Search Results (216)

Power boiler tubes are exposed to severe operating conditions that lead to wall thinning and material degradation. Reliable assessment of tube wall thickness is therefore essential for ensuring safe and efficient boiler operation. This exploratory laboratory study investigates the applicability of active thermography combined with analytical and machine learning (ML) approaches for non-contact wall thickness estimation in power boiler tubes. Experimental investigations were performed on a single boiler tube specimen with artificially introduced wall-thickness reductions. Thermal responses were recorded using an infrared camera under both heating and cooling excitation conditions. Based on the acquired thermographic data, analytical models and machine learning algorithms were developed to estimate tube wall thickness. The machine learning approach was implemented using Random Forest and Support Vector Regression models and compared with conventional analytical modeling techniques. For separately analyzed and relatively homogeneous measurement series, the machine learning models produced lower descriptive errors than the analytical models, with the estimated three-RMSE error envelope decreasing from 0.51 mm to 0.17 mm. However, when heating and cooling datasets were aggregated, the analytical models achieved lower root mean square error values and demonstrated greater stability than the machine learning methods. These findings indicate that model performance strongly depends on the size, characteristics, and homogeneity of the available training data. Owing to the limited number of independent measurement series, the reported results should be interpreted as a small-sample feasibility assessment rather than as evidence of the general superiority of machine learning modeling. The results support the potential of active thermography for non-contact assessment of boiler tube wall thickness under controlled laboratory conditions. Further validation using additional specimens, grouped cross-validation, and physics-based synthetic data is required before the methodology can be considered for industrial implementation. Full article

A CT-80 coiled tubing fractured at the gooseneck during retrieval after a 2.5 h treatment with 15% HCl under high-temperature bottom-hole conditions (196 °C). The failure was investigated by dimensional measurements, metallography, Vickers microhardness testing, SEM/EDS, and FT-IR spectroscopy. Pronounced corrosion asymmetry was observed. Cumulative external wall loss reached 1.196 mm, compared with 0.292 mm on the inner wall, while the wall loss attributed to the final operation was approximately twelve times greater externally than internally. These findings suggest two different exposure histories: predominantly uniform attack of the outer wall during backflow of spent, inhibitor-depleted acid, and localized pitting of the inner wall under incomplete inhibitor coverage. EDS mapping identified Sb-rich deposits around inner-wall pits. In combination with the relevant literature, this distribution is consistent with a possible Sb–Fe galvanic effect that may have promoted local anodic dissolution, although galvanic coupling was not measured directly. The FT-IR spectra were consistent with iron oxides/oxyhydroxides, carbonate-containing scale, sulfate-bearing products on the outer surface, and thin organic residues rather than a continuous inhibitor film. Microhardness increased from 229 HV1 in the new tubing to 243.4 HV1 at the fracture location; this increase may reflect limited hydrogen uptake together with service-induced strain hardening or residual stresses. Fractography showed necking and dimpled microvoid coalescence, supporting a predominantly ductile overload mechanism in the corrosion-thinned section. A limited contribution of hydrogen to ductility loss cannot be excluded because the hydrogen content was not quantified. Full article

The helicopter tail drive shaft is vulnerable to failure from projectile impacts during low-altitude flight. Stress wave-based inversion of impact parameters and quantitative damage assessment remain insufficiently explored. To address small-sample and nonlinear challenges, a framework based on stress wave characteristics and physics-guided hierarchical Gaussian process regression is proposed. Four key features, namely first-arrival wave trough amplitude, frequency standard deviation, ratio of low-frequency to high-frequency root mean square, and wavelet energy entropy, are extracted from transient signals to construct a hierarchical progressive architecture for damage mode discrimination, parameter inversion, and quantitative assessment. Perforation is identified using a wavelet energy entropy-based adaptive threshold. Incidence angle inversion is achieved by an adaptive composite kernel and Bayesian physical prior correction. Damage degree is assessed through residual learning guided by a physical prior surface mean function. Results show an incidence angle inversion root mean square error (RMSE) of 3.02°, with entry and exit hole equivalent failure area RMSEs of 13.32 mm² and 12.98 mm², respectively. The 95% prediction interval maintained reliable coverage across the validation samples. This framework provides a new method with both physical interpretability and uncertainty quantification for the assessment of impact damage in thin-walled tube structures. Full article

In micro-extrusion and direct ink writing, the nozzle outlet diameter is often used to estimate the deposited line width or free-filament diameter. However, highly loaded conductive silver pastes may exhibit pronounced extrusion swell after leaving the nozzle, resulting in a filament diameter larger than the nozzle inner diameter. To quantify this deviation, this study proposes a single-parameter semi-theoretical correction model based on radial force balance at the nozzle exit, integrating Herschel–Bulkley yield stress–shear-thinning rheology with a finite-deformation description. The exit radial stress is derived from pressure-driven circular tube flow, while the post-exit radial expansion is balanced against atmospheric constraint. A comprehensive correction force constant, C, is introduced to account for wall-induced energy dissipation, particle-structure rearrangement, residual elastic recovery, and model simplifications. After calibration using a transition-swelling nozzle, C was determined as 1.03 × 10⁻² N. The model was applied to six nozzle diameters and four nozzle length–pressure conditions. For Nozzles 1–4 with significant swelling, the mean absolute percentage error was 5.31%, while the overall error for all six nozzles was 11.84%, mainly due to overestimation for the nearly non-swelling Nozzle 6. For varying nozzle lengths, the error was 5.20%, and both experimental and predicted swell ratios decreased with increasing effective nozzle length. The model provides a semi-theoretical tool for estimating free-filament dimensions and analyzing nozzle-length effects, primarily under pronounced-swell conditions. Its predictive capability becomes limited as the swell ratio approaches unity, where additional corrections for wall slip, relaxation, and the zero-swell boundary are required. Full article

Thin-walled tubes and beams are widely adopted for their excellent stiffness-to-weight performance. When subjected to bending, their structural response is governed by cross-section deformation (in-plane warping) that classical beam theories neglect. This work proposes a method based on deformation modes aimed at predicting the deformation of the cross-section of thin-walled members subjected to pure bending. The objective is to capture the in-plane warping mechanisms that drive stiffness degradation and nonlinear moment–curvature behavior with a computationally light and physically interpretable model. The method represents the cross-section kinematics through a combination of a set of deformation modes and determines their amplitudes by minimizing the total potential energy under geometrically nonlinear kinematics of the tube. The approach comprehends large rotations, applies to both closed and open sections, and can be applied to a tube with a generic cross-section. Representative applications show that the model reproduces the progressive in-plane deformation of closed circular and U open tubes, yielding moment–curvature curves consistent with reference solutions. The proposed method offers a practical analytical reference for predicting cross-section deformation of tubes under a finite bending regime and provides a bridge between classical one-dimensional theories and high-fidelity shell formulations. Full article

This study presents an integrated experimental methodology to determine the forming and fracture limits of welded thin-walled steel tubes, with emphasis on weld-line effects and manufacturing-induced anisotropy. The methodology combines longitudinal and transverse uniaxial tensile tests, using specimens extracted from different positions relative to the weld line, with elastomer-based tube expansion tests. Digital Image Correlation, combined with time-dependent strain analysis, was used to identify the onset of localized necking, while local strain and thickness measurements near the fracture regions supported the determination of fracture limits. This experimental work covered strain paths in the principal strain space ranging from uniaxial tension to near plane-strain expansion within the investigated conditions, enabling the experimental determination of both the Forming Limit Curve and the Fracture Forming Line for the welded tube material. Results reveal a pronounced directional dependence of mechanical response and formability. Transverse specimens exhibited higher yield and ultimate tensile strengths but lower ductility, whereas longitudinal specimens showed greater elongation and strain-hardening capacity. Strain localization and fracture were governed by the combined effects of local thickness variations, weld heterogeneity, and manufacturing-induced anisotropy. In longitudinal specimens, fracture occurred preferentially along the weld line, while in transverse specimens it developed away from the weld region, indicating distinct failure mechanisms depending on the loading direction. These findings highlight the need to account for weld-related heterogeneity and manufacturing history when assessing the formability of welded thin-walled tubes. The proposed methodology provides valuable experimental data for improving failure prediction and supporting the design, simulation, and optimization of welded tubular components. Full article

Spacecraft are evolving toward larger scales and higher performance, enabling widespread application of sophisticated space structures such as space antennas and flexible solar arrays. Such structures may experience thermally induced vibration (TIV) due to the influence of sudden solar radiation heat flows when it enters and leaves the Earth’s shadow in orbit. This paper focuses on a space thin-walled tube structure as the test specimen, and conducts ground-based TIV experiments in a vacuum environment, comparing the results with numerical simulations. The numerical simulation results for various key parameters show good agreement with the experimental data. The relative errors of average temperature, quasi-static displacement, and vibration frequency are approximately 5%, while the relative error of vibration amplitude is around 10%. Leveraging the validated numerical model, this study further investigates the influence of gravity on the TIV of large space structures. The results indicate that the TIV response amplitude under orbital conditions is significantly larger than that obtained from ground-based experiments. Full article

This study investigates the effects of filament winding parameters (tension and mosaic pattern) on the mechanical performance of thin-walled fiber-reinforced polymer composite tubes under internal pressure. The pressure was generated through axial compression of an elastomeric insert, providing a controlled alternative to conventional hydrostatic burst testing. Tubes were manufactured with different combinations of winding tension (10–50 N) in the ±55° and hoop layers. Within the ±55° layer, several mosaic pattern configurations were tested. Structural responses were evaluated using pressure testing, Digital Image Correlation (DIC), and Scanning Electron Microscopy (SEM). 20 N was identified as the most efficient tension level, improving interlaminar integrity and increasing hoop tensile strength by approximately 8–13%. Specimens with a hoop layer failed abruptly by hoop-dominated brittle fracture, characterized by longitudinal splitting and fiber rupture in the circumferential direction. Among the investigated mosaic configurations, the 3/3 pattern demonstrated the most efficient structural response—the mean hoop tensile strength (1088 ± 43 MPa) was approximately 31–40% higher than that of the remaining configurations (722–798 MPa). Overall, the results indicate that both winding tension and mosaic pattern influence the failure pressure, with optimized configurations contributing to improved pressure resistance and structural consistency. Full article

To investigate the effect of crack geometry on tensile deformation and strain localization in X46 pipeline steel thin-walled tubes, uniaxial tensile tests were conducted on specimens containing prefabricated cracks with different sizes, types, and orientations, and full-field strain evolution was characterized by digital image correlation. The material exhibited a favorable strength-ductility balance, with an average yield strength of 324 MPa, an ultimate tensile strength of 553.5 MPa, and an elongation of 27%. Non-cracked specimens showed three deformation stages: uniform deformation, strain localization, and necking instability. In cracked specimens, strain localization initiated at the crack tips and expanded with increasing displacement. Larger cracks significantly intensified crack-tip strain concentration and enlarged the high-strain zone. Through-wall cracks caused stronger localization and earlier local instability than surface cracks because of the loss of wall continuity, whereas small surface cracks had a limited effect on the final localization path. Crack orientation also affected deformation behavior, and the 45° inclined crack produced the most severe X-shaped localization under combined normal and shear stresses. Full article

As a structural material characterised by low density, high strength, excellent corrosion resistance and recyclability, aluminium alloy tubes are finding increasingly widespread application in the construction sector. However, there is currently a lack of research on the prediction of the bearing capacity of aluminium alloy square tube columns. To investigate the failure behaviour of aluminium alloy square tube columns under axial and eccentric compression, this paper first designed 10 thin-walled aluminium alloy square tube column specimens with varying lengths, cross-sectional dimensions and wall thicknesses. Axial and eccentric compression tests were conducted, and the loading process and failure modes were analysed. Building on this, a hybrid load-bearing capacity prediction model combining Multi-Objective Particle Swarm Optimisation (MOPSO) with the Gaussian process regression (GPR) algorithm was proposed. This model is capable of automatically learning and capturing 236 sets of experimental data. Subsequently, using the established prediction model, the contributions of high-sensitivity parameters and cross-sectional influence parameters to the load-bearing capacity were determined. Based on the prediction results, a correction factor for the diameter-to-thickness ratio was introduced into the eccentric compression bearing capacity formula of the Chinese code to establish an improved calculation formula. Compared with the implicit formula provided by machine learning models, the explicit formula proposed in this paper is more suitable for practical engineering design. The results show that the prediction results agree well with the experimental results and can accurately predict the ultimate bearing capacity of aluminium alloy square columns. Compared with the bearing capacity calculation methods in existing codes, the proposed formula reduces the root mean square error (RMSE), mean absolute error (MAE) and coefficient of determination (R²) of the dataset by 70.91%, 70.85% and 64.27%, respectively, whilst increasing the coefficient of determination (R²) from 0.8107 to 0.9830 (a relative improvement of 21.25%). Full article

Tube boilers are extensively employed in oil and gas refineries, as well as in petroleum, energy, and power generation industries, where they serve critical functions in local steam-generation units and combined-cycle gas turbine (CCGT) plants. However, these boilers are prone to defects arising from waterside corrosion (e.g., thinning of U-bend tubes), fireside corrosion, and material degradation caused by stress or creeping. Among these issues, wall thinning of tube bends is particularly severe, as it results in localized metal loss, reduced structural integrity, and an elevated risk of tube rupture or failure under high-temperature and high-pressure operating conditions. Such failures can significantly compromise boiler safety and efficiency, potentially leading to forced outages, costly unplanned repairs, or catastrophic damage if not detected in time. The current condition-monitoring policy for U-bends relies on scheduled preventive maintenance and unscheduled corrective interventions. In practice, this involves randomly checking approximately 10–20% of the tubes through spot scanning, partial scanning, or full scanning, with repairs typically carried out only after an undetected failure occurs. Such maintenance strategies generally require plant shutdowns, making the process time-consuming, labor-intensive, and ultimately not cost-effective. This paper reviews existing solutions, technologies, and research addressing the problem, and introduces femtosecond laser micromachined fiber optic sensors as a transformative approach for real-time monitoring of wall thickness reduction in U-bend boiler tubes, thereby opening pathways for further research. Full article

Pelletizing is an effective way of converting abundant phosphate ore fines into usable feedstocks for yellow-phosphorus production. In this work, the oxidation-roasting behavior of siliceous–calcareous phosphate ore pellets and siliceous phosphate ore pellets was evaluated in a laboratory tube furnace. The consolidation mechanisms were revealed using optical microscopy, X-ray diffraction, scanning electron microscopy, and energy-dispersive spectroscopy. The results indicate that siliceous phosphate ore pellets exhibit superior oxidation-roasting performance relative to siliceous–calcareous phosphate ore pellets. After roasting, oxidized siliceous–calcareous phosphate ore pellets show a loose and porous framework with large pores, thin walls, and occasional surface cracking. The consolidation of siliceous–calcareous phosphate ore pellets is mainly governed by the recrystallization bonding of silicon–magnesium-bearing fluorapatite. In contrast, oxidized siliceous phosphate ore pellets display a denser microstructure and stronger intergranular bonding. The dominant bonding forms are the recrystallization bonding of silicon-bearing fluorapatite and solid-state bonding between silicon-bearing fluorapatite particles and quartz particles. Furthermore, carbonate gangue minerals are detrimental to strength development because CO₂ release during roasting promotes the development of interconnected porosity and defects, thereby reducing the compressive strength of oxidized phosphate ore pellets. Full article

When ground transportation is disrupted by natural disasters, airdropped rescue vehicles require energy-absorbing cushioning devices to prevent landing impact damage. Thin-walled circular tubes are preferred for their high energy absorption capacity and structural efficiency. However, to reduce platform force fluctuations and decrease residual stroke after compression, thereby avoiding unbalanced loading and ensuring post-landing mobility, slots are introduced into the tube wall, which renders the mean crushing force (MCF) difficult to predict accurately using conventional methods. To address this issue, this paper proposes a physics–data-driven method for predicting the energy absorption characteristics of slotted thin-walled circular tubes. The engineering scenario is introduced, followed by comparative validation via drop weight tests and impact simulations to obtain a sample set via design of experiments (DOE). A multi-layer perceptron (MLP) neural network then augments the samples to generate a dataset. Dimensional analysis yields candidate MCF prediction equations, whose forms and coefficients are determined via a physics–data-driven approach. Weighted graph encoding transforms the equation-solving problem into a graph optimization problem to reduce the computational complexity, and an improved differential evolution (DE) algorithm with a dual-adaptive mutation operator (DSADE) adjusts the parameters and accelerates convergence. The resulting MCF prediction formula, combined with drop test requirements as the optimization objective, achieves a simulation relative error below 5%. These parameters also satisfy engineering requirements in actual airdrop tests, confirming the method’s effectiveness in predicting the energy absorption characteristics of slotted thin-walled tubes. Full article

Due to high specific energy absorption, composite/metal hybrid multi-cell thin-walled tubes hold significant potential in the field of automotive passive safety. However, the material coupling effect enhancing SEA often elevated the initial peak crushing force, reducing crushing force efficiency and compromising occupant protection. To balance SEA and CFE, trigger holes were introduced as an induced deformation mechanism for hybrid tubes to reduce IPCF while preserving SEA, with the optimized perforated configuration yielding higher CFE than the non-perforated counterpart. A high-fidelity finite element model of the hybrid tube was developed and experimentally validated, and the influences of induced structural parameters on SEA and CFE were investigated. Given the strong nonlinear coupling between trigger parameters and crashworthiness, a multilayer perceptron surrogate model was constructed using 200 optimal Latin hypercube sampling samples (20 for validation). A Q-learning enhanced particle swarm optimization (QL-PSO) algorithm was adopted for optimization, with reinforcement learning dynamically adjusting PSO parameters to balance global exploration and local exploitation. Finite element simulations validated that the proposed method achieved a favorable SEA-CFE trade-off, with SEA and CFE improved by 12.02% and 16.39% respectively, outperforming reported configurations. Compared with standard PSO, QL-PSO exhibited superior search efficiency and inverse mapping accuracy, with 22% higher optimization efficiency and full compliance with inverse design performance targets. This study provided valuable guidance for the design of thin-walled energy-absorbing structures in multi-material vehicle bodies. Full article

Red clover (Trifolium pratense L.) is a crop used as a forage that possesses an exceptional nutritional profile and digestibility. Unfortunately, this crop has low seed yield. Within the framework of the “Legume Generation” EC-funded project, our team aimed to investigate the role of foliar boron application on pollen viability and pollen tube development, and to assess its overall effect on red clover cultivation. Plants of six commercial diploid red clover cultivars, Nika 11, Sofia 52, AberClaret, Milvus, Global, and S123, were field-grown and boron-treated by spraying with the commercial product “Lebasol”, 11% active water-soluble boron. To reach our purpose, the transcript levels of genes related to flower, pollen, and pollen tube development and boron transport were measured by qRT-PCR; pollen grain viability and count were assessed microscopically. For this research, eight genes were selected: Auxin Response factor (TprARF17); TprAPETALA3; Walls are thin (TprWAT1 and TprWAT2); NIPs genes (Nodulin Intrinsic Protein) TprNIP4;2, TprNIP7;1, TprNIP5;1, and TprNIP6;1. Additionally, total nitrogen content in leaves detached from field-grown boron-treated and untreated plants was assessed and compared with the expression levels of two TprNIP5;1 and TprNIP6;1 transporters. The fresh and dry biomass weight from the first and second cuts was evaluated, as well as the seed collected from the red clover plants. Seed germination percentage and vigor of seedlings were examined in vitro for both boron-treated and untreated groups of two specific cultivars. Collected data confirm that foliar application of boron affects pollen viability and plant development of red clover in the cultivation conditions of South East Europe. Full article