth of the spillway was not artificially adjusted by the end valve of the laboratory flume. The weirs are made of wood and wood glue was used for their impermeability. The flow is transferred downstream over the sinusoidal edges of the weir like a curved slide or similar to peak weirs. Also, due to the sinusoidal nature of the weirs, the flow will be transferred downstream faster next to the walls. At the edge of the keys, a local vacuum is created. As the flow rate increases, the available air volume increases. At the downstream of the inlet and outlet keys, a vortex and rotation of the flow is formed, which increases in strength as the flow speed increases. The reason for the formation of vortices is the interference of the falling flow from each sinus. Due to the sinusoidal nature of the flow and the indentations and protrusions in the weir, the flow enters the downstream with a curve and the outflow from each sinus is mixed with the outflow from the other sinus. Also, at the beginning of the outlet keys, a small submerged area is formed, which increases in length and moves downstream as the flow rate increases. In front of the inlet keys, two relatively strong hydraulic jumps are formed, and after that the flow is transferred downstream more calmly. The results were that by increasing the flow rate or increasing the depth of the flow upstream of the weir, the energy loss decreased. Also, the amount of energy loss increases with the effective length of weirs. By increasing the ratio of the width of the input keys to the width of the weir output keys, the amount of energy loss increases. Also, by increasing the ratio of flow depth plus height, such as kinetic energy upstream of the weir to the height of the weir, the amount of energy loss decreases. The amount of energy loss is the highest in the fourth weir and the third weir, respectively. On average, with a 20% increase in the height of the weir, the amount of energy loss increases by 23.2%. Also, the average energy loss in type A, B, C, and D weirs is 42.3, 47.2, 57.9, and 58.6, respectively.

Cement is one of the most widely used construction materials in the world. Considering that the production of cement is polluting and for every one ton of cement produced, one ton of carbon dioxide gas enters the atmosphere. Therefore, for this reason, most of the research in recent years is to replace cement with a new environmentally friendly material. Is. The result of this research led to the identification and introduction of a new substance called ferrock. Ferrock as a compound is an iron binder that yields a variety of waste materials to form a carbon-negative building material. To make this new material, iron dust is used along with proportions of limestone powder, fly ash, metakaolin and oxalic acid. It shows the best usage of iron ore waste powder obtained during the mining process that is just dumped away from the mines, causing air pollution, health hazards and also consuming larger area. The product indirectly reduces the carbon dioxide released by its unique strength gaining mechanism, which is in contrary with that  cement and thus stands out among many other supplements of cement. Ferrock involves a curing process with carbonation and air curing in varied number of days for better strength in terms of compression, tensile strengths and achieving desirable properties. Ferrock is thus a more promising eco friendlier binding material in terms of its carbon negativity and in best usage of the waste. Although implementing Ferrock may require an initial investment, the long-term advantages of reduced maintenance costs and improved sustainability contribute to its overall value proposition. Iron dust in the form of powder (size less than 90 microns) and fine aggregate (size between 150 microns to 2.36mm) is used to develop the iron carbonate matrix which is major binding material in ferrock and they considered light . In this research, the aim is to investigate the durability and resistance of geopolymeric mortars containing ferrock and basalt fibers against high temperature, therefore, for this purpose, different proportions of ferrock and slag are replaced with hydraulic cement and mortar samples are prepared with different percentages of basalt fibers. . Then the 28-day samples are tested at temperatures of 200 and 600 degrees. The results of these tests show that the strength of geopolymer mortar containing frac has a slight drop (14%) at 200 degrees but a noticeable drop (50%) at higher temperatures, also the results show that the samples with percentage Fewer fibers (0.3%) have gained more compressive strength after 28 days. Increasing the amount of sodium silicate and decreasing sodium hydroxide, as well as increasing the replacement percentage of basalt fibers leads to greater resistance in the period of 7 to 28 days after construction, but after high temperature, a more noticeable drop in the compressive strength of these samples can be seen. The higher the ratio of sodium silicate to sodium silicate of the manufactured samples and the more fibers are used to replace the slag in the sample, the higher the tension due to bending is obtained.

Due the limitations and lack of access to fresh water resources, groundwater is recognized as an important source. In this research, a novel method called Dual Discrete Finite Volume (DDFV) has been developed for modeling flow and contaminant transport in saturated and unsaturated porous media. In this method, structured and unstructured grids have been used to handle complex geometries. Flow and contaminant transport equations have been accurately modeled for each triangular element in the grid. This modeling process yields contaminant concentrations at the center and vertices of each element. First, the flow equation in an unsaturated medium has been solved. Parameters such as moisture content and hydraulic head have been calculated. Then, based on the obtained results, the water velocity in the soil was estimated. Finally, the contamination equation in an unsaturated medium was extracted, and the concentration values at the vertices of each element were calculated. This model has been validated for transient flow conditions with high accuracy. By comparing the two-dimensional case with the one-dimensional case, it was determined that there are no numerical oscillations in the two-dimensional case.

This paper investigates the effects of various parameters, including support conditions, the Demand to Capacity Ratio (DCR) of the member under gravitational loads, the section factor (the ratio of perimeter to area), and the fire insulation coating thickness on the fire resistance duration of steel columns under fire effects. To this end, four steel H-shaped columns and four steel tube columns with the height of 4 meters, are subjected to the standard fire curve (ASTM E119) from four sides, and the effects of different parameters are studied. Initially, a heat transfer analysis is carried out on the 2D cross-section of columns with its fire insulation coating in Abaqus software. Then, a nonlinear general static analysis is performed on a 3D steel column model subjected to gravity (concentrated axial) and thermal loading simultaneously. Results of this study indicate that the columns only expand but do not deform significantly until approximately 250oC. After that, a decrease in the steel strength and stiffness and as a result, a decrease in fire resistance and bearing capacity of the steel column occurs. This is accompanied by an increase in the mid-span horizontal displacement of the column and an increase in the effect of the P-δ bending moment, which results in the column failure at about 500oC to 650oC. The results also show that the fixed or pin support condition on the bottom end of the column does not significantly affect the column failure time under fire effects. In square box columns, the increase in the section thickness increases the fire resistance duration of the steel column. However, increasing the section width does not significantly affect the column failure time. In H-shaped columns, the increase in the flange thickness and the decrease in the column web height increases the column fire resistance duration. On the other hand, the results indicate that the section factor, the initial load level of the member due to gravitational loads, and the fire insulation coating thickness have a significant effect on column failure time to the extent that with the increase in DCR of the member from 0.3 to 0.7, the failure time of the column decreases by about 25 to 35 minutes. Based on the results of this study, two formulae have been presented to calculate the failure time of protected columns by CAFCO300. The results of these formulae have also been compared to a relationship proposed in Chapter 10 of the Iranian National Building Regulations. It is found that the results of these formulae are fairly similar, when the initial DCR equals 0.7. Therefore, the relationships of the present study provide a more optimal and accurate design of the fire insulation coating thickness, because this load level can only occur in structures that are not designed for lateral loads and are designed only under gravitational loads.

Piers are vital design elements for a bridge under seismic loading; ensuring their stability and health is crucial for the overall safety of the bridge. The most common methods available for detecting damage, primarily used in the bridge deck, are modal methods. These methods have errors in detecting damage in the structure for various reasons. On the other hand, these methods require healthy pier information. In addition to modal methods, other methods based on energy and data analysis using wavelet transform also exist, the shortcomings of which are mentioned in this article. The fundamental problem that most methods face is the existence of healthy pier information, and furthermore, parameters that should be used to detect damage must be computable or measurable. In this study, a new method is presented, using the concept of correlation, to detect the presence and location of damage with minimal error and without having healthy pier information. To this end, the tallest pier of Ramp A of the Shahid Bakri Bridge complex in Tehran was selected as the case study. Before modeling, the accuracy of the modeling method was validated, and then a precise nonlinear model was built in the OpenSees software using as-built sheets. For the first time in this article, damage in the model was created in different scenarios: reduction of stiffness in concrete cover materials, reduction of cross-sectional area of rebars at various points of the section. The location of the damage was also separately applied at three heights of the pier: 15, 25, and 35 percent of the height. To generate data on the pier, it was considered to load it with an impact load on the top of the pier. This load was applied as an impact on the deck of the pier for a very short time, and the data was collected using accelerometers at the pier height, and the correlation between each pair of consecutive sensors was calculated. Due to the high velocity of the compressive wave in concrete and the overlap that occurs in the return of the wave at both ends of the pier, data collection was performed only for about 0.001 seconds. Finally, due to the weakness of the correlation coefficient in magnifying the location of damage, using the concept of correlation, a damage index based on this concept was presented, and the capability of the presented index in detecting the presence and location of damage in various damage scenarios was evaluated. The results obtained indicate the proper performance of this index in detecting damage in various scenarios and damage intensities between 10 and 30 percent. The presented index only made an error in detecting the location of damage in cases where damage occurred in the concrete cover and rebars in small areas, but even in these cases, the presence of damage was well demonstrated. Due to limitations in sensor placement at the pier height, increasing the distance between sensors and reducing their number was also investigated, and it was observed that even with greater distances between sensors, the presented index has the capability to detect the presence and location of damage, and after finding the approximate location of damage, it is possible to identify the exact location of damage by re-sensoring in probable areas.

The initial position of particles in Smoothed Particle Hydrodynamics (SPH) method can play an important role in reducing numerical errors and its efficiency. In this research, based on water level variation modeling, and using previous modeling experiences with SPH method, six common particle distributions as: SC square distribution, Triangular distribution, distribution based on WVT algorithm, distribution based on Greedy algorithm, hexagonal distribution and distribution based on Fibonacci algorithm have been investigated. Based on the results of the pressure, velocity, and the free surface level at different times according to the physical model, the average total modeling error for each of the models (the difference between the values obtained from the modeling and the results of the laboratory model) has been presented. According to the obtained results, it was determined that the two hexagonal and Fibonacci particle distributions have the lowest average modeling error (10.2% and 11.1%, respectively). In addition, based on the obtained results, the WVT model has a lower modeling error (about 14%) than the remaining three models, i.e., square, triangular, and Greedy distributions. Therefore, since in this phenomenon, the two initial distributions of hexagonal and Fibonacci particles have less modeling error than other distributions, it is recommended to use these two initial distributions in modeling the water level variation phenomenon using the SPH method.