Search Results (1,287)

In this study, the modeling of rough surfaces by eddy-viscosity-based roughness models is investigated, specifically focusing on surfaces representative of deterioration in aero-engines. In order to test these models, experimental measurements from a rough T106C blade section at a Reynolds number of 400 K are adopted. The modeling framework is based on the k–ω–SST with Dassler’s roughness transition model. The roughness model is recalibrated for the k–ω–SST model. As a complement to the available experimental data, a high-fidelity test rig designed for scale-resolving simulations is built. This allows us to examine the local flow phenomenon in detail, enabling the identification and rectification of shortcomings in the current RANS models. The scale-resolving simulations feature a high-order flux-reconstruction scheme, which enables the use of curved element faces to match the roughness geometry. The wake-loss predictions, as well as blade pressure profiles, show good agreement, especially between LES and the model-based RANS. The slight deviation from the experimental measurements can be attributed to the inherent uncertainties in the experiment, such as the end-wall effects. The outcomes of this study lend credibility to the roughness models proposed. In fact, these models have the potential to quantify the influence of roughness on the aerodynamics and the aero-acoustics of aero-engines, an area that remains an open question in the maintenance, repair, and overhaul (MRO) of aero-engines. Full article

The use of additive manufacturing (AM) has seen increased utilization over the last decade, thanks to well-documented advantages such as lower startup costs, reduced wastage, and the ability to rapidly prototype. The poor surface finish of unprocessed AM components is one of the major drawbacks of this technology, with the research literature suggesting a measurable impact on flow characteristics and burner operability. For instance, surface roughness has been shown to potentially increase resistance to boundary layer flashback—an area of high concern, particularly when utilizing fuels with high hydrogen content. A more detailed understanding of the underlying thermophysical mechanisms is, therefore, required. Computational fluid dynamics can help elucidate the impact of these roughness effects by enabling detailed data interrogation in locations not easily accessible experimentally. In this study, roughness effects on a generic gas turbine swirler were numerically modeled using a low-y+ detached eddy simulation (DES) approach. Three DES models were investigated utilizing a smooth reference case and two rough cases, the latter employing a literature-based and novel equivalent sand-grain roughness (k_s) correlation developed for this work. Existing experimental isothermal and CH₄ data were used to validate the numerical simulations. Detailed investigations into the effects of roughness on flow characteristics, such as swirl number and recirculation zone position, were subsequently performed. The results show that literature-based k_s correlations are unsuitable for the current application. The novel correlation yields more promising outcomes, though its effectiveness depends on the chosen turbulence model. Moreover, it was demonstrated that, for identical k_s values, while trends remained consistent, the extent to which they manifested differed under reacting and isothermal conditions. Full article

In order to optimize the preparation process of microlens arrays, improve preparation efficiency, and reduce preparation costs, 248 nm KrF excimer laser direct writing is combined with a motion mask to prepare microlens arrays on PMMA substrates. Firstly, a specific exposure mask based on the contour characteristics of the microlens unit was designed, and the preparation principle was analyzed. Using COMSOL Multiphysics 6.3 simulation software, a microlens preparation model was built to intuitively describe the process of preparing microlenses by the motion mask method. Secondly, a preparation system was built, and the laser processing technology was optimized. Finally, microlens arrays were prepared based on the optimized process, and an optical microscope and white-light interferometer were used to observe their morphology. The experimental results show that this method can effectively prepare cylindrical and circular microlens arrays. The width of the cylindrical microlens array unit exceeded 90 μm, the height was 7.08 μm, and the roughness was 0.09 μm. The diameter of the circular microlens array unit was φ100 μm, the height was 4 μm, and the curvature radius was 230 μm. The geometric dimensions of the mask can be adjusted to obtain microlens units of the desired size, achieving personalized preparation of microlens arrays. The excimer laser motion mask method can prepare various types of microlens arrays, and the array units have a high consistency and high surface quality, which helps to improve the efficiency, flexibility, stability, and specificity of microlens array preparation. Full article

Polycrystalline copper optics are widely utilized in infrared systems due to their exceptional electrical and thermal conductivity combined with favorable machining characteristics. The grain size profoundly influences both surface quality consistency and fundamental material removal behavior during processing. This investigation employs multiscale numerical modeling to simulate nanoscale cutting processes in polycrystalline copper with controlled grain structures, coupled with experimental ultra-precision machining validation. Comprehensive analysis of stress distribution, subsurface damage formation, and cutting force evolution reveals that refined grain structures promote more homogeneous plastic deformation, resulting in superior surface finish with reduced roughness and diminished grain boundary step formation. However, the enhanced grain boundary density in fine-grained specimens necessitates increased cutting energy input. These findings establish critical process–structure–property relationships essential for advancing precision manufacturing of copper-based optical systems. Full article

The increasing utilization of single-use plastics in the food sector poses serious environmental challenges. A circular economy approach, i.e., reusing packaging before recycling, offers a promising solution but raises concerns about cross-contamination between food products. This study investigates how repeated use and cleaning affect the surface topography of plastic food packaging and, in turn, how these changes influence cleaning efficiency and assessment. Recycled polyethylene terephthalate (rPET) trays were subjected to 20 industrial wash cycles with and without detergent concentration of 0.3% v/v at the following temperatures: 55 °C wash, 70 °C rinse. Surface roughness was measured using mechanical and optical techniques. Additionally, trays were roughened with sandpaper of varying grit sizes to simulate mechanical wear during consumer use. Cleanability was assessed using UV fluorescence imaging and adenosine triphosphate (ATP) assays. Results showed no significant increase in surface roughness after 20 wash cycles. However, artificially roughened surfaces retained more food residue, complicating cleaning. The application of UV fluorescence imaging proved more effective than ATP assays in detecting food residues on textured surfaces. These findings support the use of advanced imaging for evaluating the hygiene of reusable packaging and highlight key considerations for implementing circular reuse systems in food packaging. Full article

Autonomous planetary rovers require robust path planning over rough 3D terrains, where traditional metrics such as path length, number of nodes, and planning time do not adequately capture path quality. Rapidly Exploring Random Trees (RRT) and its asymptotically optimal variant, RRT*, are widely used sampling-based algorithms for non-holonomic mobile robots but are limited when traversing uneven 3D terrain. This study proposes 3D-RRT*, a simplified, terrain-aware extension of Traversability-Based RRT*, designed to maintain high path quality while reducing planning time. The performance of 3D-RRT* is evaluated using metrics that are both practical and meaningful in the context of planetary rover path planning: path smoothness, path flatness, path length, and planning time. Exploration of a simulated Martian surface demonstrates that 3D-RRT* significantly improves path quality compared to standard RRT and RRT*, achieving smoother, safer, and more efficient routes for planetary rover missions. Full article

The adverse propagation environment in underground coal mine tunnels caused by enclosed spaces, rough surfaces, and dense scatterers severely degrades reliable wireless signal transmission, which further impedes the deployment of IoT applications such as gas monitors and personnel positioning terminals. However, the conventional power enhancement solutions are infeasible for the underground coal mine scenario due to strict explosion-proof safety regulations and battery-powered IoT devices. To address this challenge, we propose singular value decomposition-based Lagrangian optimization (SVD-LOP) to minimize transmit power at the mining base station (MBS) for IRS-assisted coal mine wireless communication systems. In particular, we first establish a three-dimensional twin cluster geometry-based stochastic model (3D-TCGBSM) to accurately characterize the underground coal mine channel. On this basis, we formulate the MBS transmit power minimization problem constrained by user signal-to-noise ratio (SNR) target and IRS phase shifts. To solve this non-convex problem, we propose the SVD-LOP algorithm that performs SVD on the channel matrix to decouple the complex channel coupling and introduces the Lagrange multipliers. Furthermore, we develop a low-complexity successive convex approximation (LC-SCA) algorithm to reduce computational complexity, which constructs a convex approximation of the objective function based on a first-order Taylor expansion and enables suboptimal solutions. Simulation results demonstrate that the proposed SVD-LOP and LC-SCA algorithms achieve transmit power peaks of $20.8\mathrm{dBm}$ and $21.4\mathrm{dBm}$, respectively, which are slightly lower than the $21.8\mathrm{dBm}$ observed for the SDR algorithm. It is evident that these algorithms remain well below the explosion-proof safety threshold, which achieves significant power reduction. However, computational complexity analysis reveals that the proposed SVD-LOP and LC-SCA algorithms achieve $\mathcal{O}\left(N^3\right)$ and $\mathcal{O}\left(N^2\right)$ respectively, which offers substantial reductions compared to the SDR algorithm’s $\mathcal{O}\left(N^7\right)$. Moreover, both proposed algorithms exhibit robust convergence across varying user SNR targets while maintaining stable performance gains under different tunnel roughness scenarios. Full article

Hybrid computer-aided design and computer-aided manufacturing (CAD/CAM) materials have gained prominence in restorative dentistry due to their advantageous mechanical and esthetic properties; however, their long-term performance may be adversely affected by acidic oral environments, such as those associated with gastroesophageal reflux disease (GERD). This in vitro study aimed to investigate the effects of simulated gastric acid exposure on the surface roughness, gloss, color stability, and microhardness of two hybrid CAD/CAM materials: Vita Enamic and Cerasmart. Standardized rectangular specimens (2 mm thickness) were prepared and polished using a clinically relevant intraoral protocol. Baseline measurements were obtained for surface roughness, gloss, color change (ΔE), and Vickers microhardness. All specimens were then immersed in hydrochloric acid (pH 1.2) for 24 h to simulate prolonged gastric acid exposure, after which the same properties were re-evaluated. Post-immersion analysis revealed significant increases in surface roughness and reductions in gloss and microhardness for both materials (p < 0.05), with Vita Enamic demonstrating greater susceptibility to degradation. Color changes remained below the clinically perceptible threshold, with no significant differences between materials. These findings highlight the potential vulnerability of hybrid CAD/CAM materials to acidic environments and underscore the importance of careful material selection in patients predisposed to acid-related challenges. Full article

Polylactic acid (PLA) is an eco-friendly polymer known for its biodegradability and biocompatibility, yet its properties are sensitive to recycling and sterilization. These processes may cause chain scission and structural irregularities, leading to reduced strength, brittleness, or unpredictable deformation. In this study, PLA and recycled PLA (Re-PLA) specimens were produced by FDM 3D printing with different infill rates (25%, 50%, 75%), layer thicknesses (0.15, 0.20, 0.25 mm), and printing orientations (0°, 45°, 90°). Steam sterilization at 121 °C and 1 bar for 15 min simulated biomedical conditions. Mechanical, surface, degradation, and biocompatibility properties were examined using three-point bending, roughness measurements, SEM, and cell viability tests. Results showed that infill rate was the main parameter affecting flexural strength and surface quality, while orientation increased roughness. Sterilization and recycling made deformation less predictable, particularly in St-Re-PLA. SEM revealed stronger bonding at higher infill, but more brittle fractures in PLA and Re-PLA, while sterilized specimens showed ductile features. No visible degradation occurred at any infill level. Regression analysis confirmed that second-order polynomial models effectively predicted flexural strength, with layer thickness being most influential. These findings provide critical insights into optimizing PLA and Re-PLA processing for biomedical applications, particularly in the production of sterilizable and recyclable implantable devices. Full article

Surface roughness influences biofilm adhesion on denture base materials, impacting oral health. Despite advances in polymeric denture materials, the effects of common cleaning protocols on their surface texture remain inadequately characterized. This study investigated the influence of toothbrush abrasion on the surface texture of dimethyl methacrylate-based (DMA, printed: V-Print dentbase), polymethyl methacrylate (PMMA, milled: VITA Vionic Base, pressed: IvoBase Hybrid), polyamide (PA, pressed: Bre.flex), and polyether ether ketone (PEEK, milled: Juvora Disc). The specimens were fabricated as polished discs. The Vickers and Martens hardness, indentation modulus, elastic and plastic part of indentation work, and indentation creep were determined. Toothbrushing simulation and surface texture analysis were conducted in three steps: 1800, 1800, and 3600 cycles using water, dish detergent, or toothpaste slurry. The surface texture parameters Sa, Sal, Sdr, Sku, and Ssk were determined using confocal laser scanning microscopy and suitable filtering (S-F and S-L surface). Sa, Sal, and Sdr showed significant changes depending on the choice of medium and the material used. The duration had a small effect (three-way ANOVA; all p < 0.001). DMA showed minor surface changes. Milled and pressed PMMA exhibited similar surface deformities due to wide valleys that were not considered critical for biofilm adhesion. PA showed the lowest and PEEK the highest Vickers and Martens hardness. However, both PA and PEEK exhibited surface changes that could promote biofilm development. These findings suggest that denture cleaning recommendations should remain material-specific. Regular surface inspections and repolishing are necessary to reduce the risk of biofilm formation on PA or PEEK-containing dentures. Full article

The high hardness and toughness of AISI 4130 alloy present significant challenges during machining, including excessive cutting forces, rapid tool wear, and poor surface finish control. To address these issues, this study combines numerical simulation with turning experiments to systematically investigate the effects of tool geometry and cutting parameters on cutting force, temperature, and surface roughness. Through Deform-3D finite element modeling, one-factor, and orthogonal simulation tests, it was found that the optimal tool geometric combination (λs = 2°, κ_r = 99°, γ₀ = 5°) reduces the cutting forces by 21.86% as compared to the baseline parameters. Experimental validation showed that the agreement between simulated and measured cutting forces was 86.73%–87.8%, with simulated values being 10%–13.27% higher due to idealized boundary conditions. Surface morphological analysis by Bruker Contour Elite K shows that the surface roughness of the workpiece decreases with an increasing cutting speed and increases with an increasing feed rate and depth of cut. The above studies provide a certain research basis for optimizing the tool angle and improving the cutting efficiency. Full article

The transfer of momentum and kinetic energy is a key factor in turbomachinery performance, particularly influencing the efficiency of the bladeless Tesla turbine, which holds significant potential for applications such as Organic Rankine Cycle (ORC) systems and energy recovery processes. In this study, a comprehensive numerical analysis was carried out to simulate the effects of surface roughness on the flow between the co-rotating disks of a Tesla turbine, using R1234yf and n-hexane as working fluids. To capture roughness effects, a porous medium layer (PML) approach was employed, with porous material parameters adjusted to replicate real roughness behavior. The model was first validated against experimental data for water flow in a minichannel by tuning the PML parameters to match measured pressure drops. In contrast to previous studies, this work applies the PML model to a Tesla turbine operating with organic Rankine cycle (ORC) fluids, where the working medium is changed from air to low-boiling gases. Compared to the air-based cases, the gap between the co-rotating disks is rescaled to smaller dimensions, which introduces additional challenges. Under these conditions, the effective roughness thickness must also be rescaled, and this study investigates how these rescaled roughness effects influence turbine performance using the k-ω shear stress transport (SST) turbulence model combined with the proposed roughness model. Results showed that incorporating the PML roughness model enhances momentum transfer and significantly influences flow characteristics, thereby providing an effective means of simulating Tesla turbine performance under varying roughness conditions. Full article

Marine applications often involve metallic materials, including steel, that must endure harsh conditions such as cavitation erosion (CE). This study investigates the CE behavior of 42CrMo4 steel, both in its original state and after pre-corrosion in a 3.5% NaCl solution for 120 days, simulating a simplified marine environment. Cavitation testing was conducted using an ultrasonic vibratory setup with a stationary sample, at intervals of 10 and 30 min, with a total testing time of 150 min. Mass loss (ML), mass loss rate (MLR), mean depth of erosion (MDE), and level of degradation (LoD) were calculated, while surface roughness (Rz) was measured using a TR200 tester. Surface changes were analyzed through field emission scanning electron microscopy (FESEM) and image analysis techniques. Morphological parameters such as the number of pits, average diameter, and total pit area were used to quantify surface damage. Results showed that pre-corroded samples exhibited a significantly higher erosion rate than non-corroded ones. Pre-corrosion introduced microcracks and surface defects that served as initiation sites for cavitation damage. These imperfections increased surface roughness and created favorable conditions for pit formation, leading to faster and deeper material loss. Image and FESEM analyses confirmed the presence of larger and deeper pits in pre-corroded samples compared to the smaller and shallower pits in non-corroded specimens. This study highlights the impact of pre-corrosion on the cavitation resistance of 42CrMo4 steel and demonstrates the effectiveness of combining mass loss data with morphological and surface analyses for evaluating cavitation damage under marine-like conditions. Full article

While laser-assisted turning (LAT) improves the machinability of GH 4169 through heating-induced thermal softening, revealing the influence of the laser processing parameters on its thermal field and machining efficiency is crucial. In this study, the influence of different laser processing parameters on the thermal field during the preheating process of LAT is systematically investigated by combining finite element (FE) simulation and experimentation, from which the optimal processing parameters of the LAT of GH 4169 are obtained. Firstly, the experimental platform of LAT is established, and a 2D FE model of the LAT of GH 4169 is constructed. Secondly, the absorption coefficient of GH 4169 with a 1064 nm wavelength laser is calibrated through experimentation and FE simulation, which lay an accurate foundation for the subsequent thermal field analysis. Furthermore, the FE simulation of the preheating process of the LAT of GH 4169 is carried out, focusing on the influence of laser power, laser spot diameter, laser spot movement speed and laser spot–tool edge distance on the thermal field, in terms of the peak and final preheating temperatures. The results show that laser power, laser spot movement speed and laser spot diameter have a significant influence on both of the two temperatures, while laser spot–tool edge distance only affects the final preheating temperature. In addition, the regression equations of the peak and final preheating temperatures are obtained based on the FE simulation results, and the optimal processing parameters are determined by combining the boundary conditions (peak temperature of 650–950 °C and initial preheating temperature of ≤190 °C). Comparison experiments with conventional turning (CT) show that under the optimal processing parameters, LAT can effectively reduce the cutting force, surface roughness and tool flank wear, which indicates that a rational selection of laser processing parameters is crucial for improving the capability of LAT of GH 4169. Full article

In this study, the properties of electrophoretically deposited (EPD) coatings on orthodontic implants made from Ti-6Al-4V alloy were evaluated during simulated implantation trials on animal bones. Three types of chitosan-based coatings were prepared using EPD: titanium nitride microparticles (TiNPs), titanium nitride nanoparticles (TiNNPs), and boron nitride particles (BNPs). Each of these coatings was also modified by adding a polylactic acid (PLA) layer using a dip-coating technique to compare their properties with and without this additional layer. The coatings were analysed using optical microscopy, confocal microscopy, and scanning electron microscopy (SEM) with elemental analysis. Surface roughness measurements of the coated implants were also conducted to highlight differences that could significantly influence the type and strength of the bone-implant interface, directly affecting the stability of the implant as an anchorage unit. Eventually, to evaluate the antibacterial properties of the EPD coatings, their antibacterial activity against both Gram-positive and Gram-negative bacteria strains was tested. Scanning electron observations confirmed the homogenous distribution of micro- and nanoparticles in all coatings. The highest surface roughness values were observed in layers containing titanium nitride nanoparticles (TiNNPs) and chitosan. The presence of an additional dip-coating PLA layer improved the adhesion, and its effect on the surface roughness depended on the particle size. While the antibacterial properties of the coatings show promising results, achieving optimal adhesion of the coatings to implants remains a challenge that requires further development. Full article