Search Results (1,458)

Load spectrum enhancement is a pivotal accelerated fatigue testing methodology employed to substantially reduce test duration and associated costs. This technique operates by strategically elevating load amplitudes while ensuring the preservation of the original failure mechanism. In this study, a novel fatigue life prediction model for variable amplitude loading is developed by integrating the theories of Equivalent Initial Flaw Size (EIFS) and the Equivalent Plastic Zone (EPZ). This integrated approach explicitly accounts for both the small crack effect and load interaction effects, which are critical yet often oversimplified aspects of fatigue damage accumulation. The model is subsequently applied to quantitatively establish the relationship between the Load Enhancement Factor (LEF) and the test time or compression ratio. Finally, fatigue tests on typical 2A14 aluminum alloy structures under variable amplitude loading are conducted to validate the proposed model. The results demonstrate a significant life reduction with increasing LEF, achieving a remarkable test time reduction of over 50% at an LEF of 1.2. All experimental data fall within a scatter band of three, relative to the model prediction. Additionally, the predicted mean compression ratio exhibits approximate agreement with the experimental data, with errors within an acceptable range. This work provides a physically grounded and practically validated framework for implementing efficient and reliable load spectrum enhancement. 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

This study systematically investigates the velocity characteristics and coupling mechanisms of tunnel flow fields under the interactions of natural wind, traffic wind, mechanical ventilation, and structural factors (such as transverse passages and relative positions between vehicles and fans). Using CFD simulations combined with turbulence model analyses, the flow behaviors under different coupling scenarios are explored. The results show that: (1) Under natural wind conditions, transverse passages act as key pressure boundaries, reshaping the longitudinal wind speed distribution into a segmented structure of “disturbance zones (near passages) and stable zones (mid-regions)”, with disturbances near passages showing “amplitude enhancement and range contraction” as natural wind speed increases. (2) The coupling of natural wind and traffic wind (induced by moving vehicles) generates complex turbulent structures; vehicle motion forms typical flow patterns including stagnation zones, high-speed bypass flows, and wake vortices, while natural wind modulates the wake structure through momentum exchange, affecting pollutant dispersion. (3) When natural wind, traffic wind, and mechanical ventilation are coupled, the flow field is dominated by momentum superposition and competition; adjusting fan output can regulate coupling ranges and turbulence intensity, balancing energy efficiency and safety. (4) The relative positions of vehicles and fans significantly affect flow stability: forward positioning leads to synergistic momentum superposition with high stability, while reverse positioning induces strong turbulence, compressing jet effectiveness and increasing energy dissipation. This study reveals the intrinsic laws of tunnel flow field evolution under multi-factor coupling, providing theoretical support for optimizing tunnel ventilation system design and dynamic operation strategies. Full article

Background and Aims: Decreased cerebrovascular reactivity (CVR) in patients with significant internal carotid artery stenosis (ICAS ≥ 70%) is an independent risk factor for cerebral infarction. To evaluate CVR, changes in cerebral perfusion pressure and blood flow velocity (BFV) of the middle cerebral artery (MCA) can be estimated by CO₂- (hyperventilation—HV and breath-holding—BH) and pressure–flow-based (Common Carotid Artery Compression—CCC and Valsalva Maneuver—VM) stimuli. We used a multimodal approach to characterize CVR in patients before carotid endarterectomy (CEA). Methods: HV, BH, CCC, and VM tests were performed on 31, 26, and 34 patients. BFV of MCAs was monitored by transcranial Doppler, and continuous arterial blood pressure was registered non-invasively. CVR was compared between the operated significantly stenotic and the contralateral sides. Results: The extent of HV- and BH-induced CVR was similar, but the time to the lowest HV-induced BFV was shorter on the side with significant ICAS. The response to CCC was sensitive to hemodynamic asymmetry in the transient hyperemic response ratio and in the cumulative change in the (mean arterial blood pressure)/(mean BFV) ratio. In VM, the slope of BFV increased in the ascending (2b) phase, and the time to overshoot correlated with the side of the stenosis. Conclusions: These results suggest that in patients with significant ICAS, in addition to CO₂ reactivity measurements, a more complex estimation of CVR, by using hemodynamic tests (CCC and VM), should also be used to better quantify cerebral ischemic risk. Full article

Numerical simulations, unlike experimental studies, eliminate material and setup costs while significantly reducing testing time. In this study, a random distribution program for steel-recycled polyethylene terephthalate hybrid fiber recycled concrete (SRPRAC) was developed in Python (3.11), enabling direct generation in Abaqus. Mesoscopic simulation parameters were calibrated through debugging and sensitivity analysis. The simulations examined the compressive failure mode of SRPRAC and the influence of different factors. Results indicate that larger recycled coarse aggregate particle sizes intensify tensile and compressive damage in the interfacial transition zone between the coarse aggregate and mortar. Loading rate strongly affects outcomes, while smaller mesh sizes yield more stable results. Stronger boundary constraints at the top and bottom surfaces lead to higher peak stress, peak strain, and residual stress. Failure was mainly distributed within the specimen, forming a distinct X-shaped damage zone. Increasing fiber content reduced the equivalent plastic strain area above the compressive failure threshold, though the effect diminished beyond 1% total fiber volume. During initial loading, steel fibers carried higher tensile stresses, whereas recycled polyethylene terephthalate fibers (rPETF) contributed less. After peak load, tensile stress in rPETF increased significantly, complementing the gradual stress increase in steel fibers. The mesoscopic model effectively captured the stress–strain damage behavior of SRPRAC under compression. Full article

Introduction: Currently, static interbody cages are the gold standard for achieving solid arthrodesis in the spine, enhancing segmental stability, obtaining neuroforaminal decompression, and improving as well as maintaining segmental lordosis. It is well known that restoring sagittal balance and segmental lordosis is crucial for long-term outcomes in lumbar spine fusion. For some cases, expandable interbody cages are emerging as an alternative to static cages. This study aims to evaluate the radiographic outcomes and complications of standard open transforaminal lumbar interbody fusion (TLIF). Methods: A standard open TLIF procedure using expandable cages was performed at 1 to 3 levels in 71 patients (129 levels in total), with a follow-up of two years. All patients underwent radiological assessments preoperatively, immediately postoperatively, and at one and two years postoperatively. Radiological evaluation was conducted using standing lateral X-rays. Results: Segmental lordosis (SL) increased significantly from the preoperative value (9.0° ± 3.6°) to 24 months postoperatively (15.4° ± 3.0°), with improvements maintained throughout the 24-month follow-up period (p < 0.001). Similarly, anterior disc height (ADH), posterior disc height (PDH), and foraminal height (FH) each increased significantly from preoperative to immediate postoperative measurements, and these gains were maintained over the two-year follow-up (p < 0.001 each). Lumbar lordosis increased significantly from the preoperative value (41.9° ± 10.5°) to the immediate postoperative period (45.7° ± 10.8°); however, this improvement decreased slightly at the one- and two-year follow-ups. No revisions were required for cage-related complications. One patient experienced a surgical site infection, and two patients had mechanical complications (screw loosening and proximal junctional kyphosis). Conclusions: Expandable interbody cages enable excellent restoration and maintenance of disc height and segmental lordosis in a standard open TLIF procedures at two-year. Achieving these outcomes depends on several factors, including proper preparation of the vertebral endplates, accurate cage placement and expansion, posterior facet osteotomy, and the application of posterior compression prior to final fixation. These steps are essential to fully maximize the potential of expandable cage technology. Full article

Tight conglomerate reservoirs are characterized by dense lithology, significant compositional contrasts between cement and gravel, strong stress gravel content, strong heterogeneity, and uneven spatial distribution, which collectively result in low porosity, complex pore–throat structures, and low permeability. After hydraulic fracturing, the stress sensitivity of tight conglomerate reservoirs is jointly governed by the rock matrix and induced fractures. In this study, the Mahu tight conglomerate reservoir in the Xinjiang Oilfield was selected as the research target. Stress sensitivity experiments were conducted on conglomerate matrix cores and on cores with varying fracture conditions. After stress loading, the degrees of permeability damage of the matrix, through-fracture, double short-fracture, and microfracture cores were 41%, 69%, 93%, and 97%, respectively. The matrix exhibited moderate-to-weak stress sensitivity, the through-fracture cores showed moderate-to-strong stress sensitivity, while the double short-fracture and microfracture cores exhibited strong stress sensitivity. Experimental results indicate that when fractures are present, the stress sensitivity of the core is primarily controlled by fracture closure and matrix compression. As fracture development increases, core permeability is significantly enhanced; however, stress sensitivity also increases accordingly. Under net stress, gravel protrusions embed into fracture surfaces, reducing surface roughness, while irreversible alteration of fracture geometry becomes the dominant factor driving stress sensitivity in fractured cores. These findings provide a scientific basis for predicting stress-sensitivity-induced damage in tight conglomerate reservoirs. Full article

Background/Objectives: Brain tumors arise from abnormal, uncontrolled cell growth due to changes in the DNA. Magnetic Resonance Imaging (MRI) is vital for early diagnosis and treatment planning. Artificial intelligence (AI), especially deep learning, has shown strong potential in assisting radiologists with MRI analysis. However, many brain tumor classification models achieve high accuracy at the cost of large model sizes and slow inference, limiting their practicality for medical edge computing. In this work we introduce a new attention-guided classification model and explore how model parameters can be reduced without significantly impacting accuracy. Methods: We develop a shallow attention-guided convolutional neural network (ANSA_Ensemble) and evaluate its effectiveness using Monte Carlo simulations, ablation studies, cross-dataset generalization, and Grad-CAM-generated heatmaps. Several state-of-the-art model compression techniques are also applied to improve the efficiency of our classification pipeline. The model is evaluated on three open-source brain tumor datasets. Results: The proposed ANSA_Ensemble model achieves a best accuracy of 98.04% and an average accuracy of 96.69 ± 0.64% on the Cheng dataset, 95.16 ± 0.33% on the Bhuvaji dataset, and 95.20 ± 0.40% on the Sherif dataset. Conclusions: The performance of the proposed model is comparable to state-of-the-art methods. We find that the best tradeoff between accuracy and speed-up factor is consistently achieved using depthwise separable convolutions. The ablation study confirms the effectiveness of the introduced attention blocks and shows that model accuracy improves as the number of attention blocks increases. Our code is made publicly available. Full article

Video-based point cloud compression (V-PCC) is a 3D point cloud compression standard that first projects the point cloud from 3D space onto 2D space, thereby generating geometric and attribute videos, and then encodes the geometric and attribute videos using high-efficiency video coding (HEVC). In the whole coding process, the coding of geometric videos is extremely time-consuming, mainly because the division of geometric video coding units has high computational complexity. In order to effectively reduce the coding complexity of geometric videos in video-based point cloud compression, we propose a fast segmentation algorithm based on the occupancy type of coding units. First, the CUs are divided into three categories—unoccupied, partially occupied, and fully occupied—based on the occupancy graph. For unoccupied CUs, the segmentation is terminated immediately; for partially occupied CUs, a geometric visual perception factor is designed based on their spatial depth variation characteristics, thus realizing early depth range skipping based on visual sensitivity; and, for fully occupied CUs, a lightweight fully connected network is used to make the fast segmentation decision. The experimental results show that, under the full intra-frame configuration, this algorithm significantly reduces the coding time complexity while almost maintaining the coding quality; i.e., the BD rate of D1 and D2 only increases by an average of 0.11% and 0.28% under the total coding rate, where the geometric video coding time saving reaches up to 58.71% and the overall V-PCC coding time saving reaches up to 53.96%. Full article

14CrMoR steel, possessing excellent low-temperature impact toughness and corrosion resistance, is an important material for core equipment in the coal chemical industry. In this paper, 14CrMoR steel was subjected to single-pass compression tests at deformation temperatures ranging from 900 to 1150 °C and strain rates of 0.1, 1, 5, and 10 s⁻¹. The hot deformation behavior and constitutive relationship were investigated. The strain rate sensitivity factor m, power dissipation coefficient η, and instability parameter ξ were calculated, respectively. A power dissipation map was plotted, and a hot processing map was established. The results showed that the stress of 14CrMoR steel increased with the decrease in deformation temperature and the increase in strain rate. Dynamic recrystallization was likely to occur at high deformation temperatures and low strain rates. When the strain rate was 10 s⁻¹, in the temperature range of 900–950 °C, the power dissipation rate was the lowest. With the increase in temperature, the power dissipation rate rose, and the maximum power dissipation rate was reached in the temperature range of 1100–1150 °C. The research on the hot deformation behavior of 14CrMoR steel has important guiding significance for the design and optimization of the process. Full article

Traditional manufacturing methods struggle to incorporate complex internal configurations within structures, thus restricting the potential for enhancing the strength of offshore structures through internal design. However, the advent of 3D printing technology presents innovative solutions to this challenge. Previous research has investigated the use of 3D printing to integrate lattice-like structures within conventional frameworks to achieve lightweight designs. Building upon this foundation, this paper models an embedded structure and other marine structures subjected to similar loads using simplified models and conducts a thorough investigation into their mechanical properties. Specifically, it examines the effects of the 3D-printed infill structure, infill rate, and tilt angle of printed specimens on the mechanical properties of 3D-printed components. The goal is to identify the optimal parameter combinations that ensure structural strength while also achieving a lightweight design and a secondary lightweight design for the embedded structure. This paper concludes, from tensile, torsional, and compressive experiments, that honeycomb infill structures, with specimens printed at an inclination angle of 0°, exhibit superior performance across all properties. Additionally, the bonding between the layers of the printed parts is identified as a key factor influencing the tensile and torsional properties. While increasing the infill rate can significantly improve the overall mechanical properties of specimens, it also results in a corresponding reduction in the lightweighting index. Full article

Engine knock remains a critical limitation in spark-ignition engine design. Future hybrid powertrains employ downsized engines operating on Atkinson cycles, creating different knock conditions compared to modern naturally aspirated or turbocharged engines. At the same time, petroleum-based gasoline is increasingly being replaced by biofuels and electrofuels. This study evaluates knock behavior in projected hybrid engine architectures and examines the chemical composition of emerging fuel blends. The analysis shows that hybrid engines benefit from fuels with lower sensitivity, defined as the difference between the Research and Motor Octane Numbers. This is because the higher end-gas temperatures associated with the Atkinson cycle shift the value of K, which is an interpolation factor used to capture the relationship between fuel sensitivity and anti-knock performance. In conventional engines, K is negative, favoring fuels with higher sensitivity. In hybrid engines, the increased engine temperatures result in K becoming positive, favoring low-sensitivity fuels. Using low-sensitivity fuels allows hybrid engines to operate with higher geometric compression ratios and advanced thermodynamic cycles while reducing knock constraints. Biofuels and electrofuels can meet these requirements by producing paraffinic and naphthenic hydrocarbons with high octane quality and low sensitivity. These findings emphasize the need to align renewable fuel development with hybrid engine requirements to improve thermal efficiency, reduce emissions, and reduce reliance on energy-intensive refinery processes for octane enhancement. Full article

There is a growing global trend toward reducing the consumption of natural resources and newly produced construction materials by replacing them with secondary raw materials. Concrete derived from construction and demolition waste can be recycled multiple times and is considered environmentally sustainable. This study evaluates the feasibility of reinforcing weak subsoil using crushed recycled concrete. Concrete obtained from the demolition of residential buildings was crushed under laboratory conditions to produce material with grain sizes corresponding to sands, and mixtures were subsequently prepared containing up to 30% fine fraction. The case study focuses on circular wind turbine foundations supported by symmetrically arranged columns made of four different materials, located beneath the foundation slab. The analyzed subsoil is characterized by strong stratification, low bearing capacity, and high compressibility. The calculation results indicate that the bearing capacity conditions for all foundations were met within similar ranges of the safety factor for the given loads, both for low- and high-power turbines. However, foundation deformations increased with turbine size and bending moments, and were nearly twice as large for recycled aggregates compared to recycled concrete. Numerical simulations demonstrate that recycled aggregate without fine fraction, as well as with fine fraction, and recycled concrete can provide load-bearing performance comparable to conventional concrete under low loading conditions, while offering significant environmental benefits. Full article

The aim of the manuscript is to analyze the influence of the magnetic orientation of steel microfibers (length 13 mm, diameter 0.2 mm) on the mechanical properties and fracture propagation of cementitious composites. The series varied in terms of the volumetric content of the fibers, 0%, 1% and 2% (V_f), and the orientation variant, random (S) or magnetic (S-M, B = 80 mT). Three-point bending tests were performed with force-deflection curve (F-δ) registration. The flexural tensile strength (f_ct,fl), the flexural elastic modulus (E_f), the work of fracture up to a specified residual load level (W_f) and deflection level (W_f*), as well as the compressive strength (f_c) were determined. The improvement of the mechanical properties was noted for magnetically oriented fibers in reference to random arrangement (f_ct,fl: 90–133%; f_c: 12–34%; W_f*: 98–146%). The efficiency factor (η_X) was introduced to determine the change in property per fiber content unit, which enabled comparison regardless of the fiber dosage. As the higher η_X values were determined for 1% content (e.g., f_ct,fl equal to 133%/p.p for V_f = 1% and 45%/p.p for V_f = 2%), further increase in dosage was expected to cause reduced improvement. Different fracture mechanisms were noted for S and S-M composites by means of the Digital Image Correlation method. Full article

The rapid expansion of electric vehicles in high-altitude Andean cities, such as the Metropolitan District of Quito, Ecuador’s capital, presents unique challenges for electrical infrastructure planning, necessitating advanced methodologies that capture behavioral heterogeneity and mass synchronization effects in high-penetration scenarios. This study introduces a hybrid approach that combines agent-based modelling with Monte Carlo simulation and a TimescaleDB architecture project charging demand with quarter-hour resolution through 2040. The model calibration deployed real-world data from 764 charging points collected over 30 months, which generated 2.1 million charging sessions. A dynamic coincidence factor ($F_C=0.222+0.036\ast e^{(-0.0003n)}$) was incorporated, resulting in a 52% reduction in demand overestimation compared to traditional models. The results for the 2040 project show a peak demand of 255 MW (95% CI: 240–270 MW) and an annual consumption of 800 GWh. These findings reveal that non-optimized time-of-use tariffs can generate a critical “cliff effect,” increasing peak demand by 32%, whereas smart charging management with randomization reduces it by 18 ± 2.5%. Model validation yields a MAPE of 4.2 ± 0.8% and an RMSE of 12.3 MW. The TimescaleDB architecture demonstrated processing speeds of 2398.7 records/second and achieved 91% data compression. This methodology offers robust tools for urban energy planning and demand-side management policy optimization in high-altitude contexts, with the source code available to ensure reproducibility. Full article