Showing 232 results for Type of Study: Original Research
Mr. Mehdi Abbasi, Prof. Gholamreza Lashkaripour, Prof. Naser Hafezi Moghaddas, Dr. Hossein Sadeghi,
Volume 19, Issue 1 (6-2025)
Abstract
The elastic modulus is considered one of the most essential parameters in the analysing and designing deep foundations and underground structures. Accurate determination of this parameter usually requires expensive and time-consuming in-situ testing, and validating its accuracy poses significant challenges. Therefore, researchers have consistently focused on developing empirical models based on geotechnical parameters. In the present study, multiple linear regression models, including general, coarse-grained soil, and fine-grained soil models, were developed to predict the elastic modulus using data obtained from 180 boreholes totaling 5,783 meters in the Mashhad Metro Line 3 project.. Out of 489 pressuremeter tests, 160 datasets were selected based on the availability of complete geotechnical parameters at the same depth. The analysis incorporated the influence of various parameters, including the percentage of sand, silt, and fine particles; grain size characteristics (D10, D30, D60, uniformity coefficient, and coefficient of curvature); Atterberg limits; moisture content; natural and dry density; specific gravity; and cementation indicators (gypsum, carbonate, and organic matter), as well as depth and in-situ stress. The final regression models were developed using a backward stepwise method, implemented through Python programming. The resulting regression equations were derived, and comparative plots between predicted and actual elastic modulus values were presented. The findings demonstrate that the proposed model offers reliable accuracy in estimating the elastic modulus. To evaluate the accuracy of the proposed models in predicting soil elastic modulus, an independent dataset of 39 pressuremeter test results, including both fine- and coarse-grained soils, was used. Statistical indicators demonstrated that the overall model performed best (R²=0.79, MAPE=9.86%). Additionally, the low values of normalized RMSE confirmed the stability and acceptable accuracy of all models.
Mrs Roya Masoumipour, Dr. Saeed Mahdavi,
Volume 19, Issue 1 (6-2025)
Abstract
The Chador-Malu open-pit mine is faces complex challenges regarding the long-term stability of its slopes. These are directly influenced by time, environmental changes, and stresses induced by mining activities. Considering the existing evidence of potential future instability, displacement changes along the northern to eastern pit walls were analyzed over an 18-month period. Long-term wall displacements were measured using radar. Through back-analysis and three-dimensional numerical simulations, the equivalent creep behavior of the slopes was evaluated using the Maxwell creep model. After assessing the geomechanical parameters, the impact of three scenarios passage of time, bench widening, and pit deepening on slope stability was investigated under three horizontal-to-vertical stress ratios of 0.5, 1, and 1.5. The analysis results indicated that a horizontal-to-vertical stress ratio of 1.5 better matched the field observations. In the first scenario, a 50% increase in time led to over a 100% increase in displacement rates, indicating a rise in instability potential over time. In the second scenario, unloading the first two benches reduces the instability potential, due to an 18% reduction in uplift while unloading up to the eighth bench increased instability potential due to the reduction of weight at the slide’s toe and an increase in the average uplift. In the third scenario, pit deepening formed another sliding zone between the tenth and seventeenth benches.
Ehsan Pegah,
Volume 19, Issue 1 (6-2025)
Abstract
Accurately quantifying the anisotropic elastic parameters of in situ soils is essential for many geotechnical and geological engineering studies. This research introduces an innovative geophysical field technique for assessing these parameters in situ by utilizing the directional variations of P-wave and S-wave velocities. Assuming cross-anisotropy in the soil layers at the test location, it was shown that P- and S-wave propagation velocities along different orientations and planes can be effectively measured through a combination of seismic refraction and downhole surveys. The refraction data were analyzed using Seismic Refraction Tomography (SRT), Multichannel Analysis of Surface Rayleigh Waves (MASW), and Multichannel Analysis of Love Waves (MALW) to estimate the horizontal P-wave velocity (VPH), vertical S-wave velocity (VSV), and horizontal S-wave velocity (VSH), respectively.Moreover, the vertical and oblique P-wave velocities (VPV and VPθ) were identified by evaluating the travel times and distances of wave signals obtained from downhole tests. These velocity measurements were then incorporated into advanced equations formulated from elastic wave propagation theory, facilitating the computation of elastic parameters at the site. To evaluate the accuracy and efficiency of the proposed approach, the obtained results were compared with corresponding laboratory measurements, revealing a satisfactory level of agreement between the two datasets. The proposed methodology offers a practical means for in situ assessment of cross-anisotropic elastic properties in near-surface geomaterials using field-based seismic techniques.
Nazila Dadashzadeh, Morteza Hashemi, Ebrahim Asghari-Kaljahi, Akbar Ghazi-Fard,
Volume 19, Issue 1 (6-2025)
Abstract
The urban development of Tabriz faces numerous geological and engineering challenges due to the presence of Neogene argillaceous-marly rocks. These rocks exhibit low mechanical strength and bearing capacity, as well as high deformability. This study aims to analyze these rocks and establish practical correlations among their petrographic, physical, and mechanical properties, alongside ultrasonic test results. These correlationscan help estimate uniaxial compressive strength (UCS), compression wave velocity (Vp), and elastic modulus (E). The findings indicate that argillaceous-marly samples, classified as very weak to weak rocks or hard soils with significant deformability, exhibit low compression and shear wave velocities. These samples are predominantly found in yellow, olive green, gray to dark gray, and brown colors throughout the city. The study reveals significant linear relationships between physical properties, mineralogical composition, UCS, and E with seismic wave velocity. Notably, there is a strong correlation exists between compression wave velocity and uniaxial compressive strength, shear strength parameters, cement content, and mineralogical composition in these rocks. These relationships suggest that mineralogy, porosity, density, and slake durability index are key factors influencing seismic wave velocity. Additionally, the variations in textural and microstructural diversity of argillaceous-marly-marly samples contribute to unpredictable mechanical behavior, which can pose potential hazards. Furthermore, a qualitative fissure index (IQ) was developed usingthe P-wave velocity of the samples to classify them into categories of high fissurability.
Tahereh Azari,
Volume 19, Issue 1 (6-2025)
Abstract
Accurately determining hydraulic parameter values is the first step in sustainably developing an aquifer. Since Theis (1935) introduced the type curve matching technique (TCMT), it has been used to estimate aquifer parameters from pumping test data. However, the TCMT is subject to graphical error. To eliminate this error, a multi-layer perceptron (MLP) artificial neural network (ANN) was developed as an alternative to the conventional TCMT. This MLP ANN models the Bourdet-Gringaten well function to determine fractured double porosity aquifer parameters. The MLP model was developed using a four-step protocol and trained using the backpropagation method and the Levenberg-Marquardt optimization algorithm for the well function of double-porosity aquifers. Through a trial-and-error procedure and by applying principal component analysis (PCA) to the training input data, the optimal network structure with the topology [3×6×3] is determined. We evaluated the validity of the developed network with synthetic and real field data. The network receives pumping test data and provides the user with aquifer parameter values. This network provides an automatic, fast procedure for determining double-porosity aquifer parameters, eliminating the graphical errors inherent in the conventional TCMT.
Mohammad Reza Haddad Tehrani, Mehdi Talkhablou, Mohammad Reza Asef, Mehdi Ostad Hasan,
Volume 19, Issue 2 (10-2025)
Abstract
Complex carbonate reservoirs, such as the Asmari Formation, present challenges to the accurate determination of geomechanical parameters and effective stresses due to high lithological and structural heterogeneity. The objective of this study is to develop a comprehensive three-dimensional model of geomechanical parameters and effective stresses in the Kupal oil field. Well log, core, and seismic data were used, and three-dimensional modeling was performed using the Sequential Gaussian Simulation (SGS) method based on variogram analysis. The prevailing stress regime was validated using FMI logs and wellbore breakout analysis. Additionally, a one-at-a-time sensitivity analysis was conducted on key parameters, including static Young’s modulus, Poisson’s ratio, cohesion, internal friction angle, and pore pressure. Results indicate that the maximum vertical effective stress (σv) is 87 MPa and the maximum horizontal effective stress (σHmax) is 127 MPa. Analysis of wellbore imaging data confirms a normal faulting stress regime (σv>σHmax>σhmin) in the field. Stress concentration around minor faults was also identified. The model was validated against one-dimensional models achieving 88% agreement. The findings of this study can be applied to well design, gas injection, and reservoir stability assessment in the Kupal field.
Kamal Ganjalipour, Majid Naeimi, Effat Zamani,
Volume 19, Issue 2 (10-2025)
Abstract
Exploratory studies and pumping tests are considered fundamental tools for understanding the hydrogeological behavior of aquifers. They play a critical role in water resources modeling, planning, and governing water resources. This article aims to analyze the role of these studies within the water governance framework in Iran by examining the institutional, technical, and legal challenges in comparison with developed countries. The findings indicate that weak legal requirements, the absence of an integrated data acquisition system, limited equipment, and a shortage of exploratory wells have led to reduced accuracy in baseline studies, weakened numerical models, and unstable decision-making. Additionally, the paper reviews the historical development of exploratory drilling and pumping tests, along with their tools and objectives, emphasizing the role of exploratory wells in developing conceptual models and monitoring aquifer dynamics under declining water table conditions. In conclusion, the article highlights the need to revise policymaking, strengthen institutional structures, and mandate the implementation of precise tests to achieve evidence-based water governance.
Dr Reza Toushmalani,
Volume 19, Issue 2 (10-2025)
Abstract
Inversion of magnetic data to characterisegeological structures, such as dikes, is a fundamental challenge in engineering geophysics due to its highly non-linear and ill-posed nature, necessitating robust optimization methods. This study introduces and evaluates for the first time, the Mountain Gazelle Optimizer (MGO) for the first time, examining its efficiency and potential as an effective solution to this problem. The MGOalgorithm is designed to find the global optimum by intelligently balancing exploration and exploitation within the parameter space. The performance of the MGO was assessed by comparing it with two distinct approaches: a powerful machine learning algorithm called Random Forest (RF), and a classic processing-estimation method based on Reduction to the Pole (RTP). Evaluations were conducted on synthetic data (with noise levels ranging from 0% to 20%) as well as on real field data from the Gansu iron deposit in China. The results clearly demonstrated the superiority of MGO in all scenarios. Not only did the algorithm exhibit greater stability against noise than RF, it also, achieved a Root Mean Square Error (RMSE) of 0.48 in the real data case study,, which was significantly lower than the error achieved by the classic method (0.88). Furthermore, the parameters estimated by MGO showed better alignment with the geological information from existing drilling data in the area. This study suggests that MGO's superiority obtained from its direct and global inversion approach. Ultimately, MGO is presented as an accurate and reliable tool for exploration and engineering applications.
Maedeh Roshan Liarajdameh, Milad Davari Sarem,
Volume 19, Issue 2 (10-2025)
Abstract
Iran, due to its location between two active tectonic plates, has always been exposed to numerous earthquakes. The occurrence of more than 100 severe earthquakes in the past century indicates the country’s high level of vulnerability to this natural hazard. The aim of this research is to analyze the seismicity and assess the earthquake hazard in Shahid Rajaei Port, as the largest commercial port in Iran (located at the intersection of the North-South transit corridor), which will be a fundamental step in enhancing the resilience and sustainability of the vital infrastructures in this region. In this study, all seismic events occurring within a 200-kilometer radius of the site were used, along with the Knopoff and Ez-Frisk software. The statistical analysis of historical and instrumental earthquakes indicates a high level of seismicity in the region, characterized by moderate-magnitude earthquakes with short return periods, such that earthquakes with magnitudes between four and five on the Richter scale constitute a larger share. The probabilistic hazard assessment estimated the maximum horizontal and vertical accelerations as 0.385 and 0.290 (g), respectively. Additionally, the site response spectrum was prepared based on the accelerographs of the Tabas earthquake and the isoacceleration maps of the study area, generated at intervals of 1.0 degrees in both latitude and longitude directions. The results showed that the study area has a seismic hazard of 0.85 (g), which is higher than the standard values specified in Iran’s Code 2800, placing it within the very high relative hazard zone. Therefore, implementing risk-based approaches in infrastructure development helps optimize port design and reduce earthquake-related damages.
Mojtaba Rahimi Shahid, Gholam Reza Lashkaripour, Naser Hafezi Moghaddas,
Volume 19, Issue 2 (10-2025)
Abstract
The Sanandaj–Sirjan Structural-Sedimentary Zone is one of the most important geological regions in Iran. The limestone formations in this area play a key role in civil engineering and mining projects. Knowing the precise mechanical properties of these rocks, especially the uniaxial compressive strength (UCS dry) and dry point load index (Is₅₀-dry), is essential for safely and economically designing structures. Because direct testing methods are costly and time-consuming, this study uses indirect modeling techniques, such as regression and neural networks, to predict these properties. First, a comprehensive database was compiled by collecting the physical, mechanical, dynamic, and chemical data of limestone samples from the region. Then, univariate, bivariate, and multivariate regression analyses were conducted to extract statistical relationships among the variables. Finally, multilayer perceptron neural network models with various architectures based on the Levenberg–Marquardt learning algorithm were developed. The comparison results of the model performance indicated that neural networks, due to their ability to identify complex and nonlinear relationships between parameters, provide more accurate predictions of the limestone mechanical properties compared to statistical models. A comparison of the correlation coefficients of multivariate regression equations and neural network models showed that, overall, using neural network models improves the accuracy of UCS Dry predictions by 14.89% and the Is ₅₀-Dry predictions by 4.70%. The results show that predicting UCS Dry in the presence of Is ₅₀-Dry among the input parameters has a significant impact on improving the accuracy of the models. For example, the model with the inputs Is ₅₀-Dry, SH, γ Dry and n showed very good performance. For predicting Is ₅₀-Dry, the models that included the parameters SDI1 and BI Dry as inputs also performed very well. The application of these models can contribute to cost reduction, increased speed of rock engineering studies, and improved safety in civil projects.
Dr Seyed Ali Asghari Pari,
Volume 19, Issue 6 (12-2025)
Abstract
Various factors influence earth dams' stability and flow rate, including geometric characteristics, material permeability, and upstream water height. Understanding unsaturated soil behavior in earth dams is crucial, necessitating the application of unsaturated soil mechanics principles due to the complexities involved. This study investigates the effect of Soil-Water Characteristic Curve (SWCC) parameters on the slope stability of an earth dam under steady-state and rapid drawdown conditions. The findings reveal that SWCC parameters significantly influence water flow and slope stability. Additionally, considering unsaturated unit weight can improve slope stability under varying conditions.
Seyedeh Aida Mirshafiey, Asghar Milan,
Volume 19, Issue 6 (12-2025)
Abstract
Earthquakes, as one of the major factors influencing surface elevation changes, can cause widespread subsidence or uplift in different regions. These changes primarily result from the displacement of tectonic plates, fault movements, pressure variations at depth, and processes related to crustal fractures. Depending on the fault type, an earthquake can lead to uplift or subsidence on both sides of the fault. Monitoring these changes is essential for crisis management, urban planning, and reducing environmental damage. Various methods are used to study surface elevation changes, each with different levels of accuracy and capability. Ground-based methods such as precise leveling, Global Positioning Systems, and terrestrial laser scanning allow for highly accurate assessments of elevation changes. In addition to these methods, remote sensing techniques enable the precise measurement of vertical surface displacements. This study aims to evaluate the potential of these data. In this research, data and imagery from the Sentinel-1 satellite have been utilized. One of the key advantages of these data is their wide coverage, high spatial accuracy, and capability to capture images under all weather and temporal conditions, making them suitable for accurately assessing earthquake-induced surface changes. This study examines the impact of the 5.6-magnitude Khoy earthquake on surface deformation using the differential radar interferometry technique. Radar images acquired before and after the earthquake were processed, and phase variations were converted into vertical surface displacements. The results of the study indicated that in some areas near the earthquake's epicenter, uplift occurred, whereas some locations farther from the epicenter experienced subsidence. The maximum recorded uplift was 0.07 meters, while the maximum recorded subsidence was -0.127 meters. These findings reveal that the pattern of surface elevation changes is not uniformly distributed.
Ms Solmaz Darsanj, Dr. Mehrdad Emami Tabrizi, Dr. Hassan Afshin,
Volume 19, Issue 6 (12-2025)
Abstract
Aeolian sands in arid and semi-arid regions are considered problematic soils due to their loose structure, low bearing capacity, and difficult compaction. The dry climatic conditions of Iran and phenomena such as the desiccation of Lake Urmia have intensified the dispersion of saline sands. One of the common approaches to mitigate these issues is chemical stabilization using additives such as cement. This study investigates the effect of stabilizing saline aeolian sands collected from the Lake Urmia basin using Type I Portland cement. Stabilized soil specimens were prepared with varying levels of salinity and different cement contents, and were subjected to unconfined compressive strength testing after a curing period of 7 days. The results demonstrated that increasing the cement content significantly enhances compressive strength. Moreover, the presence of salt in the studied soil did not hinder the stabilization process; instead, it contributed to improved strength in the short term. These findings underscore the importance of considering both the type and concentration of salts when designing stabilization treatments for saline granular soils in arid and semi-arid climates.
Mis Tahereh Daniyalnezad, Dr Aliakbar Momeni,
Volume 19, Issue 6 (12-2025)
Abstract
Following an unusual period of rainfall period at the end of the previous winter, several landslides occurred in Tolubin village in early spring 2019. These landslides resulted in the destruction of 12 houses as well as causingdamage to roads and gas transmission lines. This this research was therefore conducted to investigate the mechanism of these landslides. The study was comprised four main phases: a literature review, field investigations, laboratory studies, and a slope stability assessment using Slide 6.20 software. During the field surveys, landslide-prone profiles were identified, and both disturbed and undisturbed samples were collected. The disturbed samples were used for laboratory tests, including determining the grain size distribution, calculating the Atterberg limits, performing calcimetry, conducting X-ray diffraction (XRD) analysis, and carrying out scanning electron microscopy (SEM) analysis. Additionally, 27 undisturbed samples were prepared for direct shear tests under varying moisture conditions. Finally, stability analyses of the studied profiles were performed in Slide software under different moisture conditions, considering both static and quasi-static states, based on the geometric characteristics of the slopes and shear strength parameters (internal friction angle and cohesion).. The obtained safety factors indicated that all slopes were on the threshold of failure under saturated static conditions and would certainly fail under saturated quasi-static conditions. In conclusion, the high sensitivity of the slope’s marly materials to moisture variations and the unusual rainfall in February and March 2019 were identified as the primary factors contributing to these landslides.
Soroush Mahdavian, Ali Raeesi Estabragh, Shima Azadeh Ranjbar,
Volume 19, Issue 6 (12-2025)
Abstract
This research study investigated the impact of dimethyl phthalate (DMP) on the physical and mechanical properties of clay soil through experimental testing. Additionally, the impact of hydrated lime and magnesium oxide on improving the properties of clay soil was investigated. The contaminated soil was artificially produced in the laboratory. Natural and contaminated soils were mixed with the above agents at percentages of 5.0%, 10.0% and 15.0%, respectively. The experimental test programme for this study comprised: Atterberg limits, compaction, uniaxial compression tests (UCS) and scanning electron microscopy (SEM). Samples for the UCS tests, both with and without additives, were prepared using the static compaction method and tested at curing times of 7, 14 and 28 days. The results showed that, in general, the Atterberg limit, compaction parameter (maximum dry unit weight) and UCS values for the contaminated soil were lower than for the natural soil. The results also indicated a reduction in UCS values for a mixture of contaminated soil and 10% hydrated lime or magnesium oxide. A comparison of the final strength values of samples made from a mixture of contaminated soil and 10% hydrated lime or magnesium oxide showed that the strength was 34.4% and 63.8% lower than that of a mixture with 5% of these additives at the same curing time. The E50 values were calculated from the stress-strain curves of the different tests. Additionally, the SEM results showed that changes in the properties of the mixture prepared from these agents and natural or contaminated soil were due to a chemical reaction between the soil and the additives.
Eng. Mohammad Hossein Jowlar, Dr. Mashalah Khamehchiyan, Dr. Mohammad Reza Nikudel, Dr. Asghar Azadi,
Volume 19, Issue 6 (12-2025)
Abstract
Over the past three decades, research into the factors influencing the development of gypsum karsts has become an active and growing area of study. The mechanically weak nature of gypsum, along with its rapid dissolution and deformability, contributes to the formation of gypsum karsts, voids, and caverns in regions where gypsum deposits are present. This process can significantly undermine geotechnical stability by reducing bearing capacity and increasing settlement. This issue is particularly critical in heavy industrial settings such as petrochemical facilities, where large storage tanks and other infrastructure are founded directly on the ground surface. Consequently, identifying and assessing these processes is essential for the design, construction, and maintenance of engineering projects. This study assesses subsurface gypsum karsts within the Masjed Soleyman Petrochemical site using an integrated geophysical and geotechnical approach. Ground Penetrating Radar (GPR) was employed across 24 profiles totaling 2,307 meters, also geotechnical data were obtained from 113 boreholes drilled to depths of 20–40 meters. Following data analysis, 32 occurrences of subsurface gypsum karsts were identified at depths ranging from 4 to 36 meters. Subsequently, surface water drainage patterns were analyzed and digitized from historical Corona satellite imagery (1968). In parallel, groundwater levels and flow direction maps were generated using data from electric probe depth finder measurements in boreholes. The integration of these datasets revealed that most gypsum karsts are concentrated in areas where groundwater tends to accumulate and flow. Finally, groundwater sampling and chemical analysis revealed an average sulfate concentration of approximately 1,480 ppm, indicative of a severe sulfate exposure environment.
Prof Seyyed Mahmoud Fatemi Aghda, Dr Asieh Hamidi, Ms Fatemeh Amiri,
Volume 19, Issue 6 (12-2025)
Abstract
The evaluation of mechanical strength, particularly the uniaxial compressive strength (UCS) of rocks, plays a critical role in the design and performance prediction of surface and underground structures, significantly impacting project costs and safety in engineering applications. Traditional laboratory testing methods for UCS assessment are destructive, time-consuming, and expensive, while indirect methods often lack reliability due to rock heterogeneity. This study addresses these limitations by developing advanced machine learning frameworks that integrate petrographic features with conventional rock properties to predict UCS and quantify associated uncertainties. The research utilized a comprehensive dataset from sedimentary rocks collected along Iran's southern coastlines (Persian Gulf and Gulf of Oman), encompassing mechanical properties (UCS, Brazilian tensile strength, point load index, porosity, ultrasonic pulse velocity), durability indices (Los Angeles abrasion, slake durability, aggregate impact value), and detailed petrographic characteristics derived from thin-section analysis. Three complementary approaches were implemented: (1) hybrid Neural Network-Gradient Boosting regression (ANN-GBR), (2) AutoML-optimized Random Forest, and (3) Monte Carlo simulation-based uncertainty quantification. Key petrographic features including immature and mature clastic textures, the mineral composition (quartz, chert) were used as input parameters alongside alongside laboratory testing to improve the prediction of UCS.The influence of these petrographic features on the rock’s microstructure and microcrack propagation contributes to reducing model uncertainty and enhances the reliability of predictions in complex and heterogeneous rock conditions. The AutoML-optimized Random Forest model demonstrated exceptional predictive performance with R² = 0.9884, RMSE = 0.5732 MPa, and MAPE = 3.6%, significantly outperforming traditional empirical methods. The ANN-GBR hybrid approach achieved R² = 0.9412 with RMSE = 1.385 MPa, while Monte Carlo simulations provided robust probabilistic assessments through 95% confidence intervals and systematic bias identification. Feature importance analysis revealed that soundness parameters and mineralogical composition are the most influentialpredictors, emphasizing the critical role of micro-scale petrographic properties in determining macroscopic mechanical behavior.
Dr Emad Namavar,
Volume 19, Issue 6 (12-2025)
Abstract
Accurate geotechnical classification is essential for excavation design in urban environments, where soil behavior is highly influenced by excavation-induced stresses. This study refines the geotechnical characterization of fine-grained alluvial deposits belonging to the youngest sedimentary unit (Unit D) in Rieben’s classification. A comprehensive investigation was conducted through borehole drilling, Standard Penetration Tests (SPT), pressuremeter testing, and laboratory experiments including triaxial, uniaxial, and direct shear tests. Excavation stability was assessed using the Morgenstern–Price method under both short-term and long-term conditions. Based on the geotechnical parameters and slope stability simulations, Unit D was subdivided into three distinct zones (D1, D2, and D3) with different excavation behaviors. Zone D1, characterized by lower sand content, allows deeper vertical cuts, whereas the presence of sandy lenses in Zone D3 restricts excavation depth and requires gentler slopes. The findings provide an updated geotechnical classification framework for fine-grained alluvia, offering practical guidelines for safe excavation design and contributing to the broader understanding of alluvial systems in urban geotechnical engineering.
The developed framework offers substantial practical advantages including cost reduction through minimized laboratory testing, rapid prediction capabilities for quality control, and enhanced risk assessment through uncertainty quantification. The integration of petrographic analysis with machine learning provides engineers and practitioners with a scientifically robust and economically viable approach to rock strength assessment, supporting more reliable engineering design and reducing the risk of costly project failures.
Reza Mohseni Afkham, Dr Mojtaba Bahaaddini, Dr Abbas Majdi,
Volume 19, Issue 6 (12-2025)
Abstract
Tensile strength is one of the most important mechanical properties of brittle materials and plays a decisive role in the stability of many civil and mining structures. The Brazilian test is the most common indirect method for determining tensile strength and is widely employed. In this test, it is generally assumed that a central tensile crack initiates and propagates along the loading axis. However, the actual fracture process in the Brazilian test remains a controversial issue, and using curved loading platens has been recommended to better concentrate tensile stresses at the center of specimen. This study investigated the influence of platen curvature on the estimated tensile strength and the fracture patterns. To this end, five types of platen with curvature ratios of 0, 0.50, 0.57, 0.67, and 0.80 were prepared. All tests were recorded using a high-speed camera to precisely capture the initiation and propagation of cracks. To minimize the effect of rock heterogeneity and obtain consistent results, synthetic specimens were used, and five samples were tested for each curvature ratio.The results indicated that increasing the platen curvature led to a higher estimated tensile strength. While the increase was negligible for curvature ratios up to 0.67, at the ratio of 0.80 the tensile strength was approximately 48% higher compared to 0.67. Analysis of fracture patterns revealed that at the curvature ratio of 0.80, the fracture mode shifted to an unstable and disturbed pattern, characterized by secondary shear cracks and the irregular propagation of the main crack.
Ms Haniye Yaghoubi, Dr. Reza Jahanshahi, Dr. Morteza Mozafari,
Volume 19, Issue 6 (12-2025)
Abstract
This study examines the hydrochemistry and contamination levels of groundwater resources in the urban area of Birjand in eastern Iran. Water quality was assessed and pollution sources were identified through sampling 22 wells, 12 qanats and 4 springs. The results showed that electrical conductivity varied from 300 to 8,000 µS/cm, while pH ranged from 7.23 to 8.71. According to the Piper diagram, the dominant hydrochemical facies were chloride, sulphate and bicarbonate types. In some of the samples, the nitrate concentration exceeded the permissible limit of 50 mg/L set by the World Health Organization, indicating the influence of urban wastewater and agricultural effluents. The ionic ratios reveal the influence of halite and gypsum dissolution processes, as well as ion exchange reactions, on the chemical composition of the water. A health risk assessment showed that, while most sources are within the safe range for adults, some wells and qanats pose a higher risk to infants and children. This study aims to provide a scientific framework for understanding the geochemical processes that control water quality, and to identify high-risk areas for the sustainable planning and management of groundwater resources in the Birjand plain.
