This paper describes the development of artificial neural network (ANN) models and multi-response optimization technique to predict and select the best cutting parameters of wire electro-discharge ...machining (WEDM) process. To predict the performance characteristics namely material removal rate and surface roughness, artificial neural network models were developed using back-propagation algorithms. Inconel 718 was selected as work material to conduct experiments. A brass wire of 0.25
mm diameter was applied as tool electrode to cut the specimen. Experiments were planned as per Taguchi's L9 orthogonal array. Experiments were performed under different cutting conditions of pulse on time, delay time, wire feed speed, and ignition current. The responses were optimized concurrently using multi-response signal-to-noise (MRSN) ratio in addition to Taguchi's parametric design approach. Analysis of variance (ANOVA) was employed to identify the level of importance of the machining parameters on the multiple performance characteristics. Finally, experimental confirmations were carried out to identify the effectiveness of this proposed method. A good improvement was obtained.
•Effect of inherent anisotropy of shale on the size of inelastic zone at crack tip is revealed.•Anisotropic features of the crack surface roughness generated by NDB specimens are analyzed.•Mode II ...fracture has significant effects on both the crack surface roughness and propagation path.
Understanding the anisotropic fracture mechanism of shale is of significance to assess the development of a stimulated reservoir volume. In this study, three-point bending tests were carried out using notched deep beam specimens of shale with 7 different bedding dip angles to investigate the anisotropic fracture behavior. The anisotropic characteristics of the fracture toughness, energy release rate, inelastic zone and crack propagation path were comprehensively analyzed and highlighted. The results showed that the fracture toughness decreases with increasing bedding dip angle. When the bedding dip angle is 0° and 90°, the fracture toughness reaches the maximum and minimum values, respectively, with a ratio of 1.60. The variation tendency of the energy release rate with the bedding inclination angle is consistent with that of the fracture toughness, but the ratio of the maximum value to the minimum value of the energy release rate is about 3.24. The size of the inelastic zone first decreases and then increases at different bedding inclination angles from 0° to 90° and reaches the maximum size of 1.51 mm when the bedding plane inclination angle is 45°. The crack propagates along the bedding plane rather than straight along the initial crack direction when the bedding dip angle is higher than 45°. As the bedding plane dip angle increases from 0° to 45°, the crack surface roughness of the tested shale first increases, then decreases and finally reaches the maximum. The discussion indicated that the presence of the Mode II fracture has a considerable influence on the crack surface roughness and crack propagation path, although it has little effect on the failure load. Compared with the maximum energy release rate (MERR) criterion, the maximum tangential stress (MTS) criterion seems more accurate in predicting the anisotropic Mode I fracture toughness. The applicability of these two classical crack initiation criteria of fracture mechanics has been analyzed based on our experimental results, which demonstrates the validity of the MTS criterion to assess the anisotropic fracture toughness of shales.
The effect of surface roughness and polishing orientation on fatigue life is investigated. Fully reversed bending fatigue tests are conducted on ASTM A1008 specimens having surface roughness ...asperities ranging from mirror finish (Ra = 0.05 μm) to coarse (Ra = 1.5 μm). Two polishing directions (i.e., orientations) are examined. For the range of roughness values tested, the results suggest that polishing orientation has a strong influence on fatigue life. Specifically, within the range of surface roughness values tested, fatigue life was found to be relatively insensitive to surface roughness asperities when the roughness orientation was parallel to the direction of surface stress but sensitive to surface roughness asperities when the orientation crossed the direction of surface stress. Results are generalized using the concept of fracture fatigue entropy (FFE). It is shown that, unlike fatigue life, FFE is independent of polishing orientation, a noteworthy result. To explain the behavior of FFE in relation to surface roughness asperities, a fatigue thermodynamics theory is presented that hypothesizes that all specimens of the same material fail at equivalent entropy levels.
Highlights
The influence of surface roughness on fatigue life is investigated.
Extensive fully reversed bending fatigue tests are performed.
Surface roughness lay has a pronounced influence on fatigue life.
Fracture fatigue entropy (FFE) is sensitive to the roughness regardless of its lay.
Remote sensing study of the carbon cycle in coastal marine systems using machine learning methods has received significant attention recently. The partial pressure of carbon dioxide (CO2) in seawater ...(<inline-formula> <tex-math notation="LaTeX">{p} </tex-math></inline-formula>CO2w) is a crucial parameter for quantifying the air-sea carbon dioxide exchange. However, previous studies did not consider the effect of sea surface roughness (SSR) on <inline-formula> <tex-math notation="LaTeX">{p} </tex-math></inline-formula>CO2w caused by wind, waves, and other ocean dynamics. In this study, for the first time, we used SSR data derived from synthetic aperture radar (SAR), with sea surface temperature (SST), chlorophyll-<inline-formula> <tex-math notation="LaTeX">{a} </tex-math></inline-formula> (Chl-<inline-formula> <tex-math notation="LaTeX">{a} </tex-math></inline-formula>) concentration, sea surface salinity (SSS) conventional remote sensing data to predict the <inline-formula> <tex-math notation="LaTeX">{p} </tex-math></inline-formula>CO2w data along the North American East Coast from 2015 to 2021 using the Cubist algorithm. Results show that the semi-analytic algorithm, Cubist, performs best among 20 statistical and machine learning models. Moreover, compared with the control experiment without the SSR data, after adding SSR as an independent variable, the final Cubist model's coefficient of determination (<inline-formula> <tex-math notation="LaTeX">{R} ^{2} </tex-math></inline-formula>) increased from 0.88 to 0.95, and the root mean square error (RMSE) reduced from 21.75 to <inline-formula> <tex-math notation="LaTeX">14.79~\mu </tex-math></inline-formula>atm. Our results showed significant improvement over the previous study (<inline-formula> <tex-math notation="LaTeX">{R} ^{2} </tex-math></inline-formula> = 0.8), proving the applicability of applying SSR data in retrieving high spatial resolution carbonate system parameters in the future, especially for coastal regions where wind and wave dynamics are more variable.
Metasurfaces are planar optical elements that hold promise for overcoming the limitations of refractive and conventional diffractive optics. Original dielectric metasurfaces are limited to ...transparency windows at infrared wavelengths because of significant optical absorption and loss at visible wavelengths. Thus, it is critical that new materials and nanofabrication techniques be developed to extend dielectric metasurfaces across the visible spectrum and to enable applications such as high numerical aperture lenses, color holograms, and wearable optics. Here, we demonstrate high performance dielectric metasurfaces in the form of holograms for red, green, and blue wavelengths with record absolute efficiency (>78%). We use atomic layer deposition of amorphous titanium dioxide with surface roughness less than 1 nmand negligible optical loss. We use a process for fabricating dielectric metasurfaces that allows us to produce anisotropic, subwavelength-spaced dielectric nanostructures with shape birefringence. This process is capable of realizing any high-efficiency metasurface optical element, e.g., metalenses and axicons.
A comprehensive understanding of the combined effects of surface roughness and wettability on the dynamics of the trapping process is lacking. This can be primarily attributed to the contradictory ...experimental and numerical results regarding the impact of wettability on the capillary trapping efficiency. The discrepancy is presumably caused by the surface roughness of the inner pore‐solid interface. Herein, we present a comparative μ‐CT study of the static fluid‐fluid pattern in porous media with smooth (glass beads) and rough surfaces (natural sands). For the first time, a global optimization method was applied to map the characteristic geometrical and morphological properties of natural sands to 2‐D micromodels that exhibit different degrees of surface roughness. A realistic wetting model that describes the apparent contact angle of the rough surface as a function surface morphology and the intrinsic contact angle was also proposed. The dynamics of the trapping processes were studied via visualization micromodel experiments. Our results revealed that sand and glass beads displayed opposite trends in terms of the contact angle dependence between 5° and 115°. Sand depicted a nonmonotonous functional contact angle dependency, that is, a transition from maximal trapping to no trapping, followed by an increase to medium trapping. In contrast, glass beads showed a sharp transition from no trapping to maximal trapping. Since both porous media exhibit similar morphological properties (similar Minkowski functions: porosity, surface density, mean curvature density, Euler number density), we deduce that this difference in behavior is caused by the difference in surface roughness that allows complete wetting and hence precursor thick‐film flow for natural sands. Experimental results on micromodels verified this hypothesis.
Key Points
Wettability, surface roughness, and pore space structure have an impact on trapping efficiency
Porous media with rough surface, as natural sands and glass‐ceramic micromodels, were studied
Wettability‐controlled crossover from snap‐off to by‐pass trapping and spontaneous precursor thick‐film flow were observed
•The topology of SLM/EBM as built surface is better captured by tomography and optical micrography.•Micro-notches associated to surface roughness initiates non propagating cracks.•Numerical modeling ...of the surface coupled to extreme statistics allow properly describe surface criticality.•A non local approach allow to predict the impact of surface roughness on the HCF behavior.•Purely elastic and elasto-plastic behavior impact the local stress state but not the non-local fatigue criteria.
Selective Laser Melting (SLM) is a powder bed fusion process which allows to build-up parts by successive addition of layers using 3D-CAD models. Among the advantages, the high degree of freedom for part design and the small loss of material explain the increasing number of Ti-6Al-4V parts obtained by this process. However, right after additive manufacturing, these parts contain defects (surface roughness, porosity, residual stresses) which significantly decrease the High Cycle Fatigue (HCF) life. In order to minimize the porosity and residual stresses, post-processing treatments like Hot Isostatic Pressing (HIP) and Stress Relieving (SR) are often conducted. But the reduction of the surface roughness by machining is very costly and not always possible, especially for parts with complex geometry. The aim of this work is to evaluate the effect of the surface roughness of Ti-6Al-4V parts produced by SLM on the HCF behavior and to propose a methodology to estimate this effect. Three sets of specimens were tested in tension-compression: Hot-Rolled (reference); SLM HIP machined; SLM HIP as-built. For each condition, microstructure characterization, observation of the fracture surface of broken specimens, surface analysis and volume analysis were carried out respectively by Optical Microscope (OM), Scanning Electron Microscope (SEM), 3D optical profilometer and 3D X-ray tomograph. Results of fatigue testing show a significant decrease of the HCF life mainly due to the surface roughness. Along with experimental testing, numerical simulations using FEM were conducted using the surface scans obtained by profilometry and tomography. Based on extreme values statistics of a non-local fatigue indicator parameter (FIP), a methodology is proposed to take into account the effect of the surface roughness on the HCF life.
This study aimed to investigate how titanium (Ti) surface with different range roughness created by industrial machining influence the biological response of primary human gingival fibroblasts (HGFB) ...and keratinocytes (HGKC) in terms of cell proliferation and cytotoxicity.
Four Ti surfaces of different roughness ranges were investigated: smooth (S: 0.08–0.1 µm), minimally rough (MM: 0.3–0.5 µm), moderately rough (MR: 1.2–1.4 µm) and rough (R: 3.3–3.7 µm). Discs topography and surface roughness were evaluated by scanning electron microscopy (SEM) and non-contact profilometer. Both cell lines were cultured, expanded, and maintained according to their supplier’s protocols. Cell proliferation and cytotoxicity were evaluated at days 1, 3, 5, and 10 using cell viability and cytotoxicity colorimetric assays. Data were analysed via two-way ANOVA, one-way ANOVA and Tukey’s post hoc test (p = 0.05 for all tests).
Both cell lines showed comparable initial proliferation activity of 70–86% for all the investigated roughnesses. HGKC showed better and higher proliferation % with S surface at all time points than all the other investigated surfaces which was significantly higher than MM at day 3 and higher than all the other investigated surfaces at day 5 and 10. On the other hand, HGFB exhibited the best proliferation with both MM and R surfaces with no significant differences from the other two surfaces (S and MR). Different surface roughnesses and exposure times showed significant effect on cell proliferation in both cell lines. Cytotoxicity for both cell lines was generally the highest on day 3, with the following order from highest to lowest: S (19.86%)> R> MR> MM for HGKC and MM (39.48%)> MR> S> R for HGFB. Different exposure times showed a significant effect on cell cytotoxicity in both cell lines and a significant effect of surface roughness in HGFB.
All investigated roughness levels were sufficiently biologically compatible with cells representative of the major population of the soft tissue surrounding dental implants. However, the S surface was most cytotoxic to HGKC, while the MM surface was most cytotoxic to HGFB cells.
The conductor surface roughness effect on microstrip lines is physically represented by proposing a step-by-step methodology that uses experimental <inline-formula> <tex-math ...notation="LaTeX">S</tex-math> </inline-formula>-parameters supported by electromagnetic (EM) simulations assuming smooth conductor surfaces. This avoids implementing the microstrip line model by arbitrarily fitting simulations with experimental data that include multiple-frequency-dependent effects. Furthermore, a priori knowledge of the roughness profile is not required in this proposal. From the analysis, the peak-to-valley feature of the surface roughness that allows for the representation of the corresponding effect on the electrical response of the lines is obtained. The implemented models show a correlation with experimental data up to 35 GHz.
The normal restitution coefficient is an important parameter in particle deposition which is widely used in industrial fields. The normal restitution coefficient can be affected by many factors, and ...a typical factor is the surface roughness. Furthermore, a rough surface will influence the adhesion force and friction coefficient. The adhesion force and friction coefficient have effects on the normal restitution coefficient. However, the relationship between the normal restitution coefficient and the surface roughness has not been obtained. Therefore, an experimental study of microspheres impact on a rough surface is developed. The normal restitution coefficient decreases with the increasing surface roughness. The adhesion force is calculated by the Rabinovich model, and the results indicated that the adhesion force increases with the increasing surface roughness within the surface roughness range in this paper. Moreover, the adhesion energy and friction coefficient dissipation increase with the increasing surface roughness.
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•The normal restitution coefficient versus surface roughness was obtained by experiment.•The adhesion force versus surface roughness was calculated by Rabinovich model.•The adhesion energy dissipation versus the surface roughness were obtained.•the friction coefficient versus the surface roughness was obtained.
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