University of TehranCivil Engineering Infrastructures Journal2322-209359120260601Advancements in Geopolymer Concrete Technology: A Comprehensive Review of Fresh, Hardened and Microstructural Properties1289938410.22059/ceij.2024.376588.2062ENRajatRawatM. Tech. Scholar, Department of Civil Engineering, Graphic Era (Deemed to be University), Dehradun, India.0009-0003-7944-5992IshitaBachhetiM. Tech. Scholar, Department of Civil Engineering, Graphic Era (Deemed to be University), Dehradun, India.0009-0003-7770-2270BheemPratapAssistant Professor, Department of Civil Engineering, Graphic Era (Deemed to be University), Dehradun, India.0000-0001-5683-0829Journal Article20240516This review summarizes recent developments in Geopolymer Concrete (GPC) technology, focusing on fresh, hardened, and microstructural properties. Key findings include the impact of ultrafine Ground Granulated Blast furnace Slag (GGBS) on enhancing workability and reducing setting times. GPC exhibits lower density and improved water resistance compared to traditional concrete, with compressive, flexural, and split tensile strengths increasing over time. Microstructural analyses highlight denser matrices and improve mechanical properties through effective activation processes. These advancements highlight GPC's potential as a sustainable and durable construction material, emphasizing the need for further research and development for widespread adoption in the industry. The review categorizes frequently employed precursors based on their primary chemical components and explores how different binder types impact various aspects of lightweight geopolymers. Additionally, it consolidates optimal mix designs from various studies to aid readers in choosing suitable binders and achieving desired density and compressive strength goals through the utilization of different precursors, alkaline binder solutions, and lightweight concrete.https://ceij.ut.ac.ir/article_99384_dbaa2b95ad2abf81e5c7f7cf72ebd04d.pdfUniversity of TehranCivil Engineering Infrastructures Journal2322-209359120260601Multiphysics Finite Element Analysis of Limestone Dissolution Case Study: Northern Plains Limestone Bed of Hamedan29439831410.22059/ceij.2024.364910.1959ENHosseinHossein Pour HamedaniPh.D. Candidate , Civil Engineering Department, Bu-Ali Sina University Hamedan, Iran.0009-0000-7199-0396MohammadMalekiProfessor, Civil Engineering Department, Bu-Ali Sina University Hamedan, Iran.0000-0001-6524-5701Journal Article20230906Fluid flow in the karst bed leads to enlarged voids and cavities and increases the risk of instability and consequently, catastrophic events such as sinkholes may occur. In this paper, the dissolution of limestone was simulated numerically by employing a finite element code capable of taking into account multi-physics governing equations and incorporating mesh movement and updating . In the first step, the finite element code was identified based on dissolution experimental results concerning three regions of Hamekasi, Ali Sadr, and Abshineh in the northern plains of hamedan city. In the second step, the temporal geometrical evolution of a vertical cavity in the dissolution process during time for the mentioned limestone beds were studied and compared. The results showed that the proposed numerical model has very good capabilities in reproducing experimental data. The results of the dissolution in a vertical hole indicate that entering fluid velocity in comparison with the initial diameter cavity, plays an important role in the hole widening. The widening trend of the hole in the inlet and outlet sections is the same for different initial hole diameters, however, the width of the inlet section of the flow is greater than the width of the middle and outlet sections.https://ceij.ut.ac.ir/article_98314_07a09583bb41fc5bb599299eca9a2fac.pdfUniversity of TehranCivil Engineering Infrastructures Journal2322-209359120260601Hybrid Neuro-Fuzzy ML and MC Simulation-Based Reliability Analysis of Simply Supported Beam45639835910.22059/ceij.2024.374883.2045ENAbhishekKumarPh.D. Candidate, Department of Civil Engineering, National Institute of Technology, Patna, India.0009-0002-9192-6820BabooRaiAssociate Professor, Department of Civil Engineering, National Institute of Technology, Patna, India.0000-0003-2906-6479PijushSamuiProfessor, Department of Civil Engineering, National Institute of Technology, Patna, India.0000-0003-2906-6479Journal Article20240418This paper introduces an innovative approach utilizing hybrid Adaptive Neuro Fuzzy Inference System (ANFIS) models for the reliability-based design of structural beams. While structural reliability analysis with hybrid ANFIS models remains largely unexplored, existing studies primarily rely on rudimentary simulation models. To address this gap, this study employs Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) to enhance the performance of the ANFIS model. The Machine Learning (ML) models are validated on three Monte-Carlo datasets of size 1000, 2500, and 5000. The findings demonstrate satisfactory performance across all ML models, with the hybrid ANFIS models exhibiting superior predictive capabilities compared to traditional methods. Among the hybrid ANFIS models, ANFIS-PSO emerges as the most robust. The reliability indices and Probability of Failure (POF) values are calculated for the predicted values and compared with actual values. It is concluded that the ANFIS-PSO-based methodology is the most robust model and outperforms the other models. It is noteworthy that while the ANFIS-PSO model demonstrates exceptional performance, all models presented in this study serve as valuable tools for reliability-based structural design, offering robust alternatives to conventional methodologies.https://ceij.ut.ac.ir/article_98359_04c08b6e8ea351b5b41a40686b75b9b3.pdfUniversity of TehranCivil Engineering Infrastructures Journal2322-209359120260601Numerical Simulation of Local Reinforcement of Steel Column-Beam Connections65849893710.22059/ceij.2024.377321.2077ENWardaBadisPh.D. Candidate, Department of Civil Engineering, University of Blida 1, Blida, Algeria.0009-0009-9207-9572MenadiBelkacemProfessor, Department of Civil Engineering, Faculty of Technology, University of Blida 1, Algeria.0000-0001-5710-5928RafikTalebAssociate Professor, Department of Civil Engineering, Faculty of Technology, University of Blida 1, Algeria.0000-0002-4021-7824Journal Article20240611This study examines the behavior of beam-to-column moment connections where the beam tension flange force is transferred to the column flanges through bolts attached to a welded end-plate or T-stub. A significant challenge with this type of connection is the potential inability of the column flange to develop the required design resistance, necessitating either an increase in size or local reinforcement. Three-dimensional finite element analysis models of nine T-stubs were developed using ABAQUS software to investigate the behavior of such connections when locally reinforced with non-welded stiffeners. The numerical simulation results were compared with available experimental data from the literature. The study evaluated the influence of different reinforcement types on the stress and displacement distribution at the column flange level. The effectiveness of using angles and channels as reinforcement was clearly demonstrated, with an observed improvement in connection strength of over 250% for models with channel plates and 280% for models with angle plates compared to the unreinforced model. Additionally, these reinforcements resulted in significantly lower displacement, with reductions of about 90% for both channel and angle plate models.https://ceij.ut.ac.ir/article_98937_73a3320fa46a5e4fad268056af61cd42.pdfUniversity of TehranCivil Engineering Infrastructures Journal2322-209359120260601Probabilistic Analysis of Braced Excavation for Box Drain Construction in Cuttack851039893910.22059/ceij.2024.371955.2012ENPratimaKumariM.Sc., Department of Civil Engineering, National Institute of Technology, Patna, India.0009-0006-8613-1547AvijitBurmanAssociate Professor, Department of Civil Engineering, National Institute of Technology, Patna, India.0000-0001-8243-351XPijushSamuiProfessor, Department of Civil Engineering, National Institute of Technology, Patna, India.0000-0003-2906-6479Journal Article20240208This study presents a probabilistic failure analysis of a Braced Excavation System (BES) for a 9.0 m deep box drain in Cuttack, Odisha, using Monte Carlo Simulation (MCS) and Subset Simulation (SS) methods. The drain spans 3.0 km through highly plastic clayey soil with low shear strength, requiring excavation and braced techniques. Geotechnical field exploration suggests that the soil along the 3.0 km long stretch of the proposed box drain site has a very wide variation. A probabilistic analysis is conducted to ascertain the risk involved in the designed BES. In probabilistic analysis of the BES, cohesion and unit weight of soil are treated as lognormal distributed random variables. Spatially correlated random fields along the depth are generated using the Pearson correlation matrix and the Markov correlation function. MCS with 10000 samples has been run to conduct the probabilistic response of the BES. The paper also presents the results of SS, an advanced version of MCS that enables rapid probabilistic analysis. Furthermore, the results obtained using MCS and SS are compared to establish the relative superiority of SS over MCS.https://ceij.ut.ac.ir/article_98939_d4f1ce2bdf21a44d8c89932eac47f846.pdfUniversity of TehranCivil Engineering Infrastructures Journal2322-209359120260601A Study on Geotechnical Behavior of Municipal Solid Waste Ash Treated with Fiber and Cement1051229911210.22059/ceij.2024.375087.2049ENNeelamSinghResearch Scholar, Department of Civil Engineering, Central University of Haryana, Mahendergarh, India.0000-0003-2973-4932VikasKumarAssistant Professor, Department of Civil Engineering, Central University of Haryana, Mahendergarh, India.0000-0003-4807-6584Journal Article20240422The geotechnical properties of untreated Municipal Solid Waste (MSW) ash and the MSW ash treated with fiber and cement were investigated through a series of laboratory tests including compaction, Unconfined Compressive Strength (UCS), and Split Tensile Strength (STS) with different mixing proportions of fiber and cement. The physical characteristics of MSW ash are similar to those of silty sand, with a specific gravity of 2.26. The combination of fiber and cement is capable of improving the compaction behavior of MSW ash by increasing its strength and reducing its tendency to deform or crack under the load. It is observed from the test study that the addition of 0.5% fiber of 12 mm length with 8% cement by weight of MSW ash mix gives the optimum result in terms of UCS and STS as compared to untreated MSW ash. The increment in cohesion (<em>c</em>) and angle of internal friction (<em>ϕ</em>) is associated with the increment in cement and fiber content, respectively. An improvement factor (<em>I<sub>f</sub></em>) is defined to determine the percentage increment in the value of UCS and STS.https://ceij.ut.ac.ir/article_99112_ad59566544352f19adce87108468deb4.pdfUniversity of TehranCivil Engineering Infrastructures Journal2322-209359120260601Experimental and Numerical Study of the Effect of Friction Damper on the Seismic Behavior of Concrete Frame1231389915110.22059/ceij.2024.378792.2088ENSiamakNajafiM.Sc., Department of Civil Engineering, Faculty of Engineering, Razi University, Kermanshah, Iran.0009-0003-2618-985XRezaAghayariAssociate Professor, Department of Civil Engineering, Faculty of Engineering, Razi University, Kermanshah, Iran.0000-0002-9747-3810KambizCheraghiM.Sc., Department of Civil Engineering, Faculty of Engineering, Razi University, Kermanshah, Iran.0000-0002-8177-394XMehrzadTahamouliRoudsariAssociate Professor, Department of Civil Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.0000-0003-1069-3763Journal Article20240701Friction dampers are an effective way to reduce earthquake forces in concrete structures. The study examines the performance of three experimental Reinforced Concrete (RC) moment frames with different friction dampers. Two dampers had a transmission function, and one had a rotational function. After loading, their hysteresis diagrams were extracted and compared. In order to study the impact of slip force on the seismic performance of a concrete frame, numerical analyses were conducted. This section focused on a rotational damper that had demonstrated excellent experimental performance. At first, the friction damper was investigated numerically, and an approximate equation was proposed to calculate its sliding force. Similarly, following validation, the concrete frame equipped with rotational friction dampers was numerically analyzed. The analysis was performed using nonlinear static analysis, and the outputs of the model included resistance, ductility, energy dissipation, and stiffness. The experimental results demonstrated that, in terms of ductility, energy dissipation, and elastic stiffness, the rotational friction damper exhibited the best performance. Based on the numerical results, the best performance of the frame was obtained when the sliding force of the damper was equal to 1.4 times the strength of the bare frame.https://ceij.ut.ac.ir/article_99151_32b16f836851b3eb95600ca69ea2dfbf.pdfUniversity of TehranCivil Engineering Infrastructures Journal2322-209359120260601Integrating Machine Learning and Genetic Expression Programming for Enhanced Punching Shear Strength Prediction1391609931710.22059/ceij.2024.380171.2118ENAlirezaMahmoudianM.Sc., Department of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran.0009-0005-4870-5493NimaTajikPh.D. Candidate, Department of Civil, Structural and Environmental Engineering, State University of New York at Buffalo, USA.0009-0006-5228-9223AmirhosseinDarabiM.Sc., School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran.0009-0000-2994-0205MostafaMohammadzadeh TaleshiPh.D. Candidate, Civil and Environmental Engineering Department, University of Nevada, Reno.0009-0008-7049-5068SabaMarmarchiniaPh.D. Candidate, Department of Civil, Structural and Environmental Engineering, State University of New York at Buffalo, USA.0009-0000-4221-5200AbazarAsghariAssociate Professor, School of Civil Engineering, College of Engineering, University of Tehran, Iran.0009-0005-3224-1815Seyed RasoulMirghaderiProfessor, School of Civil Engineering, College of Engineering, University of Tehran, Iran.0009-0001-6256-3971Journal Article20240730Estimating the punching shear strength of Reinforced Concrete (RC) flat slabs is critical in structural engineering due to potential catastrophic failures. This study introduces advanced data-driven methods, including Machine Learning (ML), Deep Learning (DL), and Genetic Expression Programming (GEP), to improve predictions of punching shear strength. Analyzing a dataset of 380 test samples, the research evaluates various models such as linear regression, stochastic gradient descent, ridge regression, decision trees, K-nearest neighbors, random forests, adaptive boosting, Extreme Gradient Boosting (XGBoost) for ML, alongside Artificial Neural Networks (ANNs) for DL, and GEP for deriving explicit equations. Significant enhancements in model performance were achieved through rigorous hyperparameter tuning, notably with the XGBoost model, which attained an coefficient of determination (R²) score of 0.98, surpassing other models and existing code-based predictions. The study uses SHapley values to interpret model predictions, highlighting the significant impact of slab depth on punching shear strength, especially in the XGBoost model. Additionally, the GEP method derives explicit equations that accurately represent the relationship between input features and punching shear strength. This research highlights the advantages of advanced computational models and offers new insights into the factors influencing punching shear strength in RC slabs.https://ceij.ut.ac.ir/article_99317_cc5c572f4f6b9a63939c02b68e7f4cd9.pdfUniversity of TehranCivil Engineering Infrastructures Journal2322-209359120260601Use of Microgrid Fiber as a New Reinforcement Additive to Improve Compressive Strength and Ductility Properties of Cement Stabilized Sands1611729938310.22059/ceij.2024.376780.2064ENErenKomurluAssociate Professor, Department of Civil Engineering, Giresun University, Giresun, Turkey.0000-0002-2123-7678Journal Article20240520In this study, the use of a new polypropylene geofiber type called Microgrid Fiber (MGF) was investigated in comparison with a conventional Polypropylene Fiber (PPF) product. Uniaxial Compressive Strength (UCS), modulus of elasticity, ductility, and energy absorption capacities of Cement Stabilized Sand (CSS) mixes reinforced with different polypropylene type geofiber additives were investigated, carrying out a series of uniaxial deformability tests. According to the results, MGF-type fibers increased the strength and modulus of elasticity values at higher rates in comparison with the conventional PPF product. For the same fiber content, MGF-type new additive supplied up to 31% higher UCS values and 26% higher modulus elasticity values than those of the specimens with the conventional PPF additive. In addition, it was determined that MGF-type new fiber additives can supply better increases in ductility and Energy Absorption Capacity (EAC) properties of the CSS compared to the conventional PPF product. Rather than the conventional fiber, the novel MGF additives were assessed to be more effective for having proper adherence and soil reinforcement performances.https://ceij.ut.ac.ir/article_99383_b355bcbbdacf1ee84ba6a0b9d9820047.pdfUniversity of TehranCivil Engineering Infrastructures Journal2322-209359120260601Mechanical and Durability Properties of Green SCC Mixed with Pozzolan and Ferro-Silicomanganese Slag as Partial Aggregate Replacement1731889962010.22059/ceij.2024.376496.2060ENRezaFarazmandM.Sc., Kerman Cement Concrete Research Center, Kerman Cement Industries Group, Kerman, Iran.0000-0002-1772-8554Seyed JamilaldinFatemiProfessor, Department of Chemistry, Faculty of Science, Shahid Bahonar University of Kerman, Kerman, Iran.0000-0001-6126-5481FereidounRahmaniM.Sc., Kerman Cement Concrete Research Center, Kerman Cement Industries Group, Kerman, Iran.0009-0003-1760-4417MeysamRashidiM.Sc., Kerman Cement Concrete Research Center, Kerman Cement Industries Group, Kerman, Iran.0009-0000-3086-2566ImanAghamolaieAssistant Professor, Department of Geology, Faculty of Science, Shahid Bahonar University of Kerman, Kerman, Iran.0000-0003-1711-9510MehdiShafieeM.Sc., Kerman Cement Concrete Research Center, Kerman Cement Industries Group, Kerman, Iran.0000-0003-3493-9078Journal Article20240514Making green Self-Compacting Concrete (SCC) is one of the valuable measures that, along with the development of communities, helps to reduce environmental pollution. 10 different SCC mix designs were designed and fabricated using Khash and Sirjan pozzolans, 25, 50, 75, and 100% replacement of aggregate with dimensions in the range of 4.75-9.5 mm with Ferro-Silicomanganese Slag (FSiMnS). The water-to-cement ratio is 0.36 for all SCC mixes. Slump flow, V-funnel, and l-box tests were performed on fresh concrete to investigate the fresh properties and rheology of green SCC. A total of 250 cubic specimens of 10 × 10 cm<sup>2</sup>, 60 cubic specimens of 15 × 15 cm<sup>2</sup>, and 40 cylindrical specimens of 10 × 20 cm<sup>2</sup> for testing compressive strength, Rapid Chloride Permeability Test (RCPT), surface electrical resistance, water penetration depth under pressure, and half-hour water absorption to evaluate the durability properties of concrete, were sampled. From the obtained results, it was concluded that replacing the aggregate with FSiMnS provides better compressive strength results up to 18%, and somehow increase in durability test results, but has adverse effects on the workability parameters of SCC. Sirjan pozzolan has shown better performance than Khash pozzolan in all durability tests, while Khash pozzolan has higher initial compressive strength.https://ceij.ut.ac.ir/article_99620_3855280ae05920f6a6ea9cd8de4e3cc8.pdfUniversity of TehranCivil Engineering Infrastructures Journal2322-209359120260601Performance of Under Shear Reinforced Concrete Beams with Varying Strength against Static and Impact Load1892069969910.22059/ceij.2024.379538.2106ENSenthilKasilingamAssistant Professor, Department of Civil Engineering, Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India.0000-0001-5051-0920ManishKhannaResearch Scholar, Department of Civil Engineering, Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India.Journal Article20240730An attempt has been made to study the response of under shear Reinforced Concrete (RC) beams with varying strength concrete under static and impact loads. The experiment has been performed on beam strength as 20, 30, 40, and 50 MPa having cross sections of 50 × 100 mm with a span of 1.1 m. Also, a benchmark study was performed under a four-point bending static test, and further, three-point bending was converted theoretically in order to keep the test configuration equivalent to a three-point impact load test for comparison. The resistance of RC beams was studied in terms of impact force versus time and the deformed profile. It was observed that the resistance of beams was found to increase with increasing the strength of concrete; however, the beams were failed by shear. The reason may be due to the lack of shear capacity. The peak static force by four-point bending tests was found to be 33% higher than that of three-point bending tests. It was also observed that the Dynamic Amplification Factor (DAF) increases with an increase of concrete strength, and the highest DAF was found to be 4.75, corresponding to M50 concrete, whereas the same was found to be 3.5, corresponding to M20 concrete.https://ceij.ut.ac.ir/article_99699_ea651f8fe64fe9294ad879dd2dde10a6.pdfUniversity of TehranCivil Engineering Infrastructures Journal2322-209359120260601A Comparative Study and Analysis of Transmission Vapor Pipelines for Optimizing Water Purification and Transfer20722310447210.22059/ceij.2025.392043.2273ENKooshaAghazadehPh.D., School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran.0000-0003-3413-2995Behrouz AsadzadehTotonchiM.Sc., School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran.0009-0003-4496-1081RezaAttarnejadAssociate Professor, School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran.0000-0003-1955-2887Journal Article20250312Water scarcity poses a significant challenge globally, driving the need for effective solutions in water transport and purification. This paper examines the innovative use of vapor pipelines that leverage water vapor for efficient transportation, based on the principles of evaporation and condensation. It focuses on optimizing water treatment and transmission by investigating pressure differentials that enable vapor flow from the evaporation to the condensation section under sub-atmospheric conditions. The study compares two desalination pipeline systems: an adiabatic system and a steam trap system. Findings indicate that the steam trap system transfers 30% to 35% more water than the adiabatic system, with an additional 5% collected during transit. Temperature assessments reveal that the adiabatic system maintains higher temperatures, correlating with reduced energy consumption, while the steam trap system displays greater variation in vapor velocity. Additionally, the steam trap experiences a 20% greater pressure drop, suggesting potential benefits for the adiabatic approach in specific contexts. Economic feasibility is contingent on environmental conditions, with each system facing distinct operational challenges. This study highlights the necessity of evaluating both systems based on their unique circumstances to effectively tackle the pressing issue of water scarcity. Ultimately, tailored solutions are essential for optimizing water resources worldwide.https://ceij.ut.ac.ir/article_104472_28ecb00cae05faadc96ff85378692bc1.pdfUniversity of TehranCivil Engineering Infrastructures Journal2322-209359120260601Sustainable Fire Safety Assessment and Rapid Visual Screening Framework for Existing Buildings22523910274210.22059/ceij.2025.392064.2274ENFarhazAhmedPh.D. Candidate, Department of Civil Engineering, School of Engineering and Technology (SET), Manav Rachna International Institute of Research and Studies, Faridabad, India.0000-0002-6667-9138AnjaliGuptaProfessor, Department of Civil Engineering, School of Engineering and Technology (SET), Manav Rachna International Institute of Research and Studies, Faridabad, India.0000-0001-5117-5896Journal Article20250323This study investigates fire safety compliance in existing buildings using a dual-method approach: a stakeholder survey and a Rapid Visual Screening (RVS)-based Fire Safety Rating (FSR) system. A survey of 50 professionals (including architects, engineers, fire officers, and occupants) identified key barriers such as inadequate safety measures (40%) and poor retrofitting practices (30%). Statistical analysis using SPSS revealed a significant negative correlation between fire safety compliance and building age. Chi-square tests confirmed that older buildings are notably more non-compliant (χ² = 50.000, <em>p</em> < 0.001). Based on these insights, a comprehensive RVS framework was developed to evaluate six critical domains: fire prevention, detection systems, suppression systems, emergency escape, structural protection, and preparedness. Field application in 10 residential, commercial, and educational buildings exposed major deficiencies, particularly in escape routes and suppression systems in commercial buildings. Reliability testing validated the framework’s effectiveness as a practical assessment tool. The study also integrates sustainability elements, such as Solar-Powered Alarms (SPA) and Eco-Friendly Extinguishers (EFE), to promote resilient, future-ready fire safety strategies. This research offers a scalable model for assessing and improving fire safety in aging urban infrastructure, with implications for policy, regulatory reform, and urban resilience planning.https://ceij.ut.ac.ir/article_102742_3efcb63b2d22bea513eebd2c6382ff19.pdfUniversity of TehranCivil Engineering Infrastructures Journal2322-209359120260601Thermal Performance Prediction for Alkali-Activated Concrete Using GGBFS, NaOH and Sodium Silicate2412539894910.22059/ceij.2024.369661.1996ENPramodKumarAssistant Professor, Department of Civil Engineering, Mohan Babu University (SVEC), Tirupati, Andhra Pradesh, India.0000-0002-1411-9374SanjaySharmaResearch Scholar, Department of Civil Engineering, National Institute of Technology, Jamshedpur, Jharkhand, India.0009-0005-3129-6080P SivaKumarAssistant Professor, Department of Civil Engineering, Mohan Babu University (SVEC), Tirupati, Andhra Pradesh, India.0009-0008-9864-3165M. S.YuvarajAssistant Professor, Department of Civil Engineering, Mohan Babu University (SVEC), Tirupati, Andhra Pradesh, India.0000-0003-4431-053XD VPurushothamAssistant Professor, Department of Civil Engineering, Mohan Babu University (SVEC), Tirupati, Andhra Pradesh, India.0009-0008-9864-3165SaurabhKumarAssistant Professor, Department of Civil Engineering, IIMT University, Meerut, Uttar Pradesh, India.0000-0002-1044-5658Kapil KumarVashisthaAssistant Professor, Department of Civil Engineering, IIMT University, Meerut, Uttar Pradesh, India.0000-0002-1044-5658AmitKumarAssistant Professor, Department of Civil Engineering, IIMT University, Meerut, Uttar Pradesh, India.0000-0002-8475-2538AbhilashGogineniResearch Scholar, Department of Civil Engineering, National Institute of Technology, Jamshedpur, Jharkhand, India.Journal Article20231215In fire safety, understanding the behaviour of concrete exposed to high temperatures is essential. This study experimentally explored the mechanical properties of Alkali-Activated Concrete (AAC) and utilized Recurrent Neural Network (RNN)-based Long Short-Term Memory (LSTM) techniques to predict the mechanical properties of AAC at elevated temperatures. The LSTM models accurately predicted compressive, flexural, and split tensile strengths, with coefficients of determination (R²) exceeding 0.9 for training and testing datasets. Specifically, R² values were 0.9838 and 0.9134 for compressive strength, 0.9965 and 0.9861 for flexural strength, and 0.9743 and 0.9852 for split tensile strength in training and testing, respectively. The models also yielded low Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) values, further underscoring their predictive reliability. Error analysis across all mechanical properties affirmed the LSTM models' robustness in capturing AAC's complex behaviour under thermal stress. These results suggest that LSTM networks are highly effective tools for predicting material properties crucial for structural fire safety and sustainable construction, offering a promising approach for improving the resilience and safety of AAC structures in extreme conditions.https://ceij.ut.ac.ir/article_98949_562b7248bf501ee9275924a11569aefd.pdfUniversity of TehranCivil Engineering Infrastructures Journal2322-209359120260601Analysis of Hydraulic Jump Characteristics in U-Shaped Channel2552689961910.22059/ceij.2024.374899.2046ENSumitGandhiProfessor, Department of Civil Engineering, Jaypee University of Engineering and Technology, Guna (MP), India.0000-0003-4382-5937Journal Article20240409Typical supercritical flow characteristics like, sequent depth ratio, relative jump height, relative energy loss, efficiency of jump, relative prejump depth, relative postjump depth, relative length of the roller and jump in the U-shaped channel are experimentally studied. Based on the experimental findings, physical theories for the variance in these characteristics concerning the Froude number are presented. Empirical models are developed considering the influence of inflow Froude number varying between 4 and 20 and Reynolds number between 1,638,009 and 3,394,784. Some models were also validated and yielded satisfactory results with good R<sup>2</sup> values. For comparison and a deeper comprehension of hydraulic jump characteristics, computational multivariate statistical techniques like Principal Component Analysis (PCA) and Factor Analysis (FA) are applied. These techniques are used to identify patterns in an effort to explain the variation in a sizable set of closely related jump characteristics. Verifiers for the different principal components were analyzed, and verifactor VF1 (with 64 %) had strong positive loadings on the sequent depth ratio, the relative jump height, the relative energy loss, the relative length of the roller and jump, while VF2 (with 33%) had strong positive loadings on the relative prejump depth and the relative postjump depth and moderate positive loading on the efficiency of jump. These statistical methods proved to be valuable tools for identifying the key characteristics of a phenomenon and its relative significance.https://ceij.ut.ac.ir/article_99619_9e3a40b7eee0f51ee4632e6951a8d05e.pdf