Surface Roughness Research Articles

In-Vitro Comparison of Titanium Disc Surface Roughness and Bacterial Colonization after Ultrasonic Instrumentation with Three Different Tips.

During implant maintenance, preserving a smooth surface on the machined trans-mucosa abutment is critical to reduce biofilm attachment and colonization. The present study compare the surface roughness and bacterial colonization of machined titanium surfaces after instrumentation with various materials. Forty-four machined Grade 23 titanium discs were instrumented with a round Polyether Ether Ketone (PEEK) tip, a plastic curette tip, or a pure titanium curette tip with piezoelectric devices. Before and after instrumentation, the surface roughness (Ra and Rz) values were analyzed with a profilometer and scanning electron microscopy (SEM). Streptococcus sanguinis was cultured and incubated for 24 hours on the instrumented discs, and colony-forming units (CFU)/mL were obtained for each group. Samples instrumented with the metal ultrasonic tip significantly increased surface roughness compared to the other groups. Thisresulted in greater colonization by S. sanguinis than surfaces instrumented with PEEK tips or the negative control. Samples instrumented with PEEK and plastic tips did not exhibit any statistically significant increase in surface roughness. SEM analysis revealed a significantly rougher surface of discs instrumented with metal compared to discs instrumented with plastic or PEEK tip, despite the possibility of debris from tip dissolution. Our results suggested that instrumentation with metal ultrasonic tips with piezoelectric devices significantly increase machined titanium's surface roughness and elicited higher biofilm formation in vitro. Meanwhile, instrumentation of machined titanium with PEEK or plastic ultrasonic tips did not affect the surface roughness or bacterial adhesion.

Parametric Analysis and Optimization on Fiber Laser Micro-Milling on AZ31 Magnesium Alloy

One of the proficient machining technologies to create micro-features in a variety of materials is the laser micro-milling process. This procedure involves irradiating a highly concentrated laser beam on the sample and performing laser cutting at various cutting patterns to change the surface conditions and enhance the characteristics of that surface tribology. In this work, an effort has been made to mill magnesium alloy (AZ31) material using a laser. The pulse frequency, laser beam power, cutting speed, number of passes, and transverse feed are among the different process variables taken into account for the current research effort. Measured results include depth of cut and surface roughness. To ensure the validity of the established empirical models, this paper also presents experimental data. Several surface plots have been used to examine the test data. To get the lowest values of surface roughness and depth of cut, multiperformance optimization is also utilized. The influence of process factors on response has also been examined using optical microscopic images. Gray relational analysis approach is also applied to obtain the multiobjective optimization parametric combination and based on the calculated results of gray relational grade, it is revealed that improvement in the value of gray relational grade at predictive setting is 0.054 compared to the initial parametric combination.

Microstructure, electrochemical corrosion and corrosion mechanism of electroplated Ni–W alloy coating by DFT calculation

ABSTRACT A Ni–W alloy coating with a thickness of 5 μm was electroplated on N80 steel, and its electrochemical performance in a 3.5% NaCl solution was investigated. The atomic models of passive films and corrosion mechanism were analysed with the density functional theory calculation. The results show that the electroplated Ni–W alloy coating is composed of W atoms in the Ni lattice, and its surface roughness and particle size are 66.1 and 640.4 nm, respectively. The corrosion current density of Ni–W coating is lower than that of the substrate, indicating better corrosion resistance, while the corrosion potential is opposite, which is more passive than the substrate. The total impedance of Ni–W coating is higher than that of the substrate, which is attributed to the formation of NiO passive film during the corrosion process.

Optimization of machining parameters for turning operation of heat-treated Ti-6Al-3Mo-2Nb-2Sn-2Zr-1.5Cr alloy by Taguchi method

TC21 alloy is a high-strength titanium alloy that has been gaining attention in various industries for its excellent combination of strength, toughness, and corrosion resistance. Given that this alloy is hard to cut material, therefore this study aims to optimize the process parameters of Turing this alloy under different conditions (i.e. as-received alloy, and heat-treated alloy). The L9 Taguchi approach-base orthogonal array is used to determine the optimum cutting parameters and the least number of experimental trials required. The achievement of this target, three different cutting parameters are used in the experimental work; each cutting parameter has three levels. The cutting speeds are chosen as 120, 100, and 80 m/min. The feed rates’ values are 0.15, 0.1, and 0.05, mm/rev, and the depth of cut values are 0.6, 0.4, and 0.2 mm. After applying three steps of heat treatment (First step: is heating the sample to 920 °C for 1 h then decreasing to 820 °C also for 1 h, second step: cooling the sample to room temperature by water quenching (WQ), the third step: holding the sample at 600 °C for 4 h (Aging process)). The results revealed that the triple heat treatment led to the change in the microstructure from (α + β) to (α + β) with secondary α platelets (αs) formed in residual β matrix leading to a decreased surface roughness by 56.25% and tool wear by 24.18%. The two most critical factors that affect the tool insert wear and surface roughness are the death of cut and cutting speed, which contribute 46.6% and 46.7% of the total, respectively. Feed rate, on the other hand, has the least importance, contributing 20.2% and 31.9% respectively.

Polyimide impregnated silver nanowire-titanium oxide core–shell nanostructures as ultra-stable flexible transparent electrode for multiple applications

Silver nanowires (AgNWs)-based flexible-transparent conducting electrode (f-TCE) have various optoelectronic applications. Although, bare AgNW-based f-TCE faces challenges of poor adhesion with the substrate, rough surface and low thermal stability. In this work, we demonstrate preparation of f-TCE by coating a very thin layer of TiO2 over AgNWs to form AgNW-TiO2 core–shell structures. Due to very thin TiO2 film in core–shell structure, the amorphous TiO2 converted into crystalline and delivered excellent conductivity at low curing temperature of 100 °C. The adhesion and roughness issues are solved by impregnating the core–shell AgNW-TiO2 within polyimide (PI) matrix. The PI impregnated AgNW-TiO2 core–shell structure as f-TCE delivered excellent stability after 5000 times of bending and number of peeling off cycles. The as prepared f-TCE delivered sheet resistance (Rs) of 8.61 Ω/sq with transmittance of 85 % at 550 nm and Rs of 4.2 Ω/sq with transmittance of 81 % when cured at 250 °C. The surface temperature of f-TCE was found to increase up to 90 °C in 40 s after applying 4 V of supply indicating its potential as transparent heater. In addition to that the CIGS solar cell fabricated by utilization of our f-TCE exhibited efficiency of 9.6 %, demonstrating its applicability for photovoltaic applications.

Mechanical responses and fracturing behaviors of coal under complex normal and shear stresses, Part I: Experimental results

This work presents experimental tests based on coal collected from a coal mine based underground water reservoir (CMUWR). The mechanical responses of dry and water-soaked coal samples under the complex normal and shear stresses under multi-amplitude and variable frequency is investigated. The experimental results reveal the effects of stress path, water soaking and frequency on deformation, energy dissipation, secant modulus and shear failure surface roughness. The experimental results show that when normal and shear stresses are applied simultaneously, there is a significant competitive relationship between them. On the dominant side, the strain rate will be significantly increased. The sample under a loading frequency of 0.2 Hz exhibits a longer fatigue life. During the cyclic shear test, the shear strain of the water-soaked sample is higher than that of the dry samples. The average roughness coefficient of failure surface exhibits an increasing pattern with increase in shear strength, the elevated roughness of a shear surface is advantageous in constraining shear displacements of specimens, thereby lowering the energy dissipation. This study can provide theoretical and practical implications for a long-term safety evaluation of CMUWR.

Roughness affects the response of human fibroblasts and macrophages to sandblasted abutments

BackgroundA strong seal of soft-tissue around dental implants is essential to block pathogens from entering the peri-implant interface and prevent infections. Therefore, the integration of soft-tissue poses a challenge in implant-prosthetic procedures, prompting a focus on the interface between peri-implant soft-tissues and the transmucosal component. The aim of this study was to analyse the effects of sandblasted roughness levels on in vitro soft-tissue healing around dental implant abutments. In parallel, proteomic techniques were applied to study the interaction of these surfaces with human serum proteins to evaluate their potential to promote soft-tissue regeneration.ResultsGrade-5 machined titanium discs (MC) underwent sandblasting with alumina particles of two sizes (4 and 8 μm), resulting in two different surface types: MC04 and MC08. Surface morphology and roughness were characterised employing scanning electron microscopy and optical profilometry. Cell adhesion and collagen synthesis, as well as immune responses, were assessed using human gingival fibroblasts (hGF) and macrophages (THP-1), respectively. The profiles of protein adsorption to the surfaces were characterised using proteomics; samples were incubated with human serum, and the adsorbed proteins analysed employing nLC–MS/MS. hGFs exposed to MC04 showed decreased cell area compared to MC, while no differences were found for MC08. hGF collagen synthesis increased after 7 days for MC08. THP-1 macrophages cultured on MC04 and MC08 showed a reduced TNF-α and increased IL-4 secretion. Thus, the sandblasted topography led a reduction in the immune/inflammatory response. One hundred seventy-six distinct proteins adsorbed on the surfaces were identified. Differentially adsorbed proteins were associated with immune response, blood coagulation, angiogenesis, fibrinolysis and tissue regeneration.ConclusionsIncreased roughness through MC08 treatment resulted in increased collagen synthesis in hGF and resulted in a reduction in the surface immune response in human macrophages. These results correlate with the changes in protein adsorption on the surfaces observed through proteomics.

Machine learning method for roughness prediction

This work aims to employ machine-learning models, specifically neural networks, to predict the time evolution of the global surface roughness in a lattice model that represents a film growing on a d-dimensional substrate. We analyze the well-known ballistic deposition (BD) model for d=1, 2 since it presents strong corrections to the scaling, making it difficult to observe directly, via effective scaling exponents, its correspondence with the Kardar-Parisi-Zhang (KPZ) universality class. As an alternative to overcome this difficulty, we first intend to learn the time evolution of the global roughness for substrate sizes that are computationally viable to simulate. To test the learning, we apply two different methodologies for d = 1: the first one learns the Family-Vicsek scaling relation, and by doing the reverse transformation, we get the global roughness as a function of the time, and the second one learns the kinetic roughening directly from the time series data. For growth in d = 2 where applications arise and no exact KPZ scaling exponents are known, we apply the second methodology. However, we employ a more resilient learning model tailored for time series problems. Hence, the time required to generate the same amount of data, showing the evolution of global roughness, is reduced dramatically. Importantly, machine learning techniques capture the scaling corrections of the BD model, predicting an effective global roughness exponent, α, calculated from the learned data extracted from very large lateral sizes and times that cannot be simulated using lattice models. Our prediction is consistent with accurate estimates of the KPZ roughness exponent reported in the literature for d = 2.

Influence of discrete laser surface melting on scuffing resistance of W6Mo5Cr4V2 steel gear

The gear transmission system is advancing towards high-speed and heavy-duty applications. Among the main failure modes of the system, tooth surface scuffing due to increased tooth surface temperature has emerged as a prominent concern in mechanical transmission. Addressing the enhancement of gear scuffing resistance has thus become an urgent challenge in this field. This paper utilized discrete laser surface melting (DLSM) treatment to create discrete laser surface melted (DLSMed) units on the surface of W6Mo5Cr4V2 steel gears, resembling the radial ribs found on the surface of Limaria basilica. The paper investigated the size, hardness, residual austenite content, and residual stress of the DLSMed units at varying current intensities and laser frequencies. Microstructural observations were conducted on the DLSMed units, followed by gear scuffing experiments performed on the Forschungsstelle für Zahnräder und Getriebebau (FZG) testing machine. The experimental findings revealed that the change in laser frequency had a clearly weaker impact on the size of the DLSMed unit compared to current intensity. The DLSMed unit consisted of two parts: the melting zone (MZ) and the heat-affected zone (HAZ), with equiaxed and dendritic microstructures, respectively. Both zones exhibited refinement with increasing current intensity and laser frequency. Moreover, the microhardness of the DLSMed unit showed significant improvement compared to that of as-received gears. The scuffing resistance of DLSMed gears was found to be closely linked to their initial surface roughness. Residual stress formation in DLSMed gears was attributed to thermal stress and microstructural stress. The distribution pattern of DLSMed units had varying effects on the scuffing load-carrying capacity of DLSMed gears. Specifically, DLSMed gears with transverse distribution of DLSMed units demonstrated a 12.5% improvement in anti-scuffing performance compared to those with longitudinal distribution. Finally, this paper elucidated the mechanism through which DLSM enhances the scuffing resistance of W6Mo5Cr4V2 steel gears.

Effect of R410a coolant on tool wear, dimensional deviation and surface roughness in turning of AISI 1045 steel

Abstract Friction between the tool and the workpiece during machining operations always increases the tool wear rate. Removing this problem by using fluids and cooling the tools is essential. In this research, the effects of two cooling conditions: Water Soluble Cutting Oil (WSCO) fluid and R410a coolant, on the tool wear rate, dimensional deviation and surface roughness of AISI 1045 steel (CK45) in turning with a high-speed steel (HSS) tool were investigated. The selected parameters were cutting speeds of 15, 25, 40 and 55 m/min, cutting depths of 0.5, 1 and 1.5 mm and feed rates of 0.05, 0.12 and 0.2 mm/rev. The results show that cooling by R410a coolant reduces the tool wear rate due to its high cooling power and better temperature control at the cutting zone compared to WSCO fluid. Based on the minimums of tool wear, dimensional deviation and surface roughness in different conditions, using R410a coolant can increase the cutting speed by 60% from 25 to 40 m/min. Also, in the optimal condition at a cutting speed of 40 m/min, cutting depth of 1 mm and feed rate of 0.05 mm/rev., tool wear, dimensional deviation and surface roughness are reduced by up to 20, 6 and 10 times respectively. In the optimal condition, the dimensional deviation based on the diameter difference along 300 mm is reduced to 14 µm and also the tool wear rate and surface roughness after 60 min. of turning are reduced to 20 and 3.1 µm respectively. The effect of each input variable on tool wear, dimensional deviation and surface roughness was calculated by statistical analysis and was validated by ANOVA.

A COMPARATIVE MODELING AND OPTIMIZATION OF SURFACE ROUGHNESS IN THE END MILLING OF Al 3003 SUBJECTED TO NON-EQUAL CHANNEL ANGULAR PRESSING (NECAP)

This paper highlights the surface roughness optimization of a specific material, Al 3003, which has been subjected to the non-equal channel angular pressing (NECAP) process. Considering spindle speed, feed rate, and depth of cut as input variables and surface roughness as an output variable, experiments have been conducted based on the L27 orthogonal array of the Taguchi method. Four prediction models, namely exponential and response surface methodology (RSM) as mathematical models, and artificial neural networks (ANNs) prediction models with different training algorithms (Bayesian Regularization (BR) and Levenberg–Marquardt (LM)), are proposed. Applying effectiveness and performance criteria, the prediction accuracy of the exponential model (90.35%), RSM (93.07%), BR (97.83%), and LM (97.54%) shows that all proposed prediction models are efficient enough. The ANN model trained with BR is found to be the best fit for predicting surface roughness. In order to optimize surface roughness, a newly introduced optimization method called the Intelligible-in-time Logics Algorithm (ILA) is employed. High spindle speed (1000[Formula: see text]rev/min), low feed rate (100[Formula: see text]mm/min) and depth of cut (0.5[Formula: see text]mm) have been the optimum cutting parameter combinations to obtain minimum surface roughness (0.4956[Formula: see text][Formula: see text]m). The results have been verified by confirmation tests and Particle Swarm Optimization (PSO) method. ILA and PSO predict the same optimum parameter combinations and minimum surface roughness, while ILA performs optimization in less time (114.4[Formula: see text]s), about 3.5 times faster than PSO. The paper’s findings strongly advocate the application of ILA in machining data optimization.

An experimental investigation of process parameters on material removal and surface roughness improvement in abrasive flow machining

Abstract Today, there is huge demand for mechanical components with long life cycles, and superior surface finishes as a result of the industrial revolution. New methods for nano-finishing complex structures, including abrasive flow machining (AFM), have been developed in response to the need for superior surface finish. This is a relatively new technique in non-conventional machining techniques. Because abrasion only happens in locations where flow is restricted, this approach is utilized to polish metallic parts as well as interior, inaccessible cavities, and recesses using a semi-liquid paste. It has evolved to flow of abrasives with a viscoelastic polymer (referred to as abrasive media) over complex geometries, and edges to deburr, and radius those surfaces. This paper focuses on investigating the impact of process parameters on material removal, and percentage improvement in surface roughness on cylindrical brass workpieces using Taguchi L9 orthogonal array, the number of cycles, extrusion pressure, and grit size of abrasives have been selected. The abrasive medium employed in this investigation is composed of a blend of polymer, hydrocarbon gel, and aluminium oxide abrasive particles with varying grit sizes. The outcome shows which process parameters to optimize for material removal, and improvement in percentage improvement in surface roughness. The number of cycles that have the largest percentage contribution to material removal was 83.74%. For the response material removal, the percentage contributions of the abrasive particle grit size, and extrusion pressure are 2.03%, and 14.16%, respectively. N2P2G3 has the optimal level used for material removal. The largest percentage contribution to improvement in surface roughness, or 83.48%, was the result of the number of cycles. Extrusion pressure, and abrasive particle grit size account for 7.38%, and 8.88% of the total percentage contribution, respectively. N3P2G3 has the optimal level obtained for percentage improvement in surface roughness improvement.

Extreme roughness reduction and ultrafine quality of innovative dual function material extrusion 3D printer

Purpose This paper aims to use hybrid manufacturing (HM) to overcome several drawbacks of material extrusion three-dimensional (3D) printers, such as low dimension ranging from 0.2 to 0.5 µm, resulting in a noticeable staircase effect and elevated surface roughness. Design/methodology/approach Subtractive manufacturing (SM) through computer numerical control milling is renowned for its precision and superior surface finish. This study integrates additive manufacturing (AM) and SM into a single material extrusion 3D printer platform, creating a HM system. Two sets of specimens, one exclusively printed and the other subjected to both printing and milling, were assessed for dimension accuracy and surface roughness. Findings The outcomes were promising, with postmilling accuracy reaching 99.94%. Significant reductions in surface roughness were observed at 90° (93.4% decrease from 15.598 to 1.030 µm), 45° (89% decrease from 26.727 to 2.946 µm) and the face plane (71% decrease from 12.176 to 3.535 µm). Practical implications The 3D printer was custom-built based on material extrusion and modified with an additional milling tool on the same gantry. An economic evaluation based on cost-manufacturing demonstrated that constructing this dual-function 3D printer costs less than US$560 in materials, offering valuable insights for researchers looking to replicate a similar machine. Originality/value The modified general 3D printer platform offered an easy way to postprocessing without removing the workpiece from the bed. This mechanism can reduce the downtime of changing the machine. The proven increased dimension accuracy and reduced surface roughness value increase the value of 3D-printed specimens.

CHARACTERIZATION OF SURFACE, SUBSURFACE DAMAGE AND THEIR EFFECT ON FATIGUE LIFE AFTER MACHINING OF AEROSPACE-GRADE ALUMINUM ALLOY (Al 6082-T6)

Aluminum alloys are widely used in the automotive and aerospace industries due to their lower mass-to-strength ratio than other metallic alloys. Apart from their inherent properties, aluminum alloys like other metallic alloys show a significant change in their mechanical properties according to the machining parameters. The research literature on obtaining optimum mechanical properties of aluminum alloys that undergo machining is very limited. Moreover, the combined effect of several parameters on the machinability of aluminum alloys has not yet been explored. In this paper, the effect of three machining parameters (Depth of Cut (DoC)), feed rate (FR), and cutting speed (CS) on the subsurface damage and fatigue life of aerospace-grade aluminum alloy (Al-6082-T6) is observed. Samples are prepared using a full fractional approach to effectively capture the effect of all input parameters. Thereafter, samples were subjected to surface roughness, micro-hardness, and fatigue life tests. Results of surface roughness and micro-hardness tests are compared with fatigue life. The general linear model was employed to capture the percentage effect of each input parameter on the output parameters. The results showed that DoC was the main contributing factor that caused subsurface damage, while surface roughness and fatigue life were mainly affected by FR and CS. Optical microscope images showed a white layer formation that had higher hardness than the base metal. Overall, this research work proposes the input parameters that can be used to achieve minimum surface damage and fatigue life.

An energy concisions analytical modelling approach with experimental verification for cutting performance assessment in EDM of Ti-based superalloy

Abstract Electric discharge machining (EDM) is a stochastic process which is commonly engaged for cutting of Ti-based difficult-to-cut alloys. Experimental investigation in EDM is costly and requires significant amount of time due to the complex nature of the process. Moreover, the energy intensive nature is another criticism associated to this technique. Therefore, this research is focused on developing an energy conscious mathematical model of the process while considering the categorical parameters like type of dielectric, electrode and nano-powder along with pulse time ratio. Taguchi design of experiment (DOE) has been executed for the experimentation. The comprehensive analysis of the findings depicts transformer oil (TO) delivers a remarkable improvement in MRR and SEC in comparison to other dielectric choices. Furthermore, brass electrode stands out for achieving the best surface finish. When it comes to micro-additives, SiC exhibits substantial potential in increasing MRR, and graphite gives a better surface finish. The process has also been effectively modeled which helps to predict material removal rate (MRR), surface roughness (SR) and specific energy consumption with decent precision which is the key contribution of this study. 3D simulation for EDM illustrates that the features of the crater are defined by the liquefied region, whilst the dynamics of the mushy zone play a crucial role in controlling and characterizing the microstructure size progression. The confirmatory experimental results revealed that the use of optimized parametric combinations demonstrate 90.87% improvement in MRR, 52.07% reduction in SR and 96.19% decrease in SEC in contest to the responses’ values obtained at non-optimal settings.

In-vitro wear of Titanium reinforced Hydroxyapatite coatings in simulated body fluid

Abstract Titanium-reinforced hydroxyapatite (Ti-HAP) composite coating has been deposited over 254 SMO stainless steel using a Low-Velocity Oxygen Fuel (LVOF) spraying technique. FESEM, XRD, Vickers Microhardness and shear strength tests have been performed to characterize the developed coatings. Further, in-vitro wear behaviors of the coatings were investigated using a pin-on-disc wear tester under simulated body fluid conditions. The results reveal that Ti40-HAP coating possesses superior wear resistance compared to Ti60-HAP, Ti, and HAP coatings, attributed to higher surface hardness and higher shear strength values. Amongst the tested samples, the friction coefficient was lower for Ti coating, followed by Ti60-HAP composite coating. The surface roughness was a prominent factor in reducing the friction coefficient of coating samples. Local detachment and brittle fracture were the dominant wear modes in Ti-HAP coating, whereas an additional micro-ploughing wear mode was observed in pure hydroxyapatite and titanium coating.

Study on electrochemical polishing mechanism of TC4 titanium alloy

Abstract To achieve a high-quality and precise surface on TC4 titanium alloy for demanding engineering applications, electrochemical polishing (ECP) technology was employed to investigate the polishing process of TC4 titanium alloy in an ethylene glycol-sodium chloride green electrolyte. The macro and micro morphology, surface roughness, material removal rate, surface elements, surface corrosion resistance, and surface hardness of TC4 titanium alloy were measured before and after polishing. Single-factor experiments were conducted to explore the effects of processing gap, electrolyte temperature, polishing voltage, and polishing time on TC4 titanium alloy surface quality. Optimal polishing parameters were determined to be an electrode gap of 12 mm, a voltage of 20 V, a temperature of 40 °C, and a polishing time of 10 minutes. The experimental results indicated that after electrochemical polishing, the workpiece surface roughness Ra decreased from 256 nm to 25 nm, achieving a roughness reduction rate of 90.23%, the material removal rate was 3.348 μm/min. The self-corrosion potential of the polished surface increased from -0.416 V to -0.375 V and the self-corrosion current density decreased from 4.447×10-7 A·cm-2 to 1.873×10-7 A·cm-2, the surface indentation hardness of the workpiece decreased from 5.8669 GPa to 4.6726 GPa. Based on the characterization of polished surface, the mechanism of electrochemical polishing of TC4 titanium alloy was proposed. The results demonstrate that electrochemical polishing of TC4 titanium alloy is highly efficient, involves no mechanical action, and causes no subsurface damage, making it a promising technology to meet medical requirements.

Long-Term Estimation of Depositions on Heating Surface During Boiling of Long-Life Coolant

Abstract Long-term boiling experiments with long-life coolant have been made with the aim to apply a boiling cooling technology to the next generation high exothermic electronic devices. The long-life coolant commonly used for cooling electronic devices is a mixture of ethylene glycol and water with multiple antirust inhibitors as additives, which may result in some depositions on the heat transfer surface during the boiling. In this study, the heat transfer surface made of copper was set vertically, and long-term experiments have been performed under the pool boiling. The deposition process was monitored for constant heating conditions. From experimental results, a distinct surface temperature change was observed under constant heat flux conditions. Just after keeping constant heat flux, the surface temperature increases with time, a certain time later decreases, and finally takes a stable value. During the temperature rise, the deposition adheres to the heat transfer surface in dots, which may cause an increase in thermal resistance between the wall surface and the working fluid. However, during the temperature drop, large growth of dot-like depositions on the heat transfer surface could alter wettability and surface roughness, enhancing boiling heat transfer. In addition, to investigate the characteristics of the depositions adhered to the heat transfer surface, a component analysis has been performed, which shows that the main substance was strontium hydroxyapatite, which might be formed by chemical reaction between components in the additives under the boiling.

Evaluation of tool wear and surface roughness in high-speed dry turning of Incoloy 800

Evaluation of tool wear and surface roughness in high-speed dry turning of Incoloy 800

Surface properties of the seas of Titan as revealed by Cassini mission bistatic radar experiments

Saturn’s moon Titan was explored by the Cassini spacecraft from 2004 to 2017. While Cassini revealed a lot about this Earth-like world, its radar observations could only provide limited information about Titan’s liquid hydrocarbons seas Kraken, Ligeia and Punga Mare. Here, we show the results of the analysis of the Cassini mission bistatic radar experiments data of Titan’s polar seas. The dual-polarized nature of bistatic radar observations allow independent estimates of effective relative dielectric constant and small-scale roughness of sea surface, which were not possible via monostatic radar data. We find statistically significant variations in effective dielectric constant (i.e., liquid composition), consistent with a latitudinal dependence in the methane-ethane mixing-ratio. The results on estuaries suggest lower values than the open seas, compatible with methane-rich rivers entering seas with higher ethane content. We estimate small-scale roughness of a few millimeters from the almost purely coherent scattering from the sea surface, hinting at the presence of capillary waves. This roughness is concentrated near estuaries and inter-basin straits, perhaps indicating active tidal currents.