Lost circulation during drilling and cementing operations is a critical and costly technical challenge, particularly in complex reservoirs with fractured, vugular, and tectonically disturbed formations where conventional mitigation methods are often inadequate. This article presents a systematic analysis of current lost circulation control technologies, classifying them into tool-based and advanced chemical approaches. The analysis identifies a fundamental shortcoming: the lack of precise control over the activation and placement of blocking agents, resulting in dilution and ineffective fracture sealing. To address this, we developed and validated a novel class of chemically delayed, cross-linked polymer systems based on xanthan gum. Laboratory testing on simulated fractures demonstrated the formation of a resilient barrier capable of withstanding pressure differentials up to 8 MPa. Recognizing the inherent constraints of purely chemical activation in downhole environments, this research proposes a paradigm shift towards hydrodynamically-activated systems. The core scientific contribution is the establishment of a methodological framework for such systems, which are designed to remain inert during standard circulation but undergo rapid, targeted gelation triggered by high shear rates and localized heating directly within the thief zone. This is achieved through a dedicated downhole tool that creates the necessary hydrodynamic conditions. The paper concludes by defining the essential requirements for a specialized research test bench to model this process, a critical step in transitioning the technology from concept to field application. This work bridges the gap between laboratory validation and the development of the next generation of controllable, reliable lost circulation solutions.
This paper presents the results of a comprehensive geochemical investigation of core material, extracted bitumens, and gas condensates from the southwestern part of the Yenisei-Khatanga Regional Trough (Arctic region). The study aimed to evaluate the petroleum source potential of the investigated stratigraphic units, determine the type and thermal maturity of organic matter, and clarify its genetic relationships with hydrocarbons. The research was carried out using total organic carbon (TOC) determination, programmed pyrolysis (Rock-Eval analogue) with analysis of the S1 and S2 parameters, solvent extraction of bitumens, and biomarker analysis by gas chromatography-mass spectrometry (GC- MS). The obtained data revealed a wide range of TOC values and significant lithological and geochemical heterogeneity within the studied section. In several samples, elevated S1 values combined with low residual generative potential (S2) were identified, which is interpreted as evidence of advanced thermal transformation of organic matter and the presence of migrated hydrocarbons in certain intervals. Biomarker investigations enabled differentiation of genetic types of organic matter and revealed variations in depositional environments. The results refine current understanding of the petroleum source characteristics of the studied formations and may be applied in the interpretation of hydrocarbon genesis and in further petroleum geological investigations of the region.
This study investigates the design, processing, and optimization of electromagnetic wave-absorbing nano-coatings based on epoxy matrices reinforced with Al2O3, Fe2O3, and ZnO nanoparticles. The research focuses on understanding the key parameters influencing microwave absorption and developing multilayer structures capable of minimizing reflection loss over a broad frequency range. Nanoparticles with an average size of 10-100 nm were uniformly incorporated into epoxy resins, and the resulting composites were examined through FTIR, SEM, and vector network analysis. SEM results confirmed strong interfacial adhesion between the matrix and fillers, while FTIR spectra indicated no chemical incompatibility, demonstrating effective hydrogen bonding and stable network formation. Network analyzer measurements in the 8-14 GHz range showed reflection losses of-16.3 dB for Fe2O3, -12.8 dB for ZnO, and-18.3 dB for Al2O3, corresponding to radar absorption levels of 85%, 77%, and 88%, respectively. To enhance performance, an imitation-based optimization (ISO) algorithm was applied to determine the most efficient multilayer absorber architecture. The optimal configuration, a three-layer epoxy system combining Fe2O3, ZnO, and Al2O3 nanofillers, achieved a reflection loss of-45 dB, equivalent to approximately 94% microwave absorption. These results highlight the potential of ISO-guided design for engineering advanced radar-absorbing coatings.
A-517 steel is a low-alloy quench-tempered steel with high strength. This steel finds application in the shipbuilding, boiler, and marine industries. Weldability is generally one of the key factors to consider when selecting raw materials for the construction of an engineering structure. One criterion for weldability was the hardness of the weld and the surrounding regions. In this work, the AISI 420 martensitic stainless-steel cladded over the A-517 by GTAW. The cladded samples were prepared in three types of As-Weld, heat treatment at 200 and 300 degrees. Subsequently, several samples of the Austenitic stainless steel 430 cladded over the A-517 by GTAW were prepared in three types of As-Weld, heat treatment at 200 and 300 degrees for tensile testing and comparison with AISI 420. AISI 420 martensitic stainless-steel has a higher weldability than the A-517 steel. Analysis of the four butt-joint sections of the welded sheets was demonstrated Weldability in the cladded sample is improved compared to the not cladded sample. The results obtained from the pressure test show that the compressive strength has increased slightly. The welding distortion in different lines (A-G) for cladded sample was studied. Tension strength of sample cladded by martensitic stainless steel 420 and elongation of the A-517 sheet metal cladded by stainless steel austenite 430 were increased.
Integrating lean principles into the multi-mode resource-constrained project scheduling problem (MRCPSP) provides a structured approach to eliminate waste of resources. This study introduces a triobjective mixed-integer linear programming (MILP) model for an extended MRCPSP variant (LMRCPSP) aimed at minimizing project makespan, total cost, and waste of resources (WoR) including both renewable and non-renewable types while ensuring compliance with minimum quality standards. The model incorporates preemptive and crashable activities to improve scheduling flexibility. It also includes rework after activity execution to ensure project quality meets or exceeds the minimum acceptable standard. A real-world construction case study validates the proposed approach, and the AUGMECON2 algorithm is employed to generate Pareto-optimal solutions and explore trade-offs among objectives. A comparative analysis with Microsoft Project schedules, along with sensitivity analyses, further demonstrates the impact of excluding key contributions, confirming that neglecting preemption, rework, or waste reduction leads to higher costs, longer durations, and reduced quality. This underscores the practical value of the proposed framework. Finally, the conclusion and further directions are provided.
The article discusses the development and application of heavy kill fluids (HKF) for well completion and workover operations under conditions of abnormally high formation pressures (AHFP). Particular attention is given to salt-based compositions with densities of 1600, 1800, and 2000 kg/m3, which are designed for use in various climatic environments. Experimental studies were conducted to determine their rheological properties, pH, crystallization temperature, corrosion activity, and contraction behavior when mixed with water and other solutions. It was found that with increasing fluid density, the mass fraction of salts rises, pH decreases, and the corrosion rate at elevated temperatures increases, necessitating the use of corrosion inhibitors. All tested fluids exhibit low crystallization temperatures, which ensures their effective application in winter conditions. The contraction phenomenon-volume shrinkage upon mixing with water-was also identified and shown to depend on fluid density and salt concentration. The results obtained make it possible to optimize the composition of HKFs and improve the safety and cost-effectiveness of well completion and workover operations under AHFP conditions.
This article presents the results of an experimental and numerical study of the effect of pipe inclination on thermal and aerodynamic characteristics of finned bundles of air cooling devices (ACD). Two four-row staggered beams are compared: a horizontal one (Bundle I) and a beam with a slope of 6 degrees for 2-4 rows with an increased longitudinal pitch (Bundle II). It has been experimentally established that the beam tilt makes it possible to reduce its aerodynamic drag by 14% without significant deterioration in heat transfer, which is explained by a change in the flow structure and turbulence from the first horizontal row. Criterion equations for calculating heat transfer and hydraulic resistance of the studied beams were obtained. Additionally, numerical modeling in ANSYS Fluent has shown that magnetic-abrasive treatment of contact surfaces and fins, simulated by increasing heat transfer coefficients, leads to a decrease in the operating temperature of the structure by 5-7 degrees C, which indicates an increase in the efficiency of heat removal. We concluded that it is promising to use inclined layouts and surface quality improvement technologies to modernize ACD. doi: 10.5829/ije.2027.40.01a.15
Musculoskeletal disorders remain one of the leading occupational health concerns in agriculture, especially in physically demanding environments such as greenhouse cultivation. This study evaluates the ergonomic risks associated with 15 tasks involved in the complete cultivation cycle of vine tomatoes in Almeria, Spain, using two complementary approaches: the Rapid Upper Limb Assessment (RULA) method and a fuzzy logic-based inference system. The fuzzy model integrates six biomechanical input variables and enables both real-time evaluation and simulation of ergonomic scenarios. The results highlight critical postural loads in several tasks, with the manual digging of planting holes identified as the most hazardous. A semi-automatic pneumatic system was proposed and analyzed, showing a substantial reduction in ergonomic risk, validated by both RULA and fuzzy logic outputs. This confirms that fuzzy logic not only mirrors expert ergonomic evaluation but also allows the assessment of potential improvements introduced by technological interventions. The methodology offers a scalable, interpretable, and adaptable decision-support tool for improving worker safety and promoting sustainable agriculture.
This study proposes a multi-objective framework for optimizing urban shortest paths by simultaneously considering traffic congestion and air quality. The objective is to minimize a weighted combination of travel time and pollutant exposure, with binary decision variables representing route selection. Real-world air quality data (SO2, NO2, CO) were collected from IoT sensors on 500 vehicles and 50 fixed stations across Tehran, integrated with traffic data via spatio-temporal synchronization using inverse distance weighting and 500m grid mapping. The transportation network was extracted from OpenStreetMap (14,287 nodes, 32,456 edges). The Incremental C-means Adaptive Weights (ICAW) algorithm was applied for real-time clustering of congestion and pollution hotspots, with optimal clusters (c=5) determined via the elbow method. Route optimization was performed using a hybrid Genetic Algorithm (population=200, tournament selection) with adaptive edge weights updated dynamically. The framework was evaluated across three pollution scenarios with 100 routing instances per scenario. Results demonstrate statistically significant improvements (p<0.01): pollutant exposure reduced by 18.7% (S1: good downtown air), 23.4% (S2: moderate pollution), and 31.6% (S3: severe pollution), with travel time reductions of 12.4%, 10.8%, and 8.9%, while distance increased by only 3.2-6.9%. Comparative analysis shows ICAW-GA achieves 28% lower computational time than NSGA-II and 42% faster convergence than PSO. The framework successfully balances transportation efficiency and environmental sustainability, providing real-time adaptive routing suitable for smart city deployment.
This study presents a dynamic-probabilistic framework for analyzing the behavior of individual members of a fixed offshore platform located in the South Pars field, utilizing the First-Order Reliability Method (FORM) and Importance Sampling (IS) to evaluate the reliability index and determine the required level of strengthening. The 100-year environmental loads-including waves with a maximum height of 12 m, wind with a speed of 36.7 m/s, and current with a velocity of 1.20 m/s-were modeled. A 20-minute time-history analysis with a 0.25-second time step was performed, and 16 representative members were examined under axial forces and bending moments. Probabilistic distributions including Lognormal, Weibull, and Normal were assigned to the environmental loads and material properties. The results indicated that the lowest reliability index occurs in the first mode with (3 = 4.21, increasing up to (3 = 9.00 in higher modes. The highest sensitivity of the Limit State Function (LSF) corresponds to the bending moment about they-axis, contributing over 48%, while axial force contributes only about 12%. Members located in the splash zone exhibited up to 25% reduction in (3 compared with deeper members. Increasing member thickness by 7% raised the reliability index to approximately (3 approximate to 5.10 and reduced the probability of failure by more than 35%. Increasing member diameter yielded only about 8-10% improvement. The difference between the FORM and IS results was less than 0.02, confirming the accuracy of the proposed model.
The dynamic behavior of high-slenderness-ratio vessels is critical for operational safety and effectiveness. This study presents a comprehensive numerical investigation into the seakeeping performance of the benchmark DTMB 5415 hull under varied physical and environmental conditions. A validated linear strip theory model, implemented in the TRIBON M3 environment, forms the basis of the analysis. Following successful validation against experimental and URANS data for heave and pitch motions in head seas, a systematic parametric study was conducted. The effects of wave encounter angle (90 degrees-180 degrees), vessel speed (Fr = 0.13-0.5), draft (4.5-7 m), and trim angle (+/- 1 degrees) on Response Amplitude Operators (RAOs) and added resistance were quantified. Furthermore, operational performance was assessed against seakeeping criteria (i.e., NORDFORSK, NATO STANAG 4154) in Sea States 5, 6, and 7. Results indicate that off-design loading conditions, particularly a trim by fore and a reduced draft, significantly amplify dynamic responses and added resistance. The seakeeping assessment reveals the vessel operates within limits in Sea State 5, but critical criteria for lateral accelerations, deck wetness, and slamming are approached or exceeded in higher sea states, especially at high speeds in beam-to-head seas.
A comprehensive nonlinear finite element analysis was conducted to investigate the rehabilitation of reinforced concrete beams that have suffered a significant loss of flexural strength. The proposed rehabilitation strategy integrates near-surface-mounted (NSM) embedded steel bars with externally bonded (EB) steel plate confinement, offering a cost-effective and mechanically reliable alternative to fiber-reinforced polymer (FRP)-based methods. Numerical simulations in ABAQUS assessed the effects of key parameters, including the number, length, and equivalent area of embedded steel bars, the confinement length of steel plates, the presence or absence of lap splices, the loading type, and the concrete compressive strength. Model validation against experimental data showed close agreement in ultimate load, deflection, and load-deflection response. Results demonstrated that NSM steel bars partially restored flexural capacity, while the addition of confinement steel plates substantially improved both strength recovery and deformability. Increased confinement length and continuous main reinforcement were especially effective, resulting in load capacities surpassing those of undamaged control beams. Repeated loading negatively impacted NSM-only systems, whereas NSM-EB rehabilitation achieved significant load recovery. Higher concrete compressive strength further enhanced load recovery but reduced deformation capacity. These findings establish that the combined application of embedded steel bars and confinement steel plates is an efficient repairing strategy for damaged RC beams.
Understanding online purchase behavior of Generation Z consumers is critical for e-commerce businesses due to this cohort's strong reliance on digital technologies. Although the Theory of Planned Behavior (TPB) has been widely used to explain consumer purchase intentions and behaviors, prior studies often rely on conventional statistical models or machine learning approaches with limited interpretability, resulting in a gap between predictive accuracy and behavioral explanation. To address this gap, this study proposes a data-driven and explainable framework for analyzing Generation Z online purchase behavior. TPB constructs attitude, subjective norm, and perceived behavioral control are operationalized as predictive features and evaluated using multiple machine learning models. Explainable artificial intelligence techniques, including SHAP and LIME, are employed to interpret model predictions and assess the influence of behavioral factors. Results show that machine learning models, particularly CatBoost, achieve superior predictive performance. Explainability analyses indicate that attitude and perceived behavioral control play a dominant role in shaping self-reported purchase behavior, while subjective norm has a supportive influence. The proposed framework provides actionable insights for targeted marketing and improved decision-making in online retail contexts.
The accurate prediction of the allowable bearing capacity (q(all)) for deep mat foundations, governed by a settlement criterion, is a critical yet complex challenge in geotechnical engineering. This study presents a robust predictive framework by integrating high-fidelity numerical modeling with machine learning. An extensive database of 5000 samples was generated using three-dimensional FLAC3D simulations employing the Hardening Soil model. Three machine learning algorithms-Random Forest, Support Vector Regression, and Gradient Boosting (GB)-were developed and compared. The GB model demonstrated exceptional predictive accuracy (R-2 = 0.9954), significantly outperforming a hierarchy of three traditional elasticity-based analytical methods. A subsequent sensitivity analysis using SHapley Additive exPlanations (SHAP) revealed that the model autonomously learned complex and physically meaningful geotechnical principles, including the inverse relationship between foundation width and the settlement-governed allowable pressure. This research validates the synergy between numerical simulations and machine learning, offering a highly accurate and interpretable tool that surpasses conventional methods for the detailed design of deep mat foundations.
Currently, three-dimensional printing (3DP) using direct ink writing (DIW), especially for biomaterials, is developing rapidly. However, in printed products, the shrinkage occurs, followed by cracking due to slow solidification. Therefore, an accelerated solidification process is required, which can be achieved by a curing process. The novelty of the study is the development of a new material composite and a modified 3DP DIW by adding UV light. The study aims to determine the optimal parameters and identify the error dimensions. New biomaterial consists of hydroxyapatite/HA (30% w/v) and Permanent ODS Resin A3/PORA3 (100% v/v). The printing parameters were nozzle diameter (0.6, 1.4, 2.2 mm), print speed (1, 20.5, 40 mm/s), layer height (0.1, 0.65, 1.2 mm), and distance from the nozzle (0.1, 0.3, 0.5 mm). Optimum process parameters were determined using the response surface method with Box-Behnken design, involving 27 experiments. The optimum product was in line and circular shape, whereas the error dimension was achieved with characterisation using Fourier transform infrared spectroscopy, scanning electron microscope, and energy dispersive X-ray. The results indicate that the optimum parameters of nozzle diameter, print speed, layer height, and nozzle distance are 2.2 mm, 32.52 mm, 1.2 mm, and 0.5 mm, with an error dimension of 3.08%. The morphology of the printed PORA3/HA composite is spherical, porous for HA and solid for PORA3, with compositions of C, O, and Ca found, while the HA and PO43-spectrum was confirmed. Thus, 3DP DIW light UV curing is recommended for use due to its dimensional accuracy in the printed product.
