https://www.ijcoe.org/ International Journal Of Coastal, Offshore And Environmental Engineering(ijcoe) en daily 1 Mon, 11 Mar 2024 00:00:00 +0330 Mon, 11 Mar 2024 00:00:00 +0330 https://www.ijcoe.org/article_192306.html Sea surface temperature fronts are crucial in studying climate change, air-sea interaction, fisheries production, and oceanography. These fronts are formed due to various oceanographic features, such as bathymetry, upwelling, the convergence of surface waters, and internal waves. To identify the temperature fronts of the Caspian Sea, researchers in this study used remote sensing techniques. The SIED method was employed, which is considered one of the best techniques for detecting temperature fronts in satellite images. This method works by analysing the temperature histogram of surface water masses, making it more reliable than other methods. The study analyzed MODIS images over a period of five years to establish the relationship between physical phenomena and temperature fronts. The results confirmed that the traits of the temperature fronts of the Caspian Sea are variable in time and place, and the maximum presence of temperature fronts inside the northern half of the Caspian Sea belongs to November and December, while in the southern half, it belongs to January. Middle Caspian Sea temperature fronts correspond to inner waves, particularly in February, May, and March. On the other hand, the temperature fronts are shaped greater at a distance from the coast, wherein there's a steep bed and in deep areas, the variety of diagnosed fronts is small. The presence of mesoscale eddies inside the Middle Caspian is likewise one of the motives for growing temperature fronts at the eastern and western coasts of the Middle Caspian. https://www.ijcoe.org/article_192454.html Sonar image registration poses challenges due to its unique characteristics and real-time application demands. With lower resolution and higher noise levels compared to optical images, sonar imagery lacks distinct features, complicating traditional detection methods. Computational complexity further escalates with higher-order moments and larger image sizes. In real-time contexts like underwater vehicle autonomy, rapid and efficient moment computation is vital for timely decision-making and navigation. Overcoming these obstacles requires innovative hardware structures and parallel processing techniques. In our previous study, we introduced a systolic array and pipeline structure for high-order moment computation in grayscale images. Expanding on this, our current paper introduces the Parallel and Comparator-based Structure (PCS) to accelerate moment calculation for sonar image registration. PCS employs parallel computation and a comparator for efficiency. Through strategic adder relocation and integration of power cores, compressors, and adder units, PCS achieves streamlined computation with fixed latency. Experimental results demonstrate significant speed enhancements, positioning PCS as a promising solution for real-time underwater image processing. https://www.ijcoe.org/article_192156.html Image moments are pivotal in the control of Unmanned Underwater Vehicles (UUVs), empowering them to extract valuable insights from onboard camera images, identify objects, navigate autonomously, and adapt to evolving environmental conditions. Integrating image moment analysis into UUV control systems amplifies their effectiveness in exploration, research, surveillance, and various underwater applications. However, the computational demands of moment calculation algorithms pose challenges for real-time implementation, particularly with higher moment orders. In this study, we propose a novel structure based on systolic arrays, leveraging pipeline technique, to compute moments up to the 14th order of grayscale images in real time. Implemented in 45nm CMOS technology, our design demonstrates impressive performance, with each cell capable of computing the 14th order moment of a 1024×1024 image at a remarkable rate of 954 fps. Moreover, our design boasts low power consumption, registering at only 3.254 mW, demonstrating its potential for enhancing UUV control systems for diverse underwater applications. https://www.ijcoe.org/article_195598.html Wind waves are one of the most important phenomena in marine environments that affect inshore and offshore processes. This research aims to investigate the accuracy of empirical and spectral methods in predicting wind wave characteristics in Amir Abad port. For this purpose, empirical methods SMB, SPM, CEM, and JONSWAP were used, and wave characteristics for wind durations of 1 to 12 hours were calculated. Predicted wave heights and wave periods were compared with measured data, and errors in experimental procedures were determined. According to the study, the most appropriate method to predict wave heights is the JONSWAP method, while the CEM method is the most suitable for determining wave periods. The SPM method was found to be inappropriate for determining the wave profile in Amir Abad port. To more completely evaluate methods to predict waves, wave heights of measured data were compared with significant wave height measured by the spectrum of JONSWAP, Pierson-Moskowitz, Mitsuyasu, and ITTC. It was found that two peaks with different frequencies are observed in the spectrum of measured data. Then, the spectrum of the region, regardless of swell peak, was compared with other mentioned spectra. In this comparison, Mitsuyasu was determined to be the most appropriate spectrum, and after calibration, wave parameters Hm0, H1/10, Tz, and Tp were calculated. By comparing the calculated Hs using Multipeak and Mitsuyasu spectrum, it was found that Multipeak spectrum has the minimum error in calculating significant wave height. https://www.ijcoe.org/article_197048.html In recent times,the field of robotics and its applications have become increasingly attractive for researchers, particularly in the context of industrial control and automation. However, the approach predominant in the design and construction of robots until not too long ago favored solidity over flexibility. The primary rationale behind this inclination was the perceived weakness associated with highly flexible robots. While flexibility is deemed acceptable for certain purposes, the tendency was to prioritize simplicity and control, leading to the widespread adoption of rigid robotic structures.The drawback of this rigid approach became apparent as achieving control in highly rigid robots posed challenges. Such robots were often heavy, voluminous, and possessed a high weight-to-tolerance ratio, resulting in substantial energy consumption. The lack of adaptability and flexibility at joints further compounded these issues. The assumption that rigidity simplifies control was a guiding principle in designing robots. However, the contemporary consensus is that a rigid-centric methodology does not meet all the control needs in robotics. There is a growing recognition of the importance of flexibility and adaptability in robotic joints. This shift in perspective is driven by the understanding that not every joint in a robot needs to be rigid. Accepting flexibility in joints is based on the assumption that simplicity in control can still be achieved without rigid constraints. In the present era, it is acknowledged that a rigid-centric approach does not provide a comprehensive solution for the diverse requirements of robotic control.The acceptance of flexibility and adaptability in robotic systems has gained momentum. https://www.ijcoe.org/article_197056.html This study explores the enhancement of power quality in AC-AC direct converters through the integration of hybrid filters. AC-AC direct converters play a crucial role in various applications, including motor drives and renewable energy systems. However, they often suffer from power quality issues such as harmonic distortion and voltage fluctuations. Hybrid filters offer a promising solution by combining passive and active filtering techniques to mitigate these issues effectively. The historical evolution of matrix converters provides valuable insights into the development of AC-AC direct converters. Control strategies based on vector space modulation (SVM) and pulse-width modulation (PWM) techniques are investigated to optimize the performance of hybrid filters. Additionally, the implementation of hybrid filters in AC-AC direct converters is analyzed to achieve improved power quality and system stability. Overall, this research contributes to advancing the understanding and application of hybrid filters for enhancing the power quality of AC-AC direct converters. Abstract ok https://www.ijcoe.org/article_197058.html Energy has been a central focus throughout human history, and currently, with the imperative for sustainable development, there is a global increase in the utilization of renewable energy sources. The adoption of renewable energy is considered a key indicator of a nation's progress in energy consumption. Three major factors contribute to the growing market interest in renewable energies. Firstly, there is a concern for national energy security as oil consumption is on the rise and expected to surpass domestic production levels soon. This has prompted a shift towards alternative energy sources such as hydropower, wind, solar, and geothermal power, encouraging large-scale power generation. This article explores the development of an optimal energy management program, considering renewable energy sources like wind power plants and photovoltaic panels. The optimization process employs meta-heuristic algorithms, specifically genetics (multi-objective) and gray wolf algorithms. The results of network analysis reveal that in the initial state, certain buses exhibit a relatively large numerical value for the sensitivity coefficient, while others show a smaller value. The sensitivity coefficient indicates the degree of dependence and sensitivity of a bus on losses. Buses with high sensitivity coefficients are identified as potential candidates for installing Distributed Generators (DGs) to improve overall system efficiency. https://www.ijcoe.org/article_197404.html In the field of structural engineering, neural networks are utilized to detect damage in offshore jacket platforms using a combination of modal analysis results. By analyzing the shape of natural frequencies and utilizing information from five modal results, damage identification indices are developed. This study investigates Structural Health Monitoring (SHM) strategies utilizing mode shape analysis and neural networks to detect failures within a multi-story structure. Various failure scenarios, including corrosion-induced damage and collisions, were analyzed across 52 structural members, with induced damage ranging from 0% to 20%.Results reveal the critical importance of floor levels: the fourth floor exhibited heightened accuracy in failure detection, particularly in columns and wind braces, crucial for corrosion protection. Notably, secondary beams consistently displayed higher precision in identifying failures compared to main beams. The neural network performance peaked at a mean squared error of 0.039206, validating its efficiency in detecting and allocating damage across different structural elements. Subsequent scenarios involving two members of the fourth floor demonstrated the adaptability of the approach in addressing diverse failure rates. This research underscores the efficacy of combining mode shape analysis and neural networks for robust SHM. It emphasizes the significance of floor levels and specific structural elements in enhancing failure detection accuracy, offering valuable insights for proactive maintenance and structural integrity preservation. https://www.ijcoe.org/article_198595.html This academic article presents a comprehensive study on the numerical solving of the Duffing equation using the Euler method in the time domain and analytical investigation in the frequency domain, with a specific focus on its application to a Tension Leg Platform (TLP) offshore wind turbine system. The Duffing equation, a classical nonlinear mathematical model, serves as a valuable tool for characterizing the dynamic response of the TLP platform subjected to varying wind loads and wave excitations. In the numerical approach, the Euler method is employed to solve the Duffing equation in the time domain, offering an efficient and straightforward numerical solution. By discretizing the equation, the system's transient behavior is captured, enabling a detailed analysis of the TLP wind turbine's response to different operational conditions. Conversely, an analytical investigation of the Duffing equation in the frequency domain is conducted, providing valuable insights into the system's steady-state response under harmonic excitations. By applying mathematical techniques, the system's frequency response is obtained, enabling the identification of resonance and frequency-domain characteristics critical to the TLP wind turbine's performance. In conclusion, the research outcomes contribute to the deeper understanding of the complex interactions between wind, waves, and the TLP platform, providing valuable knowledge for the further development and optimization of offshore wind energy systems. Additionally, the successful application of the Euler method and the analytical approach to the Duffing equation can be extended to other nonlinear systems in engineering and scientific disciplines. https://www.ijcoe.org/article_200921.html In this study, a convolutional neural network has been proposed to estimate the speed model of the subsurface structure based on multi-channel surface wave (MASW) analysis, addressing the Full-waveform Inversion (FWI) problem. A structure of deep supervision U-net architecture with two-stage encoder-decoder has been used in the proposed network. The proposed network structure is evaluated by 2D data models of an open source synthetic seismic Dataset, OPEN FWI, with different layering structures using Mean Squared Error (MSE), Structural Similarity (SSIM) and Mean Absolute Error (MAE) criteria. Also, in order to evaluate the robustness of the proposed method, the effect of filtering and removing parts of the input data have been investigated. A comparison results with several FWI methods in the current literature have been provided. The experimental results show that the proposed method is able to provide more accuracy in estimating and reconstructing the velocity model which results in better subsurface layering estimation. https://www.ijcoe.org/article_201148.html This study investigates the behavior of a positively buoyant jet from a single-port discharge using both numerical and experimental approaches. Shortly after discharge into the sea, a buoyant jet reaches the surface, potentially having a significant impact on the local environment. We evaluated the use of downward-inclined nozzles as a solution to enhance flow trajectory and dilution up to the surface. The discharge process was numerically simulated using OpenFoam, with nozzle inclinations of 0 and -15 degrees, to explore the inclination effect. OpenFoam which is an open-source software for CFD simulation, was developed to facilitate the modeling of complex hydrodynamic processes. The simulated scenario was experimentally validated using a laboratory-scaled model of the horizontal discharge in front of the Laser-Induced Fluorescence (LIF) system for various discharge densimetric Froude numbers (〖Fr〗_d=10, 15, 20). This setup was used for the capture and analysis of jet trajectory and dilution along the flow path. Comparing the numerical results with experimental data demonstrates that the model can predict geometric characteristics and dilution with reasonable accuracy. Once calibrated, the model has been used to predict flow features from the inclined nozzle at -15 degrees. For the -15-degree jet, the dilution rate at the sea surface was found 18.72% higher than the horizontal discharge. Downward inclination directs the flow in the opposite direction of the effective buoyancy and it leads to a longer path and better mixing. Therefore, our results show that to what extent the inclination of the nozzle will affect flow mixing and dilution at the surface of receiving water in coastal sewage disposal. https://www.ijcoe.org/article_201150.html This paper presents a fully automated methodology for extracting time-series of monthly shoreline changes along the sandy beaches of the Ongole coast in Andhra Pradesh, India, from 2000 to 2023 using publicly available satellite imagery. The methodology involves the identification of sandy coastline sections within the region of interest, creating cross shore transects automatically at each site, and utilizing the open-source global shoreline mapping toolbox called CoastSat. The CoastSat tool is employed to extract time-series of shoreline change at each transect. To account for variations in tide levels among satellite images, the final step includes tidally correcting the shoreline change time-series using predicted tide levels and an image-derived estimation of the average intertidal beach slope. In conclusion, this paper presents a robust and automated methodology for analysing shoreline changes along the Prakasam district coast of Andhra Pradesh. By leveraging publicly available satellite imagery and the CoastSat tool, the study provides valuable insights into the long-term dynamics of beach. https://www.ijcoe.org/article_201262.html Over the last few decades, excessive production of municipal wastes and inattention to waste management in the coastal countries of the Caspian Sea has led to the disposal of large amounts of waste into this closed basin. So , the global problem of marine debris is becoming a major challenge there too. Floating debris transports along the southern coasts of the Caspian Sea are investigated by developing a hydrodynamic model . The direct impacts of the wind and waves on the floating debris were ignored and only wind and wave-driven currents in the coastal zone were considered. The results show that floating debris entering the sea at the mouth of the Babolrood River tends to move eastward towards the Gorgan Bay. However, after a year , our results show that litters reach the northern part of the southern basin and trap in the gyres of the middle Caspian Sea . https://www.ijcoe.org/article_201266.html Ports are considered as links of connections in logistics and supply chain. They have always been the main sources of risk occurrence in maritime trade and transport. The majority of the risk elements prone to happen in ports are sourced from accidents and injuries that are directly or indirectly associated with human interception, complexity of technology, development plans and the agility of operations in ports. This study aims to identify and prioritize risks associated with accidents and injuries related to loading and discharging operations of container terminals. This study is considered as an applied and qualitative-quantitative research in aims and nature and a quantitative, qualitative and mixed research based on the nature of the data analyzed. About 36 accidents and injuries considered as affecting risk attributes were identified in the majority of container terminals in Middle East. The study has been conducted over the past ten years surveillance, amongst which, 15 sub-attributes were determined and classified under seven main criteria. The risk factors were identified and analyzed through a panel of Delphi members comprising of twenty experts and operating managers of the container terminals. The problem is developed and analyzed throughout of the study using the application of the Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy Delphi Method (FDM). https://www.ijcoe.org/article_203043.html A novel numerical procedure for optimization of prefabricated vertical drains (PVDs) depth and spacing under surcharge preloading is proposed. A case history is presented and verified and then the settlement, lateral displacement curves for different depth of installations that had lengths greater and smaller than the installation length in verified case, was modeled using finite element method (FEM). Based on the resultant settlement curves, two lengths were chosen that were used for a new model with “one and between” configuration. Despite a 17 percent reduction in PVDs installation, the overall system efficiency has been raised by 12 to 15 percent based on time. By applying this new method, the time needed for target settlement has decreased considerably, which in this case study was 115 days. As a result of greater depth of installation in comparison to common methods, the uneven settlement potential would decrease. The new proposed method has the potential to be substituted for the common method especially for situations where soil layers with high compressibility index exist underneath. The proposed FEM approach can be used for determination of optimum PVDs depth and spacing along with existing analytical and empirical solutions to attain economical and more efficient designs. https://www.ijcoe.org/article_203671.html Plastic is considered the main component of waste and sometimes accumulates on beaches. The studied stations are located in the coastal areas, approximately 35 km long in the Caspian Sea in Gilan province, Iran. This study aims to quantitatively and qualitatively investigate the presence of microplastics and their combined impact with heavy metals in the environment (water and sediment) as well as in aquatic organisms (specifically Gammarus) within the southwestern area of the Caspian Sea. The results of this research have shown that the highest average concentration of microplastics was found in the water environment samples from the 4th station (13400±658 pieces per liter), while the lowest average concentrations were recorded in the first and fifth stations (5200±370) and (5600±357) pieces per liter, respectively. Microplastics in the form of purple fragments in the size of 0.5 to 1 mm with a magnification of 40 are the most abundant. Heavy metals, notably copper and chromium, have been identified in Gammarus specimens. Additionally, polymers were detected in both water and Gammarus samples, potentially originating from fishing nets and general waste in the area. The presence of microplastics in study stations has increased the concentration of heavy metals in Gammarus and the water environment. The ANOVA test also showed that there is a direct and significant relationship at the 1% level between the concentration of heavy metals and microplastics. These results indicate the mutual and important synergistic effects between microplastics and heavy metals on the marine environment of the Caspian region. https://www.ijcoe.org/article_203823.html Depending on some factors like material, design, and magnitude of the impact, impact loading can have significant effects on various structures. For example, the effects of impact loading on marine structures are significant. It can be caused to structural damage, fatigue, corrosion, material degradation, and many other problems. Wave action, vessel collisions, and underwater explosions are the factors that can all contribute to impact loading. Cyclic impact loading resulting from the waves on offshore structures reduces the life of structures in the elastic area. In this study, as a comprehensive experimental investigation considering four mix designs, 64 rectangular composite panels were made with 100 mm2 area and 30-, 45-, 60-, and 75-mm thickness and tested by impact loading. Tensile, compressive, and flexural loading were done on all specimens. Steel fibers with 0, 0.25, 0.5, and 0.75 percent and 25 m of length were utilized to make the concrete composites. A hammer with 180 kg weight and 7500 J power was dropped on specimens for impact loading with a drop hammer test machine (DH-TM). Specimens were dynamically loaded by drop test from a 60 cm height. The composition of steel fibers and expanded metal sheets with each other significantly increases energy absorption. Moreover, the initial peak force increases, while crushing length and specimen’s deformation reduces. Models based on two well-known techniques artificial neural networks (ANN) and adaptive network-based fuzzy inference systems (ANFIS) have been developed. The performances of both techniques were compared and finally, the most appropriate one for predicting new data is introduced. https://www.ijcoe.org/article_215305.html The excessive energy consumption in buildings and the associated costs for maintaining thermal comfort necessitate the implementation of effective alternatives to reduce energy demand. Natural ventilation is one of the most efficient solutions, utilizing air circulation within the environment, offering a sustainable and cost-free method. This research aims to analyze the application of natural ventilation in industrial buildings, with the Ghovam-ol-Saltaneh Tea Factory selected as a case study. The study evaluates the performance of an atrium and a solar chimney as potential strategies for achieving thermal comfort in the given environment. The research employs a descriptive-analytical method, gathering data through both library resources and computer simulations using DesignBuilder software to assess thermal comfort conditions for three atrium and solar chimney models during the hottest week of the year (July 21 to July 27). The selected models are subsequently subjected to internal and external CFD (Computational Fluid Dynamics) analysis, allowing the identification of the best-performing configurations for optimizing natural ventilation. Based on the research findings, annual electricity consumption at the site was reduced by 42%, thanks to the incorporation of the atrium and solar chimney, indicating their potential as viable alternatives to conventional energy sources (electricity) in providing thermal comfort. https://www.ijcoe.org/article_216633.html This study investigated thermal and cold stress in the southern Caspian Sea. For this purpose, climate data from 11 synoptic stations from 1993 to 2022 were analyzed using the Rayman model and the SET, PET, and PMV thermal indices. These indices were calculated based on five climatic elements: mean temperature, water vapor pressure, relative humidity, cloudiness, and wind speed. The results showed that the thermal stress conditions of the stations are significantly affected by season and geographical location. In the cold months of the year, the western stations in the region face more severe cold stress, while in the warm months, the eastern stations experience more heat stress. In particular, the PMV index showed that the Gonbad-Kavos station in the eastern Caspian may experience heat stress even in the cold months. The PET index also confirmed these regional differences, with heat stress dominating the eastern Caspian and cold stress more significant in the western Caspian. The SET index also provided similar results, with the number of stations with thermal comfort increasing in summer and extreme cold prevailing in winter. This study showed that the eastern regions of the Caspian are more sensitive to heat stress and the western regions are more prone to cold stress. These findings can be used for climate planning, improving biological conditions, managing agricultural resources, and reducing damages related to climate stress. https://www.ijcoe.org/article_236346.html Hybrid renewable energy systems are regarded as an effective solution to address energy security and environmental challenges. Wave energy is a prominent clean energy source that has attracted significant attention due to its high reliability. The adoption of electric and hydrogen vehicles in place of traditional gasoline vehicles is recognized as a sustainable solution for environmental preservation. This study simulates the power and energy supply of a car charging station at Chabahar Port using hybrid renewable energy systems, incorporating wave energy converters (WECs) specifically AquaBuOY, OWC, and CETO, alongside photovoltaic panels and wind turbines in the modelling. A range of configurations incorporating the three categories of wave energy converters was assessed. The disconnection from the electrical grid and the elimination of fossil fuel reliance led to the total elimination of greenhouse gas emissions. Among the various configurations, those that incorporated all three energy generation sources exhibited superior economic efficiency compared to arrangements that utilised only two sources, specifically wave energy converters in conjunction with wind turbines or photovoltaic panels. The most cost-effective hybrid system was the PV/WT/AquabuOY configuration, which attained a Levelized Cost of Energy (LCOE) of $0.375 per kWh. The Net Present Cost of this system is approximately $0.700 million less than that of the next most favourable alternative. The PV/WT/CETO configuration was the least economical, exhibiting an LCOE of 0.477 $/kWh. The techno-economic analysis of wave energy converters revealed that although CETO incurs a substantially higher cost, it is essential to the overall system, providing approximately 14% of the total energy demand. Notwithstanding its high expense, CETO has a LCOE of $0.769 $/kWh, which is more advantageous than the LCOEs of AquabuOY and OWC, noted at 0.815 and 1.17 $/kWh, respectively. This indicates that CETO is appropriately adapted to the wave conditions in the study area. https://www.ijcoe.org/article_236347.html This study has formulated a mixed integer linear programming (MILP) mathematical model for continuous and dynamic multiple-quay berth allocation problems (MQ-BAP) to minimize the total cost of activities. Some parameters of the problem are considered indeterministic to approach the optimum solution in reality assuming the indeterministic nature of ship activities and operations. Uncertainty of parameters has been assessed using a credibility-based fuzzy approach considering them triangular fuzzy parameters. Uncertainty and ambiguity of parameters may depend on some conditions, such as delayed arrival and berthing of ships and vessels in container terminals due to bad weather conditions, operator schedule errors, equipment failure, etc. An improved metaheuristic genetic algorithm (IMGA) optimization algorithm has been used to solve this real problem with large dimensions and complex solution time. The efficiency of the proposed algorithm has been compared and ensured by solving the model based on the metaheuristic Simulated Annealing (SA) algorithm. The proposed algorithm has a perfect performance in obtaining fast and good solutions in MQ-BAP in real dimensions. These computations show that the proposed indeterministic problem-solving based on the algorithms mentioned above can be one of the underlying factors in increasing the efficiency of container terminals, which is the main purpose and advantage of this study compared to the base model presented by Pablo Frojan et al. (2015) that is analyzed based on the deterministic data. https://www.ijcoe.org/article_245590.html High-tech industries technology industries that have superior technology and technical knowledge, innovation and creativity, attention to its definition and development, need to create a knowledge management system in such a way that the flow of knowledge required by the organization and individuals is effective and timely. By examining the main dimensions of human capital of Marine Agile Project-Oriented Organizations, law, indicators related to these dimensions and their relationship with each other; Relationship between human capital components in the human capital model of Marine Agile Project-Oriented Organizations We prioritized the dimensions and components presented. Considering that extensive research in such organizations has not been done so far; Therefore, the results of this research can be very useful for completing the circle of knowledge management and achieving the goals of knowledge flow in high-tech industries organizations, as well as making available and transferring the experiences of people working in this field, as well as saving time and reducing costs https://www.ijcoe.org/article_241336.html The strategic development of energy infrastructure along the Makran Subduction Zone (MSZ), particularly the Kooh Mobarak Terminal near the Strait of Hormuz, demands a rigorous transition from deterministic assessments to risk-informed frameworks. While the eastern MSZ has a well-documented seismic history, the western segment presents a critical latent threat due to strong inter-seismic coupling. This study introduces an integrated framework combining Probabilistic Tsunami Hazard Assessment (PTHA) with advanced time-frequency analysis to quantify multi-dimensional risks. Building upon high-resolution hydrodynamic simulations, site-specific "Hydrodynamic Design Envelopes" were derived to explicitly correlate wave height and current velocity. Results indicate that for the 975-year Maximum Credible Earthquake, the nearshore breakwater faces extreme compound loads, with wave heights approaching 3.0 m and velocities exceeding 2.3 m/s, necessitating a shift to hydrodynamic drag-based design criteria. Furthermore, spectral characterization using Welch’s method and Continuous Wavelet Transform (CWT) identifies dominant energy bands at 24–30 and ~64 minutes, providing vital geometric constraints to avoid destructive harbor resonance. Additionally, time-frequency analysis reveals a significant lag between initial arrival and peak energy flux, demonstrating that hazardous agitation persists for over 4 hours. These findings underscore the imperative of adopting a performance-based design philosophy that accounts for probabilistic exceedance, resonance avoidance, and extended operational exclusion windows. https://www.ijcoe.org/article_245594.html One of the methods that has appropriate accuracy, applicability and reliability and will be discussed in this study is the Bidirectional Energy Based Pushover (BEP) method. Because the capacity curve obtained from BEP is unique and the main parameters of the pusher (load pattern, control point and monitor point) cannot question the accuracy of this approach; because there is no need to select a point monitor to obtain the capacity curve and instead, all the monitor points must be displaced to calculate the energy absorbed in the pusher stage. This method has been evaluated in terms of accuracy and applicability in building structures. This is while the aim of this study is to extend this method to assess the seismic vulnerability of bridges with curvature in plan.After identifying and selecting the methods and models considered for each element, and considering the defined uncertainties, the proposed models are modeled in OpenSeesPy software to perform IDA analysis. In order of material behavior, concrete, steel, geometry and modeling details, boundary conditions are selected based on previous studies, and modeling is performed accordingly. In this paper evaluated the effects of radius of curvature on the seismic response of curved bridges. For 4-span bridges, the weak and strong earthquake errors increase with increasing radius of curvature. However, for 2-span and 3-span bridges, the curved bridge with a radius of 420 m in two spans and the curved bridge with a radius of 1000 m in three spans experienced lower average errors in very strong motions (84th percentile) than the other curves. This indicates that the effect of curvature on accuracy depends on the bridge configuration. The errors between the BEP curve and the accurate IDA vary depending on the earthquake magnitude (percentiles). Weaker and stronger earthquakes (84th and 16th percentiles) generally showed higher errors compared to moderate intensity (50th percentile). https://www.ijcoe.org/article_241334.html The Makran Subduction Zone (MSZ) represents a critical tsunamigenic structure in the northwestern Indian Ocean. While the historical seismicity of the eastern segment has been extensively studied following the 1945 earthquake, the hazard potential of the western segment, specifically its threat to strategic energy infrastructure near the Strait of Hormuz, remains poorly constrained. This study presents a high-resolution deterministic tsunami hazard assessment for the Kooh Mobarak coastal onshore developments and its associated marine facilities. Utilizing the ComMIT/MOST numerical model within a nested grid framework, twelve fault rupture scenarios ranging from Mw 8.0 to 9.0 were simulated across the western, central, and eastern Makran segments. The results challenge conventional hazard zonations, demonstrating that a rupture in the Western segment (Mw 8.9) generates wave heights (~2.8 m) and current velocities (>2.0 m/s) at the Kooh Mobarak area that are comparable to those of a worst-case Central Makran scenario (Mw 9.0). Furthermore, a sensitivity analysis regarding the initial tidal level reveals a critical hydrodynamic dichotomy: while increasing the water level to Mean High Water Springs (MHWS) slightly attenuates the pure tsunami amplitude due to reduced non-linear shoaling, it significantly elevates the Total Water Level, thereby expanding the inundation extent into backshore tidal creeks. These findings underscore the imperative of adopting a dual-criterion design approach that incorporates near-field western ruptures and compound tidal interactions to ensure the resilience of critical coastal structures. https://www.ijcoe.org/article_245595.html Vertical mixing is fundamental to thermohaline circulation, deep-water ventilation, and biogeochemical cycling in enclosed seas, yet its spatiotemporal variability remains poorly quantified. Using a validated 9-year (2010–2018) 3D ocean circulation model, we identify three distinct vertical mixing hotspots with unique physical drivers: (1) Deep Basin winter convection (December–March, Kh ≈ 0.01 m²/s), driven by surface cooling; (2) Eastern Slope upwelling/frontal hotspot (June–September, Kh ≈ 0.01 m²/s), where shear instability and internal wave breaking overcome strong stratification (N² ≈ 0.0005 s⁻²); and (3) Volga Shelf river plume hotspot (April–August, Kh ≈ 0.01–0.001 m²/s), driven by plume instabilities and bottom friction. From 2015 to 2018, winter mixed-layer depth decreased by 30–50 m and surface Kh declined by a factor of 2–3, consistent with recent interannual variability and strengthened stratification in the region. In contrast, deep Kh (100–200 m) showed a slight increase (typically 0.001 to 0.01 m²/s), indicating vertical decoupling. Nutrient flux estimates show the Eastern Slope sustains summer supply on the order of 10 to 100 μmol N m⁻² day⁻¹ (one to two orders of magnitude higher than the stratified interior ≈ 0.1 μmol N m⁻² day⁻¹), explaining persistent coastal productivity. Deep-water ventilation timescales exceed 2000 years below 300 m, highlighting extreme vulnerability to hypoxia in the isolated deep layers. As basin-scale winter convection weakens under warming, lateral-vertical exchange via slope mixing hotspots becomes increasingly critical. These findings provide a mechanistic framework for physical-biological coupling in enclosed basins and inform fisheries management and climate adaptation in the Caspian Sea and similar systems worldwide. https://www.ijcoe.org/article_245596.html The present research studies the impact of wave charactristics as well as the power take-off (PTO) damping on the hydrodynamic performance of a two-body floating point absorber (FPA) which sometimes called self-reacting point absorber (SRPA) or two-body wave energy converter (WEC) device. This type of WEC is designed for operation in the Gulf of Oman and its geometry is inspired from the famous reference model (RM3) which was developed at the National Renewable Energy Laboratory (NREL), United States. The numerical model was developed in the Siemens STAR-CCM+ software which solves the complete form of fluid governing equations. The parameters of the incident waves, was selected based on the previous researches on this region and PTO damping is specified based on the RM3 model design. The results show that changes in wave period and PTO damping significantly influence energy capture and converter efficiency. The results show that the absorbed power increases monotonically with wave height and reaches a maximum at a wave period of 6 s, indicating a clear resonant response of the two‑body WEC across all tested sea states. https://www.ijcoe.org/article_245597.html This study presents the development of a three-dimensional numerical model, the Persian Gulf Oceanic Model (ZSF974), designed to predict oceanographic parameters in the Persian Gulf, along with the results of its validation. The model is based on the primitive equations formulated in a spherical coordinate system with a sigma vertical coordinate. The model equations are solved numerically using the finite difference method: the Lax–Wendroff scheme for advective terms, the DuFort–Frankel scheme for diffusive terms, and the Matsuno scheme to control computational instabilities. The mesh employed is a modified Arakawa C grid. The model accommodates irregular bathymetry and supports variable resolution in both horizontal and vertical directions. Model accuracy was enhanced by optimizing the execution process and by properly applying Nihoul's (1977) theory on the wind-induced surface stress's effect on subsurface layers. After validating the model in idealized laboratory basins against established principles of physical oceanography and previous research, it was applied to the real-world environment of the Persian Gulf. Key results from the model's implementation include a counterclockwise water circulation, the presence of an amphidromic point, the dominance of tidal forces, and the influence of the Arvandrud and Mond rivers. Notably, this riverine impact is significant along the coasts of the United Arab Emirates. The model successfully simulates the general behavior of the oceanic environment in response to various forcing mechanisms. However, long-term simulations indicate that the open boundary conditions require modification and that real tidal forcing should be incorporated. Overall, the model shows significant potential for further development to yield more accurate simulations and robust conclusions. https://www.ijcoe.org/article_245598.html Cementitious materials used in coastal and offshore infrastructures are frequently subjected to aggressive acidic environments resulting from industrial discharge, marine pollution, and sulfur-based biochemical processes. This study examines the mechanical behavior and acid resistance of mortar incorporating lightweight expanded clay aggregate (LECA) as an environmentally sustainable partial replacement for natural sand, with the added benefit of internal curing. Four mortar mixtures containing 0%, 5%, 10%, and 15% LECA were prepared, water-cured for 28 days, and subsequently exposed to a sulfuric acid solution (pH 1.5) for up to 90 days to simulate severe acid attack. Compressive strength, flexural strength, mass loss, and strength–degradation correlations were evaluated. Results indicate that LECA replacement does not compromise initial mechanical performance, while the mixture containing 10% LECA exhibited the highest long-term durability under acid exposure, demonstrating reduced mass loss and significantly lower strength degradation compared to the control mix. The enhanced performance is attributed to the internal curing effect of LECA and its ability to mitigate microcracking in chemically aggressive environments. These findings highlight the potential of LECA-modified mortar as a sustainable and durable alternative for coastal and offshore structures subjected to acidic conditions. https://www.ijcoe.org/article_237102.html Accurate prediction of atmosphere–ocean conditions in coastal and offshore regions requires high-quality input data and reliable coupled atmosphere–ocean modeling. In this study, two datasets—FNL forecast data and GFS reanalysis data—were employed to evaluate the performance of atmospheric and wave models in reconstructing the conditions of Tropical Cyclone Asna (2024) over the northern Indian Ocean. The results showed that limitations in the quality of FNL forecast data led to an inadequate representation of the intensity and structure of surface winds, and this weakness was directly reflected in the WWIII wave model. Consequently, the simulated significant wave height (SWH) was underestimated compared with observational or reanalysis values, and the timing of the wave peaks exhibited delays and unrealistic fluctuations. In contrast, the GFS reanalysis data successfully reproduced the wave growth and decay processes as well as the spatiotemporal structure of the storm with higher accuracy. However, due to their retrospective nature, these data are not applicable for operational real-time forecasting.These findings clearly indicate that the lack of high-quality and up-to-date atmospheric input data is the main obstacle to producing accurate atmosphere–ocean forecasts in the target regions, and that relying solely on global operational datasets such as FNL or GFS cannot fully capture the dynamic and thermodynamic characteristics of tropical cyclones. Accordingly, the necessity of developing and implementing a native coupled atmosphere–ocean model at both global and regional scales is evident. Such a model, by integrating local observational data and advanced data assimilation techniques, can provide more accurate initial and boundary conditions and enable the production of forecasts with higher accuracy and reliability. Achieving this capability will be a fundamental step toward strengthening scientific and operational capacity in physical oceanography and will pave the way for applying modeling results to secondary marine and coastal activities such as crisis management, maritime safety, coastal infrastructure design, and the sustainable exploitation of marine resources. https://www.ijcoe.org/article_237103.html Article History:Received….Accepted ….Available online ….Background and Theoretical Framework: In recent decades, economic and trade diplomacy has emerged as a strategic instrument for states to expand their share of global trade. Iran, due to its unique geopolitical position and access to international waters, possesses significant potential in maritime trade development. However, challenges such as international sanctions, underdeveloped logistics infrastructure, and intense regional competition have hindered the full realization of this potential. Under these circumstances, the rule of international trade laws and regulations can play a critical role in facilitating trade relations, attracting foreign investment, and enhancing Iran’s credibility within the global economic system.Methodology: This study adopts a descriptive–analytical approach, relying on library resources and data from international organizations such as UNCTAD, IMO, and the World Bank. A comparative analysis has also been applied to examine the experiences of successful countries in maritime economic diplomacy, including the United Arab Emirates and Singapore.Findings: The findings indicate that the effective implementation of international trade laws and compliance with global standards can: Improve security and transparency in port and shipping activities; Facilitate Iran’s access to global markets; Enhance the competitiveness of Iranian ports against regional rivals; Attract foreign investment in maritime and logistics infrastructures.Conclusion: The study concludes that Iran’s maritime economic and trade diplomacy can only be effective if conducted within the framework of international trade regulations. Adherence to these rules not only prevents legal and political disputes but also builds trust among trade partners and foreign investors. Hence, the strategic integration of active economic diplomacy with the governance of international trade laws paves the way for the sustainable development of Iran’s maritime trade. https://www.ijcoe.org/article_237105.html This study conducts a sensitivity analysis of wave and current behavior during minor storms along the southern coast of the Caspian Sea, focusing on the port of Nowshahr, a significant maritime hub in northern Iran. Using MIKE21, a numerical modeling software, the analysis evaluates various parameters such as mesh size, angular divisions, bed roughness, and wave breaking coefficients. The numerical models were calibrated and validated by comparing their outputs with field measurements obtained during small storm events. Results indicate that certain parameters, such as computational grid size and wave breaking coefficients, significantly influence model accuracy, while others, such as angular divisions, have minimal impact. Wind data from ECMWF-ERA5 was used to simulate local conditions accurately. The findings provide insights into optimizing numerical model calibration for improved predictions of wave and current behavior, particularly under storm conditions, thereby supporting coastal engineering projects and enhancing understanding of marine hydrodynamics in this region. https://www.ijcoe.org/article_237121.html Rip currents, often appearing as mushroom-shaped features within the surf zone, are a primary cause of swimmer drownings along beaches worldwide. Due to their transient nature, the application of advanced remote sensing and computer vision techniques for localized detection of these phenomena significantly mitigates the limitations traditionally associated with their study. In addition to these methods, the emergence of machine learning and artificial intelligence (AI) techniques provides powerful tools for a more precise investigation of rip currents, offering substantial support to remote sensing approaches and enhancing the efficiency of coastal lifeguard operations on larger scales. This study aims to present a comprehensive review of the relevant literature from 2014 to 2023, evaluating both traditional and modern approaches to analyzing the behavior of these coastal currents. Particular emphasis is placed on examining the conducted studies, including details on the categorization of research objectives, comparison of various tools, and exploration of associated opportunities and challenges. https://www.ijcoe.org/article_237125.html Given the necessity of understanding coastal dynamics and predicting erosion in coastal areas, this research employs the Adaptive Neuro-Fuzzy Inference System as a machine learning model for predicting beach cusp spacing and subsequently optimizing coastal management. ANFIS has the advantage over other techniques to model the more complex nonlinear relationships involved in beach cusp formation. It learns from existing data, adapts to new information varying with coastal hydrodynamic conditions, and gives back to the user interpretability by showing underlying rules dictating cusp dynamics. This paper discusses implementing ANFIS to predict beach cusp spacing and examines its performance against a neural network. In this way, different ANFIS configurations were tested, and the effect of membership functions on the performance of the fuzzy system was investigated. The main outcomes of this research indicate that even though optimized Artificial Neural Network (ANN) models perform reasonably well for the upper beach face, the optimized ANFIS (trimf) model performs better in accuracy and stability for the middle and lower beach faces. This study effectively highlights the importance of selecting the optimal model tailored to each beach section's specific conditions and characteristics. https://www.ijcoe.org/article_237126.html ABSTRACTAccurate satellite–in-situ collocation remains a key source of uncertainty in quantitative retrievals of coastal water turbidity, particularly in shallow and optically complex environments. This study presents a systematic assessment of how spatial, temporal, and depth-related collocation choices influence the performance of commonly used Sentinel–2 reflectance-based indices for turbidity monitoring. Three indices—the Normalized Difference Turbidity Index (NDTI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Vegetation Index (NDVI)—were evaluated against an extensive in-situ dataset of CTD turbidity measurements aggregated into three near-surface depth layers (0–1 m, 1–2 m, and 2–3 m). Satellite–in-situ matching was conducted using spatial buffers ranging from 120 to 400 m, two processing resolutions (20 and 40 m), and a temporal matching window of up to ±48 h. Across all collocation scenarios, NDWI exhibited the strongest and most stable relationship with turbidity (FTU), with regression slopes and explained variance remaining consistent across depth layers, buffer sizes, and spatial resolutions. NDVI showed a weaker but coherent negative response, while NDTI demonstrated negligible predictive skill within the observed turbidity range. The limited sensitivity of retrieval performance to collocation parameter choices indicates that, for moderate turbidity conditions in shallow coastal waters, robust satellite-based estimates can be achieved without highly restrictive matching criteria. The proposed workflow provides a transferable and reproducible framework for evaluating satellite–in-situ collocation uncertainty and supports routine and operational coastal water-quality monitoring using Sentinel–2 data. https://www.ijcoe.org/article_237151.html The Mooring systems play a significant role in the hydrodynamic behaviour of the floating offshore platforms. This research examines the role of mooring systems in regulating the pitch motion of semi-submersible platforms, given their growing application in deep-water operations. Excessive platform movements can compromise structural stability and operational performance. To analyze platform motion, numerical simulations of the AmirKabir semi-submersible platform were conducted under various mooring configurations using nonlinear time-domain analysis. Two optimization approaches were employed: a numerical trial-and-error method and a genetic algorithm based on stochastic selection, both utilizing numerical modeling to define the fitness function. The predicted outcomes from the genetic algorithm align with those obtained from numerical methods in reducing platform pitch motion. Three mooring configurations derived from the genetic algorithm demonstrate an approximately 32% improvement over numerical models. The results indicate that combining catenary and taut mooring lines yields optimal behavior in controlling the pitch motion of semi-submersible platforms. https://www.ijcoe.org/article_237723.html Due to the expansion of industry and maritime transport, as well as the need for better use of coastal areas, in recent years, studies in this regard have been increased. Beach sandy soils (known also as blown sands), if exposed to the path of water flow, are washed away and do not show sufficient bearing capacity due to their uniform granulation and lack of adhesion. Soil improvement to increase its bearing capacity and enhance its geotechnical properties through new technologies such as nanomaterials has led to successful results in engineering. In this study, the effect of using nano clay on improving the geotechnical properties of beach sand has been evaluated and compared to other methods such as the use of cement and clay with high plasticity properties. The mixture designs used in this study were selected for nano clay 1, 2 and 3% by weight, cement 5, 7 and 9%, and adhesive clay with a combined ratio of 1:9, 1:6 and 1:3. The results indicate the positive impact of nano clay, when used alone, on improving the plasticity and resistance parameters and particularly the proper performance of this material combined with other materials in improving soil properties, so that soil density increased by 1.89 g/cm3 using nano clay 1%. Besides, using nano clay 3%, soil compressive strength increased by about 119 kPa. In this work, the nano clay-cement combined performance was also examined, which indicated an increase in specific weight up to 1.91 g/cm3 in the compaction section. https://www.ijcoe.org/article_238474.html The issue of frequency control and voltage control in the shipboard microgrid (SM) is of great importance. Due to the presence of load disturbances and disturbances caused by renewable energy sources (RES) in the SM, as well as the uncertainty of the parameters of this system, the frequency control and voltage control in this system will be more complicated. LFC and AVR are responsible for frequency control and voltage control in this system, respectively. In this paper, the DO-FOPID controller is designed in the structure of LFC and AVR by considering the effect of time delay in the microgrid. Also, the GWO is used to adjust the parameters of the proposed controller due to its fast convergence and simple structure. This controller provides more accurate adjustment for the shipboard microgrid due to having two different fractional order parts for each of the integrator and derivative parts of the FOPID controller, and it will also improve the performance of LFC and AVR against disturbances to the microgrid and uncertainties of the system parameters. Finally, it will improve the steady-state error caused by frequency and voltage deviations. In order to compare the proposed method, several scenarios have been simulated, and the proposed method has been compared with the 2DOF-PID(GOA) and FOPID controllers, and the results show the superiority of the proposed control method (DO-FOPID(GWO)) compared to other control methods. In fact, the control method has been able to improve the maximum frequency deviations and maximum voltage deviations caused by disturbances on the SM and uncertainties by 64% and 60%, respectively. https://www.ijcoe.org/article_240848.html Tropical cyclones over the North Indian Ocean, including the Bay of Bengal and the Arabian Sea, pose a large threat to the teeming and low-lying coastal areas. There has long been recognition of the need for a detailed understanding and representation of the spatiotemporal organization and characteristics of the cyclone tracks. This paper uses the International Best Track Archive for Climate Stewardship (IBTrACS) best-track dataset from 1980 through 2025, and utilizes a complex network approach in the representation of the tropical cyclone tracks over the North Indian Ocean. The domain has been divided into 2° x 2° boxes in terms of the latitude-longitude location, and the cyclones treated as a temporally ordered sequence of visits on the boxes. The resulting directed and weighted network has then been assessed using classical network statistical measures, namely the degree, strength, betweenness centrality, clustering coefficient, and the modular communities. The paper specifically aims to provide a conceptual framework in the representation and ultimate understanding of the organized cyclone tracks over the different seasons and multi-decadal periods in an unambiguous manner. The approach aims to present the first detailed and rigorous investigation within the complex network framework, and provides evidence and insights on the hub nodes and paths in the organized cyclones in the middle and northern regions and the northeast Arabian Sea continental shelf, and the changes in the connections in the Arabian Sea over the past decades. https://www.ijcoe.org/article_240884.html The Strait of Hormuz is a very important and strategic waterway between the Persian Gulf and the Sea of Oman. The importance of this region is high politically, militarily and economically. In order to exploit this area, it is necessary to fully understand its surface and subsurface waters in terms of oceanography. The investigations' findings reveal the presence of a permanent thermocline layer in the northern areas of the Oman Sea (adjacent to the Strait), leading to a reduction in sound wave propagation by over 25-30 m/s. In contrast, the Persian Gulf and the Strait of Hormuz experience the formation of a thermocline layer solely during the warm season, resulting in the creation of a weak sound channel near the seabed. It is important to highlight that across all surveyed regions, the speed of sound wave propagation is significantly influenced by temperature variations, and vertical structure of the water masses in the strait. https://www.ijcoe.org/article_241333.html The precise estimation of extreme water level fluctuations induced by storm surges constitutes a fundamental prerequisite for the reliable design of marine structures and effective coastal risk management. In this study, the hydrodynamic response of the Southern Caspian Sea coast to atmospheric forcing mechanisms is investigated using the advanced ADCIRC numerical model, employing the solution of Shallow Water Equations (SWE) over an unstructured finite element mesh. To conduct a rigorous spatial and parametric sensitivity analysis, simulations were executed under various wind field and atmospheric pressure scenarios across six strategic stations characterized by distinct morphological features, ranging from the shallow waters of Gomishan to the steep bathymetry of Astara. Quantitative results substantiate a distinct non-linear inverse correlation between the seabed depth gradient and surge amplitude; specifically, the southeastern coasts experience surge magnitudes of a higher order compared to the steep western coasts, attributed to the continental shelf geometry and the momentum trapping phenomenon. Furthermore, the decoupling of driving forces reveals that water level variations within the Caspian basin are predominantly governed by the wind shear stress vector and effective fetch, with the inverse barometric effect playing a secondary role. By elucidating the spatial heterogeneity of coastal risks—inundation hazards in the east versus wave impact loads in the west—the findings provide a novel framework for determining the Design Water Level (DWL) and calculating hydrodynamic loads on offshore piles and protective seawalls. https://www.ijcoe.org/article_245490.html The accurate prediction of extreme local precipitation is critical for effective coastal flood hazard modeling and risk mitigation, especially in topographically complex regions where coarse-scale atmospheric models fail to capture orographic effects. This research introduces a novel application of the Random Forest (RF) Machine Learning algorithm to statistically downscale daily precipitation data for the humid, mountainous coastal region of the Southern Caspian Sea (Gilan and Mazandaran provinces, Northern Iran). The methodology utilized high-resolution GPM-IMERG satellite data as the ground truth, trained against large-scale dynamic atmospheric predictors derived from ERA5 reanalysis data across multiple pressure levels (e.g., 500 hPa vorticity, MSLP, and high-resolution topography). The RF model was rigorously validated against independent station data and compared against traditional methods (SVM, KNN, GBR). The results demonstrated the superior performance of the RF framework, achieving an R^2 above 0.81 during unseen test periods against GPM data and significantly outperforming coarser ERA5 outputs at validation stations . The model’s ability to accurately resolve local intensity, particularly by prioritizing variables related to moisture convergence from the sea and orographic forcing, confirms its strength in capturing the physical mechanisms leading to heavy coastal rainfall events. This downscaled, high-resolution precipitation product directly addresses a key uncertainty in Marine Hazard assessments. The developed AI-driven framework provides a robust, supplementary tool for real-time operational forecasting, enabling water resource managers and civil engineers to enhance the accuracy of coastal flood warning systems and improve the resilience of coastal infrastructure.