Surface Damage Research Articles

Sand Production Prediction and Management Using a One-Dimensional Geomechanical Model: A Case Study in NahrUmr Formation, Subba Oil Field

Sand production in sandstone reservoirs is a complex problem for oil and gas companies. This problem can damage downhole equipment and surface production facilities. This paper presents a sand production case and quantifies sand risks for the NahrUmr formation located in Subbaoilfied.The risk of sanding or rock failure is commonly observed during production phases as well as drilling operations. A (1D) mechanical earth model was created using wireline log data and core data for estimating the formations mechanical properties.The extrapolation method is utilized for vertical stress prediction, whereas pore pressure and static Young’s modulus were calculated using Slowness Eaton method and John Fuller correlation respectively. The poro-elastic model was used to determine horizontal principal stresses and hydrocarbon intervals susceptible to sand production issues.The purpose of this study was achieved using Tech-Log software. Sand onset intervals are firstly predicted as an open hole using ten methods: Loading factor (LF), Critical drawdown pressure (CDDP), B-index, schlumberger (Sc), Elastic combination index (Ec-index), Interval Transit-Time (DTc), Total porosity method (PHIT), unconfined compressive strength (UCS), Shear modulus to bulk compressibility ratio (G/Cb), and shear failure method. Approximately ten methods refer to the same intervals that can produce sand. Secondly, sand depths were predicted by representing the well according to what actually existed as a cased hole by calculating the critical drawdown pressure (CDDP), which is calculated at various depletion rates (0%, 15%, 25%, and 35%) in order to measure the effect of reservoir pressure depletion on sand production. The results show that as the rock strength is increased, the amount of sand-free drawdown and depletion becomes larger. Also, a single-depth analysis was conducted for problem intervals, indicatg a sandwillproducefromdepth of 2527.7 m under certain conditions. Therefore, it is necessary to install sand control equipment in this well.

Design and Experimental Research of a Non-Destructive Detection Device for High-Precision Cylindrical Roller Dynamic Unbalance

Due to their small size and light mass, small precision cylindrical rollers present challenges in dynamic unbalance detection, including difficulties in measurement and the risk of surface damage. This paper proposes a non-destructive detection device for assessing the dynamic unbalance of small precision cylindrical rollers. The device utilizes an air flotation support method combined with resonance amplification to indirectly measure the dynamic unbalance. A dynamic model of the air flotation tooling-cylindrical roller vibration system was developed to explore the relationship between the vibration parameters of the air flotation tooling and the dynamic unbalance of the cylindrical roller. Modal analysis and harmonic response analysis were performed, revealing that the amplitude of the vibration system at resonance could be detected using the sensor. Additionally, modal testing was conducted to determine the natural frequency of the system. A non-destructive detection platform was constructed for testing the dynamic unbalance of cylindrical rollers. Microscopic observation of the roller surface before and after testing confirmed that the device successfully performs non-destructive detection of dynamic unbalance.

DCW-YOLO: An Improved Method for Surface Damage Detection of Wind Turbine Blades

Wind turbine blades (WTBs) are prone to damage from their working environment, including surface peeling and cracks. Early and effective detection of surface defects on WTBs can avoid complex and costly repairs and serious safety hazards. Traditional object detection methods have disadvantages of insufficient detection capabilities, extended model inference times, low recognition accuracy for small objects, and elongated strip defects within WTB datasets. In light of these challenges, a novel model named DCW-YOLO for surface damage detection of WTBs is proposed in this research, which leverages image data collected by unmanned aerial vehicles (UAVs) and the YOLOv8 algorithm for image analysis. Firstly, Dynamic Separable Convolution (DSConv) is introduced into the C2f module of YOLOv8, allowing the model to more effectively focus on the geometric structural details associated with damage on WTBs. Secondly, the upsampling method is replaced with the content-aware reassembly of features (CARAFE), which significantly minimizes the degradation of image characteristics throughout the upsampling process and boosts the network’s ability to extract features. Finally, the loss function is substituted with the WIoU (Wise-IoU) strategy. This strategy allows for a more accurate regression of the target bounding boxes and helps to improve the reliability in the localization of WTBs damages, especially for low-quality examples. This model demonstrates a notable superiority in surface damage detection of WTBs compared to the original YOLOv8n and has achieved a substantial improvement in the mAP@0.5 metric, rising from 91.4% to 93.8%. Furthermore, in the more rigorous mAP@0.5–0.95 metric, it has also seen an increase from 68.9% to 71.2%.

Surface Damage by Physical Cleans during Semiconductors Manufacturing

This paper investigates surface damage caused by physical cleaning processes during semiconductor manufacturing. The study focuses on various materials, including FDSOI wafers and polymer films, subjected to high-velocity sprays and cryogenic cleans. Thanks to the supplier process performances and quality control, FDSOI films do not present any specific concern linked with this failure mode. This latter can be observed on whatever films exposed to aggressive physical cleans and the wafers are cleverly used as a test vehicle to evidence surface defects with a revelation method using a wet etchant. It enables the detection of nano-cracks and other damages. Same defects are observed in bulk silicon wafers, and solutions exist to avoid these damages. Different spray types are compared, highlighting the impact of droplet energy distribution on surface integrity. Additionally, a direct characterization method using polymer films is developed to assess physical cleaning damage. The findings emphasize the importance of optimizing cleaning processes to balance defect removal efficiency and surface preservation. Emerging cleaning solutions like polymer coat and peel methods are also discussed for their potential to offer high cleaning performance with minimal surface damage.

Tinidazole mouth rinse for the treatment of oral lichen planus: an observational pilot study

BackgroundGiven the limited treatment options available for oral lichen planus (OLP), a study was undertaken to obtain preliminary information on the therapeutic efficacy of tinidazole mouth rinse in patients with OLP.MethodsA prospective, open-label pilot study was conducted to assess the efficacy of thrice-daily tinidazole mouth rinse for one week in OLP patients (n = 27). Reticulation/erythema/ulceration (REU) scores and visual analog scale (VAS) scores were used to measure lesions at baseline and after one week of treatment. Mucosal samples were collected, and the abundance of Fusobacterium nucleatum was quantified using RT-PCR. Statistical analysis using t-test, Wilcoxon signed rank test and Pearson correlation test.ResultsAfter treatment, VAS scores significantly decreased in both reticular (P = 0.03) and erosive OLP patients (P = 0.003). However, REU scores significantly decreased only in erosive OLP patients (P = 0.002). The relative abundance of Fusobacterium nucleatum on the damaged mucosa surface significantly decreased in all OLP patients (P = 0.01). In erosive OLP patients, the triamcinolone group showed a significantly greater improvement in VAS scores compared to the tinidazole group (P = 0.01). However, there was no statistically significant correlation between the relative abundance of Fusobacterium nucleatum and REU scores in OLP patients (r = 0.0754, P = 0.61).ConclusionTinidazole mouth rinse showed potential in reducing disease severity in OLP patients and was well-tolerated, suggesting its viability as a local therapeutic option. However, randomized controlled studies are warranted to confirm these preliminary findings.

Intraoperative cartilage analysis of the first carpometacarpal joint - comparison with conventional staging according to Eaton and Littler.

Osteoarthritis of the first carpometacarpal joint is a common pathology of the hand, which may show an increasing prevalence in Germany due to the demographic development. In recent years, not only the current gold standard - the resection arthroplasty of the thumb saddle joint - has been used, but also therapeutic thumb saddle joint arthroscopy. In addition to the patient's clinical complaints, radiographic diagnostics have been used to decide on treatment, although it has not been proven whether there is a correlation between imaging and clinical complaints. Between 2020 and 2022, 20 articular surfaces of the thumb saddle joint undergoing resection arthroplasty for symptomatic basal thumb osteoarthritis were prospectively examined, mapped and compared with preoperative conventional radiographs. The evaluation of the corresponding articular surfaces showed a higher cartilage destruction at the articular surfaces of the trapezium compared to the first metacarpal. No correlation was found between the stage of osteoarthritis and the Eaton-Littler classification. Overall, there is a patient-specific heterogeneity of the cartilage damage of the articular surface of the trapezium bone, as well in the metacarpal bone I base in relation to the radiographic diagnosis. Furthermore, an inhomogeneity of the radiographic stage of osteoarthritis of the carpometacarpal joint according to Eaton and Littler in relation to the intraoperatively assessed cartilage damage. The statistical significance of the surgically assessed cartilage damage in relation to the conventional radiographs could not be demonstrated. Thus, the treatment of symptomatic osteoarthritis of the carpometacarpal joint should primarily address the patient's individual complaints. The radiographic classification according to Eaton and Littler can be used as an additional factor to decide on the surgical procedure but should not delay the therapeutic treatment. III.

Impact of repetitive ELM transients on ITER divertor tungsten monoblock top surfaces

Abstract Owing to the high stored energy of ITER plasmas, the heat pulses due to uncontrolled Type I edge localized modes (ELMs) can be sufficient to melt the top surface of several poloidal rows of tungsten monoblocks in the divertor strike point regions. Coupled with the melt motion associated with tungsten in the strong tokamak magnetic fields, the resulting surface damage after even a comparatively small number of such repetitive transients may have a significant impact on long-term stationary power handling capability. The permissible numbers set important boundaries on operation and on the performance required from the plasma control system. Modelling is carried out with the recently updated MEMENTO melt dynamics code, which is tailored to tackle melt motion problems characterized by a vast spatio-temporal scale separation. The crucial role of coupling between surface deformation and shallow angle heat loading in aggravating melt damage is highlighted. As a consequence, the allowable operational space in terms of ELM-induced transient heat loads is history-dependent and once deformation has occurred, weaker heat loads, incapable of melting a pristine surface, can further extend the damage.

TSCB-Net: transformer-enhanced semantic segmentation of surface damage of concrete bridges

Concrete bridges are susceptible to surface damage such as water-corrosion, spalling, and rebar-corrosion, which can pose serious safety risks, and to detect this is crucial to ensure their safety. Computer vision-based methods to detect surface damages in concrete bridges have seen great progress. However, mainstream methods can only locate surface damage but cannot obtain detailed information, such as the proportion of damaged pixels. To address these challenges, this paper propose TSCB-Net, a semantic segmentation model for surface damage detection in concrete bridges. TSCB-Net employs both Transformers and an encoder-decoder structure, offering a strong alternative to detect surface damage in concrete bridges. Its encoder uses improved baselines with pyramid vision transformer (PVTV2) to extract semantic information and spatial details of concrete bridge images, layer by layer, and to capture long-term dependence between features. The decoder incorporates a context information recovery (CIR) module in the final upsampling stage, using convolutional layers to realize a larger receptive field. This module effectively models context information for semantic segmentation and facilitates multi-scale surface damage detection of concrete bridges. In experiments, TSCB-Net achieves an overall mIoU of 75.84% and an mF1 of 85.54% when the number of parameters is 5.84 M, outperforming state-of-the-art models. TSCB-Net can quickly and accurately detect and identify surface bridge damage, which can help in the early detection of structural problems and the adoption of appropriate repair and protection measures.

Ethanol steam reforming for hydrogen production over cobalt catalyst supported on the cerium oxide prepared via the one-step hard template method

This study describes a cobalt catalyst supported on highly porous cerium oxide beads (CeO2-XAD) prepared via the one-step hard template method (using resin Amberlite® XAD7HP as a template) for catalytic steam reforming of ethanol (SRE) for hydrogen production. For comparative purposes, Co catalyst supported on a commercial CeO2 is discussed (Co/CeO2-COM). Comprehensive studies, including TEM, XPS and H2-TPR analysis, reveal that the bare CeO2-XAD consists of tiny particles with highly damaged surfaces, which contain various forms of oxygen. The hierarchical structure of the support beads, fixed after calcination, ensures high mesoporosity favouring the formation of small, evenly dispersed Co3O4 crystallites on CeO2-XAD (∼3 times smaller than in Co/CeO2-COM), which then, after reduction, transformed into fine, homogenously dispersed Co particles that strongly interact with the support. Consequently, the Co catalyst supported on CeO2-XAD exhibits high catalytic activity in SRE (much higher than Co/CeO2-COM). Although both catalysts deactivate during SRE due to carbon deposition the process is less severe for the catalyst with smaller Co crystallites and nanostructured support. This study reveals the huge role played by the appropriate morphology and nanostructure of the catalyst support in SRE since they affect not only the ethanol conversion efficiency but also increase the selectivity of the process and thus limit the deactivation of the catalyst.

Anomaly detection of cracks in synthetic masonry arch bridge point clouds using fast point feature histograms and PatchCore

Management of ageing masonry arch bridges entails periodic site inspections to identify signs of potential structural degradation. Previous research has focused on detecting surface cracks from images. This paper develops an alternative approach where cracks are identified from point clouds via geometric distortions. An image-based anomaly detection method called PatchCore is customized for 3D applications for this purpose. First, Fast Point Feature Histograms (FPFH) are used to extract geometric features. Then PatchCore is applied on synthetic point clouds with crack labels, generated using 3D finite element modelling (FEM) and graphical modelling. Results show that the proposed method can capture surface and internal cracks in arches. Analyses show that the method is robust against measurement noise, initial damage and masonry surface roughness, and can be applied to other bridge components. Limitations of the method in detecting small changes in curvature and in-plane geometric distortions are highlighted for further improvements.

Optimizing the diamond wire sawing of polycrystalline silicon: An experimental approach

This study aims to determine the optimized cutting conditions for diamond wire sawing of polycrystalline silicon (poly-Si) wafers using a laboratory machine-tool that employs continuous cutting movement and reach cutting conditions similar to those in the industry. The experimental cutting was carried out following a central composite design, varying the wire cutting speed (vc) and feed rate (vf). A response surface methodology was employed to find the optimized cutting conditions for minimum surface roughness and subsurface micro-crack depth of the as-sawn poly-Si wafer. The results showed that the as-sawn poly-Si exhibited ductile scratches and fragile fractures in its surface morphology, with high vc and low vf resulting in a smooth surface. The response surfaces indicated that increasing vf led to increased Ra and Rq values, while increasing vc reduced them. Median micro-cracks were slightly inclined in the subsurface region, with the response surface indicating that their depth reduced with increasing vc and decreasing vf. The vf/vc ratio significantly affected surface integrity, with a lower vf/vc ratio being more suitable for reaching a smoother surface and shallower subsurface damage. The following material removal mechanisms was identified: optimal ductile region, ductile-to-brittle transition, brittle-ductile mixture region, and brittle region. Simulations using the response surface models indicated minimum values of Ra = 0.35 μm, Rq = 0.48 μm and SSD = 3.29 μm. Thus, this study provides a processing parameter window for diamond wire sawing of poly-Si wafers, which could be useful for both the photovoltaic and microelectronic industries.

Bridge Surface Defect Localization Based on Panoramic Image Generation and Deep Learning-Assisted Detection Method

Applying unmanned aerial vehicles (UAVs) and vision-based analysis methods to detect bridge surface damage significantly improves inspection efficiency, but the existing techniques have difficulty in accurately locating damage, making it difficult to use the results to assess a bridge’s degree of deterioration. Therefore, this study proposes a method to generate panoramic bridge surface images using multi-view images captured by UAVs, in order to automatically identify and locate damage. The main contributions are as follows: (1) We propose a UAV-based image-capturing method for various bridge sections to collect close-range, multi-angle, and overlapping images of the surface; (2) we propose a 3D reconstruction method based on multi-view images to reconstruct a textured bridge model, through which an ultra-high resolution panoramic unfolded image of the bridge surface can be obtained by projecting from multiple angles; (3) we applied the Swin Transformer to optimize the YOLOv8 network and improve the detection accuracy of small-scale damages based on the established bridge damage dataset and employed sliding window segmentation to detect damage in the ultra-high resolution panoramic image. The proposed method was applied to detect surface damage on a three-span concrete bridge. The results indicate that this method automatically generates panoramic images of the bridge bottom, deck, and sides with hundreds of millions of pixels and recognizes damage in the panoramas. In addition, the damage detection accuracy reached 98.7%, which is improved by 13.6% when compared with the original network.

Extreme low‐level wind jets in Storm Ciarán

AbstractSatellite imagery of Storm Ciarán as it approached the UK early on 1 November 2023 showed characteristic banding that fuelled media reports that Ciarán could contain a sting jet, with enhanced likelihood of damaging surface winds and gusts. Here operational numerical weather prediction model output is used with trajectory analysis to reveal the existence of at least two wind speed maxima attributed to sting jets. The small‐scale sting jets are located beneath, and likely affected by, far broader overrunning strong wind regions attributed to a deeply descending dry intrusion, thus highlighting the likely interaction of these airstreams at low levels.

Fabrication, Microstructure and Plasma Resistance Behavior of Y-Al-Si-O (YAS) Glass-Ceramics Coated on Alumina Ceramics.

This study investigates the fabrication, microstructural characteristics and plasma resistance of Y-Al-Si-O (YAS) glass-ceramics coated on alumina ceramics. YAS frits were initially prepared using a melt-quenching method, then homogenously milled and coated onto alumina ceramics. The melt-coating process was conducted at 1650 °C for 1 h. The composition and microstructure of the glass frits and coatings were thoroughly characterized using X-ray diffraction, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. These analyses revealed a dense microstructure with a polycrystalline structure predominantly composed of Y3Al5O12 (YAG) phase and a minor phase of Y2Si2O7. The YAS coatings on alumina revealed a dense layer with strong adhesion to the substrate. Subsequently, the coatings underwent C4F6/Ar/O2 plasma treatment for 1 h. Plasma exposure tests demonstrated that the YAS-coated alumina exhibited significantly better etching resistance compared to uncoated alumina, with minimal surface damage observed on the YAS coating, confirming its protective properties against plasma. The superior plasma resistance of YAS coatings is attributed to the predominance of its YAG phase. This research offers a more stable and cost-efficient solution for protecting ceramics in demanding plasma environments.

Characterization of Graphite and ZrO2 Reinforced Aluminium Metal Matrix Composite For Enhanced Mechanical Properties in Electronics Applications

Abstract The objective of this work is to examine the wear properties of a hybrid Metal Matrix Composite (MMC) consisting of 92 weight percent (wt. %) Aluminium Alloy 6061 (AA6061), 2 wt. % Graphite (C), and 6 wt. % Zirconium Dioxide (ZrO2). It was previously determined that this composition was ideal for improved metallurgical and mechanical properties. Nine specimens of the same composition were fabricated for this continuation work and put through wear tests with different applied load, sliding velocity, and sliding distance settings. To evaluate the performance of the composite, measurements were made of the wear rate and Coefficient of Friction (COF). According to the results, the wear rate typically increased as the applied load and sliding velocity increased. At the lowest load (10 N) and velocity (2 m/s), the lowest wear rate (50.90 µg) and COF (0.197) were noted. Specimens with lower wear rates had smoother surfaces and less wear, as revealed by SEM analysis of the worn surfaces; specimens with higher wear rates showed more significant surface damage, such as deeper cuts and serrations. In specimens with less wear, XRD analysis verified the presence of crystalline aluminium, indicating a strong correlation between wear resistance and the crystalline structure of the composite. Linear regression equations were created to predict wear behavior under different conditions. According to the results, the composite's wear characteristics are greatly influenced by the sliding velocity and applied load. ZrO2 and C together have lubricating and strengthening properties that, under certain circumstances, reduce wear. The composite exhibits potential for usage in electronics applications, especially in components where wear resistance and mechanical durability are critical due to its favorable wear characteristics and mechanical properties.

Interface mechanical properties of CFRP-seawater sea sand concrete under simulated seawater immersion

In this study, the interfacial mechanical properties of carbon fiber-reinforced polymer (CFRP) sheet reinforced seawater sea sand concrete (SSSC) in simulated seawater immersion environment were studied. The results present that the interface bearing capacity of CFRP-SSSC decreases significantly after seawater immersion. The decreasing rate increases greatly with the extending of immersion periods. Seawater immersion also affects the failure mode of interface between CFRP and SSSC, which leads to the damaged surface expanding from the base layer of concrete to the junction section of resin and aggregate. The distribution of strain and stress along the bonding direction presents the load transfer from the loading end to the free end. The shear stress peak locates near the loading end and decreased about 15–20 % due to seawater immersion as a result of the deterioration of the interfacial property. The analysis on the microstructure of CFRP-SSSC interface proves that the chemical ions in seawater causes the hydrolyzation of epoxy resin adhesive layer. The CFRP-SSSC interface presents a lower interfacial bonding properties than CFRP reinforced normal concrete (NC). The improvement of strength grade of concrete from C30 to C50 increases the bonding properties of the CFRP about 9–12 % and mitigates the influence of seawater immersion. The obtained bond-slip curve indicates that the seawater immersion decreases the interface ductility. A modified Popovics model is applied to predict the bond-slip curve and presents a high fitting degree.

Dry eye disease and spondyloarthritis: expanding the spectrum of systemic inflammatory disorders associated with ocular surface disease. Data from the international AIDA Network Spondyloarthritis Registry.

Dry eye disease (DED) is a condition associated with a myriad of systemic disorders. According to recent preliminary data, axial spondylarthritis (axial-SpA) could represent a new entity associated with DED. Therefore, this study aimed to assess DED in patients with axial SpA by performing quantitative and qualitative specific tests to investigate the potential association between DED and ocular surface damage in patients with axial-SpA and to identify potential variables associated with DED. A total of 71 patients with axial-SpA who fulfilled the Assessment of SpondyloArthritis International Society (ASAS) classification criteria and 19 healthy controls were enrolled in this study. Both the patients and the controls underwent a complete ocular assessment aimed at evaluating the tear film and ocular surface, which included the Schirmer test, tear break-up time (TBUT), fluorescein staining, and lissamine green staining. The Ocular Surface Disease Index (OSDI) questionnaire was administered to all patients. DED symptoms were reported in 46 (64.8%) patients and three (15.8%) healthy controls (p = 0.0004). The odds ratio for receiving a diagnosis of axial-SpA based on the presence of dry-eye-related symptoms was 9.2 (95% C.I. 2.72-42.52, p = 0.001). The Schirmer test values of < 6 mm/5 min were observed in 31 (43.7%) patients with axial-SpA and two (10.5%) healthy controls (p = 0.013); a TBUT of <5 s was observed in 34 (47.9%) patients with axial-SpA and six (31.6%) healthy controls. The median OSDI score was found to be 22.9 (IQR = 29.35) among the patients with axial-SpA and 0.0 (IQR = 4.69) among the healthy controls (p = 0.009). The fluorescein and lissamine green staining of the ocular surface indicated a significantly higher Oxford Grading Scale in the patients with axial-SpA than in the healthy controls. Patients with axial-SpA often complain of eye dryness, which may be quantified with the self-administered OSDI questionnaire and objectively assessed through the tests commonly used for the diagnosis of DED. Patients suspected of having axial-SpA should routinely be asked about dry eye symptoms and evaluated for potential corneal and conjunctival damage.

Qualitative Comparison of Hydrogen Peroxide Decontamination Systems: Vapor vs. Aerosol

This study aimed to compare the efficiency of two methods for airborne surface decontamination: hydrogen peroxide vapor (HPV) and aerosolized hydrogen peroxide (aHP). Spores of G. stearothermophilus and B. atrophaeus were exposed to a 35% hydrogen peroxide solution under controlled laboratory conditions, including specific concentrations, exposure durations, humidity levels, and temperatures. Following each decontamination procedure, the spores were incubated for 7 days to evaluate bacterial growth and assess the efficacy of each method. The results indicate that the aHP method achieved biocidal rates of 84.76% for G. stearothermophilus and 89.52% for B. atrophaeus, while the HPV method demonstrated respective rates of 90.95% and 90.48%. These findings suggest that both the aHP and HPV methods are highly effective for microbial decontamination, with HPV showing a slight edge in overall efficacy. However, despite its comparable effectiveness, the HPV method has raised concerns regarding technical and economic factors. Observations highlighted issues such as fluctuations in humidity levels causing surface damage, a problem not encountered with the aHP method. Economically, HPV requires specific devices that can cost up to EUR 50,000, whereas aHP equipment costs do not exceed EUR 10,000. These observations emphasize the importance of critically evaluating the pros and cons of each decontamination method, taking into account factors such as biocidal efficacy, technical feasibility, and the associated costs.

Influences of fiber orientation and process parameters on diamond wire sawn surface characteristics of 2.5D Cf/SiC composites

2.5D Cf/SiC composite materials are widely used in aerospace high-temperature components, optical system structural components and other fields due to their excellent performance. For the cutting of 2.5D Cf/SiC composites, diamond wire saw cutting process has great potential for application. In this study, experiments were conducted on cutting 2.5D Cf/SiC composites with diamond wire saw along different fiber orientations (P0°, P90°, V90°) and different process parameters. The effects of fiber orientation, feed speed, and wire speed on the surface morphology, surface waviness profile, and roughness of the as-sawn surface were analyzed. The results show that fiber orientation significantly affects the fiber damage mode and surface quality of the as-sawn surface, with the surface quality of the slices ranked as V90°>P0°>P0°. The surface morphology and surface roughness improves with decreasing feed speed and increasing wire speed. However, surface waviness profile peak-valley (PV) values increases with increasing the feed speed and wire speed. The study provides experimental references for process optimization and quality improvement in diamond wire saw cutting of 2.5D Cf/SiC composite materials.

LiFSO-Net: A lightweight feature screening optimization network for complex-scale flat metal defect detection

Defect recognition of flat metals is paramount for ensuring quality control during the production process. However, the diverse origins of metal surface damage, ranging from mechanical impacts to chemical corrosion, and the resulting varied morphology and scale of surface defects, particularly numerous microdefects and elongated defects with high aspect ratios, complicate defect recognition. Existing methods fail to select the most beneficial features during extraction and commonly lose critical feature information during gradient sampling. To overcome these challenges, we propose a lightweight network to optimize feature screening for defect recognition. First, we propose a deformable context–guided block that employs deformable convolution to dynamically adapt the perception of the spatial context, providing precise guidance of relevant semantic information in complex surface textures. Second, we develop a content-aware feature compression block that implements adaptive weighting of features, which significantly reduces information loss during the downsampling stage. Finally, we introduce an intra-scale feature interaction transformer block, which optimizes high-order semantic features to enhance the accuracy and reliability of defect detection. Experimental validation on the NEU-DET, APS-DET, and GC10-DET datasets demonstrated significant improvements in the detection accuracy and parameter efficiency, confirming the proposed method's robust generalizability.