Search Results (462)

Fused deposition modelling/fused filament fabrication (FDM/FFF) enables rapid manufacturing of functional polymer components; however, the reliability of printed parts remains strongly governed by internal architecture, process-induced porosity, and exposure to service fluids. This study quantifies the combined influence of (i) infill pattern (linear, triangular, hexagonal) at 30% density, (ii) infill density (30%, 60%, 100%) for linear infill, and (iii) short-term lubricant exposure on the tensile and microstructural response of FDM-printed polyethylene terephthalate glycol-modified (PETG) and short-carbon-fibre-reinforced PETG (PETG+CF). Specimens were printed following ISO 527-2 and tensile-tested at 5 mm/min. Microstructural analysis coupled quantitative porosity with mechanical response, Young’s Modulus, and strain-to-break. At 30% density, PETG with hexagonal infill achieved the highest tensile strength (18.54 ± 0.67 MPa), exceeding linear (16.99 ± 0.52 MPa) and triangular (14.15 ± 0.70 MPa) patterns, while triangular and linear patterns exhibited higher Young’s Modulus, indicating topology-driven decoupling of stiffness and strength. Increasing linear infill density raised strength to 31.35 ± 0.33 MPa (PETG) and 38.90 ± 0.28 MPa (PETG+CF) at 100%, consistent with reduced porosity. Seven-day immersion in SAE 15W-40 mineral engine oil reduced PETG strength by ~17% while increasing deformation to failure, whereas PETG+CF showed only minor changes. Overall, the results demonstrate that architecture-aware design, supported by quantitative porosity descriptors, is essential for ensuring the reliable mechanical performance of FDM/FFF-printed PETG-based components exposed to service fluids. Full article

In this paper, aiming at the aging problem of rubber sealing strips in key parts of hydropower units under long-term load, this study proposes a quantitative aging-feature-extraction technique centered on the ratio of the short-axis length to the original diameter (b/D) of serviced rubber strips. Through a systematic approach combining theoretical analysis, numerical simulation, and measured data calculations, the research first derives from energy principles that the elastic modulus (E) and yield stress (σ_s) are key physical parameters characterizing rubber aging, reflecting the material’s energy storage capacity and irreversible deformation threshold, respectively. Based on this, a radial compression simulation model of rubber strips is established, focusing on the cross-sectional deformation laws under 25% and 30% compression ratios in serviced conditions. It is found that the short-axis diameter ratio b/D exhibits a significant linear relationship with the dimensionless yield stress (σ_s/E), and a quadratic relationship with the dimensionless unit-length reaction force (F/ED). Using measured data, fluororubber (FKM) and nitrile rubber (NBR) specimens after 17 years of service are selected for radial compression experiments to extract the elastic modulus. The calculated results are compared with elasticity modulus estimates based on hardness empirical formulas (Gent’s and Qi’s formulas), showing consistency, particularly with Qi’s formula for NBR. This method enables rapid and accurate assessment of rubber aging, demonstrating the effectiveness and practicality of using b/D as a feature parameter. The study provides a quantitative and convenient tool for condition monitoring and life prediction of industrial equipment seals, especially suitable for the operation and maintenance of rubber components in complex environments such as hydropower units. Full article

Thin-walled partition frame parts are key load-bearing components in aerospace structures. Machining deformation directly affects assembly accuracy and service reliability. During milling, the release of residual stress caused by material removal is one of the main factors leading to deformation of thin-walled parts. To address this problem, aluminum alloy thin-walled partition frame parts are taken as the research object. A machining accuracy control method based on stress-sensitive region analysis is proposed. Key machining accuracy is used as the constraint condition. The concepts of stress-sensitive regions and sensitive directions are introduced. A coupled analysis model of residual stress and machining deformation is established. Residual stress is applied to element meshes in a finite element analysis platform and released under a free state. The influence of residual stress in different regions on part deformation is qualitatively identified. The dominant deformation directions are also determined. Based on these results, the milling tool path is specifically optimized. Strategies are adopted to avoid highly stress-sensitive regions or to control residual stress release by region. Overall machining deformation is effectively reduced. Experimental results show that the optimized tool path significantly suppresses part deformation compared with the conventional tool path. The flatness of the bottom surface is improved by up to 25.33%. The proposed method provides a feasible approach for machining process optimization of aerospace thin-walled parts with high precision. Full article

Cloud detection in remote sensing imagery is a research hotspot in the field of image processing, and accurately detecting and segmenting cloud regions is crucial for improving the utilization efficiency of remote sensing data. However, standard convolutional neural networks face limitations in modeling the complex spatial structures of clouds. To address these challenges, this paper proposes a cloud detection method based on DDS-DeeplabV3+. First, a lightweight design of the Xception network is adopted to control model complexity, and part of its standard convolutional layers are replaced with Deformable Convolutional Networks (DCN), which enhances the capability of the model to capture geometric features of irregular cloud formations. Second, a Dual-Branch Collaborative Mechanism (DCM) that integrates global context modeling with local detail perception is designed to reconstruct the Atrous Spatial Pyramid Pooling (ASPP) module, thereby improving performance in handling complex scenes and fine boundary delineation. Finally, the SimAM (Simple, Parameter-Free Attention Module) is incorporated into the decoder module, enhancing thin cloud detection capability. Experimental results on the Landsat-8 and GF-1 datasets show that the proposed model achieves Mean Intersection over Union (MIoU) values of 92.61% and 94.04%, respectively, outperforming other comparative methods and demonstrating its superior performance in cloud detection tasks. Full article

Cellular structures are well-established in biological materials and are often mimicked in many kinds of structural designs applicable to engineering. This results from their lightweight designs and good mechanical properties. Cellular designs in nature have extremely complex configurations. As a result, the deformation behaviour models for bioinspired hollow parts based on these geometries, that are presently available in the literature, are limited in their capacity to provide detailed descriptions of the mechanisms resulting in deformation. Extensions to the existing deformation behaviour mechanisms of cellular parts are proposed in this paper. First, a general outlook on cellular designs is given. This is followed by a review of the commonly recognised two-stage stress–strain curve for cellular parts and its comparison with the new curve suggested in this paper, which incorporates suggestions more fully accounting for the deformation mechanisms of these structures. Further, analytical models that are available in the literature, outlining the behaviour of cellular parts, are highlighted, together with new models developed here for predicting failure of lattice structures based on the Tresca and von Mises criterion. Next follows a discussion of proposed strategies that could be adopted in deformation behaviour models for optimising the design of hollow structures to improve their mechanical properties. Finally, the anticipated challenges for and future insights into the incorporation of the cellular behaviour models suggested here, in cutting-edge structural design for additive manufacturing (AM), are highlighted. Full article

Thin-walled parts are widely used in the automotive manufacturing industry due to their lightweight characteristics and high structural efficiency. However, it is difficult to accurately measure machining errors in key regions due to the feature deformation. To improve the online measurement accuracy of complex thin-walled parts, a machining error measurement approach based on multi-constraint point cloud registration is proposed. To address the low overlap and complex geometric features among multi-segment measured point clouds, a point cloud stitching method based on hole boundary features is developed to acquire complete measured point clouds. Meanwhile, a point cloud surface extraction method based on normal neighborhood searching is developed to acquire model point clouds. Since different regions of thin-walled parts require different geometric tolerances, a registration model integrating multiple locating and assembly constraints is proposed to satisfy the requirements for optimal point cloud registration. A measurement system composed of a line-structured light sensor and a six-axis robotic arm is developed to validate the proposed method. Experimental results show that the proposed approach reduces the overall dimensional error of point cloud stitching by approximately 70–86% and decreases the point number deviation between upper and lower surfaces by more than 98%. Furthermore, the measurement accuracy in locating holes and key assembly regions is improved to 0.05 mm and 2 mm, representing improvements of approximately 96.3% and 23.9% compared with registration methods without multi-constraint conditions, and approximately 95.3% and 14.5% compared with commonly used multi-constraint registration methods. Full article

With unconventional oil–gas reservoir exploration and oil and gas theory development, more and more importance is attached to the wellbore integrity. The casing deformation and damage is an integral part of the wellbore integrity theory. In the shale gas block in southwestern China, the casing deformation is grave because of the nonuniform stress of the reservoir, posing a significant influence on the productivity and economic efficiency of the shale gas development. In order to clarify the causes and mechanisms of the casing deformation caused by the nonuniform stress, the author of this paper has established the mechanical properties mathematical model of the casing under the nonuniform load as well as the casing–cement ring–stratum assembly numerical model based on the data of in situ multi-arm well logger and reservoir geological characteristics. Such models are established to study the response pattern of the casing under the nonuniform creep ground stress of the shale gas reservoir. The study herein serves as a reference for the optimization of casing design and target-specific exploration technology adjustments and lays the foundation for promoting the cost-effective development of shale gas reservoirs. Full article

The Dead Sea (DS) region has experienced a sharp increase in sinkhole formation in recent years, posing environmental and infrastructure risks. The Geological Survey of Israel (GSI) employs Interferometric Synthetic Aperture Radar (InSAR) to monitor sinkhole activity and manually map land subsidence along the western shore of the DS. This process is both time-consuming and prone to human error. Automating detection with Deep Learning (DL) offers a transformative opportunity to enhance monitoring precision, scalability, and real-time decision-making. DL segmentation architectures such as UNet, Attention UNet, SAM, TransUNet, and SegFormer have shown effectiveness in learning geospatial deformation patterns in InSAR and related remote sensing data. This study provides a first comprehensive evaluation of a DL segmentation model applied to InSAR data for detecting land subsidence areas that occur as part of the sinkhole-formation process along the western shores of the DS. Unlike image-based tasks, our new model learns interferometric phase patterns that capture subtle ground deformations rather than direct visual features. As the ground truth in the supervised learning process, we use subsidence areas delineated on the phase maps by the GSI team over the years as part of the operational subsidence surveillance and monitoring activities. This unique data poses challenges for annotation, learning, and interpretability, making the dataset both non-trivial and valuable for advancing research in applied remote sensing and its application in the DS. We train the model across three partition schemes, each representing a different type and level of generalization, and introduce object-level metrics to assess its detection ability. Our results show that the model effectively identifies and generalizes subsidence areas in InSAR data across different setups and temporal conditions and shows promising potential for geographical generalization in previously unseen areas. Finally, large-scale subsidence trends are inferred by reconstructing smaller-scale patches and evaluated for different confidence thresholds. Full article

The processes occurring inside a spiral jet mill are significantly influenced by the flow conditions within the grinding chamber. As part of this work, an experimental 3D model of the grinding gas flow is successfully developed for the first time based on the results of PIV measurements. This model demonstrates the typical spiral vortex flow superimposed by the nozzle jets, as well as the characteristic comminution and classifying zones. In addition, the three-dimensional analysis of the nozzle jet enables the first experimental validation of the theoretical assumption proposed in the literature that the flow dynamics in this region can be described by Abramovich’s nozzle jet model. The vortex pair located on the back of the nozzle jet essentially contributes to the formation of the kidney-shaped flow cross-section of the nozzle jet. The two vortices are verified both by the flow dynamics based on the unloaded grinding gas flow and by observing the abrasion on the inner wall of the grinding chamber caused by the particle-loaded flow. Consequently, the experimental findings can be utilized to create a model of the deflected and deformed nozzle jet, thereby providing a profound understanding of the flow processes within a spiral jet mill, particularly in the region of the nozzle jets. Full article

This article presents the results of research on the possibility of extruding oxygen-free copper pipes in bridge dies. The possibility of continuous production of a finished product of any length with a uniformly deformed wall was analysed. One of the most important elements of the work was to determine the shape of the tool (die and bridge) that would allow durable connection of the material. Numerical studies conducted using the commercial computer programme FORGE^®NxT 2.1, including analysis of the distribution of material temperature and hydrostatic pressure in the welding zone of the bridge die affecting the copper joint during the manufacture of tubular profiles, confirmed the validity of the research issue. The results of the numerical studies were supplemented by laboratory tests, confirming the accuracy of the selected variant of the finished product manufacturing process. The process of bonding under conditions of two-part material compression was used for physical modelling of copper welding. The tests were conducted using the Gleeble 3800 metallurgical process simulator with the PocketJaw module. Based on the analysis of the obtained results, it was found that for tubes with a wall-thickness-to-inner-diameter ratio of 0.5, it is justified to use tools with a longer sizing section and welding chamber, as well as a larger mandrel generating-line angle within the welding chamber. Full article

The article is devoted to the issues of designing the exploitation of a seam deposit in the boundary areas of underground mines in terms of minimizing the risk of dynamic phenomena. Its main goal was to attempt to demonstrate the relationship between the method of extracting resources trapped in the boundary pillar and the magnitude of the induced seismicity of the rock mass accompanying this process. The substantive considerations concerned the single-wall model and were divided into two main parts—theoretical and verification. As part of the theoretical piece, based on model studies, a geomechanical assessment of the impact of the working face advance on changes in the stress–strain behaviour occurring in the burst-prone layer in terms of the possible loss of continuity of its original structure was carried out. The starting point for the key analyses were the results of numerical simulations based on the algorithms of S. Knothe and W. Budryk’s theories in combination with classical solutions of the mechanics of deformable bodies. Two variants of mining operations in a two-sided environment of goaf were considered, differing in the direction of progress, the degree of constraint of the start and end of the face advance, and mining circumstances in the vicinity of both sides of the advancing face. As part of the verification piece, the results of model analyses were related to an example polygon of a crossing longwall in one of the functioning, rockburst USCB hard coal mines. The scope of the research included a comparison of the experimentally indicated zones of occurrence of tremor-favourable effort processes in the roof of the seam with the actual location of the seismic phenomena foci recorded during the ongoing exploitation. The considerations included in the work formed the basis for formulating conclusions of a cognitive and applicable nature. Full article

There are significant differences in the deformation patterns of different parts of arch dams, and there is a common situation of periodic data loss. To accurately analyze the deformation behavior of arch dams, this paper proposes a safety warning and anomaly diagnosis method for arch dam deformation based on the separation of environmental variable effects in different partitions and a knowledge-driven approach. This method combines various techniques such as an optimized ISODATA clustering method, probabilistic principal component analysis (PPCA), square prediction error (SPE) norm control chart, and contribution chart. By defining data forms and rules, existing engineering specifications and experience are transformed into “knowledge” and applied to the operation and management of arch dams, achieving accurate monitoring of arch dam deformation status and timely diagnosis of outliers. Through monitoring data verification of horizontal displacement in a certain arch dam partition, the results show that this method can accurately identify deformation anomalies in the arch dam and effectively separate the influence of environmental variables and noise interference, providing strong support for the safe operation of the arch dam. Accurate deformation monitoring of arch dams is essential for ensuring structural safety and optimizing operational management. However, conventional early warning indicators and empirical models often fail to capture the spatial heterogeneity of deformation and the complex coupling between environmental variables and structural responses. To overcome these limitations, this study proposes a knowledge-driven safety early warning and anomaly diagnosis model for arch dam deformation, based on spatiotemporal clustering and partitioned environmental variable separation. The method integrates the optimized ISODATA clustering algorithm, probabilistic principal component analysis (PPCA), squared prediction error (SPE) control chart, and contribution chart to establish a comprehensive monitoring framework. The optimized ISODATA identifies deformation zones with similar mechanical behavior, PPCA separates environmental influences such as temperature and reservoir level from structural responses, and the SPE and contribution charts quantify abnormal variations and locate potential risk regions. Application of the proposed method to long-term deformation monitoring data demonstrates that the PPCA-based framework effectively separates environmental effects, improves the interpretability of zoned deformation characteristics, and enhances the accuracy and reliability of anomaly identification compared with conventional approaches. These findings indicate that the proposed knowledge-driven model provides a robust and interpretable framework for precise deformation safety evaluation of arch dams. Full article

When drilling inclined and horizontal sections, a significant part of the drill string is in a compressed state which leads to a loss of stability and longitudinal bending. Modeling of the stress–strain state (SSS) of the drill string (DS), including prediction of its stability loss, is carried out using modern software packages; the basis of the software’s mathematical apparatus and algorithms is represented by deterministic statically defined formulae and equations. At the same time, a number of factors such as the friction of the drill string against the borehole wall, the presence of tool joints, drill string dynamic operating conditions, and the uncertainty of the position of the borehole in space cast doubt on the accuracy of the calculations and the reliability of the predictive models. This paper attempts to refine the actual behavior of the drill string in critical and post-critical conditions. To study the influence of dynamic conditions in the well on changes in the SSS of the DS due to its buckling, the following initial data were used: a drill pipe with an outer diameter of 88.9 mm and tool joints causing pipe deflection under gravitational acceleration of 9.81 m/s² placed in a horizontal wellbore with a diameter of 152.4 mm; axial vibrations with an amplitude of variable force of 15–80 kN and a frequency of 1–35 Hz; lateral vibrations with an amplitude of variable impact of 0.5–1.5 g and a frequency of 1–35 Hz; and an increasing axial load of up to 500 kN. A series of experiments are conducted with or without friction of the drill string against the wellbore walls. The results of computational experiments indicate a stabilizing effect of friction forces. It should be noted that the distance between tool joints and their diametrical ratio to the borehole, taking into account gravitational acceleration, has a stabilizing effect due to the formation of additional contact force and bending stresses. It was established that drill string vibrations may either provide a stabilizing effect or lead to a loss of stability, depending on the combination of their frequency and vibration type, as well as the amplitude of variable loading. In the experiments without friction, the range of critical loads under vibration varied from 85 to >500 kN, compared to 268 kN as obtained in the reference experiment without vibrations. In the presence of friction, the range was 150 to >500 kN, while in the reference experiment without vibrations, no buckling was observed. Based on the results of this study, it is proposed to monitor the deformation rate of the string during loading as a criterion for identifying buckling in the DS stress–strain state monitoring system. Full article

The aim of this work was to investigate the evolution of the mechanical integrity of the selected offshore oil reservoir during its life cycle. The geomechanical stability of the reservoir formation, including the caprock and base rock, was investigated from the exploitation phase through waterflooding production to the final phase of enhanced oil recovery (EOR) with CO₂ injection. In this study, non-isothermal flow simulations were performed during the process of cold water and CO₂ injection into the oil reservoir as part of the secondary EOR method. The analysis of in situ stress was performed to improve quality of the geomechanical model. The continuous changes in elastic and thermal properties were taken into account. The stress–strain tensor was calculated to efficiently describe and analyze the geomechanical phenomena occurring in the reservoir as well as in the caprock and base rock. The integrity of the reservoir formation was then analyzed in detail with regard to potential reactivation or failure associated with plastic deformation. The consideration of poroelastic and thermoelastic effects made it possible to verify the development method of the selected oil reservoir with regard to water and CO₂ injection. The numerical method that was applied to describe the evolution of an offshore oil reservoir in the context of evaluating the geomechanical state has demonstrated its usefulness and effectiveness. Thermally induced stresses have been found to play a dominant role over poroelastic stresses in securing the geomechanical stability of the reservoir and the caprock during oil recovery enhanced by water and CO₂ injection. It was found that the injection of cold water or CO₂ in a supercritical state mostly affected horizontal stress components, and the change in vertical stress was negligible. The transition from the initial strike-slip regime to the normal faulting due to formation cooling was closely related to the observed failure zones in hybrid and tensile modes. It has been estimated that changes in the geomechanical state of the oil reservoir can increase the formation permeability by sixteen times (fracture reactivation) to as much as thirty-five times (tensile failure). Despite these events, the integrity of the overburden was maintained in the simulations, demonstrating the safety of enhanced oil recovery with CO₂ injection (EOR-CO₂) in the selected offshore oil reservoir. Full article

In this study, the thermal and structural behavior of battery module components produced from polymer-based composites was systematically evaluated using coupled Moldflow 2016 and ANSYS Fluent 2024 simulations. Three thermoplastics—metal-flake-reinforced PC+ABS (Polycarbonate/Acrylonitrile Butadiene Styrene), carbon-fiber-reinforced PEEK (Polyether Ether Ketone), and hybrid mineral-filled PP (Polypropylene)—were investigated as alternatives to conventional aluminum components. Moldflow simulations enabled the assessment of injection molding performance by determining injection pressure, volumetric shrinkage, warpage, residual stress, flow front temperature, and part weight. PEEK exhibited the best dimensional stability, with minimal warpage and shrinkage, while PP showed significant thermomechanical distortion, indicating poor resistance to thermally induced deformation. For thermal management, steady-state simulations were performed on a 1P3S pouch cell battery configuration using the NTGK/DCIR model under a constant heat load of 190 W. Material properties, including temperature-dependent thermal conductivity, density, and specific heat capacity, were defined based on validated databases. The results revealed that temperature distribution and Joule heat generation were strongly influenced by thermal conductivity. While aluminum exhibited the most favorable thermal dissipation, PC+ABS closely matched its electrical performance, with only a 1.3% lower average current magnitude. In contrast, PEEK and PP generated higher cell core temperatures (up to 20 K) due to limited heat conduction, although they had comparable current magnitudes imposed by the energy-conserving model. Overall, the findings indicate that reinforced thermoplastics, particularly PC+ABS, can serve as lightweight and cost-effective alternatives to aluminum in mid-range battery modules, providing similar electrical performance and thermal losses within acceptable limits. Full article