Surface roughness is a critical factor affecting the performance of dental implants. One approach to influence this is through sandblasted, large grit, acid-etched (SLA) modification on pure titanium implant surfaces. In this study, SLA was performed on grade IV pure titanium. Sandblasting was conducted at distances of 2, 4, and 6 cm. Subsequently, the samples were etched with a mixed acid solution of HCl, H2SO4, and H2O for 0, 30, and 60 min. Surface roughness and X-ray diffraction (XRD) characterizations were conducted on the samples. The results revealed that surface roughness increased but was not too significant as the sandblasting distance decreased. Longer etching durations for sandblasted with acid-etched samples led to reduced surface roughness (Sa and Sz). It was found that a 60 min-etched sample resulted in optimal Sa, Sz, and Ssk values, i.e., 1.19 μm, 13.76 μm, and −0.60, respectively. The XRD texture was significantly influenced by sandblasting, with compressive residual stress increasing as the sandblasting distance decreased. Normal stress causes hill formations at shorter sandblasting distances. For etched samples, the residual stress decreased with longer etching durations. Normal stress-decreasing trend aligns with the initial reduction in hill and valley within the samples and subsequent hill enhancement at extended etching duration.

The accelerated rate of product development and design complexities offered by Additive Manufacturing (AM) has allowed for innovation in the space industry. However, the surface roughness of parts poses a challenge, as it impacts performance and is tied to design choices. Design tools for traditional manufacturing methods fall short in AM contexts, prompting the need for alternative design processes. This work proposes an experimental approach to design for AM investigation using design artefacts to explore a process-structure-property-performance relationship.

Tall, spiky snow structures (penitentes) occur high in subtropical mountains, in the form of blades oriented east-west and tilted toward the noontime sun. By trapping sunlight, they cause a reduction of albedo by ~0.3 relative to flat snow. The formation of penitentes, explained by Lliboutry in 1954, requires weather conditions allowing the troughs to deepen rapidly by melting while the peaks remain dry and cold by sublimation, losing little mass, because of the 8.5-fold difference in latent heats. Lliboutry's explanation has been misrepresented in some recent publications. A concern has been raised that in the low latitudes of Jupiter's moon Europa, the ice surface may have developed penitentes, which would pose a hazard to a lander. They would require a different mechanism of formation, because Europa is too cold for melting to occur. If penitentes are present on Europa, they cannot be resolved by the coarse-resolution satellite images available now, but the high albedo of Europa (~0.7 at visible wavelengths) argues against the existence of such extreme roughness.

Surface roughness (SR) is one of the major parameters used to govern the quality of the fused deposition modeling (FDM)-printed products, and the FDM process parameters can be easily regulated in order to obtain a good surface finish. The surface quality of the product produced by the FDM is generally affected by the staircase effect that needs to be managed. Also, the production time (PT) to fabricate the product and volume percentage error (VPE) should be minimized to make the FDM process more efficient. The aim of this paper is to accomplish these three objectives with the use of the parametric optimization technique integrating the artificial neural network (ANN) and the whale optimization algorithm (WOA). The FDM parameters which have been taken into consideration are layer thickness, nozzle temperature, printing speed, and raster width. Experimentation has been conducted on printed samples to examine the impact of the input parameters on SR, VPE, and PT according to Taguchi's L27 orthogonal array. The ANN model has been built up using the experimental data, which was further used as an objective function in the WOA with an aim to minimize output responses. The robustness of the proposed method has been validated on the optimal combinations of FDM process parameters.

Laser Powder Bed Fusion (LPBF) brings the possibility to manufacture innovative near-net-shape part designs. But unfortunately, some designed surfaces suffer from rough surface finish due to characteristics of the LPBF process. This paper explores trends in managing surface roughness and through a space industry case study, a proposed process that uses Additive Manufacturing Design Artefacts (AMDAs) is used to investigate the relationship between design, surface roughness and fatigue. The process enables the identification of design uncertainties, however, iterations of AMDA's can be required.

One often-cited benefit of using metal additive manufacturing (AM) is the possibility to design and produce complex geometries that suit the required function and performance of end-use parts. In this context, laser powder bed fusion (LPBF) is one suitable AM process. Due to accessibility issues and cost-reduction potentials, such ‘complex’ LPBF parts should utilise net-shape manufacturing with minimal use of post-process machining. The inherent surface roughness of LPBF could, however, impede part performance, especially from a structural perspective and in particular regarding fatigue. Engineers must therefore understand the influence of surface roughness on part performance and how to consider it during design. This paper presents a systematic literature review of research related to LPBF surface roughness. In general, research focuses on the relationship between surface roughness and LPBF build parameters, material properties, or post-processing. Research on design support on how to consider surface roughness during design for AM is however scarce. Future research on such supports is therefore important given the effects of surface roughness highlighted in other research fields.

The ability to accurately and precisely measure the thickness of biomaterial constructs is critical for characterizing both specific dimensional features and related mechanical properties. However, in the absence of a standardized approach for thickness measurements, a variety of imaging modalities have been employed, which have been associated with varying limits of accuracy, particularly for ultrathin hydrated structures. Electron microscopy (EM), a commonly used modality, yields thickness values for extensively processed and nonhydrated constructs, potentially resulting in overestimated mechanical properties, including elastic modulus and ultimate tensile strength. Confocal laser scanning microscopy (CLSM) has often been used as a nondestructive imaging alternative. However, published CLSM-derived image analysis protocols use arbitrary signal intensity cutoffs and provide minimal information regarding thickness variability across imaged surfaces. To address the aforementioned limitations, we present a standardized, user-independent CLSM image acquisition and analysis approach developed as a custom ImageJ macro and validated with collagen-based scaffolds. In the process, we also quantify thickness discrepancies in collagen-based scaffolds between CLSM and EM techniques, further illustrating the need for improved strategies. Employing the same image acquisition protocol, we also demonstrate that this approach can be used to estimate the surface roughness of the same scaffolds without the use of specialized instrumentation.

This paper investigates the generation of passive intermodulation (PIM) in coaxial connectors during vibration. A series of experiments were designed and the simulation model and method were proposed for understanding these phenomena. We found that PIM is mainly influenced by the contact stress and contact surface roughness during vibration. Thus, a power spectral density method is presented to identify the roughness parameter of contact surface based on the Weierstrass–Mandelbrot model, and the simulation model and method were verified by the relative experiments. Eventually, some suggestions for engineering application were provided.

This paper addresses the construction of digital twins (exact mirror images of real-world in cyberspace) using hidden Markov models for the futuristic manufacturing systems known as Industry 4.0. The proposed digital twin consists of two components namely model component and simulation component. The model component forms a Markov chain that encapsulates the dynamics underlying the phenomenon by using some discrete states and their transition probabilities. The simulation component recreates the phenomenon using a Monte Carlo simulation process. The efficacy of the proposed digital twin construction methodology is shown by a case study, where the digital twin of the surface roughness of a surface created by successive grinding operations is described. The developers of the cyber-physical systems will be benefitted from the outcomes of this study because these systems need the computable virtual abstractions of the manufacturing phenomena to address the issues related to the maturity index of futuristic manufacturing systems (i.e., understand, predict, decide, and adopt).

Based upon the Shliomis ferromagnetic fluid model and the Stokes microcontinuum theory incorporating with the Christensen stochastic model, a modified Reynolds equation of centrosymmetric squeeze films has been derived in this paper. The Reynolds equation includes the combined effects of non-Newtonian rheology, magnetic fluids with applied magnetic fields, rotational inertia forces, and surface roughness. To guide the use of the derived equation, the squeeze film of rotational rough-surface circular disks lubricated with non-Newtonian magnetic fluids is illustrated. According to the results obtained, the effects of rotation inertia decrease the load capacity and the squeeze film time of smooth circular disks. By the use of non-Newtonian magnetic fluids with applied magnetic fields, the rotational circular disks predict better squeeze film performances. When the influences of circumferential roughness patterns are considered, the non-Newtonian magnetic-fluid lubricated rotational rough disks with applied magnetic fields provide further higher values of the load capacity and the squeeze film time as compared to those of the smooth case.

The high-cycle fatigue (HCF) behavior is significantly affected by surface roughness, especially for high strength metal FV520B-I. However, with surface roughness effect, neither the fatigue property, nor the high-cycle fatigue life model about FV520B-I with surface roughness has been reported. In this paper, designed fatigue experiment using the specimen with different surface roughness is presented to study the effectiveness of the roughness to the fatigue. The observations of the fatigue crack initiation sites and the crack propagation. Then the high cycle fatigue behavior of FV520B-I affected by surface roughness is analyzed. The existing very-high-cycle fatigue life model is not well-fit for high-cycle fatigue model of FV520B-I. A NEW high-cycle fatigue life prediction model of FV520B-I, taking surface roughness as a main effective variable is proposed. The model is built up by a comprehensive use of experimental data and the traditional fatigue modeling theory. The new finding between the fatigue strength coefficient and stress amplitude, with surface roughness, is adopted, leading to a NEW modified life prediction model. Study on fatigue model of FV520B-I with surface roughness is a very beneficial effort in fatigue theory and fatigue engineering development.

The machining of shape memory alloys (SMAs) is fairly essential and integral part in the manufacture of components for utilizing in engineering applications. An effort has been made in the present work to study the effect of wire electro discharge machining process parameters such as pulse on time (Ton), pulse off time (Toff) and servo voltage (SV) have been analyzed on material removal rate and surface roughness. The investigation clearly reveals that an increased pulse on time with decrease in pulse off time as well as SV increases the amount of material removed in machining of SMAs. On the other hand, the surface roughness increases with increased pulse on time and decreases with increased pulse off time as well as SV. The surface topography of the machined surface was analyzed using scanning electron microscope (SEM) and confocal micrographs. Phase changes on the machined surface with respect to pulse on time and SV were evaluated from X-ray diffractometer (XRD) analysis.

The impact of lubricants on pole-tip recession and surface morphology of hard disk drive heads in the precision lapping process was investigated with atomic force microscopy, scanning electron microscopy, and auger electron spectroscopy. In particular, the effects of deionized water, hydrocarbon oil, ethanediol, isopropanol, and ethanol lubricants were evaluated. The results reveal that proper selection of lubricant is critical for achieving optimal performance in the lapping process. A mixture of 68% hydrocarbon oil, 30% isopropanol, and 2% octadecenoic acid was found to yield the most favorable results, displaying a writer shield recession, first shield of reader recession, and surface roughness of 0.423, 0.581, and 0.242 nm, respectively.

Micro milling operation is a fabrication process to create 3D parts from tens of micrometers to a few millimeters in size using a tool with diameter less than 1mm. Micro groove is one of the common features observed in the micro parts. The surface roughness of micro grooves plays an important role in their performance. Since most of the finishing processes could not be easily performed on the micro grooves, it is of extreme importance to find a relationship between micro milling parameters and the surface roughness profile. In this paper, in order to anticipate the profile and surface roughness of the groove floor a model is proposed based on the kinematic of cutting process and tool geometry. The effects of minimum chip thickness, elastic recovery, size effect and tool deflection are included in the model. Relationship between position of points on the floor surface of groove and kinematics of cutting process are derived. In next step, simulations of proposed model are performed in the ACIS environment. Finally, using the DOE method surface roughness is investigated stochastically. The simulated and measured surface roughnesses are compared together that confirm the validity of proposed model.

In the conventional X-ray reflectivity (XRR) analysis, the reflectivity is calculated based on the Parratt formalism, incorporating the effect of the interface roughness according to Nevot and Croce. However, the results of calculations of the XRR have shown strange outcomes, where interference effects increase at a rough surface because of a lack of consideration of diffuse scattering within the Parratt formalism. Therefore, we have developed a new improved formalism in which the effects of the surface and interface roughness are included correctly. In this study, for deriving a more accurate formalism of XRR, we tried to compare the measurements of surface roughness of the same sample by atomic force microscopy (AFM) and XRR. It is found that the AFM result could not be completely reproduced even with the improved XRR formalism. By careful study of the AFM results, we determined the need for an additional effective roughness term within the XRR simulation that depends on the angle of incidence of the beam.

In the present work, a recently developed in-house 2D CFD code is used to study the effect of gas turbine stator blade roughness on various performance parameters of a two-dimensional blade cascade. The 2D CFD model is based on a high resolution flux difference splitting scheme of Roe (1981). The Reynolds Averaged Navier-Stokes (RANS) equations are closed using the zero-equation turbulence model of Baldwin-Lomax (1978) and two-equation Shear Stress Transport (SST) turbulence model. For the smooth blade, results are compared with experimental data to validate the model. Finally, a correlation between roughness Reynolds number and loss coefficient for both turbulence models is presented and tested for three other roughness heights. The results of 2D turbine blade cascades can be used for one-dimensional models such as mean line analysis or quasi-three-dimensional models e.g. streamline curvature method.

X-ray reflectometry is a powerful tool for investigating rough surface and interface structures. Presently, X-ray reflectivity is based on Parratt formalism, accounting for the effect of roughness by the theory of Nevot–Croce. However, the calculated results showed a strange phenomenon in that the amplitude of the oscillation because of interference effects increases in the case of a specific roughness of the surface. We propose that the strange results originated from the currently used equation because of a serious error in which the Fresnel transmission coefficient in the reflectivity equation is increased at a rough interface, and the increase in the transmission coefficient completely overpowers any decrease in the value of the reflection coefficient because of lack of consideration in diffuse scattering. In the present study, we present a new improved formalism that corrects this error, and thereby derives an accurate analysis of X-ray reflectivity from a multilayer surface, taking into account the effect of roughness-induced diffuse scattering.